GapMind for catabolism of small carbon sources

 

glycerol catabolism in Phaeobacter inhibens BS107

Best path

glpS, glpT, glpP, glpQ, glpV, 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 (11 with candidates)

Or see definitions of steps

Step Description Best candidate 2nd candidate
glpS glycerol ABC transporter, ATPase component 1 (GlpS) PGA1_c05220 PGA1_c13180
glpT glycerol ABC transporter, ATPase component 2 (GlpT) PGA1_c05210 PGA1_c02740
glpP glycerol ABC transporter, permease component 1 (GlpP) PGA1_c05200 PGA1_c16700
glpQ glycerol ABC transporter, permease component 2 (GlpQ) PGA1_c05190 PGA1_c16690
glpV glycerol ABC transporter, substrate-binding component GlpV PGA1_c05230
glpK glycerol kinase PGA1_c32030
glpD glycerol 3-phosphate dehydrogenase (monomeric) PGA1_c08240
tpi triose-phosphate isomerase PGA1_c20650 PGA1_c17530
Alternative steps:
aqp-3 glycerol porter aqp-3
dhaD glycerol dehydrogenase PGA1_c27200 PGA1_c23360
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 glpF PGA1_c14980
glpF' glycerol facilitator-aquaporin
glpO glycerol 3-phosphate oxidase PGA1_c08240
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