Alignments for a candidate for fadA in Pseudomonas simiae WCS417

GapMind for catabolism of small carbon sources

Alignments for a candidate for fadA in Pseudomonas simiae WCS417

Align acetyl-CoA C-acetyltransferase (EC 2.3.1.16) (characterized)
to candidate GFF2062 PS417_10515 acetyl-CoA acetyltransferase

Query= metacyc::MONOMER-20831
         (393 letters)



>FitnessBrowser__WCS417:GFF2062
          Length = 393

 Score =  760 bits (1963), Expect = 0.0
 Identities = 393/393 (100%), Positives = 393/393 (100%)

Query: 1   MQDVVIVAATRTAVGSFQGSLASIPAPELGAAVIRRLLEQTGLDPAQVDEVILGQVLTAG 60
           MQDVVIVAATRTAVGSFQGSLASIPAPELGAAVIRRLLEQTGLDPAQVDEVILGQVLTAG
Sbjct: 1   MQDVVIVAATRTAVGSFQGSLASIPAPELGAAVIRRLLEQTGLDPAQVDEVILGQVLTAG 60

Query: 61  SGQNPARQASILAGLPHAVPSLTLNKVCGSGLKALHLGAQAIRCGDAEVIIAGGMENMSL 120
           SGQNPARQASILAGLPHAVPSLTLNKVCGSGLKALHLGAQAIRCGDAEVIIAGGMENMSL
Sbjct: 61  SGQNPARQASILAGLPHAVPSLTLNKVCGSGLKALHLGAQAIRCGDAEVIIAGGMENMSL 120

Query: 121 APYVLPAARTGLRMGHAKMIDSMITDGLWDAFNDYHMGITAENLVDKYGISREAQDAFAA 180
           APYVLPAARTGLRMGHAKMIDSMITDGLWDAFNDYHMGITAENLVDKYGISREAQDAFAA
Sbjct: 121 APYVLPAARTGLRMGHAKMIDSMITDGLWDAFNDYHMGITAENLVDKYGISREAQDAFAA 180

Query: 181 ASQQKATAAIEAGRFVDEITPILIPQRKGDPVAFAVDEQPRAGTTAESLAKLKPAFKKDG 240
           ASQQKATAAIEAGRFVDEITPILIPQRKGDPVAFAVDEQPRAGTTAESLAKLKPAFKKDG
Sbjct: 181 ASQQKATAAIEAGRFVDEITPILIPQRKGDPVAFAVDEQPRAGTTAESLAKLKPAFKKDG 240

Query: 241 SVTAGNASSLNDGAAAVLLMSADKAKALGLPVLARIASYANAGVDPAIMGIGPVSATRRC 300
           SVTAGNASSLNDGAAAVLLMSADKAKALGLPVLARIASYANAGVDPAIMGIGPVSATRRC
Sbjct: 241 SVTAGNASSLNDGAAAVLLMSADKAKALGLPVLARIASYANAGVDPAIMGIGPVSATRRC 300

Query: 301 LDKAGWSLGDLDLIEANEAFAAQSLAVGKELEWDAEKVNVNGGAIAIGHPIGASGCRVLV 360
           LDKAGWSLGDLDLIEANEAFAAQSLAVGKELEWDAEKVNVNGGAIAIGHPIGASGCRVLV
Sbjct: 301 LDKAGWSLGDLDLIEANEAFAAQSLAVGKELEWDAEKVNVNGGAIAIGHPIGASGCRVLV 360

Query: 361 TLLHEMIKRDAKKGLATLCIGGGQGVALALERS 393
           TLLHEMIKRDAKKGLATLCIGGGQGVALALERS
Sbjct: 361 TLLHEMIKRDAKKGLATLCIGGGQGVALALERS 393


Lambda     K      H
   0.317    0.133    0.378 

Gapped
Lambda     K      H
   0.267   0.0410    0.140 


Matrix: BLOSUM62
Gap Penalties: Existence: 11, Extension: 1
Number of Sequences: 1
Number of Hits to DB: 626
Number of extensions: 11
Number of successful extensions: 1
Number of sequences better than 1.0e-02: 1
Number of HSP's gapped: 1
Number of HSP's successfully gapped: 1
Length of query: 393
Length of database: 393
Length adjustment: 31
Effective length of query: 362
Effective length of database: 362
Effective search space:   131044
Effective search space used:   131044
Neighboring words threshold: 11
Window for multiple hits: 40
X1: 16 ( 7.3 bits)
X2: 38 (14.6 bits)
X3: 64 (24.7 bits)
S1: 41 (21.7 bits)
S2: 50 (23.9 bits)

Align candidate GFF2062 PS417_10515 (acetyl-CoA acetyltransferase)
to HMM TIGR01930 (acetyl-CoA C-acyltransferase (EC 2.3.1.16))

# hmmsearch :: search profile(s) against a sequence database
# HMMER 3.3.1 (Jul 2020); http://hmmer.org/
# Copyright (C) 2020 Howard Hughes Medical Institute.
# Freely distributed under the BSD open source license.
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
# query HMM file:                  ../tmp/path.carbon/TIGR01930.hmm
# target sequence database:        /tmp/gapView.10337.genome.faa
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -

Query:       TIGR01930  [M=385]
Accession:   TIGR01930
Description: AcCoA-C-Actrans: acetyl-CoA C-acyltransferase
Scores for complete sequences (score includes all domains):
   --- full sequence ---   --- best 1 domain ---    -#dom-
    E-value  score  bias    E-value  score  bias    exp  N  Sequence                           Description
    ------- ------ -----    ------- ------ -----   ---- --  --------                           -----------
   1.2e-152  494.2   5.1   1.4e-152  494.1   5.1    1.0  1  lcl|FitnessBrowser__WCS417:GFF2062  PS417_10515 acetyl-CoA acetyltra


Domain annotation for each sequence (and alignments):
>> lcl|FitnessBrowser__WCS417:GFF2062  PS417_10515 acetyl-CoA acetyltransferase
   #    score  bias  c-Evalue  i-Evalue hmmfrom  hmm to    alifrom  ali to    envfrom  env to     acc
 ---   ------ ----- --------- --------- ------- -------    ------- -------    ------- -------    ----
   1 !  494.1   5.1  1.4e-152  1.4e-152       1     385 []       6     391 ..       6     391 .. 0.99

  Alignments for each domain:
  == domain 1  score: 494.1 bits;  conditional E-value: 1.4e-152
                           TIGR01930   1 ivdavRtpigklggslkelsaedLlaavikelleragldpekidevilGnvlqageqaniaReaalaaglpesvp 75 
                                         iv+a+Rt++g+++gsl++++a +L+aavi++lle++gldp+++devilG+vl+ag+++n+aR+a + aglp+ vp
  lcl|FitnessBrowser__WCS417:GFF2062   6 IVAATRTAVGSFQGSLASIPAPELGAAVIRRLLEQTGLDPAQVDEVILGQVLTAGSGQNPARQASILAGLPHAVP 80 
                                         8************************************************************************** PP

                           TIGR01930  76 altvnrvCaSglqAvalaaqkikaGeadvvvaGGvEsmSrvpillkaslrreslklgkakledqllkdl...vkt 147
                                         +lt+n+vC+Sgl+A++l+aq+i++G+a+v++aGG+E+mS +p++l+a+  r +l++g+ak+ d+++ d+   + +
  lcl|FitnessBrowser__WCS417:GFF2062  81 SLTLNKVCGSGLKALHLGAQAIRCGDAEVIIAGGMENMSLAPYVLPAA--RTGLRMGHAKMIDSMITDGlwdAFN 153
                                         **********************************************98..89********************99* PP

                           TIGR01930 148 klsmgetAenlakkygisReeqDeyalrShqkaakAieegkfkdeivpvevkgk...kkvvskDegirpnttlek 219
                                         +++mg+tAenl +kygisRe qD++a++S+qka++Aie+g+f dei+p+ ++++   ++ ++ De++r++tt+e+
  lcl|FitnessBrowser__WCS417:GFF2062 154 DYHMGITAENLVDKYGISREAQDAFAAASQQKATAAIEAGRFVDEITPILIPQRkgdPVAFAVDEQPRAGTTAES 228
                                         ***************************************************9999999***************** PP

                           TIGR01930 220 LakLkpafkekkgstvtAgNssqlnDGAaalllmseevakelgltplarivsaavagvdpeemglgpvpAiekaL 294
                                         LakLkpafk+ +gs vtAgN+s+lnDGAaa+llms ++ak+lgl +lari s+a+agvdp++mg+gpv A++++L
  lcl|FitnessBrowser__WCS417:GFF2062 229 LAKLKPAFKK-DGS-VTAGNASSLNDGAAAVLLMSADKAKALGLPVLARIASYANAGVDPAIMGIGPVSATRRCL 301
                                         ********95.9*7.************************************************************ PP

                           TIGR01930 295 kkaglsisdidlvEinEAFAaqvlavekelgsldlekvNvnGGAiAlGHPlGasGarivltllkeLkergkkyGl 369
                                         +kag+s+ d+dl+E nEAFAaq lav kel+  d ekvNvnGGAiA+GHP+GasG+r+++tll+e+ +r++k Gl
  lcl|FitnessBrowser__WCS417:GFF2062 302 DKAGWSLGDLDLIEANEAFAAQSLAVGKELE-WDAEKVNVNGGAIAIGHPIGASGCRVLVTLLHEMIKRDAKKGL 375
                                         *******************************.88***************************************** PP

                           TIGR01930 370 atlCvggGqGaAvile 385
                                         atlC+ggGqG+A+ le
  lcl|FitnessBrowser__WCS417:GFF2062 376 ATLCIGGGQGVALALE 391
                                         ************9886 PP



Internal pipeline statistics summary:
-------------------------------------
Query model(s):                            1  (385 nodes)
Target sequences:                          1  (393 residues searched)
Passed MSV filter:                         1  (1); expected 0.0 (0.02)
Passed bias filter:                        1  (1); expected 0.0 (0.02)
Passed Vit filter:                         1  (1); expected 0.0 (0.001)
Passed Fwd filter:                         1  (1); expected 0.0 (1e-05)
Initial search space (Z):                  1  [actual number of targets]
Domain search space  (domZ):               1  [number of targets reported over threshold]
# CPU time: 0.01u 0.00s 00:00:00.01 Elapsed: 00:00:00.01
# Mc/sec: 11.57
//
[ok]

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

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Protein sequences (fasta format)
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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, 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

GapMind for catabolism of small carbon sources