Nizar Drou

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 body’s 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-naïve 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-naïve 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.

The studies on the prevalence and genetic diversity of begomoviruses in Saudi Arabia are minimal. In this study, field-grown symptomatic tomato and muskmelon plants were collected, and initially, begomovirus infection was confirmed by the core coat protein sequences. Four tomato and two muskmelon plants with viral infections were further evaluated for Illumina MiSeq sequencing, and twelve sequences (2.7–2.8 kb) equivalent to the full-length DNA-A or DNA-B components of begomoviruses were obtained along with eight sequences (~1.3–1.4 kb) equivalent to the begomovirus-associated DNA-satellite components. Four begomovirus sequences obtained from tomato plants were variants of tomato yellow leaf curl virus (TYLCV) with nt sequence identities of 95.3–100%. Additionally, two tomato plants showed a mixed infection of TYLCV and cotton leaf curl Gezira virus (CLCuGeV), okra yellow crinkle Cameroon alphasatellite (OYCrCMA), and okra leaf curl Oman betasatellite (OLCuOMB). Meanwhile, from muskmelon plants, two sequences were closely related (99–99.6%) to the tomato leaf curl Palampur virus (ToLCPalV) DNA-A, whereas two other sequences showed 97.9–100% sequence identities to DNA-B of ToLCPalV, respectively. Complete genome sequences of CLCuGeV and associated DNA-satellites were also obtained from these muskmelon plants. The nt sequence identities of the CLCuGeV, OYCrCMA, and OLCuOMB isolates obtained were 98.3–100%, 99.5–100%, and 95.6–99.7% with their respective available variants. The recombination was only detected in TYLCV and OLCuOMB isolates. To our knowledge, this is the first identification of a mixed infection of bipartite and monopartite begomoviruses associated with DNA-satellites from tomato and muskmelon in Saudi Arabia. The begomovirus variants reported in this study were clustered with Iranian isolates of respective begomovirus components in the phylogenetic dendrogram. Thus, the Iranian agroecological route can be a possible introduction of these begomoviruses and/or their associated DNA-satellites into Saudi Arabia.

Exposure to microgravity affects astronauts’ health in adverse ways. However, less is known about the extent to which fibroblast differentiation during the wound healing process is affected by the lack of gravity. One of the key steps of this process is the differentiation of fibroblasts into myofibroblasts, which contribute functionally through extracellular matrix production and remodeling. In this work, we utilized collagen-based three-dimensional (3D) matrices to mimic interstitial tissue and studied fibroblast differentiation under simulated microgravity (sµG). Our results demonstrated that alpha-smooth muscle actin (αSMA) expression and translocation of Smad2/3 into the cell nucleus were reduced upon exposure to sµG compared to the 1g control, which suggests the impairment of fibroblast differentiation under sµG. Moreover, matrix remodeling and production were decreased under sµG, which is in line with the impaired fibroblast differentiation. We further investigated changes on a transcriptomic level using RNA sequencing. The results demonstrated that sµG has less effect on fibroblast transcriptomes, while sµG triggers changes in the transcriptome of myofibroblasts. Several genes and biological pathways found through transcriptome analysis have previously been reported to impair fibroblast differentiation. Overall, our data indicated that fibroblast differentiation, as well as matrix production and remodeling, are impaired in 3D culture under sµG conditions.

Background: As 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). Results: NASQAR 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. Conclusions: NASQAR 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.

Motivation: High-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. Results: Here, we present BioSAILs ( B ioinformatics S tandardized A nalysis I nformation L ayers), 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. Availability: BioSAILs 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.