Physician-scientist · Weill Cornell Medicine
Dr. Jez Lim Marston
MD, PhD
Tracking viruses, immune responses, and the viral DNA we already carry.
I work where molecular virology, host-pathogen immunology, gene expression, and AI meet, and increasingly where that intersection becomes a biosecurity question. Postdoctoral researcher in the Cesarman Lab, studying viral influence on immune cell function and dysregulation.
Research.
Viruses and immune cell function
In the Cesarman Lab, I study how viruses shape immune cell function and drive its dysregulation. I resolve EBV lytic and latent programs, and HIV-1 transcription, alongside host gene expression at single-cell resolution across EBV+ lymphoma, including EBV/HIV co-infected patients. My interests also include studying human endogenous retroviruses (HERV), the fossil remains of ancient infections, and how their expression in human cells affects human immune surveillance and tolerance. Our work has shown that SARS-CoV-2 induces expression of specific HERV loci even in comparison to related viruses (SARS-CoV and MERS-CoV) and that locus-level HERV expression can tell lymphoma subtypes apart.
Research →
Computational biology
In the Nixon Lab, I co-developed Stellarscope, a bioinformatic tool to quantify locus-specific expression of transposable element sequences, and published the first single-cell atlas of TE and HERV expression across the human immune system. I now lead development of scTEQuant, a next-generation Bayesian pipeline for locus-specific viral and transposable-element quantification from single-cell and bulk RNA-seq. The scTEQuant manuscript is in preparation and its code is private until publication.
Tools →
AI and biosecurity
I use AI tools in my own research every day, so I think about how they lower the technical barrier to dual-use biology and why evaluation and guardrails matter. I am drawn to explore how these tools can be utilized for the advancement of scientific knowledge and public health goals, without harm. As an independent project, I mapped how six HIV antibodies get through the virus's sugar shield. I chose this focus for my project due to my commitment to HIV research and the comparatively low risk as an agent of concern, as a precaution in running an independent exploration.
Cracking the Glycan Shield →
Additional interests
I also follow autoimmunity, immuno-oncology, and skin immunology, which meet my work on viral latency and endogenous retroviruses.
Full research page →
Selected works.
- A single-cell transposable element atlas of human cell identity Reyes-Gopar H*, Marston JL*, et al. Cell Reports Methods, 2025. *Co-first authors Single-cellTransposable elementsStellarscope
- Locus-specific human endogenous retroviruses reveal lymphoma subtypes Singh B, Dopkins N, Fei T, Marston JL, et al. iScience, 2025. HERVsLymphoma
- Ribosomal profiling of human endogenous retroviruses in healthy tissues Dopkins N, Singh B, Marston JL, et al. BMC Genomics, 2024. HERVsTranslation
- How human endogenous retroviruses interact with the microbiota in health and disease Dopkins N, O'Mara MM, Singh B, Marston JL, Bendall ML, Nixon DF. Trends in Microbiology, 2022. HERVsMicrobiome
- SARS-CoV-2 infection mediates differential expression of human endogenous retroviruses Marston JL, Greenig M, et al. JCI Insight, 2021. SARS-CoV-2HERVs
About.
I am a physician-scientist who applies computational biology expertise to study virology and immunology. My research asks how viruses, and the virus-derived elements in our genomes, influence immune cell function and drive its dysregulation, using gene expression at single-cell resolution, from endogenous retroviruses in the immune system to EBV and HIV in lymphoma.
I work hands-on under BSL-2+ conditions with HIV-1, EBV, and SARS-CoV-2. That, together with daily use of AI tools, has given me a practical sense of how AI lowers the barrier to dual-use work. I believe AI can meaningfully advance biomedicine, and that doing so safely depends on people who understand both the biology and the tools.
I am interested in roles evaluating and mitigating biological risk in frontier AI systems, and more broadly in computational virology, immunology, and translational biotechnology.