Evidence map›Paper›PMID 42183906›Full record

ArticleWorld journal of microbiology & biotechnology2026

Pathogen-induced modulation of the volatile metabolome of Hanseniaspora uvarum LE-1 and its role in post-harvest disease suppression.

Pratibha Murmu, Aundy Kumar, Deeba Kamil, Aditi Kundu, Subhrautpal Karmakar, S Rajna, Amrita Das

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Article in World journal of microbiology & biotechnology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

7 authors.

Pratibha MurmuDivision of Plant Pathology, ICAR-Indian Agricultural Research Institute, New Delhi, 110012, India.
Aundy KumarDivision of Plant Pathology, ICAR-Indian Agricultural Research Institute, New Delhi, 110012, India.
Deeba KamilDivision of Plant Pathology, ICAR-Indian Agricultural Research Institute, New Delhi, 110012, India.
Aditi KunduDivision of Agricultural Chemicals, ICAR-Indian Agricultural Research Institute, New Delhi, 110012, India.
Subhrautpal KarmakarDivision of Agricultural Chemicals, ICAR-Indian Agricultural Research Institute, New Delhi, 110012, India.
S RajnaDivision of Entomology, ICAR-Indian Agricultural Research Institute, New Delhi, 110012, India.
Amrita DasDivision of Plant Pathology, ICAR-Indian Agricultural Research Institute, New Delhi, 110012, India. amritapatho@gmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The use of yeasts as biocontrol agents to prevent post-harvest fruit diseases offers a promising alternative to synthetic fungicides. Volatile organic compounds (VOCs) of microbial origin represent an effective strategy for managing post-harvest decay. This study systematically evaluates the role of VOCs produced by the antagonistic yeast Hanseniaspora uvarum LE‑1 against Alternaria alternata, Colletotrichum musae, and Penicillium italicum, causing post-harvest diseases in apples, bananas, and oranges, respectively. In preliminary dual‑plate assays, H. uvarum LE‑1 achieved approximately 50% inhibition of pathogen growth, with maximal suppression observed in C. musae. The VOCs produced by H. uvarum LE-1 exhibited concentration‑dependent inhibition of phytopathogen growth, with maximum suppression observed in C. musae (85%), followed by A. alternata (74%) and P. italicum (54%) at 100 µl under in vitro conditions. The volatile compounds produced by H. uvarum LE-1 were mainly alcohols, especially phenyl-ethanol (24.17%), along with some esters and fatty acid derivatives. However, when the yeast was co-cultured with post-harvest pathogens, the volatile profile changed markedly, with higher amounts of hydrocarbons, cycloalkanes, and ketones, resulting in a distinct chemical pattern for each interaction. Further, phenyl-ethanol exhibited strong, concentration-dependent antifungal activity against the test pathogens, significantly inhibiting both mycelial growth and spore germination, where C. musae was found most sensitive under in vitro conditions. In vivo fumigation with phenyl-ethanol significantly suppressed post-harvest diseases by 95.75% in banana, 87.12% in apple, and 78.84% in orange. The in silico investigation additionally revealed that phenyl-ethanol binds stably within sterol-14-α-demethylase of C. musae, supporting its potential to interfere with ergosterol biosynthesis in the fungus. The outcome indicated that microbial or chemical interactions can modulate the volatile metabolome and highlight the potential of yeast-derived volatile compounds as promising tools for sustainable post-harvest disease management.

Indexed as

HanseniasporaMetabolomePlant DiseasesVolatile Organic CompoundsAlternariaColletotrichumFruitFungicides, IndustrialMalusPenicilliumFungicides, IndustrialVolatile Organic CompoundsAntagonist yeastHanseniaspora uvarumPhenyl-ethanolPost-harvest pathogensVolatile organic compounds

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.