Alignments for a candidate for pcaF in Sinorhizobium meliloti 1021

GapMind for catabolism of small carbon sources

Alignments for a candidate for pcaF in Sinorhizobium meliloti 1021

Align β-ketoadipyl-CoA thiolase (EC 2.3.1.174; EC 2.3.1.223) (characterized)
to candidate SM_b20589 SM_b20589 beta-ketoadipyl CoA thiolase

Query= metacyc::MONOMER-15952
         (401 letters)



>FitnessBrowser__Smeli:SM_b20589
          Length = 400

 Score =  561 bits (1447), Expect = e-165
 Identities = 284/401 (70%), Positives = 336/401 (83%), Gaps = 1/401 (0%)

Query: 1   MNEALIIDAVRTPIGRYAGALASVRADDLGAIPLKALIARHPQLDWSAVDDVIYGCANQA 60
           M EA I D +RTPIGR+ G+LASVRADDLGAIPLKAL+ R+  +DW AVDDVI+GCANQA
Sbjct: 1   MREAYICDYIRTPIGRFGGSLASVRADDLGAIPLKALMDRNRSVDWEAVDDVIFGCANQA 60

Query: 61  GEDNRNVARMAALLAGLPVSVPGTTLNRLCGSGLDAVGSAARALRCGEAGLMLAGGVESM 120
           GEDNRN+ARM+ LLAGLPV+VPGTT+NRLCGSG+DAV +AARA++CGEA LM+AGGVESM
Sbjct: 61  GEDNRNIARMSLLLAGLPVAVPGTTINRLCGSGMDAVIAAARAIKCGEAELMIAGGVESM 120

Query: 121 SRAPFVMGKSEQAFGRSAEIFDTTIGWRFVNKLMQQGFGIDSMPETAENVAAQFNISRAD 180
           SRAPFV+ K+E AF R+AEI+DTTIGWRFVN LM+  +G+DSMPET ENVA  + +SR D
Sbjct: 121 SRAPFVLPKAESAFSRNAEIYDTTIGWRFVNPLMKAQYGVDSMPETGENVAEDYKVSRED 180

Query: 181 QDAFALRSQHKAAAAIANGRLAKEIVAVEIAQRKGPAKIVEHDEHPRGDTTLEQLAKLGT 240
           QDAFALRSQ KAAAA ANGRLA EIVAV I QRKG   +++ DEHPR  TT+E LA L T
Sbjct: 181 QDAFALRSQAKAAAAQANGRLASEIVAVTIPQRKGGPVVIDRDEHPRA-TTIEALAGLKT 239

Query: 241 PFRQGGSVTAGNASGVNDGACALLLASSEAAQRHGLKARARVVGMATAGVEPRIMGIGPV 300
           PFR+GG+VTAGNASGVNDGA AL++AS EAA++HGL+  AR++G A+AGV PRIMG+GPV
Sbjct: 240 PFREGGTVTAGNASGVNDGAAALIIASEEAARKHGLRPMARILGGASAGVPPRIMGMGPV 299

Query: 301 PATRKVLELTGLALADMDVIELNEAFAAQGLAVLRELGLADDDERVNPNGGAIALGHPLG 360
           PA+++++   G      DVIELNEAFA+QGLAVLR LG+ADDD RVN NGGAIALGHPLG
Sbjct: 300 PASQRLMTRLGATQDRFDVIELNEAFASQGLAVLRALGIADDDPRVNRNGGAIALGHPLG 359

Query: 361 MSGARLVTTALHELEERQGRYALCTMCIGVGQGIALIIERI 401
           MSGAR+  TA  EL E  GR +L TMCIGVGQGIA+ +ER+
Sbjct: 360 MSGARITGTAALELAETGGRTSLSTMCIGVGQGIAVALERV 400


Lambda     K      H
   0.319    0.134    0.384 

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: 570
Number of extensions: 18
Number of successful extensions: 2
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: 401
Length of database: 400
Length adjustment: 31
Effective length of query: 370
Effective length of database: 369
Effective search space:   136530
Effective search space used:   136530
Neighboring words threshold: 11
Window for multiple hits: 40
X1: 16 ( 7.4 bits)
X2: 38 (14.6 bits)
X3: 64 (24.7 bits)
S1: 41 (21.8 bits)
S2: 50 (23.9 bits)

Align candidate SM_b20589 SM_b20589 (beta-ketoadipyl CoA thiolase)
to HMM TIGR02430 (pcaF: 3-oxoadipyl-CoA thiolase (EC 2.3.1.174))

# 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/TIGR02430.hmm
# target sequence database:        /tmp/gapView.13238.genome.faa
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -

Query:       TIGR02430  [M=400]
Accession:   TIGR02430
Description: pcaF: 3-oxoadipyl-CoA thiolase
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-213  695.6  10.3   1.1e-213  695.5  10.3    1.0  1  lcl|FitnessBrowser__Smeli:SM_b20589  SM_b20589 beta-ketoadipyl CoA th


Domain annotation for each sequence (and alignments):
>> lcl|FitnessBrowser__Smeli:SM_b20589  SM_b20589 beta-ketoadipyl CoA thiolase
   #    score  bias  c-Evalue  i-Evalue hmmfrom  hmm to    alifrom  ali to    envfrom  env to     acc
 ---   ------ ----- --------- --------- ------- -------    ------- -------    ------- -------    ----
   1 !  695.5  10.3  1.1e-213  1.1e-213       1     400 []       2     400 .]       2     400 .] 1.00

  Alignments for each domain:
  == domain 1  score: 695.5 bits;  conditional E-value: 1.1e-213
                            TIGR02430   1 kevyivdairtpiGrygGslssvraddlaavplkallarnpsldaaaiddvilGcanqaGednrnvarmaalla 74 
                                          +e+yi+d irtpiGr+gGsl+svraddl+a+plkal++rn s+d++a+ddvi+GcanqaGednrn+arm++lla
  lcl|FitnessBrowser__Smeli:SM_b20589   2 REAYICDYIRTPIGRFGGSLASVRADDLGAIPLKALMDRNRSVDWEAVDDVIFGCANQAGEDNRNIARMSLLLA 75 
                                          69************************************************************************ PP

                            TIGR02430  75 GlpvsvpgttvnrlcgsgldalglaaraikaGeadlviaGGvesmsrapfvlGkadsafsrsakledttiGwrf 148
                                          Glpv+vpgtt+nrlcgsg+da+  aaraik+Gea+l+iaGGvesmsrapfvl ka+safsr+a++ dttiGwrf
  lcl|FitnessBrowser__Smeli:SM_b20589  76 GLPVAVPGTTINRLCGSGMDAVIAAARAIKCGEAELMIAGGVESMSRAPFVLPKAESAFSRNAEIYDTTIGWRF 149
                                          ************************************************************************** PP

                            TIGR02430 149 vnpklkalyGvdsmpetaenvaeefgvsredqdafalrsqqrtaaaqakGffaeeivpveikqkkGeetvvdkd 222
                                          vnp +ka+yGvdsmpet envae+++vsredqdafalrsq+++aaaqa+G +a+eiv v+i+q+kG ++v+d+d
  lcl|FitnessBrowser__Smeli:SM_b20589 150 VNPLMKAQYGVDSMPETGENVAEDYKVSREDQDAFALRSQAKAAAAQANGRLASEIVAVTIPQRKGGPVVIDRD 223
                                          ************************************************************************** PP

                            TIGR02430 223 ehlraettlealaklkavvredgtvtaGnasGvndGaaalllaseeavkrhgltprarilaaasaGveprvmGl 296
                                          eh+r  tt+eala lk+++re+gtvtaGnasGvndGaaal++aseea+++hgl+p aril+ asaGv pr+mG+
  lcl|FitnessBrowser__Smeli:SM_b20589 224 EHPR-ATTIEALAGLKTPFREGGTVTAGNASGVNDGAAALIIASEEAARKHGLRPMARILGGASAGVPPRIMGM 296
                                          ****.89******************************************************************* PP

                            TIGR02430 297 gpvpavkkllaraglsledldvielneafaaqalavlrelgladddarvnpnGGaialGhplGasGarlvltal 370
                                          gpvpa ++l++r+g + + +dvielneafa+q+lavlr+lg+addd rvn nGGaialGhplG+sGar+  ta 
  lcl|FitnessBrowser__Smeli:SM_b20589 297 GPVPASQRLMTRLGATQDRFDVIELNEAFASQGLAVLRALGIADDDPRVNRNGGAIALGHPLGMSGARITGTAA 370
                                          ************************************************************************** PP

                            TIGR02430 371 kqleksggryalatlciGvGqGialvierv 400
                                           +l+++ggr +l+t+ciGvGqGia+++erv
  lcl|FitnessBrowser__Smeli:SM_b20589 371 LELAETGGRTSLSTMCIGVGQGIAVALERV 400
                                          *****************************8 PP



Internal pipeline statistics summary:
-------------------------------------
Query model(s):                            1  (400 nodes)
Target sequences:                          1  (400 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: 10.66
//
[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