Harnessing metabolic plasticity in CHO cells for enhanced perfusion cultivation.

Chinese Hamster Ovary (CHO) cells have rapidly become a cornerstone in biopharmaceutical production. Recently, a reinvigoration of perfusion culture mode in CHO cell cultivation has been observed. However, most cell lines currently in use have been engineered and adapted for fed-batch culture methods, and may not perform optimally under perfusion conditions. To improve the cell's resilience and viability during perfusion culture, we cultured a triple knockout CHO cell line, deficient in three apoptosis related genes BAX, BAK, and BOK in a perfusion system. After 20 days of culture, the cells exhibited a halt in cell proliferation. Interestingly, following this phase of growth arrest, the cells entered a second growth phase. During this phase, the cell numbers nearly doubled, but cell specific productivity decreased. We performed a proteomics investigation, elucidating a distinct correlation between growth arrest and cell cycle arrest and showing an upregulation of the central carbon metabolism and oxidative phosphorylation. The upregulation was partially reverted during the second growth phase, likely caused by intragenerational adaptations to stresses encountered. A phase-dependent response to oxidative stress was noted, indicating glutathione has only a secondary role during cell cycle arrest. Our data provides evidence of metabolic regulation under high cell density culturing conditions and demonstrates that cell growth arrest can be overcome. The acquired insights have the potential to not only enhance our understanding of cellular metabolism but also contribute to the development of superior cell lines for perfusion cultivation.

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.

Faster Growth Enhances Low Carbon Fuel and Chemical Production Through Gas Fermentation.

Gas fermentation offers both fossil carbon-free sustainable production of fuels and chemicals and recycling of gaseous and solid waste using gas-fermenting microbes. Bioprocess development, systems-level analysis of biocatalyst metabolism, and engineering of cell factories are advancing the widespread deployment of the commercialised technology. Acetogens are particularly attractive biocatalysts but effects of the key physiological parameter-specific growth rate (µ)-on acetogen metabolism and the gas fermentation bioprocess have not been established yet. Here, we investigate the µ-dependent bioprocess performance of the model-acetogen Clostridium autoethanogenum in CO and syngas (CO + CO2+H2) grown chemostat cultures and assess systems-level metabolic responses using gas analysis, metabolomics, transcriptomics, and metabolic modelling. We were able to obtain steady-states up to µ ∼2.8 day-1 (∼0.12 h-1) and show that faster growth supports both higher yields and productivities for reduced by-products ethanol and 2,3-butanediol. Transcriptomics data revealed differential expression of 1,337 genes with increasing µ and suggest that C. autoethanogenum uses transcriptional regulation to a large extent for facilitating faster growth. Metabolic modelling showed significantly increased fluxes for faster growing cells that were, however, not accompanied by gene expression changes in key catabolic pathways for CO and H2 metabolism. Cells thus seem to maintain sufficient "baseline" gene expression to rapidly respond to CO and H2 availability without delays to kick-start metabolism. Our work advances understanding of transcriptional regulation in acetogens and shows that faster growth of the biocatalyst improves the gas fermentation bioprocess.

Multi-omic characterisation of Streptomyces hygroscopicus NRRL 30439: detailed assessment of its secondary metabolic potential.

The emergence of multidrug-resistant pathogenic bacteria creates a demand for novel antibiotics with distinct mechanisms of action. Advances in next-generation genome sequencing promised a paradigm shift in the quest to find new bioactive secondary metabolites. Genome mining has proven successful for predicting putative biosynthetic elements in secondary metabolite superproducers such as Streptomycetes. However, genome mining approaches do not inform whether biosynthetic gene clusters are dormant or active under given culture conditions. Here we show that using a multi-omics approach in combination with antiSMASH, it is possible to assess the secondary metabolic potential of a Streptomyces strain capable of producing mannopeptimycin, an important cyclic peptide effective against Gram-positive infections. The genome of Streptomyces hygroscopicus NRRL 30439 was first sequenced using PacBio RSII to obtain a closed genome. A chemically defined medium was then used to elicit a nutrient stress response in S. hygroscopicus NRRL 30439. Detailed extracellular metabolomics and intracellular proteomics were used to profile and segregate primary and secondary metabolism. Our results demonstrate that the combination of genomics, proteomics and metabolomics enables rapid evaluation of a strain's performance in bioreactors for industrial production of secondary metabolites.

Root samples provide early and improved detection of Candidatus Liberibacter asiaticus in Citrus.

Huanglongbing (HLB), or Citrus Greening, is one of the most devastating diseases affecting agriculture today. Widespread throughout Citrus growing regions of the world, it has had severe economic consequences in all areas it has invaded. With no treatment available, management strategies focus on suppression and containment. Effective use of these costly control strategies relies on rapid and accurate identification of infected plants. Unfortunately, symptoms of the disease are slow to develop and indistinct from symptoms of other biotic/abiotic stressors. As a result, diagnosticians have focused on detecting the pathogen, Candidatus Liberibacter asiaticus, by DNA-based detection strategies utilizing leaf midribs for sampling. Recent work has shown that fibrous root decline occurs in HLB-affected trees before symptom development among leaves. Moreover, the pathogen, Ca. Liberibacter asiaticus, has been shown to be more evenly distributed within roots than within the canopy. Motivated by these observations, a longitudinal study of young asymptomatic trees was established to observe the spread of disease through time and test the relative effectiveness of leaf- and root-based detection strategies. Detection of the pathogen occurred earlier, more consistently, and more often in root samples than in leaf samples. Moreover, little influence of geography or host variety was found on the probability of detection.