O-Glycosylation Landscapes of SARS-CoV-2 Spike Proteins

The densely glycosylated spike (S) proteins that are highly exposed on the surface of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) facilitate viral attachment, entry, and membrane fusion. We have previously reported all the 22 N-glycosites and site-specific N-glycans in the S protein protomer. Herein, we report the O-glycosylation landscapes of SARS-CoV-2 S proteins, which were characterized through high-resolution mass spectrometry. Following digestion with trypsin and trypsin/Glu-C, and de-N-glycosylation using PNGase F, we determined the GalNAc-type O-glycosylation pattern of S proteins, including O-glycosites and the six most common O-glycans occupying them, via Byonic identification and manual validation. Finally, 255 intact O-glycopeptides composed of 50 peptides sequences and 43 O-glycosites were discovered by higher energy collision-induced dissociation (HCD), and three O-glycosites were confidently identified by electron transfer/higher energy collision-induced dissociation (EThcD) in the insect cell-expressed S protein. Most glycosites were modified by non-sialylated O-glycans such as HexNAc(1) and HexNAc(1)Hex (1). In contrast, in the human cell-expressed S protein S1 subunit, 407 intact O-glycopeptides composed of 34 peptides sequences and 30 O-glycosites were discovered by HCD, and 11 O-glycosites were unambiguously assigned by EThcD. However, the measurement of O-glycosylation occupancy hasn’t been made. Most glycosites were modified by sialylated O-glycans such as HexNAc(1)Hex (1)NeuAc (1) and HexNAc(1)Hex (1)NeuAc (2). Our results reveal that the SARS-CoV-2 S protein is an O-glycoprotein; the O-glycosites and O-glycan compositions vary with the host cell type. These comprehensive O-glycosylation landscapes of the S protein are expected to provide novel insights into the viral binding mechanism and present a strategy for the development of vaccines and targeted drugs.

Energy-collision-aware Minimum Latency Aggregation Scheduling for Energy-harvesting Sensor Networks

The emerging energy-harvesting technology enables charging sensor batteries with renewable energy sources, which has been effectively integrated into Wireless Sensor Networks (EH-WSNs). Due to the limited energy-harvesting capacities of tiny sensors, the captured energy remains scarce and differs greatly among nodes, which makes the data aggregation scheduling problem more challenging than that in energy-abundant WSNs. In this article, we investigate the Minimum Latency Aggregation Scheduling (MLAS) problem in EH-WSNs. First, we identify a new kind of collision in EH-WSNs, named as energy-collision, and design several special structures to avoid it during data aggregation. To reduce the latency, we try to choose the parent adaptively according to nodes’ transmission tasks and energy-harvesting ability, under the consideration of collisions avoidance. By considering transmitting time, residual energy, and energy-collision, three scheduling algorithms are proposed under protocol interference model. Under physical interference model, several approximate algorithms are also designed by taking account of the interference from the nodes several hops away. Finally, the theoretical analysis and simulation results verify that the proposed algorithms have high performance in terms of latency.

Analysis of Multipolar Linear Paul Traps for Ion–Atom Ultracold Collision Experiments

We evaluate the performance of multipole, linear Paul traps for the purpose of studying cold ion–atom collisions. A combination of numerical simulations and analysis based on the virial theorem is used to draw conclusions on the differences that result, by considering the trapping details of several multipole trap types. Starting with an analysis of how a low energy collision takes place between a fully compensated, ultracold trapped ion and an stationary atom, we show that a higher order multipole trap is, in principle, advantageous in terms of collisional heating. The virial analysis of multipole traps then follows, along with the computation of trapped ion trajectories in the quadrupole, hexapole, octopole and do-decapole radio frequency traps. A detailed analysis of the motion of trapped ions as a function of the amplitude, phase and stability of the ion’s motion is used to evaluate the experimental prospects for such traps. The present analysis has the virtue of providing definitive answers for the merits of the various configurations, using first principles.

Mass spectrometry-based sequencing of the anti-FLAG-M2 antibody using multiple proteases and a dual fragmentation scheme

Antibody sequence information is crucial to understanding the structural basis for antigen binding and enables the use of antibodies as therapeutics and research tools. Here we demonstrate a method for direct de novo sequencing of monoclonal IgG from the purified antibody products. The method uses a panel of multiple complementary proteases to generate suitable peptides for de novo sequencing by LC-MS/MS in a bottom-up fashion. Furthermore, we apply a dual fragmentation scheme, using both stepped high-energy collision dissociation (stepped HCD) and electron transfer high-energy collision dissociation (EThcD) on all peptide precursors. The method achieves full sequence coverage of the monoclonal antibody Herceptin, with an accuracy of 98% in the variable regions. We applied the method to sequence the widely used anti-FLAG-M2 mouse monoclonal antibody, which we successfully validated by remodeling a high-resolution crystal structure of the Fab and demonstrating binding to a FLAG-tagged target protein in Western blot analysis. The method thus offers robust and reliable sequences of monoclonal antibodies.

Attenuation of doubly charged ion interferences on arsenic and selenium by ICP-MS under low kinetic energy collision cell conditions with hydrogen cell gas

A collision cell with hydrogen gas in place of the widely used helium attenuates not only polyatomic ion interference but also doubly charged ion interference by using KED.

The influence of surface charge on the coalescence of ice and dust particles in the mesosphere

Agglomeration of charged ice and dust particles in the mesosphere is studied using a classical electrostatic approach, which is extended to capture the induced polarisation of surface charge. Collision outcomes are predicted whilst varying particle size, charge, dielectric constant, relative kinetic energy, collision geometry and the coefficient of restitution. In addition to attractive Coulomb forces acting on particles of opposite charge, instances of strong attraction between particles of the same sign of charge are predicted, which take place at small separation distances and also lead to the formation of stable aggregates. These attractive forces are governed by the polarisation of surface charge.

SIZE-DEPENDENT EFFECTS IN ATOMIC CLUSTERS

The size-dependence of different physical properties of atomic clusters (by the example of binding energy, collision diameter, and static isotropic polarizability) is discussed.