Biology subjects

Zangle, T. A.

Publications and source records attributed to Zangle, T. A..

13 recordsLinked to original sources

bioRxiv2026

Temporal dynamics improves machine learning-based prediction of cell state from quantitative phase imaging

Cell morphology reflects cell health and can distinguish cell-cycle stage, growth arrest, and distinct pathways of cell death. Live, label-free quantitative phase imaging (QPI) captures these features non-invasively and with high temporal resolution, yet many image-based classifiers rely on single frames and cannot separate states whose differences emerge only over time. How much temporal information is needed, and which architecture best exploits it, remain open questions. We assembled 1,874 QPI timelapse sequences spanning six cell states (interphase, mitosis, cell cycle arrest, apoptosis, ferroptosis, and necroptosis) and compared two-dimensional convolutional neural networks (CNNs) with a three-dimensional (3D) spatiotemporal CNN across increasing frame counts. Accuracy improved as frames were added, with the largest gain between one and three frames. The 2D models saturated beyond three frames, whereas the 3D architecture kept improving, reaching 96.5% accuracy and a 3.5% error rate at eleven frames. The temporal information needed tracked the timescale of each process: mitosis was resolved from a single frame, while ferroptosis benefited most from extended sequences. Overall, these results show that dynamic information, rather than static morphology alone, drives accurate cell-state classification, and that 3D architectures are needed to fully exploit it for label-free dynamic phenotyping.

bioengineering↗

bioRxiv2026

Autocatalytic growth offset by constant degradation explains mass accumulation during B cell activation

How cells regulate growth is a fundamental question in cell biology. Here we use quantitative phase imaging (QPI) to measure the dry mass of individual naive primary mouse B cells during ex vivo stimulation. B cells undergo an approximately 4-fold increase in mass prior to first division, far exceeding the doubling in size typical of immortalized cell lines and enabling discrimination of growth models that are otherwise indistinguishable. We find that a pure exponential model of mass accumulation exhibits systematic error that is resolved by an offset exponential model, indicating that only an active fraction of cell mass participates in biosynthesis. Monte Carlo simulations establish when these two models can be discriminated as a function of final to initial mass ratio, the magnitude of the degradative pressure, and measurement precision. Analysis of growth rate versus mass independently confirms the offset exponential model and implies that it can be interpreted as indicating a constant degradative pressure that opposes exponential biosynthesis. This model is structurally equivalent to super-exponential growth models derived from autocatalytic ribosome dynamics in bacteria, with the exponential rate reflecting autocatalytic accumulation of biosynthetic machinery and the active mass fraction serving as a proxy for initial ribosomal capacity. Here, the low active fraction in quiescent B cells ([~]20%) is consistent with a limited ribosomal content of resting lymphocytes. Comparison of follicular and marginal zone B cells stimulated with CpG reveals a conserved degradative pressure across subtypes and stimulation conditions. These results demonstrate that deviations from pure exponential growth, previously identified in bacteria, extend to mammalian cells, suggesting that autocatalytic ribosome accumulation offset by constitutive protein turnover is a conserved feature of single-cell growth dynamics across domains of life.

biophysics↗

bioRxiv2025

QUILPEN provides independent and label-free single-cell quantification of pigmentation dynamics and organelle content

The relationship between melanogenesis, pigmentation, and melanocyte behavior is complex. In melanocytes, pigmentation is often associated with differentiation, yet mature melanocytes vary in pigment content. In melanoma, pigmentation-linked transcriptional programs may have prognostic value, but visual assessments of tumor pigmentation have yielded inconsistent results. Progress linking pigmentation phenotypes to cell state has been limited by a lack of tools that can directly and dynamically quantify melanin content in live cells. Here we present QUantitative Imaging of Label-free Pigment-associated ENtities (QUILPEN), a label-free multi-modal imaging technique that combines quantitative phase imaging (QPI), quadrant darkfield (QDF), and absorption imaging, to independently capture light that has been transmitted, scattered, and absorbed. This non-destructive method enables live-cell imaging over multiple days without labels. We show absorption as a reliable readout of melanin content, which can be decoupled from melanosome content detected by QDF, which measures scattered light. Applying QUILPEN to melanoma cells before and during repigmentation, we find that melanin content is highly heterogeneous, and that this heterogeneity is reinstated upon repigmentation. Lineage tracking further reveals that melanin synthesis rates are heritable and can be transmitted both symmetrically and asymmetrically. QUILPEN enables real-time quantification of pigmentation dynamics and cell-level heterogeneity. SignificancePigmentation is a defining feature of melanocytic cells and linked to behavior, yet melanins optical properties complicate direct measurement with existing approaches. Taking advantage of the absorbing nature of pigment and scattering properties of organelles, we can independently track pigment and organelle content over time and along cell lineages in a label-free manner to reveal population heterogeneity and patterns of inheritance. Research HighlightsQUILPEN is a label-free, live cell imaging pipeline that independently quantifies pigment and organelles in melanocytic cells. Tracking pigment and organelle content along cell lineages reveals varied inheritance of pigment-associated features. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=103 SRC="FIGDIR/small/683473v1_ufig1.gif" ALT="Figure 1"> View larger version (41K): org.highwire.dtl.DTLVardef@8d1ef9org.highwire.dtl.DTLVardef@ec6ebdorg.highwire.dtl.DTLVardef@5a7b64org.highwire.dtl.DTLVardef@5b0d80_HPS_FORMAT_FIGEXP M_FIG C_FIG

cell biology↗

bioRxiv2025

Determination of Drug Sensitivity in Patient Derived Models of Breast Cancer by Multiparametric QPI

Functional precision oncology seeks to match patients with effective therapies by empirically testing patient-derived samples for drug sensitivity in the laboratory. However, existing approaches require significant sample expansion time and expense prior to analysis, rendering them impractical for routine clinical testing. Quantitative phase imaging (QPI) provides a potential path forward by directly measuring responses at single cell resolution without the need for extensive sample expansion. In previous work, we demonstrated that multiple, independent parameters of cellular response to therapeutic agents can be derived from QPI data, an approach we call multiparametric QPI (mQPI). Here, we demonstrate application of mQPI using cells from patient derived xenograft organoid (PDxO) models, as well as cells viably frozen direct from patients. Using mQPI with breast cancer PDxO models, we uncover distinct drug responses for cells originating from different anatomic sites in the same patient and resolve cellular heterogeneity of response in a model of acquired therapeutic resistance. We also show that mQPI can detect drug responses in viably frozen primary patient samples, either direct from thaw or after a short term expansion of only 2 weeks. Overall, these data provide proof-of-principle for application of mQPI to a range of sample types, including cryopreserved material direct from patients. This underscores the clinical potential of mQPI as a time- and materials-efficient alternative to current methods in functional precision oncology.

bioengineering↗

bioRxiv2025

Marginal zone and follicular B cells respond differently to TLR4 and TLR9 stimulation

Marginal zone (MZ) B cells are considered to be innate-like immune cells, and follicular (FO) B cells are considered to be adaptive immune B cells. Yet, the proliferative response of MZ and FO B cells to different innate stimuli remains unclear. Here, we investigated cell growth, division, and death to determine the collective proliferative response of MZ and FO B cells in response to innate stimuli, LPS and CpG. We show that the growth rate of FO B cells is higher than that of MZ B cells in response to CpG, though MZ B cells acquire a higher mass at division, whereas both the growth rate and mass at division for MZ and FO B cells remain similar in response to LPS stimulation. We show that MZ B cells divide faster and induce a higher cRel expression in response to both CpG and LPS stimulation than FO B cells. A higher proportion of MZ B cells enter first division in response to LPS stimulation, not in response to CpG stimulation, than FO B cells. Interestingly, CpG stimulation, not LPS stimulation, leads to higher cell death in MZ B cells than FO B cells. In response to LPS stimulation, MZ B cells show a higher cell number at early time and a reduced/ similar cell number at late time, whereas in response to CpG stimulation, MZ B cells show a lower cell number at both early and late time. Our study suggests that LPS and CpG stimulation impact cell growth, division, and death differently, which in turn regulate different proliferative responses of MZ and FO B cells. Thus, our study offers a new perspective that different innate stimuli regulate different features of proliferative responses.

immunology↗

bioRxiv2024

Quadrant darkfield (QDF) for label-free imaging of intracellular puncta

SignificanceMeasuring changes in cellular structure and organelles is crucial for understanding disease progression and cellular responses to treatments. A label-free imaging method can aid in advancing biomedical research and therapeutic strategies. AimThis study introduces a computational darkfield imaging approach named quadrant darkfield (QDF) to separate smaller cellular features from large structures, enabling label-free imaging of cell organelles and structures in living cells. ApproachUsing a programmable LED array as illumination source, we vary the direction of illumination to encode additional information about the feature size within cells. This is possible due to the varying level of directional scattering produced by features based on their sizes relative to the wavelength of light used. ResultsQDF successfully resolved small cellular features without interference from larger structures. QDF signal is more consistent during cell shape changes than traditional darkfield. QDF signals correlate with flow cytometry side scatter measurements, effectively differentiating cells by organelle content. ConclusionsQDF imaging enhances the study of subcellular structures in living cells, offering improved quantification of organelle content compared to darkfield without labels. This method can be simultaneously performed with other techniques such as quantitative phase imaging to generate a multidimensional picture of living cells in real-time.

bioengineering↗

bioRxiv2024

Receptor tyrosine kinase inhibition leads to regression of acral melanoma by targeting the tumor microenvironment

Acral melanoma (AM) is an aggressive melanoma variant that arises from palmar, plantar, and nail unit melanocytes. Compared to non-acral cutaneous melanoma (CM), AM is biologically distinct, has an equal incidence across genetic ancestries, typically presents in advanced stage disease, is less responsive to therapy, and has an overall worse prognosis. Independent analysis of published genomic and transcriptomic sequencing identified that receptor tyrosine kinase (RTK) ligands and adapter proteins are frequently amplified, translocated, and/or overexpressed in AM. To target these unique genetic changes, a zebrafish acral melanoma model was exposed to a panel of narrow and broad spectrum multi-RTK inhibitors, revealing that dual FGFR/VEGFR inhibitors decrease acral-analogous melanocyte proliferation and migration. The potent pan-FGFR/VEGFR inhibitor, Lenvatinib, uniformly induces tumor regression in AM patient-derived xenograft (PDX) tumors but only slows tumor growth in CM models. Unlike other multi-RTK inhibitors, Lenvatinib is not directly cytotoxic to dissociated AM PDX tumor cells and instead disrupts tumor architecture and vascular networks. Considering the great difficulty in establishing AM cell culture lines, these findings suggest that AM may be more sensitive to microenvironment perturbations than CM. In conclusion, dual FGFR/VEGFR inhibition may be a viable therapeutic strategy that targets the unique biology of AM.

cancer biology↗

bioRxiv2024

Tracking of Lineage Mass via Quantitative Phase Imaging and Confinement in Low Refractive Index Microwells

Measurements of cell lineages is central to a variety of fundamental biological questions, ranging from developmental to cancer biology. However, accurate lineage tracing requires nearly perfect cell tracking, which can be challenging due to cell motion during imaging. Here we demonstrate the integration of microfabrication, imaging, and image processing approaches to demonstrate a platform for cell lineage tracing. We use quantitative phase imaging (QPI) a label-free imaging approach that quantifies cell mass. This gives an additional parameter, cell mass, that can be used to improve tracking accuracy. We confine lineages within microwells fabricated to reduce cell adhesion to sidewalls made of a low refractive index polymer. This also allows the microwells themselves to serve as references for QPI, enabling measurement of cell mass even in confluent microwells. We demonstrate application of this approach to immortalized adherent and nonadherent cell lines as well as stimulated primary B cells cultured ex vivo. Overall, our approach enables lineage tracking, or measurement of lineage mass, in a platform that can be customized to varied cell types.

bioengineering↗

bioRxiv2023

LVING Reveals the Intracellular Structure of Cell Growth

The continuous balance of growth and degradation inside cells maintains homeostasis. Disturbance of the balance by internal or external factors cause state of disease. Effective disease treatments seek to restore this balance. Here, we present a method based on quantitative phase imaging (QPI) based measurements of cell mass and the velocity of mass transport to quantify the balance of growth and degradation within intracellular control volumes. The result, which we call Lagrangian velocimetry for intracellular net growth (LVING), provides high resolution maps of intracellular biomass production and degradation. We use LVING to quantify the growth in different regions of the cell during phases of the cell cycle. LVING can also be used to quantitatively compare the effect of range of chemotherapy drug doses on subcellular growth processes. Finally, we applied LVING to characterize the effect of autophagy on the growth machinery inside cells. Overall, LVING reveals both the structure and distribution of basal growth within cells, as well as the disruptions to this structure that occur during alterations in cell state.

bioengineering↗

bioRxiv2023

Voltage-dependent volume regulation controls epithelial cell extrusion and morphology

Epithelial cells work collectively to provide a protective barrier, yet also turn over rapidly by cell death and division. If the number of dying cells does not match those dividing, the barrier would vanish, or tumors can form. Mechanical forces and the stretch-activated ion channel (SAC) Piezo1 link both processes; stretch promotes cell division and crowding triggers cell death by initiating live cell extrusion1,2. However, it was not clear how particular cells within a crowded region are selected for extrusion. Here, we show that individual cells transiently shrink via water loss before they extrude. Artificially inducing cell shrinkage by increasing extracellular osmolarity is sufficient to induce cell extrusion. Pre-extrusion cell shrinkage requires the voltage-gated potassium channels Kv1.1 and Kv1.2 and the chloride channel SWELL1, upstream of Piezo1. Activation of these voltage-gated channels requires the mechano-sensitive Epithelial Sodium Channel, ENaC, acting as the earliest crowd-sensing step. Imaging with a voltage dye indicated that epithelial cells lose membrane potential as they become crowded and smaller, yet those selected for extrusion are markedly more depolarized than their neighbours. Loss of any of these channels in crowded conditions causes epithelial buckling, highlighting an important role for voltage and water regulation in controlling epithelial shape as well as extrusion. Thus, ENaC causes cells with similar membrane potentials to slowly shrink with compression but those with reduced membrane potentials to be eliminated by extrusion, suggesting a chief driver of cell death stems from insufficient energy to maintain cell membrane potential.

cell biology↗

bioRxiv2021

Multiparametric quantitative phase imaging for real-time, single cell, drug screening in breast cancer

Quantitative phase imaging (QPI) measures the growth rate of individual cells by quantifying changes in mass versus time. Here, we use the breast cancer cell lines MCF-7, BT-474, and MDA-MB-231 to validate QPI as a multiparametric approach for determining response to single-agent therapies. Our method allows for rapid determination of drug sensitivity, cytotoxicity, heterogeneity, and time of response for up to 100,000 individual cells or small clusters in a single experiment. We find that QPI EC50 values are concordant with CellTiter-Glo (CTG), a gold standard metabolic endpoint assay. In addition, we apply multiparametric QPI to characterize cytostatic/cytotoxic and rapid/slow responses and track the emergence of resistant subpopulations. Thus, QPI reveals dynamic changes in response heterogeneity in addition to average population responses, a key advantage over endpoint viability or metabolic assays. Overall, multiparametric QPI reveals a rich picture of cell growth by capturing the dynamics of single-cell responses to candidate therapies.

bioengineering↗

bioRxiv2021

Laterally transferred macrophage mitochondria acts as a signaling source promoting cancer cell proliferation

Lateral transfer of mitochondria occurs in many physiological and pathological conditions. Given that mitochondria provide essential energy for cellular activities, mitochondrial transfer is currently thought to promote the rescue of damaged cells. We report that mitochondrial transfer occurs between macrophages and breast cancer cells, leading to increased cancer cell proliferation. Unexpectedly, transferred macrophage mitochondria are dysfunctional, lacking mitochondrial membrane potential. Rather than performing essential mitochondrial activities, transferred mitochondria accumulate reactive oxygen species which activates ERK signaling, indicating that transferred mitochondria act as a signaling source that promotes cancer cell proliferation. We also demonstrate that pro-tumorigenic M2-like macrophages exhibit increased mitochondrial transfer to cancer cells. Collectively, our findings reveal how mitochondrial transfer is regulated and leads to sustained functional changes in recipient cells. One-Sentence SummaryLateral transfer of macrophage mitochondria acts as a ROS signaling source, regulating cancer cell proliferation through ERK signaling.

cancer biology↗

bioRxiv2021

Quantitative Phase Velocimetry for Label-Free Measurement of Intracellular Mass Transport Velocity

Transport of mass within cells helps maintain homeostasis and is disrupted by disease and stress. Here, we develop quantitative phase velocimetry (QPV) as a label-free approach to make the invisible flow of mass within cells visible and quantifiable. We benchmark our approach against alternative image registration methods, a theoretical error model, and synthetic data. Our method tracks not just individual labeled particles or molecules, but the entire flow of bulk material through the cell. This enables us to measure diffusivity within distinct cell compartments using a single approach, which we use here for direct comparison of nuclear and cytoplasmic diffusivity. As a label-free method, QPV can be used for long-term tracking to capture dynamics through the cell cycle.

bioengineering↗