Biology subjects

Wu, F.

Publications and source records attributed to Wu, F..

At least 37 records · Page 2Linked to original sources

bioRxiv2026

Gut microbiota-derived indole-3-propionic acid preserves dorsal hippocampal catecholamines to prevent post-stroke cognitive impairment

BackgroundGut dysbiosis has been increasingly implicated in post-stroke cognitive impairment (PSCI), yet the causal contribution and therapeutic potential of gut microbiota-derived metabolites remain unclear. This study aimed to identify key microbiota-derived metabolites involved in PSCI and to elucidate their underlying mechanisms. ResultsWe found that both PSCI patients and middle cerebral artery occlusion (MCAO) mice exhibited distinct gut microbial alterations, characterized by a marked reduction in tryptophan-metabolizing bacteria and indole-3-propionic acid (IPA), a gut microbiota-derived tryptophan metabolite. Exogenous IPA administration alleviated PSCI-like phenotypes in MCAO mice. Mechanistically, IPA preserved tyrosine hydroxylase-positive (Th) fibers and catecholamine levels in the dorsal hippocampus. Further analyses showed that IPA binds to the adaptor protein Ywhab, promotes ERK activation, and enhances neuronal survival, thereby counteracting neuronal apoptosis-associated inflammation and subsequent Th fiber degeneration. ConclusionThese findings identify IPA as a gut microbiota-derived neuromodulator that mitigates PSCI by preserving dorsal hippocampal catecholaminergic transmission. IPA may therefore serve as a promising predictive biomarker and therapeutic candidate for PSCI.

neuroscience↗

bioRxiv2026

Potential of HLA-E-targeting diabodies to induce lysis of HIV-1-infected cells by CD8+ T cells

A long-lived reservoir of cells harboring intact HIV-1 provirus persists throughout decades of antiretroviral therapy and can give rise to rapid viral rebound after treatment interruption. Some cure strategies employ cytotoxic T lymphocytes (CTL) to target this reservoir; however, the applicability and efficacy of immunotherapeutic strategies involving MHC class I-restricted CTL is limited by the polymorphic nature of MHC class I molecules and their downregulation by HIV-1 Nef. The non-polymorphic non-classical class I molecule HLA-E is stably expressed on HIV-1-infected CD4+ T cells and presents a potential universal target. We generated a single-chain diabody RLP-13 that redirects CTLs to target cells presenting a well-characterized peptide derived from Mycobacterium tuberculosis in the context of HLA-E. We verified the affinity and specificity of RLP-13. Through co-culture experiments, we confirmed that RLP-13 mediates polyfunctional, HLA-agnostic CTL responses. Using an HIV-1 reporter construct encoding the target peptide, we demonstrated robust and specific elimination of the HIV-1-expressing cell population. This proof-of-concept study shows that HLA-E antigens are promising immunotherapeutic targets that can bypass the limitations of classical MHC class I antigens - allelic variation and downregulation - and that such bispecific antibodies recognizing HIV-1-derived HLA-E binding epitopes could induce elimination of productively infected cells. SummarySengupta, Bachmann et al. utilize a novel HLA-E-restricted CD3-engaging single-chain diabody to induce antigen-specific polyfunctional CTL-responses that are HLA-type-independent. They further show that such biologics have potential to eliminate HIV-1-infected cells by targeting HLA-E-binding epitopes encoded in the HIV-1 provirus.

microbiology↗

bioRxiv2026

Virtual multiplex staining of the pancreatic islets across type 1 diabetes progression using a Schroedinger bridge

Classical hematoxylin and eosin (H&E) staining enables review of tissue morphology but lacks information regarding the molecular state of cells. Immunohistochemical (IHC) techniques label specific proteins in tissue, allowing differentiation of relevant structures that may go undetectable in H&E. However, the IHC process is complex, expensive, and time-consuming, especially for multiplex IHC (mIHC) limiting its use in large cohorts. Stain conversion of H&E to IHC using generative artificial intelligence models such as generative adversarial networks (GANs) represent one solution to this problem. However, GANs are unstable during out of distribution sampling and are prone to hallucinations or mode collapse, limiting their accuracy in challenging image conversion tasks. To address this, the field has recently turned to diffusion models. Here, we introduce Schrodinger-bridge for Multiplex ImmunoLabel Estimation (SMILE). Unlike conventional diffusion models that map from source to target through an intermediate Gaussian noise, Schrodinger-bridge diffusion models skip this step and have been shown to better preserve structures during image translation. To test the performance of SMILE, we generated a large cohort of high-fidelity H&E-mIHC image pairs from pancreatic organ donors, targeting insulin, glucagon, and CD3. Our dataset well-sampled across type-1 diabetes status, pancreas anatomical location, age, and sex. Using this cohort, we demonstrate the superiority of SMILE compared to GANs via a comprehensive evaluation framework incorporating texture, distribution, and antibody-specific metrics, as well as blinded pathologist reviews. We further confirmed the ability of SMILE to generate accurate mIHC images from H&Es generated at an external site, to perform whole slide image conversion, and to generate realistic three-dimensional maps of the pancreatic islets in non-diabetic, auto-antibody positive, and type-1 diabetic donor tissue. Finally, we performed stain conversion of paired H&E to HER2 and Ki67 images in breast cancer, confirming the superiority of SMILE in diverse stain conversion applications. Collectively, this framework provides a scalable pipeline for high-throughput proteomic inference from archival H&Es, providing transformative potential for pancreatic research and digital pathology.

bioinformatics↗

bioRxiv2026

Bacterial endosymbionts enhance fungal virulence by disrupting the disease-suppressive rhizobiome

The mechanisms by which bacterial endosymbionts (bacteria living within fungal cells) enhance the fitness and virulence of fungal pathogens remain poorly understood. Here, we report that the tomato Fusarium wilt pathogen Fusarium oxysporum f. sp. lycopersici (FOL) hosts Achromobacter sp. endosymbionts that enhance fungal virulence. This virulence potentiation is partially dependent on interactions with the native rhizosphere microbiota. We show that bacterial endosymbiont-harboring FOL reshapes the rhizosphere bacterial community during pathogen infection and decreased the abundance of disease{square}suppressive bacteria, including Streptomyces sp. taxa. This inhibitory effect is mediated by bacterial endosymbiont{square}stimulated production of beauvericin (an antibacterial cyclic hexadepsipeptide) by FOL. Together, our findings reveal a tripartite interaction in which a fungal pathogen leverages its bacterial endosymbiont to weaken rhizosphere microbiome{square}based disease suppression by inhibiting plant-protective bacterial taxa. This work highlights how cross{square}kingdom symbioses can modulate pathogen ecology and virulence in soil environments.

microbiology↗

bioRxiv2026

Selection-free whole genome transplantation revives dead microbes

We present a living, synthetic bacterial cell made by transplanting a complete genome into a dead cell. After killing Mycoplasma capricolum cells by chemically crosslinking their genome with Mitomycin C (MMC), we installed synthetic Mycoplasma mycoides genomes into the resulting dead cells using Whole Genome Transplantation (WGT)1,2. During WGT, a synthetic donor genome is placed into a recipient cell, thereby reprogramming that cell to adopt a new genetic identity3. WGT has only been demonstrated using species within one phylogenetic clade of Mollicutes bacteria4. A major barrier to expanding WGT to diverse bacterial species has been the inability to inactivate the recipient genome, leading to false positive transplants due to homologous recombination of antibiotic resistance markers from the donor genome into the recipient cell genome. Here, we address this key limitation by removing reliance on an antibiotic resistance marker to select for transplants; recipient cells are dead unless revived by the installation of a new genome. Our work demonstrates a general approach to fully inactivate the recipient cell genome, reports the first living synthetic bacterial cell constructed from non-living parts, and advances WGT for building engineered or synthetic cells for diverse applications.

synthetic biology↗

bioRxiv2026

Sex-determination cascade orchestrates male-male pheromone synthesis in the bean bug

Volatile pheromones are vital for insect intraspecific communication, yet the genetic basis of homosexual recognition remains elusive. In the bean bug Riptortus pedestris, we show that two previously identified aggregation pheromone components, (E)-2-hexenyl-(Z)-3-hexenoate (E2HZ3H) and (E)-2-hexenyl-(E)-2-hexenoate (E2HE2H), serve as key chemosensory cues for male-male recognition during mate selection. Their biosynthesis is governed by the sex-determination cascade Rpfmd-Rpdsx. The male-specific isoform Rpdsx_M promotes pheromone production in males and induces ectopic synthesis in females upon knockdown of the feminizing switch gene Rpfmd. Knockdown of Rpdsx_M in males abolishes both compounds, prompting wild-type males to court them as if they were females. Metathoracic gland cells act as the production hub. Behaviourally, E2HZ3H or E2HE2H disrupt mating when applied to females: males avoid such females. E2HZ3H reduces female mobility in the presence of the male-derived primary aggregation pheromone tetradecyl isobutyrate (14:iBu), whereas E2HE2H shows no obvious such effect. These differential effects ensure mating accuracy. The discovery of volatile pheromones functioning in male-male recognition and of their synthesis being governed by the sex-determination cascade updates our understanding of mating accuracy in insect chemical communication.

animal behavior and cognition↗

bioRxiv2026

Simulated Microgravity Recapitulates Aspects of Biological Aging in Humans

Spaceflight and microgravity profoundly affect human physiology and have been proposed to recapitulate key features of biological aging, yet the underlying mechanisms remain incompletely understood. Here, we performed whole-genome transcriptomic profiling to define immune cell alterations associated with both natural aging and simulated microgravity. Leveraging the longitudinal nature of the Stanford 1,000 immunomes Project, we compared peripheral blood mononuclear cells (PBMCs) exposed to rotating wall vessel bioreactor with matched samples collected up to 9 years later from the same individuals. We quantified changes across aging hallmarks, molecular pathways, gene modules, cellular energetics, disease risk and vaccine-response signatures. Microgravity-induced transcriptional closely tracked subject-level aging trajectories spanning across disease risk domains including those affecting the metabolic, musculoskeletal and circulatory systems, and multiple aging hallmarks involving nutrient sensing, intrinsic capacity, chronic inflammation, proteostasis, cellular senescence and metabolic regulation. Independent validation using Single-Cell Energetic Metabolism by Profiling Translation Inhibition (SCENITH) profiling confirmed these observed metabolic adaptations and revealed reduced mitochondrial dependence with minimal compensatory glucose dependence across immune cell subsets, features that strongly parallel aging biology. Consistent with previous findings, longitudinal changes indicated that close of 1/3 of participants do not follow population trajectories but these can be partly predicted with simulated microgravity exposure. Together, this within-donor framework establishes simulated microgravity as a scalable and experimentally tractable platform to model aspects of biological aging in humans and accelerating the prioritization of candidate countermeasures for spaceflight and aging on Earth.

immunology↗

bioRxiv2026

Antibody-Dependent Heterotypic Syncytia Drive COVID-19 Inflammation and Disease Progression

Severe COVID-19 is characterized by profound immune dysregulation and excessive inflammation. Aberrant myeloid responses drive hyperinflammation, yet the precise mechanisms remain elusive. Here, we demonstrate that certain spike antibodies promote the formation of heterotypic syncytia between monocytes/macrophages and virus-infected pneumocytes, leading to excessive inflammatory cytokine release. This antibody-dependent syncytium formation requires Fc{gamma}RI (CD64) and ADAM10, as well as the assembly of the six-helix bundle by the spike S2 subunit. Notably, these syncytia exhibit a stronger proinflammatory signature compared to virus-infected epithelial cells. In vivo, sub-neutralizing antibody concentrations amplified inflammation and exacerbated disease in SARS-CoV-2-infected mice without increasing viral burden. Furthermore, scRNA-seq of postmortem lung tissues from COVID-19 patients implicated the monocyte/macrophage-derived syncytia as a key cellular source of inflammatory cytokines. Together, these findings define a novel mechanism of antibody-dependent enhancement of inflammation that helps explain the hyperinflammatory responses in severe COVID-19 and suggest new therapeutic opportunities targeting this pathway.

immunology↗

bioRxiv2026

Proteogenomic Profiling Reveals a Distinct Endogenous p16INK4a-Associated Senescence Signature in the Human Ovary.

The tumor suppressor and cell cycle regulator, p16INK4a (p16), has been extensively linked to cellular senescence, and its accumulation can reflect endogenous senescence within ovarian tissue. However, gene and protein signatures associated with p16 have not been well defined in human tissue. We utilized immunohistochemical (IHC) staining for P16 to identify distinct positive (P16+) and negative (P16-) regions within the ovarian cortex and employed the GeoMx Digital Spatial Profiler for simultaneous proteomic and transcriptomic analyses on cortical tissue cores. Differential expression and translation between p16-positive and p16-negative cores identified genes and proteins that are cellular senescence related (e.g., CDKN1A, GADD45B, GADD45G, and MYC) or key regulators of the extracellular matrix (e.g., collagen I, ADAMTS4, and MMP11). Additionally, the transcriptomic signature identified here was significantly enriched for the spatially derived ovarian p16-associated signature, BuckSenOvary, but not for other senescence gene sets. Lastly, given the association between changes to the extracellular matrix in aged ovaries and ovarian cancer, we compared genes upregulated and downregulated in p16-positive regions relative to p16-negative regions against multiple ovarian cancer transcriptomic datasets. These findings provide new insight into the molecular landscape of naturally occurring ovarian senescence and its possible relationship to age-associated disease processes, including cancer development.

cell biology↗

bioRxiv2026

Optimizing broadly neutralizing antibodies via all-atom interaction modeling and pre-trained language models

Antibody optimization is a fundamental challenge, and the identification of antibody-antigen interactions is crucial in the optimization process. However, current methods cannot accurately predict antibody-antigen interactions, providing limited functional guidance to improve the time-consuming and costly traditional optimization techniques. Here, we present InterAb and InterAb-Opt, a unified computational framework that integrates all-atom modeling with antibody language models to predict antibody-antigen interactions and enable antibody optimization. Leveraging the proposed all-atom modeling approach, AtomInter, and pre-trained antibody language models, InterAb outperforms existing methods in predicting antibody specificity and antibody-antigen binding affinity. InterAb successfully identified influenza A virus-binding antibodies from an antibody library and accurately detected high-affinity antibodies in the AIntibody competition. Empowered by the robust functional insights from InterAb, InterAb-Opt was developed to optimize broadly neutralizing antibodies. For R1-32 antibody, biolayer interferometry results reveal that 85%, 80%, 90%, and 67.5% of the 40 InterAb-Opt-optimized antibodies exhibit enhanced binding affinities to wild-type SARS-CoV-2, Lambda, BQ.1.1, and EG.5.1, respectively, with a maximum improvement of up to 96-fold. For the newly emerging BA.2.86 and KP.3, 55% and 52.5% of the optimized antibodies notably transition from non-binding to binding. Neutralization assays demonstrated that the optimized antibodies exhibited enhanced neutralization activity across multiple targets, highlighting the capability of InterAb-Opt in engineering broadly neutralizing antibodies. This technology enables precise analysis of antibody-antigen interactions and optimization of broadly neutralizing antibodies, holding promise for addressing challenges in immune evasion and vaccine design.

bioinformatics↗

bioRxiv2026

Isolation and Characterisation of Hair Follicle-Derived Melanocytes

Melanocytes are unique population of cells which produce melanin pigment. However, the property of melanocytes from hair follicle and epidermis, particularly, their molecular signatures remained largely unknown. In this study, we investigated the properties of epidermis and hair follicle melanocytes by biochemical and molecular biological assays. We found that epidermal melanocytes are differentiated and mature form of hair follicle melanocytes, and they are potentially related. Irradiation with NB-UVB did not induce cell death of hair follicle melanocytes as observed in epidermal melanocytes, but activate hair follicle melanocytes, promote proliferation and migration. In situ study suggested that after UVB irradiation, root sheath of hair follicles, particularly proximity of interfollicular epidermis and hair bulb become darker, suggesting migration and maturation of hair follicle melanocytes after UVB irradiation, rather than cell death. This observation provides hints and evidence to the relationship between hair follicle and epidermal melanocytes, helps to explain the contradiction of melanocytes cell death after UVB irradiation and the use of UVB in treatment of vitiligo lesion, as well as the perifollicular repigmentation phenomenon observed in vitiligo lesion after NB-UVB phototherapy.

cell biology↗

bioRxiv2025

AI Identifies Broadly Neutralizing Antibodies from an IGHV1-69 Public Antibody Class Exerting Continued Selection Over SARS-CoV-2

R1-32-like public antibodies, characterized by shared IGHV1-69/IGLV1-40 usage, are elicited in more than 50% of individuals with COVID-19 and have been implicated in driving recurrent mutations at L452SARS2 and F490SARS2 within their convergent epitope in the SARS-CoV-2 spike receptor-binding domain. These mutations effectively mediate escape from non-affinity-matured R1-32-like antibodies with germline-like sequences. Here, we characterize four affinity-matured R1-32-like antibodies, C092, C807, BD56-104, and BD56-597, that tolerate L452SARS2 and F490SARS2 mutations. We show that this tolerance arises from residues introduced by somatic hypermutation at convergent positions across multiple CDR loops and surrounding regions, thereby creating additional contacts that reinforce epitope binding. An unusual N354SARS2 glycosylation site, which emerged in BA.2.86 and became fixed in its descendants, is linked to escape from affinity-matured R1-32-like antibodies, implying ongoing selection by this public antibody class. Using an AI model trained on integrated structural, neutralization, and binding data, we further identified ZL525, an ultrapotent R1-32-like antibody with pan-SARS-CoV-2 variant activity, including against the highly evasive KP.3 variant carrying the N354SARS2 glycosylation, and broad sarbecovirus cross-reactivity extending to SARS-CoV-1. Together, these findings show how affinity maturation enables public antibodies to adapt to viral antigenic drift, reveal their role in shaping SARS-CoV-2 antigenic evolution, and demonstrate the potential of AI-empowered strategies for discovering broadly neutralizing antibodies.

immunology↗

bioRxiv2025

A global atlas of deep-sea cold seep viruses uncovers extensive genomic novelty, pervasive viral dark matter, and biotechnological potential

Cold seeps are globally distributed deep-sea ecosystems harboring diverse chemosynthetic microbial communities, yet their viral components remain poorly understood. Here, we establish the Global Cold Seep Virome, a comprehensive catalog of 191,937 species-level viral operational taxonomic units (vOTUs) and 2.44 million viral protein clusters reconstructed from 314 metagenomes spanning 18 cold seep sites worldwide. Most vOTUs are distinct from those in existing environmental viromes, suggesting that cold seeps harbor a largely unexplored viral reservoir. Host prediction suggests diverse viral associations with key prokaryotes, including anaerobic methanotrophic archaea. Protein annotation reveals that these viruses encode widespread uncharacterized proteins and viral hallmark proteins with divergent physicochemical properties, potentially contributing to their ecological adaptability. We also identify putative auxiliary metabolic genes, anti-defense genes, and lysins, and experimentally validate representative anti-defense proteins and lysins with strong activities. This resource expands current knowledge of deep-sea viral diversity and provides a foundation for studying virus-host interactions, testing biogeochemical hypotheses, and exploring biotechnological potential in cold seep ecosystems.

microbiology↗

bioRxiv2025

AI recognizes convergent somatic hypermutation signatures to allow the discovery of variant-resilient broadly neutralizing antibodies

Elucidating the mechanisms by which broadly neutralizing antibodies (bnAbs) develop to confer durable immunity in humans is pivotal for the rational design of next-generation vaccines and therapeutics. VH3-53/3-66-encoded public antibodies are widely elicited in the population after the COVID-19 pandemic. Here, we isolated 15 VH3-53/3-66-encoded bnAbs from elite neutralizers who experienced sequential SARS-CoV-2 Omicron breakthrough infections. These bnAbs exhibit exceptional potency and breadth against circulating variants and, as members of a long-lived public antibody lineage, likely contribute to durable humoral protection. Genetic analysis of VH3-53/3-66-encoded bnAbs reveals a convergent somatic hypermutation pattern at seven positions in and around the CDR loops that emerges with repeated viral exposures and distinguishes them from non-bnAbs. Grafting these combined mutations onto clinically escaped antibodies broadens their breadth and restores neutralization activity. Structural analysis shows that these convergent mutations cooperatively remodel CDRs to bind and tolerate virus receptor-binding domain mutations. Using an AI-based antibody language model trained on data linking somatic hypermutations to binding affinity and neutralization, the model is able to identify mutational patterns predictive of breadth, enabling the discovery of a rare bnAb with protective activity against the latest variants from early-pandemic antibody repertoires. This demonstrates the feasibility of establishing an AI-empowered pipeline to identify mutation-tolerant bnAbs from early-pandemic antibody repertoires to fight fast-evolving newly introduced viruses.

immunology↗

bioRxiv2025

Senescence-Linked Fibrosis in the Aging Human Ovary Revealed by p16-Based Histological Profiling and Spatial Transcriptomics

Cellular senescence is implicated as a driver of ovarian aging, but senescent cells in the human postmenopausal ovary remain poorly defined. Using spatially resolved p16INK4a protein expression, a canonical senescence marker, we identified and mapped senescent cells in postmenopausal ovaries. We integrated p16 immunohistochemistry, multiplexed immunofluorescence, spatial transcriptomics, and AI-guided digital pathology to map senescent microenvironments. p16-positive cells formed discrete stromal, vascular, and cyst-associated clusters that increased with age and were enriched for macrophages and myofibroblast-like cells. Wholetranscriptome profiling of 92 spatial regions uncovered a 32-gene p16-associated signature, BuckSenOvary, that distinguished p16-positive regions across cortex and medulla. BuckSenOvary is characterized by suppression of cell-cycle regulators and activation of inflammatory and extracellular-matrix remodelling genes. AI-based collagen matrix analysis confirmed that p16-positive regions exhibit more architecturally complex collagen, demonstrating that focal senescent microenvironments are fibro-inflammatory. These findings position senescent ovarian niches as therapeutic targets to preserve ovarian function.

cell biology↗

bioRxiv2025

A foundation model for microbial growth dynamics

Microbial growth dynamics contain rich information about microbial populations, which support applications from antibiotic testing to microbiome engineering. However, the high dimensionality of growth data and the scarcity of large, task-specific datasets have limited generalizable modeling analysis across systems. Here, we develop a foundation model for microbial growth dynamics. It is a large-scale, self-supervised representation model trained on [~]370,000 experimental and simulated growth curves spanning diverse microbial species, environmental conditions, and community contexts. The model learns lower-dimensional latent embeddings that capture essential dynamical features of raw growth data and enable accurate reconstruction of these data. The concise representations enhance predictive performance in diverse downstream applications. Using these embedding, we achieve few-shot learning for antibiotic classification and concentration prediction, accurate forecasting of simulated and experimental communities, and inference of total abundance from relative-abundance data. By extracting transferable representations from heterogeneous datasets, our model provides a general framework for analyzing and predicting microbial community dynamics from limited measurements.

synthetic biology↗

bioRxiv2025

Cycling of sulfur redox intermediates drives microbial activity in the sulfate-methane transition zone of cold methane seeps

Microbial sulfate reduction is a cornerstone of marine sediment biogeochemistry, driving carbon remineralization and fueling the anaerobic oxidation of methane (AOM). Yet in zones of high methane flux, sulfate limitations may constrain the sulfate-reducing bacteria (SRB) and anaerobic methanotrophic archaea (ANME) that typically perform AOM. Although often overlooked, sulfur redox intermediates are readily utilized by diverse microorganisms, potentially driving AOM in sulfate-limited zones. To resolve the microbial mechanisms underlying cryptic sulfur cycling in such sediments, Monterey Canyon cold methane seeps were investigated through an integrated geochemical, isotopic, and metatranscriptomic approach. High-resolution electrochemical measurements confirmed intense sulfide production in seep sites, and long-term anoxic incubations were conducted with sediment from the SMTZ amended with elemental sulfur, thiosulfate, or sulfate as the sole sulfur source, with or without methane. Over 650 days, sulfide accumulation was greatest in elemental sulfur treatments, followed by thiosulfate and sulfate; in all cases methane addition enhanced sulfide production. Isotopic measurements showed modest S-isotope fractionation indicating that the large fractionations typical of slow sulfate reduction were muted by additional sulfur transformations. In elemental sulfur treatments, isotopic and geochemical patterns suggested that disproportionation was unlikely. Metatranscriptomes revealed broad expression of sox genes and abundant dsr/apr across treatments, along with thiosulfate-linked phs upregulation. While ANME-2c and SEEP-SRB2 activity increased with methane, transcriptomic and isotopic data together highlighted the roles of Desulfocapsaceae, Desulfobulbaceae, and Sulfurovaceae lineages in mediating sulfur transformations. Taken together, these results demonstrate how cryptic sulfur cycling may sustain microbial communities in sulfate-depleted deep-sea sediments and contribute to AOM.

ecology↗

bioRxiv2025

Tiarins, a diverse family of natural Trojan-horse aminoacyl-tRNA synthetase inhibitors discovered by genome mining

Trifolitoxin (TFX) is a ribosomally synthesized and post-translationally modified peptide antibiotic produced by Rhizobium anhuiense T24. Although discovered more than half a century ago, its mechanism of action has remained elusive. Here we demonstrate that TFX inhibits arginyl-tRNA synthetase (ArgRS), an essential translation enzyme. TFX acts as a Trojan-horse antibiotic: it enters cells via the inner membrane oligopeptide transporter YejABEF and then undergoes partial proteolysis by the aminopeptidase PepN to release a "warhead" that binds ArgRS and arrests translation. A systematic analysis of prokaryotic genomes revealed that TFX belongs to a widespread family of modified peptides that we designate the tiarins. In addition to ArgRS inhibitors, the tiarin family includes compounds that specifically target at least seven other aminoacyl-tRNA synthetases. These findings define a previously unrecognized family of natural antibiotics and provide a framework for developing a new class of inhibitors targeting various tRNA synthetases.

molecular biology↗