Microbiome 101: Studying, Analyzing, and Interpreting Gut Microbiome Data for Clinicians

Gut microbiome alpha diversity decreases in relation to body weight, antibiotic exposure, and infection with multidrug-resistant organisms

BACKGROUND

The human gastrointestinal tract is home to a dense and diverse microbiome, predominated by bacteria. Despite the conservation of critical functionality across most individuals, the composition of the gut microbiome is highly individualized, leading to differential responses to perturbations such as oral antibiotics or multidrug-resistant organism (MDRO) infection. Herein, subject responses to these perturbations based on their body weight were evaluated.

METHODS

Fecal samples were collected from 45 subjects at the Detroit Medical Center to evaluate the effects of perturbations on subjects' gut microbiome composition. Bacterial profiling was completed using 16S rRNA gene sequencing.

RESULTS

Subjects with multiple MDROs, subjects weighing greater than 80 kg infected with MDRO E coli, and subjects weighing less than 80 kg with exposure to vancomycin and carbapenem antibiotics during hospitalization had significantly decreased gut microbiome richness.

CONCLUSIONS

Both administration of oral antibiotics and MDRO infections decreased gut microbiome alpha diversity, but the magnitude of these gut microbiome perturbations was body weight dependent.

The effect of multiple sclerosis therapy on gut microbiota dysbiosis: a longitudinal prospective study

Gut microbiota has complex immune functions, related to different pathologies, including multiple sclerosis (MS).This study evaluated the influence of treatments on gut microbiota in people with MS (PwMS). The research comprised 60 participants, including 39 PwMS and 21 healthy controls (HC). Among the PwMS, 20 were prescribed a disease-modifying therapy (DMT), either interferon beta1a or teriflunomide, while 19 received a combination of classical DMT and an immunoglobulin Y (IgY) supplement. For each participant, two sets of gut samples were collected: one at the study's outset and another after two months. Alpha and beta diversity analyses revealed no significant differences between groups. In comparison to the HC, the MS group exhibited an increase in Prevotella stercorea and a decrease in Faecalibacterium prausnitzii. Following treatment, individuals with MS showed enrichment in Lachnospiraceae and Streptococcus. The second sample, compared to the first one, demonstrated an increase in Bifidobacterium angulatum and a decrease in Oscillospira for individuals with MS. Gut microbiota diversity in PwMS is not significantly different to HC.However, specific taxonomic changes indicate the presence of a dysbiosis state. The use of DMTs and immunoglobulin Y supplements may contribute to alterations in microbial composition, potentially leading to the restoration of a healthier microbiome.

The Gut Microbiome and Mental Health

The gut microbiome has been well researched in the past few years and may be a target for treating mental illness. Trillions of bacteria in the digestive system work with the brain, immune function, and endocrine pathways. This gut microbiome ecosystem mediates the interaction between the human being and the environment making its inclusion in holistic nursing essential. Changes in normal balance of the gut microbiome occur with diet, antibiotics and other medications, stress, cancer treatment, geography and environment, and current illnesses. When the microbiome is challenged a "dysbiotic" state leads to inadequate production of needed neurotransmitters such as serotonin and dopamine. Research has shown links between the dysbiosis, and the inflammatory response system that are known to contribute to depression, anxiety, and schizophrenia. Understanding the role of the gut microbiome can be beneficial to holistic nurses, providing a new tool to prevent, treat, or reduce symptoms of mental illness and improve general immune function. This innocuous holistic approach to mental wellness is becoming an important evidenced-based approach.

Fast detection of bacterial gut pathogens on miniaturized devices: an overview

INTRODUCTION

Gut microbes pose challenges like colon inflammation, deadly diarrhea, antimicrobial resistance dissemination, and chronic disease onset. Development of early, rapid and specific diagnosis tools is essential for improving infection control. Point-of-care testing (POCT) systems offer rapid, sensitive, low-cost and sample-to-answer methods for microbe detection from various clinical and environmental samples, bringing the advantages of portability, automation, and simple operation.

AREAS COVERED

Rapid detection of gut microbes can be done using a wide array of techniques including biosensors, immunological assays, electrochemical impedance spectroscopy, mass spectrometry and molecular biology. Inclusion of Internet of Things, machine learning, and smartphone-based point-of-care applications is an important aspect of POCT. In this review, the authors discuss various fast diagnostic platforms for gut pathogens and their main challenges.

EXPERT OPINION

Developing effective assays for microbe detection can be complex. Assay design must consider factors like target selection, real-time and multiplex detection, sample type, reagent stability and storage, primer/probe design, and optimizing reaction conditions for accuracy and sensitivity. Mitigating these challenges requires interdisciplinary collaboration among scientists, clinicians, engineers, and industry partners. Future efforts are essential to enhance sensitivity, specificity, and versatility of POCT systems for gut microbe detection and quantification, advancing infectious disease diagnostics and management.

Meta-analysis of the human gut microbiome uncovers shared and distinct microbial signatures between diseases

Microbiome studies have revealed gut microbiota's potential impact on complex diseases. However, many studies often focus on one disease per cohort. We developed a meta-analysis workflow for gut microbiome profiles and analyzed shotgun metagenomic data covering 11 diseases. Using interpretable machine learning and differential abundance analysis, our findings reinforce the generalization of binary classifiers for Crohn's disease (CD) and colorectal cancer (CRC) to hold-out cohorts and highlight the key microbes driving these classifications. We identified high microbial similarity in disease pairs like CD vs ulcerative colitis (UC), CD vs CRC, Parkinson's disease vs type 2 diabetes (T2D), and schizophrenia vs T2D. We also found strong inverse correlations in Alzheimer's disease vs CD and UC. These findings detected by our pipeline provide valuable insights into these diseases.

Gut microbiota in patients with prostate cancer: a systematic review and meta-analysis

BACKGROUND

Increasing evidence indicates that gut microbiota are closely related to prostate cancer. This study aims to assess the gut microbiota composition in patients with prostate cancer compared to healthy participants, thereby advancing understanding of gut microbiota's role in prostate cancer.

METHODS

A systematic search was conducted across PubMed, Web of Science, and Embase databases, in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The methodological quality of included studies was evaluated using the Newcastle-Ottawa Scale (NOS), and pertinent data were analyzed. The kappa score assessed interrater agreement.

RESULTS

This study encompassed seven research papers, involving 250 prostate cancer patients and 192 controls. The kappa was 0.93. Meta-analysis results showed that alpha-diversity of gut microbiota in prostate cancer patients was significantly lower than in the control group. In terms of gut microbiota abundance, the ratio of Proteobacteria, Bacteroidia, Clostridia, Bacteroidales, Clostridiales, Prevotellaceae, Lachnospiraceae, Prevotella, Escherichia-Shigella, Faecalibacterium, and Bacteroides was higher in prostate cancer patients. Conversely, the abundance ratio of Actinobacteria, Bacteroidetes, Firmicutes, Selenomonadales, Veillonella, and Megasphaera was higher in the control group.

CONCLUSION

Our study reveals differences in alpha-diversity and abundance of gut microbiota between patients with prostate cancer and controls, indicating gut microbiota dysbiosis in those with prostate cancer. However, given the limited quality and quantity of selected studies, further research is necessary to validate these findings.

A common trajectory of gut microbiome development during the first month in healthy neonates with limited inter-individual environmental variations

The early development of the gut microbiome is governed by multiple factors and has significantly long-term effects on later-in-life health. To minimize inter-individual variations in the environment, we determined developmental trajectories of the gut microbiome in 28 healthy neonates during their stay at a postpartum center. Stool samples were collected at three time points: the first-pass meconium within 24 h of life, and at 7 and 28 days of age. Illumina sequencing of the V3-V4 region of 16S rRNA was used to investigate microbiota profiles. We found that there was a distinct microbiota structure at each time point, with a significant shift during the first week. Proteobacteria was most abundant in the first-pass meconium; Firmicutes and Actinobacteria increased with age and were substituted as the major components. Except for a short-term influence of different delivery modes on the microbiota composition, early microbiome development was not remarkably affected by gravidity, maternal intrapartum antibiotic treatment, premature rupture of membranes, or postnatal phototherapy. Hence, our data showed a similar developmental trajectory of the gut microbiome during the first month in healthy neonates when limited in environmental variations. Environmental factors external to the host were crucial in the early microbiome development.

Gut Microbiome Changes in Anorexia Nervosa: A Comprehensive Review

Anorexia nervosa (AN) remains a challenging condition in psychiatric management and its pathogenesis is not yet fully understood. An imbalance in the gut microbiota composition may contribute to its pathophysiology. This review aims to explore the link between the human gut microbiota and AN (objective 1) or refeeding syndrome in AN (objective 2). The online databases MEDLINE and PsycINFO were searched for relevant studies. A total of 14 studies met the inclusion and exclusion criteria and only answered objective 1. A total of 476 AN patients, 554 healthy-weight (HC) controls, and 0 patients with other psychiatric disorders were included. Compared to HC, there were consistently reduced abundances of Faecalibacterium prausnitzii and Roseburia inulinivorans, and increased Methanobrevibacter smithii, in AN patients. Changes in alpha diversity were inconsistent, while beta diversity increased in four of six studies. Our model suggests that an imbalance in gut microbiota composition leads to reduced short-chain fatty acids, contributing to a proinflammatory state in AN, which is also common in other psychiatric comorbidities. Microbial changes may also contribute to the semistarvation state through endocrine changes and altered energy utilization.

What if gastrointestinal complications in endurance athletes were gut injuries in response to a high consumption of ultra-processed foods? Please take care of your bugs if you want to improve endurance performance: a narrative review

To improve performance and recovery faster, athletes are advised to eat more often than usual and consume higher doses of simple carbohydrates, during and after exercise. Sports energetic supplements contain food additives, such as artificial sweeteners, emulsifiers, acidity regulators, preservatives, and salts, which could be harmful to the gut microbiota and impair the intestinal barrier function. The intestinal barrier plays a critical function in bidirectionally regulation of the selective transfer of nutrients, water, and electrolytes, while preventing at the same time, the entrance of harmful substances (selective permeability). The gut microbiota helps to the host to regulate intestinal homeostasis through metabolic, protective, and immune functions. Globally, the gut health is essential to maintain systemic homeostasis in athletes, and to ensure proper digestion, metabolization, and substrate absorption. Gastrointestinal complaints are an important cause of underperformance and dropout during endurance events. These complications are directly related to the loss of gut equilibrium, mainly linked to microbiota dysbiosis and leaky gut. In summary, athletes must be cautious with the elevated intake of ultra-processed foods and specifically those contained on sports nutrition supplements. This review points out the specific nutritional interventions that should be implemented and/or discontinued depending on individual gut functionality.

Decentralized ORP Measurements for Gut Redox Status Monitoring: Toward Personalized Gut Microbiota Balance

Gut microbiome targeting has emerged as a new generation of personalized medicine and a potential wellness and disease driver. Specifically, the gut redox balance plays a key role in shaping the gut microbiota and its link with the host, immune system, and disease evolution. In this sense, precise and personalized nutrition has proven synergy and capability to modulate the gut microbiome environment through the formulation of dietary interventions, such as vitamin support. Accordingly, there are urgent demands for simple and effective analytical platforms for understanding the relationship between the tailored vitamin administration and the gut microbiota balance by rapid noninvasive on-the-spot oxidation/reduction potential monitoring for frequent and close surveillance of the gut redox status and targeting by personalized nutrition interventions. Herein, we present a disposable potentiometric sensor chip and a homemade multiwell potentiometric array to address the interplay of vitamin levels with the oxidation/reduction potential in human feces and saliva. The potentiometric ORP sensing platforms have been successfully validated and scaled up for the setup of a multiapplication prototype for cross-talk-free simple screening of many specimens. The interpersonal variability of the gut microbiota environment illustrates the potential of feces and saliva samples for noninvasive, frequent, and decentralized monitoring of the gut redox status to support timely human microbiota surveillance and guide precise dietary intervention toward restoring and promoting personalized gut redox balance.

The intersection of social determinants of health, the microbiome, and health outcomes in immigrants: A scoping review

In the present scoping review, we explore whether existing evidence supports the premise that social determinants of health (SDoH) affect immigrant health outcomes through their effects on the microbiome. We adapt the National Institute on Minority Health and Health Disparities' research framework to propose a conceptual model that considers the intersection of SDoH, the microbiome, and health outcomes in immigrants. We use this conceptual model as a lens through which to explore recent research about SDoH, biological factors associated with changes to immigrants' microbiomes, and long-term health outcomes. In the 17 articles reviewed, dietary acculturation, physical activity, ethnicity, birthplace, age at migration and length of time in the host country, socioeconomic status, and social/linguistic acculturation were important determinants of postmigration microbiome-related transformations. These factors are associated with progressive shifts in microbiome profile with time in host country, increasing the risks for cardiometabolic, mental, immune, and inflammatory disorders and antibiotic resistance. The evidence thus supports the premise that SDoH influence immigrants' health postmigration, at least in part, through their effects on the microbiome. Omission of important postmigration social-ecological variables (e.g., stress, racism, social/family relationships, and environment), limited research among minoritized subgroups of immigrants, complexity and inter- and intra-individual differences in the microbiome, and limited interdisciplinary and biosocial collaboration restrict our understanding of this area of study. To identify potential microbiome-based interventions and promote immigrants' well-being, more research is necessary to understand the intersections of immigrant health with factors from the biological, behavioral/psychosocial, physical/built environment, and sociocultural environment domains at all social-ecological levels.

Cannabis and Endometriosis: The Roles of the Gut Microbiota and the Endocannabinoid System

Endometriosis, a chronic condition affecting around 10-14% of women, is challenging to manage, due to its complex pathogenesis and limited treatment options. Research has suggested a potential role of the gut microbiota and the endocannabinoid system in the development and progression of endometriosis. This narrative review aims to explore the role of, and any potential interactions between, the endocannabinoid system (ECS) and the gut microbiota in endometriosis. This review found that both the ECS and microbiota influence endometriosis, with the former regulating inflammation and pain perception and the latter influencing immune responses and hormonal balance. There is evidence that a dysregulation of the endocannabinoid system and the gut microbiota influence endometriosis symptoms and progression via changes in CB1 receptor expression and increased circulating levels of endocannabinoids. Microbial imbalances in the gut, such as increases in Prevotella, have been directly correlated to increased bloating, a common endometriosis symptom, while increases in E. coli have supported the bacterial contamination hypothesis as a potential pathway for endometriosis pathogenesis. These microbial imbalances have been correlated with increases in inflammatory markers such as TNF-α and IL-6, both often raised in those with endometriosis. Protective effects of the ECS on the gut were observed by increases in endocannabinoids, including 2-AG, resulting in decreased inflammation and improved gut permeability. Given these findings, both the ECS and the gut microbiota may be targets for therapeutic interventions for endometriosis; however, clinical studies are required to determine effectiveness.

Clinical trials targeting the gut-microbiome to effect ocular health: a systematic review

Clinical trials targeting the gut microbiome to mitigate ocular disease are now on the horizon. A review of clinical data thus far is essential to determine future directions in this novel promising field. This review examines recent clinical trials that support the plausibility of a gut-eye axis, and may form the basis of novel clinical interventions. PubMed was queried for English language clinical studies examining the relationships between gut microbiota and ocular pathology. 25 studies were extracted from 828 candidate publications, which suggest that gut imbalance is associated with ocular pathology. Of these, only four interventional studies exist which suggest probiotic supplementation or fecal microbiota transplant can reduce symptoms of chalazion or uveitis. The gut-eye axis appears to hold clinical relevance, but current data is limited in sample size and design. Further investigation via longitudinal clinical trials may be warranted.

Microbiome depiction through user-adapted bioinformatic pipelines and parameters

Introduction. The role of the microbiome in health and disease continues to be increasingly recognized. However, there is significant variability in the bioinformatic protocols for analysing genomic data. This, in part, has impeded the potential incorporation of microbiomics into the clinical setting and has challenged interstudy reproducibility. In microbial compositional analysis, there is a growing recognition for the need to move away from a one-size-fits-all approach to data processing.Gap Statement. Few evidence-based recommendations exist for setting parameters of programs that infer microbiota community profiles despite these parameters significantly impacting the accuracy of taxonomic inference.Aim. To compare three commonly used programs (DADA2, QIIME2, and mothur) and optimize them into four user-adapted pipelines for processing paired-end amplicon reads. We aim to increase the accuracy of compositional inference and help standardize microbiomic protocol.Methods. Two key parameters were isolated across four pipelines: filtering sequence reads based on a whole-number error threshold (maxEE) and truncating read ends based on a quality score threshold (QTrim). Closeness of sample inference was then evaluated using a mock community of known composition.Results. We observed that raw genomic data lost were proportionate to how stringently parameters were set. Exactly how much data were lost varied by pipeline. Accuracy of sample inference correlated with increased sequence read retention. Falsely detected taxa and unaccounted for microbial constituents were unique to pipeline and parameter. Implementation of optimized parameter values led to better approximation of the known mock community.Conclusions. Microbial compositions generated based on the 16S rRNA marker gene should be interpreted with caution. To improve microbial community profiling, bioinformatic protocols must be user-adapted. Analysis should be performed with consideration for the select target amplicon, pipelines and parameters used, and taxa of interest.

Intravenous ferric carboxymaltose and ferric derisomaltose alter the intestinal microbiome in female iron-deficient anemic mice

Iron deficiency anemia (IDA) is a leading global health concern affecting approximately 30% of the population. Treatment for IDA consists of replenishment of iron stores, either by oral or intravenous (IV) supplementation. There is a complex bidirectional interplay between the gut microbiota, the host's iron status, and dietary iron availability. Dietary iron deficiency and supplementation can influence the gut microbiome; however, the effect of IV iron on the gut microbiome is unknown. We studied how commonly used IV iron preparations, ferric carboxymaltose (FCM) and ferric derisomaltose (FDI), affected the gut microbiome in female iron-deficient anemic mice. At the phylum level, vehicle-treated mice showed an expansion in Verrucomicrobia, mostly because of the increased abundance of Akkermansia muciniphila, along with contraction in Firmicutes, resulting in a lower Firmicutes/Bacteroidetes ratio (indicator of dysbiosis). Treatment with either FCM or FDI restored the microbiome such that Firmicutes and Bacteroidetes were the dominant phyla. Interestingly, the phyla Proteobacteria and several members of Bacteroidetes (e.g., Alistipes) were expanded in mice treated with FCM compared with those treated with FDI. In contrast, several Clostridia class members were expanded in mice treated with FDI compared with FCM (e.g., Dorea spp., Eubacterium). Our data demonstrate that IV iron increases gut microbiome diversity independently of the iron preparation used; however, differences exist between FCM and FDI treatments. In conclusion, replenishing iron stores with IV iron preparations in clinical conditions, such as inflammatory bowel disease or chronic kidney disease, could affect gut microbiome composition and consequently contribute to an altered disease outcome.

Integrated multi-omics analyses of microbial communities: a review of the current state and future directions

Integrated multi-omics analyses of microbiomes have become increasingly common in recent years as the emerging omics technologies provide an unprecedented opportunity to better understand the structural and functional properties of microbial communities. Consequently, there is a growing need for and interest in the concepts, approaches, considerations, and available tools for investigating diverse environmental and host-associated microbial communities in an integrative manner. In this review, we first provide a general overview of each omics analysis type, including a brief history, typical workflow, primary applications, strengths, and limitations. Then, we inform on both experimental design and bioinformatics analysis considerations in integrated multi-omics analyses, elaborate on the current approaches and commonly used tools, and highlight the current challenges. Finally, we discuss the expected key advances, emerging trends, potential implications on various fields from human health to biotechnology, and future directions.

Meta-Analysis of Publicly Available Clinical and Preclinical Microbiome Data From Studies of Burn Injury

Following burn injury, alterations in host commensal microbiota across body spaces may leave patients susceptible to opportunistic pathogens and serious sequelae such as sepsis. Generally, studies examining the microbiome postburn have had a limited sample size and lack of longitudinal data, which coupled with experimental and analytic variation, impacts overall interpretation. We performed a meta-analysis of publicly available sequencing data from preclinical and clinical burn studies to determine if there were consistent alterations in the microbiome across various anatomical sites and hosts. Ten human and animal 16S rRNA sequencing studies spanning respiratory, urinary, cutaneous, and gastrointestinal microbiomes were included. Taxonomic classification and alpha and beta diversity metrics were analyzed using QIIME2 v2021.8. Alpha diversity was consistently higher in control samples compared to burn-injured samples which were also different based on host and anatomical location; however, phylogenetic evaluation (ie, Faith PD) elucidated more significant differences compared to taxonomic metrics (ie, Shannon entropy). Beta diversity analysis based on weighted UniFrac showed that rodent specimens clustered less closely to humans than pig samples for both rectal and skin sources. Host species and performing institute were found to have a significant impact on community structure. In rectal samples, bacterial composition in pig and human burn samples included Bacteroidetes, Firmicutes, and Proteobacteria, while rodent samples were dominated by Firmicutes. Proteobacteria and Firmicutes increased on burned skin in each host species. Our results suggest that host species and the performing institute strongly influence microbiome structure. Burn-induced alterations in microbiome diversity and taxa exist across hosts, with phylogenetic metrics more valuable than others. Coordinated, multicenter studies, both clinical and preclinical, within the burn community are needed to more completely realize the diagnostic and therapeutic potential of the microbiome for improving outcomes postburn.

Gut Microbiome and Dietar Considerations

The gut microbiome represents a complex microbial ecosystem that exerts direct and indirect effects on other organ systems and contributes to both health and disease. It is sensitive to various stimuli such as childhood immunity, medications, diet, stressors, and sleep. Modulating the gut microbiome can prevent and even treat certain disease states. Although no definitive guidelines exist to support a healthy microbiome, there are several evidence-based interventions proved to improve gut health and reduce the risk for numerous chronic diseases.

The Role of Fecal Microbiota Transplantation in the Allogeneic Stem Cell Transplant Setting

Microbiota changes during allogeneic hematopoietic stem cell transplantation has several known causes: conditioning chemotherapy and radiation, broad-spectrum antibiotic administration, modification in nutrition status and diet, and graft-versus-host disease. This article aims to review the current knowledge about the close link between microbiota and allogeneic stem cell transplantation setting. The PubMed search engine was used to perform this review. We analyzed data on microbiota dysbiosis related to the above-mentioned affecting factors. We also looked at treatments aimed at modifying gut dysbiosis and applications of fecal microbiota transplantation in the allogeneic stem cell transplant field, with particular interest in fecal microbiota transplantation for graft-versus-host disease (GvHD), multidrug-resistant and clostridium difficile infections, and microbiota restoration after chemotherapy and antibiotic therapy.

Early Gut Microbiota Profile in Healthy Neonates: Microbiome Analysis of the First-Pass Meconium Using Next-Generation Sequencing Technology

Gut microbiome development during early life has significant long-term effects on health later in life. The first-pass meconium is not sterile, and it is important to know the initial founder of the subsequent gut microbiome. However, there is limited data on the microbiota profile of the first-pass meconium in healthy neonates. To determine the early gut microbiota profile, we analyzed 39 samples of the first-pass meconium from healthy neonates using 16S rRNA sequencing. Our results showed a similar profile of the microbiota composition in the first-pass meconium samples. Pseudomonas was the most abundant genus in most samples. The evenness of the microbial communities in the first-pass meconium was extremely poor, and the average Shannon diversity index was 1.31. An analysis of the relationship between perinatal characteristics and the meconium microbiome revealed that primigravidae babies had a significantly higher Shannon diversity index (p = 0.041), and the Bacteroidales order was a biomarker for the first-pass meconium of these neonates. The Shannon diversity index was not affected by the mode of delivery, maternal intrapartum antibiotic treatment, prolonged rupture of membranes, or birth weight. Our study extends previous research with further characterization of the gut microbiome in very early life.

Microbiome-metabolomics analysis reveals abatement effects of itaconic acid on odorous compound production in Arbor Acre broilers

BACKGROUND

Public complaints concerning odor emissions from intensive livestock and poultry farms continue to grow, as nauseous odorous compounds have adverse impacts on the environment and human health. Itaconic acid is a metabolite from the citric acid cycle of the host and shows volatile odor-reducing effects during animal production operations. However, the specific role of itaconic acid in decreasing intestinal odorous compound production remains unclear. A total of 360 one-day-old chicks were randomly divided into 6 treatment groups: control group (basal diet) and itaconic acid groups (basal diet + 2, 4, 6, 8 and 10 g/kg itaconic acid). The feeding experiment lasted for 42 d.

RESULTS

Dietary itaconic acid supplementation linearly and quadratically decreased (P < 0.05) the cecal concentrations of indole and skatole but did not affect (P > 0.05) those of lactic, acetic, propionic and butyric acids. The cecal microbial shift was significant in response to 6 g/kg itaconic acid supplementation, in that the abundances of Firmicutes, Ruminococcus and Clostridium were increased (P < 0.05), while those of Bacteroidetes, Escherichia-Shigella and Bacteroides were decreased (P < 0.05), indicative of increased microbial richness and diversity. Furthermore, a total of 35 significantly (P < 0.05) modified metabolites were obtained by metabolomic analysis. Itaconic acid decreased (P < 0.05) the levels of nicotinic acid, nicotinamide, glucose-6-phosphate, fumatic acid and malic acid and increased (P < 0.05) 5-methoxytroptomine, dodecanoic acid and stearic acid, which are connected with the glycolytic pathway, citrate acid cycle and tryptophan metabolism. Correlation analysis indicated significant correlations between the altered cecal microbiota and metabolites; Firmicutes, Ruminococcus and Clostridium were shown to be negatively correlated with indole and skatole production, while Bacteroidetes, Escherichia-Shigella and Bacteroides were positively correlated with indole and skatole production.

CONCLUSIONS

Itaconic acid decreased cecal indole and skatole levels and altered the microbiome and metabolome in favor of odorous compound reduction. These findings provide new insight into the role of itaconic acid and expand its application potential in broilers.

An efficient method for high molecular weight bacterial DNA extraction suitable for shotgun metagenomics from skin swabs

The human skin microbiome represents a variety of complex microbial ecosystems that play a key role in host health. Molecular methods to study these communities have been developed but have been largely limited to low-throughput quantification and short amplicon-based sequencing, providing limited functional information about the communities present. Shotgun metagenomic sequencing has emerged as a preferred method for microbiome studies as it provides more comprehensive information about the species/strains present in a niche and the genes they encode. However, the relatively low bacterial biomass of skin, in comparison to other areas such as the gut microbiome, makes obtaining sufficient DNA for shotgun metagenomic sequencing challenging. Here we describe an optimised high-throughput method for extraction of high molecular weight DNA suitable for shotgun metagenomic sequencing. We validated the performance of the extraction method, and analysis pipeline on skin swabs collected from both adults and babies. The pipeline effectively characterised the bacterial skin microbiota with a cost and throughput suitable for larger longitudinal sets of samples. Application of this method will allow greater insights into community compositions and functional capabilities of the skin microbiome.

Maternal Vitamin A deficiency during pregnancy and lactation induced damaged intestinal structure and intestinal flora homeostasis in offspring mice

The small intestine serves as the first channel of dietary Vitamin A (VA) and the unique organ of VA absorption and metabolism. However, there have not been extensive investigations on the exact mechanisms within VA-related changes in intestinal metabolic disorders. This research is designed to analyze whether and how VA affects intestinal metabolic phenotypes. Male C57BL/6 mice after weaning were randomly fed a VA control diet (VAC) or a VA-deficient diet (VAD) during the entire pregnancy and lactation process. After a total of 11 weeks, cohorts of VA deprived were next fed to a VA control diet (VAD-C) for another 8 weeks. The concentration of retinol was measured by a high-performance liquid chromatography system. The 16S gene sequencing was used to evaluate the intestinal microbiota changes. Through the use of histological staining, western blots, quantitative PCR, and enzyme-linked immunosorbent assays, the intestinal morphology, inflammatory factors, and intestinal permeability were all evaluated. Following the decrease of the tissue VA levels, VAD mice show a decrease in tissue VA levels, community differences, and the richness and diversity of intestinal microbiota. VAD diet-driven changes occur in intestinal microbiota, accompanied by a higher mRNA expression of intestinal inflammatory cytokines and an increase in intestinal permeability. As dietary VA is reintroduced into VAD diet-fed mice, the tissue VA levels, inflammatory response, and intestinal homeostasis profiles are all restored, which are similar to those found after the occurrence of VA-controlled changes within intestinal microbiota. VA deficiency caused the imbalance of intestinal metabolic phenotypes through a mechanism involving changes in intestinal microbiota. It is thought that intestinal microbiota metabolic influences represent a new salient and additional mechanism, which can be used as a new method to achieve the onset and treatment of the effect of VAD on intestinal homeostasis impairment.

Gut microbiota in patients with kidney stones: a systematic review and meta-analysis

BACKGROUND

Mounting evidence indicates that the gut microbiome (GMB) plays an essential role in kidney stone (KS) formation. In this study, we conducted a systematic review and meta-analysis to compare the composition of gut microbiota in kidney stone patients and healthy individuals, and further understand the role of gut microbiota in nephrolithiasis.

RESULTS

Six databases were searched to find taxonomy-based comparison studies on the GMB until September 2022. Meta-analyses were performed using RevMan 5.3 to estimate the overall relative abundance of gut microbiota in KS patients and healthy subjects. Eight studies were included with 356 nephrolithiasis patients and 347 healthy subjects. The meta-analysis suggested that KS patients had a higher abundance of Bacteroides (35.11% vs 21.25%, Z = 3.56, P = 0.0004) and Escherichia_Shigella (4.39% vs 1.78%, Z = 3.23, P = 0.001), and a lower abundance of Prevotella_9 (8.41% vs 10.65%, Z = 4.49, P < 0.00001). Qualitative analysis revealed that beta-diversity was different between the two groups (P < 0.05); Ten taxa (Bacteroides, Phascolarctobacterium, Faecalibacterium, Flavobacterium, Akkermansia, Lactobacillus, Escherichia coli, Rhodobacter and Gordonia) helped the detection of kidney stones (P < 0.05); Genes or protein families of the GMB involved in oxalate degradation, glycan synthesis, and energy metabolism were altered in patients (P < 0.05).

CONCLUSIONS

There is a characteristic gut microbiota dysbiosis in kidney stone patients. Individualized therapies like microbial supplementation, probiotic or synbiotic preparations and adjusted diet patterns based on individual gut microbial characteristics of patients may be more effective in preventing stone formation and recurrence.

Epsilon toxin-producing Clostridium perfringens colonize the multiple sclerosis gut microbiome overcoming CNS immune privilege

Multiple sclerosis (MS) is a complex disease of the CNS thought to require an environmental trigger. Gut dysbiosis is common in MS, but specific causative species are unknown. To address this knowledge gap, we used sensitive and quantitative PCR detection to show that people with MS were more likely to harbor and show a greater abundance of epsilon toxin-producing (ETX-producing) strains of C. perfringens within their gut microbiomes compared with individuals who are healthy controls (HCs). Isolates derived from patients with MS produced functional ETX and had a genetic architecture typical of highly conjugative plasmids. In the active immunization model of experimental autoimmune encephalomyelitis (EAE), where pertussis toxin (PTX) is used to overcome CNS immune privilege, ETX can substitute for PTX. In contrast to PTX-induced EAE, where inflammatory demyelination is largely restricted to the spinal cord, ETX-induced EAE caused demyelination in the corpus callosum, thalamus, cerebellum, brainstem, and spinal cord, more akin to the neuroanatomical lesion distribution seen in MS. CNS endothelial cell transcriptional profiles revealed ETX-induced genes that are known to play a role in overcoming CNS immune privilege. Together, these findings suggest that ETX-producing C. perfringens strains are biologically plausible pathogens in MS that trigger inflammatory demyelination in the context of circulating myelin autoreactive lymphocytes.

Human gut microbiome: A primer for the clinician

The human host gets tremendously influenced by a genetically and phenotypically distinct and heterogeneous constellation of microbial species-the human microbiome-the gut being one of the most densely populated and characterized site for these organisms. Microbiome science has advanced rapidly, technically with respect to the analytical methods and biologically with respect to its mechanistic influence in health and disease states. A clinician conducting a microbiome study should be aware of the nuances related to microbiome research, especially with respect to the technical and biological factors that can influence the interpretation of research outcomes. Hence, this review is an attempt to detail these aspects of the human gut microbiome, with emphasis on its determinants in a healthy state.

Lung-gut axis of microbiome alterations following co-exposure to ultrafine carbon black and ozone

BACKGROUND

Microbial dysbiosis is a potential mediator of air pollution-induced adverse outcomes. However, a systemic comparison of the lung and gut microbiome alterations and lung-gut axis following air pollution exposure is scant. In this study, we exposed male C57BL/6J mice to inhaled air, CB (10 mg/m3), O3 (2 ppm) or CB + O3 mixture for 3 h/day for either one day or four consecutive days and were euthanized 24 h post last exposure. The lung and gut microbiome were quantified by 16 s sequencing.

RESULTS

Multiple CB + O3 exposures induced an increase in the lung inflammatory cells (neutrophils, eosinophils and B lymphocytes), reduced absolute bacterial load in the lungs and increased load in the gut. CB + O3 exposure was more potent as it decreased lung microbiome alpha diversity just after a single exposure. CB + O3 co-exposure uniquely increased Clostridiaceae and Prevotellaceae in the lungs. Serum short chain fatty acids (SCFA) (acetate and propionate) were increased significantly only after CB + O3 co-exposure. A significant increase in SCFA producing bacterial families (Ruminococcaceae, Lachnospiraceae, and Eubacterium) were also observed in the gut after multiple exposures. Co-exposure induced significant alterations in the gut derived metabolite receptors/mediator (Gcg, Glp-1r, Cck) mRNA expression. Oxidative stress related mRNA expression in lungs, and oxidant levels in the BALF, serum and gut significantly increased after CB + O3 exposures.

CONCLUSION

Our study confirms distinct gut and lung microbiome alterations after CB + O3 inhalation co-exposure and indicate a potential homeostatic shift in the gut microbiome to counter deleterious impacts of environmental exposures on metabolic system.

Effect of Non-Nutritive Sweeteners on the Gut Microbiota

The human gut microbiota, a complex community of microorganisms living in the digestive tract, consists of more than 1500 species distributed in more than 50 different phyla, with 99% of bacteria coming from about 30-40 species. The colon alone, which contains the largest population of the diverse human microbiota, can harbor up to 100 trillion bacteria. The gut microbiota is essential in maintaining normal gut physiology and health. Therefore, its disruption in humans is often associated with various pathological conditions. Different factors can influence the composition and function of the gut microbiota, including host genetics, age, antibiotic treatments, environment, and diet. The diet has a marked effect, impacting the gut microbiota composition, beneficially or detrimentally, by altering some bacterial species and adjusting the metabolites produced in the gut environment. With the widespread use of non-nutritive sweeteners (NNS) in the diet, recent investigations have focused on their effect on the gut microbiota as a mediator of the potential impact generated by gastrointestinal-related disturbances, such as insulin resistance, obesity, and inflammation. We summarized the results from pre-clinical and clinical studies published over the last ten years that examined the single effects of the most consumed NNS: aspartame, acesulfame-K, sucralose, and saccharin. Pre-clinical studies have given conflicting results for various reasons, including the administration method and the differences in metabolism of the same NNS among the different animal species. A dysbiotic effect of NNS was observed in some human trials, but many other randomized controlled trials reported a lack of significant impacts on gut microbiota composition. These studies differed in the number of subjects involved, their dietary habits, and their lifestyle; all factors related to the baseline composition of gut microbiota and their response to NNS. The scientific community still has no unanimous consensus on the appropriate outcomes and biomarkers that can accurately define the effects of NNS on the gut microbiota.

The potential role of molecular mimicry by the anaerobic microbiome in the aetiology of autoimmune disease

Autoimmune diseases are thought to develop as a consequence of various environmental and genetic factors, each of which contributes to dysfunctional immune responses and/or a breakdown in immunological tolerance towards native structures. Molecular mimicry by microbial components is among the environmental factors thought to promote a breakdown in immune tolerance, particularly through the presence of cross-reactive epitopes shared with the human host. While resident members of the microbiome are essential promoters of human health through immunomodulation, defence against pathogenic colonisation and conversion of dietary fibre into nutritional resources for host tissues, there may be an underappreciated role of these microbes in the aetiology and/or progression of autoimmune disease. An increasing number of molecular mimics are being identified amongst the anaerobic microbiota which structurally resemble endogenous components and, in some cases, for example the human ubiquitin mimic of Bacteroides fragilis and DNA methyltransferase of Roseburia intestinalis, have been associated with promoting antibody profiles characteristic of autoimmune diseases. The persistent exposure of molecular mimics from the microbiota to the human immune system is likely to be involved in autoantibody production that contributes to the pathologies associated with immune-mediated inflammatory disorders. Here-in, examples of molecular mimics that have been identified among resident members of the human microbiome and their ability to induce autoimmune disease through cross-reactive autoantibody production are discussed. Improved awareness of the molecular mimics that exist among human colonisers will help elucidate the mechanisms involved in the breakdown of immune tolerance that ultimately lead to chronic inflammation and downstream disease.

Integrating microbiome and metabolome revealed microbe-metabolism interactions in the stomach of patients with different severity of peptic ulcer disease

Background

Peptic ulcer disease (PUD) is a multi-cause illness with an unknown role for gastric flora and metabolism in its pathogenesis. In order to further understand the pathogenesis of gastric flora and metabolism in PUD, this study used histological techniques to analyze the microbiome and metabolome of gastric biopsy tissue. In this paper, our work described the complex interactions of phenotype-microbial-metabolite-metabolic pathways in PUD patients at different pathological stages.

Methods

Gastric biopsy tissue samples from 32 patients with chronic non-atrophic gastritis, 24 patients with mucosal erosions, and 8 patients with ulcers were collected for the microbiome. UPLC-MS metabolomics was also used to detect gastric tissue samples. These datasets were analyzed individually and integrated using various bioinformatics methods.

Results

Our work found reduced diversity of gastric flora in patients with PUD. PUD patients at different pathological stages presented their own unique flora, and there were significant differences in flora phenotypes. Coprococcus_2, Phenylobacterium, Candidatus_Hepatoplasma, and other bacteria were found in the flora of people with chronic non-atrophic gastritis (HC). The representative flora of mucosal erosion (ME) had uncultured_bacterium_c_Subgroup_6, Sphingomonadaceae, Xanthobacteraceae, and uncultured_bacterium_f_Xanthobacteraceae. In comparison, the characteristic flora of the PUD group was the most numerous and complex, including Ruminococcus_2, Agathobacter, Alistipes, Helicobacter, Bacteroides and Faecalibacterium. Metabolomics identified and annotated 66 differential metabolites and 12 significantly different metabolic pathways. The comprehensive analysis correlated microorganisms with metabolites at different pathological stages and initially explored the complex interactions of phenotype-microbial-metabolite-metabolic pathways in PUD patients at different pathological stages.

Conclusion

Our research results provided substantial evidence to support some data on the analysis of the microbial community and its metabolism in the stomach, and they demonstrated many specific interactions between the gastric microbiome and the metabolome. Our study can help reveal the pathogenesis of PUD and indicate plausible disease-specific mechanisms for future studies from a new perspective.

Defining the Role of the Gut Microbiome in the Pathogenesis and Treatment of Lymphoid Malignancies

The gut microbiome is increasingly being recognized as an important immunologic environment, with direct links to the host immune system. The scale of the gut microbiome's genomic repertoire extends the capacity of its host's genome by providing additional metabolic output, and the close communication between gut microbiota and mucosal immune cells provides a continued opportunity for immune education. The relationship between the gut microbiome and the host immune system has important implications for oncologic disease, including lymphoma, a malignancy derived from within the immune system itself. In this review, we explore past and recent discoveries describing the role that bacterial populations play in lymphomagenesis, diagnosis, and therapy. We highlight key relationships within the gut microbiome-immune-oncology axis that present exciting opportunities for directed interventions intended to shape the microbiome for therapeutic effect. We conclude with a limited summary of active clinical trials targeting the microbiome in hematologic malignancies, along with future directions on gut microbiome investigations within lymphoid malignancies.

Application of emerging technologies for gut microbiome research

Microbiome is associated with a wide range of diseases. The gut microbiome is also a dynamic reflection of health status, which can be modified, thus representing great potential to exploit the mechanisms that influence human physiology. Recent years have seen a dramatic rise in gut microbiome studies, which has been enabled by the rapidly evolving high-throughput sequencing methods (i.e. 16S rRNA sequencing and shotgun sequencing). As the emerging technologies for microbiome research continue to evolve (i.e. metatranscriptomics, metabolomics, culturomics, synthetic biology), microbiome research has moved beyond phylogenetic descriptions and towards mechanistic analyses. In this review, we highlight different approaches to study the microbiome, in particular, the current limitations and future promise of these techniques. This review aims to provide clinicians with a framework for studying the microbiome, as well as to accelerate the adoption of these techniques in clinical practice.

An exploratory study of the gut microbiota in major depression with anxious distress

OBJECTIVES

To explore differences in the diversity and composition of the gut microbiome between major depressive disorder (MDD) with and without anxious distress.

METHODS

The study comprised 117 participants (79 female, 36 male, 2 other, mean age 38.2 ± 13.4 years) with a current major depressive episode (MDE) with (n = 63) and without (n = 54) the anxious distress specifier. A clinical psychologist administered the structured clinical interview for the DSM-5-RV to confirm a diagnosis of depression. Participants provided stool samples which were immediately frozen and stored at -80 °C. These samples were analysed using the Illumina 16S Metagenomics sequencing protocol in which the sequencing primers target the V3 and V4 regions of the 16S rRNA gene. Participants also completed mental health questionnaires to assess severity of depression (BDI-II), generalized anxiety (GAD-7), and stress (PSS).

RESULTS

There were no significant group differences in α-diversity (Shannon's diversity Index; Simpson Index), richness (ACE; Chao1), (Pielou's) evenness, or beta diversity (Bray-Curtis dissimilarity index and weighted UniFrac distance) of gut bacteria. Significant group differences in the relative abundance of gut microbiota however were observed at each taxonomical level, including across 15 genera and 18 species.

LIMITATIONS

This was an exploratory study that needs to be replicated across larger samples and compared with a healthy control group.

CONCLUSIONS

The research contributes to knowledge of the depressive gut microbial profile unique to the anxious distress subtype of MDD.

The bidirectional relationship between endometriosis and microbiome

Endometriosis has been described by many different theories of pathogenesis over the years. It is now also appreciated to be a state of chronic inflammation, and the role of immune dysfunction in its development has been proven. There is increasing evidence to support the role of the microbiome in the formation and progression of endometriosis via inflammatory pathways. The dysbiosis seen in endometriosis is thought to be both causative and a consequence of the pathogenesis. Gut, peritoneal fluid and female reproductive tract microbiota has been studied to understand if there are any microbiome signatures specific to endometriosis. New research on how to manipulate the microbiome for better detection and treatment of endometriosis is emerging.

Analysis of correlations between gut microbiota, stool short chain fatty acids, calprotectin and cardiometabolic risk factors in postmenopausal women with obesity: a cross-sectional study

BACKGROUND

Microbiota and its metabolites are known to regulate host metabolism. In cross-sectional study conducted in postmenopausal women we aimed to assess whether the microbiota, its metabolites and gut barrier integrity marker are correlated with cardiometabolic risk factors and if microbiota is different between obese and non-obese subjects.

METHODS

We analysed the faecal microbiota of 56 obese, postmenopausal women by means of 16S rRNA analysis. Stool short chain fatty acids, calprotectin and anthropometric, physiological and biochemical parameters were correlates to microbiome analyses.

RESULTS

Alpha-diversity was inversely correlated with lipopolysaccharide (Rho = - 0.43, FDR P (Q) = 0.004). Bray-Curtis distance based RDA revealed that visceral fat and waist circumference had a significant impact on metabolic potential (P = 0.003). Plasma glucose was positively correlated with the Coriobacteriaceae (Rho = 0.48, Q = 0.004) and its higher taxonomic ranks, up to phylum (Actinobacteria, Rho = 0.46, Q = 0.004). At the metabolic level, the strongest correlation was observed for the visceral fat (Q < 0.15), especially with the DENOVOPURINE2-PWY, PWY-841 and PWY0-162 pathways. Bacterial abundance was correlated with SCFAs, thus some microbiota-glucose relationships may be mediated by propionate, as indicated by the significant average causal mediation effect (ACME): Lachnospiraceae (ACME 1.25, 95%CI (0.10, 2.97), Firmicutes (ACME 1.28, 95%CI (0.23, 3.83)) and Tenericutes (ACME - 0.39, 95%CI (- 0.87, - 0.03)). There were significant differences in the distribution of phyla between this study and Qiita database (P < 0.0001).

CONCLUSIONS

Microbiota composition and metabolic potential are associated with some CMRF and fecal SCFAs concentration in obese postmenopausal women. There is no unequivocal relationship between fecal SCFAs and the marker of intestinal barrier integrity and CMRF. Further studies with appropriately matched control groups are warranted to look for causality between SCFAs and CMRF.

Meta-analysis of caries microbiome studies can improve upon disease prediction outcomes

As one of the most prevalent infective diseases worldwide, it is crucial that we not only know the constituents of the oral microbiome in dental caries but also understand its functionality. Herein, we present a reproducible meta-analysis to effectively report the key components and the associated functional signature of the oral microbiome in dental caries. Publicly available sequencing data were downloaded from online repositories and subjected to a standardized analysis pipeline before analysis. Meta-analyses identified significant differences in alpha and beta diversities of carious microbiomes when compared to healthy ones. Additionally, machine learning and receiver operator characteristic analysis showed an ability to discriminate between healthy and disease microbiomes. We identified from importance values, as derived from random forest analyses, a group of genera, notably containing Selenomonas, Aggregatibacter, Actinomyces and Treponema, which can be predictive of dental caries. Finally, we propose the most appropriate study design for investigating the microbiome of dental caries by synthesizing the studies, which had the most accurate differentiation based on random forest modelling. In conclusion, we have developed a non-biased, reproducible pipeline, which can be applied to microbiome meta-analyses of multiple diseases, but importantly we have derived from our meta-analysis a key group of organisms that can be used to identify individuals at risk of developing dental caries based on oral microbiome inhabitants.

Microbe-based therapies for colorectal cancer: Advantages and limitations

Cancer is one of the leading global causes of death in both men and women. Colorectal cancer (CRC) alone accounts for ∼10 % of total new global cases and poses an over 4% lifetime risk of developing cancer. Recent advancements in the field of biotechnology and microbiology concocted novel microbe-based therapies to treat various cancers, including CRC. Microbes have been explored for human use since centuries, especially for the treatment of various ailments. The utility of microbes in cancer therapeutics is widely explored, and various bacteria, fungi, and viruses are currently in use for the development of cancer therapeutics. The human gut hosts about 100 trillion microbes that release their metabolites in active, inactive, or dead conditions. Microbial secondary metabolites, proteins, immunotoxins, and enzymes are used to target cancer cells to induce cell cycle arrest, apoptosis, and death. Various approaches, such as dietary interventions, the use of prebiotics and probiotics, and fecal microbiota transplantation have been used to modulate the gut microbiota in order to prevent or treat CRC pathogenesis. The present review highlights the role of the gut microbiota in CRC precipitation, the potential mechanisms and use of microorganisms as CRC biomarkers, and strategies to modulate microbiota for the prevention and treatment of CRC.

A Host-Directed Approach to the Detection of Infection in Hard-to-Heal Wounds

Wound infection is traditionally defined primarily by visual clinical signs, and secondarily by microbiological analysis of wound samples. However, these approaches have serious limitations in determining wound infection status, particularly in early phases or complex, chronic, hard-to-heal wounds. Early or predictive patient-derived biomarkers of wound infection would enable more timely and appropriate intervention. The observation that immune activation is one of the earliest responses to pathogen activity suggests that immune markers may indicate wound infection earlier and more reliably than by investigating potential pathogens themselves. One of the earliest immune responses is that of the innate immune cells (neutrophils) that are recruited to sites of infection by signals associated with cell damage. During acute infection, the neutrophils produce oxygen radicals and enzymes that either directly or indirectly destroy invading pathogens. These granular enzymes vary with cell type but include elastase, myeloperoxidase, lysozyme, and cathepsin G. Various clinical studies have demonstrated that collectively, these enzymes, are sensitive and reliable markers of both early-onset phases and established infections. The detection of innate immune cell enzymes in hard-to-heal wounds at point of care offers a new, simple, and effective approach to determining wound infection status and may offer significant advantages over uncertainties associated with clinical judgement, and the questionable value of wound microbiology. Additionally, by facilitating the detection of early wound infection, prompt, local wound hygiene interventions will likely enhance infection resolution and wound healing, reduce the requirement for systemic antibiotic therapy, and support antimicrobial stewardship initiatives in wound care.

Infections and Changes in Commensal Bacteria and the Pathogenesis of Parkinson’s Disease

The cause of Parkinson’s disease (PD) is unknown, but environmental factors are purported to influence risk. Interest in PD as a sequel of infection dates back to reports of parkinsonism arising from encephalitis lethargica. The objective of this paper is to review the literature as it relates to infections and changes in microbiome and the genesis of PD. There is evidence to support prior infection with Helicobacter pylori, hepatitis C virus, Malassezia, and Strep pneumonia in association with PD. A large number of studies support an association between changes in commensal bacteria, especially gut bacteria, and PD. Extant literature supports a role for some infections and changes in commensal bacteria in the genesis of PD. Studies support an inflammatory mechanism for this association, but additional research is required for translation of these findings to therapeutic options.

Systems to model the personalized aspects of microbiome health and gut dysbiosis

The human gut microbiome is a complex and dynamic microbial entity that interacts with the environment and other parts of the body including the brain, heart, liver, and immune system. These multisystem interactions are highly conserved from invertebrates to humans, however the complexity and diversity of human microbiota compositions often yield a context that is unique to each individual. Yet commonalities remain across species, where a healthy gut microbiome will be rich in symbiotic commensal biota while an unhealthy gut microbiota will be experiencing abnormal blooms of pathobiont bacteria. In this review we discuss how omics technologies can be applied in a personalized approach to understand the microbial crosstalk and microbial-host interactions that affect the delicate balance between eubiosis and dysbiosis in an individual gut microbiome. We further highlight the strengths of model organisms in identifying and characterizing these conserved synergistic and/or pathogenic host-microbe interactions. And finally, we touch upon the growing area of personalized therapeutic interventions targeting gut microbiome.

Type 2 diabetes, gut microbiome, and systems biology: A novel perspective for a new era

The association between the physio-pathological variables of type 2 diabetes (T2D) and gut microbiota composition suggests a new avenue to track the disease and improve the outcomes of pharmacological and non-pharmacological treatments. This enterprise requires new strategies to elucidate the metabolic disturbances occurring in the gut microbiome as the disease progresses. To this end, physiological knowledge and systems biology pave the way for characterizing microbiota and identifying strategies in a move toward healthy compositions. Here, we dissect the recent associations between gut microbiota and T2D. In addition, we discuss recent advances in how drugs, diet, and exercise modulate the microbiome to favor healthy stages. Finally, we present computational approaches for disentangling the metabolic activity underlying host-microbiota codependence. Altogether, we envision that the combination of physiology and computational modeling of microbiota metabolism will drive us to optimize the diagnosis and treatment of T2D patients in a personalized way.

Sex-Dependent Effects of Inhaled Nicotine on the Gut Microbiome

INTRODUCTION

The impact of nicotine, the addictive component of both traditional cigarettes and e-cigarettes, on many physiological processes remains poorly understood. To date, there have been few investigations into the impact of nicotine on the gut microbiome, and these studies utilized oral administration rather than inhalation. This study aimed to establish if inhaled nicotine alters the gut microbiome and the effect of sex as a biological variable.

METHODS

Female (n = 8 air; n = 10 nicotine) and male (n = 10 air; n = 10 nicotine) C57BL6/J mice were exposed to air (control) or nicotine vapor (12 hour/day) for 13 weeks. A fecal sample was collected from each mouse at the time of sacrifice, and the gut microbiome was analyzed by 16S rRNA gene sequencing. QIIME2, PICRUSt, and STAMP were used to detect gut bacterial differences and functional metabolic pathways.

RESULTS

Sex-specific differences were observed in both alpha and beta diversities in the absence of nicotine. While nicotine alters microbial community structure in both male and female mice as revealed by the beta diversity metric, nicotine significantly reduced alpha diversity only in female mice. A total of 42 bacterial taxa from phylum to species were found to be significantly different among the treatment groups. Finally, analysis for functional genes revealed significant differences in twelve metabolic pathways in female mice and ten in male mice exposed to nicotine compared to air controls.

CONCLUSIONS

Nicotine inhalation alters the gut microbiome and reduces bacterial diversity in a sex-specific manner, which may contribute to the overall adverse health impact of nicotine.

IMPLICATIONS

The gut microbiota plays a fundamental role in the well-being of the host, and traditional cigarette smoking has been shown to affect the gut microbiome. The effects of nicotine alone, however, remain largely uncharacterized. Our study demonstrates that nicotine inhalation alters the gut microbiome in a sex-specific manner, which may contribute to the adverse health consequences of inhaled nicotine. This study points to the importance of more detailed investigations into the influence of inhaled nicotine on the gut microbiota.

A comparison of faecal glucocorticoid metabolite concentration and gut microbiota diversity in bonobos (Pan paniscus)

Sex, age, diet, stress and social environment have all been shown to influence the gut microbiota. In several mammals, including humans, increased stress is related to decreasing gut microbial diversity and may differentially impact specific taxa. Recent evidence from gorillas shows faecal glucocorticoid metabolite concentration (FGMC) did not significantly explain gut microbial diversity, but it was significantly associated with the abundance of the family Anaerolineaceae. These patterns have yet to be examined in other primates, like bonobos (Pan paniscus). We compared FGMC to 16S rRNA amplicons for 202 bonobo faecal samples collected across 5 months to evaluate the impact of stress, measured with FGMC, on the gut microbiota. Alpha diversity measures (Chao's and Shannon's indexes) were not significantly related to FGMC. FGMC explained 0.80 % of the variation in beta diversity for Jensen-Shannon and 1.2% for weighted UniFrac but was not significant for unweighted UniFrac. We found that genus SHD-231, a member of the family Anaerolinaceae had a significant positive relationship with FGMC. These results suggest that bonobos are relatively similar to gorillas in alpha diversity and family Anaerolinaceae responses to FGMC, but different from gorillas in beta diversity. Members of the family Anaerolinaceae may be differentially affected by FGMC across great apes. FGMC appears to be context dependent and may be species-specific for alpha and beta diversity but this study provides an example of consistent change in two African apes. Thus, the relationship between physiological stress and the gut microbiome may be difficult to predict, even among closely related species.

Statistical challenges in longitudinal microbiome data analysis

The microbiome is a complex and dynamic community of microorganisms that co-exist interdependently within an ecosystem, and interact with its host or environment. Longitudinal studies can capture temporal variation within the microbiome to gain mechanistic insights into microbial systems; however, current statistical methods are limited due to the complex and inherent features of the data. We have identified three analytical objectives in longitudinal microbial studies: (1) differential abundance over time and between sample groups, demographic factors or clinical variables of interest; (2) clustering of microorganisms evolving concomitantly across time and (3) network modelling to identify temporal relationships between microorganisms. This review explores the strengths and limitations of current methods to fulfill these objectives, compares different methods in simulation and case studies for objectives (1) and (2), and highlights opportunities for further methodological developments. R tutorials are provided to reproduce the analyses conducted in this review.

Level of injury is an independent determining factor of gut dysbiosis in people with chronic spinal cord injury: A cross-sectional study

STUDY DESIGN

A cross-sectional study.

OBJECTIVE

To investigate the correlations between gut microbiota and metabolic parameters in people with different levels of chronic spinal cord injury (SCI).

SETTING

An SCI-specialized rehabilitation facility in a university hospital.

METHODS

Forty-three participants with chronic SCI were recruited. Blood samples of each participant were collected for analysis of metabolic parameters. Feces were collected after the bowel opening method the patient routinely uses to evaluate fecal bacterial microbiota using quantitative RT-PCR. Body composition was examined using dual-energy x-ray absorptiometry (DEXA). Data were analyzed to evaluate the correlations between gut microbiota and other parameters.

RESULTS

Of the 43 participants, 31 people (72.1%) were paraplegic and 12 people (27.9%) tetraplegic. Thirty-two people (74.4%) were diagnosed with obesity using the percentage of body fat (% body fat) criteria. The mean (SD) ratio of Firmicutes:Bacteroides (F/B), which represents the degree of gut dysbiosis, was 18.3 (2.45). Using stepwise multivariable linear regression analysis, both having tetraplegia and being diagnosed with obesity from % body fat evaluated by DEXA were independent positively-correlating factors of F/B (p < 0.001 and p = 0.001, respectively), indicating more severe gut dysbiosis in people with tetraplegia than paraplegia.

CONCLUSION

In people with chronic SCI, having tetraplegia and being diagnosed with obesity from % body fat evaluated by DEXA are independent positive-correlating factors of gut dysbiosis. These results indicate a significant association between gut microbiota and the characteristics of SCI as well as metabolic parameters.

Distinctive Clinical Correlates of Small Intestinal Bacterial Overgrowth with Methanogens

BACKGROUND AND AIMS

Most patients with small intestinal bacterial overgrowth (SIBO) produce hydrogen by fermentation of dietary carbohydrates; however, ∼30% of patients with SIBO are colonized with Archaea, anaerobic organisms that produce methane. SIBO is associated with a plethora of symptoms and conditions, but their diagnostic significance is unclear. We aimed to determine if specific symptoms and conditions are associated with methanogenic SIBO.

METHODS

This study received institutional review board approval (IRB00059873). In this retrospective cross-sectional study, we queried a database of glucose breath tests conducted for suspected SIBO at our tertiary care medical center, which included data on the presence or absence of gastrointestinal symptoms and conditions often associated with SIBO. All patients had undergone a standardized breath testing protocol.

RESULTS

In a cohort of 1461 patients, 33.1% were SIBO positive; of these, 49.8% produced only hydrogen, 38.8% produced only methane, and 11.4% produced both gases. The following factors distinguished patients with hydrogen-producing SIBO, but not methanogenic SIBO, from SIBO-negative patients: vitamin B₁₂ deficiency (odds ratio, 1.44; confidence interval [CI], 1.01-2.06; P = .046), Roux-en-Y gastric bypass (odds ratio, 2.14; CI, 1.09-4.18; P = .027), cholecystectomy (odds ratio, 1.42; CI, 1.06-1.91; P = .020), and diabetes (odds ratio, 1.59; CI, 1.13-2.24; P = .008). The absence of vitamin B₁₂ deficiency was the sole discriminating factor between methanogenic and hydrogenic SIBO (odds ratio, 0.57; CI, 0.34-0.97; P = .038).

CONCLUSIONS

Patients with SIBO caused by methane-producing Archaea display a different spectrum of associated symptoms and clinical conditions compared with patients with SIBO caused by hydrogen-producing bacteria, particularly a lower incidence of vitamin B₁₂ deficiency.

Deep Learning Encoding for Rapid Sequence Identification on Microbiome Data

We present a novel approach for rapidly identifying sequences that leverages the representational power of Deep Learning techniques and is applied to the analysis of microbiome data. The method involves the creation of a latent sequence space, training a convolutional neural network to rapidly identify sequences by mapping them into that space, and we leverage the novel encoded latent space for denoising to correct sequencing errors. Using mock bacterial communities of known composition, we show that this approach achieves single nucleotide resolution, generating results for sequence identification and abundance estimation that match the best available microbiome algorithms in terms of accuracy while vastly increasing the speed of accurate processing. We further show the ability of this approach to support phenotypic prediction at the sample level on an experimental data set for which the ground truth for sequence identities and abundances is unknown, but the expected phenotypes of the samples are definitive. Moreover, this approach offers a potential solution for the analysis of data from other types of experiments that currently rely on computationally intensive sequence identification.

Variability in the Pre-Analytical Stages Influences Microbiome Laboratory Analyses

Introduction: There are numerous confounding variables in the pre-analytical steps in the analysis of gut microbial composition that affect data consistency and reproducibility. This study compared two DNA extraction methods from the same faecal samples to analyse differences in microbial composition. Methods: DNA was extracted from 20 faecal samples using either (A) chemical/enzymatic heat lysis (lysis buffer, proteinase K, 95 °C + 70 °C) or (B) mechanical and chemical/enzymatic heat lysis (bead-beating, lysis buffer, proteinase K, 65 °C). Gut microbiota was mapped through the 16S rRNA gene (V3−V9) using a set of pre-selected DNA probes targeting >300 bacteria on different taxonomic levels. Apart from the pre-analytical DNA extraction technique, all other parameters including microbial analysis remained the same. Bacterial abundance and deviations in the microbiome were compared between the two methods. Results: Significant variation in bacterial abundance was seen between the different DNA extraction techniques, with a higher yield of species noted in the combined mechanical and heat lysis technique (B). The five predominant bacteria seen in both (A) and (B) were Bacteroidota spp. and Prevotella spp. (p = NS), followed by Bacillota (p = 0.005), Lachhnospiraceae (p = 0.0001), Veillonella spp. (p < 0.0001) and Clostridioides (p < 0.0001). Conclusion: As microbial testing becomes more easily and commercially accessible, a unified international consensus for optimal sampling and DNA isolation procedures must be implemented for robustness and reproducibility of the results.

The rise to power of the microbiome: power and sample size calculation for microbiome studies

A priori power and sample size calculations are crucial to appropriately test null hypotheses and obtain valid conclusions from all clinical studies. Statistical tests to evaluate hypotheses in microbiome studies need to consider intrinsic features of microbiome datasets that do not apply to classic sample size calculation. In this review, we summarize statistical approaches to calculate sample sizes for typical microbiome study scenarios, including those that hypothesize microbiome features to be the outcome, the exposure or the mediator, and provide relevant R scripts to conduct some of these calculations. This review is intended to be a resource to facilitate the conduct of sample size calculations that are based on testable hypotheses across several dimensions of the microbiome. Implementation of these methods will improve the quality of human or animal microbiome studies, enabling reliable conclusions that will generalize beyond the study sample.