Evidence map›Paper›PMID 26637602›Full record

ArticleApplied and environmental microbiology2016

Novel Rhizosphere Soil Alleles for the Enzyme 1-Aminocyclopropane-1-Carboxylate Deaminase Queried for Function with an In Vivo Competition Assay.

Zhao Jin, Sara C Di Rienzi, Anders Janzon, Jeff J Werner, Largus T Angenent, Jeffrey L Dangl, Douglas M Fowler, Ruth E Ley

Open access · hybridAbstract read
In one paragraph

Article in Applied and environmental microbiology, 2016. 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
0.9field-weighted citation impact, top 21% of its field
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, 13 citations in OpenAlex.

  1. Review
  2. A Glucuronic Acid-Producing EndophyteFrontiers in plant science · 2022
    Article
  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

8 authors at 3 institutions in 2 countries.

Zhao JinDepartment of Molecular Biology and Genetics, Cornell University, Ithaca, New York, USA Department of Microbiology, Cornell University, Ithaca, New York, USA.
Sara C Di RienziDepartment of Molecular Biology and Genetics, Cornell University, Ithaca, New York, USA Department of Microbiology, Cornell University, Ithaca, New York, USA.
Anders JanzonDepartment of Molecular Biology and Genetics, Cornell University, Ithaca, New York, USA Department of Microbiology, Cornell University, Ithaca, New York, USA.
Jeff J WernerDepartment of Biological and Environmental Engineering, Cornell University, Ithaca, New York, USA.
Largus T AngenentDepartment of Biological and Environmental Engineering, Cornell University, Ithaca, New York, USA.
Jeffrey L DanglHoward Hughes Medical Institute, Chevy Chase, Maryland, USA Department of Biology, University of North Carolina, Chapel Hill, North Carolina, USA Department of Microbiology and Immunology, University of North Carolina, Chapel Hill, North Carolina, USA Carolina Center for Genome Sciences, University of North Carolina, Chapel Hill, North Carolina, USA.
Douglas M FowlerDepartment of Genome Sciences, University of Washington, Seattle, Washington, USA.
Ruth E LeyDepartment of Molecular Biology and Genetics, Cornell University, Ithaca, New York, USA Department of Microbiology, Cornell University, Ithaca, New York, USA Max Planck Institute for Developmental Biology, Tübingen, Germany rel222@cornell.edu.
Cornell University · USHoward Hughes Medical Institute · USUniversity of Washington · US

Funding

Howard Hughes Medical Institute
6 · The paper itself

Abstract

Metagenomes derived from environmental microbiota encode a vast diversity of protein homologs. How this diversity impacts protein function can be explored through selection assays aimed to optimize function. While artificially generated gene sequence pools are typically used in selection assays, their usage may be limited because of technical or ethical reasons. Here, we investigate an alternative strategy, the use of soil microbial DNA as a starting point. We demonstrate this approach by optimizing the function of a widely occurring soil bacterial enzyme, 1-aminocyclopropane-1-carboxylate (ACC) deaminase. We identified a specific ACC deaminase domain region (ACCD-DR) that, when PCR amplified from the soil, produced a variant pool that we could swap into functional plasmids carrying ACC deaminase-encoding genes. Functional clones of ACC deaminase were selected for in a competition assay based on their capacity to provide nitrogen to Escherichia coli in vitro. The most successful ACCD-DR variants were identified after multiple rounds of selection by sequence analysis. We observed that previously identified essential active-site residues were fixed in the original unselected library and that additional residues went to fixation after selection. We identified a divergent essential residue whose presence hints at the possible use of alternative substrates and a cluster of neutral residues that did not influence ACCD performance. Using an artificial ACCD-DR variant library generated by DNA oligomer synthesis, we validated the same fixation patterns. Our study demonstrates that soil metagenomes are useful starting pools of protein-coding-gene diversity that can be utilized for protein optimization and functional characterization when synthetic libraries are not appropriate.

Indexed as

AllelesRhizosphereSoil MicrobiologyCarbon-Carbon LyasesEscherichia coliGenetic TestingMetagenomicsNitrogen1-aminocyclopropane-1-carboxylate deaminaseCarbon-Carbon LyasesNitrogen

Identifiers

PMID26637602
PMCPMC4751833
OpenAlexW2256516288

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.