Soil aggregates as massively concurrent evolutionary incubators

Soil aggregation, a key component of soil structure, has mostly been examined from the perspective of soil management and the mediation of ecosystem processes such as soil carbon storage. However, soil aggregation is also a major factor to consider in terms of the fine-scale organization of the soil microbiome. For example, the physico-chemical conditions inside of aggregates usually differ from the conditions prevalent in the bulk soil and aggregates therefore increase the spatial heterogeneity of the soil. In addition, aggregates can provide a refuge for microbes against predation since their interior is not accessible to many predators. Soil aggregates are thus clearly important for microbial community ecology in soils (for example, Vos et al., 2013; Rillig et al., 2016) and for microbially driven biogeochemistry, and soil microbial ecologists are increasingly appreciating these aspects of soil aggregation. Soil aggregates have, however, so far been neglected when it comes to evolutionary considerations (Crawford et al., 2005) and we here propose that the process of soil aggregation should be considered as an important driver of evolution in the soil microbial community

Structure and Evolution of Streptomyces Interaction Networks in Soil and In Silico

Soil grains harbor an astonishing diversity of Streptomyces strains producing diverse secondary metabolites. However, it is not understood how this genotypic and chemical diversity is ecologically maintained. While secondary metabolites are known to mediate signaling and warfare among strains, no systematic measurement of the resulting interaction networks has been available. We developed a high-throughput platform to measure all pairwise interactions among 64 Streptomyces strains isolated from several individual grains of soil. We acquired more than 10,000 time-lapse movies of colony development of each isolate on media containing compounds produced by each of the other isolates. We observed a rich set of such sender-receiver interactions, including inhibition and promotion of growth and aerial mycelium formation. The probability that two random isolates interact is balanced; it is neither close to zero nor one. The interactions are not random: the distribution of the number of interactions per sender is bimodal and there is enrichment for reciprocity—if strain A inhibits or promotes B, it is likely that B also inhibits or promotes A. Such reciprocity is further enriched in strains derived from the same soil grain, suggesting that it may be a property of coexisting communities. Interactions appear to evolve rapidly: isolates with identical 16S rRNA sequences can have very different interaction patterns. A simple eco-evolutionary model of bacteria interacting through antibiotic production shows how fast evolution of production and resistance can lead to the observed statistical properties of the network. In the model, communities are evolutionarily unstable—they are constantly being invaded by strains with new sets of interactions. This combination of experimental and theoretical observations suggests that diverse Streptomyces communities do not represent a stable ecological state but an intrinsically dynamic eco-evolutionary phenomenon

Statistical Mechanics of Horizontal Gene Transfer in Evolutionary Ecology

The biological world, especially its majority microbial component, is strongly interacting and may be dominated by collective effects. In this review, we provide a brief introduction for statistical physicists of the way in which living cells communicate genetically through transferred genes, as well as the ways in which they can reorganize their genomes in response to environmental pressure. We discuss how genome evolution can be thought of as related to the physical phenomenon of annealing, and describe the sense in which genomes can be said to exhibit an analogue of information entropy. As a direct application of these ideas, we analyze the variation with ocean depth of transposons in marine microbial genomes, predicting trends that are consistent with recent observations using metagenomic surveys.Comment: Accepted by Journal of Statistical Physic

Cultural Evolution as Distributed Computation

The speed and transformative power of human cultural evolution is evident from the change it has wrought on our planet. This chapter proposes a human computation program aimed at (1) distinguishing algorithmic from non-algorithmic components of cultural evolution, (2) computationally modeling the algorithmic components, and amassing human solutions to the non-algorithmic (generally, creative) components, and (3) combining them to develop human-machine hybrids with previously unforeseen computational power that can be used to solve real problems. Drawing on recent insights into the origins of evolutionary processes from biology and complexity theory, human minds are modeled as self-organizing, interacting, autopoietic networks that evolve through a Lamarckian (non-Darwinian) process of communal exchange. Existing computational models as well as directions for future research are discussed.Comment: 13 pages Gabora, L. (2013). Cultural evolution as distributed human computation. In P. Michelucci (Ed.) Handbook of Human Computation. Berlin: Springe

Effect of Correlated tRNA Abundances on Translation Errors and Evolution of Codon Usage Bias

Despite the fact that tRNA abundances are thought to play a major role in determining translation error rates, their distribution across the genetic code and the resulting implications have received little attention. In general, studies of codon usage bias (CUB) assume that codons with higher tRNA abundance have lower missense error rates. Using a model of protein translation based on tRNA competition and intra-ribosomal kinetics, we show that this assumption can be violated when tRNA abundances are positively correlated across the genetic code. Examining the distribution of tRNA abundances across 73 bacterial genomes from 20 different genera, we find a consistent positive correlation between tRNA abundances across the genetic code. This work challenges one of the fundamental assumptions made in over 30 years of research on CUB that codons with higher tRNA abundances have lower missense error rates and that missense errors are the primary selective force responsible for CUB

Ancient horizontal gene transfer and the last common ancestors

Background The genomic history of prokaryotic organismal lineages is marked by extensive horizontal gene transfer (HGT) between groups of organisms at all taxonomic levels. These HGT events have played an essential role in the origin and distribution of biological innovations. Analyses of ancient gene families show that HGT existed in the distant past, even at the time of the organismal last universal common ancestor (LUCA). Most gene transfers originated in lineages that have since gone extinct. Therefore, one cannot assume that the last common ancestors of each gene were all present in the same cell representing the cellular ancestor of all extant life. Results Organisms existing as part of a diverse ecosystem at the time of LUCA likely shared genetic material between lineages. If these other lineages persisted for some time, HGT with the descendants of LUCA could have continued into the bacterial and archaeal lineages. Phylogenetic analyses of aminoacyl-tRNA synthetase protein families support the hypothesis that the molecular common ancestors of the most ancient gene families did not all coincide in space and time. This is most apparent in the evolutionary histories of seryl-tRNA synthetase and threonyl-tRNA synthetase protein families, each containing highly divergent “rare” forms, as well as the sparse phylogenetic distributions of pyrrolysyl-tRNA synthetase, and the bacterial heterodimeric form of glycyl-tRNA synthetase. These topologies and phyletic distributions are consistent with horizontal transfers from ancient, likely extinct branches of the tree of life. Conclusions Of all the organisms that may have existed at the time of LUCA, by definition only one lineage is survived by known progeny; however, this lineage retains a genomic record of heterogeneous genetic origins. The evolutionary histories of aminoacyl-tRNA synthetases (aaRS) are especially informative in detecting this signal, as they perform primordial biological functions, have undergone several ancient HGT events, and contain many sites with low substitution rates allowing deep phylogenetic reconstruction. We conclude that some aaRS families contain groups that diverge before LUCA. We propose that these ancient gene variants be described by the term “hypnologs”, reflecting their ancient, reticulate origin from a time in life history that has been all but erased”.National Science Foundation (U.S.) (Grant DEB 0830024)Exobiology Program (U.S.) (Grant NNX10AR85G)United States. National Aeronautics and Space Administration (Postdoctoral Program

Dynamics of Genome Rearrangement in Bacterial Populations

Genome structure variation has profound impacts on phenotype in organisms ranging from microbes to humans, yet little is known about how natural selection acts on genome arrangement. Pathogenic bacteria such as Yersinia pestis, which causes bubonic and pneumonic plague, often exhibit a high degree of genomic rearrangement. The recent availability of several Yersinia genomes offers an unprecedented opportunity to study the evolution of genome structure and arrangement. We introduce a set of statistical methods to study patterns of rearrangement in circular chromosomes and apply them to the Yersinia. We constructed a multiple alignment of eight Yersinia genomes using Mauve software to identify 78 conserved segments that are internally free from genome rearrangement. Based on the alignment, we applied Bayesian statistical methods to infer the phylogenetic inversion history of Yersinia. The sampling of genome arrangement reconstructions contains seven parsimonious tree topologies, each having different histories of 79 inversions. Topologies with a greater number of inversions also exist, but were sampled less frequently. The inversion phylogenies agree with results suggested by SNP patterns. We then analyzed reconstructed inversion histories to identify patterns of rearrangement. We confirm an over-representation of “symmetric inversions”—inversions with endpoints that are equally distant from the origin of chromosomal replication. Ancestral genome arrangements demonstrate moderate preference for replichore balance in Yersinia. We found that all inversions are shorter than expected under a neutral model, whereas inversions acting within a single replichore are much shorter than expected. We also found evidence for a canonical configuration of the origin and terminus of replication. Finally, breakpoint reuse analysis reveals that inversions with endpoints proximal to the origin of DNA replication are nearly three times more frequent. Our findings represent the first characterization of genome arrangement evolution in a bacterial population evolving outside laboratory conditions. Insight into the process of genomic rearrangement may further the understanding of pathogen population dynamics and selection on the architecture of circular bacterial chromosomes

Patterns of Gene Flow Define Species of Thermophilic Archaea

A genomic view of speciation in Archaea shows higher rates of gene flow within coexisting microbial species than between them

A three-way comparative genomic analysis of Mannheimia haemolytica isolates

<p>Abstract</p> <p>Background</p> <p><it>Mannhemia haemolytica </it>is a Gram-negative bacterium and the principal etiological agent associated with bovine respiratory disease complex. They transform from a benign commensal to a deadly pathogen, during stress such as viral infection and transportation to feedlots and cause acute pleuropneumonia commonly known as shipping fever. The U.S beef industry alone loses more than one billion dollars annually due to shipping fever. Despite its enormous economic importance there are no specific and accurate genetic markers, which will aid in understanding the pathogenesis and epidemiology of <it>M. haemolytica </it>at molecular level and assist in devising an effective control strategy.</p> <p>Description</p> <p>During our comparative genomic sequence analysis of three <it>Mannheimia haemolytica </it>isolates, we identified a number of genes that are unique to each strain. These genes are "high value targets" for future studies that attempt to correlate the variable gene pool with phenotype. We also identified a number of high confidence single nucleotide polymorphisms (hcSNPs) spread throughout the genome and focused on non-synonymous SNPs in known virulence genes. These SNPs will be used to design new hcSNP arrays to study variation across strains, and will potentially aid in understanding gene regulation and the mode of action of various virulence factors.</p> <p>Conclusions</p> <p>During our analysis we identified previously unknown possible type III secretion effector proteins, clustered regularly interspaced short palindromic repeats (CRISPR) and CRISPR-associated sequences (Cas). The presence of CRISPR regions is indicative of likely co-evolution with an associated phage. If proven functional, the presence of a type III secretion system in <it>M. haemolytica </it>will help us re-evaluate our approach to study host-pathogen interactions. We also identified various adhesins containing immuno-dominant domains, which may interfere with host-innate immunity and which could potentially serve as effective vaccine candidates.</p