Evidence map›Paper›PMID 42473946›Full record

ReviewJournal of basic microbiology2026

Phages as Metabolic Switches in Plant-Associated Microbiomes: Implications for Climate-Smart Agriculture.

Baber Ali, Muhammad Khan, Muhammad Osama, Hamza Iftikhar, Pakiza Zaman, Mustafa Naeem Khan, Ayesha Imran, Nijat Imin, Zeeshan Khan

Abstract readReview
In one paragraph

Review in Journal of basic 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.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Baber AliFaculty of Engineering, Computing and Science, Western Sydney University, Penrith, New South Wales, Australia.ORCID https://orcid.org/0000-0003-1553-2248
Muhammad KhanAtta ur Rahman School of Applied Biosciences (ASAB), National University of Sciences and Technology (NUST), Islamabad, Pakistan.ORCID https://orcid.org/0009-0005-9234-6563
Muhammad OsamaAtta ur Rahman School of Applied Biosciences (ASAB), National University of Sciences and Technology (NUST), Islamabad, Pakistan.ORCID https://orcid.org/0009-0004-5149-911X
Hamza IftikharAtta ur Rahman School of Applied Biosciences (ASAB), National University of Sciences and Technology (NUST), Islamabad, Pakistan.ORCID https://orcid.org/0009-0009-7354-1194
Pakiza ZamanAtta ur Rahman School of Applied Biosciences (ASAB), National University of Sciences and Technology (NUST), Islamabad, Pakistan.ORCID https://orcid.org/0009-0002-4901-297X
Mustafa Naeem KhanAtta ur Rahman School of Applied Biosciences (ASAB), National University of Sciences and Technology (NUST), Islamabad, Pakistan.ORCID https://orcid.org/0009-0002-6647-6100
Ayesha ImranAtta ur Rahman School of Applied Biosciences (ASAB), National University of Sciences and Technology (NUST), Islamabad, Pakistan.ORCID https://orcid.org/0009-0002-5029-808X
Nijat IminFaculty of Engineering, Computing and Science, Western Sydney University, Penrith, New South Wales, Australia.
Zeeshan KhanAtta ur Rahman School of Applied Biosciences (ASAB), National University of Sciences and Technology (NUST), Islamabad, Pakistan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Bacteriophages constitute a regulatory layer in plant-associated microbiomes that has been systematically under-characterized relative to their ecological importance. This review advances the hypothesis that phages function as metabolic switches, alternating between lytic nutrient release and lysogenic host-fitness enhancement to govern the microbial metabolic states that determine nutrient cycling, stress responses, and microbiome stability in the rhizosphere and phyllosphere. During lytic infection, phage-driven cell lysis releases dissolved organic carbon, ammonium, and phosphate through the viral shunt, redistributing microbial biomass into forms directly accessible to plant roots and surviving microbial taxa. Lysogenic integration, by contrast, delivers prophage-encoded auxiliary metabolic genes that reprogram bacterial hosts with enhanced metabolic capacity across multiple generations without immediate cell death. Environmental stressors, include drought, salinity, temperature extremes, heavy metal contamination, and pathogen pressure remodel root exudation profiles, alter microbial metabolic bottlenecks, and shift phage life-cycle decisions through quorum-sensing-responsive and SOS-dependent switching mechanisms. These phage-mediated processes have cascading consequences for plant-relevant outcomes including nutrient uptake efficiency, oxidative stress management, phytohormone signaling, and growth-defense trade-offs mediated by plant growth-promoting rhizobacteria. By integrating mechanistic evidence across abiotic and biotic stress contexts, this review proposes a phage-microbe-plant metabolic axis as a unifying framework for understanding how soil virome dynamics translate into plant physiological outcomes. Practical implications for engineering phage-informed microbiomes and developing climate-resilient agricultural systems are evaluated alongside ecological risks, knowledge gaps, and priorities for field validation, virome mapping, and predictive modeling that must be addressed before phage-based interventions can be reliably deployed in crop production.

Indexed as

BacteriaBacteriophagesMicrobiotaPlantsAgricultureLysogenyPlant RootsRhizosphereSoil MicrobiologyStress, Physiologicalauxiliary metabolic genesbacteriophagesclimate‐smart agriculturelytic‐lysogenic switchingmetabolic switchingplant stress physiologyrhizosphere microbiomeviral shunt

Identifiers

PMID42473946
PMCPMC13383287

What OpenQuestion holds

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Registered trials

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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.