研究目的：肠道菌群已被证明可通过微生物-肠-器官轴影响人类健康，肠道菌群的紊乱与许多疾病相关，因此肠道菌群的检测至关重要。目前常用的检测手段是16S rRNA基因组检测，但该方法存在检测周期长、成本高等问题。本研究旨在开发一种快速低成本的多模态光谱检测技术，为临床快速检测肠道菌群提供一种新的方法。

研究方法：

（1）通过分析肠道菌群的光谱特性，搭建了可同时检测吸收光谱、激发光谱和发射光谱的多模态光谱检测系统，并进行了准确性与稳定性测试。

（2）利用搭建的多模态光谱检测系统对常见的12种光受体标准品进行光谱检测，分析了其光谱特征，建立了光受体标准品光谱特征库。

（3）在属水平上，检测了肠道菌群4种菌种12株不同人源细菌的光谱特征，通过种内及种间光谱特征数据分析，验证多模态光谱检测技术的生物重复性及对肠道细菌进行分类鉴别的可行性。

（4）检测了158例平原与高原人群粪便样本的肠道菌群光谱数据，并分析了两个人群的光谱特征，验证了多模态光谱检测技术对于人群分类的可行性。

研究结果：

（1）自行搭建的多模态光谱检测系统可获得200-1000nm范围内的吸收光谱、发射光谱和激发光谱，灵敏度为1nm。以喜泊芬为样品，验证了系统在吸收光谱和发射光谱上具有很高的准确性，并以PBS为样品，验证了该系统的稳定性。

（2）完成了4种12株肠道细菌的光谱检测，分析了4种肠道细菌的光谱特征峰，表明该方法具有很好的生物重复性。通过特征峰分析，筛选出了4种肠道细菌8个共有的特征峰及5个差异特征峰；与光受体标准品光谱库对比，分析了4种肠道细菌共有的光受体及差异光受体。并通过混菌实验验证了该方法鉴定肠道菌群的可行性。

（3）平原和高原两组人群具有显著的光谱特征峰差异，主要表现在特征峰光强均值和离散度上，特征峰位置和个数在两个人群上无差异。这与16S rRNA基因检测结果一致。

结论：

本研究建立了一种快速低成本的多模态光谱检测方法，并初步验证了该方法在检测区分肠道菌群上的可行性，有望成为一种新的快速低成本的肠道菌群检测方法。

Objective：The gut microbiota has been shown to affect human health through the microbiota gut organ axis, and the disruption of gut microbiota is associated with many diseases. Therefore, the detection of gut microbiota is crucial. The current commonly used detection method is 16S rRNA genome detection, but this method has problems such as long detection cycle and high cost. The aim of this study is to develop a fast and low-cost multimodal spectral detection technology, providing a new method for clinical rapid detection of gut microbiota.

Methods：

(1) By analyzing the spectral characteristics of gut microbiota, a multimodal spectral detection system was constructed that can simultaneously detect absorption, excitation, and emission spectra, and accuracy and stability tests were conducted.

(2) A multimodal spectral detection system was constructed to perform spectral detection on 12 common photoreceptor standards, analyze their spectral characteristics, and establish a spectral feature library for photoreceptor standards.

(3) At the genus level, the spectral characteristics of 12 different strains of human derived bacteria from 4 different species of gut microbiota were detected. Through the analysis of intra - and inter species spectral feature data, the biological repeatability of multimodal spectral detection technology and the feasibility of classifying and identifying gut bacteria were verified.

(4) We detected the spectral data of gut microbiota in 158 fecal samples from plain and plateau populations, and analyzed the spectral characteristics of the two populations, verifying the feasibility of multimodal spectral detection technology for population classification.

Results：

(1) The self built multimodal spectral detection system can obtain absorption spectra, emission spectra, and excitation spectra in the range of 200-1000nm, with a sensitivity of 1nm. The high accuracy of the system in absorption and emission spectra was verified using Hematoporphyrin injection as a sample, and the stability of the system was verified using PBS as a sample.

(2) We have completed the spectral detection of 12 strains of intestinal bacteria from 4 species and analyzed the spectral characteristic peaks of these bacteria, indicating that this method has good biological repeatability. Through characteristic peak analysis, 8 common characteristic peaks and 5 differential characteristic peaks of 4 gut bacteria were screened out; Compared with the standard spectral library of photoreceptors, the common and differential photoreceptors of four intestinal bacteria were analyzed. And the feasibility of identifying gut microbiota using this method was verified through mixed bacterial experiments.

(3) There is a significant difference in spectral characteristic peaks between the plain and plateau populations, mainly manifested in the mean and dispersion of characteristic peak light intensity. There is no difference in the position and number of characteristic peaks between the two populations. This is consistent with the results of 16S rRNA gene detection.

Conclusion：This study establishes a fast and low-cost multimodal spectral detection method, and preliminarily verifies the feasibility of this method in detecting and distinguishing intestinal microbiota, which is expected to become a new fast and low-cost method for detecting intestinal microbiota.