Biology subjects

Brusic, V.

Publications and source records attributed to Brusic, V..

7 recordsLinked to original sources

bioRxiv2026

Lachesin is a mosquito receptor for multiple arthritogenic alphaviruses

Arthritogenic alphaviruses cause acute febrile illnesses associated with rash and arthritis when they are transmitted to humans through the bite of infected mosquitoes. Among these, chikungunya virus (CHIKV), transmitted primarily through the bite of infected Aedes aegypti and Aedes albopictus mosquitoes, causes explosive outbreaks involving hundreds of thousands to millions of cases, with recent re-emergence in several global regions. While several cellular receptors that mediate alphavirus entry into mammalian cells have been identified, their mosquito counterparts remained unknown, largely due to a lack of functional genomics tools for these invertebrate species. Here, we established a CRISPR-based genetic screening platform in Aedes albopictus cells and used it to identify Lachesin, a conserved invertebrate cell adhesion molecule, as a receptor for CHIKV and multiple related alphaviruses including Semliki Forest virus (SFV), onyong-nyong virus (ONNV), Mayaro virus (MAYV), and Ross River virus (RRV). Lachesin depletion using RNA interference, anti-Lachesin antibody treatment, and soluble forms of Lachesin blocked CHIKV and SFV E2-E1 glycoprotein-mediated infection of mosquito cells. We show that alphavirus E2-E1 glycoproteins bind the first immunoglobulin domain of Lachesin, facilitating attachment and internalization of virus-like particles. Orthologs from divergent mosquito genera, but not from arachnids or other arthropods, also serve as alphavirus receptors, suggesting that cellular receptor binding is not the main obstacle to arthritogenic alphavirus vector host expansion. Our findings enhance understanding of the mechanisms of alphavirus emergence and vector competence and could aid in the development of broadly active, entry-targeted therapeutics against multiple alphaviruses that threaten public health.

microbiology↗

bioRxiv2025

Molecular basis for shifted receptor recognition by an encephalitic arbovirus

After decades of inactivity throughout the Americas, western equine encephalitis virus (WEEV) recently re-emerged in South America, causing a large-scale outbreak in humans and horses. WEEV binds protocadherin 10 (PCDH10) as a receptor; however, nonpathogenic strains no longer bind human or equine PCDH10 but retain the ability to bind avian receptors. Highly virulent WEEV strains can also bind the very low-density lipoprotein receptor (VLDLR) and apolipoprotein E receptor 2 (ApoER2) as alternative receptors. Here, by determining cryo-electron microscopy structures of WEEV strains isolated from 1941-2005 bound to mammalian receptors, we identify polymorphisms in the WEEV spike protein that explain shifts in receptor dependencies and that can allow nonpathogenic strains to infect primary cortical neurons. We predict the receptor dependencies of additional strains and of a related North American alphavirus. Our findings have implications for outbreak preparedness and enhance understanding of arbovirus neurovirulence through virus receptor binding patterns.

microbiology↗

bioRxiv2023

Structural basis for VLDLR recognition by eastern equine encephalitis virus

Alphaviruses are arthropod-borne enveloped RNA viruses that include several important human pathogens with outbreak potential. Among them, eastern equine encephalitis virus (EEEV) is the most virulent, and many survivors develop neurological sequelae, including paralysis and intellectual disability. The spike proteins of alphaviruses comprise trimers of heterodimers of their envelope glycoproteins E2 and E1 that mediate binding to cellular receptors and fusion of virus and host cell membranes during entry. We recently identified very-low density lipoprotein receptor (VLDLR) and apolipoprotein E receptor 2 (ApoER2), two closely related proteins that are expressed in the brain, as cellular receptors for EEEV and a distantly related alphavirus, Semliki forest virus (SFV)1. The EEEV and SFV spike glycoproteins have low sequence homology, and how they have evolved to bind the same cellular receptors is unknown. Here, we used single-particle cryo-electron microscopy (cryo-EM) to determine structures of the EEEV and SFV spike glycoproteins bound to the VLDLR ligand-binding domain. The structures reveal that EEEV and SFV use distinct surfaces to bind VLDLR; EEEV uses a cluster of basic residues on the E2 subunit of its spike glycoprotein, while SFV uses two basic residues at a remote site on its E1 glycoprotein. Our studies reveal that different alphaviruses interact with the same cellular receptor through divergent binding modes. They further suggest that the ability of LDLR-related proteins to interact with viral spike proteins through very small footprints with flexible binding modes results in a low evolutionary barrier to the acquisition of LDLR-related proteins as cellular receptors for diverse sets of viruses.

microbiology↗

bioRxiv2021

Prediction of therapy outcomes of CLL using gene expression intensity, clustering, and ANN classification of single cell transcriptomes

BackgroundSingle cell transcriptomics is a new technology that enables us to measure the expression levels of genes from an individual cell. The expression information reflects the activity of that individual cell which could be used to indicate the cell types. Chronic lymphocytic leukemia (CLL) is a malignancy of B cells, one of the peripheral blood mononuclear cells subtypes. We applied five analytical tools for the study of single cell gene expression in CLL course of therapy. These tools included the analysis of gene expression distributions - median, interquartile ranges, and percentage above quality control (QC) threshold; hierarchical clustering applied to all cells within individual single cell data sets; and artificial neural network (ANN) for classification of healthy peripheral blood mononuclear cell (PBMC) subtypes. These tools were applied to the analysis of CLL data representing states before and during the therapy. ResultsWe identified patterns in gene expression that distinguished two patients that had complete remission (complete response), a patient that had a relapse, and a patient that had partial remission within three years of Ibrutinib therapy. Patients with complete remission showed a rapid decline of median gene expression counts, and the total number of gene counts below the QC threshold for healthy cells (670 counts) in 80% of more of the cells. These patients also showed the emergence of healthy-like PBMC cluster maps within 120 days of therapy and distinct changes in predicted proportions of PBMC cell types. ConclusionsThe combination of basic statistical analysis, hierarchical clustering, and supervised machine learning identified patterns from gene expression that distinguish four CLL patients treated with Ibrutinib that experienced complete remission, partial remission, or relapse. These preliminary results suggest that new bioinformatics tools for single cell transcriptomics, including ANN comparison to healthy PBMC, offer promise in prognostics of CLL.

bioinformatics↗

bioRxiv2021

Artificial Neural Networks for classification of single cell gene expression

BackgroundSingle-cell transcriptome (SCT) sequencing technology has reached the level of high-throughput technology where gene expression can be measured concurrently from large numbers of cells. The results of gene expression studies are highly reproducible when strict protocols and standard operating procedures (SOP) are followed. However, differences in sample processing conditions result in significant changes in gene expression profiles making direct comparison of different studies difficult. Unsupervised machine learning (ML) uses clustering algorithms combined with semi-automated cell labeling and manual annotation of individual cells. They do not scale up well and a workflow used on a specific dataset will not perform well with other studies. Supervised ML classification shows superior classification accuracy and generalization properties as compared to unsupervised ML methods. We describe a supervised ML method that deploys artificial neural networks (ANN), for 5-class classification of healthy peripheral blood mononuclear cells (PBMC) from multiple diverse studies. ResultsWe used 58 data sets to train ANN incrementally - over ten cycles of training and testing. The sample processing involved four protocols: separation of PBMC, separation of PBMC + enrichment (by negative selection), separation of PBMC + FACS, and separation of PBMC + MACS. The training data set included between 85 and 110 thousand cells, and the test set had approximately 13 thousand cells. Training and testing were done with various combinations of data sets from four principal data sources. The overall accuracy of classification on independent data sets reached 5-class classification accuracy of 94%. Classification accuracy for B cells, monocytes, and T cells exceeded 95%. Classification accuracy of natural killer (NK) cells was 75% because of the similarity between NK cells and T cell subsets. The accuracy of dendritic cells (DC) was low due to very low numbers of DC in the training sets. ConclusionsThe incremental learning ANN model can accurately classify the main types of PBMC. With the inclusion of more DC and resolving ambiguities between T cell and NK cell gene expression profiles, we will enable high accuracy supervised ML classification of PBMC. We assembled a reference data set for healthy PBMC and demonstrated a proof-of-concept for supervised ANN method in classification of previously unseen SCT data. The classification shows high accuracy, that is consistent across different studies and sample processing methods.

bioinformatics↗

bioRxiv2020

The ancient fusogen EnvP(b)1 is expressed in human tissues and its structure informs the evolution of gammaretrovirus envelope proteins

Host genomes have acquired diversity from viruses through the capture of viral elements, often from endogenous retroviruses (ERVs). These viral elements contribute new transcriptional control elements and new protein encoding genes, and their refinement through evolution can generate novel physiological functions for the host. EnvP(b)1 is an endogenous retroviral envelope gene found in human and other primate genomes. We show that EnvP(b)1 arose very early in the evolution of primates, i.e. at least 40-47 million years ago, but has nevertheless retained its ability to fuse primate cells. We have detected similar sequences in the genome of a lemur species, suggesting that a progenitor virus may have circulated 55+ million years ago. We demonstrate that EnvP(b)1 protein is expressed in multiple human tissues and is fully processed, rendering it competent to fuse cells. This activated fusogen is expressed in multiple healthy human tissues and is under purifying selection, suggesting that its expression is selectively advantageous. We determined a structure of the inferred receptor binding domain of human EnvP(b)1, revealing close structural similarities between this Env protein and those of currently circulating leukemia viruses, despite poor sequence conservation. This observation highlights a common scaffold from which novel receptor binding specificities have evolved. The evolutionary plasticity of this domain may underlie the diversity of related Envs in circulating viruses and coopted elements alike. The function of EnvP(b)1 in primates remains unknown. SIGNIFICANCE STATEMENTOrganisms can access genetic and functional novelty by capturing viral elements within their genomes, where they can evolve to drive new cellular or organismal processes. We demonstrate that a retrovirus envelope gene, EnvP(b)1, has been maintained as a functional protein for 40 to [≥]55 million years and is expressed as a protein in multiple healthy human tissues. We believe it has an unknown function in primates. We determined the structure of its inferred receptor binding domain and compared it with the same domain in modern viruses. We find a common conserved architecture that underlies the varied receptor binding activity of divergent Env genes. The modularity and versatility of this domain may underpin the evolutionary success of this clade of fusogens.

microbiology↗

bioRxiv2019

Vesicular stomatitis virus transcription is inhibited by TRIM69 in the interferon-induced antiviral state

Interferons (IFNs) induce the expression of many interferon stimulated genes (ISGs), many of which are responsible for the cellular antiviral state in which the replication of numerous viruses is blocked. How the majority of individual ISGs inhibit the replication of particular viruses is unknown. We conducted a loss-of-function screen to identify genes required for the activity of IFN against vesicular stomatitis virus, Indiana serotype (VSVIND), a prototype negative strand RNA virus. Our screen revealed that TRIM69, a member of tripartite motif family of proteins, is a VSVIND inhibitor. TRIM69 potently inhibited VSVIND replication through a previously undescribed transcriptional inhibition mechanism. Specifically, TRIM69 physically associates with the VSVIND phosphoprotein (P), requiring a specific peptide target sequence encoded therein. P is a cofactor for the viral polymerase, and is required for viral RNA synthesis as well as the assembly of replication compartments. By targeting P, TRIM69 inhibits pioneer transcription of the incoming virion-associated minus strand RNA, thereby preventing the synthesis of viral mRNAs, and consequently impedes all downstream events in the VSVIND replication cycle. Unlike some TRIM proteins, TRIM69 does not inhibit viral replication by inducing degradation of target viral proteins. Rather, higher-order TRIM69 multimerization is required for its antiviral activity, suggesting that TRIM69 functions by sequestration or anatomical disruption of the viral machinery required for VSVIND RNA synthesis.\n\nSIGNIFICANCE STATEMENTInterferons are important antiviral cytokines that work by inducing hundreds of host genes whose products inhibit replication of many viruses. While the antiviral activity of interferon has long been known, the identities and mechanisms of action of most interferon-induced antiviral proteins remain to be discovered. We identified gene products that are important for the antiviral activity of interferon against vesicular stomatitis virus (VSV) a model virus that whose genome consists a single RNA molecule with negative sense polarity. We found that a particular antiviral protein, TRIM69, functions by a previously undescribed molecular mechanism. Specifically, TRIM69 interacts with, and inhibits the function, of a particular phosphoprotein (P) component the viral transcription machinery, preventing the synthesis of viral messenger RNAs.

microbiology↗