A mathematical model of Bacteroides thetaiotaomicron, Methanobrevibacter smithii, and Eubacterium rectale interactions in the human gut

The human gut microbiota is a complex ecosystem that affects a range of human physiology. In order to explore the dynamics of the human gut microbiota, we used a system of ordinary differential equations to model mathematically the biomass of three microorganism populations: $\textit{Bacteroides thetaiotaomicron}$, $\textit{Eubacterium rectale}$, and $\textit{Methanobrevibacter smithii}$. Additionally, we modeled the concentrations of relevant nutrients necessary to sustain these populations over time. Our model highlights the interactions and the competition among these three species. These three microorganisms were specifically chosen due to the system's end product, butyrate, which is a short chain fatty acid that aids in developing and maintaining the intestinal barrier in the human gut. The basis of our mathematical model assumes the gut is structured such that bacteria and nutrients exit the gut at a rate proportional to its volume, the rate of volumetric flow, and the biomass or concentration of the particular population or nutrient. We performed global sensitivity analyses using Sobol' sensitivities to estimate the relative importance of model parameters on simulation results

A mathematical model of <i>Bacteroides thetaiotaomicron</i>, <i>Methanobrevibacter smithii</i>, and <i>Eubacterium rectale</i> interactions in the human gut

The human gut microbiota is a complex ecosystem that affects a range of human physiology. In order to explore the dynamics of the human gut microbiota, we used a system of ordinary differential equations to model mathematically the biomass of three microorganism populations: Bacteroides thetaiotaomicron, Eubacterium rectale, and Methanobrevibacter smithii. Additionally, we modeled the concentrations of relevant nutrients necessary to sustain these populations over time. Our model highlights the interactions and the competition among these three species. These three microorganisms were specifically chosen due to the system’s end product, butyrate, which is a short chain fatty acid that aids in developing and maintaining the intestinal barrier in the human gut. The basis of our mathematical model assumes the gut is structured such that bacteria and nutrients exit the gut at a rate proportional to its volume, the rate of volumetric flow, and the biomass or concentration of the particular population or nutrient. We performed global sensitivity analyses using Sobol’ sensitivities to estimate the relative importance of model parameters on simulation results

Diet-microbiome-immune interplay in multiple sclerosis: Understanding the impact of phytoestrogen metabolizing gut bacteria

Multiple sclerosis (MS) is a chronic and progressive autoimmune disease of the central nervous system (CNS), with both genetic and environmental factors contributing to the pathobiology of the disease. Although HLA genes have emerged as the strongest genetic factor linked to MS, consensus on the environmental risk factors is lacking. Recently, the gut microbiota has garnered increasing attention as a potential environmental factor in MS, as mounting evidence suggests that individuals with MS exhibit microbial dysbiosis (changes in the gut microbiome). Thus, there has been a strong emphasis on understanding the role of the gut microbiome in the pathobiology of MS, specifically, factors regulating the gut microbiota and the mechanism(s) through which gut microbes may contribute to MS. Among all factors, diet has emerged to have the strongest influence on the composition and function of gut microbiota. As MS patients lack gut bacteria capable of metabolizing dietary phytoestrogen,we will specifically discuss the role of a phytoestrogen diet and phytoestrogen metabolizing gut bacteria in the pathobiology of MS. A better understanding of these mechanisms will help to harness the enormous potential of the gut microbiota as potential therapeutics to treat MS and other autoimmune diseases

Dietary Isoflavones Alter Gut Microbiota and Lipopolysaccharide Biosynthesis to Reduce Inflammation

The etiopathogenesis of multiple sclerosis (MS) is strongly affected by environmental factors such as diet and the gut microbiota. An isoflavone-rich (ISO) diet was previously shown to reduce the severity of MS in the animal model experimental autoimmune encephalomyelitis (EAE). Translation of this concept to clinical trial where dietary isoflavones may be recommended for MS patients will require preliminary evidence that providing the isoflavone-rich diet to people with MS (PwMS) who lack phytoestrogen-metabolizing bacteria has beneficial effects. We have previously shown that the gut microbiota of PwMS resembles the gut microbiota of mice raised under a phytoestrogen-free (phyto-free) diet in that it lacks phytoestrogen-metabolizing bacteria. To investigate the effects of phytoestrogens on the microbiota inflammatory response and EAE disease severity we switched the diet of mice raised under a phyto-free (PF) diet to an isoflavone-rich diet. Microbiota analysis showed that the change in diet from one that is ISO to one that is PF reduces beneficial bacteria such as Bifidobacterium species. In addition we observed functional differences in lipopolysaccharide (LPS) biosynthesis pathways. Moreover LPS extracted from feces of mice fed an ISO diet induced increased production of anti-inflammatory cytokines from bone marrow-derived macrophages relative to fecal-LPS isolated from mice fed a PF diet. Eventually mice whose diet was switched from a PF diet to an ISO diet trended toward reduced EAE severity and mortality. Overall we show that an isoflavone-rich diet specifically modulates LPS biosynthesis of the gut microbiota imparts an anti-inflammatory response and decreases disease severity

Airway Memory CD4 + T Cells Mediate Protective Immunity against Emerging Respiratory Coronaviruses

Two zoonotic coronaviruses (CoV), SARS-CoV and MERS-CoV have crossed species to cause severe human respiratory disease. Here, we showed that induction of airway memory CD4+ T cells specific for a conserved epitope shared by SARS-CoV and MERS-CoV is a potential strategy for developing pan-coronavirus vaccines. Airway memory CD4+ T cells differed phenotypically and functionally from lung-derived cells and were crucial for protection against both CoVs in mice. Protection was interferon-γ-dependent and required early induction of robust innate and virus-specific CD8+ T cell responses. The conserved epitope was also recognized in SARS-CoV and MERS-CoV-infected human leukocyte antigen DR2 and DR3 transgenic mice, indicating potential relevance in human populations. Additionally, this epitope was cross-protective between human and bat CoVs, the progenitors for many human CoVs. Vaccine strategies that induce airway memory CD4+ T cells targeting conserved epitopes may have broad applicability in the context of new CoV and other respiratory virus outbreaks

A UPLC-MS/MS Based Rapid, Sensitive, and Non-Enzymatic Methodology for Quantitation of Dietary Isoflavones in Biological Fluids

Dietary isoflavones, a type of phytoestrogens, have gained importance owing to their health-promoting benefits. However, the beneficial effects of isoflavones are mediated by smaller metabolites produced with the help of gut bacteria that are known to metabolize these phytoestrogenic compounds into Daidzein and Genistein and biologically active molecules such as S-Equol. Identifying and measuring these phytoestrogens and their metabolites is an important step towards understanding the significance of diet and gut microbiota in human health and diseases. We have overcome the reported difficulties in quantitation of these isoflavones and developed a simplified, sensitive, non-enzymatic, and sulfatases-free extraction methodology. We have subsequently used this method to quantify these metabolites in the urine of mice using UPLC-MS/MS. The extraction and quantitation method was validated for precision, linearity, accuracy, recoveries, limit of detection (LOD), and limit of quantification (LOQ). Linear calibration curves for Daidzein, Genistein, and S-Equol were set up by performing linear regression analysis and checked using the correlation coefficient (r2 > 0.995). LOQs for Daidzein, Genistein, and S-Equol were 2, 4, and 2 ng/mL, respectively. This UPLC-MS/MS swift method is suitable for quantifying isoflavones and the microbial-derived metabolite S-Equol in mice urine and is particularly useful for large numbers of samples