Mehdi Bouhaddou, Ph.D.

Assistant Professor

Office Phone TBD

Assistant Professor, Microbiology, Immunology, and Molecular Genetics (MIMG)

Member, Quantitative and Computational Biosciences Institute (QCBio)

Research Interests

We are a Quantitative Systems Biology lab that seeks to understand the biological principles that govern the interplay between viruses and host signaling—from systems-level features to basic mechanisms. We systematically compare how different viruses manipulate, or are manipulated by, host phosphorylation signaling, using a combination of mass spectrometry [phospho]proteomics, experimental virology, and computational modeling.

In addition to developing governing principles and discovering novel mechanisms of viral pathogenesis, we seek to identify and test multi-virus therapeutics. Conversely, we also use viruses to learn about ourselves, using them as tools to probe our own signaling circuitry, with applications to other disease areas such as cancer.

The lab is half “wet” and half “dry”, cultivating an interactive exchange between experimental and computational workflows. Experimentally, we focus on global mass spectrometry proteomics, affinity purification mass spectrometry (APMS), cell culture-based virology, genetic perturbation screens, pharmacology, and molecular biology. Computationally, we specialize in bioinformatics, network modeling, and ordinary differential equation (ODE) modeling. 


Dr. Mehdi Bouhaddou performed his postdoctoral training with Dr. Nevan J. Krogan at UC San Francisco (UCSF) in virology, mass spectrometry proteomics, bioinformatics, and network modeling as a member of the Quantitative Biosciences Institute (QBI) Coronavirus Research Group (QCRG). During his postdoc, Dr. Bouhaddou received F32 (NCI) and K99 (NIAID) awards to study phosphorylation signaling and protein-protein interactions in the context of infectious disease and cancer, co-mentored by Danielle L. Swaney. He developed virus-host interaction networks for SARS-CoV-2 and other coronaviruses, and systematically compared the molecular response to emerging SARS-CoV-2 variants to pinpoint variant-specific mechanisms of pathogenesis. Prior to his postdoc, Dr Bouhaddou worked at Roche with Drs. Li Yu and Antje-Christine Walz to develop pharmacokinetics and pharmacodynamics (PK/PD) mathematical models of epigenetic modifier drugs in cancer. He received his PhD in Biomedical Sciences advised by Dr. Marc Birtwistle at the Icahn School of Medicine at Mount Sinai in New York City, where he developed ordinary differential equation (ODE) models of cancer signaling to predict personalized therapeutic strategies tailored to specific cancer mutational contexts. Lastly, Dr. Bouhaddou received his Bachelor’s degree from UC Berkeley in Cognitive Neuroscience.

The Bouhaddou lab will officially open in the QCBio space in February 2023!



Google Scholar

Selected publications 

Mehdi Bouhaddou, Danish Memon, Bjoern Meyer, Kris M. White, Veronica V. Rezelj, Miguel Correa Marrero, Benjamin J. Polacco, et al. 2020. “The Global Phosphorylation Landscape of SARS-CoV-2 Infection.” Cell

Lucy G. Thorne, Mehdi Bouhaddou, Ann-Kathrin Reuschl, Lorena Zuliani-Alvarez, Ben Polacco, Adrian Pelin, Jyoti Batra, et al. 2022. “Evolution of Enhanced Innate Immune Evasion by SARS-CoV-2.” Nature

David E. Gordon, Joseph Hiatt, Mehdi Bouhaddou, Veronica V. Rezelj, Svenja Ulferts, Hannes Braberg, Alexander S. Jureka, et al. 2020. “Comparative Host-Coronavirus Protein Interaction Networks Reveal Pan-Viral Disease Mechanisms.” Science

David E. Gordon, Gwendolyn M. Jang, Mehdi Bouhaddou, Jiewei Xu, Kirsten Obernier, Kris M. White, Matthew J. O’Meara, et al. 2020. “A SARS-CoV-2 Protein Interaction Map Reveals Targets for Drug Repurposing.” Nature

Ruofan Wang, Camille R. Simoneau, Jessie Kulsuptrakul, Mehdi Bouhaddou, Katherine A. Travisano, Jennifer M. Hayashi, Jared Carlson-Stevermer, et al. 2021. “Genetic Screens Identify Host Factors for SARS-CoV-2 and Common Cold Coronaviruses.” Cell

Mehdi Bouhaddou, Anne Marie Barrette, Alan D. Stern, Rick J. Koch, Matthew S. DiStefano, Eric A. Riesel, Luis C. Santos, Annie L. Tan, Alex E. Mertz, and Marc R. Birtwistle. 2018. “A Mechanistic Pan-Cancer Pathway Model Informed by Multi-Omics Data Interprets Stochastic Cell Fate Responses to Drugs and Mitogens.” PLoS Computational Biology

Minkyu Kim, Jisoo Park, Mehdi Bouhaddou, Kyumin Kim, Ajda Rojc, Maya Modak, Margaret Soucheray, et al. 2021. “A Protein Interaction Landscape of Breast Cancer.” Science

Mehdi Bouhaddou, Rex H. Lee, Hua Li, Neil E. Bhola, Rachel A. O’Keefe, Mohammad Naser, Tian Ran Zhu, et al. 2021. “Caveolin-1 and Sox-2 Are Predictive Biomarkers of Cetuximab Response in Head and Neck Cancer.” JCI Insight