The development of an ingestible biosensor for the characterization of gut metabolites related to major depressive disorder: hypothesis and theory

Amanda Densil, Mya Elisabeth George, Hala Mahdi, Andrew Chami, Alyssa Mark, Chantal Luo, Yifan Wang, Aribah Ali, Pengpeng Tang, Audrey Yihui Dong, Sin Yu Pao, Rubani Singh Suri, Isabella Valentini, Lila Al-Arabi, Fanxiao Liu, Alesha Singh, Linda Wu, Helen Peng, Anjana Sudharshan, Zoha Naqvi, Jayda Hewitt, Catherine Andary, Vincent Leung, Paul Forsythe, Jianping Xu
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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.
开发用于描述与重度抑郁障碍有关的肠道代谢物特征的可摄取生物传感器:假设与理论
在北美,精神疾病的诊断过程由《精神疾病诊断和统计手册》(DSM)指导。多年来,DSM的修订导致了诊断门槛的全面降低,导致误诊和过度诊断率的增加。再加上耻辱感,这种模糊性和缺乏一致性加剧了临床医生和科学家在重度抑郁症(MDD)等情绪障碍的临床评估和研究中面临的挑战。虽然目前表征重度抑郁症的努力主要集中在定性方法上,但生理特征的广泛变化,例如在肠道中发现的生理特征,表明使用生物标志物提供定量和客观评估的巨大潜力。在这里,我们建议开发一种益生菌大肠杆菌(E. coli)多输入可摄取生物传感器,用于表征与MDD相关的关键肠道代谢物。使用基于CRISPR的编辑器编写DNA允许对信号进行分子记录,而核黄素检测则是建立大肠时间和空间特异性的一种手段。我们通过系统的动力学建模来测试这种方法的可行性,该系统以时间和剂量依赖的方式展示了对大肠内代谢物的靶向传感和稳健记录。此外,一个事后归一化模型成功地控制了核黄素浓度的个体差异等混杂因素,在实际代谢物浓度和预测代谢物浓度之间产生了线性关系。我们还强调吲哚、丁酸盐、四氢叶酸、过氧化氢和四硫酸盐是关键的肠道代谢物,它们有可能指导我们提出的MDD生物传感器。最终,我们提出的生物传感器有潜力允许对许多情绪障碍的疾病病理生理学,评估和治疗反应有更深入的了解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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