Alignments for a candidate for nagA in Caulobacter crescentus NA1000

GapMind for catabolism of small carbon sources

Alignments for a candidate for nagA in Caulobacter crescentus NA1000

Align N-acetylglucosamine-6-phosphate deacetylase (EC 3.5.1.25) (characterized)
to candidate CCNA_00568 CCNA_00568 N-acetylglucosamine-6-phosphate deacetylase

Query= reanno::Caulo:CCNA_00452
         (378 letters)



>FitnessBrowser__Caulo:CCNA_00568
          Length = 387

 Score =  565 bits (1457), Expect = e-166
 Identities = 284/377 (75%), Positives = 322/377 (85%)

Query: 1   MPAALINGRVLTESGVVEGKAVLVKDGLILDVIEAAQTPSDAKPRDLKGGLLVPGFIDTQ 60
           MP AL+NGRVLT +G V GKAVLV++G+++ +++A   P+DA+  DL G  LVPGFIDTQ
Sbjct: 1   MPIALVNGRVLTPAGFVSGKAVLVENGVVVALLDARDVPADAQRHDLGGDRLVPGFIDTQ 60

Query: 61  VNGGGGVLFNDAPTVETIATIGAAHRRFGTTGFLPTLISDDLRVVDQAMRATEEAIARGV 120
           VNGGGG LFNDAPT  TIATIG AHR +GTTGFLPTLISDDL VVD A+RATE+AIA+GV
Sbjct: 61  VNGGGGALFNDAPTARTIATIGEAHRAYGTTGFLPTLISDDLEVVDAALRATEDAIAQGV 120

Query: 121 PGVLGLHIEGPFLNPKRKGIHDAGKFRVIDDEALALLTSLKRGKTLVTLAPERTTPQIIR 180
           PGVLG+HIEGPFLNPKRKGIHD  KFRVID++A+ALL+SLKRGK L+TLAPERTTP II 
Sbjct: 121 PGVLGVHIEGPFLNPKRKGIHDEAKFRVIDEDAIALLSSLKRGKLLLTLAPERTTPDIIA 180

Query: 181 RLADAGVIVAAGHTNALYATMRQALEHGLTGFTHLFNAMSPLTSREPGAVGAALESPDAW 240
           RLA AGVIVAAGHTNA Y TMR+AL+HGLTG THLFNAMSPLTSREPG VGA LE+ +AW
Sbjct: 181 RLAAAGVIVAAGHTNAHYETMRRALDHGLTGVTHLFNAMSPLTSREPGVVGAVLENQNAW 240

Query: 241 CGIIVDGRHVDPVVLKIALRTRALDRFMLVTDAMPTVGLPDKRFNLQGRDIRVVDGVCVD 300
            GIIVDGRHVDPV LKIALRTR LDRFMLVTDAMPTVGL +KRFNLQGR+I V DGVCVD
Sbjct: 241 AGIIVDGRHVDPVTLKIALRTRPLDRFMLVTDAMPTVGLTNKRFNLQGREIVVRDGVCVD 300

Query: 301 DHGTLAGSDLDMIGAVRNAIDLLDLSLDDAVMMASHAPASFLGLGHGRGLIAPGYAADLC 360
           + GTLAGSDLDM  AVRNA+ +L L+L+DAVMMAS AP++ LGL   RG IAPG AAD C
Sbjct: 301 EAGTLAGSDLDMAAAVRNAVSMLGLTLEDAVMMASAAPSALLGLQQRRGAIAPGLAADFC 360

Query: 361 LLNDRLEVAATWIDGQE 377
            L+D L V +TWIDG+E
Sbjct: 361 RLDDALNVTSTWIDGKE 377


Lambda     K      H
   0.321    0.140    0.410 

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: 609
Number of extensions: 18
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: 378
Length of database: 387
Length adjustment: 30
Effective length of query: 348
Effective length of database: 357
Effective search space:   124236
Effective search space used:   124236
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: 50 (23.9 bits)

Align candidate CCNA_00568 CCNA_00568 (N-acetylglucosamine-6-phosphate deacetylase)
to HMM TIGR00221 (nagA: N-acetylglucosamine-6-phosphate deacetylase (EC 3.5.1.25))

# 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/TIGR00221.hmm
# target sequence database:        /tmp/gapView.23772.genome.faa
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -

Query:       TIGR00221  [M=380]
Accession:   TIGR00221
Description: nagA: N-acetylglucosamine-6-phosphate deacetylase
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
    ------- ------ -----    ------- ------ -----   ---- --  --------                             -----------
    1.4e-96  309.7   0.0    1.5e-96  309.5   0.0    1.0  1  lcl|FitnessBrowser__Caulo:CCNA_00568  CCNA_00568 N-acetylglucosamine-6


Domain annotation for each sequence (and alignments):
>> lcl|FitnessBrowser__Caulo:CCNA_00568  CCNA_00568 N-acetylglucosamine-6-phosphate deacetylase
   #    score  bias  c-Evalue  i-Evalue hmmfrom  hmm to    alifrom  ali to    envfrom  env to     acc
 ---   ------ ----- --------- --------- ------- -------    ------- -------    ------- -------    ----
   1 !  309.5   0.0   1.5e-96   1.5e-96       5     380 .]       3     376 ..       1     376 [. 0.96

  Alignments for each domain:
  == domain 1  score: 309.5 bits;  conditional E-value: 1.5e-96
                             TIGR00221   5 lllkdkailtendvlddsavvindekikavvteaeleeeikeidlkgnvltpGliDvqlnGcgGvdtndasv. 76 
                                           ++l + ++lt   ++  +av+++++++ a+   ++ + + ++ dl g  l pG+iD q+nG+gG+ +nda + 
  lcl|FitnessBrowser__Caulo:CCNA_00568   3 IALVNGRVLTPAGFVSGKAVLVENGVVVALLDARDVPADAQRHDLGGDRLVPGFIDTQVNGGGGALFNDAPTa 75 
                                           68999****************************************************************8777 PP

                             TIGR00221  77 etleimsealaksGvtsfLptlitredeeikkavkvareylakeknakiLGlhleGPflslekkGahpkeyir 149
                                            t+  + ea   +G+t+fLptli+ + e +  a++++ +++a+     +LG+h+eGPfl++++kG+h +   r
  lcl|FitnessBrowser__Caulo:CCNA_00568  76 RTIATIGEAHRAYGTTGFLPTLISDDLEVVDAALRATEDAIAQGVP-GVLGVHIEGPFLNPKRKGIHDEAKFR 147
                                           ******************************************9988.8********************99989 PP

                             TIGR00221 150 epdvellkkfldeagdvitkvtlapeekqtaelisklleagiivsaGhtnatyeelkeafkaGitfathlyna 222
                                            +d + +  +     +    +tlap e++t ++i +l+ ag+iv aGhtna ye+++ a   G t +thl+na
  lcl|FitnessBrowser__Caulo:CCNA_00568 148 VIDEDAIALLSSLKRGK-LLLTLAP-ERTTPDIIARLAAAGVIVAAGHTNAHYETMRRALDHGLTGVTHLFNA 218
                                           88888755555444444.469****.89999****************************************** PP

                             TIGR00221 223 mskldhRepgviGavLdeddvvteiiaDGlhihpknirlakklkgdsklvlvtDslaaagaklekfifaGkev 295
                                           ms+l+ Repgv+GavL++++  ++ii+DG h++p ++++a + +   +++lvtD++ + g++ ++f  +G+e+
  lcl|FitnessBrowser__Caulo:CCNA_00568 219 MSPLTSREPGVVGAVLENQNAWAGIIVDGRHVDPVTLKIALRTRPLDRFMLVTDAMPTVGLTNKRFNLQGREI 291
                                           ************************************************************************* PP

                             TIGR00221 296 yiredtlldkngtlaGssltmiegvknlvefveislsdvvrisslnparalgiddrlGsvakGkdanLavltk 368
                                            +r++ ++d+ gtlaGs l m  +v+n+v   +++l+d+v ++s  p+  lg+++r+G++a G  a+   l+ 
  lcl|FitnessBrowser__Caulo:CCNA_00568 292 VVRDGVCVDEAGTLAGSDLDMAAAVRNAVSMLGLTLEDAVMMASAAPSALLGLQQRRGAIAPGLAADFCRLDD 364
                                           ************************************************************************* PP

                             TIGR00221 369 dfeviltivegk 380
                                             +v+ t ++gk
  lcl|FitnessBrowser__Caulo:CCNA_00568 365 ALNVTSTWIDGK 376
                                           *********997 PP



Internal pipeline statistics summary:
-------------------------------------
Query model(s):                            1  (380 nodes)
Target sequences:                          1  (387 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: 0.00u 0.00s 00:00:00.00 Elapsed: 00:00:00.01
# Mc/sec: 11.87
//
[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