Alignments for a candidate for fadA in Pseudomonas putida KT2440

GapMind for catabolism of small carbon sources

Alignments for a candidate for fadA in Pseudomonas putida KT2440

Align FadA (EC 2.3.1.16) (characterized)
to candidate PP_2137 PP_2137 beta-ketoadipyl CoA thiolase, beta component

Query= metacyc::G1G01-2278-MONOMER
         (391 letters)



>FitnessBrowser__Putida:PP_2137
          Length = 391

 Score =  780 bits (2014), Expect = 0.0
 Identities = 391/391 (100%), Positives = 391/391 (100%)

Query: 1   MSLNPRDVVIVDFGRTPMGRSKGGMHRNTRAEDMSAHLISKLLERNGKVDPKEVEDVIWG 60
           MSLNPRDVVIVDFGRTPMGRSKGGMHRNTRAEDMSAHLISKLLERNGKVDPKEVEDVIWG
Sbjct: 1   MSLNPRDVVIVDFGRTPMGRSKGGMHRNTRAEDMSAHLISKLLERNGKVDPKEVEDVIWG 60

Query: 61  CVNQTLEQGWNIARMASLMTPIPHTSAAQTVSRLCGSSMSALHTAAQAIMTGNGDVFVVG 120
           CVNQTLEQGWNIARMASLMTPIPHTSAAQTVSRLCGSSMSALHTAAQAIMTGNGDVFVVG
Sbjct: 61  CVNQTLEQGWNIARMASLMTPIPHTSAAQTVSRLCGSSMSALHTAAQAIMTGNGDVFVVG 120

Query: 121 GVEHMGHVSMMHGVDPNPHLSLHAAKASGMMGLTAEMLGKMHGITREQQDLFGLRSHQLA 180
           GVEHMGHVSMMHGVDPNPHLSLHAAKASGMMGLTAEMLGKMHGITREQQDLFGLRSHQLA
Sbjct: 121 GVEHMGHVSMMHGVDPNPHLSLHAAKASGMMGLTAEMLGKMHGITREQQDLFGLRSHQLA 180

Query: 181 HKATVEGKFKDEIIPMQGYDENGFLKVFDFDETIRPETTLEGLASLKPAFNPKGGTVTAG 240
           HKATVEGKFKDEIIPMQGYDENGFLKVFDFDETIRPETTLEGLASLKPAFNPKGGTVTAG
Sbjct: 181 HKATVEGKFKDEIIPMQGYDENGFLKVFDFDETIRPETTLEGLASLKPAFNPKGGTVTAG 240

Query: 241 TSSQITDGASCMIVMSGQRAMDLGIQPLAVIRSMAVAGVDPAIMGYGPVPSTQKALKRAG 300
           TSSQITDGASCMIVMSGQRAMDLGIQPLAVIRSMAVAGVDPAIMGYGPVPSTQKALKRAG
Sbjct: 241 TSSQITDGASCMIVMSGQRAMDLGIQPLAVIRSMAVAGVDPAIMGYGPVPSTQKALKRAG 300

Query: 301 LTMADIDFIELNEAFAAQALPVLKDLKVLDKMDEKVNLHGGAIALGHPFGCSGARISGTL 360
           LTMADIDFIELNEAFAAQALPVLKDLKVLDKMDEKVNLHGGAIALGHPFGCSGARISGTL
Sbjct: 301 LTMADIDFIELNEAFAAQALPVLKDLKVLDKMDEKVNLHGGAIALGHPFGCSGARISGTL 360

Query: 361 LNVMKQNGGTLGVATMCVGLGQGITTVFERV 391
           LNVMKQNGGTLGVATMCVGLGQGITTVFERV
Sbjct: 361 LNVMKQNGGTLGVATMCVGLGQGITTVFERV 391


Lambda     K      H
   0.319    0.134    0.392 

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: 716
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: 391
Length of database: 391
Length adjustment: 31
Effective length of query: 360
Effective length of database: 360
Effective search space:   129600
Effective search space used:   129600
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 (21.7 bits)
S2: 50 (23.9 bits)

Align candidate PP_2137 PP_2137 (beta-ketoadipyl CoA thiolase, beta component)
to HMM TIGR02445 (fadA: acetyl-CoA C-acyltransferase FadA (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/TIGR02445.hmm
# target sequence database:        /tmp/gapView.28667.genome.faa
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -

Query:       TIGR02445  [M=385]
Accession:   TIGR02445
Description: fadA: acetyl-CoA C-acyltransferase FadA
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
    ------- ------ -----    ------- ------ -----   ---- --  --------                           -----------
   2.2e-235  766.7   8.1   2.4e-235  766.5   8.1    1.0  1  lcl|FitnessBrowser__Putida:PP_2137  PP_2137 beta-ketoadipyl CoA thio


Domain annotation for each sequence (and alignments):
>> lcl|FitnessBrowser__Putida:PP_2137  PP_2137 beta-ketoadipyl CoA thiolase, beta component
   #    score  bias  c-Evalue  i-Evalue hmmfrom  hmm to    alifrom  ali to    envfrom  env to     acc
 ---   ------ ----- --------- --------- ------- -------    ------- -------    ------- -------    ----
   1 !  766.5   8.1  2.4e-235  2.4e-235       1     385 []       7     391 .]       7     391 .] 1.00

  Alignments for each domain:
  == domain 1  score: 766.5 bits;  conditional E-value: 2.4e-235
                           TIGR02445   1 dvvivdalrtpmgrskggafrntraedlsahllkkllarnpkveaaevediywgcvqqtleqgfniarnaallae 75 
                                         dvvivd++rtpmgrskgg++rntraed+sahl++kll+rn kv++ eved++wgcv+qtleqg+niar+a+l++ 
  lcl|FitnessBrowser__Putida:PP_2137   7 DVVIVDFGRTPMGRSKGGMHRNTRAEDMSAHLISKLLERNGKVDPKEVEDVIWGCVNQTLEQGWNIARMASLMTP 81 
                                         79************************************************************************* PP

                           TIGR02445  76 vphevaavtvnrlcgssmqalhdaaraimtgdaevcliggvehmghvsmshgvdfhpglskhvakaagmmgltae 150
                                         +ph++aa+tv+rlcgssm+alh+aa+aimtg+++v+++ggvehmghvsm+hgvd++p+ls h+aka+gmmgltae
  lcl|FitnessBrowser__Putida:PP_2137  82 IPHTSAAQTVSRLCGSSMSALHTAAQAIMTGNGDVFVVGGVEHMGHVSMMHGVDPNPHLSLHAAKASGMMGLTAE 156
                                         *************************************************************************** PP

                           TIGR02445 151 mlgklhgisreqqdafaarsharahaatlegkfkneiiptegydadgvlkvldydevirpettvealaalrpafd 225
                                         mlgk+hgi+reqqd f++rsh++ah+at+egkfk+eiip++gyd++g+lkv+d+de+irpett+e+la+l+paf+
  lcl|FitnessBrowser__Putida:PP_2137 157 MLGKMHGITREQQDLFGLRSHQLAHKATVEGKFKDEIIPMQGYDENGFLKVFDFDETIRPETTLEGLASLKPAFN 231
                                         *************************************************************************** PP

                           TIGR02445 226 pkngtvtagtssalsdgasamlvmseeraqelgvkprarirsmavagvdpsimgygpvpatkkalkraglsisdi 300
                                         pk+gtvtagtss+++dgas+m+vms +ra +lg++p+a+irsmavagvdp+imgygpvp+t+kalkragl++ di
  lcl|FitnessBrowser__Putida:PP_2137 232 PKGGTVTAGTSSQITDGASCMIVMSGQRAMDLGIQPLAVIRSMAVAGVDPAIMGYGPVPSTQKALKRAGLTMADI 306
                                         *************************************************************************** PP

                           TIGR02445 301 dvlelneafaaqalpvlkdlglldkldekvnlnggaialghplgcsgaristtllnlmerkdakfglatmciglg 375
                                         d++elneafaaqalpvlkdl++ldk+dekvnl+ggaialghp+gcsgaris+tlln+m++++++ g+atmc+glg
  lcl|FitnessBrowser__Putida:PP_2137 307 DFIELNEAFAAQALPVLKDLKVLDKMDEKVNLHGGAIALGHPFGCSGARISGTLLNVMKQNGGTLGVATMCVGLG 381
                                         *************************************************************************** PP

                           TIGR02445 376 qgiatvferv 385
                                         qgi+tvferv
  lcl|FitnessBrowser__Putida:PP_2137 382 QGITTVFERV 391
                                         *********7 PP



Internal pipeline statistics summary:
-------------------------------------
Query model(s):                            1  (385 nodes)
Target sequences:                          1  (391 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: 10.53
//
[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