Toward Accurate and Quantitative Comparative Metagenomics

Cultivation of common bacterial species and strains from human skin, oral, and gut microbiota

BACKGROUND

Genomics-driven discoveries of microbial species have provided extraordinary insights into the biodiversity of human microbiota. In addition, a significant portion of genetic variation between microbiota exists at the subspecies, or strain, level. High-resolution genomics to investigate species- and strain-level diversity and mechanistic studies, however, rely on the availability of individual microbes from a complex microbial consortia. High-throughput approaches are needed to acquire and identify the significant species- and strain-level diversity present in the oral, skin, and gut microbiome. Here, we describe and validate a streamlined workflow for cultivating dominant bacterial species and strains from the skin, oral, and gut microbiota, informed by metagenomic sequencing, mass spectrometry, and strain profiling.

RESULTS

Of total genera discovered by either metagenomic sequencing or culturomics, our cultivation pipeline recovered between 18.1-44.4% of total genera identified. These represented a high proportion of the community composition reconstructed with metagenomic sequencing, ranging from 66.2-95.8% of the relative abundance of the overall community. Fourier-Transform Infrared spectroscopy (FT-IR) was effective in differentiating genetically distinct strains compared with whole-genome sequencing, but was less effective as a proxy for genetic distance.

CONCLUSIONS

Use of a streamlined set of conditions selected for cultivation of skin, oral, and gut microbiota facilitates recovery of dominant microbes and their strain variants from a relatively large sample set. FT-IR spectroscopy allows rapid differentiation of strain variants, but these differences are limited in recapitulating genetic distance. Our data highlights the strength of our cultivation and characterization pipeline, which is in throughput, comparisons with high-resolution genomic data, and rapid identification of strain variation.

Performance of Multiple Metagenomics Pipelines in Understanding Microbial Diversity of a Low-Biomass Spacecraft Assembly Facility

NASA planetary protection (PP) requires an assessment of the biological contamination of the potential microbial burden on spacecraft destined to explore planetary bodies that may harbor signs of life, like Mars and Europa. To help meet these goals, the performance of multiple metagenomic pipelines were compared and assessed for their ability to detect microbial diversity of a low-biomass clean room environment used to build spacecraft destined to these planetary bodies. Four vendors were chosen to implement their own metagenomic analysis pipeline on the shotgun sequences retrieved from environmental surfaces in the relevant environments at NASA's Jet Propulsion Laboratory. None of the vendors showed the same microbial profile patterns when analyzing same raw dataset since each vendor used different pipelines, which begs the question of the validity of a single pipeline to be recommended for future NASA missions. All four vendors detected species of interest, including spore-forming and extremotolerant bacteria, that have the potential to hitch-hike on spacecraft and contaminate the planetary bodies explored. Some vendors demonstrated through functional analysis of the metagenomes that the molecular mechanisms for spore-formation and extremotolerance were represented in the data. However, relative abundances of these microorganisms varied drastically between vendor analyses, questioning the ability of these pipelines to quantify the number of PP-relevant microorganisms on a spacecraft surface. Metagenomics offers tantalizing access to the genetic and functional potential of a microbial community that may offer NASA a viable method for microbial burden assays for planetary protection purposes. However, future development of technologies such as streamlining the processing of shotgun metagenome sequence data, long read sequencing, and all-inclusive larger curated and annotated microbial genome databases will be required to validate and translate relative abundances into an actionable assessment of PP-related microbes of interest. Additionally, the future development of machine learning and artificial intelligence techniques could help enhance the quality of these metagenomic analyses by providing more accurate identification of the genetic and functional potential of a microbial community.

Exploring Semi-Quantitative Metagenomic Studies Using Oxford Nanopore Sequencing: A Computational and Experimental Protocol

The gut microbiome plays a major role in chronic diseases, of which several are characterized by an altered composition and diversity of bacterial communities. Large-scale sequencing projects allowed for characterizing the perturbations of these communities. However, translating these discoveries into clinical applications remains a challenge. To facilitate routine implementation of microbiome profiling in clinical settings, portable, real-time, and low-cost sequencing technologies are needed. Here, we propose a computational and experimental protocol for whole-genome semi-quantitative metagenomic studies of human gut microbiome with Oxford Nanopore sequencing technology (ONT) that could be applied to other microbial ecosystems. We developed a bioinformatics protocol to analyze ONT sequences taxonomically and functionally and optimized preanalytic protocols, including stool collection and DNA extraction methods to maximize read length. This is a critical parameter for the sequence alignment and classification. Our protocol was evaluated using simulations of metagenomic communities, which reflect naturally occurring compositional variations. Next, we validated both protocols using stool samples from a bariatric surgery cohort, sequenced with ONT, Illumina, and SOLiD technologies. Results revealed similar diversity and microbial composition profiles. This protocol can be implemented in a clinical or research setting, bringing rapid personalized whole-genome profiling of target microbiome species.

High-Throughput Single-Cell Technology Reveals the Contribution of Horizontal Gene Transfer to Typical Antibiotic Resistance Gene Dissemination in Wastewater Treatment Plants

The spread of antibiotic resistance genes (ARGs) has gained much attention worldwide, while the contribution of vertical gene transfer (VGT) and horizontal gene transfer (HGT) is still elusive. Here, we improved an emerging high-throughput single-cell-based technology, emulsion, paired isolation, and concatenation polymerase chain reaction (epicPCR), by lengthening the sequence of ARG in the fused ARG-16S rRNA fragments to cover the variance of both ARG and its hosts. The improved epicPCR was applied to track the hosts of a widely detected ARG, sul1 gene, in five urban wastewater treatment plants (UWTPs) during two seasons. The sul1 host bacteria were highly diverse and mostly classified as Proteobacteria and Bacteroidetes. Clear seasonal divergence of α-diversity and interaction networks were present in the host community. The consensus phylogenetic trees of the sul1 gene and their host demonstrated incorrespondence on the whole and regularity on abundant groups, suggesting the important role of both HGT and VGT, respectively. The relative importance of these two ways was further measured; HGT (54%) generally played an equal or even more important role as VGT (46%) in UWTPs. The application of the improved epicPCR technology provides a feasible approach to quantify the relative contributions of VGT and HGT in environmental dissemination of ARGs.

Meta-analysis of Clinical Microbiome Studies in Urolithiasis Reveal Age, Stone Composition, and Study Location as the Predominant Factors in Urolithiasis-Associated Microbiome Composition

To determine whether functionally relevant questions associated with the urinary or gut microbiome and urinary stone disease (USD) can be answered from metagenome-wide association studies (MWAS), we performed the most comprehensive meta-analysis of published clinical MWAS in USD to date, using publicly available data published prior to April 2021. Six relevant studies met inclusion criteria. For alpha-diversity, significant differences were noted between USD status, stone composition, sample type, study location, age, diet, and sex. For beta-diversity, significant differences were noted by USD status, stone composition, sample type, study location, antibiotic use (30 days and 12 months before sampling), sex, hypertension, water intake, body habitus, and age. Prevotella and Lactobacillus in the gut and urinary tract, respectively, were associated with healthy individuals, while Enterobacteriaceae was associated with USD in the urine and stones. Paradoxically, other Prevotella strains were also strongly associated with USD in the gut microbiome. When data were analyzed together, USD status, stone composition, age group, and study location were the predominant factors associated with microbiome composition. Meta-analysis showed significant microbiome differences based on USD status, stone composition, age group or study location. However, analyses were limited by a lack of public data from published studies, metadata collected, and differing study protocols. Results highlight the need for field-specific standardization of experimental protocols in terms of sample collection procedures and the anatomical niches to assess, as well as in defining clinically relevant metadata and subphenotypes such as stone composition.

Gulf of Mexico blue hole harbors high levels of novel microbial lineages

Exploration of oxygen-depleted marine environments has consistently revealed novel microbial taxa and metabolic capabilities that expand our understanding of microbial evolution and ecology. Marine blue holes are shallow karst formations characterized by low oxygen and high organic matter content. They are logistically challenging to sample, and thus our understanding of their biogeochemistry and microbial ecology is limited. We present a metagenomic and geochemical characterization of Amberjack Hole on the Florida continental shelf (Gulf of Mexico). Dissolved oxygen became depleted at the hole's rim (32 m water depth), remained low but detectable in an intermediate hypoxic zone (40-75 m), and then increased to a secondary peak before falling below detection in the bottom layer (80-110 m), concomitant with increases in nutrients, dissolved iron, and a series of sequentially more reduced sulfur species. Microbial communities in the bottom layer contained heretofore undocumented levels of the recently discovered phylum Woesearchaeota (up to 58% of the community), along with lineages in the bacterial Candidate Phyla Radiation (CPR). Thirty-one high-quality metagenome-assembled genomes (MAGs) showed extensive biochemical capabilities for sulfur and nitrogen cycling, as well as for resisting and respiring arsenic. One uncharacterized gene associated with a CPR lineage differentiated hypoxic from anoxic zone communities. Overall, microbial communities and geochemical profiles were stable across two sampling dates in the spring and fall of 2019. The blue hole habitat is a natural marine laboratory that provides opportunities for sampling taxa with under-characterized but potentially important roles in redox-stratified microbial processes.

A large-scale metagenomic study for enzyme profiles using the focused identification of the NGS-based definitive enzyme research (FINDER) strategy

Excavating the molecular details of many diverse enzymes from metagenomes remains challenging in agriculture, food, health, and environmental fields. We present a versatile method that accelerates metabolic enzyme discovery for highly selective gene capture in metagenomes using next-generation sequencing. Culture-independent enzyme mining of environmental DNA is based on a set of short identifying degenerate sequences specific for a wide range of enzyme superfamilies, followed by multiplexed DNA barcode sequencing. A strategy of 'focused identification of next-generation sequencing-based definitive enzyme research' enabled us to generate targeted enzyme datasets from metagenomes, resulting in minimal hands-on obtention of high-throughput biological diversity and potential function profiles, without being time-consuming. This method also provided a targeted inventory of predicted proteins and molecular features of metabolic activities from several metagenomic samples. We suggest that the efficiency and sensitivity of this method will accelerate the decryption of microbial diversity and the signature of proteins and their metabolism from environmental samples.

Microbiome signatures of progression toward celiac disease onset in at-risk children in a longitudinal prospective cohort study

Other than exposure to gluten and genetic compatibility, the gut microbiome has been suggested to be involved in celiac disease (CD) pathogenesis by mediating interactions between gluten/environmental factors and the host immune system. However, to establish disease progression markers, it is essential to assess alterations in the gut microbiota before disease onset. Here, a prospective metagenomic analysis of the gut microbiota of infants at risk of CD was done to track shifts in the microbiota before CD development. We performed cross-sectional and longitudinal analyses of gut microbiota, functional pathways, and metabolites, starting from 18 mo before CD onset, in 10 infants who developed CD and 10 matched nonaffected infants. Cross-sectional analysis at CD onset identified altered abundance of six microbial strains and several metabolites between cases and controls but no change in microbial species or pathway abundance. Conversely, results of longitudinal analysis revealed several microbial species/strains/pathways/metabolites occurring in increased abundance and detected before CD onset. These had previously been linked to autoimmune and inflammatory conditions (e.g., Dialister invisus, Parabacteroides sp., Lachnospiraceae, tryptophan metabolism, and metabolites serine and threonine). Others occurred in decreased abundance before CD onset and are known to have anti-inflammatory effects (e.g., Streptococcus thermophilus, Faecalibacterium prausnitzii, and Clostridium clostridioforme). Additionally, we uncovered previously unreported microbes/pathways/metabolites (e.g., Porphyromonas sp., high mannose-type N-glycan biosynthesis, and serine) that point to CD-specific biomarkers. Our study establishes a road map for prospective longitudinal study designs to better understand the role of gut microbiota in disease pathogenesis and therapeutic targets to reestablish tolerance and/or prevent autoimmunity.

Strategies for Natural Products Discovery from Uncultured Microorganisms

Microorganisms are highly regarded as a prominent source of natural products that have significant importance in many fields such as medicine, farming, environmental safety, and material production. Due to this, only tiny amounts of microorganisms can be cultivated under standard laboratory conditions, and the bulk of microorganisms in the ecosystems are still unidentified, which restricts our knowledge of uncultured microbial metabolism. However, they could hypothetically provide a large collection of innovative natural products. Culture-independent metagenomics study has the ability to address core questions in the potential of NP production by cloning and analysis of microbial DNA derived directly from environmental samples. Latest advancements in next generation sequencing and genetic engineering tools for genome assembly have broadened the scope of metagenomics to offer perspectives into the life of uncultured microorganisms. In this review, we cover the methods of metagenomic library construction, and heterologous expression for the exploration and development of the environmental metabolome and focus on the function-based metagenomics, sequencing-based metagenomics, and single-cell metagenomics of uncultured microorganisms.

Standardization of microbiome studies for urolithiasis: an international consensus agreement

Numerous metagenome-wide association studies (MWAS) for urolithiasis have been published, leading to the discovery of potential interactions between the microbiome and urolithiasis. However, questions remain about the reproducibility, applicability and physiological relevance of these data owing to discrepancies in experimental technique and a lack of standardization in the field. One barrier to interpreting MWAS is that experimental biases can be introduced at every step of the experimental pipeline, including sample collection, preservation, storage, processing, sequencing, data analysis and validation. Thus, the introduction of standardized protocols that maintain the flexibility to achieve study-specific objectives is urgently required. To address this need, the first international consortium for microbiome in urinary stone disease - MICROCOSM - was created and consensus panel members were asked to participate in a consensus meeting to develop standardized protocols for microbiome studies if they had published an MWAS on urolithiasis. Study-specific protocols were revised until a consensus was reached. This consensus group generated standardized protocols, which are publicly available via a secure online server, for each step in the typical clinical microbiome-urolithiasis study pipeline. This standardization creates the benchmark for future studies to facilitate consistent interpretation of results and, collectively, to lead to effective interventions to prevent the onset of urolithiasis, and will also be useful for investigators interested in microbiome research in other urological diseases.

Next generation sequencing approaches to evaluate water and wastewater quality

The emergence of next generation sequencing (NGS) is revolutionizing the potential to address complex microbiological challenges in the water industry. NGS technologies can provide holistic insight into microbial communities and their functional capacities in water and wastewater systems, thus eliminating the need to develop a new assay for each target organism or gene. However, several barriers have hampered wide-scale adoption of NGS by the water industry, including cost, need for specialized expertise and equipment, challenges with data analysis and interpretation, lack of standardized methods, and the rapid pace of development of new technologies. In this critical review, we provide an overview of the current state of the science of NGS technologies as they apply to water, wastewater, and recycled water. In addition, a systematic literature review was conducted in which we identified over 600 peer-reviewed journal articles on this topic and summarized their contributions to six key areas relevant to the water and wastewater fields: taxonomic classification and pathogen detection, functional and catabolic gene characterization, antimicrobial resistance (AMR) profiling, bacterial toxicity characterization, Cyanobacteria and harmful algal bloom identification, and virus characterization. For each application, we have presented key trends, noteworthy advancements, and proposed future directions. Finally, key needs to advance NGS technologies for broader application in water and wastewater fields are assessed.

Parasites, niche modification and the host microbiome: A field survey of multiple parasites

Parasites can affect and be affected by the host's microbiome, with consequences for host susceptibility, parasite transmission, and host and parasite fitness. Yet, two aspects of the relationship between parasite infection and host microbiota remain little understood: the nature of the relationship under field conditions, and how the relationship varies among parasites. To overcome these limitations, we performed a field survey of the within-leaf fungal community in a tall fescue population. We investigated how diversity and composition of the fungal microbiome associate with natural infection by fungal parasites with different feeding strategies. A parasite's feeding strategy affects both parasite requirements of the host environment and parasite impacts on the host environment. We hypothesized that parasites that more strongly modify niches available within a host will be associated with greater changes in microbiome diversity and composition. Parasites with a feeding strategy that creates necrotic tissue to extract resources (necrotrophs) may not only have different niche requirements, but also act as particularly strong niche modifiers. Barcoded amplicon sequencing of the fungal ITS region revealed that leaf segments symptomatic of necrotrophs had lower fungal diversity and distinct composition compared to segments that were asymptomatic or symptomatic of other parasites. There were no clear differences in fungal diversity or composition between leaf segments that were asymptomatic and segments symptomatic of other parasite feeding strategies. Our results motivate future experimental work to test how the relationship between the microbiome and parasite infection is impacted by parasite feeding strategy and highlight the potential importance of parasite traits.

Toward Accurate and Robust Environmental Surveillance Using Metagenomics

Environmental surveillance is a critical tool for combatting public health threats represented by the global COVID-19 pandemic and the continuous increase of antibiotic resistance in pathogens. With its power to detect entire microbial communities, metagenomics-based methods stand out in addressing the need. However, several hurdles remain to be overcome in order to generate actionable interpretations from metagenomic sequencing data for infection prevention. Conceptually and technically, we focus on viability assessment, taxonomic resolution, and quantitative metagenomics, and discuss their current advancements, necessary precautions and directions to further development. We highlight the importance of building solid conceptual frameworks and identifying rational limits to facilitate the application of techniques. We also propose the usage of internal standards as a promising approach to overcome analytical bottlenecks introduced by low biomass samples and the inherent lack of quantitation in metagenomics. Taken together, we hope this perspective will contribute to bringing accurate and consistent metagenomics-based environmental surveillance to the ground.

COVID-19 Crisis Creates Opportunity towards Global Monitoring & Surveillance

The spectrum of emerging new diseases as well as re-emerging old diseases is broadening as infectious agents evolve, adapt, and spread at enormous speeds in response to changing ecosystems. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a recent phenomenon and may take a while to understand its transmission routes from less traveled territories, ranging from fomite exposure routes to wastewater transmission. The critical challenge is how to negotiate with such catastrophic pandemics in high-income countries (HICs ~20% of the global population) and low-and middle-income countries (LMICs ~ 80% of the global population) with a total global population size of approximately eight billion, where practical mass testing and tracing is only a remote possibility, particularly in low-and middle-income countries (LMICs). Keeping in mind the population distribution disparities of high-income countries (HICs) and LMICs and urbanisation trends over recent years, traditional wastewater-based surveillance such as that used to combat polio may help in addressing this challenge. The COVID-19 era differs from any previous pandemics or global health challenges in the sense that there is a great deal of curiosity within the global community to find out everything about this virus, ranging from diagnostics, potential vaccines/therapeutics, and possible routes of transmission. In this regard, the fact that the gut is the common niche for both poliovirus and SARS-CoV-2, and due to the shedding of the virus through faecal material into sewerage systems, the need for long-term wastewater surveillance and developing early warning systems for better preparedness at local and global levels is increasingly apparent. This paper aims to provide an insight into the ongoing COVID-19 crisis, how it can be managed, and what measures are required to deal with a current global international public health concern. Additionally, it shed light on the importance of using wastewater surveillance strategy as an early warning practical tool suitable for massive passive screening, as well as the urgent need for microfluidic technology as a rapid and cost-effective approach tracking SARS-CoV-2 in wastewater.

An Expanded Gene Catalog of Mouse Gut Metagenomes

High-quality and comprehensive reference gene catalogs are essential for metagenomic research. The rather low diversity of samples used to construct existing catalogs of the mouse gut metagenome limits the numbers of identified genes in existing catalogs. We therefore established an expanded catalog of genes in the mouse gut metagenome (EMGC) containing >5.8 million genes by integrating 88 newly sequenced samples, 86 mouse gut-related bacterial genomes, and 3 existing gene catalogs. EMGC increases the number of nonredundant genes by more than 1 million genes compared to the so-far most extensive catalog. More than 60% of the genes in EMGC were assigned to Bacteria, with 54.20% being assigned to a phylum and 35.33% to a genus, while 30.39% were annotated at the KEGG orthology level. Nine hundred two metagenomic species (MGS) assigned to 122 taxa are identified based on the EMGC. The EMGC-based analysis of samples from groups of mice originating from different animal providers, housing laboratories, and genetic strains substantiated that diet is a major contributor to differences in composition and functional potential of the gut microbiota irrespective of differences in environment and genetic background. We envisage that EMGC will serve as a valuable reference data set for future metagenomic studies in mice.

IMPORTANCE We established an expanded gene catalog of the mouse gut metagenome not only to increase the sample size compared to that in existing catalogs but also to provide a more comprehensive reference data set of the mouse gut microbiome for bioinformatic analysis. The expanded gene catalog comprises more than 5.8 million unique genes, as well as a wide range of taxonomic and functional information. Particularly, the analysis of metagenomic species with the expanded gene catalog reveals a great novelty of mouse gut-inhabiting microbial species. We envisage that the expanded gene catalog of the mouse gut metagenome will serve as a valuable bioinformatic resource for future gut metagenomic studies in mice.

Monitoring the microbiome for food safety and quality using deep shotgun sequencing

In this work, we hypothesized that shifts in the food microbiome can be used as an indicator of unexpected contaminants or environmental changes. To test this hypothesis, we sequenced the total RNA of 31 high protein powder (HPP) samples of poultry meal pet food ingredients. We developed a microbiome analysis pipeline employing a key eukaryotic matrix filtering step that improved microbe detection specificity to >99.96% during in silico validation. The pipeline identified 119 microbial genera per HPP sample on average with 65 genera present in all samples. The most abundant of these were Bacteroides, Clostridium, Lactococcus, Aeromonas, and Citrobacter. We also observed shifts in the microbial community corresponding to ingredient composition differences. When comparing culture-based results for Salmonella with total RNA sequencing, we found that Salmonella growth did not correlate with multiple sequence analyses. We conclude that microbiome sequencing is useful to characterize complex food microbial communities, while additional work is required for predicting specific species' viability from total RNA sequencing.

Information Theoretic Metagenome Assembly Allows the Discovery of Disease Biomarkers in Human Microbiome

Quantitative metagenomics is an important field that has delivered successful microbiome biomarkers associated with host phenotypes. The current convention mainly depends on unsupervised assembly of metagenomic contigs with a possibility of leaving interesting genetic material unassembled. Additionally, biomarkers are commonly defined on the differential relative abundance of compositional or functional units. Accumulating evidence supports that microbial genetic variations are as important as the differential abundance content, implying the need for novel methods accounting for the genetic variations in metagenomics studies. We propose an information theoretic metagenome assembly algorithm, discovering genomic fragments with maximal self-information, defined by the empirical distributions of nucleotides across the phenotypes and quantified with the help of statistical tests. Our algorithm infers fragments populating the most informative genetic variants in a single contig, named supervariant fragments. Experiments on simulated metagenomes, as well as on a colorectal cancer and an atherosclerotic cardiovascular disease dataset consistently discovered sequences strongly associated with the disease phenotypes. Moreover, the discriminatory power of these putative biomarkers was mainly attributed to the genetic variations rather than relative abundance. Our results support that a focus on metagenomics methods considering microbiome population genetics might be useful in discovering disease biomarkers with a great potential of translating to molecular diagnostics and biotherapeutics applications.

Predicting drug-metagenome interactions: Variation in the microbial β-glucuronidase level in the human gut metagenomes

Characterizing the gut microbiota in terms of their capacity to interfere with drug metabolism is necessary to achieve drug efficacy and safety. Although examples of drug-microbiome interactions are well-documented, little has been reported about a computational pipeline for systematically identifying and characterizing bacterial enzymes that process particular classes of drugs. The goal of our study is to develop a computational approach that compiles drugs whose metabolism may be influenced by a particular class of microbial enzymes and that quantifies the variability in the collective level of those enzymes among individuals. The present paper describes this approach, with microbial β-glucuronidases as an example, which break down drug-glucuronide conjugates and reactivate the drugs or their metabolites. We identified 100 medications that may be metabolized by β-glucuronidases from the gut microbiome. These medications included morphine, estrogen, ibuprofen, midazolam, and their structural analogues. The analysis of metagenomic data available through the Sequence Read Archive (SRA) showed that the level of β-glucuronidase in the gut metagenomes was higher in males than in females, which provides a potential explanation for the sex-based differences in efficacy and toxicity for several drugs, reported in previous studies. Our analysis also showed that infant gut metagenomes at birth and 12 months of age have higher levels of β-glucuronidase than the metagenomes of their mothers and the implication of this observed variability was discussed in the context of breastfeeding as well as infant hyperbilirubinemia. Overall, despite important limitations discussed in this paper, our analysis provided useful insights on the role of the human gut metagenome in the variability in drug response among individuals. Importantly, this approach exploits drug and metagenome data available in public databases as well as open-source cheminformatics and bioinformatics tools to predict drug-metagenome interactions.

Comprehensive insights into arsenic- and iron-redox genes, their taxonomy and associated environmental drivers deciphered by a meta-analysis

In nature, arsenic (As) and iron (Fe) biotransformation are interconnected, influencing local As mobility and toxicity. While As- or Fe-metabolizing microorganisms are widely documented, knowledge concerning their cycling genes, associated with geophysicochemical data and taxonomic distribution, remains scarce. We performed a meta-analysis to explore the distribution and environmental importance of As- and Fe-redox genes (AsRGs and FeRGs) and predict their significant correlations and hosts. The most abundant and ubiquitous AsRGs and FeRGs were arsC and ccoN, respectively. The ccoN gene had the highest frequency at pH ≥ 9.1, in which dissolved Fe(II) is scarce, possibly contributing to enhanced host survival. Fe(III) oxidation genes iro and ccoN appear to be associated with As(V) detoxification in mesophilic environments. No correlation was observed between Fe(III) reduction gene omcB and arsenate reductase genes. Cytochromes with putative roles in Fe-redox reactions were identified (including yceJ and fbcH) and were significantly correlated with As(V) reduction genes under diverse geophysicochemical conditions. The taxonomies of AsRGs and FeRGs-carrying contigs revealed great diversity, among which various, such as Chlamydea (arsC) and Firmicutes (omcB), were previously undescribed. Nearly all (98.9%) of the AsRGs and FeRGs were not carried by any plasmid sequences. This meta-analysis expands our understanding of the global environmental, taxonomic and functional microbiome involved in As- and Fe-redox transformations. Moreover, these findings should help guide studies on putative in vivo functional roles of cytochromes in Fe-redox pathways.

Increasing Reproducibility in Oral Microbiome Research

Evidence on the role of the oral microbiome in health and disease is changing the way we understand, diagnose, and treat ailments. Numerous studies on diseases affecting the oral cavity have revealed a large amount of data that is invaluable for the advancements in diagnosing and treating these diseases. However, the clinical translation of most of these exploratory data is stalled by variable methodology between studies and non-uniform reporting of the data.Understanding the key areas that are gateways to bias in microbiome studies is imperative to overcome this challenge faced by oral microbiome research. Bias can be multifactorial and may be introduced in a microbiome research study during the formulation of the study design, sample collection and storage, or the sample processing protocols before sequencing. This chapter summarizes the recommendations from literature to eliminate bias in the microbiome research studies and to ensure the reproducibility of the microbiome research data.

Revisiting Plant-Microbe Interactions and Microbial Consortia Application for Enhancing Sustainable Agriculture: A Review

The present scenario of agricultural sector is dependent hugely on the use of chemical-based fertilizers and pesticides that impact the nutritional quality, health status, and productivity of the crops. Moreover, continuous release of these chemical inputs causes toxic compounds such as metals to accumulate in the soil and move to the plants with prolonged exposure, which ultimately impact the human health. Hence, it becomes necessary to bring out the alternatives to chemical pesticides/fertilizers for improvement of agricultural outputs. The rhizosphere of plant is an important niche with abundant microorganisms residing in it. They possess the properties of plant growth promotion, disease suppression, removal of toxic compounds, and assimilating nutrients to plants. Utilizing such beneficial microbes for crop productivity presents an efficient way to modulate the crop yield and productivity by maintaining healthy status and quality of the plants through bioformulations. To understand these microbial formulation compositions, it becomes essential to understand the processes going on in the rhizosphere as well as their concrete identification for better utilization of the microbial diversity such as plant growth–promoting bacteria and arbuscular mycorrhizal fungi. Hence, with this background, the present review article highlights the plant microbiome aboveground and belowground, importance of microbial inoculants in various plant species, and their subsequent interactive mechanisms for sustainable agriculture.

Comparative viromes of Culicoides and mosquitoes reveal their consistency and diversity in viral profiles

The genus Culicoides includes biting midges, some of which are vectors for viruses that cause diseases in humans and animals. Knowledge of the roles of Culicoides in viral ecology is inadequate. We collected ~300 000 samples of Culicoides and mosquitoes in 15 representative regions within Yunnan, China. Using mosquitoes as reference vectors, we designed a comparative virome strategy to study the viral composition, diversity, hosts and spatiotemporal distribution of Culicoides. A map of viromes in Culicoides and mosquitoes in Yunan province, China, was constructed. At the same locations, Culicoides and mosquitoes usually share a similar viral diversity. At least 10 important pathogenic viruses were detected from Culicoides. Many novel viruses were discovered, including 21 segmented viruses of Flaviviridae, 180 viruses of Monjiviricetes and 130 viruses of Bunyavirales. The findings demonstrate that Culicoides is an important part of viral ecology and should be studied and monitored for potentially emerging viruses.

A novel 3D in vitro model of the human gut microbiota

Clinical trials and animal studies on the gut microbiota are often limited by the difficult access to the gut, restricted possibility of in vivo monitoring, and ethical issues. An easily accessible and monitorable in vitro model of the gut microbiota represents a valid tool for a wider comprehension of the mechanisms by which microbes interact with the host and with each other. Herein, we present a novel and reliable system for culturing the human gut microbiota in vitro. An electrospun gelatin structure was biofabricated as scaffold for microbial growth. The efficiency of this structure in supporting microbial proliferation and biofilm formation was initially assessed for five microbes commonly inhabiting the human gut. The human fecal microbiota was then cultured on the scaffolds and microbial biofilms monitored by confocal laser and scanning electron microscopy and quantified over time. Metagenomic analyses and Real-Time qPCRs were performed to evaluate the stability of the cultured microbiota in terms of qualitative and quantitative composition. Our results reveal the three-dimensionality of the scaffold-adhered microbial consortia that maintain the bacterial biodiversity and richness found in the original sample. These findings demonstrate the validity of the developed electrospun gelatin-based system for in vitro culturing the human gut microbiota.

Measuring the microbiome: Best practices for developing and benchmarking microbiomics methods

Microbiomes are integral components of diverse ecosystems, and increasingly recognized for their roles in the health of humans, animals, plants, and other hosts. Given their complexity (both in composition and function), the effective study of microbiomes (microbiomics) relies on the development, optimization, and validation of computational methods for analyzing microbial datasets, such as from marker-gene (e.g., 16S rRNA gene) and metagenome data. This review describes best practices for benchmarking and implementing computational methods (and software) for studying microbiomes, with particular focus on unique characteristics of microbiomes and microbiomics data that should be taken into account when designing and testing microbiomics methods.

Human Gut Microbiome-Based Knowledgebase as a Biomarker Screening Tool to Improve the Predicted Probability for Colorectal Cancer

Colorectal cancer (CRC) is a common clinical malignancy globally ranked as the fourth leading cause of cancer mortality. Some microbes are known to contribute to adenoma-carcinoma transition and possess diagnostic potential. Advances in high-throughput sequencing technology and functional studies have provided significant insights into the landscape of the gut microbiome and the fundamental roles of its components in carcinogenesis. Integration of scattered knowledge is highly beneficial for future progress. In this study, literature review and information extraction were performed, with the aim of integrating the available data resources and facilitating comparative research. A knowledgebase of the human CRC microbiome was compiled to facilitate understanding of diagnosis, and the global signatures of CRC microbes, sample types, algorithms, differential microorganisms and various panels of markers plus their diagnostic performance were evaluated based on statistical and phylogenetic analyses. Additionally, prospects about current changelings and solution strategies were outlined for identifying future research directions. This type of data integration strategy presents an effective platform for inquiry and comparison of relevant information, providing a tool for further study about CRC-related microbes and exploration of factors promoting clinical transformation (available at: http://gsbios.com/index/experimental/dts_ mben?id=1).

Assessing the Risk of Transfer of Microorganisms at the International Space Station Due to Cargo Delivery by Commercial Resupply Vehicles

BACKGROUND

With increasing numbers of interplanetary missions, there is a need to establish robust protocols to ensure the protection of extraterrestrial planets being visited from contamination by terrestrial life forms. The current study is the first report comparing the commercial resupply vehicle (CRV) microbiome with the International Space Station (ISS) microbiome to understand the risks of contamination, thus serving as a model system for future planetary missions.

RESULTS

Samples obtained from the internal surfaces and ground support equipment of three CRV missions were subjected to various molecular techniques for microbial diversity analysis. In total, 25 samples were collected with eight defined locations from each CRV mission prior to launch. In general, the internal surfaces of vehicles were clean, with an order of magnitude fewer microbes compared to ground support equipment. The first CRV mission had a larger microbial population than subsequent CRV missions, which were clean as compared to the initial CRV locations sampled. Cultivation assays showed the presence of Actinobacteria, Proteobacteria, Firmicutes, and Bacteroidetes and members of Ascomycota and Basidiomycota. As expected, shotgun metagenome analyses revealed the presence of more microbial taxa compared to cultivation-based assays. The internal locations of the CRV microbiome reportedly showed the presence of microorganisms capable of tolerating ultraviolet radiation (e.g., Bacillus firmus) and clustered separately from the ISS microbiome.

CONCLUSIONS

The metagenome sequence comparison of the CRV microbiome with the ISS microbiome revealed significant differences showing that CRV microbiomes were a negligible part of the ISS environmental microbiome. These findings suggest that the maintenance protocols in cleaning CRV surfaces are highly effective in controlling the contaminating microbial population during cargo transfer to the ISS via the CRV route.

Integration of metagenomics-metabolomics reveals specific signatures and functions of airway microbiota in mite-sensitized childhood asthma

BACKGROUND

Childhood asthma is a multifactorial inflammatory condition of the airways, associated with specific changes in respiratory microbiome and circulating metabolome.

METHODS

To explore the functional capacity of asthmatic microbiome and its intricate connection with the host, we performed shotgun sequencing of airway microbiome and untargeted metabolomics profiling of serum samples in a cohort of children with mite-sensitized asthma and non-asthmatic controls.

RESULTS

We observed higher gene counts and sample-to-sample dissimilarities in asthmatic microbiomes, indicating a more heterogeneous community structure and functionality among the cases than in controls. Moreover, we identified airway microbial species linked to changes in circulating metabolites and IgE responses of the host, including a positive correlation between Prevotella sp oral taxon 306 and dimethylglycine that were both decreased in patients. Several control-enriched species (Eubacterium sulci, Prevotella pallens, and Prevotella sp oral taxon 306) were inversely correlated with total and allergen-specific IgE levels. Genes related to microbial carbohydrate, amino acid, and lipid metabolism were differentially enriched, suggesting that changes in microbial metabolism may contribute to respiratory health in asthmatics. Pathway modules relevant to allergic responses were differentially abundant in asthmatic microbiome, such as enrichments for biofilm formation by Pseudomonas aeruginosa, membrane trafficking, histidine metabolism, and glycosaminoglycan degradation, and depletions for polycyclic aromatic hydrocarbon degradation. Further, we identified metagenomic and metabolomic markers (eg, Eubacterium sulci) to discriminate cases from the non-asthmatic controls.

CONCLUSIONS

Our dual-omics data reveal the connections between respiratory microbes and circulating metabolites perturbed in mite-sensitized pediatric asthma, which may be of etiological and diagnostic implications.

When the Sum of the Parts Tells You More Than the Whole: The Advantage of Using Metagenomics to Characterize Bartonella spp. Infections in Norway Rats (Rattus norvegicus) and Their Fleas

Urban Norway rats (Rattus norvegicus) are a reservoir for Bartonella spp. - a genus of zoonotic bacteria transmitted by hematophagous vectors, particularly fleas. Rats and fleas may be infected with more than one Bartonella species; however, mixed infections may be difficult to detect using culture and/or mono-locus PCR. We set out to characterize Bartonella spp. using gltA PCR and Sanger sequencing on blood (n = 480) and Nosopsyllus fasciatus flea pools (n = 200) obtained from a population of urban Norways rats from Vancouver, Canada. However, when contamination of a subset of flea pools necessitated the use of a second target (ssrA) and the results of gltA and ssrA were discordant, a metagenomic approach was used to better characterize the Bartonella spp. present in these samples and our objective transitioned to comparing data obtained via metagenomics to those from PCR/sequencing. Among the Bartonella spp.-positive rats (n = 95), 52 (55.3%), and 41 (43.6%) had Sanger sequences consistent with Bartonella tribocorum and Bartonella vinsonii, respectively. One rat had a mixed infection. All sequences from Bartonella spp.-positive flea pools (n = 85), were consistent with B. tribocorum, and re-analysis of 34 bloods of varying Bartonella spp. infection status (based gltA PCR and sequencing) using ssrA PCR showed that the assay was capable of identifying B. tribocorum but not B. vinsonii. Metagenomics analysis of a subset of PCR-positive blood samples (n = 70) and flea pools (n = 24) revealed that both B. tribocorum and B. vinsonii were circulating widely in the study population with 31/70 (44.3%) rats and 5/24 (2.1%) flea pools infected with both species. B. vinsonii, however, made up a smaller relative proportion of the reads for samples with mixed infections, which may be why it was generally not detected by genus-specific PCR and Sanger sequencing. Further analysis of 16S−23S ITS sequences amplified from a subset of samples identified the B. vinsonii strain as B. vinsonii subsp. berkhoffii type II. This demonstrates the value of a metagenomic approach for better characterizing the ecology and health risks associated with this bacterium, particularly given that the less dominant species, B. vinsonii is associated with greater pathogenicity in people.

Seasonal Regime Shift in the Viral Communities of a Permafrost Thaw Lake

Permafrost thaw lakes including thermokarst lakes and ponds are ubiquitous features of Subarctic and Arctic landscapes and are hotspots of microbial activity. Input of terrestrial organic matter into the planktonic microbial loop of these lakes may greatly amplify global greenhouse gas emissions. This microbial loop, dominated in the summer by aerobic microorganisms including phototrophs, is radically different in the winter, when metabolic processes shift to the anaerobic degradation of organic matter. Little is known about the viruses that infect these microbes, despite evidence that viruses can control microbial populations and influence biogeochemical cycling in other systems. Here, we present the results of a metagenomics-based study of viruses in the larger than 0.22 µm fraction across two seasons (summer and winter) in a permafrost thaw lake in Subarctic Canada. We uncovered 351 viral populations (vOTUs) in the surface waters of this lake, with diversity significantly greater during the summer. We also identified and characterized several phage genomes and prophages, which were mostly present in the summer. Finally, we compared the viral community of this waterbody to other habitats and found unexpected similarities with distant bog lakes in North America.

A quasi-paired cohort strategy reveals the impaired detoxifying function of microbes in the gut of autistic children

Growing evidence suggests that autism spectrum disorder (ASD) is strongly associated with dysbiosis in the gut microbiome, with the exact mechanisms still unclear. We have proposed a novel analytic strategy-quasi-paired cohort-and applied it to a metagenomic study of the ASD microbiome. By comparing paired samples of ASD and neurotypical subjects, we have identified significant deficiencies in ASD children in detoxifying enzymes and pathways, which show a strong correlation with biomarkers of mitochondrial dysfunction. Diagnostic models based on these detoxifying enzymes accurately distinguished ASD individuals from controls, and the dysfunction score inferred from the model increased with the clinical rating scores of ASD. In summary, our results suggest a previously undiscovered potential role of impaired intestinal microbial detoxification in toxin accumulation and mitochondrial dysfunction, a core component of ASD pathogenesis. These findings pave the way for designing future therapeutic strategies to restore microbial detoxification capabilities for patients with ASD.

Latitude and chlorophyll a density drive the distribution of carbohydrate-active enzymes in the planktonic microbial fraction of the epipelagic zone

Microbes drive the majority of the global carbon cycle. The effect of environmental conditions on selecting microbial functional diversity is well established, and recent studies have revealed the effects of geographic distances on selecting the functional components of marine microbial communities. Our study is the first attempt at establishing the effects of environmental factors on driving the marine carbohydrate-active enzyme (CAZyme) distribution. We characterized the diversity of CAZyme genes and investigated the correlations between their distributions and biogeographic parameters (latitude, longitude, distance from the equator, site depth, water depth, chlorophyll density, salinity and temperature). Therefore, we accessed a subset of surface water samples (38 metagenomes) from the Global Ocean Sampling project. Only chlorophyll and latitude altered the distribution patterns of CAZymes, revealing the existence of two latitudinal gradients (positive and negative) of marine CAZyme abundance. Considering the importance of carbohydrates in microbial life, characterization of the spatial patterns of the genetic repertoire involved in carbohydrate metabolism represents an important step in improving our understanding of the metabolic strategies associated with the microbial marine carbon cycle and their effects on the productivity of marine ecosystems.

A network approach to elucidate and prioritize microbial dark matter in microbial communities

Microbes compose most of the biomass on the planet, yet the majority of taxa remain uncharacterized. These unknown microbes, often referred to as “microbial dark matter,” represent a major challenge for biology. To understand the ecological contributions of these Unknown taxa, it is essential to first understand the relationship between unknown species, neighboring microbes, and their respective environment. Here, we establish a method to study the ecological significance of “microbial dark matter” by building microbial co-occurrence networks from publicly available 16S rRNA gene sequencing data of four extreme aquatic habitats. For each environment, we constructed networks including and excluding unknown organisms at multiple taxonomic levels and used network centrality measures to quantitatively compare networks. When the Unknown taxa were excluded from the networks, a significant reduction in degree and betweenness was observed for all environments. Strikingly, Unknown taxa occurred as top hubs in all environments, suggesting that “microbial dark matter” play necessary ecological roles within their respective communities. In addition, novel adaptation-related genes were detected after using 16S rRNA gene sequences from top-scoring hub taxa as probes to blast metagenome databases. This work demonstrates the broad applicability of network metrics to identify and prioritize key Unknown taxa and improve understanding of ecosystem structure across diverse habitats.

Compositional and functional differences of the mucosal microbiota along the intestine of healthy individuals

Gut mucosal microbes evolved closest to the host, developing specialized local communities. There is, however, insufficient knowledge of these communities as most studies have employed sequencing technologies to investigate faecal microbiota only. This work used shotgun metagenomics of mucosal biopsies to explore the microbial communities' compositions of terminal ileum and large intestine in 5 healthy individuals. Functional annotations and genome-scale metabolic modelling of selected species were then employed to identify local functional enrichments. While faecal metagenomics provided a good approximation of the average gut mucosal microbiome composition, mucosal biopsies allowed detecting the subtle variations of local microbial communities. Given their significant enrichment in the mucosal microbiota, we highlight the roles of Bacteroides species and describe the antimicrobial resistance biogeography along the intestine. We also detail which species, at which locations, are involved with the tryptophan/indole pathway, whose malfunctioning has been linked to pathologies including inflammatory bowel disease. Our study thus provides invaluable resources for investigating mechanisms connecting gut microbiota and host pathophysiology.

The Nubeam reference-free approach to analyze metagenomic sequencing reads

We present Nubeam (nucleotide be a matrix) as a novel reference-free approach to analyze short sequencing reads. Nubeam represents nucleotides by matrices, transforms a read into a product of matrices, and assigns numbers to reads based on the product matrix. Nubeam capitalizes on the noncommutative property of matrix multiplication, such that different reads are assigned different numbers and similar reads similar numbers. A sample, which is a collection of reads, becomes a collection of numbers that form an empirical distribution. We demonstrate that the genetic difference between samples can be quantified by the distance between empirical distributions. Nubeam includes the k-mer method as a special case, but unlike the k-mer method, it is convenient for Nubeam to account for GC bias and nucleotide quality. As a reference-free approach, Nubeam avoids reference bias and mapping bias, and can work with organisms without reference genomes. Thus, Nubeam is ideal to analyze data sets from metagenomics whole genome shotgun (WGS) sequencing, where the amount of unmapped reads is substantial. When applied to a WGS sequencing data set to quantify distances between metagenomics samples from various human body habitats, Nubeam recapitulates findings made by mapping-based methods and sheds light on contributions of unmapped reads. Nubeam is also useful in analyzing 16S rRNA sequencing data, which is a more prevalent type of data set in metagenomics studies. In our analysis, Nubeam recapitulated the findings that natural microbiota in mouse gut are resilient under challenges, and Nubeam detected differences in vaginal microbiota between cases of polycystic ovary syndrome and healthy controls.

Life at the Frozen Limit: Microbial Carbon Metabolism Across a Late Pleistocene Permafrost Chronosequence

Permafrost is an extreme habitat yet it hosts microbial populations that remain active over millennia. Using permafrost collected from a Pleistocene chronosequence (19 to 33 ka), we hypothesized that the functional genetic potential of microbial communities in permafrost would reflect microbial strategies to metabolize permafrost soluble organic matter (OM) in situ over geologic time. We also hypothesized that changes in the metagenome across the chronosequence would correlate with shifts in carbon chemistry, permafrost age, and paleoclimate at the time of permafrost formation. We combined high-resolution characterization of water-soluble OM by Fourier-transform ion-cyclotron-resonance mass spectrometry (FT-ICR MS), quantification of organic anions in permafrost water extracts, and metagenomic sequencing to better understand the relationships between the molecular-level composition of potentially bioavailable OM, the microbial community, and permafrost age. Both age and paleoclimate had marked effects on both the molecular composition of dissolved OM and the microbial community. The relative abundance of genes associated with hydrogenotrophic methanogenesis, carbohydrate active enzyme families, nominal oxidation state of carbon (NOSC), and number of identifiable molecular formulae significantly decreased with increasing age. In contrast, genes associated with fermentation of short chain fatty acids (SCFAs), the concentration of SCFAs and ammonium all significantly increased with age. We present a conceptual model of microbial metabolism in permafrost based on fermentation of OM and the buildup of organic acids that helps to explain the unique chemistry of ancient permafrost soils. These findings imply long-term in situ microbial turnover of ancient permafrost OM and that this pooled biolabile OM could prime ancient permafrost soils for a larger and more rapid microbial response to thaw compared to younger permafrost soils.

Microbiome and Metagenome Analyses of a Closed Habitat during Human Occupation

This study provides the first assessment of monitoring cultivable and viable microorganisms on surfaces within a submerged, closed, analog habitat. The results of the analyses presented herein suggest that the surface material plays a role in microbial community structure, as the microbial populations differed between LDP and metal/glass surfaces. The metal/glass surfaces had less-complex community, lower bioburden, and more closely resembled the controls. These results indicated that material choice is crucial when building closed habitats, even if they are simply analogs. Finally, while a few species were associated with previously cultivated isolates from the International Space Station and MIR spacecraft, the majority of the microbial ecology of the submerged analog habitat differs greatly from that of previously studied analog habitats.

Microbial contamination during long-term confinements of space exploration presents potential risks for both crew members and spacecraft life support systems. A novel swab kit was used to sample various surfaces from a submerged, closed, analog habitat to characterize the microbial populations. Samples were collected from various locations across the habitat which were constructed from various surface materials (linoleum, dry wall, particle board, glass, and metal), and microbial populations were examined by culture, quantitative PCR (qPCR), microbiome 16S rRNA gene sequencing, and shotgun metagenomics. Propidium monoazide (PMA)-treated samples identified the viable/intact microbial population of the habitat. The cultivable microbial population ranged from below the detection limit to 10⁶ CFU/sample, and their identity was characterized using Sanger sequencing. Both 16S rRNA amplicon and shotgun sequencing were used to characterize the microbial dynamics, community profiles, and functional attributes (metabolism, virulence, and antimicrobial resistance). The 16S rRNA amplicon sequencing revealed abundance of viable (after PMA treatment) Actinobacteria (Brevibacterium, Nesternkonia, Mycobacterium, Pseudonocardia, and Corynebacterium), Firmicutes (Virgibacillus, Staphylococcus, and Oceanobacillus), and Proteobacteria (especially Acinetobacter) on linoleum, dry wall, and particle board (LDP) surfaces, while members of Firmicutes (Leuconostocaceae) and Proteobacteria (Enterobacteriaceae) were high on the glass/metal surfaces. Nonmetric multidimensional scaling determined from both 16S rRNA and metagenomic analyses revealed differential microbial species on LDP surfaces and glass/metal surfaces. The shotgun metagenomic sequencing of samples after PMA treatment showed bacterial predominance of viable Brevibacterium (53.6%), Brachybacterium (7.8%), Pseudonocardia (9.9%), Mycobacterium (3.7%), and Staphylococcus (2.1%), while fungal analyses revealed Aspergillus and Penicillium dominance.

IMPORTANCE This study provides the first assessment of monitoring cultivable and viable microorganisms on surfaces within a submerged, closed, analog habitat. The results of the analyses presented herein suggest that the surface material plays a role in microbial community structure, as the microbial populations differed between LDP and metal/glass surfaces. The metal/glass surfaces had less-complex community, lower bioburden, and more closely resembled the controls. These results indicated that material choice is crucial when building closed habitats, even if they are simply analogs. Finally, while a few species were associated with previously cultivated isolates from the International Space Station and MIR spacecraft, the majority of the microbial ecology of the submerged analog habitat differs greatly from that of previously studied analog habitats.

A novel normalization and differential abundance test framework for microbiome data

MOTIVATION

Microbial communities have been proved to have close relationship with many diseases. The identification of differentially abundant microbial species is clinically meaningful for finding disease-related pathogenic or probiotic bacteria. However, certain characteristics of microbiome data have hurdled the accuracy and effectiveness of differential abundance analysis. The abundances or counts of microbiome species are usually on different scales and exhibit zero-inflation and over-dispersion. Normalization is a crucial step before the differential abundance test. However, existing normalization methods typically try to adjust counts on different scales to a common scale by constructing size factors with the assumption that count distributions across samples are equivalent up to a certain percentile. These methods often yield undesirable results when differentially abundant species are of low to medium abundance level. For differential abundance analysis, existing methods often use a single distribution to model the dispersion of species which lacks flexibility to catch a single species' distinctiveness. These methods tend to detect a lot of false positives and often lack of power when the effect size is small.

RESULTS

We develop a novel framework for differential abundance analysis on sparse high-dimensional marker gene microbiome data. Our methodology relies on a novel network-based normalization technique and a two-stage zero-inflated mixture count regression model (RioNorm2). Our normalization method aims to find a group of relatively invariant microbiome species across samples and conditions in order to construct the size factor. Another contribution of the paper is that our testing approach can take under-sampling and over-dispersion into consideration by separating microbiome species into two groups and model them separately. Through comprehensive simulation studies, the performance of our method is consistently powerful and robust across different settings with different sample size, library size and effect size. We also demonstrate the effectiveness of our novel framework using a published dataset of metastatic melanoma and find biological insights from the results.

AVAILABILITY AND IMPLEMENTATION

The R package 'RioNorm2' can be installed from Github athttps://github.com/yuanjing-ma/RioNorm2.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

ATLAS: a Snakemake workflow for assembly, annotation, and genomic binning of metagenome sequence data

BACKGROUND

Metagenomics studies provide valuable insight into the composition and function of microbial populations from diverse environments; however, the data processing pipelines that rely on mapping reads to gene catalogs or genome databases for cultured strains yield results that underrepresent the genes and functional potential of uncultured microbes. Recent improvements in sequence assembly methods have eased the reliance on genome databases, thereby allowing the recovery of genomes from uncultured microbes. However, configuring these tools, linking them with advanced binning and annotation tools, and maintaining provenance of the processing continues to be challenging for researchers.

RESULTS

Here we present ATLAS, a software package for customizable data processing from raw sequence reads to functional and taxonomic annotations using state-of-the-art tools to assemble, annotate, quantify, and bin metagenome data. Abundance estimates at genome resolution are provided for each sample in a dataset. ATLAS is written in Python and the workflow implemented in Snakemake; it operates in a Linux environment, and is compatible with Python 3.5+ and Anaconda 3+ versions. The source code for ATLAS is freely available, distributed under a BSD-3 license.

CONCLUSIONS

ATLAS provides a user-friendly, modular and customizable Snakemake workflow for metagenome data processing; it is easily installable with conda and maintained as open-source on GitHub at https://github.com/metagenome-atlas/atlas.

Global distribution of a chlorophyll f cyanobacterial marker

Some cyanobacteria use light outside the visible spectrum for oxygenic photosynthesis. The far-red light (FRL) region is made accessible through a complex acclimation process that involves the formation of new phycobilisomes and photosystems containing chlorophyll f. Diverse cyanobacteria ranging from unicellular to branched-filamentous forms show this response. These organisms have been isolated from shaded environments such as microbial mats, soil, rock, and stromatolites. However, the full spread of chlorophyll f-containing species in nature is still unknown. Currently, discovering new chlorophyll f cyanobacteria involves lengthy incubation times under selective far-red light. We have used a marker gene to detect chlorophyll f organisms in environmental samples and metagenomic data. This marker, apcE2, encodes a phycobilisome linker associated with FRL-photosynthesis. By focusing on a far-red motif within the sequence, degenerate PCR and BLAST searches can effectively discriminate against the normal chlorophyll a-associated apcE. Even short recovered sequences carry enough information for phylogenetic placement. Markers of chlorophyll f photosynthesis were found in metagenomic datasets from diverse environments around the globe, including cyanobacterial symbionts, hypersaline lakes, corals, and the Arctic/Antarctic regions. This additional information enabled higher phylogenetic resolution supporting the hypothesis that vertical descent, as opposed to horizontal gene transfer, is largely responsible for this phenotype’s distribution.

An optimized method for the extraction of ancient eukaryote DNA from marine sediments

Marine sedimentary ancient DNA (sedaDNA) provides a powerful means to reconstruct marine palaeo-communities across the food web. However, currently there are few optimized sedaDNA extraction protocols available to maximize the yield of small DNA fragments typical of ancient DNA (aDNA) across a broad diversity of eukaryotes. We compared seven combinations of sedaDNA extraction treatments and sequencing library preparations using marine sediments collected at a water depth of 104 m off Maria Island, Tasmania, in 2018. These seven methods contrasted frozen versus refrigerated sediment, bead-beating induced cell lysis versus ethylenediaminetetraacetic acid (EDTA) incubation, DNA binding in silica spin columns versus in silica-solution, diluted versus undiluted DNA in shotgun library preparations to test potential inhibition issues during amplification steps, and size-selection of low molecular-weight (LMW) DNA to increase the extraction efficiency of sedaDNA. Maximum efficiency was obtained from frozen sediments subjected to a combination of EDTA incubation and bead-beating, DNA binding in silica-solution, and undiluted DNA in shotgun libraries, across 45 marine eukaryotic taxa. We present an optimized extraction protocol integrating these steps, with an optional post-library LMW size-selection step to retain DNA fragments of ≤500 base pairs. We also describe a stringent bioinformatic filtering approach for metagenomic data and provide a comprehensive list of contaminants as a reference for future sedaDNA studies. The new extraction and data-processing protocol should improve quantitative paleo-monitoring of eukaryotes from marine sediments, as well as other studies relying on the detection of highly fragmented and degraded eukaryote DNA in sediments.

Crewmember microbiome may influence microbial composition of ISS habitable surfaces

The International Space Station (ISS) is a complex built environment physically isolated from Earth. Assessing the interplay between the microbial community of the ISS and its crew is important for preventing biomedical and structural complications for long term human spaceflight missions. In this study, we describe one crewmember’s microbial profile from body swabs of mouth, nose, ear, skin and saliva that were collected at eight different time points pre-, during and post-flight. Additionally, environmental surface samples from eight different habitable locations in the ISS were collected from two flights. Environmental samples from one flight were collected by the crewmember and samples from the next flight were collected after the crewmember departed. The microbial composition in both environment and crewmember samples was measured using shotgun metagenomic sequencing and processed using the Livermore Metagenomics Analysis Toolkit. Ordination of sample to sample distances showed that of the eight crew body sites analyzed, skin, nostril, and ear samples are more similar in microbial composition to the ISS surfaces than mouth and saliva samples; and that the microbial composition of the crewmember’s skin samples are more closely related to the ISS surface samples collected by the crewmember on the same flight than ISS surface samples collected by other crewmembers on different flights. In these collections, species alpha diversity in saliva samples appears to decrease during flight and rebound after returning to Earth. This is the first study to compare the ISS microbiome to a crewmember’s microbiome via shotgun metagenomic sequencing. We observed that the microbiome of the surfaces inside the ISS resemble those of the crew’s skin. These data support future crew and ISS microbial surveillance efforts and the design of preventive measures to maintain crew habitat onboard spacecraft destined for long term space travel.

Aeromonas hydrophila, Bacillus thuringiensis, Escherichia coli and Pseudomonas aeruginosa utilization of Ammonium-N, Nitrate-N and Urea-N in culture

Agricultural drainage ditches represent a major source of nutrient pollution. Shifts in nitrogen source and use of animal manures have changed the bacterial composition both in species of bacteria and their abundance in agricultural ditches. This change affects how nitrogen is being cycled and potentially the final forms of available nutrients. In particular, animal manures often have bacteria such as Escherichia coli present, increasing the abundance of a bacterial species in ditches. Research has shown that the effect of different nitrogen sources is to change bacterial community composition (class, family). How this influences the role of an individual bacterial species is poorly understood. Thus, our question was how individual species would respond to different sources of nitrogen. We used Aeromonas hydrophila, Bacillus thuringiensis, Escherichia coli and Pseudomonas aeruginosa that are common in agricultural ditches and exposed them to different concentrations of nitrogen in cultures of 1 × 10⁰ and 1 × 10⁻¹ dilutions from a stock solution of bacteria. Nitrogen sources were ammonium chloride, sodium nitrate and urea. The results showed A. hydrophila and E. coli have strong similarities particularly with nitrate-N and urea-N utilization and the response was often correlated with the amount of nutrient added. P. aeruginosa while similar did not show any strong correlation with amount of nutrient added. B. thuringiensis was different from the other three bacteria in utilization or production. Research has provided insight into the role of some bacteria in nitrogen cycling and may be valuable in the future to developing management strategies to reduce nutrients.

Integrative metagenomic and metabolomic analyses reveal severity-specific signatures of gut microbiota in chronic kidney disease

Chronic kidney disease (CKD) is a serious healthcare dilemma, associated with specific changes in gut microbiota and circulating metabolome. Yet, the functional capacity of CKD microbiome and its intricate relationship with the host metabolism at different stages of disease are less understood. Methods: Here, shotgun sequencing of fecal samples and targeted metabolomics profiling of serum bile acids, short- and medium-chain fatty acids, and uremic solutes were performed in a cohort of CKD patients with different severities and non-CKD controls. Results: We identified that levels of 13 microbial species and 6 circulating metabolites were significantly altered across early to advanced stages or only in particular stage(s). Among these, Prevotella sp. 885 (decreased) was associated with urea excretion, while caproic acid (decreased) and p-cresyl sulfate (elevated) were positively and negatively correlated with the glomerular filtration rate, respectively. In addition, we identified gut microbial species linked to changes in circulating metabolites. Microbial genes related to secondary bile acid biosynthesis were differentially abundant at the early stage, while pathway modules related to lipid metabolism and lipopolysaccharide biosynthesis were enriched in the CKD microbiome at the advanced stage, suggesting that changes in microbial metabolism and host inflammation may contribute to renal health. Further, we identified metagenomic and metabolomic markers to discriminate cases of different severities from the controls, among which Bacteroides eggerthii individually was of particular value in early diagnosis. Conclusions: Our dual-omics data reveal the connections between intestinal microbes and circulating metabolites perturbed in CKD, which may be of etiological and diagnostic importance.

What Is in Umbilicaria pustulata? A Metagenomic Approach to Reconstruct the Holo-Genome of a Lichen

Lichens are valuable models in symbiosis research and promising sources of biosynthetic genes for biotechnological applications. Most lichenized fungi grow slowly, resist aposymbiotic cultivation, and are poor candidates for experimentation. Obtaining contiguous, high-quality genomes for such symbiotic communities is technically challenging. Here, we present the first assembly of a lichen holo-genome from metagenomic whole-genome shotgun data comprising both PacBio long reads and Illumina short reads. The nuclear genomes of the two primary components of the lichen symbiosis-the fungus Umbilicaria pustulata (33 Mb) and the green alga Trebouxia sp. (53 Mb)-were assembled at contiguities comparable to single-species assemblies. The analysis of the read coverage pattern revealed a relative abundance of fungal to algal nuclei of ∼20:1. Gap-free, circular sequences for all organellar genomes were obtained. The bacterial community is dominated by Acidobacteriaceae and encompasses strains closely related to bacteria isolated from other lichens. Gene set analyses showed no evidence of horizontal gene transfer from algae or bacteria into the fungal genome. Our data suggest a lineage-specific loss of a putative gibberellin-20-oxidase in the fungus, a gene fusion in the fungal mitochondrion, and a relocation of an algal chloroplast gene to the algal nucleus. Major technical obstacles during reconstruction of the holo-genome were coverage differences among individual genomes surpassing three orders of magnitude. Moreover, we show that GC-rich inverted repeats paired with nonrandom sequencing error in PacBio data can result in missing gene predictions. This likely poses a general problem for genome assemblies based on long reads.

Complementary Metagenomic Approaches Improve Reconstruction of Microbial Diversity in a Forest Soil

Soil ecosystems harbor diverse microorganisms and yet remain only partially characterized as neither single-cell sequencing nor whole-community sequencing offers a complete picture of these complex communities. Thus, the genetic and metabolic potential of this "uncultivated majority" remains underexplored. To address these challenges, we applied a pooled-cell-sorting-based mini-metagenomics approach and compared the results to bulk metagenomics. Informatic binning of these data produced 200 mini-metagenome assembled genomes (sorted-MAGs) and 29 bulk metagenome assembled genomes (MAGs). The sorted and bulk MAGs increased the known phylogenetic diversity of soil taxa by 7.2% with respect to the Joint Genome Institute IMG/M database and showed clade-specific sequence recruitment patterns across diverse terrestrial soil metagenomes. Additionally, sorted-MAGs expanded the rare biosphere not captured through MAGs from bulk sequences, exemplified through phylogenetic and functional analyses of members of the phylum Bacteroidetes Analysis of 67 Bacteroidetes sorted-MAGs showed conserved patterns of carbon metabolism across four clades. These results indicate that mini-metagenomics enables genome-resolved investigation of predicted metabolism and demonstrates the utility of combining metagenomics methods to tap into the diversity of heterogeneous microbial assemblages.IMPORTANCE Microbial ecologists have historically used cultivation-based approaches as well as amplicon sequencing and shotgun metagenomics to characterize microbial diversity in soil. However, challenges persist in the study of microbial diversity, including the recalcitrance of the majority of microorganisms to laboratory cultivation and limited sequence assembly from highly complex samples. The uncultivated majority thus remains a reservoir of untapped genetic diversity. To address some of the challenges associated with bulk metagenomics as well as low throughput of single-cell genomics, we applied flow cytometry-enabled mini-metagenomics to capture expanded microbial diversity from forest soil and compare it to soil bulk metagenomics. Our resulting data from this pooled-cell sorting approach combined with bulk metagenomics revealed increased phylogenetic diversity through novel soil taxa and rare biosphere members. In-depth analysis of genomes within the highly represented Bacteroidetes phylum provided insights into conserved and clade-specific patterns of carbon metabolism.

Diet influences the functions of the human intestinal microbiome

Gut microbes programme their metabolism to suit intestinal conditions and convert dietary components into a panel of small molecules that ultimately affect host physiology. To unveil what is behind the effects of key dietary components on microbial functions and the way they modulate host-microbe interaction, we used for the first time a multi-omic approach that goes behind the mere gut phylogenetic composition and provides an overall picture of the functional repertoire in 27 fecal samples from omnivorous, vegan and vegetarian volunteers. Based on our data, vegan and vegetarian diets were associated to the highest abundance of microbial genes/proteins responsible for cell motility, carbohydrate- and protein-hydrolyzing enzymes, transport systems and the synthesis of essential amino acids and vitamins. A positive correlation was observed when intake of fiber and the relative fecal abundance of flagellin were compared. Microbial cells and flagellin extracted from fecal samples of 61 healthy donors modulated the viability of the human (HT29) colon carcinoma cells and the host response through the stimulation of the expression of Toll-like receptor 5, lectin RegIIIα and three interleukins (IL-8, IL-22 and IL-23). Our findings concretize a further and relevant milestone on how the diet may prevent/mitigate disease risk.

Tools for Analysis of the Microbiome

Over the past decade, it has become exceedingly clear that the microbiome is a critical factor in human health and disease and thus should be investigated to develop innovative treatment strategies. The field of metagenomics has come a long way in leveraging the advances of next-generation sequencing technologies resulting in the capability to identify and quantify all microorganisms present in human specimens. However, the field of metagenomics is still in its infancy, specifically in regard to the limitations in computational analysis, statistical assessments, standardization, and validation due to vast variability in the cohorts themselves, experimental design, and bioinformatic workflows. This review summarizes the methods, technologies, computational tools, and model systems for characterizing and studying the microbiome. We also discuss important considerations investigators must make when interrogating the involvement of the microbiome in health and disease in order to establish robust results and mechanistic insights before moving into therapeutic design and intervention.