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

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.

Optimizing UniFrac with OpenACC Yields Greater Than One Thousand Times Speed Increase

UniFrac is an important tool in microbiome research that is used for phylogenetically comparing microbiome profiles to one another (beta diversity). Striped UniFrac recently added the ability to split the problem into many independent subproblems, exhibiting nearly linear scaling but suffering from memory contention. Here, we adapt UniFrac to graphics processing units using OpenACC, enabling greater than 1,000× computational improvement, and apply it to 307,237 samples, the largest 16S rRNA V4 uniformly preprocessed microbiome data set analyzed to date. IMPORTANCE UniFrac is an important tool in microbiome research that is used for phylogenetically comparing microbiome profiles to one another. Here, we adapt UniFrac to operate on graphics processing units, enabling a 1,000× computational improvement. To highlight this advance, we perform what may be the largest microbiome analysis to date, applying UniFrac to 307,237 16S rRNA V4 microbiome samples preprocessed with Deblur. These scaling improvements turn UniFrac into a real-time tool for common data sets and unlock new research questions as more microbiome data are collected.

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.

Promises of microbiome-based therapies

Humans harbour large quantities of microbes, including bacteria, fungi, viruses and archaea, in the gut. Patients with liver disease exhibit changes in the intestinal microbiota and gut barrier dysfunction. Preclinical models demonstrate the importance of the gut microbiota in the pathogenesis of various liver diseases. In this review, we discuss how manipulation of the gut microbiota can be used as a novel treatment approach for liver disease. We summarise current data on untargeted approaches, including probiotics and faecal microbiota transplantation, and precision microbiome-centered therapies, including engineered bacteria, postbiotics and phages, for the treatment of liver diseases.

Proposal of a health gut microbiome index based on a meta-analysis of Korean and global population datasets

The disruption of the human gut microbiota has been linked to host health conditions, including various diseases. However, no reliable index for measuring and predicting a healthy microbiome is currently available. Here, the sequencing data of 1,663 Koreans were obtained from three independent studies. Furthermore, we pooled 3,490 samples from public databases and analyzed a total of 5,153 fecal samples. First, we analyzed Korean gut microbiome covariates to determine the influence of lifestyle on variation in the gut microbiota. Next, patterns of microbiota variations across geographical locations and disease statuses were confirmed using a global cohort and di-sease data. Based on comprehensive comparative analysis, we were able to define three enterotypes among Korean cohorts, namely, Prevotella type, Bacteroides type, and outlier type. By a thorough categorization of dysbiosis and the evaluation of microbial characteristics using multiple datasets, we identified a wide spectrum of accuracy levels in classifying health and disease states. Using the observed microbiome patterns, we devised an index named the gut microbiome index (GMI) that could consistently predict health conditions from human gut microbiome data. Compared to ecological metrics, the microbial marker index, and machine learning approaches, GMI distinguished between healthy and non-healthy individuals with a higher accuracy across various datasets. Thus, this study proposes a potential index to measure health status of gut microbiome that is verified from multiethnic data of various diseases, and we expect this model to facilitate further clinical application of gut microbiota data in future.

Reduced Enterohepatic Recirculation of Mycophenolate and Lower Blood Concentrations are Associated with the Stool Bacterial Microbiome After Hematopoietic Cell Transplantation

BACKGROUND

Mycophenolate mofetil (MMF) is an important immunosuppressant used after allogeneic hematopoietic cell transplant (HCT). MMF has a narrow therapeutic index and blood concentrations of mycophenolic acid (MPA), the active component of MMF, are highly variable. Low MPA concentrations are associated with risk of graft vs host disease (GvHD) while high concentrations are associated with toxicity. Reasons for variability are not well known and may be due, at least in part, to the presence of β-glucuronidase producing bacteria in the gastrointestinal tract which enhance MPA enterohepatic recirculation (EHR) by transforming MPA metabolites formed in the liver back to MPA.

OBJECTIVE

To determine if individuals with high MPA EHR have a greater abundance of β-glucuronidase producing bacteria in their stool and higher MPA concentrations relative to those with low EHR.

STUDY DESIGN

We conducted a pharmacomicrobiomics study in 20 adult HCT recipients receiving a myeloablative or reduced intensity preparative regimen. Participants received MMF 1g IV every 8 hours with tacrolimus. Intensive pharmacokinetic sampling of mycophenolate was conducted before hospital discharge. Total MPA, MPA glucuronide (MPAG) and acylMPAG were measured. EHR was defined as a ratio of MPA area under the concentration-versus-time curve (AUC)_4-8 to MPA AUC_0-8. Differences in stool microbiome diversity and composition, determined by shotgun metagenomic sequencing, were compared above and below the median EHR (22%, range 5-44%).

RESULTS

Median EHR was 12% and 29% in the low and high EHR groups, respectively. MPA troughs, MPA AUC_4-8 and acylMPAG AUC_4-8/AUC_0-8, were greater in the high EHR group vs low EHR group [1.53 vs 0.28 mcg/mL, p = 0.0001], [7.33 vs 1.79 hr*mcg/mL, p = 0.0003] and [0.33 vs 0.24 hr*mcg/mL, p = 0.0007], respectively. MPA AUC_0-8 was greater in the high EHR than the low EHR group and trended towards significance [22.8 vs. 15.3 hr*mcg/mL, p=0.06]. Bacteroides vulgatus, stercoris and thetaiotaomicron were 1.2-2.4 times more abundant (p=0.039, 0.024, 0.046, respectively) in the high EHR group. MPA EHR was positively correlated with B. vulgatus (⍴=0.58, p≤0.01) and B. thetaiotaomicron (⍴=0.46, p<0.05) and negatively correlated with Blautia hydrogenotrophica (⍴=-0.53, p<0.05). Therapeutic MPA troughs were achieved in 80% of patients in the high EHR group and 0% in the low EHR. There was a trend towards differences in MPA AUC_0-8 and MPA C_ss mcg/mL in high vs. low EHR groups (p=0.06).

CONCLUSION

MPA EHR was variable. Patients with high MPA EHR had greater abundance of Bacteroides species in stool and higher MPA exposure than patients with low MPA EHR. Bacteroides may therefore be protective from poor outcomes such as graft vs host disease but in others it may increase the risk of MPA adverse effects. These data need to be confirmed and studied after oral MMF.

An optimized approach for processing of frozen lung and lavage samples for microbiome studies

The respiratory tract has a resident microbiome with low biomass and limited diversity. This results in difficulties with sample preparation for sequencing due to uneven bacteria-to-host DNA ratio, especially for small tissue samples such as mouse lungs. We compared effectiveness of current procedures used for DNA extraction in microbiome studies. Bronchoalveolar lavage fluid (BALF) and lung tissue samples were collected to test different forms of sample pre-treatment and extraction methods to increase bacterial DNA yield and optimize library preparation. DNA extraction using a pre-treatment method of mechanical lysis (lung tissue) and one-step centrifugation (BALF) increased DNA yield and bacterial content of samples. In contrast, a significant increase of environmental contamination was detected after phenol chloroform isoamyl alcohol (PCI) extraction and nested PCR. While PCI has been a standard procedure used in microbiome studies, our data suggests that it is not efficient for DNA extraction of frozen low biomass samples. Finally, a DNA Enrichment kit was tested and found to improve the 16S copy number of lung tissue with a minor shift in microbial composition. Overall, we present a standardized method to provide high yielding DNA and improve sequencing coverage of low microbial biomass frozen samples with minimal contamination.

Gut microbiota of elite female football players is not altered during an official international tournament

The current study aimed to investigate if the gut microbiota composition of elite female football players changes during an official international tournament. The study was conducted throughout ten consecutive days, encompassing seven training sessions, and three official matches. The matches were separated by 48-72 h. Seventeen elite female football players from the Portuguese women's national football team participated in the study. Fecal samples were collected at two time points: at the beginning and end of the tournament. Fecal microbiota was analyzed by sequencing the 16S rRNA gene. Throughout the study, the duration and rating of perceived exertion (RPE) were recorded after training sessions and matches. The internal load was determined by the session RPE. The gut microbiota of players was predominantly composed of bacteria from the phyla Firmicutes (50% of relative abundance) and Bacteroidetes (20%); the genera Faecalibacterium (29%) and Collinsella (16%); the species Faecalibacterium prausnitzii (30%) and Collinsella aerofaciens (17%). Overall, no significant changes were observed between time points (p ≥ 0.05). Also, no relationship was found between any exercise parameter and the gut microbiota composition (p ≥ 0.05). These findings demonstrate that the physical and physiological demands of training and matches of an official international tournament did not change the gut microbiota composition of elite female football players. Furthermore, it supports that the gut microbiota of athletes appears resilient to the physical and physiological demands of training and match play.

Overview of paratransgenesis as a strategy to control pathogen transmission by insect vectors

This article presents an overview of paratransgenesis as a strategy to control pathogen transmission by insect vectors. It first briefly summarises some of the disease-causing pathogens vectored by insects and emphasises the need for innovative control methods to counter the threat of resistance by both the vector insect to pesticides and the pathogens to therapeutic drugs. Subsequently, the state of art of paratransgenesis is described, which is a particularly ingenious method currently under development in many important vector insects that could provide an additional powerful tool for use in integrated pest control programmes. The requirements and recent advances of the paratransgenesis technique are detailed and an overview is given of the microorganisms selected for genetic modification, the effector molecules to be expressed and the environmental spread of the transgenic bacteria into wild insect populations. The results of experimental models of paratransgenesis developed with triatomines, mosquitoes, sandflies and tsetse flies are analysed. Finally, the regulatory and safety rules to be satisfied for the successful environmental release of the genetically engineered organisms produced in paratransgenesis are considered.

Jejunoileal mucosal growth in mice with a limited microbiome

Previous work demonstrated enhanced enterocyte proliferation and mucosal growth in gnotobiotic mice, suggesting that intestinal flora participate in mucosal homeostasis. Furthermore, broad-spectrum enteral antibiotics are known to induce near germ-free (GF) conditions in mice with conventional flora (CONV). We hypothesized that inducing near GF conditions with broad-spectrum enteral antibiotics would cause ordered small intestinal mucosal growth in CONV mice but would have no effect in GF mice with no inherent microbiome. C57BL/6J CONV and GF mice received either an antibiotic solution (Ampicillin, Ciprofloxacin, Metronidazole, Vancomycin, Meropenem) or a vehicle alone. After treatment, small intestinal villus height (VH), crypt depth (CD), mucosal surface area (MSA), crypt proliferation index (CPI), apoptosis, and villus and crypt cell types were assessed. Antibiotic-treated CONV (Abx-CONV) mice had taller villi, deeper crypts, increased CPI, increased apoptosis, and greater MSA compared to vehicle-treated CONV mice. Minor differences were noted in enterocyte and enterochromaffin cell proportions between groups, but goblet and Paneth cell proportions were unchanged in Abx-CONV mice compared to vehicle-treated CONV mice (p>0.05). Antibiotics caused no significant changes in VH or MSA in GF mice when compared to vehicle-treated GF mice (p>0.05). Enteral administration of broad-spectrum antibiotics to mice with a conventional microbiome stimulates ordered small intestinal mucosal growth. Mucosal growth was not seen in germ-free mice treated with antibiotics, implying that intestinal mucosal growth is associated with change in the microbiome in this model.

The Intestinal Microbiota May Be a Potential Theranostic Tool for Personalized Medicine

The human intestine is colonized by a huge number of microorganisms from the moment of birth. This set of microorganisms found throughout the human body, is called the microbiota; the microbiome indicates the totality of genes that the microbiota can express, i.e., its genetic heritage. Thus, microbiota participates in and influences the proper functioning of the organism. The microbiota is unique for each person; it differs in the types of microorganisms it contains, the number of each microorganism, and the ratio between them, but mainly it changes over time and under the influence of many factors. Therefore, the correct functioning of the human body depends not only on the expression of its genes but also on the expression of the genes of the microorganisms it coexists with. This fact makes clear the enormous interest of community science in studying the relationship of the human microbiota with human health and the incidence of disease. The microbiota is like a unique personalized "mold" for each person; it differs quantitatively and qualitatively for the microorganisms it contains together with the relationship between them, and it changes over time and under the influence of many factors. We are attempting to modulate the microbial components in the human intestinal microbiota over time to provide positive feedback on the health of the host, from intestinal diseases to cancer. These interventions to modulate the intestinal microbiota as well as to identify the relative microbiome (genetic analysis) can range from dietary (with adjuvant prebiotics or probiotics) to fecal transplantation. This article researches the recent advances in these strategies by exploring their advantages and limitations. Furthermore, we aim to understand the relationship between intestinal dysbiosis and pathologies, through the research of resident microbiota, that would allow the personalization of the therapeutic antibiotic strategy.

Treatment With Multi-Species Probiotics Changes the Functions, Not the Composition of Gut Microbiota in Postmenopausal Women With Obesity: A Randomized, Double-Blind, Placebo-Controlled Study

Probiotics are known to regulate host metabolism. In randomized controlled trial we aimed to assess whether interventions with probiotic containing following strains: Bifidobacterium bifidum W23, Bifidobacterium lactis W51, Bifidobacterium lactis W52, Lactobacillus acidophilus W37, Levilactobacillus brevis W63, Lacticaseibacillus casei W56, Ligilactobacillus salivarius W24, Lactococcus lactis W19, and Lactococcus lactis W58 affect gut microbiota to promote metabolic effects. By 16S rRNA sequencing we analyzed the fecal microbiota of 56 obese, postmenopausal women randomized into three groups: (1) probiotic dose 2.5 × 10⁹ CFU/day (n = 18), (2) 1 × 10¹⁰ CFU/day (n = 18), or (3) placebo (n = 20). In the set of linear mixed-effects models, the interaction between pre- or post-treatment bacterial abundance and time on cardiometabolic parameters was significantly (FDR-adjusted) modified by type of intervention (26 and 19 three-way interactions for the pre-treatment and post-treatment abundance, respectively), indicating the modification of the bio-physiological role of microbiota by probiotics. For example, the unfavorable effects of Erysipelotrichi, Erysipelotrichales, and Erysipelotrichaceae on BMI might be reversed, but the beneficial effect of Betaproteobacteria on BMI was diminished by probiotic treatment. Proinflammatory effect of Bacteroidaceae was alleviated by probiotic administration. However, probiotics did not affect the microbiota composition, and none of the baseline microbiota-related features could predict therapeutic response as defined by cluster analysis. Conclusions: Probiotic intervention alters the influence of microbiota on biochemical, physiological and immunological parameters, but it does not affect diversity and taxonomic composition. Baseline microbiota is not a predictor of therapeutic response to a multispecies probiotic. Further multi-omic and mechanistic studies performed on the bigger cohort of patients are needed to elucidate the cardiometabolic effect of investigated probiotics in postmenopausal obesity.

Role of the Microbiome in Regulating Bone Metabolism and Susceptibility to Osteoporosis

The human microbiota functions at the interface between diet, medication-use, lifestyle, host immune development and health. It is therefore closely aligned with many of the recognised modifiable factors that influence bone mass accrual in the young, and bone maintenance and skeletal decline in older populations. While understanding of the relationship between micro-organisms and bone health is still in its infancy, two decades of broader microbiome research and discovery supports a role of the human gut microbiome in the regulation of bone metabolism and pathogenesis of osteoporosis as well as its prevention and treatment. Pre-clinical research has demonstrated biological interactions between the microbiome and bone metabolism. Furthermore, observational studies and randomized clinical trials have indicated that therapeutic manipulation of the microbiota by oral administration of probiotics may influence bone turnover and prevent bone loss in humans. In this paper, we summarize the content, discussion and conclusions of a workshop held by the Osteoporosis and Bone Research Academy of the Royal Osteoporosis Society in October, 2020. We provide a detailed review of the literature examining the relationship between the microbiota and bone health in animal models and in humans, as well as formulating the agenda for key research priorities required to advance this field. We also underscore the potential pitfalls in this research field that should be avoided and provide methodological recommendations to facilitate bridging the gap from promising concept to a potential cause and intervention target for osteoporosis.

Stool microbiota are superior to saliva in distinguishing cirrhosis and hepatic encephalopathy using machine learning

BACKGROUND & AIMS

Saliva and stool microbiota are altered in cirrhosis. Since stool is logistically difficult to collect compared to saliva, it is important to determine their relative diagnostic and prognostic capabilities. We aimed to determine the ability of stool vs. saliva microbiota to differentiate between groups based on disease severity using machine learning (ML).

METHODS

Controls and outpatients with cirrhosis underwent saliva and stool microbiome analysis. Controls vs. cirrhosis and within cirrhosis (based on hepatic encephalopathy [HE], proton pump inhibitor [PPI] and rifaximin use) were classified using 4 ML techniques (random forest [RF], support vector machine, logistic regression, and gradient boosting) with AUC comparisons for stool, saliva or both sample types. Individual microbial contributions were computed using feature importance of RF and Shapley additive explanations. Finally, thresholds for including microbiota were varied between 2.5% and 10%, and core microbiome (DESeq2) analysis was performed.

RESULTS

Two hundred and sixty-nine participants, including 87 controls and 182 patients with cirrhosis, of whom 57 had HE, 78 were on PPIs and 29 on rifaximin were included. Regardless of the ML model, stool microbiota had a significantly higher AUC in differentiating groups vs. saliva. Regarding individual microbiota: autochthonous taxa drove the difference between controls vs. patients with cirrhosis, oral-origin microbiota the difference between PPI users/non-users, and pathobionts and autochthonous taxa the difference between rifaximin users/non-users and patients with/without HE. These were consistent with the core microbiome analysis results.

CONCLUSIONS

On ML analysis, stool microbiota composition is significantly more informative in differentiating between controls and patients with cirrhosis, and those with varying cirrhosis severity, compared to saliva. Despite logistic challenges, stool should be preferred over saliva for microbiome analysis.

LAY SUMMARY

Since it is harder to collect stool than saliva, we wanted to test whether microbes from saliva were better than stool in differentiating between healthy people and those with cirrhosis and, among those with cirrhosis, those with more severe disease. Using machine learning, we found that microbes in stool were more accurate than saliva alone or in combination, therefore, stool should be preferred for analysis and collection wherever possible.

Applications and Comparison of Dimensionality Reduction Methods for Microbiome Data

Dimensionality reduction techniques are a key component of most microbiome studies, providing both the ability to tractably visualize complex microbiome datasets and the starting point for additional, more formal, statistical analyses. In this review, we discuss the motivation for applying dimensionality reduction techniques, the special characteristics of microbiome data such as sparsity and compositionality that make this difficult, the different categories of strategies that are available for dimensionality reduction, and examples from the literature of how they have been successfully applied (together with pitfalls to avoid). We conclude by describing the need for further development in the field, in particular combining the power of phylogenetic analysis with the ability to handle sparsity, compositionality, and non-normality, as well as discussing current techniques that should be applied more widely in future analyses.

Vaginal microbiome of women with adenomyosis: A case-control study

Immune dysregulation can involve invasion and survival of endometrial glands inside the myometrium of the adenomyosis. There is limited available data concerning alterations of the bacterial microbiome in the reproductive tract of adenomyosis women. The present cross-sectional age-matched study aims to compare vaginal microbiota between women with and without adenomyosis. We recruited women with adenomyosis (N = 40) and age-matched women without adenomyosis (N = 40) from the Departments of Obstetrics and Gynaecology, Ramathibodi Hospital Mahidol University, from August 2020 to January 2021. Vaginal swab samples were collected from the participants. DNA isolation and bacterial 16s rDNA gene sequencing and data analyses were then performed. Comparison of the diversity of vaginal microbiota, microbiota composition, and the operational taxonomic unit (OTU) between adenomyosis and non-adenomyosis (control) groups were undertaken. Data from 40 and 38 women with and without adenomyosis, respectively, were analyzed. Alpha-diversity analysis (Chao1 index) at the species level showed higher vaginal microbial richness in the adenomyosis group when compared with the control group (p = 0.006). The linear discriminant analysis effect size technique (LeFSe) indicated an elevated abundance of several vaginal microbial taxa in the adenomyosis group, including Alloscardovia, Oscillospirales, Ruminoccoccaceae, UCG_002, Oscillospiraceae, Enhydrobacter, Megamonas, Moraxellaceae, Subdoligranulum, Selenomonadaceae, and Faecalibacterium. On the other hand, an increase in the abundance of Megaspehera, Fastidiosipila, Hungateiclostridiaceae, and Clostridia was identified in the control group. Vaginal community state type (CST)-III and -IV were dominated in adenomyosis, while only CST-IV was dominated in the non-adenomyosis group. Lactobacillus was the most abundant vaginal microbial in both groups. In this study, the differences in vaginal microbiome profile were noted between adenomyosis and non-adenomyosis group. The increasing of microbial richness was associated with adenomyosis. Nevertheless, further investigations were required to elucidate the mechanisms and apply them for clinical implications.

Exercise for the Diabetic Gut-Potential Health Effects and Underlying Mechanisms

It can be assumed that changes in the gut microbiota play a crucial role in the development of type 2 diabetes mellitus (T2DM). It is generally accepted that regular physical activity is beneficial for the prevention and therapy of T2DM. Therefore, this review analyzes the effects of exercise training on the gut microbiota composition and the intestinal barrier function in T2DM. The current literature shows that regular exercise can influence the gut microbiota composition and the intestinal barrier function with ameliorative effects on T2DM. In particular, increases in the number of short-chain fatty acid (SCFA)-producing bacteria and improvements in the gut barrier integrity with reduced endotoxemia seem to be key points for positive interactions between gut health and T2DM, resulting in improvements in low-grade systemic inflammation status and glycemic control. However, not all aspects are known in detail and further studies are needed to further examine the efficacy of different training programs, the role of myokines, SCFA-producing bacteria, and SCFAs in the relevant metabolic pathways. As microbial signatures differ in individuals who respond differently to exercise training programs, one scientific focus could be the development of computer-based methods for the personalized analysis of the gut microbiota in the context of a microbiota/microbiome-based training program.

Gut microbiome in neuropsychiatric disorders

ABSTRACT Background: Neuropsychiatric disorders are a significant cause of death and disability worldwide. The mechanisms underlying these disorders include a constellation of structural, infectious, immunological, metabolic, and genetic etiologies. Advances in next-generation sequencing techniques have demonstrated that the composition of the enteric microbiome is dynamic and plays a pivotal role in host homeostasis and several diseases. The enteric microbiome acts as a key mediator in neuronal signaling via metabolic, neuroimmune, and neuroendocrine pathways. Objective: In this review, we aim to present and discuss the most current knowledge regarding the putative influence of the gut microbiome in neuropsychiatric disorders. Methods: We examined some of the preclinical and clinical evidence and therapeutic strategies associated with the manipulation of the gut microbiome. Results: targeted taxa were described and grouped from major studies to each disease. Conclusions: Understanding the complexity of these ecological interactions and their association with susceptibility and progression of acute and chronic disorders could lead to novel diagnostic biomarkers based on molecular targets. Moreover, research on the microbiome can also improve some emerging treatment choices, such as fecal transplantation, personalized probiotics, and dietary interventions, which could be used to reduce the impact of specific neuropsychiatric disorders. We expect that this knowledge will help physicians caring for patients with neuropsychiatric disorders.

The Serum and Fecal Metabolomic Profiles of Growing Kittens Treated with Amoxicillin/Clavulanic Acid or Doxycycline

Simple Summary

This study investigated the impact of antibiotic treatment οn the serum and fecal metabolome (the collection of all small molecules produced by the gut bacteria and the host) of young cats. Thirty 2-month-old cats with an upper respiratory tract infection were treated with either amoxicillin/clavulanic acid for 20 days or doxycycline for 28 days. In addition, another 15 control cats that did not receive antibiotics were included. Blood was collected on days 0 (before treatment), 20/28 (last day of treatment), and 300 (10 months after the end of treatment), while feces were collected on days 0, 20/28, 60, 120, and 300. Seven serum and fecal metabolites differed between cats treated with antibiotics and control cats at the end of treatment period. Ten months after treatment, no metabolites differed from healthy cats, suggesting that amoxicillin/clavulanic acid or doxycycline treatment only temporarily affects the abundance of the serum and fecal metabolome.

Abstract

The long-term impact of antibiotics on the serum and fecal metabolome of kittens has not yet been investigated. Therefore, the objective of this study was to evaluate the serum and fecal metabolome of kittens with an upper respiratory tract infection (URTI) before, during, and after antibiotic treatment and compare it with that of healthy control cats. Thirty 2-month-old cats with a URTI were randomly assigned to receive either amoxicillin/clavulanic acid for 20 days or doxycycline for 28 days, and 15 cats of similar age were enrolled as controls. Fecal samples were collected on days 0, 20/28, 60, 120, and 300, while serum was collected on days 0, 20/28, and 300. Untargeted and targeted metabolomic analyses were performed on both serum and fecal samples. Seven metabolites differed significantly in antibiotic-treated cats compared to controls on day 20/28, with two differing on day 60, and two on day 120. Alterations in the pattern of serum amino acids, antioxidants, purines, and pyrimidines, as well as fecal bile acids, sterols, and fatty acids, were observed in antibiotic-treated groups that were not observed in control cats. However, the alterations caused by either amoxicillin/clavulanic acid or doxycycline of the fecal and serum metabolome were only temporary and were resolved by 10 months after their withdrawal.

The Neglected Gut Microbiome: Fungi, Protozoa, and Bacteriophages in Inflammatory Bowel Disease

The gut microbiome has been implicated in the pathogenesis of inflammatory bowel disease (IBD). Studies suggest that the IBD gut microbiome is less diverse than that of the unaffected population, a phenomenon often referred to as dysbiosis. However, these studies have heavily focused on bacteria, while other intestinal microorganisms-fungi, protozoa, and bacteriophages-have been neglected. Of the nonbacterial microbes that have been studied in relation to IBD, most are thought to be pathogens, although there is evidence that some of these species may instead be harmless commensals. In this review, we discuss the nonbacterial gut microbiome of IBD, highlighting the current biases, limitations, and outstanding questions that can be addressed with high-throughput DNA sequencing methods. Further, we highlight the importance of studying nonbacterial microorganisms alongside bacteria for a comprehensive view of the whole IBD biome and to provide a more precise definition of dysbiosis in patients. With the rise in popularity of microbiome-altering therapies for the treatment of IBD, such as fecal microbiota transplantation, it is important that we address these knowledge gaps to ensure safe and effective treatment of patients.

Implications of the Gut Microbiome in Sports

CONTEXT

Two-thirds of an individual's gut microbiota is unique and influenced by dietary and exercise habits, age, sex, genetics, ethnicity, antibiotics, health, and disease. It plays important roles in nutrient and vitamin metabolism, inflammatory modulation, immune system function, and overall health of an individual. Specifically, in sports it may help decrease recovery time and improve athletic performance.

EVIDENCE ACQUISITION

PubMed and Medline databases were used for the literature search. Bibliographies based on the original search were utilized to pursue further literature search.

STUDY DESIGN

Clinical review.

LEVEL OF EVIDENCE

Level 4.

RESULTS

Diet and exercise play very important roles in the composition of the gut microbiota in the athletic and nonathletic individual. Ingestion of carbohydrates during and after exercise seems to have an anti-inflammatory effect postexercise. Supplementation with probiotic seems to aid in recovery after exercise, too, especially restoring the "normal" gut microbiota. Physically active individuals of all levels have more alpha diversity and "health-promoting gut species" in their microbiome than nonactive individuals, along with higher concentrations of short-chain fatty acids (SCFA) and SCFA-producing organisms. However, exercise interventions should be longer than 8 weeks to see these positive characteristics. Immune function is highly influenced by the gut microbiota's response to exercise. A transient immune dysfunction occurs after prolonged high-intensity exercise, which correlates with microbiota dysregulation. Nevertheless, long-term exposure to exercise will enhance the immune response and lead to positive changes in the gut microbiota.

CONCLUSION

Although the exact mechanisms of the effects that diet, exercise, and genetics have on the gut microbiota remain largely unknown, there is evidence that suggests overall health benefits. In the athletic population, these benefits can ultimately lead to performance improvement.

Microbiome differential abundance methods produce different results across 38 datasets

Identifying differentially abundant microbes is a common goal of microbiome studies. Multiple methods are used interchangeably for this purpose in the literature. Yet, there are few large-scale studies systematically exploring the appropriateness of using these tools interchangeably, and the scale and significance of the differences between them. Here, we compare the performance of 14 differential abundance testing methods on 38 16S rRNA gene datasets with two sample groups. We test for differences in amplicon sequence variants and operational taxonomic units (ASVs) between these groups. Our findings confirm that these tools identified drastically different numbers and sets of significant ASVs, and that results depend on data pre-processing. For many tools the number of features identified correlate with aspects of the data, such as sample size, sequencing depth, and effect size of community differences. ALDEx2 and ANCOM-II produce the most consistent results across studies and agree best with the intersect of results from different approaches. Nevertheless, we recommend that researchers should use a consensus approach based on multiple differential abundance methods to help ensure robust biological interpretations.

Many microbiome differential abundance methods are available, but it lacks systematic comparison among them. Here, the authors compare the performance of 14 differential abundance testing methods on 38 16S rRNA gene datasets with two sample groups, and show ALDEx2 and ANCOM-II produce the most consistent results.

A systematic review of the factors influencing microbial colonization of the preterm infant gut

Prematurity coupled with the necessary clinical management of preterm (PT) infants introduces multiple factors that can interfere with microbial colonization. This study aimed to review the perinatal, physiological, pharmacological, dietary, and environmental factors associated with gut microbiota of PT infants. A total of 587 articles were retrieved from a search of multiple databases. Sixty studies were included in the review after removing duplicates and articles that did not meet the inclusion criteria. Review of this literature revealed that evidence converged on the effect of postnatal age, mode of delivery, use of antibiotics, and consumption of human milk in the composition of gut microbiota of PT infants. Less evidence was found for associations with race, sex, use of different fortifiers, macronutrients, and other medications. Future studies with rich metadata are needed to further explore the impact of the PT exposome on the development of the microbiota in this high-risk population.

Bile acids, gut microbiota and metabolic surgery

Metabolic surgery, or bariatric surgery, is currently the most effective approach for treating obesity and its complications. Vertical sleeve gastrectomy (VSG) and Roux-en-Y gastric bypass (RYGB) are the top two types of commonly performed metabolic surgery now. The precise mechanisms of how the surgeries work are still unclear, therefore much research has been conducted in this area. Gut hormones such as GLP-1 and PYY have been studied extensively in the context of metabolic surgery because they both participate in satiety and glucose homeostasis. Bile acids, whose functions cover intestinal lipid absorption and various aspects of metabolic regulation via the action of FXR, TGR5, and other bile acid receptors, have also been actively investigated as potential mediators of metabolic surgery. Additionally, gut microbiota and their metabolites have also been studied because they can affect metabolic health. The current review summarizes and compares the recent scientific progress made on identifying the mechanisms of RYGB and VSG. One of the long-term goals of metabolic/bariatric surgery research is to develop new pharmacotherapeutic options for the treatment of obesity and diabetes. Because obesity is a growing health concern worldwide, there is a dire need in developing novel non-invasive treatment options.

Exploring the Microbiome Analysis and Visualization Landscape

Research on the microbiome has boomed recently, which resulted in a wide range of tools, packages, and algorithms to analyze microbiome data. Here we investigate and map currently existing tools that can be used to perform visual analysis on the microbiome, and associate the including methods, visual representations and data features to the research objectives currently of interest in microbiome research. The analysis is based on a combination of a literature review and workshops including a group of domain experts. Both the reviewing process and workshops are based on domain characterization methods to facilitate communication and collaboration between researchers from different disciplines. We identify several research questions related to microbiomes, and describe how different analysis methods and visualizations help in tackling them.

A review and roadmap of the skin, lung and gut microbiota in systemic sclerosis

As our understanding of the genetic underpinnings of SSc increases, questions regarding the environmental trigger(s) that induce and propagate SSc in the genetically predisposed individual emerge. The interplay between the environment, the immune system, and the microbial species that inhabit the patient's skin and gastrointestinal tract is a pathobiological frontier that is largely unexplored in SSc. The purpose of this review is to provide an overview of the methodologies, experimental study results and future roadmap for elucidating the relationship between the SSc host and his/her microbiome.

Oral microbiome associated with lymph node metastasis in oral squamous cell carcinoma

Oral microbiota can alter cancer susceptibility and progression by modulating metabolism and inflammation. We assessed the association between the oral microbiome and lymph node (LN) metastasis in oral squamous cell carcinoma (OSCC). We collected a total of 54 saliva samples from patients with OSCC before surgery. LN metastasis was assessed based on postoperative pathological examination. We used QIIME2, linear discriminant analysis effect size (LEfSe), and PICRUSt2 methods to analyze microbial dysbiosis. A random forest classifier was used to assess whether the oral microbiome could predict LN metastasis. Among the 54 OSCC samples, 20 had LN metastasis, and 34 had no evidence of metastasis. There was a significant difference in β-diversity between the metastasis and no metastasis groups. Through LEfSe analysis, the metastasis group was enriched in the genera Prevotella, Stomatobaculum, Bifidobacterium, Peptostreptococcaceae, Shuttleworthia and Finegoldia. Pathways related to signal peptidase II were predominant in the no metastasis group. The RF model showed a modestly high accuracy for predicting metastasis. Differences in microbial community composition and functions were observed in the oral microbiome of patients with OSCC with and without LN metastasis. However, the finding that specific taxa may be associated with LN metastasis should be verified in a further prospective study.

Feasibility of an At-Home Adult Stool Specimen Collection Method in Rural Cambodia

The human microbiome has received significant attention over the past decade regarding its potential impact on health. Epidemiological and intervention studies often rely on at-home stool collection methods designed for high-resource settings, such as access to an improved toilet with a modern toilet seat. However, this is not always appropriate or applicable to low-resource settings. Therefore, the design of a user-friendly stool collection kit for low-resource rural settings is needed. We describe the development, assembly, and user experience of a simple and low-cost at-home stool collection kit for women living in rural Cambodia as part of a randomized controlled trial in 2020. Participants were provided with the stool collection kit and detailed verbal instruction. Enrolled women (n = 480) provided two stool specimens (at the start of the trial and after 12 weeks) at their home and brought them to the health centre that morning in a sterile collection container. User specimen collection compliance was high, with 90% (n = 434) of women providing a stool specimen at the end of the trial (after 12 weeks). This feasible and straightforward method has strong potential for similar or adapted use among adults residing in other rural or low-resource contexts.

Gut Microbiota Parameters Potentially Useful in Clinical Perspective

Interest in gut microbiota analyses is at an all-time high. Gut microbiota is thought to relate to an increasing range of diseases of interest to physicians and nutritionists. Overweight, obesity, response to diet, metabolic syndrome, low grade inflammation, diabetes and colon neoplasms could maybe be observed in microbiota if affordable markers were available. Possible biomarkers like the Firmicutes/Bacteroidetes ratio, the Gram-positive/Gram-negative ratio, the Prevotella/Bacteroides ratio, and the Fusobacterium nucleatum/Faecalibacterium prausnitzii ratio are here reviewed in a narrative way in the attempt to highlight their possible future role in routine practice and clinically relevant diagnostics.

Current Trends in IBD-Development of Mucosal-Based Biomarkers and a Novel Minimally Invasive Recoverable Sampling System

Despite recent developments in therapy for inflammatory bowel diseases (IBDs), there have been limited advances in diagnostic tools available to aid in disease management. A growing body of evidence suggests that there are important host-microbe interactions at the mucosal interface that modulate the inflammatory response in patients with IBD. Additionally, the importance of mucosal integrity and its disruption appears to be important in the pathophysiology and perpetuation of the disease. The ability to characterize this interface may provide valuable information for both disease monitoring and identification of new treatment targets. Endoscopy remains the primary tool for disease monitoring, and mucosal healing is the primary therapeutic target in IBD treatment. However, establishing mucosal healing requires repetitive endoscopic procedures, and endoscopy is limited by factors such as invasiveness, cost, and risk of adverse events. Moreover, the use of a bowel preparation for colonoscopies alters the mucus layer and thus perturbs evaluation of the host-microbe interaction. Stool sampling may also be inaccurate because it reflects the end state of metabolites and proteins, failing to take into account the degradation or alteration of substrates of interest by bacterial proteases and other enzymes during passage through the colon. A novel sampling capsule, called the Recoverable Sampling System (RSS), is being developed as a complementary tool to colonoscopy. The RSS is intended to be a platform for noninvasive autonomous sampling, preservation, handling, and storage of analytes of interest found in the gastrointestinal fluids. A proprietary preservative contained within the chambers of the capsule has been developed to stabilize DNA and proteins for ex vivo microbiome and metabolomics analyses. Surrogate markers such as SPP24 and GUCA2a have been identified to correlate with gut health, intestinal permeability, and inflammation and could be locally sampled by the RSS. The potential clinical utility of an RSS device is broad and would likely be able to guide therapy by allowing for more frequent disease monitoring, aiding in disease characterization, and facilitating in the identification of novel therapeutic targets.

Intestinal Bacteriophage Therapy: Looking for Optimal Efficacy

Several human intestinal microbiota studies suggest that bacteriophages, viruses infecting bacteria, play a role in gut homeostasis. Currently, bacteriophages are considered a tool to precisely engineer the intestinal microbiota, but they have also attracted considerable attention as a possible solution to fight against bacterial pathogens resistant to antibiotics. These two applications necessitate bacteriophages to reach and kill their bacterial target within the gut environment. Unfortunately, exploitable clinical data in this field are scarce. Here, we review the administration of bacteriophages to target intestinal bacteria in mammalian experimental models. While bacteriophage amplification in the gut was often confirmed, we found that in most studies, it had no significant impact on the load of the targeted bacteria. In particular, we observed that the outcome of bacteriophage treatments is linked to the behavior of the target bacteria toward each animal model. Treatment efficacy ranges from poor in asymptomatic intestinal carriage to high in intestinal disease. This broad range of efficacy underlines the difficulties to reach a consensus on the impact of bacteriophages in the gut and calls for deeper investigations of key parameters that influence the success of such interventions before launching clinical trials.

Gut microbiome and amyotrophic lateral sclerosis: A systematic review of current evidence

Amyotrophic lateral sclerosis (ALS), characterized by a loss of motor neurons in the brain and spinal cord, is a relatively rare but currently incurable neurodegenerative disease. The global incidence of ALS is estimated as 1.75 per 100,000 person-years and the global prevalence is estimated as 4.1-8.4 per 100,000 individuals. Contributions from outside the central nervous system to the etiology of ALS have been increasingly recognized. Gut microbiome is one of the most quickly growing fields of research for ALS. In this article, we performed a comprehensive review of the results from existing animal and human studies, to provide an up-to-date summary of the current research on gut microbiome and ALS. In brief, we found relatively consistent results from animal studies, suggesting an altered gut microbiome composition in experimental ALS. Publication bias might however be a concern. Findings from human studies are largely inconclusive. A few animal and human studies demonstrated the usefulness of intervention with microbial-derived metabolites in modulating the disease progression of ALS. We discussed potential methodological concerns in these studies, including study design, statistical power, handling process of biospecimens and sequencing data, as well as statistical methods and interpretation of results. Finally, we made a few proposals for continued microbiome research in ALS, with the aim to provide valid, reproducible, and translatable findings.

Efficacy of Probiotics as Prophylaxis for Urinary Tract Infections in Premenopausal Women: A Systematic Review and Meta-Analysis

INTRODUCTION

Although antibiotic therapy has been the mainstay of prophylaxis and treatment of urinary tract infections (UTIs), antibacterial resistance has led to increased incidence of infections and healthcare spending in both community-acquired and nosocomial UTIs. This has led to an active exploration of alternative remedies for both the prophylaxis and treatment of UTIs, especially in women with recurrent urinary tract infections. Probiotic supplementation is one novel intervention that has been studied as a prophylactic measure in patients with UTIs. The current systematic review and meta-analysis was conducted to evaluate the efficacy of probiotics for prophylaxis in UTIs in premenopausal women.

METHODS

Detailed search strategies for each electronic database were developed for PubMed, EMBASE, and Scopus to identify relevant literature published between 2001-2021. RevMan 5.3 statistical software was used to analyze data in studies. The random-effects model was used for pooling the data. The risk of bias and study quality were assessed using Cochrane Collaboration's tool for assessing risk of bias in included studies. The scope of focus for this review was premenopausal adult women with a history of one or more UTI. The intervention consisted of a probiotic regimen for which the goal was to enhance the defensive microflora of the urogenital tract. Studies comparing a probiotic regimen to a placebo regimen were included. These studies' primary outcome was the proportion of women with at least one symptomatic bacterial UTI in each group (i.e., UTI recurrence rate) in the 12-month period following probiotic intervention. This study extends the work of researchers who systematically investigated the scientific literature on probiotics in the prevention of urinary tract infections with a particular focus on premenopausal women.

RESULTS

After screening, three parallel-group randomized-controlled trials (RCTs) were included. We estimated the overall pooled data of these three studies with a total of 284 participants to have met the predefined inclusion criteria and were therefore included in this review. The results demonstrated that probiotics did not have a significant effect in the prophylaxis of UTIs. (Risk Ratio (RR): 0.59 confidence interval (CI): 0.26, 1.33), Heterogeneity: Chi² = 6.63, df = 2 (p = 0.04); I² =70%, Test for overall effect: Z = 1.27 (p = 0.20).  Conclusions: Probiotics did not demonstrate a significant benefit in reducing UTI recurrence compared to placebo in premenopausal women. However, more conclusive data is needed to determine the effect that probiotics have on strengthening the urogenital microbial barrier against pathogenic bacteria and protecting against UTI recurrence.

Oral Antibiotic Prophylaxis Reduces Surgical Site Infection and Anastomotic Leakage in Patients Undergoing Colorectal Cancer Surgery

BACKGROUND

Surgical-site infection (SSI) and anastomotic leakage (AL) are major complications following surgical resection of colorectal carcinoma (CRC). The beneficial effect of prophylactic oral antibiotics (OABs) on AL in particular is inconsistent. We investigated the impact of OABs on AL rates and on SSI.

METHODS

A systematic review and meta-analysis of recent RCTs and cohort studies was performed including patients undergoing elective CRC surgery, receiving OABs with or without mechanical bowel preparation (MBP). Primary outcomes were rates of SSI and AL. Secondarily, rates of SSI and AL were compared in broad-spectrum OABs and selective OABs (selective decontamination of the digestive tract (SDD)) subgroups.

RESULTS

Eight studies (seven RCTs and one cohort study) with a total of 2497 patients were included. Oral antibiotics combined with MBP was associated with a significant reduction in SSI (RR = 0.46, 95% confidence interval (CI) 0.31-0.69), I² = 1.03%) and AL rates (RR = 0.58, 95% CI 0.37-0.91, I² = 0.00%), compared to MBP alone. A subgroup analysis demonstrated that SDD resulted in a significant reduction in AL rates compared to broad-spectrum OABs (RR = 0.52, 95% CI 0.30 to 0.91), I² = 0.00%).

CONCLUSION

OABs in addition to MBP reduces SSI and AL rates in patients undergoing elective CRC surgery and, more specifically, SDD appears to be more effective compared to broad-spectrum OABs in reducing AL.

Bacillus subtilis Colonization of Arabidopsis thaliana Roots Induces Multiple Biosynthetic Clusters for Antibiotic Production

Beneficial and probiotic bacteria play an important role in conferring immunity of their hosts to a wide range of bacterial, viral, and fungal diseases. Bacillus subtilis is a Gram-positive bacterium that protects the plant from various pathogens due to its capacity to produce an extensive repertoire of antibiotics. At the same time, the plant microbiome is a highly competitive niche, with multiple microbial species competing for space and resources, a competition that can be determined by the antagonistic potential of each microbiome member. Therefore, regulating antibiotic production in the rhizosphere is of great importance for the elimination of pathogens and establishing beneficial host-associated communities. In this work, we used B. subtilis as a model to investigate the role of plant colonization in antibiotic production. Flow cytometry and imaging flow cytometry (IFC) analysis supported the notion that Arabidopsis thaliana specifically induced the transcription of the biosynthetic clusters for the non-ribosomal peptides surfactin, bacilysin, plipastatin, and the polyketide bacillaene. IFC was more robust in quantifying the inducing effects of A. thaliana, considering the overall heterogeneity of the population. Our results highlight IFC as a useful tool to study the effect of association with a plant host on bacterial gene expression. Furthermore, the common regulation of multiple biosynthetic clusters for antibiotic production by the plant can be translated to improve the performance and competitiveness of beneficial members of the plant microbiome.

Gut Microbiota in Psychiatric Disorders: A Systematic Review

OBJECTIVE

This systematic review sought to comprehensively summarize gut microbiota research in psychiatric disorders following PRISMA guidelines.

METHODS

Literature searches were performed on databases using keywords involving gut microbiota and psychiatric disorders. Articles in English with human participants up until February 13, 2020, were reviewed. Risk of bias was assessed using a modified Newcastle-Ottawa Scale for microbiota studies.

RESULTS

Sixty-nine of 4231 identified studies met the inclusion criteria for extraction. In most studies, gut microbiota composition differed between individuals with psychiatric disorders and healthy controls; however, limited consistency was observed in the taxonomic profiles. At the genus level, the most replicated findings were higher abundance of Bifidobacterium and lower abundance of Roseburia and Faecalibacterium among patients with psychiatric disorders.

CONCLUSIONS

Gut bacteria that produce short-chain fatty acids, such as Roseburia and Faecalibacterium, could be less abundant in patients with psychiatric disorders, whereas commensal genera, for example, Bifidobacterium, might be more abundant compared with healthy controls. However, most included studies were hampered by methodological shortcomings including small sample size, unclear diagnostics, failure to address confounding factors, and inadequate bioinformatic processing, which might contribute to inconsistent results. Based on our findings, we provide recommendations to improve quality and comparability of future microbiota studies in psychiatry.

Long-term association between diet quality and characteristics of the gut microbiome in the multiethnic cohort study

As past usual diet quality may affect gut microbiome (GM) composition, we examined the association of the Healthy Eating Index (HEI)-2015 assessed 21 and 9 years before stool collection with measures of fecal microbial composition in a subset of the Multiethnic Cohort. A total of 5936 participants completed a validated quantitative FFQ (QFFQ) at cohort entry (Q1, 1993-1996), 5280 at follow-up (Q3, 2003-2008) and 1685 also at a second follow-up (Adiposity Phenotype Study (APS), 2013-2016). All participants provided a stool sample in 2013-2016. Fecal microbial composition was obtained from 16S rRNA gene sequencing (V1-V3 regions). HEI-2015 scores were computed based on each QFFQ. Using linear regression adjusted for relevant covariates, we calculated associations of HEI-2015 scores with gut microbial diversity and 152 individual genera. The mean HEI-2015 scores increased from Q1 (67 (sd 10)) to Q3 (71 (sd 11)) and APS (72 (sd 10)). Alpha diversity assessed by the Shannon Index was significantly higher with increasing tertiles of HEI-2015. Of the 152 bacterial genera tested, seven (Anaerostipes, Coprococcus_2, Eubacterium eligens, Lachnospira, Lachnospiraceae_ND3007, Ruminococcaceae_UCG-013 and Ruminococcus_1) were positively and five (Collinsella, Parabacteroides, Ruminiclostridium_5, Ruminococcus gnavus and Tyzzerella) were inversely associated with HEI-2015 assessed in Q1, Q3 and APS. The estimates of change per unit of the HEI-2015 score associated with the abundance of these twelve genera were consistent across the three questionnaires. The quality of past diet, assessed as far as ∼20 years before stool collection, is equally predictive of GM composition as concurrently assessed diet, indicative of the long-term consistency of this relation.

The Role of the Oral Microbiota in the Etiopathogenesis of Oral Squamous Cell Carcinoma

Dysbiosis in the oral environment may play a role in the etiopathogenesis of oral squamous cell carcinoma (OSCC). This review aims to summarize the current knowledge about the association of oral microbiota with OSCC and to describe possible etiopathogenetic mechanisms involved in processes of OSCC development and progression. Association studies included in this review were designed as case–control/case studies, analyzing the bacteriome, mycobiome, and virome from saliva, oral rinses, oral mucosal swabs, or oral mucosal tissue samples (deep and superficial) and comparing the results in healthy individuals to those with OSCC and/or with premalignant lesions. Changes in relative abundances of specific bacteria (e.g., Porphyromonas gingivalis, Fusobacterium nucleatum, Streptococcus sp.) and fungi (especially Candida sp.) were associated with OSCC. Viruses can also play a role; while the results of studies investigating the role of human papillomavirus in OSCC development are controversial, Epstein–Barr virus was positively correlated with OSCC. The oral microbiota has been linked to tumorigenesis through a variety of mechanisms, including the stimulation of cell proliferation, tumor invasiveness, angiogenesis, inhibition of cell apoptosis, induction of chronic inflammation, or production of oncometabolites. We also advocate for the necessity of performing a complex analysis of the microbiome in further studies and of standardizing the sampling procedures by establishing guidelines to support future meta-analyses.