GapMind for catabolism of small carbon sources

 

myo-inositol catabolism in Pseudomonas putida KT2440

Best path

iolT, iolG, iolE, iolD, iolB, iolC, iolJ, mmsA, tpi

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 (13 with candidates)

Or see definitions of steps

Step Description Best candidate 2nd candidate
iolT myo-inositol:H+ symporter
iolG myo-inositol 2-dehydrogenase PP_2602
iolE scyllo-inosose 2-dehydratase
iolD 3D-(3,5/4)-trihydroxycyclohexane-1,2-dione hydrolase
iolB 5-deoxy-D-glucuronate isomerase
iolC 5-dehydro-2-deoxy-D-gluconate kinase
iolJ 5-dehydro-2-deoxyphosphogluconate aldolase PP_4960
mmsA malonate-semialdehyde dehydrogenase PP_0597 PP_4667
tpi triose-phosphate isomerase PP_4715 PP_4963
Alternative steps:
eda 2-keto-3-deoxygluconate 6-phosphate aldolase PP_1024
HMIT myo-inositol:H+ symporter
iatA myo-inositol ABC transporter, ATPase component IatA PP_2455 PP_2759
iatP myo-inositol ABC transporter, permease component IatP PP_2456
ibpA myo-inositol ABC transporter, substrate-binding component IbpA
iolF myo-inositol:H+ symporter
iolM 2-inosose 4-dehydrogenase PP_0552
iolN 2,4-diketo-inositol hydratase
iolO 5-dehydro-L-gluconate epimerase
kdgK 2-keto-3-deoxygluconate kinase PP_3378
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 PP_2759 PP_2455
PS417_11885 myo-inositol ABC transporter, substrate-binding component PP_2372
PS417_11890 myo-inositol ABC transporter, ATPase component PP_2759 PP_2455
PS417_11895 myo-inositol ABC transporter, permease component PP_2456
SMIT1 myo-inositol:Na+ symporter
uxaE D-tagaturonate epimerase
uxuA D-mannonate dehydratase
uxuB D-mannonate dehydrogenase

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