Alignments for a candidate for fadA in Sinorhizobium meliloti 1021

GapMind for catabolism of small carbon sources

Alignments for a candidate for fadA in Sinorhizobium meliloti 1021

Align acetyl-CoA acetyltransferase (EC 2.3.1.16) (characterized)
to candidate SMc03879 SMc03879 acetyl-CoA acetyltransferase

Query= metacyc::MONOMER-13585
         (391 letters)



>FitnessBrowser__Smeli:SMc03879
          Length = 393

 Score =  606 bits (1562), Expect = e-178
 Identities = 298/388 (76%), Positives = 338/388 (87%)

Query: 3   NVVIVSAARTAVGSFNGAFASTPAHDLGAAVIEAVVARAGIDKADVSETILGQVLTAGQG 62
           ++VI SAARTAVGSFNGAF +T AH+LGAA I+AV+ RAG++  +V E ILGQVL AG+G
Sbjct: 5   SIVIASAARTAVGSFNGAFGNTLAHELGAAAIKAVLERAGVEAGEVDEVILGQVLPAGEG 64

Query: 63  QNPARQAHIKAGLPQESAAWSINQVCGSGLRAVALAAQHVQLGDASIVVAGGQENMSLSP 122
           QNPARQA +KAGLPQE  AW +NQ+CGSGLRAVAL  Q +  GDA ++VAGG E+MS++P
Sbjct: 65  QNPARQAAMKAGLPQEKTAWGMNQLCGSGLRAVALGMQQIATGDAKVIVAGGMESMSMAP 124

Query: 123 HVAHLRAGQKMGDLSFIDSMIKDGLWDAFNGYHMGQTAENVAAKWQISRDMQDEFAVASQ 182
           H AHLR G KMGD   ID+MIKDGL DAF GYHMG TAENVA KWQ++R+ QDEFA+ASQ
Sbjct: 125 HCAHLRGGVKMGDYKMIDTMIKDGLTDAFYGYHMGITAENVARKWQLTREEQDEFALASQ 184

Query: 183 NKAEAAQKAGRFADEIVPFVIKTRKGDVTVDADEYIRHGATLDAMAKLRPAFIKDGTVTA 242
           NKAEAAQKAGRFADEIVPFV+KTRKGDV VD DEYIRHGATLD++AKLRPAF K+GTVTA
Sbjct: 185 NKAEAAQKAGRFADEIVPFVVKTRKGDVNVDQDEYIRHGATLDSIAKLRPAFDKEGTVTA 244

Query: 243 ANASGINDGAAAVLVMSAEEAEKRGLSPLARIASYATAGLDPSIMGVGPIHASRKALEKA 302
            NASG+NDGAAA L+M+  EA +RG+ PLARI S+ATAG+DP IMG GPI ASRKALEKA
Sbjct: 245 GNASGLNDGAAAALLMTEAEAARRGIQPLARIVSWATAGVDPQIMGTGPIPASRKALEKA 304

Query: 303 GWKVGDLDLVEANEAFAAQACAVNKDMGWDPSIVNVNGGAIAIGHPIGASGARVLNTLLF 362
           GW V D++LVEANEAFAAQACAVNKD+GWDPSIVNVNGGAIAIGHPIGASGARVLNTLLF
Sbjct: 305 GWSVADIELVEANEAFAAQACAVNKDLGWDPSIVNVNGGAIAIGHPIGASGARVLNTLLF 364

Query: 363 EMQRRNAKKGLATLCIGGGMGVAMCLER 390
           EM+RR   KGLATLCIGGGMGVAMC+ER
Sbjct: 365 EMKRRGVSKGLATLCIGGGMGVAMCVER 392


Lambda     K      H
   0.317    0.130    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: 534
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: 391
Length of database: 393
Length adjustment: 31
Effective length of query: 360
Effective length of database: 362
Effective search space:   130320
Effective search space used:   130320
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 (21.7 bits)
S2: 50 (23.9 bits)

Align candidate SMc03879 SMc03879 (acetyl-CoA 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.17531.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
    ------- ------ -----    ------- ------ -----   ---- --  --------                           -----------
   1.6e-146  474.1  10.5   1.9e-146  473.9  10.5    1.0  1  lcl|FitnessBrowser__Smeli:SMc03879  SMc03879 acetyl-CoA acetyltransf


Domain annotation for each sequence (and alignments):
>> lcl|FitnessBrowser__Smeli:SMc03879  SMc03879 acetyl-CoA acetyltransferase
   #    score  bias  c-Evalue  i-Evalue hmmfrom  hmm to    alifrom  ali to    envfrom  env to     acc
 ---   ------ ----- --------- --------- ------- -------    ------- -------    ------- -------    ----
   1 !  473.9  10.5  1.9e-146  1.9e-146       1     385 []       8     391 ..       8     391 .. 0.98

  Alignments for each domain:
  == domain 1  score: 473.9 bits;  conditional E-value: 1.9e-146
                           TIGR01930   1 ivdavRtpigklggslkelsaedLlaavikelleragldpekidevilGnvlqageqaniaReaalaaglpesvp 75 
                                         i +a+Rt++g+++g++ ++ a++L+aa+ik++lerag+++ ++devilG+vl+age++n+aR+aa++aglp++  
  lcl|FitnessBrowser__Smeli:SMc03879   8 IASAARTAVGSFNGAFGNTLAHELGAAAIKAVLERAGVEAGEVDEVILGQVLPAGEGQNPARQAAMKAGLPQEKT 82 
                                         789************************************************************************ PP

                           TIGR01930  76 altvnrvCaSglqAvalaaqkikaGeadvvvaGGvEsmSrvpillkaslrreslklgkakledqllkdl...vkt 147
                                         a+ +n++C+Sgl+Aval++q+i++G+a+v+vaGG+EsmS +p+  +    r ++k+g++k+ d+++kd+   +  
  lcl|FitnessBrowser__Smeli:SMc03879  83 AWGMNQLCGSGLRAVALGMQQIATGDAKVIVAGGMESMSMAPHCAHL---RGGVKMGDYKMIDTMIKDGltdAFY 154
                                         ******************************************97776...69*****************999889 PP

                           TIGR01930 148 klsmgetAenlakkygisReeqDeyalrShqkaakAieegkfkdeivpvevkgk..kkvvskDegirpnttlekL 220
                                         +++mg+tAen+a+k++++ReeqDe+al+S++ka++A+++g+f+deivp++vk++  ++ v++De ir + tl+++
  lcl|FitnessBrowser__Smeli:SMc03879 155 GYHMGITAENVARKWQLTREEQDEFALASQNKAEAAQKAGRFADEIVPFVVKTRkgDVNVDQDEYIRHGATLDSI 229
                                         9***************************************************99999999*************** PP

                           TIGR01930 221 akLkpafkekkgstvtAgNssqlnDGAaalllmseevakelgltplarivsaavagvdpeemglgpvpAiekaLk 295
                                         akL+paf++ +g tvtAgN+s+lnDGAaa+llm+e+ a++ g++plarivs+a+agvdp++mg+gp+pA++kaL+
  lcl|FitnessBrowser__Smeli:SMc03879 230 AKLRPAFDK-EG-TVTAGNASGLNDGAAAALLMTEAEAARRGIQPLARIVSWATAGVDPQIMGTGPIPASRKALE 302
                                         *******95.8*.6************************************************************* PP

                           TIGR01930 296 kaglsisdidlvEinEAFAaqvlavekelgsldlekvNvnGGAiAlGHPlGasGarivltllkeLkergkkyGla 370
                                         kag+s+ di+lvE nEAFAaq+ av+k+lg  d++ vNvnGGAiA+GHP+GasGar++ tll e+k+rg+  Gla
  lcl|FitnessBrowser__Smeli:SMc03879 303 KAGWSVADIELVEANEAFAAQACAVNKDLG-WDPSIVNVNGGAIAIGHPIGASGARVLNTLLFEMKRRGVSKGLA 376
                                         ******************************.88****************************************** PP

                           TIGR01930 371 tlCvggGqGaAvile 385
                                         tlC+ggG+G+A+ +e
  lcl|FitnessBrowser__Smeli:SMc03879 377 TLCIGGGMGVAMCVE 391
                                         ************987 PP



Internal pipeline statistics summary:
-------------------------------------
Query model(s):                            1  (385 nodes)
Target sequences:                          1  (393 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: 00:00:00.01
# Mc/sec: 9.38
//
[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