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bioRxiv2017

Or22 allelic variation alone does not explain differences in discrimination of yeast-produced volatiles by D. melanogaster

Different lines of the fruit fly Drosophila melanogaster show variation in the ability to discriminate between volatiles produced by the yeast Saccharomyces cerevisiae under natural (nitrogen-limiting, YVN) or laboratory (sugar-limiting, YVL) conditions. Previous work in our laboratory uncovered a strong correlation between heightened sensitivity to YVN wild D. melanogaster lines that harbored a chimeric variant of the highly variable odorant receptor 22 (Or22) locus of D. melanogaster. We sought to determine if this trend held for an extended set of D. melanogaster lines, if observed variation within chimeric and non-chimeric lines could be explained by nucleotide polymorphisms and if replacing Or22 with a chimeric allele in a non-chimeric background could confer the enhanced ability to detect YVN. In parallel, we performed crosses of chimeric and non-chimeric fly lines and assayed the behavior of their progeny for enhanced sensitivity to YVN to assess the heritability of the Or22 locus. Ultimately, we found that, while the overall trend of increased sensitivity to YVN in chimeric lines persists, there are exceptions and variation that cannot be explained by sequence variation at the Or22 locus. In addition, we did not observe increased sensitivity for YVN upon replacing the Or22 allele in a non-chimeric line (OreR) with that from our most YVN-sensitive, chimeric line (ME). Though our results do not support our hypothesis that Or22 is the primary driver of sensitivity to YVN, Or22 remains an interesting locus in the context of fly-yeast ecology.

genetics↗

bioRxiv2017

Genomic evidence for population specific selection in Nilo-Saharan and Niger-Congo linguistic groups in Africa

BackgroundThere are over 2000 genetically diverse ethno-linguistic groups in Africa that could help decipher human evolutionary history and the genetic basis of phenotypic variation. We have sequenced 300 genomes from Niger-Congo populations from six sub-Saharan African countries (Uganda, Democratic Republic of Congo, Cameroon, Zambia, Ivory Coast, Guinea) and a Nilo-Saharan population from Uganda. Of these, we analysed 289 samples for population structure, genetic admixture, population history and signatures of selection. These samples were collected as part of the TrypanoGEN consortium project [1].\n\nResultsThe population genetic structure of the 289 individuals revealed four clusters, which correlated with ethno-linguistic group and geographical latitude. These were the West African Niger-Congo A, Central African Niger-Congo B, East African Niger-Congo B and the Nilo-Saharan. We observed a spatial distribution of positive natural selection signatures in genes previously associated with AIDS, Tuberculosis, Malaria and Human African Trypanosomiasis among the TrypanoGEN samples. Having observed a marked difference between the Nilo-Saharan Lugbara and Niger-Congo populations, we identified four genes (APOBEC3G, TOP2B, CAPN9, LANCL2), which are highly differentiated between the two ethnic groups and under positive selection in the Lugbara population (_iHS -log p > 3.0, Rsb -log p > 3.0, Fst > 0.1 bonferroni p > 1.8x10e4).\n\nConclusionThe signatures that differentiate ethnically distinct populations could provide information on the specific ecological adaptations with respect to disease history and susceptibility/resistance. For instance in this study we identified APOBEC3G which is believed to be involved in the susceptibility of the Nilo-Saharan Lugbara population to Hepatitis B virus infection.

genomics↗

bioRxiv2017

A rainfall-manipulation experiment with 517 Arabidopsis thaliana accessions

The gold standard for studying natural selection and adaptation in the wild is to quantify lifetime fitness of individuals from natural populations that have been grown together in a common garden, or that have been reciprocally transplanted. By combining fitness values with species traits and genome sequences, one can infer selection coefficients at the genetic level. Here we present a rainfall-manipulation experiment with 517 whole-genome sequenced natural accessions of the plant Arabidopsis thaliana spanning the global distribution of the species. The experiments were conducted in two field stations in contrasting climates, in the Mediterranean and in Central Europe, where we built rainout shelters and simulated high and low rainfall. Using custom image analysis we quantified fitness- and phenology-related traits for 23,154 pots, which contained about 14,500 plants growing independently, and over 310,000 plants growing in small populations (max. 30 plants). This large field experiment dataset, which associates fitness and ecologically-relevant traits with genomes, will provide an important resource to test eco-evolutionary genetic theories and to understand the potential evolutionary impacts of future climates on an important plant model species.

evolutionary biology↗

bioRxiv2017

Rapid seasonal evolution in innate immunity of wild Drosophila melanogaster

Understanding the rate of evolutionary change and the genetic architecture that facilitates rapid adaptation is a current challenge in evolutionary biology. Comparative studies show that genes with immune function are among the most rapidly evolving genes in a range of taxa. Here, we use immune defense in natural populations of D. melanogaster to understand the rate of evolution in natural populations and the genetics underlying the rapid change. We probed the immune system using the natural pathogens Enterococcus faecalis and Providencia rettgeri to measure post-infection survival and bacterial load of wild D. melanogaster populations collected across seasonal time along a latitudinal transect on the eastern North America (Massachusetts, Pennsylvania, and Virginia). There are pronounced and repeatable changes in the immune response over approximately 10 generations between the spring and fall populations with a significant but less distinct difference among geographic locations. Genes with known immune function are not enriched among alleles that cycle with seasonal time, but the immune function of a subset of seasonally cycling alleles in immune genes was tested using reconstructed outbred populations. We find that flies containing seasonal alleles in Thioester-containing protein 3 (Tep3) have different functional responses to infection and that epistatic interactions among seasonal Tep3 and Drosomycin-like 6 (Dro6) alleles produce the immune phenotypes observed in natural populations. This rapid, cyclic response to seasonal environmental pressure broadens our understanding of the complex ecological and genetic interactions determining the evolution of immune defense in natural populations.

evolutionary biology↗

bioRxiv2017

Internal amino acid state modulates yeast taste neurons to support protein homeostasis in Drosophila

To optimize fitness, animals must dynamically match food choices to their current needs. For drosophilids, yeast fulfils most dietary protein and micronutrient requirements. While several yeast metabolites activate known gustatory receptor neurons (GRNs) in Drosophila melanogaster, the chemosensory channels mediating yeast feeding remain unknown. Here we identify a class of proboscis GRNs required for yeast intake, and show that these GRNs act redundantly to mediate yeast feeding. While nutritional and reproductive states synergistically increase yeast appetite, we find a separation of these state signals at the level of GRN responses to yeast: amino acid but not mating state enhances yeast GRN gain. The sensitivity of sweet GRNs to sugar is not increased by protein deprivation, providing a potential basis for protein-specific appetite. The emerging picture is that different internal states act at distinct levels of a dedicated gustatory circuit to elicit nutrient-specific appetites towards a complex, ecologically relevant protein source.

neuroscience↗

bioRxiv2017

xenoGI: reconstructing the history of genomic island insertions in clades of closely related bacteria

BackgroundGenomic islands play an important role in microbial genome evolution, providing a mechanism for strains to adapt to new ecological conditions. A variety of computational methods, both genome-composition based and comparative have been developed to identify them. Some of these methods are explicitly designed to work in single strains, while others make use of multiple strains. In general, existing methods do not identify islands in the context of the phylogeny in which they evolved. Even multiple strain approaches are best suited to identifying genomic islands that are present in one strain but absent in others. They do not automatically recognize islands which are shared between some strains in the clade or determine the branch on which these islands inserted within the phylogenetic tree.\n\nResultsWe have developed a software package, xenoGI, that identifies genomic islands and maps their origin within a clade of closely related bacteria, determining which branch they inserted on. It takes as input a set of sequenced genomes and a tree specifying their phylogenetic relationships. Making heavy use of synteny information, the package builds gene families in a species-tree-aware way, and then attempts to combine into islands those families whose members are adjacent and whose most recent common ancestor is shared. The package provides a variety of text-based analysis functions, as well as the ability to export genomic islands into formats suitable for viewing in a genome browser. We demonstrate the capabilities of the package with several examples from enteric bacteria, including an examination of the evolution of the acid fitness island in the genus Escherichia. In addition we use output from simulations and a set of known genomic islands from the literature to show that xenoGI can accurately identify genomic islands and place them on a phylogenetic tree.\n\nConclusionsxenoGI is an effective tool for studying the history of genomic island insertions in a clade of microbes. It identifies genomic islands, and determines which branch they inserted on within the phylogenetic tree for the clade. Such information is valuable because it helps us understand the adaptive path that has produced living species. Given the large and growing number of sequenced microbial genomes, this sort of analysis will become increasingly useful in the future.

bioinformatics↗

bioRxiv2017

A global Brassica pest and a sympatric cryptic ally, Plutella australiana (Lepidoptera: Plutellidae), show strong divergence despite the capacity to hybridize

The diamondback moth, Plutella xylostella, has been intensively studied due to its ability to evolve insecticide resistance and status as the worlds most destructive pest of brassicaceous crops. The surprise discovery of a cryptic ally, Plutella australiana Landry & Hebert, with apparent endemism to Australia, immediately raised questions regarding the extent of ecological and genetic diversity between these two species, whether gene flow could occur, and ultimately if specific management was required. Here, we show that despite sympatric distributions and the capacity to hybridize in controlled laboratory experiments, striking differences in genetic and phenotypic traits exist that are consistent with contrasting colonization histories and reproductive isolation after secondary contact. Almost 1500 Plutella individuals were collected from wild and cultivated brassicaceous plants at 75 locations throughout Australia. Plutella australiana was commonly found on all Brassica host types sampled except commercial vegetables, which are routinely sprayed with insecticide. Bioassays using four commonly-used insecticides found that P. australiana was 19-306 fold more susceptible than P. xylostella. Genome-wide SNPs derived from RADseq revealed substantially higher levels of genetic diversity across P. australiana compared with P. xylostella nuclear genomes, yet both species showed limited variation in mtDNA. Infection with a single Wolbachia subgroup B strain was fixed in P. australiana, suggesting that a selective sweep contributed to low mtDNA diversity, while a subgroup A strain infected just 1.5 % of P. xylostella. Although P. australiana is a potential pest of brassica crops, it is of secondary importance to P. xylostella.

genetics↗

bioRxiv2017

Inferring Continuous and Discrete Population Genetic Structure Across Space

A classic problem in population genetics is the characterization of discrete population structure in the presence of continuous patterns of genetic differentiation. Especially when sampling is discontinuous, the use of clustering or assignment methods may incorrectly ascribe differentiation due to continuous processes (e.g., geographic isolation by distance) to discrete processes, such as geographic, ecological, or reproductive barriers between populations. This reflects a shortcoming of current methods for inferring and visualizing population structure when applied to genetic data deriving from geographically distributed populations. Here, we present a statistical framework for the simultaneous inference of continuous and discrete patterns of population structure. The method estimates ancestry proportions for each sample from a set of two-dimensional population layers, and, within each layer, estimates a rate at which relatedness decays with distance. This thereby explicitly addresses the \"clines versus clusters\" problem in modeling population genetic variation. The method produces useful descriptions of structure in genetic relatedness in situations where separated, geographically distributed populations interact, as after a range expansion or secondary contact. We demonstrate the utility of this approach using simulations and by applying it to empirical datasets of poplars and black bears in North America.\n\nAuthor summaryOne of the first steps in the analysis of genetic data, and a principal mission of biology, is to describe and categorize natural variation. A continuous pattern of differentiation (isolation by distance), where individuals found closer together in space are, on average, more genetically similar than individuals sampled farther apart, can confound attempts to categorize natural variation into groups. This is because current statistical methods for assigning individuals to discrete clusters cannot accommodate spatial patterns, and so are forced to use clusters to describe what is in fact continuous variation. As isolation by distance is common in nature, this is a substantial shortcoming of existing methods. In this study, we introduce a new statistical method for categorizing natural genetic variation - one that describes variation as a combination of continuous and discrete patterns. We demonstrate that this method works well and can capture patterns in population genomic data without resorting to splitting populations where they can be described by continuous patterns of variation.

evolutionary biology↗

bioRxiv2017

Phylogeny-corrected identification of microbial gene families relevant to human gut colonization

The mechanisms by which different microbes colonize the healthy human gut versus other body sites, the gut in disease states, or other environments remain largely unknown. Identifying microbial genes influencing fitness in the gut could lead to new ways to engineer probiotics or disrupt pathogenesis. We approach this problem by measuring the statistical association between having a species having a gene and the probability that the species is present in the gut microbiome. The challenge is that closely related species tend to be jointly present or absent in the microbiome and also share many genes, only a subset of which are involved in gut adaptation. We show that this phylogenetic correlation indeed leads to many false discoveries and propose phylogenetic linear regression as a powerful solution. To apply this method across the bacterial tree of life, where most species have not been experimentally phenotyped, we use metagenomes from hundreds of people to quantify each species prevalence in and specificity for the gut microbiome. This analysis reveals thousands of genes potentially involved in adaptation to the gut across species, including many novel candidates as well as processes known to contribute to fitness of gut bacteria, such as acid tolerance in Bacteroidetes and sporulation in Firmicutes. We also find microbial genes associated with a preference for the gut over other body sites, which are significantly enriched for genes linked to fitness in an in vivo competition experiment. Finally, we identify gene families associated with higher prevalence in patients with Crohns disease, including Proteobacterial genes involved in conjugation and fimbria regulation, processes previously linked to inflammation. These gene targets may represent new avenues for modulating host colonization and disease. Our strategy of combining metagenomics with phylogenetic modeling is general and can be used to identify genes associated with adaptation to any environment.\n\nAuthor SummaryWhy do certain microbes and not others colonize our gut, and why do they differ between healthy and sick people? One explanation is the genes in their genomes. If we can find microbial genes involved in gut adaptation, we may be able to keep out pathogens and encourage the growth of beneficial microbes. One could look for genes that were present more often in prevalent microbes, and less often in rare ones.\n\nHowever, this ignores that related species are more likely to share an environment and also share many unrelated phenotypes simply because of common ancestry. To solve this problem, we used a method from ecology that accounts for phylogenetic relatedness. We first calculated gut prevalence for thousands of species using a compendium of shotgun sequencing data, then tested for genes associated with prevalence, adjusting for phylogenetic relationships. We found genes that are associated with overall gut prevalence, with a preference for the gut over other body sites, and with the gut in Crohns disease versus health. Many of these findings have biological plausibility based on existing literature. We also showed agreement with the results of a previously published high-throughput screen of bacterial gene knockouts in mice. These results, and this type of analysis, may eventually lead to new strategies for maintaining gut health.

bioinformatics↗

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

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