COLAUTTI LAB

Change is Constant

The Colautti Lab investigates rapid evolution in a changing world

Human activity is causing rapid changes to the earth's ecosystems, benefitting some species with adverse effects on others. We investigate how human activity is changing genes, genomes and phenotypic traits of species in nature, and how this in turn affects the viability of species. Our approach combines cutting-edge advances in genomics and computational biology with experiments in controlled and natural environments. We think knowledge from these experiments can help improve human health and management of ecosystem services threatened by global change.

Will Evolution Save Us?

Evolution can happen very fast in nature, but it has limits.

We are currently researching hard limits to evolutionary change that may be important for understanding how species evolve in response to human activity over the next century. This research grew from our empirical work on the invasive plant Lythrum salicaria (see below), and it's a good example of how basic research on non-model systems can provide new scientific insigth.

Our first paper on this topic is now published and available (Free, Open Access): Effects of species interactions on the potential for evolution at species' range limits

This 10 minute YouTube video summarizes our ongoing work. The video was recorded in June 2021 for the (Virtual) Evolution 2021 conference, held annually by the Society for the Study of Evolution (SSE), Society of Systematic Biologists (SSB) and the American Society of Naturalists (ASN).

COVID-19 & SARS-CoV-2

Our lab's expertise in Data Science and Genomics have been put to use in COVID-19 research, including genome sequencing of SARS-CoV-2 genomes -- the virus responsible for the disease more commonly known as COVID-19. This work is currently ongoing with collaborators from Queen's University and Kingston Health Sciences Centre including Dr. Prameet Sheth, Dr. Calvin Sjaarda and others (see coauthors on papers linked below).

Phlogenomics of early-stage COVID-19 patients in Ontario, Canada

Our first research paper (published in Nature Scientific Reports) describes our sequencing of SARS-CoV-2 genomes using two different technologies, including a 'handheld' nanopore-based sequencer called the MinION by Oxford Nanopore. We analyzed SARS-CoV-2 genomes using evolutionary phylogenetics to identify sources of introduction and spread among the first COVID-19 cases in eastern Ontario. This work shows how portable sequencers and applied evolution can improve the public health response to emerging pandemics.

Fully reproducible code for this project is available on GitHub.

Temporal Dynamics and Evolution of SARS-CoV-2 in Ontario, Canada

Different genetic lineages (i.e. variants) have different mutations that may affect the rate of spread of COVID-19. In this study published in eSphere, we found variable infection rates in different lineages through time. Even in these early stages of the pandemic, variability in infection rates and the growing number of genetic lineages was cause for concern.

Metabolomics and Immune Response

Current projects (unpublished) track the immune response of COVID-19 patients and use chemistry of nasal swabs to identify biochemical changes in COVID-19 patients. These provide insights into the pathology of SARS-CoV-2, potential therapeutic targets, and the need for age-specific booster shots.

Ticks & tick-borne diseases

In situ detection, characterization, and risk assessment of tick-borne pathogens

Our 2021 opinion paper makes the case for a transdisciplinary research programme in vector-borne diseases, published in Trends in Parasitology

Rates of Lyme disease and other tick-borne illnesses are rapidly increasing in Canada and the United States. To better address this growing threat to human health, we are taking a multidisciplinary and integrated approach for in situ detection, characterization, and risk management of tick-borne pathogens. The objectives of this project are:

1. Screen for known pathogens and identify environmental factors affecting disease risk.
2. Develop and test field protocols and analytical tools for in situ microbiome analysis of tick, human and pet samples. This includes identification of known pathogens including distinct strains of Borrelia (the causative agent of Lyme disease).
3. Build bioinformatics tools to match microbial DNA sequences between ticks and bite victims to identify candidates for new and emerging pathogens.
4. Develop new risk assessment tools that, for medical educators, public health officials, and the affected populace, using updated models of risk of tick-borne pathogens.

Media coverage:

2021

Tick Sequencing:
CTV | CTV (website) | National Post | Globe & Mail | CBC Radio Ottawa | Toronto Star | Kingston Whig-Standard

Tick Surveys:
Ottawa Citizen | Global Kingston | gate.io CTV Ottawa | CTV Ottawa Website | May 2021 Press Release

2020

Tick Surveys:
Queen's Gazette | CTV | Global | ICI(CBC) Radio-Canada | Ottawa Sun | Whig-Standard | Kingston Herald

Open-source for Open Science

baRcodeR

baRcodeR is a tool for generating unique identifier strings and printable Linear or 2D (QR) barcodes. It improves repeatability of labelling biological samples and facilitates data collection, tracking and curating.

Available for R and on the web

Features:

1. Graphical interface (R Studio) and command line options : install.packates(baRcodeR) in R
2. Generate simple ID codes (Ex001, Ex002, Ex003,…)
3. Generate hierarchical (i.e. nested) ID codes (Pop01-Trt01-01:00, Pop01-Trt01-02:45, Pop01-Trt02-01:00, Pop01-Trt-02-02:45, Pop02-Trt01-01:00,…)
4. Generate printable PDF files of paired ID codes and QR barcodes
5. Customize the PDF layout for any type of printable format (e.g, vinyl stickers, waterproof paper)
6. Generate reproducible code for archival purposes (e.g. in publications or online repositories)
7. Create CSV files to link unique IDs and sampling hierarchy with downstream data collection workflows.
8. Integration with the PyTrackDat pipeline to set up a web-based data collection platform: PyTrackDat

baRcodeR links:

Invasive Species and Evolution:

Rapid evolution facilitates invasion of invasive purple loosestrife

Climate and biotic interactions (e.g. herbivores, pollinators) can dramatically affect survival and reproduction in plants. We are combining genome and transcriptome sequencing with a large field experiment at the Queen’s University Biological Station (QUBS) to understand ecological and genetic factors that promote or constrain rapid adaptation in invasive Lythrum salicaria (purple loosestrife). This research helps to understand the role that evolution plays in the spread of invasive species.

Key references:

Science | PNAS

Media coverage:

CBC | Popular Science | io9

Invasive Species and Evolution:

Null and Neutral Models of Evolution

Rapid evolution of local adaptation may play an important role in the spread of invasive species, however it can be very difficult to detect when evolution has occurred, and how much it has contributed to invasion. We have been carefully reassessing published evidence for evolution to determine the extent to which evolution has contributed to the spread of invasive species.

This 30 minute YouTube video was recorded at the 2023 Invasomics Workshop in Hamilton, New Zealand. It discusses the importance of null models for inferring adaptive evolution during biological invasions and some of the unique challenges for defining null models in these systems.

P-PLANT Project

Predicting Plant Local Adaptation in the Northwest Territories

A major challenge for resource extraction and industrial development in Northern Canada is lack of access to biological resources for restoring disturbed habitats to near-pristine states.

The P-PLANT project is a collaboration with the Aurora Research Institute in the Northwest Territories. We are applying genomic tools and field studies to characterize population genetic structure in native species used in restoration and reclamation projects. Many of these species can be difficult to distinguish based on morphological characteristics, and the extent to which populations are differentiated and adapted to local conditions is largely unknown. Our research will help restoration projects maintain the integrity of locally adapted populations.