Plasma membrane abundance dictates phagocytic capacity and functional crosstalk in myeloid cells.

Professional phagocytes like neutrophils and macrophages tightly control what they eat, how much they eat, and when they move after eating. We show that plasma membrane abundance is a key arbiter of these cellular behaviors. Neutrophils and macrophages lacking the G-protein subunit Gb4 exhibit profound plasma membrane expansion due to enhanced production of sphingolipids. This increased membrane allocation dramatically enhances phagocytosis of bacteria, fungus, apoptotic corpses, and cancer cells. Gb4 deficient neutrophils are also defective in the normal inhibition of migration following cargo uptake. In Gb4 knockout mice, myeloid cells exhibit enhanced phagocytosis of inhaled fungal conidia in the lung but also increased trafficking of engulfed pathogens to other organs. These results reveal an unexpected, biophysical control mechanism lying at the heart of myeloid functional decision-making.

Fully automated multi-grid cryoEM screening using Smart Leginon.

Single-particle cryo-electron microscopy (cryoEM) is a swiftly growing method for understanding protein structure. With increasing demand for high-throughput, high-resolution cryoEM services comes greater demand for rapid and automated cryoEM grid and sample screening. During screening, optimal grids and sample conditions are identified for subsequent high-resolution data collection. Screening is a major bottleneck for new cryoEM projects because grids must be optimized for several factors, including grid type, grid hole size, sample concentration, buffer conditions, ice thickness and particle behavior. Even for mature projects, multiple grids are commonly screened to select a subset for high-resolution data collection. Here, machine learning and novel purpose-built image-processing and microscope-handling algorithms are incorporated into the automated data-collection software Leginon, to provide an open-source solution for fully automated high-throughput grid screening. This new version, broadly called Smart Leginon, emulates the actions of an operator in identifying areas on the grid to explore as potentially useful for data collection. Smart Leginon Autoscreen sequentially loads and examines grids from an automated specimen-exchange system to provide completely unattended grid screening across a set of grids. Comparisons between a multi-grid autoscreen session and conventional manual screening by 5 expert microscope operators are presented. On average, Autoscreen reduces operator time from ∼6 h to <10 min and provides a percentage of suitable images for evaluation comparable to the best operator. The ability of Smart Leginon to target holes that are particularly difficult to identify is analyzed. Finally, the utility of Smart Leginon is illustrated with three real-world multi-grid user screening/collection sessions, demonstrating the efficiency and flexibility of the software package. The fully automated functionality of Smart Leginon significantly reduces the burden on operator screening time, improves the throughput of screening and recovers idle microscope time, thereby improving availability of cryoEM services.