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dnaapler

Dnaapler is a simple tool that reorients complete circular microbial genomes.

Quick Start

# creates empty conda environment
conda create -n dnaapler_env

# activates conda environment
conda activate dnaapler_env

# installs dnaapler
conda install -c bioconda dnaapler

# runs dnaapler all 
dnaapler all -i input_mixed_contigs.fasta -o output_directory_path -p my_bacteria_name -t 8

# runs dnaapler chromosome
dnaapler chromosome -i input_chromosome.fasta -o output_directory_path -p my_bacteria_name -t 8

Paper

Dnaapler has been published in JOSS here. If you use Dnaapler in your work, please cite it as follows:


George Bouras, Susanna R. Grigson, Bhavya Papudeshi, Vijini Mallawaarachchi, Michael J. Roach (2024). Dnaapler: A tool to reorient circular microbial genomes. Journal of Open Source Software, 9(93), 5968, https://doi.org/10.21105/joss.05968

Additionally, please consider citing the dependencies where relevant:

Altschul S.F., Gish W., Miller W., Myers E.W., Lipman D.J. Basic local alignment search tool. J Mol Biol. 1990 Oct 5;215(3):403-10. doi: 10.1016/S0022-2836(05)80360-2. PMID: 2231712.

Steinegger M, Söding J. MMseqs2 enables sensitive protein sequence searching for the analysis of massive data sets. Nat Biotechnol. 2017 Nov;35(11):1026-1028. doi: 10.1038/nbt.3988.

Larralde, M., (2022). Pyrodigal: Python bindings and interface to Prodigal, an efficient method for gene prediction in prokaryotes. Journal of Open Source Software, 7(72), 4296, https://doi.org/10.21105/joss.04296.

Hyatt, D., Chen, GL., LoCascio, P.F. et al. Prodigal: prokaryotic gene recognition and translation initiation site identification. BMC Bioinformatics 11, 119 (2010). https://doi.org/10.1186/1471-2105-11-119.

v1

For example - on my machine (Ubuntu 20.04, Intel i9 13th gen 13900 CPU with 32 threads), for a Staphylococcus aureus genome with 1 small plasmid, dnaapler -i staph.fasta -o staph_dnaapler -t 8 took ~129 seconds wallclock with v0.8.1 using BLAST, while it took ~3 seconds wallclock with v1.0.0 using MMseqs2.

Google Colab Notebooks

If you don't want to install dnaapler locally, you can run dnaapler all without any code using the Google Colab notebook.

Table of Contents

Description

<p align="center"> <img src="paper/Dnaapler_figure.png" alt="Dnaapler Figure"> </p>

dnaapler is a simple python program that takes a single nucleotide input sequence (in FASTA format), finds the desired start gene using MMseqs2 against an amino acid sequence database, checks that the start codon of this gene is found, and if so, then reorients the chromosome to begin with this gene on the forward strand.

It was originally designed to replicate the reorientation functionality of Unicycler with dnaA, but for for long-read first assembled chromosomes. We have extended it to work with plasmids (dnaapler plasmid) and phages (dnaapler phage), or for any input FASTA desired with dnaapler custom, dnaapler mystery or dnaapler nearest.

For bacterial chromosomes, dnaapler chromosome should ensure the chromosome breakpoint never interrupts genes or mobile genetic elements like prophages. It is intended to be used with good-quality completed bacterial genomes, generated with methods such as Trycycler, Dragonflye or my own pipeline hybracter.

Additionally, you can also reorient multiple bacterial chromosomes/plasmids/phages at once using the dnaapler bulk subcommand.

If your input FASTA is mixed (e.g. has chromosome and plasmids), you can also use dnaapler all, with the option to ignore some contigs with the --ignore parameter.

Documentation

The full documentation for dnaapler can be found here.

Commands

Installation

dnaapler requires only MMseqs2 v13.45111 as an external dependency.

Installation from conda is highly recommended as this will install MMseqs2 automatically.

Conda

dnaapler is available on bioconda.

conda install -c bioconda dnaapler

Pip

You can also install dnaapler with pip.

pip install dnaapler

Usage

Usage: dnaapler [OPTIONS] COMMAND [ARGS]...

Options:
  -h, --help     Show this message and exit.
  -V, --version  Show the version and exit.

Commands:
  all         Reorients contigs to begin with any of dnaA, repA...
  archaea     Reorients your genome to begin with the archaeal COG1474...
  bulk        Reorients multiple genomes to begin with the same gene
  chromosome  Reorients your genome to begin with the dnaA chromosomal...
  citation    Print the citation(s) for this tool
  custom      Reorients your genome with a custom database
  largest     Reorients your genome the begin with the largest CDS as...
  mystery     Reorients your genome with a random CDS
  nearest     Reorients your genome the begin with the first CDS as...
  phage       Reorients your genome to begin with the terL large...
  plasmid     Reorients your genome to begin with the repA replication...

Usage: dnaapler all [OPTIONS]

Reorients contigs to begin with any of dnaA, repA, terL or archaeal COG1474 Orc1/cdc6

Options:
-h, --help               Show this message and exit.
-V, --version            Show the version and exit.
-i, --input PATH         Path to input file in FASTA format  [required]
-o, --output PATH        Output directory   [default: output.dnaapler]
-t, --threads INTEGER    Number of threads to use with MMseqs2  [default: 1]
-p, --prefix TEXT        Prefix for output files  [default: dnaapler]
-f, --force              Force overwrites the output directory
-e, --evalue TEXT        e value for MMseqs2  [default: 1e-10]
--ignore PATH            Text file listing contigs (one per row) that are to
                         be ignored
-a, --autocomplete TEXT  Choose an option to autocomplete reorientation if
                         MMseqs2 based approach fails. Must be one of: none,
                         mystery, largest, or nearest [default: none]
--seed_value INTEGER     Random seed to ensure reproducibility.  [default:
                         13]

The reoriented output FASTA will be {prefix}_reoriented.fasta in the specified output directory.

Example Usage

dnaapler all -i input.fasta -o output_directory_path -p my_genome_name --ignore list_of_contigs_to_ignore.txt

dnaapler chromosome -i input.fasta -o output_directory_path -p my_bacteria_name -t 8

dnaapler phage -i input.fasta -o output_directory_path -p my_phage_name -t 8

dnaapler plasmid -i input.fasta -o output_directory_path -p my_plasmid_name -t 8

dnaapler archaea -i input.fasta -o output_directory_path -p my_archaea_name -t 8

dnaapler custom -i input.fasta -o output_directory_path -p my_genome_name -t 8 -c my_custom_database_file

dnaapler mystery -i input.fasta -o output_directory_path -p my_genome_name

dnaapler nearest -i input.fasta -o output_directory_path -p my_genome_name

dnaapler largest -i input.fasta -o output_directory_path -p my_genome_name

# to reorient multiple bacterial chromosomes
dnaapler bulk -i input_file_with_multiple_chromosomes.fasta -m chromosome -o output_directory_path -p my_genome_name

Databases

dnaapler chromosome uses 584 proteins downloaded from Swissprot with the query "Chromosomal replication initiator protein DnaA" on 24 May 2023 as its database for dnaA. All hits from the query were also filtered to ensure "GN=dnaA" was included in the header of the FASTA entry.

dnaapler plasmid uses the repA database curated by Ryan Wick in Unicycler.

dnaapler phage uses a terL database curated using PHROGs. All the AA sequences of the 55 phrogs annotated as 'large terminase subunit' were downloaded, combined and depduplicated using seqkit seqkit rmdup -s -o terL.faa phrog_terL.faa.

dnaapler archaea uses a database of 403 archaeal COG1474 Orc1/cdc6 genes curated from here.

dnaapler all uses all four databases combined into one.

dnaapler custom uses a custom amino acid FASTA format file that you specify using -c.

The matching is strict - it requires a strong MMseqs2 match (default e-value 1E-10), and the first amino acid of a MMseqs2 hit gene to be identified as Methionine, Valine or Leucine, the 3 most used start codons in bacteria/phages.

For the most commonly studied microbes (ESKAPE pathogens, etc), the dnaA database should suffice.

If you try dnaapler on a more novel or under-studied microbe with a dnaA gene that has little sequence similarity to the database, you may need to provide your own dnaA gene(s) in amino acid FASTA format using dnaapler custom.

After this issue, dnaapler mystery was added. It predicts all ORFs in the input using pyrodigal, then picks a random gene to re-orient your sequence with.

Motivation

  1. I couldn't get Circlator to work and it is no longer supported.
  2. berokka doesn't orient chromosomes to begin with dnaa.
  3. After reading Ryan Wick's masterful bacterial genome assembly tutorial, I realised that it is probably optimal to run 2 polishing steps, once before then once after rotating the chromosome, to ensure the breakpoint is polished. Further, for some "complete" long read bacterial assemblies that didn't circularise properly, I figured that as long as you have a complete assembly (even if not "circular" as marked as in Flye), polishing after a re-orientation would be likely to circularise the chromosome. A bit like Ryan's rotate_circular_gfa.py script, without the requirement of strict circularity.
  4. While researching MGEs in S. aureus whole genome sequences, I repeatedly found instances where MGEs were interrupted by the chromosome breakpoint. So I thought I'd add a tool to automate it in my pipeline.
  5. It's probably good to have all your sequences start at the same location for synteny analyses.

Contributing

If you would like to help improve dnaapler you are very welcome!

For changes to be accepted, they must pass the CI checks.

Please see CONTRIBUTING.md for more details.

Acknowledgements

Thanks to Torsten Seemann, Ryan Wick and the Circlator team for their existing work in the space. Also to Michael Hall, whose repository tbpore we took and adapted a lot of scaffolding code from because he writes really nice code.