A communal catalogue reveals Earth's multiscale microbial diversity

Geographical pattern of methanogenesis in paddy and wetland soils across eastern China

Large variation of CH₄ emissions from paddy and wetland ecosystems exists across different geographical locations in China. To obtain mechanistic understanding of this variation, we investigated the dynamics of methanogenesis over the course of glucose degradation in fourteen paddy field soils and five wetland soils collected from different regions of China. The results revealed that the maximal rate (2-3 mM per day) and the total amount (25-30 mM) of CH₄ produced were similar across soil samples. The lag phase of methanogenesis, however, differed substantially with the shortest lag phase of 4 days in a paddy soil from north China and the longest of 32 days in a soil from south China, and this difference reflected a general geographical trend among all soils tested. Nitrate was reduced completely within 4 days in all soils. The reduction of Fe(III) and sulfate was completed after 21 days and 29 days, respectively. The depletion time of Fe(III) and sulfate were positively correlated with the lag phase of methanogenesis. Competition for common substrates between methanogens and iron and sulfate reducers, however, does not explain this coincidence because a slow production of CH₄ was detected at the very beginning. It appears that the geographical variations in methanogenesis and the reduction of ferric iron and sulfate are related to the variation in soil pH but not to temperature, soil organic C and nutrient conditions in paddy and wetland soils across eastern China.

Tracing seafood at high spatial resolution using NGS-generated data and machine learning: Comparing microbiome versus SNPs

Developing reliable tools to trace food origin represents a major goal for producers and control authorities. Here, we test the hypothesis whether NGS-generated data could provide a reliable tool to ensure seafood traceability. As a test case, we used the Manila clam Ruditapes philippinarum, a bivalve mollusk of high commercial interest with worldwide distribution, collected in the Venice lagoon sites subjected to prohibition of clam harvesting because of chemical contamination as well as in authorized clam harvesting areas. The results obtained demonstrated that the geographic origin of Manila clam may be more accurately determined basing on microbiome data than single nucleotide polymorphisms. In particular, combining microbiome data with machine-learning techniques, we provide the experimental evidence that it is possible to trace the clam place of origin at high spatial resolution. Considering its low cost and portability, NGS-analysis of microbiome data might represent a cost-effective, high-resolution tool for reliable food traceability.

Future climate change is predicted to affect the microbiome and condition of habitat-forming kelp

Climate change is driving global declines of marine habitat-forming species through physiological effects and through changes to ecological interactions, with projected trajectories for ocean warming and acidification likely to exacerbate such impacts in coming decades. Interactions between habitat-formers and their microbiomes are fundamental for host functioning and resilience, but how such relationships will change in future conditions is largely unknown. We investigated independent and interactive effects of warming and acidification on a large brown seaweed, the kelp Ecklonia radiata, and its associated microbiome in experimental mesocosms. Microbial communities were affected by warming and, during the first week, by acidification. During the second week, kelp developed disease-like symptoms previously observed in the field. The tissue of some kelp blistered, bleached and eventually degraded, particularly under the acidification treatments, affecting photosynthetic efficiency. Microbial communities differed between blistered and healthy kelp for all treatments, except for those under future conditions of warming and acidification, which after two weeks resembled assemblages associated with healthy hosts. This indicates that changes in the microbiome were not easily predictable as the severity of future climate scenarios increased. Future ocean conditions can change kelp microbiomes and may lead to host disease, with potentially cascading impacts on associated ecosystems.

Evaluating Metagenomic Prediction of the Metaproteome in a 4.5-Year Study of a Patient with Crohn's Disease

Although genetic approaches are the standard in microbiome analysis, proteome-level information is largely absent. This discrepancy warrants a better understanding of the relationship between gene copy number and protein abundance, as this is crucial information for inferring protein-level changes from metagenomic data. As it remains unknown how metaproteomic systems evolve during dynamic disease states, we leveraged a 4.5-year fecal time series using samples from a single patient with colonic Crohn's disease. Utilizing multiplexed quantitative proteomics and shotgun metagenomic sequencing of eight time points in technical triplicate, we quantified over 29,000 protein groups and 110,000 genes and compared them to five protein biomarkers of disease activity. Broad-scale observations were consistent between data types, including overall clustering by principal-coordinate analysis and fluctuations in Gene Ontology terms related to Crohn's disease. Through linear regression, we determined genes and proteins fluctuating in conjunction with inflammatory metrics. We discovered conserved taxonomic differences relevant to Crohn's disease, including a negative association of Faecalibacterium and a positive association of Escherichia with calprotectin. Despite concordant associations of genera, the specific genes correlated with these metrics were drastically different between metagenomic and metaproteomic data sets. This resulted in the generation of unique functional interpretations dependent on the data type, with metaproteome evidence for previously investigated mechanisms of dysbiosis. An example of one such mechanism was a connection between urease enzymes, amino acid metabolism, and the local inflammation state within the patient. This proof-of-concept approach prompts further investigation of the metaproteome and its relationship with the metagenome in biologically complex systems such as the microbiome. IMPORTANCE A majority of current microbiome research relies heavily on DNA analysis. However, as the field moves toward understanding the microbial functions related to healthy and disease states, it is critical to evaluate how changes in DNA relate to changes in proteins, which are functional units of the genome. This study tracked the abundance of genes and proteins as they fluctuated during various inflammatory states in a 4.5-year study of a patient with colonic Crohn's disease. Our results indicate that despite a low level of correlation, taxonomic associations were consistent in the two data types. While there was overlap of the data types, several associations were uniquely discovered by analyzing the metaproteome component. This case study provides unique and important insights into the fundamental relationship between the genes and proteins of a single individual's fecal microbiome associated with clinical consequences.

Redox traits characterize the organization of global microbial communities

Biological communities are conventionally described as assemblages of species, whose ecological roles are known or predictable from their observable morphology. In microbial ecology, such a taxonomic approach is hindered by limited capacity to discriminate among different microbes, which bear highly dynamic genomes and establish complex associations. Approaches based on culture-independent functional genes profiling might overcome these problems, but a set of usable established genes in a general situation is still lacking. We show that genes related to reduction-oxidation (redox) processes separate microbial communities into their corresponding biomes. This redox-based characterization is linked to the microbial energetics of ecosystems and to most biogeochemical cycles and might be useful for assessing the impact of environmental degradation on the ecosystem services, underpinned by microorganisms.

The structure of biological communities is conventionally described as profiles of taxonomic units, whose ecological functions are assumed to be known or, at least, predictable. In environmental microbiology, however, the functions of a majority of microorganisms are unknown and expected to be highly dynamic and collectively redundant, obscuring the link between taxonomic structure and ecosystem functioning. Although genetic trait-based approaches at the community level might overcome this problem, no obvious choice of gene categories can be identified as appropriate descriptive units in a general ecological context. We used 247 microbial metagenomes from 18 biomes to determine which set of genes better characterizes the differences among biomes on the global scale. We show that profiles of oxidoreductase genes support the highest biome differentiation compared with profiles of other categories of enzymes, general protein-coding genes, transporter genes, and taxonomic gene markers. Based on oxidoreductases’ description of microbial communities, the role of energetics in differentiation and particular ecosystem function of different biomes become readily apparent. We also show that taxonomic diversity is decoupled from functional diversity, e.g., grasslands and rhizospheres were the most diverse biomes in oxidoreductases but not in taxonomy. Considering that microbes underpin biogeochemical processes and nutrient recycling through oxidoreductases, this functional diversity should be relevant for a better understanding of the stability and conservation of biomes. Consequently, this approach might help to quantify the impact of environmental stressors on microbial ecosystems in the context of the global-scale biome crisis that our planet currently faces.

CAMISIM: simulating metagenomes and microbial communities

BACKGROUND

Shotgun metagenome data sets of microbial communities are highly diverse, not only due to the natural variation of the underlying biological systems, but also due to differences in laboratory protocols, replicate numbers, and sequencing technologies. Accordingly, to effectively assess the performance of metagenomic analysis software, a wide range of benchmark data sets are required.

RESULTS

We describe the CAMISIM microbial community and metagenome simulator. The software can model different microbial abundance profiles, multi-sample time series, and differential abundance studies, includes real and simulated strain-level diversity, and generates second- and third-generation sequencing data from taxonomic profiles or de novo. Gold standards are created for sequence assembly, genome binning, taxonomic binning, and taxonomic profiling. CAMSIM generated the benchmark data sets of the first CAMI challenge. For two simulated multi-sample data sets of the human and mouse gut microbiomes, we observed high functional congruence to the real data. As further applications, we investigated the effect of varying evolutionary genome divergence, sequencing depth, and read error profiles on two popular metagenome assemblers, MEGAHIT, and metaSPAdes, on several thousand small data sets generated with CAMISIM.

CONCLUSIONS

CAMISIM can simulate a wide variety of microbial communities and metagenome data sets together with standards of truth for method evaluation. All data sets and the software are freely available at https://github.com/CAMI-challenge/CAMISIM.

A census-based estimate of Earth's bacterial and archaeal diversity

The global diversity of Bacteria and Archaea, the most ancient and most widespread forms of life on Earth, is a subject of intense controversy. This controversy stems largely from the fact that existing estimates are entirely based on theoretical models or extrapolations from small and biased data sets. Here, in an attempt to census the bulk of Earth's bacterial and archaeal ("prokaryotic") clades and to estimate their overall global richness, we analyzed over 1.7 billion 16S ribosomal RNA amplicon sequences in the V4 hypervariable region obtained from 492 studies worldwide, covering a multitude of environments and using multiple alternative primers. From this data set, we recovered 739,880 prokaryotic operational taxonomic units (OTUs, 16S-V4 gene clusters at 97% similarity), a commonly used measure of microbial richness. Using several statistical approaches, we estimate that there exist globally about 0.8–1.6 million prokaryotic OTUs, of which we recovered somewhere between 47%–96%, representing >99.98% of prokaryotic cells. Consistent with this conclusion, our data set independently "recaptured" 91%–93% of 16S sequences from multiple previous global surveys, including PCR-independent metagenomic surveys. The distribution of relative OTU abundances is consistent with a log-normal model commonly observed in larger organisms; the total number of OTUs predicted by this model is also consistent with our global richness estimates. By combining our estimates with the ratio of full-length versus partial-length (V4) sequence diversity in the SILVA sequence database, we further estimate that there exist about 2.2–4.3 million full-length OTUs worldwide. When restricting our analysis to the Americas, while controlling for the number of studies, we obtain similar richness estimates as for the global data set, suggesting that most OTUs are globally distributed. Qualitatively similar results are also obtained for other 16S similarity thresholds (90%, 95%, and 99%). Our estimates constrain the extent of a poorly quantified rare microbial biosphere and refute recent predictions that there exist trillions of prokaryotic OTUs.

A massive survey of Earth's Bacteria and Archaea reveals that their diversity is orders of magnitude lower than previously thought. The study also indicates that extinctions played an important role in prokaryotic evolution.

The global diversity of Bacteria and Archaea ("prokaryotes"), the most ancient and most widespread forms of life on Earth, is subject to high uncertainty. Here, to estimate the global diversity of prokaryotes, we analyzed a large number of 16S ribosomal RNA gene sequences, found in all prokaryotes and commonly used to catalogue prokaryotic diversity. Sequences were obtained from a multitude of environments across thousands of geographic locations worldwide. From this data set, we recovered 739,880 prokaryotic operational taxonomic units (OTUs), i.e., 16S gene clusters sharing 97% similarity, roughly corresponding to prokaryotic species. Using several statistical approaches and through comparison with existing databases and previous independent surveys, we estimate that there exist globally between 0.8 and 1.6 million prokaryotic OTUs. When restricting our analysis to the Americas, while controlling for the number of studies, we obtain similar estimates as for the global data set, suggesting that most OTUs are not restricted to a single continent but are instead globally distributed. Our estimates constrain the extent of a commonly hypothesized but poorly quantified rare prokaryotic biosphere and refute recent predictions that there exists trillions of prokaryotic OTUs. Our findings also indicate that, contrary to common speculation, extinctions may strongly influence global prokaryotic diversity.

Towards a systematic understanding of differences between archaeal and bacterial diversity

In this crystal ball, we discuss emerging methodologies that can help reaching a synthesis on the biodiversity of Archaea and Bacteria and thereby inform a central enigma in microbiology, i.e. the fundamental split between these primary domains of life and the apparent lower diversity of the Archaea.

Spatiotemporal Dynamics of Molecular Messaging in Bacterial Co-Cultures Studied by Multimodal Chemical Imaging

Microbial community behavior is coupled to a set of genetically-regulated chemical signals that correlate with cell density - the quorum sensing (QS) system - and there is growing appreciation that the QS-regulated behavior of bacteria is chemically, spatially, and temporally complex. In addition, while it has been known for some time that different species use different QS networks, we are beginning to appreciate that different strains of the same bacterial species also differ in their QS networks. Here we combine mass spectrometric imaging (MSI) and confocal Raman microscopy (CRM) approaches to investigate co-cultures involving different strains (FRD1 and PAO1C) of the same species (Pseudomonas aeruginosa) as well as those involving different species (P. aeruginosa and E. coli). Combining MSI and CRM makes it possible to supersede the limits imposed by individual imaging approaches and enables the spatial mapping of individual bacterial species and their microbial products within a mixed bacterial community growing in situ on surfaces. MSI is used to delineate the secretion of a specific rhamnolipid surfactant as well as alkyl quinolone (AQ) messengers between FRD1 and PAO1C strains of P. aeruginosa, showing that the spatial distribution and production rate of AQ messengers in PAO1C far outstrips that of FRD1. In the case of multiple species, CRM is used to show that the prolific secretion of AQs by the PAO1C strain of P. aeruginosa is used to mediate its interaction with co-cultured E. coli.

Available energy fluxes drive a transition in the diversity, stability, and functional structure of microbial communities

A fundamental goal of microbial ecology is to understand what determines the diversity, stability, and structure of microbial ecosystems. The microbial context poses special conceptual challenges because of the strong mutual influences between the microbes and their chemical environment through the consumption and production of metabolites. By analyzing a generalized consumer resource model that explicitly includes cross-feeding, stochastic colonization, and thermodynamics, we show that complex microbial communities generically exhibit a transition as a function of available energy fluxes from a "resource-limited" regime where community structure and stability is shaped by energetic and metabolic considerations to a diverse regime where the dominant force shaping microbial communities is the overlap between species' consumption preferences. These two regimes have distinct species abundance patterns, different functional profiles, and respond differently to environmental perturbations. Our model reproduces large-scale ecological patterns observed across multiple experimental settings such as nestedness and differential beta diversity patterns along energy gradients. We discuss the experimental implications of our results and possible connections with disorder-induced phase transitions in statistical physics.

Kelpie: generating full-length 'amplicons' from whole-metagenome datasets

Introduction

Whole-metagenome sequencing can be a rich source of information about the structure and function of entire metagenomic communities, but getting accurate and reliable results from these datasets can be challenging. Analysis of these datasets is founded on the mapping of sequencing reads onto known genomic regions from known organisms, but short reads will often map equally well to multiple regions, and to multiple reference organisms. Assembling metagenomic datasets prior to mapping can generate much longer and more precisely mappable sequences but the presence of closely related organisms and highly conserved regions makes metagenomic assembly challenging, and some regions of particular interest can assemble poorly. One solution to these problems is to use specialised tools, such as Kelpie, that can accurately extract and assemble full-length sequences for defined genomic regions from whole-metagenome datasets.

Methods

Kelpie is a kMer-based tool that generates full-length amplicon-like sequences from whole-metagenome datasets. It takes a pair of primer sequences and a set of metagenomic reads, and uses a combination of kMer filtering, error correction and assembly techniques to construct sets of full-length inter-primer sequences.

Results

The effectiveness of Kelpie is demonstrated here through the extraction and assembly of full-length ribosomal marker gene regions, as this allows comparisons with conventional amplicon sequencing and published metagenomic benchmarks. The results show that the Kelpie-generated sequences and community profiles closely match those produced by amplicon sequencing, down to low abundance levels, and running Kelpie on the synthetic CAMI metagenomic benchmarking datasets shows similar high levels of both precision and recall.

Conclusions

Kelpie can be thought of as being somewhat like an in-silico PCR tool, taking a primer pair and producing the resulting ‘amplicons’ from a whole-metagenome dataset. Marker regions from the 16S rRNA gene were used here as an example because this allowed the overall accuracy of Kelpie to be evaluated through comparisons with other datasets, approaches and benchmarks. Kelpie is not limited to this application though, and can be used to extract and assemble any genomic region present in a whole metagenome dataset, as long as it is bound by a pairs of highly conserved primer sequences.

Urogenital schistosomiasis is associated with signatures of microbiome dysbiosis in Nigerian adolescents

Urogenital schistosomiasis is a neglected tropical disease caused by the parasite Schistosoma haematobium, which resides in the vasculature surrounding the urogenital system. Previous work has suggested that helminthic infections can affect the intestinal microbiome, and we hypothesized that S. haematobium infection could result in an alteration of immune system-microbiota homeostasis and impact the composition of the gut microbiota. To address this question, we compared the fecal microbiomes of infected and uninfected schoolchildren from the Argungu Local Government Area of Kebbi State, Nigeria, detecting significant differences in community composition between the two groups. Most remarkably, we observed a decreased abundance of Firmicutes and increased abundance of Proteobacteria - a shift in community structure which has been previously associated with dysbiosis. More specifically, we detected a number of changes in lower taxa reminiscent of inflammation-associated dysbiosis, including decreases in Clostridiales and increases in Moraxellaceae, Veillonellaceae, Pasteurellaceae, and Desulfovibrionaceae. Functional potential analysis also revealed an enrichment in orthologs of urease, which has been linked to dysbiosis and inflammation. Overall, our analysis indicates that S. haematobium infection is associated with perturbations in the gut microbiota and may point to microbiome disruption as an additional consequence of schistosome infection.

Soil parameters, land use, and geographical distance drive soil bacterial communities along a European transect

To better understand the relationship between soil bacterial communities, soil physicochemical properties, land use and geographical distance, we considered for the first time ever a European transect running from Sweden down to Portugal and from France to Slovenia. We investigated 71 sites based on their range of variation in soil properties (pH, texture and organic matter), climatic conditions (Atlantic, alpine, boreal, continental, Mediterranean) and land uses (arable, forest and grassland). 16S rRNA gene amplicon pyrosequencing revealed that bacterial communities highly varied in diversity, richness, and structure according to environmental factors. At the European scale, taxa area relationship (TAR) was significant, supporting spatial structuration of bacterial communities. Spatial variations in community diversity and structure were mainly driven by soil physicochemical parameters. Within soil clusters (k-means approach) corresponding to similar edaphic and climatic properties, but to multiple land uses, land use was a major driver of the bacterial communities. Our analyses identified specific indicators of land use (arable, forest, grasslands) or soil conditions (pH, organic C, texture). These findings provide unprecedented information on soil bacterial communities at the European scale and on the drivers involved; possible applications for sustainable soil management are discussed.

The Microbiome Stress Project: Toward a Global Meta-Analysis of Environmental Stressors and Their Effects on Microbial Communities

Microbial community structure is highly sensitive to natural (e.g., drought, temperature, fire) and anthropogenic (e.g., heavy metal exposure, land-use change) stressors. However, despite an immense amount of data generated, systematic, cross-environment analyses of microbiome responses to multiple disturbances are lacking. Here, we present the Microbiome Stress Project, an open-access database of environmental and host-associated 16S rRNA amplicon sequencing studies collected to facilitate cross-study analyses of microbiome responses to stressors. This database will comprise published and unpublished datasets re-processed from the raw sequences into exact sequence variants using our standardized computational pipeline. Our database will provide insight into general response patterns of microbiome diversity, structure, and stability to environmental stressors. It will also enable the identification of cross-study associations between single or multiple stressors and specific microbial clades. Here, we present a proof-of-concept meta-analysis of 606 microbiomes (from nine studies) to assess microbial community responses to: (1) one stressor in one environment: soil warming across a variety of soil types, (2) a range of stressors in one environment: soil microbiome responses to a comprehensive set of stressors (incl. temperature, diesel, antibiotics, land use change, drought, and heavy metals), (3) one stressor across a range of environments: copper exposure effects on soil, sediment, activated-sludge reactors, and gut environments, and (4) the general trends of microbiome stressor responses. Overall, we found that stressor exposure significantly decreases microbiome alpha diversity and increases beta diversity (community dispersion) across a range of environments and stressor types. We observed a hump-shaped relationship between microbial community resistance to stressors (i.e., the average pairwise similarity score between the control and stressed communities) and alpha diversity. We used Phylofactor to identify microbial clades and individual taxa as potential bioindicators of copper contamination across different environments. Using standardized computational and statistical methods, the Microbiome Stress Project will leverage thousands of existing datasets to build a general framework for how microbial communities respond to environmental stress.

Evolutionary constraints on species diversity in marine bacterioplankton communities

Variation in microbial species diversity has typically been explained as the outcome of local ecological factors driving species coexistence, overlooking the roles of evolutionary constraints. Here, we argue that macro-evolutionary niche conservatism and unequal diversification rates among phylum-level lineages are strong determinants of diversity-environment relationships in bacterial systems. That is, apart from stochasticity, environmental effects operate most strongly on phylum composition, which in turn dictates the species diversity of bacterial communities. This concept is demonstrated using bacterioplankton in the surface seawaters of the East China Sea. Furthermore, we show that the species richness of a local bacterioplankton community can generally be estimated based on the relative abundances of phyla and their contributions of species numbers in the global seawater pool-highlighting the important influence of evolutionary constraints on local community diversity.

Microbiome 101: Studying, Analyzing, and Interpreting Gut Microbiome Data for Clinicians

Advances in technical capabilities for reading complex human microbiomes are leading to an explosion of microbiome research, leading in turn to intense interest among clinicians in applying these techniques to their patients. In this review, we discuss the content of the human microbiome, including intersubject and intrasubject variability, considerations of study design including important confounding factors, and different methods in the laboratory and on the computer to read the microbiome and its resulting gene products and metabolites. We highlight several common pitfalls for clinicians, including the expectation that an individual's microbiome will be stable, that diet can induce rapid changes that are large compared with the differences among subjects, that everyone has essentially the same core stool microbiome, and that different laboratory and computational methods will yield essentially the same results. We also highlight the current limitations and future promise of these techniques, with the expectation that an understanding of these considerations will help accelerate the path toward routine clinical application of these techniques developed in research settings.

The Microbiome and Its Potential for Pharmacology

The human microbiota (the microscopic organisms that inhabit us) and microbiome (their genes) hold considerable potential for improving pharmacological practice. Recent advances in multi-"omics" techniques have dramatically improved our understanding of the constituents of the microbiome and their functions. The implications of this research for human health, including microbiome links to obesity, drug metabolism, neurological diseases, cancer, and many other health conditions, have sparked considerable interest in exploiting the microbiome for targeted therapeutics. Links between microbial pathways and disease states further highlight a rich potential for companion diagnostics and precision medicine approaches. For example, the success of fecal microbiota transplantation to treat Clostridium difficile infection has already started to redefine standard of care with a microbiome-directed therapy. In this review we briefly discuss the nature of human microbial ecosystems and with pathologies and biological processes linked to the microbiome. We then review emerging computational metagenomic, metabolomic, and wet lab techniques researchers are using today to learn about the roles host-microbial interactions have with respect to pharmacological purposes and vice versa. Finally, we describe how drugs affect the microbiome, how the microbiome can impact drug response in different people, and the potential of the microbiome itself as a source of new therapeutics.

Identification of Microbial Dark Matter in Antarctic Environments

Numerous studies have applied molecular techniques to understand the diversity, evolution, and ecological function of Antarctic bacteria and archaea. One common technique is sequencing of the 16S rRNA gene, which produces a nearly quantitative profile of community membership. However, the utility of this and similar approaches is limited by what is known about the evolution, physiology, and ecology of surveyed taxa. When representative genomes are available in public databases some of this information can be gleaned from genomic studies, and automated pipelines exist to carry out this task. Here the paprica metabolic inference pipeline was used to assess how well Antarctic microbial communities are represented by the available completed genomes. The NCBI's Sequence Read Archive (SRA) was searched for Antarctic datasets that used one of the Illumina platforms to sequence the 16S rRNA gene. These data were quality controlled and denoised to identify unique reads, then analyzed with paprica to determine the degree of overlap with the closest phylogenetic neighbor with a completely sequenced genome. While some unique reads had perfect mapping to 16S rRNA genes from completed genomes, the mean percent overlap for all mapped reads was 86.6%. When samples were grouped by environment, some environments appeared more or less well represented by the available genomes. For the domain Bacteria, seawater was particularly poorly represented with a mean overlap of 80.2%, while for the domain Archaea glacial ice was particularly poorly represented with an overlap of only 48.0% for a single sample. These findings suggest that a considerable effort is needed to improve the representation of Antarctic microbes in genome sequence databases.

Bacterial-fungal interactions: ecology, mechanisms and challenges

Fungi and bacteria are found living together in a wide variety of environments. Their interactions are significant drivers of many ecosystem functions and are important for the health of plants and animals. A large number of fungal and bacterial families engage in complex interactions that lead to critical behavioural shifts of the microorganisms ranging from mutualism to antagonism. The importance of bacterial-fungal interactions (BFI) in environmental science, medicine and biotechnology has led to the emergence of a dynamic and multidisciplinary research field that combines highly diverse approaches including molecular biology, genomics, geochemistry, chemical and microbial ecology, biophysics and ecological modelling. In this review, we discuss recent advances that underscore the roles of BFI across relevant habitats and ecosystems. A particular focus is placed on the understanding of BFI within complex microbial communities and in regard of the metaorganism concept. We also discuss recent discoveries that clarify the (molecular) mechanisms involved in bacterial-fungal relationships, and the contribution of new technologies to decipher generic principles of BFI in terms of physical associations and molecular dialogues. Finally, we discuss future directions for research in order to stimulate synergy within the BFI research area and to resolve outstanding questions.

Clinician Guide to Microbiome Testing

Recent recognition that the intestinal microbiome plays potential roles in the pathogenesis of multiple common diseases has led to a growing interest in personalized microbiome analysis among clinical investigators and patients. Permissibility of direct access testing has allowed the emergence of commercial companies offering microbiome analysis to patients seeking to gain a better understanding of their symptoms and disease conditions. In turn, physicians are often asked to help with interpretation of such tests or even requested by their patients to order them. Therefore, physicians need to have a basic understanding of the current state of microbiome science. This review examines how the perspective of microbial ecology, which is fundamental to understanding the microbiome, updates the classical version of the germ theory of disease. We provide the essential vocabulary of microbiome science and describe its current limitations. We look forward to the future when microbiome diagnostics may live up to its potential of becoming integral to clinical care that will become increasingly individualized, and microbiome analysis may become incorporated into that future paradigm. However, we caution patients and providers that the current microbiome tests, given the state of knowledge and technology, do not provide much value in clinical decisions. Considerable research remains to be carried out to make this objective a reality.

Microbial diversity and biogeography in Arctic soils

Microorganisms dominate terrestrial environments in the polar regions and Arctic soils are known to harbour significant microbial diversity, far more diverse and numerous in the region than was once thought. Furthermore, the geographic distribution and structure of Arctic microbial communities remains elusive, despite their important roles in both biogeochemical cycling and in the generation and decomposition of climate active gases. Critically, Arctic soils are estimated to store over 1500 Pg of carbon and, thus, have the potential to generate positive feedback within the climate system. As the Arctic region is currently undergoing rapid change, the likelihood of faster release of greenhouse gases such as CO₂ , CH₄ and N₂ O is increasing. Understanding the microbial communities in the region, in terms of their diversity, abundance and functional activity, is key to producing accurate models of greenhouse gas release. This review brings together existing data to determine what we know about microbial diversity and biogeography in Arctic soils.

A practical introduction to microbial molecular ecology through the use of isolation chips

In the context of antimicrobial resistance as one of the most serious issues faced globally by health providers, we explored a practical introduction to molecular microbial ecology. We designed field work and practical experiments for third year members of a 4 year undergraduate Masters Program, in which the students employed traditional and novel isolation techniques to identify antimicrobial activities from soil dwelling microorganisms. Students gained experience in isolating DNA from complex microbial communities, amplifying 16S rRNA genes and applied richness/diversity indices as well as principal coordinate analyses to the interpretation of the data they obtained from high throughput sequencing. Our results confirmed that isolation chips facilitate the growth of a greater diversity and different species subset from the complex soil microorganism community than traditional plate spreading techniques. However, rarefaction of 16S rRNA amplicon sequencing data showed that the majority of observed species in soil remain unculturable by current methods. Based on the written reports produced by the students carrying out the work, we concluded that the described protocols are robust and informative, that these activities provide a good practical introduction to the theories and practice of molecular ecology and can be easily deployed to groups of six or more students in a cost-effective manner.

Gut microbial features can predict host phenotype response to protein deficiency

Malnutrition remains a major health problem in low- and middle-income countries. During low protein intake, <0.67 g/kg/day, there is a loss of nitrogen (N2 ) balance, due to the unavailability of amino acid for metabolism and unbalanced protein catabolism results. However, there are individuals, who consume the same low protein intake, and preserve N2 balance for unknown reasons. A novel factor, the gut microbiota, may account for these N2 balance differences. To investigate this, we correlated gut microbial profiles with the growth of four murine strains (C57Bl6/J, CD-1, FVB, and NIH-Swiss) on protein deficient (PD) diet. Results show that a PD diet exerts a strain-dependent impact on growth and N2 balance as determined through analysis of urinary urea, ammonia and creatinine excretion. Bacterial alpha diversity was significantly (P < 0.05, FDR) lower across all strains on a PD diet compared to normal chow (NC). Multi-group analyses of the composition of microbiomes (ANCOM) revealed significantly differential microbial signatures between the four strains independent of diet. However, mice on a PD diet demonstrated differential enrichment of bacterial genera including, Allobaculum (C57Bl6/J), Parabacteroides (CD-1), Turicibacter (FVB), and Mucispirillum (NIH-Swiss) relative to NC. For instance, selective comparison of the CD-1 (gained weight) and C57Bl6/J (did not gain weight) strains on PD diet also demonstrated significant pathway enrichment of dihydroorodate dehydrogenase, rRNA methyltransferases, and RNA splicing ligase in the CD-1 strains compared to C57Bl6/J strains; which might account in their ability to retain growth despite a protein deficient diet. Taken together, these results suggest a potential relationship between the specific gut microbiota, N2 balance and animal response to malnutrition.

Experimental bacterial adaptation to the zebrafish gut reveals a primary role for immigration

All animals live in intimate association with microorganisms that profoundly influence their health and development, yet the traits that allow microorganisms to establish and maintain host associations are not well understood. To date, most investigations aimed at identifying traits required for host association have focused on intrahost niches. Consequently, little is known about the relative contribution of extrahost factors such as environmental growth and survival and immigration into hosts from the external environment, as promoters of host association. To address this, we developed a tractable experimental evolution system that investigates both intra- and extrahost factors contributing to bacterial adaptation to the vertebrate gut. We passaged replicate lines of a zebrafish bacterial isolate, Aeromonas veronii, through populations of germ-free larval zebrafish (Danio rerio), each time using gut-associated Aeromonas populations to inoculate the aquatic environment of the next zebrafish population. We observed rapid increased adaptation to the host in all replicate lines. The initial adaptations present in early-evolved isolates did not increase intrahost fitness but rather enhanced both immigration from the environment and interhost transmission. Only in later-evolved isolates did we find evidence for intrahost-specific adaptations, as demonstrated by comparing their competitive fitness in the host genotype to which they evolved to that in a different genotype. Our results show how selection for bacterial transmission between hosts and their environment can shape bacterial-host association. This work illuminates the nature of selective forces present in host-microbe systems and reveals specific mechanisms of increased host association. Furthermore, our findings demonstrate that the entire host-microbe-environment system must be considered when identifying microbial traits that contribute to host adaptation.

SEDE-GPS: socio-economic data enrichment based on GPS information

BACKGROUND

Microbes are essentail components of all ecosystems because they drive many biochemical processes and act as primary producers. In freshwater ecosystems, the biodiversity in and the composition of microbial communities can be used as indicators for environmental quality. Recently, some environmental features have been identified that influence microbial ecosystems. However, the impact of human action on lake microbiomes is not well understood. This is, in part, due to the fact that environmental data is, albeit theoretically accessible, not easily available.

RESULTS

In this work, we present SEDE-GPS, a tool that gathers data that are relevant to the environment of an user-provided GPS coordinate. To this end, it accesses a list of public and corporate databases and aggregates the information in a single file, which can be used for further analysis. To showcase the use of SEDE-GPS, we enriched a lake microbial ecology sequencing dataset with around 18,000 socio-economic, climate, and geographic features. The sources of SEDE-GPS are public databases such as Eurostat, the Climate Data Center, and OpenStreetMap, as well as corporate sources such as Twitter. Using machine learning and feature selection methods, we were able to identify features in the data provided by SEDE-GPS that can be used to predict lake microbiome alpha diversity.

CONCLUSION

The results presented in this study show that SEDE-GPS is a handy and easy-to-use tool for comprehensive data enrichment for studies of ecology and other processes that are affected by environmental features. Furthermore, we present lists of environmental, socio-economic, and climate features that are predictive for microbial biodiversity in lake ecosystems. These lists indicate that human action has a major impact on lake microbiomes. SEDE-GPS and its source code is available for download at http://SEDE-GPS.heiderlab.de.

Multiple Facets of Marine Invertebrate Conservation Genomics

Conservation genomics aims to preserve the viability of populations and the biodiversity of living organisms. Invertebrate organisms represent 95% of animal biodiversity; however, few genomic resources currently exist for the group. The subset of marine invertebrates includes the most ancient metazoan lineages and possesses codes for unique gene products and possible keys to adaptation. The benefits of supporting invertebrate conservation genomics research (e.g., likely discovery of novel genes, protein regulatory mechanisms, genomic innovations, and transposable elements) outweigh the various hurdles (rare, small, or polymorphic starting materials). Here we review best conservation genomics practices in the laboratory and in silico when applied to marine invertebrates and also showcase unique features in several case studies of acroporid corals, crown-of-thorns starfish, apple snails, and abalone. Marine conservation genomics should also address how diversity can lead to unique marine innovations, the impact of deleterious variation, and how genomic monitoring and profiling could positively affect broader conservation goals (e.g., value of baseline data for in situ/ex situ genomic stocks).

The murine vaginal microbiota and its perturbation by the human pathogen group B Streptococcus

BACKGROUND

Composition of the vaginal microbiota has significant influence on female urogenital health and control of infectious disease. Murine models are widely utilized to characterize host-pathogen interactions within the vaginal tract, however, the composition of endogenous vaginal flora remains largely undefined with modern microbiome analyses. Here, we employ 16S rRNA amplicon sequencing to establish the native microbial composition of the vaginal tract in adult C57Bl/6 J mice. We further interrogate the impact of estrous cycle and introduction of the human vaginal pathobiont, group B Streptococcus (GBS) on community state type and stability, and conversely, the impact of the vaginal microbiota on GBS persistence.

RESULTS

Sequencing analysis revealed five distinctive community states of the vaginal microbiota dominated largely by Staphylococcus and/or Enterococcus, Lactobacillus, or a mixed population. Stage of estrus did not impact microbial composition. Introduction of GBS decreased community stability at early timepoints; and in some mice, GBS became the dominant bacterium by day 21. Endogenous Staphylococcus abundance correlated with GBS ascension into the uterus, and increased community stability in GBS-challenged mice.

CONCLUSIONS

The murine vaginal flora is diverse and fluctuates independently of the estrous cycle. Endogenous flora may impact pathogen colonization and dissemination and should be considered in urogenital infection models.

On the Road to Breeding 4.0: Unraveling the Good, the Bad, and the Boring of Crop Quantitative Genomics

Understanding the quantitative genetics of crops has been and will continue to be central to maintaining and improving global food security. We outline four stages that plant breeding either has already achieved or will probably soon achieve. Top-of-the-line breeding programs are currently in Breeding 3.0, where inexpensive, genome-wide data coupled with powerful algorithms allow us to start breeding on predicted instead of measured phenotypes. We focus on three major questions that must be answered to move from current Breeding 3.0 practices to Breeding 4.0: ( a) How do we adapt crops to better fit agricultural environments? ( b) What is the nature of the diversity upon which breeding can act? ( c) How do we deal with deleterious variants? Answering these questions and then translating them to actual gains for farmers will be a significant part of achieving global food security in the twenty-first century.

Benchmarking taxonomic assignments based on 16S rRNA gene profiling of the microbiota from commonly sampled environments

Background

Taxonomic profiling of ribosomal RNA (rRNA) sequences has been the accepted norm for inferring the composition of complex microbial ecosystems. Quantitative Insights Into Microbial Ecology (QIIME) and mothur have been the most widely used taxonomic analysis tools for this purpose, with MAPseq and QIIME 2 being two recently released alternatives. However, no independent and direct comparison between these four main tools has been performed. Here, we compared the default classifiers of MAPseq, mothur, QIIME, and QIIME 2 using synthetic simulated datasets comprised of some of the most abundant genera found in the human gut, ocean, and soil environments. We evaluate their accuracy when paired with both different reference databases and variable sub-regions of the 16S rRNA gene.

Findings

We show that QIIME 2 provided the best recall and F-scores at genus and family levels, together with the lowest distance estimates between the observed and simulated samples. However, MAPseq showed the highest precision, with miscall rates consistently <2%. Notably, QIIME 2 was the most computationally expensive tool, with CPU time and memory usage almost 2 and 30 times higher than MAPseq, respectively. Using the SILVA database generally yielded a higher recall than using Greengenes, while assignment results of different 16S rRNA variable sub-regions varied up to 40% between samples analysed with the same pipeline.

Conclusions

Our results support the use of either QIIME 2 or MAPseq for optimal 16S rRNA gene profiling, and we suggest that the choice between the two should be based on the level of recall, precision, and/or computational performance required.

Differential Activation of Hepatic Invariant NKT Cell Subsets Plays a Key Role in Progression of Nonalcoholic Steatohepatitis

Innate immune mechanisms play an important role in inflammatory chronic liver diseases. In this study, we investigated the role of type I or invariant NKT (iNKT) cell subsets in the progression of nonalcoholic steatohepatitis (NASH). We used α-galactosylceramide/CD1d tetramers and clonotypic mAb together with intracytoplasmic cytokine staining to analyze iNKT cells in choline-deficient l-amino acid-defined (CDAA)-induced murine NASH model and in human PBMCs, respectively. Cytokine secretion of hepatic iNKT cells in CDAA-fed C57BL/6 mice altered from predominantly IL-17+ to IFN-γ+ and IL-4+ during NASH progression along with the downmodulation of TCR and NK1.1 expression. Importantly, steatosis, steatohepatitis, and fibrosis were dependent upon the presence of iNKT cells. Hepatic stellate cell activation and infiltration of neutrophils, Kupffer cells, and CD8+ T cells as well as expression of key proinflammatory and fibrogenic genes were significantly blunted in Jα18-/- mice and in C57BL/6 mice treated with an iNKT-inhibitory RAR-γ agonist. Gut microbial diversity was significantly impacted in Jα18-/- and in CDAA diet-fed mice. An increased frequency of CXCR3+IFN-γ+T-bet+ and IL-17A+ iNKT cells was found in PBMC from NASH patients in comparison with nonalcoholic fatty liver patients or healthy controls. Consistent with their in vivo activation, iNKT cells from NASH patients remained hyporesponsive to ex-vivo stimulation with α-galactosylceramide. Accumulation of plasmacytoid dendritic cells in both mice and NASH patients suggest their role in activation of iNKT cells. In summary, our findings indicate that the differential activation of iNKT cells play a key role in mediating diet-induced hepatic steatosis and fibrosis in mice and its potential involvement in NASH progression in humans.

Identifying and Predicting Novelty in Microbiome Studies

With the expansion of microbiome sequencing globally, a key challenge is to relate new microbiome samples to the existing space of microbiome samples. Here, we present Microbiome Search Engine (MSE), which enables the rapid search of query microbiome samples against a large, well-curated reference microbiome database organized by taxonomic similarity at the whole-microbiome level. Tracking the microbiome novelty score (MNS) over 8 years of microbiome depositions based on searching in more than 100,000 global 16S rRNA gene amplicon samples, we detected that the structural novelty of human microbiomes is approaching saturation and likely bounded, whereas that in environmental habitats remains 5 times higher. Via the microbiome focus index (MFI), which is derived from the MNS and microbiome attention score (MAS), we objectively track and compare the structural-novelty and attracted-attention scores of individual microbiome samples and projects, and we predict future trends in the field. For example, marine and indoor environments and mother-baby interactions are likely to receive disproportionate additional attention based on recent trends. Therefore, MNS, MAS, and MFI are proposed "alt-metrics" for evaluating a microbiome project or prospective developments in the microbiome field, both of which are done in the context of existing microbiome big data.IMPORTANCE We introduce two concepts to quantify the novelty of a microbiome. The first, the microbiome novelty score (MNS), allows identification of microbiomes that are especially different from what is already sequenced. The second, the microbiome attention score (MAS), allows identification of microbiomes that have many close neighbors, implying that considerable scientific attention is devoted to their study. By computing a microbiome focus index based on the MNS and MAS, we objectively track and compare the novelty and attention scores of individual microbiome samples and projects over time and predict future trends in the field; i.e., we work toward yielding fundamentally new microbiomes rather than filling in the details. Therefore, MNS, MAS, and MFI can serve as "alt-metrics" for evaluating a microbiome project or prospective developments in the microbiome field, both of which are done in the context of existing microbiome big data.

Trace Evidence Potential in Postmortem Skin Microbiomes: From Death Scene to Morgue

Microbes can be used effectively as trace evidence, at least in research settings. However, it is unknown whether skin microbiomes change prior to autopsy and, if so, whether these changes interfere with linking objects to decedents. The current study included microbiomes from 16 scenes of death in the City and County of Honolulu and tested whether objects at the scenes can be linked to individual decedents. Postmortem skin microbiomes were stable during repeated sampling up to 60 h postmortem and were similar to microbiomes of an antemortem population. Objects could be traced to decedents approximately 75% of the time, with smoking pipes and medical devices being especially accurate (100% match), house and car keys being poor (0%), and other objects like phones intermediate (~80%). These results show that microbes from objects at death scenes can be matched to individual decedents, opening up a new method of establishing associations and identifications.

From hairballs to hypotheses-biological insights from microbial networks

Microbial networks are an increasingly popular tool to investigate microbial community structure, as they integrate multiple types of information and may represent systems-level behaviour. Interpreting these networks is not straightforward, and the biological implications of network properties are unclear. Analysis of microbial networks allows researchers to predict hub species and species interactions. Additionally, such analyses can help identify alternative community states and niches. Here, we review factors that can result in spurious predictions and address emergent properties that may be meaningful in the context of the microbiome. We also give an overview of studies that analyse microbial networks to identify new hypotheses. Moreover, we show in a simulation how network properties are affected by tool choice and environmental factors. For example, hub species are not consistent across tools, and environmental heterogeneity induces modularity. We highlight the need for robust microbial network inference and suggest strategies to infer networks more reliably.

Reevaluating the Salty Divide: Phylogenetic Specificity of Transitions between Marine and Freshwater Systems

Marine and freshwater microbial communities are phylogenetically distinct, and transitions between habitat types are thought to be infrequent. We compared the phylogenetic diversity of marine and freshwater microorganisms and identified specific lineages exhibiting notably high or low similarity between marine and freshwater ecosystems using a meta-analysis of 16S rRNA gene tag-sequencing data sets. As expected, marine and freshwater microbial communities differed in the relative abundance of major phyla and contained habitat-specific lineages. At the same time, and contrary to expectations, many shared taxa were observed in both habitats. Based on several metrics, we found that Gammaproteobacteria, Alphaproteobacteria, Bacteroidetes, and Betaproteobacteria contained the highest number of closely related marine and freshwater sequences, suggesting comparatively recent habitat transitions in these groups. Using the abundant alphaproteobacterial group SAR11 as an example, we found evidence that new lineages, beyond the recognized LD12 clade, are detected in freshwater at low but reproducible abundances; this evidence extends beyond the 16S rRNA locus to core genes throughout the genome. Our results suggest that shared taxa are numerous, but tend to occur sporadically and at low relative abundance in one habitat type, leading to an underestimation of transition frequency between marine and freshwater habitats. Rare taxa with abundances near or below detection, including lineages that appear to have crossed the salty divide relatively recently, may possess adaptations enabling them to exploit opportunities for niche expansion when environments are disturbed or conditions change. IMPORTANCE The distribution of microbial diversity across environments yields insight into processes that create and maintain this diversity as well as potential to infer how communities will respond to future environmental changes. We integrated data sets from dozens of freshwater lake and marine samples to compare diversity across open water habitats differing in salinity. Our novel combination of sequence-based approaches revealed lineages that likely experienced a recent transition across habitat types. These taxa are promising targets for studying physiological constraints on salinity tolerance. Our findings contribute to understanding the ecological and evolutionary controls on microbial distributions, and open up new questions regarding the plasticity and adaptability of particular lineages.

High-Throughput Miniaturized 16S rRNA Amplicon Library Preparation Reduces Costs while Preserving Microbiome Integrity

Next-generation sequencing technologies have enabled many advances across biology, with microbial ecology benefiting primarily through expanded sample sizes. Although the cost of running sequencing instruments has decreased substantially over time, the price of library preparation methods has largely remained unchanged. In this study, we developed a low-cost miniaturized (5-µl volume) high-throughput (384-sample) amplicon library preparation method with the Echo 550 acoustic liquid handler. Our method reduces costs of library preparation to $1.42 per sample, a 58% reduction compared to existing automated methods and a 21-fold reduction from commercial kits, without compromising sequencing success or distorting the microbial community composition analysis. We further validated the optimized method by sampling five body sites from 46 Pacific chub mackerel fish caught across 16 sampling events over seven months from the Scripps Institution of Oceanography pier in La Jolla, CA. Fish microbiome samples were processed with the miniaturized 5-µl reaction volume with 0.2 µl of genomic DNA (gDNA) and the standard 25-µl reaction volume with 1 µl of gDNA. Between the two methods, alpha diversity was highly correlated (R 2 > 0.95), while distances of technical replicates were much lower than within-body-site variation (P < 0.0001), further validating the method. The cost savings of implementing the miniaturized library preparation (going from triplicate 25-µl reactions to triplicate 5-µl reactions) are large enough to cover a MiSeq sequencing run for 768 samples while preserving accurate microbiome measurements. IMPORTANCE Reduced costs of sequencing have tremendously impacted the field of microbial ecology, allowing scientists to design more studies with larger sample sizes that often exceed 10,000 samples. Library preparation costs have not kept pace with sequencing prices, although automated liquid handling robots provide a unique opportunity to bridge this gap while also decreasing human error. Here, we take advantage of an acoustic liquid handling robot to develop a high-throughput miniaturized library preparation method of a highly cited and broadly used 16S rRNA gene amplicon reaction. We evaluate the potential negative effects of reducing the PCR volume along with varying the amount of gDNA going into the reaction. Our optimized method reduces sample-processing costs while continuing to generate a high-quality microbiome readout that is indistinguishable from the original method.

Evaluating the Information Content of Shallow Shotgun Metagenomics

Although microbial communities are associated with human, environmental, plant, and animal health, there exists no cost-effective method for precisely characterizing species and genes in such communities. While deep whole-metagenome shotgun (WMS) sequencing provides high taxonomic and functional resolution, it is often prohibitively expensive for large-scale studies. The prevailing alternative, 16S rRNA gene amplicon (16S) sequencing, often does not resolve taxonomy past the genus level and provides only moderately accurate predictions of the functional profile; thus, there is currently no widely accepted approach to affordable, high-resolution, taxonomic, and functional microbiome analysis. To address this technology gap, we evaluated the information content of shallow shotgun sequencing with as low as 0.5 million sequences per sample as an alternative to 16S sequencing for large human microbiome studies. We describe a library preparation protocol enabling shallow shotgun sequencing at approximately the same per-sample cost as 16S sequencing. We analyzed multiple real and simulated biological data sets, including two novel human stool samples with ultradeep sequencing of 2.5 billion sequences per sample, and found that shallow shotgun sequencing recovers more-accurate species-level taxonomic and functional profiles of the human microbiome than 16S sequencing. We discuss the inherent limitations of shallow shotgun sequencing and note that 16S sequencing remains a valuable and important method for taxonomic profiling of novel environments. Although deep WMS sequencing remains the gold standard for high-resolution microbiome analysis, we recommend that researchers consider shallow shotgun sequencing as a useful alternative to 16S sequencing for large-scale human microbiome research studies where WMS sequencing may be cost-prohibitive. IMPORTANCE A common refrain in recent microbiome-related academic meetings is that the field needs to move away from broad taxonomic surveys using 16S sequencing and toward more powerful longitudinal studies using shotgun sequencing. However, performing deep shotgun sequencing in large longitudinal studies remains prohibitively expensive for all but the most well-funded research labs and consortia, which leads many researchers to choose 16S sequencing for large studies, followed by deep shotgun sequencing on a subset of targeted samples. Here, we show that shallow- or moderate-depth shotgun sequencing may be used by researchers to obtain species-level taxonomic and functional data at approximately the same cost as amplicon sequencing. While shallow shotgun sequencing is not intended to replace deep shotgun sequencing for strain-level characterization, we recommend that microbiome scientists consider using shallow shotgun sequencing instead of 16S sequencing for large-scale human microbiome studies.

Differences in the fecal microbiota of neonates born at home or in the hospital

Research on the neonatal microbiome has been performed mostly on hospital-born infants, who often undergo multiple birth-related interventions. Both the hospital environment and interventions around the time of birth may affect the neonate microbiome. In this study, we determine the structure of the microbiota in feces from babies born in the hospital or at home, and from vaginal samples of their mothers. We included 35 vaginally-born, breast-fed neonates, 14 of whom delivered at home (4 in water), and 21 who delivered in the hospital. Feces from babies and mothers and maternal vaginal swab samples were collected at enrollment, the day of birth, followed by days 1, 2, 7, 14, 21, and 28. At the time of birth, the diversity of the vaginal microbiota of mothers delivering in the hospital was lower than in mothers delivering at home, and showed higher proportion of Lactobacillus. Among 20 infants not exposed to perinatal maternal antibiotics or water birth, fecal beta diversity differed significantly by birth site, with hospital-born infants having lower Bacteroides, Bifidobacterium, Streptococcus, and Lactobacillus, and higher Clostridium and Enterobacteriaceae family (LDA > 3.0), than babies born at home. At 1 month of age, feces from infants born in the hospital also induced greater pro-inflammatory gene expression (TLR4, IL-8, occludin and TGFβ) in human colon epithelial HT-29 cells. The results of this work suggest that hospitalization (perinatal interventions or the hospital environment) may affect the microbiota of the vaginal source and the initial colonization during labor and birth, with effects that could persist in the intestinal microbiota of infants 1 month after birth. More research is needed to determine specific factors that alter bacterial transmission between mother and baby and the long-term health implications of these differences for the developing infant.

Microbial forensics: new breakthroughs and future prospects

Recent advances in genetic data generation, through massive parallel sequencing (MPS), storage and analysis have fostered significant progresses in microbial forensics (or forensic microbiology). Initial applications in circumstances of biocrime, bioterrorism and epidemiology are now accompanied by the prospect of using microorganisms (i) as ancillary evidence in criminal cases; (ii) to clarify causes of death (e.g., drownings, toxicology, hospital-acquired infections, sudden infant death and shaken baby syndromes); (iii) to assist human identification (skin, hair and body fluid microbiomes); (iv) for geolocation (soil microbiome); and (v) to estimate postmortem interval (thanatomicrobiome and epinecrotic microbial community). When compared with classical microbiological methods, MPS offers a diverse range of advantages and alternative possibilities. However, prior to its implementation in the forensic context, critical efforts concerning the elaboration of standards and guidelines consolidated by the creation of robust and comprehensive reference databases must be undertaken.

Pangenomic comparison of globally distributed Poribacteria associated with sponge hosts and marine particles

Candidatus Poribacteria is a little-known bacterial phylum, previously characterized by partial genomes from a single sponge host, but never isolated in culture. We have reconstructed multiple genome sequences from four different sponge genera and compared them to recently reported, uncharacterized Poribacteria genomes from the open ocean, discovering shared and unique functional characteristics. Two distinct, habitat-linked taxonomic lineages were identified, designated Entoporibacteria (sponge-associated) and Pelagiporibacteria (free-living). These lineages differed in flagellar motility and chemotaxis genes unique to Pelagiporibacteria, and highly expanded families of restriction endonucleases, DNA methylases, transposases, CRISPR repeats, and toxin-antitoxin gene pairs in Entoporibacteria. Both lineages shared pathways for facultative anaerobic metabolism, denitrification, fermentation, organosulfur compound utilization, type IV pili, cellulosomes, and bacterial proteosomes. Unexpectedly, many features characteristic of eukaryotic host association were also shared, including genes encoding the synthesis of eukaryotic-like cell adhesion molecules, extracellular matrix digestive enzymes, phosphoinositol-linked membrane glycolipids, and exopolysaccharide capsules. Complete Poribacteria 16S rRNA gene sequences were found to contain multiple mismatches to "universal" 16S rRNA gene primer sets, substantiating concerns about potential amplification failures in previous studies. A newly designed primer set corrects these mismatches, enabling more accurate assessment of Poribacteria abundance in diverse marine habitats where it may have previously been overlooked.

Practical considerations for sampling and data analysis in contemporary metagenomics-based environmental studies

Recent advancements in metagenomic-based studies, especially analyses of amplicon-based DNA sequencing targeting taxonomic marker genes, has led to an unprecedented characterization of microbial communities from diverse ecosystems around the world. While originally constrained by a lack of appropriate analytical tools and sequencing depth, new technologies and computational and statistical algorithms have been developed to handle highly dimensional, next-generation sequencing datasets. Both these tools allow for the robust analysis of structural and distributional patterns of microbiota essential for the understanding of microbial ecology and biogeography. Furthermore, consortia of individual laboratories working on large interdisciplinary research programs, like the Human and Earth Microbiome Projects, have developed standardized protocols for DNA extraction, sequencing pipelines, and bioinformatics. These approaches provide large repositories of publicly available data to serve as references for on-going and future, hypothesis-driven studies to better characterize the roles of microbial communities in diverse ecosystems. In this review, we outline the currently available statistical approaches and tools to aid in statistically powered study designs and analyses. Given what is now known about the enormous diversity and variability of the microbial communities in aquatic and terrestrial habitats, we also discuss practical considerations for sample collection. Due to the extensive advances made in the field of metagenomics over the last decade, rigorous, well replicated, hypothesis-driven studies are: 1) needed, 2) now possible, and 3) essential to make best use of sequencing-based technologies to characterize the roles of microbial communities in the structure and function of diverse ecosystems.

Qiita: rapid, web-enabled microbiome meta-analysis

Multi-omic insights into microbiome function and composition typically advance one study at a time. However, to understand relationships across studies, they must be aggregated into meta-analyses. This makes it possible to generate new hypotheses by finding features that are reproducible across biospecimens and data layers. Qiita dramatically accelerates such integration tasks in a web-based microbiome comparison platform, which we demonstrate with Human Microbiome Project and iHMP data.

The future of biotic indices in the ecogenomic era: Integrating (e)DNA metabarcoding in biological assessment of aquatic ecosystems

The bioassessment of aquatic ecosystems is currently based on various biotic indices that use the occurrence and/or abundance of selected taxonomic groups to define ecological status. These conventional indices have some limitations, often related to difficulties in morphological identification of bioindicator taxa. Recent development of DNA barcoding and metabarcoding could potentially alleviate some of these limitations, by using DNA sequences instead of morphology to identify organisms and to characterize a given ecosystem. In this paper, we review the structure of conventional biotic indices, and we present the results of pilot metabarcoding studies using environmental DNA to infer biotic indices. We discuss the main advantages and pitfalls of metabarcoding approaches to assess parameters such as richness, abundance, taxonomic composition and species ecological values, to be used for calculation of biotic indices. We present some future developments to fully exploit the potential of metabarcoding data and improve the accuracy and precision of their analysis. We also propose some recommendations for the future integration of DNA metabarcoding to routine biomonitoring programs.