About

Lingyan Shi is a tenured Associate Professor in the Shu Chien-Gene Lay Department of Bioengineering at the University of California, San Diego (UCSD). She joined UCSD in October 2019 after completing her postdoctoral training in the Department of Chemistry at Columbia University under the mentorship of the Min Lab. Dr. Shi's research focuses on developing and applying super-resolution multimodal nanoscopy techniques to study metabolic changes associated with aging and diseases. Her pioneering work includes the discovery of the "Golden Window," a wavelength range from 1550nm to 1870nm, which enables deep tissue imaging. She also developed the "DO-SRS" metabolic imaging platform that visualizes metabolic dynamics in cells and tissues using heavy water probing. Furthermore, her group has advanced stimulated Raman scattering (SRS) microscopy into a super-resolution multiplex nanoscopy by creating methods such as A-PoD, PRM, and SuMMIT-SRS. These innovations have revealed various lipid metabolic changes in organ tissues under both physiological and pathological conditions. Dr. Shi holds 10 awarded patents and has 17 pending patents. She has been recognized as a National Academy of Inventors member, Sloan Research Fellow, Scialog Fellow, and Hellman Fellow.

Research topics

• Biology
• Computer Science
• Physics
• Optics
• Materials science
• Cell biology
• Chemistry
• Computational biology
• Biophysics
• Anatomy
• Nanotechnology

Selected publications

• Regional and Systemic Metabolic Remodeling Promotes Longevity by Bioengineered Yeast-Derived Lipids

  bioRxiv (Cold Spring Harbor Laboratory) · 2026-04-13

  articleOpen accessSenior author

  Aging is marked by a progressive breakdown of intestinal integrity and metabolic homeostasis, which together drives systemic decline in physiology and reduces lifespan. Here, we found that dietary lipids extracted from a genetically engineered long-lived yeast strain robustly extend lifespan in Drosophila and further uncovered the mechanisms using deuterium oxide-probed stimulated Raman scattering microscopy to image metabolic dynamics and single nucleus RNA sequencing (scRNA-seq) to unveil the underlying pathways. These yeast lipids are enriched in shorter, more saturated fatty acids and phospholipids as revealed by Raman spectroscopy and lipidomics, contributing to increased membrane order and reduced lipid storage. Functionally, targeted dietary supplementation with these lipid components synergistically prolongs fly lifespan. We show that these lipids reverse age-related declines in gut lipid droplet abundance, enhance membrane lipid incorporation, and increase de novo lipid synthesis, thereby improving epithelial structural integrity and barrier function. snRNA-seq identifies transcriptional remodeling in metabolically active enterocytes, including upregulation of autophagy and protein turnover genes, alongside reduction of unsaturated fatty acid biosynthesis. In the brain, dietary lipids orchestrate a dual metabolic strategy-promoting energy conservation and enhanced signaling across most neuronal and glial populations, while selectively boosting mitochondrial function in memory-critical Kenyon cells. All these leads to the enhancement of gut-to-glia communication, particularly through EGFR and FGFR pathways. Finally, analysis of our data with the Fly Metabolic Analysis Pipeline (FLY-MAP) reveals that yeast lipids restructure gut metabolic modules to coordinate energy production, redox balance, and nutrient flexibility. Our study uncovers a cross-kingdom mechanism of metabolic longevity regulation, paving the way for leveraging yeast-derived nutritional components to support tissue homeostasis and promote healthy aging.

  PublisherDOI

• Label free multimodal optical imaging of metabolic heterogeneity in aging by integrating SRS, MPF, FLIM, and SHG

  bioRxiv (Cold Spring Harbor Laboratory) · 2026-04-14

  articleOpen access

  ABSTRACT Cellular metabolism is governed by the coordinated organization of macromolecules, including lipids and proteins, together with redox-active cofactors such as NADH and FAD. However, resolving these biochemical features quantitatively and spatially at subcellular resolution remains challenging because no single imaging modality can capture molecular composition, redox state, and tissue architecture simultaneously without labeling. Here, we present MANIFEST ( M ulti-mod A l N onlinear I maging with F luorescence E xcitation and S tatistical T emporal-resolved spectroscopy), a label-free imaging platform that integrates stimulated Raman scattering (SRS), second harmonic generation (SHG), multiphoton fluorescence (MPF), and fluorescence lifetime imaging microscopy (FLIM). The MANIFEST combines chemical imaging of lipids with autofluorescence- and lifetime-based quantification of NADH and FAD metabolism, enabling spatially resolved analysis of metabolic heterogeneity at organelle and tissue-compartment levels. We apply this framework to four distinct aging or disease models: amyloid-beta-treated tri-cultured brain cells, high-fat diet mouse liver, human non-ischemic cardiomyopathy tissue, and aging mouse retina. Across these systems, MANIFEST reveals disease-associated lipid remodeling, redox imbalance, disrupted metabolic zonation, collagen reorganization, and layer-specific metabolic changes. By integrating complementary nonlinear optical modalities into a single label-free platform, MANIFEST provides a generalizable approach for high-resolution metabolic phenotyping in complex biological systems and offers new opportunities for studying disease mechanisms, aging biology, and metabolism-driven tissue pathology.

  PublisherOA PDFDOI

• Consensus guidelines for cellular label-free optical metabolic imaging: ensuring accuracy and reproducibility in metabolic profiling

  Journal of Biomedical Optics · 2025-11-11 · 6 citations

  articleOpen access

  Significance: Cellular metabolism plays a central role in health and disease, making its study critical for advancing diagnostics and therapies. Label-free optical metabolic imaging using endogenous fluorescence from reduced nicotinamide adenine dinucleotide (phosphate) [NAD(P)H] and flavin adenine dinucleotide (FAD) provides nondestructive, high-resolution insights into metabolic function and heterogeneity from the sub-cellular to the tissue level. Standardized approaches are essential to ensure reproducibility and comparability across studies. Aim: We aim to establish a consensus framework for the acquisition, calibration, and reporting of microscopic imaging metabolic function assessments based on fluorescence intensity and lifetime measurements of NAD(P)H and FAD. Approach: We present best practices for calibrating, analyzing, and reporting fluorescence intensity-based optical redox ratios and fluorescence lifetime data using multiexponential fitting and phasor analysis. Guidelines for validation experiments and cross-system standardization are provided to improve accuracy and reproducibility. Results: We demonstrate the importance of calibration procedures and normalization strategies for intensity-based optical redox measurements. We highlight needed calibration, signal-to-noise ratio considerations, and the impact of distinct analytical approaches on fluorescence lifetime-based metabolic function metrics. Conclusion: We recommend a consistent, practical framework for reproducible, label-free, optical metabolic imaging, facilitating robust comparisons across studies and supporting the broader adoption of optical metabolic imaging technologies for biomedical research and clinical translation.

  PublisherDOI

• Single-Frame Vignetting Correction for Post-Stitched-Tile Imaging Using VISTAmap

  Nanomaterials · 2025-04-07 · 5 citations

  articleOpen accessSenior author

  Stimulated Raman Scattering (SRS) nanoscopy imaging offers unprecedented insights into tissue molecular architecture but often requires stitching multiple high-resolution tiles to capture large fields of view. This process is time-consuming and frequently introduces vignetting artifacts-grid-like intensity fluctuations that degrade image quality and hinder downstream quantitative analyses and processing such as super-resolution deconvolution. We present VIgnetted Stitched-Tile Adjustment using Morphological Adaptive Processing (VISTAmap), a simple tool that corrects these shading artifacts directly on the final stitched image. VISTAmap automatically detects the tile grid configuration by analyzing intensity frequency variations and then applies sequential morphological operations to homogenize the image. In contrast to conventional approaches that require increased tile overlap or pre-acquisition background sampling, VISTAmap offers a pragmatic, post-processing solution without the need for separate individual tile images. This work addresses pressing concerns by delivering a robust, efficient strategy for enhancing mosaic image uniformity in modern nanoscopy, where the smallest details make tremendous impacts.

  PublisherOA PDFDOI

• A mini review of quantitative optical technologies for imaging cell and tissue metabolism

  Current Opinion in Biomedical Engineering · 2025-02-10 · 3 citations

  reviewOpen accessSenior authorCorresponding

  Label-free imaging techniques, with their nondestructive, dye-free operation, and broad detection capabilities, have rapidly advanced and found application in biological tissue analysis. The integration of multimodal label-free imaging technologies has gained significant attention as it enables the acquisition of diverse molecular information from multiple sources while overcoming the limitations associated with conventional single-modality approaches. In this review, we examine several key label-free optical imaging technologies and their recent applications. We also discuss innovative multimodal imaging platforms, along with current advancements, limitations, and prospects in the field of label-free imaging.

  PublisherDOI

• Light and metabolism: label-free optical imaging of metabolic activities in biological systems [Invited]

  Biomedical Optics Express · 2025-08-14 · 6 citations

  reviewOpen access

  Metabolic imaging is critical for understanding cellular functions beyond morphology, offering significant insights into various biological processes and disease states. Label-free optical imaging techniques stand out by providing high-resolution, molecularly specific, and/or non-invasive assessments of metabolic activity without relying on exogenous contrast agents. This review discusses the key photon-tissue interactions-absorption, emission, and scattering-that underpin label-free optical imaging modalities for interrogating tissue's metabolic activities at various scales. Specifically, photoacoustic imaging (PAI) leverages absorption-based contrasts such as hemoglobin oxygenation and glucose concentrations to quantify metabolic dynamics. Emission-based techniques, including two-photon fluorescence (TPF) and fluorescence lifetime imaging microscopy (FLIM), exploit intrinsic fluorophores like nicotinamide adenine dinucleotide (NADH) and flavin adenine dinucleotide (FAD) to assess cellular energy metabolism. Interferometric methods, particularly optical coherence tomography (OCT), provide insights into tissue morphological changes. Second harmonic generation (SHG) detects extracellular matrix components such as the collagen network. Molecular vibrational imaging methods, such as stimulated Raman scattering (SRS) microscopy, visualizes spatial heterogeneity of molecular compositions. Recent clinical translations of these methods highlight their growing roles in oncology, neurology, and dermatology, underscoring their potential in early disease diagnosis and monitoring therapeutic responses. Despite challenges such as depth limitations, advancements like wavefront engineering and optical clearing techniques promise to enhance imaging penetration and clinical applicability, paving the way for broader adoption of label-free optical metabolic imaging in both research and clinical settings.

  PublisherDOI

• Far-red chemigenetic kinase biosensors enable multiplexed and super-resolved imaging of signaling networks

  Nature Biotechnology · 2025-04-21 · 18 citations

  article
  PublisherDOI

• Cross level effects of digitalization and environment management on energy savings in Chinese manufacturing firms

  Energy & Environment · 2025-12-02

  articleOpen accessSenior author

  The pathway to energy savings requires coordination of technological progress and policy implementation. Specific factors are needed to bridge cross-disciplinary conversations within just one system. Regional public digital infrastructure and enterprises’ environmental management capabilities are incorporated into a research framework on digitalization and energy savings based on the theory of digital ecosystems. A cross-level moderating model is constructed using data from 2014 to 2022 for 650 Chinese enterprises listed in the manufacturing industry to examine the impact of various digital technologies on energy savings, moderating effect of digital infrastructure and the constraint effect of environmental management systems (EMSs). Artificial intelligence and big data are found making more notable contributions to enterprise energy savings than cloud computing and block chain. For every doubling of a region's digital infrastructure level, the energy-saving effect of local enterprises’ digitalization increases by three times. Digitalization facilitates energy savings for enterprises while digital infrastructure helps overcome limitations associated with insufficient digitalization capabilities. Digitalization significantly affects energy consumption only in enterprises with EMSs, confirming digitalization as an effective energy-saving tool when the enterprise acquires environmental management capabilities.

  PublisherDOI

• Multimodal imaging of subcellular metabolic dynamics reveals the anti-aging effect of metformin

  2025-03-19

  articleSenior author
  PublisherDOI

• A multimodal imaging approach for imaging the metabolic changes resulting from bronchopulmonary dysplasia

  bioRxiv (Cold Spring Harbor Laboratory) · 2025-06-22 · 1 citations

  preprintOpen accessCorresponding

  Lung tissue is composed of various functional units, each essential for maintaining the intricate functions of the lung. Disruptions in the molecular and cellular mechanisms in the lung can cause tissue fibrosis, inflammation, and severe breathing difficulties, which are common in conditions such as bronchopulmonary dysplasia (BPD). BPD's molecular changes are not well understood, which hinders effective diagnosis and treatment. Here, we present a new multimodal imaging workflow for detailed molecular and metabolic characterization of tissues at multiple spatial scales. We applied a combined imaging approach using matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) and ultrafast focused light-based imaging & photonics platform (U-FLIP) that included two-photon fluorescence (TPF), second harmonic generation (SHG), and stimulated Raman scattering (SRS). We also developed a hierarchical multimodal registration network (HiMReg) for the precise co-registration of each modality. This approach revealed previously unknown metabolic changes in distinct functional tissue units affected by BPD, including altered lipid distributions, reduced optical redox states, and specific collagen remodeling in bronchioles. Our findings evidenced alterations in lipid composition and metabolism of BPD-affected alveoli compared to healthy tissue, providing novel insights into disease pathophysiology. Our findings elucidate the intricate spatial and molecular complexity of BPD, building on prior research that did not provide the spatial resolution necessary to capture the nuances of metabolic alterations. This multimodal approach offers exceptional insights into disease exploration and could transform the way we study spatially heterogeneous conditions. By providing detailed maps of the metabolic shifts occurring in distinct tissue microanatomical features, the methods developed here could enable the discovery of new therapeutic avenues, making it highly attractive for the field of biomedical research.

  PublisherOA PDFDOI

Recent grants

• Sugar Probed SRS Volumetric imaging of Metabolic Activities

  NIH · $1.2M · 2023–2028

• Novel Optical Imaging Approach to Study Neurovascular Coupling System

  NIH · $435k · 2022–2024

Frequent coauthors

• R. R. Alfano

  City University of New York

  137 shared

• Adrián Rodríguez‐Contreras

  57 shared

• Anthony A. Fung

  47 shared

• Laura A. Sordillo

  City College of New York

  38 shared

• Hongje Jang

  University of California, San Diego

  31 shared

• Sandra Mamani

  City College of New York

  30 shared

• Peter P. Sordillo

  Lenox Hill Hospital

  25 shared

• Bingmei M. Fu

  Shaoxing University

  24 shared

Labs

• Shi LabPI

Education

• PhD, Biomedical Engineering

  City College of New York

  2014

Awards & honors

• Blavatnik Regional Award for Young Scientist (2018)
• Hellman Fellowship Award (2021)
• 2021 Rising Star Award by LaserFocusWorld
• Rising Star Award by Nature Light Science & Applications (20…
• Advancing Bioimaging Scialog Fellow by RCSA and the Chan Zuc…