Phagocyte Biology Laboratory

Dr. Bryan Heit, Western University

About Us

Welcome! You have reached the homepage for the laboratory of Dr. Bryan Heit. Our lab is part of the Department of Microbiology and Immunology at Western University, and we are members of the Center for Human Immunology, the lead centre for the CIHR Human Immunology Network.

Our interests surround the function of phagocytes – white blood cells which ingest (phagocytose) pathogens, particles, and dead cells. We focus on the cellular and molecular processes which control the function of these cells during the maintenance of homeostasis, infection and chronic inflammatory disease. Central to most of our studies is the study of efferoctyosis – the phagocytic removal of apoptotic (dying) cells, and how failures in this process lead to inflammation, autoimmunity and infection.

What is a Phagocyte?

Phagocytes are a class of white blood cells which have the capacity to engulf large particles such as bacterial and fungal pathogens, and subsequently destroy the engulfed material. The term phagocyte literally translates to “cell that eats”, which is an apt description of the primary function of these cells in our bodies. While there are many types of phagocytes, the Heit lab focuses primarily on macrophages, which play key roles in both maintaining our bodies and in fighting infections.

Lab News

Using Evolution to Understand Phagocytes

MERTK Evolution

Quantifying MERTK Evolution

The Heit lab is excited to announce the publication of our most recent study, which uses evolution as a tool to investigate the biology of the receptor MERTK.

Every day the normal turnover of cells in our tissues results in the production of around 100 billion dying cells. These dying cells must be removed to keep our tissues healthy. MERTK plays a central role in this process – in fact, MERTK is one of the major receptors used by cells such as macrophages to recognise and remove these dying cells. In humans, defects in MERTK function can lead to many diseases including retinitis pigmentosa – a form of blindness, autoimmune diseases such as multiple sclerosis, heart diseases such as atherosclerosis, and even infertility. Furthermore, viruses such as HIV and Ebola, as well as some cancers, use MERTK to gain access to our cells and to manipulate our immune system. Despite these multiple roles in human health, we still have a poor understanding of how MERTK functions.

In our newest study, currently available as a corrected proof at Molecular Biology and Evolution, we use an evolutionary approach to better understand the function of MERTK. Unexpectedly, we discovered that MERTK has undergone recent positive selection – a form of evolution rarely observed in human genes. Further investigation into this evolution revealed that human MERTK has evolved to be present in smaller amounts on our macrophages than in our ancestors, while simultaneously evolving to self-structure into miniature “islands” on the macrophage surface. While it may seem counter-intuitive to reduce the amount of an important gene expressed by our cells, as this would make the gene less able to do its work, the lower expression decreased the ability of viruses to parasitize MERTK-expressing cells. The increase in MERTK clustering evolved to counteract this decreased expression, through enhancing the avidity of MERTK. Thus, MERTK has evolved to limit the extent to which viruses can parasitize it, and compensates for the reduced levels of MERTK by increasing its avidity.

The evolutionary trend we observed is especially exciting as it is consistent with a form of evolution termed “antagonistic coevolution”, or more commonly referred to as the red queen hypothesis. In this form of evolution, a pathogen and its host become locked in an arms-race, in which advantages gained by evolution of the host are rapidly counteracted by coevolution of the pathogen. The end-effect is a zero-sum change in the interaction between the host and the pathogen – i.e. the host and pathogen still survive, despite being better “armed” to fight each other.

Evolution aside, the observation that MERTK is structured into preformed islands on the cell surface is of great interest, as this type of clustering is often a result of interactions with other proteins. As such, these “islands” may represent a previously unsubscribed interaction between MERTK and some form of human-specific co-receptor. The Heit lab is currently investigating this possibility, in the hopes that by understanding these newly evolved interactions that we may gain further insights into the human diseases caused by MERTK dysfunction.

Reference:
Evans AL, Blackburn JW, Taruc K, Kipp A, Dirk BS, Hunt NR, Barr SD, Dikeakos JD, Heit B. Antagonistic Coevolution of MER Tyrosine Kinase Expression and Function. Mol Biol Evol. 2017 Mar 23. Pubmed ID: 28369510.

Another successful open house

A few times each year the University of Western Ontario opens its doors to the public, to give prospective students and other interested parties a look inside of our programs. The last open house was over this weekend, and was a smashing success. If you’d like to attend a future open house, or to hear or see more from the Heit lab, follow our labs twitter account.

Image Processing Resources

In the Heit lab we utilise a large range of quantitative image analysis techniques, using a variety of image processing programs. These techniques are used to extract information on protein interactions, cell morphology, cell signalling pathway activity, cell behaviours, and many other aspects of cell activity. Not only do we utilise these tools, but we also develop new tools which we share with the research community – tools such as microscopy-based quantitative efferocytosis assays, and software for analysing super-resolution images.

There are many excellent tools out there for image analysis – the two most heavily used in the Heit lab are the free program ImageJ, as well as the ImageJ variant FIJI. ImageJ is a free and open-source image processing software program that will run in nearly any operating system, and whose capacity is easily expandable through a large library of plugins (programmers can also develop their own plugins). FIJI is a variant of ImageJ which has a number of very useful plugins pre-installed, and which has been extensively documented at the FIJI wiki. Help for both software packages can be found on the ImageJ forums.

Bioimage Data Analysis CoverBut as useful as these packages are, the major factor limiting their broader acceptance by the research community is the difficulty in using the software. ImageJ/FIJI is intuitive for users already experienced in image analysis, but has a very steep learning curve for individuals new to the image processing scene. The huge number of plugins and tools available in these software packages, combined with documentation that often assumes a high degree of imaging expertise, makes these software packages hard for new users to approach.

Over this weekend I cam across two resources which close this gap. Both are free e-textbooks intended to introduce the new (or experienced) image analysis user to various software resources and techniques. The first of these books – Analyzing fluorescence microscopy images with ImageJ is a detailed guide to using ImageJ for image analysis. The book starts with the basics – what are pixels, image file formats, etc, and guides the user through the most common forms of image analysis, all in the ImageJ environment. The second book is Bioimage Data Analysis, also a free book, but registration is required. This book covers ImageJ as well as a range of other free and commercial image analysis packages, and includes some sample protocols for more advanced image analysis routines. Of particular note, this second text includes an extensive chapter on writing ImageJ macros, a “super-user” method can can largely automate many image analysis tasks.

These books have become a new part of my labs standard training materials, and I encourage anyone interested in – or even experts in – image analysis to download and read these excellent resources.

References:

Bankhead, Peter. Analyzing fluorescence microscopy images with ImageJ. https://www.gitbook.com/book/petebankhead/imagej-intro/details

 

Miura, Kota (editor). Bioimage Data Analysis. http://www.imaging-git.com/applications/bioimage-data-analysis-0

Rab17 and Antigen Fate

Rab17 Abstract2017 in nearly upon us, but the Heit lab was able to squeeze out one last paper in 2016. This is an exciting moment for our lab, as this study was the major focus of our work for nearly five years. Our goal in this study was to understand how macrophages decide how to respond to the different types of targets they encounter in tissues. This decision-making process is coordinated by Rab17, which selectively diverts non-infectious materials away from parts of the macrophage used to initiate anti-pathogen immune responses.

This decision making process is a key function of macrophages, as these cells are tasked with both “housekeeping duties” (e.g. removing the dead and dying cells that form normally in our bodies) and with anti-pathogen defence. Both dying self-cells and pathogens are internalized and degraded by macrophages, and it is at this point that macrophages need to make a key decision – whether to present these degraded materials to other immune cells, thus activating a broader immune response. Making this decision correctly is critically important as presenting degraded self-cells to your immune system may lead to an autoimmune disease such as multiple sclerosis or rheumatoid arthritis, whereas failing to present a degraded pathogen may enable infection.

How this “decision” is made was not clear – until now. By recovering macrophage vacuoles containing beads which mimicked either dead cells or pathogens, and then using mass spectrometry to identify the proteins present on each vacuole, we were able to identify the protein Rab17 as a protein selectively recruited to the dead cell-containing vacuole. Microscopy-based studies then determined that this protein directs degraded dead cell materials to an organelle called the “recycling endosome”, where that material is either absorbed or expelled by the macrophage. Rab17 does not accumulate on pathogen-containing vacuoles, thereby preventing recycling of degraded pathogens. Instead, degraded pathogens are trafficked to a different organelle, where they are loaded on the MHC II molecules that present the degraded pathogen to the immune system.

Reference: Yin C, Kim Y, Argintaru D, Heit B. Rab17 mediates differential antigen sorting following efferocytosis and phagocytosis. Cell Death and Disease. 2016 Dec 22;7(12):e2529. [PubMed][Article]

Twitter Feed

Here's what some of the people we follow are saying:

Upcoming Events

April 7-10, 2017
Canadian Society for Immunology Annual Meeting - Banff, Alberta


April 20th, 2017
RGE Murray Seminar Series - Dr. Martin McGavin, Western University


May 4th, 2017
RGE Murray Seminar Series - Dr. Bhagirath Singh, Western University


May 16-20, 2017
Canadian Society for Molecular Biology Annual Conference - Ottawa, Canada.


WordPress Appliance - Powered by TurnKey Linux