GapMind for catabolism of small carbon sources

 

N-acetyl-D-glucosamine catabolism

Analysis of pathway NAG in 35 genomes

Genome Best path
Acidovorax sp. GW101-3H11 nagEcba, nagA, nagB
Azospirillum brasilense Sp245 nagEcba, nagA, nagB
Bacteroides thetaiotaomicron VPI-5482 nagP, nagK, nagA, nagB
Burkholderia phytofirmans PsJN nagF, nagEcb, nagA, nagB
Caulobacter crescentus NA1000 nagF, nagEcb, nagA, nagB
Cupriavidus basilensis 4G11 nagEcba, nagA, nagB
Dechlorosoma suillum PS nagEcba, nagA, nagB
Desulfovibrio vulgaris Hildenborough nagEcba, nagA, nagB
Desulfovibrio vulgaris Miyazaki F nagEcba, nagA, nagB
Dinoroseobacter shibae DFL-12 nagEcba, nagA, nagB
Dyella japonica UNC79MFTsu3.2 nagP, nagK, nagA, nagB
Echinicola vietnamensis KMM 6221, DSM 17526 nagEcba, nagA, nagB
Escherichia coli BW25113 nagEcba, nagA, nagB
Herbaspirillum seropedicae SmR1 SMc02869, SMc02872, SMc02871, SMc02873, nagK, nagA, nagB
Klebsiella michiganensis M5al nagEcba, nagA, nagB
Magnetospirillum magneticum AMB-1 nagEcba, nagA, nagB
Marinobacter adhaerens HP15 nagEcba, nagA, nagB
Paraburkholderia bryophila 376MFSha3.1 nagF, nagEcb, nagA, nagB
Pedobacter sp. GW460-11-11-14-LB5 nagP, nagK, nagA, nagB
Phaeobacter inhibens BS107 SMc02869, SMc02872, SMc02871, SMc02873, nagK, nagA, nagB
Pseudomonas fluorescens FW300-N1B4 nagEcba, nagA, nagB
Pseudomonas fluorescens FW300-N2C3 nagF, nagEcb, nagA, nagB
Pseudomonas fluorescens FW300-N2E2 nagEcba, nagA, nagB
Pseudomonas fluorescens FW300-N2E3 nagF, nagEcb, nagA, nagB
Pseudomonas fluorescens GW456-L13 nagF, nagEcb, nagA, nagB
Pseudomonas putida KT2440 nagEcba, nagA, nagB
Pseudomonas simiae WCS417 nagF, nagEcb, nagA, nagB
Pseudomonas stutzeri RCH2 nagEcba, nagA, nagB
Shewanella amazonensis SB2B nagP, nagK, nagA, nagB
Shewanella loihica PV-4 nagP, nagK, nagA, nagB
Shewanella oneidensis MR-1 nagP, nagK, nagA, nagB
Shewanella sp. ANA-3 nagP, nagK, nagA, nagB
Sinorhizobium meliloti 1021 SMc02869, SMc02872, SMc02871, SMc02873, nagK, nagA, nagB
Sphingomonas koreensis DSMZ 15582 nagF, nagEcb, nagA, nagB
Synechococcus elongatus PCC 7942 nagEcba, nagA, nagB

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