Visualization-assisted binning of metagenome assemblies reveals potential new pathogenic profiles in idiopathic travelers' diarrhea

Supragingival microbiome variations and the influence of Candida albicans in adolescent orthodontic patients with gingivitis

Introduction

Gingivitis is a prevalent complication in adolescents undergoing fixed orthodontic treatments. However, changes in the supragingival microbiome associated with gingivitis and the impact of Candida albicans remain elusive. Therefore, we investigated supragingival microbiome discrepancy and C. albicans colonization in adolescent orthodontic patients with gingivitis.

Methods

Dental plaques were collected from 30 gingivitis patients and 24 healthy adolescents, all undergoing fixed orthodontic treatment. The supragingival microbiome composition was analyzed using 16S rRNA sequencing. C. albicans colonization was determined using fungal culture and real-time quantitative polymerase chain reaction.

Results

Our analysis revealed significantly heightened microbial diversity in the Gingivitis group. Notably, patients with gingivitis exhibited an enrichment of periodontal pathogens, such as Saccharibacteria (TM7) [G-1], Selenomonas, Actinomyces dentalis, and Selenomonas sputigena. Additionally, 33% of the gingivitis patients tested positive for C. albicans, exhibiting significantly elevated levels of absolute abundance, while all healthy patients tested negative. Significant differences in microbial composition were also noted between C. albicans-positive and -negative samples in the Gingivitis group.

Conclusion

Significant disparities were observed in the supragingival microbiome of adolescent orthodontic patients with and without gingivitis. The presence of C. albicans in the supragingival plaque may alter the microbiome composition and potentially contribute to gingivitis pathogenesis.

Comparison of metagenomic and traditional methods for diagnosis of E. coli enteric infections

Diarrheagenic Escherichia coli, collectively known as DEC, is a leading cause of diarrhea, particularly in children in low- and middle-income countries. Diagnosing infections caused by different DEC pathotypes traditionally relies on the cultivation and identification of virulence genes, a resource-intensive and error-prone process. Here, we compared culture-based DEC identification with shotgun metagenomic sequencing of whole stool using 35 randomly drawn samples from a cohort of diarrhea-afflicted patients. Metagenomic sequencing detected the cultured isolates in 97% of samples, revealing, overall, reliable detection by this approach. Genome binning yielded high-quality E. coli metagenome-assembled genomes (MAGs) for 13 samples, and we observed that the MAG did not carry the diagnostic DEC virulence genes of the corresponding isolate in 60% of these samples. Specifically, two distinct scenarios were observed: diffusely adherent E. coli (DAEC) isolates without corresponding DAEC MAGs appeared to be relatively rare members of the microbiome, which was further corroborated by quantitative PCR (qPCR), and thus unlikely to represent the etiological agent in 3 of the 13 samples (~23%). In contrast, ETEC virulence genes were located on plasmids and largely escaped binning in associated MAGs despite being prevalent in the sample (5/13 samples or ~38%), revealing limitations of the metagenomic approach. These results provide important insights for diagnosing DEC infections and demonstrate how metagenomic methods can complement isolation efforts and PCR for pathogen identification and population abundance.

IMPORTANCE

Diagnosing enteric infections based on traditional methods involving isolation and PCR can be erroneous due to isolation and other biases, e.g., the most abundant pathogen may not be recovered on isolation media. By employing shotgun metagenomics together with traditional methods on the same stool samples, we show that mixed infections caused by multiple pathogens are much more frequent than traditional methods indicate in the case of acute diarrhea. Further, in at least 8.5% of the total samples examined, the metagenomic approach reliably identified a different pathogen than the traditional approach. Therefore, our results provide a methodology to complement existing methods for enteric infection diagnostics with cutting-edge, culture-independent metagenomic techniques, and highlight the strengths and limitations of each approach.

Enhancing enteric pathogen detection: implementation and impact of multiplex PCR for improved diagnosis and surveillance

BACKGROUND

Syndromic surveillance of acute gastroenteritis plays a significant role in the diagnosis and management of gastrointestinal infections that are responsible for a substantial number of deaths globally, especially in developing countries. In Lebanon, there is a lack of national surveillance for acute gastroenteritis, and limited data exists regarding the prevalence of pathogens causing diarrhea. The one-year study aims to investigate the epidemiology of common gastrointestinal pathogens and compare our findings with causative agents of diarrhea reported by our study collaborative centers.

METHODS

A multicenter, cross-sectional study was conducted over a one-year period. A total of 271 samples were obtained from outpatients and inpatients presenting with symptoms of acute gastroenteritis at various healthcare facilities. The samples were then analyzed using Allplex gastrointestinal assay that identifies a panel of enteric pathogens.

RESULTS

Overall, enteropathogens were detected in 71% of the enrolled cases, 46% of those were identified in patients as single and 54% as mixed infections. Bacteria were observed in 48%, parasites in 12% and viruses in 11%. Bacterial infections were the most prevalent in all age groups. Enteroaggregative E. coli (26.5%), Enterotoxigenic E. coli (23.2%) and Enteropathogenic E. coli (20.3%) were the most frequently identified followed by Blastocystis hominis (15.5%) and Rotavirus (7.7%). Highest hospitalization rate occurred with rotavirus (63%), Enterotoxigenic E. coli (50%), Blastocystis hominis (45%) and Enteropathogenic E. coli (43%). Enteric pathogens were prevalent during summer, fall and winter seasons.

CONCLUSIONS

The adoption of multiplex real-time PCR assays in the diagnosis of gastrointestinal infections has identified gaps and improved the rates of detection for multiple pathogens. Our findings highlight the importance of conducting comprehensive surveillance to monitor enteric infections. The implementation of a syndromic testing panel can therefore provide healthcare professionals with timely and accurate information for more effective treatment and public health interventions.

BinaRena: a dedicated interactive platform for human-guided exploration and binning of metagenomes

BACKGROUND

Exploring metagenomic contigs and "binning" them into metagenome-assembled genomes (MAGs) are essential for the delineation of functional and evolutionary guilds within microbial communities. Despite the advances in automated binning algorithms, their capabilities in recovering MAGs with accuracy and biological relevance are so far limited. Researchers often find that human involvement is necessary to achieve representative binning results. This manual process however is expertise demanding and labor intensive, and it deserves to be supported by software infrastructure.

RESULTS

We present BinaRena, a comprehensive and versatile graphic interface dedicated to aiding human operators to explore metagenome assemblies via customizable visualization and to associate contigs with bins. Contigs are rendered as an interactive scatter plot based on various data types, including sequence metrics, coverage profiles, taxonomic assignments, and functional annotations. Various contig-level operations are permitted, such as selection, masking, highlighting, focusing, and searching. Binning plans can be conveniently edited, inspected, and compared visually or using metrics including silhouette coefficient and adjusted Rand index. Completeness and contamination of user-selected contigs can be calculated in real time. In demonstration of BinaRena's usability, we show that it facilitated biological pattern discovery, hypothesis generation, and bin refinement in a complex tropical peatland metagenome. It enabled isolation of pathogenic genomes within closely related populations from the gut microbiota of diarrheal human subjects. It significantly improved overall binning quality after curating results of automated binners using a simulated marine dataset.

CONCLUSIONS

BinaRena is an installation-free, dependency-free, client-end web application that operates directly in any modern web browser, facilitating ease of deployment and accessibility for researchers of all skill levels. The program is hosted at https://github.com/qiyunlab/binarena , together with documentation, tutorials, example data, and a live demo. It effectively supports human researchers in intuitive interpretation and fine tuning of metagenomic data. Video Abstract.

Arsenic (As) oxidation by core endosphere microbiome mediates As speciation in Pteris vittata roots

Pteris vittata is an arsenic(As)-hyperaccumulator that may be employed in phytoremediation of As-contaminated soils. P. vittata-associated microbiome are adapted to elevated As and may be important for host survival under stresses. Although P. vittata root endophytes could be critical for As biotransformation in planta, their compositions and metabolisms remain elusive. The current study aims to characterize the root endophytic community composition and As-metabolizing potentials in P. vittata. High As(III) oxidase gene abundances and rapid As(III) oxidation activity indicated that As(III) oxidation was the dominant microbial As-biotransformation processes compared to As reduction and methylization in P. vittata roots. Members of Rhizobiales were the core microbiome and the dominant As(III) oxidizers in P. vittata roots. Acquasition of As-metabolising genes, including both As(III) oxidase and As(V) detoxification reductase genes, through horizontal gene transfer was identified in a Saccharimonadaceae genomic assembly, which was another abundant population residing in P. vittata roots. Acquisition of these genes might improve the fitness of Saccharimonadaceae population to elevated As concentrations in P. vittata. Diverse plant growth promoting traits were encoded by the core root microbiome populations Rhizobiales. We propose that microbial As(III) oxidation and plant growth promotion are critical traits for P. vittata survival in hostile As-contaiminated sites.

Novel Virus Identification through Metagenomics: A Systematic Review

Metagenomic Next Generation Sequencing (mNGS) allows the evaluation of complex microbial communities, avoiding isolation and cultivation of each microbial species, and does not require prior knowledge of the microbial sequences present in the sample. Applications of mNGS include virome characterization, new virus discovery and full-length viral genome reconstruction, either from virus preparations enriched in culture or directly from clinical and environmental specimens. Here, we systematically reviewed studies that describe novel virus identification through mNGS from samples of different origin (plant, animal and environment). Without imposing time limits to the search, 379 publications were identified that met the search parameters. Sample types, geographical origin, enrichment and nucleic acid extraction methods, sequencing platforms, bioinformatic analytical steps and identified viral families were described. The review highlights mNGS as a feasible method for novel virus discovery from samples of different origins, describes which kind of heterogeneous experimental and analytical protocols are currently used and provides useful information such as the different commercial kits used for the purification of nucleic acids and bioinformatics analytical pipelines.

Candidate Phyla Radiation, an Underappreciated Division of the Human Microbiome, and Its Impact on Health and Disease

Candidate phyla radiation (CPR) is an emerging division of the bacterial domain within the human microbiota. Still poorly known, these microorganisms were first described in the environment in 1981 as "ultramicrobacteria" with a cell volume under 0.1 μm³ and were first associated with the human oral microbiota in 2007. The evolution of technology has been paramount for the study of CPR within the human microbiota. In fact, since these ultramicrobacteria have yet to be axenically cultured despite ongoing efforts, progress in imaging technology has allowed their observation and morphological description. Although their genomic abilities and taxonomy are still being studied, great strides have been made regarding their taxonomic classification, as well as their lifestyle. In addition, advancements in next-generation sequencing and the continued development of bioinformatics tools have allowed their detection as commensals in different human habitats, including the oral cavity and gastrointestinal and genital tracts, thus highlighting CPR as a nonnegligible part of the human microbiota with an impact on physiological settings. Conversely, several pathologies present dysbiosis affecting CPR levels, including inflammatory, mucosal, and infectious diseases. In this exhaustive review of the literature, we provide a historical perspective on the study of CPR, an overview of the methods available to study these organisms and a description of their taxonomy and lifestyle. In addition, their distribution in the human microbiome is presented in both homeostatic and dysbiotic settings. Future efforts should focus on developing cocultures and, if possible, axenic cultures to obtain isolates and therefore genomes that would provide a better understanding of these ultramicrobacteria, the importance of which in the human microbiome is undeniable.

DEPP: Deep Learning Enables Extending Species Trees using Single Genes

Placing new sequences onto reference phylogenies is increasingly used for analyzing environmental samples, especially microbiomes. Existing placement methods assume that query sequences have evolved under specific models directly on the reference phylogeny. For example, they assume single-gene data (e.g., 16S rRNA amplicons) have evolved under the GTR model on a gene tree. Placement, however, often has a more ambitious goal: extending a (genome-wide) species tree given data from individual genes without knowing the evolutionary model. Addressing this challenging problem requires new directions. Here, we introduce Deep-learning Enabled Phylogenetic Placement (DEPP), an algorithm that learns to extend species trees using single genes without pre-specified models. In simulations and on real data, we show that DEPP can match the accuracy of model-based methods without any prior knowledge of the model. We also show that DEPP can update the multi-locus microbial tree-of-life with single genes with high accuracy. We further demonstrate that DEPP can combine 16S and metagenomic data onto a single tree, enabling community structure analyses that take advantage of both sources of data.

Episymbiotic Saccharibacteria suppresses gingival inflammation and bone loss in mice through host bacterial modulation

Saccharibacteria (TM7) are obligate epibionts living on the surface of their host bacteria and are strongly correlated with dysbiotic microbiomes during periodontitis and other inflammatory diseases, suggesting they are putative pathogens. However, due to the recalcitrance of TM7 cultivation, causal research to investigate their role in inflammatory diseases is lacking. Here, we isolated multiple TM7 species on their host bacteria from periodontitis patients. These TM7 species reduce inflammation and consequential bone loss by modulating host bacterial pathogenicity in a mouse ligature-induced periodontitis model. Two host bacterial functions involved in collagen binding and utilization of eukaryotic sialic acid are required for inducing bone loss and are altered by TM7 association. This TM7-mediated downregulation of host bacterial pathogenicity is shown for multiple TM7/host bacteria pairs, suggesting that, in contrast to their suspected pathogenic role, TM7 could protect mammalian hosts from inflammatory damage induced by their host bacteria.

Fast and accurate distance-based phylogenetic placement using divide and conquer

Phylogenetic placement of query samples on an existing phylogeny is increasingly used in molecular ecology, including sample identification and microbiome environmental sampling. As the size of available reference trees used in these analyses continues to grow, there is a growing need for methods that place sequences on ultra-large trees with high accuracy. Distance-based placement methods have recently emerged as a path to provide such scalability while allowing flexibility to analyse both assembled and unassembled environmental samples. In this study, we introduce a distance-based phylogenetic placement method, APPLES-2, that is more accurate and scalable than existing distance-based methods and even some of the leading maximum-likelihood methods. This scalability is owed to a divide-and-conquer technique that limits distance calculation and phylogenetic placement to parts of the tree most relevant to each query. The increased scalability and accuracy enables us to study the effectiveness of APPLES-2 for placing microbial genomes on a data set of 10,575 microbial species using subsets of 381 marker genes. APPLES-2 has very high accuracy in this setting, placing 97% of query genomes within three branches of the optimal position in the species tree using 50 marker genes. Our proof-of-concept results show that APPLES-2 can quickly place metagenomic scaffolds on ultra-large backbone trees with high accuracy as long as a scaffold includes tens of marker genes. These results pave the path for a more scalable and widespread use of distance-based placement in various areas of molecular ecology.

Gut Microbiota Composition Changes in Constipated Women of Reproductive Age

Background

Chronic constipation is one of the most prevalent functional gastrointestinal disorders, yet its etiology is multifactorial, and the pathophysiological mechanism is still unclear. Previous studies have shown that the gut microbiota of constipated patients differs from healthy controls; however, many discrepancies exist in the findings, and no clear link has been confirmed between chronic constipation and changes in the gut microbiota. Growing evidence indicates that age, gender, and hormone levels can affect the composition of gut microbiota. The aim of this study is to examine the overall changes in gut microbiota within a specific sub-population of patients, namely, constipated women of reproductive age.

Methods

We carried out a cross-sectional study comparing the fecal microbial composition of 30 healthy women and 29 constipated women using 16S rRNA gene sequencing. Only women of reproductive age were recruited to reduce the effects of age, gender, and hormone levels on the microbiome, and to prevent conflating the impact of these factors with the effects of constipation.

Results

There were obvious differences in the gut microbiota in constipated women of reproductive age compared with the healthy controls, manifesting mainly as a significant increase in the abundance of Bacteroides (p < 0.05) and a significant decrease in the abundance of Proteobacteria (p < 0.01). The overall composition of the gut microbiota in each group was different, which was reflected in the ratios of Firmicutes to Bacteroidetes (F/B), which was 1.52 in the constipated group vs. 2.21 in the healthy group. Additionally, there was a significant decrease in butyrate-producing bacteria, like Roseburia and Fusicatenibacter (p < 0.01).

Conclusion

The overall composition of the gut microbiota changed in constipated women of reproductive age, characterized by a loss in Proteobacteria and an increase in Bacteroidetes. Furthermore, the abundance of some butyrate-producing bacteria also reduced. These changes may reflect the unique interactions between host and some bacteria, or some bacterial metabolic products, which may be important targets for future studies to explore the pathogenesis of constipation.

Randomized trial assessing impact of probiotic supplementation on gut microbiome and clinical outcome from targeted therapy in metastatic renal cell carcinoma

Studies suggest a link between the gut microbiome and metastatic renal cell carcinoma (mRCC) outcomes, including evidence that mRCC patients possess a lower abundance of Bifidobacterium spp. compared to healthy adults. We sought to assess if a Bifidobacterium‐containing yogurt product could modulate the gut microbiome and clinical outcome from vascular endothelial growth factor‐tyrosine kinase inhibitors (VEGF‐TKIs). mRCC patients initiating VEGF‐TKIs, regardless of the line of therapy, were randomized to probiotic‐supplemented (two 4 oz. servings of the probiotic yogurt product daily) or probiotic‐restricted arms. Stool samples were collected prior to therapy and at weeks 2, 3, 4, and 12. Microbiome composition was assessed using whole‐metagenome sequencing. A total of 20 patients were randomized. Bifidobacterium animalis, the active ingredient of the probiotic supplement, reached detectable levels in all patients in the probiotic‐supplemented arm versus two patients in the probiotic‐restricted arm. Clinical benefit rate was similar in probiotic‐supplemented versus probiotic‐restricted arms (70% vs. 80%, p = 0.606). Linear discriminant analysis (LDA) effect size analysis of MetaPhIAn2 abundance data predicted 25 enriched species demonstrating an LDA score >3 in either clinical benefit or no clinical benefit. In patients with clinical benefit (vs. no clinical benefit), Barnesiella intestinihominis and Akkermansia muciniphila were significantly more abundant (p = 7.4 × 10⁻⁶ and p = 5.6 × 10⁻³, respectively). This is the first prospective randomized study demonstrating modulation of the gut microbiome with a probiotic in mRCC. Probiotic supplementation successfully increased the Bifidobacterium spp. levels. Analysis of longitudinal stool specimens identified an association between B. intestinihominis, A. muciniphila, and clinical benefit with therapy.

Trial Registration: NCT02944617

Stool Microbiome Profiling of Patients with Metastatic Renal Cell Carcinoma Receiving Anti-PD-1 Immune Checkpoint Inhibitors

Preclinical models and early clinical data suggest an interplay between the gut microbiome and response to immunotherapy in solid tumors including metastatic renal cell carcinoma (mRCC). We sought to characterize the stool microbiome of mRCC patients receiving a checkpoint inhibitor (CPI) and to assess treatment-related changes in microbiome composition over the course of CPI therapy. Stool was collected from 31 patients before initiation of nivolumab (77%) or nivolumab plus ipilimumab (23%) therapy, of whom 58% experienced clinical benefit. Greater microbial diversity was associated with clinical benefit from CPI therapy (p =  0.001), and multiple species were associated with clinical benefit or lack thereof. Temporal profiling of the microbiome indicated that the relative abundance of Akkermansia muciniphila increased in patients deriving clinical benefit from CPIs. This study substantiates results from previous CPI-related microbiome profiling studies in mRCC. Temporal changes in microbiome composition suggest potential utility in modulating the microbiome for more successful CPI outcomes. PATIENT SUMMARY: We compared the composition and diversity of the gut microbiome in patients receiving immunotherapy for renal cell carcinoma. We found that higher microbial diversity is associated with better treatment outcomes. Treatment response is characterized by changes in microbial species over the course of treatment.

Chemolithoautotropic Diazotrophy Dominates the Nitrogen Fixation Process in Mine Tailings

Nutrient deficiency, especially bio-available nitrogen deficiency, often impedes the bioremediation efforts of mining generated tailings. Biological nitrogen fixation is a critical process necessary for the initial nitrogen buildup in tailings. Current knowledge regarding the diazotrophs that inhabit tailings is still in its infancy. Therefore, in this study, a comprehensive investigation combining geochemical characterization, sequence analyses, molecular techniques, and activity measurements was conducted to characterize the diazotrophic community residing in tailing environments. Significant differences between tailings and their adjacent soils in prokaryotic and diazotrophic communities were detected. Meanwhile, strong and significant correlations between the absolute abundance of the nitrogen fixation (nifH), carbon fixation (cbbL), sulfur oxidation (soxB), and arsenite oxidation (aioA) genes were observed in the tailings but not in the soils. The reconstructed nif-containing metagenome-assembled genomes (MAGs) suggest that the carbon fixation and sulfur oxidation pathways were important for potential diazotrophs inhabiting the tailings. Activity measurements further confirmed that diazotrophs inhabiting tailings preferentially use inorganic electron donors (e.g., elemental sulfur) compared to organic electron donors (e.g., sucrose), while diazotrophs inhabiting soils preferred organic carbon sources. Collectively, these findings suggest that chemolithoautotrophic diazotrophs may play essential roles in acquiring nutrients and facilitating ecological succession in tailings.

Computational Modeling of the Human Microbiome

The impact of microorganisms on human health has long been acknowledged and studied, but recent advances in research methodologies have enabled a new systems-level perspective on the collections of microorganisms associated with humans, the human microbiome. Large-scale collaborative efforts such as the NIH Human Microbiome Project have sought to kick-start research on the human microbiome by providing foundational information on microbial composition based upon specific sites across the human body. Here, we focus on the four main anatomical sites of the human microbiome: gut, oral, skin, and vaginal, and provide information on site-specific background, experimental data, and computational modeling. Each of the site-specific microbiomes has unique organisms and phenomena associated with them; there are also high-level commonalities. By providing an overview of different human microbiome sites, we hope to provide a perspective where detailed, site-specific research is needed to understand causal phenomena that impact human health, but there is equally a need for more generalized methodology improvements that would benefit all human microbiome research.

Instances of altered gut microbiomes among Irish cricketers over periods of travel in the lead up to the 2016 World Cup: A sequencing analysis

BACKGROUND

Changes and stresses experienced during travel have the potential to impact the gut microbiome, with travel implicated in the spread of antibiotic resistance genes across continents. The possibility of gut microbiome-mediated negative impacts arising from travel, and consequences for peak performance, would be of particular concern for elite athletes.

METHODS

Faecal samples were collected from male (N = 14) and female (N = 7) cricket players during the build-up to the 2016 Cricket World Cup. Baseline and post-travel samples were collected from all participants and subjected to 16S rRNA amplicon sequencing. Samples from a subset of participants (N = 4) were also analysed by shotgun metagenomic sequencing.

RESULTS

Analysis revealed a single travel time point as having the potential to have an impact on the gut microbiome. Reductions in alpha diversity following travel were observed, accompanied by shifts in the taxonomic profile of the gut microbiome. Antibiotic resistance and virulence genes were also identified as undergoing changes following travel.

CONCLUSIONS

This study reveals that periods of travel, in particular following gastrointestinal distress, may result in gut microbiome disruption. While this analysis was completed in athletes, the findings are applicable to all travelling individuals and considerations should be made surrounding travel in an attempt to reduce these changes.