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A synthetic biology standard for Chinese Hamster Ovary cell genome monitoring and contaminant detection by polymerase chain reaction

View Article: PubMed Central - PubMed

ABSTRACT

Background: Chinese Hamster Ovary (CHO) cells are the current industry standard for production of therapeutic monoclonal antibodies at commercial scales. Production optimisation in CHO cells hinges on analytical technologies such as the use of the polymerase chain reaction (PCR) to quantify genetic factors within the CHO genome and to detect the presence of contaminant organisms. PCR-based assays, whilst sensitive and accurate, are limited by (i) requiring lengthy sample preparation and (ii) a lack of standardisation.

Results: In this study we directly assess for the first time the effect of CHO cellular material on quantitative PCR (qPCR) and end-point PCR (e-pPCR) when used to measure and detect copies of a CHO genomic locus and a mycoplasma sequence. We also perform the first head-to-head comparison of the performance of a conventional qPCR method to that of the novel linear regression of efficiency (LRE) method when used to perform absolute qPCR on CHO-derived material. LRE qPCR features the putatively universal ‘CAL1’ standard.

Conclusions: We find that sample preparation is required for accurate quantitation of a genomic target locus, but mycoplasma DNA sequences can be detected in the presence of high concentrations of CHO cellular material. The LRE qPCR method matches performance of a conventional qPCR approach and as such we invite the synthetic biology community to adopt CAL1 as a synthetic biology calibration standard for qPCR.

No MeSH data available.


Related in: MedlinePlus

Statistical comparison of SC qPCR and LRE qPCR for quantitation of a CHO genomic sequence. Figure 5 data from SC qPCR and LRE qPCR methods to measure GAPDH copies in shake flask and bioreactor samples were compared using XY plot, graphs a, c respectively, and Bland–Altman plot, graphs b and d respectively. Statistical procedures were performed as described by Burd (2010). The mean bias (overall average difference) is indicated by the dark dashed line and 1.96× the standard deviation (±) of this bias is indicated by the grey dashed lines, to show the limits within which bias levels have a 95 % confidence interval
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Fig6: Statistical comparison of SC qPCR and LRE qPCR for quantitation of a CHO genomic sequence. Figure 5 data from SC qPCR and LRE qPCR methods to measure GAPDH copies in shake flask and bioreactor samples were compared using XY plot, graphs a, c respectively, and Bland–Altman plot, graphs b and d respectively. Statistical procedures were performed as described by Burd (2010). The mean bias (overall average difference) is indicated by the dark dashed line and 1.96× the standard deviation (±) of this bias is indicated by the grey dashed lines, to show the limits within which bias levels have a 95 % confidence interval

Mentions: Method comparison by XY plot (Burd 2010) gives a slope of 1.00 and an intercept of zero in the case of zero proportional bias between methods. For shake flask-derived material an XY plot (Fig. 6a) showed negligible proportional bias of SC qPCR data (slope of 1.06) when using the LRE qPCR method. The Y intercept of the XY plot was close to zero (0.0705) indicating little systematic bias. A Bland–Altman (Bland and Altman 1986) plot (Fig. 6b) indicates LRE qPCR exhibited a positive bias of SC qPCR at higher copy numbers of target DNA but that LRE qPCR and SC qPCR are broadly equivalent due to the fact that the mean bias range for both methods includes zero difference (Burd 2010).


A synthetic biology standard for Chinese Hamster Ovary cell genome monitoring and contaminant detection by polymerase chain reaction
Statistical comparison of SC qPCR and LRE qPCR for quantitation of a CHO genomic sequence. Figure 5 data from SC qPCR and LRE qPCR methods to measure GAPDH copies in shake flask and bioreactor samples were compared using XY plot, graphs a, c respectively, and Bland–Altman plot, graphs b and d respectively. Statistical procedures were performed as described by Burd (2010). The mean bias (overall average difference) is indicated by the dark dashed line and 1.96× the standard deviation (±) of this bias is indicated by the grey dashed lines, to show the limits within which bias levels have a 95 % confidence interval
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC5016487&req=5

Fig6: Statistical comparison of SC qPCR and LRE qPCR for quantitation of a CHO genomic sequence. Figure 5 data from SC qPCR and LRE qPCR methods to measure GAPDH copies in shake flask and bioreactor samples were compared using XY plot, graphs a, c respectively, and Bland–Altman plot, graphs b and d respectively. Statistical procedures were performed as described by Burd (2010). The mean bias (overall average difference) is indicated by the dark dashed line and 1.96× the standard deviation (±) of this bias is indicated by the grey dashed lines, to show the limits within which bias levels have a 95 % confidence interval
Mentions: Method comparison by XY plot (Burd 2010) gives a slope of 1.00 and an intercept of zero in the case of zero proportional bias between methods. For shake flask-derived material an XY plot (Fig. 6a) showed negligible proportional bias of SC qPCR data (slope of 1.06) when using the LRE qPCR method. The Y intercept of the XY plot was close to zero (0.0705) indicating little systematic bias. A Bland–Altman (Bland and Altman 1986) plot (Fig. 6b) indicates LRE qPCR exhibited a positive bias of SC qPCR at higher copy numbers of target DNA but that LRE qPCR and SC qPCR are broadly equivalent due to the fact that the mean bias range for both methods includes zero difference (Burd 2010).

View Article: PubMed Central - PubMed

ABSTRACT

Background: Chinese Hamster Ovary (CHO) cells are the current industry standard for production of therapeutic monoclonal antibodies at commercial scales. Production optimisation in CHO cells hinges on analytical technologies such as the use of the polymerase chain reaction (PCR) to quantify genetic factors within the CHO genome and to detect the presence of contaminant organisms. PCR-based assays, whilst sensitive and accurate, are limited by (i) requiring lengthy sample preparation and (ii) a lack of standardisation.

Results: In this study we directly assess for the first time the effect of CHO cellular material on quantitative PCR (qPCR) and end-point PCR (e-pPCR) when used to measure and detect copies of a CHO genomic locus and a mycoplasma sequence. We also perform the first head-to-head comparison of the performance of a conventional qPCR method to that of the novel linear regression of efficiency (LRE) method when used to perform absolute qPCR on CHO-derived material. LRE qPCR features the putatively universal ‘CAL1’ standard.

Conclusions: We find that sample preparation is required for accurate quantitation of a genomic target locus, but mycoplasma DNA sequences can be detected in the presence of high concentrations of CHO cellular material. The LRE qPCR method matches performance of a conventional qPCR approach and as such we invite the synthetic biology community to adopt CAL1 as a synthetic biology calibration standard for qPCR.

No MeSH data available.


Related in: MedlinePlus