The Organic Signatures of Life on Mars

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THE ORGANIC SIGNATURES OF LIFE ON MARS

A thesis submitted for the degree of Doctor of Philosophy and the Diploma of Imperial College

Renato Brito Moreira dos Santos

Department of Earth Science and Engineering

Imperial College London

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2 Declaration of Originality

I declare that this thesis, The Organic Signatures of Life on Mars, is the result of my own work carried out during my doctoral studies. Work from others is fully cited and appropriately referenced.

Renato Brito Moreira dos Santos

The copyright of this thesis rests with the author and is made available under a Creative Commons Attribution Non-Commercial No Derivatives licence. Researchers are free to copy, distribute or transmit the thesis on the condition that they attribute it, that they do not use it for commercial purposes and that they do not alter, transform or build upon it. For any reuse or redistribution, researchers must make clear to others the licence terms of this work.

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4 Abstract

The search for extraterrestrial life is one of the ultimate challenges for science. Mars was the only planet ever to be targeted for a life searching mission (NASA’s Viking) and still remains the main focus regarding the search of extraterrestrial life.

This thesis aims to find out what are the best locations on Mars to search for biosignatures of life (amino acids) and contribute to the preparation of future space missions to the Red Planet. In this thesis, two Mars soil analogues were studied: Rio Tinto in Spain and the hypersaline lakes of the Yilgarn Craton in Western Australia. Investigation of their mineralogical, microbiological and biosignature content provided hints of what future life searching missions may find in similar environments on Mars. A third set of samples, comprised of mineral standards that are relevant in the martian surface, was also used to study the influence of mineralogy in the preservation of biosignatures under simulated Mars conditions.

Overall, results show that both Mars soil analogues contained minerals that are commonly found on Mars, such as iron oxides, clays and evaporites. Generally, microbiology analyses show that life on Mars was/may be based on iron metabolism and/or halophilic. No obvious correlations were found between mineralogy, microbiology communities and biosignature content on both analogues. Detection of biosignatures was not straightforward even when life is known to be present in the sediments. Therefore, in situ detection of biosignatures on Mars may be a very difficult task and frequent sampling should be considered in future life searching missions. Results from Mars Chamber simulations suggest that locations containing sulfate minerals and smectite clays should be priority targets for the search of organic signature of martian life, due to their potential to preserve biosignatures and the fact that they usually indicate the presence of habitable environments.

5 Acknowledgements

These last four years of my life at Imperial College were, possibly, one of the most intense and challenging periods that I have ever passed through. However, these last four years were also very rewarding, mostly due to the amazing people that I met along the way.

First and foremost, I would like to thank the Department of Earth Science and Engineering of Imperial College London for the opportunity to do a PhD in such a vibrant and exciting environment and also for providing me a Janet Watson Scholarship!

On a more personal level, I would like to thank many collaborators spread around pretty much everywhere for their insightful comments and feedback provided throughout this thesis. I would like to thank Dr. Javier Cuadros and Dr. Manish Patel in particular for their absolute support, dedication, guidance and help during the Mars Chamber simulations project. Thanks to your input I managed to publish during my PhD and I feel very grateful to have had the chance to work closely with both of you!

I cannot thank enough Joost Aerts. Thank you, Joost, for guiding me and helping me during my stay in Amsterdam and all your help with the microbiology work during this project. In a similar way, I am very grateful for Dr Manuel Francisco Pereira’s help in the XRD analyses for the samples of Western Australia.

I would also like to thank Dr Pascale Ehrenfreund, Dr Susana Direito, Dr Andreas Elsaesser, late Dr.Wilfred Röling, Dr Huifang Xu and Dr Phil Bland for their contributions for this work, their insightful comments, corrections and suggestions.

I would like to express my absolute gratitude to my friends. You listened to me. You supported me. You were always there for me, even when I could not be there for you. Countless times you brought clarity into this adventure. Without your advice, friendship, kind words, stupid jokes and cheering I would not be able to make it to the finish line. Thank you (in no particular order… Don’t fight over this, please): Diogo Fonseca, Joana de Sousa, Raquel Raposo, Sara Marques, Magalie Barbosa, Carlos Encarnação, Felipe Matzke, Florian Matzke, Lachezar Kamenov, Carlos Castillo,

6 Adolfo Burgo, John Wallace, Giovanni Pelizzaro, Dr Akela Silverton, Dr Miriam Wright, Jack Ashley, Rafael Bastos, Rosana Mendes, Sérgio Esperancinha, Carolina Enes, Antje Lenhart, Dr Karwan Mustafa, Dr James Lewis, Dr Benoit Massart, Dr Jon Tennant, Dr Saba Manzoor, Deni Zenteno, Ado Farsi, Dr Peter Gordon, Luis Carvalho Silva, Pedro Assis de Oliveira, Sara Pereira, Joana Sequeira, Miguel Torres, Sandra Semblano, Hugo Alexandre, Nuno Canha, Antonio Pedro and Liliana Rodrigues. I feel blessed to have people like you in my life!

To my family (my sister and my mother in particular): thank you for encouraging me to pursue my dreams, even when that means getting trapped in saudade and staying far from you. I can’t wait to spend another great Portuguese summer with you all!

I wrote this thesis whilst working in a full-time job, therefore I would like to thank Kevin Davis and Otília Leão for supporting me and giving me the extra flexibility I needed to carry on with my writing.

At last, but certainly not the least, I feel so very much indebted to my supervisor, Dr Matthew Genge, for his support, reassurance and guidance. You were present during my field-trip to Australia, you went to the laboratory with me when I was not even under your supervision, and you were always fully supportive and helped me tremendously with the bits and pieces that I scientifically struggled with the most. Thank you for helping me bringing this whole endeavour to a good and happy conclusion! These same words are applicable to Professor Joanna Morgan and Professor Peter Allison, who I have to thank for listening to my frustrations, helping me addressing the big obstacles and support me in the final steps of this journey. Thank you very much, Matt, Jo and Peter!

To everyone included here: Muito Obrigado!

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8 Table of contents

ABSTRACT ...... 5 ACKNOWLEDGEMENTS ...... 6 TABLE OF CONTENTS ...... 9 LIST OF FIGURES ...... 14 LIST OF TABLES ...... 19 LIST OF ABBREVIATIONS ...... 21 LIST OF UNITS ...... 24 LIST OF MINERALS ...... 26

1 Introduction ...... 29

1.1 Definition of life ...... 30 1.2 The search for life in the Universe ...... 32 1.3 Life on Mars and history of Mars exploration ...... 37 1.3.1 Mars exploration after Viking mission ...... 42 1.4 Geological History of Mars ...... 47 1.5 Where to search for life? ...... 53 1.5.1 Shielding effect from subsurface environments ...... 54 1.5.1.1 UV Radiation ...... 55 1.5.1.2 GCR and SEP ...... 57 1.5.2 Mineral protection ...... 59 1.6 Signature of life ...... 62 1.7 Mars soil analogues ...... 65 1.8 project aim and dissertation outline ...... 69

2 Methods ...... 73

2.1 Introduction ...... 74 2.2 Samples and field work ...... 74 2.2.1 Rio Tinto ...... 75 2.2.1.1 Sample collection ...... 76 2.2.2 Hypersaline ephemeral lakes from the Yilgarn Craton (Western Australia) 80

9 2.2.2.1 Field trip observations ...... 81 2.2.2.2 Sample collection ...... 86 2.2.3 Mineral standards ...... 91 2.3 Methods ...... 93 2.3.1 Gas Chromatography – Mass spectrometry ...... 93 2.3.2 Derivatization of amino acids ...... 95 2.3.3 Amino acid calibration curves ...... 97 2.3.4 X-Ray Diffractometry (XRD) ...... 106 2.3.4.1 Diffraction of X-Rays and Bragg’s law ...... 106 2.3.4.2 X-Ray instrumentation ...... 107 2.3.5 Brunauer–Emmett–Teller method ...... 109 2.3.6 Scanning electron microscopy ...... 111 2.3.7 Polymerase Chain Reaction ...... 112 2.3.8 Denaturating Gradient Gel Electrophoresis ...... 114

3 Mineralogy, microbiology and amino acid analyses of Rio Tinto sediments ...... 117

Abstract ...... 118 3.1 Introduction ...... 119 3.2 Methods ...... 122 3.2.1 Samples ...... 122 3.2.2 X-Ray Diffraction (XRD) analyses ...... 122 3.2.3 Carbon, Nitrogen and Sulfur analyses (CNS) ...... 122 3.2.4 Microbial community profiling ...... 123 3.2.5 Amino acid analyses ...... 124 3.2.5.1 Chemicals and tools ...... 124 3.2.5.2 Extraction, derivatization and GC-MS analyses ...... 125 3.3 Results ...... 126 3.3.1 XRD analyses ...... 126 3.3.2 Carbon, Nitrogen and Sulfur (CNS) analyses ...... 128 3.3.3 Microbial community profiling ...... 129 3.3.4 Amino acid analyses ...... 131 3.4 Discussion ...... 135 3.4.1 Implications for the detection of biosignatures on Mars ...... 140

3.5 Conclusions ...... 145

4 Mineralogical composition of lacustrine Mars soil analogues: The acidic ephemeral lakes of Western Australia ...... 147

Abstract ...... 148 4.1 Introduction ...... 149 4.2 Methods ...... 151 4.2.1 Sample and sample collection conditions ...... 151 4.2.2 Field observations ...... 152 4.2.2.1 Lake Brown ...... 152 4.2.2.2 Lake Baladjie ...... 153 4.2.2.3 Lake Deborah West ...... 153 4.2.2.4 Lake Gilmore ...... 154 4.2.3 XRD analyses ...... 155 4.2.4 SEM analysis ...... 155 4.3 Results ...... 156 4.3.1 XRD results and spatial heterogeneity ...... 156 4.3.1.1 Lake Brown ...... 156 4.3.1.2 Lake Baladjie ...... 161 4.3.1.3 Lake Deborah West ...... 162 4.3.1.4 Lake Gilmore ...... 163 4.3.2 Variability of mineralogical composition between lakes ...... 164 4.3.3 SEM results ...... 167 4.4 Discussion ...... 170 4.4.1 Origin of mineral assemblages ...... 172 4.4.2 Ephemeral lakes as Mars analogues ...... 177 4.5 Conclusions ...... 182

5 Microbial communities and amino acid abundances of the acidic, hypersaline lakes of Western Australia ...... 185

Abstract ...... 186 5.1 Introduction ...... 188 5.2 Methods ...... 191

5.2.1 Samples ...... 191 5.2.2 Microbial community profiling ...... 192 5.2.2.1 DNA extraction ...... 192 5.2.2.2 16S rDNA amplicon sequencing and processing ...... 193 5.2.3 Amino acid analyses ...... 195 5.2.3.1 Chemicals and tools ...... 195 5.2.3.2 Extraction, derivatization and GC-MS analyses ...... 196 5.3 Results ...... 197 5.3.1 16S rDNA amplicon sequencing and processing (Illumina) ...... 197 5.3.1.1 Lake Gilmore ...... 201 5.3.1.2 Lake Brown ...... 202 5.3.1.3 Lake Baladjie ...... 202 5.3.1.4 Lake Deborah West ...... 203 5.3.2 Amino acid analyses ...... 204 5.3.3 Mineralogy and pH of the sediment samples ...... 206 5.4 Discussion ...... 207 5.4.1 Microbial communities in the sediment samples of the saline lakes of Western Australia ...... 207 5.4.2 Comparison with other hypersaline environments ...... 211 5.4.3 Amino acid abundance and relation to the mineralogy and microbiology content ...... 212 5.4.4 Implications for Mars ...... 215 5.5 Conclusions ...... 219

6 Influence of mineralogy on the preservation of amino acids under simulated Mars conditions ...... 221 Abstract ...... 222 6.1 Conclusions ...... 223 6.2 Materials and methods ...... 226 6.2.1 Minerals and XRD characterization ...... 226 6.2.2 Chemicals and tools ...... 228 6.2.3 Spiking of amino acids ...... 229 6.2.4 Mars Chamber simulations ...... 230

6.2.5 Extraction, derivatization and GC-MS analyses of amino acids ...... 233 6.2.6 Brunauer–Emmett–Teller (BET) analyses ...... 236 6.3 Results ...... 237 6.3.1 Degradation of amino acids under simulated Mars conditions ...... 237 6.3.2 BET analyses ...... 245 6.4 Discussion ...... 246 6.4.1 Effect of the amino acid structure ...... 246 6.4.2 Effects from the mineral features ...... 248 6.4.2.1 Role of iron ...... 248 6.4.2.2 Role of ferrous iron ...... 250 6.4.2.3 Surface area and pore size ...... 251 6.4.3 Concentration effect ...... 253 6.4.4 Implications for Mars exploration ...... 255 6.5 Conclusions ...... 258

7 Conclusions and future work ...... 261 7.1 Conclusions ...... 262 7.2 Future work ...... 270

References ...... 273

Annexes...... 309

List of figures

Figure 1.1: One of the first photographs of the martian surface, taken by Mariner 4 flyby mission, showing craters in the Memnonia Fossae region of Mars, 1965. (Image Credit: JPL/NASA).

Figure 1.2: Mariner 9 image of a Nirgal Vallis region showing the first evidences of ancient river channels on Mars, 1971. (Image credit: JPL/NASA).

Figure 1.3: Schematic representation of Mars geological history since its formation (4.5 billion years ago) up to the present day and main geological phenomena that occurred in each geological era. The Pre-Noachian and Noachian are joined together for image simplification. The top three images of Mars show how the planet gradually lost its liquid water on the surface and became the planet we know today. The three bottom photographs were taken by the High Resolution Stereo Camera onboard ESA's Mars Express. The left photograph is a representative Noachian surface with eroded impact craters (the bigger one being 25km wide) in Hellas Basin. The middle photograph shows outflow channels in Kasei Valles, a geological feature typically associated with Hesperian terrains. The bottom right image shows Reull Vallis, and illustrates a typical Amazonian landscape, with few impact craters. The valley is 7 km with a depth of around 300 m and is believed to be formed in a similar way to glacial valleys on Earth. (Figure based on Bibring et al. 2006. Top images credits: NASA Ames Research Center Image Library. Three bottom photographs credits: ESA/DLR/FU Berlin).

Figure 1.4: Schematic representation of the upper martian crust and immediate subsurface environments. The darker section (right underneath the surface) illustrates subsurface regions that are highly affected by multiple radiation forms, such as ultra-violet radiation (UV, purple arrow, affecting the surface), solar energetic particles (SEP, yellow arrow, affecting the surface and penetrating into the first centimeters of martian regolith) and galactic cosmic rays (GCR, red arrow, which can penetrate up to the meter scale into the regolith). The lighter section in this image represents putative subsurface environments, not highly affected by oxidizing radiation and generally assumed to contain preserved organic molecules (biosignatures). Image credit: ESA.

Figure 1.5: Schematic representation of two enantiomers of a generic -amino acid.

Figure 1.6: World map showing the locations of some environments that are analogous to Mars: 1- Rio Tinto, in Spain; 2- Salten Skov, Denmark; 3- Mojave Desert, CA, USA; 4- Mars Desert Research Station, Utah Desert, UT, USA; 5- Volcanic deposits of Hawaii; 6- Arequipa Desert; 7- Atacama Desert; 8- Hypersaline lakes of the Yilgarn Craton and 9- Dry valleys of Antarctica (Fernández-Remolar et al., 2005; Nornberg et al., 2004; Farr, 2004; Kotler et al., 2011; Perko et al., 2006; Marlow et al., 2008; Benison and Bowen, 2006; Aerts et al., 2014).

Figure 2.1: Map view of Annabel’s garden and Rio Tinto Area visited during the CAREX field trip. a) – Iberian Peninsula. b) – Huelva region and Rio Tinto mining park. c) – Annabel’s garden location where samples were collected within Rio Tinto mining park, near the town of Nerva, Embalse de Tumbanales and Rio Tinto river source.

Figure 2.2: Pictures of Rio Tinto samples collected at the river’s source near Annabel’s garden during the CAREX field trip, described in Table 1: a), sample RT1; b), sample RT2; c), sample RT3; d), sample RT4; e), sample RT5; f), sample RT6; g), sample RT7; h), sample RT8; i), sample RT9 and j), sample RT10. Photos taken by Susana Direito.

Figure 2.3: Map showing the approximate locations of the lakes visited during the fieldtrip to the Yilgarn Craton region. a) Map of Australia; b) Map of Western Australia and the Yilgarn Craton (1- Lake Brown, 2- Lake Baladjie, 3- Lake Deborah West, 4- Lake Victoria Rock, 5- Lake Lefroy, 6- Lake Cowan, 7- Lake Dundas and 8- Lake Gilmore).

Figure 2.4: Photographs of the eight saline lakes visited during the fieldtrip to the Yilgarn Craton in Western Australia in early August 2013. The photos show the general views of A) Lake Brown; B) Lake Baladjie; C) Lake Deborah West; D) Lake Victoria Rock; E) Lake Lefroy; F) Lake Cowan; G) Lake Dundas and H) Lake Gilmore. Photos taken by Renato dos Santos.

Figure 2.5: Photographs showing geological features present in the lakes visited during the field trip to the Yilgarn Craton. A) Generic view of the vegetated gypsum sands surrounding Lake Brown; B) Mudcracks in a desiccated section of Lake Victoria Rock; C) halite deposition and algae films often associated with highly texturized algal mats; D) linguoid ripples found in Lake Cowan; E) Formation of bubbles in the wet lacustrine mud surface due to algal activity and F) formation of Salt flats at Lake Baladjie. Photos taken by Renato dos Santos.

Figure 2.6: Map view of Australia, Western Australia, approximate boundaries of the Yilgarn Craton, location of the four acidic lakes and sampling sites. a) Australia; b) Western Australia and the Yilgarn Craton (1- Lake Brown, 2- Lake Baladjie, 3- Lake Deborah West. 4- Lake Gilmore); c) General satellite map of southern Lake Brown; d) View of the southeastern section of Lake Brown and sampling sites of LB samples; e) General satellite map of Lake Baladjie; f) View of southern lake shore of Lake Baladjie and sampling sites of LBa samples. Lake images obtained from Google Maps and Google Earth.

Figure 2.7: Map view of Australia, Western Australia, approximate boundaries of the Yilgarn Craton, location of the four acidic lakes and sampling sites. a) Australia; b) Western Australia and the Yilgarn Craton (1- Lake Brown, 2- Lake Baladjie, 3- Lake Deborah West. 4- Lake Gilmore); c) General satellite view of Lake Deborah West; d) View of the southern lake shore and sampling sites of LDW samples; e) General satellite map of Lake Gilmore; f) Detailed view of the northwestern section of Lake Gilmore and sampling sites of LG samples. Lake images obtained from Google Maps and Google Earth.

Figure 2.8: Schematic representation of a GC-MS and its main components.

Figure 2.9: Photograph of the GC-MS equipment used in this dissertation, with the identification of the gas chromatograph (GC), mass spectrometer (MS) and associated computer for chromatogram analysis (PC).

Figure 2.10: Derivatization of amino acids with isopropanol/acetyl chloride and trifluoroacetic anhydride.

Figure 2.11: Mass spectra for derivatized aspartic acid, and corresponding fragmentation pattern of the derivatized aspartic acid molecule.

Figure 2.12: Single ion GC-MS chromatograms (20 to 110 minutes) of the derivatized (N- TFA, O-isopropyl) amino acids (m/z 126, 140, 154, 168, 182, 184, 196, 198 and 210). 1) α- AIB; 2) D,L-Isovaline; 3) D-Alanine; 4) L-Alanine; 5) D- α-ABA; 6) D-Valine; 7) L- α-ABA; 8) L-Valine; 9) Glycine; 10) D-β-AIB; 11) D-Norvaline; 12) L-β-AIB ; 13) D-β-ABA; 14) β- Alanine; 15) L-β-ABA; 16) L-Norvaline; 17) D-Leucine; 18) D-Norleucine; 19) L-Leucine; 20) L-Norleucine; 21) γ-ABA; 22) D-2-aminoheptanoic acid; 23) L-2-aminoheptanoic acid (internal standard); 24) D-Aspartic acid; 25) L-Aspartic acid; 26) 6-AHA; 27) D-Glutamic acid and 28) L-Glutamic acid.

Figure 2.13: GC-MS calibration curve for derivatized (N-TFA, O-isopropyl) D-Aspartic acid.

Figure 2.14: GC-MS calibration curve for derivatized (N-TFA, O-isopropyl) L-Aspartic acid.

Figure 2.15: Schematic representation of diffraction and Bragg’s Law.

Figure 2.16: Schematic representation of a XRD and its main components.

Figure 3.1: X-ray diffraction pattern of a Rio Tinto sample 4 (RT4) and identification of jarosite, barite, quartz and pyrite minerals using the Rigaku’s 2DP software and a mineral database. Mineral quantification was determined using the Rietveld refinement method.

Figure 3.2: Single ion GC-MS chromatograms (25 to 85 minutes) of the derivatized (N-TFA, O-isopropyl) amino acids extracted from sample RT9 (m/z 126, 140, 154, 168, 182, 184, 198 and 210). Figure legend is as follows: 1) D-alanine; 2) L-alanine; 3) L-valine; 4) glycine; 5) L- leucine; 6) D-aspartic acid; 7) L-aspartic acid; 8) D-2-aminoheptanoic acid; 9) internal standard (L-2-aminoheptanoic acid); 10) D-glutamic acid and 11) L-glutamic acid, X) unidentified compounds.

Figure 3.3: Single ion GC-MS chromatograms (25 to 85 minutes) of the derivatized (N-TFA, O-isopropyl) serpentinite blank (m/z 126, 140, 154, 168, 182, 184, 198 and 210). Figure legend is as follows: 8) D-2-aminoheptanoic acid and 9) internal standard (L-2- aminoheptanoic acid), X) unidentified compounds.

Figure 4.1: X-ray diffraction pattern obtained from the XRD analysis of the soluble fraction of sample LB7. This XRD pattern is consistent with the presence of halite and gypsum.

Figure 4.2: Schematic representation of the mineralogical variability verified by XRD data between the 27 samples collected from the surface and subsurface of Lake Brown (LB), Lake Baladjie (LBa), Lake Deborah West (LDW) and Lake Gilmore (LG).

Figure 4.3: Representative backscattered electron image of sample LG5 and two elemental X- ray spectra suggesting the presence of iron oxide phases (hematite). Iron oxides are present in trace amounts in the samples collected from the acidic lakes from Western Australia.

Figure 4.4: Representative backscattered electron image of sample LDW1 and three elemental X-ray spectra suggesting the presence of iron oxide phases (goethite and ilmenite). Iron oxides are present in trace amounts in the samples collected from the acidic lakes from Western

Australia.

Figure 5.1: Relative classes abundances obtained from 16S rRNA amplicon sequencing and corresponding total number of reads for the sediment samples collected from Lake Brown, Lake Baladjie, Lake Deborah West and Lake Gilmore in Western Australia.

Figure 5.2: Single ion GC-MS chromatograms (20 to 85 minutes) of the derivatized (N-TFA, O-isopropyl) amino acids extracted from sample LBa5 (m/z 126, 140, 154, 168, 182, 184, and 198). Figure legend is as follows: 1) L-alanine; 2) L-valine; 3) glycine; 4) D-aspartic acid; 5) L-aspartic acid; 6) D-glutamic acid; 7) L-glutamic acid; 8) internal standard (D-2- aminoheptanoic acid); 9) internal standard (L-2-aminoheptanoic acid).

Figure 6.1 - Powder X-Ray diffraction patterns of hematite (Fe2O3). The figures indicate the d-spacing of the several peaks in angstroms. The intensity increase at ∼10 °2θ is produced by the X-ray fluorescence of Fe.

Figure 6.2 - Mars Chamber simulator located at the Open University (left) and the experimental setup inside the chamber showing the amino acid-spiked minerals (right).

Figure 6.3 - UV lamp spectrum and modelled UV spectrum expected at the martian surface.

Figure 6.4 - Single ion GC-MS chromatograms (25 to 85 min) of the derivatized (N-TFA, O- isopropyl) amino acids extracted from control sample G4 (goethite spiked with solution 4, but not subjected to the Mars simulation; chromatograms pointing upwards) and corresponding sample G4 (goethite spiked with solution 4 and analysed after the Mars chamber simulations; chromatograms pointing downwards). All single ions chromatograms are in the same scale. 1) α-AIB; 2) D,L-isovaline; 3) D-alanine; 4) L-alanine; 5) D-valine; 6) L-valine; 7) glycine; 8) D-norvaline; 9) D-β-AIB; 10) L-β-AIB; 11) D-β-ABA; 12) β-alanine; 13) L-β-ABA; 14) L- norvaline; 15) D-leucine; 16) D-norleucine; 17) L-leucine; 18) L-norleucine; 19) D-2- aminoheptanoic acid (internal standard); 20) γ-ABA; 21) L-2-aminoheptanoic acid (L-2-AHA, internal standard); 22) D-aspartic acid; 23) L-aspartic acid; 24) 6-AHA; 25) D-glutamic acid; 26) L-glutamic acid.

Figure 6.5 - Single ion GC-MS chromatograms (20 to 100 min) of the derivatized (N-TFA, O- isopropyl) extracts from the mineral labradorite used in the Mars Chamber simulations. All single ions chromatograms are in the same scale. 1) D-2-aminoheptanoic acid (internal standard); 2) L-2-aminoheptanoic acid (L-2-AHA, internal standard). Peaks x1, x2 and x3 represent unidentified compounds.

Figure 6.6 – Average amino acid recovery rates (in %) obtained for the control (i.e., non simulated) mineral standard samples. The rates presented in this figure are the ratios between the amount of the 25 amino acids extracted from the spiked, non simulated minerals and the total amount of the 25 amino acids spiked originally in the samples.

17 in a given experiment found in Table 6.1, Table 6.2 and Table 6.3. The lack of bars in basaltic lava and enstatite for experiment 2 means complete degradation of amino acids. Labradorite and jarosite were not used in experiments 4 and 2, respectively.

List of tables

Table 1.1: List of past, operational and future space missions to Mars (Source: Chronology of Mars Exploration, NASA).

Table 2.1: General information about the sediment samples collected during the three days CAREX field campaign at Annabel’s garden area, located in Rio Tinto’s river source.

Table 2.2: General information about the lacustrine sediment samples collected in the four ephemeral acidic lakes in the Yilgarn Craton, Western Australia: Lake Brown (LB), Lake Baladjie (LBa), Lake Deborah West (LDW) and Lake Gilmore (LG).

Table 2.3: Chemical structures of the amino acids and respective N-Trifluoroacetyl-O- isopropyl- (N-TFA, O-isopropyl-) derivatives used in the research.

Table 2.4: Molecular ions used for identification of the amino acids present in the samples.

Table 2.5: GC-MS calibration curves for derivatized (N-TFA, O-isopropyl) amino acids.

Table 3.1: XRD mineral identification and quantitative analyses of Rio Tinto sediment samples based on Rigaku’s 2DP software. Quantification is based on the Rietveld refinement method (weight percentage, wt%).

Table 3.2: Average of the carbon, nitrogen and sulfur (CNS) content (percentage per weight, %) obtained for the Rio Tinto samples collected during the CAREX field campaign. CNS analyses were performed twice for each sample.

Table 3.3 – Summary of phylogenetic affiliations, similarities and characteristics of microorganisms detected in Rio Tinto sediment samples.

Table 3.4 – Summary of the amino acid abundances (in ppb) obtained for the Rio Tinto samples measured by GC-MSa.

Table 3.5 - Summary of the mineralogical, elemental, microbiological and amino acid composition performed on ten Rio Tinto sediment samples collected during the CAREX field campaign.

Table 4.1: Results for mineral composition obtained by XRD for the sediment samples collected from Lake Brown and Lake Baladjie, in Western Australia. Minerals are written according to their relative abundances (i.e., from the most abundant mineral down to the least abundant mineral).

Table 4.2: Results for mineral composition obtained by XRD for the sediment samples collected from Lake Deborah West and Lake Gilmore, in Western Australia. Minerals are

19 written according to their relative abundances (i.e., from the most abundant mineral down to the least abundant mineral).

Table 5.1 – Relative abundances (in %) of the Archaea and Bacteria classes detected in the sediment samples collected from four hypersaline lakes (Lake Brown, Lake Baladjie, Lake Deborah West and Lake Gilmore) using 16S rRNA amplicon sequencing.

Table 5.2 – Summary of the amino acid abundances measured by GC-MS (in ppb) from the sediment samples of the acidic lakes from Western Australiaa.

Table 6.1 – Summary of the individual A/A0 ratios (in %) obtained for experiment 2 (spiking solution, 10 M of each amino acid) where A is the amount of the remaining amino acids detected in simulated samples and A0 is the amount of amino acids detected in the control.

List of abbreviations

α-ABA – alfa aminobutyric acid

α-AIB – alfa aminoisobutyric acid

2-AHA - 2-aminoheptanoic acid

6-AHA – 6-aminohexanoic acid

AMD – Acid mine drainages

BBOT - 2,5-Bis(5-tert-ButylbenzOxazol-2yl)Thiophene

BET - Brunauer-Emmett-Teller

CAREX - Coordination Action for Research on life in Extreme Environments

CheMin - Chemistry and Mineralogy

CNS – Carbon, Nitrogen and Sulfur

CRISM - Compact Reconnaissance Imaging Spectrometer for Mars

DCM – Dichloromethane

DGGE - Denaturing gradient gel electrophoresis

DNA - deoxyribonucleic acid

EDS - energy dispersive X-ray spectroscopy

EDTA - 2,2',2'',2'''-(Ethane-1,2-diyldinitrilo)tetraacetic acid

EGA - evolved gas analysis

ESA – European Space Agency

GCR - galactic cosmic rays

GC-MS – Gas chromatography and Mass Spectrometry

GPS - Global Positioning System

HiRISE - High Resolution Imaging Science Experiment

HPLC - High performance liquid chromatography

IDP - interplanetary dust particles

ILEWG - International Lunar Exploration Working Group

JPL – Jet Propulsion Laboratory

JSC – Johnson Space Center

LB – Lake Brown

LBa- Lake Baladjie

LDW – Lake Deborah West

LG- Lake Gilmore

MARSIS - Mars Advanced Radar for Subsurface and Ionosphere Sounding

MDRS – Mars Desert Research Station

MER – Mars Exploration Rover

MSL - Mars Science Laboratory

NASA - National Aeronautics and Space Administration

NHM – Natural History Museum

OMEGA - Observatoire pour la Minéralogie, l'Eau, les Glaces et l'Activité

OU – Open University

OTU - Operational taxonomic unit

PCR - Polymerase Chain Reaction

R2 - coefficient correlation

RNA – ribonucleic acid

ROS - reactive oxygen species

SAM - Sample Analysis at Mars

SEM - Scanning electron microscopy

SEP - solar energetic particles

TFA – Trifluoroacetyl

TFAA -Trifluoacetic anhydride

TFAA-IPA - Trifluoroacetic anhydride isopropanol

UK – United Kingdom

USA – United States of America

UV – Ultraviolet

XRD - X-ray diffractometry

List of Units

% - percent ° - degree °C – degrees centigrade Å – Angstrom cm - centimetre eV – electonvolt g – gram h – hour K – Kelvin kV – kilovolt km – kilometre km/h – kilometre per hour m – metre m2 – square metre M- molar MeV - megaelectronvolt m/z - mass/charge mGy – miligray mA – miliampere mg- milligram mL- millilitre mg/mL – milligram per millilitre min – minute mL/min – millilitre per minute nA – nanoampere ng – nanogram nm - nanometre ppb – parts per billion ppbv – parts per billion volume

24 ppm – parts per million sec – second wt % - percentage weight w/v – weight per volume yr- year μL – microliter μm – micrometre µmol – micromol μM – micromolar

List of minerals

Albite - NaAlSi3O8

Alunite -KAl3(SO4)2(OH)6

Ankerite - Ca(Fe,Mg,Mn)(CO3)2

Aragonite - CaCO3

Arcanite - K2SO4

Augite - (Ca,Na)(Mg,Fe,Al,Ti)(Si,Al)2O6

Barite - BaSO4

Bassanite - CaSO4 . 0.5(H2O) 2+ 3+ Copiapite - Fe Fe (SO ) (OH) .20(H O) 4 4 6 2 2 3+ Coquimbite - Fe 2(SO4)3.9(H2O)

Dolomite - CaMg(CO3)2

Enstatite - Mg2(Si2O6)

Goethite - FeO(OH)

Gypsum - CaSO4.2(H2O)

Halite – NaCl

Halloysite - Al2Si2O5(OH)4

Hematite - Fe2O3

Hexahydrite - MgSO4.6H2O

Illite - (K,H3O)(Al,Mg,Fe)2(Si,Al)4O10[(OH)2,(H2O)]

Jarosite - KFe3(SO4)2(OH)6

Kaolinite - Al2Si2O5(OH)4

K-feldspar - KAlSi3O8

Labradorite - (Ca, Na)(Al, Si)4O8

Microcline - KAlSi3O8

Montmorillonite - (Na,Ca)0.33(Al,Mg)2(Si4O10)(OH)2·nH2O

Muscovite - KAl2(AlSi3O10)(F,OH)2

Nacrite - Al2Si2O5(OH)4

Nontronite - Ca.5(Si7Al.8Fe.2)(Fe3.5Al.4Mg1)O20(OH)4

Olivine - (Mg, Fe)2SiO4

Plagioclase - NaAlSi3O8 – CaAl2Si2O8

Pyrite – FeS2

Quartz - SiO2

Saponite - Ca0.25(Mg,Fe)3((Si,Al)4O10)(OH)

Sylvite - KCl

Vanthoffite - Na6Mg(SO4)4

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Chapter 1

Introduction Chapter 1

Understanding the origin, evolution, distribution and future of life in the 3 universe are some of the major scientific challenges for science. The possibility that 0

Earth is the only planet harbouring life is as striking as the idea of an independent genesis elsewhere in our solar system or the universe. Astrobiology is the science that addresses these fundamental questions, incorporating subjects that not only have immense scientific significance but also arouse interest and stimulate our imagination.

The astrobiology research presented in this thesis focuses on studying amino acids as biosignatures of putative martian life as well as identifying the most suitable places to find life on Mars in future life-searching missions.

1.1 Definition of life

Finding an answer to the simple question “What is Life?”, or reaching a consensual definition of life seems to be a challenging and puzzling task, especially when we take into account the multiple interpretations and opinions that we can find on the subject (Tsokolov, 2009). One of the most cited definitions of life states that

“Life is a self-sustained chemical system capable of undergoing Darwinian evolution”

(Joyce, 1994). This sentence, however, still arises several questions regarding the basic definitions of life itself. Viruses, for instance, prompt intense debate whether they should be considered “life” or not. Despite the fact that viral particles are by far the most abundant biological entities on our planet (Suttle, 2007) and are also subject to Darwinian evolution, viruses appear to stand in a peculiar borderline of what we consider living entities and non-living entities. Even though viruses are made of the same macromolecules as cells from Archaea, Bacteria or Eukarya, they require a host

Introduction

to reproduce (Forterre, 2010). Furthermore, aspects that are considered hallmarks of the living world are also found in abiotic self-replicating systems, such as self- replication of nucleic acids or peptide-based molecular replicators based on coiled leucine zippers (for a review on abiotic self-replication see Meyer et al., 2012).

An alternative way to approach the problem around the definition of life was proposed by Koshland (2002). Instead of trying to define life itself, Koshland (2002) preferred to identify instead what seems to be common in all life forms on Earth, this means the basic pillars on which life is based upon. These pillars are: 1) a program

(stored in deoxyribonucleic acid (DNA), which contain the genes that encode for proteins, nucleic acids, etc. that carry out the reactions in living systems); 2) improvisation (to allow adjustments to pillar number 1, the program); 3) compartmentalization (all organisms are confined to a limited volume); 4) a continuous source of energy; 5) ability of regeneration; 6) adaptability and 7) seclusion. Campbell and Reece (2002) also listed what seems to be common traits in terrestrial life forms and these include: 1) ordered structure and organization; 2) ability to reproduce; 3) growth and development; 4) energy utilization; 5) response to environmental factors; 6) homeostasis and 7) evolutionary adaptation.

Regardless of the multiple definitions of Life that we may come across, it is known that, from a chemical standpoint, life as we know it is based on carbon and liquid water. Even though other types of biochemistry based on other elements, such as silicon may be a possibility, carbon is the essential element of all organic molecules that serve as the basis for all known forms of life. Carbon is also ubiquitous in the universe and is the fourth most abundant element (Arnett, 1996). Moreover,

Chapter 1 carbon is known for its versatility in terms of interactions and chemical bonding, thus 3 enabling the formation of complex molecules that are essential for life (Pace, 2001). 2

Another critical aspect for the occurrence of life is the access to energy sources, since energy utilization is a basic necessity for life (Campbell and Reece,

2002; Koshland, 2002). Life on our planet depends on external sources of energy, foremost of which are sunlight and energetically favourable redox-reactions of organic and inorganic molecules susceptible to oxidation (i.e., chemical energy).

Phototrophs are organisms that use the energy from light to carry out cellular metabolic processes, whilst chemotrophs meet these energetic needs from the oxidation of electron donors found in the environment. The most common types of metabolism include aerobic respiration, methanogenesis, hydrogen oxidation, sulfur reduction, denitrification, and iron/manganese reduction (Dirk and Irwin, 2004). The occurence of oxidation of rare elements present in our planet, (e.g arsenic, uranium, selenium, copper and lead), also suggests that life adapts in terms of energetic requirements and that life may have evolved to depend on different forms of energy elsewhere in the universe (Dirk and Irwin, 2004).

1.2 The search for life in the Universe

The exploration of our own planet has revealed that life can be found in truly inhospitable places. Extremophiles are defined as organisms that adapted to conditions that, from an anthropocentric perspective, appear to be extreme (Trent,

2000). The discovery and study of these extremophiles from the three domains of life

(i.e., Archaea, Bacteria and Eukarya), has often challenged the paradigms of biology

Introduction

and also triggered discussion on the definitions, origins and limits of life (Rampelotto,

2013).

Extremophiles may be found in extremely cold or hot environments

(psychorophiles and thermophiles, respectively) and extremely acidic or alkaline habitats, which comprises acidophiles or alkaliphiles (Satyanarayana et al., 2005).

Other relevant classes of extremophiles include: halophiles, which tolerate high levels of salinity; barophiles, which withstand high pressure levels; oligotrophs, comprising organisms that thrive in environments containing extremely low amount of nutrients; radiation-resistant microorganisms, which can survive under intense levels of radiation; and toxitolerants, which include organisms that thrive in the presence of organic solvents, hydrocarbons and heavy metals (Satyanarayana et al., 2005). The realisation that organisms can survive in a broad range of extreme environments on

Earth has greatly expanded the number of extraterrestrial bodies that are considered good candidates to find signs of extinct/extant life.

In the quest to find extraterrestrial life, several planets and satellites have already been proposed as potential targets for exploration and research, such as Mars, the Jovian satellite Europa as well as Saturn’s satellites Enceladus and Titan (McKay,

2011). Among these planetary bodies, Mars, the fourth planet in our solar system and roughly half of the size and a tenth of the mass of the Earth, is the main focus of space exploration in the search for alien life. Mars not only provides environments that are, or were, likely to be hospitable for living organisms, but also represents the least logistically and technically difficult target for exploration. Numerous planetary missions have, therefore, already examined the planet and others are currently in operation or planned. Table 1.1 lists all the missions that were developed or being

Chapter 1 currently planned to explore Mars. Up to the present day, approximately, only 41 % 3 of space missions to the Red Planet were completely successful. This illustrates 4 difficulty of the endeavor and the importance of exhaustive preparation regarding the identification of biosignatures on Mars.

Table 1.1: List of past, operational and future space missions to Mars (Source: Chronology of Mars Exploration, NASA). Spacecraft Launch date Country/Operator Type of mission Result

1M No1 10 October 1960 USSR Flyby Launch failure (Marsnik 1) 1M No2 14 October 1960 USSR Flyby Launch failure (Marsnik 2) 2MV-4 No1 24 October 1962 USSR Flyby Launch failure (Sputnik 22) 2MV-4 No2 1 November 1962 USSR Flyby Spacecraft failure (Mars 1) 2MV-3 No1 4 November 1962 USSR Lander Launch failure (Sputnik 24) Mariner 3 5 November 1964 United States Flyby Launch Failure Mariner 4 28 November 1964 United States Flyby Successful 3MV-4A No2 30 November 1964 USSR Flyby Spacecraft failure (Zond 2) Mariner 6 25 February 1969 United States Flyby Successful Mariner 7 27 March 1969 United States Flyby Successful 2M No521 27 March 1969 USSR Orbiter Launch failure 2M No522 2 April 1969 USSR Orbiter Launch failure Mariner 8 9 May 1971 United States Orbiter Launch Failure 2MS No170 10 May 1971 USSR Orbiter Launch failure (Kosmos 419) 4M No171 Orbiter successful/ 19 May 1971 USSR Orbiter/Lander (Mars 2) lander failure Orbiter successful/ 4M No172 lander partial 28 May 1971 USSR Orbiter/Lander/Rover (Mars 3) success/ rover failure Mariner 9 30 May 1971 United States Orbiter Successful 3MS No52S 21 July 1973 USSR Orbiter Spacecraft failure (Mars 4) 3MS No53S 25 July 1973 USSR Orbiter Spacecraft failure (Mars 5)

Introduction

Table 1.1 (cont): List of past, operational and future space missions to Mars (Source: Chronology of Mars Exploration, NASA). Spacecraft Launch date Country/Operator Type of mission Result

3MP No50P 5 August 1973 USSR Flyby/Lander Lander contact lost (Mars 6)

3MP No51P 9 August 1973 USSR Lander Spacecraft failure

(Mars 7)

Viking 1 20 August 1975 United States Orbiter/Lander Successful

Viking 2 9 September 1975 United States Orbiter/Lander Successful

1F No101 7 July 1988 USSR Orbiter/Phobos Lander Spacecraft failure

(Phobos 1)

1F No102 7 July 1988 USSR Orbiter/Phobos Lander Orbiter success/ lander failure (Phobos 2)

Mars Observer 25 September 1992 United States Orbiter Spacecraft failure

Mars Global 7 November 1996 United States Orbiter Successful Surveyor

M1 No520 16 November 1996 Russia Orbiter/Lander Launch failure

(Mars 96)

Mars 4 December 1996 United States Lander/Rover Successful Pathfinder/Sojourner

PLANET-B 3 July 1998 Japan Orbiter Spacecraft failure

(Nozomi)

Mars Climate 11 December 1998 United States Orbiter Spacecraft failure Orbiter

Mars Polar 3 January 1999 United States Landers Spacecraft failure Lander/Deep Space 2

Mars Odyssey 7 April 2001 United States Orbiter Successful and still operating

Mars Express 2 June 2003 Europe (ESA) Orbiter Successful and still operating

Beagle 2 2 June 2003 Europe (ESA) Lander Successful landing but no contact

MER-A 10 June 2003 United States Rover Successful

(Spirit)

MER-B 8 July 2003 United States Rover Successful and still operating (Opportunity)

Mars 12 August 2005 United States Orbiter Successful and still Reconnaissance operating Orbiter

Chapter 1

Table 1.1 (cont): List of past, operational and future space missions to Mars (Source: Chronology of Mars Exploration, NASA). 3 Spacecraft Launch date Country/Operator Type of mission Result 6 Phoenix 4 August 2007 United States Lander Successful Mars Science 26 November 2011 United States Rover Successful and still Laboratory operating

(Curiosity)

Mars Orbiter 5 November 2013 India Orbiter Successful and still Mission operating

(Mangalyaan)

MAVEN 18 November 2013 United States Orbiter Successful and still operating

ExoMars Trace Gas 14 March 2016 Europe (ESA)/Russia Orbiter Successful and still Orbiter operating

Schiaparelli EDM 14 March 2016 Europe (ESA)/Russia Lander Spacecraft failure Lander

InSight 5 May 2018 United States Lander In development

Mars 2020 July 2020 United States Rover In development

ExoMars Rover July 2020 Europe (ESA) Rover In development

Mars today is a cold, desert-like rocky body with a thin atmosphere approximately composed of 95 % of CO2 (Grady, 2008; Fairén et al., 2010; Quinn et al., 2013). The harsh martian environment is caused mostly by low atmospheric pressure (approximately 600 Pa) and the absence of a magnetosphere (Grady, 2008;

Fairén et al., 2010). These factors result that: 1) liquid water is mostly absent in the surface, 2) the planet experiences freezing temperatures (average temperature is -

65 ̊C) and 3) organic molecules present in the martian regolith are subjected to intense and multiple forms of solar radiation (Cockell et al., 2000; Hassler et al., 2014).

Despite these harsh conditions, there are plentiful lines of evidence that Mars had previously a different environment that may have made it much more habitable. It is now assumed that Mars and Earth were, in fact, very much alike in their early history and shared similarities in their early geological periods, including the early

Introduction

delivery of organic molecules, essential to life, during periods of cometary and meteoritic bombardment (e.g., Kanavarioti and Mancinelli, 1990; Grady, 2008).

Moreover, it is also known that some martian river channels were formed recently on geological timescales, certainly significantly after the origin of life on

Earth (Gulick and Baker, 1989). The current knowledge of the geological history of

Mars, including the presence of liquid water in the past, and the ability of extremophiles to adapt to inhospitable environments on Earth ultimately support and motivate the development of life-searching missions to the Red Planet.

1.3 Life on Mars and history of Mars exploration

Mars has been, since the emergence of the earliest civilizations (Egyptians,

Babylonians and Greeks), the subject of much interest to humans (Sheehan, 1996). In

1609, Galileo Galilei observed Mars for the first time in a telescope (Sheehan, 1996) and speculation about possible martian life started to emerge as early as 1698, when

Christiaan Huygens’s Cosmotheoros was posthumously published. Through regular observations of a dark spot on Mars’ surface (Syrtis Major), Huygens realized that the complete rotation movement of Mars would take approximately 24.5 hours. Huygens theorized then that martian inhabitants would experience days and night similar to what humans experienced on Earth. The first suggestion that Mars had climatic seasons just like Earth was proposed by Friedrich Herschel in 1783, after discovering that Mars’ axial inclination was very similar to that of Earth (Sheehan, 1996). Almost a century later, in 1879, Giovanni Schiaparelli observed for the first time that Mars

Chapter 1 had linear feature on its surface and suggested they were systems of canals 3 comparable to fluvial systems on Earth. Schiaparelli stated in a correspondence that 8

“It is as impossible to doubt their existence as that of the Rhine on the surface of the

Earth” (Sheehan, 1996). The observation of supposed canals on martian surface sparked intense debate on their nature and also contributed to theorize on possible martian life. The most notable and controversial case was Percival Lowell’s theory of martian canals, which suggested that these structures were, in fact, the work of an intelligent civilization and were built for irrigation of fertile lands in a water-limited world (Sheehan, 1996). The idea that Mars had canals was greatly contested by other scientists such as Alfred Wallace and eventually proven as optical illusions by Eugène

Antoniadi in 1909 (Sheehan, 1996). Spectroscopic evidence that Mars was, in great extent, dominated by extreme desert conditions started to appear as soon as in the decade of 1920 (Adams and St. John, 1925).

The extreme aridity of the martian surface, the presence of impact craters and the absence martian artificial canals were confirmed in the 1960s, when NASA’s flyby missions Mariner 4, Mariner 6 and Mariner 7 successfully photographed the planet (Leighton et al., 1965; Leighton et al., 1969). The first images unveiled by

Mariner 4, 6 and 7 revealed that the martian surface was surprisingly “moon-like”, i.e., intensely cratered and dry as it is shown in Figure 1.1 (Leighton et al., 1965;

Leighton et al., 1969; Sheehan, 1996).

Introduction

Figure 1.1: One of the first photographs of the martian surface, taken by Mariner 4 flyby mission, showing craters in the Memnonia Fossae region of Mars, 1965. (Image Credit: JPL/NASA).

In addition to the surface images, the discovery of a thin atmosphere, low temperature and absence of magnetic field lowered considerably the expectations and prospects of finding liquid water and extant life on the Red Planet (Sheehan, 1996).

In 1971, Mariner 9 was the first object to orbit another planet and, over the course of one year, the orbiter photographed extensively the surface of Mars (Figure

1.2). Mariner 9 provided image evidence of channels formed by running liquid

(probably water) that resembled riverbeds on Earth (Milton, 1973; Jones, 2008). On

Earth, liquid water is an essential pre-requisite for the existence of life. The suggestion that liquid water was once present on Mars raised the question of whether microscopic forms of live ever developed on the martian surface, presumably in a geological time when climatic conditions were more amenable (McKay 1997, Jones

Chapter 1

2008). The discovery of such channels and evidence of past-flowing liquid water 4 suggest that Mars experienced slow but major changes throughout its geological 0 history, including climatic conditions and the ability to support life.

Figure 1.2: Mariner 9 image of a Nirgal Vallis region showing the first evidences of ancient river channels on Mars, 1971. (Image credit: JPL/NASA).

The results obtained from the Mariner 9 mission were entirely obtained from orbit and soon the Viking 1 and Viking 2 missions were developed to go a step further and actually perform experiments in the martian surface (Sheehan, 1996). NASA’s

Viking program was the very first ever to land on another planet with the aim to search for signs of extraterrestrial life (Klein et al., 1972).

The Viking landers had programmed three scientific experiments in order to detect signatures of life on Mars. One, called pyrolytic release experiment, tried to

14 detect photosynthetic activity in the martian soil using CO and CO2 labeled with C

Introduction

(Hubbard, 1976). The second experiment, the gas exchange experiment, aimed to determine which gases were produced by the martian sample after the addition of nutrients (Oyama, 1972). Finally, the third experiment, called the labeled released experiment, was designed to detect which carbonated gases would be released after the addition of nutrients labeled with 14C (Levin and Straat, 1976). From these experiments, only the labeled release experiment yielded results compatible with the presence of life in the martian samples (Klein, 1978; Levin and Straat, 1977).

However, the most striking results were obtained by the gas chromatograph-mass spectrometers (GC-MS) onboard the Viking landers, which were unable to detect any indigenous organic molecules in the martian regolith above a few parts per million

(ppm) (Biemann et al., 1977).

The GC-MS results were surprising, considering that carbon and organic molecules are continuously brought to Mars by meteorites and interplanetary dust particles (Chyba and Sagan, 1992; Zent and McKay 1994, Flynn 1996), contributing

2.4 x 106 kg of organic matter per year. Based on these facts, it was later suggested that the absence of detectable organic molecules on the surface was due to lack of sensitivity of Viking’s instrumentation. Results from Glavin et al. (2001) indicate that pyrolysis’ degradation products coming from several million bacterial cells in one gram of martian soil would not be detected by Viking’s GC-MS. Alternative interpretations for Viking’s results are based on possible oxidative degradation processes originated by ultraviolet (UV) radiation and/or oxidizing chemicals (such as

H2O2) present on martian surface (Klein, 1978; Stoker and Bullock, 1997; Benner et al., 2000). Moreover, results observed by Quinn et al. (2005) using Atacama soils suggest that the oxidative nature of martian regolith may also be caused also by acid

Chapter 1 mediated reactions caused by accumulated strong acids and high oxidation potential 4 during brief wetting events. Oxidation of organic molecules sourced by meteoritic 2 infall could also produce non-volatile organic compounds (such as benzenecarboxylates, oxalates and acetates salts) that would not be detected by GC-

MS (Benner et al., 2000).

Re-analysis of Viking’s data was performed after NASA’s Phoenix lander detected the presence of perchlorate at concentrations around 0.5 wt% (Hecht et al.,

2009). Navarro‐González et al. (2010), argued that the trace amounts of chloromethane and dichloromethane (parts per billion (ppb)) detected by Viking were actually products of thermal induced oxidation of martian organic compounds by perchlorate during pyrolysis. These conclusions, however, were questioned by

Biemann and Bada (2011) who argue that: 1) if the kinetic models used by Navarro‐

González et al. (2010) assume chloromethane and dichloromethane are produced by reaction of chlorine (produced from perchlorate thermal decomposition) with methane, other chloroalkanes such as chloroform and tetrachloromethane should also be also detected; and 2) methane could not be detected when soils are heated without perchlorate. Debates aside, it is known, though, that perchlorate salts do combust organic compounds during pyrolysis (Ming et al., 2009).

1.3.1 Mars exploration after Viking mission

The results obtained from the the Viking missions constituted for nearly twenty years the most important set of scientific evidence about the Red Planet. After the Viking missions, Mars was successfully explored in 1997 by NASA’s Pathfinder

Introduction

lander and Mars Global Surveyor orbiter (Grady, 2008). Pathfinder was mainly seen as a proof-of-concept mission, aiming to test technology that would be used in future

NASA rovers (Mishkin et al., 1998). The Mars Global Surveyor orbiter on the other hand, gathered, during more than three years, high resolution photographs of the martian surface (Malin and Edgett, 2001). The photographs taken by the orbiter revealed a much more complex surface than previously thought and revealed that

Mars was not merely a lunar-like crust underneath an atmosphere. The planet Mars that was revealed by the Mars Global Surveyor orbiter was found to have, for example, gullies that seemed to be caused by surface runoff of water on martian slopes, streaks resulting from mass movements on the surface, pervasive layering of the crust up to depths of ten kilometres and multiple evidence of weathering, transport and deposition of materials near crater rims (Malin and Edgett, 2001).

Further evidence of water on Mars was obtained by the neutron spectrometer onboard NASA’s orbiter Mars Odyssey, which was launched in 2001 (Feldman et al.,

2002). Large amounts of hydrogen were found near the poles (± 60̊ latitude), buried in the first meters of martian soil. Feldman et al., (2002) suggested that the neutron spectrometer data obtained could be readily explained by the presence of near-surface water ice buried underneath hydrogen-poor soil.

In 2003, ESA’s Mars Express entered martian orbit (Grady, 2008). Within the first months of operation, the OMEGA (Observatoire pour la Minéralogie, l'Eau, les

Glaces et l'Activité) instrument onboard Mars Express discovered mafic and ultramafic materials (pyroxene and olivine); confirmed the presence of perennial water ice in both poles and permafrost surrounding the south pole; identified phyllosilicates (e.g., nontronite) resulting from the alteration of mafic to ultramafic

Chapter 1 igneous rocks; detected sulfates (kieserite and gypsum) commonly associated with 4 hydrated silicates and/or ferric oxides (Bibring et al., 2005). The discovery of sulfates 4 on Mars represented at the time, according to Bibring et al., (2005), the best mineralogical record of a water-driven past activity on the planet. Furthermore, the

Planetary Fourier Spectrometer onboard the Mars Express spacecraft detected an average of 10 ± 5 parts per billion by volume (ppbv) of methane in the martian atmosphere, which could be originated by microorganisms, hydrothermal activity, or cometary impacts (Formisano et al., 2004). Finally, results obtained by the Mars

Advanced Radar for Subsurface and Ionosphere Sounding (MARSIS) instrument support the existence of an ancient ocean on the northern lowlands. Mouginot et al.,

(2012) observed that dielectric constants on the northern plains are lower than the dielectric constants typically measured in volcanic materials, suggesting the existence of a large water body during the Late Hesperian that eventually sublimed to the atmosphere or froze in place and stayed preserved underground.

The Mars Reconnaissance Orbiter entered Mars orbit in 2006 and transported the High Resolution Imaging Science Experiment camera (HiRISE), which allowed mapping the planet in high definition (McEwen et al., 2007). The Mars

Reconnaissance Orbiter observed recurring slope lineae in equatorial Mars, showing that intermittent flow of briny water may be a reality on Mars and that abundant liquid water may be present in near-surface equatorial regions (McEwen et al. 2014). Other interpretations suggest, however, that the occurrence of recurring slope lineae on Mars may be related to dry, granular flows of martian regolith that are inconsistent with significant amounts of water (Dundas et al., 2017). In addition, the

HiRISE camera also found newly formed impact craters in mid-latitudes that revealed

Introduction

exposed bright layers indicative of relatively pure water ice (Byrne et al., 2009). The

HiRISE camera also photographed five newly formed impact craters and found that their brightness was fading, showing the sublimation of the exposed ice sheets in the craters (Byrne et al., 2009). The HiRISE camera studied in detail geological features related to volcanism, including vents, flood lavas and suggestions of widespread pyroclastic deposits. (Keszthelyi et al., 2008). Through Mars Reconnaissance Orbiter imaging it was observed that Athabasca Valles, the youngest outflow channel system on Mars and likely formed by aqueous processes, is draped by lava and contains hydrovolcanic cones, suggesting that surface exposures of flood sediments may be difficult to find (Jaeger et al., 2007). Furthermore, The Mars Reconnaissance Orbiter also detected, with the Compact Reconnaissance Imaging Spectrometer for Mars

(CRISM) instrument, aluminium and ferro-magnesian smectites, kaolinite, hydrated sulfates and carbonates, showing an increased variety of minerals related to aqueous activity (Murchie et al., 2009).

Surface exploration of Mars was resumed in 2004 by the Mars Exploration

Rovers Spirit (MER-A) and Opportunity (MER-B) with the aim to search for signs of water activities on the surface of Mars (Rieder et al., 2003). In the same year,

NASA’s Opportunity rover confirmed, at Meridiani Planum, the presence of outcrops rich in hematite and jarosite using Mössbauer spectroscopy (Klingelhöfer et al.,

2004). The rover Spirit, on the other hand, identified goethite in Columbia Hills

(Morris et al., 2006) The in-situ identification of these minerals in martian outcrops are relevant for astrobiology because they are an indicator of past water activity and indicated the presence of a putative habitable region (Squyres et al., 2004; Morris et al., 2006). For instance, jarosite deposits are usually formed through evaporation of

Chapter 1 acidic water basins under oxidative conditions showing that climate conditions 4 changed considerably on Mars (Klingelhöfer et al., 2004). 6

In 2008, NASA’s Phoenix lander was the first spacecraft to land near the polar regions and detected the perchlorate anion (Hecht et al., 2009), which may have contributed for the conflicting results obtained by the Viking landers regarding the absence of organic molecules in the martian regolith (Navarro‐González et al., 2010).

The martian surface is currently being studied by NASA’s Mars Science

Laboratory (MSL) rover Curiosity. This rover, which landed in August 2012, was designed to study past and present habitability conditions of Mars at Gale Crater

(Mahaffy, 2008). Over the course of four years, Curiosity confirmed the existence of past fluvial-lacustrine habitable environments at Yellowknife Bay and its potential to have hosted microbial life (Grotzinger et al., 2014). In addition, results obtained by the Sample Analysis at Mars (SAM) instrument onboard Curiosity also point towards a widespread occurrence of perchlorate salts over Mars, due to the detection of this anion in Gale Crater (Archer et al., 2013; Leshin et al., 2013; Ming et al., 2014).

Curiosity also observed that the presence of salts in the martian surface allows the formation of transient liquid brines in the uppermost 5 cm of equatorial subsurface and that these brines, despite not being able to support microbial life due to low water activity, may be widespread beyond equatorial regions (Martin-Torrez et al., 2015).

Curiosity was the first spacecraft to drill the martian surface, at Yellowknife Bay (the first drill site being known as John Klein), and pyrolysis of the subsurface samples revealed, in a similar way to Viking results, the presence of chloromethanes (Ming et al., 2014). These chlorinated hydrocarbons detected from the pyrolysis experiments could not be confirmed as indigenous and it was suggested, instead, that these

Introduction

molecules were derived from internal carbon sources carried by the instruments

(Ming et al., 2014). The definitive identification of indigenous martian organic molecules occurred at the Cumberland drill hole site in the Sheepbed mudstone at

Yellowknife Bay (Freissinet et al., 2015). The identification of chlorobenzene (up to

300 parts per billion (ppb)) and C2 to C4 dichloroalkanes (up to 70 ppb) with the SAM instrument (GC-MS) and detection of chlorobenzene in the direct evolved gas analysis (EGA) was interpreted to be a result of martian chlorine and organic carbon derived from martian sources (e.g., igneous, hydrothermal, atmospheric, or biological) or exogenous sources such as meteorites, comets, or interplanetary dust particles

Freissinet et al., (2015).

1.4 Geological History of Mars

The geological history of Mars, which is based on size and frequency analysis of the impact craters present on the martian surface, is divided into four main periods:

Pre-Noachian, Noachian, Hesperian and Amazonian (Baker, 2006).

The pre-Noachian period refers to the geological era that extends from the planetary formation and accretion (4.5 billion years ago) up to the start of the

Noachian era (4.1 billion years ago). There are few insights about the very early events that occurred during the pre-Noachian, due to subsequent surface processes such as erosion and impact cratering (Carr and Head, 2010). The main observable geologic feature attributed to the pre-Noachian period is the crustal dichotomy between the northern and southern martian hemispheres, which include, for example, differences in elevations and crustal thickness and evidence that Mars had a magnetic field (Carr and Head, 2010). For instance, the elevation difference between the two

Chapter 1 hemispheres is approximately 5.5 km (Aharonson et al., 2001) and the thickness of 4 the northern crust is estimated to be, on average, approximately half of the thickness 8 of the southern crust (Neumann et al., 2004). Also, even though magnetic anomalies resulting from Mars early magnetization are found globally, crustal magnetization in the northern lowlands is much weaker than that found in the southern highlands

(Acuña et al., 1999). The most common hipotheses considered for the formation of the martian crustal dicothomy are excavation of the northern lowlands by giant impacts or endogenic mechanisms related to mantle dynamics (Reese et al., 2010).

The differences in hemispherical elevations caused by this early, pre-Noachian crustal dicothomy most likely provided the ideal physical and geological conditions in the northern hemisphere to contain higher amounts of water, including a putative primordial northern ocean covering Vastitas Borealis (Villanueva et al., 2015).

The Noachian, which comprises the period of time ranging from 4.1 up to 3.7 billion years ago, was named after the heavily cratered region of Noachis Terra, located on the southern hemisphere of Mars. During this era, Mars experienced high rate of crater formation and intense volcanism. Most of the Tharsis region is thought to have formed during this era (Carr and Head, 2010). Mars during the Noachian was certainly a wetter planet and Noachian erosion rates were up to 5 orders of magnitude higher than in subsequent eras. This is backed by evidence of erosion in Noachian craters, which usually have highly eroded rims and partly filled interiors as is shown in Figure 1.3 (Carr and Head, 2010). Valley formation was also common during the

Noachian, hypothetically caused by a substantial primordial martian atmosphere that was similar to that found on early Earth (Craddock and Howard, 2002). Condensation within the denser atmosphere present during the Noachian resulted in precipitation

Introduction

onto the surface and into the regolith, contributing to the processes that carved the valley networks, created outflow channel formations and eroded impact craters in the southern highlands (Hynek et al., 2010).

Figure 1.3: Schematic representation of Mars geological history since its formation (4.5 billion years ago) up to the present day and main geological phenomena that occurred in each

geological era. The Pre-Noachian and Noachian are joined together for image simplification. The top three images of Mars show how the planet gradually lost its liquid water on the surface and became the planet we know today. The three bottom photographs were taken by the High Resolution Stereo Camera onboard ESA's Mars Express. The left photograph is a representative Noachian surface with eroded impact craters (the bigger one being 25km wide) in Hellas Basin. The middle photograph shows outflow channels in Kasei Valles, a geological feature typically associated with Hesperian terrains. The bottom right image shows Reull Vallis, and illustrates a typical Amazonian landscape, with few impact craters. The valley is 7 km with a depth of around 300 m and is believed to be formed in a similar way to glacial valleys on Earth. (Figure based on Bibring et al. 2006. Top images credits: NASA Ames Research Center Image Library. Three bottom photographs credits: ESA/DLR/FU Berlin).

Chapter 1

Furthermore, the existence of a primordial ocean on the northern hemisphere 5 during the Noachian, covering approximately one third of the planet’s surface, 0 seemed like an inevitability, given the hydraulic and thermal conditions that existed during the early stages of this period (Clifford and Parker, 2001). For instance, the water ice found in the polar caps is greatly enriched in deuterium, suggesting significant loss of vasts amounts of water that could have covered the whole entire surface of Mars up to a depth of 137m, but were instead mostly concentrated in the northern plains (Villanueva et al., 2015). Ultimately, surface conditions that prevailed during this wet period enabled a widespread production of weathering mineral products such as phyllosilicates (Bibring et al., 2006). Phyllosilicates are abundant in old Noachian surfaces and craters, implying that long-term chemical interactions between liquid water and igneous rocks took place in the region (Ehlmann et al.,

2011).

The Hesperian, named after Hesperia Planum, was the geological period that started after the cessation of the late heavy bombardment, around 3.7 billion years ago. The Hesperian, which is thought to have ended around 3 billion years ago, was a period that was mostly marked by intense volcanism, which led to the resurfacing of at least 30 % of the planet (Carr and Head, 2010). On the other hand, the Hesperian was also marked by a sharp decline of impact cratering rate, due to the cessation of the late heavy bombardment, as well as a decrease of valley formation, weathering, and erosion (Warner et al., 2010). The global environmental change that started during the Noachian-Hesperian transition may have been primarily influenced by a gradual atmospheric loss to the space and atmospheric erosion caused by impacts during the Late Heavy Bombardment (Pham et al., 2009; Terada et al., 2009). It is

Introduction

also assumed that water abundance started to decrease during the transition from the

Noachian into the Hesperian, turning the once water-rich Noachian Mars into an increasingly arid planet with saline and acidic near surface waters (Warner et al.,

2010). A significant part of the fluvial features found on Hesperian terrains were formed by large and catastrophic outflow channels (Figure 1.3 - Carr and Head,

2010). Hesperian terrains on Mars with limited and temporary access to water were mostly subjected to acid sulfate weathering, which triggered the formation of sulfate- bearing deposits (Bibring et al., 2006). The predominance of sulfate-minerals in this period was likely linked to massive influx of SO2 into the martian atmosphere/hydrosphere caused by the intense Noachian-Hesperian volcanism

(Bullock and Moore, 2007).

The Amazonian period, named after Amazonis Planitia, is the longest geological period of Mars, extending from approximately 3 billion years ago until the present day. Surface geomorphological changes during the Amazonian period, such as impact cratering, tectonism and volcanism are relatively scarce, especially when compared with the Noachian and Hesperian (Golombek et al., 2006). Furthermore, the extremely low erosion and weathering rates that were verified during the

Hesperian continued and decreased even further with the advance of the Amazonian period (Golombek et al., 2006). Even though the Amazonian climate is mostly characterized by the current prevailing conditions that we can observe on Mars today

- cold and hyperarid – there are several examples showing that water activity has not been entirely absent from the planet during relatively recent geological times (Figure

1.3). Most of the water activity that occurred/occurs in the Amazonian is related to ice. Mars contains a large reservoir of water ice and, according to Christensen (2006);

Chapter 1 the approximate volumes of water ice are 5x106 km3 in polar layered materials, over 5 6x104 km3 in mid-latitude mantles and ice-rich sediments, and approximately 3x10-2 2 km3 in the seasonal ice caps and atmosphere. This reservoir, if melted, would have enough quantity to form a layer of water approximately 35 m deep over the entire planet (Christensen, 2006). On the other hand, due to low atmospheric pressures, ice is unstable at the surface between mid to high latitudes. Mellon and Jakosky (1995) suggest that water ice may be globally stable in many locations in the subsurface, but its abundance is strongly affected by obliquity, which is the spin axis orientation of the planet. Mars’ obliquity is known to evolve chaotically and the extreme changes in martian obliquity throughout geological periods of time had important implications in the Red Planet’s climate (Laskar et al. 2004; Wordsworth, 2016). Pronounced changes in obliquity have strong effects on seasonal distribution and intensity of solar radiation, atmospheric pressure and distribution of relevant martian volatiles (such as

CO2 and water) on the planet and between atmospheric, surface, and subsurface reservoirs (Laskar et al. 2004). For instance, water ice at present obliquity values

(approximately 25°) is expected to be stable only in high-latitude areas. On the other hand, at high obliquity values (e.g., >40°), substantial amounts of water ice may sublime from the polar regions and move to the equator, where it would be more stable (Jakosky et al.,1995).

Recently, the Phoenix lander confirmed the presence of shallow water ice table a few centimetres below the surface (Smith et al., 2009). Subsurface water ice may be also exposed by impact cratering (Byrne et al., 2009). Water activity during the Amazonian, however, has not been exclusively related to water ice. This is supported, for example, by traces of channels, deltas, fan-shaped deposits in the

Introduction

southern highlands and early Amazonian valleys showing signs of formation by precipitation and surface runoff (Hauber et al., 2013). Moreover, analyses of the 1.3 billion year-old Lafayette meteorite by Swindle et al. (2000) revealed the presence of iddingstite (MgFe2Si3O10•4(H2O)), which is formed by alteration of basalt (olivine) by liquid water. The presence of weathering products in the Lafayette meteorite suggest that liquid water was certainly present on Mars around 1.3 billion years ago and possibly within the last 650 million years (Swindle et al., 2000). Hauber et al.

(2013) verified that several delta formations located around the ancient impact basin

Chryse Planitia were formed in the Late Amazonian. The formation of deltas during this period shows that geological formations suggesting the presence of water do not require longstanding water bodies or sustained periods of global climatic conditions favouring precipitation.

Even though the Amazonian is known to be the period when Mars became a hyperarid and desiccated planet, water in the liquid state has been present, although only episodically, for transient intervals, and mostly within isolated spots.

1.5 Where to search for Life?

Mars geological history suggests that the Red Planet had, during the Pre-

Noachian and the Noachian, the right set of conditions for the origin of microbial life.

However, habitability conditions on Mars have gradually degraded since the

Noachian period, and it is thought that habitable environments were always heterogeneously distributed both on a spatial scale and geological time frame (Westall

Chapter 1 et al., 2013). This is due to the climatic changes that Mars experienced throughout its 5 history and also due to the absence of a global ocean (Westall et al., 2013). Therefore, 4 if life ever existed on Mars, its spatial distribution would likely be more limited than on Earth. With these constraints to martian habitability, it is therefore important to know which regions on Mars are more likely to preserve putative life and or its biosignatures.

1.5.1 Shielding effect from subsurface environments

The detection of indigenous organic molecules by Curiosity in past habitable fluvial-lacustrine environments, such as Yellowknife Bay, suggests that organic molecules related to life may actually be found if life is/was ever present. However, owing to the harsh conditions present on the martian surface, any evidence of extinct/extant life or related chemical signature should be easier to find below the surface (Figure 1.4). Environments in the subsurface of Mars offer the possibility of preserving organic molecules and putative life from the multiple forms of harmful solar radiation, including UV radiation, galactic cosmic rays (GCR) and solar energetic particles (SEP) (Cockell et al., 2000; Hassler et al., 2014). This preservation potential offered by subsurface environments will be explored in future life-searching missions such as ExoMars, which will be able to drill samples up to 2 metres below the surface (Vago et al., 2013). The following two sections aim to explain why subsurface environments prevent the degradation of organic molecules and why they should be targeted if we want to maximize the chances of finding life and its signatures.

Introduction

Figure 1.4: Schematic representation of the upper martian crust and immediate subsurface environments. The darker section (right underneath the surface) illustrates subsurface regions that are highly affected by multiple radiation forms, such as ultra-violet radiation (UV, purple arrow, affecting the surface), solar energetic particles (SEP, yellow arrow, affecting the surface and penetrating into the first centimetres of martian regolith) and galactic cosmic rays (GCR, red arrow, which can penetrate up to the meter scale into the regolith). The lighter section in this image represents putative subsurface environments, not highly affected by oxidizing radiation and generally assumed to contain preserved organic molecules (biosignatures). Image credit: ESA.

1.5.1.1 - UV radiation

Solar UV radiation is an important source of radiation that influences the chemistry of the martian regolith and fate of organic molecules on the Red Planet’s surface. Owing to a thinner atmosphere and lack of a significant protective ozone layer, the solar UV radiation flux that reaches Mars’ surface is higher than in the case of Earth, (Cockell et al., 2000). Moreover, CO2 is the most abundant component of the martian atmosphere (around 95.7 % abundance). Carbon dioxide provides

Chapter 1 efficient shielding only for UV radiation below 200 nm (Garry et al., 2007). 5 Therefore, unlike Earth, the martian regolith is irradiated by more energetic (i.e., 6 shorter wavelengths) forms of UV radiation, such as UV-B (280-320 nm) and UV-C

(200-280 nm) (Garry et al., 2007). The energy of UV photons in the 200 – 300 nm range falls under the units of eV (e.g., 200 nm is around 6 eV). Taking into account that the bond energies of organic molecules at 298 K are also around units of eV per molecule (e.g., bond energy of methane at 298 K is 4.5 eV per molecule; Blanksby and Ellison, 2003), the irradiation of martian surface with highly energetic UV radiation will have a deleterious effect in the long term abundance of organic molecules on Mars.

In addition to direct photolysis of organic molecules by energetic UV photos, solar UV radiation also degrades organic molecules indirectly due to the formation of reactive oxygen species (ROS) in the martian environment. The UV radiation on Mars is energetic enough to dissociate water to give H⋅ and HO⋅ radicals (Benner et al.,

2000). In addition, the strong reactivity and dimerization of HO⋅ radicals can also generate strong oxidants such as hydrogen peroxide (H2O2) or other oxidants through combination with elements present in the martian surface (McDonald et al., 1998;

Benner et al., 2000). Meteorological conditions can also contribute to degradation of organic molecules as ROS such as hydrogen peroxide or even more potent superoxides may be generated in the atmosphere by dust sand storms (Atreya et al.,

2006). Radical species may be also formed by interaction of water frost with ultramafic silicate rock, such as pyroxene, pyrite or olivine (Huguenin et al., 1979;

Davilla et al., 2008). Similarly, Hurowitz et al. (2007) verified that H2O2 is produced from aqueous suspensions of labradorite, augite, and olivine grains.

Introduction

Solar UV radiation has an impact on the atmospheric and immediate martian surface environments (Figure 1.4). Studies have shown that UV radiation penetration may be as low as 100 nm into the mineral matrices. For instance, simulations with martian meteorites using UV radiation assumed that UV photon penetration in the minerals ranges between 20 and 130 nm (Keppler et al., 2012). UV penetration into the minerals on the martian surface may be actually higher, due to mixing of martian regolith by wind and other surface processes. The harmful effect of UV radiation and its potential to degrade organic molecules has been addressed several times. Past studies have shown that UV radiation on Mars’ surface is sufficiently high to preclude the accumulation of organic compounds supplied by meteoritic infall (Stoker and

Bullock, 1997). Moreover, it is also known that UV radiation induces the degradation of amino acids and carboxylic acids under simulated Mars conditions (Stoker and

Bullock, 1997; ten Kate et al., 2005; Shkrob et al., 2010; dos Santos et al., 2016).

1.5.1.2 - GCR and SEP

It is mostly assumed that GCRs are generated in diffusive shock acceleration in supernova remnants, which in turn diffuse to fill the whole galaxy and are then influenced by the heliosphere (Vainio et al., 2009). Approximately 85 % of the GCR spectrum is composed of protons (nuclei of hydrogen atoms). The remaining part of the GCR spectrum is constituted by 14 % of alpha particles (He nuclei) and a small fraction of other fully ionized atomic nuclei and electrons (Dartnell, 2011). SEPs are generated by flares and solar mass ejections and therefore correlated with solar activity (Dartnell, 2011). The flux of GCR is generally constant and much lower than that of the SEP, but GCR spectra may reach much higher energy levels than SEPs.

Chapter 1

For instance, SEP have an average flux of photons with an energy around 10 MeV, 5 while photons from GCR radiation may reach energies around 1020 eV at very low 8 flux (Dartnell, 2011).

Both GCR and SEPs interact with the atmosphere and may reach the martian surface if sufficiently energetic. The interaction of GCR and SEPs with the thin martian atmosphere and regolith generates secondary particles, such as neutrons and

γ-rays, which are scattered back out of the surface and contributes to the complex radiation environment on Mars (Dartnell, 2011; Hassler et al., 2014). SEP, due to their lower energy, generally interact and penetrate into the very first few centimeters of martian regolith such as depicted in Figure 1.4 (Kminek and Bada, 2006; Pavlov et al., 2012). GCR, on the other hand, due to their high energies, can penetrate several meters into the martian surface, which is also illustrated in Figure 1.4 (Kminek and

Bada, 2006; Pavlov et al., 2012; Hassler et al., 2014).

Taking into account that the bond energies of organic molecules at 298 K are around a few units of eV per molecule (e.g., bond energy of methane at 298 K is 4.5 eV per molecule; Blanksby and Ellison, 2003), the irradiation of martian surface with

GCR and SEPs, which have energies several order of magnitude higher than eV units, will also impact the abundance of organic molecules on the martian surface. As a matter of fact, Kminek and Bada (2006) suggested that ionizing radiation from space severely affects the long-term survival of amino acids present in the first few meters of martian subsurface. The authors presume that amino acids can survive up to 3 billion years at depths lower than 2 meters, where radiation levels, mainly originated by radioactive decay, are low. Kminek and Bada (2006) verified as well that the

Introduction

radiolysis of amino acids increased linearly with molecular weight. Similar results were obtained by Pavlov et al. (2012), who also verified the increase of degradation induced by ionizing radiation with increasing molecular weight. In the simulations of

Pavlov et al. (2012), it was estimated that organic molecules with molecular weights around 100 units may be able to survive in the shallow subsurface of Mars up to approximately a billion years.

1.5.2 - Mineral protection

The mineral composition of a soil also has a key role regarding the shielding ability to protect organic molecules from radiation. Sulfate minerals, which were first detected in 2004 by NASA’s rover Opportunity (Klingelhöfer et al., 2004), are known to provide effective shielding from harmful UV radiation. Aubrey et al. (2006) suggested that amino acids present in terrestrial soils rich in sulfate minerals, such as gypsum and jarosite, may be preserved for billions of years (Aubrey et al. 2006).

Sulfate minerals, for instance, are also known to protect microscopic life forms in extreme environments on Earth, as it was observed by Hughes and Lawley (2003) studying microbial endolithic communities living within gypsum crusts in Antarctica.

Hughes and Lawley (2003) verified that Antarctic gypsum crusts effectively shielded

UV radiation below 400 nm.

Clay minerals are also known to provide protection from UV radiation.

Phyllosilicates usually result from the alteration of primary silicates in the presence of water. Clay minerals were first detected in the Mawrth Vallis region by the OMEGA instrument onboard the ESA’s Mars Express (Poulet et al., 2005), and kaolinite was detected by CRISM onboard the NASA’s Mars Reconnaissance Orbiter (McKeown et

Chapter 1 al., 2009). More recently, NASA’s rover Curiosity made the first drill ever on another 6 planet at Yellowknife Bay, finding new evidence of clays and sulfate minerals. The 0 analyses of the drilled samples showed a significant presence of Fe-Mg-smectites, believed to be formed within an ancient lake bed during early diagenesis, and also a cross-cutting set of sulfate-filled veins in the rock, which were formed during post lithification processes (Grotzinger et al., 2015). Hoang-Minh et al. (2010) verified that clays show potential for UV protection through absorption or reflection of UV radiation. Results obtained by Hoang-Minh et al. (2010) also suggest that the protection effect of the clays depends on iron content and whether the clays are expandable or not.

The ability of sulfate and clay minerals to protect organic molecules is highly significant since these evaporite minerals are often deposited along with organic material (Mancinelli et al., 2004). For instance, the abundance of sulfate minerals in a soil also appears to be correlated with its amino acids content as it was demonstrated by Martins et al. (2011), who analyzed soils from the Mars Desert Research Station

(MDRS) in Utah, USA. In addition, clays are long known to be related with the retention of organic molecules in the environment (e.g., Hedges, 1977). This is particularly relevant for the case of clays of the smectite group (i.e., expandable clays), which have particularly large surface areas and the ability to adsorb organic molecules not only in the external mineral faces, but also in the space between the interlayers (Mortland, 1970; Raussel-Colom and Serratosa, 1987).

Another important reason to target sulfate and clay minerals in the search for organic molecules is the fact that their presence is often related with habitable environments. In the case of sulfate minerals detected by NASA’s Opportunity rover,

Introduction

the presence of jarosite was indicative of a past environment that contained an acidic evaporite water system (Klingelhöfer et al., 2004; Squyres et al., 2004). On the other hand, the detection of clays on Mars is of the utmost importance because clay formation from water alteration does not require acidic environments. For example, the presence of substantial quantities of saponitic smectite clays recently found by

Curiosity was likely formed by aqueous alteration of olivine in an environments that could have had supported life (Grotzinger et al., 2014; Vaniman et al., 2014). Hence, sulfate and clay minerals, despite both being good indicators of habitable environments likely to accumulate and preserve organic molecules may eventually be considered as products of different climatic conditions and representative of different martian eras (Poulet et al., 2005).

Despite giving hints about past water activity, martian soils rich in clay minerals may pose a challenge in the detection of organic molecules or molecular signatures of life. It has been demonstrated that clays may impair the ability to perform extractions because they strongly adsorb organic molecules, including DNA

(Mortland, 1970; Paget et al., 1992; Direito et al., 2012; Saeki and Kunito, 2010).

Similar results were obtained by Martins et al. (2011), which verified that the extraction of amino acids from soils from MDRS in Utah was not successful in clay rich mineral matrices. Therefore, further studies are needed in order to optimize extraction methods for organic molecules from clay minerals for future space missions to Mars (Ehrenfreund et al., 2011).

Chapter 1

1.6 Signatures of life 6 2

The most usual approach to look for signatures of life on Mars is based on the search for fossils or identification of the basic molecules that sustain life, usually called “biosignatures” (McKay, 2011).

Some types of molecules - such as nucleobases, proteins, amino acids, hydrocarbons and carboxylic acids – have been tagged as priority targets for identification of alien life (Parnell et al., 2007). This thesis is based on the study of amino acids as the main biosignatures of interest. One of the reasons behind the choice of amino acid as priority targets for life detection is that they are the building blocks of essential macromolecules called proteins. For instance, proteins are the major class of biomolecules present in E. coli’s dry weight (around 55 %), compared with nucleic acids (24 %), lipids (9 %) and other types of molecules (12 %)

(Neidhardt et al., 1996). Also, as it was discussed previously in section 1.3.1.2, amino acids may be preserved in the martian environment for long geological periods of time (e.g., Kminek and Bada, 2006), turning these molecules into useful targets for life-detection missions.

Introduction

Figure 1.5: Schematic representation of two enantiomers of a generic -amino acid.

One of the main features of most amino acids is that they have a chiral centre at the -carbon and may exist, therefore, in the form of two optic isomers that are the mirror images of each other, but not superimposable (Figure 1.5). Isomers are molecules that share the same chemical formula but have a distinct spatial and structural arrangement. Optic isomers are also known as enantiomers.

In the case of chiral amino acids the enantiomers are denominated either by L, for levorotatory, or D, for dextrorotatory, forms. The simplest amino acid, glycine, for instance, is not a chiral molecule because it does not have a chiral centre in the - carbon. On Earth, all living organisms use the L-enantiomers. L-amino acids from biological origin that are released into geological samples after death suffer racemization (i.e., conversion of the L- enantiomers into to equal amounts of D- and

L- forms, racemic mixture) through long geological periods of time (Martins, 2011).

This means that mixtures of amino acids containing L- and D- enantiomers but exhibiting a L-enantiomeric excess may be related to fossils (i.e., indicative of extinct

Chapter 1 life forms). On the other hand, abiotic synthesis of amino acids yields a racemic 6 mixture, with a ratio of D and L forms around 1. The racemization process is much 4 slower on Mars when compared to Earth, due to the aridity and low temperatures prevalent in the martian environment (Aubrey et al., 2006). Owing to this enantiomeric excess preservation potential on Mars, analysis of the enantiomeric excesses of putative martian amino acids may also be useful for future life searching missions.

Unambiguous identification of martian organic molecules associated with life as we know it would not be, per se, an unambiguous identification of life. Even if chirality of amino acids may be a useful feature for future life detection missions on the Red Planet, it is known that organic compounds, including amino acids, are delivered to the martian surface by interplanetary dust particles (IDPs) and meteorites every year (Chyba and Sagan, 1992; Zent and McKay, 1994; Flynn, 1996; Bland and

Smith, 2000). Even if most non-protein chiral amino acids present in meteorites are racemic, enantiomeric excesses up to 18.5 % were reported in meteorites (Pizzarello et al., 2003; Glavin and Dworkin, 2009; Martins and Sephton, 2009). Moreover, on

Earth, life forms use predominantly 20 amino acids. There is an increased variety of amino acids associated with abiotic origins. More than 80 different amino acids have been detected in the Murchison meteorite, including rare amino acids on Earth such as isovaline and α-aminoisobutyric acid (Martins, 2011).

Introduction

1.7 Mars Soil Analogues

Space missions are enormous endeavors that require large investments of time and money. Therefore, careful and extensive preparation is needed in order to increase the chances of success, guarantee functionality of all equipment and validity of experimental procedures.

Testing protocols of future space missions aiming for Mars exploration have an inconvenience related to the lack of substantial amount of available martian samples on Earth to use. martian meteorites are the only martian material available on

Earth and, at the time of writing (May 2017), there was a total of 190 recognized specimens of martian meteorites, which is a very limited amount when compared with the many thousands meteorites that have been recovered on Earth until now

(information available in the Meteoritical Bulletin Database, The Meteoritical

Society). On top of the issue surrounding the scarcity of martian meteorites, it is also known that these meteorites are prone to rapid amino acid contamination after direct exposure to the terrestrial environment, as was verified by Glavin et al. (1999) after analyses of the Nakhla meteorite. Therefore, within the scope of a space mission to

Mars, and due to the poor availability of adequate martian samples, the use of terrestrial soils that mimic the martian’s regolith properties (i.e. Mars soil analogues) is of the utmost importance. Mars soil analogues provide a preview of the environment that spacecraft will work on and they can be classified based on the martian properties they best mimic (Marlow et al., 2008; Marlow et al., 2011).

Chapter 1

On Earth there are several areas containing environmental, geological and 6 geochemical features that resemble Mars and that are, therefore, useful for testing and 6 the development of future spacecraft to the Red Planet. Some of these areas include hot deserts such as Arequipa, Atacama and Mojave deserts or cold deserts such as

Antarctica dry valleys (Figure 1.6). Locations such as Arequipa and Atacama serve as good organic martian analogues due to their mineralogy and low organic content

(Marlow et al., 2008). A similar set of geochemical features may be found in the Mars

Desert Research Station in Utah Desert, USA. Results from Martins et al. (2011) and

Kotler et al. (2011) concluded that samples from the Utah Desert are good Mars analogues due to their low organic content and an adequate mineralogical profile. The environment found in the Mojave Desert is, for instance, used primarily as a mechanical analogue which allows ground testing of rovers and respective landing systems (Marlow et al., 2008). The Mojave Desert offers a variety of landforms and evidence of geological processes relevant to martian highlands known to contain paleolake deposits and evaporites (Farr, 2004).

The dry valleys of Antarctica are one of the harshest environments to be found on Earth. This habitat shares several environmental constraints for life with the Red

Planet, namely: the freezing temperatures, desiccation, high radiation levels (such as

UV) and it is also the only known terrestrial location with the occurrence of dry permafrost, which also occurs near the martian poles (Aerts et al., 2014).

Other Mars soil analogues include Salten Skov in Denmark, which is known to be a region containing red coloured sediments that have high concentrations of iron oxides such as hematite, maghemite and goethite (Nornberg, 2004). Salten Skov is mostly used as a magnetic and chemical analogue, useful to study dust related

Introduction

processes on the martian surface (Nornberg et al., 2009). Salten Skov offers otherwise a poor match in terms of bacterial concentrations, which are too high when compared, for example, with deserts analogues (Hansen et al., 2005).

The volcanic deposits found in Hawaii are good analogues to high albedo regions on Mars (Singer,1982). Hawaii offers the opportunity to study eruption and emplacement of lava flows and traversability studies for Mars rovers (Farr, 2004).

For instance, weathered volcanic ashes from the Pu'u Nene cinder cone on Hawaii have been used for JSC-1, which is a developed Mars soil simulant (Perko et al.,

2006). Rio Tinto, in Spain, is one of the most studied Mars analogues. Its particular relevance lies in the fact that it is an extreme environment dominated by acidic conditions, high concentration of heavy metals, an active and widespread iron-cycle and the sulphate chemistry provides an example of a natural setting to study the development and active deposition of certain minerals found in martian soil by MER

Opportunity, such as jarosite and hematite (Fernández-Remolar et al.,

2005; Klingelhöfer et al., 2004).

The hypersaline lakes of Western Australia are also considered valuable analogues for ancient environments on Mars (Benison and Bowen, 2006). The hypersaline lakes are characterized by a mineral assemblage that resembles Mars, with the ocurrence of halite, gypsum, kaolinite, iron oxides, jarosite, and alunite

(Benison et al., 2007). Findings from Benison and Bowen (2006) and Benison et al.,

(2007) also suggest that the lacustrine sediments closely mimic the depositional and diagenetic facies and the formation of hematite concretions found in several martian outcrops, such as the Burns Formation explored by MER Opportunity (Grotzinger et al., 2005).

Chapter 1

6 8

The use of these and other Mars soil analogues is fundamental not only to develop and prepare space missions, but also to build a common knowledge that will help the interpretation of future Mars exploration missions results. The use of Mars soil analogues has some limitations, mostly due to the fact that different analogues match different aspects of the martian regolith and environment. However, the simultaneous use of multiple Mars soil analogues gives the scientific community the opportunity to study and simulate a variety of different aspects of Mars and, therefore, to have a close preview of what future missions may be faced with.

Introduction

1.8 Project aim and dissertation outline

In the next few years, there are several missions planned to explore Mars, including two life detection missions. One is the European Space Agency-Roscosmos

ExoMars mission and another one is NASA 2020 mission. Both missions will include rovers set to be launched in July 2020 and designed to explore the martian surface.

These two rovers will be the first spacecraft after NASA’s Viking landers to actively search for signs of extant or extinct life on the Red Planet (Mustard et al., 2013; Vago et al., 2013). Due to the potential of finding preserved organic molecules in the martian subsurface, ExoMars rover will have the capability to drill to depths up to 2 metres in order to collect and analyse samples that were shielded from the harsh conditions prevailing on the surface (Vago et al., 2013).

Careful planning is of the utmost importance for these kinds of endeavors. In light of this, this dissertation aims to: 1) contribute to the field of astrobiology; 2) find out what are the best locations to find organic signatures of life on Mars and land- based future life-searching missions; 3) study the influence of mineralogy on the preservation of biosignatures under simulated Mars conditions and 4) help in the development and planning of future space missions to Mars as well as share scientific data that will help in the interpretation of these missions. These goals will be attained by providing scientific data obtained from mineralogical, microbiological and amino acid analyses of two Mars soil analogues: Rio Tinto and the hypersaline lakes of the

Yilgarn Craton, in Western Australia, and studying the evolution of amino acids spiked onto mineral standards under simulated Mars conditions.

Chapter 1

Rio Tinto is known by its inorganic geochemistry, which can provide a good 7 model for the processes behind the formation of Meridiani Planum’s outcrops, namely 0 the formation of iron oxides which are ubiquitous on Mars. Rio Tinto may also serve as an analogue of putative present sub-surface environments where liquid water and sulfate deposits may be found.

The hypersaline lakes of the Yilgarn Craton, in Western Australia, are studied here due to the fact that: 1) they serve as analogues for past martian environments where shallow liquid water bodies may have existed and 2) they also serve as good mineralogical analogues to martian locations containing evaporites.

It is also known that a soil’s mineralogical composition is a critical aspect for life searching missions. Therefore, in addition to the study of Mars soil analogues, this dissertation also presents data on the preservation of biosignatures (amino acids) adsorbed onto Mars relevant minerals under simulated Mars conditions. The data obtained from these simulations allows the identification of which minerals are the most suited to preserve biosignatures of putative extant/extinct martian life.

In terms of dissertation structure, Chapter 2 provides the methodological details about the practical work carried out. This includes a description and origin of

Mars soil analogues samples used in this work, as well as details about field work in

Western Australia and the basic theoretical concepts behind the geochemical and analytical methods used in the laboratory.

The mineralogical, microbiological and amino acid analyses of Rio Tinto sediments are described and discussed together in Chapter 3 and those of hypersaline lakes of the Yilgarn Craton, in Western Australia are separated in two

Introduction

chapters. The mineralogy of these hypersaline lakes is explored in Chapter 4 whereas the microbiological and amino acid analyses are explored in Chapter 5. The large number of samples collected from the hypersaline lakes in Western Australia, almost the triple than those collected in Rio Tinto, allowed more in-depth study to be performed, warranting chapters devoted to separate elements of the research. Also, unlike the case of the Rio Tinto sample set, samples from the hypersaline lakes in the

Yilgarn Craton were collected during a field-trip carried out during the doctoral studies, resulting in field observations and sample collection descriptions. Therefore, in order to help in the interpretation of the different set of results and environmental context of the samples, the mineralogy of these hypersaline lakes is presented and discussed separately from the microbiological and amino acid analyses.

The work based on the Mars chamber simulations is addressed in Chapter 6.

The Mars chamber simulations were performed in order to study which minerals are best suited to preserve organic signatures of life under simulated Mars conditions.

Chapter 6 is based on the paper “Influence of mineralogy on the preservations of amino acids under simulated Mars conditions”, published during the PhD by dos

Santos et al. (2016).

Finally, the main conclusions of this dissertation and suggestions for further work are explored in Chapter 7.

Chapter 1

7 2

Chapter 2

Methods Chapter 2

2.1 Introduction

Astrobiology is a multidisciplinary science. The research on which this thesis is based was carried out not only in the field (in order to collect geological samples), but also in a variety of laboratories where protocols of chemistry, geology and biology were used. Therefore, a deep understanding of the theoretical concepts behind the methods used during the research is of the utmost importance in order to acquire results with good quality and ensure an adequate interpretation. This chapter not only provides the details regarding the collection/acquisition of samples that were used in this work, but also provides a general theoretical overview of the methods used in the laboratory experiments. Specific details about methodology and experimental conditions for each set of analyses are provided instead in the relevant experimental methods section of each chapter.

2.2 Samples and field work

In this dissertation samples from two different Mars soil analogues were used:

Rio Tinto (Spain) and hypersaline ephemeral lakes from the Yilgarn Craton (Western

Australia). These samples were obtained and collected in order to perform analysis of their biosignature content, mineralogical composition and profile of their microbial communities. An additional set of samples was also used, which will be referred to in this chapter, as mineral standards. This set of mineral standards was used in this dissertation to study the influence of mineralogy on the preservation of amino acids under simulated Mars conditions.

Methods

2.2.1 – Rio Tinto

The recent discovery of minerals suggesting past water activity on Mars and their potential to preserve organics under harsh conditions require good mineralogical analogues. In order to understand what geological events lead to the formation of martian minerals relevant for life detection missions, one must study in detail what are the processes behind the formation of the same minerals on Earth.

NASA’s Opportunity rover confirmed the presence of outcrops rich in hematite and jarosite at the Meridiani Planum (Klingelhöfer et al., 2004). The occurrence of these minerals has been interpreted as the result of the evaporation of an acidic water system formed by oxidation of iron sulphides (Klingelhöfer et al., 2004). On Earth, iron sulphates like jarosite are most usually found near acid mine drainages, owing to weathering and oxidation of sulphide ore deposits (Blowes et al., 1991).

Rio Tinto, in southern Spain, rises in the core of the Iberian Pyritic Belt, in the south-western region of the Iberian Peninsula. Its geochemistry is dominated by the weathering and oxidation of massive and extensive sulphide ore deposits, which results in the occurrence of acidified headwaters, owing to sulphuric acid formation and leaching of heavy metals (Bigham and Nordstrom 2000, Fernández-Remolar et al., 2005).

The current acid-sulfate chemistry found in Rio Tinto provides a helpful model for the development of sulfates and iron oxides found martian soils (Marlow et al.,

2008). In addition, Rio Tinto was selected as an appropriate analogue to study the influence of the Mars-like inorganic geochemistry and mineralogy in the detection of biosignatures and microbial communities.

Chapter 2

2.2.1.1 – Sample collection

Rio Tinto samples used in this work were collected during a field trip that occurred before the start of this project. Sample collection occurred near the source of the Rio Tinto river in an area called Annabel’s garden, located approximately 5 km north of the town of Nerva, close to Embalse de Tumbanales (GPS coordinates:

37°43'31.0"N 6°33'34.5"W, Figure 2.1).

The three-day fieldtrip by the Coordination Action for Research on life in

Extreme Environments group (CAREX), an FP7 EC programme, which was coordinated by the Centro de Astrobiologia (INTA-CAB) was held on the 21st-23rd of

September 2009, and described by Gómez et al. (2011). The samples were selected to cover a range of different environments that might resemble Mars and to obtain an insight into the biological, environmental and mineralogical heterogeneity and likely variation in sediment properties. Samples were collected within an approximate range of 150 meters and the area contained significant amounts of red, brown and yellow precipitates resulting from pyrite oxidation together with evidence of green and brown algal mats (Gómez et al., 2011).

General information about each sample and pictures are provided in Table 1.1 and Figure 2.2, respectively. Samples were named Rio Tinto 1 (abbreviated to RT1) to Rio Tinto 10 (RT10). There is a correspondence (indicated in Table 1) with some samples described by Gómez et al., (2011).

Methods

Chapter 2

Table 2.1: General information about the sediment samples collected during the three days CAREX field campaign at Annabel’s garden area, located in Rio Tinto’s river source. Sample Location and sample description Sample name correspondence with Gómez et al. 2011 RT1 Wet, dark brown/red compact clay sediment collected SD#11 clay from a drying pond containing mudcracks (Linx’ Pond) hexagons

RT2 Grey surface sediment from “Marte Planitia”. Pyrite fine a sand with particles below < 0.2 mm

RT3 Medium to coarse grained brown/grey sediment with a a fraction of silt. Collected close to Jana’s Stream RT4 Dark grey/yellow surface granules collected near stream SD#13-CS shore shore. Particle size above 0.2 mm. Collected downstream stream mud from red crust sample RT7 (see below) RT5 Gark grey, gravel-like sediment collected at the same a location as RT4 but from 5 centimetres below the surface. Particle size between 2 and 5 mm. RT6 Fine to medium light grey/yellow sand, crystal-like a shaped sediments from Annabel’s garden. Particle size around 2 mm. RT7 Orange/red, easily breakable, iron oxide like crust found a in Annabel’s garden stream. Collected upstream from sample RT4 and RT5. RT8 Yellow popcorn-like texture, sulfate-like crusts, coarse a grained sediments from Annabel’s garden. RT9 Red/grey, fine to medium grained sediments, easily #7-SD-red breakable upon collection, collected after dam in globule on clay Annabel’s garden RT10 Fine angular gravel. Yellow sample collected before #1-SD-PS-IF stream at Annabel’s garden. Identified on-site by XRD Jarosite as hydronium jarosite and identified by RAMAN as Jarosite (Gómez et al. 2011) a- No correspondence with Gómez et al. 2011.

Methods

Chapter 2

2.2.2 - Hypersaline ephemeral lakes from the Yilgarn Craton (Western Australia)

Hypersaline ephemeral lakes are a typical feature and consequence of water accumulation in low rainfall, arid environments. Several hundred of these hypersaline lakes are present in Western Australia within and around the Yilgarn Craton, which is a vast region in the south-west part of Western Australia and one of the largest

Archaean crusts in the world (De Laeter et al., 1981).

The hypersaline lacustrine environments present in the Yilgarn Craton are usually associated with limited meteoritic and fluvial input by localised drainage within closed basins. The accumulation of run-offs during seasonal rainfall events within enclosed depressions, followed by evaporation during extended dry seasons, results in the occurrence of acid or alkaline, shallow hypersaline lakes which can precipitate halite, gypsum, carbonate, iron hydroxides, iron oxides and/or jarosite

(Benison and Bowen, 2006). These minerals have also been detected on Mars, also including rarer chloride salts and carbonates (for a detailed review see Chevrier and

Mathe, 2007; Ehlmann and Edwards, 2014). For this reason, the hypersaline lakes have been designated as a good mineralogical analogue to Mars (Benison and Bowen,

2006).

In addition to the mineralogical assemblage, the geological features present in the ephemeral lakes from the Yilgarn Craton were characterised as strikingly similar to the Burns formation at Meridiani Planum by Benison and Bowen (2006). The authors proposed that the ephemeral acid saline lakes and adjacent environments in southern

Western Australia may provide the best known Earth analogue for past environments

Methods

on Mars and that similar lacustrine systems may have been present in the Red Planet

(Benison and Bowen, 2006).

2.2.2.1 – Field trip observations

A field trip to perform field

observations and collect

samples from the hypersaline

lakes of Western Australia

took place from the 11th until

the 16th of August 2013,

during the wet season and

austral winter. During the

field trip eight ephemeral

hypersaline lakes were

visited: Lake Brown, Lake

Baladjie, Lake Deborah West,

Lake Victoria Rock, Lake Figure 2.3: Map showing the approximate locations of the lakes visited during the fieldtrip to the Yilgarn Craton Lefroy, Lake Dundas, Lake region. a) Map of Australia; b) Map of Western Australia and the Yilgarn Craton (1- Lake Brown, 2- Lake Cowan and Lake Gilmore. A Baladjie, 3- Lake Deborah West, 4- Lake Victoria Rock, 5- Lake Lefroy, 6- Lake Cowan, 7- Lake Dundas and 8- map showing the locations of Lake Gilmore). the lakes within the Yilgarn

Craton region can be found in Figure 2.3. General photo views of the eight lakes visited during the fieldtrip are provided in Figure 2.4.

Transient and sometimes heavy localized rainfall occurred during and prior to the period that the field trip took place, resulting in large differences between lakes.

Chapter 2

Methods

During the field observations, several common sedimentary facies were identified by key sedimentary structures. The following facies were all observed in more than one saline lake: (1) gypsum-rich sand dunes, (2) mudflats/sand-flats and (3) salt-flats.

Gypsum-rich sand dunes are ubiquitous at all studied lakes, mostly concentrated in the down-wind lacustrine shore, partly vegetated by small bushes and thus somewhat stabilised against erosion (Figure 2.5A). A high variability in grain sizes was observed (5 mm down to 0.75 mm). Moreover, the presence of other clastic grains such as quartz, micas and traces of iron oxides suggests a strong influence of the surrounding bedrock in the sand grain composition. The presence of gypsum sand dunes means that gypsum precipitated in the lakes and was exposed, eroded and transported by wind. This agrees with field observation reported by Benison and

Bowen (2006), which found sub-surface primary gypsum-layers at Lake Brown.

Gypsum was also found to be the dominating precipitating mineral in other lakes in the Yilgarn Craton, including Lake Lefroy (Clark, 1994; Benison and Bowen, 2007).

Mudflats were found to be ubiquitous around the margins of lakes and within interdune regions on the lacustrine surface. The mudflats observed in the field included linguoid ripple mudflats, sinuous ripple mudflats, and algal mudflats. Large extensions of the lakes’ surface were found to be covered with linguoid ripple mudflats. These generally had wavelengths around 3-4 cm, low amplitudes of below

5 mm, and associated with fine-grained halite and/or gypsum found on the surface.

Sinuous ripple mudflats were observed in Lake Baladjie, Lake Dundas and Lake

Lefroy and were long crested bifurcating ripples with low amplitudes (<5 mm) and wavelengths of 15-20 cm. The sinuous ripples in Lake Baladjie were the most

Chapter 2

developed and preserved ones, with some areas containing parallel sinuous ripples being around tens of meters long. The sinuous ripples were most likely formed by transient longitudinal shallow currents driven by high speed winds. Mudcracks were often present in severely desiccated areas of the lacustrine surface (Figure 2.5B)

Methods

Some areas of the lakes showed evidence of folds and blisters in the surface, suggesting that the area was in fact an algal mudflat. The algal mudflats presented themselves as irregular surfaces, sporadically containing elongated and arcuate structures with rounded asymmetric profiles (Figure 2.5C). The formation of folds in these algal mudflats is believed to be caused by shearing of the algal mat under the influence of strong winds.

On some occasions, some folded areas in the algal mats also exhibited abundant hemispherical blisters. The presence of blisters was not limited to the algal mat areas, with some blisters being found in association with mudflat sections containing linguoid ripples (Figure 2.5D). Another feature found in the algal mudflats was the presence of algal surface deposits within the upper few millimetres of the sediment layer. Usually, the algal surface deposits occurred as ochre, green-ochre to brown masses with a folded surface texture composed of filamentous materials. These deposits were most likely formed by stranding of surface floating algae. Overall, the lakes presented several morphological sedimentary features which were interpreted as presence of microbial organisms with folding, blisters, raised rim polygons and presence of bubbles in the surface (Figure 2.5E) testifying to benthic cyanobacteria mats and blisters.

Saltflats were observed at Lake Baladjie, with the occurrence of thick (1-4 cm) halite-rich crusts just lake below the water line. Halite precipitation was actively occurring during the field observations (Figure 2.5F). The presence of salt crusts at the bottom of the water layer implies that these structures were being formed by crystallisation from dense brine. This dense brine was concentrated by evaporation, along the floor of the lake. The thickness of the salt crust was found to increase with

Chapter 2

the distance to the shore. The crusts formed elongate lens-shaped areas of white compact halite in a matrix of ochre-halite, containing inclusions of iron-rich sediment

(Figure 2.5F).

Field observations also revealed that the lacustrine sediments of Lakes Brown,

Baladjie and Gilmore were surrounded mostly by Archaean undifferentiated felsic/intermediate rocks combined with locally metamorphosed, foliated gneissic intrusions. In Lake Brown, bedrock was also found to be partially exposed as high grade metamorphic rocks. The bedrock surrounding Lake Baladjie’s sampling sites also included Archaean mafic intrusive rocks and extensive sections of high magnesium volcanic outcrops. In Lake Deborah West, on the other hand, sampling sites were mostly surrounded by extrusive, igneous, magnesium rich mafic rocks.

Nearby bedrock outcrops also included Archaean undifferentiated felsic/intermediate rocks and locally metamorphosed, foliated gneissic intrusions.

2.2.2.2 – Sample collection

A total of 50 samples were collected across the eight lakes that were visited during the fieldwork. In this thesis only the samples from Lake Brown, Lake Baladjie,

Lake Deborah West and Lake Gilmore were analysed for mineralogy, amino acid abundance and microbial community profile. Table 2.2 provides sampling details, including GPS locations, and a brief characterization of the selected samples for study.

The same information for the remaining samples collected during the field trip in Lake

Victoria Rock, Lake Lefroy, Lake Cowan and Lake Dundas may be found in Annex 1.

Methods

Figure 2.6 and Figure 2.7 show Google Maps and Google Earth images illustrating where the samples used in this study were collected in the four hypersaline lakes. In order to verify how microbial communities and amino acid abundances vary with depth, surface and 30 cm sub-surface samples were collected at each sampling site. Generally, samples with odd numbers were sampled at the surface whereas even numbers means they were collected 30 cm below. Exception to this naming procedure include: sample LB7, which was collected at 50 cm below the surface; sample LVR6, which was collected 10 cm below the surface; sample LD2, which was collected in the surface; sample LD3, which was collected 30 cm below the surface and sample LD4, which was sampled from the surface of Lake Dundas (Table 2.2 and Annex 1).

At the time of sampling the lakes contained some sections of their surface partially covered by shallow water, likely provided by the significant rainfall observed during the month of July 2013, which in some cases was the wettest month of the year1. Rainfall measurement data from the closest open meteorological stations show that during the month of July, regions surrounding Lake Brown, Lake Baladjie, Lake

Deborah West and Lake Gilmore received approximately 48.7 mm, 30.1 mm,

29.4 mm and 53.4 mm of rainfall, respectively (Australian Bureau of Meteorology).

Sediment pH in samples was measured using a Gardman soil pH meter, and are shown in Table 2.2. The average soil pH values measured for Lake Brown, Lake

Baladjie, Lake Deborah West and Lake Gilmore were 5.3, 6.2, 6.9 and 6.1, respectively. Air temperatures during collection ranged from 13 up to 25 °C with

1 Note: The fieldtrip to the hypersaline lakes was organised for July - and the wet season - due to calendar commitments of the team members.

Chapter 2

significant differences due to cloud cover and wind chill. Wind speed was approximately 10 km/h.

In order to prevent contamination of the samples, sampling in the field was carried out using spatulas that were previously sterilized by wrapping in aluminium foil and heated to 500 °C for at least three hours. The samples were stored in 50 mL sterile, DNA free falcons and bags.

Methods

Lake Deborah West Lake Brown (LB) Lake Baladjie (LBa) Lake Gilmore (LG) (LDW)

LB1 LB2 LB3 LB4 LB5 LB6 LB7 LBa1 LBa2 LBa3 LBa4 LBa5 LBa6 LBa7 LBa8 LDW1 LDW2 LDW3 LDW4 LG1 LG2 LG3 LG4 LG5 LG6 LG7 LG8 Sample name a and site S Sub S Sub S Sub Sub (50cm) S Sub S Sub S Sub S Sub S Sub S Sub S Sub S Sub S Sub S Sub

S-31.12640º S-31.12675º S-31.1264º S-31.12645º S-30.96025º S-30.96023º S-30.96010º S-30.95957º S-30.81946º S-30.81847º S-32.60969º S-32.60979º S-32.61026º S-32.61033º E118.3015º E118.30164º E118.30250º E118.30254º E118.93240º E118.93245º E118.93274º E118.93300º E118.97868º E118.9793º E121.55947º E121.56001º E121.5615º GPS E121.56278º coordinates Elevation: Elevation: Elevation: Elevation: Elevation: Elevation: Elevation: Elevation: Elevation: Elevation: Elevation: Elevation: Elevation: Elevation: 235 m 283 m 283 m 284 m 284 m 381 m 381 m 323 m 325 m 322 m 322 m 234 m 237 m 235 m

Soil pH 5.5 5.5 4.8 5.2 5.2 5.2 6.0 5.6 5.0 6.2 6.9 6.0 6.9 6.9 6.1 6.9 6.9 6.9 6.9 6.0 6.0 6.0 6.0 6.0 6.0 6.2 6.9

tals

Texture and Colour organics. Dark Brown. organics. Nuddy, brown Sandy. Brown. Sandy Sandy and brown Sandy and brown Sandy Sandy and creamy. Sandy and creamy. Muddy Muddy and creamy Sandy Sandy and red/brown Sandy. Cream/brown. Muddy Muddy and red/brown Sandy Sandy and dark brown Sandy Sandy and dark brown. Sandy and dark brown. Muddy Muddy and dark brown Sandy. Creamy and Red. Muddy/sandy. Red/brown. Muddy/sandy. Sandy, big Sandy, crystals, red/brownbig Muddy, red/brown Muddy, with red/brown crystals Red/brown Red/brown mud. Gypsum crystals Red/brown mud. Gypsum crystals Red/brown mud. Gypsum crys Red/brown mud. Gypsum crystals Sandy Sandy with Sandy with Dark Brown. organics. Sandy, big Sandy, crystals. Green and big grey. Sandy and ochre. Crystals Sandy up and to Crystals ochre. 0.5cm Sandy Sandy with Brown and organics. black. aS- Samples collected at surface. Sub- Samples from 30 cm subsurface, unless stated otherwise. Methods

2.2.3 – Mineral standards

Mars crust is predominantly basaltic with regionally variable quantities of plagioclase, pyroxene, and olivine crust. In addition, martian crust composition is similar to terrestrial oceanic crust, which is magnesium-rich (Ehlmann and Edwards,

2014). Eleven mineral samples were selected for the Mars chamber simulation work presented in Chapter 6.

Augite and enstatite were chosen as representative pyroxenes specimens, with enstatite representing the magnesium-rich mineral of the pyroxene group. The minerals goethite and hematite were selected as relevant martian iron oxide minerals.

Goethite and hematite are often found in association on Earth (Schwertmann, 1985).

Similar association was found on Mars when the Mössbauer spectrometer on-board

MER Spirit identified goethite associated with hematite in some altered outcrops in

Columbia Hills (Klingelhöfer et al., 2005; Morris et al., 2006). Gypsum and jarosite were the minerals from the sulfates group that were chosen to perform the simulations.

Sulphur is a key element in the martian surface and its abundance in the martian crust is significantly higher than that found on Earth’s crust (Chevrier and Mathe, 2007).

Gypsum is known to occur on Mars in dunes and interdunes systems found in and around the northern plains (Ehlmann and Edwards, 2014). The ferric sulfate jarosite was detected by the MER Opportunity at Meridiani Planum’s Eagle Crater

(Klingelhöfer et al., 2004). Jarosite formation is thus thought to require a wet, oxidizing and acidic environment that may be habitable. This mineral is a characteristic phase in acid mine drainage environments and it is associated with

Chapter 2

oxidation of sulphide minerals and alteration of volcanic rocks by acidic, sulphur-rich fluids near volcanic vents (Madden et al., 2004).

Labradorite was chosen as a representative specimen of the feldspar group.

Feldspars are known to be one of the dominant minerals in most of the southern highlands (Ehlmann and Edwards, 2014). Forsterite was selected as the representative mineral from the olivine group, as magnesium rich olivines are common in Mars.

Olivine compositions range from Fe-rich to Mg-rich (∼Fo40–Fo90) and have been globally mapped in the Red Planet, with an increased occurrence in the ancient southern highlands (Ody et al., 2013).

The phyllosilicates montmorillonite, nontronite and saponite were chosen as relevant clay minerals from the smectite group in the martian environment. In the martian crust, Fe/Mg smectites such as nontronite and saponite are often overlain by

Al smectites (e.g., montmorillonite; Ehlmann and Edwards, 2014). According to

Ehlmann and Edwards (2014), the deposition of Al phyllosilicates on top of Fe/Mg smectites most likely results from more acidic alteration and/or enhanced leaching in more recent periods of Mars history (late Noachian–early Hesperian) that affected the uppermost crust. Basaltic lava was also used in the Mars chamber simulations as a material representative of general basaltic environments that are prevalent on Mars

(Ehlmann and Edwards, 2014).

All the standard minerals used in the Mars chamber simulations were analysed by X-ray diffraction at the Natural History Museum (London, UK) in order to evaluate their purity. Specific details about the mineral standard samples and X-ray diffraction results obtained with them can be found in Chapter 6.

Methods

2.3 Methods

2.3.1 - Gas chromatography–mass spectrometry

Gas chromatography–mass spectrometry is a technique that combines a gas chromatograph (GC) with a mass spectrometer (MS) (Figure 2.8). This technique was used for all quantitative analysis of amino acids in all samples mentioned in this thesis.

The gas chromatograph allows separation and resolution of organic compounds from a sample, while mass spectrometry gives information useful for molecular identification. After sample injection in the inlet, organic compounds are evaporated and carried by a carrier gas (or mobile phase) into and through a silica capillary column coated with a stationary phase. A distinct interaction between flowing organic compounds and the stationary phase during the assay (which includes an oven temperature program) results in a different retention time for a given compound.

After the separation process, organic compounds are eluted into mass spectrometer’s ion source, undergoing ionisation. The electron ionisation uses an electron beam to remove one electron from the organic compounds, thus creating the molecular ion (M+.). The molecular ion (which gives the molecular weight of the compound) is usually fairly unstable and quickly fragments into smaller ions which are separated according to their mass by a mass filter (usually a quadrupole) before reaching the detector. The relative abundances of these smaller fragments creates distinct fragmentation patterns (composed of single ion traces, m/z) for each

Chapter 2

compound, allowing the identification of organic molecules. The plotting of the intensity of the signal of the detected species versus time is called chromatogram.

Figure 2.8: Schematic representation of a GC-MS and its main components.

Among the various analytical techniques used for amino acid analyses, gas chromatography is considered to be the best analytical technique for in situ search for organic molecules in extra-terrestrial environments (Pietrogrande and Basaglia, 2010).

Gas chromatography is mainly used to analyse compounds that can be easily vaporised without suffering thermal decomposition. Although amino acids are not volatile, they can still be analysed by GC-MS after being chemically adapted into volatile derivates in a derivatization process.

Methods

2.3.2 – Derivatization of amino acids

One of the fundamental principles of gas chromatography is the separation of highly volatile compounds that are present in a sample through a capillary column.

Despite the intrinsic low volatility of amino acids, GC-MS analyses of low volatile compounds may also be performed, provided that the targeted organic molecules are modified into correspondent derivates with increased volatility in a process called derivatization. The derivatization of highly polar molecules into volatile derivatives

Chapter 2

allows the elution of the compounds at reasonable temperatures and also avoids thermal decomposition or molecular re-arrangements (Blau and King, 1979; Knapp,

1979; Kühnel et al., 2007). Organic molecules containing functional groups with active and labile hydrogens such as -SH, -OH, -NH and -COOH are of primary concern in the scope of GC analyses because of their tendency to form intermolecular hydrogen bonds (Zaikin and Halket, 2003). Hydrogen bonds severely affect not only the volatility and thermal stability of organic molecules, but also increase the risk of interactions with the column packing materials (Sobolevsky et al., 2003).

In this dissertation the derivatization of amino acids was carried out by subjecting the organic molecules to an esterification step with isopropanol, followed by an acylation reaction using Trifluoacetic anhydride (TFAA) as shown in Figure

2.10. The esterification changes the carboxylic acid functional group into a bigger and more volatile ester. The acylation reaction changes the amino functional group into an amide. After these two reactions, the original amino acids are found as N-

Trifluoroacetyl-O-isopropyl- (N-TFA, O-isopropyl-) derivatives with increased volatility, thermal stability and suitable to be analysed by GC-MS.

Figure 2.10: Derivatization of amino acids with isopropanol/acetyl chloride and trifluoroacetic anhydride.

Methods

2.3.3 - Amino acid calibration curves

Standard calibration curve method was chosen for future detection and quantification of amino acids in the Mars soil analogue samples and mineral standards.

Calibration curve method consists of establishing of a linear relationship between instrument responses in relation to analyte concentration. In this work, amino acid peak areas (obtained from the extracted m/z peaks in the specific ion chromatogram) are normalized by internal standard area. This ratio is then plotted against the amount of mass injected into the GC-MS creating the calibration curve. The amino acids 2- aminoheptanoic acid (2-AHA) was used as internal standard because it is a rare amino acid, unlikely to be found in environmental samples and also due to its distinct retention time, unique single ion trace (m/z = 196), which do not interfere/overlap with other amino acids present on samples. Calibration curves for 27 amino acids were prepared. The amino acids selected were: α-AIB; D,L-Isovaline; D,L-Alanine; D,L-α-

ABA; D,L-Valine; Glycine; D,L-Norvaline; D,L-β-AIB; D,L-β-ABA; β-Alanine; D,L-

Leucine; D,L-Norleucine; γ-ABA; D,L-Aspartic acid; D,L-Glutamic acid and 6-AHA.

The structures of these amino acids and respective N-Trifluoroacetyl-O-isopropyl- (N-

TFA, O-isopropyl-) derivatives are provided in Table 2.3.

Chapter 2

Table 2.3: Chemical structures of the amino acids and respective N-Trifluoroacetyl-O- isopropyl- (N-TFA, O-isopropyl-) derivatives used in the research. Amino acid Normal structure Derivatized structure α-AIB

D,L-Isovaline

D,L-Alanine

D,L-α-ABA

D,L-Valine

Glycine

D,L-Norvaline

D,L-β-AIB

D,L-β-ABA

β-Alanine

Methods

Table 2.3 (cont): Chemical structures of the amino acids and respective N- Trifluoroacetyl-O-isopropyl- (N-TFA, O-isopropyl-) derivatives used in the research. Amino acid Normal structure Derivatized structure D,L-Leucine

D,L-Norleucine

γ-ABA

D,L-Aspartic acid

D,L-Glutamic acid

6-AHA

2-AHA (internal standard)

In order to obtain the calibration curves needed for quantification, stock solutions (0.005 M) of each amino acid were prepared. A stock solution containing a mixture of all standard amino acids was prepared by transferring 50 μL of each amino acid stocks into a vial and diluted to 1 mL. This amino acid mixture was diluted into several ratios in order obtain standard solutions with a concentration range that should

Chapter 2

include the expected concentrations of amino acids in the Mars soil analogues samples. All this standard solutions were derivatized and injected into the GC-MS to analyse retention times and amino acid fragmentation patterns.

The first step of this work required obtaining fragmentation patterns and retention times for the derivatized amino acids standards in order to identify amino acids and obtain calibration curves for future sample measurements. Figure 2.11 displays the mass spectra and fragmentation pattern as detected by GC-MS for the derivatized aspartic acid.

100.00 184 90.00 Aspartic acid 80.00

70.00 212 60.00 139 50.00 40.00

Relative Relative abundance 30.00 166 20.00 226 10.00 0.00 m/z Figure 2.11: Mass spectra for derivatized aspartic acid, and corresponding fragmentation pattern of the derivatized aspartic acid molecule.

The remaining mass spectra and fragmentation patterns for other amino acids are presented in Annex 2. The mass/charge (m/z) peaks used for molecule identification are displayed in Table 2.4. The single ion GC-MS chromatograms of the

100

Methods

derivatized ((N-TFA, O-isopropyl) amino acid standard solutions are shown in Figure

2.12.

Table 2.4: Molecular ions used for identification of the amino acids present in the samples. Derivatized amino acid Mass/charge peak (m/z) α-AIB 154 D,L-Isovaline 168 D,L-Alanine 140 D,L-α-ABA 154 D,L-Valine 168 Glycine 126 D,L-Norvaline 168 D,L-β-AIB 182 D,L-β-ABA 182 β-Alanine 168 D,L-Leucine 140 D,L-Norleucine 182 γ-ABA 182 D,L-Aspartic acid 184 D,L-Glutamic acid 198 6-AHA 210 2-AHA (internal standard) 196

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relative abundance

Figure 2.12: Single ion GC-MS chromatograms (20 to 110 minutes) of the derivatized (N-TFA, O-isopropyl) amino acids (m/z 126, 140, 154, 168, 182, 184, 196, 198 and 210). 1) α- AIB; 2) D,L-Isovaline; 3) D-Alanine; 4) L-Alanine; 5) D- α-ABA; 6) D-Valine; 7) L- α-ABA; 8) L-Valine; 9) Glycine; 10) D-β-AIB; 11) D-Norvaline; 12) L-β-AIB ; 13) D-β-ABA; 14) β- Alanine; 15) L-β-ABA; 16) L-Norvaline; 17) D-Leucine; 18) D-Norleucine; 19) L-Leucine; 20) L-Norleucine; 21) γ-ABA; 22) D-2-aminoheptanoic acid; 23) L-2-aminoheptanoic acid (internal standard); 24) D-Aspartic acid; 25) L-Aspartic acid; 26) 6-AHA; 27) D-Glutamic acid and 28) L-Glutamic acid.

A critical point when preparing calibration curves is to ensure that linearity is

observed within the chosen concentration range. The calibration curve is obtained in

the form of a linear regression y = mx + b, where “m” is the slope and “b” gives the y-

intercept. The degree of linearity and dependence of the two variables is measured by

the coefficient correlation (R2).

Calculating the area of relevant peaks allows quantification of injected and

resoluted species. For that purpose, each amino acid peak area is divided by the

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internal standard peak area obtained in the same assay. Repeating this procedure for several standard concentrations gives then a set of amino acid/ internal standard peak ratios that when plotted against the amount of sample injected, gives a calibration curve.

With that aim, several standard amino acids acid samples were injected in the

GC-MS in order to obtain amino acid calibration curves. Figure 2.13 and Figure 2.14 display examples of a calibration curve for D- and L- Aspartic acid, respectively.

4 D-Aspartic Acid

3.5

2.5

1.5

1 y = 344934676.9265x - 0.0770 R² = 0.9959 0.5

ratio amino acid peak area/internal peak area area/internal standard peak acid amino ratio 0 0 1E-09 2E-09 3E-09 4E-09 5E-09 6E-09 7E-09 8E-09 9E-09 mass injected into GCMS (g/injection)

Figure 2.13: GC-MS calibration curve for derivatized (N-TFA, O-isopropyl) D-Aspartic acid.

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4 L-Aspartic Acid

3.5

2.5

1.5

1 y = 339733505.7016x - 0.0651 R² = 0.9963 0.5

ratio amino acid peak area/internal peak area area/internal standard peak acid amino ratio 0 0 1E-09 2E-09 3E-09 4E-09 5E-09 6E-09 7E-09 8E-09 9E-09 mass injected into GCMS (g/injection)

Figure 2.14: GC-MS calibration curve for derivatized (N-TFA, O-isopropyl) L-Aspartic acid.

The remaining calibration curves are presented in Annex 3. On the other hand,

Table 2.5 contains a summary of slope, origin intercept and correlation coefficient values for the calibration curves obtained during the preparatory work carried out in the laboratory. These calibration curves were used to calculate all the amino acid abundances analyses carried out with real environmental samples and mineral standards.

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Table 2.5: GC-MS calibration curves for derivatized (N-TFA, O-isopropyl) amino acids. Amino Acid Slope (m) Origin intercept (b) Correlation coefficient (R2)

α-AIB 1154956809.4134 - 0.0017 0.9750

D,L-Isovaline 499063076.2865 - 0.0054 0.9778

D-Alanine 995709450.4074 - 0.1072 0.9924

L-Alanine 1065070827.2639 - 0.0487 0.9903

D- αABA 826994223.3696 - 0.0248 0.9840

L- αABA 928199634.1335 0.0083 0.9917

D- Valine 551305880.2163 - 0.0002 0.9911

L-Valine 583773921.5309 - 0.0099 0.9932

Glycine 530773476.2191 - 0.0058 0.9895

D-β-AIB 184673512.0147 - 0.0301 0.9963

L-β-AIB 228218923.4570 - 0.0410 0.9931

D-Norvaline 519038497.6093 0.0002 0.9937

L-Norvaline 510402616.9917 - 0.0004 0.9937

β-Alanine 441275073.2699 0.0005 0.9889

D-β-ABA 452234920.6018 - 0.0377 0.9960

L-β-ABA 402141399.7442 - 0.0170 0.9949

D-Leucine 437020079.2389 0.0002 0.9887

L-Leucine 438590809.2582 - 0.0006 0.9937

D-Norleucine 369250671.7314 - 0.0664 0.9985

L-Norleucine 387655251.2126 - 0.0161 0.9955

γ-ABA 293031624.7618 - 0.0351 0.9926

D-Aspartic acid 344934676.9265 - 0.0770 0.9959

L-Aspartic acid 339733505.7016 - 0.0651 0.9963

D-Glutamic acid 272261256.3077 - 0.0643 0.9952

L-Glutamic acid 277926496.3682 - 0.0642 0.9935

6-AHA 202855934.5041 - 0.0697 0.9941

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2.3.4 - X-ray diffractometry (XRD)

X-ray diffractometry is a technique used to identify crystals, study their structures and make mineralogical quantifications based on diffraction of X-rays.

XRD was used in this thesis to identify and quantificate mineral phases in sediment samples from Rio Tinto and hypersaline lakes from Western Australia, which is reported in Chapter 3 and Chapter 4, respectively. XRD was also used to analyse to evaluate and determine the purity of the mineral standards used for the Mars Chamber simulations covered in Chapter 6.

2.3.4.1 – Diffraction of X-rays and Bragg’s Law

Max von Laue discovered that X-rays are the only type of radiation with the correct wavelength for inter-atomic-scale diffraction in a crystal and proved that X- rays were electromagnetic in nature (von Laue, 1914). Von Laue’s discovery opened the way for Sir William Lawrence Bragg and his father Sir William Henry Bragg to develop X-ray crystallography in 1913. Both observed that the irradiation of solid crystals with X-rays under specific wavelengths and angles of incidence produced intense peaks of reflected radiation (Bragg and Bragg, 1913).

Solid crystals have their constituent atoms arranged in an organized and well defined structure, which is usually called a lattice. Bragg’s law accounts for the phenomenon that occurs when waves with identical wavelength (λ) and same phase approach a solid crystal with the same angle of incidence (θ) are reflected by two different atoms in different layers of the crystalline lattice, spaced by a certain distance d, in a constructive interference (Figure 2.15).

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Figure 2.15: Schematic representation of diffraction and Bragg’s Law.

In Figure 2.15 the two waves are scattered from two different planes of the lattice. The path difference between these two waves undergoing constructive interference is, therefore, an integer multiple of the respective waves’ wavelength.

This path difference is given by Bragg’s law, which postulates that:

n λ = 2d sin θ (n, integral number)

Measurement of the reflected waves’ intensities as a function of the incidence angle results in a diffraction pattern. Identification of mineral phases in a diffractogram is achieved by comparison of d-spacings present in a sample with those obtained from standard reference patterns.

2.3.4.2 – X-Ray instrumentation

X-rays are usually generated by the bombardment of an anode metal plate with accelerated electrons coming from a heated cathode. The impact causes the loss of inner shell electrons and X-rays are generated by the relaxation of the anode metal

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plate’s atoms. Cu and Mo are the most commonly used metal targets for the generation of X-rays. Monochrometers are used to select and filter the monochromatic X-rays needed for diffraction. For example, CuKα and MoKα wavelengths are 1.5148 Å and

0.7107 Å, respectively.

X-rays interact mostly with electrons and after reaching the sample they can be either diffracted or transmitted. As it was mentioned in section 2.3.4.1, when X-rays interact with the organized lattice of a sample, they are deflected in a unique and specific pattern from which the arrangement of atoms in the structure can be determined. The diffracted beams are detected using a moveable detector (Figure

2.16).

Figure 2.16: Schematic representation of a XRD and its main components.

The collection of diffracted X-rays by the detector ultimately results in a diffractogram. A diffractogram is a sum of all diffraction patterns (i.e., the fingerprints) of all individual phases present in a given sample. Analysis of a diffractogram allows, therefore, the identification of crystalline phases in a mixture.

Furthermore, the intensity of X-rays peaks in a diffractogram is related to the quantity

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of the relative phases in the sample mixture. This relation allows the quantification of mineral phases by XRD. Nowadays, the Rietveld method is the most commonly applied method to quantificate crystalline phases in multicomponent mixtures, because it does not require calibration or the use of internal standards (Bish and Howard,

1988). The Rietveld method is based on an algorithm that finds the best fit to the whole diffraction pattern of the mixture, taking into account all reflection modes of the crystalline phases present in the sample as well as being less susceptible to signal extinction and minor amounts of preferred orientation (Bish and Howard, 1988).

2.3.5- Brunauer-Emmett-Teller method

The Brunauer-Emmett-Teller (BET) method is the most widely used for the measurement of the surface area of solid materials. This method was employed to determine the surface area of the mineral standards used for the Mars Chamber simulations (Chapter 6).

The determination of the surface area by the BET method involves the use of the BET equation, provided originally in Brunauer et al. (1938):

푃/푃 1 푃 (퐶 − 1) 0 = + ( ) 푉푎 (1 − 푃/푃0) 푉푚 퐶 푃0 푉푚퐶

In the BET equation provide above, 푉푎 is the volume of gas adsorbed, 푃/푃0 is

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the pressure to saturation pressure ratio during equilibrium, 푉푚 is the volume of the adsorbed monolayer and 퐶 is the BET constant. The terms 푉푚 and 퐶 can be calculated easily from the slope and intercept after plotting the left hand term of the equation against the saturation pressure ratio 푃/푃0.

The BET constant, 퐶, which takes into account the adsorption energy gap between the first adsorbed layer and the following ones that will adsorb on top, must be positive and can also be expressed as:

퐸 −퐸 ( 1 2) 퐶 = 푒 푅푇

Where 퐸1 is the heat of adsorption of the first layer and 퐸2 is the heat of liquefaction.

In addition, the total surface area (퐴푡) of the solid can be calculated by the following equation:

푣 N 푠 퐴 = 푚 A 푡 푉

where, 푣푚 is the volume of the gas that is adsorbed (usually N2), NA is the

Avogadro’s number, 푠 is the adsorption cross section of the adsorbent and 푉 is the molar volume of the adsorbant gas.

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2.3.6 - Scanning electron microscopy

Scanning electron microscopy (SEM) is used as a method to obtain images of the surface of a sample at the microscopic level. This is achieved by irradiating the sample with a beam of high energy electrons that is generated by a cathode filament.

The interaction of this beam of high energy electrons with the atomic structure of the sample generates two types of electrons: secondary and backscattered electrons. SEM images are created by secondary electrons, which have lower energies than backscattered electrons, ranging up to 50 eV. The secondary electrons that are emitted from the sample’s surface are detected by the secondary electron detector in the instrument. The amount of high energy electrons from the beam that interact with the sample is dependent on its surface topography and irregularities. As a result, surface topography also has an impact on the amount of secondary electrons that are generated and detected by the instrument. The signal created by the secondary electrons emitted from the sample is multiplied in a photomultiplier and, ultimately, converted into a digital image, showing the topography and surface of the sample in detail. The samples that are subjected to SEM must be electrically conductive and in the solid state. In the case of nonconductive samples, sample coating with a thin layer of a conducting material is usually performed.

Scanning electron microscopy may also be coupled with energy dispersive X- ray spectroscopy (EDS). When the beam of high energy electrons interacts with the sample, X-rays characteristic of the atoms present in the surface are also emitted. EDS allow particular mineral phases to be identified through comparison to XRD data,

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elemental emission lines and crystal morphology. Therefore, EDS is a useful method to determine the elemental composition of environmental samples. This technique was used in this work in order to identify mineral phases present in small abundances that could not be detected by XRD in the lacustrine samples from the hypersaline lakes in

Western Australia. Additional information may be found in section 4.2.4 in Chapter

2.3.7 - Polymerase Chain Reaction

In biology, molecular methods provide a fundamental way for the detection, identification and characterisation of microorganisms found in environmental samples.

Polymerase Chain Reaction (PCR) is an enzymatic amplification of a specific region of the DNA molecule obtained from a DNA extraction (Saiki et al., 1988). PCR amplification is possible with minimal starting amounts of DNA. A single copy or a few copies of a piece of DNA can be amplified by several orders of magnitude, generating thousands to millions of copies of a targeted DNA sequence and enabling the access to a higher amount of DNA material to work with. One of the most common target regions for PCR amplification is the 16S ribosomal DNA, which encodes for a part of the ribosomes that are required by all prokaryotic microorganisms to synthesise proteins (Röling and Head, 2005). The PCR requires the use of pre-defined primers, i.e. strand of short nucleic acid sequences that serve as a starting point for DNA synthesis.

The PCR method relies on the repetition of thermal cycling, which includes initialization, annealing, elongation steps. The initialization of the PCR process begins

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with the denaturation of the double stranded DNA molecules around 94-95 C.̊ The hydrogen bonds established between the DNA complementary bases are disrupted during this step, forcing the double stranded DNA to become single stranded. During the next stage, the annealing stage, the selected primers anneal to the single stranded

DNA template originated in the initialization process. Annealing occurs at lower temperatures, around 50–65 ̊C, allowing for hybridization of the primer to the specific complementary part of the single stranded DNA template. The extension stage is the stage when the thermostable DNA polymerase (Taq polymerase) synthesizes a new

DNA strand complementary to the DNA template. The time that it takes to complete the extension stage depends on the Taq polymerase used and also on the length of the

DNA fragment aimed to get amplified.

After the repetition of the number of cycles required to obtain an adequate amount of amplified DNA material, the PCR process ends with the final extension and final hold stages. The final extension stage, which lasts usually between 5 and 10 minutes, is used in order to assure that any remaining single-stranded DNA section is completely extended. The final hold stage of the PCR process is usually carried out around 4 up to 15 ̊C and is used to storage the PCR products and maintain their integrity before being used in subsequent laboratory procedures.

PCR was used in this thesis in order to amplify the amount of DNA extracted from the sediment samples of Rio Tinto and the hypersaline lakes of Western

Australia (Chapter 3 and Chapter 5, respectively). High amounts of DNA were required to carry out the microbial community profiling and genome sequencing reported in Chapter 3 and Chapter 5.

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2.3.8 - Denaturating Gradient Gel Electrophoresis

Denaturing gradient gel electrophoresis (DGGE) is a widely used fingerprinting method applied in the detection of microbial communities and diversities in a sample. The theoretical principles of this technique were described for the first time by Fischer and Lerman (1983). This method consists of the separation of

DNA fragments (amplified PCR products) based on their ability to partially revert from double to single-stranded DNA, in a polyacrylamide gel, under the effect of an electric current (electrophoresis). Changes in the DNA base sequence lead to differences in the GC content and distribution of the DNA fragments. Therefore, differences in DNA sequences between DNA from different species will have distinct melting behaviours in a polyacrylamide gel containing an increasing gradient of DNA denaturants, such as a mixture of urea and formamide. The melting occurs in step processes and sections of the fragment become single stranded within a very narrow range of denaturating conditions (i.e., the DNA fragment does not melt in a continuous, “zipper-like” way - Muyzer et al., 1993). DNA fragment migration through the gel decreases drastically as DNA fragments become increasingly melted.

This allows an effective profiling of multiple DNA fragments from different microorganisms present in a single sample, resulting in the occurrence of many bands on the gel. The differences in microbial diversity between samples may be assessed by comparing how different the bands spread through the gel. The complete dissociation of the double-stranded DNA in prevented by a 30-50 base pair GC-rich sequence, a

GC-clamp, which is attached to the 5’-end of one of the primers (Sheffield et al.,

1989).

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After the DGGE run, the separated bands in the gel may be excised from the

DGGE gel and extracted from the DGGE cut outs. The DNA extracted from the

DGGE gel may be then subjected again to the PCR process, in order to increase the available amount of DNA, and be sent out for sequencing. Sequencing provides information about the nucleotide order in the DNA molecules and this allows the identification of species and, ultimately, through phylogenetic assignment tools, the study of the microbial communities in the environment.

DGGE was used to study the microbial community profiles present in the sediment samples from Rio Tinto (Chapter 3) and the hypersaline lakes of Western

Australia (Chapter 5).

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Mineralogy, microbiology and amino acid analyses of Rio Tinto sediments

Chapter 3

ABSTRACT

The presence of acidic liquid water during Mars’ early history is inferred by the presence of hematite and jarosite on the martian surface. Biosignatures are usually deposited with and preserved by evaporite minerals, suggesting that, if life was ever present on Mars, its signatures may be preserved associated with these minerals. Rio

Tinto (Spain) has been identified as a terrestrial analogue for acidic martian environments. In order to investigate how different geological environments and mineralogy affect the detection of biosignatures, we determined the mineralogy, carbon, nitrogen and sulfur concentrations, microbial community profile and amino acid content of ten Rio Tinto sediment samples. Jarosite, hematite, goethite, illite and montmorillonite were detected using X-Ray diffraction. Carbon, nitrogen and sulfur analyses showed that sulfur is more abundant than carbon and nitrogen. Moreover, microbial ecology studies identified acidophiles commonly found in acid mine drainages. Enantiomeric separation of amino acids in Rio Tinto samples was achieved for the first time with total abundances ranging from less than 0.003 up to 548.2 parts per million (ppm). With the exception of microbiology analysis, we did not find an obvious trend between geochemical features and amino acid abundances. The results presented here investigate the interplay of mineralogy, organic chemistry and microbial life in terrestrial analogue environments with implications for the potential detection of biosignatures on Mars in future missions such as ESA’s ExoMars2020 or

NASA’s 2020 rover.

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3.1 - Introduction

Mars is a major target for space missions owing to its close proximity to Earth and potential to harbour extant/extinct life. The Thermal Emission Spectrometer on

NASA’s Mars Global Surveyor orbiter detected large extensions of crystalline grey hematite at Sinus Meridiani, suggesting that liquid water was present in the past

(Christensen et al., 2000). In 2004, NASA’s Opportunity rover confirmed the presence of outcrops rich in hematite and jarosite at Meridiani Planum using Mössbauer spectroscopy (Klingelhöfer et al., 2004, Squyres et al., 2004). Jarosite, which has also been remotely detected in other regions (Milliken et al., 2008, Farrand et al., 2009,

Wendt et al., 2011, Sefton-Nash et al., 2012, Weitz et al., 2013), imposes some limits on the interpretation of outcrop formation, as this mineral only occurs under acidic and oxidative conditions (Bigham and Nordstrom, 2000). On Earth, acidic waters can be formed either by dissolution and oxidation of gases (such as H2S or SO2) originating from volcanism or by oxidation of iron sulfides (Bigham and Nordstrom, 2000). The lack of volcanic craters near Meridiani Planum suggests that an acidic water system was formed by oxidation of iron sulfides. On Earth, jarosite is commonly found near acid mine drainages (AMD), owing to weathering and oxidation of sulfide ore deposits

(Blowes et al., 1991).

Rio Tinto (Spain) occurs in the core of the Iberian Pyritic Belt and displays an interesting acid-iron-sulfate chemistry. Oxidation of sulfide ore deposits in the region results in acidic headwaters (average pH value of 2.3) and an unusually high concentration of ferric iron (Fe3+) and heavy metals (Fernández-Remolar et al., 2005,

Amils et al., 2007). Deposition of evaporitic iron-sulfate mineral mainly occurs in the dry season when water evaporation is significant, leading to an increase of sulfate and

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iron concentrations (Fernández-Remolar et al., 2005). Despite the extreme conditions and lack of a complete understanding of pyrite oxidation mechanisms in the region

(Hubbard et al., 2009), there is a thriving microbial community, including chemolithotrophic microorganisms, which are believed to be the main contributors for pyrite weathering (López-Archilla et al., 2001). In fact, oxidation of iron sulfides is usually associated with microbial activity (Bigham and Nordstrom, 2000).

Evaporite minerals are usually deposited with organic molecules (Mancinelli et al., 2004). Furthermore, sulfate minerals are known to preserve organic compounds for billions of years (Aubrey et al., 2006) and their abundance in sediments appears to be correlated with the content of amino acids (Martins et al., 2011). These results suggest that soils rich in iron-sulfate minerals should be targeted for organic molecule detection on Mars (Aubrey et al., 2006). Additionally, iron oxides can also preserve a variety of biological structures (Fernández-Remolar et al., 2008), suggesting that if life was ever present on Mars at the time of iron oxides deposition, preserved organic biosignatures may be identified.

The chemistry of Rio Tinto provides a good model for the inorganic geochemistry and iron-sulfate mineral formation in Mars’ Meridiani Planum

(Fernández-Remolar et al., 2005). Space missions are expensive, time-consuming and require careful and extensive preparation. Optimal performance of instrumentation and protocols on Mars can be uniquely supported by investigating terrestrial analogues.

Hence, Rio Tinto has been designated as an important site to test the design, performance of instruments and understand the geological processes behind the formation of Meridiani Planum’s outcrops (Amils et al., 2007, Marlow et al., 2008).

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The X-ray diffraction (XRD) instrument Chemistry and Mineralogy (CheMin)

XRD on-board Curiosity rover has recently determined the mineralogy of Yellowknife

Bay (Vaniman et al., 2014) and Rocknest (Bish et al., 2013) at Gale Crater. This chapter presents the analysis of the mineralogical composition of ten sediment samples from Rio Tinto, collected during the Coordination Action for Research on life in

Extreme Environments (CAREX) field campaign, using XRD methodologies tested for the International Lunar Exploration Working Group (ILEWG) EuroMoonMars field campaigns programme (Foing et al., 2011; Ehrenfreund et al., 2011). This work in particular covers a variety of minerals that might be important in similar environments on Mars, in order to establish whether, despite large local heterogeneity, the mineralogical composition and potential biosignatures are related. The samples used in this work were also characterised in terms of carbon, nitrogen and sulfur composition, microbial distribution, and amino acid content.

Rio Tinto has been extensively studied and used as a Mars soil analogue in an astrobiology context. However, this is the first time that enantiomeric separation of amino acids has been achieved and reported. The overall set of results support the preparation of future space missions by examining the relationship between the mineralogy, isotopic and elemental compositions, microbial diversity and amino acid abundances of sediments in acidic environments similar to Mars.

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3.2 – Methods

3.2.1 - Samples

The samples used for the work reported in this chapter were collected near the source of the Rio Tinto river in an area called Annabel’s garden, located approximately 5 km north of the town of Nerva, close to Embalse de Tumbanales

(GPS coordinates: 37°43'31.0"N 6°33'34.5"W). Full details regarding the fieldtrip organized by CAREX and sample collection may be found in section 2.2.2.1 (Sample collection) in Chapter 2.

3.2.2 - X-Ray Diffraction (XRD) analyses

XRD analyses were carried out using a Rigaku Rapid II X-ray diffraction system (Mo Kα radiation). Samples were ground and placed in thin-wall glass capillaries. Diffraction data were collected on a 2-D image-plate detector. The two- dimensional images were then integrated to produce conventional 2θ vs. intensity patterns using Rigaku’s 2DP software. Quantitative analyses were carried out using

Rietveld method with MDI’s Jade software (Version 9.5). Quartz was used as internal standard. The amounts of swelling clay (montmorillonite) in sample RT1 and RT3 were determined based on an empirical curve for the montmorillonite-quartz system.

3.2.3 - Carbon, nitrogen and sulfur analyses (CNS)

Samples were ground to powder using a mortar and pestle and dried in an oven at 60 ̊C for at least 24 hours. Analyses were carried out using a FlashEA 1112 by

Thermo Scientific, coupled with a thermo-conductive detector and controlled by

EAGER 300 software. For carbon and nitrogen measurements, 10-20 mg of sample

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was weighed in silver cups. An empty cup was used as a blank. 2-3 mg of 2,2',2'',2'''-

(Ethane-1,2-diyldinitrilo)tetraacetic acid (EDTA) was used as a reference standard

(7.522 % N, 32.237% C, 4.836 % H, 34.386% O, 0 % S). For inorganic carbon removal, cups containing the samples were placed upright in an exsiccator containing a 12 M HCl solution and left exposed to the vapours overnight. Complete removal of inorganic carbon was tested by adding 10 µl of 10 % HCl to a cup. This procedure was repeated until no fumes were produced and/or inorganic carbon removal was needed.

Samples were dried once more before CN measurements. The silver cups were sealed off and placed within a tin cup, which was then also sealed, prior to measurement by the FlashEA1112 analyser. The procedure for sulfur measurements was as follows: 5-

15 mg of sample was weighed in a tin cup. An empty cup was used as a blank. 2-3 mg of 2,5-Bis(5-tert-ButylbenzOxazol-2yl)Thiophene (BBOT) (6.517 % N, 72.53 % C,

6.09 % H, 7.43 % O, 7.44 % S) was used as standard. Sulfur release was improved with vanadium (V) oxide. Cups were sealed and measured by the FlashEA1112.

Measurements were carried out in duplicates.

3.2.4 - Microbial community profiling

DNA was extracted according to an adapted PowerSoil DNA isolation kit protocol (MO BIO Laboratories, Solana Beach, CA, USA) developed by Direito et al.

(2012). This modified method, designed to minimize nucleic acid adsorption, is particularly useful for environmental samples with low biomass and rich in clay minerals. Positive controls (containing only DNA, no soil sample) and extraction blanks (containing only DNase and RNase free water) were run in parallel as quality controls. Polymerase chain reaction (PCR) amplification of 16S rRNA gene fragments was performed using primers for Bacteria and Archaea. Each PCR reaction was

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performed in a 25 μL solution containing: 3 μL of DNA template, 1 μL of 0.01 mM of each primer, 1 μL of Bovine Serum Albumin (10 mg/mL, New England Biolabs),

12.5 μL of Fidelitaq PCR Master Mix (USB Corporation, Cleveland, OH) and 6.5 μL of DNase and RNase free water. Negative and positive controls were included

(DNase- and RNase-free water, and spikes of bacterial or archeal DNA) to monitor for contamination and to validate PCR amplification. As PCR products were weak for both Bacteria and Archaea, a second PCR was performed using a 1:50 dilution of the first PCR products as templates. PCR products were checked by gel electrophoresis over 1.5 % agarose gels, stained with ethidium bromide and illuminated under a UV transilluminator. Primers and programs for Bacteria and Archaea PCRs, and denaturing gradient gel electrophoresis (DGGE) profiling of the PCR products followed the procedure described in Direito et al. (2011). The bands of interest were cut out of the DGGE gel and soaked overnight in sterile Tris-EDTA buffer at 4 ̊C. The isolated amplicons were amplified without a GC clamp prior to sending them out for purification and sequencing (Macrogen Europe, Amsterdam, The Netherlands).

3.2.5 – Amino acid analyses

3.2.5.1- Chemicals and tools

All pipette tips and eppendorfs used were bought sterile. Hydrochloric acid

(37 wt%), and high performance liquid chromatography (HPLC)-grade water were purchased from Sigma-Aldrich. Sodium hydroxide was purchased from Riedel-de

Haen. Aluminium hydroxide and 2-aminoheptanoic acid (>97 %) were purchased from Fluka. All amino acid standards were purchased from Sigma-Aldrich, except

D,L-isovaline, which was bought from Acros Organics. AG 50W-X8 resin (100-200

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mesh) was acquired from Bio-Rad. HPLC-grade dichloromethane (DCM) was purchased from Fisher Scientific. Trifluoroacetic anhydride isopropanol (TFAA-IPA) derivatization kit was obtained from Alltech. Copper turnings were purchased from

BDH. All glassware tools and ceramics used were sterilized by wrapping in aluminum foil and heating for at least 3 hours at 500 ºC.

3.2.5.2 - Extraction, derivatization and GC-MS analyses

Amino acid extraction follows the procedure described by Martins et al. (2011,

2015), which was developed and optimized originally by Kvenvolden et al. (1970) and others (Tsugita et al. 1987; Keil and Kirchman 1991; Glavin et al. 1999; Glavin and

Bada, 2001). A serpentinite sample provided by the Natural History Museum in Bern was heated to 500 ̊C for at least 3 hours and used as a procedural blank. A step to remove sulfur was performed between the desalting and derivatization, by using copper turnings (activated in a 10 % HCl solution). The activated copper turnings were added to V-vials containing the desalted residues, previously brought up with 1 mL of

HPLC grade water, and left overnight. The copper turnings were then removed and the

V-vials were dried under a flow of N2. Derivatized amino acids were dissolved in

75 μL of DCM. Analyses were performed using a Perkin Elmer Clarus 580 gas chromatograph/ Clarus SQ 8S mass spectrometer. The amino acids were separated using two Agilent Chirasil L-Val capillary columns (each 25 m, inner diameter

0.25 mm, film thickness 0.12 μm) connected by a zero dead volume connector.

Helium was used as carrier gas with a 1 mL/min flow. GC injector temperature was set at 220 ̊C. Automatic splitless mode was used for injection and the oven programme was: 1) 35 ̊C for 10 minutes; 2) 2 ̊C per minute increase until 80 ̊C, hold for 5 minutes;

3) 1 ̊C per minute increase until 100 ̊C; and 4) 2 ̊C per minute increase until 200 ̊C,

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hold for 10 minutes (total run time 117.5 minutes). Temperatures for transfer line and the MS ion source were set at 220 ̊C and 230 ̊C, respectively. Amino acids present in the samples were identified by comparing the retention time and mass fragmentation pattern to amino acid standard mixtures.

3.3 - Results

3.3.1 - XRD analyses

Figure 3.1 provides an example of an XRD pattern obtained for sample RT4 and the identification of minerals that are typically found in Rio Tinto sediments, such as jarosite (KFe3(SO4)2(OH)6), barite (BaSO4), quartz (SiO2) and pyrite (FeS2).

Diffraction patterns for the remaining samples were obtained and may be found in

Annex 4.

Pyrite was identified in samples RT2, RT3, RT4 and RT5 (Table 3.1). Sulfate minerals (jarosite, barite, copiapite (Fe2+ Fe3+ (SO ) (OH) .20(H O) and coquimbite 4 4 6 2 2

3+ (Fe 2(SO4)3.9(H2O)) were identified in all samples except in sample RT9. Iron oxide minerals (hematite (Fe2O3) and goethite (FeO(OH)) occurred in five samples

(hematite: RT1 and RT5; goethite: RT1, RT7 and RT10). K-feldspar (KAlSi3O8) was detected in one sample (RT9) and quartz was identified in most of the samples, except in samples RT7 and RT8. Clay minerals (illite

((K,H3O)(Al,Mg,Fe)2(Si,Al)4O10[(OH)2,(H2O)] and montmorillonite

((Na,Ca)0.33(Al,Mg)2(Si4O10)(OH)2·nH2O) were found in two samples (RT1 and RT3)

(Table 3.1).

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Pyrite 53.9 10.2 39.3 31.0 Jarosite 23.3 21.3 10.1 12.6 6.2 45.1 Coquimbite 12.1 58.4 Copiapite 3.3 79.3 41.6 Barite 3.6 18.3 20.2 23.4 10.7 9.1 Goethite 3.3 93.8 38.5 Hematite 5.5 25.9 K-Feldspar 73.3 Quartz 25.3 15.7 17.2 27.2 32.4 8.1 26.7 7.3 Illite 29.1 16.7 Montmorillonite 9.9 11.1

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3.3.2 - Carbon, nitrogen and sulfur (CNS) analyses

The carbon content in the samples ranged from 0.41 % (sample RT7) up to

2.45 % (sample RT9) (Table 3.2). Nitrogen content ranged from 0.015 % (sample

RT2) up to 0.066 % (sample RT1). Results obtained for the sulfur content suggest that this element is significantly more abundant than carbon and nitrogen in all samples, except for sample RT9, with values ranging from 0.10 % (RT9) up to 23.97 % (RT2)

(Table 3.2).

Sample Average C Average N Average S

(%) (%) (%)

RT1 0.540 ± 0.162 0.073 ± 0.004 5.65 ± 0.36

RT2 0.490 ± 0.184 0.017 ± 0.006 23.97 ± 0.60

RT3 1.310 ± 0.096 0.056 ± 0.008 8.75 ± 0.34

RT4 0.60 ± 0.196 0.040 ± 0.001 22.15 ± 1.02

RT5 0.680 ± 0.181 0.057 ± 0.005 6.33 ± 0.86

RT6 1.930 ± 0.652 0.043 ± 0.008 16.22 ± 0.26

RT7 0.410 ± 0.540 0.030 ± 0.005 17.36 ± 1.28

RT8 1.050 ± 0.635 0.013 ± 0.003 17.81 ± 1.36

RT9 2.450 ± 0.940 0.024 ± 0.001 0.10 ± 0.11

RT10 0.780 ± 0.180 0.070 + 0.004 3.83 ± 0.14

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3.3.3 - Microbial community profiling

Table 3.3 provides a summary of phylogenetic affiliations, microbial distribution and characteristics of the dominant bands found in the DGGE gels

(sequencing was only successful for a restrict number of DGGE bands). Bacteria were detected in all extracts except in sample RT2. Archaea were detected in 5 out of 10 samples (RT1, RT7, RT8, RT9, RT10). Phylogenetic analyses of DGGE bands have shown sequences from Alphaproteobacteria, Betaproteobacteria and Actinobacteria for Bacteria. For Archaea the sequences were associated with Euryarchaeota

(Thermoplasmatales order). Sequences obtained from bacterial and archaea DGGE band cut outs were generally related to iron oxidizers and uncultured acidophilic, microorganisms identified in other AMD and acidic environments, including

Ferroplasma acidiphilum and Ferrovum myxofaciens.

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Table 3.3 – Summary of phyllogenetic affiliations, similarities and characteristics of microorganisms detected in Rio Tinto sediment samples. Closest related sequence and ascension code in Similarity Domain / characteristics Samplesa NCBI database (%) RT RT RT RT RT RT RT RT RT RT 1 2 3 4 5 6 7 8 9 10 Uncultured alpha proteobacterium found in Bacteria from det det det det det 95 cyanobacterial blooms (HQ691867) Alphaproteobacterium class Uncultured Magnetospirillum sp. From a pond in Bacteria, Magnetospirillum det det 95 Catalina Island, CA, USA (JX295191) genus Uncultured bacterium from an acidic lake, Boiling det det det det 96 Bacteria Springs Lake (JX428621) Bacteria. Ferrovum genus. det det det det det det det Ferrovum myxofaciens (KC677643) 93 Acidophile, oxidates Fe2. Bacterium CS11 isolated from acidic mine drainage Bacteria. Acidimicrobiales det 97 from North Wales (AY765999) order o xidates Fe2+ Uncultured bacterium found in sulfate-reducing det 99 Bacteria columns treating acid mine drainages (KF581323) Propionibacterium sp. found in a microbial community Bacteria, det det det 96 in a methanogenic fermenter (AB264622) Propionibacterium genus Uncultured bacterium from endolithic microbial det det 98 Bacteria communities in Rio Tinto (EF441915) Archaea. Acidophile, det Ferroplasma acidiphilum (KF940052) 99 oxidates Fe2+ Uncultured archaeon found in an abandoned sulfides Archaea, order det 91 gallery near Oviedo, Spain (KF225646) Thermoplasmatales Uncultured archaeon found in an abandoned sulfides Archaea order det 86 gallery near Oviedo, Spain (KF225694) Thermoplasmatales Archaea, order det Uncultured Thermoplasmatales archaeon found in an 83 Thermoplasmatales acidic river in Argentina (JN982117) (acidophiles) Uncultured archaeon found in an abandoned sulfides Archaea, order det 97 gallery near Oviedo, Spain (KF225646) Thermoplasmatales uncultured archaeon from gold mines in South Africa det 100 Archaea (DQ088720) uncultured archaeon from gold mines in South Africa det 99 Archaea (DQ088720) a- det - sequence detected in the sample.

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3.3.4 – Amino acid analyses

Figure 3.2 shows a typical single ion GC-MS chromatogram of the derivatized

(N-TFA, O-isopropyl) hot-water extract of sample RT9. A similar chromatogram of the serpentinite procedural blank is shown in Figure 3.3. Single ion GC-MS chromatograms were obtained for all samples but are not shown.

L-alanine, L-valine, glycine, L-leucine, L-aspartic acid and L-glutamic acid were the most abundant amino acids identified in all samples (Table 3.4). L-leucine and the D-enantiomers of glutamic acid, aspartic acid and alanine were also detected in lower amounts. The amino acid distribution obtained from Rio Tinto sediment samples agrees with those found in other Mars soil analogues, (e.g., Martins et al.,

2007, Peeters et al., 2009, Martins et al., 2011). The total amino acid content ranged from less than 0.003 parts per million (ppm) up to 548.2 ppm (Table 3.4).

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relative abundance

Figure 3.2: Single ion GC-MS chromatograms (25 to 85 minutes) of the derivatized (N-TFA, O-isopropyl) amino acids extracted from sample RT9 (m/z 126, 140, 154, 168, 182, 184, 198 and 210). Figure legend is as follows: 1) D-alanine; 2) L-alanine; 3) L-valine; 4) glycine; 5) L-leucine; 6) D-aspartic acid; 7) L-aspartic acid; 8) D-2- aminoheptanoic acid; 9) internal standard (L-2-aminoheptanoic acid); 10) D-glutamic acid and 11) L-glutamic acid, X) unidentified compounds.

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relative abundance

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Table 3.4 – Summary of the amino acid abundances (in ppb) obtained for the Rio Tinto samples measured by GC-MSa.

RT1 RT2 RT3 RT4 RT5 RT6 RT7 RT8 RT9 RT10

α-AIB < 3d < 3d < 3d < 3d < 3d < 3d < 3d < 3d < 3d < 3d D,L-Isovalineb < 8 d < 8 d < 8 d < 8 d < 8 d < 8 d < 8 d < 8 d < 8 d < 8 d D-Alanine < 3 d < 3d < 3d < 3d < 3d 1900 ± 100 < 3d < 3d 6700 ± 300 < 3d L-Alanine 10400 ± 800 < 3 e 3000 ± 100 3000 ± 100 3500 ±100 12100 ± 600 4800 ± 300 1200 ±100 106100 ± 3200 < 3 e D- α-ABA < 3d < 3d < 3d < 3d < 3d < 3d < 3d < 3d < 3d < 3d L- α-ABA < 3d < 3d < 3d < 3d < 3d < 3d < 3d < 3d < 3d < 3d D- Valine <4 d <4 d <4 d <4 d <4 d <4 d <4 d <4 d <4 d <4 d L- Valine 6800 ± 500 <4 e 1700 ± 100 1500 ± 100 2500 ± 100 4800 ± 200 3600 ± 100 <4 d 79000 ± 1300 <4 d Glycine 6900 ± 200 < 6 e 1800 ± 100 2500 ± 100 3000 ± 100 16000 ± 700 3600 ± 200 < 6 d 82800 ± 2100 < 6 d DL- β- AIBb,c < 8 d < 8 d < 8 d < 8 d < 8 d < 8 d < 8 d < 8 d < 8 d < 8 d DL- β- ABAb,c < 8 d < 8 d < 8 d < 8 d < 8 d < 8 d < 8 d < 8 d < 8 d < 8 d D- Norvaline < 3d < 3d < 3d < 3d < 3d < 3d < 3d < 3d < 3d < 3d L- Norvaline < 3d < 3d < 3d < 3d < 3d < 3d < 3d < 3d < 3d < 3d β-Alanine <7d <7d <7d <7d <7d <7d <7d <7d <7d <7d D- Leucine <4d <4d <4d <4d <4d <4d <4d <4d <4d <4d L- Leucine 4200 ± 200 <4d <4d <4d <4d <4d 2400 ± 100 <4d 79200 ± 900 <4d D- Norleucine < 3d < 3d < 3d < 3d < 3d < 3d < 3d < 3d < 3d < 3d L- Norleucine < 3d < 3d < 3d < 3d < 3d < 3d < 3d < 3d < 3d < 3d γ-ABA <7d <7d <7d <7d <7d <7d <7d <7d <7d <7d D- Aspartic acid 5100 ± 100 <4d 4300 ± 100 4600 ± 100 4100 ± 100 5400 ± 100 <4d <4d 13000 ± 300 <4d L- Aspartic acid 8500 ± 200 <4d 6700 ± 300 8500 ± 600 7600 ± 500 13700 ± 400 <4d <4d 62000 ± 1100 <4d D- Glutamic <5d <5d 4200 ± 100 4300 ± 100 4400 ± 100 5500 ± 100 <5d <5d 18600 ± 500 4700 ± 100 acid L- Glutamic 9500 ± 400 <5d 8200 ± 500 12200 ± 200 17200 ± 300 13700 ± 400 4700 ± 100 <5d 101300 ± 3200 6500 ± 200 acid Total 51,400 29,900 36,600 42,300 73,100 19,100 1,200 548,200 11,200

Amino acid quantification includes background level correction using a serpentinite blank. Associated errors were calculated using standard deviations of the average values for eight measurements (N) with a standard error δx=σx. N-1/2. Enantiomeric separation not possible under chromatographic conditions. Optically pure standard not available for enantiomeric identification. These concentrations are upper limits and were not included in the total amino acid concentration.

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3.4 - Discussion

In order to evaluate the potential relationship between the mineralogy, carbon, nitrogen and sulfur contents, amino acid abundances and microbiology in the Rio

Tinto sediment samples, the discussion is this chapter is based on a sample by sample approach.

Sample RT1 was collected in the middle of a drying pond and contains significant amounts of clay minerals (illite and montmorillonite), together with jarosite and smaller amounts of hematite and barite (Table 3.1). Illite and montmorillonite are known to be stable under acidic environments. Crouse and Bish (2012) verified that montmorillonite seems to suffer negligible acid-sulfate alteration when exposed to pH values as low as 2 (i.e., similar environment to Rio Tinto). Galán et al., (1999), on the other hand, attested the stability of illite by exposing the mineral to natural Rio Tinto water samples. The deposition of hematite and jarosite is interpreted as the result of pyrite weathering. Barite, on the other hand, is commonly associated with metal sulfide deposits that are formed at or near the seafloor (Paytan et al., 2002, Shanks III and Koski, 2012). The massive sulfide deposits in Rio Tinto resulted in fact from sub- aqueous deposition of sulfides in confined sedimentary basins, where hydrothermal fluids are mixed with seawater (Nehlig et al., 1998). This, therefore, helps to explain the occurrence of barite in Rio Tinto samples.

Minerals have a strong influence on the composition of microbial communities

(Direito et al., 2012, Röling et al., 2015). The widespread occurrence of iron-based minerals satisfies iron availability and the microbial community observed in our samples was predominantly associated with this element. The microbial community

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present in sample RT1 includes a species related to Ferrovum myxofaciens (93 % similarity) and also a closely related species to Ferroplasma acidiphilum (99 % similarity, Table 3.3). Pyrite oxidation (and formation of iron oxides and sulfates) is mediated by these species that were also reported in previous Rio Tinto studies (e.g.

Garcıa-Moyano et al., 2012, Gonzalez-Toril et al., 2003). Ferroplasma acidiphilum is a common species in acid mine drainages and has a critical role in cycling and mobilization of heavy metals from sulfide deposits such as pyrite, arsenopyrite, copper sulfides (Golyshina and Timmis, 2005). In addition, Ferrovum myxofaciens is an acidophile iron oxidizer of the class Betaprotebacteria that was recently characterized for the first time by Johnson et al. (2014). This new species was cultured and isolated from water samples collected at Mynydd Parys copper mine in north Wales.

Sample RT2 stands out as the only sample that had no amino acids detected above the detection limit of the GC-MS, 3 parts-per-billion (ppb) (Table 3.4). DNA extraction and PCR were not successful for this sample suggesting that the amino acid result was not a false negative (Table 3.3). Results point towards an absence of microorganisms, combined with a low amount of nitrogen according to CNS data

(Table 3.2). Despite the agreement between the different sets of data, it cannot be ruled out that amino acid and DNA adsorption did not occur onto minerals and ultimately interfered with extraction.

Just like sample RT1, sample RT3 also contained illite and montmorillonite

(Table 3.1). The total amount of amino acids in sample RT3 was 29.9 ppm, while in sample RT1 it was 51.4 ppm (Table 3.4). Our results showed that, unlike results

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Mineralogy, microbiology and amino acid analyses of Rio Tinto sediments obtained by Martins et al. (2011), clays do not necessarily preclude the extraction of amino acids.

DGGE profiling in sample RT3 yielded a sequence with 96 % similarity

(Table 3.3) to an uncultured bacterium from an acidic lake with pH 2 (Boiling Springs

Lake California, USA, Siering et al., 2013). Despite the similarities in terms of acidic conditions, the concentrations of sulfuric acid, heavy metals and nutrients in this lake are remarkably lower than in Rio Tinto (Siering et al., 2006). A sequence related to a

Magnetospirillum found in a pond in Catalina Island (California, USA, Lin et al.,

2013) was also identified (95 % similarity, Table 3.3) in sample RT3. This genus includes species that are able to biomineralize magnetite in bacterial magnetosomes

(Faivre and Schüler, 2008). Pyrite, jarosite and goethite in sample RT3 deliver the ferric and ferrous iron needed for magnetite formation. However, according to

Bazylinski and Lefèvre (2013), there are no reports of Magnetospirillum occurring in extreme acidic environments. The authors suggest, though, that the increased solubility of iron at low pH should be considered as a favourable condition for these bacteria to thrive in acidic environments (Bazylinski and Lefèvre, 2013).

Samples RT4 and RT5 were collected in the same location, near the stream shore; the former came from the surface while the latter was collected 5 centimetres below. Their mineralogical profile is similar, although sample RT4 contained freshly deposited jarosite, while sample RT5 contained hematite instead (Table 3.1). Hematite is generally more abundant in ancient sediment deposits and its formation is likely related with early diagenesis of other iron bearing minerals in acidic environment

(Goss, 1987).

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Total amino acid abundances for these samples were 36.6 ppm for RT4 and

42.3 ppm RT5 (Table 3.4), which agreed with their relative total nitrogen content

(Table 3.2). The microbial community in sample RT4 included the same sequences that were discussed in sample RT3: an uncultured bacterium from an acidic lake with pH 2 - Boiling Springs Lake California, USA (Siering et al., 2013), and a sequence related to a Magnetospirillum found in Catalina Island, California, USA (Table 6; Lin et al., 2013). In addition, the sequence related to Ferrovum myxofaciens (93 % similarity) already discussed in Sample RT1, was also present in samples RT4 and

RT5, likely contributing to the oxidation of pyrite and formation of hematite and jarosite detected by XRD (Table 3.1).

Sample RT7 was collected from a freshly deposited red iron crust near the water stream, which was rich in goethite, according to XRD data (Table 3.1). Total amount of amino acids was 19.1 ppm (Table 3.4). Sample RT10 also contains a significant amount of goethite (Table 3.1), and its total amount of amino acids was

11.2 ppm (Table 3.4). The relatively lower amino acid abundances obtained for these two samples when compared to the other samples may be caused by strong adsorption of organic matter on goethite, which is known to establish strong interactions between carboxylic groups and mineral surfaces at low pH (Chorover and Amistadi, 2001).

Another reason may be that microorganisms able to reduce ferric iron from goethite are more commonly associated with anaerobic environments (Lovley, 1993). This would limit the amount of biomass in an aerobic environment and, therefore, the total amount of amino acids. Results from DGGE profiling showed that sample RT7 contained the highest variety of microorganisms (Table 3.3). Most sequences are related to uncultured microorganisms that participate in the iron cycle and bacteria

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Mineralogy, microbiology and amino acid analyses of Rio Tinto sediments from acidic environments, including AMD (Table 3.3). Samples RT7 and RT10 also included the sequence related to Ferrovum myxofaciens, already discussed in sample

RT1. Sample RT10 proved to have less variety; sequences obtained from this sample also include an uncultured archaeon from gold mines in South Africa, and also one sequence found in endolithic microbial communities in Rio Tinto (Table 3.3).

Sample RT8 had a unique mineralogical profile, being a mixture of coquimbite and copiapite (Table 3.1). These sulfate minerals were also identified and reported by

Fernández-Remolar et al. (2005) and Buckby et al. (2003) in other Rio Tinto samples.

Sample RT6 is a copiapite-rich sample with smaller amounts of quartz and jarosite

(Table 3.1). The total amount of amino acids for sample RT8 (1.2 ppm, Table 3.4) matched the low amount of nitrogen obtained (Table 3.2). Sample RT6 contained the second highest amount of total amino acids, (73.1 ppm, Table 3.4). This result was in agreement with the total amount of carbon obtained, which was also the second highest (Table 3.2).

DGGE profiling from samples RT6 and RT8 showed that the microbial community in these samples are related to an uncultured bacterium from an acidic lake with pH 2 - Boiling Springs Lake California, USA (Siering et al., 2013), and the sequence related to Ferrovum myxofaciens (93 % similarity), which were already discussed in the paragraphs dedicated to samples RT3 and RT4 (Table 3.3).

Sample RT9 yielded the highest amount of amino acids (548.2 ppm, Table

3.4). This is likely to be related to a completely distinct mineralogical profile, as this sample was a rich K-feldspar sediment (Table 3.1). The absence of sulfur-bearing minerals suggests a distinct microenvironment within the extreme conditions generally

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found on Rio Tinto and also explains the low amount of sulfur (Table 3.2). The amino acid abundance agreed with the highest amount of organic carbon (Table 3.2). Total amount of organic carbon was found to agree with the samples with the highest amount of total amino acids (samples RT6 and RT9). On the other hand, total nitrogen content was useful to verify the results obtained for samples RT2 and RT8, which suggests lower amino acid abundance due to lower availability of nitrogen.

Sequencing of DGGE bands showed that sample RT9, like sample RT10, contains the same bacteria found in endolithic microbial communities in Rio Tinto

(Table 3.3).

3.4.1- Implications for the detection of biosignatures on Mars

Table 3.5 compiles the main results obtained from the mineralogical, elemental, amino acids and DNA analyses. The samples analyzed in this work were collected within an area 150 metres across. Our results showed that the detection of biosignatures in sediments that are analogues to Mars may vary significantly, even when sampling sites are in close proximity. Therefore, this variability should be also expected to be verified in future Mars exploration.

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Table 3.5 - Summary of the mineralogical, elemental, microbiological and amino acid composition performed on ten Rio Tinto sediment samples collected during the CAREX field campaign.

RT1 RT2 RT3 RT4 RT5 RT6 RT7 RT8 RT9 RT10

Pyrite 53.9 10.2 39.3 31.0

Sulfates 26.9 30.4 44.8 33.5 10.7 91.9 6.2 100 54.2 Iron oxides 8.8 25.9 93.8 38.5 K-Feldspar 73.3 Quartz 25.3 15.7 17.2 27.2 32.4 8.1 26.7 7.3

Mineralogy (%) Mineralogy Clays 39.0 27.8 0.540 ± 0.490 ± 1.310 ± 0.60 ± 0.680 ± 1.930 ± 0.410 ± 1.050 ± 2.450 ± 0.780 ±

Total carbon 0.162 0.184 0.096 0.196 0.181 0.652 0.540 0.635 0.940 0.180 0.073 ± 0.017 ± 0.056 ± 0.040 ± 0.057 ± 0.043 ± 0.030 ± 0.013 ± 0.024 ± 0.070 + Total nitrogen 0.004 0.006 0.008 0.001 0.005 0.008 0.005 0.003 0.001 0.004 23.97 ± 22.15 ± 16.22 ± 17.36 ± 17.81 ± Total sulfur 5.65 ± 0.36 8.75 ± 0.34 6.33 ± 0.86 0.10 ± 0.11 3.83 ± 0.14

CNS analyses (%) analyses CNS 0.60 1.02 0.26 1.28 1.36

Microrganisms + - + + + + + + + +

Total amino acid (ppm) 51.4 n.d. 29.9 36.6 42.3 73.1 19.1 1.2 548.2 11.2 n.d.: non-detected above detection limit of the GC-MS (3 ppb).

+: Positive signal

-: No signal

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Our results also suggest that there was no obvious correlation between mineralogical content and total amino acid abundance. On the other hand, DNA data and amino acid content were in agreement, as sample RT2, a pyrite-rich sample, showed non-detectable DNA and amino acids. On the other hand, other pyrite rich samples (i.e. samples RT4 and RT5) showed detectable organic signatures. This lack of correlation between mineralogical and amino acid analyses data sets show that a good location to detect biosignatures based on mineralogical screening is a challenging task. Furthermore, a discrepancy in two sulfate-rich samples (RT6 and

RT8) was observed in the amino acid abundance. Sulfate minerals are relevant in the astrobiology context as they are able to preserve organic molecules for billions of years and some sulfate minerals are opaque to radiation below 400 nm (Hughes and

Lawley, 2003; Aubrey et al. 2006). In other Mars soil analogues the abundance of sulfate minerals was correlated with the amount of organic molecules (Martins et al.,

2011). However, we could not find such a correlation in our samples. Sulfate minerals may have a profound impact on the successful detection of biosignatures in future

Mars mission looking for biosignatures.

The presence of biosignatures has an impact on the stability of minerals.

Glycine, for example, proved to have an impact on thermal stability of sodium and ammonium jarosites (Kotler et al., 2009). Notwithstanding, Lewis et al. (2015) demonstrated that jarosite might be an obstacle during thermal analyses due to decomposition of sulfate ions and oxidation of organic molecules. Coquimbite and copiapite were found in samples RT2, RT6 and RT8 (Table 3). Copiapite was also detected in the northern Mawrth Vallis region on Mars (Farrand et al., 2014). These

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sulfate minerals have a similar composition to jarosite (Jerz and Rimstidt, 2003) and also release sulfur dioxide during thermal analyses, caused by the degradation of sulfate ions (August, 1991; Ackermann et al., 2009). Considering their similarities to jarosite, copiapite and coquimbite may also interfere with the detection of organic molecules on Mars using thermal methods, in a similar way to what was demonstrated by Lewis et al. (2015). This hypothesis needs, of course, further assessment.

The presence of clay minerals (illite and montmorillonite) in samples RT1 and

RT3 did not preclude the extraction of amino acids, unlike what was observed by

Martins et al. (2011). Illite and montmorillonite have been identified on Mars (Poulet et al., 2005; Clark et al., 2007; Mustard et al., 2008; Ehlmann et al., 2009, Carter et al., 2013). NASA’s rover Curiosity drilled for the first time at Yellowknife Bay, finding new evidence of clays. This is relevant for astrobiology purposes given the general abundance of phyllosilicates on proposed landing sites for Mars exploration missions (Rogers and Bandfield, 2009; Grant et al., 2011; Golombek et al., 2012) and the recent results from Curiosity, which associate clays with environments that could have supported life (Grotzinger et al., 2013; Vaniman et al., 2014).

Results from DNA sequencing showed that the majority of micro-organisms identified are also commonly found in AMD, related to the iron cycle and microbial contributors to pyrite oxidation. Microbial metabolism based on iron is thought to be one of the most ancient on our planet, and also a plausible one on Mars (Weber et al.,

2006).

The total carbon data allowed us to corroborate which samples contained more amino acids (RT6 and RT9). On the other hand the total nitrogen data were good

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indicators of environments with limited nitrogen content which coincided with the absence (detection limit of the GC-MS of 3 pbb) or low amount of amino acids

(samples RT2 and RT8, respectively). Despite this agreement, we could not find a general trend between CNS data and amino acid content for the remaining samples.

CNS results account for total amount of organic molecules in a sample, which includes more classes of compounds than amino acids. Also, minerals may interfere with hot water extraction of organic molecules may be detected by thermal methods, contributing to discrepancies between data sets. Overall, quantitative measurements of elemental carbon and nitrogen may be useful as a screening tool to determine which soils are better suited for the detection of organic molecules.

Potential biosignatures of putative martian life may be present in locations that contained (or still contain) liquid water. Evidence of liquid water was found by the

Mars Reconnaissance Orbiter and more recently by NASA’s Curiosity at Gale crater.

Curiosity’s results point towards a broader distribution of liquid water beyond the equatorial region (McEwen et al., 2014; Martín-Torres et al., 2015). The selection of landing sites on Mars has to take into consideration multiple aspects, such as: engineering constraints, local geological characteristics, accessibility to presumable habitable environments and biosignature preservation potential (Golombek et al.,

2012). Rio Tinto shares geochemical and mineralogical similarities with martian regions that were considered in the selection process of NASA’s MSL landing site, such as Syrtis Major, Nili Fossae and Mawrth Vallis. Just like Rio Tinto, those landing sites also contain significant amounts of sulfate, clays and iron oxide minerals (Rogers and Bandfield, 2009; Grant et al., 2011; Golombek et al., 2012). However, direct extrapolation of results obtained from Mars soil analogues into a Mars context is not

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advisable. Rio Tinto is based on a massive iron sulphide deposit and such deposits have not been found on Mars yet. Even if sulphide deposits are found, their distribution around the planet would be probably limited. Also, trace element composition of sulphide deposits may also be important and this should also be taken into account while using Rio Tinto as a Mars analogue.

Ultimately, the variety of results obtained from 10 samples from the Rio Tinto region reinforces not only the importance of a high sampling frequency even within short range, but also an interdisciplinary approach in order to select the best sampling sites for future Mars mission targeting biosignatures.

3.5 - Conclusions

We presented measurements on the mineralogy of ten sediment samples collected in the Rio Tinto region as well as data on carbon, nitrogen and sulfur composition and microbial ecology. This is the first time that enantiomeric separation of amino acids is reported for Rio Tinto sediment samples. Total amino acid abundances range from less than 0.003 ppm (sample RT2) up to 548.2 ppm (sample

RT9). We found no correlation between the mineralogical and sulfur isotope compositions, and the amino acids content. In contrast, amino acid and DNA results were in agreement for sample RT2. Our data showed that clays do not necessarily hinder amino acid extraction. In addition, elemental composition analyses showed that samples with higher amount of total carbon also contain a higher amount of amino

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acids. Samples with the lowest amount of nitrogen contained the lowest amount of amino acids. Furthermore, samples collected in close proximity are not necessarily similar in terms of mineralogical and elemental compositions, pointing towards a high local heterogeneity. The variability and (lack of) relationship between mineralogical profile, microbiology communities and amino acid content of the samples shows the importance of frequent sampling at future landing sites on Mars. These results contribute to deeper insights on how the interplay of different sample properties may affect the detection of biosignatures in a Mars-like environment, and also stress the importance of an interdisciplinary approach in the preparation for future Mars missions such as ESA’s ExoMars2018 or NASA’s 2020 rover.

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Mineralogical composition of lacustrine Mars soil analogues: The acidic ephemeral lakes of Western Australia

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Abstract

The Yilgarn Craton in Western Australia hosts several acidic, ephemeral, hypersaline, shallow lakes that are fed mostly by saline, acidic ground waters, with a sporadic contribution from scarce rainfall runoff. These are thought to represent good analogues of past martian environments. We have used X-ray diffraction (XRD) data to determine the mineralogical assemblage of 27 samples collected from Lake Brown,

Lake Baladjie, Lake Deborah West and Lake Gilmore located in the Yilgarn Craton.

The results show that the mineralogical composition of the four lakes is generally dominated by halite, calcium sulfates, quartz, microcline and Al-rich clays. Scanning electron microscopy (SEM) was used to confirm that iron oxides (hematite, goethite and ilmenite) are present in trace amounts. Our data show spatial heterogeneity in mineral composition within the same lake and between distinct lakes. Several geochemical and mineralogical features were also found to be shared between these lakes and potential future and past landing sites on Mars, including the Burns formation, flat closed basins, craters in Terra Sirenum and other putative ancient lake environments on Mars. Lake Gilmore, in particular, is strikingly similar in terms of mineralogy to Columbus crater. These martian locations could have had shallow, hypersaline, acidic water bodies similar to the acidic lakes in the Yilgarn Craton. Our results improve our knowledge about these lacustrinal Mars analogues and should aid the interpretation of present and future mineralogical results that may be obtained from ongoing and future missions to Mars.

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4.1- Introduction

The Yilgarn Craton is a large region (approximately 1.8 million km2) located in Western Australia, and is characterized by the widespread occurrence of hypersaline, acidic, shallow, ephemeral lakes. Several hundreds of these lakes exist today due to the deposition of sediments in enclosed basins, leading to the formation of playas that overlay a complex network of fluvial incised inset-valleys from the

Eocene found within wider, low-gradient paleodrainage systems formed in the

Mesozoic (de Broekert and Sandiford, 2005). These lacustrinal and fluvial deposits are accompanied by deep weathering profiles. Moreover, the lakes can also be in contact with Archaean bedrocks of granite-gneiss complexes and greenstone belts common in the region (Benison and Bowen, 2006). The limited amount of water is mostly provided by saline, acidic groundwater, with some contribution of scarce rainfall runoff typical from arid/semiarid climate (Benison and Bowen, 2006). The ground waters are usually acidic (pH < 4) with a high concentration of total dissolved solids, including magnesium, sodium, chloride, sulfate, aluminum, iron and bromide (Benison and Bowen, 2006; Bowen and Benison, 2009). The ground water composition, together with desiccation, evaporation and winds, contribute to the unique geological and mineralogical features found on the lacustrine deposits (Benison et al., 2007). The variation of bedrock geology, the overlying weathered deposits and drainage patterns result in considerable variations in mineralogy and sedimentation between even nearby lakes (Genge et al. in preparation, dos Santos et al. in preparation).

Some sedimentary and mineralogical features found in these ephemeral acidic saline lakes have been suggested to be analogous to those found on some martian

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outcrops, including the presence of iron and calcium sulfates and iron oxides (Benison and Bowen, 2006). Bowen et al. (2008) and Benison and Bowen (2006) verified that

Lake Brown could provide a good model for hematite concretion formation that occurred in the Burns formation on Mars (Grotzinger et al., 2005). Similarities between hematite concretions found at Lake Brown and Mars include the hematite content, depositional environment and resulting sedimentary features (Bowen et al.,

2008). Despite differences in terms of concretion size, other secondary phases and distinct bedrock composition (i.e. surface bedrocks on Mars are basaltic, whereas they are predominantly granites, greenstones and gneisses in the Yilgarn Craton), acid saline lakes in Western Australia provide a good model for past environments and hematite concretion formation on Mars (Benison and Bowen 2006, Bowen et al.,

2008).

The occurrence of large numbers of lakes within the Yilgarn Craton provides a unique opportunity to investigate mineralogical variation within ephemeral lacustrine systems. The aim of this work is to improve our knowledge and determine the mineralogical composition of four acidic ephemeral lakes that share geochemical and sedimentary features with ancient closed-basin lake environments on Mars, in particular to examine their mineralogical variation in the context of their sedimentary setting. This chapter provides the mineralogical profiles of 27 samples collected from

Lake Brown, Lake Baladjie, Lake Deborah West and Lake Gilmore during the austral winter (August 2013). The mineralogical composition was determined by X-ray diffraction (XRD) and scanning electron microscopy (SEM) was also used to investigate the abundance and distribution of iron oxide minerals in the samples.

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4.2 - Methods

4.2.1 – Samples and sample collection conditions

A total of 50 samples were collected from eight acidic ephemeral lakes in the

Yilgarn Craton (Western Australia) during the austral winter (from the 11th until the

15th of August 2013) in a five-day campaign (Chapter 2, section 2.2.2.1).

The samples were collected using spatulas that were previously cleaned by wrapping in aluminum foil and heated at 500 ̊C for at least three hours. The collected samples were stored in sterile falcons purchased from Sterilin (UK). From the total set of 50 samples, 27 of those samples were selected to be studied. The selected samples for analyses were collected from Lake Brown, Lake Baladjie, Lake Deborah West and

Lake Gilmore (Chapter 2, section 2.2.2.2). Seven samples were collected from Lake

Brown (samples LB1 to LB7), eight samples were collected from Lake Baladjie

(samples LBa1 to LBa8), four samples were collected from Lake Deborah West

(samples LDW1 to LDW4) and eight samples were collected from Lake Gilmore

(samples LG1 to LG8). For each sampling site, samples were collected at the surface and at 30 cm beneath the surface in order to verify changes in mineralogical profile with depth. Sample LB7 was the only sample collected at 50 cm subsurface. Locations of sample collection were chosen through field observation to sample the diversity of sedimentary environments.

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4.2.2 – Field observations

Representative photos of the four lakes may be found in section 2.2.2.1 in

Chapter 2. Maps showing the sampling sites are provided in Figure 2.6 and Figure

2.7 from section 2.2.2.2, Chapter 2.

4.2.2.1 – Lake Brown

Lake Brown is best described as a roughly elliptical shallow lake located within extensive farmland areas. The observations took place in the southern-eastern section of the lake and we could verify in the immediate surroundings areas of desert scrub associated with vegetated gypsum sands dunes and a sparse Eucalyptus and

Juniper forest. Some gypsum sand and small gypsum crystals were also found in the mudflats, close to the lake shore. However, the abundance of gypsum sand and crystals decreased as we advanced into the mudflats. Some runoff channels were observed in the lake. In its eastern section, the lake is crossed by a road built upon raised embankments. Active halite precipitation was verified to occur in the shallowest and driest sections of the water body. The sediments of the lake were compact mudflats with a red/brown colour, suggesting the presence of iron oxides and clays.

The driest parts of the lake were found to have mudcracks and sections closer to the sand dunes contained faint and poorly defined ripple marks obliquous to the shore.

The sediment profile was fairly constant at the three sampling locations and included an upper 2 cm of thick red clay, followed by approximately a 40 cm layer of thick dark red silty clay and a basal layer of light grey compact clay.

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4.2.2.2 – Lake Baladjie

The observations and sampling of Lake Baladjie took place in the southern section of the lake. Lake Baladjie is a curved, long, elongated lake, surrounded mostly by desert-like scrubs and few farmland dedicated areas. The majority of visible areas of the lake were mostly covered with shallow water due to recent precipitation.

Similarly to what was observed in Lake Brown, the immediate vicinity of the lake was mostly composed of partly vegetated gypsum-sand dunes. The red/brown, clay-like sediment found next to the shoreline contained rain-prints and certain section exhibited a top fine-grained halite crust. Linguoid and sinuous ripples were found slightly further into the lake, parallel to the shoreline. Sinuous ripples were often found being superimposed by linguoid ripples. Approximately 100 m into the lake, large areas were covered by thick halite crusts (approximately 1 cm thickness) were found near the lake water edge. Some halite crusts had a faint pink colour and the sediment profile whilst sampling was mostly consistent, consisting of a 1 cm top layer of red/brown clay grade material, followed by a 4 cm thick red silty mud section that contained gypsum crystals (approximately 1cm in size). These two layers were on sedimented on top of a 15 cm thick grey clay layer, followed by a basal layer with approximately 20 cm of sandy red mud.

4.2.2.3 – Lake Deborah West

Sampling and observations of Lake Deborah West were made close to the southwestern shore of the lake. Relatively close to Lake Baladjie, this lake is also an elongated lake, surrounded by desert-like scrub and some nearby fields that were not

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cultivated. No traces of water were seen whilst observations and sampling took place.

In a similar way to what was observed in Lake Brown and Lake Baladjie, vegetated sand dunes were found whilst approaching the lake shore, as well as poorly defined halite crystals in certain channel and runoff areas. Rain-prints, and some gypsum crystals were also found in the dry red/brown-clay like sediments close to the lake shore. Linguoid ripples preserved in widespread small halite crystals were found throughout the extensive and dry mudflat. During the sampling process it was observed that sediment profile was fairly constant and much less varied than the profiles found in Lakes Baladjie and Brown. The sediment consisted of a uniform brown/red mud and well developed gypsum crystals (some up to 4 cm in size) were found in the subsurface. Water table was found approximately around 15 cm deep.

4.2.2.4 – Lake Gilmore

Lake Gilmore is an elliptical shaped lake, located approximately 45 km south of the town of Norseman, in Western Australia. Lake Gilmore is located mostly in the wilderness, with several minor roads leading to it and a rail track and a national highway passing next to the northwestern region of the lake. The southern areas of the lake contained significant amounts of water. The northwestern part of the lake, where the observations and sampling took place, was characterized by a large mudflat covering an inlet approximately 4 km long by 400 m wide. Sedimentary facies present in the northwestern part of the lake were essentially vegetated gypsum-sand dunes (up to 3 m high). Unlike the three previously described lakes, the sediments from Lake

Gilmore were not brown/red coloured, but pale/gray instead, suggesting an increased amount of gypsum.

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Gypsum-pavements were observed within 30m down the shoreline and consist of cemented muddy-fine sand grey sediment. The pavements generally overlaid ocre muddy sand. The sediment profile observed during sampling was consistent throughout the observed regions and consisted of a thick red-brown mud layer topped by an ocre-gray layer. Sparse gypsum and hematite-like crystals were found down to

30 cm depth.

4.2.3 – XRD analyses

X-Ray diffraction was performed to identify the mineral phases present in coarse, fine and soluble fractions of the sample. The samples were submitted to wet sieving (60 micron) in 2 fractions (coarse and fine). The soluble fraction and fines were then separated by settling in water and subsequent centrifugation. Soluble fraction was studied after 40 ̊C oven evaporation prior to XRD analysis.

Quantifications reported in this chapter account for the relative abundance of each fraction in the total sample. Powder XRD analyses were performed using a

PANalytical X’Pert-PRO diffractometer system (Cu anode and Ni filter) at Instituto

Superior Tecnico (Lisbon, Portugal). Measurements were performed with the following parameters: V = 40 kV, I = 35 mA, 2θ = 5-60º, step size 0.0330º 2θ, scan step time 100 s. X´Pert High Score Plus software, coupled with a PDF4 database, was used to identify minerals in XRD patterns.

4.2.4 – SEM analysis

Four samples (LB2, LB6, LDW1 and LG5) were studied by analytical SEM using a Zeiss EVO at the Natural History Museum (NHM) in London, in order to

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identify mineral phases present in small abundances that could not be detected by

XRD. These samples were chosen due to their intense red to ochre coloration which is often considered indicative of the presence of iron oxide phases. Dried samples were prepared as unpolished grain mounts on probe stubs and were carbon-coated. SEM images were obtained using an accelerating voltage of 15 kV and a beam current of 3 nA in rastering mode. Analyses of unpolished samples are qualitative and small grain- size frequently precludes analysis of individual phases since beam size is ~ 4 m.

4.3 – Results

4.3.1- XRD results and spatial heterogeneity

4.3.1.1 – Lake Brown

X-ray diffraction results obtained for soluble, fine (< 60 µm) and coarse fractions (> 60 µm) of Lake Brown (LB) samples are shown in Table 4.1. Figure 4.1 shows an illustrative XRD pattern obtained for the soluble fraction of sample LB7

(patterns from the remaining 26 samples collected in the four lakes were obtained. The remaining XRD diffractograms for the coarse, fine and soluble fractions of the 27 collected samples are presented in Annex 5). Halite (NaCl) and quartz (SiO2) were identified in all the samples of this lake.

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Figure 4.1: X-ray diffraction pattern obtained from the XRD analysis of the soluble fraction of sample LB7. This XRD pattern is consistent with the presence of halite (Hal) and gypsum (Gy).

Quartz was mostly prevalent in bulk and fine fractions, whereas halite was present in the bulk and soluble phases. Gypsum (CaSO4.2H2O) was detected in all the samples except LB4 (sampled from 30 cm subsurface) and was predominantly found in the bulk fractions. Kaolinite (Al2Si2O5(OH)4) was commonly identified in the fine fractions and was present in all the samples except in the surface sample LB1.

Microcline (KAlSi3O8) was identified in all the samples except LB7 and it was mostly found in the bulk fractions. Other minerals detected include: albite (NaAlSi3O8),

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aragonite (CaCO3), bassanite (CaSO4.0.5H2O), dolomite (CaMg(CO3)2), hexahydrite

(MgSO4.6H2O), illite ((K,H3O)(Al,Mg,Fe)2(Si,Al)4O10[(OH)2,(H2O)]), nacrite

(Al2Si2O5(OH)4), sylvite (KCl) and vanthoffite (Na6Mg(SO4)4).

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Sample LB1 S LB2 LB3 LB4 LB5 LB6 LB7 LBa1 LBa2 LBa3 LBa4 LBa5 LBa6 LBa7 LBa8 name and Sub S Sub S Sub Sub S Sub S Sub S Sub S Sub sitea (50 cm) % soluble 9 6 15 6 10 7 24 7 5 6 8 6 6 10 15

% fines 2 8 2 10 7 17 28 36 9 21 63 24 10 71 27

% coarse 89 85 83 85 84 76 48 56 86 73 29 70 84 19 59

hal, hal, hal, XRD hal, gy, hal, hal, hal, hal, dol, hal, bas hal, gy hal, bas hal, bas hal, bas hal, bas hal, bas hex, solubleb bass bas, hex hex, bas bas hex, v bas syl qz, k, nac, qz, k, qz, k, k, qz, qz, hal, XRD qz, k, qz, k, qz, k, qz, k, qz, k, k, qz qz, hal, k, qz, qz, hal, hal, mic, ab gy, ill, gy, k hal, k, finesb gy ill ill mic, ab hal hal, py k, mic hal, ill k msc/ill, bas mic amph mic, ab mic qz, qz, qz, qz, k, qz, k, k, qz, k, qz, qz, gy, qz, hal, qz, k, qz, hal, k, qz hal, qz, XRD gy, qz, hal gy, hal, k, hal, k, gy, qz, hal, hal mic, hal, mic, hal, k, gy, hal, mic, ab, hal, k, mic, bulkb mic, ara hal, nac mic, hal mic, ab, ab, gy, msc plag, ill, mic mic, k mic, ab k, gy mic ab mic mic gy gy ill mic gy aS- Samples collected at surface. Sub- samples from 30 cm subsurface, unless stated otherwise.

b Mineral names presented with the following designations: ab- albite (NaAlSi3O8), amph – amphibole, ara- aragonite (CaCO3), bass- bassanite (CaSO4 . 0.5

H2O), dol- dolomite (CaMg(CO3)2), gy- gypsum (CaSO4.2H2O), hal- halite (NaCl), hex- hexahydrite (MgSO4.6H2O), ill- illite

((K,H3O)(Al,Mg,Fe)2(Si,Al)4O10[(OH)2,(H2O)]), k- kaolinite (Al2Si2O5(OH)4), mic- microcline (KAlSi3O8), msc- muscovite (KAl2(AlSi3O10)(F,OH)2), nac-

nacrite (Al2Si2O5(OH)4), plag- plagioclase (NaAlSi3O8 – CaAl2Si2O8), py – pyroxene group, qz- quartz (SiO2), syl- sylvite (KCl), v- vanthoffite

(Na6Mg(SO4)4).

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Table 4.2: Results for mineral composition obtained by XRD for the sediment samples collected from Lake Deborah West and Lake Gilmore, in Western Australia. Minerals are written according to their relative abundances (i.e., from the most abundant mineral down to the least abundant mineral).

Sample LDW1 S LDW2 LDW3 LDW4 LG1 LG2 LG3 LG4 LG5 LG6 LG7 LG8 name and Sub S Sub S Sub S Sub S Sub S Sub site a % soluble 7 16 18 8 3 1 4 2 9 3 5 3

% fines 43 48 45 52 15 6 9 6 25 5 21 16

% coarse 50 36 37 40 82 93 87 92 65 93 74 81

hal, hal, XRD hal, bas, hal, ank, hal, bas, hal, gy, bas,arc, hal hal hal hal hex, hal, bas, gy hal, bas solubleb dol, arc hex, arc hex, arc bas hex ank

k, qz, mic, k, qz, mic, qz, alu, k, qz, hal, gy, alu, jar, qz, qz, k, mic, k, qz, mic, qz, alu, qz, k, hal, qz, gy, k, qz, XRD finesb hal, plag, hal, plag, hal, plag, qz, k, hally, ill, k, hal, hally, plag, hal hal, plag k, ill, hal msc, alu, k alu, hal gy amph mic alu, py amph qz, hal, qz, hal, qz, hal, k, qz, gy, gy, qz, hal, qz, hal, k, qz, hal, k, qz, hal, k, qz, hal, k, qz, hal, qz, hal, qz, hal, alu, XRD bulkb k, mic, alu, mic, ill, mic, hal, alu, hally, alu, gy, mic, ab gy, mic, ab gy, mic, ab gy, mic, ab alu, alu jar, hally plag k plag jar jar aS- Samples collected at surface. Sub- samples from 30 cm subsurface, unless stated otherwise.

b Mineral names presented with the following designations: ab- albite (NaAlSi3O8), alu- alunite (KAl3(SO4)2(OH)6), amph – amphibole, ank- ankerite

(Ca(Fe,Mg,Mn)(CO3)2), arc- arcanite (K2SO4), bass- bassanite (CaSO4 . 0.5 H2O) , dol- dolomite (CaMg(CO3)2), gy- gypsum (CaSO4 . 2 H2O), hal- hal (NaCl),

hally- halloysite (Al2Si2O5(OH)4), hex- hexahydrite (MgSO4 . 6 H2O), ill- illite ((K,H3O)(Al,Mg,Fe)2(Si,Al)4O10[(OH)2,(H2O)]), jar- jarosite

(KFe3(SO4)2(OH)6), k- kaolinite (Al2Si2O5(OH)4), mic- microcline (KAlSi3O8), msc- muscovite (KAl2(AlSi3O10)(F,OH)2), nac- nacrite (Al2Si2O5(OH)4), plag-

plagioclase (NaAlSi3O8 – CaAl2Si2O8), py – pyroxene group, qz- quartz (SiO2), syl- sylvite (KCl), v- vanthoffite (Na6Mg(SO4)4).

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Data also show spatial heterogeneity obtained for the LB samples in terms of mineralogical composition. Heterogeneity is also visible between the surface and subsurface samples located at the same site (Table 4.1 and Figure 4.2). For instance, albite, aragonite, bassanite and nacrite were only detected in the surface sample LB1. On the other hand, dolomite, hexahydrite, kaolinite and vanthoffite were detected at 30 cm subsurface in sample LB2 (Table 4.1). Calcium sulfate minerals with different hydration states (bassanite and gypsum) and sylvite were detected in the surface sample LB3, while sample LB4 contained hexahydrite and nacrite instead. Samples LB5 and LB6 differ mainly in the presence of bassanite in the former and illite and hexahydrite in the latter. The higher occurrence of sulfate and chloride minerals in the samples LB1, LB3 and LB5 is related to evaporation of shallow lacustrine waters at the surface, which results in the precipitation of calcium sulfates and potassium chloride. The presence of small amount of amphibole in LB5 sample could be related to the outcrops of granodiorite or monzonite rocks inside of the felsic intrusive or metamorphic complexes.

4.3.1.2 – Lake Baladjie

Lake Baladjie (LBa) samples have broadly similar mineralogy to those of Lake

Brown and are shown in Table 4.1. Quartz, kaolinite, microcline, halite and bassanite were detected in all the samples. Quartz and kaolinite were identified in all the bulk and fine fractions. Halite occurred in all the fractions, whereas microcline and bassanite were mostly in the bulk and soluble fractions, respectively. Albite was identified in five samples, while gypsum was detected in four, both mostly found in the bulk fraction. Other minerals detected less frequently include: hexahydrite, illite,

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muscovite ((KAl2(AlSi3O10)(F,OH)2) and plagioclase (NaAlSi3O8 – CaAl2Si2O8). The variability of mineralogical composition at Lake Baladjie samples is not as large as in the Lake Brown samples. Mineralogical profiles were found to be fairly consistent at all the sampling sites (Table 4.1 and Figure 4.2). Exceptions include the detection of gypsum at the surface sample LBa1 and LBa3, and the absence of this mineral in samples LBa2 and LBa4. Differences between the samples LBa3 and LBa4 also include the presence of albite and illite at the surface (LBa3) and muscovite and diopside (MgCaSi2O6) at the subsurface environment (LBa4). Samples LBa5 and

LBa6 differ in their mineralogical composition, mostly due to the presence of albite in sample LBa5 and illite and plagioclase in the sample LBa6. Samples LBa7 and LBa8 were collected within a shallow body of saturated water that was actively precipitating halite. These samples include illite at the surface, while albite and hexahydrite were found in the subsurface.

4.3.1.3 – Lake Deborah West

The XRD results obtained for the soluble, fine and coarse fractions of the Lake

Deborah West (LDW) samples are provided in Table 4.2. Quartz, kaolinite, halite, microcline, gypsum, arcanite (K2SO4), albite and plagioclase were detected in all the samples. Halite was present in all the fractions, whereas quartz, kaolinite and microcline were identified in the bulk and fine fractions. Arcanite, hexahydrite, and plagioclase were only found in the soluble and fine fractions, respectively. Gypsum and albite, on the other hand, were mainly recognized in the bulk fractions largely as coarse grained material. Fine fraction of LDW2 presents a minor amount of gypsum.

Bassanite, ankerite (Ca(Fe,Mg,Mn)(CO3)2) and hexahydrite were detected more

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frequently in the soluble fractions. Similar to Lake Baladjie, the mineralogical composition in the Lake Deborah West samples was found to be mostly invariable

(Table 4.2 and Figure 4.2). Small differences were found in mineralogical composition of soluble fractions, including hexahydrite in the sample LDW1 and dolomite in the sample LDW2. Sample LDW2 was the only one for which hexahydrite was not detected. In addition, the sample LDW3 contains the carbonate mineral ankerite whereas sample LDW4 was found to have bassanite instead. Bassanite was only absent in the sample LDW3. Amphibole grains are recognized in the fine fraction of LDW4 sample and can be related to the basic rock formations outcropping at the lake margins.

4.3.1.4 – Lake Gilmore

The XRD results obtained for the soluble, fine and coarse fractions of the Lake

Gilmore (LG) samples are provided in Table 4.2. Quartz and halite are the dominant minerals present in samples. Halite was frequently detected in all the fractions, while quartz occurs mostly in the bulk and fine fractions. Alunite (KAl3(SO4)2(OH)6) and kaolinite were detected in six samples and mostly associated with the bulk and fine fractions. Microcline was detected in four samples, while bassanite and plagioclase were found in three samples. Other minerals detected include: muscovite, illite, hexahydrite, halloysite (Al2Si2O5(OH)4), gypsum and ankerite. A higher level of spatial heterogeneity was found in Lake Gilmore (Table 4.2 and Figure 4.2), especially when compared with Lake Baladjie and Lake Deborah West. Despite the absence of alunite in the subsurface sample LG2, samples LG1 and LG2 were found to be very similar in mineralogical composition. This alunite distribution between pairs

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of surface and subsurface samples was also found in the samples LG3 and LG4 (i.e., alunite is not detected in the subsurface). Plagioclase was found only in the following samples: LG1, LG2 and LG4. Samples LG3 and LG4 were the only two samples from this lake to contain illite. Moreover, muscovite was detected only in the sample LG4.

Samples LG5, LG6 and LG8 contained calcium sulfate minerals (gypsum and bassanite) and jarosite (KFe3(SO4)2(OH)6). Gypsum was found in the surface samples

LG5 and LG7. Sample LG6 differs from sample LG5 mostly due to the presence of hexahydrite and ankerite and absence of bassanite and jarosite. Differences in clay mineral composition were found in sample pair LG7/LG8 and the six remaining ones.

Halloysite was detected in the samples LG7 and LG8. In the remaining samples kaolinite was the predominant clay mineral. Those samples, located in the inner part of the lake, contain also ferromagnesian silicates (pyroxene and amphibole group minerals). The Archean bedrock in the area is constituted by undifferentiated felsic intrusive rocks, but locally mafic and ultramafic inclusions are abundant, which can explain the presence of the mafic minerals in the fine fractions of LG7 and LG8 samples.

4.3.2 - Variability of mineralogical composition between lakes

The XRD results indicate that despite the overall similarity of the mineral assemblages found within sediments, a degree of variability occurs between samples from different lakes (Figure 4.2). Lake Gilmore, in particular was found to have a somewhat distinct mineralogical composition from the other three lakes (Lake Brown,

Lake Baladjie and Lake Deborah West). Unique features of Lake Gilmore samples include the presence of alunite, jarosite and halloysite (Table 4.2). Some of the less

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common minerals such as nacrite, aragonite, sylvite and vanthoffite were also only detected in Lake Brown. Carbonate minerals were not observed in Lake Baladjie despite their presence in small amounts in all three other lakes. Noteworthy is also the fact that all Lake Deborah West samples contained arcanite in the soluble fractions.

On the other hand, illite was not identified in any samples from this lake.

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Mineralogical composition of lacustrine Mars soil analogues: The acidic ephemeral lakes of Western Australia

4.3.3 – SEM results

Illustrative SEM images and X-ray spectra for elemental identification obtained from samples LG5 and LDW1 are shown on Figures 4.3 and 4.4 (similar images and spectra were obtained for LB2 and LB6 but are not shown). Analytical

SEM data obtained on samples LB2, LB6, LDW1 and LG5 indicate that samples comprise of a mixture of evaporite crystals within a fine-grained, mud-grade matrix dominated by kaolinite with minor clay minerals, which are probably magnesian smectites.

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Energy dispersive spectroscopy (EDS) was applied to study particles with distinct Fe Klines within spectra. Matrix overlap with surrounding phases, often kaolinite, due to the 4 m spot size, results in spectra with emission lines derived from a mixture of phases. However, the limited solubility of Fe within kaolinite, in addition to the observation of discrete high-Z images within backscattered electron images allows identification of iron-rich phases. Discrete high-Z phases with prominent Fe and Ti Klines can be identified as ilmenite (FeTiO3), whilst those with Fe and Cr as chromite (FeCr2O4). Areas with only Fe could be a range of iron oxides and are identified here as hematite (Fe2O3) where discrete equant grains are observed, or goethite (FeO(OH)), where high-Z areas have sheet-like or acicular habits. Iron- bearing areas that also included Mg, together with Al, Si and O are suggested to be ferromagnesian clay minerals or silicates (amphibole and/or pyroxene particles were identified in few cases by XRD).

The fine-grained matrix exhibits sheet to acicular phases up to 2 μm in length with variable backscattered electron potential. EDS spectra of low backscattered electron potential areas within the groundmass are dominated by Kα peaks of O, Al, Si and are, therefore, dominated by kaolinite. Higher potential areas exhibit significant Fe

Kα peaks in addition to O, Al, Si and K. The low solubility of Fe within kaolinite suggests these areas contain iron oxide phases, whilst the sheet-like morphologies the crystals imply these are hydrated iron oxides, such as goethite. Discrete sub-micron high-Z grains were also observed within the fine-grained matrix. Equant grains, often

<1 μm in size exhibit spectra with intense Fe Kα peaks, suggesting that these are non- hydrated iron oxides such as hematite. The red coloration of the sediment also

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suggests these are probably hematite. Acicular high-Z crystals, up to 2 μm in length, are also present and have spectra featuring Ti and Fe Kα peaks suggesting these are ilmenite. The correlation of the Fe and Ti peak in these areas supports the presence of a Fe-Ti-oxide rather than a Ti-oxide such as anatase. In addition to the matrix, the samples contain abundant halite, present both as cubic crystals >2 μm in size, and within some areas of the matrix. Gypsum was present as tabular crystals, in particular within sediments from Lake Gilmore.

4.4 – Discussion

One of the features of the ephemeral acidic lakes located in Western Australia is the composition of groundwater and lacustrine water, namely the amount of total dissolved solids (e.g., salinity can reach values up to 28 % of total dissolved solids

(TDS)) (Benison et al., 2007). Western Australian lakes are commonly rich in NaMg-

2+ + Cl-SO4 and some degree of variation can be seen in Ca and K concentrations

(Benison and Bowen, 2006). The widespread occurrence of these brines in the Yilgarn

Craton also results in an equally widespread occurrence of minerals such as halite, gypsum, bassanite and (more rarely) hexahydrite, which were detected in sediments of the four lakes analysed in this study (Tables 4.1 and 4.2). During evapoconcentration phases, the precipitation of halite and gypsum occurs in all extreme acidic lakes of the

Yilgarn Craton, although one evaporite mineral tends to dominate over the other

(Benison et al., 2007). In this study we verified that halite is currently the dominant precipitating salt to form in all lakes (Tables 4.1 and 4.2).

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The mineralogy of Lake Brown was previously studied by Benison and Bowen

(2006) and Benison et al. (2007). The authors also reported the precipitation of halite and gypsum at Lake Brown, which were formed through the evaporation of lacustrine brines. In addition, Bowen et al. (2008) reported kaolinite in Lake Brown. This clay was also identified by Benison et al. (2007) exclusively in the subsurface samples of other lakes of the Yilgarn Craton (Lake Aerodrome and Twin Lake West). However, our results show that kaolinite is present both in the surface and subsurface samples of all lakes (Tables 4.1 and 4.2).

Alunite was exclusively identified in the samples collected from Lake Gilmore

(Table 4.2), which is in agreement with results obtained by Alpers et al. (1992) and

McArthur et al. (1989, 1991) who also reported extensive amounts of this mineral in the northwest region of the lake, where our samples were also collected. Furthermore, jarosite was only detected in Lake Gilmore, even though in smaller amounts than alunite, which also agrees with the results described by Alpers et al. (1992).

Additional studies from Lake Aerodrome, Twin Lake West and Lake Walker samples from Western Australia (Story et al., 2010; Benison and Bowen, 2013) show a similar mineralogical profile to those found in the samples collected from Lake

Brown, Lake Baladjie, Lake Deborah West and Lake Gilmore. The similarities between XRD results include the detection of quartz, plagioclase, muscovite, kaolinite, halloysite, halite, gypsum, bassanite, alunite, jarosite, microcline/K-feldspar, albite/Na-feldspar, pyroxene and amphibole remains. On the other hand, hexahydrite, ankerite, nacrite, dolomite, arcanite, sylvite and aragonite were only reported in the samples collected for this work. In addition, Story et al. (2010) detected minerals that

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were not identified in our samples, such as dickite, chlorites, palygorskite-sepiolite, amnesite, rozenite, hydrobasaluminite, marcasite, anatase, gibbsite, calcite, riebeckite

(amphibole), mullite and heulandite-clinoptilotite.

The red colouration of the samples (particularly for Lake Brown, Lake Baladjie and Lake Deborah West samples) suggested the presence of iron oxides. Identification of these minerals was only attained by SEM and this was possibly caused by low concentrations and poor crystallization of these mineral phases. Microscopy observations confirmed the presence of trace amounts of iron oxide minerals

(hematite, goethite, chromite and ilmenite) that are below the detection limits of XRD instrumentation.

In terms of geochemical and mineralogical profile variability, field observations and XRD results show that the assemblage and mineral composition of the lacustrine sediments is relatively consistent within the same lakes, with occasional variations present particularly in the minor phases. The conservation of the mineralogical profile is especially evident in the case of Lake Baladjie and Lake

Deborah West samples. This disagrees with observations by Baldridge et al. (2009) and Story et al. (2010) who verified a general high degree of vertical and lateral variability in other lacustrine sediments from hypersaline lakes in Western Australia.

4.4.1- Origin of Mineral Assemblages

Minerals found in the lacustrine sediments are likely to have four different modes of formation: (1) evaporite minerals, formed by precipitation from saline

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solutions resulting from evapoconcentration; (2) detrital minerals, formed by erosion of bedrock and transport by aeolian and fluvial processes into the lakes; (3) authigenic minerals, formed by diagenetic processes within lake sediments, and (4) pedogenic minerals, formed by weathering of bedrock within deep soil horizons as a result of prolonged exposure to groundwater.

The formation of many of the minerals found in the samples from Lake Brown,

Lake Baladjie, Lake Deborah West and Lake Gilmore is associated with the evaporation of shallow surface water and groundwater. Chloride and/or sulfate salt minerals (such as halite, gypsum and bassanite) are formed in the acidic ephemeral lakes in Australia as evaporite minerals during evapoconcentration phases of Na-Mg-

K-Ca-Cl-SO4 rich brines (Long et al., 1992; Benison and Bowen, 2006; Benison and

Bowen, 2013). Hexahydrite, a hydrated magnesium sulfate, was only detected in the subsurface samples from the four lakes. The detection of this mineral was verified after drying the samples in the laboratory. Therefore, it is not possible to evaluate a likely formation mechanism at sampling sites. This magnesium salt was detected more frequently in Lake Brown and Lake Deborah West, suggesting that Mg is likely more pervasive and/or there is a possible higher amount of magnesium in the ground waters of these two lakes compared to Lake Baladjie and Lake Gilmore.

The study of hypersaline sediments sampled from a similar acidic lake system to that found in the Yilgarn Craton (Lake Tyrell in Australia) show that alunite and jarosite precipitation is the result of evaporitic processes (Long et al., 1992). McArthur et al. (1989, 1991) also verified the same process behind alunite deposition in Lake

Gilmore. Benison and Bowen (2013) likewise reported the occurrence of alunite and

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jarosite in the Western Australian Lake Twin West, Roo Lake and Prado Lake.

Formation of jarosite and alunite is limited to acidic environments, which allow availability and mobility of Al3+ and Fe3+ (McArthur et al., 1991). Such conditions are indeed found throughout the acidic ephemeral lakes of Western Australia.

The XRD results also show the presence of feldspar minerals and quartz in the four lakes analysed. Overall, feldspars were generally less abundant than other minerals (Tables 4.1 and 4.2). Microcline (alkali feldspar) is the most common tectosilicate in the samples, while albite and plagioclase were also detected less frequently (Tables 4.1 and 4.2). The Yilgarn Craton hosts extensive granite outcrops that may contribute to the occurrence of feldspars and quartz in the lake playas as detrital minerals (Myers, 1997). The presence of albite at the surface sample LB1

(Table 4.1), for instance, is more consistent with a detrital origin from surrounding bedrock. It is known that albite can be formed authigenically from brine fluids, although this is more commonly associated with in environments likely to form carbonate rocks (e.g.: Spötl et al. 1999)

Field observations of aeolian dunes proximal to lakes support active transport by wind of particulates at least over short distances. Mud and silt flats, together with channels indicate that fluvial transport from surrounding areas also occurs during transient rainfall. The lack of rock outcrops in the immediate vicinity of lakes and the general deep soil profiles suggests only those minerals that survive pedogenic processing are truly detrital in nature. The detrital origin of feldspars in Lake Brown ultimately agrees with a detrital origin from nearby exposed Archaean intrusive felsic intrusions. Notwithstanding, the formation of authigenic feldspars in acidic

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environments similar to Western Australia acidic lakes is known to occur (Long and

Lyons, 1992; Benison and Goldstein, 2002).

The formation of trace levels of iron oxides such as hematite and goethite

(identified by SEM, Figures 4.3 and 4.4) is mostly related to oxidized iron mobility in the acidic ground waters, which ultimately precipitates iron oxides (Bowen et al.,

2008). Also, the origin of the widespread acidity found in the Yilgarn Craton region may be attributable to multiple factors, including oxidation of sulfides, ferrolysis, putative presence of acidophilic microorganisms, climate and weather, and the lack of significant buffer capacity provided by the intensely weathered Archaean bedrock

(Benison and Bowen, 2015). These facts suggest that hematite and goethite may have a pedogenic origin. Bowen et al. (2008) verified the formation of diagenetic hematite concretions, suggesting that the formation of iron oxides may have multiple origins in the lakes. On the other hand, the presence of ilmenite in sands is mostly associated with a detrital origin (Grigsby, 1992) and its occurrence in the lacustrine sediment samples should be explained by erosion of exposed Archaean bedrock and subsequent aeolian/fluvial transport.

Small amounts of carbonate minerals (ankerite, aragonite and dolomite) were identified in Lake Brown, Lake Deborah West and Lake Gilmore (Tables 4.1 and 4.2).

Precipitation of carbonate minerals is generally considered to be an unlikely event in extreme acidic environments. However, biologically mediated precipitation of carbonate minerals (siderite and ankerite) was verified in another extreme acidic environment, Rio Tinto (Fernández-Remolar et al., 2012). Microorganisms are able to locally change physico-chemical properties, including pH, thus creating

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microenvironments that allow precipitation of carbonate minerals due to formation of mineral nanoglobules associated with bacterial cell surfaces (Sánchez-Román et al.,

2014 and references therein).

The clays identified by XRD were exclusively aluminium-rich phyllosilicates.

Trace amounts of putative magnesium smectite were detected by SEM in sample LG5

(Figure 4.3). Kaolinite was identified in all the lakes in significant amounts.

Halloysite was solely identified in Lake Gilmore. Muscovite was also identified only in one sample from Lake Gilmore (LG4) and another sample from Lake Baladjie

(LG4) and nacrite in two Lake Brown samples (LB1 and LB4) (Tables 4.1 and 4.2).

Illite was detected in all the lakes except Lake Deborah West. Formation of most minerals from the kaolin group is associated with weathering of feldspars, such as k- feldspar and albite or authigenic precipitation from solution (Huang, 1974; Poppe et al., 2002) and thus probably is pedogenic in nature. Nacrite, the rarest mineral from the kaolin group, is often associated as a high-temperature polymorph of kaolinite, although the authigenic precipitation of nacrite at low temperature has also been reported (Bühmann, 1988). Muscovite and illite are usually formed by weathering of feldspars and also alteration of other clay minerals (Poppe et al., 2002). In the context of the geological and geochemical features found during sample collection, formation of illite and kaolin group minerals in the acidic lakes of the Yilgarn Craton may be related to the weathering of abundant feldspars found throughout the lakes

(microcline, albite or plagioclase) and, to a lesser extent, to precipitation from the acidic shallow waters/ground waters. Story et al. (2010) suggests multiple formation pathways for Al-phyllosilicates found in the Lake Aerodrome and Twins Lake,

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including direct precipitation from acid lake waters and shallow acid groundwaters and weathering of feldspars and amphiboles.

The widespread distribution of kaolinite and the lack of detection of smectites by XRD in the four acid lakes analysed is in agreement with several reports on the higher chemical stability of kaolinite in acid solutions. In fact, experiments that exposed Fe and Al-rich smectites (nontronite and montmorillonite, respectively) and kaolinite to acid solutions showed not only that Al-clays are considerably more resilient in acidic environments when compared to Fe-smectite, but also that kaolinite is more stable than montmorillonite in such conditions (Madejová et al., 2009;

Altheide et al., 2010). This is due to the fact that low-pH water in contact with clays will disrupt more quickly the structure of expandable clays due to reaction with the more easily accessible OH groups (Madejová et al., 2009). This agrees with the clay distribution observed in our samples and high abundances of the non-expandable-Al clays kaolinite and illite. Story et al. (2010) also verified that Al-phyllosilicates are the dominant clays identified in Lake Aerodrome and Twins Lake. One fundamental difference between our results and those found in Story et al. (2010) is the fact that moderate amounts of Fe/Mg-clays were reported in Lake Aerodrome and Twins Lake.

This may be due to distinct compositions of respective ground waters and/or variation of surrounding bedrock for these different lakes, which are the most important contributors of ions in these playa systems, at least via deep soil horizons.

4.4.2 - Ephemeral acidic lakes as Mars analogues

The results from XRD and sedimentology features verified during the fieldwork and sample collection show that the ephemeral acidic saline lakes have

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strong similarities with features found on Mars. This was also verified by Benison and

Bowen (2006) who claimed that the acid saline lakes in Western Australia were likely the best known terrestrial analogue for the Burns formation on Mars and martian past environments. Furthermore, the palaeodrainage on which the hypersaline lakes are based upon is remarkably long-lived, with a very stable and widespread weathering profile throughout the Yilgarn Craton. On Earth, this stability is rarely found, given that geological changes occur on timescales of a few million years. Geological change on Mars is likewise very slow, especially owing to the lack of plate tectonics.

With regard to mineralogy, the acidic ephemeral lakes contain several minerals that were detected on Mars, including quartz, plagioclase, muscovite/illite, kaolinite, halloysite, gypsum, bassanite, hexahydrite, alunite, jarosite, ankerite, hematite, goethite and ilmenite (Ehlmann and Edwards, 2014). The sedimentary features found on the acidic ephemeral lakes analysed include gypsum-rich sand dunes, mudflats/sandflats and salt flats typically found in playa/dune systems. These sedimentary features were ubiquitous in the four lakes, with the exception of thick salt flats, which were only verified in Lake Baladjie. Evidence of ancient interdune/playa systems were found on Mars (Grotzinger et al., 2005; Metz et al., 2009; Andrews-

Hanna et al., 2010; Wray et al. 2011). Occurrence of chloride salts was also verified at

Meridiani Planum and Terra Sirenum, including likely interdune/playa systems that share similarities to the acidic ephemeral lakes of Western Australia (Murchie et al.,

2009; Osterloo et al., 2010). In addition to the Burns formation (Grotzinger et al.,

2005), Swayze et al. (2008) and Wray et al. (2011) described geological features and mineralogical profiles from craters located in Terra Sirenum. Alunite and Al-clays

(kaolinite and halloysite) were reported by Swayze et al. (2008) in Cross crater,

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suggesting an ancient closed basin environment that hosted a shallow acidic lake, which suggest strong similarities with the environment present at Lake Gilmore.

The mineralogy of the Columbus crater was described by Wray et al. (2011) and is also strikingly similar to the mineralogical composition of the acidic lakes from the Yilgarn Craton, namely Lake Gilmore, including the presence of gypsum, kaolinite, jarosite, alunite and iron oxides. One of the main differences between the two different mineralogical assemblages is the occurrence of Fe/Mg-clays and absence of halite in Columbus Crater. The absence of NaCl may be explained by the results obtained by the Alpha Particle X-Ray Spectrometers onboard the Mars Exploration

Rovers which suggest that Na is generally less abundant on Mars than Al, Ca, Mg and

Fe (Brückner et al., 2008). The formation of Fe/Mg-clays may be explained by the differences found in the bedrock composition. The Archean bedrock of the Yilgarn

Craton is composed of igneous granite-gneiss complexes and greenstone belts

(Benison and Bowen, 2006). Significantly, the mineralogy of Lake Gilmore reported in this study and Lake Aerodrome differ from the other lakes in this study, and these are located close to Norseman where Mg-rich serpentinised ultrabasic rocks are exposed at the surface (Hill et al., 1995). martian bedrock, on the other hand, is predominantly basaltic (Christensen et al., 2001) which results in a more widespread distribution of Fe/Mg-rich clays (Ehlmann and Edwards, 2014). In addition, the abundance of Al-rich clays is favoured under acidic conditions, which contrast with the basaltic (and more basic) composition of the martian bedrock (Madejová et al.,

2009; Altheide et al., 2010).

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This important difference between the predominant clays in Mars and the acidic lakes in Western Australia emphasizes the limitations of terrestrial Mars soil analogues to fully replicate the geochemical and geological features found on the Red

Planet. Besides the differences in terms of bedrock composition, the long term effects of geological processes, weathering, hydrological cycle and distinct climate between

Mars and Earth have also to be taken into account, especially when using the Mars soil analogues as templates for preparation work in future missions to Mars.

Grotzinger et al. (2005) also considered that, despite the similarities between the two playa/dune/interdune systems, the acidic lakes of Western Australia are considerably smaller than those found on Mars and also lack extensive adjacent sand dune fields. Grotzinger et al. (2005) also suggests that acid-water mineral production in the acidic lakes in Western Australia is not as significant as in other analogues such as Rio Tinto. Rio Tinto may provide a better insight into the mineral formation, although it has a completely dissimilar set of sedimentary processes to the ephemeral lakes (Grotzinger et al., 2005). Despite these dissimilarities, the acid ephemeral lakes of Western Australia provide a valuable base to support future endeavours to the Red

Planet. The acidic lakes analysed here, and Lake Gilmore in particular, show a striking geochemical similarity with ancient shallow lacustrine environments on Mars that may be of considerable interest for astrobiology purposes, such as the closed basins and craters located in Terra Sirenum (Swayze et al., 2008; Wray et al., 2011). In addition, the acid saline lakes should also prove themselves useful for studies regarding different regions that were in contact with saline, acidic water that resulted in the deposition of sulfate evaporites, clays and iron oxides, given the widespread distribution of these minerals on Mars (Ehlmann and Edwards, 2014).

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The occurrence of phyllosilicates and sulfates on Mars is mostly seen as an indication of different climatic conditions that prevailed in distinct martian geological eras. For instance, Bibring et al. (2006), suggested that martian phyllosilicates were formed very early in martian geological history, whereas sulfate formation was mostly confined to the late Noachian and the Hesperian, under more acidic conditions.

Ultimately, the study of the mineralogy of these hypersaline lakes of Western

Australia show that the occurrence of associated phyllosilicates and sulfates on Mars is not necessarily based on drastic events of climate change and both classes of minerals could have been formed simultaneously.

An additional important aspect of our results is the variability of mineralogical composition that was found within the sediment samples collected in the same lake

(particularly in Lake Brown and Lake Gilmore) and also between distinct lakes. Even though this variability was not observed in all lakes (e.g., Lake Baladjie and Lake

Deborah West), the exclusive occurrence of alunite and jarosite on Lake Gilmore and the exclusive hexahydrite precipitation on subsurface samples are examples that point towards the possible existence of playa/interdune system areas with a high variation of high mineralogical composition on Mars. This mineralogical variation may include samples that are closely located, or even surface and subsurface sediments located at the same sampling site. Many processes can influence mineralogical variability in the sediments. For instance, sudden influxes due to runoff can concentrate detrital minerals and/or even separate minerals by density at a given locations.

These variations in mineral assemblage may also include similar variations of habitats available for putative martian life forms within small and closely located

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areas. Future life searching missions to the Red Planet would, most likely, benefit from a high sampling frequency approach in order to maximize success rate.

4.5 - Conclusions

This chapter provides the results of the mineralogical composition, determined by XRD, of 27 samples collected in four ephemeral acidic lakes from the Yilgarn

Craton, Western Australia - Lake Brown, Lake Baladjie, Lake Deborah West and Lake

Gilmore. The variety of evaporitic, authigenic, pedogenic and detrital minerals that were observed in the samples suggest that the mineralogy of the lacustrine sediments from these lakes is complex and influenced by the Archaean bedrock’s composition.

Analysis of the coarse, fine and soluble fractions from the samples show the predominance of evaporitic authigenic minerals such halite and calcium sulfates that result from the deposition that occurs during evapoconcentration of the shallow acidic lacustrine waters and precipitation from saturated acidic ground waters. Other abundant minerals in the lacustrine sediments of the four lakes analysed include quartz and microcline. Non-expandable Al-phyllosilicates (kaolinite, halloysite and illite) were the only clays identified in the sediments due to their stability in acidic environments. Despite the red coloration generally found in the samples, SEM data revealed that iron oxides (hematite, goethite, chromite and ilmenite) were detected only in trace amounts in the four lakes. The XRD results show some spatial heterogeneity of mineral composition between samples collected in the same lake, including surface and 30 cm subsurface samples collected at the same site. In terms of mineral composition between different lakes, Lake Gilmore showed a somewhat

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distinct mineralogical profile, due to the presence of jarosite, alunite and halloysite.

Given the resemblance between the geochemical and sedimentary features of the acidic lakes from Western Australia, similar results in terms of mineralogical composition and spatial heterogeneity should be expected on Mars. This is particularly relevant for the Burns formation, flat closed basins and craters on Mars such as the

Cross and Columbus craters in Terra Sirenum. These locations could have had shallow, hypersaline, acidic water bodies and similar conditions found on the acidic lakes in the Yilgarn Craton. These results contribute to improve and expand our knowledge about the mineralogy of these Mars soil analogues and should prove useful for the interpretation of present and future mineralogical results that may be obtained on ongoing and future missions to the Red Planet.

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Microbial communities and amino acid abundances of the acidic, hypersaline lakes of Western Australia

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Abstract

The detection of life and its organic signatures is the goal of future space endeavours such as ESA-Roscosmos’ ExoMars or NASA’s 2020 rover mission. Preparatory work using Earth soil samples that are analogous to Mars is critical to predict the conditions that these missions may find on the Red Planet. Here, we report the microbial community and abundance of biosignatures (amino acids) present in 27 sediment samples collected from both the surface and subsurface of the ephemeral, shallow, hypersaline lakes from Western Australia which are considered extreme environments analogous to Mars. Seven samples were collected from Lake Brown, eight from Lake

Baladjie and Lake Gilmore and, finally, four from Lake Deborah West. We determined the microbial community (Bacteria and Archaea) composition and biosignature abundance of these samples using 16S rDNA amplicon sequencing

(MiSeq Illumina platform) and gas chromatography-mass spectrometry (GC-MS), respectively. Sequencing results from Archaea and Bacterial DNA showed that all samples had microorganisms and the microbial community present in the samples was generally dominated by putative halophilic archaea and bacteria, with samples from

Lake Gilmore being particularly richer in cyanobacteria. On the other hand, amino acids were detected in six samples and total amino acid abundances in the sediments ranged from values below detection limit (3 parts per billion, ppb), to up to 94,800 ppb. The low occurrence of amino acids in detectable amounts may be caused by the low preservation potential of organic molecules in hypersaline environments and possible adsorption of amino acids onto minerals. Comparison between mineralogical

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and microbiological data seems to suggest that the higher abundance of cyanobacteria in Lake Gilmore may be cause by a somewhat distinct mineral assemblage present in this lake. The possible influence of mineralogy on the results of the microbiology and amino acid analyses needs to be studied in further detail. The results presented in this work provide information on the distribution and abundance of life and respective biosignatures in a Mars soil analogue and are, therefore, of particular interest for future missions such as ESA-Roscosmos’ ExoMars and NASA’s 2020 rover mission, which aim to detect life on the Red Planet.

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5.1- Introduction

Current environmental conditions on Mars include low temperature, extreme aridity, low atmospheric pressure, reactive regolith and a surface exposed to intense levels of full spectrum solar radiation (Fairén et al., 2010; Quinn et al., 2013; Hassler et al., 2014). Despite this combination of harsh conditions, Mars has been the primary target for the search for alien life. This is due to its proximity and evidence of a congenial past environment, including the ability to maintain an Earth-like hydrological cycle and habitable conditions (Craddock and Howard, 2002; Squyres et al., 2004; Grotzinger et al., 2013). On Earth, microbial life can be found in extreme habitats that resemble Mars, such as environments containing high salinity, high radiation levels, aridity and low temperatures (Satyanarayana et al., 2005). The ability of microorganisms to withstand such conditions motivates the search for life beyond

Earth. Alien life detection may be attained by detecting fossils, biofilm deposits, structures that are biologically created, and/or organic molecules related to the cellular machinery (Parnell et al., 2007). Successful alien life detection on Mars is dependent on its own potential to not only harbour signatures of extinct/extant life, but also to confer long-term protection from harsh conditions found on the surface. Organic molecules, including the building blocks of life such as amino acids, are destroyed if they are exposed to the radiation and the reactive/oxidising nature of martian regolith

(Kminek and Bada, 2006; Pavlov et al. 2012; Noblet et al., 2012; Quinn et al., 2013,

Hassler et al., 2014). However, long-term preservation of organic molecules, endolithic microbial communities and respective biosignatures from these environmental constraints may be attained in the subsurface and/or through association

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with minerals (e.g., Aubrey et al., 2006; Kminek and Bada, 2006, Dong et al. 2007,

Summons et al. 2011, Bertrand et al., 2015).

Mineralogy is a feature that affects the abundance and diversity of microbial communities, and also the extractability and preservation of its biosignatures (Röling et al., 2015). Minerals can support life forms by providing nutrients (Mauck and

Roberts, 2007; Carson et al., 2009), and protection from predators and environmental hazards (Hughes and Lawley, 2003; Wey et al., 2008). In addition, minerals may adsorb, preserve, catalyse reactions and affect the extractability and detection of organic molecules (Aubrey et al., 2006; Hazen and Sverjensky, 2010; Martins et al.,

2011, Summons et al., 2011; Direito et al., 2012; Lewis et al., 2015). In fact, the detection of indigenous organic molecules (such as chlorinated hydrocarbons) on Mars by the Sample Analysis at Mars (SAM) onboard NASA’s Curiosity shows that organic molecules can be detected in samples exposed to ionizing radiation and oxidative conditions (Freissinet et al., 2015). This result shows that organic biosignatures may be found if life was ever/is present on Mars.

The acidic ephemeral lakes of the Yilgarn Craton in Western Australia were deemed an ideal analogue for past martian environments, due to the resemblance between their mineralogical and sedimentary features and those found at the Burns formation, flat closed basins and craters such as the Cross and Columbus craters in

Terra Sirenum (Benison and Bowen, 2006, dos Santos et al., in preparation). These acidic saline shallow lakes overlay complex networks of fluvial incised inset-valleys from the Eocene confined within a paleodrainage system from the Mesozoic (de

Broekert and Sandiford, 2005) and Archaean bedrocks, granite-gneiss complexes and greenstone belts (Benison and Bowen, 2006; Bowen et al., 2008). The shallow water

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bodies present on the playas are generally acidic (pH <4) and contain high amounts of total dissolved solids, including magnesium, sodium, chloride, sulfate, aluminium, iron and bromide (Benison and Bowen, 2006, Bowen and Benison, 2009). The sediments of the acidic lakes are composed of significant amounts of halite, calcium/iron sulfates, iron oxides and clays (Benison and Bowen, 2006, Bowen and

Benison, 2009, dos Santos et al. submitted).

In this paper we present for the first time the amino acid composition of 27 sediment samples collected from four lacustrine hypersaline environments located in the Yilgarn Craton (Western Australia): Lake Brown, Lake Baladjie, Lake Deborah

West and Lake Gilmore. We also studied the microbial community structure of these sediments. The mineral composition of these sediment samples has already been described by us (dos Santos et al. submitted). The main goal of this manuscript is to provide a description of the microbial life and respective biosignature abundances in these hypersaline habitats that are geologically and geochemically analogous to past environments that contained liquid water on Mars. The results presented here help us in the preparation of future life detection missions to Mars, such as ESA-Roscosmos’

ExoMars and NASA’s 2020 rover mission, by providing an example of how life and respective biosignatures are distributed in Mars-like environments.

5.2- Methods

5.2.1 – Samples

The 27 samples used in this work were collected from the lacustrinal sediments of four ephemeral lakes in the Yilgarn Craton (Lake Brown, Lake Baladjie, Lake

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Deborah West and Lake Gilmore) during a field trip that took place in the austral winter (August 2013). Full details regarding the fieldtrip, field observations, sample collection procedure, sampling locations and sample details may be found in Chapter

2, sections 2.2.2.1 and 2.2.2.2.

The samples were collected from the surface and subsurface of the lake sediments using spatulas that were previously sterilized by wrapping in aluminum foil and heated to 500 ̊C for at least three hours. After collection of the sediments, samples were stored in 50 mL sterile centrifuge tubes purchased from Sterilin (UK). Soil pH values were measured using a Gardman soil pH meter. The seven samples from Lake

Brown were named Lake Brown 1 and abbreviated as LB1 up to the seventh sample, which was named Lake Brown 7 and abbreviated as LB7. Similar approach was used for Lake Baladjie, where the eight samples were ultimately abbreviated as LBa1 up to

LBa8. The four samples collected in Lake Deborah West were labelled from LDW1 up to LDW4. Finally, the eight samples from Lake Gilmore were labelled LG1 up to

LG8. For each sampling site, surface and 30 cm subsurface samples were collected in order to verify whether results change with depth. Samples with odd numbers were sampled at the surface whereas even numbers means they were collected 30 cm below, which the exception of sample LB7, which was collected at 50 cm below the surface.

5.2.2 - Microbial community profiling

5.2.2.1 – DNA extraction

DNA extraction was performed according to an adapted PowerSoil DNA isolation kit protocol (MO BIO Laboratories, Solana Beach, CA, USA) developed by

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Direito et al. (2012). This adapted method aims to minimize nucleic acid adsorption in environmental samples with low biomass and rich in clay minerals. Negative controls containing only DNase/RNase free water were also performed as quality controls.

5.2.2.2 – 16S rDNA amplicon sequencing and processing

The 16S rDNA amplicon sequencing procedure described in this section was used to study only the Archaea and Bacteria communities. The eukaryotic community has not been studied in this work. PCR reactions were performed on 96-wells plates, and in triplicate for each sample to minimize PCR bias. Each twenty-five μL reaction consisted of 0.5 μL of Phusion Green Hot Start II High-Fidelity DNA Polymerase

(Thermo Fisher Scientific, Sweden), 5.0 μL of 5× Phusion Green HF buffer, 4 μL

DNase- and RNase-free water, 5.0 μL of 10 μM primer mix (1:1), 0.5 μL of 10 mM nucleotide mix and 10 μl of the DNA extract (0.05 ng/μl). The thermal cycling protocol was 98 ̊C form 30 sec, 33 cycles of 98 ̊C for 10 sec, 55 ̊C for 30 sec, 72 ̊C for

30 sec and a final 5 min extension at 72 ̊C. We targeted the V3-V4 region of the 16S rRNA gene, using the V3 forward primer S-D-Bact-0341-b-S-17, 5’-

CCTACGGGNGGCWGCAG-3 (Herlemann et al., 2011), and the V4 reverse primer

S-D-Bact-0785-a-A-21, 5’-GACTACHVGGGTATCTAATCC-3 (Muyzer et al.,

1993), giving rise to fragments of ~ 430 bp. The primers were dual barcoded and were compatible with Illumina sequencing platforms as described previously (Caporaso et al., 2011). Product size and successful amplification was tested by running incorporated positive and negative controls from the triplicate plates on a 1.5 % (w/v) agarose gel. Triplicate PCR products were combined and concentrations were

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determined using a Quant-iT Picogreen (Invitrogen, USA) fluorescence assay. All products were diluted to a concentration of 10 ng.μl-1 prior to pooling all the diluted

PCR products together in equimolar volumes (50 μl) in one composite sample

(including positive and negative controls).

In order to remove primer dimers, 50 μl of the pooled product was run on a 0.9

% (w/v) agarose gel at 40 Volts for approximately 3.5 hours. The band of the expected size was cut out and purified using a Wizard® SV Gel and PCR Clean-Up System

(Promega, USA). The composite samples were paired-end sequenced at the Vrije

Universiteit Amsterdam Medical Center (Amsterdam, The Netherlands) on a MiSeq

Desktop Sequencer with a 600-cycle MiSeq Reagent Kit v3 (Illumina) according to manufacturer’s instructions.

High-throughput sequencing raw data were demultiplexed and processed using a modified version of the Brazilian Microbiome Project 16S profiling analysis pipeline

(Pylro et al., 2014). Quality trimming was done according to the following parameters: quality score > 30, sequence length > 285, no maximum ambiguous bases and no mismatched bases in the primer. Sequences belonging to different samples were demultiplexed using bcl2fastq software version 1.8.4 (Illumina), primers were trimmed using Cutadapt (Martin, 2012) and paired-end reads were joined using

PANDAseq (Masella et al., 2012). Metadata and demultiplexed samples were merged using add_qiime_labels.py (Caporaso et al., 2010) and sequence headers were changed using bmp-Qiime2Uparse.pl (Pylro et al., 2014). UPARSE was used to

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dereplicate, discard OTUs detected less than 4 times and OTU cluster at 97 % similarity (Edgar, 2010, 2013). We filtered chimeras by reference database search using UCHIME algorithm (Edgar et al., 2011) and the SSU rRNA gene SILVA database release 123 (Quast et al., 2013). OTU taxonomy was assigned using the

UCLUST algorithm (Edgar, 2010) on QIIME (Caporaso et al., 2010) using SILVA compatible taxonomy mapping files (Quast et al., 2013) and aligned using SINA

(Pruesse et al., 2012). Taxonomy was manually curated and refined up to genus level based on 95 % similarity of reference sequences. The reference tree was calculated using FastTree 2 (Price et al., 2010). We generated a BIOM file using make_otu_table.py on QIIME (Caporaso et al., 2010). Prior further analysis we produced a OTU table and a taxonomy table using BIOM scripts (McDonald et al.,

2012). OTUs detected in the negative control samples were subtracted from the dataset.

5.2.3 – Amino acid analyses

5.2.3.1- Chemicals and tools

Hydrochloric acid (37 wt%), high performance liquid chromatography

(HPLC)-grade water, and the amino acid standards were purchased from Sigma-

Aldrich. Sodium hydroxide was purchased from Riedel-de Haen. Aluminium hydroxide and 2-aminoheptanoic acid (> 97 %) were purchased from Fluka. AG 50W-

X8 resin (100-200 mesh) was acquired from Bio-Rad. HPLC-grade dichloromethane

(DCM) was purchased from Fisher Scientific. Trifluoroacetic anhydride isopropanol

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(TFAA-IPA) derivatization kit was obtained from Alltech. Copper turnings were purchased from BDH. Pipette tips and eppendorfs were bought sterile. All glassware tools and ceramics used were sterilized by wrapping in aluminium foil and heating for at least 3 hours at 500 ºC.

5.2.3.2 - Extraction, derivatization and GC-MS analyses

One hundred milligrams of the lacustrine sediment samples were used for hot water amino acid extraction, which follows the procedure described by Martins et al.

(2011, 2015). A serpentinite sample provided by the Natural History Museum in Bern was heated to 500 °C for at least 3 hours and used as a procedural blank.

Modifications to the procedure available in Martins et al. (2011, 2015) include a step to remove sulfur from the hydrolysed hot-water extracts, which was performed between the desalting and derivatization steps. This was performed using activated copper turnings (BDH). The activation of the copper turnings was performed using a

10 % HCl solution. The activated copper turnings were added to V-vials containing the desalted residues, previously brought up with 1 mL of HPLC grade water (Sigma-

Aldrich), and left overnight. The copper turnings were then removed and the V-vials were dried under a flow of N2. Derivatized amino acids were dissolved in 75 μL of

DCM. Analyses were performed using a Perkin Elmer Clarus 580 gas chromatograph/

Clarus SQ 8S mass spectrometer. The amino acids were separated using two Agilent

Chirasil L-Val capillary columns (each 25 m, inner diameter 0.25 mm, film thickness

0.12 μm) connected by a zero dead volume connector. Helium was used as carrier gas with a 1 mL/min flow. GC injector temperature was set at 220 °C. Automatic splitless

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mode was used for injection and the oven programme was: 1) 35 °C for 10 minutes; 2)

2 °C per minute increase until 80 °C, hold for 5 minutes; 3) 1 °C per minute increase until 100 °C; and 4) 2 °C per minute increase until 200 °C, hold for 10 minutes (total run time 117.5 minutes). Temperatures for transfer line and the MS ion source were set at 220 °C and 230 °C, respectively. Amino acids present in the samples were identified by comparing the retention time and mass fragmentation pattern to amino acid standard mixtures.

5.3 – Results

5.3.1 –16S rDNA amplicon sequencing and processing (Illumina)

Pyrosequencing results retrieved a total of 58560 reads obtained from 299 sequences. The average number of sequences per sample was 2019 reads, with a standard deviation of 1137 reads (n=29). Operational taxonomic unit (OTU) clustering resulted in 120 known genera based on 97 % sequence similarity.

Total OTUs obtained for all samples clustered within 28 known classes. The relative abundances of the classes found in the four hypersaline lakes can be found in

Table 5.1. The relative abundances of the classes and number of reads retrieved obtained from all the sediment samples are provided in Figure 5.1.

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Lake Lake Lake Lake Brown Baladjie Deborah Gilmore West Acidobacteriales 0.0 0.0 0.0 1.7 Alphaproteobacteria 3.5 1.0 0.5 5.3 Betaproteobacteria 8.1 2.7 0.0 0.1 Clostridia 0.2 1.0 0.0 0.0 Subsection III (Cyanobacteria) 0.9 1.0 0.3 1.9 Chloroplast (Cyanobacteria) 1.3 0.2 0.4 22.3 Cytophagia 18.1 24.9 7.4 7.5 Deltaproteobacteria 0.3 0.4 1.9 0.3 Epsilonproteobacteria 1.6 0.0 0.0 0.0 Flavobacteria 0.6 0.1 0.4 0.0 Gammaproteobacteria 16.0 1.1 29.0 32.8 Halobacteria 38.9 54.5 37.0 10.9 PAUC43f_marine_benthic_group 3.2 2.3 12.0 0.8 Phycisphaerae 0.2 0.2 0.3 0.3 Sphingobacteriia 3.1 0.0 0.0 0.8 Other classesa 0.1 0.3 0.4 0.6 Unknown class 2.3 6.8 1.8 0.0 Unassigned 1.7 3.6 8.5 14.9 Total 100.0 100.0 100.0 100.0 a - Sum of the relative abundances of the following classes: Methanomicrobia, AMV16 class, Thermoplasmata, South African gold mine gp1 (SAGMCG-1), Planctomycetacia, Micrococcales, Acidimicrobia, Lentisphaeria, Anaerolineae, Verrucomicrobiae, Opitutae, Ignavibacteria and Thermomicrobia.

The most represented classes in all the 27 sediments were Halobacteria (36.7

%), Gammaproteobacteria (15.3 %), Cytophagia (13.4 %), Clostridia (7.9 %),

Chloroplast from Cyanobacteria (6.6 %), Alphaproteobacteria (2.5 %),

Betaproteobacteria (2.5 %), PAUc43f marine benthic group (2.5 %), Section III from

Cyanobacteria (1.0 %), Sphingobacteriia (0.9 %), Acidobacteriales (0.5 %),

Deltaproteobacteria (0.4 %), Epsilonproteobacteria (0.3 %), Flavobacteria (0.2 %) and Phycisphaerae (0.2 %). A total of 0.3 % of the obtained sequences were distributed among less abundant classes such as Methanomicrobia, AMV16 class,

Thermoplasmata, South African gold mine gp1 (SAGMCG-1), Planctomycetacia,

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Micrococcales, Acidimicrobia, Lentisphaeria, Anaerolineae, Verrucomicrobiae,

Opitutae, Ignavibacteria and Thermomicrobia. A relative large fraction (6.2 %) of the obtained sequences could not be assigned to either the Archaea or Bacteria domain based on 97 % sequence similarity. A smaller amount of bacterial sequences (2.5 %) could not be assigned to any known class.

The most abundant genera found in the sediment samples are generally related to halophillic microorganisms, such as: Halarchaeum, Haloarcula, Halobacterium,

Haloplanus, Halorhabdus, Halorientalis, Natronomonas, Salinibacter, Rhodovibrio,

Marinobacter and Salinisphaera. Results at the genera level are not provided in this thesis.

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5.3.1.1 - Lake Gilmore

The class abundances in the Lake Gilmore samples are shown in Table 5.1 and

Figure 5.1. Gammaproteobacteria is the most represented class in this lake, clustering

32.8 % of the reads. Chloroplast class from Cyanobacteria has an abundance of 22.3

% (the highest from all the lakes) while Halobacteria contributes 10.9 % of the total reads retrieved from the LG samples (the lowest abundance from all the hypersaline lakes in study). All samples except LG1, LG2, LG3 and LG4 have Halobacteria abundances equal or higher than 20% (Figure 5.1). Samples LG1, LG2, LG3 and LG4 show, instead, a higher contribution from Chloroplast class (Cyanobacteria) and

Gammaproteobacteria (Figure 5.1). In fact, with the exception of sample LG6, significant amounts of Cyanobacteria were detected in all samples from Lake

Gilmore, namely in samples LG1, LG3, LG5 and LG7 which were collected at the surface (Figure 5.1). The abundance of unassigned sequences in Lake Gilmore samples was also generally higher than the remaining lakes (14.9 %, compared to

3.6 % for Lake Baladjie samples, 8.5 % for Lake Deborah West and 1.7 % for Lake

Brown, Table 5.1). The majority of sequences retrieved from Lake Gilmore samples were associated with uncultured microorganisms (uncultured Halobacteria and uncultured Cyanobacteria). Detailed data of relative abundances at the genus level is out of scope of this work, however genera with average abundances higher than 1 % in the Lake Gilmore samples include: Salinisphaera (22 %), Uncultured cyanobacteria

(22 %), Marinobacter (9 %, only detected in sample LG2), uncultured Bacteroidetes from the ML602J-37 family (7 %), Halobacterium (2 %), Halarchaeum (2 %),

Halorhabdus (1 %) and uncultured Acidithiobacillales from the 9M32 family (1 %).

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5.3.1.2- Lake Brown

OTUs obtained from Lake Brown samples clustered most frequently in

Halobacteria (38.9 %, Table 5.1). Other abundant classes present in the LB samples include Cytophagia (18.1 %), Gammaproteobacteria (16.0 %), Betaproteobacteria

(8.1 %), Alphaproteobacteria (3.2 %), PAUC43f marine benthic group (3.2 %) and

Sphingobacteriia (3.2 %). Genera with average abundances higher than 1 % in the

Lake Brown samples include Salinibacter and Methylomonas (both with 13 %), followed by uncultured Halobacteriaceae (9 %), Halorhabdus (8 %), Halorientalis (7

%), uncultured Bacteroidetes (4 %), uncultured bacteria from the PAUC43f marine benthic group (4 %), Rhodovibrio (3 %), Sediminibacterium (3 %), Acidovorax (2 %), uncultured bacteria from the Candidate KB1 division (2 %), Halobacterium (2 %),

Haloarchaeum (2 %), Natronomonas (2 %), Sulfuricurvum (2 %), other

Rhodocyclaceae (2 %), uncultured Rhodocyclaceae (1 %), Acinetobacter (1 %),

Salinisphaera (1 %), uncultured Cyanobacteria (1 %), Flexithrix (1 %) and

Haloplanus (1 %).

5.3.1.3 - Lake Baladjie

Results from Lake Baladjie samples show a trend between surface and subsurface samples in term of Halobacteria and Cytophagia (Figure 5.1). Surface samples were found to have lower abundances of Halobacteria whereas subsurface samples have higher contributions from Cytophagia (Figure 5.1). The average

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abundance of Halobacteria and Cytophagia in LBa samples is 54.5 % and 24.9 %, respectively (Table 5.1). Other relevant classes identified in the LBa samples include

Betaproteobacteria (2.7 %), PAUC43f marine benthic group (2.3 %),

Gammaproteobacteria (1 %) and Alphaproteobacteria (1 %). The most abundant genus present in the sediments of Lake Baladjie was Salinibacter (24 %). Other genera with abundances equal or higher than 1 % include: Haloarcula (16 %), uncultured

Halobacteriaceae (15 %), Halorhabdus (10 %), Halorientalis (7 %), uncultured bacteria from the Candidate KB1 division (6 %), Natronomonas (2 %), uncultured bacteria from the PAUC43f marine benthic group (2 %), Haloplanus (1 %),

Natronoarchaeum (1 %), Rhodovibrio (1 %) and Zoogloea (1 %).

5.3.1.4 - Lake Deborah West

Besides the Halobacteria class, with an average abundance of 37.0 % in LDW samples (Table 5.1), microbial communities at Lake Deborah West include considerable fractions from Gammaproteobacteria (29.0 %), PAUC43f marine benthic group (12.0 %), Cytophagia (7.4 %) and Deltaproteobacteria (1.9 %). In Lake

Deborah West, the majority of sequences belonged to uncultured OTUs. The most abundant genus present in Lake Deborah West samples were from other

Oceanospirillales (16 %), uncultured Halobacteriaceae (13 %), uncultured bacteria from the PAUC43f marine benthic group (12 %), Natronomonas (10 %),

Halorhabdus (9 %), Alcanivorax (7 %), Salinibacter (6 %), uncultured bacteria from

Ectothiorhodospiraceae (5 %) Haloplanus (2 %), uncultured bacteria from the

Candidate KB1 division (2 %) and Rubricoccus (1 %).

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5.3.2 - Amino acid analyses

A summary of amino acid abundances extracted from the sediment samples of the acidic ephemeral lakes described in this work are presented in Table 5.2. Figure

5.2 shows an illustrative single ion GC-MS chromatogram of the derivatized (N-TFA,

O-isopropyl) hydrolysed, hot-water extract of sample LBa5 (single ion GC-MS chromatograms were obtained for all samples but are not shown).

No amino acids were detected in any of the Lake Brown and Lake Deborah

West samples above the detection limit of the instrument (i.e., 3 ppb). Amino acids were detected in samples LBa3, LBa5, LBa7, LBa8, LG3 and LG5. The following amino acids were detected in these lacustrine sediments: D-alanine, L-alanine, L- valine, glycine, L-leucine, D-aspartic acid, L-aspartic acid, D-glutamic acid and L- glutamic acid. Total amino acid abundances range from not detected above the detection limit of the GC-MS, up to 94,880 ppb for sample LBa7 (Table 5.2).

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Table 5.2 – Summary of the amino acid abundances measured by GC-MS (in ppb) from the sediment samples of the acidic lakes from Western Australiaa.

LBa3 LBa5 LBa7 LBa8 LG5 LG7 Remaining samples α-AIB <3 e <3 e < 3 e <3 e <3 e <3 e <3 e

D,L-Isovalineb < 8 e < 8 e < 8 e <8 e <8 e <8 e <8 e

D-Alanine <3 e < 3 e 1360 ± 180 < 3 e <3 e <3 e <3 e

L-Alanine < 3 e 5160 ± 420 7490 ± 430 < 3 e < 3 e 750 ± 40 < 3 e

D- α-ABA <3 e <3 e < 3 e <3 e <3 e <3 e <3 e

L-α-ABA <3 e <3 e < 3 e <3 e <3 e <3 e <3 e

D-Valine <4 e <4 e <4 e <4 e <4 e <4 e <4 e

L-Valine < 3 e 1270 ± 90 2270 ± 70 <4 e <4 e 280 ± 30 <4 e

Glycine 4330 ± 250 13110 ± 1060 22130 ± 240 800 ± 30 2750 ± 30 1500 ± 60 < 6 e

DL-β- AIBb,c <8 e <8 e <8 e <4 e <8 e <8 e <8 e

DL-β- ABAb,c <8 e <8 e <8 e <4 e <8 e <8 e <8 e

D- Norvaline <3 e <3 e < 3 e <3 e <3 e <3 e <3 e

L- Norvaline <3 e <3 e < 3 e <3 e <3 e <3 e <3 e

β-Alanine <7 e <7 e <7 e <7 e <7 e <7 e <7 e

D- Leucine <4 e <4 e <4 e <4 e <4 e <4 e <4 e

L-Leucine <4 e <4 e 3270 ± 350 <4 e <4 e <4 e <4 e

D-Norleucine <3 e <3 e < 3 e <3 e <3 e <3 e <3 e

L-Norleucine <3 e <3 e < 3 e <3 e <3 e <3 e <3 e

γ-ABA <7 e <7 e <7 e <7 e <7 e <7 e <7 e

D-Aspartic acid 1520 ± 200 2790 ± 100 12010 ± 510 <4 e <4 e 1250 ± 30 <4 e

L-Aspartic acid 2470 ± 70 8640 ± 480 26120 ± 1540 <4 e <4 e 1630 ± 50 <4 e

D-Glutamic acid <5 e 1350 ± 50 2420 ± 210 <5 e <5 e <5 e <5 e

L-Glutamic acid 1940 ± 30 8440 ± 300 17810 ± 1450 <5 e <5 e 1410 ± 40 <5 e

TOTALd 10260 40760 94880 800 2750 6820 a- Amino acid quantification includes background level correction using a serpentinite blank. Associated errors were calculated using standard deviations of the average values for six to eight measurements (N) with a standard error δx=σx. N-1/2. b- Enantiomeric separation not possible under chromatographic conditions. c- Optically pure standard not available for enantiomeric identification. d- Total amount of detected amino acids. e- These concentrations are upper limits and were not included in the total amino acid concentration.

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relative abundance

Figure 5.2: Single ion GC-MS chromatograms (20 to 85 minutes) of the derivatized (N-TFA, O-isopropyl) amino acids extracted from sample LBa5 (m/z 126, 140, 154, 168, 182, 184, and 198). Figure legend is as follows: 1) L-alanine; 2) L-valine; 3) glycine; 4) D-aspartic acid; 5) L-aspartic acid; 6) D-glutamic acid; 7) L-glutamic acid; 8) internal standard (D-2-aminoheptanoic acid); 9) internal standard (L-2- aminoheptanoic acid).

5.3.3 – Mineralogy and pH of the sediment samples

The mineralogy results of the 27 samples analysed here was determined by our

team (dos Santos et al. in preparation), and results are summarised here in Tables 4.1

and 4.2 in Chapter 4. The pH of the sediment samples, which is a relevant factor in

understanding the life present in the samples may be found in Table 2.2 in Chapter 2.

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5.4 - Discussion

5.4.1 – Microbial communities in the sediment samples of the saline lakes of Western Australia

The environment at the four lakes that were analysed in this study is mainly dominated by hypersaline and, with the exception of Lake Deborah West, slightly acidic habitats. The mineralogy of the four lakes is mostly dominated by halite, calcium sulfates (gypsum and bassanite) kaolinite, microcline and quartz (Chapter 4).

The mineralogical assemblage found in the lakes is mostly composed of salts and this is the result of the evaporation of the lacustrinal brines with high salinities.

Salinity is a powerful stressing environmental constraint for soil microorganisms and has a strong effect on the composition of microbial communities

(Sardinha et al., 2003). The results obtained from 16S rDNA pyrosequencing show that the microbial communities present in the sediment samples collected from the four hypersaline lakes in this study are largely dominated by halophilic archaeons and halophilic bacteria. Halophilic organisms are extremophiles that thrive in high salt concentrations and their dominance in the lacustrine sediments reflects the natural selection that salinity imposes in these hypersaline habitats. The ephemeral character of the lakes explains the occurrence of a variety of halophilic microorganisms that have distinct salinity tolerances and salt requirements. For instance, species from

Haloplanus have optimal growth with salinities ranging from 12-17 % (w/v) of NaCl, whereas Halorientalis’ and Halobacterium’s optimum growth fall within a range of

20-25 % (w/v) of NaCl (Oren et al., 2009; Qiu et al., 2013; Amoozegar et al., 2014).

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Furthermore, the occurrence of non halophilic genera and other genera that only tolerate low amounts of salt (e.g., Methylomonas) in the lakes is most likely caused by the rainfall that occurred shortly before sample collection in the lakes (dos Santos et al., in preparation). It is known that precipitation, particularly in arid areas such as the

Yilgarn Craton in Western Australia, causes shifts in the microbial community diversity and composition (Clark et al., 2009). As a result, the rainfall verified to occur in the hypersaline lakes immediately prior to sample collection may have caused shifts in salinity values and created more congenial conditions (i.e., less saline) for these non halophilic species to grow. In addition, the distribution and abundance of different halophilic microorganisms in ephemeral environments is not only dependent on meteorological events that change salinity. The water geochemistry should also play an important role as some genera identified in the lacustrine sediments also require significant amounts of magnesium for optimal growth, such as Haloarcula,

Halobacterium and Halorientalis (Oren et al., 2009; Namwong et al., 2011;

Amoozegar et al., 2014).

Besides salinity and water geochemistry, microorganisms also have to adapt to pH in these habitats. The majority of the genera found in the lacustrine sediments are associated with slightly acidophilic microorganisms. This agrees with the average values of soil pHs observed for Lake Brown, Lake Baladjie and Lake Gilmore (5.3,

6.2 and 6.1, respectively, dos Santos et al., in preparation). In addition, the higher average pH values obtained measured in Lake Deborah West sediments (average pH =

6.9, dos Santos et al., preparation) reflect the higher abundance of Natronomonas, which are slightly alkilophilic archaeons. Furthermore, Marinobacter, which

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comprises halophilic bacteria that prefer neutral pH, was only identified in sample

LG2. The occurrence of Marinobacter in a slightly acidic sediment may be related to the rainfall event that occurred during the month of July, just prior to sample collection (53.4 mm of rainfall, dos Santos et al., in preparation). Rainfall likely increased the pH in these sediments to more neutral values that Marinobacter requires to thrive. Mormile et al. (2009) also observed the presence of Marinobacter in the slightly acidic waters from Dead Kangaroo Lake (pH = 4.6). This suggests that another possibility for the occurrence of Marinobacter in Lake Gilmore may be actually related to new similar species within this genus that may actually withstand more acidic pH values.

According to Figure 5.1, the taxonomic distribution in samples LG1, LG2,

LG3 and LG4 is distinct to that found on the remaining samples of Lake Gilmore and the other three lakes. The abundances of Halobacteria are significantly lower on samples LG1, LG2, LG3 and LG4. We have no information regarding the salinity of the lakes and sampling sites during collection2. Despite that, samples LG1, LG2, LG3 and LG4 have on average a lower soluble fraction (i.e., deposited salts) than samples

LG5, LG6, LG7 and LG8. This suggests that changes in the microbial community may be caused by mineralogy and geochemistry variation. The influence of mineralogy in the structure and composition of microbial communities was verified by Boyd et al.

(2007) and Carson et al. (2009). The interplay between mineralogy and microbial communities is out of scope of this present paper. Further work is underway in order

2 This was due to lack of equipment and the fact that it was not planned to carry out such studies in such a small timescale.

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to study in detail the variation of the microbial communities with the geochemical and mineralogical features of these hypersaline lakes.

A comprehensive study of the microbial community from water samples collected in acidic, neutral and alkaline lakes from Western Australia was carried out by Mormile et al. (2009). Sequencing results from water samples collected from Pink

Lake, King Lake and Dead Kangaroo Lake include closely related sequences to species belonging to some of the most abundant genera also present in our sediment samples: Marinobacter, Salinisphaera, Rhodovibrio and Salinibacter. Despite this agreement, one must note that our results are based on the microbial community present in the lacustrine sediments, whereas the results obtained by Mormile et al.

(2009) are based on the aquatic planktonic community. Acidophilic, halophilic and halotolerant microorganisms were also identified in other salt lakes in Western

Australia. For instance, Conner and Benison (2013) verified that acidophilic halophilic microorganisms were present within fluid inclusions in halite crystals from Lake

Magic.

Another study performed by Johnson et al. (2015) using sediments from an acidic unnamed lake near Grass Patch (Western Australia) also revealed a notable presence of acidophilic, halophilic microorganisms belonging to the Halobacteria class and cyanobacteria. Johnson et al. (2015) also identified genes associated with sulfur metabolism (i.e., conversion of sulfate to adenylylsulfate and the subsequent production of sulfide from sulfite or oxidation of sulfide, elemental sulfur, and thiosulfate). In our work we verified that Sulfuricurvum was present in the Lake

Brown sediments (namely in samples LBa3 and LBa7, results not shown).

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Sulfuricurvum was also detected in very low amounts in two samples from Lake

Baladjie (LBa1 and LBa8, results not shown). This genus includes until now a single species, Sulfuricurvum kujiense, which is a facultative anaerobic, chemolithoautotrophic, sulfur-oxidizing bacterium described by Kodama and

Watanabe (2004). Sulfuricurvum kujiense’s optimal growth requires neutral pH and the species is negatively affected by the presence of NaCl (Kodama and Watanabe,

2004). Therefore, our results suggest the occurrence of a new halotolerant or halophilic, putative acidophilic Sulfuricurvum species. The presence of sulfur- oxidizing bacteria in the lacustrinal hypersaline habitats is environmentally relevant because their metabolism has been proposed as one of the origins for the acidity found throughout the ephemeral lakes of Western Australia, due to the oxidation of sulfides distributed in the Yilgarn Craton (Benison and Bowen, 2015).

5.4.2 – Comparison with other hypersaline environments

The majority of studies focused on microbial communities from hypersaline environments were performed in thalassohaline environments that result from seawater evaporation (Ma et al., 2010). These thalassohaline environments reflect the ionic composition of seawater and usually have a nearly neutral to slightly alkaline pH

(Ma et al., 2010). Cases of hypersaline environments that are neutral/slightly acidic are the Dead Sea in Israel (Bodaker et al., 2009), some athalassohaline lakes in the

Atacama Desert, Chile (Demergasso et al., 2004) and the hypersaline Aran-Bigdol lake in Iran (Makhdoumi-Kakhki et al., 2012). Bodaker et al., (2009) observed that the planktonic microbial community was also dominated by Halobacteria. The microbial communities present in the sediment samples used in our work and the water from the

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Dead Sea have in common the occurrence of Halorhabdus, Haloplanus and

Natronomonas (Bodaker et al., 2009). On the other hand, Demergasso et al. (2004) verified that the acidic lakes in the Atacama and Ascotan regions (Chile) had also a microbial community dominated by unidentified clones from Haloarchaea and

Proteobacteria. The hypersaline Aran-Bigdol lake in Iran contains zones of neutral and slightly acidic environments and the brines collected at this hypersaline lake were found to be also inhabited by Haloarcula, Natronomonas, Halorientalis, Halorhabdus,

Salinibacter, Rhodovibrio and Cyanobacteria (Makhdoumi-Kakhki et al., 2012).

5.4.3- Amino acid abundance and relation to the mineralogy and microbiology content

The amino acid distribution observed in the samples collected at the four hypersaline lakes in Western Australia is similar to those verified in other Mars soil analogues sediments (e.g., Martins et al., 2011 and references therein). The main differences between our results and those from Martins et al., 2011 (which report amino acids distribution and abundances from samples collected from the Mars Desert

Research Station (MDRS), Utah, USA) are the detection of D-aspartic acid in the

MDRS soils and absence of D-leucine in the hypersaline sediments analysed in this work. In addition, the amino acid distribution suggests that the amino acids detected are associated with extinct life forms. This is verifiable in the results presented in

Table 3 that show a mixture of L- and D-enantiomers for samples LBa 3, LBa5, LBa7 and LG7. This indicates that racemization of L-enantiomers has taken place, pointing towards amino acids associated with life forms that were already dead.

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The results from the amino acid analyses are generally not in agreement with the data set obtained from microbiology studies. Similarly, the same lack of relationship between DNA extraction and amino acid abundance in the sediments was verified by Ehrenfreund et al. (2011) using soils from the MDRS. In this work, DNA extractions were successful for all the sediment samples analysed, confirming the presence of microbial life. Amino acids are the building blocks of proteins and are generally the most abundant class of organic molecules in the cell, making up around

55 % of the dry weight of E. coli (Brock et al., 1984). Therefore, amino acids from the proteins associated with microbial life forms should have been detected in all sediment samples. In addition, amino acids are known to be a particularly important class of organic molecules for the metabolism of some halophilic microorganisms (Anderson et al., 2011). For instance, Halobacterium salinarum has complex nutritional needs and cultivation requires complex media that may include 15 amino acids (Gonzalez et al., 2007). Haloarchaea are known to incorporate several amino acids such as alanine, aspartate, glutamate, glycine, valine and leucine in degradative pathways (Gonzalez et al., 2007; Anderson et al., 2011). Amino acids such as glutamate may also serve as a compatible solute for osmotic adjustment for microorganisms living in hypersaline environments (Santos and da Costa, 2002). Taking this into account, amino acids should be available in the sediments to support the microbial communities that inhabit the hypersaline systems of Western Australia.

Despite the presence of microbial life in the lacustrine sediments, saline systems are known to be inefficient in terms of preservation/retention of organic matter and soil organic carbon (Wong et al., 2010). For instance, free amino acids are rapidly degraded in seawater (i.e., saline) environments (Bada and Lee, 1977). Wong

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et al. (2008) verified that saline and scalded (i.e., bare, non-vegetated) soils have lower organic carbon than soils that were vegetated and less saline. Scalded and saline surface habitats like the hypersaline lakes in Western Australia are more prone to soil dispersion, erosion and leaching, which contribute to low levels of biomass accumulation and depletion of the organic carbon content (Wong et al., 2010). The hypersaline shallow lakes are located in arid environments and the superficial sediments are particularly susceptible to aeolian processes. These aeolian processes associated with aridity may also remove overlying sediment and expose deeper layers to the surface, which then may be later covered again. This shows, therefore, the potential effect that surface process associated with aridity may have in a sedimentary profile. These processes are particularly relevant during periods of desiccation, resulting in increased erosion that most likely contributes to reduce the quantity of organic carbon in the soils.

The general lack of amino acid detection in the sediment samples is most likely a combination of multiple factors, hence the difficulty to establish correlations of biosignature abundance and microbiology/mineralogy data. Together with the known lack of preservation/retention of organic matter in these hypersaline soils, the lack of detectable amino acids in the majority of the sediment samples may also be in part related to adsorption of amino acid to the mineral phases. It is known that biomolecules may be strongly adsorbed to mineral phases (e.g., Direito et al., 2011).

Furthermore, the amount of time used for the amino acid hot-water extraction procedure, 24 hours, is long enough for significant amino acid adsorption to take place. For instance, kaolinite was present in the majority of samples and is known to

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adsorb acidic amino acids such as aspartic acid and glutamic acid (Hadges and Hare,

1987). On the other hand, results from Hadges and Hare (1987) also indicate that amino acids such as alanine, valine and leucine are not adsorbed by kaolinite. A broad study based on the adsorption of multiple amino acids to different minerals is needed in this particular case. Such a study should take into account at least two important factors. One is related to the multiple adsorption mechanisms that are possible between organic molecules and minerals. Adsorption will be affected by the nature of the interactions between organic molecules and minerals, mineralogical properties and concentration of molecules to be adsorbed. Important environmental factors such as pH and salinity in the amino acid adsorption phenomena should also be analysed in order to better understand the adsorption phenomena in a natural extreme setting. The effect of mineralogy on amino acid adsorption is, therefore, out of the scope of this work, due to the high complexity and variability of the mineralogical profile and environmental conditions present in the lacustrinal sediment samples.

5.4.4- Implications for Mars

The detection of organic signatures of life on Mars is a complex endeavour that needs to take into consideration multiple aspects. Biosignature detection in extreme environments where halophilic microorganisms are able to thrive may not be trivial, particularly for the amino acids case. With the exception of 6 samples (LBa3, LBa5,

LBa7, LBa8, LG5 and LG7), no amino acids could be detected above the detection limits, despite the presence of life in all 27 sediments. Two important ideas should be highlighted from our results. First, the dissimilarity verified between amino acid and

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microbiology analyses stress the importance of using an interdisciplinary approach in future life-searching missions based on biosignature detection. In this work we verified that the absence of biosignatures in a sample is not a guarantee of the absence of life. Second, the different results obtained between samples that were closely collected (including surface and subsurface samples) suggest that high sampling frequency should be performed in future missions even in a small candidate sampling areas. In addition, the apparent lack of correlation verified between microbiology and biosignature analysis also observed in other Mars soil analogues (which was also verified by Ehrenfreund et al., 2011) illustrates the complexity behind the search of biosignatures on Mars. The complexity of such an endeavour would be also increased by the limited amount of scientific instrumentation that can be transported to Mars and the resulting reduction of the analytical possibilities that can be applied in situ to martian samples. Furthermore, the combination of relevant chemicals in the martian soil (such as perchlorates and sulfates) and pyrolysis GC-MS based techniques are known to contribute to biosignature degradation (Navarro-González et al. 2010, Lewis et al. 2015).

In terms of microbiology analysis results, we verified that halophillic microorganisms were the most represented life forms in evaporate-rich sediments on these Mars analogues. The ability of halophile life forms to withstand complex sets of environmental stresses in Mars-like environments, suggest that similar types of microorganisms (i.e., with the ability to withstand high salinities) may have existed/exist on the Red Planet. On Earth, some halophilic microorganisms are able to use perchlorate as an electron acceptor for anaerobic growth (Oren et al., 2014) or

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perform CO oxidation in conditions similar to those found in the recurring slope lineae on Mars (King et al., 2015).

Further limitations of the hypersaline lakes of Western Australia may include the ionic content of the lacustrine waters. Despite some similarities in terms of the composition of the microbial communities between various hypersaline lakes

(mentioned in section 5.4.2), one of the main differences between, for instance, the

Dead Sea and the hypersalines lakes from Australia and Atacama is the ionic composition of the water bodies. Minerals found on Mars indicate that the brines in the planet are thought to be richer in divalent ions such as Ca2+, Mg2 than monovalent ions such as Na+ (Ehlmann and Edwards, 2014). The water from the Dead Sea is richer in divalent ions (Ca2+, Mg2+) than the waters found in the hypersaline lakes from

Australia and Atacama and results in a more extreme environment due to lower water activity values (Bodaker et al., 2009). Water activity values for the Dead Sea are approximately 0.67 (Lensky et al. 2005). Mormile et al. (2009) verified that Lake

Magic surface waters in 2006 (at halite saturation point and with a pH of 1.9) had a water activity value of 0.79. Water activity is an important aspect for life and, according to Rummel et al., (2014), there is no evidence of either cellular proliferation or cellular metabolism taking place on Earth below a water activity value of 0.60.

Even though liquid water was found on Mars, its water activity was considered too low to support microbial life (Martín-Torres et al., 2015). Despite the extreme nature of the hypersaline lakes of Western Australia, and the fact that the water activity values may decrease during desiccation periods, the presence of saline hypersaline systems with lower water activity values and higher concentrations of divalent ions

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suggest that other hypersaline lakes may be more adequate to study the limits of microbial survival under saline stress.

Another important factor to take into consideration is the fact that no present

Mars analogue can replicate completely any environments that are/were present on the

Red Planet. For instance, the acidic lakes from Western Australia, despite their relevance as analogues for Mars, may pose some limitations in terms of mineralogy due to the predominance of halite and kaolinite (dos Santos et al., in preparation) minerals. This contrasts with the general widespread occurrence of sulfates and

Fe/Mg-smectites on the Red Planet (Ehlmann and Edwards, 2014). The mineralogical profile of these samples results in the fact that the acidic lakes from Western Australia are analogues to very specific martian locations, such as the Burns formation, flat closed basins and craters on Mars such as the Cross and Columbus craters in Terra

Sirenum (dos Santos et al., submitted).

Overall, our set of results obtained from the hypersaline lacustrinal sediments of

Western Australia provide a practical example of the difficulty behind biosignature detection in an inhabited extreme environment that is analogous to Mars. Future missions to the Red Planet, such as such as ESA-Roscosmos’ ExoMars and NASA’s

2020 rover, should take into consideration that the absence of biosignatures in detectable amounts does not necessarily indicate the absence of life. As a result, similar outcomes may be expected and this fact may be minimized using an interdisciplinary approach on Mars, ultimately leading towards a better understand of

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possible distribution of life and respective biosignatures in future candidate sampling areas.

5.5 - Conclusions

In this work we presented the composition of the microbial community and amino acid abundances of 27 sediment samples collected from four ephemeral saline lakes from Western Australia (Lake Brown, Lake Baladjie, Lake Deborah West and

Lake Gilmore) that are analogues to Mars. Application of 16S rDNA amplicon sequencing revealed that halophilic archaea and bacteria are the most dominant microorganisms present in the sediments, although the eukaryotic community has not been investigated. The samples from Lake Gilmore had in general lower amounts of

Halobacteria and higher amounts of Cyanobacteria when compared to the other three lakes. This may be caused by a distinct mineralogical profile and higher amount of mineral salts in these samples, although further work needs to be performed to establish any correlation between mineralogy and composition of microbial communities in these hypersaline environments. Even though microbial life was detected in all sediments, amino acids were only detected in 6 samples from Lake

Baladjie and Lake Gilmore. Total amino acid abundances ranged from not detected

(i.e., below 3 ppb) to up to 94,800 ppb for sample LBa7. The lack of detectable amino acids in samples that contained microbial life shows that biosignature detection in extreme habitats on Earth may not be straightforward. This lack of amino acid detection needs further assessment, but may be caused by the low ability of the hypersaline systems to preserve organic molecules combined with adsorption of the

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Microbial communities and amino acid abundances of the acidic, hypersaline lakes of Western Australia

molecules onto minerals. We verified that closely located samples yielded very different results. This indicates that a high sampling frequency strategy would be advantageous even in small areas. Successful detection of biosignatures on Mars should be even more difficult especially if we take into account the limitations of analytical possibilities that can be deployed on the Red Planet. Our amino acid and microbiology analyses results using the lacustrinal sediments from Western Australia provide a practical example of how biosignature detection in an extreme environment may be challenging, even if life is present. Our results show that lack of biosignature detection may not be caused by absence of life. Therefore, an interdisciplinary approach and further studies using Mars soil analogues are needed in order to have a better understanding of the possible outcomes that may arise from future life-searching missions to the Red Planet.

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Influence of mineralogy on the preservation of amino acids under simulated Mars conditions

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Abstract

The detection of organic molecules associated with life on Mars is one of the main goals of future life searching missions such as the ESA-Roscosmos ExoMars and

NASA 2020 mission. In this work we studied the preservation of 25 amino acids that were spiked onto the Mars-relevant minerals augite, enstatite, goethite, gypsum, hematite, jarosite, labradorite, montmorillonite, nontronite, olivine and saponite, and on basaltic lava under simulated Mars conditions. Simulations were performed using the Open University Mars Chamber, which mimicked the main aspects of the martian environment, such as temperature, UV radiation and atmospheric pressure.

Quantification and enantiomeric separation of the amino acids were performed using gas-chromatography-mass spectrometry (GC–MS). Results show that no amino acids could be detected on the mineral samples spiked with 1 μM amino acid solution (0.1

μmol of amino acid per gram of mineral) subjected to simulation, possibly due to complete degradation of the amino acids and/or low extractability of the amino acids from the minerals. For higher amino acid concentrations, nontronite had the highest preservation rate in the experiments in which 50 μM spiking solution was used (5

μmol/g), while jarosite and gypsum had a higher preservation rate in the experiments in which 25 and 10 μM spiking solutions were used (2.5 and 1 μmol/g), respectively.

Overall, the 3 smectite minerals (montmorillonite, saponite, nontronite) and the two sulfates (gypsum, jarosite) preserved the highest amino acid proportions. Our data suggest that clay minerals preserve amino acids due to their high surface areas and small pore sizes, whereas sulfates protect amino acids likely due to their opacity to UV radiation or by partial dissolution and crystallization and trapping of the amino acids.

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Minerals containing ferrous iron (such as augite, enstatite and basaltic lava) preserved the lowest amount of amino acids, which is explained by iron (II) catalysed reactions with reactive oxygen species generated under Mars-like conditions. Olivine (forsterite) preserved more amino acids than the other non-clay silicates due to low or absent ferrous iron. Our results show that D- and L-amino acids are degraded at equal rates, and that there is a certain correlation between preservation/degradation of amino acids and their molecular structure: alkyl substitution in the α-carbon seem to contribute towards amino acid stability under UV radiation. These results contribute towards a better selection of sampling sites for the search of biosignatures on future life detection missions on the surface of Mars

6.1 – Introduction

The detection of organic molecules associated with extraterrestrial life has been primarily focused on Mars due to its proximity to Earth, evidence of a congenial past environment and potential to support microbial life (Westall et al., 2013).

Increasing evidence from NASA’s Opportunity and Curiosity rovers obtained at different locations indicates that the Red Planet could have indeed supported life at the surface in the past (Arvidson et al., 2014; Grotzinger et al., 2014). Furthermore, the detection of silica-rich deposits by the Spirit rover in the Gusev crater is also an indication of an environment able to support life (Des Marais 2010; Ruff et al., 2011;

Squyres et al., 2008). It is also plausible that life developed underground and biosignatures reached the surface (Michalski et al., 2013). Despite this, the environmental conditions that prevail now on Mars’ surface are not congenial to life or

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to the preservation of biosignatures. Two of the factors contributing to the harsh current martian environmental conditions are the thin atmosphere and the absence of a significant magnetosphere (Fairén et al., 2010), resulting in the inability to attenuate the intensity of the multiple forms of radiation that reach the planet, such as solar UV radiation, galactic cosmic rays and solar energetic particles (Cockell et al., 2000;

Hassler et al., 2014). As a result, the martian regolith is exposed to intense levels of radiation, contributing to the reactivity of the soil which may destroy potential martian life and degrade organic molecules (Dartnell et al., 2007; Quinn et al., 2013). UV radiation leads to the formation of radical species (e.g. reactive oxygen species such as superoxide and hydroxyl radicals) by photochemical processes, which cause degradation of any potential organic compounds present on Mars (Benner et al., 2000;

Georgiou et al., 2007, Georgiou et al., 2015; Yen et al., 2000).

Amino acids, which are the building blocks of proteins and considered important target molecules in future life-searching missions (Parnell et al., 2007), are known to be subjected to degradation by UV radiation (Garry et al., 2006; Noblet et al., 2012). A 1.5-year exposure of homogeneous thin films (1 mm thickness, 9 mm diameter) of glycine and serine to Mars-like surface UV radiation conditions in low-

Earth orbit resulted in complete degradation of these organic molecules, with estimated half times of (51.3 ± 1.3) h for glycine and (73.9 ± 10.8) h for serine in the martian regolith (Noblet et al., 2012). In order to maximize the chances of finding biosignatures on Mars, we must determine the most suitable conditions to preserve them. Preservation of organic molecules on Mars is thought to be favoured in subsurface environments, and also through associations with specific minerals that may confer protection from the harsh surface conditions (Kminek and Bada, 2006;

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Summons et al., 2011, and references therein; Poch et al., 2015). Despite the unfavourable conditions that are found at the surface, indigenous chlorinated hydrocarbons were recently detected on Mars by the Sample Analysis at Mars (SAM) instrument on-board Curiosity (Freissinet et al., 2015). The successful detection of organic molecules in samples from Mars’ surface exposed to ionizing radiation and oxidative conditions suggests that: 1) the preservation of organic molecules may not be limited to subsurface environments, and 2) organic biosignatures may be found on the surface if associated with specific minerals.

In this chapter we examine the preservation under simulated Mars-like conditions of amino acids that were spiked onto 11 minerals and onto basaltic lava, which are all present on the martian surface (Ehlmann and Edwards, 2014). The simulations were performed using a custom-built Mars environmental simulation chamber at the Open University (OU), Milton Keynes, UK. This facility permits multiple aspects of the martian environment to be simulated, including temperature,

UV radiation, atmospheric pressure and composition. Analyses of the amino acids extracted from the mineral surfaces after the experiments were performed by gas chromatography-mass spectrometry (GC-MS). This set of results are particularly relevant for future in situ life-detection missions, such as the ESA-Roscosmos

ExoMars 2018 rover and the NASA Mars 2020 mission, highlighting which minerals may be the most suitable to protect amino acids from the harsh environmental conditions found at the martian surface.

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6.2 - Materials and methods

6.2.1 - Minerals and XRD characterization

Eleven mineral samples were used in this work: augite (A), enstatite (E), goethite (G), gypsum (Gy), hematite (H), jarosite (J), labradorite (L), montmorillonite

(M), nontronite (N), olivine (O) and saponite (S). Basaltic lava (B) was also used.

They were all selected as representing abundant mineral phases on Mars (Ehlmann and

Edwards, 2014). Augite was purchased from Fisher Scientific, as an individual mineral specimen (Manufacturer: American Educational Products 562802G). The minerals jarosite, labradorite, nontronite, and saponite were purchased from Richard Tayler

(http://richardtayler.co.uk, Cobham, Surrey, UK). Jarosite’s provenance was the

Skouriotissa mine in Cyprus. Nontronite was collected in Allentown, Pennsylvania

(USA). Saponite’s origin is from Portree, Isle of Skye, in Scotland (UK), while labradorite’s provenance is from the Toliara region in Madagascar. Enstatite, goethite and olivine were obtained from the Natural History Museum collection (NHM,

London), all of them unregistered specimens in the NHM collection. The basaltic lava is a specimen collected in Mauna Loa (Hawaii) at the point of lava quenching and donated by Joe Michalski. Gypsum and hematite were purchased from Sigma Aldrich.

The montmorillonite is SAz-1 (smectite-rich rock of volcanic origin) described in Cuadros (2002).

Minerals were ground to powder by hand with a mortar and pestle and were analysed by X-ray diffraction (XRD) at the Natural History Museum (London, UK), in order to determine their purity and structure. They were side-loaded to avoid preferred

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Influence of mineralogy on the preservation of amino acids under simulated Mars conditions orientation of particles and analysed in the range 3–80° 2θ using a PANanalytical

X'Pert Pro diffractometer operated at 45 kV and 40 mA, with Cu Kα radiation, divergence slit of 0.25°, Soller slits of 1.146° and a solid-state X'Celerator detector covering an angle of 2.1°. The basaltic lava contains the following mineral phases in the estimated order of abundance: volcanic glass, pyroxene, olivine, and labradorite.

Jarosite is of the natrojarosite variety. Olivine is forsterite. The augite and enstatite contain some traces of amphibole; the nontronite and montmorillonite contain traces of quartz; the other minerals are single phases at the XRD detection level. Figure

6.1 shows the X-ray pattern of hematite as an example. Diffractograms from the remaining mineral standards may be found in Annex 6.

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6.2.2 - Chemicals and tools

The pipette tips and eppendorfs used in this work were bought sterile.

Hydrochloric acid (37 wt. %), and high performance liquid chromatography (HPLC)- grade water were purchased from SigmaAldrich. Sodium hydroxide was purchased from Riedel-de Haen. Aluminium hydroxide and 2-aminoheptanoic acid (>97%) were purchased from Fluka. AG 50W-X8 resin (100–200 mesh) was acquired from Bio-

Rad. HPLC-grade dichloromethane (DCM) was purchased from Fisher Scientific.

Copper turnings used for sulfur removal were purchased from BDH. The 25 amino acids used in the experiments were: α-aminoisobutyric acid (α-AIB); D,Lisovaline;

D,L-alanine; D,L-valine; glycine; D,L-norvaline; D,L-β- aminoisobutyric acid (D,L-β-

AIB); D,L-β-aminobutyric acid (D,L-β- ABA); β-alanine; D,L-leucine; D,L- norleucine; γ -aminobutyric acid (γ -ABA); D,L-aspartic acid; D,L-glutamic acid and

6-aminohexanoic acid (6-AHA). The amino acid L-2-aminoheptanoic acid (L-2-AHA) was not subjected to the simulation experiments and was used as internal standard for the GC-MS analysis. All the amino acid standards were purchased from Sigma-

Aldrich, except D,L-isovaline, which was bought from Acros Organics. The trifluoroacetic anhydride isopropanol (TFAA-IPA) derivatization kit was obtained from Alltech. All glass tools and ceramics used were sterilized by wrapping in aluminum foil and heating in a furnace for at least 3 h at 500 °C.

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6.2.3 - Spiking of amino acids

A stock solution of 0.005 M concentration was prepared for each of the 25 amino acids. One mL of each amino acid stock solution was used to prepare a spiking solution containing an equimolar mixture of the 25 amino acids. Four of these solutions were prepared with final concentrations of 50, 25, 10 and 1 μM of each amino acid. The spiking solutions containing 1, 10, 25 and 50 μM concentrations of each amino acid were labelled as solution 1, 2, 3 and 4, respectively. Concentrations were chosen by adapting the protocols from Parbhakar et al. (2007) and Cuadros et al.

(2009). These authors show that at low amino acid concentrations the mechanism of amino acid adsorption on smectite is a simple exchange with interlayer cations, whereas at higher amino acid concentration physical interaction between amino acid molecules become important. In the present work low-amino acid concentration were used (i.e. much lower than 0.025 M) in order to avoid interaction between amino acids. Approximately 30 mg of each mineral sample described in section. 6.2.1 were weighed in Pyrex test tubes. Three millilitres of each of the solutions described above

(1–4) were transferred into 12 test tubes, each containing one of the minerals. The experiments containing the minerals and the spiking solutions were named by the respective mineral initial provided in Section. 2.1, followed by the number of the solution. For example, augite spiked with solution 1 (i.e., 1 μM of each amino acid) was labelled as A1, while augite samples labelled as A2, A3 and A4 were spiked with solution 2, 3 and 4, respectively. Using this labelling procedure, the experiments carried out include basaltic lava (with experiments B1, B2, B3 and B4), enstatite (E1,

E2, E3 and E4), goethite (G1, G2, G3 and G4), gypsum (Gy1, Gy2, Gy3 and Gy4),

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hematite (H1, H2, H3 and H4), montmorillonite (M1, M2, M3 and M4), nontronite

(N1, N2, N3 and N4), olivine (O1, O2, O3 and O4) and saponite (S1, S2, S3 and S4).

Jarosite was only used in experiments 3 and 4, resulting in a total of two samples (J3 and J4), and labradorite was only used in experiments 1, 2 and 3 (L1, L2 and L3) due to sample losses during experimental work. All the test tubes containing the mineral samples and the spiking solutions were flame sealed and placed in an orbital shaker

(Heidolph Polymax 1040) for 24 h at 50 revolutions per minute (rpm) in order to let amino acids adsorb onto the mineral surfaces. The outside of the test tubes was rinsed with HPLC grade water and cracked open. The content of the test tubes was dried under a flow of nitrogen (i.e., the spiking solution was dried in contact with the mineral). Thus, the 1, 10, 25 and 50 μM solutions correspond to 0.1, 1, 2.5 and 5

μmol/g of the amino acids on the minerals, respectively. Control experiments were prepared by repeating the same procedure described in this section with a second set of samples. The first set of samples was used to perform the Mars chamber simulations, while the second set was used as controls (i.e., samples that were spiked but not subjected to the Mars simulation).

6.2.4 - Mars chamber simulations

The spiked mineral standards were transferred into 14 mm diameter metallic sample cups and placed inside a Mars chamber simulator at the OU, Milton Keynes,

UK (Figure 6.2). The sample cups were pre-sterilized by heat at 500 °C for 4 h. The thickness of the deposits was approximately 1 mm in order to avoid any self-shielding issues. The sample cups were placed on a custom-made cold plate, to enable the cooling of the samples to Mars-relevant temperatures. Copper shielding was provided

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Influence of mineralogy on the preservation of amino acids under simulated Mars conditions to the edges of the plate to define a cold zone, and the external faces of the plate and shields were insulated to provide an efficient sample cooling zone. The cooling plate was connected to a liquid nitrogen supply, with thermal valves providing control over the sample temperature. Temperature was monitored using an array of thermocouples mounted on the sample plate. The resulting sample configuration is shown in Figure

6.2 (right). The chamber contained a Xe light source at the top of the chamber using a fused silica window (to ensure good UV transmission) providing direct illumination of the sample area with a UV spectrum similar to that encountered on the surface of Mars

(e.g. Patel et al., 2002). The lamp output, along with a typical modelled UV irradiance expected at the surface of Mars at local noon (taken from Patel et al., 2002) is shown in Figure 6.3. After setting the samples in the chamber and

Figure 6.2 - Mars Chamber simulator located at the Open University (left) and the experimental setup inside the chamber showing the amino acid-spiked minerals (right).

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Figure 6.3 - UV lamp spectrum and modelled UV spectrum expected at the martian surface.

previous to the experiments, the pressure was reduced to a vacuum (10 min and at room temperature. This ensures that there is no air and no water vapour in the atmosphere. Then, the chamber was pressurized at 6 mbar with a mixture of 95 % CO2 and 5 % N2, mimicking the approximate Mars pressure environment. The very dry conditions established by the initial vacuum treatment and the simulated Mars atmosphere (water vapour partial pressure is nominally zero) eliminated adsorbed water from the mineral surfaces. Complete removal of adsorbed water is likely not

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Influence of mineralogy on the preservation of amino acids under simulated Mars conditions obtained, unless the samples are sufficiently heated. Thermal cycling of the sample (to simulate the potential diurnal thermal cycle of Mars, e.g. Kieffer et al., 1977) was performed, with a cycle from –80 °C to +20 °C of 2 h duration repeated throughout the exposure. During thermal cycling the samples were exposed to UV, and overnight the samples were maintained at room temperature with no UV. The samples received a total of 28 h of real time continuous UV illumination. On Mars, the diurnal profile of

UV irradiance encountered at the surface exhibits a bell-shaped profile (such as demonstrated in Patel et al., 2002), therefore the local noon irradiance represents a peak irradiance and the UV levels throughout the rest of the day are significantly lower. Given the higher irradiance level of the lamp as shown in Figure 6.3, coupled with the effect of a diurnal light curve profile, the lab irradiance of 28 h is calculated to correspond to a martian equivalent UV dose of approximately 6.5 days. Upon completion, the chamber was restored to ambient conditions before removal of the samples from the chamber.

6.2.5 - Extraction, derivatization and GC-MS analyses of amino acids

After the Mars simulation, amino acids were extracted from the minerals and derivatized according to the procedure described by Martins et al. (2011, 2015 and references therein). A step to remove sulfur was performed between the desalting and derivatization, by using copper turnings (activated in a 10% HCl solution). The activated copper turnings were added to V-vials containing the desalted amino acid sample residues, brought up with 1 mL of HPLC grade water, and left overnight. The copper turnings were then removed and the V-vials were dried under a flow of N2. The

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derivatized amino acids were dissolved in 75 μL of DCM. The GC-MS analyses were performed using a Perkin Elmer Clarus 580 gas chromatograph/Clarus SQ 8S mass spectrometer. The amino acids were separated using two Agilent Chirasil L-Val capillary columns (each 25 m, inner diameter 0.25 mm, film thickness 0.12 μm) connected by a zero dead-volume connector. Helium was used as carrier gas with a 1 mL/min flow. GC injector temperature was set at 220 °C. Automatic splitless mode was used for injection and the oven programme was: 1) 35 °C for 10 min; 2) 2 °C per minute increase until 80 °C, hold for 5 min; 3) 1 °C per minute increase until 100 °C; and 4) 2 °C per min increase until 200 °C, hold for 10 min (total run time 117.5 min).

Temperatures for the transfer line and the MS ion source were set at 220 °C and 230

°C, respectively.

The identification of amino acids was achieved by comparing the retention times and mass fragmentation patterns of the amino acids present in the samples with those obtained from known amino acid standard mixtures. The amino acid detection limit of the GC-MS was verified to be approximately 3 parts per billion (ppb). Typical

GC-MS chromatograms from simulated G4 sample and respective control are provided in Figure 6.4. In order to ascertain that the minerals were clean and devoid of detectable amino acids, runs of untreated mineral samples’ extracts were also performed. Figure 6.5 shows the GC-MS chromatograms obtained from the control run of the mineral labradorite, indicating that the mineral did not have amino acids in detectable amounts. Similar control runs were also obtained for other minerals although they are not presented. None of the minerals had amino acids in detectable amounts. Amino acids were quantified by peak area integration of the corresponding ion fragment, which were then converted to abundances using calibration curves.

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These were created by plotting the ratio of the amino acid standard/internal standard

target ion peak area versus the mass of amino acid standard injected into the column.

relative abundance

Figure 6.4 - Single ion GC-MS s (25 to 85 min) of the derivatized (N-TFA, O-isopropyl) amino acids extracted from control sample G4 (goethite spiked with solution 4, but not subjected to the Mars simulation; chromatograms pointing upwards) and corresponding sample G4 (goethite spiked with solution 4 and analysed after the Mars chamber simulations; chromatograms pointing downwards). All single ions chromatograms are in the same scale. 1) α-AIB; 2) D,L-isovaline; 3) D-alanine; 4) L-alanine; 5) D-valine; 6) L-valine; 7) glycine; 8) D-norvaline; 9) D-β-AIB; 10) L-β-AIB; 11) D-β-ABA; 12) β-alanine; 13) L-β-ABA; 14) L- norvaline; 15) D-leucine; 16) D-norleucine; 17) L-leucine; 18) L-norleucine; 19) D-2- aminoheptanoic acid (internal standard); 20) γ-ABA; 21) L-2-aminoheptanoic acid (L-2-AHA, internal standard); 22) D-aspartic acid; 23) L-aspartic acid; 24) 6-AHA; 25) D-glutamic acid; 26) L-glutamic acid.

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relative abundance

6.2.6 - Brunauer–Emmett–Teller (BET) analyses

Brunauer–Emmett–Teller (BET) analyses were performed to measure the

surface area and pore size of the 11 minerals and basaltic lava used in this work. These

two variables are likely to be the most relevant for amino acid adsorption and

protection from UV radiation because they have an important control on amino acid

distribution and arrangement on the mineral surface and on physical shielding. Prior to

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Influence of mineralogy on the preservation of amino acids under simulated Mars conditions analysis, approximately 0.5 g of all samples were outgassed overnight at 353 K, under high vacuum. Measurements were performed using a Micrometrics TriStar 3000 gas adsorption analyser, using N2 as adsorptive gas. Measurements were made in the relative pressure (P/P0) range from 0.01 up to 0.99. Final results were calculated using

9 equilibrium points in the P/P0 range between 0.03 and 0.20 (all linear regressions had a correlation coefficient higher than 0.999).

6.3 – Results

6.3.1. Degradation of amino acids under simulated Mars conditions

The fraction of extractable amino acids preserved after exposition to simulated

Mars surface conditions was calculated as the ratio A/A0 (%), where A is the amount of each amino acid that was not degraded and successfully extracted after the Mars

Chamber experiment, and A0 is the total amount of amino acid extracted from the correspondent control (i.e., equivalent samples, prepared in the same conditions, but not exposed in the Mars Chamber). The amount of the amino acids extracted from the controls is an effective way to ascertain whether a lack of detection of amino acids in a tested sample is due to degradation or to low extraction. The lack of amino acid detection in both exposed sample and correspondent control suggests that the lack of detection in the former cannot be attributed to degradation induced by the simulated martian environmental conditions.

The average fractions of amino acids extracted from the control samples (i.e. percentage of amino acids recovered from the non simulated samples) are presented in

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Figure 6.6. No amino acids were detected above the detection limit in control samples for augite A1, basalt lava B1 and nontronite N1.

Figure 6.7 shows the average A/A0 ratios (in %) obtained for the 25 amino acids that were used in experiments 2, 3 and 4. These values were calculated from the individual A/A0 (%) obtained for each of the 25 amino acids (individual A/A0 ratios are shown in Table 6.1, Table 6.2 and Table 6.3).

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Figure 6.7 - Summary of the average A/A0 amino acid ratios (in %) obtained after the simulation experiments in the Mars Chamber, where A is the amount of amino acids that were not degraded and extracted after the simulation, and A0 is the total amount of amino acids extracted from the corresponding controls. Average values presented in this figure were calculated using all the A/A0 ratios obtained for each of the 25 amino acids that were spiked in a given experiment found in Table 6. 1, Table 6.2 and Table 6.3. The lack of bars in basaltic lava and enstatite for experiment 2 means complete degradation of amino acids. Labradorite and jarosite were not used in experiments 4 and 2, respectively.

Results from experiment 1 (i.e., minerals spiked with solution containing 1 µM of each amino acid; not presented) show that no amino acids were detected in any of the exposed samples (the amino acid detection limit of the GC-MS is ∼3 ppb). In the controls, no amino acids were detected in augite (A1), basalt lava (B1) and nontronite

(N1) (Figure 6.6). Hence, the lack of amino acid detection in the A1, B1 and N1 experiments cannot be unequivocally interpreted as caused by degradation. For the remaining minerals of experiment 1, amino acid degradation was observed. In the case of enstatite (E1) all amino acids suffered complete degradation.

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In experiment 2 (spiking solution containing 10 µM of each amino acid), gypsum (Gy2) was the mineral that, on average, preserved a greater proportion of amino acids, whereas amino acids on enstatite (E2) and basaltic lava (B2) were completely degraded (Figure 6.7 and Table 6.1). Gypsum, olivine, montmorillonite and nontronite were the only minerals that preserved all amino acids (Table 6.1).

Saponite prevented degradation of all amino acids except D, L-β-AIB (Table 6.1).

Results from experiment 3 (minerals spiked with a solution containing 25 µM of each amino acid) showed that amino acids were preserved (to different degrees) in all minerals (Figure 6.5). The percentage of surviving amino acids for augite (A3), basaltic lava, (B3) enstatite (E3), hematite (H3) and labradorite (L3) were below 10 %

(Figure 6.7 and Table 6.2). On average, amino acids were preserved most efficiently in jarosite (J3). Basaltic lava (B3) preserved the smallest amount of amino acids

(Figure 6.7).

The simulations using the minerals that were spiked with the 50 µM solution

(experiment 4) reveal that nontronite (N4) preserved, on average, the largest proportion of amino acids (Figure 6.7). The lowest percentage of surviving amino acids were found in augite (A4), basaltic lava (B4) and hematite (H4), with A/A0 values of 11 %, 9 % and 9 %, respectively (Figure 6.7).

In addition, our results indicate that amino acid enantiomers are degraded to the same degree (individual preservation ratios obtained for D- and L-amino acids

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Influence of mineralogy on the preservation of amino acids under simulated Mars conditions enantiomers are provided in Table 6.1, Table 6.2 and Table 6.3). The average A/A0 calculated for all D and L enantiomers preserved after experiment 4 were 20.0 ± 1.1 % and 20.4 ± 1.1 %, respectively

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Individual amino Augite (A2) Basalt glass Enstatite Goethite Gypsum (Gy2) Hematite Labradorite Montmorillonite Nontronite Olivine (O2) Saponite acid (A/A0) vs (B2) (E2) (G2) (H2) (L2) (M2) (N2) (S2) mineral α-AIB 3 ± 1 0a 0a 9 ± 0 17 ± 1 0a 0a 42 ± 4 18 ± 2 22 ± 1 18 ± 7

D,L-isovalineb 3 ± 1 0a 0a 7 ± 0 12 ± 1 5 ± 2 0a 34 ± 3 12 ± 1 14 ± 1 14 ± 5

D-alanine 0a 0a 0a 0a 24 ± 2 0a 0a 40 ± 4 25 ± 2 16 ± 1 19 ± 6

L-alanine 0a 0a 0a 0a 20 ± 2 0a 0a 34 ± 3 22 ± 2 16 ± 2 15 ± 5

D- valine 2 ± 0 0a 0a 4 ± 0 32 ± 2 3 ± 0 9 ± 1 30 ± 2 18 ± 2 14 ± 1 15 ± 5

L- valine 2 ± 0 0a 0a 5 ± 0 30 ± 1 4 ± 1 8 ± 0 31 ± 2 19 ± 1 13 ± 1 12 ± 4

Glycine 0a 0a 0a 0a 54 ± 4 0a 0a 68 ± 5 51 ± 5 22 ± 1 18 ± 5

D- β- AIB 0a 0a 0a 0a 49 ± 2 0a 0a 32 ± 3 29 ± 3 26 ± 3 0a

L- β- AIB 0a 0a 0a 0a 48 ± 5 0a 0a 35 ± 5 24 ± 4 26 ± 2 0a

D- β- ABA 0a 0a 0a 0a 56 ± 3 0a 0a 35 ± 3 29 ± 6 17 ± 1 19 ± 6

L- β- ABA 0a 0a 0a 0a 54 ± 5 0a 0a 39 ± 3 30 ± 4 19 ± 2 14 ± 4 D- norvaline 0a 0a 0a 0a 50 ± 3 0a 10 ± 2 33 ± 1 23 ± 1 15 ± 1 15 ± 4

L- norvaline 0a 0a 0a 0a 53 ± 3 0a 11 ± 2 36 ± 2 24 ± 1 18 ± 1 15 ± 4

β-alanine 0a 0a 0a 0a 52 ± 4 0a 0a 38 ± 2 27 ± 1 19 ± 2 13 ± 4

D- leucine 0a 0a 0a 0a 51 ± 4 2 ± 0 3 ± 1 34 ± 1 22 ± 1 11 ± 1 10 ± 3

L- leucine 0a 0a 0a 0a 45 ± 3 2 ± 0 5 ± 1 32 ± 1 22 ± 1 11 ± 1 10 ± 3

D- norleucine 0a 0a 0a 0a 43 ± 4 0a 7 ± 0 18 ± 2 12 ± 1 13 ± 1 17 ± 8 L- norleucine 0a 0a 0a 0a 41 ± 1 0a 5 ± 0 21 ± 1 15 ± 1 13 ± 1 14 ± 7

γ-ABA 0a 0a 0a 0a 66 ± 4 0a 0a 32 ± 2 28 ± 3 26 ± 2 19 ± 6 D- aspartic acid 13 ± 1 0a 0a 12 ± 1 55 ± 2 9 ± 0 7 ± 1 22 ± 2 31 ± 2 24 ± 1 12 ± 3

L- aspartic acid 14 ± 1 0a 0a 14 ± 1 59 ± 3 10 ± 0 8 ± 0 25 ± 1 34 ± 2 26 ± 2 13 ± 4

6-AHA 0a 0a 0a 0a 40 ± 3 0a 0a 22 ± 1 25 ± 1 25 ± 1 20 ± 5

D- glutamic acid 0a 0a 0a 6 ± 0 51 ± 4 0a 9 ± 0 29 ± 2 29 ± 1 31 ± 3 15 ± 3 L- glutamic acid 0a 0a 0a 6 ± 0 49 ± 3 0a 9 ± 1 25 ± 2 26 ± 2 32 ± 3 14 ± 4 a- Complete degradation (A/A0 = 0). b- Enantiomeric separation not possible under chromatographic conditions.

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Table 6.2– Summary of the individual A/A0 ratios (in %) obtained for experiment 3 (spiking solution, 25 M of each amino acid) where A is the amount of the remaining amino acids detected in simulated samples and A0 is the amount of amino acids detected in the control. Individual amino Augite (A3) Basalt glass Enstatite Goethite Gypsum Hematite Jarosite (J3) Labradorite Monmorillonit Nontronit Olivine (O3) Saponite acid (A/A0) vs (B3) (E3) (G3) (Gy3) (H3) (L3) e (M3) e (N3) (S3) mineral α-AIB 16 ± 1 2 ± 0 8 ± 1 22 ± 2 0a 5 ± 1 43 ± 4 6 ± 1 17 ± 2 12 ± 1 12 ± 1 20 ± 1

D,L-isovalineb 13 ± 2 2 ± 0 6 ± 1 21 ± 2 0a 5 ± 1 44 ± 4 5 ± 1 13 ± 1 11 ± 1 8 ± 1 22 ± 2

D-alanine 6 ± 1 3 ± 1 5 ± 1 21 ± 3 11 ± 1 6 ± 1 32 ± 2 7 ± 1 24 ± 2 15 ± 2 13 ± 1 17 ± 1

L-alanine 5 ± 0 2 ± 0 4 ± 0 18 ± 2 7 ± 1 5 ± 1 28 ± 2 6 ± 1 21 ± 1 11 ± 1 12 ± 1 15 ± 1

D- valine 7 ± 0 3 ± 1 5 ± 1 24 ± 2 15 ± 2 8 ± 1 47 ± 3 8 ± 1 22 ± 2 16 ± 2 17 ± 1 24 ± 2

L- valine 7 ± 0 3 ± 0 5 ± 0 24 ± 1 12 ± 1 8 ± 1 46 ± 2 7 ± 0 20 ± 1 13 ± 1 15 ± 1 20 ± 2

Glycine 0a 0a 0a 31 ± 3 22 ± 2 7 ± 1 28 ± 4 9 ± 1 40 ± 2 19 ± 2 18 ± 2 15 ± 1

D- β- AIB 0a 0a 0a 29 ± 2 23 ± 3 0a 42 ± 5 19 ± 2 25 ± 2 31 ± 3 20 ± 2 18 ± 2

L- β- AIB 0a 0a 0a 33 ± 2 27 ± 3 0a 37 ± 5 19 ± 2 28 ± 2 30 ± 3 20 ± 3 17 ± 1

D- β- ABA 0a 0a 0a 28 ± 1 20 ± 1 7 ± 0 32 ± 4 9 ± 1 24 ± 2 24 ± 2 20 ± 2 15 ± 1

L- β- ABA 0a 0a 0a 29 ± 2 23 ± 2 8 ± 1 31 ± 3 9 ± 1 26 ± 2 24 ± 3 20 ± 2 13 ± 1

D- norvaline 6 ± 0 3 ± 1 5 ± 1 29 ± 2 20 ± 2 9 ± 0 50 ± 3 8 ± 0 26 ± 2 20 ± 1 23 ± 1 24 ± 2

L- norvaline 7 ± 0 4 ± 1 6 ± 0 32 ± 2 23 ± 1 10 ± 1 51 ± 3 9 ± 1 30 ± 2 19 ± 2 26 ± 2 21 ± 1

β-Alanine 0a 0a 0a 28 ± 2 24 ± 2 5 ± 0 24 ± 2 10 ± 1 31 ± 2 24 ± 2 17 ± 1 12 ± 1

D- Leucine 5 ± 0 3 ± 0 5 ± 0 29 ± 1 25 ± 1 7 ± 0 32 ± 3 5 ± 0 18 ± 1 13 ± 1 21 ± 1 12 ± 0

L- Leucine 5 ± 0 3 ± 0 5 ± 0 28 ± 1 24 ± 1 7 ± 0 29 ± 1 5 ± 0 19 ± 1 12 ± 1 19 ± 1 11 ± 0

D- norleucine 6 ± 1 5 ± 0 5 ± 0 26 ± 1 23 ± 1 8 ± 1 42 ± 2 8 ± 0 18 ± 2 18 ± 1 20 ± 2 20 ± 1

L- norleucine 9 ± 1 5 ± 0 5 ± 0 29 ± 1 25 ± 1 7 ± 1 45 ± 1 7 ± 0 22 ± 2 17 ± 1 23 ± 1 20 ± 1

γ-ABA 0a 0a 0a 37 ± 2 38 ± 5 10 ± 1 78 ± 3 10 ± 1 23 ± 1 39 ± 2 21 ± 1 18 ± 2

D- aspartic acid 5 ± 0 5 ± 0 6 ± 0 35 ± 3 33 ± 2 12 ± 1 32 ± 3 10 ± 0 16 ± 1 32 ± 3 26 ± 1 16 ± 1

L- aspartic acid 6 ± 0 7 ± 0 7 ± 1 40 ± 2 37 ± 2 14 ± 1 34 ± 4 11 ± 1 19 ± 1 35 ± 3 28 ± 1 18 ± 1

6-AHA 0a 0a 0a 35 ± 3 33 ± 3 8 ± 1 0a 12 ± 1 18 ± 1 28 ± 2 20 ± 1 22 ± 2 D- glutamic acid 0a 5 ± 0 7 ± 0 40 ± 4 32 ± 2 8 ± 1 40 ± 4 11 ± 0 15 ± 1 32 ± 2 26 ± 1 23 ± 2

L- glutamic acid 0a 5 ± 0 6 ± 1 37 ± 4 30 ± 2 8 ± 1 38 ± 2 10 ± 0 13 ± 1 29 ± 2 25 ± 1 22 ± 2 a- Complete degradation (A/A0 = 0). b- Enantiomeric separation not possible under chromatographic conditions.

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Table 6.3 – Summary of the individual A/A0 ratios (in %) obtained for experiment 4 (spiking solution, 50 M of each amino acid) where A is the amount of the remaining amino acids detected in simulated samples and A0 is the amount of amino acids detected in the control. Individual amino Augite (A4) Basalt glass (B4) Enstatite Goethite (G4) Gypsum (Gy4) Hematite Jarosite Montmorillonite Nontronite Olivine (O4) Saponite (S4) acid (A/A0) vs (E4) (H4) (J4) (M4) (N4) mineral α-AIB 38 ± 4 22 ± 1 27 ± 3 34 ± 3 27 ± 1 9 ± 0 27 ± 3 33 ± 4 36 ± 2 11 ± 2 11 ± 1

D,L-isovalineb 34 ± 5 23 ± 1 26 ± 2 33 ± 3 27 ± 1 9 ± 0 31 ± 3 24 ± 3 40 ± 2 8 ± 1 8 ± 0

D-alanine 21 ± 3 10 ± 1 22 ± 2 26 ± 2 21 ± 2 9 ± 0 26 ± 2 34 ± 3 31 ± 2 11 ± 1 15 ± 1 L-alanine 17 ± 2 8 ± 1 19 ± 2 22 ± 2 17 ± 2 9 ± 1 22 ± 2 30 ± 3 27 ± 2 9 ± 1 12 ± 2 D- valine 15 ± 2 16 ± 1 39 ± 2 26 ± 2 22 ± 1 8 ± 1 22 ± 1 26 ± 2 46 ± 2 16 ± 1 19 ± 1 L- valine 14 ± 1 14 ± 1 37 ± 2 26 ± 2 20 ± 1 9 ± 1 24 ± 1 24 ± 1 44 ± 2 14 ± 1 17 ± 1

Glycine 0a 4 ± 0 4 ± 1 26 ± 1 29 ± 2 13 ± 1 18 ± 2 41 ± 4 42 ± 1 15 ± 2 20 ± 1

D- β- AIB 0a 0a 18 ± 2 24 ± 2 22 ± 2 8 ± 0 20 ± 2 28 ± 1 30 ± 5 20 ± 2 25 ± 2

L- β- AIB 0a 0a 18 ± 2 25 ± 1 26 ± 2 9 ± 0 19 ± 1 31 ± 1 31 ± 3 23 ± 1 28 ± 1

D- β- ABA 0a 7 ± 0 23 ± 2 20 ± 1 19 ± 1 7 ± 0 16 ± 1 25 ± 1 34 ± 1 15 ± 1 23 ± 1

L- β- ABA 0a 9 ± 1 25 ± 3 21 ± 1 23 ± 2 7 ± 0 17 ± 1 24 ± 2 30 ± 2 17 ± 1 21 ± 1

D- norvaline 14 ± 1 15 ± 1 48 ± 1 29 ± 1 23 ± 1 9 ± 1 24 ± 1 28 ± 1 57 ± 3 18 ± 1 24 ± 1

L- norvaline 16 ± 1 17 ± 1 53 ± 3 32 ± 2 25 ± 1 11 ± 1 26 ± 1 30 ± 2 55 ± 3 20 ± 1 26 ± 1 β-Alanine 0a 0a 15 ± 2 20 ± 1 24 ± 1 15 ± 1 15 ± 1 29 ± 2 21 ± 1 14 ± 1 16 ± 1 D- leucine 9 ± 1 11 ± 0 35 ± 2 23 ± 1 17 ± 1 9 ± 1 24 ± 1 17 ± 1 31 ± 4 16 ± 1 17 ± 0

L- leucine 9 ± 1 11 ± 0 30 ± 3 25 ± 1 17 ± 1 10 ± 1 24 ± 2 17 ± 1 28 ± 3 14 ± 1 16 ± 0

D- norleucine 14 ± 1 15 ± 1 54 ± 2 20 ± 2 23 ± 1 8 ± 0 23 ± 2 19 ± 1 54 ± 3 18 ± 1 20 ± 1

L- norleucine 12 ± 1 16 ± 1 59 ± 3 24 ± 2 25 ± 1 10 ± 0 26 ± 1 22 ± 1 52 ± 2 20 ± 1 22 ± 1

γ-ABA 0a 7 ± 1 11 ± 1 18 ± 1 32 ± 2 6 ± 0 11 ± 1 22 ± 1 37 ± 3 21 ± 2 17 ± 1

D- aspartic acid 13 ± 1 4 ± 0 18 ± 2 21 ± 1 28 ± 1 13 ± 1 14 ± 1 16 ± 1 55 ± 3 17 ± 1 17 ± 2 L- aspartic acid 15 ± 1 5 ± 0 22 ± 2 23 ± 1 30 ± 1 15 ± 1 16 ± 1 18 ± 1 62 ± 4 19 ± 1 21 ± 2

6-AHA 0a 0a 9 ± 0 16 ± 1 28 ± 1 7 ± 1 9 ± 1 17 ± 1 29 ± 1 20 ± 1 16 ± 1 D- glutamic acid 9 ± 1 3 ± 0 11 ± 1 23 ± 1 34 ± 1 9 ± 1 20 ± 2 14 ± 1 54 ± 6 24 ± 2 14 ± 1

L- glutamic acid 9 ± 1 4 ± 0 10 ± 1 21 ± 1 34 ± 1 7 ± 1 17 ± 1 12 ± 1 55 ± 4 24 ± 1 13 ± 1 a- Complete degradation (A/A0 = 0). b- Enantiomeric separation not possible under chromatographic conditions.

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In experiment 3, D-amino acids had an average A/A0 of 16.5 ± 1.2 %, while L enantiomers had an average A/A0 of 16.7 ± 1.2 %. Similarly, the average A/A0 ratios for D and L-amino acids obtained for experiment 2 were 17.3 ± 1.9 % and

17.1 ± 1.9 %, respectively.

6.3.2 - BET analyses

The results obtained for the surface areas and pore sizes of the 11 minerals and basaltic lava used in the simulations are provided in Table 6.4. Surface area values range from 0.22 m2/g (for basaltic lava) up to 129.01 m2/g (for montmorillonite). Pore size values range from 5.17 nm in saponite up to 21.04 nm in olivine.

Table 6.4 - Qualitative information on the general iron/ferrous iron content and surface area and pore size value results obtained from BET analyses for the minerals used in the Mars chamber simulations. Iron content Ferrous iron BET analyses content Surface area Pore size (m2/g) (nm) Augite low Fe2+ low 1.19 ± 0.01 12.91 Basaltic Lava medium Fe2+ medium 0.22 ± 0.01 14.79 Enstatite medium Fe2+ medium 0.50 ± 0.01 14.40 Goethite high Fe3+ 2.13 ± 0.01 17.78 Gypsum no iron 2.25 ± 0.01 12.01 Hematite high Fe3+ 4.91 ± 0.04 11.51 Jarosite high Fe3+ 4.98 ± 0.01 13.25 Labradorite no iron 0.27 ± 0.01 17.11 Montmorillonite low Fe3+ 129.01 ± 0.41 5.89 Nontronite high Fe3+ 26.76 ± 0.24 7.36 Olivine no iron 0.23 ± 0.01 21.04 Saponite no iron 37.26 ± 0.35 5.17

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6.4 - Discussion

The preservation from UV-induced degradation of amino acids spiked onto minerals is likely dependant on multiple factors. Here we analyse the results obtained from the simulations in light of the effect of 1) the structure of amino acids and 2) the physical/chemical features of the minerals that were used, in particular their ferric/ferrous iron content, surface area and pore size.

6.4.1 - Effect of the amino acid structure

Decarboxylation induced by UV photolysis has been proposed as one of the main destruction pathways of amino acids (Johns and Seuret, 1970, Ehrenfreund et al.,

2001,Boillot et al., 2002, ten Kate et al., 2005 and Bertrand et al., 2015). Boillot et al.

(2002) verified that L-leucine was subjected to decarboxylation under UV radiation.

Furthermore, Ehrenfreund et al. (2001) suggested this mechanism to explain the destruction of amino acids such as glycine, alanine, α-aminoisobutyric acid and β- alanine under simulated conditions in interstellar gas and interstellar icy grains.

Decarboxylation of amino acids by UV radiation results in the formation of a radical in the α-carbon atom (Ehrenfreund et al., 2001). The stability of the radical is dependent on the substituents bonded to the α-carbon atom. Alkyl substituent groups attached to the α-carbon atom contribute towards the stability of the resulting alkyl amine radical that forms after UV-induced decarboxylation and prolong the life of the amino acid (ten Kate et al., 2005). Therefore, we should expect that glycine (the simplest amino acid, with two hydrogen atoms bonded to the α-carbon) would be more degraded and have the lowest surviving ratios after the Mars-conditions simulation experiments. In fact, Li and Brill (2003) have shown that glycine has the highest

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Influence of mineralogy on the preservation of amino acids under simulated Mars conditions relative aqueous decarboxylation rate when compared to the protein amino acids leucine, isoleucine, valine and alanine. In addition, we would expect that the amino acids more resistant to UV radiation and less prone to decarboxylation would be α- aminoisobutyric and isovaline, which are doubly substituted in the α-carbon. A group of our results agree with the overall effect of substitution in the α-carbon described above (Table 6. 1, Table 6.2 and Table 6.3). For instance, glycine was less preserved than α-aminoisobutyric and isovaline in all augite, basaltic lava, enstatite and jarosite experiments 2, 3 and 4 (Table 6. 1, Table 6.2 and Table 6.3). However, it is evident that the alkyl substituent groups are not the only factor contributing towards the stability of the amino acids. If that was the case, then isovaline and α-aminoisobutyric would be the most stable amino acids in our experiments and the ones with the highest

A/A0 values, which is not observed in our results. Other amino acid structural and chemical factors (molecule dimensions and shape, pKa values, etc.) will affect the way of interaction or adsorption between the mineral surface and the amino acid. These factors probably also play a role in the stabilization of amino acids against UV light, but their complexity is beyond the scope of this work.

It was also observed that D and L amino acids were equally degraded in the simulations (Table 6. 1, Table 6.2 and Table 6.3). This lack of enantiomeric preference regarding UV-induced degradation is consistent with the observations of Orzechowska et al. (2007) for D,L-aspartic acid, D,L-glutamic acid and D,L- phenylalanine.

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6.4.2 - Effects from the mineral features

The minerals can act as protectors of the amino acids from the UV radiation in several ways. First of all, the opacity of the mineral to UV radiation is a protection factor. Opacity increases approximately with the increasing average atomic number of the mineral. For the minerals investigated here, Fe is the only element with electrons in d orbitals, and is a much greater absorber of UV radiation than any of the other elements. Thus, as a good approximation, the presence of Fe can be considered the dominant factor controlling opacity to UV radiation. However, ferrous Fe promotes iron (II) catalysed reactions that degrade organic molecules and this is an important effect to be considered here. Other mineral protecting factors are a high specific surface area and small average pore space, both of which should allow for a greater proportion of the adsorbed amino acids to be protected from direct UV radiation. Table 6.4 provides the information on the above characteristics that can guide the discussion of their effect in the Mars simulation experiments. The chemical character of specific mineral adsorption sites may also have an effect in determining amino acid stability but they should be considered in conjunction with the chemical characteristics of the individual amino acid and are not discussed here.

6.4.2.1 - Role of iron

Iron is a transition metal with UV-photoprotective properties (Olson and

Pierson, 1986). The amount of ferric iron was found to be correlated with the ability of minerals to confer protection from UV-radiation (Hoang-Minh et al., 2010) and the protective role of ferric iron against UV radiation has been verified by Pierson et al.,

1993 and Gómez et al., 2003 and Gauger et al. (2015). In clay minerals, ferric iron

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Influence of mineralogy on the preservation of amino acids under simulated Mars conditions increases the absorbance of UV radiation (Chen et al., 1979). Similarly, for sulfates, the opacity to UV radiation increases much from gypsum to jarosite (Martinez-Frias et al., 2006). In our experiments, two ferric iron-rich minerals, jarosite and nontronite

(Table 6.4) had the highest amino acid preservation in experiments 3 and 4, respectively (Figure 6.7). Within the smectite group, montmorillonite and nontronite preserved more amino acids than saponite, probably due to the absence of Fe in saponite (Table 6.4). The absence of Fe in saponite was inferred from X-ray diffraction data, because the position of the 060 peak at 1.534 Å indicates that Fe3+ is not present in any significant amount (Brown and Brindley, 1980). Poch et al.

(2015) have suggested that nontronite not only protects amino acids from UV light by shielding but that there is also a stabilizing interaction between the clay and the amino acids. These interactions perhaps help to dissipate absorbed energy or facilitate photodissociated molecules to recombine (Poch et al., 2015).

Of the two Fe oxides in our experiments, goethite had a good protection effect in experiments 3 and 4, as expected, but low in experiment 2, while hematite protection was always low (Figure 6.7). These results highlight the fact that protection against UV radiation is controlled by a variety of phenomena. Watts et al.,

(1997) found that the combinations of hematite and hydrogen peroxide promote degradation of organic compounds. Goethite is also known to be a catalyst for iron (II) catalysed reactions (Lin and Gurol, 1998), which contributes to the degradation of organic molecules. It is then possible that minerals where Fe is very abundant may promote electronic interactions between Fe atoms and adsorbed organic substances

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that cause their degradation. Thus, their overall effect of protection against UV is a balance between the electronic transfer effect and the UV-shielding effect.

6.4.2.2 - Role of ferrous iron

Ferrous iron is known to degrade organic molecules in Mars-like conditions through iron (II) catalysed reactions (Benner et al., 2000 and Garry et al., 2006).

Adsorbed water was removed from the mineral surfaces in our Mars chamber simulation experiments due to the low water vapour partial pressure (nominally zero), although traces may have remained in the smectites as these are the most hygroscopic of the minerals. Structural water or hydroxyls are not removed using our experimental procedure, but this is not relevant here because no mineral with ferrous iron contained structural water. For these reasons, iron (II) catalysed reactions in our experiments most probably only involved ferrous iron in the minerals and the amino acids. Thus, it can be expected that minerals with ferrous Fe will have a degradation effect in our experiments. The balance between the degradation effect of Fe2+ and the UV-shielding effect of Fe will decide which of the two is manifested experimentally.

Interestingly, Olson and Pierson (1986) observed that ferrous iron absorbs less UV radiation than ferric iron between 200 and 400 nm (the UV-range used in our simulations) and Chen et al. (1979) found that the UV absorption of nontronite decreased when ferric iron was reduced to ferrous iron. Therefore, the protective effect of Fe appears to be less effective in the case of ferrous iron. In our study, the generally low amount of surviving amino acids from the minerals containing ferrous Fe, augite, basaltic lava and enstatite (Table 6.4) is in agreement with ferrous iron being an important contributor for amino acid degradation under simulated Mars conditions.

The basaltic lava includes three mineral phases containing ferrous iron: olivine,

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Influence of mineralogy on the preservation of amino acids under simulated Mars conditions pyroxene and glass. The olivine used in this work is forsterite (Mg variety) according to XRD data and has little or no ferrous iron, which would explain the high amino acid preservation in comparison to augite, enstatite and basaltic lava. This explanation is compatible with the higher amino acid preservation in enstatite for experiment 4

(Figure 6.7). The enstatite in our study is of the bronzite type, with low ferrous Fe content (10–30% FeSiO3 in the MgSiO3–FeSiO3 series).

6.4.2.3 - Surface area and pore size

According to Moores et al. (2007), the variation in small-scale geometries in the martian surface such as pits, trenches and overhangs would produce significant attenuation effects on the incident UV flux, and create safe spots for organisms and organic molecules to be preserved. A similar principle can be applied at the micro- scale for the minerals used in this work. Irregularities on the mineral surfaces will also create sites where organic molecules may be adsorbed and preserved from UV radiation. Higher surface areas in a mineral indicate smaller particle size and/or a higher amount of irregularities in the surface, both of which generate a higher number of sites where organic molecules can be protected from direct exposure to UV light.

In adsorption experiments, the key variable of the solid phase is the surface area: the larger the surface, the more adsorbate can be accommodated. Particle size is related to surface area, but is not the key variable, because surface area depends also on other variables. In our study, all the amino acid was forced to adsorb on the mineral surfaces and so there is no dependence between total amounts of amino acid adsorbed and surface area. The dependence is on how the amino acids were adsorbed and

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where, plus on the configuration of mineral particles in the well during the experiment, all of which affect exposure to radiation and resilience to it.

In addition to the surface area, the size of the pores should also influence the degradation of amino acids under a high flux of UV-radiation. Pores provide a site where organic molecules may be protected against radiation. The photoprotective effect conferred by the pores should be inversely correlated with their respective size.

The range of pore size measured by BET is provided in Table 6.4. If all amino acids were able to penetrate the whole range of pores present in our minerals, this would result in the smaller pores creating a more shielded environment for organic molecules by limiting the amount of UV influx in the site. On the contrary, bigger pores would let more radiation penetrate and induce more degradation.

From the BET results, it is observable that nontronite, montmorillonite and saponite were the minerals that had the highest surface areas and the smaller pore sizes

(Table 6.4). Clay minerals of the smectite group have large surface areas and the ability to adsorb organic molecules both in external surfaces and in the space between the layers that make up the mineral structure (Mortalnd, 1970 and Raussell-Colom and

Serratosa, 1987). This is in agreement with the generally high amounts of amino acids preserved in nontronite, montmorillonite and saponite when compared to the other minerals (Figure 6.7). With the clear exceptions of olivine and gypsum, the minerals with lower surface areas and larger pore sizes than the clays generally preserved less amino acids (Table 6.4 and Figure 6.7). Olivine, with a low surface area and the largest pore size, preserved more amino acids than labradorite, hematite, augite and basaltic lava, all of which have similar or larger surface areas and smaller pore sizes

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(Table 6.4). This is one more example that no single variable can explain amino acid preservation on the mineral surfaces and all variables have to be considered together in order to approach a correct interpretation.

6.4.3 - Concentration effect

Overall, our results show that the concentration of amino acids in the experiments had an influence on amino acid preservation. The mineral displaying the highest photoprotective effect in each experiment varied with the amount of amino acids that were spiked into the minerals. Nontronite preserved the largest proportion of amino acids in experiment 4, whereas jarosite and gypsum did so in experiments 3 and

2, respectively (Fig. 5). In experiments 2, 3 and 4 the general trend is that amino acid preservation ratio increased with increasing spiking concentration. This was clearly observed in augite, basaltic lava, enstatite, hematite, labradorite and saponite (Figure

6.7), although gypsum and montmorillonite are a clear exception to this trend, and the other minerals showed no specific trend (Figure 6.7). However, if we consider that the lowest preservations occur in experiment 1, the trend of increasing preservation with increasing amino acid amounts in the mineral surfaces appears more robust. We provide tentative explanations to address these results that will need to be explored in future work.

The general increase of amino acid preservation with increasing spiking concentration may be related to the type of sites where the amino acids were adsorbed.

During the spiking procedure we let amino acids to adsorb to the mineral surfaces for

24 h and then the solution was evaporated. At lower concentrations of the amino acids, they probably adsorbed on the most available sites. As the concentration increased,

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probably the amino acids adsorbed in less exposed sites and were thus more protected.

This effect may have been enhanced by the experimental procedure. There are two obvious stages in the adsorption process. During the first step (adsorption in the suspension) the amount of water remains constant and there was an approach to equilibrium between amino acid in solution and in mineral sites. However, during the drying step the amount of water decreased rapidly and so increased the amino acid concentration in the existing water. This increasing concentration may have forced adsorption into the less exposed sites as the more exposed ones filled quickly.

Another plausible explanation for the increase of preserved amino acid with increasing spiking concentration may be based on the association of adsorbed amino acids on the mineral surfaces. As the amount of adsorbed amino acids increased, especially as the water dried, the amino acids may have entered in contact with each other more frequently on the mineral surface. Possible interactions between amino acids adsorbed in nearby sites may increase their stability and attenuate (in some way) the degradation induced by UV-radiation. Alternatively, some of the amino acids may have been adsorbed as aggregates, of which some molecules were exposed and some were covered by other molecules. This disposition would result in increased protection of the amino acids from UV radiation (Poch et al., 2014). However, we do not think that thick aggregates were likely to form given the low amino acid concentrations

(0.1–5 µmol/g) and the available mineral surface (0.22–129 m2/g, Table 4).

Gypsum is an interesting case in our experiments because it has a large preservation rate while it has no Fe, and neither its surface area nor its average pore size suggests an especially protective capacity (Table 6.4). In addition, gypsum preserved approximately two times more amino acids in experiment 2 than in

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Influence of mineralogy on the preservation of amino acids under simulated Mars conditions experiments 3 and 4 (Figure 6.7). Gypsum is a relatively soluble salt. It is expected that gypsum was partially dissolved during the 24 h contact with the spiking solution and that the dissolved gypsum recrystallized during the drying step of the spiking protocol. It is possible that recrystallization of dissolved calcium sulfate trapped or surrounded amino acids that were adsorbed on the remaining crystals. This putative entrapment of amino acids would have likely increased protection. If this entrapment occurred, its effect would probably have been more evident in the experiments using less concentrated spiking solutions (Figure 6.7). This is because the relative amount of amino acids that were adsorbed during the 24 h contact between the solution and the gypsum was higher (as the total amino acid amount is lower, a greater proportion of it adsorbs early), and then also a higher proportion of them could be trapped by the crystallization during the later drying stage.

6.4.4 - Implications for Mars exploration

In this work, clays and sulfate minerals proved to preserve, on average, more amino acids from UV-induced degradation than silicates, pyroxenes, iron oxides and feldspars. Furthermore, the presence of clays and sulfate minerals on Mars is relevant in the astrobiology context because they indicate past habitable environments where water was present (Squyres et al., 2004 and Downs et al., 2015). Clay minerals are associated with sites of accumulation and preservation of organic molecules due to their high adsorption capacity and their ability to preserve organic matter by stabilizing it and protecting it from oxidation (Mortalnd, 1970, Raussell-Colom and

Serratosa, 1987 and Poch et al., 2015). Sulfate minerals, such as jarosite and gypsum, may actually be opaque to UV radiation and protect life and respective biosignatures

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(Hughes and Lawley, 2003, Aubrey et al., 2006 and Amaral et al., 2007). Because clays of the smectite group and sulfate minerals are (1) related to environments amenable to life and (2) good biosignature preservers, they should be targeted for the detection of organic molecules in future life-searching missions such as NASA's 2020 mission.

Olivine of forsterite composition also preserved considerable amounts of amino acids during the Mars simulation, despite its low surface area and high pore size. Olivine (including low iron varieties) is widely distributed on Mars (Ody et al.,

2013). According to our results, forsterite and perhaps other olivine minerals of low Fe content might be considered good targets for the detection of life biosignatures on

Mars, provided that there are geological clues towards possible habitable environments. However, despite the high amino acid preservation verified in our results, we believe that olivine should be less relevant for life and organic biosignature searching missions due to its usual association with basaltic minerals that do not preserve high amounts of amino acids and high weathering susceptibility by water

(Kuebler et al., 2003).

An important aspect of our experiments in relation to the search for biosignatures on Mars is the mineral ability for amino acid preservation at low amino acid content. Given the low concentrations of organic matter expected on Mars, gypsum, montmorillonite, nontronite, saponite and olivine appear as much better candidates to preserve amino acid biosignatures than the other minerals tested (Figure

6.7). This fact adds one more reason to target smectite clays (nontronite, saponite,

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Influence of mineralogy on the preservation of amino acids under simulated Mars conditions montmorillonite) and gypsum on Mars. For these minerals, their protective ability does not drop at 10 µM amino acid concentration, as appears to happen with the other

Mars-relevant minerals. To further support our results, indigenous chlorinated hydrocarbons were detected by the Curiosity rover in the Yellowknife Bay formation on Mars (informally named the Sheepbed member), which contained ∼20 wt % smectite clay (Ming et al., 2014 and Vaniman et al., 2014).

The amino acid standards used in this experiment ranged from 0.1 µmol/g of mineral to 5 µmol/g, i.e. ranged from ∼10 parts per million (ppm) to 500 ppm for each amino acid present in the mineral matrix. This range of values is quite high when compared to terrestrial Mars soil analogues. As an example, a typical Mars soil analogue from Atacama and Arequipa have individual amino acid concentration in the range of 1–10 ppb (e.g. Peeters et al., 2009), while Mars soil analogues richer in amino acids, such as Salten Skov and some Utah soils, range from 10 ppm to

50 ppm Peeters et al., 2009 and Martins et al., 2011). The abundances used in this thesis are higher than what it is expected to be present on Mars, placing a limit of detection for the preservation of amino acids under Mars conditions.

Furthermore, UV irradiation on Mars is limited to the first millimetres, but energetic particles (solar energetic particles (SEP) and galactic cosmic rays (GCR)) can go deeper in the subsurface, reach organic molecules and contribute to their degradation. A SEP dose of 600–700 mGy/yr can reach the surface of Mars and penetrate to around 10 cm, while GCR are typically capable of penetrating up to 3 m into the subsurface (Parnell et al., 2007) and over geological time, deactivate spores

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and degrade organic species (Dartnell et al., 2007). Therefore, future work should study the influence of the minerals on the preservation of organic molecules under simulated Mars conditions using SEP and GCR.

NOTE: As an important last note, we cannot exclude also the possibility that the way adsorption and simulations were carried out in the Mars simulations experiments influenced the results presented in this chapter. First, the drying step used to induce adsorption on the mineral standards may have caused an overload of amino acids on the mineral surfaces (a catalyst poisoning scenario), particularly considering the fact that 25 amino acids were spiked simultaneously. There is then a possibility that the simulations may not represent a scenario entirely applicable to Mars. Second, we must remember that the results presented in this chapter were based on a single simulation inside the Mars Chamber. It would be desirable to perform multiple simulations using the same conditions, but ensuring that the samples to be irradiated were set in different positions both in the samples support and inside the simulation compartment. This is due to the fact that we cannot guarantee that degradation conditions are uniform inside the Mars simulation chamber. Therefore, multiple simulations combined with sample rotation would ideally minimise this possibility.

Further studies should take these recommedations into account.

6.5 - Conclusions

The UV-induced degradation of 25 amino acids spiked onto augite, basaltic lava, enstatite, goethite, gypsum, hematite, jarosite, labradorite, montmorillonite,

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Influence of mineralogy on the preservation of amino acids under simulated Mars conditions nontronite, olivine and saponite under simulated Mars conditions was analysed and discussed in this chapter. The results indicated that:

(1) D- and L-enantiomers were degraded in the same extent in all experiments.

(2) The proportion of amino acid preservation in each mineral tends to increase with the concentration of amino acids in the spiking solution. At the lowest concentration (1

µM or each amino acid) no amino acids were recovered due to a combination of complete degradation and low extractability.

(3) Results from the experiments at concentrations of 10, 25 and 50 µM (of each amino acid) show that, on average, smectite clays (montmorillonite, nontronite and saponite), sulfates (gypsum and jarosite) and olivine (forsterite) were the minerals that preserved more amino acids. Augite, basaltic lava, enstatite and hematite preserved the least proportions of amino acids.

(4) For the interpretation of the results, several major variables affecting protection from UV radiation were considered: a) amino acid molecular structure and substitution in the α-carbon; b) mineral opacity to UV light, driven mainly by Fe content; c) large surface area and small average pore size are likely to promote amino acid preservation; d) ferrous iron content promotes iron (II) catalysed reactions and thus dissociation of amino acids. None of the above single variables can fully explain our results, but most of them can be related to one or more of these variables.

(5) The results presented in this chapter indicate that rocks with abundant smectite

(montmorillonite, saponite, nontronite) and/or sulfates (gypsum, jarosite) are very good targets to search for amino acid biosignatures (and possibly other type of biosignatures) on Mars, due to the preserving ability of the above minerals, even at

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relatively low amino acid concentration (1 µmol/g). This argument is strengthened because the above minerals typically form in environments amenable to life. As a result, future missions that aim to detect organic molecules on the Red Planet, such as the NASA 2020 mission should consider targeting locations rich in these minerals in order to maximize the chances of finding preserved martian organic molecules.

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Conclusions and future work

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7.1 – Conclusions

The results obtained and presented throughout this dissertation are centred around the study of organic biosignatures in Mars-like environments, in order to gain insight and better understand which martian environments should be targeted for future life-searching missions. To evaluate the preservation characteristics of different environments, amino acids abundances were analysed in three distinct set of samples: two Mars soil analogues, Rio Tinto and hypersaline lakes of Western Australia, and specimens of mineral standards that are known to be present in the Red Planet and were subjected to a simulation of martian environment. Overall the research has been successful in developing criteria that will be useful in identifying localities on Mars in which biosignatures are most likely to be detected, and as such has achieved its goal.

The results of the mineralogy, microbiology and amino acid analyses results of Rio Tinto sediment samples was presented and discussed in Chapter 3. The mineralogy results have shown that these sediments are similar to Mars, mostly due to the presence of relevant Mars iron minerals such as jarosite, hematite and goethite. It was observed that the abundance of amino acids in the Rio Tinto sediments could not be entirely explained by mineralogy, due to the absence of an obvious correlation between the results obtained for mineralogical content and total amino acid abundance. Therefore, the results obtained in this chapter suggest that mineralogical factors are not a good guide to pinpoint locations with detectable biosignatures in future life searching missions to Mars.

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Conclusions and future work

Conversely, microbiology studies, which identified mostly iron-metabolising extremophiles, seemed to better agree with the amino acid abundance analyses, with microbiology results corroborating the lack of detectable amino acids observed in sample RT2. In addition to mineralogy, microbiology and amino acid abundance studies, measurements of carbon, nitrogen and sulfur composition of the samples were found to be useful to interpret amino acid abundance. Samples that contained the highest amount of amino acids also presented the highest amount of elemental carbon.

Moreover, results from nitrogen composition analyses were useful to identify samples that yielded either no detectable amino acids or low amount of amino acids.

Measurements of nitrogen abundances suggest that low amount of amino acids will be found in environments with limited nitrogen availability. Therefore, quantitative measurements of elemental carbon and nitrogen should be considered as a screening tool in future missions to determine which sediments and soils are better suited for the detection of amino acids.

From the analyses presented and discussed in Chapter 3 one can also verify that there was no relationship found between mineralogical profile, microbiology communities and amino acid content on samples collected within a 150 metres area in

Rio Tinto, Spain. This stresses the importance of frequent sampling, even in small areas of interest, in order to obtain a better geochemical knowledge of landing sites on

Mars where life-detection is to be attempted and maximize the chances of success. The results obtained with Rio Tinto sediments should be particularly applicable to environments in Syrtis Major, Nili Fossae and Mawrth Vallis regions on Mars, for which Rio Tinto serves as an analogue. These locations were considered in the

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selection process of NASA’s MSL landing site and may be shortlisted again or even targeted in future life-searching missions.

The results of the studies performed on the sediments collected from the hypersaline lakes from the Yilgarn Craton, another Mars soil analogue, were provided and discussed Chapter 4 and Chapter 5. The mineralogy assemblages found in the samples collected in Lake Brown, Lake Baladjie, Lake Deborah West and Lake

Gilmore were presented in Chapter 4. The results from the XRD analyses of the coarse, fine and soluble fractions from the lacustrine sediment samples show the predominance of evaporitic authigenic salts, such halite and calcium sulfates, that result from the deposition that occurs during evapoconcentration periods of the shallow lacustrine waters. It was observed in these sediments that the variety of evaporitic, authigenic, pedogenic and detrital minerals is influenced by the Archaean bedrock’s composition surrounding the lakes. Aluminium phyllosilicates (kaolinite, halloysite and illite) were the only clays identified in the sediments, which is likely related to their stability in acidic environments. The predominant red colouration and small yellow/red crusts found in the sediments suggested the presence of iron oxide minerals, although these phases could not be detected by XRD. This was possibly due to the fact that their abundance was below the detection limits of the technique or due to poor crystallinity. Iron oxides such as hematite, goethite, chromite and ilmenite were detected by SEM in trace amounts in the four lakes.

Spatial heterogeneity of mineral composition was evident between samples collected in the same lake, including surface and 30cm subsurface samples collected at the same site. Even if the mineral assemblage in Lake Brown, Lake Baladjie and Lake

Deborah West was found to be somewhat similar and constant, the mineralogy of Lake

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Gilmore was found to be different, mostly due to the presence of iron sulfates such as jarosite and alunite. Spatial heterogeneity was also observed in the small region where

Rio Tinto samples were collected (Chapter 3). The mineralogy results from both

Mars analogue environments suggest that frequent sampling is desirable in future missions to Mars, because mineralogical assemblage may differ significantly within very short distances.

The results regarding the amino acid abundances and analyses of microbial communities found in the sediments collected from the hypersaline lakes from the

Yilgarn Craton were presented together in Chapter 5. Sequencing results from 16S rDNA amplicon sequencing revealed that the prokaryotic communities present in the sediments are mostly composed of halophilic archaea and bacteria that require high salinities to thrive. Based on the microbiology results obtained from the analyses on the Rio Tinto and hypersaline lakes from Western Australia (Chapter 3 and Chapter

5), putative martian life might have included microorganisms halotolerant and halophilic as well as microorganisms with a metabolism based on iron. Iron metabolism is one of the most ancient forms used by terrestrial microorganisms to obtain energy and it is also seen as a possibility in iron rich planets such as Mars

(Weber et al., 2006). Moreover, the climatic transition that Mars suffered from a once water rich planet (where life possibly originated) into an extremely arid one suggests that highly saline lakes were thus very likely to have been habitats into which life may have evolved or even persisted.

Similarly to what was observed in the mineralogy results, the sediments from

Lake Gilmore showed a somewhat different composition of the microbial communities to those of Lakes Brown, Baladjie and Deborah West. Samples from Lake Gilmore

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generally showed less readings related to Halobacteria and an increased number of readings related to Cyanobacteria. This may suggest an influence of mineralogy into microbial community composition and distribution, which requires further assessment and investigation.

The GC-MS analyses performed on the sediments from the hypersaline lakes showed that only six samples (two from Lake Baladjie and four from Lake Gilmore) in the whole sample set yielded amino acids in detectable amounts. Unlike what was observed in the case of the Rio Tinto sediments, the amino acid analyses results did not agree with those obtained from the microbial community profiling studies, where life from Archaea and Bacteria domains was detected in all samples. This shows that

1) the detection of amino acids (or biosignatures in general) even in samples collected in extreme habitats on Earth and known to be inhabited by microbial life may not be easily achieved and 2) that lack of detectable amino acids may not be strictly caused by absence of life.

Again, similar to the XRD analyses, amino acid abundances varied greatly in samples closely located, once again demonstrating that environmental conditions may change profoundly in small areas. The results described in Chapter 4 and Chapter 5 should be expected in Mars, namely in locations that likely contained flat enclosed and shallow basins. Such locations could be the Burns formation and flat closed basins and craters found throughout Mars (such as the Cross and Columbus craters located in

Terra Sirenum) which probably had shallow, hypersaline, acidic water bodies and similar conditions to those found on the Yilgarn Craton lakes.

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The detection of amino acids in hypersaline lakes was not straightforward and, more often than not, biosignatures could not be detected despite the presence of life. In the context of life searching missions, the detection of life and respective biosignatures on Mars may be even more difficult if we take into consideration the intrinsic limitations associated with a mission based on a spacecraft sent to Mars. The results of the hypersaline lakes of Western Australia, in particular, suggest that the in situ detection of martian life and biosignatures may be a very difficult task, especially taking into account the relatively limited information about martian habitats and the limited scientific capabilities of a rover exploring the martian surface. The chances of finding life and respective biosignatures will be most likely higher if the whole life on

Mars detection goal is included as part of a sample return mission. Such a mission would allow us in the future to use a much broader range of laboratorial equipment and techniques that would allow a truly interdisciplinary approach on real martian samples, therefore maximizing chances of success.

The influence of mineralogy on the preservation of amino acids in simulated martian environments was addressed and discussed in Chapter 6. The study was centred on the effects of UV-induced degradation of 25 amino acids spiked onto a variety of Mars relevant mineral standards (augite, basaltic lava, enstatite, goethite, gypsum, hematite, jarosite, labradorite, montmorillonite, nontronite, olivine and saponite) under simulated Mars conditions. The results presented and discussed in the chapter suggest that on average, smectite clays (montmorillonite, nontronite and saponite), sulfates (gypsum and jarosite) and olivine (forsterite) were the minerals that preserved more amino acids during the experiments. On the other hand, the samples

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augite, basaltic lava, enstatite and hematite were those where amino acid degradation was more significant and preserved the least amounts of biosignatures.

Several variables were considered for the interpretation of the results obtained from the Mars simulations. These included: molecular structure of the amino acids and respective substitution in the α-carbon; mineral opacity to UV light; mineral surface area; average pore size and ferrous/ferric iron content. Results from the degradation experiments could not be fully explained by one of the considered variables. In fact, the behaviour of amino acids spiked onto minerals under Mars simulations seemed to be influenced to some degree by the multiple factors that were taken into account.

This set of results resembles also the outcomes obtained from the amino acid analyses performed in the Mars soil analogues. In Chapter 3 and Chapter 5 (which reports the amino acid abundances in sediments from Rio Tinto and the hypersaline lakes in the Yilgarn Craton, respectively) it was verified that amino acid content was not solely related with a single environmental factor, namely sediment mineralogy.

These results hint that amino acid abundance in Mars analogue sediments may also depend on multiple factors, emphasizing that multiple set of analyses are needed in order to predict what are the best sediments to find for life and its biosignatures on

Mars.

One of the main goals of this thesis was to identify the best locations to find organic signatures of life on Mars. The results of Chapter 6 show that amino acid preservation is linked to amino acid concentration in the samples. The results of the experiments carried out with the lowest amount of spiked amino acids (1 µM or each amino acid) suggest that the lack of amino acid detection after Mars simulations were

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Conclusions and future work

due to a combination of complete degradation and low extractability of the molecules.

These results should be expected in Mars too. The amino acid concentration range used in the simulation experiments was between ∼10 parts ppm up to 500 ppm for each amino acid present in the mineral samples. This was higher than typical Mars soil analogue amino acid abundances reported from Atacama and Arequipa (amino acid concentration in the range of 1–10 ppb - Peeters et al., 2009) or in the same range as the amino acid abundances of the sediments collected from Rio Tinto and Western

Australia (Chapter 3 and Chapter 5, respectively). Therefore, the results presented in

Chapter 6 represent a limit of detection for the preservation of amino acids under

Mars conditions.

Locations on Mars containing sulfate minerals and smectite clays should be priority targets for the search of organic signature of martian life. Their occurrence is related to geochemical processes in environments that contained water and were habitable. On top of this, sulfates and clays are known to be sites of accumulation and deposition of organic molecules. Ultimately, according to the results reported in this thesis, the organic molecules that may be associated with these minerals may be protected from harmful radiation on Mars, even in environments with low concentrations of organic biosignatures.

In Chapter 6 it was also observed that olivine with low iron content preserved significant amount of amino acids. Olivine-rich locations could also be considered, in principle, as good targets for life searching missions, provided that there are geological clues indicating possible habitable conditions.

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7.2 – Future work

The results presented in this thesis contribute to the preparation of future life searching missions through the study of the abundance and distribution of life and respective biosignatures in Mars soil analogues. Results on the preservation of amino acids under simulated Mars conditions were also presented, which allowed the identification of which minerals are the best suited to be targeted in order to find preserved organic biosignatures of putative martian life.

The results presented in this dissertation also lay the foundations for further experiments that may contribute towards future life-detection missions and the whole subject of finding organic biosignatures on Mars.

The extractability of amino acids from mineral matrices should be addressed.

Results from the Mars Chamber simulations in Chapter 6 showed that extraction of biosignatures in environments with low concentrations of organic molecules, which is expected on Mars, may negatively influence future life detection attempts. It is therefore important to identify which minerals simultaneously show amino acid protection potential and good amino acid extractability. This is also related to the adsorption of organic molecules to mineral matrices. The phenomena of amino acid adsorption onto Mars-relevant mineral matrices should be studied in more detail, including the type of adsorption, adsorption mechanisms, influence of biosignature concentration, specific degradation behaviours between pairs of minerals/amino acids and catalytic influences. Also, future work should also follow the recommendations already given in the end of Chapter 6.

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Furthermore, the influence of radiation that can penetrate deeper in the martian regolith (SEP and GCR) on the preservation of amino acids should also be investigated. It is suggested that similar simulations to those performed with UV radiation in this work should also be performed with SEP and GCR in order to identify which minerals confer the best preservation potential.

In addition, another important experiment that should be performed would be assessing and comparing the degradation of biosignatures in their pure state with the degradation of amino acids spiked onto minerals under simulated Mars conditions.

Such an experiment could potentially identify which minerals actually accelerate and contribute to amino acid degradation under simulated Mars conditions, and would therefore enable us to determine which locations on Mars should be actually avoided in the quest for detecting organic signature of life. Simulations should also include: 1) other molecules that are considered important targets for life detection, such as nucleobases, proteins, hydrocarbons and carboxylic acids and 2) real sediment samples from Mars soils analogues in order to analyse the behavior of organic signatures of life under Mars-like environment.

The results obtained from the mineralogy, microbiology and amino acid analyses of Rio Tinto and hypersaline lakes from Western Australia sediment samples showed that it was difficult to establish a correlation between the different sets of data.

Future attempts to perform such interdisciplinary analyses of environmental samples should rely on the interpretation of data sets using multivariate statistical analysis using softwares such as CANOCO, which may allow an easier identification of

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correlations between mineralogy, microbial ecology and biosignature abundance and respective distribution. Also, future work is needed to study in detail the eukaryotic microbial communities or even identify new microbial species in these Mars soil analogues.

In his book “War of the Worlds” published in 1898, H. G. Wells described how the fictional martians, described as octopus-like creatures with oily brown skin, scrutinised our planet from afar with jealous intent and how they used their technological superiority with the aim to invade southeast England. Ironically, in a time that humans are actually starting to plan, as a long term goal, a real invasion of the Red Planet, we have still yet to find any evidence for any martians or any signatures of their presence in the Red Planet. Despite all the high tech machines developed, constructed and sent to the Red Planet, it seems that detecting life on inhospitable or Mars-like environments on Earth is far more trivial compared with detecting it on Mars.

The search for extraterrestrial life is one of the main scientific challenges for science. The work presented in this PhD thesis represents another small step in this big common endeavour which is finding extraterrestrial life and…

The Organic Signatures of Life on Mars.

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References

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Annexes

309

Annex 1 - General information about the lacustrine sediment samples collected in the four ephemeral acidic lakes in the Yilgarn Craton, Western

Australia: Victoria Rock (LVR), Lake Lefroy (LL), Lake Cowan (LC) and Lake Dundas (LD).

Lake Victoria Rock (LVR) Lake Lefroy (LL) Lake Cowan (LC) Lake Dundas (LD)

LVR6 LVR1 LVR2 LVR3 LVR4 LVR5 LVR7 LVR8 LL1 LL2 LL3 LL4 LL5 LL6 LC1 LC2 LC3 LC4 LD 1 LD2 LD3 LD4 LD5

Sub a S Sub S Sub S S Sub S Sub S Sub S Sub S Sub S Sub S S Sub S S site (10cm) Sample name and

S31.36019, S31.35980, S31.35787, S31.35659, S32.16084 S32.16167 S32.38191 S32.38282 S32.38319 S32.38343 S31.23428, S31.23429, S31.23615, E119.70271 E119.70480 E119.70403 E119.70491 E121.76917 E121.76797 E121.79113 E121.79294 E121.794330 E121.79523 E121.64400 E121.64406 E121.64480

Elevation: Elevation: Elevation: Elevation: Elevation: Elevation: Elevation: Elevation: Elevation: Elevation: Elevation: 294 m Elevation: 293 m Elevation: 295 m GPS 366 m 359 m 359 m 357 m 269 m 264 m 248 m 248 m 250 m 248 m coordinates

6.0 6.0 4.5 6.0 6.0 6.0 6.1 6.9 5.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.2 6.0 6.0 6.0 6.9 7.2 pH Soil

k brown k

mud mud mud mud mud and Colour Dry reddish mud reddish Dry mud reddish Dry mud reddish Dry mud reddish Dry Muddy and re/brown and Muddy Dark brown/black dry dry brown/black Dark dry brown/black Dark dry brown/black Dark dry brown/black Dark dry brown/black Dark Sandy and dark brown dark and Sandy brown dark and Sandy Muddy and dark brown dark and Muddy brown dark and Muddy brown dark and Muddy brown dark and Muddy brown dark and Muddy brown dark and Muddy brown dark and Muddy dar and Muddy brown dark and Muddy brown dark and Muddy Muddy, dry and re/brown and dry Muddy, Texture aS- Samples collected at surface. Sub- Samples from 30 cm subsurface, unless stated otherwise.

310

Annex 2 – Mass spectra and fragmentation patterns of derivatized amino acids standards

This annex contains the mass spectra of derivatized amino acids that are being targeted in this work. The following data was obtained from derivatized amino acid standards samples used to elaborate GC-MS calibration curves. On the right side of each amino acid mass spectrum, there is a molecular structure which illustrates what are the molecular fragments that originate the main m/z peaks.

100.00 154 90.00 α-AIB 80.00

70.00 60.00 50.00 40.00 30.00 Relative Relative abundance 20.00 59 69 114 10.00 0.00 m/z

Figure A2.1: Mass spectrum and main fragments of derivatized α-AIB.

100.00 90.00 168 Isovaline

80.00 70.00 60.00 50.00 40.00 114 30.00 Revative Revative abundance 20.00 69 10.00 0.00 m /z

Figure A2.2: Mass spectrum and main fragments of derivatized isovaline.

311

100.00 140 90.00 Alanine 80.00

70.00 60.00 50.00 40.00 30.00 Relative Relative abundance 69 20.00 168 10.00 0.00 m/z

Figure A2.3: Mass spectrum and main fragments of derivatized alanine.

100.00 154 90.00 80.00 α-ABA 70.00 60.00 50.00 40.00 30.00 Relative Relative abundance 126 20.00 69 10.00 0.00 m/z

Figure A2.4: Mass spectrum and main fragments of derivatized α-ABA.

312

100.00 168 90.00 Valine 80.00

70.00 60.00 50.00 40.00

Relative Relative abundance 30.00 153 20.00 10.00 69 0.00 m/z

Figure A2.5: Mass spectrum and main fragments of derivatized valine.

100.00 126

80.00 Glycine

60.00

40.00

Relaive Relaive abundance 69 20.00 154

0.00 m/z

Figure A2.6: Mass spectrum and main fragments of derivatized glycine.

313

100.00 168 90.00 Norvaline 80.00

70.00 126 60.00 50.00 69 40.00 30.00 Relative Relative abundance 20.00 10.00 0.00 m/z

Figure A2.7: Mass spectrum and main fragments of derivatized norvaline.

100.00 168 90.00 β-Alanine 80.00

70.00 60.00 69 50.00 126 40.00

Relative Relative abundances 30.00 185 20.00 10.00 0.00 m/z

Figure A2.8: Mass spectrum and main fragments of derivatized β-alanine.

314

100.00 140 90.00 β-ABA 80.00 69

70.00

60.00 182 50.00 40.00

Relative Relative abundance 30.00 20.00 10.00 0.00 m/z

Figure A2.9: Mass spectrum and main fragments of derivatized β-ABA.

100.00 182 90.00 80.00

69 β-AIB 70.00 60.00 50.00 40.00 114 30.00 Relative Relative abundance 20.00 126 140 153 10.00 0.00 m/z

Figure A2.10: Mass spectrum and main fragments of derivatized β-AIB.

315

100.00 182 90.00 80.00

γ-ABA 70.00 126 60.00 50.00 40.00 69 154 30.00 Relative Relative abundance 140 20.00 10.00 0.00 m/z

Figure A2.11: Mass spectrum and main fragments of derivatized γ-ABA.

100.00 69 140 90.00 80.00 Leucine 70.00 60.00

50.00 182 40.00

Relative Relative abundance 30.00 20.00 10.00 0.00 m/z

Figure A2.12: Mass spectrum and main fragments of derivatized leucine.

316

100.00 182 90.00 Norleucine 80.00 69 70.00 60.00 50.00

40.00 126

Relative Relative abundances 30.00 140 20.00 114 10.00 0.00 m/z

Figure A2.13: Mass spectrum and main fragments of derivatized norleucine.

100.00 184 90.00 80.00 Aspartic acid

70.00 139 212 60.00 50.00 40.00 30.00 166 Relative Relative abundance 226 20.00 10.00 0.00 m/z

Figure A2.14: Mass spectrum and main fragments of derivatized aspartic acid.

317

100.00 198 90.00 Glutamic acid 180 80.00 70.00 152 60.00 50.00 226 40.00

Relative Relative abundance 30.00 20.00 139 10.00 0.00 m/z

Figure A2.15: Mass spectrum and main fragments of derivatized glutamic acid.

100.00 90.00 210 6-AHA 126

80.00 70.00 60.00 50.00 69 114 40.00 30.00 Relative Relative abundance 20.00 168 10.00 0.00 m/z

Figure A2.16: Mass spectrum and main fragments of derivatized 6-AHA.

318

Annex 3 – Amino acid standard calibration curves

This annex contains the calibration curves for the derivatized amino acids that were targeted in this work. This calibration curves were used for the quantification of amino acids on Mars analogue soils and mineral standards.

α-AIB 10 9 8

7 6

peak areapeak 5 4

3 y = 1154956809.4134x - 0.0017 2 R² = 0.9750

ratio amino acid peak area/internal area/internal standard peak acid amino ratio 1 0 0 2E-09 4E-09 6E-09 8E-09 mass injected into GCMS (g/injection)

Figure A3.1: GC-MS calibration curve for derivatized α-AIB.

9 D,L-IsovalineTitle 8 7

Title 4

standard peak area standard 3 y = 499063076.2865x - 0.0054 R² = 0.9778 2 ratio amino acid peak area/internal area/internal peak acid amino ratio 1 0 0 5E-09 1E-08 1.5E-08 2E-08 mass injected into GCMS (g-injection) Figure A3.2: GC-MS calibration curve for derivatized D,L-Isovaline.

319

itle D-α-ABA 6

2 y = 826994223.3696x - 0.0248 R² = 0.9840 1

ratio amino acid peak area/internal area area/internal standard peak acid amino ratio 0 0 1E-09 2E-09 3E-09 4E-09 5E-09 6E-09 7E-09 8E-09 mass injected into GCMS (g/injection)

Figure A3.3: GC-MS calibration curve for derivatized D-α-ABA.

8 L-α-ABA 7

3 y = 928199634.1335x - 0.0083 2 R² = 0.9917

ratio amino acid peak area/internal peak area area/internal standard peak acid amino ratio 0 0 1E-09 2E-09 3E-09 4E-09 5E-09 6E-09 7E-09 8E-09 mass injected into GCMS (g/injection)

Figure A3.4: GC-MS calibration curve for derivatized L-α-ABA.

320

7 D-Alanine Title 6

area 3

2 y = 995709450.4074x - 0.1072 R² = 0.9924 1

ratio amino acid peak area/internal peak area/internal standard peak acid amino ratio 0 0 1E-09 2E-09 3E-09 4E-09 5E-09 6E-09 7E-09 mass injected into GCMS (g/injection)

Figure A3.5: GC-MS calibration curve for derivatized D-Alanine.

L-Alanine

3 y = 1065070827.2639x - 0.0487 R² = 0.9903

1 ratio amino acid peak area/internal area area/internal standard peak acid amino ratio 0 0 1E-09 2E-09 3E-09 4E-09 5E-09 6E-09 7E-09 mass injected into GCMS (g/injection)

Figure A3.6: GC-MS calibration curve for derivatized L-Alanine.

321

5 D-Valine 4.5

3.5

2.5

1.5

1 y = 551305880.2163x - 0.0002 R² = 0.9911 0.5

ratio amino acid peak area/internal peak area area/internal standard peak acid amino ratio 0 0 1E-09 2E-09 3E-09 4E-09 5E-09 6E-09 7E-09 8E-09 9E-09 mass injected into GCMS (g/injection)

Figure A3.7: GC-MS calibration curve for derivatized D-Valine.

5 L-Valine 4.5

3.5

2.5

1.5

1 y = 583773921.5309x - 0.0099 0.5 R² = 0.9932

0 ratio amino acid peak area/internal peak area area/internal standard peak acid amino ratio 0 2E-09 4E-09 6E-09 8E-09 1E-08 mass injected into GCMS (g/injection)

Figure A3.8: GC-MS calibration curve for derivatized L-Valine.

322

4 Glycinert Title 3.5

2.5

1.5 y = 530773476.2191x - 0.0058 1 R² = 0.9895

0.5 ratio amino acid area peak/internal peak area standard areaacid amino peak/internal ratio 0 0 1E-09 2E-09 3E-09 4E-09 5E-09 mass injected into GCMS (g/injection)

Figure A3.9: GC-MS calibration curve for derivatized Glycine.

4.5 D-Norvaline 4

3.5

2.5

1.5 y = 519038497.6093x + 0.0002 1 R² = 0.9937

0.5

ratio amino acid peak area/internal peak area area/internal standard peak acid amino ratio 0 0 1E-09 2E-09 3E-09 4E-09 5E-09 6E-09 7E-09 8E-09 9E-09 mass injected into GCMS (g/injection)

Figure A3.10: GC-MS calibration curve for derivatized D-Norvaline.

323

4.5 L-Norvaline 4

3.5

2.5

1.5 y = 510402616.9917x - 0.0004 R² = 0.9937 1

0.5

ratio amino acid peak area/internal peak area area/internal standard peak acid amino ratio 0 0 1E-09 2E-09 3E-09 4E-09 5E-09 6E-09 7E-09 8E-09 9E-09 mass injected into GCMS (g/injection)

Figure A3.11: GC-MS calibration curve for derivatized L-Norvaline.

3.5 β-Alanine

2.5

1.5

1 y = 441275073.2699x + 0.0005 R² = 0.9889 0.5

ratio amino acid peak area/internal peak area area/internal standard peak acid amino ratio 0 0 1E-09 2E-09 3E-09 4E-09 5E-09 6E-09 7E-09 mass injected into GCMS (g/injection)

Figure A3.12: GC-MS calibration curve for derivatized β-Alanine.

324

0.8 D-β-AIB 0.7

0.6

0.5

0.4

0.3

0.2 y = 184673512.0147x - 0.0301 R² = 0.9963 0.1

ratio amino acid peak area/internal peak area area/internal standard peak acid amino ratio 0 0 5E-10 1E-09 1.5E-09 2E-09 2.5E-09 3E-09 3.5E-09 4E-09 mass injected into GCMS (g/injection)

Figure A3.13: GC-MS calibration curve for derivatized D-β-AIB.

0.9

L-β-AIB 0.8

0.7

0.6

0.5

0.4 y = 228218923.4570x - 0.0410 0.3 R² = 0.9931

0.2

0.1

0 ratio amino acid peak area areapeak standard acid amino /internal ratio 0 5E-10 1E-09 1.5E-09 2E-09 2.5E-09 3E-09 3.5E-09 4E-09 -0.1 mass injected into GCMS (g/injection)

Figure A3.14: GC-MS calibration curve for derivatized L-β-AIB.

325

1.8 D-β-ABA 1.6

1.4

1.2

0.8

0.6 y = 452234920.6018x - 0.0377 0.4 R² = 0.9960 0.2

0 ratio amino acid peak area/internal peak area area/internal standard peak acid amino ratio 0 5E-10 1E-09 1.5E-09 2E-09 2.5E-09 3E-09 3.5E-09 4E-09 mass injected into GCMS (g/injection)

Figure A3.15: GC-MS calibration curve for derivatized D-β-ABA.

1.8 L-β-ABA 1.6

1.4

1.2

0.8

0.6

0.4 y = 402141399.7442x - 0.0170 R² = 0.9949 0.2 ratio amino acid peak area/internal standard peak area peak standard area/internal peak acid amino ratio 0 0 5E-10 1E-09 1.5E-09 2E-09 2.5E-09 3E-09 3.5E-09 4E-09

mass injected into GCMS (g/injection)

Figure A3.16: GC-MS calibration curve for derivatized L-β-ABA.

326

5 D-Leucine 4.5

3.5

2.5

1.5

1 y = 437020079.2389x + 0.0002 R² = 0.9887 0.5

ratio amino acid peak area/internal peak area area/internal standard peak acid amino ratio 0 0 1E-09 2E-09 3E-09 4E-09 5E-09 6E-09 7E-09 8E-09 9E-09 1E-08 mass injected into GCMS (g/injection)

Figure A3.17: GC-MS calibration curve for derivatized D-Leucine.

5 L-Leucine 4.5

3.5

2.5

1.5 y = 438590809.2582x - 0.0006 1 R² = 0.9937 0.5

ratio amino acid peak area/internal peak area area/internal standard peak acid amino ratio 0 0 1E-09 2E-09 3E-09 4E-09 5E-09 6E-09 7E-09 8E-09 9E-09 1E-08 mass injected into GCMS (g/injection)

Figure A3.18: GC-MS calibration curve for derivatized L-Leucine.

327

4 D-Norleucine

3.5

2.5

1.5 y = 369250671.7314x - 0.0664 R² = 0.9985 1

0.5

0 ratio amino acid peak area/internal peak area area/internal standard peak acid amino ratio 0 1E-09 2E-09 3E-09 4E-09 5E-09 6E-09 7E-09 8E-09 9E-09 1E-08 mass injected into GCMS (g/injection)

Figure A3.19: GC-MS calibration curve for derivatized D-Norleucine.

L-Norleucine 3.5

2.5

1.5

1 y = 387655251.2126x - 0.0161 R² = 0.9955 0.5 ratio amino acid peak area/internal peak area area/internal standard peak acid amino ratio

0 0 1E-09 2E-09 3E-09 4E-09 5E-09 6E-09 7E-09 8E-09 9E-09 1E-08 mass injected into GCMS (g/injection)

Figure A3.20: GC-MS calibration curve for derivatized L-Norleucine.

328

2.5 γ-ABA

1.5

0.5 y = 293031624.7618x - 0.0351 R² = 0.9926 ratio amino acid peakacid standardpeakratio area/internalamino area 0 0 1E-09 2E-09 3E-09 4E-09 5E-09 6E-09 7E-09 mass injected into GCMS (g/injection)

Figure A3.21: GC-MS calibration curve for derivatized γ-ABA.

D-Aspartic Acid 3.5

2.5

1.5

1 y = 344934676.9265x - 0.0770 R² = 0.9959 0.5

ratio amino acid peak area/internal peak area area/internal standard peak acid amino ratio 0 0 1E-09 2E-09 3E-09 4E-09 5E-09 6E-09 7E-09 8E-09 9E-09 mass injected into GCMS (g/injection)

Figure A3.22: GC-MS calibration curve for derivatized D-Aspartic acid.

329

4 L-Aspartic Acid 3.5

2.5

area 1.5

1 y = 339733505.7016x - 0.0651 0.5 R² = 0.9963

0 ratio amino acid peak area/internal peak area/internal standard peak acid amino ratio 0 1E-09 2E-09 3E-09 4E-09 5E-09 6E-09 7E-09 8E-09 9E-09 mass injected into GCMS (g/injection)

Figure A3.23: GC-MS calibration curve for derivatized L-Aspartic acid.

3.5

D-Glutamic Acid

2.5

1.5

1 y = 272261256.3077x - 0.0643 0.5 R² = 0.9952 ratio acid amino peak area/internalstandard peak area 0 0 1E-09 2E-09 3E-09 4E-09 5E-09 6E-09 7E-09 8E-09 9E-09 1E-08 mass injected into GCMS (g/injection) Figure A3.24: GC-MS calibration curve for derivatized D-Glutamic acid.

330

4 L-Glutamic Acid 3.5

2.5

2 area

1.5

1 y = 277926496.3682x - 0.0642 R² = 0.9935 0.5 ratio acid amino peak area/internalstandaard peak 0 0 1E-09 2E-09 3E-09 4E-09 5E-09 6E-09 7E-09 8E-09 9E-09 1E-08 mass inejected into GCMS (g/injection)

Figure A3.25: GC-MS calibration curve for derivatized L-Glutamic acid.

2.5 6-AHA

1.5

area 1

0.5 y = 202855934.5041x - 0.0697 R² = 0.9941 ratio acid amino peak area/internalstandard peak 0 0 1E-09 2E-09 3E-09 4E-09 5E-09 6E-09 7E-09 8E-09 9E-09 mass injected into GCMS (g/injection)

Figure A3.26: GC-MS calibration curve for derivatized 6-AHA.

331

Annex 4 – XRD of Rio Tinto sediment samples

Figure A4.1: XRD Diffractogram obtained for sample RT1.

Figure A4.2: XRD Diffractogram obtained for sample RT2.

Figure A4.3: XRD Diffractogram obtained for sample RT3.

332

Figure A4.4: XRD Diffractogram obtained for sample RT4.

Figure A4.5: XRD Diffractogram obtained for sample RT5.

Figure A4.6: XRD Diffractogram obtained for sample RT6.

333

Figure A4.7: XRD Diffractogram obtained for sample RT7.

Figure A4.8: XRD Diffractogram obtained for sample RT8.

Figure A4.9: XRD Diffractogram obtained for sample RT9.

334

Figure A4.10: XRD Diffractogram obtained for sample RT10.

335

Annex 5 – XRD of the hypersaline lakes from Western Australia

Annex 5.1 – XRD of coarse fractions

Annex 5.1.1- Lake Brown XRD coarse fraction

Figure A5.1.1.1: XRD Diffractogram obtained for sample LB1’s coarse fraction.

Figure A5.1.1.2: XRD Diffractogram obtained for sample LB2’s coarse fraction.

336

Figure A5.1.1.3: XRD Diffractogram obtained for sample LB3’s coarse fraction.

Figure A5.1.1.4: XRD Diffractogram obtained for sample LB4’s coarse fraction.

337

Figure A5.1.1.5: XRD Diffractogram obtained for sample LB5’s coarse fraction.

Figure A5.1.1.6: XRD Diffractogram obtained for sample LB6’s coarse fraction.

338

Figure A5.1.1.7: XRD Diffractogram obtained for sample LB7’s coarse fraction.

Annex 5.1.2-Lake Baladjie XRD coarse fraction

Figure A5.1.2.1: XRD Diffractogram obtained for sample LBa1’s coarse fraction.

339

Figure A5.1.2.2: XRD Diffractogram obtained for sample LBa2’s coarse fraction.

Figure A5.1.2.3: XRD Diffractogram obtained for sample LBa3’s coarse fraction.

340

Figure A5.1.2.4: XRD Diffractogram obtained for sample LBa4’s coarse fraction.

Figure A5.1.2.5: XRD Diffractogram obtained for sample LBa5’s coarse fraction.

341

Figure A5.1.2.6: XRD Diffractogram obtained for sample LBa6’s coarse fraction.

Figure A5.1.2.7: XRD Diffractogram obtained for sample LBa7’s coarse fraction.

342

Figure A5.1.2.8: XRD Diffractogram obtained for sample LBa8’s coarse fraction.

Annex 5.1.3-Lake Deborah West XRD coarse fraction

Figure A5.1.3.1: XRD Diffractogram obtained for sample LDW1’s coarse fraction.

343

Figure A5.1.3.2: XRD Diffractogram obtained for sample LDW2’s coarse fraction.

Figure A5.1.3.3: XRD Diffractogram obtained for sample LDW3’s coarse fraction.

344

Figure A5.1.3.4: XRD Diffractogram obtained for sample LDW4’s coarse fraction.

Annex 5.1.4-Lake Gilmore XRD coarse fraction

Figure A5.1.4.1: XRD Diffractogram obtained for sample LG1’s coarse fraction.

345

Figure A5.1.4.2: XRD Diffractogram obtained for sample LG2’s coarse fraction.

Figure A5.1.4.3: XRD Diffractogram obtained for sample LG3’s coarse fraction.

346

Figure A5.1.4.4: XRD Diffractogram obtained for sample LG4’s coarse fraction.

Figure A5.1.4.5: XRD Diffractogram obtained for sample LG5’s coarse fraction.

347

Figure A5.1.4.6: XRD Diffractogram obtained for sample LG6’s coarse fraction.

Figure A5.1.4.7: XRD Diffractogram obtained for sample LG7’s coarse fraction.

348

Figure A5.1.4.8: XRD Diffractogram obtained for sample LG8’s coarse fraction.

Annex 5.2 – XRD of fine fractions Annex 5.2.1- Lake Brown XRD fine fraction

Figure A5.2.1.1: XRD Diffractogram obtained for sample LB1’s fine fraction.

349

Figure A5.2.1.2: XRD Diffractogram obtained for sample LB2’s fine fraction.

Figure A5.2.1.3: XRD Diffractogram obtained for sample LB3’s fine fraction.

350

Figure A5.2.1.4: XRD Diffractogram obtained for sample LB4’s fine fraction.

Figure A5.2.1.5: XRD Diffractogram obtained for sample LB5’s fine fraction.

351

Figure A5.2.1.6: XRD Diffractogram obtained for sample LB6’s fine fraction.

Figure A5.2.1.7: XRD Diffractogram obtained for sample LB7’s fine fraction.

352

Annex 5.2.2- Lake Baladjie XRD fine fraction

Figure A5.2.2.1: XRD Diffractogram obtained for sample LBa1’s fine fraction.

Figure A5.2.2.2: XRD Diffractogram obtained for sample LBa2’s fine fraction.

353

Figure A5.2.2.3: XRD Diffractogram obtained for sample LBa3’s fine fraction.

Figure A5.2.2.4: XRD Diffractogram obtained for sample LBa4’s fine fraction.

354

Figure A5.2.2.5: XRD Diffractogram obtained for sample LBa5’s fine fraction.

Figure A5.2.2.6: XRD Diffractogram obtained for sample LBa6’s fine fraction.

355

Figure A5.2.2.7: XRD Diffractogram obtained for sample LBa7’s fine fraction.

Figure A5.2.2.8: XRD Diffractogram obtained for sample LBa8’s fine fraction.

356

Annex 5.2.3- Lake Deborah West XRD fine fraction

Figure A5.2.3.1: XRD Diffractogram obtained for sample LDW1’s fine fraction.

Figure A5.2.3.2: XRD Diffractogram obtained for sample LDW2’s fine fraction.

357

Figure A5.2.3.3: XRD Diffractogram obtained for sample LDW3’s fine fraction.

Figure A5.2.3.4: XRD Diffractogram obtained for sample LDW4’s fine fraction.

358

Annex 5.2.4- Lake Gilmore XRD fine fraction

Figure A5.2.4.1: XRD Diffractogram obtained for sample LG1’s fine fraction.

Figure A5.2.4.2: XRD Diffractogram obtained for sample LG2’s fine fraction.

359

Figure A5.2.4.3: XRD Diffractogram obtained for sample LG3’s fine fraction.

Figure A5.2.4.4: XRD Diffractogram obtained for sample LG4’s fine fraction.

360

Figure A5.2.4.5: XRD Diffractogram obtained for sample LG5’s fine fraction.

Figure A5.2.4.6: XRD Diffractogram obtained for sample LG6’s fine fraction.

361

Figure A5.2.4.7: XRD Diffractogram obtained for sample LG7’s fine fraction.

Figure A5.2.4.8: XRD Diffractogram obtained for sample LG8’s fine fraction.

362

Annex 5.3 – XRD of soluble fractions Annex 5.3.1- Lake Brown XRD soluble fraction

Figure A5.3.1.1: XRD Diffractogram obtained for sample LB1’s soluble fraction.

Figure A5.3.1.2: XRD Diffractogram obtained for sample LB2’s soluble fraction.

363

Figure A5.3.1.3: XRD Diffractogram obtained for sample LB3’s soluble fraction.

Figure A5.3.1.4: XRD Diffractogram obtained for sample LB4’s soluble fraction.

364

Figure A5.3.1.5: XRD Diffractogram obtained for sample LB5’s soluble fraction.

Figure A5.3.1.6: XRD Diffractogram obtained for sample LB6’s soluble fraction.

365

Figure A5.3.1.7: XRD Diffractogram obtained for sample LB7’s soluble fraction.

Annex 5.3.2- Lake Baladjie XRD soluble fraction

Figure A5.3.2.1: XRD Diffractogram obtained for sample LBa1’s soluble fraction.

366

Figure A5.3.2.2: XRD Diffractogram obtained for sample LBa2’s soluble fraction.

Figure A5.3.2.3: XRD Diffractogram obtained for sample LBa3’s soluble fraction.

367

Figure A5.3.2.4: XRD Diffractogram obtained for sample LBa4’s soluble fraction.

Figure A5.3.2.5: XRD Diffractogram obtained for sample LBa5’s soluble fraction.

368

Figure A5.3.2.6: XRD Diffractogram obtained for sample LBa6’s soluble fraction.

Figure A5.3.2.7: XRD Diffractogram obtained for sample LBa7’s soluble fraction.

369

Figure A5.3.2.8: XRD Diffractogram obtained for sample LBa8’s soluble fraction.

Annex 5.3.3- Lake Deborah West XRD soluble fraction

Figure A5.3.3.1: XRD Diffractogram obtained for sample LDW1’s soluble fraction.

370

Figure A5.3.3.2: XRD Diffractogram obtained for sample LDW2’s soluble fraction.

Figure A5.3.3.3: XRD Diffractogram obtained for sample LDW3’s soluble fraction.

371

Figure A5.3.3.4: XRD Diffractogram obtained for sample LDW4’s soluble fraction.

Annex 5.3.4- Lake Gilmore XRD soluble fraction

Figure A5.3.4.1: XRD Diffractogram obtained for sample LG1’s soluble fraction.

372

Figure A5.3.4.2: XRD Diffractogram obtained for sample LG2’s soluble fraction.

Figure A5.3.4.3: XRD Diffractogram obtained for sample LG3’s soluble fraction.

373

Figure A5.3.4.4: XRD Diffractogram obtained for sample LG4’s soluble fraction.

Figure A5.3.4.5: XRD Diffractogram obtained for sample LG5’s soluble fraction.

374

Figure A5.3.4.6: XRD Diffractogram obtained for sample LG6’s soluble fraction.

Figure A5.3.4.7: XRD Diffractogram obtained for sample LG7’s soluble fraction.

375

Figure A5.3.4.8: XRD Diffractogram obtained for sample LG8’s soluble fraction.

376

Annex 6 – XRD of Mars relevant mineral samples

This annex contains the X-ray diffractograms obtained from the Mars relevant mineral standards used for the Mars chamber simulations described in Chapter 6.

Figure A6.1: X-ray diffraction pattern obtained from the XRD analysis of augite.

377

Figure A6.2: X-ray diffraction pattern obtained from the XRD analysis of basalt glass.

Figure A6.3: X-ray diffraction pattern obtained from the XRD analysis of enstatite.

378

Figure A6.4: X-ray diffraction pattern obtained from the XRD analysis of goethite.

Figure A6.5: X-ray diffraction pattern obtained from the XRD analysis of gypsum.

379

Figure A6.6: X-ray diffraction pattern obtained from the XRD analysis of hematite.

Figure A6.7: X-ray diffraction pattern obtained from the XRD analysis of jarosite.

380

Figure A6.8: X-ray diffraction pattern obtained from the XRD analysis of labradorite.

Figure A6.9: X-ray diffraction pattern obtained from the XRD analysis of montmorillonite.

381 Figure A6.10: X-ray diffraction pattern obtained from the XRD analysis of nontronite.

Figure A6.11: X-ray diffraction pattern obtained from the XRD analysis of olivine.

382 Figure A6.12: X-ray diffraction pattern obtained from the XRD analysis of saponite.

383 384