Zhang Bailu, Feng Shichao, Parajuli Manushi, Xiong Yi, Pan Chongle, Guo Xuan
Department of Computer Science and Engineering, University of North Texas, Denton, TX 76207, USA.
School of Biological Sciences, University of Oklahoma, Norman, OK 73019, USA.
Bioinform Res Appl. 2024 Jul;14956:102-115. doi: 10.1007/978-981-97-5087-0_9. Epub 2024 Jul 12.
Metaproteomics, utilizing high-throughput LC-MS, offers a profound understanding of microbial communities. Quantitative metaproteomics further enriches this understanding by measuring relative protein abundance and revealing dynamic changes under different conditions. However, the challenge of missing peptide quantification persists in metaproteomics analysis, particularly in data-dependent acquisition mode, where high-intensity precursors for MS2 scans are selected. To tackle this issue, the match-between-runs (MBR) technique is used to transfer peptides between LC-MS runs. Inspired by the benefits of MBR and the need for streamlined metaproteomics data analysis, we developed SEMQuant, an end-to-end software integrating Sipros-Ensemble's robust peptide identifications with IonQuant's MBR function. The experiments show that SEMQuant consistently obtains the highest or second highest number of quantified proteins with notable precision and accuracy. This demonstrates SEMQuant's effectiveness in conducting comprehensive and accurate quantitative metaproteomics analyses across diverse datasets and highlights its potential to propel advancements in microbial community studies. SEMQuant is freely available under the GNU GPL license at https://github.com/Biocomputing-Research-Group/SEMQuant.
宏蛋白质组学利用高通量液相色谱-质谱联用技术，能够深入了解微生物群落。定量宏蛋白质组学通过测量相对蛋白质丰度并揭示不同条件下的动态变化，进一步丰富了这种认识。然而，在宏蛋白质组学分析中，尤其是在数据依赖采集模式下（即选择用于二级质谱扫描的高强度前体离子），缺失肽段定量的挑战依然存在。为解决这一问题，运行间匹配（MBR）技术被用于在液相色谱-质谱联用的不同运行之间转移肽段。受MBR技术优势以及简化宏蛋白质组学数据分析需求的启发，我们开发了SEMQuant，这是一款端到端的软件，它将Sipros-Ensemble强大的肽段鉴定功能与IonQuant的MBR功能整合在一起。实验表明，SEMQuant始终能以显著的精密度和准确度获得最高或第二高数量的定量蛋白质。这证明了SEMQuant在对各种数据集进行全面且准确的定量宏蛋白质组学分析方面的有效性，并突出了其在推动微生物群落研究进展方面的潜力。SEMQuant可在https://github.com/Biocomputing-Research-Group/SEMQuant上根据GNU GPL许可免费获取。
