GapMind for catabolism of small carbon sources

 

Aligments for a candidate for PRO3 in Azospirillum brasilense Sp245

Align Pyrroline-5-carboxylate reductase; P5C reductase; P5CR; PCA reductase; EC 1.5.1.2 (characterized)
to candidate AZOBR_RS06245 AZOBR_RS06245 pyrroline-5-carboxylate reductase

Query= SwissProt::P22008
         (273 letters)



>FitnessBrowser__azobra:AZOBR_RS06245
          Length = 275

 Score =  177 bits (448), Expect = 3e-49
 Identities = 109/264 (41%), Positives = 155/264 (58%), Gaps = 7/264 (2%)

Query: 10  GAGNMAASLIGGLRAQGVPAAQIRASDPGAEQRAKIAGEFAIDVVESNAEAVADA---DV 66
           G G M  +++ G    G+ A+ +   +P     + + G  A+ V+ S  +A+      DV
Sbjct: 15  GCGKMGGAMLDGWLKAGI-ASSVAVIEPSGLPES-LRGNPAV-VLASGVDALPAGFAPDV 71

Query: 67  VVLSVKPQAMKAVCQALAPALKPEQLIVSIAAGIPCASLEAWLGQPRPVVRCMPNTPALL 126
           VVL+VKPQ M +V  A    ++P  + +S+AAG   AS EA LG+   +VR MPNTPA +
Sbjct: 72  VVLAVKPQVMDSVLPAYRALVRPGTVFLSVAAGKTIASFEAALGEGAAIVRSMPNTPAAI 131

Query: 127 RQGASGLYANAQVSAAQCEQAGQLLSAVGIALWLDDEAQIDAVTAVSGSGPAYFFLLMQA 186
            +G +    N  V+ AQ      LL AVG   W++DE+ +D VTAVSGSGPAY FL+++A
Sbjct: 132 GRGMTVAVGNPVVTEAQKSLCDSLLRAVGDVAWVEDESLLDPVTAVSGSGPAYVFLMVEA 191

Query: 187 MTDAGEKLGLSRETASRLTLQTALGAAQMALSSEVEPAELRRRVTSPNGTTEAAIKSFQA 246
           M  AGE  GL  E A RL   T  GA ++   S    A+LR+ VTSPNGTT+AA+    A
Sbjct: 192 MAKAGEAAGLPAELAMRLARATVAGAGELLHQSPTAAADLRKAVTSPNGTTQAALDVLMA 251

Query: 247 -NGFEALVEQALNAASQRSAELAE 269
            +G + L ++A+ AA+ RS ELA+
Sbjct: 252 GDGMQPLFDRAVAAAANRSRELAK 275


Lambda     K      H
   0.315    0.127    0.348 

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: 205
Number of extensions: 8
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: 273
Length of database: 275
Length adjustment: 25
Effective length of query: 248
Effective length of database: 250
Effective search space:    62000
Effective search space used:    62000
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: 47 (22.7 bits)

Align candidate AZOBR_RS06245 AZOBR_RS06245 (pyrroline-5-carboxylate reductase)
to HMM TIGR00112 (proC: pyrroline-5-carboxylate reductase (EC 1.5.1.2))

# 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/TIGR00112.hmm
# target sequence database:        /tmp/gapView.18300.genome.faa
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -

Query:       TIGR00112  [M=263]
Accession:   TIGR00112
Description: proC: pyrroline-5-carboxylate reductase
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
    ------- ------ -----    ------- ------ -----   ---- --  --------                                 -----------
      1e-76  244.0   3.6    1.2e-76  243.8   3.6    1.0  1  lcl|FitnessBrowser__azobra:AZOBR_RS06245  AZOBR_RS06245 pyrroline-5-carbox


Domain annotation for each sequence (and alignments):
>> lcl|FitnessBrowser__azobra:AZOBR_RS06245  AZOBR_RS06245 pyrroline-5-carboxylate reductase
   #    score  bias  c-Evalue  i-Evalue hmmfrom  hmm to    alifrom  ali to    envfrom  env to     acc
 ---   ------ ----- --------- --------- ------- -------    ------- -------    ------- -------    ----
   1 !  243.8   3.6   1.2e-76   1.2e-76       3     263 .]      13     273 ..      11     273 .. 0.93

  Alignments for each domain:
  == domain 1  score: 243.8 bits;  conditional E-value: 1.2e-76
                                 TIGR00112   3 iiGaGnmgeallsgllkkgakakkeilviers.eeklaalakelgvevtsdaeeavkeadvvllavKPq 70 
                                               + G+G+mg a+l g+lk+g +  +++ vie+s  +++ +   ++  +   da  a  + dvv+lavKPq
  lcl|FitnessBrowser__azobra:AZOBR_RS06245  13 LAGCGKMGGAMLDGWLKAGIA--SSVAVIEPSgLPESLRGNPAVVLASGVDALPAGFAPDVVVLAVKPQ 79 
                                               67***************9775..799999999755555555555556666667899999********** PP

                                 TIGR00112  71 dleevlaelkseektkeklliSilAGvtiekleqlleaekrvvRvmPNtaakvgagvtaiaassevsee 139
                                               ++++vl  ++    + +++++S++AG ti+ +e +l++ +++vR mPNt+a++g+g+t+++ +  v+e+
  lcl|FitnessBrowser__azobra:AZOBR_RS06245  80 VMDSVLPAYRA-LVRPGTVFLSVAAGKTIASFEAALGEGAAIVRSMPNTPAAIGRGMTVAVGNPVVTEA 147
                                               *******9998.7789***************************************************** PP

                                 TIGR00112 140 qkelveellkavGkvveve.eklldavtalsGSgPAfvflliealadagvklGLpreeakelaaqtlkG 207
                                               qk+l ++ll+avG+v +ve e+lld vta+sGSgPA+vfl++ea+a+ag ++GLp+e+a++la++t++G
  lcl|FitnessBrowser__azobra:AZOBR_RS06245 148 QKSLCDSLLRAVGDVAWVEdESLLDPVTAVSGSGPAYVFLMVEAMAKAGEAAGLPAELAMRLARATVAG 216
                                               ********************************************************************* PP

                                 TIGR00112 208 aaklleesgehpalLkdkVtsPgGtTiaglavLeekg.vrsavieaveaavkrseeL 263
                                               a++ll++s   +a L+++VtsP+GtT+a+l vL++++ ++  +++av aa++rs+eL
  lcl|FitnessBrowser__azobra:AZOBR_RS06245 217 AGELLHQSPTAAADLRKAVTSPNGTTQAALDVLMAGDgMQPLFDRAVAAAANRSREL 273
                                               *********************************99866*****************98 PP



Internal pipeline statistics summary:
-------------------------------------
Query model(s):                            1  (263 nodes)
Target sequences:                          1  (275 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: 6.02
//
[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