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      Proteomic Profiling of Emiliania huxleyi Using a Three-Dimensional Separation Method Combined with Tandem Mass Spectrometry

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          Abstract

          Emiliania huxleyi is one of the most abundant marine planktons, and it has a crucial feature in the carbon cycle. However, proteomic analyses of Emiliania huxleyi have not been done extensively. In this study, a three-dimensional liquid chromatography (3D-LC) system consisting of strong cation exchange, high- and low-pH reversed-phase liquid chromatography was established for in-depth proteomic profiling of Emiliania huxleyi. From tryptic proteome digest, 70 fractions were generated and analyzed using liquid chromatography-tandem mass spectrometry. In total, more than 84,000 unique peptides and 10,000 proteins groups were identified with a false discovery rate of ≤0.01. The physicochemical properties of the identified peptides were evaluated. Using ClueGO, approximately 700 gene ontology terms and 15 pathways were defined from the identified protein groups with p-value ≤0.05, covering a wide range of biological processes, cellular components, and molecular functions. Many biological processes associated with CO 2 fixation, photosynthesis, biosynthesis, and metabolic process were identified. Various molecular functions relating to protein binding and enzyme activities were also found. The 3D-LC strategy is a powerful approach for comparative proteomic studies on Emiliania huxleyi to reveal changes in its protein level and related mechanism.

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          Gene Ontology: tool for the unification of biology

          Genomic sequencing has made it clear that a large fraction of the genes specifying the core biological functions are shared by all eukaryotes. Knowledge of the biological role of such shared proteins in one organism can often be transferred to other organisms. The goal of the Gene Ontology Consortium is to produce a dynamic, controlled vocabulary that can be applied to all eukaryotes even as knowledge of gene and protein roles in cells is accumulating and changing. To this end, three independent ontologies accessible on the World-Wide Web (http://www.geneontology.org) are being constructed: biological process, molecular function and cellular component.
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            Stable isotope labeling by amino acids in cell culture, SILAC, as a simple and accurate approach to expression proteomics.

            Quantitative proteomics has traditionally been performed by two-dimensional gel electrophoresis, but recently, mass spectrometric methods based on stable isotope quantitation have shown great promise for the simultaneous and automated identification and quantitation of complex protein mixtures. Here we describe a method, termed SILAC, for stable isotope labeling by amino acids in cell culture, for the in vivo incorporation of specific amino acids into all mammalian proteins. Mammalian cell lines are grown in media lacking a standard essential amino acid but supplemented with a non-radioactive, isotopically labeled form of that amino acid, in this case deuterated leucine (Leu-d3). We find that growth of cells maintained in these media is no different from growth in normal media as evidenced by cell morphology, doubling time, and ability to differentiate. Complete incorporation of Leu-d3 occurred after five doublings in the cell lines and proteins studied. Protein populations from experimental and control samples are mixed directly after harvesting, and mass spectrometric identification is straightforward as every leucine-containing peptide incorporates either all normal leucine or all Leu-d3. We have applied this technique to the relative quantitation of changes in protein expression during the process of muscle cell differentiation. Proteins that were found to be up-regulated during this process include glyceraldehyde-3-phosphate dehydrogenase, fibronectin, and pyruvate kinase M2. SILAC is a simple, inexpensive, and accurate procedure that can be used as a quantitative proteomic approach in any cell culture system.
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              Empirical Statistical Model To Estimate the Accuracy of Peptide Identifications Made by MS/MS and Database Search

              We present a statistical model to estimate the accuracy of peptide assignments to tandem mass (MS/MS) spectra made by database search applications such as SEQUEST. Employing the expectation maximization algorithm, the analysis learns to distinguish correct from incorrect database search results, computing probabilities that peptide assignments to spectra are correct based upon database search scores and the number of tryptic termini of peptides. Using SEQUEST search results for spectra generated from a sample of known protein components, we demonstrate that the computed probabilities are accurate and have high power to discriminate between correctly and incorrectly assigned peptides. This analysis makes it possible to filter large volumes of MS/MS database search results with predictable false identification error rates and can serve as a common standard by which the results of different research groups are compared.
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                Author and article information

                Journal
                Molecules
                Molecules
                molecules
                Molecules
                MDPI
                1420-3049
                02 July 2020
                July 2020
                : 25
                : 13
                : 3028
                Affiliations
                [1 ]College of Pharmacy, Gachon University, Incheon 21936, Korea; ggo1203@ 123456hotmail.com (G.Y.); bio4647@ 123456naver.com (J.-M.P.); anduong@ 123456gachon.ac.kr (V.-A.D.); jeonghunmok@ 123456naver.com (J.-H.M.); jeonjh8817@ 123456naver.com (J.J.)
                [2 ]Basilbiotech, Seoul 06621, Korea
                [3 ]Department of Life Science, Hanyang University, Seoul 04763, Korea; namonew@ 123456naver.com
                [4 ]College of Letters and Science, University of California Los Angeles, Los Angeles, CA 90095, USA; joonwonlee7@ 123456gmail.com
                Author notes
                [* ]Correspondence: esjin@ 123456hanyang.ac.kr (E.J.); hklee@ 123456gachon.ac.kr (H.L.); Tel.: +82-32-820-4927 (H.L.)
                [†]

                These authors contributed equally to this work.

                Author information
                https://orcid.org/0000-0002-4407-1383
                https://orcid.org/0000-0002-4676-1804
                https://orcid.org/0000-0002-0696-8421
                Article
                molecules-25-03028
                10.3390/molecules25133028
                7411631
                32630776
                d2c185fd-80f1-460c-934a-829c24553da8
                © 2020 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 29 May 2020
                : 30 June 2020
                Categories
                Article

                emiliania huxleyi,three-dimensional (3d-lc) separation,proteomic profiling,gene ontology,photosynthesis

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