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.
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.
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.
But 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.
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
2017 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.
We are excited to announce the publication of a collaborative study, investigating one mechanism which is used by HIV to evade the immune system. This study, a product of our long-standing collaboration with Jimmy Dikeako’s lab at Western University, discovered that the HIV protein Nef sequesters a key component of the immune system (MHC I) inside the cell. MHC I normally acts to present small fragments of pathogens such as HIV to immune cells, thereby allowing the immune system to identify and remove infected cells. By sequestering MHC I inside of infected cells, HIV “blinds” the immune system to its presence, allowing its infection to go unchecked.
This study builds upon the two previous collaborative studies produced by the Heit and Dikeakos lab – our initial description of the interaction between Nef and host cell proteins, and our development of new analysis methods for super-resolution microscopy.
Dirk BS, Pawlak EN, Johnson AL, Van Nynatten LR, Jacob RA, Heit B, Dikeakos JD. HIV-1 Nef sequesters MHC-I intracellularly by targeting early stages of endocytosis and recycling. Scientific Reports. 2016 Nov 14;6:37021. [Pubmed] [Article]
The Heit lab is excited to announce our latest publication titled Quantitative Efferocytosis Assays, and published in Methods in Molecular Biology [Pubmed] [Article]. This paper describes many of the microscopy and cell based methods we use to study efferocytosis – the processes by which cells such as macrophages identify, engage, engulf and destroy dying (apoptotic) cells.
Efferocytosis plays a key role in maintaining homeostasis. The normal turnover of cells produces tens of billions of dying cells every day which must be removed. During times of injury or infection, the numbers of dying cells generated in our body can reach astronomical proportions, with some studies estimating that as many as 100 billion dying cells are produced daily during these events. Defects in efferocytosis leads to a range of clinical conditions including inflammatory diseases such as atherosclerosis, and autoimmune diseases such as multiple sclerosis. The clinical burden and cost of these diseases is immense, as is the human toll they impart, and as a consequence, understanding efferocytosis is paramount for reducing the burden of these diseases.
A range of methods can be found in this paper, including techniques to prepare and label synthetic targets which mimic dying cells, techniques to prepare and label dying cells such that they are compatible with a range of assays, and techniques to quantify the efferocytic efficiency, and methods to assess the processing of these efferocytic targets, all using a variety of microscopy techniques.
Many of these methods are derived from classical assays for quantifying phagocytosis, the removal and destruction of pathogens by immune cells. Because of this classical basis, many of these methods can be easily employed in most labs without the need for advanced cell processing or microscopy equipment. However, these methods can be combined with advanced live-cell fluorescence microscopy and even super-resolution microscopy, enabling their use in experiments reliant on leading-edge technologies. The methods described in this paper are applicable to a broad range of research questions and investigative approaches, and can be deployed in most labs.