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Published Paper Details
Paper Title:
Study of Bacterial Toxin as Antifungal and Antibacterial and its Effect on Germ Tube Formation in Candida albicans and Cell Count of Candida paprapsilosis
Authors Name:
Dr. HEENA PATHAN
, Huma bhuvan , Aswira shaikh , Humera shaikh , Shazia shaikh , Alshifa shaikh
Microbial toxins have shown promising antifungal and antibacterial properties, making them potential candidates for alternative therapeutic strategies. This study evaluates the effects of Pseudomonas toxin and shiga toxin on fungal growth inhibition, germ tube formation in Candida albicans, and cell count reduction in Candida parapsilosis. Additionally, the antibacterial effects of these toxins against Escherichia coli and Shigella were analyzed.
Results demonstrated that Pseudomonas toxin exhibited significantly higher antifungal activity compared to shiga toxin. It caused fungal cell wall disintegration within 72 hours and inhibited germ tube formation in Candida albicans after 24 hours. Furthermore, Candida parapsilosis cell count showed a declining trend when exposed to the toxin. Antibacterial assays confirmed the effectiveness of the toxin against E. coli and Shigella, suggesting broadspectrum antimicrobial potential.
These findings highlight microbial toxins as viable alternatives to conventional antifungal and antibacterial treatments, warranting further research into their mechanisms and clinical applications.
Keywords: Microbial toxin, Pseudomonas toxin, Candida albicans, Candida parapsilosis, antifungal activity, antibacterial properties
"Study of Bacterial Toxin as Antifungal and Antibacterial and its Effect on Germ Tube Formation in Candida albicans and Cell Count of Candida paprapsilosis", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2455-2631, Vol.10, Issue 3, page no.a211-a219, March-2025, Available :http://www.ijrti.org/papers/IJRTI2503025.pdf
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ISSN:
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator