Evidence map›Paper›PMID 29619083›Full record

ArticleBiotechnology for biofuels2018

Engineering of

Zaigao Tan, Jong Moon Yoon, Anupam Chowdhury, Kaitlin Burdick, Laura R Jarboe, Costas D Maranas, Jacqueline V Shanks

Abstract read
In one paragraph

Article in Biotechnology for biofuels, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

15 citing papers in PubMed.

  1. D-CAPS: an efficient CRISPR-Cas9-based phage defense system forActa biochimica et biophysica Sinica · 2025
    Article
  2. Article
  3. Article
  4. Review
  5. Article
  6. Review
  7. Review
  8. Article
  9. The era of big data: Genome-scale modelling meets machine learning.Computational and structural biotechnology journal · 2020
    Review
  10. Development and Application of CRISPR/Cas in Microbial Biotechnology.Frontiers in bioengineering and biotechnology · 2020
    Review
  11. Article
  12. Article
  13. EngineeringPeerJ · 2019
    Article
  14. Review
  15. 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

7 authors.

Zaigao Tan *1Department of Chemical and Biological Engineering, Iowa State University, 3031 Sweeney, Ames, IA 50011 USA.ORCID 0000-0003-4528-0723
Jong Moon Yoon *1Department of Chemical and Biological Engineering, Iowa State University, 3031 Sweeney, Ames, IA 50011 USA.
Anupam Chowdhury2Department of Chemical Engineering, The Pennsylvania State University, University Park, PA 16802 USA.
Kaitlin Burdick1Department of Chemical and Biological Engineering, Iowa State University, 3031 Sweeney, Ames, IA 50011 USA.
Laura R Jarboe1Department of Chemical and Biological Engineering, Iowa State University, 3031 Sweeney, Ames, IA 50011 USA.
Costas D Maranas2Department of Chemical Engineering, The Pennsylvania State University, University Park, PA 16802 USA.
Jacqueline V Shanks1Department of Chemical and Biological Engineering, Iowa State University, 3031 Sweeney, Ames, IA 50011 USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAs a versatile platform chemical, construction of microbial catalysts for free octanoic acid production from biorenewable feedstocks is a promising alternative to existing petroleum-based methods. However, the bio-production strategy has been restricted by the low capacity of

resultsFirst, a customized OptForce methodology was run to predict a set of four genetic interventions required for production of octanoic acid at 90% of the theoretical yield. Subsequently, all the ten candidate proteins associated with the predicted interventions were regulated individually, as well as in contrast to the combination of interventions as suggested by the OptForce strategy. Among these enzymes, increased production of 3-hydroxy-acyl-ACP dehydratase (FabZ) resulted in the highest increase (+ 45%) in octanoic acid titer. But importantly, the combinatorial application of FabZ with the other interventions as suggested by OptForce further improved octanoic acid production, resulting in a high octanoic acid-producing

conclusionsThis work demonstrates the effectiveness of integration of computational strain design and experimental characterization as a starting point in rewiring metabolism for octanoic acid production. This result in conjunction with the results of other studies using OptForce in strain design demonstrates that this strategy may be also applicable to engineering

Indexed as

Combinatorial engineeringComputational strain designCRISPR–Cas9Octanoic acid (C8)OptForce

Identifiers

PMID29619083
PMCPMC5879999

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.