Evidence map›Paper›PMID 42086219›Full record

ReviewEnvironmental microbiology2026

A 'Genome-First' Framework for Next-Generation Bioinputs: From Functional Mining to Rational Synthetic Microbial Communities.

Osiel Silva Gonçalves

Abstract readReview
In one paragraph

Review in Environmental 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

1 author.

Osiel Silva GonçalvesDepartment of Biological Science, Microbial Eco-Evolutionary Genomics Group, Midwestern Parana State University (Unicentro), Paraná, Brazil.ORCID https://orcid.org/0000-0002-6311-799X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The demand for sustainable agriculture has shifted bioprospecting towards microbial bioinputs as alternatives to chemical fertilisers and pesticides. Whole-genome sequencing accelerates the discovery of plant-growth-promoting bacteria (PGPB) by enabling the identification of functional genes and the prediction of traits such as nutrient solubilisation, phytohormone production and biocontrol. Traditionally a secondary tool for strain characterisation, genomics has evolved into a 'genome-first' strategy that effectively collapses the phenotypic bottleneck in prospective bioprospecting and the rational design of synthetic microbial communities (SynComs). In this review, we argue for a transition from empirical phenotypic screening towards a genomics-guided paradigm for the selection of next-generation bioinputs. This work demonstrates how actionable insights can be gained through the integration of high-resolution genome mining into discovery pipelines. We explore the application of reverse ecology to infer ecological roles from genomic content and emphasise the critical role of pangenomics in identifying traits linked to host colonisation and niche adaptation. Furthermore, we advocate for biosafety screening as a non-negotiable prerequisite for bioinoculant development to ensure ecological and clinical safety. Finally, this work proposes that genome-scale metabolic networks are essential to enable the transition from single-strain inoculants to the assembly of stable SynComs. This framework establishes a comprehensive, data-driven approach to predictable interventions in the agricultural bioeconomy.

Indexed as

BacteriaBioprospectingGenome, BacterialMicrobiotaGenomicsbioinoculantsbioprospectinggenome‐scale metabolic networksplant‐growth‐promoting bacteria

Identifiers

PMID42086219
PMCPMC13143410

What Socratic holds

Textmetadata
LicenceCC BY
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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 Socratic graph.