GapMind for catabolism of small carbon sources

 

Aligments for a candidate for rbsK in Pseudomonas putida KT2440

Align Ribokinase (EC 2.7.1.15) (characterized)
to candidate PP_2458 PP_2458 ribokinase

Query= reanno::pseudo3_N2E3:AO353_20835
         (305 letters)



>lcl|FitnessBrowser__Putida:PP_2458 PP_2458 ribokinase
          Length = 302

 Score =  379 bits (974), Expect = e-110
 Identities = 204/300 (68%), Positives = 228/300 (76%), Gaps = 1/300 (0%)

Query: 1   MPAKVVVVGSLNMDLVTRAQRLPHAGETLHGESFATVSGGKGANQAVASARLGAQVSMIG 60
           M AKVVVVGSLNMDLV RAQRLP AGETL G+SF TV GGKGANQAVA ARLG  V+MIG
Sbjct: 1   MNAKVVVVGSLNMDLVVRAQRLPRAGETLPGDSFFTVPGGKGANQAVAVARLGGSVAMIG 60

Query: 61  CVGDDAYGEQLRAALLAEQIDCQALTSVEG-SSGVALIVVDDNSQNAIVIVAGANGQLTP 119
            VGDD YG QL  AL  E IDCQ +++    SSGVALI VD  SQN IVI+ GANG LTP
Sbjct: 61  NVGDDDYGRQLHRALYVEGIDCQGVSTCPAMSSGVALITVDAASQNCIVIIPGANGLLTP 120

Query: 120 GMVAGFDAVLAAADVIICQLEVPMHTVGYVLKRGRELGKTVILNPAPATSPLPADWYSSI 179
             V  FDA+L AA+VIICQLEVP  TV + L RG ELGK VILNPAPAT PLPADW++ I
Sbjct: 121 QSVRRFDALLQAAEVIICQLEVPASTVAWTLARGHELGKQVILNPAPATGPLPADWFAHI 180

Query: 180 DYLIPNESEASALSGLPVDSLESAELAASRLIAAGAGKVIITLGPQGSLFANGQSCEHFP 239
           DYL PNESEA AL+G+ V   +SA  A  RL+  GAGKVIITLG QG+L    Q  +H+P
Sbjct: 181 DYLTPNESEAEALTGVVVTDQDSARRAGERLLQLGAGKVIITLGAQGALLVTAQGHQHYP 240

Query: 240 APKVKSVDTTAAGDTFVGGFAAALAAGKSEVEAIRFGQVAAALSVTRAGAQPSIPSLSDV 299
           AP V+ +DTTAAGDTF+GGFAA L  G  E EAI FGQ AAALSVTRAGAQPSIP L+++
Sbjct: 241 APHVQPLDTTAAGDTFIGGFAAGLVRGLEEGEAIAFGQRAAALSVTRAGAQPSIPYLAEL 300


Lambda     K      H
   0.315    0.130    0.363 

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: 313
Number of extensions: 11
Number of successful extensions: 2
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: 305
Length of database: 302
Length adjustment: 27
Effective length of query: 278
Effective length of database: 275
Effective search space:    76450
Effective search space used:    76450
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: 48 (23.1 bits)

Align candidate PP_2458 PP_2458 (ribokinase)
to HMM TIGR02152 (rbsK: ribokinase (EC 2.7.1.15))

# 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/TIGR02152.hmm
# target sequence database:        /tmp/gapView.23393.genome.faa
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -

Query:       TIGR02152  [M=298]
Accession:   TIGR02152
Description: D_ribokin_bact: ribokinase
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
    ------- ------ -----    ------- ------ -----   ---- --  --------                           -----------
   5.3e-113  363.2   0.0   5.9e-113  363.1   0.0    1.0  1  lcl|FitnessBrowser__Putida:PP_2458  PP_2458 ribokinase


Domain annotation for each sequence (and alignments):
>> lcl|FitnessBrowser__Putida:PP_2458  PP_2458 ribokinase
   #    score  bias  c-Evalue  i-Evalue hmmfrom  hmm to    alifrom  ali to    envfrom  env to     acc
 ---   ------ ----- --------- --------- ------- -------    ------- -------    ------- -------    ----
   1 !  363.1   0.0  5.9e-113  5.9e-113       1     296 [.       5     300 ..       5     302 .] 0.99

  Alignments for each domain:
  == domain 1  score: 363.1 bits;  conditional E-value: 5.9e-113
                           TIGR02152   1 ivvvGSinvDlvlrvkrlpkpGetvkaeefkiaaGGKGANQAvaaarlgaevsmigkvGkDefgeellenlkkeg 75 
                                         +vvvGS+n+Dlv+r++rlp++Get+ +++f +++GGKGANQAva+arlg +v+mig+vG+D++g++l ++l  eg
  lcl|FitnessBrowser__Putida:PP_2458   5 VVVVGSLNMDLVVRAQRLPRAGETLPGDSFFTVPGGKGANQAVAVARLGGSVAMIGNVGDDDYGRQLHRALYVEG 79 
                                         79************************************************************************* PP

                           TIGR02152  76 idteyvkkvkktstGvAlilvdeegeNsIvvvaGaneeltpedvkaaeekikesdlvllQlEipletveealkia 150
                                         id++ v++   +s+GvAli+vd  ++N+Iv++ Gan  ltp+ v++  + +++++++++QlE+p +tv   l   
  lcl|FitnessBrowser__Putida:PP_2458  80 IDCQGVSTCPAMSSGVALITVDAASQNCIVIIPGANGLLTPQSVRRFDALLQAAEVIICQLEVPASTVAWTLARG 154
                                         *************************************************************************** PP

                           TIGR02152 151 kkagvkvllnPAPaekkldeellslvdiivpNetEaeiLtgievedledaekaaekllekgvkaviitlGskGal 225
                                         ++ g++v+lnPAPa+  l++++++++d+++pNe+Eae+Ltg+ v+d+++a++a e+ll+ g+ +viitlG++Gal
  lcl|FitnessBrowser__Putida:PP_2458 155 HELGKQVILNPAPATGPLPADWFAHIDYLTPNESEAEALTGVVVTDQDSARRAGERLLQLGAGKVIITLGAQGAL 229
                                         *************************************************************************** PP

                           TIGR02152 226 lvskdekklipalkvkavDttaAGDtFigalavaLaegksledavrfanaaaalsVtrkGaqssiPtkeev 296
                                         lv+++ +++ pa +v+ +DttaAGDtFig++a+ L +g +  +a+ f+++aaalsVtr+Gaq+siP+++e+
  lcl|FitnessBrowser__Putida:PP_2458 230 LVTAQGHQHYPAPHVQPLDTTAAGDTFIGGFAAGLVRGLEEGEAIAFGQRAAALSVTRAGAQPSIPYLAEL 300
                                         ********************************************************************997 PP



Internal pipeline statistics summary:
-------------------------------------
Query model(s):                            1  (298 nodes)
Target sequences:                          1  (302 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: 7.20
//
[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