Alignments for a candidate for ackA in Klebsiella variicola At-22

GapMind for catabolism of small carbon sources

Alignments for a candidate for ackA in Klebsiella variicola At-22

Align acetate kinase (EC 2.7.2.1) (characterized)
to candidate WP_008803940.1 KVAR_RS06910 acetate kinase

Query= BRENDA::P63411
         (400 letters)



>NCBI__GCF_000025465.1:WP_008803940.1
          Length = 400

 Score =  773 bits (1997), Expect = 0.0
 Identities = 388/400 (97%), Positives = 393/400 (98%)

Query: 1   MSSKLVLVLNCGSSSLKFAIIDAVNGDEYLSGLAECFHLPEARIKWKMDGSKQEAALGAG 60
           MSSKLVLVLNCGSSSLKFAI+DAVNGDEYLSGLAECFHLPEARIKWK+DG KQEA LGAG
Sbjct: 1   MSSKLVLVLNCGSSSLKFAILDAVNGDEYLSGLAECFHLPEARIKWKIDGGKQEAELGAG 60

Query: 61  AAHSEALNFIVNTILAQKPELSAQLTAIGHRIVHGGEKYTSSVVIDESVIQGIKDSASFA 120
           AAHSEALNFIVNTILAQKPELSAQLTAIGHRIVHGGEKYTSSVVIDESVIQGIKD+ASFA
Sbjct: 61  AAHSEALNFIVNTILAQKPELSAQLTAIGHRIVHGGEKYTSSVVIDESVIQGIKDAASFA 120

Query: 121 PLHNPAHLIGIAEALKSFPQLKDKNVAVFDTAFHQTMPEESYLYALPYSLYKEHGVRRYG 180
           PLHNPAHLIGIAEALKSFP LKDKNVAVFDTAFHQTMPEESYLYALPYSLYKEHGVRRYG
Sbjct: 121 PLHNPAHLIGIAEALKSFPHLKDKNVAVFDTAFHQTMPEESYLYALPYSLYKEHGVRRYG 180

Query: 181 AHGTSHFYVTQEAAKMLNKPVEELNIITCHLGNGGSVSAIRNGKCVDTSMGLTPLEGLVM 240
           AHGTSHFYVTQEAAK+LNKPVEELNIITCHLGNGGSVSAIRNGKCVDTSMGLTPLEGLVM
Sbjct: 181 AHGTSHFYVTQEAAKILNKPVEELNIITCHLGNGGSVSAIRNGKCVDTSMGLTPLEGLVM 240

Query: 241 GTRSGDIDPAIIFHLHDTLGMSVDQINKMLTKESGLLGLTEVTSDCRYVEDNYATKEDAK 300
           GTRSGDIDPAIIFHLHDTLGMSVD INKMLTKESGLLGLTEVTSDCRYVEDNY  K DAK
Sbjct: 241 GTRSGDIDPAIIFHLHDTLGMSVDAINKMLTKESGLLGLTEVTSDCRYVEDNYQEKADAK 300

Query: 301 RAMDVYCHRLAKYIGSYTALMDGRLDAVVFTGGIGENAAMVRELSLGKLGVLGFEVDHER 360
           RAMDVYCHRLAKYIGSYTALMDGRLDAV+FTGGIGENAAMVRELSLGKLGVLGFEVDHER
Sbjct: 301 RAMDVYCHRLAKYIGSYTALMDGRLDAVIFTGGIGENAAMVRELSLGKLGVLGFEVDHER 360

Query: 361 NLAARFGKSGFINKEGTRPAVVIPTNEELVIAQDASRLTA 400
           NLAARFGKSGFINKEGTRPAVVIPTNEELVIAQDASRLTA
Sbjct: 361 NLAARFGKSGFINKEGTRPAVVIPTNEELVIAQDASRLTA 400


Lambda     K      H
   0.318    0.134    0.384 

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: 637
Number of extensions: 9
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: 400
Length adjustment: 31
Effective length of query: 369
Effective length of database: 369
Effective search space:   136161
Effective search space used:   136161
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 WP_008803940.1 KVAR_RS06910 (acetate kinase)
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.3334729.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
    ------- ------ -----    ------- ------ -----   ---- --  --------                             -----------
   7.3e-190  616.8   0.0   8.2e-190  616.7   0.0    1.0  1  NCBI__GCF_000025465.1:WP_008803940.1  


Domain annotation for each sequence (and alignments):
>> NCBI__GCF_000025465.1:WP_008803940.1  
   #    score  bias  c-Evalue  i-Evalue hmmfrom  hmm to    alifrom  ali to    envfrom  env to     acc
 ---   ------ ----- --------- --------- ------- -------    ------- -------    ------- -------    ----
   1 !  616.7   0.0  8.2e-190  8.2e-190       1     404 [.       1     399 [.       1     400 [] 0.98

  Alignments for each domain:
  == domain 1  score: 616.7 bits;  conditional E-value: 8.2e-190
                             TIGR00016   1 mkskkilvlnaGssslkfalldaensekvllsglverikleeariktvedgekkeeeklaiedheeavkklln 73 
                                           m+sk++lvln+Gssslkfa+lda n++++ lsgl+e+++l+earik++ dg+k+e+e  a ++h+ea+++++n
  NCBI__GCF_000025465.1:WP_008803940.1   1 MSSKLVLVLNCGSSSLKFAILDAVNGDEY-LSGLAECFHLPEARIKWKIDGGKQEAELGAGAAHSEALNFIVN 72 
                                           57899************************.9****************************************** PP

                             TIGR00016  74 tlkkdkkilkelseialiGHRvvhGgekftesvivtdevlkkikdiselAPlHnpaelegieavlklkvllka 146
                                           t+ ++k   ++++++++iGHR+vhGgek+t+sv+++++v+++ikd++++APlHnpa+l+gi ++lk++++lk+
  NCBI__GCF_000025465.1:WP_008803940.1  73 TILAQK--PELSAQLTAIGHRIVHGGEKYTSSVVIDESVIQGIKDAASFAPLHNPAHLIGIAEALKSFPHLKD 143
                                           ***866..99*************************************************************** PP

                             TIGR00016 147 knvavFDtafHqtipeeaylYalPyslykelgvRrYGfHGtshkyvtqraakllnkplddlnlivcHlGnGas 219
                                           knvavFDtafHqt+pee+ylYalPyslyke+gvRrYG+HGtsh yvtq+aak+lnkp+++ln+i+cHlGnG+s
  NCBI__GCF_000025465.1:WP_008803940.1 144 KNVAVFDTAFHQTMPEESYLYALPYSLYKEHGVRRYGAHGTSHFYVTQEAAKILNKPVEELNIITCHLGNGGS 216
                                           ************************************************************************* PP

                             TIGR00016 220 vsavknGksidtsmGltPLeGlvmGtRsGdiDpaiisylaetlglsldeieetlnkksGllgisglssDlRdi 292
                                           vsa++nGk++dtsmGltPLeGlvmGtRsGdiDpaii++l++tlg+s+d+i+++l+k+sGllg+++++sD+R++
  NCBI__GCF_000025465.1:WP_008803940.1 217 VSAIRNGKCVDTSMGLTPLEGLVMGTRSGDIDPAIIFHLHDTLGMSVDAINKMLTKESGLLGLTEVTSDCRYV 289
                                           ************************************************************************* PP

                             TIGR00016 293 ldkkeegneeaklAlkvyvhRiakyigkyiaslegelDaivFtgGiGenaaevrelvleklevlGlkldleln 365
                                           +d++ +++ +ak+A++vy+hR+akyig+y+a ++g+lDa++FtgGiGenaa+vrel+l kl vlG+++d+e+n
  NCBI__GCF_000025465.1:WP_008803940.1 290 EDNY-QEKADAKRAMDVYCHRLAKYIGSYTALMDGRLDAVIFTGGIGENAAMVRELSLGKLGVLGFEVDHERN 361
                                           ****.6667**************************************************************** PP

                             TIGR00016 366 naarsgkesvisteeskvkvlviptneelviaeDalrla 404
                                            aar+gk+++i+ +e++  ++viptneelvia+Da rl+
  NCBI__GCF_000025465.1:WP_008803940.1 362 LAARFGKSGFIN-KEGTRPAVVIPTNEELVIAQDASRLT 399
                                           ***********9.89999*******************97 PP



Internal pipeline statistics summary:
-------------------------------------
Query model(s):                            1  (405 nodes)
Target sequences:                          1  (400 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: 00:00:00.00
# Mc/sec: 27.74
//
[ok]

This GapMind analysis is from Apr 09 2024. 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 2024 update 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