Periodic Reporting for period 2 - ExpoBiome (Deciphering the impact of exposures from the gut microbiome-derived molecular complex in human health and disease)
Reporting period: 2022-05-01 to 2023-10-31
The diverse ecology of the human gut microbiome is vital to human physiology. Numerous inflammation-linked chronic disorders, such as autoimmune and neurological diseases, are linked to changes in the microbiome. Chronic disorders, by definition, develop over extended periods of time and require continued medical attention. This directly or indirectly reduces the quality of life of the affected individuals and of their families and friends, resulting in a broad socioeconomic burden. Imbalances in the microorganisms constituting the microbiome are not the only disease-related changes, however. Effector molecules produced by the microbiome, such as nucleic acids, (poly)peptides, and metabolites, are produced by the microbiome and the cocktail of these is postulated to be altered in the context of disease as a reflection of the changes in the microbiome. However, these molecules have thus far not been thoroughly studied and, thus, related cause-effect relationships have not been established. This information gap restricts the mechanistic understanding of the microbiome's functional impact on key chronic disorders including Parkinson's disease (PD) and rheumatoid arthritis (RA). The ExpoBiome project aims to, for the first time, comprehensively identify the components of this effector molecule complex and their effects on the human immune system. The project develops and applies cutting-edge molecular approaches on microbiome samples taken from healthy people and those who have just been diagnosed with PD or RA. The resulting data is integrated using existing and newly developed computational biology and machine learning approaches to place knowledge into context and generate new insights on microbial factors in health and disease. A model clinical intervention (therapeutic fasting) with the aim to reduce inflammation and thereby improving health is applied and the resulting changes of the microbiome alongside immune system changes are analysed in detail. Newly identified compounds with potential anti-inflammatory properties are studied using a gut-on-chip model (HuMiX). ExpoBiome will thus lead to key advances to better understand how microbiome shifts provide benefits in the context of inflammation-linked chronic disorders, how specific molecules can be used to improve health, and to forecast treatment outcomes, thereby substantially contributing to the development of future diagnostic and therapeutic applications with potential broad impact in medicine and society at large.
In the period covering the financial report 2, the organizational and scientific foundations for the project have been successfully established. These include in a first instance the receipt of ethical approvals to perform the respective clinical studies and sample collections at the involved clinical study sites. Detailed standard operating procedures for sample collection, optimal storage, and transport have been established and applied. All study participants have been recruited. Faecal, blood, urine, and saliva samples have been collected from healthy individuals and those who have just been diagnosed with Parkinson’s disease (PD) and rheumatoid arthritis (RA) for the cross-sectional study (Objective 1: Identify) as well as for the longitudinal study (Objective 2: Intervene). Materials are also being collected for determining anti-inflammatory mechanisms in dedicated follow-up experiments (Objective 3: Validate). Sample collections (baseline and longitudinal) have been completed, forming the foundations to develop robust classification and prediction methods (Objective 1, Objective 2). A detailed description of the clinical study protocol was published in a peer-reviewed journal, and protocols for sample processing have been developed and published. A rich set of metadata, e.g. clinical lab readouts or dietary habits, of the study participants, has been collected. The necessary wet-lab procedures for obtaining extracellular biomolecules (DNA, RNA, (poly)peptides and metabolites) from the collected microbiome samples have been established and published in a peer-reviewed journal. As an extension of this method, a newly developed approach for absolute quantification of high-resolution meta-omics data has been finalized. This approach is being applied to the respective biomolecular fractions during the extraction process to generate high-resolution meta-omics data to resolve the composition, functional potential and activity of the gut microbiome as well as the effector molecules produced. Multiple manuscripts highlighting the developments and outcomes linked to the project have been published in peer-reviewed journals. These include, among others, a knowledge base (Expobiome Map) compiling the body of knowledge on interactions of microbial taxa, microbial molecules, human immune pathways, and diseases; a framework to model microbial community dynamics resolved using meta-omics data and enabling robust predictions of up to three years into the future, and in vivo results revealing how diet and bacterial curli (a protein cross-seeding with α-Synuclein) exacerbate motor performance, as well as intestinal and brain pathologies in a mouse model of Parkinson’s disease.
We have successfully established the methodological framework of the project. We have further established the concept of the human expobiome by describing this alongside the Expobiome Map, demonstrated the long-term predictability of microbiome dynamics, and highlighted the importance of diet in the context of potentially modulating Parkinson’s disease symptoms in a mouse model. These elements represent key progress beyond the state of the art. Biomolecular extractions of the baseline samples are ongoing and expected to be concluded in Q1 2024 (Objective 1: Identify). Immunophenotyping has been partially completed (CyTOF measurements) and is expected to conclude in Q2 2024. This will allow linking the immune system status to microbial taxa, functions, or molecules as well as comparing the resulting data between healthy study participants, and individuals with Parkinson’s disease (PD) or with rheumatoid arthritis (RA). The generated meta-omics data will be combined with the collected metadata and integrated using existing and newly developed computational approaches including the Expobiome Map. Using machine learning techniques, biomarkers will be identified in the cross-sectional study (Objective 1) and selected biomarkers will be followed in a targeted approach longitudinally in individuals that have undergone the therapeutic fasting intervention (Objective 2: Intervene). We are using our in-house developed gut-on-a-chip, HuMiX, to create personalised models and have started screening bacteria in relation to their anti-inflammatory properties (Objective 3: Validate). This will represent an unprecedented dataset of microbiota dynamics as well as systemic effects in Parkinson’s disease and rheumatoid arthritis compared to healthy controls and how fasting affects these dynamics as well as the human host.