Biology subjects

Jia, M.

Publications and source records attributed to Jia, M..

At least 19 recordsLinked to original sources

bioRxiv2026

An immunocompetent model of MCPyV-driven Merkel cell carcinoma reveals tumor evolution under immune selection

Merkel cell carcinoma (MCC) is a neuroendocrine skin tumor that is frequently driven by integration of Merkel cell polyomavirus (MCPyV). In MCC, the MCPyV genome is truncated, but expression of the viral tumor antigens, truncated large tumor antigen (LTT) and small tumor antigen (sT), is maintained and drives uncontrolled proliferation. We introduced constitutive expression of the MCPyV T antigens (TAs) into primary mouse dermal fibroblasts (MDFs) to determine whether these cells are susceptible to MCPyV-driven transformation. TA expression alone in MDFs induced key MCC markers, cytokeratin-20 (CK20) and Sry-box transcription factor 2 (SOX2), and promoted anchorage-independent growth indicative of cellular transformation. Subcutaneous implantation of TA-transformed fibroblasts produced high-grade MCC-like tumors that grew persistently in immunodeficient NSG mice but not in immunocompetent C57BL/6 mice. Serial in vivo passaging of the tumor cell line enhanced tumor growth, reduced expression of p53-target genes and MHC-1, and was accompanied by a shift in T antigen isoform expression, with decreased LTT and increased sT expression. Our data demonstrate that MCPyV-driven tumors acquire immune-evasive adaptions during tumor progression in vivo and suggest that the anti-tumor immune response exerts selective pressure in MCC that favors expression of sT rather than LTT. The model established in this study provides a unique platform for studying evolution of MCPyV-driven tumors under immune pressure and identifying mechanisms of immune evasion in MCC that could be used to develop new therapeutic strategies. Significance StatementMCPyV tumor antigen expression transforms mouse dermal fibroblasts to generate MCC-like tumors. Serial in vivo passaging reveals tumor evolution under immune pressure, providing a model to study immune evasion mechanisms in MCC.

cancer biology↗

bioRxiv2026

Tip growth of root hairs reveals functional divergence of plant expansins

Plant cell wall expansion is essential for plant growth, with expansins promoting wall loosening and creep during diffuse growth. Expansins role in tip growth, such as root hair elongation, is less clear. Here we used CRISPR/Cas9 to knock out root-hair specific -expansins EXPA7 and EXPA18 in Arabidopsis thaliana, abolishing root hair elongation. Complementation with expansin genes from various clades (driven by the EXPA7 promoter) revealed functional differences: some fully restored root hair growth, others only partially restored growth, while others failed, notably two EXPA clades [clade-VIII (EXPA13) and clade-IX (EXPA20)] lacking a conserved Asp considered essential for expansin-induced wall enlargement. Phylogenetic analysis indicated loss of this Asp predated angiosperms. Mutation of this Asp in EXPA7 confirmed its necessity for wall loosening. Members of the other expansin families (EXPB, EXLA and EXLB) failed to restore root hair growth. Chimeric fusions of EXPAs with mCherry revealed differences in trafficking patterns and wall binding among EXPA clades. These results demonstrate functional differences among expansin families and among EXPA clades and demonstrate a genetic platform to analyze functionalities (trafficking, wall binding, wall extension) of EXPA and other wall-modifying proteins during root-hair tip growth. Significance StatementPlant cells can enlarge >100-fold during growth, a process controlled by proteins called expansins. Plants have many expansin proteins that are difficult to study in isolation and whose specific activities and properties have remained elusive. Here, we engineered a root-hairless Arabidopsis mutant as a genetic platform to assess expansin activity in vivo. By introducing various expansins with a fluorescent tag into this mutant, we uncovered an unexpected functional diversity across the expansin superfamily. While some expansins successfully restored root hair growth, others failed, potentially due to differences in protein trafficking, cell wall binding, or evolutionary loss of critical residues required for wall loosening. These findings point to a divergence of expansin functions during >140 million years of plant evolution.

plant biology↗

bioRxiv2026

An autonomous system for multi-objective continuous evolution at scale

Natural evolution is high-dimensional; organisms adapt to many pressures at once, across substrates, environments, and genetic backgrounds. Yet most directed evolution methods flatten this landscape to a single selection axis, hiding tradeoffs, and limiting what can be learned. Phage-assisted continuous evolution (PACE) is uniquely suited for multivariate selection because horizontal gene transfer couples genotype to propagation and allows the same phage lineage to traverse different selection environments. In practice, implementing this at scale has been prohibitive because each selection demands its own host culture, and every culture must be held for days to weeks within a narrow, infectable density window using continuously responsive bioreactors. In this work, TurboPRANCE is presented as an open-source, queueable robotic platform that integrates [~]200 independently controlled turbidostats with 96 parallel PACE lagoons under closed-loop control. Each turbidostat operates as a fully separate unit that can be equilibrated and initiated on its own schedule, enabling asynchronous starts and sustained operation without intervention. Automated media formulation, programmable dosing, on-deck sterilization, and adaptive scheduling coordinate growth control with the changing needs of the robotic workflow, dynamically adjusting dilution and transfer timing around formulation, sampling, and handling steps to keep each culture at consistent infectable densities despite unpredictable method demands. Cultures can be multiplexed and titrated into lagoons at defined ratios, swapped in and out on a schedule, or kept fully separate across experiments, creating a combinatorial space of selection pressures and programs that is effectively unbounded. Additionally, to enable high-throughput evolutionary tracking that scales with TurboPRANCE, Nanopore long-read sequencing was combined with DeepVariant, a deep learning-based variant caller, enabling population-level tracking of evolving variants. The result is a system that generates high-resolution time-resolvable evolutionary trajectories and large parallel datasets spanning diverse selection regimes, yielding dense, multivariate training data to map and engineer complex fitness landscapes at scale. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=81 SRC="FIGDIR/small/709196v2_ufig1.gif" ALT="Figure 1"> View larger version (36K): org.highwire.dtl.DTLVardef@b0f8daorg.highwire.dtl.DTLVardef@a1d57eorg.highwire.dtl.DTLVardef@c771aeorg.highwire.dtl.DTLVardef@1f8729a_HPS_FORMAT_FIGEXP M_FIG Turbidostat, Phage, and Robotics-Assisted Near Continuous Evolution (TurboPRANCE) In phage-assisted continuous evolution (PACE), biomolecular activity is coupled to pIII expression, linking function to phage propagation. By altering the host strain, distinct selection pressures can be imposed on the same evolving phage population. In TurboPRANCE, [~]200 selection programs can vary over time, including periodic "drift" (mutagenesis), alternation between pressures, or rotational reassignment of host sources, enabling a combinatorial space of selection pressures. C_FIG

bioengineering↗

bioRxiv2025

Ninjurin2 Regulates Vascular Smooth Muscle Cell Phenotypic Switching and Vascular Remodeling through Interacting with PDGF Receptor-β

Vascular smooth muscle cell (VSMC) phenotypic switching from a contractile to synthetic state plays a pivotal role in vascular remodeling. Although genome-wide association studies have linked NINJ2 (encode Ninjurin2) polymorphisms are associated with risk of atherosclerosis and related conditions like ischemic stroke and coronary artery disease, its functional role in regulating VSMC plasticity remains unexplored. Here, using Ninj2 knockout (Ninj2-/-) and smooth muscle-specific overexpressing (Ninj2smcTG) mice subjected to carotid artery ligation, we demonstrate that Ninjurin2 deficiency exacerbates injury-induced intimal hyperplasia, whereas its overexpression attenuates this pathological remodeling. Mechanistically, Ninjurin2 knockdown promoted PDGF-BB-mediated VSMC phenotypic switching, proliferation, and migration, while biochemical studies revealed that Ninjurin2 interacts with PDGFR{beta} to suppress FAK signaling. These findings identify Ninjurin2 as a novel regulator of VSMC phenotypic switching via the PDGFR{beta}/FAK axis, offering new mechanistic insights into vascular remodeling and potential therapeutic avenues for atherosclerosis.

pathology↗

bioRxiv2024

Altered AP-1, RUNX, and EGR chromatin dynamics drive fibrotic lung disease

Pulmonary fibrosis, including systemic sclerosis-associated interstitial lung disease (SSc-ILD), involves myofibroblasts and SPP1hi macrophages as drivers of fibrosis. Single-cell RNA sequencing has delineated fibroblast and macrophages transcriptomes, but limited insight into transcriptional control of profibrotic gene programs. To address this challenge, we analyzed multiomic snATAC/snRNA-seq on explanted SSc-ILD and donor control lungs. The neural network tool ChromBPNet inferred increased TF binding at single base pair resolution to profibrotic genes, including CTHRC1 and ADAM12, in fibroblasts and SPP1 and CCL18 in macrophages. The novel algorithm HALO confirmed AP-1, RUNX, and EGR TF activity controlling profibrotic gene programs and established TF-regulatory element-gene networks. This TF action atlas provides comprehensive insights into the transcriptional regulation of fibroblasts and macrophages in healthy and fibrotic human lungs.

systems biology↗

bioRxiv2024

Dynamic stress- and inflammatory-based regulation of psychiatric risk loci in human neurons

The immune environment influences neurodevelopment and subsequent clinical trajectories for psychiatric outcomes in childhood and adolescence. Yet it remains unclear if the impact of maternal and fetal immune activation varies with distinct polygenic risk profiles. Therefore, here we catalogue genotype and environment (GxE) interactions, contrasting allele-specific regulatory activity between inflammatory cues. We report a cue-specific neuronal massively parallel reporter assay (MPRA) of 152 loci from genome-wide association study (GWAS) linked to ten brain traits/disorders, empirically dissecting the impact of interleukin-6 (IL-6) and interferon-alpha (IFN) on transcriptional activity. In human induced pluripotent stem cell (hiPSC)-derived glutamatergic neurons, 1,156 active candidate regulatory risk sequences (MPRA-active CRSs) are resolved, including 267 with variant-specific effects (MPRA-emVars) and 61 with variant-by-cytokine interaction effects (interaction MPRA-emVars). Broadly, neuronal immune-mediated regulatory activity is associated with differences in transcription factor binding and chromatin accessibility, the gene targets of which show pleiotropic enrichments for brain, metabolic, and immune disorders. Dynamic genetic regulation mediates neuroimmune effects, informing our understanding of the genomics of psychiatric and neurological traits, mechanisms governing pleiotropy across disorders, and how immune mechanisms mediate genetic risk.

genetics↗

bioRxiv2024

LaGrACE: Estimating gene program dysregulation using latent gene regulatory network for biomedical discovery

Gene expression programs that establish and maintain specific cellular states are orchestrated through a regulatory network composed of transcription factors, cofactors, and chromatin regulators. Dysregulation of this network can lead to a broad range of diseases by altering gene programs. This article presents LaGrACE, a novel method designed to estimate dysregulation of gene programs utilizing omics data with clinical information. This approach facilitates grouping of samples exhibiting similar patterns of gene program dysregulation, thereby enhancing the discovery of underlying molecular mechanisms. We rigorously evaluated LaGrACEs performance using synthetic data, bulk RNA-seq clinical datasets (breast cancer, chronic obstructive pulmonary disease (COPD)), and single-cell RNA-seq drug perturbation datasets. Our findings demonstrate that LaGrACE is exceptionally robust in identifying biologically meaningful and prognostic molecular subtypes. Additionally, it effectively discerns drug-response signals at a single-cell resolution. Moreover, the COPD analysis revealed a new association between LEF1 and COPD molecular mechanisms and mortality. Collectively, these results underscore the utility of LaGrACE as a valuable tool for elucidating underlying mechanisms of diseases.

bioinformatics↗

bioRxiv2023

A 50-gene high-risk profile predictive of COVID-19 and Idiopathic Pulmonary Fibrosis mortality originates from a molecular imbalance in monocyte and T-cell subsets that reverses in survivors with post-COVID-19 Interstitial Lung Disease

BackgroundWe aim to study the source of circulating immune cells expressing a 50-gene signature predictive of COVID-19 and IPF mortality. MethodsWhole blood and Peripheral Blood Mononuclear cells (PBMC) were obtained from 231 subjects with COVID-19, post-COVID-19-ILD, IPF and controls. We measured the 50-gene signature (nCounter, Nanostring), interleukin 6 (IL6), interferon {gamma}-induced protein (IP10), secreted phosphoprotein 1 (SPP1) and transforming growth factor beta (TGF-{beta}) by Luminex. PCR was used to validate COVID-19 endotypes. For single-cell RNA sequencing (scRNA-seq) we used Chromium Controller (10X Genomics). For analysis we used the Scoring Algorithm of Molecular Subphenotypes (SAMS), Cell Ranger, Seurat, Propeller, Kaplan-Meier curves, CoxPH models, Two-way ANOVA, T-test, and Fishers exact. ResultsWe identified three genomic risk profiles based on the 50-gene signature, and a subset of seven genes, associated with low, intermediate, or high-risk of mortality in COVID-19 with significant differences in IL6, IP10, SPP1 and TGF{beta}-1. scRNA-seq identified Monocytic-Myeloid-Derived Suppressive cells (M-MDSCs) expressing CD14+HLA DRlowCD163+ and high levels of the 7-gene signature (7Gene-M-MDSC) in COVID-19. These cells were not observed in post-COVID-19-ILD or IPF. The 43-gene signature was mostly expressed in CD4 T and CD8 T cell subsets. Increased expression of the 43 gene signature was seen in T cell subsets from survivors with post-COVID-19-ILD. The expression of these genes remained low in IPF. ConclusionA 50-gene, high-risk profile in COVID-19 is characterized by a genomic imbalance in monocyte and T-cell subsets that reverses in survivors with post-COVID-19 Interstitial Lung Disease

genomics↗

bioRxiv2023

Enhanced K Na 1.1 Channel Underlies Cortical Hyperexcitability and Seizure Susceptibility after Traumatic Brain Injury

Pathogenic variants of the sodium-activated potassium channel KNa1.1, have been reported in multiple epileptic disorders. However, whether and how KNa1.1 channel is involved in epileptogenesis after traumatic brain injury (TBI) remains unknown. Firstly, we used behavioral monitoring and EEG recording to examine physiological property, spontaneous seizure activity, and seizure susceptibility after TBI. We explored the changes of KNa1.1 channel following TBI, including changes of subcellular distribution and expression pattern. Meanwhile, we performed patch-clamp recording to detect the neuronal excitability. Furthermore, we built TBI model using kcnt1-/- mice and compared seizure activity with those on wild- type mice. We found severity-dependent seizure susceptibility in different degree of injured mice. Meanwhile, increased neuronal expression of KNa1.1 channel, especially in inhibitory neurons, around the lesion was also observed following TBI with increased neuronal excitability including reduced firing rate of interneurons and imbalanced excitation and inhibition (E/I). Although the maximum frequency of action potential of kcnt1-/- neurons was increased, kcnt1-/- mice displayed decreased seizure susceptibility to the pentylenetetrazole (PTZ) after TBI. Taken together, this study suggests that pathologically enhanced expression and abnormally distributed KNa1.1 channel after TBI contribute to disputed E/I and seizure susceptibility, which might provide a potential therapeutic target on the epileptogenesis after TBI.

neuroscience↗

bioRxiv2023

LEF1 isoforms regulate cellular senescence and aging

BackgroundThe study of aging and its mechanisms, such as cellular senescence, has provided valuable insights into age-related pathologies, thus contributing to their prevention and treatment. The current abundance of high throughput data combined with the surge of robust analysis algorithms has facilitated novel ways of identifying underlying pathways that may drive these pathologies. MethodsWith the focus on identifying key regulators of lung aging, we performed comparative analyses of transcriptional profiles of aged versus young human subjects and mice, focusing on the common age-related changes in the transcriptional regulation in lung macrophages, T cells, and B immune cells. Importantly, we validated our findings in cell culture assays and human lung samples. ResultsWe identified Lymphoid Enhancer Binding Factor 1 (LEF1) as an important age-associated regulator of gene expression in all three cell types across different tissues and species. Follow-up experiments showed that the differential expression of long and short LEF1 isoforms is a key regulatory mechanism of cellular senescence. Further examination of lung tissue from patients with Idiopathic Pulmonary Fibrosis (IPF), an age-related disease with strong ties to cellular senescence, we demonstrated a stark dysregulation of LEF1. ConclusionsCollectively, our results suggest that the LEF1 is a key factor of aging, and its differential regulation is associated with human and murine cellular senescence.

genomics↗

bioRxiv2023

Multi-Omics Integration For Disease Prediction Via Multi-Level Graph Attention Network And Adaptive Fusion

Multi-omics integration has demonstrated promising performance in complex disease prediction. However, existing research typically focuses on maximizing prediction accuracy, while often neglecting the essential task of discovering meaningful biomarkers. This issue is particularly important in biomedicine, as molecules often interact rather than function individually to influence disease outcomes. To this end, we propose a two-phase framework named GREMI to assist multi-omics classification and explanation. In the prediction phase, we propose to improve prediction performance by employing a graph attention architecture on sample-wise co-functional networks to incorporate biomolecular interaction information for enhanced feature representation, followed by the integration of a joint-late mixed strategy and the true-class-probability block to adaptively evaluate classification confidence at both feature and omics levels. In the interpretation phase, we propose a multi-view approach to explain disease outcomes from the interaction module perspective, providing a more intuitive understanding and biomedical rationale. We incorporate Monte Carlo tree search (MCTS) to explore local-view subgraphs and pinpoint modules that highly contribute to disease characterization from the global-view. Extensive experiments demonstrate that the proposed framework outperforms state-of-the-art methods in seven different classification tasks, and our model effectively addresses data mutual interference when the number of omics types increases. We further illustrate the functional- and disease-relevance of the identified modules, as well as validate the classification performance of discovered modules using an independent cohort. Code and data are available at https://github.com/Yaolab-fantastic/GREMI.

bioinformatics↗

bioRxiv2023

High Resolution Salmonella Subtyping by the MLSTnext Method

The food industry needs a straightforward, efficient, widely applicable and cost-efficient method to not only detect, but also determine serovar and potential sources of multiple strains in food and environment. While Whole Genome Sequencing (WGS) can generate complete genomic profile of food pathogens, it is a laborious, time-consuming, and expensive method that necessitates pure isolates. As a result, it is unsuitable for samples with complex background, limiting its widespread application by food industry. However, traditional multilocus sequence typing (MLST) approaches do not provide sufficient single nucleotide polymorphism (SNP) information to effectively track- and-trace sources of contamination. In contrast, ChapterDx MLSTnext-NGS (next-generation sequencing) Salmonella assay amplifies and sequences 47 polymorphic loci, evenly spanning the Salmonella enterica genome. As demonstrated in this study, the ChapterDx MLSTnext-NGS Salmonella can identify serovar with high resolution, distinguishing between various strains of the same serovar and resolve co-presence of different strains in a single sample. Additionally, this assay can analyze up to thousand samples in a single sequencing run within 22 hours, making it a highly efficient and scalable method for the food industry. Moreover, the cost per sample of the ChapterDx MLSTnext-NGS Salmonella assay is comparable to that of quantitative Polymerase Chain Reaction (qPCR), making it an affordable option. The assay uses ChapterDx amplification technology, allowing for the amplification of all 47 loci in a single-tube, single-step PCR reaction. This makes it one of the simplest NGS applications available. In summary, ChapterDx MLSTnext-NGS Salmonella assay can be implemented in many diagnostic laboratories to address increasingly complex food safety issues.

microbiology↗

bioRxiv2022

Towards Hierarchical Causal Representation Learning for Nonstationary Multi-Omics Data

Though open chromatin may promote active transcription, gene expression responses may not be directly coordinated with changes in chromatin accessibility. Most existing methods for single-cell multi-omics data focus only on learning stationary and shared information among these modalities, overlooking modality-specific information delineating cellular states and dynamics resulting from causal relations among modalities. To account for this, the epigenome and transcriptome relationship can be characterized in relation to time as "coupled" (changing dependently) or "decoupled" (changing independently). We propose the framework HALO, which adopts a causal approach to model these temporal causal relations on two levels. On the representation level, HALO factorizes these two modalities into both coupled and decoupled latent representations, identifying the dynamic interplay between chromatin accessibility and transcription through temporal modulations in the latent space. On the individual gene level, HALO matches gene-peak pairs and characterizes changing dynamics between gene expression and local peaks with time. HALO reveals bipotency in a subset of AT2 cells that exhibit different decisions in lineage specification between systemic sclerosis (SSc) and normal conditions. We demonstrate that using coupled and decoupled information, HALO discovers analogous biological functions between modalities, distinguishes epigenetic factors for lineage specification, and identifies temporal cis-regulation interactions relevant to cellular differentiation and complex human diseases.

bioinformatics↗

bioRxiv2022

Exosome-derived lncRNA HOXA-AS3 promotes castration resistance and progression of prostate cancer via the miR-29b-3p/Mcl-1/STAT3 axis

Prostate cancer is one of the leading causes of cancer-related deaths in men. While endocrine therapy is effective in the early stage of metastasis, significantly inhibits the progression of metastatic prostate cancer, most patients eventually develop CRPC. Tumor microenvironment are involved in the progression of prostate cancer as an "accomplice", cancer cell-secreted exosomes were identified as crucial messengers can carry lncRNAs to participate in intercellular communication. we revealed PC-3-derived exosomes promote androgen resistance in LNCaP cells. HOXA-AS3 as a ceRNA of miRNA-29b-3p affects the proliferation and invasion ability of prostate cancer cells. A series of molecular experiments, cell experiments and clinical tissue verification experiments confirmed that HOXA-AS3 participates in the castration resistance and progression of prostate cancer through regulating the miR-29b-3p/Mcl-1/STAT3/Cytochrome C/caspases-9 pathway. Dysregulation of HOXA-AS3 is observed in many cancer types, and this study shows the importance of this lncRNA in controlling prostate cancer cell progression, thus highlighting it as a potential biomarker for inhibiting prostate cancer progression and a target for immunotherapy.

genomics↗

bioRxiv2022

Early events marking lung fibroblast transition to profibrotic state in idiopathic pulmonary fibrosis

BackgroundIdiopathic Pulmonary Fibrosis (IPF) is an age-associated progressive lung disease with accumulation of scar tissue impairing gas exchange. Previous high-throughput studies elucidated the role of cellular heterogeneity and molecular pathways in advanced disease. However, critical pathogenic pathways occurring in the transition of fibroblasts from normal to profibrotic have been largely overlooked. MethodsWe used single cell transcriptomics (scRNA-seq) from lungs of healthy controls and IPF patients (lower and upper lobes). We identified fibroblast subclusters, genes and pathways associated to early disease. Immunofluorescence assays validated the role of MOXD1 early in fibrosis. FindingsWe identified four distinct fibroblast subgroups, including one marking the normal-to-profibrotic state transition. Our results show for the first time that global downregulation of ribosomal proteins and significant upregulation of the majority of copper-binding proteins, including MOXD1, mark the IPF transition. We find no significant differences in gene expression in IPF upper and lower lobe samples, which were selected to have low and high degree of fibrosis, respectively. InterpretationEarly events during IPF onset in fibroblasts include dysregulation of ribosomal and copper-binding proteins. Fibroblasts in early stage IPF have already acquired a profibrotic phenotype while hallmarks of advanced disease, including fibroblast foci and honeycomb formation, are still not evident. The new transitional fibroblasts we discover could prove very important for studying the role of fibroblast plasticity in disease progression and help develop early diagnosis tools and therapeutic interventions targeting earlier disease states.

genomics↗

bioRxiv2022

Intrinsically disordered interaction network in an RNA chaperone revealed by native mass spectrometry

RNA-binding proteins contain intrinsically disordered regions whose functions in RNA recognition are poorly understood. The RNA chaperone Hfq is a homohexamer that contains six flexible C-terminal domains (CTDs). The effect of the CTDs on Hfqs integrity and RNA binding has been challenging to study because of their sequence identity and inherent disorder. We used native mass spectrometry (nMS) coupled with surface-induced dissociation (SID) and molecular dynamics (MD) simulations to disentangle the arrangement of the CTDs and their impact on the stability of E. coli Hfq with and without RNA. The results show that the CTDs stabilize the Hfq hexamer through multiple interactions with the core and between CTDs. RNA binding perturbs this network of CTD interactions, destabilizing the Hfq ring. This destabilization is partially compensated by binding of RNAs that contact multiple surfaces of Hfq. By contrast, binding of short RNAs that only contact one or two subunits results in net destabilization of the complex. Together, the results show that a network of intrinsically disordered interactions integrate RNA contacts with the six subunits of Hfq. We propose that this CTD network raises the selectivity of RNA binding. Significance StatementHfq is a protein hexamer necessary for gene regulation by non-coding RNA in bacteria, during infection or under stress. In the cell, Hfq must distinguish its RNA partners from many similar nucleic acids. Mass spectrometry dissociation patterns, together with molecular dynamics simulations, showed that flexible extensions of each Hfq subunit form a dense network that interconnects the entire hexamer. This network is disrupted by RNA binding, but the lost interactions are compensated by RNAs that contact multiple Hfq subunits. By measuring interactions that are too irregular to be counted by other methods, mass spectrometry shows how flexible protein extensions help chaperones like Hfq recognize their RNA partners in the messy interior of the cell.

biophysics↗

bioRxiv2022

Intermittent fasting mitigates cognitive deficits in Alzheimer's disease via the gut-brain axis

Intermittent fasting (IF) is suggested to mitigate cognitive impairment in Alzheimers disease (AD). We detailed the effects of IF in AD development and assessed the contribution of the gut microbiota-metabolite-brain axis in promoting the effects of fasting. A 16-week IF regimen significantly improved spatial memory and cognitive function in AD transgenic mice; this improvement was accompanied by decreased A{beta} accumulation and suppression of neuroinflammation. IF reshaped the microbiota and beneficially altered the microbial metabolites related to cognitive function. Multi-OMICs integration demonstrated a strong connection between IF induced changes in hippocampus gene expression, the composition of the gut microbes, and the serum metabolites beneficial for cognitive function. Removal of gut microbes with antibiotics abolished the neuroprotective effects of IF. These findings suggest new avenues for therapy and nutritional intervention to prevent the development of AD and other neurodegenerative diseases.

animal behavior and cognition↗

bioRxiv2021

Dynamic Expedition of Leading Mutations in SARS-CoV-2 Spike Glycoproteins

Throughout the coronavirus disease 2019 (COVID-19) pandemic, the continuous genomic evolution of its etiological agent, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has generated many new variants with enhanced transmissibility and immune escape capabilities. Being an essential mediator of infections and a key target of antibodies, mutations of its spike glycoprotein play a vital role in modulating its evolutionary trajectory. Here, we present a time-resolved statistical method, Dynamic Expedition of Leading Mutations (deLemus), to analyze the evolutionary dynamics of the SARS-CoV-2 spike. Together with analysis of its single amino acid polymorphism (SAP), we propose the use of L-index in quantifying the mutation strength of each amino acid site, such that the evolutionary mutation pattern of the spike glycoprotein can be unravelled.

evolutionary biology↗