GapMind for catabolism of small carbon sources

 

glycerol catabolism in Pseudomonas fluorescens FW300-N2E3

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 (10 with candidates)

Or see definitions of steps

Step Description Best candidate 2nd candidate
glpF glycerol facilitator glpF AO353_04175
glpK glycerol kinase AO353_04180
glpD glycerol 3-phosphate dehydrogenase (monomeric) AO353_04190
tpi triose-phosphate isomerase AO353_05590 AO353_07945
Alternative steps:
aqp-3 glycerol porter aqp-3
dhaD glycerol dehydrogenase AO353_07245 AO353_17425
dhaK dihydroxyacetone:PEP phosphotransferase, subunit K
dhaK' dihydroxyacetone kinase, ATP dependent (monomeric)
dhaL dihydroxyacetone:PEP phosphotransferase, subunit L
dhaM dihydroxyacetone:PEP phosphotransferase, subunit M AO353_05485
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 AO353_04190
glpP glycerol ABC transporter, permease component 1 (GlpP)
glpQ glycerol ABC transporter, permease component 2 (GlpQ) AO353_25890
glpS glycerol ABC transporter, ATPase component 1 (GlpS) AO353_25895 AO353_25130
glpT glycerol ABC transporter, ATPase component 2 (GlpT) AO353_25895 AO353_03380
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 (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:

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