Discovery of hidden peptidome encoded by sORF using DDA and DIA mass spectrometry approaches

Ph.D.Proteomics has been mainly focused on the identification and quantification of proteins with higher molecular weight due to various reasons such as mass spectrometry equipment and protein database. The work in identification and quantification of small peptides is still limited. Comprehensive transcriptomics studies in various organisms have demonstrated that numerous transcripts can contain small open reading frames (sORFs, encoding peptides less than 100 amino acids). The expression levels of these transcripts could be nontrivial and there is evidence suggesting their interactions with ribosomes. However, only limited studies focus on whether these sORFs can really be translated into peptide products. The state-of-the-art mass spectrometry technology, with improved throughput, sensitivity, and resolution, has greatly promoted the research on sORF-encoded peptides (SEPs).In this project, two different data acquisition modes, the data-dependent acquisition (DDA) and the data-independent acquisition (DIA), were adopted, and a combination of two different analytical strategies, top-down and bottom-up, were used to analyze SEPs. This study mainly focused on SEPs encoded by the long non-coding RNA (lncRNA) and mRNA untranslated regions (5’UTR and 3’UTR) of soybeans under salt stress. A total of 444 SEPs were identified in this project, and 13 of them showed significant expression changes at different salt treatment time points. By comparing the identification and quantification results of DDA and DIA, DIA has many advantages over DDA, such as improved identification reproducibility and reduction of high-abundance protein identification bias, suggesting DIA may become a more promising way for future proteomics research. This project provides a solid foundation for future soybean SEP research by using the more advanced DIA strategy.一直以來，蛋白組學因為質譜設備、蛋白資料庫等各種原因，只局限於分子量較大的蛋白的鑒定和定量，而沒有在多肽的鑒定定量領域投入太多的工作量。現在隨著資訊生物學的發展，發現在生物體中許許多多轉錄的小開放閱讀框（編碼小於100個氨基酸的多肽），它們的轉錄水準很高，也有充分的證據顯示了它們於核糖體的互動，但是對於它們是否真正能夠編碼多肽卻缺少相關方面的研究。隨著質譜技術的進步，目前質譜具備了高通量，高敏感度，高解析度的優勢，這樣的質譜技術極大地促成了對於多肽的研究。在本項目中，依託於強有力的質譜儀，我採用了資料依賴型獲取和非資料依賴型獲取兩種不同模式並結合了從上致下（top-down）和從下致上（bottom-up）的兩種不同分析策略對小開放閱讀框編碼多肽進行分析。通過以上的分析模式和分析方法的組合，本研究對大豆在鹽處理下，來源於長鏈非編碼RNA和mRNA非翻譯區域的小開放閱讀框編碼多肽進行分析。在本專案中總共鑒定得到444個小開放閱讀框編碼多肽，其中有13個小開放閱讀框編碼多肽在不同的鹽處理時間點下有表達量的顯著改變。通過對比資料依賴型獲取和非資料依賴型獲取兩種不同的模式所鑒定和定量的蛋白結果，結果顯示非資料依賴型獲取模式解決了很多資料依賴型獲取的痛點，如低重複鑒定率和對於高豐度蛋白的偏向性。它相比於資料依賴型獲取模式能夠提供更高重複率且更可信的結果，或許指明了未來蛋白組學的前進的方向。本項目對於未來大豆的SEP研究奠定了堅實的基礎。Lin, Wengui.Thesis Ph.D. Chinese University of Hong Kong 2020.Includes bibliographical references (leaves 84-91).Abstracts also in Chinese.Title from PDF title page (viewed on April 21, 2022)