Towards a unified medical microbiome ecology of the OMU for metagenomes and the OTU for microbes.

BACKGROUND: Metagenomic sequencing technologies offered unprecedented opportunities and also challenges to microbiology and microbial ecology particularly. The technology has revolutionized the studies of microbes and enabled the high-profile human microbiome and earth microbiome projects. The terminology-change from microbes to microbiomes signals that our capability to count and classify microbes (microbiomes) has achieved the same or similar level as we can for the biomes (macrobiomes) of plants and animals (macrobes). While the traditional investigations of macrobiomes have usually been conducted through naturalists' (Linnaeus & Darwin) naked eyes, and aerial and satellite images (remote-sensing), the large-scale investigations of microbiomes have been made possible by DNA-sequencing-based metagenomic technologies. Two major types of metagenomic sequencing technologies-amplicon sequencing and whole-genome (shotgun sequencing)-respectively generate two contrastingly different categories of metagenomic reads (data)-OTU (operational taxonomic unit) tables representing microorganisms and OMU (operational metagenomic unit), a new term coined in this article to represent various cluster units of metagenomic genes. RESULTS: The ecological science of microbiomes based on the OTU representing microbes has been unified with the classic ecology of macrobes (macrobiomes), but the unification based on OMU representing metagenomes has been rather limited. In a previous series of studies, we have demonstrated the applications of several classic ecological theories (diversity, composition, heterogeneity, and biogeography) to the studies of metagenomes. Here I push the envelope for the unification of OTU and OMU again by demonstrating the applications of metacommunity assembly and ecological networks to the metagenomes of human gut microbiomes. Specifically, the neutral theory of biodiversity (Sloan's near neutral model), Ning et al.stochasticity framework, core-periphery network, high-salience skeleton network, special trio-motif, and positive-to-negative ratio are applied to analyze the OMU tables from whole-genome sequencing technologies, and demonstrated with seven human gut metagenome datasets from the human microbiome project. CONCLUSIONS: All of the ecological theories demonstrated previously and in this article, including diversity, composition, heterogeneity, stochasticity, and complex network analyses, are equally applicable to OMU metagenomic analyses, just as to OTU analyses. Consequently, I strongly advocate the unification of OTU/OMU (microbiomes) with classic ecology of plants and animals (macrobiomes) in the context of medical ecology.

Metagenomics of two gnotobiotically grown aromatic rice cultivars reveals genotype-dependent and tissue-specific colonization of endophytic bacterial communities attributing multiple plant growth promoting traits.

Exploration of community structures, habitations, and potential plant growth promoting (PGP) attributes of endophytic bacteria through next generation sequencing (NGS) is a prerequisite to culturing PGP endophytic bacteria for their application in sustainable agriculture. The present study unravels the taxonomic abundance and diversity of endophytic bacteria inhabiting in vitro grown root, shoot and callus tissues of two aromatic rice cultivars through 16S rRNA gene-based Illumina NGS. Wide variability in the number of bacterial operational taxonomic units (OTUs) and genera was observed between the two samples of the root (55, 14 vs. 310, 76) and shoot (26, 12 vs. 276, 73) but not between the two callus samples (251, 61 vs. 259, 51), indicating tissue-specific and genotype-dependent bacterial community distribution in rice plant, even under similar gnotobiotic growth conditions. Sizes of core bacteriomes of the selected two rice genotypes varied from 1 to 15 genera, with Sphingomonas being the only genus detected in all six samples. Functional annotation, based upon the abundance of bacterial OTUs, revealed the presence of several PGP trait-related genes having variable relative abundance in tissue-specific and genotype-dependent manners. In silico study also documented a higher abundance of certain genes in the same biochemical pathway, such as nitrogen fixation, phosphate solubilization and indole acetic acid production; implying their crucial roles in the biosynthesis of metabolites leading to PGP. New insights on utilizing callus cultures for isolation of PGP endophytes aiming to improve rice crop productivity are presented, owing to constancy in bacterial OTUs and genera in callus tissues of both the rice genotypes.

Network Analysis of Gut Microbiome and Metabolome to Discover Microbiota-Linked Biomarkers in Patients Affected by Non-Small Cell Lung Cancer.

Several studies in recent times have linked gut microbiome (GM) diversity to the pathogenesis of cancer and its role in disease progression through immune response, inflammation and metabolism modulation. This study focused on the use of network analysis and weighted gene co-expression network analysis (WGCNA) to identify the biological interaction between the gut ecosystem and its metabolites that could impact the immunotherapy response in non-small cell lung cancer (NSCLC) patients undergoing second-line treatment with anti-PD1. Metabolomic data were merged with operational taxonomic units (OTUs) from 16S RNA-targeted metagenomics and classified by chemometric models. The traits considered for the analyses were: (i) condition: disease or control (CTRLs), and (ii) treatment: responder (R) or non-responder (NR). Network analysis indicated that indole and its derivatives, aldehydes and alcohols could play a signaling role in GM functionality. WGCNA generated, instead, strong correlations between short-chain fatty acids (SCFAs) and a healthy GM. Furthermore, commensal bacteria such as Akkermansia muciniphila, Rikenellaceae, Bacteroides, Peptostreptococcaceae, Mogibacteriaceae and Clostridiaceae were found to be more abundant in CTRLs than in NSCLC patients. Our preliminary study demonstrates that the discovery of microbiota-linked biomarkers could provide an indication on the road towards personalized management of NSCLC patients.

Early detection of eukaryotic communities from marine biofilm using high-throughput sequencing: an assessment of different sampling devices.

Marine biofilms are precursors for colonization by larger fouling organisms, including non-indigenous species (NIS). In this study, high-throughput sequencing (HTS) of 18S rRNA metabarcodes was used to investigate four sampling methods (modified syringe, sterilized sponge, underwater tape and sterilized swab) for characterizing eukaryotic communities in marine biofilms. Perspex™ plates were sampled in and out of water. DNA collected with tape did not amplify. Otherwise, there were no statistical differences in communities among the remaining three sampling devices or between the two environments. Sterilized sponges are recommended for ease of use underwater. In-depth HTS analysis identified diverse eukaryotic communities, dominated by Metazoa and Chromoalveolata. Among the latter, diatoms (Bacillariophyceae) were particularly abundant (33% of reads assigned to Chromalveolata). The NIS Ciona savignyi was detected in all samples. The application of HTS in marine biofilm surveillance could facilitate early detection of NIS, improving the probability of successful eradication.

Morphometric and meristic diversity of the species Androctonus crassicauda (Olivier, 1807) (Scorpiones: Buthidae) in Saudi Arabia.

Intraspecific molecular and morphological variations among geographically isolated populations are useful for understanding the evolutionary processes, which is considered early stage of allopatric speciation. Also, the knowledge of the regional variation of scorpion venom composition is needed to improve antivenom therapeutic management. Androctonus crassicauda (Olivier, 1807) is the most common and medically important species in Arabia and the Middle East. Therefore, this study aimed to investigate the geographic morphological variation among A.crassicaudapopulations, regarding its geographical distribution in unexplored arid regions in Saudi Arabia. Samples were collected and examined morphologically under a dissecting microscope from different four eco-geographical regions. The results of ANOVA and multivariate statistical analyses provide strong evidence of geographical variation. The two populations from OTU3 and OUT4 showed the greatest degree of morphological difference from populations of OUT1 and OUT2. Each OTU3 and OTU4 populations showed significant speciation without overlapping in the two groups, while the remaining overlapped groups comprised two other populations. Several body variables influenced male separation, including carapace posterior width, metasoma 3rd length, and metasoma 2nd length. For females, telson length, metasoma 1st width, and sternite 7th width were highly influential variables. Such variation may suggest the existence of cryptic taxa within A. crassicauda populations in Saudi Arabia. Moreover, metasoma ratios can be used as good indicators in intraspecific variation studies of Scorpions.

Gut Microbiome Distinguishes Patients With Epilepsy From Healthy Individuals.

Objective: The gut microecosystem is the largest microecosystem in the human body and has been proven to be linked to neurological diseases. The main objective of this study was to characterize the fecal microbiome, investigate the differences between epilepsy patients and healthy controls, and evaluate the potential efficacy of the fecal microbiome as a diagnostic tool for epilepsy. Design: We collected 74 fecal samples from epilepsy patients (Eps, n = 24) and healthy controls (HCs, n = 50) in the First Affiliated Hospital of Zhengzhou University and subjected the samples to 16S rRNA MiSeq sequencing and analysis. We set up a train set and a test set, identified the optimal microbial markers for epilepsy after characterizing the gut microbiome in the former and built a diagnostic model, then validated it in the validation group. Results: There were significant differences in microbial communities between the two groups. The α-diversity of the HCs was higher than that of the epilepsy group, but the Venn diagram showed that there were more unique operational taxonomic unit (OTU) in the epilepsy group. At the phylum level, Proteobacteria and Actinobacteriota increased significantly in Eps, while the relative abundance of Bacteroidota increased in HCs. Compared with HCs, Eps were enriched in 23 genera, including Faecalibacterium, Escherichia-Shigella, Subdoligranulum and Enterobacteriaceae-unclassified. In contrast, 59 genera including Bacteroides, Megamonas, Prevotella, Lachnospiraceae-unclassified and Blautia increased in the HCs. In Spearman correlation analysis, age, WBC, RBC, PLT, ALB, CREA, TBIL, Hb and Urea were positively correlated with most of the different OTUs. Seizure-type, course and frequency are negatively correlated with most of the different OTUs. In addition, twenty-two optimal microbial markers were identified by a fivefold cross-validation of the random forest model. In the established train set and test set, the area under the curve was 0.9771 and 0.993, respectively. Conclusion: Our study was the first to characterize the gut microbiome of Eps and HCs in central China and demonstrate the potential efficacy of microbial markers as a noninvasive biological diagnostic tool for epilepsy.

Application of Next-Generation Sequencing for the Determination of the Bacterial Community in the Gut Contents of Brackish Copepod Species (Acartia hudsonica, Sinocalanus tenellus, and Pseudodiaptomus inopinus).

The gut bacterial communities of copepods can affect metabolic processes, and consequently, their activity can be related to the release of organic substances to the environment. Hence, they are important for organic matter cycling in marine coast food webs. However, information regarding the variation in gut bacterial communities based on copepod species and environmental variations is limited. We analysed the differences in gut bacterial communities from dominant copepod species, i.e., Acartia hudsonica, Sinocalanus tenellus, and Pseudodiaptomus inopinus, in a brackish reservoir. The core bacteria among the copepod species and locations consisted of the following main operational taxonomic units (OTUs): Novosphingobium capsulatum and the family Rhodobacteraceae belonging to Alphaproteobacteria, which is abundant in seawater and freshwater aquatic ecosystems as a zooplankton-associated bacterial community. The bacterial community composition of each copepod (except the core species) showed high variability. The bacterial community diversity differed depending on the copepod species and the sites' environmental conditions, especially salinity, e.g., compositional variations in the bacterial community of P. inopinus were high at sites with low salinity. Therefore, the gut bacterial community of each copepod species responds differently to the environment.

The Effects of Temperature on Animal Gut Microbiomes.

Temperature is a prominent abiotic environmental variable that drives the adaptive trajectories of animal lineages and structures the composition of animal communities. Global temperature regimes are expected to undergo rapid shifts in the next century, yet for many animal taxa we lack an understanding of the consequences of these predicted shifts for animal populations. In this review, we synthesize recent evidence that temperature variation shapes the composition and function of animal gut microbiomes, key regulators of host physiology, with potential consequences for host population responses to climate change. Several recent studies spanning a range of animal taxa, including Chordata, Arthropoda, and Mollusca, have reported repeatable associations between temperature and the community composition and function of the gut microbiome. In several cases, the same microbiome responses to temperature have been observed across distantly related animal taxa, suggesting the existence of conserved mechanisms underlying temperature-induced microbiome plasticity. Extreme temperatures can disrupt the stability of alpha-diversity within the gut microbiomes individual hosts and generate beta-diversity among microbiomes within host populations. Microbiome states resulting from extreme temperatures have been associated, and in some cases causally linked, with both beneficial and deleterious effects on host phenotypes. We propose routes by which temperature-induced changes in the gut microbiome may impact host fitness, including effects on colonization resistance in the gut, on host energy and nutrient assimilation, and on host life history traits. Cumulatively, available data indicate that disruption of the gut microbiome may be a mechanism by which changing temperatures will impact animal fitness in wild-living populations.

Evaluation of Healthy Canine Conjunctival, Periocular Haired Skin, and Nasal Microbiota Compared to Conjunctival Culture.

Next-generation sequencing (NGS) methods have been used to identify a diverse ocular surface (OS) microbiota in humans. These results have highlighted limitations in microbial detection via traditional culture-based techniques. The OS has mechanisms such as tear film and mechanical blinking, which may aid in preventing adherence and colonization of microbes, suggesting that only low populations of microbes may reside on the OS. Additionally, closely related tissues to the OS are exposed to a similar array of microbes, but demonstrate different defense mechanisms. Information regarding concordance of microbial communities of the OS and nearby tissues is lacking. Our study purposes were to (1) characterize the conjunctival microbiota of healthy dogs, (2) compare the conjunctival microbiota to the periocular haired skin and distal nose, and (3) compare the bacteria identified by culture to NGS of the healthy canine conjunctiva. Here, NGS was used to evaluate samples from 25 healthy adult dogs of the conjunctiva, periocular haired skin, and distal nose. Additional samples were collected from each dog for traditional conjunctival culture. The 16S rRNA gene amplicon libraries were evaluated for coverage, relative abundance, richness, and diversity. Site-dependent similarities evaluated using principal coordinate analysis (PCoA) and PERMANOVA demonstrated relatedness in community compositions between sites. The conjunctiva of healthy dogs yielded a rich and diverse microbiota based on NGS. While some regional continuity was noted, microbial communities of the conjunctiva, periocular haired skin, and nose were significantly different from each other. Comparatively, traditional culture markedly underestimated the number of bacterial taxa present on the healthy canine OS. Findings suggest similarities in nasal and conjunctival microbial communities, which may be a result of similarities in mucosal immunity and anatomic connection via the nasolacrimal system. Further investigation using NGS into changes of the composition of bacterial communities in disease is warranted.

Systematic Comparisons for Composition Profiles, Taxonomic Levels, and Machine Learning Methods for Microbiome-Based Disease Prediction.

Microbiome composition profiles generated from 16S rRNA sequencing have been extensively studied for their usefulness in phenotype trait prediction, including for complex diseases such as diabetes and obesity. These microbiome compositions have typically been quantified in the form of Operational Taxonomic Unit (OTU) count matrices. However, alternate approaches such as Amplicon Sequence Variants (ASV) have been used, as well as the direct use of k-mer sequence counts. The overall effect of these different types of predictors when used in concert with various machine learning methods has been difficult to assess, due to varied combinations described in the literature. Here we provide an in-depth investigation of more than 1,000 combinations of these three clustering/counting methods, in combination with varied choices for normalization and filtering, grouping at various taxonomic levels, and the use of more than ten commonly used machine learning methods for phenotype prediction. The use of short k-mers, which have computational advantages and conceptual simplicity, is shown to be effective as a source for microbiome-based prediction. Among machine-learning approaches, tree-based methods show consistent, though modest, advantages in prediction accuracy. We describe the various advantages and disadvantages of combinations in analysis approaches, and provide general observations to serve as a useful guide for future trait-prediction explorations using microbiome data.

Characterization of the Rat Gut Microbiota via 16S rRNA Amplicon Library Sequencing.

It is becoming increasingly apparent that microbiota have measurable effects on numerous phenotypes in laboratory animals. This "second genome" has often been disregarded or ignored due to its commensal nonpathogenic nature, and the difficulty, expense, and analysis of sequence. Recent advances in sequencing methods and analyses of large datasets have made characterization of microbiota populations routine and have uncovered previously unknown relationships of microbial communities and host biological systems. The largest and most diverse microbial community in the laboratory rat is in the gut, and has been shown to affect the physiology of the whole animal, and genetic disease penetrance. We present here a cost-effective method for the characterization of the rat fecal microbiota through multiplexed 16S ribosomal sequencing and freely available software.

A Comparative Metagenomics Study on Gastrointestinal Microbiota in Amphibious Mudskippers and Other Vertebrate Animals.

Gut microbiomes in various fish species were widely investigated with the rapid development of next-generation sequencing technologies. However, little is known about gastrointestinal (GI) microbial communities in mudskippers, a representative group of marine amphibious fishes, and their comparisons with other vertebrate animals from different habitats. Here, we performed a comprehensive analysis on microbial composition in five representative vertebrate groups (including amphibious mudskippers, marine and freshwater aquatic fishes, amphibians, and terrestrial animals) via operational taxonomic unit (OTU) survey and obtained a microbial gene catalog of five common fish species by metagenome sequencing. We observed that Cyanobacteria, Proteobacteria, Firmicutes, Bacteroidetes, and Fusobacteria were the most substantial bacteria in mudskippers. Differential variances in composition patterns of GI microbiota among the vertebrate groups were determined, although Proteobacteria and Firmicutes were the shared phyla with high abundance. In addition, Cetobacterium and Photobacterium were the most abundant genera in core OTUs of these examined omnivores, carnivores, and herbivores. Our metagenomic analysis also showed significant differences between the representative blue-spotted mudskipper and grass carp (both are herbivorous fishes) in microbes at the phylum and class levels and functional gene terms. Moreover, several bacteriocin-related genes were identified in the five common fishes, suggesting their potential contributions to pathogen resistance. In summary, our present work not only sheds new light on the correlation of GI microbiota composition with living habitats and feeding habits of the hosts, but also provides valuable bacterial genetic resources for healthy growth of aquaculture fishes.

Salivary Microbiome and Cigarette Smoking: A First of Its Kind Investigation in Jordan.

There is accumulating evidence in the biomedical literature suggesting the role of smoking in increasing the risk of oral diseases including some oral cancers. Smoking alters microbial attributes of the oral cavity by decreasing the commensal microbial population and increasing the pathogenic microbes. This study aims to investigate the shift in the salivary microbiota between smokers and non-smokers in Jordan. Our methods relied on high-throughput next-generation sequencing (NGS) experiments for V3-V4 hypervariable regions of the 16S rRNA gene, followed by comprehensive bioinformatics analysis including advanced multidimensional data visualization methods and statistical analysis approaches. Six genera-Streptococcus, Prevotella, Vellionella, Rothia, Neisseria, and Haemophilus-predominated the salivary microbiota of all samples with different percentages suggesting the possibility for the salivary microbiome to restored after quitting smoking. Three genera-Streptococcus, Prevotella, and Veillonella-showed significantly elevated levels among smokers at the expense of Neisseria in non-smokers. In conclusion, smoking has a definite impact on shifting the salivary microbiota in smokers. We can suggest that there is microbial signature at the genera level that can be used to classify smokers and non-smokers by Linear Discriminant Analysis Effect Size (LEfSe) based on the salivary abundance of genera. Proteomics and metabolomics studies are highly recommended to fully understand the effect of bacterial endotoxin release and xenobiotic metabolism on the bacterial interrelationships in the salivary microbiome and how they affect the growth of each other in the saliva of smokers.

Exploring the Impacts of Anthropogenic Disturbance on Seawater and Sediment Microbial Communities in Korean Coastal Waters Using Metagenomics Analysis.

The coastal ecosystems are considered as one of the most dynamic and vulnerable environments under various anthropogenic developments and the effects of climate change. Variations in the composition and diversity of microbial communities may be a good indicator for determining whether the marine ecosystems are affected by complex forcing stressors. DNA sequence-based metagenomics has recently emerged as a promising tool for analyzing the structure and diversity of microbial communities based on environmental DNA (eDNA). However, few studies have so far been performed using this approach to assess the impacts of human activities on the microbial communities in marine systems. In this study, using metagenomic DNA sequencing (16S ribosomal RNA gene), we analyzed and compared seawater and sediment communities between sand mining and control (natural) sites in southern coastal waters of Korea to assess whether anthropogenic activities have significantly affected the microbial communities. The sand mining sites harbored considerably lower levels of microbial diversities in the surface seawater community during spring compared with control sites. Moreover, the sand mining areas had distinct microbial taxonomic group compositions, particularly during spring season. The microbial groups detected solely in the sediment load/dredging areas (e.g., Marinobacter, Alcanivorax, Novosphingobium) are known to be involved in degradation of toxic chemicals such as hydrocarbon, oil, and aromatic compounds, and they also contain potential pathogens. This study highlights the versatility of metagenomics in monitoring and diagnosing the impacts of human disturbance on the environmental health of marine ecosystems from eDNA.

Analysis of 16S rRNA Gene Amplicon Sequences Using the QIIME Software Package.

The study of microbial ecology has undergone a paradigm shift in recent years, with rapid advances in molecular and bioinformatic tools allowing researchers with wide-ranging interests and backgrounds access to community profiling methods. While these advances have undoubtedly led to exciting new understanding of many systems, the array of protocols available and the idiosyncrasies of particular approaches can lead to confusion or, at worst, erroneous interpretation of results. Here, we describe a workflow from raw 16S rRNA gene amplicon sequence data, generated on an Illumina MiSeq instrument, to microbial community taxonomy profiles and basic diversity measures. The workflow can be adapted to input from major sequence platforms and uses freely available open source software that can be implemented on a range of operating systems.

Oral Probiotics Alter Healthy Feline Respiratory Microbiota.

Probiotics have been advocated as a novel therapeutic approach to respiratory disease, but knowledge of how oral administration of probiotics influences the respiratory microbiota is needed. Using 16S rRNA amplicon sequencing of bacterial DNA our objective was to determine whether oral probiotics changed the composition of the upper and lower airway, rectal, and blood microbiota. We hypothesized that oral probiotics would modulate the respiratory microbiota in healthy cats, demonstrated by the detection and/or increased relative abundance of the probiotic bacterial species and altered composition of the microbial population in the respiratory tract. Six healthy young research cats had oropharyngeal (OP), bronchoalveolar lavage fluid (BALF), rectal, and blood samples collected at baseline and 4 weeks after receiving oral probiotics. 16S rRNA gene amplicon libraries were sequenced, and coverage, richness, and relative abundance of representative operational taxonomic units (OTUs) were determined. Hierarchical and principal component analyses (PCA) demonstrated relatedness of samples. Mean microbial richness significantly increased only in the upper and lower airways. The number of probiotic OTUs (out of 5 total) that significantly increased in relative abundance vs. baseline was 5 in OP, 3 in BAL and 2 in feces. Using hierarchical clustering, BALF and blood samples grouped together after probiotic administration, and PERMANOVA supported that these two sites underwent significant changes in microbial composition. PERMANOVA revealed that OP and rectal samples had microbial population compositions that did not significantly change. These findings were visualized via PCA, which revealed distinct microbiomes in each site; samples clustered more tightly at baseline and had more variation after probiotic administration. This is the first study describing the effect of oral probiotics on the respiratory microbiota via detection of probiotic species in the airways. Finding bacterial species present in the oral probiotics in the upper and lower airways provides pilot data suggesting that oral probiotics could serve as a tool to target dysbiosis occurring in inflammatory airway diseases such as feline asthma, a disease in which cats serve as an important comparative and translational model for humans.