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. The ML models exploit a dataset consisting of detailed glycomic characterisation of Anti-HER fed-batch bioreactor cell cultures measured daily under 12 different culture conditions, such as changes in levels of dissolved oxygen, pH, temperature, and the use of two different commercially available media. By performing spent media quantitation and subsequent calculation of pseudo cell consumption rates (termed media markers) as inputs to the ML model, we were able to demonstrate a small subset of media markers (18 selected out of 167 mass spectrometry peaks) in a Chinese Hamster Ovary (CHO) cell cultures are important to model N-glycan relative abundances (Regression - correlations between 0.80-0.92; Classification - AUC between 75.0-97.2). The performances suggest the ML models can infer N-glycan critical quality attributes from extracellular media as a proxy. Given its accuracy, we envisage its potential applications in biomaufactucuring, especially in areas of process development, downstream and upstream bioprocessing.

A simple and highly sensitive LC-MS workflow for characterization and quantification of ADC cleavable payloads.

Antibody-drug conjugates (ADC) payloads are cleavable drugs that act as the warhead to exert an ADC's cytotoxic effects on cancer cells intracellularly. A simple and highly sensitive workflow is developed and validated for the simultaneous quantification of six ADC payloads, namely SN-38, MTX, DXd, MMAE, MMAF and Calicheamicin (CM). The workflow consists of a short and simple sample extraction using a methanol-ethanol mixture, followed by a fast liquid chromatography tandem mass spectrometry (LC-MS/MS) analysis. The results showed that well-validated linear response ranges of 0.4-100 nM for SN38, MTX and DXd, 0.04-100 nM for MMAE and MMAF, 0.4-1000 nM for CM were achieved in mouse serum. Recoveries for all six payloads at three different concentrations (low, medium and high) were more than 85%. An ultra-low sample volume of only 5 µL of serum is required due to the high sensitivity of the method. This validated method was successfully applied to a pharmacokinetic study to quantify MMAE in mouse serum samples.

MSC-Derived Small Extracellular Vesicles Exert Cardioprotective Effect Through Reducing VLCFAs and Apoptosis in Human Cardiac Organoid IRI Model.

Cardiovascular diseases (CVDs) are the leading cause of death worldwide, accounting for 31% of all deaths globally. Myocardial ischemia-reperfusion injury (IRI), a common complication of CVDs, is a major cause of mortality and morbidity. Studies have shown efficacious use of mesenchymal stem cells-derived small extracellular vesicles (MSCs-EVs) to mitigate IRI in animals, but few research has been done on human-related models. In this study, human embryonic stem cell-derived chambered cardiac organoid (CCO) was used as a model system to study the effects of MSC-EVs on myocardial IRI. The results revealed that MSC-EVs treatment reduced apoptosis and improved contraction resumption of the CCOs. Metabolomics analysis showed that this effect could be attributed to EVs' ability to prevent the accumulation of unsaturated very long-chain fatty acids (VLCFAs). This was corroborated when inhibition of fatty acid synthase, which was reported to reduce VLCFAs, produced a similar protective effect to EVs. Overall, this study uncovered the mechanistic role of MSC-EVs in mitigating IRI that involves preventing the accumulation of unsaturated VLCFA, decreasing cell death, and improving contraction resumption in CCOs.

Understanding and controlling the molecular mechanisms of protein aggregation in mAb therapeutics.

In antibody development and manufacturing, protein aggregation is a common challenge that can lead to serious efficacy and safety issues. To mitigate this problem, it is important to investigate its molecular origins. This review discusses (1) our current molecular understanding and theoretical models of antibody aggregation, (2) how various stress conditions related to antibody upstream and downstream bioprocesses can trigger aggregation, and (3) current mitigation strategies employed towards inhibiting aggregation. We discuss the relevance of the aggregation phenomenon in the context of novel antibody modalities and highlight how in silico approaches can be exploited to mitigate it.

The effect of inhibition of receptor tyrosine kinase AXL on DNA damage response in ovarian cancer.

AXL is a receptor tyrosine kinase that is often overexpressed in cancers. It contributes to pathophysiology in cancer progression and therapeutic resistance, making it an emerging therapeutic target. The first-in-class AXL inhibitor bemcentinib (R428/BGB324) has been granted fast track designation by the U.S. Food and Drug Administration (FDA) in STK11-mutated advanced metastatic non-small cell lung cancer and was also reported to show selective sensitivity towards ovarian cancers (OC) with a Mesenchymal molecular subtype. In this study, we further explored AXL's role in mediating DNA damage responses by using OC as a disease model. AXL inhibition using R428 resulted in the increase of DNA damage with the concurrent upregulation of DNA damage response signalling molecules. Furthermore, AXL inhibition rendered cells more sensitive to the inhibition of ATR, a crucial mediator for replication stress. Combinatory use of AXL and ATR inhibitors showed additive effects in OC. Through SILAC co-immunoprecipitation mass spectrometry, we identified a novel binding partner of AXL, SAM68, whose loss in OC cells harboured phenotypes in DNA damage responses similar to AXL inhibition. In addition, AXL- and SAM68-deficiency or R428 treatment induced elevated levels of cholesterol and upregulated genes in the cholesterol biosynthesis pathway. There might be a protective role of cholesterol in shielding cancer cells against DNA damage induced by AXL inhibition or SMA68 deficiency.

Muscle Injuries Induce a Prostacyclin-PPARγ/PGC1a-FAO Spike That Boosts Regeneration.

It is well-known that muscle regeneration declines with aging, and aged muscles undergo degenerative atrophy or sarcopenia. While exercise and acute injury are both known to induce muscle regeneration, the molecular signals that help trigger muscle regeneration have remained unclear. Here, mass spectrometry imaging (MSI) is used to show that injured muscles induce a specific subset of prostanoids during regeneration, including PGG1, PGD2, and the prostacyclin PGI2. The spike in prostacyclin promotes skeletal muscle regeneration via myoblasts, and declines with aging. Mechanistically, the prostacyclin spike promotes a spike in PPARγ/PGC1a signaling, which induces a spike in fatty acid oxidation (FAO) to control myogenesis. LC-MS/MS and MSI further confirm that an early FAO spike is associated with normal regeneration, but muscle FAO became dysregulated during aging. Functional experiments demonstrate that the prostacyclin-PPARγ/PGC1a-FAO spike is necessary and sufficient to promote both young and aged muscle regeneration, and that prostacyclin can synergize with PPARγ/PGC1a-FAO signaling to restore aged muscles' regeneration and physical function. Given that the post-injury prostacyclin-PPARγ-FAO spike can be modulated pharmacologically and via post-exercise nutrition, this work has implications for how prostacyclin-PPARγ-FAO might be fine-tuned to promote regeneration and treat muscle diseases of aging.

Systematic Adaptation of Bacillus licheniformis to 2-Phenylethanol Stress.

The compound 2-phenylethanol (2-PE) is a bulk flavor and fragrance with a rose-like aroma that can be produced by microbial cell factories, but its cellular toxicity inhibits cellular growth and limits strain performance. Specifically, the microbe Bacillus licheniformis has shown a strong tolerance to 2-PE. Understanding these tolerance mechanisms is crucial for achieving the hyperproduction of 2-PE. In this report, the mechanisms of B. licheniformis DW2 resistance to 2-PE were studied by multi-omics technology coupled with physiological and molecular biological approaches. 2-PE induced reactive oxygen species formation and affected nucleic acid, ribosome, and cell wall synthesis. To manage 2-PE stress, the antioxidant and global stress response systems were activated; the repair system of proteins and homeostasis of the ion and osmotic were initiated. Furthermore, the tricarboxylic acid cycle and NADPH synthesis pathways were upregulated; correspondingly, scanning electron microscopy revealed that cell morphology was changed. These results provide deeper insights into the adaptive mechanisms of B. licheniformis to 2-PE and highlight the potential targets for genetic manipulation to enhance 2-PE resistance. IMPORTANCE The ability to tolerate organic solvents is essential for bacteria producing these chemicals with high titer, yield, and productivity. As exemplified by 2-PE, bioproduction of 2-PE represents a promising alternative to chemical synthesis and plant extraction approaches, but its toxicity hinders successful large-scale microbial production. Here, a multi-omics approach is employed to systematically study the mechanisms of B. licheniformis DW2 resistance to 2-PE. As a 2-PE-tolerant strain, B. licheniformis displays multifactorial mechanisms of 2-PE tolerance, including activating global stress response and repair systems, increasing NADPH supply, changing cell morphology and membrane composition, and remodeling metabolic pathways. The current work yields novel insights into the mechanisms of B. licheniformis resistance to 2-PE. This knowledge can also be used as a clue for improving bacterial performances to achieve industrial-scale production of 2-PE and potentially applied to the production of other relevant organic solvents, such as tyrosol and hydroxytyrosol.

Cottonseed Meal Protein Isolate as a New Source of Alternative Proteins: A Proteomics Perspective.

Cottonseed meal (CSM) is a good source of dietary proteins but is unsuitable for human consumption due to its gossypol content. To unlock its potential, we developed a protein extraction process with a gossypol removal treatment to generate CSM protein isolate (CSMPI) with ultra-low gossypol content. This process successfully reduced the free and total gossypol content to 4.8 ppm and 147.2 ppm, respectively, far below the US FDA limit. In addition, the functional characterisation of CSMPI revealed a better oil absorption capacity and water solubility than pea protein isolate. Proteome profiling showed that the treatment improved protein identification, while SDS-PAGE analysis indicated that the treatment did not induce protein degradation. Amino acid analysis revealed that post-treated CSMPI was rich in branched-chain amino acids (BCAAs). Mass spectrometry analysis of various protein fractions obtained from an in vitro digestibility assay helped to establish the digestibility profile of CSM proteins. Several potential allergens in CSMPI were also found using allergenic prediction software, but further evaluation based on their digestibility profiles and literature reviews suggests that the likelihood of CSMPI allergenicity remains low. Overall, our results help to navigate and direct the application of CSMPIs as alternative proteins toward nutritive human food application.

Direct identification of A-to-I editing sites with nanopore native RNA sequencing.

Inosine is a prevalent RNA modification in animals and is formed when an adenosine is deaminated by the ADAR family of enzymes. Traditionally, inosines are identified indirectly as variants from Illumina RNA-sequencing data because they are interpreted as guanosines by cellular machineries. However, this indirect method performs poorly in protein-coding regions where exons are typically short, in non-model organisms with sparsely annotated single-nucleotide polymorphisms, or in disease contexts where unknown DNA mutations are pervasive. Here, we show that Oxford Nanopore direct RNA sequencing can be used to identify inosine-containing sites in native transcriptomes with high accuracy. We trained convolutional neural network models to distinguish inosine from adenosine and guanosine, and to estimate the modification rate at each editing site. Furthermore, we demonstrated their utility on the transcriptomes of human, mouse and Xenopus. Our approach expands the toolkit for studying adenosine-to-inosine editing and can be further extended to investigate other RNA modifications.

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. Although these models can predict the effect of CPPs on product yield, there is room to improve CQA prediction performance by capturing the complex relationships in high-dimensional data. In this regard, machine learning (ML) approaches offer immense potential in handling non-linear datasets and thus are able to identify new CPPs that could effectively predict the CQAs. ML techniques can also be synergized with mechanistic models as a 'hybrid ML' or 'white box ML' to identify how CPPs affect the product yield and quality mechanistically, thus enabling rational design and control of the bioprocess. In this review, we describe the role of statistical modeling in Quality by Design (QbD) for biomanufacturing, and provide a generic outline on how relevant ML can be used to meaningfully analyze bioprocessing datasets. We then offer our perspectives on how relevant use of ML can accelerate the implementation of systematic QbD within the biopharma 4.0 paradigm.

Fatty acid oxidation is a druggable gateway regulating cellular plasticity for driving metastasis in breast cancer.

Cell state transitions control the functional behavior of cancer cells. Epithelial-to-mesenchymal transition (EMT) confers cancer stem cell-like properties, enhanced tumorigenicity and drug resistance to tumor cells, while mesenchymal-epithelial transition (MET) reverses these phenotypes. Using high-throughput chemical library screens, retinoids are found to be potent promoters of MET that inhibit tumorigenicity in basal-like breast cancer. Cell state transitions are defined by reprogramming of lipid metabolism. Retinoids bind cognate nuclear receptors, which target lipid metabolism genes, thereby redirecting fatty acids for ß-oxidation in the mesenchymal cell state towards lipid storage in the epithelial cell state. Disruptions of key metabolic enzymes mediating this flux inhibit MET. Conversely, perturbations to fatty acid oxidation (FAO) rechannel fatty acid flux and promote a more epithelial cell phenotype, blocking EMT-driven breast cancer metastasis in animal models. FAO impinges on the epigenetic control of EMT through acetyl-CoA-dependent regulation of histone acetylation on EMT genes, thus determining cell states.

Nitro-Deficient Niclosamide Confers Reduced Genotoxicity and Retains Mitochondrial Uncoupling Activity for Cancer Therapy.

Niclosamide is an oral anthelmintic drug, approved for use against tapeworm infections. Recent studies suggest however that niclosamide may have broader clinical applications in cancers, spurring increased interest in the functions and mechanisms of niclosamide. Previously, we reported that niclosamide targets a metabolic vulnerability in p53-deficient tumours, providing a basis for patient stratification and personalised treatment strategies. In the present study, we functionally characterised the contribution of the aniline 4'-NO2 group on niclosamide to its cellular activities. We demonstrated that niclosamide induces genome-wide DNA damage that is mechanistically uncoupled from its antitumour effects mediated through mitochondrial uncoupling. Elimination of the nitro group in ND-Nic analogue significantly reduced γH2AX signals and DNA breaks while preserving its antitumour mechanism mediated through a calcium signalling pathway and arachidonic acid metabolism. Lipidomics profiling further revealed that ND-Nic-treated cells retained a metabolite profile characteristic of niclosamide-treated cells. Notably, quantitative scoring of drug sensitivity suggests that elimination of its nitro group enhanced the target selectivity of niclosamide against p53 deficiency. Importantly, the results also raise concern that niclosamide may impose a pleiotropic genotoxic effect, which limits its clinical efficacy and warrants further investigation into alternative drug analogues that may ameliorate any potential unwanted side effects.

Applications and analysis of hydrolysates in animal cell culture.

Animal cells are used in the manufacturing of complex biotherapeutic products since the 1980s. From its initial uses in biological research to its current importance in the biopharmaceutical industry, many types of culture media were developed: from serum-based media to serum-free to protein-free chemically defined media. The cultivation of animal cells economically has become the ultimate goal in the field of biomanufacturing. Serum serves as a source of amino acids, lipids, proteins and most importantly growth factors and hormones, which are essential for many cell types. However, the use of serum is unfavorable due to its high price tag, increased lot-to-lot variations and potential risk of microbial contamination. Efforts are progressively being made to replace serum with recombinant proteins such as growth factors, cytokines and hormones, as well as supplementation with lipids, vitamins, trace elements and hydrolysates. While hydrolysates are more complex, they provide a diverse source of nutrients to animal cells, with potential beneficial effects beyond the nutritional value. In this review, we discuss the use of hydrolysates in animal cell culture and briefly cover the composition of hydrolysates, mode of action and potential contaminants with some perspectives on its potential role in animal cell culture media formulations in the future.

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. In this study, we investigated the effect of pH on culture performance, product titer, and quality profiles by applying longitudinal multi-omics profiling, including transcriptomics, proteomics, metabolomics, and glycomics, at three different culture pH set points. The subsequent systematic analysis of multi-omics data showed that pH set points differentially regulated various intracellular pathways including intracellular vesicular trafficking, cell cycle, and apoptosis, thereby resulting in differences in specific productivity, product titer, and quality profiles. In addition, a time-dependent variation in mAb N-glycosylation profiles, independent of pH, was identified to be mainly due to the accumulation of mAb proteins in the endoplasmic reticulum disrupting cellular homeostasis over culture time. Overall, this multi-omics-based study provides an in-depth understanding of the intracellular processes in mAb-producing CHO cell line under varied pH conditions, and could serve as a baseline for enabling the quality optimization and control of mAb production.

Semi-Automated Glycoproteomic Data Analysis of LC-MS Data Using GlycopeptideGraphMS in Process Development of Monoclonal Antibody Biologics.

The glycosylation of antibody-based proteins is vital in translating the right therapeutic outcomes of the patient. Despite this, significant infrastructure is required to analyse biologic glycosylation in various unit operations from biologic development, process development to QA/QC in bio-manufacturing. Simplified mass spectrometers offer ease of operation as well as the portability of method development across various operations. Furthermore, data analysis would need to have a degree of automation to relay information back to the manufacturing line. We set out to investigate the applicability of using a semiautomated data analysis workflow to investigate glycosylation in different biologic development test cases. The workflow involves data acquisition using a BioAccord LC-MS system with a data-analytical tool called GlycopeptideGraphMS along with Progenesis QI to semi-automate glycoproteomic characterisation and quantitation with a LC-MS1 dataset of a glycopeptides and peptides. Data analysis which involved identifying glycopeptides and their quantitative glycosylation was performed in 30 min with minimal user intervention. To demonstrate the effectiveness of the antibody and biologic glycopeptide assignment in various scenarios akin to biologic development activities, we demonstrate the effectiveness in the filtering of IgG1 and IgG2 subclasses from human serum IgG as well as innovator drugs trastuzumab and adalimumab and glycoforms by virtue of their glycosylation pattern. We demonstrate a high correlation between conventional released glycan analysis with fluorescent tagging and glycopeptide assignment derived from GraphMS. GraphMS workflow was then used to monitor the glycoform of our in-house trastuzumab biosimilar produced in fed-batch cultures. The demonstrated utility of GraphMS to semi-automate quantitation and qualitative identification of glycopeptides proves to be an easy data analysis method that can complement emerging multi-attribute monitoring (MAM) analytical toolsets in bioprocess environments.

A synbiotic intervention modulates meta-omics signatures of gut redox potential and acidity in elective caesarean born infants.

BACKGROUND: The compromised gut microbiome that results from C-section birth has been hypothesized as a risk factor for the development of non-communicable diseases (NCD). In a double-blind randomized controlled study, 153 infants born by elective C-section received an infant formula supplemented with either synbiotic, prebiotics, or unsupplemented from birth until 4 months old. Vaginally born infants were included as a reference group. Stool samples were collected from day 3 till week 22. Multi-omics were deployed to investigate the impact of mode of delivery and nutrition on the development of the infant gut microbiome, and uncover putative biological mechanisms underlying the role of a compromised microbiome as a risk factor for NCD. RESULTS: As early as day 3, infants born vaginally presented a hypoxic and acidic gut environment characterized by an enrichment of strict anaerobes (Bifidobacteriaceae). Infants born by C-section presented the hallmark of a compromised microbiome driven by an enrichment of Enterobacteriaceae. This was associated with meta-omics signatures characteristic of a microbiome adapted to a more oxygen-rich gut environment, enriched with genes associated with reactive oxygen species metabolism and lipopolysaccharide biosynthesis, and depleted in genes involved in the metabolism of milk carbohydrates. The synbiotic formula modulated expression of microbial genes involved in (oligo)saccharide metabolism, which emulates the eco-physiological gut environment observed in vaginally born infants. The resulting hypoxic and acidic milieu prevented the establishment of a compromised microbiome. CONCLUSIONS: This study deciphers the putative functional hallmarks of a compromised microbiome acquired during C-section birth, and the impact of nutrition that may counteract disturbed microbiome development. TRIAL REGISTRATION: The study was registered in the Dutch Trial Register (Number: 2838 ) on 4th April 2011.

Highly recurrent CBS epimutations in gastric cancer CpG island methylator phenotypes and inflammation.

BACKGROUND: CIMP (CpG island methylator phenotype) is an epigenetic molecular subtype, observed in multiple malignancies and associated with the epigenetic silencing of tumor suppressors. Currently, for most cancers including gastric cancer (GC), mechanisms underlying CIMP remain poorly understood. We sought to discover molecular contributors to CIMP in GC, by performing global DNA methylation, gene expression, and proteomics profiling across 14 gastric cell lines, followed by similar integrative analysis in 50 GC cell lines and 467 primary GCs. RESULTS: We identify the cystathionine beta-synthase enzyme (CBS) as a highly recurrent target of epigenetic silencing in CIMP GC. Likewise, we show that CBS epimutations are significantly associated with CIMP in various other cancers, occurring even in premalignant gastroesophageal conditions and longitudinally linked to clinical persistence. Of note, CRISPR deletion of CBS in normal gastric epithelial cells induces widespread DNA methylation changes that overlap with primary GC CIMP patterns. Reflecting its metabolic role as a gatekeeper interlinking the methionine and homocysteine cycles, CBS loss in vitro also causes reductions in the anti-inflammatory gasotransmitter hydrogen sulfide (H2S), with concomitant increase in NF-κB activity. In a murine genetic model of CBS deficiency, preliminary data indicate upregulated immune-mediated transcriptional signatures in the stomach. CONCLUSIONS: Our results implicate CBS as a bi-faceted modifier of aberrant DNA methylation and inflammation in GC and highlights H2S donors as a potential new therapy for CBS-silenced lesions.

Maternal factor NELFA drives a 2C-like state in mouse embryonic stem cells.

Mouse embryonic stem cells (ESCs) sporadically transit into an early embryonic-like state characterized by the expression of 2-cell (2C) stage-restricted transcripts. Here, we identify a maternal factor-negative elongation factor A (NELFA)-whose heterogeneous expression in mouse ESCs is coupled to 2C gene upregulation and expanded developmental potential in vivo. We show that NELFA partners with Top2a in an interaction specific to the 2C-like state, and that it drives the expression of Dux-a key 2C regulator. Accordingly, loss of NELFA and/or Top2a suppressed Dux activation. Further characterization of 2C-like cells uncovered reduced glycolytic activity; remarkably, mere chemical suppression of glycolysis was sufficient to promote a 2C-like fate, obviating the need for genetic manipulation. Global chromatin state analysis on NELFA-induced cells revealed decommissioning of ESC-specific enhancers, suggesting ESC-state impediments to 2C reversion. Our study positions NELFA as one of the earliest drivers of the 2C-like state and illuminates factors and processes that govern this transition.