共查询到20条相似文献,搜索用时 15 毫秒
1.
2.
Nicolas Lévêque Jér?me Legoff Catherine Mengelle Séverine Mercier-Delarue Yohan N'guyen Fanny Renois Fabien Tissier Fran?ois Simon Jacques Izopet Laurent Andréoletti 《Journal of clinical microbiology》2014,52(1):212-217
Viruses are the leading cause of central nervous system (CNS) infections, ahead of bacteria, parasites, and fungal agents. A rapid and comprehensive virologic diagnostic testing method is needed to improve the therapeutic management of hospitalized pediatric or adult patients. In this study, we assessed the clinical performance of PCR amplification coupled with electrospray ionization-time of flight mass spectrometry analysis (PCR-MS) for the diagnosis of viral CNS infections. Three hundred twenty-seven cerebrospinal fluid (CSF) samples prospectively tested by routine PCR assays between 2004 and 2012 in two university hospital centers (Toulouse and Reims, France) were retrospectively analyzed by PCR-MS analysis using primers targeted to adenovirus, human herpesviruses 1 to 8 (HHV-1 to -8), polyomaviruses BK and JC, parvovirus B19, and enteroviruses (EV). PCR-MS detected single or multiple virus infections in 190 (83%) of the 229 samples that tested positive by routine PCR analysis and in 10 (10.2%) of the 98 samples that tested negative. The PCR-MS results correlated well with herpes simplex virus 1 (HSV-1), varicella-zoster virus (VZV), and EV detection by routine PCR assays (kappa values [95% confidence intervals], 0.80 [0.69 to 0.92], 0.85 [0.71 to 0.98], and 0.84 [0.78 to 0.90], respectively), whereas a weak correlation was observed with Epstein-Barr virus (EBV) (0.34 [0.10 to 0.58]). Twenty-six coinfections and 16 instances of uncommon neurotropic viruses (HHV-7 [n = 13], parvovirus B19 [n = 2], and adenovirus [n = 1]) were identified by the PCR-MS analysis, whereas only 4 coinfections had been prospectively evidenced using routine PCR assays (P < 0.01). In conclusion, our results demonstrated that PCR-MS analysis is a valuable tool to identify common neurotropic viruses in CSF (with, however, limitations that were identified regarding EBV and EV detection) and may be of major interest in better understanding the clinical impact of multiple or neglected viral neurological infections. 相似文献
3.
Jeong Hwan Shin Raymond Ranken Susan E. Sefers Robert Lovari Criziel D. Quinn Shufang Meng Heather E. Carolan Donna Toleno Haijing Li Jeong Nyeo Lee Charles W. Stratton Christian Massire Yi-Wei Tang 《Journal of clinical microbiology》2013,51(1):136-141
As pulmonary fungal infections continue to increase due to an increasing number of immunocompromised patients, rapid detection and accurate identification of these fungal pathogens are critical. A broad fungal assay was developed by incorporating broad-range multilocus PCR amplification and electrospray ionization/mass spectrometry (PCR/ESI-MS) to detect and identify fungal organisms directly from clinical specimens. The aims of this study were to evaluate the performance of PCR/ESI-MS for detection, identification, and determination of the distribution of fungal organisms in bronchoalveolar lavage (BAL) fluid specimens. The BAL fluid specimens submitted for fungal culture at Vanderbilt University Medical Center between May 2005 and October 2011 were included. Cultures and identification were done using standard procedures. In addition, DNA was extracted from BAL fluid specimens, and fungal DNA amplification/identification were performed by PCR/ESI-MS. The results were compared with those of the standard cultures. A total of 691 nonduplicated BAL fluid specimens with sufficient leftover volume for molecular testing were evaluated using PCR/ESI-MS. Among them, 134 specimens (19.4%) were positive for fungi by both culture and PCR/ESI-MS testing. Of the dual-positive specimens, 125 (93.3%) were positive for Candida and Aspergillus species, with concordances between culture and PCR/ESI-MS results being 84 (67.2%) at the species level and 109 (87.2%) at the genus level. In addition, 243 (35.2%) and 30 (4.3%) specimens were positive only by PCR/ESI-MS or by culture, respectively (odds ratio [OR] = 11.95, 95% confidence interval [CI] = 7.90 to 18.17, P = 0.0000). Codetection of fungal organisms was noted in 23 (3.3%) specimens by PCR/ESI-MS, which was significantly higher than the 4 (0.6%) in which they were noted by culture (OR = 5.91, 95% CI = 1.93 to 20.27, P = 0.0002). Among 53 specimens in which cultures failed because of bacterial overgrowth, at least one fungus was identified in 26 specimens (47.3%) by PCR/ESI-MS. PCR/ESI-MS provides an advanced tool for rapid and sensitive detection, identification, and determination of the distribution of fungal organisms directly from BAL fluid specimens. Moreover, it detected fungal organisms in specimens in which cultures failed because of bacterial overgrowth. The clinical relevance of the significantly higher detection rate of fungal organisms by PCR/ESI-MS merits further investigation. 相似文献
4.
Yu-Tzu Chang Hsuan-Chen Wang Ming-Cheng Wang An-Bang Wu Junne-Ming Sung H. Sunny Sun Ih-Jen Su Wei-Chih Kan Chih-Chiang Chien Jyh-Chang Hwang Hsien-Yi Wang Chin-Chung Tseng Chi-Jung Wu 《Journal of clinical microbiology》2014,52(4):1217-1219
PCR coupled with electrospray ionization mass spectrometry (PCR/ESI-MS) was compared with culture for pathogen detection in peritoneal dialysis (PD)-related peritonitis. Of 21 samples of PD effluent, PCR/ESI-MS identified microorganisms in 18 (86%) samples, including Mycobacterium tuberculosis in 1 culture-negative sample. Of 15 double-positive samples, PCR/ESI-MS and culture reached levels of agreement of 100% (15/15) and 87.5% (7/8) at the genus and species levels, respectively. PCR/ESI-MS can be used for rapid pathogen detection in PD-related peritonitis. 相似文献
5.
Julia Vormbrock Jeanette Liebeton Sophia Wirdeier Axel Meissner Thomas Butz Hans-Joachim Trappe Gunnar Plehn 《International journal of medical sciences》2014,11(8):834-840
Introduction: Although chronic pulmonary hypertension and right ventricular (RV) function carry important functional and prognostic implications in idiopathic dilated cardiomyopathy (IDC), little information on RV muscle mass (RVMM) and its determinants has been published.Methods: Our study comprised thirty-five consecutive patients with IDC, left ventricular (LV) ejection fraction <40% and NYHA class ≥2. Hemodynamic data and parameters on LV and RV geometry were derived from right heart catheterisation and cardiac magnetic resonance imaging.Results: RVMM was normalized to body size using a common linear, body surface area based approach (RVMMI) and by an allometric index (RVMM-AI) incorporating adjustment for age, height and weight. Stepwise multiple regression analysis revealed that pulmonary artery pressure and left ventricular muscle mass were independent predictors of RVMM-AI. The interventricular mass ratio of RV and LV mass (IVRM) was closely related to RVMM (r = 0.79, p < 0.001) and total muscle mass (r = 0.39, p < 0.02). However, there was no significant relationship between LVMM and IVMR (r = 0.17, p = 0.32).Conclusion: Our data suggest that an increase in RV mass in IDC may be explained by two mechanisms: First, as a consequence of the myopathic process itself resulting in a balanced hypertrophy of both ventricles. Second, due to the chamber specific burden of pulmonary artery pressure rise, resulting in unbalanced RV hypertrophy. 相似文献
6.
Cassandra L. Brinkman Paschalis Vergidis James R. Uhl Bobbi S. Pritt Franklin R. Cockerill James M. Steckelberg Larry M. Baddour Joseph J. Maleszewski William D. Edwards Rangarajan Sampath Robin Patel 《Journal of clinical microbiology》2013,51(7):2040-2046
Microbiological diagnosis is pivotal to the appropriate management and treatment of infective endocarditis. We evaluated PCR-electrospray ionization mass spectrometry (PCR/ESI-MS) for bacterial and candidal detection using 83 formalin-fixed paraffin-embedded heart valves from subjects with endocarditis who had positive valve and/or blood cultures, 63 of whom had positive valvular Gram stains. PCR/ESI-MS yielded 55% positivity with concordant microbiology at the genus/species or organism group level (e.g., viridans group streptococci), 11% positivity with discordant microbiology, and 34% with no detection. PCR/ESI-MS detected all antimicrobial resistance encoded by mecA or vanA/B and identified a case of Tropheryma whipplei endocarditis not previously recognized. 相似文献
7.
Detection and Direct Typing of Herpes Simplex Virus in Perianal Ulcers of Patients with AIDS by PCR 下载免费PDF全文
Maria C. do Nascimento Laura M. Sumita Vanda A. U. F. de Souza Cludio S. Pannuti 《Journal of clinical microbiology》1998,36(3):848-849
The presence of herpes simplex virus type 1 (HSV-1) and HSV-2 in perianal ulcerations of 41 AIDS patients was assessed by virus culture and a type-specific PCR-based assay. HSV was isolated from the lesion site in 24 of 41 (58.5%) patients, and HSV DNA was detected by PCR in all 24 (100%) of these specimens. Additionally, PCR was used to detect HSV DNA in 12 of 17 (70.5%) HSV culture-negative samples. Thus, HSV genomic sequences could be demonstrated in 36 of 41 (87.8%) perianal ulcers in this series. Full agreement in HSV typing by either immunodot assay or PCR was seen in 24 samples that were positive by both virus culture and PCR. HSV-2 was demonstrated in 35 of 36 (97.2%) HSV-positive samples. 相似文献
8.
目的:探讨Th17/Treg的变化及其与扩张型心肌病(DCM)发生发展的关系。方法:收集急性病毒性心肌炎(AVMC)患者及DCM患者和健康体检者的外周血,ELISA法检测血清中IL-17及TGF-β1浓度;经PE-CD4、FITC-CD25及FITC-IL-17单抗染色后,双色流式细胞术检测Th17细胞及Treg细胞的比例。结果:AVMC组Th17和IL-17高于DCM组和对照组;DCM组Treg和TGF-β1低于AVMC组与对照组;AVMC组与DCM组Th17/Treg无显著差异,但均高于对照组。结论:Thl7/Treg的升高打破了免疫平衡,促进了AVMC的发病及其向DCM的发展。 相似文献
9.
10.
本文就使用电感耦合等离子体质谱仪同时测定尿液中镍、铬元素含量的方法进行了研究。样品经简单稀释后直接进样,采用动态反应池技术消除离子干扰,并使用内标进行校正。尿液中镍、铬元素的检出限分别为0.06μg/L和0.001μg/L,检测相对标准偏差在1.4%~4.7%间,加标回收率为99.1%~102.4%,同时质控样品值也落入可信参考范围。本方法样品处理简单,测量快速、灵敏、准确,值得临床推广应用。 相似文献
11.
Patricia J. Simner Seanne P. Buckwalter James R. Uhl Nancy L. Wengenack Bobbi S. Pritt 《Journal of clinical microbiology》2013,51(11):3731-3734
Diagnosis of yeast infection is typically accomplished by fungal smear and culture, histopathologic examination, and/or serologic studies. Newer assays based on mass spectrometry may be useful for yeast identification when histologic examination is inconclusive, fungal cultures are not ordered, or cultures fail to yield a causative agent. The purpose of this study was to evaluate the ability of the PLEX-ID broad fungal assay to accurately detect and identify yeasts in formalin-fixed paraffin-embedded (FFPE) tissues. Tissue samples from 78 FFPE specimens with both histopathology and corresponding culture results for a variety of yeasts were tested using the PLEX-ID broad fungal assay. A 40-μm FFPE tissue section from each specimen was digested with proteinase K followed by nucleic acid extraction and PCR using broad-range fungal primers. Yeast DNA in amplified products was identified using electrospray ionization mass spectrometry. Discordant results were resolved by D2 rRNA gene sequencing. PLEX-ID analysis detected yeast DNA in 78.2% (61/78) of the cases, of which 91.8% (56/61) were concordant with culture results. Of the 5 discordant positive results, 4 PLEX-ID results were considered to result from environmental contaminants, while 1 clinically important discrepancy was observed (Blastomyces dermatitidis by culture and Cryptococcus neoformans by PLEX-ID). Sequencing of the discordant sample was unsuccessful. The majority of histopathology results (89.7% [70/78]) correlated with culture results. The PLEX-ID broad fungal assay identifies fungi directly from FFPE tissues and can be a useful adjunct to traditional culture and histopathology tests. 相似文献
12.
Eliete C. Romero Ana E. C. Billerbeck Valria S. Lando Eide D. Camargo Candida C. Souza Paulo H. Yasuda 《Journal of clinical microbiology》1998,36(5):1453-1455
Samples of cerebrospinal fluid from 103 patients with aseptic meningitis were tested by PCR for detection of leptospires, and the results were compared with those of the microscopic agglutination test (MAT) and an enzyme-linked immunosorbent assay for detection of immunoglobulin M (ELISA-IgM). Of these samples, 39.80% were positive by PCR and 8.74 and 3.88% were positive by MAT and ELISA-IgM, respectively. 相似文献
13.
Specific Detection of Fusarium Species in Blood and Tissues by a PCR Technique 总被引:3,自引:0,他引:3 下载免费PDF全文
Francois-Xavier Hue Michel Huerre Marie Ange Rouffault Claude de Bievre 《Journal of clinical microbiology》1999,37(8):2434-2438
Fusarium species are opportunistic nosocomial pathogens that often cause fatal invasive mycoses. We designed a primer pair that amplifies by PCR a fragment of a gene coding for the rRNA of Fusarium species. The DNAs of the main Fusarium species and Neocosmospora vasinfecta but not the DNAs from 11 medically important fungi were amplified by these primers. The lower limit of detection of the PCR system was 10 fg of Fusarium solani DNA by ethidium bromide staining. To test the ability of this PCR system to detect Fusarium DNA in tissues, we developed a mouse model of disseminated fusariosis. Using the PCR, we detected Fusarium DNA in mouse tissues and in spiked human blood. Furthermore, F. solani, Fusarium moniliforme, and Fusarium oxysporum were testing by random amplified polymorphic DNA (RAPD) analysis. The bands produced by RAPD analysis were purified, cloned, and sequenced. The information was used to design primer pairs that selectively amplified one or several Fusarium species. The method developed may be useful for the rapid detection and identification of Fusarium species both from culture and from clinical samples. 相似文献
14.
Dante P. Melendez James R. Uhl Kerryl E. Greenwood-Quaintance Arlen D. Hanssen Rangarajan Sampath Robin Patel 《Journal of clinical microbiology》2014,52(6):2202-2205
PCR coupled with electrospray ionization mass spectrometry applied to synovial fluid specimens had an 81% sensitivity and a 95% specificity for the diagnosis of prosthetic joint infection. 相似文献
15.
Autoimmune mechanisms are likely to participate in the pathogenesis of at least a subgroup of idiopathic dilated cardiomyopathy (IDC), and components of the major histocompatibility complex (MHC) may serve as markers for the propensity to develop immune‐mediated myocardial damage. Human leukocyte antigen (HLA) class II genes, especially HLA‐DQ genes, which are highly polymorphic, play an important role in the activation of immune responses and thus control the predisposition to, or protection from, IDC. This study was conducted to investigate the association of HLA‐DQA1, ‐DQB1 allele polymorphisms with an autoantibody against the myocardial mitochondria ADP/ATP carrier, and to explore susceptibility to idiopathic dilated cardiomyopathy (IDC) among the Han ethnic group in northern China and the immunological mechanisms and hereditary susceptibility to IDC. Polymerase chain reaction sequence‐specific primer (PCR‐SSP) techniques were used to analyze polymorphisms of the second exon of HLA‐DQA1 and ‐DQB1 alleles among 68 unrelated IDC patients, 4 probands of IDC pedigrees, and 100 healthy controls, all of Han nationality and having lived in northern China for a long time. Following echocardiography examination the IDC subjects were stratified according to ejection fraction (EF) values. Those with EF values higher than 50% were placed in subgroup 1, subgroup 2 included the patients with an EF value of 15–35%, and subgroup 3 consisted of those whose EF values were less than 15%. An autoantibody against the myocardial mitochondria ADP/ATP carrier was examined using immunoblot analysis. The frequencies of HLA‐DQA1*0501 and HLA‐DQB1*0303 were 0.3889 and 0.1806 in the IDC group, significantly higher than those of the healthy controls (0.0900 and 0.0364 respectively, both P < 0.05). The OR was 5.20 (95% CI: 3.60–8.50) and 4.85 (95% CI: 2.56–9.39) respectively. Further analysis of the three subgroups showed a higher frequency of HLA‐DQA1*0501 among patients whose EF was less than 15% than those whose EF values were ≥15%. Conversely, the frequencies of HLA‐DQA1*0201 and ‐DQB1*0502, *0504 were significantly lower in the IDC group (0.0139, 0.0139 and 0.0417 respectively) than in the control group (0.2000, 0.0727 and 0.1091 respectively) (P < 0.05). The frequency of the HLA‐DQA1*0501 allele was significantly higher in IDC patients whose autoantibody is positive in contrast with those whose autoantibody is negative (18.57% vs. 5.86%, P < 0.05); the relative risk (RR) was 4.32. The other frequencies of HLA‐DQA1 and ‐DQB1 alleles showed no significant difference in the antibody positive and negative groups of IDC patients. The alleles of HLA‐DQA1*0501 and HLA‐DQB1*0303 were closely associated with poor EF values in the IDC group, and may be involved in susceptibility to the disease. The DQA1*0201 and DQB1*0502, *0504 alleles may confer protection to IDC among individuals of northern Chinese Han nationality. The SER57 residue in the second exon of DQB1*0502 and *0504 may confer resistance to IDC, and defects or substitution of this amino acid residue at position 57 of the DQβ chain may be associated with IDC susceptibility. HLA‐DQ allele polymorphisms may serve as genetic markers for IDC and be involved in the regulation of the immune specific response to auto or exterior anti‐myocardium antibodies. 相似文献
16.
Myrianthi Hadjicharalambous Liya Asner Radomir Chabiniok Eva Sammut James Wong Devis Peressutti Eric Kerfoot Andrew King Jack Lee Reza Razavi Nicolas Smith Gerald Carr-White David Nordsletten 《Annals of biomedical engineering》2017,45(3):605-618
Patient-specific modelling has emerged as a tool for studying heart function, demonstrating the potential to provide non-invasive estimates of tissue passive stiffness. However, reliable use of model-derived stiffness requires sufficient model accuracy and unique estimation of model parameters. In this paper we present personalised models of cardiac mechanics, focusing on improving model accuracy, while ensuring unique parametrisation. The influence of principal model uncertainties on accuracy and parameter identifiability was systematically assessed in a group of patients with dilated cardiomyopathy (\(n=3\)) and healthy volunteers (\(n=5\)). For all cases, we examined three circumferentially symmetric fibre distributions and two epicardial boundary conditions. Our results demonstrated the ability of data-derived boundary conditions to improve model accuracy and highlighted the influence of the assumed fibre distribution on both model fidelity and stiffness estimates. The model personalisation pipeline—based strictly on non-invasive data—produced unique parameter estimates and satisfactory model errors for all cases, supporting the selected model assumptions. The thorough analysis performed enabled the comparison of passive parameters between volunteers and dilated cardiomyopathy patients, illustrating elevated stiffness in diseased hearts. 相似文献
17.
Matthew J. Binnicker Mark J. Espy Cole L. Irish 《Journal of clinical microbiology》2014,52(12):4361-4362
Central nervous system infection due to herpes simplex virus (HSV) is a medical emergency and requires rapid diagnosis and initiation of therapy. In this study, we compared a routine real-time PCR assay for HSV types 1 (HSV-1) and 2 (HSV-2) to a recently FDA-approved direct PCR assay (Simplexa HSV-1/2 Direct; Focus Diagnostics, Cypress, CA) using cerebrospinal fluid samples (n = 100). The Simplexa HSV-1/2 assays demonstrated a combined sensitivity and specificity of 96.2% (50/52) and 97.9% (47/48), respectively. In addition, the Simplexa assay does not require nucleic acid extraction, and the results are available in 60 min. 相似文献
18.
19.
Samuel Yang Padmini Ramachandran Richard Rothman Yu-Hsiang Hsieh Andrew Hardick Helen Won Aleksandar Kecojevic Joany Jackman Charlotte Gaydos 《Journal of clinical microbiology》2009,47(7):2252-2255
A rapid assay for eubacterial species identification is described using high-resolution melt analysis to characterize PCR products. Unique melt profiles generated from multiple hypervariable regions of the 16S rRNA gene for 100 clinically relevant bacterial pathogens, including category A and B biothreat agents and their surrogates, allowed highly specific species identification.Rapid and accurate diagnostic tools are critical for infectious disease surveillance and early diagnosis of disease (8, 12). A simple platform which could deliver broad-based screening and specific pathogen identification would be invaluable for the timely recognition of emerging and biothreat (BT) outbreaks, as well as commonly encountered clinical infections (2, 7, 9, 11, 12).We previously reported a probe-based PCR assay, which utilizes conserved and variable 16S rRNA gene sequences for initial broad-based eubacterial detection and subsequent identification of specific bacterial agents (11). The assay demonstrated high analytical sensitivity but was limited by an inability to differentiate closely related pathogens due to decreased specificity of the TaqMan probe chemistry and high sequence homology within selected hypervariable regions of the 16S rRNA gene. Probe-based amplicon characterization accordingly limits testing to a finite number of anticipated pathogens. Alternative strategies for amplicon analysis, such as sequencing and mass spectrometry, allow broader-scale product characterization but are costly, time-consuming, and lacking in throughput (1, 6). High-resolution melt analysis (HRMA) offers a simple, low-cost, closed-tube approach to amplicon analysis with the capacity for single-nucleotide discrimination and easy integration with PCR analysis (10). We report a unique strategy for the rapid, highly specific identification of BT- related and non-BT-related bacterial pathogens which couples eubacterial PCR with HRMA.Three hypervariable regions (V1, V3, and V6), each flanked by highly conserved sequences within the 16S rRNA gene, were selected for primer design (3). Sequence data for clinically or BT-relevant bacteria were obtained from GenBank and aligned using ClustalW (www.ebi.ac.uk/clustalw/) to determine sequence variability. Primer pairs used to target hypervariable regions were as follows: V1-F (5′-GYGGCGNACGGGTGAGTAA-3′) and V1-R (5′-TTACCCCACCAACTAGC-3′), V3-F (5′-CCAGACTCCTACGGGAGGCAG-3′) and V3-R (5′-CGTATTACCGCGGCTGCTG-3′), and V6-F (5′-TGGAGCATGTGGTTTAATTCGA-3′) and V6-R (5′-AGCTGACGACANCCATGCA-3′).One hundred common, BT-related, and BT-surrogate organisms composed of 58 different bacterial species of American Type Culture Collection (ATCC) strains, clinical isolates, or inactivated or nonpathogenic strains were used for analysis (Table (Table1).1). Ten to 15 colonies of each bacterial organism were inoculated in to 200 μl of molecular-grade water (Roche Molecular Diagnostics, Indianapolis, IN), and DNA was extracted using a Roche MAGNA Pure instrument (Roche Molecular Corporation, Indianapolis, IN). Archived DNA extracted as previously described from 40 archived clinical synovial fluid (14) and cerebral spinal fluid samples collected from patients suspected of having septic arthritis or bacterial meningitis, respectively, were also used for blinded analyses.
Open in a separate windowaClinical isolate.bCoxiella burnetti DNA was obtained from Steven Dumbler, Department of Pathology, School of Medicine, Johns Hopkins University, Baltimore, MD.cInactivated nonpathogenic strain.dNonpathogenic strain obtained from the Centers for Disease Control and Prevention, Fort Collins, CO, via the Walter Reed Army Medical Hospital, Washington, DC.eLVSB, live vaccine strain type.fWild-type strain.gDepigmented and virulence pCD1 negative.hDifference plots generated for each organism were grouped based on curve similarity within each analysis subset (V1, V3, or V6), and a unique letter code was assigned to each group as well as each individual organism with a distinct curve shape.iCombined grouping code letters assigned in each analysis subset.Extracted DNA from each organism or clinical sample was subjected to three PCR analyses, targeting V1, V3, and V6 hypervariable regions, respectively. Every PCR analysis was performed in a 10-μl total volume comprised of 8 μl of PCR master mix and 2 μl of target input. The PCR master mix contained 4 μl of 2× Universal PCR mix (Idaho Technology, Salt Lake City, UT) and LC Green dye (Idaho Technology) for high-resolution melting. A total of 1.0 μl of 1.5-μM forward primer and reverse primer was added to the master mix. Each PCR analysis contained one primer pair. The PCR was performed using a GeneAmp Thermocycler (ABI, Foster City, CA). Cycling conditions were as follows: denaturation at 95°C for 30 s, followed by 45 cycle repeats at 95°C for 30 s and annealing/extension at 60°C/72°C for 60 s, and 1 cycle at 95°C for 30 s and 28°C for 30 s.Each post-PCR sample amplicon was subjected to HRMA on the LightScanner instrument (Idaho Technology). Melting temperatures ranged from 60°C to 95°C. Data acquisition was performed for every 0.1°C increase in temperature. HRMA for each PCR sample was performed in triplicate and analyzed using the LightScanner software version 2.0 (Idaho Technology). The software function “negative filter” was first used to identify negative controls and any failed PCRs. Melt analysis of the positive samples was then subjected to fluorescence normalization and temperature shift to obtain the minimum inter- and intra-run variabilities (LightScanner version 2.0 operator''s manual; Idaho Technology, Salt Lake City, UT). Specifically, normalization minimized the variations in fluorescence magnitude between samples due to differences in starting template or optics, and a temperature shift will overcome the effect of absolute temperature variation from position to position across the plate. Derivative plots were generated to assess the number of melting peaks. Analysis subsets (V1, V3, and V6) were defined by the primer sets used for amplification. Using the melting curves of Staphylococcus aureus as the reference curve, the difference plot for each positive sample was generated for subsequent grouping analysis. “Auto grouping” was performed on the difference plots to group all positive samples with a similar curve shape within the same analysis subset. A unique letter code was manually assigned for each group identified, starting with the letter “a” and progressing alphabetically. A combination of each letter from each of the variable regions was then accumulated to provide a signature code for each organism.Each of the 100 bacterial organisms tested had a melting curve generated from HRMA for each of the analysis subsets (V1, V3, and V6) based on the primer set used. Each derivative plot revealed a single dominant peak, which was absent in the nontemplate control, indicating the presence of a single amplified sequence. The melting curves were demonstrated to be reproducible from run to run despite various target DNA concentrations over a 10,000-fold range (data not shown). Using the melting curve of Staphylococcus aureus as the reference, difference plots of the 100 tested organisms generated were compared within their analysis subset. The S. aureus melting curve was chosen as the reference curve, due mainly to the high sequence homology between various S. aureus strains (n = 8) compared within our target amplified regions. After grouping analysis, each difference plot was assigned a unique code letter and only plots with similar characteristics within the same analysis subset shared the same code letter (Fig. (Fig.1;1; Table Table1).1). Although different species were observed to share similar plots within the same analysis subset, each species was associated with a unique three-letter signature code when all three analysis subsets were included. Even closely related species (e.g., Bacillus anthracis versus Bacillus cereus) with a single-nucleotide difference within some of our target regions could be differentiated (Fig. (Fig.1).1). Identical signature codes were observed among various strains of the same species (Table (Table11).Open in a separate windowFIG. 1.The difference plots of all the category A BT bacterial organisms and their surrogates. A grouping code letter (indicated on the top left corner of each graph) is assigned for each plot based on similarity in curve shape with other organisms under the same analysis subset (V1, V3, or V6).We also performed HRMA on eubacterial PCR products from 40 blinded archived clinical samples, which included synovial fluids and cerebral spinal fluids previously collected from patients suspected of having septic arthritis or bacterial meningitis, respectively. HRMA correctly identified all 20 culture-negative samples as being negative. The signature codes generated from each of the 20 remaining positive samples were compared to our reference database of 58 different bacterial species for identification (Table (Table2).2). The species identified based on their signature codes correctly matched their respective culture organisms in all samples tested.
Open in a separate windowaTwenty blinded culture-negative samples were tested and were identified as negative by HRMA. N. meningitidis, Neisseria meningitidis.In this study, we demonstrate as proof of concept a simple, powerful approach to amplicon analysis for rapid bacterial species identification and differentiation of BT agents from their related surrogates. This approach relies on eubacterial real-time PCR analysis followed by HRMA. Unlike probe-based approaches to amplicon analysis, melt curve analysis can characterize PCR products without a priori knowledge of anticipated organisms. Further work will be required to develop a comprehensive database of signature codes from all common pathogens. Once established, nonmatching code generated from a positive amplification reaction may signify the presence of an uncommon, mutant, or emerging pathogen. This approach offers a simple work flow with a total turnaround time of 2 h (from sample collection to species identification) and obviates the need for laborious post-PCR procedures. Due to the ease of integrating the melt analysis, this approach has the potential to be used as a point-of-care test and may be feasible in resource-deficient clinical settings.Despite the high discriminatory precision of HRMA, we found that amplicons of very different sequences may generate similar melt curves. These findings have been reported previously (4). To resolve “melting groups,” Cheng et al. performed heteroduplex melt analyses between amplicons of unknown and reference bacterial species (4). A potential drawback with this approach is that closely related species with identical sequences within the amplified region may not be readily differentiated. We chose to analyze the melt profiles based on three instead of one of the 16S, hypervariable regions (3, 5). This yielded a unique set of melt plots for every non-BT or BT-relevant bacterial organism tested, with even closely related species able to be discerned (13). As expected, different strains of the same species with identical target sequences shared similar melt profiles. Future studies will determine whether the triple-PCR analyses are more cost-effective when performed in parallel or in a series for routine diagnostic testing and/or surveillance.Potential limitations of using melt analysis for pathogen identification include nucleotide polymorphisms, which may exist between intragenomic copies of the 16S rRNA gene in some bacterial species, as well as polymicrobial infections. The number of peaks in the derivative plot may allow discrimination of single versus multiple infections. Future studies will focus on assay reproducibility and specificity using expanded panels of clinically relevant bacterial species, animal studies with BT agents, and human clinical validation studies of patients with suspected systemic bacterial infections. 相似文献
TABLE 1.
Melting analysis of non-BT-related and BT-related organismsOrganism group | Organism or strain | Grouping code of analysis subseth
| Signature codei | ||
---|---|---|---|---|---|
V1 | V3 | V6 | |||
Non-BT related | Acinetobacter sp. strain ATCC 5459 | a | b | a | aba |
Acinetobacter calcoaceticus | b | d | a | bda | |
Aerococcus viridans | f | h | c | fhc | |
Bacteroides fragilisa | a | a | e | aae | |
Bordetella pertussisa | c | c | f | ccf | |
Bordetella parapertussis | a | c | h | ach | |
Campylobacter jejunia | c | a | e | cae | |
Clostridium difficile | g | f | a | gfa | |
Clostridium perfringens | b | d | d | bdd | |
Corynebacterium sp.a | c | c | e | cce | |
Chlamydia pneumoniaea | g | c | a | gca | |
Chlamydia trachomatisa | f | a | b | fab | |
Citrobacter freundiia | b | c | a | bca | |
Enterobacter aerogenes | c | b | a | cba | |
Enterococcus gallinarum | i | i | h | iih | |
Enterococcus faecium | b | a | e | bae | |
Enterobacter faecalis ATCC 29212 | i | i | a | iia | |
Escherichia coli ATCC 25927 | e | d | c | edc | |
Helicobacter pyloria | g | b | a | gba | |
Haemophilus influenzae ATCC 49247 | b | g | d | bgd | |
Klebsiella pneumoniaea | h | c | a | hca | |
Legionella pneumophila ATCC 33495 | a | a | b | aab | |
Listeria monocytogenes ATCC 7648 | b | e | a | bea | |
Micrococcus sp. strain ATCC 14396 | b | b | b | bbb | |
Moraxella catarrhalis | h | i | d | hid | |
Mycobacterium kansasii | i | c | a | ica | |
Mycobacterium gordonae | d | i | i | dii | |
Mycobacterium fortuitum | a | i | b | aib | |
Mycoplasma pneumoniaea | b | d | g | bdg | |
Mycoplasma hominisa | a | b | e | abe | |
Neisseria meningitis ATCC 6250 | d | f | c | dfc | |
Neisseria gonorrhoeaea | a | c | a | aca | |
Oligella urethralis | b | a | i | bai | |
Pasteurella multocida | b | i | a | bia | |
Pseudomonas aeruginosa ATCC 10145 | b | b | c | bbc | |
Propionibacterium acnes | e | i | e | eie | |
Proteus mirabilisa | b | a | f | baf | |
Proteus vulgarisa | c | a | i | cai | |
Salmonella sp. strain ATCC 31194 | c | e | a | cea | |
Serratia marcescens ATCC 8101 | b | j | c | bjc | |
Staphylococcus aureus ATCC 25923 | c | b | h | cbh | |
Staphylococcus epidermidis ATCC 12228 | a | a | h | aah | |
Staphylococcus lugdunensis | g | i | i | gii | |
Staphylococcus saprophyticus | h | i | h | hih | |
Streptococcus pneumoniae ATCC 49619 | g | d | g | gdg | |
Streptococcus pyogenesa | b | e | b | beb | |
Streptococcus agalactiae ATCC 13813 | b | e | d | bed | |
Treponema palliduma | f | b | e | fbe | |
Viridans group streptococci, ATCC 10556 | c | e | f | cef | |
Category A BT agent, near-neighbor, and/or surrogate | Bacillus anthracisc | c | a | a | caa |
Strain 3001 | c | a | a | caa | |
Bacillus cereusa | a | a | d | aad | |
Strain BC 9634 | a | a | d | aad | |
Strain BC 12480 | a | a | d | aad | |
Strain BC 27877 | a | a | d | aad | |
Strain BC 7064 | a | a | d | aad | |
Strain BC B33 | a | a | d | aad | |
Strain BC 1410-1 | a | a | d | aad | |
Strain BC 1410-2 | a | a | d | aad | |
Strain BC T | a | a | d | aad | |
Strain BC 2599 | a | a | d | aad | |
Strain BC 2464 | a | a | d | aad | |
Strain BC 7687 | a | a | d | aad | |
Strain BC 10329 | a | a | d | aad | |
Strain BC 11143 | a | a | d | aad | |
Strain BC 11145 | a | a | d | aad | |
Strain BC 1414 | a | a | d | aad | |
Strain BC 7089 | a | a | d | aad | |
Strain BC 6464 | a | a | d | aad | |
Strain BC 6474 | a | a | d | aad | |
Strain BC 7004 | a | a | d | aad | |
Strain BC 10987 | a | a | d | aad | |
Strain BC 23674 | a | a | d | aad | |
Strain BC 9189 | a | a | d | aad | |
Strain BC 246 | a | a | d | aad | |
Strain BC 13472 | a | a | d | aad | |
Bacillus subtilis 110 NA | a | a | g | aag | |
Strain SB168 | a | a | g | aag | |
Strain W168 | a | a | g | aag | |
Strain W23 | a | a | g | aag | |
Strain her 148 | a | a | g | aag | |
Strain T6 | a | a | g | aag | |
Strain ATCC 27505 | a | a | g | aag | |
Strain ATCC 15841 | a | a | g | aag | |
Coxiella burnettib | d | b | g | dbg | |
Strain “9 mile” | d | b | g | dbg | |
Francisella philomiragia (GAO1-2810)d | a | g | g | agg | |
Francisella tularensis (LVSB)e | b | h | g | bhg | |
Strain Fran 0001 | b | h | g | bhg | |
Yersinia pseudotuberculosis (PB1/+)f | a | g | c | agc | |
Schutze''s group type B strain/ATCC 6903 | a | g | c | agc | |
Schutze''s group II strain/ATCC 27802 | a | g | c | agc | |
Strain CDC P62 strain/ATCC 29910 | a | g | c | agc | |
Schutze''s group III strain/ATCC 13980 | a | g | c | agc | |
Raffinose-positive strain, ATCC 4284 | a | g | c | agc | |
Strain ATCC 13979 | a | g | c | agc | |
Yersinia enterocolitica, O:9 serotype | a | g | d | agd | |
Strain WA.C | a | g | d | agd | |
Yersinia pestis (P14−)g | a | b | d | abd | |
Strain 1122 | a | b | d | abd |
TABLE 2.
Melting analysis results of 20 blinded culture-positive clinical cerebrospinal and synovial fluids testedaClinical sample tested | Grouping code of analysis subsets
| Signature code | Organism determined by culture | Organism determined by melting analysis | ||
---|---|---|---|---|---|---|
V1 | V3 | V6 | ||||
BTW-C1199 | c | b | h | cbh | S. aureus | S. aureus |
BTW-C1049 | b | e | a | bea | L. monocytogenes | L. monocytogenes |
BTW-C278 | a | a | h | aah | S. epidermidis | S. epidermidis |
BTW-C425 | a | a | h | aah | S. epidermidis | S. epidermidis |
BTW-C1616 | b | g | d | bgd | H. influenzae | H. influenzae |
BTW-C1617 | g | d | g | gdg | S. pneumoniae | S. pneumoniae |
BTW-C1619 | g | d | g | gdg | S. pneumoniae | S. pneumoniae |
BTW-C1620 | g | d | g | gdg | S. pneumoniae | S. pneumoniae |
BTW-C1621 | b | g | d | bgd | H. influenzae | H. influenzae |
BTW-C1622 | d | f | c | dfc | N. meningitidis | N. meningitidis |
BTW-C1623 | d | f | c | dfc | N. meningitidis | N. meningitidis |
BTW-C1624 | b | g | d | bgd | H. influenzae | H. influenzae |
BTW-C1625 | b | g | d | bgd | H. influenzae | H. influenzae |
BTW-C1626 | d | f | c | dfc | N. meningitidis | N. meningitidis |
BTW-J0079 | a | a | h | aah | S. epidermidis | S. epidermidis |
BTW-J0098 | a | a | h | aah | S. epidermidis | S. epidermidis |
BTW-J0102 | b | e | d | bed | S. agalactiae | S. agalactiae |
BTW-J0030 | c | e | f | cef | Viridans group streptococci | Viridans group streptococci |
BTW-J0031 | c | e | f | cef | Viridans group streptococci | Viridans group streptococci |
BAY-157 | b | e | d | bed | S. agalactiae | S. agalactiae |
20.
Inflammatory DCM (iDCM) may be related to autoimmune processes. An immunoadsorption (IA) has been reported to improve cardiac hemodynamics. The benefit of IA is probably related to the removal of autoantibodies. A recent study suggests additional effects of IA on the T cell–mediated immune reactions, especially on regulatory T cells (Tregs). In this prospective study, the correlation between the level of Tregs and improvement of myocardial contractility in response to IA in patients with iDCM was investigated. Patients (n = 18) with iDCM, reduced left ventricular (LV) ejection fraction (<35%), were enrolled for IA. Before and 6 months after IA, LV systolic function was assessed by echocardiography, and blood levels of Tregs were quantified by FACS analysis. Patients (n = 12) with chronic ischaemic heart failure and comparable reduced LV‐EF served as controls. IA improved LV‐EF in 12 of 18 patients at 6‐month follow‐up. These patients were classified as ‘IA responder’. In 6 patients, LV‐EF remained unchanged. At baseline, IA responder and non‐responder subgroups showed similar values for C‐reactive protein, white blood cells, lymphocytes and T helper cells, but they differ for the number of circulating Tregs (responder: 2.32 ± 1.38% versus non‐responder: 4.86 ± 0.28%; P < 0.01). Tregs increased significantly in the IA responders, but remained unchanged in the IA non‐responders. In patients with ischaemic cardiomyopathy, none of these values changed over time. A low level of Tregs in patients with chronic iDCM may characterize a subset of patients who do best respond to IA therapy. 相似文献