Alignments for a candidate for pcaF in Pseudomonas stutzeri RCH2

GapMind for catabolism of small carbon sources

Alignments for a candidate for pcaF in Pseudomonas stutzeri RCH2

Align Beta-ketoadipyl-CoA thiolase; 3-oxoadipyl-CoA thiolase; EC 2.3.1.174 (characterized)
to candidate GFF3012 Psest_3070 3-oxoadipyl-CoA thiolase

Query= SwissProt::Q8VPF1
         (401 letters)



>FitnessBrowser__psRCH2:GFF3012
          Length = 401

 Score =  664 bits (1712), Expect = 0.0
 Identities = 335/401 (83%), Positives = 371/401 (92%)

Query: 1   MSREVYICDAVRTPIGRFGGSLAAVRADDLAAVPVKALVERNPQVDWSQLDEVYLGCANQ 60
           MSR+V+ICDAVRTPIGRFGG+LAAVRADDLAA+P++AL+ERNP +D + +DEV++G ANQ
Sbjct: 1   MSRDVFICDAVRTPIGRFGGALAAVRADDLAAIPLRALLERNPGLDPAAVDEVFMGSANQ 60

Query: 61  AGEDNRNVARMALLLAGLPDSVPGVTLNRLCASGMDAVGTAFRAIASGEAELVIAGGVES 120
           AGEDNRNVARMALLLAGLP++VPGVTLNRLCASGMDAVGTAFRAI+SGE EL IAGGVES
Sbjct: 61  AGEDNRNVARMALLLAGLPETVPGVTLNRLCASGMDAVGTAFRAISSGELELAIAGGVES 120

Query: 121 MSRAPYVMGKADSAFGRGQKIEDTTIGWRFINPLMKAQYGVDAMPETADNVADDYKVSRA 180
           MSRAPYVMGKAD+AFGR QKIEDTTIGWRFINP MK  YGVDAMP+TADNVAD+++V RA
Sbjct: 121 MSRAPYVMGKADTAFGRIQKIEDTTIGWRFINPKMKELYGVDAMPQTADNVADEWQVGRA 180

Query: 181 DQDAFALRSQQLAGRAQAAGYFAEEIVPVVIKGKKGETVVDADEHLRPDTTLEALAKLKP 240
           DQDAFALRSQQ A  AQ AG+FAEEIVPVVI+GKKGETVVD DEH R DTT EALAKLKP
Sbjct: 181 DQDAFALRSQQRAAAAQQAGFFAEEIVPVVIRGKKGETVVDTDEHPRADTTAEALAKLKP 240

Query: 241 VNGPDKTVTAGNASGVNDGSVALILASAEAVKKHGLKARAKVLGMASAGVAPRVMGIGPV 300
           VNGPDKTVTAGNASGVNDG+ A+ILASAEAV+K+GLK RAKVLGMASAGVAPR+MG GPV
Sbjct: 241 VNGPDKTVTAGNASGVNDGAAAMILASAEAVQKYGLKPRAKVLGMASAGVAPRIMGYGPV 300

Query: 301 PAVRKLLERLNLSVADFDVIELNEAFAAQGLAVTRELGIADDDARVNPNGGAIALGHPLG 360
           PAVRKL ERLN++V+DFDVIELNEAFAAQGLAVTR+LG+ DD  +VNPNGGAIALGHPLG
Sbjct: 301 PAVRKLCERLNIAVSDFDVIELNEAFAAQGLAVTRDLGVPDDSPKVNPNGGAIALGHPLG 360

Query: 361 ASGARLVLTAVHQLEKSGGQRGLCTMCVGVGQGVALAVERV 401
            SGARLVLTAVHQLEK+GG+ GL TMCVGVGQG+AL VERV
Sbjct: 361 MSGARLVLTAVHQLEKTGGRLGLATMCVGVGQGLALVVERV 401


Lambda     K      H
   0.317    0.134    0.379 

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: 628
Number of extensions: 17
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: 401
Length of database: 401
Length adjustment: 31
Effective length of query: 370
Effective length of database: 370
Effective search space:   136900
Effective search space used:   136900
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 GFF3012 Psest_3070 (3-oxoadipyl-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.3314.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
    ------- ------ -----    ------- ------ -----   ---- --  --------                           -----------
   4.9e-222  723.0  10.4   5.5e-222  722.8  10.4    1.0  1  lcl|FitnessBrowser__psRCH2:GFF3012  Psest_3070 3-oxoadipyl-CoA thiol


Domain annotation for each sequence (and alignments):
>> lcl|FitnessBrowser__psRCH2:GFF3012  Psest_3070 3-oxoadipyl-CoA thiolase
   #    score  bias  c-Evalue  i-Evalue hmmfrom  hmm to    alifrom  ali to    envfrom  env to     acc
 ---   ------ ----- --------- --------- ------- -------    ------- -------    ------- -------    ----
   1 !  722.8  10.4  5.5e-222  5.5e-222       1     400 []       3     401 .]       3     401 .] 1.00

  Alignments for each domain:
  == domain 1  score: 722.8 bits;  conditional E-value: 5.5e-222
                           TIGR02430   1 kevyivdairtpiGrygGslssvraddlaavplkallarnpsldaaaiddvilGcanqaGednrnvarmaallaG 75 
                                         ++v+i+da+rtpiGr+gG+l++vraddlaa+pl+all+rnp ld aa+d+v++G+anqaGednrnvarma+llaG
  lcl|FitnessBrowser__psRCH2:GFF3012   3 RDVFICDAVRTPIGRFGGALAAVRADDLAAIPLRALLERNPGLDPAAVDEVFMGSANQAGEDNRNVARMALLLAG 77 
                                         689************************************************************************ PP

                           TIGR02430  76 lpvsvpgttvnrlcgsgldalglaaraikaGeadlviaGGvesmsrapfvlGkadsafsrsakledttiGwrfvn 150
                                         lp++vpg+t+nrlc+sg+da+g+a+rai +Ge +l iaGGvesmsrap+v+Gkad+af+r +k+edttiGwrf+n
  lcl|FitnessBrowser__psRCH2:GFF3012  78 LPETVPGVTLNRLCASGMDAVGTAFRAISSGELELAIAGGVESMSRAPYVMGKADTAFGRIQKIEDTTIGWRFIN 152
                                         *************************************************************************** PP

                           TIGR02430 151 pklkalyGvdsmpetaenvaeefgvsredqdafalrsqqrtaaaqakGffaeeivpveikqkkGeetvvdkdehl 225
                                         pk+k+lyGvd+mp+ta+nva+e++v r+dqdafalrsqqr+aaaq++Gffaeeivpv+i++kkG etvvd+deh+
  lcl|FitnessBrowser__psRCH2:GFF3012 153 PKMKELYGVDAMPQTADNVADEWQVGRADQDAFALRSQQRAAAAQQAGFFAEEIVPVVIRGKKG-ETVVDTDEHP 226
                                         ****************************************************************.899******* PP

                           TIGR02430 226 raettlealaklkavvredgtvtaGnasGvndGaaalllaseeavkrhgltprarilaaasaGveprvmGlgpvp 300
                                         ra+tt ealaklk+v+ +d+tvtaGnasGvndGaaa++las+eav+++gl+pra++l++asaGv+pr+mG gpvp
  lcl|FitnessBrowser__psRCH2:GFF3012 227 RADTTAEALAKLKPVNGPDKTVTAGNASGVNDGAAAMILASAEAVQKYGLKPRAKVLGMASAGVAPRIMGYGPVP 301
                                         *************************************************************************** PP

                           TIGR02430 301 avkkllaraglsledldvielneafaaqalavlrelgladddarvnpnGGaialGhplGasGarlvltalkqlek 375
                                         av+kl +r++++++d+dvielneafaaq+lav+r+lg++dd+ +vnpnGGaialGhplG+sGarlvlta++qlek
  lcl|FitnessBrowser__psRCH2:GFF3012 302 AVRKLCERLNIAVSDFDVIELNEAFAAQGLAVTRDLGVPDDSPKVNPNGGAIALGHPLGMSGARLVLTAVHQLEK 376
                                         *************************************************************************** PP

                           TIGR02430 376 sggryalatlciGvGqGialvierv 400
                                         +ggr +lat+c+GvGqG+alv+erv
  lcl|FitnessBrowser__psRCH2:GFF3012 377 TGGRLGLATMCVGVGQGLALVVERV 401
                                         ************************8 PP



Internal pipeline statistics summary:
-------------------------------------
Query model(s):                            1  (400 nodes)
Target sequences:                          1  (401 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: 8.44
//
[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