Biology subjects

Lu, D.

Publications and source records attributed to Lu, D..

At least 55 records · Page 3Linked to original sources

bioRxiv2024

Diverse priming outcomes under conditions of very rare precursor B cells

Rare B cells can have special pathogen-recognition features giving them the potential to make outsized contributions to protective immunity. However, rare naive B cells infrequently participate in immune responses. We investigated how germline-targeting vaccine antigen delivery and adjuvant selection affect priming of exceptionally rare BG18-like HIV broadly neutralizing antibody-precursor B cells (~1 in 50 million) in non-human primates. Only escalating dose (ED) priming immunization using the saponin adjuvant SMNP elicited detectable BG18-like cells in germinal centers (GCs). All groups had strong GC responses, but only ED+SMNP and bolus+SMNP induced BG18-like memory B cells in >50% of animals. One group had vaccine-specific GC responses equivalent to ED+SMNP, but BG18-like memory B cells were rarely detected. Following homologous boosting, BG18-like memory B cells were more frequent in a bolus priming group, but had lower somatic hypermutation and affinities. This outcome was inversely associated with post-prime antibody titers, suggesting antibody feedback can significantly influence rare precursor B cell responses.

immunology↗

bioRxiv2024

A Multi-Property Optimizing Generative Adversarial Network for de novo Antimicrobial Peptide Design

Antimicrobial peptides (AMPs) play a crucial role in developing novel antiinfective drugs due to their broad-spectrum antimicrobial activity and lower likelihood of causing bacterial resistance. However, laboratory synthesis of AMPs is tedious and time-consuming. Existing computational methods have limited capability in optimizing multiple desired properties simultaneously. Here, we propose a Multi-Property Optimizing Generative Adversarial Network (MPOGAN), a feedback-loop framework that iteratively learns from data with multiple desired properties. This approach enables de novo design of AMPs with potent antimicrobial activity, reduced cytotoxicity, and diversity. Through extensive computational tests, MPOGAN exhibits superior performance in optimizing multiple desired properties of generated AMPs. Ten of the most promising candidates are chemically synthesized, with nine showing potent antimicrobial activity against three bacterial strains and low cytotoxicity against eukaryotic cells. MPOGAN offers a powerful computational approach for effective multi-property optimization of AMPs, thereby advancing the field of AI-aided drug discovery.

bioinformatics↗

bioRxiv2024

Substrate tunnel regulates substrate specificity switching in hyaluronan synthase

Hyaluronic acid (HA), a ubiquitous linear polysaccharide in the extracellular matrix of vertebrates and the capsule of certain pathogenic bacteria, is characterized by its unique structure of alternating {beta}-1,3-N-acetylglucosamine and {beta}-1,4-glucuronic acid units. HA is synthesized by Class I hyaluronan synthase (HAS) in the majority of organisms, but the molecular mechanisms determining the alternating sequence of HA remain unclear. Here, we demonstrated that HA synthesized in vitro using Streptococcus equisimilis HAS maintained its alternating sequence, regardless of substrate ratios and concentrations. While the active pocket lacks intrinsic selectivity, a distal allosteric regulation from the transmembrane tunnel is revealed. The lingering HA terminals in the active pocket ensure lower binding energies for alternating substrates through Coulombic repulsion and competitive binding. Moreover, the dynamic C-terminal loop at the substrate tunnel entrance reduces transport distance for alternating substrates. Our findings indicate that HA-substrate interactions and enzyme dynamics in the substrate tunnel collectively govern the alternating substrate specificity of HAS. This study provides the first molecular insight into precise substrate specificity control within a single active pocket during template-independent polymer synthesis.

biophysics↗

bioRxiv2024

Dissecting Regulatory Non-Coding Heart Disease GWAS Loci with High-Resolution 3D Chromatin Interactions Reveals Causal Genes with Pathophysiological Relevance to Heart Failure

Heart failure is caused in part by cardiac remodeling processes that include the death of cardiac myocytes and their replacement by cardiac fibroblasts. We hypothesized that these two cell types may harbor epigenetic contexts in which heart disease-associated non-coding SNPs perturb gene expression relevant to disease. Accordingly, we generated high-resolution Hi-C data layered with chromatin accessibility and transcriptomic information to annotate and link putative distal regulatory elements in heart disease-associated loci to gene promoters. Our analysis identified several target genes with established roles in cardiac fibrosis and/or heart disease (GJA1, TBC1D32, CXCL12, IL6R, and FURIN). Perturb-seq in cardiac fibroblasts to knock out putative regulatory elements confirmed regulatory relationships involving GJA1, CXCL12, and FURIN, as gene editing led to changes in transcriptomic signatures associated with fibroblasts in heart failure. Our results demonstrate how integrative multi-omic approaches can delineate pathophysiologically relevant regulatory circuits that connect protein-coding genes to non-coding genetic variants associated with disease.

genomics↗

bioRxiv2024

Crystal structure and catalytic mechanism of PL35 family glycosaminoglycan lyases with an ultrabroad substrate spectrum

Recently, a new class of glycosaminoglycan (GAG) lyases (GAGases) belonging to PL35 family has been discovered with an ultrabroad substrate spectrum that can degrade three types of uronic acid-containing GAGs (hyaluronic acid, chondroitin sulfate and heparan sulfate) or even alginate. In this study, the structures of GAGase II from Spirosoma fluviale and GAGase VII from Bacteroides intestinalis DSM 17393 were determined at 1.9 and 2.4 [A] resolution, respectively, and their catalytic mechanism was investigated by the site-directed mutant of their crucial residues and molecular docking assay. Structural analysis showed that GAGase II and GAGase VII consist of an N-terminal (/)6 toroid multidomain and a C-terminal two-layered {beta}-sheet domain with Mn2+. Notably, although GAGases share similar folds and catalytic mechanisms with some GAG lyases and alginate lyases, they exhibit higher structural similarity with alginate lyases than GAG lyases, which may present a crucial structural evidence for the speculation that GAG lyases with (/)n toroid and antiparallel {beta}-sheet structures arrived by a divergent evolution from alginate lyases with the same folds. Overall, this study not only solved the structure of PL35 GAG lyases for the first time and investigated their catalytic mechanism, especially the reason why GAGase III can additionally degrade alginate, but also provided a key clue in the divergent evolution of GAG lyases that originated from alginate lyases.

biochemistry↗

bioRxiv2024

Berberine is a novel mitochondrial calcium uniporter (MCU) inhibitor that disrupts MCU-EMRE assembly

The mitochondrial calcium uniporter (MCU) complex mediates Ca2+ entry into mitochondrial, which plays a crucial role in regulating cellular energy metabolism and apoptosis. Dysregulation of MCU is implicated in various diseases, such as neurodegenerative disorders, cardiac diseases and cancer. Despite its importance, developing specific and clinically viable MCU inhibitors has been challenging. Here, we identify Berberine, a well-established drug with a documented safety profile, as a potent MCU inhibitor through a virtual screening of an FDA-approved drug library. Berberine localizes within mitochondria and directly binds to the juxtamembrane loop domain of MCU. This binding disrupts the interaction of MCU with its essential regulator, EMRE, thereby inhibiting rapid Ca2+ entry into the mitochondria. Notably, Berberine pretreatment reduces mitochondrial Ca2+ overload and mitigate ischemia/reperfusion-induced myocardial injury in mice. Our findings establish Berberine as a potent MCU inhibitor, offering a safe therapeutic strategy for diseases associated with dysregulated mitochondrial calcium homeostasis.

cell biology↗

bioRxiv2024

PRMT7 mediated PTEN activation promotes bone formation in female mice

Although the epigenetic mechanisms underlying bone formation are recognized, their specific roles and regulatory pathways remain largely unexplored. In this study, we unveil PRMT7 as a novel epigenetic modulator of MSCs osteogenic commitment. The conditional knockout of Prmt7 in mice reveals significantly impaired osteogenesis and bone regeneration exclusively in females, affecting both long bones and craniofacial structures, with no discernible impact in males. Our findings demonstrate that PRMT7 orchestrates osteogenic differentiation through a methyltransferase-dependent manner. Mechanistically, PRMT7 modulates MSCs osteogenic differentiation through the activation of PTEN. Specifically, PRMT7 augments PTEN transcription by increasing H3R2me1 levels at the PTEN promoter. Furthermore, PRMT7 interacts with the PTEN protein, and its deficiency leads to the ubiquitination and subsequent degradation of nuclear PTEN, revealing an unprecedented pathway. Crucially, PTEN overexpression ameliorates the osteogenic deficits observed in Prmt7-deficient mice. Our research positions PRMT7 as a potential therapeutic target to enhance bone formation and offers novel molecular insights into the PRMT7-PTEN regulatory axis, underscoring its significance in bone biology and regenerative medicine. Subject Categories Developmental Biology, Musculoskeletal System, Epigenetics, Post-translational Modifications

developmental biology↗

bioRxiv2024

Dissecting cell-free DNA fragmentation variation in tumors using cell line-derived xenograft mouse

Cell-free DNA (cfDNA) is increasingly studied for its diverse applications in non-invasive detection. Non-randomly cleaved by nucleases and released into the bloodstream, cfDNA exhibits a variety of intrinsic fragmentation patterns indicative of cell status. Particularly, these fragmentation patterns have recently been demonstrated to be effective in predicting cancer and its tissue-of-origin, owing to increased variation of fragmentation features observed in tumor patients. However, there remains a lack of detailed exploration of altered cfDNA fragmentation profiles in tumors, which consist of a mixture of both non-tumor cfDNA and circulating tumor DNA (ctDNA). Hence, we leveraged the human tumor cell line-derived xenograft (CDX) mouse model, where different tumor cell lines were implanted into different anatomical sites, to isolate pure ctDNA and separately investigate the fragment properties of CDX-induced cfDNA and ctDNA. We found an enrichment of short cfDNA fragments in both CDX-induced cfDNA and ctDNA compared to normal plasma cfDNA, with more elevated short fragments in ctDNA. Moreover, the CDX-induced cfDNA fragmentation features distinguished between CDX models of different tumor cell lines, while the ctDNA fragmentation features conversely discriminate between CDX models of different anatomical sites. The results suggested that both non-tumor cfDNA and ctDNA contribute to the increased variation observed in tumors, and that cfDNA fragmentation may be highly variable and susceptible to regulations by both original cells and cells within the local niche.

cancer biology↗

bioRxiv2024

Causal Cortical and Thalamic Connections in the Human Brain

The brains functional architecture is intricately shaped by causal connections between its cortical and subcortical structures. Here, we studied 27 participants with 4864 electrodes implanted across the anterior, mediodorsal, and pulvinar thalamic regions, and the cortex. Using data from electrical stimulation procedures and a data-driven approach informed by neurophysiological standards, we dissociated three unique spectral patterns generated by the perturbation of a given brain area. Among these, a novel waveform emerged, marked by delayed-onset slow oscillations in both ipsilateral and contralateral cortices following thalamic stimulations, suggesting a mechanism by which a thalamic site can influence bilateral cortical activity. Moreover, cortical stimulations evoked earlier signals in the thalamus than in other connected cortical areas suggesting that the thalamus receives a copy of signals before they are exchanged across the cortex. Our causal connectivity data can be used to inform biologically-inspired computational models of the functional architecture of the brain.

neuroscience↗

bioRxiv2024

Identifying potential risk genes for clear cell renal cell carcinoma with deep reinforcement learning

Clear cell renal cell carcinoma (ccRCC) is the most prevalent type of renal cell carcinoma. However, our understanding of ccRCC risk genes remains limited. This gap in knowledge poses significant challenges to the effective diagnosis and treatment of ccRCC. To address this problem, we propose a deep reinforcement learning-based computational approach named RL-GenRisk to identify ccRCC risk genes. Distinct from traditional supervised models, RL-GenRisk frames the identification of ccRCC risk genes as a Markov decision process, combining the graph convolutional network and Deep Q-Network for risk gene identification. Moreover, a well-designed data-driven reward is proposed for mitigating the lim-itation of scant known risk genes. The evaluation demonstrates that RL-GenRisk outperforms existing methods in ccRCC risk gene identification. Additionally, RL-GenRisk identifies ten novel ccRCC risk genes. We successfully validated epidermal growth factor receptor (EGFR), corroborated through independent datasets and biological experimentation. This approach may also be used for other diseases in the future.

bioinformatics↗

bioRxiv2024

DiffuST: a latent diffusion model for spatial transcriptomics denoising

Spatial transcriptomics technologies have enabled comprehensive measurements of gene expression profiles while retaining spatial information and matched pathology images. However, noise resulting from low RNA capture efficiency and experimental steps needed to keep spatial information may corrupt the biological signals and obstruct analyses. Here, we develop a latent diffusion model DiffuST to denoise spatial transcriptomics. DiffuST employs a graph autoencoder and a pre-trained model to extract different scale features from spatial information and pathology images. Then, a latent diffusion model is leveraged to map different scales of features to the same space for denoising. The evaluation based on various spatial transcriptomics datasets showed the superiority of DiffuST over existing denoising methods. Furthermore, the results demonstrated that DiffuST can enhance downstream analysis of spatial transcriptomics and yield significant biological insights.

genomics↗

bioRxiv2024

Activity-Dependent Remodeling of Corticostriatal Axonal Boutons During Motor Learning

Motor skill learning induces long-lasting synaptic plasticity at not only the inputs, such as dendritic spines1-4, but also at the outputs to the striatum of motor cortical neurons5,6. However, very little is known about the activity and structural plasticity of corticostriatal axons during learning in the adult brain. Here, we used longitudinal in vivo two-photon imaging to monitor the activity and structure of thousands of corticostriatal axonal boutons in the dorsolateral striatum in awake mice. We found that learning a new motor skill induces dynamic regulation of axonal boutons. The activities of motor corticostriatal axonal boutons exhibited selectivity for rewarded movements (RM) and un-rewarded movements (UM). Strikingly, boutons on the same axonal branches showed diverse responses during behavior. Motor learning significantly increased the fraction of RM boutons and reduced the heterogeneity of bouton activities. Moreover, motor learning-induced profound structural dynamism in boutons. By combining structural and functional imaging, we identified that newly formed axonal boutons are more likely to exhibit selectivity for RM and are stabilized during motor learning, while UM boutons are selectively eliminated. Our results highlight a novel form of plasticity at corticostriatal axons induced by motor learning, indicating that motor corticostriatal axonal boutons undergo dynamic reorganization that facilitates the acquisition and execution of motor skills.

neuroscience↗

bioRxiv2024

Enhancing Gene Expression Representation and Drug Response Prediction with Data Augmentation and Gene Emphasis

Representation learning for tumor gene expression (GEx) data with deep neural networks is limited by the large gene feature space and the scarcity of available clinical and preclinical data. The translation of the learned representation between these data sources is further hindered by inherent molecular differences. To address these challenges, we propose GExMix (Gene Expression Mixup), a data augmentation method, which extends the Mixup concept to generate training samples accounting for the imbalance in both data classes and data sources. We leverage the GExMix-augmented training set in encoder-decoder models to learn a GEx latent representation. Subsequently, we combine the learned representation with drug chemical features in a dual-objective enhanced gene-centric drug response prediction, i.e., reconstruction of GEx latent embeddings and drug response classification. This dual-objective design strategically prioritizes gene-centric information to enhance the final drug response prediction. We demonstrate that augmenting training samples improves the GEx representation, benefiting the gene-centric drug response prediction model. Our findings underscore the effectiveness of our proposed GExMix in enriching GEx data for deep neural networks. Moreover, our proposed gene-centricity further improves drug response prediction when translating preclinical to clinical datasets. This highlights the untapped potential of the proposed framework for GEx data analysis, paving the way toward precision medicine.

bioinformatics↗

bioRxiv2024

The phylogenetic position of the Yunxian cranium elucidates the origin of Dragon Man and the Denisovans

Diverse Middle Pleistocene forms of Homo coexisted in Africa, Europe, and Asia, and its controversial whether these fossil humans represent different species or clades. The [~]1 Ma old Yunxian 2 fossil from China is crucial for understanding the cladogenesis of Homo and the origin of Homo sapiens. Here, we restored and reconstructed the distorted Yunxian 2 cranium using new technology. The results show that this cranium displays mosaic features of plesiomorphy and apomorphy. Geometric-morphometric, phylogenetic and Bayesian tip-dating analyses including the reconstructed Yunxian 2 suggest that it is an early member of the Asian Homo longi clade, which probably includes the Denisovans, and is the sister group to the Homo sapiens clade. Both the H. sapiens and H. longi clades had deep roots extending beyond the Middle Pleistocene, and the basal position of the Yunxian fossil cranium suggests that it represents a population lying close to the last common ancestor of the two clades. One-Sentence SummaryThe newly-reconstructed Yunxian 2 cranium represents a basal member of the Homo longi and Denisovan clade, and probably lies close to the last common ancestor of that clade and the clade of H. sapiens.

evolutionary biology↗

bioRxiv2024

Cannabinoid receptor 1 positive allosteric modulator ZCZ011 shows differential effects on behavior and the endocannabinoid system in HIV-1 Tat transgenic female and male mice

The cannabinoid receptor type 1 (CB1R) is a promising therapeutic target for various neurodegenerative diseases, including HIV-1-associated neurocognitive disorder (HAND). However, the therapeutic potential of CB1R by direct activation is limited due to its psychoactive side effects. Therefore, research has focused on indirectly activating the CB1R by utilizing positive allosteric modulators (PAMs). Studies have shown that CB1R PAMs (ZCZ011 and GAT211) are effective in mouse models of Huntingtons disease and neuropathic pain, and hence, we assess the therapeutic potential of ZCZ011 in a well-established mouse model of neuroHIV. The current study investigates the effect of chronic ZCZ011 treatment (14 days) on various behavioral paradigms and the endocannabinoid system in HIV-1 Tat transgenic female and male mice. Chronic ZCZ011 treatment (10 mg/kg) did not alter body mass, locomotor activity, or anxiety-like behavior regardless of sex or genotype. However, differential effects were noted in hot plate latency, motor coordination, and recognition memory in female mice only, with ZCZ011 treatment increasing hot plate latency and improving motor coordination and recognition memory. Only minor effects or no alterations were seen in the endocannabinoid system and related lipids except in the cerebellum, where the effect of ZCZ011 was more pronounced in female mice. Moreover, AEA and PEA levels in the cerebellum were positively correlated with improved motor coordination in female mice. In summary, these findings indicate that chronic ZCZ011 treatment has differential effects on antinociception, motor coordination, and memory, based on sex and HIV-1 Tat expression, making CB1R PAMs potential treatment options for HAND without the psychoactive side effects.

neuroscience↗

bioRxiv2024

Simultaneous detection of pathogens and antimicrobial resistance genes with the open source, cloud-based, CZ ID pipeline

Antimicrobial resistant (AMR) pathogens represent urgent threats to human health, and their surveillance is of paramount importance. Metagenomic next generation sequencing (mNGS) has revolutionized such efforts, but remains challenging due to the lack of open-access bioinformatics tools capable of simultaneously analyzing both microbial and AMR gene sequences. To address this need, we developed the Chan Zuckerberg ID (CZ ID) AMR module, an open-access, cloud-based workflow designed to integrate detection of both microbes and AMR genes in mNGS and whole-genome sequencing (WGS) data. It leverages the Comprehensive Antibiotic Resistance Database and associated Resistance Gene Identifier software, and works synergistically with the CZ ID short-read mNGS module to enable broad detection of both microbes and AMR genes. We highlight diverse applications of the AMR module through analysis of both publicly available and newly generated mNGS and WGS data from four clinical cohort studies and an environmental surveillance project. Through genomic investigations of bacterial sepsis and pneumonia cases, hospital outbreaks, and wastewater surveillance data, we gain a deeper understanding of infectious agents and their resistomes, highlighting the value of integrating microbial identification and AMR profiling for both research and public health. We leverage additional functionalities of the CZ ID mNGS platform to couple resistome profiling with the assessment of phylogenetic relationships between nosocomial pathogens, and further demonstrate the potential to capture the longitudinal dynamics of pathogen and AMR genes in hospital acquired bacterial infections. In sum, the new AMR module advances the capabilities of the open-access CZ ID microbial bioinformatics platform by integrating pathogen detection and AMR profiling from mNGS and WGS data. Its development represents a critical step toward democratizing pathogen genomic analysis and supporting collaborative efforts to combat the growing threat of AMR.

microbiology↗

bioRxiv2024

AncestryPainter 2.0: Visualizing ancestry composition and admixture history graph

To effectively depict the results of population genetics studies, it is essential to present ancestry composition and genetic distance. The growing amount of genomic data prompted us to design AncestryPainter 1.0, a Perl program to display the ancestry composition of numerous individuals using a rounded graph. Motivated by the requests of users in practical applications, we updated AncestryPainter to version 2.0 by coding in an R package and improving the layout, providing more options and compatible statistical functions for graphing. In particular, AncestryPainter 2.0 implements a method admixture history graph (AHG) to infer the admixture sequence of multiple ancestry populations, and allows for multiple pie charts at the center of the graph to display the ancestry composition of more than one target population. We also introduced an additional graphing module to visualize genetic distance through radial bars of varying lengths surrounding a core. Visualization functions per se have been enhanced in this update as well. Furthermore, AncestryPainter 2.0 includes two statistical modules to 1) merge ancestry proportion matrices and 2) infer admixture sequences through correlation analyses. AncestryPainter 2.0 is publicly available at https://github.com/Shuhua-Group/AncestryPainterV2 and https://pog.fudan.edu.cn/#/Software.

genetics↗

bioRxiv2024

Development of a First-in-Class RIPK1 Degrader to Enhance Antitumor Immunity

The scaffolding function of receptor interacting protein kinase 1 (RIPK1) confers intrinsic and extrinsic resistance to immune checkpoint blockades (ICBs) and has emerged as a promising target for improving cancer immunotherapies. To address the challenge posed by a poorly defined binding pocket within the intermediate domain, we harnessed proteolysis targeting chimera (PROTAC) technology to develop a first-in-class RIPK1 degrader, LD4172. LD4172 exhibited potent and selective RIPK1 degradation both in vitro and in vivo. Degradation of RIPK1 by LD4172 triggered immunogenic cell death (ICD) and enriched tumor-infiltrating lymphocytes and substantially sensitized the tumors to anti-PD1 therapy. This work reports the first RIPK1 degrader that serves as a chemical probe for investigating the scaffolding functions of RIPK1 and as a potential therapeutic agent to enhance tumor responses to immune checkpoint blockade therapy.

pharmacology and toxicology↗