Biology subjects

Brodsky, E.

Publications and source records attributed to Brodsky, E..

5 recordsLinked to original sources

bioRxiv2021

Transcriptomic analysis of DNA damage response in zebrafish embryos under simulated microgravity

Space is an extremely hostile environment. Traveling to space has numerous effects on the body of the astronauts at a molecular level. As space agencies prepare for long-term missions, it becomes important to investigate these problems and address them. Thus, in the current study, we assessed the impact of simulated microgravity on the basic pathways especially DNA damage response. We identified a total of 7542 significantly differentially expressed genes. Out of these genes, 4504 were found to be up-regulated while 3038 were down-regulated in the simulated microgravity group in comparison to controls. Pathway enrichment analysis revealed that simulated microgravity has an effect on vital basic biological processes like DNA damage repair, peptide transport, and metabolism. To explore if the same pathways were also altered in humans, we explored the NASA twin study data and found that DDR was also significantly affected in the astronaut but due to ionizing radiation. Upon further investigation, we found that 62 genes belonging to the DDR pathway were mutually differentially expressed in Scott Kelly and the zebrafish embryos. However, there were 29 significantly differentially expressed genes belonging to the DDR pathway in zebrafish embryos that were not found to be differentially expressed in Scott Kelly. Out of these 29 genes, 14 were specific to zebrafish. Upon further investigation, we found that the DDR pathway is affected differently in simulated microgravity as compared to ionizing radiation. These observations provide a preliminary look into the difference in DDR induced by the different factors of spaceflight.

bioinformatics↗

bioRxiv2021

In silico Analysis of Transcriptomic Profiling and Affected Biological pathways in Multiple Sclerosis

Multiple sclerosis (MS) is a chronic autoimmune, inflammatory neurological disease that is widely associated with Grey and white matter degradation due to the demyelination of axons. Thus exposing the underlying causes of this condition can lead to a novel treatment approach for Multiple Sclerosis. The total RNA microarray processed data from GEO for Multiple sclerotic patients was comprehensively analyzed to find out underlying differences between Grey Matter lesions (GML), Normal appearing Grey Matter (NAGM), and Control Grey matter at the transcriptomics level. Thus, in the current study, we performed various bioinformatics analyses on transcriptional profiles of 184 samples including 105 NAGM, 37 GML, and 42 Controls obtained from the NCBI-Bio project (PRJNA543111). First, exploratory data analysis based on gene expression data using principal component analysis (PCA) depicted distinct patterns between GML and CG samples. Subsequently, the Welchs T-test differential gene expression analysis identified 15,525 significantly differentially expressed genes (p.adj value <0.05, Fold change(>=+/-1.5) between these conditions. This study reveals the genes like CREB3L2, KIF5B, WIPI1, EP300, NDUFA1, ATG101, AND TAF4 as the key features that may substantially contribute to loss of cognitive functions in Multiple sclerosis and several other neurodegenerative disorders. Further, this study also proposes genes associated with Huntingtons disease in Multiple sclerotic patients. Eventually, the results presented here reveal new insights into MS and how it affects the development of male primary sexual characteristics.

neuroscience↗

bioRxiv2021

Analysis of Gene Expression Profiles to study Malaria Vaccine Dose Efficacy & Immune Response Modulation.

Malaria is a life-threatening disease, and the Africa is still one of the most affected endemic regions despite years of policy to limit infection and transmission rates. Further, studies into the variable efficacy of the vaccine are needed to provide a better understanding of protective immunity. Thus, the current study is designed to delineate the effect of the different vaccination doses on the transcriptional profiles of subjects to determine its efficacy and understand the molecular mechanisms underlying the protection this vaccine provides. Here, we used gene expression profiles of pre and post-vaccination patients after various doses of RTS,S based on 275 and 583 samples collected from the GEO datasets. At first, exploratory data analysis based Principal component analysis (PCA) shown the distinct pattern of different doses. Subsequently, differential gene expression analysis using edgeR revealed the significantly (FDR <0.005) 158 down-regulated and 61 upregulated genes between control vs. Controlled Human Malaria Infection (CHMI) samples. Further, enrichment analysis of significant genes using Annotation and GAGE tools delineate the involvement of CCL8, CXCL10, CXCL11, XCR1, CSF3, IFNB1, IFNE, IL12B, IL22, IL6, IL27, etc.,genes which found to be upregulated after earlier doses but downregulated after the 3rd dose in cytokine-chemokine pathways. Notably, we identified 13 cytokine genes whose expression significantly varied during three doses. Eventually, these findings give insight to the dual role of cytokine responses in malaria pathogenesis and variations in their expression patterns after various doses of vaccination involved in protection.

bioinformatics↗

bioRxiv2021

In Silico Analysis and Characterization of Differentially Expressed Genes to Distinguish Glioma Stem Cells from Normal Neural Stem Cells

Glioblastoma multiforme (GBM) is a heterogeneous, invasive primary brain tumor that develops chemoresistance post therapy. Theories regarding the aetiology of GBM focus on transformation of normal neural stem cells (NSCs) to a cancerous phenotype or tumorigenesis driven via glioma stem cells (GSCs). Comparative RNA-Seq analysis of GSCs and NSCs can provide a better understanding of the origin of GBM. Thus, in the current study, we performed various bioinformatics analyses on transcriptional profiles of a total 40 RNA-seq samples including 20 NSC and 20 GSC, that were obtained from the NCBI-SRA (SRP200400). First, differential gene expression (DGE) analysis using DESeq2 revealed 348 significantly differentially expressed genes between GSCs and NSCs (padj. value <0.05, log2fold change [≥] 3.0 (for GSCs) and [≤] -3.0 (for NSCs)) with 192 upregulated and 156 downregulated genes in GSCs in comparison to NSCs. Subsequently, exploratory data analysis using principal component analysis (PCA) based on key significant genes depicted the clear separation between both the groups. Further, Hierarchical clustering confirmed the distinct clusters of GSC and NSC samples. Eventually, the biological enrichment analysis of the significant genes showed their enrichment in tumorigenesis pathways such as Wnt-signalling, VEGF-signalling and TGF-{beta}-signalling pathways. Conclusively, our study depicted significant differences in the gene expression patterns between NSCs and GSCs. Besides, we also identified novel genes and genes previously unassociated with gliomagenesis that may prove to be valuable in establishing diagnostic, prognostic biomarkers and therapeutic targets for GBM.

cancer biology↗

bioRxiv2021

Radiation Threats to Humans in Space and an alternative approach with Probiotics

Space type radiation is an important factor to consider for scientists on International Space Stations, especially high linear transfer energy (LET) since it has imminent effects on microorganisms. The abundances of bacteria are a good indicator of how radiation influences the gut microbiome. The current study is an attempt towards this; thus, we have employed a public dataset (Bioproject code PRJNA368790) of 80 mice samples treated with a range of doses from 0Gy to 1Gy and feces samples were collected at different time points of post radiation treatment. Metagenomic analysis was performed on this data to understand the effect of radiation doses on the abundance of microbial species or microbial diversity implementing the DADA2 and Phyloseq pipelines. Our analyses have shown that 0.1Gy high LET radiation had the significant effect on the species of bacteria. There is a significant decrease in four types of bacteria, i.e., Bifidobacterium longum, Bifidobacterium castoris, Lactobacillus gasseri and Lactobacillus johnsonii, with p-value of 7.05x10-5, 0.020, 0.057and 0.020, respectively. Additionally, pathway analysis indicates the protein coding products of these bacteria are involved in the GABAergic synaptic pathway. Further, our study has shown the significant difference between post radiation time points, i.e., 10 days vs.30 days and suggested the acclimatization period could be around 10 days for these bacteria.

microbiology↗