首页|University of Maryland Reports Findings in Proteome (Developmentand Validation of RoboCap, a Robotic Capillary Platform to AutomateCapillary Electrophoresis M ass Spectrometry En Route toHigh-Throughput Single-Cell Proteomics)
University of Maryland Reports Findings in Proteome (Developmentand Validation of RoboCap, a Robotic Capillary Platform to AutomateCapillary Electrophoresis M ass Spectrometry En Route toHigh-Throughput Single-Cell Proteomics)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – New research on Peptides and Proteins - Proteome is the subject of a report. Accordingto news reporting out of Colleg e Park, Maryland, by NewsRx editors, research stated, “Currentdevelopments in s ingle-cell mass spectrometry (MS) aim to deepen proteome coverage while enhancin ganalytical speed to study entire cell populations, one cell at a time. Custom- built microanalytical capillaryelectrophoresis (mCE) played a critical role in the foundation of discovery single-cell MS proteomics.”Our news journalists obtained a quote from the research from the University of M aryland, “However,requirements for manual operation, substantial expertise, and low measurement throughput have so farhindered mCE-based single-cell studies o n large numbers of cells. Here, we design and construct a roboticcapillary (Rob oCap) platform that grants single-cell CE-MS with automation for proteomes limit ed to lessthan 100 nL. RoboCap remotely controls precision actuators to transla te the sample to the fused silicaseparation capillary, using vials in this work . The platform is hermetically enclosed and actively pressurizedto inject 1-250 nL of the sample into a CE separation capillary, with errors below 5% relative standarddeviation (RSD). The platform and supporting equipment were op erated and monitored remotely on acustom-written Virtual Instrument (LabView). Detection performance was validated empirically on 5-250nL portions of the HeLa proteome digest using a trapped ion mobility mass spectrometer (timsTOF PRO).R oboCap improved CE-ESI sample utilization to 20% from 3% on the manual mCE, the closest referencetechnology. Proof-of-principle experime nts found proteome identification and quantification to robustlyreturn 1,800 pr oteins ( 13% RSD) from 20 ng of the HeLa proteome digest on this e arlier-generationdetector.”
College ParkMarylandUnited StatesN orth and CentralAmericaCapillary ElectrophoresisChromatographyEmerging Te chnologiesMachine LearningPeptidesand ProteinsProteinsProteomeProteom icsRoboticsRobots
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