GapMind for catabolism of small carbon sources

 

L-serine catabolism

Analysis of pathway serine in 35 genomes

Genome Best path
Acidovorax sp. GW101-3H11 Ac3H11_2396, Ac3H11_1695, Ac3H11_1694, Ac3H11_1693, Ac3H11_1692, sdaB
Azospirillum brasilense Sp245 braC, braD, braE, braF, braG, sdaB
Bacteroides thetaiotaomicron VPI-5482 snatA, sdaB
Burkholderia phytofirmans PsJN Ac3H11_2396, Ac3H11_1695, Ac3H11_1694, Ac3H11_1693, Ac3H11_1692, sdaB
Caulobacter crescentus NA1000 snatA, sdaB
Cupriavidus basilensis 4G11 Ac3H11_2396, Ac3H11_1695, Ac3H11_1694, Ac3H11_1693, Ac3H11_1692, sdaB
Dechlorosoma suillum PS Ac3H11_2396, Ac3H11_1695, Ac3H11_1694, Ac3H11_1693, Ac3H11_1692, sdaB
Desulfovibrio vulgaris Hildenborough braC, braD, braE, braF, braG, sdaB
Desulfovibrio vulgaris Miyazaki F braC, braD, braE, braF, braG, sdaB
Dinoroseobacter shibae DFL-12 snatA, sdaB
Dyella japonica UNC79MFTsu3.2 serP, sdaB
Echinicola vietnamensis KMM 6221, DSM 17526 serP, sdaB
Escherichia coli BW25113 dlsT, sdaB
Herbaspirillum seropedicae SmR1 Ac3H11_2396, Ac3H11_1695, Ac3H11_1694, Ac3H11_1693, Ac3H11_1692, sdaB
Klebsiella michiganensis M5al Ac3H11_2396, Ac3H11_1695, Ac3H11_1694, Ac3H11_1693, Ac3H11_1692, sdaB
Magnetospirillum magneticum AMB-1 braC, braD, braE, braF, braG, sdaB
Marinobacter adhaerens HP15 braC, braD, braE, braF, braG, sdaB
Paraburkholderia bryophila 376MFSha3.1 Ac3H11_2396, Ac3H11_1695, Ac3H11_1694, Ac3H11_1693, Ac3H11_1692, sdaB
Pedobacter sp. GW460-11-11-14-LB5 serP, sdaB
Phaeobacter inhibens BS107 snatA, sdaB
Pseudomonas fluorescens FW300-N1B4 braC, braD, braE, braF, braG, sdaB
Pseudomonas fluorescens FW300-N2C3 braC, braD, braE, braF, braG, sdaB
Pseudomonas fluorescens FW300-N2E2 braC, braD, braE, braF, braG, sdaB
Pseudomonas fluorescens FW300-N2E3 braC, braD, braE, braF, braG, sdaB
Pseudomonas fluorescens GW456-L13 braC, braD, braE, braF, braG, sdaB
Pseudomonas putida KT2440 braC, braD, braE, braF, braG, sdaB
Pseudomonas simiae WCS417 braC, braD, braE, braF, braG, sdaB
Pseudomonas stutzeri RCH2 braC, braD, braE, braF, braG, sdaB
Shewanella amazonensis SB2B sdaC, sdaB
Shewanella loihica PV-4 sdaC, sdaB
Shewanella oneidensis MR-1 sdaC, sdaB
Shewanella sp. ANA-3 dlsT, sdaB
Sinorhizobium meliloti 1021 braC, braD, braE, braF, braG, sdaB
Sphingomonas koreensis DSMZ 15582 snatA, sdaB
Synechococcus elongatus PCC 7942 braC, braD, braE, braF, braG, sdaB

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