Expert Review of Proteomics最新文献

{"title":"Proteomic repository data submission, dissemination, and reuse: key messages.","authors":"Yasset Perez-Riverol","doi":"10.1080/14789450.2022.2160324","DOIUrl":"10.1080/14789450.2022.2160324","url":null,"abstract":"<p><strong>Introduction: </strong>The creation of ProteomeXchange data workflows in 2012 transformed the field of proteomics, consisting of the standardization of data submission and dissemination and enabling the widespread reanalysis of public MS proteomics data worldwide. ProteomeXchange has triggered a growing trend toward public dissemination of proteomics data, facilitating the assessment, reuse, comparative analyses, and extraction of new findings from public datasets. By 2022, the consortium is integrated by PRIDE, PeptideAtlas, MassIVE, jPOST, iProX, and Panorama Public.</p><p><strong>Areas covered: </strong>Here, we review and discuss the current ecosystem of resources, guidelines, and file formats for proteomics data dissemination and reanalysis. Special attention is drawn to new exciting quantitative and post-translational modification-oriented resources. The challenges and future directions on data depositions including the lack of metadata and cloud-based and high-performance software solutions for fast and reproducible reanalysis of the available data are discussed.</p><p><strong>Expert opinion: </strong>The success of ProteomeXchange and the amount of proteomics data available in the public domain have triggered the creation and/or growth of other protein knowledgebase resources. Data reuse is a leading, active, and evolving field; supporting the creation of new formats, tools, and workflows to rediscover and reshape the public proteomics data.</p>","PeriodicalId":50463,"journal":{"name":"Expert Review of Proteomics","volume":"19 7-12","pages":"297-310"},"PeriodicalIF":3.8,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7614296/pdf/EMS159053.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9174208","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Proteomic study of mesothelial and endothelial cross-talk: key lessons.","authors":"Juan Manuel Sacnun,&nbsp;Rebecca Herzog,&nbsp;Klaus Kratochwill","doi":"10.1080/14789450.2023.2174851","DOIUrl":"https://doi.org/10.1080/14789450.2023.2174851","url":null,"abstract":"<p><strong>Introduction: </strong>The peritoneum, pleura, and pericardium are yet understudied multicellular systems where mesothelial cells (MCs) and endothelial cells (ECs) are in close proximity. Crosstalk between these cell types likely plays role in molecular transport, immunological reactions, and metabolic processes in health, disease, and therapeutic intervention.</p><p><strong>Areas covered: </strong>In this review, we discuss recent proteomic efforts to characterize the crosstalk between MC and EC. We describe the proteomic methods necessary for investigation of crosstalk between MC and EC, as well as the in-vitro models that can be employed. Potential experimental approaches range from conditioned medium, via co-culture on semi-permeable membranes, to 3D cell culture based organoid models. While the biological and clinical relevance of the models may increase with their ability to mimic close cell communication, the practicality of these complex experiments corresponds vice versa, making standardization more difficult and expensive.</p><p><strong>Expert opinion: </strong>Currently, data and reports on mesothelial-to-endothelial crosstalk are still very scarce. In our opinion, the in-vitro model using semi-permeable cell culture inserts will allow to establish a basic understanding of cellular crosstalk that may occur between those cell types. Later-on, more sophisticated 3D cell cultures may be better able to simulate the transport dynamics within the peritoneal membrane.</p>","PeriodicalId":50463,"journal":{"name":"Expert Review of Proteomics","volume":"19 7-12","pages":"289-296"},"PeriodicalIF":3.4,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9488427","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Rebellion of the deregulated regulators: What is the clinical relevance of studying intrinsically disordered proteins?","authors":"Vladimir N Uversky","doi":"10.1080/14789450.2023.2176755","DOIUrl":"https://doi.org/10.1080/14789450.2023.2176755","url":null,"abstract":"Since at the molecular level, almost all physiological processes are defined by the specific activities of specific proteins or protein groups, dysfunction and deregulation of these proteins are linked to the pathogenesis of various maladies. Therefore, to get to the roots of the pathological processes and find appropriate cure for the related diseases, one should clearly know the connections between protein-centric physiology and pathology. This logic represents premises of the medical protein science, where one is looking for the connections between the ‘right’ protein structure and normal function to understand how dysfunction can be linked back to the ‘wrong’ structure and assuming that fixing such ‘wrong’ structure can serve as a means to restore a normal function and therefore cure a disease. Even though mutations in a gene encoding a culprit protein represent the major reason for this protein to gain ‘wrong’ structure, dysfunctionality can also be caused by the distortion of any means from a very broad arsenal of cellular proteostasis-related mechanisms evolved to control and regulate protein folding, structure, and function. Although for the first time, proteins were described by the Dutch chemist Gerardus Johannes Mulder (1802–1880) as enormous molecules, with empirical formula for fibrin and egg albumin being C400H620N100O120P1S1, in his 1838 paper ‘On the composition of some animal substances’ first published in French [1] and translated to German in 1839 [2], they gained serious attention of researchers only after their polypeptide nature discovered independently in 1902 by a German chemist Hermann Emil Louis Fischer (1852–1919) [3] and an early protein scientist Franz Hofmeister (1850–1922) [4] was connected to the enzymatic activity by an American chemist, James B. Sumner (1887–1955), who, in 1926, showed that the enzyme urease is a protein that can be isolated and crystallized [5]. Curiously, as early as in 1894, enzymatic activity was proposed by Emil Fischer to follow his classical ‘lock-and-key’ model [6]. This concept was eventually elaborated into the famous protein structure-function paradigm, where the amino acid sequence determines a uniquely folded 3D structure that can be visualized in the crystalline state and that, in turn, defines the unique protein function [7]. As a result, in most of the almost 185 years of their history (and definitely since 1894), proteins were equated to enzymes, being considered as biological catalysts, while many other functions of these biological macromolecules and their intriguing potential to be multifunctional were mostly ignored.","PeriodicalId":50463,"journal":{"name":"Expert Review of Proteomics","volume":"19 7-12","pages":"279-282"},"PeriodicalIF":3.4,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9120103","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Advances in phosphoproteomics and its application to COPD.","authors":"Xiaoyin Zeng,&nbsp;Yanting Lan,&nbsp;Jing Xiao,&nbsp;Longbo Hu,&nbsp;Long Tan,&nbsp;Mengdi Liang,&nbsp;Xufei Wang,&nbsp;Shaohua Lu,&nbsp;Tao Peng,&nbsp;Fei Long","doi":"10.1080/14789450.2023.2176756","DOIUrl":"https://doi.org/10.1080/14789450.2023.2176756","url":null,"abstract":"<p><strong>Introduction: </strong>Chronic obstructive pulmonary disease (COPD) was the third leading cause of global death in 2019, causing a huge economic burden to society. Therefore, it is urgent to identify specific phenotypes of COPD patients through early detection, and to promptly treat exacerbations. The field of phosphoproteomics has been a massive advancement, compelled by the developments in mass spectrometry, enrichment strategies, algorithms, and tools. Modern mass spectrometry-based phosphoproteomics allows understanding of disease pathobiology, biomarker discovery, and predicting new therapeutic modalities.</p><p><strong>Areas covered: </strong>In this article, we present an overview of phosphoproteomic research and strategies for enrichment and fractionation of phosphopeptides, identification of phosphorylation sites, chromatographic separation and mass spectrometry detection strategies, and the potential application of phosphorylated proteomic analysis in the diagnosis, treatment, and prognosis of COPD disease.</p><p><strong>Expert opinion: </strong>The role of phosphoproteomics in COPD is critical for understanding disease pathobiology, identifying potential biomarkers, and predicting new therapeutic approaches. However, the complexity of COPD requires the more comprehensive understanding that can be achieved through integrated multi-omics studies. Phosphoproteomics, as a part of these multi-omics approaches, can provide valuable insights into the underlying mechanisms of COPD.</p>","PeriodicalId":50463,"journal":{"name":"Expert Review of Proteomics","volume":"19 7-12","pages":"311-324"},"PeriodicalIF":3.4,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9118955","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Oncoproteomic profiling of AML: moving beyond genomics.","authors":"Sunil K Joshi,&nbsp;Cristina E Tognon,&nbsp;Brian J Druker,&nbsp;Karin D Rodland","doi":"10.1080/14789450.2023.2176757","DOIUrl":"https://doi.org/10.1080/14789450.2023.2176757","url":null,"abstract":"Much of what is known about protein-signaling networks in cancer, or ‘oncoproteomics,’ has been indirectly derived from transcriptomic analyses[1],[2]. However, RNA regulation precludes a one-to-one correlation of mRNA abundance to protein abundance or activity. A corollary of this is that evaluation of RNA by itself is insufficient to fully appreciate pathogenic cellular signaling within the tumor ecosystem. Global proteomics and phosphoproteomics have emerged as powerful unbiased methodologies for detailing fundamental signaling networks of cancer cells and perturbations that sustain resistance against targeted therapies, contributing to the discovery of new therapeutic targets[3]. Similar to other cancers, the utility of mass spectrometrybased technologies has augmented our ability to categorize the underlying heterogeneity in acute myeloid leukemia (AML) – expanding our capacity to classify AML beyond genomic features alone. Efforts over the past decade have resulted in the creation of new datasets that have begun to characterize the AML proteome and phosphoproteome. A subset of these studies have been exploratory in nature [4–9] – leading to the generation of new hypotheses, while others have focused on examining particular aspects of a disease state (e.g. drug resistance) to identify new biomarkers. These data provide a rich resource for further investigations aimed at mapping the ‘post-genomic’ landscape of AML (Table 1). Within this editorial, we discuss how integration and aggregation of such data with our current understanding of the AML genome and transcriptome holds the promise of refining our classification of leukemia cells – the genotype and phenotype – and yielding mechanistic insights that can inform the generation of improved therapeutic combinations. Casado et al. profiled the proteome and phosphoproteome of primary AML cells from 30 patients and the aggregation of these datasets with corresponding genomic, immunophenotypic, and pharmacologic analyses was among the first studies to infer that cell differentiation state influences kinase signaling changes and drug sensitivity profiles[4]. The authors also showed that FLT3 mutation status alone was insufficient to predict response to the FDA-approved inhibitor midostaurin and that increased activation of PKCδ and GSK3A in AML cells, as revealed by phosphoproteomics, correlated with midostaurin response[4]. Early attempts to integrate proteomic, genomic, and/or transcriptomic datasets have expanded our ability to categorize the small sub-populations of leukemic stem cells (LSCs) that govern the underlying heterogeneity and complexity of AML[5] and our understanding of the nuclear proteome in the pathogenesis of AML[6]. More recently, Jayavelu et al. identified five AML subtypes with distinct biological features via proteomic characterization of 252 AML patient samples[7]. Integration of these data with corresponding genomic, cytogenetic, and transcriptomic analyses revealed that t","PeriodicalId":50463,"journal":{"name":"Expert Review of Proteomics","volume":"19 7-12","pages":"283-287"},"PeriodicalIF":3.4,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10505090/pdf/nihms-1931031.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10298600","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"13^th annual symposium of the Canadian National Proteomics Network.","authors":"Jennifer Geddes-McAlister,&nbsp;David C Schriemer","doi":"10.1080/14789450.2022.2158815","DOIUrl":"https://doi.org/10.1080/14789450.2022.2158815","url":null,"abstract":"<p><p>The 13^th annual Canadian National Proteomics Network was held in May 2022 in Montreal, Quebec, Canada. More than 175 individuals participated in this dynamic and productive meeting either in-person or virtually. A pre-symposium organized by trainees and dedicated to highlighting the best and brightest emerging talent in proteomics across Canada preceded the main symposium, which welcomed plenary and invited speakers from around the world. The presentations covering ground-breaking science were interspersed with critical discussions on improving equity, diversity, and inclusion within the proteomics community across Canada, along with important networking opportunities for early-career researchers.</p>","PeriodicalId":50463,"journal":{"name":"Expert Review of Proteomics","volume":"19 4-6","pages":"231-233"},"PeriodicalIF":3.4,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9365891","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Can spatially resolved metabolomics uncover weak points in tumors?","authors":"Zhen Ning,&nbsp;Guowang Xu","doi":"10.1080/14789450.2023.2176754","DOIUrl":"https://doi.org/10.1080/14789450.2023.2176754","url":null,"abstract":"The complexity and diversity derived from genetics and evolution lead to tumor heterogeneity. The spatial and temporal evolution of tumor heterogeneity during tumor development results in the dynamic reprogramming of the tumor microenvironment (TME) [1]. Over the last decade, technological developments from bulk genome to single-cell sequencing have provided us with ever-more powerful tool to investigate what happens in TME [2]. Since reprogrammed energy metabolism is one of the hallmarks of cancer, metabolomics may provide a new direction for shedding light on the interactions between small molecules (mainly molecules with molecular weight less than 2000 Da) and other biomolecules in tumors. However, traditional metabolomics cannot give spatiallyrelated information unless combined with spatially resolved sampling, but revealing the metabolic reprogramming characteristics of TME and clarifying the targeting heterogeneity of antitumor drugs rely on the spatial information of metabolites or small molecule drugs. Thus, the advent of spatial metabolomics provides an opportunity to detect molecular localization based on the relative abundance of molecules and to directly correlate changes in small molecules with anatomical features. In other words, spatial metabolomics is oriented to reveal the spatial distribution and variation of metabolites [3]. Most of spatially resolved metabolomics combine ionization techniques with label-free, high-throughput mass spectrometry imaging (MSI) to obtain information on the spatial distribution of metabolites. In addition, laser capture microdissection technique combined with mass spectrometry detection is also one of the research directions in spatial metabolomics, it can select the area of interest for detailed study. Developments in MSI now make it possible to directly observe metabolic changes in tissues, even in single cells. To date, most spatial metabolomics techniques are based on matrix-assisted laser desorption ionization mass spectrometry imaging (MALDI-MSI) or desorption electrospray ionization mass spectrometry imaging (DESI-MSI), both of which are constantly being improved [4]. In recent years, spatially resolved metabolomics has reaped a series of groundbreaking insights in the fields of metabolic heterogeneity of tumors, rapid diagnosis (including tumor boundary determination), metabolic typing, targeting efficiency of antitumor drugs, and efficacy assessment by obtaining information on the distribution of metabolites and smallmolecule drugs in TME (Figure 1). The development of spatially resolved metabolomics technologies will help open the black box of TME and provide new opportunities for precision treatment of tumors.","PeriodicalId":50463,"journal":{"name":"Expert Review of Proteomics","volume":"19 4-6","pages":"227-230"},"PeriodicalIF":3.4,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9383269","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Proteomics and phosphoproteomics analysis of tissues for the reoccurrence prediction of colorectal cancer.","authors":"Liyun Ji,&nbsp;Zeyuan Wang,&nbsp;Yin Ji,&nbsp;Huiyu Wang,&nbsp;Miao Guo,&nbsp;Lu Zhang,&nbsp;Peng Wang,&nbsp;Hua Xiao","doi":"10.1080/14789450.2022.2142566","DOIUrl":"https://doi.org/10.1080/14789450.2022.2142566","url":null,"abstract":"<p><strong>Background: </strong>Many stage II/III colorectal cancer (CRC) patients may relapse after routine treatments. Aberrant phosphorylation can regulate pathophysiological processes of tumors, and finding characteristic protein phosphorylation is an efficient approach for the prediction of CRC relapse.</p><p><strong>Research design and methods: </strong>We compared the tissue proteome and phosphoproteome of stage II/III CRC patients between the relapsed group (n = 5) and the non-relapsed group (n = 5). Phosphopeptides were enriched with Ti⁴⁺-IMAC material. We utilized label-free quantification-based proteomics to screen differentially expressed proteins and phosphopeptides between the two groups. Gene Ontology (GO) analysis and Ingenuity Pathway Analysis (IPA) were used for bioinformatics analysis.</p><p><strong>Results: </strong>The immune response of the relapsed group (Z-score -2.229) was relatively poorer than that of the non-relapsed group (Z-score 1.982), while viability of tumor was more activated (Z-score 2.895) in the relapsed group, which might cause increased relapse risk. The phosphorylation degrees of three phosphosites (phosphosite 1362 of TP53BP1, phosphosite 809 of VCL and phosphosite 438 of STK10) might be reliable prognostic biomarkers.</p><p><strong>Conclusions: </strong>Some promising proteins and phosphopeptides were discovered to predict the relapse risk in postoperative follow-ups.</p>","PeriodicalId":50463,"journal":{"name":"Expert Review of Proteomics","volume":"19 4-6","pages":"263-277"},"PeriodicalIF":3.4,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10808081","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The role of E3 ubiquitin ligase in multiple myeloma: potential for cereblon E3 ligase modulators in the treatment of relapsed/refractory disease.","authors":"Paul G Richardson,&nbsp;María-Victoria Mateos,&nbsp;Annette J Vangsted,&nbsp;Karthik Ramasamy,&nbsp;Niels Abildgaard,&nbsp;P Joy Ho,&nbsp;Hang Quach,&nbsp;Nizar J Bahlis","doi":"10.1080/14789450.2022.2142564","DOIUrl":"https://doi.org/10.1080/14789450.2022.2142564","url":null,"abstract":"<p><strong>Introduction: </strong>Insights into the mechanisms of protein homeostasis and proteasomal degradation have led to new strategies of redirecting the ubiquitin-proteasome system (UPS) to reduce or eliminate proteins or survival factors key to malignant pathobiology, multiple myeloma (MM) in particular. These strategies have enabled researchers to target proteins that were previously considered difficult to modulate by pharmacological means.</p><p><strong>Areas covered: </strong>This review provides a brief overview of UPS biology, particularly the role of the CRL4^CRBN E3 ubiquitin ligase complex, and summarizes current strategies for co-opting the UPS, including CELMoD compounds, SNIPERs, PROTACs, and degronimids. A detailed discussion is provided on lead CELMoD compounds iberdomide and mezigdomide, which are currently being evaluated in clinical trials in patients with MM.</p><p><strong>Expert opinion: </strong>Since a high proportion of patients develop drug resistance, it is vital to have novel therapeutic agents for treating relapsed patients with MM more effectively. It is encouraging that the expanding pathophysiological insight into cellular signaling pathways in MM increasingly translates into the development of novel therapeutic agents such as targeted protein degraders. This holds promise for improving outcomes in MM and beyond.</p>","PeriodicalId":50463,"journal":{"name":"Expert Review of Proteomics","volume":"19 4-6","pages":"235-246"},"PeriodicalIF":3.4,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10808088","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Schistosome proteomics: updates and clinical implications.","authors":"William Castro-Borges,&nbsp;R Alan Wilson","doi":"10.1080/14789450.2022.2142565","DOIUrl":"https://doi.org/10.1080/14789450.2022.2142565","url":null,"abstract":"<p><strong>Introduction: </strong>Schistosomes are long-lived blood dwelling helminth parasites using intricate mechanisms to invade, mature, and reproduce inside their vertebrate hosts, whilst simultaneously deploying immune evasion strategies. Their multi-tissue organization and solid body plan presents particular problems for the definition of sub-proteomes.</p><p><strong>Areas covered: </strong>Here, we focus on the two host-parasite interfaces of the adult worm accessible to the immune system, namely the tegument and the alimentary tract, but also on the secretions of the infective cercaria, the migrating schistosomulum and the mature egg. In parallel, we introduce the concepts of \"leakyome' and 'disintegrome' to emphasize the importance of interpreting data in the context of schistosome biology so that misleading conclusions about the distinct proteome compositions are avoided. Lastly, we highlight the possible clinical implications of the reviewed proteomic findings for pathogenesis, vaccine design and diagnostics.</p><p><strong>Expert opinion: </strong>Proteomics has provided considerable insights into the biology of schistosomes, most importantly for rational selection of novel vaccine candidates that might confer protective immunity, but also into the pathogenesis of schistosomiasis. However, given the increasing sensitivity of mass spectrometric instrumentation, we stress the need for care in data interpretation since schistosomes do not deviate from the fundamental rules of eukaryotic cell biology.</p>","PeriodicalId":50463,"journal":{"name":"Expert Review of Proteomics","volume":"19 4-6","pages":"247-261"},"PeriodicalIF":3.4,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10826585","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}