GapMind for catabolism of small carbon sources

 

Aligments for a candidate for gloB in Dyella japonica UNC79MFTsu3.2

Align hydroxyacylglutathione hydrolase (EC 3.1.2.6) (characterized)
to candidate N515DRAFT_0434 N515DRAFT_0434 hydroxyacylglutathione hydrolase

Query= BRENDA::Q8ZRM2
         (251 letters)



>lcl|FitnessBrowser__Dyella79:N515DRAFT_0434 N515DRAFT_0434
           hydroxyacylglutathione hydrolase
          Length = 254

 Score =  216 bits (551), Expect = 3e-61
 Identities = 111/253 (43%), Positives = 151/253 (59%), Gaps = 3/253 (1%)

Query: 1   MNLNSIPAFQDNYIWVLTNDEGRCVIVDPGEAAPVLKAIAEHKWMPEAIFLTHHHHDHVG 60
           M++  +PA  DNYIW+L +D G  ++VDPGEAAP+  A+        AI LTHHH+DH+G
Sbjct: 1   MHVVPVPALADNYIWLLYDDAGDAIVVDPGEAAPIEAALDRRGLRLRAILLTHHHNDHIG 60

Query: 61  GVKELLQHFPQMTVYGPAETQDKGATHLVGDGDTIRVL--GEKFTLFATPGHTLGHVCYF 118
           GV +LL H P + VY P + +    T  V DGD + +     +F +   PGHT  H+ Y 
Sbjct: 61  GVADLLAHGP-VPVYAPRDERIGHVTQAVADGDEVTIAQPSARFRVLEIPGHTRSHIAYV 119

Query: 119 SRPYLFCGDTLFSGGCGRLFEGTPSQMYQSLMKINSLPDDTLICCAHEYTLANIKFALSI 178
               L CGDTLFS GCGRLFEGTP QM  SL ++  LP +  +CCAHEYT AN +FA ++
Sbjct: 120 GAGMLLCGDTLFSMGCGRLFEGTPQQMLASLDRLADLPGELKVCCAHEYTAANGRFAQTV 179

Query: 179 LPHDSFINEYYRKVKELRVKKQMTLPVILKNERKINLFLRTEDIDLINEINKETILQQPE 238
            P ++ + +   +V+ LR + Q TLPV L  ER  N FLR ++ D+     +        
Sbjct: 180 EPANAALAQRVEQVRALREQAQPTLPVALATERATNPFLRVDNHDVAQWCTRHGAAADRV 239

Query: 239 ARFAWLRSKKDTF 251
           +RFA LR+ KD F
Sbjct: 240 SRFAALRAAKDEF 252


Lambda     K      H
   0.323    0.140    0.436 

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: 204
Number of extensions: 8
Number of successful extensions: 3
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: 251
Length of database: 254
Length adjustment: 24
Effective length of query: 227
Effective length of database: 230
Effective search space:    52210
Effective search space used:    52210
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: 46 (22.3 bits)

Align candidate N515DRAFT_0434 N515DRAFT_0434 (hydroxyacylglutathione hydrolase)
to HMM TIGR03413 (gloB: hydroxyacylglutathione hydrolase (EC 3.1.2.6))

# 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/TIGR03413.hmm
# target sequence database:        /tmp/gapView.7438.genome.faa
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -

Query:       TIGR03413  [M=248]
Accession:   TIGR03413
Description: GSH_gloB: hydroxyacylglutathione hydrolase
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
    ------- ------ -----    ------- ------ -----   ---- --  --------                                    -----------
   1.9e-103  331.1   0.0   2.2e-103  330.9   0.0    1.0  1  lcl|FitnessBrowser__Dyella79:N515DRAFT_0434  N515DRAFT_0434 hydroxyacylglutat


Domain annotation for each sequence (and alignments):
>> lcl|FitnessBrowser__Dyella79:N515DRAFT_0434  N515DRAFT_0434 hydroxyacylglutathione hydrolase
   #    score  bias  c-Evalue  i-Evalue hmmfrom  hmm to    alifrom  ali to    envfrom  env to     acc
 ---   ------ ----- --------- --------- ------- -------    ------- -------    ------- -------    ----
   1 !  330.9   0.0  2.2e-103  2.2e-103       2     248 .]       4     252 ..       3     252 .. 0.98

  Alignments for each domain:
  == domain 1  score: 330.9 bits;  conditional E-value: 2.2e-103
                                    TIGR03413   2 iaipalsdNyiwllkdekseavvvDpgeaepvlealeekglkleaillTHhHaDHvggvaellekf 67 
                                                  +++pal+dNyiwll d++ +a+vvDpgea+p+ +al+++gl+l+aillTHhH+DH+ggva+ll++ 
  lcl|FitnessBrowser__Dyella79:N515DRAFT_0434   4 VPVPALADNYIWLLYDDAGDAIVVDPGEAAPIEAALDRRGLRLRAILLTHHHNDHIGGVADLLAHG 69 
                                                  789*************************************************************** PP

                                    TIGR03413  68 pvkvvgpaeeripgltkevkegdevel..lelevevlevpGHtlgHiayyleeekvlFcgDtLfsa 131
                                                  pv+v++p++eri ++t++v++gdev++   +++++vle+pGHt++Hiay+ +  ++l cgDtLfs+
  lcl|FitnessBrowser__Dyella79:N515DRAFT_0434  70 PVPVYAPRDERIGHVTQAVADGDEVTIaqPSARFRVLEIPGHTRSHIAYVGA--GMLLCGDTLFSM 133
                                                  ***************************5556899******************..************ PP

                                    TIGR03413 132 GCGrlfegtaeqmleslqklaaLpeetkvycaHEYtlsNlrFalavepenealkerlkevealrak 197
                                                  GCGrlfegt++qml+sl++la+Lp e kv+caHEYt++N rFa++vep+n+al++r+++v+alr++
  lcl|FitnessBrowser__Dyella79:N515DRAFT_0434 134 GCGRLFEGTPQQMLASLDRLADLPGELKVCCAHEYTAANGRFAQTVEPANAALAQRVEQVRALREQ 199
                                                  ****************************************************************** PP

                                    TIGR03413 198 gkptlPstlaeekatNpFLraeeaevkaalee..ekaeevevfaelRekkdkf 248
                                                   +ptlP+ la+e+atNpFLr+++++v++ +++  ++a++v+ fa+lR++kd+f
  lcl|FitnessBrowser__Dyella79:N515DRAFT_0434 200 AQPTLPVALATERATNPFLRVDNHDVAQWCTRhgAAADRVSRFAALRAAKDEF 252
                                                  **************************999998889999*************98 PP



Internal pipeline statistics summary:
-------------------------------------
Query model(s):                            1  (248 nodes)
Target sequences:                          1  (254 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 0.00s 00:00:00.01 Elapsed: 00:00:00.00
# Mc/sec: 10.72
//
[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:

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:

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:

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