Biology subjects

Ji, D.

Publications and source records attributed to Ji, D..

15 recordsLinked to original sources

bioRxiv2026

A unified population-genetic framework for inferring double reduction and higher-order two-locus linkage disequilibrium in autopolyploids

Polyploid genomes exhibit complex allelic interactions driven by polysomic inheritance that cannot be adequately captured by conventional pairwise linkage disequilibrium (LD) models, leaving higher-order dependency structures largely unresolved. Here, we develop a unified population-genetic framework that jointly infers double reduction and higher-order allelic associations in autopolyploids. By modeling dosage-dependent gametic structure, our approach reformulates LD as a hierarchical system, enabling decomposition of allelic dependencies beyond pairwise interactions. Through simulations, we show that conventional estimators systematically confound higher-order allelic structure with pairwise LD, leading to biased inference and loss of identifiability under dosage uncertainty. In contrast, our joint likelihood framework achieves asymptotically unbiased estimation and reveals that effective double reduction emerges as a composite parameter linking meiotic configuration to population-level allelic reshaping. Applying this model to Arabidopsis arenosa and cultivated potato, we uncover fundamental contrasts in genomic architecture. In natural populations, higher-order LD self-organizes into structured, long-range dependency networks, whereas predominantly clonal populations exhibit collapse of higher-order dependency structure. We further identify a spatial antagonism between double reduction and higher-order LD, demonstrating that elevated double reduction compresses the physical scale of allelic interactions. Our results demonstrate that autopolyploid genomes are organized as higher-order dependency systems rather than collections of pairwise associations, establishing higher-order allelic structure as a fundamental extension of classical LD theory.

genetics↗

bioRxiv2026

A Surfactant Cocktail Overcomes Air-Water Interface Artifacts in Single-Particle CryoEM

Single-particle cryogenic electron microscopy (cryoEM) is a widely used technique for structure determination of biomacromolecules to near-atomic resolution. Random distributions of these molecules in vitrified ice are necessary to accumulate enough two-dimensional views to generate a complete three-dimensional (3-D) reconstruction. However, interactions between the sample and the air-water interface (AWI) that occur during vitrification often bias the views of the sample, a phenomenon termed preferred orientation, limiting our ability to obtain 3-D reconstructions. Surfactants are often used as sample additives to prevent AWI-induced deterioration, but no general strategy exists for surfactant choice, requiring laborious screening for each sample. To circumvent these issues, we developed SurfACT, a cocktail of diverse surfactants with distinct physicochemical properties that limits AWI-dependent sample denaturation and orientation bias, while mitigating individual surfactant-specific drawbacks. Here we demonstrate SurfACTs effectiveness with four proteins plagued by AWI-induced issues, including two species of hemagglutinin (HA), molybdenum-iron protein (MoFeP) from the nitrogenase enzyme, and aldolase. All four samples show drastically improved viewing distribution and map completeness when SurfACT is applied. Cryogenic electron tomography demonstrates that SurfACT redistributes particles from the AWI into the bulk ice, driving signal recovery and inhibiting denaturation. This versatile sample additive minimizes sample-specific screening and expands the capabilities and range of suitable samples for cryoEM.

biophysics↗

bioRxiv2025

ANTIDOTE: A Metadata-Driven Neural Network for Improving CryoEM 3-D Particle Sorting

Despite the maturation of cryogenic electron microscopy (cryoEM) methodologies, generating high-resolution three-dimensional (3-D) reconstructions from micrographs is a time-intensive process involving iterative rounds of subjective data curation and hyperparameter optimization. Current approaches to particle classification are often unable to remove all low-quality particles from particle stacks, largely due to the low signal-to-noise ratio, the high dimensionality of particle images, and the multiple degrees of freedom associated with each particles unknown rotation, orientation, and class assignment. The retention of low-quality particles negatively affects the overall quality of the final EM density and continued efforts to eliminate their deleterious contributions are warranted. Here, we present ANTIDOTE (A Neural network Trained In Deleterious Object deTection and Elimination), a neural network framework that discriminates between constructive and deleterious particles using per-particle metadata generated during 3-D classification in RELION. Using benchmark and real-world cryoEM datasets, we demonstrate that ANTIDOTE paired with RELION 3-D classification achieves higher particle classification accuracy than conventional data processing approaches alone, yielding improvements in reconstruction quality, global and local resolution, and map interpretability while reducing time-consuming hyperparameter optimization. We additionally detail practical use-case scenarios for ANTIDOTE and demonstrate its versatility in increasing particle curation accuracy for high-quality cryoEM reconstruction.

biophysics↗

bioRxiv2025

iPSC-Derived Cerebral Organoids Reveal Mitochondrial, Inflammatory and Neuronal Vulnerabilities in Bipolar Disorder

Bipolar disorder (BD) is increasingly recognized as a disorder with both mitochondrial dysfunction and heightened inflammatory reactivity, yet their contribution to neuronal activity remains unclear. To address these gaps, this study utilizes iPSC-derived cerebral organoids (COs) from BD patients and healthy controls to model disease-specific metabolic and inflammatory dysfunction in a physiologically relevant system. BD COs exhibited mitochondrial impairment, dysregulated metabolic function, and increased nod-leucine rich repeat and pyrin domain containing protein 3 (NLRP3) inflammasome activation sensitivity. Treatment with MCC950, a selective NLRP3 inhibitor, effectively rescued mitochondrial function and reduced inflammatory activation in both BD and control COs. Additionally, a Bioactive Flavonoid Extract (BFE) was explored as a potential therapeutic, demonstrating partial rescue of inflammasome activation. These findings highlight a mitochondria-inflammasome axis in BD pathophysiology and establish a novel platform for studying BD-associated cellular mechanisms, ultimately bridging the gap between molecular dysfunction and therapeutic development.

neuroscience↗

bioRxiv2024

Theta oscillons in behaving rats

Recently discovered constituents of the brain waves--the oscillons--provide high-resolution representation of the extracellular field dynamics. Here we study the most robust, highest-amplitude oscillons that manifest in actively behaving rats and generally correspond to the traditional{theta} -waves. We show that the resemblances between{theta} -oscillons and the conventional{theta} -waves apply to the ballpark characteristics--mean frequencies, amplitudes, and bandwidths. In addition, both hippocampal and cortical oscillons exhibit a number of intricate, behavior-attuned, transient properties that suggest a new vantage point for understanding the{theta} -rhythms structure, origins and functions. We demonstrate that oscillons are frequency-modulated waves, with speed-controlled parameters, embedded into a noise background. We also use a basic model of neuronal synchronization to contextualize and to interpret the observed phenomena. In particular, we argue that the synchronicity level in physiological networks is fairly weak and modulated by the animals locomotion.

neuroscience↗

bioRxiv2024

Observational activation of anterior cingulate cortical neurons coordinates hippocampal replay in social learning

Social learning enables a subject to make decisions by observing the actions of another. How neural circuits acquire relevant information during observation to guide subsequent behavior is unknown. Utilizing an observational spatial working memory task, we show that neurons in the rat anterior cingulate cortex (ACC) associated with spatial trajectories during self-running in a maze are reactivated when observing another rat running the same maze. The observation-induced ACC activities are reduced in error trials and are correlated with activities of hippocampal place cells representing the same trajectories. The ACC activities during observation also predict subsequent hippocampal place cell activities during sharp-wave ripples and spatial contents of hippocampal replay prior to self-running. The results support that ACC neurons involved in decisions during self-running are reactivated during observation and interact with hippocampal replay to guide subsequent spatial navigation.

neuroscience↗

bioRxiv2024

Altered patterning of neural activity in a tauopathy mouse model

Alzheimers disease (AD) is a complex neurodegenerative condition that manifests at multiple levels and involves a spectrum of abnormalities ranging from the cellular to cognitive. Here, we investigate the impact of AD-related tau-pathology on hippocampal circuits in mice engaged in spatial navigation, and study changes of neuronal firing and dynamics of extracellular fields. While most studies are based on analyzing instantaneous or time-averaged characteristics of neuronal activity, we focus on intermediate timescales--spike trains and waveforms of oscillatory potentials, which we consider as single entities. We find that, in healthy mice, spike arrangements and wave patterns (series of crests or troughs) are coupled to the animals location, speed, and acceleration. In contrast, in tau-mice, neural activity is structurally disarrayed: brainwave cadence is detached from locomotion, spatial selectivity is lost, the spike flow is scrambled. Importantly, these alterations start early and accumulate with age, which exposes progressive disinvolvement the hippocampus circuit in spatial navigation. These features highlight qualitatively different neurodynamics than the ones provided by conventional analyses, and are more salient, thus revealing a new level of the hippocampal circuit disruptions. SignificanceWe expose differences in WT and tau brains, emerging at the circuit level, using a novel, morphological perspective on neural activity. This approach allows identifying qualitative changes in spiking patterns and in extracellular field oscillations, that are not discernible through traditional time-localized or time-averaged analyses. In particular, analyses of activity patterns facilitates detection of neurodegenerative deviations, conspicuously linking their effects to behavior and locomotion, thus opening a new venue for understanding how the architecture of neural activity shifts from normal to pathological.

neuroscience↗

bioRxiv2024

AUTO-TUNE: SELECTING THE DISTANCE THRESHOLD FOR INFERRING HIV TRANSMISSION CLUSTERS

Molecular surveillance of viral pathogens and inference of transmission networks from genomic data play an increasingly important role in public health efforts, especially for HIV-1. For many methods, the genetic distance threshold used to connect sequences in the transmission network is a key parameter informing the properties of inferred networks. Using a distance threshold that is too high can result in a network with many spurious links, making it difficult to interpret. Conversely, a distance threshold that is too low can result in a network with too few links, which may not capture key insights into clusters of public health concern. Published research using the HIV-TRACE software package frequently uses the default threshold of 0.015 substitutions/site for HIV pol gene sequences, but in many cases, investigators heuristically select other threshold parameters to better capture the underlying dynamics of the epidemic they are studying. Here, we present a general heuristic scoring approach for tuning a distance threshold adaptively, which seeks to prevent the formation of giant clusters. We prioritize the ratio of the sizes of the largest and the second largest cluster, maximizing the number of clusters present in the network. We apply our scoring heuristic to outbreaks with different characteristics, such as regional or temporal variability, and demonstrate the utility of using the scoring mechanisms suggested distance threshold to identify clusters exhibiting risk factors that would have otherwise been more difficult to identify. For example, while we found that a 0.015 substitutions/site distance threshold is typical for US-like epidemics, recent outbreaks like the CRF07_BC subtype among men who have sex with men (MSM) in China have been found to have a lower optimal threshold of 0.005 to better capture the transition from injected drug use (IDU) to MSM as the primary risk factor. Alternatively, in communities surrounding Lake Victoria in Uganda, where there has been sustained hetero-sexual transmission for many years, we found that a larger distance threshold is necessary to capture a more risk factor-diverse population with sparse sampling over a longer period of time. Such identification may allow for more informed intervention action by respective public health officials.

bioinformatics↗

bioRxiv2022

Synaptic degeneration in neuronal circuits hinders memory recall, memory rescue, and learning

Neurodegeneration is a characteristic of Alzheimers disease (AD), but its effect on neural activity dynamics underlying memory deficits is unclear. Here, we studied the effects of synaptic degeneration on neural activities associated with memory recall, memory rescue by slow-gamma stimulation, and learning a new memory, in an integrate-and-fire neuronal network. Our results showed that reducing connectivity decreases the neuronal synchronisation of memory neurons at slow-gamma frequencies and impairs memory recall performance. Although slow-gamma stimulation rescued memory recall and slow-gamma oscillations, the rescue with reduced connectivity caused a side effect of activating mixed memories. During the learning of a new memory, reducing connectivity caused an impairment in storing the new memory, but did not affect previously stored memories. Our results reveal potential computational mechanisms underlying the memory deficits caused by synaptic degeneration in AD.

neuroscience↗

bioRxiv2022

Assessment of urinary exosome NHE3 as a biomarker of acute kidney injury

The diagnosis of acute kidney injury (AKI) traditionally depends on the serum creatinine (SCr) and urine output, which lack sufficient sensitivity and specificity. Urinary exosome as a biomarker has unique advantages. To assessed whether urinary exosome Na+/H+ exchanger isoform 3 (NHE3) protein as a nonivasive diagnostic biomarker of AKI, we constructed 4 AKI rat models: cisplatin (7.5mg/kg) injection intraperitoneally (IP), furosemide (20mg/kg, IP) with low NaCl (0.03%) diet, low NaCl (0.03%) diet with candesartan (1mg/kg, IP) and bilaterally ischemia and reperfusion(I/R) injury for 40 minutes. Besides, we assessed 6 sepsis associated AKI patients and 6 healthy volunteers. Urinary exosomes were extracted by ultra-centrifugation and NHE3 protein abundance was tested by immunoblotting in all AKI rats and human subjects. The isolated cup-shape particles with an average diameter of 70nm and enrichment in CD63 were identified as exosomes. NHE3 abundance was 6 times higher in exosome than in original urine. In cisplatin induced AKI rats, urinary exosome NHE3 was increased at day 2, 1 day earlier than the increases of serum creatinine creatinine (SCr) and blood urea nitrogen (BUN). In additional rats, urinary exosome NHE3 decreased along with the decline of SCr after EPO pretreatment. In volume depletion AKI induced by furosemide injection with low NaCl diet, urinary exosome NHE3 expression was higher than control. In low NaCl diet with candesartan related AKI, urinary exosome NHE3 was elevated at day 5, 2 days earlier than SCr. In I/R injury AKI, urinary exosome NHE3 was also raised compared with control. In humans, the urinary exosome NHE3 level was also elevated in sepsis associated AKI patients in comparison with the healthy volunteers. Then urinary exosome NHE3 protein may be used as a noninvasive diagnostic biomarker of AKI. Impact StatementThe high non-recognition acute kidney injury (AKI) is due to lacking of alarming symptoms or specific early biomarkers. Urinary exosome as a biomarker has unique advantages. In our study, we detected urinary exosome NHE3 protein abundance in 4 different cause of AKI rat model. Urinary exosome NHE3 was increased in all 4 AKI, and even elevated earlier than SCr in some cases. Another novel point was we established a new AKI model of low NaCl diet with candesartan injection, which was common in patients with hypertension or proteinuria clinically. The detailed methods and mechanisms of this new AKI model were presented in another article being submitted. Third, we are not limited to animals, but also selected sepsis associated AKI patients to study. The conclusion that urinary exosome NHE3 may be used as a diagnosis biomarker of AKI has important clinical application value.

molecular biology↗

bioRxiv2022

Pattern dynamics and stochasticity of the brain rhythms

Our current understanding of brain rhythms is based on quantifying their instantaneous or time-averaged characteristics. What remains unexplored, is the actual structure of the waves--their shapes and patterns over finite timescales. To address this, we used two independent approaches to link wave forms to their physiological functions: the first is based on quantifying their consistency with the underlying mean behavior, and the second assesses "orderliness" of the waves features. The corresponding measures capture the waves characteristic and abnormal behaviors, such as atypical periodicity or excessive clustering, and demonstrate coupling between the patterns dynamics and the animals location, speed and acceleration. Specifically, we studied patterns of{theta} and{gamma} waves, and Sharp Wave Ripples, and observed speed-modulated changes of the waves cadence, an antiphase relationship between orderliness and acceleration, as well as spatial selectiveness of patterns. Further-more, we found an interdependence between orderliness and regularity: larger deviations from steady oscillatory behavior tend to accompany disarrayed temporal cluttering of peaks and troughs. Taken together, our results offer a complementary--mesoscale--perspective on brain wave structure, dynamics, and functionality.

neuroscience↗

bioRxiv2020

Germline Selection by Meiosis Defends the Transmission of defective Mitochondria with mtDNA variants

Germline selection of mtDNA is vital in maternal inheritance of mtDNA, as it can eliminate severe mtDNA mutations. However, current evidence concerning germline selection at meiosis level comes from incomplete mtDNA sequencing in human first polar body (PB1), which lacks persuasion. Here, we found various variants, including pathogenic mutation sites, present on whole genome of mtDNA in human PB1 compared with its oocyte. And that PB1 mitochondria with mtDNA variants were defective. Afterwards, to further explore how mitochondria enter PB, the defective mitochondria transfer in mouse germline, including cumulus-oocyte-complexes at germinal vesicle and matured oocytes stage. It confirmed that in the first and second meiosis, active purification selected defective mitochondria into PB1 and PB2. Thus, twice meiosis is the last defense system for purifying selection of mtDNA mutations during oogenesis, which also demonstrated that PB1 and PB2 would be final destination of deleterious mtDNA mutations in germline selection.

cell biology↗

bioRxiv2020

Transcriptomic Organization of Human Posttraumatic Stress Disorder

Posttraumatic stress disorder (PTSD) affects approximately 8% of the general population, with higher rates in extreme stress groups, including combat veterans or victims of sexual assault. Despite extensive study of the neurobiological correlates of PTSD, little is known about its molecular substrates. Here differential gene expression and network analyses of 4 prefrontal cortex (PFC) postmortem subregions of male and female PTSD subjects demonstrates extensive remodeling of the transcriptomic landscape. The data revealed a highly connected down-regulated set of interneuron transcripts in the most significant gene network associated with PTSD and integration of this data with genotype data from the largest PTSD GWAS identified the interneuron synaptic gene ELFN1 as conferring significant genetic liability for PTSD. We also identified marked sexual dimorphism in the transcriptomic signatures that could contribute to the higher rates of PTSD in women. Comparison with a matched major depressive disorder (MDD) cohort revealed significant divergence between the molecular profiles of subjects with PTSD and depression despite their high comorbidity. Our analysis provides convergent systems-level evidence of genomic networks within the PFC that contribute to the pathophysiology of PTSD in humans.

genomics↗

bioRxiv2019

Abnormal nitration and S-sulfhydration of Sp1-CSE-H2S pathway contribute to the progress of HHcy

Sp1 (Specificity protein 1)-CSE (cystathionine-{gamma}-lyase)-H2S (hydrogen sulfide) pathway plays an important role in homocysteine-metabolism, whose disorder can result in hyperhomocysteinemia. The deficiency of plasma H2S in patients and animal models with hyperhomocysteinemia has been reported but it is unclear whether this deficiency plays a role in the progress of hyperhomocysteinemia. Furthermore, it remains unknown whether the post-translational modification of Sp1 or CSE mediated by hyperhomocysteinemia itself can in turn affect the development of hyperhomocysteinemia. By both in vivo and in vitro studies, we conducted immunoprecipitation and maleimide assays to detect the post-translational modification of Sp1-CSE-H2S pathway and revealed four major findings: (1) the accumulation of homocysteine augmented the nitration of CSE, thus blunted its bio-activity and caused H2S deficiency. (2) H2S deficiency lowered the S-sulfhydration of Sp1 and inhibited its transcriptional activity, resulted in lower expression of CSE. CSE deficiency decreased the H2S level further, which in turn lowered the S-sulfhydration level of CSE. (3) CSE was S-sulfhydrated at Cys84, Cys109, Cys172, Cys229, Cys252, Cys307 and Cys310 under physiological conditions, mutation of Cys84, Cys109, Cys229, Cys252 and Cys307 decreased its S-sulfhydration level and bio-activity. (4) H2S deficiency could trap hyperhomocysteinemia into a progressive vicious circle and trigger a rapid increase of homocysteine, while blocking nitration or restoring S-sulfhydration could break this circle. In conclusion, this study reveals a novel mechanism involved in the disorder of homocysteine-metabolism, which may provide a candidate therapeutic strategy for hyperhomocysteinemia.

pathology↗

bioRxiv2018

Bayesian Trees for Automated Cytometry Data Analysis

Cytometry is an important single cell analysis technology in furthering our understanding of cellular biological processes and in supporting clinical diagnoses across a variety hematological and immunological conditions. Current data analysis workflows for cytometry data rely on a manual process called gating to classify cells into canonical types. This dependence on human annotation significantly limits the rate, reproducibility, and scope of cytometrys use in both biological research and clinical practice. We develop a novel Bayesian approach for automated gating that classifies cells into different types by combining cell-level marker measurements with an informative prior. The Bayesian approach allows for the incorporation of biologically-meaningful prior information that captures the domain expertise of human experts. The inference algorithm results in a hierarchically-structured classification of individual cells in a manner that mimics the tree-structured recursive process of manual gating, making the results readily interpretable. The approach can be extended in a natural fashion to handle data from multiple different samples by the incorporation of random effects in the Bayesian model. The proposed approach is evaluated using mass cytometry data, on the problems of unsupervised cell classification and supervised clinical diagnosis, illustrating the benefits of both incorporating prior knowledge and sharing information across multiple samples.

bioinformatics↗