Evidence map›Paper›PMID 42390747›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2026

Automating Plasmid Construction for High-Throughput Heterologous Expression of Fungal Gene Clusters.

Anjali D Shah, Andrew M Bailey, Katherine Williams

Abstract read
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Article in Methods in molecular biology (Clifton, N.J.), 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

3 authors.

Anjali D ShahSchool of Biological Sciences, Life Sciences Building, University of Bristol, Bristol, UK.
Andrew M BaileySchool of Biological Sciences, Life Sciences Building, University of Bristol, Bristol, UK.
Katherine WilliamsSchool of Biological Sciences, Life Sciences Building, University of Bristol, Bristol, UK. katherine12.williams@uwe.ac.uk.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Fungi are renowned for producing a diverse range of small-molecule natural products with applications in the food, pharmaceutical, and agrochemical industries. While bioinformatics can rapidly identify potential biosynthetic gene clusters (BGCs), their functional analysis remains a bottleneck, limiting the discovery of novel compounds. Advances in molecular techniques and genome sequencing now enable heterologous expression of biosynthetic pathways in hosts like Aspergillus oryzae, facilitating access to metabolites not achievable through traditional methods. However, given the high number of uncharacterized gene clusters, a high-throughput process is crucial for efficiently mining novel natural products. This chapter outlines a streamlined, high-throughput protocol using yeast homologous recombination and automated liquid handling to construct multigene plasmids for heterologous expression. While this chapter uses A. oryzae NSAR1 and the pTYGS series of expression vectors as an example, the core principles of this robotics-driven protocol are adaptable to other heterologous hosts, vectors, and organisms, providing a powerful tool for high-throughput discovery and engineering of natural products.

Indexed as

Aspergillus oryzaeGenes, FungalMultigene FamilyPlasmidsBiological ProductsBiosynthetic PathwaysCloning, MolecularGenetic VectorsHigh-Throughput Screening AssaysHomologous RecombinationSaccharomyces cerevisiaeBiological ProductsAspergillus oryzaeAutomationBiosynthetic gene clustersFungal natural productsHeterologous expressionHigh-throughputLiquid-handling robotSecondary metabolitesYeast homologous recombination

Identifiers

PMID42390747

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.