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BestTreat – Building a Gut Microbiome Engineering Toolbox for In-Situ Therapeutic Treatments for Non-alcoholic Fatty Liver Disease

Periodic Reporting for period 2 - BestTreat (BestTreat – Building a Gut Microbiome Engineering Toolbox for In-Situ TherapeuticTreatments for Non-alcoholic Fatty Liver Disease)

Reporting period: 2020-09-01 to 2022-08-31

An imbalance in the gut microbiome impacts the development of cardiovascular disease and metabolic syndrome, including its components type-2 diabetes and obesity. Gut microbiome imbalance and intestinal permeability appear to play a role in the progression of non-alcoholic fatty liver disease (NAFLD) progression, although the exact interaction of gut microbiota and NAFLD is still poorly understood.
NAFLD describes a range of conditions caused by the accumulation of excess fat in the liver. Reports indicate an estimated global incidence of 24% of the disease. In its early stage, it usually causes no harm, but can develop into severe liver damage, such as steatohepatitis and liver cirrhosis. Furthermore, scientists believe that NAFLD could be a major cause for liver cancer.
The goal of the BestTreat program is to study the role of the gut microbiome in the progression of NAFLD. To do this, we analyze the differences between the microbiome of healthy people and that of people with NAFLD and we investigated how dietary and lifestyle interventions can benefit NAFLD patients by restructuring the composition of gut bacteria.
The overall objectives of the program are:
i) To combine data- and hypothesis-driven approaches with emerging experimental technologies to identify new therapeutic avenues for NAFLD based on engineered gut microbes,
ii) To investigate the complex interactions between the gut microbiome and the host’s phentoype as well as,
iii) To understand the role of microbiome imbalance on NAFLD progression and to identify new therapeutic avenues for NAFLD.
In this project, we identified early microbiome and metabolites markers for NAFLD. Using this information and integrating it with clinical metadata, we generated a model that can assess the risk of a patient developing NAFLD. Our model, which is based on machine learning and taking into consideration microbiome features, outperforms existing clinical screening tools. These results serve as a proof-of-concept for developing highly accurate and explanatory AI-tools for NAFLD diagnosis.
We also conducted the first study characterizing metabolic changes in NAFLD patients due to physical exercise in various sample matrices. We demonstrated that a 12-week high-intensity interval training exercise program improves the condition of NAFLD patients on a whole-body level, and this is achieved even without requiring dietary changes and without significant weight loss. Exercise decreased blood glucose levels and increased exercise parameters that protect against hyperglycemia. We observed several metabolomic signatures indicating that NAFLD patients doing exercise have better use and metabolism of glucose, but also different metabolism of amino acids, lipids, and bile acids.
In a separate study, we followed NAFLD patients who consumed a normal diet or a resistant starch (a prebiotic nondigestible fiber that feeds beneficial bacteria in the gut) for 4 months. We found that the dietary switch to resistant starch consumption alters gut microbiota and metabolites and improves clinical parameters. In NAFLD patients we found that one species, Bacteroides stercoris, is associated with poor liver status and performance, and the change in the diet improves all these parameters and decreases the presence of Bacteroides stercoris in the gut. Moreover, we could prove that Bacteroides stercoris promotes NAFLD progression in a mouse model of the disease.
One of the aims of BestTreat was to screen and select beneficial bacterial solutions for the treatment of NAFLD. We screened a broad group of bacterial strains for traits with potential benefits in NAFLD in vitro and selected two strains for further analysis in animal models.If the experiments in animals prove positive, we plan to scale up production for use in dietary supplements, infant formulae, or pharmaceutical products.
We also explored engineered microbial strains for therapeutic use. We engineered the probiotic Escherichia coli Nissle 1917 (EcN) to express Aldafermin, a potential treatment option for patients with NAFLD. We tested the beneficial role of these strains in a comprehensive study in mice, analyzing anatomical, histological, and clinical features, as well as transcriptomics and metabolomic profiles. We found that the administration of these engineered strains has numerous beneficial effects in a mouse model of NAFLD. Our results suggest the potential efficacy of engineered EcN strains in combination with dietary changes as a novel non-invasive strategy to treat NAFLD condition, with clear benefits in restoring lipid metabolism and AA dysfunctions commonly observed in NAFLD patients.
To ensure the dissemination of our action, all publications arising from the BestTreat program are open-access and can be obtained from our Website (www.besttreat.eu).
The recent explosion of metagenomic data generation calls for new computational approaches that provide a more dynamic description of the host-microbe interactions. Applying microbiome systems biology approaches in BestTreat we could go beyond statistical and comparative studies and approach microbiome research across multiple levels. We are moving from correlative to causal evidence between microbiome shifts and the pathophysiology of NAFLD. At BestTreat we exploited cross-sectional, prospective, and randomized controlled intervention studies in patients with the disease. Not only that, but we also use a combination of emerging new technologies, including transplantation of human fecal microbiota and evaluation of microbial consortia in stem cell lines and artificial gut systems. By conducting a comprehensive bedside-to-bench-to-bedside study we expect to offer novel therapy solutions in the form of live biotherapeutics for NAFLD.
The BestTreat research program aimed to generate meaningful scientific knowledge, as well as to integrate and train students to tackle challenges with high industrial and socio-economic impact for which no solutions are currently available. With the end of the action, we can undoubtedly state that BestTreat has had a meaningful impact on diverse actors.
Firstly, our scientific discoveries will be highly relevant for the future of European research within the field of gut microbiota, with direct applications in novel therapeutics, which will be beneficial for European industrial competitiveness. Secondly, at BestTreat young researchers have been trained by internationally renowned experts from both academic and non-academic sectors to obtain innovative solutions with a major impact on the European economy. Finally, BestTreat’s action has a strong socio-economic impact with broad societal implications. Our NAFLD risk assessment model based on machine learning methods serves as a proof-of-concept to develop highly accurate and explanatory AI tools for the diagnosis of NAFLD. These could be used by virtually every NAFLD patient or at risk of developing it, which in the EU alone accounts for more than 150 million. Furthermore, our results on exercise and prebiotic diets highlight the efficacy of simple lifestyle interventions. Moreover, we hope to revolutionize NAFLD clinical management with our innovative engineered microbiome solutions for therapeutic use.
BestTreat has, first and foremost, a significant impact on the billions of citizens in need of accurate NAFLD prognosis and treatment, as well as on the heavy economic toll imposed by NAFLD on EU healthcare systems.
BestTreat focus, issue and outcome