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PubMed2026

narrowPASEF: A Sample-Aware diaPASEF Method Optimization Strategy Improving Differential Proteomics Performance on Low-Abundance Proteins.

Recent instrumental and computational innovations in mass-spectrometry-based proteomics offer new promise in biomarker discovery, thanks to unprecedented proteome coverage and depth. Data-independent acquisition (DIA) methods are very promising in this context as they allow improved proteome coverage, reduced missing value rates, and enhanced quantification precision. However, DIA methods also suffer from their own challenges, such as increased data complexity, cycle times, and background noise. In this work, we propose a sample-aware diaPASEF method optimization strategy for a timsTOF platform. Thorough method optimizations have first been conducted on standard HeLa lysates. Then, a ground-truth calibrated sample series, consisting of a range of UPS amounts spiked into a complex Arabidopsis background, was used to mimic differential analyses under controlled conditions. These benchmark experiments demonstrate clear benefits of using narrowPASEF for differential protein discovery. Finally, our strategy was applied to real use case biological samples to conduct a differential analysis of purified mouse astrocyte cells across two different conditions. narrowPASEF improved the proteome depth by 13%, considering proteins quantified with a coefficient of variation (CV) of <20%, and led to a 68% (435 vs 729) increase in differentially expressed proteins. These results provide an opportunity for a more precise and comprehensive analysis of the biological functions of biomarkers, offering a more profound understanding of the disease mechanisms. The benefits of our sample-aware narrowPASEF strategy demonstrated the most substantial impact on low-abundance proteins. Overall, these results show promise for more valuable and robust biomarker discoveries in the future.

Proteomics↗
PubMed2025

Establishing a Top-Down Proteomics Platform on a Time-of-Flight Instrument with Electron-Activated Dissociation.

Top-down proteomics is the study of intact proteins and their post-translational modifications with mass spectrometry. Historically, this field is more challenging than its bottom-up counterpart because the species are much bigger and have a larger number of possible combinations of sequences and modifications; thus, there is a great need for technological development. With improvements in instrumentation and a multiplicity of fragmentation modes available, top-down proteomics is quickly gaining in popularity with renewed attention on increasing confidence in identification and quantification. Here, we systematically evaluated the Sciex ZenoTOF 7600 system for top-down proteomics, applying standards in the field to validate the platform and further experimenting with its capabilities in electron-activated dissociation and post-translational modification site localization. The instrument demonstrated robustness in standard proteins for platform QC, as aided by zeno trapping. We were also able to apply this to histone post-translational modifications, achieving high sequence coverage that allowed PTM's site localization across protein sequences with optimized EAD fragmentation. We demonstrated the ability to analyze proteins spanning the mass range and included analysis of glycosylated proteins. This is a reference point for future top-down proteomics experiments to be conducted on the ZenoTOF 7600 system.

Proteomics↗
PubMedDate not supplied

Proteome analysis of antibody-expressing CHO cells in response to hyperosmotic pressure.

To better understand intracellular responses to hyperosmotic pressure of recombinant Chinese hamster ovary (rCHO) cells expressing an antibody, we have taken a proteomics approach. Using two-dimensional electrophoresis and mass spectrometry, a proteome profile of rCHO cells comprising 23 identified proteins was established. On the basis of this proteome profile, we found three proteins of which expression levels were significantly changed at 450 mOsm/kg. Compared to the results at 300 mOsm/kg, two glycolytic enzymes, glyceraldehyde-3-phosphate dehydrogenase and pyruvate kinase, were found to be up-regulated, probably leading to an increased metabolic energy for antibody synthesis. The elevation of specific glucose consumption rate at 450 mOsm/kg agreed with the up-regulation of these glycolytic enzymes. On the other hand, tubulin expression was down-regulated, reflecting a depressed cell growth rate at 450 mOsm/kg. Taken together, this study shows the potential of the proteomics approach in understanding intracellular and physiological changes in cells and seeking a better insight into possible environmental or genetic manipulation approaches for increasing foreign protein production in rCHO cells.

Amino Acid Sequence↗
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↗
PubMed2025

SynchroSep-MS: Parallel LC Separations for Multiplexed Proteomics.

Achieving high throughput remains a challenge in MS-based proteomics for large-scale applications. We introduce SynchroSep-MS, a novel method for parallelized, label-free proteome analysis that leverages the rapid acquisition speed of modern mass spectrometers. This approach employs multiple liquid chromatography columns, each with an independent sample, simultaneously introduced into a single mass spectrometer inlet. A precisely controlled retention time offset between sample injections creates distinct elution profiles, facilitating unambiguous analyte assignment. We modified the DIA-NN workflow to effectively process these unique parallelized data, accounting for retention time offsets. Using a dual-column setup with mouse brain peptides, SynchroSep-MS detected approximately 16,700 unique protein groups, nearly doubling the peptide information obtained from a conventional single proteome analysis. The method demonstrated excellent precision and reproducibility (median protein %RSDs less than 4%) and high quantitative linearity (median R2 greater than 0.96) with minimal matrix interference. SynchroSep-MS represents a new paradigm for data collection and the first example of label-free multiplexed proteome analysis via parallel LC separations, offering a direct strategy to accelerate throughput for demanding applications such as large-scale clinical cohorts and single-cell analyses without compromising peak capacity or causing ionization suppression.

Proteomics↗
PubMedDate not supplied

Clinical proteomics: revolutionizing disease detection and patient tailoring therapy.

The evolving discipline of Clinical Proteomics is more than simply describing and enumerating the systematic changes in the protein constituency of a cell, or just generating lists of proteins that increase or decrease in expression as a cause or consequence of disease. Clinical applications of proteomics involve the use of proteomic technologies at the bedside with the ultimate goal to characterize the information flow through the intra- and extracellular molecular protein networks that interconnect organ and circulatory systems together. These networks are both new targets for therapeutics themselves as well as underpin the dynamic changes that give rise to cascades of new diagnostic biomarkers. The analysis of human cancer can be used as a model for how clinical proteomics is having an impact at the bedside for early detection, rational therapeutic targeting, and patient-tailored therapy.

Animals↗
PubMedDate not supplied

Comparative plasma proteome analysis of lymphoma-bearing SJL mice.

In SJL mice, growth of RcsX lymphoma cells induces an inflammatory response by stimulating V(beta)16+ T cells. During inflammation, various serum protein levels can increase (e.g., acute phase reactants) or decrease (e.g., albumin), and most of these altered proteins are thus potential biomarkers. Although blood plasma is a valuable and promising sample for biomarker discovery for diseases or for novel drug targets, its proteome is complex. To address this, we have focused on a comprehensive comparison of the plasma proteomes from normal and RcsX-tumor-bearing SJL mice using the 1D-Gel-LC-MS/MS method after removing albumin and immunoglobulins. This analysis resulted in the identification of a total of 1079 nonredundant mouse plasma proteins; more than 480 in normal and 790 in RcsX-tumor-bearing SJL mouse plasma. Of these, only 191 proteins were found in common. The molecular weights ranged from 2 to 876 kDa, covering the pI values between 4.22 and 12.09, and included proteins with predicted transmembrane domains. By comparing the plasma proteomic profile of normal and RcsX-tumor-bearing SJL mice, we found significant changes in the levels of many proteins in RcsX-tumor-bearing mouse plasma. Most of the up-regulated proteins were identified as acute-phase proteins (APPs). Also, several unique proteins i.e., haptoglobin, proteosome subunits, fetuin-B, 14-3-3 zeta, MAGE-B4 antigen, etc, were found only in the tumor-bearing mouse plasma; either secreted, shed by membrane vesicles, or externalized due to cell death. These results affirm the effectiveness of this approach for protein identification from small samples, and for comparative proteomics in potential animal models of human disorders.

14-3-3 Proteins↗
PubMedDate not supplied

Analysis of protein expression during oxidative stress in breast epithelial cells using a stable isotope labeled proteome internal standard.

Normal cells undergo a variety of molecular and physiological changes upon malignant transformation, including their responses to environmental factors that induce oxidative stress. Understanding the molecular pathways regulating these changes would facilitate the development of novel cancer treatments and chemoprevention strategies. Differences in the oxidative stress response were investigated between nonmalignant (S-1) and malignant (T4-2) cell lines (both derived from the HMT-3522 breast epithelial cells) using proteomic approaches. A modification of the stable isotope labeling of amino acids in cell culture (SILAC) approach was employed in which a [(13)C,(15)N]-labeled proteome was prepared from both cells. Relative quantification of the proteome derived from the S-1 cells and the T4-2 cells was then conducted using a [(13)C,(15)N]-labeled proteome as the internal standard. Differentially expressed proteins that changed in a similar manner in both cell lines were mainly stress response proteins, including heat shock proteins, peroxiredoxins, and redox proteins. Proteins that showed significant change in expression level in only one the cell lines included cytoskeleton proteins and proteins implicated in cell cycle and apoptosis regulation. Fortilin was found to be significantly up regulated in the transformed T4-2 cells after H(2)O(2) treatment but not in the parental S-1 cells. However, Ran/TC4 was up regulated by H(2)O(2) in the nonmalignant breast epithelial cells but not in the malignant cells. These results suggest that the malignant T4-2 cells have acquired more resistance to H(2)O(2)-induced apoptosis than the nonmalignant S-1 cells.

Apoptosis↗
PubMedDate not supplied

Strategy to design improved proteomic experiments based on statistical analyses of the chemical properties of identified peptides.

Proteomics is an emerging field that uses many types of proteomic platforms however has few standardized procedures. Deciding which platform to use to perform large-scale proteomic studies is either based on personal preference or on so-called "figures of merit" such as dynamic range, resolution, and the limit of detection; these factors are often insufficient to predict the outcome of the experiment as the detection of peptides correlates to the chemical properties of each peptide. There is a need for a novel figure of merit that describes the overall performance of a platform based on measured output, which in proteomics is often a list of identified peptides. We report the development of such a figure of merit based on a predictive genetic algorithm. This algorithm takes into account the properties of the observed peptides such as length, hydrophobicity, and pI. Several large-scale studies that differed in sample type or platform were used to demonstrate the usefulness of the algorithm for improved experimental design. The figures that were obtained were clustered to find platforms that were biased in similar ways. Even though some platforms are different, they lead to the identification of similar peptide types and are thus redundant. The algorithm can thus be used as an exploratory tool to suggest a minimal number of complementary experiments in order to maximize experimental efficiency.

Algorithms↗
PubMed2006

Mass spectrometry-based proteomics combined with bioinformatic tools for bacterial classification.

Timely classification and identification of bacteria is of vital importance in many areas of public health. We present a mass spectrometry (MS)-based proteomics approach for bacterial classification. In this method, a bacterial proteome database is derived from all potential protein coding open reading frames (ORFs) found in 170 fully sequenced bacterial genomes. Amino acid sequences of tryptic peptides obtained by LC-ESI MS/MS analysis of the digest of bacterial cell extracts are assigned to individual bacterial proteomes in the database. Phylogenetic profiles of these peptides are used to create a matrix of sequence-to-bacterium assignments. These matrixes, viewed as specific assignment bitmaps, are analyzed using statistical tools to reveal the relatedness between a test bacterial sample and the microorganism database. It is shown that, if a sufficient amount of sequence information is obtained from the MS/MS experiments, a bacterial sample can be classified to a strain level by using this proteomics method, leading to its positive identification.

Amino Acid Sequence↗
PubMed2006

One-step fractionation of complex proteomes enables detection of low abundant analytes using antibody-based microarrays.

Antibody-based microarray is a novel technology with great promise within high-throughput proteomics. The tremendous complexity of all proteomes will, however, pose major technological challenges, especially when targeting low-abundant analytes that remains to be resolved. In this paper, we have shown that antibody microarrays readily could be used for screening of low-abundant low molecular weight analytes in complex proteomes by optimizing the sample format. Focused antibody microarrays, based on human recombinant single-chain Fv anti-cytokine antibodies on Ni2+-NTA functionalized glass slides or black polymer Maxisorp substrates, and crude cell supernatants from activated dendritic cells, containing low levels of secreted cytokines, was used for evaluation. The proteome was pre-fractionated based on size in a simple one-step procedure using centrifugal filter devices of various molecular weight cutoffs. The results showed that the generation of a nondiluted low molecular weight (LMW) fraction, corresponding to less than 2% of the original protein content, was critical for the successful screening of cytokines in the sub pg/mL range. The reduced complexity of the LMW fraction significantly improved the assay sensitivity, by improving the fluorescent tagging step and/or reducing the nonspecific binding to the substrates.

Chemical Fractionation↗
PubMed2006

Extracellular matrix proteome of chickpea (Cicer arietinum L.) illustrates pathway abundance, novel protein functions and evolutionary perspect.

The extracellular matrix (ECM) or cell wall is a dynamic system and serves as the first line mediator in cell signaling to perceive and transmit extra- and intercellular signals in many pathways. Although ECM is a conserved compartment ubiquitously present throughout evolution, a compositional variation does exist among different organisms. ECM proteins account for 10% of the ECM mass, however, comprise several hundreds of different molecules with diverse functions. To understand the function of ECM proteins, we have developed the cell wall proteome of a crop legume, chickpea (Cicer arietinum). This comprehensive overview of the proteome would provide a basis for future comparative proteomic efforts for this important crop. Proteomic analyses revealed new ECM proteins of unknown functions vis-à-vis the presence of many known cell wall proteins. In addition, we report here evidence for the presence of unexpected proteins with known biochemical activities, which have never been associated with ECM.

Cell Wall↗
PubMed2006

A soluble 3D LC/MS/MS proteome of the filamentous cyanobacterium Nostoc punctiforme.

Nostoc punctiforme is an oxygenic photoautotrophic cyanobacterium with multiple developmental states, which can form nitrogen-fixing symbioses with a variety of terrestrial plants. 3D LC/MS/MS shotgun peptide sequencing was used to analyze the proteome when N. punctiforme is grown in continuous moderate light with ammonia as the nitrogen source. The soluble proteome includes 1575 proteins, 50% of which can be assigned to core metabolic and transport functions. Another 39% are assigned to proteins with no known function, a substantially higher fraction than in the Escherichia coli proteome. Many expressed proteins protect against oxidative and light stress. Seventy-one sensor histidine kinases, response regulators, and serine/threonine kinases, individually and as hybrid, multidomain proteins, were identified, reflecting a substantial capacity to sense and respond to environmental change. Proteins encoded by each of the five N. punctiforme plasmids were identified, as were 10 transposases, reflecting the plasticity of the N. punctiforme genome. This core proteome sets the stage for comparison with that of other developmental states.

Bacterial Proteins↗
PubMed2004

A scaleable and integrated crystallization pipeline applied to mining the Thermotoga maritima proteome.

The wealth of genomic data available for many organisms has set the stage for the next phase of structure-function analysis. High-throughput structural genomics is currently the method of choice for rapid analysis of protein structure-function relationships on a proteome-wide basis. The Joint Center for Structural Genomics (JCSG), established in 2000 under the NIH/NIGMS Protein Structure Initiative, has developed and implemented an integrated high-throughput structure pipeline and applied it in a 2-tiered approach to mining the proteome of the thermophilic bacterium Thermotoga maritima. In the first tier, the successful application of this integrated pipeline has resulted in the cloning and expression of 73% of the T. maritima proteome (1376 out of 1877 predicted genes), and has identified 465 proteins which produced crystal hits. These 465 proteins were compared with existing structural information and a subset of 269 targets were selected to process towards structure determination in a second tier effort. To date, the JCSG pipeline applied to the Thermotoga maritima proteome has resulted in 55 new structures and has identified 6 novel folds and continues to identify structures with novel features.

Bacterial Proteins↗
PubMed2026

In vivo labeling-based proteomic analysis of early follicle oocytes and cisplatin-induced alterations in mice.

A systematic proteomic profile of oocytes from early-stage follicles, particularly primordial follicles, is critical to protect female reproductive capacity in the context of chemotherapy, yet progress has been hindered by the rarity of oocyte samples and technical challenges associated with oocyte isolation. In this study, we generated in vivo oocyte protein labeling APEX fluorescent mice. With these mice, we reconstructed the ovary in 3D, enabling precise quantification of follicles and identified 2772 proteins and 2878 gene transcripts in oocytes predominantly from primordial follicles. Proteomic shifts of short-time cisplatin treatment revealed that many altered proteins were involved in DNA damage repair and histone modification. Notably, simultaneous application of cisplatin and EZH2's inhibitor, GSK126, relieved cisplatin-induced oocyte developmental defects. Our study provides a systematic proteomic characterization of oocytes predominantly from primordial follicles in female mice, and reveals dynamic proteome shifts in response to chemotherapeutic agents, laying the foundation for targeted fertility-preserving strategies.

Animals↗
PubMed2026

Plasma proteomic profiling of septic shock and acute pancreatitis identifies shared signatures and disease-specific pathways.

Septic shock represents the most severe form of infection-driven systemic inflammation, whereas acute pancreatitis induces a sterile inflammatory response. Although clinically similar, their molecular profiles may reveal distinct mechanisms underlying infectious and non-infectious inflammation. We performed plasma proteomic profiling using LC-MS/MS in patients with septic shock (n&#x2009;=&#x2009;13), acute pancreatitis (n&#x2009;=&#x2009;8), and healthy controls (n&#x2009;=&#x2009;8). Among 663 quantified proteins, 231 were differentially expressed in septic shock versus controls, 83 in pancreatitis versus controls, and 29 in septic shock versus pancreatitis. Septic shock was characterized by higher plasma concentrations of MARCKS, HSP90AA1, PSAP, CD163, and GANAB, whereas pancreatitis showed higher levels of CPA1, APOC4, APOC3, BPGM, and APOC2. Cluster analysis demonstrated separation between groups, with overlapping proteomic patterns in sepsis and pancreatitis. Gene Ontology and KEGG analyses revealed shared inflammatory signatures, including upregulation of acute-phase responses and downregulation of coagulation pathways. However, septic shock exhibited more extensive proteomic alterations, with distinct activation of PI3K-Akt signaling and suppression of lipid metabolism. In conclusion, septic shock and pancreatitis share common inflammatory pathways, while proteomic differences highlight divergent regulation of coagulation, lipid metabolism, and anti-inflammatory signaling, offering potential biomarkers to distinguish infectious from sterile systemic inflammation.

Shock, Septic↗
PubMed2006

Organellar proteomics: turning inventories into insights.

Subcellular organization is yielding to large-scale analysis. Researchers are now applying robust mass-spectrometry-based proteomics methods to obtain an inventory of biochemically isolated organelles that contain hundreds of proteins. High-resolution methods allow accurate protein identification, and novel algorithms can distinguish genuine from co-purifying components. Organellar proteomes have been analysed by bioinformatic methods and integrated with other large-scale data sets. The dynamics of organelles can also be studied by quantitative proteomics, which offers powerful methods that are complementary to fluorescence-based microscopy. Here, we review the emerging trends in this rapidly expanding area and discuss the role of organellar proteomics in the context of functional genomics and systems biology.

Animals↗
PubMed2004

The use of isotope-coded affinity tags (ICAT) to study organelle proteomes in Arabidopsis thaliana.

Organelle proteomics is the analysis of the protein contents of a subcellular compartment. Proteins identified in subcellular proteomic studies can only be assigned to an organelle if there are no contaminants present in the sample preparation. As a result, the majority of plant organelle proteomic studies have focused on the chloroplast and mitochondria, which can be isolated relatively easily. However, the isolation of components of the endomembrane system is far more difficult due to their similar sizes and densities. For this reason, quantitative proteomics methods are being developed to enable the assignment of proteins to a specific component of the endomembrane system without the need to obtain pure organelles.

Arabidopsis↗