Taxonomic precision of different hypervariable regions of 16S rRNA gene and annotation methods for functional bacterial groups in biological wastewater treatment

The Gut Microbiome in the NOD Mouse

The microbiome (or microbiota) are an ecological community of commensal, symbiotic, and pathogenic microorganisms that outnumber the cells of the human body tenfold. These microorganisms are most abundant in the gut where they play an important role in health and disease. Alteration of the homeostasis of the gut microbiota can have beneficial or harmful consequences to health. There has recently been a major increase in studies on the association of the gut microbiome composition with disease phenotypes.The nonobese diabetic (NOD) mouse is an excellent mouse model to study spontaneous type 1 diabetes development. We, and others, have reported that gut bacteria are critical modulators for type 1 diabetes development in genetically susceptible NOD mice.Here we present our standard protocol for gut microbiome analysis in NOD mice that has been routinely implemented in our research laboratory. This incorporates the following steps: (1) Isolation of total DNA from gut bacteria from mouse fecal samples or intestinal contents; (2) bacterial DNA sequencing, and (3) basic data analysis.

Microbial Community Analysis with Ribosomal Gene Fragments from Shotgun Metagenomes

Shotgun metagenomic sequencing does not depend on gene-targeted primers or PCR amplification; thus, it is not affected by primer bias or chimeras. However, searching rRNA genes from large shotgun Illumina data sets is computationally expensive, and no approach exists for unsupervised community analysis of small-subunit (SSU) rRNA gene fragments retrieved from shotgun data. We present a pipeline, SSUsearch, to achieve the faster identification of short-subunit rRNA gene fragments and enabled unsupervised community analysis with shotgun data. It also includes classification and copy number correction, and the output can be used by traditional amplicon analysis platforms. Shotgun metagenome data using this pipeline yielded higher diversity estimates than amplicon data but retained the grouping of samples in ordination analyses. We applied this pipeline to soil samples with paired shotgun and amplicon data and confirmed bias against Verrucomicrobia in a commonly used V6-V8 primer set, as well as discovering likely bias against Actinobacteria and for Verrucomicrobia in a commonly used V4 primer set. This pipeline can utilize all variable regions in SSU rRNA and also can be applied to large-subunit (LSU) rRNA genes for confirmation of community structure. The pipeline can scale to handle large amounts of soil metagenomic data (5 Gb memory and 5 central processing unit hours to process 38 Gb [1 lane] of trimmed Illumina HiSeq2500 data) and is freely available at https://github.com/dib-lab/SSUsearch under a BSD license.

Human microbiomes and their roles in dysbiosis, common diseases, and novel therapeutic approaches

The human body is the residence of a large number of commensal (non-pathogenic) and pathogenic microbial species that have co-evolved with the human genome, adaptive immune system, and diet. With recent advances in DNA-based technologies, we initiated the exploration of bacterial gene functions and their role in human health. The main goal of the human microbiome project is to characterize the abundance, diversity and functionality of the genes present in all microorganisms that permanently live in different sites of the human body. The gut microbiota expresses over 3.3 million bacterial genes, while the human genome expresses only 20 thousand genes. Microbe gene-products exert pivotal functions via the regulation of food digestion and immune system development. Studies are confirming that manipulation of non-pathogenic bacterial strains in the host can stimulate the recovery of the immune response to pathogenic bacteria causing diseases. Different approaches, including the use of nutraceutics (prebiotics and probiotics) as well as phages engineered with CRISPR/Cas systems and quorum sensing systems have been developed as new therapies for controlling dysbiosis (alterations in microbial community) and common diseases (e.g., diabetes and obesity). The designing and production of pharmaceuticals based on our own body’s microbiome is an emerging field and is rapidly growing to be fully explored in the near future. This review provides an outlook on recent findings on the human microbiomes, their impact on health and diseases, and on the development of targeted therapies.

Next-generation sequencing (NGS) for assessment of microbial water quality: current progress, challenges, and future opportunities

Water quality is an emergent property of a complex system comprised of interacting microbial populations and introduced microbial and chemical contaminants. Studies leveraging next-generation sequencing (NGS) technologies are providing new insights into the ecology of microbially mediated processes that influence fresh water quality such as algal blooms, contaminant biodegradation, and pathogen dissemination. In addition, sequencing methods targeting small subunit (SSU) rRNA hypervariable regions have allowed identification of signature microbial species that serve as bioindicators for sewage contamination in these environments. Beyond amplicon sequencing, metagenomic and metatranscriptomic analyses of microbial communities in fresh water environments reveal the genetic capabilities and interplay of waterborne microorganisms, shedding light on the mechanisms for production and biodegradation of toxins and other contaminants. This review discusses the challenges and benefits of applying NGS-based methods to water quality research and assessment. We will consider the suitability and biases inherent in the application of NGS as a screening tool for assessment of biological risks and discuss the potential and limitations for direct quantitative interpretation of NGS data. Secondly, we will examine case studies from recent literature where NGS based methods have been applied to topics in water quality assessment, including development of bioindicators for sewage pollution and microbial source tracking, characterizing the distribution of toxin and antibiotic resistance genes in water samples, and investigating mechanisms of biodegradation of harmful pollutants that threaten water quality. Finally, we provide a short review of emerging NGS platforms and their potential applications to the next generation of water quality assessment tools.

Composition and Diversity of the Fecal Microbiome and Inferred Fecal Metagenome Does Not Predict Subsequent Pneumonia Caused by Rhodococcus equi in Foals

In equids, susceptibility to disease caused by Rhodococcus equi occurs almost exclusively in foals. This distribution might be attributable to the age-dependent maturation of immunity following birth undergone by mammalian neonates that renders them especially susceptible to infectious diseases. Expansion and diversification of the neonatal microbiome contribute to development of immunity in the gut. Moreover, diminished diversity of the gastrointestinal microbiome has been associated with risk of infections and immune dysregulation. We thus hypothesized that varying composition or reduced diversity of the intestinal microbiome of neonatal foals would contribute to increased susceptibility of their developing R. equi pneumonia. The composition and diversity indices of the fecal microbiota at 3 and 5 weeks of age were compared among 3 groups of foals: 1) foals that subsequently developed R. equi pneumonia after sampling; 2) foals that subsequently developed ultrasonographic evidence of pulmonary abscess formation or consolidation but not clinical signs (subclinical group); and, 3) foals that developed neither clinical signs nor ultrasonographic evidence of pulmonary abscess formation or consolidation. No significant differences were found among groups at either sampling time, indicating absence of evidence of an influence of composition or diversity of the fecal microbiome, or predicted fecal metagenome, on susceptibility to subsequent R. equi pneumonia. A marked and significant difference identified between a relatively short interval of time appeared to reflect ongoing adaptation to transition from a milk diet to a diet including available forage (including hay) and access to concentrate fed to the mare.

Characterization of the Bacterial Community Naturally Present on Commercially Grown Basil Leaves: Evaluation of Sample Preparation Prior to Culture-Independent Techniques

Fresh herbs such as basil constitute an important food commodity worldwide. Basil provides considerable culinary and health benefits, but has also been implicated in foodborne illnesses. The naturally occurring bacterial community on basil leaves is currently unknown, so the epiphytic bacterial community was investigated using the culture-independent techniques denaturing gradient gel electrophoresis (DGGE) and next-generation sequencing (NGS). Sample preparation had a major influence on the results from DGGE and NGS: Novosphingobium was the dominant genus for three different basil batches obtained by maceration of basil leaves, while washing of the leaves yielded lower numbers but more variable dominant bacterial genera including Klebsiella, Pantoea, Flavobacterium, Sphingobacterium and Pseudomonas. During storage of basil, bacterial growth and shifts in the bacterial community were observed with DGGE and NGS. Spoilage was not associated with specific bacterial groups and presumably caused by physiological tissue deterioration and visual defects, rather than by bacterial growth.

Back to Basics--The Influence of DNA Extraction and Primer Choice on Phylogenetic Analysis of Activated Sludge Communities

DNA extraction and primer choice have a large effect on the observed community structure in all microbial amplicon sequencing analyses. Although the biases are well known, no comprehensive analysis has been conducted in activated sludge communities. In this study we systematically explored the impact of a number of parameters on the observed microbial community: bead beating intensity, primer choice, extracellular DNA removal, and various PCR settings. In total, 176 samples were subjected to 16S rRNA amplicon sequencing, and selected samples were investigated through metagenomics and metatranscriptomics. Quantitative fluorescence in situ hybridization was used as a DNA extraction-independent method for qualitative comparison. In general, an effect on the observed community was found on all parameters tested, although bead beating and primer choice had the largest effect. The effect of bead beating intensity correlated with cell-wall strength as seen by a large increase in DNA from Gram-positive bacteria (up to 400%). However, significant differences were present at lower phylogenetic levels within the same phylum, suggesting that additional factors are at play. The best primer set based on in silico analysis was found to underestimate a number of important bacterial groups. For 16S rRNA gene analysis in activated sludge we recommend using the FastDNA SPIN Kit for Soil with four times the normal bead beating and V1-3 primers.

Dominant and novel clades of Candidatus Accumulibacter phosphatis in 18 globally distributed full-scale wastewater treatment plants

Here we employed quantitative real-time PCR (qPCR) assays for polyphosphate kinase 1 (ppk1) and 16S rRNA genes to assess relative abundances of dominant clades of Candidatus Accumulibacter phosphatis (referred to Accumulibacter) in 18 globally distributed full-scale wastewater treatment plants (WWTPs) from six countries. Accumulibacter were not only detected in the 6 WWTPs performing biological phosphorus removal, but also inhabited in the other 11 WWTPs employing conventional activated sludge (AS) with abundances ranging from 0.02% to 7.0%. Among the AS samples, clades IIC and IID were found to be dominant among the five Accumulibacter clades. The relative abundance of each clade in the Accumulibacter lineage significantly correlated (p < 0.05) with the influent total phosphorus and chemical oxygen demand instead of geographical factors (e.g. latitude), which showed that the local wastewater characteristics and WWTPs configurations could be more significant to determine the proliferation of Accumulibacter clades in full-scale WWTPs rather than the geographical location. Moreover, two novel Accumulibacter clades (IIH and II-I) which had not been previously detected were discovered in two enhanced biological phosphorus removal (EBPR) WWTPs. The results deepened our understanding of the Accumulibacter diversity in environmental samples.

The microbiome of the human lower airways: a next generation sequencing perspective

For a long time, the human lower airways were considered a sterile environment where the presence of microorganisms, typically revealed by culturing, was interpreted as an abnormal health state. More recently, high-throughput sequencing-based studies have led to a shift in this perception towards the notion that even in healthy conditions the lower airways show either transient presence or even permanent colonization by microorganisms. However, challenges related to low biomass and contamination in samples still remain, and the composition, structure and dynamics of such putative microbial communities are unclear. Here, we review the evidence for the presence of microbial communities in the human lower airways, in healthy subjects and within the context of medical conditions of interest. We also provide an overview of the methodology pertinent to high-throughput sequencing studies, specifically those based on amplicon sequencing, including a discussion of good practices and common pitfalls.

Estimating bacterial diversity for ecological studies: methods, metrics, and assumptions

Methods to estimate microbial diversity have developed rapidly in an effort to understand the distribution and diversity of microorganisms in natural environments. For bacterial communities, the 16S rRNA gene is the phylogenetic marker gene of choice, but most studies select only a specific region of the 16S rRNA to estimate bacterial diversity. Whereas biases derived from from DNA extraction, primer choice and PCR amplification are well documented, we here address how the choice of variable region can influence a wide range of standard ecological metrics, such as species richness, phylogenetic diversity, β-diversity and rank-abundance distributions. We have used Illumina paired-end sequencing to estimate the bacterial diversity of 20 natural lakes across Switzerland derived from three trimmed variable 16S rRNA regions (V3, V4, V5). Species richness, phylogenetic diversity, community composition, β-diversity, and rank-abundance distributions differed significantly between 16S rRNA regions. Overall, patterns of diversity quantified by the V3 and V5 regions were more similar to one another than those assessed by the V4 region. Similar results were obtained when analyzing the datasets with different sequence similarity thresholds used during sequences clustering and when the same analysis was used on a reference dataset of sequences from the Greengenes database. In addition we also measured species richness from the same lake samples using ARISA Fingerprinting, but did not find a strong relationship between species richness estimated by Illumina and ARISA. We conclude that the selection of 16S rRNA region significantly influences the estimation of bacterial diversity and species distributions and that caution is warranted when comparing data from different variable regions as well as when using different sequencing techniques.

Thermophiles in the genomic era: Biodiversity, science, and applications

Thermophiles and hyperthermophiles are present in various regions of the Earth, including volcanic environments, hot springs, mud pots, fumaroles, geysers, coastal thermal springs, and even deep-sea hydrothermal vents. They are also found in man-made environments, such as heated compost facilities, reactors, and spray dryers. Thermophiles, hyperthermophiles, and their bioproducts facilitate various industrial, agricultural, and medicinal applications and offer potential solutions to environmental damages and the demand for biofuels. Intensified efforts to sequence the entire genome of hyperthermophiles and thermophiles are increasing rapidly, as evidenced by the fact that over 120 complete genome sequences of the hyperthermophiles Aquificae, Thermotogae, Crenarchaeota, and Euryarchaeota are now available. In this review, we summarise the major current applications of thermophiles and thermozymes. In addition, emphasis is placed on recent progress in understanding the biodiversity, genomes, transcriptomes, metagenomes, and single-cell sequencing of thermophiles in the genomic era.

High-resolution taxonomic profiling of the subgingival microbiome for biomarker discovery and periodontitis diagnosis

The oral microbiome plays a key role for caries, periodontitis, and systemic diseases. A method for rapid, high-resolution, robust taxonomic profiling of subgingival bacterial communities for early detection of periodontitis biomarkers would therefore be a useful tool for individualized medicine. Here, we used Illumina sequencing of the V1-V2 and V5-V6 hypervariable regions of the 16S rRNA gene. A sample stratification pipeline was developed in a pilot study of 19 individuals, 9 of whom had been diagnosed with chronic periodontitis. Five hundred twenty-three operational taxonomic units (OTUs) were obtained from the V1-V2 region and 432 from the V5-V6 region. Key periodontal pathogens like Porphyromonas gingivalis, Treponema denticola, and Tannerella forsythia could be identified at the species level with both primer sets. Principal coordinate analysis identified two outliers that were consistently independent of the hypervariable region and method of DNA extraction used. The linear discriminant analysis (LDA) effect size algorithm (LEfSe) identified 80 OTU-level biomarkers of periodontitis and 17 of health. Health- and periodontitis-related clusters of OTUs were identified using a connectivity analysis, and the results confirmed previous studies with several thousands of samples. A machine learning algorithm was developed which was trained on all but one sample and then predicted the diagnosis of the left-out sample (jackknife method). Using a combination of the 10 best biomarkers, 15 of 17 samples were correctly diagnosed. Training the algorithm on time-resolved community profiles might provide a highly sensitive tool to detect the onset of periodontitis.

Bacterial assembly and temporal dynamics in activated sludge of a full-scale municipal wastewater treatment plant

Understanding environmental and biological influences on the dynamics of microbial communities has received great attention in microbial ecology. Here, utilizing large time-series 16S rRNA gene data, we show that in activated sludge of an environmentally important municipal wastewater treatment plant, 5-year temporal dynamics of bacterial community shows no significant seasonal succession, but is consistent with deterministic assemblage by taxonomic relatedness. Biological interactions are dominant drivers in determining the bacterial community assembly, whereas environmental conditions (mainly sludge retention time and inorganic nitrogen) partially explain phylogenetic and quantitative variances and indirectly influence bacterial assembly. We demonstrate a correlation-based statistical method to integrate bacterial association networks with their taxonomic affiliations to predict community-wide co-occurrence and co-exclusion patterns. The results show that although taxonomically closely related bacteria tend to positively co-occur (for example, out of a cooperative relationship), negative co-excluding correlations are deterministically observed between taxonomically less related species, probably implicating roles of competition in determining bacterial assembly. Overall, disclosures of the positive and negative species-species relations will improve our understanding of ecological niches occupied by unknown species and help to predict their biological functions in ecosystems.

Taxonomic and functional profiles of soil samples from Atlantic forest and Caatinga biomes in northeastern Brazil

Although microorganisms play crucial roles in ecosystems, metagenomic analyses of soil samples are quite scarce, especially in the Southern Hemisphere. In this work, the microbial diversity of soil samples from an Atlantic Forest and Caatinga was analyzed using a metagenomic approach. Proteobacteria and Actinobacteria were the dominant phyla in both samples. Among which, a significant proportion of stress-resistant bacteria associated to organic matter degradation was found. Sequences related to metabolism of amino acids, nitrogen, and DNA and stress resistance were more frequent in Caatinga soil, while the forest sample showed the highest occurrence of hits annotated in phosphorous metabolism, defense mechanisms, and aromatic compound degradation subsystems. The principal component analysis (PCA) showed that our samples are close to the desert metagenomes in relation to taxonomy, but are more similar to rhizosphere microbiota in relation to the functional profiles. The data indicate that soil characteristics affect the taxonomic and functional distribution; these characteristics include low nutrient content, high drainage (both are sandy soils), vegetation, and exposure to stress. In both samples, a rapid turnover of organic matter with low greenhouse gas emission was suggested by the functional profiles obtained, reinforcing the importance of preserving natural areas.