Differences in gut microbiota composition and function were observed between patients with inflammatory bowel disease or irritable bowel syndrome.

Several gastrointestinal diseases show a sex imbalance, although the underlying (patho)physiological mechanisms behind this are not well understood. The gut microbiome may be involved in this process, forming a complex interaction with host immune system, sex hormones, medication and other environmental factors. Here we performed sex-specific analyses of fecal microbiota composition in 1135 individuals from a population-based cohort. The overall gut microbiome composition of females and males was significantly different (p = 0.001), with females showing a greater microbial diversity (p = 0.009). After correcting for the effects of intrinsic factors, smoking, diet and medications, female hormonal factors such as the use of oral contraceptives and undergoing an ovariectomy were associated with microbial species and pathways. Females had a higher richness of antibiotic-resistance genes, with the most notable being resistance to the lincosamide nucleotidyltransferase (LNU) gene family. The higher abundance of resistance genes is consistent with the greater prescription of the Macrolide-Lincosamide-Streptogramin classes of antibiotics to females. Furthermore, we observed an increased resistance to aminoglycosides in females with self-reported irritable bowel syndrome. These results throw light upon the effects of common medications that are differentially prescribed between sexes and highlight the importance of sex-specific analysis when studying the gut microbiome and resistome.

Proteins are heteropolymers that play important roles in virtually every biological reaction. While many proteins have well-defined three-dimensional structures that are inextricably coupled to their function, intrinsically disordered proteins (IDPs) do not have a well-defined structure, and it is this lack of structure that facilitates their function. As many IDPs are involved in essential cellular processes, various diseases have been linked to their malfunction, thereby making them important drug targets. In this review we discuss methods for studying IDPs and provide examples of how computational methods can improve our understanding of IDPs. We focus on two intensely studied IDPs that have been implicated in very different pathologic pathways. The first, p53, has been linked to over 50% of human cancers, and the second, Amyloid-β (Aβ), forms neurotoxic aggregates in the brains of patients with Alzheimer’s disease. We use these representative proteins to illustrate some of the challenges associated with studying IDPs and demonstrate how computational tools can be fruitfully applied to arrive at a more comprehensive understanding of these fascinating heteropolymers.

Summary: Synbiotics refer to combinations of probiotics and prebiotics that act synergistically to confer health benefits to the host. As a therapeutic strategy, they provide a gentle yet powerful method for modulating the composition and metabolic output of the human gut microbiota. In the context of achieving the UN Sustainable Development Goals, synbiotics have the potential to act as cost‐effective prophylactic measures against a variety of human ailments, ranging from infant diarrhoea to metabolic and inflammatory diseases in adults, by maintaining commensal microbial communities and metabolic networks that are conducive to human health.

Engineering functional amyloids through a modular genetic strategy represents new opportunities for creating multifunctional molecular materials with tailored structures and performance. Despite important advances, how fusion modules affect the self-assembly and functional properties of amyloids remains elusive. Here, using Escherichia coli curli as a model system, we systematically studied the effect of flanking domains on the structures, assembly kinetics and functions of amyloids. The designed amyloids were composed of E. coli biofilm protein CsgA (as amyloidogenic cores) and one or two flanking domains, consisting of chitin-binding domains (CBDs) from Bacillus circulans chitinase, and/or mussel foot proteins (Mfps). Incorporation of fusion domains did not disrupt the typical β-sheet structures, but indeed affected assembly rate, morphology, and stiffness of resultant fibrils. Consequently, the CsgA-fusion fibrils, particularly those containing three domains, were much shorter than the CsgA-only fibrils. Furthermore, the stiffness of the resultant fibrils was heavily affected by the structural feature of fusion domains, with β-sheet-containing domains tending to increase the Young's modulus while random coil domains decreasing the Young's modulus. In addition, fibrils containing CBD domains showed higher chitin-binding activity compared to their CBD-free counterparts. The CBD-CsgA-Mfp3 construct exhibited significantly lower binding activity than Mfp5-CsgA-CBD due to inappropriate folding of the CBD domain in the former construct, in agreement with results based upon molecular dynamics modeling. Our study provides new insights into the assembly and functional properties of designer amyloid proteins with increasing complex domain structures and lays the foundation for the future design of functional amyloid-based structures and molecular materials.

Microbially-derived short chain fatty acids (SCFAs) in the human gut are tightly coupled to host metabolism, immune regulation, and integrity of the intestinal epithelium. However, the production of SCFAs can vary widely between individuals consuming the same diet, with lower levels often associated with disease. A systems-scale mechanistic understanding of this heterogeneity is lacking. We present a microbial community-scale metabolic modeling (MCMM) approach to predict individual-specific SCFA production profiles. We assess the quantitative accuracy of our MCMMs using in vitro , ex vivo , and in vivo data. Next, we show how MCMM SCFA predictions are significantly associated with blood-derived clinical chemistries, including cardiometabolic and immunological health markers, across a large human cohort. Finally, we demonstrate how MCMMs can be leveraged to design personalized dietary, prebiotic, and probiotic interventions that optimize SCFA production in the gut. Our results represent an important advance in engineering gut microbiome functional outputs for precision health and nutrition.