Genomics and Virulence of Fonsecaea pugnacius, Agent of Disseminated Chromoblastomycosis

Bombassaro, Amanda; Schneider, G.; Costa, Flávia F.; Leão, Aniele Carolina Ribas; Soley, Bruna da Silva; Medeiros, Fernanda; Silva, Nickolas M da; Lima, Bruna Jacomel Favoreto de Souza; Castro, Raffael Júnio Araújo de; Bocca, Anamélia Lorenzetti; Baura, Valter A.; Balsanelli, Eduardo; Pankievicz, Vânia C. S.; Hrysay, Nyvia Milicio Coblinski; Scola, Rosana Hermínia; Moreno, Leandro Ferreira; Azevedo, Conceição M. P. S. de; Souza, Emanuel Maltempi de; Gomes, Renata Rodrigues; Hoog, Sybren de; Vicente, Vânia Aparecida

doi:10.3389/fgene.2020.00822

Cited by 8 publications

(7 citation statements)

References 112 publications

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“…On the other hand, transcriptomics research on melanotic fungal genomes is recognized as cutting-edge and promising. Several studies made efforts to find genetic profiles by comparing rare human neurotropic pathogens with other known black fungi and made transcriptomic analysis of an albino mutant comparing its melanized strains, which showed that not only some highly expressed melanin genes but also some differentially expressed genes (DEGs) which associated with survival pathway, cell growth, and metabolic pathways ( Chen et al., 2014 ; Li et al., 2016 ; Bombassaro et al., 2020 ).…”

Section: Discussionmentioning

confidence: 99%

Phaeohyphomycosis in China

Zheng

Mei

et al. 2022

Front. Cell. Infect. Microbiol.

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BackgroundDue to more attentions paid to melanized fungi over the past few decades and under the background of the global coronavirus disease 2019 pandemic (COVID-19) the fact that the virus itself and the immunosuppressive agents such as glucocorticoids can further increase the risk of infections of deep mycoses, the number of patients with phaeohyphomycosis (PHM) has a substantial increase. Their spectrum is broad and the early diagnosis and treatments are extremely sticky. This study aims to more comprehensively understand the clinical features of phaeohyphomycosis in China over 35 years and to establish a more applicable systematical classification and severity grades of lesions to guide treatments and prognosis.MethodsWe reviewed 174 cases of proven phaeohyphomycosis reported in Chinese and English language literature from 1987 to 2021 and we also made the accurate classification definitions and detailed information about the epidemiology, species of clinical dematiaceous fungi, minimum inhibitory concentration values, clinical features, treatments, and prognosis.ResultsThe mortality of cerebral, disseminated and pulmonary phaeohyphomycosis are 55%, 36%, and 25%. Nearly 19% of patients had poor quality of life caused by the complications such as disability, disfigurements, and blindness. The overall misdiagnosis rate of phaeohyphomycosis was 74%. Moderate to severe rashes are accounting for 82% of subcutaneous phaeohyphomycosis. The areas of the head and face are mostly affected accounting for 16% of severe rashes. Nearly 30% of invasive infections of phaeohyphomycosis are triggered by recurrent lesions. Voriconazole, itraconazole, amphotericin B deoxycholate (AmB-DOC), and terbinafine were most commonly used but diagnosis and treatments of phaeohyphomycosis remain challenging in reality.ConclusionsOur classifications are likely to be more practical and easier to popularize, and there are still also plenty of characteristics in these non-specific lesions. There’re no significant variations in cure rates, or death rates between three grades of lesions. But patients with severe rashes have longer courses and lower effective rates.

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Section: Discussionmentioning

confidence: 99%

Phaeohyphomycosis in China

Zheng

Mei

et al. 2022

Front. Cell. Infect. Microbiol.

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“…Further, we searched the Taxonomy database [33] using the query '"host human"[Properties] AND Fungi [orgn]', obtaining a list of species with a putative human host and their TaxIDs. We then used a comprehensive selection of literature reviews and comparative studies [60][61][62][63][64][65][66][67][68][69][70][71][72][73][74][75][76] to collect additional evidence and extend the collected list of human pathogens. We manually extracted the species names and searched the NCBI Taxonomy (including synonyms) to link them to their names as reported in Taxonomy and the respective species-level TaxIDs.…”

Section: Ftp Pathmentioning

confidence: 99%

“…More specifically, we collect metadata on species infecting humans, animals or plants, supplemented with information on other plant-associated species. To this end, we integrate multiple literature (Taylor et al, 2001; Chowdhary et al, 2014; Bombassaro et al, 2020; Brunner-Mendoza et al, 2019; Franzen and Müller, 2001; Colombo et al, 2011; Han and Weiss, 2017; Hu et al, 2015; Jancic et al, 2015; Kjærbølling et al, 2018; Köhler et al, 2015; Kwon-Chung et al, 2017; Paulussen et al, 2017; Prakash et al, 2017; Delliére et al, 2020; Teixeira et al, 2017; Seyedmousavi et al, 2018; Smith, 2006; Bałazy et al, 2008; Becnel and Andreadis, 2014; Franzen and Müller, 2001; Cissé et al, 2021; Chandler et al, 2000; Evans et al, 2011; Gerson et al, 2008; Han and Weiss, 2017; Schulenburg and Félix, 2017; Leonhardt et al, 2018; Lovett and St. Leger, 2017; Rehner and Buckley, 2005; Seyedmousavi et al, 2015; Shang et al, 2015; Wu et al, 2021; St. Leger and Wang, 2020; Sung et al, 2007; Teixeira et al, 2017; van der Geest et al, 2000; Vacher et al, 2008; Doehlemann et al, 2017; Barbara and Clewes, 2003; Costa et al, 2021; Coutinho et al, 2017; Gurung et al, 2015; Jones and Baker, 2007; Kim et al, 2012, 2019; Leonhardt et al, 2018; Schardl et al, 2013; Stukenbrock et al, 2012; de Hoog et al, 2020) and database (Lu et al, 2012; Schoch et al, 2020; Farr and Rossman, 2021; Wardeh et al, 2015) sources, relying on manual curation, but also including the automatically extracted data for future reference. Table S1 summarizes the data we collected for each species.…”

Section: Data Descriptionmentioning

confidence: 99%

“…Further, we searched the Taxonomy database [Schoch et al, 2020] using the query ‘“host human”[Properties] AND Fungi [orgn]’, obtaining a list of species with a putative human host and their TaxIDs. We then used a comprehensive selection of literature reviews and comparative studies [Taylor et al, 2001, Chowdhary et al, 2014, Bombassaro et al, 2020, Brunner-Mendoza et al, 2019, Franzen and Müller, 2001, Colombo et al, 2011, Han and Weiss, 2017, Hu et al, 2015, Jančič et al, 2015, Kjærbølling et al, 2018, Köhler et al, 2015, Kwon-Chung et al, 2017, Paulussen et al, 2017, Prakash et al, 2017, Dellière et al, 2020, Teixeira et al, 2017, Seyedmousavi et al, 2018] to collect additional evidence and extend the collected list of human pathogens. We manually extracted the species names and searched the NCBI Taxonomy (including synonyms) to link them to their names as reported in Taxonomy and the respective species-level TaxIDs.…”

Section: Supplementary Informationmentioning

confidence: 99%

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Detecting DNA of novel fungal pathogens using ResNets and a curated fungi-hosts data collection

Bartoszewicz

Nasri

Nowicka

et al. 2021

Preprint

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BackgroundEmerging pathogens are a growing threat, but large data collections and approaches for predicting the risk associated with novel agents are limited to bacteria and viruses. Pathogenic fungi, which also pose a constant threat to public health, remain understudied. Relevant, curated data remains comparatively scarce and scattered among many different sources, hindering the development of sequencing-based detection workflows for novel fungal pathogens. No prediction method working for agents across all three groups is available, even though the cause of an infection is often difficult to identify from symptoms alone.ResultsWe present a curated collection of fungal host range data, comprising records on human, animal and plant pathogens, as well as other plant-associated fungi, linked to publicly available genomes. We show that the resulting database can be used to predict the pathogenic potential of novel fungal species directly from DNA sequences with either sequence homology or deep learning. We develop learned, numerical representations of the collected genomes and show that the human pathogens are separable from non-human pathogens. Finally, we train multi-class models predicting if next-generation sequencing reads originate from novel fungal, bacterial or viral threats.ConclusionsThe presented data collection enables accurate detection of novel pathogens from sequencing data. It is also a comprehensive resource that can find use beyond this particular task. This can include possible applications in proteomics and genomics, employing both machine learning and direct sequence comparison.AvailabilityThe database and models are hosted at https://zenodo.org/record/5711852 and https://zenodo.org/record/5711877. Source code is available at https://gitlab.com/dacs-hpi/deepac.

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“…is the most common pathogen underlying CBM (Queiroz-Telles et al, 2017;Santos et al, 2021). At present, the Fonsecaea clade contains the clinically relevant species F. pedrosoi (Belda et al, 2020;de Andrade et al, 2020;Santos et al, 2007;Singh et al, 2006;Vicente et al, 2008), F. monophora (Campos-Macias et al, 2021), F. nubica (You et al, 2019) and F. pugnacius (Bombassaro et al, 2020). Infection by Fonsecaea spp.…”

Section: Introductionmentioning

confidence: 99%

Evolutionary Relationships, Phylogeographic Patterns, and a Hypothesis for Air- and Sea-driven Global Spread of Chromoblastomycosis by Etiological Fonsecaea Agents

Wang

Hao²,

Cai

et al. 2022

Preprint

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Fonsecaea spp. is the most common pathogen underlying chromoblastomycosis. However, many aspects of its evolutionary history are not fully understood, and a timescale for its diversification is lacking . Here, we propose, explain, and validate the evolutionary relationships, transmission routes, and modes of transmission among pathogenic species of the genus Fonsecaea . we investigated the sequences of a total of 510 intra-ribosomal transcribed regions and 485 reported cases of eight strains of the genus Fonsecaea , that have spread epidemically worldwide, persisted, and diversified over 38.27 million years. This period coincides with the diversification of many filamentous fungi, and this evolution explains the diversity and origin of pathogenic species of Fonsecaea spp . , as well as the possible transmission routes. Fonsecaea pedrosoi originated in the Atlantic Ocean near Brazil, F. monophora originated in the Pacific Ocean near southern China, and F. nubica originated in the Indian Ocean near Madagascar. F. pugnacius originated and is endemic in the Atlantic Ocean near Brazil. We proposed the hypothesis that non-pathogenic environmental strains in the environment ( Fonsecaea brasiliensis , F. multimorphosa , F. minima , and F. erecta ) evolved into pathogenic strains ( F. pedrosoi , F. pugnacius , F. nubica , and F. monophora ) and spread globally with global tropical cyclone and ocean currents pathways. F. multimorphosa is potentially infectious to humans. The present study’s results will greatly facilitate the prevention, treatment, and cure of Fonsecaea infections and give insight and reference to researchers in the field of fungal research, especially other pathogenic fungi and environmental fungi.

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Genomics and Virulence of Fonsecaea pugnacius, Agent of Disseminated Chromoblastomycosis

Cited by 8 publications

References 112 publications

Phaeohyphomycosis in China

Phaeohyphomycosis in China

Detecting DNA of novel fungal pathogens using ResNets and a curated fungi-hosts data collection

Evolutionary Relationships, Phylogeographic Patterns, and a Hypothesis for Air- and Sea-driven Global Spread of Chromoblastomycosis by Etiological Fonsecaea Agents

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