The biophysical properties of cells reflect their identities, underpin their homeostatic state in health, and define the pathogenesis of disease. Recent leapfrogging advances in biophysical cytometry ...now give access to this information, which is obscured in molecular assays, with a discriminative power that was once inconceivable. However, biophysical cytometry should go 'deeper' in terms of exploiting the information-rich cellular biophysical content, generating a molecular knowledge base of cellular biophysical properties, and standardizing the protocols for wider dissemination. Overcoming these barriers, which requires concurrent innovations in microfluidics, optical imaging, and computer vision, could unleash the enormous potential of biophysical cytometry not only for gaining a new mechanistic understanding of biological systems but also for identifying new cost-effective biomarkers of disease.
Recent advances in biophysical cytometry now make it possible to recapitulate cellular heterogeneity at the levels of throughput, precision, specificity, and sensitivity that were once inconceivable.Technological developments in state-of-the-art biophysical cytometry include single-cell mass assays, cell traction force assays, deformability and impedance cytometry, and label-free imaging cytometry.Next-generation biophysical cytometry could be more comprehensive and information-rich by exploring multimodal integration, such as simultaneous read-out of cell mass, stiffness, and morphology.How molecular signatures translate into cellular biophysical properties is not fully understood. Advanced techniques involving microfluidics, imaging, and deep learning could investigate this link.Standardizing the protocols and datasets of biophysical cytometry will be crucial to ensure wide dissemination.
Display omitted
•The CHO genome suffers from chromosomal rearrangements and other stability-related issues.•The CHO cell instability phenotype is characterized by titer instability and product ...quality instability.•Product quality consistency is important for new therapeutics and vital for biosimilar approval.•Systems biology needed to identify instability biomarkers and to design subsequent approaches for addressing instability.
Chinese hamster ovary (CHO) cell-based bioproduction of recombinant proteins can now routinely achieve >5 g/L titers in fed-batches. This progress is partly due to the rapid adaptability of CHO cells to various genetic manipulations and changing process conditions. An inherently plastic genome allows for this adaptability; however, it also gives CHO cells the propensity for genomic rearrangements. In combination with the genomic and metabolic demand of high producer cells, CHO cell plasticity manifests itself in the bioproduction process as cell line instability, by way of a decline in productivity and product quality. In this review, we provide a definition for titer and quality stability and discuss the main causes of the CHO instability phenomenon and advances in clone selection and genetic manipulations. We also discuss advances in systems biology efforts that can provide new strategies for early prediction of CHO cell instability, which will help to identify multi-gram per liter titer cell lines that can maintain production stability and reproducible product quality over extended culture durations.
The Chinese hamster ovary (CHO) cell lines that are used to produce commercial quantities of therapeutic proteins commonly exhibit a decrease in productivity over time in culture, a phenomenon termed ...production instability. Random integration of the transgenes encoding the protein of interest into locations in the CHO genome that are vulnerable to genetic and epigenetic instability often causes production instability through copy number loss and silencing of expression. Several recent publications have shown that these cell line development challenges can be overcome by using site‐specific integration (SSI) technology to insert the transgenes at genomic loci, often called “hotspots,” that are transcriptionally permissive and have enhanced stability relative to the rest of the genome. However, extensive characterization of the CHO epigenome is needed to identify hotspots that maintain their desirable epigenetic properties in an industrial bioprocess environment and maximize transcription from a single integrated transgene copy. To this end, the epigenomes and transcriptomes of two distantly related cell lines, an industrially relevant monoclonal antibody‐producing cell line and its parental CHO‐K1 host, were characterized using high throughput chromosome conformation capture and RNAseq to analyze changes in the epigenome that occur during cell line development and associated changes in system‐wide gene expression. In total, 10.9% of the CHO genome contained transcriptionally permissive three‐dimensional chromatin structures with enhanced genetic and epigenetic stability relative to the rest of the genome. These safe harbor regions also showed good agreement with published CHO epigenome data, demonstrating that this method was suitable for finding genomic regions with epigenetic markers of active and stable gene expression. These regions significantly reduce the genomic search space when looking for CHO hotspots with widespread applicability and can guide future studies with the goal of maximizing the potential of SSI technology in industrial production CHO cell lines.
In this work, Hilliard and Lee present a novel application of multi‐scale analysis of the three‐dimensional CHO epigenome to search for safe harbor regions suitable for transgene integration in industrial therapeutic protein producing cell lines. Epigenetic differences observed between two related CHO‐K1 cell lines were associated with systemic transcriptomic changes. These strong associations enabled the use of several 3D chromatin structures as markers of expression stability, narrowing down the CHO genome to only safe harbor regions.
Durable humoral immunity is dependent upon the generation of antigen-specific antibody titers, produced by non-proliferating bone marrow resident long-lived plasma cells (LLPC). Longevity is the ...hallmark of LLPC, but why and how they survive and function for years after antigen exposure is only beginning to be understood. LLPC are not intrinsically long-lived; they require continuous signals from the LLPC niche to survive. Signals unique to LLPC survival (vs. PC survival in general) most notably include those that upregulate the anti-apoptotic factor Mcl-1 and activation of the CD28 receptor expressed on LLPC. Other potential factors include expression of BCMA, upregulation of the transcription factor ZBTB20, and upregulation of the enzyme ENPP1. Metabolic fitness is another key component of LLPC longevity, facilitating the diversion of glucose to generate pyruvate during times of stress to facilitate long term survival. A third major component of LLPC survival is the microenvironment/LLPC niche itself. Cellular partners such as stromal cells, dendritic cells, and T regulatory cells establish a niche for LLPC and drive survival signaling by expressing ligands such as CD80/CD86 for CD28 and producing soluble and stromal factors that contribute to LLPC longevity. These findings have led to the current paradigm wherein both intrinsic and extrinsic mechanisms are required for the survival of LLPC. Here we outline this diverse network of signals and highlight the mechanisms thought to regulate and promote the survival of LLPC. Understanding this network of signals has direct implications in increasing our basic understanding of plasma cell biology, but also in vaccine and therapeutic drug development to address the pathologies that can arise from this subset.
Abstract
Motivation
New single-cell technologies continue to fuel the explosive growth in the scale of heterogeneous single-cell data. However, existing computational methods are inadequately ...scalable to large datasets and therefore cannot uncover the complex cellular heterogeneity.
Results
We introduce a highly scalable graph-based clustering algorithm PARC—Phenotyping by Accelerated Refined Community-partitioning—for large-scale, high-dimensional single-cell data (>1 million cells). Using large single-cell flow and mass cytometry, RNA-seq and imaging-based biophysical data, we demonstrate that PARC consistently outperforms state-of-the-art clustering algorithms without subsampling of cells, including Phenograph, FlowSOM and Flock, in terms of both speed and ability to robustly detect rare cell populations. For example, PARC can cluster a single-cell dataset of 1.1 million cells within 13 min, compared with >2 h for the next fastest graph-clustering algorithm. Our work presents a scalable algorithm to cope with increasingly large-scale single-cell analysis.
Availability and implementation
https://github.com/ShobiStassen/PARC.
Supplementary information
Supplementary data are available at Bioinformatics online.
A compendium of stable hotspots in the CHO genome Hilliard, William; Lee, Kelvin H.
Biotechnology and bioengineering,
August 2023, 2023-Aug, 2023-08-00, 20230801, Volume:
120, Issue:
8
Journal Article
Peer reviewed
Open access
The use of targeted integration for industrial CHO cell line development currently requires significant upfront effort to identify genomic loci capable of supporting multigram per liter therapeutic ...protein production from a limited number of transgene copies. To address this barrier to widespread adoption, we characterized transgene expression from thousands of stable hotspots in the CHO genome using the Thousands of Reporters Integrated in Parallel high‐throughput screening method. This genome‐scale data set was used to define a limited set of epigenetic properties of hotspot regions with sizes on the order of 10 kb. Cell lines with landing pad integrations at eight retargeted hotspot candidates consistently exhibited higher transgene mRNA expression than a commercially viable hotspot in equivalent culture conditions. Initial benchmarking of NISTmAb and trastuzumab productivity from one of these hotspots yielded mAb productivities of approximately 0.7–2 g/L (qP range: 2.9–8.2 pg/cell/day) in small‐scale fed‐batches. These findings indicate the list of hotspot candidates identified here will be a valuable resource for targeted integration platform development within the CHO community.
Efforts to leverage clustered regularly interspaced short palindromic repeats/CRISPR‐associated protein 9 (CRISPR/Cas9) for targeted genomic modifications in mammalian cells are limited by low ...efficiencies and heterogeneous outcomes. To aid method optimization, we developed an all‐in‐one reporter system, including a novel superfolder orange fluorescent protein (sfOrange), to simultaneously quantify gene disruption, site‐specific integration (SSI), and random integration (RI). SSI strategies that utilize different donor plasmid formats and Cas9 nuclease variants were evaluated for targeting accuracy and efficiency in Chinese hamster ovary cells. Double‐cut and double‐nick donor formats significantly improved targeting accuracy by 2.3–8.3‐fold and 19–22‐fold, respectively, compared to standard circular donors. Notably, Cas9‐mediated donor linearization was associated with increased RI events, whereas donor nicking minimized RI without sacrificing SSI efficiency and avoided low‐fidelity outcomes. A screen of 10 molecules that modulate the major mammalian DNA repair pathways identified two inhibitors that further enhance targeting accuracy and efficiency to achieve SSI in 25% of transfected cells without selection. The optimized methods integrated transgene expression cassettes with 96% efficiency at a single locus and with 53%–55% efficiency at two loci simultaneously in selected clones. The CRISPR‐based tools and methods developed here could inform the use of CRISPR/Cas9 in mammalian cell lines, accelerate mammalian cell line engineering, and support advanced recombinant protein production applications.
Inflammation can be a risk factor for neurodegenerative diseases such as Alzheimer's disease (AD) and may also contribute to the progression of AD. Here, we sought to understand how inflammation ...affects the properties of the brain microvascular endothelial cells (BMECs) that compose the blood-brain barrier (BBB), which is impaired in AD. A fully human in vitro BBB model with brain microvascular endothelial cells derived from induced pluripotent stem cells and differentiating neural stem cell (NSC)-derived astrocytic cells was used to investigate the effects of neuroinflammation on barrier function. The cytokines TNF-α and IL-6 directly cause BBB dysfunction measured by a decrease in transendothelial electrical resistance, an increase in sodium fluorescein permeability, and a decrease in cell polarity, providing a link between neuroinflammation and specific aspects of BBB breakdown. An NSC-derived astrocytic cell population was added to the model and secreted cytokines and chemokines were quantified in monoculture and coculture both in the presence and absence of TNF-α and IL-6. Increased concentrations of pro-inflammatory cytokines known to be secreted by astrocytes or endothelial cells such as MCP-1, IL-8, IP-10, MIP-1β, IL-1 β, MIG, and RANTES peaked in inflammatory conditions when NSC-astrocytic cells were present. Despite the presence of several pro-inflammatory cytokines, the NSC-derived astrocytic cells mitigated the effects of inflammation measured by a restoration of transendothelial electrical resistance and IgG permeability. These results also suggest a breakdown in transcellular transport that precedes any increase in paracellular permeability in neuroinflammation. This model has the potential to resolve questions about neurodegenerative disease progression and delivery of therapeutics to the brain.
•iPSC-brain endothelial cells and NSC-astrocytes form an in vitro BBB model.•TNF-α and IL-6 cause BBB dysfunction via an increase in transcellular permeability.•With NSC-derived astrocytes, more proinflammatory cytokines are secreted.•Despite cytokines, NSC-astrocytes help barrier breakdown caused by TNF-α and IL-6.•This stem-cell derived BBB model can be used to understand disease progression.
ABSTRACT
We present Galaxy Zoo DECaLS: detailed visual morphological classifications for Dark Energy Camera Legacy Survey images of galaxies within the SDSS DR8 footprint. Deeper DECaLS images (r = ...23.6 versus r = 22.2 from SDSS) reveal spiral arms, weak bars, and tidal features not previously visible in SDSS imaging. To best exploit the greater depth of DECaLS images, volunteers select from a new set of answers designed to improve our sensitivity to mergers and bars. Galaxy Zoo volunteers provide 7.5 million individual classifications over 314 000 galaxies. 140 000 galaxies receive at least 30 classifications, sufficient to accurately measure detailed morphology like bars, and the remainder receive approximately 5. All classifications are used to train an ensemble of Bayesian convolutional neural networks (a state-of-the-art deep learning method) to predict posteriors for the detailed morphology of all 314 000 galaxies. We use active learning to focus our volunteer effort on the galaxies which, if labelled, would be most informative for training our ensemble. When measured against confident volunteer classifications, the trained networks are approximately 99 per cent accurate on every question. Morphology is a fundamental feature of every galaxy; our human and machine classifications are an accurate and detailed resource for understanding how galaxies evolve.
PDF
