Alignments for a candidate for astA in Paraburkholderia bryophila 376MFSha3.1

GapMind for catabolism of small carbon sources

Alignments for a candidate for astA in Paraburkholderia bryophila 376MFSha3.1

Align Arginine N-succinyltransferase (EC 2.3.1.109) (characterized)
to candidate H281DRAFT_06479 H281DRAFT_06479 arginine succinyltransferase

Query= reanno::Marino:GFF3098
         (339 letters)



>FitnessBrowser__Burk376:H281DRAFT_06479
          Length = 352

 Score =  219 bits (557), Expect = 1e-61
 Identities = 140/344 (40%), Positives = 191/344 (55%), Gaps = 10/344 (2%)

Query: 1   MWLVRPAEPDDLDQILAIAGTQCARLSSTLPKQGDALAYKIEQSLASFAGRISAEDDPPR 60
           M  VRP    DLD +  +A T    L S LP    AL  ++  S  SF   +    +   
Sbjct: 1   MLFVRPGRLADLDALEHMARTAQPVLHS-LPHDRRALEARVALSEDSFRAEVDFPGEE-F 58

Query: 61  FLFVLEDTETGDIAGTAGIDAHAGNGQPFYSYRRDALIHASHELGVSRRVEVLYPSHSLT 120
           +LFVLED+E+G + GTA I A AG   PFY++R DALIHAS EL V+R++  L  SH LT
Sbjct: 59  YLFVLEDSESGKLMGTASIVAAAGYSDPFYAFRNDALIHASRELHVNRKIHALTMSHELT 118

Query: 121 DVSLLCSFSIRPELQGTDAFELLSRARILFIADHREWFTQRMAVEIQGVQLEDGSVPFWD 180
             S L  + I P L+G  A  L+SRAR+++IA +R+ FT  +   + GV  E+G  PFW+
Sbjct: 119 GKSRLAGYYIDPSLRGDAAAHLMSRARMMYIAANRKRFTPEVFSLLLGVTDENGVSPFWE 178

Query: 181 SLGRHFFDMDFETADQYSGQLSKTFIAELMPPNPIYVTLLSEAAQKAMGQPHQITVPNFE 240
           ++GR FF  +F   +  SG  S+TFIAE+MP  PIYV LL EAAQ+ +G+P    +  +E
Sbjct: 179 AVGRKFFGRNFADIEIESGGRSRTFIAEVMPTYPIYVPLLPEAAQRVLGEPDSKALLAYE 238

Query: 241 LLQREGFQPGNYLDIFDAGPVLEARTDSLKTLVTSHPKELH----GTNEDTGETCLIA-A 295
           +   EGF+   ++DIFDAGPVL A+ D    +  +  +  H    G N   G T LIA  
Sbjct: 239 IHLEEGFETDRFIDIFDAGPVLTAQVDRSACVTLNETRVAHEAAAGAN---GSTYLIAHN 295

Query: 296 GEGEQFRCTLTPVAESLDDKLKVPVSTWNTLNRTAGDRVRIAPL 339
           G   QFRC L  +  + ++   +       L    GD VR  PL
Sbjct: 296 GADGQFRCVLGELPTARNEGAPLAQPARAALGVQDGDTVRCVPL 339


Lambda     K      H
   0.319    0.135    0.403 

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: 344
Number of extensions: 16
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: 339
Length of database: 352
Length adjustment: 29
Effective length of query: 310
Effective length of database: 323
Effective search space:   100130
Effective search space used:   100130
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 (21.7 bits)
S2: 49 (23.5 bits)

Align candidate H281DRAFT_06479 H281DRAFT_06479 (arginine succinyltransferase)
to HMM TIGR03245 (aruF: arginine/ornithine succinyltransferase, alpha subunit (EC 2.3.1.109))

# 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/TIGR03245.hmm
# target sequence database:        /tmp/gapView.19149.genome.faa
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -

Query:       TIGR03245  [M=336]
Accession:   TIGR03245
Description: arg_AOST_alph: arginine/ornithine succinyltransferase, alpha subunit
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
    ------- ------ -----    ------- ------ -----   ---- --  --------                                    -----------
   4.2e-155  502.4   0.0   4.8e-155  502.2   0.0    1.0  1  lcl|FitnessBrowser__Burk376:H281DRAFT_06479  H281DRAFT_06479 arginine succiny


Domain annotation for each sequence (and alignments):
>> lcl|FitnessBrowser__Burk376:H281DRAFT_06479  H281DRAFT_06479 arginine succinyltransferase
   #    score  bias  c-Evalue  i-Evalue hmmfrom  hmm to    alifrom  ali to    envfrom  env to     acc
 ---   ------ ----- --------- --------- ------- -------    ------- -------    ------- -------    ----
   1 !  502.2   0.0  4.8e-155  4.8e-155       1     336 []       3     339 ..       3     339 .. 0.98

  Alignments for each domain:
  == domain 1  score: 502.2 bits;  conditional E-value: 4.8e-155
                                    TIGR03245   1 vvrParladldaierlaresaigvtslPadrekleekiaqsessfaaevsfsgeesylfvledset 66 
                                                  +vrP+rladlda+e++ar+++++++slP+dr +le+++a+se+sf+aev+f+gee+ylfvledse+
  lcl|FitnessBrowser__Burk376:H281DRAFT_06479   3 FVRPGRLADLDALEHMARTAQPVLHSLPHDRRALEARVALSEDSFRAEVDFPGEEFYLFVLEDSES 68 
                                                  69**************************************************************** PP

                                    TIGR03245  67 gkllGtasivasaGyaePfysyrndtlvhasrelkvnnkihvlslsheltGksllasfyvdpelre 132
                                                  gkl+Gtasiva+aGy++Pfy++rnd+l+hasrel+vn+kih+l++sheltGks+la++y+dp+lr+
  lcl|FitnessBrowser__Burk376:H281DRAFT_06479  69 GKLMGTASIVAAAGYSDPFYAFRNDALIHASRELHVNRKIHALTMSHELTGKSRLAGYYIDPSLRG 134
                                                  ****************************************************************** PP

                                    TIGR03245 133 aeaaellsrarllfiaaererfasrviaellGvsdeaGesPfWdaiGrkffdldfaaverasglks 198
                                                  ++aa+l+srar+++iaa+r+rf+++v+++llGv+de+G sPfW+a+Grkff+++fa++e++sg +s
  lcl|FitnessBrowser__Burk376:H281DRAFT_06479 135 DAAAHLMSRARMMYIAANRKRFTPEVFSLLLGVTDENGVSPFWEAVGRKFFGRNFADIEIESGGRS 200
                                                  ****************************************************************** PP

                                    TIGR03245 199 ktfiaelmPsyPiyvpllpdeaqealgqvheraelafdlllreGfeadryidifdgGpvleaeldr 264
                                                  +tfiae+mP+yPiyvpllp++aq++lg+++++a la++++l+eGfe+dr+idifd+Gpvl+a++dr
  lcl|FitnessBrowser__Burk376:H281DRAFT_06479 201 RTFIAEVMPTYPIYVPLLPEAAQRVLGEPDSKALLAYEIHLEEGFETDRFIDIFDAGPVLTAQVDR 266
                                                  ****************************************************************** PP

                                    TIGR03245 265 lktvkksrekpvkieeaatggstylvs.nglledfravladlavvdGkalrlkadaaealgvseGd 329
                                                   ++v+ ++++  ++++a  +gstyl++ ng   +fr+vl +l ++  +   l + a++algv +Gd
  lcl|FitnessBrowser__Burk376:H281DRAFT_06479 267 SACVTLNETRVAHEAAAGANGSTYLIAhNGADGQFRCVLGELPTARNEGAPLAQPARAALGVQDGD 332
                                                  *******99999999999999****984677779********9999999999************** PP

                                    TIGR03245 330 avrlval 336
                                                  +vr+v+l
  lcl|FitnessBrowser__Burk376:H281DRAFT_06479 333 TVRCVPL 339
                                                  *****97 PP



Internal pipeline statistics summary:
-------------------------------------
Query model(s):                            1  (336 nodes)
Target sequences:                          1  (352 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: 6.90
//
[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
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