Alignments for a candidate for tdcB in Phaeobacter inhibens BS107

GapMind for catabolism of small carbon sources

Alignments for a candidate for tdcB in Phaeobacter inhibens BS107

Align threonine ammonia-lyase (EC 4.3.1.19) (characterized)
to candidate GFF3437 PGA1_c34900 threonine dehydratase biosynthetic

Query= BRENDA::Q04513
         (436 letters)



>FitnessBrowser__Phaeo:GFF3437
          Length = 408

 Score =  307 bits (786), Expect = 4e-88
 Identities = 173/398 (43%), Positives = 246/398 (61%), Gaps = 16/398 (4%)

Query: 24  ADIQT----AQARISSVIAPTPLQYCPRLSEETGAEIYLKREDLQDVRSYKIRGALNSGA 79
           +D QT    A+  + ++   TPLQ    LSE  GAEIYLKREDL  VRSYKIRGA N+  
Sbjct: 2   SDFQTQARAAEQAMRAIFPATPLQRSALLSERFGAEIYLKREDLSPVRSYKIRGAFNA-- 59

Query: 80  QLTQEQRDAGIVAASAGNHAQGVAYVCKSLGVQGRIYVPVQTPKQKRDRIMVHGGEFVSL 139
            + ++   +  V ASAGNHAQGVAY+C+ LG +G I++PV TP+QK  +  + GG+ V +
Sbjct: 60  -MRKQLEQSLFVCASAGNHAQGVAYMCRELGKRGVIFMPVTTPQQKIQKTRMFGGDSVEI 118

Query: 140 VVTGNNFDEASAAAHEDAERTGATLIEPFDARNTVIGQGTVAAEILSQLTSMGKSADHVM 199
            + G+ FD+  AAA +     G   + PFD  + + GQ ++A EI +QL   G + DHV+
Sbjct: 119 HLVGDYFDDTLAAAQKWCADEGGHFLSPFDDDDVIEGQSSIAVEIEAQL---GAAPDHVI 175

Query: 200 VPVGGGGLLAGVVSYMADMAPRTAIVGIEPAGAASMQAALHNGGPITLETVDPFVDGAAV 259
           +PVGGGG+ +GV  +  D   R   +  EP+G A ++AAL  G P+ L+ VD FVDGAAV
Sbjct: 176 LPVGGGGMSSGVARWFGD---RVHCLFAEPSGGACLRAALAAGHPVALDHVDTFVDGAAV 232

Query: 260 KRVGDLNYTIVEKNQGRVHMMSATEGAVCTEMLDLYQNEGIIAEPAGALSIAGLKEM-SF 318
            RVG   + ++ K      ++S  E  +CT +L++   EG++ EPAGAL+I  L+++ S+
Sbjct: 233 GRVGARPFEVL-KQVPLPDVLSIAEDRICTTILEMLNVEGVVLEPAGALAIEALRDVRSW 291

Query: 319 APGSVVVCIISGGNNDVLRYAEIAERSLVHRGLKHYFLVNFPQKPGQLRHFLEDILGPDD 378
             G  VVC+ SGGN D  R  E+ ER+  + GLK YFL+  PQ+PG L+ FL  ILGP+D
Sbjct: 292 IRGKTVVCLTSGGNFDFERLPEVKERAQRYMGLKKYFLLRLPQRPGALKEFL-GILGPED 350

Query: 379 DITLFEYLKRNNRETGTALVGIHLSEASGLDSLLERME 416
           DI  FEY+K++ R  G+ L+GI          L  R++
Sbjct: 351 DIARFEYMKKSARNFGSVLIGIETKRPENFADLYARLD 388


Lambda     K      H
   0.316    0.133    0.373 

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: 432
Number of extensions: 24
Number of successful extensions: 6
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: 436
Length of database: 408
Length adjustment: 32
Effective length of query: 404
Effective length of database: 376
Effective search space:   151904
Effective search space used:   151904
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 GFF3437 PGA1_c34900 (threonine dehydratase biosynthetic)
to HMM TIGR02079 (ilvA: threonine dehydratase (EC 4.3.1.19))

# 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/TIGR02079.hmm
# target sequence database:        /tmp/gapView.14161.genome.faa
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -

Query:       TIGR02079  [M=410]
Accession:   TIGR02079
Description: THD1: threonine dehydratase
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
    ------- ------ -----    ------- ------ -----   ---- --  --------                          -----------
   1.8e-160  520.1   0.0   2.1e-160  519.9   0.0    1.0  1  lcl|FitnessBrowser__Phaeo:GFF3437  PGA1_c34900 threonine dehydratas


Domain annotation for each sequence (and alignments):
>> lcl|FitnessBrowser__Phaeo:GFF3437  PGA1_c34900 threonine dehydratase biosynthetic
   #    score  bias  c-Evalue  i-Evalue hmmfrom  hmm to    alifrom  ali to    envfrom  env to     acc
 ---   ------ ----- --------- --------- ------- -------    ------- -------    ------- -------    ----
   1 !  519.9   0.0  2.1e-160  2.1e-160       4     410 .]       9     408 .]       6     408 .] 0.97

  Alignments for each domain:
  == domain 1  score: 519.9 bits;  conditional E-value: 2.1e-160
                          TIGR02079   4 ekakkrlkevvketPlqknerlsekykaeiylkredlqevrsyklrGaynklkqlsdeelekgvvcasaGnhaqGv 79 
                                         +a++ ++ ++  tPlq+++ lse+++aeiylkredl+ vrsyk+rGa+n++++      +  +vcasaGnhaqGv
  lcl|FitnessBrowser__Phaeo:GFF3437   9 RAAEQAMRAIFPATPLQRSALLSERFGAEIYLKREDLSPVRSYKIRGAFNAMRKQ---LEQSLFVCASAGNHAQGV 81 
                                        579999*********************************************9543...345679************ PP

                          TIGR02079  80 ayacrklgvkgtvfmPvttPkqkvdkvklfGgefievilvGdtfdeaaaaakkavekegktlipPfddkdiieGqg 155
                                        ay cr+lg +g++fmPvttP+qk++k+++fGg+ +e+ lvGd fd++ aaa+k +++eg +++ Pfdd+d+ieGq+
  lcl|FitnessBrowser__Phaeo:GFF3437  82 AYMCRELGKRGVIFMPVTTPQQKIQKTRMFGGDSVEIHLVGDYFDDTLAAAQKWCADEGGHFLSPFDDDDVIEGQS 157
                                        **************************************************************************** PP

                          TIGR02079 156 tvaveileqleeekidlvlvpvGGGGlisGvtsylkekskktkiigvePeGapslkaslkagevvtldkidkfvdG 231
                                        ++avei  ql  + +d v++pvGGGG++sGv+ ++ +++   + ++ eP+G ++l+a+l+ag++v ld++d fvdG
  lcl|FitnessBrowser__Phaeo:GFF3437 158 SIAVEIEAQLGAA-PDHVILPVGGGGMSSGVARWFGDRV---HCLFAEPSGGACLRAALAAGHPVALDHVDTFVDG 229
                                        ***********97.*********************9887...589******************************* PP

                          TIGR02079 232 aavkrvGdlnfkalkkvvd.evtlveegavcstildlynkegivaePaGalsiaaleelseeikgktvvcvvsGgn 306
                                        aav rvG   f++lk+v   +v  + e+++c+til+++n eg+v+ePaGal+i al  +++ i+gktvvc+ sGgn
  lcl|FitnessBrowser__Phaeo:GFF3437 230 AAVGRVGARPFEVLKQVPLpDVLSIAEDRICTTILEMLNVEGVVLEPAGALAIEALRDVRSWIRGKTVVCLTSGGN 305
                                        *****************998******************************************************** PP

                          TIGR02079 307 ndierleeikersllyeGlkhyflvkfpqraGalreflndvlGPndditkfeyvkksnretGevliGielsdkedf 382
                                        +d+erl+e+ker+ +y Glk+yfl+++pqr+Gal+efl  +lGP+ddi++fey+kks+r++G+vliGie++  e+f
  lcl|FitnessBrowser__Phaeo:GFF3437 306 FDFERLPEVKERAQRYMGLKKYFLLRLPQRPGALKEFLG-ILGPEDDIARFEYMKKSARNFGSVLIGIETKRPENF 380
                                        **************************************9.************************************ PP

                          TIGR02079 383 eGllerlkaadieyeainenetlyellv 410
                                        + l +rl+aa+  y++i+ +etl ++++
  lcl|FitnessBrowser__Phaeo:GFF3437 381 ADLYARLDAAGFAYTDITSDETLAQFVI 408
                                        **********************998876 PP



Internal pipeline statistics summary:
-------------------------------------
Query model(s):                            1  (410 nodes)
Target sequences:                          1  (408 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: 0.02u 0.01s 00:00:00.03 Elapsed: 00:00:00.01
# Mc/sec: 8.60
//
[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:

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