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Proteomic profiling of fibroblasts reveals a modulating effect of extracellular calumenin on the organization of the actin cytoskeleton.

CREC proteins constitute a family of EF-hand calcium binding proteins localized to the secretory pathway. Calumenin is the only member known to be secreted. Recently, it was shown that thrombin-activated thrombocytes liberate calumenin, which also is found in atherosclerotic lesions but not in normal vasculature. To study the possible effects of calumenin extracellularly, we used proteomic profiling of fibroblasts cultured in absence and in presence of calumenin. Using 2-DE and MS/MS, we show that normal fibroblasts contain several 28-29-kDa N-terminal and a 16-kDa C-terminal fragment of beta- or gamma-actin. Extracellularly added calumenin decreases the levels of both the N-terminal and C-terminal actin fragments, and, in addition, decreases the expression level of septin 2, which interacts with the actin cytoskeleton and is involved in cytokinesis. Labeling of S-phase fibroblasts with bromo-2'deoxy-uridine indicates that calumenin added to the medium also modulates the cell cycle. Our study thus indicates that calumenin may have an autocrine or a paracrine effect on the cells in its vicinity, and, therefore, may be involved in the pathophysiology of thrombosis or in wound healing.

Actins↗

Redefining ALS: Large-scale proteomic profiling reveals a prolonged pre-diagnostic phase with immune, muscular, metabolic, and brain involvement.

BACKGROUND: Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disorder with a largely unknown duration and pathophysiology of the pre-diagnostic phase, especially for the common non-monogenic form. METHODS: We leveraged the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort with up to 30 years of follow-up to identify incident ALS cases across five European countries. Pre-diagnostic plasma samples from initially healthy participants underwent high-throughput proteomic profiling (7,285 protein markers, SomaScan). Cox proportional hazards models based on 4,567 participants (including 172 incident ALS cases) were used to identify protein biomarkers associated with future ALS diagnosis. Top results were indirectly validated in two independent case-control studies of prevalent ALS (n=417 ALS, 852 controls). Functional annotation included cross-disease comparisons, gene set and tissue enrichment testing, organ-specific proteomic clocks, and the application of large-language models (LLM). FINDINGS: Five proteins (SECTM1, CA3, THAP4, KLHL41, SLC26A7) were identified as significant pre-diagnostic ALS biomarkers (FDR=0.05), detectable approximately two decades before diagnosis. Of these, all except SECTM1 were indirectly validated in independent cohorts of prevalent ALS cases, supporting their clinical significance. Additionally, 22 nominally significant (p<0.05) pre-diagnostic biomarkers were FDR-significant in prevalent ALS with consistent effect directions. Cross-disease comparisons with pre-diagnostic Parkinson's and Alzheimer's disease suggested a largely specific pre-diagnostic ALS biomarker signature. Gene ontology and tissue enrichment highlighted early involvement of immune, muscle, metabolic, and digestive processes. Furthermore, analyses of proteomic clocks revealed accelerated aging in brain-cognition, immune, and muscle tissues before clinical diagnosis. Druggability and LLM analyses revealed possible therapeutic targets and novel strategies, emphasizing translational relevance. INTERPRETATION: Our study provides first evidence of ultra-early molecular changes in common ALS up to two decades prior to clinical onset, mainly affecting immune, muscle, metabolic, digestive, and cognitive systems. Our study nominates several compelling candidates for risk stratification studies and novel therapeutic targets for early intervention. FUNDING: Clinical Research in ALS and Related Disorders for Therapeutic Development (CreATe) Consortium, Cure Alzheimer's Fund, Michael J Fox Foundation, Interdisciplinary Centre for Clinical Research, University M&#xfc;nster.

Journal Article↗

Redefining ALS: Large-scale proteomic profiling reveals a prolonged pre-diagnostic phase with immune, muscular, metabolic, and brain involvement.

BACKGROUND: Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disorder with a largely unknown duration and pathophysiology of the pre-diagnostic phase, especially for the common non-monogenic form. METHODS: We leveraged the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort with up to 30 years of follow-up to identify incident ALS cases across five European countries. Pre-diagnostic plasma samples from initially healthy participants underwent high-throughput proteomic profiling (7,285 protein markers, SomaScan). Cox proportional hazards models based on 4,567 participants (including 172 incident ALS cases) were used to identify protein biomarkers associated with future ALS diagnosis. Top results were indirectly validated in two independent case-control studies of prevalent ALS (n=417 ALS, 852 controls). Functional annotation included cross-disease comparisons, gene set and tissue enrichment testing, organ-specific proteomic clocks, and the application of large-language models (LLM). FINDINGS: Five proteins (SECTM1, CA3, THAP4, KLHL41, SLC26A7) were identified as significant pre-diagnostic ALS biomarkers (FDR=0.05), detectable approximately two decades before diagnosis. Of these, all except SECTM1 were indirectly validated in independent cohorts of prevalent ALS cases, supporting their clinical significance. Additionally, 22 nominally significant (p<0.05) pre-diagnostic biomarkers were FDR-significant in prevalent ALS with consistent effect directions. Cross-disease comparisons with pre-diagnostic Parkinson's and Alzheimer's disease suggested a largely specific pre-diagnostic ALS biomarker signature. Gene ontology and tissue enrichment highlighted early involvement of immune, muscle, metabolic, and digestive processes. Furthermore, analyses of proteomic clocks revealed accelerated aging in brain-cognition, immune, and muscle tissues before clinical diagnosis. Druggability and LLM analyses revealed possible therapeutic targets and novel strategies, emphasizing translational relevance. INTERPRETATION: Our study provides first evidence of ultra-early molecular changes in common ALS up to two decades prior to clinical onset, mainly affecting immune, muscle, metabolic, digestive, and cognitive systems. Our study nominates several compelling candidates for risk stratification studies and novel therapeutic targets for early intervention. FUNDING: Clinical Research in ALS and Related Disorders for Therapeutic Development (CreATe) Consortium, Cure Alzheimer's Fund, Michael J Fox Foundation, Interdisciplinary Centre for Clinical Research, University M&#xfc;nster.

Journal Article↗

DNA Methylation and Proteomic Profiling of Postmortem Brain Tissue Reveals Epigenetic Dysregulation and Neuroinflammatory in Fragile X-associated Tremor/Ataxia Syndrome (FXTAS).

BACKGROUND: Fragile X-associated Tremor/Ataxia Syndrome (FXTAS) is a late-onset neurodegenerative disorder caused by FMR1 premutation CGG repeat expansions (55-200 repeats). The epigenetic landscape of the FXTAS brain remains uncharacterized. We performed genome-wide DNA methylation profiling of postmortem prefrontal cortex tissue to identify differentially methylated positions (DMPs) and candidate genes, and sought protein-level support for a neuroinflammatory signal. METHODS: DNA methylation was profiled in postmortem prefrontal cortex (Brodmann area 9) from 27 male FXTAS cases and 29 male controls using the Illumina MethylationEPIC array (EPICv1 and EPICv2 platforms), merging 721,802 common probes. Surrogate variable analysis (SVA) controlled for confounders. DMPs were defined by |&#x394;&#x3b2;| > 0.10 and FDR < 0.05; exploratory Reactome 2024 pathway analysis was performed on the DMP-associated gene list. Targeted proteomic profiling was performed in the same brain region using the Olink (proximity extension assay) Inflammation panel in 9 FXTAS cases and 12 controls, with SVA-adjusted differential abundance analysis, and concordance assessment against a prior mass spectrometry dataset. RESULTS: We identified 108 significant cg-type DMPs mapping to 80 genes (50 hypermethylated, 58 hypomethylated in FXTAS). The strongest signal was CYP2E1 (7 concordant hypomethylated DMPs, mean &#x394;&#x3b2; = -0.143), an oxidative stress gene also implicated in Parkinson's disease. FTCD, a one-carbon cycle enzyme, carried 5 hypermethylated DMPs (mean &#x394;&#x3b2; = +0.210). A cluster of DMP-associated genes with established roles in innate immune and NF-&#x3ba;B signaling, TRAF3 (the single most significant DMP among the inflammation genes, hypermethylated), BATF, RCOR1, and MSI2; they pointed toward neuroinflammatory dysregulation. Additional genes included LINGO1 (myelination inhibitor), SYT3 (synaptic vesicle), and SLC39A4 (zinc transporter). Exploratory Reactome enrichment using the DMP-associated gene set nominated themes including neuroinflammation resolution, axonal growth inhibition, zinc homeostasis, and CYP2E1 metabolism at nominal significance (p<0.05); however, the gene-to-pathway mapping rate was low and no pathway survived correction for multiple testing. Olink proteomic analysis independently identified 60 significantly altered inflammation proteins (59 downregulated), including CXCL8, CXCL10, IL6, IL15, IL18, TLR3, IRAK1/4, and complement C1QA, which were directionally concordant with prior mass spectrometry data. CONCLUSIONS: This integrated study reveals a genome-wide epigenetic signature in the FXTAS prefrontal cortex implicating oxidative stress, myelination failure, zinc dysregulation, one-carbon cycle disruption, and most notably a coordinated set of epigenetically altered genes governing innate immune and NF-&#x3ba;B signaling. Convergence of TRAF3 hypermethylation with independent downregulation of TLR3 and NF-&#x3ba;B-pathway proteins at the protein level supports a coherent, cross-platform model of dysregulated neuroinflammatory signaling in FXTAS, identified here through individual gene- and protein-level convergence rather than formal pathway enrichment. FTCD hypermethylation proposes a self-reinforcing epigenetic loop via SAM depletion. These multi-omic findings establish FXTAS as a disorder of pervasive epigenetic reprogramming and nominate candidate genes for future mechanistic and therapeutic investigation.

CYP2E1↗

Proteomic profiling identifies miR-423-5p as a modulator of oncogenic metabolism in HCC.

BACKGROUND: Hepatocellular carcinoma (HCC) remains a significant clinical challenge due to limited diagnostic and therapeutic options. Non-coding RNAs (ncRNAs), such as microRNAs (miRNAs), play key roles in cancer biology. Our previous findings showed that miR-423-5p enhances anti-cancer effects on HCC patients treated with sorafenib by promoting autophagy. Here, we investigated the molecular mechanisms underlying miR-423-5p function through a comprehensive proteomic approach. METHODS: We generated an HCC cell line stably overexpressing miR-423-5p via lentiviral transduction. Total proteins were extracted from SNU-387 cells, enzymatically digested into peptides, and subsequently analysed by liquid chromatography-tandem mass spectrometry (LC-MS/M). Raw spectral data were processed and quantified using MaxQuant. Differentially expressed proteins (DEPs) were defined based on fold-change (|log2FC| &#x2265; 1) and false discovery rate (FDR < 0.05). The full proteomic dataset is available via the ProteomeXchange repository (identifier: PXD064869). Functional enrichment analysis of DEPs were performed using DAVID and Reactome. To assess clinical relevance, predicted and validated miR-423-5p targets were integrated with The Cancer Genome Atlas (TCGA) Liver Hepatocellular Carcinoma (LIHC) dataset using GEPIA platform. Survival analyses were performed using the Kaplan-Meier method. RESULTS: Proteomic profiling identified 698 DEPs in miR-423-5p-overexpressing cells compared to controls with significant enrichment in metabolic pathways, related to purine/pyrimidine metabolism and gluconeogenesis. Integration with bioinformatic predictions and miRTarBase validation identified 43 DEPs as potential direct targets of miR-423-5p. Among these, seven proteins (ACACA, ANKRD52, DVL3, MCM5, MCM7, RRM2, SPNS1, and SRM) were significantly associated with patient prognosis in the TCGA-LIHC cohort. These targets were downregulated in miR-423-5p-overexpressing cells but upregulated in advanced-stage HCC tissues, suggesting a potential role for miR-423-5p in the regulation of HCC pathogenesis. Stage-specific expression analysis showed increased levels from stage I to III, followed by a decline at stage IV. Notably, we experimentally confirmed miR-423-5p-mediated suppression of MCM7, DVL3, IMPDH1, and SRM (SPEE), supporting their functional involvement in HCC progression. CONCLUSION: Overall, our findings support a tumour-suppressive role for miR-423-5p in HCC, mediated by modulation of metabolic pathways and suppression of oncogenic proteins. These results suggest that miR-423-5p and its downstream effectors may serve as promising biomarkers and potential therapeutic targets in HCC. HIGHLIGHTS: miR-423-5p acts as a tumor suppressor in HCC by targeting key nodes of pro-tumorigenic signalling. miR-423-5p significantly altered metabolic pathways, including purine/pyrimidine metabolism and gluconeogenesis. Seven miR-423-5p targets correlate with poor prognosis in TCGA-LIHC patients and are downregulated in miR-423-5p overexpressing HCC cells. miR-423-5p over-expression induces a significant downregulation of MCM7, DVL3, IMPDH1, SPEE in HCC cell models. miR-423-5p limits tumor metabolic plasticity, suggesting therapeutic potential.

MicroRNAs↗

Enhanced proteome profiling by inhibiting proteolysis with small heat shock proteins.

Proteolytic degradation is one of the critical problems in two-dimensional electrophoresis (2-DE). Here we report that small heat shock proteins (sHsps), including IbpA(Ec) and IbpB(Ec) from Escherichia coli and Hsp26(Sc) from Saccharomyces cerevisiae, are able to protect proteins in vitro from proteolytic degradation. Addition of sHsps during 2-DE of human serum or whole cell extracts of E. coli, Mannheimia succinciproducens, Arabidopsis thaliana, and human kidney cells allowed detection of up to 50% more protein spots than those obtainable with currently available protease inhibitors. Therefore, the use of sHsps during 2-DE significantly improves proteome profiling by generally enabling the detection of many more protein spots that could not be seen previously.

Animals↗

Multivariate statistical tools applied to the characterization of the proteomic profiles of two human lymphoma cell lines by two-dimensional gel electrophoresis.

Mantle cell lymphoma (MCL) cell lines have been difficult to generate, since only few have been described so far and even fewer have been thoroughly characterized. Among them, there is only one cell line, called GRANTA-519, which is well established and universally adopted for most lymphoma studies. We succeeded in establishing a new MCL cell line, called MAVER-1, from a leukemic MCL, and performed a thorough phenotypical, cytogenetical and molecular characterization of the cell line. In the present report, the phenotypic expression of GRANTA-519 and MAVER-1 cell lines has been compared and evaluated by a proteomic approach, exploiting 2-D map analysis. By univariate statistical analysis (Student's t-test, as commonly used in most commercial software packages), most of the protein spots were found to be identical between the two cell lines. Thirty spots were found to be unique for the GRANTA-519, whereas another 11 polypeptides appeared to be expressed only by the MAVER-1 cell line. A number of these spots could be identified by MS. These data were confirmed and expanded by multivariate statistical tools (principal component analysis and soft-independent model of class analogy) that allowed identification of a larger number of differently expressed spots. Multivariate statistical tools have the advantage of reducing the risk of false positives and of identifying spots that are significantly altered in terms of correlated expression rather than absolute expression values. It is thus suggested that, in future work in differential proteomic profiling, both univariate and multivariate statistical tools should be adopted.

Cell Line, Tumor↗

Diagnosis of pancreatic cancer using serum proteomic profiling.

In the United States, mortality rates from pancreatic cancer (PCa) have not changed significantly over the past 50 years. This is due, in part, to the lack of early detection methods for this particularly aggressive form of cancer. The objective of this study was to use high-throughput protein profiling technology to identify biomarkers in the serum proteome for the early detection of resectable PCa. Using surface-enhanced laser desorption/ionization mass spectrometry, protein profiles were generated from sera of 49 PCa patients and 54 unaffected individuals after fractionation on an anion exchange resin. The samples were randomly divided into a training set (69 samples) and test set (34 samples), and two multivariate analysis procedures, classification and regression tree and logistic regression, were used to develop classification models from these spectral data that could distinguish PCa from control serum samples. In the test set, both models correctly classified all of the PCa patient serum samples (100% sensitivity). Using the decision tree algorithm, a specificity of 93.5% was obtained, whereas the logistic regression model produced a specificity of 100%. These results suggest that high-throughput proteomics profiling has the capacity to provide new biomarkers for the early detection and diagnosis of PCa.

Biomarkers, Tumor↗

Proteomic profiling of rat thyroarytenoid muscle.

PURPOSE: Proteomic methodologies offer promise in elucidating the systemwide cellular and molecular processes that characterize normal and diseased thyroarytenoid (TA) muscle. This study examined methodological issues central to the application of 2-dimensional sodium dodecyl sulfate polyacrylamide gel electrophoresis (2D SDS-PAGE) to the study of the TA muscle proteome using a rat model. METHOD: 2D SDS-PAGE was performed using 4 chemically skinned rat TA muscle samples. Gel images were analyzed and compared. Protein spot detection and matching were performed using computational image analysis algorithms only and computational image analysis followed by visual inspection and manual error correction. A synthetic master gel, constructed to control for uninteresting biological variation and technical artifact due to differences in protein loading and staining, was evaluated against its constituent gels. RESULTS: Manual error correction resulted in a consistent increase in the number of protein spots detected (between 5.8% and 40.9%) and matched (from 25.8% to 70.8%) across all gels. Sensitivity and specificity of the automatic (computational) spot detection procedure, evaluated against the manual correction procedure, were 74.1% and 97.9%, respectively. Evaluation of protein quantitation parameter values revealed statistically significant differences (p < .0001) in optical density, area, and volume for matched protein spots across gels. The synthetic master gel successfully compensated for these intergel differences. CONCLUSIONS: Valid and reliable proteomic data are dependant on well-controlled manageable variability and well-defined unmanageable variability. Manual correction of spot detection and matching errors and the use of a synthetic master gel appear to be useful strategies in addressing these issues. With these issues accounted for, 2D SDS-PAGE may be applied to quantitative experimental comparisons of normal and disease conditions affecting voice, speech, and swallowing function.

Algorithms↗

Discovering disease-associated enzymes by proteome reactivity profiling.

Proteomics aims to identify new markers and targets for the diagnosis and treatment of human disease. To realize this goal, methods and reagents are needed to profile proteins based on their functional properties, rather than mere abundance. Here, we describe a general strategy for synthesizing and evaluating structurally diverse libraries of activity-based proteomic probes. Quantitative screening of probe-proteome reactions coupled with bioinformatic analysis enabled the selection of a suite of probes that exhibit complementary protein reactivity profiles. This optimal probe set was applied to discover several enzyme activities differentially expressed in lean and obese (ob/ob) mice. Interestingly, one of these enzymes, hydroxypyruvate reductase, which was 6-fold upregulated in ob/ob livers, participates in the conversion of serine to glucose, suggesting that this unusual metabolic pathway may contribute to gluconeogenesis selectively in states of obesity.

Acetamides↗

Proteomic profiling in musculoskeletal oncology by MALDI mass spectrometry.

UNLABELLED: Proteomics is the emerging technology that evaluates normal and abnormal protein expression in tissues. Tissue profiling by matrix assisted laser desorption ionization mass spectrometry (MALDI MS) is a proteomic tool that permits the rapid detection of proteins expressed in tissues and serum. To date, tissue profiling has been successfully utilized to detect proteins specific to various cancers, including those of non-small cell lung carcinoma and glioblastoma multiforme. The usefulness of histological analyses to predict soft tissue sarcoma (STS) behavior has plateaued, and a critical need exists to identify other means to objectively predict tumor grade and behavior. We describe tissue profiling as a tool for orthopaedic research, and review recent work utilizing the technology for detecting proteins that differentiate low grade from high grade STS. We used MALDI MS tissue profiling technology to detect differentially expressed proteins in high grade and low grade STS. LEVEL OF EVIDENCE: Level I, prognostic study.

Cell Cycle Proteins↗

Developing photoactive affinity probes for proteomic profiling: hydroxamate-based probes for metalloproteases.

The denaturing aspect of current activity-based protein profiling strategies limits the classes of chemical probes to those which irreversibly and covalently modify their targeting enzymes. Herein, we present a complimentary, affinity-based labeling approach to profile enzymes which do not possess covalently bound substrate intermediates. Using a variety of enzymes belonging to the class of metalloproteases, the feasibility of the approach was successfully demonstrated in several proof-of-concept experiments. The design template of affinity-based probes targeting metalloproteases consists of a peptidyl hydroxamate zinc-binding group (ZBG), a fluorescent reporter tag, and a photolabile diazirine group. Photolysis of the photolabile unit in the probe effectively generates a covalent, irreversible linkage between the probe and the target enzyme, rendering the enzyme distinguishable from unlabeled proteins upon separation on a SDS-PAGE gel. A variety of labeling studies were carried out to confirm that the affinity-based approach selectively labeled metalloproteases in the presence of a large excess of other proteins and that the success of the labeling reaction depends intimately upon the catalytic activity of the enzyme. Addition of competitive inhibitors proportionally diminished the extent of enzyme labeling, making the approach useful for potential in situ screening of metalloprotease inhibitors. Using different probes with varying P(1) amino acids, we were able to generate unique "fingerprint" profiles of enzymes which may be used to determine their substrate specificities. Finally, by testing against a panel of yeast metalloproteases, we demonstrated that the affinity-based approach may be used for the large-scale profiling of metalloproteases in future proteomic experiments.

Affinity Labels↗

Proteomic profiling and neurodegeneration in Alzheimer's disease.

Quantitative proteome analysis of Alzheimer's disease (AD) brains was performed using 2-D gels to identify disease specific changes in protein expression. The task of characterizing the proteome and its components is now practically achievable because of the development and integration of four important tools: protein, EST, and complete genome sequence databases, mass spectrometry, matching software for protein sequences and protein separation technology. Mass spectrometry (MS) instrumentation has undergone a tremendous change over the past decade, culminating in the development of highly sensitive, robust instruments that can reliably analyze biomolecules, particularly proteins and peptides; we identified 35 proteins from over 100 protein spots on a 2-D gel. Using this current technology, protein-expression profiling, which is actually a specialized form of mining, is an important principal application of proteomics. The information obtained has tremendous potential as a means of determining the pathogenesis, and detecting disease markers and potential targets for drug therapy in AD.

Aged↗

Assessment of genome and proteome profiles in cocaine abuse.

Until recently, knowledge of the impact of abuse drugs on gene and protein expression in the brain was limited to less than 100 targets. With the advent of high-throughput genomic and proteomic techniques investigators are now able to evaluate changes across the entire genome and across thousands of proteins in defined brain regions and generate expression profiles of vulnerable neuroanatomical substrates in rodent and non-human primate drug abuse models and in human post-mortem brain tissue from drug abuse victims. The availability of gene and protein expression profiles will continue to expand our understanding of the short- and long-term consequences of drug addiction and other addictive disorders and may provide new approaches or new targets for pharmacotherapeutic intervention. This chapter will review gene expression data from rodent, non-human primate and human post-mortem studies of cocaine abuse and will provide a preliminary proteomic profile of human cocaine abuse and explore how these studies have advanced our understanding of addiction.

Animals↗

Proteomic profiling of mechanistically distinct enzyme classes using a common chemotype.

Proteomics research requires methods to characterize the expression and function of proteins in complex mixtures. Toward this end, chemical probes that incorporate known affinity labeling agents have facilitated the activity-based profiling of certain enzyme families. To accelerate the discovery of proteomics probes for enzyme classes lacking cognate affinity labels, we describe here a combinatorial strategy. Members of a probe library bearing a sulfonate ester chemotype were screened against complex proteomes for activity-dependent protein reactivity, resulting in the labeling of at least six mechanistically distinct enzyme classes. Surprisingly, none of these enzymes represented targets of previously described proteomics probes. The sulfonate library was used to identify an omega-class glutathione S-transferase whose activity was upregulated in invasive human breast cancer lines. These results indicate that activity-based probes compatible with whole-proteome analysis can be developed for numerous enzyme classes and applied to identify enzymes associated with discrete pathological states.

Affinity Labels↗

Proteomic profiling of urinary protein excretion in the factor H-deficient mouse.

BACKGROUND: Since the 1970s a variety of experimental techniques have been employed in an attempt to identify urinary biomarkers of renal injury. While these approaches have met with some success, modern proteomic tools now permit broad based high-throughput analysis of the urinary proteome. METHODS: Using the ICAT isotopic labeling based LC/MS/MS approach, comparative urinary protein profiling was performed in a murine model of membranoproliferative glomerulonephritis. Paired samples were analyzed mice with a targeted deletion of the complement regulatory protein factor H (FH-/-) and control mice. RESULTS: 25 distinct urinary proteins were identified of which 7 were differentially expressed in the FH-/- mice. Two proteins were markedly altered in the urine of FH-/- mice compared to controls: uromodulin (5.5-fold lower) and the MHC class II molecule H2e (8.6-fold higher). Differential expression was confirmed by Western blot and RT-PCR. Immunofluorescent staining demonstrated a marked increased expression of H2e and a reduction of uromodulin expression in the tubular epithelium of FH-/- mice. CONCLUSIONS: These findings provide insight into early complement-dependent alterations in tubular protein expression which may play critical roles in the development of tubulointerstitial disease, and provide experimental support for the use of urinary proteomic profiling in murine models of renal injury.

Animals↗

Identification of developmentally-regulated proteins in Leishmania panamensis by proteome profiling of promastigotes and axenic amastigotes.

We have employed proteomics to identify proteins upregulated in the amastigote life-stage of Leishmaniapanamensis, using axenically-differentiated forms as models of authentic intracellular parasites. Resolution of the soluble proteomes of axenic amastigotes and promastigotes by two-dimensional electrophoresis (2DE) in the neutral pI range (5-7) revealed equivalent numbers of protein spots in both life-stages (644-682 using Coomassie Blue and 851-863 by silver staining). Although representing a relatively low proportion (8.1-10.8%) of the predicted 8000 gene products of Leishmania, these proteome maps enabled the reproducible detection of 75 differentially-regulated protein spots in amastigotes, comprising 24 spots "uniquely" expressed in this life-stage and 51 over-expressed by 1.2-5.7-fold compared to promastigotes. Of the 11 amastigote-specific spots analysed by mass spectrometry (MS), 5 yielded peptide sequences with no orthologues in Leishmania major, and the remaining 6 were identified as 7 distinct proteins (some of which were truncated isoforms) representing several functional classes: carbohydrate/energy metabolism (fructose 1,6-bisphosphate aldolase, glucose 6-phosphate dehydrogenase, pyruvate dehydrogenase), stress response (heat shock protein [HSP] 83), cell membrane/cytoskeleton (beta-tubulin), amino acid metabolism (cysteine synthase) and cell-cycle (ran-binding protein). Four additional over-expressed spots were tentatively identified as HSPs 60 and 70 and HSP 70-related proteins -1 and -4 by positional analogy with these landmark proteins in the Leishmania guyanensis proteome. Our data demonstrate the feasibility of proteomics as an approach to identify novel developmentally-regulated proteins linked to Leishmania differentiation and intracellular survival, while simultaneously pinpointing therapeutic targets. In particular, the amastigote-specific expression of cysteine synthase underlines the importance of de novo cysteine synthesis both as a potential parasite virulence factor and as a major metabolic difference from mammalian host cells.

Amino Acid Sequence↗