Welcome to my presentation.
I will demonstrate how MicrobeTrace was easily adapted to deploy the HantaNet tool for hantavirus
genomic epidemiology and surveillance.
HantaNet is a hantavirus-specific visualization and analysis tool powered by MicrobeTrace
that facilitates data integration and sharing of standardized sequence and metadata of the
hantavirus genome.
We built three modules containing pre-loaded reference datasets of the Small, Medium and
Large genes.
You can customize views and build dashboards in HantaNet.
And since HantaNet is a browser-based visualization tool, it is secure and remains operational
without an internet connection which protects sensitive data.
Users can download the reference dataset and use it to standardize their own data for visualization
and analysis.
Networks and phylogenetic trees are two different ways to visualize the genetic relatedness
of sequences.
This is the Medium gene module displaying the network and unrooted phylogenetic tree
after applying the TN93 nucleotide substitution model.
Both views show genetic clustering of new sequences in yellow.
Networks are easier to explore because a distance cut-off can be applied to see the differences
in formation of genetic links.
In this case the cut-off is point-two.
Networks also simplify visualization of gene reassortment, a mechanism for evolution of
viruses with segmented genomes.
I will demonstrate how to build a dashboard in HantaNet to analyze new hantavirus sequences.
First, accept the license agreement and launch the module of interest.
Load the metadata and fasta files and make sure the correct file type is selected.
Re-launch the module and if needed, unpin the nodes and centralize the network.
You can change the color of the nodes representing the new sequences; for example, I changed
the node color to yellow.
There are two different strains in this cluster so I decreased the genetic distance cut-off
to remove the link and separate them.
Now open the map view and choose to display nodes by state.
Note the genetic links in the map.
Select to view the timeline based on the collection date to display geographic and temporal data.
Drag the network tile next to the map tile to build the dashboard view.
Move the tables and views to the desired positions.
Now play the timeline and see the appearance of nodes and clusters by collection date and
geographic location.
The map view can be customized to add tooltip and adjust the transparency of the links.
You can add more tiles or views to your dashboard.
As you can see, this is a very user-friendly process.
Previously, we analyzed the Large gene of Sin Nombre viruses collected in the United States.
We observed two main groups which we named SNV1 and SNV2.
The nearest neighbor algorithm was applied to prune the genetic links to keep the connection
between the closest nodes.
This is equivalent to the minimum-spanning tree and the link width is proportional to
the genetic distance.
The yellow nodes represent the sequences of interest, which could be outbreak or new sequences.
The network was overlayed on the map to perform a spatio-temporal analysis
of domestic Sin Nombre variants.
In this video, we observe the geographic location and spread of Sin Nombre variants in the United
States and potential human exposure locations based on sequence similarity of the viral
Large gene.
Nodes with a number label and available state and county-level data will appear in the map.
Finally, in this model of hantavirus active targeted surveillance, we anticipate the need
for bioinformatic tools that allow for real-time data integration, visualization and analysis...
and this can be possible with MicrobeTrace.
In conclusion, HantaNet is a model on how to deploy pathogen-specific tools with MicrobeTrace
for genomic surveillance, epidemiology and outbreak response.
I want to acknowledge the HantaNet project team.
And please visit the project sites in GitHub and feel free to contact the MicrobeTrace
Team for technical support, collaborations or to request a demo.
I have included a link in the chat and in this slide or scan the QR code to complete
a short survey about MicrobeTrace.
Thank you.