A model microbial community for Eco-Systems Biology

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 ▲]

Systematic molecular measurements reveal key microbial populations driving community-wide phenotype

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 ▲]

Computation and Visualization of Protein Topology Graphs Including Ligand Information

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

Comparative analysis of miRNAs and their targets across four plant species.

in BMC Research Notes (2011), 4

BACKGROUND: MicroRNA (miRNA) mediated regulation of gene expression has been recognized as a major posttranscriptional regulatory mechanism also in plants. We performed a comparative analysis of miRNAs ... [more ▼]

BACKGROUND: MicroRNA (miRNA) mediated regulation of gene expression has been recognized as a major posttranscriptional regulatory mechanism also in plants. We performed a comparative analysis of miRNAs and their respective gene targets across four plant species: Arabidopsis thaliana (Ath), Medicago truncatula(Mtr), Brassica napus (Bna), and Chlamydomonas reinhardtii (Cre). RESULTS: miRNAs were obtained from mirBase with 218 miRNAs for Ath, 375 for Mtr, 46 for Bna, and 73 for Cre, annotated for each species respectively. miRNA targets were obtained from available database annotations, bioinformatic predictions using RNAhybrid as well as predicted from an analysis of mRNA degradation products (degradome sequencing) aimed at identifying miRNA cleavage products. On average, and considering both experimental and bioinformatic predictions together, every miRNA was associated with about 46 unique gene transcripts with considerably variation across species. We observed a positive and linear correlation between the number miRNAs and the total number of transcripts across different plant species suggesting that the repertoire of miRNAs correlates with the size of the transcriptome of an organism. Conserved miRNA-target pairs were found to be associated with developmental processes and transcriptional regulation, while species-specific (in particular, Ath) pairs are involved in signal transduction and response to stress processes. Conserved miRNAs have more targets and higher expression values than non-conserved miRNAs. We found evidence for a conservation of not only the sequence of miRNAs, but their expression levels as well. CONCLUSIONS: Our results support the notion of a high birth and death rate of miRNAs and that miRNAs serve many species specific functions, while conserved miRNA are related mainly to developmental processes and transcriptional regulation with conservation operating at both the sequence and expression level. [less ▲]

Distribution pattern of small RNA and degradome reads provides information on miRNA gene structure and regulation.

in Plant Signaling and Behavior (2011), 6(10), 1609-11

Plant microRNAs (miRNAs) have an impact in the regulation of several biological processes such as development, growth and metabolism by negatively controlling gene expression at the post-transcriptional ... [more ▼]

Plant microRNAs (miRNAs) have an impact in the regulation of several biological processes such as development, growth and metabolism by negatively controlling gene expression at the post-transcriptional level. However, the role of these small molecules in the symbiotic interaction of plant roots and arbuscular mycorrhizal (AM) fungi remained elusive. To elucidate the role of miRNAs during AM symbiosis we used a deep sequencing approach to analyze the small RNA and degradome sequence tags of Medicago truncatula non-mycorrhizal and mycorrhizal roots. We identified 243 novel Medicago microRNAs and 118 mRNA cleavage targets of miRNA mature and star sequences. Several AM symbiosis-relevant genes were identified as miRNA targets. The transcript of MtNsp2, encoding a GRAS transcription factor involved in the nodule and mycorrhizal signaling pathway, is cleaved by a novel member of the miR171 gene family, namely miR171h. Here, we carried out a detailed analysis of the genomic structure of the MIR171h gene comprising our deep sequencing data. The results suggest a feedback circuit between mature miR171h and its own primary transcript showing the ability of this miRNA regulating itself. [less ▲]

Algebraic connectivity may explain the evolution of gene regulatory networks.

in Journal of Theoretical Biology (2010), 267(1), 7-14

Gene expression is a result of the interplay between the structure, type, kinetics, and specificity of gene regulatory interactions, whose diversity gives rise to the variety of life forms. As the dynamic ... [more ▼]

Gene expression is a result of the interplay between the structure, type, kinetics, and specificity of gene regulatory interactions, whose diversity gives rise to the variety of life forms. As the dynamic behavior of gene regulatory networks depends on their structure, here we attempt to determine structural reasons which, despite the similarities in global network properties, may explain the large differences in organismal complexity. We demonstrate that the algebraic connectivity, the smallest non-trivial eigenvalue of the Laplacian, of the directed gene regulatory networks decreases with the increase of organismal complexity, and may therefore explain the difference between the variety of analyzed regulatory networks. In addition, our results point out that, for the species considered in this study, evolution favours decreasing concentration of strategically positioned feed forward loops, so that the network as a whole can increase the specificity towards changing environments. Moreover, contrary to the existing results, we show that the average degree, the length of the longest cascade, and the average cascade length of gene regulatory networks cannot recover the evolutionary relationships between organisms. Whereas the dynamical properties of special subnetworks are relatively well understood, there is still limited knowledge about the evolutionary reasons for the already identified design principles pertaining to these special subnetworks, underlying the global quantitative features of gene regulatory networks of different organisms. The behavior of the algebraic connectivity, which we show valid on gene regulatory networks extracted from curated databases, can serve as an additional evolutionary principle of organism-specific regulatory networks. [less ▲]

Sequence-structure relationships in RNA loops: establishing the basis for loop homology modeling.

in Nucleic Acids Research (2010), 38(3), 970-80

The specific function of RNA molecules frequently resides in their seemingly unstructured loop regions. We performed a systematic analysis of RNA loops extracted from experimentally determined three ... [more ▼]

The specific function of RNA molecules frequently resides in their seemingly unstructured loop regions. We performed a systematic analysis of RNA loops extracted from experimentally determined three-dimensional structures of RNA molecules. A comprehensive loop-structure data set was created and organized into distinct clusters based on structural and sequence similarity. We detected clear evidence of the hallmark of homology present in the sequence-structure relationships in loops. Loops differing by <25% in sequence identity fold into very similar structures. Thus, our results support the application of homology modeling for RNA loop model building. We established a threshold that may guide the sequence divergence-based selection of template structures for RNA loop homology modeling. Of all possible sequences that are, under the assumption of isosteric relationships, theoretically compatible with actual sequences observed in RNA structures, only a small fraction is contained in the Rfam database of RNA sequences and classes implying that the actual RNA loop space may consist of a limited number of unique loop structures and conserved sequences. The loop-structure data sets are made available via an online database, RLooM. RLooM also offers functionalities for the modeling of RNA loop structures in support of RNA engineering and design efforts. [less ▲]

Expression pattern suggests a role of MiR399 in the regulation of the cellular response to local Pi increase during arbuscular mycorrhizal symbiosis.

in Molecular Plant-Microbe Interactions (2010), 23(7), 915-26

Many plants improve their phosphate (Pi) availability by forming mutualistic associations with arbuscular mycorrhizal (AM) fungi. Pi-repleted plants are much less colonized by AM fungi than Pi-depleted ... [more ▼]

Many plants improve their phosphate (Pi) availability by forming mutualistic associations with arbuscular mycorrhizal (AM) fungi. Pi-repleted plants are much less colonized by AM fungi than Pi-depleted plants. This indicates a link between plant Pi signaling and AM development. MicroRNAs (miR) of the 399 family are systemic Pi-starvation signals important for maintenance of Pi homeostasis in Arabidopsis thaliana and might also qualify as signals regulating AM development in response to Pi availability. MiR399 could either represent the systemic low-Pi signal promoting or required for AM formation or they could act as counter players of systemic Pi-availability signals that suppress AM symbiosis. To test either of these assumptions, we analyzed the miR399 family in the AM-capable plant model Medicago truncatula and could experimentally confirm 10 novel MIR399 genes in this species. Pi-depleted plants showed increased expression of mature miR399 and multiple pri-miR399, and unexpectedly, levels of five of the 15 pri-miR399 species were higher in leaves of mycorrhizal plants than in leaves of nonmycorrhizal plants. Compared with nonmycorrhizal Pi-depleted roots, mycorrhizal roots of Pi-depleted M. truncatula and tobacco plants had increased Pi contents due to symbiotic Pi uptake but displayed higher mature miR399 levels. Expression levels of MtPho2 remained low and PHO2-dependent Pi-stress marker transcript levels remained high in these mycorrhizal roots. Hence, an AM symbiosis-related signal appears to increase miR399 expression and decrease PHO2 activity. MiR399 overexpression in tobacco suggested that miR399 alone is not sufficient to improve mycorrhizal colonization supporting the assumption that, in mycorrhizal roots, increased miR399 are necessary to keep the MtPho2 expression and activity low, which would otherwise increase in response to symbiotic Pi uptake. [less ▲]

Identification and classification of ncRNA molecules using graph properties.

in Nucleic Acids Research (2009), 37(9), 66

The study of non-coding RNA genes has received increased attention in recent years fuelled by accumulating evidence that larger portions of genomes than previously acknowledged are transcribed into RNA ... [more ▼]

The study of non-coding RNA genes has received increased attention in recent years fuelled by accumulating evidence that larger portions of genomes than previously acknowledged are transcribed into RNA molecules of mostly unknown function, as well as the discovery of novel non-coding RNA types and functional RNA elements. Here, we demonstrate that specific properties of graphs that represent the predicted RNA secondary structure reflect functional information. We introduce a computational algorithm and an associated web-based tool (GraPPLE) for classifying non-coding RNA molecules as functional and, furthermore, into Rfam families based on their graph properties. Unlike sequence-similarity-based methods and covariance models, GraPPLE is demonstrated to be more robust with regard to increasing sequence divergence, and when combined with existing methods, leads to a significant improvement of prediction accuracy. Furthermore, graph properties identified as most informative are shown to provide an understanding as to what particular structural features render RNA molecules functional. Thus, GraPPLE may offer a valuable computational filtering tool to identify potentially interesting RNA molecules among large candidate datasets. [less ▲]

An integrative approach towards completing genome-scale metabolic networks.

in Molecular Biosystems (2009), 5(12), 1889-903

Genome-scale metabolic networks which have been automatically derived through sequence comparison techniques are necessarily incomplete. We propose a strategy that incorporates genomic sequence data and ... [more ▼]

Genome-scale metabolic networks which have been automatically derived through sequence comparison techniques are necessarily incomplete. We propose a strategy that incorporates genomic sequence data and metabolite profiles into modeling approaches to arrive at improved gene annotations and more complete genome-scale metabolic networks. The core of our strategy is an algorithm that computes minimal sets of reactions by which a draft network has to be extended in order to be consistent with experimental observations. A particular strength of our approach is that alternative possibilities are suggested and thus experimentally testable hypotheses are produced. We carefully evaluate our strategy on the well-studied metabolic network of Escherichia coli, demonstrating how the predictions can be improved by incorporating sequence data. Subsequently, we apply our method to the recently sequenced green alga Chlamydomonas reinhardtii. We suggest specific genes in the genome of Chlamydomonas which are the strongest candidates for coding the responsible enzymes. [less ▲]