Alignments for a candidate for liuB in Phaeobacter inhibens BS107

GapMind for catabolism of small carbon sources

Alignments for a candidate for liuB in Phaeobacter inhibens BS107

Align Methylcrotonoyl-CoA carboxylase (EC 6.4.1.4) (characterized)
to candidate GFF1016 PGA1_c10330 methylcrotonoyl-CoA carboxylase subunit alpha

Query= reanno::Smeli:SM_b21124
         (662 letters)



>FitnessBrowser__Phaeo:GFF1016
          Length = 645

 Score =  642 bits (1656), Expect = 0.0
 Identities = 364/662 (54%), Positives = 445/662 (67%), Gaps = 24/662 (3%)

Query: 1   MFSKLLIANRGEIACRIIRTARRLGIRTVAVYSDADGDALHVALADEAIRIGGAPAAESY 60
           MF K+LIANRGEIACR++ TAR +G+RTVAVYSDAD  A HV +ADEA+ IGG+  A+SY
Sbjct: 1   MFDKILIANRGEIACRVMETARAMGVRTVAVYSDADVTAKHVQMADEAVHIGGSAPADSY 60

Query: 61  LASAPIVQAARSVGAQAIHPGYGFLSENADFAEAVAEAGMIFVGPPPAAIRAMGLKDAAK 120
           L    I++ A+  GAQAIHPGYGFLSEN  F +AV  AG+ F+GP   AIR MGLKDAAK
Sbjct: 61  LKGDVIIRVAQESGAQAIHPGYGFLSENPAFVDAVEAAGLSFIGPSADAIRKMGLKDAAK 120

Query: 121 ALMERSGVPVVPGYHGEEQDASFLADRAREIGYPVLIKARAGGGGKGMRRVERQEDFGPA 180
           ALME++GVPVVPGYHG  QDA FLA  A +IGYPVLIKA AGGGGKGMR VE   +F  A
Sbjct: 121 ALMEKAGVPVVPGYHGANQDAEFLAGEAEKIGYPVLIKAVAGGGGKGMRLVEAPAEFSDA 180

Query: 181 LEAARREAESAFGDGSVLLERYLTKPRHIEMQVFGDRHGNIVHLFERDCSLQRRHQKVIE 240
           L++A+ EA +AFG+  VL+E+Y+ +PRHIE+QVFGD   + VHLFERDCSLQRRHQKVIE
Sbjct: 181 LKSAQGEATTAFGNPDVLIEKYIQQPRHIEVQVFGD-GTHAVHLFERDCSLQRRHQKVIE 239

Query: 241 EAPAPGMTAEVRRAMGDAAVRAAQAIGYVGAGTVEFIADVTNGLWPDHFYFMEMNTRLQV 300
           EAPAPGMTAE+R AMG+A VRAA+AIGY GAGTVEFI D ++GL  D F+FMEMNTRLQV
Sbjct: 240 EAPAPGMTAEMREAMGEAGVRAAEAIGYKGAGTVEFIVDGSDGLRTDGFWFMEMNTRLQV 299

Query: 301 EHPVTEAITGIDLVEWQLRVASGEPLPKKQADISMNGWAFEARLYAEDPARGFLPATGRL 360
           EHPVTE ITG+DLVEWQLRVASGE LP +Q D+++ G AFEARLYAED  +GFLPATG L
Sbjct: 300 EHPVTELITGVDLVEWQLRVASGESLPAQQDDLTITGHAFEARLYAEDVPKGFLPATGTL 359

Query: 361 TELSFPEGTSRVDSGVRQGDTITPYYDPLIAKLIVHGQNRSAALGRLQDALKECRIGGTV 420
           T LSFP    R DSGVR GDTI+P+YDP+I+K+IVHG  RS AL +L+ AL+   + GTV
Sbjct: 360 THLSFP-AECRADSGVRAGDTISPWYDPMISKVIVHGATRSVALSKLRRALERTEVAGTV 418

Query: 421 TNRDFLIRLTEEHDFRSGHPDTGLIDREIERLTAPVAPGDEALALAAIFSTGALDPNRST 480
           TN  FL  L     F  G  DTGLI R++E LT   A GD  +A     +  AL  ++S 
Sbjct: 419 TNLAFLGALASHQGFGRGEVDTGLIARDLEALT---AVGDMPVAHWIAAAQRALCLHKS- 474

Query: 481 DPWSSLGSWQIWGDAHRMVVIEHADVRATVTLASRGRDQFAVRAGASTLPVL---VLDRF 537
                   + +W   HR V + H +    +T+   G      +   S+  V       R 
Sbjct: 475 ---GGDSGFTLWAPLHRAVQLTHGEESLEITVEVLGPQAQRWQLDDSSHEVTFDGTCWRH 531

Query: 538 EGGARLEVA-GQKRLIRFSRDREALTLFHGGRNLVFHVPDGLTGGQSSEIADDELVAPMP 596
           +G     VA    RL  F+R            + +F   D L    ++    + + APMP
Sbjct: 532 DGHPLPNVAEADGRLTVFAR-----------ISSIFDCIDPLDRAGTAGGDTNVIEAPMP 580

Query: 597 GLVKLVRVGAGDAVTKGQALVVMEAMKMELTLSASREGTIANVHVAEGAQVSEGTVLVTL 656
           GLVK V   AG  V +G  L ++EAMKME +L A+R+G +A V  + G QV  G  LV L
Sbjct: 581 GLVKAVFAEAGAEVKEGDRLAILEAMKMEHSLLAARDGVVAEVLASAGDQVEAGAALVRL 640

Query: 657 ME 658
            E
Sbjct: 641 EE 642


Lambda     K      H
   0.319    0.135    0.394 

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: 1218
Number of extensions: 62
Number of successful extensions: 6
Number of sequences better than 1.0e-02: 1
Number of HSP's gapped: 2
Number of HSP's successfully gapped: 2
Length of query: 662
Length of database: 645
Length adjustment: 38
Effective length of query: 624
Effective length of database: 607
Effective search space:   378768
Effective search space used:   378768
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: 54 (25.4 bits)

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)
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Protein sequences (fasta format)
Organisms (tab-delimited)
SQLite3 databases

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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