Alignments for a candidate for ackA in Rubrivirga marina SAORIC-28

GapMind for catabolism of small carbon sources

Alignments for a candidate for ackA in Rubrivirga marina SAORIC-28

Align acetate kinase (EC 2.7.2.1) (characterized)
to candidate WP_095512017.1 BSZ37_RS18750 acetate kinase

Query= BRENDA::Q9WYB1
         (403 letters)



>NCBI__GCF_002283365.1:WP_095512017.1
          Length = 405

 Score =  399 bits (1025), Expect = e-116
 Identities = 211/398 (53%), Positives = 273/398 (68%), Gaps = 4/398 (1%)

Query: 1   MRVLVINSGSSSIKYQLIEMEGEKVLCKGIAERIGIEGSRLVHRVGDEK-HVIERELPDH 59
           M VLV+N+GSSS+K  LI+    + L  G  ERIG   S    RVGD K   I  + PDH
Sbjct: 1   MTVLVLNAGSSSLKVDLIDAAAGQTLAAGQVERIGAVSSLASFRVGDAKPERISLKAPDH 60

Query: 60  EEALKLILNTLVDEKLGVIKDLKEIDAVGHRVVHGGERFKESVLVDEEVLKAIEEVSPLA 119
             AL  +L T+  E  G    L +++AVGHRVVHGGERF ES L+D EV+ AI +   LA
Sbjct: 61  AAALSHLLETM-READGEEDRLPDVEAVGHRVVHGGERFAESALIDGEVVDAIRDAFDLA 119

Query: 120 PLHNPANLMGIKAAMKLLPGVPNVAVFDTAFHQTIPQKAYLYAIPYEYYEKYKIRRYGFH 179
           PLHNPANL GI+AA K  P VP VAVFDTAFHQTIP +AYLYA+P   Y ++KIRRYGFH
Sbjct: 120 PLHNPANLQGIRAAQKAFPDVPQVAVFDTAFHQTIPAEAYLYALPNRLYRRHKIRRYGFH 179

Query: 180 GTSHRYVSKRAAEILGKKLEELKIITCHIGNGASVAAVKYGKCVDTSMGFTPLEGLVMGT 239
           GTSH YVS+R  E+ G   +  +++T H+GNG S+AA++ GK VDTSMG TPLEGLVMGT
Sbjct: 180 GTSHYYVSRRLYELAGLDQQNSRVVTIHLGNGCSMAAIRDGKSVDTSMGMTPLEGLVMGT 239

Query: 240 RSGDLDPAIPFFIMEKEGISPQEMYDILNKKSGVYGLSKGFSSDMRDIEEAALKGDEWCK 299
           RSGDLDP+I F +MEKE +   E++ +LN+ SG+ GLS G+++DMRD+   A  GD  C+
Sbjct: 240 RSGDLDPSIVFEVMEKEDMPLAEVHTLLNRYSGLLGLS-GYAADMRDLLAEAADGDVRCQ 298

Query: 300 LVLEIYDYRIAKYIGAYAAAMNGVDAIVFTAGVGENSPITREDVCSYLEFLGVKLDKQKN 359
             ++++ YR+  Y+G Y A + G+DA+ FTAG+G  +   R  +   L  LG+ LD   N
Sbjct: 299 QAIDVFCYRVKSYLGRYLAVLGGLDAVAFTAGIGTFAAPVRAQILYGLAGLGMTLDAGAN 358

Query: 360 EETIRGKEGIISTPDSRVKVLVVPTNEELMIARDTKEI 397
            E   G E +I+TPDS V V VVPTNEEL+IA+DT+++
Sbjct: 359 -EAANGTEAVITTPDSAVPVWVVPTNEELVIAQDTQKL 395


Lambda     K      H
   0.318    0.138    0.391 

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: 411
Number of extensions: 17
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: 403
Length of database: 405
Length adjustment: 31
Effective length of query: 372
Effective length of database: 374
Effective search space:   139128
Effective search space used:   139128
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_095512017.1 BSZ37_RS18750 (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.564446.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
    ------- ------ -----    ------- ------ -----   ---- --  --------                             -----------
   1.5e-150  487.4   0.0   1.7e-150  487.2   0.0    1.0  1  NCBI__GCF_002283365.1:WP_095512017.1  


Domain annotation for each sequence (and alignments):
>> NCBI__GCF_002283365.1:WP_095512017.1  
   #    score  bias  c-Evalue  i-Evalue hmmfrom  hmm to    alifrom  ali to    envfrom  env to     acc
 ---   ------ ----- --------- --------- ------- -------    ------- -------    ------- -------    ----
   1 !  487.2   0.0  1.7e-150  1.7e-150       5     403 ..       2     395 ..       1     397 [. 0.97

  Alignments for each domain:
  == domain 1  score: 487.2 bits;  conditional E-value: 1.7e-150
                             TIGR00016   5 kilvlnaGssslkfalldaensekvllsglverikleeariktvedgekkeeeklaiedheeavkkllntlkk 77 
                                            +lvlnaGssslk  l+da+   ++l+ g veri    +  +  + + k e++ l+ +dh++a+++ll+t+ +
  NCBI__GCF_002283365.1:WP_095512017.1   2 TVLVLNAGSSSLKVDLIDAAA-GQTLAAGQVERIGAVSSLASFRVGDAKPERISLKAPDHAAALSHLLETMRE 73 
                                           79******************6.5556*********999977777777789999*******************9 PP

                             TIGR00016  78 dkkilkelseialiGHRvvhGgekftesvivtdevlkkikdiselAPlHnpaelegieavlklkvllkaknva 150
                                            +   + l +++++GHRvvhGge+f+es++++ ev+++i+d+ +lAPlHnpa+l+gi+a++  k  +++++va
  NCBI__GCF_002283365.1:WP_095512017.1  74 ADGEEDRLPDVEAVGHRVVHGGERFAESALIDGEVVDAIRDAFDLAPLHNPANLQGIRAAQ--KAFPDVPQVA 144
                                           999999*******************************************************..7788999*** PP

                             TIGR00016 151 vFDtafHqtipeeaylYalPyslykelgvRrYGfHGtshkyvtqraakllnkplddlnlivcHlGnGasvsav 223
                                           vFDtafHqtip eaylYalP +ly+++++RrYGfHGtsh+yv++r+ +l +   ++++++++HlGnG s++a+
  NCBI__GCF_002283365.1:WP_095512017.1 145 VFDTAFHQTIPAEAYLYALPNRLYRRHKIRRYGFHGTSHYYVSRRLYELAGLDQQNSRVVTIHLGNGCSMAAI 217
                                           ************************************************************************* PP

                             TIGR00016 224 knGksidtsmGltPLeGlvmGtRsGdiDpaiisylaetlglsldeieetlnkksGllgisglssDlRdildkk 296
                                           ++Gks+dtsmG+tPLeGlvmGtRsGd+Dp+i++ ++e++++ l+e++++ln+ sGllg+sg ++D+Rd+l++ 
  NCBI__GCF_002283365.1:WP_095512017.1 218 RDGKSVDTSMGMTPLEGLVMGTRSGDLDPSIVFEVMEKEDMPLAEVHTLLNRYSGLLGLSGYAADMRDLLAEA 290
                                           ************************************************************************* PP

                             TIGR00016 297 eegneeaklAlkvyvhRiakyigkyiaslegelDaivFtgGiGenaaevrelvleklevlGlkldlelnnaar 369
                                           ++g+ +++ A++v+++R+++y+g+y+a l g lDa+ Ft+GiG  aa vr+++l +l+ lG+ ld   n+ a 
  NCBI__GCF_002283365.1:WP_095512017.1 291 ADGDVRCQQAIDVFCYRVKSYLGRYLAVLGG-LDAVAFTAGIGTFAAPVRAQILYGLAGLGMTLDAGANE-AA 361
                                           *****************************76.**************************************.88 PP

                             TIGR00016 370 sgkesvisteeskvkvlviptneelviaeDalrl 403
                                           +g+e+vi+t++s+v v v+ptneelvia+D+ +l
  NCBI__GCF_002283365.1:WP_095512017.1 362 NGTEAVITTPDSAVPVWVVPTNEELVIAQDTQKL 395
                                           899****************************998 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: 0.00u 0.01s 00:00:00.01 Elapsed: 00:00:00.00
# Mc/sec: 16.70
//
[ok]

This GapMind analysis is from Sep 24 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