Vitek® MS v3.0 System in the Identification of Filamentous Fungi

Identification of Food Spoilage Fungi Using MALDI-TOF MS: Spectral Database Development and Application to Species Complex

Fungi, including filamentous fungi and yeasts, are major contributors to global food losses and waste due to their ability to colonize a very large diversity of food raw materials and processed foods throughout the food chain. In addition, numerous fungal species are mycotoxin producers and can also be responsible for opportunistic infections. In recent years, MALDI-TOF MS has emerged as a valuable, rapid and reliable asset for fungal identification in order to ensure food safety and quality. In this context, this study aimed at expanding the VITEK® MS database with food-relevant fungal species and evaluate its performance, with a specific emphasis on species differentiation within species complexes. To this end, a total of 380 yeast and mold strains belonging to 51 genera and 133 species were added into the spectral database including species from five species complexes corresponding to Colletotrichum acutatum, Colletotrichum gloeosporioides, Fusarium dimerum, Mucor circinelloides complexes and Aspergillus series nigri. Database performances were evaluated by cross-validation and external validation using 78 fungal isolates with 96.55% and 90.48% correct identification, respectively. This study also showed the capacity of MALDI-TOF MS to differentiate closely related species within species complexes and further demonstrated the potential of this technique for the routine identification of fungi in an industrial context.

Scedosporiosis and lomentosporiosis: modern perspectives on these difficult-to-treat rare mold infections

SUMMARYAlthough Scedosporium species and Lomentospora prolificans are uncommon causes of invasive fungal diseases (IFDs), these infections are associated with high mortality and are costly to treat with a limited armamentarium of antifungal drugs. In light of recent advances, including in the area of new antifungals, the present review provides a timely and updated overview of these IFDs, with a focus on the taxonomy, clinical epidemiology, pathogenesis and host immune response, disease manifestations, diagnosis, antifungal susceptibility, and treatment. An expansion of hosts at risk for these difficult-to-treat infections has emerged over the last two decades given the increased use of, and broader population treated with, immunomodulatory and targeted molecular agents as well as wider adoption of antifungal prophylaxis. Clinical presentations differ not only between genera but also across the different Scedosporium species. L. prolificans is intrinsically resistant to most currently available antifungal agents, and the prognosis of immunocompromised patients with lomentosporiosis is poor. Development of, and improved access to, diagnostic modalities for early detection of these rare mold infections is paramount for timely targeted antifungal therapy and surgery if indicated. New antifungal agents (e.g., olorofim, fosmanogepix) with novel mechanisms of action and less cross-resistance to existing classes, availability of formulations for oral administration, and fewer drug-drug interactions are now in late-stage clinical trials, and soon, could extend options to treat scedosporiosis/lomentosporiosis. Much work remains to increase our understanding of these infections, especially in the pediatric setting. Knowledge gaps for future research are highlighted in the review.

Evaluation of the Autof ms1000 mass spectrometry for rapid clinical identification of filamentous fungi

BACKGROUND

Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) has revolutionized microbial identification. However, there is a lack of data on its performance in identifying filamentous fungi. The objective of our study was to evaluate the accuracy of the Autof ms1000 mass spectrometry for identifying filamentous fungi in the clinical microbiology laboratory.

RESULTS

Among 106 samples tested using the Autof ms1000 system, 101 (95.28%) were identified at the genus or species level, and 81 (76.41%) were accurately identified at the species level. Additionally, we developed a new rapid formic acid extraction method with simple pretreatment for filamentous fungi that saved time and provided accurate results.

CONCLUSIONS

The Autof ms1000 mass spectrometer proved to be a valuable tool for identifying filamentous fungi. However, upgrading the database is recommended for correctly identifying rare strains.

A Practical Workflow for the Identification of Aspergillus, Fusarium, Mucorales by MALDI-TOF MS: Database, Medium, and Incubation Optimization

There is an increasing body of literature on the utility of MALDI-TOF MS in the identification of filamentous fungi. However, the process still lacks standardization. In this study, we attempted to establish a practical workflow for the identification of three clinically important molds: Aspergillus, Fusarium, and Mucorales using MALDI-TOF MS. We evaluated the performance of Bruker Filamentous Fungi database v3.0 for the identification of these fungi, highlighting when there would be a benefit of using an additional database, the MSI-2 for further identification. We also examined two other variables, namely, medium effect and incubation time on the accuracy of fungal identification. The Bruker database achieved correct species level identification in 85.7% of Aspergillus and 90% of Mucorales, and correct species-complex level in 94.4% of Fusarium. Analysis of spectra using the MSI-2 database would also offer additional value for species identification of Aspergillus species, especially when suspecting species with known identification limits within the Bruker database. This issue would only be of importance in selected cases where species-level identification would impact therapeutic options. Id-Fungi plates (IDFP) had almost equivalent performance to Sabouraud dextrose agar (SDA) for species-level identification of isolates and enabled an easier harvest of the isolates with occasional faster identification. Our study showed accurate identification at 24 h for Fusarium and Mucorales species, but not for Aspergillus species, which generally required 48 h.

The application of mass spectrometry method for the study and identification of medically important viruses (review of literature)

It is difficult to overestimate the urgency of the problem of well-timed diagnosis of viral infections. According to the WHO, dozens of outbreaks of viral diseases are recorded annually, both in developing and developed countries. Moreover, the seasonal flu virus alone is capable of infecting up to 20% of the population, even in European countries with a high level of medicine. And the annual number of deaths due to viral infections, according to official statistics, exceeds 600 thousand people around the world. That's why the provision of a reliable and fairly rapid diagnosis of viruses, along with subsequent therapy, makes a significant contribution to reducing the incidence of mortality. Despite the fact that PCR-based methods currently remain the most common method for identifying viruses in clinical practice, as recent experience shows, in addition to the already known disadvantages, in the event of large outbreaks, such test systems may simply not be in the required amount. In this regard, it is necessary to supplement and improve the existing tools for identification and research of clinically significant viruses. The MALDI-TOF mass spectrometry method combines a degree of accuracy and versatility, sufficient both for the identification of clinical strains isolated from patients, and for the study of the phenotypic properties of viruses in research laboratories and centers. This article presents and summarizes the main data on the existing or potential application of the method of time-of-flight mass spectrometry with matrix-associated laser desorption / ionization for the identification or study of viruses.

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.

Matrix-Assisted Laser Desorption Ionization Time-of-Flight for Fungal Identification

Many studies have shown successful performance of matrix-assisted laser desorption ionization time-of-flight mass spectrometry for rapid yeast and mold identification, yet few laboratories have chosen to apply this technology into their routine clinical mycology workflow. This review provides an overview of the current status of matrix-assisted laser desorption ionization time-of-flight mass spectrometry for fungal identification, including key findings in the literature, processing and database considerations, updates in technology, and exciting future prospects. Significant advances toward standardization have taken place recently; thus, accurate species-level identification of yeasts and molds should be highly attainable, achievable, and practical in most clinical laboratories.

Scedosporium and Lomentospora Infections: Contemporary Microbiological Tools for the Diagnosis of Invasive Disease

Scedosporium/Lomentospora fungi are increasingly recognized pathogens. As these fungi are resistant to many antifungal agents, early diagnosis is essential for initiating targeted drug therapy. Here, we review the microbiological tools for the detection and diagnosis of invasive scedosporiosis and lomentosporiosis. Of over 10 species, Lomentospora prolificans, Scedosporium apiospermum, S. boydii and S. aurantiacum cause the majority of infections. Definitive diagnosis relies on one or more of visualization, isolation or detection of the fungus from clinical specimens by microscopy techniques, culture and molecular methods such as panfungal PCR or genus-/species-specific multiplex PCR. For isolation from respiratory tract specimens, selective media have shown improved isolation rates. Species identification is achieved by macroscopic and microscopic examination of colonies, but species should be confirmed by ITS with or without β-tubulin gene sequencing or other molecular methods. Matrix-assisted laser desorption ionization-time of flight mass spectrometry databases are improving but may need supplementation by in-house spectra for species identification. Reference broth microdilution methods is preferred for antifungal susceptibility testing. Next-generation sequencing technologies have good potential for characterization of these pathogens. Diagnosis of Scedosporium/Lomentospora infections relies on multiple approaches encompassing both phenotypic- and molecular-based methods.

Update on Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry Identification of Filamentous Fungi

Matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS)-based species identification has found its place in many clinical routine diagnostic laboratories over the past years, allowing significantly reduced turnaround times and high-precision results. With regard to MALDI-TOF MS for filamentous fungi, here, we discuss different approaches for sample processing and growth conditions before analysis. In particular, we review the performances of different commercially available databases as well as the potential of complementary (self-constructed) in-house databases.