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  Prefrontal Cortex Cytosolic Proteome and Machine Learning-Based Predictors of Resilience toward Chronic Social Isolation in Rats

Filipovic, D., Novak, B., Xiao, J., Tadic, P., & Turck, C. W. (2024). Prefrontal Cortex Cytosolic Proteome and Machine Learning-Based Predictors of Resilience toward Chronic Social Isolation in Rats. INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES, 25(5): 3026. doi:10.3390/ijms25053026.

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 Creators:
Filipovic, Dragana, Author
Novak, Bozidar1, Author           
Xiao, Jinqiu, Author
Tadic, Predrag, Author
Turck, Christoph W.1, Author           
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1RG Proteomics and Biomarkers, Max Planck Institute of Psychiatry, Max Planck Society, ou_2040287              

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 Abstract: Chronic social isolation (CSIS) generates two stress-related phenotypes: resilience and susceptibility. However, the molecular mechanisms underlying CSIS resilience remain unclear. We identified altered proteome components and biochemical pathways and processes in the prefrontal cortex cytosolic fraction in CSIS-resilient rats compared to CSIS-susceptible and control rats using liquid chromatography coupled with tandem mass spectrometry followed by label-free quantification and STRING bioinformatics. A sucrose preference test was performed to distinguish rat phenotypes. Potential predictive proteins discriminating between the CSIS-resilient and CSIS-susceptible groups were identified using machine learning (ML) algorithms: support vector machine-based sequential feature selection and random forest-based feature importance scores. Predominantly, decreased levels of some glycolytic enzymes, G protein-coupled receptor proteins, the Ras subfamily of GTPases proteins, and antioxidant proteins were found in the CSIS-resilient vs. CSIS-susceptible groups. Altered levels of Gapdh, microtubular, cytoskeletal, and calcium-binding proteins were identified between the two phenotypes. Increased levels of proteins involved in GABA synthesis, the proteasome system, nitrogen metabolism, and chaperone-mediated protein folding were identified. Predictive proteins make CSIS-resilient vs. CSIS-susceptible groups linearly separable, whereby a 100% validation accuracy was achieved by ML models. The overall ratio of significantly up- and downregulated cytosolic proteins suggests adaptive cellular alterations as part of the stress-coping process specific for the CSIS-resilient phenotype.

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 Dates: 2024
 Publication Status: Published online
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 Rev. Type: -
 Identifiers: ISI: 001182683500001
DOI: 10.3390/ijms25053026
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Title: INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
Source Genre: Journal
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Pages: - Volume / Issue: 25 (5) Sequence Number: 3026 Start / End Page: - Identifier: ISSN: 1661-6596