Strategies to improve CHO cell culture performance: Targeted deletion of amino acid catabolism and apoptosis genes paired with growth inhibitor supplementation.

Chinese hamster ovary (CHO) cells are the predominant host of choice for recombinant monoclonal antibody (mAb) expression. Recent advancements in gene editing technology have enabled engineering new CHO hosts with higher growth, viability, or productivity. One approach involved knock out (KO) of BCAT1 gene, which codes for the first enzyme in the branched chain amino acid (BCAA) catabolism pathway; BCAT1 KO reduced accumulation of growth inhibitory short chain fatty acid (SCFA) byproducts and improved culture growth and titer when used in conjunction with high-end pH-controlled delivery of glucose (HiPDOG) technology and SCFA supplementation during production. Accumulation of SCFAs in the culture media is critical for metabolic shift toward higher specific productivity and hence titer. Here we describe knocking out BCKDHa/b genes (2XKO), which act downstream of the BCAT1, in a BAX/BAK KO CHO host cell line background to reduce accumulation of growth-inhibitory molecules in culture. Evaluation of the new 4XKO CHO cell lines in fed-batch production cultures (without HiPDOG) revealed that partial KO of BCKDHa/b genes in an apoptosis-resistant (BAX/BAK KO) background can achieve higher viabilities and mAb titers. This was evident when SCFAs were added to boost productivity as such additives negatively impacted culture viability in the WT but not BAX/BAK KO cells during batch production. Altogether, our findings suggest that SCFA addbacks can significantly increase productivity and mAb titers in the context of apoptosis-attenuated CHO cells with partial KO of BCAA genes. Such engineered CHO hosts can offer productivity advantages for expressing biotherapeutics in an industrial setting.

Nicotinic acetylcholine receptor signaling maintains epithelial barrier integrity.

Disruption of epithelial barriers is a common disease manifestation in chronic degenerative diseases of the airways, lung, and intestine. Extensive human genetic studies have identified risk loci in such diseases, including in chronic obstructive pulmonary disease (COPD) and inflammatory bowel diseases. The genes associated with these loci have not fully been determined, and functional characterization of such genes requires extensive studies in model organisms. Here, we report the results of a screen in Drosophila melanogaster that allowed for rapid identification, validation, and prioritization of COPD risk genes that were selected based on risk loci identified in human genome-wide association studies (GWAS). Using intestinal barrier dysfunction in flies as a readout, our results validate the impact of candidate gene perturbations on epithelial barrier function in 56% of the cases, resulting in a prioritized target gene list. We further report the functional characterization in flies of one family of these genes, encoding for nicotinic acetylcholine receptor (nAchR) subunits. We find that nAchR signaling in enterocytes of the fly gut promotes epithelial barrier function and epithelial homeostasis by regulating the production of the peritrophic matrix. Our findings identify COPD-associated genes critical for epithelial barrier maintenance, and provide insight into the role of epithelial nAchR signaling for homeostasis.

Notch signaling in thyrocytes is essential for adult thyroid function and mammalian homeostasis.

The thyroid functions as an apex endocrine organ that controls growth, differentiation and metabolism1, and thyroid diseases comprise the most common endocrine disorders2. Nevertheless, high-resolution views of the cellular composition and signals that govern the thyroid have been lacking3,4. Here, we show that Notch signalling controls homeostasis and thermoregulation in adult mammals through a mitochondria-based mechanism in a subset of thyrocytes. We discover two thyrocyte subtypes in mouse and human thyroids, identified in single-cell analyses by different levels of metabolic activity and Notch signalling. Therapeutic antibody blockade of Notch in adult mice inhibits a thyrocyte-specific transcriptional program and induces thyrocyte defects due to decreased mitochondrial activity and ROS production. Thus, disrupting Notch signalling in adult mice causes hypothyroidism, characterized by reduced levels of circulating thyroid hormone and dysregulation of whole-body thermoregulation. Inducible genetic deletion of Notch1 and 2 in thyrocytes phenocopies this antibody-induced hypothyroidism, establishing a direct role for Notch in adult murine thyrocytes. We confirm that hypothyroidism is enriched in children with Alagille syndrome, a genetic disorder marked by Notch mutations, suggesting that these findings translate to humans.

Dissecting the human gut microbiome to better decipher drug liability: A once-forgotten organ takes center stage.

BACKGROUND: The gut microbiome is a diverse system within the gastrointestinal tract composed of trillions of microorganisms (gut microbiota), along with their genomes. Accumulated evidence has revealed the significance of the gut microbiome in human health and disease. Due to its ability to alter drug/xenobiotic pharmacokinetics and therapeutic outcomes, this once-forgotten "metabolic organ" is receiving increasing attention. In parallel with the growing microbiome-driven studies, traditional analytical techniques and technologies have also evolved, allowing researchers to gain a deeper understanding of the functional and mechanistic effects of gut microbiome. AIM OF REVIEW: From a drug development perspective, microbial drug metabolism is becoming increasingly critical as new modalities (e.g., degradation peptides) with potential microbial metabolism implications emerge. The pharmaceutical industry thus has a pressing need to stay up-to-date with, and continue pursuing, research efforts investigating clinical impact of the gut microbiome on drug actions whilst integrating advances in analytical technology and gut microbiome models. Our review aims to practically address this need by comprehensively introducing the latest innovations in microbial drug metabolism research- including strengths and limitations, to aid in mechanistically dissecting the impact of the gut microbiome on drug metabolism and therapeutic impact, and to develop informed strategies to address microbiome-related drug liability and minimize clinical risk. KEY SCIENTIFIC CONCEPTS OF REVIEW: We present comprehensive mechanisms and co-contributing factors by which the gut microbiome influences drug therapeutic outcomes. We highlight in vitro, in vivo, and in silico models for elucidating the mechanistic role and clinical impact of the gut microbiome on drugs in combination with high-throughput, functionally oriented, and physiologically relevant techniques. Integrating pharmaceutical knowledge and insight, we provide practical suggestions to pharmaceutical scientists for when, why, how, and what is next in microbial studies for improved drug efficacy and safety, and ultimately, support precision medicine formulation for personalized and efficacious therapies.

LC-HRMS-based targeted metabolomics for high-throughput and quantitative analysis of 21 growth inhibition-related metabolites in Chinese hamster ovary cell fed-batch cultures.

Chinese hamster ovary (CHO) cells have been widely used in the biopharmaceutical industry for production of therapeutic proteins. CHO cells in fed-batch cultures produce various amino acid-derived intermediate metabolites. These small molecule metabolic byproducts have proven to be critical to cell growth, culture performance, and, more interestingly, antibody drug productivity. Herein, we developed an LC-HRMS-based targeted metabolomics approach for comprehensive quantification of total 21 growth inhibition-related metabolites generated from 14 different amino acids in CHO cell fed-batch cultures. High throughput derivatization procedures, matrix-matched calibration curves, stable isotope-labeled internal standards, and accurate mass full MS scan were utilized to achieve our goal for a wide range of metabolite screening as well as validity and reliability of metabolite quantification. We further present a novel analytical strategy for extending the assay's dynamic range by utilizing naturally occurring isotope M + 1 ion as a quantification analog in the circumstances where the principal M ion is beyond its calibration range. The integrated method was qualified for selectivity, sensitivity, linearity, accuracy, precision, isotope analysis, and other analytical aspects to demonstrate assay robustness. We then applied this metabolomics approach to characterize metabolites of interest in a CHO cell-based monoclonal antibody (mAb) production process with fed-batch bioreactor culture mode. Absolute quantification combined with multivariate statistical analysis illustrated that our target analytes derived from amino acids, especially from branched-chain amino acids, closely correlated with cell viability and significantly differentiated cellular stages in production process.

In vivo partial reprogramming alters age-associated molecular changes during physiological aging in mice.

Partial reprogramming by expression of reprogramming factors (Oct4, Sox2, Klf4 and c-Myc) for short periods of time restores a youthful epigenetic signature to aging cells and extends the life span of a premature aging mouse model. However, the effects of longer-term partial reprogramming in physiologically aging wild-type mice are unknown. Here, we performed various long-term partial reprogramming regimens, including different onset timings, during physiological aging. Long-term partial reprogramming lead to rejuvenating effects in different tissues, such as the kidney and skin, and at the organismal level; duration of the treatment determined the extent of the beneficial effects. The rejuvenating effects were associated with a reversion of the epigenetic clock and metabolic and transcriptomic changes, including reduced expression of genes involved in the inflammation, senescence and stress response pathways. Overall, our observations indicate that partial reprogramming protocols can be designed to be safe and effective in preventing age-related physiological changes. We further conclude that longer-term partial reprogramming regimens are more effective in delaying aging phenotypes than short-term reprogramming.

Selective activation of PFKL suppresses the phagocytic oxidative burst.

In neutrophils, nicotinamide adenine dinucleotide phosphate (NADPH) generated via the pentose phosphate pathway fuels NADPH oxidase NOX2 to produce reactive oxygen species for killing invading pathogens. However, excessive NOX2 activity can exacerbate inflammation, as in acute respiratory distress syndrome (ARDS). Here, we use two unbiased chemical proteomic strategies to show that small-molecule LDC7559, or a more potent designed analog NA-11, inhibits the NOX2-dependent oxidative burst in neutrophils by activating the glycolytic enzyme phosphofructokinase-1 liver type (PFKL) and dampening flux through the pentose phosphate pathway. Accordingly, neutrophils treated with NA-11 had reduced NOX2-dependent outputs, including neutrophil cell death (NETosis) and tissue damage. A high-resolution structure of PFKL confirmed binding of NA-11 to the AMP/ADP allosteric activation site and explained why NA-11 failed to agonize phosphofructokinase-1 platelet type (PFKP) or muscle type (PFKM). Thus, NA-11 represents a tool for selective activation of PFKL, the main phosphofructokinase-1 isoform expressed in immune cells.

Tracking Polymicrobial Metabolism in Cystic Fibrosis Airways: Pseudomonas aeruginosa Metabolism and Physiology Are Influenced by Rothia mucilaginosa-Derived Metabolites.

Due to a lack of effective immune clearance, the airways of cystic fibrosis patients are colonized by polymicrobial communities. One of the most widespread and destructive opportunistic pathogens is Pseudomonas aeruginosa; however, P. aeruginosa does not colonize the airways alone. Microbes that are common in the oral cavity, such as Rothia mucilaginosa, are also present in cystic fibrosis patient sputum and have metabolic capacities different from those of P. aeruginosa Here we examine the metabolic interactions of P. aeruginosa and R. mucilaginosa using stable-isotope-assisted metabolomics. Glucose-derived 13C was incorporated into glycolysis metabolites, namely, lactate and acetate, and some amino acids in R. mucilaginosa grown aerobically and anaerobically. The amino acid glutamate was unlabeled in the R. mucilaginosa supernatant but incorporated the 13C label after P. aeruginosa was cross-fed the R. mucilaginosa supernatant in minimal medium and artificial-sputum medium. We provide evidence that P. aeruginosa utilizes R. mucilaginosa-produced metabolites as precursors for generation of primary metabolites, including glutamate.IMPORTANCEPseudomonas aeruginosa is a dominant and persistent cystic fibrosis pathogen. Although P. aeruginosa is accompanied by other microbes in the airways of cystic fibrosis patients, few cystic fibrosis studies show how P. aeruginosa is affected by the metabolism of other bacteria. Here, we demonstrate that P. aeruginosa generates primary metabolites using substrates produced by another microbe that is prevalent in the airways of cystic fibrosis patients, Rothia mucilaginosa These results indicate that P. aeruginosa may get a metabolic boost from its microbial neighbor, which might contribute to its pathogenesis in the airways of cystic fibrosis patients.

Identification of small molecules using accurate mass MS/MS search.

Tandem mass spectral library search (MS/MS) is the fastest way to correctly annotate MS/MS spectra from screening small molecules in fields such as environmental analysis, drug screening, lipid analysis, and metabolomics. The confidence in MS/MS-based annotation of chemical structures is impacted by instrumental settings and requirements, data acquisition modes including data-dependent and data-independent methods, library scoring algorithms, as well as post-curation steps. We critically discuss parameters that influence search results, such as mass accuracy, precursor ion isolation width, intensity thresholds, centroiding algorithms, and acquisition speed. A range of publicly and commercially available MS/MS databases such as NIST, MassBank, MoNA, LipidBlast, Wiley MSforID, and METLIN are surveyed. In addition, software tools including NIST MS Search, MS-DIAL, Mass Frontier, SmileMS, Mass++, and XCMS2 to perform fast MS/MS search are discussed. MS/MS scoring algorithms and challenges during compound annotation are reviewed. Advanced methods such as the in silico generation of tandem mass spectra using quantum chemistry and machine learning methods are covered. Community efforts for curation and sharing of tandem mass spectra that will allow for faster distribution of scientific discoveries are discussed.

Identifying metabolites by integrating metabolome databases with mass spectrometry cheminformatics.

Novel metabolites distinct from canonical pathways can be identified through the integration of three cheminformatics tools: BinVestigate, which queries the BinBase gas chromatography-mass spectrometry (GC-MS) metabolome database to match unknowns with biological metadata across over 110,000 samples; MS-DIAL 2.0, a software tool for chromatographic deconvolution of high-resolution GC-MS or liquid chromatography-mass spectrometry (LC-MS); and MS-FINDER 2.0, a structure-elucidation program that uses a combination of 14 metabolome databases in addition to an enzyme promiscuity library. We showcase our workflow by annotating N-methyl-uridine monophosphate (UMP), lysomonogalactosyl-monopalmitin, N-methylalanine, and two propofol derivatives.

Mass spectral fragmentation of trimethylsilylated small molecules.

Mass spectrometry-based untargeted metabolomics detects many peaks that cannot be identified. While advances have been made for automatic structure annotations in LC-electrospray-MS/MS, no open source solutions are available for hard electron ionization used in GC-MS. In metabolomics, most compounds bear moieties with acidic protons, for example, amino, hydroxyl, or carboxyl groups. Such functional groups increase the boiling points of metabolites too much for use in GC-MS. Hence, in GC-MS-focused metabolomics, derivatization of these groups is essential and has been employed since the 1960s. Specifically, trimethylsilylation is known as mild and universal method for GC-MS analysis. Here, we comprehensively compile accurate mass fragmentation rules and pathways of trimethylsilylated small molecules from 80 research articles over the past 5 decades, including diagnostic fragment ions, neutral losses, and typical ion ratios, for alcohols, carboxylic acids, amines, amino acids, sugars, steroids, thiols, and phosphates. These fragmentation rules were subsequently validated by specificity and sensitivity assessments using the NIST 14 nominal mass library and a new in-house GC-QTOF MS library containing 589 accurate mass spectra. From 556 tested fragmentation patterns, 228 rules yielded true positive hits within 4 mDa mass accuracy. These rules can be applied to assign substructures for mass spectra computation and unknown identification. © 2016 Wiley Periodicals, Inc. Mass Spec Rev 37:245-257, 2018.

Using Accurate Mass Gas Chromatography-Mass Spectrometry with the MINE Database for Epimetabolite Annotation.

Mass spectrometry-based untargeted metabolomics often detects statistically significant metabolites that cannot be readily identified. Without defined chemical structure, interpretation of the biochemical relevance is not feasible. Epimetabolites are produced from canonical metabolites by defined enzymatic reactions and may represent a large fraction of the structurally unidentified metabolome. We here present a systematic workflow for annotating unknown epimetabolites using high resolution gas chromatography-accurate mass spectrometry with multiple ionization techniques and stable isotope labeled derivatization methods. We first determine elemental formulas, which are then used to query the "metabolic in-silico expansion" database (MINE DB) to obtain possible molecular structures that are predicted by enzyme promiscuity from canonical pathways. Accurate mass fragmentation rules are combined with in silico spectra prediction programs CFM-ID and MS-FINDER to derive the best candidates. We validated the workflow by correctly identifying 10 methylated nucleosides and 6 methylated amino acids. We then employed this strategy to annotate eight unknown compounds from cancer studies and other biological systems.

Heavy Metals Contents and Speciation in Surface Sediments from Gansu, Ningxia and Inner Mongolia Sections of the Yellow River of China.

So far, many investigations had been made on the concentration and species distribution of heavy metals in aquatic environments. However, there are only a few studies on heavy metals in upper reaches of the Yellow River, especially in Gansu, Ningxia and Inner Mongolia sections. We have literatures related to the Yellow River, in this work, we remarkably discussed about the contents, speciation and potential risks of Cd, Pb, Cr, V, Co, Ni, Cu, and Zn in surface sediments from 12 sampling sites in Gansu, Ningxia, and Inner Mongolia sections of the Yellow River of China in 2011 year wet season by high resolution inductively coupled plasma mass spectrometer (HR-ICP-MS) and sequential extraction procedure of BCR method. The results indicated that the metals contents were arranged as Cr > V > Zn > Cu > Ni > Pb > Co > Cd in all sites. Comparing with the background value of soil in local section, Cd showed the highest level at S5 (1.30 µg x g(-1)), which was almost 13 times higher than the background value (0.103 µg x g(-1)). Pollution assessment indicated that Cd presented a strong polluted status with the geo-accumulation index (I(geo)) value of 3.08 at S5, moderately to strong polluted status with the I(geo) ranged from 2.02 to 2.90 in Inner Mongolia section (S1-S4). Moreover, enrichment factor (EF) showed that all heavy metals in these sediments have been influenced by anthropogenic activities. According to potential ecological risk index (RI), S5 and S3 demonstrated high ecologic risk of heavy metals, while other sampling sites showed moderately ecological risk. The results of BCR exhibited that Cd was the most available metal, followed by Co and Ni, while V and Cr were unavailable in the sediments. Risk assessment code (RAC) exhibited high risk for Cd at S1-S4 and very high risk at S5, while medium risk for Ni and Co at all sites. The results and conclusions may be important information and therefore of interest to the relevant departments of the governments.

[Study on speciation and fractionation of rare earth eleinents in surface sediments in Gansu, Ningxia and Inner Mongolia sections of Yellow River].

In the present paper, BCR sequential extraction and high resolution inductively coupled plasma-mass spectrometry (HR-ICP-MS) were performed to analyze the speciation contents of 14 kinds of rare earth elements (REE) in the surface sediments from 12 sampling sites (S1-S12) in Gansu, Ningxia and Inner Mongolia Sections of Yellow River, and REE fractionation were also studied. The results indicated that the contents of REE in 12 sediment samples werethe same order. The average contents of 14 rare earth elements were in this order: Ce(66.4)>La(35.8)>Nd(28.6)>Pr(7.88)>Sm(5.87) >Gd(5.01)>Dy (4.53)>Yb(2.86)>Er(2.51)>Eu(1.31)>Ho(0.856)>Tb(0.760)>Tm(0.428)>Lu(0.404), which were similar to the Chinese soil background. The residual fractions of all elements were present at the highest percentages(71.9%-93.9%), which indicated that the bioavailability or environmental impact was low. The percentage of reducible fraction was the lowest, ranged from 0. 20% to 3. 87% with the mean value of 0.83%, while the oxidizable fraction percentage(7.61%) was close to acid-soluble fraction(7.69%). But in Maqu (S12), oxidizable percentage (16.1%) was significantly higher than the acid-soluble fraction (1.73%). Correlation analysis showed that there was a significant positive correlation between total organic carbon (TOC) content and oxidizable percentage, and the correlation coefficients were between 0.763 and 0.914. REE fractionation results showed that: the contents of REE in surface sediments of Gansu, Ningxia and Inner Mongolia Sections of Yellow River were mainly from soil weathering, with light-REE enrichment and Eu depletion. The chondrite-normalized curve implied that La and Ce in Jinshawan (S8) and Baotou-Dengkou (S1) and heavy REE at all the sampling points might have external REE sources.