An Escherichia coli-Based Phosphorylation System for Efficient Screening of Kinase Substrates.

Posttranslational modifications (PTMs), particularly phosphorylation, play a pivotal role in expanding the complexity of the proteome and regulating diverse cellular processes. In this study, we present an efficient Escherichia coli phosphorylation system designed to streamline the evaluation of potential substrates for Arabidopsis thaliana plant kinases, although the technology is amenable to any. The methodology involves the use of IPTG-inducible vectors for co-expressing kinases and substrates, eliminating the need for radioactive isotopes and prior protein purification. We validated the system's efficacy by assessing the phosphorylation of well-established substrates of the plant kinase SnRK1, including the rat ACETYL-COA CARBOXYLASE 1 (ACC1) and FYVE1/FREE1 proteins. The results demonstrated the specificity and reliability of the system in studying kinase-substrate interactions. Furthermore, we applied the system to investigate the phosphorylation cascade involving the A. thaliana MKK3-MPK2 kinase module. The activation of MPK2 by MKK3 was demonstrated to phosphorylate the Myelin Basic Protein (MBP), confirming the system's ability to unravel sequential enzymatic steps in phosphorylation cascades. Overall, this E. coli phosphorylation system offers a rapid, cost-effective, and reliable approach for screening potential kinase substrates, presenting a valuable tool to complement the current portfolio of molecular techniques for advancing our understanding of kinase functions and their roles in cellular signaling pathways.

Type 2 diabetes-related variants influence the risk of developing multiple myeloma: results from the IMMEnSE consortium.

Type 2 diabetes (T2D) has been suggested to be a risk factor for multiple myeloma (MM), but the relationship between the two traits is still not well understood. The aims of this study were to evaluate whether 58 genome-wide-association-studies (GWAS)-identified common variants for T2D influence the risk of developing MM and to determine whether predictive models built with these variants might help to predict the disease risk. We conducted a case-control study including 1420 MM patients and 1858 controls ascertained through the International Multiple Myeloma (IMMEnSE) consortium. Subjects carrying the KCNQ1rs2237892T allele or the CDKN2A-2Brs2383208G/G, IGF1rs35767T/T and MADDrs7944584T/T genotypes had a significantly increased risk of MM (odds ratio (OR)=1.32-2.13) whereas those carrying the KCNJ11rs5215C, KCNJ11rs5219T and THADArs7578597C alleles or the FTOrs8050136A/A and LTArs1041981C/C genotypes showed a significantly decreased risk of developing the disease (OR=0.76-0.85). Interestingly, a prediction model including those T2D-related variants associated with the risk of MM showed a significantly improved discriminatory ability to predict the disease when compared to a model without genetic information (area under the curve (AUC)=0.645 vs AUC=0.629; P=4.05×10(-) (06)). A gender-stratified analysis also revealed a significant gender effect modification for ADAM30rs2641348 and NOTCH2rs10923931 variants (Pinteraction=0.001 and 0.0004, respectively). Men carrying the ADAM30rs2641348C and NOTCH2rs10923931T alleles had a significantly decreased risk of MM whereas an opposite but not significant effect was observed in women (ORM=0.71 and ORM=0.66 vs ORW=1.22 and ORW=1.15, respectively). These results suggest that TD2-related variants may influence the risk of developing MM and their genotyping might help to improve MM risk prediction models.