Alignments for a candidate for fadA in Marinobacter adhaerens HP15

GapMind for catabolism of small carbon sources

Alignments for a candidate for fadA in Marinobacter adhaerens HP15

Align acetyl-CoA C-acetyltransferase (EC 2.3.1.16) (characterized)
to candidate GFF3052 HP15_2996 acetyl-CoA acetyltransferase

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



>FitnessBrowser__Marino:GFF3052
          Length = 398

 Score =  552 bits (1422), Expect = e-162
 Identities = 270/392 (68%), Positives = 330/392 (84%)

Query: 1   MQDVVIVAATRTAVGSFQGSLASIPAPELGAAVIRRLLEQTGLDPAQVDEVILGQVLTAG 60
           M+DVVIVAA RTA+G+F G L+S+ A +LG AVI+ +LE+TG+   Q++EV+LGQVLTAG
Sbjct: 7   MRDVVIVAARRTAIGTFGGGLSSLSADQLGTAVIKAILEETGVAGDQINEVVLGQVLTAG 66

Query: 61  SGQNPARQASILAGLPHAVPSLTLNKVCGSGLKALHLGAQAIRCGDAEVIIAGGMENMSL 120
            GQNPARQ++I AG+P +VP++T+NKVCGSGLKA+H+  QAIRCGDAE++IAGG E+MS 
Sbjct: 67  CGQNPARQSAINAGIPASVPAMTINKVCGSGLKAVHMAVQAIRCGDAEMMIAGGQESMSQ 126

Query: 121 APYVLPAARTGLRMGHAKMIDSMITDGLWDAFNDYHMGITAENLVDKYGISREAQDAFAA 180
           AP+VLP +R G RMG+  M+D+MI DGLWDAFNDYHMGITAEN+V+KYGISR+ QD FAA
Sbjct: 127 APHVLPNSRNGQRMGNWSMVDTMIKDGLWDAFNDYHMGITAENIVEKYGISRDEQDEFAA 186

Query: 181 ASQQKATAAIEAGRFVDEITPILIPQRKGDPVAFAVDEQPRAGTTAESLAKLKPAFKKDG 240
           ASQQKA AA EAG F  +I P+ IPQRKGDP+    DE PR G TAE L KL+ AFKKDG
Sbjct: 187 ASQQKAAAAREAGYFDGQIVPVSIPQRKGDPIVVDRDEGPRDGVTAEGLGKLRAAFKKDG 246

Query: 241 SVTAGNASSLNDGAAAVLLMSADKAKALGLPVLARIASYANAGVDPAIMGIGPVSATRRC 300
           +VTAGNASSLNDGAAAV++ SA+KA+ LGL  +A I +YANAGVDP IMG GP+ A++RC
Sbjct: 247 TVTAGNASSLNDGAAAVMVCSAEKAEELGLTPIATIKAYANAGVDPTIMGTGPIPASQRC 306

Query: 301 LDKAGWSLGDLDLIEANEAFAAQSLAVGKELEWDAEKVNVNGGAIAIGHPIGASGCRVLV 360
           L  AGWS  DLDL+EANEAFAAQ+++V +++ WD  KVNVNGGAIA+GHPIGASGCR+LV
Sbjct: 307 LKLAGWSTEDLDLVEANEAFAAQAISVNRDMGWDTGKVNVNGGAIALGHPIGASGCRILV 366

Query: 361 TLLHEMIKRDAKKGLATLCIGGGQGVALALER 392
           +LLHEM++RD  KGLATLCIGGG GVALA+ER
Sbjct: 367 SLLHEMVRRDVHKGLATLCIGGGMGVALAVER 398


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: 505
Number of extensions: 12
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: 398
Length adjustment: 31
Effective length of query: 362
Effective length of database: 367
Effective search space:   132854
Effective search space used:   132854
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 GFF3052 HP15_2996 (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.13522.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
    ------- ------ -----    ------- ------ -----   ---- --  --------                           -----------
   5.1e-149  482.3   7.7   5.8e-149  482.1   7.7    1.0  1  lcl|FitnessBrowser__Marino:GFF3052  HP15_2996 acetyl-CoA acetyltrans


Domain annotation for each sequence (and alignments):
>> lcl|FitnessBrowser__Marino:GFF3052  HP15_2996 acetyl-CoA acetyltransferase
   #    score  bias  c-Evalue  i-Evalue hmmfrom  hmm to    alifrom  ali to    envfrom  env to     acc
 ---   ------ ----- --------- --------- ------- -------    ------- -------    ------- -------    ----
   1 !  482.1   7.7  5.8e-149  5.8e-149       1     385 []      12     397 ..      12     397 .. 0.99

  Alignments for each domain:
  == domain 1  score: 482.1 bits;  conditional E-value: 5.8e-149
                           TIGR01930   1 ivdavRtpigklggslkelsaedLlaavikelleragldpekidevilGnvlqageqaniaReaalaaglpesvp 75 
                                         iv+a Rt+ig++gg l++lsa++L++avik++le +g+  ++i+ev+lG+vl+ag+++n+aR+ a++ag+p svp
  lcl|FitnessBrowser__Marino:GFF3052  12 IVAARRTAIGTFGGGLSSLSADQLGTAVIKAILEETGVAGDQINEVVLGQVLTAGCGQNPARQSAINAGIPASVP 86 
                                         89************************************************************************* PP

                           TIGR01930  76 altvnrvCaSglqAvalaaqkikaGeadvvvaGGvEsmSrvpillkaslrreslklgkakledqllkdl...vkt 147
                                         a+t+n+vC+Sgl+Av++a+q+i++G+a++++aGG EsmS++p++l++s  r++ ++g+ ++ d+++kd+   + +
  lcl|FitnessBrowser__Marino:GFF3052  87 AMTINKVCGSGLKAVHMAVQAIRCGDAEMMIAGGQESMSQAPHVLPNS--RNGQRMGNWSMVDTMIKDGlwdAFN 159
                                         ***********************************************8..89********************99* PP

                           TIGR01930 148 klsmgetAenlakkygisReeqDeyalrShqkaakAieegkfkdeivpvevkgk...kkvvskDegirpnttlek 219
                                         +++mg+tAen+ +kygisR+eqDe+a++S+qkaa+A e+g+f+ +ivpv+++++   + vv++Deg+r+++t+e 
  lcl|FitnessBrowser__Marino:GFF3052 160 DYHMGITAENIVEKYGISRDEQDEFAAASQQKAAAAREAGYFDGQIVPVSIPQRkgdPIVVDRDEGPRDGVTAEG 234
                                         ****************************************************999*99***************** PP

                           TIGR01930 220 LakLkpafkekkgstvtAgNssqlnDGAaalllmseevakelgltplarivsaavagvdpeemglgpvpAiekaL 294
                                         L+kL++afk+ +g tvtAgN+s+lnDGAaa+++ s e+a+elgltp+a+i ++a+agvdp++mg+gp+pA++++L
  lcl|FitnessBrowser__Marino:GFF3052 235 LGKLRAAFKK-DG-TVTAGNASSLNDGAAAVMVCSAEKAEELGLTPIATIKAYANAGVDPTIMGTGPIPASQRCL 307
                                         ********95.9*.6************************************************************ PP

                           TIGR01930 295 kkaglsisdidlvEinEAFAaqvlavekelgsldlekvNvnGGAiAlGHPlGasGarivltllkeLkergkkyGl 369
                                         k ag+s++d+dlvE nEAFAaq++ v++++g  d+ kvNvnGGAiAlGHP+GasG+ri+++ll+e+ +r+++ Gl
  lcl|FitnessBrowser__Marino:GFF3052 308 KLAGWSTEDLDLVEANEAFAAQAISVNRDMG-WDTGKVNVNGGAIALGHPIGASGCRILVSLLHEMVRRDVHKGL 381
                                         *******************************.88***************************************** PP

                           TIGR01930 370 atlCvggGqGaAvile 385
                                         atlC+ggG+G+A+ +e
  lcl|FitnessBrowser__Marino:GFF3052 382 ATLCIGGGMGVALAVE 397
                                         ************9886 PP



Internal pipeline statistics summary:
-------------------------------------
Query model(s):                            1  (385 nodes)
Target sequences:                          1  (398 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: 0.02u 0.01s 00:00:00.03 Elapsed: 00:00:00.01
# Mc/sec: 7.67
//
[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
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