Structure of Simian Immunodeficiency Virus Envelope Spikes Bound with CD4 and Monoclonal Antibody 36D5

Machine Learning Prediction and Phyloanatomic Modeling of Viral Neuroadaptive Signatures in the Macaque Model of HIV-Mediated Neuropathology

In human immunodeficiency virus (HIV) infection, virus replication in and adaptation to the central nervous system (CNS) can result in neurocognitive deficits in approximately 25% of patients with unsuppressed viremia. While no single viral mutation can be agreed upon as distinguishing the neuroadapted population, earlier studies have demonstrated that a machine learning (ML) approach could be applied to identify a collection of mutational signatures within the virus envelope glycoprotein (Gp120) predictive of disease. The S[imian]IV-infected macaque is a widely used animal model of HIV neuropathology, allowing in-depth tissue sampling infeasible for human patients. Yet, translational impact of the ML approach within the context of the macaque model has not been tested, much less the capacity for early prediction in other, noninvasive tissues. We applied the previously described ML approach to prediction of SIV-mediated encephalitis (SIVE) using gp120 sequences obtained from the CNS of animals with and without SIVE with 97% accuracy. The presence of SIVE signatures at earlier time points of infection in non-CNS tissues indicated these signatures cannot be used in a clinical setting; however, combined with protein structural mapping and statistical phylogenetic inference, results revealed common denominators associated with these signatures, including 2-acetamido-2-deoxy-beta-d-glucopyranose structural interactions and high rate of alveolar macrophage (AM) infection. AMs were also determined to be the phyloanatomic source of cranial virus in SIVE animals, but not in animals that did not develop SIVE, implicating a role for these cells in the evolution of the signatures identified as predictive of both HIV and SIV neuropathology. IMPORTANCE HIV-associated neurocognitive disorders remain prevalent among persons living with HIV (PLWH) owing to our limited understanding of the contributing viral mechanisms and ability to predict disease onset. We have expanded on a machine learning method previously used on HIV genetic sequence data to predict neurocognitive impairment in PLWH to the more extensively sampled SIV-infected macaque model in order to (i) determine the translatability of the animal model and (ii) more accurately characterize the predictive capacity of the method. We identified eight amino acid and/or biochemical signatures in the SIV envelope glycoprotein, the most predominant of which demonstrated the potential for aminoglycan interaction characteristic of previously identified HIV signatures. These signatures were not isolated to specific points in time or to the central nervous system, limiting their use as an accurate clinical predictor of neuropathogenesis; however, statistical phylogenetic and signature pattern analyses implicate the lungs as a key player in the emergence of neuroadapted viruses.

Adeno-Associated Virus Receptor-Binding: Flexible Domains and Alternative Conformations through Cryo-Electron Tomography of Adeno-Associated Virus 2 (AAV2) and AAV5 Complexes

Recombinant forms of adeno-associated virus (rAAV) are vectors of choice in the development of treatments for a number of genetic dispositions. Greater understanding of AAV’s molecular virology is needed to underpin needed improvements in efficiency and specificity. Recent advances have included identification of a near-universal entry receptor, AAVR, and structures detected by cryo-electron microscopy (EM) single particle analysis (SPA) that revealed, at high resolution, only the domains of AAVR most tightly bound to AAV. Here, cryogenic electron tomography (cryo-ET) is applied to reveal the neighboring domains of the flexible receptor. For AAV5, where the PKD1 domain is bound strongly, PKD2 is seen in three configurations extending away from the virus. AAV2 binds tightly to the PKD2 domain at a distinct site, and cryo-ET now reveals four configurations of PKD1, all different from that seen in AAV5. The AAV2 receptor complex also shows unmodeled features on the inner surface that appear to be an equilibrium alternate configuration. Other AAV structures start near the 5-fold axis, but now β-strand A is the minor conformer and, for the major conformer, partially ordered N termini near the 2-fold axis join the canonical capsid jellyroll fold at the βA-βB turn. The addition of cryo-ET is revealing unappreciated complexity that is likely relevant to viral entry and to the development of improved gene therapy vectors.

IMPORTANCE With 150 clinical trials for 30 diseases under way, AAV is a leading gene therapy vector. Immunotoxicity at high doses used to overcome inefficient transduction has occasionally proven fatal and highlighted gaps in fundamental virology. AAV enters cells, interacting through distinct sites with different domains of the AAVR receptor, according to AAV clade. Single domains are resolved in structures by cryogenic electron microscopy. Here, the adjoining domains are revealed by cryo-electron tomography of AAV2 and AAV5 complexes. They are in flexible configurations interacting minimally with AAV, despite measurable dependence of AAV2 transduction on both domains.

Potential neutralizing antibodies discovered for novel corona virus using machine learning

The fast and untraceable virus mutations take lives of thousands of people before the immune system can produce the inhibitory antibody. The recent outbreak of COVID-19 infected and killed thousands of people in the world. Rapid methods in finding peptides or antibody sequences that can inhibit the viral epitopes of SARS-CoV-2 will save the life of thousands. To predict neutralizing antibodies for SARS-CoV-2 in a high-throughput manner, in this paper, we use different machine learning (ML) model to predict the possible inhibitory synthetic antibodies for SARS-CoV-2. We collected 1933 virus-antibody sequences and their clinical patient neutralization response and trained an ML model to predict the antibody response. Using graph featurization with variety of ML methods, like XGBoost, Random Forest, Multilayered Perceptron, Support Vector Machine and Logistic Regression, we screened thousands of hypothetical antibody sequences and found nine stable antibodies that potentially inhibit SARS-CoV-2. We combined bioinformatics, structural biology, and Molecular Dynamics (MD) simulations to verify the stability of the candidate antibodies that can inhibit SARS-CoV-2.

Potential neutralizing antibodies discovered for novel corona virus using machine learning

The fast and untraceable virus mutations take lives of thousands of people before the immune system can produce the inhibitory antibody. The recent outbreak of COVID-19 infected and killed thousands of people in the world. Rapid methods in finding peptides or antibody sequences that can inhibit the viral epitopes of SARS-CoV-2 will save the life of thousands. To predict neutralizing antibodies for SARS-CoV-2 in a high-throughput manner, in this paper, we use different machine learning (ML) model to predict the possible inhibitory synthetic antibodies for SARS-CoV-2. We collected 1933 virus-antibody sequences and their clinical patient neutralization response and trained an ML model to predict the antibody response. Using graph featurization with variety of ML methods, like XGBoost, Random Forest, Multilayered Perceptron, Support Vector Machine and Logistic Regression, we screened thousands of hypothetical antibody sequences and found nine stable antibodies that potentially inhibit SARS-CoV-2. We combined bioinformatics, structural biology, and Molecular Dynamics (MD) simulations to verify the stability of the candidate antibodies that can inhibit SARS-CoV-2.

Segmentation by classification: A novel and reliable approach for semi-automatic selection of HIV/SIV envelope spikes

We describe a semiautomated approach to segment Env spikes from the membrane envelope of Simian Immunodeficiency Virus visualized by cryoelectron tomography of frozen-hydrated specimens. Multivariate data analysis is applied to a large set of overlapping subvolumes extracted semiautomatically from the viral envelope and does not utilize a template of the target structure. The major manual step used in the method involves determination of six points that define an ellipsoid approximating the virion shape. The approach is robust to departures of the actual virion from this starting ellipsoid. A point cage of sufficient density is generated to ensure that any spike-like protein is identified multiple times. Subsequently translational alignment of class averages to a cylindrical reference on a curved surface separates subvolumes with spikes from those without. Spike containing subvolumes identified multiple times are removed by proximity analysis. Slightly different procedures segment spikes in the equatorial and the polar regions. Once all spikes are segmented, further alignment of class averages using separately the polar and spin angles produces recognizable spike images. Our approach localized 96% of the equatorial spikes and 85% of all spikes identified manually; it identifies a significant number of additional spikes missed by manual selection. Two types of spike shapes were segmented, one with near 3-fold symmetry resembling the conventional spike, the other had a T-shape resembling the spike structure obtained when antibodies such as PG9 bind to HIV Env. The approach should be applicable to segmentation of any protein spikes extending from a cellular or virion envelope.

Isolation and Structure of an Antibody that Fully Neutralizes Isolate SIVmac239 Reveals Functional Similarity of SIV and HIV Glycan Shields

HIV- and SIV-envelope (Env) trimers are both extensively glycosylated, and antibodies identified to date have been unable to fully neutralize SIV_mac239. Here, we report the isolation, structure, and glycan interactions of antibody ITS90.03, a monoclonal antibody that completely neutralized the highly neutralization-resistant isolate, SIV_mac239. The co-crystal structure of a fully glycosylated SIV_mac239-gp120 core in complex with rhesus CD4 and the antigen-binding fragment of ITS90.03 at 2.5-Å resolution revealed that ITS90 recognized an epitope comprised of 45% glycan. SIV-gp120 core, rhesus CD4, and their complex could each be aligned structurally to their human counterparts. The structure revealed that glycans masked most of the SIV Env protein surface, with ITS90 targeting a glycan hole, which is occupied in ∼83% of SIV strains by glycan N238. Overall, the SIV glycan shield appears to functionally resemble its HIV counterpart in coverage of spike, shielding from antibody, and modulation of receptor accessibility.

HIV-1 Env trimer opens through an asymmetric intermediate in which individual protomers adopt distinct conformations

HIV-1 entry into cells requires binding of the viral envelope glycoprotein (Env) to receptor CD4 and coreceptor. Imaging of individual Env molecules on native virions shows Env trimers to be dynamic, spontaneously transitioning between three distinct well-populated conformational states: a pre-triggered Env (State 1), a default intermediate (State 2) and a three-CD4-bound conformation (State 3), which can be stabilized by binding of CD4 and coreceptor-surrogate antibody 17b. Here, using single-molecule Fluorescence Resonance Energy Transfer (smFRET), we show the default intermediate configuration to be asymmetric, with individual protomers adopting distinct conformations. During entry, this asymmetric intermediate forms when a single CD4 molecule engages the trimer. The trimer can then transition to State 3 by binding additional CD4 molecules and coreceptor.

Truncating the gp41 Cytoplasmic Tail of Simian Immunodeficiency Virus Decreases Sensitivity to Neutralizing Antibodies without Increasing the Envelope Content of Virions

An incomplete understanding of native human immunodeficiency virus (HIV) and simian immunodeficiency virus (SIV) envelope glycoproteins (Envs) impedes the development of structural models of Env and vaccine design. This shortcoming is due in part to the low number of Env trimers on virus particles. For SIV, this low expression level can be counteracted by truncating the cytoplasmic tail (CT) of Env. CT truncation has been shown to increase Env incorporation into the virion and is commonly used in vaccine and imaging studies, but its effects on viral antigenicity have not been fully elucidated. To study the effects of a CT truncation of Env in viruses in similar genetic contexts, we introduced stop codons into the CT of a SIVsmE660 molecular clone and two neutralizing antibody (NAb) escape variants. These viruses shared 98% sequence identity in Env but were characterized as either tier 1 (sensitive to neutralization), tier 2 (moderately resistant to neutralization), or tier 3 (resistant to neutralization). However, the introduction of premature stop codons in Env at position Q741/Q742 converted all three transfection-derived viruses to a tier 3-like phenotype, and these viruses were uniformly resistant to neutralization by sera from infected macaques and monoclonal antibodies (MAbs). These changes in neutralization sensitivity were not accompanied by an increase in either the virion Env content of infection-derived viruses or the infectivity of transfection-derived viruses in human cells, suggesting that CT mutations may result in global changes to the Env conformation. Our results demonstrate that some CT truncations can affect viral antigenicity and, as such, may not be suitable surrogate models of native HIV/SIV Env.IMPORTANCE Modifications to the SIV envelope protein (Env) are commonly used in structural and vaccine studies to stabilize and increase the expression of Env, often without consideration of effects on antigenicity. One such widespread modification is the truncation of the Env C-terminal tail. Here, we studied the effects of a particular cytoplasmic tail truncation in three SIVsm strains that have highly similar Env sequences but exhibit different sensitivities to neutralizing antibodies. After truncation of the Env CT, these viruses were all very resistant to neutralization by sera from infected macaques and monoclonal antibodies. The viruses with a truncated Env CT also did not exhibit the desired and typical increase in Env expression. These results underscore the importance of carefully evaluating the use of truncated Env as a model in HIV/SIV vaccine and imaging studies and of the continued need to find better models of native Env that contain fewer modifications.