Background Knowledge is growing on how gut microbiota are established, but the effects of maternal symbiotic microbes throughout early microbial successions in birds remain elusive. In this study, we examined the contributions and transmission modes of maternal microbes into the neonatal microbiota of a passerine, the zebra finch (Taeniopygia guttata), based on fostering experiments. Results Using 16S rRNA amplicon sequencing, we found that zebra finch chicks raised by their biological or foster parents (the society finch Lonchura striata domestica) had gut microbial communities converging with those of the parents that reared them. Moreover, source-tracking models revealed high contribution of zebra finches’ oral cavity/crop microbiota to their chicks’ early gut microbiota, which were largely replaced by the parental gut microbiota at later stages. The results suggest that oral feeding only affects the early stage of hatchling gut microbial development. Conclusions Our study indicates that passerine chicks mainly acquire symbionts through indirect maternal transmission—passive environmental uptake from nests that were smeared with the intestinal and cloacal microbes of parents that raised them. Gut microbial diversity was low in hand-reared chicks, emphasizing the importance of parental care in shaping the gut microbiota. In addition, several probiotics were found in chicks fostered by society finches, which are excellent foster parents for other finches in bird farms and hosts of brood parasitism by zebra finches in aviaries; this finding implies that avian species that can transfer probiotics to chicks may become selectively preferred hosts of brood parasitism in nature.

BackgroundAnnual hibernation is an adaptation that helps many animals conserve energy during food shortage in winter. This natural cycle is also accompanied by a remodeling of the intestinal immune system, which is an aspect of host biology that is both influenced by, and can itself influence, the microbiota. In amphibians, the bacteria in the intestinal tract show a drop in bacterial counts. The proportion of pathogenic bacteria is greater in hibernating frogs than that found in nonhibernating frogs. This suggests that some intestinal gut microbes in amphibians can be maintained and may contribute to the functions in this closed ecosystem during hibernation. However, these results were derived from culture-based approaches that only covered a small portion of bacteria in the intestinal tract.MethodsIn this study, we use a more comprehensive analysis, including bacterial appearance and functional prediction, to reveal the global changes in gut microbiota during artificial hibernation via high-throughput sequencing technology.ResultsOur results suggest that artificial hibernation in the brown tree frog (Polypedates megacephalus) could reduce microbial diversity, and artificially hibernating frogs tend to harbor core operational taxonomic units that are rarely distributed among nonhibernating frogs. In addition, artificial hibernation increased significantly the relative abundance of the red-leg syndrome-related pathogenic genus Citrobacter. Furthermore, functional predictions via PICRUSt and Tax4Fun suggested that artificial hibernation has effects on metabolism, disease, signal transduction, bacterial infection, and primary immunodeficiency.ConclusionsWe infer that artificial hibernation may impose potential effects on primary immunodeficiency and increase the risk of bacterial infections in the brown tree frog.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-016-3318-6) contains supplementary material, which is available to authorized users.

Growing evidence points out that the capacity of organisms to acclimate or adapt to new habitat conditions basically depends on their phenomic plasticity attributes, of which their gut commensal microbiota might be an essential impact factor. Especially in aquatic organisms, which are in direct and continual contact with the aquatic environment, the complex and dynamic microbiota have significant effects on health and development. However, an understanding of the relative contribution of internal sorting (host genetic) and colonization (environmental) processes is still unclear. To understand how microbial communities differ in response to rapid environmental change, we surveyed and studied the environmental and gut microbiota of native and habitat-exchanged shrimp (Macrobrachium nipponense) using 16S rRNA amplicon sequencing on the Illumina MiSeq platform. Corresponding with microbial diversity of their living water areas, the divergence in gut microbes of lake-to-river shrimp (CK) increased, while that of river-to-lake shrimp (KC) decreased. Importantly, among the candidate environment specific gut microbes in habitat-exchanged shrimp, over half of reads were associated with the indigenous bacteria in native shrimp gut, yet more candidates presented in CK may reflect the complexity of new environment. Our results suggest that shrimp gut microbiota has high plasticity when its host faces environmental changes, even over short timescales. Further, the changes in external environment might influence the gut microbiome not just by providing environment-associated microbes directly, but also by interfering with the composition of indigenous gut bacteria indirectly.

The gut microbial community is one of the richest and most complex ecosystems on earth, and the intestinal microbes play an important role in host development and health. Next generation sequencing approaches, which rapidly produce millions of short reads that enable the investigation on a culture independent basis, are now popular for exploring microbial community. Currently, the gut microbiome in fresh water shrimp is unexplored. To explore gut microbiomes of the oriental river prawn (Macrobrachium nipponense) and investigate the effects of host genetics and habitats on the microbial composition, 454 pyrosequencing based on the 16S rRNA gene were performed. We collected six groups of samples, including M. nipponense shrimp from two populations, rivers and lakes, and one sister species (M. asperulum) as an out group. We found that Proteobacteria is the major phylum in oriental river prawn, followed by Firmicutes and Actinobacteria. Compositional analysis showed microbial divergence between the two shrimp species is higher than that between the two populations of one shrimp species collected from river and lake. Hierarchical clustering also showed that host genetics had a greater impact on the divergence of gut microbiome than host habitats. This finding was also congruent with the functional prediction from the metagenomic data implying that the two shrimp species still shared the same type of biological functions, reflecting a similar metabolic profile in their gut environments. In conclusion, this study provides the first investigation of the gut microbiome of fresh water shrimp, and supports the hypothesis of host species-specific signatures of bacterial community composition.

BackgroundThe complexity and dynamics of microbial communities are major factors in the ecology of a system. With the NGS technique, metagenomics data provides a new way to explore microbial interactions. Lotka-Volterra models, which have been widely used to infer animal interactions in dynamic systems, have recently been applied to the analysis of metagenomic data.ResultsIn this paper, we present the Lotka-Volterra model based tool, the Metagenomic Microbial Interacticon Simulator (MetaMIS), which is designed to analyze the time series data of microbial community profiles. MetaMIS first infers underlying microbial interactions from abundance tables for operational taxonomic units (OTUs) and then interprets interaction networks using the Lotka-Volterra model. We also embed a Bray-Curtis dissimilarity method in MetaMIS in order to evaluate the similarity to biological reality. MetaMIS is designed to tolerate a high level of missing data, and can estimate interaction information without the influence of rare microbes. For each interaction network, MetaMIS systematically examines interaction patterns (such as mutualism or competition) and refines the biotic role within microbes. As a case study, we collect a human male fecal microbiome and show that Micrococcaceae, a relatively low abundance OTU, is highly connected with 13 dominant OTUs and seems to play a critical role. MetaMIS is able to organize multiple interaction networks into a consensus network for comparative studies; thus we as a case study have also identified a consensus interaction network between female and male fecal microbiomes.ConclusionsMetaMIS provides an efficient and user-friendly platform that may reveal new insights into metagenomics data. MetaMIS is freely available at: https://sourceforge.net/projects/metamis/.Electronic supplementary materialThe online version of this article (doi:10.1186/s12859-016-1359-0) contains supplementary material, which is available to authorized users.

Both cis-and trans-regulatory mutations contribute to gene expression divergence within and between species. To estimate their relative contributions, we examined two yeast strains, BY (a laboratory strain) and RM (a wild strain), for their gene-expression divergence by microarray. Using these data and published ChIP-chip data, we obtained a set of single-regulator-regulated genes that showed expression divergence between BY and RM. We randomly selected 50 of these genes for further study. We developed a step-by-step approach to assess the relative contributions of cisand trans-variations to expression divergence by using pyrosequencing to quantify the mRNA levels of the BY and RM alleles in the same culture (co-culture) and in hybrid diploids. Forty genes showed expression divergence between the two strains in co-culture, and pyrosequencing of the BY/RM hybrid diploids showed that 45% (18/40) can be attributed to differences in trans-acting factors alone, 17.5% (7/40) mainly to trans-variations, 20% (8/40) to both cis-and trans-acting factors, 7.5% (3/40) mainly to cis-variations, and 10% (4/40) to cis-acting factors alone. In addition, we replaced the BY promoter by the RM promoter in each of 10 BY genes that were found from our microarray data to have expression divergence between BY and RM, and in each case our quantitative PCR analysis revealed a cis effect of the promoter replacement on gene expression. In summary, our study suggests that trans-acting factors play the major role in expression evolution between yeast strains, but the role of cis variation is also important.

Both cis and trans mutations contribute to gene expression divergence within and between species. We used Saccharomyces cerevisiae as a model organism to estimate the relative contributions of cis and trans variations to the expression divergence between a laboratory (BY) and a wild (RM) strain of yeast. We examined whether genes regulated by a single transcription factor (TF; single input module, SIM genes) or genes regulated by multiple TFs (multiple input module, MIM genes) are more susceptible to trans variation. Because a SIM gene is regulated by a single immediate upstream TF, the chance for a change to occur in its trans-acting factors would, on average, be smaller than that for a MIM gene. We chose 232 genes that exhibited expression divergence between BY and RM to test this hypothesis. We examined the expression patterns of these genes in a BY-RM coculture system and in a BY-RM diploid hybrid. We found that trans variation is far more important than cis variation for expression divergence between the two strains. However, because in 75% of the genes studied, cis variation has significantly contributed to expression divergence, cis change also plays a significant role in intraspecific expression evolution. Interestingly, we found that the proportion of genes with diverged expression between BY and RM is larger for MIM genes than for SIM genes; in fact, the proportion tends to increase with the number of transcription factors that regulate the gene. Moreover, MIM genes are, on average, subject to stronger trans effects than SIM genes, though the difference between the two types of genes is not conspicuous.

BackgroundMicrobial interactions are ubiquitous in nature. Recently, many similarity-based approaches have been developed to study the interaction in microbial ecosystems. These approaches can only explain the non-directional interactions yet a more complete view on how microbes regulate each other remains elusive. In addition, the strength of microbial interactions is difficult to be quantified by only using correlation analysis.ResultsIn this study, a rule-based microbial network (RMN) algorithm, which integrates regulatory OTU-triplet model with parametric weighting function, is being developed to construct microbial regulatory networks. The RMN algorithm not only can extrapolate the cooperative and competitive relationships between microbes, but also can infer the direction of such interactions. In addition, RMN algorithm can theoretically characterize the regulatory relationship composed of microbial pairs with low correlation coefficient in microbial networks. Our results suggested that Bifidobacterium, Streptococcus, Clostridium XI, and Bacteroides are essential for causing abundance changes of Veillonella in gut microbiome. Furthermore, we inferred some possible microbial interactions, including the competitive relationship between Veillonella and Bacteroides, and the cooperative relationship between Veillonella and Clostridium XI.ConclusionsThe RMN algorithm provides the reconstruction of gut microbe networks, and can shed light on the dynamical interactions of microbes in the infant intestinal tract.Electronic supplementary materialThe online version of this article (doi:10.1186/s12918-015-0199-2) contains supplementary material, which is available to authorized users.