Biology subjects

Prasad, A.

Publications and source records attributed to Prasad, A..

At least 55 records · Page 3Linked to original sources

bioRxiv2023

High-affinity binding to the SARS-CoV-2 spike trimer by a nanostructured, trivalent protein-DNA synthetic antibody

Multivalency enables nanostructures to bind molecular targets with high affinity. Although IgG antibodies can be generated against a wide range of antigens, their shape and size cannot be tuned to match a given target. DNA nanotechnology provides an attractive approach for designing customized multivalent scaffolds due to the addressability and programmability of the nanostructure shape and size. Here, we use computational simulation to guide the design and synthesis of a DNA nanostructure-based synthetic antibody ("nano-synbody"). The nano-synbody is comprised of a three-helix bundle DNA nanostructure with three identical arms terminating in a mini-binder protein that targets the SARS-CoV-2 spike protein. The structure was designed to match the valence and distance between the three receptor binding domains (RBDs) in the spike trimer, in order to enhance binding through avidity effects. Moreover, the design allowed for the display of one, two, or three protein-displaying arms, thereby systematically probing the effect of multivalency on binding affinity. The binding strength of the nano-synbody increased with the increasing number of arms, yielding 11.2 pM affinity ([~]100-fold enhancement over monovalent binding) for the wild-type spike protein for the three-arm structure. Moreover, the multivalency was able to yield a 95 pM affinity for the Omicron variant, a mutant against which the monovalent protein was ineffective. The nano-synbody could also block infection of a spike protein-bearing pseudovirus, and similarly demonstrated effective inhibition of the Omicron variant when trimerized. The structure of the three-arm nano-synbody bound to the Omicron variant spike trimer was solved by negative-stain transmission electron microscopy reconstruction, and shows the protein-DNA nanostructure with all three arms bound to the RBD domains, confirming the intended trivalent attachment. Finally, nano-synbody binding could be reversed by removing one, two, or three arms in a programmable fashion, via toehold-mediated strand displacement. The ability to tune the size and shape of the nano-synbody, as well as its potential ability to attach (and then remove) two or more different binding ligands, will enable the high-affinity binding of a range of proteins, and pave the way towards their manipulation using DNA-based nano-robotic devices.

bioengineering↗

bioRxiv2023

Combined, yet Separate: cocktails of carriers (not drugs) for α-particle therapy of solid tumors expressing moderate-to-low levels of targetable markers

Alpha-particle radionuclide-antibody conjugates are being clinically evaluated against solid cancers expressing moderate levels of the targeted markers, with promising results. These findings are attributed to the high killing power of alpha-particles in spite of the expected decrease in antibody tumor uptake, that reduces tumor absorbed doses. However, when tumor absorbed doses are reduced, addressing the heterogeneities in delivery of alpha-particles within solid tumors (i.e. enabling uniform irradiation patterns) becomes critical: to maintain efficacy, the fewer alpha-particles delivered within tumors need to traverse/hit as many different cancer cells as possible. This proof-of-concept study describes an approach to complement the antibody- targeted radiotherapy by using a separate carrier to deliver a fraction of the injected radioactivity to tumor regions geographically different than those affected by the antibody; collectively, the two carriers should distribute the alpha-particle emitters, Actinium-225 in particular, more uniformly within tumors maintaining efficacy. MethodsWe monitored the extent(s) of tumor growth inhibition, onset delay of spontaneous metastases and/or survival on orthotopic MDA-MB-213 and MDA-MB-436 triple negative breast cancer mouse models and on an ectopic BxPC3 pancreatic cancer mouse model, treated systemically with the two separate carriers. Tumors were chosen to express different (but low) levels of HER1, utilized as a model antibody-targeted marker. ResultsIndependent of tumor origin and/or resistance to chemotherapy, the two separate carriers: (a) improved the primary tumor growth inhibition, (b) eliminated the formation of spontaneous metastases, and/or (c) prolonged survival, at lower or comparable tumor delivered doses relative to the antibody alone, without noticeable off-target toxicities. ConclusionThis tumor-agnostic strategy is timely and could be used to enhance the efficacy of existing alpha-particle radionuclide-antibody treatments without increasing, possibly even reducing, the total administered radioactivity.

bioengineering↗

bioRxiv2023

Amphibian segmentation clock models suggest mechanisms of slowed development across increasing genome size and nuclear volume

Evolutionary increases in genome size, cell volume, and nuclear volume have been observed across the tree of life, with positive correlations documented between all three traits. Developmental tempo slows as genomes, nuclei, and cells increase in size, yet the driving mechanisms are poorly understood. To bridge this gap, we use a mathematical model of the somitogenesis clock to link slowed developmental tempo with changes in intra-cellular gene expression kinetics induced by increasing genome size and nuclear volume. We adapt a well-known somitogenesis clock model to two model amphibian species that vary ten-fold in genome size: Xenopus laevis (3.2 Gb) and Ambystoma mexicanum (32 Gb). Based on simulations and backed by analytical derivations, we identify parameter changes originating from increased genome and nuclear size that slow gene expression kinetics. We simulate biological scenarios for which these parameter changes mathematically recapitulate slowed gene expression in A. mexicanum relative to X. laevis, and we consider scenarios for which additional alterations in gene product stability and chromatin packing are necessary. Results suggest that slowed degradation rates as well as changes induced by increasing nuclear volume, which remain relatively unexplored, are significant drivers of slowed developmental tempo.

developmental biology↗

bioRxiv2023

N-terminal targeting sequences and coding sequences act in concert to determine the localization and trafficking pathway of apicoplast proteins in Toxoplasma gondii.

Toxoplasma gondii has a relict plastid, the apicoplast, to which proteins are targeted after synthesis in the cytosol. Proteins exclusively found in the apicoplast use a Golgi-independent route for trafficking, while dually targeted proteins found in both the apicoplast and the mitochondrion use a Golgi-dependent route. For apicoplast targeting, N-terminal signal sequences have been shown to direct the localization of different reporters. In this study, we use chimeric proteins to dissect out the roles of N-terminal sequences and coding sequences in apicoplast localization and the choice of the trafficking route. We show that when the N-termini of a dually targeted protein, TgTPx1/2, or of an apicoplast protein, TgACP, are fused with the reporter protein, enhanced Green Fluorescent Protein (eGFP) or endogenous proteins, TgSOD2, TgSOD3, TgACP or TgTPx1/2, the chimeric proteins exhibit flexibility in apicoplast targeting depending on the coding sequences. Further, the chimeras that are localized to the apicoplast use different trafficking pathways depending on the combination of the N-terminal signals and the coding sequences. This report shows, for the first time, that in addition to the N-terminal signal sequences, targeting and trafficking signals also reside within the coding sequences of apicoplast proteins.

molecular biology↗

bioRxiv2023

SpatialView: An interactive web application forvisualization of multiple samples in spatialtranscriptomics experiments

Spatial transcriptomics (ST) experiments provide spatially localized measurements of genome-wide gene expression allowing for an unprecedented opportunity to investigate cellular heterogeneity and organization within a tissue. Statistical and computational frameworks exist that implement robust methods for pre-processing and analyzing data in ST experiments. However, the lack of an interactive suite of tools for visualizing ST data and results currently limits the full potential of ST experiments. To fill this gap, we developed SpatialView, an open-source web browser-based interactive application for visualizing data and results from multiple 10x Genomics ST experiments. We anticipate SpatialView will be useful to a broad array of clinical and basic science investigators utilizing ST to study disease. AvailabilitySpatialView is available at https://github.com/kendziorski-lab/SpatialView ; a demo application is available at https://www.biostat.wisc.edu/~kendzior/spatialviewdemo/ Contactcmohanty2@wisc.edu, ckendziorski@wisc.edu Supplementary informationSupplementary data are available at Bioinformatics online.

bioinformatics↗

bioRxiv2023

Using a Riemannian elastic metric for statistical analysis of tumor cell shape heterogeneity

We examine how a specific instance of the elastic metric, the Square Root Velocity (SRV) metric, can be used to study and compare cellular morphologies from the contours they form on planar surfaces. We process a dataset of images from osteocarcoma (bone cancer) cells that includes different treatments known to affect the cell morphology, and perform a comparative statistical analysis between the linear and SRV metrics. Our study indicates superior performance of the SRV at capturing the cell shape heterogeneity, with a better separation between different cell groups when comparing their distance to their mean shape, as well as a better low dimensional representation when comparing stress statistics. Therefore, our study suggests the use of a Riemannian metric, such as the SRV as a potential tool to enhance morphological discrimination for large datasets of cancer cell images.

cell biology↗

bioRxiv2023

Feeder-Free Generation of Endocardial and Cardiac Valve Cells from Human Pluripotent Stem Cells

Valvular heart disease presents a significant health burden, yet advancements in valve biology and novel therapeutics have been hindered by the lack of accessibility to human valve cells. In this study, we have developed a scalable and feeder-free method to differentiate human induced pluripotent stem cells (iPSCs) into endocardial cells. Importantly, we show that these endocardial cells are transcriptionally and phenotypically distinct from vascular endothelial cells and can be directed to undergo endothelial-to-mesenchymal transition (EndMT) to generate cardiac valve cell populations. Following this, we identified two distinct populations--one population undergoes EndMT to become valvular interstitial cells (VICs), while the other population reinforces their endothelial identity to become valvular endothelial cells (VECs). Lastly, we confirmed the identities of our iPSC-derived cell populations and identified putative markers through transcriptomic analyses. By increasing the accessibility to these cell populations, we aim to accelerate discoveries for cardiac valve biology and disease.

cell biology↗

bioRxiv2023

Orthogonal outlier detection and dimension estimation for improved MDS embedding of biological datasets

Conventional dimensionality reduction methods like Multidimensional Scaling (MDS) are sensitive to the presence of orthogonal outliers, leading to significant defects in the embedding. We introduce a robust MDS method, called DeCOr-MDS (Detection and Correction of Orthogonal outliers using MDS), based on the geometry and statistics of simplices formed by data points, that allows to detect orthogonal outliers and subsequently reduce dimensionality. We validate our methods using synthetic datasets, and further show how it can be applied to a variety of large real biological datasets, including cancer image cell data and human microbiome project data.

bioinformatics↗

bioRxiv2022

Aedes aegypti eggs use rewired polyamine and lipid metabolism to survive extreme desiccation

Upon extreme water loss, some organisms pause their life cycles and escape death, in a process called anhydrobiosis. While widespread in microbes, this is uncommon in animals. Mosquitoes of the Aedes genus are vectors for several viral diseases in humans. These mosquitoes lay eggs that survive extreme desiccation and this property greatly enhances geographical expansion of these insects. The molecular principles of egg survival and hatching post-desiccation in these insects remain obscure. In this report, we find that eggs of Aedes aegypti, in contrast to those of Anopheles stephensi, are true anhydrobiotes. Aedes embryos acquire desiccation tolerance at a late developmental stage. We uncover unique proteome-level changes in Aedes embryos during desiccation. These changes reflect a metabolic state with reduced central carbon metabolism, and precise rewiring towards polyamine production, altered lipid levels and enhanced lipid utilization for energy. Using inhibitor-based approaches targeting these processes in blood-fed mosquitoes that lay eggs, we infer a two-step process of anhydrobiosis in Aedes eggs, where polyamine accumulation as well as lipid breakdown confer desiccation tolerance, and rapid lipid breakdown fuels energetic requirements enabling the revival of mosquito larvae post rehydration.

biochemistry↗

bioRxiv2022

Exact distribution of the vesicle burst size in synaptic transmission

During electro-chemical signal transmission through synapses, triggered by an action potential (AP), a stochastic number of synaptic vesicles (SV), called the quantal content, release neurotransmitters in the synaptic cleft. It is widely accepted that the quantal content probability distribution is a binomial based on the number of ready-release SVs in the pre-synaptic terminal. But the latter number itself fluctuates due to its stochastic replenishment, hence the actual distribution of quantal content is unknown. We show that exact distribution of quantal content can be derived for general stochastic AP inputs in the steady-state. For fixed interval AP train, we prove that the distribution is a binomial, and corroborate our predictions by comparison with electrophysiological recordings from MNTB-LSO synapses of juvenile mice. For a Poisson train, we show that the distribution is non-binomial. Moreover, we find exact moments of the quantal content in the Poisson and other general cases, which may be used to obtain the model parameters from experiments.

biophysics↗

bioRxiv2022

Deep divergence and genomic diversification of gut symbionts of neotropical stingless bees

Social bees harbor conserved gut microbiota that may have been acquired in a common ancestor of social bees and subsequently co-diversified with their hosts. However, most of this knowledge is based on studies on the gut microbiota of honey bees and bumble bees. Much less is known about the gut microbiota of the third and most diverse group of social bees, the stingless bees. Specifically, the absence of genomic data from their microbiota presents an important knowledge gap in understanding the evolution and functional diversity of the social bee microbiota. Here we combined community profiling with culturing and genome sequencing of gut bacteria from six neotropical stingless bee species from Brazil. Phylogenomic analyses show that most stingless bee gut isolates form deep-branching sister clades of core members of the honey bee and bumble bee gut microbiota with conserved functional capabilities, confirming the common ancestry and ecology of their microbiota. However, our bacterial phylogenies were not congruent with those of the host indicating that the evolution of the social bee gut microbiota was not driven by strict co-diversification, but included host switches and independent symbiont gain and losses. Finally, as reported for the honey bee and bumble bee microbiota, we find substantial genomic divergence among strains of stingless bee gut bacteria suggesting adaptation to different host species and glycan niches. Our study offers first insights into the genomic diversity of the stingless bee microbiota, and highlights the need for broader samplings to understand the evolution of the social bee gut microbiota. ImportanceStingless bees are the most diverse group of the corbiculate bees and represent important pollinator species throughout the tropics and subtropics. They harbor specialized microbial communities in their gut that are related to those found in honey bees and bumble bees and that are likely important for bee health. Few bacteria have been cultured from the gut of stingless bees which has prevented characterization of their genomic diversity and functional potential. Here, we established cultures of major community members of the gut microbiota of six stingless bee species and sequenced their genomes. We find that most stingless bee isolates belong to novel bacterial species distantly related to those found in honey bees and bumble bees and encoding similar functional capabilities. Our study offers a new perspective on the evolution of the social bee gut microbiota and presents the basis to characterize the symbiotic relationships between gut bacteria and stingless bees.

microbiology↗

bioRxiv2022

SpatialCorr: Identifying Gene Sets with Spatially Varying Correlation Structure

Recent advances in spatially resolved transcriptomics technologies enable both the measurement of genome-wide gene expression profiles and their mapping to spatial locations within a tissue. A first step in spatial transcriptomics data analysis is identifying genes with expression that varies spatially, and robust statistical methods exist to address this challenge. While useful, these methods do not detect spatial changes in the coordinated expression within a group of genes. To this end, we present SpatialCorr, a method for identifying sets of genes with spatially varying correlation structure. Given a collection of gene sets pre-defined by a user, SpatialCorr tests for spatially induced differences in the correlation of each gene set within tissue regions, as well as between and among regions. An application to cutaneous squamous cell carcinoma demonstrates the power of the approach for revealing biological insights not identified using existing methods.

bioinformatics↗

bioRxiv2022

Assessing functional connectivity differences and work-related fatigue in surviving COVID-negative patients.

The Coronavirus Disease 2019 (COVID-19) has affected all aspects of life around the world. Neuroimaging evidence suggests the novel coronavirus can attack the central nervous system (CNS), causing cerebro-vascular abnormalities in the brain. This can lead to focal changes in cerebral blood flow and metabolic oxygen consumption rate in the brain. However, the extent and spatial locations of brain alterations in COVID-19 survivors are largely unknown. In this study, we have assessed brain functional connectivity (FC) using resting-state functional MRI (RS-fMRI) in 38 (25 males) COVID patients two weeks after hospital discharge, when PCR negative and 31 (24 males) healthy subjects. FC was estimated using independent component analysis (ICA) and dual regression. When compared to the healthy group, the COVID group demonstrated significantly enhanced FC in the basal ganglia and precuneus networks (family wise error (fwe) corrected, pfwe < 0.05), while, on the other hand, reduced FC in the language network (pfwe < 0.05). The COVID group also experienced higher fatigue levels during work, compared to the healthy group (p < 0.001). Moreover, within the precuneus network, we noticed a significant negative correlation between FC and fatigue scores across groups (Spearmans {rho} = - 0.47, p = 0.001, r2 = 0.22). Interestingly, this relationship was found to be significantly stronger among COVID survivors within the left parietal lobe, which is known to be structurally and functionally associated with fatigue in other neurological disorders. Significance StatementEarly neuroimaging studies have mostly focused on structural MRI imaging to report brain abnormalities in acutely ill COVID-19 patients. It is not clear whether functional abnormalities co-exist with structural alterations in patients who have survived the infection and have been discharged from the hospital. A few recent studies have emerged which attempted to address the structural/functional alterations. However, further investigations across different sites are necessary for more conclusive inference. More importantly, fatigue is a highly prevalent symptom among COVID survivors, therefore, the relations of brain imaging abnormalities to fatigue should be investigated. In this study, we try to address these gaps, by collecting imaging data from COVID survivors, now PCR negative, and healthy subjects from a single site - the Indian Institute of Technology (IIT), Delhi, India. Furthermore, this is a continuation of an ongoing study. We have recently shown structural abnormalities and stronger gray matter volume (GMV) correlates of self-reported fatigue in this group of COVID survivors compared to healthy subjects (Hafiz et al., 2022).

neuroscience↗

bioRxiv2021

Exact distribution of threshold-crossing times for protein concentrations: Implication for biological timekeeping

Stochastic transcription and translation dynamics of protein accumulation up to some concentration threshold sets the timing of many cellular physiological processes. Here we obtain the exact distribution of first threshold-crossing times of protein concentration, in either Laplace or time domain, and its associated cumulants: mean, variance and skewness. The distribution is asymmetric and its skewness non-monotonically varies with the threshold. We study lysis times of E-coli cells for holin gene mutants of bacteriophage-{lambda} and find a good match with theory. Mutants requiring higher holin thresholds show more skewed lysis time distributions as predicted.

biophysics↗

bioRxiv2021

SpotClean adjusts for spot swapping in spatial transcriptomics data

Spatial transcriptomics (ST) is a powerful and widely-used approach for profiling genome-wide gene expression across a tissue with emerging applications in molecular medicine and tumor diagnostics. Recent spatial transcriptomics experiments utilize slides containing thousands of spots with spot-specific barcodes that bind mRNA. Ideally, unique molecular identifiers at a spot measure spot-specific expression, but this is often not the case owing to bleed from nearby spots, an artifact we refer to as spot swapping. We propose SpotClean to adjust for spot swapping and, in doing so, to increase the sensitivity and precision with which downstream analyses are conducted.

genomics↗

bioRxiv2021

Evaluating the role of reference-genome phylogenetic distance on evolutionary inference

When a high-quality genome assembly of a target species is unavailable, an option to avoid the costly de novo assembly process is a mapping-based assembly. However, mapping shotgun data to a distant relative may lead to biased or erroneous evolutionary inference. Here, we used short-read data from a mammal and a bird species (beluga and rowi kiwi) to evaluate whether reference genome phylogenetic distance can impact downstream demographic (PSMC) and genetic diversity (heterozygosity, runs of homozygosity) analyses. We mapped to assemblies of species of varying phylogenetic distance (conspecific to genome-wide divergence of >7%), and de novo assemblies created using cross-species scaffolding. We show that while reference genome phylogenetic distance has an impact on demographic analyses, it is not pronounced until using a reference genome with >3% divergence from the target species. When mapping to cross-species scaffolded assemblies, we are unable to replicate the original beluga demographic analyses, but can with the rowi kiwi, presumably reflecting the more fragmented nature of the beluga assemblies. As for genetic diversity estimates, we find that increased phylogenetic distance has a pronounced impact; heterozygosity estimates deviate incrementally as phylogenetic distance increases. Moreover, runs of homozygosity are removed when mapping to any non-conspecific assembly. However, these biases can be reduced when mapping to a cross-species scaffolded assembly. Taken together, our results show that caution should be exercised when selecting the reference genome for mapping assemblies. Cross-species scaffolding may offer a way to avoid a costly, traditional de novo assembly, while still producing robust, evolutionary inference.

evolutionary biology↗

bioRxiv2021

Coupled myovascular expansion directs growth and regeneration of the neonatal mouse heart

BackgroundHeart regeneration requires multiple cell types to enable cardiomyocyte (CM) proliferation. How these cells interact to create growth niches is unclear. Here we profile proliferation kinetics of cardiac endothelial cells (CECs) and CMs in the neonatal mouse heart and find that they are spatiotemporally coupled. Methods and ResultsWe show that coupled myovascular expansion during cardiac growth or regeneration is dependent upon VEGF-VEGFR2 signaling, as genetic deletion of Vegfr2 from CECs or inhibition of VEGFA abrogates both CEC and CM proliferation. Repair of cryoinjury displays poor spatial coupling of CEC and CM proliferation. Boosting CEC density after cryoinjury with virus encoding Vegfa enhances regeneration. Using Mendelian randomization, we demonstrate that circulating VEGFA levels are positively linked with human myocardial mass, suggesting that Vegfa can stimulate human cardiac growth. ConclusionsOur work demonstrates the importance of coupled CEC and CM expansion and reveals a myovascular niche that may be therapeutically targeted for heart regeneration.

developmental biology↗

bioRxiv2020

The Protein Hourglass: Exact First Passage Time Distributions for Protein Thresholds

Protein thresholds have been shown to act as an ancient timekeeping device, such as in the time to lysis of E. coli infected with bacteriophage lambda. The time taken for protein levels to reach a particular threshold for the first time is defined as the first passage time of the protein synthesis system, which is a stochastic quantity. The first few moments of the distribution of first passage times were known earlier, but an analytical expression for the full distribution was not available. In this work, we derive an analytical expression for the first passage times for a long-lived protein. This expression allows us to calculate the full distribution not only for cases of no self-regulation, but also for both positive and negative self-regulation of the threshold protein. We show that the shape of the distribution matches previous experimental data on lambda-phage lysis time distributions. We also provide analytical expressions for the FPT distribution with non-zero degradation in Laplace space. Furthermore, we study the noise in the precision of the first passage times described by coefficient of variation (CV) of the distribution as a function of the protein threshold value. We show that under conditions of positive self-regulation, the CV declines monotonically with increasing protein threshold, while under conditions of linear negative self-regulation, there is an optimal protein threshold that minimizes the noise in the first passage times.

biophysics↗