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
Faculty of Health Sciences, McMaster University, Hamilton, ON, Canada.
Faculty of Engineering, McMaster University, Hamilton, ON, Canada.
Front Syst Biol. 2023 Dec 5;3:1274184. doi: 10.3389/fsysb.2023.1274184. eCollection 2023.
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 () 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.
在北美,精神疾病的诊断过程以《精神疾病诊断与统计手册》(DSM)为指导。多年来DSM的修订导致诊断阈值全面降低,误诊和过度诊断率均有所上升。再加上污名化,这种模糊性和缺乏一致性加剧了临床医生和科学家在诸如重度抑郁症(MDD)等情绪障碍的临床评估和研究中所面临的挑战。虽然目前对MDD的特征描述主要集中在定性方法上,但生理特征的广泛差异,如在肠道中发现的差异,表明使用生物标志物进行定量和客观评估具有巨大潜力。在此,我们提议开发一种用于表征与MDD相关的关键肠道代谢物的益生菌()多输入可摄入生物传感器。基于CRISPR的编辑器进行DNA写入可实现信号的分子记录,而核黄素检测则作为一种手段来建立大肠的时间和空间特异性。我们通过对该系统的动力学建模来测试这种方法的可行性,该模型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,事后归一化模型成功控制了诸如核黄素浓度个体差异等混杂因素,在实际和预测的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、过氧化氢和连四硫酸盐是关键的肠道代谢物,它们有可能将我们提议的生物传感器专门用于MDD。最终,我们提议的生物传感器有可能使人们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。