Neutrophils in the Clinic – A Head-to-Head Comparison of Single-Cell Technologies
For years, a major hurdle in clinical research has been the difficulty of profiling neutrophils—the most abundant but also one of the most fragile immune cells in our blood. Their low mRNA content and high levels of degrading enzymes have made them notoriously difficult to capture with standard single-cell RNA-sequencing (scRNA-seq) methods. A new paper in Cell Reports Methods by Hatje et al. from Roche provides a crucial, head-to-head comparison of three modern scRNA-seq technologies to establish a robust and practical workflow for profiling these critical cells in clinical trials.
Key Learnings & Findings from the Paper
The study was designed to answer two fundamental questions for clinical trial implementation: which technology best captures the neutrophil transcriptome, and what are the practical requirements for sample handling? To do this, the researchers compared three platforms designed for fixed or stabilized cells— 10x Genomics ' Chromium Flex, Parse Biosciences ' Evercode, and Honeycomb Biotechnologies ' HIVE—against flow cytometry as a ground truth.
1. Modern Platforms Successfully Capture Neutrophil Transcriptomes:
A key takeaway is that all three tested technologies successfully captured neutrophil transcriptomes from whole blood samples where red blood cells were depleted. This is a significant step forward, as traditional methods often fail to retain these fragile cells. Data from the fixed-cell methods (Flex and Evercode) showed particularly high quality, with low levels of mitochondrial gene expression, which is an indicator of reduced cell stress during processing.
2. 10x Flex and Parse Evercode Align Best with Flow Cytometry:
When comparing the proportions of different immune cell types captured by each method, the results from Flex and Evercode showed strong concordance with flow cytometry data. The 10x Flex platform demonstrated the closest alignment, making it the most accurate in representing the true cellular composition of the original blood sample. HIVE and the older 10x v3.1 method, while still capturing neutrophils, showed greater deviation from the flow cytometry benchmark.
3. A Critical 2-Hour Window for Sample Fixation:
Perhaps the most important clinical finding comes from the time-course experiment. The researchers tested how long blood samples could be stored at 4°C before the neutrophil transcriptome changed. While viable cells were still present after 24 hours, their gene expression profiles were not.
This result provides a clear and critical guideline for clinical trials: to preserve the integrity of the transcriptome, blood samples must be processed and fixed within 2 hours of collection.
4. 10x Flex Emerges as the Top Choice for Clinical Workflows:
Based on a combination of performance and practicality, the authors identified 10x Flex as the most suitable method for implementation in clinical trials. It not only provided the most accurate representation of cell populations but also offered a simplified sample collection and fixation protocol. The authors noted that recent updates to the Flex protocol, which allow for the stabilization of whole blood before cell separation, make it even easier to deploy at clinical sites that may lack complex lab equipment. In contrast, the Evercode protocol was found to be the most time-consuming and procedurally complex for a clinical setting.
This publication powerfully reinforces a critical step: single-cell analysis enters the clinic as a powerful tool for unraveling complex biological questions that were intractable with previous technologies. More importantly, it tackles the absolute necessity of clinically compatible and robust protocols to successfully bring these insights into patient care.
The Scailyte Perspective: Enabling Clinical Impact Through Robust Single-Cell Solutions
At Scailyte, we are acutely aware that high-quality biological insights hinge on rigorous, standardized methods. We actively invest in establishing and validating these types of robust, clinically-relevant single-cell protocols, ensuring the highest integrity of the data. Beyond data generation, our core strength lies in making sense of the vast, complex data. Through our ScaiVision, we transform complex single-cell patterns into actionable predictive biomarkers and measurable clinical assays, ultimately bringing real impact to patients through precision medicine.
Hatje K, Schneider K, Danilin S, Koechl F, Giroud N, Juglair L, Marbach D, Knuckles P, Bergauer T, Metruccio M, Garrido A, Zhang JD, Sultan M, Bell E. Comparison of single-cell RNA-seq methods to enable transcriptome profiling of neutrophils in clinical samples. Cell Rep Methods. 2025 Sep 15;5(9):101173.
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