Impact of Poloxamer 188 variability on biologics manufacturing: Mitigations and causal investigation

Poloxamer 188 (P188), a water-soluble, synthetic copolymer with hydrophilic as well as lipophilic properties, is widely used as a cell protectant for bubble-induced shear during cultivation of suspension-adapted mammalian cells for large-scale production of protein-based therapeutics. Poor cell growth and lower product yield has been recently observed at commercial scales in more than one Chinese hamster ovary-based manufacturing process within Roche network when specific lots of P188 were used. An investigation is being conducted to unearth the root cause of “poor-performing” P188 lots and to identify means to mitigate the product supply risks. P188 raw material is currently sourced from a single vendor with additional supply constraints and risks associated with the impending change in the vendor manufacturing facility and location. These factors further exacerbate the supply risks for the drugs produced by Roche. A multi-pronged approach has been undertaken. A small-scale bioreactor based screening assay was developed where a model commercial cell line was subjected to a relatively high shear stress environment to differentiate between good-performing and poor-performing lots. To discern the root cause for the lot-specific loss of P188 functionality, analytical fingerprinting methods have been used to test different hypotheses including presence of high molecular weight species1. Pilot-scale fractionation was performed using good- and poor-performing P188 lots to isolate fractions with different molecular weight and characterized using methods including LC-MS/MS and 2D NMR. The structure elucidation results were further evaluated to discern the cell-protective functionality of the different fractions. Lastly, in order to ensure uninterrupted supply of our medicines to patients, a comprehensive evaluation of an alternate manufacturer of poloxamer 188 was performed. Taken together, the findings from this investigation provide insights to understanding a long-standing risk in biopharmaceutical manufacturing

Genome-wide transcriptome analysis reveals that a pleiotropic antibiotic regulator, AfsS, modulates nutritional stress response in Streptomyces coelicolor A3(2)

<p>Abstract</p> <p>Background</p> <p>A small "sigma-like" protein, AfsS, pleiotropically regulates antibiotic biosynthesis in <it>Streptomyces coelicolor</it>. Overexpression of <it>afsS </it>in <it>S. coelicolor </it>and certain related species causes antibiotic stimulatory effects in the host organism. Although recent studies have uncovered some of the upstream events activating this gene, the mechanisms through which this signal is relayed downstream leading to the eventual induction of antibiotic pathways remain unclear.</p> <p>Results</p> <p>In this study, we employed whole-genome DNA microarrays and quantitative PCRs to examine the transcriptome of an <it>afsS </it>disruption mutant that is completely deficient in the production of actinorhodin, a major <it>S. coelicolor </it>antibiotic. The production of undecylprodigiosin, another prominent antibiotic, was, however, perturbed only marginally in the mutant. Principal component analysis of temporal gene expression profiles identified two major gene classes each exhibiting a distinct coordinate differential expression pattern. Surprisingly, nearly 70% of the >117 differentially expressed genes were conspicuously associated with nutrient starvation response, particularly those of phosphate, nitrogen and sulfate. Furthermore, expression profiles of some transcriptional regulators including at least two sigma factors were perturbed in the mutant. In almost every case, the effect of <it>afsS </it>disruption was not observed until the onset of stationary phase.</p> <p>Conclusion</p> <p>Our data suggests a comprehensive role for <it>S. coelicolor </it>AfsS as a master regulator of both antibiotic synthesis and nutritional stress response, reminiscent of alternative sigma factors found in several bacteria.</p

Technical assessment approach for vendor initiated changes of direct materials

Hundreds of direct materials are used for each biologic production process. Vendor initiated changes (VIC) to the production process, packaging, raw material sources, and other aspects of these direct materials can and will happen. Each change could have the potential for both process and product impact not only to one product, but to every product that uses it across a manufacturing network. In order to ensure these changes are assessed appropriately and in a timely manner, procedures and processes need to be in place both from the customer and supplier. In addition, if changes are complex, communication between both parties is often necessary. Complex changes may also require a deeper level of collaboration between multiple functional groups from the customer and supplier. This poster will describe Roche/Genentech’s approach for technical assessments of VICs to ensure they are evaluated properly by the necessary subject matter experts (SMEs). It will highlight case studies such as a complex VIC pertaining to Poloxamer 188 (P188) and the effective collaboration between Roche/Genentech and its supplier. Poloxamer 188 is a complex nonionic tri-block co-polymer composed of a central hydrophobic chain of polyoxypropylene (PPO) flanked by two hydrophilic chains of polyoxyethylene (PEO) which is used in biopharmaceutical manufacturing for the cultivation of mammalian cells. The supplier informed Roche/Genentech of a production site change of P188 through the VIC business process. The complexity associated with the site change VIC was further compounded by an ongoing investigation based on observed low cell growth and product yield for some large-scale biomanufacturing processes at Roche/Genentech. Lot-to-lot variability in P188 was identified as the primary source of the observed low growth and yield even though all release specifications were met (Figure below). Please click Additional Files below to see the full abstract

Genome-wide inference of regulatory networks in Streptomyces coelicolor

Background: The onset of antibiotics production in Streptomyces species is co-ordinated with differentiation events. An understanding of the genetic circuits that regulate these coupled biological phenomena is essential to discover and engineer the pharmacologically important natural products made by these species. The availability of genomic tools and access to a large warehouse of transcriptome data for the model organism, Streptomyces coelicolor, provides incentive to decipher the intricacies of the regulatory cascades and develop biologically meaningful hypotheses. Results: In this study, more than 500 samples of genome-wide temporal transcriptome data, comprising wild-type and more than 25 regulatory gene mutants of Streptomyces coelicolor probed across multiple stress and medium conditions, were investigated. Information based on transcript and functional similarity was used to update a previously-predicted whole-genome operon map and further applied to predict transcriptional networks constituting modules enriched in diverse functions such as secondary metabolism, and sigma factor. The predicted network displays a scale-free architecture with a small-world property observed in many biological networks. The networks were further investigated to identify functionally-relevant modules that exhibit functional coherence and a consensus motif in the promoter elements indicative of DNA-binding elements. Conclusions: Despite the enormous experimental as well as computational challenges, a systems approach for integrating diverse genome-scale datasets to elucidate complex regulatory networks is beginning to emerge. We present an integrated analysis of transcriptome data and genomic features to refine a whole-genome operon map and to construct regulatory networks at the cistron level in Streptomyces coelicolor. The functionally-relevant modules identified in this study pose as potential targets for further studies and verification.

Transcriptome dynamics-based operon prediction and verification in Streptomyces coelicolor

Streptomyces spp. produce a variety of valuable secondary metabolites, which are regulated in a spatio-temporal manner by a complex network of inter-connected gene products. Using a compilation of genome-scale temporal transcriptome data for the model organism, Streptomyces coelicolor, under different environmental and genetic perturbations, we have developed a supervised machine-learning method for operon prediction in this microorganism. We demonstrate that, using features dependent on transcriptome dynamics and genome sequence, a support vector machines (SVM)-based classification algorithm can accurately classify >90% of gene pairs in a set of known operons. Based on model predictions for the entire genome, we verified the co-transcription of more than 250 gene pairs by RT-PCR. These results vastly increase the database of known operons in S. coelicolor and provide valuable information for exploring gene function and regulation to harness the potential of this differentiating microorganism for synthesis of natural products

A framework to analyze multiple time series data: A case study with Streptomyces coelicolor

Transcriptional regulation in differentiating microorganisms is highly dynamic involving multiple and interwinding circuits consisted of many regulatory genes. Elucidation of these networks may provide the key to harness the full capacity of many organisms that produce natural products. A powerful tool evolved in the past decade is global transcriptional study of mutants in which one or more key regulatory genes of interest have been deleted. To study regulatory mutants of Streptomyces coelicolor , we developed a framework of systematic analysis of gene expression dynamics. Instead of pair-wise comparison of samples in different combinations, genomic DNA was used as a common reference for all samples in microarray assays, thus, enabling direct comparison of gene transcription dynamics across different isogenic mutants. As growth and various differentiation events may unfold at different rates in different mutants, the global transcription profiles of each mutant were first aligned computationally to those of the wild type, with respect to the corresponding growth and differentiation stages, prior to identification of kinetically differentially expressed genes. The genome scale transcriptome data from wild type and a Δ absA1 mutant of Streptomyces coelicolor were analyzed within this framework, and the regulatory elements affected by the gene knockout were identified. This methodology should find general applications in the analysis of other mutants in our repertoire and in other biological systems.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/47950/1/10295_2005_Article_34.pd

A Bistable Gene Switch for Antibiotic Biosynthesis: The Butyrolactone Regulon in Streptomyces coelicolor

Many microorganisms, including bacteria of the class Streptomycetes, produce various secondary metabolites including antibiotics to gain a competitive advantage in their natural habitat. The production of these compounds is highly coordinated in a population to expedite accumulation to an effective concentration. Furthermore, as antibiotics are often toxic even to their producers, a coordinated production allows microbes to first arm themselves with a defense mechanism to resist their own antibiotics before production commences. One possible mechanism of coordination among individuals is through the production of signaling molecules. The γ-butyrolactone system in Streptomyces coelicolor is a model of such a signaling system for secondary metabolite production. The accumulation of these signaling molecules triggers antibiotic production in the population. A pair of repressor-amplifier proteins encoded by scbA and scbR mediates the production and action of one particular γ-butyrolactone, SCB1. Based on the proposed interactions of scbA and scbR, a mathematical model was constructed and used to explore the ability of this system to act as a robust genetic switch. Stability analysis shows that the butyrolactone system exhibits bistability and, in response to a threshold SCB1 concentration, can switch from an OFF state to an ON state corresponding to the activation of genes in the cryptic type I polyketide synthase gene cluster, which are responsible for production of the hypothetical polyketide. The switching time is inversely related to the inducer concentration above the threshold, such that short pulses of low inducer concentration cannot switch on the system, suggesting its possible role in noise filtering. In contrast, secondary metabolite production can be triggered rapidly in a population of cells producing the butyrolactone signal due to the presence of an amplification loop in the system. S. coelicolor was perturbed experimentally by varying concentrations of SCB1, and the model simulations match the experimental data well. Deciphering the complexity of this butyrolactone switch will provide valuable insights into how robust and efficient systems can be designed using ‘‘simple’’ two-protein networks.

Additional file 1 of Genome-wide inference of regulatory networks in Streptomyces coelicolor

Additional file 1: Conserved pairs. Column 1 and 2 contain the pair of genes, column 3 the probability, and column 4 the number of genomes in which the pair is conserved. (CSV 13 KB