Alignments for a candidate for fadA in Desulfacinum hydrothermale DSM 13146

GapMind for catabolism of small carbon sources

Alignments for a candidate for fadA in Desulfacinum hydrothermale DSM 13146

Align acetyl-CoA C-acetyltransferase (EC 2.3.1.9) (characterized)
to candidate WP_084058367.1 B9A12_RS12580 acetyl-CoA C-acetyltransferase

Query= BRENDA::P45359
         (392 letters)



>NCBI__GCF_900176285.1:WP_084058367.1
          Length = 392

 Score =  534 bits (1375), Expect = e-156
 Identities = 261/392 (66%), Positives = 322/392 (82%), Gaps = 1/392 (0%)

Query: 1   MKEVVIASAVRTAIGSYGKSLKDVPAVDLGATAIKEAVKKAGIKPEDVNEVILGNVLQAG 60
           M++ VI SAVRT +GS+G+SL  +PAV LG  A++EA+K+ G+ P+ V+EVILGNVLQA 
Sbjct: 1   MQQAVIVSAVRTPVGSFGRSLAAIPAVTLGVVAVREALKRIGLSPDQVDEVILGNVLQAA 60

Query: 61  LGQNPARQASFKAGLPVEIPAMTINKVCGSGLRTVSLAAQIIKAGDADVIIAGGMENMSR 120
            GQNPARQ +   G+P ++PA TINKVC SGL++V LAAQ +  GDA V++AGG+ENMS 
Sbjct: 61  QGQNPARQVAVHTGIPHQVPAFTINKVCASGLKSVGLAAQAVMVGDAQVVVAGGIENMSA 120

Query: 121 APYLANNARWGYRMGNAKFVDEMITDGLWDAFNDYHMGITAENIAERWNISREEQDEFAL 180
           APY     RWG RMG+ + VD MI DGLWD FN YHMGITAEN+AER+ ISREEQD FAL
Sbjct: 121 APYALPKVRWGQRMGHGEMVDIMIHDGLWDIFNGYHMGITAENVAERYGISREEQDAFAL 180

Query: 181 ASQKKAEEAIKSGQFKDEIVPVVIKGRKGETVV-DTDEHPRFGSTIEGLAKLKPAFKKDG 239
           ASQ+KAE AIK G+F+DEIVPV +  RKG+ ++ DTDEHPRFG+T+E LAKL+PAFKKDG
Sbjct: 181 ASQQKAEAAIKEGRFRDEIVPVEVPQRKGDPILFDTDEHPRFGTTLEALAKLRPAFKKDG 240

Query: 240 TVTAGNASGLNDCAAVLVIMSAEKAKELGVKPLAKIVSYGSAGVDPAIMGYGPFYATKAA 299
           TVTAGNASG+ND  A LV+MS  KA ELG+ PLA I +Y SAGVDPA MG GP  A++ A
Sbjct: 241 TVTAGNASGINDGGAALVVMSERKAAELGLTPLAAIRAYASAGVDPAYMGTGPIPASRKA 300

Query: 300 IEKAGWTVDELDLIESNEAFAAQSLAVAKDLKFDMNKVNVNGGAIALGHPIGASGARILV 359
           +EKAGWT D+LDL+E+NEAFAAQ++AV K+L +D NKVNVNGGAIALGHPIGASGARIL+
Sbjct: 301 LEKAGWTPDDLDLVEANEAFAAQAIAVNKELGWDTNKVNVNGGAIALGHPIGASGARILI 360

Query: 360 TLVHAMQKRDAKKGLATLCIGGGQGTAILLEK 391
           TL++ M++R+A+KGLATLCIGGGQG A+ +E+
Sbjct: 361 TLLYEMKRRNAQKGLATLCIGGGQGMAVAVER 392


Lambda     K      H
   0.315    0.132    0.375 

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: 541
Number of extensions: 19
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: 392
Length of database: 392
Length adjustment: 31
Effective length of query: 361
Effective length of database: 361
Effective search space:   130321
Effective search space used:   130321
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: 50 (23.9 bits)

Align candidate WP_084058367.1 B9A12_RS12580 (acetyl-CoA C-acetyltransferase)
to HMM TIGR01930 (acetyl-CoA C-acyltransferase (EC 2.3.1.16))

# 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/TIGR01930.hmm
# target sequence database:        /tmp/gapView.3470928.genome.faa
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -

Query:       TIGR01930  [M=385]
Accession:   TIGR01930
Description: AcCoA-C-Actrans: acetyl-CoA C-acyltransferase
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
    ------- ------ -----    ------- ------ -----   ---- --  --------                             -----------
   1.7e-158  513.5   2.9   1.9e-158  513.3   2.9    1.0  1  NCBI__GCF_900176285.1:WP_084058367.1  


Domain annotation for each sequence (and alignments):
>> NCBI__GCF_900176285.1:WP_084058367.1  
   #    score  bias  c-Evalue  i-Evalue hmmfrom  hmm to    alifrom  ali to    envfrom  env to     acc
 ---   ------ ----- --------- --------- ------- -------    ------- -------    ------- -------    ----
   1 !  513.3   2.9  1.9e-158  1.9e-158       1     385 []       6     391 ..       6     391 .. 0.99

  Alignments for each domain:
  == domain 1  score: 513.3 bits;  conditional E-value: 1.9e-158
                             TIGR01930   1 ivdavRtpigklggslkelsaedLlaavikelleragldpekidevilGnvlqageqaniaReaalaaglpes 73 
                                           iv+avRtp+g++g sl+ ++a++L++ +++e+l+r gl+p+++devilGnvlqa++++n+aR++a+ +g+p++
  NCBI__GCF_900176285.1:WP_084058367.1   6 IVSAVRTPVGSFGRSLAAIPAVTLGVVAVREALKRIGLSPDQVDEVILGNVLQAAQGQNPARQVAVHTGIPHQ 78 
                                           8************************************************************************ PP

                             TIGR01930  74 vpaltvnrvCaSglqAvalaaqkikaGeadvvvaGGvEsmSrvpillkaslrreslklgkakledqllkdl.. 144
                                           vpa+t+n+vCaSgl++v laaq++++G+a+vvvaGG+E+mS +p+ l++   r++ ++g+ ++ d +++d+  
  NCBI__GCF_900176285.1:WP_084058367.1  79 VPAFTINKVCASGLKSVGLAAQAVMVGDAQVVVAGGIENMSAAPYALPKV--RWGQRMGHGEMVDIMIHDGlw 149
                                           ************************************************96..9******************** PP

                             TIGR01930 145 .vktklsmgetAenlakkygisReeqDeyalrShqkaakAieegkfkdeivpvevkgk...kkvvskDegirp 213
                                              ++++mg+tAen+a++ygisReeqD++al+S+qka++Ai+eg+f deivpvev+++   +  +++De++r 
  NCBI__GCF_900176285.1:WP_084058367.1 150 dIFNGYHMGITAENVAERYGISREEQDAFALASQQKAEAAIKEGRFRDEIVPVEVPQRkgdPILFDTDEHPRF 222
                                           *99*****************************************************999999*********** PP

                             TIGR01930 214 nttlekLakLkpafkekkgstvtAgNssqlnDGAaalllmseevakelgltplarivsaavagvdpeemglgp 286
                                           +ttle+LakL+pafk+ +g tvtAgN+s++nDG aal++mse++a+elgltpla i+++a agvdp++mg+gp
  NCBI__GCF_900176285.1:WP_084058367.1 223 GTTLEALAKLRPAFKK-DG-TVTAGNASGINDGGAALVVMSERKAAELGLTPLAAIRAYASAGVDPAYMGTGP 293
                                           **************95.9*.6**************************************************** PP

                             TIGR01930 287 vpAiekaLkkaglsisdidlvEinEAFAaqvlavekelgsldlekvNvnGGAiAlGHPlGasGarivltllke 359
                                           +pA++kaL+kag++ +d+dlvE nEAFAaq++av+kelg  d++kvNvnGGAiAlGHP+GasGari++tll+e
  NCBI__GCF_900176285.1:WP_084058367.1 294 IPASRKALEKAGWTPDDLDLVEANEAFAAQAIAVNKELG-WDTNKVNVNGGAIALGHPIGASGARILITLLYE 365
                                           ***************************************.88******************************* PP

                             TIGR01930 360 LkergkkyGlatlCvggGqGaAvile 385
                                           +k+r+++ GlatlC+ggGqG+Av +e
  NCBI__GCF_900176285.1:WP_084058367.1 366 MKRRNAQKGLATLCIGGGQGMAVAVE 391
                                           ***********************987 PP



Internal pipeline statistics summary:
-------------------------------------
Query model(s):                            1  (385 nodes)
Target sequences:                          1  (392 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: 16.90
//
[ok]

This GapMind analysis is from Apr 09 2024. 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 2024 update 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