Decoding Biological Mechanisms Through Cohort Multi-Omics
Our work aims to understand clinical manifestation and biological mechanism of interesting human processes discovered through cohort study
About Us
Xin Zhou, Ph.D. is a research scientist at Stanford University School of Medicine. He completed his Ph.D. training with Dr. George Weinstock in 2019 and his postdoctoral training with Dr. Michael Snyder in 2024. Xin brings extensive experience in multiple biological disciplines, focusing on the intricate relationships between the microbiome and human health.
Our Research
Our research focuses on human cohorts that have a variety of chronic disorders such as lymphedema, Type 2 Diabetes (T2D), and Pulmonary Arterial Hypertension (PAH). We perform longitudinal follow-ups of these cohorts to characterize the molecular blueprint of the host and microbiome using multi-omics technology. We also validate findings from these studies using different methods, including animal models and human organoids.
Our team is also dedicated to collecting interesting microbes from the human microbiome for their therapeutic value. In addition, we develop novel single-cell metagenomics tools and statistical methods to better understand big data and omics technologies.
Our Mission
Our mission is to revolutionize biomedical research through big data-driven precision medicine. By conducting rigorous mechanistic studies, we strive to uncover the underlying causes of diseases and pave the way for advanced personalized treatments. Through our interdisciplinary collaboration and scientific inquiry, we aim to transform patient care and public health. We invite you to explore our pioneering research and join us in our mission to harness the power of the microbiome for groundbreaking advancements in medical science.
Research Interests
Longitudinal Host Microbiome Interaction in Multiple Sites
“We found that when you get sick with something like a cold, you have this temporary change in the microbiome; it becomes very dysregulated. With diabetes, that signature is the same in many ways except that it is long-term rather than temporary.”
Precision Microbial Intervention
We develop innovative solutions for metabolic and inflammatory diseases through precision microbial interventions. We leverage two key advancements: an advanced machine learning methodology and the creation of a pioneering immune organoid. As part of the integrated Human Microbiome Project (iHMP), we’ve developed a specialized machine learning algorithm tailored to our unique multi-omics dataset, focusing on individuals with prediabetes and type 2 diabetes. This algorithm integrates various powerful techniques, such as Bayesian inference, Recursive Partitioning and Regression trees, and longitudinal causal inference. This approach has driven significant scientific and clinical progress over the past decade. In parallel, we’ve created a unique immune organoid using tonsil tissues to model immune-bacterial interactions. This organoid replicates essential immune functions, providing a valuable tool for studying specific immune responses to bacterial strains.
Single Cell Transcriptomics
Our team leverages advanced single-cell transcriptomics to decode the molecular intricacies of various chronic and inflammatory diseases. By examining individual cells with unparalleled precision, we uncover critical insights that drive our research forward. We focus on inflammatory conditions such as Pulmonary Arterial Hypertension (PAH) and Post-Treatment Lyme Disease (PTLD). Our transcriptomics studies reveal unique genetic and cellular profiles, shedding light on the underlying mechanisms of these diseases.
