NWFCS Second Annual Meeting (2025)

Annual Meeting NW Flow Cytometry Society
March 19th, 2025, Fred Hutchinson Cancer Center

The most common use of flow cytometry is to quantify the abundance of certain cells in a complex mixture by markers that are stably expressed and, in most cases, categorize these cells by a transient marker indicating a particular cell state. In recent years, the allowable parameters a flow cytometer can interpret in one panel has substantially increased. This technological advance has empowered studies to characterize the immune communication networks between different cell types and determine the plasticity of individual cells to occupy multiple immune functions. One approach to complex panel design is to decide where in the spectrum a biological question must be answered by either a panel which seeks to delineate the maximum number phenotypic markers on an individual cell type (Deep Phenotyping) or a panel which seeks to categorize the maximum number of cell lineages within a complex sample while still inferring some aspect of cell state for each lineage (Broad Phenotyping). In the following talk, I will provide examples of two optimized flow cytometry panels to illustrate strategies to be taken in designing each of these complex panel categories. I will discuss two types of spreading error that limit the overall size of complex panels; the first is the well-established spillover spreading error, and the second is a newly defined error named unmixing-dependent spreading error. As these errors may even arise in small panels without proper consideration, I hope the discussion over predictive metrics for panel development will have application to all who attend.

Skeletal muscle has the capacity to regenerate following injury. Fibro-adipogenic progenitors (FAPs) are multipotent cells that facilitate tissue remodeling after injury, but can also cause pathological fibrosis in degenerative diseases and ageing. Skeletal muscle FAPs interact with a range of immune cells and stimulate muscle stem cell (MuSC) proliferation and differentiation in response to injury. MuSCs are required to regenerate damaged myofibers.

FAPs are the main source of skeletal muscle interleukin-33 (IL-33), an alarmin sequestered in nuclei, but released by damaged cells to elicit an immune response, mediated through cells that express the IL-33 receptor ST2. Many ST2-expressing immune populations are required to coordinate regeneration. We have discovered that FAPs express the truncated soluble ST2 isoform (sST2), sequestering interstitial IL-33 and therefore reducing ligand availability. The soluble sST2 expression peak coincides with MuSC activation and proliferation, as well as infiltration of multiple immune populations that provide inflammatory signaling cascades facilitating tissue repair.

Simultaneously studying the dynamics of multiple populations by flow cytometry can be challenging without a high-parameter approach. Spectral flow cytometry can increase the parameters acquired from a limited sample and the range of fluorophores with distinct emission signatures is rapidly increasing, facilitating the expansion of antibody panels. To assess the dynamics of IL33-responsive immune cell populations, a 30+ colour spectral cytometry panel was developed with spike-in channels for fluorescent reporters and commonly used broad marker screening kits. This panel provides a tool for skeletal muscle biologists to broadly assess the infiltrating and resident cell populations in regeneration.

The immune cell populations that FAP-sourced sST2 is inhibiting during muscle regeneration could elucidate novel therapeutic targets for modulating pathological tissue degeneration and fibrosis, providing hope for muscular dystrophy patients and our ageing population affected by muscle wasting and fibrosis. We have now also deployed this antibody panel to investigate the fate of lipid nanoparticle enveloped cargo following intramuscular immunization with mRNA vaccines.

Flow cytometric cell sorting (FCCS) is a flow cytometric based method of purifying cells, often to greater than 90% purity. While this methodology is commonly used in the research laboratory, similar approaches are used to purify cells in the clinical laboratory testing. At the University of Washington Hematopathology laboratory, FCCS is used to isolate cells for a variety of diagnostic genetic tests. This presentation will briefly describe the principles of FCCS and present common clinical examples of the use of the purification of cells by FCCS for molecular and fluorescence in situ hybridization (FISH) testing. Examples presented will include purification of neoplastic B cells, T cells, and Hodgkin cells. FCCS gating strategies will also be reviewed. At the end of the presentation, attendees should understand the basic principles of FCCS for clinical use. Presented strategies are also applicable in the research laboratory.

While spectral flow cytometry has gained traction in the research in recent years, it has yet to be implemented widely in clinical laboratories. Spectral flow has significant potential advantages in analysis of specimens, allowing for more complex and informative multicolor analyses as well as maximizing information gathered from limited specimens. Limitations of reagent availability for the additional spectral channels and limited instrument software options for efficient high-volume workflow have until recently hampered efforts for clinical utilization. Here we report that advances in new classes of fluorochromes with distinct spectral signatures and improvements of instrument software have enabled development of a clinical triage panel using a 5-laser Cytek® Aurora™™ spectral cytometer for characterization of hematolymphoid neoplasms in a high-volume reference lab. The panel consists of a 25-color backbone used on all specimen types and an 11-color panel extension for bone marrow, a 6-color panel extension for peripheral blood, and a 3-color panel extension for tissues and fluids. Single-stained cells and Cytek® FSP™ CompBeads were used as reference controls for spectral unmixing. The configuration of the backbone panel and specimen-specific panel extensions, as well as gating strategies and normal and neoplastic case studies, with comparisons to our current 10-color triage panel, will be presented. This backbone panel with sample-specific panel extensions can resolve most leukemias and lymphomas without the need for add-on studies; a significant benefit in streamlining workflows and maximizing recovery from limited specimens.

Healthcare operations are significant contributors to climate and environmental hazards, primarily through carbon emissions, resource consumption, and waste production. These impacts are particularly pronounced in developed economies. As a result, healthcare systems have a critical role to play in achieving the United Nations' 2030 Agenda for Sustainable Development Goals (SDGs), which aim to protect the environment, reduce costs, and improve global health and well-being. Clinical laboratories, including flow cytometry facilities, are central to healthcare operations, often relying on energy-intensive technologies, single-use plastics, and other resource-heavy practices. While general guidelines for reducing the environmental impact of clinical laboratories exist, the specific environmental footprint of flow cytometry laboratories remains largely unexamined.

This lecture will explore how laboratories contribute to climate and environmental hazards, analyze their effects on planetary health, assess the environmental impact of flow cytometry laboratories, and highlight actionable areas for improvement. By focusing on flow cytometry, it will address the unique challenges and opportunities in creating more sustainable laboratory practices.

At the end of the lecture, participants will: 

1. Understand the impact of laboratory-related emissions, resource utilization, and waste generation on health and the planet, and recognize their sources in the flow cytometry laboratory.

2. Identify roles and opportunities for improvement in a flow cytometry laboratory.

3. Recognize the importance of establishing laboratory-specific metrics such as developing sustainability benchmarks, tracking resource usage, and calculating the environmental cost of running specific flow panels.

4. Understand the benefits of a "green laboratory," such as improved efficiency, enhanced sustainability, competitive advantage, corporate social responsibility, and innovation in laboratory design and operation.

Whether you are an established research scientist looking for an optimal way to maintain your data for your next big project or you manage a core facility, there's something in this talk for everyone. Data management is often left up to the user to determine the most efficient workflow and it can quickly become overwhelming as more and more cytometry data is generated. Justine provides an example framework for data management that has been successfully implemented, as well as a case example of how she organizes her own data as a senior scientist for her ongoing research project.

The ability to include all necessary markers to ensure accurate immunologic cell subset identification was limited by traditional flow cytometry platforms. Often, populations that are analyzed or sorted based on a limited marker set result in errantly mixed populations, resulting in inaccurate conclusions and misidentification of function and relationship. The SOULCAP consortium aims to create a framework for standardizing flow cytometry assays from essential marker combinations for human immunological cell subsets to ontological naming strings to bioinformatics analysis to address this problem. Also, a common issue in>30 color spectral assays is a loss of population resolution from spreading error and in optimal reagent choices. SOULCAP also aims to create guidelines for assay performance in health and disease. In this talk we will demonstrate the validation of marker combinations proposed by SOULCAP using the brand-new Mosaic spectral flow cytometer from Beckman Coulter.

Told through a technologist perspective we will discuss how to identify issues with flow cytometry data, what to do once you think you found an issue, and how to prevent issues from happening in the future. The talk will include tips and tricks on how you can use your analysis templates to your advantage to produce good quality flow cytometry data.

Modern immunology research relies on high-dimensional analyses to study the complex cellular makeup of disease. To achieve this, we developed Infinity Flow, which combines hundreds of overlapping flow cytometry parameters using machine learning to enable the simultaneous analysis of the co-expression patterns of hundreds of surface-expressed proteins across millions of individual cells. We demonstrate that this approach allows the comprehensive analysis of the cellular heterogeneity during the inflammatory response to pathogen. By combining the supervised machine learning algorithms of Infinity Flow with an antigen-specific activation induced marker assay and barcode multiplexing, we create a highly scalable, low-cost, and accessible solution to single-cell immunology studies.