Predictable fold switching by the SARS‐CoV‐2 protein ORF9b

Extant fold‐switching proteins remodel their secondary structures and change their functions in response to environmental stimuli. These shapeshifting proteins regulate biological processes and are associated with a number of diseases, including tuberculosis, cancer, Alzheimer''s, and autoimmune disorders. Thus, predictive methods are needed to identify more fold‐switching proteins, especially since all naturally occurring instances have been discovered by chance. In response to this need, two high‐throughput predictive methods have recently been developed. Here we test them on ORF9b, a newly discovered fold switcher and potential therapeutic target from the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS‐CoV‐2). Promisingly, both methods correctly indicate that ORF9b switches folds. We then tested the same two methods on ORF9b1, the ORF9b homolog from SARS‐CoV‐1. Again, both methods predict that ORF9b1 switches folds, a finding consistent with experimental binding studies. Together, these results (a) demonstrate that protein fold switching can be predicted using high‐throughput computational approaches and (b) suggest that fold switching might be a general characteristic of ORF9b homologs.     

PDBsum extras: SARS‐CoV‐2 and AlphaFold models

The PDBsum web server provides structural analyses of the entries in the Protein Data Bank (PDB). Two recent additions are described here. The first is the detailed analysis of the SARS‐CoV‐2 virus protein structures in the PDB. These include the variants of concern, which are shown both on the sequences and 3D structures of the proteins. The second addition is the inclusion of the available AlphaFold models for human proteins. The pages allow a search of the protein against existing structures in the PDB via the Sequence Annotated by Structure (SAS) server, so one can easily compare the predicted model against experimentally determined structures. The server is freely accessible to all at http://www.ebi.ac.uk/pdbsum.     

Selective cross‐linking of coinciding protein assemblies by in‐gel cross‐linking mass spectrometry

Cross‐linking mass spectrometry has developed into an important method to study protein structures and interactions. The in‐solution cross‐linking workflows involve time and sample consuming steps and do not provide sensible solutions for differentiating cross‐links obtained from co‐occurring protein oligomers, complexes, or conformers. Here we developed a cross‐linking workflow combining blue native PAGE with in‐gel cross‐linking mass spectrometry (IGX‐MS). This workflow circumvents steps, such as buffer exchange and cross‐linker concentration optimization. Additionally, IGX‐MS enables the parallel analysis of co‐occurring protein complexes using only small amounts of sample. Another benefit of IGX‐MS, demonstrated by experiments on GroEL and purified bovine heart mitochondria, is the substantial reduction of undesired over‐length cross‐links compared to in‐solution cross‐linking. We next used IGX‐MS to investigate the complement components C5, C6, and their hetero‐dimeric C5b6 complex. The obtained cross‐links were used to generate a refined structural model of the complement component C6, resembling C6 in its inactivated state. This finding shows that IGX‐MS can provide new insights into the initial stages of the terminal complement pathway.     

Tensor‐structured decomposition improves systems serology analysis

Systems serology provides a broad view of humoral immunity by profiling both the antigen‐binding and Fc properties of antibodies. These studies contain structured biophysical profiling across disease‐relevant antigen targets, alongside additional measurements made for single antigens or in an antigen‐generic manner. Identifying patterns in these measurements helps guide vaccine and therapeutic antibody development, improve our understanding of diseases, and discover conserved regulatory mechanisms. Here, we report that coupled matrix–tensor factorization (CMTF) can reduce these data into consistent patterns by recognizing the intrinsic structure of these data. We use measurements from two previous studies of HIV‐ and SARS‐CoV‐2‐infected subjects as examples. CMTF outperforms standard methods like principal components analysis in the extent of data reduction while maintaining equivalent prediction of immune functional responses and disease status. Under CMTF, model interpretation improves through effective data reduction, separation of the Fc and antigen‐binding effects, and recognition of consistent patterns across individual measurements. Data reduction also helps make prediction models more replicable. Therefore, we propose that CMTF is an effective general strategy for data exploration in systems serology.     

Improved coarse‐grained model for studying sequence dependent phase separation of disordered proteins

We present improvements to the hydropathy scale (HPS) coarse‐grained (CG) model for simulating sequence‐specific behavior of intrinsically disordered proteins (IDPs), including their liquid–liquid phase separation (LLPS). The previous model based on an atomistic hydropathy scale by Kapcha and Rossky (KR scale) is not able to capture some well‐known LLPS trends such as reduced phase separation propensity upon mutations (R‐to‐K and Y‐to‐F). Here, we propose to use the Urry hydropathy scale instead, which was derived from the inverse temperature transitions in a model polypeptide with guest residues X. We introduce two free parameters to shift (Δ) and scale (µ) the overall interaction strengths for the new model (HPS‐Urry) and use the experimental radius of gyration for a diverse group of IDPs to find their optimal values. Interestingly, many possible (Δ, µ) combinations can be used for typical IDPs, but the phase behavior of a low‐complexity (LC) sequence FUS is only well described by one of these models, which highlights the need for a careful validation strategy based on multiple proteins. The CG HPS‐Urry model should enable accurate simulations of protein LLPS and provide a microscopically detailed view of molecular interactions.     

An organoid‐derived bronchioalveolar model for SARS‐CoV‐2 infection of human alveolar type II‐like cells

Severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) causes coronavirus disease 2019 (COVID‐19), which may result in acute respiratory distress syndrome (ARDS), multiorgan failure, and death. The alveolar epithelium is a major target of the virus, but representative models to study virus host interactions in more detail are currently lacking. Here, we describe a human 2D air–liquid interface culture system which was characterized by confocal and electron microscopy and single‐cell mRNA expression analysis. In this model, alveolar cells, but also basal cells and rare neuroendocrine cells, are grown from 3D self‐renewing fetal lung bud tip organoids. These cultures were readily infected by SARS‐CoV‐2 with mainly surfactant protein C‐positive alveolar type II‐like cells being targeted. Consequently, significant viral titers were detected and mRNA expression analysis revealed induction of type I/III interferon response program. Treatment of these cultures with a low dose of interferon lambda 1 reduced viral replication. Hence, these cultures represent an experimental model for SARS‐CoV‐2 infection and can be applied for drug screens.     

Underwater photogrammetry for close‐range 3D imaging of dry‐sensitive objects: The case study of cephalopod beaks

• Technical advances in 3D imaging have contributed to quantifying and understanding biological variability and complexity. However, small, dry‐sensitive objects are not easy to reconstruct using common and easily available techniques such as photogrammetry, surface scanning, or micro‐CT scanning. Here, we use cephalopod beaks as an example as their size, thickness, transparency, and dry‐sensitive nature make them particularly challenging. We developed a new, underwater, photogrammetry protocol in order to add these types of biological structures to the panel of photogrammetric possibilities.
• We used a camera with a macrophotography mode in a waterproof housing fixed in a tank with clear water. The beak was painted and fixed on a colored rotating support. Three angles of view, two acquisitions, and around 300 pictures per specimen were taken in order to reconstruct a full 3D model. These models were compared with others obtained with micro‐CT scanning to verify their accuracy.
• The models can be obtained quickly and cheaply compared with micro‐CT scanning and have sufficient precision for quantitative interspecific morphological analyses. Our work shows that underwater photogrammetry is a fast, noninvasive, efficient, and accurate way to reconstruct 3D models of dry‐sensitive objects while conserving their shape. While the reconstruction of the shape is accurate, some internal parts cannot be reconstructed with photogrammetry as they are not visible. In contrast, these structures are visible using reconstructions based on micro‐CT scanning. The mean difference between both methods is very small (10⁻⁵ to 10⁻⁴ mm) and is significantly lower than differences between meshes of different individuals.
• This photogrammetry protocol is portable, easy‐to‐use, fast, and reproducible. Micro‐CT scanning, in contrast, is time‐consuming, expensive, and nonportable. This protocol can be applied to reconstruct the 3D shape of many other dry‐sensitive objects such as shells of shellfish, cartilage, plants, and other chitinous materials.

     

Concordant geographic and genetic structure revealed by genotyping‐by‐sequencing in a New Zealand marine isopod

Population genetic structure in the marine environment can be influenced by life‐history traits such as developmental mode (biphasic, with distinct adult and larval morphology, and direct development, in which larvae resemble adults) or habitat specificity, as well as geography and selection. Developmental mode is thought to significantly influence dispersal, with direct developers expected to have much lower dispersal potential. However, this prediction can be complicated by the presence of geophysical barriers to dispersal. In this study, we use a panel of 8,020 SNPs to investigate population structure and biogeography over multiple spatial scales for a direct‐developing species, the New Zealand endemic marine isopod Isocladus armatus. Because our sampling range is intersected by two well‐known biogeographic barriers (the East Cape and the Cook Strait), our study provides an opportunity to understand how such barriers influence dispersal in direct developers. On a small spatial scale (20 km), gene flow between locations is extremely high, suggestive of an island model of migration. However, over larger spatial scales (600 km), populations exhibit a clear pattern of isolation‐by‐distance. Our results indicate that I. armatus exhibits significant migration across the hypothesized barriers and suggest that large‐scale ocean currents associated with these locations do not present a barrier to dispersal. Interestingly, we find evidence of a north‐south population genetic break occurring between Māhia and Wellington. While no known geophysical barrier is apparent in this area, it coincides with the location of a proposed border between bioregions. Analysis of loci under selection revealed that both isolation‐by‐distance and adaption may be contributing to the degree of population structure we have observed here. We conclude that developmental life history largely predicts dispersal in the intertidal isopod I. armatus. However, localized biogeographic processes can disrupt this expectation, and this may explain the potential meta‐population detected in the Auckland region.     

Machine learning identifies molecular regulators and therapeutics for targeting SARS‐CoV2‐induced cytokine release

Although 15–20% of COVID‐19 patients experience hyper‐inflammation induced by massive cytokine production, cellular triggers of this process and strategies to target them remain poorly understood. Here, we show that the N‐terminal domain (NTD) of the SARS‐CoV‐2 spike protein substantially induces multiple inflammatory molecules in myeloid cells and human PBMCs. Using a combination of phenotypic screening with machine learning‐based modeling, we identified and experimentally validated several protein kinases, including JAK1, EPHA7, IRAK1, MAPK12, and MAP3K8, as essential downstream mediators of NTD‐induced cytokine production, implicating the role of multiple signaling pathways in cytokine release. Further, we found several FDA‐approved drugs, including ponatinib, and cobimetinib as potent inhibitors of the NTD‐mediated cytokine release. Treatment with ponatinib outperforms other drugs, including dexamethasone and baricitinib, inhibiting all cytokines in response to the NTD from SARS‐CoV‐2 and emerging variants. Finally, ponatinib treatment inhibits lipopolysaccharide‐mediated cytokine release in myeloid cells in vitro and lung inflammation mouse model. Together, we propose that agents targeting multiple kinases required for SARS‐CoV‐2‐mediated cytokine release, such as ponatinib, may represent an attractive therapeutic option for treating moderate to severe COVID‐19.     

Insulin binding to the analytical antibody sandwich pair OXI‐005 and HUI‐018: Epitope mapping and binding properties

The insulin epitopes for two monoclonal antibodies (mAbs), OXI‐005 and HUI‐018, commonly used in combination for insulin concentration determination in sandwich assays, were determined using X‐ray crystallography. The crystal structure of the HUI‐018 Fab in complex with human insulin (HI) was determined and OXI‐005 Fab crystal structures were determined in complex with HI and porcine insulin (PI) as well as on its own. The OXI‐005 epitope comprises insulin residues 1,3,4,19–21 (A‐chain) and 25–30 (B‐chain) and for HUI‐018 residues 7,8,10–14,17 (A‐chain) and 5–7, 10, 14 (B‐chain). The areas of insulin involved in interactions with the mAb are 20% (OXI‐005) and 24% (HUI‐018) of the total insulin surface. Based on the Fab complex crystal structures with the insulins a molecular model for simultaneous binding of the Fabs to PI was built and this model was validated by small angle X‐ray scattering measurements for the ternary complex. The epitopes for the mAbs on insulin were found well separated from each other as expected from luminiscent oxygen channeling immunoassay results for different insulins (HI, PI, bovine insulin, DesB30 HI, insulin glargine, insulin lispro). The affinities of the OXI‐005 and HUI‐018 Fabs for HI, PI, and DesB30 HI were determined using surface plasmon resonance. The K _Ds were found to be in the range of 1–4 nM for the HUI‐018 Fab, while more different for the OXI‐005 Fab (50 nM for HI, 20 nM for PI and 400 nM for DesB30 HI) supporting the importance of residue B30 for binding to OXI‐005.     

Genome‐scale metabolic modeling reveals SARS‐CoV‐2‐induced metabolic changes and antiviral targets

Tremendous progress has been made to control the COVID‐19 pandemic caused by the SARS‐CoV‐2 virus. However, effective therapeutic options are still rare. Drug repurposing and combination represent practical strategies to address this urgent unmet medical need. Viruses, including coronaviruses, are known to hijack host metabolism to facilitate viral proliferation, making targeting host metabolism a promising antiviral approach. Here, we describe an integrated analysis of 12 published in vitro and human patient gene expression datasets on SARS‐CoV‐2 infection using genome‐scale metabolic modeling (GEM), revealing complicated host metabolism reprogramming during SARS‐CoV‐2 infection. We next applied the GEM‐based metabolic transformation algorithm to predict anti‐SARS‐CoV‐2 targets that counteract the virus‐induced metabolic changes. We successfully validated these targets using published drug and genetic screen data and by performing an siRNA assay in Caco‐2 cells. Further generating and analyzing RNA‐sequencing data of remdesivir‐treated Vero E6 cell samples, we predicted metabolic targets acting in combination with remdesivir, an approved anti‐SARS‐CoV‐2 drug. Our study provides clinical data‐supported candidate anti‐SARS‐CoV‐2 targets for future evaluation, demonstrating host metabolism targeting as a promising antiviral strategy.     

Cryo‐EM structure of the CENP‐A nucleosome in complex with phosphorylated CENP‐C

The CENP‐A nucleosome is a key structure for kinetochore assembly. Once the CENP‐A nucleosome is established in the centromere, additional proteins recognize the CENP‐A nucleosome to form a kinetochore. CENP‐C and CENP‐N are CENP‐A binding proteins. We previously demonstrated that vertebrate CENP‐C binding to the CENP‐A nucleosome is regulated by CDK1‐mediated CENP‐C phosphorylation. However, it is still unknown how the phosphorylation of CENP‐C regulates its binding to CENP‐A. It is also not completely understood how and whether CENP‐C and CENP‐N act together on the CENP‐A nucleosome. Here, using cryo‐electron microscopy (cryo‐EM) in combination with biochemical approaches, we reveal a stable CENP‐A nucleosome‐binding mode of CENP‐C through unique regions. The chicken CENP‐C structure bound to the CENP‐A nucleosome is stabilized by an intramolecular link through the phosphorylated CENP‐C residue. The stable CENP‐A‐CENP‐C complex excludes CENP‐N from the CENP‐A nucleosome. These findings provide mechanistic insights into the dynamic kinetochore assembly regulated by CDK1‐mediated CENP‐C phosphorylation.     

Purification and characterization of the receptor‐binding domain of SARS‐CoV‐2 spike protein from Escherichia coli

SARS‐CoV‐2 is responsible for a disruptive worldwide viral pandemic, and renders a severe respiratory disease known as COVID‐19. Spike protein of SARS‐CoV‐2 mediates viral entry into host cells by binding ACE2 through the receptor‐binding domain (RBD). RBD is an important target for development of virus inhibitors, neutralizing antibodies, and vaccines. RBD expressed in mammalian cells suffers from low expression yield and high cost. E. coli is a popular host for protein expression, which has the advantage of easy scalability with low cost. However, RBD expressed by E. coli (RBD‐1) lacks the glycosylation, and its antigenic epitopes may not be sufficiently exposed. In the present study, RBD‐1 was expressed by E. coli and purified by a Ni Sepharose Fast Flow column. RBD‐1 was structurally characterized and compared with RBD expressed by the HEK293 cells (RBD‐2). The secondary structure and tertiary structure of RBD‐1 were largely maintained without glycosylation. In particular, the major β‐sheet content of RBD‐1 was almost unaltered. RBD‐1 could strongly bind ACE2 with a dissociation constant (K_D) of 2.98 × 10^–8 M. Thus, RBD‐1 was expected to apply in the vaccine development, screening drugs and virus test kit.     

Interleukin‐37 improves T‐cell‐mediated immunity and chimeric antigen receptor T‐cell therapy in aged backgrounds

Aging‐associated declines in innate and adaptive immune responses are well documented and pose a risk for the growing aging population, which is predicted to comprise greater than 40 percent of the world''s population by 2050. Efforts have been made to improve immunity in aged populations; however, safe and effective protocols to accomplish this goal have not been universally established. Aging‐associated chronic inflammation is postulated to compromise immunity in aged mice and humans. Interleukin‐37 (IL‐37) is a potent anti‐inflammatory cytokine, and we present data demonstrating that IL‐37 gene expression levels in human monocytes significantly decline with age. Furthermore, we demonstrate that transgenic expression of interleukin‐37 (IL‐37) in aged mice reduces or prevents aging‐associated chronic inflammation, splenomegaly, and accumulation of myeloid cells (macrophages and dendritic cells) in the bone marrow and spleen. Additionally, we show that IL‐37 expression decreases the surface expression of programmed cell death protein 1 (PD‐1) and augments cytokine production from aged T‐cells. Improved T‐cell function coincided with a youthful restoration of Pdcd1, Lat, and Stat4 gene expression levels in CD4⁺ T‐cells and Lat in CD8⁺ T‐cells when aged mice were treated with recombinant IL‐37 (rIL‐37) but not control immunoglobin (Control Ig). Importantly, IL‐37‐mediated rejuvenation of aged endogenous T‐cells was also observed in aged chimeric antigen receptor (CAR) T‐cells, where improved function significantly extended the survival of mice transplanted with leukemia cells. Collectively, these data demonstrate the potency of IL‐37 in boosting the function of aged T‐cells and highlight its therapeutic potential to overcome aging‐associated immunosenescence.     

Water‐mediated interactions destabilize proteins

Proteins are folded to avoid exposure of the nonpolar groups to water because water‐mediated interactions between nonpolar groups are a promising factor in the thermodynamic stabilities of proteins—which is a well‐accepted view as one of the unique effects of hydrophobic interactions. This article poses a critical question for this classical view by conducting an accurate solvation free‐energy calculation for a thermodynamic cycle of a protein folding using a liquid‐state density functional theory. Here, the solvation‐free energy for a leucine zipper formation was examined in the coiled‐coil protein GCN4‐p1, a typical model for hydrophobic interactions, which demonstrated that water‐mediated interactions were unfavorable for the association of nonpolar groups in the native state, while the dispersion forces between them were, instead, responsible for the association. Furthermore, the present analysis well predicted the isolated helical state stabilized by pressure, which was previously observed in an experiment. We reviewed the problems in the classical concept and semiempirical presumption that the energetic cost of the hydration of nonpolar groups is a driving force of folding.     

SARS‐CoV‐2 structural coverage map reveals viral protein assembly,mimicry, and hijacking mechanisms

We modeled 3D structures of all SARS‐CoV‐2 proteins, generating 2,060 models that span 69% of the viral proteome and provide details not available elsewhere. We found that ˜6% of the proteome mimicked human proteins, while ˜7% was implicated in hijacking mechanisms that reverse post‐translational modifications, block host translation, and disable host defenses; a further ˜29% self‐assembled into heteromeric states that provided insight into how the viral replication and translation complex forms. To make these 3D models more accessible, we devised a structural coverage map, a novel visualization method to show what is—and is not—known about the 3D structure of the viral proteome. We integrated the coverage map into an accompanying online resource (https://aquaria.ws/covid) that can be used to find and explore models corresponding to the 79 structural states identified in this work. The resulting Aquaria‐COVID resource helps scientists use emerging structural data to understand the mechanisms underlying coronavirus infection and draws attention to the 31% of the viral proteome that remains structurally unknown or dark.     

The atomic portrait of SARS‐CoV‐2 as captured by cryo‐electron microscopy

Transmission electron microscopy has historically been indispensable for virology research, as it offers unique insight into virus function. In the past decade, as cryo‐electron microscopy (cryo‐EM) has matured and become more accessible, we have been able to peer into the structure of viruses at the atomic level and understand how they interact with the host cell, with drugs or with antibodies. Perhaps, there was no time in recent history where cryo‐EM was more needed, as SARS‐CoV‐2 has spread around the globe, causing millions of deaths and almost unquantifiable economic devastation. In this concise review, we aim to mark the most important contributions of cryo‐EM to understanding the structure and function of SARS‐CoV‐2 proteins, from surface spikes to the virus core and from virus‐receptor interactions to antibody binding.     

Protein Data Bank Japan: Celebrating our 20th anniversary during a global pandemic as the Asian hub of three dimensional macromolecular structural data

Protein Data Bank Japan (PDBj), a founding member of the worldwide Protein Data Bank (wwPDB) has accepted, processed and distributed experimentally determined biological macromolecular structures for 20 years. During that time, we have continuously made major improvements to our query search interface of PDBj Mine 2, the BMRBj web interface, and EM Navigator for PDB/BMRB/EMDB entries. PDBj also serves PDB‐related secondary database data, original web‐based modeling services such as Homology modeling of complex structure (HOMCOS), visualization services and utility tools, which we have continuously enhanced and expanded throughout the years. In addition, we have recently developed several unique archives, BSM‐Arc for computational structure models, and XRDa for raw X‐ray diffraction images, both of which promote open science in the structural biology community. During the COVID‐19 pandemic, PDBj has also started to provide feature pages for COVID‐19 related entries across all available archives at PDBj from raw experimental data and PDB structural data to computationally predicted models, while also providing COVID‐19 outreach content for high school students and teachers.     

Disease‐linked TDP‐43 hyperphosphorylation suppresses TDP‐43 condensation and aggregation

Post‐translational modifications (PTMs) have emerged as key modulators of protein phase separation and have been linked to protein aggregation in neurodegenerative disorders. The major aggregating protein in amyotrophic lateral sclerosis and frontotemporal dementia, the RNA‐binding protein TAR DNA‐binding protein (TDP‐43), is hyperphosphorylated in disease on several C‐terminal serine residues, a process generally believed to promote TDP‐43 aggregation. Here, we however find that Casein kinase 1δ‐mediated TDP‐43 hyperphosphorylation or C‐terminal phosphomimetic mutations reduce TDP‐43 phase separation and aggregation, and instead render TDP‐43 condensates more liquid‐like and dynamic. Multi‐scale molecular dynamics simulations reveal reduced homotypic interactions of TDP‐43 low‐complexity domains through enhanced solvation of phosphomimetic residues. Cellular experiments show that phosphomimetic substitutions do not affect nuclear import or RNA regulatory functions of TDP‐43, but suppress accumulation of TDP‐43 in membrane‐less organelles and promote its solubility in neurons. We speculate that TDP‐43 hyperphosphorylation may be a protective cellular response to counteract TDP‐43 aggregation.