Alignments for a candidate for gloA in Pseudomonas fluorescens FW300-N2E3

GapMind for catabolism of small carbon sources

Alignments for a candidate for gloA in Pseudomonas fluorescens FW300-N2E3

Align lactoylglutathione lyase (EC 4.4.1.5) (characterized)
to candidate AO353_26955 AO353_26955 lactoylglutathione lyase

Query= BRENDA::Q88GF8
         (175 letters)



>FitnessBrowser__pseudo3_N2E3:AO353_26955
          Length = 173

 Score =  302 bits (774), Expect = 2e-87
 Identities = 143/173 (82%), Positives = 150/173 (86%)

Query: 1   MSLHDLQTLPGVTAQPDAATAQFVFNHTMLRVKDIEKSLDFYTRVLGFRLVDKRDFPEAA 60
           MSLH+L T PGVTAQPD AT QFVFNHTMLRVKDI KSLDFYTR+LGF LV+KRDFPEA 
Sbjct: 1   MSLHELNTFPGVTAQPDTATQQFVFNHTMLRVKDISKSLDFYTRILGFTLVEKRDFPEAE 60

Query: 61  FSLYFLALVDPAQIPADDTARHQWMKSIPGVLELTHNHGTENDADFAYHNGNTDPRGFGH 120
           FSLYFLALVD  QIPAD  AR QWMKSIPG+LELTHNHGTENDADFAYHNGNTDPRGFGH
Sbjct: 61  FSLYFLALVDKNQIPADAAARTQWMKSIPGILELTHNHGTENDADFAYHNGNTDPRGFGH 120

Query: 121 ICISVPDVRAACARFEELEVPFQKRLQDGRMNHLAFVKDPDGYWVEVIQPTEL 173
           ICISVPD+RAAC RFE L   FQKRL DGRM  LAF+KDPD YWVE+IQP  L
Sbjct: 121 ICISVPDIRAACERFEALGCDFQKRLNDGRMKSLAFIKDPDAYWVEIIQPAPL 173


Lambda     K      H
   0.323    0.139    0.431 

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: 224
Number of extensions: 2
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: 175
Length of database: 173
Length adjustment: 19
Effective length of query: 156
Effective length of database: 154
Effective search space:    24024
Effective search space used:    24024
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 (21.9 bits)
S2: 44 (21.6 bits)

Align candidate AO353_26955 AO353_26955 (lactoylglutathione lyase)
to HMM TIGR00068 (gloA: lactoylglutathione lyase (EC 4.4.1.5))

# 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/TIGR00068.hmm
# target sequence database:        /tmp/gapView.28970.genome.faa
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -

Query:       TIGR00068  [M=150]
Accession:   TIGR00068
Description: glyox_I: lactoylglutathione lyase
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
    ------- ------ -----    ------- ------ -----   ---- --  --------                                     -----------
    2.4e-52  162.5   0.0    2.9e-52  162.2   0.0    1.0  1  lcl|FitnessBrowser__pseudo3_N2E3:AO353_26955  AO353_26955 lactoylglutathione l


Domain annotation for each sequence (and alignments):
>> lcl|FitnessBrowser__pseudo3_N2E3:AO353_26955  AO353_26955 lactoylglutathione lyase
   #    score  bias  c-Evalue  i-Evalue hmmfrom  hmm to    alifrom  ali to    envfrom  env to     acc
 ---   ------ ----- --------- --------- ------- -------    ------- -------    ------- -------    ----
   1 !  162.2   0.0   2.9e-52   2.9e-52       7     141 ..      14     170 ..       7     173 .] 0.97

  Alignments for each domain:
  == domain 1  score: 162.2 bits;  conditional E-value: 2.9e-52
                                     TIGR00068   7 avedeatkkylllhtmlrvgdldksldfytevlGmkllrkkdfpeekfslaflgyedessa.... 67 
                                                   a+ d+at+++++ htmlrv+d+ ksldfyt++lG +l+ k+dfpe +fsl+fl+  d+++     
  lcl|FitnessBrowser__pseudo3_N2E3:AO353_26955  14 AQPDTATQQFVFNHTMLRVKDISKSLDFYTRILGFTLVEKRDFPEAEFSLYFLALVDKNQIpada 78 
                                                   678999******************************************************9**** PP

                                     TIGR00068  68 ...........avieLtynwgtek.....ydlGn....gfGhiaiavddvykacervkakGgkvv 112
                                                               ++eLt+n+gte+     y++Gn    gfGhi i+v+d+ +acer++a+G ++ 
  lcl|FitnessBrowser__pseudo3_N2E3:AO353_26955  79 aartqwmksipGILELTHNHGTENdadfaYHNGNtdprGFGHICISVPDIRAACERFEALGCDFQ 143
                                                   **********99***********99**************************************** PP

                                     TIGR00068 113 repgpvkggtkviafvkDPDGykiellek 141
                                                   ++    +g++k +af+kDPD y++e+++ 
  lcl|FitnessBrowser__pseudo3_N2E3:AO353_26955 144 KRL--NDGRMKSLAFIKDPDAYWVEIIQP 170
                                                   **9..**********************96 PP



Internal pipeline statistics summary:
-------------------------------------
Query model(s):                            1  (150 nodes)
Target sequences:                          1  (173 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: 00:00:00.00
# Mc/sec: 6.02
//
[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