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Novel Technologies for Diagnosis of Fungal Infection
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Novel Technologies for Diagnosis of Fungal Infection

A special issue of Journal of Fungi (ISSN 2309-608X). This special issue belongs to the section "Fungal Genomics, Genetics and Molecular Biology".

Deadline for manuscript submissions: closed (1 October 2022) | Viewed by 8405

Special Issue Editors

Dr. Julie Bonhomme

E-Mail Website
Guest Editor
ToxEMAC-ABTE, Centre F. Baclesse, Unicaen and Unirouen, Normandie University and Service de Microbiologie, Centre Hospitalier Universitaire de Caen, 14000 Caen, France
Interests: diagnosis and treatment of fungal infections; antifungal resistance; fungal biofilms; fungal pathogenesis; environmental fungi; environmental risk
Prof. Dr. David Garon

E-Mail Website
Guest Editor
ToxEMAC-ABTE, Centre F. Baclesse, Unicaen and Unirouen, Normandie University, Caen, France
Interests: bioaerosols; fungal exposure; environmental fungi; indoor air quality; mycotoxins

Special Issue Information

Dear Colleagues,

Fungal infections are increasing across the world. Despite the constant improvement in knowledge, training and the therapeutic management of these infections, prevalence and mortality remain high for some of them, including invasive candidiasis, aspergillosis, pneumocystosis and mucormycosis, linked in particular to an increasing proportion of subjects at risk and to delayed diagnosis. This is why it is important to develop new early detection or screening tools for human and animal fungal infections.

The aim of this Special Issue is to identify all the new techniques useful for the diagnosis of fungal infections, whether microscopic, spectrometric, molecular, bioinformatic, serological or other.

This Special Issue welcomes scientific contributions through original research articles and reviews on this topic, in order to discuss the most recent and exciting advances in this field and possibly propose diagnostic algorithms to improve the precision and the earliness of fungal diagnosis.

Dr. Julie Bonhomme
Prof. Dr. David Garon
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Journal of Fungi is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • fungal infections
  • fungal diagnostic test
  • diagnostic innovation
  • microscopy
  • mass spectrometry
  • molecular biology
  • serology
  • antigen detection

Published Papers (3 papers)

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Research

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17 pages, 1962 KiB  
Article
Transcriptional Profiles Elucidate Differential Host Responses to Infection with Cryptococcus neoformans and Cryptococcus gattii
by Zachary E. Holcomb, Julie M. Steinbrink, Aimee K. Zaas, Marisol Betancourt, Jennifer L. Tenor, Dena L. Toffaletti, J. Andrew Alspaugh, John R. Perfect and Micah T. McClain
J. Fungi 2022, 8(5), 430; https://doi.org/10.3390/jof8050430 - 22 Apr 2022
Cited by 2 | Viewed by 2212
Abstract
Many aspects of the host response to invasive cryptococcal infections remain poorly understood. In order to explore the pathobiology of infection with common clinical strains, we infected BALB/cJ mice with Cryptococcus neoformans, Cryptococcus gattii, or sham control, and assayed host transcriptomic [...] Read more.
Many aspects of the host response to invasive cryptococcal infections remain poorly understood. In order to explore the pathobiology of infection with common clinical strains, we infected BALB/cJ mice with Cryptococcus neoformans, Cryptococcus gattii, or sham control, and assayed host transcriptomic responses in peripheral blood. Infection with C. neoformans resulted in markedly greater fungal burden in the CNS than C. gattii, as well as slightly higher fungal burden in the lungs. A total of 389 genes were significantly differentially expressed in response to C. neoformans infection, which mainly clustered into pathways driving immune function, including complement activation and TH2-skewed immune responses. C. neoformans infection demonstrated dramatic up-regulation of complement-driven genes and greater up-regulation of alternatively activated macrophage activity than seen with C gattii. A 27-gene classifier was built, capable of distinguishing cryptococcal infection from animals with bacterial infection due to Staphylococcus aureus with 94% sensitivity and 89% specificity. Top genes from the murine classifiers were also differentially expressed in human PBMCs following infection, suggesting cross-species relevance of these findings. The host response, as manifested in transcriptional profiles, informs our understanding of the pathophysiology of cryptococcal infection and demonstrates promise for contributing to development of novel diagnostic approaches. Full article
(This article belongs to the Special Issue Novel Technologies for Diagnosis of Fungal Infection)
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Review

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16 pages, 891 KiB  
Review
The Use of Host Biomarkers for the Management of Invasive Fungal Disease
by James S. Griffiths, Selinda J. Orr, Charles Oliver Morton, Juergen Loeffler and P. Lewis White
J. Fungi 2022, 8(12), 1307; https://doi.org/10.3390/jof8121307 - 16 Dec 2022
Cited by 2 | Viewed by 2429
Abstract
Invasive fungal disease (IFD) causes severe morbidity and mortality, and the number of IFD cases is increasing. Exposure to opportunistic fungal pathogens is inevitable, but not all patients with underlying diseases increasing susceptibility to IFD, develop it. IFD diagnosis currently uses fungal biomarkers [...] Read more.
Invasive fungal disease (IFD) causes severe morbidity and mortality, and the number of IFD cases is increasing. Exposure to opportunistic fungal pathogens is inevitable, but not all patients with underlying diseases increasing susceptibility to IFD, develop it. IFD diagnosis currently uses fungal biomarkers and clinical risk/presentation to stratify high-risk patients and classifies them into possible, probable, and proven IFD. However, the fungal species responsible for IFD are highly diverse and present numerous diagnostic challenges, which culminates in the empirical anti-fungal treatment of patients at risk of IFD. Recent studies have focussed on host-derived biomarkers that may mediate IFD risk and can be used to predict, and even identify IFD. The identification of novel host genetic variants, host gene expression changes, and host protein expression (cytokines and chemokines) associated with increased risk of IFD has enhanced our understanding of why only some patients at risk of IFD actually develop disease. Furthermore, these host biomarkers when incorporated into predictive models alongside conventional diagnostic techniques enhance predictive and diagnostic results. Once validated in larger studies, host biomarkers associated with IFD may optimize the clinical management of populations at risk of IFD. This review will summarise the latest developments in the identification of host biomarkers for IFD, their use in predictive modelling and their potential application/usefulness for informing clinical decisions. Full article
(This article belongs to the Special Issue Novel Technologies for Diagnosis of Fungal Infection)
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13 pages, 1408 KiB  
Review
Diagnosing Onychomycosis: What’s New?
by Aditya K. Gupta, Deanna C. Hall, Elizabeth A. Cooper and Mahmoud A. Ghannoum
J. Fungi 2022, 8(5), 464; https://doi.org/10.3390/jof8050464 - 29 Apr 2022
Cited by 13 | Viewed by 3007
Abstract
An overview of the long-established methods of diagnosing onychomycosis (potassium hydroxide testing, fungal culture, and histopathological examination) is provided followed by an outline of other diagnostic methods currently in use or under development. These methods generally use one of two diagnostic techniques: visual [...] Read more.
An overview of the long-established methods of diagnosing onychomycosis (potassium hydroxide testing, fungal culture, and histopathological examination) is provided followed by an outline of other diagnostic methods currently in use or under development. These methods generally use one of two diagnostic techniques: visual identification of infection (fungal elements or onychomycosis signs) or organism identification (typing of fungal genus/species). Visual diagnosis (dermoscopy, optical coherence tomography, confocal microscopy, UV fluorescence excitation) provides clinical evidence of infection, but may be limited by lack of organism information when treatment decisions are needed. The organism identification methods (lateral flow techniques, polymerase chain reaction, MALDI-TOF mass spectroscopy and Raman spectroscopy) seek to provide faster and more reliable identification than standard fungal culture methods. Additionally, artificial intelligence methods are being applied to assist with visual identification, with good success. Despite being considered the ‘gold standard’ for diagnosis, clinicians are generally well aware that the established methods have many limitations for diagnosis. The new techniques seek to augment established methods, but also have advantages and disadvantages relative to their diagnostic use. It remains to be seen which of the newer methods will become more widely used for diagnosis of onychomycosis. Clinicians need to be aware of the limitations of diagnostic utility calculations as well, and look beyond the numbers to assess which techniques will provide the best options for patient assessment and management. Full article
(This article belongs to the Special Issue Novel Technologies for Diagnosis of Fungal Infection)
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