L-fucose catabolism in Bryobacter aggregatus MPL3

GapMind for catabolism of small carbon sources

L-fucose catabolism in Bryobacter aggregatus MPL3

Best path

HSERO_RS05250, HSERO_RS05255, HSERO_RS05260, fucU, fdh, fuconolactonase, fucD, fucDH, KDF-hydrolase

Rules

Overview: Fucose degradation in GapMind is based on the MetaCyc pathway via L-fuculose (link) or the oxidative pathway via 2,4-diketo-3-deoxy-L-fuconate (KDF) hydrolase (PMC6336799).

all:

fucose-transport, fucU, fucI, fucK, fucA, tpi and lactaldehyde-conversion
or fucose-transport, fucU, fdh, fuconolactonase, fucD, fucDH and KDF-hydrolase
Comment: In the L-fucuolose pathway, mutarotase fucU converts the beta-pyranose to the alpha-pyranose form, isomerase fucI produces L-fuculose, kinase fucK forms L-fuculose 1-phosphate, and aldolase fucA produces glycerone phosphate and (S)-lactaldehyde. Lactaldehyde might be oxidized to lactate and secreted (or oxidized to pyruvate), or, it might be reduced to propane-1,2-diol and secreted; tpi converts glycerone-phosphate to glyceraldehyde 3-phosphate. In the oxidative pathway, mutarotase fucU forms the beta-pyranose form, fucose dehydrogenase (fdh) forms L-fucono-1,5-lactone, a lactonase forms L-fuconate, dehydratase fucD forms 2-keto-3-deoxy-L-fuconate, dehydrogenase fucDH forms 2,4-diketo-3-deoxy-L-fuconate (KDF, also known as 2,4-diketo-3-deoxy-L-rhamnonate), and a hydrolase forms lactate and pyruvate. The lactate could be secreted or oxidized to pyruvate.

lactaldehyde-conversion:

aldA
or fucO
Comment: Lactaldehyde can be oxidized to lactate (aldA) or reduced to propanediol (fucO). Either of these can be excreted.

fucose-transport:

fucP
or SM_b21103, SM_b21104, SM_b21105 and SM_b21106
or BPHYT_RS34250, BPHYT_RS34245 and BPHYT_RS34240
or HSERO_RS05250, HSERO_RS05255 and HSERO_RS05260
Comment: Transporters were identified using query: transporter:L-fucose:L-fucopyranose:CPD-10329:CPD0-1107:CPD-15619

23 steps (14 with candidates)

Or see definitions of steps

Step	Description	Best candidate	2nd candidate
HSERO_RS05250	ABC transporter for L-fucose, ATPase component	M017_RS0113850
HSERO_RS05255	ABC transporter for L-fucose, permease component	M017_RS0113845
HSERO_RS05260	ABC transporter for L-fucose, substrate-binding component	M017_RS0123650	M017_RS0116120
fucU	L-fucose mutarotase FucU
fdh	L-fucose 1-dehydrogenase	M017_RS0105090	M017_RS0112325
fuconolactonase	L-fucono-1,5-lactonase	M017_RS0117440
fucD	L-fuconate dehydratase	M017_RS0120215	M017_RS0108560
fucDH	2-keto-3-deoxy-L-fuconate 4-dehydrogenase	M017_RS0105090	M017_RS0103435
KDF-hydrolase	2,4-diketo-3-deoxy-L-fuconate hydrolase	M017_RS0104905	M017_RS0101560
Alternative steps:
aldA	lactaldehyde dehydrogenase	M017_RS0114350	M017_RS0109390
BPHYT_RS34240	ABC transporter for L-fucose, permease component	M017_RS0113845
BPHYT_RS34245	ABC transporter for L-fucose, ATPase component	M017_RS0113850
BPHYT_RS34250	ABC transporter for L-fucose, substrate-binding component
fucA	L-fuculose-phosphate aldolase FucA
fucI	L-fucose isomerase FucI
fucK	L-fuculose kinase FucK
fucO	L-lactaldehyde reductase
fucP	L-fucose:H+ symporter FucP
SM_b21103	ABC transporter for L-fucose, substrate-binding component
SM_b21104	ABC transporter for L-fucose, permease component 1
SM_b21105	ABC transporter for L-fucose, permease component 2	M017_RS0107405
SM_b21106	ABC transporter for L-fucose, ATPase component	M017_RS0107395	M017_RS0113090
tpi	triose-phosphate isomerase	M017_RS0120145	M017_RS0124065

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 24 2021. 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 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