Biology subjects

Koonin, E. V.

Publications and source records attributed to Koonin, E. V..

At least 91 records · Page 5Linked to original sources

bioRxiv2020

Prediction of the virus incubation period for COVID-19 and future outbreaks

A crucial factor in mitigating respiratory viral outbreaks is early determination of the duration of the incubation period and, accordingly, the required quarantine time for potentially exposed individuals. Here, we explore different genomic features of RNA viruses that correlate with the incubation times and provide a predictive model that accurately estimates the upper limit incubation time for diverse viruses including SARS-CoV-2, and thus, could help control future outbreaks.

microbiology↗

bioRxiv2020

Selection for reducing energy cost of protein production drives the GC content and amino acid composition bias in gene transfer agents

Gene transfer agents (GTAs) are virus-like elements integrated into bacterial genomes, particularly, those of Alphaproteobacteria. The GTAs can be induced under nutritional stress, incorporate random fragments of bacterial DNA into mini-phage particles, lyse the host cells and infect neighboring bacteria, thus enhancing horizontal gene transfer. We show that the GTA genes evolve under pronounced positive selection for the reduction of the energy cost of protein production as shown by comparison of the amino acid compositions with both homologous viral genes and host genes. The energy saving in GTA genes is comparable to or even more pronounced than that in the genes encoding the most abundant, essential bacterial proteins. In cases when viruses acquire genes from GTAs, the bias in amino acid composition disappears in the course of evolution, showing that reduction of the energy cost of protein is an important factor of evolution of GTAs but not bacterial viruses. These findings strongly suggest that GTAs are bacterial adaptations rather than selfish, virus-like elements. Because GTA production kills the host cell and does not propagate the GTA genome, it appears likely that the GTAs are retained in the course of evolution via kin or group selection. Therefore, we hypothesize that GTA facilitate the survival of bacterial populations under energy-limiting conditions through the spread of metabolic and transport capabilities via horizontal gene transfer and increase of nutrient availability resulting from the altruistic suicide of GTA-producing cells. ImportanceKin and group selection remain controversial topics in evolutionary biology. We argue that these types of selection are likely to operate in bacterial populations by showing that bacterial Gene Transfer Agents (GTAs), but not related viruses, evolve under positive selection for the reduction of the energy cost of a GTA particle production. We hypothesize that GTAs are dedicated devices for the survival of bacteria under the conditions of nutrient limitation. The benefits conferred by GTAs under nutritional stress appear to include horizontal dissemination of genes that could provide bacteria with enhanced capabilities for nutrient utilization and the increase of nutrient availability through the lysis of GTA-producing bacteria.

evolutionary biology↗

bioRxiv2020

Co-evolution of Eukaryotic-like Vps4 and ESCRT-III Subunits in the Asgard Archaea

The emergence of the endomembrane system is a key step in the evolution of cellular complexity during eukaryogenesis. The Endosomal Sorting Complex Required for Transport (ESCRT) machinery is essential and required for the endomembrane system functions in eukaryotic cells. Recently, genes encoding eukaryote-like ESCRT protein components have been identified in the genomes of Asgard archaea, a newly proposed archaeal superphylum that is thought to include the closest extant prokaryotic relatives of eukaryotes. However, structural and functional features of Asgard ESCRT remain uncharacterized. Here we show that Vps4, Vps2/24/46, and Vps20/32/60, the core functional components of the Asgard ESCRT, co-evolved eukaryote-like structural and functional features. Phylogenetic analysis shows that Asgard Vps4, Vps2/24/46, and Vps20/32/60 are closely related to their eukaryotic counterparts. Molecular dynamic simulation and biochemical assays indicate that Asgard Vps4 contains a eukaryote-like Microtubule Interacting and Transport (MIT) domain that binds the distinct type-1 MIT Interacting Motif and type-2 MIT Interacting Motif in Vps2/24/46, and Vps20/32/60, respectively. The Asgard Vps4 partly, but much more efficiently than homologs from other archaea, complements the vps4 null mutant of Saccharomyces cerevisiae, further supporting the functional similarity between the membrane remodeling machineries of Asgard archaea and eukaryotes. Thus, this work provides evidence that the ESCRT complexes from Asgard archaea and eukaryotes are evolutionarily related and functionally similar. Thus, despite the apparent absence of endomembranes in Asgard archaea, the eukaryotic ESCRT seems to have been directly inherited from an Asgard ancestor, to become a key component of the emerging endomembrane system. IMPORTANCEThe discovery of Asgard archaea has changed the exiting ideas on the origins of Eukaryotes. Researchers propose that eukaryotic cells evolve from Asgard archaea. This hypothesis partly stems from the presence of multiple eukaryotic signature proteins in Asgard archaea, including homologues of ESCRT proteins that are essential components of the endomembrane system in eukaryotes. However, structural and functional features of Asgard ESCRT remain unknown. Our study provides evidence that Asgard ESCRT is functionally comparable to the eukaryotic counterparts suggesting that, despite the apparent absence of endomembranes in archaea, eukaryotic ESCRT was inherited from an Asgard archaeal ancestor, alongside the emergence of endomembrane system during eukaryogenesis.

microbiology↗

bioRxiv2020

Horizontal gene transfer barrier shapes the evolution of prokaryotic pangenomes

The genomes of bacteria and archaea evolve by extensive loss and gain of genes which, for any group of related prokaryotic genomes, result in the formation of a pangenome with the universal, asymmetrical U-shaped distribution of gene commonality. To elucidate the evolutionary factors that define the specific shape of this distribution, we investigate the fit of simple models of genome evolution to the empirically observed gene commonality distributions and genomes intersections for 33 groups of closely related bacterial genomes. The combined analysis of genome intersections and gene commonality shows that at least one of the two simplifying assumptions that are usually adopted for modeling the evolution of the U-shaped distribution, those of infinitely many genes and constant genome size, is invalid. The violation of both these assumptions stems from the horizontal gene transfer barrier, i.e. the cost of accommodation of foreign genes by prokaryotes.

evolutionary biology↗

bioRxiv2020

Genomic determinants of pathogenicity in SARS-CoV-2 and other human coronaviruses

SARS-CoV-2 poses an immediate, major threat to public health across the globe. Here we report an in-depth molecular analysis to reconstruct the evolutionary origins of the enhanced pathogenicity of SARS-CoV-2 and other coronaviruses that are severe human pathogens. Using integrated comparative genomics and machine learning techniques, we identify key genomic features that differentiate SARS-CoV-2 and the viruses behind the two previous deadly coronavirus outbreaks, SARS-CoV and MERS-CoV, from less pathogenic coronaviruses. These features include enhancement of the nuclear localization signals in the nucleocapsid protein and distinct inserts in the spike glycoprotein that appear to be associated with high case fatality rate of these coronaviruses as well as the host switch from animals to humans. The identified features could be crucial elements of coronavirus pathogenicity and possible targets for diagnostics, prognostication and interventions.

microbiology↗

bioRxiv2020

Seeker: Alignment-free identification of bacteriophage genomes by deep learning

Advances in metagenomics enable massive discovery of diverse, distinct microbes and viruses. Bacteriophages, the most abundant biological entity on Earth, evolve rapidly, and therefore, detection of unknown bacteriophages in sequence datasets is a challenge. The existing methods rely on sequence similarity to known bacteriophage sequences, impeding the identification and characterization of distinct bacteriophage families. We present Seeker, a deep-learning tool for reference-free identification of phage sequences. Seeker allows rapid detection of phages in sequence datasets and clean differentiation of phage sequences from bacterial ones, even for phages with little sequence similarity to established phage families. We comprehensively validate Seekers ability to identify unknown phages and employ Seeker to detect unknown phages, some of which are highly divergent from known phage families. We provide a web portal (seeker.pythonanywhere.com) and a user-friendly python package (https://github.com/gussow/seeker) allowing researchers to easily apply Seeker in metagenomic studies, for the detection of diverse unknown bacteriophages.

microbiology↗

bioRxiv2020

Structure and function of virion RNA polymerase of crAss-like phage

CrAss-like phages are a recently described family-level group of viruses that includes the most abundant virus in the human gut1,2. Genomes of all crAss-like phages encode a large virion-packaged protein2,3 that contains a DFDxD sequence motif, which forms the catalytic site in cellular multisubunit RNA polymerases (RNAPs)4. Using Cellulophaga baltica crAss-like phage phi14:2 as a model system, we show that this protein is a novel DNA-dependent RNAP that is translocated into the host cell along with the phage DNA and transcribes early phage genes. We determined the crystal structure of this 2,180-residue enzyme in a self-inhibited, likely pre-virion-packaged state. This conformation is attained with the help of a Cleft-blocking domain that interacts with the active site motif and occupies the RNA-DNA hybrid binding grove. Structurally, phi14:2 RNAP is most similar to eukaryotic RNAPs involved in RNA interference5,6, although most of phi14:2 RNAP structure (nearly 1,600 residues) maps to a new region of protein folding space. Considering the structural similarity, we propose that eukaryal RNA interference polymerases take their origin in a phage, which parallels the emergence of the mitochondrial transcription apparatus7.

molecular biology↗

bioRxiv2020

Viral channelrhodopsins: calcium-dependent Na+/K+ selective light-gated channels

Phytoplankton is the base of the marine food chain, oxygen, carbon cycle playing a global role in climate and ecology. Nucleocytoplasmic Large DNA Viruses regulating the dynamics of phytoplankton comprise genes of rhodopsins of two distinct families. We present a function-structure characterization of two homologous proteins representatives of family 1 of viral rhodopsins, OLPVR1 and VirChR1. VirChR1 is a highly selective, Ca2+-dependent, Na+/K+- conducting channel and, in contrast to known cation channelrhodopsins (ChRs), is impermeable to Ca2+ ions. In human neuroblastoma cells, upon illumination, VirChR1 depolarizes the cell membrane to a level sufficient to fire neurons. It suggests its unique optogenetic potential. 1.4 [A] resolution structure of OLPVR1 reveals their remarkable difference from the known channelrhodopsins and a unique ion-conducting pathway. The data suggest that viral channelrhodopsins mediate phototaxis of algae enhancing the host anabolic processes to support virus reproduction, and therefore, their key role in global phytoplankton dynamics.

biophysics↗

bioRxiv2020

Vast diversity of anti-CRISPR proteins predicted with a machine-learning approach

Bacteria and archaea evolve under constant pressure from numerous, diverse viruses and thus have evolved multiple defense systems. The CRISPR-Cas are adaptive immunity systems that have been harnessed for the development of the new generation of genome editing and engineering tools. In the incessant host-parasite arms race, viruses evolved multiple anti-defense mechanisms including numerous, diverse anti-CRISPR proteins (Acrs) that can inhibit CRISPR-Cas and therefore have enormous potential for application as modulators of genome editing tools. Most Acrs are small, highly variable proteins which makes their prediction a formidable task. We developed a machine learning approach for comprehensive Acr prediction. The model showed high predictive power when tested against an unseen test set that included several families of recently discovered Acrs and was employed to predict 2,500 novel candidate Acr families. An examination of the top candidates confirms that they possess typical Acr features. One of the top candidates was independently tested and found to possess anti-CRISPR activity (AcrIIA12). We provide a web resource (http://acrcatalog.pythonanywhere.com/) to access the predicted Acrs sequences and annotation. The results of this analysis expand the repertoire of predicted Acrs almost by two orders of magnitude and provide a rich resource for experimental Acr discovery.

microbiology↗

bioRxiv2019

In silico learning of tumor evolution through mutational time series

Cancer arises through the accumulation of somatic mutations over time. Understanding the sequence of mutation occurrence during cancer progression can assist early and accurate diagnosis and improve clinical decision-making. Here we employ Long Short-Term Memory networks (LSTMs), a class of recurrent neural network, to learn the evolution of a tumor through an ordered sequence of mutations. We demonstrate the capacity of LSTMs to learn complex dynamics of the mutational time series governing tumor progression, allowing accurate prediction of the mutational burden and the occurrence of mutations in the sequence. Using the probabilities learned by the LSTM, we simulate mutational data and show that the simulation results are statistically indistinguishable from the empirical data. We identify passenger mutations that are significantly associated with established cancer drivers in the sequence and demonstrate that the genes carrying these mutations are substantially enriched in interactions with the corresponding driver genes. Breaking the network into modules consisting of driver genes and their interactors, we show that these interactions are associated with poor patient prognosis, thus likely conferring growth advantage for tumor progression. Thus, application of LSTM provides for prediction of numerous additional conditional drivers and to reveal hitherto unknown aspects of cancer evolution.\n\nSignificanceCancer is caused by the effects of somatic mutations known as drivers. Although a number of major cancer drivers have been identified, it is suspected that many more comparatively rare and conditional drivers exist, and the interactions between different cancer-associated mutations that might be relevant for tumor progression are not well understood. We applied an advanced neural network approach to learn the sequence of mutations and the mutational burden in colon and lung cancers, and to identify mutations that are associated with individual drivers. A significant ordering of driver mutations is demonstrated, and numerous, previously undetected conditional drivers are identified. These findings broaden the existing understanding of the mechanisms of tumor progression and have implications for therapeutic strategies.

bioinformatics↗

bioRxiv2019

Homologous recombination substantially delays sequence but not gene content divergence of prokaryotic populations

Evolution of bacterial and archaeal genomes is a highly dynamic process that involves extensive gain and loss of genes. Therefore, phylogenetic trees of prokaryotes can be constructed both by the traditional sequence-based methods (gene trees) and by comparison of gene compositions (genome trees). Comparing the branch lengths in gene and genome trees with identical topologies for 34 clusters of closely related bacterial and archaeal genomes, we found that the terminal branches of gene trees were systematically compressed compared to those of genome trees. Thus, sequence evolution seems to be significantly delayed with respect to genome evolution by gene gain and loss. The extent of this delay widely differs among bacterial and archaeal lineages. We develop and explore mathematical models demonstrating that the delay of sequence divergence can be explained by sequence homogenization that is caused by homologous recombination. Once evolving genomes become isolated by barriers that impede homologous recombination, gene and genome evolution processes settle into parallel trajectories, and genomes diverge, resulting in speciation. This model of prokaryotic genome evolution gives a mechanistic explanation of our previous finding that archaeal genomes contain a class of genes that turn over rapidly, before significant sequence divergence occurs, and provides a framework for correcting phylogenetic trees, to make them consistent with the dynamics of gene turnover.

evolutionary biology↗

bioRxiv2019

Crossing fitness valleys via double substitutions within codons

Single nucleotide substitutions in protein-coding genes can be divided into synonymous (S), with little fitness effect, and non-synonymous (N) ones that alter amino acids and thus generally have a greater effect. Most of the N substitutions are affected by purifying selection that eliminates them from evolving populations. However, additional mutations of nearby bases can modulate the deleterious effect of single substitutions and thus might be subject to positive selection. To elucidate the effects of selection on double substitutions in all codons, it is critical to differentiate selection from mutational biases. We approached this problem by comparing the fractions of double substitutions within codons to those of the equivalent double S substitutions in adjacent codons. Under the assumption that substitutions occur one at a time, all within-codon double substitutions can be represented as \"ancestral-intermediate-final\" sequences and can be partitioned into 4 classes: 1) SS: S intermediate - S final, 2) SN: S intermediate - N final, 3) NS: N intermediate - S final, 4) NN: N intermediate - N final. We found that the selective pressure on the second substitution markedly differs among these classes of double substitutions. Analogous to single S substitutions, SS evolve neutrally whereas, analogous to single N substitutions, SN are subject to purifying selection. In contrast, NS show positive selection on the second step because the original amino acid is recovered. The NN double substitutions are heterogeneous and can be subject to either purifying or positive selection, or evolve neutrally, depending on the amino acid similarity between the final or intermediate and the ancestral states. The general trend is that the second mutation compensates for the deleterious effect of the first one, resulting in frequent crossing of valleys on the fitness landscape.

evolutionary biology↗

bioRxiv2018

Proteomic and Genomic Signatures of Repeat-instability in Cancer and Adjacent Normal Tissues

Repetitive sequences are hotspots of evolution at multiple levels. However, due to technical difficulties involved in their assembly and analysis, the role of repeats in tumor evolution is poorly understood. We developed a rigorous motif-based methodology to quantify variations in the repeat content of proteomes and genomes, directly from proteomic and genomic raw sequence data, and applied it to analyze a wide range of tumors and normal tissues. We identify high similarity between the repeat-instability in tumors and their patient-matched normal tissues, but also tumor-specific signatures, both in protein expression and in the genome, that strongly correlate with cancer progression and robustly predict the tumorigenic state. In a patient, the hierarchy of genomic repeat instability signatures accurately reconstructs tumor evolution, with primary tumors differentiated from metastases. We find an inverse relationship between repeat-instability and point mutation load, within and across patients, and independently of other somatic aberrations. Thus, repeat-instability is a distinct, transient and compensatory adaptive mechanism in tumor evolution.

cancer biology↗

bioRxiv2018

Virus genomes from deep sea sediments expand the ocean megavirome and support independent origins of viral gigantism

The Nucleocytoplasmic Large DNA Viruses (NCLDV) of eukaryotes (proposed order \"Megavirales\") include the families Poxviridae, Asfarviridae, Iridoviridae, Ascoviridae, Phycodnaviridae, Marseilleviridae, and Mimiviridae, as well as still unclassified Pithoviruses, Pandoraviruses, Molliviruses and Faustoviruses. Several of these virus groups include giant viruses, with genome and particle sizes exceeding those of many bacterial and archaeal cells. We explored the diversity of the NCLDV in deep-sea sediments from the Lokis Castle hydrothermal vent area. Using metagenomics, we reconstructed 23 high quality genomic bins of novel NCLDV, 15 of which are closest related to Pithoviruses, 5 to Marseilleviruses, 1 to Iridoviruses, and 2 to Klosneuviruses. Some of the identified Pitho-like and Marseille-like genomes belong to deep branches in the phylogenetic tree of core NCLDV genes, substantially expanding the diversity and phylogenetic depth of the respective groups. The discovered viruses have a broad range of apparent genome sizes including putative giant members of the family Marseilleviridae, in agreement with multiple, independent origins of gigantism in different branches of the NCLDV. Phylogenomic analysis reaffirms the monophyly of the Pitho-Irido-Marseille branch of NCLDV. Similarly to other giant viruses, the Pitho-like viruses from Lokis Castle encode translation systems components. Phylogenetic analysis of these genes indicates a greater bacterial contribution than detected previously. Genome comparison suggests extensive gene exchange between members of the Pitho-like viruses and Mimiviridae. Further exploration of the genomic diversity of \"Megavirales\" in additional sediment samples is expected to yield new insights into the evolution of giant viruses and the composition of the ocean megavirome.\n\nImportanceGenomics and evolution of giant viruses is one of the most vigorously developing areas of virus research. Lately, metagenomics has become the main source of new virus genomes. Here we describe a metagenomic analysis of the genomes of large and giant viruses from deep sea sediments. The assembled new virus genomes substantially expand the known diveristy of the Nucleo-Cytoplasmic Large DNA Viruses of eukaryotes. The results support the concept of independent evolution of giant viruses from smaller ancestors in different virus branches.

microbiology↗

bioRxiv2018

Origins and Evolution of the Global RNA Virome

Viruses with RNA genomes dominate the eukaryotic virome, reaching enormous diversity in animals and plants. The recent advances of metaviromics prompted us to perform a detailed phylogenomic reconstruction of the evolution of the dramatically expanded global RNA virome. The only universal gene among RNA viruses is the RNA-dependent RNA polymerase (RdRp). We developed an iterative computational procedure that alternates the RdRp phylogenetic tree construction with refinement of the underlying multiple sequence alignments. The resulting tree encompasses 4,617 RNA virus RdRps and consists of 5 major branches, 2 of which include positive-sense RNA viruses, 1 is a mix of positive-sense (+) RNA and double-stranded (ds) RNA viruses, and 2 consist of dsRNA and negative-sense (-) RNA viruses, respectively. This tree topology implies that dsRNA viruses evolved from +RNA viruses on at least two independent occasions, whereas -RNA viruses evolved from dsRNA viruses. Reconstruction of RNA virus evolution using the RdRp tree as the scaffold suggests that the last common ancestors of the major branches of +RNA viruses encoded only the RdRp and a single jelly-roll capsid protein. Subsequent evolution involved independent capture of additional genes, particularly, those encoding distinct RNA helicases, enabling replication of larger RNA genomes and facilitating virus genome expression and virus-host interactions. Phylogenomic analysis reveals extensive gene module exchange among diverse viruses and horizontal virus transfer between distantly related hosts. Although the network of evolutionary relationships within the RNA virome is bound to further expand, the present results call for a thorough reevaluation of the RNA virus taxonomy.\n\nIMPORTANCEThe majority of the diverse viruses infecting eukaryotes have RNA genomes, including numerous human, animal, and plant pathogens. Recent advances of metagenomics have led to the discovery of many new groups of RNA viruses in a wide range of hosts. These findings enable a far more complete reconstruction of the evolution of RNA viruses than what was attainable previously. This reconstruction reveals the relationships between different Baltimore Classes of viruses and indicates extensive transfer of viruses between distantly related hosts, such as plants and animals. These results call for a major revision of the existing taxonomy of RNA viruses.

microbiology↗

bioRxiv2018

Stability of host-parasite systems: you must differ to coevolve

BackgroundGenetic parasites are ubiquitous satellites of cellular life forms most of which host a variety of mobile genetic elements including transposons, plasmids and viruses. Theoretical considerations and computer simulations suggest that emergence of genetic parasites is intrinsic to evolving replicator systems.\n\nResultsUsing methods of bifurcation analysis, we investigated the stability of simple models of replicator-parasite coevolution in a well-mixed environment. It is shown that the simplest imaginable system of this type, one in which the parasite evolves during the replication of the host genome through a minimal mutation that renders the genome of the emerging parasite incapable of producing the replicase but able to recognize and recruit it for its own replication, is unstable. In this model, there are only either trivial or \"semi-trivial\", parasite-free equilibria: an inefficient parasite is outcompeted by the host and dies off whereas an efficient one pushes the host out of existence, which leads to the collapse of the entire system. We show that stable host-parasite coevolution (a non-trivial equilibrium) is possible in a modified model where the parasite is qualitatively distinct from the host replicator in that the replication of the parasite depends solely on the availability of the host but not on the carrying capacity of the environment.\n\nConclusionsWe analytically determine the conditions for stable host-parasite coevolution in simple mathematical models and find that a parasite that initially evolves from the host through the loss of the ability to replicate autonomously must be substantially derived for a stable host-parasite coevolution regime to be established.

evolutionary biology↗

bioRxiv2018

On the feasibility of saltational evolution

One of the key tenets of Darwins theory that was inherited by the Modern Synthesis of evolutionary biology is gradualism, that is, the notion that evolution proceeds gradually, via accumulation of \"infinitesimally small\" heritable changes 1,2. However, some of the most consequential evolutionary changes, such as, for example, the emergence of major taxa, seem to occur abruptly rather than gradually, as captured in the concepts of punctuated equilibrium 3,4 and evolutionary transitions 5,6. We examine a mathematical model of an evolutionary process on a rugged fitness landscape 7,8 and obtain analytic solutions for the probability of multi-mutational leaps, that is, several mutations occurring simultaneously, within a single generation in one genome, and being fixed all together in the evolving population. The results indicate that, for typical, empirically observed combinations of the parameters of the evolutionary process, namely, effective population size, mutation rate, and distribution of selection coefficients of mutations, the probability of a multi-mutational leap is low, and accordingly, their contribution to the evolutionary process is minor at best. However, such leaps could become an important factor of evolution in situations of population bottlenecks and elevated mutation rates, such as stress-induced mutagenesis in microbes or tumor progression, as well as major evolutionary transitions and evolution of primordial replicators.

evolutionary biology↗

bioRxiv2018

Genome plasticity, a key factor of evolution in prokaryotes

In prokaryotic genomes, the number of genes that belong to distinct functional classes shows apparent universal scaling with the total number of genes [1-5] (Fig. 1). This scaling can be approximated with a power law, where the scaling power can be sublinear, near-linear or super-linear. Scaling laws are robust under various statistical tests [4], across different databases and for different gene classifications [1-5]. Several models aimed at explaining the observed scaling laws have been proposed, primarily, based on the specifics of the respective biological functions [1, 5-8]. However, a coherent theory to explain the emergence of scaling within the framework of population genetics is lacking. We employ a simple mathematical model for prokaryotic genome evolution [9] which, together with the analysis of 34 clusters of closely related microbial genomes [10], allows us to identify the underlying forces that dictate genome content evolution. In addition to the scaling of the number of genes in different functional classes, we explore gene contents divergence to characterize the evolutionary processes acting upon genomes [11]. We find that evolution of the gene content is dominated by two factors that are specific to a functional class, namely, selection landscape and genome plasticity. Selection landscape quantifies the fitness cost that is associated with deletion of a gene in a given functional class or the advantage of successful incorporation of an additional gene. Genome plasticity, that can be considered a measure of evolvability, reflects both the availability of the genes of a given functional class in the external gene pool that is accessible to the evolving microbial population, and the ability of microbial genomes to accommodate these genes. The selection landscape determines the gene loss rate, and genome plasticity is the principal determinant of the gene gain rate.\n\nO_FIG O_LINKSMALLFIG WIDTH=197 HEIGHT=200 SRC=\"FIGDIR/small/357400_fig1.gif\" ALT=\"Figure 1\">\nView larger version (39K):\norg.highwire.dtl.DTLVardef@6df3e2org.highwire.dtl.DTLVardef@a69e8dorg.highwire.dtl.DTLVardef@f36a80org.highwire.dtl.DTLVardef@d519c9_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFigure 1.C_FLOATNO Scaling laws for all functional classes of the COGs. The number of genes in a given COG category is plotted against the total number of genes. Each point represents one genome from the analyzed set of 1490 genomes. The scaling is fitted to a power law which is indicated by a solid red line. The fitted scaling exponent is indicated in parentheses.\n\nC_FIG

microbiology↗