Nocardioides sp. str. WV_118_6 Genome
Jennifer Goff, Chris Hahn, Julia Maresca, Rebecca Ingrassia
Generated May 5, 2024

Nocardioides sp. sp. str. WV_118_6 Genome.

Abstract

Microbial consortia can be applied to the bioremediation of organofluorine compounds, a class of highly persistent environmental contaminants. Here we report the genome sequence of Nocardioides sp. str. WV_118_6 (referred to in this narrative by an older name: PFAS_118_6)—isolated from MFA minimal medium containing 2uM fluoroacetic acid.

Introduction

Genome associated with "Genome sequences of four bacterial strains isolated from organofluorine compound enrichment cultures"

The publication by Jennifer L. Goff, Chris Hahn, Rebecca A. Ingrassia, Chanistha Tiyapun, Gray G. Waldschmidt, Emma R. Smith, Miranda N. Marini, Olga Shevchenko, Julia A. Maresca is located at [url]

This Narrative explored the genome of and identified one colony type from the four colony types cultured from Wilmington Wastewater Treatment Plant influent sample. Nocardioides sp. was the result of this Narrative's genomic investigation described in detail below. These aerobic bacteria, a part of the Actinobacterium phylum, are gram positive, appear rod-like to cocci-form and can survive in low-nutrient conditions. They have outstanding degradation qualities such as high degradation rates and the ability to degrade pollutants considered hard-to-degrade(1).

Note that WV_118_6 = PFAS_118_6

Table of Contents

  1. Background and Experimental Methods
  2. Import and annotation
  3. QC, Assembly, and Annotation
  4. Taxonomic Classification
  5. Metabolic Modeling and Flux Balance Analysis
  6. References
Narrative created by: Rebecca Ingrassia

Background and Experimental Methods

Sample Collection

Samples collected in April 2019 at the Wilmington Wastewater Treatment Plant were inoculated into MFA minimal medium containing 2 uM fluoroacetic acid.

Isolation

In March 2020 this sample was kept in 12% glycerol then revived in 2021. Following transfer into a minimal medium containing 200 uM MFA then a month-long incubation, 20 uL of the culture was plated on a plate containing a solid minimal media with 1% yeast extract. Four different kinds of colonies resulted. Two colonies per colony type were chosen for LB cultivation spanning 2 days.A phenol-chloroform extraction protocol was used to extract DNA then the each isolate’s 16S gene was amplified then sequenced with 8F and 1492R primers used (2),(3).

Genome Sequencing

The PacBio SMRTbell Express template preparation kit v.2.0 was used to barcode and prepare a SMRT library. Larger DNA fragments over 6kb in length, were size selected by BluePippin (Sage Science). Using a fragment analyzer, the average library fragment size of 12kb was determined (Advanced Analytical Technologies, Inc.). A PacBio Sequel Ile single-molecule sequencer was used to complete sequencing in a 1 M v.3 LR SMRT Cell with a 30-h movie followed by demultiplexing by PacBio SMRT Link v.11. The N50 was 9900 and there were 35,425 reads.

Import

This sequenced genome was imported using a third party app, Globus and unpacked using Unpack a Compressed File in Staging Area-v1.0.12

Unpack a Compressed File in Staging Area - v1.0.12
Unpack a compressed file in the staging area.
This app completed without errors in 27s.
Summary
Uploaded Files: 1 PFAS_Genomes/demultiplex.118.6-bc2063.hifi_reads.fastq

QC, Assembly, and Annotation

1.) High-quality reads were obtained by filtering the raw reads using the app Filtlong v0.2.1

2.) This genome was assembled using the Flye app v2.9.2, which uses the Quality Assesment Tool for Genome Assemblies (QUAST).

3.) Further quality checking was performed with CheckM v1.0.18.

4.) RASTtk v1.073 was used to annotate this genome.

5.) The genome is made up of 1 contig, has a GC content of 72.74% and is 5555804 bp in length.

6.) The circular genome was depicted via the Circular Genome Visualization Tool application.

7.) The circular genome was trimmed and rotated in Flye automatically.

Filter Reads with Filtlong - v0.2.1
Filter long reads using Filtlong.
This app completed without errors in 1m 35s.
Objects
Created Object Name Type Description
PFAS_118_6_filtlong.reads SingleEndLibrary Filtered reads
Summary
Running run_kb_filtlong with params: { "workspace_name": "jgoff:narrative_1706820512139", "workspace_id": 169435, "input_reads_library": "169435/6/1", "input_short_paired_library": null, "output_reads_name": "PFAS_118_6_filtlong.reads", "min_read_length": 1000, "keep_percent": 90, "target_bases": 500000000 } Getting long reads (from reads library object). command: filtlong --min_length 1000 --keep_percent 90 --target_bases 500000000 /kb/module/work/tmp/e0e510f7-5e18-4041-b6e9-775ca3729c73.single.fastq > /kb/module/work/tmp/filtlong_output_7d8c2f68-9d0b-4a9b-914b-e167097c3bc0.fastq Scoring long reads 47 reads (488776 bp) 94 reads (984307 bp) 142 reads (1471740 bp) 188 reads (1973100 bp) 239 reads (2462540 bp) 291 reads (2949580 bp) 341 reads (3439226 bp) 388 reads (3923407 bp) 435 reads (4413035 bp) 488 reads (4899491 bp) 538 reads (5391237 bp) 587 reads (5884306 bp) 635 reads (6370237 bp) 681 reads (6853961 bp) 732 reads (7340636 bp) 781 reads (7834279 bp) 828 reads (8324106 bp) 879 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reads (341397706 bp) 34514 reads (341883203 bp) 34561 reads (342368578 bp) 34610 reads (342852805 bp) 34659 reads (343344136 bp) 34710 reads (343843229 bp) 34760 reads (344330779 bp) 34811 reads (344829419 bp) 34855 reads (345316171 bp) 34906 reads (345803883 bp) 34955 reads (346291800 bp) 35009 reads (346777634 bp) 35057 reads (347267564 bp) 35107 reads (347757293 bp) 35157 reads (348246673 bp) 35205 reads (348738884 bp) 35251 reads (349223435 bp) 35300 reads (349710166 bp) 35350 reads (350199452 bp) 35401 reads (350687211 bp) 35450 reads (351172706 bp) 35493 reads (351657589 bp) 35538 reads (352150286 bp) 35585 reads (352637700 bp) 35632 reads (353126380 bp) 35682 reads (353612892 bp) 35732 reads (354111070 bp) 35779 reads (354598181 bp) 35833 reads (355082266 bp) 35884 reads (355567213 bp) 35935 reads (356052651 bp) 35987 reads (356552890 bp) 36037 reads (357044705 bp) 36085 reads (357529314 bp) 36136 reads (358019318 bp) 36187 reads (358522414 bp) 36236 reads (359011589 bp) 36285 reads (359498750 bp) 36332 reads (359988895 bp) 36385 reads (360475077 bp) 36435 reads (360965040 bp) 36485 reads (361450365 bp) 36536 reads (361935770 bp) 36588 reads (362427051 bp) 36638 reads (362918749 bp) 36681 reads (363402371 bp) 36732 reads (363888448 bp) 36783 reads (364379870 bp) 36830 reads (364868708 bp) 36883 reads (365359519 bp) 36929 reads (365846130 bp) 36981 reads (366335379 bp) 37031 reads (366819889 bp) 37078 reads (367310357 bp) 37124 reads (367806078 bp) 37174 reads (368296252 bp) 37221 reads (368787518 bp) 37267 reads (369279712 bp) 37315 reads (369775128 bp) 37367 reads (370270890 bp) 37409 reads (370764500 bp) 37456 reads (371254510 bp) 37504 reads (371752133 bp) 37555 reads (372238572 bp) 37604 reads (372722804 bp) 37653 reads (373206596 bp) 37708 reads (373702490 bp) 37759 reads (374186363 bp) 37811 reads (374683630 bp) 37861 reads (375170853 bp) 37912 reads (375659412 bp) 37961 reads (376151151 bp) 38012 reads (376635527 bp) 38061 reads (377124765 bp) 38108 reads (377622390 bp) 38155 reads (378109477 bp) 38203 reads (378598406 bp) 38254 reads (379084880 bp) 38302 reads (379577746 bp) 38353 reads (380061974 bp) 38403 reads (380548106 bp) 38451 reads (381031997 bp) 38501 reads (381522097 bp) 38550 reads (382007673 bp) 38601 reads (382498072 bp) 38645 reads (382986739 bp) 38692 reads (383471547 bp) 38742 reads (383960777 bp) 38795 reads (384451687 bp) 38847 reads (384946954 bp) 38896 reads (385435163 bp) 38946 reads (385925623 bp) 38994 reads (386417549 bp) 39043 reads (386904483 bp) 39083 reads (387388801 bp) 39134 reads (387872967 bp) 39186 reads (388361522 bp) 39208 reads (388602307 bp) Filtering long reads target: 349742076 bp keeping 349752517 bp Outputting passed long reads Uploading filtered reads: PFAS_118_6_filtlong.reads Generating and saving report. Filtlong results saved.
PFAS_118_6_filtlong.reads
v1 - KBaseFile.SingleEndLibrary-2.1
The viewer for the data in this Cell is available at the original Narrative here: https://narrative.kbase.us/narrative/169435
PFAS_118_6_filtlong.reads
v1 - KBaseFile.SingleEndLibrary-2.1
The viewer for the data in this Cell is available at the original Narrative here: https://narrative.kbase.us/narrative/169435
Assemble Long Reads with Flye - v2.9.2
Assemble long reads using the Flye assembler.
This app completed without errors in 27m 28s.
Objects
Created Object Name Type Description
PFAS_118_6_CLR_flye.contigs2 Assembly Assembled contigs
Report
Summary
Flye results saved to: jgoff:narrative_1706820512139//kb/module/work/tmp/flye_41dbb935-9e46-48c9-81e1-c00216ca5c5f Assembly saved to: jgoff:narrative_1706820512139/PFAS_118_6_CLR_flye.contigs2 Assembled into 1 contigs. Avg Length: 5555804.0 bp. Contig Length Distribution (# of contigs -- min to max basepairs): 0 -- 5555803.5 to 5555803.6 bp 0 -- 5555803.6 to 5555803.7 bp 0 -- 5555803.7 to 5555803.8 bp 0 -- 5555803.8 to 5555803.9 bp 0 -- 5555803.9 to 5555804.0 bp 1 -- 5555804.0 to 5555804.1 bp 0 -- 5555804.1 to 5555804.2 bp 0 -- 5555804.2 to 5555804.3 bp 0 -- 5555804.3 to 5555804.4 bp 0 -- 5555804.4 to 5555804.5 bp
Links
Files
These are only available in the live Narrative: https://narrative.kbase.us/narrative/169435
  • flye_output.zip - Output file(s) generated by Flye
PFAS_118_6_CLR_flye.contigs2
v1 - KBaseGenomeAnnotations.Assembly-5.1
The viewer for the data in this Cell is available at the original Narrative here: https://narrative.kbase.us/narrative/169435
Assess Genome Quality with CheckM - v1.0.18
Runs the CheckM lineage workflow to assess the genome quality of isolates, single cells, or genome bins from metagenome assemblies through comparison to an existing database of genomes.
This app completed without errors in 5m 2s.
Report
Links
Files
These are only available in the live Narrative: https://narrative.kbase.us/narrative/169435
  • CheckM_summary_table.tsv.zip - TSV Summary Table from CheckM
  • full_output.zip - Full output of CheckM
  • plots.zip - Output plots from CheckM
Annotate Genome/Assembly with RASTtk - v1.073
Annotate or re-annotate genome/assembly using RASTtk (Rapid Annotations using Subsystems Technology toolkit).
This app completed without errors in 7m 9s.
Objects
Created Object Name Type Description
RIGenomeAssembly2 Genome RAST re-annotated genome
Report
Summary
The RAST algorithm was applied to annotating a genome sequence comprised of 1 contigs containing 5555804 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, 5488 new features were called, of which 97 are non-coding. Output genome has the following feature types: Coding gene 5391 Non-coding repeat 45 Non-coding rna 52 The number of distinct functions can exceed the number of genes because some genes have multiple functions.
Links
RIGenomeAssembly2
v1 - KBaseGenomes.Genome-11.1
The viewer for the data in this Cell is available at the original Narrative here: https://narrative.kbase.us/narrative/169435
Circular Genome Visualization Tool
Generate a map and annotations of circular genomes using CGView.
This app completed without errors in 3m 14s.
Report
Links
Files
These are only available in the live Narrative: https://narrative.kbase.us/narrative/169435
  • KBase_derived_RIGenomeAssembly2.png
  • KBase_derived_RIGenomeAssembly2.jpg
  • KBase_derived_RIGenomeAssembly2.svg

Taxonomic Identification

1.) Classify Microbes with GTDB-Tk-v1.7.0 taxonomically identified the genome as Nocardioides sp. using default parameters.

2.) A phylogenetic tree was generated using the Insert Genome into SpeciesTree v2.2.0 application.

Classify Microbes with GTDB-Tk - v1.7.0
Obtain objective taxonomic assignments for bacterial and archaeal genomes based on the Genome Taxonomy Database (GTDB) ver R06-RS202
This app completed without errors in 37m 29s.
Report
Links
Insert Genome Into SpeciesTree - v2.2.0
Add one or more Genomes to a KBase SpeciesTree.
This app completed without errors in 3m 37s.
Report
Links
Files
These are only available in the live Narrative: https://narrative.kbase.us/narrative/169435
  • RItree.newick
  • RItree-labels.newick
  • RItree.png
  • RItree.pdf

Metabolic Modeling and Flux Balance Analysis

MS2-Build Prokaryotic Metabolic Models was used to analyze which metabolic pathways this organism utilizes. Additionally MS2-Improved Gapfill Metabolic Models and Run Flux Balanace Analysis help us to investigate the minimum required biochemical reactions for a desired flux in metabolic models and to use Flux Balance Analysis (FBA) to predict fluxes in the metabolic models using certain media, respectively.

MS2 - Build Prokaryotic Metabolic Models
Using ModelSEED2 pipeline, construct draft metabolic models based on input annotated genomes.
This app completed without errors in 18m 20s.
Objects
Created Object Name Type Description
RIGenomeAssembly2.mdl FBAModel
Report
Links
RIGenomeAssembly2.mdl
v1 - KBaseFBA.FBAModel-15.0
The viewer for the data in this Cell is available at the original Narrative here: https://narrative.kbase.us/narrative/169435
MS2 - Improved Gapfill Metabolic Models
Identify the minimal set of biochemical reactions to add to draft metabolic models to enable them to produce a desired flux in a specified media.
This app completed without errors in 13m 29s.
Objects
Created Object Name Type Description
RIGenomeAssembly2.mdl.gf FBAModel
Report
Links
Run Flux Balance Analysis
Predict metabolite fluxes in a metabolic model of an organism grown on a given media using flux balance analysis (FBA).
This app completed without errors in 25s.
Objects
Created Object Name Type Description
PFAS_118_6_FBA FBA FBA-13 PFAS_118_6_FBA
Report
Summary
A flux balance analysis (FBA) was performed on the metabolic model 169435/33/1 growing in Complete media.
Output from Run Flux Balance Analysis
The viewer for the output created by this App is available at the original Narrative here: https://narrative.kbase.us/narrative/169435

References

(1) Ma Y, Wang J, Liu Y, Wang X, Zhang B, Zhang W, Chen T, Liu G, Xue L, Cui X. 2023. Nocardioides: "Specialists" for Hard-to-Degrade Pollutants in the Environment. Molecules. 21:7433

(2) Alexandrino DAM, Ribeiro I, Pinto LM, Cambra R, Oliveira RS, Pereira F, Carvalho MF. 2018. Biodegradation of mono-, di- and trifluoroacetate by microbial cultures with different origins. New Biotechnol 43:23–29.

(3) Kiledal EA, Maresca JA. 2023. Chromosomal DNA extraction from Gram-positive bacteria, V3. protocols.io.

Released Apps

  1. 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:
  2. Circular Genome Visualization Tool
    no citations
  3. Insert Genome Into SpeciesTree - v2.2.0
    • Price MN, Dehal PS, Arkin AP. FastTree 2 Approximately Maximum-Likelihood Trees for Large Alignments. PLoS One. 2010;5. doi:10.1371/journal.pone.0009490
  4. MS2 - Build Prokaryotic Metabolic Models with OMEGGA
    • [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. MS2 - Improved Gapfill Metabolic Models with OMEGGA
    • [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] Henry CS, Jankowski MD, Broadbelt LJ, Hatzimanikatis V. Genome-Scale Thermodynamic Analysis of Escherichia coli Metabolism. Biophysical Journal. 2006;90: 1453 1461. doi:10.1529/biophysj.105.071720
    • [3] Jankowski MD, Henry CS, Broadbelt LJ, Hatzimanikatis V. Group Contribution Method for Thermodynamic Analysis of Complex Metabolic Networks. Biophysical Journal. 2008;95: 1487 1499. doi:10.1529/biophysj.107.124784
    • [4] Henry CS, Zinner JF, Cohoon MP, Stevens RL. iBsu1103: a new genome-scale metabolic model of Bacillus subtilisbased on SEED annotations. Genome Biology. 2009;10: R69. doi:10.1186/gb-2009-10-6-r69
    • [5] Orth JD, Thiele I, Palsson B . What is flux balance analysis? Nature Biotechnology. 2010;28: 245 248. doi:10.1038/nbt.1614
    • [6] Latendresse M. Efficiently gap-filling reaction networks. BMC Bioinformatics. 2014;15: 225. doi:10.1186/1471-2105-15-225
    • [7] 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
  6. Run Flux Balance Analysis
    • 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
    • Orth JD, Thiele I, Palsson B . What is flux balance analysis? Nature Biotechnology. 2010;28: 245 248. doi:10.1038/nbt.1614
  7. Unpack a Compressed File in Staging Area - v1.0.12
    • Arkin AP, Cottingham RW, Henry CS, Harris NL, Stevens RL, Maslov S, et al. KBase: The United States Department of Energy Systems Biology Knowledgebase. Nature Biotechnology. 2018;36: 566. doi: 10.1038/nbt.4163

Apps in Beta

  1. Annotate Genome/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. 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] 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. Assemble Long Reads with Flye - v2.9.2
    • [1] Mikhail Kolmogorov, Jeffrey Yuan, Yu Lin and Pavel Pevzner, "Assembly of Long Error-Prone Reads Using Repeat Graphs", Nature Biotechnology, 2019 doi:10.1038/s41587-019-0072-8
  3. Classify Microbes with GTDB-Tk - v1.7.0
    • Pierre-Alain Chaumeil, Aaron J Mussig, Philip Hugenholtz, Donovan H Parks, GTDB-Tk: a toolkit to classify genomes with the Genome Taxonomy Database, Bioinformatics, Volume 36, Issue 6, 15 March 2020, Pages 1925 1927. DOI: https://doi.org/10.1093/bioinformatics/btz848
    • Parks, D., Chuvochina, M., Waite, D. et al. A standardized bacterial taxonomy based on genome phylogeny substantially revises the tree of life. Nat Biotechnol 36, 996 1004 (2018). DOI: https://doi.org/10.1038/nbt.4229
    • Parks DH, Chuvochina M, Chaumeil PA, Rinke C, Mussig AJ, Hugenholtz P. A complete domain-to-species taxonomy for Bacteria and Archaea. Nat Biotechnol. 2020;10.1038/s41587-020-0501-8. DOI:10.1038/s41587-020-0501-8
    • Rinke C, Chuvochina M, Mussig AJ, Chaumeil PA, Dav n AA, Waite DW, Whitman WB, Parks DH, and Hugenholtz P. A standardized archaeal taxonomy for the Genome Taxonomy Database. Nat Microbiol. 2021 Jul;6(7):946-959. DOI:10.1038/s41564-021-00918-8
    • Matsen FA, Kodner RB, Armbrust EV. pplacer: linear time maximum-likelihood and Bayesian phylogenetic placement of sequences onto a fixed reference tree. BMC Bioinformatics. 2010;11:538. Published 2010 Oct 30. doi:10.1186/1471-2105-11-538
    • Jain C, Rodriguez-R LM, Phillippy AM, Konstantinidis KT, Aluru S. High throughput ANI analysis of 90K prokaryotic genomes reveals clear species boundaries. Nat Commun. 2018;9(1):5114. Published 2018 Nov 30. DOI:10.1038/s41467-018-07641-9
    • Hyatt D, Chen GL, Locascio PF, Land ML, Larimer FW, Hauser LJ. Prodigal: prokaryotic gene recognition and translation initiation site identification. BMC Bioinformatics. 2010;11:119. Published 2010 Mar 8. DOI:10.1186/1471-2105-11-119
    • Price MN, Dehal PS, Arkin AP. FastTree 2--approximately maximum-likelihood trees for large alignments. PLoS One. 2010;5(3):e9490. Published 2010 Mar 10. DOI:10.1371/journal.pone.0009490 link: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2835736/
    • Eddy SR. Accelerated Profile HMM Searches. PLoS Comput Biol. 2011;7(10):e1002195. DOI:10.1371/journal.pcbi.1002195
  4. Filter Reads with Filtlong - v0.2.1
    • [1] Wick RR, 2017. Filtlong.