Salsuginivita brisbanensisTs


Citation

Formal styling
Salsuginivita brisbanensisTs Prabhu et al., 2024
Effective publication
Prabhu et al., 2024
SeqCode status
Valid (SeqCode)
Register List
seqco.de/r:sfdglxu8 (validated)
Canonical URL
https://seqco.de/i:46749

Nomenclature

Rank
Species
Syllabication
bris.ban.en'sis
Etymology
N.L. fem. adj. brisbanensis, of or belonging to Brisbane
Nomenclatural type
NCBI Assembly: GCA_038144975.1
Nomenclatural status
Validly published under the SeqCode

Taxonomy

Description
Inferred to break down a wide range of organic carbon substrates (Chitin, Pectin, Mucin, Starch) as well as carries genes for rTCA cycle to fix inorganic carbon (korABCD). Capable of nitrate uptake (NRT2), phosphorus uptake and regulation (pho, pst), polyphosphate accumulation (ppk1) and noted absence of osmoregulation genes. Based on the genome reporting standards for MAGs , the estimated completeness was 98.63%, contamination 0%, and the presence of the 16S (1,555 bp), and 23S (2, 882bp) rRNA gene and 46 tRNAs. Type genome is defined as “high-quality” draft MAG,with genome size of 2.5Mbps.
Classification
Bacteria » Verrucomicrobiota » Opitutia » Opitutales » Opitutaceae » Salsuginivita » Salsuginivita brisbanensisTs
Parent
Salsuginivita

Genomics

Accession
NCBI Assembly:GCA_038144975.1
Type
Metagenome-Assembled Genome (MAG)
Estimated Quality Metrics
  • Completeness: 98.63%
  • Contamination: 0.0%
  • Quality: 98.63
Ribosomal and transfer RNA genes
  • 1 16S rRNA (up to 100.0%)
  • 1 23S rRNA (up to 100.0%)
  • tRNAs for 20 amino acids
Source
Other features
  • G+C Content: 64.5%
  • Coding Density: 89.87%
  • Codon Table: 11
  • N50: 152,102 bp
  • Contigs: 30
  • Largest Contig: 410,793 bp
  • Assembly Length: 2,456,412 bp
  • Ambiguous Assembly Fraction: 0.0077%
Submitter comments
Completeness and contamination were evaluated using CheckM v 1.1.3
Automated checks
Complete
See additional details

Last modified 10 days ago

Metadata

Outside links and data sources
Search sequences
Local history
Registered by
Chuvochina, Maria 6 months ago
Submitted by
Chuvochina, Maria 3 months ago
Curators
Validated by
Rodriguez-R, Luis M 3 months ago
Date of priority
2024-08-12 01:22 AM (UTC)

Publications
1

Citation Title
Prabhu et al., 2024, ISME Communications Machine learning and metagenomics identifies uncharacterized taxa inferred to drive biogeochemical cycles in a subtropical hypereutrophic estuary
Effective publication



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