{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,22]],"date-time":"2026-10-22T21:26:13Z","timestamp":1792704373712,"version":"4.5.0"},"reference-count":42,"publisher":"The Endocrine Society","issue":"3","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2016,3,1]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Global proteomic analyses of complex protein samples in nanogram quantities require a fastidious approach to achieve in-depth protein coverage and quantitative reproducibility. Biological samples are often severely mass limited and can preclude the application of more robust bulk sample processing workflows. In this study, we present a system that minimizes sample handling by using online immobilized trypsin digestion and solid phase extraction to create a simple, sensitive, robust, and reproducible platform for the analysis of nanogram-size proteomic samples. To demonstrate the effectiveness of our simplified nanoproteomics platform, we used the system to analyze preimplantation blastocysts collected on day 4 of pregnancy by flushing the uterine horns with saline. For each of our three sample groups, blastocysts were pooled from three mice resulting in 22, 22, and 25 blastocysts, respectively. The resulting proteomic data provide novel insight into mouse blastocyst protein expression on day 4 of normal pregnancy because we characterized 348 proteins that were identified in at least two sample groups, including 59 enzymes and blastocyst specific proteins (eg, zona pellucida proteins). This technology represents an important advance in which future studies could perform global proteomic analyses of blastocysts obtained from an individual mouse, thereby enabling researchers to investigate interindividual variation as well as increase the statistical power without increasing animal numbers. This approach is also easily adaptable to other mass-limited sample types.<\/jats:p>","DOI":"10.1210\/en.2015-1821","type":"journal-article","created":{"date-parts":[[2016,1,8]],"date-time":"2016-01-08T18:01:04Z","timestamp":1452276064000},"page":"1307-1314","source":"Crossref","is-referenced-by-count":48,"title":["SNaPP: Simplified Nanoproteomics Platform for Reproducible Global Proteomic Analysis of Nanogram Protein Quantities"],"prefix":"10.1210","volume":"157","author":[{"given":"Eric L.","family":"Huang","sequence":"first","affiliation":[{"name":"Pacific Northwest National Laboratory (E.L.H., P.D.P., D.J.O., R.J.M., W.-J.Q., C.P.C., K.E.B.-J., R.D.S.), Richland, Washington 99352"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Paul D.","family":"Piehowski","sequence":"first","affiliation":[{"name":"Pacific Northwest National Laboratory (E.L.H., P.D.P., D.J.O., R.J.M., W.-J.Q., C.P.C., K.E.B.-J., R.D.S.), Richland, Washington 99352"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Daniel J.","family":"Orton","sequence":"first","affiliation":[{"name":"Pacific Northwest National Laboratory (E.L.H., P.D.P., D.J.O., R.J.M., W.-J.Q., C.P.C., K.E.B.-J., R.D.S.), Richland, Washington 99352"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ronald J.","family":"Moore","sequence":"first","affiliation":[{"name":"Pacific Northwest National Laboratory (E.L.H., P.D.P., D.J.O., R.J.M., W.-J.Q., C.P.C., K.E.B.-J., R.D.S.), Richland, Washington 99352"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wei-Jun","family":"Qian","sequence":"first","affiliation":[{"name":"Pacific Northwest National Laboratory (E.L.H., P.D.P., D.J.O., R.J.M., W.-J.Q., C.P.C., K.E.B.-J., R.D.S.), Richland, Washington 99352"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Cameron P.","family":"Casey","sequence":"first","affiliation":[{"name":"Pacific Northwest National Laboratory (E.L.H., 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