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1.  Defining the core Arabidopsis thaliana root microbiome 
Nature  2012;488(7409):86-90.
Land plants associate with a root microbiota distinct from the complex microbial community present in surrounding soil. The microbiota colonizing therhizosphere(immediately surroundingthe root) and the endophytic compartment (within the root) contribute to plant growth, productivity, carbon sequestration and phytoremediation1-3. Colonization of the root occurs despite a sophisticated plant immune system4,5, suggesting finely tuned discrimination of mutualists and commensals from pathogens. Genetic principles governing the derivation of host-specific endophyte communities from soil communities are poorly understood. Here we report the pyrosequencing of the bacterial 16S ribosomal RNA gene of more than 600 Arabidopsis thaliana plants to test the hypotheses that the root rhizosphere and endophytic compartment microbiota of plants grown under controlled conditions in natural soils are sufficiently dependent on the host to remain consistent across different soil types and developmental stages, and sufficiently dependent on host genotype to vary between inbred Arabidopsis accessions. We describe different bacterial communities in two geochemically distinct bulk soils and in rhizosphere and endophytic compartments prepared from roots grown in these soils. The communities in each compartment are strongly influenced by soil type. Endophytic compartments from both soils feature overlapping, low-complexity communities that are markedly enriched in Actinobacteria and specific families from other phyla, notably Proteobacteria. Some bacteria vary quantitatively between plants of different developmental stage and genotype. Our rigorous definition of an endophytic compartment microbiome should facilitate controlled dissection of plantmicrobe interactions derived from complex soil communities.
PMCID: PMC4074413  PMID: 22859206
2.  A phylogeny-driven genomic encyclopaedia of Bacteria and Archaea 
Nature  2009;462(7276):1056-1060.
Sequencing of bacterial and archaeal genomes has revolutionized our understanding of the many roles played by microorganisms1. There are now nearly 1,000 completed bacterial and archaeal genomes available2, most of which were chosen for sequencing on the basis of their physiology. As a result, the perspective provided by the currently available genomes is limited by a highly biased phylogenetic distribution3–5. To explore the value added by choosing microbial genomes for sequencing on the basis of their evolutionary relationships, we have sequenced and analysed the genomes of 56 culturable species of Bacteria and Archaea selected to maximize phylogenetic coverage. Analysis of these genomes demonstrated pronounced benefits (compared to an equivalent set of genomes randomly selected from the existing database) in diverse areas including the reconstruction of phylogenetic history, the discovery of new protein families and biological properties, and the prediction of functions for known genes from other organisms. Our results strongly support the need for systematic ‘phylogenomic’ efforts to compile a phylogeny-driven ‘Genomic Encyclopedia of Bacteria and Archaea’ in order to derive maximum knowledge from existing microbial genome data as well as from genome sequences to come.
PMCID: PMC3073058  PMID: 20033048
3.  A Bioinformatician's Guide to Metagenomics 
Summary: As random shotgun metagenomic projects proliferate and become the dominant source of publicly available sequence data, procedures for the best practices in their execution and analysis become increasingly important. Based on our experience at the Joint Genome Institute, we describe the chain of decisions accompanying a metagenomic project from the viewpoint of the bioinformatic analysis step by step. We guide the reader through a standard workflow for a metagenomic project beginning with presequencing considerations such as community composition and sequence data type that will greatly influence downstream analyses. We proceed with recommendations for sampling and data generation including sample and metadata collection, community profiling, construction of shotgun libraries, and sequencing strategies. We then discuss the application of generic sequence processing steps (read preprocessing, assembly, and gene prediction and annotation) to metagenomic data sets in contrast to genome projects. Different types of data analyses particular to metagenomes are then presented, including binning, dominant population analysis, and gene-centric analysis. Finally, data management issues are presented and discussed. We hope that this review will assist bioinformaticians and biologists in making better-informed decisions on their journey during a metagenomic project.
PMCID: PMC2593568  PMID: 19052320
4.  Genome Analysis of the Anaerobic Thermohalophilic Bacterium Halothermothrix orenii 
PLoS ONE  2009;4(1):e4192.
Halothermothirx orenii is a strictly anaerobic thermohalophilic bacterium isolated from sediment of a Tunisian salt lake. It belongs to the order Halanaerobiales in the phylum Firmicutes. The complete sequence revealed that the genome consists of one circular chromosome of 2578146 bps encoding 2451 predicted genes. This is the first genome sequence of an organism belonging to the Haloanaerobiales. Features of both Gram positive and Gram negative bacteria were identified with the presence of both a sporulating mechanism typical of Firmicutes and a characteristic Gram negative lipopolysaccharide being the most prominent. Protein sequence analyses and metabolic reconstruction reveal a unique combination of strategies for thermophilic and halophilic adaptation. H. orenii can serve as a model organism for the study of the evolution of the Gram negative phenotype as well as the adaptation under thermohalophilic conditions and the development of biotechnological applications under conditions that require high temperatures and high salt concentrations.
PMCID: PMC2626281  PMID: 19145256
5.  Millimeter-scale genetic gradients and community-level molecular convergence in a hypersaline microbial mat 
To investigate the extent of genetic stratification in structured microbial communities, we compared the metagenomes of 10 successive layers of a phylogenetically complex hypersaline mat from Guerrero Negro, Mexico. We found pronounced millimeter-scale genetic gradients that were consistent with the physicochemical profile of the mat. Despite these gradients, all layers displayed near-identical and acid-shifted isoelectric point profiles due to a molecular convergence of amino-acid usage, indicating that hypersalinity enforces an overriding selective pressure on the mat community.
PMCID: PMC2483411  PMID: 18523433
metagenomics; hypersalinity; microbial ecology; fine-scale; salt-in
6.  Denoising inferred functional association networks obtained by gene fusion analysis 
BMC Genomics  2007;8:460.
Gene fusion detection – also known as the 'Rosetta Stone' method – involves the identification of fused composite genes in a set of reference genomes, which indicates potential interactions between its un-fused counterpart genes in query genomes. The precision of this method typically improves with an ever-increasing number of reference genomes.
In order to explore the usefulness and scope of this approach for protein interaction prediction and generate a high-quality, non-redundant set of interacting pairs of proteins across a wide taxonomic range, we have exhaustively performed gene fusion analysis for 184 genomes using an efficient variant of a previously developed protocol. By analyzing interaction graphs and applying a threshold that limits the maximum number of possible interactions within the largest graph components, we show that we can reduce the number of implausible interactions due to the detection of promiscuous domains. With this generally applicable approach, we generate a robust set of over 2 million distinct and testable interactions encompassing 696,894 proteins in 184 species or strains, most of which have never been the subject of high-throughput experimental proteomics. We investigate the cumulative effect of increasing numbers of genomes on the fidelity and quantity of predictions, and show that, for large numbers of genomes, predictions do not become saturated but continue to grow linearly, for the majority of the species. We also examine the percentage of component (and composite) proteins with relation to the number of genes and further validate the functional categories that are highly represented in this robust set of detected genome-wide interactions.
We illustrate the phylogenetic and functional diversity of gene fusion events across genomes, and their usefulness for accurate prediction of protein interaction and function.
PMCID: PMC2248599  PMID: 18081932
7.  Evolutionary conservation of sequence and secondary structures in CRISPR repeats 
Genome Biology  2007;8(4):R61.
The categorisation and structural analysis of Clustered Regularly Interspaced Short Palindromic Repeats (CRISPRs) sequences from 195 microbial genomes show that repeats from diverse organisms can be grouped based on sequence similarity, and that some groups have pronounced secondary structures with compensatory base changes.
Clustered regularly interspaced short palindromic repeats (CRISPRs) are a novel class of direct repeats, separated by unique spacer sequences of similar length, that are present in approximately 40% of bacterial and most archaeal genomes analyzed to date. More than 40 gene families, called CRISPR-associated sequences (CASs), appear in conjunction with these repeats and are thought to be involved in the propagation and functioning of CRISPRs. It has been recently shown that CRISPR provides acquired resistance against viruses in prokaryotes.
Here we analyze CRISPR repeats identified in 195 microbial genomes and show that they can be organized into multiple clusters based on sequence similarity. Some of the clusters present stable, highly conserved RNA secondary structures, while others lack detectable structures. Stable secondary structures exhibit multiple compensatory base changes in the stem region, indicating evolutionary and functional conservation.
We show that the repeat-based classification corresponds to, and expands upon, a previously reported CAS gene-based classification, including specific relationships between CRISPR and CAS subtypes.
PMCID: PMC1896005  PMID: 17442114
8.  Expansion of the BioCyc collection of pathway/genome databases to 160 genomes 
Nucleic Acids Research  2005;33(19):6083-6089.
The BioCyc database collection is a set of 160 pathway/genome databases (PGDBs) for most eukaryotic and prokaryotic species whose genomes have been completely sequenced to date. Each PGDB in the BioCyc collection describes the genome and predicted metabolic network of a single organism, inferred from the MetaCyc database, which is a reference source on metabolic pathways from multiple organisms. In addition, each bacterial PGDB includes predicted operons for the corresponding species. The BioCyc collection provides a unique resource for computational systems biology, namely global and comparative analyses of genomes and metabolic networks, and a supplement to the BioCyc resource of curated PGDBs. The Omics viewer available through the BioCyc website allows scientists to visualize combinations of gene expression, proteomics and metabolomics data on the metabolic maps of these organisms. This paper discusses the computational methodology by which the BioCyc collection has been expanded, and presents an aggregate analysis of the collection that includes the range of number of pathways present in these organisms, and the most frequently observed pathways. We seek scientists to adopt and curate individual PGDBs within the BioCyc collection. Only by harnessing the expertise of many scientists we can hope to produce biological databases, which accurately reflect the depth and breadth of knowledge that the biomedical research community is producing.
PMCID: PMC1266070  PMID: 16246909
9.  Clustering the annotation space of proteins 
BMC Bioinformatics  2005;6:24.
Current protein clustering methods rely on either sequence or functional similarities between proteins, thereby limiting inferences to one of these areas.
Here we report a new approach, named CLAN, which clusters proteins according to both annotation and sequence similarity. This approach is extremely fast, clustering the complete SwissProt database within minutes. It is also accurate, recovering consistent protein families agreeing on average in more than 97% with sequence-based protein families from Pfam. Discrepancies between sequence- and annotation-based clusters were scrutinized and the reasons reported. We demonstrate examples for each of these cases, and thoroughly discuss an example of a propagated error in SwissProt: a vacuolar ATPase subunit M9.2 erroneously annotated as vacuolar ATP synthase subunit H. CLAN algorithm is available from the authors and the CLAN database is accessible at
CLAN creates refined function-and-sequence specific protein families that can be used for identification and annotation of unknown family members. It also allows easy identification of erroneous annotations by spotting inconsistencies between similarities on annotation and sequence levels.
PMCID: PMC552314  PMID: 15703069
10.  Measuring genome conservation across taxa: divided strains and united kingdoms 
Nucleic Acids Research  2005;33(2):616-621.
Species evolutionary relationships have traditionally been defined by sequence similarities of phylogenetic marker molecules, recently followed by whole-genome phylogenies based on gene order, average ortholog similarity or gene content. Here, we introduce genome conservation—a novel metric of evolutionary distances between species that simultaneously takes into account, both gene content and sequence similarity at the whole-genome level. Genome conservation represents a robust distance measure, as demonstrated by accurate phylogenetic reconstructions. The genome conservation matrix for all presently sequenced organisms exhibits a remarkable ability to define evolutionary relationships across all taxonomic ranges. An assessment of taxonomic ranks with genome conservation shows that certain ranks are inadequately described and raises the possibility for a more precise and quantitative taxonomy in the future. All phylogenetic reconstructions are available at the genome phylogeny server: <>.
PMCID: PMC548337  PMID: 15681613
11.  Comprehensive analysis of pseudogenes in prokaryotes: widespread gene decay and failure of putative horizontally transferred genes 
Genome Biology  2004;5(9):R64.
A comprehensive analysis of the occurrence of pseudogenes in a diverse selection of 64 prokaryote genomes identified around 7,000 candidate pseudogenes. A large fraction of prokaryote pseudogenes seems to have arisen from failed horizontal-transfer events.
Pseudogenes often manifest themselves as disabled copies of known genes. In prokaryotes, it was generally believed (with a few well-known exceptions) that they were rare.
We have carried out a comprehensive analysis of the occurrence of pseudogenes in a diverse selection of 64 prokaryote genomes. Overall, we find a total of around 7,000 candidate pseudogenes. Moreover, in all the genomes surveyed, pseudogenes occur in at least 1 to 5% of all gene-like sequences, with some genomes having considerably higher occurrence. Although many large populations of pseudogenes arise from large, diverse protein families (for example, the ABC transporters), notable numbers of pseudogenes are associated with specific families that do not occur that widely. These include the cytochrome P450 and PPE families (PF00067 and PF00823) and others that have a direct role in DNA transposition.
We find suggestive evidence that a large fraction of prokaryote pseudogenes arose from failed horizontal transfer events. In particular, we find that pseudogenes are more than twice as likely as genes to have anomalous codon usage associated with horizontal transfer. Moreover, we found a significant difference in the number of horizontally transferred pseudogenes in pathogenic and non-pathogenic strains of Escherichia coli.
PMCID: PMC522871  PMID: 15345048
12.  Protein families and Tribes in genome sequence space 
Nucleic Acids Research  2003;31(15):4632-4638.
Accurate detection of protein families allows assignment of protein function and the analysis of functional diversity in complete genomes. Recently, we presented a novel algorithm called TribeMCL for the detection of protein families that is both accurate and efficient. This method allows family analysis to be carried out on a very large scale. Using TribeMCL, we have generated a resource called Tribes that contains protein family information, comprising annotations, protein sequence alignments and phylogenetic distributions describing 311 257 proteins from 83 completely sequenced genomes. The analysis of at least 60 934 detected protein families reveals that, with the essential families excluded, paralogy levels are similar between prokaryotes, irrespective of genome size. The number of essential families is estimated to be between 366 and 426. We also show that the currently known space of protein families is scale free and discuss the implications of this distribution. In addition, we show that smaller families are often formed by shorter proteins and discuss the reasons for this intriguing pattern. Finally, we analyse the functional diversity of protein families in entire genome sequences. The Tribes protein family resource is accessible at
PMCID: PMC169885  PMID: 12888524
13.  Beyond 100 genomes 
Genome Biology  2003;4(5):402.
By the end of 2002, we witnessed the landmark submission of the 100th complete genome sequence in the databases. An overview of these genomes reveals certain interesting trends and provides valuable insights into possible future developments.
PMCID: PMC156585  PMID: 12734008
14.  Myriads of protein families, and still counting 
Genome Biology  2003;4(2):401.
From the historical record of genome sequencing, we show that the rate of discovery of new families has remained constant over time, indicating that our knowledge of sequence space is far from complete.
From the historical record of genome sequencing, we show that the rate of discovery of new families has remained constant over time, indicating that our knowledge of sequence space is far from complete.
PMCID: PMC151299  PMID: 12620116

Results 1-14 (14)