Honors & Awards


  • Graduate Research Fellowship (GRFP), NSF (2018)

Current Research and Scholarly Interests


Molecular host-microbe interactions, co-evolution of host and microbes, neglected infectious diseases

All Publications


  • Salmonella-Driven Polarization of Granuloma Macrophages Antagonizes TNF-Mediated Pathogen Restriction during Persistent Infection. Cell host & microbe Pham, T. H., Brewer, S. M., Thurston, T., Massis, L. M., Honeycutt, J., Lugo, K., Jacobson, A. R., Vilches-Moure, J. G., Hamblin, M., Helaine, S., Monack, D. M. 2019

    Abstract

    Many intracellular bacteria can establish chronic infection and persist in tissues within granulomas composed of macrophages. Granuloma macrophages exhibit heterogeneous polarization states, or phenotypes, that may be functionally distinct. Here, we elucidate a host-pathogen interaction that controls granuloma macrophage polarization and long-term pathogen persistence during Salmonella Typhimurium (STm) infection. We show that STm persists within splenic granulomas that are densely populated by CD11b+CD11c+Ly6C+ macrophages. STm preferentially persists in granuloma macrophages reprogrammed to an M2 state, in part through the activity of the effector SteE, which contributes to the establishment of persistent infection. We demonstrate that tumor necrosis factor (TNF) signaling limits M2 granuloma macrophage polarization, thereby restricting STm persistence. TNF neutralization shifts granuloma macrophages toward an M2 state and increases bacterial persistence, and these effects are partially dependent on SteE activity. Thus, manipulating granuloma macrophage polarization represents a strategy for intracellular bacteria to overcome host restriction during persistent infection.

    View details for DOI 10.1016/j.chom.2019.11.011

    View details for PubMedID 31883922

  • A White-Box Machine Learning Approach for Revealing Antibiotic Mechanisms of Action CELL Yang, J. H., Wright, S. N., Hamblin, M., McCloskey, D., Alcantar, M. A., Schrubbers, L., Lopatkin, A. J., Satish, S., Nili, A., Palsson, B. O., Walker, G. C., Collins, J. J. 2019; 177 (6): 1649-+

    Abstract

    Current machine learning techniques enable robust association of biological signals with measured phenotypes, but these approaches are incapable of identifying causal relationships. Here, we develop an integrated "white-box" biochemical screening, network modeling, and machine learning approach for revealing causal mechanisms and apply this approach to understanding antibiotic efficacy. We counter-screen diverse metabolites against bactericidal antibiotics in Escherichia coli and simulate their corresponding metabolic states using a genome-scale metabolic network model. Regression of the measured screening data on model simulations reveals that purine biosynthesis participates in antibiotic lethality, which we validate experimentally. We show that antibiotic-induced adenine limitation increases ATP demand, which elevates central carbon metabolism activity and oxygen consumption, enhancing the killing effects of antibiotics. This work demonstrates how prospective network modeling can couple with machine learning to identify complex causal mechanisms underlying drug efficacy.

    View details for DOI 10.1016/j.cell.2019.04.016

    View details for Web of Science ID 000469415100025

    View details for PubMedID 31080069

    View details for PubMedCentralID PMC6545570

  • A CRISPR-Cas9-based gene drive platform for genetic interaction analysis in Candida albicans NATURE MICROBIOLOGY Shapiro, R. S., Chavez, A., Porter, C. M., Hamblin, M., Kaas, C. S., DiCarlo, J. E., Zeng, G., Xu, X., Revtovich, A. V., Kirienko, N. V., Wang, Y., Church, G. M., Collins, J. J. 2018; 3 (1)
  • Understanding and Sensitizing Density-Dependent Persistence to Quinolone Antibiotics MOLECULAR CELL Gutierrez, A., Jain, S., Bhargava, P., Hamblin, M., Lobritz, M. A., Collins, J. J. 2017; 68 (6): 1147-+

    Abstract

    Physiologic and environmental factors can modulate antibiotic activity and thus pose a significant challenge to antibiotic treatment. The quinolone class of antibiotics, which targets bacterial topoisomerases, fails to kill bacteria that have grown to high density; however, the mechanistic basis for this persistence is unclear. Here, we show that exhaustion of the metabolic inputs that couple carbon catabolism to oxidative phosphorylation is a primary cause of growth phase-dependent persistence to quinolone antibiotics. Supplementation of stationary-phase cultures with glucose and a suitable terminal electron acceptor to stimulate respiratory metabolism is sufficient to sensitize cells to quinolone killing. Using this approach, we successfully sensitize high-density populations of Escherichia coli, Staphylococcus aureus, and Mycobacterium smegmatis to quinolone antibiotics. Our findings link growth-dependent quinolone persistence to discrete impairments in respiratory metabolism and identify a strategy to kill non-dividing bacteria.

    View details for DOI 10.1016/j.molcel.2017.11.012

    View details for Web of Science ID 000418607500012

    View details for PubMedID 29225037

  • Draft Genome Sequence of the Shellfish Larval Probiotic Bacillus pumilus RI06-95 MICROBIOLOGY RESOURCE ANNOUNCEMENTS Hamblin, M., Spinard, E., Gomez-Chiarri, M., Nelson, D. R., Rowley, D. C. 2015; 3 (5)

    Abstract

    Bacillus pumilus RI06-95 is a marine bacterium isolated in Narragansett, Rhode Island, which has shown probiotic activity against marine pathogens in larval shellfish. We report the genome of B. pumilus RI06-95, which provides insight into the microbe's probiotic ability and may be used in future studies of the probiotic mechanism.

    View details for DOI 10.1128/genomeA.00858-15

    View details for Web of Science ID 000460642600004

    View details for PubMedID 26337873

    View details for PubMedCentralID PMC4559722