Biology subjects

Ding, Y.

Publications and source records attributed to Ding, Y..

At least 145 records · Page 8Linked to original sources

bioRxiv2024

An inappropriate decline in ribosome levels drives a diverse set of neurodevelopmental disorders

Many neurodevelopmental defects are linked to perturbations in genes involved in housekeeping functions, such as those encoding ribosome biogenesis factors. However, how reductions in ribosome biogenesis can result in tissue and developmental specific defects remains a mystery. Here we describe new allelic variants in the ribosome biogenesis factor AIRIM primarily associated with neurodevelopmental disorders. Using human cerebral organoids in combination with proteomic analysis, single-cell transcriptome analysis across multiple developmental stages, and single organoid translatome analysis, we identify a previously unappreciated mechanism linking changes in ribosome levels and the timing of cell fate specification during early brain development. We find ribosome levels decrease during neuroepithelial differentiation, making differentiating cells particularly vulnerable to perturbations in ribosome biogenesis during this time. Reduced ribosome availability more profoundly impacts the translation of specific transcripts, disrupting both survival and cell fate commitment of transitioning neuroepithelia. Enhancing mTOR activity by both genetic and pharmacologic approaches ameliorates the growth and developmental defects associated with intellectual disability linked variants, identifying potential treatment options for specific brain ribosomopathies. This work reveals the cellular and molecular origins of protein synthesis defect-related disorders of human brain development. HighlightsO_LIAIRIM variants reduce ribosome levels specifically in neural progenitor cells. C_LIO_LIInappropriately low ribosome levels cause a transient delay in radial glia fate commitment. C_LIO_LIReduced ribosome levels impair translation of a selected subset of mRNAs. C_LIO_LIGenetic and pharmacologic activation of mTORC1 suppresses AIRIM-linked phenotypes. C_LI

developmental biology↗

bioRxiv2024

Song Torrent: A modular, open-source 96-chamber audio and video recording apparatus with optogenetic activation and inactivation capabilities for Drosophila

BackgroundO_LIMany Drosophila species use acoustic communication during courtship and studies of these communication systems have provided insight into neurobiology, behavioral ecology, ethology, and evolution. C_LIO_LIRecording Drosophila courtship sounds and associated behavior is challenging, especially at high throughput, and previously designed devices are relatively expensive and complex to assemble. C_LI ResultsO_LIWe present construction plans for a modular system utilizing mostly off-the-shelf, relatively inexpensive components that provides simultaneous high-resolution audio and video recording of 96 isolated or paired Drosophila individuals. C_LIO_LIWe provide open-source control software to record audio and video. C_LIO_LIWe designed high intensity LED arrays that can be used to perform optogenetic activation and inactivation of labelled neurons. C_LIO_LIThe basic design can be modified to facilitate novel study designs or to record insects larger than Drosophila. C_LIO_LIFewer than 96 microphones can be used in the system if the full array is not required or to reduce costs. C_LI ImplicationsO_LIOur hardware design and software provide an improved platform for reliable and comparatively inexpensive high-throughput recording of Drosophila courtship acoustic and visual behavior and perhaps for recording acoustic signals of other small animals. C_LI

animal behavior and cognition↗

bioRxiv2023

Application of slow-controlled release fertilizer coordinates the carbon flow in carbon-nitrogen metabolism to effect rice quality

Slow-controlled release fertilizers are experiencing a popularity in rice cultivation due to their effectiveness in yield and quality with low environmental costs. However, the underlying mechanism by which these fertilizers regulate grain quality remains inadequately understood. This study investigated the effects of five fertilizer management practices on rice quality in a two-year field experiment: CK, conventional fertilization, and four applications of slow-controlled release fertilizer (UF, urea formaldehyde; SCU, sulfur-coated urea; PCU, polymer-coated urea; BBF, controlled-release bulk blending fertilizer). In 2020 and 2021, the yields of UF and SCU groups showed significant decreases when compared to conventional fertilization, accompanied by a decline in nutritional quality. Additionally, PCU group exhibited poorer cooking and eating qualities. However, BBF group achieved increases in both yield (10.8 t hm-2 and 11.0 t hm-2) and grain quality reaching the level of CK group. The sufficient nitrogen supply in both the PCU and BBF groups during the grain-filling stage led to a greater capacity for the accumulation of proteins and amino acids in the PCU group compared to starch accumulation. Intriguingly, BBF group showed better carbon-nitrogen metabolism than that of PCU group. The optimal nitrogen supply present in BBF group suitable boosted the synthesis of amino acids involved in the glycolysis/ tricarboxylic acid cycle, thereby effectively coordinating carbon-nitrogen metabolism. The application of the new slow-controlled release fertilizer, BBF, is advantageous in regulating the carbon flow in the carbon-nitrogen metabolism to enhance rice quality.

plant biology↗

bioRxiv2023

Ancestral neural circuits potentiate the origin of a female sexual behavior

Courtship interactions are remarkably diverse in form and complexity among species. How neural circuits evolve to encode new behaviors that are functionally integrated into these dynamic social interactions is unknown. Here we report a recently originated female sexual behavior in the island endemic Drosophila species D. santomea, where females signal receptivity to male courtship songs by spreading their wings, which in turn promotes prolonged songs in courting males. Copulation success depends on this female signal and correlates with males ability to adjust his singing in such a social feedback loop. Functional comparison of sexual circuitry across species suggests that a pair of descending neurons, which integrates male song stimuli and female internal state to control a conserved female abdominal behavior, drives wing spreading in D. santomea. This co-option occurred through the refinement of a pre-existing, plastic circuit that can be optogenetically activated in an outgroup species. Combined, our results show that the ancestral potential of a socially-tuned key circuit node to engage the wing motor program facilitates the expression of a new female behavior in appropriate sensory and motivational contexts. More broadly, our work provides insights into the evolution of social behaviors, particularly female behaviors, and the underlying neural mechanisms.

evolutionary biology↗

bioRxiv2023

Origin and evolution of the bread wheat D genome

Bread wheat (Triticum aestivum) is a globally dominant crop and major source of calories and proteins for the human diet. Compared to its wild ancestors, modern bread wheat shows lower genetic diversity caused by polyploidisation, domestication, and breeding bottlenecks1,2. Wild wheat relatives represent genetic reservoirs, harbouring diversity and beneficial alleles that have not been incorporated into bread wheat. Here, we establish and analyse pangenome resources for Tauschs goatgrass, Aegilops tauschii, the donor of the bread wheat D genome. This new pangenome facilitated the cloning of a disease resistance gene and haplotype analysis across a complex disease resistance locus, allowing us to discern alleles from paralogous gene copies. We also reveal the complex genetic composition and history of the bread wheat D genome, involving previously unreported contributions from genetically and geographically discrete Ae. tauschii subpopulations. Together, our results reveal the complex history of the bread wheat D genome and demonstrate the potential of wild relatives in crop improvement.

genomics↗

bioRxiv2023

Comparison of tet(X4)-containing contigs from metagenomic sequencing data with plasmid sequences of isolates from a cohort of healthy subjects.

The recently discovered tigecycline-inactivating enzyme Tet(X4) can confer high-level tigecycline resistance on its hosts, which makes it a public health concern. This study focused on detection, analysis, and characterization of Tet(X4)-positive Enterobacteriaceae from the gut microbiota of a healthy cohort of individuals in Singapore using cultivation-dependent and cultivation-independent approaches. Twelve Tet(X4)-positive Enterobacteriaceae strains that were previously obtained from the cohort were fully genome-sequenced and comparatively analysed. A metagenomic sequencing (MS) dataset of the same samples was mined for contigs that harboured the tet(X4) resistance gene. The sequences of tet(X4)-containing contigs and plasmids sequences were compared. The presence of the resistance genes floR and catD (also annotated as estT) was detected in the same cassette in 10 and 12 out of the 12 tet(X4)-carrying plasmids, respectively. MS detected tet(X4)-containing contigs in two out of 109 subjects, while cultivation-dependent analysis previously reported a prevalence of 10.1%. Contig sequences are relatively short ([~]14-33 kb) but show high similarity to the respective plasmid sequences of the isolates. The frequent co-occurrence of florR and catD with tet(X4) corroborates the hypothesis that the transmission of tet(X4) may have originated from the veterinary sector. Our findings show that MS can complement efforts in the surveillance of antibiotic resistance genes for clinical samples, while it has a lower sensitivity than a cultivation-based method when the target organism have a low abundance. Further optimisation is required if MS is to be utilised in antibiotic resistance surveillance.

microbiology↗

bioRxiv2023

TRAFICA: Improving Transcription Factor Binding Affinity Prediction using Large Language Model on ATAC-seq Data

AO_SCPLOWBSTRACTC_SCPLOWIn silico transcription factor and DNA (TF-DNA) binding affinity prediction plays a vital role in examining TF binding preferences and understanding gene regulation. The existing tools employ TF-DNA binding profiles from in vitro high-throughput technologies to predict TF-DNA binding affinity. However, TFs tend to bind to sequences in open chromatin regions in vivo, such TF binding preference is seldomly considered by these existing tools. In this study, we developed TRAFICA, an open chromatin language model to predict TF-DNA binding affinity by integrating the characteristics of sequences from open chromatin regions in ATAC-seq experiments and in vitro TF-DNA binding profiles from high-throughput technologies. We applied self-supervised learning to pre-train TRAFICA on over 13 million nucleotide sequences from the peaks in ATAC-seq experiments to learn the TF binding preference in vivo. TRAFICA was further fine-tuned using the TF-DNA binding profiles from PBM and HT-SELEX technologies to learn the association between TFs and their target DNA sequences. We observed that TRAFICA significantly outperformed both machine learning-based and deep learning-based tools in predicting in vitro and in vivo TF-DNA binding affinity. These findings indicate that considering the characteristics of sequences from open chromatin regions could significantly improve TF-DNA binding affinity prediction, particularly when limited TF-DNA binding profiles from high-throughput technologies are available for specific TFs.

bioinformatics↗

bioRxiv2023

A polydiolcitrate-MoS2 composite for 3D printing Radio-opaque, Bioresorbable Vascular Scaffolds

Implantable polymeric biodegradable devices, such as biodegradable vascular stents or scaffolds, cannot be fully visualized using standard X-ray-based techniques, compromising their performance due to malposition after deployment. To address this challenge, we describe composites of methacrylated poly(1,12 dodecamethylene citrate) (mPDC) and MoS2 nanosheets to fabricate novel X-ray visible radiopaque and photocurable liquid polymer-ceramic composite (mPDC-MoS2). The composite was used as an ink with micro continuous liquid interface production (CLIP) to fabricate bioresorbable vascular scaffolds (BVS). Prints exhibited excellent crimping and expansion mechanics without strut failures and, importantly, required X-ray visibility in air and muscle tissue. Notably, MoS2 nanosheets displayed physical degradation over time in a PBS environment, indicating the potential for producing bioresorbable devices. mPDC-MoS2 is a promising bioresorbable X-ray-visible composite material suitable for 3D printing medical devices, particularly vascular scaffolds or stents, that require non-invasive X-ray-based monitoring techniques for implantation and evaluation. This innovative composite system holds significant promise for the development of biocompatible and highly visible medical implants, potentially enhancing patient outcomes and reducing medical complications. TOC O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=124 SRC="FIGDIR/small/564364v1_ufig1.gif" ALT="Figure 1"> View larger version (40K): org.highwire.dtl.DTLVardef@58cb6aorg.highwire.dtl.DTLVardef@192d2b1org.highwire.dtl.DTLVardef@4699a3org.highwire.dtl.DTLVardef@110d7f8_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioengineering↗

bioRxiv2023

3D-printed, Citrate-based Bioresorbable Vascular Scaffolds for Coronary Artery Angioplasty

Fully bioresorbable vascular scaffolds (BVSs) were designed to overcome the limitations of metallic drug-eluting stents (DESs). However, current polymer-based BVSs, such as Abbotts Absorb, the only US FDA-approved BVS, struggle with increased strut thickness (150 m for Absorb) and exacerbated tissue inflammation, leading to inferior clinical performance compared to metallic DESs. Here we develop a drug-eluting BVS (DE-BVS) through the innovative use of photopolymerizable, citrate-based materials and high-precision additive manufacturing process. Bare BVS with a clinically relevant strut thickness of 62 m can be produced in a high-throughput manner, i.e. one BVS per minute. By modulating the coating polymer and structure, we achieve a controlled release of anti-restenosis drug of everolimus from DE-BVSs. We show the mechanical competence of DE-BVS and the successful deployment in swine coronary arteries using a custom-built balloon catheter delivery system. We further demonstrate that BVS and DE-BVS remain safe and effective to keep the vessel patency, induce limited inflammation, and facilitate the recovery of smooth muscle and endothelial tissues over 28 days implantation in swine coronary arteries. All these evaluated pre-clinical performances are largely comparable to the commercial XIENCE DES (Abbott Vascular).

bioengineering↗

bioRxiv2023

Investigation of 3D Printed Bioresorbable Vascular Scaffold Crimping Behavior

The rise in additive manufacturing (AM) offers myriad opportunities for 3D-printed polymeric vascular scaffolds, such as customization and on-the-spot manufacturing, in vivo biodegradation, incorporation of drugs to prevent restenosis, and visibility under X-ray. To maximize these benefits, informed scaffold design is critical. Polymeric bioresorbable vascular scaffolds (BVS) must undergo significant deformation prior to implantation in a diameter-reduction process known as crimping which enables minimally invasive surgery. Understanding the behavior of vascular scaffolds in this step provides twofold benefits: first, it ensures the BVS is able to accommodate stresses occurring during this process to prevent failure, and further, it provides information on the radial strength of the BVS, a key metric to understanding its post-implant performance in the artery. To capitalize on the fast manufacturing speed AM provides, a low time cost solution for understanding scaffold performance during this step is necessary. Through simulation of the BVS crimping process in ABAQUS using experimentally obtained bulk material properties, we have developed a qualitative analysis tool which is capable of accurately comparing relative performance trends of varying BVS designs during crimping in a fraction of the time of experimental testing, thereby assisting in the integration of informed design into the additive manufacturing process.

bioengineering↗

bioRxiv2023

Growth inhibitory factor/metallothionein-3 is a sulfane sulfur-binding protein

Cysteine-bound sulfane sulfur atoms in proteins have received much attention as key factors in cellular redox homeostasis. However, the role of sulfane sulfur in zinc regulation has been underinvestigated. We report here that cysteine-bound sulfane sulfur atoms serve as ligands to hold and release zinc ions in growth inhibitory factor (GIF)/metallothionein-3 (MT-3) with an unexpected C-S-S-Zn structure. Oxidation of such a zinc/persulfide cluster in Zn7GIF/MT-3 results in the release of zinc ions, and intramolecular tetrasulfide bridges in apo-GIF/MT-3 efficiently undergo S-S bond cleavage by thioredoxin to regenerate Zn7GIF/MT-3. Three-dimensional molecular modeling confirmed the critical role of the persulfide group in the thermostability and Zn-binding affinity of GIF/MT-3. The present discovery raises the fascinating possibility that the function of other Zn-binding proteins is controlled by sulfane sulfur.

biochemistry↗

bioRxiv2023

Neural signatures of competition between voluntary and involuntary influences over the focus of attention in visual working memory

Adaptive behaviour relies on the selection and prioritisation of relevant sensory inputs from the external environment as well as from among internal sensory representations held in working memory. Recent behavioural evidence suggests that the classic distinction between voluntary (goal-driven) and involuntary (stimulus-driven) influences over attentional allocation also applies to the selection of internal representations held in working memory. In the current EEG study, we set out to investigate the neural dynamics associated with the competition between voluntary and involuntary control over the focus of attention in visual working memory. We show that when voluntary and involuntary factors compete for the internal focus of attention, prioritisation of the appropriate item is delayed - as reflected both in delayed gaze biases that track internal selection and in delayed neural beta (15-25 Hz) dynamics that track the planning for the upcoming memory-guided manual action. We further show how this competition is paralleled - possibly resolved - by an increase in frontal midline theta (4-8 Hz) activity that, moreover, predicts the speed of ensuing memory-guided behaviour. Finally, because theta increased following retrocues that effectively reduced working-memory load, our data unveil how frontal theta activity during internal attentional focusing tracks demands on cognitive control over and above working-memory load. Together, these data yield new insight into the neural dynamics that govern the focus of attention in visual working memory, and disentangles the contributions of frontal midline theta activity to the processes of control versus retention in working memory.

neuroscience↗

bioRxiv2023

DP/MM: A Hybrid Model for Zinc-Protein Interactions in Molecular Dynamics

Zinc-containing proteins are essential to a variety of biological processes, yet accurately modeling them using classical force fields is hindered by complicated polarization and charge transfer effects. This study introduces DP/MM, a hybrid force field model that combines ab initio accuracy with MM-level efficiency for modeling zinc-protein interactions. The DP/MM scheme utilizes a deep potential model to correct the atomic forces of zinc ions and their coordinated atoms, elevating them from MM to QM levels of accuracy. The model is trained on the difference in atomic forces between MM and QM calculations across diverse zinc coordination groups. Simulations on a variety of zinccontaining proteins demonstrate that DP/MM faithfully reproduces their coordination geometry and structural characteristics, for example, the tetrahedral coordination structures for the Cys4 and the Cys3His1 groups. Furthermore, DP/MM is capable of handling exchangeable water molecules in the zinc coordination environment. With its unique blend of accuracy, efficiency, flexibility, and transferability, DP/MM not only serves as a valuable tool for studying zinc-containing proteins but also represents a pioneering approach that augments the growing landscape of machine learning potentials in molecular modeling.

biophysics↗

bioRxiv2023

Deepurify: a multi-modal deep language model to remove contamination from metagenome-assembled genomes

Metagenome-assembled genomes (MAGs) offer valuable insights into the exploration of microbial dark matter using metagenomic sequencing data. However, there is a growing concern that contamination in MAGs may significantly impact the downstream analysis results. Existing MAG decontamination methods heavily rely on marker genes but do not fully leverage genomic sequences. To address the limitations, we have introduced a novel decontamination approach named Deepurify, which utilizes a multi-modal deep language model employing contrastive learning to learn taxonomic similarities of genomic sequences. Deepurify utilizes inferred taxonomic lineages to guide the allocation of contigs into a MAG-separated tree and employs a tree traversal strategy for maximizing the total number of medium- and high-quality MAGs. Extensive experiments were conducted on two simulated datasets, CAMI I, and human gut metagenomic sequencing data. These results demonstrate that Deepurify significantly outperforms other decontamination methods.

genomics↗

bioRxiv2023

A modular circuit architecture coordinates the diversification of courtship strategies in Drosophila

Identifying a mate is a central imperative for males of most species but poses the challenge of distinguishing a suitable partner from an array of potential male competitors or females of related species. Mate recognition systems are thus subject to strong selective pressures, driving the rapid coevolution of female sensory cues and male sensory preferences. Here we leverage the rapid evolution of female pheromones across the Drosophila genus to gain insight into how males coordinately adapt their detection and interpretation of these chemical cues to hone their mating strategies. While in some Drosophila species females produce unique pheromones that act to attract and arouse their conspecific males, the pheromones of most species are sexually monomorphic such that females possess no distinguishing chemosensory signatures that males can use for mate recognition. By comparing several close and distantly-related Drosophila species, we reveal that D. yakuba males have evolved the distinct ability to use a sexually-monomorphic pheromone, 7-tricosene (7-T), as an excitatory cue to promote courtship, a sensory innovation that enables D. yakuba males to court in the dark thereby expanding their reproductive opportunities. To gain insight into the neural adaptations that enable 7-T to act as an excitatory cue, we compared the functional properties of two key nodes within the pheromone circuits of D. yakuba and a subset of its closest relatives. We show that the instructive role of 7-T in D. yakuba arises from concurrent peripheral and central circuit changes: a distinct subpopulation of sensory neurons has acquired sensitivity to 7-T which in turn selectively signals to a distinct subset of P1 neurons in the central brain that trigger courtship behaviors. Such a modular circuit organization, in which different sensory inputs can independently couple to multiple parallel courtship control nodes, may facilitate the evolution of mate recognition systems by allowing males to take advantage of novel sensory modalities to become aroused. Together, our findings suggest how peripheral and central circuit adaptations can be flexibly linked to underlie the rapid evolution of mate recognition and courtship strategies across species.

neuroscience↗

bioRxiv2023

Functional connectome through the human life span

The lifespan growth of the functional connectome remains unknown. Here, we assemble task-free functional and structural magnetic resonance imaging data from 33,250 individuals aged 32 postmenstrual weeks to 80 years from 132 global sites. We report critical inflection points in the nonlinear growth curves of the global mean and variance of the connectome, peaking in the late fourth and late third decades of life, respectively. After constructing a fine-grained, lifespan-wide suite of system-level brain atlases, we show distinct maturation timelines for functional segregation within different systems. Lifespan growth of regional connectivity is organized along a primary-to-association cortical axis. These connectome-based normative models reveal substantial individual heterogeneities in functional brain networks in patients with autism spectrum disorder, major depressive disorder, and Alzheimers disease. These findings elucidate the lifespan evolution of the functional connectome and can serve as a normative reference for quantifying individual variation in development, aging, and neuropsychiatric disorders.

neuroscience↗

bioRxiv2023

PyHFO: Lightweight Deep Learning-poweredEnd-to-End High-Frequency Oscillations AnalysisApplication

In the context of epilepsy studies, intracranially-recorded interictal high-frequency oscillations (HFOs) in EEG signals are emerging as promising spatial neurophysiological biomarkers for epileptogenic zones. While significant efforts have been made in identifying and understanding these biomarkers, deep learning is carving novel avenues for biomarker detection and analysis. Yet, transitioning such methodologies to clinical environments is difficult due to the rigorous computational needs of processing EEG data via deep learning. This paper presents our development of an advanced end to end software platform, PyHFO, aimed at bridging this gap. PyHFO provides an integrated and user-friendly platform that includes time-efficient HFO detection algorithms such as short-term energy (STE) and Montreal Neurological Institute and Hospital (MNI) detectors and deep learning models for artifact and HFO with spike classification. This application functions seamlessly on conventional computer hardware. Our platform has been validated to adeptly handle datasets from 10-minute EEG recordings captured via grid/strip electrodes in 19 patients. Through implementation optimization, PyHFO achieves speeds up to 50 times faster than the standard HFO detection method. Users can either employ our pre-trained deep learning model for their analyses or use their EEG data to train their model. As such, PyHFO holds great promise for facilitating the use of advanced EEG data analysis tools in clinical practice and large-scale research collaborations.

neuroscience↗

bioRxiv2023

High-throughput generic single-entity sequencing using droplet microfluidics

Single-cell sequencing has revolutionized our understanding of cellular heterogeneity by providing a micro-level perspective over the past decades. Although heterogeneity is essential for various biological communities, the currently demonstrated platform predominantly focuses on eukaryotic cells without cell walls and their transcriptomics 1,2, leaving significant gaps in the study of omics from other single biological entities such as bacteria and viruses. Due to the difficulty of isolating and acquiring their DNA3, contemporary methodologies for the characterization of generic biological entities remain conspicuously constrained, with low throughput4, compromised lysis efficiency5, and highly fragmented genomes6. Herein, we present the Generic Single Entity Sequencing platform (GSE-Seq), which boasts ample versatility, high throughput, and high coverage, and is enabled by an innovative workflow, addressing the critical challenges in single entities sequencing: (1) one-step manufacturing of massive barcodes, (2) degradable hydrogel-based in situ sample processing and whole genome amplification, (3) integrated in-drop library preparation, (4) compatible long-read sequencing. By GSE-Seq, we have achieved a significant milestone by enabling high-throughput, long-read single-entity profiling of dsDNA and ssDNA from single virus sequencing (SV-seq) and single bacteria sequencing (SB-seq) of the human gut and marine sediment for the first time. Notably, our analysis uncovered previously overlooked viral and bacterial dark matter and phage-host interactions. In summary, the presented conceptually new workflow offers a toolbox based on droplet microfluidics to tackle the persistent challenges in high-throughput profiling to generic applications, which hold immense promise for diverse biological entities, especially hard-to-lyse cells.

bioengineering↗