catabolism of small carbon sources in Limnohabitans curvus MWH-C5

GapMind for catabolism of small carbon sources

catabolism of small carbon sources in Limnohabitans curvus MWH-C5

Pathways are sorted by completeness. Sort by name instead.

Pathway	Steps
isoleucine	livF, livG, livJ, livH, livM, ofo, acdH, ech, ivdG, fadA, pccA, pccB, epi, mcm-large, mcm-small
leucine	livF, livG, livJ, livH, livM, ilvE, ofo, liuA, liuB, liuD, liuC, liuE, atoA, atoD, atoB
gluconate	gntA, gntB, gntC, gntK, edd, eda
glucose	gtsA, gtsB, gtsC, gtsD, glk
aspartate	aatJ, aatQ, aatM, aatP
D-lactate	lctP, glcD, glcE, glcF
pyruvate	dctM, dctP, dctQ
acetate	actP, acs
L-lactate	lctP, L-LDH
tryptophan	aroP, tnaA
fumarate	dctA
L-malate	dctA
succinate	dctA
propionate	lctP, prpE, pccA, pccB, epi, mcm-large, mcm-small
serine	Ac3H11_2396, Ac3H11_1695, Ac3H11_1694, Ac3H11_1693, Ac3H11_1692, sdaB
asparagine	ans, aatJ, aatQ, aatM, aatP
glutamate	gltI, gltJ, gltK, gltL, aspA
fructose	frcA, frcB, frcC, scrK
alanine	braC, braD, braE, braF, braG
D-alanine	cycA, dadA
ethanol	etoh-dh-nad, adh, acs
valine	livF, livG, livJ, livH, livM, ofo, acdH, ech, bch, mmsB, mmsA, pccA, pccB, epi, mcm-large, mcm-small
threonine	braC, braD, braE, braF, braG, tdcB, tdcE, pccA, pccB, epi, mcm-large, mcm-small
tyrosine	Ac3H11_2396, Ac3H11_1695, Ac3H11_1694, Ac3H11_1693, Ac3H11_1692, HPD, hmgA, maiA, fahA, atoA, atoD, atoB
4-hydroxybenzoate	pcaK, pobA, ligA, ligB, ligC, ligI, ligU, ligJ, ligK
cellobiose	bgl, gtsA, gtsB, gtsC, gtsD, glk
maltose	susB, gtsA, gtsB, gtsC, gtsD, glk
sucrose	ams, gtsA, gtsB, gtsC, gtsD, glk
trehalose	treF, gtsA, gtsB, gtsC, gtsD, glk
glucuronate	dctP, dctQ, dctM, udh, uxuL, gudD, garL, garR, garK
proline	HSERO_RS00870, HSERO_RS00885, HSERO_RS00890, HSERO_RS00895, HSERO_RS00900, put1, putA
ribose	frcA, frcB, frcC, rbsK
mannose	frcA, frcB, frcC, man-isomerase, scrK
phenylalanine	livF, livG, livH, livM, livJ, PAH, PCBD, QDPR, HPD, hmgA, maiA, fahA, atoA, atoD, atoB
citrate	SLC13A5, acn, icd
galactose	PfGW456L13_1894, PfGW456L13_1895, PfGW456L13_1896, PfGW456L13_1897, galK, galT, galE, pgmA
deoxyribonate	deoxyribonate-transport, deoxyribonate-dehyd, ketodeoxyribonate-cleavage, garK, atoA, atoD, atoB
glucose-6-P	uhpT
2-oxoglutarate	kgtP
sorbitol	SOT, sdh, scrK
xylose	gtsA, gtsB, gtsC, gtsD, xdh, xylC, xad, DKDP-dehydrog, HDOP-hydrol, gyaR, glcB
lactose	lacA', lacC', lacB', klh, gtsA, gtsB, gtsC, gtsD, glk
galacturonate	exuT, udh, uxuL, garD, kdgD, dopDH
lysine	lysP, cadA, patA, patD, davT, davD, gcdG, gcdH, ech, fadB, atoB
glucosamine	gamP, nagB
mannitol	mtlA, mtlD
D-serine	cycA, dsdA
xylitol	fruI, x5p-reductase
deoxyribose	drdehyd-alpha, drdehyd-beta, drdehyd-cytc, deoxyribonate-transport, deoxyribonate-dehyd, ketodeoxyribonate-cleavage, garK, atoA, atoD, atoB
glycerol	glpF, glpK, glpD, tpi
putrescine	puuP, patA, patD, gabT, gabD
thymidine	nupG, deoA, deoB, deoC, adh, acs
rhamnose	rhaT, LRA1, LRA2, LRA3, LRA5, LRA6
NAG	nagEcba, nagA, nagB
deoxyinosine	nupC, deoD, deoB, deoC, adh, acs
arginine	braC, braD, braE, braF, braG, rocF, rocD, rocA
arabinose	araE, araA, araB, araD
phenylacetate	ppa, paaK, paaA, paaB, paaC, paaE, paaG, paaZ1, paaZ2, paaJ1, paaF, paaH, paaJ2
fucose	fucP, fucU, fucI, fucK, fucA, tpi, aldA
histidine	braC, braD, braE, braF, braG, hutH, hutU, hutI, hutG
citrulline	AO353_03055, AO353_03050, AO353_03045, AO353_03040, arcB, arcC, rocD, rocA
myoinositol	iolT, iolG, iolE, iolD, iolB, iolC, iolJ, mmsA, tpi

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.

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

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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:

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