Microbial communities populate most environments on earth and play a critical role in ecology and human health. Their composition is thought to be largely shaped by interspecies competition for the available resources, but cooperative interactions, such as metabolite exchanges, have also been implicated in community assembly. The prevalence of metabolic interactions in microbial communities, however, has remained largely unknown. Here, we systematically survey, by using a genome-scale metabolic modeling approach, the extent of resource competition and metabolic exchanges in over 800 communities. We find that, despite marked resource competition at the level of whole assemblies, microbial communities harbor metabolically interdependent groups that recur across diverse habitats. By enumerating flux-balanced metabolic exchanges in these co-occurring subcommunities we also predict the likely exchanged metabolites, such as amino acids and sugars, that can promote group survival under nutritionally challenging conditions. Our results highlight metabolic dependencies as a major driver of species co-occurrence and hint at cooperative groups as recurring modules of microbial community architecture.

Despite the high abundance of Archaea in the global ocean, their metabolism and biogeochemical roles remain largely unresolved. We investigated the population dynamics and metabolic activity of Thaumarchaeota in polar environments, where these microorganisms are particularly abundant and exhibit seasonal growth. Thaumarchaeota were more abundant in deep Arctic and Antarctic waters and grew throughout the winter at surface and deeper Arctic halocline waters. However, in situ single-cell activity measurements revealed a low activity of this group in the uptake of both leucine and bicarbonate (<5% Thaumarchaeota cells active), which is inconsistent with known heterotrophic and autotrophic thaumarchaeal lifestyles. These results suggested the existence of alternative sources of carbon and energy. Our analysis of an environmental metagenome from the Arctic winter revealed that Thaumarchaeota had pathways for ammonia oxidation and, unexpectedly, an abundance of genes involved in urea transport and degradation. Quantitative PCR analysis confirmed that most polar Thaumarchaeota had the potential to oxidize ammonia, and a large fraction of them had urease genes, enabling the use of urea to fuel nitrification. Thaumarchaeota from Arctic deep waters had a higher abundance of urease genes than those near the surface suggesting genetic differences between closely related archaeal populations. In situ measurements of urea uptake and concentration in Arctic waters showed that small-sized prokaryotes incorporated the carbon from urea, and the availability of urea was often higher than that of ammonium. Therefore, the degradation of urea may be a relevant pathway for Thaumarchaeota and other microorganisms exposed to the low-energy conditions of dark polar waters.

Recently, approaches have been developed to sample the genetic content of heterogeneous environments (metagenomics). However, by what means these sequences link distinct environmental conditions with specific biological processes is not well understood. Thus, a major challenge is how the usage of particular pathways and subnetworks reflects the adaptation of microbial communities across environments and habitats-i.e., how network dynamics relates to environmental features. Previous research has treated environments as discrete, somewhat simplified classes (e.g., terrestrial vs. marine), and searched for obvious metabolic differences among them (i.e., treating the analysis as a typical classification problem). However, environmental differences result from combinations of many factors, which often vary only slightly. Therefore, we introduce an approach that employs correlation and regression to relate multiple, continuously varying factors defining an environment to the extent of particular microbial pathways present in a geographic site. Moreover, rather than looking only at individual correlations (one-to-one), we adapted canonical correlation analysis and related techniques to define an ensemble of weighted pathways that maximally covaries with a combination of environmental variables (many-to-many), which we term a metabolic footprint. Applied to available aquatic datasets, we identified footprints predictive of their environment that can potentially be used as biosensors. For example, we show a strong multivariate correlation between the energy-conversion strategies of a community and multiple environmental gradients (e.g., temperature). Moreover, we identified covariation in amino acid transport and cofactor synthesis, suggesting that limiting amounts of cofactor can (partially) explain increased import of amino acids in nutrient-limited conditions.

Multicellular animals use a three-part molecular toolkit to mediate phospho-tyrosine signaling: Tyrosine kinases (TyrK), protein tyrosine phosphatases (PTP), and Src Homology 2 (SH2) domains function, respectively, as "writers," "erasers," and "readers" of phospho-tyrosine modifications. How did this system of three components evolve, given their interdependent function? Here, we examine the usage of these components in 41 eukaryotic genomes, including the newly sequenced genome of the choanoflagellate, Monosiga brevicollis, the closest known unicellular relative to metazoans. This analysis indicates that SH2 and PTP domains likely evolved earliest-a handful of these domains are found in premetazoan eukaryotes lacking tyrosine kinases, most likely to deal with limited tyrosine phosphorylation cross-catalyzed by promiscuous Ser/Thr kinases. Modern TyrK proteins, however, are only observed in two lineages, metazoans and choanoflagellates. These two lineages show a dramatic coexpansion of all three domain families. Concurrent expansion of the three domain families is consistent with a stepwise evolutionary model in which preexisting SH2 and PTP domains were of limited utility until the appearance of the TyrK domain in the last common ancestor of metazoans and choanoflagellates. The emergence of the full three-component signaling system, with its dramatically increased encoding potential, may have contributed to the advent of metazoan multicellularity.

To assess the potential of protein function prediction in environmental genomics data, we analyzed shotgun sequences from four diverse and complex habitats. Using homology searches as well as customized gene neighborhood methods that incorporate intergenic and evolutionary distances, we inferred specific functions for 76% of the 1.4 million predicted ORFs in these samples (83% when nonspecific functions are considered). Surprisingly, these fractions are only slightly smaller than the corresponding ones in completely sequenced genomes (83% and 86%, respectively, by using the same methodology) and considerably higher than previously thought. For as many as 75,448 ORFs (5% of the total), only neighborhood methods can assign functions, illustrated here by a previously undescribed gene associated with the well characterized heme biosynthesis operon and a potential transcription factor that might regulate a coupling between fatty acid biosynthesis and degradation. Our results further suggest that, although functions can be inferred for most proteins on earth, many functions remain to be discovered in numerous small, rare protein families.

The analysis of completely sequenced genomes uncovers an astonishing variability between species in terms of gene content and order. During genome history, the genes are frequently rear-ranged, duplicated, lost, or transferred horizontally between genomes. These events appear to be stochastic, yet they are under selective constraints resulting from the functional interactions between genes. These genomic constraints form the basis for a variety of techniques that employ systematic genome comparisons to predict functional associations among genes. The most powerful techniques to date are based on conserved gene neighborhood, gene fusion events, and common phylogenetic distributions of gene families. Here we show that these techniques, if integrated quantitatively and applied to a sufficiently large number of genomes, have reached a resolution which allows the characterization of function at a higher level than that of the individual gene: global modularity becomes detectable in a functional protein network. In Escherichia coli, the predicted modules can be bench-marked by comparison to known metabolic pathways. We found as many as 74% of the known metabolic enzymes clustering together in modules, with an average pathway specificity of at least 84%. The modules extend beyond metabolism, and have led to hundreds of reliable functional predictions both at the protein and pathway level. The results indicate that modularity in protein networks is intrinsically encoded in present-day genomes.

Bifidobacteria are Gram-positive prokaryotes that naturally colonize the human gastrointestinal tract (GIT) and vagina. Although not numerically dominant in the complex intestinal microflora, they are considered as key commensals that promote a healthy GIT. We determined the 2.26-Mb genome sequence of an infant-derived strain of Bifidobacterium longum, and identified 1,730 possible coding sequences organized in a 60%-GC circular chromosome. Bioinformatic analysis revealed several physiological traits that could partially explain the successful adaptation of this bacteria to the colon. An unexpectedly large number of the predicted proteins appeared to be specialized for catabolism of a variety of oligosaccharides, some possibly released by rare or novel glycosyl hydrolases acting on "nondigestible" plant polymers or host-derived glycoproteins and glycoconjugates. This ability to scavenge from a large variety of nutrients likely contributes to the competitiveness and persistence of bifidobacteria in the colon. Many genes for oligosaccharide metabolism were found in self-regulated modules that appear to have arisen in part from gene duplication or horizontal acquisition. Complete pathways for all amino acids, nucleotides, and some key vitamins were identified; however, routes for Asp and Cys were atypical. More importantly, genome analysis provided insights into the reciprocal interactions of bifidobacteria with their hosts. We identified polypeptides that showed homology to most major proteins needed for production of glycoprotein-binding fimbriae, structures that could possibly be important for adhesion and persistence in the GIT. We also found a eukaryotic-type serine protease inhibitor (serpin) possibly involved in the reported immunomodulatory activity of bifidobacteria.

By combining the pairwise interactions between proteins, as predicted by the conserved co-occurrence of their genes in operons, we obtain protein interaction networks. Here we study the properties of such networks to identify functional modules: sets of proteins that together are involved in a biological process. The complete network contains 3,033 orthologous groups of proteins in 38 genomes. It consists of one giant component, containing 1,611 orthologous groups, and of 516 small disjointed clusters that, on average, contain only 2.7 orthologous groups. These small clusters have a homogeneous functional composition and thus represent functional modules in themselves. Analysis of the giant component reveals that it is a scale-free, small-world network with a high degree of local clustering (C = 0.6). It consists of locally highly connected subclusters that are connected to each other by linker proteins. The linker proteins tend to have multiple functions, or are involved in multiple processes and have an above average probability of being essential. By splitting up the giant component at these linker proteins, we identify 265 subclusters that tend to have a homogeneous functional composition. The rare functional inhomogeneities in our subclusters reflect the mixing of different types of (molecular) functions in a single cellular process, exemplified by subclusters containing both metabolic enzymes as well as the transcription factors that regulate them. Comparative genome analysis, thus, allows identification of a level of functional interaction between that of pairwise interactions, and of the complete genome.

We have sequenced six overlapping clones from a library of bacterial artificial chromosome (BAC) clones derived from a laboratory strain of the mosquito, Anopheles gambiae, the major vector of human malaria in Africa. The resulting uninterrupted 528-kb sequence is from the 8C region of the mosquito 2R chromosome, at or very near the major refractoriness locus associated with melanotic encapsulation of parasites. This sequence represents the first extensive view of the mosquito genome structure encompassing 48 genes. Genomic comparison reveals that the majority of the orthologues are found in six microsyntenic clusters in Drosophila melanogaster. A BAC clone that is wholly contained within this region demonstrates the existence of a remarkable degree of local polymorphism in this species, which may prove important for its population structure and vectorial capacity.

Together with AIDS and tuberculosis, malaria is at the top of the list of devastating infectious diseases. However, molecular genetic studies of its major vector, Anopheles gambiae, are still quite limited. We have conducted a pilot gene discovery project to accelerate progress in the molecular analysis of vector biology, with emphasis on the mosquito's antimalarial immune defense. A total of 5,925 expressed sequence tags were determined from normalized cDNA libraries derived from immune-responsive hemocyte-like cell lines. The 3,242 expressed sequence tag-containing cDNA clones were grouped into 2,380 clone clusters, potentially representing unique genes. Of these, 1,118 showed similarities to known genes from other organisms, but only 27 were identical to previously known mosquito genes. We identified 38 candidate genes, based on sequence similarity, that may be implicated in immune reactions including antimalarial defense; 19 of these were shown experimentally to be inducible by bacterial challenge, lending support to their proposed involvement in mosquito immunity.

The determination of complete genome sequences provides us with an opportunity to describe and analyze evolution at the comprehensive level of genomes. Here we compare nine genomes with respect to their protein coding genes at two levels: (i) we compare genomes as "bags of genes" and measure the fraction of orthologs shared between genomes and (ii) we quantify correlations between genes with respect to their relative positions in genomes. Distances between the genomes are related to their divergence times, measured as the number of amino acid substitutions per site in a set of 34 orthologous genes that are shared among all the genomes compared. We establish a hierarchy of rates at which genomes have changed during evolution. Protein sequence identity is the most conserved, followed by the complement of genes within the genome. Next is the degree of conservation of the order of genes, whereas gene regulation appears to evolve at the highest rate. Finally, we show that some genomes are more highly organized than others: they show a higher degree of the clustering of genes that have orthologs in other genomes.

Accurate multiple alignments of 86 domains that occur in signaling proteins have been constructed and used to provide a Web-based tool (SMART: simple modular architecture research tool) that allows rapid identification and annotation of signaling domain sequences. The majority of signaling proteins are multidomain in character with a considerable variety of domain combinations known. Comparison with established databases showed that 25% of our domain set could not be deduced from SwissProt and 41% could not be annotated by Pfam. SMART is able to determine the modular architectures of single sequences or genomes; application to the entire yeast genome revealed that at least 6.7% of its genes contain one or more signaling domains, approximately 350 greater than previously annotated. The process of constructing SMART predicted (i) novel domain homologues in unexpected locations such as band 4.1-homologous domains in focal adhesion kinases; (ii) previously unknown domain families, including a citron-homology domain; (iii) putative functions of domain families after identification of additional family members, for example, a ubiquitin-binding role for ubiquitin-associated domains (UBA); (iv) cellular roles for proteins, such predicted DEATH domains in netrin receptors further implicating these molecules in axonal guidance; (v) signaling domains in known disease genes such as SPRY domains in both marenostrin/pyrin and Midline 1; (vi) domains in unexpected phylogenetic contexts such as diacylglycerol kinase homologues in yeast and bacteria; and (vii) likely protein misclassifications exemplified by a predicted pleckstrin homology domain in a Candida albicans protein, previously described as an integrin.

Positional cloning has already produced the sequences of more than 70 human genes associated with specific diseases. In addition to their medical importance, these genes are of interest as a set of human genes isolated solely on the basis of the phenotypic effect of the respective mutations. We analyzed the protein sequences encoded by the positionally cloned disease genes using an iterative strategy combining several sensitive computer methods. Comparisons to complete sequence databases and to separate databases of nematode, yeast, and bacterial proteins showed that for most of the disease gene products, statistically significant sequence similarities are detectable in each of the model organisms. Only the nematode genome encodes apparent orthologs with conserved domain architecture for the majority of the disease genes. In yeast and bacterial homologs, domain organization is typically not conserved, and sequence similarity is limited to individual domains. Generally, human genes complement mutations only in orthologous yeast genes. Most of the positionally cloned genes encode large proteins with several globular and nonglobular domains, the functions of some or all of which are not known. We detected conserved domains and motifs not described previously in a number of proteins encoded by disease genes and predicted functions for some of them. These predictions include an ATP-binding domain in the product of hereditary nonpolyposis colon cancer gene (a MutL homolog), which is conserved in the HS90 family of chaperone proteins, type II DNA topoisomerases, and histidine kinases, and a nuclease domain homologous to bacterial RNase D and the 3'-5' exonuclease domain of DNA polymerase I in the Werner syndrome gene product.

A systematic screen of a protein sequence data base confirms that the fibronectin type III (Fn3) domain is widely distributed among animal proteins and occurs also in several bacterial carbohydrate-splitting enzymes. The motif has yet to be identified in proteins from plants or fungi. All indications are that the bacterial sequences are much too similar to the animal type to be the result of conventional vertical descent. Rather, it is likely that the bacterial units were initially acquired from an animal source and are being spread further by horizontal transfers between distantly related bacteria.

The functionally diverse actin, hexokinase, and hsp70 protein families have in common an ATPase domain of known three-dimensional structure. Optimal superposition of the three structures and alignment of many sequences in each of the three families has revealed a set of common conserved residues, distributed in five sequence motifs, which are involved in ATP binding and in a putative interdomain hinge. From the multiple sequence alignment in these motifs a pattern of amino acid properties required at each position is defined. The discriminatory power of the pattern is in part due to the use of several known three-dimensional structures and many sequences and in part to the "property" method of generalizing from observed amino acid frequencies to amino acid fitness at each sequence position. A sequence data base search with the pattern significantly matches sugar kinases, such as fuco-, glucono-, xylulo-, ribulo-, and glycerokinase, as well as the prokaryotic cell cycle proteins MreB, FtsA, and StbA. These are predicted to have subdomains with the same tertiary structure as the ATPase subdomains Ia and IIa of hexokinase, actin, and Hsc70, a very similar ATP binding pocket, and the capacity for interdomain hinge motion accompanying functional state changes. A common evolutionary origin for all of the proteins in this class is proposed.