AUTHOR=Densil Amanda , George Mya Elisabeth , Mahdi Hala , Chami Andrew , Mark Alyssa , Luo Chantal , Wang Yifan , Ali Aribah , Tang Pengpeng , Dong Audrey Yihui , Pao Sin Yu , Suri Rubani Singh , Valentini Isabella , Al-Arabi Lila , Liu Fanxiao , Singh Alesha , Wu Linda , Peng Helen , Sudharshan Anjana , Naqvi Zoha , Hewitt Jayda , Andary Catherine , Leung Vincent , Forsythe Paul , Xu Jianping TITLE=The development of an ingestible biosensor for the characterization of gut metabolites related to major depressive disorder: hypothesis and theory JOURNAL=Frontiers in Systems Biology VOLUME=3 YEAR=2023 URL=https://www.frontiersin.org/journals/systems-biology/articles/10.3389/fsysb.2023.1274184 DOI=10.3389/fsysb.2023.1274184 ISSN=2674-0702 ABSTRACT=

The diagnostic process for psychiatric conditions is guided by the Diagnostic and Statistical Manual of Mental Disorders (DSM) in North America. Revisions of the DSM over the years have led to lowered diagnostic thresholds across the board, incurring increased rates of both misdiagnosis and over-diagnosis. Coupled with stigma, this ambiguity and lack of consistency exacerbates the challenges that clinicians and scientists face in the clinical assessment and research of mood disorders such as Major Depressive Disorder (MDD). While current efforts to characterize MDD have largely focused on qualitative approaches, the broad variations in physiological traits, such as those found in the gut, suggest the immense potential of using biomarkers to provide a quantitative and objective assessment. Here, we propose the development of a probiotic Escherichia coli (E. coli) multi-input ingestible biosensor for the characterization of key gut metabolites implicated in MDD. DNA writing with CRISPR based editors allows for the molecular recording of signals while riboflavin detection acts as a means to establish temporal and spatial specificity for the large intestine. We test the feasibility of this approach through kinetic modeling of the system which demonstrates targeted sensing and robust recording of metabolites within the large intestine in a time- and dose- dependent manner. Additionally, a post-hoc normalization model successfully controlled for confounding factors such as individual variation in riboflavin concentrations, producing a linear relationship between actual and predicted metabolite concentrations. We also highlight indole, butyrate, tetrahydrofolate, hydrogen peroxide, and tetrathionate as key gut metabolites that have the potential to direct our proposed biosensor specifically for MDD. Ultimately, our proposed biosensor has the potential to allow for a greater understanding of disease pathophysiology, assessment, and treatment response for many mood disorders.