Alignments for a candidate for ackA in Azospirillum brasilense Sp245

GapMind for catabolism of small carbon sources

Alignments for a candidate for ackA in Azospirillum brasilense Sp245

Align acetate kinase (EC 2.7.2.1) (characterized)
to candidate AZOBR_RS04605 AZOBR_RS04605 acetate kinase

Query= BRENDA::Q9WYB1
         (403 letters)



>FitnessBrowser__azobra:AZOBR_RS04605
          Length = 398

 Score =  261 bits (666), Expect = 3e-74
 Identities = 164/405 (40%), Positives = 232/405 (57%), Gaps = 22/405 (5%)

Query: 3   VLVINSGSSSIKYQLIEMEGEK--VLCKGIAERIGIEGSRLVHRVGDEKH-----VIERE 55
           +LVIN+GSSSIK+QL +       V  +G  E IG     +V   G +        +  E
Sbjct: 5   ILVINAGSSSIKFQLFDAADGTLPVRLRGRIEGIGTAPRLIVQESGQDGSRDGGVTLPAE 64

Query: 56  LPDHEEALKLILNTLVDEKLGVIKDLKEIDAVGHRVVHGGERFKESVLVDEEVLKAIEEV 115
             D        L   +  +LG    +    AVGHRVVHGG  +   V VD+ V+  +E  
Sbjct: 65  SGDGVPGALAFLGAWLRGRLGGAMPV----AVGHRVVHGGPAYDSHVAVDDAVIGTLETY 120

Query: 116 SPLAPLHNPANLMGIKAAMKLLPGVPNVAVFDTAFHQTIPQKAYLYAIPYEYYEKYKIRR 175
            PLAPLH P NL  I+A  KLLP V  VA FDTAFH+   + A  YAIP +   +  +RR
Sbjct: 121 VPLAPLHQPNNLAPIRAIRKLLPDVLQVACFDTAFHRHHSEPADRYAIP-DALHREGVRR 179

Query: 176 YGFHGTSHRYVSKRAAEILGKKLEELKIITCHIGNGASVAAVKYGKCVDTSMGFTPLEGL 235
           YGFHG S+ Y++ R  + L   +   +++  H+G+GAS+ A++ G+ VD++MGFT L+GL
Sbjct: 180 YGFHGLSYEYIAGRLPD-LAPGIAGGRVVVAHLGSGASMCAIQDGRSVDSTMGFTALDGL 238

Query: 236 VMGTRSGDLDPAIPFFIMEKEGISPQEMYDILNKKSGVYGLSKGFSSDMRDIEEAALKGD 295
            MGTR G LDP +  ++M+K G+  + +  +L    G+ GLS G S+D+RD+  +    D
Sbjct: 239 PMGTRPGQLDPGVVLYLMDK-GMDARAIERLLYHDCGLKGLS-GISNDVRDLLAST---D 293

Query: 296 EWCKLVLEIYDYRIAKYIGAYAAAMNGVDAIVFTAGVGENSPITREDVCSYLEFLGVKLD 355
              KL L+ + YR +  IGA AAAM G+D +VFTAG+GE +P  R+ +     +LGV LD
Sbjct: 294 PRAKLALDCFVYRASLAIGALAAAMGGIDGLVFTAGIGERAPAIRKAIAERARWLGVDLD 353

Query: 356 KQKNEETIRGKEGIISTPDSRVKVLVVPTNEELMIARDTKEIVEK 400
           +  N          I+TPDSRVK  V+PT+EE MIA  T+ I+ +
Sbjct: 354 EAGNAANAL----CITTPDSRVKGWVIPTDEERMIALHTRAILRR 394


Lambda     K      H
   0.318    0.138    0.391 

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: 401
Number of extensions: 16
Number of successful extensions: 6
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: 403
Length of database: 398
Length adjustment: 31
Effective length of query: 372
Effective length of database: 367
Effective search space:   136524
Effective search space used:   136524
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 AZOBR_RS04605 AZOBR_RS04605 (acetate kinase)
to HMM TIGR00016 (ackA: acetate kinase (EC 2.7.2.1))

# 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/TIGR00016.hmm
# target sequence database:        /tmp/gapView.26527.genome.faa
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -

Query:       TIGR00016  [M=405]
Accession:   TIGR00016
Description: ackA: acetate kinase
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
    ------- ------ -----    ------- ------ -----   ---- --  --------                                 -----------
   9.7e-102  326.6   0.0     2e-101  325.6   0.0    1.4  1  lcl|FitnessBrowser__azobra:AZOBR_RS04605  AZOBR_RS04605 acetate kinase


Domain annotation for each sequence (and alignments):
>> lcl|FitnessBrowser__azobra:AZOBR_RS04605  AZOBR_RS04605 acetate kinase
   #    score  bias  c-Evalue  i-Evalue hmmfrom  hmm to    alifrom  ali to    envfrom  env to     acc
 ---   ------ ----- --------- --------- ------- -------    ------- -------    ------- -------    ----
   1 !  325.6   0.0    2e-101    2e-101       4     399 ..       3     387 ..       1     392 [. 0.88

  Alignments for each domain:
  == domain 1  score: 325.6 bits;  conditional E-value: 2e-101
                                 TIGR00016   4 kkilvlnaGssslkfalldaense.kvllsglverikleeariktvedgekkeee..klaiedheeavk 69 
                                               + ilv+naGsss+kf+l+da+++   v l+g +e i  +   i   e+g++++++  ++  ++   +v 
  lcl|FitnessBrowser__azobra:AZOBR_RS04605   3 ETILVINAGSSSIKFQLFDAADGTlPVRLRGRIEGIGTAPRLIV-QESGQDGSRDggVTLPAESGDGVP 70 
                                               689******************965145699******99988555.455554444411222344445666 PP

                                 TIGR00016  70 kllntlkkdkkilkelseialiGHRvvhGgekftesvivtdevlkkikdiselAPlHnpaelegieavl 138
                                                 l  l +  + +   +   ++GHRvvhGg  + + v v+d v+  ++  ++lAPlH p++l  i+a+ 
  lcl|FitnessBrowser__azobra:AZOBR_RS04605  71 GALAFLGAWLRGRLGGAMPVAVGHRVVHGGPAYDSHVAVDDAVIGTLETYVPLAPLHQPNNLAPIRAIR 139
                                               666666653333444455578************************************************ PP

                                 TIGR00016 139 klkvllkaknvavFDtafHqtipeeaylYalPyslykelgvRrYGfHGtshkyvtqraakllnkplddl 207
                                                 k l+++ +va+FDtafH+   e+a  Ya+P ++ ++ gvRrYGfHG+s++y++ r+ +l    ++  
  lcl|FitnessBrowser__azobra:AZOBR_RS04605 140 --KLLPDVLQVACFDTAFHRHHSEPADRYAIP-DALHREGVRRYGFHGLSYEYIAGRLPDLAP-GIAGG 204
                                               ..8889999***********************.777788******************998655.59*** PP

                                 TIGR00016 208 nlivcHlGnGasvsavknGksidtsmGltPLeGlvmGtRsGdiDpaiisylaetlglsldeieetlnkk 276
                                               +++v+HlG Gas++a+++G+s+d +mG+t L+Gl mGtR G++Dp+++ yl+++ g+ + +ie++l  +
  lcl|FitnessBrowser__azobra:AZOBR_RS04605 205 RVVVAHLGSGASMCAIQDGRSVDSTMGFTALDGLPMGTRPGQLDPGVVLYLMDK-GMDARAIERLLYHD 272
                                               ***************************************************985.999*********** PP

                                 TIGR00016 277 sGllgisglssDlRdildkkeegneeaklAlkvyvhRiakyigkyiaslegelDaivFtgGiGenaaev 345
                                                Gl g+sg+s+D+Rd+l+ +   + +aklAl+ +v+R    ig+ +a++ g +D++vFt+GiGe a  +
  lcl|FitnessBrowser__azobra:AZOBR_RS04605 273 CGLKGLSGISNDVRDLLAST---DPRAKLALDCFVYRASLAIGALAAAMGG-IDGLVFTAGIGERAPAI 337
                                               *****************998...789***********************76.***************** PP

                                 TIGR00016 346 relvleklevlGlkldlelnnaarsgkesvisteeskvkvlviptneelviaeD 399
                                               r+ + e+ + lG++ld++ n      +   i+t++s+vk  vipt+ee +ia  
  lcl|FitnessBrowser__azobra:AZOBR_RS04605 338 RKAIAERARWLGVDLDEAGNA----ANALCITTPDSRVKGWVIPTDEERMIALH 387
                                               ****************99998....67789*********************965 PP



Internal pipeline statistics summary:
-------------------------------------
Query model(s):                            1  (405 nodes)
Target sequences:                          1  (398 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: 0.05u 0.01s 00:00:00.06 Elapsed: 00:00:00.06
# Mc/sec: 2.51
//
[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