L-histidine catabolism

GapMind for catabolism of small carbon sources

L-histidine catabolism

Analysis of pathway histidine in 35 genomes

Genome	Best path
Acidovorax sp. GW101-3H11	Ac3H11_2562, Ac3H11_2561, Ac3H11_2560, Ac3H11_2555, Ac3H11_2554, hutH, hutU, hutI, hutF, hutG'
Azospirillum brasilense Sp245	Ac3H11_2562, Ac3H11_2561, Ac3H11_2560, Ac3H11_2555, Ac3H11_2554, hutH, hutU, hutI, hutF, hutG'
Bacteroides thetaiotaomicron VPI-5482	permease, hutH, hutU, hutI, hutG
Burkholderia phytofirmans PsJN	BPHYT_RS24000, BPHYT_RS24005, BPHYT_RS24010, BPHYT_RS24015, hutH, hutU, hutI, hutF, hutG'
Caulobacter crescentus NA1000	PA5503, PA5504, PA5505, hutH, hutU, hutI, hutF, hutG'
Cupriavidus basilensis 4G11	Ac3H11_2562, Ac3H11_2561, Ac3H11_2560, Ac3H11_2555, Ac3H11_2554, hutH, hutU, hutI, hutF, hutG'
Dechlorosoma suillum PS	PA5503, PA5504, PA5505, hutH, hutU, hutI, hutG
Desulfovibrio vulgaris Hildenborough	permease, hutH, hutU, hutI, hutG
Desulfovibrio vulgaris Miyazaki F	hutV, hutW, hutX, hutH, hutU, hutI, hutG
Dinoroseobacter shibae DFL-12	aapJ, aapQ, aapM, aapP, hutH, hutU, hutI, hutG
Dyella japonica UNC79MFTsu3.2	PA5503, PA5504, PA5505, hutH, hutU, hutI, hutF, hutG'
Echinicola vietnamensis KMM 6221, DSM 17526	permease, hutH, hutU, hutI, hutG
Escherichia coli BW25113	hisP, hisM, hisQ, hisJ, hutH, hutU, hutI, hutG
Herbaspirillum seropedicae SmR1	PA5503, PA5504, PA5505, hutH, hutU, hutI, hutF, hutG'
Klebsiella michiganensis M5al	hisP, hisM, hisQ, hisJ, hutH, hutU, hutI, hutG
Magnetospirillum magneticum AMB-1	braC, braD, braE, braF, braG, hutH, hutU, hutI, hutG
Marinobacter adhaerens HP15	PA5503, PA5504, PA5505, hutH, hutU, hutI, hutG
Paraburkholderia bryophila 376MFSha3.1	BPHYT_RS24000, BPHYT_RS24005, BPHYT_RS24010, BPHYT_RS24015, hutH, hutU, hutI, hutF, hutG'
Pedobacter sp. GW460-11-11-14-LB5	LAT2, hutH, hutU, hutI, hutG
Phaeobacter inhibens BS107	hutV, hutW, hutX, hutH, hutU, hutI, hutF, hutG'
Pseudomonas fluorescens FW300-N1B4	hisP, hisM, hisQ, hisJ, hutH, hutU, hutI, hutF, hutG'
Pseudomonas fluorescens FW300-N2C3	hisP, hisM, hisQ, hisJ, hutH, hutU, hutI, hutF, hutG'
Pseudomonas fluorescens FW300-N2E2	hisP, hisM, hisQ, hisJ, hutH, hutU, hutI, hutF, hutG'
Pseudomonas fluorescens FW300-N2E3	hisP, hisM, hisQ, hisJ, hutH, hutU, hutI, hutF, hutG'
Pseudomonas fluorescens GW456-L13	hisP, hisM, hisQ, hisJ, hutH, hutU, hutI, hutF, hutG'
Pseudomonas putida KT2440	hisP, hisM, hisQ, hisJ, hutH, hutU, hutI, hutF, hutG'
Pseudomonas simiae WCS417	hisP, hisM, hisQ, hisJ, hutH, hutU, hutI, hutF, hutG'
Pseudomonas stutzeri RCH2	hisP, hisM, hisQ, hisJ, hutH, hutU, hutI, hutG
Shewanella amazonensis SB2B	permease, hutH, hutU, hutI, hutG
Shewanella loihica PV-4	permease, hutH, hutU, hutI, hutG
Shewanella oneidensis MR-1	permease, hutH, hutU, hutI, hutG
Shewanella sp. ANA-3	permease, hutH, hutU, hutI, hutG
Sinorhizobium meliloti 1021	braC, braD, braE, braF, braG, hutH, hutU, hutI, hutF, hutG'
Sphingomonas koreensis DSMZ 15582	Ga0059261_1577, hutH, hutU, hutI, hutF, hutG'
Synechococcus elongatus PCC 7942	natA, natB, natC, natD, natE, hutH, hutU, hutI, hutG

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