Anti-Lok (aa 115-128) polyclonal antibody

The Ste20 family of serine/threonine kinases plays an important role in numerous cellular functions such as growth, apoptosis, and morphogenesis. We have identified a previously cloned but uncharacterized family member termed Stk10, which is a human homolog of murine Lok, a serine/threonine kinase highly expressed in lymphocytes. Northern analysis demonstrated that the Stk10 transcript is present in many tissues, although highest expression levels are seen in hematopoietic cells. Due to close sequence homology to human Slk and Xenopus laevis xPlkk1, two polo-like kinase kinases, we investigated whether Stk10 might also play a role as a Plk1 activator. Plk1 has been shown to be overexpressed in multiple tumor types, thus attracting high interest to its potential upstream regulators. We show here that Stk10 can associate with Plk1 in cells and furthermore can phosphorylate Plk1 in vitro. Engineered NIH-3T3 cell lines that overexpress a dominant negative version of Stk10 display an altered cell cycle phenotype characterized by increased DNA content, raising the possibility that expression of a dominant negative Stk10 may impinge upon Plk1 function in vivo; it has previously been shown that unregulated expression of Plk1 can result in a variety of nuclear defects. We suggest, therefore, that Stk10 is a novel polo-like kinase kinase that cooperates with hSlk to regulate Plk1 function in human cells.

Background: We have recently identified a number of Quantitative Trait Loci (QTL) contributing to the 2-fold muscle weight difference between the LG/J and SM/J mouse strains and refined their confidence intervals. To facilitate nomination of the candidate genes responsible for these differences we examined the transcriptome of the tibialis anterior (TA) muscle of each strain by RNA-Seq. Results: 13,726 genes were expressed in mouse skeletal muscle. Intersection of a set of 1061 differentially expressed transcripts with a mouse muscle Bayesian Network identified a coherent set of differentially expressed genes that we term the LG/J and SM/J Regulatory Network (LSRN). The integration of the QTL, transcriptome and the network analyses identified eight key drivers of the LSRN (Kdr, Plbd1, Mgp, Fah, Prss23, 2310014F06Rik, Grtp1, Stk10) residing within five QTL regions, which were either polymorphic or differentially expressed between the two strains and are strong candidates for quantitative trait genes (QTGs) underlying muscle mass. The insight gained from network analysis including the ability to make testable predictions is illustrated by annotating the LSRN with knowledge-based signatures and showing that the SM/J state of the network corresponds to a more oxidative state. We validated this prediction by NADH tetrazolium reductase staining in the TA muscle revealing higher oxidative potential of the SM/J compared to the LG/J strain (p<0.03). Conclusion: Thus, integration of fine resolution QTL mapping, RNA-Seq transcriptome information and mouse muscle Bayesian Network analysis provides a novel and unbiased strategy for nomination of muscle QTGs.