Alignments for a candidate for ald-dh-CoA in Pseudomonas fluorescens GW456-L13

GapMind for catabolism of small carbon sources

Alignments for a candidate for ald-dh-CoA in Pseudomonas fluorescens GW456-L13

Align acetaldehyde dehydrogenase (acetylating) (EC 1.2.1.10); propanal dehydrogenase (CoA-propanoylating) (EC 1.2.1.87) (characterized)
to candidate PfGW456L13_2505 Acetaldehyde dehydrogenase, acetylating, (EC 1.2.1.10) in gene cluster for degradation of phenols, cresols, catechol

Query= BRENDA::Q79AF6
         (304 letters)



>FitnessBrowser__pseudo13_GW456_L13:PfGW456L13_2505
          Length = 302

 Score =  465 bits (1197), Expect = e-136
 Identities = 223/299 (74%), Positives = 262/299 (87%)

Query: 1   MTKKIKCALIGPGNIGTDLLAKLQRSPVLEPIWMVGIDPESDGLKRAREMGIKTTADGVD 60
           M+KK++ A+IGPGNIGTDLL K+ RS  +EP+WMVG+DP+S+GLKRAREMGIKTTA GVD
Sbjct: 1   MSKKLRAAIIGPGNIGTDLLMKMCRSQWIEPVWMVGVDPDSEGLKRAREMGIKTTAGGVD 60

Query: 61  GLIPHMQADGVQIVFDATSAYVHADNSRKVNALGALMIDLTPAAIGPFCVPTVNLKEHVG 120
           GL+PH+  D ++I FDATSAYVHA+NSRK+N LG +MIDLTPAAIGP+CVP VNLKEH  
Sbjct: 61  GLLPHVLDDDIRIAFDATSAYVHAENSRKLNELGVIMIDLTPAAIGPYCVPPVNLKEHAS 120

Query: 121 KGEMNVNMVTCGGQATIPMVAAVSRVQPVAYGEIVATVSSKSAGPGTRKNIDEFTRTTAG 180
              MNVNMVTCGGQATIPMVAAVSRVQPV+YGEIVATVSS S GPGTR+NIDEFTRTTAG
Sbjct: 121 SLAMNVNMVTCGGQATIPMVAAVSRVQPVSYGEIVATVSSGSVGPGTRQNIDEFTRTTAG 180

Query: 181 AVEKVGGAKKGKAIIILNPAEPPLIMRDTVHCLLESEPDQAKITESIHAMIKEVQKYVPG 240
           AVEK+GGA++GKAII++NPAEPPL+MRDT+HCL + EP+Q  I  S+  M++EVQ+YVPG
Sbjct: 181 AVEKIGGARRGKAIIVINPAEPPLMMRDTIHCLTDDEPNQDAIRTSVLEMVREVQRYVPG 240

Query: 241 YKLVNGPVFDGLRVSVYLEVEGLGDYLPKYAGNLDIMTAAAARTAEMFAEEILAGQLTL 299
           YKL+NGPVFDG +VS+++EVEGLGD+LPK AGNLDIMTAA  RTAEMFAEE   G L L
Sbjct: 241 YKLINGPVFDGRKVSIFIEVEGLGDFLPKSAGNLDIMTAAGLRTAEMFAEEAHKGTLQL 299


Lambda     K      H
   0.317    0.135    0.388 

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: 347
Number of extensions: 7
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: 304
Length of database: 302
Length adjustment: 27
Effective length of query: 277
Effective length of database: 275
Effective search space:    76175
Effective search space used:    76175
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: 48 (23.1 bits)

Align candidate PfGW456L13_2505 (Acetaldehyde dehydrogenase, acetylating, (EC 1.2.1.10) in gene cluster for degradation of phenols, cresols, catechol)
to HMM TIGR03215 (acetaldehyde dehydrogenase (acetylating) (EC 1.2.1.10))

# 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/TIGR03215.hmm
# target sequence database:        /tmp/gapView.7551.genome.faa
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -

Query:       TIGR03215  [M=285]
Accession:   TIGR03215
Description: ac_ald_DH_ac: acetaldehyde dehydrogenase (acetylating)
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
    ------- ------ -----    ------- ------ -----   ---- --  --------                                               -----------
   1.5e-143  463.2   0.2   1.8e-143  463.0   0.2    1.0  1  lcl|FitnessBrowser__pseudo13_GW456_L13:PfGW456L13_2505  Acetaldehyde dehydrogenase, acet


Domain annotation for each sequence (and alignments):
>> lcl|FitnessBrowser__pseudo13_GW456_L13:PfGW456L13_2505  Acetaldehyde dehydrogenase, acetylating, (EC 1.2.1.10) in gen
   #    score  bias  c-Evalue  i-Evalue hmmfrom  hmm to    alifrom  ali to    envfrom  env to     acc
 ---   ------ ----- --------- --------- ------- -------    ------- -------    ------- -------    ----
   1 !  463.0   0.2  1.8e-143  1.8e-143       1     283 [.       4     292 ..       4     294 .. 0.98

  Alignments for each domain:
  == domain 1  score: 463.0 bits;  conditional E-value: 1.8e-143
                                               TIGR03215   1 kvkvaiiGsGnigtdllikllrsevlelallvGidpesdGlararelgvetsaeG 55 
                                                             k+++aiiG+Gnigtdll+k+ rs+ +e++++vG+dp+s+Gl+rare+g++t+a G
  lcl|FitnessBrowser__pseudo13_GW456_L13:PfGW456L13_2505   4 KLRAAIIGPGNIGTDLLMKMCRSQWIEPVWMVGVDPDSEGLKRAREMGIKTTAGG 58 
                                                             789**************************************************** PP

                                               TIGR03215  56 vdalleee...didivfdatsakahaenaklleelgkividltPaavGpyvvPav 107
                                                             vd+ll +    di+i+fdatsa++haen+++l+elg+i+idltPaa+Gpy+vP+v
  lcl|FitnessBrowser__pseudo13_GW456_L13:PfGW456L13_2505  59 VDGLLPHVlddDIRIAFDATSAYVHAENSRKLNELGVIMIDLTPAAIGPYCVPPV 113
                                                             ******98888******************************************** PP

                                               TIGR03215 108 nleevldak..nvnlvtCgGqatiPivaavsrvakvkyaeivasiasksaGpgtr 160
                                                             nl+e+  +   nvn+vtCgGqatiP+vaavsrv++v+y+eiva+++s s+Gpgtr
  lcl|FitnessBrowser__pseudo13_GW456_L13:PfGW456L13_2505 114 NLKEHASSLamNVNMVTCGGQATIPMVAAVSRVQPVSYGEIVATVSSGSVGPGTR 168
                                                             *****987667******************************************** PP

                                               TIGR03215 161 anideftettskaleqvgGakkgkaiiilnPaePpllmrdtvyalv.eeadeeai 214
                                                             +nideft+tt+ a+e++gGa++gkaii++nPaePpl+mrdt+++l+ +e++++ai
  lcl|FitnessBrowser__pseudo13_GW456_L13:PfGW456L13_2505 169 QNIDEFTRTTAGAVEKIGGARRGKAIIVINPAEPPLMMRDTIHCLTdDEPNQDAI 223
                                                             **********************************************899****** PP

                                               TIGR03215 215 easveemveevqkyvpGyrlkqevvldgekvsvlleveGagdylPkyaGnldilt 269
                                                             ++sv emv+evq+yvpGy+l + +v+dg+kvs+++eveG gd+lPk aGnldi+t
  lcl|FitnessBrowser__pseudo13_GW456_L13:PfGW456L13_2505 224 RTSVLEMVREVQRYVPGYKLINGPVFDGRKVSIFIEVEGLGDFLPKSAGNLDIMT 278
                                                             ******************************************************* PP

                                               TIGR03215 270 aaalavaeklaeel 283
                                                             aa l++ae++aee 
  lcl|FitnessBrowser__pseudo13_GW456_L13:PfGW456L13_2505 279 AAGLRTAEMFAEEA 292
                                                             ***********975 PP



Internal pipeline statistics summary:
-------------------------------------
Query model(s):                            1  (285 nodes)
Target sequences:                          1  (302 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: 0.00u 0.00s 00:00:00.00 Elapsed: 00:00:00.01
# Mc/sec: 8.54
//
[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