Semidán Robaina, September 2022.

In this Notebook, we will use Pynteny through its Python API to find candidate peptide sequences beloging to the leu operon of Escherichia coli.

• Note that we could have conducted the same search through Pynteny's command-line interface. Check out a more complete example based on Pynteny's command-line interface here.

• Find more info in the documentation pages!

Let's start by importing some required modules.

Let's now create a directory to store results

Download PGAP profile HMM database¶

Pynteny downloads the PGAP's profile HMM database by default from the NCBI webpage when no path to a HMM database is provided. However, we can also manually download PGAP's database within Python through the class Download, which will unzip and store files in the specified output directory. The metadata file will be parsed and filtered to remove HMM entries that are not available in the downloaded database (this is to avoid possible downstream errors). Here is how you would run it:

Build peptide sequence database¶

For this example, we are going to use the complete genome of E. coli's K-12 MG1655 in genbank format. Our final goal is to build a peptide sequence database in a single FASTA file where each record corresponds to an inferred ORF, which will display the positional information (i.e. ORF number within the parent contig as well as the DNA strand). To this end, we will run pynteny's subcommand build within Python through the class Build.

Since we are providing a genome which is already annotated (genbank file), we don't need to predict and translate ORFs as in the command-line example. Instead, Pynteny will directly label each ORF with a unique identifier and add positional metadata (with respect to the parent contig). The labels will be organized following the structure:

<genome ID>__<contig ID>_<gene position>_<locus start>_<locus end>_<strand>

where gene position, locus start, and locus end are taken with respect to the contig.

NOTE: You'll need E. coli's genome to follow this example. It's already downloaded in the repo (tests/test_data/MG1655.gb), but you can also download it here.

Search synteny structure in E. coli¶

Finally, we are going to use pynteny class Search to search for a specific syntenic block within the previously built peptide database. Specifically, we are interested in the following structure:

<leuD 0 <leuC 1 <leuA

With this synteny structure, we are searching for peptide sequences matching the profile HMM corresponding to these gene symbols, which are also arranged in this particular order, all in the negative (antisense) strand, as indicated by <, and which are located exactly next to each other in the same contig in the case of leuD and leuC, and with at most one ORF in between in the case of leuC and leuA (as indicated by a maximum number of in-between ORFs of 0 and 1, respectively.)

First, we need to initialize the class Search with the appropiate parameters to conduct our synteny-aware search. Find more info about the parameters in the wiki pages.

Some notes:

• The only required parameters are data, the path to the position-labeled peptide database and synteny_struc, a string containing the definition of the synteny block to search for

• Providing a path to the HMM database directory (parameter hmm_dir) is optional. If not provided, then pynteny will download and store the PGAP HMM database (only once if not previously downloaded) and use it to run the search. A custom HMM database provided in hmm_dir will override pynteny's default database

• We can also manually download the PGAP HMM database with the subcommand pynteny download, or within Python through the class Download as shown above.