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PubMed2005

Effects of growth phase and the developmentally significant bldA-specified tRNA on the membrane-associated proteome of Streptomyces coelicolor.

Previous proteomic analyses of Streptomyces coelicolor by two-dimensional electrophoresis and protein mass fingerprinting focused on extracts from total cellular material. Here, the membrane-associated proteome of cultures grown in a liquid minimal medium was partially characterized. The products of some 120 genes were characterized from the membrane fraction, with 70 predicted to possess at least one transmembrane helix. A notably high proportion of ABC transporter systems was represented; the specific types detected provided a snapshot of the nutritional requirements of the mycelium. The membrane-associated proteins did not change very much in abundance in different phases of growth in liquid minimal medium. Identification of gene products not expected to be present in membrane protein extracts led to a reconsideration of the genome annotation in two cases, and supplemented scarce information on 11 hypothetical/conserved hypothetical proteins of unknown function. The wild-type membrane proteome was compared with that of a bldA mutant lacking the only tRNA capable of efficient translation of the rare UUA (leucine) codon. Such mutants are unaffected in vegetative growth but are defective in many aspects of secondary metabolism and morphological differentiation. There were a few clear changes in the membrane proteome of the mutant. In particular, two hypothetical proteins (SCO4244 and SCO4252) were completely absent from the bldA mutant, and this was associated with the TTA-containing regulatory gene SCO4263. Evidence for the control of a cluster of function-unknown genes by the SCO4263 regulator revealed a new aspect of the pleiotropic bldA phenotype.

Base Sequence↗

PubMed2000

Identification of novel human genes evolutionarily conserved in Caenorhabditis elegans by comparative proteomics.

Modern biomedical research greatly benefits from large-scale genome-sequencing projects ranging from studies of viruses, bacteria, and yeast to multicellular organisms, like Caenorhabditis elegans. Comparative genomic studies offer a vast array of prospects for identification and functional annotation of human ortholog genes. We presented a novel comparative proteomic approach for assembling human gene contigs and assisting gene discovery. The C. elegans proteome was used as an alignment template to assist in novel human gene identification from human EST nucleotide databases. Among the available 18,452 C. elegans protein sequences, our results indicate that at least 83% (15,344 sequences) of C. elegans proteome has human homologous genes, with 7,954 records of C. elegans proteins matching known human gene transcripts. Only 11% or less of C. elegans proteome contains nematode-specific genes. We found that the remaining 7,390 sequences might lead to discoveries of novel human genes, and over 150 putative full-length human gene transcripts were assembled upon further database analyses. [The sequence data described in this paper have been submitted to the

Amino Acid Sequence↗

PubMed2001

A proteomic view on genome-based signal peptide predictions.

The availability of complete genome sequences has allowed the prediction of all exported proteins of the corresponding organisms with dedicated algorithms. Even though numerous studies report on genome-based predictions of signal peptides and cell retention signals, they lack a proteomic verification. For example, 180 secretory and 114 lipoprotein signal peptides were predicted recently for the Gram-positive eubacterium Bacillus subtilis. In the present studies, proteomic approaches were used to define the extracellular complement of the B. subtilis secretome. Using different growth conditions and a hyper-secreting mutant, approximately 200 extracellular proteins were visualized by two-dimensional (2D) gel electrophoresis, of which 82 were identified by mass spectrometry. These include 41 proteins that have a potential signal peptide with a type I signal peptidase (SPase) cleavage site, and lack a retention signal. Strikingly, the remaining 41 proteins were predicted previously to be cell associated because of the apparent absence of a signal peptide (22), or the presence of specific cell retention signals in addition to an export signal (19). To test the importance of the five type I SPases and the unique lipoprotein-specific SPase of B. subtilis, the extracellular proteome of (multiple) SPase mutants was analyzed. Surprisingly, only the processing of the polytopic membrane protein YfnI was strongly inhibited in Spase I mutants, showing for the first time that a native eubacterial membrane protein is a genuine Spase I substrate. Furthermore, a mutation affecting lipoprotein modification and processing resulted in the shedding of at least 23 (lipo-)proteins into the medium. In conclusion, our observations show that genome-based predictions reflect the actual composition of the extracellular proteome for approximately 50%. Major problems are currently encountered with the prediction of extracellular proteins lacking signal peptides (including cytoplasmic proteins) and lipoproteins.

Amino Acid Sequence↗

PubMed2005

Modeling of protein signaling networks in clinical proteomics.

Molecular interactions that underlie pathophysiological states are being elucidated using techniques that profile proteomic endpoints in cellular systems. Within the field of cancer research, protein interaction networks play pivotal roles in the establishment and maintenance of the hallmarks of malignancy, including cell division, invasion, and migration. Multiple complementary tools enable a multifaceted view of how signal protein pathway alterations contribute to pathophysiological states. One pivotal technique is signal pathway profiling of patient tissue specimens. This microanalysis technology provides a proteomic snapshot at one point in time of cells directly procured from the native context of a tumor microenvironment. To study the adaptive patterns of signal pathway events over time, before and after experimental therapy, it is necessary to obtain biopsies from patients before, during, and after therapy. A complementary approach is the profiling of cultured cell lines with and without treatment. Cultured cell models provide the opportunity to study short-term signal changes occurring over minutes to hours. Through this type of system, the effects of particular pharmacological agents may be used to test the effects of signal pathway inhibition or activation on multiple endpoints within a pathway. The complexity of the data generated has necessitated the development of mathematical models for optimal interpretation of interrelated signaling pathways. In combination, clinical proteomic biopsy profiling, tissue culture proteomic profiling, and mathematical modeling synergistically enable a deeper understanding of how protein associations lead to disease states and present new insights into the design of therapeutic regimens.

Humans↗

PubMed2004

Proteome reference maps of vegetative tissues in pea. An investigation of nitrogen mobilization from leaves during seed filling.

A proteomic approach was used to analyze protein changes during nitrogen mobilization (N mobilization) from leaves to filling seeds in pea (Pisum sativum). First, proteome reference maps were established for mature leaves and stems. They displayed around 190 Coomassie Blue-stained spots with pIs from 4 to 7. A total of 130 spots were identified by mass spectrometry as corresponding to 80 different proteins implicated in a variety of cellular functions. Although the leaf proteome map contained more abundant spots, corresponding to proteins involved in energy/carbon metabolism, than the stem map, their comparison revealed a highly similar protein profile. Second, the leaf proteome map was used to analyze quantitative variations in leaf proteins during N mobilization. Forty percent of the spots showed significant changes in their relative abundance in the total protein extract. The results confirmed the importance of Rubisco as a source of mobilizable nitrogen, and suggested that in pea leaves the rate of degradation of Rubisco may vary throughout N mobilization. Correlated with the loss of Rubisco was an increase in relative abundance of chloroplastic protease regulatory subunits. Concomitantly, the relative abundance of some proteins related to the photosynthetic apparatus (Rubisco activase, Rubisco-binding proteins) and of several chaperones increased. A role for these proteins in the maintenance of a Rubisco activation state and in the PSII repair during the intense proteolytic activity within the chloroplasts was proposed. Finally, two 14-3-3-like proteins, with a potential regulatory role, displayed differential expression patterns during the massive remobilization of nitrogen.

Amino Acid Sequence↗

PubMed2006

Proteomic investigation of the effect of salicylic acid on Arabidopsis seed germination and establishment of early defense mechanisms.

The influence of salicylic acid (SA) on elicitation of defense mechanisms in Arabidopsis (Arabidopsis thaliana) seeds and seedlings was assessed by physiological measurements combined with global expression profiling (proteomics). Parallel experiments were carried out using the NahG transgenic plants expressing the bacterial gene encoding SA hydroxylase, which cannot accumulate the active form of this plant defense elicitor. SA markedly improved germination under salt stress. Proteomic analyses disclosed a specific accumulation of protein spots regulated by SA as inferred by silver-nitrate staining of two-dimensional gels, detection of carbonylated (oxidized) proteins, and neosynthesized proteins with [35S]-methionine. The combined results revealed several processes potentially affected by SA. This molecule enhanced the reinduction of the late maturation program during early stages of germination, thereby allowing the germinating seeds to reinforce their capacity to mount adaptive responses in environmental water stress. Other processes affected by SA concerned the quality of protein translation, the priming of seed metabolism, the synthesis of antioxidant enzymes, and the mobilization of seed storage proteins. All the observed effects are likely to improve seed vigor. Another aspect revealed by this study concerned the oxidative stress entailed by SA in germinating seeds, as inferred from a characterization of the carbonylated (oxidized) proteome. Finally, the proteomic data revealed a close interplay between abscisic signaling and SA elicitation of seed vigor.

Adaptation, Physiological↗

PubMed2005

Discover true association rates in multi-protein complex proteomics data sets.

Experimental processes to collect and process proteomics data are increasingly complex, while the computational methods to assess the quality and significance of these data remain unsophisticated. These challenges have led to many biological oversights and computational misconceptions. We developed a complete empirical Bayes model to analyze multi-protein complex (MPC) proteomics data derived from peptide mass spectrometry detections of purified protein complex pull-down experiments. Our model considers not only bait-prey associations, but also prey-prey associations missed in previous work. Using our model and a yeast MPC proteomics data set, we estimated that there should be an average of 28 true associations per MPC, almost ten times as high as was previously estimated. For data sets generated to mimic a real proteome, our model achieved on average 80% sensitivity in detecting true associations, as compared with the 3% sensitivity in previous work, while maintaining a comparable false discovery rate of 0.3%.

Algorithms↗

PubMed2025

Proteomics-enabled learning machine algorithms enhance the prediction of cardiovascular diseases in patients with type 2 diabetes mellitus.

BACKGROUND AND AIMS: Estimating the risk of cardiovascular disease (CVD) complications in type 2 diabetes mellitus (T2DM) patients is critical in the medical decision-making process. This study aimed to use a machine learning technique combined with proteomics to develop personalized models for predicting CVD in patients with T2DM. METHODS AND RESULTS: In total, 874 patients with T2DM and 2,920 Olink proteins obtained from the UK Biobank were used in this study. Proteins were screened using Cox regression and LASSO regression. A basic model containing clinical features and a full model combining proteome and clinical features were constructed using the random survival forest algorithm. The area under the receiver operating characteristic (ROC) curve (AUC) was used to evaluate the predictive performance of the models and compare them with other CVD predictive models. Compared with the basic model, the full model performed better in predicting CVD, with time-dependent AUCs of 0.81 (3 years), 0.74 (5 years) and 0.74 (10 years) (0.77, 0.69 and 0.67). We calculated the risk scores of the Framingham, ASCVD and Score2-Diabetes models. The results revealed that the prediction performance of the full model was also better than that of the abovementioned models. In terms of differentiation accuracy, the results of the net reclassification improvement index and integrated discrimination improvement index showed that the full model can identify high-risk individuals more accurately (accuracy rate: 79% vs. 69%). CONCLUSIONS: Proteomics can be used to predict cardiovascular complications in diabetic patients. It is also necessary to consider the applicability of the model due to the limitations of the sample size and the constraints of proteomics in clinical applications.

Humans↗

PubMedDate not supplied

Ovarian cancer in the proteomics era: diagnosis, prognosis, and therapeutics targets.

Ovarian cancer is clinically quiet as it plants seeds of metastases in the peritoneal cavity, even during early stages when there is highest potential for cure. The only available biomarker is CA125, which has an unacceptably low sensitivity and specificity for diagnostic use. Highly sensitive and specific tools to further optimize early diagnosis and treatment are needed. We propose that proteomic technologies have an important role to play in the development of these tools. Mass spectrometry platforms, such as surface-enhanced laser desorption/ionization time-of-flight, may be used to mine patient's serum for proteomic signatures that are shed by tumor and stroma. Such signatures could serve as a diagnostic tool during early-stage disease and as a remission-monitoring tool in later-stage disease. Reverse-phase protein microarrays are a new microproteomic tool to profile signaling pathways in ovarian cancer, thus identifying therapeutic targets while simultaneously suggesting prognostic indicators. Proteomic technologies have the capacity to build upon our genomic and clinical understanding of ovarian cancer by moving the focal point to the tumor and its microenvironment. This unique proteomic vantage point allows the creation of tools that will aid clinicians in making rational decisions in the diagnosis and treatment of women with ovarian cancer.

Biomarkers, Tumor↗

PubMed2002

Discovery of novel targets of quinoline drugs in the human purine binding proteome.

The quinolines have been used in the treatment of malaria, arthritis, and lupus for many years, yet the precise mechanism of their action remains unclear. In this study, we used a functional proteomics approach that exploited the structural similarities between the quinoline compounds and the purine ring of ATP to identify quinoline-binding proteins. Several quinoline drugs were screened by displacement affinity chromatography against the purine binding proteome captured with gamma-phosphate-linked ATP-Sepharose. Screening of the human red blood cell purine binding proteome identified two human proteins, aldehyde dehydrogenase 1 (ALDH1) and quinone reductase 2 (QR2). In contrast, no proteins were detected upon screening of the Plasmodium falciparum purine binding proteome with the quinolines. In a complementary approach, we passed cell lysates from mice, red blood cells, or P. falciparum over hydroxychloroquine- or primaquine-Sepharose. Consistent with the displacement affinity chromatography screen, ALDH and QR2 were the only proteins recovered from mice and human red blood cell lysate and no proteins were recovered from P. falciparum. Furthermore, the activity of QR2 was potently inhibited by several of the quinolines in vitro. Our results show that ALDH1 and QR2 are selective targets of the quinolines and may provide new insights into the mechanism of action of these drugs.

Adenosine Triphosphate↗

PubMed2004

Proteomics in aging-related research.

Aging is characterized by changes in a variety of cellular phenotypes, which in turn are caused by alterations in the concentrations, compositions, and interactions of cellular proteins. The characterization of these age-associated protein alterations and of their effect on the ability of the organism to maintain homeostasis is thus of critical importance. Proteomics is an emerging scientific discipline that focuses on the determination and analysis of the entire protein complement of a cell (termed the proteome) and of its distribution within the cell. Proteomic analysis provides information about the levels of protein expression under a variety of conditions and about the nature of posttranscriptional modifications, and reveals specific protein complexes. By comparing the proteomes of young and old cells under a variety of conditions, detailed information on the molecular basis of their different phenotypes can be obtained. Although still under development, this scientific discipline holds great promise for aging-related research.

Aging↗

PubMed2005

Global topology analysis of the Escherichia coli inner membrane proteome.

The protein complement of cellular membranes is notoriously resistant to standard proteomic analysis and structural studies. As a result, membrane proteomes remain ill-defined. Here, we report a global topology analysis of the Escherichia coli inner membrane proteome. Using C-terminal tagging with the alkaline phosphatase and green fluorescent protein, we established the periplasmic or cytoplasmic locations of the C termini for 601 inner membrane proteins. By constraining a topology prediction algorithm with this data, we derived high-quality topology models for the 601 proteins, providing a firm foundation for future functional studies of this and other membrane proteomes. We also estimated the overexpression potential for 397 green fluorescent protein fusions; the results suggest that a large fraction of all inner membrane proteins can be produced in sufficient quantities for biochemical and structural work.

Alkaline Phosphatase↗

PubMed2026

Proteomics identify disease-associated variants in patients with rare diseases undiagnosed after genome sequencing.

Despite the introduction of genome sequencing (GS) for rare disease diagnostics, a genetic cause is not identified in most patients. Here, we explored the potential of proteomics to improve the diagnostic yield in 424 patients with rare diseases from the 100,000 Genomes Project (100kGP) without a genetic diagnosis. Serum proteomic profiling was performed using the Olink Explore 1536 assay (N = 1463 proteins). For 13 patients without genetic diagnoses, detection of lower serum protein "outliers" (z-score < -2) led to confirmed genetic diagnoses by resolving variants of uncertain significance or prioritizing genes for targeted GS reanalysis. For 23 additional patients without genetic diagnoses (64% of findings), we identified candidate gene-disease links and variants through convergent evidence from lower protein outliers and variants ranked through the variant prioritization tool Exomiser. For example, we identified a candidate heterozygous missense variant [Genome Aggregation Database (gnomAD) minor allele frequency = 0.006%] in tyrosine kinase with immunoglobulin-like and epidermal growth factor homology domains 1 (TIE1) that was only present in a patient with lower TIE1 serum abundance (z-score = -5.12) and their father, both of whom were affected by the same monogenic cardiac disorder, but in no other individuals from the 100kGP. Missense (52.5%) and splice region (27.5%) variants accounted for most diagnostic or candidate variants prioritized. This proof-of-principle study demonstrated that serum proteomics can support rare disease diagnosis and identify disease-causing genes in patients undiagnosed after GS, although successful implementation will likely depend on tissue specificity of protein expression, detectability in blood, proteomic platform coverage, and sensitivity.

Humans↗

PubMed2002

Proteomic analysis reveals differential protein expression by Bacillus cereus during biofilm formation.

Bacillus cereus, a dairy-associated toxigenic bacterium, readily forms biofilms on various surfaces and was used to gain a better understanding of biofilm development by gram-positive aerobic rods. B. cereus DL5 was shown to readily adapt to an attached mode of growth, with dense biofilm structures developing within 18 h after inoculation when glass wool was used as a surface. Two-dimensional gel electrophoresis (2DE) revealed distinct and reproducible phenotypic differences between 2- and 18-h-old biofilm and planktonic cells (grown both in the presence and in the absence of glass wool). Whereas the 2-h-old biofilm proteome indicated expression of 15 unique proteins, the 18-h-old biofilm proteome contained 7 uniquely expressed proteins. Differences between the microcolony (2-h) proteome and the more developed biofilm (18-h) proteome were largely due to up- and down-regulation of the expression of a multitude of proteins. Selected protein spots excised from 2DE gels were subjected to N-terminal sequencing and identified with high confidence. Among the proteins were catabolic ornithine carbamoyltransferase and L-lactate dehydrogenase. Interestingly, increased levels of YhbH, a member of the sigma 54 modulation protein family which is strongly induced in response to environmental stresses and energy depletion via both sigma(B) and sigma(H), could be observed within 2 h in both attached cells and planktonic cultures growing in the presence of glass wool, indicating that this protein plays an important role in regulation of the biofilm phenotype. Distinct band differences were also found between the extracellular proteins of 18-h-old cultures grown in the presence and in the absence of glass wool.

Bacillus cereus↗

PubMed2005

Proteomic signature of Lactococcus lactis NCDO763 cultivated in milk.

We have compared the proteomic profiles of L. lactis subsp. cremoris NCDO763 growing in the synthetic medium M17Lac, skim milk microfiltrate (SMM), and skim milk. SMM was used as a simple model medium to reproduce the initial phase of growth of L. lactis in milk. To widen the analysis of the cytoplasmic proteome, we used two different gel systems (pH ranges of 4 to 7 and 4.5 to 5.5), and the proteins associated with the cell envelopes were also studied by two-dimensional electrophoresis. In the course of the study, we analyzed about 800 spots and identified 330 proteins by mass spectrometry. We observed that the levels of more than 50 and 30 proteins were significantly increased upon growth in SMM and milk, respectively. The large redeployment of protein synthesis was essentially associated with an activation of pathways involved in the metabolism of nitrogenous compounds: peptidolytic and peptide transport systems, amino acid biosynthesis and interconversion, and de novo biosynthesis of purines. We also showed that enzymes involved in reactions feeding the purine biosynthetic pathway in one-carbon units and amino acids have an increased level in SMM and milk. The analysis of the proteomic data suggested that the glutamine synthetase (GS) would play a pivotal role in the adaptation to SMM and milk. The analysis of glnA expression during growth in milk and the construction of a glnA-defective mutant confirmed that GS is an essential enzyme for the development of L. lactis in dairy media. This analysis thus provides a proteomic signature of L. lactis, a model lactic acid bacterium, growing in its technological environment.

Animals↗

PubMed2005

Integrative genomic, transcriptional, and proteomic diversity in natural isolates of the human pathogen Burkholderia pseudomallei.

Natural isolates of pathogenic bacteria can exhibit a broad range of phenotypic traits. To investigate the molecular mechanisms contributing to such phenotypic variability, we compared the genomes, transcriptomes, and proteomes of two natural isolates of the gram-negative bacterium Burkholderia pseudomallei, the causative agent of the human disease melioidosis. Significant intrinsic genomic, transcriptional, and proteomic variations were observed between the two strains involving genes of diverse functions. We identified 16 strain-specific regions in the B. pseudomallei K96243 reference genome, and for eight regions their differential presence could be ascribed to either DNA acquisition or loss. A remarkable 43% of the transcriptional differences between the strains could be attributed to genes that were differentially present between K96243 and Bp15682, demonstrating the importance of lateral gene transfer or gene loss events in contributing to pathogen diversity at the gene expression level. Proteins expressed in a strain-specific manner were similarly correlated at the gene expression level, but up to 38% of the global proteomic variation between strains comprised proteins expressed in both strains but associated with strain-specific protein isoforms. Collectively, >65 hypothetical genes were transcriptionally or proteomically expressed, supporting their bona fide biological presence. Our results provide, for the first time, an integrated framework for classifying the repertoire of natural variations existing at distinct molecular levels for an important human pathogen.

Bacterial Proteins↗

PubMed2005

Proteome analysis of liver cells expressing a full-length hepatitis C virus (HCV) replicon and biopsy specimens of posttransplantation liver from HCV-infected patients.

The development of a reproducible model system for the study of hepatitis C virus (HCV) infection has the potential to significantly enhance the study of virus-host interactions and provide future direction for modeling the pathogenesis of HCV. While there are studies describing global gene expression changes associated with HCV infection, changes in the proteome have not been characterized. We report the first large-scale proteome analysis of the highly permissive Huh-7.5 cell line containing a full-length HCV replicon. We detected >4,200 proteins in this cell line, including HCV replicon proteins, using multidimensional liquid chromatographic (LC) separations coupled to mass spectrometry. Consistent with the literature, a comparison of HCV replicon-positive and -negative Huh-7.5 cells identified expression changes of proteins involved in lipid metabolism. We extended these analyses to liver biopsy material from HCV-infected patients where a total of >1,500 proteins were detected from only 2 mug of liver biopsy protein digest using the Huh-7.5 protein database and the accurate mass and time tag strategy. These findings demonstrate the utility of multidimensional proteome analysis of the HCV replicon model system for assisting in the determination of proteins/pathways affected by HCV infection. Our ability to extend these analyses to the highly complex proteome of small liver biopsies with limiting protein yields offers the unique opportunity to begin evaluating the clinical significance of protein expression changes associated with HCV infection.

Amino Acid Sequence↗

PubMed2026

DIA proteomics of FFPE renal biopsies reveals two molecular subtypes of lupus nephritis and identifies APOL1 as candidate biomarker for stratification.

INTRODUCTION: Lupus nephritis (LN) exhibits substantial clinical and pathological heterogeneity. We aimed to define proteomics-based molecular subtypes of LN and identify candidate biomarkers for subtype discrimination. METHODS: We analysed formalin-fixed paraffin-embedded (FFPE) renal biopsy specimens from 292 patients with biopsy-proven LN from four tertiary hospitals using data-independent acquisition (DIA)-liquid chromatography-tandem mass spectrometry (LC-MS/MS) proteomics. Molecular subtypes were identified by non-negative matrix factorisation. Differential proteins, functional enrichment, immune pathway activity, protein-protein interaction networks and subtype-associated clinical/pathological features were evaluated. Extreme Gradient Boosting (XGBoost) with SHapley Additive exPlanations (SHAP) and Least Absolute Shrinkage and Selection Operator (LASSO) logistic regression were used to identify key subtype-related features and derive a protein panel distinguishing proliferative (class III/IV) from membranous (class V) LN. RESULTS: Two stable molecular subtypes were identified, with 1002 differential proteins between them. Subtype_2 was enriched for interferon-related innate immunity, complement activation, phagocytosis-endocytosis-lysosome pathways and ribosome biogenesis/RNA metabolism, whereas Subtype_1 was characterised by keratinisation and epithelial structural remodelling. Subtype_2 was associated with higher serum creatinine, lower estimated glomerular filtration rate and higher chronicity index. APOL1 showed discriminatory value between subtypes, and serum ELISA demonstrated a consistent pattern with FFPE proteomic findings. A five-protein LASSO panel achieved an area under the curve of approximately 0.76 for distinguishing class III/IV from class V LN. CONCLUSION: DIA-based proteomic profiling of FFPE renal biopsies identifies biologically and clinically relevant LN molecular subtypes and may support tissue-informed classification and risk stratification.

Humans↗