Multiplexed Dark FRET Biosensors: An Accessible Live-Cell Platform for Target- and Cell-Specific Monitoring of Protein–Protein Interactions in 2D and 3D Model Systems

Anthony R Braun; Elly E Liao; Nagamani Vunnam; Sophia Zafari; Noah Nathan Kochen; Marguerite Murray; Jonathan N Sachs

doi:10.1021/acssensors.5c01707

. Author manuscript; available in PMC: 2026 May 17.

Published in final edited form as: ACS Sens. 2026 Feb 6;11(2):909–922. doi: 10.1021/acssensors.5c01707

Multiplexed Dark FRET Biosensors: An Accessible Live-Cell Platform for Target- and Cell-Specific Monitoring of Protein–Protein Interactions in 2D and 3D Model Systems

Anthony R Braun ¹, Elly E Liao ², Nagamani Vunnam ³, Sophia Zafari ⁴, Noah Nathan Kochen ⁵, Marguerite Murray ⁶, Jonathan N Sachs ⁷

¹Department of Biomedical Engineering, College of Science and Engineering, University of Minnesota, 7-105 Nils Hasselmo Hall, 312 Church St SE, Minneapolis, Minnesota 55455, United States

²Department of Biomedical Engineering, College of Science and Engineering, University of Minnesota, 7-105 Nils Hasselmo Hall, 312 Church St SE, Minneapolis, Minnesota 55455, United States

³Department of Biomedical Engineering, College of Science and Engineering, University of Minnesota, 7-105 Nils Hasselmo Hall, 312 Church St SE, Minneapolis, Minnesota 55455, United States

⁴Department of Biomedical Engineering, College of Science and Engineering, University of Minnesota, 7-105 Nils Hasselmo Hall, 312 Church St SE, Minneapolis, Minnesota 55455, United States

⁵Department of Biomedical Engineering, College of Science and Engineering, University of Minnesota, 7-105 Nils Hasselmo Hall, 312 Church St SE, Minneapolis, Minnesota 55455, United States

⁶Department of Biomedical Engineering, College of Science and Engineering, University of Minnesota, 7-105 Nils Hasselmo Hall, 312 Church St SE, Minneapolis, Minnesota 55455, United States

⁷Department of Biomedical Engineering, College of Science and Engineering, University of Minnesota, 7-105 Nils Hasselmo Hall, 312 Church St SE, Minneapolis, Minnesota 55455, United States

Author Contributions

A.R.B. designed and conducted the FLT-FRET experiments, co-directed the study, and wrote and edited the manuscript. E.E.L. conducted spheroid biosensor experiments and edited the manuscript. N.V. conducted TNFR1/TNFR2 biosensor development, assisted with spheroid experiments, and edited the manuscript. S.Z. and N.N.K. assisted with FLT-FRET experiments. M.M. assisted in molecular biology and plasmid production. J.N.S. co-directed the study and edited the manuscript.

^✉

Corresponding Authors: Anthony R. Braun – Department of Biomedical Engineering, College of Science and Engineering, University of Minnesota, 7-105 Nils Hasselmo Hall, 312 Church St SE, Minneapolis, Minnesota 55455, United States; brau0123@umn.edu, Jonathan N. Sachs – Department of Biomedical Engineering, College of Science and Engineering, University of Minnesota, 7-105 Nils Hasselmo Hall, 312 Church St SE, Minneapolis, Minnesota 55455, United States; jnsachs@umn.edu

PMCID: PMC13179708 NIHMSID: NIHMS2168537 PMID: 41649486

Abstract

Simultaneous monitoring of multiple protein–protein interactions in live cells remains a key challenge in biology and drug discovery. While multiplexed FRET enables parallel molecular readouts, existing approaches are often constrained by spectral overlap, complex instrumentation, or incompatibility with live-cell models. To overcome these limitations and increase accessibility to the broader biological community, we present multiplexed dark FRET (MDF), a genetically encoded platform that uses spectrally distinct donors (mNeonGreen, mScarlet-I3) paired with nonemissive acceptors (ShadowY, ShadowR). We first establish that MDF fluorophores exhibit minimal background FRET under co-expression, enabling clean separation of donor lifetimes under multiplexed conditions. Using fluorescence lifetime (FLT) detection, we demonstrate MDF’s versatility through three biologically and translationally relevant examples: (1) cell-type-specific biosensing in organoids, as exemplified in 3D neuro-glial spheroids; (2) target specificity for drug discovery through discrimination of TNFR1 versus TNFR2 receptor conformations and selective FLT modulation by receptor-specific small molecules; and (3) protein misfolding, as exemplified through simultaneous monitoring of alpha-synuclein oligomerization and misfolding. We further show that MDF can be applied within a single cellular environment, demonstrating the feasibility of same-cell multiplexing under optimized transient transfection conditions. MDF provides a scalable framework for real-time, live-cell biosensing across high-throughput, target-specific, and tissue-level applications in complex biological systems.

Keywords: multiplexed FRET, fluorescence lifetime, dark acceptor biosensors, high-throughput screening, live-cell biosensors, 3D spheroid models

Graphical Abstract

graphic file with name nihms-2168537-f0001.jpg

Fluorescent proteins are foundational tools in modern biology used to track protein expression and subcellular localization and to monitor cellular processes across diverse systems. From single-molecule assays to whole-organism imaging, genetically encoded fluorophores have revolutionized how biologists interrogate the living cell. Multiplexed imaging using multiple fluorescent proteins — each with distinct excitation and emission properties — is now routine for studying colocalization, lineage tracing, or parallel signaling events.

Förster resonance energy transfer (FRET) builds upon this foundation, enabling real-time monitoring of protein–protein interactions, conformational changes, and dynamic signaling in living cells. FRET biosensors have been widely adopted using fluorescence intensity or fluorescence lifetime (FLT) detection modalities. However, expanding FRET to track multiple interactions simultaneously presents significant challenges. Multiplexed FRET systems must navigate crowded emission spectra, complex spectral unmixing, and the need for carefully balanced controls to distinguish overlapping signals. While advanced multiplexing approaches — such as pulsed interleaved excitation–fluorescence lifetime imaging microscopy (PIE-FLIM),^1,2 dual-color fluorescence cross-correlation spectroscopy,³ donor photochromism,⁴ and FRETfluor barcoding⁵ — have ingeniously addressed some of these barriers, they often require specialized optics, complex reagent preparations, or are restricted to in vitro^6–8 or fixed samples,⁹ limiting their general accessibility to the broader research community.

For the first time, we show the power and broad utility of multiplexing FRET using spectrally distinct donors — mNeonGreen (mNg) and mScarlet-I3 (mScI3) — with recently developed non-emissive dark acceptors — e.g., ShadowY¹⁰ (ShY) and ShadowR¹¹ (ShR) — for biological application. mNg and mSc were selected as donors for their exceptional photophysical performance — high quantum yields (QY; 0.80 and 0.65, respectively), long excited-state lifetimes (3.1 and 3.6 ns), rapid maturation (10 and 2 min), and true monomeric behavior.^12,13 These properties maximize dynamic range for lifetime-based FRET while minimizing oligomerization artifacts and donor bleed-through. Unlike conventional fluorescent acceptors such as mCherry (QY of 0.22 and an extinction coefficient [EC] of 72,000 M⁻¹ cm⁻¹), dark acceptors (ShadowY, ShadowR) — engineered variants of YFP and RFP — that absorb efficiently (EC 136,000 and 97,100 M⁻¹ cm⁻¹, respectively) but emit negligibly (QY ≤ 0.01), eliminating spectral bleed-through into donor channels.^10,11 This enables single-channel FLT detection, simplifying multiplexed measurements on standard instrumentation. This genetically encoded platform expands the accessibility of multiplexed biosensing of protein-protein interactions in living cells and is herein called Multiplexed Dark FRET (MDF). MDF enables orthogonal FRET readouts from donor fluorescence alone, significantly reducing spectral crosstalk and simplifying experimental design via straightforward implementation using standard FLT or intensity-based imaging systems. Despite the demonstrated advantages of dark acceptors, their use in simultaneous, genetically encoded live-cell biosensing has remained unexplored with only few studies leveraging them for single channel FRET or FLIM applications.^14–17 MDF fills this gap by expanding the accessibility of multiplexed FRET measurements for real-time analysis of protein-protein interactions in both 2D and 3D biological systems.

Our previous work has established a broad suite of FRET biosensors that monitor protein-protein interactions and conformation changes for high-throughput screening (HTS). These biosensors include several tumor necrosis factor superfamily receptors (TNFSFRs; e.g., TNFR1, TNFR2, and DR5^18–24) and multiple amyloidogenic proteins (e.g., alpha-synuclein [aSyn], tau, TDP43, and Huntington protein).^25–29

We demonstrate the versatility of MDF through three biologically relevant applications. First, we apply MDF in neuron–microglia spheroids to enable spatially resolved, cell-type-specific biosensing within tissue-like environments — addressing a critical need for dynamic, multiplexed measurements in advanced 3D systems. Second, we show that MDF allows live-cell discrimination of TNFR1 and TNFR2 conformational responses to pharmacologic agents, providing a streamlined and scalable approach for assessing receptor-selective activity in anti-TNFR drug discovery. Third, we leverage MDF to simultaneously monitor alpha-synuclein oligomerization and intramolecular misfolding, delivering orthogonal insight into distinct steps of the amyloidogenic cascade relevant to synucleinopathies. Together, these applications position MDF as a powerful, accessible platform for multiplexed monitoring of protein interactions and signaling in both HTS and physiologically complex biological systems.

RESULTS

Dark Acceptor-Based Biosensors Enable Orthogonal FRET in Live Cells

Conventional FRET multiplexing is hindered by spectral bleed-through where fluorescent acceptor emission overlaps donor channels, distorting FLT measurements; MDF resolves this by replacing emissive acceptors with dark variants that eliminate such crosstalk. We engineered a series of donor-only and donor–acceptor FRET constructs (Figure 1A–B and Tables S1–S5) to illustrate the technical challenges of multiplexing FRET biosensors and to showcase how the MDF platform overcomes these limitations. These biosensors include a conventional FRET pair (mNg/mCh) and two dark acceptor FRET pairs (mNg/ShY, mScI3/ShR; see Figure S1 for MDF fluorophore FRET pair excitation and emission spectra). Positive FRET controls were constructed following an acceptor-linker-donor structure with a 23 amino-acid GSG4 linker (L) segment. All dual-fluorophore biosensors were engineered with the acceptor at the N-terminus to improve expression fidelity and minimize artifacts from incomplete fluorophore maturation. N-terminal fusion proteins often fold and express more reliably than C-terminal fusions.^30–32 By placing the acceptor at the N-terminus, we minimize misfolded or truncated products that would artifactually lower FRET efficiency.

Our FLT-plate reader has two laser lines, a 473 nm laser exciting mNg and 532 nm laser for mCh and mScI3. Figure 1A,B (right panels) illustrates the emission spectra for the three conventional XFPs used in this study. Fluorescent micrographs for donor only and positive FRET acceptor-linker-donor biosensors expressed in HEK293T cells are presented in Figure S2. Only the mCh-L-mNg biosensor results in overlapped red/green signal due to emission from both donor and acceptor fluorophores (Figure 1A). Using FLT based FRET allows for monitoring of donor emission alone, which for mNg occurs over a sparse region of the spectrum. In contrast, both mCh and mScI3 emission spectra span the same wavelengths. Figure 1C highlights that both mNg/mCh and mNg/ShY biosensors have a robust change in FLT (ΔFLT) relative to mNg only condition, which indicates FRET. A similar ΔFLT is observed for the mScI3/ShR FRET pair relative to mScI3 alone (Figure 1D).

When multiplexing a conventional FRET biosensor (mNg/mCh) with a red dark-acceptor biosensor (mScI3/ShR) — Figure 1A — the emission overlap between mCh (acceptor) and mSc (donor) confounds the red channel’s FLT measurements. Figure 1D illustrates the source of this artifact: the mCh-L-mNg construct produces a short FLT when monitored in the red channel. When co-transfected with a red mScI3 biosensor (Figure 1E), this overlap between mCh acceptor emission and mSc donor fluorescence yields an apparent decrease in FLT that mimics an increase in FRET. The observed reduction in FLT therefore reflects a convolution of the two red fluorophore signals rather than true energy transfer — a classic false-positive artifact that underscores how conventional fluorescent acceptors complicate multiplexed FLT analysis. In contrast, when we mix two cell populations that express two MDF biosensors (mNg/ShY and mScI3/ShR) we eliminate the spectral overlap, allowing independent recovery of each channel’s FLT (Figure 1F,G) with no significant differences between single and mixed conditions.

In these initial MDF validation experiments we take advantage of mixed-population assays which were designed as stringent controls to verify the MDF biosensor’s optical orthogonality between channels before attempting same-cell multiplexing. This configuration mirrors the spatial segregation encountered in our 3D spheroid model (see MDF Application #1), providing a conservative demonstration of independent FLT detection. Below we evaluate the background FRET signal from these MDF systems, explore a series of MDF applications using a mixed biosensor approach, and lastly we demonstrate the MDF application in a set of co-transfected (single-cell population) systems.

MDF Biosensor Background FRET Signal

For any fluorescence-based FRET assay it is important to assess whether ΔFLT (e.g., FRET) in the absence of biologically meaningful interactions could arise simply from co-expression of donor (mNg/mScI3) and acceptor (ShY/ShR). To determine whether non-specific fluorophore interaction contributes measurably to the basal ΔFLT in multiplexed conditions, we generated a comprehensive panel of constructs — including donor-only XFPs, positive linker controls, conventional and dark acceptor constructs, and a set of dual-expression plasmids encoding donor/acceptor pairs separated by an internal ribosome entry site (IRES). The IRES design ensures stoichiometric, co-expressed fluorophores that remain spatially uncoupled.

We performed a series of control experiments using donor-only, donor and acceptor, IRES constructs for donor and acceptor, and bi-/tetra-expression systems to investigate the potential for non-specific fluorophore interactions (see Figures 2, S2, and S3). For the red channel (532 nm excitation), all tested conditions for mScI3 co-expressed with ShY, mNg, or ShY alone did not measurably alter donor mScI3 FLT (Figure 2A). Importantly, when all four MDF fluorophores (mNg, mScI3, ShY, ShR) were co-transfected as independent plasmids, no significant reduction in donor lifetime was observed for the red-channel donor (mScI3), demonstrating that emissive crosstalk between the red donor and all other XFPs is negligible under our transient transfection conditions. This observation was also repeated with the series of IRES constructs (Figure 2B) where transfection of mScI3-IRES-mNg (SIN), ShR-IRES-mScI3 (RIS), or RIS with ShY-IRES-mNg (YIN) resulted in consistent mScI3 FLT. In contrast, although the green channel (473 nm excitation) donor (mNg) had consistent FLT when co-transfected with a single fluorophore (Figure 2C), it exhibited a modest decrease in FLT when all four fluorophores were co-expressed. Critically, this effect was eliminated when the same fluorophore combinations were delivered as IRES-linked dual-expression constructs (Figure 2D). In these stoichiometric, co-expressed controls, neither SIN, YIN, nor RIS constructs exhibited significant ΔFLT relative to matched donor-only controls (Figure S3).

Figure 2. — Evaluation of background signal of co-expressed MDF fluorophores. (A) Monitoring mScI3 FLT under co-expression with ShY, mNg, ShR individually or altogether in one system resulted in no significant change in mScI3 FLT in the 532 nm channel. (B) Comparison of mScI3 to a series of IRES constructs—mScarletI3-IRES-mNeongreen (SIN); ShadowR-IRES-mScarlet (RIS); ShadowY-IRES-mNeongreen (YIN)—that produce both a separate donor and acceptor from a single CDNA show similar no change in mScI3 FLT. (C) Similar experiments as in (A) but for the mNg donor show no change for two construct transfections; however, all four resulted in a significant reduction in FLT. (D) Comparison of mNg to IRES constructs show no significant change under all conditions, including all four fluorophores. Statistical comparisons of IRES to the co-transfection conditions is presented in Figure S3. Data represent mean ± SD of n = 3 biological replicates; significance determined by one-way ANOVA (ns = p > 0.05; ** = p < 0.01).

Together, these results establish that: (1) background FRET is minimal for both MDF donor/acceptor pairs; (2) multiplexed expression of all four MDF fluorophores does not perturb donor FLT in the red channel; and (3) apparent FLT reductions in the green channel arise only under extreme, tetra-transient transfection conditions. This can be explained through a comparison of the excitation/absorbance spectra of all four fluorophores to the mNg emission spectrum (Figure S4) where the spectral overlap indicates that each of the fluorophores can act as an acceptor for mNg. More importantly, this artifact can be fully resolved by controlling fluorophore stoichiometry via IRES-linked constructs. These findings demonstrate that the MDF signal reflects bona fide protein-dependent changes in donor–acceptor interactions and is not confounded by nonspecific interactions among the fluorophores themselves.

MDF Application #1: Cell-Type-Specific FRET Readouts in 3D Neuro-Glial Spheroids

Recent advances in genetically encoded fluorescent biosensors have enabled the investigation of dynamic signaling, differentiation, and disease processes within 3D organoid systems. As one of many examples, calcium indicators like GCaMP have been applied across brain, cardiac, and intestinal organoids to track functional activity and tissue maturation,³³ while FRET-based biosensors for kinases such as ERK, PKC, and PKA have been adapted to monitor spatially resolved intracellular signaling in response to environmental cues and therapeutic agents.^34–36 These tools are increasingly paired with advanced imaging modalities — such as light-sheet microscopy for volumetric acquisition and fluorescence lifetime imaging microscopy (FLIM) for quantitative FRET detection in optically dense tissues.^33,37 However, current applications rely on single-channel reporters or require sequential measurements, limiting the ability to resolve multiple concurrent signaling events. As organoids and assembloids grow in complexity — with multiple interacting cell types and spatial organization — there is a growing need for biosensing strategies that can interrogate multiple protein interactions or signaling dynamics in a cell-type-specific manner. MDF meets this challenge by enabling orthogonal FRET readouts from genetically encoded biosensors expressed in distinct cellular compartments within live 3D systems.

To evaluate the utility of MDF in tissue-like systems, we applied the platform to 3D self-assembled aggregates composed of SHSY5Y-derived neurons and HMC3 microglia.³⁸ These co-culture neuro-glial spheroids (NGS) offer a physiologically relevant model for studying intercellular signaling. SHSY5Y (S) and HMC3 (H) cells were transfected with either donor-only (mNg or mScI3) or donor-acceptor constructs (ShY-L-mNg or ShR-L-mScI3), then self-assembled into NGS using a combination of untransfected (S0, H0) or transfected (S1, H1 for donor only; S2, H2 for donor-acceptor) cell populations. Figure 3A–D presents live cell images of two S2+H2 NGS. FLT analysis showed robust FRET responses within each cell type, with donor–acceptor constructs exhibiting significantly reduced lifetimes compared to donor-only controls (Figure 3E,I). Critically, the presence of biosensors in one cell type had no impact on FRET detection in the other, confirming that MDF maintains signal specificity in 3D mixed-cell spheroids (Figure 3F–H,J–L). The inclusion of FRET efficiency provides interpretive clarity (increased FRET = closer distances/more aggregation; reduced FRET = farther apart/dissociation); however, FLT provides higher precision because the FRET efficiency values propagate measurement error from both donor and donor+acceptor conditions.

Figure 3. — Multiplexed MDF biosensors implemented in 3D neuro-glial spheroids (NGS) resolves cell-type specific FRET. Control MDF biosensors were expressed in a series of SHSY5Y/HMC3 spheroids. Green: S0 = naive SHSY5Y; S1 = mNg; S2 = ShY-L-mNg; Red: H0 = naïve HMC3; H1 = mScI3; H2 = ShR-L-mScI3. (A–D) Live-cell fluorescent imaging of two distinct S1+H1 NGS with green SHSY5Y derived neurons and red HMC3 microglia. Transmitted light overlays in panel A, and panel C highlights NGS perimeter. Cell nuclei are stained with Hoechst dye (blue). (E) Comparison of SHSY5Y FLT in NGS spanning all HMC3 biosensor conditions. (F) No significant difference between SHSY5Y donor only (S1) across spheroid type. (G) No significant difference between SHSY5Y donor + acceptor (S2) across all NGS compositions. (H) Resulting green channel FRET is not changed across all NGS compositions. (I) Comparison of HMC3 FLT in spheroids spanning all SHSY5Y biosensor conditions. (J) No significant difference between HMC3 donor only (H1) across NGS. (K) No significant difference between HMC3 donor + acceptor (H2) across all spheroid compositions. (L) Resulting red-channel FRET is not changed across all NGS compositions. Data represent mean ± SD of n = 3 biological replicates; significance determined by one-way ANOVA (ns = p > 0.05; **** = p < 0.0001).

The transient transfection of SHSY5Y and HMC3 cells typically yields modest efficiency (~30%), resulting in a fraction of non-transfected cells within the NGS. Despite this, both green and red donor FLT signals were readily detectable, demonstrating that even partial biosensor expression is sufficient for signal acquisition. It is important to note that while optical scattering in 3D cultures can attenuate excitation light (particularly at shorter visible wavelengths such as 473 and 532 nm), the small diameter of our neuro-glial spheroids (<200 μm) and time-gated FLT detection help to minimize depth bias. Imaging studies in organoids and spheroids report effective penetration depths of ~40 to 100 μm under visible illumination (e.g., confocal imaging in cerebral organoids is typically limited to <100 μm³⁹) and marked intensity falloff with depth.⁴⁰ Moreover, tissue optics measurements⁴¹ suggest mean free paths in biological tissues on the order of 50–160 μm at visible/near-visible wavelengths, indicating that our measured FLT likely reflect contributions primarily from the outer one or two cell layers of our spheroids.

MDF Application #2: Multiplexed FRET Differentiates TNFR1 and TNFR2 Conformation Changes in Live Cells

We have previously demonstrated that cellular TNFSFR FRET biosensors report a basal FRET signal from pre-ligand dimers that reflects the proximity of the intracellular receptor termini and serves as a sensitive proxy for receptor conformation.^21,22,24,42 Importantly, we observed that perturbations to this basal FRET — through mutagenesis or small-molecule treatment — correlate with downstream signaling outcomes, including IκB degradation and activation of NF-κB transcription factors.^19,20,24 This conserved conformational signature across TNFSFRs provides a powerful foundation for HTS of receptor-specific modulators using FRET-based readouts.

We applied the MDF platform to extend this approach to a dual-receptor format, enabling simultaneous monitoring of TNFR1 and TNFR2 in live cells. Although these receptors bind the same ligand — TNF — they drive distinct and often opposing signaling outcomes: TNFR1 primarily mediates pro-inflammatory and apoptotic pathways, while TNFR2 promotes tissue regeneration and neuroprotection.^43–47 Despite this dichotomy, current anti-TNF therapies indiscriminately neutralize TNF itself — suppressing both beneficial and detrimental signaling arms — which has led to well-documented adverse effects including increased risk of infection, demyelinating disease, and impaired tissue repair.^47–49 As a result, there is increasing interest in therapeutic approaches that selectively modulate receptor activity without altering ligand availability. However, the high sequence and structural similarity between TNFR1 and TNFR2 complicates the identification of receptor-selective compounds, often requiring additional validation assays beyond the primary screen. Conventional drug screening workflows often require orthogonal, time- and resource-intensive secondary assays to distinguish on-target effects.^19,23,24,50 A biosensing platform that can resolve receptor-specific activity in real time — within a single assay — is thus a powerful tool for advancing TNFSFR-targeted drug discovery.

To address this challenge, we developed full-length, conformationally responsive FRET biosensors for TNFR1 and TNFR2 with C-terminal fusions of mScI3/ShR (TNFR1) pair and mNg/ShY (TNFR2), see Figure 4A. These biosensors report on ligand-independent conformational changes within the pre-ligand assembly domain (PLAD) that mediates constitutive receptor dimerization in TNF-receptor superfamily members. Transient co-transfection of TNFR1 and TNFR2 biosensors in HEK293T cells at a 1:1 donor-to-acceptor ratio resulted in red and green puncta across the plasma membrane (Figure S5) and a robust FRET signal (Figure 4B). When combined in mixed cell populations, MDF preserved channel specificity, allowing for orthogonal monitoring of each receptor’s conformation (Figure 5A).

Figure 4. — Design of receptor-specific MDF for TNFRSF targets. (A) Schematic of TNFR1 (R1, *left*; mScI3/ShR fusion) and TNFR2 (R2, *right*; mNg/ShY fusion) FRET biosensors using the MDF FRET pairs. Both receptors are full-length, functional constructs with a C-terminal XFP fusion and under basal conditions exist as a preligand-assembly domain (PLAD)-mediated dimer. (B) Expression of donor-only (D) or donor + acceptor (DA; at a 1:1 ratio) in HEK293T cells results in a robust ΔFLT (FRET) signal. Panel A generated in Biorender. Data represent mean ± SD of n = 3 biological replicates; significance determined by one-way ANOVA (ns = p > 0.05; **** = p < 0.0001).

Figure 5. — MDF differentiates receptor-specific TNFR1 and TNFR2 conformation changes in mixed cell populations. (A) R1 and R2 MDF biosensors show no change in FLT between single or mixed samples (two cell populations, each expressing one biosensor) for either D or DA biosensors. (B) R1 and R2 biosensor cells were treated with DMSO or 10 μM zafirlukast (Zaf) for 2 h. The TNFR1 small-molecule inhibitor Zaf disrupts R1 ΔFLT while having no change in R2 ΔFLT. (C) Similar to Zaf, a TNFR2-specific small molecule (drug-A treated at 10 μM for 2 h) reduces R2 DA FLT while having no effect on R1 or D only conditions. Data represent mean ± SD of n = 3 biological replicates; significance determined by one-way ANOVA (ns = p > 0.05; **** = p < 0.0001).

To test whether MDF could distinguish receptor-specific perturbations, we treated biosensor-expressing cells with either zafirlukast, a compound that we previously identified as a TNFR1-selective allosteric inhibitor¹⁹ or Drug-A, a hit compound identified in an unpublished TNFR2 HTS campaign. Biosensor cells were harvested and plated for FLT acquisition in 384-well, black walled plates with a pre-dispensed DMSO, zafirlukast, or Drug-A (0.5μL per well for final concentration of 10 μM compound, 0.5% DMSO v/v) and incubated for 2 h prior to FLT acquisition, consistent with previously reported TNFR1 FRET assays.^19,23,24 Zafirlukast treatment abolished the basal FRET signal in the TNFR1 biosensor while having no measurable effect on TNFR2 (Figure 5B). Conversely, Drug-A showed a reduction in TNFR2 FLT while having no effect on TNFR1 (Figure 5C).

It is important to note that the ΔFLT effect of zafirlukast for TNFR1 and Drug-A for TNFR-2 are in different directions — zafirlukast reduces FRET and is a well characterized TNFR1 inhibitor, whereas Drug-A increases FRET. Our work identify Drug-A is still preliminary and we do not yet know what the conformational changes of R2 signify, nor the functional outcome of Drug-A. Those efforts are the scope of future TNFR2 work and not part of this study. These two distinct responses confirm selective target engagement and help establish MDF as a high-resolution platform for multiplexed biosensing of TNFSFRs and demonstrate its utility in identifying conformation-selective, receptor-specific modulators with immediate translational relevance.

MDF Application #3: Dual aSyn Biosensors Monitor Aggregation and Misfolding

Alpha-synuclein misfolding and aggregation is a hallmark of Parkinson’s disease, progressing through a multi-step cascade from monomeric aSyn to toxic oligomers and eventually to fibrillar inclusions.^51–57 Pinpointing when and how these aggregation events become pathogenic remains a major challenge. Our previous work established two complementary FLT-FRET biosensors to monitor distinct aspects of aSyn aggregation. One biosensor detects intermolecular FRET between monomers, each fused at the C-terminus to either a donor or acceptor fluorophore, enabling quantification of oligomerization.²⁷ The second employs an intramolecular dual-fusion design, with donor and acceptor fluorophores positioned at the N- and C-termini of the same aSyn molecule, allowing detection of both oligomerization and conformation changes.^27,28 These biosensors have been successfully applied in high-throughput screening (HTS) campaigns, leading to the identification of nanomolar-potency inhibitors that suppress aSyn-induced toxicity.^27,28

The MDF platform extends our previously developed aSyn biosensors by enabling their simultaneous use in a multiplexed configuration. This dual-sensor approach allows real-time tracking of two mechanistically distinct events: oligomer assembly, which is reported by both biosensors, and monomer misfolding, which is uniquely captured by the intramolecular sensor through changes in FRET that are unique to the double fusion biosensor (i.e., non-overlapping hit compounds across the two, intramolecular and intermolecular, biosensors). This setup provides an integrated view of aggregation state dynamics and allows discernment between interventions that target assembly, structural conformation, or both. Figure 6A illustrates the single-fusion aSyn biosensors (aSyn-mScI3 and aSyn-ShR), which report oligomerization via reduced donor fluorescence lifetime (FLT) when co-expressed at a 1:4 donor-to-acceptor ratio.²⁷ Figure 6B shows the dual-fusion aSyn sensor (ShY-aSyn-mNg), which detects both folding and oligomerization via FLT reduction relative to donor-only controls.²⁸ HEK293T cells were used for both biosensors, an established model for aSyn FLT-FRET HTS by our group.^27,28 Transient expression of these MDF biosensors (Figure S6) results in diffuse cytoplasmic distribution, consistent with our previous studies.^27,28 As with the TNFR1/TNFR2 system, FLT measurements can be acquired under single or mixed-cell conditions (Figure 6C,D), enabling simultaneous screening of both biosensors. Importantly, using the same target protein across two spectrally distinct channels enhances the robustness of the assay by reducing susceptibility to false positives from fluorescent interfering compounds — an essential advantage for HTS applications.

Figure 6. — MDF enables concurrent monitoring of two mechanistically different aSyn aggregation biosensors. (A) Schematic of aSyn-mScI3/aSyn-ShR single-fusion (aggregation) biosensor and the corresponding FLT for donor only and donor + acceptor (1:4 D:A ratio) conditions. (B) Schematic of te ShY-aSyn-mNg double fusion (folding) biosensor and corresponding FLT for donor only and donor + acceptor conditions. These aSyn MDF biosensors are being expressed in HEK293T cells. aSyn MDF biosensors under single and mixed cell biosensor conditions show no significant difference for either the oligomerization (C) or folding biosensor (D). Panels A-B generated in Biorender. Data represent mean ± SD of n = 3 biological replicates; significance determined by one-way ANOVA (ns = p > 0.05; **** = p < 0.0001).

Demonstration of Same-Cell Multiplexing of MDF Biosensors

In the applications above, MDF multiplexing was demonstrated using mixed cell populations, a configuration that provides a stringent validation of channel orthogonality. To determine whether MDF can also function as a true same-cell multiplexing platform, we next evaluated whether both channels could be co-expressed and independently resolved within a single cellular environment. To test this feasibility, we performed co-expression experiments using (i) a linker-based positive-control system and (ii) full-length TNFR1 and TNFR2 MDF biosensors. The resulting FLT measurements, presented in Figure 7, demonstrate that both MDF channels can be simultaneously expressed and independently quantified within the same cell population. These findings extend the MDF platform beyond mixed-population formats and establish the foundation for future multiplexed biosensing applications that require same-cell resolution.

Figure 7. — Utilizing MDF biosensors within the same cellular context. Co-expression of both red and green MDF control linker biosensors within the same cell (not-mixed cell populations) for the 532 nm channel (A) and 473 nm channel (B) shows no significant difference between donor-only and linker conditions, respectively. A similar true multiplexing of TNFR1 (R1) and TNFR2 (R2) MDF biosensors within the same cell (C) R1, 532 nm channel; (D) R2, 473 nm channel) showed no change between conditions (see Discussion section for details on transfection differences). Data represent mean ± SD of n = 3 biological replicates; significance determined by one-way ANOVA (ns = p > 0.05; ** = p < 0.01; **** = p < 0.0001).

Control Linker System

We first evaluated same-cell multiplexing using the acceptor– linker–donor positive controls for each channel (ShY-Linker-mNg and ShR-Linker-mScI3). HEK293T cells were co-transfected with combinations of donor-only and linker constructs to recapitulate all relevant multiplexing configurations: (1) green-channel donor-only with red-channel linker; (2) green-channel linker with red-channel donor-only; (3) and (4) dual linker expression, in which both MDF FRET pairs were expressed within the same cells (Figure 7A,B). Across all conditions, we observed no significant differences in donor FLT relative to the corresponding single-biosensor controls, indicating that simultaneous expression of both MDF FRET pairs does not introduce detectable background FRET or optical interference in either channel. These findings confirm that the MDF fluorophore sets remain orthogonal even when co-localized within the same cellular environment.

TNFR1/TNFR2 Co-expression

We next attempted same-cell co-expression of the full-length TNFR1 and TNFR2 MDF biosensors using the same transient transfection strategy applied in the linker (Figure 7A,B) and background (Figure 2) experiments. Under these initial conditions, two issues emerged: (i) substantial cell death, consistent with TNFR1 overexpression triggering ligand-independent receptor activation, and (ii) a pronounced decrease in the green-channel donor FLT, whereas the red-channel donor remained unaffected (data not shown) — mirroring the sensitivity observed in the tetra-construct background controls (Figure 2A,C). To overcome these limitations, we red- uced the total biosensor DNA and shortened the expression window. Under these optimized conditions, co-expression of TNFR1–mScI3/ShR and TNFR2–mNg/ShY yielded robust, channel-specific FLT signals without detectable cross-interference (Figure 7C,D). These findings demonstrate that true same-cell MDF multiplexing is achievable but also indicates that tetra-construct transient transfection poses particular challenges for the green-channel donor. Further optimization — such as DNA titration, regulated expression, or stable/inducible integration — is likely to improve assay robustness and support broader implementation of same-cell MDF applications.

DISCUSSION

Several advanced multiplexing strategies have expanded the scope of FRET detection, including PIE-FLIM,^1,2 dual-color fluorescence cross-correlation spectroscopy,³ and FRETfluor barcoding.⁵ Each approach provides elegant solutions for separating overlapping signals, yet their performance gains often come at the cost of throughput and accessibility. PIE-FLIM, for example, achieves temporal separation of donor excitation by interleaving synchronized laser pulses, allowing simultaneous FLT readouts from multiple biosensors with minimal spectral interference. While this configuration provides exceptional single-cell sensitivity and quantitative precision, it requires multiple pulsed-laser sources, gated detection electronics, and computationally intensive lifetime-unmixing algorithms. Typical acquisitions for PIE-FLIM occur on a seconds-per-field timescale, which limits throughput and scalability for multi-sample or screening applications. Similarly, the recently introduced FRETfluor barcoding system⁵ attains high-density multiplexing through engineered DNA-based nanostructures that encode distinct photophysical signatures in FLT and intensity space. Although this design allows discrimination of dozens of spectrally overlapping fluorophores at single-molecule sensitivity, it demands complex nanostructure fabrication and multivariate classification pipelines and is presently confined to in vitro implementations.

In contrast, MDF extends our previously validated single plex FLT-FRET biosensors — already established as a HTS platform for drug discovery^{18,23–28,58,59} — into a multiplexed format that retains genetic encoding, standard instrumentation, and straightforward analysis. By reducing optical and computational barriers, MDF bridges high-content multiplexed biosensing with the practical requirements of scalable screening and physiologically relevant emerging 3D model systems and remains fully compatible with live-cell workflows.

We validated MDF across three biological applications, each highlighting a unique advantage of the platform. First, in 3D NGSs, MDF biosensors enabled cell-type specific, spatially resolved FRET readouts. Even with modest transfection efficiencies, MDF provided robust, channel-specific FRET signals, enabling the study of protein interactions in defined cell populations. For HTS, population-level changes in FLT offer powerful readouts of global pathway activity or aggregation. Expanding MDF to spatially resolved FLIM would further reveal heterogeneity across microenvironments. Importantly, mixed populations of biosensor-positive and -negative cells enable studies of intercellular communication, signal propagation, and tissue architecture, supporting applications such as bioprinting or modeling neuroinflammatory cascades in disease-relevant 3D systems.

Second, we applied MDF to dissect receptor-specific conformational changes in TNFR1 and TNFR2. Simultaneous tracking of both receptors revealed selective ΔFLT response for TNFR1 by zafirlukast, and TNFR2 by Drug-A, demonstrating the platform’s ability to resolve receptor specificity in real time. This eliminates the need for sequential secondary assays and addresses a key challenge in anti-TNF therapeutic development.

Third, MDF was used to probe mechanistically distinct steps in aSyn aggregation. By combining intermolecular and intramolecular FRET biosensors, MDF enables simultaneous detection of oligomerization and conformational misfolding — key features of synucleinopathies. This dual-readout approach improves mechanistic insight and assay robustness, allowing researchers to differentiate between compounds that affect oligomer formation versus conformational collapse. Additionally, pairing the same biosensor design in both channels offer internal target redundancy that reduces false positives from fluorescent compound interference.

Although all current experiments represent endpoint measurements, the MDF approach permits real-time monitoring of conformational or aggregation kinetics. In our previous HTS campaigns, we have incorporated multiple timepoint reads (e.g., 30, 60, 120 min) within the same workflow to track compound-dependent responses and signal stability.^27,28 Extending this strategy to MDF will allow systematic exploration of the temporal limits of biosensor responsiveness, including reversibility, signal recovery, and dynamic range under pharmacologic or environmental perturbation. Defining these parameters will be a central goal of ongoing work to establish MDF as a quantitative, time-resolved platform for tracking rapid molecular interactions in living systems.

MDF has broad applications across biological systems where multiple protein interactions underlie complex signaling and functional outcomes. As one of many examples, MDF holds particular promise for investigating co-proteinopathies in neurodegenerative diseases, where concomitant aggregation of proteins such as aSyn, tau, TDP43, and Aβ is recognized as a driver of disease pathology.^60–68 Recent studies demonstrate that tau and aSyn can cross- seed aggregation, exacerbating neurotoxicity.^60–64 Furthermore, the presence of TDP43 pathology in a substantial fraction of Alzheimer’s disease cases^66–68 correlates with worsened cognitive decline. Understanding how these misfolded species interact in real time within live-cell or 3D models will be essential for unraveling disease mechanisms. For example, one application of MDF could involve expressing an aSyn-targeted (green channel) and tau-targeted (red channel) biosensor in distinct neuronal populations within NGS. This configuration would allow researchers to assess how shared cellular stressors influence aggregation dynamics of each protein independently, and to identify both common and protein-specific therapeutic responses in a spatially defined, multicellular context.

Biomolecular condensates — e.g., stress granules, p-bodies — are formed through liquid–liquid phase separation and represent another class of dynamic, multicomponent ass- emblies. These membraneless organelles rely on multivalent protein–RNA interactions and are governed by intrinsically disordered domains.⁶⁹ Emerging work highlights their roles in transcription, stress response, and disease, and calls for tools that can simultaneously track multiple protein assemblies within or across condensates.^70–75 MDF provides a genetically encoded, multiplexed platform ideally suited to dissect how these multicomponent assemblies form, dissolve, and influence disease pathogenesis.

MDF’s multiplexed capabilities are also well suited to interrogating immune signaling cascades in neurobiology and oncology. In neuron–glia co-cultures or brain assembloids, for example, one biosensor could track neuronal stress or receptor activation while the other reports glial cytokine responses or inflammatory transcriptional events. This level of spatially compartmentalized signaling is essential for dissecting cell-specific neuroinflammatory cascades in neurodegenerative disease models. Recent studies emphasize the need for simultaneous imaging of cytokine and neuronal signals in 3D systems to understand how inflammation spreads through tissue-level networks.^76,77 In the context of CAR-T cell therapy, MDF can provide real-time dual readouts of antigen receptor activation and effector function. This pairing enables mechanistic studies linking signal input with therapeutic output. Multiplexed live-cell reporters are increasingly recognized as essential tools for optimizing CAR construct design and reducing toxicity, bridging signaling features with function in tumor microenvironments.^78,79 MDF provides a scalable solution for these high-content screening applications.

While MDF represents a major advancement for live-cell multiplexed biosensing, several limitations remain that will guide future development. Our same-cell co-expression experiments demonstrate that true multiplexing is feasible; however, successful implementation under transient transfection requires that the paired targets be sufficiently orthogonal and that expression levels be tightly controlled. This consideration is especially important for any blue-shifted (green channel) MDF biosensor: when all four MDF fluorophores are co-expressed, the green-channel donor (mNg) encounters two additional potential acceptors in the local environment, making this channel more sensitive to construct stoichiometry and overexpression. In contrast, the red-channel donor (mScI3) showed greater robustness during co-expression, a factor that should be considered when selecting which MDF channel to assign to a given target. These findings indicate that while true same-cell multiplexing is achievable, optimization — such as DNA titration, regulated expression, or stable/inducible integration — will enhance reliability and reduce artifacts introduced by transient overexpression.

More broadly, MDF implementation relies on FLT detection, which — though increasingly available — is less ubiquitous than intensity-based platforms. Future optimization for ratiometric or intensity-only readouts could extend MDF into multimode plate readers and flow cytometers, broadening accessibility for therapeutic discovery platforms. In complex 3D systems, additional challenges include biosensor delivery, expression control, and imaging depth. Viral vectors or stable genomic integration will be critical for consistent biosensor expression, particularly in iPSC-derived organoids, and inducible or cell-type–specific promoters will help mitigate developmental or cell-stress effects.^80–82 Imaging larger or more optically dense organoids will require advanced modalities such as multi-photon FLIM or light-sheet microscopy,^83–85 and the effects of tissue size and light scattering on FLT measurements will need to be systematically evaluated in future work.

Despite these limitations, MDF transforms previously inaccessible FRET experiments into practical, high-content assays suitable for both basic and translational research. As the need grows for real-time, multiplexed monitoring of molecular interactions in live systems, MDF provides an accessible and scalable solution for probing dynamic signaling and protein-protein interactions in physiologically relevant models.

Supplementary Material

Braun et al ACS Sensors 2026 Supplement

NIHMS2168537-supplement-Braun_et_al_ACS_Sensors_2026_Supplement.pdf^{(9.9MB, pdf)}

The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acssensors.5c01707.

Materials and methods; summary of all biosensor constructs developed for this study, single XFP control biosensor DNA and amino-acid sequences, double XFP control biosensor DNA and amino-acid sequences, TNFSFR biosensor DNA and amino-acid sequences, and aSyn biosensor DNA and amino-acid sequences; MDF protein excitation and emission characterization, live cell imaging of control MDF biosensor expression, FLT comparison of IRES to co-transfected MDF biosensors, spectra overlap comparison for potential mNg acceptors, live cell imaging of TNFR1 and TNFR2 MDF biosensor expression, and live cell imaging of aSyn MDF biosensor expression (PDF)

ACKNOWLEDGMENTS

Fluorescence spectroscopy was performed at the UMN Biophysical Technology Center. This study was supported by the U.S. National Institutes of Health (NIH) grants to J.N.S. (NINDS R01NS117968 and NIA R21AG089930).

Footnotes

Complete contact information is available at: https://pubs.acs.org/doi/10.1021/acssensors.5c01707

The authors declare no competing financial interest.

Contributor Information

Anthony R. Braun, Department of Biomedical Engineering, College of Science and Engineering, University of Minnesota, 7-105 Nils Hasselmo Hall, 312 Church St SE, Minneapolis, Minnesota 55455, United States

Elly E. Liao, Department of Biomedical Engineering, College of Science and Engineering, University of Minnesota, 7-105 Nils Hasselmo Hall, 312 Church St SE, Minneapolis, Minnesota 55455, United States

Nagamani Vunnam, Department of Biomedical Engineering, College of Science and Engineering, University of Minnesota, 7-105 Nils Hasselmo Hall, 312 Church St SE, Minneapolis, Minnesota 55455, United States.

Sophia Zafari, Department of Biomedical Engineering, College of Science and Engineering, University of Minnesota, 7-105 Nils Hasselmo Hall, 312 Church St SE, Minneapolis, Minnesota 55455, United States.

Noah Nathan Kochen, Department of Biomedical Engineering, College of Science and Engineering, University of Minnesota, 7-105 Nils Hasselmo Hall, 312 Church St SE, Minneapolis, Minnesota 55455, United States.

Marguerite Murray, Department of Biomedical Engineering, College of Science and Engineering, University of Minnesota, 7-105 Nils Hasselmo Hall, 312 Church St SE, Minneapolis, Minnesota 55455, United States.

Jonathan N. Sachs, Department of Biomedical Engineering, College of Science and Engineering, University of Minnesota, 7-105 Nils Hasselmo Hall, 312 Church St SE, Minneapolis, Minnesota 55455, United States

Data Availability

All plasmids, fluorescence biosensor constructs, and other new reagents generated during this study will be made available upon reasonable request, in compliance with University of Minnesota material transfer protocols.

REFERENCES

(1).Reissaus CA; Day KH; Mirmira RG; Dunn KW; Pavalko FM; Day RN PIE-FLIM Measurements of Two Different FRET-Based Biosensor Activities in the Same Living Cells. Biophys. J 2020, 118 (8), 1820–1829. [DOI] [PMC free article] [PubMed] [Google Scholar]
(2).Windgasse L; Grashoff C Multiplexed Molecular Tension Sensor Measurements Using PIE-FLIM. In Mechanobiology; Methods in Molecular Biology; Springer; US, 2023, pp 221–237. [DOI] [PubMed] [Google Scholar]
(3).Bertolin G; Sizaire F; Déméautis C; Chapuis C; Mérola F; Erard M; Tramier M Optimized FRET Pairs and Quantification Approaches To Detect the Activation of Aurora Kinase A at Mitosis. ACS Sens 2019, 4 (8), 2018–2027. [DOI] [PubMed] [Google Scholar]
(4).Roebroek T; Vandenberg W; Sipieter F; Hugelier S; Stove C; Zhang J; Dedecker P Simultaneous readout of multiple FRET pairs using photochromism. Nat. Commun 2021, 12 (1), 2005. [DOI] [PMC free article] [PubMed] [Google Scholar]
(5).Chu J; Ejaz A; Lin KM; Joseph MR; Coraor AE; Drummond DA; Squires AH Single-molecule fluorescence multiplexing by multi-parameter spectroscopic detection of nanostructured FRET labels. Nat. Nanotechnol 2024, 19 (8), 1150–1157. [DOI] [PMC free article] [PubMed] [Google Scholar]
(6).Ouyang W; Li Q; Niu Q; Qui M; Fu H; Du Y; Mo X A multiplexed time-resolved fluorescence resonance energy transfer ultrahigh-throughput screening assay for targeting the SMAD4-SMAD3-DNA complex. J. Mol. Cell Biol 2024, 15 (11), No. mjad068. [DOI] [PMC free article] [PubMed] [Google Scholar]
(7).Cheppali SK; Li C; Xing W; Sun R; Yang M; Xue Y; Lu S-Y; Yao J; Sun S; Chen C; et al. Single-molecule two- and three-colour FRET studies reveal a transition state in SNARE disassembly by NSF. Nat. Commun 2025, 16 (1), 250. [DOI] [PMC free article] [PubMed] [Google Scholar]
(8).Mathur D; Thakur M; Díaz SA; Susumu K; Stewart MH; Oh E; Walper SA; Medintz IL Hybrid Nucleic Acid-Quantum Dot Assemblies as Multiplexed Reporter Platforms for Cell-Free Transcription Translation-Based Biosensors. ACS Synth. Biol 2022, 11 (12), 4089–4102. [DOI] [PMC free article] [PubMed] [Google Scholar]
(9).Liu J; Liu Z; Mi F; Yao Z; Fang X; Wang Y; Zhao Z; Wu C Fluorescence Lifetime Multiplex Imaging in Expansion Microscopy with Tunable Donor–Acceptor Polymer Dots. Chem. Biomed. Imaging 2023, 1 (6), 550–557. [DOI] [PMC free article] [PubMed] [Google Scholar]
(10).Murakoshi H; Shibata ACE ShadowY: a dark yellow fluorescent protein for FLIM-based FRET measurement. Sci. Rep 2017, 7 (1), 6791. [DOI] [PMC free article] [PubMed] [Google Scholar]
(11).Murakoshi H; Horiuchi H; Kosugi T; Onda M; Sato A; Koga N; Nabekura J ShadowR: a novel chromoprotein with reduced non-specific binding and improved expression in living cells. Sci. Rep 2019, 9 (1), 12072. [DOI] [PMC free article] [PubMed] [Google Scholar]
(12).Shaner NC; Lambert GG; Chammas A; Ni Y; Cranfill PJ; Baird MA; Sell BR; Allen JR; Day RN; Israelsson M; et al. A bright monomeric green fluorescent protein derived from Branchiostoma lanceolatum. Nat. Methods 2013, 10 (5), 407–409. [DOI] [PMC free article] [PubMed] [Google Scholar]
(13).Gadella TWJ; Van Weeren L; Stouthamer J; Hink MA; Wolters AHG; Giepmans BNG; Aumonier S; Dupuy J; Royant A mScarlet3: a brilliant and fast-maturing red fluorescent protein. Nat. Methods 2023, 20 (4), 541–545. [DOI] [PubMed] [Google Scholar]
(14).Obashi K; Sochacki KA; Strub M-P; Taraska JW A conformational switch in clathrin light chain regulates lattice structure and endocytosis at the plasma membrane of mammalian cells. Nat. Commun 2023, 14 (1), 732. [DOI] [PMC free article] [PubMed] [Google Scholar]
(15).Shibata ACE; Ueda HH; Eto K; Onda M; Sato A; Ohba T; Nabekura J; Murakoshi H Photoactivatable CaMKII induces synaptic plasticity in single synapses. Nat. Commun 2021, 12 (1), 751. [DOI] [PMC free article] [PubMed] [Google Scholar]
(16).Li L-L; Klein FM; Li Greci L; Popinigis A; Freudenberg F; Courtney MJ Resonance energy transfer sensitises and monitors in situ switching of LOV2-based optogenetic actuators. Nat. Commun 2020, 11 (1), 5107. [DOI] [PMC free article] [PubMed] [Google Scholar]
(17).Demeautis C; Sipieter F; Roul J; Chapuis C; Padilla-Parra S; Riquet FB; Tramier M Multiplexing PKA and ERK1&2 kinases FRET biosensors in living cells using single excitation wavelength dual colour FLIM. Sci. Rep 2017, 7 (1), No. 41026. [DOI] [PMC free article] [PubMed] [Google Scholar]
(18).Young MC; Vunnam N; Rebbeck RT; Yuen SL; Thomas DD; Sachs JN Indirubin Inhibits TRAIL-Induced Activation of Death Receptor 5 in Jurkat Cells. Nat. Prod. Commun 2023, 18 (1), No. 1934578X221144580. [DOI] [PMC free article] [PubMed] [Google Scholar]
(19).Vunnam N; Yang M; Lo CH; Paulson C; Fiers WD; Huber E; Been M; Ferguson DM; Sachs JN Zafirlukast Is a Promising Scaffold for Selectively Inhibiting TNFR1 Signaling. ACS Bio Med Chem. Au 2023, 3 (3), 270–282. [DOI] [PMC free article] [PubMed] [Google Scholar]
(20).Vunnam N; Young MC; Liao EE; Lo CH; Huber E; Been M; Thomas DD; Sachs JN Nimesulide, a COX-2 inhibitor, sensitizes pancreatic cancer cells to TRAIL-induced apoptosis by promoting DR5 clustering †. Cancer Biol. Ther 2023, 24 (1), No. 2176692. [DOI] [PMC free article] [PubMed] [Google Scholar]
(21).Lo CH; Schaaf TM; Thomas DD; Sachs JN Fluorescence-Based TNFR1 Biosensor for Monitoring Receptor Structural and Conformational Dynamics and Discovery of Small Molecule Modulators. In The TNF Superfamily; Methods in Molecular Biology; Springer; US; 2021; pp 121–137. [DOI] [PubMed] [Google Scholar]
(22).Lo CH; Huber EC; Sachs JN Conformational states of TNFR1 as a molecular switch for receptor function. Protein Sci 2020, 29, 1401. [DOI] [PMC free article] [PubMed] [Google Scholar]
(23).Lo CH; Schaaf TM; Grant BD; Lim CK; Bawaskar P; Aldrich CC; Thomas DD; Sachs JN Noncompetitive inhibitors of TNFR1 probe conformational activation states. Sci. Signal 2019, 12 (592), No. eaav5637. [DOI] [PMC free article] [PubMed] [Google Scholar]
(24).Lo CH; Vunnam N; Lewis AK; Chiu TL; Brummel BE; Schaaf TM; Grant BD; Bawaskar P; Thomas DD; Sachs JN An Innovative High-Throughput Screening Approach for Discovery of Small Molecules That Inhibit TNF Receptors. SLAS Discov 2017, 22 (8), 950–961. [DOI] [PMC free article] [PubMed] [Google Scholar]
(25).Lo CH; Lim CK; Ding Z; Wickramasinghe SP; Braun AR; Ashe KH; Rhoades E; Thomas DD; Sachs JN Targeting the ensemble of heterogeneous tau oligomers in cells: A novel small molecule screening platform for tauopathies. Alzheimers Dement 2019, 15 (11), 1489–1502. [DOI] [PMC free article] [PubMed] [Google Scholar]
(26).Lo CH; Pandey NK; Lim CK; Ding Z; Tao M; Thomas DD; Langen R; Sachs JN Discovery of Small Molecule Inhibitors of Huntingtin Exon 1 Aggregation by FRET-Based High-Throughput Screening in Living Cells. ACS Chem. Neurosci 2020, 11 (15), 2286–2295. [DOI] [PubMed] [Google Scholar]
(27).Braun AR; Liao EE; Horvath M; Kalra P; Acosta K; Young MC; Kochen NN; Lo CH; Brown R; Evans MD Potent inhibitors of toxic alpha-synuclein identified via cellular time-resolved FRET biosensors. NPJ Parkinsons Dis 2021, 7 (1), No. 52. [DOI] [PMC free article] [PubMed] [Google Scholar]
(28).Braun AR; Kochen NN; Yuen SL; Liao EE; Cornea RL; Thomas DD; Sachs JN Advancements in a FRET Biosensor for Live-Cell Fluorescence-Lifetime High-Throughput Screening of Alpha-Synuclein. ASN Neuro 2023, 15, No. 17590914231184086. [DOI] [PMC free article] [PubMed] [Google Scholar]
(29).Nathan Kochen N; Murray M; Vunnam N; Liao EE; Chen L; Braun AR; Sachs JN Fluorescence lifetime-based FRET biosensors for monitoring N-terminal domain interactions of TDP-43 in living cells: A novel resource for ALS and FTD drug discovery. bioRxiv 2024. [DOI] [PMC free article] [PubMed] [Google Scholar]
(30).Dall NR; Mendonça CATF; Torres Vera HL; Marqusee S The importance of the location of the N-terminus in successful protein folding in vivo and in vitro. Proc. Natl. Acad. Sci. U. S. A 2024, 121 (34), No. e2321999121. [DOI] [PMC free article] [PubMed] [Google Scholar]
(31).Raran-Kurussi S; Keefe K; Waugh DS Positional effects of fusion partners on the yield and solubility of MBP fusion proteins. Protein Expr. Purif 2015, 110, 159–164. [DOI] [PMC free article] [PubMed] [Google Scholar]
(32).Ugrinov KG; Clark PL Cotranslational Folding Increases GFP Folding Yield. Biophys. J 2010, 98 (7), 1312–1320. [DOI] [PMC free article] [PubMed] [Google Scholar]
(33).Sandoval SO; Cappuccio G; Kruth K; Osenberg S; Khalil SM; Méndez-Albelo NM; Padmanabhan K; Wang D; Niciu MJ; Bhattacharyya A; et al. Rigor and reproducibility in human brain organoid research: Where we are and where we need to go. Stem Cell Rep 2024, 19 (6), 796–816. [DOI] [PMC free article] [PubMed] [Google Scholar]
(34).Ponsioen B; Post JB; Buissant Des Amorie JR; Laskaris D; Van Ineveld RL; Kersten S; Bertotti A; Sassi F; Sipieter F; Cappe B; et al. Quantifying single-cell ERK dynamics in colorectal cancer organoids reveals EGFR as an amplifier of oncogenic MAPK pathway signalling. Nat. Cell Biol 2021, 23 (4), 377–390. [DOI] [PMC free article] [PubMed] [Google Scholar]
(35).Weiser-Bitoun I; Mazgaoker S; Eid R; Brosh I; Yaniv Y Spatiotemporal profiling of protein kinase A activity in spontaneously beating hiPSC-derived cardiac organoids. iScience 2025, 28 (3), No. 112005. [DOI] [PMC free article] [PubMed] [Google Scholar]
(36).Yousafzai MS; Hammer JA Using Biosensors to Study Organoids, Spheroids and Organs-on-a-Chip: A Mechanobiology Perspective. Biosensors 2023, 13 (10), No. 905. [DOI] [PMC free article] [PubMed] [Google Scholar]
(37).Barroso M; Monaghan MG; Niesner R; Dmitriev RI Probing organoid metabolism using fluorescence lifetime imaging microscopy (FLIM): The next frontier of drug discovery and disease understanding. Adv. Drug Deliv. Rev 2023, 201, No. 115081. [DOI] [PMC free article] [PubMed] [Google Scholar]
(38).Liao EE; Yang M; Nathan Kochen N; Vunnam N; Braun AR; Ferguson DM; Sachs JN Proteasomal Stimulation by MK886 and Its Derivatives Can Rescue Tau-Induced Neurite Pathology. Mol. Neurobiol 2023, 6133. [DOI] [PMC free article] [PubMed] [Google Scholar]
(39).Lacin ME; Yildirim M Applications of multiphoton microscopy in imaging cerebral and retinal organoids. Front. Neurosci 2024, 18, No. 1360482. [DOI] [PMC free article] [PubMed] [Google Scholar]
(40).Suzuki Y; Fujii S; Watanabe S; Hayashi S Scattering reduced imaging of spheroids via refractive index estimation and shift-variant deconvolution. Biomed. Opt. Express 2025, 16 (8), 3437–3453. [DOI] [PMC free article] [PubMed] [Google Scholar]
(41).Mestre-Torà B; Duocastella M Enhanced light focusing inside scattering media with shaped ultrasound. Sci. Rep 2023, 13 (1), 11511. [DOI] [PMC free article] [PubMed] [Google Scholar]
(42).Lewis AK; James ZM; McCaffrey JE; Braun AR; Karim CB; Thomas DD; Sachs JN Open and closed conformations of the isolated transmembrane domain of death receptor 5 support a new model of activation. Biophys. J 2014, 106 (6), L21–L24. [DOI] [PMC free article] [PubMed] [Google Scholar]
(43).Gonzalez Caldito N Role of tumor necrosis factor-alpha in the central nervous system: a focus on autoimmune disorders. Front. Immunol 2023, 14, No. 1213448. [DOI] [PMC free article] [PubMed] [Google Scholar]
(44).Dong Y; Fischer R; Naude PJ; Maier O; Nyakas C; Duffey M; Van der Zee EA; Dekens D; Douwenga W; Herrmann A Essential protective role of tumor necrosis factor receptor 2 in neurodegeneration. Proc. Natl. Acad. Sci. U. S. A 2016, 113 (43), 12304–12309. [DOI] [PMC free article] [PubMed] [Google Scholar]
(45).Atretkhany KN; Gogoleva VS; Drutskaya MS; Nedospasov SA Distinct modes of TNF signaling through its two receptors in health and disease. J. Leukoc. Biol 2020, 107 (6), 893–905. [DOI] [PubMed] [Google Scholar]
(46).Atretkhany KN; Mufazalov IA; Dunst J; Kuchmiy A; Gogoleva VS; Andruszewski D; Drutskaya MS; Faustman DL; Schwabenland M; Prinz M; et al. Intrinsic TNFR2 signaling in T regulatory cells provides protection in CNS autoimmunity. Proc. Natl. Acad. Sci. U. S. A 2018, 115 (51), 13051–13056. [DOI] [PMC free article] [PubMed] [Google Scholar]
(47).Papazian I; Tsoukala E; Boutou A; Karamita M; Kambas K; Iliopoulou L; Fischer R; Kontermann RE; Denis MC; Kollias G Fundamentally different roles of neuronal TNF receptors in CNS pathology: TNFR1 and IKKβ promote microglial responses and tissue injury in demyelination while TNFR2 protects against excitotoxicity in mice. J. Neuroinflamm 2021, 18 (1), No. 222. [DOI] [PMC free article] [PubMed] [Google Scholar]
(48).Ortí-Casañ N; Boerema AS; Köpke K; Ebskamp A; Keijser J; Zhang Y; Chen T; Dolga AM; Broersen K; Fischer R; et al. The TNFR1 antagonist Atrosimab reduces neuronal loss, glial activation and memory deficits in an acute mouse model of neurodegeneration. Sci. Rep 2023, 13 (1), 10622. [DOI] [PMC free article] [PubMed] [Google Scholar]
(49).Fischer R; Kontermann RE; Pfizenmaier K Selective Targeting of TNF Receptors as a Novel Therapeutic Approach. Front. Cell Dev. Biol 2020, 8, 401. [DOI] [PMC free article] [PubMed] [Google Scholar]
(50).Vunnam N; Been M; Huber E; Paulson C; Szymonski S; Hackel BJ; Sachs JN Discovery of a Non-competitive TNFR1 Antagonist Affibody with Picomolar Monovalent Potency That Does Not Affect TNFR2 Function. Mol. Pharm 2023, 20 (4), 1884–1897. [DOI] [PMC free article] [PubMed] [Google Scholar]
(51).Uversky VN Alpha-synuclein misfolding and neurodegenerative diseases. Curr. Protein Pept. Sci 2008, 9 (5), 507–540. [DOI] [PubMed] [Google Scholar]
(52).Uversky VN; Eliezer D Biophysics of Parkinson’s disease: structure and aggregation of alpha-synuclein. Curr. Protein Pept. Sci 2009, 10 (5), 483–499. [DOI] [PMC free article] [PubMed] [Google Scholar]
(53).Luk KC; Kehm VM; Zhang B; O’Brien P; Trojanowski JQ; Lee VM Intracerebral inoculation of pathological alpha-synuclein initiates a rapidly progressive neurodegenerative alpha-synucleinopathy in mice. J. Exp. Med 2012, 209, 975–986. [DOI] [PMC free article] [PubMed] [Google Scholar]
(54).Lorenzen N; Nielsen SB; Buell AK; Kaspersen JD; Arosio P; Vad BS; Paslawski W; Christiansen G; Valnickova-Hansen Z; Andreasen M; et al. The role of stable α-synuclein oligomers in the molecular events underlying amyloid formation. J. Am. Chem. Soc 2014, 136 (10), 3859–3868. [DOI] [PubMed] [Google Scholar]
(55).Power JH; Barnes OL; Chegini F Lewy bodies and the mechanisms of neuronal cell death in parkinson’s disease and dementia with lewy bodies. Brain Pathol 2015, 27, 3–12. [DOI] [PMC free article] [PubMed] [Google Scholar]
(56).Rockenstein E; Nuber S; Overk CR; Ubhi K; Mante M; Patrick C; Adame A; Trejo-Morales M; Gerez J; Picotti P; et al. Accumulation of oligomer-prone α-synuclein exacerbates synaptic and neuronal degeneration in vivo. Brain 2014, 137 (5), 1496–1513. [DOI] [PMC free article] [PubMed] [Google Scholar] [Retracted]
(57).Kulkarni AS; Burns MR; Brundin P; Wesson DW Linking α-synuclein-induced synaptopathy and neural network dysfunction in early Parkinson’s disease. Brain Commun 2022, 4 (4), No. fcac165. [DOI] [PMC free article] [PubMed] [Google Scholar]
(58).Nathan Kochen N; Murray M; Zafari S; Vunnam N; Liao EE; Chen L; Braun AR; Sachs JN Fluorescence Lifetime-Based FRET Biosensors for Monitoring N Terminal Domain-Dependent Interactions of TDP-43 in Living Cells: A Novel Approach for ALS and FTD Drug Discovery. ACS Chem. Neurosci 2025, 16 (13), 2450–2462. [DOI] [PMC free article] [PubMed] [Google Scholar]
(59).Ratnapriya S; Braun AR; Cervera Benet H; Carlson D; Ding S; Paulson CN; Mishra N; Sachs JN; Aldrich CC; Finzi A; et al. Broad Tricyclic Ring Inhibitors Block SARS-CoV-2 Spike Function Required for Viral Entry. ACS Infect. Dis 2022, 8 (10), 2045–2058. [DOI] [PMC free article] [PubMed] [Google Scholar]
(60).Jin M; Wang S; Gao X; Zou Z; Hirotsune S; Sun L Pathological and physiological functional cross-talks of α-synuclein and tau in the central nervous system. Neural Regen. Res 2024, 19 (4), 855–862. [DOI] [PMC free article] [PubMed] [Google Scholar]
(61).Xiang J; Tang J; Kang F; Ye J; Cui Y; Zhang Z; Wang J; Wu S; Ye K Gut-induced alpha-Synuclein and Tau propagation initiate Parkinson’s and Alzheimer’s disease co-pathology and behavior impairments. Neuron 2024, 112, 3585. [DOI] [PubMed] [Google Scholar]
(62).Bassil F; Meymand ES; Brown HJ; Xu H; Cox TO; Pattabhiraman S; Maghames CM; Wu Q; Zhang B; Trojanowski JQ; et al. α-Synuclein modulates tau spreading in mouse brains. J. Exp. Med 2021, 218 (1), No. e20192193. [DOI] [PMC free article] [PubMed] [Google Scholar]
(63).Zhang X; Gao F; Wang D; Li C; Fu Y; He W; Zhang J Tau Pathology in Parkinson’s Disease. Front. Neurol 2018, 9, No. 809. [DOI] [PMC free article] [PubMed] [Google Scholar]
(64).Padilla-Godínez FJ; Vázquez-García ER; Trujillo-Villagrán MI; Soto-Rojas LO; Palomero-Rivero M; Hernández-González O; Pérez-Eugenio F; Collazo-Navarrete O; Arias-Carrión O; Guerra-Crespo M α-synuclein and tau: interactions, cross-seeding, and the redefinition of synucleinopathies as complex proteinopathies. Front. Neurosci 2025, 19, No. 1570553. [DOI] [PMC free article] [PubMed] [Google Scholar]
(65).Ge W-Y; Deng X; Shi W-P; Lin W-J; Chen L-L; Liang H; Wang X-T; Zhang T-D; Zhao F-Z; Guo W-H; et al. Amyloid Protein Cross-Seeding Provides a New Perspective on Multiple Diseases In Vivo. Biomacromolecules 2022, 24 (1), 1. [DOI] [PubMed] [Google Scholar]
(66).Latimer CS; Liachko NF Tau and TDP-43 synergy: a novel therapeutic target for sporadic late-onset Alzheimer’s disease. GeroScience 2021, (4), 1627. [DOI] [PMC free article] [PubMed] [Google Scholar]
(67).Koga S; Zhou X; Murakami A; Fernandez De Castro C; Baker MC; Rademakers R; Dickson DW Concurrent tau pathologies in frontotemporal lobar degeneration with TDP-43 pathology. Neuropathol. Appl. Neurobiol 2022, 48 (2), No. e12778. [DOI] [PMC free article] [PubMed] [Google Scholar]
(68).Hicks D TDP-43 and amyloid precursor protein processing: implications for Alzheimer’s disease. Neural Regen. Res 2021, 16 (7), No. 1402. [DOI] [PMC free article] [PubMed] [Google Scholar]
(69).Jeon S; Jeon Y; Lim J-Y; Kim Y; Cha B; Kim W Emerging regulatory mechanisms and functions of biomolecular condensates: implications for therapeutic targets. Signal Transduct. Target. Ther 2025, 10 (1), No. 4. [DOI] [PMC free article] [PubMed] [Google Scholar]
(70).Gruijs Da Silva LA; Simonetti F; Hutten S; Riemenschneider H; Sternburg EL; Pietrek LM; Gebel J; Dötsch V; Edbauer D; Hummer G; et al. Disease-linked TDP-43 hyperphosphorylation suppresses TDP-43 condensation and aggregation. EMBO J 2022, 41, No. EMBJ2021108443. [DOI] [PMC free article] [PubMed] [Google Scholar]
(71).Zambusi A; Novoselc KT; Hutten S; Kalpazidou S; Koupourtidou C; Schieweck R; Aschenbroich S; Silva L; Yazgili AS; Van Bebber F; et al. TDP-43 condensates and lipid droplets regulate the reactivity of microglia and regeneration after traumatic brain injury. Nat. Neurosci 2022, 25 (12), 1608–1625. [DOI] [PubMed] [Google Scholar]
(72).Sternburg EL; Gruijs Da Silva LA; Dormann D Post-translational modifications on RNA-binding proteins: accelerators, brakes, or passengers in neurodegeneration? Trends Biochem. Sci 2022, 47, 6–22. [DOI] [PubMed] [Google Scholar]
(73).Ray S; Buell AK Emerging experimental methods to study the thermodynamics of biomolecular condensate formation. J. Chem. Phys 2024, 160 (9), No. 091001. [DOI] [PubMed] [Google Scholar]
(74).Gotor N; Alexandros A; Giulia C; Martin V; de Groot N; Gaetano T RNA-Binding and Prion Domains: The Yin and Yang of Phase Separation. bioRxiv 2020. [DOI] [PMC free article] [PubMed] [Google Scholar]
(75).Van Treeck B; Parker R Principles of Stress Granules Revealed by Imaging Approaches. Cold Spring Harb. Perspect. Biol 2019, 11 (2), No. a033068. [DOI] [PMC free article] [PubMed] [Google Scholar]
(76).Deczkowska A; Weiner A; Amit I The Physiology, Pathology, and Potential Therapeutic Applications of the TREM2 Signaling Pathway. Cell 2020, 181 (6), 1207–1217. [DOI] [PubMed] [Google Scholar]
(77).Delekate A; Füchtemeier M; Schumacher T; Ulbrich C; Foddis M; Petzold GC Metabotropic P2Y1 receptor signalling mediates astrocytic hyperactivity in vivo in an Alzheimer’s disease mouse model. Nat. Commun 2014, 5 (1), No. 5422. [DOI] [PubMed] [Google Scholar]
(78).Wang Z; Wang J; Zhao Y; Jin J; Si W; Chen L; Zhang M; Zhou Y; Mao S; Zheng C; et al. 3D live imaging and phenotyping of CAR-T cell mediated-cytotoxicity using high-throughput Bessel oblique plane microscopy. Nat. Commun 2024, 15 (1), 6677. [DOI] [PMC free article] [PubMed] [Google Scholar]
(79).Liu L; Yoon CW; Yuan Z; Guo T; Qu Y; He P; Yu X; Zhu Z; Limsakul P; Wang Y Cellular and molecular imaging of CAR-T cell-based immunotherapy. Adv. Drug Deliv. Rev 2023, 203, No. 115135. [DOI] [PMC free article] [PubMed] [Google Scholar]
(80).Battison AS; Merrill JR; Borniger JC; Lyons SK The regulation of reporter transgene expression for diverse biological imaging applications. NPJ Imaging 2025, 3 (1), 9. [DOI] [PMC free article] [PubMed] [Google Scholar]
(81).Kallunki K; Barisic M; Jäättelä M; Liu B How to Choose the Right Inducible Gene Expression System for Mammalian Studies? Cells 2019, 8 (8), 796. [DOI] [PMC free article] [PubMed] [Google Scholar]
(82).Menche C; Farin HF Strategies for genetic manipulation of adult stem cell-derived organoids. Exp. Mol. Med 2021, 53 (10), 1483–1494. [DOI] [PMC free article] [PubMed] [Google Scholar]
(83).Raju G; Mazumder N Digging Deeper through Biological Specimens Using Adaptive Optics-Based Optical Microscopy. Photonics 2023, 10 (2), No. 178. [Google Scholar]
(84).Rakotoson I; Delhomme B; Djian P; Deeg A; Brunstein M; Seebacher C; Uhl R; Ricard C; Oheim M Fast 3-D Imaging of Brain Organoids With a New Single-Objective Planar-Illumination Two-Photon Microscope. Front. Neuroanat 2019, 13. [DOI] [PMC free article] [PubMed] [Google Scholar]
(85).Huang Q; Garrett A; Bose S; Blocker S; Rios AC; Clevers H; Shen X The frontier of live tissue imaging across space and time. Cell Stem Cell 2021, 28 (4), 603–622. [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Braun et al ACS Sensors 2026 Supplement

NIHMS2168537-supplement-Braun_et_al_ACS_Sensors_2026_Supplement.pdf^{(9.9MB, pdf)}

Data Availability Statement

[R1] (1).Reissaus CA; Day KH; Mirmira RG; Dunn KW; Pavalko FM; Day RN PIE-FLIM Measurements of Two Different FRET-Based Biosensor Activities in the Same Living Cells. Biophys. J 2020, 118 (8), 1820–1829. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R2] (2).Windgasse L; Grashoff C Multiplexed Molecular Tension Sensor Measurements Using PIE-FLIM. In Mechanobiology; Methods in Molecular Biology; Springer; US, 2023, pp 221–237. [DOI] [PubMed] [Google Scholar]

[R3] (3).Bertolin G; Sizaire F; Déméautis C; Chapuis C; Mérola F; Erard M; Tramier M Optimized FRET Pairs and Quantification Approaches To Detect the Activation of Aurora Kinase A at Mitosis. ACS Sens 2019, 4 (8), 2018–2027. [DOI] [PubMed] [Google Scholar]

[R4] (4).Roebroek T; Vandenberg W; Sipieter F; Hugelier S; Stove C; Zhang J; Dedecker P Simultaneous readout of multiple FRET pairs using photochromism. Nat. Commun 2021, 12 (1), 2005. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R5] (5).Chu J; Ejaz A; Lin KM; Joseph MR; Coraor AE; Drummond DA; Squires AH Single-molecule fluorescence multiplexing by multi-parameter spectroscopic detection of nanostructured FRET labels. Nat. Nanotechnol 2024, 19 (8), 1150–1157. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R6] (6).Ouyang W; Li Q; Niu Q; Qui M; Fu H; Du Y; Mo X A multiplexed time-resolved fluorescence resonance energy transfer ultrahigh-throughput screening assay for targeting the SMAD4-SMAD3-DNA complex. J. Mol. Cell Biol 2024, 15 (11), No. mjad068. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R7] (7).Cheppali SK; Li C; Xing W; Sun R; Yang M; Xue Y; Lu S-Y; Yao J; Sun S; Chen C; et al. Single-molecule two- and three-colour FRET studies reveal a transition state in SNARE disassembly by NSF. Nat. Commun 2025, 16 (1), 250. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R8] (8).Mathur D; Thakur M; Díaz SA; Susumu K; Stewart MH; Oh E; Walper SA; Medintz IL Hybrid Nucleic Acid-Quantum Dot Assemblies as Multiplexed Reporter Platforms for Cell-Free Transcription Translation-Based Biosensors. ACS Synth. Biol 2022, 11 (12), 4089–4102. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R9] (9).Liu J; Liu Z; Mi F; Yao Z; Fang X; Wang Y; Zhao Z; Wu C Fluorescence Lifetime Multiplex Imaging in Expansion Microscopy with Tunable Donor–Acceptor Polymer Dots. Chem. Biomed. Imaging 2023, 1 (6), 550–557. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R10] (10).Murakoshi H; Shibata ACE ShadowY: a dark yellow fluorescent protein for FLIM-based FRET measurement. Sci. Rep 2017, 7 (1), 6791. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R11] (11).Murakoshi H; Horiuchi H; Kosugi T; Onda M; Sato A; Koga N; Nabekura J ShadowR: a novel chromoprotein with reduced non-specific binding and improved expression in living cells. Sci. Rep 2019, 9 (1), 12072. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R12] (12).Shaner NC; Lambert GG; Chammas A; Ni Y; Cranfill PJ; Baird MA; Sell BR; Allen JR; Day RN; Israelsson M; et al. A bright monomeric green fluorescent protein derived from Branchiostoma lanceolatum. Nat. Methods 2013, 10 (5), 407–409. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R13] (13).Gadella TWJ; Van Weeren L; Stouthamer J; Hink MA; Wolters AHG; Giepmans BNG; Aumonier S; Dupuy J; Royant A mScarlet3: a brilliant and fast-maturing red fluorescent protein. Nat. Methods 2023, 20 (4), 541–545. [DOI] [PubMed] [Google Scholar]

[R14] (14).Obashi K; Sochacki KA; Strub M-P; Taraska JW A conformational switch in clathrin light chain regulates lattice structure and endocytosis at the plasma membrane of mammalian cells. Nat. Commun 2023, 14 (1), 732. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R15] (15).Shibata ACE; Ueda HH; Eto K; Onda M; Sato A; Ohba T; Nabekura J; Murakoshi H Photoactivatable CaMKII induces synaptic plasticity in single synapses. Nat. Commun 2021, 12 (1), 751. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R16] (16).Li L-L; Klein FM; Li Greci L; Popinigis A; Freudenberg F; Courtney MJ Resonance energy transfer sensitises and monitors in situ switching of LOV2-based optogenetic actuators. Nat. Commun 2020, 11 (1), 5107. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R17] (17).Demeautis C; Sipieter F; Roul J; Chapuis C; Padilla-Parra S; Riquet FB; Tramier M Multiplexing PKA and ERK1&2 kinases FRET biosensors in living cells using single excitation wavelength dual colour FLIM. Sci. Rep 2017, 7 (1), No. 41026. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R18] (18).Young MC; Vunnam N; Rebbeck RT; Yuen SL; Thomas DD; Sachs JN Indirubin Inhibits TRAIL-Induced Activation of Death Receptor 5 in Jurkat Cells. Nat. Prod. Commun 2023, 18 (1), No. 1934578X221144580. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R19] (19).Vunnam N; Yang M; Lo CH; Paulson C; Fiers WD; Huber E; Been M; Ferguson DM; Sachs JN Zafirlukast Is a Promising Scaffold for Selectively Inhibiting TNFR1 Signaling. ACS Bio Med Chem. Au 2023, 3 (3), 270–282. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R20] (20).Vunnam N; Young MC; Liao EE; Lo CH; Huber E; Been M; Thomas DD; Sachs JN Nimesulide, a COX-2 inhibitor, sensitizes pancreatic cancer cells to TRAIL-induced apoptosis by promoting DR5 clustering †. Cancer Biol. Ther 2023, 24 (1), No. 2176692. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R21] (21).Lo CH; Schaaf TM; Thomas DD; Sachs JN Fluorescence-Based TNFR1 Biosensor for Monitoring Receptor Structural and Conformational Dynamics and Discovery of Small Molecule Modulators. In The TNF Superfamily; Methods in Molecular Biology; Springer; US; 2021; pp 121–137. [DOI] [PubMed] [Google Scholar]

[R22] (22).Lo CH; Huber EC; Sachs JN Conformational states of TNFR1 as a molecular switch for receptor function. Protein Sci 2020, 29, 1401. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R23] (23).Lo CH; Schaaf TM; Grant BD; Lim CK; Bawaskar P; Aldrich CC; Thomas DD; Sachs JN Noncompetitive inhibitors of TNFR1 probe conformational activation states. Sci. Signal 2019, 12 (592), No. eaav5637. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R24] (24).Lo CH; Vunnam N; Lewis AK; Chiu TL; Brummel BE; Schaaf TM; Grant BD; Bawaskar P; Thomas DD; Sachs JN An Innovative High-Throughput Screening Approach for Discovery of Small Molecules That Inhibit TNF Receptors. SLAS Discov 2017, 22 (8), 950–961. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R25] (25).Lo CH; Lim CK; Ding Z; Wickramasinghe SP; Braun AR; Ashe KH; Rhoades E; Thomas DD; Sachs JN Targeting the ensemble of heterogeneous tau oligomers in cells: A novel small molecule screening platform for tauopathies. Alzheimers Dement 2019, 15 (11), 1489–1502. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R26] (26).Lo CH; Pandey NK; Lim CK; Ding Z; Tao M; Thomas DD; Langen R; Sachs JN Discovery of Small Molecule Inhibitors of Huntingtin Exon 1 Aggregation by FRET-Based High-Throughput Screening in Living Cells. ACS Chem. Neurosci 2020, 11 (15), 2286–2295. [DOI] [PubMed] [Google Scholar]

[R27] (27).Braun AR; Liao EE; Horvath M; Kalra P; Acosta K; Young MC; Kochen NN; Lo CH; Brown R; Evans MD Potent inhibitors of toxic alpha-synuclein identified via cellular time-resolved FRET biosensors. NPJ Parkinsons Dis 2021, 7 (1), No. 52. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R28] (28).Braun AR; Kochen NN; Yuen SL; Liao EE; Cornea RL; Thomas DD; Sachs JN Advancements in a FRET Biosensor for Live-Cell Fluorescence-Lifetime High-Throughput Screening of Alpha-Synuclein. ASN Neuro 2023, 15, No. 17590914231184086. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R29] (29).Nathan Kochen N; Murray M; Vunnam N; Liao EE; Chen L; Braun AR; Sachs JN Fluorescence lifetime-based FRET biosensors for monitoring N-terminal domain interactions of TDP-43 in living cells: A novel resource for ALS and FTD drug discovery. bioRxiv 2024. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R30] (30).Dall NR; Mendonça CATF; Torres Vera HL; Marqusee S The importance of the location of the N-terminus in successful protein folding in vivo and in vitro. Proc. Natl. Acad. Sci. U. S. A 2024, 121 (34), No. e2321999121. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R31] (31).Raran-Kurussi S; Keefe K; Waugh DS Positional effects of fusion partners on the yield and solubility of MBP fusion proteins. Protein Expr. Purif 2015, 110, 159–164. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R32] (32).Ugrinov KG; Clark PL Cotranslational Folding Increases GFP Folding Yield. Biophys. J 2010, 98 (7), 1312–1320. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R33] (33).Sandoval SO; Cappuccio G; Kruth K; Osenberg S; Khalil SM; Méndez-Albelo NM; Padmanabhan K; Wang D; Niciu MJ; Bhattacharyya A; et al. Rigor and reproducibility in human brain organoid research: Where we are and where we need to go. Stem Cell Rep 2024, 19 (6), 796–816. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R34] (34).Ponsioen B; Post JB; Buissant Des Amorie JR; Laskaris D; Van Ineveld RL; Kersten S; Bertotti A; Sassi F; Sipieter F; Cappe B; et al. Quantifying single-cell ERK dynamics in colorectal cancer organoids reveals EGFR as an amplifier of oncogenic MAPK pathway signalling. Nat. Cell Biol 2021, 23 (4), 377–390. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R35] (35).Weiser-Bitoun I; Mazgaoker S; Eid R; Brosh I; Yaniv Y Spatiotemporal profiling of protein kinase A activity in spontaneously beating hiPSC-derived cardiac organoids. iScience 2025, 28 (3), No. 112005. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R36] (36).Yousafzai MS; Hammer JA Using Biosensors to Study Organoids, Spheroids and Organs-on-a-Chip: A Mechanobiology Perspective. Biosensors 2023, 13 (10), No. 905. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R37] (37).Barroso M; Monaghan MG; Niesner R; Dmitriev RI Probing organoid metabolism using fluorescence lifetime imaging microscopy (FLIM): The next frontier of drug discovery and disease understanding. Adv. Drug Deliv. Rev 2023, 201, No. 115081. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R38] (38).Liao EE; Yang M; Nathan Kochen N; Vunnam N; Braun AR; Ferguson DM; Sachs JN Proteasomal Stimulation by MK886 and Its Derivatives Can Rescue Tau-Induced Neurite Pathology. Mol. Neurobiol 2023, 6133. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R39] (39).Lacin ME; Yildirim M Applications of multiphoton microscopy in imaging cerebral and retinal organoids. Front. Neurosci 2024, 18, No. 1360482. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R40] (40).Suzuki Y; Fujii S; Watanabe S; Hayashi S Scattering reduced imaging of spheroids via refractive index estimation and shift-variant deconvolution. Biomed. Opt. Express 2025, 16 (8), 3437–3453. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R41] (41).Mestre-Torà B; Duocastella M Enhanced light focusing inside scattering media with shaped ultrasound. Sci. Rep 2023, 13 (1), 11511. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R42] (42).Lewis AK; James ZM; McCaffrey JE; Braun AR; Karim CB; Thomas DD; Sachs JN Open and closed conformations of the isolated transmembrane domain of death receptor 5 support a new model of activation. Biophys. J 2014, 106 (6), L21–L24. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R43] (43).Gonzalez Caldito N Role of tumor necrosis factor-alpha in the central nervous system: a focus on autoimmune disorders. Front. Immunol 2023, 14, No. 1213448. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R44] (44).Dong Y; Fischer R; Naude PJ; Maier O; Nyakas C; Duffey M; Van der Zee EA; Dekens D; Douwenga W; Herrmann A Essential protective role of tumor necrosis factor receptor 2 in neurodegeneration. Proc. Natl. Acad. Sci. U. S. A 2016, 113 (43), 12304–12309. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R45] (45).Atretkhany KN; Gogoleva VS; Drutskaya MS; Nedospasov SA Distinct modes of TNF signaling through its two receptors in health and disease. J. Leukoc. Biol 2020, 107 (6), 893–905. [DOI] [PubMed] [Google Scholar]

[R46] (46).Atretkhany KN; Mufazalov IA; Dunst J; Kuchmiy A; Gogoleva VS; Andruszewski D; Drutskaya MS; Faustman DL; Schwabenland M; Prinz M; et al. Intrinsic TNFR2 signaling in T regulatory cells provides protection in CNS autoimmunity. Proc. Natl. Acad. Sci. U. S. A 2018, 115 (51), 13051–13056. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R47] (47).Papazian I; Tsoukala E; Boutou A; Karamita M; Kambas K; Iliopoulou L; Fischer R; Kontermann RE; Denis MC; Kollias G Fundamentally different roles of neuronal TNF receptors in CNS pathology: TNFR1 and IKKβ promote microglial responses and tissue injury in demyelination while TNFR2 protects against excitotoxicity in mice. J. Neuroinflamm 2021, 18 (1), No. 222. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R48] (48).Ortí-Casañ N; Boerema AS; Köpke K; Ebskamp A; Keijser J; Zhang Y; Chen T; Dolga AM; Broersen K; Fischer R; et al. The TNFR1 antagonist Atrosimab reduces neuronal loss, glial activation and memory deficits in an acute mouse model of neurodegeneration. Sci. Rep 2023, 13 (1), 10622. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R49] (49).Fischer R; Kontermann RE; Pfizenmaier K Selective Targeting of TNF Receptors as a Novel Therapeutic Approach. Front. Cell Dev. Biol 2020, 8, 401. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R50] (50).Vunnam N; Been M; Huber E; Paulson C; Szymonski S; Hackel BJ; Sachs JN Discovery of a Non-competitive TNFR1 Antagonist Affibody with Picomolar Monovalent Potency That Does Not Affect TNFR2 Function. Mol. Pharm 2023, 20 (4), 1884–1897. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R51] (51).Uversky VN Alpha-synuclein misfolding and neurodegenerative diseases. Curr. Protein Pept. Sci 2008, 9 (5), 507–540. [DOI] [PubMed] [Google Scholar]

[R52] (52).Uversky VN; Eliezer D Biophysics of Parkinson’s disease: structure and aggregation of alpha-synuclein. Curr. Protein Pept. Sci 2009, 10 (5), 483–499. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R53] (53).Luk KC; Kehm VM; Zhang B; O’Brien P; Trojanowski JQ; Lee VM Intracerebral inoculation of pathological alpha-synuclein initiates a rapidly progressive neurodegenerative alpha-synucleinopathy in mice. J. Exp. Med 2012, 209, 975–986. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R54] (54).Lorenzen N; Nielsen SB; Buell AK; Kaspersen JD; Arosio P; Vad BS; Paslawski W; Christiansen G; Valnickova-Hansen Z; Andreasen M; et al. The role of stable α-synuclein oligomers in the molecular events underlying amyloid formation. J. Am. Chem. Soc 2014, 136 (10), 3859–3868. [DOI] [PubMed] [Google Scholar]

[R55] (55).Power JH; Barnes OL; Chegini F Lewy bodies and the mechanisms of neuronal cell death in parkinson’s disease and dementia with lewy bodies. Brain Pathol 2015, 27, 3–12. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R56] (56).Rockenstein E; Nuber S; Overk CR; Ubhi K; Mante M; Patrick C; Adame A; Trejo-Morales M; Gerez J; Picotti P; et al. Accumulation of oligomer-prone α-synuclein exacerbates synaptic and neuronal degeneration in vivo. Brain 2014, 137 (5), 1496–1513. [DOI] [PMC free article] [PubMed] [Google Scholar] [Retracted]

[R57] (57).Kulkarni AS; Burns MR; Brundin P; Wesson DW Linking α-synuclein-induced synaptopathy and neural network dysfunction in early Parkinson’s disease. Brain Commun 2022, 4 (4), No. fcac165. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R58] (58).Nathan Kochen N; Murray M; Zafari S; Vunnam N; Liao EE; Chen L; Braun AR; Sachs JN Fluorescence Lifetime-Based FRET Biosensors for Monitoring N Terminal Domain-Dependent Interactions of TDP-43 in Living Cells: A Novel Approach for ALS and FTD Drug Discovery. ACS Chem. Neurosci 2025, 16 (13), 2450–2462. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R59] (59).Ratnapriya S; Braun AR; Cervera Benet H; Carlson D; Ding S; Paulson CN; Mishra N; Sachs JN; Aldrich CC; Finzi A; et al. Broad Tricyclic Ring Inhibitors Block SARS-CoV-2 Spike Function Required for Viral Entry. ACS Infect. Dis 2022, 8 (10), 2045–2058. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R60] (60).Jin M; Wang S; Gao X; Zou Z; Hirotsune S; Sun L Pathological and physiological functional cross-talks of α-synuclein and tau in the central nervous system. Neural Regen. Res 2024, 19 (4), 855–862. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R61] (61).Xiang J; Tang J; Kang F; Ye J; Cui Y; Zhang Z; Wang J; Wu S; Ye K Gut-induced alpha-Synuclein and Tau propagation initiate Parkinson’s and Alzheimer’s disease co-pathology and behavior impairments. Neuron 2024, 112, 3585. [DOI] [PubMed] [Google Scholar]

[R62] (62).Bassil F; Meymand ES; Brown HJ; Xu H; Cox TO; Pattabhiraman S; Maghames CM; Wu Q; Zhang B; Trojanowski JQ; et al. α-Synuclein modulates tau spreading in mouse brains. J. Exp. Med 2021, 218 (1), No. e20192193. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R63] (63).Zhang X; Gao F; Wang D; Li C; Fu Y; He W; Zhang J Tau Pathology in Parkinson’s Disease. Front. Neurol 2018, 9, No. 809. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R64] (64).Padilla-Godínez FJ; Vázquez-García ER; Trujillo-Villagrán MI; Soto-Rojas LO; Palomero-Rivero M; Hernández-González O; Pérez-Eugenio F; Collazo-Navarrete O; Arias-Carrión O; Guerra-Crespo M α-synuclein and tau: interactions, cross-seeding, and the redefinition of synucleinopathies as complex proteinopathies. Front. Neurosci 2025, 19, No. 1570553. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R65] (65).Ge W-Y; Deng X; Shi W-P; Lin W-J; Chen L-L; Liang H; Wang X-T; Zhang T-D; Zhao F-Z; Guo W-H; et al. Amyloid Protein Cross-Seeding Provides a New Perspective on Multiple Diseases In Vivo. Biomacromolecules 2022, 24 (1), 1. [DOI] [PubMed] [Google Scholar]

[R66] (66).Latimer CS; Liachko NF Tau and TDP-43 synergy: a novel therapeutic target for sporadic late-onset Alzheimer’s disease. GeroScience 2021, (4), 1627. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R67] (67).Koga S; Zhou X; Murakami A; Fernandez De Castro C; Baker MC; Rademakers R; Dickson DW Concurrent tau pathologies in frontotemporal lobar degeneration with TDP-43 pathology. Neuropathol. Appl. Neurobiol 2022, 48 (2), No. e12778. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R68] (68).Hicks D TDP-43 and amyloid precursor protein processing: implications for Alzheimer’s disease. Neural Regen. Res 2021, 16 (7), No. 1402. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R69] (69).Jeon S; Jeon Y; Lim J-Y; Kim Y; Cha B; Kim W Emerging regulatory mechanisms and functions of biomolecular condensates: implications for therapeutic targets. Signal Transduct. Target. Ther 2025, 10 (1), No. 4. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R70] (70).Gruijs Da Silva LA; Simonetti F; Hutten S; Riemenschneider H; Sternburg EL; Pietrek LM; Gebel J; Dötsch V; Edbauer D; Hummer G; et al. Disease-linked TDP-43 hyperphosphorylation suppresses TDP-43 condensation and aggregation. EMBO J 2022, 41, No. EMBJ2021108443. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R71] (71).Zambusi A; Novoselc KT; Hutten S; Kalpazidou S; Koupourtidou C; Schieweck R; Aschenbroich S; Silva L; Yazgili AS; Van Bebber F; et al. TDP-43 condensates and lipid droplets regulate the reactivity of microglia and regeneration after traumatic brain injury. Nat. Neurosci 2022, 25 (12), 1608–1625. [DOI] [PubMed] [Google Scholar]

[R72] (72).Sternburg EL; Gruijs Da Silva LA; Dormann D Post-translational modifications on RNA-binding proteins: accelerators, brakes, or passengers in neurodegeneration? Trends Biochem. Sci 2022, 47, 6–22. [DOI] [PubMed] [Google Scholar]

[R73] (73).Ray S; Buell AK Emerging experimental methods to study the thermodynamics of biomolecular condensate formation. J. Chem. Phys 2024, 160 (9), No. 091001. [DOI] [PubMed] [Google Scholar]

[R74] (74).Gotor N; Alexandros A; Giulia C; Martin V; de Groot N; Gaetano T RNA-Binding and Prion Domains: The Yin and Yang of Phase Separation. bioRxiv 2020. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R75] (75).Van Treeck B; Parker R Principles of Stress Granules Revealed by Imaging Approaches. Cold Spring Harb. Perspect. Biol 2019, 11 (2), No. a033068. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R76] (76).Deczkowska A; Weiner A; Amit I The Physiology, Pathology, and Potential Therapeutic Applications of the TREM2 Signaling Pathway. Cell 2020, 181 (6), 1207–1217. [DOI] [PubMed] [Google Scholar]

[R77] (77).Delekate A; Füchtemeier M; Schumacher T; Ulbrich C; Foddis M; Petzold GC Metabotropic P2Y1 receptor signalling mediates astrocytic hyperactivity in vivo in an Alzheimer’s disease mouse model. Nat. Commun 2014, 5 (1), No. 5422. [DOI] [PubMed] [Google Scholar]

[R78] (78).Wang Z; Wang J; Zhao Y; Jin J; Si W; Chen L; Zhang M; Zhou Y; Mao S; Zheng C; et al. 3D live imaging and phenotyping of CAR-T cell mediated-cytotoxicity using high-throughput Bessel oblique plane microscopy. Nat. Commun 2024, 15 (1), 6677. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R79] (79).Liu L; Yoon CW; Yuan Z; Guo T; Qu Y; He P; Yu X; Zhu Z; Limsakul P; Wang Y Cellular and molecular imaging of CAR-T cell-based immunotherapy. Adv. Drug Deliv. Rev 2023, 203, No. 115135. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R80] (80).Battison AS; Merrill JR; Borniger JC; Lyons SK The regulation of reporter transgene expression for diverse biological imaging applications. NPJ Imaging 2025, 3 (1), 9. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R81] (81).Kallunki K; Barisic M; Jäättelä M; Liu B How to Choose the Right Inducible Gene Expression System for Mammalian Studies? Cells 2019, 8 (8), 796. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R82] (82).Menche C; Farin HF Strategies for genetic manipulation of adult stem cell-derived organoids. Exp. Mol. Med 2021, 53 (10), 1483–1494. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R83] (83).Raju G; Mazumder N Digging Deeper through Biological Specimens Using Adaptive Optics-Based Optical Microscopy. Photonics 2023, 10 (2), No. 178. [Google Scholar]

[R84] (84).Rakotoson I; Delhomme B; Djian P; Deeg A; Brunstein M; Seebacher C; Uhl R; Ricard C; Oheim M Fast 3-D Imaging of Brain Organoids With a New Single-Objective Planar-Illumination Two-Photon Microscope. Front. Neuroanat 2019, 13. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R85] (85).Huang Q; Garrett A; Bose S; Blocker S; Rios AC; Clevers H; Shen X The frontier of live tissue imaging across space and time. Cell Stem Cell 2021, 28 (4), 603–622. [DOI] [PMC free article] [PubMed] [Google Scholar]

PERMALINK

Multiplexed Dark FRET Biosensors: An Accessible Live-Cell Platform for Target- and Cell-Specific Monitoring of Protein–Protein Interactions in 2D and 3D Model Systems

Anthony R Braun

Elly E Liao

Nagamani Vunnam

Sophia Zafari

Noah Nathan Kochen

Marguerite Murray

Jonathan N Sachs

Abstract

Graphical Abstract

RESULTS

Dark Acceptor-Based Biosensors Enable Orthogonal FRET in Live Cells

Figure 1.

MDF Biosensor Background FRET Signal

Figure 2.

MDF Application #1: Cell-Type-Specific FRET Readouts in 3D Neuro-Glial Spheroids

Figure 3.

MDF Application #2: Multiplexed FRET Differentiates TNFR1 and TNFR2 Conformation Changes in Live Cells

Figure 4.

Figure 5.

MDF Application #3: Dual aSyn Biosensors Monitor Aggregation and Misfolding

Figure 6.

Demonstration of Same-Cell Multiplexing of MDF Biosensors

Figure 7.

Control Linker System

TNFR1/TNFR2 Co-expression

DISCUSSION

Supplementary Material

ACKNOWLEDGMENTS

Footnotes

Contributor Information

Data Availability

REFERENCES

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

Similar articles

Cited by other articles

Links to NCBI Databases