GNA5031 Applied Session 3

Student's copy for case study - Phylogenetic reconstruction

1. Background

The application of wastewater-based epidemiology (WBE) to support the global response to the COVID-19 pandemic has shown encouraging outcomes. The accurate, sensitive, and high-throughput detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in municipal wastewater is critical for wastewater-based epidemiology. The origin the virus is valuable to inform public health measurements during the global response to the pandemic.

In winter 2021, several passengers from an international flight that landed in Brisbane, Australia, tested COVID-19-positive. The health authority suspected that these passengers carried the more virulent SARS-CoV-2 variant(s) that newly emerged in Brazil. The health authority then sent scientists to sample the wastewater in this passenger flight, isolate the corresponding SARS-CoV-2 nucleic acid (de-identified due to confidentiality) and then determine their genome sequences. In this case study, you will adopt phylogenetic techniques that were discussed during this week's lectures to trace the origin of the unknown SARS-CoV-2 variant(s) carried by these passengers. To achieve this goal, you will analyze the SARS-CoV-2 genome sequences derived from the wastewater samples and compare them with 500 reference genomes of known origin.

For more information of wastewater-based analysis of SARS-CoV-2, please refer to:

• study one
• study two

2. Learning Objectives:

At the conclusion of this session, students are expected to:

• Understand a genome file (with extension ".fasta")
• Align genomes using MAFFT
• Trim genomes using TrimAL
• Infer phylogenetic tree using IQTREE
• Visualize phylogenetic tree using ITOL

3. Prior knowledge: Accessing virtual machines and running commands to generate these files:

OBJECTIVES: Complete the following prerequisites, which are essential in following this practiacl session

In this course we will make extensive use of cloud computing and virtual machines. You have been provided credentials that will allow you to access these virtual machines 24/7. To access any remote server, we use the terminal and the ssh command. If you are on a mac or linux based PC, you will have a terminal in-built. If you are on a windows-based PC, please download PuTTY.

You can find the location of your virtual machine in Moodle Under week 2 Applied Session Activities- VM names

Note: You cannot share a VM, please jot down your virtual machine credentials.

The Monash VPN

Due to security constraints, our virtual machines can only be accessed from within the Monash network. You will need to first connect to the Monash Virtual Private Network (VPN). Detailed instructions can be found on the Monash website. Take the time now to install the VPN software and test your connection, this will be imperative for you accessing the VPN while offsite.

Accessing virtual machines using PuTTY- Windows

If you are using Windows you will access your virtual machines using PuTTY. PuTTY In the hostname (or IP address) box, enter the hostname that you were provided, ie. gna5031s1-XXXXXXXX-01.rep.monash.edu, where XXXXXX is your authcate . Ensure the connection type is SSH. Click open. You will be prompted to enter your username (authcate) and password in the terminal window. Enter your credentials and click enter. Note you will not see the characters as they are typed. You are now in your home directory on the VM.

Accessing virtual machines using the terminal app - Mac

To access your VM using the terminal app on Mac, search for the terminal app using the search bar in the top right hand corner of your computer. Type the following command ssh username@hostname where username is your authcate and hostname is gna5031s1-XXXXXXXX-01.rep.monash.edu, where XXXXXX is your authcate. Click enter, you will be asked for a password. Enter your Monash password and click enter. Note you will not see the characters as they are typed. You are now in your home directory on the VM.

Example:

ssh -x gnii0001@gna5031s1-gnii0001-01.rep.monash.edu

Register at ITOL

Note: Please register for a free account prior to the practical session, ITOL. This is for rendering a phylogenetic tree that we will generate in this session.

4. Hands-on component one (on your local PC)

OBJECTIVES: Learn to visualize files generated in each step of phylogenetic reconstruction, while facilitating understanding of the entire session.

4.1 Prepare local copy of data.

Press Download ZIP under Code from the following page: https://github.com/GreeningLab/GNA5031_applied3.git Decompress

Install Seaview for sequence and alignment visualisation, webpage.

Install Sublime Text 2 for working with text, webpage.

Note: Not restricted to a single text editor; if you have BBEdit from session, feel free to use it.

4.2 Visualize sequence data using Seaview

Under folder data_pregenerated:

Drag and drop input.fasta into Seaview Observe nucleotides and colors.

4.3 Visualize aligned data using Seaview

Drag and drop input.msa.fasta into Seaview Observe nucleotides and colors.

4.4 Visualize aligned and trimmed data using Seaview

Drag and drop input.msa.trimmed.fasta into Seaview Observe nucleotides and colors.

4.5 Inspect generated phylogenetic tree file using a text editor

Inspect input.msa.trimmed.treefile

5. Hands-on component two (virtual machine except last step)

OBJECTIVES: Learn to carry out phylogenetic reconstruction using the following steps. The result can help us to infer the origin of the virus based on wastewater monitoring.

Note: replace user_name with your own user name in from the following scripts

5.1 access to virtual machine, setting up directory for analysis

ssh -x user_name@gna5031s1-user_name-01.rep.monash.edu

Make sure you start in your home directory using tilde "~", which indicates home directory in Linux systems

cd ~

Download course material using git clone

git clone https://github.com/GreeningLab/GNA5031_applied3.git

Note: The required software is already installed for you in a conda environment. To activate the conda environment type:

conda activate gna5031

You'll need to do this every time you login.

5.2 Align sequences

Sequence alignment is a fundamental step in many bioinformatics applications, including phylogenetic inference and others. It allows us to identify regions of similarity and difference between two or more sequences. By aligning sequences, we can identify conserved regions, mutations, insertions, and deletions, among others. This information is useful for understanding the evolutionary relationships among the sequences, identifying functional domains, and detecting genetic variations that may be associated with disease or other phenotypes.

Common tools for alignment: MAFFT

Go to data directory

cd ~/GNA5031_applied3/data

mafft --preservecase --auto --reorder --thread -1 input.fasta > input.msa.fasta

If the above code runs without complaints, you have succeeded in this task.

5.3 Trim alignment

Trimming alignment is a common step in the process of inferring phylogenetic trees from molecular sequence data. The main reason for trimming alignment is to remove any poorly aligned or ambiguous regions in the sequence data that may affect the accuracy of the phylogenetic inference. Common tools for trimming: trimal

trimal -in input.msa.fasta  -out input.msa.trim.fasta -automated1

If the above code runs without complains, you have succeeded in this task.

5.4 Phylogenetic inference

Tree inference, also known as phylogenetic inference, is the process of reconstructing the evolutionary relationships among different organisms or groups of organisms based on their molecular or morphological characteristics. The resulting tree structure is called a phylogenetic tree, and it represents the evolutionary history of the group under study. The goal of tree inference is to reconstruct a tree that best explains the observed similarities and differences among the sequences or traits, while minimizing the number of evolutionary changes required to explain the data. A common tool is IQTREE.

iqtree -s input.msa.trim.fasta -alrt 1000 -bb 1000 -m TEST -nt 4

-s for input
-arlt for Replicates for SH approximate likelihood ratio test. The SH (Shimodaira-Hasegawa) test is a statistical test used to evaluate the support for different branches in a phylogenetic tree. Don't mind it for now.
-B for Replicates for ultrafast bootstrap (1000 is a commonly used number).
-m for model select. TEST is by testing several models.

When all analysis is done, exit analysis environment and exit virtual machine for good practice

conda deactivate
exit

If the above code runs without complaints, you have succeeded in this task.

5.5 Visualization of phylogenetic trees (exit virtual machine, return to your own computer)

iTOL (Interactive Tree Of Life) is a web-based tool that allows users to visualize and explore phylogenetic trees and other hierarchical data sets. It was developed by Ivica Letunic and Peer Bork at the European Molecular Biology Laboratory (EMBL) in Heidelberg, Germany, and has become a popular tool in the field of evolutionary biology and comparative genomics.

With iTOL, users can customize the display of their tree using a range of options, such as changing the layout, adding labels and annotations, and highlighting specific clades or branches. The tool also supports the integration of additional data sets, such as functional annotations or environmental information, which can be overlaid onto the tree to provide a more comprehensive view of the relationships between different organisms.

In addition to visualizing phylogenetic trees, iTOL can also be used to explore other types of hierarchical data sets, such as gene ontologies, protein domains, and metabolic pathways. The tool has a user-friendly interface and is freely available for use online, making it accessible to researchers and educators around the world.

Webpage: https://itol.embl.de/

4.5.1 Obtain the generated tree file

Note use pre_generated file if not ready For Mac user:

cd ~/Desktop 
mkdir tree_file
cd tree_file
scp user_name@gna5031s1-user_name-01.rep.monash.edu:/GNA5031_applied3/data/input.msa.trim.treefile .

For Windows user, use the pre-generated tree file - input.msa.trim.treefile

4.5.2 Upload to ITOL

Go to ITOL webpage press the following:

My Trees => Tree upload (drag and drop) => click on input.msa.trim.treefile to enter the tree

4.5.3 Tree exploration

After tree being uploaded, explore:

• circular or rectangular tree format
• Labels and Label options
• Advanced options
• Export options

Annotate tree labels with pre-generated file color.strip.txt Explore the following sections:

• Mandatory settings
• Actual data

Questions

• What is the meaning of MW240742.1 rgba(104,2,63,0.7) North America?
• What is the meaning of RFPL_1 rgba(255,215,0,0.7) RFPL_1?

4.5.4 Figure export

Export a pdf file for the rendered tree

Further exploration of tree styles at: https://itol.embl.de/gallery.cgi

Questions:

• Where is the likely origin of the viruses we found in this study?
• Are the SARS-CoV-2 variants carried by the passengers likely to have originated from the 2021 COVID-19 outbreak in Brazil as initially suspected?
• Is wastewater monitoring of SARS-CoV-2 a useful tool to trace the origin of the viruses?