Simulation of Energy-Resolved Mass Spectrometry Distributions from Surface-Induced Dissociation.

Understanding the relationship between protein structure and experimental data is crucial for utilizing experiments to solve biochemical problems and optimizing the use of sparse experimental data for structural interpretation. Tandem mass spectrometry (MS/MS) can be used with a variety of methods to collect structural data for proteins. One example is surface-induced dissociation (SID), which is used to break apart protein complexes (via a surface collision) into intact subcomplexes and can be performed at multiple laboratory frame SID collision energies. These energy-resolved MS/MS experiments have shown that the profile of the breakages depends on the acceleration energy of the collision. It is possible to extract an appearance energy (AE) from energy-resolved mass spectrometry (ERMS) data, which shows the relative intensity of each type of subcomplex as a function of SID acceleration energy. We previously determined that these AE values for specific interfaces correlated with structural features related to interface strength. In this study, we further examined the structural relationships by developing a method to predict the full ERMS plot from the structure, rather than extracting a single value. First, we noted that for proteins with multiple interface types, we could reproduce the correct shapes of breakdown curves, further confirming previous structural hypotheses. Next, we demonstrated that interface size and energy density (measured using Rosetta) correlated with data derived from the ERMS plot (R2 = 0.71). Furthermore, based on this trend, we used native crystal structures to predict ERMS. The majority of predictions resulted in good agreement, and the average root-mean-square error was 0.20 for the 20 complexes in our data set. We also show that if additional information on cleavage as a function of collision energy could be obtained, the accuracy of predictions improved further. Finally, we demonstrated that ERMS prediction results were better for the native than for inaccurate models in 17/20 cases. An application to run this simulation has been developed in Rosetta, which is freely available for use.

RBD-based high affinity ACE2 antagonist limits SARS-CoV-2 replication in upper and lower airways.

SARS-CoV-2 has the capacity to evolve mutations to escape vaccine-and infection-acquired immunity and antiviral drugs. A variant-agnostic therapeutic agent that protects against severe disease without putting selective pressure on the virus would thus be a valuable biomedical tool. Here, we challenged rhesus macaques with SARS-CoV-2 Delta and simultaneously treated them with aerosolized RBD-62, a protein developed through multiple rounds of in vitro evolution of SARS-CoV-2 RBD to acquire 1000-fold enhanced ACE2 binding affinity. RBD-62 treatment gave equivalent protection in upper and lower airways, a phenomenon not previously observed with clinically approved vaccines. Importantly, RBD-62 did not block the development of memory responses to Delta and did not elicit anti-drug immunity. These data provide proof-of-concept that RBD-62 can prevent severe disease from a highly virulent variant.

Modulation of type I interferon responses potently inhibits SARS-CoV-2 replication and inflammation in rhesus macaques.

Type I interferons (IFN-I) are critical mediators of innate control of viral infections but also drive the recruitment of inflammatory cells to sites of infection, a key feature of severe coronavirus disease 2019. Here, IFN-I signaling was modulated in rhesus macaques (RMs) before and during acute SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) infection using a mutated IFN-α2 (IFN-modulator; IFNmod), which has previously been shown to reduce the binding and signaling of endogenous IFN-I. IFNmod treatment in uninfected RMs was observed to induce a modest up-regulation of only antiviral IFN-stimulated genes (ISGs); however, in SARS-CoV-2-infected RMs, IFNmod reduced both antiviral and inflammatory ISGs. IFNmod treatment resulted in a potent reduction in SARS-CoV-2 viral loads both in vitro in Calu-3 cells and in vivo in bronchoalveolar lavage (BAL), upper airways, lung, and hilar lymph nodes of RMs. Furthermore, in SARS-CoV-2-infected RMs, IFNmod treatment potently reduced inflammatory cytokines, chemokines, and CD163+ MRC1- inflammatory macrophages in BAL and expression of Siglec-1 on circulating monocytes. In the lung, IFNmod also reduced pathogenesis and attenuated pathways of inflammasome activation and stress response during acute SARS-CoV-2 infection. Using an intervention targeting both IFN-α and IFN-ß pathways, this study shows that, whereas early IFN-I restrains SARS-CoV-2 replication, uncontrolled IFN-I signaling critically contributes to SARS-CoV-2 inflammation and pathogenesis in the moderate disease model of RMs.

Protein quaternary structures in solution are a mixture of multiple forms.

Over half the proteins in the E. coli cytoplasm form homo or hetero-oligomeric structures. Experimentally determined structures are often considered in determining a protein's oligomeric state, but static structures miss the dynamic equilibrium between different quaternary forms. The problem is exacerbated in homo-oligomers, where the oligomeric states are challenging to characterize. Here, we re-evaluated the oligomeric state of 17 different bacterial proteins across a broad range of protein concentrations and solutions by native mass spectrometry (MS), mass photometry (MP), size exclusion chromatography (SEC), and small-angle X-ray scattering (SAXS), finding that most exhibit several oligomeric states. Surprisingly, some proteins did not show mass-action driven equilibrium between the oligomeric states. For approximately half the proteins, the predicted oligomeric forms described in publicly available databases underestimated the complexity of protein quaternary structures in solution. Conversely, AlphaFold multimer provided an accurate description of the potential multimeric states for most proteins, suggesting that it could help resolve uncertainties on the solution state of many proteins.

Modulation of type I interferon responses potently inhibits SARS-CoV-2 replication and inflammation in rhesus macaques.

Type-I interferons (IFN-I) are critical mediators of innate control of viral infections, but also drive recruitment of inflammatory cells to sites of infection, a key feature of severe COVID-19. Here, and for the first time, IFN-I signaling was modulated in rhesus macaques (RMs) prior to and during acute SARS-CoV-2 infection using a mutated IFNα2 (IFN-modulator; IFNmod), which has previously been shown to reduce the binding and signaling of endogenous IFN-I. In SARS-CoV-2-infected RMs, IFNmod reduced both antiviral and inflammatory ISGs. Notably, IFNmod treatment resulted in a potent reduction in (i) SARS-CoV-2 viral load in Bronchoalveolar lavage (BAL), upper airways, lung, and hilar lymph nodes; (ii) inflammatory cytokines, chemokines, and CD163+MRC1-inflammatory macrophages in BAL; and (iii) expression of Siglec-1, which enhances SARS-CoV-2 infection and predicts disease severity, on circulating monocytes. In the lung, IFNmod also reduced pathogenesis and attenuated pathways of inflammasome activation and stress response during acute SARS-CoV-2 infection. This study, using an intervention targeting both IFN-α and IFN-ß pathways, shows that excessive inflammation driven by type 1 IFN critically contributes to SARS-CoV-2 pathogenesis in RMs, and demonstrates the potential of IFNmod to limit viral replication, SARS-CoV-2 induced inflammation, and COVID-19 severity.

A Protein-Engineered, Enhanced Yeast Display Platform for Rapid Evolution of Challenging Targets.

Here, we enhanced the popular yeast display method by multiple rounds of DNA and protein engineering. We introduced surface exposure-tailored reporters, eUnaG2 and DnbALFA, creating a new platform of C and N terminal fusion vectors. The optimization of eUnaG2 resulted in five times brighter fluorescence and 10 °C increased thermostability than UnaG. The optimized DnbALFA has 10-fold the level of expression of the starting protein. Following this, different plasmids were developed to create a complex platform allowing a broad range of protein expression organizations and labeling strategies. Our platform showed up to five times better separation between nonexpressing and expressing cells compared with traditional pCTcon2 and c-myc labeling, allowing for fewer rounds of selection and achieving higher binding affinities. Testing 16 different proteins, the enhanced system showed consistently stronger expression signals over c-myc labeling. In addition to gains in simplicity, speed, and cost-effectiveness, new applications were introduced to monitor protein surface exposure and protein retention in the secretion pathway that enabled successful protein engineering of hard-to-express proteins. As an example, we show how we optimized the WD40 domain of the ATG16L1 protein for yeast surface and soluble bacterial expression, starting from a nonexpressing protein. As a second example, we show how using the here-presented enhanced yeast display method we rapidly selected high-affinity binders toward two protein targets, demonstrating the simplicity of generating new protein-protein interactions. While the methodological changes are incremental, it results in a qualitative enhancement in the applicability of yeast display for many applications.

Line-FRAP, A Versatile Method to Measure Diffusion Rates In Vitro and In Vivo.

The crowded cellular milieu affect molecular diffusion through hard (occluded space) and soft (weak, non-specific) interactions. Multiple methods have been developed to measure diffusion coefficients at physiological protein concentrations within cells, each with its limitations. Here, we show that Line-FRAP, combined with rigours data analysis, is able to determine diffusion coefficients in a variety of environments, from in vitro to in vivo. The use of Line mode greatly improves time resolution of FRAP data acquisition, from 20-100 Hz in the classical mode to 800 Hz in the line mode. This improves data analysis, as intensity and radius of the bleach at the first post-bleach frame is critical. We evaluated the method on different proteins labelled chemically or fused to YFP in a wide range of environments. The diffusion coefficients measured in HeLa and in E. coli were ~2.5-fold and 15-fold slower than in buffer, and were comparable to previously published data. Increasing the osmotic pressure on E. coli further decreases diffusion, to the point at which proteins virtually stop moving. The method presented here, which requires a confocal microscope equipped with dual scanners, can be applied to study a large range of molecules with different sizes, and provides robust results in a wide range of environments and protein concentrations for fast diffusing molecules.

SARS-CoV-2 variant prediction and antiviral drug design are enabled by RBD in vitro evolution.

SARS-CoV-2 variants of interest and concern will continue to emerge for the duration of the COVID-19 pandemic. To map mutations in the receptor-binding domain (RBD) of the spike protein that affect binding to angiotensin-converting enzyme 2 (ACE2), the receptor for SARS-CoV-2, we applied in vitro evolution to affinity-mature the RBD. Multiple rounds of random mutagenic libraries of the RBD were sorted against decreasing concentrations of ACE2, resulting in the selection of higher affinity RBD binders. We found that mutations present in more transmissible viruses (S477N, E484K and N501Y) were preferentially selected in our high-throughput screen. Evolved RBD mutants include prominently the amino acid substitutions found in the RBDs of B.1.620, B.1.1.7 (Alpha), B1.351 (Beta) and P.1 (Gamma) variants. Moreover, the incidence of RBD mutations in the population as presented in the GISAID database (April 2021) is positively correlated with increased binding affinity to ACE2. Further in vitro evolution increased binding by 1,000-fold and identified mutations that may be more infectious if they evolve in the circulating viral population, for example, Q498R is epistatic to N501Y. We show that our high-affinity variant RBD-62 can be used as a drug to inhibit infection with SARS-CoV-2 and variants Alpha, Beta and Gamma in vitro. In a model of SARS-CoV-2 challenge in hamster, RBD-62 significantly reduced clinical disease when administered before or after infection. A 2.9 Å cryo-electron microscopy structure of the high-affinity complex of RBD-62 and ACE2, including all rapidly spreading mutations, provides a structural basis for future drug and vaccine development and for in silico evaluation of known antibodies.

Alternative splicing modulates Kv channel clustering through a molecular ball and chain mechanism.

Ion channel clustering at the post-synaptic density serves a fundamental role in action potential generation and transmission. Here, we show that interaction between the Shaker Kv channel and the PSD-95 scaffold protein underlying channel clustering is modulated by the length of the intrinsically disordered C terminal channel tail. We further show that this tail functions as an entropic clock that times PSD-95 binding. We thus propose a 'ball and chain' mechanism to explain Kv channel binding to scaffold proteins, analogous to the mechanism describing channel fast inactivation. The physiological relevance of this mechanism is demonstrated in that alternative splicing of the Shaker channel gene to produce variants of distinct tail lengths resulted in differential channel cell surface expression levels and clustering metrics that correlate with differences in affinity of the variants for PSD-95. We suggest that modulating channel clustering by specific spatial-temporal spliced variant targeting serves a fundamental role in nervous system development and tuning.