Selecting particles from digital micrographs is an essential step in single-particle electron cryomicroscopy (cryo-EM). As manual selection of complete datasets—typically comprising thousands of particles—is a tedious and time-consuming process, numerous automatic particle pickers have been developed. However, non-ideal datasets pose a challenge to particle picking. Here we present the particle picking software crYOLO which is based on the deep-learning object detection system You Only Look Once (YOLO). After training the network with 200–2500 particles per dataset it automatically recognizes particles with high recall and precision while reaching a speed of up to five micrographs per second. Further, we present a general crYOLO network able to pick from previously unseen datasets, allowing for completely automated on-the-fly cryo-EM data preprocessing during data acquisition. crYOLO is available as a standalone program under http://sphire.mpg.de/ and is distributed as part of the image processing workflow in SPHIRE.

Selecting particles from digital micrographs is an essential step in single particle electron cryomicroscopy (cryo-EM). Since manual selection of complete datasets typically comprising many thousands of particles is a tedious and time-consuming process, many automatic particle pickers have been developed in the past few decades.However, non-ideal datasets pose a challenge to particle picking. Here, we present a novel automated particle picking software called crYOLO, which is based on the deep learning object detection system "You Only Look Once" (YOLO). After training the network with 500 -2,500 particles per dataset, it automatically recognizes particles with high recall and precision reaching a speed of up to five micrographs per second.Importantly, we demonstrate a powerful general network trained on more than 40 datasets to select previously unseen datasets, thus paving the way for completely automated "on-the-fly" cryo-EM data pre-processing during data acquisition. CrYOLO is available as a standalone program under http://sphire.mpg.de/ and will be part of the image processing workflow in SPHIRE.

Zinc is an essential micronutrient for all living organisms, required for signaling and proper function of a range of proteins involved in e.g. DNA-binding and enzymatic catalysis 1 . In prokaryotes and photosynthetic eukaryotes Zn 2+ -transporting P-type ATPases of class IB (ZntA) are crucial for cellular redistribution and detoxification of Zn 2+ and related elements 2,3 . Here we present crystal structures representing the phosphoenzyme ground state (E2P) and a dephosphorylation intermediate (E2.P i ) of ZntA from Shigella sonnei, determined at 3.2 and 2.7 Å resolution, respectively. The structures reveal a similar fold as the Cu + -ATPases with an amphipathic helix at the membrane interface. A conserved electronegative funnel connects this region to the intramembranous high-affinity ion-binding site and may promote specific uptake of cellular Zn 2+ ions. The E2P structure displays a wide extracellular release pathway reaching the invariant residues at the high-affinity site, including Cys392, Cys394 and Asp714. The pathway closes in the E2.P i state where Asp714 interacts with the conserved Lys693, which possibly stimulates Zn 2+ release as a built-in counter-ion, as also proposed for H + -ATPases. Indeed, transport studies in liposomes provide experimental support for ZntA activity without counter-

Heavy metals in cells are typically regulated by PIB-type ATPases such as the copper transporting Cu+-ATPases. The first crystal structure of a Cu+-ATPase (LpCopA) was trapped in a transition state of dephosphorylation (E2.Pi) and inferred to be occluded. The structure revealed a PIB-specific topology and suggested a copper transport pathway across the membrane. Here we show by molecular dynamics (MD) simulations that extracellular water solvates the transmembrane (TM) domain, indicative of a pathway for Cu+ release. Furthermore, a new LpCopA crystal structure determined at 2.8 Å resolution, trapped in the E2P state (which is associated with extracellular exchange in PII-type ATPases), delineates the same conduit as also further supported by site-directed mutagenesis. The E2P and E2.Pi states therefore appear equivalent and open to the extracellular side, in contrast to PII-type ATPases where the E2.Pi state is occluded. This indicates that Cu+-ATPases couple dephosphorylation differently to the conformational changes associated with ion extrusion. The ion pathway may explain why Menkes’ and Wilson’s disease mutations at the extracellular side impair protein function, and points to an accessible site for novel inhibitors targeting Cu+-ATPases of pathogens.