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Precision Detection of Fungal Co-Infections for Enhanced COVID-19 Treatment Strategies Using FESEM Imaging

  • ORIGINAL RESEARCH ARTICLE
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Indian Journal of Microbiology Aims and scope Submit manuscript

Abstract

The treatment of fungal infections presents significant challenges due to the lack of standardized diagnostic procedures, a restricted range of antifungal treatments, and the risk of harmful interactions between antifungal medications and the immunosuppressive drugs used in anti-inflammatory treatment for critically ill patients with COVID-19. Mucormycosis and aspergillosis are the primary invasive fungal infections in patients with severe COVID-19, occurring singly or in combination. Histopathological examination is a vital diagnostic technique that details the presence and invasion of fungi within tissues and blood vessels, and the body’s response to the infection. However, the pathology report omits information on the most common fungi associated with the observed morphology, as well as other potential fungi and parasites that ought to be included in the differential diagnosis. This research marks significance in diagnosing fungal infections, such as mucormycosis and aspergillosis associated to COVID-19 by field emission scanning electron microscopy (FESEM) imaging to examine unstained histopathology slides, allowing for a detailed morphological analysis of the fungus. FESEM provides an unprecedented resolution and detail, surpassing traditional Hematoxylin & Eosin (H&E) and Grocott’s Methenamine Silver (GMS) staining methods in identifying and differentiating dual fungal infections and diverse fungal species. The findings underscore the critical need for individualized treatment plans for patients severely affected by COVID-19 and compounded by secondary fungal infections. The high-magnification micrographs reveal specific fungal morphology and reproductive patterns. Current treatment protocols largely depend on broad-spectrum antifungal therapies. However this FESEM guided diagnostic approach can help in targeted patient specific anti fungal therapies. Such precision could lead to more effective early interventions, addressing the complex management required for severe COVID-19 cases with coexisting fungal infections. This approach significantly advances disease management and patient recovery, advocating for personalized, precision medicine in tackling this multifaceted clinical challenge.

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Data Availability

All data that support the findings of this study are included within the article.

Abbreviations

ACE2:

Angiotensin converting enzyme 2

CAA:

COVID-19 Associated Aspergillosis

CAM:

COVID-19 Associated Mucormycosis

CCR2+:

C-C chemokine receptor type 2

COVID-19:

CoronaVirus Disease of 2019

FEG:

Field Emission Gun

FESEM:

Field Emission Scanning Electron Microscope

GAG:

Galactosaminogalactan

GM:

Galactomannan

GMS Stain:

Grocott-Gömöri'sMethenamine Silver stain

H&E Stain:

Hematoxylin and eosin stain

HIF-1α:

Hypoxia-Inducible Factor 1α

HMDS:

Hexamethyldisilane

ICU:

Intensive care unit

IFN:

Interferon

IFN-γ:

Interferon-gamma

IL-1ß:

Interleukin 1-beta

IL-6:

Interleukin-6

LCB:

Lactophenol cotton blue

NADPH:

Nicotinamide adenine dinucleotide phosphate

NLRs:

NOD like receptors

PAS:

Periodic acid schiff

PCR:

Polymerase chain reaction

PRRs:

Pattern recognition receptors

SARS-CoV-2:

Severe Acute Respiratory Syndrome Coronavirus 2

TNF-α:

Tumor Necrosis Factor-alpha

TLR4:

Toll-like receptor 4

WBC:

White blood cells

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Acknowledgements

One of the authors Dola Sundeep acknowledges the Ministry of Education, Government of India for providing financial support to conduct this study. Kovuri Umadevi acknowledges the Department of Pathology, Government Medical College and Hospital, Nizamabad for providing the slides to conduct the study.

Funding

Ministry of Education, Government of India, is acknowledged for providing financial assistance in to conduct this study.

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Authors and Affiliations

Authors

Contributions

K.U: Conceptualization (equal); Data curation (lead); Formal analysis (lead); Investigation (equal); Methodology (equal); Writing-original draft (lead); Writing-review & editing (equal). D.S.: Conceptualization (equal); Methodology (equal); Formal analysis (lead); Investigation (equal); Writing-review & editing (lead). E.K.V: Investigation (equal) Methodology (equal). C.C.S.: Investigation (equal); Methodology (equal); Writing-review & editing (equal). A.S. Investigation (equal); Methodology (equal). R.N.C: Investigation (equal); Methodology (equal). A.R.V: Supervision (supporting); Writing-review & editing (supporting).

Corresponding authors

Correspondence to Kovuri Umadevi or Dola Sundeep.

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All the authors declare that we don’t have any financial or any other conflict of interests.

Ethical Approval

This study was conducted following the necessary ethical approvals, as delineated by the Institutional Ethical Committee (IEC), Government Medical College and Hospital, Nizamabad, India, under the reference ECR/1896/Inst/TG/2023. The research was undertaken in strict accordance with the ethical principles laid down in the 1964 Declaration of Helsinki and its subsequent amendments. This included an extensive review and approval by the named institutional ethics committee, ensuring adherence to established ethical norms. Any potential doubts regarding ethical standards were addressed and explicitly approved by the committee. The authors declare that the manuscript is prepared by obeying the Ethical Standards as described in the Committee on Publication Ethics (COPE).

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The consent of participation was obtained a written informed consent from the patients for participation.

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Umadevi, K., Sundeep, D., Varadharaj, E.K. et al. Precision Detection of Fungal Co-Infections for Enhanced COVID-19 Treatment Strategies Using FESEM Imaging. Indian J Microbiol (2024). https://doi.org/10.1007/s12088-024-01246-1

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