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Search indexed bioRxiv preprints in genomics, neuroscience, cell biology and bioinformatics. Read source abstracts and check manuscript versions; preprints are not peer reviewed.

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bioRxiv2017

Precopulatory behavior and sexual conflict in the desert locust

Studies of mating and reproductive behavior have contributed much to our understanding of various animals ecological success. The desert locust, Schistocerca gregaria, is an important agricultural pest. However, knowledge of locust courtship and precopulatory behavior is surprisingly limited. Here we provide a comprehensive study of the precopulatory behavior of both sexes of the desert locust in the gregarious phase, with particular emphasis on the conflict between the sexes. Detailed HD-video monitoring of courtship and mating of 20 locust pairs, in a controlled environment, enabled both qualitative and quantitative descriptions of the behavior. A comprehensive list of behavioral elements was used to generate an eight-step ethogram, depicting from first encounter between the sexes to actual copulation. Further analyses included the probability of each element occurring, and a kinematic diagram based on a transitional matrix. Eleven novel behavioral elements are described in this study, and two potential points of conflict between the sexes are identified. Locust sexual interaction was characterized by the dominance of the males during the pre-mounting stage, and an overall stereotypic male courtship behavior. In contrast, females displayed no clear courtship-related behavior and an overall less organized behavioral sequence. Central elements in the sexual behavior of the females were low-amplitude hind-leg vibration, as well as rejecting males by jumping and kicking. Intricate reciprocal interactions between the sexes were evident mostly at the mounting stage. The reported findings contribute important insights to our knowledge of locust mating and reproductive behavior, and may assist in confronting this devastating agricultural pest.

animal behavior and cognition↗
bioRxiv2017

MEBS, a software platform to evaluate large (meta)genomic collections according to their metabolic machinery: unraveling the sulfur cycle

BACKGROUNDThe increasing number of metagenomic and genomic sequences has dramatically improved our understanding of microbial diversity, yet our ability to infer metabolic capabilities in such datasets remains challenging.\n\nFINDINGSWe describe the Multigenomic Entropy Based Score pipeline (MEBS), a software platform designed to evaluate, compare and infer complex metabolic pathways in large omic datasets, including entire biogeochemical cycles. MEBS is open source and available through https://github.com/eead-csic-compbio/metagenome_Pfam_score. To demonstrate its use we modeled the sulfur cycle by exhaustively curating the molecular and ecological elements involved (compounds, genes, metabolic pathways and microbial taxa). This information was reduced to a collection of 112 characteristic Pfam protein domains and a list of complete-sequenced sulfur genomes. Using the mathematical framework of relative entropy (H), we quantitatively measured the enrichment of these domains among sulfur genomes. The entropy of each domain was used to both: build up a final score that indicates whether a (meta)genomic sample contains the metabolic machinery of interest and to propose marker domains in metagenomic sequences such as DsrC (PF04358). MEBS was benchmarked with a dataset of 2,107 non-redundant microbial genomes from RefSeq and 935 metagenomes from MG-RAST. Its performance, reproducibility, and robustness were evaluated using several approaches, including random sampling, linear regression models, Receiver Operator Characteristic plots and the Area Under the Curve metric (AUC). Our results support the broad applicability of this algorithm to accurately classify (AUC=0.985) hard to culture genomes (e.g., Candidatus Desulforudis audaxviator), previously characterized ones and metagenomic environments such as hydrothermal vents, or deep-sea sediment.\n\nCONCLUSIONSOur benchmark indicates that an entropy-based score can capture the metabolic machinery of interest and be used to efficiently classify large genomic and metagenomic datasets, including uncultivated/unexplored taxa

bioinformatics↗
bioRxiv2017

Auditory brainstem responses to continuous natural speech in human listeners

Speech is an ecologically essential signal whose processing begins in the subcortical nuclei of the auditory brainstem, but there are few experimental options for studying these early responses under natural conditions. While encoding of continuous natural speech has been successfully probed in the cortex with neurophysiological tools such as electro- and magnetoencephalography, the rapidity of subcortical response components combined with unfavorable signal to noise ratios has prevented application of those methods to the brainstem. Instead, experiments have used thousands of repetitions of simple stimuli such as clicks, tonebursts, or brief spoken syllables, with deviations from those paradigms leading to ambiguity in the neural origins of measured responses. In this study we developed and tested a new way to measure the auditory brainstem response to ongoing, naturally uttered speech. We found a high degree of morphological similarity between the speech-evoked auditory brainstem responses (ABR) and the standard click-evoked ABR, notably a preserved wave V, the most prominent voltage peak in the standard click-evoked ABR. Because this method yields distinct peaks at latencies too short to originate from the cortex, the responses measured can be unambiguously determined to be subcortical in origin. The use of naturally uttered speech to evoke the ABR allows the design of engaging behavioral tasks, facilitating new investigations of the effects of cognitive processes like language processing and attention on brainstem processing.\n\nSIGNIFICANCE STATEMENTSpeech processing is usually studied in the cortex, but it starts in the auditory brainstem. However, a paradigm for studying brainstem processing of continuous natural speech in human listeners has been elusive due to practical limitations. Here we adapt methods that have been employed for studying cortical activity to the auditory brainstem. We measure the response to continuous natural speech and show that it is highly similar to the click-evoked response. The method also allows simultaneous investigation of cortical activity with no added recording time. This discovery paves the way for studies of speech processing in the human brainstem, including its interactions with higher order cognitive processes originating in the cortex.

neuroscience↗
bioRxiv2017

Direct PCR offers a fast and reliable alternative to conventional DNA isolation methods for animal gut microbiomes

The gut microbiome of animals is emerging as an important factor influencing ecological and evolutionary processes. A major bottleneck in obtaining microbiome data from large numbers of samples is the time-consuming laboratory procedures, specifically the isolation of DNA and generation of amplicon libraries. Recently, direct PCR kits have been developed that circumvent conventional DNA extraction steps, thereby streamlining the laboratory process by reducing preparation time and costs. However, the reliability and efficacy of the direct PCR method for measuring host microbiomes has not yet been investigated other than in humans with 454-sequencing. Here, we conduct a comprehensive evaluation of the microbial communities obtained with direct PCR and the widely used MoBio PowerSoil DNA extraction kit in five distinct gut sample types (ileum - caecum - colon - faeces - cloaca) from 20 juvenile ostriches, using 16S rRNA Illumina MiSeq sequencing. We found that direct PCR was highly comparable over a range of measures to the DNA extraction method in caecal, colon, and faecal samples. However, the two methods recovered significantly different microbiomes in cloacal, and especially ileal samples. We also sequenced 100 replicate sample pairs to evaluate repeatability during both extraction and PCR stages, and found that both methods were highly consistent for caecal, colon, and faecal samples (rs > 0.7), but had low repeatability for cloacal (rs = 0.39) and ileal (rs = -0.24) samples. This study indicates that direct PCR provides a fast, cheap, and reliable alternative to conventional DNA extraction methods for retrieving 16S data, which will aid future gut microbiome studies of animals.

microbiology↗
bioRxiv2017

Impaired competence in flagellar mutants of Bacillus subtilis is connected to the regulatory network governed by DegU

The competent state is a developmentally distinct phase, in which bacteria are able to take up and integrate exogenous DNA into their genome. Bacillus subtilis is one of the naturally competent bacterial species and the domesticated laboratory strain 168 is easily transformable. In this study, we report a reduced transformation frequency of B. subtilis mutants lacking functional and structural flagellar components. This includes hag, the gene encoding the flagellin protein forming the filament of the flagellum. We confirm that the observed decrease of the transformation frequency is due to reduced expression of competence genes, particularly of the main competence regulator comK. The impaired competence is due to an increase in the phosphorylated form of the response regulator DegU, which is involved in regulation of both flagellar motility and competence. Altogether, our study identified a close link between motility and natural competence in B. subtilis suggesting that hindrance in motility has great impact on differentiation of this bacterium not restricted only to the transition towards sessile growth stage.\n\nOriginality-Significance statementUnderstanding how versatile bacterial phenotypes influence each other is important for our basic understanding of microbial ecology. Our research highlights the novel intertwinement of bacterial differentiation and reveal how lack of single cell motility adjusts DNA exchange among bacterial strains.

microbiology↗
bioRxiv2017

Determinants of genetic structure of the Sub-Saharan parasitic wasp Cotesia sesamiae

Parasitoid life style represents one of the most diversified life history strategies on earth. There are however very few studies on the variables associated with intraspecific diversity of parasitoid insects, especially regarding the relationship with spatial, biotic and abiotic ecological factors. Cotesia sesamiae is a Sub-Saharan stenophagous parasitic wasp that parasitizes several African stemborer species with variable developmental success. The different host-specialized populations are infected with different strains of Wolbachia, an endosymbiotic bacterium widespread in arthropods that is known for impacting life history traits notably reproduction, and consequently species distribution. In this study, first we analyzed the genetic structure of C. sesamiae across Sub-Saharan Africa, using 8 microsatellite markers, and 3 clustering software. We identified five major population clusters across Sub-Saharan Africa, which probably originated in East African Rift region and expanded throughout Africa in relation to host genus and abiotic factors such as climatic classifications. Using laboratory lines, we estimated the incompatibility between the different strains of Wolbachia infecting C. sesamiae. We observed an incompatibility between Wolbachia strains was asymmetric; expressed in one direction only. Based on these results, we assessed the relationships between direction of gene flow and Wolbachia infections in the genetic clusters. We found that Wolbachia-induced reproductive incompatibility was less influential than host specialization in the genetic structure. Both Wolbachia and host were more influential than geography and current climatic conditions. These results are discussed in the context of African biogeography, and co-evolution between Wolbachia, virus parasitoid and host, in the perspective of improving biological control efficiency through a better knowledge of the biodiversity of biological control agents.

evolutionary biology↗
bioRxiv2017

Low cost and open source multi-fluorescence imaging system for teaching and research in biology and bioengineering

The advent of easy-to-use open source microcontrollers, off-the-shelf electronics and customizable manufacturing technologies has facilitated the development of inexpensive scientific devices and laboratory equipment. In this study, we describe an imaging system that integrates low-cost and open-source hardware, software and genetic resources. The multi-fluorescence imaging system consists of readily available 470 nm LEDs, a Raspberry Pi camera and a set of filters made with low cost acrylics. This device allows imaging in scales ranging from single colonies to entire plates. We developed a set of genetic components (e.g. promoters, coding sequences, terminators) and vectors following the standard framework of Golden Gate, which allowed the fabrication of genetic constructs in a combinatorial, low cost and robust manner. In order to provide simultaneous imaging of multiple wavelength signals, we screened a series of long stokes shift fluorescent proteins that could be combined with cyan/green fluorescent proteins. We found CyOFP1, mBeRFP and sfGFP to be the most compatible set for 3-channel fluorescent imaging. We developed open source Python code to operate the hardware to run time-lapse experiments with automated control of illumination and camera and a Python module to analyze data and extract meaningful biological information. To demonstrate the potential application of this integral system, we tested its performance on a diverse range of imaging assays often used in disciplines such as microbial ecology, microbiology and synthetic biology. We also assessed its potential for STEM teaching in a high school environment, using it to teach biology, hardware design, optics, and programming. Together, these results demonstrate the successful integration of open source hardware, software, genetic resources and customizable manufacturing to obtain a powerful, low cost and robust system for STEM education, scientific research and bioengineering. All the resources developed here are available under open source licenses.

synthetic biology↗
bioRxiv2017

Impact of spatial organization on a novel auxotrophic interaction among soil microbes

A key prerequisite to achieve a deeper understanding of microbial communities and to engineer synthetic ones is to identify the individual metabolic interactions among key species and how these interactions are affected by different environmental factors. Deciphering the physiological basis of species-species and species-environment interactions in spatially organized environment requires reductionist approaches using ecologically and functionally relevant species. To this end, we focus here on a specific defined system to study the metabolic interactions in a spatial context among a plant-beneficial endophytic fungus Serendipita indica, and the soil-dwelling model bacterium Bacillus subtilis. Focusing on the growth dynamics of S. indica under defined conditions, we identified an auxotrophy in this organism for thiamine, which is a key co-factor for essential reactions in the central carbon metabolism. We found that S. indica growth is restored in thiamine-free media, when co-cultured with B. subtilis. The success of this auxotrophic interaction, however, was dependent on the spatial and temporal organization of the system; the beneficial impact of B. subtilis was only visible when its inoculation was separated from that of S. indica either in time or space. These findings describe a key auxotrophic interaction in the soil among organisms that are shown to be important for plant ecosystem functioning, and point to the potential importance of spatial and temporal organization for the success of auxotrophic interactions. These points can be particularly important for engineering of minimal functional synthetic communities as plant-seed treatments and for vertical farming under defined conditions.

systems biology↗
bioRxiv2017

Desert Tortoises in the Genomic Age: Population Genetics and the Landscape

The California Department of Fish and Wildlife (CDFW) provided research funds to study the conservation genomics and landscape genomics of the Mojave desert tortoise, Gopherus agassizii, in response to the Desert Renewable Energy Conservation Plan (DRECP). To do this, we consolidated tissue samples of the desert tortoise from across the species range within California and southern Nevada, generated a DNA dataset consisting of full genomes of 270 tortoises, and analyzed the way in which the environment of the desert tortoise has determined modern patterns of relatedness and genetic diversity across the landscape. Here we present the implications of these results for the conservation and landscape genomics of the desert tortoise. Our work strongly indicates that several well-defined genetic groups exist within the species, including a primary north-south genetic discontinuity at the Ivanpah Valley and another separating western from eastern Mojave samples. We also use existing desert tortoise habitat modeling data with a novel extension of genetic \"resistance distance\" using geographic maps of continuous space to predict the relative impacts of five proposed development alternatives within the DRECP and rank them with respect to their likely impacts on desert tortoise gene flow and connectivity in the Mojave. Finally, we analyzed the impacts of each of the 214 distinct proposed development area \"chunks,\" derived from the proposed development polygons, and ranked each chunk in terms of its range-wide impacts on desert tortoise gene flow.\n\n\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=150 SRC=\"FIGDIR/small/195743_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (147K):\norg.highwire.dtl.DTLVardef@b60416org.highwire.dtl.DTLVardef@1c649f2org.highwire.dtl.DTLVardef@120e625org.highwire.dtl.DTLVardef@e59b34_HPS_FORMAT_FIGEXP M_FIG C_FIG PrefaceO_ST_ABSContextC_ST_ABSThe following document is a report that was submitted to the California Department of Fish and Wildlife, describing a series of analyses to help understand the impacts of several alternative spatial configurations of renewable energy development on gene flow of the federally threatened Mojave desert tortoise. These development alternatives were the centerpiece of the Desert Renewable Energy Conservation Plan (DRECP), a landscape-level land use planning initiative undertaken by the Bureau of Land Management (BLM), U.S. Fish and Wildlife Service (USFWS), California Energy Commission (CEC), and the California Department of Fish and Wildlife (CDFW). We were tasked by the California Department of Fish and Wildlife with providing a detailed analysis of these alternative plans on desert tortoise gene flow, and submitted the report for the public comment period for the initial implementation of the DRECP.\n\nFuture PlansO_ST_ABSCurrent state of landscape-level planning for the Mojave desert tortoiseC_ST_ABSThe five proposed land use configuration alternatives analyzed in the subsequent report include public and private lands spread across several counties in California. Shortly after the end of the DRECPs public comment period, the government agencies that developed the DRECP announced that they would be splitting its implementation into two phases: one that deals with land use decisions on BLM-controlled lands and one that deals with non-BLM areas (Sahagun 2015).\n\nPhase I of the DRECP was approved by the Bureau of Land Management on September 14, 2016 (U.S. Bureau of Land Management 2016). This phase includes land use planning decisions for BLM-administered lands. Specifically, 388,000 acres of public lands were designated as development focus areas (DFAs). In applications for leasing lands for renewable energy development, DFAs will not require the same degree of environmental evaluation prior to permitting, as theyve already been evaluated in the context of the DRECP. The application process for renewable energy development within DFAs will be streamlined to encourage development in these areas. Phase I also designated a total of 6,527,000 acres for natural resource conservation. This includes California Desert National Conservation Lands, Areas of Critical Environmental Concern, and Wildlife Allocations. A further 2,691,000 acres were designated for recreation under Phase I. Phase II of the DRECP is currently under development in conjunction with county-level governments to extend this landscape-level planning beyond BLM-administered lands.\n\nAuthor ContributionsThis was a collaborative report. Evan McCartney-Melstad performed the simulations of the low-coverage full genome approach (see Figure 2); conducted all of the laboratory work to generate the genome sequences; performed all of the bioinformatic analyses to bring the raw sequence data to the various stages required for different analyses; wrote the software to quickly estimate pairwise genetic relationships between individuals using read count data in low coverage sequence data (www.github.com/atcg/cPWP); performed some of the population genetic analyses; and wrote and edited several sections of the report.\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=122 SRC=\"FIGDIR/small/195743_fig2.gif\" ALT=\"Figure 2\">\nView larger version (16K):\norg.highwire.dtl.DTLVardef@30a49forg.highwire.dtl.DTLVardef@187c3d8org.highwire.dtl.DTLVardef@4abe98org.highwire.dtl.DTLVardef@126febe_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFigure 2.C_FLOATNO Comparison of two different sequencing approaches in their ability to differentiate very slightly differentiated populations (Fst=0.001)\n\nC_FIG Peter Ralph (in collaboration with Gideon Bradburd and Erik Lundgren) invented and implemented the random walk-based gene flow model that we used to estimate reductions in gene flow due to development, and also developed the theory behind the read-based pairwise pi and genetic covariance estimation used here, in addition to writing and editing several sections of the report. Gideon Bradburd also performed some of the population genetic analyses and wrote and edited several sections of the report. Jannet Vu collected and curated the spatial environmental data and generated the maps that are included in the report (Figures 10, A10-A13), and also wrote Appendices I and IV. Bridgette Hagerty, Fran Sandmeier, Chava Weitzman, and C. Richard Tracy contributed approximately 1,000 desert tortoise blood samples that they collected (at great effort), in addition to knowledge of tortoise ecology and conservation, as well as the results of previous microsatellite-based genetic analyses and editing of the report. H. Bradley Shaffer wrote and edited several sections of the report, and is listed as the lead author for his role in conceiving of and obtaining funding support for the project.\n\nO_FIG O_LINKSMALLFIG WIDTH=154 HEIGHT=200 SRC=\"FIGDIR/small/195743_fig10.gif\" ALT=\"Figure 10\">\nView larger version (82K):\norg.highwire.dtl.DTLVardef@11e99acorg.highwire.dtl.DTLVardef@1faf2f5org.highwire.dtl.DTLVardef@64c440org.highwire.dtl.DTLVardef@1907837_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFigure 10.C_FLOATNO Spatial configuration of the proposed development chunks (see Appendix 4).\n\nC_FIG

evolutionary biology↗
bioRxiv2017

A LaeA- and BrlA-dependent cellular network governs tissue-specific secondary metabolism in the human pathogen Aspergillus fumigatus

Biosynthesis of many ecologically important secondary metabolites (SMs) in filamentous fungi is controlled by several global transcriptional regulators, like the chromatin modifier LaeA, and tied to both development and vegetative growth. In Aspergillus molds, asexual development is regulated by the BrlA>AbaA>WetA transcriptional cascade. To elucidate BrlA pathway involvement in SM regulation, we examined the transcriptional and metabolic profiles of {Delta}brlA, {Delta}abaA, {Delta}wetA and wild-type strains of the human pathogen Aspergillus fumigatus. We find that BrlA, in addition to regulating production of developmental SMs, regulates vegetative SMs and the SrbA-regulated hypoxia stress response in a concordant fashion to LaeA. We further show that the transcriptional and metabolic equivalence of {Delta}brlA and {Delta}laeA is mediated by a LaeA requirement preventing heterochromatic marks in the brlA promoter. These results provide a framework for the cellular network regulating not only fungal SMs but diverse cellular processes linked to virulence of this pathogen.

microbiology↗
bioRxiv2017

Compositional clustering in task structure learning

Humans are remarkably adept at generalizing knowledge between experiences in a way that can be difficult for computers. Often, this entails generalizing constituent pieces of experiences that do not fully overlap, but nonetheless share useful similarities with, previously acquired knowledge. However, it is often unclear how knowledge gained in one context should generalize to another. Previous computational models and data suggest that rather than learning about each individual context, humans build latent abstract structures and learn to link these structures to arbitrary contexts, facilitating generalization. In these models, task structures that are more popular across contexts are more likely to be revisited in new contexts. However, these models predict that structures are either re - used as a whole or created from scratch, prohibiting the ability to generalize constituent parts of learned structures. This contrasts with ecological settings, where some aspects of task structure, such as the transition function, will be shared between context separately from other aspects, such as the reward function. Here, we develop a novel non - parametric Bayesian agent that forms independent latent clusters for transition and reward functions that may have different popularity across contexts. We compare this agent to an agent that jointly clusters both across a range of task domains. We show that relative performance of the two agents depends on the statistics of the task domain, including the mutual information between transition and reward functions in the environment, and the stochasticity of the observations. We formalize our analysis through an information theoretic account of the priors, and develop a meta learning agent that can dynamically arbitrate between strategies across task domains. We argue that this provides a first step in allowing for compositional structures in reinforcement learners, which should be provide a better model of human learning and additional flexibility for artificial agents.\n\nAuthor summaryA musician may learn to generalize behaviors across instruments for different purposes, for example, reusing hand motions used when playing classical on the flute to play jazz on the saxophone. Conversely, she may learn to play a single song across many instruments that require completely distinct physical motions, but nonetheless transfer knowledge between them. This degree of compositionality is often absent from computational frameworks of learning, forcing agents either to generalize entire learned policies or to learn new policies from scratch. Here, we propose a solution to this problem that allows an agent to generalize components of a policy independently and compare it to an agent that generalizes components as a whole. We show that the degree to which one form of generalization is favored over the other is dependent on the features of task domain, with independent generalization of task components favored in environments with weak relationships between components or high degrees of noise and joint generalization of task components favored when there is a clear, discoverable relationship between task components. Furthermore, we show that the overall meta structure of the environment can be learned and leveraged by an agent that dynamically arbitrates between these forms of structure learning.

neuroscience↗
bioRxiv2017

Diet predicts milk composition in primates

Mammalian mothers pay heavy energetic costs to fuel the growth of their offspring. These costs are highest during lactation. Energy transmitted to offspring in the form of milk must ultimately come from the maternal diet, but there have been few comparative studies of the relationship between milk properties and mammalian diets. We used interspecific data on primate milk composition and wild diets to establish that concentrations of milk protein and sugar are predicted by diet independent of maternal mass, litter mass, and infant parking behavior such that increasing folivory or faunivory increases protein concentration but decreases sugar concentration. Milk energy density is unrelated to diet, though infant parking species do produce more energy-dense milk. While parking effects have been previously explained as a result of mother-infant separation, the mechanisms causing the relationship between nutrient packaging in milk and maternal diet are currently unclear. However, they likely reflect evolved differences in maternal energetics related to maternal foraging ecology, infant growth patterns, or the relative dietary abundance of nutrients costly to synthesize in milk among primate species.

zoology↗
bioRxiv2017

Hox-logic of preadaptations for social insect symbiosis in rove beetles

How symbiotic lifestyles evolve from free-living ecologies is poorly understood. In Metazoas largest family, Staphylinidae (rove beetles), numerous lineages have evolved obligate behavioral symbioses with ants or termites. Widespread convergence of this lifestyle is thought to stem from a novel, chemically defended body plan that enables free-living species to infiltrate colonies and undergo extreme evolutionary specialization. Here we show how this innovative body plan evolved, via new Hox functions in staphylinids that remodeled the coleopteran groundplan. Using a model staphylinid, Dalotia coriaria, we reveal the Hox basis for changes in thoracic appendage morphology that shortened the beetle elytron and left the abdomen physically unprotected, selecting for an abdominal defense gland that was likely key to unlocking ant and termite societies. We present evidence that the gland evolved through a novel, combinatorial role of the abdominal Hox proteins AbdA and AbdB. These proteins function together to specify distinct gland cell types in neighboring segmental compartments, each cell type synthesizing a different class of compound--irritant, ester and solvent. Only when secreted together do these compounds constitute a bioactive secretion, providing an example of emergent chemical functionality that arises from synergy between individual gland cell types. Hox-controlled specification of glandular diversity implies a modularity in compound biosynthesis that likely catalyzed the evolvability of rove beetle chemistry, including the capacity of symbiotic taxa to produce potent compounds for host deception. This study reveals how Hox-controlled body axis modifications predispose a major animal to convergently evolve into symbionts.

evolutionary biology↗
bioRxiv2017

Motility in multicellular Chlamydomonas reinhardtii

The advent of multicellularity was a watershed event in the history of life, yet the transition from unicellularity to multicellularity is not well understood. Multicellularity opens up opportunities for innovations in intercellular communication, cooperation, and specialization, which can provide selective advantages under certain ecological conditions. The unicellular alga Chlamydomonas reinhardtii has never had a multicellular ancestor yet it is closely related to the volvocine algae, a clade containing taxa that range from simple unicells to large, specialized multicellular colonies. Simple multicellular structures have been observed to evolve in C. reinhardtii in response to predation or to settling rate-based selection. Structures formed in response to predation consist of individual cells grouped within a shared transparent extracellular matrix. Evolved isolates form such structures obligately under culture conditions in which their wild type ancestors do not, indicating that newly-evolved multicellularity is heritable. C. reinhardtii is capable of photosynthesis, and possesses an eyespot and two flagella with which it moves towards or away from light in order to optimize input of radiant energy. Motility contributes to C. reinhardtii fitness because it allows cells or colonies to achieve this optimum. Utilizing phototaxis to assay motility, we determined that newly evolved multicellular strains do not exhibit significant directional movement, even though the flagellae of their constituent unicells are present and active. In C. reinhardtii the first steps towards multicellularity in response to predation appear to result in a trade-off between motility and differential survivorship, a trade-off that must overcome by further genetic change to ensure the long-term success of the new multicellular organism.

evolutionary biology↗
bioRxiv2017

Influenza Interaction with Cocirculating Pathogens, and Its Impact on Surveillance, Pathogenesis and Epidemic Profile: A Key Role for Mathematical Modeling

Evidence is mounting that influenza virus, a major contributor to the global disease burden, interacts with other pathogens infecting the human respiratory tract. Taking into account interactions with other pathogens may be critical to determining the real influenza burden and the full impact of public health policies targeting influenza. That necessity is particularly true for mathematical modeling studies, which have become critical in public health decision-making, despite their usually focusing on lone influenza virus acquisition and infection, thereby making broad oversimplifications regarding pathogen ecology. Herein, we review evidence of influenza virus interaction with bacteria and viruses, and the modeling studies that incorporated some of these. Despite the many studies examining possible associations between influenza and Streptococcus pneumoniae, Staphylococcus aureus, Haemophilus influenzae, Neisseria meningitides, respiratory syncytial virus, human rhinoviruses, human parainfluenza viruses, etc., very few mathematical models have integrated other pathogens alongside influenza. A notable exception is the recent modeling of the pneumococcus-influenza interaction, which highlighted potential influenza-related increased pneumococcal transmission and pathogenicity. That example demonstrates the power of dynamic modeling as an approach to test biological hypotheses concerning interaction mechanisms and estimate the strength of those interactions. We explore how different interference mechanisms may lead to unexpected incidence trends and misinterpretations. Using simple transmission models, we illustrate how existing interactions might impact public health surveillance systems and demonstrate that the development of multipathogen models is essential to assess the true public health burden of influenza, and help improve planning and evaluation of control measures. Finally, we identify the public health needs, surveillance, modeling and biological challenges, and propose avenues of research for the coming years.\n\nAuthor SummaryInfluenza is a major pathogen responsible for important morbidity and mortality burdens worldwide. Mathematical models of influenza virus acquisition have been critical to understanding its epidemiology and planning public health strategies of infection control. It is increasingly clear that microbes do not act in isolation but potentially interact within the host. Hence, studying influenza alone may lead to masking effects or misunderstanding information on its transmission and severity. Herein, we review the literature on bacterial and viral species that interact with the influenza virus, interaction mechanisms, and mathematical modeling studies integrating interactions. We report evidence that, beyond the classic secondary bacterial infections, many pathogenic bacteria and viruses probably interact with influenza. Public health relevance of pathogen interactions is detailed, showing how potential misreading or a narrow outlook might lead to mistaken public health decisionmaking. We describe the role of mechanistic transmission models in investigating this complex system and obtaining insight into interactions between influenza and other pathogens. Finally, we highlight benefits and challenges in modeling, and speculate on new opportunities made possible by taking a broader view: including basic science, clinical relevance and public health.

epidemiology↗
bioRxiv2017

Demographic fluctuation of community-acquired antibiotic-resistant Staphylococcus aureus lineages: potential role of flimsy antibiotic exposure

Community-acquired (CA) -as opposed to hospital acquired- methicillin-resistant Staphylococcus aureus (MRSA) lineages arose worldwide during the 1990s. To determine which factors, including selective antibiotic pressure, govern the expansion of two major lineages of CA-MRSA, namely \"USA300\" in Northern America and the \"European ST80\" in North Africa, Europe and the Middle East, we explored virulence factor expression, and fitness levels with or without antibiotics. The sampled strains were collected in a temporal window representing various steps of the epidemics, reflecting predicted effective population size as inferred from whole genome analysis. In addition to slight variations in virulence factor expression and biofilm production that might influence the ecological niches of theses lineages, competitive fitness experiments revealed that the biological cost of resistance to methicillin, fusidic-acid and fluoroquinolone is totally reversed in the presence of trace amount of antibiotics. Our results suggest that low-level antibiotics exposure in human and animal environments contributed to the expansion of both European-ST80 and USA300 lineages in community setting. This surge was likely driven by antibiotic (ab)use promoting the accumulation of antibiotics as environmental pollutants. The current results provide a novel link between effective population size increase of a pathogen and a selective advantage conferred by antibiotic resistance.

microbiology↗
bioRxiv2017

Game theoretic consideration of transgenic bacteria in the human gut microbiota as a pro-biotic prophylactic for metabolic syndrome

A game theoretic treatment is introduced to explore the role of nutrition of the gut bacterial microflora as a potential pro-biotic therapy. Rational design of functional foods and nutraceuticals has far reaching public health and therapeutic benefits. Understanding ecological dynamics and how phenotypic manipulations of microbe-microbe interactions of the gut microbiota can provide direct health benefit is currently a fundamental question in bioengineering and more widely in the food, diet and health industries. This work considers a hypothetical adjustment of the microbiome by introducing a transgenic bacterial species that contributes to increased exposure of omega 3 fats in the gut by converting them from the omega 6 fats, dominant in the Western diet. The ratio of the two fats circulating in blood are risk markers, indicators of metabolic syndrome and related conditions. In this work, we consider nutritional exposure to a pro-biotic, a live culture of transgenic bacteria contributing omega 3 fats from omega 6 in the diet. Maintaining a long-term co-existence between native (indigenous) and transgenic bacteria is a challenge. Game theory is the appropriate tool for handling this conflict. The long-term co-existence is guaranteed if the two strains engage in the Snowdrift game. Our game theoretic treatment provides the basis of a model mechanism for prophylactic nutritional therapy for metabolic syndrome by the transgenic bacteria, providing support of indigenous gut microbiota and additional supplementation of a pro-biotic.

bioengineering↗
bioRxiv2017

Novel prosthecate bacteria from the candidate phylum Acetothermia revealed by culture-independent genomics and advanced microscopy

Members of the candidate phylum Acetothermia are globally distributed and detected in various habitats. However, little is known about their physiology and ecological importance. In this study, an OTU belonging to Acetothermia was detected at high abundance in two full-scale anaerobic digesters. The first closed genome from this phylum was obtained by differential coverage binning of metagenomes and scaffolding with nanopore data. Genome annotation and metabolic reconstruction suggested an anaerobic chemoheterotrophic lifestyle in which the bacterium obtain energy and carbon via fermentation of peptides, amino acids, and simple sugars to acetate, formate, and hydrogen. The morphology was unusual and composed of a central rod-shaped cell with bipolar prosthecae as revealed by fluorescence in situ hybridization combined with confocal laser scanning microscopy, Raman microspectroscopy and atomic force microscopy. We hypothesize that these prosthecae allow for increased nutrient uptake by greatly expanding the cell surface area, providing a competitive advantage under nutrient-limited conditions.

microbiology↗