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PubMed2000

Harnessing the power of the genome in the search for new antibiotics.

Over the past 40 years, the search for new antibiotics has been largely restricted to well-known compound classes active against a standard set of drug targets. Although many effective compounds have been discovered, insufficient chemical variability has been generated to prevent a serious escalation in clinical resistance. Recent advances in genomics have provided an opportunity to expand the range of potential drug targets and have facilitated a fundamental shift from direct antimicrobial screening programs toward rational target-based strategies. The application of genome-based technologies such as expression profiling and proteomics will lead to further changes in the drug discovery paradigm by combining the strengths and advantages of both screening strategies in a single program.

Anti-Bacterial Agents↗
PubMed2004

Simultaneous measurement of multiple radiation-induced protein expression profiles using the Luminex(TM) system.

Space flight results in the exposure of astronauts to a mixed field of radiation composed of energetic particles of varying energies, and biological indicators of space radiation exposure provides a better understanding of the associated long-term health risks. Current methods of biodosimetry have employed the use of cytogenetic analysis for biodosimetry, and more recently the advent of technological progression has led to advanced research in the use of genomic and proteomic expression profiling to simultaneously assess biomarkers of radiation exposure. We describe here the technical advantages of the Luminex(TM) 100 system relative to traditional methods and its potential as a tool to simultaneously profile multiple proteins induced by ionizing radiation. The development of such a bioassay would provide more relevant post-translational dynamics of stress response and will impart important implications in the advancement of space and other radiation contact monitoring.

Antibodies↗
PubMed2009

An outlook on ovarian cancer and borderline ovarian tumors: focus on genomic and proteomic findings.

Among the gynaecological malignancies, ovarian cancer is one of the neoplastic forms with the poorest prognosis and with the bad overall and disease-free survival rates than other gynaecological cancers. Ovarian tumors can be classified on the basis of the cells of origin in epithelial, stromal and germ cell tumors. Epithelial ovarian tumors display great histological heterogeneity and can be further subdivided into benign, intermediate or borderline, and invasive tumors. Several studies on ovarian tumors, have focused on the identification of both diagnostic and prognostic markers for applications in clinical practice. High-throughput technologies have accelerated the process of biomolecular study and genomic discovery; unfortunately, validity of these should be still demonstrated by extensive researches on sensibility and sensitivity of ovarian cancer novel biomarkers, determining whether gene profiling and proteomics could help differentiate between patients with metastatic ovarian cancer and primary ovarian carcinomas, and their potential impact on management. Therefore, considerable interest lies in identifying molecular and protein biomarkers and indicators to guide treatment decisions and clinical follow up. In this review, the current state of knowledge about the genoproteomic and potential clinical value of gene expression profiling in ovarian cancer and ovarian borderline tumors is discussed, focusing on three main areas: distinguishing normal ovarian tissue from ovarian cancers and borderline tumors, identifying different genotypes of ovarian tissue and identifying proteins linked to cancer or tumor development. By these targets, authors focus on the use of novel molecules, developed on the proteomics and genomics researches, as potential protein biomarkers in the management of ovarian cancer or borderline tumor, overlooking on current state of the art and on future perspectives of researches.

Ovarian cancer↗
PubMed2003

Proteomic approaches for the identification of cell cycle-related drug targets.

Drugs affecting the cell cycle provide insights into mechanisms underlying cancer and suggest strategies for ablating uncontrolled growth. Essential to an understanding of the activity of such compounds is the identification of the set of proteins affected, either directly or indirectly, by the drug. The combination of novel technologies for stable isotope protein tagging, chromatographic separation, tandem mass spectrometry, and data processing is an extremely powerful means for providing such identifications and, in addition, for establishing a proteome-wide profile of all proteins whose abundance levels or phosphorylation state are affected by the drug.

Animals↗
PubMed2006

Integrated molecular signature of disease: analysis of influenza virus-infected macaques through functional genomics and proteomics.

Recent outbreaks of avian influenza in humans have stressed the need for an improved nonhuman primate model of influenza pathogenesis. In order to further develop a macaque model, we expanded our previous in vivo genomics experiments with influenza virus-infected macaques by focusing on the innate immune response at day 2 postinoculation and on gene expression in affected lung tissue with viral genetic material present. Finally, we sought to identify signature genes for early infection in whole blood. For these purposes, we infected six pigtailed macaques (Macaca nemestrina) with reconstructed influenza A/Texas/36/91 virus and three control animals with a sham inoculate. We sacrificed one control and two experimental animals at days 2, 4, and 7 postinfection. Lung tissue was harvested for pathology, gene expression profiling, and proteomics. Blood was collected for genomics every other day from each animal until the experimental endpoint. Gross and microscopic pathology, immunohistochemistry, viral gene expression by arrays, and/or quantitative real-time reverse transcription-PCR confirmed successful yet mild infections in all experimental animals. Genomic experiments were performed using macaque-specific oligonucleotide arrays, and high-throughput proteomics revealed the host response to infection at the mRNA and protein levels. Our data showed dramatic differences in gene expression within regions in influenza virus-induced lesions based on the presence or absence of viral mRNA. We also identified genes tightly coregulated in peripheral white blood cells and in lung tissue at day 2 postinoculation. This latter finding opens the possibility of using gene expression arrays on whole blood to detect infection after exposure but prior to onset of symptoms or shedding.

Animals↗
PubMed2025

Extracellular vesicle proteomic expression is influenced by mining tenure in former uranium miners.

BACKGROUND: Chronic exposure to uranium (U) rich environments poses significant health risks, yet the molecular mechanisms underlying these effects remain poorly understood. Extracellular vesicles (EVs) are membrane-bound vesicles that transfer multiple biomolecules between cells and can regulate cellular function. OBJECTIVE: To determine whether U-mining tenure is associated with specific alterations in serum-derived EV proteomic and plasma cytokine profiles among former U-miners, and to assess the potential of EV-derived proteins as robust biomarkers of chronic U-exposure relative to canonical cytokines. METHODS: Serum and plasma samples were obtained from 39 former U-miners. Small and large EVs were isolated via differential ultracentrifugation and characterized by nanoparticle tracking and western blotting. EV proteomic profiles were analyzed using liquid chromatography-tandem mass spectrometry. Plasma cytokines were quantified using multiplex immunoassays. Age-adjusted linear regression was used to assess associations with mining tenure, and pathway enrichment analysis was performed on significant EV proteins. RESULTS: Eight small-EV and four large-EV proteins significantly correlated with mining tenure after age adjustment. Notably, Complement C1r subcomponent and Vitamin K-dependent protein S, and Fibrinogen alpha chain exhibited strong inverse correlations. Enrichment analyses highlighted immune-related and extracellular matrix pathways. Six cytokines were initially associated with mining tenure but lost significance after age adjustment. In contrast, EV protein associations appeared more robust for this confounding, underscoring their potential as exposure biomarkers. CONCLUSIONS: Serum EV-derived protein signatures were nominally associated with U-mining tenure independent of age, whereas cytokine profiles were confounded by age. These findings suggest that EV-derived proteins may provide sensitive biomarkers for monitoring long-term health effects of U-exposure, which warrants further investigation in larger cohorts.

Humans↗
PubMedDate not supplied

Two-dimensional mass spectra generated from the analysis of 15N-labeled and unlabeled peptides for efficient protein identification and de novo peptide sequencing.

Protein identification has been greatly facilitated by database searches against protein sequences derived from product ion spectra of peptides. This approach is primarily based on the use of fragment ion mass information contained in a MS/MS spectrum. Unambiguous protein identification from a spectrum with low sequence coverage or poor spectral quality can be a major challenge. We present a two-dimensional (2D) mass spectrometric method in which the numbers of nitrogen atoms in the molecular ion and the fragment ions are used to provide additional discriminating power for much improved protein identification and de novo peptide sequencing. The nitrogen number is determined by analyzing the mass difference of corresponding peak pairs in overlaid spectra of (15)N-labeled and unlabeled peptides. These peptides are produced by enzymatic or chemical cleavage of proteins from cells grown in (15)N-enriched and normal media, respectively. It is demonstrated that, using 2D information, i.e., m/z and its associated nitrogen number, this method can, not only confirm protein identification results generated by MS/MS database searching, but also identify peptides that are not possible to identify by database searching alone. Examples are presented of analyzing Escherichia coli K12 extracts that yielded relatively poor MS/MS spectra, presumably from the digests of low abundance proteins, which can still give positive protein identification using this method. Additionally, this 2D MS method can facilitate spectral interpretation for de novo peptide sequencing and identification of posttranslational or other chemical modifications. We envision that this method should be particularly useful for proteome expression profiling of organelles or cells that can be grown in (15)N-enriched media.

Amino Acid Sequence↗
PubMed2007

Hepatitis B virus-induced oncogenesis.

Hepatocellular carcinoma (HCC) is one of the most common cancers in the world with an annual incidence of more than 500000 in the year 2000. Its incidence is rising in many countries. Recently, it has been estimated that about 53% of HCC cases in the world are related to hepatitis B virus (HBV). The epidemiological association of HBV with HCC is well established. In recent studies, it was revealed that HBsAg carriers have a 25-37 times increased risk of developing HCC as compared to non-infected people. At present, HBV-associated carcinogenesis can be seen as a multi-factorial process that includes both direct and indirect mechanisms that might act synergistically. The integration of HBV DNA into the host genome occurs at early steps of clonal tumor expansion. The integration has been shown in a number of cases to affect a variety of cancer-related genes and to exert insertional mutagenesis. The permanent liver inflammation, induced by the immune response, resulting in a degeneration and regeneration process confers to the accumulation of critical mutations in the host genome. In addition to this, the regulatory proteins HBx and the PreS2 activators that can be encoded by the integrate exert a tumor promoter-like function resulting in positive selection of cells producing a functional regulatory protein. Gene expression profiling and proteomic techniques may help to characterize the molecular mechanisms driving HBV-associated carcinogenesis, and thus potentially identify new strategies in diagnosis and therapy.

Carcinoma, Hepatocellular↗
PubMed2002

Diabetes: a candidate disease for efficient DNA methylation profiling.

Methylation has been implied in a number of biological processes and has been shown to vary under environmental influences as well as in age. Most results on the correlation of methylation patterns with phenotypic characteristics of cells have been obtained by analysis of very few or even single genomic fragments for methylation. However, variation of methylation may more often than not be a phenomenon that affects multiple genomic loci. The role of methylation has been most conclusively demonstrated in complex disease, with cancer being the most prominent example. The influence of aging and environmental influences such as diet seems to be on global methylation patterns, in turn exerting local effects on groups of genes. Hence, methylation seems literally to be orchestrating complex genetic systems. It could, therefore, be considered an archetypal "genomics" parameter. In consequence, technologies used to analyze methylation patterns should be as industrialized as possible to capture the local events across the entire genome. Epigenomics' research team is the first to have achieved the industrialized production of genome sequence-specific wide methylation data. Our microarray and mass-spectrometry-based detection platform currently allow the analysis of up to 50,000 methylation positions per day, for the first time making methylation data amenable to sophisticated information mining. The information content of methylation position has never been analyzed using the high-dimensional statistical methods that are recognized to be required for the analysis of, for example, mRNA expression profiles or proteomic data. As methylation patterns are nothing but a quasi-digital form of expression data, their information content must be evaluated using similar but adapted algorithms. This article presents a broad set of studies that demonstrate that methylation yields information that is comparable or even superior to the current state of the art, namely, mRNA profiling. We argue that the resulting robust, digital and-because of the highly stable nature of DNA as the analyte-more reproducible information could become the "gold standard" for clinical diagnostics and disease gene identification in age-related, environmentally influenced and epigenetic disease in general, substituting for mRNA expression.

DNA Methylation↗
PubMed2004

Proteomics for hepatocellular carcinoma marker discovery.

Refinements of serological markers and screening of patients at high risk for developing hepatocellular carcinoma (HCC) may lead to better HCC detection, earlier intervention, and successful treatment, improving long-term outcomes. Proteomics promises the discovery of biomarkers for early HCC detection and diagnosis. Proteomic-based profiling uniquely allows delineation of global changes in expression patterns resulting from transcriptional and posttranscriptional control, posttranslational modifications, and shifts in proteins between cellular compartments. Approaches to that effect include direct serum protein profiling and comparative analysis of protein expression in normal, precancerous, and early-stage tumor tissues. Identification of panels of tumor antigens that elicit a humoral response also may contribute to the discovery of new markers for HCC screening and diagnosis. Today, 2-dimensional polyacrylamide gel electrophoresis, multidimensional liquid chromatography, mass spectrometry, and protein microarrays are among the proteomic tools available for biomarker and drug target discovery. We review these technologies and their application to the study of HCC. Our objective is to provide a framework for appreciating the promise, while at the same time understanding the challenges behind translating proteomics discovery into novel diagnostic tests.

Biomarkers, Tumor↗
PubMed2026

Multiomics profiling of plasma reveals lipid-immune dysregulation and exosome remodeling in mpox and mpox-HIV co-infection.

BACKGROUND: Monkeypox virus (MPXV) infects diverse human cell types, and human immunodeficiency virus (HIV) co-infection is common. The immunometabolic consequences of MPXV infection, and how it may be altered by HIV, remain poorly defined. METHODS: We performed quantitative plasma lipidomics and precise metabolomics in a discovery cohort (n = 81) comprising MPXV-monoinfected (MPLWOH), MPXV-HIV-coinfected (MPLWH), and HIV-monoinfected (PLWH) patients and healthy controls, integrating exosome proteomics, cytokine profiling, and transcriptomics of exosome-treated HepG2 and A549 cells for functional interpretation. An independent validation cohort (n = 65) was used to assess cross-cohort reproducibility. FINDINGS: MPXV infection induced broad lipid remodeling, with elevations in phosphatidylserine (PS) and phosphatidylethanolamine (PE) and reductions in phosphatidylcholine (PC), lysophospholipids, cholesteryl ester (CE), and exosomal lecithin-cholesterol acyltransferase (LCAT) and lipoprotein lipase (LPL). These lipid alterations were correlated with tissue injury markers and inflammatory cytokines. The MPLWH group exhibited more severe metabolic disruption, including marked sulfatide (SL) depletion, lower cholesterol and high-density lipoprotein cholesterol (HDL-c), and extensive rewiring of lipid-cytokine associations. SL depletion in MPLWH correlated with abundances of COPI-mediated retrograde trafficking proteins in exosomes. Transcriptomic profiling of exosome-treated cells provided functional validation: MPLWOH exosomes induced lipid metabolism and repair-associated epithelial programs, while MPLWH exosomes drove phospholipid remodeling and acute inflammatory and mucosal barrier-stress responses. CONCLUSIONS: MPXV infection reprograms host lipid metabolism and exosome composition, with HIV co-infection amplifying inflammatory, metabolic, and trafficking disruptions. These convergent multi-omics signatures link systemic lipid dysregulation to exosome-mediated immunomodulation and identify potential targets for host-directed interventions. FUNDING: This study was funded by the Major Project of Guangzhou National Laboratory.

Adult↗
PubMedDate not supplied

S100A8 chemotactic protein is abundantly increased, but only a minor contributor to LPS-induced, steroid resistant neutrophilic lung inflammation in vivo.

Neutrophilic lung inflammation is an essential component of host defense against diverse eukaryotic and prokaryotic pathogens, but in chronic inflammatory lung diseases, such as chronic obstructive lung disease (COPD), severe asthma, cystic fibrosis, and bronchiolitis, it may damage the host. Glucocorticosteroids are widely used in these conditions and in their infectious exacerbations; however, the clinical efficacy of steroids is disputed. In this study, we used a proteomic approach to identify molecules contributing to neutrophilic inflammation induced by transnasal administration of lipopolysaccharide (LPS) that were also resistant to the potent glucocorticosteroid dexamethasone (Dex). We confirmed that Dex was biologically active at both the transcript (suppression of GM-CSF and TNFalphatranscripts) and protein levels (induction of lipocortin) and used 2D-PAGE/MALDI-TOF to generate global expression profiles, identifying six LPS-induced proteins that were Dex resistant. Of these, S100A8, a candidate neutrophil chemotactic factor, was profiled in detail. Steroid refractory S100A8 expression was highly abundant, transcriptionally regulated, secreted into lung lavage fluid and immunohistochemically localized to tissue infiltrating neutrophils. However, in marked contrast to other vascular beds, neutralizing antibodies to S100A8 had only a weak anti-neutrophil recruitment effect and antibodies against the related S100A9 were ineffective. These data highlight the need for extensive in vivo profiling of proteomically identified candidate molecules and demonstrates that S100A8, despite its abundance, resistance to steroids and known chemotactic activity, is unlikely to be an important determinant of LPS-induced neutrophilic lung inflammation in vivo.

Animals↗
PubMed2005

Genomic medicine: genetic variation and its impact on the future of health care.

Advances in genome technology and other fruits of the Human Genome Project are playing a growing role in the delivery of health care. With the development of new technologies and opportunities for large-scale analysis of the genome, transcriptome, proteome and metabolome, the genome sciences are poised to have a profound impact on clinical medicine. Cancer prognostics will be among the first major test cases for a genomic medicine paradigm, given that all cancer is caused by genomic instability, and microarrays allow assessment of patients' entire expressed genomes. Analysis of breast cancer patients' expression patterns can already be highly correlated with recurrence risks. By integrating clinical data with gene expression profiles, imaging, metabolomic profiles and proteomic data, the prospect for developing truly individualized care becomes ever more real. Notwithstanding these promises, daunting challenges remain for genomic medicine. Success will require planning robust prospective trials, analysing health care economic and outcome data, assuaging insurance and privacy concerns, developing health delivery models that are commercially viable and scaling up to meet the needs of the whole population.

Delivery of Health Care↗
PubMed2001

Towards defining the urinary proteome using liquid chromatography-tandem mass spectrometry. I. Profiling an unfractionated tryptic digest.

The proteome of normal male urine from a commercial pooled source has been examined using direct liquid chromatography-tandem mass spectrometry (LC-MS/MS). The entire urinary protein mixture was denatured, reduced and enzymatically digested prior to LC-MS/MS analysis using a hybrid-quadrupole time-of-flight mass spectrometer (Q-TOF) to perform data-dependent ion selection and fragmentation. To fragment as many peptides as possible, the mixture was analyzed four separate times, with the mass spectrometer selecting ions for fragmentation from a subset of the entire mass range for each run. This approach requires only an autosampler on the HPLC for automation (i.e, unattended operation). Across these four analyses, 1.450 peptide MS/MS spectra were matched to 751 sequences to identify 124 gene products (proteins and translations of expressed sequence tags). Interestingly, the experimental time for these analyses was less than that required to run a single two-dimensional gel.

Amino Acid Sequence↗
PubMed2006

Effect of piperazine (diethylenediamine) on the moulting, proteome expression and pyrophosphatase activity of Ascaris suum lung-stage larvae.

Piperazine (diethylenediamine) is an anthelmintic widely used against animal and bird ascariasis. In this study, we show that treatment with piperazine blocks Ascaris suum larval moulting and development processes and affects larval proteome expression profiles. A. suum lung-stage L3 (LL3) obtained from an infected rabbit's lungs were cultured in RPMI medium in the presence of increasing concentrations of piperazine sulfate (Pzes). Our results showed that Pzes potently inhibited moulting of A. suum LL3 in a dose-dependent manner and that moulting was completely blocked (100%) at 50mM concentrations. We then examined the changes in A. suum LL3 proteome expression patterns following Pzes exposure using two-dimensional (2D) electrophoresis. Pzes exposure inhibited expression of at least 16 major protein spots in unmoulted LL3 out of more than 200 visible protein spots resolved on 2D gels prepared from moulted larvae (i.e., lung-stage L4). Pzes exposure also inhibited expression of 13 immunogenic protein spots in unmoulted LL3. More importantly, Pzes exposure inhibited activity of a moulting-specific enzyme, inorganic pyrophosphatase of A. suum (AsPPase), by 26%. Expression of native AsPPase was also reduced following Pzes exposure as detected by immunoblotting and immunofluorescent staining. Transmission electron microscopy showed that Pzes interfered with growth and ecdysis of the cuticle and caused damage to gut tissues of the larvae. Our results suggest that A. suum LL3 may become a suitable model to screening new-class anthelmintics with antimoulting functions and that A. suum LL3-Pzes may serve as a useful tool for identification of moulting-specific potential proteins in Ascaris roundworms.

Animals↗
PubMed2005

SELDI-MS-based expression profiling of ductal invasive and lobular invasive human breast carcinomas.

Expression profiling using proteomic techniques has a great potential to identify new biomarkers that might help to better diagnose and treat diseases such as breast cancer, which is one of the leading causes of cancer death in women. Surface-enhanced laser desorption ionization mass spectrometry (SELDI-MS) combines chromatographic separation of peptides and proteins with mass spectrometry and is a fast, user-friendly tool to analyze protein and peptide profiles. SELDI-MS was employed for a comparative analysis of lobular invasive versus ductal invasive breast tumors to find differentially expressed proteins and peptides, and to validate this technique for biomarker identification using complex samples such as tissue. After optimization of sample preparation using HMEC and MCF-7 cell lines, 20 breast tumors were analyzed, and about 550 mass signals corresponding to an estimated 140 native peptides and proteins were detected in each tumor. Only 14% of the mass signals were present in more than six tumors of one subgroup or in more than 12 tumors of both groups showing a great overall heterogeneity of the peptide and protein profiles obtained. Peptide mass signals specific for each of the analyzed groups were identified. In addition, we detected peptides from laser-microdissected ductal invasive and intraductal tumor parts corresponding to peptides present in whole tumors. The low amount of identified peptides and proteins and the observed heterogeneity suggest that SELDI-MS is not well suited for biomarker identification of and profiling experiments on complex samples such as tumor tissue.

Breast Neoplasms↗
PubMed2005

[Pharmacogenetics and antiplatelet drugs].

PURPOSE: The observation of inherited drug response variability gave rise to the field of pharmacogenetics. Pharmacogenetic research on drug targets, particularly platelet enzymes and receptors, is more recent and is becoming an emerging field. CURRENT KNOWLEDGE AND KEY POINTS: In the Framingham study, the heritability of platelet aggregation response ranges from 44 to 62%, depending on the agonists used. The gene coding for GPIIIa, a sub-unit of the fibrinogen receptor GPIIbIIIa, is one of the most extensively studied gene in relation with aggregation tests and antiplatelet drugs. The GPIIIa PLA1/PLA2 polymorphism has been associated with clopidogrel and orbofiban platelet response. However, data are more controversial concerning the association with aspirin response. Recently, Cox-1 and GPIa (part of the GPIaIIa collagen receptor) genetic variations have also been pointed out as possible candidates to explain part of the variability of the response to antiplatelet agents. Finally, the H1/H2 polymorphism of the platelet ADP receptor P2Y12 gene has been associated with ADP-induced platelet aggregation response and peripheral arterial disease. This polymorphism may modulate the effect of P2Y12 antagonists like clopidogrel and its clinical implication is currently under study. FUTURE PROSPECTS AND PROJECTS: Gene-expression profiling and proteomics may allow the identification of new candidate genes whose variations may be associated with the heritability of platelet aggregation response. In the next future, phenotypic or genotypic studies could be available to tailor the prescription of antiplatelet drugs.

Gene Expression Profiling↗