Comprehensive Evaluation and Optimization of the Data-Dependent LC-MS/MS Workflow for Deep Proteome Profiling.

Data-dependent liquid chromatography-tandem mass spectrometry (LC-MS/MS) is widely used in proteomic analyses. A well-performed LC-MS/MS workflow, which involves multiple procedures and interdependent metrics, is a prerequisite for deep proteome profiling. Researchers have previously evaluated LC-MS/MS performance mainly based on the number of identified peptides and proteins. However, this is not a comprehensive approach. This motivates us to develop MSRefine, which aims to evaluate and optimize the performance of the LC-MS/MS workflow for data-dependent acquisition (DDA) proteomics. It extracts 47 kinds of metrics, scores the metrics, and reports visual results, assisting users in evaluating the workflow, locating problems, and providing optimizing strategies. In this study, we compared and analyzed multiple pairs of datasets spanning different samples, methods, and instruments and demonstrated that the comprehensive visual metrics and scores in MSRefine enable us to evaluate the performance of the various experiments and provide optimal strategies for the identification of more peptides and proteins.

pGlycoQuant with a deep residual network for quantitative glycoproteomics at intact glycopeptide level.

Large-scale intact glycopeptide identification has been advanced by software tools. However, tools for quantitative analysis remain lagging behind, which hinders exploring the differential site-specific glycosylation. Here, we report pGlycoQuant, a generic tool for both primary and tandem mass spectrometry-based intact glycopeptide quantitation. pGlycoQuant advances in glycopeptide matching through applying a deep learning model that reduces missing values by 19-89% compared with Byologic, MSFragger-Glyco, Skyline, and Proteome Discoverer, as well as a Match In Run algorithm for more glycopeptide coverage, greatly expanding the quantitative function of several widely used search engines, including pGlyco 2.0, pGlyco3, Byonic and MSFragger-Glyco. Further application of pGlycoQuant to the N-glycoproteomic study in three different metastatic HCC cell lines quantifies 6435 intact N-glycopeptides and, together with in vitro molecular biology experiments, illustrates site 979-core fucosylation of L1CAM as a potential regulator of HCC metastasis. We expected further applications of the freely available pGlycoQuant in glycoproteomic studies.

Proteomic and metabolomic profiling of acupuncture for migraine reveals a correlative link via energy metabolism.

Migraine is a neurovascular disease with a high disability rate. Acupuncture treatment has emerged as a safe and viable alternative prophylactic therapy that can effectively alleviate the duration and frequency of migraine attacks. However, the therapeutic mechanisms underlying the effects of acupuncture are yet to be systematically elucidated. In this study, we enrolled female patients with migraine without aura (n = 20) and healthy controls (n = 10). Patients received acupuncture treatment on DU20, DU24, bilateral GB13, GB8, and GB20, applied three times per week over the course of 4 weeks for 12 sessions in total. Blood samples were collected from the median cubital vein before and after acupuncture treatment. Proteomic and metabolomic profiling was performed using liquid chromatography-mass spectrometry to determine the characteristics of differentially expressed molecules and expression of their corresponding biological pathways as well as to elucidate the pathogenesis of migraine and the biological effects underlying the treatment of migraine with acupuncture. Proteomic and metabolomic profiling of plasma samples from patients with migraine without aura before and after acupuncture treatment revealed enrichment of immune-related pathway functions and the arginine synthesis pathway. Joint pathway analyses revealed significant enrichment of the pentose phosphate and glycolysis/gluconeogenesis pathways in patients with migraine. The glycolysis/gluconeogenesis and riboflavin metabolism pathways were significantly enriched after acupuncture treatment. The expression levels of various key proteins and metabolites, including α-D-glucose, flavin adenine dinucleotide, biliverdin reductase B, and L-glutamate, were significantly differentially expressed before and after acupuncture treatment in patients with migraine without aura. Treatment of migraine with acupuncture was associated with significant changes in key molecules and pathways, indicative of physiological changes in the trigeminovascular system, glutamate neurotoxicity, and other migraine-related physiological changes. Overall, our comprehensive analysis using proteomic and metabolomic profiling demonstrates that energy metabolism may serve as a key correlative link in the occurrence of migraine and the therapeutic effects of acupuncture treatment. Our findings may facilitate the identification of diagnostic and therapeutic modalities in the ongoing search for effective treatments for migraine attacks.

Segmented MS/MS acquisition of a1 ion-based strategy for in-depth proteome quantitation.

In-depth proteome quantitation is of great significance for understanding protein functions, advancing biological, medical, environmental and metabolic engineering research. Herein, benefiting from the high formation efficiencies and intensities of dimethyl-labeled a1 ions for accurate quantitation, we developed an in-depth a1 ion-based proteome quantitation method, named deep-APQ, by a sequential MS/MS acquisition of the high mass range for identification and the low mass range for a1 ion intensity extraction to increase quantitative protein number and sequence coverage. By the analysis of HeLa protein digests, our developed method showed deeper quantitative coverage than our previously reported a1 ion-based quantitation method without mass range segmentation and lower missing values than widely-used label-free quantitation method. It also exhibited excellent accuracy and precision within a 20-fold dynamic range. We further integrated a workflow combining the deep-APQ method with highly efficient sample preparation, high-pH and low-pH reversed-phase separation and high-field asymmetric waveform ion mobility spectrometry (FAIMS) to study E. coli proteome responses under the nutritional conditions of glucose and acetate. A total of 3447 proteins were quantified, representing 82% of protein-coding genes, with the average sequence coverage up to 40%, demonstrating the high coverage of quantitation results. We found that most of the quantified proteins related to chemotaxis were differentially expressed, including the low-abundance proteins such as tap, trg, aer, cheA and cheB, indicating that chemotaxis would play an important role for E. coli cell to survive from acetate toxicity. The above results demonstrated that the deep-APQ method is of great promising to achieve the deep-coverage proteome quantitation with high confidence.

SpotLink enables sensitive and precise identification of site nonspecific cross-links at the proteome scale.

Nonspecific cross-linker can provide distance restraints between surface residues of any type, which could be used to investigate protein structure construction and protein-protein interaction (PPI). However, the vast number of potential combinations of cross-linked residues or sites obtained with such a cross-linker makes the data challenging to analyze, especially for the proteome-wide applications. Here, we developed SpotLink software for identifying site nonspecific cross-links at the proteome scale. Contributed by the dual pointer dynamic pruning algorithm and the quality control of cross-linking sites, SpotLink identified > 3000 cross-links from human cell samples within a short period of days. We demonstrated that SpotLink outperformed other approaches in terms of sensitivity and precision on the datasets of the simulated succinimidyl 4,4'-azipentanoate dataset and the condensin complexes with known structures. In addition, some valuable PPI were discovered in the datasets of the condensin complexes and the HeLa dataset, indicating the unique identification advantages of site nonspecific cross-linking. These findings reinforce the importance of SpotLink as a fundamental characteristic of site nonspecific cross-linking technologies.

Multi-Omics and Its Clinical Application in Hepatocellular Carcinoma: Current Progress and Future Opportunities.

Hepatocellular carcinoma (HCC) is the sixth most common malignancy and the fourth leading cause of cancer related death worldwide. China covers over half of cases, leading HCC to be a vital threaten to public health. Despite advances in diagnosis and treatments, high recurrence rate remains a major obstacle in HCC management. Multi-omics currently facilitates surveillance, precise diagnosis, and personalized treatment decision making in clinical setting. Non-invasive radiomics utilizes preoperative radiological imaging to reflect subtle pixel-level pattern changes that correlate to specific clinical outcomes. Radiomics has been widely used in histopathological diagnosis prediction, treatment response evaluation, and prognosis prediction. High-throughput sequencing and gene expression profiling enabled genomics and proteomics to identify distinct transcriptomic subclasses and recurrent genetic alterations in HCC, which would reveal the complex multistep process of the pathophysiology. The accumulation of big medical data and the development of artificial intelligence techniques are providing new insights for our better understanding of the mechanism of HCC via multi-omics, and show potential to convert surgical/intervention treatment into an antitumorigenic one, which would greatly advance precision medicine in HCC management.

Identification of Protein Direct Interactome with Genetic Code Expansion and Search Engine OpenUaa.

Protein crosslinks occur endogenously such as modifications by ubiquitin-like proteins for signaling, or exogenously through genetically encoded chemical crosslinkers (GECX) for studying elusive protein-protein interactions. However, it remains challenging to identify these protein crosslinks efficiently at the proteomic scale. Herein, software OpenUaa is developed for identifying protein crosslinks generated by genetically encoded unnatural amino acids and endogenous protein conjugation. OpenUaa features inclusive and open search capability, dramatically improving identification sensitivity and coverage. Integrating GECX with OpenUaa, the direct interactome of thioredoxin is identified in Escherichia coli cells, yielding 289 crosslinked peptides and corresponding to 205 direct binding protein of thioredoxin. These identified direct binders provide evidence for thioredoxin's regulation of redox state and mitochondria energy metabolism. When identifying endogenous conjugation of small ubiquitin-like modifier (SUMO), OpenUaa also markedly improves coverage of SUMOylated peptides by ≈92%, revealing new SUMO targets. GECX-OpenUaa will enable efficient identification of direct interactomes of various proteins in live cells.

Angiotensin-Converting Enzyme Genotype-Specific Immune Response Contributes to the Susceptibility of COVID-19: A Nested Case-Control Study.

Background: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the cause of coronavirus disease 2019 (COVID-19), which has resulted in a global pandemic. Methodology: We used a two-step polymerase chain reaction to detect the ACE genotype and ELISA kits to detect the cytokine factor. We also used proteomics to identify the immune pathway related to the ACE protein expression. Result: In this study, we found that the angiotensin-converting enzyme (ACE) deletion polymorphism was associated with the susceptibility to COVID-19 in a risk-dependent manner among the Chinese population. D/D genotype distributions were higher in the COVID-19 disease group than in the control group (D/D odds ratio is 3.87 for mild (p value < 0.0001), 2.59 for moderate (p value = 0.0002), and 4.05 for severe symptoms (p value < 0.0001), logic regression analysis. Moreover, genotype-specific cytokine storms and immune responses were found enriched in patients with the ACE deletion polymorphism, suggesting the contribution to the susceptibility to COVID-19. Finally, we identified the immune pathway such as the complement system related to the ACE protein expression of patients by lung and plasma proteomics. Conclusion: Our results demonstrated that it is very important to consider gene polymorphisms in the population to discover a host-based COVID-19 vaccine and drug design for preventive and precision medicine.