Time-resolved β-lactam cleavage by L1 metallo-β-lactamase

Serial x-ray crystallography can uncover binding events, and subsequent chemical conversions occurring during enzymatic reaction. Here, we reveal the structure, binding and cleavage of moxalactam antibiotic bound to L1 metallo-β-lactamase (MBL) from Stenotrophomonas maltophilia. Using time-resolved serial synchrotron crystallography, we show the time course of β-lactam hydrolysis and determine ten snapshots (20, 40, 60, 80, 100, 150, 300, 500, 2000 and 4000 ms) at 2.20 Å resolution. The reaction is initiated by laser pulse releasing Zn2+ ions from a UV-labile photocage. Two metal ions bind to the active site, followed by binding of moxalactam and the intact β-lactam ring is observed for 100 ms after photolysis. Cleavage of β-lactam is detected at 150 ms and the ligand is significantly displaced. The reaction product adjusts its conformation reaching steady state at 2000 ms corresponding to the relaxed state of the enzyme. Only small changes are observed in the positions of Zn2+ ions and the active site residues. Mechanistic details captured here can be generalized to other MBLs.

Linking scientific instruments and computation: Patterns, technologies, and experiences

Powerful detectors at modern experimental facilities routinely collect data at multiple GB/s. Online analysis methods are needed to enable the collection of only interesting subsets of such massive data streams, such as by explicitly discarding some data elements or by directing instruments to relevant areas of experimental space. Thus, methods are required for configuring and running distributed computing pipelines—what we call flows—that link instruments, computers (e.g., for analysis, simulation, artificial intelligence [AI] model training), edge computing (e.g., for analysis), data stores, metadata catalogs, and high-speed networks. We review common patterns associated with such flows and describe methods for instantiating these patterns. We present experiences with the application of these methods to the processing of data from five different scientific instruments, each of which engages powerful computers for data inversion,model training, or other purposes. We also discuss implications of such methods for operators and users of scientific facilities.

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Patterns for linking instruments and computers for online analysis are reviewed

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Methods are presented for capturing such “flows” in reusable forms

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The use of Globus automation services to run flows is described

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Implications of these methods for scientists and facilities are discussed

The industrial revolution transformed society via large-scale automation of manufacturing. Today, AI- and robotics-driven automation of scientific research seems set to usher in a new era of accelerated discovery. But just as the industrial revolution depended on new replicable and scalable manufacturing processes and methods for delivering the copious mechanical power required by those processes, so the automated discovery revolution demands new methods for implementing research automation processes and for connecting those processes to computing and data power. We present here new methods that address these essential needs by allowing scientists to capture common automation patterns in reusable flows and to embed such flows in a global trust, data, and computing fabric that enables instant access to powerful AI, simulation, and other computational capabilities. We use examples from synchrotron light sources to show how these methods can be realized in software and applied at scale.

Fixed-target serial crystallography at the Structural Biology Center

Serial synchrotron crystallography enables the study of protein structures under physiological temperature and reduced radiation damage by collection of data from thousands of crystals. The Structural Biology Center at Sector 19 of the Advanced Photon Source has implemented a fixed-target approach with a new 3D-printed mesh-holder optimized for sample handling. The holder immobilizes a crystal suspension or droplet emulsion on a nylon mesh, trapping and sealing a near-monolayer of crystals in its mother liquor between two thin Mylar films. Data can be rapidly collected in scan mode and analyzed in near real-time using piezoelectric linear stages assembled in an XYZ arrangement, controlled with a graphical user interface and analyzed using a high-performance computing pipeline. Here, the system was applied to two β-lactamases: a class D serine β-lactamase from Chitinophaga pinensis DSM 2588 and L1 metallo-β-lactamase from Stenotrophomonas maltophilia K279a.

2'-O methylation of RNA cap in SARS-CoV-2 captured by serial crystallography

The genome of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) coronavirus has a capping modification at the 5'-untranslated region (UTR) to prevent its degradation by host nucleases. These modifications are performed by the Nsp10/14 and Nsp10/16 heterodimers using S-adenosylmethionine as the methyl donor. Nsp10/16 heterodimer is responsible for the methylation at the ribose 2'-O position of the first nucleotide. To investigate the conformational changes of the complex during 2'-O methyltransferase activity, we used a fixed-target serial synchrotron crystallography method at room temperature. We determined crystal structures of Nsp10/16 with substrates and products that revealed the states before and after methylation, occurring within the crystals during the experiments. Here we report the crystal structure of Nsp10/16 in complex with Cap-1 analog (m7GpppAm2'-O). Inhibition of Nsp16 activity may reduce viral proliferation, making this protein an attractive drug target.