Definition of L-asparagine biosynthesis

GapMind for Amino acid biosynthesis

Definition of L-asparagine biosynthesis

# Asparagine biosynthesis in GapMind is based on MetaCyc pathways
# L-asparagine biosynthesis I (metacyc:ASPARAGINE-BIOSYNTHESIS),
# II (metacyc:ASPARAGINESYN-PWY),
# or III (tRNA-dependent) (metacyc:PWY490-4).
# In pathways I or II, aspartate is amidated directly, with glutamine or ammonia as the nitrogen source.
# In pathway III, aspartate is ligated to tRNA(Asn) and then amidated to Asn-tRNA(Asn).

# In BRENDA, uniprot:A4I213 is misannotated as asnB.
# Many asparagine synthases are bifunctional (obtaining nitrogen from either ammonia or glutamine)
# so similarity to EC:6.3.1.1 is ignored.
# CH_123066 has a vague annotation and it is not clear if it is actually characterized.
asnB	asparagine synthase (glutamine-hydrolysing)	EC:6.3.5.4	ignore:BRENDA::A4I213	ignore_other:EC 6.3.1.1	ignore:CharProtDB::CH_123066

# In BRENDA, uniprot:A4I213 (asnA) is misannotated as asnB.
# Many asparagine synthases are bifunctional (obtaining nitrogen from either ammonia or glutamine)
# so similarity to EC:6.3.5.4 is ignored.
# CH_123066 has a vague annotation and it is not clear if it is actually characterized.
asnA	aspartate--ammonia ligase	EC:6.3.1.1	curated:BRENDA::A4I213	ignore_other:EC 6.3.5.4	ignore:CharProtDB::CH_123066

to_asparagine: asnB
to_asparagine: asnA

# AspS2 forms both Asp-tRNA(Asp) and Asp-tRNA(Asn).
# It is difficult to distinguish the "non-discriminatory" synthase (aspS2)
# from the discriminatory synthase (aspRS) by similarity.
# Also, the presence of the tRNA-dependent amidotransferase gatABC
# is not sufficient to conclude that aspS2 is present because gatABC are
# also involved in tRNA-dependent synthesis of glutamine.
# However, if aspargine synthase and asparginyl-tRNA synthetase (asnRS) are absent,
# then we can conclude that the aspartyl-tRNA synthetase is non-discriminatory.
# This is the basis for annotating CCNA_01969 (uniprot:A0A0H3C7V8_CAUVN), Dshi_2633 (uniprot:SYDND_DINSH),
# and PGA1_c24530 (uniprot:A0A2I7KAZ8).
#
# In Desulfovibrio vulgaris (2 strains) and in Synechococcus, the situation is more complicated
# -- there is an asnRS, but it is not essential, or even improtant for fitness in most conditions.
# This also indicates the presence of the tRNA-dependent pathway.
# (It is also doubtful whether any of those genomes encode asnB or asnA.)
# This is the basis for annotating DvMF_2038 (uniprot:B8DMM5_DESVM),
# DVU3367 (uniprot:SYDND_DESVH), and Synpcc7942_1313 (uniprot:SYDND_SYNE7).
#
# Although the asp-tRNA synthetase from Mycobacterium
# tuberculosis (uniprot:P9WFW3) is annotated as aspartate-specific in BRENDA, this organism
# seems to lack asparaginyl-tRNA synthetase, so this is ignored.
# MetaCyc annotates E.coli aspS (metacyc:ASPS-MONOMER) as both discriminating and non-discriminating,
# which is incorrect, so this is ignored.
# And MetaCyc gives erdS (metacyc:MONOMER-124420) this EC number, but it is not reported to act on asparagine.
aspS2	aspartyl-tRNA(Asp/Asn) synthetase	EC:6.1.1.23	uniprot:A0A0H3C7V8_CAUVN	uniprot:SYDND_DINSH	uniprot:A0A2I7KAZ8	uniprot:B8DMM5_DESVM	uniprot:SYDND_DESVH	uniprot:SYDND_SYNE7	ignore:BRENDA::P9WFW3	ignore:metacyc::ASPS-MONOMER	ignore:metacyc::MONOMER-124420

import gln.steps:gatA gatB gatC # aspartyl-tRNA(Asn) amidotransferase complex

# Some organisms have gatDE instead of gatABC.
# GatDE are thought to form glutaminyl-tRNA only, so they are not described here
# (but TIGRFam suggests that gatD might replace gatB in some archaea).
# In the step definitions of gatABC, metacyc entries are added separately because they have HTML tags in their descriptions.
# Also there are no hits for some of the terms -- often, only gatB is annotated as a
# aspartyl/glutamyl-tRNA(Asn/Gln) amidotransferase subunit.
transamidation: gatA gatB gatC

to_asn_tRNA: aspS2 transamidation

all: to_asn_tRNA
all: to_asparagine

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Protein sequences (fasta format)
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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
changes to Amino acid biosynthesis since the publication.

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 Amino acid biosynthesis