Align Glycine betaine/proline/choline transporter VP1723 (characterized)
to candidate 14452 b0314 choline transporter of high affinity (NCBI)
Query= SwissProt::Q87NZ5 (553 letters) >FitnessBrowser__Keio:14452 Length = 677 Score = 340 bits (872), Expect = 1e-97 Identities = 179/507 (35%), Positives = 289/507 (57%), Gaps = 30/507 (5%) Query: 45 VFAISGMAIVLFVVATLTFRQQVEPFFAGLRAWLVSNLDWFFLASGNVFVIVCLVLIVTP 104 VF S I+LF + T+ FR + W+ W++L + ++++ + + + Sbjct: 17 VFYTSAGLILLFSLTTILFRDFSALWIGRTLDWVSKTFGWYYLLAATLYIVFVVCIACSR 76 Query: 105 LGRVRIGGTEATPDYSYAGWLAMLFAAGMGIGLVFFGVSEPMSHFSSALGGVNIENGVRT 164 G V++G ++ P++S W AMLFAAG+GI L+FF V+EP++ + Sbjct: 77 FGSVKLGPEQSKPEFSLLSWAAMLFAAGIGIDLMFFSVAEPVTQYMQ------------- 123 Query: 165 DWAPLGGAVGDTDAASALGMAATIYHWALHPWSIYALLALGLAIFSFNKGLPLTMRSIFY 224 P GA G T A+ M T++H+ L WS+YAL+ + L FS+ LPLT+RS Y Sbjct: 124 ---PPEGA-GQTIEAARQAMVWTLFHYGLTGWSMYALMGMALGYFSYRYNLPLTIRSALY 179 Query: 225 PLFGERVWGWVGHIIDILAVVATVFGLATSLGYGASQAATGLNFLFGVPMTDTTQVVLIV 284 P+FG+R+ G +GH +DI AV+ T+FG+AT+LG G Q GL+ LF +P + + LI Sbjct: 180 PIFGKRINGPIGHSVDIAAVIGTIFGIATTLGIGVVQLNYGLSVLFDIPDSMAAKAALIA 239 Query: 285 VITALALISVVAGLDSGVKRLSEINMILAAMLLFFVIIVGPTMAILTGFFDNIASYITNI 344 + +A ISV +G+D G++ LSE+N+ LA L+ FV+ +G T +L N+ Y+ Sbjct: 240 LSVIIATISVTSGVDKGIRVLSELNVALALGLILFVLFMGDTSFLLNALVLNVGDYVNRF 299 Query: 345 PAL---SMPFEREDVNYSQGWTAFYWAWWISWSPFVGMFIARVSRGRSVREFIICVILIP 401 + S F+R V + WT F+WAWW++WSPFVG+F+AR+SRGR++R+F++ ++IP Sbjct: 300 MGMTLNSFAFDR-PVEWMNNWTLFFWAWWVAWSPFVGLFLARISRGRTIRQFVLGTLIIP 358 Query: 402 STVCVLWMTAFGGTAISQYVNDGYEAVFNAELPLK----LFAMLDVMPFAEITSVVGIIL 457 T +LW++ FG +A+ + ++ G A F E + +++L P ++ V I Sbjct: 359 FTFTLLWLSVFGNSALYEIIHGG--AAFAEEAMVHPERGFYSLLAQYPAFTFSASVATIT 416 Query: 458 VVVFFITSSDSGSLVIDTIAAGGK---VDAPTPQRVFWCTFEGLVAIALMLGGGLAAAQA 514 ++F++TS+DSG+LV+ + K DAP RVFW GL+ + +++ G++A Q Sbjct: 417 GLLFYVTSADSGALVLGNFTSQLKDINSDAPGWLRVFWSVAIGLLTLGMLMTNGISALQN 476 Query: 515 MAVTTGLPFTIVLLVATVSLIKGLMDE 541 V GLPF+ V+ L K L E Sbjct: 477 TTVIMGLPFSFVIFFVMAGLYKSLKVE 503 Lambda K H 0.327 0.141 0.435 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: 937 Number of extensions: 58 Number of successful extensions: 5 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: 553 Length of database: 677 Length adjustment: 37 Effective length of query: 516 Effective length of database: 640 Effective search space: 330240 Effective search space used: 330240 Neighboring words threshold: 11 Window for multiple hits: 40 X1: 15 ( 7.1 bits) X2: 38 (14.6 bits) X3: 64 (24.7 bits) S1: 40 (21.7 bits) S2: 53 (25.0 bits)
This GapMind analysis is from Sep 17 2021. The underlying query database was built on Sep 17 2021.
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:
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