Chunlai Chen

Single-molecule fluorescence techniques have revolutionized our ability to probe biomolecular dynamics by resolving molecular heterogeneity and transient states inaccessible to ensemble measurements. However, conventional analysis pipelines remain constrained by several factors that compromise both reproducibility and the detection of rare but biologically significant events. To overcome these challenges, we developed DASH, an automated framework that integrates bidirectional long short-term memory networks, conditional random fields, and hidden Markov models for unbiased analysis of single-molecule fluorescence trajectories. This unified platform performs three critical functions: (1) automated trajectory classification, (2) conformational state assignment, and (3) kinetic-scheme-free event sorting, all without requiring user-defined kinetic models. We demonstrate DASH’s broad applicability across diverse protein and nucleic acid systems. By eliminating manual intervention and any predefined kinetic schemes in the event-sorting stage, DASH provides a standardized, generalizable platform for extracting comprehensive mechanistic insights from single-molecule kinetics, particularly for systems exhibiting complex dynamic heterogeneity.

Biomolecular condensation is a key process for cells to maintain their normal physiological activities. However, the process of phase transition remains mysterious, especially for the initial moments of condensation. Herein, we investigated the first microsecond of peptide condensation through temperature jump infrared spectroscopy and molecular dynamics simulations. These techniques overcome the limited spatiotemporal resolution of traditional approaches, allowing us to capture the molecular events and kinetic information on the initial moment for phase transition. The results reveal that structural transitions and early assembly of intrinsically disordered proteins occur on ultrafast time scales. Unexpectedly, backbone hydrogen bonding emerges as the overlooked key mediator to stabilize the local structure for the ultrafast condensation of hydrophobic polypeptides compared to hydrophobicity. By locking local structures, hydrogen bonds help to form more stable interaction interfaces. These findings indicate that hydrogen bonding could enable hydrophobic disordered proteins to adopt preorganized conformations in response to environmental stimuli and serve as a key factor in mediating the assembly kinetics in complex cellular environments.

Frameshift mutations, responsible for >20% of Mendelian inherited diseases, pose substantial therapeutic challenges. Here we developed Template-Independent Genome Editing for Restoration (TIGER), a platform for the efficient and precise correction of frameshift mutations across various models. By identifying reproducible nucleotide-level factors that influence therapeutic efficacy across cells and tissues, we developed a scoring system for guide RNA (gRNA)–Cas9 outcomes. Approximately 75% of deletion and 50% of insertion mutations produced ≥30% in-frame products, sufficient for phenotypic restoration, with 38% and 65% achieving wild-type correction, respectively. To expand the applicability of TIGER across species and genome wide, we retrained the inDelphi algorithm to predict therapeutic gRNAs for single-nucleotide frameshifts. In a mouse model of deafness, delivery of SpCas9 and optimal gRNA via dual adeno-associated virus restored hearing thresholds to wild-type levels, with ~90% of in-frame edits being wild type. TIGER provides a robust and broadly applicable strategy for in vivo correction of inherited frameshift diseases.

Opioid agonists such as morphine and fentanyl exert analgesic effects by binding and activating the µ-opioid receptor (µOR), yet agonism of the µOR causes a slate of serious side effects. µOR-mediated addiction and respiratory depression are the major causes of the current opioid overdose crisis, largely driven by the explosion in illicit use of fentanyl, a potent opioid receptor full agonist. Given these serious side effects (and high resulting societal cost), molecules that act as analgesics with distinct mechanisms of action are of great interest. Positive allosteric modulators (PAMs) of the µOR have the potential to avoid many off-target side effects of conventional opioid orthosteric agonists by enhancing the signaling properties of natural opioid peptide systems. We used a DNA-encoded chemical library screening approach to selectively discover active-state-specific µOR PAMs. Two out of 3 selected prospective PAMs displayed the anticipated enhancement in agonist activity. The most effective of these compounds enhanced the activity of all orthosteric opioid agonists tested, including the native opioid peptide met-enkephalin. Little is known about the underlying dynamic basis of allosteric modulation of Family A GPCRs like the µOR. To that end, we used single-molecule fluorescence resonance energy transfer experiments to detail the impact that our novel µOR PAM has on the dynamic activation behavior of a key region on the intracellular face of the receptor. Our results here provide both a new chemical scaffold that acts as a µOR PAM and detailed pharmacological and dynamic insights into its mechanism of action.

T-box riboswitches regulate gene expression by sensing tRNA aminoacylation status, but their dynamic mechanisms remain elusive. Here, we present single-molecule FRET studies of a full-length translational ileS T-box, showing that its decoding domain folds independently, and the initial tRNA anticodon binding promotes proper folding of the discriminator domain. Subsequent uncharged tRNA binding stabilizes the Antisequestrator (AntiS) conformation and GAG linker, resulting in translation initiation. Conversely, charged tRNA binds to a distinct T-box conformation, of which the linker is highly flexible and stem III is away from AntiS, rendering irreversible transition to the Sequestrator conformation if downstream sequences are transcribed, leading to translation inhibition. Collectively, both steps of tRNA binding are in a conformational selection manner, and the GAG linker, especially G96, acts as the main linchpin in tRNA 3΄-termini sensing. An elaborate model is proposed to understand how cotranscriptional folding, stepwise tRNA binding and dynamic conformational transitions coordinate T-box regulation.

Fluorescence microscopy represents a highly effective tool for examining the microscopic world. Modern microscopic techniques provide advanced temporal and spatial resolutions, while placing high demands on the photostability of fluorophores. Although it is well-known that the photostability of fluorophores is sensitive to their environment, the influence of nearby residues on the photostability of organic fluorophores attached to proteins is not yet fully understood. This study focuses on the influence of residues adjacent to the maleimide-derived fluorophore, specifically attached to cysteine residues in proteins. Under our experimental conditions, methionine, tryptophan, phenylalanine, valine, and leucine were all found to reduce the photostability, whereas glutamate was found to enhance the photostability. To put these experimental observations into perspective, we performed molecular dynamics simulations that offer insights into the mechanistic effects of adjacent residues.

Bacillus cereusalkylpurine DNA glycosylase AlkD plays a critical role in preserving genomic integrity by selectively excising cytotoxic positively charged lesions. Unlike most DNA glycosylases, AlkD employs a unique non-base-flipping mechanism involving distinct conformational states for lesion searching and excision. However, the interplay between its conformational dynamics and lesion recognition remains unclear. This study combines microsecond-scale molecular dynamics (MD) simulations, scanning fluorescence resonance energy transfer–fluorescence correlation spectroscopy (FRET-FCS) experiments, and cellular assays to investigate the lesion recognition mechanism mediated by the AlkD–dsDNA complex. We identified two critical residues, W109 and R148, that act as molecular probes to recognize DNA lesions and mismatches. These residues alter the equilibrium between the search complex (SC) and excision complex (EC), primarily distinguished by their dsDNA conformations. W109 and R148 exhibit enhanced recognition capabilities when the lesion is positively charged, explaining AlkD’s selectivity toward such lesions. Together, our study has identified the critical residues for recognizing the lesion and mismatch and regulating the enzyme’s conformational dynamics, providing valuable molecular insights into the target search and lesion recognition of AlkD.

Among the regulatory factor X (RFX) transcription factor family, RFX5 is uniquely reported to bind nucleosomes and induce nucleosome remodeling in vivo. Dysfunctions in RFX5 have been implicated in various diseases. Here, we present the cryogenic electron microscopy (cryo-EM) structure of the RFX5–nucleosome complex, revealing that the extended DNA binding domain (eDBD) of RFX5 binds to the nucleosome at superhelical location +2. RFX5 eDBD engages not only with nucleosomal DNA but also with histones through extensive interactions. Compared to the structure of a free nucleosome, RFX5 eDBD induces localized distortion of the bound DNA gyre and detachment of the adjacent DNA gyre in the RFX5–nucleosome complex. This structural alteration could potentially increase DNA accessibility and enhance transcriptional activity in vivo. Overall, our study provides novel insights into the mechanisms by which RFX5 eDBD interacts with and destabilizes nucleosomes.

Self-labeling protein tags are widely used in advanced bioimaging where dyes with high-photon budgets outperform their fluorescent protein counterparts. Further increasing the emitted photon numbers of dye-tag systems is actively pursued by both new fluorophore chemistry and protein engineering. By scrutinizing the protein microenvironment of fluorophores, here we propose that proximal thioether groups negatively affect the photostability of the dye-tag system. We attribute the disparity in photostability of rhodamine dyes on HaloTag, SNAP-tag, and TMP-tag3 to the influence of the inherent thioether linkage within the SNAP-tag and TMP-tag3. This photochemical pathway leads us to further devise tags with higher photostability. We first show that rhodamine dyes on TMP-tag3.1, which employs a proximity-induced SuFEx reaction instead of a thiol-acrylamide addition to replace the thioether adduct, achieve photon budgets comparable to those ligands on HaloTag. We further showcase that by mutating the methionine near the fluorophore pocket, HaloTag: M175L generally gives up to four times enhancement on photostability when labeled with red and far-red rhodamines. The enhancement of HaloTag modification is demonstrated with single-molecule fluorescence imaging, live-cell fluorescence imaging, and voltage imaging. During time-lapse imaging, gradual photooxidation of Met leads to a reduced photobleaching rate, mechanistically supporting the thioether pathway hypothesis. Our findings suggest that thioether editing on self-labeling tags is a general strategy to enhance the photostability of fluorophores for advanced time-lapse imaging techniques.

Single-molecule fluorescence assays enable high-resolution analysis of biomolecular dynamics, but traditional analysis pipelines are labor-intensive and rely on users' experience, limiting scalability and reproducibility. Recent deep learning models have automated aspects of data processing, yet many still require manual thresholds, complex architectures, or extensive labeled data. Therefore, we present DASH, a fully streamlined architecture for trace classification, state assignment, and automatic sorting that requires no user input. DASH demonstrates robust performance across users and experimental conditions both in equilibrium and non-equilibrium systems such as Cas12a-mediated DNA cleavage. This paper proposes a novel strategy for the automatic and detailed sorting of single-molecule fluorescence events. The dynamic cleavage process of Cas12a is used as an example to provide a comprehensive analysis. This approach is crucial for studying biokinetic structural changes at the single-molecule level.