LotuS: an efficient and user-friendly OTU processing pipeline

Fecal microbiota associated with phytohaemagglutinin-induced immune response in nestlings of a passerine bird

The vertebrate gastrointestinal tract is inhabited by a diverse community of bacteria, the so-called gut microbiota (GM). Research on captive mammalian models has revealed tight mutual interactions between immune functions and GM. However, our knowledge of GM versus immune system interactions in wild populations and nonmammalian species remains poor. Here, we focus on the association between GM community structure and immune response measured via the phytohaemagglutinin (PHA) skin swelling test in 12-day-old nestlings of a passerine bird, the barn swallow (Hirundo rustica). The PHA test, a widely used method in field ecoimmunology, assesses cell-mediated immunity. GM structure was inferred based on high-throughput 16S rRNA sequencing of microbial communities in fecal samples. We did not find any association between PHA response and GM diversity; however, our data revealed that the intensity of PHA response was correlated with differences in GM composition at the whole-community level. Ten bacterial operational taxonomic units corresponding to both putative commensal and pathogens were identified as drivers of the compositional variation. In conclusion, our study suggests existence of GM versus immune system interactions in a free-living nonmammalian species, which corresponds with previous research on captive vertebrates.

Host genetics and the rumen microbiome jointly associate with methane emissions in dairy cows

Cattle and other ruminants produce large quantities of methane (~110 million metric tonnes per annum), which is a potent greenhouse gas affecting global climate change. Methane (CH4) is a natural by-product of gastro-enteric microbial fermentation of feedstuffs in the rumen and contributes to 6% of total CH4 emissions from anthropogenic-related sources. The extent to which the host genome and rumen microbiome influence CH4 emission is not yet well known. This study confirms individual variation in CH4 production was influenced by individual host (cow) genotype, as well as the host's rumen microbiome composition. Abundance of a small proportion of bacteria and archaea taxa were influenced to a limited extent by the host's genotype and certain taxa were associated with CH4 emissions. However, the cumulative effect of all bacteria and archaea on CH4 production was 13%, the host genetics (heritability) was 21% and the two are largely independent. This study demonstrates variation in CH4 emission is likely not modulated through cow genetic effects on the rumen microbiome. Therefore, the rumen microbiome and cow genome could be targeted independently, by breeding low methane-emitting cows and in parallel, by investigating possible strategies that target changes in the rumen microbiome to reduce CH4 emissions in the cattle industry.

Comparison of initial oral microbiomes of young adults with and without cavitated dentin caries lesions using an in situ biofilm model

Dental caries is caused by acids released from bacterial biofilms. However, the in vivo formation of initial biofilms in relation to caries remains largely unexplored. The aim of this study was to compare the oral microbiome during the initial phase of bacterial colonization for individuals with (CC) and without (NC) cavitated dentin caries lesions. Bovine enamel slabs on acrylic splints were worn by the volunteers (CC: 14, NC: 13) for in situ biofilm formation (2 h, 4 h, 8 h, 1 ml saliva as reference). Sequencing of the V1/V2 regions of the 16S rRNA gene was performed (MiSeq). The relative abundances of individual operational taxonomic units (OTUs) were compared between samples from the CC group and the NC group. Random forests models were furthermore trained to separate the groups. While the overall heterogeneity did not differ substantially between CC and NC individuals, several individual OTUs were found to have significantly different relative abundances. For the 8 h samples, most of the significant OTUs showed higher relative abundances in the CC group, while the majority of significant OTUs in the saliva samples were more abundant in the NC group. Furthermore, using OTU signatures enabled a separation between both groups, with area-under-the-curve (AUC) values of ~0.8. In summary, the results suggest that initial oral biofilms provide the potential to differentiate between CC and NC individuals.

Great differences in performance and outcome of high-throughput sequencing data analysis platforms for fungal metabarcoding

Along with recent developments in high-throughput sequencing (HTS) technologies and thus fast accumulation of HTS data, there has been a growing need and interest for developing tools for HTS data processing and communication. In particular, a number of bioinformatics tools have been designed for analysing metabarcoding data, each with specific features, assumptions and outputs. To evaluate the potential effect of the application of different bioinformatics workflow on the results, we compared the performance of different analysis platforms on two contrasting high-throughput sequencing data sets. Our analysis revealed that the computation time, quality of error filtering and hence output of specific bioinformatics process largely depends on the platform used. Our results show that none of the bioinformatics workflows appears to perfectly filter out the accumulated errors and generate Operational Taxonomic Units, although PipeCraft, LotuS and PIPITS perform better than QIIME2 and Galaxy for the tested fungal amplicon dataset. We conclude that the output of each platform requires manual validation of the OTUs by examining the taxonomy assignment values.

Structure and function of the global topsoil microbiome

Soils harbour some of the most diverse microbiomes on Earth and are essential for both nutrient cycling and carbon storage. To understand soil functioning, it is necessary to model the global distribution patterns and functional gene repertoires of soil microorganisms, as well as the biotic and environmental associations between the diversity and structure of both bacterial and fungal soil communities^1-4. Here we show, by leveraging metagenomics and metabarcoding of global topsoil samples (189 sites, 7,560 subsamples), that bacterial, but not fungal, genetic diversity is highest in temperate habitats and that microbial gene composition varies more strongly with environmental variables than with geographic distance. We demonstrate that fungi and bacteria show global niche differentiation that is associated with contrasting diversity responses to precipitation and soil pH. Furthermore, we provide evidence for strong bacterial-fungal antagonism, inferred from antibiotic-resistance genes, in topsoil and ocean habitats, indicating the substantial role of biotic interactions in shaping microbial communities. Our results suggest that both competition and environmental filtering affect the abundance, composition and encoded gene functions of bacterial and fungal communities, indicating that the relative contributions of these microorganisms to global nutrient cycling varies spatially.

Fecal microbiome signatures are different in food-allergic children compared to siblings and healthy children

BACKGROUND

Intestinal microbes have been shown to influence predisposition to atopic disease, including food allergy. The intestinal microbiome of food-allergic children may differ in significant ways from genetically similar non-allergic children and age-matched controls. The aim was to characterize fecal microbiomes to identify taxa that may influence the expression of food allergy.

METHODS

Stool samples were collected from children with IgE-mediated food allergies, siblings without food allergy, and non-allergic controls. Stool microbiome characterization was performed via next-generation sequencing (Illumina) of the V1V3 and V4 variable regions of the 16S rRNA gene. Bacterial diversity, evenness, richness, and relative abundance of the operational taxonomic units (OTUs) were evaluated using QIIME. ANOVA and Welch's t test were utilized to compare groups.

RESULTS

Sixty-eight children were included: food-allergic (n = 22), non-food-allergic siblings (n = 25), and controls (n = 21). When comparing fecal microbial communities across groups, differences were noted in Rikenellaceae (P = .035), Actinomycetaceae (P = .043), and Pasteurellaceae (P = .018), and nine other distinct OTUs. Food-allergic subjects had enrichment for specific microbes within the Clostridia class and Firmicutes phylum (Oscillobacter valericigenes, Lachnoclostridium bolteae, Faecalibacterium sp.) compared to siblings and controls. Identification of Clostridium sp. OTUs revealed differences in specific Clostridia drive the separation of the allergic from the siblings and controls. Alistipes sp. were enriched in non-allergic siblings.

CONCLUSIONS

Comparisons in the fecal microbiome of food-allergic children, siblings, and healthy children point to key differences in microbiome signatures, suggesting the role of both genetic and environmental contributors in the manifestation of food-allergic disease.

The effect of biochar feedstock, pyrolysis temperature, and application rate on the reduction of ammonia volatilisation from biochar-amended soil

Ammonia (NH₃) volatilisation is one of the most important causes of nitrogen (N) loss in soil-plant systems worldwide. Carbon-based amendments such as biochar have been shown to mitigate NH₃ volatilisation in agricultural soils to various degrees. In this study, we investigated the influence of biochar feedstocks (poultry manure, green waste compost, and wheat straw), pyrolysis temperatures (250, 350, 450, 500 and 700°C) and application rates (1 and 2%), on NH₃ volatilisation from a calcareous soil. The 15 biochars were chemically characterized, and a laboratory incubation study was conducted to assess NH₃ volatilisation from the soil over a period of four weeks. Furthermore, changes to the bacterial and fungal communities were assessed via sequencing of phylogenetic marker genes. The study showed that biochar feedstock sources, pyrolysis temperature, and application rates all affected NH₃ volatilisation. Overall, low pyrolysis temperature biochars and higher biochar application rates achieved greater reductions in NH₃ volatilisation. A feedstock related effect was also observed, with poultry manure biochar reducing NH₃ volatilisation by an average of 53% in comparison to 38% and 35% reductions for biochar from green waste compost and wheat straw respectively. Results indicate that the biogeochemistry underlying biochar-mediated reduction in NH₃ volatilisation is complex and caused by changes in soil pH, NH₃ sorption and microbial community composition (especially ammonia oxidising guilds).

The gut microbiome is associated with behavioural task in honey bees

The gut microbiome is recognised as playing an integral role in the health and ecology of a wide variety of animal taxa. However, the relationship between social behavioural traits and the microbial community has received little attention. Honey bees are highly social and the workers perform different behavioural tasks in the colony that cause them to be exposed to different local environments. Here we examined whether the gut microbial community composition of worker honey bees is associated with the behavioural tasks they perform, and therefore also the local environment they are exposed to. We set up five observation hives, in which all workers were matched in age and observed the behaviour of marked bees in each colony over 4 days. The gut bacterial communities of bees seen performing predominantly foraging or predominantly in nest tasks were then characterised and compared based on amplicon sequencing of the 16S rRNA gene. Our results show that some core members of the unique honey bee gut bacterial community are represented in different relative abundances in bees performing different behavioural tasks. The differentially represented bacterial taxa include some thought to be important in carbohydrate metabolism and transport, and also linked to bee health. The results suggest an influence of task-related local environment exposure and diet on the honey bee gut microbial community and identify focal core taxa for further functional analyses.

Postnatal colonization with human "infant-type" Bifidobacterium species alters behavior of adult gnotobiotic mice

Accumulating studies have defined a role for the intestinal microbiota in modulation of host behavior. Research using gnotobiotic mice emphasizes that early microbial colonization with a complex microbiota (conventionalization) can rescue some of the behavioral abnormalities observed in mice that grow to adulthood completely devoid of bacteria (germ-free mice). However, the human infant and adult microbiomes vary greatly, and effects of the neonatal microbiome on neurodevelopment are currently not well understood. Microbe-mediated modulation of neural circuit patterning in the brain during neurodevelopment may have significant long-term implications that we are only beginning to appreciate. Modulation of the host central nervous system by the early-life microbiota is predicted to have pervasive and lasting effects on brain function and behavior. We sought to replicate this early microbe-host interaction by colonizing gnotobiotic mice at the neonatal stage with a simplified model of the human infant gut microbiota. This model consortium consisted of four “infant-type” Bifidobacterium species known to be commensal members of the human infant microbiota present in high abundance during postnatal development. Germ-free mice and mice neonatally-colonized with a complex, conventional murine microbiota were used for comparison. Motor and non-motor behaviors of the mice were tested at 6–7 weeks of age, and colonization patterns were characterized by 16S ribosomal RNA gene sequencing. Adult germ-free mice were observed to have abnormal memory, sociability, anxiety-like behaviors, and motor performance. Conventionalization at the neonatal stage rescued these behavioral abnormalities, and mice colonized with Bifidobacterium spp. also exhibited important behavioral differences relative to the germ-free controls. The ability of Bifidobacterium spp. to improve the recognition memory of both male and female germ-free mice was a prominent finding. Together, these data demonstrate that the early-life gut microbiome, and human “infant-type” Bifidobacterium species, affect adult behavior in a strongly sex-dependent manner, and can selectively recapitulate the results observed when mice are colonized with a complex microbiota.

Stool and urine trefoil factor 3 levels: associations with symptoms, intestinal permeability, and microbial diversity in irritable bowel syndrome

Previously we showed that urine trefoil factor 3 (TFF3) levels were higher in females with irritable bowel syndrome (IBS) compared to non-IBS females. To assess if TFF3 is associated with symptoms and/or reflect alterations in gastrointestinal permeability and gut microbiota in an IBS population, we correlated stool and urine TFF3 levels with IBS symptoms, intestinal permeability, stool microbial diversity and relative abundance of predominant bacterial families and genera. We also tested the relationship of stool TFF3 to urine TFF3, and compared results based on hormone contraception use. Samples were obtained from 93 females meeting Rome III IBS criteria and completing 4-week symptom diaries. TFF3 levels were measured by ELISA. Permeability was assessed with the urine lactulose/mannitol (L/M) ratio. Stool microbiota was assessed using 16S rRNA. Stool TFF3, but not urine TFF3, was associated positively with diarrhoea and loose stool consistency. Higher stool TFF3 was also associated with lower L/M ratio and microbial diversity. Of the 20 most abundant bacterial families Mogibacteriaceae and Christensenellaceae were inversely related to stool TFF3, with only Christensenellaceae remaining significant after multiple comparison adjustment. There were no significant relationships between stool or urine TFF3 levels and other symptoms, nor between stool and urine levels. In premenopausal females, urine TFF3 levels were higher in those reporting hormone contraception. Collectively these results suggest that higher stool TFF3 levels are associated with IBS symptoms (loose/diarrhoeal stools), lower gut permeability, and altered stool bacteria composition (decreased diversity and decreased Christensenellaceae), which further suggests that TFF3 may be an important marker of host-bacteria interaction.

Toxic Cyanobacteria in Svalbard: Chemical Diversity of Microcystins Detected Using a Liquid Chromatography Mass Spectrometry Precursor Ion Screening Method

Cyanobacteria synthesize a large variety of secondary metabolites including toxins. Microcystins (MCs) with hepato- and neurotoxic potential are well studied in bloom-forming planktonic species of temperate and tropical regions. Cyanobacterial biofilms thriving in the polar regions have recently emerged as a rich source for cyanobacterial secondary metabolites including previously undescribed congeners of microcystin. However, detection and detailed identification of these compounds is difficult due to unusual sample matrices and structural congeners produced. We here report a time-efficient liquid chromatography-mass spectrometry (LC-MS) precursor ion screening method that facilitates microcystin detection and identification. We applied this method to detect six different MC congeners in 8 out of 26 microbial mat samples of the Svalbard Archipelago in the Arctic. The congeners, of which [Asp³, ADMAdda⁵, Dhb⁷] MC-LR was most abundant, were similar to those reported in other polar habitats. Microcystins were also determined using an Adda-specific enzyme-linked immunosorbent assay (Adda-ELISA). Nostoc sp. was identified as a putative toxin producer using molecular methods that targeted 16S rRNA genes and genes involved in microcystin production. The mcy genes detected showed highest similarities to other Arctic or Antarctic sequences. The LC-MS precursor ion screening method could be useful for microcystin detection in unusual matrices such as benthic biofilms or lichen.

RTK: efficient rarefaction analysis of large datasets

Motivation

The rapidly expanding microbiomics field is generating increasingly larger datasets, characterizing the microbiota in diverse environments. Although classical numerical ecology methods provide a robust statistical framework for their analysis, software currently available is inadequate for large datasets and some computationally intensive tasks, like rarefaction and associated analysis.

Results

Here we present a software package for rarefaction analysis of large count matrices, as well as estimation and visualization of diversity, richness and evenness. Our software is designed for ease of use, operating at least 7x faster than existing solutions, despite requiring 10x less memory.

Availability and Implementation

C ++ and R source code (GPL v.2) as well as binaries are available from https://github.com/hildebra/Rarefaction and from CRAN (https://cran.r-project.org/).

Supplementary information

Supplementary data are available at Bioinformatics online.

Characterization of the Stool Microbiome in Hispanic Preschool Children by Weight Status and Time

BACKGROUND

Variations in gut microbiota composition and diversity have been associated with childhood adiposity, although most studies describing this have been cross-sectional in nature. Our objective was to evaluate associations between body weight and the gut microbiota over time in obese preschool-age children.

METHODS

Obese, preschool-age, Hispanic children provided stool samples at baseline and following a 6-month behavioral intervention. Normal-weight (NW) children also provided stool samples. Stool microbial community composition was characterized using 16S rRNA gene sequencing. Estimates of within-sample diversity were calculated on operational taxonomic unit (OTU) count data, and the Firmicutes:Bacteroidetes (F:B) ratio was determined on per-sample basis. Estimates of between-sample diversity were generated using the weighted Unifrac metric, differential abundances were evaluated using Wilcoxon rank-sum tests, and associations of microbiome features with clinical data were quantified using Spearman rank correlations.

RESULTS

For the 30 obese children sampled preintervention and postintervention, a decrease in body mass index (BMI) z-score from 2.55 to 2.34 (p = 0.004, paired t-test) was observed. Bacteroides massiliensis was significantly enriched in obese children, while B. plebius was significantly enriched in NW controls. We identified significant correlations between multiple Bacteroides-like OTUs and BMI z-score, but neither F:B ratios nor OTU-level abundances were altered in conjunction with weight change in the obese children. Rather, highly individualized OTU-level responses were observed.

CONCLUSIONS

Although differences exist between the gut microbiota of obese and NW children, we detected highly individualized responses of the gut microbiota of obese children over time and following weight loss.

Gut microbiota composition is associated with environmental landscape in honey bees

There is growing recognition that the gut microbial community regulates a wide variety of important functions in its animal hosts, including host health. However, the complex interactions between gut microbes and environment are still unclear. Honey bees are ecologically and economically important pollinators that host a core gut microbial community that is thought to be constant across populations. Here, we examined whether the composition of the gut microbial community of honey bees is affected by the environmental landscape the bees are exposed to. We placed honey bee colonies reared under identical conditions in two main landscape types for 6 weeks: either oilseed rape farmland or agricultural farmland distant to fields of flowering oilseed rape. The gut bacterial communities of adult bees from the colonies were then characterized and compared based on amplicon sequencing of the 16S rRNA gene. While previous studies have delineated a characteristic core set of bacteria inhabiting the honey bee gut, our results suggest that the broad environment that bees are exposed to has some influence on the relative abundance of some members of that microbial community. This includes known dominant taxa thought to have functions in nutrition and health. Our results provide evidence for an influence of landscape exposure on honey bee microbial community and highlight the potential effect of exposure to different environmental parameters, such as forage type and neonicotinoid pesticides, on key honey bee gut bacteria. This work emphasizes the complexity of the relationship between the host, its gut bacteria, and the environment and identifies target microbial taxa for functional analyses.

Community structure of the metabolically active rumen bacterial and archaeal communities of dairy cows over the transition period

Dairy cows experience dramatic changes in host physiology from gestation to lactation period and dietary switch from high-forage prepartum diet to high-concentrate postpartum diet over the transition period (parturition +/- three weeks). Understanding the community structure and activity of the rumen microbiota and its associative patterns over the transition period may provide insight for e.g. improving animal health and production. In the present study, rumen samples from ten primiparous Holstein dairy cows were collected over seven weeks spanning the transition period. Total RNA was extracted from the rumen samples and cDNA thereof was subsequently used for characterizing the metabolically active bacterial (16S rRNA transcript amplicon sequencing) and archaeal (qPCR, T-RFLP and mcrA and 16S rRNA transcript amplicon sequencing) communities. The metabolically active bacterial community was dominated by three phyla, showing significant changes in relative abundance range over the transition period: Firmicutes (from prepartum 57% to postpartum 35%), Bacteroidetes (from prepartum 22% to postpartum 18%) and Proteobacteria (from prepartum 7% to postpartum 32%). For the archaea, qPCR analysis of 16S rRNA transcript number, revealed a significant prepartum to postpartum increase in Methanobacteriales, in accordance with an observed increase (from prepartum 80% to postpartum 89%) in relative abundance of 16S rRNA transcript amplicons allocated to this order. On the other hand, a significant prepartum to postpartum decrease (from 15% to 2%) was observed in relative abundance of Methanomassiliicoccales 16S rRNA transcripts. In contrast to qPCR analysis of the 16S rRNA transcripts, quantification of mcrA transcripts revealed no change in total abundance of metabolically active methanogens over the transition period. According to T-RFLP analysis of the mcrA transcripts, two Methanobacteriales genera, Methanobrevibacter and Methanosphaera (represented by the T-RFs 39 and 267 bp), represented more than 70% of the metabolically active methanogens, showing no significant changes over the transition period; minor T-RFs, likely to represent members of the order Methanomassiliicoccales and with a relative abundance below 5% in total, decreased significantly over the transition period. In accordance with the T-RFLP analysis, the mcrA transcript amplicon sequencing revealed Methanobacteriales to cover 99% of the total reads, dominated by the genera Methanobrevibacter (75%) and Methanosphaera (24%), whereas the Methanomassiliicoccales order covered only 0.2% of the total reads. In conclusion, the present study showed that the structure of the metabolically active bacterial and archaeal rumen communities changed over the transition period, likely in response to the dramatic changes in physiology and nutritional factors like dry matter intake and feed composition. It should be noted however that for the methanogens, the observed community changes were influenced by the analyzed gene (mcrA or 16S rRNA).

The nasal and gut microbiome in Parkinson's disease and idiopathic rapid eye movement sleep behavior disorder

Background

Increasing evidence connects the gut microbiota and the onset and/or phenotype of Parkinson's disease (PD). Differences in the abundances of specific bacterial taxa have been reported in PD patients. It is, however, unknown whether these differences can be observed in individuals at high risk, for example, with idiopathic rapid eye movement sleep behavior disorder, a prodromal condition of α‐synuclein aggregation disorders including PD.

Objectives

To compare microbiota in carefully preserved nasal wash and stool samples of subjects with idiopathic rapid eye movement sleep behavior disorder, manifest PD, and healthy individuals.

Methods

Microbiota of flash‐frozen stool and nasal wash samples from 76 PD patients, 21 idiopathic rapid eye movement sleep behavior disorder patients, and 78 healthy controls were assessed by 16S and 18S ribosomal RNA amplicon sequencing. Seventy variables, related to demographics, clinical parameters including nonmotor symptoms, and sample processing, were analyzed in relation to microbiome variability and controlled differential analyses were performed.

Results

Differentially abundant gut microbes, such as Akkermansia, were observed in PD, but no strong differences in nasal microbiota. Eighty percent of the differential gut microbes in PD versus healthy controls showed similar trends in idiopathic rapid eye movement sleep behavior disorder, for example, Anaerotruncus and several Bacteroides spp., and correlated with nonmotor symptoms. Metagenomic sequencing of select samples enabled the reconstruction of genomes of so far uncharacterized differentially abundant organisms.

Conclusion

Our study reveals differential abundances of gut microbial taxa in PD and its prodrome idiopathic rapid eye movement sleep behavior disorder in comparison to the healthy controls, and highlights the potential of metagenomics to identify and characterize microbial taxa, which are enriched or depleted in PD and/or idiopathic rapid eye movement sleep behavior disorder. © 2017 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.

Integrated meta-omic analyses of the gastrointestinal tract microbiome in patients undergoing allogeneic hematopoietic stem cell transplantation

In patients undergoing allogeneic hematopoietic stem cell transplantation (allo-HSCT), treatment-induced changes to the gastrointestinal tract (GIT) microbiome have been linked to adverse outcomes, most notably graft-versus-host disease (GvHD). However, it is presently unknown whether this relationship is causal or consequential. Here, we performed an integrated meta-omic analysis to probe deeper into the GIT microbiome changes during allo-HSCT and its accompanying treatments. We used 16S and 18S rRNA gene amplicon sequencing to resolve archaea, bacteria, and eukaryotes within the GIT microbiomes of 16 patients undergoing allo-HSCT for the treatment of hematologic malignancies. These results revealed a major shift in the GIT microbiome after allo-HSCT including a marked reduction in bacterial diversity, accompanied by only limited changes in eukaryotes and archaea. An integrated analysis of metagenomic and metatranscriptomic data was performed on samples collected from a patient before and after allo-HSCT for acute myeloid leukemia. This patient developed severe GvHD, leading to death 9 months after allo-HSCT. In addition to drastically decreased bacterial diversity, the post-treatment microbiome showed a higher overall number and higher expression levels of antibiotic resistance genes (ARGs). One specific Escherichia coli strain causing a paravertebral abscess was linked to GIT dysbiosis, suggesting loss of intestinal barrier integrity. The apparent selection for bacteria expressing ARGs suggests that prophylactic antibiotic administration may adversely affect the overall treatment outcome. We therefore assert that such analyses including information about the selection of pathogenic bacteria expressing ARGs may assist clinicians in "personalizing" regimens for individual patients to improve overall outcomes.

Insights into study design and statistical analyses in translational microbiome studies

Research questions in translational microbiome studies are substantially more complex than their counterparts in basic science. Robust study designs with appropriate statistical analysis frameworks are pivotal to the success of these translational studies. This review considers how study designs can account for heterogeneous phenotypes by adopting representative sampling schemes for recruiting the study population and making careful choices about the control population. Advantages and limitations of 16S profiling and whole-genome sequencing, the two primary techniques for measuring the microbiome, are discussed followed by an overview of bioinformatic processing of high-throughput sequencing data from these measurements. Practical insights into the downstream statistical analyses including data processing and integration, variable transformations, and data exploration are provided. The merits of regularization and ensemble modeling for analyzing microbiome data are discussed along with a recommendation for selecting modeling approaches based on data-driven simulations and objective evaluation. The review builds on several recent discussions of study design issues in microbiome research but with a stronger emphasis on the downstream and often-ignored aspects of statistical analyses that are crucial for bridging the gap between basic science and translation.

Variation between the oral and faecal microbiota in a free-living passerine bird, the great tit (Parus major)

The gastrointestinal tract of vertebrates is inhabited by diverse bacterial communities that induce marked effects on the host physiology and health status. The composition of the gastrointestinal microbiota is characterized by pronounced taxonomic and functional variability among different regions of the vertebrate gastrointestinal tract. Despite the relatively solid knowledge on the among-region variations of the gastrointestinal microbiota in model mammalian species, there are only a few studies concerning among-region variations of the gastrointestinal microbiota in free-living non-mammalian vertebrate taxa. We used Illumina MiSeq sequencing of bacterial 16S rRNA amplicons to compare the diversity as well as taxonomic composition of bacterial communities in proximal vs. distal parts of the gastrointestinal tract (represented by oral swabs and faecal samples, respectively) in a wild passerine bird, the great tit (Parus major). The diversity of the oral microbiota was significantly higher compared to the faecal microbiota, whereas interindividual variation was higher in faecal than in oral samples. We also observed a pronounced difference in taxonomic content between the oral and faecal microbiota. Bacteria belonging to the phyla Proteobacteria, Firmicutes and Actinobacteria typically dominated in both oral and faecal samples. A high abundance of bacteria belonging to Tenericutes was observed only in faecal samples. Surprisingly, we found only a slight correlation between the faecal and oral microbiota at the within-individual level, suggesting that the microbial composition in these body sites is shaped by independent regulatory processes. Given the independence of these two communities at the individual level, we propose that simultaneous sampling of the faecal and oral microbiota will extend our understanding of host vs. microbiota interactions in wild populations.

From reads to operational taxonomic units: an ensemble processing pipeline for MiSeq amplicon sequencing data

The development of high-throughput sequencing technologies has provided microbial ecologists with an efficient approach to assess bacterial diversity at an unseen depth, particularly with the recent advances in the Illumina MiSeq sequencing platform. However, analyzing such high-throughput data is posing important computational challenges, requiring specialized bioinformatics solutions at different stages during the processing pipeline, such as assembly of paired-end reads, chimera removal, correction of sequencing errors, and clustering of those sequences into Operational Taxonomic Units (OTUs). Individual algorithms grappling with each of those challenges have been combined into various bioinformatics pipelines, such as mothur, QIIME, LotuS, and USEARCH. Using a set of well-described bacterial mock communities, state-of-the-art pipelines for Illumina MiSeq amplicon sequencing data are benchmarked at the level of the amount of sequences retained, computational cost, error rate, and quality of the OTUs. In addition, a new pipeline called OCToPUS is introduced, which is making an optimal combination of different algorithms. Huge variability is observed between the different pipelines in respect to the monitored performance parameters, where in general the amount of retained reads is found to be inversely proportional to the quality of the reads. By contrast, OCToPUS achieves the lowest error rate, minimum number of spurious OTUs, and the closest correspondence to the existing community, while retaining the uppermost amount of reads when compared to other pipelines. The newly introduced pipeline translates Illumina MiSeq amplicon sequencing data into high-quality and reliable OTUs, with improved performance and accuracy compared to the currently existing pipelines.

Codiversification of gastrointestinal microbiota and phylogeny in passerines is not explained by ecological divergence

Vertebrate gut microbiota (GM) is comprised of a taxonomically diverse consortium of symbiotic and commensal microorganisms that have a pronounced effect on host physiology, immune system function and health status. Despite much research on interactions between hosts and their GM, the factors affecting inter- and intraspecific GM variation in wild populations are still poorly known. We analysed data on faecal microbiota composition in 51 passerine species (319 individuals) using Illumina MiSeq sequencing of bacterial 16S rRNA (V3-V4 variable region). Despite pronounced interindividual variation, GM composition exhibited significant differences at the interspecific level, accounting for approximately 20%-30% of total GM variation. We also observed a significant correlation between GM composition divergence and host's phylogenetic divergence, with strength of correlation higher than that of GM vs. ecological or life history traits and geographic variation. The effect of host's phylogeny on GM composition was significant, even after statistical control for these confounding factors. Hence, our data do not support codiversification of GM and passerine phylogeny solely as a by-product of their ecological divergence. Furthermore, our findings do not support that GM vs. host's phylogeny codiversification is driven primarily through trans-generational GM transfer as the GM vs. phylogeny correlation does not increase with higher sequence similarity used when delimiting operational taxonomic units. Instead, we hypothesize that the GM vs. phylogeny correlation may arise as a consequence of interspecific divergence of genes that directly or indirectly modulate composition of GM.

Bacterial Communities in Boreal Forest Mushrooms Are Shaped Both by Soil Parameters and Host Identity

Despite recent advances in understanding the microbiome of eukaryotes, little is known about microbial communities in fungi. Here we investigate the structure of bacterial communities in mushrooms, including common edible ones, with respect to biotic and abiotic factors in the boreal forest. Using a combination of culture-based and Illumina high-throughput sequencing, we characterized the bacterial communities in fruitbodies of fungi from eight genera spanning four orders of the class Agaricomycetes (Basidiomycota). Our results revealed that soil pH followed by fungal identity are the main determinants of the structure of bacterial communities in mushrooms. While almost half of fruitbody bacteria were also detected from soil, the abundance of several bacterial taxa differed considerably between the two environments. The effect of host identity was significant at the fungal genus and order level and could to some extent be ascribed to the distinct bacterial community of the chanterelle, representing Cantharellales-the earliest diverged group of mushroom-forming basidiomycetes. These data suggest that besides the substantial contribution of soil as a major taxa source of bacterial communities in mushrooms, the structure of these communities is also affected by the identity of the host. Thus, bacteria inhabiting fungal fruitbodies may be non-randomly selected from environment based on their symbiotic functions and/or habitat requirements.

Colonization and Succession within the Human Gut Microbiome by Archaea, Bacteria, and Microeukaryotes during the First Year of Life

Perturbations to the colonization process of the human gastrointestinal tract have been suggested to result in adverse health effects later in life. Although much research has been performed on bacterial colonization and succession, much less is known about the other two domains of life, archaea, and eukaryotes. Here we describe colonization and succession by bacteria, archaea and microeukaryotes during the first year of life (samples collected around days 1, 3, 5, 28, 150, and 365) within the gastrointestinal tract of infants delivered either vaginally or by cesarean section and using a combination of quantitative real-time PCR as well as 16S and 18S rRNA gene amplicon sequencing. Sequences from organisms belonging to all three domains of life were detectable in all of the collected meconium samples. The microeukaryotic community composition fluctuated strongly over time and early diversification was delayed in infants receiving formula milk. Cesarean section-delivered (CSD) infants experienced a delay in colonization and succession, which was observed for all three domains of life. Shifts in prokaryotic succession in CSD infants compared to vaginally delivered (VD) infants were apparent as early as days 3 and 5, which were characterized by increased relative abundances of the genera Streptococcus and Staphylococcus, and a decrease in relative abundance for the genera Bifidobacterium and Bacteroides. Generally, a depletion in Bacteroidetes was detected as early as day 5 postpartum in CSD infants, causing a significantly increased Firmicutes/Bacteroidetes ratio between days 5 and 150 when compared to VD infants. Although the delivery mode appeared to have the strongest influence on differences between the infants, other factors such as a younger gestational age or maternal antibiotics intake likely contributed to the observed patterns as well. Our findings complement previous observations of a delay in colonization and succession of CSD infants, which affects not only bacteria but also archaea and microeukaryotes. This further highlights the need for resolving bacterial, archaeal, and microeukaryotic dynamics in future longitudinal studies of microbial colonization and succession within the neonatal gastrointestinal tract.

Functional implications of microbial and viral gut metagenome changes in early stage L-DOPA-naïve Parkinson's disease patients

BACKGROUND

Parkinson's disease (PD) presently is conceptualized as a protein aggregation disease in which pathology involves both the enteric and the central nervous system, possibly spreading from one to another via the vagus nerves. As gastrointestinal dysfunction often precedes or parallels motor symptoms, the enteric system with its vast diversity of microorganisms may be involved in PD pathogenesis. Alterations in the enteric microbial taxonomic level of L-DOPA-naïve PD patients might also serve as a biomarker.

METHODS

We performed metagenomic shotgun analyses and compared the fecal microbiomes of 31 early stage, L-DOPA-naïve PD patients to 28 age-matched controls.

RESULTS

We found increased Verrucomicrobiaceae (Akkermansia muciniphila) and unclassified Firmicutes, whereas Prevotellaceae (Prevotella copri) and Erysipelotrichaceae (Eubacterium biforme) were markedly lowered in PD samples. The observed differences could reliably separate PD from control with a ROC-AUC of 0.84. Functional analyses of the metagenomes revealed differences in microbiota metabolism in PD involving the ẞ-glucuronate and tryptophan metabolism. While the abundances of prophages and plasmids did not differ between PD and controls, total virus abundance was decreased in PD participants. Based on our analyses, the intake of either a MAO inhibitor, amantadine, or a dopamine agonist (which in summary relates to 90% of PD patients) had no overall influence on taxa abundance or microbial functions.

CONCLUSIONS

Our data revealed differences of colonic microbiota and of microbiota metabolism between PD patients and controls at an unprecedented detail not achievable through 16S sequencing. The findings point to a yet unappreciated aspect of PD, possibly involving the intestinal barrier function and immune function in PD patients. The influence of the parkinsonian medication should be further investigated in the future in larger cohorts.

Deblur Rapidly Resolves Single-Nucleotide Community Sequence Patterns

Deblur provides a rapid and sensitive means to assess ecological patterns driven by differentiation of closely related taxa. This algorithm provides a solution to the problem of identifying real ecological differences between taxa whose amplicons differ by a single base pair, is applicable in an automated fashion to large-scale sequencing data sets, and can integrate sequencing runs collected over time.

High-throughput sequencing of 16S ribosomal RNA gene amplicons has facilitated understanding of complex microbial communities, but the inherent noise in PCR and DNA sequencing limits differentiation of closely related bacteria. Although many scientific questions can be addressed with broad taxonomic profiles, clinical, food safety, and some ecological applications require higher specificity. Here we introduce a novel sub-operational-taxonomic-unit (sOTU) approach, Deblur, that uses error profiles to obtain putative error-free sequences from Illumina MiSeq and HiSeq sequencing platforms. Deblur substantially reduces computational demands relative to similar sOTU methods and does so with similar or better sensitivity and specificity. Using simulations, mock mixtures, and real data sets, we detected closely related bacterial sequences with single nucleotide differences while removing false positives and maintaining stability in detection, suggesting that Deblur is limited only by read length and diversity within the amplicon sequences. Because Deblur operates on a per-sample level, it scales to modern data sets and meta-analyses. To highlight Deblur’s ability to integrate data sets, we include an interactive exploration of its application to multiple distinct sequencing rounds of the American Gut Project. Deblur is open source under the Berkeley Software Distribution (BSD) license, easily installable, and downloadable from https://github.com/biocore/deblur.

IMPORTANCE Deblur provides a rapid and sensitive means to assess ecological patterns driven by differentiation of closely related taxa. This algorithm provides a solution to the problem of identifying real ecological differences between taxa whose amplicons differ by a single base pair, is applicable in an automated fashion to large-scale sequencing data sets, and can integrate sequencing runs collected over time.

Deblur Rapidly Resolves Single-Nucleotide Community Sequence Patterns

High-throughput sequencing of 16S ribosomal RNA gene amplicons has facilitated understanding of complex microbial communities, but the inherent noise in PCR and DNA sequencing limits differentiation of closely related bacteria. Although many scientific questions can be addressed with broad taxonomic profiles, clinical, food safety, and some ecological applications require higher specificity. Here we introduce a novel sub-operational-taxonomic-unit (sOTU) approach, Deblur, that uses error profiles to obtain putative error-free sequences from Illumina MiSeq and HiSeq sequencing platforms. Deblur substantially reduces computational demands relative to similar sOTU methods and does so with similar or better sensitivity and specificity. Using simulations, mock mixtures, and real data sets, we detected closely related bacterial sequences with single nucleotide differences while removing false positives and maintaining stability in detection, suggesting that Deblur is limited only by read length and diversity within the amplicon sequences. Because Deblur operates on a per-sample level, it scales to modern data sets and meta-analyses. To highlight Deblur's ability to integrate data sets, we include an interactive exploration of its application to multiple distinct sequencing rounds of the American Gut Project. Deblur is open source under the Berkeley Software Distribution (BSD) license, easily installable, and downloadable from https://github.com/biocore/deblur. IMPORTANCE Deblur provides a rapid and sensitive means to assess ecological patterns driven by differentiation of closely related taxa. This algorithm provides a solution to the problem of identifying real ecological differences between taxa whose amplicons differ by a single base pair, is applicable in an automated fashion to large-scale sequencing data sets, and can integrate sequencing runs collected over time.

Distinct Microbiome-Neuroimmune Signatures Correlate With Functional Abdominal Pain in Children With Autism Spectrum Disorder

BACKGROUND & AIMS

Emerging data on the gut microbiome in autism spectrum disorder (ASD) suggest that altered host-microbe interactions may contribute to disease symptoms. Although gut microbial communities in children with ASD are reported to differ from individuals with neurotypical development, it is not known whether these bacteria induce pathogenic neuroimmune signals.

METHODS

Because commensal clostridia interactions with the intestinal mucosa can regulate disease-associated cytokine and serotonergic pathways in animal models, we evaluated whether microbiome-neuroimmune profiles (from rectal biopsy specimens and blood) differed in ASD children with functional gastrointestinal disorders (ASD-FGID, n = 14) compared with neurotypical (NT) children with FGID (NT-FGID, n = 15) and without abdominal pain (NT, n = 6). Microbial 16S ribosomal DNA community signatures, cytokines, and serotonergic metabolites were quantified and correlated with gastrointestinal symptoms.

RESULTS

A significant increase in several mucosa-associated Clostridiales was observed in ASD-FGID, whereas marked decreases in Dorea and Blautia, as well as Sutterella, were evident. Stratification by abdominal pain showed multiple organisms in ASD-FGID that correlated significantly with cytokines (interleukin [IL]6, IL1, IL17A, and interferon-γ). Group comparisons showed that IL6 and tryptophan release by mucosal biopsy specimens was highest in ASD children with abdominal pain, whereas serotonergic metabolites generally were increased in children with FGIDs. Furthermore, proinflammatory cytokines correlated significantly with several Clostridiales previously reported to associate with ASD, as did tryptophan and serotonin.

CONCLUSIONS

Our findings identify distinctive mucosal microbial signatures in ASD children with FGID that correlate with cytokine and tryptophan homeostasis. Future studies are needed to establish whether these disease-associated Clostridiales species confer early pathogenic signals in children with ASD and FGID.

Sampling Strategies for Three-Dimensional Spatial Community Structures in IBD Microbiota Research

Identifying intestinal microbiota is arguably an important task that is performed to determine the pathogenesis of inflammatory bowel diseases (IBD); thus, it is crucial to collect and analyze intestinally-associated microbiota. Analyzing a single niche to categorize individuals does not enable researchers to comprehensively study the spatial variations of the microbiota. Therefore, characterizing the spatial community structures of the inflammatory bowel disease microbiome is critical for advancing our understanding of the inflammatory landscape of IBD. However, at present there is no universally accepted consensus regarding the use of specific sampling strategies in different biogeographic locations. In this review, we discuss the spatial distribution when screening sample collections in IBD microbiota research. Here, we propose a novel model, a three-dimensional spatial community structure, which encompasses the x-, y-, and z-axis distributions; it can be used in some sampling sites, such as feces, colonoscopic biopsy, the mucus gel layer, and oral cavity. On the basis of this spatial model, this article also summarizes various sampling and processing strategies prior to and after DNA extraction and recommends guidelines for practical application in future research.

Temporal Stability and the Effect of Transgenerational Transfer on Fecal Microbiota Structure in a Long Distance Migratory Bird

Animal bodies are inhabited by a taxonomically and functionally diverse community of symbiotic and commensal microorganisms. From an ecological and evolutionary perspective, inter-individual variation in host-associated microbiota contributes to physiological and immune system variation. As such, host-associated microbiota may be considered an integral part of the host’s phenotype, serving as a substrate for natural selection. This assumes that host-associated microbiota exhibits high temporal stability, however, and that its composition is shaped by trans-generational transfer or heritable host-associated microbiota modulators encoded by the host genome. Although this concept is widely accepted, its crucial assumptions have rarely been tested in wild vertebrate populations. We performed 16S rRNA metabarcoding on an extensive set of fecal microbiota (FM) samples from an insectivorous, long-distance migratory bird, the barn swallow (Hirundo rustica). Our data revealed clear differences in FM among juveniles and adults as regards taxonomic and functional composition, diversity and co-occurrence network complexity. Multiple FM samples from the same juvenile or adult collected within single breeding seasons exhibited higher similarity than expected by chance, as did adult FM samples over two consecutive years. Despite low effect sizes for FM stability over time at the community level, we identified an adult FM subset with relative abundances exhibiting significant temporal consistency, possibly inducing long-term effects on the host phenotype. Our data also indicate a slight maternal (but not paternal) effect on FM composition in social offspring, though this is unlikely to persist into adulthood. We discuss our findings in the context of both evolution and ecology of microbiota vs. host interactions and barn swallow biology.

Rhea: a transparent and modular R pipeline for microbial profiling based on 16S rRNA gene amplicons

The importance of 16S rRNA gene amplicon profiles for understanding the influence of microbes in a variety of environments coupled with the steep reduction in sequencing costs led to a surge of microbial sequencing projects. The expanding crowd of scientists and clinicians wanting to make use of sequencing datasets can choose among a range of multipurpose software platforms, the use of which can be intimidating for non-expert users. Among available pipeline options for high-throughput 16S rRNA gene analysis, the R programming language and software environment for statistical computing stands out for its power and increased flexibility, and the possibility to adhere to most recent best practices and to adjust to individual project needs. Here we present the Rhea pipeline, a set of R scripts that encode a series of well-documented choices for the downstream analysis of Operational Taxonomic Units (OTUs) tables, including normalization steps, alpha- and beta-diversity analysis, taxonomic composition, statistical comparisons, and calculation of correlations. Rhea is primarily a straightforward starting point for beginners, but can also be a framework for advanced users who can modify and expand the tool. As the community standards evolve, Rhea will adapt to always represent the current state-of-the-art in microbial profiles analysis in the clear and comprehensive way allowed by the R language. Rhea scripts and documentation are freely available at https://lagkouvardos.github.io/Rhea.

Identification of an Intestinal Microbiota Signature Associated With Severity of Irritable Bowel Syndrome

BACKGROUND & AIMS

We have limited knowledge about the association between the composition of the intestinal microbiota and clinical features of irritable bowel syndrome (IBS). We collected information on the fecal and mucosa-associated microbiota of patients with IBS and evaluated whether these were associated with symptoms.

METHODS

We collected fecal and mucosal samples from adult patients who met the Rome III criteria for IBS at a secondary/tertiary care outpatient clinics in Sweden, as well as from healthy subjects. The exploratory set comprised 149 subjects (110 with IBS and 39 healthy subjects); 232 fecal samples and 59 mucosal biopsy samples were collected and analyzed by 16S ribosomal RNA targeted pyrosequencing. The validation set comprised 46 subjects (29 with IBS and 17 healthy subjects); 46 fecal samples, but no mucosal samples, were collected and analyzed. For each subject, we measured exhaled H₂ and CH₄, oro-anal transit time, and the severity of psychological and gastrointestinal symptoms. Fecal methanogens were measured by quantitative polymerase chain reaction. Numerical ecology analyses and a machine learning procedure were used to analyze the data.

RESULTS

Fecal microbiota showed covariation with mucosal adherent microbiota. By using classic approaches, we found no differences in fecal microbiota abundance or composition between patients with IBS vs healthy patients. A machine learning procedure, a computational statistical technique, allowed us to reduce the 16S ribosomal RNA data complexity into a microbial signature for severe IBS, consisting of 90 bacterial operational taxonomic units. We confirmed the robustness of the intestinal microbial signature for severe IBS in the validation set. The signature was able to discriminate between patients with severe symptoms, patients with mild/moderate symptoms, and healthy subjects. By using this intestinal microbiota signature, we found IBS symptom severity to be associated negatively with microbial richness, exhaled CH₄, presence of methanogens, and enterotypes enriched with Clostridiales or Prevotella species. This microbiota signature could not be explained by differences in diet or use of medications.

CONCLUSIONS

In analyzing fecal and mucosal microbiota from patients with IBS and healthy individuals, we identified an intestinal microbiota profile that is associated with the severity of IBS symptoms.

TRIAL REGISTRATION NUMBER

NCT01252550.

Gut Microbiome and Inflammation: A Study of Diabetic Inflammasome-Knockout Mice

AIMS

Diabetes is a proinflammatory state, evidenced by increased pattern recognition receptors and the inflammasome (NOD-like receptor family pyrin domain (NLRP)) complex. Recent reports have elucidated the role of the gut microbiome in diabetes, but there is limited data on the gut microbiome in NLRP-KO mice and its effect on diabetes-induced inflammation.

METHODS

Gut microbiome composition and biomarkers of inflammation (IL-18, serum amyloid A) were assessed in streptozotocin- (STZ-) induced diabetic mice on a NLRP3-knockout (KO) background versus wild-type diabetic mice.

RESULTS

SAA and IL-18 levels were significantly elevated in diabetic mice (STZ) compared to control (WT) mice, and there was a significant attenuation of inflammation in diabetic NLRP3-KO mice (NLRP3-KO STZ) compared to control mice (p < 0.005). Principal coordinate analysis clearly separated controls, STZ, and NLRP3-KO STZ mice. Among the different phyla, there was a significant increase in the Firmicutes : Bacteroidetes ratio in the diabetic group compared to controls. When compared to the WT STZ group, the NLRP3-KO STZ group showed a significant decrease in the Firmicutes : Bacteroidetes ratio. Together, these findings indicate that interaction of the intestinal microbes with the innate immune system is a crucial factor that could modify diabetes and complications.

Brief Report: Dialister as a Microbial Marker of Disease Activity in Spondyloarthritis

OBJECTIVE

Dysbiosis of the intestinal microbiota has been widely established in inflammatory bowel disease (IBD). There is significant clinical and genetic overlap between spondyloarthritis (SpA) and IBD, and up to 50% of all patients with SpA exhibit microscopic signs of bowel inflammation, often bearing particular resemblance to early Crohn's disease, a subtype of IBD. This study was undertaken to assess the relationship between intestinal microbial composition, gut histology, and disease activity markers in SpA.

METHODS

Gene analysis by 16S ribosomal RNA amplicon sequencing was used to compare the microbial composition in ileal and colonic biopsy specimens from 27 patients with SpA (14 with microscopic bowel inflammation, 13 without) and 15 healthy control subjects (ileal samples from all 15 subjects and colonic samples from 6). Spearman's rank correlation tests were used to assess correlations of the microbial composition with disease activity measures.

RESULTS

The intestinal inflammation status (histologically normal versus acute or chronic inflammation) was strongly associated with the mucosal microbiota profile of patients with SpA. In inflamed biopsy tissue, the detected bacterial community composition clustered separately from that in noninflamed biopsy tissue (P < 0.05 by permutational multivariate analysis of variance, using hierarchical clustering on Bray-Curtis distances). Interestingly, abundance of the genus Dialister was found to be positively correlated with the Ankylosing Spondylitis Disease Activity Score (Spearman's rho = 0.62, false discovery rate-corrected q < 0.01). This finding was further supported by the low frequency of Dialister observed in noninflamed ileal and colonic biopsy tissue from patients with SpA and healthy controls.

CONCLUSION

These findings demonstrate a significant difference in the intestinal microbial composition in patients with SpA who have microscopic gut inflammation compared to those without microscopic gut inflammation. Moreover, Dialister may represent a potential microbial marker of disease activity in SpA.

Microbiome Changes during Tuberculosis and Antituberculous Therapy

The critical role of commensal microbiota in the human body has been increasingly recognized, and our understanding of its implications in human health and disease has expanded rapidly. The lower respiratory tract contains diverse communities of microbes known as lung microbiota, which are present in healthy individuals and in individuals with respiratory diseases. The dysbiosis of the airway microbiota in pulmonary tuberculosis (TB) may play a role in the pathophysiological processes associated with TB disease. Recent studies of the lung microbiome have pointed out changes in lung microbial communities associated with TB and other lung diseases and have also begun to elucidate the profound effects that antituberculous drug therapy can have on the human lung microbiome composition. In this review, the potential role of the human microbiome in TB pathogenesis and the changes in the human microbiome with Mycobacterium tuberculosis infection and TB therapy are presented and discussed.

Microbial succession in an inflated lunar/Mars analog habitat during a 30-day human occupation

BACKGROUND

For potential future human missions to the Moon or Mars and sustained presence in the International Space Station, a safe enclosed habitat environment for astronauts is required. Potential microbial contamination of closed habitats presents a risk for crewmembers due to reduced human immune response during long-term confinement. To make future habitat designs safer for crewmembers, lessons learned from characterizing analogous habitats is very critical. One of the key issues is that how human presence influences the accumulation of microorganisms in the closed habitat.

RESULTS

Molecular technologies, along with traditional microbiological methods, were utilized to catalog microbial succession during a 30-day human occupation of a simulated inflatable lunar/Mars habitat. Surface samples were collected at different time points to capture the complete spectrum of viable and potential opportunistic pathogenic bacterial population. Traditional cultivation, propidium monoazide (PMA)-quantitative polymerase chain reaction (qPCR), and adenosine triphosphate (ATP) assays were employed to estimate the cultivable, viable, and metabolically active microbial population, respectively. Next-generation sequencing was used to elucidate the microbial dynamics and community profiles at different locations of the habitat during varying time points. Statistical analyses confirm that occupation time has a strong influence on bacterial community profiles. The Day 0 samples (before human occupation) have a very different microbial diversity compared to the later three time points. Members of Proteobacteria (esp. Oxalobacteraceae and Caulobacteraceae) and Firmicutes (esp. Bacillaceae) were most abundant before human occupation (Day 0), while other members of Firmicutes (Clostridiales) and Actinobacteria (esp. Corynebacteriaceae) were abundant during the 30-day occupation. Treatment of samples with PMA (a DNA-intercalating dye for selective detection of viable microbial population) had a significant effect on the microbial diversity compared to non-PMA-treated samples.

CONCLUSIONS

Statistical analyses revealed a significant difference in community structure of samples over time, particularly of the bacteriomes existing before human occupation of the habitat (Day 0 sampling) and after occupation (Day 13, Day 20, and Day 30 samplings). Actinobacteria (mainly Corynebacteriaceae) and Firmicutes (mainly Clostridiales Incertae Sedis XI and Staphylococcaceae) were shown to increase over the occupation time period. The results of this study revealed a strong relationship between human presence and succession of microbial diversity in a closed habitat. Consequently, it is necessary to develop methods and tools for effective maintenance of a closed system to enable safe human habitation in enclosed environments on Earth and beyond.

Meta-omics in Inflammatory Bowel Disease Research: Applications, Challenges, and Guidelines

Meta-omics [metagenomics, metatranscriptomics, and metaproteomics] are rapidly expanding our knowledge of the gut microbiota in health and disease. These technologies are increasingly used in inflammatory bowel disease [IBD] research. Yet, meta-omics data analysis, interpretation, and among-study comparison remain challenging. In this review we discuss the role these techniques are playing in IBD research, highlighting their strengths and limitations. We give guidelines on proper sample collection and preparation methods, and on performing the analyses and interpreting the results, reporting available user-friendly tools and pipelines.

Weight gain in anorexia nervosa does not ameliorate the faecal microbiota, branched chain fatty acid profiles, and gastrointestinal complaints

The gut microbiota not only influences host metabolism but can also affect brain function and behaviour through the microbiota-gut-brain axis. To explore the potential role of the intestinal microbiota in anorexia nervosa (AN), we comprehensively investigated the faecal microbiota and short-chain fatty acids in these patients before (n = 55) and after weight gain (n = 44) in comparison to normal-weight participants (NW, n = 55) along with dietary intake and gastrointestinal complaints. We show profound microbial perturbations in AN patients as compared to NW participants, with higher levels of mucin-degraders and members of Clostridium clusters I, XI and XVIII and reduced levels of the butyrate-producing Roseburia spp. Branched-chain fatty acid concentrations, being markers for protein fermentation, were elevated. Distinct perturbations in microbial community compositions were observed for individual restrictive and binge/purging AN-subtypes. Upon weight gain, microbial richness increased, however perturbations in intestinal microbiota and short chain fatty acid profiles in addition to several gastrointestinal symptoms did not recover. These insights provide new leads to modulate the intestinal microbiota in order to improve the outcomes of the standard therapy.

Durable coexistence of donor and recipient strains after fecal microbiota transplantation

Fecal microbiota transplantation (FMT) has shown efficacy in treating recurrent Clostridium difficile infection and is increasingly being applied to other gastrointestinal disorders, yet the fate of native and introduced microbial strains remains largely unknown. To quantify the extent of donor microbiota colonization, we monitored strain populations in fecal samples from a recent FMT study on metabolic syndrome patients using single-nucleotide variants in metagenomes. We found extensive coexistence of donor and recipient strains, persisting 3 months after treatment. Colonization success was greater for conspecific strains than for new species, the latter falling within fluctuation levels observed in healthy individuals over a similar time frame. Furthermore, same-donor recipients displayed varying degrees of microbiota transfer, indicating individual patterns of microbiome resistance and donor-recipient compatibilities.

Diversity and Temporal Dynamics of the Epiphytic Bacterial Communities Associated with the Canopy-Forming Seaweed Cystoseira compressa (Esper) Gerloff and Nizamuddin

Canopy-forming seaweed species of the genus Cystoseira form diverse and productive habitats along temperate rocky coasts of the Mediterranean Sea. Despite numerous studies on the rich macrofauna and flora associated with Cystoseira spp., there is little knowledge about the epiphytic bacteria. We analyzed bacterial populations associated with canopies of Cystoseira compressa, over an annual vegetative cycle (May-October), and their relationships with the bacterial populations in the surrounding seawater, at intertidal rocky shores in Vasto (Chieti—Italy). The bacterial diversity was assessed using Illumina Miseq sequences of V1-V3 hypervariable regions of 16S rRNA gene. C. compressa bacterial community was dominated by sequences of Proteobacteria and Bacteroidetes, Verrucomicrobia, Actinobacteria, and Cyanobacteria especially of the Rhodobacteriaceae, Flavobacteriaceae, Sapropiraceae, Verrucomicrobiaceae, and Phyllobacteriaceae families. Seawater libraries were also dominated by Proteobacteria and Bacteroidetes sequences, especially of the Candidatus Pelagibacter (SAR11) and Rhodobacteriaceae families, but were shown to be clearly distinct from C. compressa libraries with only few species in common between the two habitats. We observed a clear successional pattern in the epiphytic bacteria of C. compressa over time. These variations were characterized by gradual addition of OTUs (Verrucomicrobia, Actinobacteria and SR1) to the community over a growing season, indicative of a temporal gradient, rather than a radical reorganization of the bacterial community. Moreover, we also found an increase in abundance over time of Rhodobacteraceae, comprising six potential pathogenic genera, Ruegeria, Nautella, Aquimarina, Loktanella, Saprospira, and Phaeobacter which seemed to be associated to aged thalli of C. compressa. These bacteria could have the potential to affect the health and ecology of the algae, suggesting the hypothesis of a possible, but still unexplored, role of the microbial communities in contributing to the extensive ongoing declines of populations of Cystoseira spp. in the Mediterranean Sea.

Gut Microbiota Linked to Sexual Preference and HIV Infection

The precise effects of HIV-1 on the gut microbiome are unclear. Initial cross-sectional studies provided contradictory associations between microbial richness and HIV serostatus and suggested shifts from Bacteroides to Prevotella predominance following HIV-1 infection, which have not been found in animal models or in studies matched for HIV-1 transmission groups. In two independent cohorts of HIV-1-infected subjects and HIV-1-negative controls in Barcelona (n = 156) and Stockholm (n = 84), men who have sex with men (MSM) predominantly belonged to the Prevotella-rich enterotype whereas most non-MSM subjects were enriched in Bacteroides, independently of HIV-1 status, and with only a limited contribution of diet effects. Moreover, MSM had a significantly richer and more diverse fecal microbiota than non-MSM individuals. After stratifying for sexual orientation, there was no solid evidence of an HIV-specific dysbiosis. However, HIV-1 infection remained consistently associated with reduced bacterial richness, the lowest bacterial richness being observed in subjects with a virological-immune discordant response to antiretroviral therapy. Our findings indicate that HIV gut microbiome studies must control for HIV risk factors and suggest interventions on gut bacterial richness as possible novel avenues to improve HIV-1-associated immune dysfunction.

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The fecal microbiota of gay men in Europe is systematically richer and has a distinct composition.

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HIV-1 infection is independently associated with reduced gut bacterial richness, more so in immune discordant subjects.

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Interventions to increase gut bacterial richness might offer novel avenues to improve HIV-1-associated immune dysfunction.

The human intestinal microbiota is essential for human health and well-being and is driven by genetic, lifestyle and environmental factors. Here, we show in two independent cohorts of HIV-1-infected subjects and HIV-1-negative controls in Europe that gay men often have a distinct composition of the human fecal microbiota, with increased microbial richness and diversity and enrichment in the Prevotella enterotype. This is independent of HIV-1 status, and with only a limited contribution of diet effects. After accounting for sexual orientation, however, HIV-1 infection remains associated to reduced bacterial richness, more so in subjects with suboptimal CD4 + T-cell count recovery under antiretroviral therapy. Future studies should evaluate if interventions to increase gut bacterial richness could improve HIV-associated immune dysfunction.

NINJA-OPS: Fast Accurate Marker Gene Alignment Using Concatenated Ribosomes

The explosion of bioinformatics technologies in the form of next generation sequencing (NGS) has facilitated a massive influx of genomics data in the form of short reads. Short read mapping is therefore a fundamental component of next generation sequencing pipelines which routinely match these short reads against reference genomes for contig assembly. However, such techniques have seldom been applied to microbial marker gene sequencing studies, which have mostly relied on novel heuristic approaches. We propose NINJA Is Not Just Another OTU-Picking Solution (NINJA-OPS, or NINJA for short), a fast and highly accurate novel method enabling reference-based marker gene matching (picking Operational Taxonomic Units, or OTUs). NINJA takes advantage of the Burrows-Wheeler (BW) alignment using an artificial reference chromosome composed of concatenated reference sequences, the “concatesome,” as the BW input. Other features include automatic support for paired-end reads with arbitrary insert sizes. NINJA is also free and open source and implements several pre-filtering methods that elicit substantial speedup when coupled with existing tools. We applied NINJA to several published microbiome studies, obtaining accuracy similar to or better than previous reference-based OTU-picking methods while achieving an order of magnitude or more speedup and using a fraction of the memory footprint. NINJA is a complete pipeline that takes a FASTA-formatted input file and outputs a QIIME-formatted taxonomy-annotated BIOM file for an entire MiSeq run of human gut microbiome 16S genes in under 10 minutes on a dual-core laptop.

The analysis of the microbial communities in and around us is a growing field of study, partly because of its major implications for human health, and partly because high-throughput DNA sequencing technology has only recently emerged to enable us to quantitatively study them. One of the most fundamental steps in analyzing these microbial communities is matching the microbial marker genes in environmental samples with existing databases to determine which microbes are present. The current techniques for doing this analysis are either slow or closed-source. We present an alternative technique that takes advantage of a high-speed Burrows-Wheeler alignment procedure combined with rapid filtering and parsing of the data to remove bottlenecks in the pipeline. We achieve an order-of-magnitude speedup over conventional techniques without sacrificing accuracy or memory use, and in some cases improving both significantly. Thus our method allows more biologists to process their own sequencing data without specialized computing resources, and it obtains more accurate and even optimal taxonomic annotation for their marker gene sequencing data.

Visualizing Patterns of Marine Eukaryotic Diversity from Metabarcoding Data Using QIIME

PCR amplification followed by deep sequencing of homologous gene regions is increasingly used to characterize the diversity and taxonomic composition of marine eukaryotic communities. This approach may generate millions of sequences for hundreds of samples simultaneously. Therefore, tools that researchers can use to visualize complex patterns of diversity for these massive datasets are essential. Efforts by microbiologists to understand the Earth and human microbiomes using high-throughput sequencing of the 16S rRNA gene has led to the development of several user-friendly, open-source software packages that can be similarly used to analyze eukaryotic datasets. Quantitative Insights Into Microbial Ecology (QIIME) offers some of the most helpful data visualization tools. Here, we describe functionalities to import OTU tables generated with any molecular marker (e.g., 18S, COI, ITS) and associated metadata into QIIME. We then present a range of analytical tools implemented within QIIME that can be used to obtain insights about patterns of alpha and beta diversity for marine eukaryotes.