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Coral color morphs exhibit distinct microbial and proteomic profiles linked to stress and immune mechanisms in a changing ocean.

BACKGROUND: Coral phenotypic plasticity facilitates acclimation and adaptation to environmental variability. Coral species often display a variety of color morphs, yet key biological and ecological implications of such phenotypic variation remain underexplored. Here, we present the first proteomic and untargeted lipidomic and metabolomic survey to explore the biological characteristics and potential ecological significance of different color morphs (pink and brown) of healthy Pocillopora verrucosa sampled along a latitudinal gradient. RESULTS: Our multi-omic approach elucidated distinct mechanisms associated with these dominant color morphs. We discovered bacterial indicators specific to each morph: putative pathogens such as Salmonella, Escherichia-Shigella, and carotenoid-producing Gemmatimonas were notably associated with the pink morph, whereas the brown morph was associated with potentially beneficial bacteria, such as Lysobacter, Acinetobacter, and Endozoicomonas. Despite these microbiome differences, the lipidome and metabolome of P. verrucosa were surprisingly homogeneous across colors and locations, suggesting similar metabolic performances during summer conditions. Key polar and apolar lipid classes, such as fatty acids, glycerophosphocholines, and retinoids, were prevalent. Notably, our proteomic analysis revealed morph-specific expressions, with pink morphs exhibiting enhanced levels of GFP-like proteins, Ankyrin, and the enzyme pullulanase, suggesting novel putative protective roles. In contrast, the brown morphs showed a higher abundance of heat shock proteins, indicating putative differential stress response capabilities. CONCLUSION: This comprehensive study provides the first proteomic survey of P. verrucosa and identifies key physiological pathways and trade-offs linked to color morphs, which can further contribute to enhancing our understanding of coral resilience in the face of climate change. SIGNIFICANCE STATEMENT: Understanding the phenotypic plasticity of corals is crucial for uncovering mechanisms of resilience in warming oceans, yet the biological significance of coral color morphs still needs to be explored. Using an innovative multi-omic approach (proteomics, lipidomics, and metabolomics), we provide the first comprehensive analysis of differences between pink and brown morphs of Pocillopora verrucosa. Our data reveal key taxa, potentially pathogenic or beneficial, associated with each morph, and suggest different strategies for each color morph to cope with heat stress, either expressing proteins involved in UV protection and heterotrophic activity or enhanced levels of heat stress resilience and DNA repair. These findings offer insights into the phenotypic plasticity of coral color morphs and their differential responses to climate change. Video Abstract.

Anthozoa↗

Proteomic analysis of MCF-7 cell lines expressing the zinc-finger or the proline-rich domain of retinoblastoma-interacting-zinc-finger protein.

To identify a growth-promoting activity related to retinoblastoma-interacting-zinc-finger (RIZ) protein, differential protein expression of MCF-7 cell lines expressing the zinc-finger or the proline-rich domain of RIZ protein was analyzed by a robust bottom-up mass-spectrometry proteomic approach. Spots corresponding to qualitative and quantitative differences in protein expression have been selected and identified. Some of these proteins have been previously reported as being associated with different types of carcinomas or involved in cell proliferation and differentiation. Knowledge of specific differentially expressed proteins by MCF-7-derived cell lines expressing RIZ different domains will provide the basis for identifying a growth-promoting activity related to RIZ gene products.

Biomarkers, Tumor↗

A Study on Differential Proteomics in Differentiated Gastric Adenocarcinoma With Low-grade Atypia Based on Paraffin-embedded Tissues.

In this study, we analyzed and characterized differentially expressed proteins in differentiated gastric adenocarcinoma with low-grade atypia for screening potential protein markers. We collected gastric tissue specimens from 90 patients treated at the Pathology Department of the First People's Hospital of Yunnan Province, China, between January 2019 and December 2022. These specimens had been fixed in 10% neutral-buffered formalin and embedded in paraffin. We classified these samples into 3 groups: the control group (normal gastric mucosa), the low-grade atypia group (differentiated gastric adenocarcinoma with low-grade atypia), and the high-grade atypia group (differentiated gastric adenocarcinoma with high-grade atypia), consisting of 30 cases in each group. We analyzed differential proteomes with the data-independent acquisition-mass spectrometry (DIA-MS) methodology and selected 4 differentially expressed proteins that were subjected to immunohistochemistry (IHC) staining for validation. A total of 4406 proteins were identified, among which 598 and 357 proteins were statistically different in the low-grade atypia group as compared with the control group and the high-grade atypia group, respectively. IHC staining showed that the expression of FHL3, CSRP2, and FCGR3A was significantly higher in the low-grade atypia group than in the control group ( P <0.05) and significantly higher in the high-grade atypia group than in the low-grade atypia group ( P <0.05). FHL2 expression was negative to weakly positive in the control and low-grade atypia groups and not significantly different between the 2 groups, whereas FHL2 expression in the high-grade atypia group was significantly higher than in the control and low-grade atypia groups ( P <0.05). Proteomic analysis is helpful for discovering new protein markers. Using a combination of FHL3, CSRP2, and FCGR3A can increase the accuracy of the pathologic diagnosis of differentiated gastric adenocarcinoma with low-grade atypia.

Humans↗

NR3C1 Modulates Wnt Signalling to Influence the Invasiveness and Immune Features of Nonfunctioning Invasive Pituitary Adenomas.

Pituitary adenomas (PAs) are common intracranial tumours, and invasiveness in nonfunctioning invasive pituitary adenomas (NIPAs) predicts poor prognosis. The molecular mechanisms driving this phenotype remain unclear. This study explored the role of nuclear receptor subfamily 3 group C member 1 (NR3C1) in NIPA invasiveness and its regulation of Wnt signalling. mRNA expression profiles of 32 PA samples were generated by RNA-seq, and proteomic data from 19 samples were obtained by mass spectrometry. Immune-related differentially expressed genes (DEGs) were retrieved from GeneCards. Weighted gene coexpression network analysis identified modules and hub genes linked to invasiveness, while machine learning methods (support vector machine, LASSO, random forest) prioritised key genes. Gene set enrichment analysis (GSEA) assessed pathways associated with candidate gene expression. NR3C1 expression and function were validated by immunohistochemistry, Western blotting and invasion assays. Integration of transcriptomic, proteomic and immune-related datasets yielded 11 overlapping genes, with NR3C1 emerging as the top candidate. NR3C1 was significantly upregulated in NIPAs and demonstrated good discriminatory power by ROC analysis. GSEA associated high NR3C1 expression with Wnt pathway activation. Functional experiments confirmed that NR3C1 overexpression enhances the invasive capacity of PA cells. NR3C1 promotes the invasive phenotype of NIPAs by activating Wnt signalling. These findings suggest NR3C1 as a potential biomarker and therapeutic target for invasive pituitary adenomas.

Humans↗

Maize response to acute arsenic toxicity as revealed by proteome analysis of plant shoots.

Aerial parts (shoots) of maize seedlings fed hydroponically with 300 muM sodium arsenate [As(V)] or 250 muM sodium arsenite [As(III)] for 24 h were analyzed for differentially expressed proteins by 2-DE and digital image analysis. About 15% of total detected proteins (74 out of 500) were up- or, mainly, down-regulated by arsenic, among which 14 were selected as being those most affected by the metalloid. These proteins were analyzed by MALDI-TOF MS and 7 of them were identified: translation initiation factor eIF-5A, ATP synthase, cysteine synthase, malate dehydrogenase, protein kinase C inhibitor, Tn10 transposase-like protein, and guanine nucleotide binding protein. Each of these proteins was completely repressed by As(V) and/or As(III), except protein kinase C inhibitor, which was newly detected after exposure to As(V).

Arsenic↗

Detecting differential and correlated protein expression in label-free shotgun proteomics.

Recent studies have revealed a relationship between protein abundance and sampling statistics, such as sequence coverage, peptide count, and spectral count, in label-free liquid chromatography-tandem mass spectrometry (LC-MS/MS) shotgun proteomics. The use of sampling statistics offers a promising method of measuring relative protein abundance and detecting differentially expressed or coexpressed proteins. We performed a systematic analysis of various approaches to quantifying differential protein expression in eukaryotic Saccharomyces cerevisiae and prokaryotic Rhodopseudomonas palustris label-free LC-MS/MS data. First, we showed that, among three sampling statistics, the spectral count has the highest technical reproducibility, followed by the less-reproducible peptide count and relatively nonreproducible sequence coverage. Second, we used spectral count statistics to measure differential protein expression in pairwise experiments using five statistical tests: Fisher's exact test, G-test, AC test, t-test, and LPE test. Given the S. cerevisiae data set with spiked proteins as a benchmark and the false positive rate as a metric, our evaluation suggested that the Fisher's exact test, G-test, and AC test can be used when the number of replications is limited (one or two), whereas the t-test is useful with three or more replicates available. Third, we generalized the G-test to increase the sensitivity of detecting differential protein expression under multiple experimental conditions. Out of 1622 identified R. palustris proteins in the LC-MS/MS experiment, the generalized G-test detected 1119 differentially expressed proteins under six growth conditions. Finally, we studied correlated expression of these 1119 proteins by analyzing pairwise expression correlations and by delineating protein clusters according to expression patterns. Through pairwise expression correlation analysis, we demonstrated that proteins co-located in the same operon were much more strongly coexpressed than those from different operons. Combining cluster analysis with existing protein functional annotations, we identified six protein clusters with known biological significance. In summary, the proposed generalized G-test using spectral count sampling statistics is a viable methodology for robust quantification of relative protein abundance and for sensitive detection of biologically significant differential protein expression under multiple experimental conditions in label-free shotgun proteomics.

Bacterial Proteins↗

Identification of differentiating neural progenitor cell markers using shotgun isobaric tagging mass spectrometry.

The use of neural precursor cells (NPCs) represents a promising repair strategy for many neurological disorders. This requires an understanding of the molecular events and biological features that regulate the self-renewal of NPCs and their differentiation into neurons, astrocytes, and oligodendendrocytes. In this study, we have characterized the proteomic changes that occur upon differentiation of these cells using the novel iTRAQ labeling chemistry for quantitative mass spectrometry. In total, 55 distinct proteins underwent expression changes during NPC differentiation. This included 14 proteins that were identified by our previous two-dimensional difference gel electrophoresis (2D-DIGE) analysis of differentiating mouse neurospheres. The importance of the iTRAQ approach was demonstrated by the identification of additional proteins that were not resolved by the 2D-DIGE technology. The proteins identified by the iTRAQ approach included growth factors, signaling molecules, proliferating cell-specific proteins, heat shock proteins, and other proteins involved in the regulation of metabolism and the transcriptional and translational machinery. Further characterization of the identified proteins should provide greater insight into the mechanisms involved in regulation of neurogenesis in the adult central nervous system and potentially that of other proliferating cell types, including peripheral stem cells or cancer cells.

Amino Acid Sequence↗

Proteomics: advanced technology for the analysis of cellular function.

Proteomics developed initially from the decade-long study of comprehensive protein visualization on two-dimensional electrophoresis gels has been expanded by mass spectrometry and the growth in searchable sequence databases. Currently, by use of more sophisticated technology such as a combination of multidimensional chromatography and mass spectrometry, thousands of proteins can automatically be identified in a day along with semiquantitative information on differential-protein expression. As with differential gene expression by cDNA-chips, the differential-protein analysis is useful for monitoring and identifying proteins involved in various physiological changes in cells or organisms, although the analysis alone does not necessarily provide information regarding the cause of the change or the function of the proteins. However, proteomics also provides the tools to expand into more sophisticated biochemical approaches, such as the study of protein interactions that can be determined directly by performing a pull-down assay with a bait protein followed by mass spectrometric identification of the bound proteins. Proteomics, thus, is useful for both large-scale surveys of proteins and detailed studies of the functional relationships among the proteins of interest. Certainly this approach can be applicable to the assessment of amino acid adequacy and safety.

Animals↗

Application of partial least squares discriminant analysis to two-dimensional difference gel studies in expression proteomics.

Two-dimensional difference gel electrophoresis (DIGE) is a tool for measuring changes in protein expression between samples involving pre-electrophoretic labeling ith cyanine dyes. In multi-gel experiments, univariate statistical tests have been used to identify differential expression between sample types by looking for significant changes in spot volume. Multivariate statistical tests, which look for correlated changes between sample types, provide an alternate approach for identifying spots with differential expression. Partial least squares-discriminant analysis (PLS-DA), a multivariate statistical approach, was combined with an iterative threshold process to identify which protein spots had the greatest contribution to the model, and compared to univariate test for three datasets. This included one dataset where no biological difference was expected. The novel multivariate approach, detailed here, represents a method to complement the univariate approach in identification of differentially expressed protein spots. This new approach has the advantages of reduced risk of false-positives and the identification of spots that are significantly altered in terms of correlated expression rather than absolute expression values.

Analysis of Variance↗

Quantitative proteomic analysis of age-related changes in human cerebrospinal fluid.

Identification of cerebrospinal fluid (CSF) biomarkers of the common age-related neurodegenerative diseases would be of great value to clinicians because of the difficulties in differential diagnoses of these diseases in clinical practice. Proteins are one class of potential biomarkers currently under investigation in the hope that different ensembles of proteins will aid in the diagnosis of these diseases, as well as in the assessment of progression and response to therapy. However, before undertaking a rational approach to CSF protein biomarkers of age-related neurodegeneration, we must first systematically identify CSF proteins and determine whether their levels change with normal aging. In this study, we used a powerful shotgun proteomic method, two-dimensional microcapillary liquid chromatography electrospray ionization tandem mass spectrometry, to identify proteins in human CSF. Additionally, using pooled CSF samples, we quantitatively compared the CSF proteome of younger adults with that of older adults using isotope-coded affinity tags (ICAT). From these studies we identified more than 300 proteins in CSF and found that there were 30 proteins with >20% change in concentrations between older and younger individuals. Finally, we validated changes in concentration for two of these proteins using Western blots in CSF from a separate set of individuals. These data not only expand substantially our current knowledge regarding human CSF proteins, but also supply the necessary information to appropriately interpret protein biomarkers of age-related neurodegenerative diseases.

Adult↗

Enrichment Performance Assessment of Extracellular Vesicles Using Different Functionalized Magnetic Materials and Application in Urinary Proteomics of Prostate Cancer.

Extracellular vesicles (EVs) are lipid bilayer nanovesicles that mediate intercellular communication and hold significant potential for clinical applications. Although material-based isolation strategies offer promising alternatives to conventional methods, their relative performances have not been systematically evaluated. In this study, we conducted a comparative assessment of magnetic nanomaterials with distinct surface functionalities, including metal oxides (TiO2), metal-organic frameworks (UiO-66), biopolymeric materials (chitosan), and lipid probes (DSPE-PEG, DOPE-PEG, and CLS-PEG). A comprehensive evaluation across multiple dimensions including capture capacity, capture rate, sample volume, and product purity reveals that the bifunctional magnetic nanomaterial Fe3O4@UiO-66@DSPE material exhibits superior EV capture performance. This material enables the efficient and stable enrichment of high-purity EVs by synergizing Zr4+-phosphate coordination with lipid bilayer anchoring, and preserves EV biological integrity and activity. Meanwhile, this method could be highly compatible with proteomics, and over 1000 proteins are identified by proteomic analysis of urinary EVs, while 34 proteins are upregulated and 25 proteins are downregulated in prostate cancer patients relative to healthy donors. Notably, the differentially expressed proteins, such as AGT, ITIH4, and PGLYRP2, are associated with disease progression. Overall, this work highlights the superior performance of the Fe3O4@UiO-66@DSPE material for efficient and selective EV isolation. It provides a powerful tool for clinical liquid biopsy and proteomic biomarker discovery, enabling early diagnosis, prognostic evaluation, and precision therapy.

Humans↗

[Pharmacogenomics: the frontiers of genome medicine].

The Human Genome Project provides insights so profound that it has the ability to change everything we know about medicine and how medicines are developed. Pharmacogenomics is defined as studies to identify the genes that are involved in determining the responsiveness to a given drug and to distinguish responders and non-responders to a given drug. Genome sequencing, transcriptome, and proteome analysis are of particular significance in pharmacogenomics. Transcriptome analysis can be done by methods of random cDNA sequencing, mRNA display and, differential hybridization (i.e., cDNA microarray and associated methods). Our results suggest that the pharmacogenomic transcriptome analysis and pharmainformatics have potential as strategies for defining novel drug targets in various diseases. Pharmacogenomics enhances the development, commercialization, and clinical use of conventional pharmaceutical products for common diseases, and it will eventually become a powerful tool for Evidence-Based Medicine. It is also important to predict interindividual pharmacokinetic differences by genetic polymorphisms of transporters or pharmacokinetic changes by transporter-mediated drug interactions during drug development. Pharmacogenomics and pharmainformatics enable us to move quickly and efficiently from targets to appropriate medicines.

Animals↗

Molecular classification and survival prediction in human gliomas based on proteome analysis.

The biological features of gliomas, which are characterized by highly heterogeneous biological aggressiveness even in the same histological category, would be precisely described by global gene expression data at the protein level. We investigated whether proteome analysis based on two-dimensional gel electrophoresis and matrix-assisted laser desorption/ionization time-of-flight mass spectrometry can identify differences in protein expression between high- and low-grade glioma tissues. Proteome profiling patterns were compared in 85 tissue samples: 52 glioblastoma multiforme, 13 anaplastic astrocytomas, 10 atrocytomas, and 10 normal brain tissues. We could completely distinguish the normal brain tissues from glioma tissues by cluster analysis based on the proteome profiling patterns. Proteome-based clustering significantly correlated with the patient survival, and we could identify a biologically distinct subset of astrocytomas with aggressive nature. Discriminant analysis extracted a set of 37 proteins differentially expressed based on histological grading. Among them, many of the proteins that were increased in high-grade gliomas were categorized as signal transduction proteins, including small G-proteins. Immunohistochemical analysis confirmed the expression of identified proteins in glioma tissues. The present study shows that proteome analysis is useful to develop a novel system for the prediction of biological aggressiveness of gliomas. The proteins identified here could be novel biomarkers for survival prediction and rational targets for antiglioma therapy.

Amino Acid Sequence↗

MEG3 Promoter Methylation and F11 Receptor (F11R) Overexpression Define a High-Risk Subtype of Diabetic Pancreatic Cancer.

Long-standing diabetes mellitus (long-DM) (&#x2267;3 years) is associated with worse clinical outcomes in patients with pancreatic ductal adenocarcinoma (PDAC). Emerging evidence suggests that epigenetic alterations may contribute to this association; however, the underlying mechanisms remain largely unclear. This study aimed to elucidate the role of the tumor-suppressive long noncoding RNA maternally expressed gene 3 (MEG3) and related molecules in the development of PDAC with long-DM. A total of 117 patients who underwent surgical resection for PDAC at Hirosaki University Hospital were retrospectively analyzed. Histopathological assessment followed World Health Organization criteria and the Union for International Cancer Control tumor-node-metastasis classification. Promoter methylation of MEG3 was assessed via methylation-specific PCR using formalin-fixed paraffin-embedded tissue. MEG3 expression levels were assessed by real-time quantitative PCR. Additionally, proteomic profiling was performed using liquid chromatography-tandem mass spectrometry on formalin-fixed paraffin-embedded tissue samples. Among the 117 cases with PDAC, patients with long-DM exhibited significantly poorer tumor differentiation and reduced cancer-specific survival. MEG3 promoter methylation was more prevalent in patients with long-DM. MEG3 methylation was correlated with reduced MEG3 expression, increased venous invasion, higher recurrence rates, and worse prognosis. Proteomic analysis and protein structure prediction tool revealed F11 receptor (F11R) as a potential downstream effector of MEG3. F11R protein expression levels were evaluated using semiquantitative immunohistochemistry. Higher F11R expression was observed in patients with long-DM, correlating with poor histologic differentiation and unfavorable outcomes. Patients with PDAC showing simultaneous MEG3 methylation and F11R high expression were more likely to have long-DM, with additive effects of these changes and tumor recurrence. Our results demonstrated that MEG3 and its potential downstream regulator, F11R, could be involved in PDAC progression, particularly in patients with long-DM. The findings underscore the clinical significance of epigenetic regulation in DM-related PDAC, suggesting novel targets, such as MEG3 and F11R, for potential therapeutic intervention.

Humans↗

Quantitative proteome analysis of breast cancer cell lines using 18O-labeling and an accurate mass and time tag strategy.

Proteome comparison of cell lines derived from cancer and normal breast epithelium provide opportunities to identify differentially expressed proteins and pathways associated with specific phenotypes. We employed 16O/18O peptide labeling, FT-ICR MS, and an accurate mass and time (AMT) tag strategy to simultaneously compare the relative abundance of hundreds of proteins in non-cancer and cancer cell lines derived from breast tissue. A cell line reference panel allowed relative protein abundance comparisons among multiple cell lines and across multiple experiments. A peptide database generated from multidimensional LC separations and MS/MS analysis was used for subsequent AMT tag-based peptide identifications. This peptide database represented a total of 2299 proteins, including 514 that were quantified in five cell lines using the AMT tag and 16O/18O strategies. Eighty-six proteins showed at least a threefold protein abundance change between cancer and non-cancer cell lines. Hierarchical clustering of protein abundance ratios revealed that several groups of proteins were differentially expressed between the cancer cell lines.

Breast Neoplasms↗

Quantitative analysis of acrylamide labeled serum proteins by LC-MS/MS.

Isotopic labeling of cysteine residues with acrylamide was previously utilized for relative quantitation of proteins by MALDI-TOF. Here, we explored and compared the application of deuterated and (13)C isotopes of acrylamide for quantitative proteomic analysis using LC-MS/MS and high-resolution FTICR mass spectrometry. The method was applied to human serum samples that were immunodepleted of abundant proteins. Our results show reliable quantitation of proteins across an abundance range that spans 5 orders of magnitude based on ion intensities and known protein concentration in plasma. The use of (13)C isotope of acrylamide had a slightly greater advantage relative to deuterated acrylamide, because of shifts in elution of deuterated acrylamide relative to its corresponding nondeuterated compound by reversed-phase chromatography. Overall, the use of acrylamide for differentially labeling intact proteins in complex mixtures, in combination with LC-MS/MS provides a robust method for quantitative analysis of complex proteomes.

Acrylamides↗

Proteomic analysis of plasma membrane vesicles isolated from the rat renal cortex.

Polarized epithelial cells are responsible for the vectorial transport of solutes and have a key role in maintaining body fluid and electrolyte homeostasis. Such cells contain structurally and functionally distinct plasma membrane domains. Brush border and basolateral membranes of renal and intestinal epithelial cells can be separated using a number of different separation techniques, which allow their different transport functions and receptor expressions to be studied. In this communication, we report a proteomic analysis of these two membrane segments, apical and basolateral, obtained from the rat renal cortex isolated by two different methods: differential centrifugation and free-flow electrophoresis. The study was aimed at assessing the nature of the major proteins isolated by these two separation techniques. Two analytical strategies were used: separation by sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) at the protein level or by cation-exchange high-performance liquid chromatography (HPLC) after proteolysis (i.e., at the peptide level). Proteolytic peptides derived from the proteins present in gel pieces or from HPLC fractions after proteolysis were sequenced by on-line liquid chromatography-tandem mass spectrometry (LC-MS/MS). Several hundred proteins were identified in each membrane section. In addition to proteins known to be located at the apical and basolateral membranes, several novel proteins were also identified. In particular, a number of proteins with putative roles in signal transduction were identified in both membranes. To our knowledge, this is the first reported study to try and characterize the membrane proteome of polarized epithelial cells and to provide a data set of the most abundant proteins present in renal proximal tubule cell membranes.

Amino Acid Sequence↗

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↗