Treating cell culture media with UV irradiation against adventitious agents: Minimal impact on CHO performance

Yen, Sandi; Sokolenko, Stanislav; Manocha, Bhavik; Blondeel, Eric J. M.; Aucoin, Marc G.; Patras, Ankit; Daynouri-Pancino, Farnaz; Sasges, Michael

doi:10.1002/btpr.1942

Cited by 27 publications

(21 citation statements)

References 26 publications

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“…Hydrogen nuclear magnetic resonance ( 1 H-NMR) spectroscopy is an emerging tool for metabolomic analysis of cell culture. In contrast to the established use of 13 C-NMR for targeted elucidation of intracellular metabolic flux (reviewed in [ 1 ]), the quantification of a broader cellular metabolome with 1 H-NMR in the context of recombinant protein production has been much more recent [ 2 – 6 ]. Unlike 13 C-NMR, which requires relatively expensive 13 C labelled compounds and often complex interpretation, 1 H-NMR benefits from simple sample preparation and non-selective data acquisition.…”

Section: Introductionmentioning

confidence: 99%

A correction method for systematic error in 1H-NMR time-course data validated through stochastic cell culture simulation

Sokolenko

Aucoin

2015

BMC Syst Biol

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BackgroundThe growing ubiquity of metabolomic techniques has facilitated high frequency time-course data collection for an increasing number of applications. While the concentration trends of individual metabolites can be modeled with common curve fitting techniques, a more accurate representation of the data needs to consider effects that act on more than one metabolite in a given sample. To this end, we present a simple algorithm that uses nonparametric smoothing carried out on all observed metabolites at once to identify and correct systematic error from dilution effects. In addition, we develop a simulation of metabolite concentration time-course trends to supplement available data and explore algorithm performance. Although we focus on nuclear magnetic resonance (NMR) analysis in the context of cell culture, a number of possible extensions are discussed.ResultsRealistic metabolic data was successfully simulated using a 4-step process. Starting with a set of metabolite concentration time-courses from a metabolomic experiment, each time-course was classified as either increasing, decreasing, concave, or approximately constant. Trend shapes were simulated from generic functions corresponding to each classification. The resulting shapes were then scaled to simulated compound concentrations. Finally, the scaled trends were perturbed using a combination of random and systematic errors. To detect systematic errors, a nonparametric fit was applied to each trend and percent deviations calculated at every timepoint. Systematic errors could be identified at time-points where the median percent deviation exceeded a threshold value, determined by the choice of smoothing model and the number of observed trends. Regardless of model, increasing the number of observations over a time-course resulted in more accurate error estimates, although the improvement was not particularly large between 10 and 20 samples per trend. The presented algorithm was able to identify systematic errors as small as 2.5 % under a wide range of conditions.ConclusionBoth the simulation framework and error correction method represent examples of time-course analysis that can be applied to further developments in 1H-NMR methodology and the more general application of quantitative metabolomics.Electronic supplementary materialThe online version of this article (doi:10.1186/s12918-015-0197-4) contains supplementary material, which is available to authorized users.

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Section: Introductionmentioning

confidence: 99%

A correction method for systematic error in 1H-NMR time-course data validated through stochastic cell culture simulation

Sokolenko

Aucoin

2015

BMC Syst Biol

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“…It eliminates viruses and bacteria, and it is frequently used for the disinfection of materials sensitive to high temperatures or materials that cannot be treated with chemically active substances [28]. This method has been used successfully for superficial sterilization in the biopharmaceutical industry [29] or in post-harvest crop protection [30,31]. In order to obtain an aseptic culture, an UV-C dose of low intensity was applied that might also induce the hormesis phenomenon, which is the appearance of beneficial effects due to low doses of e.g.…”

Section: Resultsmentioning

confidence: 99%

Establishing an efficient explant superficial sterilization protocol for in vitro micropropagation of bear’s garlic (Allium ursinum L.)

et al. 2015

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SummaryIntroduction:Allium ursinumL. has a commercial value due to its high contents of bio-active compounds and mild, garlic-like taste.In vitroculture played an important role in obtainingAlliumspecies with the desired characteristics and in the production of healthy reproductive material.Objective:Developing an effective method of sterilization bear’s garlic bulbs.Methods:To obtain sterile shoots of garlic several methods of sterilization involving such factors as ACE, H2O2, HgCl2, and UV-C were tested.Results:In order to obtain sterile shoots of bear’s garlic, several sterilization procedures were tested. The best procedure was based on a two-step disinfection, where the whole onions were treated with ethanol and H2O2for 20 min. Thereafter, the isolated apical buds were sterilized in ACE for 10 min, rinsed in double-distilled water and transferred onto MS medium for growing. Up to 95% of the inoculated explants formed shoots, which were sub-cultured on MS with 4 mg dm−3BAP in order to enable further propagation.Conclusion:After optimization and stabilization, this procedure may become the basic concept of a proper and reliable propagation method of bear’s garlic on commercial scale.

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“…Several approaches are commonly used such as centrifugation, washing and sieving methods, and the use of antibiotics (Bruckner and Kroth 2009;Lee et al 2015;Han et al 2016). Another method to remove bacteria commonly used in environmental technology, medical practices and the pharmaceutical industry is the use of UV (Schmidt and Kauling 2007;Carney and Lane 2014;Yen et al 2014). Ultraviolet light C (UV-C) is in the range of 200-280 nm.…”

Section: Introductionmentioning

confidence: 99%

Effect of removal of bacteria on the biomass and extracellular carbohydrate productivity of Botryococcus braunii

et al. 2019

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Botryococcus braunii CCALA778 is a green microalga that can produce large amounts of extracellular carbohydrates and therefore is a potential host for industrial applications such as materials, food and pharmaceutical products. The downside of B. braunii is its slow growth and therefore, improvements on the biomass productivity or carbohydrate production will make this microalga more attractive for industrial exploitation. Microalgae grow naturally in the presence of bacteria and these can be beneficial or antagonistic. In outdoor cultivation systems, contamination by bacteria is common. The role or effects of bacteria present in B. braunii CCALA778 are not yet fully elucidated. We used UV-C treatment to reduce bacterial abundance in B. braunii CCALA778 cultures and 16S rRNA gene amplicon MiSeq sequencing for bacterial community analysis. The effect of the reduced amount of bacteria on biomass growth and production of extracellular carbohydrates was analysed. It is shown that UV-C treatment can reduce the bacterial population substantially without harming B. braunii. Bacteria removed by UV-C were antagonistic to B. braunii CCALA778 as in their absence production of biomass and extracellular carbohydrates was enhanced significantly. CCALA778 treated with UV-C accumulated 826 ± 61 mg L −1 of extracellular carbohydrates by day 15 compared with 422 ± 135 mg L −1 accumulated extracellular carbohydrates in the untreated culture.

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Treating cell culture media with UV irradiation against adventitious agents: Minimal impact on CHO performance

Cited by 27 publications

References 26 publications

A correction method for systematic error in 1H-NMR time-course data validated through stochastic cell culture simulation

A correction method for systematic error in 1H-NMR time-course data validated through stochastic cell culture simulation

Establishing an efficient explant superficial sterilization protocol for in vitro micropropagation of bear’s garlic (Allium ursinum L.)

Effect of removal of bacteria on the biomass and extracellular carbohydrate productivity of Botryococcus braunii

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