System biology approach in predictive model design for the control of Parkinsons disease and degradation of chlorpyrifos by human gut microbiome
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Chaitra N.T.
Abstract
Chlorpyrifos strikes out as an extensively utilized organophosphorus insecticide, certified for its neurotoxic properties that have been embroiled in the etiology of Parkinson’s disease, highlighting the imperativeness of constructive degradation strategies. While bioremediation approaches have been explored for the metabolism of chlorpyrifos, there remains a pronounced void in apprehending its degradation via the human gut microbiome. This study addresses this considerable shortfall by scrutinizing the degradative proficiency of Ralstonia pickettii and Escherichia coli, leveraging CellDesigner Ver. 4.4 for the development of gene-regulatory and biochemical pathways. Pathway construction was succeeded by the ascertainment of rate equation employing SBML squeezer 2.1, aiming to elucidate the biochemical and physiological metabolism of chlorpyrifos across various compartments within the human system. Experimental results demonstrated a conspicuous reduction in chlorpyrifos concentration, alongside its metabolites TCP and DETP, over time, facilitated by the action of tcpA, dhpJ, pdeA, and phoA genes derived from the microbial community. These findings stipulate that human gut microbes endow a substantial capability for the degradation of chlorpyrifos and its metabolites, thus promoting the goal of positioning the human gut microbiome as a biomarker to investigate the bioaccumulation dynamics of pesticides within the body and their potential relationship with Parkinson’s disease.
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Research ethics: No animal and human studies were used.
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Informed consent: Not applicable.
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Author contributions: CNT: Experimentation, Formulation and Designing of the experiment, Result Analysis, Interpretation of the data, Compilation of the data, Writing the manuscript, Editing. SS: Overall guidance, Conceptualization, Final editing, Formatting, Proof reading of the results and validation, Manuscript finalization and Communication.
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Use of Large Language Models, AI and Machine Learning Tools: Not applicable.
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Competing interests: No conflict of interest.
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Research funding: Not applicable.
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Data availability: No data was used for the study.
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