GapMind for catabolism of small carbon sources

 

myo-inositol catabolism in Bacteroides thetaiotaomicron VPI-5482

Best path

iolT, iolG, iolM, iolN, iolO, uxaE, uxuB, uxuA, kdgK, eda

Also see fitness data for the top candidates

Rules

Overview: Myo-inositol degradation in GapMind is based on MetaCyc pathways myo-inositol degradation I via inosose dehydratase (link) and pathway II inosose dehydrogenase (link).

29 steps (8 with candidates)

Or see definitions of steps

Step Description Best candidate 2nd candidate
iolT myo-inositol:H+ symporter BT0794 BT0436
iolG myo-inositol 2-dehydrogenase
iolM 2-inosose 4-dehydrogenase
iolN 2,4-diketo-inositol hydratase
iolO 5-dehydro-L-gluconate epimerase
uxaE D-tagaturonate epimerase
uxuB D-mannonate dehydrogenase
uxuA D-mannonate dehydratase BT1432 BT0129
kdgK 2-keto-3-deoxygluconate kinase BT0488
eda 2-keto-3-deoxygluconate 6-phosphate aldolase BT0489 BT0895
Alternative steps:
HMIT myo-inositol:H+ symporter BT0436 BT3606
iatA myo-inositol ABC transporter, ATPase component IatA
iatP myo-inositol ABC transporter, permease component IatP
ibpA myo-inositol ABC transporter, substrate-binding component IbpA
iolB 5-deoxy-D-glucuronate isomerase
iolC 5-dehydro-2-deoxy-D-gluconate kinase
iolD 3D-(3,5/4)-trihydroxycyclohexane-1,2-dione hydrolase
iolE scyllo-inosose 2-dehydratase
iolF myo-inositol:H+ symporter
iolJ 5-dehydro-2-deoxyphosphogluconate aldolase BT1691
mmsA malonate-semialdehyde dehydrogenase
PGA1_c07300 myo-inositol ABC transport, substrate-binding component
PGA1_c07310 myo-inositol ABC transporter, permease component
PGA1_c07320 myo-inositol ABC transporter, ATPase component
PS417_11885 myo-inositol ABC transporter, substrate-binding component
PS417_11890 myo-inositol ABC transporter, ATPase component
PS417_11895 myo-inositol ABC transporter, permease component
SMIT1 myo-inositol:Na+ symporter BT0355 BT0341
tpi triose-phosphate isomerase BT3929 BT1672

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