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The high MW porin protein complex (Omp200, composed of Omp121 and Omp71) from Bacteroides fragilis ATCC 25285 was purified and tryptic peptide sequences were used to design degenerate oligonucleotide primers which were then used as a first step in amplification, identification and sequencing of the omp121 gene (GenBank Accession Number AF357210). Sequence analysis revealed an open reading frame of 3378 bases. The deduced amino acid sequence (which contained the experimentally determined peptide sequences) has 1125 or 1116 amino acids (depending on which start codon is used); the mature protein consists of 1096 amino acids, has a predicted MW of 121.4 and a theoretical pI of 6.32. It is preceded by a 29 or 18 amino acid signal peptide which includes a typical hydrophobic region near the N-terminus (VLVLVL). Hydropathy plots of the deduced amino acid sequence of B. fragilis Omp121 display striking similarity with those of Escherichia coli OmpC (a 16-stranded porin) and FepA (a 22-stranded ligand-gated transport protein). Three-dimensional modeling of B. fragilis Omp121 (based on 1D and 3D sequence profiles, coupled with secondary structure and solvation potential information) indicated that the closest homologues in terms in fold conservation were the E. coli 16-stranded porins (e.g. OsmA) and 22-stranded ligand gated transport proteins (e.g. FepA). The omp71 gene sequence was identified using the tryptic peptides to search the published Bacteroides genome data base. We found that omp71 is located immediately downstream of omp121 and confirmed this with PCR analysis. Omp71 has no known homologues but does share some characteristics with the Porphyromonas RagB antigen. [Copyright &y& Elsevier]

An efficient and potentially scalable technology was evaluated to control the ice nucleation step of the freezing process for a model monoclonal antibody formulation and the effect on process performance and quality attributes of the final lyophilized product was compared with the conventional shelf ramping method of freezing. Controlled ice nucleation resulted in uniform nucleation at temperatures between −2.3 and −3.2°C while uncontrolled nucleation resulted in random nucleation at temperatures between −10 and −16.4°C. The sublimation rate (dm/dt) during primary drying was higher in the controlled nucleation cycle (0.13g/h/vial) than in the uncontrolled nucleation cycle (0.11g/h/vial). This was due to the formation of larger ice crystals, leading to lower product resistance (R p) and 19% reduction in the primary drying for the controlled nucleation cycle. Controlled ice nucleation resulted in lyophilized cakes with more acceptable appearance, no visible collapse or shrinkage and decreased reconstitution times compared with uncontrolled nucleation. There were no observed differences in the particle size, concentration (A 280nm) and presence of aggregates (A 410nm) between the two nucleation cycles when the lyophilized cakes were reconstituted. These were confirmed by SEC and protein A-HPLC analyses which showed similar peak shapes and retention times between the two cycles. However, uncontrolled nucleation resulted in cakes with larger specific surface area (0.90m2/g) than controlled nucleation (0.46m2/g). SEM images of the lyophilized cakes from uncontrolled nucleation revealed a sponge-like morphology with smaller pores while cakes from controlled nucleation cycle revealed plate-like structures with more open and larger pores. While controlled nucleation resulted in a final product with a higher residual moisture content (2.1±0.08%) than uncontrolled nucleation (1.62±0.11%), this was resolved by increasing the secondary drying temperature. [ABSTRACT FROM AUTHOR]

Consistent high-quality antibody yield is a key goal for cell culture bioprocessing. This endpoint is typically achieved in commercial settings through product and process engineering of bioreactor parameters during development. When the process is complex and not optimized, small changes in composition and control may yield a finished product of less desirable quality. Therefore, changes proposed to currently validated processes usually require justification and are reported to the US FDA for approval. Recently, design-of-experiments-based approaches have been explored to rapidly and efficiently achieve this goal of optimized yield with a better understanding of product and process variables that affect a product's critical quality attributes. Here, we present a laboratory-scale model culture where we apply a Plackett- Burman screening design to parallel cultures to study the main effects of 11 process variables. This exercise allowed us to determine the relative importance of these variables and identify the most important factors to be further optimized in order to control both desirable and undesirable glycan profiles. We found engineering changes relating to culture temperature and nonessential amino acid supplementation significantly impacted glycan profiles associated with fucosylation, β-galactosylation, and sialylation. All of these are important for monoclonal antibody product quality. © 2015 Wiley Periodicals, Inc. and the American Pharmacists Association J Pharm Sci 104:1919-1928, 2015 [ABSTRACT FROM AUTHOR]