Alignments for a candidate for fadA in Phaeobacter inhibens BS107

GapMind for catabolism of small carbon sources

Alignments for a candidate for fadA in Phaeobacter inhibens BS107

Align 3-ketoacyl-CoA thiolase (EC 2.3.1.16) (characterized)
to candidate GFF3267 PGA1_c33180 acetyl-CoA acetyltransferase

Query= reanno::acidovorax_3H11:Ac3H11_2994
         (397 letters)



>FitnessBrowser__Phaeo:GFF3267
          Length = 390

 Score =  487 bits (1253), Expect = e-142
 Identities = 247/387 (63%), Positives = 292/387 (75%), Gaps = 2/387 (0%)

Query: 9   IVIVGAARTPMGSLQGDFSSLAAHDLGGAAIKAAIERAGVSPDAVGEVLFGNCLMAGQGQ 68
           +VI GAARTPMG  QG +  +AA +LGG+AI+AA+  AG +   V E+L G  L AGQGQ
Sbjct: 4   VVIAGAARTPMGGFQGMYDGVAAAELGGSAIRAALAGAGAT--TVDEILMGCVLPAGQGQ 61

Query: 69  APARQAAFKGGLPKGAGAVTLSKMCGSGMKAAMMAHDMLLAGSHDVMVAGGMESMTNAPY 128
           APARQA F  GL +   A TL+KMCGSGMKAAMMA+D +  G  D M+AGGMESMTNAPY
Sbjct: 62  APARQAGFAAGLGEEVPATTLNKMCGSGMKAAMMAYDQIALGQADTMIAGGMESMTNAPY 121

Query: 129 LLQKGRGGYRLGHDRIFDHMMLDGLEDAYEAGRSMGTFGEDCAAKYSFTREQQDAFATAS 188
           LL K R G RLGH ++ DHM LDGLEDAY+ GR MGTF EDCA  Y FTRE QD +A  S
Sbjct: 122 LLPKMRNGARLGHGQVVDHMFLDGLEDAYDKGRLMGTFAEDCAETYQFTREAQDEYALTS 181

Query: 189 VQRAKAATESGAFAAEIVPVTVKTRAGETVVSVDEGPGKVKLEKIATLKPAFKKDGTITA 248
           +  A AA ESGAF AEI PVTVKTR GETV + DE P   + +KI TLKPAF+KDGT+TA
Sbjct: 182 LSNALAAQESGAFDAEIAPVTVKTRKGETVTNADEQPKSARPDKIPTLKPAFRKDGTVTA 241

Query: 249 ASSSSINDGAAALVMMRESTAKKLGAKPLARIVSHATHAQEPEWFATAPLGATQKALAKA 308
           A++SSI+DGAAALV+  E  A+  G    ARI+ HA+HAQ P  F TAP+ A +K +A+ 
Sbjct: 242 ANASSISDGAAALVLASEDAAEAQGLTVRARIMGHASHAQAPGLFTTAPVPAAKKLMAQL 301

Query: 309 GWQVGDVQLWEINEAFAVVPMALMKELDLPHDKVNVNGGACALGHPIGASGARIMVTLIH 368
           GW V DV LWE+NEAFAVVPMA M E+ LP DKVNVNGGACALGHPIGASGARIMVTL++
Sbjct: 302 GWTVSDVDLWEVNEAFAVVPMAFMHEMGLPRDKVNVNGGACALGHPIGASGARIMVTLLN 361

Query: 369 ALKARGLTKGLATLCIGGGEATAVALE 395
           AL+ R L +G+A +CIGGGE TA+A+E
Sbjct: 362 ALEKRNLKRGIAAICIGGGEGTAIAIE 388


Lambda     K      H
   0.317    0.131    0.376 

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: 510
Number of extensions: 18
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: 397
Length of database: 390
Length adjustment: 31
Effective length of query: 366
Effective length of database: 359
Effective search space:   131394
Effective search space used:   131394
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 GFF3267 PGA1_c33180 (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.5918.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
    ------- ------ -----    ------- ------ -----   ---- --  --------                          -----------
   5.2e-129  416.4  10.6   6.1e-129  416.2  10.6    1.0  1  lcl|FitnessBrowser__Phaeo:GFF3267  PGA1_c33180 acetyl-CoA acetyltra


Domain annotation for each sequence (and alignments):
>> lcl|FitnessBrowser__Phaeo:GFF3267  PGA1_c33180 acetyl-CoA acetyltransferase
   #    score  bias  c-Evalue  i-Evalue hmmfrom  hmm to    alifrom  ali to    envfrom  env to     acc
 ---   ------ ----- --------- --------- ------- -------    ------- -------    ------- -------    ----
   1 !  416.2  10.6  6.1e-129  6.1e-129       1     385 []       6     388 ..       6     388 .. 0.96

  Alignments for each domain:
  == domain 1  score: 416.2 bits;  conditional E-value: 6.1e-129
                          TIGR01930   1 ivdavRtpigklggslkelsaedLlaavikelleragldpekidevilGnvlqageqaniaReaalaaglpesvpa 76 
                                        i +a+Rtp+g ++g +  + a++L+  +i+++l+ ag     +de+ +G+vl+ag+++++aR+a +aagl+e+vpa
  lcl|FitnessBrowser__Phaeo:GFF3267   6 IAGAARTPMGGFQGMYDGVAAAELGGSAIRAALAGAGA--TTVDEILMGCVLPAGQGQAPARQAGFAAGLGEEVPA 79 
                                        7899******99*********************99855..58********************************** PP

                          TIGR01930  77 ltvnrvCaSglqAvalaaqkikaGeadvvvaGGvEsmSrvpillkaslrreslklgkakledqllkdl....vktk 148
                                        +t+n++C+Sg++A ++a+++i+ G+ad+++aGG+Esm+++p+ll++   r++++lg+ ++ d++  d+     +++
  lcl|FitnessBrowser__Phaeo:GFF3267  80 TTLNKMCGSGMKAAMMAYDQIALGQADTMIAGGMESMTNAPYLLPKM--RNGARLGHGQVVDHMFLDGledaYDKG 153
                                        *********************************************97..899999999999999988889988899 PP

                          TIGR01930 149 lsmgetAenlakkygisReeqDeyalrShqkaakAieegkfkdeivpvevkgk..kkvvskDegirpnttlekLak 222
                                          mg+ Ae +a++y+++Re qDeyal S ++a +A+e+g f++ei pv+vk++  ++v++ De+++     +k+ +
  lcl|FitnessBrowser__Phaeo:GFF3267 154 RLMGTFAEDCAETYQFTREAQDEYALTSLSNALAAQESGAFDAEIAPVTVKTRkgETVTNADEQPK-SARPDKIPT 228
                                        9**************************************************999766667777776.899****** PP

                          TIGR01930 223 LkpafkekkgstvtAgNssqlnDGAaalllmseevakelgltplarivsaavagvdpeemglgpvpAiekaLkkag 298
                                        Lkpaf++ +g tvtA+N+s+++DGAaal+l+se++a++ glt+ ari+++a  +  p  ++++pvpA +k++++ g
  lcl|FitnessBrowser__Phaeo:GFF3267 229 LKPAFRK-DG-TVTAANASSISDGAAALVLASEDAAEAQGLTVRARIMGHASHAQAPGLFTTAPVPAAKKLMAQLG 302
                                        *****95.9*.6**************************************************************** PP

                          TIGR01930 299 lsisdidlvEinEAFAaqvlavekelgsldlekvNvnGGAiAlGHPlGasGarivltllkeLkergkkyGlatlCv 374
                                        +++sd+dl+E+nEAFA++ +a+++e+g l ++kvNvnGGA AlGHP+GasGari++tll++L++r+ k+G+a++C+
  lcl|FitnessBrowser__Phaeo:GFF3267 303 WTVSDVDLWEVNEAFAVVPMAFMHEMG-LPRDKVNVNGGACALGHPIGASGARIMVTLLNALEKRNLKRGIAAICI 377
                                        ***************************.88********************************************** PP

                          TIGR01930 375 ggGqGaAvile 385
                                        ggG G+A+ +e
  lcl|FitnessBrowser__Phaeo:GFF3267 378 GGGEGTAIAIE 388
                                        *******9987 PP



Internal pipeline statistics summary:
-------------------------------------
Query model(s):                            1  (385 nodes)
Target sequences:                          1  (390 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: 10.98
//
[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