Biology subjects

Dong, Z.

Publications and source records attributed to Dong, Z..

At least 73 records · Page 4Linked to original sources

bioRxiv2024

Single-shot Echo Planar Time-resolved Imaging for multi-echo functional MRI and distortion-free diffusion imaging

PurposeTo develop EPTI, a multi-shot distortion-free multi-echo imaging technique, into a single-shot acquisition to achieve improved robustness to motion and physiological noise, increased temporal resolution, and high SNR efficiency for dynamic imaging applications. MethodsA new spatiotemporal encoding was developed to achieve single-shot EPTI by enhancing spatiotemporal correlation in k-t space. The proposed single-shot encoding improves reconstruction conditioning and sampling efficiency, with additional optimization under various accelerations to achieve optimized performance. To achieve high SNR efficiency, continuous readout with minimized deadtime was employed that begins immediately after excitation and extends for an SNR-optimized length. Moreover, k-t partial Fourier and simultaneous multi-slice acquisition were integrated to further accelerate the acquisition and achieve high spatial and temporal resolution. ResultsWe demonstrated that ss-EPTI achieves higher tSNR efficiency than multi-shot EPTI, and provides distortion-free imaging with densely-sampled multi-echo images at resolutions [~]1.25-3 mm at 3T and 7T-- with high SNR efficiency and with comparable temporal resolutions to ss-EPI. The ability of ss-EPTI to eliminate dynamic distortions common in EPI also further improves temporal stability. For fMRI, ss-EPTI also provides early-TE images (e.g., 2.9ms) to recover signal-intensity and functional-sensitivity dropout in challenging regions. The multi-echo images provide TE-dependent information about functional fluctuations, successfully distinguishing noise-components from BOLD signals and further improving tSNR. For diffusion MRI, ss-EPTI provides high-quality distortion-free diffusion images and multi-echo diffusion metrics. Conclusionss-EPTI provides distortion-free imaging with high image quality, rich multi-echo information, and enhanced efficiency within comparable temporal resolution to ss-EPI, offering a robust and efficient acquisition for dynamic imaging.

bioengineering↗

bioRxiv2024

Coordinated molecular and ecological adaptations underlie a highly successful parasitoid

The success of an organism depends on the molecular and ecological adaptations that promote its beneficial fitness. Parasitoids are valuable biocontrol agents for successfully managing agricultural pests, and they have evolved diversified strategies to adapt to both the physiological condition of hosts and the competition of other parasitoids. Here, we deconstructed the parasitic strategies in a highly successful parasitoid, Trichopria drosophilae, which parasitizes a broad range of Drosophila hosts, including the globally invasive species D. suzukii. We found that T. drosophilae had developed specialized venom proteins that arrest host development to obtain more nutrients via secreting tissue inhibitors of metalloproteinases (TIMPs), as well as a unique type of cell-- teratocytes--that digest host tissues for feeding by releasing trypsin proteins. In addition to the molecular adaptations that optimize nutritional uptake, this pupal parasitoid has evolved ecologically adaptive strategies including the conditional tolerance of intraspecific competition to enhance parasitic success in older hosts and the obligate avoidance of interspecific competition with larval parasitoids. Our study not only demystifies how parasitoids weaponize themselves to colonize formidable hosts but also provided empirical evidence of the intricate coordination between the molecular and ecological adaptations that drive evolutionary success.

ecology↗

bioRxiv2023

Unbiased Complete Estimation of Chloroplast Number in Plant Cells Using Deep Learning Methods

Chloroplasts are essential organelles in plants that are involved in plant development and photosynthesis. Accurate quantification of chloroplast numbers is important for understanding the status and type of plant cells, as well as assessing photosynthetic potential and efficiency. Traditional methods of counting chloroplasts using microscopy are time-consuming and face challenges such as the possibility of missing out-of-focus samples or double counting when adjusting the focal position. Here, we developed an innovative approach called Detecting- and-Counting-chloroplasts (D&Cchl) for automated detection and counting of chloroplasts. This approach utilizes a deep-learning-based object detection algorithm called You-Only-Look-Once (YOLO), along with the Intersection Over Union (IOU) strategy. The application of D&Cchl has shown excellent performance in accurately identifying and quantifying chloroplasts. This holds true when applied to both a single image and a three-dimensional (3D) structure composed of a series of images. Furthermore, by integrating Cellpose, a cell-segmentation tool, we were able to successfully perform single-cell 3D chloroplast counting. Compared to manual counting methods, this approach improved the accuracy of detection and counting to over 95%. Together, our work not only provides an efficient and reliable tool for accurately analyzing the status of chloroplasts, enhancing our understanding of plant photosynthetic cells and growth characteristics, but also makes a significant contribution to the convergence of botany and deep learning. One-sentence summaryThis deep learning-based approach enables the accurate complete detection and counting of chloroplasts in 3D single cells using microscopic image stacks, and showcases a successful example of utilizing deep learning methods to analyze subcellular spatial information in plant cells. The authors responsible for distribution of materials integral to the findings presented in this article in accordance with the policy described in the Instructions for Authors (https://academic.oup.com/plcell/) is: Zhao Dong (dongzhao@hebeu.edu.cn), Shaokai Yang, (shaokai1@ualberta.ca), Ningjing Liu (liuningjing1@yeah.net), and Qiong Zhao (qzhao@bio.ecnu.edu.cn).

cell biology↗

bioRxiv2023

Functional imaging of nine distinct neuronal populations under a miniscope in freely behaving animals

Head-mounted miniscopes have enabled functional fluorescence imaging in freely moving animals. However, current technology is limited to recording at most two spectrally distinct fluorophores, severely restricting the number of identifiable cell types. Here we introduce multiplexed neuronal imaging (Neuroplex), a pipeline combining miniscope Ca2+ recordings with in vivo multiplexed confocal spectral imaging to distinguish nine projection-defined neuronal subtypes through the same GRIN lens. By co-registering defined neurons with fluorophore-specific spectral fingerprints via linear unmixing, we link projection-defined identities to behaviorally relevant neuronal activity. This approach overcomes spectral constraints of miniscopes, enabling circuit-level dissection of behavior in single animals.

neuroscience↗

bioRxiv2023

Filter-aided expansion proteomics

Integration of hydrogel-based tissue expansion and mass spectrometry-based proteomics enables high spatial resolution analysis of global protein expression in tissues. Here, we introduce a filter-aided tissue expansion proteomics (FAXP) method with optimized hydrogel preparation and treatment steps for spatial proteomics analysis of formalin-fixed paraffin-embedded (FFPE) specimens. Compared with our original ProteomEx method, FAXP, partially automated with robotics, exhibited 14.5-fold higher volumetric resolution, increased peptide yield leading to 250% more protein identifications, and 50% time consumption for sample preparation. We demonstrated its application in clinical colorectal tissue samples. We further integrated it with laser capture microdissection for proteomic analysis of subcellular organelles.

biochemistry↗

bioRxiv2023

LDER-GE estimates phenotypic variance component of gene-environment interactions in human complex traits accurately with GE interaction summary statistics and full LD information

Gene-environment (GE) interactions are essential in understanding human complex traits. Identifying these interactions is necessary for deciphering the biological basis of such traits. In this study, we introduce a statistical method Linkage-Disequilibrium Eigenvalue Regression for Gene-Environment interactions (LDER-GE). LDER-GE improves the accuracy of estimating the phenotypic variance component explained by genome-wide GE interactions using large-scale biobank association summary statistics. LDER-GE leverages the complete Linkage Disequilibrium (LD) matrix, as opposed to only the diagonal squared LD matrix utilized by LDSC (Linkage Disequilibrium Score)-based methods. Our extensive simulation studies demonstrate that LDER-GE performs better than LDSC-based approaches by enhancing statistical efficiency by approximately 23%. This improvement is equivalent to a sample size increase of around 51%. Additionally, LDER-GE effectively controls type-I error rate and produces unbiased results. We conducted an analysis using UK Biobank data, comprising 307,259 unrelated European-Ancestry subjects and 966,766 variants, across 151 environmental covariate-phenotype (E-Y) pairs. LDER-GE identified 35 significant E-Y pairs while LDSC-based method only identified 25 significant E-Y pairs with 23 overlapped with LDER-GE. Furthermore, we employed LDER-GE to estimate the aggregated variance component attributed to multiple GE interactions, leading to an increase in the explained phenotypic variance with GE interactions compared to considering main genetic effects only. Our results suggest the importance of impacts of GE interactions on human complex traits.

genetics↗

bioRxiv2023

Omics-assisted systematic exploration of the intricate regulatory network of guvermectin biosynthesis centered by the cluster-situated regulator GvmR in Streptomyces

Guvermectin, produced by Streptomyces bacteria, is a purine nucleoside natural product recently registered as a new biopesticide to boost rice yield. Despite its importance, the regulatory network governing guvermectin biosynthesis remains largely unknown, severely impeding industrial-scale production and widespread application in rice production. Here, we investigated the diverse regulatory mechanisms employed by the cluster-situated regulatory gene, gvmR, in controlling guvermectin production from the perspective of widespread disturbance of gene expression at genome scale. GvmR activates the expression of guvermectin cluster by binding to the gvmR, gvmA and O1 promoters. Additionally, GvmR binds to the promoter of scnR1, a previously unidentified and highly conserved regulator in Streptomyces. scnR1 overexpression significantly suppressed guvermectin production by regulating the guvermectin cluster through binding to the same promoters as GvmR. Transcriptomic analysis revealed that GvmR extensively influences the expression of numerous genes located outside the guvermectin cluster, including the precursor supply (purine biosynthesis) and energy synthesis (oxidative phosphorylation) pathway genes, as well as 252 transcriptional regulatory genes. By genetic screening from 48 of these 252 regulatory genes, we identified additional five highly conserved genes that impact guvermectin production, suggesting a functional interplay between GvmR and highly conserved regulators in coordinating guvermectin production. These findings enrich our knowledge of the regulatory network governing guvermectin biosynthesis and offer a broadly applicable approach for investigating the molecular regulation of natural product biosynthesis and their high-titer production.

microbiology↗

bioRxiv2023

Potassium stimulates fruit sugar accumulation by increasing carbon flow in Citrus

Soluble sugar is a key factor of flavor quality in citrus. Potassium (K) is known as a quality element, which plays key roles in improving sugar accumulation and fruit quality, but the mechanisms are largely unknown. This study aims to elucidate how K improves sugar accumulation by regulating carbon flow between source and sink in Newhall navel orange (Citrus sinensis). The results demonstrated that appropriate K concentration improved fruit quality and sugar accumulations in citrus, and 1.5% of K concentration in pulp was the optimal concentration for fruit quality. K increased strength of sink and source, as supported by the increased fruit growth rate, gene expressions related to sugar metabolism and sugar transport in fruit, and photosynthesis, gene expressions of sugar metabolism in leaf, respectively, which contributed to increasing sugars accumulation. Further study indicated that K improved carbon flow from source to sink by boosting symplastic and apoplastic loading of phloem, as supported by the increased CF signal intensities, plasmodesmata densities, and the expressions of CsSUT1 and CsSUT2 in leaf at early and mid stages of fruit development, finally increasing sugar accumulation in fruit. Conclusively, K stimulates fruit sugar accumulation by increasing carbon flow in Newhall navel orange. HighlightK application stimulated carbon flow between source and sink through symplastic and apoplastic loading, which were supported by the structural characteristics of phloem and the expression of CsSUTs and CsSWEETs, ultimately promoting sugar accumulation in Citrus sinensis.

plant biology↗

bioRxiv2023

BioMANIA: Simplifying bioinformatics data analysis through conversation

The rapid advancements in high-throughput sequencing technologies have produced a wealth of omics data, facilitating significant biological insights but presenting immense computational challenges. Traditional bioinformatics tools require substantial programming expertise, limiting accessibility for experimental researchers. Despite efforts to develop user-friendly platforms, the complexity of these tools continues to hinder efficient biological data analysis. In this paper, we introduce BioMANIA- an AI-driven, natural language-oriented bioinformatics pipeline that addresses these challenges by enabling the automatic and codeless execution of biological analyses. BioMANIA leverages large language models (LLMs) to interpret user instructions and execute sophisticated bioinformatics work-flows, integrating API knowledge from existing Python tools. By streamlining the analysis process, BioMANIA simplifies complex omics data exploration and accelerates bioinformatics research. Compared to relying on general-purpose LLMs to conduct analysis from scratch, BioMANIA, informed by domain-specific biological tools, helps mitigate hallucinations and significantly reduces the likelihood of confusion and errors. Through comprehensive benchmarking and application to diverse biological data, ranging from single-cell omics to electronic health records, we demonstrate BioMANIAs ability to lower technical barriers, enabling more accurate and comprehensive biological discoveries.

bioinformatics↗

bioRxiv2023

Fyn-mediated phosphorylation of Menin disrupts telomere maintenance in stem cells

Telomeres protect chromosome ends and determine the replication potential of dividing cells. The canonical telomere sequence TTAGGG is synthesized by telomerase holoenzyme, which maintains telomere length in proliferative stem cells. Although the core components of telomerase are well-defined, mechanisms of telomerase regulation are still under investigation. We report a novel role for the Src family kinase Fyn, which disrupts telomere maintenance in stem cells by phosphorylating the scaffold protein Menin. We found that Fyn knockdown prevented telomere erosion in human and mouse stem cells, validating the results with four telomere measurement techniques. We show that Fyn phosphorylates Menin at tyrosine 603 (Y603), which increases Menins SUMO1 modification, C-terminal stability, and importantly, its association with the telomerase RNA component (TR). Using mass spectrometry, immunoprecipitation, and immunofluorescence experiments we found that SUMO1-Menin decreases TRs association with telomerase subunit Dyskerin, suggesting that Fyns phosphorylation of Menin induces telomerase subunit mislocalization and may compromise telomerase function at telomeres. Importantly, we find that Fyn inhibition reduces accelerated telomere shortening in human iPSCs harboring mutations for dyskeratosis congenita.

molecular biology↗

bioRxiv2023

WBSCR16 Determines Metabolic Flexibility Via Regulating Mitochondrial 16S rRNA Maturation

Mitochondria play significant roles in energy homeostasis by dissipating excess calories. However, the key proteins in mitochondrial govern metabolically flexibility remain poorly understand. Herein, we generated adipose specific Wbscr16-/-mice and cells, both of which exhibited a preference for fat utilization and displayed dramatic mitochondrial changes. We demonstrated that WBSCR16 is essential for the specific cleavage of 16S rRNA-tRNALeu, leading to the production of maturated 16S rRNA, which in turn controls mitochondrial large ribosomal assembly. Importantly, WBSCR16 was identified as a 16S rRNA-binding protein that directly interacts with RNase P subunit MRPP3. Furthermore, evidence showed that WBSCR16 ablation promotes energy wasting via lipid cycling in BAT, leading to excess energy expenditure and resistance to obesity. Conversely, cells and mice with WBSCR16 overexpression preferred to glucose utilization. These findings suggest that WBSCR16 is the key mitochondrial switch protein between glucose and lipid metabolism, making it a promising target for the development of fat busting drug.

cell biology↗

bioRxiv2023

Three-dimensional Shear Wave Elastography Using Acoustic Radiation Force and A 2-D Row-Column Addressing (RCA) Array

Acoustic radiation force (ARF)-based shear wave elastography (SWE) is a clinically available ultrasound imaging mode that noninvasively and quantitatively measures tissue stiffness. Current implementations of ARF-SWE are largely limited to 2-D imaging, which does not provide robust estimation of heterogeneous tissue mechanical properties. Existing 3-D ARF-SWE solutions that are clinically available are based on wobbler probes, which cannot provide true 3-D shear wave motion detection. Although 3-D ARF-SWE based on 2-D matrix arrays have been previously demonstrated, they do not provide a practical solution because of the need for a high channel-count ultrasound system (e.g., 1024-channel) to provide adequate volume rates and the delicate circuitries (e.g., multiplexers) that are vulnerable to the long-duration "push" pulses. To address these issues, here we propose a new 3-D ARF-SWE method based on the 2-D row-column addressing (RCA) array which has a much lower element count (e.g., 256), provides an ultrafast imaging volume rate (e.g., 2000 Hz), and can withstand the push pulses. In this study, we combined the comb-push shear elastography (CUSE) technique with 2-D RCA for enhanced SWE imaging field-of-view. In vitro phantom studies demonstrated that the proposed method had robust 3-D SWE performance in both homogenous and inclusion phantoms. An in vivo study on a breast cancer patient showed that the proposed method could reconstruct 3-D elasticity maps of the breast lesion, which was validated using a commercial ultrasound scanner. These results demonstrate strong potential for the proposed method to provide a viable and practical solution for clinical 3-D ARF-SWE.

bioengineering↗

bioRxiv2023

Context-Aware Deep Learning Enables High-Efficacy Localization of High Concentration Microbubbles for Super-Resolution Ultrasound Localization Microscopy

Ultrasound localization microscopy (ULM) is an emerging super-resolution imaging technique for deep tissue microvascular imaging. However, conventional localization methods are constrained by low microbubble (MB) concentration, as accurate localization requires a strict separation of MB point spread functions (PSFs). Furthermore, deep learning-based localization techniques are often limited in their ability to generalize to in vivo ultrasound data due to challenges in accurately modeling highly variable MB PSF distributions and ultrasound imaging conditions. To address these limitations, we propose a novel deep learning-pipeline, LOcalization with Context Awareness (LOCA)-ULM, which employs simulation that incorporates MB context to generate synthetic data that closely resemble real MB signals, and a loss function that considers both MB count and localization loss. In in silico experiments, LOCA-ULM outperformed conventional localization with superior MB detection accuracy (94.0% vs. 74.9%) and a significantly lower MB missing rate (13.2% vs 74.8%). In vivo, LOCA-ULM achieved up to three-fold increase in MB localization efficiency and a x 9.5 faster vessel saturation rate than conventional ULM.

bioengineering↗

bioRxiv2023

One-carbon metabolism is required for epigenetic stability in the mouse placenta

One-carbon metabolism, including the folate cycle, has a crucial role in fetal development though its molecular function is complex and unclear. The hypomorphic Mtrrgt allele is known to disrupt one-carbon metabolism, and thus methyl group availability, leading to several developmental phenotypes (e.g., neural tube closure defects, fetal growth anomalies). Remarkably, previous studies showed that some of the phenotypes were transgenerationally inherited. Here, we explored the genome-wide epigenetic impact of one-carbon metabolism in placentas associated with fetal growth phenotypes and determined whether specific DNA methylation changes were inherited. Firstly, methylome analysis of Mtrrgt/gt homozygous placentas revealed genome-wide epigenetic instability. Several DMRs were identified including at the Cxcl1 gene promoter and at the En2 gene locus, which may have phenotypic implications. Importantly, we discovered hypomethylation and ectopic expression of a subset of ERV elements throughout the genome of Mtrrgt/gt placentas with broad implications for genomic stability. Next, we determined that sperm DMRs in males from the Mtrrgt model were reprogrammed in the placenta with little evidence of direct or transgenerational germline DMR inheritance. However, some sperm DMRs were associated with placental gene misexpression despite normalisation of DNA methylation, suggesting the inheritance of an alternative epigenetic mechanism. Integration of published histone ChIP-seq datasets with sperm methylome and placenta transcriptome data from the Mtrrgt model point towards H3K4me3 deposition at key loci suggesting that histone modifications might play a role in epigenetic inheritance in this context. This study sheds light on the mechanistic complexities of one-carbon metabolism in development and epigenetic inheritance.

developmental biology↗

bioRxiv2023

A double-hit of social and economic stress in mice precipitates changes in decision-making strategies

Economic stress can serve as a "second-hit" for those who already accumulated a history of adverse life experiences. How one recovers from a setback is a core feature of resilience but is seldom captured in animal studies. We challenged mice in a novel two-hit stress model by exposing animals to chronic social defeat stress (first-hit) and then testing how mice adapt to reward scarcity on a neuroeconomic task (second-hit). Mice were tested longitudinally across months on the Restaurant Row task during which mice foraged daily for their sole source of food while on a limited time budget. An abrupt transition into a reward-scarce environment on this task elicits an economic crisis, precipitating a massive drop in food intake and body weight to which mice must respond in order to survive. We found that mice with a history of social defeat mounted a robust behavioral response to this economic challenge. This recovery was achieved through a complex redistribution of how time was allocated among competing opportunities via multiple valuation algorithms. Interestingly, we found that mice with a history of social defeat displayed changes in the development of decision-making policies during the recovery process important for not only ensuring food security necessary for survival but also prioritizing subjective value. These findings indicate that an individuals capacity to "bounce back" from economic stress depends on ones prior history of stress and can affect multiple aspects of subjective well-being, highlighting a motivational balance that may be altered in stress-related disorders such as depression. In BriefDurand-de Cuttoli et al. found that after chronic social defeat stress, when mice were subsequently challenged on a neuroeconomic foraging task, an economic stressor can serve as a "second hit" and reveal changes in the development of complex decision-making strategies important for maintaining the balance between food security and subjective well-being.

animal behavior and cognition↗

bioRxiv2023

Aversive experience drives offline ensemble reactivation to link memories across days

Memories are encoded in neural ensembles during learning and stabilized by post-learning reactivation. Integrating recent experiences into existing memories ensures that memories contain the most recently available information, but how the brain accomplishes this critical process remains unknown. Here we show that in mice, a strong aversive experience drives the offline ensemble reactivation of not only the recent aversive memory but also a neutral memory formed two days prior, linking the fear from the recent aversive memory to the previous neutral memory. We find that fear specifically links retrospectively, but not prospectively, to neutral memories across days. Consistent with prior studies, we find reactivation of the recent aversive memory ensemble during the offline period following learning. However, a strong aversive experience also increases co-reactivation of the aversive and neutral memory ensembles during the offline period. Finally, the expression of fear in the neutral context is associated with reactivation of the shared ensemble between the aversive and neutral memories. Taken together, these results demonstrate that strong aversive experience can drive retrospective memory-linking through the offline co-reactivation of recent memory ensembles with memory ensembles formed days prior, providing a neural mechanism by which memories can be integrated across days.

neuroscience↗

bioRxiv2023

High Volume Rate 3-D Ultrasound Imaging Using Fast-Tilting and Redirecting Reflectors

3-D ultrasound imaging has many advantages over 2-D imaging such as more comprehensive tissue evaluation and less operator dependence. Although many 3-D ultrasound imaging techniques have been developed in the last several decades, a low-cost and accessible solution with high imaging volume rate and imaging quality remains elusive. Recently we proposed a new, high volume rate 3-D ultrasound imaging technique: Fast Acoustic Steering via Tilting Electromechanical Reflectors (FASTER), which uses a water-immersible and fast-tilting acoustic reflector to steer ultrafast plane waves in the elevational direction to achieve high volume rate 3-D ultrasound imaging with conventional 1-D array transducers. However, the initial implementation of FASTER imaging only involves a single fast-tilting acoustic reflector, which is inconvenient to use because the probe cannot be held in the regular upright position. Also, conventional FASTER imaging can only be performed inside a water tank because of the necessity of using water for acoustic conduction. To address these limitations of conventional FASTER, here we developed a novel ultrasound probe clip-on device that encloses a fast-tilting reflector, a redirecting reflector, and an acoustic wave conduction medium. The new FASTER 3-D imaging device can be easily attached to or removed from clinical ultrasound transducers, allowing rapid transformation from 2-D to 3-D ultrasound imaging. In vitro B-mode imaging studies demonstrated that the proposed method provided comparable imaging quality (e.g., spatial resolution and contrast-to-noise ratio) to conventional, mechanical-translation-based 3-D imaging while providing a much faster 3-D volume rate (e.g., 300 Hz vs [~]10 Hz). In addition to B-mode imaging, we also demonstrated 3-D power Doppler imaging and 3-D super-resolution ultrasound localization microscopy with the newly developed FASTER device. An in vivo imaging study showed that the FASTER device could clearly visualize the 3-D anatomy of the basilic vein of a healthy volunteer, and customized beamforming was implemented to accommodate the speed of sound difference between the acoustic medium and the imaging object (e.g., soft tissue). These results suggest that the newly developed redirecting reflector and the clip-on device could overcome key hurdles for future clinical translation of the FASTER 3-D imaging technology.

bioengineering↗

bioRxiv2023

Single-cell transcriptomic analyses reveal the cellular and genetic basis of aquatic locomotion in scyphozoan jellyfish

The authors have withdrawn their manuscript because the authors need to re-organize the data and writing. More experimental evidence from whole-mount ISH assay and RNAi assays will be added to support the viewpoints. Therefore, the authors do not wish this work to be cited as reference for the project. If you have any questions, please contact the corresponding author.

ecology↗