Automated cellular imaging platform efficiently and accurately predicts toxicity of chemical compounds paving the way toward safer products
Singapore — Researchers at A*STAR's Bioinformatics Institute (BII) and the Institute of Bioengineering and Nanotechnology (IBN) have developed a highly efficient and accurate cellular imaging platform for predicting the toxicity of compounds to the kidney. The approach, which combines cell culture, imaging and computational methods, could prove invaluable to companies from the food, nutrition, cosmetics, consumer care, chemical and pharmaceutical industries by enabling them to predict the safety of their products while in development.
Chemical compounds, which may originate from medicine, food or even the environment, could injure the kidney and impair its function of eliminating waste from the body. About 20% of hospital or community acquired cases of acute kidney injury can be attributed to nephrotoxic drugs. Currently there is no accurate method for screening large numbers of potentially nephrotoxic compounds with diverse chemical structures.
Existing approaches for predicting the toxicity of chemical compounds include animal testing, which involves high costs and long turnaround times that result in low throughput, making it unsuitable for screening the ever-increasing numbers of potentially nephrotoxic compounds used in products. On top of the ethical issues involved, animal testing may also result in poor prediction of human toxicity due to inter-species differences. Other methods of nephrotoxicity screening are also slow, laborious and costly, or may require prior knowledge of the compounds' chemical structures or mechanisms.
Over the past three years, researchers from IBN and BII have worked together to develop cell-based screening methods to address this highly critical need, particularly as animal testing bans for cosmetics have been implemented in the EU, Norway, India and Israel, with many more countries expected to follow suit. The A*STAR researchers were able to develop the first and only cell-based renal screening platforms that can predict nephrotoxicity with high accuracy. Improving on this, the researchers have now developed an imaging-based method that can be used to test much larger numbers of compounds.
Dr Lit-Hsin Loo, Principal Investigator from BII who co-authored the study, said "By automatically analysing more than 25,000 microscopy images of cells treated with different compounds, we were able to identify phenotypic signatures of kidney cells that can be used to predict the in vivo toxicity of compounds with diverse structures and mechanisms, with a validated accuracy of 80 – 90%."
In this study, more than 2 million individual cells were screened for their reactions to over 40 different chemical compounds, including industrial chemicals, antibiotics, antivirals, chemotherapy drugs and agricultural chemicals. The analysis was performed using an automated image analysis software called "cellXpress" that was developed by Dr Loo's team at BII.
Dr Daniele Zink, Team Leader and Principal Research Scientist from IBN who co-authored the paper, added, "This novel software platform reduces the reliance on existing laborious and time-consuming methods currently available for testing of nephrotoxic compounds, enabling much faster predictions. We will continue to work together to improve and further validate the use of this approach, and hope that our work will help to make products safer for consumers and patients".
Figure 1. "cellXpress", an automated imaging analysis software, is able to efficiently and accurately detect cellular responses (reflected in green) to nephrotoxic compounds. (refer to attached pdf)
Figure 2. BII and IBN researchers who developed the world's first high-throughput imaging platform for predicting kidney toxicity (clockwise from bottom left) : Dr Ran Su, Dr Lit-Hsin Loo, Dr Daniele Zink and Dr Sijing Xiong).
Notes to Editor:
The research findings described in this media release can be found in the journal:
Archives of Toxicology, under the title, "High-throughput imaging-based nephrotoxicity prediction for xenobiotics with diverse chemical structures" by Ran Su1, Sijing Xiong2, Daniele Zink2, Lit-Hsin Loo1,3
1 Bioinformatics Institute, 30 Biopolis Street, #07-01 Matrix, Singapore 138671, Singapore
2 Institute of Bioengineering and Nanotechnology, 31 Biopolis Way, Nanos, Singapore 138671, Singapore
3Department of Pharmacology, Yong Loo Lin School of Medicine, National University of Singapore, 10 Medical Drive, Singapore 117597, Singapore
Correspondence and requests for materials should be addressed to Daniele Zink (firstname.lastname@example.org) and Lit-Hsin Loo (email@example.com).