Linking Inflammatory Bowel Disease Symptoms to Changes in the Gut Microbiome Structure and Function

Co-expression of fibrotic genes in inflammatory bowel disease; A localized event?

Introduction

Extracellular matrix turnover, a ubiquitous dynamic biological process, can be diverted to fibrosis. The latter can affect the intestine as a serious complication of Inflammatory Bowel Diseases (IBD) and is resistant to current pharmacological interventions. It embosses the need for out-of-the-box approaches to identify and target molecular mechanisms of fibrosis.

Methods and results

In this study, a novel mRNA sequencing dataset of 22 pairs of intestinal biopsies from the terminal ileum (TI) and the sigmoid of 7 patients with Crohn's disease, 6 with ulcerative colitis and 9 control individuals (CI) served as a validation cohort of a core fibrotic transcriptomic signature (FIBSig), This signature, which was identified in publicly available data (839 samples from patients and healthy individuals) of 5 fibrotic disorders affecting different organs (GI tract, lung, skin, liver, kidney), encompasses 241 genes and the functional pathways which derive from their interactome. These genes were used in further bioinformatics co-expression analyses to elucidate the site-specific molecular background of intestinal fibrosis highlighting their involvement, particularly in the terminal ileum. We also confirmed different transcriptomic profiles of the sigmoid and terminal ileum in our validation cohort. Combining the results of these analyses we highlight 21 core hub genes within a larger single co-expression module, highly enriched in the terminal ileum of CD patients. Further pathway analysis revealed known and novel inflammation-regulated, fibrogenic pathways operating in the TI, such as IL-13 signaling and pyroptosis, respectively.

Discussion

These findings provide a rationale for the increased incidence of fibrosis at the terminal ileum of CD patients and highlight operating pathways in intestinal fibrosis for future evaluation with mechanistic and translational studies.

GMEmbeddings: An R Package to Apply Embedding Techniques to Microbiome Data

Large-scale microbiome studies investigating disease-inducing microbial roles base their findings on differences between microbial count data in contrasting environments (e.g., stool samples between cases and controls). These microbiome survey studies are often impeded by small sample sizes and database bias. Combining data from multiple survey studies often results in obvious batch effects, even when DNA preparation and sequencing methods are identical. Relatedly, predictive models trained on one microbial DNA dataset often do not generalize to outside datasets. In this study, we address these limitations by applying word embedding algorithms (GloVe) and PCA transformation to ASV data from the American Gut Project and generating translation matrices that can be applied to any 16S rRNA V4 region gut microbiome sequencing study. Because these approaches contextualize microbial occurrences in a larger dataset while reducing dimensionality of the feature space, they can improve generalization of predictive models that predict host phenotype from stool associated gut microbiota. The GMEmbeddings R package contains GloVe and PCA embedding transformation matrices at 50, 100 and 250 dimensions, each learned using ∼15,000 samples from the American Gut Project. It currently supports the alignment, matching, and matrix multiplication to allow users to transform their V4 16S rRNA data into these embedding spaces. We show how to correlate the properties in the new embedding space to KEGG functional pathways for biological interpretation of results. Lastly, we provide benchmarking on six gut microbiome datasets describing three phenotypes to demonstrate the ability of embedding-based microbiome classifiers to generalize to independent datasets. Future iterations of GMEmbeddings will include embedding transformation matrices for other biological systems. Available at: https://github.com/MaudeDavidLab/GMEmbeddings.

Chronic pain and infection: mechanisms, causes, conditions, treatments, and controversies

Throughout human history, infection has been the leading cause of morbidity and mortality, with pain being one of the cardinal warning signs. However, in a substantial percentage of cases, pain can persist after resolution of acute illness, manifesting as neuropathic, nociplastic (eg, fibromyalgia, irritable bowel syndrome), or nociceptive pain. Mechanisms by which acute infectious pain becomes chronic are variable and can include immunological phenomena (eg, bystander activation, molecular mimicry), direct microbe invasion, central sensitization from physical or psychological triggers, and complications from treatment. Microbes resulting in a high incidence of chronic pain include bacteria such as the Borrelia species and Mycobacterium leprae, as well as viruses such as HIV, SARS-CoV-2 and herpeses. Emerging evidence also supports an infectious cause in a subset of patients with discogenic low back pain and inflammatory bowel disease. Although antimicrobial treatment might have a role in treating chronic pain states that involve active infectious inflammatory processes, their use in chronic pain conditions resulting from autoimmune mechanisms, central sensitization and irrevocable tissue (eg, arthropathy, vasculitis) or nerve injury, are likely to cause more harm than benefit. This review focuses on the relation between infection and chronic pain, with an emphasis on common viral and bacterial causes.