Deep Plasma Proteomics with Data-Independent Acquisition: Clinical Study Protocol Optimization with a COVID-19 Cohort.

Plasma proteomics is a precious tool in human disease research but requires extensive sample preparation in order to perform in-depth analysis and biomarker discovery using traditional data-dependent acquisition (DDA). Here, we highlight the efficacy of combining moderate plasma prefractionation and data-independent acquisition (DIA) to significantly improve proteome coverage and depth while remaining cost-efficient. Using human plasma collected from a 20-patient COVID-19 cohort, our method utilizes commonly available solutions for depletion, sample preparation, and fractionation, followed by 3 liquid chromatography-mass spectrometry/MS (LC-MS/MS) injections for a 360 min total DIA run time. We detect 1321 proteins on average per patient and 2031 unique proteins across the cohort. Differential analysis further demonstrates the applicability of this method for plasma proteomic research and clinical biomarker identification, identifying hundreds of differentially abundant proteins at biological concentrations as low as 47 ng/L in human plasma. Data are available via ProteomeXchange with the identifier PXD047901. In summary, this study introduces a streamlined, cost-effective approach to deep plasma proteome analysis, expanding its utility beyond classical research environments and enabling larger-scale multiomics investigations in clinical settings. Our comparative analysis revealed that fractionation, whether the samples were pooled or separate postfractionation, significantly improved the number of proteins quantified. This underscores the value of fractionation in enhancing the depth of plasma proteome analysis, thereby offering a more comprehensive landscape for biomarker discovery in diseases such as COVID-19.

Integrative analysis of the transcriptome and proteome reveals the molecular responses of tobacco to boron deficiency.

BACKGROUND: Boron (B) is an essential micronutrient for plants. Inappropriate B supply detrimentally affects the productivity of numerous crops. Understanding of the molecular responses of plants to different B supply levels would be of significance in crop improvement and cultivation practices to deal with the problem. RESULTS: We conducted a comprehensive analysis of the transcriptome and proteome of tobacco seedlings to investigate the expression changes of genes/proteins in response to different B supply levels, with a particular focus on B deficiency. The global gene and protein expression profiles revealed the potential mechanisms involved in the responses of tobacco to B deficiency, including up-regulation of the NIP5;1-BORs module, complex regulation of genes/proteins related to cell wall metabolism, and up-regulation of the antioxidant machinery. CONCLUSION: Our results demonstrated that B deficiency caused severe morphological and physiological disorders in tobacco seedlings, and revealed dynamic expression changes of tobacco genes/proteins in response to different B supply levels, especially to B deficiency, thus offering valuable insights into the molecular responses of tobacco to B deficiency.

Anti-histone and anti-nucleosome rather than anti-dsDNA antibodies associate with IFN-induced biomarkers in Sudanese and Swedish Systemic Lupus Erythematosus patients.

OBJECTIVES: In SLE, anti-dsDNA can co-occur with autoantibodies against other chromatin components, like histones and nucleosomes. These antibodies induce type-1 interferon production, a hallmark of SLE. We measured antinuclear antibody (ANA) sub-specificities and investigated their associations to inflammatory biomarkers including interferon-regulated chemokines. METHODS: We included 93 Sudanese and 480 Swedish SLE patients and matched controls (N = 104 + 192). Autoantibodies targeting ANA-subspecificites: dsDNA, Sm, Sm/U1RNPcomplex, U1RNP, SSA/Ro52, SSA/Ro60, SSB/La, ribosomal P, PCNA and histones were quantified in all subjects, anti-nucleosome only in the Swedish patients, with a bead-based multiplex immunoassay. Levels of 72 plasma biomarkers were determined with Proximity Extension Assay technique or ELISA. RESULTS: Among Sudanese patients, the investigated antibodies significantly associated with 9/72 biomarkers. Anti-histone antibodies showed the strongest positive correlations with MCP-3 and S100A12 as well as with interferon I-inducible factors MCP-1 and CXCL10. Anti-dsDNA antibodies associated with CXCL10 and S100A12, but in multivariate analyses, unlike anti-histone, associations lost significance.Among Swedish patients, MCP-1, CXCL10, SA100A12 also demonstrated stronger associations to anti-histone and anti-nucleosome antibodies, compared with anti-dsDNA and other ANA sub-specificities. In multiple regression models, anti-histone/nucleosome retained the strongest associations. When excluding anti-histone or anti-nucleosome positive patients, the associations between MCP-1/CXCL10 and anti-dsDNA were lost. In contrast, when excluding anti-dsDNA positive patients, associations with anti-histone and anti-nucleosome remained significant. CONCLUSION: In two cohorts of different ethnical origin, autoantibodies targeting chromatin correlate stronger with IFN-induced inflammatory biomarkers than anti-dsDNA or other ANA sub-specificities. Our results suggest that anti-histone/nucleosome autoantibodies may be main drivers of type-1 interferon activity in SLE.

Integrated transcriptome and proteome analysis provides insights into CpFPA1 for floral induction in Chimonanthus praecox (Magnoliidae) without FLC in genome.

KEY MESSAGE: We used transcriptomic and proteomic association analysis to reveal the critical genes/proteins at three key flower bud differentiation stages and overexpression of CpFPA1 in Arabidopsis resulted in earlier flowering. Wintersweet (Chimonanthus praecox), a rare winter-flowering woody plant, is well known for its unique blooming time, fragrance and long flowering period. However, the molecular mechanism of flowering in C. praecox remains poorly unclear. In this study, we used transcriptomic and proteomic association analysis to reveal the critical genes/proteins at three key flower bud (FB) differentiation stages (FB.Apr, FB.May and FB.Nov) in C. praecox. The results showed that a total of 952 differential expressed genes (DEGs) and 40 differential expressed proteins (DEPs) were identified. Gene ontology (GO) enrichment revealed that DEGs in FB.Apr/FB.May comparison group were mainly involved in metabolic of biological process, cell and cell part of cellular component and catalytic activity of molecular function. In the EuKaryotic Orthologous Groups (KOG) functional classification, DEPs were predicted mainly in the function of general function prediction only (KOG0118), post-translational modification, protein turnover and chaperones. The autonomous pathway genes play an essential role in the floral induction. Based on transcriptome and proteome correlation analysis, six candidate genes associated with the autonomous pathway were identified, including FPA1, FPA2a, FPA2b, FCA, FLK, FY. Furthermore, CpFPA1 was isolated and functionally characterized, and ectopic expression of CpFPA1 in Arabidopsis Columbia (Col-0) resulted in earlier flowering. These data could contribute to understand the function of CpFPA1 for floral induction and provide information for further research on the molecular mechanisms of flowering in wintersweet.

AIomics: Exploring More of the Proteome Using Mass Spectral Libraries Extended by Artificial Intelligence.

The unbounded permutations of biological molecules, including proteins and their constituent peptides, present a dilemma in identifying the components of complex biosamples. Sequence search algorithms used to identify peptide spectra can be expanded to cover larger classes of molecules, including more modifications, isoforms, and atypical cleavage, but at the cost of false positives or false negatives due to the simplified spectra they compute from sequence records. Spectral library searching can help solve this issue by precisely matching experimental spectra to library spectra with excellent sensitivity and specificity. However, compiling spectral libraries that span entire proteomes is pragmatically difficult. Neural networks that predict complete spectra containing a full range of annotated and unannotated ions can be used to replace these simplified spectra with libraries of fully predicted spectra, including modified peptides. Using such a network, we created predicted spectral libraries that were used to rescore matches from a sequence search done over a large search space, including a large number of modifications. Rescoring improved the separation of true and false hits by 82%, yielding an 8% increase in peptide identifications, including a 21% increase in nonspecifically cleaved peptides and a 17% increase in phosphopeptides.

Repeat-Enhancing Featured Ion-Guided Stoichiometry for Identification and Quantification of Direct Infusion Proteome.

The direct infusion-shotgun proteome analysis (DI-SPA) alongside data-independent acquisition mass spectrometry achieved fast proteome identification and quantification without chromatographic separation. However, robust peptide identification and quantification (label and label-free) for the DI-SPA data is still insufficient. We find that in the absence of chromatography, the identification of DI-SPA can be boosted by extending acquisition cycles repeatedly and maximizing the utilization of the featured repetition characteristics, combined with the machine learning-based automatic peptide scoring strategy. Here, we present the repeat-enhancing featured ion-guided stoichiometry (RE-FIGS), a complete and compact solution to (repeated) DI-SPA data. Using our strategy, the peptide identification can be improved above 30% with high reproducibility (70.0%). Notably, the label-free quantification of repeated DI-SPA can be successfully obtained with high accuracy (mean median error, 0.108) and high reproducibility (median error, 0.001). We believe our RE-FIGS method could boost the broad application of the (repeated) DI-SPA method and offer a new choice for proteomic analysis.

Phosphoproteomic Analysis of Dopamine D2 Receptor Signaling Reveals Interplay of G Protein- and ß-Arrestin-Mediated Effects.

Leveraging biased signaling of G protein-coupled receptors has been proposed as a promising strategy for the development of drugs with higher specificity. However, the consequences of selectively targeting G protein- or ß-arrestin-mediated signaling on cellular functions are not comprehensively understood. In this study, we utilized phosphoproteomics to gain a systematic overview of signaling induced by the four biased and balanced dopamine D2 receptor (D2R) ligands MS308, BM138, quinpirole, and sulpiride in an in vitro D2R transfection model. Quantification of 14,160 phosphosites revealed a low impact of the partial G protein agonist MS308 on cellular protein phosphorylation, as well as surprising similarities between the balanced agonist quinpirole and the inverse agonist sulpiride. Analysis of the temporal profiles of ligand-induced phosphorylation events showed a transient impact of the G protein-selective agonist MS308, whereas the ß-arrestin-preferring agonist BM138 elicited a delayed, but more pronounced response. Functional enrichment analysis of ligand-impacted phosphoproteins and treatment-linked kinases confirmed multiple known functions of D2R signaling while also revealing novel effects, for example of MS308 on sterol regulatory element-binding protein-related gene expression. All raw data were deposited in MassIVE (MSV000089457).

Obesity impacts hypoxia adaptation of the lung.

Obesity is mostly associated with adverse health consequences, but may also elicit favorable effects under chronic conditions. This "obesity paradox" is under debate for pulmonary diseases. As confounding factors complicate conclusions from human studies, this study used a controlled animal model combining diet-induced obesity and chronic hypoxia as a model for pulmonary hypertension and chronic obstructive pulmonary disease. Male C57BL/6 mice were fed control or high-fat diet for 30 wk, and half of the animals were exposed to chronic hypoxia (13% O2) for 3 wk. Hypoxia induced right ventricular hypertrophy, thickening of pulmonary arterial and capillary walls, higher lung volumes, and increased hemoglobin concentrations irrespective of the body weight. In contrast, lung proteomes differed substantially between lean- and obese-hypoxic mice. Many of the observed changes were linked to vascular and extracellular matrix (ECM) proteins. In lean-hypoxic animals, circulating platelets were reduced and abundances of various clotting-related proteins were altered, indicating a hypercoagulable phenotype. Moreover, the septal ECM composition was changed, and airspaces were significantly distended pointing to lung hyperinflation. These differences were mostly absent in the obese-hypoxic group. However, the obesity-hypoxia combination induced the lowest blood CO2 concentrations, indicating hyperventilation for sufficient oxygen supply. Moreover, endothelial surface areas were increased in obese-hypoxic mice. Thus, obesity exerts differential effects on lung adaptation to hypoxia, which paradoxically include not only adverse but also rather protective changes. These differences have a molecular basis in the lung proteome and may influence the pathogenesis of lung diseases. This should be taken into account for future individualized prevention and therapy.NEW & NOTEWORTHY An "obesity paradox" is discussed for pulmonary diseases. By linking lung proteome analyses to pulmonary structure and function, we demonstrate that diet-induced obesity affects lung adaptation to chronic hypoxia in various ways. The observed changes include not only adverse but also protective effects and are associated with altered abundances of vascular and extracellular matrix proteins. These results highlight the existence of relevant differences in individuals with obesity that may influence the pathogenesis of lung diseases.

SARS-CoV-2 3D database: understanding the coronavirus proteome and evaluating possible drug targets.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a rapidly growing infectious disease, widely spread with high mortality rates. Since the release of the SARS-CoV-2 genome sequence in March 2020, there has been an international focus on developing target-based drug discovery, which also requires knowledge of the 3D structure of the proteome. Where there are no experimentally solved structures, our group has created 3D models with coverage of 97.5% and characterized them using state-of-the-art computational approaches. Models of protomers and oligomers, together with predictions of substrate and allosteric binding sites, protein-ligand docking, SARS-CoV-2 protein interactions with human proteins, impacts of mutations, and mapped solved experimental structures are freely available for download. These are implemented in SARS CoV-2 3D, a comprehensive and user-friendly database, available at https://sars3d.com/. This provides essential information for drug discovery, both to evaluate targets and design new potential therapeutics.

Three alginate lyases provide a new gut Bacteroides ovatus isolate with the ability to grow on alginate.

Humans consume alginate in the form of seaweed, food hydrocolloids, and encapsulations, making the digestion of this mannuronic acid (M) and guluronic acid (G) polymer of key interest for human health. To increase knowledge on alginate degradation in the gut, a gene catalog from human feces was mined for potential alginate lyases (ALs). The predicted ALs were present in nine species of the Bacteroidetes phylum, of which two required supplementation of an endo-acting AL, expected to mimic cross-feeding in the gut. However, only a new isolate grew on alginate. Whole-genome sequencing of this alginate-utilizing isolate suggested that it is a new Bacteroides ovatus strain harboring a polysaccharide utilization locus (PUL) containing three ALs of families: PL6, PL17, and PL38. The BoPL6 degraded polyG to oligosaccharides of DP 1-3, and BoPL17 released 4,5-unsaturated monouronate from polyM. BoPL38 degraded both alginates, polyM, polyG, and polyMG, in endo-mode; hence, it was assumed to deliver oligosaccharide substrates for BoPL6 and BoPL17, corresponding well with synergistic action on alginate. BoPL17 and BoPL38 crystal structures, determined at 1.61 and 2.11 Å, respectively, showed (α/α)6-barrel + anti-parallel ß-sheet and (α/α)7-barrel folds, distinctive for these PL families. BoPL17 had a more open active site than the two homologous structures. BoPL38 was very similar to the structure of an uncharacterized PL38, albeit with a different triad of residues possibly interacting with substrate in the presumed active site tunnel. Altogether, the study provides unique functional and structural insights into alginate-degrading lyases of a PUL in a human gut bacterium.IMPORTANCEHuman ingestion of sustainable biopolymers calls for insight into their utilization in our gut. Seaweed is one such resource with alginate, a major cell wall component, used as a food hydrocolloid and for encapsulation of pharmaceuticals and probiotics. Knowledge is sparse on the molecular basis for alginate utilization in the gut. We identified a new Bacteroides ovatus strain from human feces that grew on alginate and encoded three alginate lyases in a gene cluster. BoPL6 and BoPL17 show complementary specificity toward guluronate (G) and mannuronate (M) residues, releasing unsaturated oligosaccharides and monouronic acids. BoPL38 produces oligosaccharides degraded by BoPL6 and BoPL17 from both alginates, G-, M-, and MG-substrates. Enzymatic and structural characterization discloses the mode of action and synergistic degradation of alginate by these alginate lyases. Other bacteria were cross-feeding on alginate oligosaccharides produced by an endo-acting alginate lyase. Hence, there is an interdependent community in our guts that can utilize alginate.

Serum proteomic identification and validation of two novel atherosclerotic aortic aneurysm biomarkers, profilin 1 and complement factor D.

BACKGROUND: Effective diagnostic biomarkers for aortic aneurysm (AA) that are detectable in blood tests are required because early detection and rupture risk assessment of AA can provide insights into medical therapy and preventive treatments. However, known biomarkers for AA lack specificity and reliability for clinical diagnosis. METHODS: We performed proteome analysis of serum samples from patients with atherosclerotic thoracic AA (TAA) and healthy control (HC) subjects to identify diagnostic biomarkers for AA. Serum samples were separated into low-density lipoprotein, high-density lipoprotein, and protein fractions, and the major proteins were depleted. From the proteins identified in the three fractions, we narrowed down biomarker candidates to proteins uniformly altered in all fractions between patients with TAA and HC subjects and evaluated their capability to discriminate patients with TAA and those with abdominal AA (AAA) from HC subjects using receiver operating characteristic (ROC) analysis. For the clinical validation, serum concentrations of biomarker candidates were measured in patients with TAA and AAA registered in the biobank of the same institute, and their capability for the diagnosis was evaluated. RESULTS: Profilin 1 (PFN1) and complement factor D (CFD) showed the most contrasting profiles in all three fractions between patients with TAA and HC subjects and were selected as biomarker candidates. The PFN1 concentration decreased, whereas the CFD concentration increased in the sera of patients with TAA and AAA when compared with those of HC subjects. The ROC analysis showed that these proteins could discriminate patients with TAA and AAA from HC subjects. In the validation study, these candidates showed significant concentration differences between patients with TAA or AAA and controls. PFN1 and CFD showed sufficient area under the curve (AUC) in the ROC analysis, and their combination further increased the AUC. The serum concentrations of PFN1 and CFD also showed significant differences between patients with aortic dissection and controls in the validation study. CONCLUSION: PFN1 and CFD are potential diagnostic biomarkers for TAA and AAA and measurable in blood samples; their diagnostic performance can be augmented by their combination. These biomarkers may facilitate the development of diagnostic systems to identify patients with AA.

Protein profiling of extracellular vesicles from iPSC-derived astrocytes of patients with ALS/PDC in Kii peninsula.

BACKGROUND: Amyotrophic lateral sclerosis/Parkinsonism-dementia complex in Kii peninsula, Japan (Kii ALS/PDC), is an endemic neurodegenerative disease whose causes and pathogenesis remain unknown. However, astrocytes in autopsied cases of Kii ALS/PDC show characteristic lesions. In addition, relationships between extracellular vesicles (EVs) and neurodegenerative diseases are increasingly apparent. Therefore, we focused on proteins in EVs derived from Kii ALS/PDC astrocytes in the present study. METHODS: Induced pluripotent stem cells (iPSCs) derived from three healthy controls (HCs) and three patients with Kii ALS/PDC were differentiated into astrocytes. EVs in the culture medium of astrocytes were collected and subjected to quantitative proteome analysis. RESULTS: Our proteome analysis reveals that EV-containing proteins derived from astrocytes of patients with Kii ALS/PDC show distinctive patterns compared with those of HCs. Moreover, EVs derived from Kii ALS/PDC astrocytes display increased proteins related to proteostasis and decreased proteins related to anti-inflammation. DISCUSSION: Proteins contained in EVs from astrocytes unveil protective support to neurons and may reflect the molecular pathomechanism of Kii ALS/PDC; accordingly, they may be potential biomarker candidates of Kii ALS/PDC.

The regulatory metabolic networks of the Brassica campestris L. hairy roots in response to cadmium stress revealed from proteome studies combined with a transcriptome analysis.

Brassica campestris L., a cadmium (Cd) hyperaccumulating herbaceous plant, is considered as a promising candidate for the bioremediation of Cd pollution. However, the molecular mechanisms regulating these processes remain unclear. The present work, using proteome studies combined with a transcriptome analysis, was carried out to reveal the response mechanisms of the hairy roots of Brassica campestris L. under Cd stress. Significant tissue necrosis and cellular damage occurred, and Cd accumulation was observed in the cell walls and vacuoles of the hairy roots. Through quantitative proteomic profiling, a total of 1424 differentially expressed proteins (DEPs) were identified, and are known to be enriched in processes including phenylalanine metabolism, plant hormone signal transduction, cysteine and methionine metabolism, protein export, isoquinoline alkaloid biosynthesis and flavone biosynthesis. Further studies combined with a transcriptome analysis found that 118 differentially expressed genes (DEGs) and their corresponding proteins were simultaneously up- or downregulated. Further Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analysis of the 118 shared DEGs and DEPs indicated their involvement in calcium, ROS and hormone signaling-mediated response, including regulation of carbohydrate and energy metabolism, biosynthesis of GSH, PCs and phenylpropanoid compounds that play vital roles in the Cd tolerance of Brassica campestris L. Our findings contribute to a better understanding of the regulatory networks of Brassica campestris L. under Cd stress, as well as provide valuable information on candidate genes (e.g., BrPAL, BrTAT, Br4CL, BrCDPK, BrRBOH, BrCALM, BrABCG1/2, BrVIP, BrGCLC, BrilvE, BrGST12/13/25). These results are of particular importance to the subsequent development of promising transgenic plants that will hyperaccumulate heavy metals and efficient phytoremediation processes.

Comparative proteome analysis identified CD44 as a possible serum marker for docetaxel resistance in castration-resistant prostate cancer.

Baseline or acquired resistance to docetaxel (DOC) represents a significant risk for patients with metastatic prostate cancer (PC). In the last years, novel therapy regimens have been approved providing reasonable alternatives for DOC-resistant patients making prediction of DOC resistance of great clinical importance. We aimed to identify serum biomarkers, which are able to select patients who will not benefit from DOC treatment. DOC-resistant PC3-DR and DU145-DR sublines and their sensitive parental cell lines (DU145, PC3) were comparatively analyzed using liquid chromatography-coupled tandem mass spectrometry (LC-MS/MS). Results were filtered using bioinformatics approaches to identify promising serum biomarkers. Serum levels of five proteins were determined in serum samples of 66 DOC-treated metastatic castration-resistant PC patients (mCRPC) using ELISA. Results were correlated with clinicopathological and survival data. CD44 was subjected to further functional cell culture analyses. We found at least 177 two-fold significantly overexpressed proteins in DOC-resistant cell lines. Our bioinformatics method suggested 11/177 proteins to be secreted into the serum. We determined serum levels of five (CD44, MET, GSN, IL13RA2 and LNPEP) proteins in serum samples of DOC-treated patients and found high CD44 serum levels to be independently associated with poor overall survival (p = 0.001). In accordance, silencing of CD44 in DU145-DR cells resulted in re-sensitization to DOC. In conclusion, high serum CD44 levels may help identify DOC-resistant patients and may thereby help optimize clinical decision-making regarding type and timing of therapy for mCRPC patients. In addition, our in vitro results imply the possible functional involvement of CD44 in DOC resistance.

Proteome profiling of enzalutamide-resistant cell lines and serum analysis identified ALCAM as marker of resistance in castration-resistant prostate cancer.

Enzalutamide (ENZA) is a frequently used therapy in metastatic castration-resistant prostate cancer (mCRPC). Baseline or acquired resistance to ENZA have been observed, but the molecular mechanisms of resistance are poorly understood. We aimed to identify proteins involved in ENZA resistance and to find therapy-predictive serum markers. We performed comparative proteome analyses on ENZA-sensitive parental (LAPC4, DuCaP) and -resistant prostate cancer cell lines (LAPC4-ENZA, DuCaP-ENZA) using liquid chromatography tandem mass spectrometry (LC-MS/MS). The top four most promising candidate markers were selected using bioinformatic approaches. Serum concentrations of selected markers (ALCAM, AGR2, NDRG1, IDH1) were measured in pretreatment samples of 72 ENZA-treated mCRPC patients using ELISA. In addition, ALCAM serum levels were measured in 101 Abiraterone (ABI) and 100 Docetaxel (DOC)-treated mCRPC patients' baseline samples. Results were correlated with clinical and follow-up data. The functional role of ALCAM in ENZA resistance was assessed in vitro using siRNA. Our proteome analyses revealed 731 significantly differentially abundant proteins between ENZA-sensitive and -resistant cells and our filtering methods identified four biomarker candidates. Serum analyses of these proteins revealed only ALCAM to be associated with poor patient survival. Furthermore, higher baseline ALCAM levels were associated with poor survival in ABI- but not in DOC-treated patients. In LAPC4-ENZA resistant cells, ALCAM silencing by siRNA knockdown resulted in significantly enhanced ENZA sensitivity. Our analyses revealed that ALCAM serum levels may help to identify ENZA- and ABI-resistant patients and may thereby help to optimize future clinical decision-making. Our functional analyses suggest the possible involvement of ALCAM in ENZA resistance.

Identification and validation of serum autoantibodies in children with B-cell acute lymphoblastic leukemia by serological proteome analysis.

BACKGROUND: B-cell acute lymphoblastic leukemia (B-ALL) is the most common malignancy of childhood. Even though significant progresses have been made in the treatment of B-ALL, some pediatric B-ALL have still poor prognosis. The identification of tumor autoantibodies may have utility in early cancer diagnosis and immunotherapy. In this study, we used serological proteome analysis (SERPA) to screen serum autoantibodies of pediatric B-ALL, aiming to contribute to the early detection of B-ALL in children. METHODS: The total proteins from three pooled B-ALL cell lines (NALM-6, REH and BALL-1 cells) were separated using two-dimensional gel electrophoresis (2-DE), which was followed by Western blot by mixed serum samples from children with B-ALL (n=20) or healthy controls (n=20). We analyzed the images of 2-D gel and Western blot by PDQuest software, and then identified the spots of immune responses in B-ALL samples compared with those in control samples. The proteins from spots were identified using mass spectrometry (MS). The autoantibodies against alpha-enolase (α-enolase) and voltage-dependent anion-selective channel protein 1 (VDAC1) were further validated in sera from another 30 children with B-ALL and 25 normal individuals by the use of enzyme-linked immunosorbent assay (ELISA). The protein expression levels of the candidate antigens α-enolase and VDAC1 in B-ALL were thoroughly studied by immunohistochemical analysis. RESULTS: Utilizing the SERPA approach, α-enolase and VDAC1 were identified as candidate autoantigens in children with B-ALL. The frequencies of autoantibodies against α-enolase and VDAC1 in children with B-ALL were 27% and 23% by using ELISA analysis, respectively, which were significantly higher than those in normal controls (4% and 0, p<0.05). Immunohistochemical analysis showed the expression of α-enolase and VDAC1 was positive in 95% and 85% of B-ALL patients, respectively, but negative expression levels were showed in the control group. CONCLUSIONS: This study incidated that α-enolase and VDAC1 may be the autoantigens associated with B-ALL. Therefore, α-enolase and VDAC1 autoantibodies may be the potential serological markers for children with B-ALL.

Molecular Dynamics Simulation-assisted Ionic Liquid Screening for Deep Coverage Proteome Analysis.

In-depth coverage of proteomic analysis could enhance our understanding to the mechanism of the protein functions. Unfortunately, many highly hydrophobic proteins and low-abundance proteins, which play critical roles in signaling networks, are easily lost during sample preparation, mainly attributed to the fact that very few extractants can simultaneously satisfy the requirements on strong solubilizing ability to membrane proteins and good enzyme compatibility. Thus, it is urgent to screen out ideal extractant from the huge compound libraries in a fast and effective way. Herein, by investigating the interior mechanism of extractants on the membrane proteins solubilization and trypsin compatibility, a molecular dynamics simulation system was established as complement to the experimental procedure to narrow down the scope of candidates for proteomics analysis. The simulation data shows that the van der Waals interaction between cation group of ionic liquid and membrane protein is the dominant factor in determining protein solubilization. In combination with the experimental data, 1-dodecyl-3-methylimidazolium chloride (C12Im-Cl) is on the shortlist for the suitable candidates from comprehensive aspects. Inspired by the advantages of C12Im-Cl, an ionic liquid-based filter-aided sample preparation (i-FASP) method was developed. Using this strategy, over 3,300 proteins were confidently identified from 103 HeLa cells (∼100 ng proteins) in a single run, an improvement of 53% over the conventional FASP method. Then the i-FASP method was further successfully applied to the label-free relative quantitation of human liver cancer and para-carcinoma tissues with obviously improved accuracy, reproducibility and coverage than the commonly used urea-based FASP method. The above results demonstrated that the i-FASP method could be performed as a versatile tool for the in-depth coverage proteomic analysis of biological samples.

Conditioned Medium of Human Pluripotent Stem Cell-Derived Neural Precursor Cells Exerts Neurorestorative Effects against Ischemic Stroke Model.

Previous studies have shown that early therapeutic events of neural precursor cells (NPCs) transplantation to animals with acute ischemic stroke readily protected neuronal cell damage and improved behavioral recovery through paracrine mechanisms. In this study, we tested the hypothesis that administration of conditioned medium from NPCs (NPC-CMs) could recapitulate the beneficial effects of cell transplantation. Rats with permanent middle cerebral artery occlusion (pMCAO) were randomly assigned to one of the following groups: PBS control, Vehicle (medium) controls, single (NPC-CM(S)) or multiple injections of NPC-CM(NPC-CM(M)) groups. A single intravenous injection of NPC-CM exhibited strong neuroregenerative potential to induce behavioral recovery, and multiple injections enhanced this activity further by suppressing inflammatory damage and inducing endogenous neurogenesis leading to histopathological and functional recovery. Proteome analysis of NPC-CM identified a number of proteins that are known to be associated with nervous system development, neurogenesis, and angiogenesis. In addition, transcriptome analysis revealed the importance of the inflammatory response during stroke recovery and some of the key hub genes in the interaction network were validated. Thus, our findings demonstrated that NPC-CM promoted functional recovery and reduced cerebral infarct and inflammation with enhanced endogenous neurogenesis, and the results highlighted the potency of NPC-CM in stroke therapy.

The Role of Type VI Collagen in Alveolar Bone.

Many studies have been conducted to elucidate the role of Type VI collagen in muscle and tendon, however, its role in oral tissues remains unclear. In this study, an α2(VI) deficient mouse (Col6α2-KO) model was used to examine the role of Type VI collagen in oral tissues. Tissue volume and mineral density were measured in oral tissues by µCT. Proteome analysis was performed using protein extracted from alveolar bone. In addition, alveolar bone was evaluated with a periodontitis induced model. µCT analysis showed the Col6α2-KO mice had less volume of alveolar bone, dentin and dental pulp, while the width of periodontal ligament (PDL) was greater than WT. The mineral density in alveolar bone and dentin were elevated in Col6α2-KO mice compared with WT. Our proteome analysis showed significant changes in proteins related to ECM organization and elevation of proteins associated with biomineralization in the Col6α2-KO mice. In induced periodontitis, Col6α2-KO mice had greater alveolar bone loss compared with WT. In conclusion, Type VI collagen has a role in controlling biomineralization in alveolar bone and that changes in the ECM of alveolar bone could be associated with greater bone loss due to periodontitis.

Proteomic Analysis Revealed Different Molecular Mechanisms of Response to PEG Stress in Drought-Sensitive and Drought-Resistant Sorghums.

Drought is the major limiting factor that directly or indirectly inhibits the growth and reduces the productivity of sorghum (Sorghum bicolor (L.) Moench). As the main vegetative organ of sorghum, the response mechanism of the leaf to drought stress at the proteomic level has not been clarified. In the present study, nano-scale liquid chromatography mass spectrometry (nano-LC-MS/MS) technology was used to compare the changes in the protein expression profile of the leaves of drought-sensitive (S4 and S4-1) and drought-resistant (T33 and T14) sorghum varieties at the seedling stage under 25% PEG-6000 treatment for 24 h. A total of 3927 proteins were accurately quantitated and 46, 36, 35, and 102 differentially abundant proteins (DAPs) were obtained in the S4, S4-1, T14, and T33 varieties, respectively. Four proteins were randomly selected for parallel reaction monitoring (PRM) assays, and the results verified the reliability of the mass spectrometry (MS) results. The response mechanism of the drought-sensitive sorghum leaves to drought was attributed to the upregulation of proteins involved in the tyrosine metabolism pathway with defense functions. Drought-resistant sorghum leaves respond to drought by promoting the TCA cycle, enhancing sphingolipid biosynthesis, interfering with triterpenoid metabolite synthesis, and influencing aminoacyl-tRNA biosynthesis. The 17 screened important candidate proteins related to drought stress were verified by quantitative real-time PCR (qRT-PCR), the results of which were consistent with the results of the proteomic analysis. This study lays the foundation for revealing the drought-resistance mechanism of sorghum at the protein level. These findings will help us cultivate and improve new drought-resistant sorghum varieties.