Aligments for a candidate for ptsG-crr in Caulobacter crescentus NA1000

GapMind for catabolism of small carbon sources

Aligments for a candidate for ptsG-crr in Caulobacter crescentus NA1000

Align PTS system glucose-specific EIICBA component; EC 2.7.1.-; EC 2.7.1.69 (characterized)
to candidate CCNA_00458 CCNA_00458 PTS system, N-acetylglucosamine-specific IIBC component

Query= CharProtDB::CH_001857
         (699 letters)



>FitnessBrowser__Caulo:CCNA_00458
          Length = 584

 Score =  368 bits (945), Expect = e-106
 Identities = 221/539 (41%), Positives = 321/539 (59%), Gaps = 35/539 (6%)

Query: 8   VLQKIGRALMLPVAILPAAGILLAIG--NAMQNKDMIQVLHFLSNDNVQLVAGVMESAGQ 65
           +LQ +GRALMLP+A+LP A +LL IG  + +    +    H +S      VA    +AG 
Sbjct: 7   ILQPLGRALMLPIAVLPVAALLLRIGQPDLLGAPALAAATHGMSLS----VANTFGAAGG 62

Query: 66  IVFDNLPLLFAVGVAIGLANGD-GVAGIAAIIGYLVMNVSMSAVLLANGTIPSDSVERAK 124
            +F +L L+FA+GVA+GLA  + G AG+A ++ Y++    + A+L+A   + + +VE AK
Sbjct: 63  AIFASLGLIFAIGVAVGLARENHGAAGLAGVVCYVIATKGVEALLVAPPEVAAKAVEGAK 122

Query: 125 --FFTENHPAYVNMLGIPTLATGVFGGIIVGVLAALLFNRFYTIELPQYLGFFAGKRFVP 182
                      +  L IP        GI+ GV++  L+NR+ TI+LP+YL FF G+RFVP
Sbjct: 123 DLAIAAWKAKEIGKLSIPV-------GILSGVISGALYNRYSTIQLPEYLAFFGGRRFVP 175

Query: 183 IVTSISALILGLIMLVIWPPIQHGLNAFSTGLVEANPTLAAFIFGVIERSLIPFGLHHIF 242
           IV  ++ ++L L+    W  ++ G++  S GLV A+  L   ++G++ R LI  GLHHI 
Sbjct: 176 IVAGLAGVVLALLFGAFWSTLEAGVDGLS-GLVTASGDLGLVVYGLLNRLLIVTGLHHIL 234

Query: 243 YSPFWYEFFSYKSAAGEIIRGDQRIFMAQIKDGVQLTAGTFMTGKYPFMMFGLPAAALAI 302
            +  W+    +    G++ R     F A  K     TAG FM+G +P MMFGLPAA LA+
Sbjct: 235 NNVVWFILGDFNGVTGDLNR-----FAAGDK-----TAGAFMSGFFPVMMFGLPAACLAM 284

Query: 303 YHEAKPQNKKLVAGIMGSAALTSFLTGITEPLEFSFLFVAPVLFAIHCLFAGLSFMVMQL 362
            H A+P+ +K VAG++GS ALTSFLTG+TEP+EF+F+F+APVLFAIH L  GLS  +M +
Sbjct: 285 LHTARPERRKAVAGMLGSLALTSFLTGVTEPIEFTFMFLAPVLFAIHALLTGLSMALMNM 344

Query: 363 LNVKIGMTFSGGLIDYFLFGILPNRTAWWLVIPVGLGLAVIYYFGFRFAIRKFNLKTPGR 422
           L+VK+G  FS GL DY L       T   L+IPVGL    +YY  FRFAI +F+LKTPGR
Sbjct: 345 LDVKLGFGFSAGLFDYVL--NFNKATRPLLLIPVGLVYGALYYGVFRFAILRFDLKTPGR 402

Query: 423 EDAAEETAAPGKTGEAGDLPYEILQAMGDQENIKHLDACITRLRVTVNDQKKVDKDRLKQ 482
           ED A  +A    TG  G    ++L A+G   N+  +DAC TRLR+ V DQ  V++  LK 
Sbjct: 403 EDEAPPSAQAVTTG--GGRGADMLAALGGAANLVSVDACTTRLRLIVVDQGLVNEPALKA 460

Query: 483 LGASGVLEVGNN-IQAIFGPRSDGLKTQMQDIIAGRKPRPEPKTSAQEEVGQQVEEVIA 540
           LGA GV+   +  +Q + GP +D +  +++  I+     P P  +   +V Q  + ++A
Sbjct: 461 LGARGVVRPSDKALQVVLGPIADTVAGEIRHAISA---PPAPAPAPAPDVSQAAKALLA 516



 Score = 44.3 bits (103), Expect = 2e-08
 Identities = 24/91 (26%), Positives = 44/91 (48%), Gaps = 1/91 (1%)

Query: 425 AAEETAAPGKTGEAGDLPYEILQAMGDQENIKHLDACITRLRVTVNDQKKVDKDRLKQLG 484
           +A    AP    +       +L A+G  +N++ L    +RLRV +ND ++VD+  L   G
Sbjct: 494 SAPPAPAPAPAPDVSQAAKALLAALGGADNLRDLSVHASRLRVVLNDPQRVDQAALHTAG 553

Query: 485 ASGVLEVGNN-IQAIFGPRSDGLKTQMQDII 514
             G + VG +    + GP +  +   ++ +I
Sbjct: 554 VRGFVRVGEHAAHVVLGPEAQRIGQAVRAMI 584


Lambda     K      H
   0.323    0.141    0.412 

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: 1096
Number of extensions: 62
Number of successful extensions: 8
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: 699
Length of database: 584
Length adjustment: 38
Effective length of query: 661
Effective length of database: 546
Effective search space:   360906
Effective search space used:   360906
Neighboring words threshold: 11
Window for multiple hits: 40
X1: 16 ( 7.5 bits)
X2: 38 (14.6 bits)
X3: 64 (24.7 bits)
S1: 41 (21.9 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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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, or view the source code.

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