Biology subjects

Ren, Y.

Publications and source records attributed to Ren, Y..

At least 109 records · Page 6Linked to original sources

bioRxiv2023

Phylogeny-metabolism dual-directed single-cell genomics for dissecting and mining ecosystem function

Although microbiome-wide association studies (MWAS) have uncovered many marker organisms for an ecosystem trait, mechanisms of most microbiota-mediated processes remain elusive, due to challenges in validating the markers in situ metabolic activities and tracing such activities to individual genomes. Here we introduced a phylogeny-metabolism dual-directed single-cell genomics approach called Fluorescence-In-Situ-Hybridization-guided Single-Cell Raman-activated Sorting and Sequencing (FISH-scRACS-Seq). It directly localizes individual cells from target taxon via a FISH probe for marker organism, profiles their in situ metabolic functions via single-cell Raman spectra, sorts cells of target taxonomy and target metabolism, and produces indexed, high-coverage and precisely-one-cell genomes. From cyclohexane-contaminated seawater, cells representing the MWAS-derived marker taxon of {gamma}-Proteobacteria and that are actively degrading cyclohexane in situ were directly identified via FISH and Raman respectively, then sorted and sequenced for one-cell full genomes. In such a Pseudoalteromonas fuliginea cell, we discovered a three-component cytochrome P450 system that can convert cyclohexane to cyclohexanol in vitro, representing a previously unknown group of cyclohexane-degrading enzymes and organisms. By culture-independently unveiling enzymes, pathways, genomes and their in situ functions specifically for those single-cells with ecological relevance, FISH-scRACS-Seq is a rational and generally applicable approach for dissecting and mining microbiota functions. TeaserFISH-scRACS-Seq is a new strategy to dissect microbiota functional mechanism at single-cell resolution.

microbiology↗

bioRxiv2023

Structural adaptability and surface activity oftardigrade-inspired peptides

Tardigrades are unique micro-animals that withstand harsh conditions, such as extreme temperatures and desiccation. Recently, it was found that specific cytoprotective proteins are essential for ensuring this high environmental tolerance. In particular, cytoplasmic abundant heat soluble (CAHS) proteins, which are intrinsically disordered, adopt more ordered conformations upon desiccation, and are involved in the vitrification of the cytoplasm. The design and synthesis short peptides capable of mimicking the structural behavior (and thus the cytoprotective properties) of CAHS proteins would be beneficial for potential biomedical applications, including the development of novel heat-resistant preservatives for sensitive drug formulations. As a first step in this direction, we selected several model peptides of varying lengths derived from the conserved CAHS motifs 1 and 2, which are part of the intrinsically disordered CAHS-c2 region. We then studied their structures using circular dichroism and linear and two-dimensional infrared spectroscopy in the presence of the desolvating agent TFE (2,2,2-trifluoroethanol), which mimics desiccation. We found that the CAHS model peptides are mostly disordered at 0% TFE (a result that we confirmed by molecular dynamics simulations), but adopt a more -helical structure upon the addition of the desolvating agent, similar to what is observed for full CAHS proteins. Additionally, we employed sum frequency generation to investigate the surface activity of the peptides at the air/water interface to mimic a partial dehydration effect. Interestingly, all model peptides are surface active and also adopt a helical structure at the air/water interface. Thus, the selected sequences represent promising model peptides that show similarities in the physicochemical behavior to full CAHS proteins. Our results also suggest that arginine might be a crucial element in defining the strong propensity of these peptides to adopt a helical structure. In the future, the use CAHS model peptides to design new synthetic peptide-based materials could make it possible to mimic and exploit the cytoprotective properties of naturally occurring tardigrade proteins. SIGNIFICANCETardigrades are micro-animals that can survive extreme conditions such as desiccation and high temperatures. Recent work has shown that this capability is related to the presence of specific proteins that can remodel in order to protect the organisms cells. Mimicking this behavior using small peptides that preserve the structural properties of the full proteins is highly desirable in potential biomedical applications, such as the storage of heat-sensitive drugs. Here, we study the structural properties of model peptides derived from the conserved region of cytoplastic tardigrade proteins, and show that these peptides preserve some of the conformational behavior of the full protein under drying conditions. These peptides can therefore be used as a starting point for the design of synthetic model systems based on tardigrade-inspired peptides for tailored applications.

biochemistry↗

bioRxiv2023

A mechanical circuit in End4p coordinates force transmission during clathrin-mediated endocytosis

Mechanical forces are transmitted from the actin cytoskeleton to the membrane during clathrin-mediated endocytosis (CME) in the fission yeast Schizosaccharomyces pombe. The onset and termination of force transmission is tightly regulated temporally during different stages of CME, and spatially over the surface of the invaginated membrane. How force transmission is regulated and coordinated at the molecular scale is unclear. An adaptor protein in CME, End4p, directly transmits force by binding to both the membrane (through ANTH domain) and F-actin (through THATCH domain). We show that 8pN is required for stable binding between THATCH and F-actin. We also report the discovery and characterization of a new domain on End4p, which we named Rend (R domain in End4p), that resembles R12 of talin. Membrane localization of Rend primes the binding of THATCH to F-actin, and force-induced unfolding of Rend at 15pN terminates the transmission of force during CME. We show that the mechanical properties (mechanical stability, unfolding length, hysteresis) of Rend and THATCH are tuned to form an auto-regulated circuit for the initiation, transmission and termination of force between the actin cytoskeleton and membrane. Shorting the circuit leads to permanent End4p association with the membrane or with F-actin, or failure to enter the force transmission cycle. Mathematical modeling of force transmission through Rend-THATCH connection shows that input force from F-actin is buffered to a narrow range towards the membrane. The mechanical circuit by Rend and THATCH may be conserved and coopted evolutionarily in cell adhesion complexes.

cell biology↗

bioRxiv2023

Cryo-EM structure of the CBC-ALYREF complex

In eukaryotes, RNAs transcribed by RNA Pol II are modified at the 5 end with a 7-methylguanosine (m7G) cap, which is recognized by the nuclear cap binding complex (CBC). The CBC plays multiple important roles in mRNA metabolism including transcription, splicing, polyadenylation, and export. It promotes mRNA export through direct interaction with a key mRNA export factor, ALYREF, which in turn links the TRanscription and EXport (TREX) complex to the 5 end of mRNA. However, the molecular mechanism for CBC mediated recruitment of the mRNA export machinery is not well understood. Here, we present the first structure of the CBC in complex with an mRNA export factor, ALYREF. The cryo-EM structure of CBC-ALYREF reveals that the RRM domain of ALYREF makes direct contact with both the NCBP1 and NCBP2 subunits of the CBC. Comparing CBC-ALYREF with other cellular complexes containing CBC and/or ALYREF components provides insights into the coordinated events during mRNA transcription, splicing, and export.

molecular biology↗

bioRxiv2023

A resource for probing influences of perinatal factors on neurodevelopment in 3-10-years-old Chinese children

Adverse perinatal factors can disrupt the normal development of the brain, with potential long-term impacts on childrens overall development. Currently, the neuropathological mechanisms by which these factors lead to various neurodevelopmental disorders (NDDs) remain largely unknown. An open resource that integrate perinatal factors with brain and mental health development is essential for investigating NDD-related aetiology. In this Data Descriptor, we introduce a multicentre database containing information on perinatal factors that influence childrens brain-mind development, namely, periCBD, that combines neuroimaging and behavioural phenotypes with perinatal factors associated with a high incidence of NDDs at county/region/central district hospitals. PeriCBD was designed to establish a platform for the investigation of individual differences in brain-mind development among children aged 3-10 years are associated with perinatal factors. Ultimately, our goal was to develop an early prediction and screening model for NDDs that leverages normative data to facilitate NDD aetiology research. Herein, we provide a systematic overview of the data acquisition/cleaning/quality control/sharing, processes of periCBD and present preliminary brain-mind associations.

neuroscience↗

bioRxiv2023

ReDis: efficient metagenomic profiling via assigning ambiguous reads

SummaryMetagenomic profiling is one of the primary means of microbiome analysis, which includes classification of sequencing reads and quantification of their relative abundances. Although mang methods have been developed for metagenomic profiling, metagenomic profiling remains challenges on striking a delicate balance between accuracy and runtime as well as assigning the ambiguous reads. Here, we present a novel method, named ReDis, to overcome the above issues. ReDis combines Kraken2 with Minimap2 for aligning sequencing reads against a reference database with hundreds of gigabytes (GB) in size accurately within feasible time, and then uses a novel statistical model to assign the ambiguous reads for producing accurate abundance estimates. In contrast to the popular Kraken2+Bracken, ReDis improved the accuracy of abundance estimation on simulated reads from two highly similar genomes: Escherichia coli and Shigella flexneri. Contacth.guo@foxmail.com or jlsljf0101@126.com

bioinformatics↗

bioRxiv2023

Border-forming wound repair astrocytes

Central nervous system (CNS) lesions become surrounded by neuroprotective borders of newly proliferated reactive astrocytes. Fundamental features of these cells are poorly understood. Here, we show that 90% of border-forming astrocytes derive from proliferating Aldh1l1-expressing local astrocytes, and 10% from Pdgfra-expressing oligodendrocyte progenitors in mice. Temporal transcriptome analysis, snRNAseq and immunohistochemistry showed that after CNS injury, local mature astrocytes dedifferentiated, proliferated, and became transcriptionally reprogrammed to permanently altered new functional states, with persisting downregulation of molecules associated with astrocyte-neuron interactions, and upregulation of molecules associated with wound healing, microbial defense, and interactions with stromal and immune cells. Our findings show that at CNS injury sites, local mature astrocytes proliferate and adopt canonical features of essential wound repair cells that persist in adaptive states and are the predominant source of neuroprotective borders that re-establish CNS integrity by separating neural parenchyma from stromal and immune cells as occurs throughout the healthy CNS.

neuroscience↗

bioRxiv2023

3D-Mol: A Novel Contrastive Learning Framework for Molecular Property Prediction with 3D Information

AO_SCPLOWBSTRACTC_SCPLOWMolecular property prediction offers an effective and efficient approach for early screening and optimization of drug candidates. Although deep learning based methods have made notable progress, most existing works still do not fully utilize 3D spatial information. This can lead to a single molecular representation representing multiple actual molecules. To address these issues, we propose a novel 3D structure-based molecular modeling method named 3D-Mol. In order to accurately represent complete spatial structure, we design a novel encoder to extract 3D features by deconstructing the molecules into three geometric graphs. In addition, we use 20M unlabeled data to pretrain our model by contrastive learning. We consider conformations with the same topological structure as positive pairs and the opposites as negative pairs, while the weight is determined by the dissimilarity between the conformations. We compare 3D-Mol with various state-of-the-art(SOTA) baselines on 7 benchmarks and demonstrate our outstanding performance in 5 benchmarks.

bioinformatics↗

bioRxiv2023

Visual Sequence Encoding is Enhanced by Predictable Music Pairing via Modulating Medial Temporal Lobe and Its Connectivity with Frontostriatal Loops

Listening to music during cognitive activities, such as reading and studying, is very common in human daily life. Therefore, it is important to understand how music interacts with concurrent cognitive functions, particularly memory. Current literature has presented mixed results for whether music can benefit learning in other modalities. Evidence is needed for what neural mechanisms music can tap into to enhance concurrent memory processing. This fMRI study aimed to begin filling this gap by investigating how music of varying predictability levels influences parallel visual sequence encoding performance. Behavioral results suggest that overall, predictable music enhances visual sequential encoding, and this effect increases with the structural regularity and familiarity of music. fMRI results indicate that during visual sequence encoding, music activates traditional music-processing and motor-related areas, but decreases parahippocampal and striatal engagement. This deactivation may indicate a more efficient encoding of visual information when music is present. By comparing music conditions of different structural predictability and familiarity, we probed how this occurs. We demonstrate improved encoding with increased syntactical regularity, which was associated with decreased activity in default mode network and increased activity in inferior temporal gyrus. Furthermore, the temporal schema provided by music familiarity may influence encoding through altered functional connectivity between the prefrontal cortex, medial temporal lobe and striatum. Overall, we propose that pairing music with learning might facilitate memory by reducing neural demands for visual encoding and simultaneously strengthening the connectivity between the medial temporal lobe and frontostriatal loops important for sequencing information. Significance StatementThere is considerable interest in what mechanisms can be tapped to improve human memory. Music provides a potential modulator, but few studies have investigated music effects on encoding episodic memory. This study used a novel design to examine how music can influence concurrent visual item sequence encoding. We provided neural data to better understand mechanisms behind potential benefits of music for learning. Our results demonstrated predictable music may help guide parallel learning of sequences in another modality. We found that music might facilitate processing in neural systems associated with visual declarative long-term and working memory, and familiar music might modulate reward circuits and provide a temporal schema which facilitates better encoding of the temporal structure of new non-music information.

neuroscience↗

bioRxiv2023

Long-term impact of early life stress on serotonin connectivity

Chronic childhood stress is a prominent risk factor for developing mood disorders, yet mechanisms underlying this association remain unclear. Serotonin (5-HT) plays a crucial role in neurodevelopment and vulnerability to mood disorders. Maintenance of optimal 5-HT levels during early postnatal development is critical for the maturation of brain circuits. Developmental stress can alter the serotonin system, leading to chronic behavioral deficits. Yet, our understanding of the long-term impact of early life stress (ELS) on serotonin connectivity remains incomplete. Using a mouse model of chronic developmental stress, we sought to determine how ELS impacts brain-wide serotonin activity and behavior in adulthood. We established that adult female and male mice exposed to ELS during the first postnatal week show heightened anxiety-like behavior. Using in vivo fiber photometry and c-fos dependent activity mapping, we found that ELS enhances susceptibility to acute stress by disrupting the brain-wide functional connectivity of the raphe nucleus and the activity of dorsal raphe serotonin neuron population, in conjunction with a profound increase in the orbitofrontal cortex (OFC) activity. We further identified that 5-HT release in the medial OFC during environmental challenge is disrupted in mice exposed to ELS. Optogenetic stimulation of 5-HT terminals in the mOFC elicited an anxiolytic effect in ELS mice in a sex-dependent manner. Our findings hold significant insight into the mechanisms underlying long-term brain connectivity deficits induced by ELS, with potential implications for developing targeted stimulation-based treatments for affective disorders that arise from early life adversities.

neuroscience↗

bioRxiv2023

Species -Shared and -Unique Gyral Peaks on Human and Macaque Brains

Cortical folding is an important feature of primate brains that plays a crucial role in various cognitive and behavioral processes. Extensive research has revealed both similarities and differences in folding morphology and brain function among primates including macaque and human. The folding morphology is the basis of brain function, making cross-species studies on folding morphology important for understanding brain function and species evolution. However, prior studies on cross-species folding morphology mainly focused on partial regions of the cortex instead of the entire brain. Previously, we defined a whole-brain landmark based on folding morphology: the gyral peak. It was found to exist stably across individuals and ages in both human and macaque brains. In this study, we identified shared and unique gyral peaks in human and macaque, and investigated the similarities and differences in the spatial distribution, anatomical morphology, and functional connectivity of them.

neuroscience↗

bioRxiv2023

Sex-dependent impairments of parvalbumin expressing neurons in the retrosplenial cortex in Alzheimer's disease

Alzheimers disease is a debilitating neurodegenerative disorder with no cure and few treatment options. In early stages of Alzheimers disease, impaired metabolism, and functional connectivity of the retrosplenial cortex strongly predict future cognitive impairments. Therefore, understanding Alzheimers disease-related deficits in the retrosplenial cortex is critical for understanding the origins of cognitive impairment and identifying early treatment targets. Using the 5xFAD mouse model, we discovered early, sex-dependent alterations in parvalbumin-interneuron transcriptomic profiles. This corresponded with impaired parvalbumin-interneuron activity, which was sufficient to induce cognitive impairments and dysregulate retrosplenial functional connectivity. In fMRI scans from patients with mild cognitive impairment and Alzheimers disease, we observed a similar sex-dependent dysregulation of retrosplenial cortex functional connectivity and, in post-mortem tissue from subjects with Alzheimers disease, a loss of parvalbumin interneurons. Reversal of cognitive deficits by stimulation of parvalbumin interneurons in the retrosplenial cortex suggests that this may serve as a promising novel therapeutic strategy. One Sentence SummaryAltered function, connectivity, and survival of parvalbumin expressing neurons in the retrosplenial cortex in Alzheimers Disease.

neuroscience↗

bioRxiv2023

Identification of bioactive constituents for colitis from traditional Chinese medicine prescription via deep neural network

Colitis is a commonly encountered inflammatory disease in colon tissue, which can be triggered by various causes. Although traditional Chinese medicine (TCM) has been utilized for the treatment of colitis, it is still a great challenge to identify the major bioactive constituents and their modes of action among thousands of ingredients in TCM prescriptions. Inspired by the success of artificial intelligence and deep learning methods, we proposed a deep neural network (DNN) for TCM prescription recommendation. We constructed a graph-based DNN with 9,845 nodes and 161,950 edges, which integrated microscopic information including bioactive molecules, protein targets, and extracted features of prescriptions through feature embedding. A novel and efficient data augmentation strategy was implemented to expand the sample size based on 378 collected TCM prescriptions. Network pharmacology study revealed that the 10 most frequent ingredients in generated prescriptions were associated with multiple inflammatory signaling pathways. To verify the bioactive constituents in the generated prescriptions, 5 selected constituents were administrated to BALB/c mice with colitis. Suppressive effects of disease progression and pro-inflammatory factors comparable to sulfasalazin were observed with these compounds, revealing the effectiveness of our artificial intelligence strategy on idetification of bioactive constituents from TCM prescriptions.

bioinformatics↗

bioRxiv2023

Identification of unique cytokine expressions in tumor immune microenvironment for various cancer types using single-cell RNA sequencing data via machine learning

Cytokines are small protein molecules that exhibit potent immunoregulatory properties, which are known as the essential components of the tumor immune microenvironment (TIME). While some cytokines are known to be universally upregulated in TIME, the unique cytokine expression patterns have not been fully resolved in specific types of cancers. To address this challenge, we develop a TIME single-cell RNA sequencing (scRNA-seq) dataset, which is designed to study cytokine expression patterns for precise cancer classification. The dataset, including 39 cancers, is constructed by integrating 695 tumor scRNA-seq samples from multiple public repositories. After screening and processing, the dataset retains only the expression data of immune cells. With a machine learning classification model, unique cytokine expression patterns are identified for various cancer categories and pioneering applied to cancer classification with an accuracy rate of 78.01%. Our method will not only boost the understanding of cancer-type-specific immune modulations in TIME but also serve as a crucial reference for future diagnostic and therapeutic research in cancer immunity.

bioinformatics↗

bioRxiv2023

Endogenous recapitulation of Alzheimers disease neuropathology through human 3D direct neuronal reprogramming

Alzheimers disease (AD) is a neurodegenerative disorder that primarily affects elderly individuals, and is characterized by hallmark neuronal pathologies including extracellular amyloid-{beta} (A{beta}) plaque deposition, intracellular tau tangles, and neuronal death. However, recapitulating these age-associated neuronal pathologies in patient-derived neurons has remained a significant challenge, especially for late-onset AD (LOAD), the most common form of the disorder. Here, we applied the high efficiency microRNA-mediated direct neuronal reprogramming of fibroblasts from AD patients to generate cortical neurons in three-dimensional (3D) Matrigel and self-assembled neuronal spheroids. Our findings indicate that neurons and spheroids reprogrammed from both autosomal dominant AD (ADAD) and LOAD patients exhibited AD-like phenotypes linked to neurons, including extracellular A{beta} deposition, dystrophic neurites with hyperphosphorylated, K63-ubiquitin-positive, seed-competent tau, and spontaneous neuronal death in culture. Moreover, treatment with {beta}- or {gamma}-secretase inhibitors in LOAD patient-derived neurons and spheroids before A{beta} deposit formation significantly lowered A{beta} deposition, as well as tauopathy and neurodegeneration. However, the same treatment after the cells already formed A{beta} deposits only had a mild effect. Additionally, inhibiting the synthesis of age-associated retrotransposable elements (RTEs) by treating LOAD neurons and spheroids with the reverse transcriptase inhibitor, lamivudine, alleviated AD neuropathology. Overall, our results demonstrate that direct neuronal reprogramming of AD patient fibroblasts in a 3D environment can capture age-related neuropathology and reflect the interplay between A{beta} accumulation, tau dysregulation, and neuronal death. Moreover, miRNA-based 3D neuronal conversion provides a human-relevant AD model that can be used to identify compounds that can potentially ameliorate AD-associated pathologies and neurodegeneration.

neuroscience↗

bioRxiv2023

How well do models of visual cortex generalize to out of distribution samples?

Unit activity in particular deep neural networks (DNNs) are remarkably similar to the neuronal population responses to static images along the primate ventral visual cortex. Lin-ear combinations of DNN unit activities are widely used to build predictive models of neu-ronal activity in the visual cortex. Nevertheless, prediction performance in these models is often investigated on stimulus sets consisting of everyday objects under naturalistic set-tings. Recent work has revealed a generalization gap in how predicting neuronal responses to synthetically generated out-of-distribution (OOD) stimuli. Here, we investigated how the recent progress in improving DNNs object recognition generalization, as well as various DNN design choices such as architecture, learning algorithm, and datasets have impacted the generalization gap in neural predictivity. We came to a surprising conclusion that the performance on none of the common computer vision OOD object recognition benchmarks is predictive of OOD neural predictivity performance. Furthermore, we found that adver-sarially robust models often yield substantially higher generalization in neural predictivity, although the degree of robustness itself was not predictive of neural predictivity score. These results suggest that improving object recognition behavior on current benchmarks alone may not lead to more general models of neurons in the primate ventral visual cortex.

neuroscience↗

bioRxiv2023

Spatiotemporal transcriptome atlas of human embryos after gastrulation

The spatial and temporal atlas of gene expression in the human embryo at early gestation is critical in understanding embryo development, organogenesis, and disease origins. We obtained the spatiotemporal transcriptome from 90 sagittal sections of 16 whole human embryos from 3 to 8 post-conception weeks by Stereo-seq with high resolution and ultra-large field, establishing the development trajectory/regulatory profiling of 49 organs. We uncovered the organ-specific regulons as potential lineage-determining factors and identified the new regulatory networks during heart and brain development. The atlas refines the key organs/cell types vulnerable to virus infection and genetic disorders, and, reveals the dynamics of allelic gene expression in specific organs at different stages. These results present the first comprehensive delineation of the spatiotemporal transcriptomic dynamics of human organogenesis. One Sentence SummaryThe spatiotemporal transcriptome atlas presents a comprehensive delineation of human embryogenesis after gastrulation.

developmental biology↗

bioRxiv2023

Hagfish genome illuminates vertebrate whole genome duplications and their evolutionary consequences

Whole genome duplications (WGDs) are major events that drastically reshape genome architecture and are causally associated with organismal innovations and radiations1. The 2R Hypothesis suggests that two WGD events (1R and 2R) occurred during early vertebrate evolution2, 3. However, the veracity and timing of the 2R event relative to the divergence of gnathostomes (jawed vertebrates) and cyclostomes (jawless hagfishes and lampreys) is unresolved4-6 and whether these WGD events underlie vertebrate phenotypic diversification remains elusive7. Here we present the genome of the inshore hagfish, Eptatretus burgeri. Through comparative analysis with lamprey and gnathostome genomes, we reconstruct the early events in cyclostome genome evolution, leveraging insights into the ancestral vertebrate genome. Genome-wide synteny and phylogenetic analyses support a scenario in which 1R occurred in the vertebrate stem-lineage during the early Cambrian, and the 2R event occurred in the gnathostome stem-lineage in the late Cambrian after its divergence from cyclostomes. We find that the genome of stem-cyclostomes experienced two additional, independent genome duplications (herein CR1 and CR2). Functional genomic and morphospace analyses demonstrate that WGD events generally contribute to developmental evolution with similar changes in the regulatory genome of both vertebrate groups. However, appreciable morphological diversification occurred only after the 2R event, questioning the general expectation that WGDs lead to leaps of morphological complexity7.

genomics↗