Alignments for a candidate for tdcB in Sinorhizobium meliloti 1021

GapMind for catabolism of small carbon sources

Alignments for a candidate for tdcB in Sinorhizobium meliloti 1021

Align threonine ammonia-lyase (EC 4.3.1.19) (characterized)
to candidate SMc00936 SMc00936 threonine dehydratase

Query= BRENDA::Q04513
         (436 letters)



>FitnessBrowser__Smeli:SMc00936
          Length = 415

 Score =  317 bits (811), Expect = 6e-91
 Identities = 172/399 (43%), Positives = 240/399 (60%), Gaps = 6/399 (1%)

Query: 25  DIQTAQARISSVIAPTPLQYCPRLSEETGAEIYLKREDLQDVRSYKIRGALNSGAQ-LTQ 83
           D++ A A +  +  PTPLQ    LS   GA ++LKREDL  VRSYKIRGA N   + L  
Sbjct: 4   DVEKAAAAMREIFPPTPLQLNEHLSARCGATVFLKREDLSPVRSYKIRGAFNFFRKSLGS 63

Query: 84  EQRDAGIVAASAGNHAQGVAYVCKSLGVQGRIYVPVQTPKQKRDRIMVHGGEFVSLVVTG 143
                  V ASAGNHAQG A+VC+  GV G +++PV TP+QK D+  + G EF+++ + G
Sbjct: 64  GAAGKTFVCASAGNHAQGFAFVCRHFGVPGVVFMPVTTPQQKIDKTRMFGAEFITIRLVG 123

Query: 144 NNFDEASAAAHEDAERTGATLIEPFDARNTVIGQGTVAAEILSQLTSMGKSADHVMVPVG 203
           + FD+   AA E  E  G  ++ PFD  + + GQ TVAAEI  QL + G  AD V++PVG
Sbjct: 124 DIFDQCYKAAREHVEAIGGVMVPPFDHDDIIEGQATVAAEIAEQLPA-GPVADLVVLPVG 182

Query: 204 GGGLLAGVVSYMADMAPRTAIVGIEPAGAASMQAALHNGGPITLETVDPFVDGAAVKRVG 263
           GGGL AGV  Y+ D       +  EP GA S + +L  GG +TL+ VD FVDGAAV R+G
Sbjct: 183 GGGLAAGVTGYLGDSLSADRFLFCEPEGAPSFRRSLELGGVVTLDQVDNFVDGAAVARIG 242

Query: 264 DLNYTIVEKNQGRVHMMSATEGAVCTEMLDLYQNEGIIAEPAGALSIAGLKEM--SFAPG 321
           DLN+  + +      +M   E A+C  + ++   EG++ EPAGAL+I  L+ +      G
Sbjct: 243 DLNFAALRRFSPE-QVMLLPENAICLTITEMLNVEGVVLEPAGALAITALEALGRDSLEG 301

Query: 322 SVVVCIISGGNNDVLRYAEIAERSLVHRGLKHYFLVNFPQKPGQLRHFLEDILGPDDDIT 381
            +VV ++SGGN D  R  ++ ER++ H GLK YF++   Q+PG LR FL  +LG +DDI 
Sbjct: 302 KIVVAVVSGGNFDFERLPDVKERAMRHAGLKKYFILRMAQRPGALRDFL-GLLGEEDDIA 360

Query: 382 LFEYLKRNNRETGTALVGIHLSEASGLDSLLERMEESAI 420
            FEYLK++ R  G+ L+GI    A     L +R + + +
Sbjct: 361 RFEYLKKSARNFGSVLIGIETKHAENFPVLKQRFDAAGL 399


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: 408
Number of extensions: 17
Number of successful extensions: 7
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: 415
Length adjustment: 32
Effective length of query: 404
Effective length of database: 383
Effective search space:   154732
Effective search space used:   154732
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: 51 (24.3 bits)

Align candidate SMc00936 SMc00936 (threonine dehydratase)
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.17502.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
    ------- ------ -----    ------- ------ -----   ---- --  --------                           -----------
   2.2e-178  579.2   0.0   2.4e-178  579.0   0.0    1.0  1  lcl|FitnessBrowser__Smeli:SMc00936  SMc00936 threonine dehydratase


Domain annotation for each sequence (and alignments):
>> lcl|FitnessBrowser__Smeli:SMc00936  SMc00936 threonine dehydratase
   #    score  bias  c-Evalue  i-Evalue hmmfrom  hmm to    alifrom  ali to    envfrom  env to     acc
 ---   ------ ----- --------- --------- ------- -------    ------- -------    ------- -------    ----
   1 !  579.0   0.0  2.4e-178  2.4e-178       1     410 []       3     415 .]       3     415 .] 0.99

  Alignments for each domain:
  == domain 1  score: 579.0 bits;  conditional E-value: 2.4e-178
                           TIGR02079   1 ediekakkrlkevvketPlqknerlsekykaeiylkredlqevrsyklrGaynkl.kqlsdeelekgvvcasaGn 74 
                                         +d+eka+  ++e++ +tPlq ne+ls++ +a+++lkredl+ vrsyk+rGa+n++ k+l +    k++vcasaGn
  lcl|FitnessBrowser__Smeli:SMc00936   3 QDVEKAAAAMREIFPPTPLQLNEHLSARCGATVFLKREDLSPVRSYKIRGAFNFFrKSLGSGAAGKTFVCASAGN 77 
                                         69****************************************************9899***************** PP

                           TIGR02079  75 haqGvayacrklgvkgtvfmPvttPkqkvdkvklfGgefievilvGdtfdeaaaaakkavekegktlipPfddkd 149
                                         haqG+a+ cr++gv g+vfmPvttP+qk+dk+++fG efi ++lvGd+fd+++ aa+++ve+ g  ++pPfd++d
  lcl|FitnessBrowser__Smeli:SMc00936  78 HAQGFAFVCRHFGVPGVVFMPVTTPQQKIDKTRMFGAEFITIRLVGDIFDQCYKAAREHVEAIGGVMVPPFDHDD 152
                                         *************************************************************************** PP

                           TIGR02079 150 iieGqgtvaveileqleee.kidlvlvpvGGGGlisGvtsylkekskktkiigvePeGapslkaslkagevvtld 223
                                         iieGq+tva+ei eql+ +  +dlv++pvGGGGl++Gvt+yl +  + ++++++ePeGaps++ sl+ g vvtld
  lcl|FitnessBrowser__Smeli:SMc00936 153 IIEGQATVAAEIAEQLPAGpVADLVVLPVGGGGLAAGVTGYLGDSLSADRFLFCEPEGAPSFRRSLELGGVVTLD 227
                                         *****************99899***************************************************** PP

                           TIGR02079 224 kidkfvdGaavkrvGdlnfkalkkvvd.evtlveegavcstildlynkegivaePaGalsiaaleels.eeikgk 296
                                         ++d+fvdGaav+r+Gdlnf+al+++   +v+l++e+a+c ti +++n eg+v+ePaGal+i+ale l  + ++gk
  lcl|FitnessBrowser__Smeli:SMc00936 228 QVDNFVDGAAVARIGDLNFAALRRFSPeQVMLLPENAICLTITEMLNVEGVVLEPAGALAITALEALGrDSLEGK 302
                                         ************************98769**************************************8799**** PP

                           TIGR02079 297 tvvcvvsGgnndierleeikersllyeGlkhyflvkfpqraGalreflndvlGPndditkfeyvkksnretGevl 371
                                          vv+vvsGgn+d+erl+++ker++++ Glk+yf+++++qr+Galr+fl  +lG +ddi++fey+kks+r++G+vl
  lcl|FitnessBrowser__Smeli:SMc00936 303 IVVAVVSGGNFDFERLPDVKERAMRHAGLKKYFILRMAQRPGALRDFLG-LLGEEDDIARFEYLKKSARNFGSVL 376
                                         ************************************************9.************************* PP

                           TIGR02079 372 iGielsdkedfeGllerlkaadieyeainenetlyellv 410
                                         iGie++++e+f  l +r++aa+++y++i+ene+l ++++
  lcl|FitnessBrowser__Smeli:SMc00936 377 IGIETKHAENFPVLKQRFDAAGLRYQDITENEMLANFVI 415
                                         **********************************99876 PP



Internal pipeline statistics summary:
-------------------------------------
Query model(s):                            1  (410 nodes)
Target sequences:                          1  (415 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: 11.88
//
[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