A network-based approach to deciphering a dynamic microbiome's response to a subtle perturbation.

Over the past decades, one main issue that has emerged in ecological and environmental research is how losses in biodiversity influence ecosystem dynamics and functioning, and consequently human society. Although biodiversity is a common indicator of ecosystem functioning, it is difficult to measure biodiversity in microbial communities exposed to subtle or chronic environmental perturbations. Consequently, there is a need for alternative bioindicators to detect, measure, and monitor gradual changes in microbial communities against these slight, chronic, and continuous perturbations. In this study, microbial networks before and after subtle perturbations by adding S. acidaminiphila showed diverse topological niches and 4-node motifs in which microbes with co-occurrence patterns played the central roles in regulating and adjusting the intertwined relationships among microorganisms in response to the subtle environmental changes. This study demonstrates that microbial networks are a good bioindicator for chronic perturbation and should be applied in a variety of ecological investigations.

Successive passaging of a plant-associated microbiome reveals robust habitat and host genotype-dependent selection.

There is increasing interest in the plant microbiome as it relates to both plant health and agricultural sustainability. One key unanswered question is whether we can select for a plant microbiome that is robust after colonization of target hosts. We used a successive passaging experiment to address this question by selecting upon the tomato phyllosphere microbiome. Beginning with a diverse microbial community generated from field-grown tomato plants, we inoculated replicate plants across 5 plant genotypes for 4 45-d passages, sequencing the microbial community at each passage. We observed consistent shifts in both the bacterial (16S amplicon sequencing) and fungal (internal transcribed spacer region amplicon sequencing) communities across replicate lines over time, as well as a general loss of diversity over the course of the experiment, suggesting that much of the naturally observed microbial community in the phyllosphere is likely transient or poorly adapted within the experimental setting. We found that both host genotype and environment shape microbial composition, but the relative importance of genotype declines through time. Furthermore, using a community coalescence experiment, we found that the bacterial community from the end of the experiment was robust to invasion by the starting bacterial community. These results highlight that selecting for a stable microbiome that is well adapted to a particular host environment is indeed possible, emphasizing the great potential of this approach in agriculture and beyond. In light of the consistent response of the microbiome to selection in the absence of reciprocal host evolution (coevolution) described here, future studies should address how such adaptation influences host health.

A systematic approach re-analyzing the effects of temperature disturbance on the microbial community of mesophilic anaerobic digestion.

Microbial communities are key drivers of ecosystem processes, but their behavior in disturbed environments is difficult to measure. How microbial community composition and function respond disturbances is a common challenge in biomedical, environmental, agricultural, and bioenergy research. A novel way to solve this problem is to use a systems-level perspective and describe microbial communities as networks. Based on a mesophilic anaerobic digestion system of swine manure as a tool, we propose a simple framework to investigate changes in microbial communities via compositions, metabolic pathways, genomic properties and interspecies relationships in response to a long-term temperature disturbance. After temperature disturbance, microbial communities tend towards a competitive interaction network with higher GC content and larger genome size. Based on microbial interaction networks, communities responded to the disturbance by showing a transition from acetotrophic (Methanotrichaceae and Methanosarcinaceae) to methylotrophic methanogens (Methanomassiliicoccaceae and Methanobacteriaceae) and a fluctuation in rare biosphere taxa. To conclude, this study may be important for exploring the dynamic relationships between disturbance and microbial communities as a whole, as well as for providing researchers with a better understanding of how changes in microbial communities relate to ecological processes.

A novel molecular and chromosomal lineage of the anthropophilic Simulium (Simulium) rufibasis subgroup (Diptera: Simuliidae) in Taiwan.

The Simulium rufibasis subgroup is one of three subgroups of the Simulium (Simulium) tuberosum species-group; it is characterized by a pair of clustered stout hairs on the ventral surface of female abdominal segment 7. A member of the S. rufibasis subgroup in Taiwan was investigated morphologically and genetically using the universal cytochrome c oxidase subunit I (COI) barcoding gene and polytene chromosomal banding pattern. The Taiwanese material is morphologically similar to S. rosliramlii Takaoka & Chen from Vietnam and represents the second species of the S. rufibasis subgroup known from Taiwan. It also represents a novel molecular lineage that is distinct from three other primary lineages identified as S. doipuiense, S. doipuiense/S. rufibasis, and S. weji previously reported from Thailand. The mitochondrial evidence for a distinct lineage in Taiwan is supported by chromosomal analysis, which revealed unique sex chromosomes. For nomenclatural stability, we associate the name S. arisanum Shiraki with the Taiwanese entity. Originally described from females from Taiwan, S. arisanum until now has remained an enigmatic species.

Habitat and indigenous gut microbes contribute to the plasticity of gut microbiome in oriental river prawn during rapid environmental change.

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.

Inferring Microbial Interactions in the Gut of the Hong Kong Whipping Frog (Polypedates megacephalus) and a Validation Using Probiotics.

The concerted activity of intestinal microbes is crucial to the health and development of their host organisms. Investigation of microbial interactions in the gut should deepen our understanding of how these micro-ecosystems function. Due to advances in Next Generation Sequencing (NGS) technologies, various bioinformatic strategies have been proposed to investigate these microbial interactions. However, due to the complexity of the intestinal microbial community and difficulties in monitoring their interactions, at present there is a gap between the theory and biological application. In order to construct and validate microbial relationships, we first induce a community shift from simple to complex by manipulating artificial hibernation (AH) in the treefrog Polypedates megacephalus. To monitor community growth and microbial interactions, we further performed a time-course screen using a 16S rRNA amplicon approach and a Lotka-Volterra model. Lotka-Volterra models, also known as predator-prey equations, predict the dynamics of microbial communities and how communities are structured and sustained. An interaction network of gut microbiota at the genus level in the treefrog was constructed using Metagenomic Microbial Interaction Simulator (MetaMIS) package. The interaction network obtained had 1,568 commensal, 1,737 amensal, 3,777 mutual, and 3,232 competitive relationships, e.g., Lactococcus garvieae has a commensal relationship with Corynebacterium variabile. To validate the interacting relationships, the gut microbe composition was analyzed after probiotic trials using single strain (L. garvieae, C. variabile, and Bacillus coagulans, respectively) and a combination of L. garvieae, C. variabile, and B. coagulans, because of the cooperative relationship among their respective genera identified in the interaction network. After a 2 week trial, we found via 16S rRNA amplicon analysis that the combination of cooperative microbes yielded significantly higher probiotic concentrations than single strains, and the immune response (interleukin-10 expression) also significantly changed in a manner consistent with improved probiotic effects. By taking advantage of microbial community shift from simple to complex, we thus constructed a reliable microbial interaction network, and validated it using probiotic strains as a test system.

Functional analysis for gut microbes of the brown tree frog (Polypedates megacephalus) in artificial hibernation.

BACKGROUND: Annual 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. METHODS: In 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. RESULTS: Our 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. CONCLUSIONS: We infer that artificial hibernation may impose potential effects on primary immunodeficiency and increase the risk of bacterial infections in the brown tree frog.

Effects of Host Phylogeny and Habitats on Gut Microbiomes of Oriental River Prawn (Macrobrachium nipponense).

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.

The impact of normalization and phylogenetic information on estimating the distance for metagenomes.

Metagenomics enables the study of unculturable microorganisms in different environments directly. Discriminating between the compositional differences of metagenomes is an important and challenging problem. Several distance functions have been proposed to estimate the differences based on functional profiles or taxonomic distributions; however, the strengths and limitations of such functions are still unclear. Initially, we analyzed three well-known distance functions and found very little difference between them in the clustering of samples. This motivated us to incorporate suitable normalizations and phylogenetic information into the functions so that we could cluster samples from both real and synthetic data sets. The results indicate significant improvement in sample clustering over that derived by rank-based normalization with phylogenetic information, regardless of whether the samples are from real or synthetic microbiomes. Furthermore, our findings suggest that considering suitable normalizations and phylogenetic information is essential when designing distance functions for estimating the differences between metagenomes. We conclude that incorporating rank-based normalization with phylogenetic information into the distance functions helps achieve reliable clustering results.