D-serine catabolism
Analysis of pathway D-serine in 35 genomes
| Genome | Best path |
|---|
| Acidovorax sp. GW101-3H11 | cycA, dsdA |
| Azospirillum brasilense Sp245 | cycA, dsdA |
| Bacteroides thetaiotaomicron VPI-5482 | cycA, dsdA |
| Burkholderia phytofirmans PsJN | cycA, dsdA |
| Caulobacter crescentus NA1000 | cycA, dsdA |
| Cupriavidus basilensis 4G11 | cycA, dsdA |
| Dechlorosoma suillum PS | cycA, dsdA |
| Desulfovibrio vulgaris Hildenborough | cycA, dsdA |
| Desulfovibrio vulgaris Miyazaki F | cycA, dsdA |
| Dinoroseobacter shibae DFL-12 | cycA, dsdA |
| Dyella japonica UNC79MFTsu3.2 | cycA, dsdA |
| Echinicola vietnamensis KMM 6221, DSM 17526 | cycA, dsdA |
| Escherichia coli BW25113 | cycA, dsdA |
| Herbaspirillum seropedicae SmR1 | cycA, dsdA |
| Klebsiella michiganensis M5al | cycA, dsdA |
| Magnetospirillum magneticum AMB-1 | cycA, dsdA |
| Marinobacter adhaerens HP15 | cycA, dsdA |
| Paraburkholderia bryophila 376MFSha3.1 | cycA, dsdA |
| Pedobacter sp. GW460-11-11-14-LB5 | cycA, dsdA |
| Phaeobacter inhibens BS107 | cycA, dsdA |
| Pseudomonas fluorescens FW300-N1B4 | cycA, dsdA |
| Pseudomonas fluorescens FW300-N2C3 | cycA, dsdA |
| Pseudomonas fluorescens FW300-N2E2 | cycA, dsdA |
| Pseudomonas fluorescens FW300-N2E3 | cycA, dsdA |
| Pseudomonas fluorescens GW456-L13 | dsdX, dsdA |
| Pseudomonas putida KT2440 | cycA, dsdA |
| Pseudomonas simiae WCS417 | cycA, dsdA |
| Pseudomonas stutzeri RCH2 | cycA, dsdA |
| Shewanella amazonensis SB2B | cycA, dsdA |
| Shewanella loihica PV-4 | cycA, dsdA |
| Shewanella oneidensis MR-1 | dsdX, dsdA |
| Shewanella sp. ANA-3 | dsdX, dsdA |
| Sinorhizobium meliloti 1021 | cycA, dsdA |
| Sphingomonas koreensis DSMZ 15582 | cycA, dsdA |
| Synechococcus elongatus PCC 7942 | cycA, dsdA |
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:
- ublast finds a hit to a characterized protein at above 40% identity and 80% coverage, and bits >= other bits+10.
- (Hits to curated proteins without experimental data as to their function are never considered high confidence.)
- HMMer finds a hit with 80% coverage of the model, and either other identity < 40 or other coverage < 0.75.
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:
- ublast finds a hit at above 40% identity and 70% coverage (ignoring otherBits).
- ublast finds a hit at above 30% identity and 80% coverage, and bits >= other bits.
- HMMer finds a hit (regardless of coverage or other bits).
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:
- our ignorance of proteins' functions,
- omissions in the gene models,
- frame-shift errors in the genome sequence, or
- the organism lacks the pathway.
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:
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