Prefrontal Cortex Cytosolic Proteome and Machine Learning-Based Predictors of Resilience toward Chronic Social Isolation in Rats
Чланак у часопису (Објављена верзија)
Метаподаци
Приказ свих података о документуАпстракт
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 protei...ns 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.
Кључне речи:
chronic social isolation / machine learning algorithms / prefrontal cortex / proteomics / resilienceИзвор:
International Journal of Molecular Sciences, 2024, 25, 5, 3026-Финансирање / пројекти:
- DAAD fellowship (D.F., 2020)
- Стварање сорти топола и врба за гајење у мултифункционалним засадима (RS-MESTD-MPN2006-2010-20001)
- Министарство науке, технолошког развоја и иновација Републике Србије, институционално финансирање - 200103 (Универзитет у Београду, Електротехнички факултет) (RS-MESTD-inst-2020-200103)
DOI: 10.3390/ijms25053026
ISSN: 1422-0067
PubMed: 38474271
Scopus: 2-s2.0-85187697699
Колекције
Институција/група
VinčaTY - JOUR AU - Filipović, Dragana AU - Novak, Božidar AU - Xiao, Jinqiu AU - Tadić, Predrag AU - Turck, Christoph W. PY - 2024 UR - https://vinar.vin.bg.ac.rs/handle/123456789/13084 AB - 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. T2 - International Journal of Molecular Sciences T1 - Prefrontal Cortex Cytosolic Proteome and Machine Learning-Based Predictors of Resilience toward Chronic Social Isolation in Rats VL - 25 IS - 5 SP - 3026 DO - 10.3390/ijms25053026 ER -
@article{ author = "Filipović, Dragana and Novak, Božidar and Xiao, Jinqiu and Tadić, Predrag and Turck, Christoph W.", year = "2024", 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.", journal = "International Journal of Molecular Sciences", title = "Prefrontal Cortex Cytosolic Proteome and Machine Learning-Based Predictors of Resilience toward Chronic Social Isolation in Rats", volume = "25", number = "5", pages = "3026", doi = "10.3390/ijms25053026" }
Filipović, D., Novak, B., Xiao, J., Tadić, P.,& Turck, C. W.. (2024). Prefrontal Cortex Cytosolic Proteome and Machine Learning-Based Predictors of Resilience toward Chronic Social Isolation in Rats. in International Journal of Molecular Sciences, 25(5), 3026. https://doi.org/10.3390/ijms25053026
Filipović D, Novak B, Xiao J, Tadić P, Turck CW. Prefrontal Cortex Cytosolic Proteome and Machine Learning-Based Predictors of Resilience toward Chronic Social Isolation in Rats. in International Journal of Molecular Sciences. 2024;25(5):3026. doi:10.3390/ijms25053026 .
Filipović, Dragana, Novak, Božidar, Xiao, Jinqiu, Tadić, Predrag, Turck, Christoph W., "Prefrontal Cortex Cytosolic Proteome and Machine Learning-Based Predictors of Resilience toward Chronic Social Isolation in Rats" in International Journal of Molecular Sciences, 25, no. 5 (2024):3026, https://doi.org/10.3390/ijms25053026 . .