Alignments for a candidate for gcvT in Azospirillum brasilense Sp245

GapMind for catabolism of small carbon sources

Alignments for a candidate for gcvT in Azospirillum brasilense Sp245

Align Aminomethyltransferase (EC 2.1.2.10) (characterized)
to candidate AZOBR_RS10470 AZOBR_RS10470 aminomethyltransferase

Query= reanno::pseudo6_N2E2:Pf6N2E2_5556
         (374 letters)



>FitnessBrowser__azobra:AZOBR_RS10470
          Length = 370

 Score =  429 bits (1103), Expect = e-125
 Identities = 222/373 (59%), Positives = 268/373 (71%), Gaps = 6/373 (1%)

Query: 2   STEQLLKTPLHALHLELGARMVPFAGYDMPVQYPLGVMKEHQHTRDQAGLFDVSHMGQIR 61
           ++E L  TPLH+LHLEL  +MVPFAGYDMPVQYPLG++KEHQHTR +AGLFDVSHMGQ+R
Sbjct: 4   ASESLKTTPLHSLHLELKGKMVPFAGYDMPVQYPLGILKEHQHTRAKAGLFDVSHMGQVR 63

Query: 62  LTGAGAAKALETLVPVDIIDLPVGMQRYAMFTNENGGILDDLMVANLGNDELFLVVNAAC 121
           LTG   A ALE+LVP DI  L  G  RY +F NE GGILDDLMV N G D LFLVVNAA 
Sbjct: 64  LTGEDPAAALESLVPGDIKGLARGRMRYTLFLNEQGGILDDLMVTNAG-DHLFLVVNAAR 122

Query: 122 KDQDLAHLRAHIGAQCSIEPLFEARALLALQGPAAVTVLARLAPDVAKMTFMQFQRVTLL 181
           KD D+AH+R  +  +  +E L +  AL+ALQGP A  VL R  P+ A M FM +   T  
Sbjct: 123 KDHDVAHMRERLKGKAEVE-LLDDLALMALQGPEAAAVLGRFIPEAATMKFMSYLPTTFD 181

Query: 182 GMDCYVSRSGYTGEDGFEISVPAAEAEKLARALLAEPEVAAIGLGARDSLRLEAGLCLYG 241
           G+   ++RSGYTGEDG+EIS   ++AE +ARALLAE EV AIGLGARDSLRLEAGLCLYG
Sbjct: 182 GIPVIITRSGYTGEDGYEISCDKSDAETIARALLAEDEVEAIGLGARDSLRLEAGLCLYG 241

Query: 242 HDMNTETTPIEASLLWAISKVRRADGARAGGFPGAETVFAQQQGGVKRKRVGLLPQERTP 301
           HD++  TTP+E+ L WA+SK RR +    GGFPG   +  Q   G  R+RVGL P+ R P
Sbjct: 242 HDIDETTTPVESGLEWALSKRRREE----GGFPGYAIIKDQLANGAPRRRVGLQPEGRQP 297

Query: 302 VREGAEIVNEAGEIIGTVCSGGFGPTLGGPLAMGYLDSAYVALDTPVWAIVRGKKVPLLV 361
            RE  ++ +  G+ IG V SGGFGPT   P+AMGY+D A+ A+ TPV  +VRGK +   V
Sbjct: 298 AREHTDVCDADGQKIGEVTSGGFGPTASAPVAMGYVDRAHAAVGTPVQLMVRGKPLAAKV 357

Query: 362 SKMPFVPQRYYRG 374
           + MPFVPQRYYRG
Sbjct: 358 AAMPFVPQRYYRG 370


Lambda     K      H
   0.321    0.138    0.406 

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: 496
Number of extensions: 32
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: 374
Length of database: 370
Length adjustment: 30
Effective length of query: 344
Effective length of database: 340
Effective search space:   116960
Effective search space used:   116960
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 (21.8 bits)
S2: 49 (23.5 bits)

Align candidate AZOBR_RS10470 AZOBR_RS10470 (aminomethyltransferase)
to HMM TIGR00528 (gcvT: glycine cleavage system T protein (EC 2.1.2.10))

# 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/TIGR00528.hmm
# target sequence database:        /tmp/gapView.1436.genome.faa
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -

Query:       TIGR00528  [M=362]
Accession:   TIGR00528
Description: gcvT: glycine cleavage system T protein
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
    ------- ------ -----    ------- ------ -----   ---- --  --------                                 -----------
   8.5e-112  359.6   0.0   9.8e-112  359.4   0.0    1.0  1  lcl|FitnessBrowser__azobra:AZOBR_RS10470  AZOBR_RS10470 aminomethyltransfe


Domain annotation for each sequence (and alignments):
>> lcl|FitnessBrowser__azobra:AZOBR_RS10470  AZOBR_RS10470 aminomethyltransferase
   #    score  bias  c-Evalue  i-Evalue hmmfrom  hmm to    alifrom  ali to    envfrom  env to     acc
 ---   ------ ----- --------- --------- ------- -------    ------- -------    ------- -------    ----
   1 !  359.4   0.0  9.8e-112  9.8e-112       1     361 [.       8     364 ..       8     365 .. 0.96

  Alignments for each domain:
  == domain 1  score: 359.4 bits;  conditional E-value: 9.8e-112
                                 TIGR00528   1 lkrtpLydlhtelggklvdfaGwelPvqyk.slieeheavrtkaGlfDvshmgkvelsGskslkfLqrl 68 
                                               lk tpL+ lh el gk+v+faG+ +Pvqy  ++ +eh+ +r kaGlfDvshmg+v+l+G++  ++L++l
  lcl|FitnessBrowser__azobra:AZOBR_RS10470   8 LKTTPLHSLHLELKGKMVPFAGYDMPVQYPlGILKEHQHTRAKAGLFDVSHMGQVRLTGEDPAAALESL 76 
                                               689**************************6489************************************ PP

                                 TIGR00528  69 lanDvdaLtkGkaqysvllnaqGGvvDDlivykegednrfllvvnaataekDlewlkehleeevtldtl 137
                                               ++ D++ L++G+ +y+ +ln qGG++DDl+v++ g+   + lvvnaa +++D ++++e+l+++++++ l
  lcl|FitnessBrowser__azobra:AZOBR_RS10470  77 VPGDIKGLARGRMRYTLFLNEQGGILDDLMVTNAGDH--LFLVVNAARKDHDVAHMRERLKGKAEVE-L 142
                                               ***********************************99..99********************998875.6 PP

                                 TIGR00528 138 skeisllalqGPkaktiledlldkaveglkefffvqeaelalkkaliartGytGedGfeiavanekave 206
                                                ++++l+alqGP+a+++l   + +a   +k + ++  + + +   +i+r+GytGedG+ei++ + +a  
  lcl|FitnessBrowser__azobra:AZOBR_RS10470 143 LDDLALMALQGPEAAAVLGRFIPEA-ATMKFMSYL-PTTFDGIPVIITRSGYTGEDGYEISCDKSDAET 209
                                               799****************999765.568988888.889999999************************ PP

                                 TIGR00528 207 lwkklveaygvkPiGLgarDtLrleagmaLyGqeldeeitPleaglgwvvkker.kksdfiGravleeq 274
                                               ++++l+++  v  iGLgarD+Lrleag++LyG+++de++tP+e+gl+w+++k r ++  f G+a +++q
  lcl|FitnessBrowser__azobra:AZOBR_RS10470 210 IARALLAEDEVEAIGLGARDSLRLEAGLCLYGHDIDETTTPVESGLEWALSKRRrEEGGFPGYAIIKDQ 278
                                               **************************************************998757889********** PP

                                 TIGR00528 275 kengtekklvGlemlekgiarnelkvlltngekevGivtsGtlsPtLgknialayvdkelekiGtklev 343
                                                +ng+ +++vGl+   ++ ar++ +v  ++g +++G vtsG + Pt    +a++yvd+  + +Gt ++ 
  lcl|FitnessBrowser__azobra:AZOBR_RS10470 279 LANGAPRRRVGLQPEGRQPAREHTDVCDADG-QKIGEVTSGGFGPTASAPVAMGYVDRAHAAVGTPVQL 346
                                               *******************************.9************************************ PP

                                 TIGR00528 344 evrnklvkikvvkklfvr 361
                                                vr+k + +kv+ ++fv+
  lcl|FitnessBrowser__azobra:AZOBR_RS10470 347 MVRGKPLAAKVAAMPFVP 364
                                               ****************97 PP



Internal pipeline statistics summary:
-------------------------------------
Query model(s):                            1  (362 nodes)
Target sequences:                          1  (370 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: 6.98
//
[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