GapMind for catabolism of small carbon sources

 

D-ribose catabolism

Analysis of pathway ribose in 35 genomes

Genome Best path
Acidovorax sp. GW101-3H11 frcA, frcB, frcC, rbsK
Azospirillum brasilense Sp245 rbsU, rbsK
Bacteroides thetaiotaomicron VPI-5482 BT2809, rbsK
Burkholderia phytofirmans PsJN rbsA, rbsB, rbsC, rbsK
Caulobacter crescentus NA1000 rbsU, rbsK
Cupriavidus basilensis 4G11 rbsU, rbsK
Dechlorosoma suillum PS rbsU, rbsK
Desulfovibrio vulgaris Hildenborough rbsU, rbsK
Desulfovibrio vulgaris Miyazaki F rbsU, rbsK
Dinoroseobacter shibae DFL-12 frcA, frcB, frcC, rbsK
Dyella japonica UNC79MFTsu3.2 rbsU, rbsK
Echinicola vietnamensis KMM 6221, DSM 17526 rbsA, rbsB, rbsC, rbsK
Escherichia coli BW25113 rbsA, rbsB, rbsC, rbsK
Herbaspirillum seropedicae SmR1 rbsA, rbsB, rbsC, rbsK
Klebsiella michiganensis M5al rbsA, rbsB, rbsC, rbsK
Magnetospirillum magneticum AMB-1 rbsU, rbsK
Marinobacter adhaerens HP15 rbsU, rbsK
Paraburkholderia bryophila 376MFSha3.1 rbsA, rbsB, rbsC, rbsK
Pedobacter sp. GW460-11-11-14-LB5 rbsU, rbsK
Phaeobacter inhibens BS107 frcA, frcB, frcC, rbsK
Pseudomonas fluorescens FW300-N1B4 rbsA, rbsB, rbsC, rbsK
Pseudomonas fluorescens FW300-N2C3 rbsA, rbsB, rbsC, rbsK
Pseudomonas fluorescens FW300-N2E2 rbsA, rbsB, rbsC, rbsK
Pseudomonas fluorescens FW300-N2E3 rbsA, rbsB, rbsC, rbsK
Pseudomonas fluorescens GW456-L13 rbsA, rbsB, rbsC, rbsK
Pseudomonas putida KT2440 rbsA, rbsB, rbsC, rbsK
Pseudomonas simiae WCS417 rbsA, rbsB, rbsC, rbsK
Pseudomonas stutzeri RCH2 rbsU, rbsK
Shewanella amazonensis SB2B rbsU, rbsK
Shewanella loihica PV-4 rbsU, rbsK
Shewanella oneidensis MR-1 rbsU, rbsK
Shewanella sp. ANA-3 rbsU, rbsK
Sinorhizobium meliloti 1021 frcA, frcB, frcC, rbsK
Sphingomonas koreensis DSMZ 15582 rbsU, rbsK
Synechococcus elongatus PCC 7942 rbsU, rbsK

Confidence: high confidence medium confidence low confidence
transporter – transporters and PTS systems are shaded because predicting their specificity is particularly challenging.

This GapMind analysis is from Sep 17 2021. The underlying query database was built on Sep 17 2021.

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About GapMind

Each pathway is defined by a set of rules based on individual steps or genes. Candidates for each step are identified by using ublast against a database of manually-curated proteins (most of which are experimentally characterized) or by using HMMer. Ublast hits may be split across two different proteins.

A candidate for a step is "high confidence" if either:

where "other" refers to the best ublast hit to a sequence that is not annotated as performing this step (and is not "ignored").

Otherwise, a candidate is "medium confidence" if either:

Other blast hits with at least 50% coverage are "low confidence."

Steps with no high- or medium-confidence candidates may be considered "gaps." For the typical bacterium that can make all 20 amino acids, there are 1-2 gaps in amino acid biosynthesis pathways. Gaps may be due to:

GapMind relies on the predicted proteins in the genome and does not search the six-frame translation. In most cases, you can search the six-frame translation by clicking on links to Curated BLAST for each step definition (in the per-step page).

For more information, see the paper from 2019 on GapMind for amino acid biosynthesis, or view the source code.

If you notice any errors or omissions in the step descriptions, or any questionable results, please let us know

by Morgan Price, Arkin group, Lawrence Berkeley National Laboratory