Biology subjects

Bansal, S.

Publications and source records attributed to Bansal, S..

At least 37 records · Page 2Linked to original sources

bioRxiv2023

Qualitatively different delay-dependent working memory distortions in people with schizophrenia and healthy control subjects

BackgroundImpairments in working memory(WM) have been well-documented in people with schizophrenia(PSZ). However, these quantitative WM impairments can often be explained by nonspecific factors, such as impaired goal maintenance. Here, we used a spatial orientation delayed-response task to explore a qualitative difference in WM dynamics between PSZ and healthy control subjects(HCS). Specifically, we took advantage of the discovery that WM representations may drift either toward or away from previous-trial targets(serial dependence). We tested the hypothesis that WM representations drift toward the previous-trial target in HCS but away from the previous-trial target in PSZ. MethodsWe assessed serial dependence in PSZ(N=31) and HCS(N=25), using orientation as the to-be-remembered feature and memory delays from 0 to 8s. Participants were asked to remember the orientation of a teardrop-shaped object and reproduce the orientation after a varying delay period. ResultsConsistent with prior studies, we found that current-trial memory representations were less precise in PSZ than in HCS. We also found that WM for the current-trial orientation drifted toward the previous-trial orientation in HCS(representational attraction) but drifted away from the previous-trial orientation in PSZ(representational repulsion). ConclusionsThese results demonstrate a qualitative difference in WM dynamics between PSZ and HCS that cannot easily be explained by nuisance factors such as reduced effort. Most computational neuroscience models also fail to explain these results, because they maintain information solely by means of sustained neural firing, which does not extend across trials. The results suggest a fundamental difference between PSZ and HCS in longer-term memory mechanisms that persist across trials, such as short-term potentiation and neuronal adaptation.

neuroscience↗

bioRxiv2023

KLRG1 marks tumor-infiltrating CD4 T cell subsets associated with tumor progression and immunotherapy response

Current methods for biomarker discovery and target identification in immuno-oncology rely on static snapshots of tumor immunity. To thoroughly characterize the temporal nature of antitumor immune responses, we developed a 34-parameter spectral flow cytometry panel and performed high-throughput analyses in critical contexts. We leveraged two distinct preclinical models that recapitulate cancer immunoediting (NPK-C1) and immune checkpoint blockade (ICB) response (MC38), respectively, and profiled multiple relevant tissues at and around key inflection points of immune surveillance and escape and/or ICB response. Machine learning-driven data analysis revealed a pattern of KLRG1 expression that uniquely identified intratumoral effector CD4 T cell populations that constitutively associate with tumor burden across tumor models, and are lost in tumors undergoing regression in response to ICB. Similarly, a Helios-KLRG1 + subset of tumor-infiltrating regulatory T cells (Tregs) was associated with tumor progression from immune equilibrium to escape, and were also lost in tumors responding to ICB. Validation studies confirmed KLRG1 signatures in human tumorinfiltrating CD4 T cells associate with disease progression in renal cancer. These findings nominate KLRG1+ CD4 T cell populations as subsets for further investigation in cancer immunity and demonstrate the utility of longitudinal spectral flow profiling as an engine of dynamic biomarker and/or target discovery.

immunology↗

bioRxiv2022

Pathogen transmission modes determine contact network structure, altering other pathogen characteristics

Pathogen traits can vary greatly and impact the ability of a pathogen to persist in a population. Although this variation is fundamental to disease ecology, little is known about the evolutionary pressures that drive these differences, particularly where they interact with host behavior. We hypothesized that host behaviors relevant to different transmission routes give rise to differences in contact network structure, constraining the space over which pathogen traits can evolve to maximize fitness. Our analysis of 232 contact networks across mammals, birds, reptiles, amphibians, arthropods, fish, and mollusks found that contact network topology varies by contact events, most notably in networks that are representative of fluid-exchange transmission. Using infectious disease model simulations, we showed that these differences in network structure suggest pathogens transmitted through fluid-exchange contact events will need traits associated with high transmissibility to successfully proliferate, compared to pathogens that transmit through other types of contact. These findings were supported through a review of known traits of pathogens that transmit in humans. Our work demonstrates that contact network structure may drive the evolution of compensatory pathogen traits according to transmission strategy, providing essential context for understanding pathogen evolution and ecology.

evolutionary biology↗

bioRxiv2022

Borrowing ecological theory to infer interactions between sensitive and resistant breast cancer cell populations

While some forms of breast cancer are highly responsive to treatment, endocrine therapy-resistant breast cancers are disproportionately lethal. There has been significant progress in understanding how endocrine therapy-resistant strains evolve from therapy-susceptible strains of cancer, but little is understood about the proliferation of resistance through cancer cell populations, or the interactions that occur between populations of resistant and sensitive cells. In this study, we characterize the nature of the ecological interaction between populations of resistant and susceptible breast cancer cells to reveal novel methods of controlling drug resistance. Using in-vitro data on fluorescent-tagged resistant and susceptible cells, we use an image processing algorithm to identify and count cell growth till equilibrium. We then borrow theory from population biology to infer the type of ecological interaction that occurs between populations of resistant and sensitive cells. In particular, we use a Bayesian approach to fit single culture cell populations to infer density-dependent growth parameters (growth rate, carrying capacity) and a Generalized Lotka-Volterra model to understand how susceptible and resistant co-culture populations may be depressing or supporting growth of the other. Our results identify a net mutualistic interaction between the susceptible and resistant cancer strains, demonstrating that there are ecological dynamics to cancer resistance. Our findings also suggest that ecological dynamics change in the presence of therapy, and that an adaptive treatment protocol can induce cycling behavior suggesting that heterogeneous ecological effects contribute to empirically observed adaptive-therapeutic dynamics.

cell biology↗

bioRxiv2022

An optimized method for the isolation of urinary extracellular vesicles for molecular phenotyping: detection of biomarkers for radiation exposure

BackgroundUrinary extracellular vesicles (EVs) are a source of biomarkers with broad potential applications across clinical research, including monitoring radiation exposure. A key limitation to their implementation is minimal standardization in EV isolation and analytical analysis methods. Further, most urinary EV isolation protocols necessitate large volumes of sample. This study aimed to compare and optimize isolation and analytical methods for EVs from small volumes of urine. Methods3 EV isolation methods were compared: ultracentrifugation, magnetic bead-based, and size-exclusion chromatography from 0.5 mL or 1 mL of rat and human urine. EV yield and mass spectrometry signals (Q-ToF and Triple Quad) were evaluated from each method. Metabolomic profiling was performed on EVs isolated from the urine of rats exposed to ionizing radiation 1-, 14-, 30- or 90-days post-exposure, and human urine from patients receiving thoracic radiotherapy for the treatment of lung cancer pre- and post-treatment. ResultsSize-exclusion chromatography is the preferred method for EV isolation from 0.5 mL of urine. Mass spectrometry-based metabolomic analyses of EV cargo identified biochemical changes induced by radiation, including altered nucleotide, folate, and lipid metabolism. We have provided standard operating procedures for implementation of these methods in other laboratories. ConclusionsWe demonstrate that EVs can be isolated from small volumes of urine and analytically investigated for their biochemical contents to detect radiation induced metabolomic changes. These findings lay a groundwork to develop future methods to monitor response to radiotherapy and can be extended to an array of molecular phenotyping studies aimed at characterizing EV cargo.

cancer biology↗

bioRxiv2022

A cellular hierarchy framework for understanding heterogeneity and predicting drug response in AML

The treatment landscape of AML is evolving with promising therapies entering clinical translation, yet patient responses remain heterogeneous and biomarkers for tailoring treatment are lacking. To understand how disease heterogeneity links with therapy response, we determined the leukemia cell hierarchy make-up from bulk transcriptomes of over 1000 patients through deconvolution using single-cell reference profiles of leukemia stem, progenitor, and mature cell types. Leukemia hierarchy composition was associated with functional, genomic, and clinical properties and converged into four overall classes, spanning Primitive, Mature, GMP, and Intermediate. Critically, variation in hierarchy composition along the Primitive vs GMP or Primitive vs Mature axes were associated with response to chemotherapy or drug sensitivity profiles of targeted therapies, respectively. A 7-gene biomarker derived from the Primitive vs Mature axis was predictive of patient response to 105 investigational drugs. Thus, hierarchy composition constitutes a novel framework for understanding disease biology and advancing precision medicine in AML.

cancer biology↗

bioRxiv2021

NAD metabolism modulates mitochondrial function and inflammation and prevents progression of diabetic kidney disease

Diabetes mellitus is the leading cause of cardiovascular and renal disease in the United States. In spite of the beneficial interventions available for patients with diabetes, there remains a need for additional therapeutic targets and therapies in diabetic kidney disease (DKD). Inflammation and oxidative stress are increasingly recognized as important causes of renal diseases. Inflammation is closely associated with mitochondrial damage. The molecular connection between inflammation and mitochondrial metabolism remains to be elucidated. Recently, nicotinamide adenine nucleotide (NAD+) metabolism has been found to regulate immune function and inflammation. In the present studies we tested the hypothesis that enhancing NAD metabolism could prevent inflammation in and progression of DKD. We found that treatment of db/db mice with type 2 diabetes with nicotinamide riboside (NR) prevented several manifestations of kidney dysfunction (i.e., albuminuria, increased urinary kidney injury marker-1 (KIM1) excretion and pathologic changes). These effects were associated with decreased inflammation, at least in part via inhibiting the activation of the cyclic GMP-AMP synthase-stimulator of interferon genes (cGAS-STING) signaling pathway. An antagonist of the serum stimulator of interferon genes (STING) and whole-body STING deletion in diabetic mice showed similar renoprotection. Further analysis found that NR increased SIRT3 activity and improved mitochondrial function, which led to decreased mitochondrial DNA damage, a trigger for mitochondrial DNA leakage which activates the cGAS-STING pathway. Overall, these data show that NR supplementation boosted NAD metabolism to augment mitochondrial function, reducing inflammation and thereby preventing progression of diabetic kidney disease.

pathology↗

bioRxiv2021

The epidemiology and genomics of a virulent emerging fungal pathogen in an Australian reptile

Emerging infectious fungal diseases (EIFDs) represent a major conservation concern worldwide. Here, we provide early insights into the potential threat that Nannizziopsis barbatae (Nb), a novel EIFD, poses to Australian herpetological biodiversity. First known to the reptile pet trade as a primary pathogen causing untreatable severe dermatomycosis, since 2013, Nb has emerged in a growing number of phylogenetically and ecologically distant free-living reptiles across Australia. Observing its emergence in a long-term study population of wild eastern water dragons (Intellagama lesueurii), we demonstrate the pathogens virulence-related genomic features, within-population spatiotemporal spread, and survival costs, all of which imply that Nb could pose a threat to Australian reptiles in the future. Our findings highlight the need to closely monitor this pathogen in Australian ecosystems.

ecology↗

bioRxiv2021

A multi-omics approach identifies pancreatic cancer cell extracellular vesicles as mediators of the unfolded protein response in normal pancreatic epithelial cells.

Although cancer-derived extracellular vesicles (cEVs) are thought to play a pivotal role in promoting cancer progression events, their precise effect on neighboring normal cells is unknown. In this study, we investigated the impact of pancreatic cancer ductal adenocarcinoma (PDAC) derived EVs on recipient non-tumorigenic pancreatic normal epithelial cells upon internalization. We show that PDAC cEVs increase the proliferation and invasive capability of treated normal cells. We further demonstrate that cEVs induce endoplasmic reticulum (ER) stress and the unfolded protein response (UPR) in treated normal pancreatic epithelial cells within 24 hours. Subsequently, these cells release several inflammatory cytokines. Leveraging a layered multi-omics approach, we analyzed EV cargo from a panel of 6 PDAC and 2 normal pancreas cell lines, using multiple EV isolation methods. We found that cEVs were enriched for an array of biomolecules which can induce or regulate ER stress and the UPR, including palmitic acid, sphingomyelins, metabolic regulators of tRNA charging and proteins which regulate trafficking and degradation. We further show that palmitic acid, at doses relevant to those found in cEVs, is sufficient to induce ER stress in normal pancreas cells. These results suggest that cEV cargo packaging may be designed to disseminate proliferative and invasive characteristics upon internalization by distant recipient normal cells, hitherto unreported. This study is among the first to highlight a major role for PDAC cEVs to induce stress in treated normal pancreas cells that may modulate a systemic response leading to altered phenotypes. For the first time, our study implicates cEV transported palmitic acid as a potential driver in this process. These findings highlight the importance of EVs in mediating disease etiology and open potential areas of investigation toward understanding the role of cEV lipids in promoting cell transformation in the surrounding microenvironment.

cancer biology↗

bioRxiv2021

High-sensitivity detection of facial features on MRI brain scans with a convolutional network

Platforms and institutions that support MRI data sharing need to ensure that identifiable facial features are not present in shared images. Currently, this assessment requires manual effect as no auto-mated tools exist that can efficiently and accurately detect if an image has been "defaced". The scarcity of publicly available data with pre-served facial features, as well as the meager incentives to create such a cohort privately, have averted the development of face-detection models. Here, we introduce a framework to detect whether an input MRI brain scan has been defaced, with the ultimate goal of streamlining it within the submission protocols of MRI data archiving and sharing platforms. We present a binary (defaced/"nondefaced") classifier based on a custom convolutional neural network architecture. We train the model on 980 de-faced MRI scans from 36 different studies that are publicly available at OpenNeuro.org. To overcome the unavailability of nondefaced examples, we augment the dataset by inpainting synthetic faces into each training image. We show the adequacy of such a data augmentation in a cross-validation evaluation. We demonstrate the performance estimated with cross-validation matches that of an evaluation on a held-out dataset (N =581) preserving real faces, and obtain accuracy/sensitivity/speci-ficity scores of 0.978/0.983/0.972, respectively. Data augmentations are key to boosting the performance of models bounded by limited sample sizes and insufficient diversity. Our model contributes towards developing classifiers with[~] 100% sensitivity detecting faces, which is crucial to ensure that no identifiable data are inadvertently made public.

neuroscience↗

bioRxiv2020

Development of A Decellularized Meniscus Matrix-Based Nanofibrous Scaffold for Meniscus Tissue Engineering

The meniscus plays a critical role in knee mechanical function but is commonly injured given its central load bearing role. In the adult, meniscus repair is limited, given the low number of endogenous cells, the density of the matrix, and the limited vascularity. Menisci are fibrocartilaginous tissues composed of a micro-/nano-fibrous extracellular matrix (ECM) and a mixture of chondrocyte-like and fibroblast-like cells. Here, we developed a fibrous scaffold system that consists of bioactive components (decellularized meniscus ECM (dME) within a poly(e-caprolactone) material) fashioned into a biomimetic morphology (via electrospinning) to support and enhance meniscus cell function and matrix production. This work supports that the incorporation of dME into synthetic nanofibers increased hydrophilicity of the scaffold, leading to enhanced meniscus cell spreading, proliferation, and fibrochondrogenic gene expression. This work identifies a new biomimetic scaffold for therapeutic strategies to substitute or replace injured meniscus tissue. STATEMENT OF SIGNIFICANCEIn this study, we show that a scaffold electrospun from a combination of synthetic materials and bovine decellularized meniscus ECM provides appropriate signals and a suitable template for meniscus fibrochondrocyte spreading, proliferation, and secretion of collagen and proteoglycans. Material characterization and in vitro cell studies support that this new bioactive material is susceptible to enzymatic digestion and supports meniscus-like tissue formation.

bioengineering↗

bioRxiv2020

PRAK-03202: A triple antigen VLP vaccine candidate against SARS CoV-2

The rapid development of safe and effective vaccines against SARS CoV-2 is the need of the hour for the coronavirus outbreak. Here, we have developed PRAK-03202, the worlds first triple antigen VLP vaccine candidate in a highly characterized S. cerevisiae-based D-CryptTM platform, which induced SARS CoV-2 specific neutralizing antibodies in BALB/c mice. Immunizations using three different doses of PRAK-03202 induces antigen specific (Spike, envelope and membrane proteins) humoral response and neutralizing potential. PBMCs from convalescent patients, when exposed to PRAK-03202, showed lymphocyte proliferation and elevated IFN-{gamma} levels suggestive of conservation of epitopes and induction of T helper 1 (Th1)-biased cellular immune responses. These data support the clinical development and testing of PRAK-03202 for use in humans.

immunology↗

bioRxiv2020

Fine-scale spatial patterns of wildlife disease are common and understudied

O_LIAll parasites are heterogeneous in space, yet little is known about the prevalence and scale of this spatial variation, particularly in wild animal systems. To address this question, we sought to identify and examine spatial dependence of wildlife disease across a wide range of systems. C_LIO_LIConducting a broad literature search, we collated 31 such datasets featuring 89 replicates and 71 unique host-parasite combinations, only 51% of which had previously been used to test spatial hypotheses. We analysed these datasets for spatial dependence within a standardised modelling framework using Bayesian linear models, and we then meta-analysed the results to identify generalised determinants of the scale and magnitude of spatial autocorrelation. C_LIO_LIWe detected spatial autocorrelation in 48/89 model replicates (54%) across 21/31 datasets (68%), spread across parasites of all groups. Even some very small study areas (under 0.01km2) exhibited substantial spatial variation. C_LIO_LIDespite the common manifestation of spatial variation, our meta-analysis was unable to identify host-, parasite-, or sampling-level determinants of this heterogeneity across systems. Parasites of all transmission modes had easily detectable spatial patterns, implying that structured contact networks and susceptibility effects are potentially as important in spatially structuring disease as are environmental drivers of transmission efficiency. C_LIO_LIOur findings demonstrate that fine-scale spatial patterns of infection manifest frequently and across a range of wild animal systems, and many studies are able to investigate them whether or not the original aim of the study was to examine spatially varying processes. Given the widespread nature of these findings, studies should more frequently record and analyse spatial data, facilitating development and testing of spatial hypotheses in disease ecology. Ultimately, this may pave the way for an a priori predictive framework for spatial variation in novel host-parasite systems. C_LI

ecology↗

bioRxiv2020

miR-125-chinmo pathway regulates dietary restriction dependent enhancement of lifespan in Drosophila

Dietary restriction (DR) extends healthy lifespan in diverse species. Age and nutrient-related changes in the abundance of microRNAs (miRNAs) and their processing factors have been linked to organismal longevity. However, the mechanisms by which they modulate lifespan and the tissue-specific role of miRNA mediated networks in DR dependent enhancement of lifespan remains largely unexplored. We show that two neuronally enriched and highly conserved microRNAs, miR-125 and let-7 mediate the DR response in Drosophila melanogaster. Functional characterization of miR-125 demonstrates its role in neurons while its target chinmo acts both in neurons and the fat body to modulate fat metabolism and longevity. Proteomic analysis revealed that Chinmo exerts its DR effects by regulating expression of FATP, CG2017, CG9577, CG17554, CG5009, CG8778, CG9527 and FASN1. Our findings identify miR-125 as a conserved effector of DR pathway and open up the avenue for this small RNA molecule and its downstream effectors to be considered as potential drug candidates for treatment of late-onset diseases and biomarkers for healthy aging in humans.

molecular biology↗

bioRxiv2020

Iota carrageenan and xylitol inhibit SARS-CoV-2 in Vero cell culture

COVID-19 (coronavirus disease 2019) is a pandemic caused by SARS-CoV-2 (severe acute respiratory syndrome-coronavirus 2) infection affecting millions of persons around the world. There is an urgent unmet need to provide an easy-to-produce, affordable medicine to prevent transmission and provide early treatment for this disease. The nasal cavity and the rhinopharynx are the sites of initial replication of SARS-CoV-2. Therefore, a nasal spray may be a suitable dosage form for this purpose. The main objective of our study was to test the antiviral action of three candidate nasal spray formulations against SARS-CoV-2. We have found that iota-carrageenan in concentrations as low as 6 {micro}g/ mL inhibits SARS-CoV-2 infection in Vero cell cultures. The concentrations found to be active in vitro against SARS-CoV-2 may be easily achieved by the application of nasal sprays already marketed in several countries. Xylitol at a concentration of 5 % m/V has proved to be viricidal on its own and the association with iota-carrageenan may be beneficial, as well.

pharmacology and toxicology↗

bioRxiv2020

Negative density-dependent parasitism in a group-living carnivore

Animals living at high population densities commonly experience greater exposure to disease, leading to increased parasite burdens. However, social animals can benefit immunologically and hygienically from cooperation, and individuals may alter their socio-spatial behaviour in response to infection, both of which could counteract density-related increases in exposure. Consequently, the costs and benefits of sociality for disease are often uncertain. Here, we use a long-term study of a wild European badger population (Meles meles) to investigate how within-population variation in host density determines infection with multiple parasites. Four out of five parasite taxa exhibited consistent spatial hotspots of infection, which peaked among badgers living in areas of low local population density. Combined movement, survival, spatial, and social network analyses revealed that parasite avoidance was the likely cause of this negative density dependence, with possible roles for localised mortality, encounter-dilution effects, and micronutrient-enhanced immunity. These findings demonstrate that animals can organise their societies in space to minimise parasite infection, with important implications for badger behavioural ecology and for the control of badger-associated diseases.

ecology↗

bioRxiv2020

Multi-Antigenic Virus-like Particle of SARS CoV-2 produced in Saccharomyces cerevisiae as a vaccine candidate

Spike, Envelope and Membrane proteins from the SARS CoV-2 virus surface coat are important vaccine targets. We hereby report recombinant co-expression of the three proteins (Spike, Envelope and Membrane) in a engineered Saccharomyces cerevisiae platform (D-Crypt) and their self-assembly as Virus-like particle (VLP). This design as a multi-antigenic VLP for SARS CoV-2 has the potential to be a scalable vaccine candidate. The VLP is confirmed by transmission electron microscopy (TEM) images of the SARS CoV-2, along with supportive HPLC, Dynamic Light Scattering (DLS) and allied analytical data. The images clearly outline the presence of a "Corona" like morphology, and uniform size distribution.

biochemistry↗

bioRxiv2020

Climate change will drive novel cross-species viral transmission

At least 10,000 species of mammal virus are estimated to have the potential to spread in human populations, but the vast majority are currently circulating in wildlife, largely undescribed and undetected by disease outbreak surveillance 1-3 . In addition, changing climate and land use are already driving geographic range shifts in wildlife, producing novel species assemblages and opportunities for viral sharing between previously isolated species 4, 5 . In some cases, this will inevitably facilitate spillover into humans 6, 7 --a possible mechanistic link between global environmental change and emerging zoonotic disease 8 . Here, we map potential hotspots of viral sharing, using a phylogeographic model of the mammal-virus network, and projections of potential geographic range shifts for 3,139 mammal species under climate change and land use scenarios for the year 2070. Range-shifting mammal species are predicted to aggregate at high elevations, in biodiversity hotspots, and in areas of high human population density in Asia and Africa, driving the novel cross-species transmission of their viruses an estimated 4,000 times. Counter to expectations, holding warming under 2{degrees}C within the century does not reduce new viral sharing, due to greater potential range expansions-- highlighting the need to invest in surveillance even in a low-warming future. Most projected viral sharing is driven by diverse hyperreservoirs (rodents and bats) and large-bodied predators (carnivores). Because of their unique dispersal capacity, bats account for the majority of novel viral sharing, and are likely to share viruses along evolutionary pathways that could facilitate future emergence in humans. Our findings highlight the urgent need to pair viral surveillance and discovery efforts with biodiversity surveys tracking species range shifts, especially in tropical countries that harbor the most emerging zoonoses.

ecology↗