Heritable non-genetic phenotypes are enriched for stress responses as a form of bet hedging

To produce humanized therapeutics, Chinese hamster ovary (CHO) cells have become the preferred host organism. During manufacturing batches, these cells encounter critical levels of environmental stressors such as ammonia, lactate, and osmolality accumulation that can significantly reduce cell health and productivity. It is therefore crucial that stress adaptation and resistance be factored into cell line development (CLD) considerations. An alternative to screening stress sensitivity during CLD, where the scaled-down micro-environment makes it difficult, is selecting for or engineering cell lines with a stress resistant phenotype. In this study, we employee population-based transcriptomic analysis and differential gene expression analysis on stress-induced CHO cells to identify biomarkers for engineering stress resistance. These biomarkers are identified as genes displaying heritable properties while being differentially expressed in the presence of manufacturing relevant stress levels. Using this workflow, 199 genes displayed transcriptional variability characteristic of a bistable system that formed six network communities of co-fluctuating genes. These communities were enriched in genes related to response to stimuli, regulation of apoptotic processes, and regulation of gene expression or metabolic pathways. Significant overlap with differentially expressed genes in stress-induced production fed-batch flasks reinforce the relevancy of these heritable genes states for stress adaptation. Assessing the overlap and the biological function, six genes were identified as promising biomarkers for engineering a stress-resistant phenotype. Cell line engineering methods may be employed in the future to bias clonal populations for higher stress tolerance and adaptability to manufacturing stress, therefore increasing cell health and productivity in at-scale bioreactors. Population-based transcriptomic analysis, known as MemorySeq, in which single-cell derived mini-pools (40 samples) of CHOZN® GS -/- ZFN Clone 23 gene expression is measured in an attempt to correlate highly variable genes with those displaying heritable patterns. Samples compared to bulk RNA-Seq as a noise control to monitor innate biological variability. Collection of genes demonstrating heritable expression patterns compared to differentially expressed genes from day 5 of stress-induced production fed-batch flasks to identify heritable genes critical to stress recognition and adaptation Please note that only R1 raw data fastq file is provided for the 'MemorySeq_Sample26_Single-Cell-26' sample (as R2 file is corrupted).

为制备人源化治疗药物，中国仓鼠卵巢（Chinese hamster ovary, CHO）细胞已成为首选宿主生物体。在工业化生产批次中，这类细胞会遭遇氨、乳酸及渗透压累积等达到临界水平的环境胁迫因子，这些因素可显著降低细胞健康状态与生产能力。因此，在细胞系开发（cell line development, CLD）的考量中纳入胁迫适应与抗性相关因素至关重要。

传统上在细胞系开发阶段筛选胁迫敏感性的方案存在局限：缩小化的微环境难以真实模拟生产场景，而另一种可行思路则是筛选或工程化改造具备胁迫抗性表型的细胞系。本研究针对胁迫诱导的CHO细胞开展了基于群体的转录组学分析与差异基因表达分析，旨在挖掘可用于工程化改造胁迫抗性的生物标志物（biomarker）。

这些生物标志物被定义为在生产相关胁迫水平下呈现差异表达且具备可遗传特性的基因。通过该分析流程，共筛选得到199个呈现双稳态系统（bistable system）特征的转录变异基因，这些基因形成了6个协同波动基因的网络群落。这些群落显著富集于刺激响应、细胞凋亡过程调控、基因表达调控及代谢通路相关的基因集合中。与胁迫诱导补料分批（fed-batch）培养瓶中第5天的差异表达基因存在显著重叠，这进一步证实了这些可遗传基因状态在胁迫适应中的相关性。

通过评估基因重叠情况与生物学功能，最终筛选得到6个具备应用前景的生物标志物，可用于工程化改造胁迫抗性表型。未来可通过细胞系工程化改造方法，定向调控克隆群体以获得更高的胁迫耐受性与生产环境适应能力，进而提升大规模生物反应器中的细胞健康状态与生产效能。

本研究采用名为MemorySeq的基于群体的转录组学分析方法，对CHOZN® GS -/- ZFN Clone 23的单细胞来源微型池（共40个样本）进行基因表达量检测，以期将高度变异的基因与呈现可遗传表达模式的基因建立关联。以批量RNA测序（RNA-Seq）作为噪声对照样本，用于监测固有生物学变异。研究将这些呈现可遗传表达模式的基因集合，与胁迫诱导补料分批培养瓶中第5天的差异表达基因进行比对，以筛选出对胁迫识别与适应至关重要的可遗传基因。

请注意，'MemorySeq_Sample26_Single-Cell-26'样本仅提供了R1原始数据fastq文件（因R2文件已损坏）。