Biology subjects

Stevens, J.

Publications and source records attributed to Stevens, J..

At least 19 recordsLinked to original sources

bioRxiv2026

SEC-seq reveals translation-focused metabolic strategies for high IgG productivity in clonal CHO cells

Chinese hamster ovary (CHO) cells are the dominant host for therapeutic protein production, yet intra- and inter-clonal heterogeneity in manufacturing phenotypes, and the underlying metabolic and secretory circuitry, remain poorly defined at single-cell resolution. Here, we apply secretion encoded single-cell sequencing (SEC-seq) to simultaneously measure transcriptomes and secreted IgG in single-cells from a parental production cell line and five CHO clones, each varying in cell-specific productivity. IgG mRNA and recombinant protein secretion are only moderately correlated across single cells, indicating that transcription alone does not explain intra-clonal secretion heterogeneity. By integrating SEC-seq with single-cell metabolic and secretory task scoring, we find that CHO cells accommodating recombinant protein expression burden have more active translation-associated pathways and suppressed energy-intensive endogenous secreted protein processing. Three high-secreting clones converge on this translation-focused state but differ in their subpopulation composition and energy/redox programs coupled to IgG output: one highly productive clone shows a low-growth, glycolytic, NAD/one-carbon-associated and UPR-activated program; a second shows increased oxidative phosphorylation and fatty-acid {beta}-oxidation, and a third shows higher lipid-uptake with modest central carbon metabolism. Genes such as Aldoa, Ndufab1, Acsl5, Mthfd2 showed clone-specific correlations with IgG, linking glycolysis, mitochondrial respiration, fatty-acid metabolism, and redox to secretion. Together, these results demonstrate that SEC-seq can resolve IgG-coupled metabolic-secretory wiring within and between CHO clones, providing a framework to identify subpopulation and circuit features to engineer or select for improved recombinant protein production.

systems biology↗

bioRxiv2026

GM-CSF regulates ILC states and myeloid cell signaling during ulceration in Crohns disease

Macrophage (M-), granulocyte (G-), and granulocyte-macrophage (GM-) colony-stimulating factors (CSFs) regulate myeloid cell function, yet their relative roles during inflammation remain poorly defined. To uncover how CSFs shape spatial immune niches in Crohns disease, we performed Xenium single-cell spatial transcriptomics on ileal tissues, revealing cell-type-specific expression and source-target interactions for each CSF. GM-CSF, unlike M-CSF or G-CSF, was locally enriched in ulcerated regions where lymphocytes adjacent to macrophage aggregates signaled through STAT5 phosphorylation. To study functional consequences, we developed a csf2rb-/- zebrafish model of intestinal injury. Using this model, we found that loss of GM-CSF signaling exacerbated epithelial damage and inflammation, whereas recombinant human GM-CSF limited injury by restraining ILC1 expansion, sustaining ILC3 maintenance, and promoting IL-22 production. Cross-species single-cell analysis revealed conserved ILC gene modules and GM-CSF-dependent transcriptional networks linking lymphoid and myeloid populations. These findings establish GM-CSF as a critical spatial regulator of myeloid- lymphoid crosstalk and intestinal immune homeostasis in Crohns disease.

immunology↗

bioRxiv2026

Resampling-based validation of a SNP panel for hybrid detection across generations: a case study in European lobster

Accurate detection of hybridization and introgression is critical for both evolutionary research and applied conservation. In many systems, however, hybrid ancestry is difficult to detect beyond the F1 generation, especially when based on limited genetic markers. In European waters, hybridization between the native Homarus gammarus and the invasive H. americanus poses a direct risk to the integrity of native stocks and effective fishery management, yet detection methods are often limited to morphological traits or first-generation hybrids. A set of 79 SNPs previously developed to distinguish species between American and European lobsters and F1 individuals has shown promise, but its capacity to resolve later-generation backcrosses remains untested. Here, we present a resampling-based evaluation of this panels performance under realistic introgression scenarios, using individual-based population genetic models informed by empirical data. We show that the panel retains discriminatory power across multiple hybrid classes, with diminishing accuracy in second-generation backcrosses. These findings validate the panels utility for applied monitoring and highlight the broader potential of resumpling-anchored frameworks to benchmark hybrid detection tools in a wide range of species. Article summaryThis study tests how well a reduced panel of genetic markers can detect hybridization across multiple generations. Using empirical genetic data of a 79-SNP panel from European and American lobsters, the authors generated individuals with known ancestry proportions through a resampling framework that preserves observed genetic variation. These data were analysed using model-based genetic assignment and ordination. The results show that the marker panel reliably identifies pure species and first-generation hybrids, but has reduced power to distinguish later backcross generations, mainly between adjacent hybrid classes. The study provides a practical benchmark for evaluating reduced marker panels used in applied monitoring and conservation genetics.

genomics↗

bioRxiv2026

Targeted Chromosomal Sequencing of Wild Bonobos Identifies a Genetically Distinct Subpopulation East of the Lomami River

Bonobos (Pan paniscus), an endangered species, have for decades been genetically understudied, partly due to difficulties in obtaining high-quality samples. The study of their genome is important not only for understanding their evolution, but also for improving conservation efforts, including population management, diversity and inbreeding assessment, and tracking rescued individuals to combat illegal wildlife trafficking. Here, we use chromosome 21 target capture data from 156 non-invasively collected faecal samples from wild bonobos to perform a comprehensive analysis of their population structure. We confirm the existence of three previously suggested subpopulations identified here as Western, Central and Eastern bonobos which are defined by natural barriers of gene flow such as the Lomami River. By estimating levels of inbreeding, diversity and differentiation, we find support for isolation of mainly Western and Eastern populations and add information on the dispersal routes of their ancestors. We infer split times and separation of these populations and apply a genetic framework to geolocalize samples of unknown origin, showing that locations of their potential origin can be estimated with a precision of up to a median of [~]50 km. Our study provides valuable insight into the evolution and population structure of bonobos and reveals how rivers act as strong barriers between populations. It also offers resources for conservation efforts and highlights the need to monitor bonobo populations more closely, in particular isolated ones. ImpactBonobos have been difficult to study genetically due to their remote forest habitat and endangered status. Here we used non-invasive sampling and chromosome 21 target capture sequencing to perform the most detailed analysis to date of their population structure. We find three main subpopulations and genetic differentiation influenced by river barriers, especially with populations found on the Eastern side of the Lomami river. This data will be useful for identifying the geographic origin of confiscated samples and thus aid bonobo conservation efforts.

bioinformatics↗

bioRxiv2026

Alcohol Use Disorder Affects Brain Metals

BackgroundOne of the risks associated with alcohol use disorder (AUD) is dementia. While the exact pathology is unknown, there is increasing evidence that alcohol consumption may dysregulate iron homeostasis in the brain leading to increased brain iron concentrations. Unregulated iron can produce oxidative stress and cellular damage to neurons. Iron-related cellular death is a relatively new finding and is called ferroptosis. To test the hypothesis that alcohol use disorder may cause brain iron dysregulation, we measured iron in hippocampus, caudate and substantia nigra in brain tissues obtained from individuals diagnosed with (AUD) and from individuals with no apparent alcohol-related problems. MethodsWe obtained hippocampus, caudate, and substantia nigra tissues from the New South Wales Brain Tissue Resource Centre, University of Sydney. The tissues came from 20 males and 20 females, half of each diagnosed with AUD. The tissues were wet-ashed and prepared for analysis of iron, copper, and zinc by total x-ray reflectance fluorescence. ResultsIn the hippocampus, we observed AUD-related decreased iron, but nothing more. In the substantia nigra, we observed a significant increase in iron and a trend toward an in increase in copper content in females and decreased iron and zinc in males. In the caudate we saw a near doubling of iron in females and a significant increase in copper in females and males. ConclusionsThese results provide direct evidence that at least part of AUD-related pathophysiology involves the dysregulation of trace metals in the brain. These changes are more severe in females, which may relate to extended levels of exposure due to slower alcohol metabolism.

neuroscience↗

bioRxiv2025

Optimizing Bispecific Antibody Expression via Multi-Omics Analysis and Vector Redesign

Bispecific antibodies are a growing class of therapeutics that simultaneously engage two targets. However, their complex molecular structures pose challenges for production in Chinese hamster ovary cells, the current industry standard for biologics manufacturing. Here we present a case study of three IgG-scFv format bsAbs expressed in CHO cells, in which one candidate exhibited markedly lower titers despite high sequence homology to the other two. Using multi-omics analysis (RNA sequencing, splicing prediction, codon optimization assessment, and motif screening) to investigate potential causes, we identified several likely mechanisms for poor expression, including aberrant splicing motifs, ribosome pausing sites, and suboptimal codon usage. Through targeted protein and DNA sequence engineering, we generated a revised variant with an 11-fold increase in stable expression titers. This work demonstrates that integrating sequence-level bioinformatic and synthetic biology diagnostics can directly improve manufacturability, providing a generalizable framework for resolving hidden expression liabilities in complex biologics.

bioengineering↗

bioRxiv2025

Quantifying HLA transcripts by genotype in chimeric mixtures at single-cell resolution

Gene products from the highly variable major histocompatibility locus, including HLA, are essential for self-recognition and immune surveillance of malignancy. Following allogeneic hematopoietic cell transplantation (alloHCT), genetic and epigenetic alterations in HLA can drive disease recurrence, making precise HLA assessment critical for determining future therapy. However, current methods lack the sensitivity to quantify HLA transcripts at the single-cell level, limiting their clinical utility. We introduce scrHLA-typing, a novel technique that accurately identifies and quantifies HLA transcripts in single cells using long-read sequencing. When applied to samples from patients with post-transplant relapse, scrHLA-typing successfully detected HLA allele-specific expression, across a range of levels of donor-recipient chimerism, at clinically actionable levels. By characterizing allele expression in residual leukemia cells, our assay identified differences in expression patterns among patients. This capability highlights scrHLA-typings potential to improve risk stratification and guide the selection of appropriate salvage therapies, enhancing personalized treatment strategies after relapse.

molecular biology↗

bioRxiv2025

The cow udder is a potential mixing vessel for influenza A viruses

The incursion of high pathogenicity avian influenza A virus (IAV) into US dairy cows is unprecedented in the era of molecular diagnosis and pathogen sequencing. This raises questions over the likelihood of further outbreaks and whether dairy cattle could be a "mixing vessel" for novel strains of IAV. Using a panel of BSL2-safe reassortant viruses representing clade 2.3.4.4b H5 epizootic lineages circulating since 2020, we found that a cow B3.13 isolate displayed enhanced replication in cow mammary gland cells, along with increased viral polymerase activity and stronger interferon antagonism in cow cells compared to an earlier EA-2020-C genotype virus. However, multiple avian and mammalian IAV strains, including other clade 2.3.4.4b high pathogenicity genotypes, were replication competent in bovine cells, particularly those of the mammary gland, suggesting that there is a diverse circulating IAV pool with the potential to infect cows. Moreover, we show that cow mammary cells co-express -2,3 and -2,6 - linked sialic acids, and are susceptible to co-infection with human and avian IAVs. We conclude that the US cow influenza outbreak does not simply reflect a unique adaptation of the B3.13 genotype virus; rather, the bovine udder represents a permissive niche for IAV and a plausible site for reassortment, underscoring its potential role in generating novel influenza viruses with pandemic risk.

microbiology↗

bioRxiv2025

Condition-dependent, amorphous protein agglomerates control cytoplasmic rheology

Molecular crowding in the bacterial cytoplasm restricts the diffusion of large molecules, impacting cellular processes. However, how nutrient availability influences cytoplasmic rheology is not well understood. With single-particle tracking in Escherichia coli, we observed a threefold variation in the diffusion of a 40-nm particle across exponential growth conditions. Previously suggested determinants of rheology did not account for this variation; instead, we found a strong anticorrelation between the diffusion coefficient and the abundance of amino acid metabolism proteins, persisting upon genetic perturbations and showing that lower diffusion is associated with increased viscoelasticity. Photoactivated light microscopy revealed that some amino acid metabolism proteins form clusters. Electron microscopy showed that these proteins could form amorphous agglomerates at physiological concentrations in vitro, likely driven by their low intrinsic disorder, high compactness and hydropathy score. These findings show that protein agglomerates regulate cytoplasmic rheology in a condition-dependent manner, suggesting an underappreciated level of cytoplasmic organization. HighlightsO_LIDiffusion of 40-nm particles varies threefold across growth conditions in E. coli C_LIO_LICytoplasmic diffusion inversely correlates with COG-E protein abundance COG-E proteins form agglomerates that increase cytoplasmic viscoelasticity C_LIO_LIProtein compactness and hydrophobicity predict condition-dependent crowding effects C_LI

biophysics↗

bioRxiv2025

Image-Based Meta- and Mega-Analysis (IBMMA): A Unified Framework for Large-Scale, Multi-Site, Neuroimaging Data Analysis

The increasing scale and complexity of neuroimaging datasets aggregated from multiple study sites present substantial analytic challenges, as existing statistical analysis tools struggle to handle missing voxel-data, suffer from limited computational speed and inefficient memory allocation, and are restricted in the types of statistical designs they are able to model. We introduce Image-Based Meta- & Mega-Analysis (IBMMA), a novel software package implemented in R and Python that provides a unified framework for analyzing diverse neuroimaging features, efficiently handles large-scale datasets through parallel processing, offers flexible statistical modeling options, and properly manages missing voxel-data commonly encountered in multi-site studies. IBMMA produced stronger effect sizes and revealed findings in brain regions that traditional software overlooked due to missing voxel-data resulting in gaps in brain coverage. IBMMA has the potential to accelerate discoveries in neuroscience and enhance the clinical utility of neuroimaging findings.

neuroscience↗

bioRxiv2025

Heterogeneity across mammalian- and avian-origin A(H1N1) influenza viruses influences viral infectivity following incubation with host bacteria from the human respiratory tract

Influenza A viruses (IAV) are primarily transmitted between mammals by the respiratory route, and encounter bacteria in the respiratory tract before infecting susceptible epithelial cells. Previous studies have shown that mammalian-origin IAV can bind to the surface of different bacterial species and purified bacterial lipopolysaccharides (LPS), but despite the broad host range of IAV, few studies have included avian-origin IAV in these assessments. Since IAV that circulate in humans and birds are well-adapted to replication in the human respiratory and avian gastrointestinal tracts, respectively, we investigated the ability of multiple human and avian A(H1N1) IAV to associate with bacteria and their surface components isolated from both host niches. Binding interactions were assessed with microbial glycan microarrays, revealing that seasonal and avian IAV strains exhibited binding diversity to multiple bacterial glycans at the level of the virus and the bacterium, independent of sialic acid binding preference of the virus. Co-incubation of diverse IAV with LPS derived from Pseudomonas aeruginosa (P. aeruginosa), a respiratory tract bacterium, led to reduced retention of viral infectivity in a temperature dependent manner which was not observed when co-incubated with LPS from Escherichia coli, a gut bacterial isolate. Reduction of viral infectivity was supported by disruption of IAV virions following incubation with P. aeruginosa LPS using electron microscopy. Our findings highlight that both human and avian IAV can bind to bacterial surface components from different host sites resulting in differential functional interactions early after binding, suggesting the need to study IAV-bacteria interactions at the host range interface.

microbiology↗

bioRxiv2024

Green Conversations: Harnessing Plant Communication to control growth light intensity.

Controlled Environment Agriculture (CEA) delivers increased crop production per unit land, contributing to resilient food systems amidst challenges of climate change, population growth and urbanization. However, high energy costs associated with lighting impose substantial barriers to the widespread adoption of CEA. While light is indispensable for growth, critically its utilization by crops throughout the photoperiod remains sub-optimal, reducing photosynthetic efficiency and wasting energy. Here we have developed and demonstrated a novel real-time plant bio-feedback system that enables crops to directly communicate optimal lighting requirements. Continuous non- invasive monitoring of photochemistry elicited decreased demand for light by basil at the end of the photoperiod. Our innovative approach increased yield by 10% and reduced energy consumption per unit fresh mass by 18%, delivering a 201gCO2 gFW-1 reduction in carbon footprint. Application of this technique at scale can revolutionise resource management of CEA, reinvigorating the productivity, profitability and sustainability of this food industry. Author ContributionsJS & TL: designed the experiments; JS, PD and PK: performed all physiology experiments and data acquisition and carried out data analyses. TL, JS, PD and TH wrote the MS and all authors commented on the MS. One-sentence summaryChlorophyll fluorescence measurements of photosynthetic efficiency can be used to control growth light intensity in real time, optimising crop performance and energy use.

plant biology↗

bioRxiv2024

Integrative genomics approach identifies glial transcriptomic dysregulation and risk in the cortex of individuals with Alcohol Use Disorder

Alcohol use disorder (AUD) is a prevalent neuropsychiatric disorder that is a major global health concern, affecting millions of people worldwide. Past molecular studies of AUD used underpowered single cell analysis or bulk homogenates of postmortem brain tissue, which obscures gene expression changes in specific cell types. Here we performed single nuclei RNA-sequencing analysis of 73 post-mortem samples from individuals with AUD (N=36, Nnuclei= 248,873) and neurotypical controls (N=37, Nnuclei= 210,573) in both sexes across two institutional sites. We identified 32 clusters and found widespread cell type-specific transcriptomic changes across the cortex in AUD, particularly affecting glia. We found the greatest dysregulation in novel microglial and astrocytic subtypes that accounted for the majority of differential gene expression and co-expression modules linked to AUD. Analysis for cell type-specific enrichment of aggregate genetic risk for AUD identified subtypes of microglia and astrocytes as potential key players not only affected by but causally linked to the progression of AUD. These results highlight the importance of cell-type specific molecular changes in AUD and offer opportunities to identify novel targets for treatment.

neuroscience↗

bioRxiv2024

Integrated Single-Cell Multiomic Profiling of Caudate Nucleus Suggests Key Mechanisms in Alcohol Use Disorder

Alcohol use disorder (AUD) induces complex transcriptional and regulatory changes across multiple brain regions including the caudate nucleus, which remains understudied. Using paired single-nucleus RNA-seq and ATAC-seq on caudate samples from 143 human postmortem brains, including 74 with AUD, we identified 17 distinct cell types. We found that a significant portion of the alcohol-induced changes in gene expression occurred through altered chromatin accessibility. Notably, we identified novel transcriptional and chromatin accessibility differences in medium spiny neurons, impacting pathways such as RNA metabolism and immune response. A small cluster of D1/D2 hybrid neurons showed distinct differences, suggesting a unique role in AUD. Microglia exhibited distinct activation states deviating from classical M1/M2 designations, and astrocytes entered a reactive state partially regulated by JUND, affecting glutamatergic synapse pathways. Oligodendrocyte dysregulation, driven in part by OLIG2, was linked to demyelination and increased TGF-{beta}1 signaling from microglia and astrocytes. We also observed increased microglia-astrocyte communication via the IL-1{beta} pathway. Leveraging our multiomic data, we performed cell type-specific expression quantitative trait loci analysis, integrating that with public genome-wide association studies to identify AUD risk genes such as ADAL and PPP2R3C, providing a direct link between genetic variants, chromatin accessibility, and gene expression in AUD. These findings not only provide new insights into the genetic and cellular mechanisms in the caudate related to AUD but also demonstrate the broader utility of large-scale multiomic studies in uncovering complex gene regulation across diverse cell types, which has implications beyond the substance use field.

neuroscience↗

bioRxiv2024

Loss of neuronal lysosomal acid lipase drives amyloid pathology in Alzheimer's disease

Underlying drivers of late-onset Alzheimers disease (LOAD) pathology remain unknown. However, multiple biologically diverse risk factors share a common pathological progression. To identify convergent molecular abnormalities that drive LOAD pathogenesis we compared two common midlife risk factors for LOAD, heavy alcohol use and obesity. This revealed that disrupted lipophagy is an underlying cause of LOAD pathogenesis. Both exposures reduced lysosomal flux, with a loss of neuronal lysosomal acid lipase (LAL). This resulted in neuronal lysosomal lipid (NLL) accumulation, which opposed A{beta} localization to lysosomes. Neuronal LAL loss both preceded (with aging) and promoted (targeted knockdown) A{beta} pathology and cognitive deficits in AD mice. The addition of recombinant LAL ex vivo and neuronal LAL overexpression in vivo prevented amyloid increases and improved cognition. In WT mice, neuronal LAL declined with aging and correlated negatively with entorhinal A{beta}. In healthy human brain, LAL also declined with age, suggesting this contributes to the age-related vulnerability for AD. In human LOAD LAL was further reduced, correlated negatively with A{beta}1-42, and occurred with polymerase pausing at the LAL gene. Together, this finds that the loss of neuronal LAL promotes NLL accumulation to impede degradation of A{beta} in neuronal lysosomes to drive AD amyloid pathology. SummaryCellular and molecular drivers of late-onset Alzheimers disease (LOAD) are unknown, though several risk factors account for the majority of disease incidence1-5. Though diverse in their biological natures, each of these risk exposures converge on a shared pathological progression with the accumulation of amyloid early in the disease. Human genetic and transcriptomic studies suggest a role for altered lipid metabolism6-9, though the mechanism has been unknown. Here, using two common midlife risk exposures for LOAD, we found that dysfunctional lipophagy caused by the loss of lysosomal acid lipase (LAL) promotes early LOAD pathogenesis. Both midlife obesity and heavy alcohol reduced neuronal LAL, causing an increase in neuronal lysosomal lipid, and a subsequent accumulation of A{beta} in the extra-lysosomal cytosol. This loss of LAL preceded and promoted A{beta} pathology and cognitive deficits in AD mice. The addition of recombinant LAL ex vivo and neuronal LAL overexpression in vivo prevented increases in amyloid and improved cognition. In human brain, LAL declined with age in healthy subjects, similar to rodents, showing robust losses in LOAD subjects with polymerase pausing. Together, this implicates neuronal LAL loss in LOAD pathogenesis and presents LAL as a promising diagnostic, preventative, and/or therapeutic target for AD.

neuroscience↗

bioRxiv2024

Leveraging the genetic diversity of trout in the rivers of the British Isles and northern France to understand the movements of sea trout (Salmo trutta L.) around the English Channel

Populations of anadromous brown trout, also known as sea trout, have suffered recent marked declines in abundance due to multiple factors, including climate change and human activities. While much is known about their freshwater phase, less is known about the species marine feeding migrations. This situation is hindering the effective management and conservation of anadromous trout in the marine environment. Using a panel of 95 single nucleotide polymorphism markers we developed a genetic baseline, which demonstrated strong regional structuring of genetic diversity in trout populations around the English Channel and adjacent waters. Extensive baseline testing showed this structuring allowed high-confidence assignment of known-origin individuals to region of origin. This study presents new data on the movements of anadromous trout in the English Channel and southern North Sea. Assignment of anadromous trout sampled from 12 marine and estuarine localities highlighted contrasting results for these areas. The majority of these fisheries are composed predominately of stocks local to the sampling location. However, there were multiple cases of long-distance movements of anadromous trout, with several individuals originating from rivers in northeast England being caught in the English Channel and southern North Sea, in some cases more than 1000 km from their natal region. These results have implications for the management of sea trout in inshore waters around the English Channel and southern North Sea.

evolutionary biology↗

bioRxiv2024

Microbiota-derived inosine programs protective CD8+ T cell responses against influenza in newborns

The immunological defects causing susceptibility to severe viral respiratory infections due to early-life dysbiosis remain ill-defined. Here, we show that influenza virus susceptibility in dysbiotic infant mice is caused by CD8+ T cell hyporesponsiveness and diminished persistence as tissue-resident memory cells. We describe a previously unknown role for nuclear factor interleukin 3 (NFIL3) in repression of memory differentiation of CD8+ T cells in dysbiotic mice involving epigenetic regulation of T cell factor 1 (TCF 1) expression. Pulmonary CD8+ T cells from dysbiotic human infants share these transcriptional signatures and functional phenotypes. Mechanistically, intestinal inosine was reduced in dysbiotic human infants and newborn mice, and inosine replacement reversed epigenetic dysregulation of Tcf7 and increased memory differentiation and responsiveness of pulmonary CD8+ T cells. Our data unveils new developmental layers controlling immune cell activation and identifies microbial metabolites that may be used therapeutically in the future to protect at-risk newborns.

immunology↗

bioRxiv2023

Multi-omic characterization of antibody-producing CHO cell lines elucidates metabolic reprogramming and nutrient uptake bottlenecks

Characterizing the phenotypic diversity and metabolic capabilities of industrially relevant manufacturing cell lines is critical to bioprocess optimization and cell line development. Metabolic capabilities of the production hosts limit nutrient and resource channeling into desired cellular processes and can have a profound impact on productivity but cannot be directly inferred from measured data such as spent media concentrations or transcriptomics. Here, we present an integrated multi-omic characterization approach combining exo-metabolomics, transcriptomics, and genome-scale metabolic network analysis and apply it to three antibody-producing Chinese Hamster Ovary cell lines to reprogramming features associated with high-producer clones and metabolic bottlenecks limiting product production in an industrial bioprocess. Analysis of individual datatypes revealed a decreased nitrogenous byproduct secretion in high-producing clones and the topological changes in peripheral metabolic pathway expression associated with phase shifts. An integrated omics analysis in the context of the genome-scale metabolic model elucidated the differences in central metabolism and identified amino acid utilization bottlenecks limiting cell growth and antibody production that were not evident from exo-metabolomics or transcriptomics alone. Thus, we demonstrate the utility of a multi-omics characterization in providing an in-depth understanding of cellular metabolism, which is critical to efforts in cell engineering and bioprocess optimization.

systems biology↗