Transcriptome and proteome response is uncoupled under glutamine limitation

Understanding the quantitative relationship between transcript and protein concentrations remains a key challenge in biology. Absolute measurements of both transcript and protein concentration is critical but has not been done in human cells yet. Additionally, within-gene correlations were determined across different tissues, allowing environmental and genetic variability. Here, we address these limitations by analyzing within-gene correlations across the human cell line MCF10A with decreasing concentrations of glutamine in tissue culture as the sole independent variable. We find that the transcriptome and proteome response is uncoupled: the transcriptome primarily reallocates its resources, while the proteome changes in total protein. Furthermore, high within-gene correlations are observed in specific functional groups. Furthermore, genes with high within-gene correlation share common gene features, with the 3' UTR length shows the largest effect. These results will provide valuable insights that could improve the prediction of protein concentrations from transcripts in biomedical research and biotechnology. Overall design: MCF10A human breast epithelial cells were cultured in glutamine-free DMEM/F12 supplemented with four different concentrations of glutamine (0.04, 0.12, 0.20, and 0.28 mM) as well as normal glutamine concentration in DMEM/F12 (2.5 mM). Each glutamine condition included three biological replicates.

解析转录本与蛋白质浓度间的定量关联，始终是生物学领域的核心难题之一。同时精准测定转录本与蛋白质的绝对浓度至关重要，但目前尚未在人类细胞中完成此类工作。此外，过往研究多在不同组织间测定基因内关联，以此纳入环境与遗传变异的影响。本研究通过以组织培养中梯度变化的谷氨酰胺浓度作为唯一自变量，分析人类细胞系MCF10A的基因内关联，以此解决上述局限。研究发现转录组与蛋白质组的应答存在解偶联现象：转录组主要进行资源重分配，而蛋白质组则表现为总蛋白水平的改变。此外，特定功能基因簇中呈现出显著的高基因内关联。进一步分析显示，高基因内关联的基因共享共通的基因特征，其中3'非翻译区（3' UTR）长度的影响最为显著。本研究结果可为生物医学研究与生物技术领域中，基于转录本预测蛋白质浓度的模型优化提供重要参考。实验整体设计：将人类乳腺上皮细胞系MCF10A培养于无谷氨酰胺的DMEM/F12培养基中，分别添加4种梯度浓度的谷氨酰胺（0.04、0.12、0.20及0.28 mM），并设置DMEM/F12培养基常规谷氨酰胺浓度组（2.5 mM）作为对照。每组谷氨酰胺浓度条件均设置3次生物学重复。