More or less—On the influence of labelling strategies to infer cell population dynamics

The adoptive transfer of labelled cell populations has been an essential tool to determine and quantify cellular dynamics. The experimental methods to label and track cells over time range from fluorescent dyes over congenic markers towards single-cell labelling techniques, such as genetic barcodes. While these methods have been widely used to quantify cell differentiation and division dynamics, the extent to which the applied labelling strategy actually affects the quantification of the dynamics has not been determined so far. This is especially important in situations where measurements can only be obtained at a single time point, as e.g. due to organ harvest. To this end, we studied the appropriateness of various labelling strategies as characterised by the number of different labels and the initial number of cells per label to quantify cellular dynamics. We simulated adoptive transfer experiments in systems of various complexity that assumed either homoeostatic cellular turnover or cell expansion dynamics involving various steps of cell differentiation and proliferation. Re-sampling cells at a single time point, we determined the ability of different labelling strategies to recover the underlying kinetics. Our results indicate that cell transition and expansion rates are differently affected by experimental shortcomings, such as loss of cells during transfer or sampling, dependent on the labelling strategy used. Furthermore, uniformly distributed labels in the transferred population generally lead to more robust and less biased results than non-equal label sizes. In addition, our analysis indicates that certain labelling approaches incorporate a systematic bias for the identification of complex cell expansion dynamics.

标记细胞群的过继转移（adoptive transfer）一直是确定并量化细胞动力学的核心实验手段。用于长期标记与追踪细胞的实验方法涵盖范围广泛，从荧光染料、同源标记（congenic markers）直至单细胞标记技术，例如基因条形码（genetic barcodes）。尽管此类方法已被广泛用于量化细胞分化与增殖动力学，但截至目前，学界仍未明确所采用的标记策略实际会对动力学量化结果产生多大程度的影响。这一点在仅能获取单个时间点测量数据的场景中尤为关键——例如因器官取材限制而无法开展多时间点检测时。为此，本研究围绕不同标记种类数与每个标记对应的初始细胞数这两个核心特征，探究了各类标记策略在量化细胞动力学中的适用性。我们在多种复杂度的系统中模拟了过继转移实验，这些系统分别假设细胞处于稳态更新（homoeostatic cellular turnover），或是涉及多阶段分化与增殖的细胞扩增动态。通过仅在单个时间点对细胞进行重采样，我们分析了不同标记策略还原真实细胞动力学过程的能力。研究结果显示，细胞转化与扩增速率受实验缺陷（如转移或采样过程中的细胞丢失）的影响程度，会因所采用的标记策略而异。此外，与标记数量不均的情况相比，转移细胞群中标记分布均匀的实验方案，通常能得到更稳健、偏差更低的分析结果。此外，本研究分析还发现，部分标记策略在识别复杂细胞扩增动态的过程中，会引入系统性偏差。