Detection of Microorganisms in Body Fluids via MTT-PMS Assay.

Cheng-Han Chen,Wan-Ting Liao,Chao-Min Cheng,Ching-Fen Shen,Yi-Tzu Lee,Yu-Hsiang Liao,Po-Ting Yeh,Yu-Ting Tsao,Yung-Chih Wang

doi:10.3390/diagnostics12010046

Abstract

Early detection of microorganisms is essential for the management of infectious diseases. However, this is challenging, as traditional culture methods are labor-intensive and time-consuming. The 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide-phenazine methosulfate (MTT-PMS) assay has been used to evaluate the metabolic activity in live cells and can thus be used for detecting living microorganisms. With the addition of NaOH and Tris-EDTA, the same approach can be accelerated (within 15 min) and used for the quick detection of common bacterial pathogens. The assay results can be evaluated colorimetrically or semi-quantitatively. Here, the quick detection by MTT-PMS assay was further investigated. The assay had a detection limit of approximately 104 CFU/mL. In clinical evaluations, we used the MTT-PMS assay to detect clinical samples and bacteriuria (>105 CFU/mL). The negative predictive value of the MTT-PMS assay for determining bacteriuria was 79.59% but was 100% when the interference of abnormal blood was excluded. Thus, the MTT-PMS assay might be a potential “rule-out” tool for bacterial detection in clinical samples, at a cost of approximately USD 1 per test. Owing to its low cost, rapid results, and easy-to-use characteristics, the MTT-PMS assay may be a potential tool for microorganism detection.

Highlights

Infectious diseases remain a major cause of ill health and socioeconomic burden in contemporary healthcare systems [1]
This study further evaluated the clinical efficacy of the MTT-PMS assay for bacterial screening to determine whether it could provide semi-quantitative results when differentiating bacterial concentrations range from 100 CFU/mL to 108 CFU/mL
The results showed that the negative predictive value (NPV) of the MTT-PMS assay was 100% when urine samples with abnormal blood were excluded (Table 2)

Summary

Introduction

Infectious diseases remain a major cause of ill health and socioeconomic burden in contemporary healthcare systems [1]. According to the World Health Organization, infectious diseases are responsible for 54.4% of all global deaths. Developing areas with low healthcare accessibility, such as Africa and Latin America, exhibit high incidence of infectious diseases and related mortality [1,2]. Mortality risk from severe infection, or sepsis, increases by 7.6% for every hour of delayed antibiotic treatment; yet misuse or overuse of broad-spectrum empirical antibiotics leads to high rates of antimicrobial resistance [4,5]. By 2050, antimicrobial resistance-related mortality is estimated to increase to 10 million deaths per year, an outcome that will increase individual and communal economic burdens [5]. To effectively treat or manage infectious diseases, it is crucial to develop a tool for the early and precise determination of causal pathogens [2]

Results

Discussion

Conclusion