The osteocyte?a dynamic and metabolically active cell?regulates numerous and diverse physiologic functions (e.g., kidney, immune system, bone turnover, and others). Discoveries regarding the osteocyte?s regulatory roles are largely fortuitous, i.e., they were identified not by a systematic screen of the osteocyte?s products/functions, but rather, by identifying a particular messenger molecule that has important effects on physiologic function, then tracing its source back to the osteocyte. This approach has yielded numerous important factors, several of which have proven to be attractive drug targets for skeletal and non-skeletal therapies. However, it is very likely that the osteocyte produces many more medically important factors than are currently known, and a systematic approach to identifying the totality of osteocyte-derived factors, in vivo (where cell culture conditions are not a factor) is long overdue. The problem with a systematic approach to quantifying the osteocyte?s in vivo proteome, both the intracellular protein pool and secreted proteins, has been the lack of biological/biochemical research tools and technical proteomics tools to successfully attempt such an endeavor, until now. We now have a genetically engineered mouse model that facilitates metabolic labeling of proteins selectively within osteocytes, using an azide-tagged synthetic amino acid? Azidonorleucine (Anl)?that substitutes for Methionine in synthesizing peptide chains, only in osteocytes. Anl is bio- orthogonal, i.e., it does not perturb the biology of proteins into which it incorporates. The physical properties of Anl exclude it from interacting with the wild-type enzyme (MetRS) that attaches (?charges?) Methionine to tRNA carriers, but expression of a mutant MetRS (MetRSL274G) promotes Anl charging to tRNA. Therefore, expression of the MetRSL274G allele selectively in osteocytes, plus dietary supplementation with Anl, allows in vivo metabolic labeling of proteins made by osteocytes. Osteocyte-generated proteins can subsequently be captured from bone tissue or serum using a ?click? chemistry reaction to efficiently select for the functional azide group, and captured proteins can be identified/quantified using state-of-the-art mass spectrometry-based proteomics. The proteomics approach proposed will facilitate unprecedented sensitivity, depth, and control for very low abundance proteins. We capitalize on these advances to, for the first time, identify and quantify the entirety of the osteocyte proteome in vivo, including the secreted portion of the osteocyte proteome?the protein secretome.
In Aim 1, procedural optimization for protein labeling and capture from bone tissue samples will be accomplished.
In Aim 2, special techniques will be employed to capture and reveal circulating factors secreted into the serum by osteocytes, including the development of novel biomarker assays.
Aim 3 (the R33 phase) will follow up on the novel protein leads generated by Aims 1 & 2, using focused animal experiments. The proposal is very risky, premature, completely novel (not a continuation of previous or published work) and based on relatively few preliminary studies; however, if successful, it will open up an enormous range of potential applications, including new drug targets, new disease biomarkers, new assays, and other tools to study not only osteocytes but also the proteome of any other cell type in vivo.
A substantial rise in musculoskeletal disorders is expected in the coming years, which underscores the need for new therapies aimed at improving skeletal health. Finding new drug targets requires a deeper understanding of the particular proteins that each skeletal cell type makes. The research plan described in this application will elucidate the protein ?portfolio,? or proteome, of an important regulatory cell type in bone (the osteocyte), which could be used to design new drugs to improve patient health.
