Biology subjects

Huang, B.

Publications and source records attributed to Huang, B..

At least 55 records · Page 3Linked to original sources

bioRxiv2025

Liver Viscosity Decreases Before the Onset of Fibrosis in Metabolic Dysfunction-Associated 1 Steatohepatitis (MASH)

Background and AimMetabolic dysfunction-associated steatohepatitis (MASH) is an increasingly prevalent condition worldwide, associated with biomechanical liver changes and detectable by magnetic resonance elastography (MRE). This study explored the pathophysiological features and their biomechanical manifestations at different stages of MASH in a mouse dietary model. MethodsUsing MRE on a clinical 3 Tesla MRI scanner, we measured liver stiffness, viscosity, fat fraction and water diffusion in 45 male mice. These values were correlated with histopathology and proteomics analyses to further characterize the liver microstructural and metabolic changes during MASH progression. ResultsWe found in a high-fat, low amino-acid model that early MASH was marked by fat accumulation and increasing inflammatory activity, while later stages showed a reduction in fat despite persistent inflammation. These changes in microstructure were associated with biomechanical adaptations, including a progressive decrease in hepatic viscosity and the water diffusion. Notably, viscosity was inversely correlated with lobular inflammation, cell adhesion, antioxidant activity, and metabolic adaptations such as enhanced ketone body synthesis. These findings, which precede the onset of fibrosis and tissue stiffening, show that tissue viscosity is highly sensitive to early microstructural and metabolic alterations in MASH. ConclusionSteatosis and inflammation significantly alter liver biophysical properties, particularly viscosity, in a mouse dietary model of MASH, even in the absence of fibrosis. These findings suggest that viscosity is a potential early and clinically translatable biomarker for the development and progression of MASH.

biophysics↗

bioRxiv2025

Pocket-based molecule generation with an SE(3)-equivariant language model leads to a potent and selective HPK1 inhibitor with in vivo efficacy

Deep learning shows promise in structure-based drug discovery, yet challenges persist in generating pharmacologically plausible molecules with valid 3D conformation and decent binding mode in the pocket. We introduce SE3-BiLingoMol, an SE(3)-equivariant Transformer for pocket-based 3D molecule generation, addressing two key limitations of existing language-model approaches. First, it uses Geometric Algebra Transformers for SE(3)-equivariant handling of continuous 3D coordinates. Second, a bidirectional attention mechanism mitigates conformational errors accumulated during autoregressive sampling. These innovations enable SE3-BiLingoMol to generate 2D drug-like, 3D geometrically valid molecules with superior binding modes. Validated on DUD-E dataset containing over 100 targets, the model achieved state-of-the-art performance in de novo design and optimization. We applied SE3-BiLingoMol to design potent and selective inhibitors for HPK1, a promising immunotherapy target. Through an iterative human-AI workflow, integrating AI generation with experimental validations (X-ray crystallography, bioassays), we identified Cmpd. 6. This novel tetracyclic compound demonstrates potent HPK1 inhibition, excellent cellular activity, favorable pharmacokinetics, and robust anti-tumor in vivo efficacy as monotherapy and with PD-1 blockade. Our work establishes a sophisticated generative AI framework for 3D molecule design and demonstrates its application in developing cancer immunotherapy. Highlights[bullet] SE(3)-Equivariant Language Model for Molecule Generation: We introduce a dual-channel SE(3)-equivariant language model that supports de novo molecule design and optimization, addressing key challenges in prior language model-based 3D molecule generation approaches. [bullet]Discovery of Potent HPK1 Inhibitors: Application of this model led to the discovery of highly selective HPK1 inhibitors with robust in vivo efficacy, resulting in a promising lead compound. [bullet]AI-Guided Rational Drug Development Paradigm: This work establishes a paradigm for AI-guided rational drug development, showcasing AI as a "co-pilot" that inspires drug designers with novel ideas in an "evidence-based context".

bioinformatics↗

bioRxiv2025

Meclizine rescues cardiac function and mitochondrial ultrastructure by ATP- and glycolysis-independent mechanisms in a genetic model of mitochondrial energy dysfunction

Primary mitochondrial cardiomyopathies are an unmet clinical challenge, as there are no therapies that directly address the underlying mitochondrial dysfunction. We previously reported that the cardiomyocyte-specific deletion of the mitochondrial phosphate carrier (SLC25A3), which imports phosphate required for ATP synthesis, produces a model of mitochondrial cardiomyopathy in which total cardiac ATP levels are preserved despite defective mitochondrial ATP production. This was accompanied by increased glycolytic activity and reduced mitochondrial flux, leading us to hypothesize that pharmacologically enhancing glycolysis might be protective when the mitochondrial energy machinery is intrinsically impaired. To test this, we turned to meclizine, an FDA-approved antihistamine previously shown to shift metabolism toward glycolysis. Chronic meclizine treatment in SLC25A3-deficient mice attenuated cardiac hypertrophy, improved systolic function, and restored mitochondrial ultrastructure. Unexpectedly, meclizine suppressed glycolytic enzyme expression and reduced lactate accumulation, suggesting that meclizine does not induce a glycolytic shift in SLC25A3-deleted hearts. Instead, proteomic and functional analyses revealed preservation of mitochondrial cristae architecture via MICOS upregulation and improved NAD+/NADH homeostasis through uncoupled electron flux and NAD+ regeneration. Together, these findings identify meclizine as a clinically approved compound that promotes cardioprotection in mitochondrial disease not by driving glycolysis, but by preserving mitochondrial membrane organization and redox balance, highlighting mitochondrial quality and NAD+ redox homeostasis as therapeutic targets for primary mitochondrial cardiomyopathies.

physiology↗

bioRxiv2025

Adaptive mutations at lysine residues of PRRSV nsp12 enable evasion of host proteasomal and selective autophagic degradation

Ubiquitin signaling in viral infections can either enhance immune responses and degrade viral proteins or be exploited by viruses to target host antiviral factors. Porcine reproductive and respiratory syndrome virus (PRRSV) poses a significant threat to the pig industry, with its non-structural proteins (nsps) critical for virulence and replication. Here, we investigated the role of ubiquitination in the stability of PRRSV-encoded nsps and found that nsp12 was specifically degraded via the ubiquitin-proteasome system. Mechanistically, nsp12 underwent K48- and K63-linked polyubiquitination at lysine residues 89, 91, 127, and 130. RNF114 served as an E3 ubiquitin ligase for nsp12, with its enzymatic activity essential for both nsp12 degradation and viral replication. Additionally, nsp12 underwent ubiquitin-dependent selective autophagy through receptor-mediated recognition, wherein NBR1, SQSTM1, and NDP52 bridged its interaction with LC3 for autophagic degradation. Evolutionary analyses revealed that PRRSV nsp12 acquired non-lysine residues at positions 89, 127, and 130 during viral adaptation. Correspondingly, recombinant PRRSV strains carrying the K91/127/130R mutations within nsp12 exhibited enhanced replication, while a revertant strain with the R89K mutation in nsp12 showed attenuated infectivity. Mass spectrometry analysis further identified significant enrichment of ubiquitination-related modifications among nsp12-interacting proteins. These findings provide valuable insights for anti-PRRSV drug design and highlight the challenge posed by adaptive mutations in viral proteins to the swine industry. Author SummaryUbiquitination plays crucial roles in both proteasomal degradation and selective autophagy during viral infections, yet its impact on the stability of porcine reproductive and respiratory syndrome virus (PRRSV) nonstructural proteins (nsps) remains unexplored. Here, we found that nsp12 was targeted for proteasomal degradation through K48/K63-linked polyubiquitination at lysine residues 89, 91, 127, and 130, which requires the involvement of E3 ubiquitin ligase RNF114. Furthermore, nsp12 underwent receptor-mediated selective autophagic degradation through the action of NBR1, SQSTM1, and NDP52. Using reverse genetics technology, mutations of lysine to arginine in PRRSV nsp12 enhanced viral replication, whereas the reverse mutations reduced its infectivity. Our findings demonstrate that PRRSV evades host degradation by acquiring adaptive mutations within nsp12, which counteract ubiquitin-dependent clearance thus enhancing viral fitness. This novel mechanism illustrates a key viral immune evasion strategy and underlines the challenge in controlling PRRSV.

microbiology↗

bioRxiv2025

An activated wheat CCG10-NLR immune receptor forms an octameric resistosome

Nucleotide-binding and leucine-rich repeat (LRR) receptors (NLRs) are widespread intracellular immune sensors across kingdoms. In plants, the G10-type coiled-coil (CCG10)-NLRs form a distinct phylogenetic clade that remains poorly characterized. Here, we identified a gain-of-function (GOF) mutant of Wheat Autoimmunity 3 (WAI3), designated WAI3GOF, which encodes a constitutively activated CCG10-NLR protein due to an amino acid substitution. Cryo-EM structural analysis revealed that activated WAI3 assembles into a distinctive octameric resistosome. Arabidopsis RPS2, another CCG10-NLR, also forms an octamer, indicating a conserved structural property across monocot and dicot plants. The WAI3 resistosome mediates a prolonged and sustained increase in cytosolic calcium influx, facilitated by a unique channel architecture arising from its divergent CC domain configuration. Notably, this domain arrangement may be shared by many plant NLRs that lack the conserved EDVID motif in their CC domains. Our findings uncover a previously uncharacterized resistosome structure and provide insights into plant immune receptor plasticity.

plant biology↗

bioRxiv2025

CASP3-GSDME-mediated trophoblast pyroptosis contributes to systemic inflammation

Early-onset preeclampsia (EOPE) is associated with excessive apoptosis and inflammation, but the mechanistic link between these processes remains enigma. Here, we report elevated circulating pro-apoptotic proteins in EOPE patients at early pregnancy, along with concurrent CASP3 activation and GSDME cleavage in a subset of EOPE placentas. Using multiple trophoblast cell lines, we demonstrate that trophoblast cells, which highly express GSDME, undergo a shift from apoptosis to CASP3-dependent pyroptosis, driving inflammation. Notably, pyroptotic trophoblasts further induce pro-inflammatory macrophage polarization within placental villi organoids, establishing a feedback loop that amplifies both trophoblast pyroptosis and inflammatory responses in trophoblast organoids-macrophage assembloids. In vivo, CASP3-GSDME-mediated trophoblast pyroptosis contributes to systemic inflammation in wild-type pregnant mice but not in Gsdme-/- mice. Screening of EOPE prevention drugs reveals Vitamin D as a suppressor of GSDME activation and pyroptosis in trophoblast cells. These findings highlight the CASP3-GSDME axis as a promising therapeutic target for preeclampsia prevention.

cell biology↗

bioRxiv2025

Adaptive behavior is guided by integrated representations of controlled and non-controlled information

Understanding how task knowledge is encoded neurally is crucial for uncovering the mechanisms underlying adaptive behavior. Here, we test the theory that all task information is integrated into a conjunctive task representation by investigating whether this representation simultaneously includes two types of associations that can guide behavior: stimulus-response (non-controlled) associations and stimulus-control (controlled) associations that inform how task focus should be adjusted to achieve goal-directed behavior. We extended the classic item-specific proportion congruency paradigm to dissociate the electroencephalographic (EEG) representations of controlled and non-controlled associations. Behavioral data replicated previous findings of association-driven adaptive behaviors. Decoding analyses of EEG data further showed that associations of controlled and non-controlled information were represented concurrently and differentially. Brain-behavioral analyses also showed that the strength of both associations was associated with faster responses. These findings provide initial evidence supporting the idea that controlled and non-controlled associations are governed by an integrated task representation to guide adaptive behaviors simultaneously.

neuroscience↗

bioRxiv2025

CAR T cell cytotoxic responses are rapidly generated and sensitive to the unligated TCR

Chimeric antigen receptor (CAR) T cells expressing tumor-targeting engineered receptors can robustly eliminate cancer cells through secretion of cytotoxic factors. Durable remission in leukemia and lymphoma treatment has not been matched in solid tumors. Efforts to maximize tumor destruction and minimize toxicities have driven efforts to tune CAR signaling. However, the molecular mechanisms for CAR triggering and thresholds for activation are incompletely understood. Here, we measured the collection of CAR binding interactions that culminate in polarized delivery of lytic granules to the junction with the target. CAR T cells binarized cytotoxic activities in response to a few binding events and population outcomes were dominated by a subset of cells. Activation at the single molecule level matches the sensitivity of the native T cell receptor (TCR) and points to potent downstream signal propagation. Disruption of the unligated TCR with a transmembrane-targeting inhibitory peptide strongly dampened CAR T cell activation, indicating a critical crosstalk between the two receptors. Harnessing CAR T cell efficacy and reduction of toxicity will require new approaches to modify integration of the binding events, collected stochastically, that are rapidly digitized. These sensitive CAR T cell responses provide new insights into driving cytotoxic signaling through surface interaction engineering.

immunology↗

bioRxiv2025

De novo design of high-affinity miniprotein binders targeting Francisella tularensis virulence factor

Francisella tularensis poses considerable public health risk due to its high infectivity and potential for bioterrorism. Francisella-like lipoprotein (Flpp3), a key virulence factor unique to Francisella, plays critical roles in infection and immune evasion, making it a promising target for therapeutic development. However, the lack of well-defined binding pockets and structural information on native interactions has hindered structure-guided ligand discovery against Flpp3. Here, we used a combination of physics-based and deep-learning methods to design high-affinity miniprotein binders targeting two distinct sites on Flpp3. We identified four binders for site I with binding affinities ranging between 24-110 nM. For the second site, an initial binder showed a dissociation constant (KD) of 81 nM, and subsequent site saturation mutagenesis yielded variants with sub-nanomolar affinities. Circular dichroism confirmed the topology of designed miniproteins. The X-ray crystal structure of Flpp3 in complex with a site I binder is nearly identical to the design model (C root-mean-square deviation: 0.9 [A]). These designed miniproteins provide research tools to explore the roles of Flpp3 in tularemia and should enable the development of new therapeutic candidates.

biochemistry↗

bioRxiv2025

A mechanistic model for dynamics between CAR T cells and target cells captures features that determine killing profiles

Chimeric antigen receptor (CAR) T cells represent a potent, programmable therapeutic that repurposes T cell cytotoxicity toward target cell elimination. Direct killing of tumor cells has been demonstrated in several cancer contexts but deficits in destroying solid tumors have been attributed to molecular and mechanical complexity. Understanding and predicting the efficacy of CAR T cell therapy requires a rigorous framework to capture the mechanistic interactions between immune cells and tumor targets. Toward enumerating such features and to quantitatively describe tumor cell survival in response to CAR T cell visitation, we propose a parametric hazard rate model for the right-censored conditional lifetime of a tumor cell, having the form of a time-discounted integral of cell:cell engagement. The model, conditioned using data on the numbers, durations, and modes of contacts made during the stochastic encounters between the two cell types, extracts mechanistic details from the experiments. We suggest two types of parameters to encapsulate features of CAR T cell killing potency ({kappa}) and the resilience of the tumor ({gamma}), respectively. These parsimonious parameters, nevertheless, generate substantial insights. Firstly, phenotypic heterogeneity from interactions mediated by substrate-engaged CAR T cells dominate killing outcomes, while those initiated in suspension contribute minimally. This emphasizes that a subset of the CAR T cell population is dominating the population outcome. Secondly, the model can be used to predict the killing as a function of time upon perturbation of the system. In this case, biasing the arrival process, toward more engagement in the adherent mode, can tune the rate of killing. Collectively, insights from the model framework imply that CAR T cell accumulation and killing efficiency depend not on the sum of individual T cell interactions, but rather on the weighted, time-dependent sum of heterogeneous interactions that are environmentally modulated. The model facilitates predictive insights into how contact sequences modulate CAR T cell responses and may provide strategies to alter therapeutic regimens.

biophysics↗

bioRxiv2025

De novo designed bright, hyperstable rhodamine binders for fluorescence microscopy

De novo protein design has emerged as a powerful strategy with the promise to create new tools. The practical performance of designed fluorophore binders, however, has remained far from meeting fluorescence microscopy demands. Here, we design de novo Rhodamine Binder (Rhobin) tags that combine ideal properties including size, brightness, and now adding hyperstability. Rhobin allows live and fixed cell imaging of a wide range of subcellular targets in mammalian cells. Its reversible fluorophore binding further enables live super-resolution STED microscopy with low photobleaching, as well as PAINT-type single-molecule localization microscopy. We showcase Rhobin in the extremophile Sulfolobus acidocaldarius living at 75{degrees}C, an application previously inaccessible by existing tags. Rhobin will serve as the basis for a new class of live cell fluorescent tags and biosensors.

bioengineering↗

bioRxiv2025

Genome-wide CRISPR screens identify PTGES3 as a novel AR modulator

The androgen receptor (AR) is a critical driver of prostate cancer (PCa). To study regulators of AR protein levels and oncogenic activity, we created the first live cell quantitative endogenous AR fluorescent reporters. Leveraging this novel AR reporter, we performed genome-scale CRISPRi flow cytometry sorting screens to systematically identify genes that modulate AR protein levels. We identified and validated known AR protein regulators including HOXB13 and GATA2 and also unexpected top hits including PTGES3, a poorly characterized gene in PCa. PTGES3 repression resulted in loss of AR protein, cell cycle arrest, and cell death in AR-driven PCa models. PTGES3 is not a commonly essential gene, and our data nominate it as a prime PCa therapeutic target. Clinically, analysis of PCa data demonstrate that PTGES3 expression is associated with AR-directed therapy resistance. Mechanistically, we show PTGES3 binds directly to AR, forms a protein complex with AR in the nucleus, regulates AR protein stability in vitro and in vivo and modulates AR function in the nucleus at AR target genes. PTGES3 represents a novel therapeutic target for overcoming known mechanisms of resistance to existing AR-directed therapies in PCa.

cancer biology↗

bioRxiv2025

Designed NGF mimetics with reduced nociceptive signatures in neurons

The clinical use of Nerve Growth Factor (NGF) for neuronal regeneration has been hampered by pain sensitization side effects. NGF signals through the receptor tyrosine kinase TrkA and the co-receptor p75NTR; pain sensitization is thought to involve p75NTR. We sought to overcome this limitation by de novo design of a TrkA agonist that does not bind p75NTR. We designed homodimeric TrkA engaging constructs that dimerize TrkA subunits in a variety of geometries, and identified those eliciting the strongest signaling. The resulting designed agonists are able to stimulate transdifferentiated neurons and neuroblastoma cell lines, leading to neurite outgrowth and neuronal differentiation, with considerably reduced transcription of inflammation and pain related genes. These agonists are promising candidates for promoting neuronal regeneration without adverse side effects. HighlightsO_LIDe novo designed TrkA agonists activate MAPK and PI3K-AKT signaling C_LIO_LIRigid fusions allow for highly tunable signaling signatures C_LIO_LITrkA agonists lead to neurite outgrowth in neuroblastoma cells comparable to retinoic acid C_LIO_LIModulation of the TrkA pathway without co-stimulating p75NTR leads to a downregulation of inflammatory and nociceptive signature in neurons. C_LI Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=107 SRC="FIGDIR/small/648806v1_ufig1.gif" ALT="Figure 1"> View larger version (32K): org.highwire.dtl.DTLVardef@c48066org.highwire.dtl.DTLVardef@c9c5a7org.highwire.dtl.DTLVardef@cf8ebdorg.highwire.dtl.DTLVardef@a4345a_HPS_FORMAT_FIGEXP M_FIG C_FIG

biochemistry↗

bioRxiv2025

LncMamba: A Deep Learning Model for lncRNA Localization Prediction Based on the Mamba Model

Accurate prediction of long non-coding RNA (lncRNA) subcellular localization is crucial for understanding its biological functions. In this study, we propose a novel deep learning framework, LncMamba, which utilizes a two-layer FPN network for multi-scale feature extraction and introduces the Mamba network to lncRNA localization prediction tasks for the first time. Based on this, we improved the localization-specific attention mechanism, allowing the model to more effectively focus on key sequence motifs related to localization. Additionally, through statistical analysis of localization motifs, we revealed the potential relationship between nucleotide motifs and lncRNA subcellular localization.The code is available at: https://anonymous.4open.science/r/lncMamba-731F.

bioinformatics↗

bioRxiv2025

A cascade of structural rearrangements positions peptide release factor II for polypeptide hydrolysis on the ribosome

Peptide release factor II (RF2) catalyzes the release of the nascent polypeptide from the bacterial ribosomal complex during translation termination and a subset of ribosome rescue pathways. Despite its critical role, the mechanisms that govern RF2 function and regulation remain elusive. Here, using single-molecule fluorescence energy transfer (smFRET), we characterize the conformational landscape that RF2 explores on the ribosomal complex and show that RF2 binding and dissociation from the ribosome follows a series of conformational rearrangements which depend on its ribosomal binding platform. We also show how further interactions with the ribosomal complex are necessary to properly position RF2 for polypeptide release. This work investigates not only the dynamics RF2 undergoes while in complex with the ribosome, but also identifies a potential mechanism by which the regulation of these dynamics may be disrupted, which may be exploited for future development of broad-spectrum antibiotics.

biophysics↗

bioRxiv2025

Coenzyme Q10 alleviates the mitochondrial damage by high-fat load in hepatocytes of spotted seabass (Lateolabrax maculatus) via promoting mitophagy

Coenzyme Q10, as a natural fat-soluble compound, can play a role in protecting mitochondria, but the mechanism is still unclear. Here, we explored the mechanism of coenzyme Q10 enhancing mitochondrial function using hepatocytes of spotted seabass. Three groups were set: normal medium as control group, fatty acid group containing 100 mol/L FA (FA group), and 100 mol/L FA and 5 mol/L coenzyme Q10 group (FA+COQ10). After the culture, the results showed that FA treatment significantly increased the triglyceride content in the cells. Bodipy staining showed that many lipid droplets appeared in the FA group, while coenzyme Q10 reduced triglycerides content and lipid droplets. Moreover, coenzyme Q10 significantly reduced the content of ROS in cells. After scavenging ROS, the liver cell damage caused by FA was alleviated, the mitochondrial membrane potential and its mitochondrial metabolic enzyme activity were restored, and the ATP content was increased. Further analysis showed that FA significantly down-regulated the expression of mitophagy key genes pink, parkin and lc3b, while up-regulated the expression of p62. Through mitochondrial fluorescence staining and mtDNA content detection, it was found that the number of mitochondria in FA-treated cells decreased significantly, while the number of mitochondria increased significantly after FA+COQ10 treatment. This indicates that coenzyme Q10 can significantly promote the mitophagy process. In order to further study whether the enhancement of mitochondrial function by coenzyme Q10 is related to the activation of autophagy, we set up FA group, FA+COQ10 group and FA+COQ10+Mdivi-1 group (pretreatment with mitophagy inhibitor Mdivi-1). After Mtphagy Dye staining, it was found that the number of autophagosomes in the FA+COQ10+Mdivi-1 group was lower than that in the FA+COQ10 group, indicating that the activation of mitophagy by coenzyme Q10 was inhibited. The results of this study indicate that coenzyme Q10 enhances mitochondrial function and alleviates excessive fat deposition dependent on PINK1-mediated mitophagy.

cell biology↗

bioRxiv2025

Accessible and accurate cytometry analysis using fluorescence microscopes

We have developed a method along with a python-based analysis tool to capture images and produce flow cytometry like data utilizing simple accessible microscopes. Utilizing the recently developed generalist algorithms for cell segmentation, our approach easily segments semi-adherent or suspended cells facilitating quantification of fluorescent intensity similar to flow cytometry. We have shown that our approach exhibits similar speed and enhanced sensitivity when compared to typical flow cytometry. The utility of our approach is demonstrated by screening a set of 88 prime editing conditions utilizing the integration of mNeonGreen11 as a reporter.

cell biology↗

bioRxiv2025

Unveiling the Evolution of Antimicrobial Peptides in Gut Microbes via Foundation Model-Powered Framework

Antimicrobial resistance poses a growing threat to public health, emphasizing the urgent need for novel therapeutic strategies. Antimicrobial peptides (AMPs), short peptide sequences with diverse mechanisms of action, offer a promising alternative due to their broad-spectrum activity against pathogens. Recent advances in protein language models (PLMs) have revolutionized protein structure prediction and functional annotation, highlighting their potential for AMP discovery and therapeutic development. In this context, we present AMP-SEMiner (Antimicrobial Peptide Structural Evolution Miner), an AI-driven framework designed to identify AMPs from metagenome-assembled genomes (MAGs). By integrating PLMs, structural clustering and evolutionary analysis into the framework, AMP-SEMiner can identify AMPs encoded by small open reading frames (smORFs) and encrypted peptides (EPs), significantly expanding the discovery space. Using this approach, we identified 1,670,600 AMP candidates from diverse habitats. Experimental validation of 29 candidates revealed antimicrobial activity in 18, with 13 surpassing antibiotics in effectiveness. Further analysis of AMPs from human gut microbiomes demonstrated both conserved and adaptive evolutionary strategies, ensuring their functional efficacy in the dynamic gut environment. These findings position AMP-SEMiner as a powerful tool for the discovery and characterization of novel AMPs, with significant potential to drive the development of new antimicrobial therapies.

microbiology↗