GapMind for catabolism of small carbon sources

 

Protein 353218 in Bacteroides thetaiotaomicron VPI-5482

Annotation: BT3692 phosphate acetyltransferase (NCBI ptt file)

Length: 339 amino acids

Source: Btheta in FitnessBrowser

Candidate for 9 steps in catabolism of small carbon sources

Pathway Step Score Similar to Id. Cov. Bits Other hit Other id. Other bits
4-hydroxybenzoate catabolism pta hi phosphotransacetylase (EC 2.3.1.8) (characterized) 53% 99% 330.9
4-hydroxybenzoate catabolism pta hi pta: phosphate acetyltransferase (EC 2.3.1.8) (TIGR00651) 100% 359.1
L-lactate catabolism pta hi phosphotransacetylase (EC 2.3.1.8) (characterized) 53% 99% 330.9
L-lactate catabolism pta hi pta: phosphate acetyltransferase (EC 2.3.1.8) (TIGR00651) 100% 359.1
acetate catabolism pta hi phosphotransacetylase (EC 2.3.1.8) (characterized) 53% 99% 330.9
acetate catabolism pta hi pta: phosphate acetyltransferase (EC 2.3.1.8) (TIGR00651) 100% 359.1
2'-deoxyinosine catabolism pta hi phosphotransacetylase (EC 2.3.1.8) (characterized) 53% 99% 330.9
2'-deoxyinosine catabolism pta hi pta: phosphate acetyltransferase (EC 2.3.1.8) (TIGR00651) 100% 359.1
2-deoxy-D-ribose catabolism pta hi phosphotransacetylase (EC 2.3.1.8) (characterized) 53% 99% 330.9
2-deoxy-D-ribose catabolism pta hi pta: phosphate acetyltransferase (EC 2.3.1.8) (TIGR00651) 100% 359.1
ethanol catabolism pta hi phosphotransacetylase (EC 2.3.1.8) (characterized) 53% 99% 330.9
ethanol catabolism pta hi pta: phosphate acetyltransferase (EC 2.3.1.8) (TIGR00651) 100% 359.1
L-threonine catabolism pta hi phosphotransacetylase (EC 2.3.1.8) (characterized) 53% 99% 330.9
L-threonine catabolism pta hi pta: phosphate acetyltransferase (EC 2.3.1.8) (TIGR00651) 100% 359.1
thymidine catabolism pta hi phosphotransacetylase (EC 2.3.1.8) (characterized) 53% 99% 330.9
thymidine catabolism pta hi pta: phosphate acetyltransferase (EC 2.3.1.8) (TIGR00651) 100% 359.1
L-tryptophan catabolism pta hi phosphotransacetylase (EC 2.3.1.8) (characterized) 53% 99% 330.9
L-tryptophan catabolism pta hi pta: phosphate acetyltransferase (EC 2.3.1.8) (TIGR00651) 100% 359.1

Sequence Analysis Tools

View 353218 at FitnessBrowser

PaperBLAST (search for papers about homologs of this protein)

Search CDD (the Conserved Domains Database, which includes COG and superfam)

Search PFam (including for weak hits, up to E = 1)

Predict protein localization: PSORTb (Gram negative bacteria)

Predict transmembrane helices: TMHMM

Check the SEED with FIGfam search

Fitness BLAST: loading...

Sequence

MLNLINQIVARAKADRQRIVLPEGTEERTLKAANQILTDEVADLILLGKPAEINELAVKW
GLGNISKATIIDPETSPKHEEYAQLLCELRKKKGMTIEEARQLTNDPLFYGCLMIKSGDA
DGQLAGARNTTGNVLRPALQIIKTAPGITCVSGAMLLLTHAPEYGKNGILVMGDVAVTPV
PDPNQLAQIAVCTAQTAKAVAGIENPKVAMLSFSTKGSAKHEVVDKVVEATKIAKEMAPT
LDLDGEMQADAALVPEVGASKAPGSPVAGEANVLIVPSLEVGNISYKLVQRLGHADAIGP
ILQGIARPVNDLSRGCSIEDVYRMIAITANQAIAAKNNK

This GapMind analysis is from Sep 17 2021. The underlying query database was built on Sep 17 2021.

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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 against a database of manually-curated proteins (most of which are experimentally characterized) or by using HMMer. Ublast hits may be split across two different proteins.

A candidate for a step is "high confidence" if either:

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:

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. Gaps may be due to:

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, or view the source code.

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