Dataset Information

Identification of Biomarkers and Therapeutic Targets Related to Sepsis-associated Encephalopathy in Rats by Quantitative Proteomics

ABSTRACT: Background: Sepsis-associated encephalopathy (SAE) is a common and severe complication of sepsis. While several studies have reported the proteomic alteration in plasma, urine, heart, etc. of sepsis, few research focused on the brain tissue. This study aims at discovering the differentially abundant proteins in the brains of septic rats to identify biomarkers of SAE. Methods: The Prague-Dawley rats were randomly divided into sepsis (n = 6) or sham (n = 6) groups, and then the whole brain tissue was dissected at 24 h after surgery for further protein identification by TMT-LC–MS/MS-based proteomics. Ingenuity pathway analysis, Gene ontology knowledgebase, and STRING database are used to explore the biological significance of proteins with altered concentration. Results: Among the total of 3163 proteins identified in the brain tissue, 57 were increased while 38 were decreased in the sepsis group compared to the sham group. Bioinformatic analyses suggest that the differentially abundant proteins are highly related to cellular microtubule metabolism, energy production, nucleic acid metabolism, neurological disease, etc. Additionally, acute phase response signaling was possibly activated and PI3K/AKT signaling was suppressed during sepsis. An interaction network established by IPA revealed that Akt1, Gc-globulin, and ApoA1 were the core proteins. The increase of Gc-globulin and the decrease of Akt1 were confirmed by Western blot. Conclusions: Based on the multifunction of these proteins in several brain diseases, we first propose that Gc-globulin, ApoA1, PI3K/AKT pathway, and acute phase response proteins (hemopexin and cluster of alpha-2-macroglobulin) can potentially be diagnosis biomarkers, therapeutic targets, and prognosis indicators of SAE. These results may provide new insights into the pathologic mechanism of SAE, yet further research is required to explore the functional implications and clinical applications of the differentially abundant proteins in the brains of sepsis group.

INSTRUMENT(S): TripleTOF 5600

ORGANISM(S): Rattus Norvegicus (rat)

TISSUE(S): Brain

DISEASE(S): Bacterial Sepsis

SUBMITTER: miaoxian yang

LAB HEAD: yang miaoxian

PROVIDER: PXD035112 | Pride | 2023-03-10

REPOSITORIES: Pride

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Identification of biomarkers and therapeutic targets related to Sepsis-associated encephalopathy in rats by quantitative proteomics.

Yang Miaoxian M He Yu Y Xin Yuewen Y Jiang Junliang J Tian Mi M Tan Jiaying J Deng Shuixiang S Gong Ye Y

BMC genomics 20230104 1

<h4>Background</h4>Sepsis-associated encephalopathy (SAE) is a common and severe complication of sepsis. While several studies have reported the proteomic alteration in plasma, urine, heart, etc. of sepsis, few research focused on the brain tissue. This study aims at discovering the differentially abundant proteins in the brains of septic rats to identify biomarkers of SAE.<h4>Methods</h4>The Prague-Dawley rats were randomly divided into sepsis (n = 6) or sham (n = 6) groups, and then the whole ...[more]

PMID: 36600206

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Project description:The study aimed to investigate the mechanisms of Jianxin (JX) granules, a Traditional Chinese Medicine formulation, in the treatment of heart failure (HF) using metabolomic profiling. The HF model was established by ligation of left coronary artery. The successfully modeled rats were randomly divided into three groups: the model group, the JX granules group, and Sacubitril/Valsartan (S/V) group. Four weeks after treatment, LV tissue samples were collected. Proteomics was used to identify the differentially expressed proteins and potential pathways. The differential expressed proteins (DEPs) were obtained with Tandem Mass Tags approach. As compared to the control group, 150 DEPs were identified in model rats, comprising 112 up-regulated and 38 down-regulated proteins. Notably, in the JX granules group, 25 DEPs were identified compared to the model rats, encompassing 18 up-regulated and 7 down-regulated proteins. In comparison with the control group, 228 DEPs in the JX granules group were obtained, which comprised of 128 up-regulated and 100 down-regulated proteins. As compared with the control group, BP in the model group was mainly enriched in humoral immune response, positive regulation of apoptotic cell clearance, and the response to metal ions; Meanwhile, CC was mainly related to contractile and stress fibers, actin filaments, and extracellular space; MF was mainly enriched in the serine-type peptidase activity, actin binding, and peptidase activity. Furthermore, DEPs indicated by KEGG analysis were primarily linked to pathways such as the complement and coagulation cascades, regulation of the actin cytoskeleton, and adrenergic signaling. In contrast to the model group, BP in JX granules group was primarily associated with processes involving nucleosome organization, chromatin assembly or disassembly, DNA conformation change and small molecule catabolic processes; CC was primarily related to the protein-DNA complex, mitochondrion, intracellular, nucleosome, cytoplasm; MF displayed significant enrichment in protein dimerization and homodimerization activity, catalase activity, chromatin and nucleosomal DNA binding. Considering KEGG enrichment information, DEPs in the JX granules group were mainly enriched in metabolic pathways and ribosome pathway. The key differential genes, such as triosephosphate isomerase 1 (TPI1), lactate dehydrogenase B (LDHB), pyruvate kinase M (PKM), protein kinase B (Akt), and lactate dehydrogenase A (LDHA) were identified. The vital pathways including carbon metabolism, the PI3K-Akt signaling pathway, pyruvate metabolism, and HIF-1α signaling pathway were obtained.

Dataset Information

Identification of Biomarkers and Therapeutic Targets Related to Sepsis-associated Encephalopathy in Rats by Quantitative Proteomics

Publications

Identification of biomarkers and therapeutic targets related to Sepsis-associated encephalopathy in rats by quantitative proteomics.

Similar Datasets

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