Tag: HiLIFE trainee

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Extracting knowledge from flow cytometry data

Hi there, and welcome to the HiLIFE-Trainee blog! I’m Olivia Dreilinger, a second-year Master’s student in the Genetics and Molecular Biosciences program here at UH.

This winter I participated in Physalia’s course on Flow Cytometry Analysis with R/Bioconductor. The course was held digitally to facilitate a greater geographic range of students. Throughout the course, in addition to the lectures and coding sessions, I was able to interact with researchers and PhD students from all over the world. This made for an exciting learning environment. The conversations I had with the other participants about their work and career paths were especially inspiring.

And now, let me tell you a little more about flow cytometry, how we can analyze this fascinating data, and how I will apply this new knowledge in my work at UH.

Flow Cytometry
Flow cytometry is a powerful tool that can sort a complex mixture of cells, often from blood or bone marrow or cells from solid tissue that have been separated from each other (dissociated) into populations of different cell types. This can be used to count the number of cells belonging to a certain type or for downstream investigation of the cells such as gene expression analysis or functional assays. It has applications in cancer biology, immunology, infectious disease monitoring, and numerous other areas of cell biology. Here’s how it works: one by one, cells are sent through a machine which uses multiple laser beams to “read” properties of the cell. The machine does this by measuring how light is scattered in the forward and side direction and indicates the cell’s size and complexity (granularity) respectively. Additionally, the flow cytometry machine can detect fluorescence, making even finer distinctions between cellular subpopulations possible. Cells can be made to express fluorescent markers through staining, thus allowing for this higher level of resolution.

Once the cells have been sorted, the flow cytometry instrument returns a file regarding each cell’s fluorescent intensity with respect to each marker used. This data must then be analyzed in order to extract meaning and identify different cell populations, thus allowing for downstream research and diagnosis by comparing measures such as number of cells or mean fluorescence in each subpopulation of cells.


[Flow cytometry schematic. Cells are sent through the flow cytometry instrument one by one. The machine detects their properties and sends them to a computer for analysis. The cells can be separated by type for downstream analysis. Created with BioRender.com.]

Data Analysis
The trainee course I took focused on the step of turning the fluorescent intensity data into something meaningful about different cell populations. The first crucial step is preprocessing, which includes compensation, transformation, and cleaning—basically, the data needs to be tidied up for ease of use. Once this house-keeping task is complete, we can move on to the part we care about, namely identifying the cell populations.

The flow cytometry data can be displayed on a two dimensional plot with each axis representing the fluorescence of a given marker or how much light is scattered in a certain direction. The cells then cluster by type depending on their properties. Traditionally, these cell subpopulations were identified by eye and circled in a process called manual gating. This process can be repeated over and over again comparing different markers giving a complex gating strategy. The gating process can be automated with software packages in R such as FlowDensity and FlowSOM. This strategy looks at density of cells and uses it to determine the cell populations.

[A gating strategy for identifying cell populations. Here we can see the step-wise identification of cell populations, beginning by first identifying live cells, and then distinguishing which cells are lymphocytes from the other cells. From there, the gating strategy separates the cells that are granulocytes and continues finding subpopulations from those that are not granulocytes, and so on, using the properties of the light detected by the flow cytometry machine for each cell. Figures generated in Physalia’s Flow Cytometry Analysis with R/Bioconductor course, 2023.]

Current Research at UH
The Integrative Evolutionary Biology lab, where I am doing my thesis, uses flow cytometry to identify and investigate different types of color cells (or chromophores). We study cichlids which are tropical fish native to lakes and rivers of India, Africa, and South and Central America. There are thousands of different species of these fish with distinct and vibrant color patterns making them an exciting model system to study when it comes to the evolution of cell types and the composition of these fishes’ colorful skin. As shown below, there are a number of different chromatophores: melanophores which are dark in color, iridophores which appear iridescent and blueish, and xanthophores which are yellow. We are using flow cytometry to study the composition of cichlid skin across different species within the Cichlidae family. I’m excited to start applying what I learned in this course to our data.


[Images of the color cells (chromatophores) we are studying in cichlid skin. A) dark dendritic melanophores, B) iridescent, blue iridophores, and C) a close-up of a dendritic yellow xanthophore. Credit Alexandra Faur, Integrative Biology Lab.]

I am grateful to HiLIFE for awarding me the HiLIFE Trainee Conference Grant and to the Integrative Biology Lab for making it possible for me to participate in this excellent course, which deepened my knowledge of flow cytometry, and provided me with the tools to find meaning in this kind of data. I look forward to utilizing this technology in the future.

— Olivia Dreilinger

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Reflecting on the journey so far and embarking on a research career

Hello!

This is Rupesh with another blog post to provide an update on what happened during and after my traineeship. You can find my previous post here. It took me a little longer to write this post than promised, but here we are!

Let me start with a short recap: For the traineeship, I worked on my MSc thesis under the supervision of Dr. Ilona Rissanen and Prof. Juha Huiskonen at the Institute of Biotechnology in the University of Helsinki. My thesis was on a project aimed at discovering the structural basis of SARS-CoV-2 neutralization by the antigen-binding fragment of an antibody that was derived from a COVID-19 patient. We can understand how the antibody manages to neutralize the SARS-CoV-2 virus by figuring out where it binds to the spike protein. The antigen-binding fragment, as the name suggests, is the part of an antibody that recognizes and binds to the antigen. In order to find out the epitope of the antigen-binding fragment, I employed single-particle cryogenic electron microscopy (cryoEM). I was able to hypothesize the neutralization mechanism based on the location of the epitope and the subsequent analyses of it.

During the traineeship, I got to learn some cool techniques involved in studying a protein through cryoEM, right from sample preparation to processing the collected data. I would like to highlight a moment during my thesis work, when I got to see how the spike protein looked like in 2D in the early stages of processing the data. It was stunning to see the proteins I had expressed on the computer screen!

But the main takeaways, in my opinion, were the discussions I had with my supervisors and other lab members on how to troubleshoot experiments and interpret the results. That was where I got to understand how to approach science and the problems that arise in these projects. I found these discussions, both formal and informal, to be highly beneficial to my development as a researcher. Writing my thesis was another area where I found myself constantly learning and applying the knowledge to put the big picture together. It involved reading a lot of research articles, which was not an easy task but once I got into the thick of it, I was surprised to notice how fulfilling it was. Staying on top of current research in the field does feel good.

My thesis work had come to an end right after the traineeship period ended and it was time to submit my thesis before the academic year came to a close. As part of graduation requirements, the Genetics and Molecular Biosciences (GMB) master’s program provides the opportunity to present our thesis work during the annual GMB master’s thesis symposium. It was the first time I got to be a part of an in-person symposium in a very long time. In fact, it was the first time I got to see most of my fellow students in the program. All of us presented our work with great enthusiasm and held passionate discussions. It was a good experience to present my results to an audience with varied background and to also listen to talks on different lines of research that my colleagues were working on.

I graduated from the GMB master’s program a couple of months ago and I am incredibly thankful for having the opportunity to work in the research groups of Dr. Rissanen and Prof. Huiskonen. A huge thanks to HiLIFE for supporting me during my thesis. The traineeship resulted in a series of wonderful events which would go on to help me build myself as a researcher and for this, I am grateful!

As for the present, I have recently started to work as a research assistant with the same research groups where I’m hoping to enrich my skills even further before I embark on the journey towards a PhD next year. I’m cherishing this phase of my life where I get to do cool science surrounded by an awesome community, long may it continue!

Cheers,

Rupesh