Evidence map›Paper›PMID 30899819›Full record

ReviewSynthetic and systems biotechnology2019

Resistance mechanisms and reprogramming of microorganisms for efficient biorefinery under multiple environmental stresses.

Ke Xu, Yun Seo Lee, Jun Li, Chun Li

Erratum issuedAbstract readReview
In one paragraph

Review in Synthetic and systems biotechnology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Metabolic Engineering ofJournal of fungi (Basel, Switzerland) · 2026
    Article
  2. Article
  3. Review
  4. Achieving robust synthetic tolerance in industrialSynthetic and systems biotechnology · 2024
    Article
  5. Article
  6. Review
  7. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

Ke XuInstitute for Synthetic Biosystem/Department of Biochemical Engineering, School of Chemistry and Chemical Engineering, Beijing Institute of Technology, Beijing 100081, PR China.
Yun Seo LeeInstitute for Synthetic Biosystem/Department of Biochemical Engineering, School of Chemistry and Chemical Engineering, Beijing Institute of Technology, Beijing 100081, PR China.
Jun LiInstitute for Synthetic Biosystem/Department of Biochemical Engineering, School of Chemistry and Chemical Engineering, Beijing Institute of Technology, Beijing 100081, PR China.
Chun LiInstitute for Synthetic Biosystem/Department of Biochemical Engineering, School of Chemistry and Chemical Engineering, Beijing Institute of Technology, Beijing 100081, PR China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In the fermentation process of biorefinery, industrial strains are normally subjected to adverse environmental stresses, which leads to their slow growth, yield decline, a substantial increase in energy consumption, and other negative consequences, which ultimately seriously hamper the development of biorefinery. How to minimize the impact of stress on microorganisms is of great significance. This review not only reveals the damaging effects of different environmental stresses on microbial strains but also introduces commonly used strategies to improve microbial tolerance, including adaptive evolution, reprogramming of the industrial host based on genetic circuits, global transcription machinery engineering (gTME) and bioprocess integration. Furthermore, by integrating the advantages of these strategies and reducing the cost of system operation, the tolerance of industrial strains, combined with production efficiency and process stability, will be greatly improved, and the development prospects of biorefinery will be more widespread.

Indexed as

Bioprocess integrationBiorefineryEnvironmental stressesMicrobial resistance mechanismSynthetic biology

Identifiers

PMID30899819
PMCPMC6407310

What OpenQuestion holds

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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.