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Biology subjects

Sanyal, M.

Publications and source records attributed to Sanyal, M..

11 recordsLinked to original sources

Lipid Nanoparticles for Spleen-Targeted RNA delivery

Lipid nanoparticles (LNPs) formulated with neutral helper lipids efficiently deliver RNA to the liver in pre-clinical models and humans but achieving clinically relevant delivery to other tissues remains a major challenge. To reduce liver uptake, targeting strategies often range from active targeting relying on antibodies to quasi-active targeting by employing permanently charged helper lipids which influence biodistribution after administration. In this study, we present an alternative approach based on varying ionizable lipids and stabilizers, along with optimizing formulation parameters for targeted delivery of circular RNA via a passive targeting approach. We generated a library of 216 LNP formulations and evaluated their performance in vitro in Jurkat cells and human primary T cells. The lead LNPs showcasing activity in both Jurkat and T cells were explored for their efficacy in vivo via multiple routes of administrations. Our results show that both the identity of stabilizer and ionizable lipid had effects on decreasing hepatic vs. splenic delivery while enhancing splenic accumulation. In line with this improved tissue tropism, spleen-tropic LNPs induced distinct transcriptomic remodeling in vivo compared with conventional, FDA-approved SM-102 LNPs. These findings demonstrate that extrahepatic targeting of LNPs can be achieved without altering charge of the LNPs and further reveal that hepatic de-targeting efficiency could be influenced by the immune status of the recipient.

bioengineering↗

Comparative assessment of machine learning algorithms to predict severity of disease in COVID-19 patients based on eight cofactors

Machine learning is one of the important tools to diagnose and predict the diseased state accurately and effectively. The COVID-19 pandemic caused due to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has become one of the most researched healthcare topics worldwide. Machine learning algorithms can find efficient and reliable ways to predict the COVID-19 from vast amounts of existing health care data, allowing faster, effective, and more accurate diagnosis with lower risk based on the symptoms. Based on the countrywide data published by the Israeli Ministry of Health, we propose a system that detects COVID-19 instances using simple variables. The COVID-19 dataset used in the study consisted of 278848 patients samples with five different symptoms, namely cough, fever, sore throat, shortness of breath, and headache, apart from other basic information like age, gender, and test indication excluding confirmed COVID-19 result. The data was analyzed using traditional supervised machine learning algorithms namely, Decision tree, Support vector machine, Random Forest, Logistic regression, k-nearest neighbor, and Naive Bayes based on eight cofactors with high accuracy rate ([≥] 0.9450). Apart from Support vector machine, all other algorithms displayed better performance based on the AUC score calculated using the receiver operator characteristic (ROC) curve. This study also highlights the significant differences between precision, recall and accuracy for each model. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=97 SRC="FIGDIR/small/617884v1_ufig1.gif" ALT="Figure 1"> View larger version (19K): org.highwire.dtl.DTLVardef@33bb11org.highwire.dtl.DTLVardef@3e93aaorg.highwire.dtl.DTLVardef@508f76org.highwire.dtl.DTLVardef@faa9e2_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOGraphical AbstractC_FLOATNO C_FIG

bioinformatics↗

Design of universal Ebola virus vaccine candidates via immunofocusing

Ebola virus causes hemorrhagic fever in humans and poses a significant threat to global public health. Although two viral vector vaccines have been approved to prevent Ebola virus disease, they are distributed in the limited ring vaccination setting and only indicated for prevention of infection from orthoebolavirus zairense (EBOV) - one of three orthoebolavirus species that have caused previous outbreaks. Ebola virus glycoprotein GP mediates viral infection and serves as the primary target of neutralizing antibodies. Here we describe a universal Ebola virus vaccine approach using structure-guided design of candidates with hyperglycosylation that aims to direct antibody responses away from variable regions and toward conserved epitopes of GP. We first determined the hyperglycosylation landscape on Ebola virus GP and used that to generate hyperglycosylated GP variants with two to four additional glycosylation sites to mask the highly variable glycan cap region. We then created vaccine candidates by displaying wild-type or hyperglycosylated GP variants on ferritin nanoparticles (Fer). Immunization with these antigens elicited potent neutralizing antisera against EBOV in mice. Importantly, we observed consistent cross-neutralizing activity against Bundibugyo virus and Sudan virus from hyperglycosylated GP-Fer with two or three additional glycans. In comparison, elicitation of cross-neutralizing antisera was rare in mice immunized with wild-type GP-Fer. These results demonstrate a potential strategy to develop universal Ebola virus vaccines that confer cross-protective immunity against existing and emerging filovirus species. SIGNIFICANCE STATEMENTEbola virus outbreaks cause hemorrhagic fever with high mortality rates. Current viral vaccines require cold-chain storage and are distributed in limited ring vaccination settings. They are only indicated for protection against orthoebolavirus zairense (EBOV), one of three human-pathogenic Ebola virus species. Here we harness hyperglycosylation as an immunofocusing approach to design universal Ebola virus vaccine candidates based on Ebola virus glycoprotein (GP) displayed on ferritin nanoparticles (Fer). Compared with wild-type GP-Fer, immunization with hyperglycosylated GP-Fer elicited potently neutralizing antisera against EBOV, and more importantly, consistent cross-neutralizing activity against the other two orthoebolavirus species. Our work shows that immunofocusing antibody responses toward conserved and neutralizing epitopes of GP represents a promising strategy for vaccine design against antigenically diverse Ebola virus species.

immunology↗

Decreased efficacy of a COVID-19 vaccine due to mutations present in early SARS-CoV-2 variants of concern

With the SARS-CoV-2 virus still circulating and evolving, there remains an outstanding question if variant-specific vaccines represent the optimal path forward, or if other strategies might be more efficacious towards providing broad protection against emerging variants. Here, we examine the efficacy of strain-specific variants of our previously reported, pan-sarbecovirus vaccine candidate, DCFHP-alum, a ferritin nanoparticle functionalized with an engineered form of the SARS-CoV-2 spike protein. In non-human primates, DCFHP-alum elicits neutralizing antibodies against all known VOCs that have emerged to date and SARS-CoV-1. During development of the DCFHP antigen, we investigated the incorporation of strain-specific mutations from the major VOCs that had emerged to date: D614G, Epsilon, Alpha, Beta, and Gamma. Here, we report the biochemical and immunological characterizations that led us to choose the ancestral Wuhan-1 sequence as the basis for the final DCFHP antigen design. Specifically, we show by size exclusion chromatography and differential scanning fluorimetry that mutations in the VOCs adversely alter the antigens structure and stability. More importantly, we determined that DCFHP without strain-specific mutations elicits the most robust, cross-reactive response in both pseudovirus and live virus neutralization assays. Our data suggest potential limitations to the variant-chasing approach in the development of protein nanoparticle vaccines, but also have implications for other approaches including mRNA-based vaccines.

biochemistry↗

Prediction of Heart Disease and Survivability using Support Vector Machine and Naive Bayes Algorithm

PurposeIn the present work, we examined the outcomes and accuracy of the Support vector machine (SVM) and the Naive Bayes algorithms on a dataset, to predict whether the patient has heart disease or not, and the patients survival prediction status. MethodThe machine learning procedures were developed using the clinically validated datasets with sixteen attributes from the University of California, Irvines Centre for Machine Learning, and Intelligent Systems. Confusion matrix was used to visualise the accuracy, recall, precision, and error of the models. Statistical analysis was done to prove the model accuracy using the receiver operating characteristic (ROC) curve and area under the curve (AUC). ResultsThe proposed method of heart disease prediction using Naive Bayes had 87 % accuracy. The accuracy for heart survivability models using SVM and Naive Bayes were 88 % and 93 %. The model efficiency for heart survivability using ROC curve with AUC 0.93 for Naive Bayes and AUC 0.91 for SVM. ConclusionSuch prediction systems can help the medical sector to save energy, cost, and time by providing more efficient techniques to forecast decisions with high accuracy. This study will enable the statisticians and researchers to select more efficient and accurate machine learning algorithms to achieve better prediction of the "cardiovascular disease".

bioinformatics↗

Formulation development and comparability studies with an aluminum-salt adjuvanted SARS-CoV-2 Spike ferritin nanoparticle vaccine antigen produced from two different cell lines

The development of safe and effective second-generation COVID-19 vaccines to improve affordability and storage stability requirements remains a high priority to expand global coverage. In this report, we describe formulation development and comparability studies with a self-assembled SARS-CoV-2 spike ferritin nanoparticle vaccine antigen (called DCFHP), when produced in two different cell lines and formulated with an aluminum-salt adjuvant (Alhydrogel, AH). Varying levels of phosphate buffer altered the extent and strength of antigen-adjuvant interactions, and these formulations were evaluated for their (1) in vivo performance in mice and (2) in vitro stability profiles. Unadjuvanted DCFHP produced minimal immune responses while AH-adjuvanted formulations elicited greatly enhanced pseudovirus neutralization titers independent of [~]100%, [~]40% or [~]10% of the DCFHP antigen adsorbed to AH. These formulations differed, however, in their in vitro stability properties as determined by biophysical studies and a competitive ELISA for measuring ACE2 receptor binding of AH-bound antigen. Interestingly, after one month of 4{degrees}C storage, small increases in antigenicity with concomitant decreases in the ability to desorb the antigen from the AH were observed. Finally, we performed a comparability assessment of DCFHP antigen produced in Expi293 and CHO cells, which displayed expected differences in their N-linked oligosaccharide profiles. Despite consisting of different DCFHP glycoforms, these two preparations were highly similar in their key quality attributes including molecular size, structural integrity, conformational stability, binding to ACE2 receptor and mouse immunogenicity profiles. Taken together, these studies support future preclinical and clinical development of an AH-adjuvanted DCFHP vaccine candidate produced in CHO cells.

immunology↗

A ferritin-based COVID-19 nanoparticle vaccine that elicits robust, durable, broad-spectrum neutralizing antisera in non-human primates

While the rapid development of COVID-19 vaccines has been a scientific triumph, the need remains for a globally available vaccine that provides longer-lasting immunity against present and future SARS-CoV-2 variants of concern (VOCs). Here, we describe DCFHP, a ferritin-based, protein-nanoparticle vaccine candidate that, when formulated with aluminum hydroxide as the sole adjuvant (DCFHP-alum), elicits potent and durable neutralizing antisera in non-human primates against known VOCs, including Omicron BQ.1, as well as against SARS-CoV-1. Following a booster [~]one year after the initial immunization, DCFHP-alum elicits a robust anamnestic response. To enable global accessibility, we generated a cell line that can enable production of thousands of vaccine doses per liter of cell culture and show that DCFHP-alum maintains potency for at least 14 days at temperatures exceeding standard room temperature. DCFHP-alum has potential as a once-yearly booster vaccine, and as a primary vaccine for pediatric use including in infants.

immunology↗

Designing epitope-focused vaccines via antigen reorientation

A major challenge in vaccine development, especially against rapidly evolving viruses, is the ability to focus the immune response toward evolutionarily conserved antigenic regions to confer broad protection. For example, while many broadly neutralizing antibodies against influenza have been found to target the highly conserved stem region of hemagglutinin (HA-stem), the immune response to seasonal influenza vaccines is predominantly directed to the immunodominant but variable head region (HA-head), leading to narrow-spectrum efficacy. Here, we first introduce an approach to controlling antigen orientation based on the site-specific insertion of short stretches of aspartate residues (oligoD) that facilitates antigen-binding to alum adjuvants. We demonstrate the generalizability of this approach to antigens from the Ebola virus, SARS-CoV-2, and influenza and observe enhanced antibody responses following immunization in all cases. Next, we use this approach to reorient HA in an "upside down" configuration, which we envision increases HA-stem exposure, therefore also improving its immunogenicity compared to HA-head. When applied to HA of H2N2 A/Japan/305/1957, the reoriented H2 HA (reoH2HA) on alum induced a stem-directed antibody response that cross-reacted with both group 1 and 2 influenza A HAs. Our results demonstrate the possibility and benefits of antigen reorientation via oligoD insertion, which represents a generalizable immunofocusing approach readily applicable for designing epitope-focused vaccine candidates. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=83 SRC="FIGDIR/small/521291v1_ufig1.gif" ALT="Figure 1"> View larger version (19K): org.highwire.dtl.DTLVardef@185f949org.highwire.dtl.DTLVardef@b132a9org.highwire.dtl.DTLVardef@174fcc8org.highwire.dtl.DTLVardef@17fb872_HPS_FORMAT_FIGEXP M_FIG C_FIG Seasonal influenza vaccines induce a biased antibody response against the variable head of hemagglutinin, whereas conserved epitopes on the stem are a target for universal vaccines. Here we show that reorienting HA in an "upside-down" configuration sterically occludes the head and redirects the antibody response to the more exposed stem, thereby inducing broad cross-reactivity against hemagglutinins from diverse influenza strains.

immunology↗

Human sperm TMEM95 binds eggs and facilitates membrane fusion

Tmem95 encodes a sperm acrosomal membrane protein, whose knockout has a male-specific sterility phenotype in mice. How TMEM95 plays a role in membrane fusion of sperm and eggs has remained elusive. Here, we utilize a sperm penetration assay as a model system to investigate the function of human TMEM95. We show that human TMEM95 binds to hamster egg membranes, providing evidence for a TMEM95 receptor on eggs. Using X-ray crystallography, we reveal an evolutionarily conserved, positively charged region of TMEM95 as a putative receptor-binding surface. Amino-acid substitutions within this region of TMEM95 ablate egg-binding activity. We identify monoclonal antibodies against TMEM95 that reduce the number of human sperm fused with hamster eggs in sperm penetration assays. Strikingly, these antibodies do not block binding of sperm to eggs. Taken together, these results provide strong evidence for a specific, receptor-mediated interaction of sperm TMEM95 with eggs and suggest that this interaction may have a role in facilitating membrane fusion. Significance statementMembrane fusion of sperm and eggs is pivotal in sexual reproduction. Tmem95 knockout mice show male-specific sterility, but it was unknown how sperm TMEM95 facilitates membrane fusion with eggs. We show here that human TMEM95 binds eggs. Our crystal structure of TMEM95 suggests a region where this binding may occur. We develop monoclonal antibodies against TMEM95 that impair sperm-egg fusion but do not block sperm-egg binding. Thus, we propose that there is a receptor-mediated interaction of sperm TMEM95 with eggs, and that this interaction may have a direct role in membrane fusion. Our work suggests avenues for the identification of the TMEM95 egg receptor and may enable the development of infertility treatments and contraceptives for humans.

developmental biology↗

A single immunization with spike-functionalized ferritin vaccines elicits neutralizing antibody responses against SARS-CoV-2 in mice

Development of a safe and effective SARS-CoV-2 vaccine is a public health priority. We designed subunit vaccine candidates using self-assembling ferritin nanoparticles displaying one of two multimerized SARS-CoV-2 spikes: full-length ectodomain (S-Fer) or a C-terminal 70 amino-acid deletion (S{Delta}C-Fer). Ferritin is an attractive nanoparticle platform for production of vaccines and ferritin-based vaccines have been investigated in humans in two separate clinical trials. We confirmed proper folding and antigenicity of spike on the surface of ferritin by cryo-EM and binding to conformation-specific monoclonal antibodies. After a single immunization of mice with either of the two spike ferritin particles, a lentiviral SARS-CoV-2 pseudovirus assay revealed mean neutralizing antibody titers at least 2-fold greater than those in convalescent plasma from COVID-19 patients. Additionally, a single dose of S{Delta}C-Fer elicited significantly higher neutralizing responses as compared to immunization with the spike receptor binding domain (RBD) monomer or spike ectodomain trimer alone. After a second dose, mice immunized with S{Delta}C-Fer exhibited higher neutralizing titers than all other groups. Taken together, these results demonstrate that multivalent presentation of SARS-CoV-2 spike on ferritin can notably enhance elicitation of neutralizing antibodies, thus constituting a viable strategy for single-dose vaccination against COVID-19.

immunology↗

Adaption of a Conventional ELISA to a 96-well ELISA-Array for Measuring the Antibody Responses to Influenza virus proteins, viruses and vaccines

We describe an adaptation of conventional ELISA methods to an ELISA-Array format using non-contact Piezo printing of up to 30 spots of purified recombinant viral fusion proteins, vaccine and virus on 96 well high-protein binding plates. Antigens were printed in 1 nanoliter volumes of protein stabilizing buffer using as little as 0.25 nanograms of protein, 2000-fold less than conventional ELISA. The performance of the ELISA-Array was demonstrated by serially diluting n=8 human post-flu vaccination plasma samples starting at a 1/1000 dilution and measuring binding to the array of Influenza antigens. Plasma polyclonal antibody levels were detected using a cocktail of biotinylated anti-human kappa and lambda light chain antibodies, followed by a Streptavidin-horseradish peroxidase conjugate and the dose-dependent signal was developed with a precipitable TMB substrate. Intra- and inter-assay precision of absorbance units among the eight donor samples showed mean CVs of 4.8% and 10.8%, respectively. The plasma could be differentiated by donor and antigen with titer sensitivities ranging from 1 x 103 to 4 x 106, IC50 values from 1 x 104 to 9 x 106, and monoclonal antibody sensitivities in the ng/mL range. Equivalent sensitivities of ELISA versus ELISA-Array, compared using plasma and an H1N1 HA trimer, were achieved on the ELISA-Array printed at 0.25ng per 200um spot and 1000ng per ELISA 96-well. Vacuum-sealed array plates were shown to be stable when stored for at least 2 days at ambient temperature and up to 1 month at 4-8{degrees}C. By the use of any set of printed antigens and analyte matrices the methods of this multiplexed ELISA-Array format can be broadly applied in translational research.

immunology↗