Automated cell counting for Trypan blue-stained cell cultures using machine learning.

Cell counting is a vital practice in the maintenance and manipulation of cell cultures. It is a crucial aspect of assessing cell viability and determining proliferation rates, which are integral to maintaining the health and functionality of a culture. Additionally, it is critical for establishing the time of infection in bioreactors and monitoring cell culture response to targeted infection over time. However, when cell counting is performed manually, the time involved can become substantial, particularly when multiple cultures need to be handled in parallel. Automated cell counters, which enable significant time reduction, are commercially available but remain relatively expensive. Here, we present a machine learning (ML) model based on YOLOv4 that is able to perform cell counts with a high accuracy (>95%) for Trypan blue-stained insect cells. Images of two distinctly different cell lines, Trichoplusia ni (High FiveTM; Hi5 cells) and Spodoptera frugiperda (Sf9), were used for training, validation, and testing of the model. The ML model yielded F1 scores of 0.97 and 0.96 for alive and dead cells, respectively, which represents a substantially improved performance over that of other cell counters. Furthermore, the ML model is versatile, as an F1 score of 0.96 was also obtained on images of Trypan blue-stained human embryonic kidney (HEK) cells that the model had not been trained on. Our implementation of the ML model comes with a straightforward user interface and can image in batches, which makes it highly suitable for the evaluation of multiple parallel cultures (e.g. in Design of Experiments). Overall, this approach for accurate classification of cells provides a fast, bias-free alternative to manual counting.

Characterizing single-molecule dynamics of viral RNA-dependent RNA polymerases with multiplexed magnetic tweezers.

Multiplexed single-molecule magnetic tweezers (MT) have recently been employed to probe the RNA synthesis dynamics of RNA-dependent RNA polymerases (RdRp). Here, we present a protocol for simultaneously probing the RNA synthesis dynamics of hundreds of single polymerases with MT. We describe the preparation of a dsRNA construct for probing single RdRp kinetics. We then detail the measurement of RdRp RNA synthesis kinetics using MT. The protocol is suitable for high-throughput probing of RdRp-targeting antiviral compounds for mechanistic function and efficacy. For complete details on the use and execution of this protocol, please refer to Janissen et al. (2021).

Induced intra- and intermolecular template switching as a therapeutic mechanism against RNA viruses.

Viral RNA-dependent RNA polymerases (RdRps) are a target for broad-spectrum antiviral therapeutic agents. Recently, we demonstrated that incorporation of the T-1106 triphosphate, a pyrazine-carboxamide ribonucleotide, into nascent RNA increases pausing and backtracking by the poliovirus RdRp. Here, by monitoring enterovirus A-71 RdRp dynamics during RNA synthesis using magnetic tweezers, we identify the "backtracked" state as an intermediate used by the RdRp for copy-back RNA synthesis and homologous recombination. Cell-based assays and RNA sequencing (RNA-seq) experiments further demonstrate that the pyrazine-carboxamide ribonucleotide stimulates these processes during infection. These results suggest that pyrazine-carboxamide ribonucleotides do not induce lethal mutagenesis or chain termination but function by promoting template switching and formation of defective viral genomes. We conclude that RdRp-catalyzed intra- and intermolecular template switching can be induced by pyrazine-carboxamide ribonucleotides, defining an additional mechanistic class of antiviral ribonucleotides with potential for broad-spectrum activity.

Cell Boundary Confinement Sets the Size and Position of the E. coli Chromosome.

Although the spatiotemporal structure of the genome is crucial to its biological function, many basic questions remain unanswered on the morphology and segregation of chromosomes. Here, we experimentally show in Escherichia coli that spatial confinement plays a dominant role in determining both the chromosome size and position. In non-dividing cells with lengths increased to 10 times normal, single chromosomes are observed to expand > 4-fold in size. Chromosomes show pronounced internal dynamics but exhibit a robust positioning where single nucleoids reside robustly at mid-cell, whereas two nucleoids self-organize at 1/4 and 3/4 positions. The cell-size-dependent expansion of the nucleoid is only modestly influenced by deletions of nucleoid-associated proteins, whereas osmotic manipulation experiments reveal a prominent role of molecular crowding. Molecular dynamics simulations with model chromosomes and crowders recapitulate the observed phenomena and highlight the role of entropic effects caused by confinement and molecular crowding in the spatial organization of the chromosome.