Biology subjects

Zhao, K.

Publications and source records attributed to Zhao, K..

At least 55 records · Page 3Linked to original sources

bioRxiv2024

Elucidating the neuropathological and molecular heterogeneity of amyloid-beta and tau in Alzheimer's disease through machine learning and transcriptomic integration

Discerning functional brain network variations related to neuropathological aggregates in Alzheimers disease (AD), including amyloid-{beta} (A{beta}) and phosphorylated tau (p-tau), is crucial for understanding their link to cognitive decline and underlying molecular mechanisms. However, these variations are often confounded by normal aging-related changes, complicating interpretation. To address this challenge, we first defined Alzheimers continuum cases (A{beta} positive (A+), n = 129) and normal elderly (A{beta} negative (A-), n = 160) using cerebral spinal fluid amyloid levels, and then applied a novel deep learning approach to resting-state connectivity using functional magnetic resonance imaging (fMRI) of the 289 subjects to disentangle A+-specific dimensions in brain network alterations from those shared with A- individuals. The identified A+-specific dimensions were further refined to predict individual A{beta} and p-tau levels separately. We observed that resulting brain signatures, defined from A+-specific dimensions for predicting these two CSF biomarkers, were both attributed to the right superior temporal and anterior cingulate cortices and associated with attention and memory domains. When linking the brain signatures to gene expression data from a public transcriptomic atlas, we found that the brain signatures were associated with molecular pathways involving synaptic dysfunction and disruptions in pathways containing activity of excitatory neurons, astrocytes, and microglia. For A--shared dimensions, the A{beta}-linked brain signature involved the left fusiform and right middle cingulate cortices, correlating with the language cognitive measurement and language-related molecular pathways. The p-tau-linked signature predominantly involved the right insula and inferior temporal cortices, correlating with the aging-related molecular pathways. Collectively, our findings provided new insights in understanding of Alzheimers continuum pathological biomarkers.

neuroscience↗

bioRxiv2024

The role of PilU in the surface behaviors of Pseudomonas aeruginosa

In Pseudomonas aeruginosa, the dynamic activity of type IV pilus (TFP) is essential for various bacterial behaviors. While PilU is considered a homolog of the TFP disassembling motor PilT, its specific roles remain unclear. Using pilus visualization and single-cell tracking techniques, we characterized TFP dynamics and surface behaviors in wild-type and {Delta}pilU mutants. We found that {Delta}pilU cells displayed increased TFP numbers but reduced cell movement and delayed microcolony formation. Interestingly, beyond affecting the twitching motility, {Delta}pilU cells formed a thick multilayered colony edge on semi-solid surfaces, slowing colony expansion. Cell-cell collision responses changed from touch-turn dominance in wild-type to touch-upright dominance in {Delta}pilU, affecting colony morphology and expansion. These findings expand our understanding of PilUs physiological roles and provide potential targets for developing strategies to control P. aeruginosa biofilm formation and virulence. IMPORTANCEThe dynamic function of TFP can help cells to search appropriate spatial positions and perceive external environments, and is crucial for a variety of cell behaviors including cell movement, pathogenesis, natural transformation and biofilm formation. Beyond the current picture of PilU in generating high retraction forces through a PilT-dependent manner, this study revealed more roles of PilU in cell surface behaviors including single cell behavior like twitching and multicellular behaviors such as microcolony formation and colony expansion. These findings expand our understanding on the physiological roles of PilU in the surface behaviors of P. aeruginosa, and provide us insight in developing TFP-based methods to control the pathogenicity and biofilm formation of P. aeruginosa.

microbiology↗

bioRxiv2024

Deciphering the Cell Specific Transcript Heterogeneity and Alternative Splicing during the Early Embryonic Development of Zebrafish

Cell fate determination during early embryonic development is a complex process modulated by gene expression. The intricate interplay of transcriptional and post-transcriptional regulation is integral to the developmental trajectory of embryogenesis, yet how RNA processing may contribute to early development programming is largely elusive. Leveraging recent technological advances in single-molecule nanopore sequencing, we developed a single-cell long-read transcriptome sequencing technology, allowing a clear view of transcript diversity during zebrafish embryogenesis during pre- and post-zygotic genome activation (ZGA). A closer examination of the dynamic transcript usage and potential alternative splicing revealed that abundant stage-specific transcripts with differential coding potentials are involved in distinct biological functions. Specifically, we identified two cell populations at the onset of ZGA based on isoform diversity instead of gene profiling, which followed divergent developmental trajectories toward the ectoderm and the presumptive ectoderm. These two populations of cells were characterized by divergent splicing regulations linked to differential RNA-binding proteins, including SNRPA and SFPQ. Altogether, using the single-cell long-read transcriptome sequencing strategy, we work has revealed the cell-specific transcriptome dynamics contributing to the cell fate determination during embryogenesis.

developmental biology↗

bioRxiv2024

Longevity or Well-being? A Dual-Dimension Structure of Neuroticism

The development of personality traits is often viewed as evolutionarily adaptive. Current neuroticism research, however, predominantly highlights its negative health impacts, neglecting its potential evolutionary advantages. We propose that neuroticisms inter-individual variability can be structured into two distinct geometric dimensions. One, named the Emotional Reactivity-Instability/Distress Spectrum (ERIS), correlates strongly with longevity and is associated with chronic diseases and risk-averse lifestyle. This dimension is underpinned by evolutionarily conserved subcortical brain regions and genes. The other, resembling the overall neuroticism score, is primarily linked to mental and stress-related disorders, as well as life satisfaction. It involves higher-order emotional brain regions and is genetically enriched in human-accelerated regions. Collectively, these dimensions represent a dual-strategy personality framework that optimizes survival and well-being, with the former being evolutionarily conservative and the latter potentially a unique human adaptation.

neuroscience↗

bioRxiv2024

Optimal CXCR5 Expression during Tfh Maturation Involves the Bhlhe40-Pou2af1 Axis

The pair of transcription factors Bcl6-Blimp1 is well-known for follicular T helper (Tfh) cell fate determination, however, the mechanism(s) for Bcl6-independent regulation of CXCR5 during Tfh migration into germinal center (GC) is still unclear. In this study, we uncovered another pair of transcription factors, Bhlhe40-Pou2af1, that regulates CXCR5 expression. Pou2af1 was specifically expressed in Tfh cells whereas Bhlhe40 expression was found high in non-Tfh cells. Pou2af1 promoted Tfh formation and migration into GC by upregulating CXCR5 but not Bcl6, while Bhlhe40 repressed this process by inhibiting Pou2af1 expression. RNA-Seq analysis of antigen-specific Tfh cells generated in vivo confirmed the role of Bhlhe40-Pou2af1 axis in regulating optimal CXCR5 expression. Thus, the regulation of CXCR5 expression and migration of Tfh cells into GC involves a transcriptional regulatory circuit consisting of Bhlhe40 and Pou2af1, which operates independent of the Bcl6-Blimp1 circuit that determines the Tfh cell fate.

immunology↗

bioRxiv2024

Scheduled feeding improves sleep in a mouse model of Huntington's disease.

Sleep disturbances are common features of neurodegenerative disorders including Huntingtons disease (HD). The sleep and circadian disruptions are recapitulated in animal models, and these models provide the opportunity to evaluate whether circadian interventions can be effective countermeasures for neurodegenerative disease. Time restricted feeding (TRF) interventions successfully improve activity rhythms, sleep behavior and motor performance in mouse models of HD. Seeking to determine if these benefits of scheduled feeding extend to physiological measures of sleep, electroencephalography (EEG) was used to measure sleep/wake states and polysomnographic patterns in adult mice (six mo-old) under TRF and ad lib feeding (ALF). With each diet, both male and female wild-type (WT) and bacterial artificial chromosome transgenic (BACHD) mice were evaluated. Our findings show that male, but not female, BACHD mice exhibited significant changes in the temporal patterning of wake and non-rapid eye movement (NREM) sleep. The TRF intervention reduced the inappropriate early morning activity by increasing NREM sleep in the male BACHD mice. In addition, the scheduled feeding reduced sleep fragmentation (# bouts) in the male BACHD mice. The phase of the rhythm in rapid-eye movement (REM) sleep was significantly altered by the scheduled feeding. The treatment did impact the power spectral curves during the day in male but not female mice. Sleep homeostasis, as measured by the response to six hours of gentle handling, was not altered by the diet. Thus, TRF improves the temporal patterning and fragmentation of NREM sleep without impacting sleep homeostasis. This work adds critical support to the view that sleep is a modifiable risk factor in neurodegenerative diseases.

neuroscience↗

bioRxiv2024

Delineating Transdiagnostic Subtypes in Neurodevelopmental Disorders via Contrastive Graph Machine Learning of Brain Connectivity Patterns

Neurodevelopmental disorders, such as Attention Deficit/Hyperactivity Disorder (ADHD) and Autism Spectrum Disorder (ASD), are characterized by comorbidity and heterogeneity. Identifying distinct subtypes within these disorders can illuminate the underlying neurobiological and clinical characteristics, paving the way for more tailored treatments. We adopted a novel transdiagnostic approach across ADHD and ASD, using cutting-edge contrastive graph machine learning to determine subtypes based on brain network connectivity as revealed by resting-state functional magnetic resonance imaging. Our approach identified two generalizable subtypes characterized by robust and distinct functional connectivity patterns, prominently within the frontoparietal control network and the somatomotor network. These subtypes exhibited pronounced differences in major cognitive and behavioural measures. We further demonstrated the generalizability of these subtypes using data collected from independent study sites. Our data-driven approach provides a novel solution for parsing biological heterogeneity in neurodevelopmental disorders.

neuroscience↗

bioRxiv2024

Communication with Surprise - Computational and Neural Mechanisms for Non-Verbal Human Interactions

Communication, often grounded in shared expectations, faces challenges without common linguistic backgrounds. Our study explores how people instinctively turn to the fundamental principles of the physical world to overcome communication barriers. Specifically, through the Tacit Communication Game, we investigate how participants develop novel strategies for conveying messages without relying on common linguistic signals. We developed a new computational model built from the principle of expectancy violations of a set of common universal priors derived from movement kinetics. The model closely resembles the Senders messages, with its core variable - the information-theoretic surprise - explaining the Receivers physiological and neural responses. This is evidenced by a significant correlation with the pupil diameter, indicating cognitive effort, and neural activity in brain areas related to expectancy violations. This work highlights the adaptability of human communication, showing how surprise can be a powerful tool in forming new communicative strategies without relying on common language.

neuroscience↗

bioRxiv2024

The Drosophila histone methyl-transferase SET1 coordinates multiple signaling pathways in regulating male germline stem cell maintenance and differentiation

Many cell types come from tissue-specific adult stem cells that maintain the balance between proliferation and differentiation. Here, we study how the H3K4me3 methyltransferase, Set1, regulates early-stage male germ cell proliferation and differentiation in Drosophila. Early-stage germline-specific knockdown of set1 results in a temporally progressed defects, arising as germ cell loss and developing to overpopulated early-stage germ cells. These germline defects also impact the niche architecture and cyst stem cell lineage in a non-cell-autonomous manner. Additionally, wild-type Set1, but not the catalytically inactive Set1, could rescue the set1 knockdown phenotypes, highlighting the functional importance of the methyl-transferase activity of the Set1 enzyme. Further, RNA-seq experiments reveal key signaling pathway components, such as the JAK-STAT pathway gene stat92E and the BMP pathway gene mad, that are upregulated upon set1 knockdown. Genetic interaction assays support the functional relationships between set1 and JAK-STAT or BMP pathways, as mutations of both the stat92E and mad genes suppress the set1 knockdown phenotypes. These findings enhance our understanding of the balance between proliferation and differentiation in an adult stem cell lineage. The germ cell loss followed by over-proliferation phenotypes when inhibiting a histone methyl-transferase raise concerns about using their inhibitors in cancer therapy.

developmental biology↗

bioRxiv2023

SPDesign: protein sequence designer based on structural sequence profile using ultrafast shape recognition

Designing protein with specified structure and function involves a key component named sequence design, which can provide valuable insights into understanding the life systems as well for the diagnosis and therapy of diseases. Although deep learning methods have made great progress in protein sequence design, most of these studies focus on network structure optimization, while ignoring protein-specific physicochemical features. Inspired by the successful application of structure templates and pre-trained models in the field of protein structure prediction, we explored whether the representation of structural sequence profile can be used for protein sequence design. In this work, we proposed SPDesign, a method for protein sequence design based on structural sequence profile using ultrafast shape recognition. Given an input back-bone structure, SPDesign utilizes ultrafast shape recognition vectors to accelerate the search for similar protein structures (aka, structural analogs) in our in-house PAcluster80 structure database, and then extracts the sequence profile from the analogs through structure alignment. Combined with structural pre-trained knowledge and geometric features, they are further feed into an enhanced graph neural network to predict the sequence. Experimental results show that SPDesign significantly outperforms the state-of-the-art methods, such as ProteinMPNN, Pifold and LM-Design, leading to 21.89%, 15.54% and 11.4% accuracy gains in sequence recovery rate on CATH 4.2 benchmark, respectively. Encouraging results also have been achieved on the TS50 and TS500 benchmarks, with performance reaching 68.64% and 71.63%. Furthermore, detailed analysis conducted by the PDBench tool suggest that SPDesign performs well in subdivided structures such as buried residues and solenoid. More interestingly, we found that SPDesign can well reconstruct the sequences of some proteins that have similar structures but different sequences. Finally, the structural modeling verification experiment bears out that the sequences designed by our method can fold into the native structures more accurately.

bioinformatics↗

bioRxiv2023

A genome-wide association study of neonatal metabolites

The hereditary component significantly influences the concentration of metabolites in adults. Nevertheless, the precise influence of genetic factors on neonatal metabolites remains uncertain. To bridge this gap, we employed genotype imputation techniques on large-scale low-pass genome data obtained from non-invasive prenatal testing. Subsequently, we conducted association studies on a total of 75 metabolic components in neonates. The study identified a total 17 previous reported associations and 13 novel discovered associations between single nucleotide polymorphisms and metabolic components. These associations were initially found in the discovery cohort (8,744 participants) and subsequently confirmed in a replication cohort (19,041 participants). The average heritability of metabolic components was calculated to be 76.2%, with a range of 69-78.8%. The aforementioned findings offer valuable insights pertaining to the genetic architecture of neonatal metabolism. In BriefLarge-scale genomes of maternal non-invasive prenatal testing provide insights into the genetic contribution to neonatal metabolism. HighlightsGWAS of 27,785 low-pass genomes revealed 13 novel associations of neonatal metabolic components. Estimated an average of 76.2% heritability of neonatal metabolic components and showed the individual concentration can be accurately predicted from polygenic risk scores. A total of 17 established relationships have been observed, providing evidence that maternal genomes can be utilized in neonatal metabolite GWAS.

genetics↗

bioRxiv2023

Small RNA Analysis of Virus-virus Interaction between Two Orthotospoviruses

Mixed infections of plant viruses are commonly found in natural patho-systems and pre-sent a valuable opportunity to understand how multiple viruses can co-infect the same host. Tomato spotted wilt orthotospovirus (TSWV) and impatiens necrotic spot orthotospovirus (INSV) are pre-sent in the same geographic areas and are closely related. More mixed infections of TSWV and INSV have been reported in recent years, and the INSV host range has been reported to be increasing. In a previous study, we have isolated one strain of INSV and one of TSWV and showed that they have an antagonistic relationship in their vectors, but we were unable to determine, the underlying mech-anisms governing their antagonism in planta and the contribution of the host to this. Here, we used small RNA sequencing to study TSWV-INSV antagonistic interaction and showed that INSV alters plant responses and the processing of TSWV.

plant biology↗

bioRxiv2023

Physical fitness and motor competence performance characteristics of elite Chinese youth athletes from four track and field throwing disciplines - a cross sectional study

PurposeSystematic athletic training during adolescence may facilitate the development of sport-specific skills and the expression of sport-specific physical characteristics in young athletes. The aim of this study was to differentiate male athletes aged 14-17 years from four different throwing disciplines using anthropomorphic measurements and motor competence performance tests, in order to test whether athletes from different disciplines have physical form and fitness characteristics consistent with the sport-specific demands of each throwing discipline. MethodsThe sample consisted of 289 male youth athletes belonging to the four different throwing disciplines: shot put (n=101), hammer throw (n=16), discus throw (n=63), and javelin throw (n=109). The performance diagnosis comprised three anthropometric measurements, and twelve physical fitness tests. Discriminant analysis and neural network (Multilayer Perceptron) were used to test whether it is possible to discriminate between athletes of the four sports. ResultsThe results of this study show that for male throwing athletes aged 14-17 years, differences in generic anthropometric and sport performance tests distinguish the talent of more than two-thirds of young athletes based on individual sport (DA: 68.7%; MLP: 72.2%), regardless of the classification method used. ConclusionThe relevance of the three anthropometric parameters and twelve physical fitness measures for talent identification and training monitoring in the track and field throwing disciplines was confirmed. The discus throwers had a height advantage, the shot putters and hammer throwers had better arm strength, while the javelin throwers had better explosive strength and sprint speed. All events, except the hammer throwers, showed a high level of explosive power in the medicine ball forward or backward throw test. This was particularly important for the shot put and discus athletes.

physiology↗

bioRxiv2023

Defining Dementia Subtypes Through Neuropsychiatric Symptom-Linked Brain Connectivity Patterns

BACKGROUNDDementia is highly heterogeneous, with pronounced individual differences in neuropsychiatric symptoms (NPS) and neuroimaging findings. Understanding the heterogeneity of NPS and associated brain abnormalities is essential for effective management and treatment of dementia. METHODSUsing large-scale neuroimaging data from the Open Access Series of Imaging Studies (OASIS-3), we conducted a multivariate sparse canonical correlation analysis to identify functional connectivity-informed symptom dimensions. Subsequently, we performed a clustering analysis on the obtained latent connectivity profiles to reveal neurophysiological subtypes and examined differences in abnormal connectivity and phenotypic profiles between subtypes. RESULTSWe identified two reliable neuropsychiatric subsyndromes - behavioral and anxiety in the connectivity-NPS linked latent space. The behavioral subsyndrome was characterized by the connections predominantly involving the default mode and somatomotor networks and neuropsychiatric symptoms involving nighttime behavior disturbance, agitation, and apathy. The anxiety subsyndrome was mainly contributed by connections involving the visual network and the anxiety neuropsychiatric symptom. By clustering individuals along these two subsyndromes-linked connectivity latent features, we uncovered three subtypes encompassing both dementia patients and healthy controls. Dementia in one subtype exhibited similar brain connectivity and cognitive-behavior patterns to healthy individuals. However, dementia in the other two subtypes showed different dysfunctional connectivity profiles involving the default mode, frontoparietal control, somatomotor, and ventral attention networks, compared to healthy individuals. These dysfunctional connectivity patterns were associated with differences in baseline dementia severity and longitudinal progression of cognitive impairment and behavioral dysfunction. CONCLUSIONSOur findings shed valuable insights into disentangling the neuropsychiatric and brain functional heterogeneity of dementia, offering a promising avenue to improve clinical management and facilitate the development of timely and targeted interventions for dementia patients.

neuroscience↗

bioRxiv2023

ALS-causing SOD1 mutations H46R and G85R form similar novel amyloid fibril structures and promote ferroptosis in cells

More than two hundred genetic mutations of Cu, Zn-superoxide dismutase (SOD1) have been identified in amyotrophic lateral sclerosis (ALS), a neurodegenerative disease characterized by the selective death of motor neurons through ferroptosis. Two ALS-causing SOD1 mutations, H46R and G85R, are metal-binding region mutants with reduced affinity for metal ions. Here, we generated amyloid fibrils from the apo forms of H46R and G85R under reducing conditions and determined their structures using cryo-EM. We built models for the fibril cores, comprising residues 85-153 for H46R and 82-153 for G85R. These mutations disrupt crucial interactions in the wild-type SOD1 fibril, resulting in amyloid fibrils with distinct structures compared to the wild-type fibril. Remarkably, H46R and G85R form similar novel amyloid fibril structures. The fibril cores display a serpentine fold containing seven or eight {beta}-strands, which are stabilized by a hydrophobic cavity. In the G85R fibril core, Arg85 and Asp101 form a salt bridge for stabilization. We demonstrate that fibril seeds from H46R and G85R cause more severe mitochondrial impairment and significantly promote ferroptosis in neuronal cells, compared with those from wild-type SOD1. Our findings reveal how different SOD1 mutations can result in similar amyloid fibril structures and contribute to ALS pathology.

biochemistry↗

bioRxiv2023

Dissecting Symptom-linked Dimensions of Resting-State Electroencephalographic Functional Connectivity in Autism with Contrastive Learning

Autism spectrum disorder (ASD) is a common neurodevelopmental disorder characterized by social interaction deficits, communication difficulties, and restricted/repetitive behaviors or fixated interests. Despite its high prevalence, development of effective therapy for ASD is hindered by its symptomatic and neurophysiological heterogeneities. To collectively dissect the ASD heterogeneity in neurophysiology and symptoms, we develop a new analytical framework combining contrastive learning and sparse canonical correlation analysis to identify resting-state EEG connectivity dimensions linked to ASD behavioral symptoms within 392 ASD samples. Two dimensions are successfully identified, showing significant correlations with social/communication deficits (r = 0.70) and restricted/repetitive behaviors (r = 0.45), respectively. We confirm the robustness of these dimensions through cross-validation and further demonstrate their generalizability using an independent dataset of 223 ASD samples. Our results reveal that the right inferior parietal lobe is the core region displaying EEG activity associated with restricted/repetitive behaviors, and functional connectivity between the left angular gyrus and the right middle temporal gyrus is a promising biomarker of social/communication deficits. Overall, these findings provide a promising avenue to parse ASD heterogeneity with high clinical translatability, paving the way for treatment development and precision medicine for ASD.

neuroscience↗

bioRxiv2023

Domain-based multi-domain protein and complex structure prediction using inter-domain interactions from deep learning

Accurately capturing domain-domain interactions is key to understanding protein function and designing structure-based drugs. Although AlphaFold2 has made a breakthrough on single domain, it should be noted that the structure modeling for multi-domain protein and complex remains a challenge. In this study, we developed a multi-domain and complex structure assembly protocol, named DeepAssembly, based on domain segmentation and single domain modeling algorithms. Firstly, DeepAssembly uses a population-based evolutionary algorithm to assemble multi-domain proteins by inter-domain interactions inferred from a developed deep learning network. Secondly, protein complexes are assembled by means of domains rather than chains using DeepAssembly. Experimental results show that on 219 multi-domain proteins, the average inter-domain distance precision by DeepAssembly is 22.7% higher than that of AlphaFold2. Moreover, DeepAssembly improves accuracy by 11.8% for 164 multi-domain structures with low confidence deposited in AlphaFold database. We apply DeepAssembly for the prediction of 247 heterodimers. We find that DeepAssembly generates models with acceptable quality (DockQ [≥] 0.23) for 32.4% of the dimers, suggesting a lighter way to assemble complex structures by treating domains as assembly units and using inter-domain interactions learned from monomer structures.

bioinformatics↗

bioRxiv2023

Endogenous fine-mapping of functional regulatory elements in complex genetic loci

The vast majority of genetic loci associated with polygenic complex traits are located in non-coding regions of the human genome. However, many of these regions exhibit high- order gene regulatory relationships and complicated linkage disequilibrium (LD) configurations, which bring challenges to accurately identify causal variants and their target genes controlling specific molecular processes or traits. We employed multiplexed single-cell CRISPR interference and activation perturbations to explore the links between cis-regulatory element (CRE) and target gene expression within tight LD in the endogenous chromatin context. We validated the prevalence of multiple causality in perfect LD (pLD) for independent expression quantitative trait locus (eQTL), and revealed fine-grained genetic effects on gene expression within pLD. These effects are difficult to decipher using conventional eQTL fine-mapping or to predict via existing computational methods. We found that nearly half of the casual CREs lack classical epigenetic markers, potentially affecting gene expression through hidden regulatory mechanisms. Integrative analysis on different types of perturbation effects suggested a high regulatory plasticity of the human genome. These findings will propel further in-depth exploration of functional genomic elements, facilitating a more comprehensive understanding of gene expression regulatory patterns and the development of complex traits.

genomics↗