From Left: Dr Meiyappan Lakshamanan, Dr Dave Ow, Lim Pei Yu, Ho Pooi Leng, Ler Wei Xuan, Lokanand Koduru, Dr Ng Say Kong
Science
Commercial probiotic products often come labelled with generic claims on health benefits, such as: “aids digestion”, “relieves colic” etc., and are widely considered to be equally effective to anyone who consumes it. However, various factors including environment, diets, lifestyle, and genetics play key role in determining the efficacy of the probiotic. In our study recently published in Cell Reports 1, we describe a computational approach to assess various probiotic bacteria. Specifically, we evaluate 3 important characteristics: (1) their ability to produce metabolites that are known to be beneficial for humans, (2) their ability to survive and sustain in the intestine, and (3) their impact on other “good” intestinal microbes. We further assessed the effect of various diets, including those containing high carbohydrate, high protein, and high fat-low carbohydrate, on the 3 characteristics described above, and found that high fat-low carbohydrate diet is detrimental to probiotic bacteria. The results and insights derived from this study has the potential to influence probiotic choices and bring clarity to the process of probiotic product selection.
Societal Impact
Probiotic market is currently valued globally at US$ 57.8 billion and is projected to reach US$ 85.4 billion by 2027 2. Public awareness of the health benefits associated with probiotics and rise in gut disorders are the major drivers of their increasing demand 3,4. They are highly relevant to Singapore’s aging community where gut inflammatory disorders are on a rise 5–7. However, specific guidelines which allow public to make a choice on purchasing commercial probiotic products are mostly non-existent. The generic labels claiming health benefits could be misleading and may even expose the consumer to unwarranted risk, especially the individuals with pre-existing health conditions. In this regard, our study 1 attempts to systematize the strain selection via a scientific evidence-based approach. Based on various computational metrics to quantify potential benefits of the probiotic strains, our framework allows for a first-pass screening and a subsequent strain prioritization for clinical interventions. We believe that our approach not only significantly reduces the cost incurred in resource-intensive clinical trials, which often oversee large-scale screening of strain libraries, but also lays foundation for precision and personalized probiotic formulations.
Technical Summary
Probiotic formulations in commercial settings often claim generic health benefits, while largely ignoring environmental, dietary, lifestyle and genetic contexts of the human consumers. Moreover, insights into the components of strain physiology that enable their rational selection are largely lacking. In our study recently published in Cell Reports 1, we describe a systematic in silico framework to assess various probiotic lactic acid bacterial (LAB) strains. Specifically, we reconstructed genome-scale metabolic models of six representative LAB, established a consensus chemically defined medium supporting their growth, validated model predictions on growth and interactions with various gut commensals, profiled the strain transcriptomes and profiled cecal microbiome of mice supplemented with the strains. Integrating these datasets, we developed in silico metrics to estimate the strain capacities for synthesizing beneficial metabolites, known as “postbiotics”, and predict their ability to persist in the gut environment under various dietary regimens. We found that high fat-low carb diet leads to unfavourable probiotic growth and functioning. Our study enables rational strain selection and lays a foundation to precision and personalised probiotics.
Author contributions
L.K., M.L., D.S.-W.O., and D.-Y.L. conceived the project. L.K., P.-Y.L., M.B., and W.X.L. performed LAB experiments, and they profiled culture supernatants with inputs from S.K.N. P.L.H. and D.-S.P. performed commensal culture experiments. L.K. formulated the new LABDM with inputs from D.S.-W.O. L.K., P.-Y.L., and M.L. were involved in transcriptome sequencing and relevant bioinformatics analysis. L.K. and M.L. performed the comparative genomic analyses. Y.Q.L. and D.K. analyzed the microbiome data with inputs from M.L. L.K. and M.L. reconstructed the genome-scale models, developed in silico methods, and implemented them with assistance from Y.Q.L. L.K. and M.L. drafted the initial manuscript. L.K., M.L., D.S.-W.O., and D.-Y.L. were involved in editing and revising the manuscript. D.S.-W.O. and D.-Y.L. supervised and coordinated the project.
References
- 1. Koduru, L. et al. Systematic evaluation of genome-wide metabolic landscapes in lactic acid bacteria reveals diet- and strain-specific probiotic idiosyncrasies. Cell Rep 41, 111735 (2022).
- 2. Probiotics Market Size, Revenue, CAGR, Industry Report. https://www.marketsandmarkets.com/Market-Reports/probiotic-market-advanced-technologies-and-global-market-69.html.
- 3. Abenavoli, L. et al. Gut Microbiota and Obesity: A Role for Probiotics. Nutrients 2019, Vol. 11, Page 2690 11, 2690 (2019).
- 4. Cosme, F., Inês, A. & Vilela, A. Consumer’s acceptability and health consciousness of probiotic and prebiotic of non-dairy products. Food Research International 151, 110842 (2022).
- 5. Ang, T. L. & Yeoh, K. G. Is it time to lower the colorectal cancer screening age in average-risk adults in Singapore? Singapore Med J 62, 617 (2021).
- 6. Butler, L. M. et al. Plasma fatty acids and risk of colon and rectal cancers in the Singapore Chinese Health Study. npj Precision Oncology 2017 1:1 1, 1–10 (2017).
- 7. Low, D., Swarup, N., Okada, T. & Mizoguchi, E. Landscape of inflammatory bowel disease in Singapore. Intest Res 20, 291–296 (2022).