ATLANTIS - Attractor Landscape Analysis Toolbox for Cell Fate Discovery and Reprogramming

作者：Shah Osama Shiraz; Chaudhary Muhammad Faizyab Ali; Awan Hira Anees; Fatima Fizza; Arshad Zainab; Amina Bibi; Ahmed Maria; Hameed Hadia; Furqan Muhammad; Khalid Shareef; Faisal Amir; Chaudhary Safee Ullah^*

来源：Scientific Reports, 2018, 8(1): 3554.

DOI：10.1038/s41598-018-22031-3

Boolean modelling of biological networks is a well-established technique for abstracting dynamical biomolecular regulation in cells. Specifically, decoding linkages between salient regulatory network states and corresponding cell fate outcomes can help uncover pathological foundations of diseases such as cancer. Attractor landscape analysis is one such methodology which converts complex network behavior into a landscape of network states wherein each state is represented by propensity of its occurrence. Towards undertaking attractor landscape analysis of Boolean networks, we propose an Attractor Landscape Analysis Toolbox (ATLANTIS) for cell fate discovery, from biomolecular networks, and reprogramming upon network perturbation. ATLANTIS can be employed to perform both deterministic and probabilistic analyses. It has been validated by successfully reconstructing attractor landscapes from several published case studies followed by reprogramming of cell fates upon therapeutic treatment of network. Additionally, the biomolecular network of HCT-116 colorectal cancer cell line has been screened for therapeutic evaluation of drug-targets. Our results show agreement between therapeutic efficacies reported by ATLANTIS and the published literature. These case studies sufficiently highlight the in silico cell fate prediction and therapeutic screening potential of the toolbox. Lastly, ATLANTIS can also help guide single or combinatorial therapy responses towards reprogramming biomolecular networks to recover cell fates.

• 出版日期2018-2-23