Alignments for a candidate for maiA in Shewanella sp. ANA-3

GapMind for catabolism of small carbon sources

Alignments for a candidate for maiA in Shewanella sp. ANA-3

Align Maleylacetoacetate isomerase (EC 5.2.1.2) (characterized)
to candidate 7025626 Shewana3_2777 maleylacetoacetate isomerase (RefSeq)

Query= reanno::MR1:200836
         (216 letters)



>FitnessBrowser__ANA3:7025626
          Length = 216

 Score =  424 bits (1090), Expect = e-124
 Identities = 207/216 (95%), Positives = 212/216 (98%)

Query: 1   MILYGYWRSSAAYRVRIALNLKGVSAEQLSVHLVRDGGEQHKADYIALNPQELVPTLVVD 60
           M LYGYWRSSAAYRVRIALNLKGVSAEQLSVHLVRDGGEQHKADYIALNPQELVPTLVVD
Sbjct: 1   MKLYGYWRSSAAYRVRIALNLKGVSAEQLSVHLVRDGGEQHKADYIALNPQELVPTLVVD 60

Query: 61  DEQDGDALTQSLAIIEYLDELYPKTPLLPASALERAHVRAMALTIACEIHPLNNLRVLQY 120
           DEQDGDAL+QSLAIIEYLDELYPKTPLLPASALERAHVRAMALTIACEIHPLNNLRVLQY
Sbjct: 61  DEQDGDALSQSLAIIEYLDELYPKTPLLPASALERAHVRAMALTIACEIHPLNNLRVLQY 120

Query: 121 LTQKLTVNEEAKSAWYHHWVATGFTALETQLVRHSGRYCFGDKVTIADLCLVPQVYNAQR 180
           LTQKL V+EEAK+AWYHHWVA+GF ALETQL RHSGRYCFGDKVT+ADLCLVPQVYNAQR
Sbjct: 121 LTQKLNVDEEAKTAWYHHWVASGFAALETQLARHSGRYCFGDKVTLADLCLVPQVYNAQR 180

Query: 181 FNVDLTPYPNIMRVWAECNQLPAFADAAPERQADAV 216
           FNVDLTPYPNIMRVWAECNQLPAFADAAPERQADAV
Sbjct: 181 FNVDLTPYPNIMRVWAECNQLPAFADAAPERQADAV 216


Lambda     K      H
   0.321    0.134    0.408 

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: 270
Number of extensions: 3
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: 216
Length of database: 216
Length adjustment: 22
Effective length of query: 194
Effective length of database: 194
Effective search space:    37636
Effective search space used:    37636
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: 45 (21.9 bits)

Align candidate 7025626 Shewana3_2777 (maleylacetoacetate isomerase (RefSeq))
to HMM TIGR01262 (maiA: maleylacetoacetate isomerase (EC 5.2.1.2))

# 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/TIGR01262.hmm
# target sequence database:        /tmp/gapView.24381.genome.faa
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -

Query:       TIGR01262  [M=211]
Accession:   TIGR01262
Description: maiA: maleylacetoacetate isomerase
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
    ------- ------ -----    ------- ------ -----   ---- --  --------                         -----------
    4.1e-97  309.9   0.2    4.6e-97  309.8   0.2    1.0  1  lcl|FitnessBrowser__ANA3:7025626  Shewana3_2777 maleylacetoacetate


Domain annotation for each sequence (and alignments):
>> lcl|FitnessBrowser__ANA3:7025626  Shewana3_2777 maleylacetoacetate isomerase (RefSeq)
   #    score  bias  c-Evalue  i-Evalue hmmfrom  hmm to    alifrom  ali to    envfrom  env to     acc
 ---   ------ ----- --------- --------- ------- -------    ------- -------    ------- -------    ----
   1 !  309.8   0.2   4.6e-97   4.6e-97       1     210 [.       2     215 ..       2     216 .] 0.98

  Alignments for each domain:
  == domain 1  score: 309.8 bits;  conditional E-value: 4.6e-97
                         TIGR01262   1 klYsyfrSsasyRvRiaLaLkgidyesvpvnLlkd.GeqkkeefkalNPqelvPtLkide...gevltqSlAiieyL 73 
                                       klY+y+rSsa+yRvRiaL+Lkg++ e  +v+L++d Geq+k+++ alNPqelvPtL++d+   g+ l+qSlAiieyL
  lcl|FitnessBrowser__ANA3:7025626   2 KLYGYWRSSAAYRVRIALNLKGVSAEQLSVHLVRDgGEQHKADYIALNPQELVPTLVVDDeqdGDALSQSLAIIEYL 78 
                                       69*******************************************************998666889*********** PP

                         TIGR01262  74 eetypepaLlpkdpakrarvralalliacdihPlqNlrvlqlleeklgvdeeekkewlkhwiekGlaalEellkeka 150
                                       +e yp+++Llp+ + +ra+vra+al+iac+ihPl+Nlrvlq+l++kl+vdee+k++w++hw+++G+aalE+ l++++
  lcl|FitnessBrowser__ANA3:7025626  79 DELYPKTPLLPASALERAHVRAMALTIACEIHPLNNLRVLQYLTQKLNVDEEAKTAWYHHWVASGFAALETQLARHS 155
                                       ***************************************************************************** PP

                         TIGR01262 151 gafcvGdevtladvcLvpqvynAerfevdlaqyPtlkrieealaelpafqeahpenqpdt 210
                                       g++c+Gd+vtlad+cLvpqvynA+rf+vdl++yP + r+ +++++lpaf++a+pe+q d+
  lcl|FitnessBrowser__ANA3:7025626 156 GRYCFGDKVTLADLCLVPQVYNAQRFNVDLTPYPNIMRVWAECNQLPAFADAAPERQADA 215
                                       *********************************************************996 PP



Internal pipeline statistics summary:
-------------------------------------
Query model(s):                            1  (211 nodes)
Target sequences:                          1  (216 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: 0.00u 0.00s 00:00:00.00 Elapsed: 00:00:00.00
# Mc/sec: 6.73
//
[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