Biology subjects

Wang, C.

Publications and source records attributed to Wang, C..

At least 19 recordsLinked to original sources

bioRxiv2026

Glutamatergic and Redox Abnormalities in Major Depressive Disorder: Links to Childhood Maltreatment and Perceived Stress

Background: Childhood sexual abuse (CSA) increases the risk for major depressive disorder (MDD), yet the underlying neurobiological mechanisms remain poorly understood. We examined (1) associations of medial prefrontal cortex (mPFC) glutamatergic metabolites and redox balance with childhood maltreatment and MDD; and (2) whether these neurochemical measures predicted future perceived stress. Methods: Using proton and phosphorus 4T magnetic resonance spectroscopy, we quantified glutamate, glutamine, their sum (Glx), and the NAD/NADH ratio within the same mPFC voxel in 71 women across four groups: healthy controls (HC; n=27), current MDD without CSA (n=14), current MDD with CSA (n=14), and remitted MDD with CSA (n=16). Results: Glutamate and Glx levels were lower in both CSA-exposed groups (n=30) compared with HC (n=27), whereas women with MDD without CSA did not differ significantly from HC. Among CSA-exposed women, greater maltreatment severity was associated with lower glutamine, and greater maltreatment multiplicity with lower glutamate and Glx, specifically in women with current MDD. The association between depressive symptom severity and glutamine differed by CSA history. A significant interaction between baseline NAD/NADH ratio and clinical group predicted perceived stress at 6-month follow-up, adjusting for baseline perceived stress. Specifically, lower baseline NAD/NADH ratio predicted greater subsequent perceived stress in MDD without CSA, but not in the other clinical groups. Conclusions: Our findings suggest that mPFC glutamatergic metabolites and redox balance show distinct patterns of association with CSA history, depression status, and subsequent perceived stress, highlighting neurochemical heterogeneity in MDD and molecular markers of risk.

neuroscience↗

bioRxiv2026

A portable C-terminal rheostat calibrates RecE/Redα exonuclease activity for enhanced bacterial recombineering

Recombineering enables precise genome engineering across diverse bacteria, yet efficient tools for large DNA integration remain underdeveloped for Streptomyces and other biotechnologically relevant bacteria. Here we identify a panel of highly active RecET recombinase pairs from actinobacteriophages that mediate efficient homologous recombination in Streptomyces. The lead candidate, Che9cRecET, supports genomic integration of kilobase-scale DNA with only 50bp homology arms and enables accurate insertion of 79kb biosynthetic gene clusters, far outperforming conventional genome editing approaches. Structural and biochemical analyses reveal Che9cRecE as a distinct C3-symmetric toroidal homotrimeric 5'-3' exonuclease, whose extended C-terminal loop acts as a tunable rheostat calibrating exonuclease activity to an optimal window for recombination. We further show this portable C-terminal loop enhances recombineering efficiency across phylogenetically diverse exonucleases including Escherichia coli Redalpha/RecE and Pseudomonas A. Our work uncovers a conserved regulatory mechanism of the RecE/Redalpha exonuclease family and delivers a generalizable strategy for advancing bacterial genome editing.

molecular biology↗

bioRxiv2026

Illuminating phage dark matter beyond the reach of structural alignments with PhageFlare

Many phage proteins remain functionally uncharacterized despite advances in structural-similarity-based annotation. We introduce PhageFlare, a deep learning framework for predicting phage protein functions lacking significant structural matches to annotated references. Across three structure-disjoint benchmarks, where no significant Foldseek match was detected between training and test proteins (E-value thresholds of 10-3, 10-4, and 10-2), PhageFlare achieved macro-averaged F1 scores of 0.871, 0.889, and 0.738 outperforming the strongest baseline (0.789, 0.814, and 0.732). Systematic evaluations demonstrated that protein language model selection critically influences performance, with ESM-C achieving stronger overall performance than ESM-2 and ProtBert. Embedding-guided case studies revealed local structural correspondences among proteins with limited global similarity. Applied to the efam and Metagenomic Gut Virus datasets, PhageFlare annotated 38.0% and 51.8% of proteins unresolved by Foldseek, respectively. Furthermore, PhageFlare identified lysogenic potential in 1,866 prophage-designated genomes misclassified as lytic by BACPHLIP. These results show that PhageFlare complements structural-similarity-based annotation and expands functional discovery across viral dark matter.

microbiology↗

bioRxiv2026

A brain-behavior generative model links individual brain dynamics to perceptual decisions

Perceptual decision speed varies across individuals and trials. Explaining this variability requires linking individual brain anatomy, neural dynamics, and behavior, yet whole-brain models typically reproduce brain signals without behavior, whereas behavioral models lack anatomical constraints. Here we introduce a brain-behavior generative model in which whole-brain dynamics on each participant's structural connectome generate both single-trial electroencephalography (EEG) and reaction times. Fitted to 17 participants performing motion discrimination, the models reproduced individual event-related potentials and reaction-time distributions. Joint fitting enabled the models to predict whether held-out trials were relatively fast or slow within each stimulus condition. In silico silencing further predicted where, how, and when each person's brain controls decision speed. Sensorimotor regions affected decision speed consistently across most participants, whereas the same parietal region had opposite effects in different participants. These opposite effects reflected whether the region acted mainly through network dynamics or the decision readout. Temporal analyses suggested that early activity largely set decision speed, whereas late EEG mainly tracked the unfolding decision. These results show that brain-behavior generative modeling can link individual brain dynamics to perceptual decisions and yield testable predictions of why decision speed varies across individuals and trials.

neuroscience↗

bioRxiv2026

Aberrant cortical reorganization and astrogliosis underlie memory deficit post-traumatic brain injury: a longitudinal multiscale multimodal study

Integrating high-dimensional neuroimaging data across spatial scales remains a fundamental bottleneck in quantitative neuroscience. Here, we apply emerging analytical techniques including functional connectome gradient mapping and 3D segmentation of whole-brain cellular resolution microscopy data in a mouse model of traumatic brain injury. At the macroscale, longitudinal functional MRI revealed a transition from frontal hyperconnectivity to hippocampal hypoconnectivity and unimodal-transmodal gradient contraction indicating network dedifferentiation. At the cellular scale, deep-learning based segmentation of whole-brain light-sheet fluorescence microscopy volumes quantified regional astrogliosis, neuronal hyperactivity, and single-axon loss undetected by standard diffusion MRI. Multiscale multimodal data integration not only identified quantitative biomarkers predictive of memory performance post-injury but also enabled validation of in vivo modalities against more sensitive ex vivo histology. This study demonstrates a framework for probing complex multi-network cognitive functions and neurological disorders of network dysfunction.

neuroscience↗

bioRxiv2026

NHE1 sustains leukemia-propagating capacity and mitochondrial fitness in T-cell acute lymphoblastic leukemia

Leukemia-propagating cells (LPCs) sustain T-cell acute lymphoblastic leukemia (T-ALL) and are thought to contribute to disease progression and relapse. However, the lack of reliable LPC markers has hindered efforts to identify their vulnerabilities. We screened 786 FDA-approved compounds using a zebrafish transplantation assay that directly measures leukemia-propagating activity. Amiloride markedly reduced functional LPC frequency (p < 0.0001) without significantly delaying leukemia onset at higher transplantation doses. Because amiloride inhibits the sodium-hydrogen exchanger NHE1, we investigated its role in T-ALL. NHE1 knockdown reduced self-renewal-associated colony formation by >70% human T-ALL cells, with only modest increases in apoptosis. Transcriptomic and proteomic analyses revealed extensive molecular remodeling, including reduced abundance of proteins involved in mitochondrial respiration and translation. Amiloride treatment and NHE1 knockdown impaired mitochondrial respiration and reduced mitochondrial content, while NHE1 knockdown also decreased mitochondrial membrane potential. Metabolomic profiling revealed alterations in TCA cycle intermediates and broader cellular metabolism. In mouse xenografts, NHE1 knockdown reduced leukemia involvement in the bone marrow and spleen despite similar overall leukemia progression and survival. Together, these findings implicate NHE1 as a previously unrecognized regulator of T-ALL leukemia-propagating activity, reveal unexpected contributions of this ion exchanger to mitochondrial fitness and leukemia involvement in hematopoietic tissues, and support further investigation of NHE1 as a potential therapeutic target in T-ALL.

cancer biology↗

bioRxiv2026

KRT7 Marks an Airway Glandular Ductal Stem Cell Population That Supports Multilineage Development and Regeneration

Airway submucosal glands (SMGs) play a central role in host defense through mucus secretion, airway hydration, and mucociliary clearance. However, the hierarchical organization of glandular progenitor populations remains poorly defined, largely because SMGs are sparse and restricted to the proximal trachea in murine models. Using the ferret, a model that closely recapitulates the gland-rich submucosal architecture of human cartilaginous airways, we identify KRT7+ glandular ductal epithelial cells as a progenitor population. In both adult ferret and healthy human airways, KRT7 expression is primarily restricted to the SMG duct epithelium, where it is co-expressed with KRT19 and CD166 but only partially overlaps with ALDH1A1. During early postnatal development, KRT7 expression becomes progressively restricted to glandular ductal epithelium and is ultimately excluded from mature acinar, myoepithelial cells, and KRT5+/KRT14+ basal lineages. Fate mapping in KRT7CreER;ROSAmTmG transgenic ferrets revealed that KRT7-lineage cells serve as multipotent progenitors during SMG morphogenesis, generating both serous and mucous epithelial cells. Following severe airway injury, KRT7-lineage cells survive within gland ducts and rapidly expand to repair the damaged surface epithelium by differentiating into ciliated and secretory cells but not KRT5+ basal cells. In organoid cultures, glandular KRT7-lineage cells acquired a KRT5+ basal-like phenotype and generated multilineage epithelia with functional CFTR-mediated transport. These findings identify the KRT7+ ductal niche as a critical progenitor reservoir for airway development, homeostasis, and regeneration, with implications for cystic fibrosis therapies.

cell biology↗

bioRxiv2026

LigRNA: High-accuracy prediction of RNA-ligand binding sites via dynamic chemical complementarity and language model encoding

RNA-binding small molecules represent a validated therapeutic modality, yet pinpointing their exact RNA binding sites remains critical for mechanistic understanding and drug optimization. Experimental methods, while precise, are costly and low-throughput, necessitating robust computational alternatives. Approaches based on static feature concatenation may overlook input-dependent relationships between RNA residues and ligand functional groups. Here we present LigRNA, a graph neural network framework that predicts RNA-ligand binding sites through joint cross-modal encoding of both molecules. LigRNA integrates structure-guided language model embeddings with physicochemical features-solvent-accessible surface area and secondary structure types, to construct comprehensive RNA representations. Ligands are encoded as attributed molecular graphs via graph attention networks, preserving atom-level chemical topology rather than compressing molecules into fixed fingerprints. A cross-attention mechanism then enables dynamic, ligand-dependent modulation of RNA nucleotide attention, capturing context-specific interaction patterns. Benchmarked on TE9 and TE18 datasets, LigRNA achieves F1 scores of 0.73 and 0.58, improving on GATRsite by 7.4% and 18.4%, respectively. Ablation studies identify the RNA residual encoder as the most consistent contributor across the two benchmarks. The source code is freely available at https://github.com/WillowWang0216/LigRNA.

bioinformatics↗

bioRxiv2026

A Compact Regulatory Logic Governs Fibroblast Cell State Plasticity in Fibrosis

Fibroblast activation drives organ failure across human diseases, yet its regulatory basis remains largely undefined. Here, we repressed 280 conserved disease-activated enhancers using CRISPR droplet sequencing (CROP-seq) in ~550,000 fibroblasts, constructing a regulome of 15 gene programs governing the profibrotic state. Systematic TF perturbation converged on MEOX1 as a central regulator, and fibroblast-specific Meox1 deletion in mice improved cardiac function, reduced fibrosis, and rewired profibrotic fibroblasts toward quiescence in heart failure. Effector gene perturbation in human cardiac fibroblasts revealed distinct regulators of contractility, migration, and inflammatory signaling, and these programs were conserved across profibrotic states in human lung, liver, and skin. Simultaneous repression of just six enhancers using a multiplexed dCas12a-KRAB system collapsed the profibrotic network, suppressed migration and contraction, and rewired fibroblast paracrine signaling to attenuate macrophage inflammation. These findings define the regulatory logic of fibroblast plasticity and establish a new framework for reprogramming profibrotic cell states in disease.

genomics↗

bioRxiv2026

Reformulating Protein Corona Prediction as Universal Protein-conditioned Learning

When nanoparticles enter biological environments, their surfaces are rapidly coated by proteins, forming a protein corona that governs their biological identity and downstream responses. Existing computational methods treat each protein as an independent prediction task, preventing the learning of shared adsorption principles and limiting generalization beyond experimentally characterized proteins. Here we introduce NanoPCT, a universal protein-conditioned learning framework that jointly models nanoparticle physicochemical properties and protein sequence representations. Using frozen ESM-2 embeddings and a joint interaction transformer, NanoPCT learns transferable representations of nano-bio interaction patterns across hundreds of proteins and maintains robust performance as protein diversity increases. The learned protein representation further enables zero-shot prediction for previously unseen proteins and biologically distinct protein groups through classifier reconstruction in embedding space. Beyond prediction, NanoPCT supports large-scale in silico inverse design and reveals consistent adsorption preferences between observed and unseen protein populations, suggesting that it captures transferable interaction patterns rather than protein-specific memorization. NanoPCT provides a unified framework for protein corona prediction, zero-shot generalization, and rational nanomaterial design.

bioinformatics↗

bioRxiv2026

Dog-human gene network colocalization links synaptic signalling and ubiquitination to compulsive disorders

Obsessive-compulsive disorder (OCD) is highly polygenic, and the largest genome-wide association study (GWAS), with 53,660 cases and 2,044,417 controls, identified only 30 loci, a small fraction of loci estimated to explain its heritability - too few to resolve biological pathways. Pet dogs develop a compulsive disorder (dogCD) similar to OCD. In a GWAS of dogCD with 2,584 dogs from the community science project Darwin's Ark, each dog locus explains at least 40-fold more phenotypic variance than each human OCD locus, giving power equivalent to the human GWAS with 80-fold fewer individuals. Combining the two GWAS identifies a 165-gene network undetectable in humans at current sample sizes. This network is enriched for genes expressed in neurons, particularly in the amygdala and cortex, and comprises four biological processes: excitatory-inhibitory synaptic transmission, axon guidance and neuron recognition, protein ubiquitination, and adenylyl cyclase-activating G-protein-coupled receptor signaling. Like most complex human traits, dogCD risk is likely driven by regulatory variation: fine-mapped dogCD SNPs are non-coding, and dogCD loci are enriched in candidate cis-regulatory elements (cCREs) in a new dog epigenomic atlas spanning eight brain regions. The cross-species network implicates an inherited risk architecture largely outside current OCD pharmacotherapy, and establishes pet dogs as a model for gene network discovery, particularly for conditions underpowered in human studies.

genetics↗

bioRxiv2026

Gradients of local circuit architecture shape stability and information integration across the cortical hierarchy

The mammalian neocortex is a complex structure with many interacting regions and cell types. Multiple efforts have recently generated large datasets from multiple cortical regions to determine generalizing principles of cortical organization and activity. One such generalizing principle is the concept of a cortical hierarchy - low-dimensional macroscopic gradients of biological properties across cortical areas and a hierarchy of timescales for information processing. Such gradients in properties along a cortical hierarchy may explain how different cortical regions serve different computational roles (i.e. sensory processing versus working memory). We set out to investigate such principles using biologically realistic simulations. Starting from our previously published model of the mouse primary visual cortex (VISp) with updated connectivity reflecting recent large-scale connectomics and synaptic physiology datasets, we generated multiple versions of the cortical circuit model with increased connectivity as measured along the cortical hierarchy. We then measure the resulting neural activity in response to a simulated single-cell photostimulation paradigm and thalamocortical inputs. We found that overall circuit stability increased across the cortical hierarchy, due to both increases in connection density and increases in the relative proportion of SST cells. The results of this study link cortical cell types to population-level activity, generating insight into the function of local circuits across cortex.

neuroscience↗

bioRxiv2026

Rational Design of 5' UTRs for Optimized mRNA Expression and Cost-Effective, Rapid Analysis of Capped mRNA

In vitro-transcribed (IVT) messenger RNA (mRNA) therapeutics require rigorous quality control of 5' capping efficiency and 3' poly(A) tail length, both of which constitute critical quality attributes (CQAs). Current analytical workflows for these CQAs rely on hybridization with nucleic acid probes and biotin-based affinity purification, which constrain throughput and increase per-assay cost. Here, we report a rationally designed 5' untranslated region (5' UTR) that sustains high translational efficiency while enabling probe-free, one-step purification for rapid quantification of capping efficiency and poly(A) tail length distribution. This approach exploits a strategically engineered 5' UTR incorporating a purine-only RNase A-resistant fragment terminating at a single pyrimidine cleavage site, together with a translation-enhancing element comprising an N6-methyladenosine (m6A) deposition motif and an 18S rRNA complementarity sequence. This dual-function design accommodates GA-rich sequence segments without compromising mRNA translational output. Compared with conventional probe- and biotin-dependent workflows, the present method substantially reduces cost and processing time and is compatible with simultaneous detection of segmented AmGn poly(A) tail variants. This integrated platform provides a simplified, probe-free and construct-universal for high-throughput in-process control (IPC) of mRNA therapeutics.

bioengineering↗

bioRxiv2026

Expression trajectories in the aging male mouse colon transcriptome

Characterizing temporal dynamics during aging is crucial to understanding the course of aging-related events. The transcriptome is extensively remodeled with age, but the temporal trajectories of these changes, particularly through midlife, remain poorly defined in many tissues. Here, we address this gap in the male mouse colon. Using a dataset of 83 RNA-Seq samples from five time points during adult mouse lifespan, we show that colon aging is characterized by multiple gene-expression trajectories unfolding in parallel, with a major shift occurring during a mid- to late-life transition marked by a collapse of the unfolded protein response (UPR). Moreover, we report widespread non-monotonic trajectories, including genes that peak or dip in midlife and would be missed by comparisons limited to young versus old ages. We further describe age-dependent dynamics of transposable element-containing transcripts and a nonlinear course of transcriptomic entropy across the lifespan. Importantly, we identify a small set of genes that track chronological age and use only three of them to construct a compact transcriptomic clock, which we validate using an independent RNA-seq dataset and qPCR data. Together, our results indicate that nonlinear patterns dominate the aging colon transcriptome and underscore the value of high temporal resolution for identifying key transitions during aging.

bioinformatics↗

bioRxiv2026

Autophagosome-tethering compounds selectively lower mutant ataxin-3 in preclinical models of spinocerebellar ataxia type 3

Spinocerebellar ataxia type 3 (SCA3) is most common subtype of autosomal dominant spinocerebellar ataxia worldwide and the most prevalent CAG expansion disorder in the east Asian population, but disease-modifying therapies remain unavailable. SCA3 is caused by the accumulation of polyglutamine- (polyQ-) expanded mutant ataxin-3 (mAtxn3), while the wild-type ataxin-3 (wtAtxn3) plays an important cellular role. Thus, allele-selective clearance of mAtxn3 without affecting wtAtxn3 is highly desired for SCA3 treatment. To achieve this goal, we tested previously reported compounds that have been shown to selectively degrade the Huntingtons disease causing mutant HTT protein by tethering the expanded polyQ to the autophagosome protein LC3. Here, we demonstrated that two of these compounds, AN2 and GW5074, selectively reduced both soluble and aggregated mAtxn3 with expanded polyQ (84Q), but not wtAtxn3, in both cellular and mouse models of SCA3. Mechanistically, both compounds lowered mAtxn3 by enhancing its autophagic degradation without obvious activation of global autophagy. At the molecular level, both compounds increased mAtxn3-LC3 interaction and colocalization to enhance the allele-selectively autophagic degradation of mAtxn3. Phenotypically, both compounds rescued cell viability and ATP content of SCA3 cellular models. In SCA3 patient pluripotent stem cells (iPSCs) derived cortical neurons, both compounds allele-selectively reduced mAtxn3 and partially rescued neurite shortening. Importantly, in a well-established SCA3 transgenic mouse model (MJD84.2), intracerebroventricular, intraperitoneal, and oral administration allele-selectively reduced mAtxn3 in multiple brain regions and rescued motor function deficits. Oral dosing achieved nanomolar cerebellar exposure and showed no overt liver, kidney, or glial toxicity over 28 days. Analyses of 1303 Chinese patients with SCA3 and ATXN3 constructs of different polyglutamine lengths further supported the compounds polyQ length-dependent activity with relative sparing of normal-length ataxin-3. Together, these findings provide preclinical proof of concept that utilizing orally available small molecule compounds to allele-selectively enhance mAtxn3 autophagic degradation for SCA3 treatment. One-sentence summarySmall-molecule autophagosome-tethering compounds selectively lower mutant ataxin-3 through an LC3- and autophagy-dependent mechanism and improve disease-related phenotypes in preclinical models of SCA3.

neuroscience↗

bioRxiv2026

Impaired astrocytic Cx43 syncytial network in lateral habenula affects synaptic connectivity and drives adolescent stress-induced depression

Adolescent depression is a major neuropsychiatric disorder induced by early life stress; the underlying cellular mechanisms instigating pathological circuit malformation remain unclear, and, consequently, effective therapeutic strategy is limited. Here, we analysed the contribution of astrocytes to early life stress-induced adolescent depression using a mouse model of parental separation. We identified a previously unrecognised regional specialisation of lateral habenula (LHb) astrocytes, characterised by compact cellular domains, abundant leaflets, and enhanced Cx43 gap junctional coupling. Parental separation selectively reduced astrocytic Cx43 expression and gap junctional communication in the LHb, which was accompanied by profound astrocytic atrophy and loss of leaflets. Single-cell sequencing further revealed that parental separation induces a broad reorganisation of LHb astrocyte transcriptional states, including metabolic, stress-response, and inflammatory programs; moreover, it specifically reduces astrocyte-neuron communication. Consistent with this, we found that structural remodelling of LHb astrocytes affected tripartite synapse geometry, resulting in impaired excitatory and inhibitory synaptic transmission, and neuronal Ca2+ hyperexcitability, all ultimately associated with depressive-like behaviours. Selective knockdown of astrocytic Cx43 in the LHb recapitulated these pathological changes and translated into depressive-like behaviours. Mechanistically, we found that impaired Cx43 gap junctional communication is associated with excessive astrocytic Ca2+ dynamics, resulting in Rac1-GTPase activation and decreased p-Ezrin levels. In vivo inhibition of LHb astrocytic Ca2+ signalling rescued astrocytic atrophy and depressive-like behaviours following parental separation. Together, our findings establish a Cx43-Ca2+-Rac1-p-Ezrin pathway that links gap junction malfunction to structural remodelling of astrocytes and disruption of neuron-astrocyte interactions in the developing LHb. Our study reveals astrocytic Ca2+ dysregulation as an active downstream effector of Cx43 dysfunction and identifies a regionally specialised astrocytic mechanism through which early-life stress disrupts synaptic transmission and neuronal function during adolescence, providing a potential cellular target for intervention in adolescent depression.

neuroscience↗

bioRxiv2026

The cleaved C-terminal domain of GmERS1-1 modulates cell cycle via GmACR1

Ethylene signaling orchestrates plant development and stress adaptation, yet how post-translational modifications of its receptors coordinate growth regulation remains unresolved. Here, we uncover a proteolytic processing mechanism of the soybean ethylene receptor GmERS1-1 that directly gates cell cycle progression. The GmERS1-1 mutants exhibit elevated yield under field conditions, whereas overexpression suppresses growth and hypersensitizes plants to ethylene. Ethylene triggers nuclear translocation of C-terminal domain (GmERS1-1-CEND), which is indispensable for receptor function. Mechanistically, GmERS1-1-CEND scaffolds a trimeric complex with GmACR1 and GmCDK7, enforcing G2/M phase arrest, thereby decoupling cell division from canonical ethylene transcriptional responses. Strikingly, ethylene-induced cell cycle blockade during apple fruit maturation mirrors this pathway, suggesting deep conservation across angiosperms. Our work defines a receptor processing-dependent signaling axis that directly interlinks phytohormone perception with cell cycle control, proposing tunable targets (e.g., GmERS1-1 cleavage efficiency) for engineering crop architecture and productivity.

plant biology↗

bioRxiv2026

Ambient-Condition Visualization of Metalloenzyme Reactive Intermediates Enabled by the SHINERS Paradigm

Reactive metal-oxygen intermediates are central to metalloenzyme catalysis, yet their low populations and short lifetimes make vibrational characterization under aqueous reaction conditions challenging. Here, we establish shell-isolated nanoparticle-enhanced Raman spectroscopy (SHINERS) as a powerful vibrational approach for visualizing reaction-associated metal-ligand signatures of reactive metalloenzyme states. Across the heme and non-heme iron enzymes TauD, VioC, CYP119, and TqaLNc, isotope-sensitive features provide vibrational information on reactive coordination states. In TauD and VioC, isotope-sensitive features provide vibrational characterization of Fe(IV)=O intermediates. In CYP119, an isotope-sensitive Fe(IV)=O vibration is assigned to P450 Compound I generated by m-CPBA, including under lauric-acid turnover conditions. Most notably, in TqaLNc, combined 18O- and 15N-sensitive vibrational responses support formation of the proposed (R)HN-Fe(IV)=O coordination state and the dynamic-coordination mechanism underlying selective C-N bond formation. These results demonstrate that SHINERS can serve as a powerful technique for the in situ vibrational visualization of reactive intermediates and their coordination states in metalloenzyme catalysis.

biochemistry↗