Project description:Russell’s viper (Daboia russelii) (RV), a category I medically important snake as well as a member of the “Big Four”, is responsible for a heavy toll of snake bite mortality and morbidity in Indian sub-continent. Epidemiological studies suggest highest incidence of RV envenomation in eastern India (EI). In this study the RV venom proteomes from Burdwan and Nadia, the two districts of West Bengal, eastern India was deciphered for the first time using tandem mass spectrometry analysis.
Project description:Both single cell and bulk RNA sequencing was performed on expanding or differentiating snake venom gland organoids (from Aspidelaps Lubricus Cowlesi and Naja Nivea), or tissue (Aspidelaps Lubricus Cowlesi). Bulk RNA sequencing from the snake venom gland, liver and pancreas was performed to construct a de novo transcriptome using Trinity.
Project description:Bridging systems biology and pharmacokinetics–pharmacodynamics has resulted in models that are highly complex and complicated. They usually contain large numbers of states and parameters and describe multiple input–output relationships. Based on any given data set relating to a specific input–output process, it is possible that some states of the system are either less important or have no influence at all. In this study, we explore a simplification of a systems pharmacology model of the coagulation network for use in describing the time course of fibrinogen recovery after a brown snake bite. The technique of proper lumping is used to simplify the 62-state systems model to a 5-state model that describes the brown snake venom–fibrinogen relationship while maintaining an appropriate mechanistic relationship. The simplified 5-state model explains the observed decline and recovery in fibrinogen concentrations well. The techniques used in this study can be applied to other multiscale models.
Project description:High-throughput small RNA sequencing (sRNA-seq) has facilitated many discoveries, but extracellular sRNA (ExRNA) present unique analytical challenges that are not met by current software. Therefore, we developed a novel data analysis pipeline entitled, “TIGER”, which caters to exRNA. To demonstrate the power of this tool, sRNA-seq was performed on high-density lipoproteins (HDL), apolipoprotein B particles (APOB), bile, urine, and liver samples. TIGER was able to characterize approximately 60% of lipoprotein, and >85% of liver, bile, and urine sRNA-seq depth, a significant advance compared to existing software. A key advance for the TIGER pipeline is the ability to analyze host and non-host sRNAs at genomic, parent RNA, and individual fragment levels. Results suggest that the majority of sRNAs on lipoproteins are derived from bacterial sources in the microbiome and environment. Collectively, TIGER facilitated novel discoveries of lipoprotein and biofluid sRNAs and has tremendous applicability for the field of exRNA.