Hepatocytic transcriptional signatures predict comparative drug interaction potential of rifamycin antibiotics

Abstract

Current strategies to treat tuberculosis (TB) and co-morbidities involve multidrug combination therapies. Rifamycin antibiotics are a key component of TB therapy and a common source of drug-drug interactions (DDIs) due to induction of drug metabolizing enzymes (DMEs). Management of rifamycin DDIs are complex, particularly in patients with co-morbidities, and differences in DDI potential between rifamycin antibiotics are not well established. DME profiles induced in response to tuberculosis antibiotics (rifampin, rifabutin and rifapentine) were compared in primary human hepatocytes. We identified rifamycin induced DMEs, cytochrome P450 (CYP) 2C8/3A4/3A5, SULT2A, and UGT1A4/1A5 and predicted lower DDIs of rifapentine with 58 clinical drugs used to treat co-morbidities in TB patients. Transcriptional networks and upstream regulator analyses showed FOXA3, HNF4α, NR1I2, NR1I3, NR3C1 and RXRα as key transcriptional regulators of rifamycin induced DMEs. Our study findings are an important resource to design effective medication regimens to treat common co-conditions in TB patients.

Figure 1

Bioavailability of parent rifampin, rifabutin, and rifapentine drugs and their des-metabolites in primary human hepatocytes (PHHs). PHHs derived from healthy donors were independently treated with rifamycin antibiotics (10 µM) for 72 h. Intracellular concentration of parent to metabolites (Cp/Cm) were quantified using liquid chromatography tandem mass spectrometry (LC/MS) analysis and drug concentration per million PHHs are shown.

Figure 2

Integrated gene signature of rifamycin antibiotics and pathways induced in PHHs in response to 10 µM of rifampin (RIF), rifabutin (RFB) and rifapentine (RPT) treatment. (A) Rifampin, rifabutin, and rifapentine responsive transcripts either uniquely, combinedly, or uniformly regulated among rifamycins in PHHs are shown. (B) Heat map shows a total of 126 transcripts that are uniformly regulated among rifamycins, and transcripts were organized based on their level of mRNA expression. (C) Biological and metabolic pathways significantly (< 0.01 p value, 0.1 ratio) regulated based on a list of up regulated transcripts in response to rifampin, rifabutin, and rifapentine in PHHs as compared to controls are shown. (D) Interactive transcriptional networks of rifampin, rifabutin, and rifapentine responsive genes regulated in PHHs following drug treatments. (E) Drug metabolism networks (DMNs) of drug metabolizing enzyme (DME) transcripts specifically induced by rifampin, (F) rifabutin, and (G) rifapentine built using ingenuity pathway analysis software are shown. Red color indicates the up regulation of a transcript. Transcription factors regulating the expression of drug metabolism genes are shown in the center of the network.