What is microbial community ecology?

Modulating the Gut Microbiota of Humans by Dietary Intervention with Plant Glycans

The human colon contains a community of microbial species, mostly bacteria, which is often referred to as the gut microbiota. The community is considered essential to human well-being by conferring additional energy-harvesting capacity, niche exclusion of pathogens, and molecular signaling activities that are integrated into human physiological processes. Plant polysaccharides (glycans, dietary fiber) are an important source of carbon and energy that supports the maintenance and functioning of the gut microbiota. Therefore, the daily quantity and quality of plant glycans consumed by the human host have the potential to influence health. Members of the gut microbiota differ in ability to utilize different types of plant glycans. Dietary interventions with specific glycans could modulate the microbiota, counteracting ecological perturbations that disrupt the intricate relationships between microbiota and host (dysbiosis). This review considers prospects and research options for modulation of the gut microbiota by the formulation of diets that, when consumed habitually, would correct dysbiosis by building diverse consortia that boost functional resilience. Traditional "prebiotics" favor bifidobacteria and lactobacilli, whereas dietary mixtures of plant glycans that are varied in chemical complexity would promote high-diversity microbiotas. It is concluded that research should aim at improving knowledge of bacterial consortia that, through shared nourishment, degrade and ferment plant glycans. The consortia may vary in composition from person to person, but functional outputs will be consistent in a given context because of metabolic redundancy among bacteria. Thus, the individuality of gut microbiotas could be encompassed, functional resilience encouraged, and correction of dysbiosis achieved.

Synergistic effects in a microbial fuel cell between co-cultures and a photosynthetic alga Chlorella vulgaris improve performance

Microbial communities are catalysts that drive the operation of microbial fuel cells (MFCs). In this study, the use of a defined co-culture of Escherichia coli and Pseudomonas aeruginosa towards improved power generation in MFCs is described. The co-culture has been initially evaluated for substrate consumption, biofilm formation and microbial electron transfer activity. The co-culture gave an enhanced power density of 190.44 mW m⁻², while E. coli and P. aeruginosa as pure cultures generated lesser power densities of 139.24 and 158.76 mW m⁻² respectively. The photosynthetic alga Chlorella vulgaris was then inoculated in the cathode chamber. Co-cultures in the presence of C. vulgaris improved the mean power density from 175 mW m⁻² to 248 mW m⁻², a 41.7% rise. A synergistic effect was observed when the co-cultures were coupled with C. vulgaris. Combining co-cultures with photosynthetic MFCs offers a lot of promise in studying mechanisms and expanding the nature of applications.

Characterization of the rumen microbiota and its relationship with residual feed intake in sheep

Feed efficiency is a highly important economic trait in sheep production and has a significant impact on the economic benefits of sheep farming. Microbial fermentation of the rumen has a vital role in the host's nutrition; the rumen microbiota might affect host feed efficiency. However, the relationship between the rumen microbiota and feed efficiency in sheep is unclear. In the present study, the microbiota of 195 Hu sheep was investigated and their residual feed intake (RFI), a commonly used measure of feed efficiency, was determined. From birth, all sheep were subjected to the same management practices. At slaughter, samples of liquid rumen contents were collected and subjected to amplicon sequencing for the 16S rDNA gene on the IonS5™XL platform. To identify the bacterial taxa differentially represented at the genus or higher taxonomy levels, we used linear discriminant analysis coupled with effect size and curve fitting. In the sheep rumen, the four most abundant phyla were Firmicutes, Bacteroidetes, Fibrobacteres, and Proteobacteria; and the dominant genera were unidentified Prevotellaceae, Fibrobacter, unidentified Lachnospiraceae, Saccharofermentans, and Succinivibrio. Pathway analysis of the 16S rDNA sequencing data from the rumen microbiota identified that carbohydrate metabolism was enriched. Using α-diversity analysis, we further identified that Observed species, ACE, Good's coverage, and Chao1 are more abundant (P < 0.01) in the low-RFI (L-RFI) group compared to the high-RFI (H-RFI) group. High-RFI sheep had a higher abundance of three bacterial taxa (Prevotellaceae, Negativicutes, and Selenomonadales), and one taxa was overrepresented in the L-RFI sheep (Succinivibrio), respectively. Furthermore, model fitting showed that Veillonellaceae, Sphaerochaeta, Negativibacillus, Saccharofermentans, and members of the Tenericutes, Kiritimatiellaeota, Deltaproteobacteria, and Campylobacterales were correlated with the sheep RFI classification and thus were indicative of a role in animal efficiency. Tax4Fun analysis revealed that metabolic pathways such as "energy metabolism," "metabolism of cofactors and vitamins," "poorly characterized," and "replication recombination and repair proteins" were enriched in the rumen from H-RFI sheep, and "genetic information processing" and "lipopolysaccharide biosynthesis" were overrepresented in L-RFI sheep rumen. In addition, six Kyoto Encyclopedia of Genes and Genomes orthology pathways were identified as different between H-RFI and L-RFI groups. In conclusion, the low RFI phenotype (efficient animals) consistently (or characteristically) exhibited a more abundant and diverse microbiome in sheep.

Microbial model communities: To understand complexity, harness the power of simplicity

Natural microbial communities are complex ecosystems with myriads of interactions. To deal with this complexity, we can apply lessons learned from the study of model organisms and try to find simpler systems that can shed light on the same questions. Here, microbial model communities are essential, as they can allow us to learn about the metabolic interactions, genetic mechanisms and ecological principles governing and structuring communities. A variety of microbial model communities of varying complexity have already been developed, representing different purposes, environments and phenomena. However, choosing a suitable model community for one's research question is no easy task. This review aims to be a guide in the selection process, which can help the researcher to select a sufficiently well-studied model community that also fulfills other relevant criteria. For example, a good model community should consist of species that are easy to grow, have been evaluated for community behaviors, provide simple readouts and - in some cases - be of relevance for natural ecosystems. Finally, there is a need to standardize growth conditions for microbial model communities and agree on definitions of community-specific phenomena and frameworks for community interactions. Such developments would be the key to harnessing the power of simplicity to start disentangling complex community interactions.

Relationship between Virulence and Resistance among Gram-Negative Bacteria

Bacteria present in the human body are innocuous, providing beneficial functions, some of which are necessary for correct body function. However, other bacteria are able to colonize, invade, and cause damage to different tissues, and these are categorised as pathogens. These pathogenic bacteria possess several factors that enable them to be more virulent and cause infection. Bacteria have a great capacity to adapt to different niches and environmental conditions (presence of antibiotics, iron depletion, etc.). Antibiotic pressure has favoured the emergence and spread of antibiotic-resistant bacteria worldwide. Several studies have reported the presence of a relationship (both positive and negative, and both direct and indirect) between antimicrobial resistance and virulence among bacterial pathogens. This review studies the relationship among the most important Gram-negative bacteria (Escherichia coli and Pseudomonas aeruginosa) taking into account two points of view: (i) the effect the acquisition of resistance has on virulence, and (ii) co-selection of resistance and virulence. The relationship between resistance and virulence among bacteria depends on the bacterial species, the specific mechanisms of resistance and virulence, the ecological niche, and the host.

Seasonal variation in the gut microbiota of rhesus macaques inhabiting limestone forests of southwest Guangxi, China

Data on the gut microbiota of animals can provide new insights into dietary ecology of hosts, consequently assisting in understanding their adaptation strategy and evolutionary potential. We studied the gut microbiota composition and function of the wild rhesus macaques (Macaca mulatta) using 16S rRNA sequencing method. Our results revealed that the gut microbiota of the wild rhesus macaques was dominated by Firmicutes, Bacteroidetes, and Spirochaetes. Diversity and richness of gut microbiota were higher during the dry season than the rainy season. Specifically, higher proportions of Firmicutes, Tenericutes, Cyanobacteria, and unclassified bacteria at the phylum level and more Coprococcus at the genus level were detected in the dry season. Predictive functional analysis showed that pathways associated with carbohydrate metabolism and drug resistance (antimicrobial and antineoplastic) were richer in the dry season. These seasonal differences in microbiota could be due to their heavier dependence on leaf-based diet in the dry season. Additionally, macaques in limestone forests had a higher percentage of Spirochaetes, probably suggesting that the proportion of fruits in dietary composition also play an important role in the gut microbiota. We concluded that diet was strongly linked to the diversity, composition, and function of the gut microbiota in the wild groups of rhesus macaques living in the limestone forest, highlighting the importance of diet in the gut microbiota of macaques and the need to conduct further study on the adaptation strategy in response of environmental changes in the ground of gut microbiota.

Lactobacillus plantarum Shinshu N-07 isolated from fermented Brassica rapa L. attenuates visceral fat accumulation induced by high-fat diet in mice

Lactobacillus plantarum Shinshu N-07 (N07) and Lactobacillus curvatus #4G2 (#4G2) were isolated from fermented Brassica rapa L. and selected as promising probiotics with anti-adiposity activities based on in vitro assays. The anti-adiposity effects of these two strains were investigated using a diet-induced obesity animal model. Epididymal adipose tissue weight and adipocyte area were significantly lower and serum triglycerides and glucose tended to be lower in mice fed the high-fat diet supplemented with N07 compared with those fed the unsupplemented high-fat diet. Strain N07 suppressed hepatic steatosis, with accompanying downregulation of lipogenic genes in the liver. Expression of inflammatory cytokines and macrophage infiltration markers tended to be suppressed by N07 supplementation. Upregulation of uncoupling protein-1 in epididymal adipose tissue by N07 suggested that the transformation of white adipose tissue to brown might have been induced. Intestinal microbiota analysis revealed that a decrease in abundance of family S24-7 (phylum Bacteroidetes) following ingestion of the high-fat diet was partly recovered by supplementation with N07. Changes in those parameters were not observed in mice fed the high-fat diet supplemented with strain #4G2, suggesting strain specificities. Thus, N07 is a potential probiotic strain that could be used to develop functional foods that attenuate visceral fat accumulation after an appropriate human intervention trial.

Spatiotemporal Patterns in Diversity and Assembly Process of Marine Protist Communities of the Changjiang (Yangtze River) Plume and Its Adjacent Waters

Marine protists are highly heterogeneous and play key roles in the structure and functioning of marine ecosystems. However, little is known on the underlying biogeographic processes and seasonal diversity patterns that shape their community assembly in a regional scale in marginal sea. In this study, we conducted high-throughput sequencing of 18S rRNA gene to survey the protist community compositions (PCCs) of the Changjiang (Yangtze River) plume, an intensely human-affected coastal area, to the adjacent continental shelf waters over three seasons. Furthermore, the different impacts of environmental and spatial factors on marine PCCs were examined. The results revealed significant dissimilarities of PCC’s diversity among seasons and habitats, with more obvious seasonal variations in the Changjiang plume. Procrustes analysis showed better consistency of the community-environment relationship in shelf area, further supported by stronger correlation coefficients computed in the Mantel tests. This might be explained by seasonal dynamics of Changjiang Diluted Waters (i.e., the mixing of the Changjiang runoff with inshore water of the East China Sea) that changed the environmental conditions of coastal area dramatically, resulting in lower importance of spatial factors (dispersal limitation) on PCCs compared with environmental filters, including physicochemical properties (e.g., water temperature, salinity, dissolved oxygen, and nutrients), as well as biotic factors (e.g., Chl a and food abundance). This was further explained by higher immigration rate and fitness to neutral model, which suggested a predominant role of neutral process in shaping the PCCs in coastal area. Different richness, diversity, and taxonomic compositions but comparable biogeographic patterns were observed among abundant and rare sub-communities. In general, the abundant sub-communities exhibited higher dispersal ability which tend to respond to environmental selection during dispersal, whereas the rare sub-communities appeared to be present only in few samples due to dispersal limitation. Co-occurrence network further indicated the importance of biotic interactions in community assembly and potential roles of rare taxa in maintaining the community structure. Overall, this study suggests the dynamic in the biogeographic patterns of PCCs of the Changjiang plume to the adjacent waters in the ECS responding with the changing environmental conditions and geographical factors.

Fungal volatiles mediate cheese rind microbiome assembly

In vitro studies in plant, soil, and human systems have shown that microbial volatiles can mediate microbe-microbe or microbe-host interactions. These previous studies have often used artificially high concentrations of volatiles compared to in situ systems and have not demonstrated the roles volatiles play in mediating community-level dynamics. We used the notoriously volatile cheese rind microbiome to identify bacteria responsive to volatiles produced by five widespread cheese fungi. Vibrio casei had the strongest growth stimulation when exposed to all fungi. In multispecies community experiments, fungal volatiles caused a shift to a Vibrio-dominated community, potentially explaining the widespread occurrence of Vibrio in surface-ripened cheeses. RNA sequencing identified activation of the glyoxylate shunt as a possible mechanism underlying volatile-mediated growth promotion and community assembly. Our study demonstrates how airborne chemicals could be used to control the composition of microbiomes and illustrates how volatiles may impact the development of cheese rinds.

A piece of the pie: engineering microbiomes by exploiting division of labor in complex polysaccharide consumption

Although microbes competing for simple substrates are well-known to obey the ecological competitive exclusion principle, little is known regarding how complex substrates influence the ecology of microbial communities. The vast structural diversity of polysaccharides makes them ideal substrates for cooperative microbial degradation. Potential mechanisms for division of metabolic labor in microbial communities consuming polysaccharides are 1) complementary differences in gene content, 2) alternate regulation of polysaccharide degradation genes, 3) subtle differences in hydrolytic enzyme functionality, and 4) specialization in transport and consumption of hydrolysis products. Engineering division of labor in polysaccharide degradation using these mechanisms as control points may improve our ability to engineer microbiomes for improved productivity and stability in diverse environments.

The functional development of the rumen is influenced by weaning and associated with ruminal microbiota in lambs

Rumen development is critical for the development of early lambs. This work aims to evaluate the effects of abrupt weaning at day 21 on rumen fermentation, histomorphological traits and the ruminal microbiota compared with continuous suckling. Twelve pairs of artificially reared full-sib neonatal male Hu lambs were allocated to two groups, one of which was weaned at day 21 (EW group) and the other which was not weaned (CON group). At day 26 and day 49, six lambs from each group were randomly selected and sacrificed to collect ruminal contents and rumen tissue samples. Results showed that weaning influenced the fermentation parameters in the rumen, and altered the microbial community composition on day 49 (p < 0.05). Several genera were associated with rumen fermentation parameters (p < 0.05). Volatile fatty acid (VFA) concentration is the key parameter impacting microbiota composition. Weaning influenced the expression of genes associated with VFA metabolism and regulation of cell proliferation (p < 0.05). In conclusion, weaning significantly influenced the morphological and functional development of the rumen, and bacterial community composition. The microbial community composition was strongly associated with rumen weight and fermentation profiles, but not with morphological development.

Biohydrogen production beyond the Thauer limit by precision design of artificial microbial consortia

Dark fermentative biohydrogen (H₂) production could become a key technology for providing renewable energy. Until now, the H₂ yield is restricted to 4 moles of H₂ per mole of glucose, referred to as the "Thauer limit". Here we show, that precision design of artificial microbial consortia increased the H₂ yield to 5.6 mol mol^-1 glucose, 40% higher than the Thauer limit. In addition, the volumetric H₂ production rates of our defined artificial consortia are superior compared to any mono-, co- or multi-culture system reported to date. We hope this study to be a major leap forward in the engineering of artificial microbial consortia through precision design and provide a breakthrough in energy science, biotechnology and ecology. Constructing artificial consortia with this drawing-board approach could in future increase volumetric production rates and yields of other bioprocesses. Our artificial consortia engineering blueprint might pave the way for the development of a H₂ production bioindustry.

Microbiome definition re-visited: old concepts and new challenges

The field of microbiome research has evolved rapidly over the past few decades and has become a topic of great scientific and public interest. As a result of this rapid growth in interest covering different fields, we are lacking a clear commonly agreed definition of the term "microbiome." Moreover, a consensus on best practices in microbiome research is missing. Recently, a panel of international experts discussed the current gaps in the frame of the European-funded MicrobiomeSupport project. The meeting brought together about 40 leaders from diverse microbiome areas, while more than a hundred experts from all over the world took part in an online survey accompanying the workshop. This article excerpts the outcomes of the workshop and the corresponding online survey embedded in a short historical introduction and future outlook. We propose a definition of microbiome based on the compact, clear, and comprehensive description of the term provided by Whipps et al. in 1988, amended with a set of novel recommendations considering the latest technological developments and research findings. We clearly separate the terms microbiome and microbiota and provide a comprehensive discussion considering the composition of microbiota, the heterogeneity and dynamics of microbiomes in time and space, the stability and resilience of microbial networks, the definition of core microbiomes, and functionally relevant keystone species as well as co-evolutionary principles of microbe-host and inter-species interactions within the microbiome. These broad definitions together with the suggested unifying concepts will help to improve standardization of microbiome studies in the future, and could be the starting point for an integrated assessment of data resulting in a more rapid transfer of knowledge from basic science into practice. Furthermore, microbiome standards are important for solving new challenges associated with anthropogenic-driven changes in the field of planetary health, for which the understanding of microbiomes might play a key role. Video Abstract.

Molecular Decolonization: An Indigenous Microcosm Perspective of Planetary Health

Indigenous peoples are resilient peoples with deep traditional knowledge and scientific thought spanning millennia. Global discourse on climate change however has identified Indigenous populations as being a highly vulnerable group due to the habitation in regions undergoing rapid change, and the disproportionate burden of morbidity and mortality already faced by this population. Therefore, the need for Indigenous self-determination and the formal recognition of Indigenous knowledges, including micro-level molecular and microbial knowledges, as a critical foundation for planetary health is in urgent need. Through the process of Indigenous decolonization, even at the smallest molecular scale, we define a method back to our original selves and therefore to our planetary origin story. Our health and well-being is directly reflected at the planetary scale, and we suggest, can be rooted through the concept of molecular decolonization, which through the English language emerged from the ‘First 1000 Days Australia’ and otherwise collectively synthesized globally. It is through our evolving understanding of decolonization at a molecular level, which many of our Indigenous cultural and healing practices subtly embody, that we are better able to translate the intricacies within the current Indigenous scientific worldview through Western forms of discourse.

Temporal Dynamics of the Gut Bacteriome and Mycobiome in the Weanling Pig

Weaning is a period of environmental changes and stress that results in significant alterations to the piglet gut microbiome and is associated with a predisposition to disease, making potential interventions of interest to the swine industry. In other animals, interactions between the bacteriome and mycobiome can result in altered nutrient absorption and susceptibility to disease, but these interactions remain poorly understood in pigs. Recently, we assessed the colonization dynamics of fungi and bacteria in the gastrointestinal tract of piglets at a single time point post-weaning (day 35) and inferred interactions were found between fungal and bacterial members of the porcine gut ecosystem. In this study, we performed a longitudinal assessment of the fecal bacteriome and mycobiome of piglets from birth through the weaning transition. Piglet feces in this study showed a dramatic shift over time in the bacterial and fungal communities, as well as an increase in network connectivity between the two kingdoms. The piglet fecal bacteriome showed a relatively stable and predictable pattern of development from Bacteroidaceae to Prevotellaceae, as seen in other studies, while the mycobiome demonstrated a loss in diversity over time with a post-weaning population dominated by Saccharomycetaceae. The mycobiome demonstrated a more transient community that is likely driven by factors such as diet or environmental exposure rather than an organized pattern of colonization and succession evidenced by fecal sample taxonomic clustering with nursey feed samples post-weaning. Due to the potential tractability of the community, the mycobiome may be a viable candidate for potential microbial interventions that will alter piglet health and growth during the weaning transition.

Bacterial community composition in soils covered by different vegetation types in the Yancheng tidal marsh

Coastal wetland vegetation plays an important role in maintaining ecological function and is a key factor affecting the soil bacterial community. Spartina alterniflora was introduced to the Yancheng tidal marsh to stabilize the sediments and gradually replaced the native plants. However, the changes in the soil bacterial community profile caused by S. alterniflora invasion are poorly characterized. Here, we used MiSeq sequencing to compare the composition of the bacterial community in soil at different depths under exotic S. alterniflora (SA), native Phragmites australis (PA), and native Suaeda salsa (SS). The results showed that the pH value was lower, but the salinity, soil organic carbon, total nitrogen, and number of 16S rRNA genes were higher in SA soils than in PA and SS soils. Overall, Proteobacteria was the dominant bacterial phylum, followed by Chloroflexi, Acidobacteria, Planctomycetes, Gemmatimonadetes, and Nitrospirae. Anaerolineae in the Chloroflexi phylum showed the greatest difference based on vegetation, accounting for 14.4% of the overall bacterial community in SA soils but only about 3.8% of those in PA and SS soils. The composition, interaction, and predicted functional profiles of the bacterial community in SA soils were significantly different from those in PA and SS soils, especially for functions related to the sulfur and nitrogen cycles. Salinity was negatively correlated with the Shannon index and accounted for 37.7% of the total variation in the bacterial community, making it the most important environmental factor. Our results showed the differences in bacterial community composition among different vegetation types and soil depths in the Yancheng tidal marsh, which provides a microbial basis for a better understanding of the ecological functions in this ecosystem.

Its2vec: Fungal Species Identification Using Sequence Embedding and Random Forest Classification

Fungi play essential roles in many ecological processes, and taxonomic classification is fundamental for microbial community characterization and vital for the study and preservation of fungal biodiversity. To cope with massive fungal barcode data, tools that can implement extensive volumes of barcode sequences, especially the internal transcribed spacer (ITS) region, are necessary. However, high variation in the ITS region and computational requirements for processing high-dimensional features remain challenging for existing predictors. In this study, we developed Its2vec, a bioinformatics tool for the classification of fungal ITS barcodes to the species level. An ITS database covering more than 25,000 species in a broad range of fungal taxa was assembled. For dimensionality reduction, a word embedding algorithm was used to represent an ITS sequence as a dense low-dimensional vector. A random forest-based classifier was built for species identification. Benchmarking results showed that our model achieved an accuracy comparable to that of several state-of-the-art predictors, and more importantly, it could implement large datasets and greatly reduce dimensionality. We expect the Its2vec model to be helpful for fungal species identification and, thus, for revealing microbial community structures and in deepening our understanding of their functional mechanisms.

Seasonal Shift in Physicochemical Factors Revealed the Ecological Variables that Modulate the Density of Acinetobacter Species in Freshwater Resources

Certain environmental variables are responsible for the survival of microorganisms in aquatic environments. The influence of these environmental factors in each season (winter, autumn, spring and summer) of the year can be used to track changes in a microbial population in freshwater resources. In this study, we assessed the effect of seasonal shifts in environmental variables including temperature, pH, total dissolved solids (TDS), total suspended solids (TSS), biochemical oxygen demand (BOD) and turbidity (TBS) among others on the density of Acinetobacter species in the Great Fish, Keiskamma and Tyhume rivers in the Eastern Cape Province, South Africa. Water samples and values of the environmental factors were taken from the rivers for 12 months. The density of presumptive Acinetobacter species was estimated from the culture of water samples on a CHROMagar selective medium, while the Acinetobacter-specific recA gene was targeted for the identification of Acinetobacter species using PCR assay. The multivariate relationship between seasons and changes in variables was created using PCA, while the effect of seasonal shifts in the environmental variables on the density of Acinetobacter species was evaluated using correlation test and topological graphs. Positive association patterns were observed between the seasons, environmental factors and the bacterial density in the rivers. In addition, temperature, TBS, TSS and BOD tended to influence the bacterial density more than other physicochemical factors in the rivers across the seasons. Of the total 1107 presumptive Acinetobacter species, 844 were confirmed as Acinetobacter species. Therefore, these findings suggested that the rivers contain Acinetobacter species that could be useful for basic and applied study in ecology or biotechnology, while their clinical relevance in causing diseases cannot be underestimated.

Composition and co-occurrence patterns of the microbiota of different niches of the bovine mammary gland: potential associations with mastitis susceptibility, udder inflammation, and teat-end hyperkeratosis

Background

Within complex microbial ecosystems, microbe-microbe interrelationships play crucial roles in determining functional properties such as metabolic potential, stability and colonization resistance. In dairy cows, microbes inhabiting different ecological niches of the udder may have the potential to interact with mastitis pathogens and therefore modulate susceptibility to intramammary infection. In the present study, we investigated the co-occurrence patterns of bacterial communities within and between different niches of the bovine mammary gland (teat canal vs. milk) in order to identify key bacterial taxa and evaluate their associations with udder health parameters and mastitis susceptibility.

Results

Overall, teat canal microbiota was more diverse, phylogenetically less dispersed, and compositionally distinct from milk microbiota. This, coupled with identification of a large number of bacterial taxa that were exclusive to the teat canal microbiota suggested that the intramammary ecosystem, represented by the milk microbiota, acts as a selective medium that disfavors the growth of certain environmental bacterial lineages. We further observed that the diversity of milk microbiota was negatively correlated with udder inflammation. By performing correlation network analysis, we identified two groups of phylogenetically distinct hub species that were either positively (unclassified Bacteroidaceae and Phascolarctobacterium) or negatively (Sphingobacterium) correlated with biodiversity metrics of the mammary gland (MG). The latter group of bacteria also showed positive associations with the future incidence of clinical mastitis.

Conclusions

Our results provide novel insights into the composition and structure of bacterial communities inhabiting different niches of the bovine MG. In particular, we identified hub species and candidate foundation taxa that were associated with the inflammatory status of the MG and/or future incidences of clinical mastitis. Further in vitro and in vivo interrogations of MG microbiota can shed light on different mechanisms by which commensal microbiota interact with mastitis pathogens and modulate udder homeostasis.

Dynamic changes in intestinal microbiota in young forest musk deer during weaning

Weaning is an important event for all mammals, including young forest musk deer. However, weaning stress may cause intestinal microbiota-related disorders. Therefore, high-throughput 16S rRNA gene sequencing was applied to study the dynamic changes in intestinal microbiota during pre-weaning (10 days before weaning) and post-weaning (10 days after weaning) in 15 young forest musk deer. We saw that intestinal microbiota diversity in the post-weaning period was significantly higher than that in the pre-weaning period. The most dominant bacterial phyla were similar in the two groups (Firmicutes, Bacteroidetes and Verrucomicrobia). Meanwhile, we applied Linear discriminant analysis effect size (LefSe) to identify the most differentially microbial taxa in the pre-weaning and post-weaning groups. In the post-weaning forest musk deer, the relative abundance of Actinobacteria, Spirochaetes, Ruminococcaceae_UCG-005, Treponema and Prevotella was higher than in the pre-weaning group. However, higher relative abundance of the phyla Bacteroidetes was found in the pre-weaning group compared with that in the post-weaning group. In summary, this research provides a theoretical foundation for the dynamics of young forest musk deer intestinal microbiota during the weaning transition, which may benefit in understanding the growth and health of forest musk deer.

Coexistence and cooperation in structured habitats

Background

Natural habitats are typically structured, imposing constraints on inhabiting populations and their interactions. Which conditions are important for coexistence of diverse communities, and how cooperative interaction stabilizes in such populations, have been important ecological and evolutionary questions.

Results

We investigate a minimal ecological framework of microbial population dynamics that exhibits crucial features to show coexistence: Populations repeatedly undergo cycles of separation into compartmentalized habitats and mixing with new resources. The characteristic time-scale is longer than that typical of individual growth. Using analytic approximations, averaging techniques and phase-plane methods of dynamical systems, we provide a framework for analyzing various types of microbial interactions. Population composition and population size are both dynamic variables of the model; they are found to be decoupled both in terms of time-scale and parameter dependence. We present specific results for two examples of cooperative interaction by public goods: collective antibiotics resistance, and enhanced iron-availability by pyoverdine. We find stable coexistence to be a likely outcome.

Conclusions

The two simple features of a long mixing time-scale and spatial compartmentalization are enough to enable coexisting strains. In particular, costly social traits are often stabilized in such an environment—and thus cooperation established.

Emerging Priorities for Microbiome Research

Microbiome research has increased dramatically in recent years, driven by advances in technology and significant reductions in the cost of analysis. Such research has unlocked a wealth of data, which has yielded tremendous insight into the nature of the microbial communities, including their interactions and effects, both within a host and in an external environment as part of an ecological community. Understanding the role of microbiota, including their dynamic interactions with their hosts and other microbes, can enable the engineering of new diagnostic techniques and interventional strategies that can be used in a diverse spectrum of fields, spanning from ecology and agriculture to medicine and from forensics to exobiology. From June 19-23 in 2017, the NIH and NSF jointly held an Innovation Lab on Quantitative Approaches to Biomedical Data Science Challenges in our Understanding of the Microbiome. This review is inspired by some of the topics that arose as priority areas from this unique, interactive workshop. The goal of this review is to summarize the Innovation Lab's findings by introducing the reader to emerging challenges, exciting potential, and current directions in microbiome research. The review is broken into five key topic areas: (1) interactions between microbes and the human body, (2) evolution and ecology of microbes, including the role played by the environment and microbe-microbe interactions, (3) analytical and mathematical methods currently used in microbiome research, (4) leveraging knowledge of microbial composition and interactions to develop engineering solutions, and (5) interventional approaches and engineered microbiota that may be enabled by selectively altering microbial composition. As such, this review seeks to arm the reader with a broad understanding of the priorities and challenges in microbiome research today and provide inspiration for future investigation and multi-disciplinary collaboration.

Bevier C, Chaves Barreto C, Arturo Navas C. Environmental influences on and antimicrobial activity of the skin microbiota of Proceratophrys boiei (Amphibia, Anura) across forest fragments

The composition of the skin microbiota of amphibians is related to the biology of host species and environmental microbial communities. In this system, the environment serves as a microbial source and can modulate the hosted community. When habitats are fragmented and the environment disturbed, changes in the structure of this microbial community are expected. One important potential consequence of fragmentation is a compromised protective function of the microbiota against pathogenic microorganisms. In this study, the skin microbiota of the amphibian Proceratophrys boiei was characterized, evaluated for relationships with environmental variables and environmental sources of microbial communities, and its diversity evaluated for frog populations from fragmented and continuous forests. In addition, the antimicrobial activity of this skin community was studied in frogs from both forest types. Culture methods and 16S rRNA high-throughput gene sequencing were used to characterize the microbial community and demonstrated that the skin microbiota of P. boiei is more closely related to the soil microbial communities than those inhabiting water bodies or fragment matrix, the unforested area around the forested fragment. The microbial diversity and abundance of P. boiei skin microbiota are different between continuous forests and fragments. This community is correlated with environmental variables, especially with temperature of microhabitat and distance to human dwelling. All individuals of P. boiei harbored bacteria capable of inhibiting the growth of pathogenic bacteria and different strains of the pathogenic fungus Batrachochytrium dendrobatidis, and a total of 27 bacterial genera were detected. The results of this study indicate that the persistence of populations of this species will need balanced and sustained interactions among host, microorganisms, and environment.

Bacterial Community Changes Associated with Land Use Type in the Forest Montane Region of Northeast China

Soil microorganisms play a vital role in the biogeochemical cycle, whereas land use change is one of the primary factors that affects the biodiversity and functionality of terrestrial ecosystems. The composition and diversity of bacterial communities (by high-throughput sequencing of the bacterial 16S rRNA gene) were evaluated in the soils of the Montane Region of Northeast China, across different land use types, e.g., natural secondary forest (Quercus mongolica, QM), shrubland (SL), coniferous plantation (Larix gmelinii, LG, and Pinus koraiensis, PK), and agricultural land (Zea mays, ZM). Significant differences in the chemical characteristics and bacterial communities in soils under different land uses were observed in this study. Soil resident TC (total carbon) and TN (total nitrogen) were much higher in secondary natural forest soils, than in coniferous plantation and agricultural soils. Compared with forest and shrubland soils, soil bacterial OTUs, the Chao1 index, and the ACE index were the lowest in the ZM. There were high proportions of Proteobacteria, Actinobacteria, Acidobacteria, Chloroflexi, Gemmatimonadetes, Verrucomicrobia, Bacteroidetes, Planctomycetes, Saccharibacteria, and Nitrospirae in agricultural and forest soils, which accounted for over 90% of the reads in each sample. We found that the dominant group in the forest and shrubland soils was Proteobacteria, while the most dominant group in the ZM was Actinobacteria. The results of both heatmap and principal component analyses displayed groups according to land use types, which indicated that the bacterial communities in the areas under study were significantly influenced by long term differently managed land use. Furthermore, redundancy and Pearson correlation analyses revealed that the bacterial communities were primarily regulated by soil characteristics. This suggested that altered land use patterns initiated changes in the chemical properties of the soils, which affected the composition of microbial communities in this area. This provides a scientific basis for the evolutionary mechanism of soil quality, as well as the rational development and utilization of land resources.

Predicting Microbial Species in a River Based on Physicochemical Properties by Bio-Inspired Metaheuristic Optimized Machine Learning

The main goal of the analysis of microbial ecology is to understand the relationship between Earth’s microbial community and their functions in the environment. This paper presents a proof-of-concept research to develop a bioclimatic modeling approach that leverages artificial intelligence techniques to identify the microbial species in a river as a function of physicochemical parameters. Feature reduction and selection are both utilized in the data preprocessing owing to the scarce of available data points collected and missing values of physicochemical attributes from a river in Southeast China. A bio-inspired metaheuristic optimized machine learner, which supports the adjustment to the multiple-output prediction form, is used in bioclimatic modeling. The accuracy of prediction and applicability of the model can help microbiologists and ecologists in quantifying the predicted microbial species for further experimental planning with minimal expenditure, which is become one of the most serious issues when facing dramatic changes of environmental conditions caused by global warming. This work demonstrates a neoteric approach for potential use in predicting preliminary microbial structures in the environment.

Modelling microbial communities using biochemical resource allocation analysis

To understand the functioning and dynamics of microbial communities is a fundamental challenge in current biology. To tackle this challenge, the construction of computational models of interacting microbes is an indispensable tool. There is, however, a large chasm between ecologically motivated descriptions of microbial growth used in many current ecosystems simulations, and detailed metabolic pathway and genome-based descriptions developed in the context of systems and synthetic biology. Here, we seek to demonstrate how resource allocation models of microbial growth offer the potential to advance ecosystem simulations and their parametrization. In particular, recent work on quantitative resource allocation allow us to formulate mechanistic models of microbial growth that are physiologically meaningful while remaining computationally tractable. These models go beyond Michaelis-Menten and Monod-type growth models, and are capable of accounting for emergent properties that underlie the remarkable plasticity of microbial growth. We outline the utility and advantages of using biochemical resource allocation models by considering a coarse-grained model of cyanobacterial growth and demonstrate how the model allows us to address specific questions of relevance for the simulation of marine microbial ecosystems, including the physiological acclimation of protein expression to different environments, the description of co-limitation by several nutrients and the differential use of alternative nutrient sources, as well as the description of metabolic diversity based on our increasing knowledge about quantitative cell physiology.

Microenvironmental Interplay Predominated by Beneficial Aspergillus Abates Fungal Pathogen Incidence in Paddy Environment

Rice fungal pathogens, responsible for severe rice yield loss and biotoxin contamination, cause increasing concerns on environmental safety and public health. In the paddy environment, we observed that the asymptomatic rice phyllosphere microenvironment was dominated by an indigenous fungus, Aspergillus cvjetkovicii, which positively correlated with alleviated incidence of Magnaporthe oryzae, one of the most aggressive plant pathogens. Through the comparative metabolic profiling for the rice phyllosphere microenvironment, two metabolites were assigned as exclusively enriched metabolic markers in the asymptomatic phyllosphere and increased remarkably in a population-dependent manner with A. cvjetkovicii. These two metabolites evidenced to be produced by A. cvjetkovicii in either a phyllosphere microenvironment or artificial media were purified and identified as 2(3H)-benzofuranone and azulene, respectively, by gas chromatography coupled to triple quadrupole mass spectrometry and nuclear magnetic resonance analyses. Combining with bioassay analysis in vivo and in vitro, we found that 2(3H)-benzofuranone and azulene exerted dissimilar actions at the stage of infection-related development of M. oryzae. A. cvjetkovicii produced 2(3H)-benzofuranone at the early stage to suppress MoPer1 gene expression, leading to inhibited mycelial growth, while azulene produced lately was involved in blocking of appressorium formation by downregulation of MgRac1. More profoundly, the microenvironmental interplay dominated by A. cvjetkovicii significantly blocked M. oryzae epidemics in the paddy environment from 54.7 to 68.5% (p < 0.05). Our study first demonstrated implication of the microenvironmental interplay dominated by indigenous and beneficial fungus to ecological balance and safety of the paddy environment.

Relatively rare root endophytic bacteria drive plant resource allocation patterns and tissue nutrient concentration in unpredictable ways

PREMISE

Plant endophytic bacterial strains can influence plant traits such as leaf area and root length. Yet, the influence of more complex bacterial communities in regulating overall plant phenotype is less explored. Here, in two complementary experiments, we tested whether we can predict plant phenotype response to changes in microbial community composition.

METHODS

In the first study, we inoculated a single genotype of Populus deltoides with individual root endophytic bacteria and measured plant phenotype. Next, data from this single inoculation were used to predict phenotypic traits after mixed three-strain community inoculations, which we tested in the second experiment.

RESULTS

By itself, each bacterial endophyte significantly but weakly altered plant phenotype relative to noninoculated plants. In a mixture, bacterial strain Burkholderia BT03, constituted at least 98% of community relative abundance. Yet, plant resource allocation and tissue nutrient concentrations were disproportionately influenced by Pseudomonas sp. GM17, GM30, and GM41. We found a 10% increase in leaf mass fraction and an 11% decrease in root mass fraction when replacing Pseudomonas GM17 with GM41 in communities containing both Pseudomonas GM30 and Burkholderia BT03.

CONCLUSIONS

Our results indicate that interactions among endophytic bacteria may drive plant phenotype over the contribution of each strain individually. Additionally, we have shown that low-abundance strains contribute to plant phenotype challenging the assumption that the dominant strains will drive plant function.

Cooperation in Microbial Populations: Theory and Experimental Model Systems

Cooperative behavior, the costly provision of benefits to others, is common across all domains of life. This review article discusses cooperative behavior in the microbial world, mediated by the exchange of extracellular products called public goods. We focus on model species for which the production of a public good and the related growth disadvantage for the producing cells are well described. To unveil the biological and ecological factors promoting the emergence and stability of cooperative traits we take an interdisciplinary perspective and review insights gained from both mathematical models and well-controlled experimental model systems. Ecologically, we include crucial aspects of the microbial life cycle into our analysis and particularly consider population structures where ensembles of local communities (subpopulations) continuously emerge, grow, and disappear again. Biologically, we explicitly consider the synthesis and regulation of public good production. The discussion of the theoretical approaches includes general evolutionary concepts, population dynamics, and evolutionary game theory. As a specific but generic biological example, we consider populations of Pseudomonas putida and its regulation and use of pyoverdines, iron scavenging molecules, as public goods. The review closes with an overview on cooperation in spatially extended systems and also provides a critical assessment of the insights gained from the experimental and theoretical studies discussed. Current challenges and important new research opportunities are discussed, including the biochemical regulation of public goods, more realistic ecological scenarios resembling native environments, cell-to-cell signaling, and multispecies communities.

Microbial functional diversity: From concepts to applications

Functional diversity is increasingly recognized by microbial ecologists as the essential link between biodiversity patterns and ecosystem functioning, determining the trophic relationships and interactions between microorganisms, their participation in biogeochemical cycles, and their responses to environmental changes. Consequently, its definition and quantification have practical and theoretical implications. In this opinion paper, we present a synthesis on the concept of microbial functional diversity from its definition to its application. Initially, we revisit to the original definition of functional diversity, highlighting two fundamental aspects, the ecological unit under study and the functional traits used to characterize it. Then, we discuss how the particularities of the microbial world disallow the direct application of the concepts and tools developed for macroorganisms. Next, we provide a synthesis of the literature on the types of ecological units and functional traits available in microbial functional ecology. We also provide a list of more than 400 traits covering a wide array of environmentally relevant functions. Lastly, we provide examples of the use of functional diversity in microbial systems based on the different units and traits discussed herein. It is our hope that this paper will stimulate discussions and help the growing field of microbial functional ecology to realize a potential that thus far has only been attained in macrobial ecology.

Direct interaction network and differential network inference from compositional data via lasso penalized D-trace loss

The development of high-throughput sequencing technologies for 16S rRNA gene profiling provides higher quality compositional data for microbe communities. Inferring the direct interaction network under a specific condition and understanding how the network structure changes between two different environmental or genetic conditions are two important topics in biological studies. However, the compositional nature and high dimensionality of the data are challenging in the context of network and differential network recovery. To address this problem in the present paper, we proposed two new loss functions to incorporate the data transformations developed for compositional data analysis into D-trace loss for network and differential network estimation, respectively. The sparse matrix estimators are defined as the minimizer of the corresponding lasso penalized loss. Our method is characterized by its straightforward application based on the ADMM algorithm for numerical solution. Simulations show that the proposed method outperforms other state-of-the-art methods in network and differential network inference under different scenarios. Finally, as an illustration, our method is applied to a mouse skin microbiome data.

Effect of live yeast Saccharomyces cerevisiae supplementation on the performance and cecum microbial profile of suckling piglets

One mechanism through which S. cerevisiae may improve the performance of pigs is by altering the composition of the gut microbiota, a response that may be enhanced by early postnatal supplementation of probiotics. To test this hypothesis, newborn piglets (16 piglets/group) were treated with either S. cerevisiae yeast (5 x 109 cfu/pig: Low) or (2.5 x 1010 cfu/piglet: High) or equivalent volume of sterile water (Control) by oral gavage every other day starting from day 1 of age until weaning (28±1 days of age). Piglet body weight was recorded on days 1, 3, 7, 10, 17, 24 and 28 and average daily gain (ADG) calculated for the total period. At weaning, piglets were euthanized to collect cecum content for microbial profiling by sequencing of the 16S rRNA gene. ADG was higher in both Low and High yeast groups than in Control group (P<0.05). Alpha diversity analyses indicated a more diverse microbiota in the Control group compared with Low yeast group; the High yeast being intermediate (P < 0.01). Similarly, Beta diversity analyses indicated differences among treatments (P = 0.03), mainly between Low yeast and Control groups (P = 0.02). The sparse Partial Least Squares Discriminant Analysis (sPLS-DA) indicated that Control group was discriminated by a higher abundance of Veillonella, Dorea, Oscillospira and Clostridium; Low yeast treated pigs by higher Blautia, Collinsella and Eubacterium; and High yeast treated pigs by higher Eubacterium, Anaerostipes, Parabacteroides, Mogibacterium and Phascolarctobacterium. Partial Least Squares (PLS) analysis showed that piglet ADG was positively correlated with genus Prevotella in High yeast group. Yeast supplementation significantly affected microbial diversity in cecal contents of suckling piglets associated with an improvement of short chain fatty acid producing bacteria in a dose-dependent manner. In conclusion, yeast treatment improved piglet performance and shaped the piglet cecum microbiota composition in a dose dependent way.

Applications of the Soil, Plant and Rumen Microbiomes in Pastoral Agriculture

The production of dairy, meat, and fiber by ruminant animals relies on the biological processes occurring in soils, forage plants, and the animals' rumens. Each of these components has an associated microbiome, and these have traditionally been viewed as distinct ecosystems. However, these microbiomes operate under similar ecological principles and are connected via water, energy flows, and the carbon and nitrogen nutrient cycles. Here, we summarize the microbiome research that has been done in each of these three environments (soils, forage plants, animals' rumen) and investigate what additional benefits may be possible through understanding the interactions between the various microbiomes. The challenge for future research is to enhance microbiome function by appropriate matching of plant and animal genotypes with the environment to improve the output and environmental sustainability of pastoral agriculture.

Community analysis and co-occurrence patterns in airway microbial communities during health and disease

Ecological relationships between bacteria are important when considering variation in bacterial communities in humans, with such variation playing an important role in both health and disease.

Using high-throughput sequence data of the 16S rRNA marker-gene, we analysed the prevalence of taxa in the airways of a number of health- and disease-associated cohorts and determined the main drivers of community variance and bacterial co-occurrence.

A number of facultative and obligately anaerobic bacterial taxa are commonly associated with the upper airways, forming the main “core” microbiota, e.g. Streptococcus spp., Veillonella spp., Prevotella spp., Granulicatella spp. and Fusobacterium spp. Opportunistic pathogenic bacteria associated with chronic airways disease, such as Pseudomonas spp. (Pseudomonas aeruginosa), Burkholderia spp. (Burkholderia cepacia complex) and Haemophilus spp. (Haemophilus influenzae) demonstrated poor correlation with other members of their respective communities (ρ<0.5; p>0.005), indicating probable independent acquisition and colonisation. Furthermore, our findings suggest that intra-genus variation between health and disease may affect community assemblies.

Improved understanding of how bacteria assemble in time and space during health and disease will enable the future development of tailored treatment according to the patient's own signature microbiota, potentially providing benefit to patients suffering from airway diseases characterised by chronic infection.

Within the airways, “core” community structures are formed between microbial taxa in both health and disease, with a number of common opportunistic pathogens not being members of such core communitieshttp://bit.ly/2Kau3ni

Inference of Environmental Factor-Microbe and Microbe-Microbe Associations from Metagenomic Data Using a Hierarchical Bayesian Statistical Model

The inference of associations between environmental factors and microbes and among microbes is critical to interpreting metagenomic data, but compositional bias, indirect associations resulting from common factors, and variance within metagenomic sequencing data limit the discovery of associations. To account for these problems, we propose metagenomic Lognormal-Dirichlet-Multinomial (mLDM), a hierarchical Bayesian model with sparsity constraints, to estimate absolute microbial abundance and simultaneously infer both conditionally dependent associations among microbes and direct associations between microbes and environmental factors. We empirically show the effectiveness of the mLDM model using synthetic data, data from the TARA Oceans project, and a colorectal cancer dataset. Finally, we apply mLDM to 16S sequencing data from the western English Channel and report several associations. Our model can be used on both natural environmental and human metagenomic datasets, promoting the understanding of associations in the microbial community.

Drinking Warm Water Improves Growth Performance and Optimizes the Gut Microbiota in Early Postweaning Rabbits during Winter

Accumulating evidence indicates that cold exposure changes the composition of the gut microbiota and reduces intestinal immunity in early postweaning livestock. However, little is known about the effects of drinking warm water (WW) on gut microbiota during winter. In this study, we investigated the effects of drinking WW in winter on the growth performance and gut microbiota structure of rabbits raised in poorly insulated housing from the early postweaning period (day 46) to the subadult period (day 82). The average daily gain and feed conversion ratio in rabbits drinking WW were significantly improved compared to those of the rabbits drinking cold water (CW) during 47-58 days. In addition, rabbits drinking WW had a significantly decreased the risk of diarrhea during 71-82 days. 16S rRNA sequence analysis revealed that the alpha diversity of the cecal microbiota was not significantly different between the WW and CW groups, but significantly increased with age. The relative abundance of cecal microorganisms, such as Coprococcus spp. was considerably increased at day 70 in the group drinking WW. Correlation analysis indicated that Coprococcus spp. was negatively associated with pro-inflammatory factors. In conclusion, our results suggest that drinking WW has a positive effect on growth performance and gut microbiota in rabbits during the early postweaning stage in winter.

Reconciling Ecological and Engineering Design Principles for Building Microbiomes

Simplified microbial communities, or “benchtop microbiomes,” enable us to manage the profound complexity of microbial ecosystems. Widespread activities aiming to design and control communities result in novel resources for testing ecological theories and also for realizing new biotechnologies.

Simplified microbial communities, or “benchtop microbiomes,” enable us to manage the profound complexity of microbial ecosystems. Widespread activities aiming to design and control communities result in novel resources for testing ecological theories and also for realizing new biotechnologies. There is much to be gained by reconciling engineering design principles with ecological processes that shape microbiomes in nature. In this short Perspective, I will address how natural processes such as environmental filtering, the establishment of priority effects, and community “blending” (coalescence) can be harnessed for engineering microbiomes from complex starting materials. I will also discuss how future microbiome architects may draw inspiration from modern practices in synthetic biology. This topic is based on an important overarching research goal, which is to understand how natural forces shape microbial communities and interspecies interactions such that new engineering design principles can be extracted to promote human health or energy and environmental sustainability.

Faecal microbiota shift during weaning transition in piglets and evaluation of AO blood types as shaping factor for the bacterial community profile

The host-microbiota interplay is recognized as a key factor for the homeostatic maintenance in animals. In pigs, the weaning transition represents a drastic changes event leading to high risk of gut dysbiosis, which in most cases results in economic losses for swine industry. The blood type antigens expressed on mucosal surfaces can act as receptors for bacterial adhesion and the hypothesis of possible associations between blood groups and intestinal microbial profiles has been tested in human with contrasting results. Nevertheless, no studies testing the blood type as possible shaping factor for gut microbiota are available for pigs. The results of our previous study suggested the porcine AO blood types system as a possible factor influencing the microbiota composition. In the present study, the changes in fecal microbiota of 12 piglets were followed from 7 days after birth to 2 weeks post-weaning, testing the hypothesis that blood types may impact on its structure. No effects attributable to the difference in blood groups were detected, however, the sampling site (faeces) and the low statistical power might have masked the hypothesized impact. The data clearly showed the rearrangement of the bacterial ecosystem triggered by weaning transition; mainly consisting of a shift from a Bacteroidaceae-Enterobacteriaceae dominated community, to a Prevotellaceae-Ruminococcaceae dominated community. The functional analysis by metagenomic predictions suggested a role of the high levels of long-chain fatty acid in swine milk as energy source for Enterobacteriaceae (E. coli), in suckling piglets. This study provides a first insight for further investigations; indicating the need for larger sample size, preferably derived from intestinal mucosa, to test the potential effect of blood groups on gut microbiota profiles, and for analyses aimed at assessing the long-chain fatty acids degradation activity within the intestinal microbiota of suckling piglets, with particular attention to the role of E. coli.

Mapping the diversity of microbial lignin catabolism: experiences from the eLignin database

Lignin is a heterogeneous aromatic biopolymer and a major constituent of lignocellulosic biomass, such as wood and agricultural residues. Despite the high amount of aromatic carbon present, the severe recalcitrance of the lignin macromolecule makes it difficult to convert into value-added products. In nature, lignin and lignin-derived aromatic compounds are catabolized by a consortia of microbes specialized at breaking down the natural lignin and its constituents. In an attempt to bridge the gap between the fundamental knowledge on microbial lignin catabolism, and the recently emerging field of applied biotechnology for lignin biovalorization, we have developed the eLignin Microbial Database ( www.elignindatabase.com ), an openly available database that indexes data from the lignin bibliome, such as microorganisms, aromatic substrates, and metabolic pathways. In the present contribution, we introduce the eLignin database, use its dataset to map the reported ecological and biochemical diversity of the lignin microbial niches, and discuss the findings.

Rarity of microbial species: In search of reliable associations

The role of microbial interactions in defining the properties of microbiota is a topic of key interest in microbial ecology. Microbiota contain hundreds to thousands of operational taxonomic units (OTUs), most of them rare. This feature of community structure can lead to methodological difficulties: simulations have shown that methods for detecting pairwise associations between OTUs, which presumably reflect interactions, yield problematic results. The performance of association detection tools is impaired when there is a high proportion of zeros in OTU tables. Our goal was to understand the impact of OTU rarity on the detection of associations. We explored the utility of common statistics for testing associations; the sensitivity of alternative association measures; and the performance of network inference tools. We found that a large proportion of pairwise associations, especially negative associations, cannot be reliably tested. This constraint could hamper the identification of candidate biological agents that could be used to control rare pathogens. Identifying testable associations could serve as an objective method for filtering datasets in lieu of current empirical approaches. This trimming strategy could significantly reduce the computational time needed to infer networks and network inference quality. Different possibilities for improving the analysis of associations within microbiota are discussed.

In Vitro Infant Faecal Fermentation of Low Viscosity Barley β-Glucan and Its Acid Hydrolyzed Derivatives: Evaluation of Their Potential as Novel Prebiotics

Barley contains high level of β-1,3-1,4-glucans (BBGs) which can be fermented by microbes and are a potential prebiotic. In the present study, native BBG with low viscosity and a MW of 319 kDa was depolymerized by acid hydrolysis to produce a series of four structurally characterized fragments with MWs ranging from 6⁻104 kDa. In vitro fermentation of these BBG samples by infant faecal microbiome was evaluated using a validated deep-well plate protocol as parallel miniature bioreactors. Microbial taxa were identified using 16S amplicon sequencing after 40 h of anaerobic fermentation. Bioinformatics analysis including diversity indexes, predicted metagenomic KEGG functions and predicted phenotypes were performed on the sequenced data. Short chain fatty acids and dissolved ammonia were quantified and the SCFAs/NH₃ ratio was used to evaluate the eubiosis/dysbiosis potential. Correlation analysis showed that most of the parameters investigated showed a parabolic function instead of a monotonous function with the BBG samples having different MWs. Among the five BBGs, it was concluded that BBG with an intermediate MW of 28 kDa is the most promising candidate to be developed as a novel prebiotic.

Dynamics of the gut microbiota in developmental stages of Litopenaeus vannamei reveal its association with body weight

Increasing evidences have revealed a close interaction between the intestinal microbes and host growth performance. The shrimp (Litopenaeus vannamei) gut harbors a diverse microbial community, yet its associations with dietary, body weight and weaning age remain a matter of debate. In this study, we analyzed the effects of different dietary (fishmeal group (NC), krill meal group (KM)) and different growth stages (age from 42 day-old to 98 day-old) of the shrimp on the intestinal microbiota. High throughput sequencing of the 16S rRNA genes of shrimp intestinal microbes determined the novelty of bacteria in the shrimp gut microbiota and a core of 58 Operation Taxonomic Units (OTUs) was present among the shrimp gut samples. Analysis results indicated that the development of the shrimp gut microbiota is a dynamic process with three stages across the age according to the gut microbiota compositions. Furthermore, the dietary of KM group did not significantly change the intestinal microbiota of the shrimps compared with NC group. Intriguingly, compared to NC group, we observed in KM group that a fluctuation of the shrimp gut microbiota coincided with the shrimp body weight gain between weeks 6–7. Six OTUs associated with the microbiota change in KM group were identified. This finding strongly suggests that the shrimp gut microbiota may be correlated with the shrimp body weight likely by influencing nutrient uptake in the gut. The results obtained from this study potentially will be guidelines for manipulation to provide novel shrimp feed management approaches.

In the beginning was the word: How terminology drives our understanding of endosymbiotic organelles

The names we give objects of research, to some extent, predispose our ways of thinking about them. Misclassifications of Oomycota, Microsporidia, Myxosporidia, and Helicosporidia have obviously affected not only their formal taxonomic names, but also the methods and approaches with which they have been investigated. Therefore, it is important to name biological entities with accurate terms in order to avoid discrepancies in researching them. The endosymbiotic origin of mitochondria and plastids is now the most accepted scenario for their evolution. Since it is apparent that there is no natural definitive border between bacteria and semiautonomous organelles, I propose that mitochondria and plastids should be called bacteria and classified accordingly, in the bacterial classification system. I discuss some consequences of this approach, including: i) the resulting "changes" in the abundances of bacteria, ii) the definitions of terms like microbiome or multicellularity, and iii) the concept of endosymbiotic domestication.