DADA2: High-resolution sample inference from Illumina amplicon data

Microbial rRNA gene expression and co-occurrence profiles associate with biokinetics and elemental composition in full-scale anaerobic digesters

This study examined whether the abundance and expression of microbial 16S rRNA genes were associated with elemental concentrations and substrate conversion biokinetics in 20 full-scale anaerobic digesters, including seven municipal sewage sludge (SS) digesters and 13 industrial codigesters. SS digester contents had higher methane production rates from acetate, propionate and phenyl acetate compared to industrial codigesters. SS digesters and industrial codigesters were distinctly clustered based on their elemental concentrations, with higher concentrations of NH₃ -N, Cl, K and Na observed in codigesters. Amplicon sequencing of 16S rRNA genes and reverse-transcribed 16S rRNA revealed divergent grouping of microbial communities between mesophilic SS digesters, mesophilic codigesters and thermophilic digesters. Higher intradigester distances between Archaea 16S rRNA and rRNA gene profiles were observed in mesophilic codigesters, which also had the lowest acetate utilization biokinetics. Constrained ordination showed that microbial rRNA and rRNA gene profiles were significantly associated with maximum methane production rates from acetate, propionate, oleate and phenyl acetate, as well as concentrations of NH₃ -N, Fe, S, Mo and Ni. A co-occurrence network of rRNA gene expression confirmed the three main clusters of anaerobic digester communities based on active populations. Syntrophic and methanogenic taxa were highly represented within the subnetworks, indicating that obligate energy-sharing partnerships play critical roles in stabilizing the digester microbiome. Overall, these results provide new evidence showing that different feed substrates associate with different micronutrient compositions in anaerobic digesters, which in turn may influence microbial abundance, activity and function.

The impact of vegan production on the kimchi microbiome

Despite previous inquiry into the fermentative bacterial community of kimchi, there has been little insight into the impacts of starting ingredients on the establishment and dynamics of the microbial community. Recently some industrial producers have begun to utilize vegan production methods that omit fermented seafood ingredients. The community-level impacts of this change are unknown. In this study, we investigated the differences in the taxonomic composition of the microbial communities of non-vegan kimchi and vegan kimchi prepared through quick fermentation at room temperature. In addition to tracking the community dynamics over the fermentation process, we looked at the impact of the constituent ingredients and the production facility environment on the microbial community of fermenting kimchi. Our results indicate that the bacterial community of the prepared vegan product closely mirrors the progression and final structure of the non-vegan final product. We also found that room temperature-fermented kimchi differs minimally from more traditional cold-fermented kimchi. Finally, we found that the bacterial community of the starting ingredients show a low relative abundance of the lactic acid bacteria in fermented kimchi, whereas the production facility is dominated by these bacteria.

Taxon Disappearance from Microbiome Analysis Reinforces the Value of Mock Communities as a Standard in Every Sequencing Run

Mock communities have been used in microbiome method development to help estimate biases introduced in PCR amplification and sequencing and to optimize pipeline outputs. Nevertheless, the strong value of routine mock community analysis beyond initial method development is rarely, if ever, considered. Here we report that our routine use of mock communities as internal standards allowed us to discover highly aberrant and strong biases in the relative proportions of multiple taxa in a single Illumina HiSeqPE250 run. In this run, an important archaeal taxon virtually disappeared from all samples, and other mock community taxa showed >2-fold high or low abundance, whereas a rerun of those identical amplicons (from the same reaction tubes) on a different date yielded "normal" results. Although obvious from the strange mock community results, we could have easily missed the problem had we not used the mock communities because of natural variation of microbiomes at our site. The "normal" results were validated over four MiSeqPE300 runs and three HiSeqPE250 runs, and run-to-run variation was usually low. While validating these "normal" results, we also discovered that some mock microbial taxa had relatively modest, but consistent, differences between sequencing platforms. We strongly advise the use of mock communities in every sequencing run to distinguish potentially serious aberrations from natural variations. The mock communities should have more than just a few members and ideally at least partly represent the samples being analyzed to detect problems that show up only in some taxa and also to help validate clustering. IMPORTANCE Despite the routine use of standards and blanks in virtually all chemical or physical assays and most biological studies (a kind of "control"), microbiome analysis has traditionally lacked such standards. Here we show that unexpected problems of unknown origin can occur in such sequencing runs and yield completely incorrect results that would not necessarily be detected without the use of standards. Assuming that the microbiome sequencing analysis works properly every time risks serious errors that can be detected by the use of mock communities.

Fecal Microbiota Composition Drives Immune Activation in HIV-infected Individuals

The inflammatory properties of the enteric microbiota of Human Immunodeficiency Virus (HIV)-infected individuals are of considerable interest because of strong evidence that bacterial translocation contributes to chronic immune activation and disease progression. Altered enteric microbiota composition occurs with HIV infection but whether altered microbiota composition or increased intestinal permeability alone drives peripheral immune activation is controversial. To comprehensively assess the inflammatory properties of HIV-associated enteric microbiota and relate these to systemic immune activation, we developed methods to purify whole fecal bacterial communities (FBCs) from stool for use in in vitro immune stimulation assays with human cells. We show that the enteric microbiota of untreated HIV-infected subjects induce significantly higher levels of activated monocytes and T cells compared to seronegative subjects. FBCs from anti-retroviral therapy (ART)-treated HIV-infected individuals induced intermediate T cell activation, indicating an only partial correction of adaptive immune cell activation capacity of the microbiome with ART. In vitro activation levels correlated with activation levels and viral load in blood and were particularly high in individuals harboring specific gram-positive opportunistic pathogens. Blockade experiments implicated Tumor Necrosis Factor (TNF)-α and Toll-Like Receptor-2 (TLR2), which recognizes peptidoglycan, as strong mediators of T cell activation; This may contradict a previous focus on lipopolysaccharide as a primary mediator of chronic immune activation. These data support that increased inflammatory properties of the enteric microbiota and not increased permeability alone drives chronic inflammation in HIV.

Novel Method Reveals a Narrow Phylogenetic Distribution of Bacterial Dispersers in Environmental Communities Exposed to Low-Hydration Conditions

In this study, we developed a method that provides profiles of community-level surface dispersal from environmental samples under controlled hydration conditions and enables us to isolate and uncover the diversity of the fastest bacterial dispersers. The method expands on the porous surface model (PSM), previously used to monitor the dispersal of individual bacterial strains in liquid films at the surface of a porous ceramic disc. The novel procedure targets complex communities and captures the dispersed bacteria on a solid medium for growth and detection. The method was first validated by distinguishing motile Pseudomonas putida and Flavobacterium johnsoniae strains from their nonmotile mutants. Applying the method to soil and lake water bacterial communities showed that community-scale dispersal declined as conditions became drier. However, for both communities, dispersal was detected even under low-hydration conditions (matric potential, -3.1 kPa) previously proven too dry for P. putida strain KT2440 motility. We were then able to specifically recover and characterize the fastest dispersers from the inoculated communities. For both soil and lake samples, 16S rRNA gene amplicon sequencing revealed that the fastest dispersers were substantially less diverse than the total communities. The dispersing fraction of the soil microbial community was dominated by Pseudomonas species cells, which increased in abundance under low-hydration conditions, while the dispersing fraction of the lake community was dominated by Aeromonas species cells and, under wet conditions (-0.5 kPa), also by Exiguobacterium species cells. The results gained in this study bring us a step closer to assessing the dispersal ability within complex communities under environmentally relevant conditions.IMPORTANCE Dispersal is a key process of bacterial community assembly, and yet, very few attempts have been made to assess bacterial dispersal at the community level, as the focus has previously been on pure-culture studies. A crucial factor for dispersal in habitats where hydration conditions vary, such as soils, is the thickness of the liquid films surrounding solid surfaces, but little is known about how the ability to disperse in such films varies within bacterial communities. Therefore, we developed a method to profile community dispersal and identify fast dispersers on a rough surface resembling soil surfaces. Our results suggest that within the motile fraction of a bacterial community, only a minority of the bacterial types are able to disperse in the thinnest liquid films. During dry periods, these efficient dispersers can gain a significant fitness advantage through their ability to colonize new habitats ahead of the rest of the community.

Gut Microbial Diversity in Women With Polycystic Ovary Syndrome Correlates With Hyperandrogenism

CONTEXT

A majority of women with polycystic ovary syndrome (PCOS) have metabolic abnormalities that result in an increased risk of developing type 2 diabetes and heart disease. Correlative studies have shown an association between changes in the gut microbiome and metabolic disorders. Two recent studies reported a decrease in α diversity of the gut microbiome in women with PCOS compared with healthy women.

OBJECTIVE

We investigated whether changes in the gut microbiome correlated with specific clinical parameters in women with PCOS compared with healthy women. We also investigated whether there were changes in the gut microbiome in women with polycystic ovarian morphology (PCOM) who lacked the other diagnostic criteria of PCOS.

PARTICIPANTS

Subjects were recruited at the Poznan University of Medical Sciences. Fecal microbial diversity profiles of healthy women (n = 48), women with PCOM (n = 42), and women diagnosed with PCOS using the Rotterdam criteria (n = 73) were analyzed using 16S ribosomal RNA gene sequencing.

RESULTS

Lower α diversity was observed in women with PCOS compared with healthy women. Women with PCOM had a change in α diversity that was intermediate between that of the other two groups. Regression analyses showed that hyperandrogenism, total testosterone, and hirsutism were negatively correlated with α diversity. Permutational multivariate analysis of variance in UniFrac distances showed that hyperandrogenism was also correlated with β diversity. A random forest identified bacteria that discriminated between healthy women and women with PCOS.

CONCLUSION

These results suggest that hyperandrogenism may play a critical role in altering the gut microbiome in women with PCOS.

The colonic epithelium plays an active role in promoting colitis by shaping the tissue cytokine profile

Inflammatory bowel disease (IBD) is a chronic condition driven by loss of homeostasis between the mucosal immune system, the commensal gut microbiota, and the intestinal epithelium. Our goal is to understand how these components of the intestinal ecosystem cooperate to control homeostasis. By combining quantitative measures of epithelial hyperplasia and immune infiltration with multivariate analysis of inter- and intracellular signaling, we identified epithelial mammalian target of rapamycin (mTOR) signaling as a potential driver of inflammation in a mouse model of colitis. A kinetic analysis of mTOR inhibition revealed that the pathway regulates epithelial differentiation, which in turn controls the cytokine milieu of the colon. Consistent with our in vivo analysis, we found that cytokine expression of organoids grown ex vivo, in the absence of bacteria and immune cells, was dependent on differentiation state. Our study suggests that proper differentiation of epithelial cells is an important feature of colonic homeostasis because of its effect on the secretion of inflammatory cytokines.

Investigation of the seasonal microbiome of Anopheles coluzzii mosquitoes in Mali

The poorly understood mechanisms of dry season persistence of Anopheles spp. mosquitoes through the dry season in Africa remain a critical gap in our knowledge of Plasmodium disease transmission. While it is thought that adult mosquitoes remain in a dormant state throughout this seven-month dry season, the nature of this state remains unknown and has largely not been recapitulated in laboratory settings. To elucidate possible connections of this state with microbial composition, the whole body microbiomes of adult mosquitoes in the dry and wet seasons in two locations of Mali with varying water availability were compared by sequencing the 16S ribosomal RNA gene. These locations were a village near the Niger River with year-round water sources (N’Gabakoro, “riparian”), and a typical Sahelian area with highly seasonal breeding sites (Thierola Area, “Sahelian”). The 16S bacterial data consisted of 2057 sequence variants in 426 genera across 184 families. From these data, we found several compositional differences that were seasonally and spatially linked. Counter to our initial hypothesis, there were more pronounced seasonal differences in the bacterial microbiome of riparian, rather than Sahelian areas. These seasonal shifts were primarily in Ralstonia, Sphingorhabdus, and Duganella spp. bacteria that are usually soil and water-associated, indicating these changes may be from bacteria acquired in the larval environment, rather than adulthood. In Sahelian dry season mosquitoes, there was a unique intracellular bacteria, Anaplasma, which likely was acquired through non-human blood feeding. Cytochrome B analysis of blood meals showed greater heterogeneity in host choice of An. coluzzii independent of season in the Thierola area compared to N’Gabakoro (77.5% vs. 94.6% human-origin blood meal, respectively), indicating a relaxation of anthropophily. Overall, this exploratory study provides valuable indications of spatial and seasonal differences in bacterial composition which help refine this difficult to study state.

Allometry and Ecology of the Bilaterian Gut Microbiome

Classical ecology provides principles for construction and function of biological communities, but to what extent these apply to the animal-associated microbiota is just beginning to be assessed. Here, we investigated the influence of several well-known ecological principles on animal-associated microbiota by characterizing gut microbial specimens from bilaterally symmetrical animals (Bilateria) ranging from flies to whales. A rigorously vetted sample set containing 265 specimens from 64 species was assembled. Bacterial lineages were characterized by 16S rRNA gene sequencing. Previously published samples were also compared, allowing analysis of over 1,098 samples in total. A restricted number of bacterial phyla was found to account for the great majority of gut colonists. Gut microbial composition was associated with host phylogeny and diet. We identified numerous gut bacterial 16S rRNA gene sequences that diverged deeply from previously studied taxa, identifying opportunities to discover new bacterial types. The number of bacterial lineages per gut sample was positively associated with animal mass, paralleling known species-area relationships from island biogeography and implicating body size as a determinant of community stability and niche complexity. Samples from larger animals harbored greater numbers of anaerobic communities, specifying a mechanism for generating more-complex microbial environments. Predictions for species/abundance relationships from models of neutral colonization did not match the data set, pointing to alternative mechanisms such as selection of specific colonists by environmental niche. Taken together, the data suggest that niche complexity increases with gut size and that niche selection forces dominate gut community construction.IMPORTANCE The intestinal microbiome of animals is essential for health, contributing to digestion of foods, proper immune development, inhibition of pathogen colonization, and catabolism of xenobiotic compounds. How these communities assemble and persist is just beginning to be investigated. Here we interrogated a set of gut samples from a wide range of animals to investigate the roles of selection and random processes in microbial community construction. We show that the numbers of bacterial species increased with the weight of host organisms, paralleling findings from studies of island biogeography. Communities in larger organisms tended to be more anaerobic, suggesting one mechanism for niche diversification. Nonselective processes enable specific predictions for community structure, but our samples did not match the predictions of the neutral model. Thus, these findings highlight the importance of niche selection in community construction and suggest mechanisms of niche diversification.

Exploring Linkages between Taxonomic and Functional Profiles of the Human Microbiome

Microbiome studies typically focus on characterizing the taxonomic and functional profiles of the microbes within a community. Functional profiling is generally thought to be superior to taxonomic profiling for investigating human-microbe interactions, but there are several limitations and challenges to existing approaches.

Microbiome studies typically focus on characterizing the taxonomic and functional profiles of the microbes within a community. Functional profiling is generally thought to be superior to taxonomic profiling for investigating human-microbe interactions, but there are several limitations and challenges to existing approaches. This Perspective discusses the current sequencing and bioinformatic methods for producing taxonomic and functional profiles, recent studies utilizing and comparing these technologies, and the existing challenges and limitations of these data. In addition, functional versus taxonomic conservation across the population is questioned, while future research that focuses on investigating the taxonomic diversity of microbial functions is proposed.

A 16S rRNA gene sequencing and analysis protocol for the Illumina MiniSeq platform

High-throughput sequencing of the 16S rRNA gene on the Illumina platform is commonly used to assess microbial diversity in environmental samples. The MiniSeq, Illumina's latest benchtop sequencer, enables more cost-efficient DNA sequencing relative to larger Illumina sequencing platforms (e.g., MiSeq). Here we used a modified custom primer sequencing approach to test the fidelity of the MiniSeq for high-throughput sequencing of the V4 hypervariable region of 16S rRNA genes from complex communities in environmental samples. To this end, we designed additional sequencing primers that enabled application of a dual-index barcoding method on the MiniSeq. A mock community was sequenced alongside the environmental samples in four different sequencing runs as a quality control benchmark. We were able to recapture a realistic richness of the mock community in all sequencing runs, and identify meaningful differences in alpha and beta diversity in the environmental samples. Furthermore, rarefaction analysis indicated diversity in many environmental samples was close to saturation. These results show that the MiniSeq can produce similar quantities of high-quality V4 reads compared to the MiSeq, yet is a cost-effective option for any laboratory interested in performing high-throughput 16S rRNA gene sequencing.

Microbiota inoculum composition affects holobiont assembly and host growth in Daphnia

BACKGROUND

Host-associated microbiota is often acquired by horizontal transmission of microbes present in the environment. It is hypothesized that differences in the environmental pool of colonizers can influence microbiota community assembly on the host and as such affect holobiont composition and host fitness. To investigate this hypothesis, the host-associated microbiota of the invertebrate eco(toxico)logical model Daphnia was experimentally disturbed using different concentrations of the antibiotic oxytetracycline. The community assembly and host-microbiota interactions when Daphnia were colonized by the disturbed microbiota were investigated by inoculating germ-free individuals with the microbiota.

RESULTS

Antibiotic-induced disturbance of the microbiota had a strong effect on the subsequent colonization of Daphnia by affecting ecological interactions between members of the microbiota. This resulted in differences in community assembly which, in turn, affected Daphnia growth.

CONCLUSIONS

These results show that the composition of the pool of colonizing microbiota can be an important structuring factor of the microbiota assembly on Daphnia, affecting holobiont composition and host growth. These findings contribute to a better understanding of how the microbial environment can shape the holobiont composition and affect host-microbiota interactions.

Evaluation of milk sample fractions for characterization of milk microbiota from healthy and clinical mastitis cows

Amplicon sequencing technique has been increasingly applied to the clinical setting as a sensitive diagnostic tool. Therefore, it is of great importance to develop a DNA extraction method that accurate isolates DNA from complex host-associated microbiota. Given the multifactorial etiology of clinical mastitis and the diversified lifestyle of bacterial species harboring in milk, here four distinct milk sample fractions: raw whole milk, milk fat, casein-pellet, and casein-pellet + fat from healthy cows and cows with clinical mastitis, were subjected to bead-beating DNA extraction, followed by high-throughput sequencing. We aimed to identify the best approach for characterization of the milk microbiota and detection of mastitis pathogens (Klebsiella spp., Streptococcus spp. and Escherichia coli). DNA from each milk fraction tested was extracted by two commercial kits, which include physical, mechanical and chemical lysis; in total 280 DNA samples from 35 cows were analyzed. Milk-health-status were categorized into four groups (healthy group; E. coli-mastitis group; Klebsiella spp.-mastitis group; and Streptococcus spp.–mastitis group). Bacterial phyla and families were described for each milk-health-status group across milk sample fractions and DNA extraction kits. For the mastitis groups the relative abundance of f__Enterobacteriaceae and f__Streptococcaceae were compared to determine the efficacy of procedures in detecting the mastitis pathogens. The four milk fractions used allowed efficiently and uniformly detection of the causative agent of mastitis. Only 27% of the families detected in healthy milk were shared among the samples extracted from all fractions of milk samples; followed by 3, 4, and 12% for the samples from E. coli-mastitis, Klebsiella spp.-mastitis and Streptococcus spp-mastitis, respectively. However, the shared families comprised a mean relative abundance greater than 85%, regardless of milk-health-status, milk fraction and DNA isolation method. Taxonomic data at the family level showed that sequences from mastitis milk samples cultured positive for E. coli and Klebsiella spp. were predominantly affiliated with f__Enterobacteriaceae, while for Streptococcus spp. were dominated by f__Streptococcacea, followed by f__Pseudomonadaceae and f__Enterococcaceae. Microbial community analysis revealed that most of the microbial community composition corresponded to milk bacterial species irrespective of the DNA isolation method and milk fraction evaluated.

Guided Protocol for Fecal Microbial Characterization by 16S rRNA-Amplicon Sequencing

The human intestinal microbiome plays a central role in protecting cells from injury, in processing energy and nutrients, and in promoting immunity. Deviations from what is considered a healthy microbiota composition (dysbiosis) may impair vital functions leading to pathologic conditions. Recent and ongoing research efforts have been directed toward the characterization of associations between microbial composition and human health and disease. Advances in high-throughput sequencing technologies enable characterization of the gut microbial composition. These methods include 16S rRNA-amplicon sequencing and shotgun sequencing. 16S rRNA-amplicon sequencing is used to profile taxonomical composition, while shotgun sequencing provides additional information about gene predictions and functional annotation. An advantage in using a targeted sequencing method of the 16S rRNA gene variable region is its substantially lower cost compared to shotgun sequencing. Sequence differences in the 16S rRNA gene are used as a microbial fingerprint to identify and quantify different taxa within an individual sample. Major international efforts have enlisted standards for 16S rRNA-amplicon sequencing. However, several studies report a common source of variation caused by batch effect. To minimize this effect, uniformed protocols for sample collection, processing, and sequencing must be implemented. This protocol proposes the integration of broadly used protocols starting from fecal sample collection to data analyses. This protocol includes a column-free, direct-PCR approach that enables simultaneous handling and DNA extraction of large numbers of fecal samples, along with PCR amplification of the V4 region. In addition, the protocol describes the analysis pipeline and provides a script using the latest version of QIIME (QIIME 2 version 2017.7.0 and DADA2). This step-by-step protocol is aimed to guide those interested in initiating the use of 16S rRNA-amplicon sequencing in a robust, reproductive, easy to use, detailed way.

The Madness of Microbiome: Attempting To Find Consensus "Best Practice" for 16S Microbiome Studies

The development and continuous improvement of high-throughput sequencing platforms have stimulated interest in the study of complex microbial communities. Currently, the most popular sequencing approach to study microbial community composition and dynamics is targeted 16S rRNA gene metabarcoding. To prepare samples for sequencing, there are a variety of processing steps, each with the potential to introduce bias at the data analysis stage. In this short review, key information from the literature pertaining to each processing step is described, and consequently, general recommendations for future 16S rRNA gene metabarcoding experiments are made.

Diversity of Entamoeba spp. in African great apes and humans: an insight from Illumina MiSeq high-throughput sequencing

Understanding the complex Entamoeba communities in the mammalian intestine has been, to date, complicated by the lack of a suitable approach for molecular detection of multiple variants co-occurring in mixed infections. Here, we report on the application of a high throughput sequencing approach based on partial 18S rDNA using the Illumina MiSeq platform. We describe, to our knowledge, for the first time, the Entamoeba communities in humans, free-ranging western lowland gorillas and central chimpanzees living in the Dja Faunal Reserve in Cameroon. We detected 36 Entamoeba haplotypes belonging to six haplotype clusters, containing haplotypes possessing high and low host specificity. Most of the detected haplotypes belonged to commensal Entamoeba, however, the pathogenic species (Entamoeba histolytica and Entamoeba nuttalli) were also detected. We observed that some Entamoeba haplotypes are shared between humans and other hosts, indicating their zoonotic potential. The findings are important not only for understanding the epidemiology of amoebiasis in humans in rural African localities, but also in the context of wild great ape conservation.

Phylogenetic Diversity and Single-Cell Genome Analysis of "Melainabacteria", a Non-Photosynthetic Cyanobacterial Group, in the Termite Gut

Termite guts harbor diverse yet-uncultured bacteria, including a non-photosynthetic cyanobacterial group, the class "Melainabacteria". We herein reported the phylogenetic diversity of "Melainabacteria" in the guts of diverse termites and conducted a single-cell genome analysis of a melainabacterium obtained from the gut of the termite Termes propinquus. We performed amplicon sequencing of 16S rRNA genes from the guts of 60 termite and eight cockroach species, and detected melainabacterial sequences in 48 out of the 68 insect species, albeit with low abundances (0.02-1.90%). Most of the melainabacterial sequences obtained were assigned to the order "Gastranaerophilales" and appeared to form clusters unique to termites and cockroaches. A single-cell genome of a melainabacterium, designated phylotype Tpq-Mel-01, was obtained using a fluorescence-activated cell sorter and whole genome amplification. The genome shared basic features with other melainabacterial genomes previously reconstructed from the metagenomes of human and koala feces. The bacterium had a small genome (~1.6 Mb) and possessed fermentative pathways possibly using sugars and chitobiose as carbon and energy sources, while the pathways for photosynthesis and carbon fixation were not found. The genome contained genes for flagellar components and chemotaxis; therefore, the bacterium is likely motile. A fluorescence in situ hybridization analysis showed that the cells of Tpq-Mel-01 and/or its close relatives are short rods with the dimensions of 1.1±0.2 μm by 0.5±0.1 μm; for these bacteria, we propose the novel species, "Candidatus Gastranaerophilus termiticola". Our results provide fundamental information on "Melainabacteria" in the termite gut and expand our knowledge on this underrepresented, non-photosynthetic cyanobacterial group.

Tristetraprolin Is Required for Alveolar Bone Homeostasis

Tristetraprolin (TTP) is an RNA-binding protein that targets numerous immunomodulatory mRNA transcripts for degradation. Many TTP targets are key players in the pathogenesis of periodontal bone loss, including tumor necrosis factor-α. To better understand the extent that host immune factors play during periodontal bone loss, we assessed alveolar bone levels, inflammation and osteoclast activity in periodontal tissues, and immune response in draining cervical lymph nodes in TTP-deficient and wild-type (WT) mice in an aging study. WT and TTP-deficient (knockout [KO]) mice were used for all studies under specific pathogen-free conditions. Data were collected on mice aged 3, 6, and 9 mo. Microcomputed tomography (µCT) was performed on maxillae where 3-dimensional images were generated and bone loss was assessed. Decalcified sections of specimens were scored for inflammation and stained with tartrate-resistant acid phosphate (TRAP) to visualize osteoclasts. Immunophenotyping was performed on single-cell suspensions isolated from primary and peripheral lymphoid tissues using flow cytometry. Results presented indicate that TTP KO mice had significantly more alveolar bone loss over time compared with WT controls. Bone loss was associated with significant increases in inflammatory cell infiltration and an increased percentage of alveolar bone surfaces apposed with TRAP+ cells. Furthermore, it was found that the draining cervical lymph nodes were significantly enlarged in TTP-deficient animals and contained a distinct pathological immune profile compared with WT controls. Finally, the oral microbiome in the TTP KO mice was significantly different with age from WT cohoused mice. The severe bone loss, inflammation, and increased osteoclast activity observed in these mice support the concept that TTP plays a critical role in the maintenance of alveolar bone homeostasis in the presence of oral commensal flora. This study suggests that TTP is required to inhibit excessive inflammatory host responses that contribute to periodontal bone loss, even in the absence of specific periodontal pathogens.

Linking Associations of Rare Low-Abundance Species to Their Environments by Association Networks

Studies of microbial communities by targeted sequencing of rRNA genes lead to recovering numerous rare low-abundance taxa with unknown biological roles. We propose to study associations of such rare organisms with their environments by a computational framework based on transformation of the data into qualitative variables. Namely, we analyze the sparse table of putative species or OTUs (operational taxonomic units) and samples generated in such studies, also known as an OTU table, by collecting statistics on co-occurrences of the species and on shared species richness across samples. Based on the statistics we built two association networks, of the rare putative species and of the samples respectively, using a known computational technique, Association networks (Anets) developed for analysis of qualitative data. Clusters of samples and clusters of OTUs are then integrated and combined with metadata of the study to produce a map of associated putative species in their environments. We tested and validated the framework on two types of microbiomes, of human body sites and that of the Populus tree root systems. We show that in both studies the associations of OTUs can separate samples according to environmental or physiological characteristics of the studied systems.

Scaling up: A guide to high-throughput genomic approaches for biodiversity analysis

The purpose of this review is to present the most common and emerging DNA-based methods used to generate data for biodiversity and biomonitoring studies. As environmental assessment and monitoring programmes may require biodiversity information at multiple levels, we pay particular attention to the DNA metabarcoding method and discuss a number of bioinformatic tools and considerations for producing DNA-based indicators using operational taxonomic units (OTUs), taxa at a variety of ranks and community composition. By developing the capacity to harness the advantages provided by the newest technologies, investigators can "scale up" by increasing the number of samples and replicates processed, the frequency of sampling over time and space, and even the depth of sampling such as by sequencing more reads per sample or more markers per sample. The ability to scale up is made possible by the reduced hands-on time and cost per sample provided by the newest kits, platforms and software tools. Results gleaned from broad-scale monitoring will provide opportunities to address key scientific questions linked to biodiversity and its dynamics across time and space as well as being more relevant for policymakers, enabling science-based decision-making, and provide a greater socio-economic impact. As genomic approaches are continually evolving, we provide this guide to methods used in biodiversity genomics.

A novel mouse model of Campylobacter jejuni enteropathy and diarrhea

Campylobacter infections are among the leading bacterial causes of diarrhea and of 'environmental enteropathy' (EE) and growth failure worldwide. However, the lack of an inexpensive small animal model of enteric disease with Campylobacter has been a major limitation for understanding its pathogenesis, interventions or vaccine development. We describe a robust standard mouse model that can exhibit reproducible bloody diarrhea or growth failure, depending on the zinc or protein deficient diet and on antibiotic alteration of normal microbiota prior to infection. Zinc deficiency and the use of antibiotics create a niche for Campylobacter infection to establish by narrowing the metabolic flexibility of these mice for pathogen clearance and by promoting intestinal and systemic inflammation. Several biomarkers and intestinal pathology in this model also mimic those seen in human disease. This model provides a novel tool to test specific hypotheses regarding disease pathogenesis as well as vaccine development that is currently in progress.

Correlation between gut microbiota and personality in adults: A cross-sectional study

Personality affects fundamental behavior patterns and has been related with health outcomes and mental disorders. Recent evidence has emerged supporting a relationship between the microbiota and behavior, referred to as brain-gut relationships. Here, we first report correlations between personality traits and gut microbiota. This research was performed using the Revised NEO Personality Inventory and the sequencing data of the 16S rRNA gene in 672 adults. The diversity and the composition of the human gut microbiota exhibited significant difference when stratified by personality traits. We found that personality traits were significantly correlated with diversity of gut microbiota, while their differences were extremely subtle. High neuroticism and low conscientiousness groups were correlated with high abundance of Gammaproteobacteria and Proteobacteria, respectively when covariates, including age, sex, BMI and nutrient intake, were controlled. Additionally, high conscientiousness group also showed increased abundance of some universal butyrate-producing bacteria including Lachnospiraceae. This study was of observational and cross-sectional design and our findings must be further validated through metagenomic or metatranscriptomic methodologies, or metabolomics-based analyses. Our findings will contribute to elucidating potential links between the gut microbiota and personality, and provide useful insights toward developing and testing personality- and microbiota-based interventions for promoting health.

Influence of Pig Farming on the Human Nasal Microbiota: Key Role of Airborne Microbial Communities

It has been hypothesized that the environment can influence the composition of the nasal microbiota. However, the direct influence of pig farming on the anterior and posterior nasal microbiota is unknown. Using a cross-sectional design, pig farms (n = 28) were visited in 2014 to 2015, and nasal swabs from 43 pig farmers and 56 pigs, as well as 27 air samples taken in the vicinity of the pig enclosures, were collected. As controls, nasal swabs from 17 cow farmers and 26 non-animal-exposed individuals were also included. Analyses of the microbiota were performed based on 16S rRNA amplicon sequencing and the DADA2 pipeline to define sequence variants (SVs). We found that pig farming is strongly associated with specific microbial signatures (including alpha- and beta-diversity), which are reflected in the microbiota of the human nose. Furthermore, the microbial communities were more similar within the same farm compared to between the different farms, indicating a specific microbiota pattern for each pig farm. In total, there were 82 SVs that occurred significantly more abundantly in samples from pig farms than from cow farmers and nonexposed individuals (i.e., the core pig farm microbiota). Of these, nine SVs were significantly associated with the posterior part of the human nose. The results strongly indicate that pig farming is associated with a distinct human nose microbiota. Finally, the community structures derived by the DADA2 pipeline showed an excellent agreement with the outputs of the mothur pipeline which was revealed by procrustes analyses.

IMPORTANCE The knowledge about the influence of animal keeping on the human microbiome is important. Previous research has shown that pets significantly affect the microbial communities of humans. However, the effect of animal farming on the human microbiota is less clear, although it is known that the air at farms and, in particular, at pig farms is charged with large amounts of dust, bacteria, and fungi. In this study, we simultaneously investigated the nasal microbiota of pigs, humans, and the environment at pig farms. We reveal an enormous impact of pig farming on the human nasal microbiota which is far more pronounced compared to cow farming. In addition, we analyzed the airborne microbiota and found significant associations suggesting an animal-human transmission of the microbiota within pig farms. We also reveal that microbial patterns are farm specific, suggesting that the environment influences animals and humans in a similar manner.

SeekDeep: single-base resolution de novo clustering for amplicon deep sequencing

PCR amplicon deep sequencing continues to transform the investigation of genetic diversity in viral, bacterial, and eukaryotic populations. In eukaryotic populations such as Plasmodium falciparum infections, it is important to discriminate sequences differing by a single nucleotide polymorphism. In bacterial populations, single-base resolution can provide improved resolution towards species and strains. Here, we introduce the SeekDeep suite built around the qluster algorithm, which is capable of accurately building de novo clusters representing true, biological local haplotypes differing by just a single base. It outperforms current software, particularly at low frequencies and at low input read depths, whether resolving single-base differences or traditional OTUs. SeekDeep is open source and works with all major sequencing technologies, making it broadly useful in a wide variety of applications of amplicon deep sequencing to extract accurate and maximal biologic information.

Highlighting Clinical Metagenomics for Enhanced Diagnostic Decision-making: A Step Towards Wider Implementation

Clinical metagenomics (CMg) is the discipline that refers to the sequencing of all nucleic acid material present within a clinical specimen with the intent to recover clinically relevant microbial information. From a diagnostic perspective, next-generation sequencing (NGS) offers the ability to rapidly identify putative pathogens and predict their antimicrobial resistance profiles to optimize targeted treatment regimens. Since the introduction of metagenomics nearly a decade ago, numerous reports have described successful applications in an increasing variety of biological specimens, such as respiratory secretions, cerebrospinal fluid, stool, blood and tissue. Considerable advancements in sequencing and computational technologies in recent years have made CMg a promising tool in clinical microbiology laboratories. Moreover, costs per sample and turnaround time from specimen receipt to clinical management continue to decrease, making the prospect of CMg more feasible. Many difficulties, however, are associated with CMg and warrant further improvements such as the informatics infrastructure and analytical pipelines. Thus, the current review focuses on comprehensively assessing applications of CMg for diagnostic and subtyping purposes.

Temporal Variability of Oral Microbiota over 10 Months and the Implications for Future Epidemiologic Studies

Background: Few studies have prospectively evaluated the association between oral microbiota and health outcomes. Precise estimates of the intrasubject microbial metric stability will allow better study planning. Therefore, we conducted a study to evaluate the temporal variability of oral microbiota.Methods: Forty individuals provided six oral samples using the OMNIgene ORAL kit and Scope mouthwash oral rinses approximately every two months over 10 months. DNA was extracted using the QIAsymphony and the V4 region of the 16S rRNA gene was amplified and sequenced using the MiSeq. To estimate temporal variation, we calculated intraclass correlation coefficients (ICCs) for a variety of metrics and examined stability after clustering samples into distinct community types using Dirichlet multinomial models (DMMs).Results: The ICCs for the alpha diversity measures were high, including for number of observed bacterial species [0.74; 95% confidence interval (CI): 0.65-0.82 and 0.79; 95% CI: 0.75-0.94] from OMNIgene ORAL and Scope mouthwash, respectively. The ICCs for the relative abundance of the top four phyla and beta diversity matrices were lower. Three clusters provided the best model fit for the DMM from the OMNIgene ORAL samples, and the probability of remaining in a specific cluster was high (59.5%-80.7%).Conclusions: The oral microbiota appears to be stable over time for multiple metrics, but some measures, particularly relative abundance, were less stable.Impact: We used this information to calculate stability-adjusted power calculations that will inform future field study protocols and experimental analytic designs. Cancer Epidemiol Biomarkers Prev; 27(5); 594-600. ©2018 AACR.

Systems biology of the human microbiome

Recent research has shown that the microbiome-a collection of microorganisms, including bacteria, fungi, and viruses, living on and in a host-are of extraordinary importance in human health, even from conception and development in the uterus. Therefore, to further our ability to diagnose disease, to predict treatment outcomes, and to identify novel therapeutics, it is essential to include microbiome and microbial metabolic biomarkers in Systems Biology investigations. In clinical studies or, more precisely, Systems Medicine approaches, we can use the diversity and individual characteristics of the personal microbiome to enhance our resolution for patient stratification. In this review, we explore several Systems Medicine approaches, including Microbiome Wide Association Studies to understand the role of the human microbiome in health and disease, with a focus on 'preventive medicine' or P4 (i.e., personalized, predictive, preventive, participatory) medicine.

A spatial gradient of bacterial diversity in the human oral cavity shaped by salivary flow

Spatial and temporal patterns in microbial communities provide insights into the forces that shape them, their functions and roles in health and disease. Here, we used spatial and ecological statistics to analyze the role that saliva plays in structuring bacterial communities of the human mouth using >9000 dental and mucosal samples. We show that regardless of tissue type (teeth, alveolar mucosa, keratinized gingiva, or buccal mucosa), surface-associated bacterial communities vary along an ecological gradient from the front to the back of the mouth, and that on exposed tooth surfaces, the gradient is pronounced on lingual compared to buccal surfaces. Furthermore, our data suggest that this gradient is attenuated in individuals with low salivary flow due to Sjögren's syndrome. Taken together, our findings imply that salivary flow influences the spatial organization of microbial communities and that biogeographical patterns may be useful for understanding host physiological processes and for predicting disease.

Assembly and ecological function of the root microbiome across angiosperm plant species

Across plants and animals, host-associated microbial communities play fundamental roles in host nutrition, development, and immunity. The factors that shape host-microbiome interactions are poorly understood, yet essential for understanding the evolution and ecology of these symbioses. Plant roots assemble two distinct microbial compartments from surrounding soil: the rhizosphere (microbes surrounding roots) and the endosphere (microbes within roots). Root-associated microbes were key for the evolution of land plants and underlie fundamental ecosystem processes. However, it is largely unknown how plant evolution has shaped root microbial communities, and in turn, how these microbes affect plant ecology, such as the ability to mitigate biotic and abiotic stressors. Here we show that variation among 30 angiosperm species, which have diverged for up to 140 million years, affects root bacterial diversity and composition. Greater similarity in root microbiomes between hosts leads to negative effects on plant performance through soil feedback, with specific microbial taxa in the endosphere and rhizosphere potentially affecting competitive interactions among plant species. Drought also shifts the composition of root microbiomes, most notably by increasing the relative abundance of the Actinobacteria. However, this drought response varies across host plant species, and host-specific changes in the relative abundance of endosphere Streptomyces are associated with host drought tolerance. Our results emphasize the causes of variation in root microbiomes and their ecological importance for plant performance in response to biotic and abiotic stressors.

Wastewater treatment plant effluent introduces recoverable shifts in microbial community composition in receiving streams

Through a combined approach using analytical chemistry, real-time quantitative polymerase chain reaction (qPCR), and targeted amplicon sequencing, we studied the impact of wastewater treatment plant effluent sources at six sites on two sampling dates on the chemical and microbial population regimes within the Wissahickon Creek, and its tributary, Sandy Run, in Montgomery County, Pennsylvania, USA. These water bodies contribute flow to the Schuylkill River, one of the major drinking water sources for Philadelphia, Pennsylvania. Effluent was observed to be a significant source of nutrients, human and non-specific fecal associated taxa. There was an observed increase in the alpha diversity at locations immediately below effluent outflows, which contributed many taxa involved in wastewater treatment processes and nutrient cycling to the stream's microbial community. Unexpectedly, modeling of microbial community shifts along the stream was not controlled by concentrations of measured nutrients. Furthermore, partial recovery, in the form of decreasing abundances of bacteria and nutrients associated with wastewater treatment plant processes, nutrient cycling bacteria, and taxa associated with fecal and sewage sources, was observed between effluent sources, which we hypothesize is controlled by distance from effluent source. Antecedent moisture conditions were observed to impact overall microbial community diversity, with higher diversity occurring after rainfall. Finally, the efficacy of using a subset of the microbial community including the orders of Bifidobacteriales, Bacteroidales, and Clostridiales to estimate the degree of influence due to sewage and fecal sources was explored and verified.

Differential Susceptibility to T Cell-Induced Colitis in Mice: Role of the Intestinal Microbiota

One of the best characterized mouse models of the inflammatory bowel diseases (IBD; Crohn's disease, ulcerative colitis) is the CD4+CD45RBhigh T cell transfer model of chronic colitis. Following our relocation to Texas Tech University Health Sciences Center (TTUHSC), we observed a dramatic reduction in the incidence of moderate-to-severe colitis from a 16-year historical average of 90% at Louisiana State University Health Sciences Center (LSUHSC) to <30% at TTUHSC. We hypothesized that differences in the commensal microbiota at the 2 institutions may account for the differences in susceptibility to T cell-induced colitis. Using bioinformatic analyses of 16S rRNA amplicon sequence data, we quantified and compared the major microbial populations in feces from healthy and colitic mice housed at the 2 institutions. We found that the bacterial composition differed greatly between mice housed at LSUHSC vs TTUHSC. We identified several genera strongly associated with, and signficantly overrepresented in high responding RAG-/- mice housed at LSUHSC. In addition, we found that colonization of healthy TTUHSC RAG-/- mice with feces obtained from healthy or colitic RAG-/- mice housed at LSUHSC transferred susceptibility to T cell-induced colitis such that the recipients developed chronic colitis with incidence and severity similar to mice generated at LSUHSC. Finally, we found that the treatment of mice with preexisting colitis with antibiotics remarkably attenuated disease. Taken together, our data demonstrate that specific microbial communities determine disease susceptibility and that manipulation of the intestinal microbiota alters the induction and/or perpetuation of chronic colitis.

Age and fecal microbial strain-specific differences in patients with spondyloarthritis

Background

Prior studies have demonstrated abnormalities in the composition of the gastrointestinal microbiota in pediatric and adult patients with spondyloarthritis (SpA). In particular, diminished fecal abundance of Faecalibacterium prausnitzii and abnormalities in both directions in the abundance of the Bacteroides genus have been identified.

Methods

We obtained fecal specimens from 30 children with treatment-naïve enthesitis-related arthritis (ERA) and 19 healthy controls, as well as specimens from 11 adult patients with longstanding SpA and 10 adult healthy controls. All of the samples underwent sequencing of the 16S ribosomal DNA. A subset of the pediatric fecal samples was subjected to shotgun metagenomics sequencing.

Results

ERA patients had decreased abundance of the anti-inflammatory F. prausnitzii A2-165 strain (41 ± 28% versus 54 ± 20% of all sequences matching F. prausnitzii, p = 0.084) and an increased abundance of the control F. prausnitzii L2/6 strain (28 ± 28% versus 15 ± 15%, p = 0.038). Similar trends were observed in adults with longstanding SpA (n = 11) and controls (n = 10). In contrast, the fecal abundance of Bacteroides fragilis was increased in ERA subjects (2.0 ± 4.0% versus 0.45 ± 0.7% of all sequences, p = 0.045), yet was diminished in adult subjects (0.2 ± % versus 1.0 ± % of all sequences, p = 0.106). Shotgun metagenomics sequencing of the fecal DNA in the pediatric subjects revealed diminished coverage of the butanoate pathway (abundance normalized to controls of 1 ± 0.48 versus 0.72 ± 0.33 in ERA, p = 0.037).

Conclusions

The anti-inflammatory F. prausnitzii A2-165 strain appears to be depleted in both pediatric and adult SpA. In contrast, B. fragilis may be depleted in adult disease yet abundant in pediatric SpA, suggesting developmental effects on the immune system.

Electronic supplementary material

The online version of this article (10.1186/s13075-018-1510-6) contains supplementary material, which is available to authorized users.

Human Microbiome Acquisition and Bioinformatic Challenges in Metagenomic Studies

The study of the human microbiome has become a very popular topic. Our microbial counterpart, in fact, appears to play an important role in human physiology and health maintenance. Accordingly, microbiome alterations have been reported in an increasing number of human diseases. Despite the huge amount of data produced to date, less is known on how a microbial dysbiosis effectively contributes to a specific pathology. To fill in this gap, other approaches for microbiome study, more comprehensive than 16S rRNA gene sequencing, i.e., shotgun metagenomics and metatranscriptomics, are becoming more widely used. Methods standardization and the development of specific pipelines for data analysis are required to contribute to and increase our understanding of the human microbiome relationship with health and disease status.

Combining 16S rRNA gene variable regions enables high-resolution microbial community profiling

BACKGROUND

Most of our knowledge about the remarkable microbial diversity on Earth comes from sequencing the 16S rRNA gene. The use of next-generation sequencing methods has increased sample number and sequencing depth, but the read length of the most widely used sequencing platforms today is quite short, requiring the researcher to choose a subset of the gene to sequence (typically 16-33% of the total length). Thus, many bacteria may share the same amplified region, and the resolution of profiling is inherently limited. Platforms that offer ultra-long read lengths, whole genome shotgun sequencing approaches, and computational frameworks formerly suggested by us and by others all allow different ways to circumvent this problem yet suffer various shortcomings. There is a need for a simple and low-cost 16S rRNA gene-based profiling approach that harnesses the short read length to provide a much larger coverage of the gene to allow for high resolution, even in harsh conditions of low bacterial biomass and fragmented DNA.

RESULTS

This manuscript suggests Short MUltiple Regions Framework (SMURF), a method to combine sequencing results from different PCR-amplified regions to provide one coherent profiling. The de facto amplicon length is the total length of all amplified regions, thus providing much higher resolution compared to current techniques. Computationally, the method solves a convex optimization problem that allows extremely fast reconstruction and requires only moderate memory. We demonstrate the increase in resolution by in silico simulations and by profiling two mock mixtures and real-world biological samples. Reanalyzing a mock mixture from the Human Microbiome Project achieved about twofold improvement in resolution when combing two independent regions. Using a custom set of six primer pairs spanning about 1200 bp (80%) of the 16S rRNA gene, we were able to achieve ~ 100-fold improvement in resolution compared to a single region, over a mock mixture of common human gut bacterial isolates. Finally, the profiling of a Drosophila melanogaster microbiome using the set of six primer pairs provided a ~ 100-fold increase in resolution and thus enabling efficient downstream analysis.

CONCLUSIONS

SMURF enables the identification of near full-length 16S rRNA gene sequences in microbial communities, having resolution superior compared to current techniques. It may be applied to standard sample preparation protocols with very little modifications. SMURF also paves the way to high-resolution profiling of low-biomass and fragmented DNA, e.g., in the case of formalin-fixed and paraffin-embedded samples, fossil-derived DNA, or DNA exposed to other degrading conditions. The approach is not restricted to combining amplicons of the 16S rRNA gene and may be applied to any set of amplicons, e.g., in multilocus sequence typing (MLST).

Postmenopausal breast cancer and oestrogen associations with the IgA-coated and IgA-noncoated faecal microbiota

Background:

The diversity and composition of the gut microbiota may affect breast cancer risk by modulating systemic levels of oestrogens and inflammation. The current investigation tested this hypothesis in postmenopausal women by identifying breast cancer associations with an inflammation marker, oestrogen levels, and faecal microbes that were or were not coated with mucosal immunoglobulin A (IgA).

Methods:

In this population-based study, we compared 48 postmenopausal breast cancer cases (75% stage 0–1, 88% oestrogen-receptor positive) to 48 contemporaneous, postmenopausal, normal-mammogram, age-matched controls. Microbiota metrics employed 16S rRNA gene amplicon sequencing from IgA-coated and -noncoated faecal microbes. High-performance liquid chromatography/mass spectrometry (HPLC/MS) and radioimmunoassay were used to quantify urine prostaglandin E metabolite (PGE-M), a possible marker of inflammation; urine oestrogens and oestrogen metabolites were quantified by HPLC/MS-MS.

Results:

Women with pre-treatment breast cancer had non-significantly elevated oestrogen levels; controls’ (but not cases’) oestrogens were directly correlated with their IgA-negative microbiota alpha diversity (P=0.012). Prostaglandin E metabolite levels were not associated with case status, oestrogen levels, or alpha diversity. Adjusted for oestrogens and other variables, cases had significantly reduced alpha diversity and altered composition of both their IgA-positive and IgA-negative faecal microbiota. Cases’ faecal microbial IgA-positive imputed Immune System Diseases metabolic pathway genes were increased; also, cases’ IgA-positive and IgA-negative imputed Genetic Information Processing pathway genes were decreased (P⩽0.01).

Conclusions:

Compared to controls, breast cancer cases had significant oestrogen-independent associations with the IgA-positive and IgA-negative gut microbiota. These suggest that the gut microbiota may influence breast cancer risk by altered metabolism, oestrogen recycling, and immune pressure.

Maturation of the gut microbiome and risk of asthma in childhood

The composition of the human gut microbiome matures within the first years of life. It has been hypothesized that microbial compositions in this period can cause immune dysregulations and potentially cause asthma. Here we show, by associating gut microbial composition from 16S rRNA gene amplicon sequencing during the first year of life with subsequent risk of asthma in 690 participants, that 1-year-old children with an immature microbial composition have an increased risk of asthma at age 5 years. This association is only apparent among children born to asthmatic mothers, suggesting that lacking microbial stimulation during the first year of life can trigger their inherited asthma risk. Conversely, adequate maturation of the gut microbiome in this period may protect these pre-disposed children.

Colonization of commensal bacteria is thought to impact immune development, especially in the earliest years of life. Here, the authors show, by analyzing the development of the gut microbiome of 690 children, that microbial composition at the age of 1 year is associated with asthma diagnosed in the first 5 years of life.

Comammox Nitrospira are abundant ammonia oxidizers in diverse groundwater-fed rapid sand filter communities

The recent discovery of completely nitrifying Nitrospira demands a re-examination of nitrifying environments to evaluate their contribution to nitrogen cycling. To approach this challenge, tools are needed to detect and quantify comammox Nitrospira. We present primers for the simultaneous quantification and diversity assessement of both comammox Nitrospira clades. The primers cover a wide range of comammox diversity, spanning all available high quality sequences. We applied these primers to 12 groundwater-fed rapid sand filters, and found comammox Nitrospira to be abundant in all filters. Clade B comammox comprise the majority (∼75%) of comammox abundance in all filters. Nitrosomonadaceae were present in all filters, although at low abundance (mean = 1.8%). Ordination suggests that temperature impacts the structure of nitrifying communities, and in particular that increasing temperature favours Nitrospira. The nitrogen content of the filter material, sulfate concentration and surface ammonium loading rates shape the structure of the comammox guild in the filters. This work provides an assay for simultaneous detection and diversity assessment of clades A and B comammox Nitrospira, expands our current knowledge of comammox Nitrospira diversity and demonstrates a key role for comammox Nitrospira in nitrification in groundwater-fed biofilters.

Time Course-Dependent Methanogenic Crude Oil Biodegradation: Dynamics of Fumarate Addition Metabolites, Biodegradative Genes, and Microbial Community Composition

Biodegradation of crude oil in subsurface petroleum reservoirs has adversely impacted most of the world's oil, converting this resource to heavier forms that are of lower quality and more challenging to recover. Oil degradation in deep reservoir environments has been attributed to methanogenesis over geological time, yet our understanding of the processes and organisms mediating oil transformation in the absence of electron acceptors remains incomplete. Here, we sought to identify hydrocarbon activation mechanisms and reservoir-associated microorganisms that may have helped shape the formation of biodegraded oil by incubating oilfield produced water in the presence of light (°API = 32) or heavy crude oil (°API = 16). Over the course of 17 months, we conducted routine analytical (GC, GC-MS) and molecular (PCR/qPCR of assA and bssA genes, 16S rRNA gene sequencing) surveys to assess microbial community composition and activity changes over time. Over the incubation period, we detected the formation of transient hydrocarbon metabolites indicative of alkane and alkylbenzene addition to fumarate, corresponding with increases in methane production and fumarate addition gene abundance. Chemical and gene-based evidence of hydrocarbon biodegradation under methanogenic conditions was supported by the enrichment of hydrocarbon fermenters known to catalyze fumarate addition reactions (e.g., Desulfotomaculum, Smithella), along with syntrophic bacteria (Syntrophus), methanogenic archaea, and several candidate phyla (e.g., “Atribacteria”, “Cloacimonetes”). Our results reveal that fumarate addition is a possible mechanism for catalyzing the methanogenic biodegradation of susceptible saturates and aromatic hydrocarbons in crude oil, and we propose the roles of community members and candidate phyla in our cultures that may be involved in hydrocarbon transformation to methane in crude oil systems.

Diversity-Function Relationships in Natural, Applied, and Engineered Microbial Ecosystems

The connection between ecosystem function and taxonomic diversity has been of interest and relevance to macroecologists for decades. After many years of lagging behind due to the difficulty of assigning both taxonomy and function to poorly distinguishable microscopic cells, microbial ecology now has access to a suite of powerful molecular tools which allow its practitioners to generate data relating to diversity and function of a microbial community on an unprecedented scale. Instead, the problem facing today's microbial ecologists is coupling the ease of generation of these datasets with the formulation and testing of workable hypotheses relating the diversity and function of environmental, host-associated, and engineered microbial communities. Here, we review the current state of knowledge regarding the links between taxonomic alpha- and beta-diversity and ecosystem function, comparing our knowledge in this area to that obtained by macroecologists who use more traditional techniques. We consider the methodologies that can be applied to study these properties and how successful they are at linking function to diversity, using examples from the study of model microbial ecosystems, methanogenic bioreactors (anaerobic digesters), and host-associated microbiota. Finally, we assess ways in which our newly acquired understanding might be used to manipulate diversity in ecosystems of interest in order to improve function for the benefit of us or the environment in general through the provision of ecosystem services.

Predicting the Functional Potential of the Microbiome from Marker Genes Using PICRUSt

Marker-gene sequencing is a cost-effective method of taxonomically profiling microbial communities. Unlike metagenomic approaches, marker-gene sequencing does not provide direct information about the functional genes that are present in the genomes of community members. However, by capitalizing on the rapid growth in the number of sequenced genomes, it is possible to infer which functions are likely associated with a marker gene based on its sequence similarity with a reference genome. The PICRUSt tool is based on this idea and can predict functional category abundances based on an input marker gene. In brief, this method requires a reference phylogeny with tips corresponding to taxa with reference genomes as well as taxa lacking sequenced genomes. A modified ancestral state reconstruction (ASR) method is then used to infer counts of functional categories for taxa without reference genomes. The predictions are written to pre-calculated files, which can be cross-referenced with other datasets to quickly generate predictions of functional potential for a community. This chapter will give an in-depth description of these methods and describe how PICRUSt should be used.

Environmental temperature alters the digestive performance and gut microbiota of a terrestrial amphibian

Environmental temperature and gut microbial communities can both have profound impacts on the digestive performance of ectothermic vertebrates. Additionally, the diversity, composition, and function of gut microbial communities themselves are influenced by temperature. It is typically assumed that the temperature-dependent nature of ectotherm digestive performance is due to factors such as host physiological changes and adaptation to local climatic conditions. However, it is also possible that temperature-induced alterations to gut microbiota may influence the relationship between temperature and digestion. To explore the connections between these three factors, we compared digestive performance and gut microbial community diversity and composition in red-backed salamanders housed at three experimental temperatures—10°C, 15°C, and 20°C. We also investigated associations between specific bacterial taxa and temperature, or salamander digestive performance. We found that salamander digestive performance was greatest at 15°C, while gut microbial diversity was reduced at 20°C. Further, gut microbial community composition differed among the three temperature treatments. The relative abundances of 25 bacterial genera were dependent on temperature, with high temperatures being associated with reductions in relative abundance of disease-resistant bacteria and increases in pathogenic taxa. The relative abundances of four bacterial genera were correlated with salamander energy assimilation, two of which are known to digest chitin, a main component of the red-backed salamander diet. These findings suggest that gut microbiota may mediate the relationship between temperature and digestion in ectotherms. We discuss how global climate change may impact ectotherms by altering host-microbe interactions.

Protocols for Investigating the Leaf Mycobiome Using High-Throughput DNA Sequencing

High-throughput sequencing of taxon-specific loci, or DNA metabarcoding, has become an invaluable tool for investigating the composition of plant-associated fungal communities and for elucidating plant-fungal interactions. While sequencing fungal communities has become routine, there remain numerous potential sources of systematic error that can introduce biases and compromise metabarcoding data. This chapter presents a protocol for DNA metabarcoding of the leaf mycobiome based on current best practices to minimize errors through careful laboratory practices and validation.

16S rRNA Gene Analysis with QIIME2

Microbial marker-gene sequence data can be used to generate comprehensive taxonomic profiles of the microorganisms present in a given community and for other community diversity analyses. The process of going from raw gene sequences to taxonomic profiles or diversity measures involves a series of data transformations performed by numerous computational tools. This includes tools for sequence quality checking, denoising, taxonomic classification, alignment, and phylogenetic tree building. In this chapter, we demonstrate how the Quantitative Insights Into Microbial Ecology version 2 (QIIME2) software suite can simplify 16S rRNA marker-gene analysis. We walk through an example data set extracted from the guts of bumblebees in order to show how QIIME2 can transform raw sequences into taxonomic bar plots, phylogenetic trees, principal co-ordinates analyses, and other visualizations of microbial diversity.

DNA-SIP based genome-centric metagenomics identifies key long-chain fatty acid-degrading populations in anaerobic digesters with different feeding frequencies

Fats, oils and greases (FOG) are energy-dense wastes that can be added to anaerobic digesters to substantially increase biomethane recovery via their conversion through long-chain fatty acids (LCFAs). However, a better understanding of the ecophysiology of syntrophic LCFA-degrading microbial communities in anaerobic digesters is needed to develop operating strategies that mitigate inhibitory LCFA accumulation from FOG. In this research, DNA stable isotope probing (SIP) was coupled with metagenomic sequencing for a genome-centric comparison of oleate (C18:1)-degrading populations in two anaerobic codigesters operated with either a pulse feeding or continuous-feeding strategy. The pulse-fed codigester microcosms converted oleate into methane at over 20% higher rates than the continuous-fed codigester microcosms. Differential coverage binning was demonstrated for the first time to recover population genome bins (GBs) from DNA-SIP metagenomes. About 70% of the 13C-enriched GBs were taxonomically assigned to the Syntrophomonas genus, thus substantiating the importance of Syntrophomonas species to LCFA degradation in anaerobic digesters. Phylogenetic comparisons of 13C-enriched GBs showed that phylogenetically distinct Syntrophomonas GBs were unique to each codigester. Overall, these results suggest that syntrophic populations in anaerobic digesters can have different adaptive capacities, and that selection for divergent populations may be achieved by adjusting reactor operating conditions to maximize biomethane recovery.

Normalization of Microbiome Profiling Data

Normalization is a term that is often used but rarely defined and poorly understood. The number of choices of normalization procedure is large-some are inappropriate or inadmissible-and all are narrowly relevant to a specific analysis that depends on both the nature of the data and the question being asked. This chapter describes key definitions of normalization as they apply in metagenomics, mainly for taxonomic profiling data; while also demonstrating specific, reproducible examples of normalization procedures in the context of analysis techniques for which they were intended. The analysis and graphics code is distributed as a supplemental companion to this chapter so that the motivated reader can re-use it on new data.

Soil Microbiomes Associated with Verticillium Wilt-Suppressive Broccoli and Chitin Amendments are Enriched with Potential Biocontrol Agents

Two naturally infested Verticillium wilt-conducive soils from the Salinas Valley of coastal California were amended with disease-suppressive broccoli residue or crab meal amendments, and changes to the soil prokaryote community were monitored using Illumina sequencing of a 16S ribosomal RNA gene library generated from 160 bulk soil samples. The experiment was run in a greenhouse, twice, with eggplant as the Verticillium wilt-susceptible host. Disease suppression, plant height, soil microsclerotia density, and soil chitinase activity were assessed at the conclusion of each experiment. In soil with high microsclerotia density, all amendments significantly reduced Verticillium wilt severity and microsclerotia density, and increased soil chitinase activity. Plant height was increased only in the broccoli-containing treatments. In total, 8,790 error-corrected sequence variants representing 1,917,893 different sequences were included in the analyses. The treatments had a significant impact on the soil microbiome community structure but measures of α diversity did not vary between treatments. Community structure correlated with disease score, plant height, microsclerotia density, and soil chitinase activity, suggesting that the prokaryote community may affect the disease-related response variables or vice versa. Similarly, the abundance of 107 sequence variants correlated with disease-related response variables, which included variants from genera with known antagonists of filamentous fungal plant pathogens, such as Pseudomonas and Streptomyces. Overall, genera with antifungal antagonists were more abundant in amended soils than unamended soils, and constituted up to 8.9% of all sequences in broccoli+crabmeal-amended soil. This study demonstrates that substrate-mediated shifts in soil prokaryote communities are associated with the transition of Verticillium wilt-conducive soils to Verticillium wilt-suppressive soils, and suggests that soils likely harbor numerous additional antagonists of fungal plant pathogens that contribute to the biological suppression of plant disease.

The gut microbiota as a novel regulator of cardiovascular function and disease

The gut microbiome has emerged as a critical regulator of human physiology. Deleterious changes to the composition or number of gut bacteria, commonly referred to as gut dysbiosis, has been linked to the development and progression of numerous diet-related diseases, including cardiovascular disease (CVD). Most CVD risk factors, including aging, obesity, certain dietary patterns, and a sedentary lifestyle, have been shown to induce gut dysbiosis. Dysbiosis is associated with intestinal inflammation and reduced integrity of the gut barrier, which in turn increases circulating levels of bacterial structural components and microbial metabolites that may facilitate the development of CVD. The aim of the current review is to summarize the available data regarding the role of the gut microbiome in regulating CVD function and disease processes. Particular emphasis is placed on nutrition-related alterations in the microbiome, as well as the underlying cellular mechanisms by which the microbiome may alter CVD risk.