Parabacteroides distasonis induces depressive-like behavior in a mouse model of Crohn's disease.

Patients with inflammatory bowel disease (IBD) are particularly susceptible to behavioral diagnoses, and the microbiome has been repeatedly implicated in the pathogenesis of IBD. The intestinal microbiome's ability to affect behavior has become increasingly recognized and studied. The so-called 'psychobiome' has been linked to a plethora of neurological and psychological diagnoses, including autism and Parkinson's disease. Despite the ability of many bacterial species within the human intestinal microbiome to synthesize neurotransmitters, it has never been previously reported that a single bacterial species is sufficient to induce depression. Here, we demonstrate that our mouse model of Crohn's disease (CD)-like ileitis, the SAMP1/YitFc (SAMP1), does not exhibit baseline behavioral abnormalities. By comparison, SAMP6 mice develop depressive-like behavior that is associated with a rise in the GABA-producing bacterial genus Parabacteroides. We finally demonstrate that administration of Parabacteroides distasonis into our SAMP1 mice induces depressive-like behavior. Colonization with P. distasonis was not associated with increased intestinal inflammation or alterations in other measures of behavior. The intestinal environment of CD may be particularly conducive to colonization with P. distasonis and subsequent induction of depressive-like behavior. To our knowledge, this is the first report of a bacterial species specifically inducing depressive-like behavior.

'Statistical Irreproducibility' Does Not Improve with Larger Sample Size: How to Quantify and Address Disease Data Multimodality in Human and Animal Research.

Poor study reproducibility is a concern in translational research. As a solution, it is recommended to increase sample size (N), i.e., add more subjects to experiments. The goal of this study was to examine/visualize data multimodality (data with >1 data peak/mode) as cause of study irreproducibility. To emulate the repetition of studies and random sampling of study subjects, we first used various simulation methods of random number generation based on preclinical published disease outcome data from human gut microbiota-transplantation rodent studies (e.g., intestinal inflammation and univariate/continuous). We first used unimodal distributions (one-mode, Gaussian, and binomial) to generate random numbers. We showed that increasing N does not reproducibly identify statistical differences when group comparisons are repeatedly simulated. We then used multimodal distributions (>1-modes and Markov chain Monte Carlo methods of random sampling) to simulate similar multimodal datasets A and B (t-test-p = 0.95; N = 100,000), and confirmed that increasing N does not improve the 'reproducibility of statistical results or direction of the effects'. Data visualization with violin plots of categorical random data simulations with five-integer categories/five-groups illustrated how multimodality leads to irreproducibility. Re-analysis of data from a human clinical trial that used maltodextrin as dietary placebo illustrated multimodal responses between human groups, and after placebo consumption. In conclusion, increasing N does not necessarily ensure reproducible statistical findings across repeated simulations due to randomness and multimodality. Herein, we clarify how to quantify, visualize and address disease data multimodality in research. Data visualization could facilitate study designs focused on disease subtypes/modes to help understand person-person differences and personalized medicine.

Textile Masks and Surface Covers-A Spray Simulation Method and a "Universal Droplet Reduction Model" Against Respiratory Pandemics.

The main form of COVID-19 transmission is via "oral-respiratory droplet contamination" (droplet: very small drop of liquid) produced when individuals talk, sneeze, or cough. In hospitals, health-care workers wear facemasks as a minimum medical "droplet precaution" to protect themselves. Due to the shortage of masks during the pandemic, priority is given to hospitals for their distribution. As a result, the availability/use of medical masks is discouraged for the public. However, for asymptomatic individuals, not wearing masks in public could easily cause the spread of COVID-19. The prevention of "environmental droplet contamination" (EnvDC) from coughing/sneezing/speech is fundamental to reducing transmission. As an immediate solution to promote "public droplet safety," we assessed household textiles to quantify their potential as effective environmental droplet barriers (EDBs). The synchronized implementation of a universal "community droplet reduction solution" is discussed as a model against COVID-19. Using a bacterial-suspension spray simulation model of droplet ejection (mimicking a sneeze), we quantified the extent by which widely available clothing fabrics reduce the dispersion of droplets onto surfaces within 1.8 m, the minimum distance recommended for COVID-19 "social distancing." All textiles reduced the number of droplets reaching surfaces, restricting their dispersion to <30 cm, when used as single layers. When used as double-layers, textiles were as effective as medical mask/surgical-cloth materials, reducing droplet dispersion to <10 cm, and the area of circumferential contamination to ~0.3%. The synchronized implementation of EDBs as a "community droplet reduction solution" (i.e., face covers/scarfs/masks and surface covers) will reduce COVID-19 EnvDC and thus the risk of transmitting/acquiring COVID-19.

Autologous fecal microbiota transplantation for the treatment of inflammatory bowel disease.

The term autologous fecal microbiota transplantation (a-FMT) refers herein to the use of one's feces during a healthy state for later use to restore gut microbial communities after perturbations. Generally, heterologous fecal microbiota transplantation (h-FMT), where feces from a ``healthy" donor is transplanted into a person with illness, has been used to treat infectious diseases such as recurrent Clostridioides difficile infection (CDI), with cure rates of up to 90%. In humans, due to limited response to medicines, h-FMT has become a hallmark intervention to treat CDI. Extrapolating the benefits from CDI, h-FMT has been attempted in various diseases, including inflammatory bowel disease (IBD), but clinical response has been variable and less effective (ranging between 24% and 50%). Differences in h-FMT clinical response could be because CDI is caused by a Clostridial infection, whereas IBD is a complex, microbiome-driven immunological inflammatory disorder that presents predominantly within the gut wall of genetically-susceptible hosts. FMT response variability could also be due to differences in microbiome composition between donors, recipients, and within individuals, which vary with diet, and environments, across regions. While donor selection has emerged as a key factor in FMT success, the use of heterologous donor stool still places the recipient at risk of exposure to infectious/pathogenic microorganisms. As an implementable solution, herein we review the available literature on a-FMT, and list some considerations on the benefits of a-FMT for IBD.

Artificial microbiome heterogeneity spurs six practical action themes and examples to increase study power-driven reproducibility.

With >70,000 yearly publications using mouse data, mouse models represent the best engrained research system to address numerous biological questions across all fields of science. Concerns of poor study and microbiome reproducibility also abound in the literature. Despite the well-known, negative-effects of data clustering on interpretation and study power, it is unclear why scientists often house >4 mice/cage during experiments, instead of ≤2. We hypothesized that this high animal-cage-density  practice abounds in published literature because more mice/cage could be perceived as a strategy to reduce housing costs. Among other sources of 'artificial' confounding, including cyclical oscillations of the 'dirty-cage/excrement microbiome', we ranked by priority the heterogeneity of modern husbandry practices/perceptions across three professional organizations that we surveyed in the USA. Data integration (scoping-reviews, professional-surveys, expert-opinion, and 'implementability-score-statistics') identified Six-Actionable Recommendation Themes (SART) as a framework to re-launch emerging protocols and intuitive statistical strategies to use/increase study power. 'Cost-vs-science' discordance was a major aspect explaining heterogeneity, and scientists' reluctance to change. With a 'housing-density cost-calculator-simulator' and fully-annotated statistical examples/code, this themed-framework streamlines the rapid analysis of cage-clustered-data and promotes the use of 'study-power-statistics' to self-monitor the success/reproducibility of basic and translational research. Examples are provided to help scientists document analysis for study power-based sample size estimations using preclinical mouse data to support translational clinical trials, as requested in NIH/similar grants or publications.

Regulation of Intestinal Inflammation by Dietary Fats.

With the epidemic of human obesity, dietary fats have increasingly become a focal point of biomedical research. Epidemiological studies indicate that high-fat diets (HFDs), especially those rich in long-chain saturated fatty acids (e.g., Western Diet, National Health Examination survey; NHANES 'What We Eat in America' report) have multi-organ pro-inflammatory effects. Experimental studies have confirmed some of these disease associations, and have begun to elaborate mechanisms of disease induction. However, many of the observed effects from epidemiological studies appear to be an over-simplification of the mechanistic complexity that depends on dynamic interactions between the host, the particular fatty acid, and the rather personalized genetics and variability of the gut microbiota. Of interest, experimental studies have shown that certain saturated fats (e.g., lauric and myristic fatty acid-rich coconut oil) could exert the opposite effect; that is, desirable anti-inflammatory and protective mechanisms promoting gut health by unanticipated pathways. Owing to the experimental advantages of laboratory animals for the study of mechanisms under well-controlled dietary settings, we focus this review on the current understanding of how dietary fatty acids impact intestinal biology. We center this discussion on studies from mice and rats, with validation in cell culture systems or human studies. We provide a scoping overview of the most studied diseases mechanisms associated with the induction or prevention of Inflammatory Bowel Disease in rodent models relevant to Crohn's Disease and Ulcerative Colitis after feeding either high-fat diet (HFD) or feed containing specific fatty acid or other target dietary molecule. Finally, we provide a general outlook on areas that have been largely or scarcely studied, and assess the effects of HFDs on acute and chronic forms of intestinal inflammation.

Human Gut Microbiome Transplantation in Ileitis Prone Mice: A Tool for the Functional Characterization of the Microbiota in Inflammatory Bowel Disease Patients.

BACKGROUND: Inflammatory bowel disease (IBD) is a lifelong digestive disease characterized by periods of severe inflammation and remission. To our knowledge, this is the first study showing a variable effect on ileitis severity from human gut microbiota isolated from IBD donors in remission and that of healthy controls in a mouse model of IBD. METHODS: We conducted a series of single-donor intensive and nonintensive fecal microbiota transplantation (FMT) experiments using feces from IBD patients in remission and healthy non-IBD controls (N = 9 donors) in a mouse model of Crohn's disease (CD)-like ileitis that develops ileitis in germ-free (GF) conditions (SAMP1/YitFC; N = 96 mice). RESULTS: Engraftment studies demonstrated that the microbiome of IBD in remission could have variable effects on the ileum of CD-prone mice (pro-inflammatory, nonmodulatory, or anti-inflammatory), depending on the human donor. Fecal microbiota transplantation achieved a 95% ± 0.03 genus-level engraftment of human gut taxa in mice, as confirmed at the operational taxonomic unit level. In most donors, microbiome colonization abundance patterns remained consistent over 60 days. Microbiome-based metabolic predictions of GF mice with Crohn's or ileitic-mouse donor microbiota indicate that chronic amino/fatty acid (valine, leucine, isoleucine, histidine; linoleic; P < 1e-15) alterations (and not bacterial virulence markers; P > 0.37) precede severe ileitis in mice, supporting their potential use as predictors/biomarkers in human CD. CONCLUSION: The gut microbiome of IBD remission patients is not necessarily innocuous. Characterizing the inflammatory potential of each microbiota in IBD patients using mice may help identify the patients' best anti-inflammatory fecal sample for future use as an anti-inflammatory microbial autograft during disease flare-ups.

Complementary and Alternative Medicine Strategies for Therapeutic Gut Microbiota Modulation in Inflammatory Bowel Disease and their Next-Generation Approaches.

The human gut microbiome exerts a major impact on human health and disease, and therapeutic gut microbiota modulation is now a well-advocated strategy in the management of many diseases, including inflammatory bowel disease (IBD). Scientific and clinical evidence in support of complementary and alternative medicine, in targeting intestinal dysbiosis among patients with IBD, or other disorders, has increased dramatically over the past years. Delivery of "artificial" stool replacements for fecal microbiota transplantation (FMT) could provide an effective, safer alternative to that of human donor stool. Nevertheless, optimum timing of FMT administration in IBD remains unexplored, and future investigations are essential.

Metabolic phenotyping for understanding the gut microbiome and host metabolic interplay.

There is growing interest in the role of the gut microbiome in human health and disease. This unique complex ecosystem has been implicated in many health conditions, including intestinal disorders, inflammatory skin diseases and metabolic syndrome. However, there is still much to learn regarding its capacity to affect host health. Many gut microbiome research studies focus on compositional analysis to better understand the causal relationships between microbial communities and disease phenotypes. Yet, microbial diversity and complexity is such that community structure alone does not provide full understanding of microbial function. Metabolic phenotyping is an exciting field in systems biology that provides information on metabolic outputs taking place in the system at a given moment in time. These readouts provide information relating to by-products of endogenous metabolic pathways, exogenous signals arising from diet, drugs and other lifestyle and environmental stimuli, as well as products of microbe-host co-metabolism. Thus, better understanding of the gut microbiome and host metabolic interplay can be gleaned using such analytical approaches. In this review, we describe research findings focussed on gut microbiota-host interactions, for functional insights into the impact of microbiome composition on host health. We evaluate different analytical approaches for capturing metabolic activity and discuss analytical methodological advancements that have made a contribution to the field. This information will aid in developing novel approaches to improve host health in the future, and therapeutic modulation of the microbiome may soon augment conventional clinical strategies.