Publication: Project 4: Gut Microbiome and Kidney Transplant
Date
2023-08
Authors
Cho, Minseo
Herdrich, Kyle
Jung, Isaac
Liu, Jiahui
Journal Title
Journal ISSN
Volume Title
Publisher
George Mason University
Abstract
Background: The gut microbiota, comprising the entire population of microorganisms that colonize the colon, has evolved over time to establish a symbiotic relationship with the human body, yielding mutual benefits [1]. This microbiome plays a pivotal role in critical bodily functions, including biosynthesis, short-chain fatty acid (SCFA) production, gut regulation, and immune system function. Under normal circumstances, these gut bacteria are referred to as indigenous microbiota, performing their customary functions; however, in the presence of disturbances, detrimental or opportunistic bacteria emerge, known as pathobionts [2]. Imbalances within the gut microbiota have been associated with various diseases, including obesity, metabolic disorders, inflammatory bowel diseases, colorectal cancer, allergies, and autoimmune disorders [1]. Of particular concern is the impact of immunosuppressants and antibiotics administered after kidney transplant surgeries, as they disrupt the patients' gut microbiome, alter indigenous microbiota, and promote the proliferation of pathobionts, resulting in a condition known as dysbiosis. Dysbiosis, in turn, may facilitate the development of acute kidney injury (AKI) by modifying SCFA composition and generating elevated levels of toxins. Both AKI and pathobionts can contribute to the progression of atherosclerosis, cardiovascular diseases, inflammation, and chronic kidney disease (CKD). If left untreated, CKD can escalate to infections and even rejection of the newly transplanted kidney by the recipient's immune system [2].
Objective: This project aims to 1) examine the degree of change occurred in the abundance and diversity of the gut microbiome, before and after kidney transplantation, and 2) identify treatments that support the microbiome in returning to its healthy, stable state.