title: Output-driven feedback system control platform optimizes combinatorial therapy of tuberculosis using a macrophage cell culture model.
abstract: Tuberculosis (TB) remains a major global public health problem, and improved treatments are needed to shorten duration of therapy, decrease disease burden, improve compliance, and combat emergence of drug resistance. Ideally, the most effective regimen would be identified by a systematic and comprehensive combinatorial search of large numbers of TB drugs. However, optimization of regimens by standard methods is challenging, especially as the number of drugs increases, because of the extremely large number of drug-dose combinations requiring testing. Herein, we used an optimization platform, feedback system control (FSC) methodology, to identify improved drug-dose combinations for TB treatment using a fluorescence-based human macrophage cell culture model of TB, in which macrophages are infected with isopropyl β-D-1-thiogalactopyranoside (IPTG)-inducible green fluorescent protein (GFP)-expressing Mycobacterium tuberculosis (Mtb). On the basis of only a single screening test and three iterations, we identified highly efficacious three- and four-drug combinations. To verify the efficacy of these combinations, we further evaluated them using a methodologically independent assay for intramacrophage killing of Mtb; the optimized combinations showed greater efficacy than the current standard TB drug regimen. Surprisingly, all top three- and four-drug optimized regimens included the third-line drug clofazimine, and none included the first-line drugs isoniazid and rifampin, which had insignificant or antagonistic impacts on efficacy. Because top regimens also did not include a fluoroquinolone or aminoglycoside, they are potentially of use for treating many cases of multidrug- and extensively drug-resistant TB. Our study shows the power of an FSC platform to identify promising previously unidentified drug-dose combinations for treatment of TB.
authors.affiliation: Department of Mechanical and Aerospace Engineering, University of California, Los Angeles, CA 90095;
authors.forename: Aleidy
authors.initials: A
authors.lastname: Silva
authors.affiliation: Division of Infectious Diseases, Department of Medicine, University of California, Los Angeles, CA 90095;
authors.forename: Bai-Yu
authors.initials: BY
authors.lastname: Lee
authors.affiliation: Division of Infectious Diseases, Department of Medicine, University of California, Los Angeles, CA 90095;
authors.forename: Daniel L
authors.initials: DL
authors.lastname: Clemens
authors.affiliation: Department of Bioengineering, University of California, Los Angeles, CA 90095;
authors.forename: Theodore
authors.initials: T
authors.lastname: Kee
authors.affiliation: Med-X Research Institute, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai 200030, China.
authors.forename: Xianting
authors.initials: X
authors.lastname: Ding
authors.affiliation: Department of Mechanical and Aerospace Engineering, University of California, Los Angeles, CA 90095; Department of Bioengineering, University of California, Los Angeles, CA 90095; chihming@g.ucla.edu MHorwitz@mednet.ucla.edu.
authors.forename: Chih-Ming
authors.initials: CM
authors.lastname: Ho
authors.affiliation: Division of Infectious Diseases, Department of Medicine, University of California, Los Angeles, CA 90095; chihming@g.ucla.edu MHorwitz@mednet.ucla.edu.
authors.forename: Marcus A
authors.initials: MA
authors.lastname: Horwitz
mesh_terms: D000995:Antitubercular Agents / Q000008:administration & dosage / Q000494:pharmacology*; D002460:Cell Line; D002478:Cells, Cultured; D004338:Drug Combinations; D004347:Drug Interactions; D005246:Feedback; D049452:Green Fluorescent Proteins / Q000235:genetics; D057166:High-Throughput Screening Assays; D006801:Humans; D007544:Isopropyl Thiogalactoside / Q000235:genetics; D008264:Macrophages / Q000382:microbiology; D009169:Mycobacterium tuberculosis / Q000187:drug effects* / Q000235:genetics; D014376:Tuberculosis / Q000188:drug therapy
chemical_list: D000995:Antitubercular Agents; D004338:Drug Combinations; D049452:Green Fluorescent Proteins; D007544:Isopropyl Thiogalactoside
keywords: Mycobacterium tuberculosis; drug combination optimization; feedback system control; tuberculosis