Transcriptomic responses to antibiotic exposure in Mycobacterium tuberculosis

Author:

Poonawala Husain1234ORCID,Zhang Yu5,Kuchibhotla Sravya6,Green Anna G.5,Cirillo Daniela Maria7ORCID,Di Marco Federico7ORCID,Spitlaeri Andrea78,Miotto Paolo7ORCID,Farhat Maha R.59ORCID

Affiliation:

1. Department of Medicine and Department of Pathology and Laboratory Medicine, Tufts Medical Center, Boston, Massachusetts, USA

2. Department of Medicine and Department of Anatomic and Clinical Pathology, Tufts University School of Medicine, Boston, Massachusetts, USA

3. Stuart B. Levy Center for Integrated Management of Antimicrobial Resistance, Boston, Massachusetts, USA

4. Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA

5. Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, USA

6. Harvard College, Cambridge, Massachusetts, USA

7. Emerging Bacterial Pathogens Unit, Division of Immunology, Transplantation and Infectious Diseases, IRCCS San Raffaele Scientific Institute, Milan, Italy

8. Department of Medical Biotechnology and Translational Medicine, Università degli Studi di Milano, Milan, Italy

9. Department of Medicine, Division of Pulmonary and Critical Care Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA

Abstract

ABSTRACT Transcriptional responses in bacteria following antibiotic exposure offer insights into antibiotic mechanism of action, bacterial responses, and characterization of antimicrobial resistance. We aimed to define the transcriptional antibiotic response (TAR) in Mycobacterium tuberculosis (Mtb) isolates for clinically relevant drugs by pooling and analyzing Mtb microarray and RNA-seq data sets. We generated 99 antibiotic transcription profiles across 17 antibiotics, with 76% of profiles generated using 3–24 hours of antibiotic exposure and 49% within one doubling of the WHO antibiotic critical concentration. TAR genes were time-dependent, and largely specific to the antibiotic mechanism of action. TAR signatures performed well at predicting antibiotic exposure, with the area under the receiver operating curve (AUC) ranging from 0.84-1.00 (TAR <6 hours of antibiotic exposure) and 0.76–1.00 (>6 hours of antibiotic exposure) for upregulated genes and 0.57–0.90 and 0.87–1.00, respectfully, for downregulated genes. This work desmonstrates that transcriptomics allows for the assessment of antibiotic activity in Mtb within 6 hours of exposure.

Funder

HHS | NIH | National Institute of Allergy and Infectious Diseases

EC | Seventh Framework Programme

HHS | NIH | National Center for Advancing Translational Sciences

Publisher

American Society for Microbiology

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