Dataset Information

Etiologic diagnosis of lower respiratory tract bacterial infections using sputum samples and quantitative loop-mediated isothermal amplification.

ABSTRACT: Etiologic diagnoses of lower respiratory tract infections (LRTI) have been relying primarily on bacterial cultures that often fail to return useful results in time. Although DNA-based assays are more sensitive than bacterial cultures in detecting pathogens, the molecular results are often inconsistent and challenged by doubts on false positives, such as those due to system- and environment-derived contaminations. Here we report a nationwide cohort study on 2986 suspected LRTI patients across P. R. China. We compared the performance of a DNA-based assay qLAMP (quantitative Loop-mediated isothermal AMPlification) with that of standard bacterial cultures in detecting a panel of eight common respiratory bacterial pathogens from sputum samples. Our qLAMP assay detects the panel of pathogens in 1047(69.28%) patients from 1533 qualified patients at the end. We found that the bacterial titer quantified based on qLAMP is a predictor of probability that the bacterium in the sample can be detected in culture assay. The relatedness of the two assays fits a logistic regression curve. We used a piecewise linear function to define breakpoints where latent pathogen abruptly change its competitive relationship with others in the panel. These breakpoints, where pathogens start to propagate abnormally, are used as cutoffs to eliminate the influence of contaminations from normal flora. With help of the cutoffs derived from statistical analysis, we are able to identify causative pathogens in 750 (48.92%) patients from qualified patients. In conclusion, qLAMP is a reliable method in quantifying bacterial titer. Despite the fact that there are always latent bacteria contaminated in sputum samples, we can identify causative pathogens based on cutoffs derived from statistical analysis of competitive relationship.ClinicalTrials.gov NCT00567827.

SUBMITTER: Kang Y

PROVIDER: S-EPMC3375278 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Etiologic diagnosis of lower respiratory tract bacterial infections using sputum samples and quantitative loop-mediated isothermal amplification.

Kang Yu Y Deng Rui R Wang Can C Deng Tao T Peng Peichao P Cheng Xiaoxing X Wang Guoqing G Qian Minping M Gao Huafang H Han Bei B Chen Yusheng Y Hu Yinghui Y Geng Rong R Hu Chengping C Zhang Wei W Yang Jingping J Wan Huanying H Yu Qin Q Wei Liping L Li Jiashu J Tian Guizhen G Wang Qiuyue Q Hu Ke K Wang Siqin S Wang Ruiqin R Du Juan J He Bei B Ma Jianjun J Zhong Xiaoning X Mu Lan L Cai Shaoxi S Zhu Xiangdong X Xing Wanli W Yu Jun J Deng Minghua M Gao Zhancheng Z

PloS one 20120614 6

<h4>Unlabelled</h4>Etiologic diagnoses of lower respiratory tract infections (LRTI) have been relying primarily on bacterial cultures that often fail to return useful results in time. Although DNA-based assays are more sensitive than bacterial cultures in detecting pathogens, the molecular results are often inconsistent and challenged by doubts on false positives, such as those due to system- and environment-derived contaminations. Here we report a nationwide cohort study on 2986 suspected LRTI ...[more]

PMID: 22719933

Similar Datasets

Project description:BackgroundRespiratory infections such as influenza account for significant global mortality each year. Generating lipid profiles is a novel and emerging research approach that may provide new insights regarding the development and progression of priority respiratory infections. We hypothesized that select clusters of lipids in human sputum would be associated with specific viral infections (Influenza (H1N1, H3N2) or Rhinovirus).MethodsLipid identification and semi-quantitation was determined with liquid chromatography and high-resolution mass spectrometry in induced sputum from individuals with confirmed respiratory infections (influenza (H1N1, H3N2) or rhinovirus). Clusters of lipid species and associations between lipid profiles and the type of respiratory viral agent was determined using Bayesian profile regression and multinomial logistic regression.ResultsMore than 600 lipid compounds were identified across the sputum samples with the most abundant lipid classes identified as triglycerides (TG), phosphatidylethanolamines (PE), phosphatidylcholines (PC), Sphingomyelins (SM), ether-PC, and ether-PE. A total of 12 lipid species were significantly different when stratified by infection type and included acylcarnitine (AcCar) (10:1, 16:1, 18:2), diacylglycerols (DG) (16:0_18:0, 18:0_18:0), Lysophosphatidylcholine (LPC) (12:0, 20:5), PE (18:0_18:0), and TG (14:1_16:0_18:2, 15:0_17:0_19:0, 16:0_17:0_18:0, 19:0_19:0_19:0). Cluster analysis yielded three clusters of lipid profiles that were driven by just 10 lipid species (TGs and DGs). Cluster 1 had the highest levels of each lipid species and the highest prevalence of influenza A H3 infection (56%, n = 5) whereas cluster 3 had lower levels of each lipid species and the highest prevalence of rhinovirus (60%; n = 6). Using cluster 3 as the reference group, the crude odds of influenza A H3 infection compared to rhinovirus in cluster 1 was significantly (p = 0.047) higher (OR = 15.00 [95% CI: 1.03, 218.29]). After adjustment for confounders (smoking status and pulmonary comorbidities), the odds ratio (OR) became only marginally significant (p = 0.099), but the magnitude of the effect estimate was similar (OR = 16.00 [0.59, 433.03]).ConclusionsIn this study, human sputum lipid profiles were shown to be associated with distinct types of viral infection. Better understanding the relationship between respiratory infections of global importance and lipids contributes to advancing knowledge of pathogenesis of infections including identifying populations with increased susceptibility and developing effective therapeutics and biomarkers of health status.

Project description:BackgroundFemale reproductive tract infection (RTI) is the common source of varied diseases, especially as an important risk factor for pregnancy outcomes, therefore the rapid, accurate and simultaneous detection of multiple pathogens is in urgent need for assisting the diagnosis and treatment of RTI in pregnant women. Streptococcus agalactiae (S. agalactiae), Enterococcus faecalis (E. faecalis), Gardnerella vaginalis (G. vaginalis), Candida albicans (C. albicans) and Chlamydia trachomatis (C. trachomatis) are five main pathogens in lower genital tract with high risk, serious consequences and clinical demands. The combination of loop-mediated isothermal amplification (LAMP) and microfluidic technology was used to develop the LAMP-microfluidic chip for rapid, simple, sensitive and simultaneous detection of the five target pathogens above.ResultsStandard strains and clinical isolates were used for the establishment of the novel LAMP method in tube and LAMP-microfluidic chip, followed by the chip detection on 103 clinical samples and PCR verification partially. The sensitivities of LAMP of S. agalactiae, E. faecalis, G. vaginalis, and C. albicans in tube were 22.0, 76.0, 13.2, 1.11 CFU/μL, respectively, and C. trachomatis was 41.3 copies/μL; on LAMP-microfluidic chip they were 260, 154, 3.9 and 7.53 CFU/μL, respectively, and C. trachomatis was 120 copies/μL. The positive coincidence rates of clinical stains in tube and on chip experiments were 100%. Compared with the classic culture method performed in hospitals, the positive coincidence rate of the 103 clinical samples detected by LAMP-microfluidic chip were 100%. For the six inconsistent ones, including four G. vaginalis and two C. albicans positive samples tested by LAMP-microfluidic chip and verified by PCR were negative by culturing method in hospitals, indicating the lack of efficient detection by the classic culturing method.ConclusionOur study suggested that the LAMP-microfluidic chips could simultaneously, efficiently, and accurately detect multiple main pathogens, including S. agalactiae, E. faecalis, G. vaginalis, C. albicans and C. trachomatis, in clinical samples of female RTI to give a great clinical value. Accordingly, this novel method has the potential to provide a valuable reference for female RTI screening and early diagnosis during pregnancy.

Dataset Information

Etiologic diagnosis of lower respiratory tract bacterial infections using sputum samples and quantitative loop-mediated isothermal amplification.

Publications

Etiologic diagnosis of lower respiratory tract bacterial infections using sputum samples and quantitative loop-mediated isothermal amplification.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets