A conceptual framework for nomenclatural stability and validity of medically important fungi: a proposed global consensus guideline for fungal name changes supported by ABP, ASM, CLSI, ECMM, ESCMID-EFISG, EUCAST-AFST, FDLC, IDSA, ISHAM, MMSA, and MSGERC

Implication of genotypes for prognosis of Candida glabrata bloodstream infections

BACKGROUND

Genotyping isolates of a specific pathogen may demonstrate unique patterns of antimicrobial resistance, virulence or outcomes. However, evidence for genotype-outcome association in Candida glabrata is scarce. We aimed to characterize the mycological and clinical relevance of genotypes on C. glabrata bloodstream infections (BSIs).

METHODS

Non-duplicated C. glabrata blood isolates from hospitalized adults were genotyped by MLST, and further clustered by the unweighted pair group method with arithmetic averages (UPGMA). A clonal complex (CC) was defined by UPGMA similarities of >90%. Antifungal susceptibility testing was performed by a colorimetric microdilution method and interpreted following CLSI criteria.

RESULTS

Of 48 blood isolates evaluated, 13 STs were identified. CC7 was the leading CC (n = 14; 29.2%), including 13 ST7. The overall fluconazole and echinocandin resistance rates were 6.6% and 0%, respectively. No specific resistance patterns were associated with CC7 or other CCs. Charlson comorbidity index (adjusted OR, 1.49; 95% CI, 1.05-3.11) was the only predictor for CC7. By multivariable Cox regression analyses, CC7 was independently associated with 28 day mortality [adjusted HR (aHR), 3.28; 95% CI, 1.31-8.23], even after considering potential interaction with neutropenia (aHR, 3.41; 95% CI, 1.23-9.42; P for interaction, 0.24) or limited to 34 patients with monomicrobial BSIs (aHR, 2.85; 95% CI, 1.15-7.08). Also, the Kaplan-Meier estimate showed greater mortality with CC7 (P = 0.003). Fluconazole resistance or echinocandin therapy had no significant impact on mortality.

CONCLUSIONS

Our data suggested comorbid patients were at risk of developing CC7 BSIs. Further, CC7 was independently associated with worse outcomes.

Universal digital high-resolution melting for the detection of pulmonary mold infections

Invasive mold infections (IMIs) are associated with high morbidity, particularly in immunocompromised patients, with mortality rates between 40% and 80%. Early initiation of appropriate antifungal therapy can substantially improve outcomes, yet early diagnosis remains difficult to establish and often requires multidisciplinary teams evaluating clinical and radiological findings plus supportive mycological findings. Universal digital high-resolution melting (U-dHRM) analysis may enable rapid and robust diagnoses of IMI. A universal fungal assay was developed for U-dHRM and used to generate a database of melt curve signatures for 19 clinically relevant fungal pathogens. A machine learning algorithm (ML) was trained to automatically classify these pathogen curves and detect novel melt curves. Performance was assessed on 73 clinical bronchoalveolar lavage samples from patients suspected of IMI. Novel curves were identified by micropipetting U-dHRM reactions and Sanger sequencing amplicons. U-dHRM achieved 97% overall fungal organism identification accuracy and a turnaround time of ~4 hrs. U-dHRM detected pathogenic molds (Aspergillus, Mucorales, Lomentospora, and Fusarium) in 73% of 30 samples classified as IMI, including mixed infections. Specificity was optimized by requiring the number of pathogenic mold curves detected in a sample to be >8 and a sample volume to be 1 mL, which resulted in 100% specificity in 21 at-risk patients without IMI. U-dHRM showed promise as a separate or combination diagnostic approach to standard mycological tests. U-dHRM's speed, ability to simultaneously identify and quantify clinically relevant mold pathogens in polymicrobial samples, and detect emerging opportunistic pathogens may aid treatment decisions, improving patient outcomes.

IMPORTANCE

Improvements in diagnostics for invasive mold infections are urgently needed. This work presents a new molecular detection approach that addresses technical and workflow challenges to provide fast pathogen detection, identification, and quantification that could inform treatment to improve patient outcomes.

Phylogenomic approaches reveal a robust time-scale phylogeny of the Terminal Fusarium Clade

The Terminal Fusarium Clade (TFC) is a group in the Nectriaceae family with agricultural and clinical relevance. In recent years, various phylogenies have been presented in the literature, showing disagreement in the topologies, but only a few studies have conducted analyses on the divergence time scale of the group. Therefore, the evolutionary history of this group is still being determined. This study aimed to understand the evolutionary history of the TFC from a phylogenomic perspective. To achieve this objective, we performed a phylogenomic analysis using the available genomes in GenBank and ran eight different pipelines. We presented a new robust topology of the TFC that differs at some nodes from previous studies. These new relationships allowed us to formulate new hypotheses about the evolutionary history of the TFC. We also inferred new divergence time estimates, which differ from those of previous studies due to topology discordances and taxon sampling. The results suggested an important diversification process in the Neogene period, likely associated with the diversification and predominance of terrestrial ecosystems by angiosperms. In conclusion, we presented a robust time-scale phylogeny that allowed us to formulate new hypotheses regarding the evolutionary history of the TFC.

Fungal diversity in the soil Mycobiome: Implications for ONE health

Today, over 300 million individuals worldwide are afflicted by severe fungal infections, many of whom will perish. Fungi, as a result of their plastic genomes have the ability to adapt to new environments and extreme conditions as a consequence of globalization, including urbanization, agricultural intensification, and, notably, climate change. Soils and the impact of these anthropogenic environmental factors can be the source of pathogenic and non-pathogenic fungi and subsequent fungal threats to public health. This underscores the growing understanding that not only is fungal diversity in the soil mycobiome a critical component of a functioning ecosystem, but also that soil microbial communities can significantly contribute to plant, animal, and human health, as underscored by the One Health concept. Collectively, this stresses the importance of investigating the soil microbiome in order to gain a deeper understanding of soil fungal ecology and its interplay with the rhizosphere microbiome, which carries significant implications for human health, animal health and environmental health.

The yeast genus Tardiomyces gen. nov. with one new species and two new combinations

PURPOSE

Rare yeasts species are increasingly reported as causative agents of invasive human infection. Proper identification and antifungal therapy are essential to manage these infections. Candida blankii is one of these emerging pathogens and is known for its reduced susceptibility to multiple antifungals.

METHODS

To obtain more insight into the characteristics of this species, 26 isolates reported as C. blankii were investigated using genetic and phenotypical approaches.

RESULTS

Among the 26 isolates, seven recovered either from blood, sputum, urine, or the oral cavity, displayed substantial genetic and some phenotypical differences compared to the other isolates, which were confirmed as C. blankii. We consider these seven strains to represent a novel species, Tardiomyces depauwii. Phylogenomics assigned C. blankii, C. digboiensis, and the novel species in a distinct branch within the order Dipodascales, for which the novel genus Tardiomyces is erected. The new combinations Tardiomyces blankii and Tardiomyces digboiensis are introduced. Differences with related, strictly environmental genera Sugiyamaella, Crinitomyces, and Diddensiella are enumerated. All three Tardiomyces species share the rare ability to grow up to 42 °C, display slower growth in nutrient-poor media, and show a reduced susceptibility to azoles and echinocandins. Characteristics of T. depauwii include high MIC values with voriconazole and a unique protein pattern.

CONCLUSION

We propose the novel yeast species Tardiomyces depauwii and the transfer of C. blankii and C. digboiensis to the novel Tardiomyces genus.

MycoNews 2023: Editorial, news, reports, awards, personalia, and book news

This fifth annual edition of MycoNews starts with an editorial on the critical importance of International Mycological Congresses (IMCs) to the health of mycology. Items on Counting down to IMC12, the State of the World's Plants and Fungi 2023, and progress towards Improving nomenclatural stability in medically important fungi follow. Reports are provided of several mycological meetings in 2023: the Asian Mycological Congress, XIX Congress of European Mycologists, a meeting of European Mycological Groups and Societies, the XI Latin American Mycological Congress, Westerdijk Spring Symposium on Fungal Evolution, the Brazilian Society of Mycology, the Annual Meeting of the Mycological Society of China, and the Fifth Iranian Mycological Congress. Information is provided on how to make nominations for the various IMA Awards due to be presented at IMC12 in August, the new Future is Fungi Award launched in 2023, and the Adel-Azeem and Stamets Award for work on Psilocybe in Africa. The Westerdijk Fungal Biodiversity Institute Awards for 2023 were made to Andrey Yurkov and Cathie Aime and the citations to those awards are provided. We include tributes to the passing of two eminent mycologists, Lorelei Norvell and Takashi Matsushima, and also send birthday greetings to Bryce Kendrick who turned 90, and Maria Ławrynowicz, Yu Li, and Anthony Whalley who all became octogenarians. Reviews of seven mycological books published in 2022-2023 are included in the Book News section.

Molecular typing and antifungal susceptibility profile of Candida krusei bloodstream isolates from Türkiye

Candida krusei also known as Pichia kudriavzevii is a potentially multidrug-resistant yeast because it is intrinsically resistant to fluconazole and develops acquired resistance to echinocandins and polyenes. Here, we aim to provide a better understanding of the epidemiology and transmission modes of C. krusei infections by comparing invasive bloodstream (n = 35) and non-invasive vaginal (n = 20) C. krusei isolates. The genetic relatedness of the isolates was assessed using a newly described short tandem repeat (STR) analysis and their sensitivity to eight antifungal compounds was evaluated by antifungal susceptibility testing using the CLSI microbroth dilution method. All C. krusei isolates revealed unique STR genotypes, indicating the absence of clonal transmission in the study group. Furthermore, no drug-resistant or non-wild-type isolates were identified. Our findings demonstrated high resolution of STR genotyping for the detection and simultaneous genetic analysis of multiple C. krusei strains in clinical samples and excellent in vitro activity of common antifungal agents against invasive strains.

Morphological and phylogenetic analyses reveal three new species of Fusarium (Hypocreales, Nectriaceae) associated with leaf blight on Cunninghamialanceolata in China

Chinese fir (Cunninghamialanceolata) is a special fast-growing commercial tree species in China with high economic value. In recent years, leaf blight disease on C.lanceolata has been observed frequently. The diversity of Fusarium species associated with leaf blight on C.lanceolata in China (Fujian, Guangxi, Guizhou, and Hunan provinces) was evaluated using morphological study and molecular multi-locus analyses based on RNA polymerase second largest subunit (RPB2), translation elongation factor 1-alpha (TEF-1α), and RNA polymerase largest subunit (RPB1) genes/region as well as the pairwise homoplasy index tests. A total of five Fusarium species belonging to four Fusarium species complexes were recognized in this study. Two known species including Fusariumconcentricum and F.fujikuroi belonged to the F.fujikuroi species complex, and three new Fusarium species were described, i.e., F.fujianense belonged to the F.lateritium species complex, F.guizhouense belonged to the F.sambucinum species complex, and F.hunanense belonged to the F.solani species complex. To prove Koch's postulates, pathogenicity tests on C.lanceolata revealed a wide variation in pathogenicity and aggressiveness among the species, of which F.hunanense HN33-8-2 caused the most severe symptoms and F.fujianense LC14 led to the least severe symptoms. To our knowledge, this study also represented the first report of F.concentricum, F.fujianense, F.fujikuroi, F.guizhouense, and F.hunanense causing leaf blight on C.lanceolata in China.

Universal Digital High Resolution Melt for the detection of pulmonary mold infections

Background

Invasive mold infections (IMIs) such as aspergillosis, mucormycosis, fusariosis, and lomentosporiosis are associated with high morbidity and mortality, particularly in immunocompromised patients, with mortality rates as high as 40% to 80%. Outcomes could be substantially improved with early initiation of appropriate antifungal therapy, yet early diagnosis remains difficult to establish and often requires multidisciplinary teams evaluating clinical and radiological findings plus supportive mycological findings. Universal digital high resolution melting analysis (U-dHRM) may enable rapid and robust diagnosis of IMI. This technology aims to accomplish timely pathogen detection at the single genome level by conducting broad-based amplification of microbial barcoding genes in a digital polymerase chain reaction (dPCR) format, followed by high-resolution melting of the DNA amplicons in each digital reaction to generate organism-specific melt curve signatures that are identified by machine learning.

Methods

A universal fungal assay was developed for U-dHRM and used to generate a database of melt curve signatures for 19 clinically relevant fungal pathogens. A machine learning algorithm (ML) was trained to automatically classify these 19 fungal melt curves and detect novel melt curves. Performance was assessed on 73 clinical bronchoalveolar lavage (BAL) samples from patients suspected of IMI. Novel curves were identified by micropipetting U-dHRM reactions and Sanger sequencing amplicons.

Results

U-dHRM achieved an average of 97% fungal organism identification accuracy and a turn-around-time of 4hrs. Pathogenic molds (Aspergillus, Mucorales, Lomentospora and Fusarium) were detected by U-dHRM in 73% of BALF samples suspected of IMI. Mixtures of pathogenic molds were detected in 19%. U-dHRM demonstrated good sensitivity for IMI, as defined by current diagnostic criteria, when clinical findings were also considered.

Conclusions

U-dHRM showed promising performance as a separate or combination diagnostic approach to standard mycological tests. The speed of U-dHRM and its ability to simultaneously identify and quantify clinically relevant mold pathogens in polymicrobial samples as well as detect emerging opportunistic pathogens may provide information that could aid in treatment decisions and improve patient outcomes.