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PubMed2006

Clinical proteomics and mass spectrometry profiling for cancer detection.

A key challenge in the clinical proteomics of cancer is the identification of biomarkers that would enable early detection, diagnosis and monitoring of disease progression to improve long-term survival of patients. Recent advances in proteomic instrumentation and computational methodologies offer a unique chance to rapidly identify these new candidate markers or pattern of markers. The combination of retentate affinity chromatography and mass spectrometry is one of the most interesting new approaches for cancer diagnostics using proteomic profiling. This review presents two technologies in this field, surface-enhanced laser desorption/ionization time-of-flight and Clinprot, and aims to summarize the results of studies obtained with the first of them for the early diagnosis of human cancer. Despite promising results, the use of the proteomic profiling as a diagnostic tool brought some controversies and technical problems, and still requires some efforts to be standardized and validated.

Biomarkers, Tumor↗

PubMed2006

Proteomic technology for biomarker profiling in cancer: an update.

The progress in the understanding of cancer progression and early detection has been slow and frustrating due to the complex multifactorial nature and heterogeneity of the cancer syndrome. To date, no effective treatment is available for advanced cancers, which remain a major cause of morbidity and mortality. Clearly, there is urgent need to unravel novel biomarkers for early detection. Most of the functional information of the cancer-associated genes resides in the proteome. The later is an exceptionally complex biological system involving several proteins that function through posttranslational modifications and dynamic intermolecular collisions with partners. These protein complexes can be regulated by signals emanating from cancer cells, their surrounding tissue microenvironment, and/or from the host. Some proteins are secreted and/or cleaved into the extracellular milieu and may represent valuable serum biomarkers for diagnosis purpose. It is estimated that the cancer proteome may include over 1.5 million proteins as a result of posttranslational processing and modifications. Such complexity clearly highlights the need for ultra-high resolution proteomic technology for robust quantitative protein measurements and data acquisition. This review is to update the current research efforts in high-resolution proteomic technology for discovery and monitoring cancer biomarkers.

Biomarkers, Tumor↗

PubMed2006

Proteomic analysis of urine in kidney transplant patients with BK virus nephropathy.

The differentiation of BK virus-associated renal allograft nephropathy (BKVAN) from acute allograft rejection (AR) in renal transplant recipients is an important clinical problem because the treatment can be diametrically opposite for the two conditions. The aim of this discovery-phase biomarker development study was to examine feasibility of developing a noninvasive method to differentiate BKVAN from AR. Surface-enhanced laser desorption/ionization (SELDI) time-of-flight mass spectrometry analysis was used to compare proteomic profiles of urine samples of 21 patients with BKVAN, 28 patients with AR (Banff Ia to IIb), and 29 patients with stable graft function. SELDI analysis showed proteomic profiles that were significantly different in the BKVAN group versus the AR and stable transplant groups. Peaks that corresponded to m/z values of 5.872, 11.311, 11.929, 12.727, and 13.349 kD were significantly higher in patients with BKVAN. Bioinformatics analyses allowed distinction of profiles of patients with BKVAN from patients with AR and stable patients. SELDI profiles also showed a high degree of reproducibility. Proteomic analysis of urine may offer a noninvasive way to differentiate BKVAN from AR in clinical practice. The identification of individual proteomic peaks can improve further the clinical utility of this screening method.

Adult↗

PubMed2025

Four-dimensional data independent acquisition proteomics and metabolomics reveal mechanisms of hydrogen-rich water at Zusanli (ST36) point against triple-negative breast cancer in mice.

OBJECTIVE: To develop a safe and effective green therapy for triple-negative breast cancer, this study combines hydrogen-rich water with acupuncture point injection, and finds that it can prevent tumor growth and minimize cancer metastasis. METHODS: After 21 d of hydrogen rich water injection treatment on 4T1 (mouse breast cancer cells) xenograft mice, in order to systematically identify differentially expressed proteins in tumor samples between the model group and the Zusanli (ST36) group injected with hydrogen rich water at acupoints, with a focus on functional proteins or signaling pathways related to tumor occurrence and development, researchers conducted four-dimensional data independent acquisition (4D-DIA) proteomic analysis on tumor tissues. In order to further investigate the dynamic changes of metabolites after therapeutic intervention, researchers conducted liquid chromatography-tandem mass spectrometry untargeted metabolomics identification and analysis on mouse serum. The results of the joint proteomics-metabolomics analysis were validated using experimental methods such as immunofluorescence, Western blotting, and quantitative reverse transcription polymerase chain reaction detection. RESULTS: Injecting hydrogen-rich water into acupoints significantly inhibited tumor growth (P < 0.05). 4D-DIA proteomics and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses uncovered pathways such as T helper 1 cell (Th1) and T helper 2 cell (Th2) cell differentiation. The KEGG metabolic pathways identified in the metabolomics analysis included galactose metabolism along with fructose and mannose metabolism. Based on the combined proteomics and metabolomics analysis, the key pathways included the C-type lectin receptor signaling pathway. The major cancer-related differential proteins detected in Th1 and Th2 cell differentiation [interleukin 6 signal transducer, nuclear factor of activated T cells 4, recombinant mitogen activated protein kinase 10 (MAPK10), and MAPK11] were upregulated after the injection of hydrogen-rich water into the Zusanli (ST36) acupoint, whereas Linker for activation of T cells (Lat), signal transducer and activator of transcription 1, and protein kinase C, theta were downregulated. CONCLUSION: The injection of hydrogen-rich water into the Zusanli (ST36) acupoint effectively inhibited the hyperplasia of 4T1 BC cells and enhanced their apoptosis, potentially exerting a therapeutic effect through multiple pathways and targeting various sites.

Animals↗

PubMed2026

Integrated analysis of plasma metabolomics and proteomics reveals the biological characteristics of damp-heat and stasis-toxin syndrome in colorectal cancer.

OBJECTIVE: To investigate the biological attributes of core syndromes in colorectal cancer, namely, the damp-heat and stasis-toxin syndrome (SRYD). METHODS: Between October 2021 and October 2022, a cohort comprising 40 patients with colorectal cancer (CRC) diagnosed with damp-heat and stasis-toxin syndrome (SRYD group), 40 patients with CRC without this syndrome (non-SRYD group), and 40 healthy controls (Normal group) was recruited at Jiangsu Province Hospital of Chinese Medicine. Untargeted metabolomics analysis was conducted on plasma samples from all 120 participants, while differential protein analysis using four-dimensional data-independent acquisition proteomics was performed on 20 randomly selected samples per group. A combined analysis of proteomics and metabolomics data followed, and the identified potential diagnostic biomarkers were subsequently used to train and validate multiple machine learning models. RESULTS: Proteomic analysis revealed 130 differential proteins in the colorectal cancer with damp-heat and stasis-toxin syndrome (CRC-SRYD) group, enriched in pathways including complement and coagulation cascades, as well as nuclear factor kappa-B (NF-κB) signaling. Metabolomic analysis identified 584 differential metabolites within the same group, showing enrichment in pathways such as primary bile acid biosynthesis, central carbon metabolism in cancer, and glucagon signaling. Integrated pathway analysis indicated heightened activity of the NF-κB signaling pathway in the CRC-SRYD group. A biomarker panel, comprising 6 proteins and 9 metabolites selected through the ReliefF algorithm, was used to construct a diagnostic model with random forest, achieving an accuracy of 93.33%, sensitivity of 80.00%, and specificity of 100%. CONCLUSION: This study systematically elucidates plasma metabolomic and proteomic alterations in patients with CRC, establishing a robust diagnostic model for CRC syndrome (CRC-SRYD). Further investigation is warranted to clarify the underlying molecular mechanisms and biological foundations.

Humans↗

PubMed2004

Proteomic analyses using an accurate mass and time tag strategy.

An accurate mass and time (AMT) tag approach for proteomic analyses has been developed over the past several years to facilitate comprehensive high-throughput proteomic measurements. An AMT tag database for an organism, tissue, or cell line is established by initially performing standard shotgun proteomic analysis and, most importantly, by validating peptide identifications using the mass measurement accuracy of Fourier transform ion cyclotron resonance (FTICR) mass spectrometry (MS) and liquid chromatography (LC) elution time constraint. Creation of an AMT tag database largely obviates the need for subsequent MS/MS analyses, and thus facilitates high-throughput analyses. The strength of this technology resides in the ability to achieve highly efficient and reproducible one-dimensional reversed-phased LC separations in conjunction with highly accurate mass measurements using FTICR MS. Recent improvements allow for the analysis of as little as picrogram amounts of proteome samples by minimizing sample handling and maximizing peptide recovery. The nanoproteomics platform has also demonstrated the ability to detect >10(6) differences in protein abundances and identify more abundant proteins from subpicogram amounts of samples. The AMT tag approach is poised to become a new standard technique for the in-depth and high-throughput analysis of complex organisms and clinical samples, with the potential to extend the analysis to a single mammalian cell.

Amino Acid Sequence↗

PubMed2002

Bacterial proteomics and vaccine development.

Until recently, the development of vaccines for use in humans relied on the response to attenuated or whole-cell preparations, or empirically selected antigens. The post-genomic era holds the possibility of rational design of novel vaccines for important human pathogens. The discovery and development of these new vaccines is likely to be accomplished through integrated proteomic strategies. Although most proteomic studies are based on two-dimensional gel electrophoresis (2D-PAGE) as a separation technique, new methods have been developed within the past two years that provide complementary information concerning microbial protein expression. The 2D-PAGE technique in combination with Western blotting has been successfully applied in the discovery of antigens from Helicobacter pylori, Chlamydia trachomatis and Borrelia garinii. Two-dimensional semi-preparative electrophoresis has provided complementary information regarding membrane protein expression in a strain of H. pylori. Through two-dimensional liquid chromatography-tandem mass spectrometry, the most comprehensive information to date regarding protein expression in yeast was obtained. This technique may shortly become an important tool in vaccinology. This review of the current state of bacterial proteomics as applied in vaccinology presents analytical techniques for protein separation, proteomics without gels, reverse vaccinology, and functional approaches to the identification of virulence proteins in microbes.

Bacterial Proteins↗

PubMed2005

Applying proteomics in clinical trials: assessing the potential and practical limitations in ovarian cancer.

Ovarian cancer is the leading cause of death from gynecologic malignancies among American women and the fourth most frequent cause of death from cancer in women in Europe and the US. Despite appropriate surgical and chemotherapeutic intervention, the 5-year survival in patients with metastatic cancer remains poor. Currently available screening methods, including CA125, additional biomarkers, and transvaginal ultrasound lack the necessary sensitivity and specificity to provide accurate and cost-efficient screening for the general population or the ability to assess who will benefit most from each treatment. These limitations have prompted the study of proteomic technology and its application in ovarian cancer diagnostics. Proteomics is the study of molecules in the functional protein pathways of normal or diseased states. Clinical trials are currently being conducted to assess the sensitivity and specificity of serum proteomic patterns and additional clinical trials are designed to evaluate the effects of molecularly targeted agents on protein signaling pathways in human subjects. Overcoming both scientific and practical limitations will lead to increased knowledge of deranged protein networks in cancer cells. Clinical trials in proteomics may result in improved early detection, better monitoring, new drugs and molecularly targeted therapeutics, and individualized therapies.

Biomarkers, Tumor↗

PubMed2005

Proteomic cancer classification with mass spectrometry data.

The ultimate goal of cancer proteomics is to adapt proteomic technologies for routine use in clinical laboratories for the purpose of diagnostic and prognostic classification of disease states, as well as in evaluating drug toxicity and efficacy. Analysis of tumor-specific proteomic profiles may also allow better understanding of tumor development and the identification of novel targets for cancer therapy. The biological variability among patient samples as well as the huge dynamic range of biomarker concentrations are currently the main challenges facing efforts to deduce diagnostic patterns that are unique to specific disease states. While several strategies exist to address this problem, we focus here on cancer classification using mass spectrometry (MS) for proteomic profiling and biomarker identification. Recent advances in MS technology are starting to enable high-throughput profiling of the protein content of complex samples. For cancer classification, the protein samples from cancer patients and noncancer patients or from different cancer stages are analyzed through MS instruments and the MS patterns are used to build a diagnostic classifier. To illustrate the importance of feature selection in cancer classification, we present a method based on support vector machine-recursive feature elimination (SVM-RFE), demonstrated on two cancer datasets from ovarian and lung cancer.

Biomarkers, Tumor↗

PubMed2006

Spots, blots, peaks and chips: proteomic approaches in autoimmune diseases.

During the past five years, investigations employing a variety of proteomic technologies have yielded a wealth of information on a number of autoimmune disorders. Animal models of autoimmune disease have been examined and have provided clues that can be useful in elucidating molecular pathways and mechanisms that play a role in autoimmune disorders. Human sera and body fluids have been analyzed and have resulted in the identification of autoantibodies that can be used as diagnostic markers in specific autoimmune diseases, and proteomic fingerprints of tissues and body fluids have resulted in the identification of individual proteins or patterns of protein expression that are deregulated in autoimmune diseases. The information provided by these proteomic studies are of diagnostic and therapeutic potential. This review provides an overview of the approaches used in the proteomic analyses of autoimmune disease.

Animals↗

PubMed2026

Exogenous ABA enhances cold tolerance of Rhododendron yedoense var. poukhanense under subzero temperature: integrating physiology, transcriptome, and proteome.

Low temperature limits the growth and ornamental value of evergreen shrubs. Rhododendron yedoense var. poukhanense, an important ornamental shrub from Northeast China, frequently suffers freezing damage during winter. While exogenous abscisic acid (ABA) enhances cold tolerance in many plants, its molecular mechanisms at subzero temperatures remain poorly understood in non-model species lacking chromosome-level reference genomes. This study investigated the effects of exogenous ABA on freezing tolerance in R. yedoense var. poukhanense at -4 °C using an integrated physiological, transcriptomic, and proteomic approach. Cutting seedlings were subjected to four treatments: CK (22°C control), A (22°C + ABA), LT (-4°C), and ALT (-4°C + ABA). Photosynthetic pigments, osmotic regulation substances, antioxidant enzyme activities, and malondialdehyde (MDA) content were measured. Transcriptome sequencing and quantitative proteomics were performed, and transcriptome data were validated by quantitative real-time PCR (qRT-PCR) of 15 selected genes. ABA pretreatment reduced visible cold injury severity, partially preserved photosynthetic pigments, decreased MDA content by 28.7%, and promoted recovery of catalase (+43.6%), superoxide dismutase (+31.1%), and peroxidase (+20.0%) activities under freezing stress. Transcriptome analysis revealed 8, 444 differentially expressed genes (DEGs) in LT versus CK and 6, 481 DEGs in ALT versus CK, representing a 23% reduction in transcriptional reprogramming scope attributable to ABA priming. The ALT versus LT comparison identified only 1, 690 additional DEGs, indicating that most cold-responsive genes were pre-activated during the ABA priming phase. Proteome analysis identified 1, 461 differentially expressed proteins (DEPs) in ALT versus CK. Integrated analysis revealed extensive post-transcriptional regulation, with transcript-protein concordance of only 1.0-4.1%, and co-enriched Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways in both omics layers. qRT-PCR validation confirmed high reliability of the transcriptome data (R2 = 0.8500). These findings demonstrate that exogenous ABA enhances freezing tolerance through multi-layered molecular regulation encompassing transcriptional buffering, translational reprogramming, and functional reallocation from photosynthesis to stress protection. This study provides the first integrated physiology-transcriptome-proteome framework for ABA-mediated freezing tolerance in an evergreen ornamental shrub and offers theoretical support for ABA-based winter protection strategies.

Rhododendron yedoense var. Poukhanense↗

PubMed2006

Current status and prospects of clinical proteomics studies on detection of colorectal cancer: hopes and fears.

Colorectal adenocarcinoma (CRC) is the third most common type of cancer and the fourth most frequent cause of death due to cancer worldwide. Given the natural history of CRC, early diagnosis appears to be the most appropriate tool to reduce disease-related mortality. A field of recent interest is clinical proteomics, which was reported to lead to high sensitivity and specificities for early detection of several solid tumors. This emerging field uses mass spectrometry-based protein profiles/patterns of easy accessible body fluids to distinguish cancer from non-cancer patients. These discrepancies may be a result of: (1) proteins being abnormally produced or shed and added to the serum proteome, (2) proteins clipped or modified as a consequence of the disease process, or (3) proteins subtracted from the proteome owing to disease-related proteolytic degradation pathways. Therefore, protein pattern diagnostics would provide easy and reliable tools for detection of cancer. This paper focuses on the current status of clinical proteomics research in oncology and in colorectal cancer especially, and will reflect on pitfalls and fears in this relatively new area of clinical medicine, which are reproducibility issues and pre-analytical factors, statistical issues, and identification and nature of discriminating proteins/peptides.

Adenocarcinoma↗

PubMed2004

Proteomic analysis of human breast cancer tissue with laser-capture microdissection and reverse-phase protein microarrays.

Despite recent advances in breast cancer therapy, women with similar types of breast cancers may respond very differently to standard treatments. The emerging field of clinical proteomics has the potential to revolutionize breast cancer therapy. The ultimate goal of clinical proteomics is to characterize information flow through protein cascades for individual patients. After the protein networks have been elucidated, drug therapies may be specially designed for each patient. The following review describes the proteomic technologies of laser-capture microdissection (LCM) and reverse-phase protein arrays (RPPAs). These technologies allow scientists to analyze relative abundances of key cellular signaling proteins from pure cell populations. Cell survival and apoptotic protein pathways are currently being monitored with LCM and RPPAs at the National Institutes of Health, in phase II clinical trials of metastatic breast and ovarian cancers. Ultimately, proteomics will become an integral component of tracking and managing individualized breast cancer therapy.

Breast↗

PubMed2006

Proteomic analysis of hemangioblastoma cyst fluid.

OBJECTIVE: Hemangioblastomas are benign CNS tumors that occur sporadically or in patients with von Hippel-Lindau (VHL) disease. These tumors are characteristically associated with formation of intra- or peritumoral cysts. Hemangioblastoma cyst formation is a major cause of morbidity and mortality with these tumors. While peritumoral cysts have been suggested to result from vascular leakage, the mechanism of intratumoral cyst formation is not understood. METHODS: To elucidate the origin of intratumoral hemangioblastoma cyst fluid, we characterized its biochemical composition by two-dimensional (2D) proteomic profiling followed by sequencing of several proteins. The proteomic pattern of intratumoral cyst fluid was furthermore compared to the proteomic pattern of serum, hemangioblastoma tumor tissue, and hemangioblastoma peritumoral cyst fluid. RESULTS: We show that proteomic patterns of intra- and peritumoral cyst fluid are identical Both are highly similar to serum and not to tumor. CONCLUSIONS: Intratumoral hemangioblastoma cyst fluid originates from serum. Cyst formation associated with hemangioblastoma, whether peri- or intratumoral, is a consequence of vascular leakage. Anti-VEGF therapy may effectively control hemangioblastoma cyst formation.

Biomarkers, Tumor↗

PubMed2026

Proteomic Analysis of Extracellular Vesicles Reveals Vitronectin and Laminin Subunit Alpha-3 as Candidate Biomarkers for Gastric Cancer.

BACKGROUND/AIMS: Clinically useful noninvasive biomarkers for gastric cancer remain limited. Extracellular vesicles (EVs) carry a molecular cargo reflective of their cells of origin and have emerged as promising candidates for blood-based cancer biomarkers. We aimed to identify EV-associated protein biomarkers for gastric cancer via a proteomic approach. METHODS: Proteomic profiling of EVs was performed using one normal gastric cell line (Hs738st/int) and two gastric cancer cell lines (AGS and NCI-N87). Selected proteins were validated in blood-derived EVs isolated from plasma samples of 10 healthy controls and 36 patients with gastric cancer. RESULTS: Proteomic analysis identified 224 differentially expressed proteins whose expression was consistently altered in gastric cancer cell line-derived EVs. Among these, vitronectin (VTN) and laminin subunit alpha-3 (LAMA3) were selected based on their consistent upregulation. EV-associated LAMA3 levels were significantly higher in patients with gastric cancer than in healthy controls (p=0.003), with significant elevations observed from stage II onward (p=0.041, p=0.017, and p=0.004 for stages II, III, and IV, respectively). EV-associated VTN levels were not significantly different overall (p=0.089); however, stage-specific analysis demonstrated significant increases in VTN levels in patients with stage III (p=0.036) and stage IV (p=0.005) gastric cancer. Both EV-associated VTN and LAMA3 levels showed significant positive correlations with the cancer stage (ρ=0.564 and ρ=0.611, respectively; both p<0.001). CONCLUSIONS: The levels of EV-associated VTN and LAMA3 appear to be more closely associated with disease progression than with early-stage detection of gastric cancer. These findings suggest that EV-based proteomic biomarkers may have clinical utility for monitoring tumor progression in patients with clinically advanced gastric cancer.

Humans↗

PubMed1999

[Proteome analysis: the state of the art of the methodology].

The proteome is the protein complement of a genome. Proteome analysis has been progressing worldwide. Two-dimensional electrophoresis (2-DE), a key technique in proteome analysis, separates proteins on a polyacrylamide gel according to the isoelectric point and molecular mass. A total of 1,000-1,500 protein spots can be separated and detected on a polyacrylamide gel using silver-staining. It is important to identify individual protein spots in order to correlate the information of the genome to that of the corresponding proteome. By automatic amino-terminal sequencing, around 15 amino acid residues from the amino terminus can be determined from 1 pmole of a protein sample. The homology search of the obtained sequences against a protein sequence database can clarify the protein unambigously. Recently, a carboxyl-terminal sequencing method using a vapor from a high concentration of an organic acid has been developed. Peptide-mass-fingerprinting is a new method for protein identification using residue-specific proteases and mass spectrometry. Two types of chemical cleavage methods, the carboxyl side cleavage of the aspartyl peptide bond and the amino terminal cleavage of serine/threonine peptide bonds would be more suitable for peptide-mass-fingerprinting of micro amount protein because of no contamination from the gel matrix or the enzyme used. It would be possible to analyse less amount protein sample (100 femtomole) more rapidly according to advancement of mass spectrometry.

Amino Acid Sequence↗

PubMedDate not supplied

Cancer proteomics: from biomarker discovery to signal pathway profiling.

In the post-genomic era of science, the field of proteomics promises the discovery of new molecular targets for therapy, biomarkers for early detection, and new endpoints for therapeutic efficacy and toxicity. Patient-specific targeted therapeutics with reduced toxicity and increased efficacy, the ultimate goal for rational drug development, can only be achieved if direct analyses of the tissue cells in the actual human malignancy are analyzed. To that end, technologies such as Laser Capture Microdissection (LCM), is providing unparalleled access to the purified diseased human cells directly from tissue specimens. However, limited availability of patient material is a challenge towards the development of new highly sensitive proteomic methodologies. Two-dimensional gel electrophoresis (2D-PAGE), still the mainstay of most proteomic analysis of disease, is being complemented, and in some instances replaced by new exciting approaches to multiparametric protein characterization. The use of rapid, high throughput mass spectrometric-based fingerprints of peptides and proteins may prove to be valuable for new molecular classification of human tumors and disease stages. Coupled with LCM, high-density protein arrays, antibody arrays, and small molecular arrays, could have a substantial impact on proteomic profiling of human malignancies. Finally, detailed real-time knowledge about the states of intracellular signaling circuitry and pathways in the normal and malignant cells before, during and after therapy will yield invaluable information about mechanism of action and efficacy of existing and novel therapeutics for the treatment of human cancer.

Biomarkers↗

PubMed2001

Proteomic approach to identify novel mitochondrial proteins in Arabidopsis.

An Arabidopsis mitochondrial proteome project was started for a comprehensive investigation of mitochondrial functions in plants. Mitochondria were prepared from Arabidopsis stems and leaves or from Arabidopsis suspension cell cultures, and the purity of the generated fractions was tested by the resolution of organellar protein complexes applying two-dimensional blue-native/N-[2-hydroxy-1,1-bis(hydroxymethyl)ethyl]glycine (Tricine) sodium dodecyl sulfate-polyacrylamide gel electrophoresis. The Arabidopsis mitochondrial proteome was analyzed by two-dimensional isoelectric focusing/ Tricine sodium dodecyl sulfate-polyacrylamide gel electrophoresis and 650 different proteins in a pI range of pH 3 to 10 were separated on single gels. Solubilization conditions, pH gradients for isoelectric focusing, and gel staining procedures were varied, and the number of separable proteins increased to about 800. Fifty-two protein spots were identified by immunoblotting, direct protein sequencing, and mass spectrometry. The characterized proteins cooperate in various processes, such as respiration, citric acid cycle, amino acid and nucleotide metabolism, protection against O(2), mitochondrial assembly, molecular transport, and protein biosynthesis. More than 20% of the identified proteins were not described previously for plant mitochondria, indicating novel mitochondrial functions. The map of the Arabidopsis mitochondrial proteome should be useful for the analysis of knockout mutants concerning nuclear-encoded mitochondrial genes. Considerations of the total complexity of the Arabidopsis mitochondrial proteome are discussed. The data from this investigation will be made available at http://www.gartenbau.uni-hannover.de/genetik/AMPP.

Arabidopsis↗