Alignments for a candidate for ackA in Shewanella loihica PV-4

GapMind for catabolism of small carbon sources

Alignments for a candidate for ackA in Shewanella loihica PV-4

Align acetate kinase (EC 2.7.2.1) (characterized)
to candidate 5209945 Shew_2393 acetate kinase (RefSeq)

Query= BRENDA::E3W769
         (401 letters)



>FitnessBrowser__PV4:5209945
          Length = 398

 Score =  667 bits (1721), Expect = 0.0
 Identities = 328/398 (82%), Positives = 362/398 (90%), Gaps = 1/398 (0%)

Query: 1   MSDKLVLVLNCGSSSLKFAIIDAQSGDDKISGLAECFGLEDSRIKWKFNGGKNEAKLGAF 60
           MS+KLVLVLNCGSSSLKFAIIDA +GDD+ISGLAECFGLEDSRIKWK +G K E+KLGAF
Sbjct: 1   MSNKLVLVLNCGSSSLKFAIIDALTGDDQISGLAECFGLEDSRIKWKVDGNKFESKLGAF 60

Query: 61  TAHREAVEFFIVNNILAEHPELAAQIKAIGHRIVHGGEKFTRSVIITPEVIQGIEDCASL 120
           TAHREAVEF IV  IL ++P++AAQI+AIGHR+VHGGEKFT SV+I   VI GIEDCA+L
Sbjct: 61  TAHREAVEF-IVKEILGQYPDVAAQIQAIGHRVVHGGEKFTHSVVIDDSVIAGIEDCAAL 119

Query: 121 APLHNPAHLIGIRAAIASFPQLPQVTVFDTAFHQTMPEKAYIYALPYKLYREHSIRRYGM 180
           APLHNPAHLIGIRAA ASFP LPQV VFDTAFHQTMPE+A++YALPYKLYREH IRRYGM
Sbjct: 120 APLHNPAHLIGIRAAQASFPGLPQVAVFDTAFHQTMPERAFVYALPYKLYREHGIRRYGM 179

Query: 181 HGTSHFYVCREAAKVLGKDVKDINVICAHLGNGASVAAIKGGKSVDTSMGLTPLEGLVMG 240
           HGTSH +V REAAK LGK++ D NVICAHLGNGASV A+KGGKSVDTSMGLTPLEGLVMG
Sbjct: 180 HGTSHLFVSREAAKALGKELADTNVICAHLGNGASVTAVKGGKSVDTSMGLTPLEGLVMG 239

Query: 241 TRCGDLDPSIIFHLVKQLGYTLDEVNNLLNKQSGLLGISELTNDCRGIEEGYHDGHKGAT 300
           TRCGD+DPSII+HLV +LGYTLDEVNNL+NKQSGLLGISELTNDCRGIEEGY +GHKGAT
Sbjct: 240 TRCGDIDPSIIYHLVDRLGYTLDEVNNLMNKQSGLLGISELTNDCRGIEEGYAEGHKGAT 299

Query: 301 LALDIFCYRLAKYIASYTVPLGRLDAIIFTGGIGENSNLIREKVLNLLEIFNFKVDDILN 360
           LAL+IFCYRLAKYIASYTVPLGRLDA++FTGGIGENS+LIREKVLNLL IFNF+VD   N
Sbjct: 300 LALEIFCYRLAKYIASYTVPLGRLDALVFTGGIGENSDLIREKVLNLLAIFNFEVDPARN 359

Query: 361 KAARFGQQGVITQAGTPIAMVIPTNEEWVIAEDAIKLI 398
           +AARFG QG IT    P+AMVIPTNEEWVIAEDA+ L+
Sbjct: 360 QAARFGNQGQITTDNGPVAMVIPTNEEWVIAEDAVSLL 397


Lambda     K      H
   0.321    0.139    0.409 

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: 600
Number of extensions: 22
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: 398
Length adjustment: 31
Effective length of query: 370
Effective length of database: 367
Effective search space:   135790
Effective search space used:   135790
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 5209945 Shew_2393 (acetate kinase (RefSeq))
to HMM TIGR00016 (ackA: acetate kinase (EC 2.7.2.1))

# 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/TIGR00016.hmm
# target sequence database:        /tmp/gapView.10361.genome.faa
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -

Query:       TIGR00016  [M=405]
Accession:   TIGR00016
Description: ackA: acetate kinase
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
    ------- ------ -----    ------- ------ -----   ---- --  --------                        -----------
   9.8e-168  544.0   0.0   1.1e-167  543.8   0.0    1.0  1  lcl|FitnessBrowser__PV4:5209945  Shew_2393 acetate kinase (RefSeq


Domain annotation for each sequence (and alignments):
>> lcl|FitnessBrowser__PV4:5209945  Shew_2393 acetate kinase (RefSeq)
   #    score  bias  c-Evalue  i-Evalue hmmfrom  hmm to    alifrom  ali to    envfrom  env to     acc
 ---   ------ ----- --------- --------- ------- -------    ------- -------    ------- -------    ----
   1 !  543.8   0.0  1.1e-167  1.1e-167       2     404 ..       2     397 ..       1     398 [] 0.97

  Alignments for each domain:
  == domain 1  score: 543.8 bits;  conditional E-value: 1.1e-167
                        TIGR00016   2 kskkilvlnaGssslkfalldaensekvllsglverikleeariktvedgekkeeeklaiedheeavkkllntlkkdk 79 
                                      ++k++lvln+Gssslkfa++da +++   +sgl+e++ le++rik+++dg+k e++  a+++h+eav+++++++    
  lcl|FitnessBrowser__PV4:5209945   2 SNKLVLVLNCGSSSLKFAIIDALTGDDQ-ISGLAECFGLEDSRIKWKVDGNKFESKLGAFTAHREAVEFIVKEILG-- 76 
                                      6799*******************99999.9*********************************************7.. PP

                        TIGR00016  80 kilkelseialiGHRvvhGgekftesvivtdevlkkikdiselAPlHnpaelegieavlklkvllkaknvavFDtafH 157
                                      +  +  ++i++iGHRvvhGgekft+sv+++d+v+++i+d + lAPlHnpa+l+gi+a+++++  +  ++vavFDtafH
  lcl|FitnessBrowser__PV4:5209945  77 QYPDVAAQIQAIGHRVVHGGEKFTHSVVIDDSVIAGIEDCAALAPLHNPAHLIGIRAAQASF--PGLPQVAVFDTAFH 152
                                      5699*******************************************************555..5567********** PP

                        TIGR00016 158 qtipeeaylYalPyslykelgvRrYGfHGtshkyvtqraakllnkplddlnlivcHlGnGasvsavknGksidtsmGl 235
                                      qt+pe+a++YalPy+ly+e+g+RrYG+HGtsh +v+++aak l+k+l+d n+i +HlGnGasv+avk Gks+dtsmGl
  lcl|FitnessBrowser__PV4:5209945 153 QTMPERAFVYALPYKLYREHGIRRYGMHGTSHLFVSREAAKALGKELADTNVICAHLGNGASVTAVKGGKSVDTSMGL 230
                                      ****************************************************************************** PP

                        TIGR00016 236 tPLeGlvmGtRsGdiDpaiisylaetlglsldeieetlnkksGllgisglssDlRdildkkeegneeaklAlkvyvhR 313
                                      tPLeGlvmGtR+GdiDp+ii +l ++lg +lde+++++nk+sGllgis+l++D+R i++ ++eg++ a+lAl+++++R
  lcl|FitnessBrowser__PV4:5209945 231 TPLEGLVMGTRCGDIDPSIIYHLVDRLGYTLDEVNNLMNKQSGLLGISELTNDCRGIEEGYAEGHKGATLALEIFCYR 308
                                      ****************************************************************************** PP

                        TIGR00016 314 iakyigkyiaslegelDaivFtgGiGenaaevrelvleklevlGlkldlelnnaarsgkesvisteeskvkvlviptn 391
                                      +akyi++y+  l g+lDa+vFtgGiGen+  +re+vl+ l+++ +++d+++n+aar+g+++ i+t+++ v ++viptn
  lcl|FitnessBrowser__PV4:5209945 309 LAKYIASYTVPL-GRLDALVFTGGIGENSDLIREKVLNLLAIFNFEVDPARNQAARFGNQGQITTDNGPV-AMVIPTN 384
                                      ************.67***************************************************9998.589**** PP

                        TIGR00016 392 eelviaeDalrla 404
                                      ee+viaeDa+ l 
  lcl|FitnessBrowser__PV4:5209945 385 EEWVIAEDAVSLL 397
                                      *********9886 PP



Internal pipeline statistics summary:
-------------------------------------
Query model(s):                            1  (405 nodes)
Target sequences:                          1  (398 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: 0.02u 0.00s 00:00:00.02 Elapsed: 00:00:00.01
# Mc/sec: 9.14
//
[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, or view the source code.

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