CRISPR-based systems for sensitive and rapid on-site COVID-19 diagnostics.

The COVID-19 pandemic has strained healthcare systems. Sensitive, specific, and timely COVID-19 diagnosis is crucial for effective medical intervention and transmission control. RT-PCR is the most sensitive/specific, but requires costly equipment and trained personnel in centralized laboratories, which are inaccessible to resource-limited areas. Antigen rapid tests enable point-of-care (POC) detection but are significantly less sensitive/specific. CRISPR-Cas systems are compatible with isothermal amplification and dipstick readout, enabling sensitive/specific on-site testing. However, improvements in sensitivity and workflow complexity are needed to spur clinical adoption. We outline the mechanisms/strategies of major CRISPR-Cas systems, evaluate their on-site diagnostic capabilities, and discuss future research directions.

Assessing Toxicity with Human Cell-Based In Vitro Methods.

In toxicology, there is a strong push towards replacing animal experiments with alternative methods, which include cell-based in vitro methods for the assessment of adverse health effects in humans. High-throughput methods are of central interest due to the large and steadily growing numbers of compounds that require assessment. Tremendous progress has been made during the last decade in developing and applying such methods. Innovative technologies for addressing complex biological interactions include induced pluripotent stem cell- and organoid-based approaches, organotypic coculture systems, and microfluidic 'multiorgan' chips. Combining in vitro methods with bioinformatics and in silico modeling generates new powerful tools for toxicity assessment, and the rapid progress in the field is expected to continue.

Stem cell-derived kidney cells and organoids: Recent breakthroughs and emerging applications.

The global rise in the numbers of kidney patients and the shortage in transplantable organs have led to an increasing interest in kidney-specific regenerative therapies, renal disease modelling and bioartificial kidneys. Sources for large quantities of high-quality renal cells and tissues would be required, also for applications in in vitro platforms for compound safety and efficacy screening. Stem cell-based approaches for the generation of renal-like cells and tissues would be most attractive, but such methods were not available until recently. This situation has drastically changed since 2013, and various protocols for the generation of renal-like cells and precursors from pluripotent stem cells (PSC) have been established. The most recent breakthroughs were related to the establishment of various protocols for the generation of PSC-derived kidney organoids. In combination with recent advances in genome editing, bioprinting and the establishment of predictive renal screening platforms this results in exciting new possibilities. This review will give a comprehensive overview over current PSC-based protocols for the generation of renal-like cells, precursors and organoids, and their current and potential applications in regenerative medicine, compound screening, disease modelling and bioartificial organs.

Prediction of drug-induced nephrotoxicity and injury mechanisms with human induced pluripotent stem cell-derived cells and machine learning methods.

The renal proximal tubule is a main target for drug-induced toxicity. The prediction of proximal tubular toxicity during drug development remains difficult. Any in vitro methods based on induced pluripotent stem cell-derived renal cells had not been developed, so far. Here, we developed a rapid 1-step protocol for the differentiation of human induced pluripotent stem cells (hiPSC) into proximal tubular-like cells. These proximal tubular-like cells had a purity of >90% after 8 days of differentiation and could be directly applied for compound screening. The nephrotoxicity prediction performance of the cells was determined by evaluating their responses to 30 compounds. The results were automatically determined using a machine learning algorithm called random forest. In this way, proximal tubular toxicity in humans could be predicted with 99.8% training accuracy and 87.0% test accuracy. Further, we studied the underlying mechanisms of injury and drug-induced cellular pathways in these hiPSC-derived renal cells, and the results were in agreement with human and animal data. Our methods will enable the development of personalized or disease-specific hiPSC-based renal in vitro models for compound screening and nephrotoxicity prediction.

Identification of nephrotoxic compounds with embryonic stem-cell-derived human renal proximal tubular-like cells.

The kidney is a major target for drug-induced toxicity, and the renal proximal tubule is frequently affected. Nephrotoxicity is typically detected only late during drug development, and the nephrotoxic potential of newly approved drugs is often underestimated. A central problem is the lack of preclinical models with high predictivity. Validated in vitro models for the prediction of nephrotoxicity are not available. Major problems are related to the identification of appropriate cell models and end points. As drug-induced kidney injury is associated with inflammatory reactions, we explored the expression of inflammatory markers as end point for renal in vitro models. In parallel, we developed a new cell model. Here, we combined these approaches and developed an in vitro model with embryonic stem-cell-derived human renal proximal tubular-like cells that uses the expression of interleukin (IL)-6 and IL-8 as end points. The predictivity of the model was evaluated with 41 well-characterized compounds. The results revealed that the model predicts proximal tubular toxicity in humans with high accuracy. In contrast, the predictivity was low when well-established standard in vitro assays were used. Together, the results show that high predictivity can be obtained with in vitro models employing pluripotent stem cell-derived human renal proximal tubular-like cells.