Biology subjects

Tian, Y.

Publications and source records attributed to Tian, Y..

At least 127 records · Page 7Linked to original sources

bioRxiv2024

Hallmarks of tumor-experienced T cells are absent in multiple myeloma patients from diagnosis through maintenance therapy

Dysregulation of the bone marrow (BM) niche in multiple myeloma (MM) alters the composition and state of resident immune cells, potentially impeding anti-tumor immunity. One common mechanism of immune inhibition in solid tumors is the induction of exhaustion in tumor-specific T cells. However, the extent of T cell tumor recognition and exhaustion is not well-characterized in MM. As the specific mechanisms of immune evasion are critical for devising effective therapeutic strategies, we deeply profiled the CD8+ T cell compartment of newly-diagnosed MM (NDMM) patients for evidence of tumor reactivity and T cell exhaustion. We applied single-cell multi-omic sequencing and antigen-specific mass cytometry to longitudinal BM and peripheral blood (PB) samples taken from timepoints spanning from diagnosis through induction therapy, autologous stem cell transplant (ASCT), and maintenance therapy. We identified an exhausted-like population that lacked several canonical exhaustion markers, was not significantly enriched in NDMM patients, and consisted of small, nonpersistent clones. We also observed an activated population with increased frequency in the PB of NDMM patients exhibiting phenotypic and clonal features consistent with homeostatic, antigen-nonspecific activation. However, there was no evidence of "tumor-experienced" T cells displaying hallmarks of terminal exhaustion and/or tumor-specific activation/expansion in NDMM patients at any timepoint.

immunology↗

bioRxiv2024

Suppression of autophagy induces senescence in the heart

Aging is a critical risk factor for heart disease, including ischemic heart disease and heart failure. Cellular senescence, characterized by DNA damage, resistance to apoptosis and the senescence-associated secretory phenotype (SASP), occurs in many cell types, including cardiomyocytes. Senescence precipitates the aging process in surrounding cells and the organ through paracrine mechanisms. Generalized autophagy, which degrades cytosolic materials in a non-selective manner, is decreased during aging in the heart. This decrease causes deterioration of cellular quality control mechanisms, facilitates aging and negatively affects lifespan in animals, including mice. Although suppression of generalized autophagy could promote senescence, it remains unclear whether the suppression of autophagy directly stimulates senescence in cardiomyocytes, which, in turn, promotes myocardial dysfunction in the heart. We addressed this question using mouse models with a loss of autophagy function. Suppression of general autophagy in cardiac-specific Atg7 knockout (Atg7cKO) mice caused accumulation of senescent cardiomyocytes. Induction of senescence via downregulation of Atg7 was also observed in chimeric Atg7 cardiac-specific KO mice and cultured cardiomyocytes in vitro, suggesting that the effect of autophagy suppression upon induction of senescence is cell autonomous. ABT-263, a senolytic agent, reduced the number of senescent myocytes and improved cardiac function in Atg7cKO mice. Suppression of autophagy and induction of senescence were also observed in doxorubicin-treated hearts, where activation of autophagy alleviated senescence in cardiomyocytes and cardiac dysfunction. These results suggest that suppression of general autophagy directly induces senescence in cardiomyocytes, which in turn promotes cardiac dysfunction. O_FIG O_LINKSMALLFIG WIDTH=147 HEIGHT=200 SRC="FIGDIR/small/595978v1_ufig1.gif" ALT="Figure 1"> View larger version (26K): org.highwire.dtl.DTLVardef@dd3551org.highwire.dtl.DTLVardef@d78a85org.highwire.dtl.DTLVardef@c7505aorg.highwire.dtl.DTLVardef@16c84b6_HPS_FORMAT_FIGEXP M_FIG C_FIG

cell biology↗

bioRxiv2024

Sexually dimorphic phenotypes and the role of androgen receptors in UBE3A-dependent autism spectrum disorder

Autism spectrum disorders (ASDs) are characterized by social, communication, and behavioral challenges. UBE3A is one of the most common ASD genes. ASDs display a remarkable sex difference with a 4:1 male to female prevalence ratio; however, the underlying mechanism remains largely unknown. Using the UBE3A-overexpressing mouse model for ASD, we studied sex differences at behavioral, genetic, and molecular levels. We found that male mice with extra copies of Ube3A exhibited greater impairments in social interaction, repetitive self-grooming behavior, memory, and pain sensitivity, whereas female mice with UBE3A overexpression displayed greater olfactory defects. Social communication was impaired in both sexes, with males making more calls and females preferring complex syllables. At the molecular level, androgen receptor (AR) levels were reduced in both sexes due to enhanced degradation mediated by UBE3A. However, AR reduction significantly dysregulated AR target genes only in male, not female, UBE3A-overexpressing mice. Importantly, restoring AR levels in the brain effectively normalized the expression of AR target genes, and rescued the deficits in social preference, grooming behavior, and memory in male UBE3A-overexpressing mice, without affecting females. These findings suggest that AR and its signaling cascade play an essential role in mediating the sexually dimorphic changes in UBE3A-dependent ASD.

neuroscience↗

bioRxiv2024

Self-Assembled Origami Neural Probes for Scalable, Multifunctional, Three-Dimensional Neural Interface

Flexible intracortical neural probes have drawn attention for their enhanced longevity in high-resolution neural recordings due to reduced tissue reaction. However, the conventional monolithic fabrication approach has met significant challenges in: (i) scaling the number of recording sites for electrophysiology; (ii) integrating of other physiological sensing and modulation; and (iii) configuring into three-dimensional (3D) shapes for multi-sided electrode arrays. We report an innovative self-assembly technology that allows for implementing flexible origami neural probes as an effective alternative to overcome these challenges. By using magnetic-field-assisted hybrid self-assembly, multiple probes with various modalities can be stacked on top of each other with precise alignment. Using this approach, we demonstrated a multifunctional device with scalable high-density recording sites, dopamine sensors and a temperature sensor integrated on a single flexible probe. Simultaneous large-scale, high-spatial-resolution electrophysiology was demonstrated along with local temperature sensing and dopamine concentration monitoring. A high-density 3D origami probe was assembled by wrapping planar probes around a thin fiber in a diameter of 80[~]105 m using optimal foldable design and capillary force. Directional optogenetic modulation could be achieved with illumination from the neuron-sized micro-LEDs (LEDs) integrated on the surface of 3D origami probes. We could identify angular heterogeneous single-unit signals and neural connectivity 360{degrees} surrounding the probe. The probe longevity was validated by chronic recordings of 64-channel stacked probes in behaving mice for up to 140 days. With the modular, customizable assembly technologies presented, we demonstrated a novel and highly flexible solution to accommodate multifunctional integration, channel scaling, and 3D array configuration.

neuroscience↗

bioRxiv2024

Towards anchoring evolutionary fitness for protein stability with virtual chemical environment recovery

Predicting the protein stability changes upon mutations is one of the effective ways to improve the efficiency of protein engineering. Here, we propose a dual-view ensemble learning-based framework, DVE-stability, for mutation-induced protein stability change prediction from single sequence. DVE-stability integrates the global and local dependencies of mutations to capture the intramolecular interactions from two views through ensemble learning, in which a structural microenvironment simulation module is designed to indirectly introduce the information of structural microenvironment at the sequence level. DVE-stability achieved state-of-the-art prediction performance on 7 single-point mutation benchmark datasets, and comprehensively surpassed other methods on 5 of them. Furthermore, DVE-stability outperformed other methods comprehensively through zero-shot inference on multiple-point mutation prediction task, demonstrating superior model generalizability to capture the epistasis of multiple-point mutations. More importantly, DVE-stability exhibited superior generalization performance in predicting rare beneficial mutations that are crucial for practical protein directed evolution scenarios. In addition, DVE-stability identified important intramolecular interactions via attention scores, demonstrating interpretable. Overall, DVE-stability provides a flexible and efficient tool for mutation-induced protein stability change prediction in an interpretable ensemble learning manner.

bioinformatics↗

bioRxiv2024

Multiple Omics Find New Cecal Microbial Features Associated with Feed Efficiency in Ducks

As the global population continues to grow exponentially, the competition for resources between livestock and humans has become increasingly intense. Breeding efficient animal breeds, fully utilizing feed resources, and reducing environmental damage are major challenges facing the livestock industry. To address these issues, enhancing the feed utilization efficiency in the poultry industry is crucial. Recent studies have elucidated the pivotal role of gut microbiota in modulating the feeding behavior of their host organisms. Thus, we used metagenomics, transcriptomics, and metabolomics to explore how the intestinal microbiome affects the feed utilization efficiency in ducks. Our metagenomic analysis revealed a significant up-regulation of Elusimicrobiota at the phylum level within the high residual feed intake (HRFI) group, in comparison to the low residual feed intake (LRFI) group. Additionally, functional analysis using Clusters of Orthologous Groups of proteins (COG) indicated prominent disparities in the category of secondary metabolites biosynthesis, transport, and catabolism between the HRFI and LRFI groups. Furthermore, our metabolomics investigation identified an upregulated expression of the secondary metabolite 15-deoxy-{Delta}12,14-prostaglandin J2 (15d-PGJ2) in the HRFI group compared to the LRFI group. Liver transcriptome analysis identified prostaglandin-endoperoxide synthase 2 (PTGS2) as a key hub gene, exerting significant regulatory influence within the arachidonic acid pathway. Notably, the metabolite 15d-PGJ2 is a terminal product in the metabolic pathway of arachidonic acid. The correlation analysis between the cecal microbiota and differential metabolites revealed a significant negative correlation between Elusimicrobiota and the metabolite 15d-PGJ2. In summary, we assumed that the intestinal microbiome Elusimicrobiota regulates the expression of the PTGS2 gene, consequently inducing variations in PTGS2 efficiency between the HRFI and LRFI groups, ultimately leading to diverse residual feed intake levels in ducks. IMPORTANCEThis investigation utilizes metabolomics to elucidate the interplay between genes and microbiome communities. We present evidence of disparities in the composition of microbial consortia among ducks RFI, alongside identification of pivotal genes within the liver that potentially modulate RFI. These results provide novel perspectives on the processes through which the cecum and liver influence RFI.

microbiology↗

bioRxiv2024

Hierarchical cortical entrainment orchestrates the multisensory processing of biological motion

When observing others behaviors, we continuously integrate their movements with the corresponding sounds to enhance perception and develop adaptive responses. However, how the human brain integrates these complex audiovisual cues based on their natural temporal correspondence remains unclear. Using electroencephalogram (EEG), we demonstrated that rhythmic cortical activity tracked the hierarchical rhythmic structures in audiovisually congruent human walking movements and footstep sounds. Remarkably, the cortical tracking effects exhibit distinct multisensory integration modes at two temporal scales: an additive mode in a lower-order, narrower temporal integration window (step-cycle) and a super-additive enhancement in a higher-order, broader temporal window (gait-cycle). Furthermore, while neural responses at the lower-order timescale reflect a domain-general audiovisual integration process, cortical tracking at the higher-order timescale is exclusively engaged in the integration of biological motion cues. In addition, only this higher-order, domain-specific cortical tracking effect correlates with individuals autistic traits, highlighting its potential as a neural marker for autism spectrum disorder. These findings unveil the multifaceted mechanism whereby rhythmic cortical activity supports the multisensory integration of human motion, shedding light on how neural coding of hierarchical temporal structures orchestrates the processing of complex, natural stimuli across multiple timescales.

neuroscience↗

bioRxiv2024

Development of a Two-Leaf Photosynthetic Model Sensitive to Chlorophyll and Its Coupling with a Wheat Growth Model

Crop growth models (CGMs) commonly simulates the response of photosynthetic rate to nitrogen (N) dynamic by calculating critical N concentration. However, critical N concentration makes it hard to describe the physiological effect of N dynamic on photosynthesis. Meanwhile, the effect of diffuse light on photosynthesis was limited in previous studies. In this study, we introduced a Two-leaf Photosynthetic Model Sensitive to Chlorophyll Content (TPMSCC) and coupled it with the crop growth model (WheatGrow) to enhance our understanding of how N dynamic and diffuse light affects photosynthesis. By coupling the Farquhar-von Caemmerer-Berry (FvCB) C3 photosynthesis model with a canopy radiative transfer model (PROSAIL), TPMSCC simulated the light interception of direct and diffuse light, and employed leaf chlorophyll content (LCC) to simulate the light absorption and electron transfer rate of leaves. Result showed that TPMSCC well simulated the light absorption of the wheat canopy and found the canopy photosynthetic rate benefited from the increase of diffuse radiation fraction (DRF) except for when the condition of a dense canopy at a high solar zenith angle was present. Research found the logarithmic and linear relationships of LCC to the initial light use efficiency ([a]) and the maximum photosynthetic rate (Amax), respectively, which followed the field measurements. Additionally, the optimized WheatGrow model outperforms its predecessor in describing the response of N application rate on photosynthesis.

biophysics↗

bioRxiv2024

An Open Resource: MR and light sheet microscopy stereotaxic atlas of the mouse brain

We have combined MR histology and light sheet microscopy (LSM) of five postmortem C57BL/6J mouse brains in a stereotaxic space based on micro-CT yielding a multimodal 3D atlas with the highest spatial and contrast resolution yet reported. Brains were imaged in situ with multi gradient echo (mGRE) and diffusion tensor imaging (DTI) at 15 m resolution ([~] 2.4 million times that of clinical MRI). Scalar images derived from the average DTI and mGRE provide unprecedented contrast in 14 complementary 3D volumes, each highlighting distinct histologic features. The same tissues scanned with LSM and registered into the stereotaxic space provide 17 different molecular cell type stains. The common coordinate framework labels (CCFv3) complete the multimodal atlas. The atlas has been used to correct distortions in the Allen Brain Atlas and harmonize it with Franklin Paxinos. It provides a unique resource for stereotaxic labeling of mouse brain images from many sources.

neuroscience↗

bioRxiv2024

Interpretable antibody-antigen interaction prediction by bridging structure to sequence

With the application of personalized and precision medicine, more precise and efficient antibody drug development technology is urgently needed. Identification of antibody-antigen interactions is crucial to antibody engineering. The time-consuming and expensive nature of wet-lab experiments calls for efficient computational methods. Taking into account the non-overlapping advantage of current structure-dependent and sequence-only computational methods, we propose an interpretable antibody-antigen interaction prediction method, S3AI. The introduction of structural knowledge, combined with explicit modeling of chemical rules, establishes a sequence-to-function route in S3AI, thereby facilitating its perception of intricate molecular interactions through providing route and priors guidance. S3AI significantly and comprehensively outperforms the state-of-the-art models and exhibits excellent generalization when predicting unknown antibody-antigen pairs, surpassing specialized prediction methods designed for out-of-distribution generalization in fair comparisons. More importantly, S3AI captures the universal pattern of antibody-antigen interactions, which not only identifies the CDRs responsible for specific binding to the antigen but also unearths the importance of CDR-H3 for the interaction. Structure-free design and superior performance make S3AI ideal for large-scale, parallelized antibody optimization and screening, enabling the rapid and precise identification of promising candidates within the extensive antibody space.

bioinformatics↗

bioRxiv2024

High Frequency Terahertz Stimulation Alleviates Neuropathic Pain by Inhibiting the Pyramidal Neuron Activity in the Anterior Cingulate Cortex of mice

Neuropathic pain (NP) is caused by a lesion or disease of the somatosensory system and is characterized by abnormal hypersensitivity to stimuli and nociceptive responses to non-noxious stimuli, affecting approximately 7-10% of the general population. However, current first-line drugs like non-steroidal anti-inflammatory agents and opioids have limitations, including dose-limiting side effects, dependence, and tolerability issues. Therefore, developing new interventions for the management of NP is urgent. In this study, we discovered that the high-frequency terahertz stimulation (HFTS) at approximate 36 THz effectively alleviates NP symptoms in mice with spared nerve injury. Computational simulation suggests that the frequency resonates with the carbonyl group in the filter region of Kv1.2 channels, facilitating the translocation of potassium ions. In vivo and in vitro results demonstrate that HFTS reduces the excitability of pyramidal neurons in the anterior cingulate cortex through enhancing the voltage-gated K+ and also the leak K+ conductance. This research presents a novel optical intervention strategy with terahertz waves for the treatment of NP and holds promising application in other nervous system diseases.

neuroscience↗

bioRxiv2024

ATG6 interacting with NPR1 increases Arabidopsis thaliana resistance to Pst DC3000/avrRps4 by increasing its nuclear accumulation and stability

Autophagy-related gene 6 (ATG6) plays a crucial role in plant immunity. Nonexpressor of pathogenesis-related genes1 (NPR1) acts as a signaling hub of plant immunity. However, the relationship between ATG6 and NPR1 is unclear. Here, we find that ATG6 directly interacts with NPR1. ATG6 overexpression significantly increased nuclear accumulation of NPR1. Furthermore, we demonstrate that ATG6 increases NPR1 protein levels and improves its stability. Interestingly, ATG6 promotes the formation of SINCs (SA-induced NPR1 condensates)-like condensates. Additionally, ATG6 and NPR1 synergistically promote the expression of pathogenesis-related genes. Further results showed that silencing ATG6 in NPR1-GFP exacerbates Pst DC3000/avrRps4 infection, while double overexpression of ATG6 and NPR1 synergistically inhibits Pst DC3000/avrRps4 infection. In summary, our findings unveil an interplay of NPR1 with ATG6 and elucidate important molecular mechanisms for enhancing plant immunity. HighlightWe unveil a novel relationship in which ATG6 positively regulates NPR1 in plant immunity.

plant biology↗

bioRxiv2024

Structural architecture of amyloid-β oligomers, curvilinear protofibrils and annular assemblies, imaged by cryo-EM and cryo-ET

Small prefibrillar structures of the amyloid-{beta} peptide (A{beta}) are believed to be central to cytotoxicity in Alzheimers disease, the most common form of dementia. A snapshot of these prefibrillar assemblies has therefore been characterized using a combination of cryo-ET and cryo-EM single particle analysis. This has facilitated an understanding of the relationship between, oligomers, curvilinear protofibrils and annular assemblies. A highly consistent diameter for all curvilinear protofibrils and oligomers of 28 [A], indicates that these assemblies are simply structural extensions from the smaller oligomers. Furthermore, their basic crosssection suggests mature amyloid fibrils might be initiated by the lateral binding of two curvilinear protofibrils. Ab-initio 3D reconstruction also reveals ring-shaped annular assemblies. These possess a central internal channel, ca. 14 [A] in diameter and 54 [A] long, which is capable of traversing lipid membranes. Large conductance recorded using patch-clamp electrophysiology, match the internal diameter of the A{beta} annular architecture.

biophysics↗

bioRxiv2024

Inflammatory pain resolution by mouse serum-derived small extracellular vesicles

Chronic pain is a significant public health issue. Current treatments have limited efficacy and significant side effects, warranting research on alternative strategies for pain management. One approach involves using small extracellular vesicles (sEVs) to transport beneficial biomolecular cargo to aid pain resolution. Exosomes are 30-150 nm sEVs that can carry RNAs, proteins, and lipid mediators to recipient cells via circulation. Exosomes can be beneficial or harmful depending on their source and contents. To investigate the short and long-term effects of mouse serum-derived sEVs in pain modulation, sEVs from naive control or spared nerve injury (SNI) model donor mice were injected intrathecally into naive recipient mice. Basal mechanical thresholds transiently increased in recipient mice. This effect was mediated by opioid signaling as this outcome was blocked by naltrexone. Mass Spectrometry of sEVs detected endogenous opioid peptide leu-enkephalin. A single prophylactic intrathecal injection of sEVs two weeks prior to induction of the pain model in recipient mice delayed mechanical allodynia in SNI model mice and accelerated recovery from inflammatory pain after complete Freunds adjuvant (CFA) injection. ChipCytometry of spinal cord and dorsal root ganglion (DRG) from sEV treated mice showed that prophylactic sEV treatment reduced the number of natural killer (NK) and NKT cells in spinal cord and increased CD206+ anti-inflammatory macrophages in (DRG) after CFA injection. Further characterization of sEVs showed the presence of immune markers suggesting that sEVs can exert immunomodulatory effects in recipient mice to promote the resolution of inflammatory pain. Collectively, these studies demonstrate multiple mechanisms by which sEVs can attenuate pain.

neuroscience↗

bioRxiv2024

Spatiotemporal Changes in Netrin/Dscam1 Signaling Dictate Axonal Projection Direction in Drosophila Small Ventral Lateral Clock Neurons

Axon projection is a spatial and temporal-specific process in which the growth cone receives environmental signals guiding axons to their final destination. However, the mechanisms underlying changes in axonal projection direction without well-defined landmarks remain elusive. Here, we present evidence showcasing the dynamic nature of axonal projections in Drosophilas small ventral lateral clock neurons (s-LNvs). Our findings reveal that these axons undergo an initial vertical projection in the early larval stage, followed by a subsequent transition to a horizontal projection in the early-to-mid third instar larvae. The vertical projection of s-LNv axons correlates with mushroom body calyx expansion, while the s-LNv-expressed Down syndrome cell adhesion molecule (Dscam1) interacts with Netrins to regulate the horizontal projection. During a specific temporal window, locally newborn dorsal clock neurons (DNs) secrete Netrins, facilitating the transition of axonal projection direction in s-LNvs. Our study establishes a compelling in vivo model to probe the mechanisms of axonal projection direction switching in the absence of clear landmarks. These findings underscore the significance of dynamic local microenvironments in the complementary regulation of axonal projection direction transitions.

neuroscience↗

bioRxiv2024

ChineseEEG: A Chinese Linguistic Corpora EEG Dataset for Semantic Alignment and Neural Decoding

An Electroencephalography (EEG) dataset utilizing rich text stimuli can advance the understanding of how the brain encodes semantic information and contribute to semantic decoding in brain-computer interface (BCI). Addressing the scarcity of EEG datasets featuring Chinese linguistic stimuli, we present the ChineseEEG dataset, a high-density EEG dataset complemented by simultaneous eye-tracking recordings. This dataset was compiled while 10 participants silently read approximately 11 hours of Chinese text from two well-known novels. This dataset provides long-duration EEG recordings, along with pre-processed EEG sensor-level data and semantic embeddings of reading materials extracted by a pre-trained natural language processing (NLP) model. As a pilot EEG dataset derived from natural Chinese linguistic stimuli, ChineseEEG can significantly support research across neuroscience, NLP, and linguistics. It establishes a benchmark dataset for Chinese semantic decoding, aids in the development of BCIs, and facilitates the exploration of alignment between large language models and human cognitive processes. It can also aid research into the brains mechanisms of language processing within the context of the Chinese natural language.

neuroscience↗

bioRxiv2024

Nature AND Nurture: Enabling formate-dependent growth in Methanosarcina acetivorans

Methanogenic archaea are crucial in global carbon cycling as around 1 Gt of the potent greenhouse gas, methane, is produced annually. Major contributors belong to the order Methanosarcinales, which contain some of the most versatile methanogens that are capable of acetotrophic, methylotrophic and CO2-reducing methanogenesis. The genetically tractable model methanogen, Methanosarcina acetivorans, by its nature shows versatility in substrate utilization and energy conservation pathways but cannot utilize formate. In this study, we expanded the primary metabolism of M. acetivorans to include formate-dependent methanogenesis. By introducing an exogenous formate dehydrogenase, the two metabolically engineered M. acetivorans strains acquired the capacity for formate-dependent methanogenesis pathways with one capable of formate-dependent methyl-reduction and the other capable of formate-dependent CO2-reduction. Through nurturing the strain capable of CO2-reduction with adaptive laboratory evolution, we were able to enable growth and methanogenesis of M. acetivorans solely on formate, a metabolism only reported in methanogens without cytochromes which are limited by their versatility. M. acetivorans also showed acetogenic potential where the formate-dependent CO2-reducing strain was able to divert {approx} 10% of carbon to acetate instead of methane. Our results show that even though M. acetivorans lacks energy converting hydrogenase and cannot use H2, it has yet-uncharacterized capacity to obtain reduced ferredoxins from oxidizing formate. Our work encourages reevaluation of our understanding of formate utilization in Methanosarcinales. By enabling formate-dependent methanogenesis, we have expanded the substrate spectrum of a versatile model methanogen with cytochromes to include formate as well.

microbiology↗

bioRxiv2024

Hunting for peptide binders of specific targets with data-centric generative language models

Bioactive peptides have become strong candidates for a variety of clinical therapies due to their diverse advantages, which promotes the development of deep generative models for peptide design. Considering that existing methods cannot effectively deal with the conformational flexibility of peptides and are difficult to capture accurate residue-to-residue interaction dependencies, we propose a unified weakly order-dependent autoregressive language modeling architecture (PepGenWOA) for bioactive peptide generative design with tolerating out-of-order input as inductive bias. The superiority of PepGenWOA is demonstrated by generating three classes of therapeutic peptides, including antimicrobial peptides, anticancer peptides, and peptide binders. For antimicrobial and anticancer peptide generation, PepGenWOA not only comprehensively outperforms state-of-the-art baseline models, but also exhibits a significant propensity to incorporate specific types of residues that are beneficial for antimicrobial or anticancer bioactivity. For characteristic-guided peptide binder generation, the pretrained PepGenWOA is fine-tuned with Mixture-of-Experts-style plugins with lifelong learning paradigm, thereby achieving the best trade-off between memory stability for world knowledge and learning plasticity for new downstream tasks. The subsequent structure-based virtual screening anchors the 7 most promising candidates from the mega-scale synthetic sequence space, reducing the number of candidates for in vitro experimental validation by 5 orders of magnitude. A target binding rate of 28.6% with binding specificity further confirms the effectiveness of the fine-tuning strategy. Overall, PepGenWOA is a unified architecture for peptide generative design that can be flexibly customized for different task requirements, thereby harnessing generative language models to reach the "dark space" of biological language.

bioinformatics↗