Alignments for a candidate for fadA in Marinobacter adhaerens HP15

GapMind for catabolism of small carbon sources

Alignments for a candidate for fadA in Marinobacter adhaerens HP15

Align 3-oxo-acyl CoA thiolase (EC 2.3.1.16) (characterized)
to candidate GFF49 HP15_49 acetyl-CoA acetyltransferase

Query= metacyc::G185E-7833-MONOMER
         (386 letters)



>FitnessBrowser__Marino:GFF49
          Length = 391

 Score =  346 bits (888), Expect = e-100
 Identities = 192/402 (47%), Positives = 258/402 (64%), Gaps = 28/402 (6%)

Query: 1   MTEAYVIDAVRTAVGKRGGALAGIHPVDLGALAWRGLLDRTDIDPAAVDDVIAGCVDAIG 60
           M +  ++DAVRT VG+  G+LAG+    LGAL    LL R  +   ++DDV+ GCV  IG
Sbjct: 1   MKDVVIVDAVRTPVGRFRGSLAGVRADHLGALVLNELLYRNGLAAESIDDVVFGCVTQIG 60

Query: 61  GQAGNIARLSWLAAGYPEEVPGVTVDRQCGSSQQAISFGAQAIMSGTADVIVAGGVQNMS 120
            Q+ NIAR S L AG+P  VPG+T+DR+CGS + A+     AI +G+A+++VAGG +NMS
Sbjct: 61  EQSANIARTSLLGAGWPTSVPGLTIDRKCGSGEAAVHCAFGAIAAGSAEIVVAGGAENMS 120

Query: 121 QIPISSAMTV-GEQFGFTSPTNESKQWLHRYGD--QEISQFRGSELIAEKWNLSREEMER 177
           ++P+ S   + GE FG            H   D  +  SQ   +E +AEKWNL RE+++ 
Sbjct: 121 RVPMGSNRDLHGEAFG------------HLVSDRYEMTSQGEAAERVAEKWNLDREQLDA 168

Query: 178 YSLTSHERAFAAIRAGHFENEIITV----------ETESGPFRVDEG-PRESSLEKMAGL 226
           ++L SH RA  A  +G+F++EI+ V          E   G F  DE   R++SLEK+A L
Sbjct: 169 FALESHRRAAVAADSGYFKSEIVPVPVADYRENGAEKVEGKFAADETIRRDTSLEKLATL 228

Query: 227 QPLV--EGGRLTAAMASQISDGASAVLLASERAVKDHGLRPRARIHHISARAADPVFMLT 284
           +     E GR+TA  +SQISDG SA+LL S    ++ GL+P+ARI  ++   ADP  MLT
Sbjct: 229 KTSFRKENGRITAGNSSQISDGCSALLLMSSDVARNLGLKPKARIRAVTTVGADPTLMLT 288

Query: 285 GPIPATRYALDKTGLAIDDIDTVEINEAFAPVVMAWLKEIKADPAKVNPNGGAIALGHPL 344
           GPI ATR  L K GL +D+ID  EINEAFA V +AW+KE+ ADP ++N NGGAIALGHPL
Sbjct: 289 GPIGATRKVLAKAGLELDEIDLFEINEAFASVPLAWMKEVGADPERLNVNGGAIALGHPL 348

Query: 345 GATGAKLFTTMLGELERIGGRYGLQTMCEGGGTANVTIIERL 386
           GA+GA++ T+ML ELER  GRY LQ +C  GG    TIIER+
Sbjct: 349 GASGARIMTSMLNELERRRGRYALQAICCAGGMGTATIIERI 390


Lambda     K      H
   0.317    0.134    0.389 

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: 423
Number of extensions: 23
Number of successful extensions: 3
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: 386
Length of database: 391
Length adjustment: 30
Effective length of query: 356
Effective length of database: 361
Effective search space:   128516
Effective search space used:   128516
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 GFF49 HP15_49 (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.22087.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
    ------- ------ -----    ------- ------ -----   ---- --  --------                         -----------
   5.6e-143  462.4   1.2   6.4e-143  462.3   1.2    1.0  1  lcl|FitnessBrowser__Marino:GFF49  HP15_49 acetyl-CoA acetyltransfe


Domain annotation for each sequence (and alignments):
>> lcl|FitnessBrowser__Marino:GFF49  HP15_49 acetyl-CoA acetyltransferase
   #    score  bias  c-Evalue  i-Evalue hmmfrom  hmm to    alifrom  ali to    envfrom  env to     acc
 ---   ------ ----- --------- --------- ------- -------    ------- -------    ------- -------    ----
   1 !  462.3   1.2  6.4e-143  6.4e-143       1     385 []       6     388 ..       6     388 .. 0.96

  Alignments for each domain:
  == domain 1  score: 462.3 bits;  conditional E-value: 6.4e-143
                         TIGR01930   1 ivdavRtpigklggslkelsaedLlaavikelleragldpekidevilGnvlqageq.aniaReaalaaglpesvpa 76 
                                       ivdavRtp+g+++gsl+ ++a++L+a v++ell r+gl +e id+v++G+v+q geq aniaR+ +l ag p+svp+
  lcl|FitnessBrowser__Marino:GFF49   6 IVDAVRTPVGRFRGSLAGVRADHLGALVLNELLYRNGLAAESIDDVVFGCVTQIGEQsANIARTSLLGAGWPTSVPG 82 
                                       9**************************************************************************** PP

                         TIGR01930  77 ltvnrvCaSglqAvalaaqkikaGeadvvvaGGvEsmSrvpillkaslrreslklgkakledqllkdlvktklsmge 153
                                       lt++r C+Sg +Av+ a  +i+aG a++vvaGG+E+mSrvp++++++l+  +  +g+  ++        ++  s+ge
  lcl|FitnessBrowser__Marino:GFF49  83 LTIDRKCGSGEAAVHCAFGAIAAGSAEIVVAGGAENMSRVPMGSNRDLH--GEAFGHLVSDR-------YEMTSQGE 150
                                       *********************************************9854..44455555554.......56789*** PP

                         TIGR01930 154 tAenlakkygisReeqDeyalrShqkaakAieegkfkdeivpvevkgk........kkvvskDegirpnttlekLak 222
                                        Ae++a+k+++ Re++D++al+Sh++aa A ++g+fk+eivpv v +         +  ++ De+ir++t+lekLa+
  lcl|FitnessBrowser__Marino:GFF49 151 AAERVAEKWNLDREQLDAFALESHRRAAVAADSGYFKSEIVPVPVADYrengaekvEGKFAADETIRRDTSLEKLAT 227
                                       *******************************************99887899*99988889***************** PP

                         TIGR01930 223 LkpafkekkgstvtAgNssqlnDGAaalllmseevakelgltplarivsaavagvdpeemglgpvpAiekaLkkagl 299
                                       Lk+ f++++g+ +tAgNssq++DG +alllms++va++lgl+p+ari++++++g dp+ m++gp+ A++k+L+kagl
  lcl|FitnessBrowser__Marino:GFF49 228 LKTSFRKENGR-ITAGNSSQISDGCSALLLMSSDVARNLGLKPKARIRAVTTVGADPTLMLTGPIGATRKVLAKAGL 303
                                       **********6.***************************************************************** PP

                         TIGR01930 300 sisdidlvEinEAFAaqvlavekelgsldlekvNvnGGAiAlGHPlGasGarivltllkeLkergkkyGlatlCvgg 376
                                       ++++idl+EinEAFA++ la++ke+g  d+e++NvnGGAiAlGHPlGasGari++++l+eL++r+++y+l+++C +g
  lcl|FitnessBrowser__Marino:GFF49 304 ELDEIDLFEINEAFASVPLAWMKEVG-ADPERLNVNGGAIALGHPLGASGARIMTSMLNELERRRGRYALQAICCAG 379
                                       **************************.88************************************************ PP

                         TIGR01930 377 GqGaAvile 385
                                       G+G+A+i+e
  lcl|FitnessBrowser__Marino:GFF49 380 GMGTATIIE 388
                                       *******97 PP



Internal pipeline statistics summary:
-------------------------------------
Query model(s):                            1  (385 nodes)
Target sequences:                          1  (391 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 0.01s 00:00:00.02 Elapsed: 00:00:00.01
# Mc/sec: 10.50
//
[ok]

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

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Candidates (tab-delimited)
Steps (tab-delimited)
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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