Antibody glycan quality predicted from CHO cell culture media markers and machine learning.

N-glycosylation can have a profound effect on the quality of mAb therapeutics. In biomanufacturing, one of the ways to influence N-glycosylation patterns is by altering the media used to grow mAb cell expression systems. Here, we explore the potential of machine learning (ML) to forecast the abundances of N-glycan types based on variables related to the growth media.

Driving towards digital biomanufacturing by CHO genome-scale models.

Genome-scale metabolic models (GEMs) of Chinese hamster ovary (CHO) cells are valuable for gaining mechanistic understanding of mammalian cell metabolism and cultures. We provide a comprehensive overview of past and present developments of CHO-GEMs and in silico methods within the flux balance analysis (FBA) framework, focusing on their practical utility in rational cell line development and bioprocess improvements. There are many opportunities for further augmenting the model coverage and establishing integrative models that account for different cellular processes and data for future applications.

Evaluating oleaginous yeasts for enhanced microbial lipid production using sweetwater as a sustainable feedstock.

Background: Yeasts exhibit promising potential for the microbial conversion of crude glycerol, owing to their versatility in delivering a wide range of value-added products, particularly lipids. Sweetwater, a methanol-free by-product of the fat splitting process, has emerged as a promising alternative feedstock for the microbial utilization of crude glycerol. To further optimize sweetwater utilization, we compared the growth and lipid production capabilities of 21 oleaginous yeast strains under different conditions with various glycerol concentrations, sweetwater types and pH.

Mitigating biomass composition uncertainties in flux balance analysis using ensemble representations.

The biomass equation is a critical component in genome-scale metabolic models (GEMs): it is used as the objective function in flux balance analysis (FBA). This equation accounts for the quantities of all known biomass precursors that are required for cell growth based on the macromolecular and monomer compositions measured at certain conditions. However, it is often reported that the macromolecular composition of cells could change across different environmental conditions and thus the use of the same single biomass equation in FBA, under multiple conditions, is questionable.

Systematic evaluation of genome-wide metabolic landscapes in lactic acid bacteria reveals diet- and strain-specific probiotic idiosyncrasies.

Lactic acid bacteria (LAB) are well known to elicit health benefits in humans, but their functional metabolic landscapes remain unexplored. Here, we analyze differences in growth, intestinal persistence, and postbiotic biosynthesis of six representative LAB and their interactions with 15 gut bacteria under 11 dietary regimes by combining multi-omics and in silico modeling. We confirmed predictions on short-term persistence of LAB and their interactions with commensals using cecal microbiome abundance and spent-medium experiments.

Combined multivariate statistical and flux balance analyses uncover media bottlenecks to the growth and productivity of Chinese hamster ovary cell cultures.

Chinese hamster ovary (CHO) cells are widely used for producing recombinant proteins. To enhance their productivity and product quality, media reformulation has been a key strategy, albeit with several technical challenges, due to the myriad of complex molecular mechanisms underlying media effects on culture performance. Thus, it is imperative to characterize metabolic bottlenecks under various media conditions systematically.

Systems Biology of Gut Microbiota-Human Receptor Interactions: Toward Anti-inflammatory Probiotics.

The incidence and prevalence of inflammatory disorders have increased globally, and is projected to double in the next decade. Gut microbiome-based therapeutics have shown promise in ameliorating chronic inflammation. However, they are largely experimental, context- or strain-dependent and lack a clear mechanistic basis.

Harnessing the potential of machine learning for advancing "Quality by Design" in biomanufacturing.

Ensuring consistent high yields and product quality are key challenges in biomanufacturing. Even minor deviations in critical process parameters (CPPs) such as media and feed compositions can significantly affect product critical quality attributes (CQAs). To identify CPPs and their interdependencies with product yield and CQAs, design of experiments, and multivariate statistical approaches are typically used in industry.

Enhancing Microbiome Research through Genome-Scale Metabolic Modeling.

Construction and analysis of genome-scale metabolic models (GEMs) is a well-established systems biology approach that can be used to predict metabolic and growth phenotypes. The ability of GEMs to produce mechanistic insight into microbial ecological processes makes them appealing tools that can open a range of exciting opportunities in microbiome research. Here, we briefly outline these opportunities, present current rate-limiting challenges for the trustworthy application of GEMs to microbiome research, and suggest approaches for moving the field forward.

Multi-omics profiling of a CHO cell culture system unravels the effect of culture pH on cell growth, antibody titer, and product quality.

A robust monoclonal antibody (mAb) bioprocess requires physiological parameters such as temperature, pH, or dissolved oxygen to be well-controlled as even small variations in them could potentially impact the final product quality. For instance, pH substantially affects N-glycosylation, protein aggregation, and charge variant profiles, as well as mAb productivity. However, relatively less is known about how pH jointly influences product quality and titer.

Oral microbiome-systemic link studies: perspectives on current limitations and future artificial intelligence-based approaches.

In the past decade, there has been a tremendous increase in studies on the link between oral microbiome and systemic diseases. However, variations in study design and confounding variables across studies often lead to inconsistent observations. In this narrative review, we have discussed the potential influence of study design and confounding variables on the current sequencing-based oral microbiome-systemic disease link studies.

Enzyme capacity-based genome scale modelling of CHO cells.

Chinese hamster ovary (CHO) cells are most prevalently used for producing recombinant therapeutics in biomanufacturing. Recently, more rational and systems approaches have been increasingly exploited to identify key metabolic bottlenecks and engineering targets for cell line engineering and process development based on the CHO genome-scale metabolic model which mechanistically characterizes cell culture behaviours. However, it is still challenging to quantify plausible intracellular fluxes and discern metabolic pathway usages considering various clonal traits and bioprocessing conditions.

Publisher Correction: MEMOTE for standardized genome-scale metabolic model testing.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Genome-scale metabolic reconstruction and in silico analysis of the rice leaf blight pathogen, Xanthomonas oryzae.

Xanthomonas oryzae pv. oryzae (Xoo) is a vascular pathogen that causes leaf blight in rice, leading to severe yield losses. Since the usage of chemical control methods has not been very promising for the future disease management, it is of high importance to systematically gain new insights about Xoo virulence and pathogenesis, and devise effective strategies to combat the rice disease.

In silico model-based characterization of metabolic response to harsh sparging stress in fed-batch CHO cell cultures.

Mammalian cell culture platform has been successfully implemented for industrial biopharmaceutical production through the advancements in early stage process development including cell-line engineering, media design and process optimization. However, late stage developments such as scale-up, scale-down and large-scale cell cultivation still face many industrial challenges to acquire comparable process performance between different culture scales. One of them is the sparging strategy which significantly affects productivity, quality and comparability.

Multi-omics profiling of CHO parental hosts reveals cell line-specific variations in bioprocessing traits.

Chinese hamster ovary (CHO) cells are the most prevalent mammalian cell factories for producing recombinant therapeutic proteins due to their ability to synthesize human-like post-translational modifications and ease of maintenance in suspension cultures. Currently, a wide variety of CHO host cell lines has been developed; substantial differences exist in their phenotypes even when transfected with the same target vector. However, relatively less is known about the influence of their inherited genetic heterogeneity on phenotypic traits and production potential from the bioprocessing point of view.

Metabolic Modeling of Microbial Community Interactions for Health, Environmental and Biotechnological Applications.

In nature, microbes do not exist in isolation but co-exist in a variety of ecological and biological environments and on various host organisms. Due to their close proximity, these microbes interact among themselves, and also with the hosts in both positive and negative manners. Moreover, these interactions may modulate dynamically upon external stimulus as well as internal community changes.

In silico model-guided identification of transcriptional regulator targets for efficient strain design.

Background: Cellular metabolism is tightly regulated by hard-wired multiple layers of biological processes to achieve robust and homeostatic states given the limited resources. As a result, even the most intuitive enzyme-centric metabolic engineering endeavours through the up-/down-regulation of multiple genes in biochemical pathways often deliver insignificant improvements in the product yield. In this regard, targeted engineering of transcriptional regulators (TRs) that control several metabolic functions in modular patterns is an interesting strategy.

Comparative phenotypic analysis of CHO clones and culture media for lactate shift.

We explored the effects of media and clonal variation on the lactate shift which can be considered as one of the desirable features in CHO cell culture. Various culture profiles with the specific growth and antibody production rates under three different media conditions in two CHO producing clones were evaluated by resorting to multivariate statistical analysis. In most cases, glutamine depletion coincided with lactate consumption, suggesting that glutaminolysis rather than glycolysis was the preferred pathway for the pyruvate supply toward lactate production.

Ginseng Genome Database: an open-access platform for genomics of Panax ginseng.

Background: The ginseng (Panax ginseng C.A. Meyer) is a perennial herbaceous plant that has been used in traditional oriental medicine for thousands of years.

Genome and evolution of the shade-requiring medicinal herb Panax ginseng.

Panax ginseng C. A. Meyer, reputed as the king of medicinal herbs, has slow growth, long generation time, low seed production and complicated genome structure that hamper its study.

Genome-scale model-driven strain design for dicarboxylic acid production in Yarrowia lipolytica.

Background: Recently, there have been several attempts to produce long-chain dicarboxylic acids (DCAs) in various microbial hosts. Of these, Yarrowia lipolytica has great potential due to its oleaginous characteristics and unique ability to utilize hydrophobic substrates. However, Y.

Genome-scale modeling and transcriptome analysis of Leuconostoc mesenteroides unravel the redox governed metabolic states in obligate heterofermentative lactic acid bacteria.

Obligate heterofermentative lactic acid bacteria (LAB) are well-known for their beneficial health effects in humans. To delineate the incompletely characterized metabolism that currently limits their exploitation, at systems-level, we developed a genome-scale metabolic model of the representative obligate heterofermenting LAB, Leuconostoc mesenteroides (iLME620). Constraint-based flux analysis was then used to simulate several qualitative and quantitative phenotypes of L.