Biology subjects

Drou, N.

Publications and source records attributed to Drou, N..

7 recordsLinked to original sources

bioRxiv2025

Earth-Observation and Environmental Vision Transformers Reveal Genome-Environment Associations in Macroalgae

Macroalgae thrive in extreme environments, yet the genomic basis of their tolerance remains poorly resolved. We describe nine Arabian Gulf macroalgae and integrate them with 117 published genomes (126 total; 70 Rhodophyta, 43 Ochrophyta, 13 Chlorophyta) to test genome-environment associations. Google Earth Engine (GEE) for broad-scale oceanography and 10-meter resolution AlphaEarth Foundations (AEF) embeddings for fine-scale habitat heterogeneity. We identified 157 significant (FDR q < 0.05) correlations with global GEE variables--including a strong negative temperature association with DUF3570--while AEF embeddings uncovered over 1,000 lineage-specific signals within Rhodophyta and identified climate-driven Pfam modules. The von Willebrand factor type-A domain emerged as uniquely robust across all frameworks and enriched in Arabian Gulf species. In the Arabian Gulf, enrichment of this domain is consistent with selection for adhesion mechanisms capable of withstanding chronic hydrodynamic stress compounded by high temperature and salinity. These results demonstrate that converging remote sensing with deep learning identifies conserved and lineage-specific genomic signatures of ecological differentiation across diverse macroalgal lineages.

genomics↗

bioRxiv2025

Integrative multi-omic analysis reveals oral microbiome-metabolome signatures of obesity

Obesity is a major global health challenge and a leading risk factor for cardiometabolic disorders. The global surge in obesity, driven by industrialization and the widespread consumption of low-fiber, ultra-processed food, highlights an urgent need for deeper biological insights. While the gut microbiome has been studied in the context of obesity, the contribution of the oral microbiome--the second largest microbial ecosystem in the human body-remains largely underexplored. Here, we report findings from a deeply-phenotyped prospective-cohort of 628 Emirati adults, leveraging amplicon sequencing of mouthwash samples and multi-omics profiling and functional and metabolic activity analysis of 97 obese individuals and 95 matched controls, making this the most comprehensive multi-omics analysis of the oral microbiome. We identified significant differences in oral microbial diversity, composition, functional pathways, and metabolic profiles between obese and non-obese groups. Integrated multi-omics analysis of the 192 matched metagenomes and metabolome samples uncovered significant metabolic reprogramming and altered energy regulation in obesity. Specifically, the oral microbiome of obese participants were enriched for the proinflammatory Streptococcus parasanguinis and Actinomyces oris, and the lactate-producing Oribacterium sinus. Many microbial pathways involved in dietary carbohydrate metabolism, histidine degradation, as well as the production of obesogenic biomolecules were also enriched in obese participants; however, B-vitamin and heme production pathways were depleted. Consequently, metabolites resulting from these pathways such as lactate, histidine derivatives, choline, uridine, and uracil were elevated in obesity. These consistent microbiome-metabolite shifts were strongly associated with prominent obesity-associated cardiometabolic markers, including serum triglycerides and alkaline phosphatases, establishing a robust link between oral microbiome and obesity. These findings provide the most comprehensive insights into how disrupted microbial-metabolic cross-talk in the oral cavity may contribute to obesity and related cardiometabolic disease risk, underscoring the potential of targeting of oral microbiome-host interactions as a novel avenue for obesity prevention and intervention.

microbiology↗

bioRxiv2024

Morphological and functional convergence of visual projections neurons from diverse neurogenic origins in Drosophila

The Drosophila visual system is a powerful model to study the development of neural circuits. Projection neurons that relay visual information from the lobula part of the optic lobe to the central brain (the lobula columnar neurons-LCNs), are thought to encode different visual features relevant to natural behavior. There are [~]20 classes of LCNs whose projections form highly specific, non-overlapping synaptic domains in the brain called optic glomeruli. Although functional investigations of several LCN circuits have been carried out, very little is known about their developmental origin and the stem cell lineages that generate the LCN subtypes. To address their origin, we used single-cell mRNA sequencing to define the transcriptome of each LCN subtype and identified driver lines that are expressed in specific LCNs throughout development. We show that LCNs originate from neural stem cells in four distinct regions in the fly brain that exhibit different modes of neurogenesis, including the ventral and dorsal tips of the outer proliferation center (tOPC), the ventral tips of the inner proliferation center (vtIPC) and the central brain (CB). This convergence of similar neurons illustrates the complexity of generating neuronal diversity in the brain and likely reflects the evolutionary origin of each LCN subtype that detects a highly specific visual feature and influence behaviors that might be specific to each species.

neuroscience↗

bioRxiv2023

Nighttime-specific gene expression changes in suprachiasmatic nucleus and habenula are associated with resiliency to chronic social stress

The molecular mechanisms that link stress and circadian rhythms still remain unclear. The habenula (Hb) is a key brain region involved in regulating diverse types of emotion-related behaviours while the suprachiasmatic nucleus (SCN) is the bodys central clock. To investigate the effects of chronic social stress on transcription patterns, we performed gene expression analysis in the Hb and SCN of stress naive and stress exposed mice. Our analysis revealed a large number of differentially expressed genes and enrichment of synaptic and cell signalling pathways between resilient and stress-naive mice at ZT16 in both the Hb and SCN. This transcriptomic signature was nighttime-specific and observed only in stress-resilient mice. In contrast, there were relatively few differences between the stress-susceptible and stress-naive groups across timepoints. Our results reinforce the functional link between diurnal gene expression patterns and differential responses to stress, thereby highlighting the importance of temporal expression patterns in homeostatic stress responses.

neuroscience↗

bioRxiv2020

Diatom Modulation of Microbial Consortia Through Use of Two Unique Secondary Metabolites

Unicellular eukaryotic phytoplankton, such as diatoms, rely on microbial communities for survival despite lacking specialized compartments to house microbiomes (e.g., animal gut). Microbial communities have been widely shown to benefit from diatom excretions that accumulate within the microenvironment surrounding phytoplankton cells, known as the phycosphere. However, mechanisms that enable diatoms and other unicellular eukaryotes to nurture specific microbiomes by fostering beneficial bacteria and repelling harmful ones are mostly unknown. We hypothesized that diatom exudates may attune microbial communities and employed an integrated multi-omics approach using the ubiquitous diatom Asterionellopsis glacialis to reveal how it modulates its naturally associated bacteria. We show that A. glacialis reprograms its transcriptional and metabolic profiles in response to bacteria to secrete a suite of central metabolites and two unusual secondary metabolites, rosmarinic acid and azelaic acid. While central metabolites are utilized by potential bacterial symbionts and opportunists alike, rosmarinic acid promotes attachment of beneficial bacteria to the diatom and simultaneously suppresses the attachment of opportunists. Similarly, azelaic acid enhances growth of beneficial bacteria, while simultaneously inhibiting growth of opportunistic ones. We further show that the bacterial response to azelaic acid is widespread in the worlds oceans and taxonomically restricted to a handful of bacterial genera. Our results demonstrate the innate ability of an important unicellular eukaryotic group to modulate their microbial consortia, similar to higher eukaryotes, using unique secondary metabolites that regulate bacterial growth and behavior inversely in different bacterial populations.

microbiology↗

bioRxiv2019

NASQAR: A web-based platform for High-throughput sequencing data analysis and visualization

BackgroundAs high-throughput sequencing applications continue to evolve, the rapid growth in quantity and variety of sequence-based data calls for the development of new software libraries and tools for data analysis and visualization. Often, effective use of these tools requires computational skills beyond those of many researchers. To ease this computational barrier, we have created a dynamic web-based platform, NASQAR (Nucleic Acid SeQuence Analysis Resource). ResultsNASQAR offers a collection of custom and publicly available open-source web applications that make extensive use of a variety of R packages to provide interactive data analysis and visualization. The platform is publicly accessible at http://nasqar.abudhabi.nyu.edu/. Open-source code is on GitHub at https://github.com/nasqar/NASQAR, and the system is also available as a Docker image at https://hub.docker.com/r/aymanm/nasqarall. NASQAR is a collaboration between the core bioinformatics teams of the NYU Abu Dhabi and NYU New York Centers for Genomics and Systems Biology. ConclusionsNASQAR empowers non-programming experts with a versatile and intuitive toolbox to easily and efficiently explore, analyze, and visualize their Transcriptomics data interactively. Popular tools for a variety of applications are currently available, including Transcriptome Data Preprocessing, RNA-seq Analysis (including Single-cell RNA-seq), Metagenomics, and Gene Enrichment.

bioinformatics↗

bioRxiv2019

BioSAILs: versatile workflow management for high-throughput data analysis

MotivationHigh-throughput analysis in the current era of systems biology encompasses a range of analysis workflows for different applications, such as transcriptomics, epigenetics, variant discovery, de novo genome assembly, etc. Many research institutes house a genomics core facility that is responsible for generating high-throughput sequencing data and often includes a core bioinformatics team that carries out data analysis. Core teams must both keep track of data and maintain numerous software packages and databases - which must be scalable according to ever-changing research needs - and they must allocate computational resources to them. Typical data analysis pipelines involve multiple software packages and require the ability to install, execute, and maintain software stacks on a variety of hardware/operating system configurations, including high-performance computing (HPC) facilities, stand-alone servers, and Cloud services. At the same time, individual researchers need to analyze their data and share their analysis steps with collaborators. Having to rely on ad hoc scripts and rigid internally developed pipelines is inefficient, difficult to track and maintain, and ultimately, limits the ability to adapt and evolve as research methods progress.\n\nResultsHere, we present BioSAILs (Bioinformatics Standardized Analysis Information Layers), a scientific workflow management system (WMS) developed by the Core Bioinformatics team at NYU Abu Dhabi. BioSAILs comprises two central components, BioX command and HPCRunner command, supported by BioStacks software stacks. BioX structures executable workflows that may be either run directly on a desktop or lab server, or submitted by HPCRunner to HPC infrastructure or the Cloud. BioSAILs is supported by a range of pre-configured, customizable BioStacks software stacks for various applications (e.g. RNA-seq, de novo genome/transcriptome assembly, variant discovery, etc.) Software stacks are built using Conda and BioConda (6), have been pre-packaged into modules using EasyBuild, and can be deployed with or without BioSAILs. Within the BioSAILs WMS, users can also invoke commands that take advantage of containerized software in Docker (10) and Singularity (8). Finally, the BioSAILs web resource provides documentation, blog posts related to various BioSAILs analysis tasks, forums, knowledge base & FAQs, as well as an interactive web-based workflow editor/creator. BioSAILs is production-level software that has been in use as the main WMS at NYU Abu Dhabi for the past 2 years and is continuously developed and maintained by the core bioinformatics team.\n\nAvailabilityBioSAILs is open source software, available under the GNU license. Online documentation, support and guides can be found at biosails.abudhabi.nyu.edu. The public Github project is available at Github - BioSAILs. HPC-Runner and BioX-Workflow can be installed through Conda using the BioConda channel.

bioinformatics↗