Alignments for a candidate for fadA in Pseudomonas stutzeri RCH2

GapMind for catabolism of small carbon sources

Alignments for a candidate for fadA in Pseudomonas stutzeri RCH2

Align subunit of β-ketoadipyl CoA thiolase (EC 2.3.1.174; EC 2.3.1.16) (characterized)
to candidate GFF3012 Psest_3070 3-oxoadipyl-CoA thiolase

Query= metacyc::MONOMER-3207
         (400 letters)



>FitnessBrowser__psRCH2:GFF3012
          Length = 401

 Score =  653 bits (1685), Expect = 0.0
 Identities = 328/399 (82%), Positives = 364/399 (91%)

Query: 2   RDVFICDAIRTPIGRFGGALAGVRADDLAAVPLKALIEPNPAVQWDQVDEVFFGCANQAG 61
           RDVFICDA+RTPIGRFGGALA VRADDLAA+PL+AL+E NP +    VDEVF G ANQAG
Sbjct: 3   RDVFICDAVRTPIGRFGGALAAVRADDLAAIPLRALLERNPGLDPAAVDEVFMGSANQAG 62

Query: 62  EDNRNVARMALLLAGLPESIPGVTLNRLCASGMDAIGTAFRAIASGEMELAIAGGVESMS 121
           EDNRNVARMALLLAGLPE++PGVTLNRLCASGMDA+GTAFRAI+SGE+ELAIAGGVESMS
Sbjct: 63  EDNRNVARMALLLAGLPETVPGVTLNRLCASGMDAVGTAFRAISSGELELAIAGGVESMS 122

Query: 122 RAPFVMGKAESGYSRNMKLEDTTIGWRFINPLMKSQYGVDSMPETADNVADDYQVSRADQ 181
           RAP+VMGKA++ + R  K+EDTTIGWRFINP MK  YGVD+MP+TADNVAD++QV RADQ
Sbjct: 123 RAPYVMGKADTAFGRIQKIEDTTIGWRFINPKMKELYGVDAMPQTADNVADEWQVGRADQ 182

Query: 182 DAFALRSQQKAAAAQAAGFFAEEIVPVRIAHKKGETIVERDEHLRPETTLEALTKLKPVN 241
           DAFALRSQQ+AAAAQ AGFFAEEIVPV I  KKGET+V+ DEH R +TT EAL KLKPVN
Sbjct: 183 DAFALRSQQRAAAAQQAGFFAEEIVPVVIRGKKGETVVDTDEHPRADTTAEALAKLKPVN 242

Query: 242 GPDKTVTAGNASGVNDGAAALILASAEAVKKHGLTPRARVLGMASGGVAPRVMGIGPVPA 301
           GPDKTVTAGNASGVNDGAAA+ILASAEAV+K+GL PRA+VLGMAS GVAPR+MG GPVPA
Sbjct: 243 GPDKTVTAGNASGVNDGAAAMILASAEAVQKYGLKPRAKVLGMASAGVAPRIMGYGPVPA 302

Query: 302 VRKLTERLGVAVSDFDVIELNEAFASQGLAVLRELGVADDAPQVNPNGGAIALGHPLGMS 361
           VRKL ERL +AVSDFDVIELNEAFA+QGLAV R+LGV DD+P+VNPNGGAIALGHPLGMS
Sbjct: 303 VRKLCERLNIAVSDFDVIELNEAFAAQGLAVTRDLGVPDDSPKVNPNGGAIALGHPLGMS 362

Query: 362 GARLVLTALHQLEKSGGRKGLATMCVGVGQGLALAIERV 400
           GARLVLTA+HQLEK+GGR GLATMCVGVGQGLAL +ERV
Sbjct: 363 GARLVLTAVHQLEKTGGRLGLATMCVGVGQGLALVVERV 401


Lambda     K      H
   0.318    0.134    0.383 

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: 619
Number of extensions: 16
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: 400
Length of database: 401
Length adjustment: 31
Effective length of query: 369
Effective length of database: 370
Effective search space:   136530
Effective search space used:   136530
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 GFF3012 Psest_3070 (3-oxoadipyl-CoA thiolase)
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.1514.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
    ------- ------ -----    ------- ------ -----   ---- --  --------                           -----------
   1.1e-141  458.1   2.3   1.3e-141  457.9   2.3    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 !  457.9   2.3  1.3e-141  1.3e-141       1     385 []       7     399 ..       7     399 .. 0.95

  Alignments for each domain:
  == domain 1  score: 457.9 bits;  conditional E-value: 1.3e-141
                           TIGR01930   1 ivdavRtpigklggslkelsaedLlaavikellera.gldpekidevilGnvlqageq.aniaReaalaaglpes 73 
                                         i davRtpig++gg+l+ ++a+dL+a  +++ller+ gldp+++dev +G + qage+  n+aR+a+l aglpe+
  lcl|FitnessBrowser__psRCH2:GFF3012   7 ICDAVRTPIGRFGGALAAVRADDLAAIPLRALLERNpGLDPAAVDEVFMGSANQAGEDnRNVARMALLLAGLPET 81 
                                         789*******************************************************9**************** PP

                           TIGR01930  74 vpaltvnrvCaSglqAvalaaqkikaGeadvvvaGGvEsmSrvpillkaslrreslklgkakledqllkdl.... 144
                                         vp++t+nr+CaSg++Av +a ++i++Ge ++++aGGvEsmSr+p+++ ++  ++  +++k+++       +    
  lcl|FitnessBrowser__psRCH2:GFF3012  82 VPGVTLNRLCASGMDAVGTAFRAISSGELELAIAGGVESMSRAPYVMGKA-DTAFGRIQKIEDTTI----Gwrfi 151
                                         **********************************************9997.445555555555443....13456 PP

                           TIGR01930 145 ......vktklsmgetAenlakkygisReeqDeyalrShqkaakAieegkfkdeivpvevkgk..kkvvskDegi 211
                                                +   +m +tA+n+a+++++ R +qD++alrS+q+aa+A+++g+f++eivpv+++gk  ++vv++De++
  lcl|FitnessBrowser__psRCH2:GFF3012 152 npkmkeLYGVDAMPQTADNVADEWQVGRADQDAFALRSQQRAAAAQQAGFFAEEIVPVVIRGKkgETVVDTDEHP 226
                                         998887666779**************************************************9*99********* PP

                           TIGR01930 212 rpnttlekLakLkpafkekkgstvtAgNssqlnDGAaalllmseevakelgltplarivsaavagvdpeemglgp 286
                                         r++tt+e+LakLkp+  + +  tvtAgN+s++nDGAaa++l+s e+++++gl+p a++ ++a agv p++mg+gp
  lcl|FitnessBrowser__psRCH2:GFF3012 227 RADTTAEALAKLKPVNGP-DK-TVTAGNASGVNDGAAAMILASAEAVQKYGLKPRAKVLGMASAGVAPRIMGYGP 299
                                         ****************95.77.7**************************************************** PP

                           TIGR01930 287 vpAiekaLkkaglsisdidlvEinEAFAaqvlavekelgsld.lekvNvnGGAiAlGHPlGasGarivltllkeL 360
                                         vpA++k+ ++ ++ +sd+d++E+nEAFAaq lav+++lg  d   kvN nGGAiAlGHPlG+sGar+vlt +++L
  lcl|FitnessBrowser__psRCH2:GFF3012 300 VPAVRKLCERLNIAVSDFDVIELNEAFAAQGLAVTRDLGVPDdSPKVNPNGGAIALGHPLGMSGARLVLTAVHQL 374
                                         ***************************************855699****************************** PP

                           TIGR01930 361 kergkkyGlatlCvggGqGaAvile 385
                                         ++ g+++Glat+Cvg GqG A+++e
  lcl|FitnessBrowser__psRCH2:GFF3012 375 EKTGGRLGLATMCVGVGQGLALVVE 399
                                         ***********************97 PP



Internal pipeline statistics summary:
-------------------------------------
Query model(s):                            1  (385 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: 10.05
//
[ok]

This GapMind analysis is from Sep 17 2021. The underlying query database was built on Sep 17 2021.

Downloads

Candidates (tab-delimited)
Steps (tab-delimited)
Rules (tab-delimited)
Protein sequences (fasta format)
Organisms (tab-delimited)
SQLite3 databases

Related tools

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