GapMind for catabolism of small carbon sources

 

Aligments for a candidate for aruG in Burkholderia phytofirmans PsJN

Align arginine N-succinyltransferase (EC 2.3.1.109) (characterized)
to candidate BPHYT_RS07705 BPHYT_RS07705 arginine succinyltransferase

Query= BRENDA::P80358
         (340 letters)



>lcl|FitnessBrowser__BFirm:BPHYT_RS07705 BPHYT_RS07705 arginine
           succinyltransferase
          Length = 346

 Score =  260 bits (664), Expect = 4e-74
 Identities = 143/340 (42%), Positives = 202/340 (59%), Gaps = 8/340 (2%)

Query: 1   MIVRPVTSADLPALIELARSTGTGLTTLPANEQRLQHRVSWAEKAFRGEAERGDADYLFV 60
           ++VR V   D+ AL+ LA+ TG GLTT   +   L  RV  A +    +AE  +A Y FV
Sbjct: 2   IVVRVVQRGDVDALMRLAQETGPGLTTFKPDRDALAARVERARRTMEDKAEAHEAGYFFV 61

Query: 61  LED-DAGKVVGISAIAGAVGLREPWYNYRVGLTVSASQELNIHREIPTLFLANDLTGNSE 119
           +ED D G V G+  I  AVGL++P+YNYRV   V ASQ+L I   +  L +++DLTG +E
Sbjct: 62  MEDTDTGDVAGVCGIETAVGLQQPFYNYRVSTVVHASQDLGIWTRMRALNISHDLTGYAE 121

Query: 120 LCSLFLHADHRSGLNGKLLSRARFLFIAEFRHLFGDKLIAEMRGMSDEEGRSPFWESLGR 179
           +CSLFL   +R+   G LLSR+RF+F+A+FR  F  +L AE+RG  D EG SPFW ++G 
Sbjct: 122 VCSLFLSPRYRTSGVGGLLSRSRFMFLAQFRERFPQRLCAELRGHFDAEGTSPFWRAVGS 181

Query: 180 HFFKMEFSQADYLTGVGNKAFIAELMPKFPLYTCFLSEEARGVIGRVHPNTEPALAMLKA 239
           HF++++F+ ADYL+  G KAF+AELMP++P+Y   L EEA+  +G  H +T PA  ML++
Sbjct: 182 HFYQIDFNAADYLSSHGRKAFLAELMPRYPVYVELLPEEAQQCVGLTHNDTIPARRMLES 241

Query: 240 EGFSYQGYVDIFDAGPAIEAETDKIRAIAESQNLVL------AVGTPGDDAEPYLIHNRK 293
           EG  Y+ +VDIFDAGP +E     +R + ES  + +      A G P  D    ++ N  
Sbjct: 242 EGLRYENHVDIFDAGPVLECHIADLRTVRESVVVPVEIAPSSASGAP-QDGPKSMVSNTS 300

Query: 294 REDCRITAAPARAAAGTLVVDPLTAKRLRLSAGASVRAVP 333
             D R+         G   +    A  L + AG  VR +P
Sbjct: 301 LGDFRVGVVAGVPQDGVFRLSATEAAALDVKAGDLVRVLP 340


Lambda     K      H
   0.320    0.136    0.398 

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: 292
Number of extensions: 11
Number of successful extensions: 2
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: 340
Length of database: 346
Length adjustment: 29
Effective length of query: 311
Effective length of database: 317
Effective search space:    98587
Effective search space used:    98587
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: 49 (23.5 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:

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 preprint 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