FMT to Eradicate Intestinal Colonization by Carbapenem-resistant Enterobacteriaceae

Overview

Antibiotic resistance (AR) is a critical public health threat and one of the greatest challenges of the 21st century. In an estimate of 2019, nearly 700.000 infections and 33.000 attributable deaths from multi-drug-resistant bacteria (MDRB) have occurred in Europe in 2015. The gastrointestinal tract is a large reservoir for MDRB, and the gut microbiota can harbor a collection of AR genes, called gut resistome. Preliminary nonrandomized evidence suggests that fecal microbiota transplant (FMT) could be a promising treatment option to eradicate MDRB, but established evidence, as well as mechanisms that underpin this therapeutic pathway, are still unavailable. Leveraging our expertise in FMT (OU1), microbiome (OU2) and MDRB (OU3), we aim to evaluate the efficacy of FMT (from donors with limited presence of AR genes) in eradicating intestinal MDRB through a randomized controlled trial and identifying microbial features that are associated with clinical efficacy and clearance of AR genes

Antibiotic resistance (AR) is a critical public health threat and one of the greatest challenges of the 21st century. In an estimate of 2019, nearly 700.000 infections and 33.000 attributable deaths from multi-drug-resistant bacteria (MDRB) have occurred in Europe in 2015. Despite specific interventions, including antibiotic stewardship measures and AR surveillance programs, this burden has nearly doubled since 2007 and is highest for infections caused by intestinal bacteria. The gastrointestinal tract is a large reservoir for MDRB, and the gut microbiota can harbor a collection of AR genes, called gut resistome. There is increasing evidence that healthy gut microbiota can prevent the colonization of MDRB through mechanisms of colonization resistance, including competition, production of antimicrobial peptides, immune regulation. However, this protective mechanism can be impaired by therapies that alter gut microbiota (e.g. antibiotics). The restoration of healthy gut microbiota by fecal microbiota transplantation (FMT) may lead to the eradication of antibiotic-resistant bacteria. After becoming a standard treatment for Clostridioides difficile infection, FMT has been investigated in several disorders, and preliminary nonrandomized reports suggest that it could be a promising treatment option to eradicate MDRB, but established evidence, as well as mechanisms that underpin this therapeutic pathway, are still unavailable. We hypothesize that 1) FMT from donors with limited presence of AR genes can be more effective than placebo in eradicating intestinal MDRB (focusing on carbapenem-resistant Enterobacteriaceae) and 2) microbial features of donors and patients can be reproducibly associated with clinical efficacy and clearance of AR genes. Our results will pave the way for the development of effective, targeted microbiome-based therapies against MDRB, alleviating the burden of AR, with considerable benefits for healthcare systems. The extended aims of this study are: * To identify FMT donors with limited presence of AR genes and store feces for FMT * To assess the efficacy of FMT in eradicating intestinal MDRB (carbapenem-resistant Enterobacteriaceae) and collect stool samples for multi-omics analysis * To characterize the fecal microbiome (bacteriome, virome, mycobiome), resistome, of donors and patients before and after FMT, to associate microbial profiles with clearance of AR genes and clinical efficacy, and identify the microbial features that influence it The investigators will carry out a single-centre placebo-controlled, double blind randomised clinical trial of donor FMT vs placebo FMT in carriers of CRE Patients will be recruited among those referred to the infectious disease outpatient clinic of the Fondazione Policlinico Universitario "A. Gemelli". Patients with all inclusion criteria and none of the exclusion criteria (detailed in the specific section of this website) will be considered for this study. Before randomisation, demographic data will be collected by the infectious disease staff. Moreover, patients will repeat rectal swab and stool culture. Additionally, patients will be requested to give stool samples to be collected in a sterile, sealed container and stored at -80°C for metagenomic assessment of gut microbiome and meta-transcriptome assessment by the microbiology staff. After baseline assessments, patients will be randomly assigned to one of the following treatment arms: * Donor FMT (D-FMT) * Placebo FMT (P-FMT) Patients in both groups will undergo a single FMT procedure by colonoscopy. Each patient in the donor FMT group will receive faeces from one single donor. Placebo FMT will be made of 250 mL water. Donors will be recruited among healthy individuals, following international guidelines and according the new recommendation imposed by the reorganisation of faecal microbiota transplant during the COVID-19 pandemic. Only donors with a history of limited antibiotic usage (\<5 antibiotic courses shorter than 10 days) will be chosen for resistome analysis, and only the three donors with the lowest rate of AR genes will be finally enrolled. Each donor will be asked to donate frequently (\>7 aliquots/donor) and in a limited timeframe (3 months) to minimize the risk of changes in intestinal AR genes. Selected donors will be excluded if they will undergo antibiotic therapies within the donating period. Thirty-six patients with intestinal colonization by CRE will be enrolled, based on sample size calculation. Informed consent will be collected from all patients. At baseline, stool samples will be collected for multi-omics analysis. Patients will be then randomized to colonoscopic FMT or placebo and will be followed up at week 1, 4 and 12 after treatments. At each visit they will undergo a clinical visit and a rectal swab for CRE, and stool samples will be collected and stored for multi-omics analysis. Study Outcomes are detailed in the specific section of this website. Statistical analysis will be performed both on an intention-to-treat and per-protocol basis. Differences among groups will be assessed with a two-tailed Wilcoxon-rank sum test for continuous data and with Fisher¿s exact probability test (using two- tailed P-values) for categorical data. For microbiome analysis, statistical differences between group means will be calculated using a two-tailed Wilcoxon-Rank Sum Test, through the R statistical software package (R Core Team, Vienna, Austria). Machine learning models will be used to identify and reproducibly characterize responder and nonresponder profiles. In particular, in a Python 3.9 environment using scikit-learn (ver. 0.22.1), two unsupervised ML algorithm, namely K-means and Agglomerative Hierarchical Clustering, will be used for creating patient clusters based on baseline microbiome features, in order to assess whether ML may identify distinct microbiome profiles associated with clinical response and changes in AR levels.