Semidán Robaina, September 2022.

In this Notebook, we will use Pynteny through its command-line interface to find candidate peptide sequences beloging to the susC-susD gene pair within unannotated, fully sequenced, genomes of marine prokaryotic organisms.

The pair susC-susD is characteristic of the phylum Bacteroidota and allows these bacteria to feed on long polysaccharides collected from the environment through a "pedal-bin" mechanism. Bacteroidota is found across different environments, including the oceans, soil and our gut.

Interestingly, susC, a TomB-dependent membrane protein, has a number of known homologs, such as RagA and OmpW. Hence, labelling unannotated sequences as susC solely based on sequence similarity may be difficult to accomplish. Here, we are going to leverage the genomic context information of the pair susC-susD to reduce function annotation uncertainty. Since the gene pair is specific to Bacteroidota, wi will also explore the taxonomy assigned to the environmental sequences.

Note that we could have conducted the same search through Pynteny's python API. Find more info in the documentation pages. Let's start by importing some required modules.

Preprocess data¶

In this notebook, we will start directly with the already-built peptide database, which contains positional information in sequence labels. We have also previously downloaded the PGAP's profile HMM database.

These steps are shown here

Search synteny structure in MAR ref¶

We are going to use pynteny's search subcommand to search for the gene pair susC-susD within the MAR ref database:

>OMP_RagA_SusC 0 >SusD

Here, we are using the gene symbols as found in the metadata file of the PGAP's profile HMM database. We the above 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 positive (sense) strand, as indicated by >, and which are located exactly next to each other in the same contig (no ORFs allowed between them, as indicated by a maximum number of in-between ORFs of 0 in all cases.)

It would be interesting to compare the results generated by using the above synteny structure with those generated by simply matching the gene susC, that is, without considering genomic context. Hence, we will run pynteny's search subcommand also for this second case.

Pynteny has generated a number of output files in the provided output directory. HMMER3 hit results are stored within the subdirectory hmmer_outputs. The main output file, synteny_matched.tsv contains the labels of the matched sequences grouped by synteny block and sorted by gene number within their parent contig. The remaining (FASTA) files contain the retrieved peptide sequences for each gene symbol / HMM name in the synteny structure.

Assigning GTDB taxonomy to sequence hits¶

The pair susC-susD is specific to phylum Bacteroidota. Let's check if the taxonomy assigned to the retrieved sequences matches that phylum. To this end, we will extract that info from the MAR ref database itself, which provides a metadata file that contains GTDB taxonomical information for each genome in it.

Let's do some basic statistics¶

Alright, everything is ready. Let's briefly explore the results obtained by our pynteny searches. First, let's count the total number of hits correspondin to susC and to the pair susC-susD.

As expected, susC-susD received fewer hits than susC. Let's check next whether these hits belog to phylum Bacteroidota.

As expected, all hits to the pair susC-susD belog to Bacteroidota, as it is specific to that phylum. What about hits corresponding to susC alone?

Well, the majority still belong to Bacteroidota, but we see other phyla represented as well, particularly Proteobacteria.