About

Jim Collins is the Termeer Professor of Medical Engineering & Science and Professor of Biological Engineering at MIT. He is a member of the Harvard-MIT Health Sciences & Technology Faculty, a Core Founding Faculty member of the Wyss Institute for Biologically Inspired Engineering at Harvard University, and an Institute Member of the Broad Institute of MIT and Harvard. He is recognized as one of the founders of the field of synthetic biology, with his research group focusing on using synthetic biology to create next-generation diagnostics and therapeutics. His work employs engineering principles to model, design, and build synthetic gene circuits and programmable cells, aiming to develop novel classes of diagnostics and therapeutics. Professor Collins' patented technologies have been licensed by over 25 biotech, pharma, and medical device companies, and he has co-founded several companies including Synlogic, Senti Biosciences, Sherlock Biosciences, and Cellarity, as well as Phare Bio, a non-profit dedicated to AI-driven antibiotic discovery. His research group also works in synthetic biology and systems biology, with a particular focus on network biology approaches to study antibiotic action, bacterial defense mechanisms, and the emergence of resistance. Collins has received numerous awards, including a MacArthur “Genius” Award and the Dickson Prize in Medicine, and he is an elected member of the National Academy of Sciences, the National Academy of Engineering, and the National Academy of Medicine.

Research topics

• Biology
• Computational biology
• Biochemistry
• Medicine
• Cell biology
• Microbiology
• Virology
• Pathology
• Genetics
• Chemistry
• Molecular biology
• Immunology
• Computer Science
• Veterinary medicine
• Environmental ethics
• Bioinformatics
• Art
• Literature
• Environmental health
• Biophysics
• Philosophy

Selected publications

• Genetic code expansion enables programmable covalent protein design

  bioRxiv (Cold Spring Harbor Laboratory) · 2026-05-16

  articleOpen access

  Abstract Covalent chemistry has transformed small-molecule drug discovery, yet analogous strategies for proteins remain largely inaccessible because covalent warheads cannot be readily integrated into biologics. Conventional genetic code expansion requires engineering a dedicated aminoacyl-tRNA synthetase for each new amino acid, rendering broad warhead screening impractical. Here we introduce AminoX, a platform that bypasses this limitation through direct tRNA acylation, enabling site-specific incorporation of chemically diverse non-standard amino acids (nsAAs), including covalent warhead nsAAs compatible with scalable biologic manufacturing and multifunctional nsAAs. Using a pooled mRNA display workflow, we screened more than 2,000 warhead-position combinations in machine learning-designed de novo miniproteins targeting CTLA-4, enabling parallel interrogation of covalent chemistry, linker geometry, and incorporation site. We confirmed covalent engagement on cells together with enhanced functional blockade. Finally, we demonstrate multifunctional nsAAs that combine covalent warheads with fluorogenic reporters for real-time detection of target engagement, as well as dual nsAA incorporation for macrocyclization and fluorescent imaging of covalent binding on cell surfaces. By uniting synthetic biology, chemical biology, generative protein design, and high-throughput functional selection, AminoX compresses covalent protein engineering timelines by orders of magnitude, accelerating the development of next-generation therapeutics, biosensors, and chemical probes.

  PublisherDOI

• Essay: Using Machine Learning for Antibiotic Discovery

  Physical Review Letters · 2025-07-15 · 7 citations

  reviewSenior author

  Antimicrobial resistance is a critical global health challenge and one of the World Health Organization's top ten public health threats. The alarming rise of drug-resistant pathogens threatens to usher in a postantibiotic era where common infections could once again become fatal. Despite the urgency, traditional discovery methods are time-consuming, expensive, and insufficient to keep pace with rapidly evolving resistance. Recent advances in machine learning (ML) and artificial intelligence (AI) present a transformative alternative, enabling the rapid identification of potential candidate antibiotics in a fraction of the time required by conventional methods. In this Essay, we discuss how ML and AI significantly accelerate antibiotic discovery, drawing on previous works and insights in this emerging field. We also consider the promises and challenges of this emerging area and speculate on its evolution in the coming years, highlighting the potential contributions from the physics community. Part of a series of Essays in Physical Review Letters which concisely present author visions for the future of their field.

  PublisherDOI

• Active learning framework leveraging transcriptomics identifies modulators of disease phenotypes

  Science · 2025-10-23 · 19 citations

  article

  Phenotypic drug screening remains constrained by the vastness of chemical space and the technical challenges of scaling experimental workflows. To overcome these barriers, computational methods have been developed to prioritize compounds, but they rely on either single-task models lacking generalizability or heuristic-based genomic proxies that resist optimization. We designed an active deep learning framework that leverages omics to enable scalable, optimizable identification of compounds that induce complex phenotypes. Our generalizable algorithm outperformed state-of-the-art models on classical recall, translating to a 13- to 17-fold increase in phenotypic hit rate across two hematological discovery campaigns. Combining this algorithm with a lab-in-the-loop signature refinement step, we achieved an additional twofold increase in hit rate along with molecular insights. In sum, our framework enables efficient phenotypic hit identification campaigns, with broad potential to accelerate drug discovery.

  PublisherDOI

• Reversing transgene silencing via targeted chromatin editing

  bioRxiv (Cold Spring Harbor Laboratory) · 2025-10-30 · 1 citations

  preprintOpen access

  Mammalian cell engineering offers the opportunity to uncover biological principles and develop next-generation biotechnologies. However, epigenetic silencing of transgenes hinders the control of gene expression in mammalian cells. Here, we use chromatin editing of an integrated reporter in CHO-K1 and human induced pluripotent stem cells to study the molecular interactions driving silencing and its reversal. After transient induction of either DNA methylation or H3K9me3, stable silencing was exclusively observed with both marks. Due to the positive feedback between DNA methylation and H3K9me3 and the relative low stability of H3K9me3, our model predicts that removing DNA methylation is sufficient for transgene reactivation. Accordingly, targeted DNA demethylation reactivated the reporter irrespective of whether silencing was achieved by inducing DNA methylation, H3K9me3, or by the endogenous cellular machinery. These results shed light on molecular mechanisms at play during silencing and provide engineering tools for potent and specific transgene reactivation in mammalian cells.

  PublisherOA PDFDOI

• Loss of vitamin C biosynthesis protects from a parasitic infection

  bioRxiv (Cold Spring Harbor Laboratory) · 2025-07-26 · 2 citations

  preprintOpen access

  ABSTRACT The ability to synthesize essential molecules is sometimes lost in evolution. A classic example is ascorbate (Vitamin C), which is synthesized in most animals by L-Gulonolactone Oxidase (GULO), an enzyme lost multiple independent times in animal evolution. This event is thought to be evolutionarily neutral, however, GULO- deficient animals including humans need to obtain ascorbate from their diet and are susceptible to ascorbate deficiency and scurvy. We therefore hypothesized that this disadvantage of GULO loss is offset by physiological benefits. Here we show that ascorbate deficiency protects mice from schistosomiasis, a debilitating parasitic disease which afflicts 250 million people. Schistosoma mansoni worms required host ascorbate to produce eggs in vivo. Consequently, ascorbate-deficient mice were protected from schistosomiasis pathologies and transmission. Intermittent ascorbate deficiency protected Gulo -deficient mice from both scurvy and schistosomiasis mortality. The effects of ascorbate on schistosome reproduction were mediated by ascorbate-dependent histone demethylation which promoted vitellocyte development in female schistosomes. We propose that vitamin deficiencies are not always detrimental but can protect animals from pathogens which need to obtain vitamins from their host.

  PublisherOA PDFDOI

• Associations between internal and external training load measures and neuromuscular performance in elite soccer players

  Sport Sciences for Health · 2025-03-18 · 2 citations

  articleOpen access1st authorCorresponding

  Abstract The study investigates the relationship between internal and external training load and neuromuscular performance in elite soccer players. Twenty-eight professional players from a squad across a season participated. Players performed a countermovement jump as a measure of neuromuscular performance, with tests conducted the day before a game. Training load data were aggregated over 7-, 14-, and 28-day periods to assess their relationship with performance metrics, including reactive strength index modified (RSI-mod), time to take off, and jump height. Internal load was measured using session ratings of perceived exertion, while external load was analyzed with 10 Hz GPS units. External load measures included total distance, high-speed running, sprint distance, and accelerations and decelerations. In the 7-day window, total distance (ES = 0.03) and acceleration (ES = 0.04) showed a weak positive relationship with performance metrics. In the 14-day window, RSI-mod and time to take off significantly interacted with internal load (ES = 1.54) and high-speed running (ES = 1.44). For the 28-day window, jump height was strongly associated with sprint distance (ES = 1.86). Practitioners should use a multi-metric approach with measures of NMP and should evaluate both outcome and strategy metrics within a force–time curve, to gain a deeper understanding of their athletes.

  PublisherOA PDFDOI

• Optogenetics-enabled discovery of integrated stress response modulators

  Cell · 2025-07-15 · 13 citations

  article
  PublisherDOI

• Mitigating antimicrobial resistance by innovative solutions in AI (MARISA): a modified James Lind Alliance analysis

  npj Antimicrobials and Resistance · 2025-09-01 · 5 citations

  articleOpen access

  Antimicrobial resistance (AMR) is a critical global health threat and artificial intelligence (AI) presents new opportunities for our response. However, research priorities at the AI-AMR intersection remain undefined. This study aimed to identify and prioritise key areas for future investigation. Using a modified James Lind Alliance approach, we conducted semi-structured interviews with eight experts in AI and AMR between February and June 2024. Analysis of 338 coded responses revealed 44 distinct themes. Major barriers included fragmented data access, integration challenges and economic disincentives. The top ten priorities identified were: Combination Therapy, Novel Therapeutics, Data Acquisition, AMR Public Health Policy, Prioritisation, Economic Resource Allocation, Diagnostics, Modelling Microbial Evolution, AMR Prediction and Surveillance. A notable limitation was the underrepresentation of data from high-burden regions, limiting the generalisability of findings. To address these gaps, we propose the novel BARDI framework: Brokered Data-sharing, AI-driven Modelling, Rapid Diagnostics, Drug Discovery and Integrated Economic Prevention.

  PublisherOA PDFDOI

• Engineering synthetic phosphorylation signaling networks in human cells

  Science · 2025-01-02 · 26 citations

  article

  Protein phosphorylation signaling networks have a central role in how cells sense and respond to their environment. We engineered artificial phosphorylation networks in which reversible enzymatic phosphorylation cycles were assembled from modular protein domain parts and wired together to create synthetic phosphorylation circuits in human cells. Our design scheme enabled model-guided tuning of circuit function and the ability to make diverse network connections; synthetic phosphorylation circuits can be coupled to upstream cell surface receptors to enable fast-timescale sensing of extracellular ligands, and downstream connections can regulate gene expression. We engineered cell-based cytokine controllers that dynamically sense and suppress activated T cells. Our work introduces a generalizable approach that allows the design of signaling circuits that enable user-defined sense-and-respond function for diverse biosensing and therapeutic applications.

  PublisherDOI

• Mitigating Antimicrobial Resistance by Innovative Solutions in AI (MARISA): a modified James Lind Alliance Analysis

  Research Square · 2025-06-06

  preprintOpen access
  PublisherOA PDFDOI

Recent grants

• NIH Grant R24DK092760

  NIH · $10.7M · 2020

• NIH Grant R01HD037880

  NIH · $2.0M · 2008

• NIH Grant R21DC003484

  NIH · $85k · 1999

• Pre Clinical Discovery Core

  NIH · $39.3M · 2008–2027

• Synthetic Genetic Controller Circuits to Reprogram Cell Fate

  NIH · $1.9M · 2017–2023

Frequent coauthors

• George Q. Daley

  Harvard University

  208 shared

• Michael A. Lobritz

  Roche (Switzerland)

  129 shared

• Yuin‐Han Loh

  Institute of Molecular and Cell Biology

  125 shared

• Lewis A. Lipsitz

  Hebrew College

  121 shared

• Hu Li

  95 shared

• D. Casey Kerrigan

  OESH Shoes (United States)

  82 shared

• Chadi El Farran

  Dana-Farber Cancer Institute

  78 shared

• George M. Church

  Harvard–MIT Division of Health Sciences and Technology

  75 shared

Education

• Ph.D., Biochemistry

  University of California, San Francisco

  1986

• B.S., Chemistry

  University of California, Berkeley

  1981

Awards & honors

• MacArthur "Genius" Award
• Dickson Prize in Medicine
• Elected member of the National Academy of Sciences
• Elected member of the National Academy of Engineering
• Elected member of the National Academy of Medicine