Development of a Semi-Quantitative Multiplex PCR Method for Detecting Residual Pichia Pastoris Host Cell DNA in Biopharmaceuticals

 The use of the methylotrophic yeast, Pichia pastoris, as one of the most effective and versatile systems for the expression of heterologous proteins in biopharmaceutical manufacturing has become increasingly popular in recent years. The impurity caused by residual host cell DNA is one of the major concerns in production of recombinant therapeutics. The aim of the present study was to develop a semi-quantitative, multiplex PCR method to determine the level of impurity in biopharmaceuticals produced in Pichia pastoris as the host. Primers were designed based on the rDNA repeat region and optimized to achieve the limit of detection in a multiplex PCR following by analyzing with MYImageAnalysis (Thermo Fisher Scientific, USA) software to quantify the concentration of Pichia pastoris genomic DNA in pertinent controls and drug samples. The multiplex PCR were able to detect up to 1 femtogram (fg) of genomic DNA under optimized conditions. Moreover, achieved concentration of DNA in controls and samples through relevant standard curve indicates the feasibility of this method in the presence of inhibitory effects. In comparison with other methods such as real-time PCR and Threshold assay, the assay shows acceptable sensitivity, precision and linearity along with ease of use, low equipment costs and analyte flexibility. We thus propose this method to be considered as a useful tool to estimate host cell residual DNA in biopharmaceuticals produced in Pichia pastoris.Highlights The impurity of residual host cell DNA is an important concern in production of biopharmaceuticals.Pichia pastoris is an effective and versatile system for the expression of recombinant proteinsQuantitative Polymerase Chain Reaction could be used for quantifying residual host-cell DNAWe designed a sensitive and valid PCR method for detection and quantification of Pichia residual DN

The Essentiality of Reporting Hardy-Weinberg Equilibrium Calculations in Population-Based Genetic Association Studies

Population-based genetic association studies have proven to be a powerful tool in identifying genes implicated in many complex human diseases that have a huge impact on public health. An essential quality control step in such studies is to undertake Hardy-Weinberg equilibrium (HWE) calculations. Deviations from HWE in the control group may reflect important problems including selection bias, population stratification and genotyping errors. If HWE is violated, the inferences of these studies may thus be biased. We therefore aimed to examine the extent to which HWE calculations are reported in genetic association studies published in Cell Journal(Yakhteh) (Cell J). Using keywords pertaining to genetic association studies, eleven relevant articles were identified of which ten provided full genotypic data. The genotype distribution of 16 single nucleotide polymorphisms (SNPs) was re-analyzed for HWE by using three different methods where appropriate. HWE was not reported in 60% of all articles investigated. Among those reporting, only one article provided calculations correctly and in detail. Therefore, 90% of articles analyzed failed to provide sufficient HWE data. Interestingly, three articles had significant HWE deviation in their control groups of which one highly deviated from HWE expectations (P= 9.8×10-12). We thus show that HWE calculations are under-reported in genetic association studies published in this journal. Furthermore, the conclusions of the three studies showing significant HWE in their control groups should be treated cautiously as they may be potentially misleading. We therefore recommend that reporting of detailed HWE calculations should become mandatory for such studies in the future

Generation of induced pluripotent stem cell lines from three individuals with autism spectrum disorder

Uncovering the molecular mechanisms of autism spectrum disorder (autism) necessitates development of relevant experimental models that are capable of recapitulating features of the clinical phenotype. Using non-integrative episomal vectors, peripheral blood mononuclear cells derived from three unrelated individuals diagnosed with autism were reprogrammed to induced pluripotent stem cells (iPSCs). The resultant lines exhibited the expected cellular morphology, karyotype, and evidence of pluripotency. These iPSCs constitute a valuable resource to support investigations of the underlying aetiology of autism