Omics strategies decipher therapeutic discoveries of traditional Chinese medicine against different diseases at multiple layers molecular-level

Traditional Chinese medicine (TCM) has been broadly used for the personalized treatment of many diseases in China for thousands of years. In the past century, TCM was also introduced to other Asian countries and even the Western world. Increasing evidence has shown that TCM has the capacity to treat numerous complex diseases in the clinic, such as cardiovascular diseases (CVDs), infectious diseases, metabolic diseases, and neurodegenerative diseases. However, the earlier lack of analytical strategies to annotate the chemical complexity has severely impeded the modern study and translational application of TCM. This critical review aims to explore and exploit applications of systems biology-driven omics methods in TCM against a diversity of diseases, toward the specific use of TCM to treat patients with different diseases. Such effort shall enhance the applicability of systems biology-driven omics strategies in deciphering the mechanisms by which TCM treats different diseases and may lead to the discovery of new therapeutic directions. In addition, we proposed the possible strategies to innovate the applicable pattern of omics technologies in TCM niches, such as precision-modification metabolomics and chinmedomics methods, allowing to unveil the complexity of TCM, which must enable TCM to serve better for the population-health. Taken together, this review eventually shall highlight the core value of omics technologies in innovating TCM to combat the diseases in a new horizon.

Improved Scalability of Neuron-Based Phenotypic Screening Assays for Therapeutic Discovery in Neuropsychiatric Disorders

There is a pressing need to improve approaches for drug discovery related to neuropsychiatric disorders (NSDs). Therapeutic discovery in neuropsychiatric disorders would benefit from screening assays that can measure changes in complex phenotypes linked to disease mechanisms. However, traditional assays that track complex neuronal phenotypes, such as neuronal connectivity, exhibit poor scalability and are not compatible with high-throughput screening (HTS) procedures. Therefore, we created a neuronal phenotypic assay platform that focused on improving the scalability and affordability of neuron-based assays capable of tracking disease-relevant phenotypes. First, using inexpensive laboratory-level automation, we industrialized primary neuronal culture production, which enabled the creation of scalable assays within functioning neural networks. We then developed a panel of phenotypic assays based on culturing of primary neurons from genetically modified mice expressing HTS-compatible reporters that capture disease-relevant phenotypes. We demonstrated that a library of 1,280 compounds was quickly screened against both assays using only a few litters of mice in a typical academic laboratory setting. Finally, we implemented one assay in a fully automated high-throughput academic screening facility, illustrating the scalability of assays designed using this platform. These methodological improvements simplify the creation of highly scalable neuron-based phenotypic assays designed to improve drug discovery in CNS disorders.

MicroRNAs: tools of mechanistic insights and biological therapeutics discovery for the rare neurogenetic syndrome Lesch-Nyhan disease (LND)

MicroRNAs (miRNAs) are small regulatory RNAs that modulate the translation of mRNA. They have emerged over the past few years as indispensable entities in the transcriptional regulation of genes. Their discovery has added additional layers of complexity to regulatory networks that control cellular homeostasis. Also, their dysregulated pattern of expression is now well demonstrated in myriad diseases and pathogenic processes. In the current review, we highlight the role of miRNAs in Lesch-Nyhan disease (LND), a rare neurogenetic syndrome caused by mutations in the purine metabolic gene encoding the hypoxanthine-guanine phosphoribosyltransferase (HPRT) enzyme. We describe how experimental and biocomputational approaches have helped to unravel genetic and signaling pathways that provide mechanistic understanding of some of the molecular and cellular basis of this ill-defined neurogenetic disorder. Through miRNA-based target predictions, we have identified signaling pathways that may be of significance in guiding biological therapeutic discovery for this incurable neurological disorder. We also propose a model to explain how a gene such as HPRT, mostly known for its housekeeping metabolic functions, can have pleiotropic effects on disparate genes and signal transduction pathways. Our hypothetical model suggests that HPRT mRNA transcripts may be acting as competitive endogenous RNAs (ceRNAs) intertwined in multiregulatory cross talk between key neural transcripts and miRNAs. Overall, this approach of using miRNA-based genomic approaches to elucidate the molecular and cellular basis of LND and guide biological target identification might be applicable to other ill-defined rare inborn-error metabolic diseases.