Biology subjects

Ngo, T.

Publications and source records attributed to Ngo, T..

30 records · Page 2Linked to original sources

bioRxiv2020

Neutralizing antibodies induced by first-generation gp41-stabilized HIV-1 envelope trimers and nanoparticles

Antigen-specific B-cell sorting and next-generation sequencing (NGS) were combined to isolate HIV-1 neutralizing antibodies (NAbs) from mice and rabbits immunized with BG505 trimers and nanoparticles. Three mouse NAbs potently neutralize BG505.T332N and recognize a glycan epitope centered at the C3/V4 region, as revealed by electron microscopy (EM), x-ray crystallography, and epitope mapping. Three potent NAbs were sorted from rabbit B cells that target glycan holes on the BG505 envelope glycoprotein (Env) and account for a significant portion of autologous NAb response. We then determined a 3.4[A]-resolution crystal structure for the clade C transmitted/founder Du172.17 Env with a redesigned heptad repeat 1 (HR1) bend. This clade C Env, as a soluble trimer and attached to a ferritin nanoparticle, along with a clade A Q482-d12 Env trimer, elicited distinct NAb responses in rabbits. Our study demonstrates that nanoparticles presenting gp41-stabilized trimers can induce potent NAb responses in mice and rabbits with Env-dependent breadth. TEASERMouse and rabbit NAbs elicited by gp41-stabilized trimers and nanoparticles neutralize autologous HIV-1 by targeting different epitopes

microbiology↗

bioRxiv2020

SEPIA: Simulation-based Evaluation of Prioritization Algorithms

BackgroundThe ability to prioritize people living with HIV by risk of future transmissions could aid public health officials in optimizing epidemiological intervention. While methods exist to perform such prioritization based on molecular data, their effectiveness and accuracy are poorly understood, and it is unclear how one can directly compare the accuracy of different methods. We introduce SEPIA (Simulation-based Evaluation of PrIoritization Algorithms), a novel simulation-based framework for determining the effectiveness of prioritization algorithms. Under several metrics of effectiveness that we propose, we utilize various properties of the simulated contact networks and transmission histories to compare existing prioritization approaches: one phylogenetic (ProACT) and one distance-based (growth of HIV-TRACE transmission clusters). ResultsUsing all metrics of effectiveness that we propose, ProACT consistently slightly outperformed the transmission cluster growth approach. However, both methods consistently performed just marginally better than random, suggesting that there is significant room for improvement in prioritization tools. ConclusionWe hope that, by providing ways to quantify the effectiveness of prioritization methods in simulation, SEPIA will aid researchers in developing novel tools for prioritizing people living with HIV by risk of future transmissions.

bioinformatics↗

bioRxiv2020

Evolution of Modularity, Interactome and Functions of GIV/Girdin (CCDC88A) from Invertebrates to Vertebrates

PDZ domains are one of the most abundant protein domains in eukaryotes and frequently found on junction-localized scaffold proteins. Various signaling molecules bind to PDZ proteins via PDZ-binding motifs (PBM) and finetune cellular signaling. Here we describe the presence of a PBM on GIV/Girdin (CCDC88A) that is conserved throughout evolution, from invertebrates to vertebrates, and is generated as a long isoform-variant in humans, which we named GIV-L. Unlike GIV, which lacks PBM and is cytosolic, GIV-L localizes to the cell junctions, and has a unique PDZ-interactome, which impacts GIV-Ls ability to bind and activate trimeric G-protein, Gi through its guanine-nucleotide exchange modulator (GEM) module; the GEM module is found exclusively in vertebrates. Thus, the two functional modules in GIV evolved sequentially: the ability to bind PDZ proteins via the PBM evolved earlier in invertebrates, whereas G-protein binding and activation may have evolved later only among vertebrates. Phenotypic studies in Caco-2 cells revealed that GIV and GIV-L may have antagonistic effects on cell growth, proliferation (cell cycle), and survival. Immunohistochemical analyses in human colon tissues showed that GIV expression increases with a concomitant decrease in GIV-L during cancer initiation. Taken together, these findings reveal how GIV/CCDC88A in humans displays evolutionary flexibility in modularity, which allows the resultant isoforms to play opposing roles either as a tumor suppressor (GIV-L) or as an oncogene (GIV).

biochemistry↗

bioRxiv2020

Host immune responses after suprachoroidal delivery of AAV8 in nonhuman primate eyes

The suprachoroid is a potential space located between the sclera and choroid of the eye which provides a novel route for ocular drug or viral vector delivery. Suprachoroidal injection of AAV8 using transscleral microneedles enables widespread transgene expression in eyes of nonhuman primates, but may cause intraocular inflammation. We characterized the host humoral and cellular immune responses after suprachoroidal delivery of AAV8 expressing green fluorescent protein (GFP) in rhesus macaques, and found that it can induce a mild chorioretinitis that resolves after systemic corticosteroid administration, with recovery of photoreceptor morphology but persistent immune cell infiltration after 3 months. Suprachoroidal AAV8 triggered B-cell and T-cell responses against GFP, but only mild antibody responses to the viral capsid as compared to intravitreal injections of the same vector and dose. Systemic biodistribution studies showed lower AAV8 levels in liver and spleen after suprachoroidal injection compared with intravitreal delivery. Our findings suggest that suprachoroidal AAV8 primarily triggers host immune responses to GFP, likely due to sustained transgene expression in scleral fibroblasts outside the blood-retinal barrier, but elicits less humoral immune reactivity to the viral capsid than intravitreal delivery due to lower egress into systemic circulation. Thus, suprachoroidal AAV delivery of human transgenes may have significant translational potential for retinal gene therapy.

genetics↗

bioRxiv2020

Self-assembling nanoparticles presenting receptor binding domain and stabilized spike as next-generation COVID-19 vaccines

Vaccination against SARS-CoV-2 provides an effective tool to combat the COIVD-19 pandemic. Here, we combined antigen optimization and nanoparticle display to develop vaccine candidates for SARS-CoV-2. We first displayed the receptor-binding domain (RBD) on three self-assembling protein nanoparticle (SApNP) platforms using the SpyTag/SpyCatcher system. We then identified heptad repeat 2 (HR2) in S2 as the cause of spike metastability, designed an HR2-deleted glycine-capped spike (S2G{Delta}HR2), and displayed S2G{Delta}HR2 on SApNPs. An antibody column specific for the RBD enabled tag-free vaccine purification. In mice, the 24-meric RBD-ferritin SApNP elicited a more potent neutralizing antibody (NAb) response than the RBD alone and the spike with two stabilizing proline mutations in S2 (S2P). S2G{Delta}HR2 elicited two-fold-higher NAb titers than S2P, while S2G{Delta}HR2 SApNPs derived from multilayered E2p and I3-01v9 60-mers elicited up to 10-fold higher NAb titers. The S2G{Delta}HR2-presenting I3-01v9 SApNP also induced critically needed T-cell immunity, thereby providing a promising vaccine candidate. ONE-SENTENCE SUMMARYThe SARS-CoV-2 receptor binding domain and S2G{Delta}HR2 spike elicited potent immune responses when displayed on protein nanoparticles as vaccine candidates.

microbiology↗

bioRxiv2020

Orphan G protein-coupled receptor, GPR37L1: pharmacological toolbox empty once again

Orphan G protein-coupled receptors (GPCRs) are largely intractable therapeutic targets, owing to the lack of chemical tools for exploring their pharmacology. The discovery of such tools, however, is hampered by a number of unknowns, such as effector coupling and appropriate positive controls. In our 2017 Nature Chemical Biology paper1, we developed a computational chemical tool discovery approach called GPCR Contact-Informed Neighboring Pocket (GPCR-CoINPocket). This method predicted pharmacological similarity of GPCRs in a ligand- and structure-independent manner, to enable the discovery of off-target activities of known compounds at orphan GPCRs and hence the identification of so-called surrogate ligands. Our orphan GPCR target for prospective surrogate ligand discovery efforts was GPR37L1, a brain-specific receptor linked to cerebellar development2 and seizures3. We had previously demonstrated that GPR37L1 constitutively coupled to Gs and generated ligand-independent increases in intracellular cAMP4[§]. Thus, the inverse agonist activities of computationally predicted surrogates were tested in the cAMP response element luciferase (CRE-luc) reporter gene assay in human embryonic kidney (HEK293) cells expressing either vector control or what we thought was untagged GPR37L1 in pcDNA3.1. However, we recently discovered that the GPR37L1 construct used in that study was incorrect: instead of pcDNA3.1, it carried the receptor inserted backwards into a yeast p426GPD vector (hereafter referred to as p426-r37L1). Here, we correct the cloning error and describe our subsequent unsuccessful efforts to re-test the computationally predicted GPR37L1 ligands (triggering an author-initiated retraction of1). NoteWe, the authors, are working with the Nature Chemical Biology Editors to retract our 2017 paper Orphan receptor ligand discovery by pickpocketing pharmacological neighbors1. The present manuscript is under review at Nature Chemical Biology as a Matters Arising accompaniment to the anticipated author-initiated retraction. We initiated the steps towards the retraction upon discovering a regrettable cloning error that put into question the in vitro findings reported in1. This action was unanimously agreed upon by all authors. The computational aspects of the original manuscript1 are unaffected by this error.

pharmacology and toxicology↗

bioRxiv2020

Single-component multilayered self-assembling nanoparticles presenting rationally designed glycoprotein trimers as Ebola virus vaccines

Ebola virus (EBOV) glycoprotein (GP) can be recognized by neutralizing antibodies (NAbs) and is the main target for vaccine design. Here, we first investigate the contribution of the stalk and heptad repeat 1-C (HR1C) regions to GP metastability. Specific stalk and HR1C modifications in a mucin-deleted form (GP{Delta}muc) increase trimer yield, whereas alterations of HR1C exert a more complex effect on thermostability. Crystal structures are determined to validate two rationally designed GP{Delta}muc trimers in their unliganded state. We then display a modified GP{Delta}muc trimer on reengineered nanoparticles that encapsulate a layer of locking domains (LD) and a cluster of helper T-cell epitopes. In mice and rabbits, GP trimers and nanoparticles elicit cross-ebolavirus NAbs, as well as non-NAbs that enhance pseudovirus infection. Repertoire sequencing reveals quantitative profiles of vaccine-induced B-cell responses. This study demonstrates a promising vaccine strategy for filoviruses, such as EBOV, based on GP stabilization and nanoparticle display.

microbiology↗

bioRxiv2020

Receptor tyrosine kinases activate heterotrimeric G proteins via phosphorylation within the interdomain cleft of Gαi

The molecular mechanisms by which receptor tyrosine kinases (RTKs) and heterotrimeric G proteins, two major signaling hubs in eukaryotes, independently relay signals across the plasma membrane have been extensively characterized. How these hubs crosstalk has been a long-standing question, but answers remain elusive. Using linear-ion-trap mass spectrometry in combination with biochemical, cellular, and computational approaches, we unravel a mechanism of activation of heterotrimeric G proteins by RTKs and chart the key steps that mediate such activation. Upon growth factor stimulation, the guanine-nucleotide exchange modulator, GIV, dissociates Gi*{beta}{gamma} trimers, scaffolds monomeric Gi with RTKs, and facilitates the phosphorylation on two tyrosines located within the inter-domain cleft of Gi. Phosphorylation triggers the activation of Gi and inhibits second messengers (cAMP). Tumor-associated mutants reveal how constitutive activation of this pathway impacts cells decision to go vs. grow. These insights define a tyrosine-based G protein signaling paradigm and reveal its importance in eukaryotes. Significance StatementGrowth factors and heterotrimeric G proteins are two of the most widely studied signaling pathways in eukaryotes; their crosstalk shapes some of the most fundamental cellular responses in both health and disease. Although mechanisms by which G protein pathways transactivate growth factor RTKs has been well-defined, how the reverse may happen is less understood. This study defines the key steps and cellular consequences of a fundamental mechanism of signal crosstalk that enables RTKs to transactivate heterotrimeric G protein, Gi. Mutations found in tumors shed light on how derailing this mechanism impacts tumor cell behavior. Thus, findings not only show how cells integrate extracellular signals via pathway crosstalk, but also demonstrate the relevance of this pathway in cancers.

biochemistry↗

bioRxiv2020

The N-terminus of GPR37L1 is proteolytically processed by matrix metalloproteases

GPR37L1 is an orphan G protein-coupled receptor expressed exclusively in the brain and linked to seizures, neuroprotection and cardiovascular disease. Based upon the observation that fragments of the GPR37L1 N-terminus are found in human cerebrospinal fluid, we hypothesized that GPR37L1 was subject to post-translational modification. Heterologous expression of GPR37L1-eYFP in either HEK293 or U87 glioblastoma cells yielded two cell surface species of approximately equivalent abundance, the larger of which is N-glycosylated at Asn105. The smaller species is produced by matrix metalloprotease/ADAM-mediated proteolysis (shown by the use of pharmacological inhibitors) and has a molecular weight identical to that of a mutant lacking the entire N-terminus, Δ122 GPR37L1. Serial truncation of the N-terminus prevented GPR37L1 expression except when the entire N-terminus was removed, narrowing the predicted site of N-terminal proteolysis to residues 105-122. Using yeast expressing different G protein chimeras, we found that wild type GPR37L1, but not Δ122 GPR37L1, coupled constitutively to Gpa1/Gαs and Gpa1/Gα16 chimeras, in contrast to previous studies. We tested the peptides identified in cerebrospinal fluid as well as their putative newly-generated N-terminal ‘tethered’ counterparts in both wild type and Δ122 GPR37L1 Gpa1/Gαs strains but saw no effect, suggesting that GPR37L1 does not signal in a manner akin to the protease-activated receptor family. We also saw no evidence of receptor activation or regulation by the reported GPR37L1 ligand, prosaptide/TX14A. Finally, the proteolytically processed species predominated both in vivo and ex vivo in organotypic cerebellar slice preparations, suggesting that GPR37L1 is rapidly processed to a signaling-inactive form. Our data indicate that the function of GPR37L1 in vivo is tightly regulated by metalloprotease-dependent N-terminal cleavage.Competing Interest StatementThe authors have declared no competing interest.View Full Text

biochemistry↗

bioRxiv2020

Functional anatomy of the full length CXCR4-CXCL12 complex systematically dissected by quantitative model-guided mutagenesis

Due to their prominent role in development and infamy in cancer and HIV, the chemokine receptor CXCR4 and its ligand, CXCL12, have been the subject of numerous structural and functional studies. Nevertheless, a high resolution structure of the CXCR4-CXCL12 complex has not been reported. Even with several alternative computational models of the complex at hand, the relative contributions of different interaction epitopes to ligand binding, ligand selectivity and signaling are not readily apparent. Here, building upon our latest structural model, we employed a systematic mutagenesis strategy to dissect the functional anatomy of the of CXCR4-CXCL12 complex. Key charge swap mutagenesis experiments supported pairwise interactions between oppositely charged residues in the receptor and chemokine, confirming the accuracy of the predicted orientation of the chemokine relative to the receptor, while also providing insight into ligand selectivity. Progressive deletion of N-terminal residues revealed an unexpected contribution of the receptor N-terminus to chemokine signaling; this finding challenges a longstanding "two-site" hypothesis about the essential features of the receptor-chemokine interaction where the N-terminus is purported to only contribute to binding affinity. The results suggest that while the interaction of the chemokine N-terminus with the receptor binding pocket is the key driver of signaling, the signaling amplitude depends on the extent to which the receptor N-terminus binds the chemokine. Along with systematic characterization of other epitopes, the current data allow us to propose a comprehensive experimentally-consistent structural model for how the chemokine binds CXCR4 and initiates signal transmission through the receptor TM domain. One sentence summaryA systematic structure-guided mutagenesis study of chemokine receptor CXCR4 reveals novel insights into epitopes regulating ligand recognition, ligand specificity and CXCL12-mediated signaling.

pharmacology and toxicology↗

bioRxiv2020

Crosslinking-guided geometry of a complete CXC receptor-chemokine complex and the basis of chemokine subfamily selectivity

Chemokines and their receptors are orchestrators of cell migration in humans. Because dysregulation of the receptor-chemokine system leads to inflammation and cancer, both chemokines and receptors are highly sought therapeutic targets. Yet one of the barriers for their therapeutic targeting is the limited understanding of the structural principles behind receptor-chemokine recognition and selectivity. The existing structures do not include CXC subfamily complexes and lack information about the receptor distal N-termini, despite the importance of the latter in signaling, regulation, and bias. Here we report the discovery of the geometry of the complex between full-length CXCR4, a prototypical CXC receptor and driver of cancer metastasis, and its endogenous ligand CXCL12. By comprehensive disulfide crosslinking, we establish the existence and the structure of a novel interface between the CXCR4 distal N-terminus and CXCL12 {beta}1-strand, while also recapitulating earlier findings from NMR, modeling and crystallography of homologous receptors. A crosslinking-informed high-resolution model of the CXCR4-CXCL12 complex pinpoints the interaction determinants and reveals the occupancy of the receptor major subpocket by the CXCL12 proximal N-terminus. This newly found positioning of the chemokine proximal N-terminus provides a structural explanation of CXC receptor-chemokine selectivity against other subfamilies. Our findings challenge the traditional two-site understanding of receptor-chemokine recognition, suggest the possibility of new affinity and signaling determinants, and fill a critical void on the structural map of an important class of therapeutic targets. These results will aid the rational design of selective chemokine-receptor-targeting small molecules and biologics with novel pharmacology.

biochemistry↗

bioRxiv2019

Identification of snails and parasites of medical importance via convolutional neural network: an application for human schistosomiasis

Schistosomiasis is a debilitating parasitic disease infecting over 250 million people with nearly 800 million people at risk worldwide, primarily in sub-Saharan Africa. Transmission to humans involves freshwater snails as intermediate hosts, which are particularly prevalent in developing countries where dams and water resource projects have expanded freshwater snail habitat. At our study sites in the lower Senegal River Basin, we have collected more than 5,500 images of the 7 freshwater snail species (grouped into 4 categories) most frequently encountered in this aquatic ecosystem, 5 of which amplify and transmit either urinary or intestinal human schistosomiasis, with the other 2 species responsible for the transmission of less common parasitic diseases of humans and/or livestock. We have also collected over 5,100 images of 11 classes of trematodes, including human and non-human schistosomes. It takes a great deal of training and expertise to accurately classify these organisms morphologically. In recent years, deep convolutional neural networks (CNNs) have proven to be highly efficient for image recognition tasks across many object categories. Here we demonstrate classification capacity for snail and parasite images and test our models performance against 8 highly-trained human parasitologists with experience taxonomically classifying snail and parasite species from the Senegal River Basin in West Africa. We establish and train a single CNN end-to-end directly from images with only pixels and labels as inputs. Applying this state-of-the-art algorithm, we are able to classify images of 4 snail categories with 99.64% accuracy and images of 11 parasite categories with 88.14% accuracy, which rivals highly-trained human parasitologists. The trained algorithm could next be deployed to mobile devices for use in remote field settings by local technicians, and significantly improve monitoring snail and parasite occurrence in the field for disease control purposes.\n\nAuthor SummarySchistosomiasis is a neglected tropical disease (NTD) infecting over 250 million people worldwide. The current approach to mitigate this disease in endemic regions is community or school-based mass drug administration. However, parasites are primarily transmitted through environmental reservoirs where freshwater snails serve as intermediate hosts. People use the contaminated water sources for their daily tasks and get re-infected after drug treatment. Therefore, drug administration alone is not effective for schistosomiasis control in such high transmission settings. Recent studies show that snail population control is essential to reduce disease transmission risks. To discern between parasitic worms of humans in snails and those of other non-human species is a necessary step to precisely quantify transmission risk for human schistosomiasis. However, it takes a great deal of expertise to train lab and field technicians to accurately classify snail and parasite species. Artificial intelligence (AI)-powered computer vision algorithms have recently proven to be highly efficient for image recognition tasks. We have collected thousands of snail and parasite images in Senegal during 2015-2018. Using these images as training data, we developed an AI model that classifies images of 4 snail categories and 11 parasite categories with, in some cases, higher accuracy than well-trained human parasitologists. This model could next be deployed to mobile devices for use in remote field settings to support local technicians to identify transmission hotspots and target control.

bioinformatics↗