Michael Chang
· MDVerifiedUniversity of California, San Diego · Gastroenterology
Active 2002–2025
About
Michael Chang is an Associate Clinical Professor of Medicine at UC San Diego. His research focuses on esophageal anatomy and physiology, particularly across different phenotypes of disorders of esophagogastric junction outflow. His work includes studying diagnostic methods to measure spastic segments and guide tailored myotomy length in type 3 achalasia, as well as comparing various endoscopic techniques for gastrointestinal procedures. Chang has contributed to the understanding and management of gastrointestinal conditions through his publications and clinical expertise. His research also encompasses endoscopic management of gastrointestinal bleeding, treatment of biliary and esophageal conditions, and the development of innovative endoscopic techniques.
Research topics
- Biology
- Virology
- Bioinformatics
- Artificial Intelligence
- Computer Science
- Evolutionary biology
- Internal medicine
- Cartography
- Medicine
- Computational biology
- Pharmacology
- Biochemistry
- Programming language
- Human–computer interaction
- Endocrinology
Selected publications
bioRxiv (Cold Spring Harbor Laboratory) · 2025-10-03
preprintOpen accessSUMMARY Persistence of senescent alveolar transitional progenitors following lung injury is implicated in the pathogenesis of fibrosis. We identified transitional cells in uninjured Cldn18 knockout (KO) mouse lungs distinct from previously reported damage-associated transitional progenitors (DATPs) with a less fibrogenic transcriptomic profile. Cldn18 KO mice are protected from bleomycin-induced fibrosis, with early restoration of cellular homeostasis. Lineage tracing implicates accelerated differentiation as a mechanism for protection from fibrosis, leading us to name these cells regeneration-associated transitional progenitors (RATPs). Multiome confirms that RATPs and DATPs are epigenetically distinct, with RATPs comprised of RATP2s and RATP1s based on epigenomic proximity to AT2s and AT1s, respectively, and suggests dynamic regulatory remodeling during AT2-to-AT1 differentiation, with NKX2.1 and AP-1 active in early transitions and TEAD factors in later stages. These results reveal an unexpected role for Cldn18 in regulation of AEC plasticity, while identification of RATPs challenges the notion that persistence of transitional alveolar cells is invariably pathologic.
Integrative multi-omics analysis in vivo identifies influenza virus host factors
iScience · 2025-09-24 · 2 citations
articleOpen accessInfluenza A virus (IAV) infection remodels cellular processes to support viral replication. The modulation of host factors by the virus drives pathogenesis during infection, and these factors may serve as therapeutic targets. Here, we infect mice with two IAV strains, H1N1 and H5N1, and analyze lung tissue with multi-omics. Using network propagation analysis, we identify twenty-four distinct host modules altered by infection, encompassing 2920 genes/proteins. Independently, we develop a computational pipeline, MidTOD, which integrates metabolomic data with other OMICs data-types, linking metabolites to gene/protein alterations. Combining datasets from both approaches reveals alterations in mitochondrial and peroxisomal metabolism in IAV-infected cells and identifies arginine:glycine amidinotransferase (GATM) as a host dependency factor in both human cells and mice. Knockdown of this enzyme reduces IAV-mediated pathology and host inflammatory responses after infection. Collectively, this work provides an integrated systems-level view of host changes during infection and identifies an abundance of IAV-host factors.
Journal of Investigative Dermatology · 2024-07-19
articleOpen accessClaudin-18 Regulates Alveolar Epithelial Cell Plasticity and Regeneration
2024-04-30
articleJournal of Biological Chemistry · 2024-05-04 · 4 citations
articleOpen accessTriclosan (TCS) is an antimicrobial toxicant found in a myriad of consumer products and has been detected in human tissues, including breastmilk. We have evaluated the impact of lactational TCS on UDP-glucuronosyltransferase 1A1 (UGT1A1) expression and bilirubin metabolism in humanized <i>UGT1</i> (<i>hUGT1</i>) neonatal mice. In <i>hUGT1</i> mice, expression of the hepatic UGT1A1 gene is developmentally delayed resulting in elevated total serum bilirubin (TSB) levels. We found that newborn <i>hUGT1</i> mice breastfed or orally treated with TCS presented lower TSB levels along with induction of hepatic UGT1A1. Lactational and oral treatment by gavage with TCS leads to the activation of hepatic nuclear receptors constitutive androstane receptor (CAR), peroxisome proliferator-activated receptor alpha (PPARα), and stress sensor, activating transcription factor 4 (ATF4). When CAR-deficient <i>hUGT1</i> mice (<i>hUGT1/Car</i><sup>−/−</sup>) were treated with TCS, TSB levels were reduced with a robust induction of hepatic UGT1A1, leaving us to conclude that CAR is not tied to UGT1A1 induction. Alternatively, when PPARα-deficient <i>hUGT1</i> mice (<i>hUGT1/Ppar</i>α<sup>−/−</sup>) were treated with TCS, hepatic UGT1A1 was not induced. Additionally, we had previously demonstrated that TCS is a potent inducer of ATF4, a transcriptional factor linked to the integrated stress response. When ATF4 was deleted in liver of <i>hUGT1</i> mice (<i>hUGT1/Atf4</i><sup>ΔHep</sup>) and these mice treated with TCS, we observed superinduction of hepatic UGT1A1. Oxidative stress genes in livers of <i>hUGT1/Atf4</i><sup>ΔHep</sup> treated with TCS were increased, suggesting that ATF4 protects liver from excessive oxidative stress. The increase oxidative stress may be associated with superinduction of UGT1A1. The expression of ATF4 in neonatal <i>hUGT1</i> hepatic tissue may play a role in the developmental repression of UGT1A1.
Gastroenterology · 2024-05-01
articlePLoS Pathogens · 2024-01-10 · 8 citations
articleOpen accessCorrespondingHybrid immunity (vaccination + natural infection) to SARS-CoV-2 provides superior protection to re-infection. We performed immune profiling studies during breakthrough infections in mRNA-vaccinated hamsters to evaluate hybrid immunity induction. The mRNA vaccine, BNT162b2, was dosed to induce binding antibody titers against ancestral spike, but inefficient serum virus neutralization of ancestral SARS-CoV-2 or variants of concern (VoCs). Vaccination reduced morbidity and controlled lung virus titers for ancestral virus and Alpha but allowed breakthrough infections in Beta, Delta and Mu-challenged hamsters. Vaccination primed for T cell responses that were boosted by infection. Infection back-boosted neutralizing antibody responses against ancestral virus and VoCs. Hybrid immunity resulted in more cross-reactive sera, reflected by smaller antigenic cartography distances. Transcriptomics post-infection reflects both vaccination status and disease course and suggests a role for interstitial macrophages in vaccine-mediated protection. Therefore, protection by vaccination, even in the absence of high titers of neutralizing antibodies in the serum, correlates with recall of broadly reactive B- and T-cell responses.
Drug target prediction through deep learning functional representation of gene signatures
Nature Communications · 2024-02-29 · 75 citations
articleOpen accessMany machine learning applications in bioinformatics currently rely on matching gene identities when analyzing input gene signatures and fail to take advantage of preexisting knowledge about gene functions. To further enable comparative analysis of OMICS datasets, including target deconvolution and mechanism of action studies, we develop an approach that represents gene signatures projected onto their biological functions, instead of their identities, similar to how the word2vec technique works in natural language processing. We develop the Functional Representation of Gene Signatures (FRoGS) approach by training a deep learning model and demonstrate that its application to the Broad Institute's L1000 datasets results in more effective compound-target predictions than models based on gene identities alone. By integrating additional pharmacological activity data sources, FRoGS significantly increases the number of high-quality compound-target predictions relative to existing approaches, many of which are supported by in silico and/or experimental evidence. These results underscore the general utility of FRoGS in machine learning-based bioinformatics applications. Prediction networks pre-equipped with the knowledge of gene functions may help uncover new relationships among gene signatures acquired by large-scale OMICs studies on compounds, cell types, disease models, and patient cohorts.
Position-dependent function of human sequence-specific transcription factors
Nature · 2024-07-17 · 74 citations
articleOpen accessAbstract Patterns of transcriptional activity are encoded in our genome through regulatory elements such as promoters or enhancers that, paradoxically, contain similar assortments of sequence-specific transcription factor (TF) binding sites 1–3 . Knowledge of how these sequence motifs encode multiple, often overlapping, gene expression programs is central to understanding gene regulation and how mutations in non-coding DNA manifest in disease 4,5 . Here, by studying gene regulation from the perspective of individual transcription start sites (TSSs), using natural genetic variation, perturbation of endogenous TF protein levels and massively parallel analysis of natural and synthetic regulatory elements, we show that the effect of TF binding on transcription initiation is position dependent. Analysing TF-binding-site occurrences relative to the TSS, we identified several motifs with highly preferential positioning. We show that these patterns are a combination of a TF’s distinct functional profiles—many TFs, including canonical activators such as NRF1, NFY and Sp1, activate or repress transcription initiation depending on their precise position relative to the TSS. As such, TFs and their spacing collectively guide the site and frequency of transcription initiation. More broadly, these findings reveal how similar assortments of TF binding sites can generate distinct gene regulatory outcomes depending on their spatial configuration and how DNA sequence polymorphisms may contribute to transcription variation and disease and underscore a critical role for TSS data in decoding the regulatory information of our genome.
Edward Elgar Publishing eBooks · 2024-02-13
paratextOpen accessExploring the link between Sustainable Development Goals (SDGs) and the built environment, this erudite Companion provides a comprehensive overview and critical examination of key topics and complex research issues. Structured around the 5Ps of the SDGs - people, planet, prosperity, peace, and partnerships - the Companion suggests potential routes for the future direction of research within this multidisciplinary field of study.
Frequent coauthors
- 38 shared
Christopher Benner
University of California, San Diego
- 29 shared
Lars Pache
Discovery Institute
- 25 shared
Adolfo Garcı́a-Sastre
Icahn School of Medicine at Mount Sinai
- 21 shared
Sumit K. Chanda
Scripps Research Institute
- 16 shared
Laura Martin‐Sancho
Imperial College London
- 15 shared
Courtney Nguyen
The University of Texas Health Science Center at Houston
- 13 shared
Paul D. De Jesus
Scripps Research Institute
- 12 shared
Sascha H. Duttke
Washington State University
Labs
Michael Chang | UCSD ProfilesPI
Education
- 2000
Ph.D., Molecular and Computational Biology
University of California, San Diego
- 1997
M.S., Molecular and Computational Biology
University of California, San Diego
- 1995
B.S., Biology
University of California, San Diego
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