Evidence map›Paper›PMID 42210068›Full record

ArticleBMC microbiology2026

Functional and genomic characterization of ligninolytic Bacillus strains for improved jute fibre delignification.

Shrestha Barai, Bijan Majumdar, Pranit Mukherjee, Lipi Chattopadhyay, Gouranga Kar, Subhojit Datta

Abstract read
In one paragraph

Article in BMC microbiology, 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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0citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Shrestha Barai *Division of Crop Production, ICAR - Central Research Institute for Jute and Allied Fibres, Barrackpore, West Bengal, 700121, India.ORCID 0009-0005-9990-7677
Bijan MajumdarDivision of Crop Production, ICAR - Central Research Institute for Jute and Allied Fibres, Barrackpore, West Bengal, 700121, India. bmajumdar65@gmail.com.ORCID 0000-0001-7991-0960
Pranit Mukherjee *Biotechnology Unit, Division of Crop Improvement, ICAR-Central Research Institute for Jute and Allied Fibres, Nilganj, Barrackpore, Kolkata, West Bengal, 700121, India.ORCID 0000-0003-0992-0455
Lipi ChattopadhyayDivision of Crop Production, ICAR - Central Research Institute for Jute and Allied Fibres, Barrackpore, West Bengal, 700121, India.ORCID 0000-0002-9107-9046
Gouranga KarICAR - Central Research Institute for Jute and Allied Fibres, Nilganj, Barrackpore, Kolkata, West Bengal, 700121, India.ORCID 0000-0001-8744-7574
Subhojit DattaBiotechnology Unit, Division of Crop Improvement, ICAR-Central Research Institute for Jute and Allied Fibres, Nilganj, Barrackpore, Kolkata, West Bengal, 700121, India. subhojitdatta1@gmail.com.ORCID 0000-0002-5924-4355

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Lignin, the second most abundant biopolymer on Earth, imparting rigidity to plant cell walls but poses a challenge in the processing of lignocellulosic biomass such as jute (Corchorus spp.). Compared to other bast fibers such as flax and ramie, jute fiber has a very high lignin content (13.3% to 15%), hindering its use in the textile sector. Although chemical methods for lignin degradation are widely used, they are environmentally damaging and economically unfeasible. Consequently, bacterial lignin-degrading enzymes, especially those derived from Bacillus species, have attracted interest owing to their resilience and adaptability. This study investigated three Bacillus strains-LJRB1 (Bacillus subtilis), LJRB2 (Bacillus amyloliquefaciens), and LJRB3 (Bacillus licheniformis)-which were identified for their efficient lignin-degrading capabilities. Comprehensive characterization of these strains was performed, including growth condition optimization, enzyme profiling (MnP and LiP), and genomic analysis via whole-genome sequencing to identify key ligninolytic genes. These strains, if combined with previously proven high-efficiency pectinolytic strains (PJRB 1-3) will enhance the microbial retting consortium by simultaneously reducing the fiber lignin content and retting time. These findings lay the foundation for the development of a next-generation microbial retting formulation that is eco-friendly, cost-effective, and industry-oriented, potentially enhancing the quality and marketability of jute fiber for high-end applications.

Indexed as

BacillusLigninBacillus licheniformisBacterial ProteinsGenomicsBacterial ProteinsLigninlignocelluloseBacillus speciesCAZymesJute rettingLigninolytic enzymesMicrobial consortium

Identifiers

PMID42210068
PMCPMC13435682

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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.