Biology subjects

Roy, A.

Publications and source records attributed to Roy, A..

At least 91 records · Page 5Linked to original sources

bioRxiv2024

Optimized LC-MS/MS method for Doxorubicin quantification: validating drug uptake and tumor reduction in zebrafish xenograft model of breast cancer

Doxorubicin, a potent chemotherapeutic drug, is widely used against various cancers, notably breast cancer. While its efficacy is well-documented, precise dosage determination in experimental models remains challenging. Zebrafish xenografts of various cancers confirm doxorubicins anti-cancerous effect; however, since doxorubicin treatment of zebrafish larva is done by adding doxorubicin to fish water, the precise chemotherapeutic dosage for zebrafish larva remains unknown. In this study, we provide a liquid chromatography tandem mass-spectrometry (LC-MS/MS) method for quantifying doxorubicin uptake in zebrafish larvae and thus provide a direct estimate of doses required for the therapeutic effect. Alongside quantification, we measured the therapeutic effect of doxorubicin in zebrafish larvae xenografted with triple negative breast cancer cell line, MDA-MB-231. LD50 value of doxorubicin was first determined by incubating 3-days post fertilization (dpf) larvae with different doses of doxorubicin for 72 h. Doxorubicin was quantified both from zebrafish larval homogenate and treatment solution. Analysis was performed by selected-reaction monitoring (SRM) scans in positive ionization mode. LD50 value for 72 h calculated to be 35.95 mg/L. As expected, doxorubicin-treated xenografts exhibited a significant reduction in tumor growth. The range of limit of detection (LOD) and limit of quantification (LOQ) for doxorubicin were 2 and 5 g/L respectively. Intra- and inter-day accuracy was within the range of 82-114%. Overall, in this study we describe a reliable method for quantifying doxorubicin in zebrafish larvae. Our study facilitates precise dosage estimation, enhancing the relevance of zebrafish xenograft model in cancer research and potentially improving translational applications of chemotherapeutic treatments.

cancer biology↗

bioRxiv2024

Human Vascularized Macrophage-Islet Organoids to Model Immune-Mediated Pancreatic β cell Pyroptosis upon Viral Infection

There is a paucity of human models to study immune-mediated host damage. Here, we utilized the GeoMx spatial multi-omics platform to analyze immune cell changes in COVID-19 pancreatic autopsy samples, revealing an accumulation of proinflammatory macrophages. Single cell RNA-seq analysis of human islets exposed to SARS-CoV-2 or Coxsackievirus B4 (CVB4) viruses identified activation of proinflammatory macrophages and {beta} cell pyroptosis. To distinguish viral versus proinflammatory macrophage-mediated {beta} cell pyroptosis, we developed human pluripotent stem cell (hPSC)-derived vascularized macrophage-islet (VMI) organoids. VMI organoids exhibited enhanced marker expression and function in both {beta} cells and endothelial cells compared to separately cultured cells. Notably, proinflammatory macrophages within VMI organoids induced {beta} cell pyroptosis. Mechanistic investigations highlighted TNFSF12-TNFRSF12A involvement in proinflammatory macrophage-mediated {beta} cell pyroptosis. This study established hPSC- derived VMI organoids as a valuable tool for studying immune cell-mediated host damage and uncovered mechanism of {beta} cell damage during viral exposure.

developmental biology↗

bioRxiv2024

Diet breadth in two polyphagous Spodoptera moths in a wide range of host and non-host plants and the potential for range expansion

O_LISeveral polyphagous moths are severe crop pests. Diet breadth patterns and mechanisms among polyphagous insects provide an excellent system to study ecological and evolutionary processes in herbivores, driving dietary specialization. However, studies of diet breadth on more than a handful of crops are scarce. C_LIO_LIHere, we estimated the diet breadth in two species of lepidopteran herbivores from the genus Spodoptera: S. littoralis (SL), with host range including both mono- and dicotyledonous plants and S. frugiperda (SF) Corn strain, primarily adapted to different grass species. C_LIO_LILarval performance on 23 crop and wild plant species from 17 families from terrestrial and wetland habitats was compared to an artificial diet in no-choice feeding bioassays. SL survived and performed better on most tested plants, particularly on the family level, except on two monocot plants (maize and leek), where SF performed well. There were five wild non-host plants where both generalists failed to survive. Nutrition indices assay corroborates the findings on a subset of plants. C_LIO_LIIn a subset of plants, larval feeding preference correlated partly, and larval attraction correlated well with larval performance. Female oviposition choice showed a weak correlation with larval performance. This weak correlation implies that these traits are decoupled, and other factors are crucial for female host plant selection. C_LIO_LIDuring larval dispersal greenhouse experiments, SL and SF larvae strongly tended to migrate onto their suitable host plants, indicating that this is one factor that modulates female host plant selection. C_LIO_LIIn summary, SL has a broader diet breath compared to SF, surviving on wild plants with no previous exposure. The present study provides the first comprehensive data on the diet breadth of two range-expanding and highly invasive polyphagous herbivores. C_LI

ecology↗

bioRxiv2024

Lipotoxicity Induces Beta Cell Small Extracellular Vesicle-mediated Beta Cell Dysfunction

Chronically elevated circulating excess free fatty acids (i.e. lipotoxicity) is a pathological process implicated in several metabolic disorders, including obesity-driven Type 2 diabetes (T2D). Lipotoxicity exerts detrimental effects on pancreatic islet {beta}-cells by reducing glucose-stimulated insulin secretion (GSIS), altering {beta}-cell transcriptional identity, and promoting apoptosis. While {beta}-cell-derived small extracellular vesicles (sEV) have been shown to contribute to {beta}-cell failure in T2D, their specific role in lipotoxicity-mediated {beta}-cell failure remains to be elucidated. In this work, we demonstrate that lipotoxicity enhances the release of sEVs from {beta}-cells, which exhibit altered proteomic and lipidomic profiles. These lipotoxic sEV induce {beta}-cell dysfunction in healthy mouse and human islets and trigger significant islet transcriptional changes, including the upregulation of genes associated with the TGF{beta}/Smad3 pathway, as noted by RNA sequencing. Importantly, pharmacological inhibition of the TGF{beta}I/II receptor improved lipotoxic sEV-induced {beta}-cell dysfunction, underscoring their involvement in activating the TGF{beta}/Smad3 pathway during this process. We have comprehensively characterized lipotoxic {beta}-cell sEVs and implicated their role in inducing {beta}-cell functional failure in T2D. These findings highlight potential avenues for therapeutic interventions targeting sEV-mediated pathways to preserve {beta}-cell health in metabolic disorders. Article HighlightsO_LIDiabetogenic lipotoxic conditions enhance {beta}-cell sEV release and induce alterations in both protein and lipid content. C_LIO_LIGlobal islet transcriptional changes and alterations in {beta}-cell function were noted upon exposure to lipotoxic sEV. C_LIO_LILipotoxic sEV were shown to activate the TGF{beta}/Smad3 pathway and blockade of this pathway improved {beta}-cell function. C_LI

molecular biology↗

bioRxiv2024

MDRepo - an open environment for data warehousing and knowledge discovery from molecular dynamics simulations

BackgroundMolecular Dynamics (MD) simulation of biomolecules provides important insights into conformational changes and dynamic behavior, revealing critical information about folding and interactions with other molecules. This enables advances in drug discovery and the design of therapeutic interventions. The collection of simulations stored in computers across the world holds immense potential to serve as training data for future Machine Learning models that will transform the prediction of structure, dynamics, drug interactions, and more. A needIdeally, there should exist an open access repository that enables scientists to submit and store their MD simulations of proteins and protein-drug interactions, and to find, retrieve, analyze, and visualize simulations produced by others. However, despite the ubiquity of MD simulation in structural biology, no such repository exists; as a result, simulations are instead stored in scattered locations without uniform metadata or access protocols. A solutionHere, we introduce MDRepo, a robust infrastructure that supports a relatively simple process for standardized community contribution of simulations, activates common downstream analyses on stored data, and enables search, retrieval, and visualization of contributed data. MDRepo is built on top of the open-source CyVerse research cyberinfrastructure, and is capable of storing petabytes of simulations, while providing high bandwidth upload and download capabilities and laying a foundation for cloud-based access to its stored data.

biochemistry↗

bioRxiv2024

De Novo Design of Integrin α5β1 Modulating Proteins for Regenerative Medicine

Integrin 5{beta}1 is crucial for cell attachment and migration in development and tissue regeneration, and 5{beta}1 binding proteins could have considerable utility in regenerative medicine and next-generation therapeutics. We use computational protein design to create de novo 5{beta}1-specific modulating miniprotein binders, called NeoNectins, that bind to and stabilize the open state of 5{beta}1. When immobilized onto titanium surfaces and throughout 3D hydrogels, the NeoNectins outperform native fibronectin and RGD peptide in enhancing cell attachment and spreading, and NeoNectin-grafted titanium implants outperformed fibronectin and RGD-grafted implants in animal models in promoting tissue integration and bone growth. NeoNectins should be broadly applicable for tissue engineering and biomedicine. One-Sentence SummaryA de novo-designed fibronectin substitute, NeoNectin, is specific for integrin 5{beta}1 and can be incorporated into biomaterials for regenerative medicine.

bioengineering↗

bioRxiv2024

The Hidden Potential of PDE4 Inhibitor Rolipram: A Multifaceted Examination of its Inhibition of MMP2/9 Reveals Theraputic Implications

A PDE4 inhibitor, Rolipram, was previously found to down-regulate (in a manner dependent on cAMP-PKA) MMP2 and MMP9 levels, important markers of epithelial-to-mesenchymal transition in human breast cancer cell lines. However, zymographic studies revealed that rolipram could also alter the enzymatic activities of these MMPs, even in the presence of the PKA inhibitor H89. This calls for more detailed investigations of the inhibitory mechanism of rolipram on MMP2 and MMP9. The prediction of ligand-based targets through online reverse screening indicated that proteases are likely targets of rolipram. Computational molecular docking also demonstrated significant binding affinities of rolipram for both MMP2 and MMP9 proteins. Concurrently, a well-known inhibitor of MMPs, SB3CT, was utilized as a positive control for this study. The best models of the docked complexes were used as initial conditions for molecular dynamics (MD) simulations to explore their dynamic behavior and stability. In particular, both the MMP2-rolipram and MMP9-rolipram complexes were found to be stable and compact for the duration of the simulation (300 ns). Several stable hydrogen bonds were also detected between the proteins and rolipram. In vitro experiments using primary cells from patients with breast cancer also showed that rolipram could alter the enzymatic activities of MMP2 and MMP9, independent of the cAMP-PKA signaling pathway. These observations indicate the ability of rolipram to control breast cancer by regressing the functions of MMP2 and MMP9, thus having off-targets other than PDE4 to have direct control over proteins that are involved in the advancement of metastasis.

cancer biology↗

bioRxiv2024

Crosstalk between plasma membrane and Staphylococcus α-hemolysin during oligomerization

The infectious microbe Staphylococcus aureus releases an array of cytotoxic pore-forming toxins (PFTs) that severely damage the cell membrane during bacterial infection. However, the interaction interfaces between the host cell and toxin were merely explored. Herein, we monitored the active oligomeric states facilitated membrane disruption processes such as lysis, and protrusion in the plasma membrane and lipid membrane. Furthermore, necrosis was triggered in the neutrophil-like cells upon synergistic binding and oligomerization of the monomeric -HL. Additionally, we solved RBC membrane stabilized structure of different conformational states of this {beta}-PFT using a single-particle cryo-EM. We further confirmed that internal membrane fluidity was the deterministic factor associated with the formation of intermediate pre-pores, heptameric pore-like, and complete pore species. Together, this is the first study to unveil the structure-function analysis of pre-pore to pore transition of any small {beta}-PFT during its crosstalk with the cell. HighlightsO_LI-HL promotes necrosis in HL60 cells and lysis of shorter lipid bilayer region. C_LIO_LICryo-EM of small PFT in the cellular environment. C_LIO_LIStructural characterization of heptameric pore, pore-like, and pre-pore complex in the presence of RBCs. C_LIO_LIBilayer phase behavior (Ld/Lo) governs different conformational and geometrical variants of -HL. C_LI

biophysics↗

bioRxiv2024

Resting state brain network segregation is associated with walking speed and working memory in older adults

Older adults exhibit larger individual differences in walking ability and cognitive function than young adults. Characterizing intrinsic brain connectivity differences in older adults across a wide walking performance spectrum may provide insight into the mechanisms of functional decline in some older adults and resilience in others. Thus, the objectives of this study were to: (1) determine whether young adults and high- and low-functioning older adults show group differences in brain network segregation, and (2) determine whether network segregation is associated with working memory and walking function in these groups. The analysis included 21 young adults and 81 older adults. Older adults were further categorized according to their physical function using a standardized assessment; 54 older adults had low physical function while 27 were considered high functioning. Structural and functional resting state magnetic resonance images were collected using a Siemens Prisma 3T scanner. Working memory was assessed with the NIH Toolbox list sorting test. Walking speed was assessed with a 400 m-walk test at participants self-selected speed. We found that network segregation in mobility-related networks (sensorimotor, vestibular) was higher in older adults with higher physical function compared to older adults with lower physical function. There were no group differences in laterality effects on network segregation. We found multivariate associations between working memory and walking speed with network segregation scores. The interaction of left sensorimotor network segregation and age groups was associated with higher working memory function. Higher left sensorimotor, left vestibular, right anterior cingulate cortex, and interaction of left anterior cingulate cortex network segregation and age groups were associated with faster walking speed. These results are unique and significant because they demonstrate higher network segregation is largely related to higher physical function and not age alone. HighlightsO_LIOlder adults with high and low physical function have network segregation differences. C_LIO_LINetwork segregation for high-functioning older adults was more similar to that of young adults. C_LIO_LILaterality of functional network segregation is not different between age groups. C_LIO_LIHigher network segregation is associated with faster walking speed. C_LI

neuroscience↗

bioRxiv2024

Non Parametric Differential Network Analysis: A Tool for Unveiling Specific Molecular Signatures.

The rewiring of molecular interactions in various conditions leads to distinct phenotypic outcomes. Differential Network Analysis (DNA) is dedicated to exploring these rewirings within gene and protein networks. Leveraging statistical learning and graph theory, DNA algorithms scrutinize alterations in interaction patterns derived from experimental data. Introducing a novel approach to differential network analysis, we incorporate differential gene expression based on sex and gender attributes. We hypothesize that gene expression can be accurately represented through non-Gaussian processes. Our methodology involves quantifying changes in non-parametric correlations among gene pairs and expression levels of individual genes. Applying our method to public expression datasets concerning diabetes mellitus and atherosclerosis in liver tissue, we identify gender-specific differential networks. Results underscore the biological relevance of our approach in uncovering meaningful molecular distinctions. Author summaryThis paper explores a novel technique for Differential Network Analysis (DNA) that considers sex-based variations. DNA compares biological networks under different conditions, like healthy vs. diseased states. Our method tackles the limitations of traditional DNA approaches, which often assume specific data distributions. We propose a non-parametric DNA methodology that integrates sex differences and identifies differential edges between networks. This approach utilizes data on gene expression levels and sex to construct a more accurate picture of the molecular mechanisms underlying diseases, particularly those exhibiting sex-dependent variations. Our method paves the way for a deeper understanding of how sex and age influence disease processes at the molecular level.

bioinformatics↗

bioRxiv2024

Neuronal downregulation of PLCG2 impairs synaptic function and elicits Alzheimer disease hallmarks

We developed a high content screening to investigate how Alzheimer disease (AD) genetic risk factors may affect synaptic mechanisms in rat primary neuronal cultures. Out of the target genes identified, we found that Plcg2 downregulation in mouse dentate gyrus neurons consistently disrupted dendritic morphology and synaptic function. In human neuronal cultures (hNCs), PLCG2 downregulation also impaired synaptic function and increased A{beta} levels and Tau phosphorylation. Very rare PLCG2 loss-of-function (LoF) variants were associated with a 10-fold increased AD risk. PLCG2 LoF carriers exhibit low mRNA/protein PLCG2/PLC{gamma}2 levels and the R953* LoF mutation compromised synaptic function and increased AD hallmarks in hNCs. Single nuclei RNAseq analyses confirmed that the downregulation of PLCG2 impacted pathways related to synaptic and neuronal functions, potentially through neurexin in neurons. In conclusion, PLC{gamma}2 downregulation could increase AD risk by impairing synaptic functions and increasing the A{beta} levels and Tau phosphorylation in neurons.

neuroscience↗

bioRxiv2024

The Area Law of Molecular Entropy: Moving Beyond Harmonic Approximation.

Inspired by black hole thermodynamics, the area law that entropy is proportional to horizon area has been proposed in quantum entanglement entropy and has largely maintained its validity. This article shows that the area law is also valid for the thermodynamic entropy of molecules. We showed that the gas-phase entropy of molecules obeys the area law with our proposed correction for the different curvatures of the molecular surface. The coefficient for the ultraviolet cutoff for the molecular entropy, calculated from our curated experimental data, is tantalizingly close to the value [Formula] proposed by Hawking [Hawking, 1976]. The ability to estimate gas-phase entropy by the area law also allows us to calculate molecular entropy faster and more accurately than currently popular methods of estimating molecular entropy with harmonic oscillator approximation. The speed and accuracy of our method will open up new possibilities for the explicit inclusion of entropy in computational biology methods, such as virtual screening applications.

biophysics↗

bioRxiv2024

Comparative metagenomic study unveils bacterial communities and their putative involvement in ecological success of two pine-feeding Ips beetle holobionts

Climate change has recently boosted the severity and frequency of the pine bark beetle attacks. The bacterial community associated with these beetles acts as "hidden players", enhancing their ability to infest and thrive on defence-rich pine trees. There is limited understanding of the environmental acquisition of these hidden players and their life stage-specific association with different pine-feeding bark beetles. There is inadequate knowledge on novel bacterial introduction to pine trees after the beetle infestation. Hence, we conducted the first comparative bacterial metabarcoding study comprehensively revealing the bacterial communities in the pine trees before and after beetle feeding and in different life stages of two dominant pine-feeding bark beetles, namely Ips sexdentatus and Ips acuminatus. We also evaluated the bacterial association between wild and lab-bred beetles to measure the deviation due to inhabiting a controlled environment. Significant differences in bacterial amplicon sequence variance (ASVs) abundance existed among different life stages within and between the pine beetles. Such observations endorsed that the bark beetle life stage shaped bacterial assemblage. Furthermore, lab-bred and wild-collected adult beetles had distinct bacterial assemblages, implying that the breeding environment induced crucial changes. Alteration of pine wood bacteriome after beetle feeding is an intriguing observation in the present study, which demands further investigation. We validated the relative abundances of selected bacterial taxa estimated by metagenomic sequencing with quantitative PCR. Functional predictions revealed that these bacterial genera might execute conserved functions, aiding the ecological success of these beetles. Nevertheless, these findings shed new insights into bacterial associations and their putative metabolic roles in pine beetles under the influence of various drivers such as environment, host, and life stages and provide the foundation for future downstream functional investigations. ImportanceThe current understanding of bark beetle as holobiont is restricted. Most studies lack information on microbial community assembly in bark beetle microhabitats. No data comprehensively reveals the influence of lab breeding on pine beetle microbial associations. It is unknown if there is any adaptive convergence in beetle microbial assemblage due to feeding on the same host. Such information is essential to developing a bark beetle management strategy to restore forests from beetle-mediated damage. Our study shows that lab-breeding considerably influences beetle bacterial community assembly. We documented that beetle feeding alters bacteriome at the microhabitat level, and the beetle life stage shapes the bacterial associations. Nevertheless, our study revisited the bark beetle symbiosis under the influence of different drivers and revealed intriguing insight into bacterial community assembly, facilitating future functional studies.

microbiology↗

bioRxiv2024

Ready, set, yellow! Color Preference of Indian Free-ranging Dogs

Most of the research on color vision related behaviors in dogs has involved training the dogs to perform visual discrimination tasks. We investigated the meaning of color to untrained Indian free-ranging dogs (FRDs). Using one-time multi-option choice tests for color preference in 134 adult dogs, we found the dogs to prefer yellow objects over blue or gray ones (p < 0.001, Cramers V = 0.433) while there was no preference between blue and gray (N = 102, p = 0.165). We next pitted a yellow object against a gray object that had food. Here, the dogs ignored the food to approach the yellow object first, both when the food was biscuit (N = 52, p < 0.001, Cramers V = 0.576) and chicken (N = 61, p < 0.001, Cramers V = 0.540), indicating the color preference to be quite strong. Color preference has previously been investigated in many other animals and has implications for behaviors like mate choice and foraging. Our study provides a new perspective into the ecology of Indian FRDs and might have implications for pet dogs as well, if they too show this preference. HighlightsO_LIIndian free-ranging dogs (FRDs) show preference toward the color yellow over blue and gray. C_LIO_LIIndian FRDs show no preference between blue and gray colors. C_LIO_LIAttraction towards a yellow object can be stronger than attraction towards food rewards for Indian FRDs. C_LI

animal behavior and cognition↗

bioRxiv2024

DIRT/μ - Automated extraction of root hair traits using combinatorial optimization

Similar to any microscopic appendages, such as cilia or antennae, phenotyping of root hairs has been a challenge due to their complex intersecting arrangements in two-dimensional (2D) images and the technical limitations of automated measurements. Digital Imaging of Root Traits at Microscale (DIRT/) addresses this issue by computationally resolving intersections and extracting individual root hairs from 2D microscopy images. This solution enables automatic and precise trait measurements of individual root hairs. DIRT/ rigorously defines a set of rules to resolve intersecting root hairs and minimizes a newly designed cost function to combinatorically identify each root hair in the microscopy image. As a result, DIRT/ accurately measures traits such as root hair length (RHL) distribution and root hair density (RHD), which are impractical for manual assessment. We tested DIRT/ on three datasets to validate its performance and showcase potential applications. By measuring root hair traits in a fraction of the time manual methods require, DIRT/ eliminates subjective biases from manual measurements. Automating individual root hair extraction accelerates phenotyping and quantifies trait variability within and among plants, creating new possibilities to characterize root hair function and their underlying genetics.

plant biology↗

bioRxiv2024

Mutation of highly conserved residues in loop 2 of the coronavirus macrodomain demonstrates that enhanced ADP-ribose binding is detrimental to infection

All coronaviruses (CoVs) encode for a conserved macrodomain (Mac1) located in nonstructural protein 3 (nsp3). Mac1 is an ADP-ribosylhydrolase that binds and hydrolyzes mono-ADP-ribose from target proteins. Previous work has shown that Mac1 is important for virus replication and pathogenesis. Within Mac1, there are several regions that are highly conserved across CoVs, including the GIF (glycine-isoleucine-phenylalanine) motif. To determine how the biochemical activities of these residues impact CoV replication, the isoleucine and the phenylalanine residues were mutated to alanine (I-A/F-A) in both recombinant Mac1 proteins and recombinant CoVs, including murine hepatitis virus (MHV), Middle East respiratory syndrome coronavirus (MERS-CoV), and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The F-A mutant proteins had ADP-ribose binding and/or hydrolysis defects that led to attenuated replication and pathogenesis in cell culture and mice. In contrast, the I-A mutations had normal enzyme activity and enhanced ADP-ribose binding. Despite increased ADP-ribose binding, I-A mutant MERS-CoV and SARS-CoV-2 were highly attenuated in both cell culture and mice, indicating that this isoleucine residue acts as a gate that controls ADP-ribose binding for efficient virus replication. These results highlight the function of this highly conserved residue and provide unique insight into how macrodomains control ADP-ribose binding and hydrolysis to promote viral replication. AUTHOR SUMMARYThe conserved CoV macrodomain (Mac1) counters the activity of host ADP-ribosyltransferases by removing ADP-ribose from target proteins and is critical for CoV replication and pathogenesis. Mac1 is a potential therapeutic target for CoV disease and several groups are actively developing Mac1 inhibitors. However, we lack a basic knowledge of how many of the key residues in the Mac1 ADP-ribose binding pocket contribute to its biochemical and virological functions. In this study, we engineered alanine mutations into two highly conserved residues in the ADP-ribose binding pocket of Mac1, both as recombinant proteins and recombinant viruses for both MERS-CoV and SARS-CoV-2 to determine their importance in both Mac1 biochemical functions and CoV infection. Interestingly, an isoleucine-to-alanine mutation in loop 2 of both MERS-CoV and SARS-CoV-2 Mac1 proteins enhanced ADP-ribose binding. But surprisingly, that proved to be detrimental to virus infection, indicating that this isoleucine functions to control Mac1 ADP-ribose binding and is beneficial for virus replication and pathogenesis. These results provide unique insight into how macrodomains control ADP-ribose binding to promote infection and will be critical for the development of novel inhibitors targeting Mac1 that could be used to treat CoV-induced disease.

microbiology↗

bioRxiv2023

Non Parametric Differential Network Analysis for Biological Data

Rewiring of molecular interactions under different conditions causes different phenotypic responses. Differential Network Analysis (also indicated as DNA) aims to investigate the rewiring of gene and protein networks. DNA algorithms combine statistical learning and graph theory to explore the changes in the interaction patterns starting from experimental observation. Despite there exist many methods to model rewiring in networks, we propose to use age and gender factors to guide rewiring algorithms. We present a novel differential network analysis method that consider the differential expression of genes by means of sex and gender attributes. We hypothesise that the expression of genes may be represented by using a non-gaussian process. We quantify changes in nonparametric correlations between gene pairs and changes in expression levels for individual genes. We apply our method to identify the differential networks between males and females in public expression datasets related to mellitus diabetes in liver tissue. Results show that this method can find biologically relevant differential networks.

bioinformatics↗

bioRxiv2023

Age, sex, and cell type-resolved hypothalamic gene expression across the pubertal transition in mice

Although the hypothalamus plays a critical role in the regulation of puberty, more research is needed to identify the gene regulatory networks that control pubertal timing. Here, we investigate the age-, sex- and cell-type-specific gene regulation in the hypothalamus across the pubertal transition. We used RNA-seq to profile hypothalamic gene expression in male and female mice at five time points spanning the onset of puberty (postnatal days (PD) 12, 22, 27, 32, and 37). By combining this data with hypothalamic scRNA-seq data of pre- and post-pubertal mice, we were able to assign gene expression changes to their cell types of origin. In our colony, pubertal onset occurs earlier in male mice allowing us to focus on genes whose expression is dynamic across ages and offset between sexes and to explore bases of sex effects. Our age-by- sex pattern of expression enriched for biological pathways involved hormone production, neuronal activation, and glial maturation. Additionally, we found a dramatic expansion of oligodendrocytes precursor cells into mature oligodendrocytes spanning the pre-pubertal (PD12) to peri-pubertal (PD27) timepoints, and that genes driving this expansion enrich for genes involved in pubertal regulation. Together, by incorporating multiple biological timepoints with male and female mice simultaneously, our work furthers the understanding of gene and cell-type changes that accompany the development of secondary sex characteristics in both sexes.

genomics↗