Biology subjects

Price, N.

Publications and source records attributed to Price, N..

15 recordsLinked to original sources

bioRxiv2026

Curcumin and Sulforaphane Preserve Mobility in Aging Caenorhabditis elegans via Distinct yet Complementary Transcriptional Signatures

Aging involves a progressive decline in bodily functions, underscoring the need for interventions that enhance healthspan. In this study, we screened nine natural products in Caenorhabditis elegans using whole-organism phenotyping to assess mobility endpoints, and subsequently focused on curcumin, sulforaphane, and their combination. In replicated follow-up experiments, all three interventions improved late-adult mobility after Day 2 of adulthood. Sulforaphane and the combination provided the strongest gains, whereas curcumin showed a distinct benefit profile, with more pronounced effects on time active measures than on speed-based metrics. To examine associated molecular changes, we performed transcriptomic profiling on Day 3 adults. Curcumin was associated with lipid and sphingolipid remodeling together with reduced expression of several innate immune effectors, whereas sulforaphane induced glutathione-linked detoxification signatures involving multiple gst genes. The combination retained major features of both single-compound responses while adding combination-specific changes that broadened detoxification-associated signatures and extended repression of lectin-and lysozyme-associated genes. Transcription factor activity inference further supported SKN-1-linked detoxification responses under sulforaphane and the combination. Overall, these results suggest that curcumin and sulforaphane engage distinct yet partially convergent maintenance-related programs, and that their combination broadens the underlying molecular response without producing additive mobility gains. These findings motivate further testing of natural product combinations in healthspan-related contexts.

Systems Biology↗

bioRxiv2025

Model-based separation of visual and oculomotor signals in marmoset lateral intraparietal area

The lateral intraparietal area (LIP) integrates visual information with task demands to guide saccadic eye movements. Most prior studies have relied on imposed prolonged delays to separate sensory and motor activity, whereas natural behavior involves rapid sensory-motor transformations. To examine LIP function during more naturalistic oculomotor behavior, we recorded multi-unit activity from LIP in two marmosets performing a task requiring rapid selection of salient visual stimuli. Because sensory and motor signals temporally overlap in such fast tasks, we used a Generalized Linear Model (GLM) that separately captured visually driven and oculomotor-related components. The model explained substantial neural variance during correct and missed saccades, as well as spontaneous eye movements, and revealed heterogeneous sensory and motor encoding across recorded neural units. Our approach demonstrated that the origins of neural activity can be segregated without relying on imposed delays, and showed the presence of a strong post-saccadic motor signal in LIP.

neuroscience↗

bioRxiv2025

Divergent viral phosphodiesterases for immune signaling evasion

Cyclic dinucleotides (CDNs) and other short oligonucleotides play fundamental roles in immune system activation in organisms ranging from bacteria to humans. In response, viruses use phosphodiesterase-mediated oligonucleotide cleavage for immune evasion, a strategy whose diversity has not yet been explored. We used a canonical 2H phosphodiesterase (2H PDE) structure-based search of prokaryotic and eukaryotic viral sequences to identify an exceptional diversity of 2H PDEs across the virome, including enzymes not detectable with sequence search methods alone. Despite active site conservation, biochemical experiments revealed remarkable substrate specificity of these PDEs that corresponds to variation in the core 2H fold. This nuanced specificity allows 2H PDEs to selectively degrade oligonucleotide messengers to avoid interfering with host immune signaling. Together, these findings nominate viral 2H PDEs as key regulators of CDN signaling across the tree of life.

biochemistry↗

bioRxiv2024

Placental Network Differences Among Obstetric Syndromes Identified With An Integrated Multiomics Approach

The placenta is essential for a healthy pregnancy, and placental pathology can endanger both maternal and fetal health. Placental function is affected by dynamic, complex, and interconnected molecular, cellular, and environmental events; therefore, we need a systems biology approach to study disease in normal physiological placenta function. We use placental multiomics (short and bulk transcriptomics, untargeted metabolomics, and targeted proteomics) paired with clinical data and placental histopathology reports from 321 placentas across multiple obstetric conditions: fetal growth restriction (FGR), FGR with pregnancy-related hypertension (FGR+HDP), preeclampsia (PE), and spontaneous preterm delivery (PTD). We first performed cellular deconvolution to estimate cell type numbers from bulk transcriptomes: FGR+HDP placentas were the most different from control placentas driven by a higher estimated number of extravillous trophoblast (p<0.0001). Next, we evaluated the impact of fetal sex and gestational age on analyte levels, adjusting for these confounders. We then generated obstetric condition-specific correlation networks and identified communities of related analytes associated with physiology and disease. We demonstrated how network connectivity and its disruption in disease can be used to identify signatures unique to a clinical outcome. We examined a community defined in control placentas for which the most connected node was miR-365a-3p in contrast to the corresponding community in FGR+HDP placentas for which the most connected node was hypoxia-induced miR-210-3p. From this community, we identified a signature containing mRNA transcripts implicated in placental dysfunction (e.g. FLT1, FSTL3, HTRA4, LEP, and PHYHIP). This signature distinguishes between FGR+HDP placentas and placentas of differing clinical outcomes in high-dimensional space. These findings illustrate the power of systems biology-driven interomics network analysis in a single tissue type, laying the groundwork for future multi-tissue studies.

systems biology↗

bioRxiv2024

Birth of new protein folds and functions in the virome

Rapid virus evolution generates proteins essential to infectivity and replication but with unknown function due to extreme sequence divergence1. Using a database of 67,715 newly predicted protein structures from 4,463 eukaryotic viral species, we found that 62% of viral proteins are evolutionarily young and lack homologs in the Alphafold database2,3. Among the 38% of more ancient viral proteins, many have non-viral structural homologs that revealed surprising similarities between human pathogens and their eukaryotic hosts. Structural comparisons suggested putative functions for >25% of unannotated viral proteins, including those with roles in the evasion of innate immunity. In particular, RNA ligase T- (ligT) like phosphodiesterases were found to resemble phage-encoded proteins that hydrolyze the host immune-activating cyclic dinucleotides 33 and 23 cyclic G-A monophosphate (cGAMP). Experimental analysis showed that ligT homologs encoded by avian poxviruses likewise hydrolyze 23 cGAMP, showing that ligT-mediated targeting of cGAMP is an evolutionarily conserved mechanism of immune evasion present in both bacteriophage and eukaryotic viruses. Together, the viral protein structural database and analytics presented here afford new opportunities to identify mechanisms of virus-host interactions that are common across the virome.

microbiology↗

bioRxiv2023

Broad-spectrum antiviral inhibitors targeting pandemic potential RNA viruses

RNA viruses continue to remain a clear and present threat for potential pandemics due to their rapid evolution. To mitigate their impact, we urgently require antiviral agents that can inhibit multiple families of disease-causing viruses, such as arthropod-borne and respiratory pathogens. Potentiating host antiviral pathways can prevent or limit viral infections before escalating into a major outbreak. Therefore, it is critical to identify broad-spectrum antiviral agents. We have tested a small library of innate immune agonists targeting pathogen recognition receptors, including TLRs, STING, NOD, Dectin and cytosolic DNA or RNA sensors. We observed that TLR3, STING, TLR8 and Dectin-1 ligands inhibited arboviruses, Chikungunya virus (CHIKV), West Nile virus (WNV) and Zika virus, to varying degrees. Cyclic dinucleotide (CDN) STING agonists, such as cAIMP, diABZI, and 2,3-cGAMP, and Dectin-1 agonist scleroglucan, demonstrated the most potent, broad-spectrum antiviral function. Comparative transcriptome analysis revealed that CHIKV-infected cells had larger number of differentially expressed genes than of WNV and ZIKV. Furthermore, gene expression analysis showed that cAIMP treatment rescued cells from CHIKV-induced dysregulation of cell repair, immune, and metabolic pathways. In addition, cAIMP provided protection against CHIKV in a CHIKV-arthritis mouse model. Cardioprotective effects of synthetic STING ligands against CHIKV, WNV, SARS-CoV-2 and enterovirus D68 (EV-D68) infections were demonstrated using human cardiomyocytes. Interestingly, the direct-acting antiviral drug remdesivir, a nucleoside analogue, was not effective against CHIKV and WNV, but exhibited potent antiviral effects against SARS-CoV-2, RSV (respiratory syncytial virus), and EV-D68. Our study identifies broad-spectrum antivirals effective against multiple families of pandemic potential RNA viruses, which can be rapidly deployed to prevent or mitigate future pandemics.

microbiology↗

bioRxiv2022

A Genome Scale Transcriptional Regulatory Model of the Human Placenta

Gene regulation is essential to placental function and fetal development. We report a genome-scale transcriptional regulatory network (TRN) of the human placenta built using digital genomic footprinting and transcriptomic data. We integrated 475 transcriptomes and 12 DNase hypersensitivity datasets from placental samples to globally and quantitatively map transcription factor (TF)-target gene interactions. In an independent dataset, the TRN model predicted target gene expression with an out of sample R2 value greater than 0.25 for 74% of target genes. We performed siRNA knockdowns of 4 TFs and achieved concordance between the predicted gene targets in our TRN and differences in expression of knockdowns with an accuracy of >0.7 for 3 of the 4 TFs. Our final model contained 113,158 interactions across 391 TFs and 7,712 target genes and is publicly available. We identified six TFs which were significantly enriched as regulators for genes previously associated with preterm birth.

systems biology↗

bioRxiv2022

LIRcentral: a manually curated online database of experimentally validated functional LIR-motifs

Several selective macroautophagy receptor and adaptor proteins bind members of the Autophagy-related protein 8 (Atg8) family using short linear motifs (SLiMs), most often referred to as Atg8-interacting motifs (AIM) or LC3-interacting motifs (LIR). AIM/LIR-motifs have been extensively studied during the last fifteen years, since they can uncover the underlying biological mechanisms and possible substrates for this key catabolic process of eukaryotic cells. Prompted by the fact that experimental information regarding LIR-motifs can be found scattered across heterogeneous literature resources, we have developed LIRcentral (https://lircentral.eu), a freely available online repository for user-friendly access to comprehensive, high-quality information regarding LIR-motifs from manually curated publications. Herein, we describe the development of LIRcentral and showcase currently available data and features, along with our plans for the expansion of this resource. Information incorporated in LIRcentral is useful for accomplishing a variety of research tasks, including: (i) guiding wet biology researchers for the characterization of novel instances of LIR-motifs, (ii) giving bioinformaticians/computational biologists access to high-quality LIR-motifs for building novel prediction methods for LIR-motifs and LIR containing proteins (LIRCPs) and (iii) performing analyses to better understand the biological importance/features of functional LIR-motifs. We welcome feedback on the LIRcentral content and functionality by all interested researchers and anticipate this work to spearhead a community effort for sustaining this resource which will further promote progress in studying LIR-motifs/LIRCPs.

bioinformatics↗

bioRxiv2021

A wipe-based stool collection and preservation kit for microbiome community profiling

While a range of methods for stool collection exist, many require complicated, self-directed protocols and stool transfer. In this study, we introduce and validate a novel, wipe-based approach to fecal sample collection and stabilization for metagenomics analysis. A total of 72 samples were collected across four different preservation types: freezing at -20{degrees}C, room temperature storage, a commercial DNA preservation kit, and DESS (dimethyl sulfoxide, ethylenediaminetetraacetic acid, sodium chloride) solution. These samples were sequenced and analyzed for taxonomic abundance metrics, metabolic pathway classification, and diversity analysis. Overall, the DESS wipe results validated the use of a wipe-based capture method to collect stool samples for microbiome analysis, showing an R2 of 0.96 for species across all kingdoms, as well as exhibiting a maintenance of Shannon diversity (3.1-3.3) and species richness (151-159) compared to frozen samples. Moreover, DESS showed comparable performance to the commercially available preservation kit (R2 of 0.98), and samples consistently clustered by subject across each method. Future studies will be needed to further explore sample processing options and their applications in non-healthy subjects, particularly patients with irritable bowel syndrome, inflammatory bowel disease, and colorectal cancer, but these data suggest the DESS wipe method can be used for stable, room temperature collection and transport of human stool specimens.

microbiology↗

bioRxiv2021

Conserved Architecture of Brain Transcriptome Changes between Alzheimer's Disease and Progressive Supranuclear Palsy in Pathologically Affected and Unaffected Regions

We identify a striking correlation in the directionality and magnitude of gene expression changes in brain transcriptomes between Alzheimers disease (AD) and Progressive Supranuclear Palsy (PSP). Further, the transcriptome architecture in AD and PSP is highly conserved between the temporal and cerebellar cortices, indicating highly similar transcriptional changes occur in pathologically affected and "unaffected" areas of the brain. These data have broad implications for interpreting transcriptomic data in neurodegenerative disorders.

neuroscience↗

bioRxiv2020

Linking genomic signatures of selection to expression variation and direct evidence of local adaptation

Understanding how genomic and expression variation is linked to adaptation of plants to local environments is fundamental to the fields of evolutionary biology and species conservation. Using locally adapted Arabidopsis thaliana Italy and Sweden populations, we examine how variation in gene expression under control and cold acclimation conditions, is linked to allele frequency differentiation (AFD); linkage disequilibrium (LD); selective constraint at nonsynonymous sites; and genetic-tradeoff quantitative trait loci (GT-QTL). Our results indicate that contrary to genes showing a main effect in environment (E), expression genotype by environment interactions (GxE) show significantly higher AFD along cis-regulatory and nonsynonymous sites than the neutral expectation; and interestingly, highly differentiated GxE genes show higher expression and inter-species selective constraint than the rest of the genes. When examining the association between genomic signatures of selection along GxE/E genes and GT-QTL, we find that GxE genes showing a high AFD and LD, display a significant and much higher enrichment along GT-QTL than the genome-wide/E set of genes. Nonetheless, E genes show a higher enrichment than the genome-wide control. In summary, our results suggest, that these highly expressed and selectively constrained GxE genes, may have been part of a cold-responsive regulon of E genes that experienced recent selection when migrating to new environments. Candidate GxE genes underlying GT-QTL reveal interesting biological processes that may underlie local adaptation to temperature, including flowering time, light-dependent cold acclimation, freezing tolerance, and response to hypoxia. Finally, we find no evidence linking lower expression of the CBF-dependent freezing tolerance pathway to genetic-tradeoffs and adaptation to warmer climates.

evolutionary biology↗

bioRxiv2019

MOBN: an interactive database of multi-omics biological networks

It is essential to reveal the associations between different omics data for a comprehensive understanding of the altered biological process in human wellness and disease. To date, very few studies have focused on collecting and exhibiting multi-omics associations in a single database. Here, we present iNetModels, an interactive database and visualization platform of Multi-Omics Biological Networks (MOBNs). This platform describes the associations between the clinical chemistry, anthropometric parameters, plasma proteomics and metabolomics as well as metagenomics for oral and gut microbiome obtained from the same individuals. Moreover, iNetModels includes tissue- and cancer-specific Gene Co-expression Networks (GCNs) for exploring the connections between the specific genes. This platform allows the user to interactively explore a single feature's association with other omics data and customize its particular context (e.g. male/female specific). The users can also register their own data for sharing and visualization of the MOBNs and GCNs. Moreover, iNetModels allows users who do not have a bioinformatics background to facilitate human wellness and diseases research. iNetModels can be accessed freely at https://inetmodels.com without any limitation.

bioinformatics↗

bioRxiv2019

In the presence of population structure: From genomics to candidate genes underlying local adaptation

Understanding the genomic signatures, genes, and traits underlying local adaptation of organisms to heterogeneous environments is of central importance to the field evolutionary biology. Mixed linear mrsodels that identify allele associations to environment, while controlling for genome-wide variation at other loci, have emerged as the method of choice when studying local adaptation. Despite their importance, it is unclear whether this approach performs better than identifying environmentally-associated SNPs without accounting for population structure. To examine this, we first use the mixed linear model GEMMA, and simple Spearman correlations, to identify SNPs showing significant associations to climate with and without accounting for population structure. Subsequently, using Italy and Sweden populations, we compare evidence of allele frequency differentiation (FST), linkage disequilibrium (LD), fitness variation, and functional constraint, underlying these SNPs. Using a lenient cut-off for significance, we find that SNPs identified by both approaches, and SNPs uniquely identified by Spearman correlations, were enriched at sites showing genomic evidence of local adaptation and function but were limited across Quantitative Trait Loci (QTL) explaining fitness variation. SNPs uniquely identified by GEMMA, showed no direct or indirect evidence of local adaptation, and no enrichment along putative functional sites. Finally, SNPs that showed significantly high FST and LD, were enriched along fitness QTL peaks and cis-regulatory/nonsynonymous sites showing significant functional constraint. Using these SNPs, we identify genes underlying fitness QTL, and genes linking flowering time to local adaptation. These include a regulator of abscisic-acid (FLDH) and flowering time genes PIF3, FIO1, and COL5.

evolutionary biology↗

bioRxiv2018

Drought adaptation in nature by extensive genetic loss-of-function

Visions of a second green revolution empowered by emerging technologies have called for interdisciplinary syntheses to scale up the discovery of functionally definitive gene variants responsible for climate adaptation in plants. We integrated novel approaches using whole genome sequences and satellite remote sensing to identify natural knockout alleles associated with drought histories in wild Arabidopsis thaliana. Genes identified exhibit signatures of parallel molecular evolution, selection for loss-of-function alleles, and shared associations with flowering time phenotypes in directions consistent with longstanding adaptive hypotheses 7 times more often than expected by chance. Artificial knockout lines then confirmed predicted phenotypes experimentally. These findings further challenge popular assumptions about the adaptive value of genetic loss-of-function in nature and inspire new opportunities for engineering climate resilience in crops.\n\nOne sentence summaryWhole genome sequences and satellite-detected droughts point to gene knockouts as valuable genetic fuel for climate adaptation.

evolutionary biology↗

bioRxiv2018

Reproducible big data science: A case study in continuous FAIRness

Big biomedical data create exciting opportunities for discovery, but make it difficult to capture analyses and outputs in forms that are findable, accessible, interoperable, and reusable (FAIR). In response, we describe tools that make it easy to capture, and assign identifiers to, data and code throughout the data lifecycle. We illustrate the use of these tools via a case study involving a multi-step analysis that creates an atlas of putative transcription factor binding sites from terabytes of ENCODE DNase I hypersensitive sites sequencing data. We show how the tools automate routine but complex tasks, capture analysis algorithms in understandable and reusable forms, and harness fast networks and powerful cloud computers to process data rapidly, all without sacrificing usability or reproducibility--thus ensuring that big data are not hard-to-(re)use data. We compare and contrast our approach with other approaches to big data analysis and reproducibility.

bioinformatics↗