Gene clusters reflecting macrodomain structure respond to nucleoid perturbations

Focusing on the DNA-bridging nucleoid proteins Fis and H-NS, and integrating several independent experimental and bioinformatic data sources, we investigate the links between chromosomal spatial organization and global transcriptional regulation. By means of a novel multi-scale spatial aggregation analysis, we uncover the existence of contiguous clusters of nucleoid-perturbation sensitive genes along the genome, whose expression is affected by a combination of topological DNA state and nucleoid-shaping protein occupancy. The clusters correlate well with the macrodomain structure of the genome. The most significant of them lay symmetrically at the edges of the ter macrodomain and involve all of the flagellar and chemotaxis machinery, in addition to key regulators of biofilm formation, suggesting that the regulation of the physical state of the chromosome by the nucleoid proteins plays an important role in coordinating the transcriptional response leading to the switch between a motile and a biofilm lifestyle.Comment: Article: first 24 pages, 3 figures Supplementary methods: 1 page, 1 figure Supplementary results: 14 pages, 11 figure

Integration of benchwork, clinical trials, and real world data to investigate drug interactions

Real world data (RWD), data from various sources other than clinical trials, is increasingly being integrated into the research setting. In particular, electronic health records (EHRs), which serve as a clinical record to document a patient’s medical history as well as support administrative functions, have been an invaluable resource rich with patient data. Here we present three projects spanning four chapters where EHRs, in combination with clinical trials and pharmacokinetic and pharmacodynamic (PKPD) modelling, were used to extend and complement studies and findings in the laboratory focusing on transporter-mediated drug interactions. Transporter-mediated drug interactions have the potential to influence both drug efficacy as well as toxicity. During the clinical development of the Janus Kinase 2 (JAK2) inhibitor fedratinib, several patients developed symptoms similar to Wernicke’s encephalopathy, a life-threating disease caused by Vitamin B1 (thiamine) deficiency; subsequent in vitro studies showed that fedratinib is a potent inhibitor of ThTR-2. Motivated by this drug-nutrient interaction (DNI) observed in the fedratinib trial, we investigated if commonly used prescription drugs can inhibit ThTR-2. Using a multifaceted approach, we started with an in vitro high-throughput screen which was further complemented by quantitative structure activity relationship (QSAR) modelling and real world data. Our comprehensive analysis suggested that several marketed drugs inhibit ThTR-2 and may contribute to thiamine deficiency, especially in at-risk populations. In order to further explore the impact of these potential inhibitors in humans, we designed and conducted a clinical study in healthy volunteers. Interestingly, we observed that thiamine concentrations were higher when co-administered with trimethoprim, one of the potent, clinically relevant inhibitors identified in our screen. The maximum concentration achieved (Cmax) and area under the curve from 0 to 24 hours (AUC0-24) were 2.7- and 4.6-fold higher in the combination arm, respectively. We hypothesized that trimethoprim may inhibit OCT1, a hepatic uptake transporter, in addition to ThTR-2, which was supported using EHR data by comparing laboratory values of endogenous OCT1 biomarkers in patients prescribed trimethoprim versus patients not prescribed trimethoprim. Next, we shifted our focus to pharmacogenomics, that is, genetic factors that affect drug response. Response to allopurinol, the first line treatment for gout, is highly variable; the reduced function variant BCRP p.Q141K has been associated with poor response to allopurinol. Thus, we aimed to characterize the relationship between BCRP p.Q141K, allopurinol/oxypurinol, and serum uric acid (SUA) levels by performing a clinical trial, building a PKPD model, and mining EHRs. Our clinical study found that p.Q141K associated with longer half-life of oxypurinol and our PKPD model found that gender affected oxypurinol volume of distribution while BCRP genotype and kidney function were significant covariates for baseline SUA levels. Additionally, using RWD, we found that drugs that were clinical inhibitors of BCRP associated with increased SUA levels, suggesting the potential of these drugs to cause hyperuricemia. Finally, given the ongoing COVID19 pandemic, we conducted extensive in vitro experiments aimed at predicting the potential for 25 small molecule drugs in clinical trials for COVID19 to cause transporter-mediated drug-drug interactions (DDIs). We found that 21 of the drugs were predicted to cause a clinically relevant DDI, and we were able to provide preliminary validation of these in vitro findings using EHR data, including a database representing nearly 120,000 COVID19 patients. Collectively, my dissertation research demonstrates how the integration of benchwork, clinical trials, and real world data provides us a new approach to translational research, bridging findings from the laboratory to patients

Integration of benchwork, clinical trials, and real world data to investigate drug interactions

Real world data (RWD), data from various sources other than clinical trials, is increasingly being integrated into the research setting. In particular, electronic health records (EHRs), which serve as a clinical record to document a patient’s medical history as well as support administrative functions, have been an invaluable resource rich with patient data. Here we present three projects spanning four chapters where EHRs, in combination with clinical trials and pharmacokinetic and pharmacodynamic (PKPD) modelling, were used to extend and complement studies and findings in the laboratory focusing on transporter-mediated drug interactions. Transporter-mediated drug interactions have the potential to influence both drug efficacy as well as toxicity. During the clinical development of the Janus Kinase 2 (JAK2) inhibitor fedratinib, several patients developed symptoms similar to Wernicke’s encephalopathy, a life-threating disease caused by Vitamin B1 (thiamine) deficiency; subsequent in vitro studies showed that fedratinib is a potent inhibitor of ThTR-2. Motivated by this drug-nutrient interaction (DNI) observed in the fedratinib trial, we investigated if commonly used prescription drugs can inhibit ThTR-2. Using a multifaceted approach, we started with an in vitro high-throughput screen which was further complemented by quantitative structure activity relationship (QSAR) modelling and real world data. Our comprehensive analysis suggested that several marketed drugs inhibit ThTR-2 and may contribute to thiamine deficiency, especially in at-risk populations. In order to further explore the impact of these potential inhibitors in humans, we designed and conducted a clinical study in healthy volunteers. Interestingly, we observed that thiamine concentrations were higher when co-administered with trimethoprim, one of the potent, clinically relevant inhibitors identified in our screen. The maximum concentration achieved (Cmax) and area under the curve from 0 to 24 hours (AUC0-24) were 2.7- and 4.6-fold higher in the combination arm, respectively. We hypothesized that trimethoprim may inhibit OCT1, a hepatic uptake transporter, in addition to ThTR-2, which was supported using EHR data by comparing laboratory values of endogenous OCT1 biomarkers in patients prescribed trimethoprim versus patients not prescribed trimethoprim. Next, we shifted our focus to pharmacogenomics, that is, genetic factors that affect drug response. Response to allopurinol, the first line treatment for gout, is highly variable; the reduced function variant BCRP p.Q141K has been associated with poor response to allopurinol. Thus, we aimed to characterize the relationship between BCRP p.Q141K, allopurinol/oxypurinol, and serum uric acid (SUA) levels by performing a clinical trial, building a PKPD model, and mining EHRs. Our clinical study found that p.Q141K associated with longer half-life of oxypurinol and our PKPD model found that gender affected oxypurinol volume of distribution while BCRP genotype and kidney function were significant covariates for baseline SUA levels. Additionally, using RWD, we found that drugs that were clinical inhibitors of BCRP associated with increased SUA levels, suggesting the potential of these drugs to cause hyperuricemia. Finally, given the ongoing COVID19 pandemic, we conducted extensive in vitro experiments aimed at predicting the potential for 25 small molecule drugs in clinical trials for COVID19 to cause transporter-mediated drug-drug interactions (DDIs). We found that 21 of the drugs were predicted to cause a clinically relevant DDI, and we were able to provide preliminary validation of these in vitro findings using EHR data, including a database representing nearly 120,000 COVID19 patients. Collectively, my dissertation research demonstrates how the integration of benchwork, clinical trials, and real world data provides us a new approach to translational research, bridging findings from the laboratory to patients

Meta-Analysis of Maternal and Fetal Transcriptomic Data Elucidates the Role of Adaptive and Innate Immunity in Preterm Birth

Preterm birth (PTB) is the leading cause of newborn deaths around the world. Spontaneous preterm birth (sPTB) accounts for two-thirds of all PTBs; however, there remains an unmet need of detecting and preventing sPTB. Although the dysregulation of the immune system has been implicated in various studies, small sizes and irreproducibility of results have limited identification of its role. Here, we present a cross-study meta-analysis to evaluate genome-wide differential gene expression signals in sPTB. A comprehensive search of the NIH genomic database for studies related to sPTB with maternal whole blood samples resulted in data from three separate studies consisting of 339 samples. After aggregating and normalizing these transcriptomic datasets and performing a meta-analysis, we identified 210 genes that were differentially expressed in sPTB relative to term birth. These genes were enriched in immune-related pathways, showing upregulation of innate immunity and downregulation of adaptive immunity in women who delivered preterm. An additional analysis found several of these differentially expressed at mid-gestation, suggesting their potential to be clinically relevant biomarkers. Furthermore, a complementary analysis identified 473 genes differentially expressed in preterm cord blood samples. However, these genes demonstrated downregulation of the innate immune system, a stark contrast to findings using maternal blood samples. These immune-related findings were further confirmed by cell deconvolution as well as upstream transcription and cytokine regulation analyses. Overall, this study identified a strong immune signature related to sPTB as well as several potential biomarkers that could be translated to clinical use

Drug-nutrient interactions : discovering prescription drug inhibitors of the thiamine transporter ThTR-2 (SLC19A3)

Background: Transporter-mediated drug-nutrient interactions have the potential to cause serious adverse events. However, unlike drug-drug interactions, these drug-nutrient interactions receive little attention during drug development. The clinical importance of drug-nutrient interactions was highlighted when a phase III clinical trial was terminated due to severe adverse events resulting from potent inhibition of thiamine transporter 2 (ThTR-2: SLC19A3). Objective: In this study, we tested the hypothesis that therapeutic drugs inhibit the intestinal thiamine transporter ThTR-2, which may lead to thiamine deficiency. Methods: For this exploration, we took a multifaceted approach. starting with a high-throughput in vitro primary screen to identify inhibitors, building in silico models to characterize inhibitors, and leveraging real-world data from electronic health records to begin to understand the clinical relevance of these inhibitors. Results: Our high-throughput screen of 1360 compounds, including many clinically used drugs, identified 146 potential inhibitors at 200 mu M. Inhibition kinetics were determined for 28 drugs with half-maximal inhibitory concentration (IC50) values ranging from 1.03 mu M to >1 mM. Several oral drugs, including metformin, were predicted to have intestinal concentrations that may result in ThTR-2-mediated drug-nutrient interactions. Complementary analysis using electronic health records suggested that thiamine laboratory values are reduced in individuals receiving prescription drugs found to significantly inhibit ThTR2. particularly in vulnerable populations (e.g., individuals with alcoholism). Conclusions: Our comprehensive analysis of prescription drugs suggests that several marketed drugs inhibit ThTR-2, which may contribute to thiamine deficiency, especially in at-risk populations