GapMind for catabolism of small carbon sources

 

Aligments for a candidate for glk in Escherichia coli BW25113

Align glucokinase (EC 2.7.1.1; EC 2.7.1.2; EC 2.7.1.8) (characterized)
to candidate 16493 b2388 glucokinase (NCBI)

Query= ecocyc::GLUCOKIN-MONOMER
         (321 letters)



>FitnessBrowser__Keio:16493
          Length = 321

 Score =  648 bits (1672), Expect = 0.0
 Identities = 321/321 (100%), Positives = 321/321 (100%)

Query: 1   MTKYALVGDVGGTNARLALCDIASGEISQAKTYSGLDYPSLEAVIRVYLEEHKVEVKDGC 60
           MTKYALVGDVGGTNARLALCDIASGEISQAKTYSGLDYPSLEAVIRVYLEEHKVEVKDGC
Sbjct: 1   MTKYALVGDVGGTNARLALCDIASGEISQAKTYSGLDYPSLEAVIRVYLEEHKVEVKDGC 60

Query: 61  IAIACPITGDWVAMTNHTWAFSIAEMKKNLGFSHLEIINDFTAVSMAIPMLKKEHLIQFG 120
           IAIACPITGDWVAMTNHTWAFSIAEMKKNLGFSHLEIINDFTAVSMAIPMLKKEHLIQFG
Sbjct: 61  IAIACPITGDWVAMTNHTWAFSIAEMKKNLGFSHLEIINDFTAVSMAIPMLKKEHLIQFG 120

Query: 121 GAEPVEGKPIAVYGAGTGLGVAHLVHVDKRWVSLPGEGGHVDFAPNSEEEAIILEILRAE 180
           GAEPVEGKPIAVYGAGTGLGVAHLVHVDKRWVSLPGEGGHVDFAPNSEEEAIILEILRAE
Sbjct: 121 GAEPVEGKPIAVYGAGTGLGVAHLVHVDKRWVSLPGEGGHVDFAPNSEEEAIILEILRAE 180

Query: 181 IGHVSAERVLSGPGLVNLYRAIVKADNRLPENLKPKDITERALADSCTDCRRALSLFCVI 240
           IGHVSAERVLSGPGLVNLYRAIVKADNRLPENLKPKDITERALADSCTDCRRALSLFCVI
Sbjct: 181 IGHVSAERVLSGPGLVNLYRAIVKADNRLPENLKPKDITERALADSCTDCRRALSLFCVI 240

Query: 241 MGRFGGNLALNLGTFGGVFIAGGIVPRFLEFFKASGFRAAFEDKGRFKEYVHDIPVYLIV 300
           MGRFGGNLALNLGTFGGVFIAGGIVPRFLEFFKASGFRAAFEDKGRFKEYVHDIPVYLIV
Sbjct: 241 MGRFGGNLALNLGTFGGVFIAGGIVPRFLEFFKASGFRAAFEDKGRFKEYVHDIPVYLIV 300

Query: 301 HDNPGLLGSGAHLRQTLGHIL 321
           HDNPGLLGSGAHLRQTLGHIL
Sbjct: 301 HDNPGLLGSGAHLRQTLGHIL 321


Lambda     K      H
   0.322    0.141    0.426 

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: 533
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: 321
Length of database: 321
Length adjustment: 28
Effective length of query: 293
Effective length of database: 293
Effective search space:    85849
Effective search space used:    85849
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 (21.9 bits)
S2: 48 (23.1 bits)

Align candidate 16493 b2388 (glucokinase (NCBI))
to HMM TIGR00749 (glk: glucokinase (EC 2.7.1.2))

# 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/TIGR00749.hmm
# target sequence database:        /tmp/gapView.12389.genome.faa
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -

Query:       TIGR00749  [M=315]
Accession:   TIGR00749
Description: glk: glucokinase
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
    ------- ------ -----    ------- ------ -----   ---- --  --------                       -----------
   1.7e-160  519.4   0.0   1.9e-160  519.2   0.0    1.0  1  lcl|FitnessBrowser__Keio:16493  b2388 glucokinase (NCBI)


Domain annotation for each sequence (and alignments):
>> lcl|FitnessBrowser__Keio:16493  b2388 glucokinase (NCBI)
   #    score  bias  c-Evalue  i-Evalue hmmfrom  hmm to    alifrom  ali to    envfrom  env to     acc
 ---   ------ ----- --------- --------- ------- -------    ------- -------    ------- -------    ----
   1 !  519.2   0.0  1.9e-160  1.9e-160       1     315 []       6     310 ..       6     310 .. 1.00

  Alignments for each domain:
  == domain 1  score: 519.2 bits;  conditional E-value: 1.9e-160
                       TIGR00749   1 lvgdiGGtnarlalvevapgeieqvktyssedfpsleavvrvyleeakvelkdpikgcfaiatPiigdfvrltnldWal 79 
                                     lvgd+GGtnarlal+++a+gei+q+ktys++d+psleav+rvylee+kve+kd   gc+aia+Pi+gd+v++tn++Wa+
  lcl|FitnessBrowser__Keio:16493   6 LVGDVGGTNARLALCDIASGEISQAKTYSGLDYPSLEAVIRVYLEEHKVEVKD---GCIAIACPITGDWVAMTNHTWAF 81 
                                     89***************************************************...*********************** PP

                       TIGR00749  80 sieelkqelalaklelindfaavayailalkeedliqlggakveesaaiailGaGtGlGvatliqqsdgrykvlageGg 158
                                     si+e+k++l++++le+indf+av++ai++lk+e+liq+gga+++e+++ia++GaGtGlGva+l++ +d+r+++l+geGg
  lcl|FitnessBrowser__Keio:16493  82 SIAEMKKNLGFSHLEIINDFTAVSMAIPMLKKEHLIQFGGAEPVEGKPIAVYGAGTGLGVAHLVH-VDKRWVSLPGEGG 159
                                     *****************************************************************.************* PP

                       TIGR00749 159 hvdfaPrseleillleylrkkygrvsaervlsGsGlvliyealskrkgerevsklskeelkekdiseaalegsdvlarr 237
                                     hvdfaP+se+e+++le+lr+++g+vsaervlsG+Glv++y+a++k++     ++l+ e+lk+kdi+e+al++s++++rr
  lcl|FitnessBrowser__Keio:16493 160 HVDFAPNSEEEAIILEILRAEIGHVSAERVLSGPGLVNLYRAIVKAD-----NRLP-ENLKPKDITERALADSCTDCRR 232
                                     ***********************************************.....****.9********************* PP

                       TIGR00749 238 alelflsilGalagnlalklgarGGvyvaGGivPrfiellkkssfraafedkGrlkellasiPvqvvlkkkvGllGag 315
                                     al+lf++i+G+++gnlal+lg++GGv++aGGivPrf+e++k+s+fraafedkGr+ke++++iPv++++++++GllG+g
  lcl|FitnessBrowser__Keio:16493 233 ALSLFCVIMGRFGGNLALNLGTFGGVFIAGGIVPRFLEFFKASGFRAAFEDKGRFKEYVHDIPVYLIVHDNPGLLGSG 310
                                     ****************************************************************************97 PP



Internal pipeline statistics summary:
-------------------------------------
Query model(s):                            1  (315 nodes)
Target sequences:                          1  (321 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: 6.73
//
[ok]

This GapMind analysis is from Sep 17 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:

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:

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:

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