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bioRxiv2018

Terrestriality and bacterial transfer: A comparative study of gut microbiomes in sympatric Malagasy mammals

The gut microbiomes of mammals appear to mirror their hosts phylogeny, suggesting a shared history of co-speciation. Yet, much of this evidence stems from comparative studies of distinct wild or captive populations that lack data for disentangling the relative influences of shared phylogeny and environment. Here, we present phylogenetic and multivariate analyses of gut microbiomes from six sympatric (i.e., co-occurring) mammal species inhabiting a 1-km2 area in western Madagascar--three lemur and three non-primate species--that consider genetic, dietary, and ecological predictors of microbiome functionality and composition. Host evolutionary history, indeed, appears to drive gut microbial patterns among distantly related species. However, we also find that diet--reliance on leaves versus fruit--is the best predictor of microbiome similarity among closely related lemur species, and that host substrate preference--ground versus tree-- constrains horizontal transmission via incidental contact with feces, with arboreal species harboring far more distinct communities than those of their terrestrial and semi-terrestrial counterparts.

microbiology↗

bioRxiv2018

Characterisation of the UK honey bee (Apis mellifera) metagenome.

The European honey bee (Apis mellifera) plays a major role in pollination and food production, but is under threat from emerging pathogens and agro-environmental insults. As with other organisms, honey bee health is a complex product of environment, host genetics and associated microbes (commensal, opportunistic and pathogenic). Improved understanding of bee genetics and their molecular ecology can help manage modern challenges to bee health and production. Sampling bee and cobiont genomes, we characterised the metagenome of 19 honey bee colonies across Britain. Low heterozygosity was observed in bees from many Scottish colonies, sharing high similarity to the native dark bee, A. mellifera mellifera. Apiaries exhibited high diversity in the composition and relative abundance of individual microbiome taxa. Most non-bee sequences derived from known honey bee commensal bacteria or known pathogens, e.g. Lotmaria passim (Trypanosomatidae), and Nosema spp. (Microsporidia). However, DNA was also detected from numerous additional bacterial, plant (food source), protozoan and metazoan organisms. To classify sequences from cobionts lacking genomic information, we developed a novel network analysis approach clustering orphan contigs, allowing the identification of a pathogenic gregarine. Our analyses demonstrate the power of high-throughput, directed metagenomics in agroecosystems identifying potential threats to honey bees present in their microbiota.

genomics↗

bioRxiv2018

Hypoxia increases the tempo of evolution in the peri-necrotic niche in glioblastoma

BackgroundLow oxygen in tumours have long been associated with poor prognosis and metastatic disease, precise reasons for which remain poorly understood. Somatic evolution drives cancer progression and treatment resistance. This process is fuelled not only by genetic and epigenetic mutation, but by selection resulting from the interactions between tumour cells, normal cells and physical microenvironment. The ecological habitat tumour cells inhabit influences evolutionary dynamics but impact on tempo of evolution is less clear. MethodsWe explored this complex dialogue with a combined clinical-theoretical approach. Using an agent-based-model, we simulated proliferative hierarchy under heterogeneous oxygen availability. Predictions were compared against clinical data derived from histology samples taken from glioblastoma patients, stained to elucidate areas of hypoxia / necrosis, and p53 expression heterogeneity. ResultsSimulation results indicate cell division in hypoxic environments is effectively upregulated, and that low-oxygen niches provide new avenues for tumour cells to spread. Analysis of human data indicates cell division isnt decreased in low-oxygen regions, despite evidence of significant physiological stress. This is consistent with simulation, suggesting hypoxia is a crucible that effectively warping evolutionary velocity, making deleterious mutations more likely than in well-oxygenated regions. ConclusionsResults suggest hypoxic regions alter evolutionary tempo, driving mutations which fuel tumour heterogeneity..

cancer biology↗

bioRxiv2018

Manganese oxide biomineralization is a social trait protecting against nitrite toxicity

Manganese bio-mineralization by oxidation is a costly but, still, widespread process among bacteria and fungi. While certain potential advantages of manganese oxidation have been suggested, to date there is no conclusive experimental evidence for, how and if this process impacts microbial fitness in the environment. Here we show how a model organism for manganese oxidation, Roseobacter sp. AzwK-3b, is growth-inhibited by nitrite, and that this inhibition is mitigated when manganese is added to the culture medium. We show that manganese-mediated mitigation of nitrite-inhibition is dependent on the culture inoculum size, with larger inocula being able to withstand higher concentrations of nitrite stress. Furthermore, the bio-mineralized manganese oxide (MnOX) forms granular precipitates in the culture, rather than sheaths around individual cells. These findings support the notion that MnOX is a shared community product that improves the cultures survival against nitrite-stress. We show that the mechanistic basis of the MnOX effect involves both its ability to catalyze nitrite oxidation into (non-toxic) nitrate under physiological conditions, and its potential role in influencing redox chemistry around reactive oxygen species (ROS). Taken together, these results provide for the first direct evidence of improved microbial fitness by MnOX deposition in an ecological setting, i.e. mitigation of nitrite toxicity, and point to a key role of MnOX in handling stresses arising from ROS. These findings could be of general relevance for all organisms oxidizing manganese, allowing them to offset costs associated with extracellular bio-mineralization.

microbiology↗

bioRxiv2018

Social Motility: Interaction between two sessile soil bacteria leads to emergence of surface motility

Bacteria often live in complex communities in which they interact with other organisms. Consideration of the social environment of bacteria can reveal emergent traits and behaviors that would be overlooked by studying bacteria in isolation. Here we characterize a social trait which emerges upon interaction between the distantly-related soil bacteria Pseudomonas fluorescens Pf0-1 and Pedobacter sp. V48. On hard agar, which is not permissive for motility of the mono-culture of either species, co-culture reveals an emergent phenotype we term interspecies social spreading, where the mixed colony spreads across the hard surface. We show that initiation of social spreading requires close association between the two species of bacteria. Both species remain associated throughout the spreading colony, with reproducible and non-homogenous patterns of distribution. The nutritional environment influences social spreading; no social behavior is observed under high nutrient conditions, but low nutrient conditions are insufficient to promote social spreading without high salt concentrations. This simple two-species consortium is a tractable model system that will facilitate mechanistic investigations of interspecies interactions and provide insight into emergent properties of interacting species. These studies will contribute to the broader knowledge of how bacterial interactions influence the functions of communities they inhabit.\n\nImportanceThe wealth of studies on microbial communities has revealed the complexity and dynamics of the composition of communities in many ecological settings. Fewer studies probe the functional interactions of the community members. Function of the community as a whole may not be fully revealed by characterizing the individuals. In our two-species model community, we find an emergent trait resulting from the interaction of the soil bacteria Pseudomonas fluorescens Pf0-1 and Pedobacter sp. V48. Observation of emergent traits suggests there may be many functions of a community that are not predicted based on a priori knowledge of the community members. These types of studies will provide a more holistic understanding of microbial communities, allowing us to connect information about community composition with behaviors determined by interspecific interactions. These studies increase our ability to understand communities, such as the soil microbiome, plant-root microbiome, and human gut microbiome, with the final goal of being able to manipulate and rationally improve these communities.

microbiology↗

bioRxiv2018

Functional Quantitative Trait Loci (QTL) analysis for adaptive traits in a three-generation Scots pine pedigree

In forest tree breeding, QTL identification aims to accelerate the breeding cycle and increase the genetic gain of traits with economical and ecological value. In our study, both phenotypic data and predicted breeding values were used in the identification QTL linked to the adaptive value in a three-generation pedigree population, for the first time in a conifer species (Pinus sylvestris L.). A total of 11 470 open pollinated F2-progeny trees established at three different locations, were measured for growth and adaptive traits. Breeding values were predicted for their 360 mothers, originating from a single cross of two parents. A multilevel LASSO association analysis was conducted to detect QTL using genotypes of the mothers with the corresponding phenotypes and estimated breeding values (EBVs). Different levels of genotype-by-environment (GxE) effects among sites and ages were detected for survival and height. Moderate-to-low narrow sense heritabilities and EBVs accuracies were found for all traits and all sites. We identified 18 AFLPs and 12 SNPs to be associated with QTL for one or more traits. 62 QTL were significant with percentages of variance explained ranging from 1.7 to 18.9%, mostly for traits based on phenotypic data. Two SNP-QTL showed pleiotropic effects for traits related with survival, seed and flower production. Furthermore, we detected several QTL with significant effects across multiple ages, which could be considered as strong candidate loci for early selection. The lack of reproducibility of some QTL detected across sites may be due to environmental heterogeneity and QTL-by-environment effects.

genetics↗

bioRxiv2018

HMP16SData: Efficient Access to the Human Microbiome Project through Bioconductor

Phase 1 of the NIH Human Microbiome Project (HMP) investigated 18 body subsites of 239 healthy American adults, to produce the first comprehensive reference for the composition and variation of the \"healthy\" human microbiome. Publicly-available data sets from amplicon sequencing of two 16S rRNA variable regions, with extensive controlled-access participant data, provide a reference for ongoing microbiome studies. However, utilization of these data sets can be hindered by the complex bioinformatic steps required to access, import, decrypt, and merge the various components in formats suitable for ecological and statistical analysis. The HMP16SData package provides count data for both 16S variable regions, integrated with phylogeny, taxonomy, public participant data, and controlled participant data for authorized researchers, using standard integrative Bioconductor data objects. By removing bioinformatic hurdles of data access and management, HMP16SData enables epidemiologists with only basic R skills to quickly analyze HMP data.

bioinformatics↗

bioRxiv2018

Metagenomic sequencing provides insights into the location of microbial detoxification in the gut of a small mammalian herbivore

Microbial detoxification of plant defense compounds influences the use of certain plants as food sources by herbivores. The location of microbial detoxification along the gut could have profound influences on the distribution, metabolism, and tolerance to toxic compounds. Stephens woodrats (Neotoma stephensi) specialize on juniper, which is heavily defended by numerous defensive compounds, such as oxalate, phenolics, and monoterpenes. Woodrats maintain two gut chambers harboring dense microbial communities: a foregut chamber proximal to the major site of toxin absorption, and a cecal chamber in their hindgut. We performed several experiments to investigate the location of microbial detoxification in the woodrat gut. First, we measured levels of toxins across gut chambers. Compared to food material, oxalate concentrations were immediately lower in the foregut chamber, while concentrations of terpenes remain high in the foregut, and are lowest in the cecal chamber. We also conducted metagenomic sequencing of the foregut and cecal chambers to compare microbial functions. We found that the majority of genes associated with detoxification functions were more abundant in the cecal chamber. However, some genes associated with degradation of oxalate and phenolic compounds were more abundant in the foregut. Thus, it seems that microbial detoxification may take place in various chambers depending on the class of chemical compound. We hypothesize that the location of microbial detoxification could impact the tolerance of animals to these compounds, which may have ecological and evolutionary consequences.

microbiology↗

bioRxiv2018

ampvis2: an R package to analyse and visualise 16S rRNA amplicon data

SummaryMicrobial community analysis using 16S rRNA gene amplicon sequencing is the backbone of many microbial ecology studies. Several approaches and pipelines exist for processing the raw data generated through DNA sequencing and convert the data into OTU-tables. Here we present ampvis2, an R package designed for analysis of microbial community data in OTU-table format with focus on simplicity, reproducibility, and sample metadata integration, with a minimal set of intuitive commands. Unique features include flexible heatmaps and simplified ordination. By generating plots using the ggplot2 package, ampvis2 produces publication-ready figures that can be easily customised. Furthermore, ampvis2 includes features for interactive visualisation, which can be convenient for larger, more complex data.\n\nAvailabilityampvis2 is implemented in the R statistical language and is released under the GNU A-GPL license. Documentation website and source code is maintained at: https://github.com/MadsAlbertsen/ampvis2\n\nContactMads Albertsen (ma@bio.aau.dk)

bioinformatics↗

bioRxiv2018

Integrated culturing, modeling and transcriptomics uncovers complex interactions and emergent behavior in a synthetic gut community

Whereas the composition of the human gut microbiome is relatively well resolved, predictive understanding of its response to perturbations such as diet shifts is still lacking. Here, we followed a bottom-up strategy to explore human gut community dynamics. We established a synthetic community composed of three representative human gut isolates in well-controlled conditions in vitro. We then explored species interactions by performing all mono- and pair-wise fermentation experiments and quantified with a mechanistic community model how well tri-culture dynamics was predicted from mono-culture data. With the model as a reference, we demonstrated that species grown in co-culture behaved differently than in mono-culture and confirmed their altered behavior at the transcriptional level. In addition, we showed with replicate tri-cultures and in simulations that dominance in tri-culture sensitively depends on initial conditions. Our work has important implications for gut microbial community modeling as well as ecological interaction detection from batch cultures.

bioinformatics↗

bioRxiv2018

Costless metabolic secretions as drivers of interspecies interactions in microbial ecosystems

Metabolic exchange can mediate beneficial interactions among microbes, helping explain diversity in microbial communities. These interactions are often assumed to involve a fitness cost, prompting questions on how cooperative phenotypes can be stable and withstand the emergence of cheaters. Here we use genome-scale models of metabolism to investigate whether a radically different scenario, the pervasive release of \"costless\" metabolites (i.e. those that cause no fitness cost to the producing organism), can serve as a prominent mechanism for inter-microbial interactions. By carrying out over 1 million pairwise growth simulations for 14 microbial species in a combinatorial assortment of environmental conditions, we find that there is indeed a large space of metabolites that can be secreted at no cost, which can generate ample cross-feeding opportunities. In addition to providing an atlas of putative costless interdependencies, our modeling also demonstrates that oxygen availability significantly enhances mutualistic interactions by providing more opportunities for metabolic exchange through costless metabolites, resulting in an over-representation of specific ecological network motifs. In addition to helping explain natural diversity, we show how the exchange of costless metabolites can facilitate the engineering of stable synthetic microbial consortia.

systems biology↗

bioRxiv2018

Evidence for multifactorial processes underlying phenotypic variation in bat visual opsins

Studies of opsin genes offer insights into the evolutionary history and molecular basis of vertebrate color vision, but most assume intact open reading frames equate to functional phenotypes. Despite known variation in opsin repertoires and associated visual phenotypes, the genetic basis of such patterns has not been examined at each step of the central dogma. By comparing sequences, gene expression, and protein localization across a hyperdiverse group of mammals, noctilionoid bats, we find evidence that independent losses of S-opsin arose through disruptions at different stages of protein synthesis, while maintenance relates to frugivory. Discordance between DNA, RNA, and protein reveals that the loss of short-wave sensitivity in some lineages resulted from transcriptional and post-transcriptional changes in addition to degradation of open reading frames. These mismatches imply that visual phenotypes cannot reliably be predicted from genotypes alone, and connect ecology to multiple mechanisms behind the loss of color in vertebrates.

genomics↗

bioRxiv2018

Polygenic adaptation and convergent evolution across both growth and cardiac genetic pathways in African and Asian rainforest hunter-gatherers

Different human populations facing similar environmental challenges have sometimes evolved convergent biological adaptations, for example hypoxia resistance at high altitudes and depigmented skin in northern latitudes on separate continents. The pygmy phenotype (small adult body size), a characteristic of hunter-gatherer populations inhabiting both African and Asian tropical rainforests, is often highlighted as another case of convergent adaptation in humans. However, the degree to which phenotypic convergence in this polygenic trait is due to convergent vs. population-specific genetic changes is unknown. To address this question, we analyzed high-coverage sequence data from the protein-coding portion of the genomes (exomes) of two pairs of populations, Batwa rainforest hunter-gatherers and neighboring Bakiga agriculturalists from Uganda, and Andamanese rainforest hunter-gatherers (Jarawa and Onge) and Brahmin agriculturalists from India. We observed signatures of convergent positive selection between the Batwa and Andamanese rainforest hunter-gatherers across the set of genes with annotated growth factor binding functions (p < 0.001). Unexpectedly, for the rainforest groups we also observed convergent and population-specific signatures of positive selection in pathways related to cardiac development (e.g. cardiac muscle tissue development; p = 0.001). We hypothesize that the growth hormone sub-responsiveness likely underlying the pygmy phenotype may have led to compensatory changes in cardiac pathways, in which this hormone also plays an essential role. Importantly, in the agriculturalist populations we did not observe similar patterns of positive selection on sets of genes associated with either growth or cardiac development, indicating that our results most likely reflect a history of convergent adaptation to the similar ecology of rainforest hunter-gatherers rather than a more common or general evolutionary pattern for human populations.

genomics↗

bioRxiv2018

The genetic architecture of shoot and root trait divergence between upland and lowland ecotypes of a perennial grass.

Introduction Introduction Materials and Methods Results Discussion Conclusion Author Contributions: References Adaptation to abiotic stress is an important driver of contemporary evolution in plant populations. Abiotic stressors have been implicated as driving factors in ecological speciation (Stebbins, 1952;Lexer & Fay, 2005), where populations have diverged across a number of traits, exhibit different niche characteristics, and eventually become reproductively isolated (Clausen, 1951; Lowry, 2012; Yardeni et al., 2016). Local adaptation to soil water availability is an especially important driver of plant evolution (Stebbins, 1952; Rajakaruna, 2004; ...

plant biology↗

bioRxiv2018

Unifying mutualism diversity for interpretation and prediction

Coarse-grained rules are widely used in chemistry, physics and engineering. In biology, however, such rules are less common and under-appreciated. This gap can be attributed to the difficulty in establishing general rules to encompass the immense diversity and complexity of biological systems. Even when a rule is established, it is often challenging to map it to mechanistic details and to quantify these details. We here address these challenges on a study of mutualism, an essential type of ecological interaction in nature. Using an appropriate level of abstraction, we deduced a general rule that predicts the outcomes of mutualistic systems, including coexistence and productivity. We further developed a standardized calibration procedure to apply the rule to mutualistic systems without the need to fully elucidate or characterize their mechanistic underpinnings. Our approach consistently provides explanatory and predictive power with various simulated and experimental mutualistic systems. Our strategy can pave the way for establishing and implementing other simple rules for biological systems.

systems biology↗

bioRxiv2018

Robust predictions of specialized metabolism genes through machine learning

Plant specialized metabolism (SM) enzymes produce lineage-specific metabolites with important ecological, evolutionary, and biotechnological implications. Using Arabidopsis thaliana as a model, we identified distinguishing characteristics of SM and GM (general metabolism, traditionally referred to as primary metabolism) genes through a detailed study of features including duplication pattern, sequence conservation, transcription, protein domain content, and gene network properties. Analysis of multiple sets of benchmark genes revealed that SM genes tend to be tandemly duplicated, co-expressed with their paralogs, narrowly expressed at lower levels, less conserved, and less well connected in gene networks relative to GM genes. Although the values of each of these features significantly differed between SM and GM genes, any single feature was ineffective at predicting SM from GM genes. Using machine learning methods to integrate all features, a well performing prediction model was established with a true positive rate of 0.87 and a true negative rate of 0.71. In addition, 86% of known SM genes not used to create the machine learning model were predicted as SM genes, further demonstrating its accuracy. We also demonstrated that the model could be further improved when we distinguished between SM, GM, and junction genes responsible for reactions shared by SM and GM pathways. Application of the prediction model led to the identification of 1,217 A. thaliana genes with previously unknown functions, providing a global, high-confidence estimate of SM gene content in a plant genome.\n\nSignificanceSpecialized metabolites are critical for plant-environment interactions, e.g., attracting pollinators or defending against herbivores, and are important sources of plant-based pharmaceuticals. However, it is unclear what proportion of enzyme-encoding genes play roles in specialized metabolism (SM) as opposed to general metabolism (GM) in any plant species. This is because of the diversity of specialized metabolites and the considerable number of incompletely characterized pathways responsible for their production. In addition, SM gene ancestors frequently played roles in GM. We evaluate features distinguishing SM and GM genes and build a computational model that accurately predicts SM genes. Our predictions provide candidates for experimental studies, and our modeling approach can be applied to other species that produce medicinally or industrially useful compounds.

plant biology↗

bioRxiv2018

Dissecting bacterial resistance and resilience in antibiotic responses

An essential property of microbial communities is the ability to survive a disturbance. Survival can be achieved through resistance, the ability to absorb effects of a disturbance without a significant change, or resilience, the ability to recover after being perturbed by a disturbance. These concepts have long been applied to the analysis of ecological systems, though their interpretations are often subject to debate. Here we show that this framework readily lends itself to the dissection of the bacterial response to antibiotic treatment, where both terms can be unambiguously defined. The ability to tolerate the antibiotic treatment in the short term corresponds to resistance, which primarily depends on traits associated with individual cells. In contrast, the ability to recover after being perturbed by an antibiotic corresponds to resilience, which primarily depends on traits associated with the population. This framework effectively reveals the phenotypic signatures of bacterial pathogens expressing extended spectrum {beta}-lactamases (ESBLs), when treated by a {beta}-lactam antibiotic. Our analysis has implications for optimizing treatment of these pathogens using a combination of a {beta}-lactam and a {beta}-lactamase (Bla) inhibitor. In particular, our results underscore the need to dynamically optimize combination treatments based on the quantitative features of the bacterial response to the antibiotic or the Bla inhibitor.

cell biology↗

bioRxiv2018

Introduced populations of ragweed show as much evolutionary potential as native populations

Invasive species are a global economic and ecological problem. They also offer an opportunity to understand evolutionary processes in a colonizing context. The impacts of evolutionary factors, such as genetic variation, on the invasion process are increasingly appreciated but there remain gaps in the empirical literature. The adaptive potential of populations can be quantified using genetic variance-covariance matrices (G), which encapsulate the heritable genetic variance in a population. Here, we use a multivariate, Bayesian approach to assess the adaptive potential of introduced populations of ragweed, Ambrosia artemisiifolia, a serious allergen and agricultural weed. We compared several aspects of genetic architecture and the structure of G matrices between three native and three introduced populations, based on data collected in the field in a common garden experiment. We find moderate differences in the quantitative genetic architecture among populations, but we do not find that introduced populations suffer from a limited adaptive potential compared to native populations. Ragweed has an annual life history, is an obligate outcrosser, and produces billions of seeds and pollen grains per. These characteristics, combined with the significant additive genetic variance documented here, suggest ragweed will be able to respond quickly to selection pressures in both its native and introduced ranges.

evolutionary biology↗