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Editor's Pick Research Article | Molecular Biology and Physiology

GapMind: Automated Annotation of Amino Acid Biosynthesis

Morgan N. Price, Adam M. Deutschbauer, Adam P. Arkin
Steven J. Hallam, Editor
Morgan N. Price
aEnvironmental Genomics and Systems Biology, Lawrence Berkeley National Laboratory, Berkeley, California, USA
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Adam M. Deutschbauer
aEnvironmental Genomics and Systems Biology, Lawrence Berkeley National Laboratory, Berkeley, California, USA
bPlant & Microbial Biology, University of California, Berkeley, California, USA
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Adam P. Arkin
aEnvironmental Genomics and Systems Biology, Lawrence Berkeley National Laboratory, Berkeley, California, USA
cDepartment of Bioengineering, University of California, Berkeley, California, USA
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Steven J. Hallam
University of British Columbia
Roles: Editor
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DOI: 10.1128/mSystems.00291-20
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Figures

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  • FIG 1
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    FIG 1

    How GapMind works. (A) A pathway with no variants. (B) The definition of a step. (C) Confidence levels for candidates from ublast. (D) Confidence levels for candidates from HMMER.

  • FIG 2
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    FIG 2

    GapMind handles fusion proteins and split proteins. (A) HSERO_RS20920 from Herbaspirillum seropedicae SmR1 is a fusion of AroL and AroB (shown with Swiss-Prot identifiers). (B) Split candidates for vitamin B12-dependent methionine synthase (MetH) in Burkholderia phytofirmans PsJN and Bacteroides thetaiotaomicron VPI-5482. a.a., amino acids.

  • FIG 3
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    FIG 3

    Arginine biosynthesis with succinylated intermediates. (A) The standard pathway. Protein names are from Escherichia coli or Bacillus subtilis. The formation of carbamoyl phosphate (catalyzed by CarAB) is not shown. (B) The pathway in Bacteroides and in other Bacteroidetes. (C) Fitness data from Bacteroides thetaiotaomicron VPI-5482, Echinicola vietnamensis KMM 6221 (DSSM 17526), and Pedobacter sp. strain GW460-11-11-14-LB5 (from references 8 and 20). Each fitness value is the log2 change in the abundance of the mutants in a gene during an experiment. Each experiment went from an optical density at 600 nm of 0.02 to saturation (usually 4 to 8 doublings). Fitness values for CA265_RS18510 were not estimated, because mutants of this gene were at low abundance in the starting samples.

  • FIG 4
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    FIG 4

    Tyrosine synthesis via phenylalanine hydroxylase in Dyella japonica and Echinicola vietnamensis. (A) Gene fitness in Dyella japonica UNC79MFTsu3.2. The x axis shows the median fitness across 59 genes that are predicted to be involved in amino acid biosynthesis (by TIGRFam role [14]), and the y axis shows the fitness of the predicted phenylalanine hydroxylase (PAH). (B) Gene fitness in Echinicola vietnamensis KMM 6221 (DSM 17526) for prephenate dehydrogenase (x axis) and for PAH (y axis). In both panels, we color code experiments by whether or not tyrosine was present in the media. The experiments with tyrosine usually included it via yeast extract or Casamino Acids, while the experiments without tyrosine are in defined media with just one or no amino acids added. Lines show x = 0 and y = 0, corresponding to no effect of mutating the genes. In panel A, lines show x = y.

  • FIG 5
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    FIG 5

    Number of gaps in amino acid biosynthesis in 148 diverse bacteria and archaea that can grow without amino acids. (These are distinct from the 35 bacteria with fitness data.)

  • FIG 6
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    FIG 6

    GapMind’s website renders the best paths for amino acid biosynthesis in Desulfovibrio alaskensis G20. Each step is color coded by its confidence level, and a question mark indicates known gaps in related organisms.

Tables

  • Figures
  • Supplemental Material
  • TABLE 1

    Remaining gaps in amino acid biosynthesis for 35 bacteria that can make all 20 amino acids and have large-scale genetic data

    TABLE 1

Supplemental Material

  • Figures
  • Tables
  • TEXT S1

    Variant pathways and enzymes in GapMind. Download Text S1, PDF file, 0.1 MB.

    Copyright © 2020 Price et al.

    This content is distributed under the terms of the Creative Commons Attribution 4.0 International license.

  • TEXT S2

    Potential pathways not included in GapMind. Download Text S2, PDF file, 0.04 MB.

    Copyright © 2020 Price et al.

    This content is distributed under the terms of the Creative Commons Attribution 4.0 International license.

  • DATA SET S1

    Thirty-five bacteria with large-scale genetic data that grow in defined minimal media. Download Data Set S1, XLS file, 0.01 MB.

    Copyright © 2020 Price et al.

    This content is distributed under the terms of the Creative Commons Attribution 4.0 International license.

  • DATA SET S2

    Novel or diverged biosynthetic enzymes that we annotated using the genetic data. Download Data Set S2, XLS file, 0.03 MB.

    Copyright © 2020 Price et al.

    This content is distributed under the terms of the Creative Commons Attribution 4.0 International license.

  • TEXT S3

    Errors in genome sequences or gene models. Download Text S3, PDF file, 0.04 MB.

    Copyright © 2020 Price et al.

    This content is distributed under the terms of the Creative Commons Attribution 4.0 International license.

  • DATA SET S3

    Genomes of 148 additional bacteria and archaea that grow in defined minimal media. Download Data Set S3, XLS file, 0.04 MB.

    Copyright © 2020 Price et al.

    This content is distributed under the terms of the Creative Commons Attribution 4.0 International license.

  • DATA SET S4

    Manual examination of 20 low-confidence steps from the nitrogen-fixing subset of the 148 bacteria and archaea. Download Data Set S4, XLS file, 0.02 MB.

    Copyright © 2020 Price et al.

    This content is distributed under the terms of the Creative Commons Attribution 4.0 International license.

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GapMind: Automated Annotation of Amino Acid Biosynthesis
Morgan N. Price, Adam M. Deutschbauer, Adam P. Arkin
mSystems Jun 2020, 5 (3) e00291-20; DOI: 10.1128/mSystems.00291-20

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GapMind: Automated Annotation of Amino Acid Biosynthesis
Morgan N. Price, Adam M. Deutschbauer, Adam P. Arkin
mSystems Jun 2020, 5 (3) e00291-20; DOI: 10.1128/mSystems.00291-20
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KEYWORDS

amino acid biosynthesis
gene annotation
high-throughput genetics

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