Online Databases for Taxonomy and Identification of Pathogenic Fungi and Proposal for a Cloud-Based Dynamic Data Network Platform

Diagnosis and Treatment Challenges of Candida guilliermondii in Immunocompromised Patients: A Case Study in a Neutropenic AML Patient

Although fungal infections causing intestinal perforation and necrosis are rare, they can be particularly dangerous in immunosuppressed patients, often leading to increased mortality rates and poor prognoses. Candida species are typically surface fungi, but in patients with compromised immune systems, they can invade the small intestine and cause angioinvasive infections. A case study involving a 30-year-old female with acute myeloid leukemia (AML) illustrates this phenomenon. The patient was presented with symptoms of abdominal pain, fever, diarrhea, recurrent episodes of intestinal necrosis, hematomas due to thrombocytopenia, and subsequent postoperative enterocutaneous fistulas. Extensive testing ruled out other possible causes of intestinal necrosis and enteritis, including Crohn's and CMV diseases. Candida guilliermondi was ultimately identified in blood cultures from the periphery, peritoneal fluid, and intestinal biopsy of respected sections, indicating that it was responsible for intestinal invasion and necrosis. The patient was then treated with amphotericin B, cefepime, and metronidazole. This case highlights the potential severity of fungal infections in immunosuppressed patients, particularly Candida species, and the importance of prompt diagnosis and appropriate treatment.

Artificial Intelligence: Exploring utility in detection and typing of fungus with futuristic application in fungal cytology

Artificial Intelligence (AI) is an emerging, transforming and revolutionary technology that has captured attention worldwide. It is translating research into precision oncology treatments. AI can analyse large or big data sets requiring high-speed specialized computing solutions. The data are big in terms of volume and multimodal with the amalgamation of images, text and structure. Machine learning has identified antifungal drug targets, and taxonomic and phylogenetic classification of fungi based on sequence analysis is now available. Real-time identification tools and user-friendly mobile applications for identifying fungi have been discovered. Akin to histopathology, AI can be applied to fungal cytology. AI has been fruitful in cytopathology of the thyroid gland, breast, urine and uterine cervical lesions. AI has a huge scope in fungal cytology and would certainly bear fruit with its accuracy, reproducibility and capacity for handling big data. The purpose of this systematic review was to highlight the AI's utility in detecting fungus and its typing with a special focus on future application in fungal cytology. We also touch upon the basics of AI in brief.

Development of a novel mycobiome diagnostic for fungal infection

BACKGROUND

Amplicon-based mycobiome analysis has the potential to identify all fungal species within a sample and hence could provide a valuable diagnostic assay for use in clinical mycology settings. In the last decade, the mycobiome has been increasingly characterised by targeting the internal transcribed spacer (ITS) regions. Although ITS targets give broad coverage and high sensitivity, they fail to provide accurate quantitation as the copy number of ITS regions in fungal genomes is highly variable even within species. To address these issues, this study aimed to develop a novel NGS fungal diagnostic assay using an alternative amplicon target.

METHODS

Novel universal primers were designed to amplify a highly diverse single copy and uniformly sized DNA target (Tef1) to enable mycobiome analysis on the Illumina iSeq100 which is a low cost, small footprint and simple to use next-generation sequencing platform. To enable automated analysis and rapid results, a streamlined bioinformatics workflow and sequence database were also developed. Sequencing of mock fungal communities was performed to compare the Tef1 assay and established ITS1-based method. The assay was further evaluated using clinical respiratory samples and the feasibility of using internal spike-in quantitative controls was assessed.

RESULTS

The Tef1 assay successfully identified and quantified Aspergillus, Penicillium, Candida, Cryptococcus, Rhizopus, Fusarium and Lomentospora species from mock communities. The Tef1 assay was also capable of differentiating closely related species such as A. fumigatus and A. fischeri. In addition, it outperformed ITS1 at identifying A. fumigatus and other filamentous pathogens in mixed fungal communities (in the presence or absence of background human DNA). The assay could detect as few as 2 haploid genome equivalents of A. fumigatus from clinical respiratory samples. Lastly, spike-in controls were demonstrated to enable semi-quantitation of A. fumigatus load in clinical respiratory samples using sequencing data.

CONCLUSIONS

This study has developed and tested a novel metabarcoding target and found the assay outperforms ITS1 at identifying clinically relevant filamentous fungi. The assay is a promising diagnostic candidate that could provide affordable NGS analysis to clinical mycology laboratories.

Nanopore sequencing of full rRNA operon improves resolution in mycobiome analysis and reveals high diversity in both human gut and environments

High-throughput sequencing has substantially improved our understanding of fungal diversity. However, the short read (<500 bp) length of current second-generation sequencing approaches provides limited taxonomic and phylogenetic resolution for species discrimination. Longer sequences containing more information are highly desired to provide greater taxonomic resolution. Here, we amplified full-length rRNA operons (~5.5 kb) and established a corresponding fungal rRNA operon database for ONT sequences (FRODO), which contains ONT sequences representing eight phyla, 41 classes, 109 orders, 256 families, 524 genera and 1116 species. We also benchmarked the optimal method for sequence classification and determined that the RDP classifier based on our FRODO database was capable of improving the classification of ONT reads, with an average of 98%-99% reads correctly classified at the genus or species level. We investigated the applicability of our approach in three representative mycobiomes, namely, the soil, marine and human gut mycobiomes, and found that the gut contains the largest number of unknown species (over 90%), followed by the marine (42%) and soil (33.8%) mycobiomes. We also observed a distinct difference in the composition of the marine and soil mycobiomes, with the highest richness and diversity detected in soils. Overall, our study provides a systematic approach for mycobiome studies and revealed that the previous methods might have underestimated the diversity of mycobiome species. Future application of this method will lead to a better understanding of the taxonomic and functional diversity of fungi in environmental and health-related mycobiomes.

Yeast metagenomics: analytical challenges in the analysis of the eukaryotic microbiome

Even if their impact is often underestimated, yeasts and yeast-like fungi represent the most prevalent eukaryotic members of microbial communities on Earth. They play numerous roles in natural ecosystems and in association with their hosts. They are involved in the food industry and pharmaceutical production, but they can also cause diseases in other organisms, making the understanding of their biology mandatory. The ongoing loss of biodiversity due to overexploitation of environmental resources is a growing concern in many countries. Therefore, it becomes crucial to understand the ecology and evolutionary history of these organisms to systematically classify them. To achieve this, it is essential that our knowledge of the mycobiota reaches a level similar to that of the bacterial communities. To overcome the existing challenges in the study of fungal communities, the first step should be the establishment of standardized techniques for the correct identification of species, even from complex matrices, both in wet lab practices and in bioinformatic tools.

Next-generation fungal identification using target enrichment and Nanopore sequencing

BACKGROUND

Rapid and accurate pathogen identification is required for disease management. Compared to sequencing entire genomes, targeted sequencing may be used to direct sequencing resources to genes of interest for microbe identification and mitigate the low resolution that single-locus molecular identification provides. This work describes a broad-spectrum fungal identification tool developed to focus high-throughput Nanopore sequencing on genes commonly employed for disease diagnostics and phylogenetic inference.

RESULTS

Orthologs of targeted genes were extracted from 386 reference genomes of fungal species spanning six phyla to identify homologous regions that were used to design the baits used for enrichment. To reduce the cost of producing probes without diminishing the phylogenetic power, DNA sequences were first clustered, and then consensus sequences within each cluster were identified to produce 26,000 probes that targeted 114 genes. To test the efficacy of our probes, we applied the technique to three species representing Ascomycota and Basidiomycota fungi. The efficiency of enrichment, quantified as mean target coverage over the mean genome-wide coverage, ranged from 200 to 300. Furthermore, enrichment of long reads increased the depth of coverage across the targeted genes and into non-coding flanking sequence. The assemblies generated from enriched samples provided well-resolved phylogenetic trees for taxonomic assignment and molecular identification.

CONCLUSIONS

Our work provides data to support the utility of targeted Nanopore sequencing for fungal identification and provides a platform that may be extended for use with other phytopathogens.

Fungal taxonomy: A puzzle with many missing pieces

Fungi are multifaceted organisms found in almost all ecosystems on Earth, where they establish various types of symbiosis with other living beings. Despite being recognized by humans since ancient times, and the high number of works delving into their biology and ecology, much is still unknown about these organisms. Some criteria classically used for their study are nowadays limited, generating confusion in categorizing them, and even more, when trying to understand their genealogical relationships. To identify species within Fungi, phenotypic characters to date are not sufficient, and to construct a broad phylogeny or a phylogeny of a particular group, there are still gaps affecting the generated trees, making them unstable and easily debated. For health professionals, fungal identification at lower levels such as genus and species, is enough to select the most appropriate therapy for their control, understand the epidemiology of clinical pictures associated, and recognize outbreaks and antimicrobial resistance. However, the taxonomic location within the kingdom, information with apparently little relevance, can allow phylogenetic relationships to be established between fungal taxa, facilitating the understanding of their biology, distribution in nature, and pathogenic potential evolution. Advances in molecular biology and computer science techniques from the last 30 years have led to crucial changes aiming to establish the criteria to define a fungal species, allowing us to reach a kind of stable phylogenetic construction. However, there is still a long way to go, and it requires the joint work of the scientific community at a global level and support for basic research.

Updates in Laboratory Identification of Invasive Fungal Infection in Neonates

Invasive fungal infection (IFI) in immunocompromised neonates is significantly associated with high morbidity and mortality and has become the third most common infection in Neonatal Intensive Care Units. The early diagnosis of IFI for neonatal patients is difficult because of the lack of specific symptoms. The traditional blood culture remains the gold standard in clinical diagnosis for neonatal patients but it requires a long duration, which delays treatment initiation. Detections of fungal cell-wall components are developed for early diagnosis but the diagnostic accuracy in neonates needs to be improved. PCR-based laboratory methods, such as real-time PCR, droplet digital PCR, and the cationic conjugated polymer fluorescence resonance energy transfer (CCP-FRET) system, distinguish the infected fungal species by their specific nucleic acids and show a high sensitivity and specificity. Particularly, the CCP-FRET system, which contains a cationic conjugated polymer (CCP) fluorescent probe and pathogen-specific DNA labeled with fluorescent dyes, could identify multiple infections simultaneously. In the CCP-FRET system, the CCP and fungal DNA fragments can self-assemble into a complex with an electrostatic interaction and the CCP triggers the FRET effect under ultraviolet light to make the infection visible. Here, we summarize the recent laboratory methods for neonatal IFI identification and provide a new perspective for early clinical fungal diagnosis.

Epiphitic Microbiome of Alvarinho Wine Grapes from Different Geographic Regions in Portugal

Geographic location and, particularly, soil and climate exert influence on the typicality of a wine from a specific region, which is often justified by the terroir, and these factors also influence the epiphytic flora associated with the surface of the grape berries. In the present study, the microbiome associated with the surface of berries obtained from ten vineyards of the Alvarinho variety located in different geographical locations in mainland Portugal was determined and analyzed. The removal of microbial flora from the surface of the berries was carried out by washing and sonication, after which the extraction and purification of the respective DNA was carried out. High-throughput short amplicon sequencing of the fungal ITS region and the bacterial 16S region was performed, allowing for the determination of the microbial consortium associated with Alvarinho wine grapes. Analysis of α-diversity demonstrated that parcels from the Monção and Melgaço sub-region present a significantly (p < 0.05) lower fungal diversity and species richness when compared to the plots analyzed from other regions/sub-regions. The ubiquitous presence of Metschnikowia spp., a yeast with enologic potential interest in all parcels from Monção and Melgaço, was also observed.

Diversity, Distribution, and Host Plant of Endophytic Fungi: A Focus on Korea

Endophytic fungi occupy inner plant tissues, which results in various interactions between the fungus and host. Studies on endophytic fungi have been conducted in Korea for over 30 years. This paper summarizes the published results of those studies. The endophytic fungi of approximately 132 plant species in Korea have been studied since the 1990s, resulting in over 118 publications. The host plants featured in these studies comprised 3 species of mosses, 34 species of woody plants, and 95 species of herbaceous plants. At the family level, the most studied plants were members of the Poaceae family, covering 18 species. Regionally, these studies were conducted throughout Korea, but over half of the studies were conducted in Gyeongsangbuk-do, Gangwon-do, and Chungcheongnam-do. Relatively few studies have been conducted in a metropolis such as Seoul. We confirmed 5 phyla, 16 classes, 49 orders, 135 families, 305 genera, and 855 taxa of endophytic fungi, excluding Incertae sedis, whose relationship with others are unknown. Most of the endophytic fungi belonged to Ascomycota (93.2%), and a few belonged to Basidiomycota (3.6%). Since the diversity of endophytic fungi differs depending on the host plant, plant tissue, and distribution region, future studies should be conducted on multiple host plants and in various regions. Future studies on endophytic fungi are expected to broaden, including genomics and taxonomic and ecological studies of secondary metabolites.

Candida guilliermondii as an agent of postpartum subacute mastitis in Rio de Janeiro, Brazil: Case report

Candida spp. can cause mild-to-severe human infections. Certain species have been described as the etiologic agent of human mastitis, inflammation of the breast tissue. Mastitis affects millions of lactating women and can be a source of disease transmission to the infant. In this work, we report the detection of the unusual etiologic agent of human mastitis, Candida guilliermondii, isolated from the milk of a puerperal woman with subacute mastitis in Rio de Janeiro, Brazil. Species identification was performed by MALDI-TOF MS and genetic sequencing. The patient had a full recovery after antifungal therapy.

Bioinformatics strategies for studying the molecular mechanisms of fungal extracellular vesicles with a focus on infection and immune responses

Fungal extracellular vesicles (EVs) are released during pathogenesis and are found to be an opportunistic infection in most cases. EVs are immunocompetent with their host and have paved the way for new biomedical approaches to drug delivery and the treatment of complex diseases including cancer. With computing and processing advancements, the rise of bioinformatics tools for the evaluation of various parameters involved in fungal EVs has blossomed. In this review, we have complied and explored the bioinformatics tools to analyze the host-pathogen interaction, toxicity, omics and pathogenesis with an array of specific tools that have depicted the ability of EVs as vector/carrier for therapeutic agents and as a potential theme for immunotherapy. We have also discussed the generation and pathways involved in the production, transport, pathogenic action and immunological interactions of EVs in the host system. The incorporation of network pharmacology approaches has been discussed regarding fungal pathogens and their significance in drug discovery. To represent the overview, we have presented and demonstrated an in silico study model to portray the human Cryptococcal interactions.

DBHR: a collection of databases relevant to human research

BACKGROUND

The achievement of the human genome project provides a basis for the systematic study of the human genome from evolutionary history to disease-specific medicine. With the explosive growth of biological data, a growing number of biological databases are being established to support human-related research.

OBJECTIVE

The main objective of our study is to store, organize and share data in a structured and searchable manner. In short, we have planned the future development of new features in the database research area.

MATERIALS & METHODS

In total, we collected and integrated 680 human databases from scientific published work. Multiple options are presented for accessing the data, while original links and short descriptions are also presented for each database.

RESULTS & DISCUSSION

We have provided the latest collection of human research databases on a single platform with six categories: DNA database, RNA database, protein database, expression database, pathway database and disease database.

CONCLUSION

Taken together, our database will be useful for further human research study and will be modified over time. The database has been implemented in PHP, HTML, CSS and MySQL and is available freely at https://habdsk.org/database.php.

Microbiological and Molecular Diagnosis of Mucormycosis: From Old to New

Members of the order Mucorales may cause severe invasive fungal infections (mucormycosis) in immune-compromised and otherwise ill patients. Diagnosis of Mucorales infections and discrimination from other filamentous fungi are crucial for correct management. Here, we present an overview of current state-of-the-art mucormycosis diagnoses, with a focus on recent developments in the molecular field. Classical diagnostic methods comprise histology/microscopy as well as culture and are still the gold standard. Newer molecular methods are evolving quickly and display great potential in early diagnosis, although standardization is still missing. Among them, quantitative PCR assays with or without melt curve analysis are most widely used to detect fungal DNA in clinical samples. Depending on the respective assay, sequencing of the resulting PCR product can be necessary for genus or even species identification. Further, DNA-based methods include microarrays and PCR-ESI-MS. However, general laboratory standards are still in development, meaning that molecular methods are currently limited to add-on analytics to culture and microscopy.

Antifungal Susceptibility Testing and Identification

The requirement for antifungal susceptibility testing is increasing given the availability of new drugs, increasing populations of individuals at risk for fungal infection, and emerging multiresistant fungi. Rapid and accurate fungal identification remains at the forefront of laboratory efforts to guide empiric therapy. Antifungal susceptibility testing methods have greatly improved, but are subject to variation in results between methods. Careful standardization, validation, and extensive training of users is essential to ensure susceptibility results are clinically useful and interpreted appropriately. Interpretive criteria for many drugs and species are still lacking, but this will continue to evolve.

The Interaction between Rice Genotype and Magnaporthe oryzae Regulates the Assembly of Rice Root-Associated Microbiota

BACKGROUND

Utilizating the plant microbiome to enhance pathogen resistance in crop production is an emerging alternative to the use of chemical pesticides. However, the diversity and structure of the microbiota, and the assembly mechanisms of root-associated microbial communities of plants are still poorly understood.

RESULTS

We invstigated the microbiota of the root endosphere and rhizosphere soils of the rice cultivar Nipponbare (NPB) and its Piz-t-transgenic line (NPB-Piz-t) when infected with the filamentous fungus Magnaporthe oryzae (M. oryzae) isolate KJ201, using 16S rRNA and internal transcribed spacer 1 (ITS1) amplicon sequencing. The rhizosphere soils showed higher bacterial and fungal richness and diversity than the endosphere except for fungal richness in the rhizosphere soils of the mock treatment. Bacteria richness and diversity increased in the endospheric communities of NPB and Piz-t under inoculation with KJ201 (referred to as 'NPB-KJ201' and 'Piz-t-KJ201', respectively) compared with the corresponding mock treatments, with the NPB-KJ201 showing the highest diversity in the four bacterial endocompartments. In contrast, fungal richness and diversity decreased in the endospheric communities of NPB-KJ201 and Piz-t-KJ201, relative to the corresponding mock treatments, with NPB-KJ201 and Piz-t-KJ201 having the lowest richness and diversity, respectively, across the four fungal endocompartments. Principal component analysis (PCA) indicated that the microbiota of Piz-t-KJ201 of root endophytes were mostly remarkablely distinct from that of NPB-KJ201. Co-occurrence network analysis revealed that the phyla Proteobacteria and Ascomycota were the key contributors to the bacterial and fungal communities, respectively. Furthermore, a comparative metabolic analysis showed that the contents of tryptophan metabolism and indole alkaloid biosynthesis were significantly lower in the Piz-t-KJ201 plants.

CONCLUSIONS

In this study, we compared the diversity, composition, and assembly of microbial communities associated with the rhizosphere soils and endosphere of Piz-t-KJ201 and NPB-KJ201. On the basis of the different compositions, diversities, and assemblies of the microbial communities among different compartments, we propose that the host genotype and inoculation pattern of M. oryzae played dominant roles in determining the microbial community assemblage. Further metabolomics analysis revealed that some metabolites may influence changes in bacterial communities. This study improves our understanding of the complex interactions between rice and M. oryzae, which could be useful in developing new strategies to improve rice resistance through the manipulation of soil microorganisms.

Fungal Genomic Resources for Strain Identification and Diversity Analysis of 1900 Fungal Species

Identification and diversity analysis of fungi is greatly challenging. Though internal transcribed spacer (ITS), region-based DNA fingerprinting works as a “gold standard” for most of the fungal species group, it cannot differentiate between all the groups and cryptic species. Therefore, it is of paramount importance to find an alternative approach for strain differentiation. Availability of whole genome sequence data of nearly 2000 fungal species are a promising solution to such requirement. We present whole genome sequence-based world’s largest microsatellite database, FungSatDB having >19M loci obtained from >1900 fungal species/strains using >4000 assemblies across globe. Genotyping efficacy of FungSatDB has been evaluated by both in-silico and in-vitro PCR. By in silico PCR, 66 strains of 8 countries representing four continents were successfully differentiated. Genotyping efficacy was also evaluated by in vitro PCR in four fungal species. This approach overcomes limitation of ITS in species, strain signature, and diversity analysis. It can accelerate fungal genomic research endeavors in agriculture, industrial, and environmental management.

DNA barcoding of phytopathogens for disease diagnostics and bio-surveillance

DNA barcoding has proven to be a versatile tool for plant disease diagnostics in the genomics era. As the mass parallel and next generation sequencing techniques gained importance, the role of specific barcodes came under immense scrutiny. Identification and accurate classification of phytopathogens need a universal approach which has been the main application area of the concept of barcode. The present review entails a detailed description of the present status of barcode application in plant disease diagnostics. A case study on the application of Internal Transcribed Spacer (ITS) as barcode for Aspergillus and Fusarium spp. sheds light on the requirement of other potential candidates as barcodes for accurate identification. The challenges faced while barcoding novel pathogens have also been discussed with a comprehensive outline of integrating more recent technologies like meta-barcoding and genome skimming for detecting plant pathogens.

Production, purification, characterization, antioxidant and antiproliferative activities of extracellular L-asparaginase produced by Fusarium equiseti AHMF4

L-Asparaginase is an antileukemic agent that depletes L-asparagine “an important nutrient for cancer cells” through the hydrolysis of L-asparagine into L-aspartic acid and ammonia leading to leukemia cell starvation and apoptosis in susceptible leukemic cell populations. Moreover currently, bacterial L-asparaginase has been limited by problems of lower productivity, stability, selectivity and a number of toxicities along with the resistance towards bacterial L-asparaginase. Then the current work aimed to provide pure L-asparaginase with in-vitro efficacy against various human carcinomas without adverse effects related to current L-asparaginase formulations. Submerged fermentation (SMF) bioprocess was applied and improved to maximize L-asparaginase production from Fusarium equiseti AHMF4 as alternative sources of bacteria. The enzyme production in SMF was maximized to reach 40.78 U mL⁻¹ at the 7th day of fermentation with initial pH 7.0, incubation temperature 30 °C, 1.0% glucose as carbon source, 0.2% asparagine as nitrogen source, 0.1% alanine as amino acid supplement and 0.1% KH₂PO₄. The purification of AHMF4 L-asparaginase yielded 2.67-fold purification and 48% recovery with final specific activity of 488.1 U mg⁻¹ of protein. Purified L-asparaginase was characterized as serine protease enzyme with molecular weight of 45.7 kDa beside stability at neutral pH and between 20 and 40 °C. Interestingly, purified L-asparaginase showed promising DPPH radical scavenging activity (IC₅₀ 69.12 μg mL⁻¹) and anti-proliferative activity against cervical epitheloid carcinoma (Hela), epidermoid larynx carcinoma (Hep-2), hepatocellular carcinoma (HepG-2), Colorectal carcinoma (HCT-116), and breast adenocarcinoma (MCF-7) with IC₅₀ equal to 2.0, 5.0, 12.40, 8.26 and 22.8 μg mL⁻¹, respectively. The enzyme showed higher activity, selectivity and anti-proliferative activity against cancerous cells along with tiny cytotoxicity toward normal cells (WI-38) which indicates that it has selective toxicity and it could be applied as a less toxic alternative to the current formulations.

Rapid and real-time identification of fungi up to species level with long amplicon nanopore sequencing from clinical samples

The availability of long-read technologies, like Oxford Nanopore Technologies, provides the opportunity to sequence longer fragments of the fungal ribosomal operon, up to 6 Kb (18S-ITS1-5.8S-ITS2-28S) and to improve the taxonomy assignment of the communities up to species level and in real-time. We assess the applicability for taxonomic assignment of amplicons targeting a 3.5 Kb region (V3 18S-ITS1-5.8S-ITS2-28S D2) and a 6 Kb region (V1 18S-ITS1-5.8S-ITS2-28S D12) with the What's in my pot (WIMP) classifier. We used the ZymoBIOMICSTM mock community and different microbiological fungal cultures as positive controls. Long amplicon sequencing correctly identified Saccharomyces cerevisiae and Cryptococcus neoformans from the mock community and Malassezia pachydermatis, Microsporum canis and Aspergillus fumigatus from the microbiological cultures. Besides, we identified Rhodotorula graminis in a culture mislabelled as Candida spp. We applied the same approach to external otitis in dogs. Malassezia was the dominant fungal genus in dogs' ear skin, whereas Ma. pachydermatis was the main species in the healthy sample. Conversely, we identified a higher representation of Ma. globosa and Ma. sympodialis in otitis affected samples. We demonstrate the suitability of long ribosomal amplicons to characterize the fungal community of complex samples, either healthy or with clinical signs of infection.

An innovative user-friendly platform for Covid-19 pandemic databases and resources

BACKGROUND

The current coronavirus disease-19 (COVID-19) is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a global outbreak of a disease from a new coronavirus. Several databases have been published on this pandemic, but the research community still needs an easy way to get comprehensive information on COVID-19.

OBJECTIVES

COVID-19 pandemic database (CO-19 PDB) aims to provide wonderful insights for COVID-19 researchers with the well-gathered of all the COVID-19 data to one platform, which is a global challenge for the research community these days.

METHODS

We gathered 59 updated databases since December-2019 until May 2021 and divided them into six categories: digital image database, genomic database, literature database, visualization tools database, chemical structure database, and social science database. These categories focus on taking number of functions from the images, information from gene sequences, updates from relevant papers, essays, reports, articles, and books, the data or information in the form of maps, graphs, and charts, information of bonds between atoms, and updates about events of the physical and social environment, respectively.

RESULTS

Users can search the information of interest in two ways including typing the name of the database in the search bar or by clicking the right category directly. Computer languages such as CSS, PHP, HTML, Java, etc. are utilized to construct CO-19 PDB.

CONCLUSION

This article attempts to compile up-to-date appropriate COVID-19 datasets and resources that have not been compiled and given in such an accessible and user-friendly manner. As a result, the CO-19 PDB offers extensive open data sharing for both worldwide research communities and local people. Further, we have planned future development of new features, that will be awesome for future study.

Fun(gi)omics: Advanced and Diverse Technologies to Explore Emerging Fungal Pathogens and Define Mechanisms of Antifungal Resistance

The landscape of infectious fungal agents includes previously unidentified or rare pathogens with the potential to cause unprecedented casualties in biodiversity, food security, and human health. The influences of human activity, including the crisis of climate change, along with globalized transport, are underlying factors shaping fungal adaptation to increased temperature and expanded geographical regions. Furthermore, the emergence of novel antifungal-resistant strains linked to excessive use of antifungals (in the clinic) and fungicides (in the field) offers an additional challenge to protect major crop staples and control dangerous fungal outbreaks.

The landscape of infectious fungal agents includes previously unidentified or rare pathogens with the potential to cause unprecedented casualties in biodiversity, food security, and human health. The influences of human activity, including the crisis of climate change, along with globalized transport, are underlying factors shaping fungal adaptation to increased temperature and expanded geographical regions. Furthermore, the emergence of novel antifungal-resistant strains linked to excessive use of antifungals (in the clinic) and fungicides (in the field) offers an additional challenge to protect major crop staples and control dangerous fungal outbreaks. Hence, the alarming frequency of fungal infections in medical and agricultural settings requires effective research to understand the virulent nature of fungal pathogens and improve the outcome of infection in susceptible hosts. Mycology-driven research has benefited from a contemporary and unified approach of omics technology, deepening the biological, biochemical, and biophysical understanding of these emerging fungal pathogens. Here, we review the current state-of-the-art multi-omics technologies, explore the power of data integration strategies, and highlight discovery-based revelations of globally important and taxonomically diverse fungal pathogens. This information provides new insight for emerging pathogens through an in-depth understanding of well-characterized fungi and provides alternative therapeutic strategies defined through novel findings of virulence, adaptation, and resistance.

A DNA Repair Inhibitor Isolated from an Ecuadorian Fungal Endophyte Exhibits Synthetic Lethality in PTEN-Deficient Glioblastoma

Disruption of the tumor suppressor PTEN, either at the protein or genomic level, plays an important role in human cancer development. The high frequency of PTEN deficiency reported across several cancer subtypes positions therapeutic approaches that exploit PTEN loss-of-function with the ability to significantly impact the treatment strategies of a large patient population. Here, we report that an endophytic fungus isolated from a medicinal plant produces an inhibitor of DNA double-strand-break repair. Furthermore, the novel alkaloid product, which we have named irrepairzepine (1), demonstrated synthetic lethal targeting in PTEN-deficient glioblastoma cells. Our results uncover a new therapeutic lead for PTEN-deficient cancers and an important molecular tool toward enhancing the efficacy of current cancer treatments.

Updates in Laboratory Diagnostics for Invasive Fungal Infections

Appropriate diagnosis of invasive fungal infections (IFIs) is critical due to the high rates of morbidity and mortality, as well as the substantial economic burden, associated with the management of these diseases. The recognition of IFI and differentiation from other infections with similar clinical presentations can be challenging, which can lead to diagnostic error that not only has an impact on individual patient health outcomes but also on antimicrobial drug usage and the growing threat of antimicrobial resistance in bacteria. Therefore, there is a significant need for improved stewardship related to diagnostic testing for and treatment of IFIs. The purpose of this review is to highlight recent advances related to current fungal diagnostics, as well as explore some of the most innovative technology that has emerged with the potential to shift the paradigm of clinical mycology. In general, this review will discuss research related to enhanced fungal culture utilization and identification techniques, expanded applications of fungal antigen testing, and recently developed molecular assays and other novel nonculture fungal diagnostic approaches. Specifically, the application of mass spectrometry, novel glycobiomarker detection, and detection of fungal-specific volatile organic compounds will be reviewed, along with other key updates, to provide the reader with an updated review that extends beyond the basics of IFI laboratory diagnostics. Where appropriate, the reader will be directed to more comprehensive reviews of certain aspects of clinical mycology laboratory testing to provide a broader context for the critical consideration of these updates.

Gut mycobiota under scrutiny: fungal symbionts or environmental transients?

The human gastrointestinal tract is home to a thriving community of microbes including the fungal 'mycobiota'. Although sequencing methodology has enumerated diverse fungal genera within this niche, discerning persistent symbiotic residents from contaminants and purely environmental transients remains a challenge. Recent advances in culturomics and sequencing employing metagenomics, metatranscriptomics and longitudinal studies have begun to reveal a human symbiont 'core mycobiome' that may contribute to human health and disease. Trans-kingdom interactions between the bacterial microbiota and evolution within the niche have defined C. albicans as a true symbiont, setting a bar for defining other fungi. Additionally, elegant investigations of mammalian antifungal immunity have examined mononuclear phagocytes, neutrophils, antigen-specific recognition by T cells and other mechanisms important for local and systemic effects on the host, providing further evidence supporting gut persistence. In this review we discuss current research aimed at investigating the symbiotic mycobiota and propose four criteria aiding in the differentiation of fungal symbionts from environmental transients.

The gut mycobiota: insights into analysis, environmental interactions and role in gastrointestinal diseases

The gut microbiota is a dense and diverse ecosystem that is involved in many physiological functions as well as in disease pathogenesis. It is dominated by bacteria, which have been extensively studied in the past 15 years; however, other microorganisms, such as fungi, phages, archaea and protists, are also present in the gut microbiota. Exploration of the fungal component, namely, the mycobiota, is at an early stage, and several specific technical challenges are associated with mycobiota analysis. The number of fungi in the lower gastrointestinal tract is far lower than that of bacteria, but fungal cells are much larger and much more complex than bacterial cells. In addition, a role of the mycobiota in disease, notably in IBD, is indicated by both descriptive data in humans and mechanistic data in mice. Interactions between bacteria and fungi within the gut, their functional roles and their interplay with the host and its immune system are fascinating areas that researchers are just beginning to investigate. In this Review, we discuss the newest data on the gut mycobiota and explore both the technical aspects of its study and its role in health and gastrointestinal diseases.

Molecular diagnostics in medical mycology

Diagnosing fungal infections poses a number of unique problems, including a decline in expertise needed for identifying fungi, and a reduced number of instruments and assays specific for fungal identification compared to that of bacteria and viruses.These problems are exacerbated by the fact that patients with fungal infections are often immunosuppressed, which predisposes to infections from both commonly and rarely seen fungi. In this review, we discuss current and future molecular technologies used for fungal identification, and some of the problems associated with development and implementation of these technologies in today’s clinical microbiology laboratories.

Diagnosing fungal infections poses a number of unique problems. In this Review, Wickes and Wiederhold discuss molecular technologies used for fungal identification, and the problems associated with their development and implementation in today’s clinical microbiology laboratories.

MALDI-TOF MS-Based Identification of Melanized Fungi is Faster and Reliable After the Expansion of In-House Database

PURPOSE

Invasive fungal infections caused by melanized fungi are a growing concern. Rapid and reliable identification plays an important role in optimizing therapy. Matrix-assisted laser desorption/ionization-time-of-flight mass spectrometry (MALDI-TOF MS)-based identification has emerged as a faster and more accurate diagnostic technique. However, lack of a protein extraction protocol and limited database restricts the identification of melanized fungi by MALDI-TOF MS. The study is designed to standardize protein extraction protocol, to enrich the existing, and to create an in-house database for the rapid identification of melanized fungi.

EXPERIMENTAL DESIGN

In this study, 59 sequence-confirmed, melanized fungi were used to expand and to create an in-house database using a modified protein extraction protocol. A total of 117 clinical isolates are further used to validate the created database.

RESULT

Using existing Bruker database, only 29(24.8%) out of 117 moulds could be identified. However, all the isolates are identified accurately by supplementing the Bruker database with the created in-house database. MALDI-TOF MS takes significantly lesser time for identification compared to DNA sequencing.

CONCLUSION AND CLINICAL RELEVANCE

An expanded database with modified protein extraction protocol can reduce significant time to identify melanized fungi by MALDI-TOF MS.

Advances in the diagnosis and treatment of fungal infections of the CNS

Fungal infections of the CNS are challenging to treat and their optimal management requires knowledge of their epidemiology, host characteristics, diagnostic criteria, and therapeutic options. Aspergillus and Cryptococcus species predominate among fungal infections of the CNS. Most of these fungi are ubiquitous, but some have restricted geographical distribution. Fungal infections of the CNS usually originate from primary sites outside the CNS (eg, fungal pneumonia) or occur after inoculation (eg, invasive procedures). Most patients with these infections have immunodeficiencies, but immunocompetent individuals can also be infected through heavy exposure. The infecting fungi can be grouped into moulds, yeasts, and dimorphic fungi. Substantial progress has been made with new diagnostic approaches and the introduction of novel antifungal drugs, but fungal infections of the CNS are frequently lethal because of diagnostic delays, impaired drug penetration, resistance to antifungal treatments, and inadequate restoration of immune function. To improve outcomes, future research should advance diagnostic methods (eg, molecular detection and fungus identification), develop antifungal compounds with enhanced CNS-directed efficacy, and further investigate crucial host defence mechanisms.

Comparison of sequencing the D2 region of the large subunit ribosomal RNA gene (MicroSEQ®) versus the internal transcribed spacer (ITS) regions using two public databases for identification of common and uncommon clinically relevant fungal species

CONTEXT

Fungal infections cause considerable morbidity and mortality in immunocompromised patients. Rapid and accurate identification of fungi is essential to guide accurately targeted antifungal therapy. With the advent of molecular methods, clinical laboratories can use new technologies to supplement traditional phenotypic identification of fungi.

OBJECTIVE

The aims of the study were to evaluate the sole commercially available MicroSEQ® D2 LSU rDNA Fungal Identification Kit compared to the in-house developed internal transcribed spacer (ITS) regions assay in identifying moulds, using two well-known online public databases to analyze sequenced data.

DESIGN

85 common and uncommon clinically relevant fungi isolated from clinical specimens were sequenced for the D2 region of the large subunit (LSU) of ribosomal RNA (rRNA) gene with the MicroSEQ® Kit and the ITS regions with the in house developed assay. The generated sequenced data were analyzed with the online GenBank and MycoBank public databases.

RESULTS

The D2 region of the LSU rRNA gene identified 89.4% or 92.9% of the 85 isolates to the genus level and the full ITS region (f-ITS) 96.5% or 100%, using GenBank or MycoBank, respectively, when compared to the consensus ID. When comparing species-level designations to the consensus ID, D2 region of the LSU rRNA gene aligned with 44.7% (38/85) or 52.9% (45/85) of these isolates in GenBank or MycoBank, respectively. By comparison, f-ITS possessed greater specificity, followed by ITS1, then ITS2 regions using GenBank or MycoBank. Using GenBank or MycoBank, D2 region of the LSU rRNA gene outperformed phenotypic based ID at the genus level. Comparing rates of ID between D2 region of the LSU rRNA gene and the ITS regions in GenBank or MycoBank at the species level against the consensus ID, f-ITS and ITS2 exceeded performance of the D2 region of the LSU rRNA gene, but ITS1 had similar performance to the D2 region of the LSU rRNA gene using MycoBank.

CONCLUSION

Our results indicated that the MicroSEQ® D2 LSU rDNA Fungal Identification Kit was equivalent to the in-house developed ITS regions assay to identify fungi at the genus level. The MycoBank database gave a better curated database and thus allowed a better genus and species identification for both D2 region of the LSU rRNA gene and ITS regions.