Project description:There is a great need for setting novel measurable attributes at the cell physiological level in a scalable biopharmaceutical production process to be able to predict the process outcomes and improve process understanding. In a biologic production process, changes in culture environment due to several factors such as shear and bubble induced damage from gas sparging and agitation are known to occur. There is a gap in the knowledge of cellular response due to varying bioreactor environment itself during the course of cell culture, from lag-phase to log-phase to stationary-phase in culture. With the emergence of micro-arrays as tools for exploring cell physiological changes, it opens the possibility for studying the effect of bioreactor culture environment itself on the cell substrate. Such information could be eventually used to designate gene transcripts as biomarkers for cell status in a controlled bioreactor system. A model 5L bench-scale bubble aerated and impeller agitated bioreactor system was used to study gene expression profiles of a hybridoma cell line during the time-course of batch culture. Gene expression profiles that were variable from early-to-late in batch culture, as well as invariant gene profiles were summarized using microarray findings. Typical cellular functions studied were oxidative stress response, DNA damage response, apoptosis, antioxidant activity, cellular metabolism, and protein folding. These findings were also verified with a more rigorous semi-quantitative RT-PCR technique. The results of this study suggest that under predefined bioreactor culture conditions, significant gene changes from lag to log to stationary phase could be identified, which could then be used to track the culture state.
Project description:Here, we successfully used NO as the direct electron acceptor for the enrichment of a microbial community in a continuous bioreactor. The enrichment culture, mainly comprised of two new organisms from the Sterolibacteriaceae family, grew on NO reduction to N2 and formate oxidation, with virtually no accumulation of N2O. The microbial growth kinetics of the enrichment culture as well as its affinity for different N-oxides were determined. In parallel, using metagenomics, metatranscriptomics, and metaproteomics, the biochemical reactions underlying the growth of these microorganisms on NO were investigated. This study demonstrates that microorganisms thrive and can be enriched on NO, and presents new opportunities to study microbial growth on this highly energetic and climate-active molecule that may have been pivotal in the evolution of aerobic respiration.
Project description:There is a great need for setting novel measurable attributes at the cell physiological level in a scalable biopharmaceutical production process to be able to predict the process outcomes and improve process understanding. In a biologic production process, changes in culture environment due to several factors such as shear and bubble induced damage from gas sparging and agitation are known to occur. There is a gap in the knowledge of cellular response due to varying bioreactor environment itself during the course of cell culture, from lag-phase to log-phase to stationary-phase in culture. With the emergence of micro-arrays as tools for exploring cell physiological changes, it opens the possibility for studying the effect of bioreactor culture environment itself on the cell substrate. Such information could be eventually used to designate gene transcripts as biomarkers for cell status in a controlled bioreactor system. A model 5L bench-scale bubble aerated and impeller agitated bioreactor system was used to study gene expression profiles of a hybridoma cell line during the time-course of batch culture. Gene expression profiles that were variable from early-to-late in batch culture, as well as invariant gene profiles were summarized using microarray findings. Typical cellular functions studied were oxidative stress response, DNA damage response, apoptosis, antioxidant activity, cellular metabolism, and protein folding. These findings were also verified with a more rigorous semi-quantitative RT-PCR technique. The results of this study suggest that under predefined bioreactor culture conditions, significant gene changes from lag to log to stationary phase could be identified, which could then be used to track the culture state. We ran consecutive 5L bioreactor runs, each with an independent vial thaw, to achieve multiple biological replicates per time-point. Bioreactors were sampled approximately every 12 hours for RNA extraction. For the 5L bioreactors, microarray samples were run for day 1 (n=2), day 2 (n=2), day 3 (n=3), and day 3.5 (n=3). Here 2 or 3 of the three biological replicates run for each time-point were included in the analysis, based on >70% genes found. We define early exponential as day 1, peak exponential as day 2 and day 3 and late stationary as day 3.5.
Project description:These research areas concentrate on stress induced proteases in recombinant Escherichia coli, glycosylation heterogeneity due to bioprocess conditions produced in mammalian cells, and metabolic engineering of E. coli. The hypothesis of this project is that recombinant protein glycosylation is inefficient under normal bioreactor conditions since the additional glycosylation reactions necessary for the recombinant protein exceed the metabolic capacity of the cells. Normal bioreactor conditions have been optimized for cell growth, and sometimes for protein productivity. Only recently has it been accepted that optimal glycosylation may not occur under optimal growth or protein productivity conditions. Specific Aim: Determine the relationship between bioreactor conditions and glycosylation gene expression in NS0 cells. EXPERIMENT: Mouse NS0 myeloma cells were grown in culture, stressed with 5 mM NaCl, 10 mM proline plus 5 mM ammonia, or 5 mM ammonia, along with an unstressed control group. The growth of the cultures were followed until the late exponential phase (90 hours), at which time two 50 mLs of cells were harvested and RNA extracted. Samples were prepared in triplicate, for a total of 12 samples. The RNA was amplified and labeled by Microarray Core (E) and hybridized to the GLYCOv3 microarrays.