Alignments for a candidate for fadA in Dinoroseobacter shibae DFL-12

GapMind for catabolism of small carbon sources

Alignments for a candidate for fadA in Dinoroseobacter shibae DFL-12

Align acetyl-CoA:acetyl-CoA C-acetyltransferase / acetyl-CoA:propanoyl-CoA 2-C-acetyltransferase (EC 2.3.1.9; EC 2.3.1.16) (characterized)
to candidate 3609683 Dshi_3066 acetyl-CoA acetyltransferase (RefSeq)

Query= reanno::Phaeo:GFF329
         (391 letters)



>FitnessBrowser__Dino:3609683
          Length = 391

 Score =  714 bits (1842), Expect = 0.0
 Identities = 355/391 (90%), Positives = 372/391 (95%)

Query: 1   MTNVVIASAARTAVGSFGGAFAKTPAHDLGAAVLQAVVERAGIDKSEVSETILGQVLTAA 60
           MTNVVIASAARTAVGSFGG+FA TPAHDLG+AVL+A+V RAGI+K EVSETILGQVLT  
Sbjct: 1   MTNVVIASAARTAVGSFGGSFANTPAHDLGSAVLEALVARAGIEKGEVSETILGQVLTGG 60

Query: 61  QGQNPARQAHINAGLPQESAAWSLNQVCGSGLRAVALAAQHIQLGDAAIVCAGGQENMTL 120
           QGQNPARQAHINAGLPQESAAW LNQVCGSGLRAVAL AQHIQLGDA IVCAGGQENMTL
Sbjct: 61  QGQNPARQAHINAGLPQESAAWGLNQVCGSGLRAVALGAQHIQLGDAEIVCAGGQENMTL 120

Query: 121 SPHAANLRAGHKMGDMSYIDTMIRDGLWDAFNGYHMGQTAENVAEKWQISREMQDEFAVA 180
           SPH ANLRAG KMGDM +ID+MIRDGLWDAFNGYHMGQTAENVAEKWQISREMQDEFAVA
Sbjct: 121 SPHVANLRAGQKMGDMKFIDSMIRDGLWDAFNGYHMGQTAENVAEKWQISREMQDEFAVA 180

Query: 181 SQNKAEAAQKAGKFADEIAAFTVKTRKGDIIVDQDEYIRHGATIEAMQKLRPAFAKDGSV 240
           SQNKAEAAQKAGKF DE+ AFT+KTRKGDI+VD+DEYIRHGAT+EAMQKLRPAF KDGSV
Sbjct: 181 SQNKAEAAQKAGKFDDEVVAFTIKTRKGDIVVDKDEYIRHGATMEAMQKLRPAFTKDGSV 240

Query: 241 TAANASGLNDGAAATLLMSADDAEKRGIEPLARIASYATAGLDPSIMGVGPIYASRKALE 300
           TAANASGLNDGAA  LLMSA++AEKRGI P+ARIASYATAGLDPSIMGVGPIYASRKALE
Sbjct: 241 TAANASGLNDGAAGVLLMSAENAEKRGITPMARIASYATAGLDPSIMGVGPIYASRKALE 300

Query: 301 KAGWSVDDLDLVEANEAFAAQACAVNKDMGWDPAIVNVNGGAIAIGHPIGASGCRVLNTL 360
           KAGW VDDLDLVEANEAFAAQACAVNKDMGWDPAIVNVNGGAIAIGHPIGASG RVLNTL
Sbjct: 301 KAGWKVDDLDLVEANEAFAAQACAVNKDMGWDPAIVNVNGGAIAIGHPIGASGARVLNTL 360

Query: 361 LFEMKRRDAKKGLATLCIGGGMGVAMCVERP 391
           LFEM+RRDAKKGLATLCIGGGMGVA+CVERP
Sbjct: 361 LFEMQRRDAKKGLATLCIGGGMGVALCVERP 391


Lambda     K      H
   0.316    0.130    0.376 

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: 620
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: 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 3609683 Dshi_3066 (acetyl-CoA acetyltransferase (RefSeq))
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.13767.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-141  458.0  10.3   1.4e-141  457.8  10.3    1.0  1  lcl|FitnessBrowser__Dino:3609683  Dshi_3066 acetyl-CoA acetyltrans


Domain annotation for each sequence (and alignments):
>> lcl|FitnessBrowser__Dino:3609683  Dshi_3066 acetyl-CoA acetyltransferase (RefSeq)
   #    score  bias  c-Evalue  i-Evalue hmmfrom  hmm to    alifrom  ali to    envfrom  env to     acc
 ---   ------ ----- --------- --------- ------- -------    ------- -------    ------- -------    ----
   1 !  457.8  10.3  1.4e-141  1.4e-141       1     385 []       6     389 ..       6     389 .. 0.98

  Alignments for each domain:
  == domain 1  score: 457.8 bits;  conditional E-value: 1.4e-141
                         TIGR01930   1 ivdavRtpigklggslkelsaedLlaavikelleragldpekidevilGnvlqageqaniaReaalaaglpesvpal 77 
                                       i +a+Rt++g++ggs+++++a+dL++av+++l++rag+++ ++ e ilG+vl+ g+++n+aR+a ++aglp++ +a+
  lcl|FitnessBrowser__Dino:3609683   6 IASAARTAVGSFGGSFANTPAHDLGSAVLEALVARAGIEKGEVSETILGQVLTGGQGQNPARQAHINAGLPQESAAW 82 
                                       789************************************************************************** PP

                         TIGR01930  78 tvnrvCaSglqAvalaaqkikaGeadvvvaGGvEsmSrvpillkaslrreslklgkakledqllkdl...vktklsm 151
                                        +n+vC+Sgl+Aval+aq+i+ G+a++v+aGG E+m+ +p++ +    r++ k+g++k  d++++d+   + ++++m
  lcl|FitnessBrowser__Dino:3609683  83 GLNQVCGSGLRAVALGAQHIQLGDAEIVCAGGQENMTLSPHVANL---RAGQKMGDMKFIDSMIRDGlwdAFNGYHM 156
                                       ****************************************98776...58999999**************99***** PP

                         TIGR01930 152 getAenlakkygisReeqDeyalrShqkaakAieegkfkdeivpvevkgk..kkvvskDegirpnttlekLakLkpa 226
                                       g+tAen+a+k++isRe+qDe+a++S++ka++A+++gkf+de+v +++k++  + vv+kDe ir + t+e+++kL+pa
  lcl|FitnessBrowser__Dino:3609683 157 GQTAENVAEKWQISREMQDEFAVASQNKAEAAQKAGKFDDEVVAFTIKTRkgDIVVDKDEYIRHGATMEAMQKLRPA 233
                                       ************************************************999999*********************** PP

                         TIGR01930 227 fkekkgstvtAgNssqlnDGAaalllmseevakelgltplarivsaavagvdpeemglgpvpAiekaLkkaglsisd 303
                                       f++ +gs vtA+N+s+lnDGAa +llms e a++ g+tp+ari s+a+ag+dp++mg+gp++A++kaL+kag++++d
  lcl|FitnessBrowser__Dino:3609683 234 FTK-DGS-VTAANASGLNDGAAGVLLMSAENAEKRGITPMARIASYATAGLDPSIMGVGPIYASRKALEKAGWKVDD 308
                                       *95.9*7.********************************************************************* PP

                         TIGR01930 304 idlvEinEAFAaqvlavekelgsldlekvNvnGGAiAlGHPlGasGarivltllkeLkergkkyGlatlCvggGqGa 380
                                       +dlvE nEAFAaq+ av+k++g  d++ vNvnGGAiA+GHP+GasGar++ tll e+++r++k GlatlC+ggG+G+
  lcl|FitnessBrowser__Dino:3609683 309 LDLVEANEAFAAQACAVNKDMG-WDPAIVNVNGGAIAIGHPIGASGARVLNTLLFEMQRRDAKKGLATLCIGGGMGV 384
                                       **********************.88**************************************************** PP

                         TIGR01930 381 Avile 385
                                       A+ +e
  lcl|FitnessBrowser__Dino:3609683 385 ALCVE 389
                                       *9886 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 0.01s 00:00:00.02 Elapsed: 00:00:00.01
# Mc/sec: 10.57
//
[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
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