Biology subjects

Ye, S.

Publications and source records attributed to Ye, S..

At least 55 records · Page 3Linked to original sources

bioRxiv2024

Increased functional integration of emotional control network in late adulthood

Emotional wellbeing has often been shown to improve across the adult lifespan. The corresponding effects, however, in the emotion regulation brain networks remain underexplored. By utilizing large-scale datasets such as the Human Connectome Project (HCP-Aging, N=621, 349 females) and Cambridge Centre for Ageing and Neuroscience (Cam-CAN, N=333, 155 females), we were able to investigate how emotion regulation networks functional topography differs across the entire adult lifespan. Based on previous meta-analytic work that identified four large-scale functional brain networks involved in emotion generation and regulation, we investigated the association between the integration of these emotion regulation networks and measures of mental wellbeing with age in the HCP-Aging dataset. We found an increased functional integration of the emotional control network among older adults, which was replicated using the Cam-CAN dataset. Further we found that the interoceptive network, which is mediating emotion generative and regulative processes and carries our introspective and reflective functions, is less integrated in higher age. Our study highlights the importance of identifying topological changes in the functional emotion network architecture across the lifespan, as it allows for a better understanding of functional brain network changes that accompany emotional aging. HighlightsO_LIWe aimed to identify age-related differences in the functional integration of large-scale emotion regulation brain networks across the adult lifespan, and its implications for well-being. C_LIO_LIFrontal emotion control network showed increased while interoception network showed decreased functional integration with higher age in the HCP-Aging dataset. C_LIO_LIIncreased integration of emotion control network was replicated and validated in the Cam-CAN dataset. C_LI

neuroscience↗

bioRxiv2024

Unraveling the Genetic Comorbidity Landscape of Alzheimer's Disease

Alzheimers disease (AD) has emerged as the most prevalent and complex neurodegenerative disorder among the elderly population. However, the genetic comorbidity etiology for AD remains poorly understood. In this study, we conducted pleiotropic analysis for 41 AD phenotypic comorbidities, identifying ten genetic comorbidities with 16 pleiotropy genes associated with AD. Through biological functional and network analysis, we elucidated the molecular and functional landscape of AD genetic comorbidities. Furthermore, leveraging the pleiotropic genes and reported biomarkers for AD genetic comorbidities, we identified 50 potential biomarkers for AD diagnosis. Our findings deepen the understanding of the occurrence of AD genetic comorbidities and provide new insights for the search for AD diagnostic markers. HighlightsThe present study has focused on the comorbidities associated with Alzheimers disease (AD) by constructing a landscape of these comorbidities at various levels, including diseases, genetics, and pathways. O_LIThe study findings reveal novel and significant pathways that contribute to the etiology of AD and its comorbidities. C_LIO_LIBy exploring pleiotropic genes and reported biomarkers of AD comorbidities, the study has identified several potential diagnostic biomarker candidates for AD. C_LI O_FIG O_LINKSMALLFIG WIDTH=192 HEIGHT=200 SRC="FIGDIR/small/583453v1_figG1.gif" ALT="Figure 1"> View larger version (33K): org.highwire.dtl.DTLVardef@2fc040org.highwire.dtl.DTLVardef@f6d801org.highwire.dtl.DTLVardef@1df65a4org.highwire.dtl.DTLVardef@18a307e_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOGraphic abstract.C_FLOATNO Study pipeline. C_FIG

neuroscience↗

bioRxiv2024

Exploring the repository of de novo designed bifunctional antimicrobial peptides through deep learning

Antimicrobial peptides (AMPs) are attractive candidates to combat antibiotic resistance for their capability to target bio-membranes and restrict a wide range of pathogens. It is a daunting challenge to discover novel AMPs due to their sparse distributions in a vast peptide universe, especially for peptides that demonstrate potencies for both bacterial membranes and viral envelopes. Here we establish a de novo AMP design framework by bridging a deep generative module and a graph-encoding activity regressor. The generative module learns hidden grammars of AMP features and produces candidates sequentially pass antimicrobial predictor and antiviral classifiers. We discover 16 bifunctional AMPs and experimentally validated their abilities to inhibit a spectrum of pathogens in vitro and in animal models. Notably, P076 is a highly potent bactericide with the minimal inhibitory concentration of 0.21 M against multidrug-resistant A. baumannii, while P002 broadly inhibits five enveloped viruses. Our study provides feasible means to uncover sequences that simultaneously encode antimicrobial and antiviral activities, thus bolstering the function spectra of AMPs to combat a wide range of drug-resistant infections.

microbiology↗

bioRxiv2024

BAMBI: Integrative biostatistical and artificial-intelligence method discover coding and non-coding RNA genes as biomarkers

Accurate disease diagnosis and prognosis are crucial for effective treatment management and improving patient outcomes. However, accurately detecting early signs of certain diseases or recurrence remains challenging. Existing machine-learning methods for identifying gene expression biomarkers have several limitations, including poor performance on independent test datasets, inability to directly process omics data, and difficulty in identifying noncoding RNA genes as biomarkers. Additionally, these methods may not provide sufficient biological interpretation of their results, and the panel biomarkers they identify may not be suitable for clinical application. To address these limitations, we have developed a new computational method called BAMBI, which integrates multiple machine-learning algorithms and statistical approaches to identify putative coding and noncoding genes as biomarkers for disease diagnosis and prognosis. We evaluated BAMBI ability to identify diagnostic and prognostic biomarkers by analyzing multiple RNA-seq datasets from cancerous and non-cancerous diseases at population levels. The results from BAMBI demonstrate significant biological interpretability and state-of-the-art prediction performance. When the singular gene identified by BAMBI is used as a diagnostic biomarker, it achieves a balance accuracy exceeding 95% in studies of both breast cancer and psoriasis. Additionally, the prognostic biomarkers that BAMBI identifies from RNA-seq data of Acute Myeloid Leukemia (AML) patients significantly correlate with the survival rates in an independent AML patient cohort. Additionally, BAMBI outperforms existing methods by delivering more robust results, identifying biomarkers with fewer genes, and simultaneously achieving superior prediction accuracy. We have implemented BAMBI into user-friendly software for the research community. In summary, BAMBI serves as a more reliable pipeline for identifying both coding and noncoding genes as biosignature markers, enhancing the accuracy of disease diagnosis and prognosis. BAMBI is available via https://github.com/CZhouLab/BAMBI.

bioinformatics↗

bioRxiv2023

Resilience-driven neural synchrony during naturalistic movie watching: an ultra-high field fMRI study

Psychological resilience protects individuals against the negative consequences of exposure to adversity. Despite increasing attention given to resilience for its role in maintaining mental health, a clear conceptualization of resilience remains elusive, and the intricacies of its neural correlates are poorly understood. Here, we recorded brain activity in healthy young adults using a 7T MRI scanner while they naturally watched movies. Stronger and more extensive resilience-driven neural synchrony, as estimated by inter-subject correlation, was observed in a wider set of brain regions in response to the negative movie compared to the neutral movie. Moreover, we found that high-resilience individuals had similar neural activities to their peers, while low-resilience individuals showed more variable neural activities. Intolerance of uncertainty (IU), a personality trait that shapes biased perception and cognition, damped the resilience-driven brain synchrony in regions related to attention, indicating IU may compromise resilience by affecting attentional functions. We propose that similarity of neural responses among resilient individuals highlights adaptive emotional processing. Conversely, the variability in neural responses indicates vulnerability to adverse psychological outcomes. These insights shed light on the mechanisms of resilience, highlighting that it operates as a system encompassing multiple neuropsychological processes crucial for adapting to external stimuli.

neuroscience↗

bioRxiv2023

Accurate Prediction of Antibody Function and Structure Using Bio-Inspired Antibody Language Model

In recent decades, antibodies have emerged as indispensable therapeutics for combating diseases, particularly viral infections. However, their development has been hindered by limited structural information and labor-intensive engineering processes. Fortunately, significant advancements in deep learning methods have facilitated the precise prediction of protein structure and function by leveraging co-evolution information from homologous proteins. Despite these advances, predicting the conformation of antibodies remains challenging due to their unique evolution and the high flexibility of their antigen-binding regions. Here, to address this challenge, we present the Bio-inspired Anti-body Language Model (BALM). This model is trained on a vast dataset comprising 336 million 40% non-redundant unlabeled antibody sequences, capturing both unique and conserved properties specific to antibodies. Notably, BALM showcases exceptional performance across four antigen-binding prediction tasks. Moreover, we introduce BALMFold, an end-to-end method derived from BALM, capable of swiftly predicting full atomic antibody structures from individual sequences. Remarkably, BALMFold outperforms those well-established methods like AlphaFold2, IgFold, ESMFold, and OmegaFold in the antibody benchmark, demonstrating significant potential to advance innovative engineering and streamline therapeutic antibody development by reducing the need for unnecessary trials.

bioinformatics↗

bioRxiv2023

Comparative chemical genomics in Babesia species identifies the alkaline phosphatase phoD as a novel determinant of resistance

Babesiosis is an emerging zoonosis and widely distributed veterinary infection caused by 100+ species of Babesia parasites. The diversity of Babesia parasites, coupled with the lack of potent inhibitors necessitates the discovery of novel conserved druggable targets for the generation of broadly effective antibabesials. Here, we describe a comparative chemogenomics (CCG) pipeline for the identification of novel and conserved targets. CCG relies on parallel in vitro evolution of resistance in independent populations of evolutionarily-related Babesia spp. (B. bovis and B. divergens). We identified a potent antibabesial inhibitor from the Malaria Box, MMV019266. We were able to select for resistance to this compound in two species of Babesia, achieving 10-fold or greater resistance after ten weeks of intermittent selection. After sequencing of multiple independently derived lines in the two species, we identified mutations in a single conserved gene in both species: a membrane-bound metallodependent phosphatase (putatively named PhoD). In both species, the mutations were found in the phoD-like phosphatase domain, proximal to the predicted ligand binding site. Using reverse genetics, we validated that mutations in PhoD confer resistance to MMV019266. We have also demonstrated that PhoD localizes to the endomembrane system and partially with the apicoplast. Finally, conditional knockdown and constitutive overexpression of PhoD alter the sensitivity to MMV019266 in the parasite: overexpression of PhoD results in increased sensitivity to the compound, while knockdown increases resistance, suggesting PhoD is a resistance mechanism. Together, we have generated a robust pipeline for identification of resistance loci, and identified PhoD as a novel determinant of resistance in Babesia species. HighlightsO_LIUse of two species for in vitro evolution identifies a high confidence locus associated with resistance C_LIO_LIResistance mutation in phoD was validated using reverse genetics in B. divergens C_LIO_LIPerturbation of phoD using function genetics results in changes in the level of resistance to MMV019266 C_LIO_LIEpitope tagging reveals localization to the ER/apicoplast, a conserved localization with a similar protein in diatoms C_LIO_LITogether, phoD is a novel resistance determinant in multiple Babesia spp. C_LI

molecular biology↗

bioRxiv2023

Novel Imaging Guidance for Cholesteatoma Surgery usingTissue Autofluorescence

SignificanceCholesteatoma is an expansile destructive lesion of the middle ear and mastoid, which can result in significant complications by eroding adjacent bony structures. Currently, there is an inability to accurately distinguish cholesteatoma tissue margins from middle ear mucosa tissue, causing a high recidivism rate. Accurately differentiating cholesteatoma and mucosa will enable a more complete removal of the tissue. AimDevelop an imaging system to enhance the visibility of cholesteatoma tissue and margins during surgery. ApproachCholesteatoma and mucosa tissue samples were excised from the inner ear of patients and illuminated with 405, 450, and 520 nm narrowband lights. Measurements were made with a spectroradiometer equipped with a series of different longpass filters. Images were obtained using a red-green-blue (RGB) digital camera equipped with a long pass filter to block reflected light. ResultsCholesteatoma tissue fluoresced under 405 and 450 nm illumination. Middle ear mucosa tissue did not fluoresce under the same illumination and measurement conditions. All measurements were negligible under 520 nm illumination conditions. All spectroradiometric measurements of cholesteatoma tissue fluorescence can be predicted by a linear combination of emissions from keratin and flavin adenine dinucleotide (FAD). We built a prototype of a fluorescence imaging system using a 495 nm longpass filter in combination with an RGB camera. The system was used to capture calibrated digital camera images of cholesteatoma and mucosa tissue samples. The results confirm that cholesteatoma emits light when it is illuminated with 405 and 450 nm, whereas mucosa tissue does not. ConclusionsWe prototyped an imaging system that is capable of measuring cholesteatoma tissue autofluorescence.

bioengineering↗

bioRxiv2023

A Novel Angiogenesis Role of GLP-1(32-36) to Rescue Diabetic Ischemic Lower Limbs via GLP-1R-Dependent Glycolysis

Glucagon-like peptide 1 (GLP-1) improves angiogenesis, but the mechanism remains unclear. To address this question, we conducted a metabolomics analysis in bone marrow-derived endothelial progenitor cells (EPCs) isolated from T1DM mice treated with or without GLP-1(32-36) amide, an end-product of GLP-1. GLP-1(32-36) treatment recovered glycolysis. In addition, GLP-1(32-36) treatment rescued diabetic ischemic lower limbs and EPCs dysfunction by regulating PFKFB3-driven glycolytic flux capacity and mitochondrial dynamics. The effects of GLP-1(32-36) were abolished in mice lacking a functional GLP-1 receptor (Glp1r-/-), which could be partially rescued in EPCs transiently expressing GLP-1R. GLP-1(32-36) treatment activated the eNOS/cGMP/PKG pathway, increased glycolysis, and enhanced EPCs angiogenesis. Taken together, these findings suggest that GLP-1(32-36) could be used as a monotherapy or add-on therapy with existing treatments for DPAD. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=117 SRC="FIGDIR/small/543344v1_ufig1.gif" ALT="Figure 1"> View larger version (50K): org.highwire.dtl.DTLVardef@2559eorg.highwire.dtl.DTLVardef@1430faborg.highwire.dtl.DTLVardef@1b9b188org.highwire.dtl.DTLVardef@36809c_HPS_FORMAT_FIGEXP M_FIG C_FIG

cell biology↗

bioRxiv2023

Allele-specific epigenetic regulation of FURIN expression at a coronary artery disease susceptibility locus

BackgroundGenome-wide association studies have revealed an association between the genetic variant rs17514846 on chromosome 15q26.1 and coronary artery disease susceptibility. Studies have shown that rs17514846 influences the expression of the FES Upstream Region (FURIN) gene located at this locus in monocytes. We investigated the mechanism through which rs17514846 modulates FURIN expression. Methods and ResultsAn analysis of isogenic monocytic cell lines with either the rs17514846 C/C or A/A genotype showed that the cells of the A/A genotype expressed higher levels of FURIN than cells of the C/C genotype. A pyrosequencing methylation analysis showed that the cytosine (in a CpG motif) at the rs17514846 position on the C allele was methylated. Treatment with the DNA methylation inhibitor 5-aza-2-deoxycytidine increased FURIN expression. A bioinformatic analysis indicated that the rs17514846 site might interact with the transcription factor MeCP2 that often functions as a gene repressor by binding to methylated CpG sites. An electrophoretic mobility super-shift assay with a probe corresponding to the DNA sequence at and around the rs17514846 position of the C allele detected two DNA-protein complex bands, which were altered by the addition of an anti-MeCP2 antibody in the assay, whilst these DNA-protein complexes were barely detectable with a probe for the A allele. A chromatin immunoprecipitation assay showed an enrichment of the DNA sequence containing the rs17514846 site in chromatin precipitates pulled down by an anti-MeCP2 antibody. siRNA-mediated knockdown of MeCP2 caused an increase in FURIN expression. Furthermore, MeCP2 knockdown increased monocyte migration and proliferation, and this effect was diminished by a FURIN inhibitor. ConclusionsThe results of our study suggest that DNA methylation inhibits FURIN expression and that the coronary artery disease predisposing variant rs17514846 modulates FURIN expression and monocyte migration via an allele-specific effect on DNA methylation.

genetics↗

bioRxiv2023

Computational insights into the conformational transition of STING: mechanistic, energetic considerations, and the influence of crucial mutations

STING (stimulator of interferon genes) is a crucial protein in the innate immune systems response to viral and bacterial infections. In this study, we investigated the mechanistic and energetic mechanism of the conformational transition process of STING activated by cGAMP binding. We found that the STING connector region undergoes an energetically unfavorable transition during this process, which is compensated by the favorable interaction between cGAMP and the STING ligand binding domain. We utilized enhanced sampling methods to study STINGs rotation and finds that several disease-causing mutations, such as N154S and V155L, can result in a smoother transition process, while V147L exhibits unfavorable conformational transition energy. These findings indicate that V147L may not be a gain-of-function mutation, as previously thought, and are further supported by an evolutionary analysis of the STING connector region. Overall, our study provides detailed insights into the mechanism of STINGs rotation and has implications for the development of treatments for STING-related diseases.

biophysics↗

bioRxiv2023

Frustrated Microphase Separation Produces Interfacial Environment within Biological Condensates

The phase separation of intrinsically disordered proteins is emerging as an important mechanism for cellular organization. However, efforts to connect protein sequences to the physical properties of condensates, i.e., the molecular grammar, are hampered by a lack of effective approaches for probing high-resolution structural details. Using a combination of multiscale simulations and fluorescence lifetime imaging microscopy experiments, we systematically explored a series of systems consisting of diblock elastin-like polypeptides (ELP). The simulations succeeded in reproducing the variation of condensate stability upon amino acid substitution and revealed different microenvironments within a single condensate, which we verified with environmentally sensitive fluorophores. The interspersion of hydrophilic and hydrophobic residues and a lack of secondary structure formation result in an interfacial environment, which explains both the strong correlation between ELP condensate stability and interfacial hydrophobicity scales, as well as the prevalence of protein-water hydrogen bonds. Our study uncovers new mechanisms for condensate stability and organization that may be broadly applicable.

biophysics↗

bioRxiv2023

Micropolarity governs the structural organization of biomolecular condensates

Microenvironment is critical to the function of cells and organisms. One example is provided by biomolecular condensates, whose microenvironment can be vastly different from the surrounding cellular environments to engage unique biological functions. How microenvironments of biomolecular condensates affect their structure and function remains unknown. Here, we show that the arrangements and partitioning of biomolecules are dictated by the differences between the micropolarity of each subcompartment. Sufficient difference in micropolarity results in layered structures with the exterior shell presenting a more polar microenvironment than the interior core. Accordingly, micropolarity inversion is accompanied by conversions of the layered structures. These findings demonstrated the central role of the previously overlooked microenvironment in regulating the structural organization and function of membraneless organelles.

biochemistry↗

bioRxiv2023

Keypoint-MoSeq: parsing behavior by linking point tracking to pose dynamics

Keypoint tracking algorithms have revolutionized the analysis of animal behavior, enabling investigators to flexibly quantify behavioral dynamics from conventional video recordings obtained in a wide variety of settings. However, it remains unclear how to parse continuous keypoint data into the modules out of which behavior is organized. This challenge is particularly acute because keypoint data is susceptible to high frequency jitter that clustering algorithms can mistake for transitions between behavioral modules. Here we present keypoint-MoSeq, a machine learning-based platform for identifying behavioral modules ("syllables") from keypoint data without human supervision. Keypoint-MoSeq uses a generative model to distinguish keypoint noise from behavior, enabling it to effectively identify syllables whose boundaries correspond to natural sub-second discontinuities inherent to mouse behavior. Keypoint-MoSeq outperforms commonly used alternative clustering methods at identifying these transitions, at capturing correlations between neural activity and behavior, and at classifying either solitary or social behaviors in accordance with human annotations. Keypoint-MoSeq therefore renders behavioral syllables and grammar accessible to the many researchers who use standard video to capture animal behavior.

neuroscience↗

bioRxiv2023

Probing the hierarchical dynamics of DNA-sperm nuclear transition protein complex through fuzzy interaction and mesoscale condensation

Nuclear transition protein TNP1 is a crucial player mediating histone-protamine exchange in condensing spermatids. A unique combination of intrinsic disorder and multivalent properties turns TNP1 into an ideal agent for orchestrating the formation of versatile TNP-DNA assembly and endows the protein with potent value for vaccine design. Despite its significance, the physicochemical property and the molecular mechanism taken by TNP1 for histone replacement and DNA condensation are still poorly understood. In this study, for the first time, we expressed and purified in vitro human TNP1. We investigated the hierarchical dynamics of TNP1: DNA interaction by combing computational simulations, biochemical assay, fluorescence imaging, and atomic force microscopy. We analyzed fuzzy interactions between TNP1 and DNA at the atomistic level and assessed the influence of TNP1 association on the electrostatic and mechanical properties of DNA. Furthermore, the alteration of the physicochemical properties of the TNP1-DNA complex modulates its molecular assembly and phase separation. Our study sets the foundation for understanding TNP1-mediated histone replacement and sheds light on the encapsulation of genetic material by TNP1 for vaccine development.

biophysics↗

bioRxiv2023

Cryo-EM structure of the polyphosphate polymerase VTC: Coupling polymer synthesis to membrane transit

The eukaryotic polyphosphate (polyP) polymerase VTC complex synthesizes polyP from adenosine triphosphate (ATP) and translocates polyP across the vacuolar membrane to maintain an intracellular phosphate (Pi) homeostasis. To discover how VTC complex solves this fundamental aspect, we determined a cryo-electron microscopy structure of an endogenous VTC complex (Vtc4/Vtc3/Vtc1) from Saccharomyces cerevisiae at 3.1 [A] resolution. The structure reveals a heteropentameric architecture of one Vtc4, one Vtc3 and three Vtc1 subunits. The transmembrane region forms a polyP selective channel, probably adopting a resting state conformation, in which a latch-like, horizonal helix of Vtc4 limits the entrance. The catalytic Vtc4 central domain locates on top of the pseudo-symmetric polyP channel, creating a strongly electropositive pathway for nascent polyP that can couple synthesis to translocation. The SPX domain of Vtc4 positively regulates polyP synthesis and regulation of VTC complex. The non-catalytic Vtc3 regulates VTC through a phoshorylatable loop. Our findings, along with the functional data, allow us to propose a mechanism of polyP channel gating and VTC complex activation.

biophysics↗

bioRxiv2023

Astrocytic connection to engram neurons increased after learning

Astrocytes directly participate in learning and memory. However, the structural association between astrocytes and memory-encoding engram neurons after learning remains to be elucidated. We developed astrocyte-enhanced green fluorescent protein reconstitution across synaptic partners (eGRASP) to examine tripartite synapses between astrocytes and engram neurons. Using astrocyte-eGRASP, we found that astrocytes had increased connections to engram neurons after learning. Dendritic spines with astrocytic contacts showed enhanced morphology. Live-cell imaging of astrocyte-eGRASP revealed that astrocytic connections are stabilized by neuronal activity. These results indicate that astrocytes distinguish contact between engram neurons and generate engram-specific contact patterns during learning.

neuroscience↗

bioRxiv2023

Identification and Characterization of novel long non-coding RNAs in vascular smooth cells

A significant portion of the RNA produced from the human genome consists of long non-coding RNAs (lncRNAs). These molecules tend to have lower levels of expression, are more specific to certain tissues, and show greater variation in expression between individuals compared to protein-coding messenger RNAs (mRNAs). LncRNAs have been linked with regulatory roles in gene expression and genome architecture. There is growing evidence that lncRNAs play important roles in many biological processes and diseases, and a number of lncRNAs have been identified as potential therapeutic targets. Here, we report the identification and characterization of the lncRNA landscape of vascular smooth muscle cells (VSMC). We used an ensemble of bioinformatics tools to identify 329 novel lncRNAs from a large VSMC RNA-Seq dataset. We found that majority of the novel lncRNAs are natural antisense transcripts of protein-coding genes. In addition, we predicted cellular localization and potential miRNAs that targets the novel lncRNAs and found that most localize in the cytoplasm and that miRNA target site ranged from 2-889 sites on each novel lncRNA. Furthermore, we identified co-expressed lncRNAs that correlate with the proliferation, migration and apoptosis of vascular smooth muscle cells. These results suggest that we have identified a diverse set of previously unknown lncRNAs that may be involved in important regulatory pathways in vascular smooth muscle cells.

bioinformatics↗