Mapping Cancer Metabolism by Mid-infrared Photothermal Microscopy

节目概要 虽然改变的细胞代谢正在成为癌症的标志，但对用于治疗癌症的新工具的需求尚未得到满足。 代谢物的定量。NMR光谱法、质谱法、FTIR和拉曼光谱法被广泛地应用。 用于组织提取物或完整组织中的分子检测。然而，这些工具并不表明空间 分析物在细胞内的位置。我们通过开发无锁定、宽范围的 场中红外光热（MIP）显微镜。我们的技术将使定量振动成像 活肿瘤细胞和完整活检组织中的代谢物。在PI实验室最近开发的MIP显微镜中（Sci Adv 2016），可见光束探测诱导的热效应（例如折射率和热膨胀的变化 被脉冲红外线束照射然后通过锁定放大器提取MIP信号。为了与IR/可见光 照明领域，PI实验室进一步开发了一种宽视场MIP显微镜，其中互补金属- 利用氧化物半导体（CMOS）相机和同步电子器件进行全场锁定 检测（Sci Adv 2019）。尽管这些初步的成功，MIP显微镜的灵敏度是有限的， 检测方案。首先，黄金标准锁定检测错过了MIP中的所有谐波频率 信号了其次，典型CMOS相机的阱深度严重限制了采样时的探测功率为0.01 mW。 因此，需要许多平均值来达到合理的信噪比。我们克服了这些困难 通过两项创新。第一种方法是对快速光电二极管接收到的探测光子进行滤波。然后在 在频域中，使用匹配滤波器来提取基频和谐波频率处的所有MIP信号。 第二种方法是执行图案化探测照明，并使用光电二极管收集光子， 饱和阈值为数十mW。然后，通过矩阵求逆来恢复MIP图像。在这个“单像素 在“相机”的方法中，探头功率可以增加1000倍，这表明速度可以 提高了30倍，在散粒噪声极限下达到与宽视场MIP相同的信噪比。的目标 这个R33的建议是开发一个数字信号处理，单像素相机MIP显微镜，并验证其 潜在的高含量癌症代谢成像。特别是，我们的目标是验证代谢开关， 葡萄糖介导的脂肪生成对卵巢癌中的脂肪酸摄取/氧化产生耐药性。 通过完成拟议的研究，我们将产生高速高光谱中红外光热 化学成像平台，能够以亚微米空间分辨率绘制活细胞代谢图。代谢 通过该平台对活的耐药癌细胞进行成像为揭示隐藏的特征提供了新的机会 这可能会导致抑制癌症耐药性发展的适应性疗法。

Program Summary While altered cell metabolism is emerging as a hallmark of cancer, there is an unmet need for new tools for quantitation of metabolites. NMR spectroscopy, mass spectrometry, FTIR, and Raman spectroscopy are widely used for molecular detection in tissue extracts or intact tissues. Yet, these tools do not indicate the spatial locations of the analytes inside the cell. We address this unmet need via development of a lock-in free, wide- field mid-infrared photothermal (MIP) microscope. Our technology will enable quantitative vibrational imaging of metabolites in live tumor cells and intact biopsies. In MIP microscopy recently developed in the PI lab (Sci Adv 2016), a visible beam probes the thermal effect (e.g. change of refractive index and thermal expansion) induced by a pulsed infrared beam. The MIP signal is then extracted through a lock-in amplifier. To match the IR/visible illumination area, the PI lab further developed a wide-field MIP microscope in which a complementary metal– oxide–semiconductor (CMOS) camera and synchronization electronics are harnessed for whole-field lock-in detection (Sci Adv 2019). Despite these initial successes, the sensitivity of MIP microscopy is limited by the detection schemes. First, the golden standard lock-in detection misses all the harmonic frequencies in the MIP signal. Second, the well-depth of a typical CMOS camera seriously limits the probe power to 0.01 mW at sample. Thus, many averages are needed to reach a reasonable signal to noise ratio. We overcome these difficulties through two innovations. The first one is to digitize the probe photons received by a fast photodiode. Then, in the frequency domain, a match filter is used to extract all MIP signals at fundamental and harmonic frequencies. The second one is to perform patterned probe illumination and collect photons with a photodiode which has a saturation threshold of tens of mW. Then, a MIP image is recovered by matrix inversion. In this “single-pixel camera” approach, the probe power can be increased by 1000 times, which indicates that the speed can be improved 30 times to reach the same signal to noise ratio of wide field MIP at the shot noise limit. The goal of this R33 proposal is to develop a digital signal processing, single pixel camera MIP microscope and validate its potential for high-content cancer metabolic imaging. In particular, we aim to validate a metabolic switch from glucose-mediated lipogenesis to fatty acids uptake/oxidation in ovarian cancers that become resistant to cisplatin. By accomplishing the proposed studies, we will generate a high-speed hyperspectral mid-infrared photothermal chemical imaging platform that is able to map the live cell metabolism at sub-micron spatial resolution. Metabolic imaging of live drug-resistant cancer cells by this platform opens new opportunities of unveiling hidden signatures that can potentially lead to adaptive therapies that inhibit the development of drug resistance in cancers.