Biology subjects

Liang, Y.

Publications and source records attributed to Liang, Y..

At least 163 records · Page 9Linked to original sources

bioRxiv2024

A foundation model for generalizable cancer diagnosis and survival prediction from histopathological images

Computational pathology, utilizing whole slide image (WSI) for pathological diagnosis, has advanced the development of intelligent healthcare. However, the scarcity of annotated data and histological differences hinder the general application of existing methods. Extensive histopathological data and the robustness of self-supervised models in small-scale data demonstrate promising prospects for developing foundation pathology models. Due to the need for deployment, lightweight foundation models also need to be developed. In this work, we propose the BEPH (BEiT-based model Pre-training on Histopathological images), a general lightweight foundation model that leverages self-supervised learning to learn meaningful representations from 11 million unlabeled histopathological images. These representations are then efficiently adapted to various tasks, including 2 cancer patch-level recognition tasks, 3 cancer WSI-level classification tasks, and 6 cancer subtypes survival prediction tasks. Experimental results demonstrate that our model consistently outperforms several comparative models with similar parameters, even with limited training data reduced to 50%. Especially when the downstream structure is the same, the model can improve ResNet and DINO by up to a maximum increase of 8.8% and 7.2% (WSI level classification), and 6.44% and 3.28% on average (survival prediction), respectively. Therefore, BEPH offers a universal solution to enhance model performance, reduce the burden of expert annotations, and enable widespread clinical applications of artificial intelligence. The code and models can be obtained at https://github.com/Zhcyoung/BEPH. And currently, online fine-tuning of WSI classification tasks is available for use on http://yulab-sjtu.natapp1.cc/BEPH.

pathology↗

bioRxiv2024

Electroacupuncture regulates microglia activation through theSTING/NF-κB pathway to reduce pain in bone cancer pain mouse

Cancer pain is a global public health problem. The mechanism of cancer pain is complex, and opioid analgesics, which are widely used clinically, have obvious addiction and side effects, which seriously affect patientslife functions and may aggravate their anxiety, depression and other negative emotions. Acupuncture has a history of thousands of years in China, and acupuncture analgesia has been confirmed by many studies. This study investigated whether electroacupuncture can alleviate abnormal pain in bone cancer pain (BCP) mouse models and its possible central mechanism. A bone cancer pain model was established by injecting Lewis lung cancer cells into the left femoral cavity of adult male mice. Mechanical paw withdrawal threshold was tested baseline before surgery and 1, 4, 7, 10, 14 and 21 days after surgery. On day 21, behaviours related to depression emotions were tested. After the behaviours, the femurs were removed to observe pathological changes, the neck was broken and brain tissue was collected from the basal lateral amygdala (BLA) area for subsequent Western Blot and ELISA experiments were performed to verify the expression of (stimulator of interferon genes, STING) STING/NF-{kappa}B pathway proteins and the expression of inflammatory factors. Immunofluorescence of Ionized calcium-binding adapter molecule-1 (Iba-1) and STING in the basal lateral amygdala (BLA) brain region was also performed. The results show that electroacupuncture can increase the pain threshold of the bone cancer pain model and alleviate the depressive-like emotional phenotype. Electroacupuncture inhibited the expression of STING/NF-{kappa}B pathway proteins, activation of microglia and release of inflammatory factors in the basal lateral amygdala (BLA) area. Therefore, this study shows that electroacupuncture may relieve bone cancer pain by regulating microglial activation and inflammatory factor release through the STING/NF-{kappa}B pathway.

animal behavior and cognition↗

bioRxiv2024

Flat-field superresolution structured illumination microscopy with joint temporal-spatial light modulation

AbstractSuper-resolution structured illumination microscope (SR-SIM) has been established as a powerful tool for visualizing subcellular dynamics and studying organelle interactions in live cells. However, the interfering Gaussian beams result in a limited and nonuniform field of view (FOV) which hinders its application for large whole-cell dynamics and pathological sample imaging. Here, we proposed a joint spatial-temporal light modulation (JSTLM) method to reshape the excitation light field into flat-field structured illumination without disturbing the interfering fringes. Our flat-field structured illumination microscopy (flat-field SIM) improves the uniformity across the whole FOV significantly, hence enabling SR image stitching. Skeleton dynamics and vesicle transportation in and between whole cells were visualized by flat-field SIM. With the stitching of multi-FOV flat-field SIM images, millimeter-sized SR images can be obtained which provides the possibility for cell heterogeneity studies and pathological diagnoses. The JSTLM method can be further incorporated with regions of interest to reduce unnecessary photodamage to live cells during multicolor imaging. ContributionsY.L. and X.H.C. conceived and designed the idea. Y.L., S.M.L., X.J., and G.W. built the SIM setup. Y.L. performed the data acquisitions. Y.L. and X.H.C. conducted the optical wave simulation. J.Z. prepared the cell samples. Y.T. and L.B.W. performed the image analyses. Y.L. prepared the illustrations. X.H.C. and J.G. supervised the project. Y.L. and H.L. wrote the manuscript.

cell biology↗

bioRxiv2024

Diversity and ecological potentials of viral assemblages from the seamount sediments of the Northwest Pacific Ocean

Viruses are the most abundant life forms in the sea, influencing the community structure and metabolism of host cells as well as biogeochemical cycles. However, the diversity and ecological roles of viruses within seamount ecosystems, natural microbiota havens characterized by high biodiversity, remain unknown. Here, the first seamount viral genome (SMVG) dataset, based on a metagenomic analysis of twelve seamount sediment samples collected from the seamount regions of the Northwest Pacific Ocean, is established. A total of 78,069 viral operational taxonomic units (vOTUs) were found, spanning 18 viral classes and 63 viral families. The detection of sixteen viral auxiliary metabolic genes (vAMGs) suggests that viruses may participate in both the complex metabolic dynamics associated with sediment microbial communities and also biogeochemical cycles, including carbon, sulfur, metal, heme, and cobalamin cycling. vAMGs involved in the metabolism of heme, cobalamin and metals, in particular, are more often detected in seamount sediments than in trenches, cool seeps, and hydrothermal vents. This investigation of the viral communities in these seamount sediments provides new insights into the high diversity and ecological potential of the viruses and establishes a foundation for the future study of benthic viruses from deep-sea seamounts.

ecology↗

bioRxiv2024

Topology-Driven Negative Sampling Enhances Generalizability in Protein-Protein Interaction Prediction

Unraveling the human interactome to uncover disease-specific patterns and discover drug targets hinges on accurate protein-protein interaction (PPI) predictions. However, challenges persist in machine learning (ML) models due to a scarcity of quality hard negative samples, shortcut learning, and limited generalizability to novel proteins. Here, we introduce a novel approach for strategic sampling of protein-protein non-interactions (PPNIs) by leveraging higher-order network characteristics that capture the inherent complementarity-driven mechanisms of PPIs. Next, we introduce UPNA-PPI (Unsupervised Pre-training of Node Attributes tuned for PPI), a high throughput sequence-to-function ML pipeline, integrating unsupervised pretraining in protein representation learning with topological PPNI samples, capable of efficiently screening billions of interactions. UPNA-PPI improves PPI prediction generalizability and interpretability, particularly in identifying potential binding sites locations on amino acid sequences, strengthening the prioritization of screening assays and facilitating the transferability of ML predictions across protein families and homodimers. UPNA-PPI establishes the foundation for a fundamental negative sampling methodology in graph machine learning by integrating insights from network topology.

bioinformatics↗

bioRxiv2024

scCaT: an explainable capsulating architecture for sepsis diagnosis transferring from single-cell RNA sequencing

Sepsis is a life-threatening condition characterized by an exaggerated immune response to pathogens, leading to organ damage and high mortality rates in the intensive care unit. Although deep learning has achieved impressive performance on prediction and classification tasks in medicine, it requires large amounts of data and lacks explainability, which hinder its application to sepsis diagnosis. We introduce a deep learning framework, called scCaT, which blends the capsulating architecture with Transformer to develop a sepsis diagnostic model using single-cell RNA sequencing data and transfers it to bulk RNA data. The capsulating architecture effectively groups genes into capsules based on biological functions, which provides explainability in encoding gene expressions. The Transformer serves as a decoder to classify sepsis patients and controls. Our model achieves high accuracy with an AUROC of 0.93 on the single-cell test set and an average AUROC of 0.98 on seven bulk RNA cohorts. Additionally, the capsules can recognize different cell types and distinguish sepsis from control samples based on their biological pathways. This study presents a novel approach for learning gene modules and transferring the model to other data types, offering potential benefits in diagnosing rare diseases with limited subjects. Author summaryDeep learning models used in disease diagnosis usually suffer from insufficient data for training and the lack of explainability, especially in rare diseases. These shortages hinder their application to sepsis diagnosis. Here we propose a diagnostic framework name scCaT(https://github.com/Kimxbzheng/CaT), which transfers knowledge learned from single-cell RNA-seq, for diseases with insufficient bulk data. The framework uses capsulating architecture to group genes into capsules and provide explainability to the deep learning model for sepsis diagnosis. ScCaT achieves robust and outstanding performance for sepsis diagnosis in both scRNA-seq and bulk RNA datasets. This architecture offers potential approaches in diagnosing rare diseases with limited subjects with explainability.

bioinformatics↗

bioRxiv2024

Transcriptome-wide identification of 5-methylcytosine by deaminase and reader protein-assisted sequencing

5-Methylcytosine (m5C) is one of the post-transcriptional modifications in mRNA and is involved in the pathogenesis of various diseases. However, the capacity of existing assays for accurately and comprehensively transcriptome-wide m5C mapping still needs improvement. Here, we develop a detection method named DRAM (deaminase and reader protein assisted RNA methylation analysis), in which deaminases (APOBEC1 and TadA-8e) are fused with m5C reader proteins (ALYREF and YBX1) to identify the m5C sites through deamination events neighboring the methylation sites. This antibody-free and bisulfite-free approach provides transcriptome-wide editing regions which are highly overlapped with the publicly available BS-seq datasets and allows for a more stable and comprehensive identification of the m5C loci. In addition, DRAM system even supports ultra-low input RNA (10ng). We anticipate that the DRAM system could pave the way for uncovering further biological functions of m5C modifications.

biochemistry↗

bioRxiv2024

Spatiotemporal transcriptomic profiling reveals the dynamic immunological landscape of alveolar echinococcosis

Alveolar echinococcosis (AE) is caused by the invasive growth of the metacestodes of Echinococcus multilocularis (E. multilocularis). The early diagnosis, management, and treatment of AE remains challenging. Herein, we integrated bulk RNA-seq, scRNA-seq, and ST technologies to reveal the immune characteristics both spatially and chronologically in E. multilocularis infected mouse liver. An unprecedented high-resolution spatial atlas of the E. multilocularis infection foci was obtained, revealing the pivotal role of neutrophils, Spp1+ monocyte-derived macrophages (MoMFs), and fibroblasts in AE progression. We observed continuous recruitment of neutrophils and macrophages into the infected tissues, indicating prolonged immune stimulation by the growing metacestodes. However, their spatial distribution patterns and functions changed during the infection cause. At the early infection stage, Il1bhi neutrophils aggregated in the lesion displayed the highest pattern-recognition receptor activity and may kill the metacestodes through NETosis, but their death in the infection foci might also trigger immune suppression. Meanwhile, Spp1+ MoMFs attached to the protoscoleces to clear the infection. At the late infection stage, the neutrophils failed to infiltrate into the lesion although their continuous recruitment into the infected liver. Even though the Spp1+ MoMFs enclosing the microcysts of E. multilocularis may retain their pathogen-killing ability, they may also promote fibrosis and angiogenesis through interaction with fibroblasts. The pro- and anti-inflammatory phenotype balance of these immune cells may be associated with the transition of parasite control strategy from "active killing" to "negative segregation" by the host. Our findings identify key molecular traits involved in AE development, which may benefit the treatment of echinococcosis.

immunology↗

bioRxiv2024

High resolution cryo-EM of V-ATPase in native synaptic vesicles

Neurotransmitter release into the synaptic cleft between neurons enables the intercellular communication central to the function of the brain. In the presynaptic neuron, the proton pumping vesicular- or vacuolar-type ATPase (V-ATPase) powers neurotransmitter loading into synaptic vesicles (SVs), with the V1 complex dissociating from the membrane region of the enzyme before exocytosis. We isolated SVs from rat brain using SidK, a V-ATPase-binding bacterial effector protein. Single particle electron cryomicroscopy of the vesicles allowed high-resolution structure determination of V-ATPase within the native SV membrane. In the structure, regularly spaced cholesterol molecules decorate the enzymes rotor and the abundant SV protein synaptophysin binds the complex stoichiometrically. Conditions where ATP hydrolysis drives glutamate loading result in loss of V1 from the SV membrane, suggesting that SV loading is sufficient to induce V-ATPase dissociation.

biochemistry↗

bioRxiv2024

Protein disulfide isomerase disassembles stress granules and blocks cytoplasmic aggregation of TDP-43 in ALS

Cytoplasmic aggregation of the transactive response DNA-binding protein-43 (TDP-43) in neurons, a pathological feature common to amyotrophic lateral sclerosis (ALS) and frontotemporal lobar degeneration, has been found in some Alzheimers patients. Protein disulfide isomerase (PDI) functions as both an enzyme and a molecular chaperone to correct or eliminate misfolded proteins under pathological conditions. Here, we report that TDP-43 is mislocalized to the cytoplasm and colocalizes with PDI in the brain and spinal cord of two ALS patients and the brain of six Alzheimers patients compared to controls. TDP-43 selectively recruits wild-type PDI into its phase-separated condensate, which in turn slows down in vitro liquid-liquid phase separation of TDP-43, shifting the equilibrium phase boundary to higher protein concentrations. Importantly, wild-type PDI decreases oxidative stress-induced interaction between TDP-43 and G3BP1 to disassemble stress granules containing TDP-43 in neuronal cells. Wild-type PDI blocks the oxidative stress-induced mislocalization of TDP-43 to the cytoplasm, and blocks subsequent pathological phosphorylation and aggregation of TDP-43. We demonstrate that under pathological stress conditions, wild-type PDI disassembles stress granules, blocks cytoplasmic mislocalization and aggregation of TDP-43, and suppresses mitochondrial damage and TDP-43 toxicity. In the presence of abnormal forms of PDI, however, PDI loses its activity, and stress granules containing TDP-43 are assembled into amyloid fibrils, resulting in mitochondrial impairment and neuronal cell death in ALS patients and some Alzheimers patients. TeaserPDI disassembles SGs, blocks cytoplasmic mislocalization and aggregation of TDP-43, and suppress TDP-43 toxicity in ALS.

biochemistry↗

bioRxiv2024

PhyloForge: Unifying micro and macro evolution with comprehensive genomic signals

With the explosive growth of biological data, the dimensions of phylogenetic research have expanded to encompass various aspects, including the study of large-scale populations at the microevolutionary level and comparisons between different species or taxonomic units at the macroevolutionary level. Traditional phylogenetic tools often struggle to handle the diverse and complex data required for these different evolutionary scales. In response to this challenge, we introduce PhyloForge-a robust tool designed to seamlessly integrate the demands of both micro- and macro-evolution, comprehensively utilizing diverse phylogenomic signals, such as genes, SNPs, structural variations, as well as mitochondrial and chloroplast genomes. PhyloForges groundbreaking innovation lies in its capability to seamlessly integrate multiple phylogenomic signals, enabling unified analysis of multidimensional genomic data. This unique feature empowers researchers to gain a more comprehensive understanding of diverse aspects of biological evolution. PhyloForge not only provides highly customizable analysis tools for experienced researchers but also features an intuitively designed interface, facilitating effortless phylogenetic analysis for beginners. Extensive testing across various domains, including animals, plants, and fungi, attests to its broad applicability in the field of phylogenetics. In summary, the developmental background and innovative features of PhyloForge position it with significant potential in the era of large-scale genomics, offering a new perspective and toolset for a deeper understanding of the evolution of life.

molecular biology↗

bioRxiv2024

Boosting the Sensitivity of Quantitative Single-Cell Proteomics with Activated Ion-Tandem Mass Tags (AI-TMT)

Single-cell proteomics is a powerful approach to precisely profile protein landscapes within individual cells toward a comprehensive understanding of proteomic functions and tissue and cellular states. The inherent challenges associated with limited starting material in single-cell analyses demands heightened analytical sensitivity. Just as advances in sample preparation maximize the amount of material that makes it from the cell to the mass spectrometer, we strive to maximize the number of ions that make it from ion source to the detector. In isobaric tagging experiments, limited reporter ion generation limits quantitative accuracy and precision. The combination of infrared photoactivation and ion parking circumvents the m/z dependence inherent in HCD, maximizing reporter generation and avoiding unintended degradation of TMT reporter molecules in a method we term activated ion-tandem mass tags (AI-TMT). The method was applied to single-cell human proteomes using 18-plex TMTpro, resulting in a 4-5-fold increase in reporter ion signal on average compared to conventional SPS-MS3 approaches. AI-TMT enables faster duty cycles, higher throughput, and increased peptide identification and quantification. Comparative experiments showcase 4-5-fold lower injection times for AI-TMT, providing superior sensitivity without compromising accuracy. In all, AI-TMT enhances the sensitivity and dynamic range of proteomic experiments and is compatible with other techniques, including gas-phase fractionation and real-time searching, promising increased gains in the study of cellular heterogeneity and disease mechanisms.

biochemistry↗

bioRxiv2024

Chemogenetic activation of microglial Gi signaling decreases microglial surveillance and impairs neuronal synchronization

Microglia actively survey the brain and dynamically interact with neurons to maintain brain homeostasis. Microglial Gi-protein coupled receptors (Gi-GPCRs) play a critical role in microglia-neuron communications. However, the impact of temporally activating microglial Gi signaling on microglial dynamics and neuronal activity in the homeostatic brain remains largely unknown. In this study, we employed Gi-based Designer Receptors Exclusively Activated by Designer Drugs (Gi-DREADD) to selectively and temporally modulate microglial Gi signaling pathway. By integrating this chemogenetic approach with in vivo two-photon imaging, we observed that exogenous activation of microglial Gi signaling transiently inhibited microglial process dynamics, reduced neuronal activity, and impaired neuronal synchronization. These altered neuronal functions were associated with a decrease in interactions between microglia and neuron somata. Altogether, this study demonstrates that acute, exogenous activation of microglial Gi signaling can regulate neuronal circuit function, offering a potential pharmacological target for neuromodulation through microglia.

neuroscience↗

bioRxiv2024

Lack of the IFN-γ signal leads to lethal Orientia tsutsugamushi infection in mice with skin eschar lesions

Scrub typhus is an acute febrile disease due to Orientia tsutsugamushi (Ot) infection and can be life-threatening with organ failure, hemorrhage, and fatality. Yet, little is known as to how the host reacts to Ot bacteria at early stages of infection; no reports have addressed the functional roles of type I versus type II interferon (IFN) responses in scrub typhus. In this study, we used comprehensive intradermal (i.d.) inoculation models and two clinically predominant Ot strains (Karp and Gilliam) to uncover early immune events. Karp infection induced sequential expression of Ifnb and Ifng in inflamed skin and draining lymph nodes at days 1 and 3 post-infection. Using double Ifnar1-/-Ifngr1-/- and Stat1-/- mice, we found that deficiency in IFN/STAT1 signaling resulted in lethal infection with profound pathology and skin eschar lesions, that resembled to human scrub typhus. Further analyses demonstrated that deficiency in IFN-{gamma}, but not IFN-I, resulted in impaired NK cell and macrophage activation and uncontrolled bacterial growth and dissemination, leading to metabolic dysregulation, excessive inflammatory cell infiltration, and exacerbated tissue damage. NK cells were found to be the major cellular source of early IFN-{gamma}, contributing to the initial Ot control. In vitro studies with dendritic cell cultures revealed a superior antibacterial effect offered by IFN-{gamma} than IFN-{beta}. Comparative in vivo studies with Karp- and Gilliam-infection revealed a crucial role of IFN-{gamma} signaling in protection against progression of eschar lesions and Ot infection lethality. Additionally, our i.d. mouse models of lethal infection with eschar lesions are promising tools for immunological study and vaccine development for scrub typhus. SummaryScrub typhus can lead to severe complications and even fatality if not treated properly; however, the early host immune responses to Ot bacterium infection remain unclear. This study focused on the functional roles of IFNs in i.d. inoculation mouse models of scrub typhus. We found that mice lacking IFN receptors were highly susceptible to Ot infection, which resulted in severe pathology and skin eschar lesions that resembled to human scrub typhus. Further investigation revealed that the lack of IFN-{gamma}, but not IFN-I, resulted in dysregulated innate immune responses, leading to uncontrolled bacterial burdens and tissue damage. Using IFN-{gamma} reporter mice and neutralizing antibody treatment, we confirmed that NK cells were the major source of early IFN-{gamma}, and thus played a key role in controlling Ot dissemination. Moreover, our comparative studies with two Ot strains revealed bacterium strain- and dose-dependent eschar formation and disease severity. In conclusion, our study highlights the crucial role of IFN-{gamma} signaling in ensuring host protection against Ot infection. Our mouse models resemble skin eschar lesions and lethal infections observed in human disease, offering potential for future immunological studies on scrub typhus.

immunology↗

bioRxiv2024

CACIMAR: Cross-species Analysis of Cell Identities, Markers, Regulations and Interactions Using Single-cell RNA Sequencing Data

Transcriptomic analysis across species is increasingly used to reveal conserved gene regulations which implicate crucial regulators. Cross-species analysis of single-cell RNA sequencing (scRNA-seq) data provides new opportunities to identify the cellular and molecular conservations especially for cell types and cell type-specific gene regulations. However, few methods have been developed to analyze cross-species scRNA-seq data to uncover both molecular and cellular conservation patterns. Here, we built a tool called CACIMAR, which can perform cross-species analysis of cell identities, markers, regulations and interactions using scRNA-seq profiles. Based on the weighted sum models of the conserved features, we developed different conservation scores to measure the conservation of cell types, regulatory networks and intercellular interactions. Using publicly available scRNA-seq data on retinal regeneration in mice and zebrafish, we demonstrated four main functions of CACIMAR. First, CACIMAR allows to identify evolutionarily conserved cell types, including poorly conserved cell types. Second, the tool facilitates the identification of evolutionarily conserved or species-specific marker genes. Third, CACIMAR enables the identification of conserved intracellular regulations, including cell type-specific regulatory subnetworks and regulators. Lastly, CACIMAR provides a unique feature on the identification of conserved intercellular interactions. Overall, CACIMAR facilitates the identification of evolutionarily conserved cell types, marker genes, intracellular regulations and intercellular interactions, providing insights on the cellular and molecular mechanisms of species evolution.

bioinformatics↗

bioRxiv2024

Overloading And unpacKing (OAK) - droplet-based combinatorial indexing for ultra-high throughput single-cell multiomic profiling

Multiomic profiling of single cells by sequencing is a powerful technique for investigating cellular diversity in complex biological systems. Although the existing droplet-based microfluidic methods have advanced single-cell sequencing, they produce a plethora of cell-free droplets and underutilize barcoding capacities due to their low cell concentration prerequisites. Meanwhile, combinatorial indexing on microplates can index cells in a more effective way; however, it requires time-consuming and laborious protocols involving multiple splitting and pooling steps. Addressing these constraints, we have developed "Overloading And unpacKing" (OAK). With reduced labor intensity, OAK can provide cost-effective multiomic profiling for hundreds of thousands of cells, offering detection sensitivity on par with commercial droplet-based methods. To demonstrate OAKs versatility, we conducted single-cell RNA sequencing (scRNA-Seq) as well as joint single-nucleus RNA sequencing (snRNA-Seq) and single-nucleus Assay for Transposase Accessible Chromatin with sequencing (snATAC-Seq) using cell lines. We further showcased OAKs performance on more complex samples, including in vitro differentiated bronchial epithelial cells and primary retinal tissues. Finally, we examined transcriptomic responses of 408,000 melanoma cells across around 1,000 starting lineages over a 90-day treatment with a RAF inhibitor, belvarafenib. We discovered a rare cell population (0.12%) that underwent a sequence of transcriptomic changes, resulting in belvarafenib resistance. Ultra-high throughput, broad compatibility with diverse molecular modalities, high detection sensitivity, and simplified experimental procedures distinguish OAK from previous methods, and render OAK a powerful tool for large-scale analysis of molecular signatures, even for rare cells.

molecular biology↗

bioRxiv2024

CD8+ T cell response promotes viral clearance and reduces chances of severe testicular damage in mouse models of long-term Zika virus infection of the testes.

Zika virus (ZIKV) causes human testicular inflammation and alterations in sperm parameters and causes testicular damage in mouse models. The involvement of individual immune cells in testicular damage is not fully understood. We detected virus in the testes of the interferon (IFN) /{beta} receptor-/- A129 mice three weeks post-infection and found elevated chemokines in the testes, suggesting chronic inflammation and long-term infection play a role in testicular damage. In the testes, myeloid cells and CD4+ T cells were absent at 7 dpi but were present at 23 days post-infection (dpi), and CD8+ T cell infiltration started at 7 dpi. CD8-/- mice with an antibody-depleted IFN response had a significant reduction in spermatogenesis, indicating that CD8+ T cells are essential to prevent testicular damage during long-term ZIKV infections. Our findings on the dynamics of testicular immune cells and importance of CD8+ T cells functions as a framework to understand mechanisms underlying observed inflammation and sperm alterations in humans.

microbiology↗

bioRxiv2024

Restraint Validation of Biomolecular Structures Determined by NMR in the Protein Data Bank

Biomolecular structure analysis from experimental NMR studies generally relies on restraints derived from a combination of experimental and knowledge-based data. A challenge for the structural biology community has been a lack of standards for representing these restraints, preventing the establishment of uniform methods of model-vs-data structure validation against restraints and limiting interoperability between restraint-based structure modeling programs. The NMR exchange (NEF) and NMR-STAR formats provide a standardized approach for representing commonly used NMR restraints. Using these restraint formats, a standardized validation system for assessing structural models of biopolymers against restraints has been developed and implemented in the wwPDB OneDep data deposition-validation-biocuration system. The resulting wwPDB Restraint Violation Report provides a model vs. data assessment of biomolecule structures determined using distance and dihedral restraints, with extensions to other restraint types currently being implemented. These tools are useful for assessing NMR models, as well as for assessing biomolecular structure predictions based on distance restraints. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=100 SRC="FIGDIR/small/575520v2_ufig1.gif" ALT="Figure 1"> View larger version (20K): org.highwire.dtl.DTLVardef@bac5eforg.highwire.dtl.DTLVardef@190cdborg.highwire.dtl.DTLVardef@9b3d83org.highwire.dtl.DTLVardef@1e38ccc_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIPDB Structure Validation Report expanded to include Restraint Analysis C_LIO_LINMR Exchange Format (NEF) and NMR-STAR for distance restraint representation C_LIO_LIStandard distance and dihedral restraint formats for model vs. restraint assessment C_LIO_LIStandardized restraint formats provide interoperability between modeling programs C_LI

bioinformatics↗