Mapping Cancer Metabolism by Mid-infrared Photothermal Microscopy

计划摘要 虽然细胞代谢改变正在成为癌症的一个标志，但对治疗癌症的新工具的需求仍未得到满足 代谢物的定量。核磁共振光谱、质谱学、傅立叶变换红外光谱和拉曼光谱被广泛使用 用于组织提取物或完整组织中的分子检测。然而，这些工具并不指示空间 分析物在细胞内的位置。我们通过开发一种自由锁定的、宽范围的 野外中红外光热(MIP)显微镜。我们的技术将使定量振动成像成为可能 活体肿瘤细胞和完整活检组织中的代谢物。在PI实验室中最近发展起来的MIP显微镜(Sci Adv 2016)，可见光探测引起的热效应(例如，折射率和热膨胀的变化 通过脉冲红外线光束。然后通过锁定放大器提取MIP信号。匹配红外线/可见光 在照明区域，PI实验室进一步开发了广视场MIP显微镜，在该显微镜中，互补金属- 利用氧化物半导体(Cmos)摄像机和同步电子技术实现全场锁定。 检测(Sci Adv 2019)。尽管取得了这些初步的成功，但MIP显微镜的灵敏度受到 检测方案。首先，金标准锁定检测遗漏了MIP中的所有谐波频率 信号。其次，典型的CMOS相机的井深严重限制了样品的探测功率为0.01 mW。 因此，需要许多平均值才能达到合理的信噪比。我们克服了这些困难 通过两项创新。第一种方法是将快速光电二极管接收到的探测光子数字化。然后，在 在频域，使用匹配滤波器来提取所有基频和谐波频率的MIP信号。 第二种方法是进行图案化的探测器照明，并用具有 饱和阈值为数十mW。然后，通过矩阵求逆恢复MIP图像。在这个“单像素 采用“相机”方式，探头功率可以提高1000倍，这表明速度可以 提高了30倍，在散粒噪声极限下达到了与宽场MIP相同的信噪比。的目标是 本R33方案是为了开发一台数字信号处理、单像素相机MIP显微镜，并验证其 高含量癌症代谢成像的潜力。特别是，我们的目标是验证代谢转换从 对顺铂耐药的卵巢癌患者，葡萄糖介导的脂肪生成与脂肪酸摄取/氧化有关。 通过完成所提出的研究，我们将产生高速高光谱中红外光热 能够以亚微米空间分辨率绘制活细胞代谢图的化学成像平台。新陈代谢 该平台对活体耐药癌细胞的成像为揭示隐藏特征开辟了新的机会 这可能会导致适应性治疗，抑制癌症耐药性的发展。

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.