The mammalian gut is a complex environment where digestion, immune responses, and interactions with microbes occur. MicroRNAs (miRNAs), small non-coding RNA molecules that regulate gene expression, play significant roles in these processes. Importantly, these miRNAs are present in feces, presenting a non-invasive avenue to study gut health.
Motivated by the profound impact of these tiny molecules, microbiologist Emma Layton embarked on research to study fecal miRNAs during her graduate studies at the University of Manchester. However, she encountered challenges due to the lack of standardized methods for extracting RNA from fecal samples and constructing libraries for small RNA sequencing.
To address this, Layton and her team optimized a pipeline for detecting fecal miRNAs and demonstrated its effectiveness by profiling these molecules in mouse stool samples. Their findings, published in Nature Communications, provide a robust framework for isolating and sequencing fecal miRNAs, which could serve as biomarkers for diseases such as cancer.
Alessio Naccarati, a molecular epidemiologist at the Italian Institute for Genomic Medicine (IIGM) not involved in the study, remarked on the significance of this research, noting its potential implications for diagnostic analysis.
Previously, various methods were employed to isolate and sequence miRNAs. Layton's team sought to standardize the process by testing and refining different protocol components. They determined optimal storage temperatures for fecal pellets to yield high-quality RNA and identified suitable PCR settings for constructing cDNA libraries for RNA sequencing. Compared to three commonly used methods, their approach produced the highest number of miRNA reads and detected a greater diversity of miRNA species. Layton expressed her surprise and satisfaction at these improved results.
With the optimized protocol in hand, the team assessed its efficacy in profiling miRNAs during intestinal infections. They infected mice with the intestinal parasite Trichuris muris and analyzed their fecal miRNA profiles. Infected mice exhibited increased levels of three miRNAs, including miR-200c, and decreased levels of four, including miR-29a. Predicted targets of these miRNAs suggest they may influence fibrosis, a condition characterized by excessive collagen production leading to tissue scarring. This finding opens the possibility of using miRNAs as biomarkers for fibrosis, which is also observed in conditions like inflammatory bowel disease.
To explore the role of these miRNAs in fibrosis, researchers treated cultured fibroblasts with molecules that mimic or inhibit the specific miRNAs. Fibroblasts exposed to a miR-29a inhibitor produced more collagen, indicating that reduced miR-29a levels post-infection promote collagen deposition and fibrosis. Conversely, introducing a miR-200c mimic increased collagen production, aligning with observations of elevated miR-200c levels following infection.
Further validation came from in vivo studies of intestinal tissues from both control and T. muris-infected mice. The infected mice displayed extensive fibrosis and higher levels of fibrosis-associated miRNAs, corroborating the hypothesis that these small RNAs are involved in infection-induced fibrosis. Layton highlighted this as a significant confirmation of the technique's potential to identify disease biomarkers. Naccarati emphasized the novelty of linking infection-associated changes to miRNAs, suggesting that additional studies under varying conditions could enhance understanding of the protocol's effectiveness in identifying disease biomarkers.
Barbara Pardini, another molecular epidemiologist at IIGM not involved in the study, acknowledged the comprehensive description of the framework but noted potential cost concerns. Layton acknowledged that future efforts could focus on making the pipeline more high-throughput and cost-efficient, expressing hope that their work would inform further optimizations.
Source:https://www.the-scientist.com/profiling-microrna-from-poo-to-understand-gut-health-and-disease-73025
This is non-financial/medical advice and made using AI so could be wrong.