Crowell Christopher K, Qin Qiang, Grampp Gustavo E, Radcliffe Richard A, Rogers Gary N, Scheinman Robert I
Process & Clinical Operations, Amgen Inc., Thousand Oaks, California, USA.
Biotechnol Bioeng. 2008 Jan 1;99(1):201-13. doi: 10.1002/bit.21539.
Recombinant human erythropoietin (rHuEPO) produced in a human kidney fibrosarcoma cell line, HT1080, was used as a model to study the effects of sodium butyrate (SB) on protein glycosylation. Treatment with 2 mM SB resulted in complex changes with respect to sugar nucleotide pools including an increase in UDP-Gal and a decrease in UDP-GlcNac. In addition, polylactosamine structures present on rHuEPO increased after SB treatment. To determine if these phenotypic changes correlated with changes in mRNA abundance, we profiled mRNA levels over a 24-h period in the presence or absence of SB using oligonucleotide microarrays. By filtering our data through a functional glycomics gene list associated with the processes of glycan degradation, glycan synthesis, and sugar nucleotide synthesis and transport we identified 26 genes with significantly altered mRNA levels. We were able to correlate the changes in message in six of these genes with measurable phenotypic changes within our system including: neu1, b3gnt6, siat4b, b3gnt1, slc17a5, and galt. Interestingly, for the two genes: cmas and gale, our measurable phenotypic changes did not correlate with changes in mRNA expression. These data demonstrate both the utility and pit falls of coupling biochemical analysis with high throughput oligonucleotide microarrays to predict how changes in cell culture environments will impact glycoprotein oligosaccharide content.
用人肾纤维肉瘤细胞系HT1080生产的重组人促红细胞生成素(rHuEPO)作为模型,研究丁酸钠(SB)对蛋白质糖基化的影响。用2 mM SB处理导致糖核苷酸池发生复杂变化,包括UDP-Gal增加和UDP-GlcNac减少。此外,SB处理后rHuEPO上存在的多乳糖胺结构增加。为了确定这些表型变化是否与mRNA丰度的变化相关,我们使用寡核苷酸微阵列在存在或不存在SB的情况下,在24小时内分析mRNA水平。通过将我们的数据通过与聚糖降解、聚糖合成以及糖核苷酸合成和转运过程相关的功能糖组学基因列表进行筛选,我们鉴定出26个mRNA水平有显著变化的基因。我们能够将其中六个基因的信息变化与我们系统内可测量的表型变化相关联,包括:neu1、b3gnt6、siat4b、b3gnt1、slc17a5和galt。有趣的是,对于两个基因:cmas和gale,我们可测量的表型变化与mRNA表达的变化不相关。这些数据证明了将生化分析与高通量寡核苷酸微阵列相结合以预测细胞培养环境变化如何影响糖蛋白寡糖含量的实用性和局限性。