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Metatranscriptomic Analysis of Community Structure And School of Environmental Sciences Metatranscriptomic analysis of community structure and metabolism of the rhizosphere microbiome by Thomas Richard Turner Submitted in partial fulfilment of the requirement for the degree of Doctor of Philosophy, September 2013 This copy of the thesis has been supplied on condition that anyone who consults it is understood to recognise that its copyright rests with the author and that use of any information derived there from must be in accordance with current UK Copyright Law. In addition, any quotation or extract must include full attribution. i Declaration I declare that this is an account of my own research and has not been submitted for a degree at any other university. The use of material from other sources has been properly and fully acknowledged, where appropriate. Thomas Richard Turner ii Acknowledgements I would like to thank my supervisors, Phil Poole and Alastair Grant, for their continued support and guidance over the past four years. I’m grateful to all members of my lab, both past and present, for advice and friendship. Graham Hood, I don’t know how we put up with each other, but I don’t think I could have done this without you. Cheers Salt! KK, thank you for all your help in the lab, and for Uma’s biryanis! Andrzej Tkatcz, thanks for the useful discussions about our projects. Alison East, thank you for all your support, particularly ensuring Graham and I did not kill each other. I’m grateful to Allan Downie and Colin Murrell for advice. For sequencing support, I’d like to thank TGAC, particularly Darren Heavens, Sophie Janacek, Kirsten McKlay and Melanie Febrer, as well as John Walshaw, Mark Alston and David Swarbreck for bioinformatic support. To all of the friends I’ve made during my time here, particularly Matt, Jack, Henry and Ellis for our regular pub visits. To Ade, Kate and Beth for many successful pub quiz nights, and to Joy, Dave, Hannah, Tori and Millie for giving me a home away from home. Finally, I’m very grateful to my family for constantly supporting me, particularly my Mum and Dad, my sister Ellie and soon-to-be-brother-in-law Gary, as well as my late grandparents Fred and Hilda Winifred Turner, who inspired me to do this PhD project. iii Abstract Plant-microbe interactions in the rhizosphere, the region of soil influenced by plant roots, are integral to biogeochemical cycling, and maintenance of plant health and productivity. Interactions between model plants and microbes are well understood, but relatively little is about the plant microbiome. Here, comparative metatranscriptomics was used to determine taxonomic compositions and metabolic responses of microbes in soil and the rhizospheres of wheat, oat and pea. Additionally a wild-type oat was compared to a mutant (sad1) deficient in production of antifungal avenacins. Analyses of taxonomic compositions and functions based on rRNA and protein coding genes agreed that rhizosphere microbiomes differed from soil and between plant species. Pea had a stronger effect than wheat and oat, suggesting distinct cereal and legume microbiomes. Proportions of eukaryotic rRNA in the oat and pea rhizospheres were more than fivefold higher than in the wheat rhizosphere or soil. Nematodes and bacterivorous protozoa were enriched in all rhizospheres, while the pea rhizosphere was highly enriched for fungi. Only the eukaryotic community was distinct from wild-type oat in the sad1 mutant, suggesting avenacins have a broader role than protecting from fungal pathogens. The addition of an internal RNA standard allowed quantitative determination of global transcriptional activity in each environment. This was generally higher in the rhizospheres, particularly pea, than in soil. Taxa known to possess metabolic traits potentially important for rhizosphere colonisation, plant growth promotion and pathogenesis were selected by plants. Such traits included cellulose and other plant polymer degradation, nitrogen fixation, hydrogen oxidation, methylotrophy and antibiotic production. These functions were also more highly expressed in rhizospheres than soil. Microbes also induced functions involved in chemotaxis, motility, attachment, pathogenesis, responses to oxidative stress, cycling of nitrogen and sulphur, acquisition of phosphorous, iron and other metals, as well as metabolism of a variety of sugars, aromatics, organic and amino acids, many plant species specific. Profiling microbial communities with metatranscriptomics allowed comparison of relative and quantitative abundance of microbes and their metabolism, from multiple samples, across all domains of life, without PCR bias. This revealed profound differences in the taxonomic composition and metabolic functions of rhizosphere microbiomes between crop plants and soil. iv Contents Chapter 1: The plant microbiome 1 1.1 Introduction 1 1.2 Approaches used to study the plant microbiome 2 1.2.1 Culture dependent approaches 2 1.2.2 Ribosomal RNA and other genes as phylogenetic markers 4 1.2.3 Genetic fingerprinting 4 1.2.4 High throughput analysis of 16S rRNA gene sequences 5 1.2.5 Metagenomics 6 1.2.6 Metatranscriptomics and the challenge of mRNA enrichment 8 1.3 The phyllosphere environment 13 1.4 The rhizosphere environment 14 1.4.1 Molecular determinants of rhizosphere colonisation 16 1.4.2 The arbuscular mycorrhizal fungi 17 1.4.3 Nutrient cycling 18 1.4.4 Disease suppression 21 1.5 Plant host factors determining microbiome structure and function 21 1.5.1 Antimicrobials 21 1.5.2 The plant immune system 24 1.5.3 Chemical signalling between plants and their microbiota 25 1.6 Perspective 26 1.6.1 Aims of this project 27 Chapter 2: Materials and methods 29 2.1 General considerations 29 2.2 Plant growth and harvesting 29 2.2.1 Soil sampling 29 2.2.2 Plant seed sterilisation, germination, and planting 30 2.3 Nucleic acid isolation and manipulations 31 2.3.1 Nucleic acid extraction with PowerSoil 31 2.3.2 Nucleic acid quantification 32 2.3.3 DNase treatment of total RNA 34 v 2.3.4 Whole transcriptome amplification with Rubicon 34 2.3.5 Purification of DNA from PCR and enzymatic reactions 35 2.3.6 Amplification of RNA using SENSATION 35 2.3.7 Quantitative and reverse transcription quantitative PCR of nucleic acids 37 2.3.8 In vitro transcription using MEGAScript 38 2.3.9 Generation of an RNA internal standard (RIS) 39 2.4 Ribosomal RNA depletion methods 41 2.4.1 Depletion of ribosomal RNA using MICROBExpress 41 Subtractive hybridisation using sample-specific, anti-sense RNA capture 2.4.2 probes 42 2.4.3 Duplex specific nuclease treatment 43 2.4.4 Ribosomal RNA depletion with Ribo-Zero Metabacteria (non-magnetic) 45 Ribosomal RNA depletion with Ribo-Zero Bacteria and Plant Seed / Root 2.4.5 (magnetic) 46 2.5 Sequencing and bioinformatic analyses 48 2.5.1 Preparation of samples for sequencing 48 2.5.2 Bioinformatic analysis of 454 pyrosequencing data 48 2.5.3 Analysis of Illumina HiSeq sequencing data 49 2.5.4 Calculation of sequencing depth and transcript abundances 51 2.6 Primer oligonucleotide sequences 52 Chapter 3: Ribosomal RNA based community analysis of crop plant rhizosphere microbiomes 53 3.1 Introduction 53 3.2 Materials and methods 55 3.3 Results and discussion 55 3.3.1 Sequencing and analysis summary 55 3.3.2 Identification of a human contaminated sample 58 3.3.3 Lowest common ancestor analysis with MEGAN 60 3.3.4 Analysis of plant rRNA in soil and the rhizospheres 61 3.3.5 Total Community Structure and Diversity 65 3.3.6 Highly abundant microbes in soil and rhizospheres 71 3.3.7 Indepdendent comparison of metatranscriptomic data with qPCR 73 vi 3.3.8 Plant selection of microbes 75 3.3.9 Comparison of the wild-type oat with the sad1 oat mutant 83 3.4 Conclusion 91 Chapter 4: Protein coding gene based community analysis of crop plant rhizosphere microbiomes 96 4.1 Introduction 96 4.2 Materials and methods 97 4.3 Results and discussion 98 4.3.1 Analysis of metagenomic data with Metaphyler and Metaphlan 98 4.3.2 Comparison of Metaphyler and Metaphlan outputs 105 4.3.3 Comparison of DNA and RNA based taxonomic profiles from Metaphyler 106 4.3.4 Analysis of metatranscriptomic data by rapsearch2 113 4.3.5 Community structure and highly abundant microbes 115 4.3.6 Selection of microbes by plants 122 4.3.7 Taxa selected by all plants 123 4.3.8 Taxa specifically enriched in the wheat rhizosphere 124 4.3.9 Taxa specifically enriched in the oat rhizosphere 125 4.3.10 Taxa specifically enriched in the pea rhizosphere 126 4.3.11 Taxa enriched in the wheat and oat rhizospheres 127 4.3.12 Taxa enriched in the wheat and pea rhizospheres 127 4.3.13 Taxa enriched in the oat and pea rhizospheres 128 4.4 Conclusion 128 Chapter 5: Optimising mRNA enrichment for soil and rhizosphere metatranscriptomics 131 5.1 Introduction 131 5.2 Materials and methods 131 5.3 Results and discussion 132 5.3.1 Determination of rRNA depletion efficacy with sequencing tests 132 5.3.2 Differences in subtractive hybridisation based methods 133 5.3.3 Determining rRNA depletion using molecular weight profiles 135 vii 5.3.4 Spiking RNA to calculate efficacy of rRNA depletion 137 5.3.5 Determining rRNA depletion using qPCR 139 5.3.6 Amplification of RNA using SENSATION 141 5.3.7 Removal of residual rRNA in silico 142 5.3.8 Differences in rRNA depletion due sample origin 143 5.3.9 Analysing the poorly depleted soil sample 2388 144 5.3.10 Identifying rRNA not removed by MICROBExpress and Ribo-Zero Bacteria 146 Identifying rRNA not removed by the Ribo-Zero Bacteria and Plant 5.3.11 combination 149 5.4 Conclusion 151 Chapter 6:
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