Bloom and bust: intestinal microbiota dynamics in response to hospital exposures and Clostridium difficile colonization or infection

Clinical effects of chemical drugs, fecal microbiota transplantation, probiotics, dietary fiber, and acupuncture in the treatment of chronic functional constipation: a systematic review and network meta-analysis

Currently, there are increasingly diverse treatment modalities for chronic functional constipation (CFC). This study aims to compare the relative efficacy and safety of chemical drugs, fecal microbiota transplantation (FMT), probiotics, dietary fiber, and acupuncture in the treatment of patients with CFC. We searched relevant randomized controlled trials (RCTs) published in five databases up to November 2023. Network meta-analysis (NMA) was carried out using R Studio 4.2.1. Cumulative ranking probability plots, assessed through the surface under the cumulative ranking (SUCRA), were employed to rank the included drugs for various outcome measures. We included a total of 45 RCT studies with 17 118 patients with CFC. From the SUCRA values and NMA results FMT showed the best utility in terms of clinical efficacy, Bristol stool form scale scores, patient assessment of constipation quality of life scores, and the treatment modality with the lowest ranked incidence of adverse effects was electroacupuncture. Subgroup analysis of the chemotherapy group showed that sodium A subgroup analysis of the chemical group showed that sodium picosulfate 10 mg had the highest clinical efficacy. FMT is more promising in the treatment of CFC and may be more effective in combination with the relatively safe treatment of acupuncture.

Characterization and dynamics of intestinal microbiota in patients with Clostridioides difficile colonization and infection

Gut microbiota dysbiosis increases the susceptibility to Clostridioides difficile infection (CDI). In this study, we monitored C. difficile colonization (CDC) patients from no CDC status (CDN) to CDC status (CDCp) and CDI patients from asymptomatic status before CDI (PRECDI), CDI status (ONCDI), to asymptomatic status after CDI (POSTCDI). Based on metagenomic sequencing, we aimed to investigate the interaction pattern between gut microbiota and C. difficile. There was no significant difference of microbiota diversity between CDN and CDCp. In CDCp, Bacteroidetes and short-chain fatty acid (SCFA)-producing bacteria increased, with a positive correlation between SCFA-producing bacteria and C. difficile colonization. Compared with PRECDI, ONCDI and POSTCDI showed a significant decrease in microbiota diversity, particularly in Bacteroidetes and SCFA-producing bacteria, with a positive correlation between opportunistic pathogen and C. difficile. Fatty acid metabolism, and amino acid biosynthesis were enriched in CDN, CDCp, and PRECDI, while bile secretion was enriched in ONCDI and POSTCDI. Microbiota and metabolic pathways interaction networks in CDN and CDCp were more complex, particularly pathways in fatty acid and bile acid metabolism. Increasing of Bacteroidetes and SCFA-producing bacteria, affecting amino acid and fatty acid metabolism, is associated with colonization resistance to C. difficile and inhibiting the development of CDI.

Bacillus siamensis Improves the Immune Status and Intestinal Health of Weaned Piglets by Improving Their Intestinal Microbiota

Previous studies on the early interference of gut microbiota by Bacillus siamensis (B. siamensis) in weaned piglets are rarely reported, and the present trial is a preliminary study. This experiment was conducted to investigate the effects of B. siamensis supplementation on the growth performance, serum biochemistry, immune response, fecal short-chain fatty acids and microbiota of weaned piglets. Sixty weaned piglets were randomly divided into a control group (CON) and a B. siamensis group (BS), which were fed a basal diet and the basal diet supplemented with 5 × 1010 CFU B. siamensis per kg, respectively. Each group had 3 replicates and 10 piglets per replicate. The trial lasted for 28 days. The results showed that B. siamensis significantly increased the serum growth hormone (GH) and insulin-like growth factor (IGF) in piglets. Compared with the CON group, the levels of serum immunoglobulin and inflammatory factors in the BS group were significantly improved. In addition, the serum concentrations of zonulin and endotoxin (ET) in the BS group were lower. The dietary addition of B. siamensis significantly increased fecal short-chain fatty acid (SCFA) levels in piglets. Notably, B. siamensis improved the microbial composition by increasing beneficial genera, including Weissella, Lachnospiraceae_NK4A136_group and Bifidobacterium, and decreasing pathogenic genera, including Pantoea, Fusobacterium and Gemella, in piglet feces. Correlation analysis showed that the benefits of dietary B. siamensis supplementation were closely related to its improved microbial composition. In summary, the addition of B. siamensis can improve the immunity function, inflammatory response, gut permeability and SCFA levels of weaned piglets, which may be achieved through the improvement of their microbiota.

Approach to the diagnosis and management of dysbiosis

All microorganisms like bacteria, viruses and fungi that reside within a host environment are considered a microbiome. The number of bacteria almost equal that of human cells, however, the genome of these bacteria may be almost 100 times larger than the human genome. Every aspect of the physiology and health can be influenced by the microbiome living in various parts of our body. Any imbalance in the microbiome composition or function is seen as dysbiosis. Different types of dysbiosis are seen and the corresponding symptoms depend on the site of microbial imbalance. The contribution of the intestinal and extra-intestinal microbiota to influence systemic activities is through interplay between different axes. Whole body dysbiosis is a complex process involving gut microbiome and non-gut related microbiome. It is still at the stage of infancy and has not yet been fully understood. Dysbiosis can be influenced by genetic factors, lifestyle habits, diet including ultra-processed foods and food additives, as well as medications. Dysbiosis has been associated with many systemic diseases and cannot be diagnosed through standard blood tests or investigations. Microbiota derived metabolites can be analyzed and can be useful in the management of dysbiosis. Whole body dysbiosis can be addressed by altering lifestyle factors, proper diet and microbial modulation. The effect of these interventions in humans depends on the beneficial microbiome alteration mostly based on animal studies with evolving evidence from human studies. There is tremendous potential for the human microbiome in the diagnosis, treatment, and prognosis of diseases, as well as, for the monitoring of health and disease in humans. Whole body system-based approach to the diagnosis of dysbiosis is better than a pure taxonomic approach. Whole body dysbiosis could be a new therapeutic target in the management of various health conditions.

Long access heroin self-administration significantly alters gut microbiome composition and structure

Introduction

It is well known that chronic opioid use disorder is associated with alterations in gastrointestinal (GI) function that include constipation, reduced motility, and increased bacterial translocation due to compromised gut barrier function. These signs of disrupted GI function can be associated with alterations in the gut microbiome. However, it is not known if long-access opioid self-administration has effects on the gut microbiome.

Methods

We used 16S rRNA gene sequencing to investigate the gut microbiome in three independent cohorts (N=40 for each) of NIH heterogeneous stock rats before onset of long-access heroin self-administration (i.e., naïve status), at the end of a 15-day period of self-administration, and after post-extinction reinstatement. Measures of microbial α- and β-diversity were evaluated for all phases. High-dimensional class comparisons were carried out with MaAsLin2. PICRUSt2 was used for predicting functional pathways impacted by heroin based on marker gene sequences.

Results

Community α-diversity was not altered by heroin at any of the three phases by comparison to saline-yoked controls. Analyses of β-diversity showed that the heroin and saline-yoked groups clustered significantly apart from each other using the Bray-Curtis (community structure) index. Heroin caused significant alterations at the ASV level at the self-administration and extinction phases. At the phylum level, the relative abundance of Firmicutes was increased at the self-administration phase. Deferribacteres was decreased in heroin whereas Patescibacteria was increased in heroin at the extinction phase. Potential biomarkers for heroin emerged from the MaAsLin2 analysis. Bacterial metabolomic pathways relating to degradation of carboxylic acids, nucleotides, nucleosides, carbohydrates, and glycogen were increased by heroin while pathways relating to biosynthesis of vitamins, propionic acid, fatty acids, and lipids were decreased.

Discussion

These findings support the view that long access heroin self-administration significantly alters the structure of the gut microbiome by comparison to saline-yoked controls. Inferred metabolic pathway alterations suggest the development of a microbial imbalance favoring gut inflammation and energy expenditure. Potential microbial biomarkers and related functional pathways likely invoked by heroin self-administration could be targets for therapeutic intervention.

Fecal microbiota transplantation repairs intestinal permeability and regulates the expression of 5-HT to influence alcohol-induced depression-like behaviors in C57BL/6J mice

The epidemic of alcohol abuse affects millions of people worldwide. Relevant evidence supports the notion that the gut microbiota (GM) plays a crucial role in central nervous system (CNS) function, and its composition undergoes changes following alcohol consumption. Therefore, the purpose of this study was to investigate the effect of reconstructing the gut microbiota by fecal microbiota transplantation (FMT) on alcohol dependence. Here, we established an alcohol dependence model with C57BL/6J mice and proved that FMT treatment improved anxiety-like behavior and alcohol-seeking behavior in alcohol-dependent mice. Additionally, we found that the expression of the intestinal intercellular tight junction structure proteins ZO-1 and occludin was significantly increased after FMT. FMT repaired intestinal permeability in alcohol-dependent mice and decreased the levels of lipopolysaccharide (LPS) and proinflammatory factors. Moreover, the serotonin (5-hydroxytryptamine, 5-HT) content was significantly increased in alcohol-dependent mouse intestinal and brain tissues after receiving the fecal microbiome from healthy mice. 16S rRNA sequencing demonstrated that FMT markedly reshaped the composition of the gut microbiota and elicited changes in the intestinal barrier and 5-HT levels. Collectively, our results revealed that FMT has a palliative effect on alcohol dependence and explored the underlying mechanisms, which provides new strategies for the treatment of alcohol dependence.

Opioid trail: Tracking contributions to opioid use disorder from host genetics to the gut microbiome

Opioid use disorder (OUD) is a worldwide public health crisis with few effective treatment options. Traditional genetics and neuroscience approaches have provided knowledge about biological mechanisms that contribute to OUD-related phenotypes, but the complexity and magnitude of effects in the brain and body remain poorly understood. The gut-brain axis has emerged as a promising target for future therapeutics for several psychiatric conditions, so characterizing the relationship between host genetics and the gut microbiome in the context of OUD will be essential for development of novel treatments. In this review, we describe evidence that interactions between host genetics, the gut microbiome, and immune signaling likely play a key role in mediating opioid-related phenotypes. Studies in humans and model organisms consistently demonstrated that genetic background is a major determinant of gut microbiome composition. Furthermore, the gut microbiome is susceptible to environmental influences such as opioid exposure. Additional work focused on gene by microbiome interactions will be necessary to gain improved understanding of their effects on OUD-related behaviors.

A culture-based assessment of the microbiota of conventional and free-range chicken meat from Irish processing facilities

Chicken meat is the most popularly consumed meat worldwide, with free-range and ethically produced meat a growing market among consumers. However, poultry is frequently contaminated with spoilage microbes and zoonotic pathogens which impact the shelf-life and safety of the raw product, constituting a health risk to consumers. The free-range broiler microbiota is subject to various influences during rearing such as direct exposure to the external environment and wildlife which are not experienced during conventional rearing practices. Using culture-based microbiology approaches, this study aimed to determine whether there is a detectable difference in the microbiota from conventional and free-range broilers from selected Irish processing plants. This was done through analysis of the microbiological status of bone-in chicken thighs over the duration of the meat shelf-life. It was found that the shelf-life of these products was 10 days from arrival in the laboratory, with no statistically significant difference (P > 0.05) evident between free-range and conventionally raised chicken meat. A significant difference, however, was established in the presence of pathogenesis-associated genera in different meat processors. These results reinforce past findings which indicate that the processing environment and storage during shelf-life are key determinants of the microflora of chicken products reaching the consumer.

Diet, Gut Microbiome, and Their End Metabolites Associate With Acute Pancreatitis Risk

INTRODUCTION

Diet and decreased gut microbiome diversity has been associated with acute pancreatitis (AP) risk. However, differences in dietary intake, gut microbiome, and their impact on microbial end metabolites have not been studied in AP. We aimed to determine differences in (i) dietary intake (ii) gut microbiome diversity and sulfidogenic bacterial abundance, and (iii) serum short-chain fatty acid (SCFA) and hydrogen sulfide (H 2 S) concentrations in AP and control subjects.

METHODS

This case-control study recruited 54 AP and 46 control subjects during hospitalization. Clinical and diet data and stool and blood samples were collected. 16S rDNA sequencing was used to determine gut microbiome alpha diversity and composition. Serum SCFA and H 2 S levels were measured. Machine learning (ML) model was used to identify microbial targets associated with AP.

RESULTS

AP patients had a decreased intake of vitamin D 3 , whole grains, fish, and beneficial eicosapentaenoic, docosapentaenoic, and docosahexaenoic acids. AP patients also had lower gut microbiome diversity ( P = 0.021) and a higher abundance of sulfidogenic bacteria including Veillonella sp. and Haemophilus sp., which were associated with AP risk. Serum acetate and H 2 S concentrations were significantly higher in the AP group ( P < 0.001 and P = 0.043, respectively). ML model had 96% predictive ability to distinguish AP patients from controls.

DISCUSSION

AP patients have decreased beneficial nutrient intake and gut microbiome diversity. An increased abundance of H 2 S-producing genera in the AP and SCFA-producing genera in the control group and predictive ability of ML model to distinguish AP patients indicates that diet, gut microbiota, and their end metabolites play a key role in AP.

A self-knowledge distillation-driven CNN-LSTM model for predicting disease outcomes using longitudinal microbiome data

Motivation

Human microbiome is complex and highly dynamic in nature. Dynamic patterns of the microbiome can capture more information than single point inference as it contains the temporal changes information. However, dynamic information of the human microbiome can be hard to be captured due to the complexity of obtaining the longitudinal data with a large volume of missing data that in conjunction with heterogeneity may provide a challenge for the data analysis.

Results

We propose using an efficient hybrid deep learning architecture convolutional neural network-long short-term memory, which combines with self-knowledge distillation to create highly accurate models to analyze the longitudinal microbiome profiles to predict disease outcomes. Using our proposed models, we analyzed the datasets from Predicting Response to Standardized Pediatric Colitis Therapy (PROTECT) study and DIABIMMUNE study. We showed the significant improvement in the area under the receiver operating characteristic curve scores, achieving 0.889 and 0.798 on PROTECT study and DIABIMMUNE study, respectively, compared with state-of-the-art temporal deep learning models. Our findings provide an effective artificial intelligence-based tool to predict disease outcomes using longitudinal microbiome profiles from collected patients.

Availability and implementation

The data and source code can be accessed at https://github.com/darylfung96/UC-disease-TL.

HIV, opioid use, and alterations to the gut microbiome: elucidating independent and synergistic effects

Background

The microbiome is essential to immune development, defense against pathogens, and modulation of inflammation. Microbial dysbiosis has been reported in various diseases including human immunodeficiency virus (HIV) and opioid use disorder (OUD). Notably, people living with HIV (PLWH) have been reported to both have higher rates of OUD and use opioids at higher rates than the general public. Thus, studying gut microbial alterations in people living with HIV and with OUD could elucidate mechanisms pertaining to how these conditions both shape and are shaped by the microbiome. However, to date few studies have investigated how HIV and OUD in combination impact the microbiome.

Aim of review

Here, we review previous studies outlining interactions between HIV, opioid use, and microbial dysbiosis and describe attempts to treat this dysbiosis with fecal microbial transplantation, probiotics, and dietary changes.

Key scientific concepts of review

While the limited number of studies prevent overgeneralizations; accumulating data suggest that HIV and opioid use together induce distinct alterations in the gut microbiome. Among the three existing preclinical studies of HIV and opioid use, two studies reported a decrease in Lachnospiraceae and Ruminococcaceae, and one study reported a decrease in Muribaculaceae in the combined HIV and opioid group relative to HIV-alone, opioid-alone, or control groups. These bacteria are known to modulate immune function, decrease colonic inflammation, and maintain gut epithelial barrier integrity in healthy individuals. Accordingly, modulation of the gut microbiome to restore gut homeostasis may be attempted to improve both conditions. While mixed results exist regarding treating dysbiosis with microbial restoration in PLWH or in those with opioid dependency, larger well-defined studies that can improve microbial engraftment in hosts hold much promise and should still be explored.

Clostridioides difficile infection in patients with nonalcoholic fatty liver disease-current status

Nonalcoholic fatty liver disease (NAFLD) is the most common chronic liver disease, leading to fibrosis, cirrhosis and hepatocellular carcinoma and also associated with increased cardiovascular disease mortality. The pathogenesis of NAFLD is not fully understood, although NAFLD is thought to be a hepatic form of metabolic syndrome. There is an increasing understanding of the role of microbiota disturbances in NAFLD pathogenesis, and as with many other conditions affecting the microbiota, NAFLD may be a novel risk factor for Clostridioides difficile (C. difficile) colonization (CDC) and C. difficile infection (CDI). CDI is an emerging nosocomial disease, and community-acquired cases of infection are growing, probably due to an increase in CDC rates. The association of NAFLD with CDI has been shown in only 4 studies to date, three of which included less than 1000 patients, although the frequency of NAFLD in these studies was observed in almost 20% of the total patient cohort. These data revealed that NAFLD is a risk factor for CDI development and, moreover, is a risk factor for intestinal complications of CDI. More studies are needed to investigate this association and move forward CDC and CDI screening efforts for this group of patients.

A Taxonomy-Agnostic Approach to Targeted Microbiome Therapeutics-Leveraging Principles of Systems Biology

The study of human microbiomes has yielded insights into basic science, and applied therapeutics are emerging. However, conflicting definitions of what microbiomes are and how they affect the health of the "host" are less understood. A major impediment towards systematic design, discovery, and implementation of targeted microbiome therapeutics is the continued reliance on taxonomic indicators to define microbiomes in health and disease. Such reliance often confounds analyses, potentially suggesting associations where there are none, and conversely failing to identify significant, causal relationships. This review article discusses recent discoveries pointing towards a molecular understanding of microbiome "dysbiosis" and away from a purely taxonomic approach. We highlight the growing role of systems biological principles in the complex interrelationships between the gut microbiome and host cells, and review current approaches commonly used in targeted microbiome therapeutics, including fecal microbial transplant, bacteriophage therapies, and the use of metabolic toxins to selectively eliminate specific taxa from dysbiotic microbiomes. These approaches, however, remain wholly or partially dependent on the bacterial taxa involved in dysbiosis, and therefore may not capitalize fully on many therapeutic opportunities presented at the bioactive molecular level. New technologies capable of addressing microbiome-associated diseases as molecular problems, if solved, will open possibilities of new classes and categories of targeted microbiome therapeutics aimed, in principle, at all dysbiosis-driven disorders.

Antibiotic Knockdown of Gut Bacteria Sex-Dependently Enhances Intravenous Fentanyl Self-Administration in Adult Sprague Dawley Rats

Communication between the brain and gut bacteria impacts drug- and addiction-related behaviors. To investigate the role of gut microbiota on fentanyl reinforcement and reward, we depleted gut bacteria in adult Sprague Dawley male and female rats using an oral, nonabsorbable antibiotic cocktail and allowed rats to intravenously self-administer fentanyl on an escalating schedule of reinforcement. We found that antibiotic treatment enhanced fentanyl self-administration in males, but not females, at the lowest schedule of reinforcement (i.e., fixed ratio 1). Both males and females treated with antibiotics self-administered greater amounts of fentanyl at higher schedules of reinforcement. We then replete microbial metabolites via short-chain fatty acid administration to evaluate a potential mechanism in gut-brain communication and found that restoring metabolites decreases fentanyl self-administration back to controls at higher fixed ratio schedules of reinforcement. Our findings highlight an important relationship between the knockdown and rescue of gut bacterial metabolites and fentanyl self-administration in adult rats, which provides support for a significant relationship between the gut microbiome and opioid use. Further work in this field may lead to effective, targeted treatment interventions in opioid-related disorders.

A maximum-type microbial differential abundance test with application to high-dimensional microbiome data analyses

Background

High-throughput metagenomic sequencing technologies have shown prominent advantages over traditional pathogen detection methods, bringing great potential in clinical pathogen diagnosis and treatment of infectious diseases. Nevertheless, how to accurately detect the difference in microbiome profiles between treatment or disease conditions remains computationally challenging.

Results

In this study, we propose a novel test for identifying the difference between two high-dimensional microbiome abundance data matrices based on the centered log-ratio transformation of the microbiome compositions. The test p-value can be calculated directly with a closed-form solution from the derived asymptotic null distribution. We also investigate the asymptotic statistical power against sparse alternatives that are typically encountered in microbiome studies. The proposed test is maximum-type equal-covariance-assumption-free (MECAF), making it widely applicable to studies that compare microbiome compositions between conditions. Our simulation studies demonstrated that the proposed MECAF test achieves more desirable power than competing methods while having the type I error rate well controlled under various scenarios. The usefulness of the proposed test is further illustrated with two real microbiome data analyses. The source code of the proposed method is freely available at https://github.com/Jiyuan-NYU-Langone/MECAF.

Conclusions

MECAF is a flexible differential abundance test and achieves statistical efficiency in analyzing high-throughput microbiome data. The proposed new method will allow us to efficiently discover shifts in microbiome abundances between disease and treatment conditions, broadening our understanding of the disease and ultimately improving clinical diagnosis and treatment.

Associations of Mucosal Nerve Fiber Innervation Density with Hirschsprung-Associated Enterocolitis: A Retrospective Three-Center Cohort Study

OBJECTIVE

 Hirschsprung's disease (HSCR) is a congenital intestinal neurodevelopmental disorder characterized by the absence of enteric ganglion cells in the distal colon. Although Hirschsprung-associated enterocolitis (HAEC) is the most frequent life-threatening complication in HSCR, to date reliable biomarkers predicting the likelihood of HAEC are yet to be established. We established a three-center retrospective study including 104 HSCR patients surgically treated between 1998 and 2019.

MATERIALS AND METHODS

 Patient-derived cryopreserved or paraffin-preserved colonic tissue at surgery was analyzed via βIII-tubulin immunohistochemistry. We subsequently determined extrinsic mucosal nerve fiber density in resected rectosigmoid specimens and classified HSCR patients accordingly into nerve fiber-high or fiber-low groups. We compared the distribution of clinical parameters obtained from medical records between the fiber-high (n = 36) and fiber-low (n = 68) patient groups. We assessed the association between fiber phenotype and enterocolitis using univariate and multivariate logistic regression adjusted for age at operation.

RESULTS

 Enterocolitis was more prevalent in patients with sparse mucosal nerve fiber innervation (fiber-low phenotype, 87%) compared with the fiber-high phenotype (13%; p = 0.002). In addition, patients developing enterocolitis had a younger age at surgery (3 vs. 7 months; p = 0.016). In the univariate analysis, the odds for enterocolitis development in the fiber-low phenotype was 5.26 (95% confidence interval [CI], 1.67-16.59; p = 0.005) and 4.01 (95% CI, 1.22-13.17; p = 0.022) when adjusted for age.

CONCLUSION

 Here, we showed that HSCR patients with a low mucosal nerve fiber innervation grade in the distal aganglionic colon have a higher risk of developing HAEC. Consequently, histopathologic analysis of the nerve fiber innervation grade could serve as a novel sensitive prognostic marker associated with the development of enterocolitis in HSCR patients.

Gut community alterations associated with Clostridioides difficile colonization in hospitalized gastroenterological patients with or without inflammatory bowel disease

Clostridioides difficile colonization and development of infection commonly occur in inflammatory bowel disease (IBD) patients and can trigger flare-ups. Both conditions are inherently linked to disrupted gut microbiota. This study included 149 hospitalized gastrointestinal patients, which were divided into IBD (n = 48) and non-IBD patients (n = 101). Patients were tested for C. difficile colonization (qPCR and selective plating), and gut bacterial communities were analyzed with 16S amplicon sequencing. Blood test results were retrospectively collected from the medical records. IBD and non-IBD patients had comparable C. difficile colonization rates (31.7 and 33.3%, respectively). Compared to non-IBD C. difficile-non-colonized patients, IBD and C. difficile-colonized patients shared multiple common bacterial community characteristics including decreased diversity and reduced abundance of strict anaerobic bacteria. Furthermore, certain microbiota alterations were enhanced when IBD was accompanied by C. difficile colonization, indicating a synergistic effect between both medical complications. Conversely, certain microbial patterns were specific to C. difficile colonization, e.g., co-occurrence with Enterococcus, which was most common in IBD patients (81.3%).

Source of human milk (mother or donor) is more important than fortifier type (human or bovine) in shaping the preterm infant microbiome

Milk fortifiers help meet the nutritional needs of preterm infants receiving their mother’s own milk (MOM) or donor human milk. We conducted a randomized clinical trial (NCT03214822) in 30 very low birth weight premature neonates comparing bovine-derived human milk fortifier (BHMF) versus human-derived fortifier (H2MF). We found that fortifier type does not affect the overall microbiome, although H2MF infants were less often colonized by an unclassified member of Clostridiales Family XI. Secondary analyses show that MOM intake is strongly associated with weight gain and microbiota composition, including Bifidobacterium, Veillonella, and Propionibacterium enrichment. Finally, we show that while oxidative stress (urinary F2-isoprostanes) is not affected by fortifier type or MOM intake, fecal calprotectin is higher in H2MF infants and lower in those consuming more MOM. Overall, the source of human milk (mother versus donor) appears more important than the type of milk fortifier (human versus bovine) in shaping preterm infant gut microbiota.

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Milk fortifier type (human versus bovine) has little impact on the preterm microbiome

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Milk source (mother versus donor) is strongly associated with microbiome composition

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Feeding mother’s own milk is linked to better weight gain and less gut inflammation

Deciphering Resistome in Patients With Chronic Obstructive Pulmonary Diseases and Clostridioides difficile Infections

Antibiotics alter the gut microbiome and cause dysbiosis leading to antibiotic-resistant organisms. Different patterns of antibiotic administration cause a difference in bacterial composition and resistome in the human gut. We comprehensively investigated the association between the distribution of antibiotic resistance genes (ARGs), bacterial composition, and antibiotic treatments in patients with chronic obstructive pulmonary diseases (COPD) and Clostridioides difficile infections (CDI) who had chronic or acute intermittent use of antibiotics and compared them with healthy individuals. We analyzed the gut microbiomes of 61 healthy individuals, 16 patients with COPD, and 26 patients with CDI. The COPD patients were antibiotic-free before stool collection for a median of 40 days (Q1: 9.5; Q3: 60 days), while the CDI patients were antibiotic-free for 0 days (Q1: 0; Q3: 0.3). The intra-group beta diversity measured by the median Bray-Curtis index was the lowest for the healthy individuals (0.55), followed by the COPD (0.69) and CDI groups (0.72). The inter-group beta diversity was the highest among the healthy and CDI groups (median index = 0.89). The abundance of ARGs measured by the number of reads per kilobase per million reads (RPKM) was 684.2; 1,215.2; and 2,025.1 for the healthy, COPD, and CDI groups. It was negatively correlated with the alpha diversity of bacterial composition. For the prevalent ARG classes, healthy individuals had the lowest diversity and abundance of aminoglycoside, β-lactam, and macrolide-lincosamide-streptogramin (MLS) resistance genes, followed by the COPD and CDI groups. The abundances of Enterococcus and Escherichia species were positively correlated with ARG abundance and the days of antibiotic treatment, while Bifidobacterium and Ruminococcus showed negative correlations for the same. In addition, we analyzed the mobilome patterns of aminoglycoside and β-lactam resistance gene carriers using metagenomic sequencing data. In conclusion, the ARGs were significantly enhanced in the CDI and COPD groups than in healthy individuals. In particular, aminoglycoside and β-lactam resistance genes were more abundant in the CDI and COPD groups, but the dominant mobile genetic elements that enable the transfer of such genes showed similar prevalence patterns among the groups.

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.

Drugs and Bugs: The Gut-Brain Axis and Substance Use Disorders

Substance use disorders (SUDs) represent a significant public health crisis. Worldwide, 5.4% of the global disease burden is attributed to SUDs and alcohol use, and many more use psychoactive substances recreationally. Often associated with comorbidities, SUDs result in changes to both brain function and physiological responses. Mounting evidence calls for a precision approach for the treatment and diagnosis of SUDs, and the gut microbiome is emerging as a contributor to such disorders. Over the last few centuries, modern lifestyles, diets, and medical care have altered the health of the microbes that live in and on our bodies; as we develop, our diets and lifestyle dictate which microbes flourish and which microbes vanish. An increase in antibiotic treatments, with many antibiotic interventions occurring early in life during the microbiome's normal development, transforms developing microbial communities. Links have been made between the microbiome and SUDs, and the microbiome and conditions that are often comorbid with SUDs such as anxiety, depression, pain, and stress. A better understanding of the mechanisms influencing behavioral changes and drug use is critical in developing novel treatments for SUDSs. Targeting the microbiome as a therapeutic and diagnostic tool is a promising avenue of exploration. This review will provide an overview of the role of the gut-brain axis in a wide range of SUDs, discuss host and microbe pathways that mediate changes in the brain's response to drugs, and the microbes and related metabolites that impact behavior and health within the gut-brain axis.

Dose- and Sex-Dependent Bidirectional Relationship between Intravenous Fentanyl Self-Administration and Gut Microbiota

Gut bacteria influence neural circuits in addiction-related behaviors. Given the association between opioid use, gastrointestinal distress, and microbial dysbiosis in humans and mice, we test the hypothesis that interactions between gut bacteria and the brain mediate the rewarding and reinforcing properties of fentanyl. We implant rats with intravenous catheters in preparation for fentanyl intravenous self-administration (IVSA) on an escalating schedule of reinforcement to determine factors that influence fentanyl intake, including sex, dose, and gut microbiota. Our data show the impact of fentanyl IVSA on gut microbiota diversity, as well as the role of gut microbiota on fentanyl IVSA, in Sprague Dawley rats in a sex- and dose-dependent manner (n = 10–16/group). We found that the diversity of gut microbiota within females dose-dependently predicts progressive but not fixed ratio schedules of fentanyl IVSA. Depending on sex and fentanyl dose, alpha diversity (richness and evenness measured with Shannon index) is either increased or decreased following fentanyl IVSA and predicts progressive ratio breakpoint. Our findings collectively suggest a role of gut bacteria in drug-related behavior, including motivation and reinforcement. This work provides feasibility for an intravenous fentanyl self-administration model and uncovers potential factors mediating drug use, which may lead to the development of effective addiction interventions.

Effectiveness of Partially Hydrolyzed Guar Gum in Reducing Constipation in Long Term Care Facility Residents: A Randomized Single-Blinded Placebo-Controlled Trial

OBJECTIVES

To assess the effectiveness of partially hydrolyzed guar gum (PHGG) in improving constipation and reducing the use of laxatives among long term care facility (LTCF) residents.

DESIGN

A single-center, prospective, randomized, placebo-controlled, single-blinded parallel-group trial from September 2021 to November 2021.

SETTING

Four LTCF in Hong Kong.

PARTICIPANTS

Fifty-two LTCF residents with chronic constipation (mean age: 83.9±7.6 years, male 38%).

INTERVENTION

5g PHGG mixed with 200ml water per day for 4 weeks was given to intervention group participants. Control group received 200ml water for 4 weeks. Participants continued their usual as-needed laxative (lactulose, senna or dulcolax) on their own initiative.

MEASUREMENTS

Baseline measurements included age, gender, Charlson comorbidity index, Roackwood's Clinical Frailty Scale, body mass index and daily dietary fiber intake. Outcome measures were fecal characteristics assessed by Bristol Stool Form Scale, bowel opening frequency and laxative use frequency at baseline, first, second, third and fourth week of trial. Adverse events were measured. The study was registered on ClinicalTrial.gov; identifier: NCT05037565.

RESULTS

There was no significant difference in bowel frequency and stool characteristics between the treatment group and control group. However, there was a significantly lower frequency of lactulose, senna, and total laxative use in the treatment group compared with controls in the third and fourth week. There was no significant difference in adverse effects between the two groups.

CONCLUSION

This study showed that daily dietary fibre supplementation by using PHGG for 4 weeks in LTCF residents results in significantly less laxative use than placebo. It may be an effective way to reduce laxative dependence among older people living in LTCFs.

Fast and accurate metagenotyping of the human gut microbiome with GT-Pro

Single nucleotide polymorphisms (SNPs) in metagenomics are used to quantify population structure, track strains and identify genetic determinants of microbial phenotypes. However, existing alignment-based approaches for metagenomic SNP detection require high-performance computing and enough read coverage to distinguish SNPs from sequencing errors. To address these issues, we developed the GenoTyper for Prokaryotes (GT-Pro), a suite of methods to catalog SNPs from genomes and use unique k-mers to rapidly genotype these SNPs from metagenomes. Compared to methods that use read alignment, GT-Pro is more accurate and two orders of magnitude faster. Using high-quality genomes, we constructed a catalog of 104 million SNPs in 909 human gut species and used unique k-mers targeting this catalog to characterize the global population structure of gut microbes from 7,459 samples. GT-Pro enables fast and memory-efficient metagenotyping of millions of SNPs on a personal computer.

An integrative understanding of the large metabolic shifts induced by antibiotics in critical illness

Antibiotics are commonly used in the Intensive Care Unit (ICU); however, several studies showed that the impact of antibiotics to prevent infection, multi-organ failure, and death in the ICU is less clear than their benefit on course of infection in the absence of organ dysfunction. We characterized here the compositional and metabolic changes of the gut microbiome induced by critical illness and antibiotics in a cohort of 75 individuals in conjunction with 2,180 gut microbiome samples representing 16 different diseases. We revealed an "infection-vulnerable" gut microbiome environment present only in critically ill treated with antibiotics (ICU⁺). Feeding of Caenorhabditis elegans with Bifidobacterium animalis and Lactobacillus crispatus, species that expanded in ICU⁺ patients, revealed a significant negative impact of these microbes on host viability and developmental homeostasis. These results suggest that antibiotic administration can dramatically impact essential functional activities in the gut related to immune responses more than critical illness itself, which might explain in part untoward effects of antibiotics in the critically ill.

Assessment of independent comorbidities and comorbidity measures in predicting healthcare facility-onset Clostridioides difficile infection in Kenya

INTRODUCTION

Clostridioides difficile is primarily associated with hospital-acquired diarrhoea. The disease burden is aggravated in patients with comorbidities due to increased likelihood of polypharmacy, extended hospital stays and compromised immunity. The study aimed to investigate comorbidity predictors of healthcare facility-onset C. difficile infection (HO-CDI) in hospitalized patients.

METHODOLOGY

We performed a cross sectional study of 333 patients who developed diarrhoea during hospitalization. The patients were tested for CDI. Data on demographics, admission information, medication exposure and comorbidities were collected. The comorbidities were also categorised according to Charlson Comorbidity Index (CCI) and Elixhauser Comorbidity Index (ECI). Comorbidity predictors of HO-CDI were identified using multiple logistic regression analysis.

RESULTS

Overall, 230/333 (69%) patients had comorbidities, with the highest proportion being in patients aged over 60 years. Among the patients diagnosed with HO-CDI, 63/71(88.7%) reported comorbidities. Pairwise comparison between HO-CDI patients and comparison group revealed significant differences in hypertension, anemia, tuberculosis, diabetes, chronic kidney disease and chronic obstructive pulmonary disease. In the multiple logistic regression model significant predictors were chronic obstructive pulmonary disease (odds ratio [OR], 9.51; 95% confidence interval [CI], 1.8-50.1), diabetes (OR, 3.56; 95% CI, 1.11-11.38), chronic kidney disease (OR, 3.88; 95% CI, 1.57-9.62), anemia (OR, 3.67; 95% CI, 1.61-8.34) and hypertension (OR, 2.47; 95% CI, 1.-6.07). Among the comorbidity scores, CCI score of 2 (OR 6.67; 95% CI, 2.07-21.48), and ECI scores of 1 (OR, 4.07; 95% CI, 1.72-9.65), 2 (OR 2.86; 95% CI, 1.03-7.89), and ≥ 3 (OR, 4.87; 95% CI, 1.40-16.92) were significantly associated with higher odds of developing HO-CDI.

CONCLUSION

Chronic obstructive pulmonary disease, chronic kidney disease, anemia, diabetes, and hypertension were associated with an increased risk of developing HO-CDI. Besides, ECI proved to be a better predictor for HO-CDI. Therefore, it is imperative that hospitals should capitalize on targeted preventive approaches in patients with these underlying conditions to reduce the risk of developing HO-CDI and limit potential exposure to other patients.

Towards the biogeography of prokaryotic genes

Microbial genes encode the majority of the functional repertoire of life on earth. However, despite increasing efforts in metagenomic sequencing of various habitats^1-3, little is known about the distribution of genes across the global biosphere, with implications for human and planetary health. Here we constructed a non-redundant gene catalogue of 303 million species-level genes (clustered at 95% nucleotide identity) from 13,174 publicly available metagenomes across 14 major habitats and use it to show that most genes are specific to a single habitat. The small fraction of genes found in multiple habitats is enriched in antibiotic-resistance genes and markers for mobile genetic elements. By further clustering these species-level genes into 32 million protein families, we observed that a small fraction of these families contain the majority of the genes (0.6% of families account for 50% of the genes). The majority of species-level genes and protein families are rare. Furthermore, species-level genes, and in particular the rare ones, show low rates of positive (adaptive) selection, supporting a model in which most genetic variability observed within each protein family is neutral or nearly neutral.

The Microbiome-Gut-Brain Axis, a Potential Therapeutic Target for Substance-Related Disorders

Substance addiction is a complex worldwide public health problem. It endangers both personal life and social stability, causing great loss on economy. Substance-related disorder is considered to be a complicated chronic brain disorder. It resulted from interactions among pharmacological properties of addictive substances, individual susceptibility, and social–environmental factors. Unfortunately, there is still no ideal treatment for this disorder. Recent lines of evidence suggest that gut microbiome may play an important role in the pathogenesis of neuropsychiatric disorders, including substance-related disorders. This review summarizes the research on the relationship between gut microbiome and substance-related disorders, including different types of substance, different individual susceptibility, and the occurrence and development of substance-induced mental disorders. We also discuss the potentiation of gut microbiome in the treatment of substance-related disorders, especially in the treatment of substance-induced mental disorders and manipulation on individuals’ responsiveness to addictive substances.

The effect of opioids on gastrointestinal function in the ICU

Gastrointestinal (GI) dysfunction is common in the critical care setting and is highly associated with clinical outcomes. Opioids increase the risk for GI dysfunction and are frequently prescribed to reduce pain in critically ill patients. However, the role of opioids in GI function remains uncertain in the ICU. This review aims to describe the effect of opioids on GI motility, their potential risk of increasing infection and the treatment of GI dysmotility with opioid antagonists in the ICU setting.

Impact of non-antibiotic drugs on the human intestinal microbiome

INTRODUCTION

The gut microbiota is composed of trillions of microbial cells and viruses that interact with hosts. The composition of the gut microbiota is influenced by several factors including age, diet, diseases, or medications. The impact of drugs on the microbiota is not limited to antibiotics and many non-antibiotic molecules significantly alter the composition of the intestinal microbiota.

AREAS COVERED

This review focuses on the impact of four of the most widely prescribed non-antibiotic drugs in the world: Proton-pump inhibitors, metformin, statins, and non-steroidal anti-inflammatory. We conducted a systematic review by searching online databases including Medline, Web of science, and Scopus for indexed articles published in English until February 2021. We included studies assessing the intestinal microbiome alterations associated with proton pump inhibitors (PPIs), metformin, statins, and nonsteroidal anti-inflammatory drugs (NSAIDs). Only studies using culture-independent molecular techniques were included.

EXPERT OPINION

The taxonomical signature associated with non-antibiotic drugs are not yet fully described, especially in the field of metabolomic. The identification of taxonomic profiles associated a specific molecule provides information on its mechanism of action through interaction with the intestinal microbiota. Many side effects could be related to the dysbiosis induced by these molecules.

Human host status inference from temporal microbiome changes via recurrent neural networks

With the rapid increase in sequencing data, human host status inference (e.g. healthy or sick) from microbiome data has become an important issue. Existing studies are mostly based on single-point microbiome composition, while it is rare that the host status is predicted from longitudinal microbiome data. However, single-point-based methods cannot capture the dynamic patterns between the temporal changes and host status. Therefore, it remains challenging to build good predictive models as well as scaling to different microbiome contexts. On the other hand, existing methods are mainly targeted for disease prediction and seldom investigate other host statuses. To fill the gap, we propose a comprehensive deep learning-based framework that utilizes longitudinal microbiome data as input to infer the human host status. Specifically, the framework is composed of specific data preparation strategies and a recurrent neural network tailored for longitudinal microbiome data. In experiments, we evaluated the proposed method on both semi-synthetic and real datasets based on different sequencing technologies and metagenomic contexts. The results indicate that our method achieves robust performance compared to other baseline and state-of-the-art classifiers and provides a significant reduction in prediction time.

Fecal microbiota transplantation and antibiotic treatment attenuate naloxone-precipitated opioid withdrawal in morphine-dependent mice

Opioid addiction can produce severe side effects including physical dependence and withdrawal. Perturbations of the gut microbiome have recently been shown to alter opioid-induced side-effects such as addiction, tolerance and dependence. In the present study, we investigated the influence of the gut microbiome on opioid withdrawal by evaluating the effects of fecal microbiota transplantation (FMT), antibiotic and probiotic treatments, and pharmacological inhibition of gut permeability in a mouse model of opioid dependence. Repeated intraperitoneal (i.p.) morphine treatment produced physical dependence that was quantified by measuring somatic signs of withdrawal (i.e. number of jumps) precipitated using the opioid antagonist naloxone. Morphine-dependent mice that received FMT from morphine-treated donor mice exhibited fewer naloxone-precipitated jumps compared to morphine-dependent counterparts receiving FMT from saline-treated donor mice. Microbial contents in the mouse cecum were altered by morphine treatment but were not differentially impacted by FMT. A broad-spectrum antibiotic cocktail (ABX) regimen reduced the bacterial load and attenuated naloxone-precipitated morphine withdrawal in morphine-dependent mice, whereas commercially available probiotic strains did not reliably alter somatic signs of opioid withdrawal. ML-7, a pharmacological inhibitor of gut permeability, reduced the morphine-induced increase in gut permeability in vivo but did not reliably alter somatic signs of naloxone-precipitated opioid withdrawal. Our results suggest that the gut microbiome impacts the development of physical dependence induced by chronic morphine administration, and that therapeutic manipulations of the gut microbiome may reduce opioid withdrawal.

Genes Encoding Microbial Acyl Coenzyme A Binding Protein/Diazepam-Binding Inhibitor Orthologs Are Rare in the Human Gut Microbiome and Show No Links to Obesity

Acyl coenzyme A (CoA) binding protein (ACBP), also called diazepam-binding inhibitor (DBI), is a phylogenetically conserved protein that is expressed by all eukaryotic species as well as by some bacteria. Since elevated ACBP/DBI levels play a major role in the inhibition of autophagy, increase in appetite, and enhanced lipid storage that accompany obesity, we wondered whether ACBP/DBI produced by the human microbiome might affect host weight. We found that the genomes of bacterial commensals rarely contain ACBP/DBI homologues, which are rather encoded by genomes of some pathogenic or environmental taxa that were not prevalent in human feces. Exhaustive bioinformatic analyses of 1,899 gut samples from healthy individuals refuted the hypothesis that bacterial ACBP/DBI might affect the body mass index (BMI) in a physiological context. Thus, the physiological regulation of BMI is unlikely to be affected by microbial ACBP/DBI-like proteins. However, at the speculative level, it remains possible that ACBP/DBI produced by potential pathogenic bacteria might enhance their virulence by inhibiting autophagy and hence subverting innate immune responses.

IMPORTANCE Acyl coenzyme A (CoA) binding protein (ACBP) can be encoded by several organisms across the domains of life, including microbes, and has shown to play major roles in human metabolic processes. However, little is known about its presence in the human gut microbiome and whether its microbial counterpart could also play a role in human metabolism. In the present study, we found that microbial ACBP/DBI sequences were rarely present in the gut microbiome across multiple metagenomic data sets. Microbes that carried ACBP/DBI in the human gut microbiome included Saccharomyces cerevisiae, Lautropia mirabilis, and Comamonas kerstersii, but these microorganisms were not associated with body mass index, further indicating an unconvincing role for microbial ACBP/DBI in human metabolism.

The effect of prescribing antibiotics with opioids on the development of opioid use disorder: a national database study

The goal of this study was to examine the impact of inpatient- or emergency department- prescribed antibiotic treatment in combination with opioids on the risk of developing opioid use disorder 12 months following discharge from the hospital. The authors conducted a propensity score-matched cohort study with data from the TriNetX Research Network database to identify adult subjects (18-65 years old) with no previous history of an opioid use disorder. Three cohorts were defined for the analyses: subjects who were prescribed an opioid, opioid in combination with an antibiotic, or an antibiotic while in the emergency department or inpatient unit, from the years 2012 to 2018. The diagnosis of an Opioid Related Disorder (F11.10-F11.20) 12 months following discharge from the emergency department or inpatient unit was then observed within the cohorts following the index event as identified by the ICD-10 procedural coding system. Primary analysis (propensity-score matched on age and sex) showed that opioids prescribed in combination with antibiotics had a protective effect against the development of opioid use disorder. This effect was consistent throughout all of the years included in this study with the smallest protective effect observed in 2018 (2012 risk ratio = 1.27 (95% CI: 1.23, 1.32); 2018 risk ratio: 1.03 (95% CI: 1.01, 1.05). These findings suggest that opioids prescribed in combination with antibiotics in the hospital setting are protective against the development of OUD at later time points following hospital discharge.

Epidemiology of community-acquired and recurrent Clostridioides difficile infection

Clostridioides difficile infection is a leading cause of healthcare-associated infections with significant morbidity and mortality. For the past decade, the bulk of infection prevention and epidemiologic surveillance efforts have been directed toward mitigating hospital-acquired C. difficile. However, the incidence of community-associated infection is on the rise. Patients with community-associated C. difficile tend to be younger and have lower mortality rate. Rates of recurrent C. difficile infection overall have decreased in the United States, but future research and public health endeavors are needed to standardize and improve disease detection, stratify risk factors in large-scale population studies, and to identify regional and local variations in strain types, reservoirs and transmission routes to help characterize and combat the changing epidemiology of C. difficile.

Functional Restoration of Bacteriomes and Viromes by Fecal Microbiota Transplantation

BACKGROUND & AIMS

Fecal microbiota transplantation (FMT) is an effective therapy for recurrent Clostridioides difficile infection (rCDI). However, the overall mechanisms underlying FMT success await comprehensive elucidation, and the safety of FMT has recently become a serious concern because of the occurrence of drug-resistant bacteremia transmitted by FMT. We investigated whether functional restoration of the bacteriomes and viromes by FMT could be an indicator of successful FMT.

METHODS

The human intestinal bacteriomes and viromes from 9 patients with rCDI who had undergone successful FMT and their donors were analyzed. Prophage-based and CRISPR spacer-based host bacteria-phage associations in samples from recipients before and after FMT and in donor samples were examined. The gene functions of intestinal microorganisms affected by FMT were evaluated.

RESULTS

Metagenomic sequencing of both the viromes and bacteriomes revealed that FMT does change the characteristics of intestinal bacteriomes and viromes in recipients after FMT compared with those before FMT. In particular, many Proteobacteria, the fecal abundance of which was high before FMT, were eliminated, and the proportion of Microviridae increased in recipients. Most temperate phages also behaved in parallel with the host bacteria that were altered by FMT. Furthermore, the identification of bacterial and viral gene functions before and after FMT revealed that some distinctive pathways, including fluorobenzoate degradation and secondary bile acid biosynthesis, were significantly represented.

CONCLUSIONS

The coordinated action of phages and their host bacteria restored the recipients' intestinal flora. These findings show that the restoration of intestinal microflora functions reflects the success of FMT.

One dog's waste is another dog's wealth: A pilot study of fecal microbiota transplantation in dogs with acute hemorrhagic diarrhea syndrome

Canine acute hemorrhagic diarrhea syndrome (AHDS) has been associated in some studies with Clostridioides perfringens overgrowth and toxin-mediated necrosis of the intestinal mucosa. We aimed to determine the effect of a single fecal microbiota transplantation (FMT) on clinical scores and fecal microbiomes of 1 and 7 dogs with AHDS from New Zealand and South Africa. We hypothesized that FMT would improve AHDS clinical scores and increase microbiota alpha-diversity and short-chain fatty acid (SCFA)-producing microbial communities’ abundances in dogs with AHDS after FMT. We sequenced the V3-V4 region of the 16S-rRNA gene in the feces of AHDS FMT-recipients and sham-treated control dogs, and their healthy donors at admission, discharge, and 30 days post-discharge. There were no significant differences in median AHDS clinical scores between FMT-recipients and sham-treated controls at admission or discharge (P = 0.22, P = 0.41). At admission, the Shannon diversity index (SDI) was lower in AHDS dogs than healthy donors (P = 0.002). The SDI did not change from admission to 30 days in sham-treated dogs yet increased in FMT-recipients from admission to discharge (P = 0.04) to levels not different than donors (P = 0.33) but significantly higher than sham-treated controls (P = 0.002). At 30 days, the SDI did not differ between FMT recipients, sham-treated controls, and donors (P = 0.88). Principal coordinate analysis of the Bray-Curtis index separated post-FMT and donor dogs from pre-FMT and sham-treated dogs (P = 0.009) because of increased SCFA-producing genera’s abundances after FMT. A single co-abundance subnetwork contained many of the same OTUs found to be differentially abundant in FMT-recipients, and the abundance of this module was increased in FMT-recipients at discharge and 30 days, compared to sham-treated controls. We conclude in this small pilot study FMT did not have any clinical benefit. A single FMT procedure has the potential to increase bacterial communities of SCFA-producing genera important for intestinal health up to 30 days post-FMT.

Incidence and predictive biomarkers of Clostridioides difficile infection in hospitalized patients receiving broad-spectrum antibiotics

Trial enrichment using gut microbiota derived biomarkers by high-risk individuals can improve the feasibility of randomized controlled trials for prevention of Clostridioides difficile infection (CDI). Here, we report in a prospective observational cohort study the incidence of CDI and assess potential clinical characteristics and biomarkers to predict CDI in 1,007 patients ≥ 50 years receiving newly initiated antibiotic treatment with penicillins plus a beta-lactamase inhibitor, 3rd/4th generation cephalosporins, carbapenems, fluoroquinolones or clindamycin from 34 European hospitals. The estimated 90-day cumulative incidences of a first CDI episode is 1.9% (95% CI 1.1-3.0). Carbapenem treatment (Hazard Ratio (95% CI): 5.3 (1.7-16.6)), toxigenic C. difficile rectal carriage (10.3 (3.2-33.1)), high intestinal abundance of Enterococcus spp. relative to Ruminococcus spp. (5.4 (2.1-18.7)), and low Shannon alpha diversity index as determined by 16 S rRNA gene profiling (9.7 (3.2-29.7)), but not normalized urinary 3-indoxyl sulfate levels, predicts an increased CDI risk.

Lack of Mucosal Cholinergic Innervation Is Associated With Increased Risk of Enterocolitis in Hirschsprung's Disease

BACKGROUND & AIMS

Hirschsprung's disease (HSCR) is a congenital intestinal motility disorder defined by the absence of enteric neuronal cells (ganglia) in the distal gut. The development of HSCR-associated enterocolitis remains a life-threatening complication. Absence of enteric ganglia implicates innervation of acetylcholine-secreting (cholinergic) nerve fibers. Cholinergic signals have been reported to control excessive inflammation, but the impact on HSCR-associated enterocolitis is unknown.

METHODS

We enrolled 44 HSCR patients in a prospective multicenter study and grouped them according to their degree of colonic mucosal acetylcholinesterase-positive innervation into low-fiber and high-fiber patient groups. The fiber phenotype was correlated with the tissue cytokine profile as well as immune cell frequencies using Luminex analysis and fluorescence-activated cell sorting analysis of colonic tissue and immune cells. Using confocal immunofluorescence microscopy, macrophages were identified in close proximity to nerve fibers and characterized by RNA-seq analysis. Microbial dysbiosis was analyzed in colonic tissue using 16S-rDNA gene sequencing. Finally, the fiber phenotype was correlated with postoperative enterocolitis manifestation.

RESULTS

The presence of mucosal nerve fiber innervation correlated with reduced T-helper 17 cytokines and cell frequencies. In high-fiber tissue, macrophages co-localized with nerve fibers and expressed significantly less interleukin 23 than macrophages from low-fiber tissue. HSCR patients lacking mucosal nerve fibers showed microbial dysbiosis and had a higher incidence of postoperative enterocolitis.

CONCLUSIONS

The mucosal fiber phenotype might serve as a prognostic marker for enterocolitis development in HSCR patients and may offer an approach to personalized patient care and new therapeutic options.

Resilience of the oral microbiome

The human mouth harbors a complex microbiota, the composition of which is potentially influenced by a wide range of factors, including the intake of food and drink, the availability of endogenous nutrients, the host immune system, drug treatments, and systemic diseases. Despite these possible influences, the oral microbiota is remarkably resilient, particularly in comparison with the microbiota of the large intestine. Diet, with the exception of excessive and/or frequent consumption of fermentable carbohydrate or supplementation with nitrate, has minimal impact on the composition of the oral bacterial community. The common oral diseases dental caries and the periodontal diseases is associated with modification of the oral microbiota primarily as a result of the ecological changes induced by excessive acid production and inflammation, respectively. Systemically-administered antimicrobials have only a small effect on the composition of the oral bacterial community, and while locally delivered antimicrobials can have some clinical benefits, the biofilm lifestyle of oral bacteria lends them substantial resistance to the agents used. Saliva plays an important role in oral microbial ecology, by supplying nutrients and providing protection against colonization by nonoral organisms. Dry mouth is one condition that has a major effect on the microbiota, resulting in increased colonization by opportunistic pathogens. Some systemic diseases do affect the oral microbiome, notably diabetes, in which raised levels of glucose in saliva and tissue impact on bacterial nutrition.

Predictors of Clostridioides difficile Infection Among Asymptomatic, Colonized Patients: A Retrospective Cohort Study

BACKGROUND

Asymptomatic patients colonized with Clostridioides difficile are at risk of developing C. difficile infection (CDI), but the factors associated with disease onset are poorly understood. Our aims were to identify predictors of hospital-onset CDI (HO-CDI) among colonized patients and to explore the potential benefits of primary prophylaxis to prevent CDI.

METHODS

We conducted a retrospective cohort study in a tertiary academic institution. Colonized patients were identified by detecting the tcdB gene by polymerase chain reaction on a rectal swab. Univariate and multivariate logistic regression analyses were used to identify predictors of HO-CDI.

RESULTS

There were 19 112 patients screened, from which 960 (5%) colonized patients were identified: 513 met the inclusion criteria. Overall, 39 (7.6%) developed a HO-CDI, with a 30-day attributable mortality of 15%. An increasing length of stay (adjusted odds ratio [aOR] per day, 1.03; P = .006), exposure to multiple classes of antibiotics (aOR per class, 1.45; P = .02), use of opioids (aOR, 2.78; P = .007), and cirrhosis (aOR 5.49; P = .008) were independently associated with increased risks of HO-CDI, whereas the use of laxatives was associated with a lower risk of CDI (aOR 0.36; P = .01). Among the antimicrobials, B-lactam with B-lactamase inhibitors (OR 3.65; P < .001), first-generation cephalosporins (OR 2.38; P = .03), and carbapenems (OR 2.44; P = .03) correlated with the greatest risk of HO-CDI. By contrast, patient age, the use of proton pump inhibitors, and the use of primary prophylaxis were not significant predictors of HO-CDI.

CONCLUSIONS

This study identifies several factors that are associated with CDI among colonized patients. Whether modifying these variables could decrease the risk of CDI should be investigated.

Oxygen and Metabolism: Digesting Determinants of Antibiotic Susceptibility in the Gut

Microbial metabolism is a major determinant of antibiotic susceptibility. Environmental conditions that modify metabolism, notably oxygen availability and redox potential, can directly fine-tune susceptibility to antibiotics. Despite this, relatively few studies have discussed these modifications within the gastrointestinal tract and their implication on in vivo drug activity and the off-target effects of antibiotics in the gut. In this review, we discuss the environmental and biogeographical complexity of the gastrointestinal tract in regard to oxygen availability and redox potential, addressing how the heterogeneity of gut microhabitats may modify antibiotic activity in vivo. We contextualize the current literature surrounding oxygen availability and antibiotic efficacy and discuss empirical treatments. We end by discussing predicted patterns of antibiotic activity in prominent microbiome taxa, given gut heterogeneity, oxygen availability, and polymicrobial interactions. We also propose additional work required to fully elucidate the role of oxygen metabolism on antibiotic susceptibility in the context of the gut.

Zero-Inflated gaussian mixed models for analyzing longitudinal microbiome data

Motivation

The human microbiome is variable and dynamic in nature. Longitudinal studies could explain the mechanisms in maintaining the microbiome in health or causing dysbiosis in disease. However, it remains challenging to properly analyze the longitudinal microbiome data from either 16S rRNA or metagenome shotgun sequencing studies, output as proportions or counts. Most microbiome data are sparse, requiring statistical models to handle zero-inflation. Moreover, longitudinal design induces correlation among the samples and thus further complicates the analysis and interpretation of the microbiome data.

Results

In this article, we propose zero-inflated Gaussian mixed models (ZIGMMs) to analyze longitudinal microbiome data. ZIGMMs is a robust and flexible method which can be applicable for longitudinal microbiome proportion data or count data generated with either 16S rRNA or shotgun sequencing technologies. It can include various types of fixed effects and random effects and account for various within-subject correlation structures, and can effectively handle zero-inflation. We developed an efficient Expectation-Maximization (EM) algorithm to fit the ZIGMMs by taking advantage of the standard procedure for fitting linear mixed models. We demonstrate the computational efficiency of our EM algorithm by comparing with two other zero-inflated methods. We show that ZIGMMs outperform the previously used linear mixed models (LMMs), negative binomial mixed models (NBMMs) and zero-inflated Beta regression mixed model (ZIBR) in detecting associated effects in longitudinal microbiome data through extensive simulations. We also apply our method to two public longitudinal microbiome datasets and compare with LMMs and NBMMs in detecting dynamic effects of associated taxa.

Gut microbiome profiling of a rural and urban South African cohort reveals biomarkers of a population in lifestyle transition

BACKGROUND

Comparisons of traditional hunter-gatherers and pre-agricultural communities in Africa with urban and suburban Western North American and European cohorts have clearly shown that diet, lifestyle and environment are associated with gut microbiome composition. Yet, little is known about the gut microbiome composition of most communities in the very diverse African continent. South Africa comprises a richly diverse ethnolinguistic population that is experiencing an ongoing epidemiological transition and concurrent spike in the prevalence of obesity, largely attributed to a shift towards more Westernized diets and increasingly inactive lifestyle practices. To characterize the microbiome of African adults living in more mainstream lifestyle settings and investigate associations between the microbiome and obesity, we conducted a pilot study, designed collaboratively with community leaders, in two South African cohorts representative of urban and transitioning rural populations. As the rate of overweight and obesity is particularly high in women, we collected single time-point stool samples from 170 HIV-negative women (51 at Soweto; 119 at Bushbuckridge), performed 16S rRNA gene sequencing on these samples and compared the data to concurrently collected anthropometric data.

RESULTS

We found the overall gut microbiome of our cohorts to be reflective of their ongoing epidemiological transition. Specifically, we find that geographical location was more important for sample clustering than lean/obese status and observed a relatively higher abundance of the Melainabacteria, Vampirovibrio, a predatory bacterium, in Bushbuckridge. Also, Prevotella, despite its generally high prevalence in the cohorts, showed an association with obesity. In comparisons with benchmarked datasets representative of non-Western populations, relatively higher abundance values were observed in our dataset for Barnesiella (log2fold change (FC) = 4.5), Alistipes (log2FC = 3.9), Bacteroides (log2FC = 4.2), Parabacteroides (log2FC = 3.1) and Treponema (log2FC = 1.6), with the exception of Prevotella (log2FC = - 4.7).

CONCLUSIONS

Altogether, this work identifies putative microbial features associated with host health in a historically understudied community undergoing an epidemiological transition. Furthermore, we note the crucial role of community engagement to the success of a study in an African setting, the importance of more population-specific studies to inform targeted interventions as well as present a basic foundation for future research.

NBZIMM: negative binomial and zero-inflated mixed models, with application to microbiome/metagenomics data analysis

BACKGROUND

Microbiome/metagenomic data have specific characteristics, including varying total sequence reads, over-dispersion, and zero-inflation, which require tailored analytic tools. Many microbiome/metagenomic studies follow a longitudinal design to collect samples, which further complicates the analysis methods needed. A flexible and efficient R package is needed for analyzing processed multilevel or longitudinal microbiome/metagenomic data.

RESULTS

NBZIMM is a freely available R package that provides functions for setting up and fitting negative binomial mixed models, zero-inflated negative binomial mixed models, and zero-inflated Gaussian mixed models. It also provides functions to summarize the results from fitted models, both numerically and graphically. The main functions are built on top of the commonly used R packages nlme and MASS, allowing us to incorporate the well-developed analytic procedures into the framework for analyzing over-dispersed and zero-inflated count or proportion data with multilevel structures (e.g., longitudinal studies). The statistical methods and their implementations in NBZIMM particularly address the data characteristics and the complex designs in microbiome/metagenomic studies. The package is freely available from the public GitHub repository https://github.com/nyiuab/NBZIMM .

CONCLUSION

The NBZIMM package provides useful tools for complex microbiome/metagenomics data analysis.

The role of gut-immune-brain signaling in substance use disorders

Substance use disorders (SUDs) are debilitating neuropsychiatric conditions that exact enormous costs in terms of loss of life and individual suffering. While much progress has been made defining the neurocircuitry and intracellular signaling cascades that contribute to SUDs, these studies have yielded limited effective treatment options. This has prompted greater exploration of non-traditional targets in addiction. Emerging data suggest inputs from peripheral systems, such as the immune system and the gut microbiome, impact multiple neuropsychiatric diseases, including SUDs. Until recently the gut microbiome, peripheral immune system, and the CNS have been studied independently; however, current work shows the gut microbiome and immune system critically interact to modulate brain function. Additionally, the gut microbiome and immune system intimately regulate one another via extensive bidirectional communication. Accumulating evidence suggests an important role for gut-immune-brain communication in the pathogenesis of substance use disorders. Thus, a better understanding of gut-immune-brain signaling could yield important insight to addiction pathology and potential treatment options.

Quantitative characterization of Clostridioides difficile population in the gut microbiome of patients with C. difficile infection and their association with clinical factors

Objective was to analyse bacterial composition and abundance of Clostridioides difficile in gut microbiome of patients with C. difficile infection (CDI) in association with clinical characteristics. Whole metagenome sequencing of gut microbiome of 26 CDI patients was performed, and the relative abundance of C. difficile and its toxin genes was measured. Clinical characteristics of the patients were obtained through medical records. A strong correlation between the abundance of C. difficile and tcdB genes in CDI patients was found. The relative abundance of C. difficile in the gut microbiome ranged from undetectable to 2.8% (median 0.089). Patients with fever exhibited low abundance of C. difficile in their gut, and patients with fewer C. difficile organisms required long-term anti-CDI treatment. Abundance of Bifidobacterium and Bacteroides negatively correlated with that of C. difficile at the genus level. CDI patients were clustered using the bacterial composition of the gut: one with high population of Enterococcus (cluster 1, n = 12) and another of Bacteroides or Lactobacillus (cluster 2, n = 14). Cluster1 showed significantly lower bacterial diversity and clinical cure at the end of treatment. Additionally, patients with CDI exhibited increased ARGs; notably, bla_TEM, bla_SHV and bla_CTX-M were enriched. C. difficile existed in variable proportion of the gut microbiome in CDI patients. CDI patients with Enterococcus-rich microbiome in the gut had lower bacterial diversity and poorer clinical cure.

Understanding the impact of antibiotic perturbation on the human microbiome

The human gut microbiome is a dynamic collection of bacteria, archaea, fungi, and viruses that performs essential functions for immune development, pathogen colonization resistance, and food metabolism. Perturbation of the gut microbiome's ecological balance, commonly by antibiotics, can cause and exacerbate diseases. To predict and successfully rescue such perturbations, first, we must understand the underlying taxonomic and functional dynamics of the microbiome as it changes throughout infancy, childhood, and adulthood. We offer an overview of the healthy gut bacterial architecture over these life stages and comment on vulnerability to short and long courses of antibiotics. Second, the resilience of the microbiome after antibiotic perturbation depends on key characteristics, such as the nature, timing, duration, and spectrum of a course of antibiotics, as well as microbiome modulatory factors such as age, travel, underlying illness, antibiotic resistance pattern, and diet. In this review, we discuss acute and chronic antibiotic perturbations to the microbiome and resistome in the context of microbiome stability and dynamics. We specifically discuss key taxonomic and resistance gene changes that accompany antibiotic treatment of neonates, children, and adults. Restoration of a healthy gut microbial ecosystem after routine antibiotics will require rationally managed exposure to specific antibiotics and microbes. To that end, we review the use of fecal microbiota transplantation and probiotics to direct recolonization of the gut ecosystem. We conclude with our perspectives on how best to assess, predict, and aid recovery of the microbiome after antibiotic perturbation.

Microbiota in Clostridioides difficile-Associated Diarrhea: Comparison in Recurrent and Non-Recurrent Infections

Clostridioides difficile infection (CDI) is the leading cause of antibiotic-associated diarrhea, especially in hospitalized elderly patients, representing a global public health concern. Clinical presentations vary from mild diarrhea to severe pseudomembranous colitis that may progress to toxic megacolon or intestinal perforation. Antibiotic therapy is recognized as a risk factor and exacerbates dysbiosis of the intestinal microbiota, whose role in CDI is increasingly acknowledged. A clinically challenging complication is the development of recurrent disease (rCDI). In this study, using amplicon metagenomics, we compared the fecal microbiota of CDI and rCDI patients (sampled at initial and recurrent episode) and of non-infected controls. We also investigated whether CDI severity relates to specific microbiota compositions. rCDI patients showed a significantly decreased bacterial diversity as compared to controls (p < 0.01). The taxonomic composition presented significant shifts: both CDI and rCDI patients displayed significantly increased frequencies of Firmicutes, Peptostreptococcaceae, Clostridium XI, Clostridium XVIII, and Enterococcaceae. Porphyromonadaceae and, within it, Parabacteroides displayed opposite behaviors in CDI and rCDI, appearing discriminant between the two. Finally, the second episode of rCDI was characterized by significant shifts of unclassified Clostridiales, Escherichia/Shigella and Veillonella. No peculiar taxa composition correlated with the severity of infection, likely reflecting the role of host-related factors in determining severity.