Application of Transcriptomics for Predicting Protein Interaction Networks, Drug Targets and Drug Candidates.

Protein interaction pathways and networks are critically-required for a vast range of biological processes. Improved discovery of candidate druggable proteins within specific cell, tissue and disease contexts will aid development of new treatments. Predicting protein interaction networks from gene expression data can provide valuable insights into normal and disease biology. For example, the resulting protein networks can be used to identify potentially druggable targets and drug candidates for testing in cell and animal disease models. The advent of whole-transcriptome expression profiling techniques-that catalogue protein-coding genes expressed within cells and tissues-has enabled development of individual algorithms for particular tasks. For example,: (i) gene ontology algorithms that predict gene/protein subsets involved in related cell processes; (ii) algorithms that predict intracellular protein interaction pathways; and (iii) algorithms that correlate druggable protein targets with known drugs and/or drug candidates. This review examines approaches, advantages and disadvantages of existing gene expression, gene ontology, and protein network prediction algorithms. Using this framework, we examine current efforts to combine these algorithms into pipelines to enable identification of druggable targets, and associated known drugs, using gene expression datasets. In doing so, new opportunities are identified for development of powerful algorithm pipelines, suitable for wide use by non-bioinformaticians, that can predict protein interaction networks, druggable proteins, and related drugs from user gene expression datasets.

Single-cell RNA sequencing predicts motility networks in purified human gastric interstitial cells of Cajal.

BACKGROUND: Gastrointestinal (GI) motility disorders affect millions of people worldwide, yet they remain poorly treated in part due to insufficient knowledge of the molecular networks controlling GI motility. Interstitial cells of Cajal (ICC) are critical GI pacemaker cells, and abnormalities in ICC are implicated in GI motility disorders. Two cell surface proteins, KIT and ANO1, are used for identifying ICC. However, difficulties accessing human tissue and the low frequency of ICC in GI tissues have meant human ICC are insufficiently characterized. Here, a range of characterization assays including single-cell RNA sequencing (scRNA-seq) was performed using KIT+ CD45- CD11B- primary human gastric ICC to better understand networks controlling human ICC biology. METHODS: Excess sleeve gastrectomy tissues were dissected; ICC were analyzed by immunofluorescence, fluorescence-activated cell sorting (FACSorting), real-time PCR, mass spectrometry, and scRNA-seq. KEY RESULTS: Immunofluorescence identified ANO1+ /KIT+ cells throughout the gastric muscle. Compared to the FACSorted negative cells, PCR showed the KIT+ CD45- CD11B- ICC were enriched 28-fold in ANO1 expression (p < 0.01). scRNA-seq analysis of the KIT- CD45+ CD11B+ and KIT+ CD45- CD11B- ICC revealed separate clusters of immune cells and ICC (respectively); cells in the ICC cluster expressed critical GI motility genes (eg, CAV1 and PRKG1). The scRNA-seq data for these two cell clusters predicted protein interaction networks consistent with immune cell and ICC biology, respectively. CONCLUSIONS & INFERENCES: The single-cell transcriptome of purified KIT+ CD45- CD11B- human gastric ICC presented here provides new molecular insights and hypotheses into evolving models of GI motility. This knowledge will provide an improved framework to investigate targeted therapies for GI motility disorders.

Single cell RNA-sequencing data generated from human pluripotent stem cell-derived lens epithelial cells.

Detailed transcriptomic analyses of differentiated cell populations derived from human pluripotent stem cells is routinely used to assess the identity and utility of the differentiated cells. Here we provide single cell RNA-sequencing data obtained from ROR1-expressing lens epithelial cells (ROR1e LECs), obtained via directed differentiation of CA1 human embryonic stem cells. Analysis of the data using principal component analysis, heat maps and gene ontology assessments revealed phenotypes associated with lens epithelial cells. These data provide a resource for future characterisation of both normal and cataractous human lens biology. Corresponding morphological and functional data obtained from ROR1e LECs are reported in the associated research article "A simplified method for producing human lens epithelial cells and light-focusing micro-lenses from pluripotent stem cells " (Dewi et al., 2020).

A simplified method for producing human lens epithelial cells and light-focusing micro-lenses from pluripotent stem cells.

Here we describe a modified method for harvesting tens-of-millions of human lens epithelial-like cells from differentiated pluripotent stem cell cultures. To assess the utility of this method, we analysed the lens cell population via: light microscopy; single cell RNA-sequencing and gene ontology analyses; formation of light-focusing micro-lenses; mass spectrometry; and electron microscopy. Both individually and collectively, the data indicate this simplified harvesting method provides a large-scale source of stem cell-derived lens cells and micro-lenses for investigating human lens and cataract formation.

Women's health during mid-life survey: the use of complementary and alternative medicine by symptomatic women transitioning through menopause in Sydney.

OBJECTIVE: To survey the extent of complementary and alternative medicine (CAM) use among women for the alleviation of menopausal symptoms. DESIGN: A total of 1,296 eligible women aged 45 to 65 years were recruited from three Sydney menopause clinics, general practice clinics, and government agencies between July 2003 and July 2004. Volunteers were invited to complete a 19-item questionnaire covering basic demographics, general health status, use of CAM therapies and products, use of pharmaceuticals, and sources of CAM advice. RESULTS: Of respondents, 53.8% had visited a CAM practitioner and/or used a CAM product during the past year, with 34% using a product only and 5% consulting a practitioner only. The most commonly visited practitioners were naturopaths (7.2%) and acupuncturists (4.8%), whereas the most popular products were soy (25.4%) and evening primrose oil (18.4%). Massage, chiropractic, and nutrition were rated the most effective therapies, and phytoestrogen tablets, evening primrose oil, and black cohosh were deemed the most effective products. Of the 59.9% of respondents currently using prescription or over-the-counter pharmaceuticals, 62.5% reported using CAM products during the past 12 months. Of CAM users 71% had informed their doctor about CAM use, whereas 26.4% of respondents reported their doctor had inquired about CAM use. CONCLUSIONS: CAM use by women to alleviate menopausal symptoms is common, with several therapies perceived to be effective. Although a significant proportion of women may use CAM in conjunction with pharmaceuticals, relevant communication between medical practitioners and patients remains inadequate and may expose the patient to potential drug-herb interactions.