MOLECULAR ANALYSIS OF MICROBIAL COMMUNITIES FROM OIL INDUSTRY ENVIRONMENTS Magdalena K. Sztyler A thesis submitted in partial fulfilment of the requirements for the award of the degree of Doctor of Philosophy of the University of Portsmouth Institute of Biomedical and Biomolecular Sciences School of Pharmacy and Biomedical Sciences May 2014 “Więcej się można nauczyć podróżując...” Olga A. Jackowska Rodzicom AUTHORS’ DECLARATION Whilst registered as a candidate for the above degree, I have not been registered for any other research award. The results and conclusions embodied in this thesis are the work of the named candidate and have not been submitted for any other academic award. Magdalena K. Sztyler I ABSTRACT The effects of microbiologically influenced corrosion (MIC) can be very expensive to correct, dangerous to workers and its mechanisms are poorly understood. Understanding these processes is important so that they can be monitored and mitigated (Koch et al., 2001). It is now accepted that for the assessment of biocorrosion risks, the most powerful approach is to detect functional genes encoding the enzymes that play an important part in material deterioration (Schadt et al., 2004). The main aim of this study was to identify the microbial community present in corroded and non-corroded systems, and to detect genes that might be implicated in corrosion processes, particularly iron corrosion, so that a biochip could be designed for risk assessment of oil environments. In this thesis the microbial populations and their actives were assessed using sequencing and hybridisation techniques for three oil field sites, generating information that can help identify MIC risk. The final section of the thesis describes the development and design of functional gene probes, identified from hybridisation studies that might be included in a biochip for risk assessment in oil field environments. Microbial groups known to be involved in MIC, such as sulphate-reducing procaryota, iron-reducing bacteria, nitrate-reducing bacteria, hydrocarbon- degrading bacteria were detected, according to their 16S rRNA gene sequence, in the water injection system and production pipelines. In addition to these expected groups, sequences for Firmicutes, acetogens and methanogens were detected. Firmicutes, primarily Clostridium species, and Synergistetes sequences pre- dominated the corroded systems. Functional genes involved in biocorrosion, many of which belonged to the groups named above, were detected using the GeoChip, and a list of marker genes that can be utilised for biocorrosion monitoring has been proposed. Oligonucleotide probes for biochip development were either designed or selected from published sources. A quick and inexpensive method for probe evaluation during microarray development is described. A total of 16 II probes, representing 15 genes were tested; all the probes exhibited similar hybridisation behaviour under standard conditions. The results presented in this thesis were part of an extensive EU project, BIOCOR, involving academic and industrial partners, on fundamental and applied aspects of microbial corrosion in oil field environments, which was funded to generate the knowledge needed to develop monitoring techniques for corrosion. The results presented in this thesis are the final report to the European Commission. III ACKNOWLEDGEMENTS There are many people that I would like to thank and without whom this thesis would not be possible. First, I would like to thank my supervisors for giving me the great opportunity to be involved in the BIOCOR ITN project, which allowed me to develop myself, to deepen my scientific knowledge and to meet so many interesting people. Above all, I am sincerely grateful to Dr Julian Mitchell for accepting the task of being my supervisor, for guidance, for friendly and useful discussions during meetings. Without him this thesis would not have been completed. I am most grateful to Dr Sarah Thresh who was always interested, always available and who helped me so much. Thank you for your support, useful suggestions and patience. I would like to acknowledge the University of Oklahoma especially Dr Kathleen E. Duncan, Dr Bradley Stevenson, Dr Athenia L. Oldham, Dr Joseph M. Suflita and Dr Joy D. Van Nostrand for the warm welcome during my stay at the university and for their helpfulness. I am very indebted to my parents Bogusława and Wojciech, sister Marta and my friend Marcin for their encouragement, forbearance and support throughout my education. I really appreciate it. Finally, I wish to thank all of BIOCOR partners, coordinators and fellows for advice, friendship and efforts during the project. This research was supported by funding from the European Community's Seventh Framework Programme (FP7/2007-2013) under grant agreement n°238579 as a part of extensive EU project under Marie Curie Thematic Network Programme “BIOCOR”. Project website: www.biocor.eu/ip5 (RSP1&2). IV LIST OF ABBREVIATIONS AMP Adenosine monophosphate AOP Ammonia oxidising prokaryote APB Acid producing bacteria APS Ammonium persulphate APS Adenosine phosphosulfate ATCC American type culture collection ATP Adenosine triphosphate bp Base pairs CCD Charge coupled device cDNA Complementary DNA CGA Community genome array CN Copy number CSLM Confocal laser scanning microscope CT Cycle threshold Cy3 Bis(dithiarsolanyl)-bis(sulfobutyl) Cyanine 3 Cy5 Bis(dithiarsolanyl)-bis(sulfobutyl) Cyanine 5 DAPI 4’,6-diamidino-2-phenylindole dATP Deoxyadenosine triphosphate dCTP Deoxycytidine triphosphate ddNTP Dideoxynucleotide triphosphate DGGE Denaturing gradient gel electrophoresis dGTP Deoxyguanosine triphosphate DNA Deoxyribonucleic acid dNDP Deoxynucleotide diphosphate dNMP Deoxynucleotide monophosphate dNTP Deoxynucleotide triphosphate DSMZ Deutsche Sammlung von Mikroorganismen und Zellkulturen dTTP Deoxythymidine triphosphate EDTA Ethyleno-diamino tetra-acetic acid EOR Enhanced oil recovery V EPS Extracellular polymeric substance ESS Environmental shotgun sequencing FGA Functional gene array FISH Fluorescence in situ hybridization FRET Fluorescence resonance energy transfer GAB General anaerobe bacteria GDP Gross domestic product HDP Hydrocarbon-degrading prokaryotes Hex Hexachloro-fluorescein HFT High frequency trading IOB Iron oxidizing bacteria IPTG Isopropyl-β-D-thiogalactopyranoside IRB Iron-reducing bacteria kb Kilobase pairs LB medium Luria broth medium ln Natural logarithm LSM Laser scanning microscope MEOR Microbial enhanced oil recovery MIC Microbial influenced corrosion MIS Microbiologically induced souring MOB Metal-oxidising bacteria MRB Metal-reducing bacteria mRNA Messenger RNA MW Molecular weight NA Avogadro’s number NOB Nitrite-oxidising bacteria NRB Nitrate-reducing bacteria NUB Nitrate-utilizing bacteria OTU Operational taxonomic units PAGE Polyacrylamide gel electrophoresis PCR Polymerase chain reaction pH Hydronium ion concentration; pH=-log[H+] Pi Inorganic phosphate VI PNA Peptide nucleic acid POA Phylogenetic oligonucleotide array POP Primary oil production PPi Pyrophosphate QPCR Quantitative PCR QS Quorum sensing RNA Ribonucleic acid rpm Revolutions per minute rRNA Ribosomal RNA SD Standard deviation SDS Sodium dodecyl-sulphate SE Standard error SiNW Silicon nanowires SNP Single nucleotide polymorphisms SOB Sulfur-oxidizing bacteria sp./spp. Species/Many species SQRT Square root SRB Sulphate-reducing bacteria SRP Sulphate-reducing prokaryote SSC Saline-sodium citrate buffer STC Sample tracking control TEMED N,N,N’,N’-Tetramethylethylenediamine Tm Melting temperature, the temperature at which a DNA double helix dissociates into single strands Tris-HCl Tris (hydroxylmethyl) aminomethane UV Ultra violet light VM Vitamin medium VMI Vitamin medium with iron X-Gal 5-bromo-4-chloro-3-indolyl-β-D- galactopyranoside %(v/v) Percentage volume/volume %(w/v) Percentage mass/volume VII LIST OF FIGURES Figure 1.1.1: Simplified scheme of oil and gas extraction .................................................. 3 Figure 1.1.2: Pigging devices ......................................................................................................... 7 Figure 1.2.1: A model representing stages of bacterial biofilm development ......... 11 Figure 1.3.1: Basic corrosion cell under anaerobic conditions .................................. ....15 Figure 1.3.2: Schematic description of microbially influenced corrosion (MIC) .... 20 Figure 1.4.1: Schematic presentation of the specific pathways and the key functional genes used in this study ............................................................................................ 28 Figure 1.4.2: Principle of GC clamp operation in DGGE .................................................... 31 Figure 1.4.3: Principle of pyrosequencing technology ...................................................... 34 Figure 2.1.2: A photograph of examples received field samples provided by the industrial partner .............................................................................................................................. 47 Figure 3.1.1: CLSM visualisation of microorganisms in the ID1 field sample (Installation D – production pipeline) ....................................................................................... 75 Figure 3.1.2: Copy number of 16S rRNA genes per ml of sample for Bacteria based on QPCR analysis ............................................................................................................................... 77 Figure 3.1.3: Copy number of 16S rRNA genes per ml