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Title: pLMSNOSite: an ensemble-based approach for predicting protein S-nitrosylation sites by integrating supervised word embedding and embedding from pre-trained protein language model
Protein S-nitrosylation (SNO) plays a key role in transferring nitric oxide-mediated signals in both animals and plants and has emerged as an important mechanism for regulating protein functions and cell signaling of all main classes of protein. It is involved in several biological processes including immune response, protein stability, transcription regulation, post translational regulation, DNA damage repair, redox regulation, and is an emerging paradigm of redox signaling for protection against oxidative stress. The development of robust computational tools to predict protein SNO sites would contribute to further interpretation of the pathological and physiological mechanisms of SNO.  more » « less
Award ID(s):
1901191
NSF-PAR ID:
10481200
Author(s) / Creator(s):
; ; ;
Publisher / Repository:
Springer Nature
Date Published:
Journal Name:
BMC bioinformatics
ISSN:
1471-2105
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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  1. Abstract Background

    Protein S-nitrosylation (SNO) plays a key role in transferring nitric oxide-mediated signals in both animals and plants and has emerged as an important mechanism for regulating protein functions and cell signaling of all main classes of protein. It is involved in several biological processes including immune response, protein stability, transcription regulation, post translational regulation, DNA damage repair, redox regulation, and is an emerging paradigm of redox signaling for protection against oxidative stress. The development of robust computational tools to predict protein SNO sites would contribute to further interpretation of the pathological and physiological mechanisms of SNO.

    Results

    Using an intermediate fusion-based stacked generalization approach, we integrated embeddings from supervised embedding layer and contextualized protein language model (ProtT5) and developed a tool called pLMSNOSite (protein language model-based SNO site predictor). On an independent test set of experimentally identified SNO sites, pLMSNOSite achieved values of 0.340, 0.735 and 0.773 for MCC, sensitivity and specificity respectively. These results show that pLMSNOSite performs better than the compared approaches for the prediction of S-nitrosylation sites.

    Conclusion

    Together, the experimental results suggest that pLMSNOSite achieves significant improvement in the prediction performance of S-nitrosylation sites and represents a robust computational approach for predicting protein S-nitrosylation sites. pLMSNOSite could be a useful resource for further elucidation of SNO and is publicly available athttps://github.com/KCLabMTU/pLMSNOSite.

     
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  2. Nitric oxide (NO) is a short-lived radical gas that acts as a signaling molecule in all higher organisms, and that is involved in multiple plant processes, including germination, root growth, and fertility. Regulation of NO-levels is predominantly achieved by reaction of oxidation products of NO with glutathione to form S -nitrosoglutathione (GSNO), the principal bioactive form of NO. The enzyme S -nitrosoglutathione reductase (GSNOR) is a major route of NADH-dependent GSNO catabolism and is critical to NO homeostasis. Here, we performed a proteomic analysis examining changes in the total leaf proteome of an Arabidopsis thaliana GSNOR null mutant ( hot5-2/gsnor1-3 ). Significant increases or decreases in proteins associated with chlorophyll metabolism and with redox and stress metabolism provide insight into phenotypes observed in hot5-2/gsnor1-3 plants. Importantly, we identified a significant increase in proteins that belong to the aldo-keto reductase (AKR) protein superfamily, AKR4C8 and 9. Because specific AKRs have been linked to NO metabolism in mammals, we expressed and purified A. thaliana AKR4C8 and 9 and close homologs AKR4C10 and 11 and determined that they have NADPH-dependent activity in GSNO and S -nitroso-coenzyme A (SNO-CoA) reduction. Further, we found an increase of NADPH-dependent GSNO reduction activity in hot5-2/gsnor1-3 mutant plants. These data uncover a new, NADPH-dependent component of NO metabolism that may be integrated with NADH-dependent GSNOR activity to control NO homeostasis in plants. 
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  3. Summary

    The plant hormone abscisic acid (ABA) plays crucial roles in regulation of stress responses and growth modulation. Heterotrimeric G‐proteins are key mediators of ABA responses. Both ABA and G‐proteins have also been implicated in intracellular redox regulation; however, the extent to which reversible protein oxidation manipulates ABA and/or G‐protein signaling remains uncharacterized.

    To probe the role of reversible protein oxidation in plant stress response and its dependence on G‐proteins, we determined the ABA‐dependent reversible redoxome of wild‐type and Gβ‐protein null mutantagb1of Arabidopsis.

    We quantified 6891 uniquely oxidized cysteine‐containing peptides, 923 of which show significant changes in oxidation following ABA treatment. The majority of these changes required the presence of G‐proteins. Divergent pathways including primary metabolism, reactive oxygen species response, translation and photosynthesis exhibited both ABA‐ and G‐protein‐dependent redox changes, many of which occurred on proteins not previously linked to them.

    We report the most comprehensive ABA‐dependent plant redoxome and uncover a complex network of reversible oxidations that allow ABA and G‐proteins to rapidly adjust cellular signaling to adapt to changing environments. Physiological validation of a subset of these observations suggests that functional G‐proteins are required to maintain intracellular redox homeostasis and fully execute plant stress responses.

     
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