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Guo, D.

Publications and source records attributed to Guo, D..

At least 37 records · Page 2Linked to original sources

Multi-omics characterization of the skin microbiota reveals the anti-aging roles of Stenotrophomonas maltophilia

Shifts in the skin microbiome have shown a close link to chronological age. However, the contribution of skin microbiome in skin aging phenotypes remains unclear. To explore this, we performed phenotypic, metabolomic, metagenomic, and functional analyses on a cohort with divergent skin aging phenotypes. Genome-scale metabolic models (GEMs) integrated with metabolomic analysis revealed that Stenotrophomonas maltophilia, enriched in the younger group (categorized by AI-predicted age and skin elasticity), utilizes the glutathione cycle to maintain redox homeostasis. Cellular experiments showed its metabolites enhanced GSH synthesis and alleviated oxidative stress-induced skin aging by upregulating key genes in fibroblasts, including GCLM, PGD, SOD2, and NQO1. Additionally, GEMs highlighted its potential anti-aging roles in regulating host metabolic pathways involving betaine, lysolecithin, and porphyrin. In parallel, Acinetobacter guillouiae was found to influence host melanin metabolism by degrading dopamine (DA) and 3-methoxytyramine (3-MT), offering potential therapeutic strategies for mitigating pigmentation. Our findings highlight the dynamic interplay between skin microbiota and the host in aging, offering new insights for designing targeted anti-aging interventions.

microbiology↗

Ammonia-mediated Conformational Dynamics in SCAP for SREBP Activation

Cholesterol homeostasis is regulated by the sterol regulatory element-binding protein (SREBP) pathway, with the membrane-embedded SREBP-cleavage-activating protein (SCAP) and insulin-inducible gene protein (Insig)-1/2 acting as sterol sensors. Our previous studies unveiled a critical role of ammonia in activating the SREBP pathway. Here, we performed extensive molecular dynamics (MD) simulations to elucidate the structural mechanisms through which ammonia binding triggers SCAP/Insig dissociation and subsequently activate SREBP. The SCAP S4 helix exists in two distinct conformations: a partially unfolded S4 and an intact S4; the transition between these states may constitute a crucial aspect of SCAP activation. We first studied the binding of ammonia to SCAP in different S4 conformational states. We then explored how the binding of ammonia or 25-hydroxycholesterol (25-HC) affects the conformational transition of S4 using targeted MD simulations. Finally, we performed comparative analysis of the 25-HC-bound inactive SCAP and the ammonia-bound active SCAP. Collectively, our findings highlight the importance of S4 helix conformation in activating the SCAP protein. Our simulations suggest that ammonia and 25-HC act as an agonist and antagonist of SCAP activation, respectively. Specifically, ammonia binding facilitates the transition of S4 from the unfolded to the straight conformation, triggering subsequent conformational changes in the transmembrane domain of SCAP. These changes eventually promote the SCAP/Insig dissociation and alter the position of the MELADL motif at the membrane surface. Significant StatementCellular cholesterol homeostasis is tightly regulated by the SREBP pathway, which relies on the membrane proteins SCAP and Insig to sense sterol levels. While ammonia has recently been identified as a novel activator of this pathway, its structural mechanism of action remained unknown. Here, extensive molecular dynamics simulations reveal that ammonia binding promotes a critical conformational transition in the SCAP S4 helix, facilitating SCAP activation and its dissociation from Insig. Our findings show that ammonia and cholesterol act as opposing modulators--agonist and antagonist--of SCAP activity. This work uncovers a previously unrecognized structural switch in SCAP and provides new molecular insight into small-molecule regulation of cholesterol sensing.

molecular biology↗

Efficient Cas9 nuclease-based editing in skeletal muscle via lipid nanoparticle delivery

Gene editing holds great promise for muscular dystrophy treatment, but the rapid evaluation of different editing modalities in skeletal muscle in vivo remains challenging due to lack of simple, effective delivery tools. Here we demonstrate that selective organ targeting (SORT) lipid nanoparticles (LNP) encapsulating optimized Cas9 cargo can facilitate efficient, local delivery to skeletal muscles achieving editing rates [≥]35% and restore protein expression for a proof-of-concept muscular dystrophy target. Interestingly, efficient editing in skeletal muscle was observed despite a strong adaptive immune response to repeat dosing of the Cas9 LNPs. High efficiency editing mediated by LNP-based delivery of Cas9 to skeletal muscle permitted detailed analysis of insertion and deletion (InDel) outcomes in vivo for a set of potential therapeutic target sites, which differed substantially from InDel outcomes observed in proliferating cells in one specific instance. Overall, our findings on enhanced LNP delivery of Cas9, platform-specific immune responses, and differential editing patterns observed between in vitro and in vivo models provide valuable insights that should inform the development of gene editing therapeutics for neuromuscular diseases. One Sentence SummarySORT LNPs permitted efficient Cas9-mediated repair of a pathogenic allele in skeletal muscle in a mouse model of LGMDR7.

molecular biology↗

Multi-step antibody class switching in a primary human response is restricted after IGHG2 and dependent on B cell maturation stage.

Class switch recombination (CSR) allows the formation of functionally specialized antibodies. Understanding of CSR dynamics is key for better design and prediction of vaccines to protect mucosal surfaces. To investigate CSR in a primary human immune response under a controlled setting, we sampled healthy volunteers without COVID-19 history every other day during the first three weeks after SARS-CoV-2 vaccination, with additional time points up to six months. Leveraging bulk and single-cell B cell receptor repertoires, single-cell transcriptomics, and immunophenotyping, we uncover paradigm-shifting insights into CSR. Newly activated B cells produce sterile transcripts of all antibody isotype constant regions (IGHC) simultaneously up to IGHG2, challenging the view that sterile transcription occurs for only a single IGHC gene at a time. CSR follows a multistep progression along the IGHC locus; in this challenge vaccine-induced B cells switch from IGHM to IGHG3 and IGHG1, followed by a subsequent switching to IGHA1 and IGHG2 after secondary immunization. IGHA2 clones require pre-switching to IGHA1 clones. Notably, switching tendency, measured by IGHC sterile transcription, is memory B cell subtype dependent, particularly beyond IGHG2. Contrary to other vaccines, antigen-specific B cells are enriched in DN2, Cmem2 and DN4 subtypes after immunization. We also observe a temporal decoupling of CSR and somatic hypermutation (SHM), with the latter detectable only after six months post-immunization. Our data describes the dynamics between CSR, SHM, sterile transcription and B cell memory development during a human primary response, challenges textbook models of CSR and offers new insights to aid control of CSR direction. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=188 HEIGHT=200 SRC="FIGDIR/small/652638v1_ufig1.gif" ALT="Figure 1"> View larger version (49K): org.highwire.dtl.DTLVardef@785769org.highwire.dtl.DTLVardef@b2c54eorg.highwire.dtl.DTLVardef@b78c72org.highwire.dtl.DTLVardef@65b5aa_HPS_FORMAT_FIGEXP M_FIG C_FIG One Sentence SummaryClass switch recombination occurs independently of somatic hypermutation and in a multistep fashion up to IGHG2 during a primary response in humans.

immunology↗

Tuning antibody stability and function by rational designs of framework mutations

Artificial intelligence and machine learning models have been developed to engineer antibodies for specific recognition of antigens, however these approaches often focus on the antibody complementarity determining region (CDR) whilst ignoring the immunoglobulin framework (FW) which provides structural rigidity and support for the flexible CDR loops. Here we present an integrated computational-experimental workflow, combining static structure analyses, molecular dynamics simulations and in vitro physicochemical and functional assays to generate rational designs of FW mutations for modulating antibody stability and activity. We first showed that recent antibody-specific language models lacked insights in FW mutagenesis, in comparison to approaches which utilised antibody structure information. Using the widely-used breast cancer therapeutic trastuzumab as a use case, we designed stabilising mutants which were distal to the CDR and preserved the antibodys functionality to engage its cognate antigen (HER2) and induce antibody-dependent cellular cytotoxicity (ADCC). Interestingly, guided by local backbone motions predicted using molecular dynamics simulations, we designed a FW mutation on the trastuzumab light chain which retained antigen-binding effects but lost Fab-mediated and Fc-mediated effector functions. This highlighted effects of FW on immunological functions engendered in distal areas of the antibody, and the importance to consider attributes other than binding affinity when assessing antibody function. Our approach incorporates interdomain dynamics and distal effects between FW and the Fc domains, expands the scope of antibody engineering beyond the CDR, and underscores the importance of a holistic perspective that considers the entire antibody structure as a whole in optimising antibody stability, developability and function.

immunology↗

Genome modeling and design across all domains of life with Evo 2

All of life encodes information with DNA. While tools for sequencing, synthesis, and editing of genomic code have transformed biological research, intelligently composing new biological systems would also require a deep understanding of the immense complexity encoded by genomes. We introduce Evo 2, a biological foundation model trained on 9.3 trillion DNA base pairs from a highly curated genomic atlas spanning all domains of life. We train Evo 2 with 7B and 40B parameters to have an unprecedented 1 million token context window with single-nucleotide resolution. Evo 2 learns from DNA sequence alone to accurately predict the functional impacts of genetic variation--from noncoding pathogenic mutations to clinically significant BRCA1 variants--without task-specific finetuning. Applying mechanistic interpretability analyses, we reveal that Evo 2 autonomously learns a breadth of biological features, including exon-intron boundaries, transcription factor binding sites, protein structural elements, and prophage genomic regions. Beyond its predictive capabilities, Evo 2 generates mitochondrial, prokaryotic, and eukaryotic sequences at genome scale with greater naturalness and coherence than previous methods. Guiding Evo 2 via inference-time search enables controllable generation of epigenomic structure, for which we demonstrate the first inference-time scaling results in biology. We make Evo 2 fully open, including model parameters, training code, inference code, and the OpenGenome2 dataset, to accelerate the exploration and design of biological complexity.

genomics↗

ImmunoMatch learns and predicts cognate pairing of heavy and light immunoglobulin chains

The development of stable antibodies formed by compatible heavy (H) and light (L) chain pairs is crucial in both the in vivo maturation of antibody-producing cells and the ex vivo designs of therapeutic antibodies. We present here a novel machine learning framework, ImmunoMatch, for deciphering the molecular rules governing the pairing of antibody chains. Fine-tuned on an antibody-specific language model, ImmunoMatch learns from paired H and L sequences from single human B cells to distinguish cognate H-L pairs and randomly paired sequences. We find that the predictive performance of ImmunoMatch can be augmented by training separate models on the two types of antibody L chains in humans,{kappa} and{lambda} , in line with the in vivo mechanism of B cell development in the bone marrow. Using ImmunoMatch, we illustrate that refinement of H-L chain pairing is a hallmark of B cell maturation in both healthy and disease conditions. We find further that ImmunoMatch is sensitive to sequence differences at the H-L interface. ImmunoMatch focusses on H-L chain pairing as a specific, under-explored problem in antibody developability, and facilitates the computational assessment and modelling of stably assembled immunoglobulins towards large-scale optimisation of efficacious antibody therapeutics.

bioinformatics↗

In Silico Discovery of Small Molecule Modulators Targeting Ebola Virus VP 35 and VP 40 protein

Ebola virus (EBoV) proteins VP35 and VP40 are acknowledged as significant pharmacological targets for disrupting viral replication, virion assembly, and the budding process from host cells. We employed molecular docking based throughput virtual screening (HTVS), standard precision (SP), and extra precision (XP) docking to discover candidate compounds. Subsequently, molecular dynamics simulations, and ADMET analyses to identify potential small molecular compounds that could inhibit the Ebola virus. Among 210,590 compounds from the SPECS database, we found the compounds AO-022/43452438, AN-465/43369333, and AN-465/43369198 were optimal candidates for the EBOV-VP35 protein, while AN-465/43369160, AN-465/4341136, and AN-465/43369952 also emerged as optimal compounds for the EBOV-VP40 protein. Furthermore, we employed the energy decomposition technique, MM-GB/SA, to identify the top ten amino acids that significantly contribute to the binding interactions. ADMET result implicated that the six compounds have potential druggability, but special attention should be given to AN-465/43369333 due to potential cardiac toxicity. In conclusions, the six compounds and their key interacting amino acid sites identified in this study may serve as a valuable platform for the future development of novel therapeutics targeting the Ebola virus.

bioinformatics↗

Comprehensive Infectome Analysis Reveals Diverse Infectious Agents with Zoonotic Potential in Wildlife

Understanding wildlife-pathogen interactions is crucial for mitigating zoonotic risk. Through meta-transcriptomic sequencing we profiled the infectomes of 1,922 samples from 67 mammalian species across China, uncovering a remarkable diversity of viral, bacterial, fungal, and parasitic pathogens. Of the 195 pathogens identified, 62 were novel, including a bi- segmented coronavirus in diseased lesser pandas, which we propose represents a new genus - Zetacoronavirus. The orders Carnivora and Rodentia exhibited the highest pathogen diversity and were implicated in numerous host-jumping events. Comparative analysis of diseased versus healthy animals revealed a trend of higher pathogen loads in the former, with possible differences in tissue tropisms. In total, 48 zoonotic and 17 epizootic pathogens were identified, with frequent cross-species transmission, emphasizing the potential for emerging public health threats. This study highlights the urgent need for wildlife pathogen surveillance to inform proactive disease management strategies.

microbiology↗

In vivo imaging of inferior olive neurons reveals roles of co-activation and cerebellar feedback in olivocerebellar signaling

Complex spikes (CSs), generated by inferior olive (IO) neurons, are foundational to most theories of cerebellar function and motor learning. Despite their importance, recordings from IO neurons in living animals have been limited to single-electrode methods, providing no insights into multineuron dynamics within intact circuits. Here, we used a novel ventral surgical approach that allows calcium imaging-based monitoring of multicellular activity in the IO of anesthetized mice. This method provides direct optical access to the ventral medulla, enabling simultaneous recording of spontaneous and sensory-evoked activity within localized clusters of IO neurons, specifically in the principal (PO) and dorsal accessory olives (DAO). Our findings reveal that spontaneous activity rates and event magnitudes differ between the PO and DAO, consistent with observations from cerebellar cortex recordings in zebrin-positive (Z+) and zebrin-negative (Z-) zones, respectively. We further demonstrate that spontaneous event amplitudes are influenced by co-activation among neighboring neurons, so that events occurring in clusters are larger than single ones. Event co-activation is more pronounced in the PO than in the DAO, potentially explaining the differences in complex spike sizes observed in Z+ and Z-zones. Sensory-evoked events induced by periocular airpuff stimulation were larger than spontaneous ones, as expected. However, this difference diminishes when accounting for the higher levels of co-activation during sensory stimulation. By comparing spontaneous and sensory-evoked events categorized as clustered or single, we find no intrinsic differences in amplitudes, emphasizing the role of co-activation in shaping event magnitude. Next, we optogenetically activated cerebellar nucleo-olivary (N-O) axons, a pathway central to theories of CS generation. To our surprise, while this robustly suppressed spontaneous IO activity, sensory-evoked events showed no reduction in either their probability or waveform. Our findings suggest that the traditional view of the N-O pathway as purely inhibitory or desynchronizing might be complemented with selective suppression of background activity while preserving sensory-driven responses. Together with the role of local co-activation in shaping IO event magnitudes, this work offers new insight into the timing and variation in complex spikes and their functional significance for behavior.

neuroscience↗

Small mammals in biodiversity hotspot harbor viruses of epidemic potential

Metagenomic sequencing has transformed our understanding of viral diversity in wildlife and its threat to human health. Despite this progress, many studies have lacked systematic and ecologically informed sampling, which has left numerous potentially emergent viruses undiscovered, and the drivers of their ecology and evolution poorly understood. We conducted an extensive analysis of viruses in the lung, spleen, and gut of 1,688 animals from 38 mammalian species across 428 sites in Yunnan, China--a hotspot for zoonotic diseases. We identified 162 mammalian viral species, including 102 novel species and 24 posing potential risks to humans due to their relationships with known pathogens associated with serious diseases and their ability to cross major host species barriers. Our findings offer an in-depth view of virus organotropism, cross-species transmission, host sharing patterns, and the ecological factors influencing viral evolution, all of which are critical for anticipating and mitigating future zoonotic outbreaks.

microbiology↗

SegFinder: an automated tool for identifying RNA virus genome segments through co-occurrence in multiple sequenced samples

Metagenomic sequencing has expanded the RNA virosphere, but many identified viral genomes remain incomplete, especially for segmented viruses. Traditional methods relying on sequence homology struggle to identify highly divergent segments and group them confidently within a single virus species. To address this, we developed a new bioinformatic tool - SegFinder - that identifies virus genome segments based on their common co-occurrence at similar abundance within segmented viruses. SegFinder successfully re-discovered all segments from a test data set of individual mosquito transcriptomes, which was also used to establish parameter thresholds for reliable segment identification. Using these optimal parameters, we applied SegFinder to 858 libraries from eight metagenomic sequencing projects, including vertebrates, invertebrates, plants, and environmental samples. Furthermore, we identified 108 (excluding RdRP) unique viral genome segments, of which 55 were novel and 32 showed no recognizable sequence homology to known sequences but which were verified by the presence of conserved sequences at the genome termini. SegFinder is also able to identify segmented genome structures in viruses previously considered to be predominantly unsegmented, and in doing so expanded the number of known families and orders of segmented RNA viruses, making it a valuable tool in an era of large-scale parallel sequencing.

bioinformatics↗

MYH11 rare variant augments aortic growth and induces cardiac hypertrophy and heart failure with pressure overload

Smooth muscle cell-specific myosin heavy chain, encoded by MYH11, is selectively expressed in smooth muscle cells (SMCs). Pathogenic variants in MYH11 predispose to a number of disorders, including heritable thoracic aortic disease associated with patent ductus arteriosus, visceral myopathy, and megacystis-microcolon-intestinal hypoperistalsis syndrome. Rare variants of uncertain significance occur throughout the gene, including MYH11 p.Glu1892Asp, and we sought to determine if this variant causes thoracic aortic disease in mice. Genomic editing was used to generate Myh11E1892D/E1892D mice. Wild-type (WT) and mutant mice underwent cardiovascular phenotyping and with transverse aortic constriction (TAC). Myh11E1892D/E1892D and WT mice displayed similar growth, blood pressure, root and ascending aortic diameters, and cardiac function up to 13 months of age, along with similar contraction and relaxation on myographic testing. TAC induced hypertension similarly in Myh11E1892D/E1892D and WT mice, but mutant mice showed augmented ascending aortic enlargement and increased elastic fragmentation on histology. Unexpectedly, male Myh11E1892D/E1892D mice two weeks post-TAC had decreased ejection fraction, stroke volume, fractional shortening, and cardiac output compared to similarly treated male WT mice. Importantly, left ventricular mass increased significantly due to primarily posterior wall thickening, and cardiac histology confirmed cardiomyocyte hypertrophy and increased collagen deposition in the myocardium and surrounding arteries. These results further highlight the clinical heterogeneity associated with MYH11 rare variants. Given that MYH11 is selectively expressed in SMCs, these results implicate a role of vascular SMCs in the heart contributing to cardiac hypertrophy and failure with pressure overload. Author SummaryIn this study, we explore the impact of a specific genetic variant, MYH11 p.Glu1892Asp, on the heart and blood vessels in mice. The MYH11 gene is crucial for smooth muscle cells, which are found in the walls of blood vessels and play an important role in various vascular diseases. We created mice with this genetic variant to see if it would lead to thoracic aortic disease, a condition affecting the main artery from the heart. We found that mice with the variant were similar to normal mice in many aspects, such as growth, blood pressure, and heart function, for up to 13 months. However, when we induced high blood pressure in the mice, the mutant mice showed more significant enlargement of the aorta and damage to the elastic fibers in the aortic walls. Interestingly, male mutant mice also developed heart problems, such as reduced heart pumping ability and increased heart muscle thickness, after the high blood pressure challenge. This was accompanied by signs of heart muscle cell enlargement and increased tissue stiffness. These findings suggest that this rare MYH11 variant can contribute to a range of heart and vascular issues, particularly under conditions of pressure overload, and highlight the importance of smooth muscle cells in the development of these problems.

genetics↗

First-male sperm precedence in polyandrous Spodoptera frugiperda allows sterile males induce population suppression

Males respond to intense sperm competition by adapting reproductive strategies to promote fertilization success, which is critical for population reproduction. Thus, investigating the patterns and mechanisms of sperm competition is crucial for the development and application of pest population management techniques. In this study, we analyzed the sperm precedence pattern of a major pest, the fall armyworm, and used this pattern to manage the pest population. First, we found that females had a post-mating response and did not gain direct benefit through multiple mating. Next, in a double mating experiment, we used a molecular marker created by CRISPR/Cas9 to determine that most females use only the sperm of the first male to produce offspring. To further explore the role of fertilizing sperm in sperm competition, we constructed a sterile male line with eupyrene sperm defect by knocking out the B2t gene. Interestingly, two round mating assays showed that first mating with B2t-null males inhibited sperm fertilization from a second wild-type male. In other words, prior mating with B2t-null males significantly reduced the fertility and fecundity of females. Based on this finding, we continued to explore whether sperm-deficient sterile males could be used in the management of FAW populations. Cage experiments and mathematical modeling analyses showed that the release of excess B2t-null males induced population suppression. Our study expands our knowledge of sperm competition patterns in lepidopteran. In addition, our study provides a paradigm to develop and apply genetic control methods based on sperm competition outcome in polyandrous pests. SignificanceSperm competition is essential for maintaining population reproduction. Understanding patterns and mechanisms of sperm competition facilitates the development of appropriate pest genetic control methods. Here, we describe that a globally major pest, the fall armyworm displays the first-male sperm precedence pattern. Interestingly, first mating with B2t-null males, which produces non-functional eupyrene sperm, significantly reduces the fertility and fecundity of females. That means that the ejaculate of the first male, even if its eupyrene sperm are defective, can inhibit sperm fertilization from a second wild-type male. Based on this, the release of excess B2t-null males significantly suppresses FAW populations. These results suggest that future development of genetic control techniques based on targeting nucleated sperm can effectively control FAW populations.

zoology↗

VirID: Beyond Virus Discovery - An Integrated Platform for Comprehensive RNA Virus Characterization

RNA viruses exhibit vast phylogenetic diversity and can significantly impact public health and agriculture. However, current bioinformatics tools for viral discovery from metagenomic data frequently generate false positive virus results, overestimate viral diversity, and misclassify virus sequences. Additionally, current tools often fail to determine virus-host associations, which hampers investigation of the potential threat posed by a newly detected virus. To address these issues we developed VirID, a software tool specifically designed for the discovery and characterization of RNA viruses from metagenomic data. The basis of VirID is a comprehensive RNA-dependent RNA polymerase (RdRP) database to enhance a workflow that includes RNA virus discovery, phylogenetic analysis, and phylogeny-based virus characterization. Benchmark tests on a simulated data set demonstrated that VirID had high accuracy in profiling viruses and estimating viral richness. In evaluations with real-world samples, VirID was able to identity RNA viruses of all type, but also provided accurate estimations of viral genetic diversity and virus classification, as well as comprehensive insights into virus associations with humans, animals, and plants. VirID therefore offers a robust tool for virus discovery and serves as a valuable resource in basic virological studies, pathogen surveillance, and early warning systems for infectious disease outbreaks.

bioinformatics↗

Decoding the anti-aging effect of retinol in reshaping the human skin microbiome niches

Retinol has been widely added to skincare products due to its ability to promote the proliferation of skin keratinocytes and regulate skin cell collagen expression. While it is known the skin harbors a myriad of commensal bacteria, the impact of retinol on the skin microbiome, as well as the role of the skin microbiome in mediating the anti-aging properties of retinol, remains poorly understood. In this study, we incorporated phenomics, metagenomics and metabolomics to explore the human skin alterations during the anti-aging process mediated by retinol, and potential interactions between retinol, skin microbiome and metabolites. Topical retinol significantly improved skin conditions, including enhancing skin hydration, acidifying the epidermis, strengthening the skin barrier, and reducing the number and volume of wrinkles. Furthermore, retinol also reshaped the skin microecology by altering the structure and function of the skin microbiome as well as the host and microbial metabolites. Through GEM construction, we identified 2 skin microorganism, Sericytochromatia sp. and Corynebacterium kefirresidentii capable of oxidizing retinol to retinal. Over 10 skin microbes can utilize UDP-glucose as a carbon source, potentially accelerating RAG hydrolysis and increasing glucuronic acid consumption. The retinoic acid and retinol generated by RAG hydrolysis are reused by skin cells and microbes, enhancing retinol metabolism and its effective duration. This combined effect between the skin microbiome and retinol improves skin condition and anti-aging efficacy.

microbiology↗

VCAb: A web-tool for structure-guided antibody engineering

Effective responses against different immune challenges require secretion of antibodies with various isotypes performing specific effector functions. Structural information on these isotypes is essential to engineer antibodies with desired physico-chemical features of their antigen-binding properties, and optimal stability and developability as potential therapeutic antibodies. In silico mutational scanning profiles on antibody structures would further pinpoint candidate mutations for enhancing antibody stability and function. Although a number of antibody structure databases exist, a public data resource which provides clear, consistent annotation of isotypes, species coverage of 3D antibody structures and their deep mutation profiles is currently lacking. The V and C region bearing antibody (VCAb) web tool is established with the purpose to clarify these annotations and provide an accessible and easily consultable resource to facilitate antibody engineering. VCAb currently provides data on 6,948 experimentally determined antibody structures including both V and C regions from different species. Additionally, VCAb provides annotations of species and isotypes with both V and C region numbering schemes applied, which can be interactively queried or downloaded in batch. Multiple in silico mutational scanning methods are applied on VCAb structures to provide an easily accessible interface for querying the impact of mutations on antibody stability. These features are implemented in a R shiny application to enable interactive data interrogation. VCAb is freely accessible at https://fraternalilab.cs.ucl.ac.uk/VCAb/. The source code to generate the VCAb database and the online R shiny application is available at https://github.com/Fraternalilab/VCAb, enabling users to set up local VCAb instances.

bioinformatics↗

Propiconazole and Tianfengsu Regulated the Growth, Flavor, and Nutrition of Brassica rapa by Brassinosteroid Pathway

Propiconazole (PCZ) and Tianfengsu (TFS) are widely used plant growth regulators in vegetable production for improving crop growth, quality, and flavor. This study investigated the effects of PCZ and TFS, applied individually or in combination, on the growth, development, flavor quality, and nutritional components of choy sum (Brassica rapa) and Arabidopsis thaliana, as well as the underlying molecular mechanisms. The results showed that PCZ inhibited the growth of choy sum and Arabidopsis but enhanced the accumulation of flavor compounds such as soluble sugars, proteins, and vitamin C. In contrast, TFS promoted plant growth and increased the content of nutritional components, including chlorophyll and unsaturated fatty acids. Notably, the combined application of PCZ and TFS significantly improved overall plant quality, achieving the optimal balance of flavor and nutritional value while maintaining high yield. Transcriptomic analysis revealed the molecular mechanisms of PCZ and TFS in differentially regulating the expression of brassinosteroid (BR) signaling and downstream metabolism-related genes. Weighted gene co-expression network analysis (WGCNA) further identified key gene modules and hub genes controlling flavor metabolism in choy sum. This study elucidates the synergistic mechanisms of PCZ and TFS in regulating vegetable growth and quality formation, providing valuable insights for the safe production of high-quality choy sum and the development of novel plant growth regulators or elite varieties. HIGHLIGHTSO_LIPCZ and TFS treatments differentially modulate choy sum growth and development by regulating the BR pathway, with PCZ inhibiting while TFS promoting growth. C_LIO_LIPCZ enhances the accumulation of soluble sugars, soluble proteins, and vitamin C, while TFS increases photosynthetic pigments and unsaturated fatty acids, synergistically improving the flavor and nutritional quality of choy sum. C_LIO_LITranscriptomic analysis and WGCNA uncover key genes and modules controlling flavor metabolism in choy sum, providing potential targets for developing novel plant growth regulators or breeding elite varieties C_LI

plant biology↗