Excessive interferon-α signaling in autoimmunity alters glycosphingolipid processing in B cells.

Excessive interferon-α (IFN-α) production by innate immune cells is a hallmark of autoimmune diseases. What other cell type secretes IFN-α and how IFN-α affects immune cell metabolism and homeostasis in autoimmunity are largely unclear. Here, we report that autoimmune B cells, arising from two different B cell-specific genetic lesions in mice, secrete IFN-α. In addition, IFN-α, found in abundance in autoimmunity, elicited profound changes in the B cell lipidome, increasing their expression of glycosphingolipids (GSLs) and leading to their CD1d-mediated depletion of iNKT cells in vitro and in vivo. IFN-α receptor blockade could reverse the loss of iNKT cells. Excessive stimulation of B cells with IFN-α altered the expression of enzymes that catalyze critical steps in GSL processing, increasing the expressions of glucosylceramide synthase (GCS) and globotrihexosylceramide synthase (Gb3S) but decreasing that of α-galactosidase A (α-galA). Inhibiting GCS or restoring α-galA expression prevented iNKT depletion by IFN-α-activated B cells. Taken together, our work indicated that excessive IFN-α perturbs GSL metabolism in B cells which in turn adversely affects iNKT homeostasis.

Computational approach for understanding and improving GS-NS0 antibody production under hyperosmotic conditions.

A systematic computational framework is proposed for studying the underlying mechanisms of hyperosmotic conditions on GS-NS0 antibody production and to predict the optimal hyperosmotic induction time. Both IgG mRNA and polypeptide chain concentrations were positively related to the specific antibody productivity (q(Ab)) for normal and hyperosmotic conditions throughout. Hyperosmotic conditions resulted in 100% increase in specific IgG mRNA transcription rates; however, mRNA half-lives were 25% lower at both the mid-exponential and stationary phases. The IgG specific translation rates were higher (24%) at the mid-exponential phase for hyperosmotic cultures but were comparable in later phases. The main mechanism through which hyperosmotic conditions improve q(Ab) was concluded to be the heightened specific transcription rates. The predictive capability of the model was experimentally verified by identifying the optimal hyperosmotic induction time for biphasic GS-NS0 cultures at 72 h. The systematic approach that seamlessly combined experimentation and mathematical modelling, allowed both for the model based design of experiments that yielded valuable biological insight and for the prediction of the optimal hyperosmotic induction time. This framework enables "closing-the-loop" in mammalian cell bioprocess modelling by guiding experimentation through modelling.

Rapid characterization of high/low producer CHO cells using matrix-assisted laser desorption/ionization time-of-flight.

An intact-cell mass spectrometry (ICM) method using matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) was evaluated for the screening of stable recombinant Chinese hamster ovary (CHO) cell lines, an important mammalian cell line in bioprocessing. With rapid and simple cell pretreatments, viabilities of cells could be rapidly distinguished on the different fingerprints of mass spectra. Detectable m/z values on cell surfaces and their relative intensities were processed by two biostatistical methods, principle components analysis (PCA) and partial least squares (PLS), with promising results. Discrimination among cell lines with different expressed recombinant proteins or different productivities could be achieved. The ICM method has the advantage of providing multiple parameters simultaneously and possesses the potential to become a powerful method for routine monitoring of bioprocesses.

Development and analysis of a mathematical model for antibody-producing GS-NS0 cells under normal and hyperosmotic culture conditions.

The GS-NS0 cell line is industrially important and is currently used for the large-scale production of several therapeutic monoclonal antibodies. A novel hybrid model, consisting of both unstructured and structured elements, has been developed to describe cell growth and death, metabolism, and antibody production in the GS-NS0 system under normal culture conditions. A comparison between the hybrid model and a large-scale single-cell model (SCM) describing detailed metabolic processes verified the predictive ability of the hybrid model (when compared with experimental data) and highlighted the practical difficulties involved in utilizing complex models. Global sensitivity analysis (GSA) on the hybrid model identified the specific transcription and translation rates of heavy and light immunoglobulin chains as parameters with the largest impact on the antibody production process. This information, together with the addition of a 24-h lag phase, resulted in the successful extension of the hybrid model to represent GS-NS0 system behavior under hyperosmotic culture conditions.