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.

Canonical transient receptor channels (TRPC) are non-selective cation channels. They are involved in receptor-operated Ca2+ signaling and have been proposed to act as store-operated channels (SOC). Their malfunction is related to cardiomyopathies and their modulation by small molecules has been shown to be effective against renal cancer cells. The molecular mechanism underlying the complex activation and regulation is poorly understood. Here, we report the electron cryo-microscopy structure of zebrafish TRPC4 in its unliganded (apo), closed state at an overall resolution of 3.6 Å. The structure reveals the molecular architecture of the cation conducting pore, including the selectivity filter and lower gate. The cytoplasmic domain contains two key hubs that have been shown to interact with modulating proteins. Structural comparisons with other TRP channels give novel insights into the general architecture and domain organization of this superfamily of channels and help to understand their function and pharmacology.

Interferons induce a pleiotropy of responses through binding the same cell surface receptor. Here we investigated the molecular mechanism driving interferon-induced apoptosis. Using a nonbiased small interfering RNA (siRNA) screen, we show that silencing genes whose products are directly engaged in the initiation of interferon signaling completely abrogate the interferon antiproliferative response. Apoptosis-related genes such as the caspase-8, cFLIP, and DR5 genes specifically interfere with interferon-induced apoptosis, which we found to be independent of the activity of death ligands. The one gene for which silencing resulted in the strongest proapoptotic effect upon interferon signaling is the cFLIP gene, where silencing shortened the time of initiation of apoptosis from days to hours and increased dramatically the population of apoptotic cells. Thus, cFLIP serves as a regulator for interferon-induced apoptosis. A shift over time in the balance between cFLIP and caspase-8 results in downstream caspase activation and apoptosis. While gamma interferon (IFN-␥) also causes caspase-8 upregulation, we suggest that it follows a different path to apoptosis.

Canonical transient receptor channels (TRPC) are non-selective cation channels. They are involved in receptor-operated Ca 2+ signaling and have been proposed to act as store-operated channels (SOC). Their malfunction is related to cardiomyopathies and their modulation by small molecules has been shown to be effective against renal cancer cells. The molecular mechanism underlying the complex activation and regulation is poorly understood. Here, we report the electron cryo-microscopy structure of zebrafish TRPC4 in its unliganded (apo), closed state at an overall resolution of 3.6 Å. The structure reveals the molecular architecture of the cation conducting pore, including the selectivity filter and lower gate. The cytoplasmic domain contains two key hubs that have been shown to interact with modulating proteins.Structural comparisons with other TRP channels give novel insights into the general architecture and domain organization of this superfamily of channels and help to understand their function and pharmacology.

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DNA is an attractive medium for storage of digital data in the cloud, owing to a form factor several orders of magnitude smaller than any other. Key to storing binary data in synthetic in DNA is the translation between the binary representation of digital data to the quaternary domain of DNA. This translation must adhere to constraints imposed by the synthesis and sequencing processes used to write and read respectively. A technological advance in either process changes the constraints and renders current encoding schemes obsolete. In this paper we present a recipe for taking constraints and producing an appropriate encoding scheme. Such a mechanism allows moving the encoding in lockstep with the technological advances in the underlying processes. We further show a method to understand trade-offs in constraints for a given overhead of bits needed to meet such constraints.

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