Generated November 3, 2020

Complete Genome Sequence of the Novel Roseimicrobium sp. Strain ORNL1, a Verrucomicrobium Isolated from the Populus deltoides Rhizosphere

Introduction

This narrative was used for a complete genome sequence of a Roseimicrobium species, which belongs to the Verrucomicrobia phylum. This phylum is found in many environments, but very few members have been cultured. This publication sequences an example isolated from a rhizosphere of a Populus deltoides tree in Oak Ridge, TN.

The publication by Mircea Podar, Joel Turner, Leah H. Burdick, and Dale A. Pelletier can be found here: https://mra.asm.org/content/9/27/e00617-20

Table of Contents

  1. Prior Methods
  2. Import and Annotation
  3. Compute ANI with FastANI
  4. Metabolic Modelling
  5. References

Narrative created by Mircea Podar, edited by Zachary Crockett

Prior Methods

Sample Collection and Isolation

A root-associated soil sample was taken from the rhizophere of a mature forest Populus deltoides in Oak Ridge, TN. Single cells were selected using flow cytometry on agar-containing DSMZ medium and incubated at 28°C. Taxonomic classification was performed using small-subunit rRNA gene sequencing. The colony was found to have 99% identity with Roseimicrobium gellanilyticum which is a species of Verrucomicrobia isolated in Japan.

Sequencing

A culture of the isolated strain was grown at 30°C for 3 days, and then genomic DNA was isolated. The DNA was sequenced, quality filtered, and assembled in the PacBio SMRTLink v8.0 pipeline, resulting in a polished contig 7,957,557 nt long. Gene prediction and functional annotation were performed using NCBI PGAP1. A metabolic model was generated in KBase, shown below.

Import and Annotation

The assembled reads were imported, along with an assembly and Genbank genome from a related organism, Roseimicrobium gellanilyticum. The isolate reads were then annotated using RASTtk through the Annotate Microbial Assembly App.

Import a FASTA file from your staging area into your Narrative as an Assembly data object
This app completed without errors in 59s.
Objects
Created Object Name Type Description
Roseimicrobium_populi Assembly Imported Assembly
Links
Annotate a bacterial or archaeal assembly using components from the RAST (Rapid Annotations using Subsystems Technology) toolkit (RASTtk).
This app completed without errors in 9m 1s.
Objects
Created Object Name Type Description
Roseimicrobium_populi_genome Genome Annotated genome
Summary
The RAST algorithm was applied to annotating a genome sequence comprised of 1 contigs containing 7957748 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, 7088 new features were called, of which 136 are non-coding.
Output genome has the following feature types:
	Coding gene                     6952 
	Non-coding repeat                 62 
	Non-coding rna                    74 
Overall, the genes have 1832 distinct functions. 
The genes include 3318 genes with a SEED annotation ontology across 947 distinct SEED functions.
The number of distinct functions can exceed the number of genes because some genes have multiple functions.
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/56021
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
Roseimicrobium_gellanilyticum Genome Imported Genome
Links
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/56021
v1 - KBaseGenomes.Genome-11.0
The viewer for the data in this Cell is available at the original Narrative here: https://narrative.kbase.us/narrative/56021

Compute ANI with FastANI

The previously imported assemblies were compared using FastANI, which reported the same 99% identity as cited in the paper.

Allows users to compute fast whole-genome Average Nucleotide Identity (ANI) estimation.
This app completed without errors in 1m 54s.
Links

Metabolic Modeling

The annotated genome object created above was used for metabolic modeling using the Build Metabolic Model App with default parameters and gapfilling.

Generate a draft metabolic model based on an annotated genome.
This app completed without errors in 2m 16s.
Objects
Created Object Name Type Description
Roseimicrobium_populi_model FBAModel FBAModel-12 Roseimicrobium_populi_model
Roseimicrobium_populi_model.gf.0 FBA FBA-13 Roseimicrobium_populi_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/56021
v1 - KBaseFBA.FBAModel-12.0
The viewer for the data in this Cell is available at the original Narrative here: https://narrative.kbase.us/narrative/56021

References

  1. 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. doi:10.1093/nar/gkw569.

Apps

  1. Annotate Microbial Assembly with RASTtk - v1.073
    • [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.vThe 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] Altschul SF, Madden TL, Schaffer AA, Zhang J, Zhang Z, Miller W, Lipman DJ. Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Res. 1997;25: 3389-3402. doi:10.1093/nar/25.17.3389
    • [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] Meyer F, Overbeek R, Rodriguez A. FIGfams: yet another set of protein families. Nucleic Acids Res. 2009;37 6643-54. doi:10.1093/nar/gkp698.
    • [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
  2. 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.
  3. Compute ANI with FastANI
    • [1] Jain C, Rodriguez-R LM, Phillippy AM, Konstantinidis KT, Aluru S. High-throughput ANI Analysis of 90K Prokaryotic Genomes Reveals Clear Species Boundaries. 2017; doi:10.1101/225342
    • [2] Goris J, Konstantinidis KT, Klappenbach JA, Coenye T, Vandamme P, Tiedje JM. DNA-DNA hybridization values and their relationship to whole-genome sequence similarities. Int J Syst Evol Microbiol. 2007;57: 81 91. doi:10.1099/ijs.0.64483-0
    • FastANI module and source code:
  4. Import FASTA File as Assembly from Staging Area
    no citations
  5. Import GenBank File as Genome from Staging Area
    no citations