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bioRxiv2016

Host-selected mutations converging on a global regulator drive an adaptive leap by bacteria to symbiosis

Even though eukaryote health relies on beneficial symbionts, host defenses targeting pathogens create substantial obstacles for the establishment of these essential partnerships. To reveal mechanisms of symbiotic adaptation, we experimentally evolved ecologically distinct bioluminescent Vibrio fischeri through Euprymna scolopes squid light organs. Serial passaging of V. fischeri populations through squid hosts produced eight distinct mutations in the binK sensor kinase gene that conferred an exceptional selective advantage demonstrated through both empirical and theoretical analysis. Squid-adaptive binK alleles promoted colonization and immune evasion behavior which was mediated by symbiotic polysaccharide (Syp). binK variation also produced metabolic convergence with native symbionts, and altered quorum sensing and luminescence. Preexisting coordination of symbiosis traits facilitated an efficient solution where altered function of a regulator was the key to unlock multiple colonization barriers. These results identify a genetic basis for microbial adaptability and underscore the importance of hosts as selective agents that shape emergent symbiont populations.\n\nImpact statementSquid selection on non-native Vibrio fischeri drove rapid adaptation through convergent mutations of large effect, unmasking preexisting coordinate regulation of symbiosis.\n\nMajor subject areas, keywords, and research organism(s)\n\nMajor subject area: Genomics and evolutionary biology

Evolutionary Biology↗

bioRxiv2016

Stochastic Assembly Produces Heterogeneous Communities in the C. elegans Intestine

Author SummaryHost-associated bacterial communities vary extensively between individuals, but it can be very difficult to determine the sources of this variation. In this manuscript, we demonstrate experimentally how randomness in colonization can result in large differences in the composition of host-associated bacterial communities, using the nematode worm C. elegans as a tractable host model. Here, the amount of variation between individual communities is a function of two rates relevant to how bacteria colonize the host intestine, the colonization rate and the birth rate. We can therefore control the degree of variation between communities by controlling the colonization rate, using the amount of bacteria presented to the worms to control the rate at which migrants enter the intestine. When worms are fed with two neutrally-competing fluorescently labeled bacterial strains at low colonization rates, we are able to produce noise-induced bistability in this system, where each community is dominated by bacteria of only one color. These results demonstrate the potential importance of noise as a driver of variation between communities and highlight the utility of the simple model organism C. elegans for studying questions relevant to host-associated microbial communities.\n\nAbstractHost-associated bacterial communities vary extensively between individuals, but it can be very difficult to determine the sources of this heterogeneity. Here we demonstrate that stochastic bacterial community assembly in the C. elegans intestine is sufficient to produce strong inter-worm heterogeneity in community composition. When worms are fed with two neutrally-competing fluorescently labeled bacterial strains, we observe stochastically-driven bimodality in community composition, where approximately half of the worms are dominated by each bacterial strain. A simple model incorporating stochastic colonization suggests that heterogeneity between worms is driven by the low rate at which bacteria successfully establish new intestinal colonies. We can increase this rate experimentally by feeding worms at high bacterial density; in these conditions the bimodality disappears. These results demonstrate that demographic noise is a potentially important driver of diversity in bacterial community formation and suggest a role for C. elegans as a model system for ecology of host-associated communities.

Microbiology↗

bioRxiv2016

Recombination-driven genome evolution and stability of bacterial species

While bacteria divide clonally, horizontal gene transfer followed by homologous recombination is now recognized as an important and sometimes even dominant contributor to their evolution. However, the details of how the competition between clonal inheritance and recombination shapes genome diversity, population structure, and species stability remains poorly understood. Using a computational model, we find two principal regimes in bacterial evolution and identify two composite parameters that dictate the evolutionary fate of bacterial species. In the divergent regime, characterized by either a low recombination frequency or strict barriers to recombination, cohesion due to recombination is not sufficient to overcome the mutational drift. As a consequence, the divergence between any pair of genomes in the population steadily increases in the course of their evolution. The species as a whole lacks genetic coherence with sexually isolated clonal sub-populations continuously formed and dissolved. In contrast, in the metastable regime, characterized by a high recombination frequency combined with low barriers to recombination, genomes continuously recombine with the rest of the population. The population remains genetically cohesive and stable over time. The transition between these two regimes can be affected by relatively small changes in evolutionary parameters. Using the Multi Locus Sequence Typing (MLST) data we classify a number of well-studied bacterial species to be either the divergent or the metastable type. Generalizations of our framework to include fitness and selection, ecologically structured populations, and horizontal gene transfer of non-homologous regions are discussed.

Evolutionary Biology↗

bioRxiv2016

The Modular Adaptive Ribosome

The ribosome is an ancient machine, performing the same function across organisms. Although functionally unitary, recent experiments suggest specialized roles for some ribosomal proteins. Our central thesis is that ribosomal proteins function in a modular fashion to decode genetic information in a context dependent manner. We show through large data analyses that although many ribosomal proteins are essential with consistent effect on growth in different conditions in yeast and similar expression across cell and tissue types in mice and humans, some ribosomal proteins are used in an environment specific manner. The latter set of variable ribosomal proteins further function in a coordinated manner forming modules, which are adapted to different environmental cues in different organisms. We show that these environment specific modules of ribosomal proteins in yeast have differential genetic interactions with other pathways and their 5UTRs show differential signatures of selection in yeast strains, presumably to facilitate adaptation. Similarly, we show that in higher metazoans such as mice and humans, different modules of ribosomal proteins are expressed in different cell types and tissues. A clear example is nervous tissue that uses a ribosomal protein module distinct from the rest of the tissues in both mice and humans. Our results suggest a novel stratification of ribosomal proteins that could have played a role in adaptation, presumably to optimize translation for adaptation to diverse ecological niches and tissue microenvironments.

Systems Biology↗

bioRxiv2016

Population structure reduces the benefits from partner choice in mutualism

Mutualisms are key drivers of evolutionary and ecological processes. Understanding how different species can evolve to interact in mutually beneficial ways is an important goal of evolutionary theory, especially when the benefits require costly investments by the partners. For such costly investments to evolve, some sort of fitness feedback mechanism must exist that more than recoups the direct costs. Several such feedback mechanisms have been explored both theoretically and empirically, yet we know relatively little how they might act together, as they probably do in nature. In this paper, I model the joint action of three of the main mechanisms that can maintain symbiotic cooperation: partner choice by hosts, population structure amongst symbionts, and undirected rewards from hosts to symbionts. My results show that population structure reduces the benefit from partner choice to hosts. It may help or hinder beneficial symbionts and create positive or negative frequency dependence depending on the nature of host rewards to the symbiont. Strong population structure also makes it less likely that host choosiness and symbiont cooperation will be jointly maintained in a population. The intuition behind my results is that all else being equal, population structure reduces local variation available to the host to choose from. Thus, population structure is not always beneficial for the evolution of cooperation between species. My results also underscore the need to do full analyses of multiple mechanisms of social evolution to uncover their interactions to uncover the interactions between them.

Evolutionary Biology↗

bioRxiv2016

Rapid evolution of distinct Helicobacter pylori subpopulations in the Americas

For the last 500 years, the Americas have been a melting pot both for genetically diverse humans and for the pathogenic and commensal organisms associated with them. One such organism is the stomach dwelling bacterium Helicobacter pylori, which is highly prevalent in Latin America where it is a major current public health challenge because of its strong association with gastric cancer. By analyzing the genome sequence of H. pylori isolated in North, Central and South America, we found evidence for admixture between H. pylori of European and African origin throughout the Americas, without substantial input from pre-Columbian (hspAmerind) bacteria. In the US, strains of African and European origin have remained genetically distinct, while in Colombia and Nicaragua, bottlenecks and rampant genetic exchange amongst isolates have led to the formation of national gene pools. We found four outer membrane proteins with atypical levels of Asian ancestry in American strains, including the adhesion factor AlpB, suggesting a role for the ethnic makeup of hosts in the colonization of incoming strains. Our results show that new H. pylori subpopulations can rapidly arise, spread and adapt during times of demographic flux, and suggest that differences in transmission ecology between high and low prevalence areas may substantially affect the composition of bacterial populations.\n\nAuthor SummaryHelicobacter pylori is one of the best studied examples of an intimate association between bacteria and humans, due to its ability to colonize the stomach for decades and to transmit from generation to generation. A number of studies have sought to link diversity in H. pylori to human migrations but there are some discordant signals such as an \"out of Africa\" dispersal within the last few thousand years that has left a much stronger signal in bacterial genomes than in human ones. In order to understand how such discrepancies arise, we have investigated the evolution of H. pylori during the recent colonization of the Americas. We find that bacterial populations evolve quickly and can spread rapidly to people of different ethnicities. Distinct new bacterial subpopulations have formed in Colombia from a European source and in Nicaragua and the US from African sources. Genetic exchange between bacterial populations is rampant within Central and South America but is uncommon within North America, which may reflect differences in prevalence. Our results also suggest that adaptation of bacteria to particular human ethnic groups may be confined to a handful of genes involved in interaction with the immune system.

Genetics↗

bioRxiv2016

Genome-scale rates of evolutionary change in bacteria

Estimating the rates at which bacterial genomes evolve is critical to understanding major evolutionary and ecological processes such as disease emergence, long-term host-pathogen associations, and short-term transmission patterns. The surge in bacterial genomic data sets provides a new opportunity to estimate these rates and reveal the factors that shape bacterial evolutionary dynamics. For many organisms estimates of evolutionary rate display an inverse association with the time-scale over which the data are sampled. However, this relationship remains unexplored in bacteria due to the difficulty in estimating genome-wide evolutionary rates, which are impacted by the extent of temporal structure in the data and the prevalence of recombination. We collected 36 whole genome sequence data sets from 16 species of bacterial pathogens to systematically estimate and compare their evolutionary rates and assess the extent of temporal structure in the absence of recombination. The majority (28/36) of data sets possessed sufficient clock-like structure to robustly estimate evolutionary rates. However, in some species reliable estimates were not possible even with \"ancient DNA\" data sampled over many centuries, suggesting that they evolve very slowly or that they display extensive rate variation among lineages. The robustly estimated evolutionary rates spanned several orders of magnitude, from 10-6 to 10-8 nucleotide substitutions site-1 year-1. This variation was largely attributable to sampling time, which was strongly negatively associated with estimated evolutionary rates, with this relationship best described by an exponential decay curve. To avoid potential estimation biases such time-dependency should be considered when inferring evolutionary time-scales in bacteria.

Evolutionary Biology↗

bioRxiv2016

Widespread Historical Contingency in Influenza Viruses

In systems biology and genomics, epistasis characterizes the impact that a substitution at a particular location in a genome can have on a substitution at another location. This phenomenon is often implicated in the evolution of drug resistance or to explain why particular disease-causing mutations do not have the same outcome in all individuals. Hence, uncovering these mutations and their locations in a genome is a central question in biology. However, epistasis is notoriously difficult to uncover, especially in fast-evolving organisms. Here, we present a novel statistical approach that replies on a model developed in ecology and that we adapt to analyze genetic data in fast-evolving systems such as the influenza A virus. We validate the approach using a two-pronged strategy: extensive simulations demonstrate a low-to-moderate sensitivity with excellent specificity and precision, while analyses of experimentally-validated data recover known interactions, including in a eukaryotic system. We further evaluate the ability of our approach to detect correlated evolution during antigenic shifts or at the emergence of drug resistance. We show that in all cases, correlated evolution is prevalent in influenza A viruses, involving many pairs of sites linked together in chains, a hallmark of historical contingency. Strikingly, interacting sites are separated by large physical distances, which entails either long-range conformational changes or functional tradeoffs, for which we find support with the emergence of drug resistance. Our work paves a new way for the unbiased detection of epistasis in a wide range of organisms by performing whole-genome scans.

Evolutionary Biology↗

bioRxiv2016

Inferring physiological energetics of loggerhead turtle (Caretta caretta) from existing data using a general metabolic theory

Loggerhead turtle is an endangered sea turtle species with a migratory lifestyle and worldwide distribution, experiencing markedly different habitats throughout its lifetime. Environmental conditions, especially food availability and temperature, constrain the acquisition and the use of available energy, thus affecting physiological processes such as growth, maturation, and reproduction. These physiological processes at the population level determine survival, fecundity, and ultimately the population growth rate--a key indicator of the success of conservation efforts. As a first step towards the comprehensive understanding of how environment shapes the physiology and the life cycle of a loggerhead turtle, we constructed a full life cycle model based on the principles of energy acquisition and utilization embedded in the Dynamic Energy Budget (DEB) theory. We adapted the standard DEB model using data from published and unpublished sources to obtain parameter estimates and model predictions that could be compared with data. The outcome was a successful mathematical description of ontogeny and life history traits of the loggerhead turtle. Some deviations between the model and the data existed (such as an earlier age at sexual maturity and faster growth of the post-hatchlings), yet probable causes for these deviations were found informative and discussed in great detail. Physiological traits such as the capacity to withstand starvation, trade-offs between reproduction and growth, and changes in the energy budget throughout the ontogeny were inferred from the model. The results offer new insights into physiology and ecology of loggerhead turtle with the potential to lead to novel approaches in conservation of this endangered species.

Zoology↗

bioRxiv2016

Application of the stochastic labeling methods with random-sequence barcodes for simultaneous quantification and sequencing of environmental 16S rRNA genes

Next-generation sequencing (NGS) is a powerful tool for analyzing environmental DNA and provides the comprehensive molecular view of microbial communities. For obtaining the copy number of particular sequences in the NGS library, however, additional quantitative analysis as quantitative PCR (qPCR) or digital PCR (dPCR) is required. Furthermore, number of sequences in a sequence library does not always reflect the original copy number of a target gene because of biases caused by PCR amplification, making it difficult to convert the proportion of particular sequences in the NGS library to the copy number using the mass of input DNA. To address this issue, we applied stochastic labeling approach with random-tag sequences and developed a NGS-based quantification protocol, which enables simultaneous sequencing and quantification of the targeted DNA. This quantitative sequencing (qSeq) is initiated from single-primer extension (SPE) using a primer with random tag adjacent to the 5 end of target-specific sequence. During SPE, each DNA molecule is stochastically labeled with the random tag. Subsequently, first-round PCR is conducted, specifically targeting the SPE product, followed by second-round PCR to index for NGS. The number of random tags is only determined during the SPE step and is therefore not affected by the two rounds of PCR that may introduce amplification biases. In the case of 16S rRNA genes, after NGS sequencing and taxonomic classification, the absolute number of target phylotypes 16S rRNA gene can be estimated by Poisson statistics by counting random tags incorporated at the end of sequence. To test the feasibility of this approach, the 16S rRNA gene of Sulfolobus tokodaii was subjected to qSeq, which resulted in accurate quantification of 5.0 x 103 to 5.0 x 104 copies of the 16S rRNA gene. Furthermore, qSeq was applied to mock microbial communities and environmental samples, and the results were comparable to those obtained using digital PCR and relative abundance based on a standard sequence library. We demonstrated that the qSeq protocol proposed here is advantageous for providing less-biased absolute copy numbers of each target DNA with NGS sequencing at one time. By this new experiment scheme in microbial ecology, microbial community compositions can be explored in more quantitative manner, thus expanding our knowledge of microbial ecosystems in natural environments.

Microbiology↗

bioRxiv2016

Major host transitions are modulated through transcriptome-wide reprograming events in Schistocephalus solidus, a threespine stickleback parasite

Parasites with complex life cycles have developed numerous phenotypic strategies, closely associated with developmental events, to enable the exploitation of different ecological niches and facilitate transmission between hosts. How these environmental shifts are regulated from a metabolic and physiological standpoint, however, still remain to be fully elucidated. We examined the transcriptomic response of Schistocephalus solidus, a trophically-transmitted parasite with a complex life cycle, over the course of its development in an intermediate host, the threespine stickleback, and the final avian host. Results from our differential gene expression analysis show major reprogramming events among developmental stages. The final host stage is characterized by a strong activation of reproductive pathways and redox homeostasis. The attainment of infectivity in the fish intermediate host - which precedes sexual maturation in the final host and is associated with host behaviour changes - is marked by transcription of genes involved in neural pathways and sensory perception. Our results suggest that un-annotated and S. solidus-specific genes could play a determinant role in host-parasite molecular interactions required to complete the parasites life cycle. Our results permit future comparative analyses to help disentangle species-specific patterns of infection from conserved mechanisms, ultimately leading to a better understanding of the molecular control and evolution of complex life cycles.

Genomics↗

bioRxiv2016

Selection on heterozygosity drives adaptation in intra- and interspecific hybrids

Hybridization is often considered maladaptive, but sometimes hybrids can invade new ecological niches and adapt to novel or stressful environments better than their parents. However, the genomic changes that occur following hybridization and facilitate genome resolution and/or adaptation are not well understood. Here, we address these questions using experimental evolution of de novo interspecific hybrid yeast Saccharomyces cerevisiae x Saccharomyces uvarum and their parentals. We evolved these strains in nutrient limited conditions for hundreds of generations and sequenced the resulting cultures to identify genomic changes. Analysis of 16 hybrid clones and 16 parental clones identified numerous point mutations, copy number changes, and loss of heterozygosity events, including a number of nuclear-mitochondrial mutations and species biased amplification of nutrient transporters. We focused on a particularly interesting example, in which we saw repeated loss of heterozygosity at the high affinity phosphate transporter gene PHO84 in both intra- and interspecific hybrids. Using allele replacement methods, we tested the fitness of different alleles in hybrid and S. cerevisiae strain backgrounds and found that the loss of heterozygosity is indeed the result of selection on one allele over the other in both S. cerevisiae and the hybrids. This illuminates an example where hybrid genome resolution is driven by positive selection on existing heterozygosity, and generally demonstrates that outcrossing need not be frequent to have long lasting impacts on adaptation.

Evolutionary Biology↗

bioRxiv2016

Fossils matter: improved estimates of divergence times in Pinus reveal older diversification

BackgroundThe taxonomy of the genus Pinus is widely accepted and a well-resolved phylogeny based on entire plastome sequences exists. However, there is a large discrepancy in estimated divergence times of major pine clades among existing studies mainly due to differences in fossil placement and dating methods used. We currently lack a dated molecular pine phylogeny that makes full usage of the rich fossil record in pines. This study is the first to estimate the divergence dates of pines based on a large number of fossils (21) evenly distributed across all major clades in combination with applying the most novel dating method.\n\nResultsWe present a range of molecular phylogenetic trees of Pinus generated within a Bayesian framework using both the novel fossilized birth-death and the traditional node dating method with different fossil sets. We find the origin of pines likely to be up to 30 Myr older (Early Cretaceous) than inferred in most previous studies (Late Cretaceous) and propose generally older divergence times for major clades within Pinus than previously thought. Our age estimates vary significantly between the different dating approaches but the results generally agree on older divergence times. We present a revised list of 21 fossils that are suitable to use in dating or comparative analyses of pines.\n\nConclusionsAn accurate timescale for the divergence times in pines is essential if we are to link diversification processes and functional adaptation of this genus to geological events or to changing climates. Next to older divergence times in Pinus, our results indicate that node age estimates in pines depend on dating approaches and fossil sets used due to different inherent characteristics of dating approaches. Our set of dated phylogenetic trees of pines presented herein provide the basis to account for uncertainties in age estimations when applying comparative phylogenetic methods, which will improve our understanding of the evolutionary and ecological history in pines.

Evolutionary Biology↗

bioRxiv2016

Assessing data quality in citizen science - preprint

Ecological and environmental citizen science projects have enormous potential to advance science, influence policy, and guide resource management by producing datasets that are otherwise infeasible to generate. This potential can only be realized, though, if the datasets are of high quality. While scientists are often skeptical of the ability of unpaid volunteers to produce accurate datasets, a growing body of publications clearly shows that diverse types of citizen science projects can produce data with accuracy equal to or surpassing that of professionals. Successful projects rely on a suite of methods to boost data accuracy and account for bias, including iterative project development, volunteer training and testing, expert validation, replication across volunteers, and statistical modeling of systematic error. Each citizen science dataset should therefore be judged individually, according to project design and application, rather than assumed to be substandard simply because volunteers generated it.

Preprint↗

bioRxiv2016

The Impact of Migratory Flyways on the Spread of Avian Influenza Virus in North America

Wild birds are the major reservoir hosts for influenza A viruses (AIVs) and have been implicated in the emergence of pandemic events in livestock and human populations. Understanding how AIVs spread within and across continents is therefore critical to the development of successful strategies to manage and reduce the impact of influenza outbreaks. In North America many bird species undergo seasonal migratory movements along a North-South axis, thereby fostering opportunities for viruses to spread over long distances. However, the role played by such avian flyways in shaping the genetic structure of AIV populations has proven controversial. To assess the relative contribution of bird migration along flyways to the genetic structure of AIV we performed a large-scale phylogeographic study of viruses sampled in the USA and Canada, involving the analysis of 3805 to 4505 sequences from 36 to 38 geographic localities depending on the gene data set. To assist this we developed a maximum likelihood-based genetic algorithm to explore a wide range of complex spatial models, thereby depicting a more complete picture of the migration network than previous studies. Based on phylogenies estimated from nucleotide data sets, our results show that AIV migration rates within flyways are significantly higher than those between flyways, indicating that the migratory patterns of birds play a key role in pathogen dispersal. These findings provide valuable insights into the evolution, maintenance and transmission of AIVs, in turn allowing the development of improved programs for surveillance and risk assessment.\n\nSignificance StatementAvian influenza viruses infect a wide variety of wild bird species and represent a potential disease threat to the poultry industry and hence to human and livestock populations. However, the ecological factors that drive the geographic spread and evolution of these viruses are both poorly understood and controversial at the continental scale, particularly the role played by migratory flyways in shaping patterns of virus dispersal. Using a novel phylogeographic analysis of large genomic data sets we show migration flyways act as important transmission barriers to the spread of avian influenza viruses in North America. Hence, these results indicate that the spread of avian influenza virus in wild birds in North America has an element of predictability.

Evolutionary Biology↗

bioRxiv2016

Using RNA-seq for genomic scaffold placement, correcting assemblies, and genetic map creation in a common Brassica rapa mapping population.

Brassica rapa is a model species for agronomic, ecological, evolutionary and translational studies. Here we describe high-density SNP discovery and genetic map construction for a Brassica rapa recombinant inbred line (RIL) population derived from field collected RNA-seq data. This high-density genotype data enables the detection and correction of putative genome mis-assemblies and accurate assignment of scaffold sequences to their likely genomic locations. These assembly improvements represent 7.1-8.0% of the annotated Brassica rapa genome. We demonstrate how using this new resource leads to a significant improvement for QTL analysis over the current low-density genetic map. Improvements are achieved by the increased mapping resolution and by having known genomic coordinates to anchor the markers for candidate gene discovery. These new molecular resources and improvements in the genome annotation will benefit the Brassicaceae genomics community and may help guide other communities in finetuning genome annotations.

Genomics↗

bioRxiv2016

dbOTU3: A new implementation of distribution-based OTU calling

1Distribution-based operational taxonomic unit-calling (dbOTU) improves on other approaches by incorporating information about the input sequences distribution across samples. Previous implementations of dbOTU presented challenges for users. Here we introduce and evaluate a new implementation of dbOTU that is faster and more user-friendly. We show that this new implementation has theoretical and practical improvements over previous implementations of dbOTU, making the algorithm more accessible to microbial ecology and biomedical researchers.

Bioinformatics↗

bioRxiv2016

Co-operation, competition and crowding: a discrete framework linking Allee kinetics, nonlinear diffusion, shocks and sharp-fronted travelling waves

AO_SCPLOWBSTRACTC_SCPLOWInvasion processes are ubiquitous throughout cell biology and ecology. During invasion, individuals can become isolated from the bulk population and behave differently. We present a discrete, exclusion-based description of the birth, death and movement of individuals. The model distinguishes between individuals that are part of, or are isolated from, the bulk population by imposing different rates of birth, death and movement. This enables the simulation of various co-operative or competitive mechanisms, where there is either a positive or negative benefit associated with being part of the bulk population, respectively. The mean-field approximation of the discrete process gives rise to 22 different classes of partial differential equation, which can include Allee kinetics and nonlinear diffusion. Here we examine the ability of each class of partial differential equation to support travelling wave solutions and interpret the long time behaviour in terms of the individual-level parameters. For the first time we show that the strong Allee effect and nonlinear diffusion can result in shock-fronted travelling waves. We also demonstrate how differences in group and individual motility rates can influence the persistence of a population and provide conditions for the successful invasion of a population.

Biophysics↗