The use of next genera/on sequencing to determine the effects of land use on soil microbial communi/es Serena K. Thomson1, David Bass2, Christopher J. van der Gast3 and Gary D. Bending1 1 University of Warwick, Gibbet Hill Campus, Coventry CV4 7AL, 2 Natural History Museum, London SW7 5BD, 3 Centre for Hydrology & Ecology, Wallingford, OX10 8BB OBJECTIVES METHODS BACKGROUND •  Maintaining healthy soil is crucial to sustaining a complex and diverse microbial community. •  Agricultural prac<ces are known to impact the community which can affect ecosystem processes. •  High throughput sequencing can provide a thorough understanding of community assembly and func<on to determine the role of microbiota in the soil. This inves<ga<on aims to: •  Determine community assembly and landscape distribu<on of soil microbiota under set aside and arable (cropped) farming prac<ce. Ø  This will involve the assessment of whole microbial community structure (dominance and evenness), diversity and composi<on. Major groups including Bacteria, Fungi, Nematodes, Cercozoa and general Eukaryotes will be inves<gated. •  To par<<on the data into core (typically abundant, widely distributed) and satellite (less abundant, restricted distribu<on) taxa. This is expected to unearth informa<on regarding species area distribu<ons that can go unmissed when only looking at the whole community, (Unterseher et al, 2011). •  To characterise the distribu<on of communi<es across the landscape and whether these can be explained by landscape heterogeneity. Soil samples were taken from 17 paired sites across UK •
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A range of soil parameters recorded: pH, Nitrogen, Carbon, Magnesium and Phosphorous, as well as soil type. •
Data were pooled for 454 pyrosequencing. 6 sets of primers were used – Bacteria, Eukaryotes, Fungi, Cercozoa, Nematoda, Ro/fers. •
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Sequence data were analyzed using QIIME (Quan<ta<ve Insights Into Microbial Ecology) which included denoising, chimera removal and standard quality filtering. These steps resulted in removing approximately 50% of the raw sequences, classified as ‘noise’. •
AHer sequences were ‘cleaned’, sta<s<cal analyses were performed which included calcula<ng distribu<on-­‐abundance rela<onships, frequency histograms, Poisson distribu<on and rank abundances. •
Data were analyzed on a meta-­‐community level and divided into highly abundant and frequently occurring groups (core) and low abundant, rarely occurring (satellite) communi<es (Gast et al, 2011). CERCOZOA -­‐ RESULTS Arable SetAside FIG 2 FIG 1 Distribu<on-­‐abundance rela<onship FIG 3 FIG 4 Frequency histogram Non Random/core FIG 5 FIG 6 Non Random/core Random/satellite Random/satellite Poisson distribu<on STRUCTURE: Cercozoa (mostly heterotrophic flagellate or amoeboid protozoa) demonstrated a significant posi<ve distribu<on abundance rela<onship (Figure 1, 2). Species with high abundance were highly persistent (occurred at many sites). Cercozoa interes<ngly showed some species which had low persistence, that were also highly abundant. Community structure was characterized by an excess of rare ‘species’, (indicated by a strong leH skew when ploJed on a frequency histogram, see Fig 3, 4). This trend was also seen in all other groups. To inves<gate structure in more detail, core and satellite groups were ascertained using the Poisson distribu<on (calculated from the index of dispersion). It highlights that the community can be par<<oned into rare/satellite and common/core groups (Fig 5, 6). The line in Fig 5, 6 indicates the 2.5% Confidence Intervals. (97.5% line not drawn as no OTUs occurred under this line). DIVERSITY: Species richness was measured under arable and set aside sites, for all, core and satellite data (Fig 7). Greatest richness occurred in the satellite group under set aside treatment, which supports the structure data. Effect size (strength of rela<onship rela<ve to its variability) as described by Stewart (2009) shows that Satellite taxa have a strong posi<ve effect on data, therefore driving diversity, (Fig 8). FIG 7 FIG 8 RESULTS DIFFERENCES BETWEEN WHOLE COMMUNITIES •  When assessing the whole community, significant differences were found between arable and set aside treatments for most groups. (Results derived from t-­‐distribu<on summary sta<s<cs based on logis<c regressions, see Fig 9). •  b value depicts the slope of the line which provides informa<on on evenness and dominance. Lower b values in set aside sites for eukaryotes indicates a more even structure within these communi<es. Bacterial groups showed the opposite, where structure is more even in arable treatments (Fig 9). CORE AND SATELLITE COMMUNITIES •  The satellite taxa supported the above trend -­‐ higher evenness under set aside treatment, within the eukaryote groups, with more even community structure in arable sites for the bacterial groups (Fig 10). •  Structure within the core communi<es showed the opposite trend where the eukaryote groups showed higher evenness in arable sites and the bacterial groups had greater evenness in set aside sites (summarized in Fig 11).G FIG 9 Blue highligh<ng indicates insignificant groups FIG 10 Green highligh<ng indicates where greater evenness occurs. FIG 11 Summarizes findings in Fig 2. CONCLUSIONS CONCLUSIONS Significant differences in overall community structure for all groups (excluding arthropoda) under set aside and arable treatments. Clear dis<nc<on in structure between fungal and bacterial communi<es. Structure of eukaryote communi<es showed higher level of evenness under set aside treatments, whereas bacteria showed higher evenness under arable treatments. Communi<es can be par<<oned into core and satellite groups, where satellite OTUs for eukaryotes show higher evenness in structure at set aside sites. Bacteria showed the opposite trend. These results are supported by a greater species richness and higher diversity in set aside for satellites groups. REFERENCES REFERENCES •  Stewart, G. (2010) Meta-­‐analysis in applied ecology Biol. LeJs 6: 78-­‐81. •  Unterseher, M., et al (2011) Species abundance distribu<on and richness es<ma<ons in fungal metagenomics – lessons learned from community ecology. Molecular Ecology 20: 275-­‐285. •  Van der Gast, C., et al (2011) Par<<oning core and satellite taxa from within cys<c fibrosis lung bacterial communi<es. ISME 5: 780-­‐791 ACKNOWLEDGEMENTS Many thanks to my supervisors Gary Bending, David Bass and Chris van der Gast for their guidance. Thanks also to the QIIME programmers Greg Caporaso, Tony Walters and Jose Clemente who have provided assistance throughout the processing stages
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