Journal of Proteome Research最新文献

The distinction between noncancerous and cancerous breast tissues is challenging in clinical settings, and discovering new proteomics-based biomarkers remains underexplored. Through a pilot proteomic study (discovery cohort), we aimed to identify a protein signature indicative of breast cancer for subsequent validation using six published proteomics/transcriptomics data sets (validation cohorts). Sequential window acquisition of all theoretical (SWATH)-based mass spectrometry revealed 370 differentially abundant proteins between noncancerous tissue and breast cancer. Protein-protein interaction-based networks and enrichment analyses revealed dysregulation in pathways associated with extracellular matrix organization, platelet degranulation, the innate immune system, and RNA metabolism in breast cancer. Through multivariate unsupervised analysis, we identified a four-protein signature (OGN, LUM, DCN, and COL14A1) capable of distinguishing breast cancer. This dysregulation pattern was consistently verified across diverse proteomics and transcriptomics data sets. Dysregulation magnitude was notably higher in poor-prognosis breast cancer subtypes like Basal-Like and HER2 compared to Luminal A. Diagnostic evaluation (receiver operating characteristic (ROC) curves) of the signature in distinguishing breast cancer from noncancerous tissue revealed area under the curve (AUC) ranging from 0.87 to 0.9 with predictive accuracy of 80% to 82%. Upon stratifying, to solely include the Basal-Like/Triple-Negative subtype, the ROC AUC increased to 0.922-0.959 with predictive accuracy of 84.2%-89%. These findings suggest a potential role for the identified signature in distinguishing cancerous from noncancerous breast tissue, offering insights into enhancing diagnostic accuracy.

Measuring responses in the proteome to various perturbations improves our understanding of biological systems. The value of information gained from such studies is directly proportional to the number of proteins measured. To overcome technical challenges associated with highly multiplexed measurements, we developed an affinity reagent-based method that uses aptamers with protein-like side chains along with an assay that takes advantage of their unique properties. As hybrid affinity reagents, modified aptamers are fully comparable to antibodies in terms of binding characteristics toward proteins, including epitope size, shape complementarity, affinity and specificity. Our assay combines these intrinsic binding properties with serial kinetic proofreading steps to allow highly effective partitioning of stable specific complexes from unstable nonspecific complexes. The use of these orthogonal methods to enhance specificity effectively overcomes the severe limitation to multiplexing inherent to the use of sandwich-based methods. Our assay currently measures half of the unique proteins encoded in the human genome with femtomolar sensitivity, broad dynamic range and exceptionally high reproducibility. Using machine learning to identify patterns of change, we have developed tests based on measurement of multiple proteins predictive of current health states and future disease risk to guide a holistic approach to precision medicine.

The aim of this study was to identify, using proteomics, the molecular alterations caused by human serum exposure to Klebsiella pneumoniae ACH2. The analysis was performed under two different conditions, native serum from healthy donors and heat-inactivated serum (to inactivate the complement system), and at two different times, after 1 and 4 h of serum exposure. More than 1,000 bacterial proteins were identified at each time point. Enterobactin, a siderophore involved in iron uptake, and proteins involved in translation were upregulated at 1 h, while the chaperone ProQ and the glyoxylate cycle were identified after 4 h. Enzymes involved in the stress response were downregulated, and the SOD activity was validated using an enzymatic assay. In addition, an intricate metabolic adaptation was observed, with pyruvate and thiamine possibly involved in survival and virulence in the first hour of serum exposure. The addition of exogenous thiamine contributes to bacterial growth in human serum, corroborating this result. During 4 h of serum exposure, the glyoxylate cycle (GC) probably plays a central role, and the addition of exogenous succinate suppresses the GC, inducing a decrease in serum resistance. Therefore, serum exposure causes important changes in iron acquisition, the expression of virulence factors, and metabolic reprogramming, which could contribute to bacterial serum resistance.

Metabolic reprogramming is a ubiquitous feature of transformed cells, comprising one of the hallmarks of cancer and enabling neoplastic cells to adapt to new environments. Accumulated evidence reports on the failure of some neoplastic cells to convert mannose-6-phosphate into fructose-6-phosphate, thereby impairing tumor growth in cells displaying low levels of mannose-6-phosphate isomerase (MPI). Thus, we performed functional analyses and profiled the proteome landscape and the repertoire of substrates of proteases (degradome) of melanoma cell lines with distinct mutational backgrounds submitted to treatment with mannose. Our results suggest a significant rearrangement in the proteome and degradome of melanoma cell lines upon mannose treatment including the activation of catabolic pathways (such as protein turnover) and differences in protein N-terminal acetylation. Even though MPI protein abundance and gene expression status are not prognostic markers, perturbation in the network caused by an exogenous monosaccharide source (i.e., mannose) significantly affected the downstream interconnected biological circuitry. Therefore, as reported in this study, the proteomic/degradomic mapping of mannose downstream effects due to the metabolic rewiring caused by the functional status of the MPI enzyme could lead to the identification of specific molecular players from affected signaling circuits in melanoma.

SARS-CoV-19 infection provokes a variety of symptoms; most patients present mild/moderate symptoms, whereas a small proportion of patients progress to severe illness with multiorgan failure accompanied by metabolic disturbances requiring ICU-level care. Given the importance of the disease, researchers focused on identifying severity-associated biomarkers in infected patients as well as markers associated with patients suffering long-COVID. However, little is known about the presence of biomarkers that remain a few years after SARS-CoV-2 infection once the patients fully recover of the symptoms. In this study, we evaluated the presence of persistent biomarkers in the nasopharyngeal tract two years after SARS-Cov-2 infection in fully asymptomatic patients, taking into account the severity of their infection (mild/moderate and severe infections). In addition to the direct identification of several components of the Coronavirus Infection Pathway in those individuals that suffered severe infections, we describe herein 371 proteins and their associated canonical pathways that define the different adverse effects of SARS-CoV-2 infections. The persistence of these biomarkers for up to two years after infection, along with their ability to distinguish the severity of the infection endured, highlights the surprising presence of persistent nasopharyngeal exudate changes in fully recovered patients.

Sin3 is an evolutionarily conserved repressor protein complex mainly associated with histone deacetylase (HDAC) activity. Many proteins are part of Sin3/HDAC complexes, and the function of most of these members remains poorly understood. SAP25, a previously identified Sin3A associated protein of 25 kDa, has been proposed to participate in regulating gene expression programs involved in the immune response but the exact mechanism of this regulation is unclear. SAP25 is not expressed in HEK293 cells, which hence serve as a natural knockout system to decipher the molecular functions uniquely carried out by this Sin3/HDAC subunit. Using molecular, proteomic, protein engineering, and interaction network approaches, we show that SAP25 interacts with distinct enzymatic and regulatory protein complexes in addition to Sin3/HDAC. Additional proteins uniquely recovered from the Halo-SAP25 pull-downs included the SCF E3 ubiquitin ligase complex SKP1/FBXO3/CUL1 and the ubiquitin carboxyl-terminal hydrolase 11 (USP11). Furthermore, mutational analysis demonstrates that distinct regions of SAP25 participate in its interaction with USP11, OGT/TETs, and SCF(FBXO3). These results suggest that SAP25 may function as an adaptor protein to coordinate the assembly of different enzymatic complexes to control Sin3/HDAC-mediated gene expression. The data were deposited with the MASSIVE repository with the identifiers MSV000093576 and MSV000093553.

The liquid chromatography-high resolution mass spectrometry (LC-HRMS) technique enables the detection of phytochemicals present in the extracts. LC-HRMS-generated mass list showed abundant compounds of interest, artifacts, and primary metabolites. The identification of a secondary metabolite of interest within the extract is very challenging. We hypothesized that identifying the "new metabolite" in the whole metabolome is more challenging than identifying it within the class of metabolites. The proposed prioritization strategy focused on the elimination of unknown and prioritizing the known class of secondary metabolites to identify new metabolites. The prioritization strategy demonstrated on Murraya paniculata for the identification of new metabolites. LC-HRMS-generated information is used as a filter to target the secondary metabolite and the new metabolites. This strategy successfully annotated the new coumarin and coumarin alkaloids from the mass list of 1448 metabolites. Varanasine (3), schroffanone (4), schroffanene (5), and O-methylmurraol (9) are new compounds, and coumarin (1, 2, and 6-8) are known. Varanasine (3) is the first naturally occurring 7-aminocoumarin with additional N-formyl functionality. The isolates were screened for cytotoxicity against the panel of cancer cell lines. Varanasine (3) and minumicrollin (6) showed significant cytotoxicity and apoptosis-inducing potential. The immunoblot analysis confirmed inhibition of apoptotic protein PARP-1 and caspase-3 expression by 3 and 6.

Despite extensive research, the genes/proteins and pathways responsible for the physiological effects of estrogen remain elusive. In this study, we determined the effect of estrogen on global protein expression in breast cancer MCF7 cells using a proteomic method. The expression of 77 cytosolic, 74 nuclear, and 81 membrane/organelle proteins was significantly altered by 17-β-estradiol (E2). Protein enrichment analyses suggest that E2 may stimulate cell division primarily by promoting the G1 to S phase transition and advancing the G2/M checkpoint. The effect of E2 on cell survival was complex, as it could simultaneously enhance and inhibit apoptosis. Bioinformatics analysis suggests that E2 may enhance apoptosis by promoting the accumulation of the pore-forming protein Bax in the mitochondria and inhibit apoptosis by activating the PI3K/AKT/mTOR signaling pathway. We verified the activation of the PI3K signaling and the accumulation of Bax in the membrane/organelle fraction in E2-treated cells using immunoblotting. Treatment of MCF7 cells with E2 and the PI3K inhibitor Ly294002 significantly enhanced apoptosis compared to those treated with E2 alone, suggesting that combining estrogen with a PI3K inhibitor could be a promising strategy for treating ERα-positive breast cancer. Interestingly, many of the E2-upregulated proteins contained the HEAT, KH, and RRM domains.

Many shotgun proteomics experiments are negatively influenced by highly abundant proteins, such as those measuring residual host cell proteins (HCP) amidst highly abundant recombinant biotherapeutic or plasma proteins amidst albumin and immunoglobulins. While western blotting and ELISAs can reveal the presence of specific low abundance proteins from highly abundant background proteins, mass spectrometry approaches are required to define the low abundance protein composition in these scenarios. The challenge in detecting low abundance proteins in a high protein background by standard shotgun approaches is that spectra are often not triggered on their peptides in data dependent acquisition methods but rather on the highly abundant background peptides. Here, we use tandem mass tags (TMT) to introduce a carrier proteome approach to enhance the detection of proteins, such as from residual host cell proteomes amidst a highly abundant background. Using a mixture of bovine serum albumin (BSA) and E. coli as a mock high background/low abundance target protein formulation, we demonstrate proof-of-principle experiments allowing the improved detection of target proteins amidst a high protein background. While we observed significant coisolation interference, we mitigated it by using a spike-in interference detection TMT channel. Finally, we use the approach to identify 300 residual E. coli proteins from a protein A pulldown of a human IgG antibody, demonstrating that it may be applicable to analysis of HCPs in biotherapeutic protein formulations.

Although amino acid (AA) metabolism is linked to tumor progression and could serve as an attractive intervention target, its association with neuroblastoma (NB) is unknown. Based on AA metabolism-related genes, we established three NB subtypes associated with distinct prognoses and specific functions, with C1 and C2 having better outcomes. The C1 displayed enhanced metabolic activity and recruited metabolism-associated cells. The C2 exhibited an activated immune microenvironment and was more vulnerable to immunotherapy. The C3, characterized by cell cycle peculiarity, possessed a dismal prognosis and high frequency of gene mutations and was susceptible to chemotherapy. Furthermore, single-cell RNA sequencing analysis revealed that the C3-associated Scissor+ cell subpopulation was characterized by notorious functional states and orchestrated an immunosuppressive microenvironment. Additionally, we identified that ALK and BIRC5 contributed to the shorter lifespan of C3 and their corresponding inhibitors were potential interventions. In conclusion, we identified three distinct subtypes of NB, which help us foster individualized therapeutic strategies to improve the prognosis of NB.