Alignments for a candidate for ackA in Alkalitalea saponilacus SC/BZ-SP2

GapMind for catabolism of small carbon sources

Alignments for a candidate for ackA in Alkalitalea saponilacus SC/BZ-SP2

Align acetate kinase monomer (EC 2.7.2.15) (characterized)
to candidate WP_079556774.1 CDL62_RS16315 acetate kinase

Query= metacyc::ACKCLOS-MONOMER
         (401 letters)



>NCBI__GCF_002201795.1:WP_079556774.1
          Length = 405

 Score =  457 bits (1177), Expect = e-133
 Identities = 226/403 (56%), Positives = 296/403 (73%), Gaps = 4/403 (0%)

Query: 1   MKNLVINCGSSSIKYQFIDMKDET--VLAKGLVERIGIKGSVITH-KVNGEKYVTETPME 57
           MK LV+NCGSSSIKYQ   M+ ET  V+AKG VE+IG+KGS + H K NGEK + E  + 
Sbjct: 1   MKILVLNCGSSSIKYQLFFMEGETWDVMAKGGVEKIGLKGSFLKHEKSNGEKVLLEGEIL 60

Query: 58  DHKKAIKLVLDALLNDEYGVIKNIDEISAVGHRIVHGGEKYANSVLIDEDVMKSIEDCVS 117
           DH+  I  +L  LL+D +G IK ++EI AVGHR+VHGGE + +SV I ++V+  +EDC+ 
Sbjct: 61  DHETGIDYILGILLSDLHGCIKEMEEIDAVGHRVVHGGETFNSSVFITDEVISKMEDCID 120

Query: 118 LAPLHNPPHIIGINACKELMPNVPMVAVFDTAFHQTIPDYAYMYAIPYEYYDKYKIRKYG 177
           LAPLHNPP++ GI A   L+PNVP V VFDTAFHQT+P +AYMYAIP+  Y KY +R+YG
Sbjct: 121 LAPLHNPPNLKGIRAISSLLPNVPQVGVFDTAFHQTMPKHAYMYAIPFSLYKKYGVRRYG 180

Query: 178 FHGTSHKYVSRTAAEFIGKKVEDLKMVVCHMGNGASITAVENGKSVDTSMGFTPLGGLAM 237
           FHGTSH+YVS+ A E +G   +  +++ CH+GNGAS+ A+ NG+SVDTSMGFTPL GL M
Sbjct: 181 FHGTSHRYVSKRACEALGVDYKKQRIISCHLGNGASVAAIMNGESVDTSMGFTPLEGLMM 240

Query: 238 GTRSGDMDPAVVTFLMDKLNINASEVNNLLNKKSGIEGLSGISSDMRDIKKGNYVDKDPK 297
           GTR GD+D    T++MDK  I     + L NK SG+ G++GISSDMR+I+      KDP 
Sbjct: 241 GTRCGDLDIGAATYIMDKELIGIQSASILFNKHSGMLGVTGISSDMREIESA-LEKKDPM 299

Query: 298 AMLAYSVFNYKIKQFIGSYTAVMNGLDCLVFTGGIGENSFENRREICKNMDYLGIKIDDK 357
           A L  S++NY+IK+F+GSY A M G+D L+FTGGIGEN    RRE+CK +D++G+ +DD+
Sbjct: 300 AELGMSMYNYRIKKFVGSYAAAMGGVDILIFTGGIGENGDLTRREVCKGLDFMGMVLDDE 359

Query: 358 KNDETMGIPMDISAEGSKVRVLVIPTNEELMIARDTKDIVGKL 400
           KN    G  MDIS + SK R++V+PTNEEL+IA DTK IV +L
Sbjct: 360 KNTGLRGKEMDISKKESKCRIMVVPTNEELVIAVDTKKIVTEL 402


Lambda     K      H
   0.317    0.136    0.390 

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: 514
Number of extensions: 18
Number of successful extensions: 4
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: 405
Length adjustment: 31
Effective length of query: 370
Effective length of database: 374
Effective search space:   138380
Effective search space used:   138380
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: 50 (23.9 bits)

Align candidate WP_079556774.1 CDL62_RS16315 (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.549629.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
    ------- ------ -----    ------- ------ -----   ---- --  --------                             -----------
     8e-154  498.2   0.5   9.1e-154  498.0   0.5    1.0  1  NCBI__GCF_002201795.1:WP_079556774.1  


Domain annotation for each sequence (and alignments):
>> NCBI__GCF_002201795.1:WP_079556774.1  
   #    score  bias  c-Evalue  i-Evalue hmmfrom  hmm to    alifrom  ali to    envfrom  env to     acc
 ---   ------ ----- --------- --------- ------- -------    ------- -------    ------- -------    ----
   1 !  498.0   0.5  9.1e-154  9.1e-154       4     404 ..       1     399 [.       1     400 [. 0.97

  Alignments for each domain:
  == domain 1  score: 498.0 bits;  conditional E-value: 9.1e-154
                             TIGR00016   4 kkilvlnaGssslkfalldaen.sekvllsglverikleeariktvedgekkeeeklaiedheeavkkllntl 75 
                                           +kilvln+Gsss+k++l+ +e+ +  v+++g ve+i l+++++k  +++++k   + +i dhe++++ +l  l
  NCBI__GCF_002201795.1:WP_079556774.1   1 MKILVLNCGSSSIKYQLFFMEGeTWDVMAKGGVEKIGLKGSFLKHEKSNGEKVLLEGEILDHETGIDYILGIL 73 
                                           69****************9995344569********************************************* PP

                             TIGR00016  76 kk.dkkilkelseialiGHRvvhGgekftesvivtdevlkkikdiselAPlHnpaelegieavlklkvllkak 147
                                            +  +  +ke++ei+++GHRvvhGge+f++sv +tdev++k++d ++lAPlHnp++l+gi+a++    l++++
  NCBI__GCF_002201795.1:WP_079556774.1  74 LSdLHGCIKEMEEIDAVGHRVVHGGETFNSSVFITDEVISKMEDCIDLAPLHNPPNLKGIRAIS--SLLPNVP 144
                                           9956889*********************************************************..8999*** PP

                             TIGR00016 148 nvavFDtafHqtipeeaylYalPyslykelgvRrYGfHGtshkyvtqraakllnkplddlnlivcHlGnGasv 220
                                           +v vFDtafHqt+p++ay+Ya+P+slyk++gvRrYGfHGtsh+yv++ra + l+   ++ ++i+cHlGnGasv
  NCBI__GCF_002201795.1:WP_079556774.1 145 QVGVFDTAFHQTMPKHAYMYAIPFSLYKKYGVRRYGFHGTSHRYVSKRACEALGVDYKKQRIISCHLGNGASV 217
                                           ************************************************************************* PP

                             TIGR00016 221 savknGksidtsmGltPLeGlvmGtRsGdiDpaiisylaetlglsldeieetlnkksGllgisglssDlRdil 293
                                           +a+ nG+s+dtsmG+tPLeGl+mGtR+Gd+D ++ +y+++++   ++    ++nk+sG+lg++g+ssD+R+i+
  NCBI__GCF_002201795.1:WP_079556774.1 218 AAIMNGESVDTSMGFTPLEGLMMGTRCGDLDIGAATYIMDKELIGIQSASILFNKHSGMLGVTGISSDMREIE 290
                                           ************************************************************************* PP

                             TIGR00016 294 dkkeegneeaklAlkvyvhRiakyigkyiaslegelDaivFtgGiGenaaevrelvleklevlGlkldlelnn 366
                                           ++ e+++  a+l +++y +Ri+k++g+y+a++ g +D ++FtgGiGen    r++v+++l+++G+ ld e+n+
  NCBI__GCF_002201795.1:WP_079556774.1 291 SALEKKDPMAELGMSMYNYRIKKFVGSYAAAMGG-VDILIFTGGIGENGDLTRREVCKGLDFMGMVLDDEKNT 362
                                           ********************************76.*************************************9 PP

                             TIGR00016 367 aarsgkesvisteeskvkvlviptneelviaeDalrla 404
                                              +gke  is++esk++++v+ptneelvia D+ +++
  NCBI__GCF_002201795.1:WP_079556774.1 363 -GLRGKEMDISKKESKCRIMVVPTNEELVIAVDTKKIV 399
                                           .999*****************************98875 PP



Internal pipeline statistics summary:
-------------------------------------
Query model(s):                            1  (405 nodes)
Target sequences:                          1  (405 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: 16.00
//
[ok]

This GapMind analysis is from Sep 24 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