Evaluation of Sort Recovery via Rmax.

Cell sorting performance can be evaluated in regard to the purity and recovery of the sorted fractions. The purity provides checks on sample quality, acquisition settings, gating strategy, and the sort decisions made by the instrument, but alone it is not sufficient to evaluate sorting performance. Recovery, defined here as the number of target particles sorted relative to the number of original target particles to be sorted, is a key metric of sort fitness and performance but is often neglected due to difficulties in its measurement. Both purity and recovery require re-sampling of the sorted fraction, but unlike determining purity, calculating recovery calls for the absolute counting of particles in the sorted fraction that comes with large errors, and may not be feasible for rare populations or precious samples. Here, we describe a recently developed metric and method for calculating sort recovery called Rmax, representing the maximum expected recovery for a particular set of instrument settings. Rmax calculation avoids re-sampling of the total sorted fraction and absolute counting, being instead based on the ratios of target and non-target populations in the original pre-sort sample and in the waste stream or center stream catch. The Rmax method is ideal to evaluate and troubleshoot the optimum drop-charge delay of the sorter or any instrument-related failures that will affect sort performance. It can be used as a daily quality control check but can be particularly useful to assess instrument fitness before single-cell or rare population sorts. Because the sorted fraction is not perturbed, we can calculate Rmax during the sort run. © 2024 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Evaluating sorter setup with Rmax Basic Protocol 2: Finding the maximum Rmax: scanning over the drop charge delay Alternate Protocol: Finding the maximum Rmax for cells: scanning over the drop charge delay Basic Protocol 3: Estimating sorted cell number with Rmax.

SARS-CoV-2 can recruit a heme metabolite to evade antibody immunity.

The coronaviral spike is the dominant viral antigen and the target of neutralizing antibodies. We show that SARS-CoV-2 spike binds biliverdin and bilirubin, the tetrapyrrole products of heme metabolism, with nanomolar affinity. Using cryo-electron microscopy and x-ray crystallography, we mapped the tetrapyrrole interaction pocket to a deep cleft on the spike N-terminal domain (NTD). At physiological concentrations, biliverdin significantly dampened the reactivity of SARS-CoV-2 spike with immune sera and inhibited a subset of neutralizing antibodies. Access to the tetrapyrrole-sensitive epitope is gated by a flexible loop on the distal face of the NTD. Accompanied by profound conformational changes in the NTD, antibody binding requires relocation of the gating loop, which folds into the cleft vacated by the metabolite. Our results indicate that SARS-CoV-2 spike NTD harbors a dominant epitope, access to which can be controlled by an allosteric mechanism that is regulated through recruitment of a metabolite.

SARS-CoV-2 recruits a haem metabolite to evade antibody immunity.

The coronaviral spike is the dominant viral antigen and the target of neutralizing antibodies. We show that SARS-CoV-2 spike binds biliverdin and bilirubin, the tetrapyrrole products of haem metabolism, with nanomolar affinity. Using cryo-electron microscopy and X-ray crystallography we mapped the tetrapyrrole interaction pocket to a deep cleft on the spike N-terminal domain (NTD). At physiological concentrations, biliverdin significantly dampened the reactivity of SARS-CoV-2 spike with immune sera and inhibited a subset of neutralizing antibodies. Access to the tetrapyrrole-sensitive epitope is gated by a flexible loop on the distal face of the NTD. Accompanied by profound conformational changes in the NTD, antibody binding requires relocation of the gating loop, which folds into the cleft vacated by the metabolite. Our results indicate that the virus co-opts the haem metabolite for the evasion of humoral immunity via allosteric shielding of a sensitive epitope and demonstrate the remarkable structural plasticity of the NTD.

Combining fluorescence imaging with Hi-C to study 3D genome architecture of the same single cell.

Fluorescence imaging and chromosome conformation capture assays such as Hi-C are key tools for studying genome organization. However, traditionally, they have been carried out independently, making integration of the two types of data difficult to perform. By trapping individual cell nuclei inside a well of a 384-well glass-bottom plate with an agarose pad, we have established a protocol that allows both fluorescence imaging and Hi-C processing to be carried out on the same single cell. The protocol identifies 30,000-100,000 chromosome contacts per single haploid genome in parallel with fluorescence images. Contacts can be used to calculate intact genome structures to better than 100-kb resolution, which can then be directly compared with the images. Preparation of 20 single-cell Hi-C libraries using this protocol takes 5 d of bench work by researchers experienced in molecular biology techniques. Image acquisition and analysis require basic understanding of fluorescence microscopy, and some bioinformatics knowledge is required to run the sequence-processing tools described here.