GapMind for catabolism of small carbon sources

 

glycerol catabolism in Desulfovibrio vulgaris Miyazaki F

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 (14 with candidates)

Or see definitions of steps

Step Description Best candidate 2nd candidate
glpF glycerol facilitator glpF DvMF_0810
glpK glycerol kinase DvMF_0809
glpD glycerol 3-phosphate dehydrogenase (monomeric) DvMF_0811
tpi triose-phosphate isomerase DvMF_0348 DvMF_0975
Alternative steps:
aqp-3 glycerol porter aqp-3
dhaD glycerol dehydrogenase DvMF_0321 DvMF_0990
dhaK dihydroxyacetone:PEP phosphotransferase, subunit K DvMF_2582
dhaK' dihydroxyacetone kinase, ATP dependent (monomeric) DvMF_2582
dhaL dihydroxyacetone:PEP phosphotransferase, subunit L DvMF_2583
dhaM dihydroxyacetone:PEP phosphotransferase, subunit M DvMF_2584
fps1 glycerol uptake/efflux facilitator protein
glpA glycerol 3-phosphate dehydrogenase subunit A DvMF_1126
glpB glycerol 3-phosphate dehydrogenase subunit B
glpC glycerol 3-phosphate dehydrogenase subunit C
glpF' glycerol facilitator-aquaporin DvMF_0810
glpO glycerol 3-phosphate oxidase DvMF_0811
glpP glycerol ABC transporter, permease component 1 (GlpP)
glpQ glycerol ABC transporter, permease component 2 (GlpQ)
glpS glycerol ABC transporter, ATPase component 1 (GlpS) DvMF_0655 DvMF_1960
glpT glycerol ABC transporter, ATPase component 2 (GlpT) DvMF_0655 DvMF_1960
glpV glycerol ABC transporter, substrate-binding component GlpV
PLT5 glycerol:H+ symporter PLT5
stl1 glycerol:H+ symporter Stl1p
TIPa glycerol facilitator TIPa
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 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, 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