Profiling Analysis Reveals the Potential Contribution of Peptides to Human Adipocyte Differentiation

Peptidomics Analysis Discloses That Novel Bioactive Peptides Participate in Necrotizing Enterocolitis in a Rat Model

Necrotizing enterocolitis (NEC) is a common devastating gastrointestinal disease in premature infants, the molecular mechanisms of which have not been fully elucidated. Recently, endogenous peptides have garnered much attention owing to their role in diagnosis and treatment. However, changes in the peptide expression of NEC intestinal tissues remain poorly understood. In the present study, a comparative peptidomics profiling analysis was performed between NEC and control intestinal tissues via liquid chromatography-tandem mass spectrometry (LC-MS). In total, 103 upregulated and 73 downregulated peptides were identified in the intestinal tissues (fold change ≥ 1.5, p < 0.05). Bioinformatics analysis revealed that these differentially expressed peptides were significantly associated with NEC pathophysiology, including apoptosis, the TGF-β signaling pathway, the Wnt signaling pathway, and the MAPK signaling pathway. Furthermore, two putative peptides could inhibit apoptosis and promote the migration of intestinal epithelial cells induced by lipopolysaccharide; these peptides were derived from the protein domains MT1 and EZRI, respectively. In conclusion, our study revealed that endogenous peptides are involved in the pathophysiologic mechanism of NEC; nevertheless, further exploration is required in this regard.

Profiling Analysis Reveals the Crucial Role of the Endogenous Peptides in Bladder Cancer Progression

Background

Peptide drugs provide promising regimes in bladder cancer. In order to identify potential bioactive peptides involved in bladder cancer, we performed the present study.

Methods

Liquid chromatography/mass spectrometry assay was used to compare the endogenous peptides between bladder cancer and normal control. The potential biological functions of these dysregulated peptides are assessed by GO analysis and KEGG pathway analysis of their precursors. The SMART and UniProt databases are used to identify the sequences of the dysregulated peptides located in the functional domains. The Open Targets Platform database was used to investigate the precursors related to metabolic diseases.

Results

A total of 9 up-regulated peptides and 110 down-regulated peptides in bladder cancer compared with normal control were identified (fold change > 1.2, P < 0.05). The MW of these dysregulated peptides ranged from 500 Da to 2500 Da and the MW of all identified peptides was below 3500 Da. The GO and KEGG pathway analysis indicated that these dysregulated peptides could play an important role in bladder cancer. Our further analysis revealed that ⁴⁵HFNPRFNAHGDAN ⁵⁷ derived from LGALS1 and those peptides derived from P4HB and SERPINA1 might be the promising diagnostic biomarkers and therapeutic targets of bladder cancer.

Conclusion

In the present study, we have identified the profile of the peptides significantly dysregulated in bladder cancer. Moreover, using bioinformatic analysis, we found the peptides derived from LGALS1, P4HB and SERPINA1 could be the promising diagnostic biomarkers and therapeutic targets of bladder cancer.

Peptidomic analysis reveals multiple protection of human breast milk on infants during different stages

It has been shown that human breast milk (HBM) is an important nutrient for the growth and development of newborns. Currently, peptide drugs provide promising regimes in neonatal disease treatment, especially peptides from HBM that exhibit multiple functions within cells. To explore the potential biological function peptides among the colostrum, transition and mature milk from mother of extremely low birth weight children (the samples were collected from Women's Hospital of Nanjing Medical University from December 2016 to February 2017). A total of 3,182 nonredundant peptides were identified and compared among colostrum, transitional and mature milk using liquid chromatography/mass spectrometry technology, and the numbers and fragments of peptides were various. The isoelectric point and molecular weight analysis of the differentially expressed peptides basically accord with the range of mass spectrometry identification (<3 kDa). Gene Ontology analysis and Pathway analysis, restriction sites analysis, as well as bioinformatics analysis showed that these differentially expressed peptides enriched a variety of biological processes. We identified several putative peptides that might have bioactive effects in diseases and development of newborns, which will inform further functional investigations. Our preliminary research provided a better understanding of the function of peptides during the newborn periods. Furthermore, it laid a foundation for discovering new peptide drugs in neonatal disease treatment.

A prognostic prediction system for hepatocellular carcinoma based on gene co-expression network

In the present study, gene expression data of hepatocellular carcinoma (HCC) were analyzed by using a multi-step Bioinformatics approach to establish a novel prognostic prediction system. Gene expression profiles were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. The overlapping differentially expressed genes (DEGs) between these two datasets were identified using the limma package in R. Prognostic genes were further identified by Cox regression using the survival package. The significantly co-expressed gene pairs were selected using the R function cor to construct the co-expression network. Functional and module analyses were also performed. Next, a prognostic prediction system was established by Bayes discriminant analysis using the discriminant.bayes function in the e1071 package, which was further validated in another independent GEO dataset. A total of 177 overlapping DEGs were identified from TCGA and the GEO dataset (GSE36376). Furthermore, 161 prognostic genes were selected and the top six were stanniocalcin 2, carbonic anhydrase 12, cell division cycle (CDC) 20, deoxyribonuclease 1 like 3, glucosylceramidase β3 and metallothionein 1G. A gene co-expression network involving 41 upregulated and 52 downregulated genes was constructed. SPC24, endothelial cell specific molecule 1, CDC20, CDCA3, cyclin (CCN) E1 and chromatin licensing and DNA replication factor 1 were significantly associated with cell division, mitotic cell cycle and positive regulation of cell proliferation. CCNB1, CCNE1, CCNB2 and stratifin were clearly associated with the p53 signaling pathway. A prognostic prediction system containing 55 signature genes was established and then validated in the GEO dataset GSE20140. In conclusion, the present study identified a number of prognostic genes and established a prediction system to assess the prognosis of HCC patients.

A Comparative Peptidomic Characterization of Cultured Skeletal Muscle Tissues Derived From db/db Mice

As an important secretory organ, skeletal muscle has drawn attention as a potential target tissue for type 2 diabetic mellitus (T2DM). Recent peptidomics approaches have been applied to identify secreted peptides with potential bioactive. However, comprehensive analysis of the secreted peptides from skeletal muscle tissues of db/db mice and elucidation of their possible roles in insulin resistance remains poorly characterized. Here, we adopted a label-free discovery using liquid chromatography tandem mass spectrometry (LC-MS/MS) technology and identified 63 peptides (42 up-regulated peptides and 21 down-regulated peptides) differentially secreted from cultured skeletal muscle tissues of db/db mice. Analysis of relative molecular mass (Mr), isoelectric point (pI) and distribution of Mr vs pI of differentially secreted peptides presented the general feature. Furthermore, Gene ontology (GO) and pathway analyses for the parent proteins made a comprehensive functional assessment of these differential peptides, indicating the enrichment in glycolysis/gluconeogenesis and striated muscle contraction processes. Intercellular location analysis pointed out most precursor proteins of peptides were cytoplasmic or cytoskeletal. Additionally, cleavage site analysis revealed that Lysine (N-terminal)-Alanine (C-terminal) and Lysine (N-terminal)-Leucine (C-terminal) represents the preferred cleavage sites for identified peptides and proceeding peptides respectively. Mapped to the precursors' sequences, most identified peptides were observed cleaved from creatine kinase m-type (KCRM) and fructose-bisphosphate aldolase A (Aldo A). Based on UniProt and Pfam database for specific domain structure or motif, 44 peptides out of total were positioned in the functional motif or domain from their parent proteins. Using C2C12 myotubes as cell model in vitro, we found several candidate peptides displayed promotive or inhibitory effects on insulin and mitochondrial-related pathways by an autocrine manner. Taken together, this study will encourage us to investigate the biologic functions and the potential regulatory mechanism of these secreted peptides from skeletal muscle tissues, thus representing a promising strategy to treat insulin resistance as well as the associated metabolic disorders.