Bonnie L Hurwitz
Assistant Professor, Agricultural-Biosystems Engineering
Assistant Professor, BIO5 Institute
Assistant Professor, Genetics - GIDP
Assistant Professor, Statistics-GIDP
Clinical Instructor, Pharmacy Practice-Science
Primary Department
Department Affiliations
(520) 626-9819
Work Summary
Our lab focuses on large-scale –omics datasets, high-throughput computing, and big data analytics. We leverage these technologies to answer questions related to the relationship between microbes, their hosts, and the environment. In particular, we focus on viral-host interactions and co-evolution given environmental factors (i) in aquatic systems and (ii) for phage treatment of diabetic foot ulcers.
Research Interest
Dr. Bonnie Hurwitz is an Assistant Professor of Biosystems Engineering at the University of Arizona and BIO5 Research Institute Fellow. She has worked as a computational biologist for nearly two decades on interdisciplinary projects in both industry and academia. Her research on the human/earth microbiome incorporates large-scale –omics datasets, high-throughput computing, and big data analytics towards research questions in “One Health”. In particular, Dr. Hurwitz is interested in the relationship between the environment, microbial communities, and their hosts. Dr. Hurwitz is well-cited for her work in computational biology in diverse areas from plant genomics to viral metagenomics with over 1200 citations


Ball, C. L., Daniel, S. G., Besselsen, D. G., Hurwitz, B. L., & Doetschman, T. C. (2017). Functional changes in the gut microbiome contribute to Transforming Growth Factor β-deficient colon cancer. mSystems, 2(5), 1-17.
BIO5 Collaborators
David G Besselsen, Thomas C Doetschman, Bonnie L Hurwitz
Alberti, A., Poulain, J., Engelen, S., Labadie, K., Romac, S., Ferrera, I., Albini, G., Aury, J. M., Belser, C., Bertrand, A., Cruaud, C., Da Silva, C., Dossat, C., Gavory, F., Gas, S., Guy, J., Haquelle, M., Jacoby, E., Jaillon, O., , Lemainque, A., et al. (2017). Viral to metazoan marine plankton nucleotide sequences from the Tara Oceans expedition. Scientific data, 4, 170093.

A unique collection of oceanic samples was gathered by the Tara Oceans expeditions (2009-2013), targeting plankton organisms ranging from viruses to metazoans, and providing rich environmental context measurements. Thanks to recent advances in the field of genomics, extensive sequencing has been performed for a deep genomic analysis of this huge collection of samples. A strategy based on different approaches, such as metabarcoding, metagenomics, single-cell genomics and metatranscriptomics, has been chosen for analysis of size-fractionated plankton communities. Here, we provide detailed procedures applied for genomic data generation, from nucleic acids extraction to sequence production, and we describe registries of genomics datasets available at the European Nucleotide Archive (ENA, The association of these metadata to the experimental procedures applied for their generation will help the scientific community to access these data and facilitate their analysis. This paper complements other efforts to provide a full description of experiments and open science resources generated from the Tara Oceans project, further extending their value for the study of the world's planktonic ecosystems.

U'Ren, J. M., Wisecaver, J. H., Paek, A. L., Dunn, B. L., & Hurwitz, B. L. (2015). Draft Genome Sequence of the Ale-Fermenting Saccharomyces cerevisiae Strain GSY2239. Genome announcements, 3(4).

Saccharomyces cerevisiae strain GSY2239 is derived from an industrial yeast strain used to ferment ale-style beer. We present here the 11.5-Mb draft genome sequence for this organism.

Liang, C., Jaiswal, P., Hebbard, C., Avraham, S., Buckler, E. S., Casstevens, T., Hurwitz, B., McCouch, S., Ni, J., Pujar, A., Ravenscroft, D., Ren, L., Spooner, W., Tecle, I., Thomason, J., Tung, C., Wei, X., Yap, I., Youens-Clark, K., , Ware, D., et al. (2008). Gramene: a growing plant comparative genomics resource. Nucleic acids research, 36(Database issue), D947-53.

Gramene ( is a curated resource for genetic, genomic and comparative genomics data for the major crop species, including rice, maize, wheat and many other plant (mainly grass) species. Gramene is an open-source project. All data and software are freely downloadable through the ftp site ( and available for use without restriction. Gramene's core data types include genome assembly and annotations, other DNA/mRNA sequences, genetic and physical maps/markers, genes, quantitative trait loci (QTLs), proteins, ontologies, literature and comparative mappings. Since our last NAR publication 2 years ago, we have updated these data types to include new datasets and new connections among them. Completely new features include rice pathways for functional annotation of rice genes; genetic diversity data from rice, maize and wheat to show genetic variations among different germplasms; large-scale genome comparisons among Oryza sativa and its wild relatives for evolutionary studies; and the creation of orthologous gene sets and phylogenetic trees among rice, Arabidopsis thaliana, maize, poplar and several animal species (for reference purpose). We have significantly improved the web interface in order to provide a more user-friendly browsing experience, including a dropdown navigation menu system, unified web page for markers, genes, QTLs and proteins, and enhanced quick search functions.

Hurwitz, B. L., & Sullivan, M. B. (2013). The Pacific Ocean virome (POV): a marine viral metagenomic dataset and associated protein clusters for quantitative viral ecology. PloS one, 8(2), e57355.

Bacteria and their viruses (phage) are fundamental drivers of many ecosystem processes including global biogeochemistry and horizontal gene transfer. While databases and resources for studying function in uncultured bacterial communities are relatively advanced, many fewer exist for their viral counterparts. The issue is largely technical in that the majority (often 90%) of viral sequences are functionally 'unknown' making viruses a virtually untapped resource of functional and physiological information. Here, we provide a community resource that organizes this unknown sequence space into 27 K high confidence protein clusters using 32 viral metagenomes from four biogeographic regions in the Pacific Ocean that vary by season, depth, and proximity to land, and include some of the first deep pelagic ocean viral metagenomes. These protein clusters more than double currently available viral protein clusters, including those from environmental datasets. Further, a protein cluster guided analysis of functional diversity revealed that richness decreased (i) from deep to surface waters, (ii) from winter to summer, (iii) and with distance from shore in surface waters only. These data provide a framework from which to draw on for future metadata-enabled functional inquiries of the vast viral unknown.