About

Dr. Jo Handelsman is the Director of the Wisconsin Institute for Discovery at the University of Wisconsin-Madison, a Vilas Research Professor, and a Howard Hughes Medical Institute Professor. She received her Ph.D. in Molecular Biology from the University of Wisconsin–Madison and has authored over 200 scientific research publications, 30 editorials, and 29 essays. Her research focuses on the genetic and biochemical processes underlying interactions within plant and human microbiomes, with groundbreaking studies in microbial communication and metagenomics. In addition to her scientific contributions, she is widely recognized for her efforts in science education and promoting diversity in science, having authored numerous articles on classroom methods and mentoring, and co-authored six books about teaching, including 'Entering Mentoring' and 'Scientific Teaching.' Dr. Handelsman previously served as a science advisor to President Barack Obama as the Associate Director for Science at the White House Office of Science and Technology Policy, and has held faculty positions at the University of Wisconsin and Yale University. Her numerous honors include the Presidential Award for Excellence in Science, Mathematics, and Engineering Mentoring, induction into the American Academy of Arts and Sciences, and election to the National Academy of Sciences.

Research topics

• Political Science
• Sociology
• Social Science
• Computer Science
• Biology
• Bioinformatics
• Microbiology
• Psychology
• Artificial Intelligence
• Public relations
• Data science
• Data Mining
• Database
• Biochemistry
• Engineering
• Pedagogy
• Engineering ethics
• World Wide Web
• Computational biology
• Genetics

Selected publications

• Nematicidal indole oxazoles and chemoattractants from soil bacteria

  bioRxiv (Cold Spring Harbor Laboratory) · 2026-01-20

  articleOpen accessSenior authorCorresponding

  Abstract Ecological interactions between bacteria and nematodes in many environments provide a basis for the prediction that diverse bacteria produce anti-nematode compounds. The discovery of microbial secondary metabolites with broad-spectrum nematostatic or nematicidal properties can be hastened by drug screening approaches that include several nematode species and phenotypes. We cultured a collection of 22 soil-derived bacterial isolates that carry in their genomes putative pathways for production of unknown secondary metabolites. Isolates were cultured in various media to enhance natural product diversity and yield, and we evaluated culture filtrates for activity against two evolutionarily distinct nematode species: Clade V free-living nematode Caenorhabditis elegans and Clade III mammalian parasitic nematodes in the genus Brugia . Partitioned extracts from Pseudomonas sp. strain TE4607 stunted C. elegans development and caused motility defects in both blood-circulating larval and adult stages of Brugia . The primary active compound was identified as labradorin 1, an indole with known antibacterial and anticancer properties that had not been previously described as affecting nematodes. Notably, filtrates of Pseudomonas sp. TE4607 cultures attracted free-living nematodes in sensory assays, adding to evidence that certain Pseudomonas species modulate the behavior of free-living nematodes. These findings underscore the need to further explore the link between nematode sensory responses and whole-organism effects of microbial metabolites, with potential applications in anthelmintic discovery. Abstract Figure

  PublisherOA PDFDOI

• Using cross-species co-expression to predict metabolic interactions in microbiomes

  mSystems · 2025-12-09 · 1 citations

  articleOpen access

  ABSTRACT In microbial ecosystems, metabolic interactions are key determinants of species’ relative abundance and activity. Given the immense number of possible interactions in microbial communities, their experimental characterization is best guided by testable hypotheses generated through computational predictions. However, widely adopted software tools—such as those utilizing microbial co-occurrence—typically fail to highlight the pathways underlying these interactions. Bridging this gap will require methods that utilize microbial activity data to infer putative target pathways for experimental validation. In this study, we explored a novel approach by applying cross-species co-expression to predict interactions from microbial co-culture RNA-sequencing data. Specifically, we investigated the extent to which co-expression between genes and pathways of different bacterial species can predict competition, cross-feeding, and specialized metabolic interactions. Our analysis of the Mucin and Diet-based Minimal Microbiome (MDb-MM) data yielded results consistent with previous findings and demonstrated the method’s potential to identify pathways that are subject to resource competition. Our analysis of the Hitchhikers of the Rhizosphere (THOR) data showed links between related specialized functions, for instance, between antibiotic and multidrug efflux system expression. Additionally, siderophore co-expression and further evidence suggested that increased siderophore production of the Pseudomonas koreensis koreenceine BGC deletion-mutant drives siderophore production in the other community members. In summary, our findings confirm the feasibility of using cross-species co-expression to predict pathways potentially involved in microbe-microbe interactions. We anticipate that the approach will also facilitate the discovery of novel gene functions through their association with other species’ metabolic pathways, for example, those involved in antibiotic response. IMPORTANCE An improved mechanistic understanding of microbial interactions can guide targeted interventions or inform the rational design of microbial communities to optimize them for applications such as pathogen control, food fermentation, and various biochemical processes. Existing methodologies for inferring the mechanisms behind microbial interactions often rely on complex model-building and are, therefore, sensitive to the introduction of biases from the incorporated existing knowledge and model-building assumptions. We highlight the microbial interaction prediction potential of cross-species co-expression analysis, which contrasts with these methods by its data-driven nature. We describe the utility of cross-species co-expression for various types of interactions and thereby inform future studies on use-cases of the approach and the opportunities and pitfalls that can be expected in its application.

  PublisherDOI

• Boosting scientific community values: The impact of social inclusion interventions on biomedical instructors

  Journal of Clinical and Translational Science · 2025-01-01 · 1 citations

  articleOpen access

  Abstract Interventions to foster inclusive learning environments may benefit college STEMM instructors (NASEM, 2019). We investigated the impact of a social inclusion intervention (SII) on scientific self-efficacy, identity, community values, and persistence intentions in a large and diverse sample of biomedical college instructors ( n = 116) in the USA. The results indicated that the SII group developed stronger scientific community values than the control group, and the effect was the strongest for instructors who had initially expressed lower values. From a mentoring perspective, the intervention helps boost feelings of community values, which is linked to increased persistence in STEMM careers.

  PublisherOA PDFDOI

• University scientists’ willingness to participate in public engagement: A concept explication

  PLoS ONE · 2025-11-25

  articleOpen accessSenior authorCorresponding

  Public engagement is increasingly recognized as a critical responsibility of the scientific community. Scientists in academic settings are well positioned to lead these efforts, but they are not always willing or able to participate in engagement. Public engagement can encompass a range of activities that may require different resources and skills, and which may have different outcomes for both scientists and non-scientists. Therefore, understanding which activities scientists are willing to participate in is critical for supporting their engagement efforts at the institutional level. Using survey data from a case study of science faculty at a large land-grant university in the United States, we conduct a systematic concept explication to better understand the dimensions of public engagement activities that scientists are willing to participate in. Based on thirteen different activities, we define and analyze the reliability of five dimensions of engagement: public scholarship, educational activities, direct engagement with public audiences, stakeholder-focused collaboration, and industry engagement. We also examine the validity of these five dimensions and how factors including institutional culture and norms, professional status, and attitudes towards engagement relate to scientists' willingness to participate in engagement. Our results provide a robust categorization of willingness to engage as a blueprint for future research in this space.

  PublisherDOI

• Using cross-species co-expression to predict metabolic interactions in microbiomes

  bioRxiv (Cold Spring Harbor Laboratory) · 2025-09-16

  preprintOpen access

  Abstract In microbial ecosystems, metabolic interactions are key determinants of species’ relative abundance and activity. Given the immense number of possible interactions in microbial communities, their experimental characterization is best guided by testable hypotheses generated through computational predictions. However, widely adopted software tools – such as those utilizing microbial co-occurrence – typically fail to highlight the pathways underlying these interactions. Bridging this gap will require methods that utilize microbial activity data to infer putative target pathways for experimental validation. In this study, we explored a novel approach by applying cross-species co-expression to predict interactions from microbial co-culture RNA-sequencing data. Specifically, we investigated the extent to which co-expression between genes and pathways of different bacterial species can predict competition, cross-feeding, and specialized metabolic interactions. Our analysis of the Mucin and Diet-based Minimal Microbiome (MDb-MM) data yielded results consistent with previous findings and demonstrated the method’s potential to identify pathways that are subject to resource competition. Our analysis of the Hitchhikers of the Rhizosphere (THOR) data showed links between related specialized functions, for instance, between antibiotic and multidrug efflux system expression. Additionally, siderophore co-expression and further evidence suggested that increased siderophore production of the Pseudomonas koreensis koreenceine BGC deletion-mutant drives siderophore production in the other community members. In summary, our findings confirm the feasibility of using cross-species co-expression to predict pathways potentially involved in microbe-microbe interactions. We anticipate that the approach will also facilitate the discovery of novel gene functions through their association with other species’ metabolic pathways, for example, those involved in antibiotic response. Importance An improved mechanistic understanding of microbial interactions can guide targeted interventions or inform the rational design of microbial communities to optimize them for applications such as pathogen control, food fermentation, and various biochemical processes. Existing methodologies for inferring the mechanisms behind microbial interactions often rely on complex model-building and are therefore sensitive to the introduction of biases from the incorporated existing knowledge and model-building assumptions. We highlight the microbial interaction prediction potential of cross-species co-expression analysis, which contrasts with these methods by its data-driven nature. We describe the utility of cross-species co-expression for various types of interactions and thereby inform future studies on use-cases of the approach and the opportunities and pitfalls that can be expected in its application.

  PublisherOA PDFDOI

• Fueling Future Antibiotic Discovery: An Analysis of Taxonomic and Biosynthetic Diversity in Antimicrobial-Producing Soil Bacterial Isolates

  UF Journal of Undergraduate Research · 2025-11-05

  articleOpen access

  More than 80% of clinical antibiotics are compounds produced by soil bacteria, and there are many more unknown pathogen-inhibiting compounds encoded by clusters of co-localized genes (i.e., biosynthetic gene clusters) in soil bacterial genomes. To find novel antimicrobial drug candidates using a genome-level approach, biosynthetic gene clusters (BGCs) can be identified and compared against a database of known BGCs to infer what secondary metabolite(s) may be encoded. This study aims to uncover the diversity of these BGCs and characterize evolutionary patterns of BGC distribution across a phylogeny of 305 soil-derived bacterial isolates. BGCs were predicted through antiSMASH and taxonomic classification was conducted via GTDB-tk. OrthoFinder was used to perform a multi-locus sequence analysis and phylogenetic tree construction. The results of this investigation, an annotated phylogeny with mapped BGC data, will provide future antibiotic discovery researchers with deeper genetic insight into the biosynthetic potential and evolutionary patterns of BGCs for the investigated bacterial strains.

  PublisherDOI

• Tiny Earth CURE Demonstrates Equitable Benefits for U.S. College Science Students

  CBE—Life Sciences Education · 2025-05-29 · 3 citations

  articleOpen access

  Course-based undergraduate research experiences (CURE) enhance student retention in science, technology, engineering, and math (STEM), particularly among students who belong to historically excluded communities. Yet the mechanisms by which CUREs contribute to student integration and persistence are poorly understood. Utilizing the tripartite integration model of social influence (TIMSI), this longitudinal study examines whether and how Tiny Earth-an antibiotic-discovery CURE designed for flexible implementation in a variety of course contexts-impacts students' scientific self-efficacy, scientific identity, endorsement of scientific community values, and intentions to persist in science. The study also explores how gains in TIMSI factors (i.e., scientific self-efficacy, identity, and values) vary as a function of student demographics and course characteristics. A comparison of pre- and postcourse measurements showed that scientific self-efficacy and identity increased among students in Tiny Earth. Some student demographics and course characteristics moderated these gains. Gains in all three TIMSI factors correlated with gains in persistence intentions, whereas student demographics and course characteristics did not. This study shows that the Tiny Earth curriculum equitably improved students' scientific self-efficacy and identity. It also showed that orientation toward scientific values and STEM persistence intentions held steady across most demographic groups.

  PublisherDOI

• Co-zorbs: Motile, multispecies biofilms aid transport of diverse bacterial species

  Proceedings of the National Academy of Sciences · 2025-02-03 · 4 citations

  articleOpen accessSenior authorCorresponding

  Biofilms are three-dimensional structures containing one or more bacterial species embedded in extracellular polymeric substances. Although most biofilms are stationary, Flavobacterium johnsoniae forms a motile spherical biofilm called a zorb, which is propelled by its base cells and contains a polysaccharide core. Here, we report the formation of spatially organized, motile, multispecies biofilms, designated “co-zorbs,” that are distinguished by a core–shell structure. F. johnsoniae forms zorbs whose cells collect other bacterial species and transport them to the zorb core, forming a co-zorb. Live imaging revealed that co-zorbs also form in zebrafish, thereby demonstrating a different type of bacterial movement in vivo. This finding opens different avenues for understanding community behaviors, the role of biofilms in bulk bacterial transport, and collective strategies for microbial success in various environments.

  PublisherOA PDFDOI

• Skin-associated <i>Corynebacterium amycolatum</i> shares cobamides

  mSphere · 2024-12-18 · 2 citations

  articleOpen access

  ABSTRACT The underlying interactions that occur to maintain skin microbiome composition, function, and overall skin health are largely unknown. Often, these types of interactions are mediated by microbial metabolites. Cobamides, the vitamin B 12 family of cofactors, are essential for metabolism in many bacteria but are only synthesized by a fraction of prokaryotes, including certain skin-associated species. Therefore, we hypothesize that cobamide sharing mediates skin community dynamics. Preliminary work predicts that several skin-associated Corynebacterium species encode de novo cobamide biosynthesis and that their abundance is associated with skin microbiome diversity. Here, we show that commensal Corynebacterium amycolatum produces cobamides and that this synthesis can be tuned by cobalt limitation. To demonstrate cobamide sharing by C. amycolatum , we employed a co-culture assay using an E. coli cobamide auxotroph and showed that C. amycolatum produces sufficient cobamides to support Escherichia coli growth, both in liquid co-culture and when separated spatially on solid medium. We also generated a C. amycolatum non-cobamide-producing strain (cob – ) using UV mutagenesis that contains mutated cobamide biosynthesis genes cobK (precorrin-6X reductase) and cobO (corrinoid adenosyltransferase) and confirm that disruption of cobamide biosynthesis abolishes the support of E. coli growth through cobamide sharing. Our study provides a unique model to study metabolite sharing by microorganisms, which will be critical for understanding the fundamental interactions that occur within complex microbiomes and for developing approaches to target the human microbiota for health advances. IMPORTANCE The human skin serves as a crucial barrier for the body and hosts a diverse community of microbes known as the skin microbiome. The interactions that occur to maintain a healthy skin microbiome are largely unknown but are thought to be driven in part, by nutrient sharing between species in close association. Here we show that the skin-associated bacteria Corynebacterium amycolatum produces and shares cobalamin, a cofactor essential for survival in organisms across all domains of life. This study provides a unique model to study metabolite sharing by skin microorganisms, which will be critical for understanding the fundamental interactions that occur within the skin microbiome and for developing therapeutic approaches aiming to engineer and manipulate the skin microbiota.

  PublisherDOI

• multimedia: Multimodal Mediation Analysis of Microbiome Data

  bioRxiv (Cold Spring Harbor Laboratory) · 2024-03-30

  preprintOpen access

  Abstract Mediation analysis has emerged as a versatile tool for answering mechanistic questions in microbiome research because it provides a statistical framework for attributing treatment effects to alternative causal pathways. Using a series of linked regressions, this analysis quantifies how complementary data relate to one another and respond to treatments. Despite these advances, existing software’s rigid assumptions often result in users viewing mediation analysis as a black box. We designed the multimedia R package to make advanced mediation analysis techniques accessible, ensuring that statistical components are interpretable and adaptable. The package provides a uniform interface to direct and indirect effect estimation, synthetic null hypothesis testing, bootstrap confidence interval construction, and sensitivity analysis, enabling experimentation with various mediator and outcome models while maintaining a simple overall workflow. The software includes modules for regularized linear, compositional, random forest, hierarchical, and hurdle modeling, making it well-suited to microbiome data. We illustrate the package through two case studies. The first re-analyzes a study of the microbiome and metabolome of Inflammatory Bowel Disease patients, uncovering potential mechanistic interactions between the microbiome and disease-associated metabolites, not found in the original study. The second analyzes new data about the influence of mindfulness practice on the microbiome. The mediation analysis highlights shifts in taxa previously associated with depression that cannot be explained indirectly by diet or sleep behaviors alone. A gallery of examples and further documentation can be found at https://go.wisc.edu/830110 . IMPORTANCE Microbiome studies routinely gather complementary data to capture different aspects of a microbiome’s response to a change, such as the introduction of a therapeutic. Mediation analysis clarifies the extent to which responses occur sequentially via mediators, thereby supporting causal, rather than purely descriptive, interpretation. multimedia is a modular R package with close ties to the wider microbiome software ecosystem that makes statistically rigorous, flexible mediation analysis easily accessible, setting the stage for precise and causally informed microbiome engineering.

  PublisherOA PDFDOI

Recent grants

• NIH Grant R01GM075830

  NIH · $845k · 2009

• NIH Grant R03AI042786

  NIH · $195k · 2002

• A New Wave of Scientific Teaching

  NSF · $200k · 2006–2008

• NIH Grant R01GM099563

  NIH · $1.1M · 2016

• From phalanx to assassins: The commensal-to-pathogen switch in the lepidopteran gut microbial community

  NSF · $177k · 2010–2011

Frequent coauthors

• Gabriel L. Lozano

  Wisconsin Institutes for Discovery

  106 shared

• Nichole A. Broderick

  Johns Hopkins University

  55 shared

• Amanda Hurley

  Wisconsin Institutes for Discovery

  47 shared

• Juan I. Bravo

  University of Southern California

  38 shared

• Marc G. Chevrette

  Florida Museum of Natural History

  35 shared

• Eric V. Stabb

  University of Illinois Chicago

  32 shared

• Robert M. Goodman

  29 shared

• Kenneth F. Raffa

  University of Wisconsin–Madison

  29 shared

Labs

• Handelsman LabPI

Education

• Ph.D., Microbiology

  Massachusetts Institute of Technology

  1986

• B.S., Microbiology

  University of California, Berkeley

  1981

Awards & honors

• Presidential Award for Excellence in Science, Mathematics, a…
• Inducted into the American Academy of Arts and Sciences (201…
• Elected to the National Academy of Sciences (2023)