PPI network identifies interacting pathogenic signaling pathways in Candida albicans†

IF 2.4 4区 生物学 Q3 BIOCHEMISTRY & MOLECULAR BIOLOGY
Molecular omics Pub Date : 2025-05-01 DOI:10.1039/D5MO00042D
Deepanjan Chattopadhyay, Sanjib Das, Paromita Saha Mondal, Tanushree Mondal, Subhasree Samanta, Amalesh Mondal, Achintya Mohan Goswami and Tanima Saha
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Abstract

Candida albicans, an opportunistic and systemic infection causing fungus, causes skin, nail, and mucosal layer lesions in healthy individuals and hospital borne catheter-related and nosocomial infections. This particular fungus exists in two distinct stages in its life cycle: yeast and hyphae. In this study, 20 signaling pathways associated with 177 proteins from C. albicans were identified to construct a PPI network. The core part of the network consisted of 165 proteins. Network topology analyses revealed that the formed PPI network is biologically robust and scale-free, with significant interactions between proteins through 19 252 shortest pathways. In this network, the top 10 hub proteins (RAS1, CDC42, HOG1, CPH1, STE11, EFG1, CEK1, HSP90, TEC1 and CST20) were identified using network analysis, which seem to be the most important proteins involved in different pathways for the development of pathogenesis and virulence. Modular analysis of the network resulted in top six sub-networks, three of which shared eight hub proteins. Ontology and functional enrichment analyses revealed that the majority of the proteins were associated with regulation of transcription by RNA polymerase II, plasma membrane and nucleic acid binding in biological processes, and cellular components and molecular functions, respectively. Enrichment analysis indicated that the proteins were mostly involved in oxidative phosphorylation and purine metabolism signaling pathways. We determined the complex web of signaling pathway involving proteins via PPI network analysis to unravel and decipher protein interactions within C. albicans to understand the complex pathogenesis processes for targeted therapeutic interferences using novel bioinformatics strategies.

Abstract Image

PPI网络识别白色念珠菌相互作用的致病信号通路。
白色念珠菌是一种引起真菌的机会性和全身性感染,可导致健康个体的皮肤、指甲和粘膜层病变以及医院传播的导管相关感染和院内感染。这种特殊的真菌在其生命周期中存在两个不同的阶段:酵母和菌丝。本研究鉴定了与177种白色念珠菌蛋白相关的20条信号通路,构建了一个PPI网络。该网络的核心部分由165个蛋白质组成。网络拓扑分析表明,形成的PPI网络具有生物鲁棒性和无标度性,蛋白质之间通过19 252条最短路径进行显著相互作用。在该网络中,通过网络分析鉴定出前10个枢纽蛋白(RAS1、CDC42、HOG1、CPH1、STE11、EFG1、CEK1、HSP90、TEC1和CST20),它们似乎是参与不同途径的发病和毒力发展的最重要的蛋白。对该网络进行模块化分析,得到前6个子网络,其中3个共享8个集线器蛋白。本体分析和功能富集分析显示,大部分蛋白分别与RNA聚合酶II转录调控、生物过程中质膜和核酸结合、细胞组分和分子功能相关。富集分析表明,这些蛋白主要参与氧化磷酸化和嘌呤代谢信号通路。我们通过PPI网络分析确定了涉及蛋白质的复杂信号通路网络,以揭示和破译白色念珠菌内蛋白质相互作用,从而利用新的生物信息学策略了解靶向治疗干扰的复杂发病过程。
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来源期刊
Molecular omics
Molecular omics Biochemistry, Genetics and Molecular Biology-Biochemistry
CiteScore
5.40
自引率
3.40%
发文量
91
期刊介绍: Molecular Omics publishes high-quality research from across the -omics sciences. Topics include, but are not limited to: -omics studies to gain mechanistic insight into biological processes – for example, determining the mode of action of a drug or the basis of a particular phenotype, such as drought tolerance -omics studies for clinical applications with validation, such as finding biomarkers for diagnostics or potential new drug targets -omics studies looking at the sub-cellular make-up of cells – for example, the subcellular localisation of certain proteins or post-translational modifications or new imaging techniques -studies presenting new methods and tools to support omics studies, including new spectroscopic/chromatographic techniques, chip-based/array technologies and new classification/data analysis techniques. New methods should be proven and demonstrate an advance in the field. Molecular Omics only accepts articles of high importance and interest that provide significant new insight into important chemical or biological problems. This could be fundamental research that significantly increases understanding or research that demonstrates clear functional benefits. Papers reporting new results that could be routinely predicted, do not show a significant improvement over known research, or are of interest only to the specialist in the area are not suitable for publication in Molecular Omics.
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