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PubMed2026

Transcriptome-Proteome Analysis of Human Naive and Memory B Cell Subsets Reveals Isotype and Subclass-Specific Phenotypes.

Antibodies produced by B cells aid in the recognition and clearance of pathogens and are the cornerstone of vaccination strategies. Humans produce nine different antibody isotypes, and their effector functions differ according to the type of antigen and route of exposure. Phenotypic variation between isotype-switched B cell subsets is expected but not studied in detail. To obtain a molecular definition of isotype-defined cell identity, we performed proteomics and transcriptomics on isotype-defined populations of human naive and memory B cells (MBCs): CD27-IgM+IgD+, CD27+CD38lo/-IgM+IgD+, CD27+CD38lo/-IgM+IgD-, and IgA1, IgA2, IgG1, IgG2, IgG3, and IgG4 MBCs (CD27+CD38lo/-Ig+). Combined proteome and transcriptome analysis revealed that mRNA and protein expression profiles separate isotype-defined B cell subsets according to their differentiation status. mRNA and protein expression levels correlated reasonably well for many genes. IgG4-switched B cells were most distinct from naive B cells in terms of mRNA as well as protein expression profiles. Besides a distinct expression profile of cytokine and Fc receptors, we identified a high expression of IgE-coding mRNA in IgG4-switched B cells. SDR16C5 was identified as uniquely upregulated in IgG4-switched B cells. Taken together, this study highlights the distinct phenotypic profile of IgG4-switched B cells.

Humans↗
PubMed2026

Elucidating the In Vitro Adverse Effect of Functionalized Single-Walled Carbon Nanotubes Against Breast Cancer Cells at the Proteomics Level.

The tremendous therapeutic potential of carbon-based nanomaterials (CNMs) has been limited by inconsistent data regarding the nanotoxicity assessment. Although a bulk of studies have been performed to assess the in vitro cytotoxicity mechanism of CNMs, the exact factors responsible for the cytotoxicity of CNMs have not been fully understood. With the rapid advancement of mass spectrometry technologies, proteomics has emerged as a powerful strategy for systematically investigating the molecular and cellular mechanisms underlying toxicity induced by nanomaterials. This study examined the in vitro cytotoxicity of single-walled carbon nanotubes (SWCNTs) in human MCF-7 breast cancer cells by conducting a comparative proteome-level analysis using mass spectrometry. Initially, the characterized SWCNTs were incubated with MCF-7 cells for 3, 6, and 24 h. Proteins were subsequently extracted from each treatment group and subjected to nano-liquid chromatography-tandem mass spectrometry (nLC-MS/MS) analysis. The relative abundance of the identified proteins was determined by comparison with the control group, and differential expression patterns, including upregulated and downregulated proteins, were assessed. A total of 3482 unique protein groups were identified across all exposure periods. Among these, 3466 protein groups were detected following 3 h of exposure, 3469 following 6 h of exposure, and 3480 following 24 h of exposure. Compared with the control group, the identified differentially expressed proteins exhibited fold changes ranging from 2-fold to 20-fold across the incubation periods. In total, 70 proteins were found to be significantly regulated following SWCNT exposure. Of the differentially expressed proteins, 45 were significantly upregulated, whereas 25 were significantly downregulated. Visualization of these regulations over time was shown in a heatmap of log2-transformed fold-change values to explore time-specific proteomic alterations. Functional enrichment analysis of these proteins also showed that the regulated proteins were significantly associated with Reactome pathways, including ER-to-Golgi anterograde transport, Golgi-to-ER retrograde transport, COPI-mediated vesicle trafficking, regulation of insulin-like growth factor transport and uptake by insulin-like growth factor-binding proteins, protein metabolism, and posttranslational protein modification. Furthermore, a systematic comparison of previous studies within the present findings was provided to situate our study within the broader context of understanding CNT-induced cellular toxicity. Collectively, these findings provided an important proteomic evidence of the adverse effects of SWCNTs on MCF-7 cells. Furthermore, this study showed a comprehensive proteomic landscape of cellular responses to SWCNT exposure, contributing to a better understanding of the molecular mechanisms underlying SWCNT-induced cytotoxicity and bridging the gap between protein regulation and the resulting cellular responses. In this study, we characterized the proteomic landscape of MCF-7 cells following SWCNT exposure, revealing molecular mechanisms associated with cellular responses and cytotoxicity. The identified differentially expressed proteins established a link between altered protein regulation and SWCNT-induced cellular effects. Moreover, these proteins need to be further validated in different cell models and would potentially represent promising candidates for the identification of novel molecular targets involved in SWCNT-induced cytotoxicity.

MCF‐7 cells↗
PubMed2004

Cellular and physiological effects of short-chain fatty acids.

Short chain fatty acids (SCFA) have multiple in vivo and in vitro effects including cell cycle arrest and induction of protein synthesis, differentiation, and apoptosis. Butyrate or derivatives have promise for treating inflammatory bowel disease and colon cancer. Genomic and proteomic analysis have generated new knowledge on function and applications for SCFA.

Animals↗
PubMed2006

Proteomic analysis of rat hippocampal plasma membrane: characterization of potential neuronal-specific plasma membrane proteins.

The hippocampus is a distinct brain structure that is crucial in memory storage and retrieval. To identify comprehensively proteins of hippocampal plasma membrane (PM) and detect the neuronal-specific PM proteins, we performed a proteomic analysis of rat hippocampus PM using the following three technical strategies. First, proteins of the PM were purified by differential and density-gradient centrifugation from hippocampal tissue and separated by one-dimensional electophoresis, digested with trypsin and analyzed by electrospray ionization (ESI) quadrupole time-of-flight (Q-TOF) tandem mass spectrometry (MS/MS). Second, the tryptic peptide mixture from PMs purified from hippocampal tissue using the centrifugation method was analyzed by liquid chromatography ion-trap ESI-MS/MS. Finally, the PM proteins from primary hippocampal neurons purified by a biotin-directed affinity technique were separated by one-dimensional electrophoresis, digested with trypsin and analyzed by ESI-Q-TOF-MS/MS. A total of 345, 452 and 336 non-redundant proteins were identified by each technical procedure respectively. There was a total of 867 non-redundant protein entries, of which 64.9% are integral membrane or membrane-associated proteins. One hundred and eighty-one proteins were detected only in the primary neurons and could be regarded as neuronal PM marker candidates. We also found some hypothetical proteins with no functional annotations that were first found in the hippocampal PM. This work will pave the way for further elucidation of the mechanisms of hippocampal function.

Animals↗
PubMed2006

Proteomic profiling of rat bone marrow mesenchymal stem cells induced by 5-azacytidine.

Mesenchymal stem cells (MSCs) can differentiate into different types of cells and thus have tremendous potential for cell therapy and tissue engineering. 5-Azacytidine (5-aza), a DNA demethylation reagent, has been reported to induce MSCs to differentiate into cardiomyocytes in vitro. To determine a global effect of 5-aza on MSCs, we investigated the protein expressions of rat MSCs with two-dimensional gel electrophoresis (2-DE). We have generated a proteome reference map of rat MSCs, and have successfully identified 34 proteins with MALDI-TOF-MS analysis. Nine proteins showed distinct regulation in MSCs after 5-aza treatment. The proteins regulated by 5-aza included cytoskeletal proteins, cadmium-binding proteins, and metabolic proteins, etc. These proteins have been reported to be involved in cell proliferation and differentiation through different signaling pathways, and the molecular mechanism of MSCs differentiation is discussed at the proteome level.

Animals↗
PubMed2006

Proteomic analysis of the transition from quiescent to proliferating stages in rat liver hepatectomy model.

The 70% (or 2/3) partial hepatectomy (PHx) rat liver model provides an effective medium for study of the transition and regulation of hepatocytes from quiescent to proliferating phase. Although the gene expression pattern has come under intense scrutiny, a differential proteomic study could help to reveal the mechanism of how the process is initiated and regulated. The proteomic changes were analyzed in two groups, 7 h after 70% PHx test group and sham-operation control group, by two-dimensional gel electrophoresis with 907 +/- 33 and 910 +/- 64 spots on gels, respectively. Twelve down-regulated spots and twenty-six up-regulated spots were recognized using ImageMaster software and were identified by matrix-assisted laser desorption/ionization-mass spectrometry-quadrupole time of flight mass spectrometry and/or tandem mass spectrometry reconfirmation. Some of the differential proteins were associated with stress defense, lipid metabolism, and macromolecular biosynthesis while the others were shown to be involved in regulating transcript factors associated with liver regeneration. A "proteomic model" for liver regeneration was suggested based on our data and related scientific literature to interpret the differential proteome pattern that reflected the transition of cells from quiescent to proliferating state, including but not limited to the rat liver after 70% PHx.

Animals↗
PubMed2025

Integrative metabolomic and proteomic analysis of diabetic kidney disease progression with younger-onset type 2 diabetes.

AIM: Younger-onset type 2 diabetes (YT2D) confers a disproportionately high risk of diabetic kidney disease (DKD), yet early biomarkers and underlying mechanisms remain poorly defined. We aimed to identify metabolites associated with DKD progression and integrate metabolomic and proteomic data to elucidate pathways involved in a multi-ethnic Asian cohort. MATERIALS AND METHODS: In this prospective study, 787 YT2D patients (diagnosed at ≤ age 40) were followed for a median of 5.7 years. DKD progression was defined as an annual decline in estimated glomerular filtration rate (eGFR) of ≥3 mL/min/1.73 m2 or ≥ 40% reduction in eGFR from baseline. Plasma metabolites were measured by nuclear magnetic resonance spectroscopy. Multivariable regression analysis was performed in a discovery (N = 550) and internal validation cohort (N = 237). Integrative metabolomic-proteomic analysis (N = 428) was performed using sparse partial least squares discriminant analysis (sPLS-DA). RESULTS: Ninety-eight metabolites were differentially expressed between DKD progressors and non-progressors, of which total branched-chain amino acids (BCAAs) (OR = 0.60, 95% CI 0.46-0.79), valine (OR = 0.62, 95% CI 0.48-0.81), and leucine (OR = 0.56, 95% CI 0.43-0.74) associated with DKD progression, independent of metabolic risk factors. Integrative analysis identified three components comprising 23 proteins and 30 metabolites, involved in the citrate cycle and apoptosis, which improved prediction of DKD progression beyond clinical risk factors (AUC 0.69-0.83). CONCLUSION: Lower plasma BCAA levels are independently associated with DKD progression in YT2D. Integrative multi-omics analysis highlights disruptions in metabolic and apoptotic pathways, providing insights into DKD pathophysiology and potential biomarkers for early risk stratification.

Humans↗
PubMed2001

Proteomic analysis of the brain in Alzheimer's disease: molecular phenotype of a complex disease process.

Alzheimer's disease (AD) is a progressive neurodegenerative disorder accounting for about 50% of all dementias, yet its pathogenic mechanisms remain poorly understood. In order to provide a more complete picture of pathogenesis in AD, we analysed six human brain regions for alterations in their proteomes. Quantitative proteome analysis was used to compare signals corresponding to individual proteins between post mortem brain tissues from persons with AD, and those from age-matched nondemented control (NC) tissues. In severely injured brain regions, 76 proteins were differentially expressed in AD hippocampus compared with NC, 62 proteins were differentially expressed in temporal cortex, and 39 proteins were differentially expressed in entorhinal cortex. Significant differences were also present in relatively spared regions. Thus, 34 proteins were differentially expressed in AD cerebellum compared with NC, 125 proteins were differentially expressed in cingulate gyrus, and 75 proteins were differentially expressed in sensorimotor cortex. The identity of 37 of these proteins was determined, and the possible relevance of changes in key pathogenic pathways analysed. These studies provide a unique snapshot illustrating the complexity of interrelated disease mechanisms at work in a complex, multifactorial disease, and show that comparative proteome analysis is a method with the power to develop important new insights into pathogenic mechanisms in the dementias.

Alzheimer Disease↗
PubMed2005

A genomic and proteomic study of the spectrum of nonalcoholic fatty liver disease.

Nonalcoholic fatty liver disease (NAFLD) is the most common chronic liver disease, and some of its forms are progressive. This study describes the profiling of hepatic gene expression and serum protein content in patients with different subtypes of NAFLD. Liver biopsy specimens from 98 bariatric surgery patients were classified as normal, steatosis alone, steatosis with nonspecific inflammation, and nonalcoholic steatohepatitis (NASH). Microarray hybridizations were performed in triplicate and the microarray expression levels of a selected group of genes were confirmed using real-time quantitative reverse-transcriptase polymerase chain reaction. Serum protein profiles of the same patients were determined by SELDI-TOF mass spectrometry. Of 98 obese patients, 91 were diagnosed with NAFLD (12 steatosis alone, 52 steatosis with nonspecific inflammation, and 27 NASH), and 7 patients without NAFLD served as obese controls. Each group of NAFLD patients was compared with the obese controls, and 22 genes with more than twofold differences in expression levels were revealed. Proteomics analyses were performed for the same group comparisons and revealed twelve significantly different protein peaks. In conclusion, this genomic/proteomic analysis suggests differential expression of several genes and protein peaks in patients within and across the forms of NAFLD. These findings may help clarify the pathogenesis of NAFLD and identify potential targets for therapeutic intervention.

Adult↗
PubMed2002

Differential protein expression at the stage of neural tube closure in the mouse embryo.

Analysis of the protein complement of a biological system through proteomics provides the opportunity to directly monitor the functional readout of gene expression. In this study, proteomics was applied to the mouse embryo to investigate the molecular events underlying the processes occurring at the stage of neural tube closure. Protein profiles of embryos between embryonic days 8.5 and 10.5 exhibited a number of stage-specific changes. Identification of developmentally regulated proteins by mass spectrometry revealed several groups of functionally related proteins including circulatory, cytoskeletal, and stress proteins. Additional proteins of unknown function were identified, such as Copine 1 and PICOT, whose developmental regulation was previously unsuspected.

Animals↗
PubMed2005

Integrative genomic and proteomic analysis of prostate cancer reveals signatures of metastatic progression.

Molecular profiling of cancer at the transcript level has become routine. Large-scale analysis of proteomic alterations during cancer progression has been a more daunting task. Here, we employed high-throughput immunoblotting in order to interrogate tissue extracts derived from prostate cancer. We identified 64 proteins that were altered in prostate cancer relative to benign prostate and 156 additional proteins that were altered in metastatic disease. An integrative analysis of this compendium of proteomic alterations and transcriptomic data was performed, revealing only 48%-64% concordance between protein and transcript levels. Importantly, differential proteomic alterations between metastatic and clinically localized prostate cancer that mapped concordantly to gene transcripts served as predictors of clinical outcome in prostate cancer as well as other solid tumors.

Disease Progression↗
PubMed2006

Mass spectrometry-based study of the plasma proteome in a mouse intestinal tumor model.

Early detection of cancer can greatly improve prognosis. Identification of proteins or peptides in the circulation, at different stages of cancer, would greatly enhance treatment decisions. Mass spectrometry (MS) is emerging as a powerful tool to identify proteins from complex mixtures such as plasma that may help identify novel sets of markers that may be associated with the presence of tumors. To examine this feature we have used a genetically modified mouse model, Apc(Min), which develops intestinal tumors with 100% penetrance. Utilizing liquid chromatography-tandem mass spectrometry (LC-MS/MS), we identified total plasma proteome (TPP) and plasma glycoproteome (PGP) profiles in tumor-bearing mice. Principal component analysis (PCA) and agglomerative hierarchial clustering analysis revealed that these protein profiles can be used to distinguish between tumor-bearing Apc(Min) and wild-type control mice. Leave-one-out cross-validation analysis established that global TPP and global PGP profiles can be used to correctly predict tumor-bearing animals in 17/19 (89%) and 19/19 (100%) of cases, respectively. Furthermore, leave-one-out cross-validation analysis confirmed that the significant differentially expressed proteins from both the TPP and the PGP were able to correctly predict tumor-bearing animals in 19/19 (100%) of cases. A subset of these proteins was independently validated by antibody microarrays using detection by two color rolling circle amplification (TC-RCA). Analysis of the significant differentially expressed proteins indicated that some might derive from the stroma or the host response. These studies suggest that mass spectrometry-based approaches to examine the plasma proteome may prove to be a valuable method for determining the presence of intestinal tumors.

Animals↗
PubMed2026

hypeR-GEM: connecting metabolite signatures to enzyme-coding genes via genome-scale metabolic models.

MOTIVATION: Enrichment analysis is a cornerstone of "omics" data interpretation, enabling researchers to connect analysis results to biological processes and generate testable hypotheses. Enrichment analysis in metabolomics poses distinct challenges for interpretation and multi-omics integration due to the lack of well-defined and consistent connections to well-curated gene-centered biological knowledge repositories. To address these challenges, we developed hypeR-GEM, a methodology and associated R package that adapts gene set enrichment analysis to metabolomics. hypeR-GEM leverages genome-scale metabolic models (GEMs) to infer reaction-based links between metabolites and enzyme-coding genes, enabling the mapping of metabolite signatures to gene signatures and their subsequent annotation via gene set enrichment analysis. RESULTS: We validated hypeR-GEM using paired metabolomics-proteomics and metabolomics-transcriptomics datasets by assessing whether genes mapped from metabolites significantly overlapped with differentially expressed proteins or transcripts. We further evaluated whether pathways enriched via hypeR-GEM-mapped genes corresponded to those derived from paired proteomic or transcriptomic data. In most datasets analyzed, both the predicted enzyme-coding genes and the associated enriched pathways showed significant concordance with independently derived omics signatures, supporting the utility and robustness of hypeR-GEM. Finally, we applied hypeR-GEM to the analysis of age-associated metabolic signatures from the New England Centenarian Study. The results revealed consistent enrichment of lipid-related pathways, aligning with the well-established role of lipid metabolism in aging, and highlighted additional pathways not captured in the metabolites' annotation, demonstrating hypeR-GEM's practical utility in a real-world use case. AVAILABILITY AND IMPLEMENTATION: The hypeR-GEM R package, documentation, and workflow examples are freely available at https://github.com/montilab/hypeR-GEM and archived at https://doi.org/10.5281/zenodo.20586748.

Metabolomics↗
PubMed2025

Acoustic ejection mass spectrometry: the potential for personalized medicine.

INTRODUCTION: The emergence of personalized medicine (PM) has shifted the focus of healthcare from the traditional 'one-size-fits-all' approach to strategies tailored to individual patients, accounting for genetic, environmental, and lifestyle factors. Acoustic ejection mass spectrometry (AEMS) is a novel technology that offers a robust and scalable platform for high-throughput MS readout. AEMS achieves analytical speeds of one sample per second while maintaining high data quality, broad compound coverage, and minimal sample preparation, making it an invaluable tool for PM. AREAS COVERED: This article explores the potential of AEMS in critical PM applications, including therapeutic drug monitoring (TDM), proteomics, metabolomics, and mass spectrometry imaging. AEMS simplifies conventional workflows by minimizing sample preparation, enhancing automation compatibility, and enabling direct analysis of complex biological matrices. EXPERT OPINION: Integrating AEMS with orthogonal separation techniques such as differential mobility spectrometry (DMS) further addresses challenges in isomer discrimination, expanding the platform's analytical capabilities. Additionally, the development of high-throughput data processing tools could further enable AEMS to accelerate the development of personalized medicine.

Humans↗
PubMed2004

A high-throughput approach for subcellular proteome: identification of rat liver proteins using subcellular fractionation coupled with two-dimensional liquid chromatography tandem mass spectrometry and bioinformatic analysis.

Four fractions from rat liver (a crude mitochondria (CM) and cytosol (C) fraction obtained with differential centrifugation, a purified mitochondrial (PM) fraction obtained with nycodenz density gradient centrifugation, and a total liver (TL) fraction) were analyzed with two-dimensional liquid chromatography tandem mass spectrometry analysis. A total of 564 rat proteins were identified and were bioinformatically annotated according to their physicochemical characteristics and functions. While most extreme alkaline ribosomal proteins were identified in the TL fraction, the C fraction mainly included neutral enzymes and the PM fraction enriched alkaline proteins and proteins with electron transfer activity or oxygen binding activity. Such characteristics were more apparent in proteins identified only in the TL, C, or PM fraction. The Swiss-Prot annotation and the bioinformatic prediction results proved that the C and PM fractions had enriched cytoplasmic or mitochondrial proteins, respectively. Combination usage of subcellular fractionation with two-dimensional liquid chromatography tandem mass spectrometry was proved to be a high-throughput, sensitive, and effective analytical approach for subcellular proteomics research. Using such a strategy, we have constructed the largest proteome database to date for rat liver (564 rat proteins) and its cytosol (222 rat proteins) and mitochondrial fractions (227 rat proteins). Moreover, the 352 proteins with Swiss-Prot subcellular location annotation in the 564 identified proteins were used as an actual subcellular proteome dataset to evaluate the widely used bioinformatics tools such as PSORT, TargetP, TMHMM, and GRAVY.

Animals↗
PubMed2005

Proteome analysis of skin distinguishes acute guttate from chronic plaque psoriasis.

Psoriasis is a disease with considerable heterogeneity in clinical presentation. This is the first study using two-dimensional gel electrophoresis to compare global protein expression patterns in lesional and non-lesional skin from subjects with acute guttate psoriasis associated with streptococcal throat infection and chronic plaque psoriasis. Samples from experimentally induced contact eczema and normal skin from healthy controls were also included. Proteins with statistically significant differences in expression were used in hierarchical cluster analyses resulting in separation of the different samples into groups. Chronic plaque and guttate psoriasis samples were distinctly separated, indicating that they represent discrete phenotypes at the protein expression level. Interestingly, there was a trend in which guttate psoriasis lesions clustered closer to eczema than to chronic plaque psoriasis lesions, indicating that the duration of the inflammatory reaction may affect clustering. Several of the differentially expressed proteins were identified by mass spectrometry.

Acute Disease↗
PubMed2003

Proteomic approach to coronary atherosclerosis shows ferritin light chain as a significant marker: evidence consistent with iron hypothesis in atherosclerosis.

Coronary artery disease (CAD) is the leading cause of mortality and morbidity in developed nations. We hypothesized that CAD is associated with distinct patterns of protein expression in the coronary arteries, and we have begun to employ proteomics to identify differentially expressed proteins in diseased coronary arteries. Two-dimensional (2-D) gel electrophoresis of proteins and subsequent mass spectrometric analysis identified the ferritin light chain as differentially expressed between 10 coronary arteries from patients with CAD and 7 coronary arteries from normal individuals. Western blot analysis indicated significantly increased expression of the ferritin light chain in the diseased coronary arteries (1.41 vs. 0.75; P = 0.01). Quantitative real-time PCR analysis showed that expression of ferritin light chain mRNA was decreased in diseased tissues (0.70 vs. 1.17; P = 0.013), suggesting that increased expression of ferritin light chain in CAD coronary arteries may be related to increased protein stability or upregulation of expression at the posttranscriptional level in the diseased tissues. Ferritin light chain protein mediates storage of iron in cells. We speculate that increased expression of the ferritin light chain may contribute to pathogenesis of CAD by modulating oxidation of lipids within the vessel wall through the generation of reactive oxygen species. Our results provide in situ proteomic evidence consistent with the "iron hypothesis," which proposes an association between excessive iron storage and a high risk of CAD. However, it is also possible that the increased ferritin expression in diseased coronary arteries is a consequence, rather than a cause, of CAD.

Adult↗
PubMedDate not supplied

Application of proteomics technologies in the investigation of the brain.

Approximately 30-50% of the genes in mammals are expressed in the nervous system. A differential expression of genes in distinct patterns is necessary for the generation of the large variety of neuronal phenotypes. Proteomic analysis of brain compartments may be useful to understand the complexity, to investigate disorders of the central nervous system, and to search for corresponding early markers. Up to now, proteomics has mainly studied the identity and levels of the abundant human, rat, and mouse brain proteins as well as changes of their levels and the modifications that result from various neurological disorders, like Alzheimer's disease and Down's syndrome in humans and in animal models of those diseases. The proteins, for which altered levels in these disorders have been observed, exert mainly neurotransmission, guidance, and signal-transduction functions, or are involved in detoxification, metabolism, and conformational changes. Some of those proteins may be potential drug targets. Further improvement of proteomics technologies to increase sensitivity and efficiency of detection of certain protein classes is necessary for a more detailed analysis of the brain proteome. In this review, a description of the proteomics technologies applied in the investigation of the brain, the major findings that resulted from their application, and the potential and limitations of the current technologies are discussed.

Animals↗