We are a computational biology research group with members coming from different scientific disciplines, including chemistry, cell biology, computer science, and bioinformatics.
The overall goal of our research is to understand the modes of action (MoAs) of xenobiotics, such as environmental agents and drugs; and predict their human efficacy and/or toxicity. We develop and use novel phenotypic and molecular profiling methods to elucidate the MoAs of xenobiotics, and build computational models that can predict the in vivo effects of these agents.
We collaborate with different academic, clinical, industrial, and governmental research groups, including Institute of Molecular and Cell Biology (IMCB), NanoBioLab (NBL), Institute of Bioengineering and Nanotechnology (IBN) (all three from A*STAR), Singapore General Hospital (SGH), the United States Environmental Protection Agency (US EPA), and the Netherlands National Institute for Public Health and the Environment (RIVM).
Our current research is focused on three major areas, namely phenotypic profiling and digital pathology, toxicodynamics of xenobiotics, and pulmonary effects of xenobiotics (Fig. 1).
Phenotypic profiling is a computational procedure to construct quantitative and compact representations of cellular or tissue phenotypes based on images obtained from high-throughput microscopy (Bougen-Zhukov et al., 2017). We have developed several phenotypic profiling methods, including the Drug-Profiling (“D-profiling”) algorithm (Loo et al., 2007) and the Protein-localization Profiling (“P-profiling”) algorithm (Loo et al., 2014). We also develop a user-friendly and efficient phenotypic profiling software called “cellXpress” (Laksameethanasan et al., 2013), which can handle terabytes of image data collected under large numbers of experimental conditions. Phenotypic profiles constructed using these methods have been used to classify the effects of small molecules (Loo et al., 2007, 2009), or assess potentially toxic effects of environmental agents (Friedman et al., 2019; Lee et al., 2018; and Su et al., 2016). Recently, we have also developed a new digital histopathology platform based on phenotypic profiling for cancer diagnosis and prognosis (Fig. 2). The platform can help researchers and clinicians to rapidly and accurately quantify the effects of cancer therapeutic agents, resulting in more systematic clinical decision-making processes.
Many xenobiotics have unknown and/or non-specific intracellular targets. To study the toxicodynamics of these chemicals, unbiased approaches that do not require prior information about the targets or mechanisms of the chemicals are required. Together with eight other research teams from A*STAR, we are developing the Toxicity Mode-of-Action Discovery (ToxMAD) Platform to elucidate the modes of action of xenobiotics in major target cell types using advanced phenotypic, signaling, and genomic profiling methods. Our focus is to study chemical analogs with related structures but differential cellular effects, and develop fit-for-purpose assays that will be used by regulatory agencies and industrial research laboratories to assess chemical safety. In 2019, we participated in an international case study that demonstrates the utility of in vitro bioactivity as a lower bound estimate of in vivo adverse effect levels in risk-based prioritization (Friedman et al., 2019).
Human lungs are exposed to inhaled or blood-borne soluble xenobiotics that may originate from the environment, food, consumer products, and/or pharmaceuticals. We are broadly interested in the understanding the biological targets and pathways affected by these chemicals in the lung cells. We have recently developed a high-throughput and predictive in vitro pulmonary toxicity assay (Fig. 3; Lee et al., 2018). We found that the resulting assay based on two phenotypic features of a human bronchial epithelial cell line, BEAS-2B, can accurately classify 33 reference chemicals with human pulmonotoxicity information (88.8% balance accuracy, 84.6% sensitivity, and 93.0% specificity). We also studied the effects of talc particles, a sclerosis agent commonly used in the management of malignant pleural effusions, in human lung cancer cells (Bougen-Zhukov, et al., 2019). We found a novel role of the PI3K pathway in talc-induced cell death and IL-6 secretion, which are key cellular events known to drive pleural fibrosis. This provides a better understanding of the mechanisms of talc sclerosis in the malignant pleural space.
Loo Lit Hsin is a Senior Principal Investigator at the Bioinformatics Institute (BII), A*STAR, Singapore. He is leading an interdisciplinary team of scientists developing in vitro and computational models for predicting the toxicity and/or targets of chemical compounds with diverse or unknown structures. His team has developed novel imaging-based phenotypic profiling methods and tools that led to the first high-throughput and predictive in vitro platform for nephrotoxicity prediction. Dr. Loo is also an adjunct Assistant Professor at the Department of Pharmacology, Yong Loo Lin School of Medicine, National University of Singapore. He was the recipient of the Lush Prize – Science Award (2016), Award for Excellence in Postdoctoral Research (2010) and the Alfred Gilman Award (2009) by the University of Texas Southwestern (UTSW) Medical Center, and the Doctoral Award in Mathematical Sciences and Engineering (2005) by Drexel University. Dr. Loo was a postdoctoral fellow in the Bauer Center for Genomics Research at Harvard University (2005), and then in the Department of Pharmacology at the UTSW Medical Center, USA (2005-2010).
Dr. Loo’s background is in computational and systems biology. His team has previously developed novel high-throughput imaging-based phenotypic profiling (HIPPTox) methods that led to highly predictive in vitro assays for kidney and lung toxicities. Under the IFCS Programme, he is responsible to integrate various unique molecular and phenotypic profiling technologies developed in multiple A*STAR research institutes into a single platform, called the ToxMAD Platform, for elucidating the targets and modes of action of chemicals. Dr. Loo is also leading A*STAR’s participations in the International Workgroup on Accelerating the Pace of Chemical Risk Assessments (APRCA) and the associated Point-of-Departure case study.