Searching the Resource Information Network

Our searching services are busy right now. Please try again later

  • Register
X
Forgot Password

If you have forgotten your password you can enter your email here and get a temporary password sent to your email.

X

Leaving Community

Are you sure you want to leave this community? Leaving the community will revoke any permissions you have been granted in this community.

No
Yes

Genome sequence of Candidatus Nitrososphaera evergladensis from group I.1b enriched from Everglades soil reveals novel genomic features of the ammonia-oxidizing archaea.

Kateryna V Zhalnina | Raquel Dias | Michael T Leonard | Patricia Dorr de Quadros | Flavio A O Camargo | Jennifer C Drew | William G Farmerie | Samira H Daroub | Eric W Triplett
PloS one | 2014

The activity of ammonia-oxidizing archaea (AOA) leads to the loss of nitrogen from soil, pollution of water sources and elevated emissions of greenhouse gas. To date, eight AOA genomes are available in the public databases, seven are from the group I.1a of the Thaumarchaeota and only one is from the group I.1b, isolated from hot springs. Many soils are dominated by AOA from the group I.1b, but the genomes of soil representatives of this group have not been sequenced and functionally characterized. The lack of knowledge of metabolic pathways of soil AOA presents a critical gap in understanding their role in biogeochemical cycles. Here, we describe the first complete genome of soil archaeon Candidatus Nitrososphaera evergladensis, which has been reconstructed from metagenomic sequencing of a highly enriched culture obtained from an agricultural soil. The AOA enrichment was sequenced with the high throughput next generation sequencing platforms from Pacific Biosciences and Ion Torrent. The de novo assembly of sequences resulted in one 2.95 Mb contig. Annotation of the reconstructed genome revealed many similarities of the basic metabolism with the rest of sequenced AOA. Ca. N. evergladensis belongs to the group I.1b and shares only 40% of whole-genome homology with the closest sequenced relative Ca. N. gargensis. Detailed analysis of the genome revealed coding sequences that were completely absent from the group I.1a. These unique sequences code for proteins involved in control of DNA integrity, transporters, two-component systems and versatile CRISPR defense system. Notably, genomes from the group I.1b have more gene duplications compared to the genomes from the group I.1a. We suggest that the presence of these unique genes and gene duplications may be associated with the environmental versatility of this group.

Pubmed ID: 24999826

Research resources used in this publication

None found

Antibodies used in this publication

None found

Associated grants

None

Publication data is provided by the National Library of Medicine ® and PubMed ®. Data is retrieved from PubMed ® on a weekly schedule. For terms and conditions see the National Library of Medicine Terms and Conditions.

This is a list of tools and resources that we have found mentioned in this publication.


MIRA (tool)

RRID:SCR_010731

Sequence assembler and mapper for whole genome shotgun and EST/RNASeq sequencing data.

View all literature mentions

MUSCLE (tool)

RRID:SCR_011812

Multiple sequence alignment method with reduced time and space complexity.Multiple sequence alignment with high accuracy and high throughput. Data analysis service for multiple sequence comparison by log- expectation.

View all literature mentions

PhyML (tool)

RRID:SCR_014629

Web phylogeny server based on the maximum-likelihood principle.

View all literature mentions

Visual Statistics Group (tool)

RRID:SCR_008317

The general goal is to achieve a deeper understanding of natural image statistics because from this knowledge it should be possible to explain the behavior of the visual cortex and propose new alternatives in a number of applications in image processing and computer vision in which the basic problem is the choice of an appropriate signal representation. The range of basic and applied topics in which we are currently working include: * Mathematical models of human vision * Statistical image models * Image distortion metrics * Image coding * Motion estimation * Video coding * Image restoration * Color representation

View all literature mentions