Proteomic analysis of the colistin-resistant E. coli clinical isolate: Explorations of the resistome

2021 ◽  
Vol 28 ◽  
Author(s):  
Divakar Sharma ◽  
Manisha Aswal ◽  
Nayeem Ahmad ◽  
Manish Kumar ◽  
Asad U Khan
Keyword(s):  
Clinical Isolate ◽  
Protein Interaction ◽  
Functional Annotation ◽  
Drug Targets ◽  
Bacterial Infections ◽  
Sugar Metabolism ◽  
Colistin Resistance ◽  
Phosphotransferase System ◽  
E Coli ◽  
Protein Protein Interaction

Background: Antimicrobial resistance is a worldwide problem after the emergence of colistin resistance since it was the last option left to treat carbapenemase-resistant bacterial infections. The mcr gene and its variants are one of the causes for colistin resistance. Besides mcr genes, some other intrinsic genes are also involved in colistin resistance but still need to be explored. Objective: The aim of this study was to investigate differential proteins expression of colistin-resistant E. coli clinical isolate and to understand their interactive partners as future drug targets. Methods: In this study, we have employed the whole proteome analysis through LC-MS/MS. The advance proteomics tools were used to find differentially expressed proteins in the colistin-resistant Escherichia coli clinical isolate compared to susceptible isolate. Gene ontology and STRING were used for functional annotation and protein-protein interaction networks, respectively. Results: LC-MS/MS analysis showed overexpression of 47 proteins and underexpression of 74 proteins in colistin-resistant E. coli. These proteins belong to DNA replication, transcription and translational process; defense and stress related proteins; proteins of phosphoenol pyruvate phosphotransferase system (PTS) and sugar metabolism. Functional annotation and protein-protein interaction showed translational and cellular metabolic process, sugar metabolism and metabolite interconversion. Conclusion: We conclude that these protein targets and their pathways might be used to develop novel therapeutics against colistin-resistant infections. These proteins could unveil the mechanism of colistin resistance.

scholarly journals Development of a Novel High-Throughput Screen and Identification of Small-Molecule Inhibitors of the Gα–RGS17 Protein–Protein Interaction Using AlphaScreen

2011 ◽  
Vol 16 (8) ◽  
pp. 869-877 ◽  
Author(s):  
Duncan I. Mackie ◽  
David L. Roman
Keyword(s):  
Small Molecule ◽  
High Throughput ◽  
Protein Interaction ◽  
High Throughput Screening ◽  
Drug Targets ◽  
Screening Method ◽  
Fold Increase ◽  
Rgs Proteins ◽  
High Throughput Screen ◽  
Protein Protein Interaction

In this study, the authors used AlphaScreen technology to develop a high-throughput screening method for interrogating small-molecule libraries for inhibitors of the Gαo–RGS17 interaction. RGS17 is implicated in the growth, proliferation, metastasis, and the migration of prostate and lung cancers. RGS17 is upregulated in lung and prostate tumors up to a 13-fold increase over patient-matched normal tissues. Studies show RGS17 knockdown inhibits colony formation and decreases tumorigenesis in nude mice. The screen in this study uses a measurement of the Gαo–RGS17 protein–protein interaction, with an excellent Z score exceeding 0.73, a signal-to-noise ratio >70, and a screening time of 1100 compounds per hour. The authors screened the NCI Diversity Set II and determined 35 initial hits, of which 16 were confirmed after screening against controls. The 16 compounds exhibited IC50 <10 µM in dose–response experiments. Four exhibited IC50 values <6 µM while inhibiting the Gαo–RGS17 interaction >50% when compared to a biotinylated glutathione-S-transferase control. This report describes the first high-throughput screen for RGS17 inhibitors, as well as a novel paradigm adaptable to many other RGS proteins, which are emerging as attractive drug targets for modulating G-protein-coupled receptor signaling.

scholarly journals Analysis of Protein-Protein Interaction Network of Laminopathy Based on Topological Properties

2018 ◽  
Vol 11 (2) ◽  
pp. 1091-1103
Author(s):  
Sapana Singh Yadav ◽  
Usha Chouhan
Keyword(s):  
Protein Interaction ◽  
Protein Interaction Network ◽  
Drug Targets ◽  
Genetic Disorders ◽  
Seed Proteins ◽  
Interaction Network ◽  
Large Degree ◽  
Closeness Centrality ◽  
Ppi Network ◽  
Protein Protein Interaction

Laminopathy is a group of rare genetic disorders, including EDMD, HGPS, Leukodystrophy and Lipodystrophy, caused by mutations in genes, encoding proteins of the nuclear lamina. Analysis of protein interaction network in the cell can be the key to understand; how complex processes, lead to diseases. Protein-protein interaction (PPI) in network analysis provides the possibility to quantify the hub proteins in large networks as well as their interacting partners. A comprehensive genes/proteins dataset related to Laminopathy is created by analysing public proteomic data and text mining of scientific literature. From this dataset the associated PPI network is acquired to understand the relationships between topology and functionality of the PPI network. The extended network of seed proteins including one giant network consisted of 381 nodes connected via 1594 edges (Fusion) and 390 nodes connected via 1645 edges (Coexpression), targeted for analysis. 20 proteins with high BC and large degree have been identified. LMNB1 and LMNA with highest BC and Closeness centrality located in the centre of the network. The backbone network derived from giant network with high BC proteins presents a clear and visual overview which shows all important proteins of Laminopathy and the crosstalk between them. Finally, the robustness of central proteins and accuracy of backbone are validated by 248 test networks. Based on the network topological parameters such as degree, closeness centrality, betweenness centrality we found out that integrated PPIN is centred on LMNB1 and LMNA. Although finding of other interacting partners strongly represented as novel drug targets for Laminopathy.

scholarly journals Colistin-resistant Escherichia coli clinical isolate harbouring the mcr-1 gene in Ecuador

2016 ◽  
Vol 144 (14) ◽  
pp. 2967-2970 ◽  
Author(s):  
D. ORTEGA-PAREDES ◽  
P. BARBA ◽  
J. ZURITA
Keyword(s):  
Escherichia Coli ◽  
Minimum Inhibitory Concentration ◽  
Clinical Isolate ◽  
Inhibitory Concentration ◽  
Resistance Mechanism ◽  
Sequence Type ◽  
Colistin Resistance ◽  
Gram Negative ◽  
E Coli ◽  
Commensal Strain

SUMMARYColistin resistance mediated by the mcr-1 gene has been reported worldwide, but to date not from the Andean region, South America. We report the first clinical isolate of Escherichia coli harbouring the mcr-1 gene in Ecuador. The strain was isolated from peritoneal fluid from a 14-year-old male with acute appendicitis, and subjected to molecular analysis. The minimum inhibitory concentration of colistin for the strain was 8 mg/ml and it was susceptible to carbapenems but resistant to tigecycline. The strain harboured mcr-1 and blaCTX-M-55 genes and was of sequence type 609. The recognition of an apparently commensal strain of E. coli harbouring mcr-1 serves as an alert to the presence in the region of this recently described resistance mechanism to one of the last line of drugs available for the treatment of multi-resistant Gram-negative infections.

CORRELATION BETWEEN FUNCTIONAL ANNOTATION AND TOPOLOGY OF PROTEIN-PROTEIN INTERACTION NETWORK

2008 ◽  
Vol 22 (06) ◽  
pp. 719-726 ◽  
Author(s):  
JIUN-YAN HUANG
Keyword(s):  
Protein Interaction ◽  
Protein Interaction Network ◽  
Protein Function ◽  
Functional Annotation ◽  
Interaction Network ◽  
Protein Interaction Data ◽  
Characteristic Distance ◽  
Protein Protein Interaction ◽  
Functional Correlation ◽  
Protein Protein Interaction Network

The functional annotation of proteins was believed to be related to the topology of the protein-protein interaction network. People utilized the protein-protein interaction network to infer the protein function by various methods. Here, we select the protein interaction data of Saccharomyces cerevisia and calculated the correlation between functional annotation of proteins and the topology of protein-protein interaction network. The result shows that the functional correlation decays exponentially with the distance between two proteins, and beyond the characteristic distance, it has no correlation.

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