Evidence map›Paper›PMID 39628520›Full record

ReviewEngineering microbiology2023

Next-generation synthetic biology approaches for the accelerated discovery of microbial natural products.

Lei Li

Abstract readReview
In one paragraph

Review in Engineering microbiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Antimicrobial Activity ofInternational journal of molecular sciences · 2025
    Review
  2. Review
  3. Article
  4. Article
  5. Article
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.

Lei LiState Key Laboratory of Microbial Metabolism and School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, 800 Dongchuan Rd., Shanghai 200240, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Microbial natural products (NPs) and their derivates have been widely used in health care and agriculture during the past few decades. Although large-scale bacterial or fungal (meta)genomic mining has revealed the tremendous biosynthetic potentials to produce novel small molecules, there remains a lack of universal approaches to link NP biosynthetic gene clusters (BGCs) to their associated products at a large scale and speed. In the last ten years, a series of emerging technologies have been established alongside the developments in synthetic biology to engineer cryptic metabolite BGCs and edit host genomes. Diverse computational tools, such as antiSMASH and PRISM, have also been simultaneously developed to rapidly identify BGCs and predict the chemical structures of their products. This review discusses the recent developments and trends pertaining to the accelerated discovery of microbial NPs driven by a wide variety of next-generation synthetic biology approaches, with an emphasis on the

Indexed as

Large-scale discoveryNatural productsPeptide synthesisSilent BGCsSynthetic biology

Identifiers

PMID39628520
PMCPMC11610963

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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Registered trials

None linked

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.