catabolism of small carbon sources in Cupriavidus basilensis 4G11

GapMind for catabolism of small carbon sources

catabolism of small carbon sources in Cupriavidus basilensis 4G11

Pathways are sorted by completeness. Sort by name instead.

Pathway	Steps
valine	livF, livG, livJ, livH, livM, ofo, acdH, ech, bch, mmsB, mmsA, prpC, acnD, prpF, acn, prpB
isoleucine	livF, livG, livJ, livH, livM, ofo, acdH, ech, ivdG, fadA, prpC, acnD, prpF, acn, prpB
leucine	livF, livG, livJ, livH, livM, ilvE, ofo, liuA, liuB, liuD, liuC, liuE, atoA, atoD, atoB
tyrosine	Ac3H11_2396, Ac3H11_1695, Ac3H11_1694, Ac3H11_1693, Ac3H11_1692, HPD, hmgA, maiA, fahA, atoA, atoD, atoB
histidine	Ac3H11_2562, Ac3H11_2561, Ac3H11_2560, Ac3H11_2555, Ac3H11_2554, hutH, hutU, hutI, hutF, hutG'
4-hydroxybenzoate	pcaK, pobA, pcaH, pcaG, pcaB, pcaC, pcaD, pcaI, pcaJ, pcaF
threonine	RR42_RS28305, ltaE, adh, ackA, pta, gcvP, gcvT, gcvH, lpd
glucuronate	exuT, udh, uxuL, gudD, garL, garR, garK
proline	HSERO_RS00870, HSERO_RS00885, HSERO_RS00890, HSERO_RS00895, HSERO_RS00900, put1, putA
galacturonate	exuT, udh, uxuL, garD, kdgD, dopDH
serine	Ac3H11_2396, Ac3H11_1695, Ac3H11_1694, Ac3H11_1693, Ac3H11_1692, sdaB
asparagine	ans, aatJ, aatQ, aatM, aatP
glutamate	gltI, gltJ, gltK, gltL, gdhA
aspartate	aatJ, aatQ, aatM, aatP
ethanol	etoh-dh-nad, adh, ackA, pta
fructose	frcA, frcB, frcC, scrK
gluconate	gntT, gntK, edd, eda
D-lactate	lctP, glcD, glcE, glcF
L-lactate	lctP, lutA, lutB, lutC
acetate	actP, ackA, pta
citrate	citA, acn, icd
pyruvate	dctM, dctP, dctQ
D-alanine	cycA, dadA
alanine	cycA
fumarate	dctA
L-malate	dctA
2-oxoglutarate	kgtP
succinate	dctA
phenylalanine	livF, livG, livH, livM, livJ, ARO8, PPDCalpha, PPDCbeta, pad-dh, paaK, paaA, paaB, paaC, paaE, paaG, paaZ1, paaZ2, paaJ1, paaF, paaH, paaJ2
tryptophan	aroP, kynA, kynB, kyn, antA, antB, antC, xylE, praB, praC, praD, mhpD, mhpE, adh, ackA, pta
phenylacetate	ppa, paaK, paaA, paaB, paaC, paaE, paaG, paaZ1, paaZ2, paaJ1, paaF, paaH, paaJ2
glycerol	glpS, glpT, glpP, glpQ, glpV, glpK, glpD, tpi
deoxyribose	drdehyd-alpha, drdehyd-beta, drdehyd-cytc, deoxyribonate-transport, deoxyribonate-dehyd, ketodeoxyribonate-cleavage, garK, atoA, atoD, atoB
deoxyribonate	deoxyribonate-transport, deoxyribonate-dehyd, ketodeoxyribonate-cleavage, garK, atoA, atoD, atoB
propionate	lctP, prpE, prpC, acnD, prpF, acn, prpB
D-serine	cycA, dsdA
lysine	lysP, cadA, patA, patD, davT, davD, gcdG, gcdH, ech, fadB, atoB
arginine	artJ, artM, artP, artQ, rocF, ocd, put1, putA
xylose	xylF, xylG, xylH, xdh, xylC, xad, DKDP-dehydrog, HDOP-hydrol, gyaR, glcB
mannose	HSERO_RS03635, HSERO_RS03640, HSERO_RS03645, man-isomerase, scrK
sucrose	ams, frcA, frcB, frcC, scrK
citrulline	AO353_03055, AO353_03050, AO353_03045, AO353_03040, arcB, arcC, ocd, put1, putA
cellobiose	bgl, mglA, mglB, mglC, glk
trehalose	treF, mglA, mglB, mglC, glk
arabinose	araE, xacB, xacC, xacD, xacE, xacF
glucose	mglA, mglB, mglC, glk
putrescine	puuP, patA, patD, gabT, gabD
sorbitol	SOT, sdh, scrK
thymidine	nupG, deoA, deoB, deoC, adh, ackA, pta
glucose-6-P	uhpT
maltose	susB, mglA, mglB, mglC, glk
glucosamine	SLC2A2, glc-kinase, nagB
mannitol	PLT5, mt2d, scrK
galactose	galP, galdh, galactonolactonase, dgoD, dgoK, dgoA
ribose	rbsU, rbsK
xylitol	fruI, x5p-reductase
lactose	lacP, lacZ, galdh, galactonolactonase, dgoD, dgoK, dgoA, glk
deoxyinosine	nupC, deoD, deoB, deoC, adh, ackA, pta
NAG	nagEcba, nagA, nagB
myoinositol	PS417_11885, PS417_11890, PS417_11895, iolG, iolM, iolN, iolO, uxaE, uxuB, uxuA, kdgK, eda
rhamnose	rhaT, LRA1, LRA2, LRA3, LRA4, aldA
fucose	HSERO_RS05250, HSERO_RS05255, HSERO_RS05260, fucU, fdh, fuconolactonase, fucD, fucDH, KDF-hydrolase

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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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