GapMind for catabolism of small carbon sources


L-aspartate catabolism

Analysis of pathway aspartate in 35 genomes

Genome Best path
Acidovorax sp. GW101-3H11 aatJ, aatQ, aatM, aatP
Azospirillum brasilense Sp245 bztA, bztB, bztC, bztD
Bacteroides thetaiotaomicron VPI-5482 dauA
Burkholderia phytofirmans PsJN aatJ, aatQ, aatM, aatP
Caulobacter crescentus NA1000 glt
Cupriavidus basilensis 4G11 aatJ, aatQ, aatM, aatP
Dechlorosoma suillum PS aatJ, aatQ, aatM, aatP
Desulfovibrio vulgaris Hildenborough dauA
Desulfovibrio vulgaris Miyazaki F dauA
Dinoroseobacter shibae DFL-12 bztA, bztB, bztC, bztD
Dyella japonica UNC79MFTsu3.2 BPHYT_RS17540
Echinicola vietnamensis KMM 6221, DSM 17526 glt
Escherichia coli BW25113 aatJ, aatQ, aatM, aatP
Herbaspirillum seropedicae SmR1 aatJ, aatQ, aatM, aatP
Klebsiella michiganensis M5al aatJ, aatQ, aatM, aatP
Magnetospirillum magneticum AMB-1 dauA
Marinobacter adhaerens HP15 glt
Paraburkholderia bryophila 376MFSha3.1 aatJ, aatQ, aatM, aatP
Pedobacter sp. GW460-11-11-14-LB5 glt
Phaeobacter inhibens BS107 bztA, bztB, bztC, bztD
Pseudomonas fluorescens FW300-N1B4 aatJ, aatQ, aatM, aatP
Pseudomonas fluorescens FW300-N2C3 aatJ, aatQ, aatM, aatP
Pseudomonas fluorescens FW300-N2E2 aatJ, aatQ, aatM, aatP
Pseudomonas fluorescens FW300-N2E3 aatJ, aatQ, aatM, aatP
Pseudomonas fluorescens GW456-L13 aatJ, aatQ, aatM, aatP
Pseudomonas putida KT2440 aatJ, aatQ, aatM, aatP
Pseudomonas simiae WCS417 aatJ, aatQ, aatM, aatP
Pseudomonas stutzeri RCH2 glt
Shewanella amazonensis SB2B glt
Shewanella loihica PV-4 glt
Shewanella oneidensis MR-1 glt
Shewanella sp. ANA-3 glt
Sinorhizobium meliloti 1021 aapJ, aapQ, aapM, aapP
Sphingomonas koreensis DSMZ 15582 glt
Synechococcus elongatus PCC 7942 natF, bgtB', natH, bgtA

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 (a fast alternative to protein BLAST) against a database of manually-curated proteins (most of which are experimentally characterized) or by using HMMer with enzyme models (usually from TIGRFam). 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. For diverse bacteria and archaea that can utilize a carbon source, there is a complete high-confidence catabolic pathway (including a transporter) just 38% of the time, and there is a complete medium-confidence pathway 63% of the time. 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, the paper from 2022 on GapMind for carbon sources, 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