Alignments for a candidate for kbl in Echinicola vietnamensis KMM 6221, DSM 17526

GapMind for catabolism of small carbon sources

Alignments for a candidate for kbl in Echinicola vietnamensis KMM 6221, DSM 17526

Align 2-amino-3-ketobutyrate coenzyme A ligase (EC 2.3.1.29) (characterized)
to candidate Echvi_0145 Echvi_0145 2-amino-3-ketobutyrate coenzyme A ligase

Query= reanno::Cup4G11:RR42_RS28295
         (400 letters)



>FitnessBrowser__Cola:Echvi_0145
          Length = 397

 Score =  542 bits (1397), Expect = e-159
 Identities = 256/389 (65%), Positives = 322/389 (82%)

Query: 11  IRQELESIEQAGLFKTERVIASPQGSLIRTTDGKEVINLCANNYLGLSSHPEVVEAAHRA 70
           + +EL+ I  AGL+K+ER+I SPQG+ I T++GK+V+N CANNYLGLSSHP+V+EAA  A
Sbjct: 9   LEKELKEISDAGLYKSERIITSPQGAEISTSEGKQVLNFCANNYLGLSSHPKVIEAAKNA 68

Query: 71  LGERGFGLSSVRFICGTQDLHKSLEARLASFLGTEDTILYGSAFDANGGLFETLLGSDDA 130
           +   G+G+SSVRFICGTQD+HK LE +++ FLGTEDTILY +AFDANGG+FE +LG +DA
Sbjct: 69  IDTHGYGMSSVRFICGTQDIHKELERKISEFLGTEDTILYAAAFDANGGVFEPILGPEDA 128

Query: 131 VISDELNHASIIDGIRLCKAKRFRYKNNDLEDLREQLKAADAAGARFKLVFTDGVFSMDG 190
           +ISD LNHASIIDG+RLCKA RFRYK+ND+EDL  QLK A+A GA+ K++ TDG FSMDG
Sbjct: 129 IISDALNHASIIDGVRLCKAMRFRYKHNDMEDLETQLKEANAKGAKQKIIVTDGAFSMDG 188

Query: 191 TIARLDEIREICDEFGALLGIDECHATGFLGQRGRGSHEHRGIFGKVDIITGTLGKALGG 250
           TIA++D+I  + +++ AL+  DECH+TGF+G+ GRG HE +G+ GK+DIITGTLGKALGG
Sbjct: 189 TIAQMDKIVALAEQYDALVMSDECHSTGFIGKTGRGVHELKGVMGKMDIITGTLGKALGG 248

Query: 251 ASGGFTSGRKEVVALLRQRSRPYLFSNTVAPCIVGATLKVLDLLEADTTLRDKLERNARY 310
           ASGGFTSGRKE++ +LRQRSRPYLFSNT+AP I GA++ V DLL   T LRDKLE N  Y
Sbjct: 249 ASGGFTSGRKEIIDILRQRSRPYLFSNTLAPAITGASIAVFDLLSETTELRDKLEDNTTY 308

Query: 311 FRGKLGTLGFDVKPGDHPIIPVMVYDAEKAQRLSRRLLELGVYVIGFFYPVVPRGQARIR 370
           FR K+   GFD+KPG HPI+P+M+YDA  +Q+++ +LLE GVYVIGF+YPVVP+GQARIR
Sbjct: 309 FREKMTAAGFDIKPGVHPIVPIMLYDAVLSQQMAEKLLERGVYVIGFYYPVVPKGQARIR 368

Query: 371 VQISALHDSAELDQALEAFEIAGKELGII 399
           VQISA HD   LD A+EAF   GKELG+I
Sbjct: 369 VQISAAHDRKHLDAAIEAFTEVGKELGVI 397


Lambda     K      H
   0.321    0.140    0.402 

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: 546
Number of extensions: 10
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: 400
Length of database: 397
Length adjustment: 31
Effective length of query: 369
Effective length of database: 366
Effective search space:   135054
Effective search space used:   135054
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: 50 (23.9 bits)

Align candidate Echvi_0145 Echvi_0145 (2-amino-3-ketobutyrate coenzyme A ligase)
to HMM TIGR01822 (kbl: glycine C-acetyltransferase (EC 2.3.1.29))

# 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/TIGR01822.hmm
# target sequence database:        /tmp/gapView.13962.genome.faa
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -

Query:       TIGR01822  [M=393]
Accession:   TIGR01822
Description: 2am3keto_CoA: glycine C-acetyltransferase
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-220  716.1   0.5   6.1e-220  715.9   0.5    1.0  1  lcl|FitnessBrowser__Cola:Echvi_0145  Echvi_0145 2-amino-3-ketobutyrat


Domain annotation for each sequence (and alignments):
>> lcl|FitnessBrowser__Cola:Echvi_0145  Echvi_0145 2-amino-3-ketobutyrate coenzyme A ligase
   #    score  bias  c-Evalue  i-Evalue hmmfrom  hmm to    alifrom  ali to    envfrom  env to     acc
 ---   ------ ----- --------- --------- ------- -------    ------- -------    ------- -------    ----
   1 !  715.9   0.5  6.1e-220  6.1e-220       2     393 .]       6     397 .]       5     397 .] 0.99

  Alignments for each domain:
  == domain 1  score: 715.9 bits;  conditional E-value: 6.1e-220
                            TIGR01822   2 kailaaelesireaGlfkkeriitspqkadirvadGrevlnfcannylGlsdhpeviqaakdaldehGfGlssv 75 
                                          k  l++el+ i +aGl+k+eriitspq+a+i +++G++vlnfcannylGls+hp+vi+aak+a+d+hG+G+ssv
  lcl|FitnessBrowser__Cola:Echvi_0145   6 KPKLEKELKEISDAGLYKSERIITSPQGAEISTSEGKQVLNFCANNYLGLSSHPKVIEAAKNAIDTHGYGMSSV 79 
                                          567999******************************************************************** PP

                            TIGR01822  76 rficGtqdlhkelekklaeflgtedailyascfdangGlfeallgeedaiisdalnhasiidGvrlckakryry 149
                                          rficGtqd+hkele+k++eflgted+ilya++fdangG+fe++lg+edaiisdalnhasiidGvrlcka r+ry
  lcl|FitnessBrowser__Cola:Echvi_0145  80 RFICGTQDIHKELERKISEFLGTEDTILYAAAFDANGGVFEPILGPEDAIISDALNHASIIDGVRLCKAMRFRY 153
                                          ************************************************************************** PP

                            TIGR01822 150 enadledleaklkearaagarlrliatdGvfsmdGtiapldeicalaekydalvlvdechatGflGatGrGsae 223
                                          +++d+edle++lkea+a+ga++++i+tdG+fsmdGtia++d+i+alae+ydalv+ dech+tGf+G+tGrG++e
  lcl|FitnessBrowser__Cola:Echvi_0145 154 KHNDMEDLETQLKEANAKGAKQKIIVTDGAFSMDGTIAQMDKIVALAEQYDALVMSDECHSTGFIGKTGRGVHE 227
                                          ************************************************************************** PP

                            TIGR01822 224 lldvldkvdiitgtlGkalGGasGGfttakkevvellrqrsrpylfsnslapavvgasikvlelleasnelrdk 297
                                          l++v++k+diitgtlGkalGGasGGft+++ke++++lrqrsrpylfsn+lapa+ gasi+v++ll++++elrdk
  lcl|FitnessBrowser__Cola:Echvi_0145 228 LKGVMGKMDIITGTLGKALGGASGGFTSGRKEIIDILRQRSRPYLFSNTLAPAITGASIAVFDLLSETTELRDK 301
                                          ************************************************************************** PP

                            TIGR01822 298 lventryfrekleaaGfdvkpaehaiipvmlydaklaqklaerlleeGiyviGffypvvpkGqarirvqlsaah 371
                                          l++nt yfrek++aaGfd+kp+ h+i+p+mlyda l+q++ae+lle+G+yviGf+ypvvpkGqarirvq+saah
  lcl|FitnessBrowser__Cola:Echvi_0145 302 LEDNTTYFREKMTAAGFDIKPGVHPIVPIMLYDAVLSQQMAEKLLERGVYVIGFYYPVVPKGQARIRVQISAAH 375
                                          ************************************************************************** PP

                            TIGR01822 372 eeeqldkaveafvkvGrelgvi 393
                                          ++++ld+a+eaf++vG+elgvi
  lcl|FitnessBrowser__Cola:Echvi_0145 376 DRKHLDAAIEAFTEVGKELGVI 397
                                          ********************98 PP



Internal pipeline statistics summary:
-------------------------------------
Query model(s):                            1  (393 nodes)
Target sequences:                          1  (397 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: 00:00:00.02
# Mc/sec: 7.58
//
[ok]

This GapMind analysis is from Sep 17 2021. The underlying query database was built on Sep 17 2021.

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Protein sequences (fasta format)
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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