ABSTRACT
Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) has been shown to be an alternative method for identification of bacteria via their protein profile spectra, being able to identify bacteria at the genus, species and even at subspecies level. With the aim of large-scale identification of pathogens causing mastitis by this platform, a total of 305 isolates of bacteria identified from cows with subclinical mastitis were analyzed by conventional microbiological culture (MC) as well as by MALDI-TOF MS coupled with Biotyper data processing. Approximately 89% of the identifications performed by MALDI-TOF MS were consistent with results obtained by MC. From the remaining isolates (11%), 6.3% of isolates were classified as misidentified (discordance for both genus and species level), and 4.7% showed identification agreement at the genus level but not at the species level, being classified as unidentified at species level. The disagreement results were mostly associated with identification of Streptococcus and Enterococcus species probably due to the narrow phenotypic similarity between these two genera. These disagreement results suggest that biochemical assays might be prone to identification errors and, MALDI-TOF MS therefore may be an alternative to overcome incorrect species-specific identification. Standard microbiological methods for bovine mastitis diagnosis are time consuming, laborious and prone to errors for some bacteria genera. In our study, we showed that MALDI-TOF MS coupled with Biotyper may be an alternative method for large-scale identification of bacteria isolated from milk samples compared to classical microbiological routine protocols.(AU)
A espectrometria de massas (MALDI-TOF MS) tem mostrado ser um método alternativo para a identificação de bactérias, sendo capaz de identificar as bactérias causadoras de mastite em gênero, espécie ou até mesmo subespécie. Com o objetivo de identificar os patógenos causadores de mastite em grande-escala por esta plataforma, um total de 305 isolados bacterianos oriundos de vacas com mastite subclínica foram analisados pela cultura microbiológica convencional (CM) e pela MALDI-TOF MS acoplada ao software Biotyper. Aproximadamente 89% das identificações realizadas pela MALDI-TOF MS foram consistentes com os resultados obtidos pela CM. Do restante de isolados bacterianos (11%), 6,3% foram classificados como identificação errônea (discordância de gênero e espécie), e 4,7% apresentaram concordância de gênero, mas discordância da espécie. Os resultados que apresentaram divergência estavam mais associados com a identificação das espécies de Streptococcus spp. e Enterococcus spp. devido à similaridade fenotípica entre os dois gêneros. Estes resultados divergentes sugerem que os ensaios bioquímicos podem ser propensos a erros de identificação, por isso a MALDI-TOF MS pode ser considerada um método alternativo para superar os erros de identificação da CM. A cultura microbiológica padrão e os ensaios bioquímicos utilizados na identificação de agentes causadores de mastite são demorados, trabalhosos e propensos a erros quando utilizados na identificação em nível de espécie. No presente estudo, demonstramos que a MALDI-TOF MS acoplada ao software Biotyper pode ser considerada um método alternativo de identificação de bactérias causadoras de mastite em grande-escala quando comparado com a cultura microbiológica convencional.(AU)
Subject(s)
Animals , Cattle , Spectrum Analysis/statistics & numerical data , Mastitis/diagnosis , Mastitis/veterinaryABSTRACT
To explore the application of protein fingerprint technique and differential diagnosis in bacteriological negative pulmonary tuberculosis and pneumonia ,60 patients with bacteriological negative pulmonary tuberculosis ,60 patients with pneumonia ,and 60 healthy volunteers were selected from known clinical cases .Surface strengthening laser desorption ioniza-tion time of flight mass spectrometry (SELDI ToF Ms) and protein chip technology were applied to detect serum proteins ,and analyze their protein peaks by Ciphergen protein chip 3 .1 .1 software .Comparison of the serum protein fingerprinting data from the pool of 180 patients and healthy volunteers showed significant difference in 5 protein peaks (1 028 .49 ,4 796 .56 ,7 564 .77 , 8 048 .02 ,and 11 526 .75 m/z) identified between pulmonary tuberculosis and pneumonia (P<0 .01) .The total effective rate of the 5 protein peaks as a diagnosis model for differential diagnosis of bacteriological negative pulmonary tuberculosis and pneumonia was 84 .2% (101/120) ,the specificity was 82 .5% (52/63) ,the sensitivity was 85 .9% (49/57) ,the positive pre-dictive value was 86 .7% (52/60) ,and the negative predictive value was 81 .7% (49/60) .The total effective rate of the diagno-sis model for differential diagnosis of bacteriological negative pulmonary tuberculosis ,pneumonia and healthy volunteers was 89 .4% (161/180) .The specificity was 100% (60/60) ,the sensitivity was 84 .2% (101/120) ,the positive predictive value was 100% (101/101) ,and the negative predictive value was 75 .9% (60/79) .Protein fingerprinting technology is advanta-geous of being a simple method ,quick detection ,and requires less amount of sample .It is an effective means to screening the tuberculosis specific markers .We found the good diagnosis model through the detection of serum protein by protein fingerprint-ing technology .
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Objective To screen and build diagnostic model of Uygur's renal cancer in Xinjiang by surface-enhanced laser desorption/ionization time of flight mass spectrometry (SELDI-TOF-MS).Methods SELDI-TOF-MS and CM10 protein chip were used to detect the serum protein patterns of 45 cases of Uygur with renal cancer and 45 normal controls of Uygur.The data was analyzed and the diagnostic model was established by using ZUCI-protein chip data analyze system software package.The data of spectra were analyzed by support vector machine (SVM) to establish a diagnostic model which was evaluated and validated by leave one cross validation.Results Nine protein markers were identified with the relative molecular weights of 4296,4305,5914,5935,6116,6887,8085,8142,8573.The differences of these protein markers between renal cancer patients and controls were statistically significant (P ＜ 0.05).The detective model could differentiate renal cancer from healthy controls with the sensitivity of 100％ (45/45),and specificity of 91％ (41/45).The sensitivity and specificity of double blind confirmation procedure were 93％ (28/30) and 85％ (17/20),respectively.Conclusion The predictive models of Uygur's renal cancer in Xinjiang established by the differences of serum protein fingerprint could be a highly specific and sensitive diagnostic tool for renal cell carcinoma.
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Objective To establish protein fingerprinting identification model of Pseudomonas aeruginosa (P. aeruginosa) and to lay a foundation for rapid identification of P. aeruginosa by proteinchip golden array. Methods Sixty-four P. aeruginosa and one hundred and ninety-nine control bacteria identified in our laboratory were collected and divided into training and testing group. Surface enhanced laser desorption ionization time of flight mass spectrometry (SELDI-TOF-MS) and proteinchip golden array were used to detect the protein profiling of the bacteria. Data were automatically collected by Ciphergen Proteinchip Software and protein markers of P. aeruginosa were screened by BioMarker Wizard Software. Classification tree model was developed and validated by BioMarker Patterns Software. The model was blindly tested with twenty-nine P. aeruginosa and sixty-four control bacteria. Results Eighty protein peaks were detected between 3000 and 20 000, among which fifty-eight ones showed significantly difference between P. aeruginosa and the control bacteria (P＜0.01). By BioMarker Patterns Software, one protein peak ( M/Z at 14 045.2) was chosen to develop a classification tree model. The results exhibited with sensitivity of 96. 55% and specificity of 100%. Conclusion Proteinchip golden array has the potential for rapid identification of P. aeruginosa.
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Two-dimensional gel electrophoresis (2DE) is an important tool for investigating the complexity of snake venom proteomes. Apart from applications based on whole proteome analysis, we suggest that 2DE can be used as an assay to guide the progress of protein purification. The aim of this study was to prove the feasibility of this concept by using it to purify rhodocetin from Calloselasma rhodostoma venom. Rhodocetin (α subunit) spot on the 2DE profile of C. rhodostoma venom was first identified and confirmed by mass spectrometry, with a molecular mass of 16 kDa and calculated pI of 5.16. Rhodocetin was subsequently purified by successive anion-exchange and gel filtration chromatography. Every peak from both chromatography profiles was collected and tested on 2DE. The presence of rhodocetin (α subunit) spot in the 2DE profile of the peak DP2 indicated the presence of the protein. The purified compound was used to spike the crude venom. A spiked spot with a 1.6-fold increase in intensity was observed and its position matched to that of rhodocetin (α subunit) on the 2DE profile. Together, these spots confirmed the identity of the purified compound as rhodocetin. Hence, our results have demonstrated the effectiveness of the concept we now term 2DE-guided purification.(AU)
Subject(s)
Animals , Snake Venoms/isolation & purification , Electrophoresis, Gel, Two-Dimensional , Chromatography, Gel , Proteome/isolation & purificationABSTRACT
Objective To analyze the characteristic of serum proteins in non-small cell lung cancer (NSCLC) patients, establish serum markers pattern for the diagnosis of NSCLC. Methods Surface enhanced laser desorption ionization time of flight mass spectormetry ( SELDI-TOF-MS) technology was used to analyze serum samples. Bio-marker Pattern Software (BPS) was used to detect the protein peaks. Results Sixteen significantly different pro-tein peaks were found in serum samples in NSCLC patients and healthy controls. Eight up-regulated protein peaks and eight down-regulated protein peaks ( P < 0. 001 ) were identified in serum samples of NSCLC patients. Three up-regulated protein peaks(P <0. 05) were identified in serum samples of patients of NSCLC with smoking history. Two up-regulated protein peaks(P <0. 01) were identified in serum samples of patients of squamous carcinoma comparing with adenocarcinoma. No significantly different protein peak was found in serum samples of NSCLC patients at different clinical stages . Conclusion SELDI - TOF - MS technology can identify different protein peaks and so function as a diagnostic tool with high sensitivity and specificity.
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ObjectiveTo study serum proteomic fingerprints of colorectal cancer during onset and progression and to screen tumor markers related to prognosis.Methods Serum from colorectal cancer patients, non-cancer patients, and healthy control were profiled using WCX ProteinChip or magnetic beads and analyzed by mass spectrometry. Results Seven protein peaks were found related to colorectal cancer. Several peaks were closely related to lymph node metastasis, distal organ metastasis and decreased after surgery. The diagnostic model composed of 3398.3、5477.1、8453.9 u can detect CEA negative colorectal cancer in 100%. Conclusion Protein fingerprinting technology (PFT) in conjunction with bioinformatics can significantly identify novel biomarkers in the serum of colorectal cancer patients with potential values for prognostic evaluation, detection of CEA negative colorectal cancer and changing its progression.
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Protein fingerprinting technology(PFT) is a novel technology for laboratory diagnosis developed in recent five years.It has advantages of simple operation,testing quickly,high sensitivity and specificity.It is a revolutional progress for laboratory diagnosis.The application of PFT in medical field is mainly for the detection of diseases.The sensitivity and specificity in cancer detection are about 80%.Immunomic mass spectrometry(IMS) is a novel technology using the combined group antibodies for capture multi biomarkers and applying mass spectrometry to precisely analyze the modification or isoforms of the biomarker in single platform,whereas traditional assay could not be able to identify the variation of biomarkers.PFT and IMS have significantly influenced in cancer early detection,especially to evaluate cancers which did not express traditional tumor markers like AFP,CEA,etc.PFT and IMS have characteristics of early detection in the molecular and gene level.PFT and IMS are diagnostic technologies with bright future and potential applications.
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Objective To study the influence of sampling,handling,shipping and storage on low-molecular-weight serum proteome profiling.Methods Serum samples instantly separated and aliquoted,some stored at-80 ℃ for up to 6 months,others stored at 4 ℃ or room temperature(25 ℃) for 2 to 72 hrs.The variations of protein profiling under these conditions on WCX magnetic beads were studied.Profiling influenced by hemolysis,multi freeze-thaw cycles,storage conditions.Results Different handling procedures and storage conditions have different effects on serum profiling.Serum stored at-80 ℃ up to 6 months,stored at 4 ℃ or 25 ℃ for 2 h or one freeze-thaw cycle,had little effects on serum proteomic analysis.If serum diluted into 9 mol/L urea buffer at room temperature,the result is stable for 24 hours.Statistics analysis shows that 35.9% peaks have significant changes(P
ABSTRACT
Objective To analyze the characteristic of serum proteins in non-small cell lung cancer (NSCLC) patients,establish serum markers pattern for the diagnosis of NSCLC. Methods Surface enhanced laser desorption ionization time of flight mass spectormetry(SELDI-TOF-MS) technology was used to analyze serum samples. Biomarker Pattern Software (BPS) was used to detect the protein peaks. Results Sixteen significantly different protein peaks were found in serum samples in NSCLC patients and healthy controls. Eight up-regulated protein peaks and eight down-regulated protein peaks (P