DynamicKit - Analysis of Antibiotic Resistance Profiles of Mycobacteria

Investigation of antibiotic resistance profiles of mycobacteria was performed by a combined approach of high-performance liquid chromatography coupled to mass spectrometry by intact mass analysis and bottom-up proteomics.

In a previous study, newly synthesized proteins in mycobacteria were measured using stable isotope labeling and matrix-assisted laser desorption-ionization time-of-flight mass spectrometry (MALDI-TOF MS). By tracking de novo protein synthesis after adding ¹³C-glycerol, the approach enables high-resolution monitoring of metabolic responses to antibiotics. The method detects how different antimicrobials alter protein synthesis within half a doubling time. Because it is untargeted and does not require genetic modification, it can be applied to both model strains and clinical isolates.

In this follow-up study, the previous approach was expanded by integrating high-performance liquid chromatography–mass spectrometry (HPLC-MS), providing deeper insights into the antibiotic resistance profiles of mycobacteria. Two complementary strategies were employed: an untargeted intact-mass analysis and a bottom-up proteomics workflow using tandem-mass-tag (TMT) labeling for precise protein quantification. The intact-mass approach enabled the detection of 229 proteins in the model strain M. smegmatis and revealed distinct protein responses in a selected subset following rifampicin treatment. With HPLC-MS, the overall proteome coverage increased to >100 proteins. A subsequent bottom-up analysis confirmed the presence of 15 proteins previously identified by intact-mass profiling. To assess antibiotic-induced proteome changes in wild-type and dormant M. smegmatis across multiple time points, TMT-based quantification was performed, uncovering characteristic patterns of protein up- and downregulation in response to rifampicin and BTZ-043. Network analysis further indicated that regulatory pathways are modulated by antibiotic exposure.

Responsible

Anja Dollinger, Dominik Schum

Funding

Bayerisches Staatsministerium für Wissenschaft und Kunst
Fraunhofer ITMP 

Branch Immunology, Infectious Diseases und Pandemic Research IIP

Partner

Fraunhofer ITMP 

Branch Immunology, Infectious Diseases und Pandemic Research IIP