D-glucuronate catabolism in Sinorhizobium medicae WSM419

GapMind for catabolism of small carbon sources

D-glucuronate catabolism in Sinorhizobium medicae WSM419

Best path

dctP, dctQ, dctM, uxaC, uxuB, uxuA, kdgK, eda

Rules

Overview: Glucuronate utilization in GapMind is based on MetaCyc pathways D-glucuronate degradation II (oxidation of 5-keto-4-deoxyglucarate, link), a related pathway via 5-keto-4-deoxyglucarate aldolase (link), or degradation via fructuronate (link). GapMind also includes a variation on the oxidative pathway with a glucarolactonase, as in Pseudomonas putida. MetaCyc pathway I (via L-gulonate and xylitol, link) is not reported in prokaryotes and is not described here.

all:

glucuronate-transport, udh, gci and 5-dehydro-4-deoxyglucarate-degradation
or glucuronate-transport, udh, uxuL, gudD and 5-dehydro-4-deoxyglucarate-degradation
or glucuronate-transport, uxaC, uxuB, uxuA, kdgK and eda
Comment: In pathway II, dehydrogenase udh forms D-glucaro-1,5-lactone, which spontaneously rearranges to D-glucaro-1,4-lactone, and the cycloisomerase gci forms 5-dehydro-4-deoxy-D-glucarate. In P. putida, genetic data suggests that the lactone is hydrolyzed to D-glucarate by uxuL and the dehydratase gudD forms 5-dehydro-4-deoxy-D-glucarate. In the fructuronate pathway, an isomerase (uxaC) converts D-glucuronate to D-fructuronate, followed by oxidation to D-mannonate, dehydration to 2-dehydro-3-deoxy-D-gluconate, phosphorylation to 2-dehydro-3-deoxy-D-gluconate 6-phosphate, and an aldolase reaction to glyceraldehyde-3-phosphate and pyruvate.

5-dehydro-4-deoxyglucarate-degradation:

kdgD and dopDH
or garL, garR and garK
Comment: As part of pathway II, 5-dehydro-4-deoxyglucarate is dehydrated/decarboxylated to 2,5-dioxopentanoate (by kdgD) and oxidized to 2-oxoglutarate (by dopDH). Alternatively, 5-dehydro-4-deoxy-D-glucarate can be consumed by aldolase garL, which forms pyruvate and tartronate semialdehyde (2-hydroxy-3-oxopropionate); tartronate semialdehyde is reduced to D-glycerate and phosphorylated to enter glycolysis.

glucuronate-transport:

exuT
or dctP, dctQ and dctM
Comment: Transporters were identified using query: transporter:glucuronate:D-glucuronate:D-glucopyranuronate:CPD-14488:CPD-12521:CPD-15530

18 steps (17 with candidates)

Or see definitions of steps

Step	Description	Best candidate	2nd candidate
dctP	D-glucuronate TRAP transporter, solute receptor component	SMED_RS23730	SMED_RS24735
dctQ	D-glucuronate TRAP transporter, small permease component	SMED_RS23725
dctM	D-glucuronate TRAP transporter, large permease component	SMED_RS23720	SMED_RS12385
uxaC	D-glucuronate isomerase	SMED_RS23735
uxuB	D-mannonate dehydrogenase	SMED_RS21255	SMED_RS11745
uxuA	D-mannonate dehydratase	SMED_RS18495	SMED_RS18065
kdgK	2-keto-3-deoxygluconate kinase	SMED_RS11585	SMED_RS23820
eda	2-keto-3-deoxygluconate 6-phosphate aldolase	SMED_RS13920	SMED_RS12300
Alternative steps:
dopDH	2,5-dioxopentanonate dehydrogenase	SMED_RS22390	SMED_RS30185
exuT	D-glucuronate:H+ symporter ExuT
garK	glycerate 2-kinase	SMED_RS21575	SMED_RS15870
garL	5-dehydro-4-deoxy-D-glucarate aldolase	SMED_RS16165
garR	tartronate semialdehyde reductase	SMED_RS21570	SMED_RS27590
gci	D-glucaro-1,4-lactone cycloisomerase	SMED_RS29000	SMED_RS18065
gudD	D-glucarate dehydratase	SMED_RS28895
kdgD	5-dehydro-4-deoxyglucarate dehydratase	SMED_RS25295	SMED_RS03350
udh	D-glucuronate dehydrogenase	SMED_RS16665
uxuL	D-glucaro-1,5-lactonase UxuL or UxuF	SMED_RS16680	SMED_RS18010

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 Apr 09 2024. The underlying query database was built on Sep 17 2021.

Downloads

Candidates (tab-delimited)
Steps (tab-delimited)
Rules (tab-delimited)
Protein sequences (fasta format)
Organisms (tab-delimited)
SQLite3 databases

Related tools

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:

ublast finds a hit to a characterized protein at above 40% identity and 80% coverage, and bits >= other bits+10.
- (Hits to curated proteins without experimental data as to their function are never considered high confidence.)
HMMer finds a hit with 80% coverage of the model, and either other identity < 40 or other coverage < 0.75.

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:

ublast finds a hit at above 40% identity and 70% coverage (ignoring otherBits).
ublast finds a hit at above 30% identity and 80% coverage, and bits >= other bits.
HMMer finds a hit (regardless of coverage or other bits).

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:

our ignorance of proteins' functions,
omissions in the gene models,
frame-shift errors in the genome sequence, or
the organism lacks the pathway.

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 2024 update on GapMind for amino acid biosynthesis
the paper from 2022 on GapMind for carbon sources
the source code
instructions for running GapMind on your computer

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

GapMind for catabolism of small carbon sources