Alignments for a candidate for dddA in Stenotrophomonas chelatiphaga DSM 21508

GapMind for catabolism of small carbon sources

Alignments for a candidate for dddA in Stenotrophomonas chelatiphaga DSM 21508

Align 3-hydroxypropionate dehydrogenase (EC 1.1.1.59) (characterized)
to candidate WP_057687529.1 ABB28_RS16885 choline dehydrogenase

Query= metacyc::MONOMER-15202
         (579 letters)



>NCBI__GCF_001431535.1:WP_057687529.1
          Length = 559

 Score =  336 bits (862), Expect = 1e-96
 Identities = 206/542 (38%), Positives = 298/542 (54%), Gaps = 21/542 (3%)

Query: 36  FDYIVVGAGTAGCLLANRLSADPANRVLLIEAGGRDNY--HWIHIPVGYLYCINNPRTDW 93
           +DYI++GAG+AG +LA RL+ D    VLL+EAGG D        +P    + +   R +W
Sbjct: 7   YDYIIIGAGSAGNVLATRLTEDADVSVLLLEAGGPDYRLDFRTQMPAALAFPLQGKRYNW 66

Query: 94  RFRTEPDPGLNGRSLIYPRGKTLGGCSSINGMLYLRGQARDYDGWAELTGDDAWRWDNCL 153
            ++T+P+P +N R +   RGK LGG S INGM Y+RG A DYD WA + G + W + +CL
Sbjct: 67  AYKTDPEPHMNNRRMDCGRGKGLGGSSLINGMCYIRGNAMDYDNWASMPGLEDWTYADCL 126

Query: 154 PDFMRHEDHYRLDEGGDADPDHYKFHGHGGEWRIEKQRL-KWQVLADFATAAVEAGVPRT 212
           P F + E     D GG+       +HG  G  ++   +    ++ A    A V+AG PRT
Sbjct: 127 PYFRKAETR---DIGGN------DYHGSDGPLQVTTPKNGNNELFAAMIEAGVQAGYPRT 177

Query: 213 RDFNRGDNEGVDAFE--VNQRSGWRWNASKAFLRGVEQRGNLTVWHSTQVLKLDFASGEG 270
            D N    EG    +  V  R G R + ++ +L    +R NLT+       ++ FA    
Sbjct: 178 DDLNGYQQEGFGPMDRTVTPR-GRRSSTARGYLDQARERPNLTIVTHALTDRILFAG--- 233

Query: 271 SEPRCCGVTVERAGKKVVTTARCEVVLSAGAIGSPQLLQLSGIGPTALLAEHAIPVVADL 330
              R  GV   R  +     AR EV+L  GAI SPQ+LQ SG+GP  LL    I VV DL
Sbjct: 234 --KRAVGVAWLRNDEPQKARARREVLLCGGAIASPQVLQRSGVGPADLLRGLGIEVVHDL 291

Query: 331 PGVGENLQDHLQIRSIYKVKGAKTLNTMANSLIGKAKIGLEYILKRSGPMSMAPSQLCIF 390
           PGVG NLQDHL++   Y+ +   +L   A  L  +  IG E++   +G  +    +   F
Sbjct: 292 PGVGANLQDHLEMYLQYECRKPVSL-APALKLYNQPAIGAEWLFNGTGIGASNQFEGGGF 350

Query: 391 TRSSKEYEHPNLEYHVQPLSLEAFGQPLHDFPAITASVCNLNPTSRGTVRIKSGNPRQAP 450
            RS++E++ PNL+YH  P+++   G       +    V ++   SRG + ++S +PR  P
Sbjct: 351 IRSNEEFDWPNLQYHFLPVAINYNGSNPIKEHSFQMHVGSMRSPSRGRIHVRSTDPRVHP 410

Query: 451 AISPNYLSTEEDRQVAADSLRVTRHIASQPAFAKYDPEEFKPGVQYQSDEDLARLAGDIG 510
           +I  NY+S E+D +   D +R+TR I  QPA + Y   E  PG Q ++D ++     +  
Sbjct: 411 SILFNYMSHEQDWREFRDGIRITREIFGQPALSPYTGREISPGSQLRTDAEIDAFVREHA 470

Query: 511 TTIFHPVGTAKMGRDDDPMAVVDSHLRVRGVTGLRVVDASIMPTITSGNTNSPTLMIAEK 570
            T +HP  + KMG   DPMAVVD H RV G+ GLR++DASIMP + +GN N+PT+M+AEK
Sbjct: 471 ETAYHPSCSNKMGSAADPMAVVDGHGRVHGMEGLRIIDASIMPQVVTGNLNAPTIMMAEK 530

Query: 571 AA 572
            A
Sbjct: 531 LA 532


Lambda     K      H
   0.318    0.135    0.418 

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: 978
Number of extensions: 50
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: 579
Length of database: 559
Length adjustment: 36
Effective length of query: 543
Effective length of database: 523
Effective search space:   283989
Effective search space used:   283989
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 (21.7 bits)
S2: 53 (25.0 bits)

This GapMind analysis is from Sep 24 2021. The underlying query database was built on Sep 17 2021.

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Candidates (tab-delimited)
Steps (tab-delimited)
Rules (tab-delimited)
Protein sequences (fasta format)
Organisms (tab-delimited)
SQLite3 databases

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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