Aligments for a candidate for fadA in Caulobacter crescentus NA1000

GapMind for catabolism of small carbon sources

Aligments for a candidate for fadA in Caulobacter crescentus NA1000

Align acetyl-CoA acetyltransferase (EC 2.3.1.16) (characterized)
to candidate CCNA_00544 CCNA_00544 acetyl-CoA acetyltransferase

Query= metacyc::MONOMER-13585
         (391 letters)



>FitnessBrowser__Caulo:CCNA_00544
          Length = 391

 Score =  565 bits (1455), Expect = e-165
 Identities = 279/389 (71%), Positives = 331/389 (85%)

Query: 1   MTNVVIVSAARTAVGSFNGAFASTPAHDLGAAVIEAVVARAGIDKADVSETILGQVLTAG 60
           M+ +VIVSAART VGSFNGA AS PA +LG AVIEA V+RAGI  +DV E ILGQVL A 
Sbjct: 1   MSEIVIVSAARTPVGSFNGALASLPASELGKAVIEAAVSRAGIAPSDVDEVILGQVLQAA 60

Query: 61  QGQNPARQAHIKAGLPQESAAWSINQVCGSGLRAVALAAQHVQLGDASIVVAGGQENMSL 120
            GQ PARQA +KAG+P E+ AWS+NQ+CGSGLRAVALAAQ +  G A +VVAGGQE+MS 
Sbjct: 61  AGQGPARQASVKAGIPVEAPAWSLNQLCGSGLRAVALAAQQIADGSAKVVVAGGQESMSQ 120

Query: 121 SPHVAHLRAGQKMGDLSFIDSMIKDGLWDAFNGYHMGQTAENVAAKWQISRDMQDEFAVA 180
           +PH  +LR GQKMGDL F+D+MIKDGLWDAF+GYHMGQTAEN+A++WQI+R+ QD+FAV 
Sbjct: 121 APHAQNLRGGQKMGDLQFVDTMIKDGLWDAFHGYHMGQTAENIASRWQITREDQDKFAVT 180

Query: 181 SQNKAEAAQKAGRFADEIVPFVIKTRKGDVTVDADEYIRHGATLDAMAKLRPAFIKDGTV 240
           SQN+AEAAQKAG+F DEIVP  IK RKGD  VD DE+IRHGAT++++  L+P F K+G+V
Sbjct: 181 SQNRAEAAQKAGKFDDEIVPITIKGRKGDTIVDKDEFIRHGATIESVQGLKPVFNKEGSV 240

Query: 241 TAANASGINDGAAAVLVMSAEEAEKRGLSPLARIASYATAGLDPSIMGVGPIHASRKALE 300
           TAANASG+NDGAAA+++MSAEEA KRGL PLARIAS+A AG++P IMG GPI AS+KALE
Sbjct: 241 TAANASGLNDGAAALVLMSAEEAAKRGLKPLARIASWANAGVEPEIMGTGPIPASKKALE 300

Query: 301 KAGWKVGDLDLVEANEAFAAQACAVNKDMGWDPSIVNVNGGAIAIGHPIGASGARVLNTL 360
           KAGW V DLDLVE+NEAFAAQA  V +++G DP+ VNVNGGAIAIGHPIGASGAR+L TL
Sbjct: 301 KAGWSVSDLDLVESNEAFAAQALCVVRELGLDPAKVNVNGGAIAIGHPIGASGARILTTL 360

Query: 361 LFEMQRRNAKKGLATLCIGGGMGVAMCLE 389
           + EM+R  AKKGLATLC+GGGMGVAMC+E
Sbjct: 361 VHEMKRSGAKKGLATLCVGGGMGVAMCVE 389


Lambda     K      H
   0.317    0.130    0.375 

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: 517
Number of extensions: 10
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: 391
Length of database: 391
Length adjustment: 31
Effective length of query: 360
Effective length of database: 360
Effective search space:   129600
Effective search space used:   129600
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 CCNA_00544 CCNA_00544 (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.2618.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
    ------- ------ -----    ------- ------ -----   ---- --  --------                             -----------
     1e-150  487.9   9.7   1.2e-150  487.7   9.7    1.0  1  lcl|FitnessBrowser__Caulo:CCNA_00544  CCNA_00544 acetyl-CoA acetyltran


Domain annotation for each sequence (and alignments):
>> lcl|FitnessBrowser__Caulo:CCNA_00544  CCNA_00544 acetyl-CoA acetyltransferase
   #    score  bias  c-Evalue  i-Evalue hmmfrom  hmm to    alifrom  ali to    envfrom  env to     acc
 ---   ------ ----- --------- --------- ------- -------    ------- -------    ------- -------    ----
   1 !  487.7   9.7  1.2e-150  1.2e-150       1     385 []       6     389 ..       6     389 .. 0.98

  Alignments for each domain:
  == domain 1  score: 487.7 bits;  conditional E-value: 1.2e-150
                             TIGR01930   1 ivdavRtpigklggslkelsaedLlaavikelleragldpekidevilGnvlqageqaniaReaalaaglpes 73 
                                           iv+a+Rtp+g+++g+l++l+a++L++avi++++ rag+ p+++devilG+vlqa++++ +aR+a ++ag+p +
  lcl|FitnessBrowser__Caulo:CCNA_00544   6 IVSAARTPVGSFNGALASLPASELGKAVIEAAVSRAGIAPSDVDEVILGQVLQAAAGQGPARQASVKAGIPVE 78 
                                           8************************************************************************ PP

                             TIGR01930  74 vpaltvnrvCaSglqAvalaaqkikaGeadvvvaGGvEsmSrvpillkaslrreslklgkakledqllkdl.. 144
                                            pa+++n++C+Sgl+Avalaaq+i+ G a+vvvaGG EsmS++p+  +    r + k+g+ +  d+++kd+  
  lcl|FitnessBrowser__Caulo:CCNA_00544  79 APAWSLNQLCGSGLRAVALAAQQIADGSAKVVVAGGQESMSQAPHAQNL---RGGQKMGDLQFVDTMIKDGlw 148
                                           ********************************************86665...6999***************** PP

                             TIGR01930 145 .vktklsmgetAenlakkygisReeqDeyalrShqkaakAieegkfkdeivpvevkgk..kkvvskDegirpn 214
                                            + ++++mg+tAen+a +++i+Re+qD++a+ S+++a++A+++gkf+deivp+++kg+  +++v+kDe ir +
  lcl|FitnessBrowser__Caulo:CCNA_00544 149 dAFHGYHMGQTAENIASRWQITREDQDKFAVTSQNRAEAAQKAGKFDDEIVPITIKGRkgDTIVDKDEFIRHG 221
                                           *99********************************************************999*********** PP

                             TIGR01930 215 ttlekLakLkpafkekkgstvtAgNssqlnDGAaalllmseevakelgltplarivsaavagvdpeemglgpv 287
                                            t+e++++Lkp+f++ +gs vtA+N+s+lnDGAaal+lms e a++ gl+plari s+a+agv+pe+mg+gp+
  lcl|FitnessBrowser__Caulo:CCNA_00544 222 ATIESVQGLKPVFNK-EGS-VTAANASGLNDGAAALVLMSAEEAAKRGLKPLARIASWANAGVEPEIMGTGPI 292
                                           *************96.8*7.***************************************************** PP

                             TIGR01930 288 pAiekaLkkaglsisdidlvEinEAFAaqvlavekelgsldlekvNvnGGAiAlGHPlGasGarivltllkeL 360
                                           pA++kaL+kag+s+sd+dlvE nEAFAaq+l v++elg ld++kvNvnGGAiA+GHP+GasGari++tl++e+
  lcl|FitnessBrowser__Caulo:CCNA_00544 293 PASKKALEKAGWSVSDLDLVESNEAFAAQALCVVRELG-LDPAKVNVNGGAIAIGHPIGASGARILTTLVHEM 364
                                           **************************************.99******************************** PP

                             TIGR01930 361 kergkkyGlatlCvggGqGaAvile 385
                                           k+ g+k GlatlCvggG+G+A+ +e
  lcl|FitnessBrowser__Caulo:CCNA_00544 365 KRSGAKKGLATLCVGGGMGVAMCVE 389
                                           **********************987 PP



Internal pipeline statistics summary:
-------------------------------------
Query model(s):                            1  (385 nodes)
Target sequences:                          1  (391 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: 10.33
//
[ok]

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 (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