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PubMed2026

Multiomic Integration Reveals Novel miRNA-mRNA-Protein Expression Profile in the Aged Female Retina.

PURPOSE: Aging is a leading risk factor for retinal degeneration. MicroRNAs (miRNAs) regulate posttranscriptional gene suppressors and influence inflammation and oxidative stress, two processes disrupted during retinal aging. This study aimed to identify age-related miRNA-mRNA-protein associations between young and older retinas and uncover dysregulated pathways that may contribute to retinal degeneration. METHODS: Retinal function was assessed using electroretinography (ERG), and microgliosis was quantified by microglial immunohistochemistry (IHC). A multiomics approach was used to examine molecular changes in older (30-month-old) female C57BL/6J mouse retinas and compared with young female (3-month-old) controls. Illumina sequencing profiled short miRNAs (20 bp) and bulk mRNAs (150 bp), while total proteomics via mass spectrometry assessed protein expression. Bioinformatic analyses included targetome analysis (miRNet), pathway enrichment (Gene Ontology), and clustering to identify age-associated molecular targets and pathways. RESULTS: Retinas from older mice displayed neuronal dysfunction and increased microgliosis. Sequencing revealed significant dysregulation of miRNAs linked to immune and inflammatory pathways, supported by enrichment of their predicted mRNA targets. In the older mice, mRNA expression showed broad inflammatory activation, though only 14% of dysregulated mRNAs overlapped with predicted miRNA targets. Proteomic profiling revealed a disconnect between RNA and protein expression, yet all omics layers showed enrichment in inflammatory pathways. Integrated analysis identified associations involving several gene regulatory networks in the older retina. CONCLUSIONS: This study demonstrates that at an advanced age, miRNA expression and their predicted downstream regulatory networks are dysregulated, highlighting potential molecular mechanisms underlying age-related retinal degeneration.

Animals↗

PubMed2004

Mycobacterium tuberculosis functional network analysis by global subcellular protein profiling.

Trends in increased tuberculosis infection and a fatality rate of approximately 23% have necessitated the search for alternative biomarkers using newly developed postgenomic approaches. Here we provide a systematic analysis of Mycobacterium tuberculosis (Mtb) by directly profiling its gene products. This analysis combines high-throughput proteomics and computational approaches to elucidate the globally expressed complements of the three subcellular compartments (the cell wall, membrane, and cytosol) of Mtb. We report the identifications of 1044 proteins and their corresponding localizations in these compartments. Genome-based computational and metabolic pathways analyses were performed and integrated with proteomics data to reconstruct response networks. From the reconstructed response networks for fatty acid degradation and lipid biosynthesis pathways in Mtb, we identified proteins whose involvements in these pathways were not previously suspected. Furthermore, the subcellular localizations of these expressed proteins provide interesting insights into the compartmentalization of these pathways, which appear to traverse from cell wall to cytoplasm. Results of this large-scale subcellular proteome profile of Mtb have confirmed and validated the computational network hypothesis that functionally related proteins work together in larger organizational structures.

Automation↗

PubMed2005

SELDI-TOF MS profiling of serum for detection of the progression of chronic hepatitis C to hepatocellular carcinoma.

Proteomic profiling of serum is an emerging technique to identify new biomarkers indicative of disease severity and progression. The objective of our study was to assess the use of surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS) to identify multiple serum protein biomarkers for detection of liver disease progression to hepatocellular carcinoma (HCC). A cohort of 170 serum samples obtained from subjects in the United States with no liver disease (n = 39), liver diseases not associated with cirrhosis (n = 36), cirrhosis (n = 38), or HCC (n = 57) were applied to metal affinity protein chips for protein profiling by SELDI-TOF MS. Across the four test groups, 38 differentially expressed proteins were used to generate multiple decision classification trees to distinguish the known disease states. Analysis of a subset of samples with only hepatitis C virus (HCV)-related disease was emphasized. The serum protein profiles of control patients were readily distinguished from each HCV-associated disease state. Two-way comparisons of chronic hepatitis C, HCV cirrhosis, or HCV-HCC versus healthy had a sensitivity/specificity range of 74% to 95%. For distinguishing chronic HCV from HCV-HCC, a sensitivity of 61% and a specificity of 76% were obtained. However, when the values of known serum markers alpha fetoprotein, des-gamma carboxyprothrombin, and GP73 were combined with the SELDI peak values, the sensitivity and specifity improved to 75% and 92%, respectively. In conclusion, SELDI-TOF MS serum profiling is able to distinguish HCC from liver disease before cirrhosis as well as cirrhosis, especially in patients with HCV infection compared with other etiologies.

Adult↗

PubMed2004

The use of plasma surface-enhanced laser desorption/ionization time-of-flight mass spectrometry proteomic patterns for detection of head and neck squamous cell cancers.

PURPOSE: Our study was undertaken to determine the utility of plasma proteomic profiling using surface-enhanced laser desorption/ionization time-of-flight (SELDI-TOF) mass spectrometry for the detection of head and neck squamous cell carcinomas (HNSCCs). EXPERIMENTAL DESIGN: Pretreatment plasma samples from HNSCC patients or controls without known neoplastic disease were analyzed on the Protein Biology System IIc SELDI-TOF mass spectrometer (Ciphergen Biosystems, Fremont, CA). Proteomic spectra of mass:charge ratio (m/z) were generated by the application of plasma to immobilized metal-affinity-capture (IMAC) ProteinChip arrays activated with copper. A total of 37356 data points were generated for each sample. A training set of spectra from 56 cancer patients and 52 controls were applied to the "Lasso" technique to identify protein profiles that can distinguish cancer from noncancer, and cross-validation was used to determine test errors in this training set. The discovery pattern was then used to classify a separate masked test set of 57 cancer and 52 controls. In total, we analyzed the proteomic spectra of 113 cancer patients and 104 controls. RESULTS: The Lasso approach identified 65 significant data points for the discrimination of normal from cancer profiles. The discriminatory pattern correctly identified 39 of 57 HNSCC patients and 40 of 52 noncancer controls in the masked test set. These results yielded a sensitivity of 68% and specificity of 73%. Subgroup analyses in the test set of four different demographic factors (age, gender, and cigarette and alcohol use) that can potentially confound the interpretation of the results suggest that this model tended to overpredict cancer in control smokers. CONCLUSIONS: Plasma proteomic profiling with SELDI-TOF mass spectrometry provides moderate sensitivity and specificity in discriminating HNSCC. Further improvement and validation of this approach is needed to determine its usefulness in screening for this disease.

Adult↗

PubMed2026

Proteogenomic features define subtypes of mantle cell lymphoma.

Mantle cell lymphoma (MCL) is a biologically heterogeneous B-cell malignancy. Although genomics and transcriptomics have delineated parts of the MCL disease spectrum, proteomics remains largely unexplored. Here, we conducted a comprehensive proteogenomic analysis integrating genomics, transcriptomics, and proteomics on peripheral blood samples from 27 patients with MCL and 4 healthy donors to investigate the translational and posttranslational dimensions of MCL. Our study identified 1296 downregulated and 468 upregulated proteins in MCL cells. The splicing pathways were significantly upregulated at both the mRNA and protein levels, suggesting a critical role for aberrant RNA splicing in MCL pathogenesis. Integration of proteomic data with genetic aberrations revealed immunoglobulin heavy chain variable mutational status and CCND1 mutation are associated with distinctive transcriptomic and proteomic profiles, which correspond to significant differences in clinical outcomes. A multiomics molecular stratification model incorporating proteomic data showed superior predictive power for patient survival compared with single-omics models (concordance index, 0.83 vs 0.74). This study provides, to our knowledge, the first comprehensive proteogenomic profile of MCL, offering novel insights into its molecular mechanisms and clinical behavior. The identification of molecular subtypes and prognostic protein signatures underscores the potential of proteomics to guide precision medicine strategies for MCL.

Humans↗

PubMed2026

Quantitative Proteomic Analysis of APP/PS1 Transgenic Mice.

BACKGROUND: Alzheimer's disease (AD) is a prevalent neurodegenerative disorder affecting the central nervous system (CNS), with its etiology still shrouded in uncertainty. The interplay of extracellular amyloid-β (Aβ) deposition, intracellular neurofibrillary tangles (NFTs) composed of tau protein, cholinergic neuronal impairment, and other pathogenic factors is implicated in the progression of AD. OBJECTIVE: The current study endeavors to delineate the proteomic landscape alterations in the hippocampus of an AD murine model, utilizing proteomic analysis to identify key physiological and pathological shifts induced by the disease. This endeavor aims to shed light on the underlying pathogenic mechanisms, which could facilitate early diagnosis and pave the way for novel therapeutic interventions for AD. METHODS: To dissect the proteomic perturbations induced by Aβ and Presenilin-1 (PS1) in the AD pathogenesis, we undertook a label-free quantitative (LFQ) proteomic analysis focusing on the hippocampal proteome of the APP/PS1 transgenic mouse model. Employing a multi-faceted approach that included differential protein functional enrichment, cluster analysis, and protein-protein interaction (PPI) network analysis, we conducted a comprehensive comparative proteomic study between APP/PS1 transgenic mice and their wild-type C57BL/6 counterparts. RESULTS: Mass spectrometry identified a total of 4817 proteins in the samples, with 2762 proteins being quantifiable. Comparative analysis revealed 396 proteins with differential expression between the APP/PS1 and control groups. Notably, 35 proteins exhibited consistent temporal regulation trends in the hippocampus, with concomitant alterations in biological pathways and PPI networks. CONCLUSIONS: This study presents a comparative proteomic profile of transgenic (APP/PS1) and wild-type mice, highlighting the proteomic divergences. Furthermore, it charts the trajectory of proteomic changes in the AD mouse model across the developmental stages from 2 to 12 months, providing insights into the physiological and pathological implications of the disease-associated genetic mutations.

Animals↗

PubMed2005

Proteome-based identification of molecular markers predicting chemosensitivity to each category of anticancer agents in human gliomas.

To identify the protein markers that are clinically useful for predicting efficacy of anticancer agents, we investigated the correlation between the proteome profiling patterns and the in vitro chemosensitivity in human gliomas. The proteome of 93 surgical samples were analyzed with two-dimensional gel electrophoresis (2DE) and mass spectrometry. The in vitro chemosensitivities to 10 different kinds of anticancer agents (cyclophosphamide, nimustine, cisplatin, cytosine arabinoside, mitomycin C, peplomycin, adriamycin, etoposide, vincristine, paclitaxel) were measured by flow cytometric detection of apoptosis. We identified a set of 41 proteins that significantly affected the in vitro chemosensitivity to each category of anticancer agents. Many of the proteins that correlated with chemoresistance were categorized into the signal transduction proteins including the G-proteins. The present study showed that the proteome analysis using 2DE could provide a list of proteins that may be the potential predictive markers for chemosensitivity in human gliomas. They can also be direct and rational targets for anti-glioma therapy and be used for sensitization to the conventional chemotherapeutic regimens.

Antineoplastic Agents↗

PubMed2005

Large scale protein profiling by combination of protein fractionation and multidimensional protein identification technology (MudPIT).

In the past decade, shotgun proteomic analysis has been utilized extensively to answer complex biological questions. New challenges arise in large scale proteomic profiling when dealing with complex biological mixtures such as the mammalian cell lysate. In this study, we explored the approach of protein separation prior to the shotgun multidimensional protein identification technology (MudPIT) analysis. We fractionated the mammalian cancer cell lysate using the PF 2D ProteomeLab system and analyzed the distribution of molecular weight, isoelectric point, and cellular localization of the eluted proteins. As a result, we were able to reduce sample complexity by protein fractionation and increase the possibility of detecting proteins with lower abundance in the complex protein mixture.

Biomarkers, Tumor↗

PubMed2001

Integrating molecular medicine with functional proteomics: realities and expectations.

We analyze key proteomic issues and cutting-edge technologies that will spearhead inroads into functional interpretations of human diseases and their therapeutic rectification, following the availability of the predicted human proteome. We contrast the distinctions between high quality data that are low throughput, (e.g., 3-D proteomic reconstructions in embryogenic and nervous system contexts, and multigenerational transgenic studies), versus automated data harvesting that is more distant from human disease phenotypes and currently fulfills a diagnostic role, (e.g., molecular portraits of human diseases via transcriptomic analyses). We examine the extent to which these approaches impinge upon a realistic understanding of human diseases, namely how close they come to revealing the causal events involved in the initiation of disease. While tissue sources from human embryogenesis, foetal development and the brain remain the absolute priority, the pragmatic approaches utilize judicious data integration from selected proteomic studies of model organisms. The role of genome-wide disease-related screens, "humanized" transgenic analyses, multigenerational gene interference methods, and analyses of post-translational modifications in epigenetic contexts from Drosophila will be crucial, since these avenues are far too slow and transgenically cumbersome in mammals. Finally, the implementation of multi compartment electrolyzers (MCE) and multi photon detection (MPD) systems will be pivotal for the proteomic profiling of human tissue samples.

Animals↗

PubMed2026

Analysis of Confounding Factors in Reactive Cysteine Profiling Reveals Enhanced Chromatin-Protein Association via CDK7 Inhibition by THZ1.

Recent advances in activity-based proteome profiling (ABPP) have enabled the global mapping of cysteine ligandability, uncovering novel biological insights and opportunities for identifying disease vulnerabilities. While both live-cell-based and native-lysate-based ABPP have been applied, how cysteine ligandability differs between these systems and what factors influence these measurements remain unclear. Building on our previous development of a high-throughput TMT-ABPP workflow for native lysates, here we adapt the protocol for live cells and systematically compare cysteine ligandability across both platforms. Our analysis reveals three major contributors to the discrepancies: in-cellular cysteine accessibility, protein abundance changes, and protein relocalization. Notably, we highlight that the CDK7 inhibitor THZ1 induces substantial protein relocalization and promotes chromatin binding. Together, these results provide a practical framework for ABPP experimental design and data interpretation, supporting the more accurate application of ABPP in functional proteomics and drug discovery.

Cysteine↗

PubMed2026

Body mass index-specific nanoparticle protein corona signatures in late pregnancy.

The protein corona (PC) formed on the surface of nanoparticles (NPs) upon exposure to human biofluids is a dynamic interface that reflects the physiological and pathological status of the host. In this study, we investigated how the maternal body mass index (BMI) influences the composition of the NPs' PC during late pregnancy. Polystyrene NPs were incubated with plasma samples collected from third-trimester pregnant individuals across normal weight, overweight, and obese BMI categories. Comprehensive characterization using dynamic light scattering (DLS), zeta potential measurements, and transmission electron microscopy (TEM) confirmed BMI-dependent differences in PC thickness and colloidal stability. SDS-PAGE and label-free quantitative proteomics revealed distinct molecular compositions: PCs from obese individuals were enriched in inflammatory and lipid metabolism-associated proteins (e.g., APOE and CRP), while normal weight-derived PCs showed higher levels of complementary regulators and extracellular matrix proteins. Principal component analysis (PCA) demonstrated clear clustering of proteomic profiles by the BMI group, suggesting BMI-specific PC fingerprints. These findings indicate that the maternal metabolic phenotype shapes nano-bio interactions at the proteomic level and highlight the potential of PC profiling as a non-invasive approach for assessing maternal health and metabolic status. This work lays the foundation for integrating NP-based proteomics into precision nanomedicine for maternal-fetal health monitoring.

Female↗

PubMed2003

Molecular diagnostics.

It is increasingly evident that molecular diagnostics, that is, the use of diagnostic testing to understand the molecular mechanisms of an individual patient's disease, will be pivotal in the delivery of safe and effective therapy for many diseases in the future. A huge body of new information on the genetic, genomic and proteomic profiles of different hematopoietic diseases is accumulating. This chapter focuses on new technologies and advancements in understanding the molecular basis of hematologic disorders, providing an overview of new information and its significance to patient care. In Section I, Dr. Braziel discusses the impact of new genetic information and research technologies on the actual practice of diagnostic molecular hematopathology. Recent and projected changes in methodologies and analytical strategies used by clinical molecular diagnostics laboratories for the evaluation of hematologic disorders will be discussed, and some of the challenges to clinical implementation of new molecular information and techniques will be highlighted. In Section II, Dr. Shipp provides an update on current scientific knowledge in the genomic profiling of malignant lymphomas, and describes some of the technical aspects of gene expression profiling. Analysis methods and the actual and potential clinical and therapeutic applications of information obtained from genomic profiling of malignant lymphomas are discussed. In Section III, Dr. Liotta presents an update on proteomic analysis, a new and very active area of research in hematopoietic malignancies. He describes new technologies for rapid identification of different important proteins and protein networks, and the potential therapeutic and prognostic value of the elucidation of these proteins and protein pathways in the clinical care of patients with malignant lymphomas.

Cytogenetic Analysis↗

PubMed2026

Ank3 loss in adult forebrain excitatory neurons disrupts behavior, neuronal activity, membrane proteome, and myelination.

ANK3, encoding the scaffolding protein ankyrin-G, is a major risk gene for bipolar disorder and schizophrenia, but its cellular and circuit-level mechanisms remain poorly defined. Here, we demonstrate that deletion of Ank3 in forebrain excitatory neurons-either prenatally (Ank3-/-:Emx1-Cre) or in adolescence (Ank3-/-:CaMKIIα-Cre) leads to convergent behavioral phenotypes in adulthood, including hyperactivity, reduced anxiety-like behavior, and decreased depression-like responses. Calcium imaging in cultured neurons and acute brain slices revealed that ankyrin-G loss reduces both spontaneous and evoked neuronal activity. Quantitative proteomic profiling of membrane-enriched cortical fractions uncovered widespread remodeling of the synaptic proteome, including upregulation of the kinase Taok2 and unexpected downregulation of myelin basic protein (Mbp), a structural component of oligodendrocyte-derived myelin. Importantly, chronic lithium treatment, known to reverse behavioral abnormalities in Ank3-deficient mice, also restored Mbp expression. Together, our findings identify ankyrin-G as a molecular bridge between excitatory neuronal activity, synaptic structure, and myelin-associated protein expression, revealing a pathway by which ANK3 variants may contribute to neuropsychiatric disease.

Animals↗

PubMed2006

Plasma proteome analysis reveals the geographical origin and liver tumor status of Dab (Limanda limanda) from UK marine waters.

The flatfish species dab (Limanda limanda) is the sentinel for offshore marine monitoring in the United Kingdom National Marine Monitoring Programme (NMMP). At certain sites in the North and Irish Seas, the prevalence of macroscopic liver tumors can exceed 10%. The plasma proteome of these fish potentially contains reporter proteins or "biomarkers" that may enable development of diagnostic tests for liver cancer and further our understanding of the disease. Following selection of sample groups by quality-assured histopathology ("phenotype anchoring"), we used surface-enhanced laser desorption/ionization (SELDI) time-of-flight mass spectrometry to produce proteomic profiles of plasma from 213 dab collected during the 2004 UK NMMP. The resulting protein profiles were compared between fish from the North and Irish Seas and between fish with liver neoplasia or nondiseased liver. Significant differences were found between the plasma proteomes of dab from the North Sea and Irish Sea, which in conjunction with artificial neural networks can correctly determine from which sea dab were captured in 85% of the cases. In addition, the presence of liver tumors is associated with significant changes in the plasma proteome. We conclude that SELDI-based plasma profiling is potentially of use in nonlethal marine monitoring using wild sentinels such as dab. Furthermore, accurate selection of sample groups is critical for avoiding effects of confounding factors such as age, gender, and geographic origin of samples.

Adenoma, Liver Cell↗

PubMed2026

Integration of metabolomics and proteomics reveals the toxicological mechanisms of environmentally relevant concentrations of cadmium on juvenile rockfish (Sebastes schlegelii).

As a highly toxic heavy metal, cadmium (Cd) is widely distributed in the coastal environments of the Bohai Sea, posing significant ecological and health risks. This is of particular concern for Sebastes schlegelii, a rockfish species commonly found along the Bohai coast and consumed by local populations. In this study, juvenile S. schlegelii were randomly assigned to three groups (control, 5 and 50 μg/L Cd) for a 14-day exposure period, followed by analysis of Cd bioaccumulation, as well as metabolomic and proteomic profiling. ICP-MS analysis indicated dose-dependent Cd bioaccumulation in the whole body, with 0.11 ± 0.07 μg/g dry weight in the 5 μg/L group and 0.38 ± 0.09 μg/g dry weight in the 50 μg/L group (9.5-fold higher than the control, p < 0.05). An iTRAQ-based proteomic analysis determined 168 differentially expressed proteins, while 1H NMR-based metabolomic profiling identified 34 metabolites with significant alterations. Integrated analysis of the proteomic and metabolomic data provided insights into the molecular responses of juvenile rockfish to Cd exposure. Specifically, metabolomic results indicated significant alterations in key metabolites, including lactate, phosphocholine, adenosine triphosphate, alanine, and inosine in the Cd-treated groups. Proteomic analysis further suggested that Cd exposure was associated with immune and oxidative stress responses, neurotoxicity, cellular damage, and disruptions in critical metabolic pathways, such as glycolysis, the tricarboxylic acid cycle, amino acid and lipid metabolism. Overall, this study demonstrates the utility of integrating proteomics and metabolomics to characterize molecular responses to Cd stress in juvenile S. schlegelii.

Animals↗

PubMed2006

Clinical proteomics: present and future prospects.

Advances in proteomics technology offer great promise in the understanding and treatment of the molecular basis of disease. The past decade of proteomics research, the study of dynamic protein expression, post-translational modifications, cellular and sub-cellular protein distribution, and protein-protein interactions, has culminated in the identification of many disease-related biomarkers and potential new drug targets. While proteomics remains the tool of choice for discovery research, new innovations in proteomic technology now offer the potential for proteomic profiling to become standard practice in the clinical laboratory. Indeed, protein profiles can serve as powerful diagnostic markers, and can predict treatment outcome in many diseases, in particular cancer. A number of technical obstacles remain before routine proteomic analysis can be achieved in the clinic; however the standardisation of methodologies and dissemination of proteomic data into publicly available databases is starting to overcome these hurdles. At present the most promising application for proteomics is in the screening of specific subsets of protein biomarkers for certain diseases, rather than large scale full protein profiling. Armed with these technologies the impending era of individualised patient-tailored therapy is imminent. This review summarises the advances in proteomics that has propelled us to this exciting age of clinical proteomics, and highlights the future work that is required for this to become a reality.

Journal Article↗

PubMed2026

Identification of tomato leaf miner secretory proteins and their roles in influencing plant defenses.

The tomato leaf miner (Tuta absoluta) is a globally destructive pest that cause extensive damage to tomato crops by chewing mouthparts, leading to severe necrosis, fruit abortion, and substantial yield losses. To date, the elicitors/effectors of T. absoluta have not been characterized. In this study, we combined proteomic profiling of T. absoluta-infested tomato leaves with transcriptomic analysis of salivary glands to identify candidate molecules involved in herbivory-driven plant responses. Bioinformatics analyses predicted 40 candidate elicitors and effectors, which were subsequently assessed through transient expression assays in Nicotiana benthamiana. The results demonstrated that the candidate number 33 (T. absoluta 33, Ta33) induced cell death in both the intracellular space and the apoplast, while Ta21 triggered a strong apoplastic reactive oxygen species (ROS) burst. Conversely, Ta38 effectively suppressed INF1-induced cell death. Quantitative real-time PCR analysis further showed that these genes were highly expressed during the feeding stage, supporting their involvement in plant-insect molecular dialogue. This study systematically identified and characterized elicitors and effectors of T. absoluta, providing a foundational framework for elucidating its herbivory mechanisms and developing targeted management strategies.

Moths↗

PubMed2004

Transcriptomic and proteomic analysis of a 14-3-3 gene-deficient yeast.

BMH1 and BMH2 encode Saccharomyces cerevisiae 14-3-3 homologues whose exact functions have remained unclear. The present work compares the transcriptomic and proteomic profiles of the wild type and a BMH1/2-deficient S. cerevisiae mutant (bmhDelta) using DNA microarrays and two-dimensional polyacrylamide gel electrophoresis. It is reported here that, although the global patterns of gene and protein expression are very similar between the two types of yeast cells, a subset of genes and proteins (a total of 220 genes) is significantly induced or reduced in the absence of Bmh1/2p. These genes include approximately 60 elements that could be linked to the reported phenotypes of the bmhDelta mutant (e.g., accumulation of glycogen and hypersensitivity to environmental stress) and/or could be the potential downstream targets of interacting partners of Bmh1/2p such as Msn2p and Rtg3p. Importantly, >30% of the identified genes (71 genes) were found to be associated with carbon (C) and nitrogen (N) metabolism and transport, thereby suggesting that Bmh1/2p may play a major role in the regulation of C/N-responsive cellular processes. This study presents the first comprehensive overview of the genes and proteins that are affected by the depletion of Bmh1/2p and extends the scope of knowledge of the regulatory roles of Bmh1/2p in S. cerevisiae.

14-3-3 Proteins↗