Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry for Combined Species Identification and Drug Sensitivity Testing in Mycobacteria

MALDI-TOF mass spectrometry from nucleic acid: development and evaluation of a novel platform for identification of mycobacteria and detection of genetic markers of resistance

Complete identification methods are critical for evaluating nontuberculous mycobacteria (NTM). Here, we describe a novel diagnostic method for identification of eight NTM, Mycobacterium tuberculosis complex, and three drug resistance markers using PCR/matrix-assisted, laser-desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) from cultured organisms. With this technology, a multiplex end-point PCR is performed for targets of interest. Detection probes that are extended in the presence of a target are added. The extended probes have greater molecular weight and can be detected by MALDI-TOF MS. An AFB Primary Panel was designed to differentiate Mycobacterium avium; Mycobacterium intracellulare subsp. chimaera; Mycobacterium avium complex (other); Mycobacterium abscessus subsp. abscessus, bolletii, and massiliense; Mycobacterium kansasii, and M. tuberculosis complex. This design should cover 90% (3,483/3,691) of mycobacteria seen onsite. A development set of unblinded isolates (n = 217) was used to develop PCR primers, detection probes, and probe barcodes. It demonstrated 99.1% (215/217) agreement with reference methods. An evaluation set using blinded isolates (n = 320) showed an overall sensitivity of 94.3% (range by target: 90.0-100%). Overall specificity from negative media, non-target mycobacteria, and bacteria was 99.1% (108/109; range by target: 94.4-100%). Three drug resistance markers erm (41), rrl, and rrs demonstrated 100%, 91%, and 100% sensitivity, respectively, and >99% specificity. Limit of detection per target ranged from 2.2 × 103 to 9.9 × 106 CFU/mL. The AFB Primary Panel allows for mycobacterial speciation, subspeciation, and resistance mutation detection, which is essential for diagnosis, appropriate therapy, identifying outbreaks, and managing treatment-refractory disease. It can perform with high-throughput and high specificity and sensitivity from isolates.IMPORTANCEEven closely related mycobacteria can have unique treatment patterns, but differentiating these organisms is a challenge. Here, we tested an innovative platform that combines two commonly used technologies and creates something new: matrix-assisted, laser-desorption ionization time-of flight mass spectrometry was performed on PCR amplicons instead of on proteins. This created a robust system with the advantages of PCR (high discriminatory power, high throughput, detection of resistance) with the advantages of mass spectrometry (more targets, lower operational cost) in order to identify closely related mycobacterial organisms.

Tuberculosis Diagnosis: Current, Ongoing, and Future Approaches

Tuberculosis (TB) remains an impactful infectious disease, leading to millions of deaths every year. Mycobacterium tuberculosis causes the formation of granulomas, which will determine, through the host-pathogen relationship, if the infection will remain latent or evolve into active disease. Early TB diagnosis is life-saving, especially among immunocompromised individuals, and leads to proper treatment, preventing transmission. This review addresses different approaches to diagnosing TB, from traditional methods such as sputum smear microscopy to more advanced molecular techniques. Integrating these techniques, such as polymerase chain reaction (PCR) and loop-mediated isothermal amplification (LAMP), has significantly improved the sensitivity and specificity of M. tuberculosis identification. Additionally, exploring novel biomarkers and applying artificial intelligence in radiological imaging contribute to more accurate and rapid diagnosis. Furthermore, we discuss the challenges of existing diagnostic methods, including limitations in resource-limited settings and the emergence of drug-resistant strains. While the primary focus of this review is on TB diagnosis, we also briefly explore the challenges and strategies for diagnosing non-tuberculous mycobacteria (NTM). In conclusion, this review provides an overview of the current landscape of TB diagnostics, emphasizing the need for ongoing research and innovation. As the field evolves, it is crucial to ensure that these advancements are accessible and applicable in diverse healthcare settings to effectively combat tuberculosis worldwide.

Applications and advances in molecular diagnostics: revolutionizing non-tuberculous mycobacteria species and subspecies identification

Non-tuberculous mycobacteria (NTM) infections pose a significant public health challenge worldwide, affecting individuals across a wide spectrum of immune statuses. Recent epidemiological studies indicate rising incidence rates in both immunocompromised and immunocompetent populations, underscoring the need for enhanced diagnostic and therapeutic approaches. NTM infections often present with symptoms similar to those of tuberculosis, yet with less specificity, increasing the risk of misdiagnosis and potentially adverse outcomes for patients. Consequently, rapid and accurate identification of the pathogen is crucial for precise diagnosis and treatment. Traditional detection methods, notably microbiological culture, are hampered by lengthy incubation periods and a limited capacity to differentiate closely related NTM subtypes, thereby delaying diagnosis and the initiation of targeted therapies. Emerging diagnostic technologies offer new possibilities for the swift detection and accurate identification of NTM infections, playing a critical role in early diagnosis and providing more accurate and comprehensive information. This review delineates the current molecular methodologies for NTM species and subspecies identification. We critically assess the limitations and challenges inherent in these technologies for diagnosing NTM and explore potential future directions for their advancement. It aims to provide valuable insights into advancing the application of molecular diagnostic techniques in NTM infection identification.

Streptococcus pneumoniae favors tolerance via metabolic adaptation over resistance to circumvent fluoroquinolones

Streptococcus pneumoniae is a major human pathogen of global health concern and the rapid emergence of antibiotic resistance poses a serious public health problem worldwide. Fluoroquinolone resistance in S. pneumoniae is an intriguing case because the prevalence of fluoroquinolone resistance does not correlate with increasing usage and has remained rare. Our data indicate that deleterious fitness costs in the mammalian host constrain the emergence of fluoroquinolone resistance both by de novo mutation and recombination. S. pneumoniae was able to circumvent such deleterious fitness costs via the development of antibiotic tolerance through metabolic adaptation that reduced the production of reactive oxygen species, resulting in a fitness benefit during infection of mice treated with fluoroquinolones. These data suggest that the emergence of fluoroquinolone resistance is tightly constrained in S. pneumoniae by fitness tradeoffs and that mutational pathways involving metabolic networks to enable tolerance phenotypes are an important contributor to the evasion of antibiotic-mediated killing.IMPORTANCEThe increasing prevalence of antibiotic resistant bacteria is a major global health concern. While many species have the potential to develop antibiotic resistance, understanding the barriers to resistance emergence in the clinic remains poorly understood. A prime example of this is fluroquinolone resistance in Streptococcus pneumoniae, whereby, despite continued utilization, resistance to this class of antibiotic remains rare. In this study, we found that the predominant pathways for developing resistance to this antibiotic class severely compromised the infectious capacity of the pneumococcus, providing a key impediment for the emergence of resistance. Using in vivo models of experimental evolution, we found that S. pneumoniae responds to repeated fluoroquinolone exposure by modulating key metabolic pathways involved in the generation of redox molecules, which leads to antibiotic treatment failure in the absence of appreciable shifts in resistance levels. These data underscore the complex pathways available to pathogens to evade antibiotic mediating killing via antibiotic tolerance.

Machine learning to identify clinically relevant Candida yeast species

Fungal infections, especially due to Candida species, are on the rise. Multi-drug resistant organisms such as Candida auris are difficult and time consuming to identify accurately. Machine learning is increasingly being used in health care, especially in medical imaging. In this study, we evaluated the effectiveness of six convolutional neural networks (CNNs) to identify four clinically important Candida species. Wet-mounted images were captured using bright field live-cell microscopy followed by separating single-cells, budding-cells, and cell-group images which were then subjected to different machine learning algorithms (custom CNN, VGG16, ResNet50, InceptionV3, EfficientNetB0, and EfficientNetB7) to learn and predict Candida species. Among the six algorithms tested, the InceptionV3 model performed best in predicting Candida species from microscopy images. All models performed poorly on raw images obtained directly from the microscope. The performance of all models increased when trained on single and budding cell images. The InceptionV3 model identified budding cells of C. albicans, C. auris, C. glabrata (Nakaseomyces glabrata), and C. haemulonii in 97.0%, 74.0%, 68.0%, and 66.0% cases, respectively. For single cells of C. albicans, C. auris, C. glabrata, and C. haemulonii InceptionV3 identified 97.0%, 73.0%, 69.0%, and 73.0% cases, respectively. The sensitivity and specificity of InceptionV3 were 77.1% and 92.4%, respectively. Overall, this study provides proof of the concept that microscopy images from wet-mounted slides can be used to identify Candida yeast species using machine learning quickly and accurately.

Diagnostic efficacy of an optimized nucleotide MALDI-TOF-MS assay for anti-tuberculosis drug resistance detection

PURPOSE

We aimed at evaluating the diagnostic efficacy of a nucleotide matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF-MS) assay to detect drug resistance of Mycobacterium tuberculosis.

METHODS

Overall, 263 M. tuberculosis clinical isolates were selected to evaluate the performance of nucleic MALDI-TOF-MS for rifampin (RIF), isoniazid (INH), ethambutol (EMB), moxifloxacin (MXF), streptomycin (SM), and pyrazinamide (PZA) resistance detection. The results for RIF, INH, EMB, and MXF were compared with phenotypic microbroth dilution drug susceptibility testing (DST) and whole-genome sequencing (WGS), and the results for SM and PZA were compared with those obtained by WGS.

RESULTS

Using DST as the gold standard, the sensitivity, specificity, and kappa values of the MALDI-TOF-MS assay for the detection of resistance were 98.2%, 98.7%, and 0.97 for RIF; 92.8%, 99%, and 0.90 for INH; 82.4%, 98.0%, and 0.82 for EMB; and 92.6%, 99.5%, and 0.94 for MXF, respectively. Compared with WGS as the reference standard, the sensitivity, specificity, and kappa values of the MALDI-TOF-MS assay for the detection of resistance were 97.4%, 100.0%, and 0.98 for RIF; 98.7%, 92.9%, and 0.92 for INH; 96.3%, 100.0%, and 0.98 for EMB; 98.1%, 100.0%, and 0.99 for MXF; 98.0%, 100.0%, and 0.98 for SM; and 50.0%, 100.0%, and 0.65 for PZA.

CONCLUSION

The nucleotide MALDI-TOF-MS assay yielded highly consistent results compared to DST and WGS, suggesting that it is a promising tool for the rapid detection of sensitivity to RIF, INH, EMB, and MXF.

Accurate noise-robust classification of Bacillus species from MALDI-TOF MS spectra using a denoising autoencoder

Bacillus strains are ubiquitous in the environment and are widely used in the microbiological industry as valuable enzyme sources, as well as in agriculture to stimulate plant growth. The Bacillus genus comprises several closely related groups of species. The rapid classification of these remains challenging using existing methods. Techniques based on MALDI-TOF MS data analysis hold significant promise for fast and precise microbial strains classification at both the genus and species levels. In previous work, we proposed a geometric approach to Bacillus strain classification based on mass spectra analysis via the centroid method (CM). One limitation of such methods is the noise in MS spectra. In this study, we used a denoising autoencoder (DAE) to improve bacteria classification accuracy under noisy MS spectra conditions. We employed a denoising autoencoder approach to convert noisy MS spectra into latent variables representing molecular patterns in the original MS data, and the Random Forest method to classify bacterial strains by latent variables. Comparison of the DAE-RF with the CM method using the artificially noisy test samples showed that DAE-RF offers higher noise robustness. Hence, the DAE-RF method could be utilized for noise-robust, fast, and neat classification of Bacillus species according to MALDI-TOF MS data.

MGIT-seq for the Identification of Nontuberculous Mycobacteria and Drug Resistance: a Prospective Study

Because nontuberculous mycobacterial pulmonary disease is a considerable health burden, a simple and clinically applicable analytical protocol enabling the identification of subspecies and drug-resistant disease is required to determine the treatment strategy. We aimed to develop a simplified workflow consisting only of direct sequencing of mycobacterial growth indicator tube cultures (MGIT-seq). In total, 138 patients were prospectively enrolled between April 2021 and May 2022, and culture-positive MGIT broths were subjected to sequencing using MinION, a portable next-generation sequencer. Sequence analysis was conducted to identify species using core genome multilocus sequence typing and to predict macrolide and amikacin (AMK) resistance based on previously reported mutations in rrl, rrs, and erm(41). The results were compared to clinical tests for species identification and drug susceptibility. A total of 116 patients with positive MGIT cultures were included in the analysis. MGIT-seq yielded 99.1% accuracy in species-level identification and identified 98 isolates (84.5%) at the subspecies level. Macrolide and AMK resistance were detected in 19.4% and 1.9% of Mycobacterium avium complex (MAC) and Mycobacterium abscessus isolates. The predicted macrolide and AMK resistance was consistent with the results of conventional drug susceptibility tests, with specificities of 97.6% and 100.0%, respectively. Direct MGIT-seq has achieved comprehensive identification and drug resistance detection of nontuberculous mycobacteria, which could be applicable to determine the treatment strategy by a single test in clinical practice.

A Rapid and Easy Method of MALDI Biotyper Antibiotic Susceptibility Test Rapid Assay To Provide Early Meropenem Susceptibility Profile in Enterobacterales

Antimicrobial susceptibility testing (AST) that can provide faster results is necessary. The MALDI Biotyper antibiotic susceptibility test rapid assay (MBT-ASTRA) can provide early AST results but still needs to be simplified in order to facilitate its execution by microbiology laboratories. The aim of this study was to evaluate an adaptation of MBT-ASTRA. Isolates of Enterobacterales were tested for meropenem susceptibility by MBT-ASTRA using a solution prepared from meropenem disks and performing a manual spectrum analysis. The relative growth (RG) was calculated for each isolate, and a cutoff value was established to determine the susceptibility profile of the isolates. Results of the adapted method were compared with the standard susceptibility method (broth microdilution). An adapted method of MBT-ASTRA was developed. The RG cutoff values for meropenem were ≤0.1510 for susceptibility and >0.6272 for resistance, presenting 95.65% categorical agreement, with 2.9% (2/69) minor discrepancy and 3.23% (1/31) very major discrepancy. MBT-ASTRA can be used to provide rapid AST results with a simpler and more accessible protocol, especially regarding spectrum analysis. IMPORTANCE The simplification of the MBT-ASTRA technique, especially in spectrum analysis, can considerably allow more laboratories to rapidly determine antimicrobial susceptibility profiles.

Diagnostic performance of metagenomic next-generation sequencing in non-tuberculous mycobacterial pulmonary disease when applied to clinical practice

OBJECTIVE

To compare non-tuberculous mycobacterial pulmonary disease (NTMPD) diagnosis by metagenomic next-generation sequencing (mNGS) with Bactec mycobacterial growth indicator tube (MGIT) 960.

METHODS

A total of 422 patients with suspected NTMPD in Shanghai Pulmonary Hospital between January 2020 and May 2021 were retrospectively analyzed; 194 were diagnosed with NTMPD. The diagnostic performance of mNGS and MGIT 960 for NTMPD was assessed. Receiver operating characteristic (ROC) curves and areas under curve (AUCs) were compared.

RESULTS

The sensitivity of mNGS in NTMPD diagnosis was 81.4% and higher than that of MGIT 960 (53.6%). The specificity of mNGS in NTMPD diagnosis was 97.8%, similar to that of MGIT 960 (100%). The sensitivity of combined mNGS and MGIT 960 in NTMPD diagnosis was 91.8%. The sensitivity of mNGS for bronchoalveolar lavage fluid (BALF), pulmonary puncture tissue fluid, and sputum was 84.8%, 80.6%, and 77.5%, respectively; all were higher than that of MGIT 960 (P < 0.05). The AUC of mNGS and MGIT 960 was 0.897 and 0.768, respectively. The AUC of mNGS were BALF (0.916), pulmonary puncture tissue fluid (0.903), and sputum (0.870).

CONCLUSION

The sensitivity of mNGS was superior to that of Bactec MGIT 960; the specificity in NTMPD diagnosis was similar. mNGS shows effective performance in NTMPD diagnosis.

Mycobacterium chimaera Identification Using MALDI-TOF MS Technology: A Practical Approach for the Clinical Microbiology Laboratories

Mycobacterium chimaera (MC) is an environmental, slowly growing, non-tuberculous mycobacterium (NTM) belonging to Mycobacterium avium complex (MAC), which recently has been linked to severe cardiovascular infections following open heart and vascular surgery. The majority of the diagnostic laboratory tests used in routine are not able to distinguish MC from M. intracellulare (MI), because of the great genetic similarity existing between these two species. The Genotype Mycobacterium NTM-DR™ represents a valid method to differentiate between these species, but it is expensive, requiring also specialized personnel. Recently, MALDI-TOF MS has been proposed to identify relevant NTM. However, a software implementation is required to distinguish between MC and MI, presenting the two microorganisms’ overlapping spectra. The present study evaluates the feasibility of applying a MALDI-TOF logarithmic-based analysis in the routine of a clinical microbiology laboratory, and proposes an easy-to-use template spreadsheet to make the results quickly interpretable. The protocol was previously validated through the identification of 87 strains of MC/MI collected from clinical and environmental samples, and it was identified using the GenoType Mycobacterium NTM-DR™ and/or WGS. The proposed protocol provides accurate identification for the isolates tested; moreover, it is less expensive and more rapid than sequencing methods and can be implemented with minimum effort.

Multicentre study on the reproducibility of MALDI-TOF MS for nontuberculous mycobacteria identification

The ability of MALDI-TOF for the identification of nontuberculous mycobacteria (NTM) has improved recently thanks to updated databases and optimized protein extraction procedures. Few multicentre studies on the reproducibility of MALDI-TOF have been performed so far, none on mycobacteria. The aim of this study was to evaluate the reproducibility of MALDI-TOF for the identification of NTM in 15 laboratories in 9 European countries. A total of 98 NTM clinical isolates were grown on Löwenstein-Jensen. Biomass was collected in tubes with water and ethanol, anonymized and sent out to the 15 participating laboratories. Isolates were identified using MALDI Biotyper (Bruker Daltonics). Up to 1330 MALDI-TOF identifications were collected in the study. A score ≥ 1.6 was obtained for 100% of isolates in 5 laboratories (68.2–98.6% in the other). Species-level identification provided by MALDI-TOF was 100% correct in 8 centres and 100% correct to complex-level in 12 laboratories. In most cases, the misidentifications obtained were associated with closely related species. The variability observed for a few isolates could be due to variations in the protein extraction procedure or to MALDI-TOF system status in each centre. In conclusion, MALDI-TOF showed to be a highly reproducible method and suitable for its implementation for NTM identification.

Bacterial species identification using MALDI-TOF mass spectrometry and machine learning techniques: A large-scale benchmarking study

Today machine learning methods are commonly deployed for bacterial species identification using MALDI-TOF mass spectrometry data. However, most of the studies reported in literature only consider very traditional machine learning methods on small datasets that contain a limited number of species. In this paper we present benchmarking results on an unprecedented scale for a wide range of machine learning methods, using datasets that contain almost 100,000 spectra and more than 1000 different species. The size and the diversity of the data allow to compare three important identification scenarios that are often not distinguished in literature, i.e., identification for novel biological replicates, novel strains and novel species that are not present in the training data. The results demonstrate that in all three scenarios acceptable identification rates are obtained, but the numbers are typically lower than those reported in studies with a more limited analysis. Using hierarchical classification methods, we also demonstrate that taxonomic information is in general not well preserved in MALDI-TOF mass spectrometry data. For the novel species scenario, we apply for the first time neural networks with Monte Carlo dropout, which have shown to be successful in other domains, such as computer vision, for the detection of novel species.

Matrix-Assisted Laser Desorption/Ionization Time of Flight Mass Spectrometry (MALDI-TOF MS) Analysis for the Identification of Pathogenic Microorganisms: A Review

Matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) has been used in the field of clinical microbiology since 2010. Compared with the traditional technique of biochemical identification, MALDI-TOF MS has many advantages, including convenience, speed, accuracy, and low cost. The accuracy and speed of identification using MALDI-TOF MS have been increasing with the development of sample preparation, database enrichment, and algorithm optimization. MALDI-TOF MS has shown promising results in identifying cultured colonies and rapidly detecting samples. MALDI-TOF MS has critical research applications for the rapid detection of highly virulent and drug-resistant pathogens. Here we present a scientific review that evaluates the performance of MALDI-TOF MS in identifying clinical pathogenic microorganisms. MALDI-TOF MS is a promising tool in identifying clinical microorganisms, although some aspects still require improvement.

MALDI-TOF mass spectrometry for antimicrobial susceptibility testing

The advent of matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) in clinical microbiology has dramatically improved the accuracy and speed of diagnostics. However, this progress has mainly been limited to the identification of microorganisms, whereas the practical improvement of antimicrobial susceptibility testing (AST) still lags behind. MALDI-TOF MS-based approaches include the detection of selected resistance mechanisms and the universal phenotypic AST. This minireview focuses on the discussion of those MALDI-TOF MS methods that allow universal growth-based phenotypic AST. The method of minimal profile change concentrations (MPCC) is based on detecting proteome modification in presence of an antimicrobial. Using stable-isotope labeling, characteristic mass shifts in the presence of an antimicrobial indicate the incorporation of the isotopic labels, and, thus, the viability and resistance of the microorganism. For MALDI Biotyper antibiotic susceptibility test rapid assay (MBT-ASTRA), microorganisms are incubated with or without an antimicrobial, followed by cell lysis, protein extraction, and transfer of the cell lysate onto a MALDI target plate. Using the internal standard, peak intensities are correlated to the amount of microbial proteins, and the relative microbial growth is calculated. Most recent development in the field is the direct-on-target microdroplet growth assay (DOT-MGA). Here, incubation of microorganisms with antimicrobials takes place directly on spots of a MALDI target in form of microdroplets. After incubation, nutrient medium is removed by dabbing with absorptive material. Resistant microorganisms grow despite the presence of antimicrobial, and their amplified biomass is detected by MALDI-TOF MS. Finally, an outlook is provided for further assay improvements.

Therapeutic Drug Monitoring in Non-Tuberculosis Mycobacteria Infections

Nontuberculous mycobacteria can cause minimally symptomatic self-limiting infections to progressive and life-threatening disease of multiple organs. Several factors such as increased testing and prevalence have made this an emerging infectious disease. Multiple guidelines have been published to guide therapy, which remains difficult owing to the complexity of therapy, the potential for acquired resistance, the toxicity of treatment, and a high treatment failure rate. Given the long duration of therapy, complex multi-drug treatment regimens, and the risk of drug toxicity, therapeutic drug monitoring is an excellent method to optimize treatment. However, currently, there is little available guidance on therapeutic drug monitoring for this condition. The aim of this review is to provide information on the pharmacokinetic/pharmacodynamic targets for individual drugs used in the treatment of nontuberculous mycobacteria disease. Lacking data from randomized controlled trials, in vitro, in vivo, and clinical data were aggregated to facilitate recommendations for therapeutic drug monitoring to improve efficacy and reduce toxicity.

Detection of Antibiotic-Resistance by MALDI-TOF Mass Spectrometry: An Expanding Area

Several MALDI-TOF MS-based methods have been proposed for rapid detection of antimicrobial resistance. The most widely studied methods include assessment of β-lactamase activity by visualizing the hydrolysis of the β-lactam ring, detection of biomarkers responsible for or correlated with drug-resistance/non-susceptibility, and the comparison of proteomic profiles of bacteria incubated with or without antimicrobial drugs. Antimicrobial-resistance to a number of antibiotics belonging to different classes has been successfully tested by MALDI-TOF MS in a variety of clinically relevant bacterial species including members of Enterobacteriaceae family, non-fermenting Gram-negative bacteria, Gram-positive cocci, anaerobic bacteria and mycobacteria, opening this field to further clinically important developments. Early detection of drug-resistance by MALDI-TOF MS can be particularly helpful for clinicians to streamline the antibiotic therapy for a better outcome of patients with systemic infection, in all cases where a prompt and effective antibiotic treatment is essential to preserve organ function and/or patient survival.

Evaluation of MALDI Biotyper Interpretation Criteria for Accurate Identification of Nontuberculous Mycobacteria

Identification of mycobacteria by matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) requires not only a good protein extraction protocol but also an adequate cutoff score in order to provide reliable results. The aim of this study was to assess the cutoff scores proposed by the MALDI-TOF MS system for mycobacterial identification. A total of 693 clinical isolates from a liquid medium and 760 from a solid medium were analyzed, encompassing 67 different species of nontuberculous mycobacteria (NTM). MALDI-TOF MS identified 558 (80.5%) isolates from the liquid medium and 712 (93.7%) isolates from the solid medium with scores of ≥1.60. Among these, four (0.7%) misidentifications were obtained from the liquid medium and four (0.5%) from the solid medium. With regard to species diversity, MALDI-TOF MS successfully identified 64 (95.5%) different species, while PCR-reverse hybridization (GenoType Mycobacterium CM and AS assays) identified 24 (35.8%) different species. With MALDI-TOF MS scores of ≥2, all isolates were correctly identified, and with scores in the range from 1.60 to 1.99, most isolates were correctly identified, except for Mycobacterium angelicum, M. parascrofulaceum, M. peregrinum, M. porcinum, and M. gastri In conclusion, MALDI-TOF MS is a useful method for identifying a large diversity of NTM species. A score threshold of 1.60 proved useful for identifying almost all the isolates tested; only a few species required a higher score (≥2.00) to obtain a valid definitive identification.

Non-Tuberculous Mycobacteria: Molecular and Physiological Bases of Virulence and Adaptation to Ecological Niches

Non-tuberculous mycobacteria (NTM) are paradigmatic colonizers of the total environment, circulating at the interfaces of the atmosphere, lithosphere, hydrosphere, biosphere, and anthroposphere. Their striking adaptive ecology on the interconnection of multiple spheres results from the combination of several biological features related to their exclusive hydrophobic and lipid-rich impermeable cell wall, transcriptional regulation signatures, biofilm phenotype, and symbiosis with protozoa. This unique blend of traits is reviewed in this work, with highlights to the prodigious plasticity and persistence hallmarks of NTM in a wide diversity of environments, from extreme natural milieus to microniches in the human body. Knowledge on the taxonomy, evolution, and functional diversity of NTM is updated, as well as the molecular and physiological bases for environmental adaptation, tolerance to xenobiotics, and infection biology in the human and non-human host. The complex interplay between individual, species-specific and ecological niche traits contributing to NTM resilience across ecosystems are also explored. This work hinges current understandings of NTM, approaching their biology and heterogeneity from several angles and reinforcing the complexity of these microorganisms often associated with a multiplicity of diseases, including pulmonary, soft-tissue, or milliary. In addition to emphasizing the cornerstones of knowledge involving these bacteria, we identify research gaps that need to be addressed, stressing out the need for decision-makers to recognize NTM infection as a public health issue that has to be tackled, especially when considering an increasingly susceptible elderly and immunocompromised population in developed countries, as well as in low- or middle-income countries, where NTM infections are still highly misdiagnosed and neglected.

Review of the impact of MALDI-TOF MS in public health and hospital hygiene, 2018

Introduction

MALDI-TOF MS represents a new technological era for microbiology laboratories. Improved sample processing and expanded databases have facilitated rapid and direct identification of microorganisms from some clinical samples. Automated analysis of protein spectra from different microbial populations is emerging as a potential tool for epidemiological studies and is expected to impact public health.

Aim

To demonstrate how implementation of MALDI-TOF MS has changed the way microorganisms are identified, how its applications keep increasing and its impact on public health and hospital hygiene.

Methods

A review of the available literature in PubMED, published between 2009 and 2018, was carried out.

Results

Of 9,709 articles retrieved, 108 were included in the review. They show that rapid identification of a growing number of microorganisms using MALDI-TOF MS has allowed for optimisation of patient management through prompt initiation of directed antimicrobial treatment. The diagnosis of Gram-negative bacteraemia directly from blood culture pellets has positively impacted antibiotic streamlining, length of hospital stay and costs per patient. The flexibility of MALDI-TOF MS has encouraged new forms of use, such as detecting antibiotic resistance mechanisms (e.g. carbapenemases), which provides valuable information in a reduced turnaround time. MALDI-TOF MS has also been successfully applied to bacterial typing.

Conclusions

MALDI-TOF MS is a powerful method for protein analysis. The increase in speed of pathogen detection enables improvement of antimicrobial therapy, infection prevention and control measures leading to positive impact on public health. For antibiotic susceptibility testing and bacterial typing, it represents a rapid alternative to time-consuming conventional techniques.

Modern Tools for Rapid Diagnostics of Antimicrobial Resistance

Fast, robust, and affordable antimicrobial susceptibility testing (AST) is required, as roughly 50% of antibiotic treatments are started with wrong antibiotics and without a proper diagnosis of the pathogen. Validated growth-based AST according to EUCAST or CLSI (European Committee on Antimicrobial Susceptibility Testing, Clinical Laboratory Standards Institute) recommendations is currently suggested to guide the antimicrobial therapy. Any new AST should be validated against these standard methods. Many rapid diagnostic techniques can already provide pathogen identification. Some of them can additionally detect the presence of resistance genes or resistance proteins, but usually isolated pure cultures are needed for AST. We discuss the value of the technologies applying nucleic acid amplification, whole genome sequencing, and hybridization as well as immunodiagnostic and mass spectrometry-based methods and biosensor-based AST. Additionally, we evaluate the potential of integrated systems applying microfluidics to integrate cultivation, lysis, purification, and signal reading steps. We discuss technologies and commercial products with potential for Point-of-Care Testing (POCT) and their capability to analyze polymicrobial samples without pre-purification steps. The purpose of this critical review is to present the needs and drivers for AST development, to show the benefits and limitations of AST methods, to introduce promising new POCT-compatible technologies, and to discuss AST technologies that are likely to thrive in the future.

Identifying isoniazid resistance markers to guide inclusion of high-dose isoniazid in tuberculosis treatment regimens

OBJECTIVES

Effective use of antibiotics is critical to control the global tuberculosis pandemic. High-dose isoniazid (INH) can be effective in the presence of low-level resistance. We performed a systematic literature review to improve our understanding of the differential impact of genomic Mycobacterium tuberculosis (Mtb) variants on the level of INH resistance. The following online databases were searched: PubMed, Web of Science and Embase. Articles reporting on clinical Mtb isolates with linked genotypic and phenotypic data and reporting INH resistance levels were eligible for inclusion.

METHODS

All genomic regions reported in the eligible studies were included in the analysis, including: katG, inhA, ahpC, oxyR-ahpC, furA, fabG1, kasA, rv1592c, iniA, iniB, iniC, rv0340, rv2242 and nat. The level of INH resistance was determined by MIC: low-level resistance was defined as 0.1-0.4 μg/mL on liquid and 0.2-1.0 μg/mL on solid media, high-level resistance as >0.4μg/mL on liquid and >1.0 μg/mL on solid media.

RESULTS

A total of 1212 records were retrieved of which 46 were included. These 46 studies reported 1697 isolates of which 21% (n = 362) were INH susceptible, 17% (n = 287) had low-level, and 62% (n = 1048) high-level INH resistance. Overall, 24% (n = 402) of isolates were reported as wild type and 76% (n = 1295) had ≥1 relevant genetic variant. Among 1295 isolates with ≥1 variant, 78% (n = 1011) had a mutation in the katG gene. Of the 867 isolates with a katG mutation in codon 315, 93% (n = 810) had high-level INH resistance. In contrast, only 50% (n = 72) of the 144 isolates with a katG variant not in the 315-position had high-level resistance. Of the 284 isolates with ≥1 relevant genetic variant and wild type katG gene, 40% (n = 114) had high-level INH resistance.

CONCLUSIONS

Presence of a variant in the katG gene is a good marker of high-level INH resistance only if located in codon 315.

Fast Pathogen Identification Using Single-Cell Matrix-Assisted Laser Desorption/Ionization-Aerosol Time-of-Flight Mass Spectrometry Data and Deep Learning Methods

In diagnostics of infectious diseases, matrix-assisted laser desorption/ionization-time-of-flight mass spectrometry (MALDI-TOF MS) can be applied for the identification of pathogenic microorganisms. However, to achieve a trustworthy identification from MALDI-TOF MS data, a significant amount of biomass should be considered. The bacterial load that potentially occurs in a sample is therefore routinely amplified by culturing, which is a time-consuming procedure. In this paper, we show that culturing can be avoided by conducting MALDI-TOF MS on individual bacterial cells. This results in a more rapid identification of species with an acceptable accuracy. We propose a deep learning architecture to analyze the data and compare its performance with traditional supervised machine learning algorithms. We illustrate our workflow on a large data set that contains bacterial species related to urinary tract infections. Overall we obtain accuracies up to 85% in discriminating five different species.

One System for All: Is Mass Spectrometry a Future Alternative for Conventional Antibiotic Susceptibility Testing?

The two main pillars of clinical microbiological diagnostics are the identification of potentially pathogenic microorganisms from patient samples and the testing for antibiotic susceptibility (AST) to allow efficient treatment with active antimicrobial agents. While routine microbial species identification is increasingly performed with matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS), routine AST still largely relies on conventional and molecular techniques such as broth microdilution or disk and gradient diffusion tests, PCR and automated variants thereof. However, shortly after the introduction of MALDI-TOF MS based routine identification, first attempts to perform AST on the same instruments were reported. Today, a number of different approaches to perform AST with MALDI-TOF MS and other MS techniques have been proposed, some restricted to particular microbial taxa and resistance mechanisms while others being more generic. Further, while some of the methods are in a stage of proof of principles, others are already commercialized. In this review we discuss the different principal approaches of mass spectrometry based AST and evaluate the advantages and disadvantages compared to conventional and molecular techniques. At present, the possibility that MS will soon become a routine tool for AST seems unlikely – still, the same was true for routine microbial identification a mere 15 years ago.

Rapid detection of antibiotic resistance in positive blood cultures by MALDI-TOF MS and an automated and optimized MBT-ASTRA protocol for Escherichia coli and Klebsiella pneumoniae

Introduction: For fast and effective antibiotic therapy of serious infections like sepsis, it is crucial with rapid information about antibiotic susceptibility, especially in a time when the number of infections caused by multi resistant bacteria has escalated in the world.Methods: Here, we have used a semi-quantitative MALDI-TOF-MS based method for antibiotic resistance detection, MBT-ASTRA™, which is based on the comparison of growth rate of the bacteria cultivated with and without antibiotics. We demonstrate a new protocol where several parameters have been optimized and automated leading to reduced hands-on time and improved capacity to simultaneously analyse multiple clinical samples and antibiotics.Results: Ninety minutes of incubation at 37 °C with agitation was sufficient to differentiate the susceptible and resistant strains of E. coli and K. pneumoniae, for the antibiotics cefotaxime, meropenem and ciprofloxacin. In total, 841 positive blood culture analyses of 14 reference strains were performed. The overall sensitivity was 99%, specificity 99% and the accuracy 97%. The assay gave no errors for cefotaxime (n = 263) or meropenem (n = 289) for sensitive and resistant strains, whilst ciprofloxacin (n = 289) gave six (0.7%) major errors (false resistance) and four (0.5%) very major errors (false susceptibility). The intermediate strains showed a larger variety compared to the E-test MIC values.Conclusions: The hands-on time and the analysis time to detect antibiotic resistance of clinical blood samples can be substantially reduced and the sample capacity can be increased by using automation and this improved protocol.

Matrix-Assisted Laser Desorption/Ionization Time-of-Flight: The Revolution in Progress

This article summarizes recent advances in the application of matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) to new areas of infectious diseases diagnostics. We discuss progress toward routine identification of mycobacteria and filamentous fungi and direct identification of pathogens from clinical specimens. Of greatest interest is the use of MALDI-TOF MS for identifying organisms from positive blood cultures and from clinical specimens such as urine. Last, We highlight some exciting new possibilities for MALDI-TOF MS phenotypic susceptibility testing for bacteria and yeast.

Candida auris Identification and Rapid Antifungal Susceptibility Testing Against Echinocandins by MALDI-TOF MS

Candida auris was first reported in an ear swab from Japan in 2009; it then promptly spread over five continents and turned into a global nosocomial problem. The main challenges faced by many researchers are the mis-identification by conventional methods in clinical laboratories and failure in treatment. About 90% of C. auris strains are intrinsically resistant to fluconazole (FLU), and it is developing resistance to multiple classes of available antifungals. Echinocandins are the most potent class of antifungals against C. auris; however, reduced susceptibility to one or many echinocandin drugs has been recently observed. Thus, the main issues addressed in this paper are the fast and accurate identification of C. auris derived from Sabouraud dextrose agar and blood culture bottles as well as the rapid antifungal susceptibility test by MALDI-TOF MS. This study successfully identified all isolates of C. auris (n = 50) by MALDI-TOF MS, with an average log score of ≥ 2. An accuracy of 100% was found on both agar plate and blood culture bottles. MALDI Biotyper antibiotic susceptibility test-rapid assay (MBT ASTRA) was used for rapid antifungal susceptibility testing (AFST). A comparison between MBT ASTRA and the Clinical and Laboratory Standards Institute guidelines (CLSI) detected a sensitivity and specificity of 100% and 98% for anidulafungin, and 100% and 95.5% for micafungin, respectively. A categorical agreement of 98% and 96% was calculated for the two methods. For caspofungin, sensitivity and specificity of 100 and 73% were found, respectively, with a categorical agreement of 82%. MBT ASTRA has the great potential to detect C. auris isolates non-susceptible against echinocandin antifungals within 6 h, which makes it a promising candidate for AFST in clinical laboratories in the future.

Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry for the Rapid Detection of Antimicrobial Resistance Mechanisms and Beyond

Matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) has been successfully applied in recent years for first-line identification of pathogens in clinical microbiology because it is simple to use, rapid, and accurate and has economic benefits in hospital management. The range of clinical applications of MALDI-TOF MS for bacterial isolates is increasing constantly, from species identification to the two most promising applications in the near future: detection of antimicrobial resistance and strain typing for epidemiological studies. The aim of this review is to outline the contribution of previous MALDI-TOF MS studies in relation to detection of antimicrobial resistance and to discuss potential future challenges in this field. Three main approaches are ready (or almost ready) for clinical use, including the detection of antibiotic modifications due to the enzymatic activity of bacteria, the detection of antimicrobial resistance by analysis of the peak patterns of bacteria or mass peak profiles, and the detection of resistance by semiquantification of bacterial growth in the presence of a given antibiotic. This review provides an expert guide for MALDI-TOF MS users to new approaches in the field of antimicrobial resistance detection, especially possible applications as a routine diagnostic tool in microbiology laboratories.

Recent Advances in the Race to Design a Rapid Diagnostic Test for Antimicrobial Resistance

Even with advances in antibiotic therapies, bacterial infections persistently plague society and have amounted to one of the most prevalent issues in healthcare today. Moreover, the improper and excessive administration of antibiotics has led to resistance of many pathogens to prescribed therapies, rendering such antibiotics ineffective against infections. While the identification and detection of bacteria in a patient's sample is critical for point-of-care diagnostics and in a clinical setting, the consequent determination of the correct antibiotic for a patient-tailored therapy is equally crucial. As a result, many recent research efforts have been focused on the development of sensors and systems that correctly guide a physician to the best antibiotic to prescribe for an infection, which can in turn, significantly reduce the instances of antibiotic resistance and the evolution of bacteria "superbugs." This review details the advantages and shortcomings of the recent advances (focusing from 2016 and onward) made in the developments of antimicrobial susceptibility testing (AST) measurements. Detection of antibiotic resistance by genomic AST techniques relies on the prediction of antibiotic resistance via extracted bacterial DNA content, while phenotypic determinations typically track physiological changes in cells and/or populations exposed to antibiotics. Regardless of the method used for AST, factors such as cost, scalability, and assay time need to be weighed into their design. With all of the expansive innovation in the field, which technology and sensing systems demonstrate the potential to detect antimicrobial resistance in a clinical setting?

Rapid antibiotic susceptibility testing on blood cultures using MALDI-TOF MS

Antibiotic resistance is a major public health problem requiring the early optimization of antibiotic prescriptions. Matrix-Assisted Laser Desorption Ionization-Time Of Flight Mass Spectrometry (MALDI-TOF MS) has been shown to accurately identify bacteria from positive blood culture. Here, we developed a rapid detection of Escherichia coli resistance to amoxicillin (AMX) and cefotaxime (CTX) from positive blood culture based on MALDI-TOF MS. Potential sparing of broad-spectrum antibiotics was also evaluated. We tested 103 E. coli-positive blood cultures. Blood cultures were subculture 1-hour in antibiotic-free rich liquid media before further incubation with and without AMX for 2.5 h or CTX for 2 h. Protein extracts associated with an internal control were spotted on a MALDI-TOF target and spectra were analyzed with the MBT-ASTRA prototype software (Bruker Daltonik GmbH, Bremen, Germany). Bacterial growth ratio was calculated from the AUC spectra obtained in the presence and absence of the antibiotic and compared to a threshold which classified E. coli as susceptible or resistant. Results were interpreted with MICs determined using agar dilution method as reference technique. MBT-ASTRA recognized 95% and 84% of the AMX- and CTX-susceptible isolates, respectively. Overall, quantitative analysis of mass spectra allows susceptibility testing within 4 hours after the positivity of blood culture with E. coli. At the first report of positive blood culture, MALDI-TOF MS would then provide the prescribers with the bacterial identification and the susceptibility to AMX and CTX, thus limiting the use of broad-spectrum compounds.

Rapid detection of tetracycline resistance in bovine Pasteurella multocida isolates by MALDI Biotyper antibiotic susceptibility test rapid assay (MBT-ASTRA)

Pasteurella multocida is notorious for its role as an opportunistic pathogen in infectious bronchopneumonia, the economically most important disease facing cattle industry and leading indication for antimicrobial therapy. To rationalize antimicrobial use, avoiding imprudent use of highly and critically important antimicrobials for human medicine, availability of a rapid antimicrobial susceptibility test is crucial. The objective of the present study was to design a MALDI Biotyper antibiotic susceptibility test rapid assay (MBT-ASTRA) procedure for tetracycline resistance detection in P. multocida. This procedure was validated on 100 clinical isolates with MIC-gradient strip test, and a comparison with disk diffusion was made. Sensitivity and specificity of the MBT-ASTRA procedure were 95.7% (95% confidence interval (CI) = 89.8–101.5) and 100% (95% CI = 100–100), respectively, classifying 98% of the isolates correctly after only three hours of incubation. Sensitivity and specificity of disk diffusion were 93.5% (95% CI = 86.3–100.6) and 96.3% (95% CI = 91.3–101.3) respectively, classifying 95% of the isolates correctly. In conclusion, this MBT-ASTRA procedure has all the potential to fulfil the need for a rapid and highly accurate tetracycline susceptibility testing in P. multocida to rationalize antimicrobial use in outbreaks of bronchopneumonia in cattle or other clinical presentations across species.

Proof of Concept for MBT ASTRA, a Rapid Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry (MALDI-TOF MS)-Based Method To Detect Caspofungin Resistance in Candida albicans and Candida glabrata

The incidence of candidemia caused by Candida albicans and Candida glabrata is constantly increasing and is accompanied by the rising use of the few available antifungals. The widespread use of echinocandins and azoles for the treatment of invasive candidemia has enhanced the development of antifungal resistance, resulting in an increasing health care problem. Hence, the rapid detection of resistant strains is required. This study aimed to evaluate the detection of C. albicans and C. glabrata strains resistant to caspofungin by the matrix-assisted laser desorption ionization Biotyper antibiotic susceptibility test rapid assay (MBT ASTRA). This novel semiquantitative technique facilitates the detection of caspofungin-resistant strains within 6 h. MBT ASTRA results were compared to the data obtained by the use of Clinical and Laboratory Standards Institute (CLSI) guidelines. Clinical isolates of C. albicans (n = 58) and C. glabrata (n = 57) were analyzed by MBT ASTRA and the CLSI microdilution method. Antifungal susceptibility testing against caspofungin by the CLSI microdilution method classified the C. albicans isolates into 36 susceptible and 22 resistant strains and the C. glabrata isolates into 5 susceptible, 33 resistant, and 19 intermediate strains. For C. albicans, the comparison of MBT ASTRA and the CLSI method revealed an excellent categorical agreement of 100%. A sensitivity and a specificity between MBT ASTRA and the CLSI microdilution method of 94% and 80%, respectively, were detected for C. glabrata strains, based on categorical agreement. In conclusion, the results obtained by MBT ASTRA indicate that this is a very promising approach for the rapid detection of Candida isolates resistant to caspofungin.

MALDI-TOF mass spectrometry technology for detecting biomarkers of antimicrobial resistance: current achievements and future perspectives

The laboratory diagnosis of infections is based on pathogen identification and antimicrobial susceptibility determination. The gold standard of cultivation, isolation and susceptibility testing is a time-consuming procedure and in some cases this can be threatening for patients' outcome. In the current review the applications of mass spectrometry in pathogen identification and especially in detecting biomarkers of antimicrobial resistance are analyzed. MALDI-TOF (matrix-assisted laser desorption/ionization time-of-flight) mass spectrometry is a new technology that has revolutionized pathogen identification and has also proven to accelerate detection of antimicrobial resistance compared to the traditional antibiotic susceptibility tests (AST) as well as DNA amplification methodologies. The technology has incorporated up to know four different methodologies: (I) the detection of differences of mass spectra of susceptible and resistant isolates of a given microorganism using the classical strain typing methodology; (II) the analysis of bacterial induced hydrolysis of β-lactam antibiotics; (III) the detection of stable (non-radioactive) isotope-labeled amino acids; and (IV) the analysis of bacterial growth in the presence and absence of antibiotics using an internal standard. The implementation of MALDI-TOF methodologies has improved detection of resistance in aerobic, Gram-positive and Gram-negative bacteria, mycobacteria, anaerobic bacteria, fungi and viruses. The MALDI-TOF is an easy to use, rapid, reliable, economical, and environmentally friendly methodology. However, this technology needs further development of research protocols that will be validated for routine application.

A Rapid Growth-Independent Antibiotic Resistance Detection Test by SYBR Green/Propidium Iodide Viability Assay

Antibiotic-resistant bacteria have caused huge concerns and demand innovative approaches for their prompt detection. Current antimicrobial susceptibility tests (AST) rely on the growth of the organisms which takes 1–2 days for fast-growing organisms and several weeks for slow growing organisms. Here, we show for the first time the utility of the SYBR Green I/propidium iodide (PI) viability assay for rapidly identifying antibiotic resistance in less than 30 min for major, antibiotic-resistant, fast-growing bacteria, such as Staphylococcus aureus, Escherichia coli, Klebsiella pneumoniae, and Acinetobacter baumannii for bactericidal and bacteriostatic agents and in 16 h for extremely rapid detection of drug resistance for isoniazid and pyrazinamide in slow-growing Mycobacterium tuberculosis. The SYBR Green I/PI assay generated rapid and robust results in concordance with traditional AST methods. This novel growth-independent methodology changes the concept of the current growth-based AST and may revolutionize current drug susceptibility testing for all cells of prokaryotic and eukaryotic origin and, subject to further clinical validation, may play a major role in saving lives and improving patient outcomes.

MALDI Spectra Database for Rapid Discrimination and Subtyping of Mycobacterium kansasii

Mycobacterium kansasii is an emerging non-tuberculous mycobacterial (NTM) pathogen capable of causing severe lung disease. Of the seven currently recognized M. kansasii genotypes (I-VII), genotypes I and II are most prevalent and have been associated with human disease, whereas the other five (III-VII) genotypes are predominantly of environmental origin and are believed to be non-pathogenic. Subtyping of M. kansasii serves as a valuable tool to guide clinicians in pursuing diagnosis and to initiate the proper timely treatment. Most of the previous rapid diagnostic tests for mycobacteria employing the matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) technology focused on species-level identification. The purpose of this study was to establish MALDI-TOF MS reference spectra database for discrimination of M. kansasii at the genotype level. A panel of 32 strains, representatives of M. kansasii genotypes I-VI were selected, whole cell proteins extracted and measured with MALDI-TOF MS. A unique main spectra (MSP) library was created using MALDI Biotyper Compass Explorer software. The spectra reproducibility was assessed by computing composite correlation index and MSPs cross-matching. One hundred clinical M. kansasii isolates used for testing of the database resulted in 90% identification at genus-level, 7% identification at species-level and 2% identification was below the threshold of log score value 1.7, of which all were correct at genotype level. One strain could not be identified. On the other hand, 37% of strains were identified at species level, 40% at genus level and 23% was not identified with the manufacturer's database. The MALDI-TOF MS was proven a rapid and robust tool to detect and differentiate between M. kansasii genotypes. It is concluded that MALDI-TOF MS has a potential to be incorporated into the routine diagnostic workflow of M. kansasii and possibly other NTM species.

Antimicrobial susceptibility testing of Bacteroides fragilis using the MALDI Biotyper antibiotic susceptibility test rapid assay (MBT-ASTRA)

This study evaluated the MBT-ASTRA for antimicrobial susceptibility testing of Bacteroides fragilis with different classes of antibiotics. MALDI-TOF MS peak AUCs from suspensions with B. fragilis with and without an antibiotic were used to calculate the relative growth (AUC "with antibiotic" divided by "without antibiotic"). Antimicrobial susceptibility testing of B. fragilis ATCC 25285 (susceptible) and B. fragilis O18 (resistant) was demonstrated with a clear difference of the relative growth between susceptible and resistant. The MBT-ASTRA needs further development and assessment but could be a relatively easy and inexpensive method for rapid antimicrobial susceptibility testing in specific cases of infection with B. fragilis.

How to: identify non-tuberculous Mycobacterium species using MALDI-TOF mass spectrometry

BACKGROUND

The implementation of MALDI-TOF MS for microorganism identification has changed the routine of the microbiology laboratories as we knew it. Most microorganisms can now be reliably identified within minutes using this inexpensive, user-friendly methodology. However, its application in the identification of mycobacteria isolates has been hampered by the structure of their cell wall. Improvements in the sample processing method and in the available database have proved key factors for the rapid and reliable identification of non-tuberculous mycobacteria isolates using MALDI-TOF MS.

AIMS

The main objective is to provide information about the proceedings for the identification of non-tuberculous isolates using MALDI-TOF MS and to review different sample processing methods, available databases, and the interpretation of the results.

SOURCES

Results from relevant studies on the use of the available MALDI-TOF MS instruments, the implementation of innovative sample processing methods, or the implementation of improved databases are discussed.

CONTENT

Insight about the methodology required for reliable identification of non-tuberculous mycobacteria and its implementation in the microbiology laboratory routine is provided.

IMPLICATIONS

Microbiology laboratories where MALDI-TOF MS is available can benefit from its capacity to identify most clinically interesting non-tuberculous mycobacteria in a rapid, reliable, and inexpensive manner.

Semi-quantitative MALDI-TOF for antimicrobial susceptibility testing in Staphylococcus aureus

Antibiotic resistant bacterial infections are a significant problem in the healthcare setting, in many cases requiring the rapid administration of appropriate and effective antibiotic therapy. Diagnostic assays capable of quickly and accurately determining the pathogen resistance profile are therefore crucial to initiate or modify care. Matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry (MS) is a standard method for species identification in many clinical microbiology laboratories and is well positioned to be applied towards antimicrobial susceptibility testing. One recently reported approach utilizes semi-quantitative MALDI-TOF MS for growth rate analysis to provide a resistance profile independent of resistance mechanism. This method was previously successfully applied to Gram-negative pathogens and mycobacteria; here, we evaluated this method with the Gram-positive pathogen Staphylococcus aureus. Specifically, we used 35 strains of S. aureus and four antibiotics to optimize and test the assay, resulting in an overall accuracy rate of 95%. Application of the optimized assay also successfully determined susceptibility from mock blood cultures, allowing both species identification and resistance determination for all four antibiotics within 3 hours of blood culture positivity.