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See detailCommunity integrated omics links the dominance of a microbial generalist to fine-tuned resource usage
Muller, Emilie UL; Pinel, Nicolás; Laczny, Cedric Christian UL et al

Poster (2014)

Microbial communities are complex and dynamic systems that are influenced by stochastic-neutral processes but are mainly structured by resource availability and usage. High-resolution “meta-omics” offer ... [more ▼]

Microbial communities are complex and dynamic systems that are influenced by stochastic-neutral processes but are mainly structured by resource availability and usage. High-resolution “meta-omics” offer exciting prospects to investigate microbial populations in their native environment. In particular, integrated meta-omics, by allowing simultaneous resolution of fundamental niches (genomics) and realised niches (transcriptomics, proteomics and metabolomics), can resolve microbial lifestyles strategies (generalist versus specialist) in situ. We have recently developed the necessary wet- and dry-lab methodologies to carry out systematic molecular measurements of microbial consortia over space and time, and to integrate and analyse the resulting data at the population-level. We applied these methods to oleaginous mixed microbial communities located on the surface of anoxic biological wastewater treatment tanks to investigate how niche breadth (generalist versus specialist strategies) relates to community-level phenotypes and ecological success (i.e. population size). Coupled metabolomics and 16S rRNA gene-based deep sequencing demonstrate that the community-wide lipid accumulation phenotype is associated with the dominance of Candidatus Microthrix parvicella. By integrating population-level genomic reconstructions with transcriptomic and proteomic data, we found that the dominance of this microbial generalist population results from finely tuned resource usage and optimal foraging behaviour. Moreover, the fluctuating environmental conditions constrain the accumulation of variations, leading to a genetically homogeneous population likely due to fitness trade-offs. By integrating metagenomic, metatranscriptomic, metaproteomic and metabolomic information, we demonstrate that natural microbial population sizes and structures are intricately linked to resource usage and that differing microbial lifestyle strategies may explain the varying degrees of within-population genetic heterogeneity observed in metagenomic datasets. Elucidating the exact mechanism driving fitness trade-offs, e.g., antagonistic pleiotropy or others, will require additional integrated omic datasets to be generated from samples taken over space and time. Based on our observations, niche breadth and lifestyle strategies (generalists versus specialists) have to be considered as important factors for understanding the evolutionary processes governing microbial population sizes and structures in situ. [less ▲]

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See detailCommunity integrated omics links the dominance of a microbial generalist to fine-tuned resource usage
Muller, Emilie UL; Pinel, Nicolás; Laczny, Cedric Christian UL et al

Scientific Conference (2014)

Microbial communities are complex and dynamic systems that are influenced by stochastic-neutral processes but are mainly structured by resource availability and usage. High-resolution “meta-omics” offer ... [more ▼]

Microbial communities are complex and dynamic systems that are influenced by stochastic-neutral processes but are mainly structured by resource availability and usage. High-resolution “meta-omics” offer exciting prospects to investigate microbial populations in their native environment. In particular, integrated meta-omics, by allowing simultaneous resolution of fundamental niches (genomics) and realised niches (transcriptomics, proteomics and metabolomics), can resolve microbial lifestyles (generalist versus specialist lifestyle strategies) in situ. We have recently developed the necessary wet- and dry-lab methodologies to carry out systematic molecular measurements of microbial consortia over space and time, and to integrate and analyse the resulting data at the population-level. We applied these methods to oleaginous mixed microbial communities located on the surface of anoxic biological wastewater treatment tanks to investigate how niche breadth (generalist versus specialist lifestyle strategies) relates to community-level phenotypes and ecological success (i.e. population size). Coupled metabolomics and 16S rRNA gene-based deep sequencing demonstrate that the community-wide lipid accumulation phenotype is associated with the dominance of Candidatus Microthrix parvicella. By integrating population-level genomic reconstructions with transcriptomic and proteomic data, we found that the dominance of this microbial generalist population results from finely tuned resource usage and optimal foraging behaviour. Moreover, the fluctuating environmental conditions constrain the accumulation of variations, leading to a genetically homogeneous population likely due to fitness trade-offs. By integrating metagenomic, metatranscriptomic, metaproteomic and metabolomic information, we demonstrate that natural microbial population sizes and structures are intricately linked to resource usage and that differing microbial lifestyle strategies may explain the varying degrees of within-population genetic heterogeneity observed in metagenomic datasets. Elucidating the exact mechanism driving fitness trade-offs, e.g., antagonistic pleiotropy or others, will require additional integrated omic datasets to be generated from samples taken over space and time. Based on our observations, niche breadth and lifestyle strategies (generalists versus specialists) have to be considered as important factors for understanding the evolutionary processes governing microbial population sizes and structures in situ. [less ▲]

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See detailMercator: A fast and simple web server for genome scale functional annotation of plant sequence data
Lohse, Marc; Nagel, Axel; Herter, Thomas et al

in Plant, Cell & Environment (2014), 37(5), 1250-8

Next-generation technologies generate an overwhelming amount of gene sequence data. Efficient annotation tools are required, to make this data amenable to functional genomics analyses. The Mercator ... [more ▼]

Next-generation technologies generate an overwhelming amount of gene sequence data. Efficient annotation tools are required, to make this data amenable to functional genomics analyses. The Mercator pipeline automatically assigns functional terms to protein or nucleotide sequences. It uses the MapMan “BIN” ontology, which is tailored for functional annotation of plant “omics” data. The classification procedure performs parallel sequence searches against reference databases, compiles the results, and computes the most likely MapMan BINs for each query. In the current version, the pipeline relies on manually curated reference classifications originating from the three reference organisms (Arabidopsis, Chlamydomonas, rice), various other plant species that have a reviewed SwissProt annotation, and more than 2000 protein domain and family profiles at InterPro, CDD and KOG. Functional annotations predicted by Mercator achieve accuracies above 90% when benchmarked against manual annotation. In addition to mapping files for direct use in the visualization software MapMan, Mercator provides graphical overview charts, detailed annotation information in a convenient web browser interface and a MapMan-to-GO translation Table to export results as GO terms. Mercator is available free of charge via http://mapman.gabipd.org/web/guest/app/Mercator. [less ▲]

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See detailPOMO - Plotting Omics analysis results for Multiple Organisms
Lin, Jake UL; Kreisberg, Richard; Kallio, Aleksi et al

in BMC Genomics (2013), 14(918),

Background Systems biology experiments studying different topics and organisms produce thousands of data values across different types of genomic data. Further, data mining analyses are yielding ranked ... [more ▼]

Background Systems biology experiments studying different topics and organisms produce thousands of data values across different types of genomic data. Further, data mining analyses are yielding ranked and heterogeneous results and association networks distributed over the entire genome. The visualization of these results is often difficult and standalone web tools allowing for custom inputs and dynamic filtering are limited. Results We have developed POMO (http://pomo.cs.tut.fi), an interactive web-based application to visually explore omics data analysis results and associations in circular, network and grid views. The circular graph represents the chromosome lengths as perimeter segments, as a reference outer ring, such as cytoband for human. The inner arcs between nodes represent the uploaded network. Further, multiple annotation rings, for example depiction of gene copy number changes, can be uploaded as text files and represented as bar, histogram or heatmap rings. POMO has built-in references for human, mouse, nematode, fly,yeast, zebrafish, rice, tomato, Arabidopsis, and Escherichia coli. In addition, POMO provides custom options that allow integrated plotting of unsupported strains or closely related species associations, such as human and mouse orthologs or two yeast wild types, studied together within a single analysis. The web application also supports interactive label and weight filtering. Every iterative filtered result in POMO can be exported as image file and text file for sharing or direct future input. Conclusions The POMO web application is a unique tool for omics data analysis, which can be used to visualize and filter the genome-wide networks in the context of chromosomal locations as well as multiple network layouts. With the several illustration and filtering options the tool supports the analysis and visualization of any heterogeneous omics data analysis association results for many organisms. POMO is freely available and does not require any installation or registration. [less ▲]

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See detailGenomic Sequence Diversity and Population Structure of Saccharomyces cerevisiae Assessed by RAD-seq
Cromie, Gareth A.; Hyma, Katie E.; Ludlow, Catherine L. et al

in Genes, Genomes and Genomics (2013), 3(12), 2163-2171

The budding yeast Saccharomyces cerevisiae is important for human food production and as a model organism for biological research. The genetic diversity contained in the global population of yeast strains ... [more ▼]

The budding yeast Saccharomyces cerevisiae is important for human food production and as a model organism for biological research. The genetic diversity contained in the global population of yeast strains represents a valuable resource for a number of fields, including genetics, bioengineering, and studies of evolution and population structure. Here, we apply a multiplexed, reduced genome sequencing strategy (known as RAD-seq) to genotype a large collection of S. cerevisiae strains, isolated from a wide range of geographical locations and environmental niches. The method permits the sequencing of the same 1% of all genomes, producing a multiple sequence alignment of 116,880 bases across 262 strains. We find diversity among these strains is principally organized by geography, with European, North American, Asian and African/S. E. Asian populations defining the major axes of genetic variation. At a finer scale, small groups of strains from cacao, olives and sake are defined by unique variants not present in other strains. One population, containing strains from a variety of fermentations, exhibits high levels of heterozygosity and mixtures of alleles from European and Asian populations, indicating an admixed origin for this group. In the context of this global diversity, we demonstrate that a collection of seven strains commonly used in the laboratory encompasses only one quarter of the genetic diversity present in the full collection of strains, underscoring the relatively limited genetic diversity captured by the current set of lab strains. We propose a model of geographic differentiation followed by human-associated admixture, primarily between European and Asian populations and more recently between European and North American populations. The large collection of genotyped yeast strains characterized here will provide a useful resource for the broad community of yeast researchers. [less ▲]

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See detailThe Effects of Carbon Dioxide and Temperature on microRNA Expression in Arabidopsis Development
May, Patrick UL; Liao, Will; Wu, Yijin et al

in Nature Communications (2013), 4(2145),

Elevated levels of CO2 and temperature can both affect plant growth and development, but the molecular pathways and signaling mechanisms regulating these processes are still obscure. MicroRNAs function to ... [more ▼]

Elevated levels of CO2 and temperature can both affect plant growth and development, but the molecular pathways and signaling mechanisms regulating these processes are still obscure. MicroRNAs function to silence gene expression, and environmental stresses can alter their expressions to modulate plant phenotypes. Here we show, using the small RNA-sequencing method, the identification of microRNAs that are changed significantly in expression by either doubling the atmospheric CO2 concentration or by increasing temperature 3-6˚C. Notably, nearly all CO2-influenced microRNAs are also affected by elevated temperature. Using the RNA-sequencing method, we determine strongly correlated expression changes between miR156/157 and miR172 and their target transcription factors under elevated CO2 concentration, suggesting a mechanism for a CO2-induced early flowering phenotype. Similar correlations are also revealed for microRNAs acting in auxin-signaling, stress responses, and potential cell wall carbohydrate synthesis. Our results demonstrate that elevated CO2 and elevated temperature can signal microRNA expressions to affect Arabidopsis growth and development, and microRNA regulation of flowering time might underlie the onset of flowering affected by increasing CO2. [less ▲]

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See detailHigh-throughput tetrad analysis
Ludlow, Catherine L.; Scott, Adrian C.; Cromie, Gareth A. et al

in Nature Methods (2013), 10

Tetrad analysis has been a gold-standard genetic technique for several decades. Unfortunately, the need to manually isolate, disrupt and space tetrads has relegated its application to small-scale studies ... [more ▼]

Tetrad analysis has been a gold-standard genetic technique for several decades. Unfortunately, the need to manually isolate, disrupt and space tetrads has relegated its application to small-scale studies and limited its integration with high-throughput DNA sequencing technologies. We have developed a rapid, high-throughput method, called barcode-enabled sequencing of tetrads (BEST), that uses (i) a meiosis-specific GFP fusion protein to isolate tetrads by FACS and (ii) molecular barcodes that are read during genotyping to identify spores derived from the same tetrad. Maintaining tetrad information allows accurate inference of missing genetic markers and full genotypes of missing (and presumably nonviable) individuals. An individual researcher was able to isolate over 3,000 yeast tetrads in 3 h, an output equivalent to that of almost 1 month of manual dissection. BEST is transferable to other microorganisms for which meiotic mapping is significantly more laborious. [less ▲]

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See detailLinking mixed microbial community phenotype to individual genotypes
Muller, Emilie UL; Pinel, Nicolás; May, Patrick UL et al

Poster (2013)

Biological wastewater treatment is arguably the most widely used biotechnological process on Earth. Wastewater also represents a valuable energy commodity that is currently not being harnessed ... [more ▼]

Biological wastewater treatment is arguably the most widely used biotechnological process on Earth. Wastewater also represents a valuable energy commodity that is currently not being harnessed comprehensively. Mixed microbial communities that naturally occur at the air-water interface of certain biological wastewater treatment systems accumulate excess long chain fatty acids intracellularly. This phenotypic trait may potentially be exploited for the transformation of lipid-rich wastewater into biodiesel (fatty acid methyl esters). Using a molecular Eco-Systems Biology approach, we are studying which genes contribute to the lipid accumulation phenotype and, thus, overall community function. We first compared the lipid accumulation phenotype to the structure of lipid accumulating communities from a local wastewater treatment plant by coupled deep sequencing of the 16S rRNA locus, metagenome sequencing and metabolomic analysis of 4 biological replicates sampled at 4 different time points. Based on the results of these analyses and in order to obtain a detailed view of the structure and function of the respective microbial communities, metagenomic, metatranscriptomic, metaproteomic and (meta-)metabolomic analyses were completed for a single representative biological sample of highest interest. In order to facilitate meaningful data integration of this highly heterogeneous consortium, biomolecular fractions used for the omic analyses were extracted from a unique single sample using a recently developed biomolecular isolation protocol. The coupled survey and the comparative metagenomic analysis demonstrate that the communities change significantly from dates with warm water temperatures to cold water temperatures while alpha diversity remains stable. In the winter period, this switch results in a strong enrichment of a bacterial genus well known to accumulate intracellular lipids, namely Microthrix spp., a representative genome of which has recently been sequenced by us. Correlation networks based on microorganism and concomitant intra- and extra-cellular metabolite abundances provides an overview of organisms potentially involved in the community-wide lipid accumulating phenotype. A sample with the highest abundance of Microthrix spp. was subsequently chosen for the construction of a community-wide metabolic model using metagenomic, metatranscriptomic, metaproteomic and (meta-)metabolomics data. Based on these omic datasets, expressed enzyme variants linked to the lipid accumulation phenotype have been identified and are currently undergoing in vitro characterization. Meta-omic analyses offer exciting prospects for elucidating the genetic blueprints and the functional relevance of specific populations within microbial communities. Consequently, connecting the overall community phenotype to specific genotypes will allow much needed fundamental ecological understanding of microbial community and population dynamics, particularly in relation to environment-driven demography changes leading to tipping points and catastrophic bifurcations. [less ▲]

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See detailDifferentiated SH-SY5Y Cells as PD Model for Mitochondrial Dysfunction: From Whole Genome Sequencing to an Educated Design of High-Throughput Experiments
Antony, Paul UL; Krishna, Abhimanyu UL; May, Patrick UL et al

Poster (2013)

Objectives: Mitochondrial dysfunction is a cellular hallmark of Parkinson's disease (PD) and energetic stress of dopaminergic neurons appears to be a physiological risk factor for mitochondrial ... [more ▼]

Objectives: Mitochondrial dysfunction is a cellular hallmark of Parkinson's disease (PD) and energetic stress of dopaminergic neurons appears to be a physiological risk factor for mitochondrial dysfunction. It is however challenging to assess the high variety of factors regulating mitochondrial physiology in living neurons in a high throughput manner. To overcome this bottleneck, we established an analysis platform, using the neuroblastoma cell line SH-SY5Y. For the first time ever we have characterized the SH-SY5Y cell line in an integrated whole genome, transcriptome, and proteome approach. In addition, we show that neuronal differentiation improves the physiological properties of this experimental model for studying mitochondrial dysfunction in PD. Methods: Whole genome sequencing, RNA-Seq, qRT-PCR, MS, FRET using Voltage sensing proteins, Immunofluorescence, cytometry, and live cell imaging. Results: The integrated molecular characterization of SH-SY5Y uncovers the level of molecular network integrity and hence the relevance of this cell line for targeted studies in selected molecular processes. Furthermore, we dissect changes in mitochondrial and energetic stress factors during the process of neuronal differentiation. Conclusions: In terms of both morphology and energetic stress response, differentiated SH-SY5Y cells are more similar to dopaminergic neurons than their undifferentiated precursors. Thanks to dividing progenitors and the short duration of differentiation, combined with the use of specific endpoints analysed with high-content microscopy, our platform paves the route for high throughput experiments on a neuronal cell culture model for PD. Our genomic characterization and expression profiling of SH-SY5Y cells furthermore helps guiding the experimental design and interpretation of such studies. [less ▲]

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See detailNew insights into Chlamydomonas reinhardtii hydrogen production processes by combined microarray/RNA-seq transcriptomics.
Toepel, Jorg; Illmer-Kephalides, Maike; Jaenicke, Sebastian et al

in Plant Biotechnology Journal (2013)

Hydrogen production with Chlamydomonas reinhardtii induced by sulphur starvation is a multiphase process while the cell internal metabolism is completely remodelled. The first cellular response is ... [more ▼]

Hydrogen production with Chlamydomonas reinhardtii induced by sulphur starvation is a multiphase process while the cell internal metabolism is completely remodelled. The first cellular response is characterized by induction of genes with regulatory functions, followed by a total remodelling of the metabolism to provide reduction equivalents for cellular processes. We were able to characterize all major processes that provide energy and reduction equivalents during hydrogen production. Furthermore, C. reinhardtii showed a strong transcript increase for gene models responsible for stress response and detoxification of oxygen radicals. Finally, we were able to determine potential bottlenecks and target genes for manipulation to increase hydrogen production or to prolong the hydrogen production phase. The investigation of transcriptomic changes during the time course of hydrogen production in C. reinhardtii with microarrays and RNA-seq revealed new insights into the regulation and remodelling of the cell internal metabolism. Both methods showed a good correlation. The microarray platform can be used as a reliable standard tool for routine gene expression analysis. RNA-seq additionally allowed a detailed time-dependent study of gene expression and determination of new genes involved in the hydrogen production process. [less ▲]

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See detailHierarchical representation of supersecondary structures using a graph-theoretical approach.
Koch, Ina; Kreuchwig, Annika; May, Patrick UL

in Methods in Molecular Biology (Clifton, N.J.) (2013), 932

The unique representation of proteins becomes more and more important with the growing number of known protein structure data. Graph-theory provides many methods not only for the description but also for ... [more ▼]

The unique representation of proteins becomes more and more important with the growing number of known protein structure data. Graph-theory provides many methods not only for the description but also for comparison and classification of protein structures. Here, we describe a graph-theoretical modeling approach of the protein supersecondary structure. The resulting linear notations are intuitive and can be used to find common substructures very fast and easily. We illustrate the necessary definitions by biological examples and discuss the representation of various supersecondary structure motifs. [less ▲]

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See detailA model microbial community for Eco-Systems Biology
Muller, Emilie UL; Roume, Hugo UL; Buschart, Anna UL et al

Poster (2013)

Objective Microbial communities (MCs) play crucial roles in human health and disease. In-depth characterization of the vast organismal and functional diversity of MCs is now facilitated by high-resolution ... [more ▼]

Objective Microbial communities (MCs) play crucial roles in human health and disease. In-depth characterization of the vast organismal and functional diversity of MCs is now facilitated by high-resolution molecular approaches. Systematic measurements are key for meaningful data integration, analysis and modeling. Based on a model MC from a biological wastewater treatment plant, we have developed a new framework based on wet- and dry-lab methods for the integrated analyses of MCs at the population- as well as at the community-level. Methods The overall methodological framework first relies on a standardised wet-lab procedure for the isolation of concomitant biomolecules, i.e., DNA, RNA, proteins and metabolites, from single undivided samples. Purified biomolecular fractions then are subjected to high-resolution omic analyses including metagenomics, metatranscriptomics, metaproteomics and (meta-) metabolomics. The resulting data form the input for integrated bioinformatic analyses. Population-level integrated omic analyses rely on a newly developed binning and re-assembly method, which yields near-complete genome reconstructions for dominant populations. Community-level analyses involve the reconstruction of community-wide metabolic networks. Functional omic data is then mapped onto these reconstructions and contextualized. Results Application of the population-centric workflow has allowed us to reconstruct and identify 10 major populations within the model MC and has led to the identification of a key generalist population, Candidatus Microthrix spp., within the community. Analysis of the community-wide metabolic networks has allowed the identification of keystone genes involved in lipid and nitrogen metabolism within the MC. Conclusions Our new methodological framework offers exciting new prospects for elucidating the functional relevance of specific populations and genes within MCs. The established workflows are now being applied to samples of biomedical research interest such as human gastrointestinal tract-derived samples. [less ▲]

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See detailA Protein Prioritization Approach Tailored for the FA/BRCA Pathway
Haitjema, Anneke; Brandt, Bernd W.; Ameziane, Najim et al

in PLoS ONE (2013), 8(4), 62017

<sec><title/><p>Fanconi anemia (FA) is a heterogeneous recessive disorder associated with a markedly elevated risk to develop cancer. To date sixteen FA genes have been identified, three of which ... [more ▼]

<sec><title/><p>Fanconi anemia (FA) is a heterogeneous recessive disorder associated with a markedly elevated risk to develop cancer. To date sixteen FA genes have been identified, three of which predispose heterozygous mutation carriers to breast cancer. The FA proteins work together in a genome maintenance pathway, the so-called FA/BRCA pathway which is important during the <italic>S</italic> phase of the cell cycle. Since not all FA patients can be linked to (one of) the sixteen known complementation groups, new FA genes remain to be identified. In addition the complex FA network remains to be further unravelled. One of the FA genes, <italic>FANCI</italic>, has been identified via a combination of bioinformatic techniques exploiting FA protein properties and genetic linkage. The aim of this study was to develop a prioritization approach for proteins of the entire human proteome that potentially interact with the FA/BRCA pathway or are novel candidate FA genes. To this end, we combined the original bioinformatics approach based on the properties of the first thirteen FA proteins identified with publicly available tools for protein-protein interactions, literature mining (Nermal) and a protein function prediction tool (FuncNet). Importantly, the three newest FA proteins FANCO/RAD51C, FANCP/SLX4, and XRCC2 displayed scores in the range of the already known FA proteins. Likewise, a prime candidate FA gene based on next generation sequencing and having a very low score was subsequently disproven by functional studies for the FA phenotype. Furthermore, the approach strongly enriches for GO terms such as DNA repair, response to DNA damage stimulus, and cell cycle-regulated genes. Additionally, overlaying the top 150 with a haploinsufficiency probability score, renders the approach more tailored for identifying breast cancer related genes. This approach may be useful for prioritization of putative novel FA or breast cancer genes from next generation sequencing efforts.</p></sec> [less ▲]

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See detailCondensing the omics fog of microbial communities
Muller, Emilie UL; Glaab, Enrico UL; May, Patrick UL et al

in Trends in Microbiology (2013), 21(7), 325333

Natural microbial communities are ubiquitous, complex, heterogeneous and dynamic. Here, we argue that the future standard for their study will require systematic omic measurements of spatially and ... [more ▼]

Natural microbial communities are ubiquitous, complex, heterogeneous and dynamic. Here, we argue that the future standard for their study will require systematic omic measurements of spatially and temporally resolved unique samples in line with a discovery-driven planning approach. Resulting datasets will allow the generation of solid hypotheses about causal relationships and, thereby, will facilitate the discovery of previously unknown traits of specific microbial community members. However, to achieve this, solid wet-lab, bioinformatic and statistical methodologies are required to have the promises of the emerging field of Eco-Systems Biology come to fruition. [less ▲]

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See detailSystematic molecular measurements reveal key microbial populations driving community-wide phenotype
Muller, Emilie UL; Pinel, Nicolás; May, Patrick UL et al

Poster (2013)

Natural microbial communities are heterogeneous and dynamic. Therefore, a major consideration for multiple omic data studies is the sample-to-sample heterogeneity, which can lead to inconsistent results ... [more ▼]

Natural microbial communities are heterogeneous and dynamic. Therefore, a major consideration for multiple omic data studies is the sample-to-sample heterogeneity, which can lead to inconsistent results if the different biomolecular fractions are obtained from distinct sub-samples. Conversely, systematic omic measurements, i.e. the standardised, reproducible and simultaneous measurement of multiple features from a single undivided sample, result in fully integrable datasets. Objective In order to prove the feasibility and benefits of such systematic measurements in the study of the respective contributions of different populations to the community-wide phenotype, we purified and analysed all biomolecular fractions, i.e. DNA, RNA, proteins and metabolites, obtained from a unique undivided sample of lipid accumulating microbial community (LAMC) from wastewater treatment plant and integrate the resulting datasets. Methods One time point of particular interest was first selected out of 4 LAMC samples for its high diversity and strong lipid accumulation phenotype. Then, the systematic measurement strategy was applied to the selected undivided LAMC sample and the purified biomolecules were analysed by high-throughput techniques. DNA and RNA sequencing reads were assembled at the population-level using different binning strategies. A database, containing predicted proteins, was constructed to identify the detected peptides. Finally, all biomolecular information was mapped onto the assembled composite genomes to identify the precise roles of the different populations in the community-wide lipid accumulation phenotype. Results Metabolomics and 16S diversity analyses were used to select the sample of highest interest for detailed analysis. The systematic measurements of the selected sample followed by data integration have allowed us to probe the functional relevance of the population-level composite genomes, leading to the identification of the LAMC key players. Conclusion As community phenotype is not the sum of the different partner phenotypes, understanding a microbial community system requires more than the study of isolated organisms. Even if both approaches are complementary, top-down systematic approached only provides a holistic perspective of micro-ecological processes. [less ▲]

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See detailComputation and Visualization of Protein Topology Graphs Including Ligand Information
Schäfer, Tim; May, Patrick UL; Koch, Ina

in Böcker, Sebasttian; Hufsky, Franziska; Scheubert, Kerstin (Eds.) et al German Conference on Bioinformatics 2012 (2012)

Detailed reference viewed: 64 (12 UL)