Evidence map›Paper›PMID 18252819›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2008

Assessing the potential of mutational strategies to elicit new phenotypes in industrial strains.

Daniel Klein-Marcuschamer, Gregory Stephanopoulos

Abstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.

0numbers the graph read from it
0cells of the map it votes in
27citing 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

27 citing papers in PubMed.

  1. Article
  2. Review
  3. Improving acid resistance ofFrontiers in bioengineering and biotechnology · 2023
    Article
  4. Article
  5. Applied and environmental microbiology · 2020
    Article
  6. Article
  7. Article
  8. Mutator genomes decay, despite sustained fitness gains, in a long-term experiment with bacteria.Proceedings of the National Academy of Sciences of the United States of America · 2017
    Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Review
  14. Article
  15. Article
  16. Review
  17. Review
  18. Article
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  20. 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

2 authors.

Daniel Klein-MarcuschamerDepartment of Chemical Engineering, Massachusetts Institute of Technology, Room 56-469, Cambridge, MA 02139, USA.
Gregory Stephanopoulos

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Industrial strains have been traditionally improved by rational approaches and combinatorial methods involving mutagenesis and selection. Recently, other methods have emerged, such as the use of artificial transcription factors and engineering of the native ones. As methods for generating genetic diversity continue to proliferate, the need for quantifying phenotypic diversity and, hence, assessing the potential of various genetic libraries for strain improvement becomes more pronounced. Here, we present a metric based on the quantification of phenotypic diversity, using Lactobacillus plantarum as a model organism. We found that phenotypic diversity can be introduced by mutagenesis of the principal sigma factor, that this diversity can be modulated by tuning the sequence diversity, and that this method compares favorably with commonly used protocols for chemical mutagenesis. The results of the diversity metric here developed also correlated well with the probability of finding improved mutants in the different libraries, as determined by recursive screening under stress. In addition, we subjected our libraries to lactic and inorganic acids and found strains with improved growth in both conditions, with a concomitant increase in lactate productivity.

Indexed as

MutagenesisBiotechnologyDatabases, GeneticGenetic EngineeringHydrogen-Ion ConcentrationIndustryLactic AcidLactiplantibacillus plantarumMeiosisMutationPhenotypeSigma FactorLactic AcidSigma Factor

Identifiers

PMID18252819
PMCPMC2268134

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.