Comparative evaluation of label-free quantification strategies

Translation of the downstream ORF from bicistronic mRNAs by human cells: Impact of codon usage and splicing in the upstream ORF

Biochemistry textbooks describe eukaryotic mRNAs as monocistronic. However, increasing evidence reveals the widespread presence and translation of upstream open reading frames preceding the "main" ORF. DNA and RNA viruses infecting eukaryotes often produce polycistronic mRNAs and viruses have evolved multiple ways of manipulating the host's translation machinery. Here, we introduce an experimental model to study gene expression regulation from virus-like bicistronic mRNAs in human cells. The model consists of a short upstream ORF and a reporter downstream ORF encoding a fluorescent protein. We have engineered synonymous variants of the upstream ORF to explore large parameter space, including codon usage preferences, mRNA folding features, and splicing propensity. We show that human translation machinery can translate the downstream ORF from bicistronic mRNAs, albeit reporter protein levels are thousand times lower than those from the upstream ORF. Furthermore, synonymous recoding of the upstream ORF exclusively during elongation significantly influences its own translation efficiency, reveals cryptic splice signals, and modulates the probability of downstream ORF translation. Our results are consistent with a leaky scanning mechanism facilitating downstream ORF translation from bicistronic mRNAs in human cells, offering new insights into the role of upstream ORFs in translation regulation.

Protein Sample Preparation for Bottom-Up, Label-Free Quantitative Proteomics of Adipose Tissue

Adipose tissue (AT) is a complex, multifunctional endocrine organ that plays a significant role in animal evolution and human disease. Profiling of the proteome, or the set of proteins produced by a cell or tissue at a given time, can be used to explore the myriad functions of adipose tissue and understand its role in health and disease. The main challenges of adipose tissue proteomics include the high lipid and low protein content of the tissue and association of many proteins with lipid droplets. Here, we present a protocol for gel-free, label-free, bottom-up, relative quantitative proteomics of adipose tissue based on findings from the literature and our laboratory that yields reproducible protein and peptide identification rates while minimizing cost and processing time. This approach involves tissue homogenization, protein precipitation from homogenates, solubilization and denaturation of proteins in a buffer containing 5% sodium deoxycholate (SDC, an acid-insoluble detergent) and 5 mM tris(2-carboxyethyl)phosphine (TCEP, a reducing agent), alkylation with chloroacetamide, and in-solution tandem digestion with trypsin and Lys-C enzymes in the presence of 1% SDC. Acidification of peptides efficiently removes SDC prior to desalting and mass spectrometry. This method has been used successfully in our laboratory by both experienced researchers and those with limited technical backgrounds, including high school, undergraduate, and graduate students. We have identified >1500 proteins in adipose tissue of non-model mammals (e.g., blubber of marine mammals) spanning a dynamic range of 105 using this approach, including proteins of interest for comparative physiology such as adipokines, metabolic and antioxidant enzymes, lipid droplet proteins, metabolite transporters, and mitochondrial proteins, among others.

Challenges of MS-based small extracellular vesicles proteomics

Proteomic profiling of small extracellular vesicles (sEV) is a powerful tool for discovering biomarkers of various diseases. This process most often assisted by mass spectrometry (MS) usually lacks standardization and recognition of challenges which may lead to unreliable results. General recommendations for sEV MS analyses have been briefly given in the MISEV2023 guidelines. The present work goes into detail for every step of sEV protein profiling with an overview of factors influencing such analyses. This includes reporting and defining the sEV source and vesicle isolation, protein solubilization and digestion, 'offline' and 'online' sample complexity reduction, the analysis type itself, and subsequent data analysis. Every stage in this process affects the others, which could result in different outcomes. Although characterization and comparisons of different sEV isolation methods are known and accessible and MS-based profiling details are provided for cell or tissue samples, no consensus work has been ever published to describe the whole process of sEV proteomic analysis. Reliable results can be obtained from sEV profiling provided that the analysis is well planned, prepared for, and backed by pilot studies or appropriate research.

Endothelial cell Ass1 inhibits arteriosclerotic calcification in diabetes mellitus

Endothelial cell (EC) dysfunction is an important pathological feature of early calcification in diabetic plaques. Argininosuccinic synthase 1 (Ass1) is important in protecting EC activity. Therefore, this study aimed to explore the effect of endothelial Ass1 on calcification in diabetic plaques and its potential regulatory mechanism. In this study, serum Ass1 levels were measured in 84 patients, and the study showed that the serum Ass1 level in patients with diabetes was significantly decreased compared with the non-diabetic group, and the serum Ass1 level in patients with coronary artery calcification was significantly decreased compared with the non-coronary artery calcification group. The ApoE-/- mouse diabetic plaque calcification model and the mouse aortic endothelial cell (MAEC) calcification model were constructed, and the influence of endothelial cell Ass1 on diabetic plaque calcification was further investigated by adeno-associated virus and plasmid intervention. Molecular biology studies have shown that endothelial Ass1 overexpression can reduce plaque calcification and inhibit MAEC osteogenic differentiation in diabetic mice, and Ass1 has protective effects on EC and blood vessels in mice. 4D-label-free proteomic sequencing, bioinformatics analysis, and IP experiments were performed on ApoE-/- mouse aorta after adeno-associated virus intervention. It was found that the differential protein Ptk2b was closely related to vascular calcification (VC) and interacted with the target protein Ass1. The above studies indicate that endothelial Ass1 affects calcification formation in diabetic plaques, and the mechanism may be related to Ptk2b. Ass1 may be a new target for the treatment of diabetic VC.

Lysine lactylation-based insight to understanding the characterization of cervical cancer

Lysine lactylation (Kla), a recently discovered post-translational modification (PTM), is not only present in histone proteins but also widely distributed among non-histone proteins in tumor cells and immunocytes. However, the precise characterization and functional implications of these non-histone Kla proteins remain to be explored. Herein, a comprehensive proteomic analysis of Kla was conducted in HeLa cells. As a result, a total of 3633 Kla sites on 1637 proteins were identified. Subsequently, the stable Kla substrates were obtained and sorted to investigate the characterization and function of Kla proteins. Moreover, we characterized the Kla-related features of cervical cancers through integrative analyses of multiple datasets with proteomes, transcriptomes and single-cell transcriptome profiling. Kla-related genes (KRGs) were used to stratify cervical cancers into two clusters (C1 and C2). C2 cluster display inhibition in glycosylation and increased oxidative phosphorylation activity with high survival rate. In addition, we constructed a prognostic model based on two lactate signature genes, namely ISY1 and PPP1R14B. Interestingly, our findings revealed a negative correlation between PPP1R14B expression and the infiltration of CD8+ T cells, as well as a lower survival rate. This observation was further validated at the single-cell resolution. Simultaneously, we found that K140R mutant of PPP1R14B resulted in the decrease of Kla level and enhanced the proliferation and migration capabilities of cervical cancer cell lines, suggesting PPP1R14B-K140la has an effect on tumor behaviors. Collectively, we provides a Kla-based insight to understanding the characterization of cervical cancer, offering a potential avenue for therapeutic approaches.

Proteomes of plasmodium knowlesi early and late ring-stage parasites and infected host erythrocytes

The emerging malaria parasite Plasmodium knowlesi threatens the goal of worldwide malaria elimination due to its zoonotic spread in Southeast Asia. After brief ex-vivo culture we used 2D LC/MS/MS to examine the early and late ring stages of infected Macaca mulatta red blood cells harboring P. knowlesi. The M. mulatta clathrin heavy chain and T-cell and macrophage inhibitor ERMAP were overexpressed in the early ring stage; glutaredoxin 3 was overexpressed in the late ring stage; GO term differential enrichments included response to oxidative stress and the cortical cytoskeleton in the early ring stage. P. knowlesi clathrin heavy chain and 60S acidic ribosomal protein P2 were overexpressed in the late ring stage; GO term differential enrichments included vacuoles in the early ring stage, ribosomes and translation in the late ring stage, and Golgi- and COPI-coated vesicles, proteasomes, nucleosomes, vacuoles, ion-, peptide-, protein-, nucleocytoplasmic- and RNA-transport, antioxidant activity and glycolysis in both stages. SIGNIFICANCE: Due to its zoonotic spread, cases of the emerging human pathogen Plasmodium knowlesi in southeast Asia, and particularly in Malaysia, threaten regional and worldwide goals for malaria elimination. Infection by this parasite can be fatal to humans, and can be associated with significant morbidity. Due to zoonotic transmission from large macaque reservoirs that are untreatable by drugs, and outdoor biting mosquito vectors that negate use of preventive measures such as bed nets, its containment remains a challenge. Its biology remains incompletely understood. Thus we examine the expressed proteome of the early and late ex-vivo cultured ring stages, the first intraerythrocyte developmental stages after infection of host rhesus macaque erythrocytes. We used GO term enrichment strategies and differential protein expression to compare early and late ring stages. The early ring stage is characterized by the enrichment of P. knowlesi vacuoles, and overexpression of the M. mulatta clathrin heavy chain, important for clathrin-coated pits and vesicles, and clathrin-mediated endocytosis. The M. mulatta protein ERMAP was also overexpressed in the early ring stage, suggesting a potential role in early ring stage inhibition of T-cells and macrophages responding to P. knowlesi infection of reticulocytes. This could allow expansion of the host P. knowlesi cellular niche, allowing parasite adaptation to invasion of a wider age range of RBCs than the preferred young RBCs or reticulocytes, resulting in proliferation and increased pathogenesis in infected humans. Other GO terms differentially enriched in the early ring stage include the M. mulatta cortical cytoskeleton and response to oxidative stress. The late ring stage is characterized by overexpression of the P. knowlesi clathrin heavy chain. Combined with late ring stage GO term enrichment of Golgi-associated and coated vesicles, and enrichment of COPI-coated vesicles in both stages, this suggests the importance to P. knowlesi biology of clathrin-mediated endocytosis. P. knowlesi ribosomes and translation were also differentially enriched in the late ring stage. With expression of a variety of heat shock proteins, these results suggest production of folded parasite proteins is increasing by the late ring stage. M. mulatta endocytosis was differentially enriched in the late ring stage, as were clathrin-coated vesicles and endocytic vesicles. This suggests that M. mulatta clathrin-based endocytosis, perhaps in infected reticulocytes rather than mature RBC, may be an important process in the late ring stage. Additional ring stage biology from enriched GO terms includes M. mulatta proteasomes, protein folding and the chaperonin-containing T complex, actin and cortical actin cytoskeletons. P knowlesi biology also includes proteasomes, as well as nucleosomes, antioxidant activity, a variety of transport processes, glycolysis, vacuoles and protein folding. Mature RBCs have lost internal organelles, suggesting infection here may involve immature reticulocytes still retaining organelles. P. knowlesi parasite proteasomes and translational machinery may be ring stage drug targets for known selective inhibitors of these processes in other Plasmodium species. To our knowledge this is the first examination of more than one timepoint within the ring stage. Our results expand knowledge of both host and parasite proteins, pathways and organelles underlying P. knowlesi ring stage biology.

A Mass Spectrometry Strategy for Protein Quantification Based on the Differential Alkylation of Cysteines Using Iodoacetamide and Acrylamide

Mass spectrometry has become the most prominent yet evolving technology in quantitative proteomics. Today, a number of label-free and label-based approaches are available for the relative and absolute quantification of proteins and peptides. However, the label-based methods rely solely on the employment of stable isotopes, which are expensive and often limited in availability. Here we propose a label-based quantification strategy, where the mass difference is identified by the differential alkylation of cysteines using iodoacetamide and acrylamide. The alkylation reactions were performed under identical experimental conditions; therefore, the method can be easily integrated into standard proteomic workflows. Using high-resolution mass spectrometry, the feasibility of this approach was assessed with a set of tryptic peptides of human serum albumin. Several critical questions, such as the efficiency of labeling and the effect of the differential alkylation on the peptide retention and fragmentation, were addressed. The concentration of the quality control samples calculated against the calibration curves were within the ±20% acceptance range. It was also demonstrated that heavy labeled peptides exhibit a similar extraction recovery and matrix effect to light ones. Consequently, the approach presented here may be a viable and cost-effective alternative of stable isotope labeling strategies for the quantification of cysteine-containing proteins.

Label-free based quantitative proteomics analysis to explore the molecular mechanism of gynecological cold coagulation and blood stasis syndrome

Cold coagulation and blood stasis (CCBS) syndrome is one of the common traditional Chinese medicine (TCM) syndromes of gynecological diseases. However, the molecular mechanism of CCBS syndrome is still unclear. Thus, there is a need to reveal the occurrence and regulation mechanism of CCBS syndrome, in order to provide a theoretical basis for the treatment of CCBS syndrome in gynecological diseases. The plasma proteins in primary dysmenorrhea (PD) patients with CCBS syndrome, endometriosis (EMS) patients with CCBS syndrome, and healthy women were screened using Label-free quantitative proteomics. Based on the TCM theory of "same TCM syndrome in different diseases," the differentially expressed proteins (DEPs) identified in each group were subjected to intersection mapping to obtain common DEPs in CCBS syndrome. The DEPs of gynecological CCBS syndrome in the intersection part were again cross-mapped with the DEPs of gynecological CCBS syndrome obtained by the research group according to the TCM theory of "different TCM syndromes in same disease" theory in the early stage, so as to obtain the DEPs of gynecological CCBS syndrome that were shared by the two parts. The common DEPs were subjected to bioinformatics analysis, and were verified by enzyme-linked immunosorbent assay (ELISA). A total of 67 common DEPs were identified in CCBS syndrome, of which 33 DEPs were upregulated and 34 DEPs were downregulated. The functional classification of DEPs involved in metabolic process, energy production and conversion, immune system process, antioxidant activity, response to stimulus, and biological adhesion. The subcellular location mainly located in the cytoplasm, nucleus, and extracellular. Gene ontology (GO) enrichment analysis showed that the upregulated DEPs mainly concentrated in lipid transport, cell migration, and inflammatory reaction, and the downregulated DEPs mostly related to cell junction, metabolism, and energy response. Protein domain enrichment analysis and clustering analysis revealed that the DEPs mainly related to cell proliferation and differentiation, cell morphology, metabolism, and immunity. The Kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment analysis clustering analysis showed that the upregulated DEPs were involved in inflammation and oxidative damage, while the downregulated DEPs were involved in inflammation, cell adhesion, cell apoptosis, and metabolism. The results of ELISA showed significantly increased levels of Cell surface glycoprotein MUC18 (MCAM) and Apolipoprotein C1 (APOC1), and significantly decreased levels of Vasodilator-stimulated phosphoprotein (VASP), Fatty acid-binding protein 5 (FABP5), and Vinculin (VCL) in patients with CCBS syndrome compared with healthy women. We speculated that cold evil may affect the immune process, inflammatory response, metabolic process, energy production and conversion, oxidative damage, endothelial cell dysfunction, and other differential proteins expression to cause CCBS syndrome in gynecological diseases.

Egg protein profile and dynamics during embryogenesis in Haemaphysalis flava ticks

Tick eggs contain all essential proteins for embryogenesis, and egg proteins are a potential reservoir of tick-protective antigens. However, the protein profile and dynamics during embryonic development remain unknown. This study aimed to depict the protein profile and dynamics in tick embryogenesis, further providing protein candidates for targeted interventions. Eggs from Haemaphysalis flava ticks were incubated at 28 °C and 85% relative humidity. On days 0 (newly laid eggs without incubation), 7, 14 and 21, eggs were collected, dewaxed and subject to protein extraction. Extracted proteins were digested by filter-aided sample preparation and analyzed by liquid chromatography-tandem mass spectrometry (LC/MS-MS). MS data were searched against an in-house H. flava protein database for tick-derived protein identification. Abundances of 40 selected high-confidence proteins were further quantified by LC-parallel reaction monitoring (PRM)/MS analysis throughout egg incubation. A total of 93 high-confidence proteins were identified in eggs on 0-day incubation. Identified proteins belonged to seven functional categories: transporters, enzymes, proteinase inhibitors, immunity-related proteins, cytoskeletal proteins, heat shock proteins and uncharacterized proteins. The enzyme category contained the most types of proteins. Neutrophil elastase inhibitors represented the most abundant proteins in terms of intensity-based absolute-protein-quantification. LC-PRM/MS revealed that the abundances of 20 proteins increased including enolase, calreticulin, actin, GAPDH et cetera, and the abundances of 11 proteins decreased including vitellogenins, neutrophil elastase inhibitor, carboxypeptidase Q, et cetera from 0- to 21-day incubation. This study provides the most comprehensive egg protein profile and dynamics during tick embryogenesis. Further investigations are needed to test the tick-control efficacy by targeting the egg proteins.

Plasma extracellular vesicle proteins as promising noninvasive biomarkers for diagnosis of idiopathic pulmonary fibrosis

High-resolution computed tomography (HRCT) imaging is critical for diagnostic evaluation of Idiopathic Pulmonary Fibrosis (IPF). However, several other interstitial lung diseases (ILDs) often exhibit radiologic pattern similar to IPF on HRCT making the diagnosis of the disease difficult. Therefore, biomarkers that distinguish IPF from other ILDs can be a valuable aid in diagnosis. Using mass spectrometry, we performed proteomic analysis of plasma extracellular vesicles (EVs) in patients diagnosed with IPF, chronic hypersensitivity pneumonitis, nonspecific interstitial pneumonitis, and healthy subjects. A five-protein signature was identified by lasso regression and was validated in an independent cohort using ELISA. The five-protein signature derived from mass spectrometry data showed an area under the receiver operating characteristic curve of 0.915 (95%CI: 0.819-1.011) and 0.958 (95%CI: 0.882-1.034) for differentiating IPF from other ILDs and from healthy subjects, respectively. Stepwise backwards elimination yielded a model with 3 and 2 proteins for discriminating IPF from other ILDs and healthy subjects, respectively, without compromising diagnostic accuracy. In summary, we discovered and validated EV protein biomarkers for differential diagnosis of IPF in independent cohorts. Interestingly, the biomarker panel could also distinguish IPF and healthy subjects with high accuracy. The biomarkers need to be evaluated in large prospective cohorts to establish their clinical utility.

Protein biomarkers for radiation injury and testing of medical countermeasure efficacy: promises, pitfalls, and future directions

INTRODUCTION

Radiological/nuclear accidents, hostile military activity, or terrorist strikes have the potential to expose a large number of civilians and military personnel to high doses of radiation resulting in the development of acute radiation syndrome and delayed effects of exposure. Thus, there is an urgent need for sensitive and specific assays to assess the levels of radiation exposure to individuals. Such radiation exposures are expected to alter primary cellular proteomic processes, resulting in multifaceted biological responses.

AREAS COVERED

This article covers the application of proteomics, a promising and fast developing technology based on quantitative and qualitative measurements of protein molecules for possible rapid measurement of radiation exposure levels. Recent advancements in high-resolution chromatography, mass spectrometry, high-throughput, and bioinformatics have resulted in comprehensive (relative quantitation) and precise (absolute quantitation) approaches for the discovery and accuracy of key protein biomarkers of radiation exposure. Such proteome biomarkers might prove useful for assessing radiation exposure levels as well as for extrapolating the pharmaceutical dose of countermeasures for humans based on efficacy data generated using animal models.

EXPERT OPINION

The field of proteomics promises to be a valuable asset in evaluating levels of radiation exposure and characterizing radiation injury biomarkers.

Comparative proteomic analysis of glomerular proteins in IgA nephropathy and IgA vasculitis with nephritis

BACKGROUND

IgA nephropathy (IgAN) and IgA vasculitis with nephritis (IgAVN) are related glomerular diseases characterized by marked similarities in immunological and histological findings. We herein performed a comparative proteomic analysis of glomerular proteins in IgAN and IgAVN.

METHODS

We used renal biopsy specimens from 6 IgAN patients without nephrotic syndrome (NS) (IgAN-I subgroup), 6 IgAN patients with NS (IgAN-II subgroup), 6 IgAVN patients with 0-8.0% of glomeruli with crescent formation (IgAVN-I subgroup), 6 IgAVN patients with 21.2-44.8% of glomeruli with crescent formation (IgAVN-II subgroup), 9 IgAVN patients without NS (IgAVN-III subgroup), 3 IgAVN patients with NS (IgAN-IV subgroup), and 5 control cases. Proteins were extracted from laser microdissected glomeruli and analyzed using mass spectrometry. The relative abundance of proteins was compared between groups. An immunohistochemical validation study was also performed.

RESULTS

More than 850 proteins with high confidence were identified. A principal component analysis revealed a clear separation between IgAN and IgAVN patients and control cases. In further analyses, 546 proteins that were matched with ≥ 2 peptides were selected. The levels of immunoglobulins (IgA, IgG, and IgM), complements (C3, C4A, C5, and C9), complement factor H-related proteins (CFHR) 1 and 5, vitronectin, fibrinogen chains, and transforming growth factor-β inducible gene-h3 were higher (> 2.6 fold) in the IgAN and IgAVN subgroups than in the control group, whereas hornerin levels were lower (< 0.3 fold). Furthermore, C9 and CFHR1 levels were significantly higher in the IgAN group than in the IgAVN group. The abundance of some podocyte-associated proteins and glomerular basement membrane (GBM) proteins was significantly less in the IgAN-II subgroup than in the IgAN-I subgroup as well as in the IgAVN-IV subgroup than in the IgAVN-III subgroup. Among the IgAN and IgAVN subgroups, talin 1 was not detected in the IgAN-II subgroup. This result was supported by immunohistochemical findings.

CONCLUSIONS

The present results suggest shared molecular mechanisms for glomerular injury in IgAN and IgAVN, except for enhanced glomerular complement activation in IgAN. Differences in the protein abundance of podocyte-associated and GBM proteins between IgAN and IgAVN patients with and without NS may be associated with the severity of proteinuria.

Phosphoproteomic Approaches for Identifying Phosphatase and Kinase Substrates

Protein phosphorylation is a ubiquitous post-translational modification controlled by the opposing activities of protein kinases and phosphatases, which regulate diverse biological processes in all kingdoms of life. One of the key challenges to a complete understanding of phosphoregulatory networks is the unambiguous identification of kinase and phosphatase substrates. Liquid chromatography-coupled mass spectrometry (LC-MS/MS) and associated phosphoproteomic tools enable global surveys of phosphoproteome changes in response to signaling events or perturbation of phosphoregulatory network components. Despite the power of LC-MS/MS, it is still challenging to directly link kinases and phosphatases to specific substrate phosphorylation sites in many experiments. Here, we survey common LC-MS/MS-based phosphoproteomic workflows for identifying protein kinase and phosphatase substrates, noting key advantages and limitations of each. We conclude by discussing the value of inducible degradation technologies coupled with phosphoproteomics as a new approach that overcomes some limitations of current methods for substrate identification of kinases, phosphatases, and other regulatory enzymes.

Urinary protein biomarkers based on LC-MS/MS analysis to discriminate vascular dementia from Alzheimer's disease in Han Chinese population

Objective

This study aimed to identify the potential urine biomarkers of vascular dementia (VD) and unravel the disease-associated mechanisms by applying Liquid chromatography tandem-mass spectrometry (LC-MS/MS).

Methods

LC-MS/MS proteomic analysis was applied to urine samples from 3 groups, including 14 patients with VD, 9 patients with AD, and 21 normal controls (NC). By searching the MS data by Proteome Discoverer software, analyzing the protein abundances qualitatively and quantitatively, comparing between groups, combining bioinformatics analysis using Gene Ontology (GO) and pathway crosstalk analysis using Kyoto Encyclopedia of Genes and Genomes (KEGG), and literature searching, the differentially expressed proteins (DEPs) of VD can be comprehensively determined at last and were further quantified by receiver operating characteristic (ROC) curve methods.

Results

The proteomic findings showed quantitative changes in patients with VD compared to patients with NC and AD groups; among 4,699 identified urine proteins, 939 and 1,147 proteins displayed quantitative changes unique to VD vs. NC and AD, respectively, including 484 overlapped common DEPs. Then, 10 unique proteins named in KEGG database (including PLOD3, SDCBP, SRC, GPRC5B, TSG101/STP22/VPS23, THY1/CD90, PLCD, CDH16, NARS/asnS, AGRN) were confirmed by a ROC curve method.

Conclusion

Our results suggested that urine proteins enable detection of VD from AD and VC, which may provide an opportunity for intervention.

Discovering Protein-Protein Interactions using Co-Fractionation-Mass Spectrometry with Label-Free Quantitation

Proteins generally achieve their functions through interactions with other proteins, so being able to determine which proteins interact with which other proteins underlies much of molecular biology. Co-fractionation (CF) is a mass spectrometry-based method for detecting proteome-wide protein-protein interactions. An attractive feature of CF is that it is not necessary to label or otherwise alter samples. Although we have previously published a widely used protocol for a label-incorporated CF methodology, no published protocols currently exist for the label-free variation. In this chapter, we describe a label-free CF-MS protocol. This protocol takes a minimum of a week, excluding the time for cell/tissue culture. It begins with cell/tissue lysis under non-denaturing conditions, after which intact protein complexes are isolated using size exclusion chromatography (SEC) where they are fractionated according to size. The proteins in each fraction are then prepared for mass spectrometry analysis where the constituent proteins are identified and quantified. Finally, we describe an in-house bioinformatics pipeline, PrInCE, to accurately predict protein complexes. Taken together, co-fractionation methodologies combined with mass spectrometry can identify and quantify thousands of protein-protein interactions in biological systems.

Functional Diversity and Evolution of the Drosophila Sperm Proteome

Spermatozoa are central to fertilization and the evolutionary fitness of sexually reproducing organisms. As such, a deeper understanding of sperm proteomes (and associated reproductive tissues) has proven critical to the advancement of the fields of sexual selection and reproductive biology. Due to their extraordinary complexity, proteome depth-of-coverage is dependent on advancements in technology and related bioinformatics, both of which have made significant advancements in the decade since the last Drosophila sperm proteome was published. Here, we provide an updated version of the Drosophila melanogaster sperm proteome (DmSP3) using improved separation and detection methods and an updated genome annotation. Combined with previous versions of the sperm proteome, the DmSP3 contains a total of 3176 proteins, and we provide the first label-free quantitation of the sperm proteome for 2125 proteins. The top 20 most abundant proteins included the structural elements α- and β-tubulins and sperm leucyl-aminopeptidases. Both gene content and protein abundance were significantly reduced on the X chromosome, consistent with prior genomic studies of X chromosome evolution. We identified 9 of the 16 Y-linked proteins, including known testis-specific male fertility factors. We also identified almost one-half of known Drosophila ribosomal proteins in the DmSP3. The role of this subset of ribosomal proteins in sperm is unknown. Surprisingly, our expanded sperm proteome also identified 122 seminal fluid proteins (Sfps), proteins originally identified in the accessory glands. We show that a significant fraction of 'sperm-associated Sfps' are recalcitrant to concentrated salt and detergent treatments, suggesting this subclass of Sfps are expressed in testes and may have additional functions in sperm, per se. Overall, our results add to a growing landscape of both sperm and seminal fluid protein biology and in particular provides quantitative evidence at the protein level for prior findings supporting the meiotic sex-chromosome inactivation model for male-specific gene and X chromosome evolution.

Proteomic analysis of low- and high-grade human colon adenocarcinoma tissues and tissue-derived primary cell lines reveals unique biological functions of tumours and new protein biomarker candidates

Background

Colon cancer is the third most common cancer and second highest cause of cancer deaths worldwide. The aim of the study was to find new biomarkers for diagnosis, prognosis and therapeutic drug targets for this disease.

Methods

Four low-grade and four high-grade human colon adenocarcinoma tumours with patient-matched normal colon tissues were analysed. Additionally, tissue-derived primary cell lines were established from each tumour tissue. The cell lines were validated using DNA sequencing to confirm that they are a suitable in vitro model for colon adenocarcinoma based on conserved gene mutations. Label-free quantitation proteomics was performed to compare the proteomes of colon adenocarcinoma samples to normal colon samples, and of colon adenocarcinoma tissues to tissue-derived cell lines to find significantly differentially abundant proteins. The functions enriched within the differentially expressed proteins were assessed using STRING. Proteomics data was validated by Western blotting.

Results

A total of 4767 proteins were identified across all tissues, and 4711 across primary tissue-derived cell lines. Of these, 3302 proteins were detected in both the tissues and the cell lines. On average, primary cell lines shared about 70% of proteins with their parent tissue, and they retained mutations to key colon adenocarcinoma-related genes and did not diverge far genetically from their parent tissues. Colon adenocarcinoma tissues displayed upregulation of RNA processing, steroid biosynthesis and detoxification, and downregulation of cytoskeletal organisation and loss of normal muscle function. Tissue-derived cell lines exhibited increased interferon-gamma signalling and aberrant ferroptosis. Overall, 318 proteins were significantly up-regulated and 362 proteins significantly down-regulated by comparisons of high-grade with low-grade tumours and low-grade tumour with normal colon tissues from both sample types.

Conclusions

The differences exhibited between tissues and cell lines highlight the additional information that can be obtained from patient-derived primary cell lines. DNA sequencing and proteomics confirmed that these cell lines can be considered suitable in vitro models of the parent tumours. Various potential biomarkers for colon adenocarcinoma initiation and progression and drug targets were identified and discussed, including seven novel markers: ACSL4, ANK2, AMER3, EXOSC1, EXOSC6, GCLM, and TFRC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12014-022-09364-y.

The Intracellular Interaction of Porcine β-Defensin 2 with VASH1 Alleviates Inflammation via Akt Signaling Pathway

Defensins are a major class of antimicrobial peptides that facilitate the immune system to resist pathogen infection. To date, only β-defensins have been identified in pigs. In our previous studies, porcine β-defensin 2 (PBD-2) was shown to have both bactericidal activity and modulatory roles on inflammation. PBD-2 can interact with the cell surface TLR4 and interfere with the NF-κB signaling pathway to suppress the inflammatory response. In this study, the intracellular functions of PBD-2 were investigated. The fluorescently labeled PBD-2 could actively enter mouse macrophage cells. Proteomic analysis indicated that 37 proteins potentially interacted with PBD-2, among which vasohibin-1 (VASH1) was further tested. LPS, an inflammation inducer, suppressed the expression of VASH1, whereas PBD-2 inhibited this effect. PBD-2 inhibited LPS-induced activation of Akt, expression and release of the inflammatory mediators vascular endothelial growth factor and NO, and cell damage. A follow-up VASH1 knockdown assay validated the specificity of the above observations. In addition, PBD-2 inhibited LPS-induced NF-κB activation via Akt. The inhibition effects of PBD-2 on LPS triggered suppression of VASH1 and activation of Akt, and NF-κB and inflammatory cytokines were also confirmed using pig alveolar macrophage 3D4/21 cells. Therefore, the data indicate that PBD-2 interacts with intracellular VASH1, which inhibits the LPS-induced Akt/NF-κB signaling pathway, resulting in suppression of inflammatory responses. Together with our previous findings, we conclude that PBD-2 interacts with both the cell surface receptor (TLR4) and also with the intracellular receptor (VASH1) to control inflammation, thereby providing insights into the immunomodulatory roles of defensins.

Label-Free Quantification (LFQ) of Fecal Proteins for Potential Pregnancy Detection in Polar Bears

Reliable pregnancy diagnostics would be beneficial for monitoring polar bear (Ursus maritimus) populations both in situ and ex situ, but currently there is no method of non-invasive pregnancy detection in this species. Recent reports in several carnivore species described the identification of fecal proteins that may serve as pregnancy biomarkers; however, repeatability has been limited. The objective of the current analysis was to utilize an unbiased, antibody-free, label-free method for the identification and quantification of fecal proteins to determine if differences associated with pregnancy are detectable in polar bears. Protein was extracted from fecal samples (n = 48) obtained from parturient (n = 6) and non-parturient (n = 6) profiles each at four timepoints: pre-breeding season, embryonic diapause, early placental pregnancy, and mid-placental pregnancy. Protein was prepared and analyzed on the Thermo Orbitrap Eclipse nanoLC-MS/MS system. A total of 312 proteins was identified and quantified; however, coefficients of variation (CV) were high for both abundance ratio variability (384.8 ± 61.0% SEM) and within group variability (86.8 ± 1.5%). Results of this study suggest that the inconsistencies in specific protein concentrations revealed previously by antibody-based assays may not be due to that methodology’s limitations, but rather, are reflective of true variation that exists among samples.

Extracellular vesicles expressing CEACAM proteins in the urine of bladder cancer patients

Early detection and long‐term monitoring are important for urothelial carcinoma of the bladder (UCB). Urine cytology and existing markers have insufficient diagnostic performance. Here, we examined medium‐sized extracellular vesicles (EVs) in urine to identify specific markers for UCB and evaluated their usefulness as diagnostic material. To identify specific markers in urinary EVs derived from UCB, we undertook shotgun proteomics using urine from four UCB patients and four healthy subjects. Next, 29 healthy specimens, 18 noncancer specimens, and 33 UCB specimens, all from men, were analyzed for urinary EVs by flow cytometry to evaluate the diagnostic performance of UCB‐specific EVs. Nanoparticle‐tracking analysis indicated that the size of EVs extracted from urine was mostly <400 nm. By shotgun proteomics, we detected several proteins characteristic of UCB and found that carcinoembryonic antigen‐related adhesion molecule (CEACAM) proteins were increased in patients. Flow cytometric analysis revealed that the degree of expression of CEACAM1, CEACAM5, and CEACAM6 proteins on the surface of EVs varied among patients. Extracellular vesicles expressing CEACAM proteins also expressed mucin 1, suggesting that they were derived from tumorigenic uroepithelial cells. The number of EVs expressing CEACAM1, 5, and 6 proteins was significantly increased in UCB (mean ± SD, 8.6 ± 13%) compared to non‐UCB (0.69 ± 0.46) and healthy (0.46 ± 0.34) by flow cytometry. The results of receiver operating characteristic (ROC) analysis showed a good score of area under the ROC curve of 0.907. We identified EVs that specifically express CEACAM proteins in urine and have potential for diagnostic applications. These EVs are potential targets in a new liquid biopsy test for UCB patients.

Wheat Proteomics for Abiotic Stress Tolerance and Root System Architecture: Current Status and Future Prospects

Wheat is an important staple cereal for global food security. However, climate change is hampering wheat production due to abiotic stresses, such as heat, salinity, and drought. Besides shoot architectural traits, improving root system architecture (RSA) traits have the potential to improve yields under normal and stressed environments. RSA growth and development and other stress responses involve the expression of proteins encoded by the trait controlling gene/genes. Hence, mining the key proteins associated with abiotic stress responses and RSA is important for improving sustainable yields in wheat. Proteomic studies in wheat started in the early 21st century using the two-dimensional (2-DE) gel technique and have extensively improved over time with advancements in mass spectrometry. The availability of the wheat reference genome has allowed the exploration of proteomics to identify differentially expressed or abundant proteins (DEPs or DAPs) for abiotic stress tolerance and RSA improvement. Proteomics contributed significantly to identifying key proteins imparting abiotic stress tolerance, primarily related to photosynthesis, protein synthesis, carbon metabolism, redox homeostasis, defense response, energy metabolism and signal transduction. However, the use of proteomics to improve RSA traits in wheat is in its infancy. Proteins related to cell wall biogenesis, carbohydrate metabolism, brassinosteroid biosynthesis, and transportation are involved in the growth and development of several RSA traits. This review covers advances in quantification techniques of proteomics, progress in identifying DEPs and/or DAPs for heat, salinity, and drought stresses, and RSA traits, and the limitations and future directions for harnessing proteomics in wheat improvement.

Label-free LC-MS/MS proteomics analyses reveal proteomic changes in oxidative stress and the SOD antioxidant strategy in TM cells

Background

Treatment for glaucoma has traditionally been limited to reducing intraocular pressure (IOP). Inhibiting oxidative stress in the trabecular meshwork (TM) is regarded as a new treatment for glaucoma; however, the effects do not meet expectations. Exploring the mechanism by which oxidative stress and antioxidant stress occur in TM cells will offer clues to aid the development of new treatments.

Methods and results

In our study, we cultured TM cells and used H₂O₂ and SOD to induce and inhibit oxidative stress, respectively. Label-free LC–MS/MS quantitative proteomic analysis was conducted to analyze the differentially expressed proteins and relevant signaling pathways. A total of 24 upregulated proteins and 18 downregulated proteins were identified under oxidative stress. PTGS2, TGFβr2 and ICAM-1 are the key proteins. The PTGS2/NF-ĸb pathway, TGF-β/Smad signaling pathway and AGE-RAGE signaling pathway in diabetic complications may be the major signaling pathways under conditions of ROS-induced damage in TM cells. Seventy-eight proteins were upregulated and 73 proteins were downregulated under antioxidant stress in TM cells. The key protein was ICAM-1, which participates in the African trypanosomiasis pathway, one of the most important pathways under antioxidant stress. Combining the results of the Venn diagram with protein–protein interactions (PPIs), ICAM-1 was identified as the major protein. Cell Counting Kit-8 (CCK-8) and western blotting (WB) were used to reveal that suppressing the expression of ICAM-1 would improve the survival of TM cells.

Conclusions

Key proteins and signaling pathways play important roles in the mechanisms of oxidative stress and antioxidant strategies in TM cells. ICAM-1 knockdown can suppress the apoptosis of TM cells induced by H₂O_2, which may reveal new therapeutic targets and biomarkers for glaucoma.

StatsPro: Systematic integration and evaluation of statistical approaches for detecting differential expression in label-free quantitative proteomics

Quantitative label-free mass spectrometry (MS) is an increasingly powerful technology for profiling thousands of proteins from complex biological samples. One of the primary goals of analyses performed on such proteomics data is to detect differentially expressed proteins (DEPs) under different experimental conditions. Many statistical methods have been developed and assessed for DEP detection in various proteomics studies. However, it remains a challenge for many proteomics scientists to choose an appropriate statistical procedure. Therefore, in this study, we organized 12 common testing algorithms and 6 P-value combination methods and further provided Cohen's d effect size for every protein and three evaluation criteria to help proteomics scientists investigate their influence on DEP detection in a systematic manner. To promote the widespread use of these methods, we developed a user-friendly web tool, StatsPro, and presented two case studies involving label-free quantitative proteomics data obtained using data-dependent acquisition and data-independent acquisition to illustrate its practicability. This tool is freely available in our GitHub repository (https://github.com/YanglabWCH/StatsPro/). SIGNIFICANCE: One of the primary goals of analyses performed on liquid chromatography-mass spectrometry (LC-MS) based proteomics data is to detect differentially expressed proteins (DEPs) under different experimental conditions. Despite of many research efforts have been proposed to detect DEPs, to date, there is a scarcity of efficient, systematic, and easy-to-handle tools that are tailored for proteomics scientists to choose an appropriate statistical procedure. Herein, we present a new tool, StatsPro, to enable implementation and evaluation of different statistical methods for proteomics scientists. This tool has two significant advances compared to existing software: a) It integrates up to 18 common statistical approaches (12 statistical tests and 6 P-value combination strategies) and performs Cohen's d effect size systematically for users, moreover, it provides a web-based interface and can be quite conveniently operated by users, even those with less profound computational background. b) It supports three performance evaluation criteria (e.g. number of DEPs, correlation coefficient between P-values and effect sizes, Area under the ROC curve) for users to review the final statistical results, which may guide the method selection for DEPs detection.

Identification of proteins associated with treatment response of neoadjuvant chemoradiotherapy in rectal mucinous adenocarcinoma by co-expression network analysis based on proteomic analysis

For rectal mucinous adenocarcinoma (MAC), identifying biomarkers of neoadjuvant chemoradiotherapy (NCRT) response has become imperative. This study applied label-free mass spectrometry and weighted gene co-expression network analysis to identify hub proteins in association with the NCRT response in 20 rectal MAC patients. We identified 131 differentially abundant proteins and 7 candidate proteins associated with the NCRT response. The immunostaining expressions of six proteins (ENOA, ILEU, MDHM, RM11, PTGDS, and RL3) were significantly associated with the NCRT response. Logistic regression analysis revealed that ENOA (OR = 6.275, P = 0.006) was independent risk hub protein for the NCRT response. Tow hub proteins (ENOA and PTGDS) were identified as significant risk factors by Cox regression analysis. A prognostic risk score system was constructed: risk score = (0.910 × EXP_ENOA) + (-1.519 × EXP_PTGDS), and found to be an independent predictor of DFS in rectal MAC patients (HR = 10.308, P < 0.001). Our study suggested that ENOA may be a novel biomarker for the NCRT response and prognosis in rectal MAC patients. A two-hub-protein-based risk score system might be used for predicting tumor recurrence in rectal MAC patients. SIGNIFICANCE: NCRT resistance is a major problem in the treatment of rectal MAC patients. Identifying robust predictive biomarkers for NCRT resistance is beneficial to the stratified treatment of rectal MAC patients. In this study, label-free mass spectrometry and weighted gene co-expression network analysis identified ENOA as a potential novel biomarker for the NCRT response and prognosis. ENOA may be involved in the process of the NCRT resistance and tumor recurrence through the carbon metabolism pathway.

The proteomes of endometrial stromal cell-derived extracellular vesicles following a decidualizing stimulus define the cells' potential for decidualization success

Adequate endometrial stromal cell (ESC) decidualization is vital for endometrial health. Given the importance of extracellular vesicles (EVs) in intercellular communication, we investigated how their protein landscape is reprogrammed and dysregulated during decidual response. Small EVs (sEVs) from human ESC-conditioned media at Day-2 and -14 following decidual stimuli were grouped as well- (WD) or poorly decidualized (PD) based on their prolactin secretion and subjected to mass spectrometry-based quantitative proteomics. On Day 2, in PD- versus WD-ESC-sEVs, 17 sEV- proteins were down-regulated (C5, C6; complement/coagulation cascades, and SERPING1, HRG; platelet degranulation and fibrinolysis) and 39 up-regulated (FLNA, COL1A1; focal adhesion, ENO1, PKM; glycolysis/gluconeogenesis, and RAP1B, MSN; leukocyte transendothelial migration). On Day 14, in PD- versus WD-ESC-sEVs, FLNA was down-regulated while 21 proteins were up-regulated involved in complement/coagulation cascades (C3, C6), platelet degranulation (SERPINA4, ITIH4), B-cell receptor signalling and innate immune response (immunoglobulins). Changes from Days 2 to 14 suggested a subsequent response in PD-ESC-sEVs with 89 differentially expressed proteins mostly involved in complement and coagulation cascades (C3, C6, C5), but no change in WD-ESC-sEVs ESC. Poor decidualization was also associated with loss of crucial sEV-proteins for cell adhesion and invasion (ITGA5, PFN1), glycolysis (ALDOA, PGK1) and cytoskeletal reorganization (VCL, RAC1). Overall, this study indicates varied ESC response even prior to decidualization and provides insight into sEVs-proteomes as a benchmark of well-decidualized ESC. It shows distinct variation in sEV-protein composition depending on the ESC decidual response that is critical for embryo implantation, enabling and limiting trophoblast invasion during placentation and sensing a healthy embryo.

The Big Picture of Glioblastoma Malignancy: A Meta-Analysis of Glioblastoma Proteomics to Identify Altered Biological Pathways

Glioblastoma is a highly malignant cancer with no effective treatment. It is vital to elucidate the mechanisms which drive glioblastoma in order to identify therapeutic targets. The differences in protein expression between glioblastoma, grade I-III glioma, and normal brain tissue reflect the functional alterations driving malignancy. However, proteomic analysis of glioblastoma has been hampered by the heterogeneity of glioblastoma and the variety of methodology used in its study. To reduce these inconsistencies, we performed a meta-analysis of the literature published since 2015, including 14 datasets from eight papers comparing the whole proteome of glioblastoma to normal brain or grade I-III glioma. We found that 154 proteins were commonly upregulated and 116 proteins were commonly downregulated in glioblastoma compared to normal brain. Meanwhile, 240 proteins were commonly upregulated and 125 proteins were commonly downregulated in glioblastoma compared to grade I-III glioma. Functional enrichment analysis revealed upregulation of proteins involved in mRNA splicing and the immune system and downregulation of proteins involved in synaptic signaling and glucose and glutamine metabolism. The identification of these altered biological pathways provides a basis for deeper investigation in the pursuit of an effective treatment for glioblastoma.

Characterization of the NiRAN domain from RNA-dependent RNA polymerase provides insights into a potential therapeutic target against SARS-CoV-2

Apart from the canonical fingers, palm and thumb domains, the RNA dependent RNA polymerases (RdRp) from the viral order Nidovirales possess two additional domains. Of these, the function of the Nidovirus RdRp associated nucleotidyl transferase domain (NiRAN) remains unanswered. The elucidation of the 3D structure of RdRp from the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), provided the first ever insights into the domain organisation and possible functional characteristics of the NiRAN domain. Using in silico tools, we predict that the NiRAN domain assumes a kinase or phosphotransferase like fold and binds nucleoside triphosphates at its proposed active site. Additionally, using molecular docking we have predicted the binding of three widely used kinase inhibitors and five well characterized anti-microbial compounds at the NiRAN domain active site along with their drug-likeliness. For the first time ever, using basic biochemical tools, this study shows the presence of a kinase like activity exhibited by the SARS-CoV-2 RdRp. Interestingly, a well-known kinase inhibitor- Sorafenib showed a significant inhibition and dampened viral load in SARS-CoV-2 infected cells. In line with the current global COVID-19 pandemic urgency and the emergence of newer strains with significantly higher infectivity, this study provides a new anti-SARS-CoV-2 drug target and potential lead compounds for drug repurposing against SARS-CoV-2.

The on-going coronavirus disease 2019 (COVID-19) pandemic caused by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is significantly affecting the world health. Unfortunately, over 180 million cases of COVID-19 resulting in nearly 4 million deaths have been reported till June, 2021. In this study, using a combination of bioinformatics, biochemical and mass spectrometry methods, we show that the Nidovirus RdRp associated Nucleotidyl transferase (NiRAN) domain of the RNA-dependent RNA polymerase (RdRp) of SARS-CoV-2 exhibits a kinase like activity. Additionally, we also show that few broad spectrum anti-cancer and anti-microbial drugs dampen this kinase like activity. Of note, Sorafenib, an FDA approved anti-cancer kinase inhibiting drug significantly reduces the SARS-CoV-2 load in cell lines. Our study suggests that NiRAN domain of the SARS-CoV-2 RdRp is indispensible for the successful viral life cycle and shows that abolishing this enzymatic function of RdRp by small molecule inhibitors may open novel avenues for COVID-19 therapeutics.

Characterization of the NiRAN domain from RNA-dependent RNA polymerase provides insights into a potential therapeutic target against SARS-CoV-2

Apart from the canonical fingers, palm and thumb domains, the RNA dependent RNA polymerases (RdRp) from the viral order Nidovirales possess two additional domains. Of these, the function of the Nidovirus RdRp associated nucleotidyl transferase domain (NiRAN) remains unanswered. The elucidation of the 3D structure of RdRp from the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), provided the first ever insights into the domain organisation and possible functional characteristics of the NiRAN domain. Using in silico tools, we predict that the NiRAN domain assumes a kinase or phosphotransferase like fold and binds nucleoside triphosphates at its proposed active site. Additionally, using molecular docking we have predicted the binding of three widely used kinase inhibitors and five well characterized anti-microbial compounds at the NiRAN domain active site along with their drug-likeliness. For the first time ever, using basic biochemical tools, this study shows the presence of a kinase like activity exhibited by the SARS-CoV-2 RdRp. Interestingly, a well-known kinase inhibitor- Sorafenib showed a significant inhibition and dampened viral load in SARS-CoV-2 infected cells. In line with the current global COVID-19 pandemic urgency and the emergence of newer strains with significantly higher infectivity, this study provides a new anti-SARS-CoV-2 drug target and potential lead compounds for drug repurposing against SARS-CoV-2.

Multiple Imputation Approaches Applied to the Missing Value Problem in Bottom-Up Proteomics

Analysis of differential abundance in proteomics data sets requires careful application of missing value imputation. Missing abundance values widely vary when performing comparisons across different sample treatments. For example, one would expect a consistent rate of “missing at random” (MAR) across batches of samples and varying rates of “missing not at random” (MNAR) depending on the inherent difference in sample treatments within the study. The missing value imputation strategy must thus be selected that best accounts for both MAR and MNAR simultaneously. Several important issues must be considered when deciding the appropriate missing value imputation strategy: (1) when it is appropriate to impute data; (2) how to choose a method that reflects the combinatorial manner of MAR and MNAR that occurs in an experiment. This paper provides an evaluation of missing value imputation strategies used in proteomics and presents a case for the use of hybrid left-censored missing value imputation approaches that can handle the MNAR problem common to proteomics data.

Convolutional neural network in proteomics and metabolomics for determination of comorbidity between cancer and schizophrenia

The association between cancer risk and schizophrenia is widely debated. Despite many epidemiological studies, there is still no strong evidence regarding the molecular basis for the comorbidity between these two pathological conditions. The vast majority of assays have been performed using clinical records of schizophrenic patients or those undergoing cancer treatment and monitored for sufficient time to find shared features between the considered conditions. We performed mass spectrometry-based proteomic and metabolomic investigations of patients with different cancer phenotypes (breast, ovarian, renal, and prostate) and patients with schizophrenia. The resulting vast quantity of proteomic and metabolomic data were then processed using systems biology and one-dimensional (1D) convolutional neural network (1DCNN) machine learning approaches. Traditional systematic approaches permit the segregation of schizophrenia and cancer phenotypes on the level of biological processes, while 1DCNN recognized "signatures" that could segregate distinct cancer phenotypes and schizophrenia at the comorbidity level. The designed network efficiently discriminated unrelated pathologies with a model accuracy of 0.90 and different subtypes of oncophenotypes with an accuracy of 0.94. The proposed strategy integrates systematic analysis of identified compounds and application of 1DCNN model for unidentified ones to reveal the similarity between distinct phenotypes.

Emerging roles of non-histone protein crotonylation in biomedicine

Crotonylation of proteins is a newly found type of post-translational modifications (PTMs) which occurs leadingly on the lysine residue, namely, lysine crotonylation (Kcr). Kcr is conserved and is regulated by a series of enzymes and co-enzymes including lysine crotonyltransferase (writer), lysine decrotonylase (eraser), certain YEATS proteins (reader), and crotonyl-coenzyme A (donor). Histone Kcr has been substantially studied since 2011, but the Kcr of non-histone proteins is just an emerging field since its finding in 2017. Recent advances in the identification and quantification of non-histone protein Kcr by mass spectrometry have increased our understanding of Kcr. In this review, we summarized the main proteomic characteristics of non-histone protein Kcr and discussed its biological functions, including gene transcription, DNA damage response, enzymes regulation, metabolic pathways, cell cycle, and localization of heterochromatin in cells. We further proposed the performance of non-histone protein Kcr in diseases and the prospect of Kcr manipulators as potential therapeutic candidates in the diseases.

Comparative Evaluation of MaxQuant and Proteome Discoverer MS1-Based Protein Quantification Tools

MS1-based label-free quantification can compare precursor ion peaks across runs, allowing reproducible protein measurements. Among bioinformatic platforms enabling MS1-based quantification, MaxQuant (MQ) is one of the most used, while Proteome Discoverer (PD) has recently introduced the Minora tool. Here, we present a comparative evaluation of six MS1-based quantification methods available in MQ and PD. Intensity (MQ and PD) and area (PD only) of the precursor ion peaks were measured and then subjected or not to normalization. The six methods were applied to data sets simulating various differential proteomics scenarios and covering a wide range of protein abundance ratios and amounts. PD outperformed MQ in terms of quantification yield, dynamic range, and reproducibility, although neither platform reached a fully satisfactory quality of measurements at low-abundance ranges. PD methods including normalization were the most accurate in estimating the abundance ratio between groups and the most sensitive when comparing groups with a narrow abundance ratio; on the contrary, MQ methods generally reached slightly higher specificity, accuracy, and precision values. Moreover, we found that applying an optimized log ratio-based threshold can maximize specificity, accuracy, and precision. Taken together, these results can help researchers choose the most appropriate MS1-based protein quantification strategy for their studies.

Domain Mapping of Chondroitin/Dermatan Sulfate Glycosaminoglycans Enables Structural Characterization of Proteoglycans

Of all posttranslational modifications known, glycosaminoglycans (GAGs) remain one of the most challenging to study, and despite the recent years of advancement in MS technologies and bioinformatics, detailed knowledge about the complete structures of GAGs as part of proteoglycans (PGs) is limited. To address this issue, we have developed a protocol to study PG-derived GAGs. Chondroitin/dermatan sulfate conjugates from the rat insulinoma cell line, INS-1832/13, known to produce primarily the PG chromogranin-A, were enriched by anion-exchange chromatography after pronase digestion. Following benzonase and hyaluronidase digestions, included in the sample preparation due to the apparent interference from oligonucleotides and hyaluronic acid in the analysis, the GAGs were orthogonally depolymerized and analyzed using nano-flow reversed-phase LC-MS/MS in negative mode. To facilitate the data interpretation, we applied an automated LC-MS peak detection and intensity measurement via the Proteome Discoverer software. This approach effectively provided a detailed structural description of the nonreducing end, internal, and linkage region domains of the CS/DS of chromogranin-A. The copolymeric CS/DS GAGs constituted primarily consecutive glucuronic-acid-containing disaccharide units, or CS motifs, of which the N-acetylgalactosamine residues were 4-O-sulfated, interspersed by single iduronic-acid-containing disaccharide units. Our data suggest a certain heterogeneity of the GAGs due to the identification of not only CS/DS GAGs but also of GAGs entirely of CS character. The presented protocol allows for the detailed characterization of PG-derived GAGs, which may greatly increase the knowledge about GAG structures in general and eventually lead to better understanding of how GAG structures are related to biological functions.

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Protocol developed to structurally characterize glycosaminoglycans of proteoglycans.

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Comprehensive characterization of cellular glycosaminoglycan structures.

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Relative quantification of nonreducing end, internal, and linkage region domains.

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Overall chondroitin/dermatan sulfate glycosaminoglycan structures of chromogranin-A.