ArticleScientific reports2025
Combined genomic and phenomic analyses reveals multifunctionality of Paenibacillus polymyxa K16 for plant's nutrition, growth and health.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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.
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.
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Who cites it
2 citing papers in PubMed.
- ALife (Basel, Switzerland) · 2026Article
- Integrated functional genomics and safety assessment of plant-growth-promoting Caryophanales from post-maize-cultivation soils.BMC genomics · 2026Article
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Authors and funding
12 authors.
Funding
Abstract
The application of beneficial microorganisms with biostimulant, biofertilizer, and/or biopesticide properties represents an alternative to the use of chemicals in agriculture. Nevertheless, bioproducts' selection and application efficacy under field condition need to be improved. A deeper understanding of the bioinoculant strains at genomic and phenomic level, would advance selection process and field application. The objective of this manuscript was to develop a combined genomic-phenomic approach for the characterization of bioproducts, and to demonstrate its application with a real use-case scenario. At the genomic level, the presence of several functional genes supporting plant nutrition (e.g., nitrate conversion into ammonia, phosphorous solubilization, siderophore production), improving plant growth (e.g., plant hormones) or promoting plant health through antagonism to plant pathogens, pointed to the multifunctionality of the strain. The phenomic analysis showed various carbon, nitrogen, phosphate, and sulfur utilization patterns, and confirmed the expression of the associated metabolic pathways. Our analysis approach encompasses as many aspects of the genome and phenome as possible for understanding the complexities of a microorganism, enabling the generation of greater value compared to the individual technologies. The proposed approach unlocks data-driven decision making in bioproduct optimisation, as such should be routinely included in screening programs.
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Registered trials
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.