Developing global regression models for metabolite concentration prediction regardless of cell line.

Following the Process Analytical Technology (PAT) of the Food and Drug Administration (FDA), drug manufacturers are encouraged to develop innovative techniques in order to monitor and understand their processes in a better way. Within this framework, it has been demonstrated that Raman spectroscopy coupled with chemometric tools allow to predict critical parameters of mammalian cell cultures in-line and in real time. However, the development of robust and predictive regression models clearly requires many batches in order to take into account inter-batch variability and enhance models accuracy. Nevertheless, this heavy procedure has to be repeated for every new line of cell culture involving many resources. This is why we propose in this paper to develop global regression models taking into account different cell lines. Such models are finally transferred to any culture of the cells involved. This article first demonstrates the feasibility of developing regression models, not only for mammalian cell lines (CHO and HeLa cell cultures), but also for insect cell lines (Sf9 cell cultures). Then global regression models are generated, based on CHO cells, HeLa cells, and Sf9 cells. Finally, these models are evaluated considering a fourth cell line(HEK cells). In addition to suitable predictions of glucose and lactate concentration of HEK cell cultures, we expose that by adding a single HEK-cell culture to the calibration set, the predictive ability of the regression models are substantially increased. In this way, we demonstrate that using global models, it is not necessary to consider many cultures of a new cell line in order to obtain accurate models. Biotechnol. Bioeng. 2017;114: 2550-2559. © 2017 Wiley Periodicals, Inc.

Multivariate statistical process control (MSPC) using Raman spectroscopy for in-line culture cell monitoring considering time-varying batches synchronized with correlation optimized warping (COW).

Multivariate statistical process control (MSPC) is increasingly popular as the challenge provided by large multivariate datasets from analytical instruments such as Raman spectroscopy for the monitoring of complex cell cultures in the biopharmaceutical industry. However, Raman spectroscopy for in-line monitoring often produces unsynchronized data sets, resulting in time-varying batches. Moreover, unsynchronized data sets are common for cell culture monitoring because spectroscopic measurements are generally recorded in an alternate way, with more than one optical probe parallelly connecting to the same spectrometer. Synchronized batches are prerequisite for the application of multivariate analysis such as multi-way principal component analysis (MPCA) for the MSPC monitoring. Correlation optimized warping (COW) is a popular method for data alignment with satisfactory performance; however, it has never been applied to synchronize acquisition time of spectroscopic datasets in MSPC application before. In this paper we propose, for the first time, to use the method of COW to synchronize batches with varying durations analyzed with Raman spectroscopy. In a second step, we developed MPCA models at different time intervals based on the normal operation condition (NOC) batches synchronized by COW. New batches are finally projected considering the corresponding MPCA model. We monitored the evolution of the batches using two multivariate control charts based on Hotelling's T2 and Q. As illustrated with results, the MSPC model was able to identify abnormal operation condition including contaminated batches which is of prime importance in cell culture monitoring We proved that Raman-based MSPC monitoring can be used to diagnose batches deviating from the normal condition, with higher efficacy than traditional diagnosis, which would save time and money in the biopharmaceutical industry.

Mammalian cell culture monitoring using in situ spectroscopy: Is your method really optimised?

In recent years, as a result of the process analytical technology initiative of the US Food and Drug Administration, many different works have been carried out on direct and in situ monitoring of critical parameters for mammalian cell cultures by Raman spectroscopy and multivariate regression techniques. However, despite interesting results, it cannot be said that the proposed monitoring strategies, which will reduce errors of the regression models and thus confidence limits of the predictions, are really optimized. Hence, the aim of this article is to optimize some critical steps of spectroscopic acquisition and data treatment in order to reach a higher level of accuracy and robustness of bioprocess monitoring. In this way, we propose first an original strategy to assess the most suited Raman acquisition time for the processes involved. In a second part, we demonstrate the importance of the interbatch variability on the accuracy of the predictive models with a particular focus on the optical probes adjustment. Finally, we propose a methodology for the optimization of the spectral variables selection in order to decrease prediction errors of multivariate regressions. © 2017 American Institute of Chemical Engineers Biotechnol. Prog., 33:308-316, 2017.

Structure determination of feline calicivirus virus-like particles in the context of a pseudo-octahedral arrangement.

The vesivirus feline calicivirus (FCV) is a positive strand RNA virus encapsidated by an icosahedral T=3 shell formed by the viral VP1 protein. Upon its expression in the insect cell - baculovirus system in the context of vaccine development, two types of virus-like particles (VLPs) were formed, a majority built of 60 subunits (T=1) and a minority probably built of 180 subunits (T=3). The structure of the small particles was determined by x-ray crystallography at 0.8 nm resolution helped by cryo-electron microscopy in order to understand their formation. Cubic crystals belonged to space group P213. Their self-rotation function showed the presence of an octahedral pseudo-symmetry similar to the one described previously by Agerbandje and co-workers for human parvovirus VLPs. The crystal structure could be solved starting from the published VP1 structure in the context of the T=3 viral capsid. In contrast to viral capsids, where the capsomers are interlocked by the exchange of the N-terminal arm (NTA) domain, this domain is disordered in the T=1 capsid of the VLPs. Furthermore it is prone to proteolytic cleavage. The relative orientation of P (protrusion) and S (shell) domains is alerted so as to fit VP1 to the smaller T=1 particle whereas the intermolecular contacts around 2-fold, 3-fold and 5-fold axes are conserved. By consequence the surface of the VLP is very similar compared to the viral capsid and suggests a similar antigenicity. The knowledge of the structure of the VLPs will help to improve their stability, in respect to a use for vaccination.

Anatomical, physiological, and pharmacological characteristics of histidine decarboxylase knock-out mice: evidence for the role of brain histamine in behavioral and sleep-wake control.

The hypothesis that histaminergic neurons are involved in brain arousal is supported by many studies. However, the effects of the selective long-term abolition of histaminergic neurons on the sleep-wake cycle, indispensable in determining their functions, remain unknown. We have compared brain histamine(HA)-immunoreactivity and the cortical-EEG and sleep-wake cycle under baseline conditions or after behavioral or pharmacological stimuli in wild-type (WT) and knock-out mice lacking the histidine decarboxylase gene (HDC-/-). HDC-/-mice showed an increase in paradoxical sleep, a decrease in cortical EEG power in theta-rhythm during waking (W), and a decreased EEG slow wave sleep/W power ratio. Although no major difference was noted in the daily amount of spontaneous W, HDC-/-mice showed a deficit of W at lights-off and signs of somnolence, as demonstrated by a decreased sleep latencies after various behavioral stimuli, e.g., WT-mice placed in a new environment remained highly awake for 2-3 hr, whereas HDC-/-mice fell asleep after a few minutes. These effects are likely to be attributable to lack of HDC and thus of HA. In WT mice, indeed, intraperitoneal injection of alpha-fluoromethylhistidine (HDC-inhibitor) caused a decrease in W, whereas injection of ciproxifan (HA-H3 receptor antagonist) elicited W. Both injections had no effect in HDC-/-mice. Moreover, PCR and immunohistochemistry confirmed the absence of the HDC gene and brain HA-immunoreactive neurons in the HDC-/-mice. These data indicate that disruption of HA-synthesis causes permanent changes in the cortical-EEG and sleep-wake cycle and that, at moments when high vigilance is required (lights off, environmental change em leader ), mice lacking brain HA are unable to remain awake, a prerequisite condition for responding to behavioral and cognitive challenges. We suggest that histaminergic neurons also play a key role in maintaining the brain in an awake state faced with behavioral challenges.