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Results for “Integrated proteomics”

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PubMed2026

Multi-omics analysis reveals Protein Kinase A-associated regulatory remodeling during adaptation of Trichoderma reesei to lignocellulosic substrate.

The filamentous fungus Trichoderma reesei is a major industrial source of holocellulolytic enzymes, and its response to complex carbon sources is regulated by nutrient-sensing mechanisms, including the cyclic adenosine monophosphate (cAMP)-protein kinase A (PKA) signaling pathway. Here, we integrated transcriptomics, quantitative proteomics, and phosphoproteomics to analyze PKAc1-associated responses in the parental strain QM9414 and a Δpkac1 strain cultivated under glucose or sugarcane bagasse conditions. Deletion of pkac1 was associated with altered growth-related phenotypes and reduced extracellular activities of selected biomass-depolymerizing enzymes. Multi-omics profiling revealed condition-dependent changes affecting subsets of carbohydrate-active enzymes (CAZymes) genes and proteins, nutrient transporters, stress-associated proteins, and regulatory factors. Phosphoproteomics identified phosphorylation-state changes associated with pkac1 deletion, including reduced phosphorylation at sites enriched for the PKA consensus motif. In silico peptide docking was used to prioritize candidate PKAc1-associated substrates for future validation, including a Sec 7-derived peptide with favorable docking behavior relative to the control peptide. Together, these data support a working model in which PKAc1 contributes to regulatory and phosphorylation-state remodeling during adaptation to sugarcane bagasse, with effects on the magnitude and/or timing of selected CAZyme-related outputs in T. reesei.

Trichoderma↗

PubMed2026

Immunopeptidomics-guided cancer vaccine design: Advances, challenges, and emerging opportunities.

Selecting clinically relevant tumor antigens remains a major challenge in the development of therapeutic cancer vaccines. Although computational approaches have considerably improved neoantigen prediction, many candidate epitopes identified in silico are not ultimately presented on the tumor cell surface. The emergence of immunopeptidomics has provided direct access to naturally processed HLA-associated peptides and has offered new opportunities for antigen discovery. Increasing evidence has shown that information derived from the immunopeptidome becomes considerably more informative when interpreted alongside genomic, transcriptomic, and proteomic data. This integrative view has broadened the spectrum of targetable antigens and has also revealed important limitations related to peptide abundance, HLA diversity, tumor heterogeneity, and the imperfect relationship between antigen presentation and immunogenicity. These issues have renewed interest in multi-antigen vaccine strategies designed to better reflect the complexity of tumor antigen landscapes. Advances in bioinformatics and artificial intelligence are facilitating the interpretation of increasingly complex datasets and are beginning to support more systematic approaches to antigen prioritization. In this review, we discuss how immunopeptidomics is contributing to next-generation cancer vaccine development, summarize the major translational challenges, and highlight emerging concepts that may improve the clinical applicability of immunopeptidomics-guided immunotherapy.

Cancer immunotherapy↗

PubMed2026

Multiomic insights into fungal polylactic acid degradation: Metabolic adaptation and hydrolytic mechanisms of Sporobolomyces pararoseus.

Polylactic acid (PLA), a biodegradable polyester from renewable resources, is a sustainable alternative to petrochemical plastics. However, its environmental degradation is inefficient naturally, requiring specific microbial activities. While bacterial PLA-degrading mechanisms are well documented, fungal degrading systems-particularly their molecular mechanisms-are underexplored.We isolated Sporobolomyces pararoseus ZRQ01 from the gut microbiota of PLA-fed mealworms. This fungal strain noticeably degraded PLA in PLA-containing medium supplemented with 2% glucose. Biodegradation assays revealed 22.8% loss of the PLA film weight after 35 days of incubation, and scanning electron microscopy confirmed extensive surface erosion and pore formation. Integrated transcriptomic and proteomic analyses, together with the reference genome of S. pararoseus ZRQ01, revealed that S. pararoseus ZRQ01 upregulates hydrolytic enzymes at both transcript and protein levels to cleave PLA into lactic acid. After lactic acid is transferred into S. pararoseus ZRQ01 cells by monocarboxylate transporters with increased abundance, it is assimilated by pathways of pyruvate metabolism and the TCA cycle with increased protein abundance. Intriguingly, upregulation of genes in autophagy-related and MAPK signaling pathways underscores an adaptive stress response potentially supporting cellular homeostasis and degradation-related gene expression. Our results highlight S. pararoseus ZRQ01's metabolic potential for bioremediation and offer insights into fungal bioplastic degradation pathways.

Polyesters↗

PubMed2026

Integrative multi-omics analysis of metabolite-protein interaction networks across different stages of coronary heart disease.

To elucidate the molecular characteristics of synergistic interactions across the clinical stages of coronary heart disease (CHD)-specifically stable angina pectoris (SAP), unstable angina pectoris (UAP), and acute myocardial infarction (AMI)-through integrated metabolomic and proteomic analyses. Based on a cohort including SAP, UAP, AMI, and healthy controls, metabolomic and proteomic analyses were performed to identify differentially expressed molecules, followed by KEGG pathway enrichment analysis. Pathways co-enriched across both omics platforms were selected to construct metabolite-protein interaction networks. The number of pathways co-enriched in both metabolomic and proteomic analyses increased markedly with disease stage. Only two pathways (histidine metabolism and arginine and proline metabolism) were identified in the SAP stage; this number increased to five in the UAP stage (including ferroptosis and efferocytosis) and expanded to 25 in the AMI stage, encompassing three major functional modules: immune inflammation, metabolic reprogramming, and cell signaling. The core network exhibited a stepwise increase in connectivity, shifting from a sparse structure in the SAP stage to a highly interconnected architecture in the AMI stage, with L-glutamate and KNG1 identified as the central hubs in this cross-sectional network. In addition, CNDP1 exhibited a stage-dependent functional transition, shifting from downregulation in SAP to upregulation in AMI. In this cross-sectional analysis, metabolic dysregulation and immune activation exhibited stepwise increases in interconnectivity across the SAP, UAP, and AMI groups, with the most extensive crosstalk observed in the AMI stage-a network configuration consistent with a tightly coupled "molecular storm". These findings provide novel insights into stage-associated molecular signatures of CHD and identify candidate hub molecules for stage-oriented therapeutic investigation.

Humans↗

PubMed2026

The multilayered cuticle underlying structural coloration in red algae shares features with the metazoan extracellular matrix.

Structural coloration, a physical phenomenon observed in many living organisms, may arise from the interference of light with highly organized surface nanostructures. In some seaweeds, these nanostructures consist of cuticular lamellae in the outer part of the extracellular matrix (ECM) of the epidermis. However, the chemical composition of seaweed cuticles is poorly understood and the molecular components of lamellae remain unidentified. Here, we use integrated genomic, transcriptomic, proteomic, and metabolomic approaches together with analytical profiling of carbohydrates to determine the composition of the multilayered cuticle in the red alga Chondrus crispus and assess its evolutionary conservation. The structural assembly reveals common features with the ECM of animals. The carbohydrate fraction includes a complex mixture of carrageenans and glycosaminoglycan-like compositions. A major von Willebrand factor A domain protein, Lamellae Cohesive Protein, plays a critical role in protein-protein interactions and binding to sulfated polysaccharides. We have further identified the major proteins of the algal cuticle, providing a framework for addressing the evolutionary origins of the cuticle and raising important questions regarding its role, particularly across the red algal life cycle marked by major structural differences in its ECM.

Extracellular Matrix↗

PubMed2026

Activation of mTOR pathway by human cytomegalovirus promoting host ribosomal protein expression by coordinated transcriptional and translational controls.

Human cytomegalovirus (HCMV) profoundly reprograms host transcription and RNA metabolism, yet its impact on transcription start site (TSS) regulation of host genes remains poorly understood. Here, we employed NanoCap Analysis of Gene Expression sequencing (NanoCAGE-seq) to investigate HCMV-driven changes in alternative TSS usage across the host transcriptome. We identified widespread TSS switching, with ribosomal protein genes (RPGs) emerging as a highly enriched category. Alternative TSS usage produced isoforms with distinct 5'untranslated regions (UTRs), thereby altering cis-regulatory elements that shape translational efficiency. Integrative transcriptomic and proteomic analyses revealed a paradoxical accumulation of RPG proteins despite transcriptional downregulation during infection. Using 5' Rapid Amplification of cDNA Ends (5'RACE), we characterized four RPGs of RPL4, RPS11, RPS23, and RPS24 that generated 5'UTR variants through alternative TSS usage. Notably, isoforms containing a 5'terminal oligopyrimidine (5'TOP) motif were significantly enriched, correlating with mTOR activation induced by HCMV. Functional assays with bicistronic reporter constructs in HEK293 cells and infection models in human embryonic lung fibroblasts demonstrated that the RPL4 5'TOP isoform exhibited enhanced mTORC1-driven translation compared with non-5'TOP counterparts. Importantly, RPL4 upregulation facilitated viral protein synthesis and boosted production of infectious virions. Together, our findings reveal that dynamic TSS switching of RPGs provides a simple, yet effective, mechanism for fine-tuning mTORC1-responsive translation. By co-opting host transcriptional and translational programs, HCMV enhances ribosome function to optimize the cellular environment for productive viral replication.

Humans↗

PubMed2005

Recent advancements in differential proteomics based on stable isotope coding.

Stable isotope coding continues to be a powerful approach in comparative proteomics. This review focuses on recent developments in stable isotope coding-based strategies targeted towards protein expression, protein interactions with other biomolecules, post-translational modifications and absolute quantification. The focus of the bulk of proteomics studies is still on protein expression. An important recent application of isotope coding has been in organelle proteomics. The review ends with the conclusion that isotope coding remains an integral part of quantitative proteomics. There is, however, a need to develop coding strategies which can differentiate changes in protein expression and post-translational modification, address issues of protein dynamic range and facilitate real-time detection of proteins which show a statistically significant change after stimulus.

Amino Acids↗

PubMed2004

A statistical framework for combining and interpreting proteomic datasets.

MOTIVATION: To identify accurately protein function on a proteome-wide scale requires integrating data within and between high-throughput experiments. High-throughput proteomic datasets often have high rates of errors and thus yield incomplete and contradictory information. In this study, we develop a simple statistical framework using Bayes' law to interpret such data and combine information from different high-throughput experiments. In order to illustrate our approach we apply it to two protein complex purification datasets. RESULTS: Our approach shows how to use high-throughput data to calculate accurately the probability that two proteins are part of the same complex. Importantly, our approach does not need a reference set of verified protein interactions to determine false positive and false negative error rates of protein association. We also demonstrate how to combine information from two separate protein purification datasets into a combined dataset that has greater coverage and accuracy than either dataset alone. In addition, we also provide a technique for estimating the total number of proteins which can be detected using a particular experimental technique. AVAILABILITY: A suite of simple programs to accomplish some of the above tasks is available at www.unm.edu/~compbio/software/DatasetAssess

Algorithms↗

PubMed2026

Recent Advances in the Comprehension of Molecular and Genetic Mechanisms Underlying Yeast Biocontrol Efficacy Against Fungal Pathogens in Agriculture.

Recent advances in biotechnologies have enabled scientists to uncover biological processes across multiple research fields. Still, the molecular and genetic mechanisms underlying the biological control efficacy of yeast biocontrol agents (YBCAs) against fungal plant pathogens remain incompletely elucidated. This review focuses on recent insights into the regulatory bases and molecular interplay underlying successful disease control by YBCAs. It provides a detailed description of core antagonistic molecular mechanisms-nutrient and iron competition, mycoparasitism via cell wall degradation, antifungal compounds production, oxidative stress resistance, biofilm formation and colonization, and induction of the host defense responses-and integrates genomic, transcriptomic, proteomic, and metabolomic evidence to elucidate each mechanism. Further, how genetic engineering-based approaches that leverage omics data and functional genetics can help overcoming obstacles to translate YBCAs efficacy from laboratory conditions to the field are also discussed. Finally, the use of the CRISPR-Cas technology is recommended to better exploit how master transcription factors coordinate multiple mechanisms simultaneously; these factors are crucial for the synergistic antifungal effect, which is critical for developing highly effective YBCAs. Ultimately, the mechanism-based perspective provides a unified conceptual framework for understanding YBCAs efficacy and can guide the rational design of next-generation biocontrol agents for sustainable agriculture.

CRISPR-Cas technology↗

PubMed2026

Monocytes Defined by Platelet Interactions and Oxidative Stress Signaling Underlie HIV-Associated Atherosclerosis.

BACKGROUND: Monocytes contribute to atherosclerosis by migrating into inflamed endothelium and differentiating into lipid-laden macrophages. In people living with HIV, chronic inflammation increases atherosclerosis risk, yet the role of specific monocyte subsets remains unclear. We investigated how distinct monocyte populations contribute to vascular pathology in early HIV-associated atherosclerosis. METHODS: We profiled 123 965 circulating monocytes using single-cell RNA sequencing and integrated plasma microparticle proteomics in 32 individuals stratified by HIV and atherosclerosis status. Supervised learning identified cluster- and disease-specific signatures, validated by platelet-monocyte cocultures, reverse transcription-quantitative polymerase chain reaction, bulk RNA sequencing, flow cytometry, and ELISA. RESULTS: Seven monocyte clusters were identified, including a subset characterized by platelet-monocyte complexes. Bulk RNA sequencing of platelet-monocyte cocultures revealed platelet-driven upregulation of genes involved in inflammation, lipid metabolism, oxidative stress, and endothelial adhesion. Platelet-monocyte complex-derived macrophages secreted higher levels of TGF-β (transforming growth factor-β) and IL-10 (interleukin-10), displayed decreased CD14 and increased CD80/CD86 while retaining CD36, and promoted endothelial-to-mesenchymal transition (decreased expression of CDH5 and PECAM1; increased expression of S100A4 and markers of vascular inflammation (ICAM1), VCAM), and IL-6 (interleukin-6), and CCL2 (C-C motif chemokine ligand 2) secretion). Additionally, CD14+ monocytes from HIV+ atherosclerosis-negative and HIV+ atherosclerosis-positive groups showed enhanced ROS-NRF2 (reactive oxygen species-nuclear factor erythroid 2-related factor 2) pathway activities, supported by increased basal and H2O2-induced p90RSK phosphorylation, indicating oxidative stress priming. CONCLUSIONS: Two monocyte clusters contribute independently to vascular immune dysregulation in people living with HIV. Platelet-monocyte complex-derived macrophages promote endothelial dysfunction while adopting a profibrotic cytokine profile. CD14+ monocytes show heightened oxidative signaling and stress responses, consistent with vascular activation. Together, these mechanisms may accelerate atherosclerosis development in HIV, even in the absence of traditional cardiovascular risk factors.

Humans↗

PubMed2006

Thematic review series: systems biology approaches to metabolic and cardiovascular disorders. Lipidomics: a global approach to lipid analysis in biological systems.

Lipids are water-insoluble molecules that have a wide variety of functions within cells, including: 1) maintenance of electrochemical gradients; 2) subcellular partitioning; 3) first- and second-messenger cell signaling; 4) energy storage; and 5) protein trafficking and membrane anchoring. The physiological importance of lipids is illustrated by the numerous diseases to which lipid abnormalities contribute, including atherosclerosis, diabetes, obesity, and Alzheimer's disease. Lipidomics, a branch of metabolomics, is a systems-based study of all lipids, the molecules with which they interact, and their function within the cell. Recent advances in soft-ionization mass spectrometry, combined with established separation techniques, have allowed the rapid and sensitive detection of a variety of lipid species with minimal sample preparation. A "lipid profile" from a crude lipid extract is a mass spectrum of the composition and abundance of the lipids it contains, which can be used to monitor changes over time and in response to particular stimuli. Lipidomics, integrated with genomics, proteomics, and metabolomics, will contribute toward understanding how lipids function in a biological system and will provide a powerful tool for elucidating the mechanism of lipid-based disease, for biomarker screening, and for monitoring pharmacologic therapy.

Animals↗

PubMed2026

Systematic profiling of nudivirus-like genes reveals conserved and differentiated roles in a domesticated endogenous virus.

Cotesia vestalis bracovirus (CvBV) is a type of domesticated endogenous virus (DEV) derived from ancestral nudiviruses that is integrated into the genome of the parasitoid wasp Cotesia vestalis. The CvBV proviral genome is composed of two distinct components: one encoding genes associated with virion morphogenesis and assembly, and the other harboring virulence genes that are excised, circularized, and packaged into virions. CvBV replication and particle assembly occur exclusively in the ovaries of female wasps. While prior studies have largely focused on the function of virulence genes during parasitization, the molecular mechanisms underlying CvBV replication and assembly remain poorly understood. Here, we identified 71 nudivirus-like genes in the C. vestalis genome through integrated transcriptomic and proteomic analyses. Using gene silencing and microscopy-based imaging approaches, we functionally characterized 24 key genes involved in DNA replication (helicase, integrase-1, and integrase-2), transcriptional regulation (p47, lef-5, and lef-9), capsid formation (vp39, PmV, HzNVorf9-1, HzNVorf9-2, HzNVorf106, 38k, 27b, and K425_459), envelope formation (11k, 17a-1, 35a-1, 35a-2, and K425_461), virion assembly (vlf-1, HzNVorf140-1, and HzNVorf140-2), and viral infectivity (pif-0 and vp91). Although the functions of most nudivirus-like genes are generally conserved among baculoviruses, nudiviruses, and bracoviruses, lef-5, K425_459, 11k, and vp91 appear to have undergone functional divergence relative to their homologs in baculoviruses, nudiviruses, and Microplitis demolitor bracovirus, highlighting lineage-specific adaptations in CvBV. Collectively, our work provides a molecular framework for understanding CvBV assembly and serves as a valuable resource for investigating bracovirus evolution.

Animals↗

PubMed2025

Multi-Omics Analysis of the Potential Mechanisms of Skin Albinism in Edangered Percocypris pingi: Abnormal Ubiquitination and Calcium Signal Inhibition.

Percocypris pingi is an endangered protected fish species in China. Its albino variants exhibit growth retardation and physiological abnormalities. Understanding its albinism mechanism holds significant scientific importance for molecular breeding programs and disease model development. This study integrated transcriptomic and proteomic analyses, combined with histopathological and molecular biological techniques, to systematically compare molecular differences in skin tissues between albino and wild-type P. pingi, with a focus on elucidating the multidimensional regulatory mechanisms underlying skin albinism. Our findings suggest that albinism in P. pingi is synergistically driven by hyperactivation of ubiquitin-mediated proteolysis (which suppressed TYR/TYRP1 enzymatic activity and disrupted the pH homeostasis of melanosomes), and inhibition of calcium signaling (which impeded melanin transport). This discovery provides novel insights into the mechanisms of pigment loss in fish species and offers a valuable reference for molecular breeding of endangered species as well as research on pigmentation-related disorders.

Animals↗

PubMed2002

Biomic study of human myeloid leukemia cells differentiation to macrophages using DNA array, proteomic, and bioinformatic analytical methods.

A biomic approach by integrating three independent methods, DNA microarray, proteomics and bioinformatics, is used to study the differentiation of human myeloid leukemia cell line HL-60 into macrophages when induced by 12-O-tetradecanoyl-phorbol-13-acetate (TPA). Analysis of gene expression changes at the RNA level using cDNA against an array of 6033 human genes showed that 5950 (98.6%) of the genes were expressed in the HL-60 cells. A total of 624 genes (10.5%) were found to be regulated during HL-60 cell differentiation. Most of these genes have not been previously associated with HL-60 cells and include genes encoded for secreted proteins as well as genes involved in cell adhesion, signaling transduction, and metabolism. Protein analysis using two-dimensional gel electrophoresis showed a total of 682 distinct protein spots; 136 spots (19.9%) exhibited quantitative changes between HL-60 control and macrophages. These differentially expressed proteins were identified by mass spectrometry. We developed a bioinformatics program, the Bulk Gene Search System (BGSS, http://www.sinica.edu.tw:8900/perl/genequery.pl) to search for the functions of genes and proteins identified by cDNA microarrays and proteomics. The identified regulated proteins and genes were classified into seven groups according to subcellular locations and functions. This powerful holistic biomic approach using cDNA microarray, proteomics coupled to bioinformatics can provide in-depth information on the impact and importance of the regulated genes and proteins for HL-60 differentiation.

Cell Differentiation↗

PubMed2026

Kv11.1 (hERG) Protein Interaction Networks Connect Endocytic Trafficking to Polygenic Influences on Cardiac Repolarization.

Polygenic scores (PGS) capture the combined effect of many common genetic variants on quantitative traits and disease risk, yet their functional consequences at the protein level remain poorly defined. Here, we integrated quantitative and interaction proteomics to resolve how polygenic liability for cardiac repolarization manifests in human cells. We studied human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) from donors with extreme PGS for QT interval duration, a clinically relevant electrophysiologic trait associated with arrhythmia risk. Global quantitative proteomics revealed increased abundance of mitochondrial proteins in high-PGS cardiomyocytes. To define protein network-level effects on a key repolarizing ion channel, we performed multiplexed affinity purification-mass spectrometry (AP-MS) of Kv11.1. While mitochondrial changes did not directly explain Kv11.1-associated complexes, interactome analysis revealed increased association of Kv11.1 with myosin motor proteins and endosomal recycling machinery in high-PGS cells. These findings suggest altered channel trafficking dynamics of Kv11.1, distinct from the trafficking defects observed in monogenic Kv11.1 variants. Together, these data show that integrating global and interaction proteomics can resolve how polygenic variation reshapes protein networks. Future work using these methods could connect genomic risk to subcellular remodeling and our work provides a generalizable framework to probe the proteomic basis of complex traits. SIGNIFICANCE STATEMENT: Polygenic scores (PGS) predict disease risk, but how biological pathways are influenced by these common variants remains difficult to define. We generated human induced pluripotent stem cells from individuals with extreme high- and low- PGS for QT interval, a key electrocardiographic measure linked to arrhythmia risk. By combining global proteomics and interactomics for a common ion channel involved in regulating the QT interval (Kv11.1) we found potential mechanisms that are influenced by common genetic traits in patients. Our work provides an approach to connect polygenic scores to pathway-level molecular mechanisms in human cells and a general framework for uncovering how complex genetic architecture drives disease-relevant biology.

AP-MS↗

PubMed2026

Network methods for diagonal integration of unpaired single-cell multiomics data: a review.

MOTIVATION: Advances in single-cell sequencing have enabled multiomics profiling at unprecedented resolution; however, mass spectrometry-based single-cell proteomics (scMS) remains inherently destructive, precluding simultaneous transcriptomic capture. Unlike antibody-based methods such as CITE-seq, which permit paired profiling but are restricted to targeted protein panels, scMS provides unbiased, genome-scale coverage of the intracellular proteome yet necessitates post hoc integration of unpaired datasets. This diagonal integration challenge, where transcriptomes and proteomes are measured in separate cells lacking shared anchors, remains underserved by existing reviews, which focus predominantly on vertical integration strategies enabled by non-destructive assays. RESULTS: We survey the complete computational pipeline for constructing mechanistic proteogenomic networks from unpaired single-cell data, covering: (i) unimodal network inference such as knowledge-based approaches, probabilistic graphical models, temporal directionality inference, and generative and foundation model strategies that establish the transcriptomic scaffold; (ii) cross-modal integration architectures such as network propagation, graph neural networks (scMRDR, scmFormer, scCotag), and consensus frameworks designed explicitly for the unpaired proteomics setting; and (iii) benchmarking paradigms spanning network reconstruction (BEELINE, GRETA, CausalBench) and multi-task integration evaluation (scMultiBench, SCMMIB), with guidance on metric selection under network sparsity and class imbalance. We identify three principal axes of future development: generative proteomic translation from transcriptomic precursors, inductive prior embedding in next-generation architectures, and perturbation-based causal benchmarking. AVAILABILITY AND IMPLEMENTATION: This is a review article; no novel software is distributed. A curated benchmark resource table, methods starter guide, and per-method bottleneck annotations are provided in the Supplementary Material.

Multiomics↗

PubMed2005

Integrated microfluidic device for mass spectrometry-based proteomics and its application to biomarker discovery programs.

The present investigation describes the analytical performances of a microfluidic device comprising an enrichment column, a reversed-phase separation channel, and a nanoelectrospray emitter embedded altogether in polyimide layers. This configuration minimizes transfer lines and connections and reduces postcolumn peak broadening and dead volumes. This compact and versatile modular nanoLC-chip system was interfaced to both ion trap and time-of-flight mass spectrometers, and its analytical potentials were evaluated in the context of proteomics applications. The figures of merit of this system in terms of peak capacity, reproducibility, sensitivity, and linear dynamic range of peptide detection were determined using tryptic digests of complex protein extracts including albumin- and immunoglobulin-depleted rat plasma samples. The analysis of peak profiles for more than 600 peptide ions reproducibly detected across replicate nanoLC-chip-MS runs (n = 10) indicated that this system provided good reproducibility of retention time and peak intensity with RSD values of less than 0.5 and 9.1%, respectively. Variation in peptide abundance as low as 2-fold changes was identified for spiked tryptic digests present at levels of 2-5 fmol in plasma samples. Sensitivity measurements were performed on dilution series of protein digests spiked into rat plasma samples and provided a detection limit of 1-5 fmol. The modular concept of the microfluidic systems also facilitated the integration of two-dimensional chromatography (strong cation exchange/C18) thereby increasing the sample loading and selectivity of the nanoLC-chip-MS system. The application of this integrated device was evaluated for complex rat plasma samples to compare the number of protein identifications obtained using one- and two-dimensional nanoLC-chip-MS/MS.

Biomarkers↗

PubMed2001

[Identification of proteome molecules by proteomics using two-dimensional gel electrophoresis and MALDI-TOF MS].

Genomic technologies have enabled rapid accumulation of information from complex biological systems over the last two decades. The complete DNA sequence is now known for many organisms and the informational database obtained from genome sequencing projects has provided the base for the specification of proteome - the protein complement of genome. Genomic functions can be inferred from the analysis of gene structure and gene expression profiles because proteins are the functional molecules of an organism. Integrated technologies including protein separation, identification, characterization and information manage system are essential to analyze the proteins in complex cellular matrix. This study is focusing on the strategies of proteome analysis using sample preparation, 2-dimensional gel electrophoresis, processing of protein spots and identification of proteins, protein-protein interaction and posttranslational modification using MALDI-TOF-MS. 2-D gel electrophoresis is currently the most powerful protein separation technique and MALDI-TOF MS is powerful identification technique for protein and peptides as a sensitive, rapid, and high resolution analytical method. The developed integrated proteome technologies are very useful to understand the biological phenomena at molecular level by identifying the new molecules and their modifications in various cellular processes, and can be applied for biotechnology including medical science.

Databases, Protein↗