Terriglobus albidus ORNL
Mircea Podar, Zach Crockett
Generated June 15, 2020

Complete Genome Sequence of Terriglobus albidus Strain ORNL, an Acidobacterium Isolated from the Populus deltoides Rhizosphere

Introduction

This Narrative was used for a complete genome sequence of a new strain of Terriglobus albidus. It is a heterotrophic bacterium associated with the rhizophere of the eastern cottonwood tree (Populus deltoides).

The publication by Mircea Podar, Joel Turner, Leah Burdick, and Dale Pelletier can be found here https://mra.asm.org/content/ga/8/46/e01065-19.full.pdf.

Table of Contents

  1. Sample Collection, Isolation, and Sequencing
  2. Import, QC, and Annotation
  3. Metabolic Modeling
  4. References

Sample Collection, Isolation, and Sequencing

Sample Collection

Cells from a root sample from a Populus deltoides rhizosphere in Oak Ridge, Tennessee, were selected by flow cytometry and incubated on R2A medium at 28°C.

Isolation

The colonies that grew were identified using 16S rRNA sequencing. The colony selected has 99.8% identify with a previously identified Terriglobus albidus strain1. The isolated strain was grown in liquid R2A for five days.

Sequencing

The isolated was sequenced on a Pacific Biosciences instrument and assembled using a PacBio pipeline. Sequencing produced 78,854 filtered subreads which were assembled into a 6,405,582 bp contig. NCBI PGAP v4.82 identified 5,010 protein coding sequences, 47 tRNAs, 1 rRNA operon, and 3 noncoding RNAs.

Metabolic modeling was done in KBase based on RAST annotations, as shown below.

Import, QC, and Annotation

  1. FASTA and Genbank files from the PacBio Pipeline were imported using default parameters.
  2. CheckM was used to assess the quality of the FASTA assembly.
  3. Both the FASTA assembly and the Genbank genome were annotated with RAST using the Annotate Microbial Assembly and Annotate Microbial Genome Apps, respectively.
Import FASTA File as Assembly from Staging Area
Import a FASTA file from your staging area into your Narrative as an Assembly data object
This app completed without errors in 1m 3s.
Objects
Created Object Name Type Description
Terriglobus_A1.fasta_assembly Assembly Imported Assembly
Report
Links
  • report.html - HTML summary report for Imported Assembly
Import GenBank File as Genome from Staging Area
Import a GenBank file from your staging area into your Narrative as a Genome data object
This app completed without errors in 2m 9s.
Objects
Created Object Name Type Description
Terriglobus.gb_genome Genome Imported Genome
Report
Links
  • report.html - HTML summary report for imported Genome
Output from Import GenBank File as Genome from Staging Area
The viewer for the output created by this App is available at the original Narrative here: https://narrative.kbase.us/narrative/44746
Assess Genome Quality with CheckM - v1.0.8
Runs the CheckM lineage workflow to assess the genome quality of isolates, single cells, or genome bins from metagenome assemblies
This app completed without errors in 8m 48s.
Report
Links
Files
These are only available in the live Narrative: https://narrative.kbase.us/narrative/44746
  • full_output.zip - Full output of CheckM
  • plots.zip - Output plots from CheckM
Annotate Microbial Genome
Annotate or re-annotate bacterial or archaeal genome using RASTtk.
This app completed without errors in 2m 21s.
Objects
Created Object Name Type Description
Terriglobus_annotated Genome Annotated genome
Summary 
The RAST algorithm was applied to annotating an existing genome: Terriglobus albidus. 
The sequence for this genome is comprised of 1 contigs containing 6405582 nucleotides. 
The input genome has 5074 existing coding features and 110 existing non-coding features.
Input genome has the following feature types:
	Non-coding gene                   53 
	Non-coding ncRNA                   2 
	Non-coding rRNA                    3 
	Non-coding regulatory              4 
	Non-coding tRNA                   47 
	Non-coding tmRNA                   1 
	gene                            5074 
A scan was conducted for the following additional feature types: rRNA; crispr.
The genome features were functionally annotated using the following algorithm(s): Kmers V2; Kmers V1; protein similarity.
In addition to the remaining original 5074 coding features and 110 non-coding features, 3 new features were called, of which 3 are non-coding.
Output genome has the following feature types:
	Coding gene                     5074 
	Non-coding gene                   53 
	Non-coding ncRNA                   2 
	Non-coding rRNA                    3 
	Non-coding regulatory              4 
	Non-coding rna                     3 
	Non-coding tRNA                   47 
	Non-coding tmRNA                   1 
Overall, the genes have 1999 distinct functions. 
The genes include 3577 genes with a SEED annotation ontology across 1040 distinct SEED functions.
The number of distinct functions can exceed the number of genes because some genes have multiple functions.
Output from Annotate Microbial Genome
The viewer for the output created by this App is available at the original Narrative here: https://narrative.kbase.us/narrative/44746
Annotate Microbial Assembly
Annotate a bacterial or archaeal assembly using components from the RAST (Rapid Annotations using Subsystems Technology) toolkit (RASTtk).
This app completed without errors in 7m 1s.
Objects
Created Object Name Type Description
Terriglobus_RAST Genome Annotated genome
Summary 
The RAST algorithm was applied to annotating a genome sequence comprised of 1 contigs containing 6405582 nucleotides. 
No initial gene calls were provided.
Standard features were called using: glimmer3; prodigal.
A scan was conducted for the following additional feature types: rRNA; tRNA; selenoproteins; pyrrolysoproteins; repeat regions; crispr.
The genome features were functionally annotated using the following algorithm(s): Kmers V2; Kmers V1; protein similarity.
In addition to the remaining original 0 coding features and 0 non-coding features, 5615 new features were called, of which 205 are non-coding.
Output genome has the following feature types:
	Coding gene                     5410 
	Non-coding repeat                155 
	Non-coding rna                    50 
Overall, the genes have 2001 distinct functions. 
The genes include 2500 genes with a SEED annotation ontology across 1042 distinct SEED functions.
The number of distinct functions can exceed the number of genes because some genes have multiple functions.

Metabolic Modeling

The Build Metabolic Model App was used to created a gapfilled metabolic model based on the RAST-annotated Genbank genome.

Output from Annotate Microbial Assembly
The viewer for the output created by this App is available at the original Narrative here: https://narrative.kbase.us/narrative/44746
Build Metabolic Model
Generate a draft metabolic model based on an annotated genome.
This app completed without errors in 2m 47s.
Objects
Created Object Name Type Description
Terriglobus_model FBAModel FBAModel-11 Terriglobus_model
Terriglobus_model.gf.0 FBA FBA-13 Terriglobus_model.gf.0
Report
Output from Build Metabolic Model
The viewer for the output created by this App is available at the original Narrative here: https://narrative.kbase.us/narrative/44746
Terriglobus_model
v1 - KBaseFBA.FBAModel-11.0
The viewer for the data in this Cell is available at the original Narrative here: https://narrative.kbase.us/narrative/44746

References

  1. Pascual J, Wust PK, Geppert A, Foesel BU, Huber KJ, Overmann J. 2015. Terriglobus albidus sp. nov., a member of the family Acidobacteriaceae isolated from Namibian semiarid savannah soil. Int J Syst Evol Microbiol 65:3297–3304. https://doi.org/10.1099/ijsem.0.000411.
  2. Tatusova T, DiCuccio M, Badretdin A, Chetvernin V, Nawrocki EP, Zaslavsky L, Lomsadze A, Pruitt KD, Borodovsky M, Ostell J. 2016. NCBI Prokaryotic Genome Annotation Pipeline. Nucleic Acids Res 44: 6614 – 6624. https://doi.org/10.1093/nar/gkw569.

Apps

  1. Annotate Microbial Assembly
    • Aziz RK, Bartels D, Best AA, DeJongh M, Disz T, Edwards RA, et al. The RAST Server: Rapid Annotations using Subsystems Technology. BMC Genomics. 2008;9: 75. doi:10.1186/1471-2164-9-75
    • Brettin T, Davis JJ, Disz T, Edwards RA, Gerdes S, Olsen GJ, et al. RASTtk: a modular and extensible implementation of the RAST algorithm for building custom annotation pipelines and annotating batches of genomes. Sci Rep. 2015;5: 8365. doi:10.1038/srep08365
    • Overbeek R, Olson R, Pusch GD, Olsen GJ, Davis JJ, Disz T, et al. The SEED and the Rapid Annotation of microbial genomes using Subsystems Technology (RAST). Nucleic Acids Res. 2014;42: D206-214. doi:10.1093/nar/gkt1226
  2. Annotate Microbial Genome
    • [1] Aziz RK, Bartels D, Best AA, DeJongh M, Disz T, Edwards RA, et al. The RAST Server: Rapid Annotations using Subsystems Technology. BMC Genomics. 2008;9: 75. doi:10.1186/1471-2164-9-75
    • [2] Overbeek R, Olson R, Pusch GD, Olsen GJ, Davis JJ, Disz T, et al. The SEED and the Rapid Annotation of microbial genomes using Subsystems Technology (RAST). Nucleic Acids Res. 2014;42: D206 D214. doi:10.1093/nar/gkt1226
    • [3] Brettin T, Davis JJ, Disz T, Edwards RA, Gerdes S, Olsen GJ, et al. RASTtk: A modular and extensible implementation of the RAST algorithm for building custom annotation pipelines and annotating batches of genomes. Sci Rep. 2015;5. doi:10.1038/srep08365
    • [4] Kent WJ. BLAT The BLAST-Like Alignment Tool. Genome Res. 2002;12: 656 664. doi:10.1101/gr.229202
    • [5] Camacho C, Coulouris G, Avagyan V, Ma N, Papadopoulos J, Bealer K, et al. BLAST+: architecture and applications. BMC Bioinformatics. 2009;10: 421. doi:10.1186/1471-2105-10-421
    • [6] Lowe TM, Eddy SR. tRNAscan-SE: a program for improved detection of transfer RNA genes in genomic sequence. Nucleic Acids Res. 1997;25: 955 964.
    • [7] Cobucci-Ponzano B, Rossi M, Moracci M. Translational recoding in archaea. Extremophiles. 2012;16: 793 803. doi:10.1007/s00792-012-0482-8
    • [8] Siguier P, Perochon J, Lestrade L, Mahillon J, Chandler M. ISfinder: the reference centre for bacterial insertion sequences. Nucleic Acids Res. 2006;34: D32 D36. doi:10.1093/nar/gkj014
    • [9] van Belkum A, Sluijuter M, de Groot R, Verbrugh H, Hermans PW. Novel BOX repeat PCR assay for high-resolution typing of Streptococcus pneumoniae strains. J Clin Microbiol. 1996;34: 1176 1179.
    • [10] Croucher NJ, Vernikos GS, Parkhill J, Bentley SD. Identification, variation and transcription of pneumococcal repeat sequences. BMC Genomics. 2011;12: 120. doi:10.1186/1471-2164-12-120
    • [11] Hyatt D, Chen G-L, Locascio PF, Land ML, Larimer FW, Hauser LJ. Prodigal: prokaryotic gene recognition and translation initiation site identification. BMC Bioinformatics. 2010;11: 119. doi:10.1186/1471-2105-11-119
    • [12] Delcher AL, Bratke KA, Powers EC, Salzberg SL. Identifying bacterial genes and endosymbiont DNA with Glimmer. Bioinformatics. 2007;23: 673 679. doi:10.1093/bioinformatics/btm009
    • [13] Akhter S, Aziz RK, Edwards RA. PhiSpy: a novel algorithm for finding prophages in bacterial genomes that combines similarity- and composition-based strategies. Nucleic Acids Res. 2012;40: e126. doi:10.1093/nar/gks406
  3. Assess Genome Quality with CheckM - v1.0.18
    • Parks DH, Imelfort M, Skennerton CT, Hugenholtz P, Tyson GW. CheckM: assessing the quality of microbial genomes recovered from isolates, single cells, and metagenomes. Genome Res. 2015;25: 1043 1055. doi:10.1101/gr.186072.114
    • CheckM source:
    • Additional info:
  4. Build Metabolic Model
    • [1] Henry CS, DeJongh M, Best AA, Frybarger PM, Linsay B, Stevens RL. High-throughput generation, optimization and analysis of genome-scale metabolic models. Nat Biotechnol. 2010;28: 977 982. doi:10.1038/nbt.1672
    • [2] Overbeek R, Olson R, Pusch GD, Olsen GJ, Davis JJ, Disz T, et al. The SEED and the Rapid Annotation of microbial genomes using Subsystems Technology (RAST). Nucleic Acids Res. 2014;42: D206 D214. doi:10.1093/nar/gkt1226
    • [3] Latendresse M. Efficiently gap-filling reaction networks. BMC Bioinformatics. 2014;15: 225. doi:10.1186/1471-2105-15-225
    • [4] Dreyfuss JM, Zucker JD, Hood HM, Ocasio LR, Sachs MS, Galagan JE. Reconstruction and Validation of a Genome-Scale Metabolic Model for the Filamentous Fungus Neurospora crassa Using FARM. PLOS Computational Biology. 2013;9: e1003126. doi:10.1371/journal.pcbi.1003126
    • [5] Mahadevan R, Schilling CH. The effects of alternate optimal solutions in constraint-based genome-scale metabolic models. Metab Eng. 2003;5: 264 276.
  5. Import FASTA File as Assembly from Staging Area
    no citations
  6. Import GenBank File as Genome from Staging Area
    no citations