Biology subjects

Zhang, X.-H.

Publications and source records attributed to Zhang, X.-H..

12 recordsLinked to original sources

bioRxiv2026

De novo design of functional RNAs through higher-order interactions

Designing RNA sequences that reliably adopt functional three-dimensional structures remains a central challenge in RNA engineering because folding depends on cooperative interactions beyond canonical base pairing. Here we present DS3dRNA, an interaction-based framework for de novo RNA sequence design that combines a three-body statistical potential with physics-guided sequence sampling and supports design against multiple conformations. Across the evaluated benchmarks, DS3dRNA outperformed representative RNA inverse-design methods in native-sequence recovery and agreement between predicted and target structures. Energy-sequence-quality analyses further showed that lower design energies generally accompanied higher sequence recovery and macro-averaged F1 scores (MacroF1). Experimentally tested Mango II designs retained high-affinity fluorogenic activity, and five twister ribozyme designs yielded mean endpoint cleavage fractions of 37.7-50.6%, compared with 23.5% for the wild type. These results establish explicit higher-order interaction scoring as a complementary approach to emerging data-driven RNA design methods and provide a framework for designing functional RNAs from experimental or predicted structural ensembles.

biophysics↗

bioRxiv2025

The cellular associates of late life changes in white matter microstructure

The microstructural architecture of white matter supporting information flow across local circuits and large-scale networks changes throughout the lifespan. However, the genetic and cellular factors underlying age-related variations in white matter microstructure have yet to be established. Here, we examined the genetic associates of individual differences in diffusion-based measures of white matter in a population-based cohort (N=29,862) from the UK Biobank. Estimates of heritability from Genome-Wide Association Study (GWAS) data revealed that genetic factors are linked to population variability in 96.1% of 432 tract microstructural measures. The presence of shared genetic influences was observed to be greater within, relative to between, broad tract classes (commissural, association, projection, and complex cerebellar). Age associations with microstructural changes were estimated across diffusivity measures, with association class tracts showing the greatest vulnerability to age-related decline in older adults. Analyses of imputed cellular associates of age-related changes in white matter revealed a preferential relationship with cell gene markers of oligodendrocytes and other glial cell types, with sparse relationships observed for inhibitory and excitatory cells. These data indicate that white matter tract microstructure is shaped by genetic factors and suggest a role for glial cell-related transcripts in late-life changes in the structural wiring properties of the human brain. Significance StatementThe structural wiring of the human brain supports interregional communication and is essential for cognition, yet the genetic and cellular drivers underlying age-related changes are not well understood. Here, we characterize the extent to which genetic factors follow the major organizational patterns of white matter connectivity and associated age-related changes in late life. Age-related changes were most pronounced in late-developing association tracts, key pathways for higher cognitive functions. By integrating genetic and transcriptomic data, we show that genetic variation linked to glial cell markers accounts for a substantial proportion of age-related white matter changes. These findings provide a mechanistic framework for understanding genetic and cellular determinants of structural brain aging.

neuroscience↗

bioRxiv2025

Subtyping psychotic disorders using a data-driven approach reveals divergent cortical and cellular signatures

Structural brain abnormalities in psychosis are well-replicated but heterogenous posing a barrier to uncovering the pathophysiology, etiology, and treatment of psychosis. To parse neurostructural heterogeneity and assess for the presence of anatomically-derived subtypes, we applied a data-driven method, similarity network fusion (SNF), to structural neuroimaging data in a broad cohort of individuals with psychosis (schizophrenia spectrum disorders (SSD) n=280; bipolar disorder with psychotic features (BD) n=101). SNF identified two transdiagnostic subtypes in psychosis (subtype 1: n=158 SSD, n=75 BD; subtype 2: n=122 SSD, n=26 BD) that exhibited divergent patterns of abnormal cortical surface area and subcortical volumes. Compared to controls (n=243), subtype 1 showed moderate enlargement of surface area in frontal and parietal areas and larger dorsal striatal volumes, whereas subtype 2 demonstrated markedly smaller surface areas in frontal and temporal areas and subcortical volumes, including hippocampus, amygdala, thalamus and ventral striatum. When comparing subtypes on clinical characteristics, subtype 2 had more severe negative symptoms, greater neuropsychological impairment, and lower estimated premorbid intellectual functioning compared to subtype 1. Integrating cell-type data imputed from gene expression in the Allen Human Brain Atlas revealed an association between interregional reductions in surface area and layer 5 glutamatergic neuron abundance, critical for corticostriatal network connectivity and cognitive function, whereas reductions in cortical thickness spatially coupled with glia cell and interneuron abundance, in subtype 2. These outcomes indicate that regional variations in surface area, linked to different cell-types than cortical thickness, may be an important biomarker for understanding the pathophysiological trajectories of psychotic disorders.

neuroscience↗

bioRxiv2025

Proposal of two new genera and seventy-seven new species of ascomycetous yeasts isolated from China

Ascomycetous yeasts belong to Saccharomycotina and Taphrinomycotina, with about 1,200 described species distributed worldwide. More than 300 ascomycetous yeast species have been reported from China, which indicates that China possesses a hotspot with high yeast diversity. However, our knowledge of yeast diversity and distribution remains limited, and this area needs to be explored in depth. Here we describe 77 new ascomycetous yeast species with 195 isolates obtained over the past two decades during the continuous yeast diversity surveys in China, based on the phylogenetic analyses of the sequences of D1/D2 domains of the large subunit (LSU) and the internal transcribed spacer region including the 5.8S rDNA (ITS) of the nuclear ribosomal DNA (rDNA). The average nucleotide identity (ANI) analysis was used to delimitate closely related species with low sequence heterogeneity in the ITS and D1/D2 regions. Seventy-five of these new species belong to 35 genera in the Saccharaomycotina, while the other two are distributed in Taphrina of the Taphrinomycotina. In addition, we propose two new genera, namely Gaboromyces gen. nov. and Yurkovozyma gen. nov.

microbiology↗

bioRxiv2025

Inferring macroscopic intrinsic neural timescales using optimal control theory

The temporal evolution of brain activity relies on complex interactions within and between brain regions that are mediated by neurobiology and connectivity. To understand these interactions, many large-scale efforts have measured structural connectivity, neural activity, gene expression, and cognition across multiple modalities and species. However, data-driven discovery of large-scale activity models remains difficult owing to the lack of flexible quantitative frameworks for estimating the interplay between brain structure and function while preserving biophysical realism. Here, we provide such a framework by integrating network control theory (NCT) with automatic differentiation to estimate model parameters with greater biophysical realism from data. Specifically, we estimate the structural form of regional self-inhibition--a quantity that is experimentally difficult to measure--from MRI data. Next, we demonstrate that the resulting model-based self-inhibition parameters correlate significantly with regions intrinsic neural timescales (INTs), neurobiological measures of gene expression and cell-type densities, as well as behavioral measures of cognition. We demonstrate consistent results across multiple datasets and species. Finally, we demonstrate that our self-inhibition parameters enable the efficient control of brain dynamics from fewer brain regions. Taken together, our results provide a simple and flexible quantitative framework that more accurately captures the interplay between brain structure, function, and dynamics with greater biophysical realism.

neuroscience↗

bioRxiv2025

The molecular and cellular underpinnings of human brain lateralization

Hemispheric specialization is a fundamental characteristic of human brain organization, where most individuals exhibit left-hemisphere dominance for language and right-hemisphere dominance for visuospatial attention. While some lateralized functions are evident in other species, the human brain displays a strong, species-wide bias. Despite the evolutionary and functional significance of these asymmetries, their molecular and cellular foundations remain poorly understood. Here, we identify key neurochemical and cellular asymmetries that underpin cortical lateralization. Specifically, we demonstrate lateralized gradients in neurotransmitter receptor densities, particularly along the multimodal monoaminergic-cholinergic axis, as well as asymmetries in mitochondrial distribution and the spatial prevalence of microglia and glutamatergic excitatory neurons. Using a multimodal approach that integrates in vivo functional MRI, PET imaging, and post-mortem transcriptomic and cellular data, we delineate two distinct cortical clusters: a left-lateralized network centered on language processing and a right-lateralized network supporting visuospatial attention. These results highlight a biologically embedded substrate for lateralized cognition that may inform both evolutionary theory and our mechanistic understanding of neuropsychiatric illnesses characterized by disrupted lateralization.

neuroscience↗

bioRxiv2024

Individual brain activity patterns during task are predicted by distinct resting-state networks that may reflect local neurobiological features

Understanding how individual cortical features shape functional brain organization offers a promising framework for examining the principles of cognitive specialization in the human brain. This study explores the relationship between various cortical characteristics--i.e resting-state functional connectivity, structural connectivity, microstructure, morphology, and geometry--and the layout of task-specific functional activations. We employ linear models to predict the functional layout of the cortex at the individual level from each of these feature modalities. Our findings demonstrate that resting-state component loadings predict individual task activations, consistently across hemispheres and independent datasets. Whereas the first few components provide a common space for functional activations across tasks, predictive higher-order component loadings demonstrated task-specificity. Cortical microstructure/morphology was notably predictive of activation strength in the occipital cortex, highlighting its relevance for cortical functional specialization. By relating resting state components to a set of reference maps of cortical organization, we identify associations that suggest possible neurobiological underpinnings of specific cognitive functions. The remaining feature modalities were only predictive of group-level functional activations. These results advance our understanding of how distinct cortical features may contribute to functional specialization, guiding future inquiry into the organization of cognitive functions on the cortex.

neuroscience↗

bioRxiv2024

A neutral process of genome reduction in marine bacterioplankton

Marine bacterioplankton communities are dominated by cells equipped with small genomes. Streamlining selection has been accepted as the main force driving their genome reduction. Here, we report that a neutral evolutionary mechanism governs genome reduction in the Roseobacter group that represents 5-20% of the bacterioplankton cells in coastal waters. Using representative strains that fall into three genome size groups (2-3, 3-4, and 4-5 Mbp), we measured their genomic mutation rates () through long-term mutation accumulation experiments followed by genome sequencing the resulting 437 mutant lines. We further calculated their effective population sizes (Ne) based on and the neutral genetic diversity of the studied species, the latter estimated based on multiple genome sequences of natural isolates collected from global oceans with their population structure considered. A surprising finding is that Ne scales positively with genome size, which is the opposite of the expectation from the streamlining selection theory. As the strength of random genetic drift is the inverse of Ne, this result instead suggests drift as the primary driver of genome reduction. Additionally, we report a negative scaling between and genome size, which is the first experimental evidence for the long-lasting hypothesis that mutation rate increases play a part in marine bacterial genome reduction. As scales inversely with Ne, genetic drift appears to be the ultimate cause of genome reduction in these Roseobacters. Our finding discounts, but is insufficient to reject, the streamlining theory because streamlining process is expected to be more effective in oligotrophic open ocean waters.

microbiology↗

bioRxiv2023

The Cellular Underpinnings of the Human Cortical Connectome

The functional properties of the human brain arise, in part, from the vast assortment of cell types that pattern the cortex. The cortical sheet can be broadly divided into distinct networks, which are further embedded into processing streams, or gradients, that extend from unimodal systems through higher-order association territories. Here, using transcriptional data from the Allen Human Brain Atlas, we demonstrate that imputed cell type distributions are spatially coupled to the functional organization of cortex, as estimated through fMRI. Cortical cellular profiles follow the macro-scale organization of the functional gradients as well as the associated large-scale networks. Distinct cellular fingerprints were evident across networks, and a classifier trained on post-mortem cell-type distributions was able to predict the functional network allegiance of cortical tissue samples. These data indicate that the in vivo organization of the cortical sheet is reflected in the spatial variability of its cellular composition.

neuroscience↗

bioRxiv2021

Observation of reversal in twist-stretch coupling of RNA suggests a unified mechanism for the opposite couplings of DNA and RNA

The functions of DNA and RNA rely on their deformations. When stretched, both DNA and RNA duplexes change their twist angles through twist-stretch coupling. The coupling is negative for DNA but positive for RNA, which is not yet completely understood. Here, our magnetic tweezers experiments show that the coupling of RNA reverses from positive to negative by multivalent cations. Combining with the previously reported tension-induced negative-to-positive coupling-reversal of DNA, we propose a unified mechanism of the couplings of both RNA and DNA based on molecular dynamics simulations. Two deformation pathways are competing when stretched: shrinking the radius causes positive couplings but widening the major groove causes negative couplings. For RNA whose major groove is clamped by multivalent cations and canonical DNA, their radii shrink when stretched, thus exhibiting positive couplings. For elongated DNA whose radius already shrinks to the minimum and canonical RNA, their major grooves are widened when stretched, thus exhibiting negative coupling.

biophysics↗

bioRxiv2021

Presynaptic HCN channels constrain GABAergic synaptic transmission in pyramidal cells of the medial prefrontal cortex

Hyperpolarization-activated cyclic nucleotide-gated (HCN) channels are widely expressed in neurons in the central nervous system. It has been documented that HCN channels regulate the intrinsic excitability of pyramidal cells in the medial prefrontal cortex (mPFC) of rats. Here, we report that HCN channels limited GABAergic transmission onto pyramidal cells in the mPFC. Pharmacological block of HCN channels resulted in a significant increase in the frequency of both spontaneous and miniature inhibitory postsynaptic currents (IPSCs) in mPFC pyramidal cells. Such facilitation effect on mIPSCs required presynaptic Ca2+ influx and reversed by high-dose cAMP. Such facilitation did not exist in the presence of the T-type Ca2+ channel selective blockers. Immunofluorescence staining revealed that HCN channels expressed in presynaptic GABAergic terminals, as well as in both soma and neurite of parvalbumin-expressing (PV-expressing) basket cells in the mPFC. The present results indicate that HCN channels in GABAergic interneurons, most likely PV-expressing basket cells, constrain inhibitory control over layer 5-6 pyramidal cells through restricting presynaptic Ca2+ entry.

neuroscience↗

bioRxiv2019

The Clinical Significance and Biological Function of DPEP1 in B-cell Acute Lymphoblastic Leukemia

Dehydropeptidase-1 (DPEP1) is a zinc-dependent metalloproteinase abnormally expressed in many cancers. However, its potential role in adults with B-cell acute lymphoblastic leukaemia (ALL) is unknown.\n\nWe found that in adults with common-B-cell ALL high DPEP1 transcript levels at diagnosis was independently-associated with an increased CIR and worse RFS compared with subjects with low transcript levels. We show an increased proliferation and pro-survival role of DPEP1 in B-cell ALL cells via regulation of phosphCREB and p53 which may be the biological basis of the clinical correlation we report. Our data implicate DPEP1 expression in the biology of common B-cell ALL in adults. We report clinical correlates and provide a potential biological basis for these correlations. If confirmed, analyzing DPEP1 transcript levels at diagnosis could help predict therapy-outcomes. Moreover, regulation of DPEP1 expression could be a therapy target in B-cell ALL.

molecular biology↗