923 resultados para biomarkers, protein, creatinine, osmolarity, urine, proteinuria, proteomics, hematuria


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Subsistence farmers are exposed to a range of mycotoxins. This study applied novel urinary multi-mycotoxin LC-MS/MS methods to determine multiple exposure biomarkers in the high oesophageal cancer region, Transkei, South Africa. Fifty-three female participants donated part of their maize-based evening meal and first void morning urine, which was analysed both with sample clean-up (single and multi-biomarker) and by a 'dilute-and-shoot' multi-biomarker method. Results were corrected for recovery with LOD for not detected. A single biomarker method detected fumonisin B1 (FB1) (87% incidence; mean±standard deviation 0.342±0.466 ng/mg creatinine) and deoxynivalenol (100%; mean 20.4±49.4 ng/mg creatinine) after hydrolysis with β-glucuronidase. The multi-biomarker 'dilute-and-shoot' method indicated deoxynivalenol-15-glucuronide was predominantly present. A multi-biomarker method with β-glucuronidase and immunoaffinity clean-up determined zearalenone (100%; 0.529±1.60 ng/mg creatinine), FB1 (96%; 1.52±2.17 ng/mg creatinine), α-zearalenol (92%; 0.614±1.91 ng/mg creatinine), deoxynivalenol (87%; 11.3±27.1 ng/mg creatinine), β-zearalenol (75%; 0.702±2.95 ng/mg creatinine) and ochratoxin A (98%; 0.041±0.086 ng/mg creatinine). These demonstrate the value of multi-biomarker methods in measuring exposures in populations exposed to multiple mycotoxins. This is the first finding of urinary deoxynivalenol, zearalenone, their conjugates, ochratoxin A and zearalenols in Transkei.

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Intake of heterocyclic amines (HCAs, carcinogens produced during cooking of meat/fish, the most abundant being PhIP, DiMeIQx and MeIQx) is influenced by many factors including type/thickness of meat and cooking method/temperature/duration. Thus, assessment of HCA dietary exposure is difficult. Protein adducts of HCAs have been proposed as potential medium-term biomarkers of exposure, e.g. PhIP adducted to serum albumin or haemoglobin. However, evidence is still lacking that HCA adducts are viable biomarkers in humans consuming normal diets. The FoodCAP project, supported by World Cancer Research Fund, developed a highly sensitive mass spectrometric method for hydrolysis, extraction and detection of acid-labile HCAs in blood and assessed their validity as biomarkers of exposure. Multiple acid/alkaline hydrolysis conditions were assessed, followed by liquid-liquid extraction, clean-up by cation-exchange SPE and quantification by UPLC-ESI-MS/ MS. Blood was analysed from volunteers who completed food diaries to estimate HCA intake based on the US National Cancer Institute’s CHARRED database. Standard HCAs were recovered quantitatively from fortified blood. In addition, PhIP/MeIQx adducts bound to albumin and haemoglobin prepared in vitro using a human liver microsome system were also detectable in blood fortified at low ppt concentrations. However, except for one sample (5pg/ml PhIP), acid-labile PhIP, 7,8-DiMeIQx, 4,8-DiMeIQx and MeIQx were not observed above the 2pg/ml limit of detection in plasma (n=35), or in serum, whole blood or purified albumin, even in volunteers with high meat consumption (nominal HCA intake >2µg/day). It is concluded that HCA blood protein adducts are not viable biomarkers of exposure. Untargeted metabolomic analyses may facilitate discovery of suitable markers.

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AIM: We investigated tissue biomarkers in non-small cell lung cancer (NSCLC) to find indicators of brain metastasis and peritumoral brain edema.

PATIENTS AND METHODS: Fifty-two cases were studied out of which 26 had corresponding brain metastatic tissue. Clinicopathological characteristics of tumors were correlated with biomarkers of cell adhesion, cell growth, cell cycle and apoptosis regulation that were previously immunohistochemically studied but never analyzed separately according to histological subgroups, gender and smoking history.

RESULTS: Increased collagen XVII in adenocarcinoma (ADC) and increased caspase-9, CD44v6, and decreased cellular apoptosis susceptibility protein (CAS) and Ki-67 in squamous cell carcinoma (SCC) correlated significantly with brain metastasis. Increased β-catenin, E-cadherin and decreased caspase-9 expression in primary SCC, and decreased CD44v6 expression in brain metastatic SCC tissues showed a significant correlation with the extent of peritumoral brain edema. Positive correlation between smoking and biomarker expression could be observed in metastatic ADCs with p16 and caspase-8, while-negative correlation was found in SCC without brain metastasis with caspase-3, and in SCC with brain metastasis with p27.

CONCLUSION: Our results highlight the importance of separate analysis of biomarker expression in histological subtypes of NSCLC.

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Heterocyclic aromatic amines (HCA) are carcinogenic mutagens formed during cooking of protein-rich foods. HCA residues adducted to blood proteins have been postulated as biomarkers of HCA exposure. However, the viability of quantifying HCAs following hydrolytic release from adducts in vivo and correlation with dietary intake are unproven. To definitively assess the potential of labile HCA-protein adducts as biomarkers, a highly sensitive UPLC-MS/MS method was validated for four major HCAs: 2-amino-1-methyl-6-phenylimidazo[4,5-b]pyridine (PhIP), 2-amino-3,8-dimethylimidazo[4,5-f]quinoxaline (MeIQx), 2-amino-3,4,8-trimethylimidazo[4,5-f]quinoxaline (4,8-DiMeIQx) and 2-amino-3,7,8-trimethylimidazo[4,5-f]quinoxaline (7,8-DiMeIQx). Limits of detection were 1e5 pg/ml plasma and recoveries 91e115%. Efficacy of hydrolysis was demonstrated by HCA-protein adducts synthesised in vitro. Plasma and 7-day food diaries were collected from 122 fasting adults consuming their habitual diets. Estimated HCA intakes ranged from 0 to 2.5 mg/day. An extensive range of hydrolysis conditions was examined for release of adducted HCAs in plasma. HCA was detected in only one sample (PhIP, 9.7 pg/ml), demonstrating conclusively for the first time that acid-labile HCA adducts do not reflect dietary HCA intake and are present at such low concentrations that they are not feasible biomarkers of exposure. Identification of biomarkers remains important. The search should concentrate on stabilised HCA peptide markers and use of untargeted proteomic and metabolomic approaches.

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Infection is a leading cause of neonatal morbidity and mortality worldwide. Premature neonates are particularly susceptible to infection because of physiologic immaturity, comorbidity, and extraneous medical interventions. Additionally premature infants are at higher risk of progression to sepsis or severe sepsis, adverse outcomes, and antimicrobial toxicity. Currently initial diagnosis is based upon clinical suspicion accompanied by nonspecific clinical signs and is confirmed upon positive microbiologic culture results several days after institution of empiric therapy. There exists a significant need for rapid, objective, in vitro tests for diagnosis of infection in neonates who are experiencing clinical instability. We used immunoassays multiplexed on microarrays to identify differentially expressed serum proteins in clinically infected and non-infected neonates. Immunoassay arrays were effective for measurement of more than 100 cytokines in small volumes of serum available from neonates. Our analyses revealed significant alterations in levels of eight serum proteins in infected neonates that are associated with inflammation, coagulation, and fibrinolysis. Specifically P- and E-selectins, interleukin 2 soluble receptor alpha, interleukin 18, neutrophil elastase, urokinase plasminogen activator and its cognate receptor, and C-reactive protein were observed at statistically significant increased levels. Multivariate classifiers based on combinations of serum analytes exhibited better diagnostic specificity and sensitivity than single analytes. Multiplexed immunoassays of serum cytokines may have clinical utility as an adjunct for rapid diagnosis of infection and differentiation of etiologic agent in neonates with clinical decompensation.

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Currently, there are no biomarkers which can identify patients with an increased risk of developing urothelial cancer as a result of occupational chemical exposure. The aim of this study was to evaluate the relationships between final diagnosis and 22 biomarkers measured in urine, serum and plasma collected from 156 hematuric patients. Fourteen of the 80 patients (17.5%) with urothelial cancer and 13/76 (17.1%) of the controls were deemed to have a history of chemical exposure. We applied Fisher's exact tests to explore associations between chemical exposure and final diagnosis, and tumor stage and grade, where applicable; ANOVA and t-test to compare age across patients with and without chemical exposure; and Zelen's exact test to evaluate relationships across final diagnosis, chemical exposure and smoking. Following pre-selection of biomarkers using Lasso, we identified biomarkers with differential levels across patients with and without chemical exposure using Welch's t-test. Using a one-sided t-test and considering multiple testing using FDR, we observed that TM levels in urine were significantly higher in samples from patients with a history of chemical exposure regardless of their diagnosis as control or urothelial cancer (one-sided t-test, pUC = 0.014 and pCTL = 0.043); in the presence of dipstick protein and when urinary pH levels ≤ 6 (p = 0.003), but not in the presence of dipstick blood (p = 0.115). Urothelial cancer patients with a history of chemical exposure were significantly younger (64.1 years) than those without chemical exposure (70.2 years) (one-sided t-test p-value = 0.012); and their tumors were higher grade (Fisher's exact test; p = 0.008). There was a strong association between a history of chemical exposure and smoking in urothelial cancer patients (Zelen's exact test; p = 0.025). Elevated urinary thrombomodulin levels could have the potential to identify chemical exposure in hematuric patients at high risk of developing urothelial cancer.

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Chapter 1 introduces the scope of the work by identifying the clinically relevant prenatal disorders and presently available diagnostic methods. The methodology followed in this work is presented, along with a brief account of the principles of the analytical and statistical tools employed. A thorough description of the state of the art of metabolomics in prenatal research concludes the chapter, highlighting the merit of this novel strategy to identify robust disease biomarkers. The scarce use of maternal and newborn urine in previous reports enlightens the relevance of this work. Chapter 2 presents a description of all the experimental details involved in the work performed, comprising sampling, sample collection and preparation issues, data acquisition protocols and data analysis procedures. The proton Nuclear Magnetic Resonance (NMR) characterization of maternal urine composition in healthy pregnancies is presented in Chapter 3. The urinary metabolic profile characteristic of each pregnancy trimester was defined and a 21-metabolite signature found descriptive of the metabolic adaptations occurring throughout pregnancy. 8 metabolites were found, for the first time to our knowledge, to vary in connection to pregnancy, while known metabolic effects were confirmed. This chapter includes a study of the effects of non-fasting (used in this work) as a possible confounder. Chapter 4 describes the metabolomic study of 2nd trimester maternal urine for the diagnosis of fetal disorders and prediction of later-developing complications. This was achieved by applying a novel variable selection method developed in the context of this work. It was found that fetal malformations (FM) (and, specifically those of the central nervous system, CNS) and chromosomal disorders (CD) (and, specifically, trisomy 21, T21) are accompanied by changes in energy, amino acids, lipids and nucleotides metabolic pathways, with CD causing a further deregulation in sugars metabolism, urea cycle and/or creatinine biosynthesis. Multivariate analysis models´ validation revealed classification rates (CR) of 84% for FM (87%, CNS) and 85% for CD (94%, T21). For later-diagnosed preterm delivery (PTD), preeclampsia (PE) and intrauterine growth restriction (IUGR), it is found that urinary NMR profiles have early predictive value, with CRs ranging from 84% for PTD (11-20 gestational weeks, g.w., prior to diagnosis), 94% for PE (18-24 g.w. pre-diagnosis) and 94% for IUGR (2-22 g.w. pre-diagnosis). This chapter includes results obtained for an ultraperformance liquid chromatography-mass spectrometry (UPLC-MS) study of pre-PTD samples and correlation with NMR data. One possible marker was detected, although its identification was not possible. Chapter 5 relates to the NMR metabolomic study of gestational diabetes mellitus (GDM), establishing a potentially predictive urinary metabolic profile for GDM, 2-21 g.w. prior to diagnosis (CR 83%). Furthermore, the NMR spectrum was shown to carry information on individual phenotypes, able to predict future insulin treatment requirement (CR 94%). Chapter 6 describes results that demonstrate the impact of delivery mode (CR 88%) and gender (CR 76%) on newborn urinary profile. It was also found that newborn prematurity, respiratory depression, large for gestational age growth and malformations induce relevant metabolic perturbations (CR 82-92%), as well as maternal conditions, namely GDM (CR 82%) and maternal psychiatric disorders (CR 91%). Finally, the main conclusions of this thesis are presented in Chapter 7, highlighting the value of maternal or newborn urine metabolomics for pregnancy monitoring and disease prediction, towards the development of new early and non-invasive diagnostic methods.

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Tese de doutoramento, Farmácia (Toxicologia), Universidade de Lisboa, Faculdade de Farmácia, 2014

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Environmental tobacco smoke (ETS) is recognized as an occupational hazard in the hospitality industry. Although Portuguese legislation banned smoking in most indoor public spaces, it is still allowed in some restaurants/bars, representing a potential risk to the workers’ health, particularly for chronic respiratory diseases. The aims of this work were to characterize biomarkers of early genetic effects and to disclose proteomic signatures associated to occupational exposure to ETS and with potential to predict respiratory diseases development. A detailed lifestyle survey and clinical evaluation (including spirometry) were performed in 81 workers from Lisbon restaurants. ETS exposure was assessed through the level of PM 2.5 in indoor air and the urinary level of cotinine. The plasma samples were immunodepleted and analysed by 2D-SDSPAGE followed by in-gel digestion and LC-MS/MS. DNA lesions and chromosome damage were analysed innlymphocytes and in exfoliated buccal cells from 19 cigarette smokers, 29 involuntary smokers, and 33 non-smokers not exposed to tobacco smoke. Also, the DNA repair capacity was evaluated using an ex vivo challenge comet assay with an alkylating agent (EMS). All workers were considered healthy and recorded normal lung function. Interestingly, following 2D-DIGE-MS (MALDI-TOF/TOF), 61 plasma proteins were found differentially expressed in ETS-exposed subjects, including 38 involved in metabolism, acute-phase respiratory inflammation, and immune or vascular functions. On the other hand, the involuntary smokers showed neither an increased level of DNA/chromosome damage on lymphocytes nor an increased number of micronuclei in buccal cells, when compared to non-exposed non-smokers. Noteworthy, lymphocytes challenge with EMS resulted in a significantly lower level of DNA breaks in ETS-exposed as compared to non-exposed workers (P<0.0001) suggestive of an adaptive response elicited by the previous exposure to low levels of ETS. Overall, changes in proteome may be promising early biomarkers of exposure to ETS. Likewise, alterations of the DNA repair competence observed upon ETS exposure deserves to be further understood. Work supported by Fundação Calouste Gulbenkian, ACSS and FCT/Polyannual Funding Program.

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Hepatocellular Carcinoma (HCC) is a major healthcare problem, representing the third most common cause of cancer-related mortality worldwide. Chronic infections with Hepatitis B virus (HBV) and/or Hepatitis C virus (HCV) are the major risk factors for the development of HCC. The incidence of HBV -associated HCC is in decline as a result of an effective HBV vaccine; however, since an equally effective HCV vaccine has not yet been developed, there are 130 million HCV infected patients worldwide who are at a high-risk for developing HCC. Because reliable parameters and/or tools for the early detection of HCC among high-risk individuals are severely lacking, HCC patients are always diagnosed at a late stage where surgical solutions or effective treatment are not possible. Using urine as a non-invasive sample source, two different approaches (proteomic-based and genomic-based approaches) were pursued with the common goal of discovering potential biomarker candidates for the early detection of HCC among high-risk chronic HCV infected patients. Urine was collected from 106 HCV infected Egyptian patients, 32 of whom had already developed HCC and 74 patients who were diagnosed as HCC-free at the time of initial sample collection. In addition to these patients, urine samples were also collected from 12 healthy control individuals. Total urinary proteins, Trans-renal nucleic acid (Tr-NA) and microRNA (miRNA) were isolated from urine using novel methodologies and silicon carbide-loaded spin columns. In the first, "proteomic-based", approach, liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) was used to identify potential candidates from pooled urine samples. This was followed by validating relative expression levels of proteins present in urine among all the patients using quantitative real time-PCR (qRT-PCR). This approach revealed that significant over-expression of three proteins: DJ-1, Chromatin Assembly Factor-1 (CAF-1) and 11 Moemen Abdalla HCC Biomarkers Heat Shock Protein 60 (HSP60), were characteristic events among HCC-post HCV infected patients. As a single-based HCC biomarker, CAF-1 over-expression identified HCC among HCV infected patients with a specificity of 90%, sensitivity of 66% and with an overall diagnostic accuracy of 78%. Moreover, the CAF-lIHSP60 tandem identified HCC among HCV infected patients with a specificity of 92%, sensitivity of 61 % and with an overall diagnostic accuracy of 77%. In the second genomic-based approach, two different approaches were processed. The first approach was the miRNA-based approach. The expression levels of miRNAs isolated from urine were studied using the Illumina MicroRNA Expression Profiling Assay. This was followed by qRT-PCR-based validation of deregulated expression of identified miRNA candidates among all the patients. This approach shed the light on the deregulated expression of a number of miRNAs, which may have a role in either the development of HCC among HCV infected patients (i.e. miR-640, miR-765, miR-200a, miR-521 and miR-520) or may allow for a better understanding of the viral-host interaction (miR-152, miR-486, miR-219, miR452, miR-425, miR-154 and miR-31). Moreover, the deregulated expression of both miR-618 and miR-650 appeared to be a common event among HCC-post HCV infected patients. The results of the search for putative targets of these two miRNA suggested that miR-618 may be a potent oncogene, as it targets the tumor-suppressor gene Low density lipoprotein-related protein 12 (LPR12), while miR-650 may be a potent tumor-suppressor gene, as it is supposed to downregulate the TNF receptor-associated factor-4 (TRAF4) oncogene. The specificity of miR-618 and miR-650 deregulated expression patterns for the early detection of HCC among HCV infected patients was 68% and 58%, respectively, whereas the sensitivity was 64% and 72%, respectively. When the deregulated expression of both miRNAs was combined as a tandem biomarker, the specificity and the sensitivity were 75% and 58% respectively. 111 Moemen Abdalla HCC Biomarkers In the second, "Trans-renal nucleic acid-based", approach, the urinary apoptotic nucleic acid (uaNA) levels of 70ng/mL or more were found to be a good predictor of HCC among chronic HCV infected patients. The specificity and the sensitivity of this diagnostic approach were 76% and 86%, respectively, with an overall diagnostic value of 81 %. The uaNA levels positively correlated to HCC disease progression as monitored by epigenetic changes of a panel of eight tumor-suppressor genes (TSGs) using methylation-sensitive PCR. Moreover, the pairing of high uaNA levels (:::: 70 ng/mL) and CAF-1 over-expreSSIOn produced a highly specific (l 00%) multiple-based HCC biomarker with an acceptable sensitivity of 64%, and with a diagnostic accuracy of 82%. In comparison to the previous pairing, the uaNA levels (:::: 70 ng/mL) in tandem with HSP60 over-expression was less specific (89%) but highly sensitive (72%), resulting in a diagnostic accuracy of 64%. The specificities of miR-650 deregulated expression in combination with either high uaNA content or HSP 60 over-expression were 82% and 79%, respectively, whereas, the sensitivities of these combinations were 64% and 58%, respectively. The potential biomarkers identified in this study compare favorably with the diagnostic accuracy of the a-fetoprotein levels test, which has a specificity of 75%, sensitivity of 68% and an overall diagnostic accuracy of 70%. Here we present an intriguing study which shows the significance of using urine as a noninvasive sample source for the identification of promising HCC biomarkers. We have also introduced new techniques for the isolation of different urinary macromolecules, especially miRNA, from urine. Furthermore, we strongly recommend the potential biomarkers indentified in this study as focal points of any future research on HCC diagnosis. A larger testing pool will determine if their use is practical for mass population screening. This explorative study identified potential targets that merit further investigation for the development of diagnostically accurate biomarkers isolated from 1-2 mL urine samples that were acquired in a non-invasive manner.

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The primary objective of this research project was to identify prostate cancer (PCa) -specific biomarkers from urine. This was done using a multi-faceted approach that targeted (1) the genome (DNA); (2) the transcriptome (mRNA and miRNA); and (3) the proteome. Toward this end, urine samples were collected from ten healthy individuals, eight men with PCa and twelve men with enlarged, non-cancerous prostates or with Benign Prostatic Hyperplasia (BPH). Urine samples were also collected from the same patients (PCa and BPH) as part of a two-year follow-up. Initially urinary nucleic acids and proteins were assessed both qualitatively and quantitatively for characteristics either unique or common among the groups. Subsequently macromolecules were pooled within each group and assessed for either protein composition via LC-MS/MS or microRNA (miRNA) expression by microarray. A number of potential candidates including miRNAs were identified as being deregulated in either pooled PCa or BPH with respect to the healthy control group. Candidate biomarkers were then assessed among individual samples to validate their utility in diagnosing PCa and/or differentiating PCa from BPH. A number of potential targets including deregulation of miRNAs 1825 and 484, and mRNAs for Fibronectin and Tumor Protein 53 Inducible Nuclear Protein 2 (TP53INP2) appeared to be indicative of PCa. Furthermore, deregulation of miR-498 appeared to be indicative of BPH. The sensitivities and specificities associated with using deregulation in many of these targets to subsequently predict PCa or BPH were also determined. This research project has identified a number of potential targets, detectable in urine, which merit further investigation towards the accurate identification of PCa and its discrimination from BPH. The significance of this work is amplified by the non-invasive nature of the sample source from which these candidates were derived, urine. Many cancer biomarker discovery studies have tended to focus primarily on blood (plasma or serum) and/or tissue samples. This is one of the first PCa biomarker studies to focus exclusively on urine as a sample source.

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Globally, Prostate cancer (PCa) is the most frequently occurring non-cutaneous cancer, and is the second highest cause of cancer mortality in men. Serum prostate specific antigen (PSA) has been the standard in PCa screening since its approval by the American Food & Drug Administration (FDA) in 1994. Currently, PSA is used as an indicator for PCa - patients with a serum PSA level above 4ng/mL will often undergo prostate biopsy to confirm cancer. Unfortunately fewer than similar to 30% of these men will biopsy positive for cancer, meaning that the majority of men undergo invasive biopsy with little benefit. Despite PSA's notoriously poor specificity (33%), there is still a significant lack of credible alternatives. Therefore an ideal biomarker that can specifically detect PCa at an early stage is urgently required. The aim of this study was to investigate the potential of using deregulation of urinary proteins in order to detect Prostate Cancer (PCa) among Benign Prostatic Hyperplasia (BPH). To identify the protein signatures specific for PCa, protein expression profiling of 8 PCa patients, 12 BPH patients and 10 healthy males was carried out using LC-MS/MS. This was followed by validating relative expression levels of proteins present in urine among all the patients using quantitative real time-PCR. This was followed by validating relative expression levels of proteins present in urine among all the patients using quantitative real time-PCR. This approach revealed that significant the down-regulation of Fibronectin and TP53INP2 was a characteristic event among PCa patients. Fibronectin mRNA down-regulation, was identified as offering improved specificity (50%) over PSA, albeit with a slightly lower although still acceptable sensitivity (75%) for detecting PCa. As for TP53INP2 on the other hand, its down-regulation was moderately sensitive (75%), identifying many patients with PCa, but was entirely non-specific (7%), designating many of the benign samples as malignant and being unable to accurately identify more than one negative.

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In recent years, we observed a significant increase of food fraud ranging from false label claims to the use of additives and fillers to increase profitability. Recently in 2013, horse and pig DNA were detected in beef products sold from several retailers. Mass spectrometry has become the workhorse in protein research and the detection of marker proteins could serve for both animal species and tissue authentication. Meat species authenticity will be performed using a well defined proteogenomic annotation, carefully chosen surrogate tryptic peptides and analysis using a hybrid quadrupole-Orbitrap mass spectrometer. Selected mammalian meat samples were homogenized, proteins were extracted and digested with trypsin. The samples were analyzed using a high-resolution mass spectrometer. The chromatography was achieved using a 30 minutes linear gradient along with a BioBasic C8 100 × 1 mm column at a flow rate of 75 µL/min. The mass spectrometer was operated in full-scan high resolution and accurate mass. MS/MS spectra were collected for selected proteotypic peptides. Muscular proteins were methodically analyzed in silico in order to generate tryptic peptide mass lists and theoretical MS/MS spectra. Following a comprehensive bottom-up proteomic analysis, we were able to detect and identify a proteotypic myoglobin tryptic peptide [120-134] for each species with observed m/z below 1.3 ppm compared to theoretical values. Moreover, proteotypic peptides from myosin-1, myosin-2 and -hemoglobin were also identified. This targeted method allowed a comprehensive meat speciation down to 1% (w/w) of undesired product.

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The completion of the Human Genome Project has revealed a multitude of potential avenues for the identification of therapeutic targets. Extensive sequence information enables the identification of novel genes but does not facilitate a thorough understanding of how changes in gene expression control the molecular mechanisms underlying the development and regulation of a cell or the progression of disease. Proteomics encompasses the study of proteins expressed by a population of cells, and evaluates changes in protein expression, post-translational modifications, protein interactions, protein structure and splice variants, all of which are imperative for a complete understanding of protein function within the cell. From the outset, proteomics has been used to compare the protein profiles of cells in healthy and diseased states and as such can be used to identify proteins associated with disease development and progression. These candidate proteins might provide novel targets for new therapeutic agents or aid the development of assays for disease biomarkers. This review provides an overview of the current proteomic techniques available and focuses on their application in the search for novel therapeutic targets for the treatment of disease.