Evaluation of the ASTA MicroIDSys matrix-assisted laser desorption ionization time-of-flight mass spectrometry system for identification of mycobacteria directly from positive MGIT liquid cultures

Skin and soft tissue infections due to rapidly growing mycobacteria

PURPOSE OF REVIEW

The aim of this article is to review skin and soft tissue infections due to rapidly growing mycobacteria (RGM), with a particular focus on recently published literature (2021-2022).

RECENT FINDINGS

RGM are increasingly reported as a cause of skin and soft tissue infections, both in the community setting and as a cause of nosocomial outbreaks. Recent advances in molecular methods have expanded the number of species of RGM and resulted in increased diagnosis. New treatment options are under evaluation particularly for Mycobacterium abscessus , the most difficult-to-treat among RGM.

SUMMARY

RGM are an uncommon cause of skin and soft tissue infections and a high clinical suspicion together with advanced laboratory facilities are required for diagnosis. Species identification and antimicrobial susceptibility testing are essential to drive appropriate treatment, which combines surgical debridement with prolonged antimycobacterial combination therapy.

“Omic” Approaches to Bacteria and Antibiotic Resistance Identification

The quick and accurate identification of microorganisms and the study of resistance to antibiotics is crucial in the economic and industrial fields along with medicine. One of the fastest-growing identification methods is the spectrometric approach consisting in the matrix-assisted laser ionization/desorption using a time-of-flight analyzer (MALDI-TOF MS), which has many advantages over conventional methods for the determination of microorganisms presented. Thanks to the use of a multiomic approach in the MALDI-TOF MS analysis, it is possible to obtain a broad spectrum of data allowing the identification of microorganisms, understanding their interactions and the analysis of antibiotic resistance mechanisms. In addition, the literature data indicate the possibility of a significant reduction in the time of the sample preparation and analysis time, which will enable a faster initiation of the treatment of patients. However, it is still necessary to improve the process of identifying and supplementing the existing databases along with creating new ones. This review summarizes the use of “-omics” approaches in the MALDI TOF MS analysis, including in bacterial identification and antibiotic resistance mechanisms analysis.

Rapid and Accurate Identification of Nontuberculous Mycobacteria Directly from Positive Primary MGIT Cultures by MALDI-TOF MS

Over the last years, nontuberculous mycobacteria (NTM) have emerged as important human pathogens. Accurate and rapid mycobacterial species identification is needed to successfully diagnose, treat, and manage infections caused by NTM. Matrix-assisted laser desorption ionization time-of-flight mass spectrometry, MALDI-TOF MS, was demonstrated to effectively identify mycobacteria isolates subcultured from solid or liquid media rather than new positive cultures. The present study aims to develop a new extraction protocol to yield rapid and accurate identification of NTM from primary MGIT cultures by MALDI-TOF MS. A total of 60 positive MGIT broths were examined by the Bruker Biotyper system with Mycobacteria Library v. 2.0 (Bruker Daltonics GmbH & Co. KG., Bremen, Germany). The results were compared with those obtained by the molecular method, line probe assay GenoType Mycobacterium CM/AS/NTM-DR. All samples were concordantly identified by MALDI-TOF MS and the molecular test for all the tested mycobacteria. Fifty-seven (95%) MGIT positive cultures for NTM from clinical samples had a MALDI-TOF MS analysis score S ≥ 1.8. Although a small number of strains and a limited diversity of mycobacterial species were analysed, our results suggest that MALDI-TOF MS could represent a promising routine diagnostic tool for identifying mycobacterial species directly from primary liquid culture.

New design of multilocus sequence analysis of rpoB, ssrA, tuf, atpE, ku, and dnaK for identification of Mycobacterium species

BACKGROUND

Differentiating Mycobacterium tuberculosis (MTB) from nontuberculous mycobacteria (NTM) is very important in the treatment process of patients. According to the American Thoracic Society guideline (ATS), NTM clinical isolates should be identified at the species level proper treatment and patient management. This study aimed to identify NTM clinical isolates by evaluationg rpoB, ssrA, tuf, atpE, ku, and dnaK genes, and use multilocus sequence analysis (MLSA) to concatenate the six genes.

METHODS

Ninety-six Mycobacterium isolates, including 86 NTM and 10 MTB isolates, from all the patients referred to the certain TB Reference Centres were included. All isolates were evaluated by PCR amplification of rpoB, ssrA, tuf, ku, atpE, and dnaK genes and MLSA.

RESULTS

Out of 96 isolates, 91 (94.8%), 87 (90.6%), 72 (75%), 84 (87.5%) and 79 (82.3%) were differentiated to the species level by rpoB, tuf, ssrA, dnaK and atpE genes, respectively. The ku gene was able to identify 69 (80.2%) isolates of the 86 NTM isolates to the species level. We could identify 100% of the isolates to the species level by MLSA.

CONCLUSIONS

None of the PCR targets used in this study were able to completely differentiate all species. The MLSA technique used to concatenate the six genes could increase the identification of clinical Mycobacterium isolates and all 16 species were well-differentiated.

Substantial Improvement in Nontuberculous Mycobacterial Identification Using ASTA MicroIDSys Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry with an Upgraded Database

Identifying Mycobacterium using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) is challenging. We evaluated the performance of MALDI-TOF MS in identifying nontuberculous mycobacteria (NTM) using the ASTA MicroIDSys system (ASTA Inc., Suwon, Korea) with the MycoDB v1.95s and upgraded MycoDB v2.0-beta databases. We tested 124 NTM isolates collected from Ogawa medium at Severance Hospital, Seoul, Korea, between January and April 2019. MicroIDSys scores were categorized into three groups: ≥140, reliable identification; 130-139, ambiguous identification; and <130, invalid identification. To validate the results, we used the reverse blot hybridization assay (Molecutech REBA MycoID, YD Diagnostics Corp., Korea). Initial analysis using MycoDB v1.95s resulted in 26.6% (33/124) reliable, 43.5% (54/124) ambiguous, and 29.8% (37/124) invalid identifications. Re-analysis using the upgraded MycoDB v2.0-beta database resulted in 94.4% (117/124) reliable, 4.0% (5/124) ambiguous, and 1.6% invalid (2/124) identifications. The percentage of reliable identifications that matched with the reference increased from 26.6% (33/124) with MycoDB v1.95s to 93.5% (116/124) with MycoDB v2.0-beta. The upgraded databases enable substantially improved NTM identification through deep learning in the inference algorithm and by considering more axes in the correlation analysis. MALDI-TOF MS using the upgraded database unambiguously identified most NTM species. Our study lays a foundation for applying MALDI-TOF MS for the simple and rapid identification of NTM isolated from solid media.

Comparative Evaluation of Bruker Biotyper and ASTA MicroIDSys for Species Identification in a Clinical Microbiology Laboratory

Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI–TOF MS) has been widely used for microbial identification, because of its speed and accuracy, since its introduction to clinical microbiology laboratories. In this study, we evaluated the performance of ASTA MicroIDSys, a newly developed MALDI–TOF, and compared it with the widely used Bruker Biotyper. Microbial identification with the Bruker Biotyper system was performed by using a direct smear method and the Bruker Biotyper database (reference library version 6.0.0.0). The isolates were also tested in parallel, using the ASTA MicroIDSys system with a direct smear method and the MicroIDSys database, CoreDB v1.26. A total of 914 clinical isolates were recovered from the clinical specimens. Identical results with confidence scores (≥2.0, for the Bruker Biotyper) and acceptable scores (≥140 for the ASTA MicroIDSys) were obtained for 840 (91.9%) isolates. The minor errors were defined as misidentification at the species level, and the rate was 1.1% (9/792) for Bruker Biotyper and 1.6% (13/792) for ASTA MicroIDSys. Major errors were defined as misidentification at the genus level, and the rate was 0.3% (2/792) for both Bruker Biotyper and ASTA MicroIDSys. ASTA MicroIDSys showed reliable performance for microbial identification, which was comparable to that of the Bruker Biotyper. Therefore, ASTA MicroIDSys can be applied for the identification of microorganisms in clinical microbiology laboratories.