Siwo Geoffrey H, Tan Asako, Button-Simons Katrina A, Samarakoon Upeka, Checkley Lisa A, Pinapati Richard S, Ferdig Michael T
Department of Biological Sciences, Eck Institute for Global Health, University of Notre Dame, Notre Dame, IN, USA.
Geisel School of Medicine, Dartmouth College, Hanover, NH, USA.
BMC Genomics. 2015 Feb 22;16(1):115. doi: 10.1186/s12864-015-1261-6.
The paradigm of resistance evolution to chemotherapeutic agents is that a key coding mutation in a specific gene drives resistance to a particular drug. In the case of resistance to the anti-malarial drug chloroquine (CQ), a specific mutation in the transporter pfcrt is associated with resistance. Here, we apply a series of analytical steps to gene expression data from our lab and leverage 3 independent datasets to identify pfcrt-interacting genes. Resulting networks provide insights into pfcrt's biological functions and regulation, as well as the divergent phenotypic effects of its allelic variants in different genetic backgrounds.
To identify pfcrt-interacting genes, we analyze pfcrt co-expression networks in 2 phenotypic states - CQ-resistant (CQR) and CQ-sensitive (CQS) recombinant progeny clones - using a computational approach that prioritizes gene interactions into functional and regulatory relationships. For both phenotypic states, pfcrt co-expressed gene sets are associated with hemoglobin metabolism, consistent with CQ's expected mode of action. To predict the drivers of co-expression divergence, we integrate topological relationships in the co-expression networks with available high confidence protein-protein interaction data. This analysis identifies 3 transcriptional regulators from the ApiAP2 family and histone acetylation as potential mediators of these divergences. We validate the predicted divergences in DNA mismatch repair and histone acetylation by measuring the effects of small molecule inhibitors in recombinant progeny clones combined with quantitative trait locus (QTL) mapping.
This work demonstrates the utility of differential co-expression viewed in a network framework to uncover functional and regulatory divergence in phenotypically distinct parasites. pfcrt-associated co-expression in the CQ resistant progeny highlights CQR-specific gene relationships and possible targeted intervention strategies. The approaches outlined here can be readily generalized to other parasite populations and drug resistances.
化疗药物耐药性演变的模式是特定基因中的关键编码突变导致对特定药物的耐药性。在抗疟药物氯喹（CQ）耐药的情况下，转运蛋白pfcrt中的特定突变与耐药性相关。在此，我们对来自我们实验室的基因表达数据应用了一系列分析步骤，并利用3个独立数据集来鉴定与pfcrt相互作用的基因。所得网络为pfcrt的生物学功能和调控以及其等位基因变体在不同遗传背景下的不同表型效应提供了见解。
为了鉴定与pfcrt相互作用的基因，我们使用一种将基因相互作用按功能和调控关系进行优先级排序的计算方法，分析了处于两种表型状态——氯喹耐药（CQR）和氯喹敏感（CQS）重组子代克隆——的pfcrt共表达网络。对于这两种表型状态，pfcrt共表达基因集都与血红蛋白代谢相关，这与CQ预期的作用模式一致。为了预测共表达差异产生的驱动因素，我们将共表达网络中的拓扑关系与现有的高可信度蛋白质-蛋白质相互作用数据相结合。该分析确定了来自ApiAP2家族的3个转录调节因子和组蛋白乙酰化是这些差异的潜在介导因素。我们通过测量小分子抑制剂在重组子代克隆中的作用并结合数量性状基因座（QTL）定位，验证了DNA错配修复和组蛋白乙酰化中预测的差异。
这项工作证明了在网络框架中观察到的差异共表达在揭示表型不同的寄生虫中功能和调控差异方面的效用。CQ耐药子代中与pfcrt相关的共表达突出了CQR特异性的基因关系和可能的靶向干预策略。这里概述的方法可以很容易地推广到其他寄生虫群体和耐药性情况。
