Duration of rupture of membranes and microbiome transmission to the newborn: A prospective study.

OBJECTIVE: To assess whether labour variables (i.e. individuals characteristics, labour characteristics and medical interventions) impact maternal and newborn microbiomes. DESIGN: Prospective monocentric study. SETTING: Saint-Joseph Hospital tertiary maternity unit, in Paris, France. POPULATION: All consecutive primiparous women with a physiological pregnancy and term labour from 15 April to 1 June 2017. METHODS: 16S ribosomal RNA gene sequencing of the maternal vaginal, newborn skin and newborn oral microbiomes from 58 mother-baby dyads. MAIN OUTCOME MEASURES: Analysis of the effects of 19 labour variables on the composition and diversity of these microbiomes. RESULTS: The 19 labour variables explained a significant part of the variability in the vaginal, newborn oral and skin microbiomes (44%-67%). Strikingly, duration of rupture of membranes was the single factor that explained the greatest variability (adjusted R2: 7.7%-8.4%, p ≤ 0.002) and conditioned, by itself, the compositions of the three microbiomes under study. Long duration of rupture of membranes was specifically associated with a lower relative abundance of the Lactobacillus genus (1.7-fold to 68-fold reduction, p < 0.0001) as well as an increase in microbiome diversity, including genera implicated in nosocomial infections. The effects of duration of rupture of membranes were also present in newborns delivered by non-elective caesarean section. CONCLUSIONS: Maternal and newborn microbiomes were greatly affected by labour variables. Duration of rupture of membranes, even in non-elective caesarean sections, should be considered in epidemiological and microbiological studies, as well as in vaginal seeding practices.

Aging at Evolutionary Crossroads: Longitudinal Gene Co-expression Network Analyses of Proximal and Ultimate Causes of Aging in Bats.

How, when, and why do organisms, their tissues, and their cells age remain challenging issues, although researchers have identified multiple mechanistic causes of aging, and three major evolutionary theories have been developed to unravel the ultimate causes of organismal aging. A central hypothesis of these theories is that the strength of natural selection decreases with age. However, empirical evidence on when, why, and how organisms age is phylogenetically limited, especially in natural populations. Here, we developed generic comparisons of gene co-expression networks that quantify and dissect the heterogeneity of gene co-expression in conspecific individuals from different age-classes to provide topological evidence about some mechanical and fundamental causes of organismal aging. We applied this approach to investigate the complexity of some proximal and ultimate causes of aging phenotypes in a natural population of the greater mouse-eared bat Myotis myotis, a remarkably long-lived species given its body size and metabolic rate, with available longitudinal blood transcriptomes. M. myotis gene co-expression networks become increasingly fragmented with age, suggesting an erosion of the strength of natural selection and a general dysregulation of gene co-expression in aging bats. However, selective pressures remain sufficiently strong to allow successive emergence of homogeneous age-specific gene co-expression patterns, for at least 7 years. Thus, older individuals from long-lived species appear to sit at an evolutionary crossroad: as they age, they experience both a decrease in the strength of natural selection and a targeted selection for very specific biological processes, further inviting to refine a central hypothesis in evolutionary aging theories.

CompositeSearch: A Generalized Network Approach for Composite Gene Families Detection.

Genes evolve by point mutations, but also by shuffling, fusion, and fission of genetic fragments. Therefore, similarity between two sequences can be due to common ancestry producing homology, and/or partial sharing of component fragments. Disentangling these processes is especially challenging in large molecular data sets, because of computational time. In this article, we present CompositeSearch, a memory-efficient, fast, and scalable method to detect composite gene families in large data sets (typically in the range of several million sequences). CompositeSearch generalizes the use of similarity networks to detect composite and component gene families with a greater recall, accuracy, and precision than recent programs (FusedTriplets and MosaicFinder). Moreover, CompositeSearch provides user-friendly quality descriptions regarding the distribution and primary sequence conservation of these gene families allowing critical biological analyses of these data.

Paternity Analysis of Wood Turtles (Glyptemys insculpta) Reveals Complex Mating Patterns.

Mating system characteristics are of great importance as they may influence male and female reproductive success and reproductive isolation. The wood turtle (Glyptemys insculpta) is a terrestrial freshwater species listed as endangered by the International Union for Conservation of Nature. Considering its conservation status and the paucity of information currently available on parentage relationship for the species, we performed a microsatellite analysis to study the mating system of wood turtles in the Shawinigan River (Québec). We sampled 38 clutches over 2 years (14 in 2006 and 24 in 2007), for a total of 248 offspring genotyped with 7 microsatellite loci. The reconstructed genotypes of the fathers revealed that reproductive success in the sampled clutches varied greatly between males and are positively correlated with the number of mates and clutches sired. Frequency of multiple paternity was estimated at 37% through a consensus of 3 different estimation methods. Positive correlation was observed between the genetic diversity of clutches and the number of fathers. Repeat paternity, however, was observed in 88% of the clutches by the same female in successive years, which suggests either a frequent use of sperm storage, or remating with the same partner in successive years.

Using hybridization networks to retrace the evolution of Indo-European languages.

BACKGROUND: Curious parallels between the processes of species and language evolution have been observed by many researchers. Retracing the evolution of Indo-European (IE) languages remains one of the most intriguing intellectual challenges in historical linguistics. Most of the IE language studies use the traditional phylogenetic tree model to represent the evolution of natural languages, thus not taking into account reticulate evolutionary events, such as language hybridization and word borrowing which can be associated with species hybridization and horizontal gene transfer, respectively. More recently, implicit evolutionary networks, such as split graphs and minimal lateral networks, have been used to account for reticulate evolution in linguistics. RESULTS: Striking parallels existing between the evolution of species and natural languages allowed us to apply three computational biology methods for reconstruction of phylogenetic networks to model the evolution of IE languages. We show how the transfer of methods between the two disciplines can be achieved, making necessary methodological adaptations. Considering basic vocabulary data from the well-known Dyen's lexical database, which contains word forms in 84 IE languages for the meanings of a 200-meaning Swadesh list, we adapt a recently developed computational biology algorithm for building explicit hybridization networks to study the evolution of IE languages and compare our findings to the results provided by the split graph and galled network methods. CONCLUSION: We conclude that explicit phylogenetic networks can be successfully used to identify donors and recipients of lexical material as well as the degree of influence of each donor language on the corresponding recipient languages. We show that our algorithm is well suited to detect reticulate relationships among languages, and present some historical and linguistic justification for the results obtained. Our findings could be further refined if relevant syntactic, phonological and morphological data could be analyzed along with the available lexical data.

Most genetic roots of fungal and animal aging are hundreds of millions of years old according to phylostratigraphy analyses of aging networks.

Few studies have systematically analyzed how old aging is. Gaining a more accurate knowledge about the natural history of aging could however have several payoffs. This knowledge could unveil lineages with dated genetic hardware, possibly maladapted to current environmental challenges, and also uncover "phylogenetic modules of aging," i.e., naturally evolved pathways associated with aging or longevity from a single ancestry, with translational interest for anti-aging therapies. Here, we approximated the natural history of the genetic hardware of aging for five model fungal and animal species. We propose a lower-bound estimate of the phylogenetic age of origination for their protein-encoding gene families and protein-protein interactions. Most aging-associated gene families are hundreds of million years old, older than the other gene families from these genomes. Moreover, we observed a form of punctuated evolution of the aging hardware in all species, as aging-associated families born at specific phylogenetic times accumulate preferentially in genomes. Most protein-protein interactions between aging genes are also old, and old aging-associated proteins showed a reduced potential to contribute to novel interactions associated with aging, suggesting that aging networks are at risk of losing in evolvability over long evolutionary periods. Finally, due to reshuffling events, aging networks presented a very limited phylogenetic structure that challenges the detection of "maladaptive" or "adaptative" phylogenetic modules of aging in present-day genomes.

Network analyses unveil ageing-associated pathways evolutionarily conserved from fungi to animals.

The genetic roots of the diverse paces and shapes of ageing and of the large variations in longevity observed across the tree of life are poorly understood. Indeed, pathways associated with ageing/longevity are incompletely known, both in terms of their constitutive genes/proteins and of their molecular interactions. Moreover, there is limited overlap between the genes constituting these pathways across mammals. Yet, dedicated comparative analyses might still unravel evolutionarily conserved, important pathways associated with longevity or ageing. Here, we used an original strategy with a double evolutionary and systemic focus to analyse protein interactions associated with ageing or longevity during the evolution of five species of Opisthokonta. We ranked these proteins and interactions based on their evolutionary conservation and centrality in past and present protein-protein interaction (PPI) networks, providing a big systemic picture of the evolution of ageing and longevity pathways that identified which pathways emerged in which Opisthokonta lineages, were conserved, and/or central. We confirmed that longevity/ageing-associated proteins (LAPs), be they pro- or anti-longevity, are highly central in extant PPI, consistently with the antagonistic pleiotropy theory of ageing, and identified key antagonistic regulators of ageing/longevity, 52 of which with homologues in humans. While some highly central LAPs were evolutionarily conserved for over a billion years, we report a clear transition in the functionally important components of ageing/longevity within bilaterians. We also predicted 487 novel evolutionarily conserved LAPs in humans, 54% of which are more central than mTOR, and 138 of which are druggable, defining new potential targets for anti-ageing treatments in humans.

Harvesting evolutionary signals in a forest of prokaryotic gene trees.

Phylogenomic studies produce increasingly large phylogenetic forests of trees with patchy taxonomical sampling. Typically, prokaryotic data generate thousands of gene trees of all sizes that are difficult, if not impossible, to root. Their topologies do not match the genealogy of lineages, as they are influenced not only by duplication, losses, and vertical descent but also by lateral gene transfer (LGT) and recombination. Because this complexity in part reflects the diversity of evolutionary processes, the study of phylogenetic forests is thus a great opportunity to improve our understanding of prokaryotic evolution. Here, we show how the rich evolutionary content of such novel phylogenetic objects can be exploited through the development of new approaches designed specifically for extracting the multiple evolutionary signals present in the forest of life, that is, by slicing up trees into remarkable bits and pieces: clans, slices, and clips. We harvested a forest of 6,901 unrooted gene trees comprising up to 100 prokaryotic genomes (41 archaea and 59 bacteria) to search for evolutionary events that a species tree would not account for. We identified 1) trees and partitions of trees that reflected the lifestyle of organisms rather than their taxonomy, 2) candidate lifestyle-specific genetic modules, used by distinct unrelated organisms to adapt to the same environment, 3) gene families, nonrandomly distributed in the functional space, that were frequently exchanged between archaea and bacteria, sometimes without major changes in their sequences. Finally, 4) we reconstructed polarized networks of genetic partnerships between archaea and bacteria to describe some of the rules affecting LGT between these two Domains.

Applying novel connectivity networks to wood turtle populations to provide comprehensive conservation management strategies for species at risk.

Genetic diversity within and among populations is frequently used in prioritization processes to rank populations based on their vulnerability or distinctiveness, however, connectivity and gene flow are rarely considered within these frameworks. Using a wood turtle (Glyptemys insculpta) population graph, we introduce BRIDES as a new tool to evaluate populations for conservation purpose without focusing solely on individual nodes. BRIDES characterizes different types of shortest paths among the nodes of a subgraph and compares the shortest paths among the same nodes in a complete network. The main objectives of this study were to (1) introduce a BRIDES selection process to assist conservation biologists in the prioritization of populations, and (2) use different centrality indices and node removal statistics to compare BRIDES results and assess gene flow among wood turtle populations. We constructed six population subgraphs and used a stepwise selection algorithm to choose the optimal number of additional nodes, representing different populations, required to maximize network connectivity under different weighting schemes. Our results demonstrate the robustness of the BRIDES selection process for a given scenario, while inconsistencies were observed among node-based metrics. Results showed repeated selection of certain wood turtle populations, which could have not been predicted following only genetic diversity and distinctiveness estimation, node-based metrics and node removal analysis. Contrary to centrality measures focusing on static networks, BRIDES allowed for the analysis of evolving networks. To our knowledge, this study is the first to apply graph theory for turtle conservation genetics. We show that population graphs can reveal complex gene flow dynamics and population resiliency to local extinction. As such, BRIDES offers an interesting complement to node-based metrics and node removal to better understand the global processes at play when addressing population prioritization frameworks.

Proximate Drivers of Population-Level Lizard Gut Microbial Diversity: Impacts of Diet, Insularity, and Local Environment.

Diet has been suggested to be an important driver of variation in microbiota composition in mammals. However, whether this is a more general phenomenon and how fast changes in gut microbiota occur with changes in diet remains poorly understood. Forty-nine years ago, ten lizards of the species Podarcis siculus were taken from the island of Pod Kopiste and introduced onto the island of Pod Mrcaru (Croatia). The introduced population underwent a significant dietary shift, and their descendants became omnivorous (consuming up to 80% plant material during summer). Variation in their gut microbiota has never been investigated. To elucidate the possible impact on the gut microbiota of this rapid change in diet, we compared the microbiota (V4 region of the 16S rRNA gene) of P. siculus from Pod Mrcaru, Pod Kopiste, and the mainland. In addition, we explored other drivers of variation in gut microbiota including insularity, the population of origin, and the year of sampling. Alpha-diversity analyses showed that the microbial diversity of omnivorous lizards was higher than the microbial diversity of insectivorous lizards. Moreover, omnivorous individuals harbored significantly more Methanobrevibacter. The gut microbial diversity of insectivorous lizards was nonetheless more heterogeneous. Insectivorous lizards on the mainland had different gut microbial communities than their counterparts on the island of Pod Kopiste. Bacillus and Desulfovibrio were more abundant in the gut microbiota from insular lizards compared to mainland lizards. Finally, we showed that the population of origin was also an important driver of the composition of the gut microbiota. The dietary shift that occurred in the introduced population of P. siculus has had a detectable impact on the gut microbiota, but other factors such as insularity and the population of origin also contributed to differences in the gut microbial composition of these lizards, illustrating the multifactorial nature of the drivers of variation in gut microbiota. Overall, our data show that changes in gut microbiota may take place on ecological timescales. Yet, diet is only one of many factors driving variation in gut microbiota across populations.

The performance of the Congruence Among Distance Matrices (CADM) test in phylogenetic analysis.

BACKGROUND: CADM is a statistical test used to estimate the level of Congruence Among Distance Matrices. It has been shown in previous studies to have a correct rate of type I error and good power when applied to dissimilarity matrices and to ultrametric distance matrices. Contrary to most other tests of incongruence used in phylogenetic analysis, the null hypothesis of the CADM test assumes complete incongruence of the phylogenetic trees instead of congruence. In this study, we performed computer simulations to assess the type I error rate and power of the test. It was applied to additive distance matrices representing phylogenies and to genetic distance matrices obtained from nucleotide sequences of different lengths that were simulated on randomly generated trees of varying sizes, and under different evolutionary conditions. RESULTS: Our results showed that the test has an accurate type I error rate and good power. As expected, power increased with the number of objects (i.e., taxa), the number of partially or completely congruent matrices and the level of congruence among distance matrices. CONCLUSIONS: Based on our results, we suggest that CADM is an excellent candidate to test for congruence and, when present, to estimate its level in phylogenomic studies where numerous genes are analysed simultaneously.

Retrieving a mitogenomic mammal tree using composite taxa.

Supermatrices are often characterized by a large amount of missing data. One possible approach to minimize such missing data is to create composite taxa. These taxa are formed by sampling sequences from different species in order to obtain a composite sequence that includes a maximum number of genes. Although this approach is increasingly used, its accuracy has rarely been tested and some authors prefer to analyze incomplete supermatrices by coding unavailable sequences as missing. To further validate the composite taxon approach, it was applied to complete mitochondrial matrices of 102 mammal species representing 93 families with varying amount of missing data. On average, missing data and composite matrices showed similar congruence to model trees obtained from the complete sequence matrix. As expected, the level of congruence to model trees decreased as missing data increased, with both approaches. We conclude that the composite taxon approach is worth considering in a phylogenomic context since it performs well and reduces computing time when compared to missing data matrices.

Weighted bootstrapping: a correction method for assessing the robustness of phylogenetic trees.

BACKGROUND: Non-parametric bootstrapping is a widely-used statistical procedure for assessing confidence of model parameters based on the empirical distribution of the observed data 1 and, as such, it has become a common method for assessing tree confidence in phylogenetics 2. Traditional non-parametric bootstrapping does not weigh each tree inferred from resampled (i.e., pseudo-replicated) sequences. Hence, the quality of these trees is not taken into account when computing bootstrap scores associated with the clades of the original phylogeny. As a consequence, traditionally, the trees with different bootstrap support or those providing a different fit to the corresponding pseudo-replicated sequences (the fit quality can be expressed through the LS, ML or parsimony score) contribute in the same way to the computation of the bootstrap support of the original phylogeny. RESULTS: In this article, we discuss the idea of applying weighted bootstrapping to phylogenetic reconstruction by weighting each phylogeny inferred from resampled sequences. Tree weights can be based either on the least-squares (LS) tree estimate or on the average secondary bootstrap score (SBS) associated with each resampled tree. Secondary bootstrapping consists of the estimation of bootstrap scores of the trees inferred from resampled data. The LS and SBS-based bootstrapping procedures were designed to take into account the quality of each "pseudo-replicated" phylogeny in the final tree estimation. A simulation study was carried out to evaluate the performances of the five weighting strategies which are as follows: LS and SBS-based bootstrapping, LS and SBS-based bootstrapping with data normalization and the traditional unweighted bootstrapping. CONCLUSIONS: The simulations conducted with two real data sets and the five weighting strategies suggest that the SBS-based bootstrapping with the data normalization usually exhibits larger bootstrap scores and a higher robustness compared to the four other competing strategies, including the traditional bootstrapping. The high robustness of the normalized SBS could be particularly useful in situations where observed sequences have been affected by noise or have undergone massive insertion or deletion events. The results provided by the four other strategies were very similar regardless the noise level, thus also demonstrating the stability of the traditional bootstrapping method.

The use and validity of composite taxa in phylogenetic analysis.

In phylogenetic analysis, one possible approach to minimize missing data in DNA supermatrices consists in sampling sequences from different species to obtain a complete sequence for all genes included in the study. We refer to those complete sequences as composite taxa because DNA sequences that are combined belong to different species. An alternative approach is to analyze incomplete supermatrices by coding unavailable DNA sequences as missing. The accuracy of phylogenetic trees estimated using matrices that include composite taxa has recently been questioned, and the best approach for analyzing incomplete supermatrices is highly debated. Through computer simulations, we compared the phylogenetic accuracy of the 2 competing approaches. We explored the effect of composite taxa when inferring higher level relationships, that is, relationships between monophyletic groups. DNA sequences were simulated on a 42-taxon model tree and incomplete supermatrices containing different percentages of missing data were generated. These incomplete supermatrices were analyzed either by coding the missing data with "?" or by reducing the amount of missing data through the combination of 2 or more taxa to generate composite taxa. Of 180 comparisons (18 simulation cases with 2 different inference methods and 5 levels of incompleteness), we observed significantly higher phylogenetic accuracies for composite matrices in 46 comparisons, whereas missing data matrices outperformed composites in 8 comparisons. In all other cases, the phylogenetic accuracy obtained with composite matrices was not significantly different from that of missing data matrices. This study demonstrates that composite taxa represent an interesting approach to minimize the amount of missing data in supermatrices and we suggest that it is the optimal approach to use in phylogenomic studies to reduce computing time.

Microsatellite analyses provide evidence of male-biased dispersal in the radiated tortoise Astrochelys radiata (Chelonia: Testudinidae).

Dispersal is a major force in shaping the genetic structure and dynamics of species; thus, its understanding is critical in formulating appropriate conservation strategies. In many species, sexes do not face the same evolutionary pressures, and consequently dispersal is often asymmetrical between males and females. This is well documented in birds and mammals but has seldom been investigated in other taxa, including reptiles and, more specifically, nonmarine chelonians. In these species, nest-site fidelity observations are frequent but still remain to be associated with natal homing. Here, we tested for sex-biased dispersal in the radiated tortoise (Astrochelys radiata) from southern Madagascar. Using data from 13 microsatellite markers, we investigated patterns of relatedness between sexes in 2 populations. All Mantel tests indicated significant isolation by distance at the individual level in females but not in males. Furthermore, spatial autocorrelation analyses and 2 analytical approaches designed to assess general trends in sex-specific dispersal also supported male-biased dispersal. On the other hand, comparisons of overall genetic structure among sampling sites did not provide conclusive support for greater philopatry in females, but these tests may have low statistical power because of methodological and biological constraints. Radiated tortoises appear to be both polyandrous and polygynous, and evolutionary processes that may lead to a sex bias in dispersal are discussed with respect to tortoise breeding biology. Female natal homing is hypothesized as a key trait explaining greater female philopatry in A. radiata. These findings highlight the necessity of additional research on natal homing in tortoises, a behavioral trait with direct implications for conservation.

Antifungal Potential of the Skin Microbiota of Hibernating Big Brown Bats (Eptesicus fuscus) Infected With the Causal Agent of White-Nose Syndrome.

Little is known about skin microbiota in the context of the disease white-nose syndrome (WNS), caused by the fungus Pseudogymnoascus destructans (Pd), that has caused enormous declines of hibernating North American bats over the past decade. Interestingly, some hibernating species, such as the big brown bat (Eptesicus fuscus), appear resistant to the disease and their skin microbiota could play a role. However, a comprehensive analysis of the skin microbiota of E. fuscus in the context of Pd has not been done. In January 2017, we captured hibernating E. fuscus, sampled their skin microbiota, and inoculated them with Pd or sham inoculum. We allowed the bats to hibernate in the lab under controlled conditions for 11 weeks and then sampled their skin microbiota to test the following hypotheses: (1) Pd infection would not disrupt the skin microbiota of Pd-resistant E. fuscus; and (2) microbial taxa with antifungal properties would be abundant both before and after inoculation with Pd. Using high-throughput 16S rRNA gene sequencing, we discovered that beta diversity of Pd-inoculated bats changed more over time than that of sham-inoculated bats. Still, the most abundant taxa in the community were stable throughout the experiment. Among the most abundant taxa, Pseudomonas and Rhodococcus are known for antifungal potential against Pd and other fungi. Thus, in contrast to hypothesis 1, Pd infection destabilized the skin microbiota but consistent with hypothesis 2, bacteria with known antifungal properties remained abundant and stable on the skin. This study is the first to provide a comprehensive survey of skin microbiota of E. fuscus, suggesting potential associations between the bat skin microbiota and resistance to the Pd infection and WNS. These results set the stage for future studies to characterize microbiota gene expression, better understand mechanisms of resistance to WNS, and help develop conservation strategies.

Corrigendum: Antifungal Potential of the Skin Microbiota of Hibernating Big Brown Bats (Eptesicus fuscus) Infected With the Causal Agent of White-Nose Syndrome.

[This corrects the article DOI: 10.3389/fmicb.2020.01776.].

Introducing Trait Networks to Elucidate the Fluidity of Organismal Evolution Using Palaeontological Data.

Explaining the evolution of animals requires ecological, developmental, paleontological, and phylogenetic considerations because organismal traits are affected by complex evolutionary processes. Modeling a plurality of processes, operating at distinct time-scales on potentially interdependent traits, can benefit from approaches that are complementary treatments to phylogenetics. Here, we developed an inclusive network approach, implemented in the command line software ComponentGrapher, and analyzed trait co-occurrence of rhinocerotoid mammals. We identified stable, unstable, and pivotal traits, as well as traits contributing to complexes, that may follow to a common developmental regulation, that point to an early implementation of the postcranial Bauplan among rhinocerotoids. Strikingly, most identified traits are highly dissociable, used repeatedly in distinct combinations and in different taxa, which usually do not form clades. Therefore, the genes encoding these traits are likely recruited into novel gene regulation networks during the course of evolution. Our evo-systemic framework, generalizable to other evolved organizations, supports a pluralistic modeling of organismal evolution, including trees and networks.

Hundreds of novel composite genes and chimeric genes with bacterial origins contributed to haloarchaeal evolution.

BACKGROUND: Haloarchaea, a major group of archaea, are able to metabolize sugars and to live in oxygenated salty environments. Their physiology and lifestyle strongly contrast with that of their archaeal ancestors. Amino acid optimizations, which lowered the isoelectric point of haloarchaeal proteins, and abundant lateral gene transfers from bacteria have been invoked to explain this deep evolutionary transition. We use network analyses to show that the evolution of novel genes exclusive to Haloarchaea also contributed to the evolution of this group. RESULTS: We report the creation of 320 novel composite genes, both early in the evolution of Haloarchaea during haloarchaeal genesis and later in diverged haloarchaeal groups. One hundred and twenty-six of these novel composite genes derived from genetic material from bacterial genomes. These latter genes, largely involved in metabolic functions but also in oxygenic lifestyle, constitute a different gene pool from the laterally acquired bacterial genes formerly identified. These novel composite genes were likely advantageous for their hosts, since they show significant residence times in haloarchaeal genomes-consistent with a long phylogenetic history involving vertical descent and lateral gene transfer-and encode proteins with optimized isoelectric points. CONCLUSIONS: Overall, our work encourages a systematic search for composite genes across all archaeal major groups, in order to better understand the origins of novel prokaryotic genes, and in order to test to what extent archaea might have adjusted their lifestyles by incorporating and recycling laterally acquired bacterial genetic fragments into new archaeal genes.

Enrichment of beneficial bacteria in the skin microbiota of bats persisting with white-nose syndrome.

BACKGROUND: Infectious diseases of wildlife are increasing worldwide with implications for conservation and human public health. The microbiota (i.e. microbial community living on or in a host) could influence wildlife disease resistance or tolerance. White-nose syndrome (WNS), caused by the fungus Pseudogymnoascus destructans (Pd), has killed millions of hibernating North American bats since 2007. We characterized the skin microbiota of naïve, pre-WNS little brown bats (Myotis lucifugus) from three WNS-negative hibernation sites and persisting, previously exposed bats from three WNS-positive sites to test the hypothesis that the skin microbiota of bats shifts following WNS invasion. RESULTS: Using high-throughput 16S rRNA gene sequencing on 66 bats and 11 environmental samples, we found that hibernation site strongly influenced the composition and diversity of the skin microbiota. Bats from WNS-positive and WNS-negative sites differed in alpha and beta diversity, as well as in microbiota composition. Alpha diversity was reduced in persisting, WNS-positive bats, and the microbiota profile was enriched with particular taxa such Janthinobacterium, Micrococcaceae, Pseudomonas, Ralstonia, and Rhodococcus. Some of these taxa are recognized for their antifungal activity, and specific strains of Rhodococcus and Pseudomonas are known to inhibit Pd growth. Composition of the microbial community in the hibernaculum environment and the community on bat skin was superficially similar but differed in relative abundance of some bacterial taxa. CONCLUSIONS: Our results are consistent with the hypothesis that Pd invasion leads to a shift in the skin microbiota of surviving bats and suggest the possibility that the microbiota plays a protective role for bats facing WNS. The detection of what appears to be enrichment of beneficial bacteria in the skin microbiota of persisting bats is a promising discovery for species re-establishment. Our findings highlight not only the potential value of management actions that might encourage transmission, growth, and establishment of beneficial bacteria on bats, and within hibernacula, but also the potential risks of such management actions.