GapMind for catabolism of small carbon sources

 

glycerol catabolism in Sphingomonas koreensis DSMZ 15582

Best path

glpF, glpK, glpD, tpi

Also see fitness data for the top candidates

Rules

Overview: Glycerol utilization in GapMind is based on MetaCyc pathways glycerol degradation I via glycerol kinase (link), II via dihydroxyacetone kinase (link), or V via dihydroxyacetone:PEP phosphotransferase (link). Two fermentative pathways are not included because they do not lead to carbon incorporation (link, link).

25 steps (9 with candidates)

Or see definitions of steps

Step Description Best candidate 2nd candidate
glpF glycerol facilitator glpF Ga0059261_1307 Ga0059261_3272
glpK glycerol kinase Ga0059261_0833 Ga0059261_2623
glpD glycerol 3-phosphate dehydrogenase (monomeric) Ga0059261_3265
tpi triose-phosphate isomerase Ga0059261_0254 Ga0059261_0728
Alternative steps:
aqp-3 glycerol porter aqp-3
dhaD glycerol dehydrogenase Ga0059261_2879 Ga0059261_2966
dhaK dihydroxyacetone:PEP phosphotransferase, subunit K
dhaK' dihydroxyacetone kinase, ATP dependent (monomeric)
dhaL dihydroxyacetone:PEP phosphotransferase, subunit L
dhaM dihydroxyacetone:PEP phosphotransferase, subunit M
fps1 glycerol uptake/efflux facilitator protein
glpA glycerol 3-phosphate dehydrogenase subunit A
glpB glycerol 3-phosphate dehydrogenase subunit B
glpC glycerol 3-phosphate dehydrogenase subunit C
glpF' glycerol facilitator-aquaporin
glpO glycerol 3-phosphate oxidase Ga0059261_3265
glpP glycerol ABC transporter, permease component 1 (GlpP)
glpQ glycerol ABC transporter, permease component 2 (GlpQ)
glpS glycerol ABC transporter, ATPase component 1 (GlpS)
glpT glycerol ABC transporter, ATPase component 2 (GlpT) Ga0059261_3874 Ga0059261_2556
glpV glycerol ABC transporter, substrate-binding component GlpV
PLT5 glycerol:H+ symporter PLT5 Ga0059261_1777
stl1 glycerol:H+ symporter Stl1p
TIPa glycerol facilitator TIPa Ga0059261_1307
YFL054C glycrol facilitator protein

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 preprint 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