The understanding of anti-tumor drug effects requires specific experimental settings which model clinical scenarios. We describe a protocol for 10-day treatment of lowly aggressive tumor cell lines with antineoplastic agents at concentrations which do not affect cell growth. We describe steps for seeding cells and treating cells with anti-tumor drugs. We then detail steps for cell sensitivity, cell proliferation, and mRNA and protein expression assays. We also detail assays to determine modifications in compound efflux. For complete details on the use and execution of this protocol, please refer to Rios Medrano et al.1.

CRISPR genome editing is a widely used tool to perturb genes of interest within cells and tissues and can be used as a research tool to study the connection between genotypes and cellular phenotypes. Highly efficient genome editing is limited in certain cell types due to low transfection efficiency or single-cell survivability. This is true for BeWo cells, an in vitro model of placental syncytiotrophoblast cell-cell fusion and hormone secretion. Here we describe an optimized and easy-to-use protocol for knockout in BeWo cells using CRISPR Cas9 ribonucleoprotein (RNP) complexes delivered via electroporation. Further, we describe parameters for successful guide RNA design and how to assess genetic knockouts in BeWo cells so that users can apply this technique to their own genes of interest. We provide a positive control for inducing highly efficient knockout of the cell-cell fusion protein Syncytin-2 (ERVFRD-1) and assessing editing efficiency at this locus. We anticipate that efficient RNP-mediated genetic knockouts in BeWo cells will facilitate the study of new genes involved in cell-cell fusion and hormone secretion in this important cellular model system. Furthermore, this strategy of optimized nucleofection and RNP delivery may be of use in other difficult-to-edit trophoblast cells or could be applied to efficiently deliver transgenes to BeWo cells.

Modern machine learning has the potential to fundamentally change the way bioprocesses are developed. In particular, horizontal knowledge transfer methods, which seek to exploit data from historical processes to facilitate process development for a new product, provide an opportunity to rethink current workflows. In this work, we first assess the potential of two knowledge transfer approaches, meta learning and one-hot encoding, in combination with Gaussian process (GP) models. We compare their performance with GPs trained only on data of the new process, that is, local models. Using simulated mammalian cell culture data, we observe that both knowledge transfer approaches exhibit test set errors that are approximately halved compared to those of the local models when two, four, or eight experiments of the new product are used for training. Subsequently, we address the question whether experiments for a new product could be designed more effectively by exploiting existing knowledge. In particular, we suggest to specifically design a few runs for the novel product to calibrate knowledge transfer models, a task that we coin calibration design. We propose a customized objective function to identify a set of calibration design runs, which exploits differences in the process evolution of historical products. In two simulated case studies, we observed that training with calibration designs yields similar test set errors compared to common design of experiments approaches. However, the former requires approximately four times fewer experiments. Overall, the results suggest that process development could be significantly streamlined when systematically carrying knowledge from one product to the next.

Scale-down models (SDM) are pivotal tools for process understanding and improvement to accelerate the development of vaccines from laboratory research to global commercialization. In this study, a 3 L SDM representing a 50 L scale Vero cell culture process of a live-attenuated virus vaccine using microcarriers was developed and qualified based on the constant impeller power per volume principle. Both multivariate data analysis (MVDA) and the traditional univariate data analysis showed comparable and equivalent cell growth, metabolic activity, and product quality results across scales. Computational fluid dynamics simulation further confirmed similar hydrodynamic stress between the two scales.

Chronic hepatitis C virus infection (HCV) causes liver inflammation and fibrosis, leading to the development of severe liver disease, such as cirrhosis or hepatocellular carcinoma (HCC). Approval of direct-acting antiviral drug combinations has revolutionized chronic HCV therapy, with virus eradication in >98% of the treated patients. The efficacy of these treatments is such that it is formally possible for cured patients to carry formerly infected cells that display irreversible transcriptional alterations directly caused by chronic HCV Infection. Combining differential transcriptomes from two different persistent infection models, we observed a major reversion of infection-related transcripts after complete infection elimination. However, a small number of transcripts were abnormally expressed in formerly infected cells. Comparison of the results obtained in proliferating and growth-arrested cell culture models suggest that permanent transcriptional alterations may be established by several mechanisms. Interestingly, some of these alterations were also observed in the liver biopsies of virologically cured patients. Overall, our data suggest a direct and permanent impact of persistent HCV infection on the host cell transcriptome even after virus elimination, possibly contributing to the development of HCC.

We aimed to assess the performance of Ag-RDT and RT-qPCR with regard to detecting infectious SARS-CoV-2 in cell cultures, as their diagnostic test accuracy (DTA) compared to virus isolation remains largely unknown. We searched three databases up to 15 December 2021 for DTA studies. The bivariate model was used to synthesise the estimates. Risk of bias was assessed using QUADAS-2/C. Twenty studies (2605 respiratory samples) using cell culture and at least one molecular test were identified. All studies were at high or unclear risk of bias in at least one domain. Three comparative DTA studies reported results on Ag-RDT and RT-qPCR against cell culture. Two studies evaluated RT-qPCR against cell culture only. Fifteen studies evaluated Ag-RDT against cell culture as reference standard in RT-qPCR-positive samples. For Ag-RDT, summary sensitivity was 93% (95% CI 78; 98%) and specificity 87% (95% CI 70; 95%). For RT-qPCR, summary sensitivity (continuity-corrected) was 98% (95% CI 95; 99%) and specificity 45% (95% CI 28; 63%). In studies relying on RT-qPCR-positive subsamples (n = 15), the summary sensitivity of Ag-RDT was 93% (95% CI 92; 93%) and specificity 63% (95% CI 63; 63%). Ag-RDT show moderately high sensitivity, detecting most but not all samples demonstrated to be infectious based on virus isolation. Although RT-qPCR exhibits high sensitivity across studies, its low specificity to indicate infectivity raises the question of its general superiority in all clinical settings. Study findings should be interpreted with caution due to the risk of bias, heterogeneity and the imperfect reference standard for infectivity.

The trabecular meshwork (TM) from primary open-angle glaucoma (POAG) cases has been found to contain decreased levels of intracellular plasmalogens. Plasmalogens are a subset of lipids involved in diverse cellular processes such as intracellular signaling, membrane asymmetry, and protein regulation. Proper plasmalogen biosynthesis is regulated by rate-limiting enzyme fatty acyl-CoA reductase (Far1). ATPase phospholipid transporting 8B2 (ATP8B2) is a type IV P-type ATPase responsible for the asymmetric distribution of plasmalogens between the intracellular and extracellular leaflets of the plasma membranes. Here we describe the methodology for extraction and culturing of TM cells from corneal tissue and subsequent downregulation of ATP8B2 using siRNA transfection. Further quantification and downstream effects of ATP8B2 gene knockdown will be analyzed utilizing immunoblotting techniques.

Genome editing is a powerful tool for establishing gene knockout or mutant cell lines. Here, we present a protocol for establishing knockout cell clones by deletion of large gene fragments using CRISPR-Cas9 with multiple guide RNAs. We describe steps for designing guide RNAs, cloning them into CRISPR-Cas9 vectors, cell seeding, transfection into cultured cells, clonal selection, and screening assays. This protocol can delete gene regions over 100 kbp, including GC-rich domains, and is applicable to various cell lines. For complete details on the use and execution of this protocol, please refer to Saito et al.,1 Saito and Endo et al.,2 and Higashi et al.3.

Isolating high-quality different cell types is a powerful approach for understanding cellular compositions and features in the heart, but it is challenging. The available protocols typically focus on isolating one or two cell types. Here, we present a protocol to simultaneously isolate high-quality and high-quantity cardiomyocytes and non-myocyte cells, including immune cells, from adult rat hearts. We describe steps for purifying cells using bovine serum albumin. We also detail procedures for viability analysis and cell type identification using fluorescence-activated cell sorting. For complete details on the use and execution of this protocol, please refer to Zhang et al.,1 Valkov et al.,2 Vang et al.,3 and Li et al.4.

This chapter introduces the increasing significance of mesenchymal stromal/stem cell (MSC) production in regenerative medicine and cellular therapeutics, outlines the growing interest in MSCs for various medical applications, and highlights their potential in advanced therapy medicinal products (ATMPs) and the advancements in cell culture technologies that have facilitated large-scale MSC production under Good Manufacturing Practices (GMP), ensuring safety and efficacy. This chapter describes an optimized upstream protocol for laboratory-scale MSC production from different tissue sources. This protocol, conducted in flasks, controls critical parameters and lays the foundation for downstream processing to generate ATMPs. This comprehensive approach underscores the potential of MSCs in clinical applications and the importance of tailored production processes.