Oral administration of the commensal Alistipes onderdonkii prolongs allograft survival.

Intestinal commensals can exert immunomodulatory effects on the host, with beneficial or detrimental consequences depending on underlying diseases. We have previously correlated longer survival of minor mismatched skin grafts in mice with the presence of an intestinal commensal bacterium, Alistipes onderdonkii. In this study, we investigated its sufficiency and mechanism of action. Oral administration of A onderdonkii strain DSM19147 but not DSM108265 was sufficient to prolong minor mismatched skin graft survival through inhibition of tumor necrosis factor production. Through metabolomic and metagenomic comparisons between DSM19147 and DSM108265, we identified candidate gene products associated with the anti-inflammatory effect of DSM19147. A onderdonkii DSM19147 can lower inflammation both at a steady state and after transplantation and may serve as an anti-inflammatory probiotic beneficial for transplant recipients.

Limited introgression from non-native commercial strains and signatures of adaptation in the key pollinator Bombus terrestris.

Insect pollination is fundamental for natural ecosystems and agricultural crops. The bumblebee species Bombus terrestris has become a popular choice for commercial crop pollination worldwide due to its effectiveness and ease of mass rearing. Bumblebee colonies are mass produced for the pollination of more than 20 crops and imported into over 50 countries including countries outside their native ranges, and the risk of invasion by commercial non-native bumblebees is considered an emerging issue for global conservation and biological diversity. Here, we use genome-wide data from seven wild populations close to and far from farms using commercial colonies, as well as commercial populations, to investigate the implications of utilizing commercial bumblebee subspecies in the UK. We find evidence for generally low levels of introgression between commercial and wild bees, with higher admixture proportions in the bees occurring close to farms. We identify genomic regions putatively involved in local and global adaptation, and genes in locally adaptive regions were found to be enriched for functions related to taste receptor activity, oxidoreductase activity, fatty acid and lipid biosynthetic processes. Despite more than 30 years of bumblebee colony importation into the UK, we observe low impact on the genetic integrity of local B. terrestris populations, but we highlight that even limited introgression might negatively affect locally adapted populations.

A continental-scale survey of Wolbachia infections in blue butterflies reveals evidence of interspecific transfer and invasion dynamics.

Infections by maternally inherited bacterial endosymbionts, especially Wolbachia, are common in insects and other invertebrates but infection dynamics across species ranges are largely under studied. Specifically, we lack a broad understanding of the origin of Wolbachia infections in novel hosts, and the historical and geographical dynamics of infections that are critical for identifying the factors governing their spread. We used Genotype-by-Sequencing data from previous population genomics studies for range-wide surveys of Wolbachia presence and genetic diversity in North American butterflies of the genus Lycaeides. As few as one sequence read identified by assembly to a Wolbachia reference genome provided high accuracy in detecting infections in host butterflies as determined by confirmatory PCR tests, and maximum accuracy was achieved with a threshold of only 5 sequence reads per host individual. Using this threshold, we detected Wolbachia in all but 2 of the 107 sampling localities spanning the continent, with infection frequencies within populations ranging from 0% to 100% of individuals, but with most localities having high infection frequencies (mean = 91% infection rate). Three major lineages of Wolbachia were identified as separate strains that appear to represent 3 separate invasions of Lycaeides butterflies by Wolbachia. Overall, we found extensive evidence for acquisition of Wolbachia through interspecific transfer between host lineages. Strain wLycC was confined to a single butterfly taxon, hybrid lineages derived from it, and closely adjacent populations in other taxa. While the other 2 strains were detected throughout the rest of the continent, strain wLycB almost always co-occurred with wLycA. Our demographic modeling suggests wLycB is a recent invasion. Within strain wLycA, the 2 most frequent haplotypes are confined almost exclusively to separate butterfly taxa with haplotype A1 observed largely in Lycaeides melissa and haplotype A2 observed most often in Lycaeides idas localities, consistent with either cladogenic mode of infection acquisition from a common ancestor or by hybridization and accompanying mutation. More than 1 major Wolbachia strain was observed in 15 localities. These results demonstrate the utility of using resequencing data from hosts to quantify Wolbachia genetic variation and infection frequency and provide evidence of multiple colonizations of novel hosts through hybridization between butterfly lineages and complex dynamics between Wolbachia strains.

Model-based genotype and ancestry estimation for potential hybrids with mixed-ploidy.

Non-random mating among individuals can lead to spatial clustering of genetically similar individuals and population stratification. This deviation from panmixia is commonly observed in natural populations. Consequently, individuals can have parentage in single populations or involving hybridization between differentiated populations. Accounting for this mixture and structure is important when mapping the genetics of traits and learning about the formative evolutionary processes that shape genetic variation among individuals and populations. Stratified genetic relatedness among individuals is commonly quantified using estimates of ancestry that are derived from a statistical model. Development of these models for polyploid and mixed-ploidy individuals and populations has lagged behind those for diploids. Here, we extend and test a hierarchical Bayesian model, called entropy, which can use low-depth sequence data to estimate genotype and ancestry parameters in autopolyploid and mixed-ploidy individuals (including sex chromosomes and autosomes within individuals). Our analysis of simulated data illustrated the trade-off between sequencing depth and genome coverage and found lower error associated with low-depth sequencing across a larger fraction of the genome than with high-depth sequencing across a smaller fraction of the genome. The model has high accuracy and sensitivity as verified with simulated data and through analysis of admixture among populations of diploid and tetraploid Arabidopsis arenosa.

Dirichlet-multinomial modelling outperforms alternatives for analysis of microbiome and other ecological count data.

Molecular ecology regularly requires the analysis of count data that reflect the relative abundance of features of a composition (e.g., taxa in a community, gene transcripts in a tissue). The sampling process that generates these data can be modelled using the multinomial distribution. Replicate multinomial samples inform the relative abundances of features in an underlying Dirichlet distribution. These distributions together form a hierarchical model for relative abundances among replicates and sampling groups. This type of Dirichlet-multinomial modelling (DMM) has been described previously, but its benefits and limitations are largely untested. With simulated data, we quantified the ability of DMM to detect differences in proportions between treatment and control groups, and compared the efficacy of three computational methods to implement DMM-Hamiltonian Monte Carlo (HMC), variational inference (VI), and Gibbs Markov chain Monte Carlo. We report that DMM was better able to detect shifts in relative abundances than analogous analytical tools, while identifying an acceptably low number of false positives. Among methods for implementing DMM, HMC provided the most accurate estimates of relative abundances, and VI was the most computationally efficient. The sensitivity of DMM was exemplified through analysis of previously published data describing lung microbiomes. We report that DMM identified several potentially pathogenic, bacterial taxa as more abundant in the lungs of children who aspirated foreign material during swallowing; these differences went undetected with different statistical approaches. Our results suggest that DMM has strong potential as a statistical method to guide inference in molecular ecology.