Biology subjects

Sonawane, A.

Publications and source records attributed to Sonawane, A..

4 recordsLinked to original sources

bioRxiv2022

The Network Zoo: a multilingual package for the inference and analysis of biological networks

Inference and analysis of cellular biological networks requires software tools that integrate multi-omic data from various sources. The Network Zoo (netZoo; netzoo.github.io) is an open-source software suite to model biological networks, including context-specific gene regulatory networks and multi-omics partial correlation networks, to conduct differential analyses, estimate community structure, and model the transitions between biological states. The netZoo builds on our ongoing development of network methods, harmonizing the implementations in various computing languages (R, Python, MATLAB, and C) and between methods to allow a better integration of these tools into analytical pipelines. To demonstrate the value of this integrated toolkit, we analyzed the multi-omic data from the Cancer Cell Line Encyclopedia (CCLE) by inferring gene regulatory networks for each cancer cell line and associating network features with other phenotypic attributes such as drug sensitivity. This allowed us to identify transcription factors that play a critical role in both drug resistance and cancer development in melanoma. We also used netZoo to build a pan-cancer, multi-tiered CCLE map and used it to identify known metabolic hallmarks of cancer and to estimate novel context-specific elements that mediate post-transcriptional regulation. Because the netZoo tools are open-source and there is a growing community of both users and developers, we built an ecosystem to support community contributions, share use cases, and visualize networks online. As additional data types become available and our suite of methods grows, we will expand "the zoo" to incorporate an increasingly sophisticated collection of tools for network inference and analysis.

genomics↗

bioRxiv2021

ETV2 regulates PARP-1 binding protein to induce ER stress-mediated cell death in tuberin-deficient cells

Lymphangioleiomyomatosis (LAM) is a rare progressive disease, characterized by mutations in the tuberous sclerosis complex genes (Tsc1 or Tsc2), and hyperactivation of mechanistic target of rapamycin complex 1 (mTORC1). The effectiveness of mTORC1 inhibitors is limited by their lack of cytotoxic effects. Here, we report that E26 transformation specific (ETS) Variant Transcription Factor 2 (ETV2) is a critical regulator of Tsc2-deficient cell survival. Nuclear localization of ETV2 in Tsc2-deficient cells is mTORC1-independent and is enhanced by spleen tyrosine kinase (Syk) inhibition. In the nucleus, ETV2 transcriptionally regulates poly(ADP-ribose) polymerase 1 binding protein (PARPBP), a coregulator of transcription, mRNA and protein expression. Silencing of ETV2 or PARPBP in Tsc2-deficient cells induced ER-stress and increased cell death in vitro and in vivo. We also found ETV2 expression in human cells with loss of heterozygosity for TSC2 lending support to the translational relevance of our findings. In conclusion, we report a novel signaling axis unique to Syk-inhibition is mTORC1-independent and promotes a cytocidal response in Tsc2-deficient cells, and therefore, maybe a potential alternative therapeutic target in LAM.

cell biology↗

bioRxiv2021

GRAND: A database of gene regulatory network models across human conditions

Gene regulation plays a fundamental role in shaping tissue identity, function, and response to perturbation. Regulatory processes are controlled by complex networks of interacting elements, including transcription factors, miRNAs and their target genes. The structure of these networks helps to determine phenotypes and can ultimately influence the development of disease or response to therapy. We developed GRAND (https://grand.networkmedicine.org) as a database for gene regulatory network models that can be compared between biological states, or used to predict which drugs produce changes in regulatory network structure. The database includes 12,468 genome-scale networks covering 36 human tissues, 28 cancers, 1,378 unperturbed cell lines, as well as 173,013 TF and gene targeting scores for 2,858 small molecule-induced cell line perturbation paired with phenotypic information. GRAND allows the networks to be queried using phenotypic information and visualized using a variety of interactive tools. In addition, it includes a web application that matches disease states to potentially therapeutic small molecule drugs using regulatory network properties. Graphical abstract O_FIG_DISPLAY_L [Figure 1] M_FIG_DISPLAY Modeling gene regulation across human conditions integrates cancer tissues and cell lines, small molecules, and normal tissue networks. C_FIG_DISPLAY

genomics↗

bioRxiv2017

Mycobacterium tuberculosis LprE enhances bacterial persistence by inhibiting cathelicidin and autophagy in macrophages

Mycobacterium tuberculosis(Mtb) lipoproteins are known to facilitate bacterial survival by manipulating the host immune responses. Here, we have characterized a novel Mtb lipoprotein LprE(LprEMtb), and demonstrated its role in mycobacterial survival. LprEMtb acts by down-regulating the expression of cathelicidin, Cyp27B1, VDR and p38-MAPK via TLR-2 signaling pathway. Deletion of lprEMtb resulted in induction of cathelicidin and decreased survival in the host. Interestingly, LprEMtb was also found to inhibit autophagy mechanism to dampen host immune response. Episomal expression of LprEMtb in non-pathogenic Mycobacterium smegmatis(Msm) increased bacillary persistence by down-regulating the expression of cathelicidin and autophagy, while deletion of LprEMtb orthologue in Msm, had no effect on cathelicidin and autophagy expression. Moreover, LprEMtb blocked phago-lysosome fusion by suppressing the expression of EEA1, Rab7 and LAMP-1 endosomal markers by down-regulating IL-12 and IL-22 cytokines. Our results indicate that LprEMtb plays an important role in mycobacterial pathogenesis in the context of innate immunity.

physiology↗