Members

Tufts University

Aldridge Lab Website

Department of Molecular Biology and Microbiology, Tufts University School of Medicine

Boston, Massachusetts USA

Member since 2020

Aldridge virtual group meeting- Bree Aldridge (2022)

Representative

Bree Aldridge, Ph.D. Principal Investigator and Professor

Team

  • Ali Bootwala
  • Alanna Callendrello
  • Hope D’Erasmo
  • Nora Dockter
  • Timothy Fitzgerald
  • Elorm Ninsin
  • Hidetomi Nitta
  • Trever Smith
  • Tracy Washington
  • Joshua Whiteley

About

We are a multidisciplinary research team integrating quantitative measurement with computational modeling and analysis to create intuitive descriptions of complex cell biology. We focus our studies on (1) characterizing single-cell determinants of mycobacterial virulence and drug tolerance, (2) understanding how growth heterogeneity is controlled, and (3) engineering combination therapy.

Role & Expertise

In the TBDA, our work focuses on the design of optimized combination therapies for tuberculosis. We systematically measure the effects of drug combinations on M. tuberculosis to simultaneously explore the drug combination space for therapeutic potential and determine how lesion microenvironments influence bacterial response to specific drug regimens. In a second focus area, we combine fixed-cell imaging with machine learning to better understand drug pathways of action. Our goal is to develop and apply quantitative in vitro measurement with mathematical modeling to prioritize drug combinations for in vivo studies early in drug development.

Links

Aldridge Lab website

References

  1. Yoon MH, Culviner PH, Pereira Moraes M, Nitta H, Thuong NTT, Fortune SM, Aldridge BB. Strain diversity drives heterogeneous responses to tuberculosis combination therapy. Antimicrobial Agents and Chemotherapy. 2026 Jun 3;70(6):e0184925. https://doi: 10.1128/aac.01849-25. Epub 2026 May 15. PMID: 42138375; PMCID: PMC13182990.
  2. Greenstein T, Via LE, Moraes MP, Weiner DM, Dayao EK, Walker AM, Abdi A, Fleegle JD, Gomez F, Repoli KM, Woodcock MJ, Boshoff HIM, Egbelowo O, Gausi K, Denti P, Kaya F, Zimmerman M, Miller EL, Dartois VA, Barry CE 3rd, Aldridge BB. PET/CT imaging of tuberculosis lung lesions in marmosets treated with different drug regimens aligns with human clinical outcomes. Science Translational Medicine. 2026;18(831):ead9383. doi: https://doi.org/10.1126/scitranslmed.ado9383. NIHMSID: 2129178. PMCID: PMC12870020.
  3. Johnson WC, Alivisatos A, Smith TC 2nd, Van N, Soni V, Wallach JB, Clark NA, Fitzgerald TA, Whiteley JJ, Sokolov A, Ando DM, Schnappinger D, Rhee KY, Aldridge BB. Integration of multi-modal measurements identifies critical mechanisms of tuberculosis drug action. Cell Systems. 2025;16(8):101348. doi: 10.1016/j.cels.2025.101348. PMID: 40738114, PMCID PMC12365861, NIHMSID: 2100790.
  4. Chung ES, Kar P, Kamkaew M, Amir A, Aldridge BB. Single-cell imaging of the Mycobacterium tuberculosis cell cycle reveals linear and heterogeneous growth. Nature Microbiology. 2024;9(12):3332-3344. doi: 10.1038/s41564-024-01846-z. PMID: 39548343, PMCID: PMC11602732.
  5. Van N, Degefu YN, Leus PA, Larkins-Ford J, Klickstein J, Maurer FP, Stone D, Poonawala H, Thorpe CM, Smith TC 2nd, Aldridge BB. Novel synergies and isolate specificities in the drug interactions landscape of Mycobacterium abscessus. Antimicrobial Agents and Chemotherapy. 2023;67(7):e0009023. doi: 10.1128/aac.00090-23. PMID: 37278639, PMCID: PMC10353461.
  6. Larkins-Ford, J.; Aldridge, B. B. Advances in the Design of Combination Therapies for the Treatment of Tuberculosis. Expert Opinion on Drug Discovery 2023, 18 (1), 83–97. https://doi.org/10.1080/17460441.2023.2157811.
  7. Greenstein, T.; Aldridge, B. B. Tools to Develop Antibiotic Combinations That Target Drug Tolerance in Mycobacterium Tuberculosis. Frontiers in Cellular and Infection Microbiology 2023, 12.  https://doi.org/10.3389/fcimb.2022.1085946
  8. Larkins-Ford J, Degefu YN, Van N, Sokolov A, Aldridge BB. Design principles to assemble drug combinations for effective tuberculosis therapy using interpretable pairwise drug response measurements. Cell Reports Medicine. 2022;3(9):100737. doi: 10.1016/j.xcrm.2022.100737. PMID: 36084643, PMCID:  PMC9512659.Davis, K.; Greenstein, T.; Viau Colindres, R.; Aldridge, B. B. Leveraging Laboratory and Clinical Studies to Design Effective Antibiotic Combination Therapy. Current Opinion in Microbiology 2021, 64, 68–75. https://doi.org/10.1016/J.MIB.2021.09.006.
  9. Li, M.; Patel, H. V.; Cognetta, A. B.; Smith, T. C.; Mallick, I.; Cavalier, J.-F.; Previti, M. L.; Canaan, S.; Aldridge, B. B.; Cravatt, B. F.; Seeliger, J. C. Identification of Cell Wall Synthesis Inhibitors Active against Mycobacterium Tuberculosis by Competitive Activity-Based Protein Profiling. Cell Chemical Biology 2021. https://doi.org/10.1016/j.chembiol.2021.09.002.
  10. Larkins-Ford, J.; Greenstein, T.; Van, N.; Degefu, Y. N.; Olson, M. C.; Sokolov, A.; Aldridge, B. B. Systematic Measurement of Combination-Drug Landscapes to Predict in Vivo Treatment Outcomes for Tuberculosis. Cell Systems 2021, 12 (11), 1046-1063.e7. https://doi.org/10.1016/j.cels.2021.08.004.
  11. Egbelowo, O.; Sarathy, J. P.; Gausi, K.; Zimmerman, M. D.; Wang, H.; Wijnant, G. J.; Kay, F.; Gengenbacher, M.; Van, N.; Degefu, Y.; Nacy, C.; Aldridge, B. B.; Carter, C. L.; Denti, P.; Dartois, V. Pharmacokinetics and Target Attainment of SQ109 in Plasma and Human-like Tuberculosis Lesions in Rabbits. Antimicrobial Agents and Chemotherapy 2021, 65 (9). https://doi.org/10.1128/AAC.00024-21.
  12. Van, N.; Degefu, Y. N.; Aldridge, B. B. Efficient Measurement of Drug Interactions with DiaMOND (Diagonal Measurement of N-Way Drug Interactions); 2021; pp 703–713. https://doi.org/10.1007/978-1-0716-1460-0_30.
  13. Smith, T.C. 2nd.; Pullen, K. M.; Olson, M. C.; McNellis, M. E.; Richardson, I.; Hu, S.; Larkins-Ford, J.; Wang, X.; Freundlich, J. S.; Ando, D. M.; Aldridge, B. B. Morphological Profiling of Tubercle Bacilli Identifies Drug Pathways of Action. Proceedings of the National Academy of Sciences of the United States of America 2020, 117 (31). https://doi.org/10.1073/pnas.2002738117.
  14. Ma, S.; Jaipalli, S.; Larkins-Ford, J.; Lohmiller, J.; Aldridge, B. B.; Sherman, D. R.; Chandrasekaran, S. Transcriptomic Signatures Predict Regulators of Drug Synergy and Clinical Regimen Efficacy against Tuberculosis. mBio 2019, 10 (6). https://doi.org/10.1128/mBio.02627-19.
  15. Katzir, I.; Cokol, M.; Aldridge, B. B.; Alon, U. Prediction of Ultra-High-Order Antibiotic Combinations Based on Pairwise Interactions. PLoS Computational Biology 2019, 15 (1). https://doi.org/10.1371/journal.pcbi.1006774.
  16. Logsdon, M. M.; Ho, P.-Y.; Papavinasasundaram, K.; Richardson, K.; Cokol, M.; Sassetti, C. M.; Amir, A.; Aldridge, B. B. A Parallel Adder Coordinates Mycobacterial Cell-Cycle Progression and Cell-Size Homeostasis in the Context of Asymmetric Growth and Organization. Current Biology 2017, 27 (21), 3367-3374.e7. https://doi.org/10.1016/j.cub.2017.09.046.
  17. Cokol, M.; Kuru, N.; Bicak, E.; Larkins-Ford, J.; Aldridge, B. B. Efficient Measurement and Factorization of High-Order Drug Interactions in Mycobacterium Tuberculosis. Science Advances 2017, 3 (10). https://doi.org/10.1126/sciadv.1701881.
  18. Richardson, K.; Bennion, O. T.; Tan, S.; Hoang, A. N.; Cokol, M.; Aldridge, B. B. Temporal and Intrinsic Factors of Rifampicin Tolerance in Mycobacteria. Proceedings of the National Academy of Sciences of the United States of America 2016, 113 (29). https://doi.org/10.1073/pnas.1600372113.   
  19. Aldridge, B. B.; Fernandez-Suarez, M.; Heller, D.; Ambravaneswaran, V.; Irimia, D.; Toner, M.; Fortune, S. M. Asymmetry and Aging of Mycobacterial Cells Lead to Variable Growth and Antibiotic Susceptibility. Science 2012, 335 (6064). https://doi.org/10.1126/science.1216166.