Daniel Leung

Mucosal Associated Invariant T (MAIT) cells in Mucosal Infections

MAIT cells are recently identified innate-like lymphocytes. They are primarily found in mucosal tissues and represent up to 10% of circulating T cells in humans. They are restricted by MR1, the non-classical MHC class I related protein, and MAIT ligands belong to a class of transitory intermediates of the riboflavin synthesis pathway. MAITs are capable of releasing both pro- and anti- inflammatory cytokines in response to stimulation, and possess cytotoxic activity

Cholera

We have recently reported that MAIT cells are activated in cholera and are associated with higher class-switched V. cholerae polysaccharide-specific antibody responses. we have reported on the capacity of MAIT cells to participate in B cell help, and identified a novel subset of MAIT cells that are enriched in human tonsil germinal centers possessing markers of follicular helper T cells. In a mouse model, we have examined the potential for use of a MAIT-activating ligand as a mucosal adjuvant in cholera vaccination. Working in collaboration with the International Centre for Diarrhoeal Disease Research, Bangladesh (icddr,b), we are examining the role that MAIT cells play in the adaptive response against V. cholerae infection and vaccination. We are characterizing the clonal expansions of MAIT cells during human V. cholerae infection and oral cholera vaccination. At the same time, we are examining the mechanisms through which MAIT cells affect B cell differentiation and antibody production. Through these studies, we hope to gain new information on the capacity of MAIT cells to impact polysaccharide-specific antibody responses, which are associated with protection against cholera. This information has the potential to critically inform the development of better vaccine strategies targeted at preventing cholera and other enteric infections in young children.

Sepsis

Recent studies have found that septic patients have an early decrease in circulating MAITs, associated with an increased risk of secondary infections. Working in collaboration with the Rondina, Campbell, and Hale labs, we have found that MAITs from septic patients are highly dysfunctional, and that animals deficient in MAITs have a much higher mortality from experimental sepsis. Our goal is to determine how MAIT cells contribute to protective host responses by regulating inflammatory mediators. We are using a number of immunologic, genomic, and epigenetic techniques to examine the role of MAIT cells in both human and experimental models of sepsis.

Linking Respiratory and Intestinal Microbiota and Immune Dysregulation

The human intestinal and respiratory tracts share a common mucosal immune system. Infections of the intestine and respiratory tracts are the two most common infections occurring in children in low-resource settings. Very little is known of how disturbances in the intestinal microbiota may affect the immunity and health of the respiratory tract. Using animal models and clinical studies, we are examining how lung immune responses changes during an intestinal infection, and if susceptibility to pneumonia challenge is affected. Our goal is to determine whether (and how) intestinal infections affect the lung, and whether intervening on intestinal infections could help prevent respiratory health problems.

Estimating Cholera Burden with Cross-sectional Immunologic Data

Identifying key populations at high risk of cholera is essential to guide global efforts to fight cholera, including targeting use of the oral cholera vaccine. Current methods to estimate cholera burden are largely based on clinical reporting with infrequent microbiological confirmation. These methods are limited by the sporadic nature of outbreaks, poor surveillance infrastructure, and fundamental uncertainties in the number of asymptomatic or mildly symptomatic cases. Detection of immune responses in serum (serosurveillance) can provide a new avenue for rapid and accurate estimates of cholera exposure and risk. We currently do not understand what immunological and clinical parameters are most predictive of recent exposure, nor whether immune responses in areas with different levels of endemicity are similar. We are pioneering the use of longitudinal antibody response kinetics, paired with novel statistical and machine learning approaches, to provide generalizable tools to estimate the incidence of exposure to Vibrio cholerae from cross sectional serosurveys. In collaboration with scientists at the icddr,b in Bangladesh, GHESKIO in Haiti, Johns Hopkins, and University of Florida, we are developing models to estimate the time since exposure to Vibrio cholerae and exposure incidence from cross-sectional antibody profiles and demographic data from cohorts of patients in Bangladesh and Haiti. We are also working to optimize and validate field-adapted methods to measure cholera-specific antibodies, including the use of dried blood spotand lateral flow assays. Our goal is to develop new tools to measure susceptibility to cholera in a population. These tools will have the potential to transform cholera control efforts from the current reactive strategies to proactive ones, with the potential to contribute to disease elimination.

Development of Clinical Decision Tools for Management of Diarrhea of Children in High and Low Resource Settings

Diarrheal diseases are the among the leading cause of death in children worldwide, most of which occur in low-income countries. In high-income countries, pediatric diarrhea remains a major utilization of healthcare resources. Treatment of diarrhea is mostly empiric, with antibiotic use mostly based on clinical suspicion for bacterial causes. However, the majority of cases of diarrhea do not benefit from antibiotic use, and inappropriate use leads to toxicity and resistance. Furthermore, despite the increasing availability of rapid molecular testing, there is little data to base a decision of whom or when to test. Our goal is to develop and validate clinical decision tools for management of diarrheal illnesses in children of both high and low resource settings. We have used data from clinical studies of pediatric diarrhea in both the US and in low- and middle-income countries (LMICs) to derive and validate clinical prediction rules for etiology of diarrheal illness and for poor outcomes following diarrheal illness. We have developed a framework using a Bayesian approach to integrate pre-test probability and other patient-extrinsic factors into clinical prediction of etiology. We have translated these rules into electronic clinical decision support tools (eCDST) for clinicians in LMICs, performed external validation of this approach, and implemented a randomized clinical trial of an App operationalizing this tool in clinicians in Bangladesh and Mali. We have also developed prediction tools to assess risk of etiology for traveler’s diarrhea and antimicrobial resistance gene colonization in international Ultimately, we hope to make available clinical tools that healthcare workers worldwide can use for evidence-based care of children with diarrhea.

Our Research is Funded by the Following:

NIH (R01AI130378, R01AI135114, R01AI135115, R21HD109819, K24AI166087)

Bill & Melinda Gates Foundation (OPP1198876)