Can phenotypic data complement our understanding of antimycobacterial effects for drug combinations?

Frank Kloprogge, Robert Hammond, Andrew Copas, Stephen H Gillespie, Oscar Della Pasqua

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)
9 Downloads (Pure)


Objectives: To demonstrate how phenotypic cell viability data can provide insight into antimycobacterial effects for the isoniazid/rifampicin treatment backbone.

Methods: Data from a Mycobacterium komossense hollow-fibre infection model comprising a growth control group, rifampicin at three different exposures (Cmax = 0.14, 0.4 and 1.47 mg/L with t½ = 1.57 h and τ = 8 h) and rifampicin plus isoniazid (Cmax rifampicin = 0.4 mg/L and Cmax isoniazid = 1.2 mg/L with t½ = 1.57 h and τ = 8 h) were used for this investigation. A non-linear mixed-effects modelling approach was used to fit conventional cfu data, quantified using solid-agar plating. Phenotypic proportions of respiring (alive), respiring but with damaged cell membrane (injured) and 'not respiring' (dead) cells data were quantified using flow cytometry and Sytox Green™ (Sigma-Aldrich, UK) and resazurin sodium salt staining and fitted using a multinomial logistic regression model.

Results: Isoniazid/rifampicin combination therapy displayed a decreasing overall antimicrobial effect with time (θTime1/2 = 438 h) on cfu data, in contrast to rifampicin monotherapy where this trend was absent. In the presence of isoniazid a phenotype associated with cell injury was displayed, whereas with rifampicin monotherapy a pattern of phenotypic cell death was observed. Bacterial killing onset time on cfu data correlated negatively (θTime50 = 28.9 h, θLAGRIF50 = 0.132 mg/L) with rifampicin concentration up to 0.165 mg/L and this coincided with a positive relationship between rifampicin concentration and the probability of phenotypic cell death.

Conclusions: Cell viability data provide structured information on the pharmacodynamic interaction between isoniazid and rifampicin that complements the understanding of the antibacillary effects of this mycobacterial treatment backbone.
Original languageEnglish
Pages (from-to)3530–3536
Number of pages7
JournalJournal of Antimicrobial Chemotherapy
Issue number12
Early online date25 Aug 2019
Publication statusPublished - Dec 2019


Dive into the research topics of 'Can phenotypic data complement our understanding of antimycobacterial effects for drug combinations?'. Together they form a unique fingerprint.

Cite this