Single-Batch Expression of an Experimental Recombinant Snakebite Antivenom Based on an Oligoclonal Mixture of Human Monoclonal Antibodies.

Oligoclonal antibodies, which are carefully defined mixtures of monoclonal antibodies, are valuable for the treatment of complex diseases, such as infectionss and cancer. In addition to these areas of medicine, they could be utilized for the treatment of snakebite envenoming, where recombinantly produced monoclonal human antibodies could overcome many of the drawbacks accompanying traditional antivenoms. However, producing multiple individual batches of monoclonal antibodies in an industrial setting is associated with significant costs. Therefore, it is attractive to produce oligoclonal antibodies by mixing multiple antibody-producing cell lines in a single batch to have only one upstream and downstream process. In this study, we selected four antibodies that target different toxins found in the venoms of various elapid snake species, such as mambas and cobras, and generated stable antibody-producing cell lines. Upon co-cultivation, we found the cell line ratios to be stable over 7 days. The purified oligoclonal antibody cocktail contained the anticipated antibody concentrations and bound to the target toxins as expected. These results thus provide a proof of concept for the strategy of mixing multiple cell lines in a single batch to manufacture tailored antivenoms recombinantly, which could be utilized for the treatment of snakebite envenoming and in other fields where oligoclonal antibody mixtures could find utility.

Unlocking DOE potential by selecting the most appropriate design for rAAV optimization.

Producing recombinant adeno-associated virus (rAAV) for gene therapy via triple transfection is an intricate process involving many cellular interactions. Each of the different elements encoded in the three required plasmids-pHelper, pRepCap, and pGOI-plays a distinct role, affecting different cellular pathways when producing rAAVs. The required expression balance emphasizes the critical need to fine-tune the concentration of all these different elements. The use of design of experiments (DOE) to find optimal ratios is a powerful method to streamline the process. However, the choice of the DOE method and design construction is crucial to avoid misleading results. In this work, we examined and compared four distinct DOE approaches: rotatable central composite design (RCCD), Box-Behnken design (BBD), face-centered central composite design (FCCD), and mixture design (MD). We compared the abilities of the different models to predict optimal ratios and interactions among the plasmids and the transfection reagent. Our findings revealed that blocking is essential to reduce the variability caused by uncontrolled random effects and that MD coupled with FCCD outperformed all other approaches, improving volumetric productivity 109-fold. These outcomes underscore the importance of selecting a model that can effectively account for the biological context, ultimately yielding superior results in optimizing rAAV production.

Multiplex genome editing eliminates the Warburg Effect without impacting growth rate in mammalian cells.

The Warburg effect is ubiquitous in proliferative mammalian cells, including cancer cells, but poses challenges for biopharmaceutical production, as lactate accumulation inhibits cell growth and protein production. Previous efforts to eliminate lactate production via knockout have failed in mammalian bioprocessing since lactate dehydrogenase has proven essential. However, here we eliminated the Warburg effect in Chinese hamster ovary (CHO) and HEK293 cells by simultaneously knocking out lactate dehydrogenase and regulators involved in a negative feedback loop that typically inhibits pyruvate conversion to acetyl-CoA. In contrast to long-standing assumptions about the role of aerobic glycolysis, Warburg-null cells maintain wildtype growth rate while producing negligible lactate. Further characterization of Warburg-null CHO cells showed a compensatory increase in oxygen consumption, a near total reliance on oxidative metabolism, and higher cell densities in fed-batch cell culture. These cells remained amenable for production of diverse biotherapeutic proteins, reaching industrially relevant titers and maintaining product glycosylation. Thus, the ability to eliminate the Warburg effect is an important development for biotherapeutic production and provides a tool for investigating a near-universal metabolic phenomenon.

Unravelling the essential elements for recombinant adeno-associated virus (rAAV) production in animal cell-based platforms.

Recombinant adeno-associated viruses (rAAVs) stand at the forefront of gene therapy applications, holding immense significance for their safe and efficient gene delivery capabilities. The constantly increasing and unmet demand for rAAVs underscores the need for a more comprehensive understanding of AAV biology and its impact on rAAV production. In this literature review, we delved into AAV biology and rAAV manufacturing bioprocesses, unravelling the functions and essentiality of proteins involved in rAAV production. We discuss the interconnections between these proteins and how they affect the choice of rAAV production platform. By addressing existing inconsistencies, literature gaps and limitations, this review aims to define a minimal set of genes that are essential for rAAV production, providing the potential to advance rAAV biomanufacturing, with a focus on minimizing the genetic load within rAAV-producing cells.

CRISPR-Cas12a-integrated transgenes in genomic safe harbors retain high expression in human hematopoietic iPSC-derived lineages and primary cells.

Discovery of genomic safe harbor sites (SHSs) is fundamental for multiple transgene integrations, such as reporter genes, chimeric antigen receptors (CARs), and safety switches, which are required for safe cell products for regenerative cell therapies and immunotherapies. Here we identified and characterized potential SHS in human cells. Using the CRISPR-MAD7 system, we integrated transgenes at these sites in induced pluripotent stem cells (iPSCs), primary T and natural killer (NK) cells, and Jurkat cell line, and demonstrated efficient and stable expression at these loci. Subsequently, we validated the differentiation potential of engineered iPSC toward CD34+ hematopoietic stem and progenitor cells (HSPCs), lymphoid progenitor cells (LPCs), and NK cells and showed that transgene expression was perpetuated in these lineages. Finally, we demonstrated that engineered iPSC-derived NK cells retained expression of a non-virally integrated anti-CD19 CAR, suggesting that several of the investigated SHSs can be used to engineer cells for adoptive immunotherapies.

A Multi-Level Systems Biology Analysis of Aldrin's Metabolic Effects on Prostate Cancer Cells.

Although numerous studies support a dose-effect relationship between Endocrine disruptors (EDs) and the progression and malignancy of tumors, the impact of a chronic exposure to non-lethal concentrations of EDs in cancer remains unknown. More specifically, a number of studies have reported the impact of Aldrin on a variety of cancer types, including prostate cancer. In previous studies, we demonstrated the induction of the malignant phenotype in DU145 prostate cancer (PCa) cells after a chronic exposure to Aldrin (an ED). Proteins are pivotal in the regulation and control of a variety of cellular processes. However, the mechanisms responsible for the impact of ED on PCa and the role of proteins in this process are not yet well understood. Here, two complementary computational approaches have been employed to investigate the molecular processes underlying the acquisition of malignancy in prostate cancer. First, the metabolic reprogramming associated with the chronic exposure to Aldrin in DU145 cells was studied by integrating transcriptomics and metabolomics via constraint-based metabolic modeling. Second, gene set enrichment analysis was applied to determine (i) altered regulatory pathways and (ii) the correlation between changes in the transcriptomic profile of Aldrin-exposed cells and tumor progression in various types of cancer. Experimental validation confirmed predictions revealing a disruption in metabolic and regulatory pathways. This alteration results in the modification of protein levels crucial in regulating triacylglyceride/cholesterol, linked to the malignant phenotype observed in Aldrin-exposed cells.

Recycling carbon for sustainable protein production using gas fermentation.

Current food production practices contribute significantly to climate change. To transition into a sustainable future, a combination of new food habits and a radical food production innovation must occur. Single-cell protein from microbial fermentation can profoundly impact sustainability. This review paper explores opportunities offered by gas fermentation to completely replace our reliance on fossil fuels for the production of food. Together with synthetic biology, designed microbial proteins from gas fermentation have the potential to reduce our dependence on fossil fuels and make food production more sustainable.

Analytical tools for unravelling the metabolism of gas-fermenting Clostridia.

Acetogens harness the Wood-Ljungdahl Pathway, a unique metabolic pathway for C1 capture close to the thermodynamic limit. Gas fermentation using acetogens is already used for CO-to-ethanol conversion at industrial-scale and has the potential to valorise a range of C1 and waste substrates to short-chain and medium-chain carboxylic acids and alcohols. Advances in analytical quantification and metabolic modelling have helped guide industrial gas fermentation designs. Further advances in the measurements of difficult to measure metabolites are required to improve kinetic modelling and understand the regulation of acetogen metabolism. This will help guide future synthetic biology designs needed to realise the full potential of gas fermentation in stimulating a circular bioeconomy.

Modeling apoptosis resistance in CHO cells with CRISPR-mediated knockouts of Bak1, Bax, and Bok.

Chinese hamster ovary (CHO) cells are the primary platform for the production of biopharmaceuticals. To increase yields, many CHO cell lines have been genetically engineered to resist cell death. However, the kinetics that governs cell fate in bioreactors are confounded by many variables associated with batch processes. Here, we used CRISPR-Cas9 to create combinatorial knockouts of the three known BCL-2 family effector proteins: Bak1, Bax, and Bok. To assess the response to apoptotic stimuli, cell lines were cultured in the presence of four cytotoxic compounds with different mechanisms of action. A population-based model was developed to describe the behavior of the resulting viable cell dynamics as a function of genotype and treatment. Our results validated the synergistic antiapoptotic nature of Bak1 and Bax, while the deletion of Bok had no significant impact. Importantly, the uniform application of apoptotic stresses permitted direct observation and quantification of a delay in the onset of cell death through Bayesian inference of meaningful model parameters. In addition to the classical death rate, a delay function was found to be essential in the accurate modeling of the cell death response. These findings represent an important bridge between cell line engineering strategies and biological modeling in a bioprocess context.

Network mapping of primary CD34+ cells by Ampliseq based whole transcriptome targeted resequencing identifies unexplored differentiation regulatory relationships.

With the exception of a few master transcription factors, regulators of neutrophil maturation are poorly annotated in the intermediate phenotypes between the granulocyte-macrophage progenitor (GMP) and the mature neutrophil phenotype. Additional challenges in identifying gene expression regulators in differentiation pathways relate to challenges wherein starting cell populations are heterogeneous in lineage potential and development, are spread across various states of quiescence, as well as sample quality and input limitations. These factors contribute to data variability make it difficult to draw simple regulatory inferences. In response we have applied a multi-omics approach using primary blood progenitor cells primed for homogeneous proliferation and granulocyte differentiation states which combines whole transcriptome resequencing (Ampliseq RNA) supported by droplet digital PCR (ddPCR) validation and mass spectrometry-based proteomics in a hypothesis-generation study of neutrophil differentiation pathways. Primary CD34+ cells isolated from human cord blood were first precultured in non-lineage driving medium to achieve an active, proliferating phenotype from which a neutrophil primed progenitor was isolated and cultured in neutrophil lineage supportive medium. Samples were then taken at 24-hour intervals over 9 days and analysed by Ampliseq RNA and mass spectrometry. The Ampliseq dataset depth, breadth and quality allowed for several unexplored transcriptional regulators and ncRNAs to be identified using a combinatorial approach of hierarchical clustering, enriched transcription factor binding motifs, and network mapping. Network mapping in particular increased comprehension of neutrophil differentiation regulatory relationships by implicating ARNT, NHLH1, PLAG1, and 6 non-coding RNAs associated with PU.1 regulation as cell-engineering targets with the potential to increase total neutrophil culture output. Overall, this study develops and demonstrates an effective new hypothesis generation methodology for transcriptome profiling during differentiation, thereby enabling identification of novel gene targets for editing interventions.

Heterologous Production of 6-Deoxyerythronolide B in Escherichia coli through the Wood Werkman Cycle.

Polyketides are a remarkable class of natural products with diverse functional and structural diversity. The class includes many medicinally important molecules with antiviral, antimicrobial, antifungal and anticancer properties. Native bacterial, fungal and plant hosts are often difficult to cultivate and coax into producing the desired product. As a result, Escherichia coli has been used for the heterologous production of polyketides, with the production of 6-deoxyerythronolide B (6-dEB) being the first example. Current strategies for production in E. coli require feeding of exogenous propionate as a source for the precursors propionyl-CoA and S-methylmalonyl-CoA. Here, we show that heterologous polyketide production is possible from glucose as the sole carbon source. The heterologous expression of eight genes from the Wood-Werkman cycle found in Propionibacteria, in combination with expression of the 6-dEB synthases DEBS1, DEBS2 and DEBS3 resulted in 6-dEB formation from glucose as the sole carbon source. Our results show that the Wood-Werkman cycle provides the required propionyl-CoA and the extender unit S-methylmalonyl-CoA to produce up to 0.81 mg/L of 6-dEB in a chemically defined media.

Stoichiometric gene-to-reaction associations enhance model-driven analysis performance: Metabolic response to chronic exposure to Aldrin in prostate cancer.

BACKGROUND: Genome-scale metabolic models (GSMM) integrating transcriptomics have been widely used to study cancer metabolism. This integration is achieved through logical rules that describe the association between genes, proteins, and reactions (GPRs). However, current gene-to-reaction formulation lacks the stoichiometry describing the transcript copies necessary to generate an active catalytic unit, which limits our understanding of how genes modulate metabolism. The present work introduces a new state-of-the-art GPR formulation that considers the stoichiometry of the transcripts (S-GPR). As case of concept, this novel gene-to-reaction formulation was applied to investigate the metabolic effects of the chronic exposure to Aldrin, an endocrine disruptor, on DU145 prostate cancer cells. To this aim we integrated the transcriptomic data from Aldrin-exposed and non-exposed DU145 cells through S-GPR or GPR into a human GSMM by applying different constraint-based-methods. RESULTS: Our study revealed a significant improvement of metabolite consumption/production predictions when S-GPRs are implemented. Furthermore, our computational analysis unveiled important alterations in carnitine shuttle and prostaglandine biosynthesis in Aldrin-exposed DU145 cells that is supported by bibliographic evidences of enhanced malignant phenotype. CONCLUSIONS: The method developed in this work enables a more accurate integration of gene expression data into model-driven methods. Thus, the presented approach is conceptually new and paves the way for more in-depth studies of aberrant cancer metabolism and other diseases with strong metabolic component with important environmental and clinical implications.

RNA-Seq Highlights High Clonal Variation in Monoclonal Antibody Producing CHO Cells.

The development of next-generation sequencing technologies has opened new opportunities to better characterize complex eukaryotic cells. Chinese hamster ovary (CHO) cells play a primary role in therapeutic protein production, with currently five of the top ten blockbuster drugs produced in CHO. However, engineering superior CHO cells with improved production features has had limited success to date and cell lines are still developed through the generation and screening of large strain pools. Here, we applied RNA sequencing to contrast a high and a low monoclonal antibody producing cell line. Rigorous experimental design achieved high reproducibility between biological replicates, remarkably reducing variation to less than 10%. More than 14 000 gene-transcripts are identified and surprisingly 58% are classified as differentially expressed, including 2900 with a fold change higher than 1.5. The largest differences are found for gene-transcripts belonging to regulation of apoptosis, cell death, and protein intracellular transport GO term classifications, which are found to be significantly enriched in the high producing cell line. RNA sequencing is also performed on subclones, where down-regulation of genes encoding secreted glycoproteins is found to be the most significant change. The large number of significant differences even between subclones challenges the notion of identifying and manipulating a few key genes to generate high production CHO cell lines.

Arginine deiminase pathway provides ATP and boosts growth of the gas-fermenting acetogen Clostridium autoethanogenum.

Acetogens are attractive organisms for the production of chemicals and fuels from inexpensive and non-food feedstocks such as syngas (CO, CO2 and H2). Expanding their product spectrum beyond native compounds is dictated by energetics, particularly ATP availability. Acetogens have evolved sophisticated strategies to conserve energy from reduction potential differences between major redox couples, however, this coupling is sensitive to small changes in thermodynamic equilibria. To accelerate the development of strains for energy-intensive products from gases, we used a genome-scale metabolic model (GEM) to explore alternative ATP-generating pathways in the gas-fermenting acetogen Clostridium autoethanogenum. Shadow price analysis revealed a preference of C. autoethanogenum for nine amino acids. This prediction was experimentally confirmed under heterotrophic conditions. Subsequent in silico simulations identified arginine (ARG) as a key enhancer for growth. Predictions were experimentally validated, and faster growth was measured in media containing ARG (tD~4h) compared to growth on yeast extract (tD~9h). The growth-boosting effect of ARG was confirmed during autotrophic growth. Metabolic modelling and experiments showed that acetate production is nearly abolished and fast growth is realised by a three-fold increase in ATP production through the arginine deiminase (ADI) pathway. The involvement of the ADI pathway was confirmed by metabolomics and RNA-sequencing which revealed a ~500-fold up-regulation of the ADI pathway with an unexpected down-regulation of the Wood-Ljungdahl pathway. The data presented here offer a potential route for supplying cells with ATP, while demonstrating the usefulness of metabolic modelling for the discovery of native pathways for stimulating growth or enhancing energy availability.

Overexpression of the regulatory subunit of glutamate-cysteine ligase enhances monoclonal antibody production in CHO cells.

For decades, Chinese hamster ovary (CHO) cells have been the preferred host for therapeutic monoclonal antibody (mAb) production; however, increasing mAb titer by rational engineering remains a challenge. Our previous proteomic analysis in CHO cells suggested that a higher content of glutathione (GSH) might be related to higher productivity. GSH is an important antioxidant, cell detoxifier, and is required to ensure the formation of native disulfide bonds in proteins. To investigate the involvement of GSH in mAb production, we generated stable CHO cell lines overexpressing genes involved in the first step of GSH synthesis; namely the glutamate-cysteine ligase catalytic subunit (Gclc) and the glutamate-cysteine ligase modifier subunit (Gclm). The two genes were reconstructed from our RNA-Seq de novo assembly and then were functionally annotated. Once the sequences of the genes were confirmed using proteogenomics, a transiently expressed mAb was introduced into cell lines overexpressing either Gclc or Gclm. The new cell lines were compared for mAb production to the parental cell line and changes at the proteome level were measured using SWATH. As per our previous proteomics observations, overexpressing Gclm improved productivity, titer, and the frequency of high producer clones by 70%. In contrast, overexpressing Gclc, which produced a higher amount of GSH, did not increase mAb production. We show that GSH cannot be linked to higher productivity and that Gclm may be controlling other cellular processes involved in mAb production yet to be elucidated. Biotechnol. Bioeng. 2017;114: 1825-1836. © 2017 Wiley Periodicals, Inc.

Spliced synthetic genes as internal controls in RNA sequencing experiments.

RNA sequencing (RNA-seq) can be used to assemble spliced isoforms, quantify expressed genes and provide a global profile of the transcriptome. However, the size and diversity of the transcriptome, the wide dynamic range in gene expression and inherent technical biases confound RNA-seq analysis. We have developed a set of spike-in RNA standards, termed 'sequins' (sequencing spike-ins), that represent full-length spliced mRNA isoforms. Sequins have an entirely artificial sequence with no homology to natural reference genomes, but they align to gene loci encoded on an artificial in silico chromosome. The combination of multiple sequins across a range of concentrations emulates alternative splicing and differential gene expression, and it provides scaling factors for normalization between samples. We demonstrate the use of sequins in RNA-seq experiments to measure sample-specific biases and determine the limits of reliable transcript assembly and quantification in accompanying human RNA samples. In addition, we have designed a complementary set of sequins that represent fusion genes arising from rearrangements of the in silico chromosome to aid in cancer diagnosis. RNA sequins provide a qualitative and quantitative reference with which to navigate the complexity of the human transcriptome.

Tetanus toxin production is triggered by the transition from amino acid consumption to peptides.

Bacteria produce some of the most potent biomolecules known, of which many cause serious diseases such as tetanus. For prevention, billions of people and countless animals are immunised with the highly effective vaccine, industrially produced by large-scale fermentation. However, toxin production is often hampered by low yields and batch-to-batch variability. Improved productivity has been constrained by a lack of understanding of the molecular mechanisms controlling toxin production. Here we have developed a reproducible experimental framework for screening phenotypic determinants in Clostridium tetani under a process that mimics an industrial setting. We show that amino acid depletion induces production of the tetanus toxin. Using time-course transcriptomics and extracellular metabolomics to generate a 'fermentation atlas' that ascribe growth behaviour, nutrient consumption and gene expression to the fermentation phases, we found a subset of preferred amino acids. Exponential growth is characterised by the consumption of those amino acids followed by a slower exponential growth phase where peptides are consumed, and toxin is produced. The results aim at assisting in fermentation medium design towards the improvement of vaccine production yields and reproducibility. In conclusion, our work not only provides deep fermentation dynamics but represents the foundation for bioprocess design based on C. tetani physiological behaviour under industrial settings.

A probabilistic framework for the exploration of enzymatic capabilities based on feasible kinetics and control analysis.

BACKGROUND: Analysis of limiting steps within enzyme-catalyzed reactions is fundamental to understand their behavior and regulation. Methods capable of unravelling control properties and exploring kinetic capabilities of enzymatic reactions would be particularly useful for protein and metabolic engineering. While single-enzyme control analysis formalism has previously been applied to well-studied enzymatic mechanisms, broader application of this formalism is limited in practice by the limited amount of kinetic data and the difficulty of describing complex allosteric mechanisms. METHODS: To overcome these limitations, we present here a probabilistic framework enabling control analysis of previously unexplored mechanisms under uncertainty. By combining a thermodynamically consistent parameterization with an efficient Sequential Monte Carlo sampler embedded in a Bayesian setting, this framework yields insights into the capabilities of enzyme-catalyzed reactions with modest kinetic information, provided that the catalytic mechanism and a thermodynamic reference point are defined. RESULTS: The framework was used to unravel the impact of thermodynamic affinity, substrate saturation levels and effector concentrations on the flux control and response coefficients of a diverse set of enzymatic reactions. CONCLUSIONS: Our results highlight the importance of the metabolic context in the control analysis of isolated enzymes as well as the use of statistically sound methods for their interpretation. GENERAL SIGNIFICANCE: This framework significantly expands our current capabilities for unravelling the control properties of general reaction kinetics with limited amount of information. This framework will be useful for both theoreticians and experimentalists in the field.

Filling the void: allogeneic myeloid cells for transplantation.

PURPOSE OF REVIEW: The success of allogeneic haematopoietic stem and progenitor cell (HSPC) transplantations remains inconsistent. Umbilical cord blood (UCB) is a promising source of HSPCs for transplantation, but low cell yield hampers its widespread use. Multiple strategies are being developed to manipulate UCB to either increase HSPC content or enhance bone marrow homing upon transfusion. RECENT FINDINGS: Several ex-vivo manipulation protocols have increased engraftment success in recent phase I/II clinical trials. Additionally, by exploiting knowledge of the transcriptome, mature cells were dedifferentiated into induced haematopoietic stem cells capable of self-renewal and reconstitution of haematopoiesis in vivo. SUMMARY: UCB is a more readily available source of allogeneic transplant material compared with bone marrow and mobilized peripheral blood. However, the number of HSPCs in a graft is correlated to the rate and success of engraftment and UCB grafts typically contain 10 times less cells compared with bone marrow or mobilized peripheral blood grafts that contain around 1 × 108 CD34⁺ cells. Recently, research efforts have focused on increasing UCB engrafting cells in addition to the methods to accelerate engraftment or to provide transient protection and support until engraftment succeeds.

Cyclic-di-AMP synthesis by the diadenylate cyclase CdaA is modulated by the peptidoglycan biosynthesis enzyme GlmM in Lactococcus lactis.

The second messenger cyclic-di-adenosine monophosphate (c-di-AMP) plays important roles in growth, virulence, cell wall homeostasis, potassium transport and affects resistance to antibiotics, heat and osmotic stress. Most Firmicutes contain only one c-di-AMP synthesizing diadenylate cyclase (CdaA); however, little is known about signals and effectors controlling CdaA activity and c-di-AMP levels. In this study, a genetic screen was employed to identify components which affect the c-di-AMP level in Lactococcus. We characterized suppressor mutations that restored osmoresistance to spontaneous c-di-AMP phosphodiesterase gdpP mutants, which contain high c-di-AMP levels. Loss-of-function and gain-of-function mutations were identified in the cdaA and gdpP genes, respectively, which led to lower c-di-AMP levels. A mutation was also identified in the phosphoglucosamine mutase gene glmM, which is commonly located within the cdaA operon in bacteria. The glmM I154F mutation resulted in a lowering of the c-di-AMP level and a reduction in the key peptidoglycan precursor UDP-N-acetylglucosamine in L. lactis. C-di-AMP synthesis by CdaA was shown to be inhibited by GlmM(I154F) more than GlmM and GlmM(I154F) was found to bind more strongly to CdaA than GlmM. These findings identify GlmM as a c-di-AMP level modulating protein and provide a direct connection between c-di-AMP synthesis and peptidoglycan biosynthesis.