Biology subjects

Li, H.

Publications and source records attributed to Li, H..

At least 109 records · Page 6Linked to original sources

bioRxiv2026

Saturated mutagenesis screen of M-MLV reverse transcriptase identifies variants enhancing prime editing efficiency

Prime editing enables the precise modification of genomes, thereby holding great potential for the treatment of genetic diseases. Despite substantial advancements in prime editing technology and the initiation of the first clinical trial for treating chronic granulomatous disease, further enhancement of editing efficiency across edit types is still urgently needed. Here, we developed a compact prime editor, PE2{Delta}R, by deleting the RNase H domain of the MMLV reverse transcriptase (MMLV-RT). We then conducted a saturated mutagenesis screen targeting two DNA interacting regions within the PE2{Delta}R-RT Fingers domain. By integrating three highly effective mutations (I61R, V101R, S67W) into PEmax lacking RNase H domain (termed PEmax{Delta}RM3), we achieved up to a 90% increase in editing efficiency across editing types compared to PEmax. Structural modelling using AlphaFold 3 suggests that these mutations enhance primer-template stabilization and guide the RNA/DNA hybrid into a catalytically favourable trajectory, providing a mechanistic explanation for the enhanced activity. Taken together, our study demonstrates proof-of-concept for the application of unbiased mutagenesis screen to identify novel mutations that enhance prime editor performance. Furthermore, we discovered that RT variants (I61R, V101R, S67W) synergize with PEmax and epegRNA to improve prime editing efficiency across edit types, with the strongest improvement observed in introducing small deletions.

molecular biology↗

bioRxiv2026

Nuclear Cx43 restrains microglial neurotoxicity during brain development

Microglia are essential for sculpting the developing brain, yet the molecular mechanisms that select beneficial overreactive phagocytosis remain incompletely understood. Connexin 43 (Cx43, encoded by GJA1 in humans) is best known as a gap junction and hemichannel protein, although its non-canonical, channel-independent functions are increasingly recognized. We found that Cx43 is highly expressed in microglia during the perinatal period in human and mouse, whereas proportion of full-length multimeric Cx43 unexpectedly localizes to the nucleoplasm. Deletion of microglial Cx43 in mice during development instigates a transient neurotoxic state with microgliosis, upregulated phagocytic and complement pathways, excessive neuronal apoptosis, translating into depressive-like and cognitive deficits in the adulthood. Notably, neither microglia-specific deletion of Cx43 in adulthood nor hemichannel blockade recapitulate these changes, indicating a channel-independent, developmental stage-specific neuroprotective mechanism. Nucleus-targeted Cx43 overexpression suppresses neurotoxic markers and neural apoptosis. Nuclear Cx43 interacts with transcriptional regulators to restrain proinflammatory gene programs, nuclear import of Cx43 is driven by neurogenic niche-derived bFGF, which triggers AKT-mediated phosphorylation of a C-terminal nucleus localization signal (NLS), 14-3-3 binding, and importin-dependent nucleus translocation. These findings reveal a developmentally restricted nuclear Cx43 function that restrains microglial neurotoxicity while promoting microglial physiological functions thus expanding connexin biology to transcriptional co-regulation and pointing to a potential avenue for therapeutic intervention.

neuroscience↗

bioRxiv2026

Multi-layered regulatory networks driving human dopaminergic neuron differentiation

Neuronal differentiation requires coordinated regulation across chromatin organization, gene expression, protein abundance, and post-translational modifications. Using the LUHMES human dopaminergic neuronal differentiation model, we integrated proteome and phosphoproteome profiling with previously generated enhancer-promoter interaction maps from NET-CAGE and HiCap and transcriptomic analysis across three consecutive differentiation stages. Differentiation was accompanied by increased abundance and phosphorylation of proteins involved in axon guidance, cytoskeletal organization, and synaptic signaling, alongside repression of the cell cycle, DNA replication, and chromatin-associated programs. Phosphoproteome analysis further revealed extensive remodeling of signaling networks associated with neuronal maturation. Enhancer-promoter interaction analysis revealed substantially greater rewiring at enhancers than promoters and identified master and relay transcription factors regulated across multiple molecular layers. siRNA-mediated knockdown showed that transcription factors MYT1, ISL2, and NHLH2 are crucial for proper neuronal maturation, whereas LCOR acts as a negative regulator of differentiation. Integrative network reconstruction further nominated MEOX2 as a candidate enhancer-associated regulator of late dopaminergic maturation. Together, these findings provide a multi-layered view of regulatory networks governing human neuronal differentiation.

systems biology↗

bioRxiv2026

Rapamycin Mitigates a Sex-biased Convergent Aging Trajectory

Rapamycin extends lifespan across species, yet its cell-type-specific benefits and vulnerabilities remain unclear at whole-organism scale. Here, we present the Rapamycin Fly Cell Atlas (Rapa-FCA), a whole-organism single-nucleus transcriptomic atlas of Drosophila spanning both sexes, multiple ages, 18 cell classes, and 181 cell types. Rapamycin elicited a highly heterogeneous response, with prominent effects in reproductive, digestive, and neuromuscular systems and modest responses in most neuronal populations. Across diverse tissues, we identified a rapamycin-sensitive Convergent Aging Trajectory (CAT), marked by Fkbp12 enrichment and mTORC1-linked metabolic programs, including glycolysis and lipid synthesis. CAT-high nuclei accumulated with age and were preferentially reduced by rapamycin, especially in females, consistent with stronger female lifespan extension. By integrating CAT abundance, aging-clock predictions, and nucleus-ratio changes, we mapped sex- and cell-type-specific geroprotection effects of rapamycin. Together, the Rapa-FCA provides an organism-wide framework for resolving how rapamycin reshapes cellular aging across sex, tissue, and cellular state.

developmental biology↗

bioRxiv2026

HiFi-ST: High-Fidelity Reconstruction of Continuous Spatial Transcriptomic Expression Fields via Conditional Neural Fields

Spatial transcriptomics characterizes tissue-scale gene expression patterns, yet its observations are sparse discrete samples of an underlying continuous molecular field, leading to spatial aliasing and sub-resolution information loss. Existing methods usually formulate this task as spot-level point regression, making it difficult to capture both expression continuity and the regional nature of observation. Here, we propose HiFi-ST, a conditional neural field framework for continuous spatial transcriptomics modeling. HiFi-ST formulates spatial gene expression prediction as continuous expression field learning, models each spot as a regional observation over a finite support domain, approximates local integration through Monte Carlo sampling, and integrates multiscale tissue feature extraction with FiLM-based conditional modulation to improve modeling of complex spatial heterogeneity and consistency with the underlying measurement process. Systematic evaluation on three independent datasets (HER2+, cSCC, and Alex_NatGen) showed that HiFi-ST outperformed mclSTExp, BLEEP, THItoGene, His2ST, and HisToGene on key metrics. On HER2+, HiFi-ST achieved an average PCC improvement of 65.1% and an average MSE reduction of 40.9%; on cSCC, PCC improved by 10.2% and MSE decreased by 51.2%; on Alex_NatGen, PCC improved by 80.0% and MSE decreased by 16.3%. In addition, the learned multiscale tissue representations supported downstream spatial immunoanalysis, including assisted identification of candidate TLS regions. Overall, HiFi-ST provides a unified framework bridging discrete measurements and continuous expression field reconstruction for tumor microenvironment analysis and spatial immune structure characterization.

genomics↗

bioRxiv2026

A CSF Proteomic Clock Reveals Opposing Brain-Aging Programs and Predicts Neurological Disease Progression

Aging is the risk factor for neurological disease, yet the molecular architecture of human brain aging remains poorly defined. Here, we analyzed more than 10,000 cerebrospinal fluid (CSF) proteomes across multiple cohorts and proteomic platforms to developed a 249-protein CSF aging clock that accurately predicts age and generalizes across independent datasets. CSF brain-age acceleration was increased across diverse neurological diseases, associated with blood-brain barrier (BBB) dysfunction, and predictive of longitudinal cognitive decline, neuroimaging progression, and dementia conversion. A simplified 30-protein panel retained similar prognostic performance. Biologically, clock proteins resolved two opposing programs: pro-aging activation of immune, vascular/BBB, ECM and coagulation pathways marked by CHI3L1, CD14, VWF, LRG1 and LTBP2, and anti-aging collapse of neuronal, synaptic, axonal and structural-maintenance programs marked by NPTX2, COL1A2, NID1, CDH8 and PENK. Brain-wide single-cell and regional mapping linked these programs to disease-vulnerable compartments. These findings establish a molecular framework for biological brain aging and neurological disease vulnerability.

neuroscience↗

bioRxiv2026

Phenotypic CRISPR screening identifies ZBTB10 as a novel regulator of human trophoblast differentiation

The human placenta is built by trophoblast cells that fuse together, secrete hormones, and invade the uterus, and defects in these processes contribute to pregnancy disorders such as preeclampsia. Because cell-cell fusion and hormone secretion are inherently non-cell-autonomous processes, their regulators have remained inaccessible to conventional pooled CRISPR screens. Here, we developed an arrayed CRISPR screen in fusogenic BeWo trophoblasts that simultaneously quantifies fusion and hCG secretion across 412 gene perturbations. The screen revealed that these two hallmark functions of trophoblast differentiation are genetically separable. We characterized the strongest novel hit, ZBTB10, in trophoblast stem cells, organoids, and placental tissue and find that ZBTB10 is an essential regulator of human trophoblast differentiation. ZBTB10 is required for invasive extravillous trophoblast differentiation and supports syncytiotrophoblast maturation, establishing it as a cross-lineage regulator that both activates and represses distinct trophoblast fate programs. Together, these findings provide a genetic platform and phenotypic dissection of how regulatory networks control human placental development.

cell biology↗

bioRxiv2026

A Selective Multivalent NET-Associated Chromatin Neutralizer Resolves Infection-Associated Inflammation in Severe Sepsis

Targeting the overwhelming inflammation driven by neutrophil extracellular traps (NETs) during infection provides an opportunity to manage severe sepsis. This potential needs to be realized by exploring selective NET-neutralization materials, which remains a challenge. Herein, we report a multivalent macromolecular strategy that targets NET-associated DNA-histone chromatin complexes while preserving antibacterial activity of aminoglycoside. We identify 8-arm PEG-conjugated netilmicin (8-arm Netil) as a lead NETs-neutralizer from a library of multivalent aminoglycoside-displayed materials. When compared with 2- and 4-arm counterparts, 8-arm Netil exhibits potent antibacterial activity and high-affinity binding to DNA-histone chromatin complexes through stable multivalent noncovalent interactions, thereby suppressing NET-induced TLR4/TLR9 activation and macrophage inflammatory responses. In severe septic mice, intravenously administered 8-arm Netil preferentially accumulates in inflamed tissues, leading to improved survival protection, owing to the reduction of bacterial dissemination, NET accumulation, systemic cytokine production, and multiple-organ injury. These findings establish NET-associated DNA-histone chromatin complexes as actionable extracellular targets and demonstrate multivalent chromatin targeting as a rational material design strategy for selective NET neutralization and inflammation control in severe sepsis.

bioengineering↗

bioRxiv2026

In vivo spatial coordination with synthetic paracrine signaling

The immune system uses paracrine signaling to spatially confine potent responses such as inflammation. A bio-orthogonal synthetic paracrine system could enable engineering of analogous multicellular circuits in which different cell types coordinate their functions in a spatially organized fashion. Here, using the plant hormone auxin as a bio-orthogonal chemical signal, we introduce programmable paracrine circuits that distribute sensing and effector functions to different cell types to spatially restrict responses in mouse xenografts. Cells engineered to express auxin biosynthetic genes generated auxin-dense regions with tunable length scales in vivo. This localized signaling ability enabled design of a multicellular sentinel-effector system, in which THP-1 sentinel cells conditionally produce auxin in regions expressing the tumor-specific antigen EGFRvIII, and Jurkat effector cells respond by locally modulating the activity of a chimeric antigen receptor (CAR). This two-cell type system was able to achieve localized activation of engineered effector cells in vivo. These results establish a foundation for engineering multicellular therapeutic systems that focus responses in specific tissue contexts or disease sites.

Synthetic Biology↗

bioRxiv2026

Cerebrovascular Single-Nucleus RNA-Seq Reveals Heat Shock Activation and Vascular Remodeling in Alzheimer's Disease and Primary Tauopathies

Cerebrovascular alterations are widely observed in both Alzheimers Disease (AD) and primary tauopathies. Here, we hypothesized that mechanisms of cerebrovascular alterations are shared between AD and primary tauopathies. We performed single-nucleus RNA sequencing of postmortem human inferior temporal gyrus to characterize transcriptomic changes across cerebrovascular cell types in AD and primary tauopathies (Corticobasal Degeneration, Picks disease, and Progressive Supranuclear Palsy). Differential gene expression analyses revealed disease-specific transcriptional programs across vascular cell populations. However, genes involved in the heat-shock response were consistently upregulated across all diseases, suggesting a conserved cerebrovascular stress response during neurodegeneration. We further identified marked cerebrovascular remodeling in AD relative to primary tauopathies, along with dysregulation of genes mapping to AD risk loci in endothelial cells. Transcriptomic findings were validated using tissue clearing, light-sheet microscopy, and immunofluorescence quantification of vascular markers. These results define a conserved vascular stress program alongside AD-specific remodeling, highlighting the vasculature as a therapeutic target in neurodegeneration.

neuroscience↗

bioRxiv2026

Defining biologically directed therapy target signatures in urothelial carcinoma: A transcriptomic framework for precision therapy

IntroductionNectin-4 targeting antibody-drug conjugate (ADC) enfortumab vedotin (EV), in combination with pembrolizumab, is the first-line treatment for patients with locally advanced or metastatic urothelial carcinoma (UC). Optimal treatment strategies for patients who are non-responders or progress on EV with pembrolizumab remain an unmet clinical need. We sought to characterize ADC and immunotherapy (IO)-associated target expression profiles to identify candidate therapeutic vulnerabilities beyond EV. MethodsWe conducted a literature review to identify ADC and IO targets with approved or investigational relevance in UC. Unsupervised hierarchical clustering was used to identify clusters of target gene expression in RNA-seq data. Transcriptomic clustering analyses were performed in 434 patients from The Cancer Genome Atlas Bladder Urothelial Carcinoma cohort (TCGA-BLCA) and validated in an independent cohort of 478 patients from the Oncology Research Information Exchange Network (ORIEN) consortium. Proteomic interrogation of these targets was performed using mass spectrometry data from additional cohort of 116 patients. Differential gene expression analyses evaluated associations between target expression patterns, histologic variants, and consensus molecular subtypes of muscle-invasive bladder cancer (CMIBC). ResultsWe identified 13 ADC and 10 IO-associated targets with translational relevance in UC. Transcriptomic analyses revealed three reproducible clusters of overexpressed target genes across independent cohorts: 1) a luminal/epithelial-associated cluster enriched for VTCN1, SLITRK6, FGFR3, NECTIN4, TACSTD2, ERBB2, and ERBB3; 2) an immune target predominant cluster enriched for BTLA, LAG3, PDCD1, TIGIT, CTLA4, TNFRSF9, TNFRSF18, TNFRSF4; and 3) a basal/neuroendocrine-associated cluster characterized by CD274, F3, NT5E, EGFR, MET and DLL3. Similar clusters were largely conserved at the proteomic level. Adenocarcinomas overexpressed ERBB3 compared to neuroendocrine and squamous cell carcinomas. Pure squamous cell carcinomas overexpressed TACSTD2 compared to adenocarcinomas. In CMIBC subtypes, basal/squamous tumors expressed higher levels of CD274, EGFR, F3, LAG3, NT5E, and TNFRSF18, whereas luminal tumors demonstrated higher ERBB2 and ERBB3 expression. Neuroendocrine-like tumors showed higher DLL3 expression compared to all other subtypes. Tumors with low expression of NECTIN4, TACSTD2, and FGFR3 were enriched for alternative targets including DLL3, CD274, and CD276. Our findings provide a framework for hypothesis-driven therapeutic prioritization in advanced UC. Conclusions: UC is characterized by reproducible, biologically distinct patterns of ADC and IO target expressions. The degree of expression of NECTIN4 was positively associated with TACSTD2, FGFR3 and inversely associated with DLL3, CD276, and CD274, supporting alternative biologically informed treatment strategies besides EV . Histologic variants and molecular subtypes of UC also display distinct patterns of target expression. This study provides the first integrated transcriptomic framework linking ADC and IO target co-expression patterns for hypothesis-driven therapeutic prioritization. These findings provide a basis for rational ADC and immunotherapy development in advanced UC and support prospective proteomic validation in treatment stratified cohorts. Statement of Translational RelevanceEnfortumab vedotin plus pembrolizumab has redefined first-line therapy for advanced urothelial carcinoma, yet treatment selection following resistance or progression remains undefined. In this study, we integrate transcriptomic and proteomic analyses across independent cohorts to define reproducible patterns of antibody-drug conjugate (ADC) and immunotherapy target co-expression in urothelial carcinoma. We identify biologically distinct target-expression patterns that are associated with histologic and molecular subtypes and demonstrate coordinated and, in some cases, mutually exclusive relationships among therapeutically actionable targets. These findings have direct translational implications. First, they provide biologic rationale for rational sequencing and combination strategies based on co-expressed targets in NECTIN4-enriched tumors. Second, they identify alternative therapeutic vulnerabilities, including DLL3- and CD274-associated pathways, in tumors with low NECTIN4 expression, a population potentially enriched for resistance to EV-based therapy. Finally, this framework establishes a foundation for biomarker-driven clinical trials in urothelial carcinoma and supports the development of precision therapeutic approaches beyond current standards.

cancer biology↗

bioRxiv2026

SEMFA: A General Framework for Inferring Statistical Significance of Mahalanobis Similarity between Multi-Omics Profiled Samples Built on Multiple Factor Analysis

MotivationWith rapid advances in sequencing technologies, many heterogeneous omics datasets have been generated, as seen in the Encyclopedia of DNA Elements (ENCODE) and many single-cell multi-omics sequencing projects, bringing substantial challenges to existing integrative methods. In this article, we report a novel multi-omics fusion and analysis software SEMFA which performs general parametric tests for the Mahalanobis Similarity of samples based on the factor scores generated by an Extended version of conventional Multiple Factor Analysis. ResultsOur developed method is effective and robust under both Gaussian and non-Gaussian assumptions. The mean F1 scores are over 0.8 when the column similarity level is 0.9 and the noise level ranges between 0.1 and 0.2, using simulation studies based on ENCODE count data. It was also efficient and effective at handling large-scale single-cell multi-omics data, as demonstrated in colon cancer cases as it unveiled signature network organization patterns of cells for stages III and IV.

bioinformatics↗

bioRxiv2026

Decoding Spatial Programs in Human Glioblastoma Through Surprisal Information-Theoretical Analysis

Glioblastoma (GBM) is a highly heterogeneous and invasive brain tumor in which complex interactions among tumor cells, immune cells, and neurons shape disease progression and therapeutic resistance. Resolving spatial patterns programs in glioblastoma (GBM) requires analytical approaches that go beyond variance-driven embeddings. Here, we applied thermodynamic surprisal analysis, an information-theoretic decomposition framework, to spatial transcriptomic sequencing from human GBM specimens to identify orthogonal constraint modes that capture dominant and previously hidden spatial programs. Surprisal analysis revealed structured patterns in the data that are not highlighted by standard approaches such as PCA or cell type deconvolution, including immune-activation-associated signatures as well as spatial programs consistent with synapse remodeling. Coupling surprisal decomposition with spatial ligand-receptor interaction analysis, NICHES, along with multiplexed protein imaging connected these spatial hidden modes to reveal potential communication networks. Together, these results position surprisal analysis as a powerful, complementary strategy for interrogating spatial tumor architecture, enabling discovery of non-obvious spatial programs and interactions that are obscured by variance-based methods.

systems biology↗

bioRxiv2026

Nod factor signaling controlled genes in Medicago truncatula nodules

O_LILegume nodule formation is induced by rhizobia secreted Nod factors (NFs). It has been shown that NF receptors also accumulate in the apex of Medicago truncatula nodules. However, the NF signaling induced transcriptional changes in there have never been studied. C_LIO_LIHere, we studied this by using NF signaling mutant TE7, a weak allele of IPD3, blocked in rhizobial release. Nodule apices were isolated with laser microdissection and used for transcriptional analysis. C_LIO_LIWe identified 1655 NF signaling controlled genes in nodule apex. By comparing this with the transcriptome data from VAMP721d&e RNAi nodule apices, we identified a subset of 445 genes whose expression depends on NF signaling and rhizobial release. Further, we compared the set of genes controlled by NF signaling in nodule apices with that controlled in root epidermis, and these showed only a small overlap. NIN is induced by NF signaling both in the root epidermis and in the nodule. By overexpression of NIN in TE7 and knock down of NIN in wildtype nodules we showed that NF signaling controlled rhizobial release depends on NIN. C_LIO_LINF signaling controls a distinct set of genes in nodules, the function of which depends at least in part on NIN. C_LI

Developmental Biology↗

bioRxiv2026

CellTosg2Sequence: A Unified Text-Omics-Signaling-Graph Large Language Model for Single-Cell Analysis

In single-cell (sc)-based scientific discovery, text-formatted biomedical prior knowledge and signaling graphs are essential for annotating and interpreting numeric sc-omics data and for generating novel testable hypotheses. A major limitation of existing single-cell large language models (scLLMs) is that they rely on numeric expression data with gene names as the only textual signal, while comprehensive biomedical priors -- cellular localization, gene function, disease associations, and signaling interaction patterns -- remain absent from the model input. We introduce CellTosg2Sequence, a textual-prior- and signaling-graph-augmented cell-omics-sentence language model. A lightweight heterogeneous graph encoder maps a curated 62,507-node biomedical knowledge graph (KG) into compact virtual tokens that are prepended to each cell sentence, allowing the language model to condition on biological structure with minimal sequence-length overhead. We train CellTosg2Sequence with a three-stage objective: Stage I anchors the KG channel under autoregressive language-model pretraining, leveraging Qwen2.5-32Bs own language reasoning for rapid KG alignment; Stage II aligns labels via supervised fine-tuning with KG-anchored InfoNCE; Stage III applies Group Relative Policy Optimization (GRPO) with an ontology-hierarchy reward, enabling free-generation cell-type prediction that generalizes beyond the closed training vocabulary. Across multiple benchmarks and ablation experiments, CellTosg2Sequence outperforms strong baselines. All results are achieved with lightweight LoRA training and a single unified checkpoint. Data ethicsThis work uses publicly available single-cell datasets from the Human Cell Atlas (https://www.humancellatlas.org) and the Tahoe-100M consortium. All HCA constituent studies were collected under appropriate donor consent and institutional oversight as described in their original publications; we perform computational re-analysis only and introduce no new human subjects data. HCA data access follows the HCA Data Portal terms of use. No new patient data are collected in this study; no additional IRB approval is required for this secondary computational analysis.

bioinformatics↗

bioRxiv2026

ContinuumCellAgent: A Framework-Guided Agent for Long-Horizon Scientific Research

AI-scientist systems are beginning to automate parts of scientific research. We present CO_SCPLOWONTINUUMC_SCPLOWCO_SCPLOWELLC_SCPLOWAO_SCPLOWGENTC_SCPLOW, an autonomous agent that executes literature review, hypothesis formation, computational experimentation, manuscript drafting, and adversarial peer review as a single unattended run. Existing AI scientist systems remain difficult to diagnose because they lack modularity, systematic prompt grounding, and observability into long-running behavior. CO_SCPLOWONTINUUMC_SCPLOWCO_SCPLOWELLC_SCPLOWAO_SCPLOWGENTC_SCPLOW addresses these gaps with a modular supernode architecture for stage-wise backend swapping, protocols grounded in curated research-method checklists that also define reviewer rubrics, and a diagnostics layer that records file-based artifacts, message traces, and state transitions. We evaluate the system on open-domain QA benchmarks and biomedical/longevity case studies, showing that it can produce checkable research artifacts while exposing pipeline dynamics for rigorous AI co-scientist research.

bioinformatics↗

bioRxiv2026

Widespread phages exhibit depth-structured infection coupled with ammonia oxidation

Ammonia oxidation is a rate-limiting step in the nitrogen cycle, yet viral contributions to this process remain largely unresolved. Here, we identify three genomically distinct groups of amoC-encoding phages (155-338 kilobases in length; termed as amoC-phages) from multiple freshwater lakes in Europe and North America, including the Laurentian Great Lakes. These phages are highly divergent in phylogeny, genome architecture, and gene content, and are predicted to infect two distinct Nitrosomonadaceae ammonia-oxidizing bacterial lineages. The placement of phage-encoded amoC genes across these divergent viral clades indicates independent acquisition of amoC. Time-series and depth-resolved metagenomes and metatranscriptomes reveal persistent and depth-structured distributions of amoC-phages and their predicted hosts, with seasonal mixing periodically reshaping their co-occurrence patterns. Furthermore, virome data from Lake Mendota show that some of the amoC-phages occur as free viral particles, supporting active viral lysis and particle redistribution along the water column. Metatranscriptomes of the Laurentian Great Lakes reveal coordinated expression of phage structural genes (e.g., major capsid protein) together with phage-encoded amoC, indicating active infection in situ. Together, these results support a framework in which amoC-phage infection is depth-structured, seasonally dynamic, and coupled to ammonia-oxidizing bacterial host activity, highlighting viruses as previously overlooked components of freshwater nitrogen cycling.

microbiology↗

bioRxiv2026

Dehydration/1,6-addition-based Site-specific Bioconjugation Unveils Norepinephrinylation as a Widespread Post-translational Modification in the Cellular Proteome

Norepinephrine (NE) is a key neurotransmitter and hormone involved in diverse physiological and pathological processes. Beyond its canonical non-covalent signaling through binding adrenergic receptors, NE also induces protein post-translational modifications (PTMs), representing an emerging regulatory mechanism. Two major forms of NE-derived PTMs have been proposed: non-enzymatic norepinephrinylation (NEylation) of cysteine residues mediated by NE quinone and transglutaminase 2 (TG2)-catalyzed NEylation of glutamine residues. However, the cellular abundance, biochemical basis, and pathophysiological roles of NEylation remain poorly understood due to limited detection tools. Here, we report a novel bioconjugation chemistry for selective labeling and enrichment of the endogenous NEylation proteome in cell lines and tissues, which is based on acid-catalyzed dehydration and 1,6-addition to thiol probes. This strategy enables fluorescence imaging and chemical proteomic profiling, revealing NEylation as a widespread PTM that affects enzymatic activities of modified proteins, including protein tyrosine-protein phosphatase non-receptor type 11 (PTPN11). Visual Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=75 SRC="FIGDIR/small/731782v3_ufig1.gif" ALT="Figure 1"> View larger version (21K): org.highwire.dtl.DTLVardef@406ac5org.highwire.dtl.DTLVardef@121d6b9org.highwire.dtl.DTLVardef@98354corg.highwire.dtl.DTLVardef@d312ef_HPS_FORMAT_FIGEXP M_FIG C_FIG

biochemistry↗