Benchmarking and Automating the Biotinylation Proteomics Workflow.

Protein biotinylation has been widely used in biotechnology with various labeling and enrichment strategies. However, different enrichment strategies have not been systematically evaluated due to the lack of a benchmarking model for fair comparison. Most biotinylation proteomics workflows suffer from lengthy experimental steps, non-specific bindings, limited throughput, and experimental variability. To address these challenges, we designed a two-proteome model, where biotinylated yeast proteins were spiked in unlabeled human proteins, allowing us to distinguish true enrichment from non-specific bindings. Using this benchmarking model, we compared common biotinylation proteomics methods and provided practical selection guidelines. We significantly optimized and shortened sample preparation from 3 days to 9 hours, enabling fully-automated 96-well plate sample processing. Next, we applied this optimized and automated workflow for proximity labeling to investigate the intricate interplay between mitochondria and lysosomes in living cells under both healthy state and mitochondrial damage. Our results suggested a time-dependent proteome remodeling and dynamic translocation within mitochondria and between mitochondria and lysosomes upon mitochondrial damage. This newly established benchmarking model and the fully-automated 9-hour workflow can be readily applied to the broad fields of protein biotinylation to study protein interaction and organelle dynamics.

Renal autocrine neuropeptide FF (NPFF) signaling regulates blood pressure.

The kidney and brain play critical roles in the regulation of blood pressure. Neuropeptide FF (NPFF), originally isolated from the bovine brain, has been suggested to contribute to the pathogenesis of hypertension. However, the roles of NPFF and its receptors, NPFF-R1 and NPFF-R2, in the regulation of blood pressure, via the kidney, are not known. In this study, we found that the transcripts and proteins of NPFF and its receptors, NPFF-R1 and NPFF-R2, were expressed in mouse and human renal proximal tubules (RPTs). In mouse RPT cells (RPTCs), NPFF, but not RF-amide-related peptide-2 (RFRP-2), decreased the forskolin-stimulated cAMP production in a concentration- and time-dependent manner. Furthermore, dopamine D1-like receptors colocalized and co-immunoprecipitated with NPFF-R1 and NPFF-R2 in human RPTCs. The increase in cAMP production in human RPTCs caused by fenoldopam, a D1-like receptor agonist, was attenuated by NPFF, indicating an antagonistic interaction between NPFF and D1-like receptors. The renal subcapsular infusion of NPFF in C57BL/6 mice decreased renal sodium excretion and increased blood pressure. The NPFF-mediated increase in blood pressure was prevented by RF-9, an antagonist of NPFF receptors. Taken together, our findings suggest that autocrine NPFF and its receptors in the kidney regulate blood pressure, but the mechanisms remain to be determined.

Contaminant Spot Check and Removal Assay (ContamSPOT) for Mass Spectrometry Analysis.

Mass spectrometry (MS) analysis is often challenged by contaminations from detergents, salts, and polymers that compromise data quality and can damage the chromatography and MS instruments. However, researchers often discover contamination issues only after they acquire the data. There is no existing contaminant assay that is sensitive enough to detect trace amounts of contaminants from a few microliters of samples prior to MS analysis. To address this crucial need in the field, we developed a sensitive, rapid, and cost-effective contaminant spot check and removal assay (ContamSPOT) to detect and quantify trace amounts of contaminants, such as detergents, salts, and other chemicals commonly used in the MS sample preparation workflow. Only 1 µL of the sample was used prior to MS injection to quantify contaminants by ContamSPOT colorimetric or fluorometric assay on a thin layer chromatography (TLC) plate. We also optimized contaminant removal methods to salvage samples with minimal loss when ContamSPOT showed a positive result. ContamSPOT was then successfully applied to evaluate commonly used bottom-up proteomic methods regarding the effectiveness of removing detergent, peptide recovery, reproducibility, and proteome coverage. We expect ContamSPOT to be widely adopted by MS laboratories as a last-step quality checkpoint prior to MS injection. We provided a practical decision tree and a step-by-step protocol with a troubleshooting guide to facilitate the use of ContamSPOT by other researchers. ContamSPOT can also provide a unique readout of sample cleanliness for developing new MS-based sample preparation methods in the future.