Complete genome sequence of Citroniella saccharovorans DSM 29873, isolated from human fecal sample

A complete genome was recovered from Citroniella saccharovorans, strain DSM 29873, using Oxford Nanopore Technologies. The genome assembly contains 1,413,868 bp with 30.23% G+C content. The species belongs to the family Peptoniphilaceae and, as of yet, is the only cultivated representative of the genus Citroniella.

Current progresses and challenges for microbiome research in human health: a perspective

It is becoming increasingly clear that the human microbiota, also known as "the hidden organ", possesses a pivotal role in numerous processes involved in maintaining the physiological functions of the host, such as nutrient extraction, biosynthesis of bioactive molecules, interplay with the immune, endocrine, and nervous systems, as well as resistance to the colonization of potential invading pathogens. In the last decade, the development of metagenomic approaches based on the sequencing of the bacterial 16s rRNA gene via Next Generation Sequencing, followed by whole genome sequencing via third generation sequencing technologies, has been one of the great advances in molecular biology, allowing a better profiling of the human microbiota composition and, hence, a deeper understanding of the importance of microbiota in the etiopathogenesis of different pathologies. In this scenario, it is of the utmost importance to comprehensively characterize the human microbiota in relation to disease pathogenesis, in order to develop novel potential treatment or preventive strategies by manipulating the microbiota. Therefore, this perspective will focus on the progress, challenges, and promises of the current and future technological approaches for microbiome profiling and analysis.

Re-framing the importance of Group B Streptococcus as a gut-resident pathobiont

Streptococcus agalactiae (Group B Streptococcus, GBS) is a Gram-positive bacterial species that causes disease in humans across the lifespan. While antibiotics are used to mitigate GBS infections, it is evident that antibiotics disrupt human microbiomes (which can predispose people to other diseases later in life), and antibiotic resistance in GBS is on the rise. Taken together, these unintended negative impacts of antibiotics highlight the need for precision approaches for minimizing GBS disease. One possible approach involves selectively depleting GBS in its commensal niches before it can cause disease at other body sites or be transmitted to at-risk individuals. One understudied commensal niche of GBS is the adult gastrointestinal (GI) tract, which may predispose colonization at other body sites in individuals at risk for GBS disease. However, a better understanding of the host-, microbiome-, and GBS-determined variables that dictate GBS GI carriage is needed before precise GI decolonization approaches can be developed. In this review, we synthesize current knowledge of the diverse body sites occupied by GBS as a pathogen and as a commensal. We summarize key molecular factors GBS utilizes to colonize different host-associated niches to inform future efforts to study GBS in the GI tract. We also discuss other GI commensals that are pathogenic in other body sites to emphasize the broader utility of precise de-colonization approaches for mitigating infections by GBS and other bacterial pathogens. Finally, we highlight how GBS treatments could be improved with a more holistic understanding of GBS enabled by continued GI-focused study.

Improved DNA Extraction and Amplification Strategy for 16S rRNA Gene Amplicon-Based Microbiome Studies

Next-generation sequencing technology has driven the rapid advancement of human microbiome studies by enabling community-level sequence profiling of microbiomes. Although all microbiome sequencing methods depend on recovering the DNA from a sample as a first critical step, lysis methods can be a major determinant of microbiome profile bias. Gentle enzyme-based DNA preparation methods preserve DNA quality but can bias the results by failing to open difficult-to-lyse bacteria. Mechanical methods like bead beating can also bias DNA recovery because the mechanical energy required to break tougher cell walls may shear the DNA of the more easily lysed microbes, and shearing can vary depending on the time and intensity of beating, influencing reproducibility. We introduce a non-mechanical, non-enzymatic, novel rapid microbial DNA extraction procedure suitable for 16S rRNA gene-based microbiome profiling applications that eliminates bead beating. The simultaneous application of alkaline, heat, and detergent ('Rapid' protocol) to milligram quantity samples provided consistent representation across the population of difficult and easily lysed bacteria equal to or better than existing protocols, producing sufficient high-quality DNA for full-length 16S rRNA gene PCR. The novel 'Rapid' method was evaluated using mock bacterial communities containing both difficult and easily lysed bacteria. Human fecal sample testing compared the novel Rapid method with a standard Human Microbiome Project (HMP) protocol for samples from lung cancer patients and controls. DNA recovered from both methods was analyzed using 16S rRNA gene sequencing of the V1V3 and V4 regions on the Illumina platform and the V1V9 region on the PacBio platform. Our findings indicate that the 'Rapid' protocol consistently yielded higher levels of Firmicutes species, which reflected the profile of the bacterial community structure more accurately, which was confirmed by mock community evaluation. The novel 'Rapid' DNA lysis protocol reduces population bias common to bead beating and enzymatic lysis methods, presenting opportunities for improved microbial community profiling, combined with the reduction in sample input to 10 milligrams or less, and it enables rapid transfer and simultaneous lysis of 96 samples in a standard plate format. This results in a 20-fold reduction in sample handling time and an overall 2-fold time advantage when compared to widely used commercial methods. We conclude that the novel 'Rapid' DNA extraction protocol offers a reliable alternative for preparing fecal specimens for 16S rRNA gene amplicon sequencing.

Microbiome Dynamics: A Paradigm Shift in Combatting Infectious Diseases

Infectious diseases have long posed a significant threat to global health and require constant innovation in treatment approaches. However, recent groundbreaking research has shed light on a previously overlooked player in the pathogenesis of disease-the human microbiome. This review article addresses the intricate relationship between the microbiome and infectious diseases and unravels its role as a crucial mediator of host-pathogen interactions. We explore the remarkable potential of harnessing this dynamic ecosystem to develop innovative treatment strategies that could revolutionize the management of infectious diseases. By exploring the latest advances and emerging trends, this review aims to provide a new perspective on combating infectious diseases by targeting the microbiome.

Synthetic Communities of Gut Microbes for Basic Research and Translational Approaches in Animal Health and Nutrition

Microbes and animals have a symbiotic relationship that greatly influences nutrient uptake and animal health. This relationship can be studied using selections of microbes termed synthetic communities, or SynComs. SynComs are used in many different animal hosts, including agricultural animals, to investigate microbial interactions with nutrients and how these affect animal health. The most common host focuses for SynComs are currently mouse and human, from basic mechanistic research through to translational disease models and live biotherapeutic products (LBPs) as treatments. We discuss SynComs used in basic research models and findings that relate to human and animal health and nutrition. Translational use cases of SynComs are discussed, followed by LBPs, especially within the context of agriculture. SynComs still face challenges, such as standardization for reproducibility and contamination risks. However, the future of SynComs is hopeful, especially in the areas of genome-guided SynCom design and custom SynCom-based treatments.

How the adaptation of the human microbiome to harsh space environment can determine the chances of success for a space mission to Mars and beyond

The ability of human cells to adapt to space radiation is essential for the well-being of astronauts during long-distance space expeditions, such as voyages to Mars or other deep space destinations. However, the adaptation of the microbiomes should not be overlooked. Microorganisms inside an astronaut's body, or inside the space station or other spacecraft, will also be exposed to radiation, which may induce resistance to antibiotics, UV, heat, desiccation, and other life-threatening factors. Therefore, it is essential to consider the potential effects of radiation not only on humans but also on their microbiomes to develop effective risk reduction strategies for space missions. Studying the human microbiome in space missions can have several potential benefits, including but not limited to a better understanding of the major effects space travel has on human health, developing new technologies for monitoring health and developing new radiation therapies and treatments. While radioadaptive response in astronauts' cells can lead to resistance against high levels of space radiation, radioadaptive response in their microbiome can lead to resistance against UV, heat, desiccation, antibiotics, and radiation. As astronauts and their microbiomes compete to adapt to the space environment. The microorganisms may emerge as the winners, leading to life-threatening situations due to lethal infections. Therefore, understanding the magnitude of the adaptation of microorganisms before launching a space mission is crucial to be able to develop effective strategies to mitigate the risks associated with radiation exposure. Ensuring the safety and well-being of astronauts during long-duration space missions and minimizing the risks linked with radiation exposure can be achieved by adopting this approach.

[Key challenges in the dietary intake structure and cutting edge technologies for optimizing nutrition to protect the health of the Russian рopulation]

This article presents an analysis of some of the results of the work of the Federal Research Center for Nutrition and Biotechnology (Center) in recent years, highlighting the most important, promising areas of Nutrition Science and Food Hygiene that need further development. The priority area of Center functioning is scientific support for the implementation of the Doctrine of Food Security of the Russian Federation (Decree of the President of the Russian Federation dated January 21, 2020 No. 20), Decree of the President of the Russian Federation dated July 21, 2020 No. 474 «On the national development goals of the Russian Federation for the period until 2030 «in terms of ensuring an increase in life expectancy and improving the life quality of the population, the Strategy for Improving the Quality of Food Products in the Russian Federation until 2030 (Order of the Government of the Russian Federation dated June 29, 2016 No. 1364-r). The Center coordinates all research on medical nutrition problems in the Russian Federation within the framework of the work of the Problem Commission on Nutrition Hygiene of the Scientific Council of the Federal Service for Supervision of Consumer Rights Protection and Human Welfare, the Scientific Council of the Russian Academy of Sciences on Medical Nutrition Problems, the Scientific and Technical Committee of the Comprehensive Scientific Program «Priority Research in the Field of Nutrition of the Population», Profile Commission on Dietetics of the Expert Council in the Field of Health of the Ministry of Healthcare of Russian Federation, ensuring the implementation of their results with the participation of members of the Consortium "Healthcare, Nutrition, Demography". The most important area of the Center's work is scientific and expert support in the field of international and national technical regulation of the production and turnover of foods and raw materials, in particular, the work of the Russian national contact point of the Codex Alimentarius Commission (established by FAO and WHO), as well as the work of the Russian side in the Eurasian Economic Commission regarding the preparation of proposals for technical regulations of the Customs Union in the field of food safety, evaluation of draft technical regulations and amendments and additions to them.

A bacterial sensor taxonomy across earth ecosystems for machine learning applications

Microbial communities have evolved to colonize all ecosystems of the planet, from the deep sea to the human gut. Microbes survive by sensing, responding, and adapting to immediate environmental cues. This process is driven by signal transduction proteins such as histidine kinases, which use their sensing domains to bind or otherwise detect environmental cues and "transduce" signals to adjust internal processes. We hypothesized that an ecosystem's unique stimuli leave a sensor "fingerprint," able to identify and shed insight on ecosystem conditions. To test this, we collected 20,712 publicly available metagenomes from Host-associated, Environmental, and Engineered ecosystems across the globe. We extracted and clustered the collection's nearly 18M unique sensory domains into 113,712 similar groupings with MMseqs2. We built gradient-boosted decision tree machine learning models and found we could classify the ecosystem type (accuracy: 87%) and predict the levels of different physical parameters (R2 score: 83%) using the sensor cluster abundance as features. Feature importance enables identification of the most predictive sensors to differentiate between ecosystems which can lead to mechanistic interpretations if the sensor domains are well annotated. To demonstrate this, a machine learning model was trained to predict patient's disease state and used to identify domains related to oxygen sensing present in a healthy gut but missing in patients with abnormal conditions. Moreover, since 98.7% of identified sensor domains are uncharacterized, importance ranking can be used to prioritize sensors to determine what ecosystem function they may be sensing. Furthermore, these new predictive sensors can function as targets for novel sensor engineering with applications in biotechnology, ecosystem maintenance, and medicine.IMPORTANCEMicrobes infect, colonize, and proliferate due to their ability to sense and respond quickly to their surroundings. In this research, we extract the sensory proteins from a diverse range of environmental, engineered, and host-associated metagenomes. We trained machine learning classifiers using sensors as features such that it is possible to predict the ecosystem for a metagenome from its sensor profile. We use the optimized model's feature importance to identify the most impactful and predictive sensors in different environments. We next use the sensor profile from human gut metagenomes to classify their disease states and explore which sensors can explain differences between diseases. The sensors most predictive of environmental labels here, most of which correspond to uncharacterized proteins, are a useful starting point for the discovery of important environment signals and the development of possible diagnostic interventions.

Role of gut-microbiota in disease severity and clinical outcomes

A delicate balance of nutrients, antigens, metabolites and xenobiotics in body fluids, primarily managed by diet and host metabolism, governs human health. Human gut microbiota is a gatekeeper to nutrient bioavailability, pathogens exposure and xenobiotic metabolism. Human gut microbiota starts establishing during birth and evolves into a resilient structure by adolescence. It supplements the host's metabolic machinery and assists in many physiological processes to ensure health. Biotic and abiotic stressors could induce dysbiosis in gut microbiota composition leading to disease manifestations. Despite tremendous scientific advancements, a clear understanding of the involvement of gut microbiota dysbiosis during disease onset and clinical outcomes is still awaited. This would be important for developing an effective and sustainable therapeutic intervention. This review synthesizes the present scientific knowledge to present a comprehensive picture of the role of gut microbiota in the onset and severity of a disease.

Draft genomes of 12 Bifidobacterium isolates from human IBD fecal samples

Twelve Bifidobacterium strains were isolated from fecal samples of inflammatory bowel disease patients and matched "household control" individuals. These include the species Bifidobacterium adolescentis, Bifidobacterium animalis, Bifidobacterium breve, Bifidobacterium catenulatum, Bifidobacterium longum, and Bifidobacterium pseudocatenulatum.

Complete genomes of Limosilactobacillus portuensis and Limosilactobacillus vaginalis isolated from the urine of postmenopausal women

There is frequent evidence that Limosilactobacillus vaginalis colonizes female genitourinary tracts but few reports of Limosilactobacillus portuensis. Their role in urinary tract infection (UTI) is unclear. We present the first complete genome of L. portuensis and a complete genome of L. vaginalis isolated from postmenopausal women with varying UTI histories.

Gut microbiome and antibiotic resistance effects during travelers' diarrhea treatment and prevention

IMPORTANCE

The travelers' gut microbiome is potentially assaulted by acute and chronic perturbations (e.g., diarrhea, antibiotic use, and different environments). Prior studies of the impact of travel and travelers' diarrhea (TD) on the microbiome have not directly compared antibiotic regimens, and studies of different antibiotic regimens have not considered travelers' microbiomes. This gap is important to be addressed as the use of antibiotics to treat or prevent TD-even in moderate to severe cases or in regions with high infectious disease burden-is controversial based on the concerns for unintended consequences to the gut microbiome and antimicrobial resistance (AMR) emergence. Our study addresses this by evaluating the impact of defined antibiotic regimens (single-dose treatment or daily prophylaxis) on the gut microbiome and resistomes of deployed servicemembers, using samples collected during clinical trials. Our findings indicate that the antibiotic treatment regimens that were studied generally do not lead to adverse effects on the gut microbiome and resistome and identify the relative risks associated with prophylaxis. These results can be used to inform therapeutic guidelines for the prevention and treatment of TD and make progress toward using microbiome information in personalized medical care.

Cytokine and microbiota profiles in obesity-related hypertension patients

Background

Systemic arterial hypertension is linked to a heightened risk of cardiovascular diseases on a global scale. In Mexico, nearly half of adults in vulnerable conditions experience hypertension. Imbalance in the oral and intestinal microbiota composition has been observed in patients with hypertension, documented by a decrease of bacteria producing short-chain fatty acids, which play a critical role in blood pressure regulation.

Aim

To examine the cytokines' profile and assess the characteristics of oral and gut microbiota in obesity-related hypertension in Mexican patients.

Methods

A cross-sectional, observational, and analytical study was carried out. Twenty-two patients were categorized by their body mass index (BMI) as overweight and obese, and the diagnosis of primary hypertension. DNA from supragingival dental plaque and feces samples was used to carry out 16S rRNA sequencing. Additionally, 13 cytokines were quantified.

Results

In the oral microbiota, Kluyvera was found to be significantly enriched in obese compared to overweight patients. Instead, the gut microbiota was dominated by Firmicutes. However, the correlation between certain genera and proinflammatory cytokines was noted.

Conclusion

This exploratory study provides insights into the complex relationship between the oral and gut microbiota and their association with systemic inflammation in obesity-related hypertension.

Quantitative assessment of multiple pathogen exposure and immune dynamics at scale

IMPORTANCE

Serology reveals exposure to pathogens, as well as the state of autoimmune and other clinical conditions. It is used to evaluate individuals and their histories and as a public health tool to track epidemics. Employing a variety of formats, studies nearly always perform serology by testing response to only one or a few antigens. However, clinical outcomes of new infections also depend on which previous infections may have occurred. We developed a high-throughput serology method that evaluates responses to hundreds of antigens simultaneously. It can be used to evaluate thousands of samples at a time and provide a quantitative readout. This tool will enable doctors to monitor which pathogens an individual has been exposed to and how that changes in the future. Moreover, public health officials could track populations and look for infectious trends among large populations. Testing many potential antigens at a time may also aid in vaccine development.

MiMultiCat: A Unified Cloud Platform for the Analysis of Microbiome Data with Multi-Categorical Responses

The field of the human microbiome is rapidly growing due to the recent advances in high-throughput sequencing technologies. Meanwhile, there have also been many new analytic pipelines, methods and/or tools developed for microbiome data preprocessing and analytics. They are usually focused on microbiome data with continuous (e.g., body mass index) or binary responses (e.g., diseased vs. healthy), yet multi-categorical responses that have more than two categories are also common in reality. In this paper, we introduce a new unified cloud platform, named MiMultiCat, for the analysis of microbiome data with multi-categorical responses. The two main distinguishing features of MiMultiCat are as follows: First, MiMultiCat streamlines a long sequence of microbiome data preprocessing and analytic procedures on user-friendly web interfaces; as such, it is easy to use for many people in various disciplines (e.g., biology, medicine, public health). Second, MiMultiCat performs both association testing and prediction modeling extensively. For association testing, MiMultiCat handles both ecological (e.g., alpha and beta diversity) and taxonomical (e.g., phylum, class, order, family, genus, species) contexts through covariate-adjusted or unadjusted analysis. For prediction modeling, MiMultiCat employs the random forest and gradient boosting algorithms that are well suited to microbiome data while providing nice visual interpretations. We demonstrate its use through the reanalysis of gut microbiome data on obesity with body mass index categories. MiMultiCat is freely available on our web server.

Prophages: an integral but understudied component of the human microbiome

Phages integrated into a bacterial genome - called prophages - continuously monitor the vigour of the host bacteria to determine when to escape the genome and to protect their host from other phage infections, and they may provide genes that promote bacterial growth. Prophages are essential to almost all microbiomes, including the human microbiome. However, most human microbiome studies have focused on bacteria, ignoring free and integrated phages, so we know little about how these prophages affect the human microbiome. To address this gap in our knowledge, we compared the prophages identified in 14 987 bacterial genomes isolated from human body sites to characterize prophage DNA in the human microbiome. Here, we show that prophage DNA is ubiquitous, comprising on average 1-5 % of each bacterial genome. The prophage content per genome varies with the isolation site on the human body, the health of the human and whether the disease was symptomatic. The presence of prophages promotes bacterial growth and sculpts the microbiome. However, the disparities caused by prophages vary throughout the body.

The human microbiome and cancer: a diagnostic and therapeutic perspective

Recent evidence has shown that the human microbiome is associated with various diseases, including cancer. The salivary microbiome, fecal microbiome, and circulating microbial DNA in blood plasma have all been used experimentally as diagnostic biomarkers for many types of cancer. The microbiomes present within local tissue, other regions, and tumors themselves have been shown to promote and restrict the development and progression of cancer, most often by affecting cancer cells or the host immune system. These microbes have also been shown to impact the efficacy of various cancer therapies, including radiation, chemotherapy, and immunotherapy. Here, we review the research advances focused on how microbes impact these different facets and why they are important to the clinical care of cancer. It is only by better understanding the roles these microbes play in the diagnosis, development, progression, and treatment of cancer, that we will be able to catch and treat cancer early.

Machine-learning analysis of cross-study samples according to the gut microbiome in 12 infant cohorts

IMPORTANCE

There are challenges in merging microbiome data from diverse research groups due to the intricate and multifaceted nature of such data. To address this, we utilized a combination of machine-learning (ML) models to analyze 16S sequencing data from a substantial set of gut microbiome samples, sourced from 12 distinct infant cohorts that were gathered prospectively. Our initial focus was on the mode of delivery due to its prior association with changes in infant gut microbiomes. Through ML analysis, we demonstrated the effective merging and comparison of various gut microbiome data sets, facilitating the identification of robust microbiome biomarkers applicable across varied study populations.

Harnessing the Microbiome: A Comprehensive Review on Advancing Therapeutic Strategies for Rheumatic Diseases

Rheumatic diseases are a group of disorders that affect the joints, muscles, and bones. These diseases, such as rheumatoid arthritis, lupus, and psoriatic arthritis, can cause pain, stiffness, and swelling, leading to reduced mobility and disability. Recent studies have identified the microbiome, the diverse community of microorganisms that live in and on the human body, as a potential factor in the development and progression of rheumatic diseases. Harnessing the microbiome offers a promising new avenue for developing therapeutic strategies for these debilitating conditions. There is growing interest in the role of oral and gut microbiomes in the management of rheumatoid arthritis and other autoimmune disease. Microbial metabolites have immunomodulatory properties that could be exploited for rheumatic disorders. A wide range of microorganisms are present in the oral cavity and are found to be vulnerable to the effects of the environment. The physiology and ecology of the microbiota become intimately connected with those of the host, and they critically influence the promotion of health or progression toward disease. This article aims to provide a comprehensive overview of the current state of knowledge on oral and gut microbiome and its potential future role in the management of rheumatic diseases. This article will also discuss newer treatment strategies such as bioinformatic analyses and fecal transplantation.

Stimulation of Pro-inflammatory Cytokines in Mixed Cultures of Peripheral Blood Mononuclear Cells and Anaerobic Bacteria

In the last couple of decades, much progress has been made in studying bacteria living in humans. However, there is much more to learn about bacteria immune cell interactions. Here, we show that anaerobic bacteria do not grow when cultured overnight with human cells under atmospheric air. Air contains about 18% oxygen, which inhibits the growth of these bacteria while supporting the cultivation of human cells. The bacteria cultured with human peripheral blood mononuclear cells (PBMCs) inflamed with phytohemagglutinin (PHA) greatly increased the production of proinflammatory cytokines like tumor necrosis factor-alpha (TNFα) while inhibiting the production of monocyte chemoattractant protein-1 (MCP-1), an important chemokine.

MiTree: A Unified Web Cloud Analytic Platform for User-Friendly and Interpretable Microbiome Data Mining Using Tree-Based Methods

The advent of next-generation sequencing has greatly accelerated the field of human microbiome studies. Currently, investigators are seeking, struggling and competing to find new ways to diagnose, treat and prevent human diseases through the human microbiome. Machine learning is a promising approach to help such an effort, especially due to the high complexity of microbiome data. However, many of the current machine learning algorithms are in a "black box", i.e., they are difficult to understand and interpret. In addition, clinicians, public health practitioners and biologists are not usually skilled at computer programming, and they do not always have high-end computing devices. Thus, in this study, we introduce a unified web cloud analytic platform, named MiTree, for user-friendly and interpretable microbiome data mining. MiTree employs tree-based learning methods, including decision tree, random forest and gradient boosting, that are well understood and suited to human microbiome studies. We also stress that MiTree can address both classification and regression problems through covariate-adjusted or unadjusted analysis. MiTree should serve as an easy-to-use and interpretable data mining tool for microbiome-based disease prediction modeling, and should provide new insights into microbiome-based diagnostics, treatment and prevention. MiTree is an open-source software that is available on our web server.

Complete genome sequences of Ruminococcus torques strains JCM 36208 and JCM 36209, isolated from the feces of a healthy Japanese male

Here, we report the complete genome sequences of two Ruminococcus torques strains (JCM 36208 and JCM 36209) that were newly isolated from the feces of a healthy Japanese male. Both genomes consist of a single circular chromosome with a length of ~2.8 Mbp and a G+C content of 41.8%.

Extension of the Segatella copri complex to 13 species with distinct large extrachromosomal elements and associations with host conditions

The Segatella copri (formerly Prevotella copri) complex (ScC) comprises taxa that are key members of the human gut microbiome. It was previously described to contain four distinct phylogenetic clades. Combining targeted isolation with large-scale metagenomic analysis, we defined 13 distinct Segatella copri-related species, expanding the ScC complex beyond four clades. Complete genome reconstruction of thirteen strains from seven species unveiled the presence of genetically diverse large circular extrachromosomal elements. These elements are consistently present in most ScC species, contributing to intra- and inter-species diversities. The nine species-level clades present in humans display striking differences in prevalence and intra-species genetic makeup across human populations. Based on a meta-analysis, we found reproducible associations between members of ScC and the male sex and positive correlations with lower visceral fat and favorable markers of cardiometabolic health. Our work uncovers genomic diversity within ScC, facilitating a better characterization of the human microbiome.

Oral microbiome characterization in oral mucositis patients-A systematic review

BACKGROUND

Oral mucositis (OM) is a severe and common adverse effect of cancer treatment. The oral microbiome appears to play a role on the onset and severity of OM. Therefore, this systematic review aims to characterize the oral dysbiosis associated with OM.

METHODS

The PRISMA checklist was followed and PubMed, Web of Science, and Scopus were screened for clinical studies characterizing the oral microbiome alterations in patients with OM.

RESULTS

From a total of 2500 articles retrieved, we included nine articles in this systematic review. Certain types of bacteria, as Fusobacterium, were recognized as predictors of the onset of OM. In addition, it was reported that patients with severe OM presented a reduction in alpha-diversity, an increase in beta-diversity. The abundance of some taxa significantly changed with OM severity, with Bacillota phylum and genera Leptotrichia, Actinomyces, and Prevotella decreasing and Treponema increasing with disease progression. Additionally, during cancer treatment, changes in the oral microbiome have been observed in OM patients, with an increase in Candida and nosocomial pathogens, including Staphylococcus species.

CONCLUSION

Our review indicates that cancer treatment can significantly alter the oral microbiome, with more pronounced changes observed in patients with severe OM in all relevant oral phyla, but more pronounced in Bacillota phylum.

Salivary microbiome of healthy women of reproductive age

IMPORTANCE

The salivary microbiome has been proven to play a crucial role in local and systemic diseases. Moreover, the effects of biological and lifestyle factors such as oral hygiene and smoking on this microbial community have already been explored. However, what was not yet well understood was the natural variation of the saliva microbiome in healthy women and how this is associated with specific use of hormonal contraception and with the number of different sexual partners with whom microbiome exchange is expected regularly. In this paper, we characterized the salivary microbiome of 255 healthy women of reproductive age using an in-depth questionnaire and self-sampling kits. Using the large metadata set, we were able to investigate the associations of several host-related and lifestyle variables with the salivary microbiome profiles. Our study shows a high preservation between individuals.

Expanded microbiome niches of RAG-deficient patients

The complex interplay between microbiota and immunity is important to human health. To explore how altered adaptive immunity influences the microbiome, we characterize skin, nares, and gut microbiota of patients with recombination-activating gene (RAG) deficiency-a rare genetically defined inborn error of immunity (IEI) that results in a broad spectrum of clinical phenotypes. Integrating de novo assembly of metagenomes from RAG-deficient patients with reference genome catalogs provides an expansive multi-kingdom view of microbial diversity. RAG-deficient patient microbiomes exhibit inter-individual variation, including expansion of opportunistic pathogens (e.g., Corynebacterium bovis, Haemophilus influenzae), and a relative loss of body site specificity. We identify 35 and 27 bacterial species derived from skin/nares and gut microbiomes, respectively, which are distinct to RAG-deficient patients compared to healthy individuals. Underscoring IEI patients as potential reservoirs for viral persistence and evolution, we further characterize the colonization of eukaryotic RNA viruses (e.g., Coronavirus 229E, Norovirus GII) in this patient population.

Overview of data preprocessing for machine learning applications in human microbiome research

Although metagenomic sequencing is now the preferred technique to study microbiome-host interactions, analyzing and interpreting microbiome sequencing data presents challenges primarily attributed to the statistical specificities of the data (e.g., sparse, over-dispersed, compositional, inter-variable dependency). This mini review explores preprocessing and transformation methods applied in recent human microbiome studies to address microbiome data analysis challenges. Our results indicate a limited adoption of transformation methods targeting the statistical characteristics of microbiome sequencing data. Instead, there is a prevalent usage of relative and normalization-based transformations that do not specifically account for the specific attributes of microbiome data. The information on preprocessing and transformations applied to the data before analysis was incomplete or missing in many publications, leading to reproducibility concerns, comparability issues, and questionable results. We hope this mini review will provide researchers and newcomers to the field of human microbiome research with an up-to-date point of reference for various data transformation tools and assist them in choosing the most suitable transformation method based on their research questions, objectives, and data characteristics.

Comprehensive microbiome causal mediation analysis using MiMed on user-friendly web interfaces

It is a central goal of human microbiome studies to see the roles of the microbiome as a mediator that transmits environmental, behavioral, or medical exposures to health or disease outcomes. Yet, mediation analysis is not used as much as it should be. One reason is because of the lack of carefully planned routines, compilers, and automated computing systems for microbiome mediation analysis (MiMed) to perform a series of data processing, diversity calculation, data normalization, downstream data analysis, and visualizations. Many researchers in various disciplines (e.g. clinicians, public health practitioners, and biologists) are not also familiar with related statistical methods and programming languages on command-line interfaces. Thus, in this article, we introduce a web cloud computing platform, named as MiMed, that enables comprehensive MiMed on user-friendly web interfaces. The main features of MiMed are as follows. First, MiMed can survey the microbiome in various spheres (i) as a whole microbial ecosystem using different ecological measures (e.g. alpha- and beta-diversity indices) or (ii) as individual microbial taxa (e.g. phyla, classes, orders, families, genera, and species) using different data normalization methods. Second, MiMed enables covariate-adjusted analysis to control for potential confounding factors (e.g. age and gender), which is essential to enhance the causality of the results, especially for observational studies. Third, MiMed enables a breadth of statistical inferences in both mediation effect estimation and significance testing. Fourth, MiMed provides flexible and easy-to-use data processing and analytic modules and creates nice graphical representations. Finally, MiMed employs ChatGPT to search for what has been known about the microbial taxa that are found significantly as mediators using artificial intelligence technologies. For demonstration purposes, we applied MiMed to the study on the mediating roles of oral microbiome in subgingival niches between e-cigarette smoking and gingival inflammation. MiMed is freely available on our web server (http://mimed.micloud.kr).

Investigating the Association Between Fusobacterium nucleatum and Oral Squamous Cell Carcinoma: A Pilot Case-Control Study on Tissue Samples

Background Fusobacterium nucleatum (F. nucleatum) has been increasingly linked to oral squamous cell carcinoma (OSCC), prompting this study to explore its presence using polymerase chain reaction (PCR) and evaluate its clinical significance. Methods In this pilot case-control study, 12 OSCC tissue samples and 12 non-cancerous oral mucosal tissue samples were analyzed. Total RNA extraction and complementary DNA (cDNA) synthesis were performed using Trizol-based methods, followed by PCR amplification and gel electrophoresis. The clinical characteristics of participants and PCR results were recorded. Results Among the OSCC tissue samples, three out of 12 tested positive for F. nucleatum, while none of the control samples showed its presence. The detection rate of F. nucleatum in OSCC was 25%. Gel analysis confirmed specific amplicon amplification, and ImageJ software enabled copy number quantification. Discussion Our findings support previous research indicating a potential association between F. nucleatum and OSCC. Understanding the etiological significance of F. nucleatum in OSCC has clinical implications, including early detection, risk stratification, and prognostication. However, the limited sample size and the need for further research to elucidate underlying mechanisms are acknowledged. Conclusion This pilot study provides initial evidence of F. nucleatum's presence in a subset of OSCC samples, supporting its potential association with oral cancer. Detecting F. nucleatum in OSCC tissues holds promise for future research and clinical applications as a diagnostic and prognostic biomarker. Understanding its role in oral carcinogenesis will facilitate the development of targeted therapeutic strategies. Larger studies are warranted to validate these findings and investigate the precise mechanisms involved.

A prospective randomized clinical trial to assess antibiotic pocket irrigation on tissue expander breast reconstruction

Bacterial infection is the most common complication following staged post-mastectomy breast reconstruction initiated with a tissue expander (TE). To limit bacterial infection, antibiotic irrigation of the surgical site is commonly performed despite little high-quality data to support this practice. We performed a prospective randomized control trial to compare the impact of saline irrigation alone to a triple antibiotic irrigation regimen (1 g cefazolin, 80 mg gentamicin, and 50,000 units of bacitracin in 500 mL of saline) for breast implant surgery. The microbiome in breasts with cancer (n = 16) was compared to those without (n = 16), as all patients (n = 16) had unilateral cancers but bilateral mastectomies (n = 32). Biologic and prosthetic specimens procured both at the time of mastectomy and during TE removal months later were analyzed for longitudinal comparison. Outcomes included clinical infection, bacterial abundance, and relative microbiome composition. No patient in either group suffered a reconstructive failure or developed an infection. Triple antibiotic irrigation administered at the time of immediate TE reconstruction did not reduce bacterial abundance or impact microbial diversity relative to saline irrigation at the time of planned exchange. Implanted prosthetic material adopted the microbial composition of the surrounding host tissue. In cancer-naïve breasts, relative to saline, antibiotic irrigation increased bacterial abundance on periprosthetic capsules (P = 0.03) and acellular dermal matrices (P = 0.04) and altered the microbiota on both. These data show that, relative to saline only, the use of triple antibiotic irrigation in TE breast reconstruction does impact the bacterial abundance and diversity of certain biomaterials from cancer-naïve breasts. IMPORTANCE The lifetime risk of breast cancer is ~13% in women and is treated with a mastectomy in ~50% of cases. The majority are reconstructed, usually starting with a tissue expander to help restore the volume for a subsequent permanent breast implant or the women's own tissues. The biopsychosocial benefits of breast reconstruction, though, can be tempered by a high complication rate of at least 7% but over 30% in some women. Bacterial infection is the most common complication, and can lead to treatment delays, patient physical and emotional distress and escalating health care cost. To limit this risk, plastic surgeons have tried a variety of strategies to limit bacterial infection including irrigating the pocket created after removing the breast implant with antibiotic solutions, but good-quality data are scarce. Herein, we study the value of antibiotics in pocket irrigation using a robust randomized clinical trial design and molecular microbiology approaches.

Finding Novel AMPs Secreted from the Human Microbiome as Potent Antibacterial and Antibiofilm Agents and Studying Their Synergistic Activity with Ag NCs

Due to the enhanced resistance of bacteria to antibiotics, researchers always try to find effective alternatives to treat drug-resistant bacterial infections. In this context, we have explored antimicrobial peptides (AMPs), which are a broad class of small peptide molecules, and investigated their efficacy as potent antibacterial and antibiofilm agents. AMPs can cause cell death either through disruption of the cell membrane or by inhibiting vital intracellular functions, by binding to RNA, DNA, or intracellular components upon transversion through the cell membrane. We attempted to find potent intracellular cationic AMPs that can demonstrate antibacterial activity through interaction with DNA. As a source of AMPs, we have utilized those that are secreted from the human microbiome with the anticipation that these will be non-toxic in nature. Out of the total 1087 AMPs, 27 were screened on the basis of amino acid length and efficacy to cross the cell membrane barrier. From the list of 27 peptides, 4 candidates were selected through the docking score of these peptides with the DNA binding domain of H2A proteins. Further, the molecular dynamics simulation analysis demonstrated that 2 AMPs, i.e., peptides 7 and 25, are having considerable membrane permeation and DNA binding ability. Further, the in vitro analysis indicated that both peptides 7 and 25 could exhibit potent antibacterial and antibiofilm activities. In order to further enhance the antibiofilm potency, the above AMPs were used as supplements to silver nanoclusters (Ag NCs) to get synergistic activity. The synergistic activity of Ag NCs was found to be significantly increased with both the above AMPs.

Blood, Gut, and Oral Microbiome in Kidney Transplant Recipients

Background and Objective

Recent reports describe the existence of a blood microbiome profile not associated with an infection state. Given the high impact that the dysbiotic human microbiome appears to have in chronic kidney disease and, in particular, in the outcome of kidney transplant recipients (KTRs), we aimed to explore the variations and correlations of the gut, oral, and blood microbiome of recipients, 3 months after kidney transplantation.

Materials and Methods

We conducted a cross-sectional study where the microbiome of stool, saliva, and blood collected from recipients 3 months after kidney transplantation (N = 6) was analyzed by polymerase chain reaction (PCR) amplification and sequencing of the V3-V4 hypervariable regions of the 16S rRNA gene using MiSeq Illumina® technology.

Results

Blood of KTRs harbors a distinct low-abundance microbiome dominated by Proteobacteria and Firmicutes. Gut and oral microbiome of KTRs also present distinct profiles. The existence of a proportion of shared operational taxonomic units among the different body sites is reported, mainly classified as Proteobacteria and Firmicutes.

Conclusions

This study provides evidence of existence a blood microbiome in KTRs, different from the gut and the oral microbiome profiles, with a small number of operational taxonomic units representing a shared microbiome. The clinical relevance of this observation should be further explored in these patients.

Leveraging the human microbiota to target bacterial respiratory pathogens: new paths toward an expanded antimicrobial armamentarium

Acute respiratory infections are the most frequent infections across the lifespan and are the leading infectious cause of death among children globally. Bacterial respiratory infections are routinely treated with antibiotics, nearly all of which are derived from microbial natural products. Unfortunately, antibiotic-resistant bacteria are an increasingly frequent cause of respiratory infections, and there are few new antibiotics in development that target these pathogens. In the article by Stubbendieck et al., the authors identified Rothia species that demonstrate in vitro and ex vivo growth inhibition of the respiratory pathobiont Moraxella catarrhalis. The authors present experiments suggesting that this activity is mediated at least in part through the secretion of a novel peptidoglycan endopeptidase that targets the M. catarrhalis cell wall. In this commentary, we discuss these findings in the context of the urgent threat of antimicrobial resistance and highlight the promise of the human respiratory microbiota as a source of novel biotherapeutics.

Urinary Plasmids Reduce Permissivity to Coliphage Infection

The microbial community of the urinary tract (urinary microbiota or urobiota) has been associated with human health. Bacteriophages (phages) and plasmids present in the urinary tract, like in other niches, may shape urinary bacterial dynamics. While urinary Escherichia coli strains associated with urinary tract infection (UTI) and their phages have been catalogued for the urobiome, bacterium-plasmid-phage interactions have yet to be explored. In this study, we characterized urinary E. coli plasmids and their ability to decrease permissivity to E. coli phage (coliphage) infection. Putative F plasmids were predicted in 47 of 67 urinary E. coli isolates, and most of these plasmids carried genes that encode toxin-antitoxin (TA) modules, antibiotic resistance, and/or virulence. Urinary E. coli plasmids, from urinary microbiota strains UMB0928 and UMB1284, were conjugated into E. coli K-12 strains. These transconjugants included genes for antibiotic resistance and virulence, and they decreased permissivity to coliphage infection by the laboratory phage P1vir and the urinary phages Greed and Lust. Plasmids in one transconjugant were maintained in E. coli K-12 for up to 10 days in the absence of antibiotic resistance selection; this included the maintenance of the antibiotic resistance phenotype and decreased permissivity to phage. Finally, we discuss how F plasmids present in urinary E. coli strains could play a role in coliphage dynamics and the maintenance of antibiotic resistance in urinary E. coli. IMPORTANCE The urinary tract contains a resident microbial community called the urinary microbiota or urobiota. Evidence exists that it is associated with human health. Bacteriophages (phages) and plasmids present in the urinary tract, like in other niches, may shape urinary bacterial dynamics. Bacterium-plasmid-phage interactions have been studied primarily in laboratory settings and are yet to be thoroughly tested in complex communities. This is especially true of the urinary tract, where the bacterial genetic determinants of phage infection are not well understood. In this study, we characterized urinary E. coli plasmids and their ability to decrease permissivity to E. coli phage (coliphage) infection. Urinary E. coli plasmids, encoding antibiotic resistance and transferred by conjugation into naive laboratory E. coli K-12 strains, decreased permissivity to coliphage infection. We propose a model by which urinary plasmids present in urinary E. coli strains could help to decrease phage infection susceptibility and maintain the antibiotic resistance of urinary E. coli. This has consequences for phage therapy, which could inadvertently select for plasmids that encode antibiotic resistance.

Dissecting Microbiome-Derived SCFAs in Prostate Cancer: Analyzing Gut Microbiota, Racial Disparities, and Epigenetic Mechanisms

Prostate cancer (PCa) continues to be the most diagnosed cancer and the second primary cause of fatalities in men globally. There is an abundance of scientific evidence suggesting that the human microbiome, together with its metabolites, plays a crucial role in carcinogenesis and has a significant impact on the efficacy of anticancer interventions in solid and hematological cancers. These anticancer interventions include chemotherapy, immune checkpoint inhibitors, and targeted therapies. Furthermore, the microbiome can influence systemic and local immune responses using numerous metabolites such as short-chain fatty acids (SCFAs). Despite the lack of scientific data in terms of the role of SCFAs in PCa pathogenesis, recent studies show that SCFAs have a profound impact on PCa progression. Several studies have reported racial/ethnic disparities in terms of bacterial content in the gut microbiome and SCFA composition. These studies explored microbiome and SCFA racial/ethnic disparities in cancers such as colorectal, colon, cervical, breast, and endometrial cancer. Notably, there are currently no published studies exploring microbiome/SCFA composition racial disparities and their role in PCa carcinogenesis. This review discusses the potential role of the microbiome in PCa development and progression. The involvement of microbiome-derived SCFAs in facilitating PCa carcinogenesis and their effect on PCa therapeutic response, particularly immunotherapy, are discussed. Racial/ethnic differences in microbiome composition and SCFA content in various cancers are also discussed. Lastly, the effects of SCFAs on PCa progression via epigenetic modifications is also discussed.

Profiling novel lateral gene transfer events in the human microbiome

Lateral gene transfer (LGT) is an important mechanism for genome diversification in microbial populations, including the human microbiome. While prior work has surveyed LGT events in human-associated microbial isolate genomes, the scope and dynamics of novel LGT events arising in personal microbiomes are not well understood, as there are no widely adopted computational methods to detect, quantify, and characterize LGT from complex microbial communities. We addressed this by developing, benchmarking, and experimentally validating a computational method (WAAFLE) to profile novel LGT events from assembled metagenomes. Applying WAAFLE to >2K human metagenomes from diverse body sites, we identified >100K putative high-confidence but previously uncharacterized LGT events (~2 per assembled microbial genome-equivalent). These events were enriched for mobile elements (as expected), as well as restriction-modification and transport functions typically associated with the destruction of foreign DNA. LGT frequency was quantifiably influenced by biogeography, the phylogenetic similarity of the involved taxa, and the ecological abundance of the donor taxon. These forces manifest as LGT networks in which hub species abundant in a community type donate unequally with their close phylogenetic neighbors. Our findings suggest that LGT may be a more ubiquitous process in the human microbiome than previously described. The open-source WAAFLE implementation, documentation, and data from this work are available at http://huttenhower.sph.harvard.edu/waafle.

Rare phylotypes in stone, stool, and urine microbiomes are associated with urinary stone disease

Introduction: In complex microbial communities, the importance of microbial species at very low abundance levels and their prevalence for overall community structure and function is increasingly being recognized. Clinical microbiome studies on urinary stone disease (USD) have indicated that both the gut and urinary tract microbiota are associated with the onset of the disease and that kidney stones them-selves harbor a complex, yet consistent and viable, microbiome. However, how rare phylotypes contribute to this association remains unclear. Delineating the contribution of rare and common phylotypes to urinary stone disease is important for the development of bacteriotherapies to promote urologic health. Methods: The objectives of the current report were to conduct a metaanalysis of 16S rRNA datasets derived from the kidney stone, stool, and urine samples of participants with or without urinary stone disease. To delineate the impact of rare and common phylotypes, metaanalyses were conducted by first separating rare and common taxa determined by both the frequency and abundance of amplicon sequence variants. Results: Consistent with previous analyses, we found that gut, upper urinary, and lower urinary tract microbiomes were all unique. Rare phylotypes comprised the majority of species observed in all sample types, with kidney stones exhibiting the greatest bias toward rarity, followed by urine and stool. Both rare and common fractions contributed significantly to the differences observed between sample types and health disparity. Furthermore, the rare and common fractions were taxonomically unique across all sample types. A total of 222 and 320 unique rare phylotypes from urine and stool samples were found to be significantly associated with USD. A co-occurrence correlation analysis revealed that rare phylotypes are most important for microbiome structure in stones, followed by urine and stool. Discussion: Collectively, the results indicate that rare phylotypes may be important for the pathophysiology of USD, particularly in the kidney stone matrix, which is inherently a very low microbial biomass niche that can have implications for the diagnosis and treatment of kidney stones. Further studies are needed to investigate the functional significance of rare phylotypes in kidney stone pathogenesis.

COVID-19 alters human microbiomes: a meta-analysis

Introduction

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has infected a substantial portion of the world's population, and novel consequences of COVID-19 on the human body are continuously being uncovered. The human microbiome plays an essential role in host health and well-being, and multiple studies targeting specific populations have reported altered microbiomes in patients infected with SARS-CoV-2. Given the global scale and massive incidence of COVID on the global population, determining whether the effects of COVID-19 on the human microbiome are consistent and generalizable across populations is essential.

Methods

We performed a synthesis of human microbiome responses to COVID-19. We collected 16S rRNA gene amplicon sequence data from 11 studies sampling the oral and nasopharyngeal or gut microbiome of COVID-19-infected and uninfected subjects. Our synthesis included 1,159 respiratory (oral and nasopharyngeal) microbiome samples and 267 gut microbiome samples from patients in 11 cities across four countries.

Results

Our reanalyses revealed communitywide alterations in the respiratory and gut microbiomes across human populations. We found significant overall reductions in the gut microbial diversity of COVID-19-infected patients, but not in the respiratory microbiome. Furthermore, we found more consistent community shifts in the gut microbiomes of infected patients than in the respiratory microbiomes, although the microbiomes in both sites exhibited higher host-to-host variation in infected patients. In respiratory microbiomes, COVID-19 infection resulted in an increase in the relative abundance of potentially pathogenic bacteria, including Mycoplasma.

Discussion

Our findings shed light on the impact of COVID-19 on the human-associated microbiome across populations, and highlight the need for further research into the relationship between long-term effects of COVID-19 and altered microbiota.

Preliminary landscape of Candidatus Saccharibacteria in the human microbiome

Introduction

Candidate Phyla Radiation (CPR) and more specifically Candidatus Saccharibacteria (TM7) have now been established as ubiquitous members of the human oral microbiota. Additionally, CPR have been reported in the gastrointestinal and urogenital tracts. However, the exploration of new human niches has been limited to date.

Methods

In this study, we performed a prospective and retrospective screening of TM7 in human samples using standard PCR, real-time PCR, scanning electron microscopy (SEM) and shotgun metagenomics.

Results

Using Real-time PCR and standard PCR, oral samples presented the highest TM7 prevalence followed by fecal samples, breast milk samples, vaginal samples and urine samples. Surprisingly, TM7 were also detected in infectious samples, namely cardiac valves and blood cultures at a low prevalence (under 3%). Moreover, we observed CPR-like structures using SEM in all sample types except cardiac valves. The reconstruction of TM7 genomes in oral and fecal samples from shotgun metagenomics reads further confirmed their high prevalence in some samples.

Conclusion

This study confirmed, through their detection in multiple human samples, that TM7 are human commensals that can also be found in clinical settings. Their detection in clinical samples warrants further studies to explore their role in a pathological setting.

How Can the Microbiome Induce Carcinogenesis and Modulate Drug Resistance in Cancer Therapy?

Over the years, cancer has been affecting the lives of many people globally and it has become one of the most studied diseases. Despite the efforts to understand the cell mechanisms behind this complex disease, not every patient seems to respond to targeted therapies or immunotherapies. Drug resistance in cancer is one of the limiting factors contributing to unsuccessful therapies; therefore, understanding how cancer cells acquire this resistance is essential to help cure individuals affected by cancer. Recently, the altered microbiome was observed to be an important hallmark of cancer and therefore it represents a promising topic of cancer research. Our review aims to provide a global perspective of some cancer hallmarks, for instance how genetic and epigenetic modifications may be caused by an altered human microbiome. We also provide information on how an altered human microbiome can lead to cancer development as well as how the microbiome can influence drug resistance and ultimately targeted therapies. This may be useful to develop alternatives for cancer treatment, i.e., future personalized medicine that can help in cases where traditional cancer treatment is unsuccessful.

Pragmatic Considerations When Extracting DNA for Metagenomics Analyses of Clinical Samples

Microbiome analyses are essential for understanding microorganism composition and diversity, but interpretation is often challenging due to biological and technical variables. DNA extraction is a critical step that can significantly bias results, particularly in samples containing a high abundance of challenging-to-lyse microorganisms. Taking into consideration the distinctive microenvironments observed in different bodily locations, our study sought to assess the extent of bias introduced by suboptimal bead-beating during DNA extraction across diverse clinical sample types. The question was whether complex targeted extraction methods are always necessary for reliable taxonomic abundance estimation through amplicon sequencing or if simpler alternatives are effective for some sample types. Hence, for four different clinical sample types (stool, cervical swab, skin swab, and hospital surface swab samples), we compared the results achieved from extracting targeted manual protocols routinely used in our research lab for each sample type with automated protocols specifically not designed for that purpose. Unsurprisingly, we found that for the stool samples, manual extraction protocols with vigorous bead-beating were necessary in order to avoid erroneous taxa proportions on all investigated taxonomic levels and, in particular, false under- or overrepresentation of important genera such as Blautia, Faecalibacterium, and Parabacteroides. However, interestingly, we found that the skin and cervical swab samples had similar results with all tested protocols. Our results suggest that the level of practical automation largely depends on the expected microenvironment, with skin and cervical swabs being much easier to process than stool samples. Prudent consideration is necessary when extending the conclusions of this study to applications beyond rough estimations of taxonomic abundance.

Prenatal lead exposure is negatively associated with the gut microbiome in childhood

Background

Metal exposures are associated with gut microbiome (GM) composition and function, and exposures early in development may be particularly important. Considering the role of the GM in association with many adverse health outcomes, understanding the relationship between prenatal metal exposures and the GM is critically important. However, there is sparse knowledge of the association between prenatal metal exposure and GM later in childhood.

Objectives

This analysis aims to identify associations between prenatal lead (Pb) exposure and GM composition and function in children 9-11 years old.

Methods

Data come from the Programming Research in Obesity, Growth, Environment and Social Stressors (PROGRESS) cohort based in Mexico City, Mexico. Prenatal metal concentrations were measured in maternal whole blood drawn during the second and third trimesters of pregnancy. Stool samples collected at 9-11 years old underwent metagenomic sequencing to assess the GM. This analysis uses multiple statistical modeling approaches, including linear regression, permutational analysis of variance, weighted quantile sum regression (WQS), and individual taxa regressions, to estimate the association between maternal blood Pb during pregnancy and multiple aspects of the child GM at 9-11 years old, adjusting for relevant confounders.

Results

Of the 123 child participants in this pilot data analysis, 74 were male and 49 were female. Mean prenatal maternal blood Pb was 33.6 (SE = 2.1) ug/L and 34.9 (SE = 2.1) ug/L at second and third trimesters, respectively. Analysis suggests a consistent negative relationship between prenatal maternal blood Pb and the GM at age 9-11, including measures of alpha and beta diversity, microbiome mixture analysis, and individual taxa. The WQS analysis showed a negative association between prenatal Pb exposure and the gut microbiome, for both second and third trimester exposures (2Tβ = -0.17, 95%CI = [-0.46,0.11]; 3Tβ = -0.17, 95%CI = [-0.44,0.10]). Ruminococcus gnavus, Bifidobacterium longum, Alistipes indistinctus, Bacteroides caccae, and Bifidobacterium bifidum all had weights above the importance threshold from 80% or more of the WQS repeated holdouts in association with both second and third trimester Pb exposure.

Discussion

Pilot data analysis suggests a negative association between prenatal Pb exposure and the gut microbiome later in childhood; however, additional investigation is needed.

Comparison of gut microbiome composition in colonic biopsies, endoscopically-collected and at-home-collected stool samples

Aim

The goal of this study is to compare microbiome composition in three different sample types in women, namely stool brought from home vs. solid stool samples obtained at the time of an unprepped sigmoidoscopy vs. biopsies of the colonic mucosa at the time of an unprepped sigmoidoscopy, using alpha- and beta-diversity metrics following bacterial 16S rRNA sequencing. The findings may have relevance to health and disease states in which bacterial metabolism has a significant impact on molecules/metabolites that are recirculated between the gut lumen and mucosa and systemic circulation, such as estrogens (as in breast cancer) or bile acids.

Methods

Concomitant at-home-collected stool, endoscopically-collected stool, and colonic biopsy samples were collected from 48 subjects (24 breast cancer, 24 control.) After 16S rRNA sequencing, an amplicon sequence variant (ASV) based approach was used to analyze the data. Alpha diversity metrics (Chao1, Pielou's Evenness, Faith PD, Shannon, and Simpson) and beta diversity metrics (Bray-Curtis, Weighted and Unweighted Unifrac) were calculated. LEfSe was used to analyze differences in the abundance of various taxa between sample types.

Results

Alpha and beta diversity metrics were significantly different between the three sample types. Biopsy samples were different than stool samples in all metrics. The highest variation in microbiome diversity was noted in the colonic biopsy samples. At-home and endoscopically-collected stool showed more similarities in count-based and weighted beta diversity metrics. There were significant differences in rare taxa and phylogenetically-diverse taxa between the two types of stool samples. Generally, there were higher levels of Proteobacteria in biopsy samples, with significantly more Actinobacteria and Firmicutes in stool (all p < 0.001, q-value < 0.05). Overall, there was a significantly higher relative abundance of Lachnospiraceae and Ruminococcaceae in stool samples (at-home collected and endoscopically-collected) and higher abundances of Tisserellaceae in biopsy samples (all p < 0.001, q-value < 0.05).

Conclusion

Our data shows that different sampling methods can impact results when looking at the composition of the gut microbiome using ASV-based approaches.

Advances in the clinical use of metaproteomics

INTRODUCTION

Investigating the taxonomic and functional composition of human microbiomes can aid in the understanding of disease etiologies, diagnosis, and therapy monitoring for several diseases, including inflammatory bowel disease or obesity. One method for microbiome monitoring is metaproteomics, which assesses human and microbial proteins and thus enables the study of host-microbiome interactions. This advantage led to increased interest in metaproteome analyses and significant developments to introduce this method into a clinical context.

AREAS COVERED

This review summarizes the recent progress from a technical side and an application-related point of view.

EXPERT OPINION

Numerous publications imply the massive potential of metaproteomics to impact human health care. However, the key challenges of standardization and validation of experimental and bioinformatic workflows and accurate quantification methods must be overcome.

Bacterial extracellular electron transfer in plant and animal ecosystems

Extracellular electron transfer (EET) is a bioelectrochemical process performed by electrochemically active bacteria (EAB) found in host-associated environments, including plant and animal ecosystems and fermenting plant- and animal-derived foods. Through direct or mediated electron transfer pathways, certain bacteria use EET to enhance ecological fitness with host-impacting effects. In the plant rhizosphere, electron acceptors support the growth of EAB such as members of the Geobacter, cable bacteria, and some clostridia with the capacity to influence iron and heavy metal uptake by plants. In animal microbiomes, EET is associated with diet-derived iron in the intestines of soil-dwelling termites, earthworms, and beetle larvae. EET is also associated with the colonization and metabolism of some bacteria in human and animal microbiomes, such as Streptococcus mutans in the mouth, Enterococcus faecalis and Listeria monocytogenes in the intestine, and Pseudomonas aeruginosa in the lungs. During the fermentation of plant tissues and bovine milk, lactic acid bacteria like Lactiplantibacillus plantarum and Lactococcus lactis may use EET to increase their growth and food acidification, as well as decrease environmental oxidation-reduction potential. EET is thus likely an important metabolic pathway for host-associated bacteria and has implications for ecosystem function, health and disease, and biotechnological applications.

Prenatal Lead Exposure is Negatively Associated with the Gut Microbiome in Childhood

Background

Metal exposures are associated with gut microbiome (GM) composition and function, and exposures early in development may be particularly important. Considering the role of the GM in association with many adverse health outcomes, understanding the relationship between prenatal metal exposures and the GM is critically important. However, there is sparse knowledge of the association between prenatal metal exposure and GM later in childhood.

Objectives

This analysis aims to identify associations between prenatal lead (Pb) exposure and GM composition and function in children 9-11 years old.

Methods

Data come from the Programming Research in Obesity, Growth, Environment and Social Stressors (PROGRESS) cohort based in Mexico City, Mexico. Prenatal metal concentrations were measured in maternal whole blood drawn during the second and third trimesters of pregnancy. Stool samples collected at 9-11 years old underwent metagenomic sequencing to assess the GM. This analysis uses multiple statistical modeling approaches, including linear regression, permutational analysis of variance, weighted quantile sum regression (WQS), and individual taxa regressions, to estimate the association between maternal blood Pb during pregnancy and multiple aspects of the child GM at 9-11 years old, adjusting for relevant confounders.

Results

Of the 123 child participants in this pilot data analysis, 74 were male and 49 were female. Mean prenatal maternal blood Pb was 33.6(SE=2.1) ug/L and 34.9(SE=2.1) ug/L at second and third trimesters, respectively. Analysis suggests a consistent negative relationship between prenatal maternal blood Pb and the GM at age 9-11, including measures of alpha and beta diversity, microbiome mixture analysis, and individual taxa. The WQS analysis showed a negative association between prenatal Pb exposure and the gut microbiome, for both second and third trimester exposures (2Tβ=-0.17,95%CI=[-0.46,0.11]; 3Tβ=-0.17,95%CI=[-0.44,0.10]). Ruminococcus gnavus, Bifidobacterium longum, Alistipes indistinctus, Bacteroides caccae, and Bifidobacterium bifidum all had weights above the importance threshold from 80% or more of the WQS repeated holdouts in association with both second and third trimester Pb exposure.

Discussion

Pilot data analysis suggests a negative association between prenatal Pb exposure and the gut microbiome later in childhood; however, additional investigation is needed.

Prophage rates in the human microbiome vary by body site and host health

Phages integrated into a bacterial genome-called prophages-continuously monitor the health of the host bacteria to determine when to escape the genome, protect their host from other phage infections, and may provide genes that promote bacterial growth. Prophages are essential to almost all microbiomes, including the human microbiome. However, most human microbiome studies focus on bacteria, ignoring free and integrated phages, so we know little about how these prophages affect the human microbiome. We compared the prophages identified in 11,513 bacterial genomes isolated from human body sites to characterise prophage DNA in the human microbiome. Here, we show that prophage DNA comprised an average of 1-5% of each bacterial genome. The prophage content per genome varies with the isolation site on the human body, the health of the human, and whether the disease was symptomatic. The presence of prophages promotes bacterial growth and sculpts the microbiome. However, the disparities caused by prophages vary throughout the body.