pFind Studio: a computational solution for mass spectrometry-based proteomics
2024
Redox Biology2024. Zhang, Yulong et al.
State Key Laboratory of Respiratory Disease, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, 510530, China
ABSTRACT:
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Molecular Cancer2024. Li, Yaming et al.
Research Institute of Breast Cancer, Shandong University, Jinan, Shandong,
ABSTRACT:Peptides and proteins encoded by noncanonical open reading frames (ORFs) of circRNAs have recently been recognized to play important roles in disease progression, but the biological functions and mechanisms of these peptides and proteins are largely unknown. Here, we identified a potential coding circular RNA, circTRIM1, that was upregulated in doxorubicin-resistant TNBC cells by intersecting transcriptome and translatome RNA-seq data, and its expression was correlated with clinicopathological characteristics and poor prognosis in patients with TNBC. CircTRIM1 possesses a functional IRES element along with an 810 nt ORF that can be translated into a novel endogenously expressed protein termed TRIM1-269aa. Functionally, we demonstrated that TRIM1-269aa, which is involved in the biological functions of circTRIM1, promoted chemoresistance and metastasis in TNBC cells both in vitro and in vivo. In addition, we found that TRIM1-269aa can be packaged into exosomes and transmitted between TNBC cells. Mechanistically, TRIM1-269aa enhanced the interaction between MARCKS and calmodulin, thus promoting the calmodulin-dependent translocation of MARCKS, which further initiated the activation of the PI3K/AKT/mTOR pathway. Overall, circTRIM1, which encodes TRIM1-269aa, promoted TNBC chemoresistance and metastasis by enhancing MARCKS translocation and PI3K/AKT/mTOR activation. Our investigation has yielded novel insights into the roles of protein-coding circRNAs and supported circTRIM1/TRIM1-269aa as a novel promising prognostic and therapeutic target for patients with TNBC.
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Frontiers in Immunology2024. Jiaru Song1 et al.
Department of Pediatrics, Peking University First Hospital, Beijing, China
ABSTRACT:
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Genomics, Proteomics & Bioinformatics2024. Chen, Yiling Elaine et al.
Department of Statistics and Data Science, University of California
ABSTRACT:
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Journal of Proteome Research2024. Shengzhi Lai et al.
Department of Electronic and Computer Engineering, The Hong Kong University of Science and Technology, Hong Kong, Hong Kong, China
ABSTRACT:Peptide identification is important in bottom-up proteomics. Post-translational modifications (PTMs) are crucial in regulating cellular activities. Many database search methods have been developed to identify peptides with PTMs and characterize the PTM patterns. However, the PTMs on peptides hinder the peptide identification rate and the PTM characterization precision, especially for peptides with multiple PTMs. To address this issue, we present a sensitive open search engine, PIPI2, with much better performance on peptides with multiple PTMs than other methods. With a greedy approach, we simplify the PTM characterization problem into a linear one, which enables characterizing multiple PTMs on one peptide. On the simulation data sets with up to four PTMs per peptide, PIPI2 identified over 90% of the spectra, at least 56% more than five other competitors. PIPI2 also characterized these PTM patterns with the highest precision of 77%, demonstrating a significant advantage in handling peptides with multiple PTMs. In the real applications, PIPI2 identified 30% to 88% more peptides with PTMs than its competitors.
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Nature Communications2024. Liu, Dan-Dan et al.
Life Sciences Institute, Department of Medical Oncology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Zhejiang University, Hangzhou, Zhejiang, 310058, China
ABSTRACT:Latent bioreactive unnatural amino acids (Uaas) have been widely used in the development of covalent drugs and identification of protein interactors, such as proteins, DNA, RNA and carbohydrates. However, it is challenging to perform high-throughput identification of Uaa cross-linking products due to the complexities of protein samples and the data analysis processes. Enrichable Uaas can effectively reduce the complexities of protein samples and simplify data analysis, but few cross-linked peptides were identified from mammalian cell samples with these Uaas. Here we develop an enrichable and multiple amino acids reactive Uaa, eFSY, and demonstrate that eFSY is MS cleavable when eFSY-Lys and eFSY-His are the cross-linking products. An identification software, AixUaa is developed to decipher eFSY mass cleavable data. We systematically identify direct interactomes of Thioredoxin 1 (Trx1) and Selenoprotein M (SELM) with eFSY and AixUaa.
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Analytical Chemistry2024. Hu, Yingwei et al.
Department of Pathology, School of Medicine, Johns Hopkins University, Baltimore, Maryland 21231, United States
ABSTRACT:Rapid development and wide adoption of mass spectrometry-based glycoproteomic technologies have empowered scientists to study proteins and protein glycosylation in complex samples on a large scale. This progress has also created unprecedented challenges for individual laboratories to store, manage, and analyze proteomic and glycoproteomic data, both in the cost for proprietary software and high-performance computing and in the long processing time that discourages on-the-fly changes of data processing settings required in explorative and discovery analysis. We developed an open-source, cloud computing-based pipeline, MS-PyCloud, with graphical user interface (GUI), for proteomic and glycoproteomic data analysis. The major components of this pipeline include data file integrity validation, MS/MS database search for spectral assignments to peptide sequences, false discovery rate estimation, protein inference, quantitation of global protein levels, and specific glycan-modified glycopeptides as well as other modification-specific peptides such as phosphorylation, acetylation, and ubiquitination. To ensure the transparency and reproducibility of data analysis, MS-PyCloud includes open-source software tools with comprehensive testing and versioning for spectrum assignments. Leveraging public cloud computing infrastructure via Amazon Web Services (AWS), MS-PyCloud scales seamlessly based on analysis demand to achieve fast and efficient performance. Application of the pipeline to the analysis of large-scale LC-MS/MS data sets demonstrated the effectiveness and high performance of MS-PyCloud. The software can be downloaded at https://github.com/huizhanglab-jhu/ms-pycloud.
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Nature Communications2024. Ann Schirin Mirsanaye et al.
Center for Chromosome Stability, Department of Cellular and Molecular Medicine, University of Copenhagen, DK-2200, Copenhagen, Denmark
ABSTRACT:The hexameric AAA+ ATPase p97/VCP functions as an essential mediator of ubiquitin-dependent cellular processes, extracting ubiquitylated proteins from macromolecular complexes or membranes by catalyzing their unfolding. p97 is directed to ubiquitylated client proteins via multiple cofactors, most of which interact with the p97 N-domain. Here, we discover that FAM104A, a protein of unknown function also named VCF1 (VCP/p97 nuclear Cofactor Family member 1), acts as a p97 cofactor in human cells. Detailed structure-function studies reveal that VCF1 directly binds p97 via a conserved alpha-helical motif that recognizes the p97 N-domain with unusually high affinity, exceeding that of other cofactors. We show that VCF1 engages in joint p97 complex formation with the heterodimeric primary p97 cofactor UFD1-NPL4 and promotes p97-UFD1-NPL4-dependent proteasomal degradation of ubiquitylated substrates in cells. Mechanistically, VCF1 indirectly stimulates UFD1-NPL4 interactions with ubiquitin conjugates via its binding to p97 but has no intrinsic affinity for ubiquitin. Collectively, our findings establish VCF1 as an unconventional p97 cofactor that promotes p97-dependent protein turnover by facilitating p97-UFD1-NPL4 recruitment to ubiquitylated targets.p97/VCP, a nexus of the ubiquitin system, recognizes and unfolds ubiquitylated substrates via multiple cofactors. Here, the authors identify VCF1, a nuclear cofactor promoting p97 recruitment to, and proteasomal degradation of, ubiquitylated targets.
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Journal of Computer and Communications2024. He, Changjiu et al.
School of Computer Science and Technology, Shandong University of Technology
ABSTRACT:
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Journal of Proteomics2024. LunfeiZou et al.
Key Laboratory of Optoelectronic Chemical Materials and Devices, Ministry of Education, School of Optoelectronic Materials & Technology, Jianghan University, Wuhan 430056, Hubei, People's Republic of China
ABSTRACT:Investigating site-specific protein phosphorylation remains a challenging task. The present study introduces a two-step chemical derivatization method for accurate identification of phosphopeptides. Methylamine neutralizes carboxyl groups, thus reducing the adsorption of non-phosphorylated peptides during enrichment, while dimethylamine offers a cost-effective reagent for stable isotope labeling of phosphorylation sites. The derivatization improves the mass spectra obtained through liquid chromatography-tandem mass spectrometry. The product ions at m/z 58.07 and 64.10 Da, resulting from dimethylamine-d0 and dimethylamine-d6 labeled phosphorylation sites respectively, can serve as report ions. Derivatized phosphopeptides from casein demonstrate enhanced ionization and formation of product ions, yielding a significant increase in the number of identifiable peptides. When using the parallel reaction monitoring technique, it is possible to distinguish isomeric phosphopeptides with the same amino acid sequence but different phosphorylation sites. By employing a proteomic software and screening the report ions, we identified 29 endogenous phosphopeptides in 10 mu L of human saliva with high reliability. These findings indicate that the two-step derivatization strategy has great potential in site-specific phosphorylation and large-scale phosphoproteomics research. Significance: There is a significant need to improve the accuracy of identifying phosphoproteins and phosphopeptides and analyzing them quantitatively. Several chemical derivatization techniques have been developed to label phosphorylation sites, thus enabling the identification and relative quantification of phosphopeptides. Nevertheless, these methods have limitations, such as incomplete conversion or the need for costly isotopic reagents. Building upon previous contributions, our study moves the field forward due to high efficiency in sitespecific labeling, cost-effectiveness, improved sensitivity, and comprehensive product ion coverage. Using the two-step derivatization approach, we successfully identified 29 endogenous phosphopeptides in 10 mu L of human saliva with high reliability. The outcomes underscore the possibility of the method for site-specific phosphorylation and large-scale phosphoproteomics investigations.
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