Alignments for a candidate for fadA in Dechlorosoma suillum PS

GapMind for catabolism of small carbon sources

Alignments for a candidate for fadA in Dechlorosoma suillum PS

Align 3-ketoacyl-CoA thiolase; Acetyl-CoA acyltransferase; Beta-ketothiolase; EC 2.3.1.16 (characterized)
to candidate Dsui_0317 Dsui_0317 acetyl-CoA acetyltransferase

Query= SwissProt::O32177
         (391 letters)



>FitnessBrowser__PS:Dsui_0317
          Length = 399

 Score =  362 bits (928), Expect = e-104
 Identities = 200/400 (50%), Positives = 266/400 (66%), Gaps = 18/400 (4%)

Query: 1   MKEAVIVSGARTPVGKAKKGSLATVRPDDLGAICVKETLKRAGGYE-GNIDDLIIGCATP 59
           +++A IV+  R PV K + G   T RPDD+ A  +K  + +    +   ++D+I+GCA P
Sbjct: 5   IQDAYIVAATRLPVAK-RNGMFKTTRPDDMLAHALKSVMAQVPQLDPALVEDVIVGCAMP 63

Query: 60  EAEQGLNMARNIGALAGLPYTVPAITVNRYCSSGLQSIAYAAEKIMLGAYDTAIAGGAES 119
           EAEQG+N+AR    LAGLP TVP +T+NR+CSSG+Q++A AA +I LG  D  +A G E+
Sbjct: 64  EAEQGMNVARIGLLLAGLPDTVPGLTINRFCSSGVQAVADAAARIRLGEADVMLAAGTET 123

Query: 120 MSQVP-MMGHVTRPNLALAEKAPEYYMS--MGHTAEQVAKKYGVSREDQDAFAVRSHQNA 176
           MS +  MMG+    N A+ EK     ++  MG TAE+VA+K+G+SR+DQDAFAV SHQ A
Sbjct: 124 MSLMSQMMGNKVSLNPAIFEKDENVAIAYGMGLTAEKVAQKWGISRDDQDAFAVASHQKA 183

Query: 177 AKALAEGKFKDEIVPVEVTVTEIGEDHKPMEK-------QFVFSQDEGVRPQTTADILST 229
             A+A GKFKDEI P  V        H P  K       + V   DEG RP ++   L+ 
Sbjct: 184 VAAIAAGKFKDEISPYTVRA------HLPDLKSGTVRIVEKVCDTDEGPRPDSSLQGLAK 237

Query: 230 LRPAFSVDGTVTAGNSSQTSDGAAAVMLMDREKADALGLAPLVKFRSFAVGGVPPEVMGI 289
           L+P F+  G+VTAGNSSQ SDGA AV+L+  +      L PL +F  F+V GVPPE+MGI
Sbjct: 238 LKPVFNARGSVTAGNSSQMSDGAGAVLLVSEKILKQFNLQPLARFAGFSVAGVPPEIMGI 297

Query: 290 GPVEAIPRALKLAGLQLQDIGLFELNEAFASQAIQVIRELGIDEEKVNVNGGAIALGHPL 349
           GP+ AIP+ L  AG++  D+   ELNEAFA+QA+ V RELG+D  K+N  GGAIALGHPL
Sbjct: 298 GPIAAIPKVLAQAGIKQDDLDWIELNEAFAAQALAVTRELGLDPAKINPQGGAIALGHPL 357

Query: 350 GCTGTKLTLSLIHEMKRRNEQFGVVTMCIGGGMGAAGVFE 389
           G TG   T +L+H M+R N+++G+VTMCIG GMGAAG+FE
Sbjct: 358 GATGAIRTATLVHGMRRENKKWGMVTMCIGTGMGAAGLFE 397


Lambda     K      H
   0.316    0.133    0.377 

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: 420
Number of extensions: 15
Number of successful extensions: 4
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: 399
Length adjustment: 31
Effective length of query: 360
Effective length of database: 368
Effective search space:   132480
Effective search space used:   132480
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 (21.6 bits)
S2: 50 (23.9 bits)

Align candidate Dsui_0317 Dsui_0317 (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.1376.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
    ------- ------ -----    ------- ------ -----   ---- --  --------                         -----------
   2.6e-142  460.2   3.0   2.9e-142  460.1   3.0    1.0  1  lcl|FitnessBrowser__PS:Dsui_0317  Dsui_0317 acetyl-CoA acetyltrans


Domain annotation for each sequence (and alignments):
>> lcl|FitnessBrowser__PS:Dsui_0317  Dsui_0317 acetyl-CoA acetyltransferase
   #    score  bias  c-Evalue  i-Evalue hmmfrom  hmm to    alifrom  ali to    envfrom  env to     acc
 ---   ------ ----- --------- --------- ------- -------    ------- -------    ------- -------    ----
   1 !  460.1   3.0  2.9e-142  2.9e-142       1     385 []      10     397 ..      10     397 .. 0.97

  Alignments for each domain:
  == domain 1  score: 460.1 bits;  conditional E-value: 2.9e-142
                         TIGR01930   1 ivdavRtpigklggslkelsaedLlaavikellera.gldpekidevilGnvlqageq.aniaReaalaaglpesvp 75 
                                       iv+a+R p++k +g +k+++++d+la+++k++++++ +ldp+ +++vi+G++++++eq +n+aR  +l aglp++vp
  lcl|FitnessBrowser__PS:Dsui_0317  10 IVAATRLPVAKRNGMFKTTRPDDMLAHALKSVMAQVpQLDPALVEDVIVGCAMPEAEQgMNVARIGLLLAGLPDTVP 86 
                                       8*********99***************************************************************** PP

                         TIGR01930  76 altvnrvCaSglqAvalaaqkikaGeadvvvaGGvEsmSrvpillkaslrreslklgkakledqllkdlvktklsmg 152
                                       +lt+nr+C+Sg+qAva+aa++i+ Geadv++a+G E+mS +  ++ ++    sl++  +++++      v  ++ mg
  lcl|FitnessBrowser__PS:Dsui_0317  87 GLTINRFCSSGVQAVADAAARIRLGEADVMLAAGTETMSLMSQMMGNK---VSLNPAIFEKDE-----NVAIAYGMG 155
                                       ****************************************99888775...789988887777.....456789*** PP

                         TIGR01930 153 etAenlakkygisReeqDeyalrShqkaakAieegkfkdeivpvevkgk............kkvvskDegirpnttl 217
                                        tAe++a+k+gisR++qD++a++Shqka +Ai++gkfkdei p++v+ +            +kv+++Deg+rp+++l
  lcl|FitnessBrowser__PS:Dsui_0317 156 LTAEKVAQKWGISRDDQDAFAVASHQKAVAAIAAGKFKDEISPYTVRAHlpdlksgtvrivEKVCDTDEGPRPDSSL 232
                                       **********************************************999************9*************** PP

                         TIGR01930 218 ekLakLkpafkekkgstvtAgNssqlnDGAaalllmseevakelgltplarivsaavagvdpeemglgpvpAiekaL 294
                                       + LakLkp+f+   gs vtAgNssq++DGA+a+ll+se+++k+++l+plar+ +++vagv+pe+mg+gp+ Ai+k+L
  lcl|FitnessBrowser__PS:Dsui_0317 233 QGLAKLKPVFNA-RGS-VTAGNSSQMSDGAGAVLLVSEKILKQFNLQPLARFAGFSVAGVPPEIMGIGPIAAIPKVL 307
                                       **********96.8*7.************************************************************ PP

                         TIGR01930 295 kkaglsisdidlvEinEAFAaqvlavekelgsldlekvNvnGGAiAlGHPlGasGarivltllkeLkergkkyGlat 371
                                       ++ag++ +d+d++E+nEAFAaq+lav++elg ld++k+N +GGAiAlGHPlGa+Ga+ ++tl++ +++++kk G++t
  lcl|FitnessBrowser__PS:Dsui_0317 308 AQAGIKQDDLDWIELNEAFAAQALAVTRELG-LDPAKINPQGGAIALGHPLGATGAIRTATLVHGMRRENKKWGMVT 383
                                       *******************************.99******************************************* PP

                         TIGR01930 372 lCvggGqGaAvile 385
                                       +C+g+G+GaA ++e
  lcl|FitnessBrowser__PS:Dsui_0317 384 MCIGTGMGAAGLFE 397
                                       **********9986 PP



Internal pipeline statistics summary:
-------------------------------------
Query model(s):                            1  (385 nodes)
Target sequences:                          1  (399 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: 00:00:00.02
# Mc/sec: 7.20
//
[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
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