Polymerase chain reaction for detection of Mycoplasma genitalium in clinical samples

Abstract

We have used the polymerase chain reaction to detect Mycoplasma genitalium in artificially seeded human throat swab samples as well as in clinical material. On the basis of the published nucleotide sequence of the M. genitalium 140-kDa adhesin gene, primers were chosen to produce an amplified fragment of 281 bp. Five different previously isolated strains, including the type strain of M. genitalium, could all be detected by the polymerase chain reaction, and DNAs from other mycoplasmal and bacterial species yielded negative results. The detection limits were estimated to be approximately 50 organisms by inspection of ethidium bromidestained agarose gels and 4 organisms when a biotinylated oligonucleotide probe was used in filter hybridization. The amplified DNA fragments were subjected to restriction enzyme analysis. DNAs from the five different isolates all possessed EcoRI, SspI, AluI, Sau3AI, and DdeI restriction sites, as predicted from the published sequence. A total of 150 urogenital swabs collected from 100 patients for culturing of Chiamydia trachomatis were tested for the presence of M. genitalium DNA. Ten samples from eight patients were found positive. The amplified DNA fragments from all of our clinical samples possessed the AluI, Sau3AI, and DdeI restriction sites, but three samples from two patients did not contain the SspI site and none of the samples contained the EcoRI site.

Prevalence of Mycoplasma genitalium in early pregnancy and relationship between its presence and pregnancy outcome

“…13 All positive results were confirmed by a second polymerase chain reaction detecting the MgPa adhesin gene. 9 The M. genitalium DNA load in the positive specimens was determined by TaqMan quantitative polymerase chain reaction procedure targeting a conserved part of the MgPa adhesin gene. The results were expressed in terms of genome equivalent (geq) per mL of urine.…”

Background review for the 2016 European guideline on Mycoplasma genitalium infections

“…2 It is an extremely slow-growing and fastidious bacterium, and its role as a pathogen in human disease was not established until the first diagnostic polymerase chain reaction assays (PCRs) were developed in the early 1990s. 3,4 Male NGU was the first syndrome unequivocally associated with M. genitalium infection 5,6 and in a meta-analysis including 37 studies up to 2010, 7 M. genitalium was associated with a pooled OR of 5.5 (95% CI:4.4-7.0) for NGU. In the 29 studies where information on chlamydial infection was available, M. genitalium was associated with a pooled OR of 7.6 (95% CI:5.5-10.5) for non-chlamydial non-gonococcal urethritis (NCNGU).…”

Sexual behaviours, knowledge and attitudes regarding safe sex, and prevalence of non‐viral sexually transmitted infections among attendees of youth clinics in St. Petersburg, Russia

“…†Syphilis, gonorrhoea, chlamydial infection, trichomoniasis, genital herpes, bacterial vaginosis, candidiasis, condylomatosis. ‡A total score was calculated by adding the number of correct responses to the 14 items; the knowledge was considered poor if the total score was less than or equal to the median (0-10), and good if the total score was above the median (11)(12)(13). §A total score was calculated by adding the number of responses displaying positive attitudes to the 10 items; the attitude was considered negative if the total score was less than or equal to the median (0-6), and positive if the total score was above the median (7)(8)(9)(10)(11).…”

“…Associations between the surveyed variables and the STIs were investigated using univariate and multivariate logistic regression. True positive if positive by (i) the international methods, [9][10][11] (ii) at least two Russian assays using different targets, or (iii) any of the PCRs when the matched sample true positive Sample size calculation for logistic regression was performed according to the description by Peduzzi et al 13 The age variables (age and age at first sexual intercourse) were entered in all logistic regression models in several categories. To estimate the risks of detection of the STI agents in single vs. multiple infections, odds ratios (ORs) with 95% confidence intervals (95% CIs) and P-values were calculated.…”