Biology subjects

Yang, Z.

Publications and source records attributed to Yang, Z..

At least 397 records · Page 22Linked to original sources

bioRxiv2022

Reactivation of memory-encoding dentate gyrus neurons during memory consolidation is associated with subregion-specific, learning- and sleep-mediated biosynthetic changes

Post-learning sleep is essential for hippocampal memory processing, including contextual fear memory (CFM) consolidation. We used targeted recombination in activated populations (TRAP) to label context-encoding engram neurons in the hippocampal dentate gyrus (DG) and assessed reactivation of these neurons after fear learning. Post-learning sleep deprivation (SD), which impairs CFM consolidation, selectively disrupted reactivation of inferior blade DG engram neurons. This change was linked to more general suppression of neuronal activity markers in the inferior, but not superior, DG blade by SD. To further characterize how learning and subsequent sleep or SD affect these (and other) hippocampal subregions, we used subregion-specific spatial profiling of transcripts and proteins. We found that transcriptomic responses to sleep loss differed greatly between hippocampal regions CA1, CA3, and DG inferior blade, superior blade, and hilus - with activity-driven transcripts, and those associated with cytoskeletal remodeling, selectively suppressed in the inferior blade. Critically, learning-driven transcriptomic changes, measured 6 h following contextual fear learning, were limited to the two DG blades, differed dramatically between the blades, and were absent from all other regions. These changes suggested an increase in glutamatergic receptor signaling, and a decrease in GABA receptor signaling, during CFM consolidation. Protein abundance across hippocampal subregions was also differentially impacted by learning and sleep, with most alterations to protein expression restricted to DG. Together, these data suggest that the DG is critical for sleep-dependent memory consolidation, and that the effects of sleep loss on the hippocampus are highly subregion-specific, even within the DG itself.

neuroscience↗

bioRxiv2022

MdrDB: Mutation-induced drug resistance DataBase

AO_SCPLOWBSTRACTC_SCPLOWMutation-induced drug resistance - where the efficacy of drugs is diminished by structural changes in proteins - presents a significant challenge to drug development and the clinical treatment of disease. Understanding the effects of mutation on protein-ligand binding affinities is a key step in developing more effective drugs and therapies, but as a research community we are currently hindered by the lack of a comprehensive database of relevant information. To address this issue, we have developed MdrDB, a database of information related to changes in protein-ligand affinity caused by mutations in protein structure. MdrDB combines data from seven publicly available datasets with calculated biochemical features, as well as 3D structures computed with PyMOL and AlphaFold 2.0, to form the largest database of its kind. With 3D structural information provided for all samples, MdrDB was specifically created to have the size, breadth, and complexity to be useful for practical protein mutation studies and drug resistance modeling. The database brings together wild type and mutant protein-ligand complexes, binding affinity changes upon mutation ({Delta}{Delta}G), and biochemical features calculated from complexes to advance our understanding of mutation-induced drug resistance, the development of combination therapies, and the discovery of novel chemicals. In total, MdrDB contains 100,537 samples generated from 240 proteins (5,119 total PDB structures), 2,503 mutations, and 440 drugs. Of the total samples, 95,971 are based on available PDB structures, with the remaining 4,566 based on AlphaFold 2.0 predicted structures.

bioinformatics↗

bioRxiv2022

Macaque Brainnetome Atlas with Fine-grained Parcellations and Reliable Connections

The rhesus macaque (Macaca mulatta) is a crucial experimental animal that shares many genetic, brain organizational, and behavioral characteristics with humans. A macaque brain atlas that identifies anatomically and functionally distinct regions is fundamental to biomedical and evolutionary research. However, even though connectivity information is vital for understanding brain functions, a connectivity-based whole-brain atlas of the macaque has not previously been made. In this study, we created a new whole-brain map, the Macaque Brainnetome Atlas (MacBNA), based on the anatomical connectivity profiles provided by high angular and spatial resolution ex vivo diffusion MRI data. The new atlas consists of 248 cortical and 56 subcortical regions as well as their structural and functional connections. The parcellation and the diffusion-based tractography were comprehensively evaluated with multi-contrast MRI, invasive neuronal-tracing, and Nissl-stained images collected from a single subject and with open-access datasets from other cohorts. As a demonstrative application, the structural connectivity divergence between macaque and human brains was mapped using the Brainnetome atlases of those two species to uncover the genetic underpinnings of the evolutionary changes in brain structure. The resulting resource includes (1) the thoroughly delineated Macaque Brainnetome Atlas (MacBNA), (2) regional connectivity profiles, (3) the postmortem high resolution macaque diffusion and T2-weighted MRI dataset (Brainnetome-8), and (4) multi-contrast MRI, block-face, and section images collected from a single macaque. MacBNA can serve as a common reference frame for mapping multifaceted features across modalities and spatial scales and for integrative investigation and characterization of brain organization and function. Therefore, it will enrich the collaborative resource platform for nonhuman primates and facilitate translational and comparative neuroscience research.

neuroscience↗

bioRxiv2022

Insitutype: likelihood-based cell typing for single cell spatial transcriptomics

Accurate cell typing is fundamental to analysis of spatial single-cell transcriptomics, but legacy scRNA-seq algorithms can underperform in this new type of data. We have developed a cell typing algorithm, Insitutype, designed for statistical and computational efficiency in spatial transcriptomics data. Insitutype is based on a likelihood model that weighs the evidence from every expression value, extracting all the information available in each cells expression profile. This likelihood model underlies a Bayes classifier for supervised cell typing, and an Expectation-Maximization algorithm for unsupervised and semi-supervised clustering. Insitutype also leverages alternative data types collected in spatial studies, such as cell images and spatial context, by using them to inform prior probabilities of cell type calls. We demonstrate rapid clustering of millions of cells and accurate fine-grained cell typing of kidney and non-small cell lung cancer samples.

bioinformatics↗

bioRxiv2022

Field dependent deep learning enables high-throughput whole-cell 3D super-resolution imaging

Single-molecule localization microscopy (SMLM) in a typical wide-field setup has been widely used for investigating sub-cellular structures with super resolution. However, field-dependent aberrations restrict the field of view (FOV) to only few tens of micrometers. Here, we present a deep learning method for precise localization of spatially variant point emitters (FD-DeepLoc) over a large FOV covering the full chip of a modern sCMOS camera. Using a graphic processing unit (GPU) based vectorial PSF fitter, we can fast and accurately model the spatially variant point spread function (PSF) of a high numerical aperture (NA) objective in the entire FOV. Combined with deformable mirror based optimal PSF engineering, we demonstrate high-accuracy 3D SMLM over a volume of ~180 x 180 x 5 m3, allowing us to image mitochondria and nuclear pore complex in the entire cells in a single imaging cycle without hardware scanning - a 100-fold increase in throughput compared to the state-of-the-art.

biophysics↗

bioRxiv2022

Chemical inhibition of PIN auxin transporters by the anti-inflammatory drug Naproxen

The phytohormone auxin plays central roles in many growth and developmental processes in plants. Development of chemical tools targeting the auxin pathway is useful for both plant biology and agriculture. Here we uncover that Naproxen, a synthetic compound with anti-inflammatory activity in humans, acts as an auxin transport inhibitor targeting PIN transporters in plants. Physiological experiments indicate that exogenous Naproxen treatment affects pleiotropic auxin-regulated developmental processes. Further cellular and biochemical evidence supports that Naproxen suppresses auxin transport, specifically PIN-mediated auxin efflux. Moreover, biochemical and structural analysis confirms that Naproxen binds directly to PIN1 protein, via the same binding cavity as the IAA substrate. Thus, by combining cellular, biochemical, and structural approaches, this study well establishes that Naproxen is a PIN inhibitor and elucidates the underlying mechanisms. Further use of the compound may advance our understanding on the molecular mechanisms of PIN-mediated auxin transport, and expand our toolkit in auxin biology and agriculture.

plant biology↗

bioRxiv2022

Pangenome-based dynamic trajectories of intracellular gene transfers in Poaceae unveil a high rate of unceasing integration and selective retention in Triticeae

Intracellular gene transfers (IGTs) between the nucleus and organelles, including plastids and mitochondria, constantly reshapes the nuclear genome during evolution. Despite the substantial contribution of IGTs to genome variation, the dynamic trajectories of IGTs at the pangenomic level remain elusive. Here, we propose a novel approach, IGTminer, to map the evolutionary trajectories of IGTs by collinearity and gene reannotation across multiple genome assemblies. IGTminer was applied to create a nuclear organelle gene (NOG) map across 67 genomes covering 15 Poaceae species, including important crops, revealing the polymorphisms and trajectory dynamics of NOGs. The NOGs produced were verified by experimental evidence and resequencing datasets. We found that most of the NOGs were recently transferred and lineage specific, and that Triticeae species tended to have more NOGs than other Poaceae species. Wheat had a higher retention rate of NOGs than maize and rice, and the retained NOGs were likely involved in the photosynthesis and translation pathways. Large numbers of NOG clusters were aggregated in hexaploid wheat during two rounds of polyploidization and contributed to the genetic diversities among modern wheat varieties. Finally, we proposed a radiocarbon-like model illustrating the transfer and elimination dynamics of NOGs, highlighting the unceasing integration and selective retention of NOGs over evolutionary time. In addition, we implemented an interactive webserver for NOG exploration in Poaceae. In summary, this study provides new resources and clues for the roles of IGTs in shaping inter- and intraspecies genome variation and driving plant genome evolution.

evolutionary biology↗

bioRxiv2022

Mechanism of dual pharmacological correction and potentiation of human CFTR

Cystic fibrosis (CF) is caused by mutations in a chloride channel called the human Cystic Fibrosis Transmembrane Conductance Regulator (hCFTR). We used cryo-EM global conformational ensemble reconstruction to characterize the mechanism by which the breakthrough drug VX445 (Elexacaftor) simultaneously corrects both protein-folding and channel-gating defects caused by CF mutations. VX445 drives hCFTR molecules harboring the gating-defective G551D mutation towards the open-channel conformation by binding to a site in the first transmembrane domain. This binding interaction reverses the usual pathway of allosteric structural communication by which ATP binding activates channel conductance, which is blocked by the G551D mutation. Our ensemble reconstructions include a 3.4 [A] non-native structure demonstrating that detachment of the first nucleotide-binding domain of hCFTR is directly coupled to local unfolding of the VX445 binding site. Reversal of this unfolding transition likely contributes to its corrector activity by cooperatively stabilizing NBD1 and the transmembrane domains of hCFTR during biogenesis. SummaryCryo-EM global conformational ensemble reconstruction has been used to characterize the mechanism-of-action of a breakthrough pharmaceutical that corrects fatal protein-folding and channel-gating defects in the human cystic fibrosis transmembrane conductance regulator (CFTR).

biophysics↗

bioRxiv2022

The RNA m6A reader YTHDF1 promotes hematopoietic malignancy by maintaining oncogenic translation

N6-methyladenosine (m6A), the most abundant modification in mRNAs, has been defined as a crucial modulator in the progression of acute myeloid leukemia (AML), while the detailed mechanism remains elusive. Here we report that YTHDF1, an m6A reader protein, is overexpressed in human AML samples with enrichment in leukemia stem cells (LSCs). Whereas YTHDF1 is dispensable for normal hematopoiesis in mice, depletion of YTHDF1 attenuates self-renewal and proliferation of patient-derived LSCs, and impedes leukemia establishment in immunodeficient mice. Mechanistically, YTHDF1 promotes the translation of diverse m6A-modified oncogene mRNAs particularly cyclin E2. We applied a structure-based virtual screening of FDA-approved drugs and identified tegaserod as a potential YTHDF1 inhibitor. Tegaserod blocks the direct binding of YTHDF1 with m6A-modified mRNAs and inhibits YTHDF1-regulated mRNA translation. Moreover, tegaserod inhibits leukemogenesis in vitro and in mice, phenocopying the loss of YTHDF1. Together, our study defines YTHDF1 as an integral regulator of AML progression at the translational level and identifies tegaserod as a potential therapeutic agent for AML by targeting YTHDF1. Statement of SignificanceO_LIThe RNA m6A reader YTHDF1 is an oncoprotein in AML. C_LIO_LIYTHDF1 promotes the translation of m6A-modified oncogene mRNAs. C_LIO_LITegaserod, an FDA-approved drug for irritable bowel syndrome, inhibits YTHDF1-regulated mRNA translation and leukemogenesis. C_LI Graphical Abstract O_FIG_DISPLAY_L [Figure 1] M_FIG_DISPLAY C_FIG_DISPLAY

cancer biology↗

bioRxiv2022

Genetic, clinical underpinnings of subtle early brain change along Alzheimer's dimensions

Alzheimers disease (AD) is associated with heterogeneous atrophy patterns. We employed a semi-supervised clustering technique known as Surreal-GAN, through which we identified two dominant dimensions of brain atrophy in symptomatic mild cognitive impairment (MCI) and AD patients: the "diffuse-AD" (R1) dimension shows widespread brain atrophy, and the "MTL-AD" (R2) dimension displays focal medial temporal lobe (MTL) atrophy. Critically, only R2 was associated with widely known sporadic AD genetic risk factors (e.g., APOE {varepsilon}4) in MCI and AD patients at baseline. We then independently detected the presence of the two dimensions in the early stages by deploying the trained model in the general population and two cognitively unimpaired cohorts of asymptomatic participants. In the general population, genome-wide association studies found 77 genes unrelated to APOE differentially associated with R1 and R2. Functional analyses revealed that these genes were overrepresented in differentially expressed gene sets in organs beyond the brain (R1 and R2), including the heart (R1) and the pituitary gland, muscle, and kidney (R2). These genes were enriched in biological pathways implicated in dendritic cells (R2), macrophage functions (R1), and cancer (R1 and R2). Several of them were "druggable genes" for cancer (R1), inflammation (R1), cardiovascular diseases (R1), and diseases of the nervous system (R2). The longitudinal progression showed that APOE {varepsilon}4, amyloid, and tau were associated with R2 at early asymptomatic stages, but this longitudinal association occurs only at late symptomatic stages in R1. Our findings deepen our understanding of the multifaceted pathogenesis of AD beyond the brain. In early asymptomatic stages, the two dimensions are associated with diverse pathological mechanisms, including cardiovascular diseases, inflammation, and hormonal dysfunction - driven by genes different from APOE - which may collectively contribute to the early pathogenesis of AD.

bioengineering↗

bioRxiv2022

CD4-binding site immunogens elicit heterologous anti-HIV-1 neutralizing antibodies in transgenic and wildtype animals

Passive transfer of broadly neutralizing anti-HIV-1 antibodies (bNAbs) protects against infection, and therefore eliciting bNAbs by vaccination is a major goal of HIV-1 vaccine efforts. bNAbs that target the CD4-binding site (CD4bs) on HIV-1 Env are among the most broadly active, but to date, responses elicited against this epitope in vaccinated animals have lacked potency and breadth. We hypothesized that CD4bs bNAbs resembling the antibody IOMA might be easier to elicit than other CD4bs antibodies that exhibit higher somatic mutation rates, a difficult-to-achieve mechanism to accommodate Envs N276gp120 N-glycan, and rare 5-residue light chain complementarity determining region 3s (CDRL3s). As an initial test of this idea, we developed IOMA germline-targeting Env immunogens and evaluated a sequential immunization regimen in transgenic mice expressing germline-reverted IOMA. These mice developed CD4bs epitope-specific responses with heterologous neutralization, and cloned antibodies overcame neutralization roadblocks including accommodating the N276gp120 glycan, with some neutralizing selected HIV-1 strains more potently than IOMA. The immunization regimen also elicited CD4bs-specific responses in animals containing polyclonal antibody repertoires. Thus, germline-targeting of IOMA-class antibody precursors represents a potential vaccine strategy to induce CD4bs bNAbs.

immunology↗

bioRxiv2022

MedDiC: high dimensional mediation analysis via difference in coefficients

High dimensional mediation analysis has been receiving increasing popularity, largely motivated by the scientific problems in genomics and biomedical imaging. Previous literature has primarily focused on mediator selection for high dimensional mediators. In this paper, we aim at the estimation and inference of overall indirect effect for high dimensional exposures and high dimensional mediators. We propose MedDiC, a novel debiased estimator of the high dimensional overall indirect effect based on difference-in-coefficients approach. We evaluate the proposed method using intensive simulations and find that MedDiC provides valid inference and offers higher power and shorter computing time than the competitors for both low dimensional and high dimensional exposures. We also apply MedDiC to a mouse f2 dataset for diabetes study and a dataset composed of diverse maize inbred lines for flowering time, and show that MedDiC yields more biologically meaningful gene lists, and the results are reproduciable across analyses using different measures of identical biological signal or related phenotype as the outcome. Upon the acceptance of the paper, the code will be available on GitHub (https://github.com/QiZhangStat/MedDiC).

genetics↗

bioRxiv2022

Immune dynamics at single cell protein level after delta/omicron infection in COVID-19 vaccinated convalescent individuals

Both COVID-19 mRNA or recombinant Adenovirus vector (rAdVV) based vaccines have shown a great efficacy in generating humoral and cellular immune responses. Two doses of the COVID-19 vaccines generate enough antibodies and generate spike-specific T cell responses. However, after 6-8 months there is a decline in antibody production and T cell responses. Due to the rise of new SARS-CoV-2 variants of concern, a third or even fourth dose of vaccine was recommended for the elderly, immune comprised and frontline medical health care workers. However, despite additional booster doses given, those who were infected with either delta or omicron (during December 2021 - March 2022) had symptoms of illness. By what means these COVID-19 vaccines provide immunity against the SARS-CoV-2 virus at the molecular level is not explored extensively yet and, it is an emerging research field as to how the SARS-CoV-2 virus is able to evade the host immunity. Most of the infected people had mild symptoms whilst some were asymptomatic. Many of the people had developed nucleocapsid antibodies against the SARS-CoV-2 delta/omicron variants confirming a humoral immune response against viral infection. Furthermore, cellular analysis shows that post-vaccinated recovered COVID-19 individuals have significantly reduced NK cells and increased T naive CD4+, TEM CD8+ and B cells. This decrease in cellular immunity corresponds to individuals who recovered from alpha variants infection and had mild symptoms. Our results highlight that booster doses clearly reduce the severity of infection against delta/omicron infection. Furthermore, our cellular and humoral immune system is trained by vaccines and ready to deal with breakthrough infections in the future.

immunology↗

bioRxiv2022

KMer-Node2Vec: Learning Vector Representations of K-mers from the K-meGraph

Learning low-dimensional continuous vector representation for short k-mers divided from long DNA sequences is key to DNA sequence modeling that can be utilized in many bioinformatics investigations, such as DNA sequence classification and retrieval. DNA2Vec is the most widely used method for DNA sequence embedding. However, it poorly scales to large data sets due to its extremely long training time in kmer embedding. In this paper, we propose a novel efficient graph-based kmer embedding method, named Kmer-Node2Vec, to tackle this concern. Our method converts the large DNA corpus into one kmer co-occurrence graph and extracts kmer relation on the graph by random walks to learn fast and high-quality kmer embedding. Extensive experiments show that our method is faster than DNA2Vec by 29 times for training on a 4GB data set, and on par with DNA2Vec in terms of task-specific accuracy of sequence retrieval and classification.

bioinformatics↗

bioRxiv2022

Dynamic modelling and analysis of autophagy in the clearance of aggregated α-synuclein in Parkinson's disease

The widely-accepted hallmark pathology of Parkinsons disease (PD) is the presence of Lewy bodies (LB) with characteristic abnormal aggregated -synuclein (Syn). Growing physiological evidences suggest that there is a pivotal role for the autophagy-lysosome pathway in the clearance of misfolded Syn (Syn*) for maintaining homeostasis and neural cell function. In this work, we establish a new mathematical model for Syn* degradation through the autophagy pathway. The qualitative simulations discover the tri-stability phenomena and dynamical behaviors of Syn*, i.e., the coexistence of three stable steady states, in which the lower, medium and upper steady states correspond to the healthy, critical and diseased stages of pathological mechanism of PD, respectively. Diverse analyses on codimension-1 and -2 bifurcations suggest that autophagy can control the switches among the stable steady states for the aggregation of Syn*. It is also found that the double negative crosstalk feedback between autophagy and apoptosis is important to the robustness of tri-stability of Syn* for this biodynamic system. Our novel results may be valuable for making further therapeutic strategies in prevention and treatment for PD. Author summarySyn* is one of the most and primary remarkable targets for the universal neurodegenerative disease of PD. Efficient clearance mechanism of autophagy, contains a lot of molecular components to maintain the cellular homeostasis and cell renewal, could be the possible therapy for PD. Understand the complexity of autophagy in degrading Syn* requires the integration of both theoretical and experimental points of view. Here, we have proposed a novel mathematical model that analyses the temporal and dynamic behaviors of the biosystem for autophagy degrades Syn* to access PD states. The model explains that the tri-stability is of particularly relevance to this biosystem that switch among the healthy, critical and disease states, and captures that the critical intermedium state exits for preventing the system transform healthy to disease state directly, and further illustrates that the molecular signaling feedback loops of autophagy may be important for the robustness of tri-stability. Our work deepens the researches of PD by uncovering the important buffering medium state and providing promising potential therapeutic insights.

systems biology↗

bioRxiv2022

Now What Sequence? Pre-trained Ensembles for Bayesian Optimization of Protein Sequences

Pre-trained models have been transformative in natural language, computer vision, and now protein sequences by enabling accuracy with few training examples. We show how to use pre-trained sequence models in Bayesian optimization to design new protein sequences with minimal labels (i.e., few experiments). Pre-trained models give good predictive accuracy at low data and Bayesian optimization guides the choice of which sequences to test. Pre-trained sequence models also remove the common requirement of having a list of possible experiments. Any sequence can be considered. We show significantly fewer labeled sequences are required for three sequence design tasks, including creating novel peptide inhibitors with AlphaFold. These de novo peptide inhibitors require only sequence information, no known protein-protein structures, and we can predict highly-efficient binders with less than 10 AlphaFold calculations.

bioinformatics↗

bioRxiv2022

Molecular basis for antiviral activity of pediatric neutralizing antibodies targeting SARS-CoV-2 Spike receptor binding domain

Neutralizing antibodies (NAbs) hold great promise for clinical interventions against SARS-CoV- 2 variants of concern (VOCs). Understanding NAb epitope-dependent antiviral mechanisms is crucial for developing vaccines and therapeutics against VOCs. Here we characterized two potent NAbs, EH3 and EH8, isolated from an unvaccinated pediatric patient with exceptional plasma neutralization activity. EH3 and EH8 cross-neutralize the early VOCs and mediate strong Fc-dependent effector activity in vitro. Structural analyses of EH3 and EH8 in complex with the receptor-binding domain (RBD) revealed the molecular determinants of the epitope-driven protection and VOC-evasion. While EH3 represents the prevalent IGHV3-53 NAb whose epitope substantially overlaps with the ACE2 binding site, EH8 recognizes a narrow epitope exposed in both RBD-up and RBD-down conformations. When tested in vivo, a single-dose prophylactic administration of EH3 fully protected stringent K18-hACE2 mice from lethal challenge with Delta VOC. Our study demonstrates that protective NAbs responses converge in pediatric and adult SARS-CoV-2 patients.

microbiology↗

bioRxiv2022

Antibody recognition of CD4-induced open HIV-1 Env trimers

HIV-1 envelope (Env), a heterotrimer of gp120-gp41 subunits, mediates fusion of the viral and host cell membranes after interactions with the host receptor CD4 and a coreceptor. CD4 binding induces rearrangements in Env trimer, resulting in a CD4-induced (CD4i) open Env conformation. Structural studies of antibodies isolated from infected donors have defined antibody-Env interactions, with one class of antibodies specifically recognizing the CD4i open Env conformation. Here, we characterize a group of monoclonal antibodies isolated from HIV-1 infected donors (V2i mAbs) that display characteristics of CD4i antibodies. Binding experiments demonstrate that the V2i mAbs preferentially recognize CD4-bound open Env trimers. Structural characterizations of V2i mAb-Env-CD4 trimer complexes using single-particle cryo-electron microscopy show recognition by V2i mAbs using different angles of approach to the gp120 V1V2 domain and the {beta}2/{beta}3 strands on a CD4i open conformation Env with no direct interactions of the mAbs with CD4. We also characterize CG10, a CD4i antibody that was raised in mice immunized with a gp120-CD4 complex, complexed with Env trimer and CD4. CG10 exhibits similar characteristics to the V2i antibodies: i.e., recognition of the open Env conformation, but shows direct contacts to both CD4 and gp120. Structural comparisons of these and previously characterized CD4i antibody interactions with Env provide a suggested mechanism for how these antibodies are elicited during HIV-1 infection. ImportanceThe RV144 HIV-1 clinical vaccination trial showed mild protection against viral infection. Antibody responses to the V1V2 region of HIV-1 Env gp120 were correlated inversely with the risk of infection. In addition, antibodies targeting V1V2 have been correlated with protections from SIV and SHIV infections in non-human primates. We structurally characterized V2i antibodies directed against V1V2 isolated from HIV-1 infected humans in complex with open Env trimers bound to the host receptor CD4. We also characterized a CD4i antibody that interacts with CD4 as well as the gp120 subunit of an open Env trimer. Our study suggests how V2i and CD4i antibodies were elicited during HIV-1 infection.

immunology↗