Biology subjects

He, Z.

Publications and source records attributed to He, Z..

At least 235 records · Page 13Linked to original sources

bioRxiv2021

Detecting unreported recalls in memory experiments

In experiments on free recall from lists of items, not all memory retrievals are necessarily reported. Previous studies investigated unreported retrievals by attempting to induce their externalization. We show that, without any intervention, their statistics may be directly estimated through a model-free analysis of inter-response times - the silent intervals between recalls. A delay attributable to unreported recalls emerges in three situations: if the final item was already recalled ("silent recency effect"); if the item that, within the list, follows the latest recalled item was already recalled ("silent contiguity effect"); and in sequential recalls within highly performing trials ("sequential slowdown"). We then turn to reproducing all these effects by a minimal model where the discarding of memories ("bouncing") occurs either if they are repetitious or, in strategically organized trials, if they are not sequential. Based on our findings, we propose various approaches to further probing the submerged dynamics of memory retrieval.

animal behavior and cognition↗

bioRxiv2021

IRGM/Irgm1 Aggravates Progression of Atherosclerosis by Inducing Macrophage Apoptosis

AimsAtherosclerosis underlies most cardiovascular diseases, among which acute coronary syndrome (ACS) caused by plaque rupture (PR) often leads to death. Immune-related GTPases (IRGM/Irgm1) have been extensively studied in inflammatory diseases, but their role in atherosclerosis is unclear. Determining how IRGM/Irgm1 promotes atherosclerotic plaque vulnerability will provide information for new biomarkers and/or therapeutic targets. Methods and resultsWe identified ruptured and unruptured plaques by optical coherence tomography, and found that serum IRGM was highly expressed in patients with ST-segment elevation myocardial infarction in PR. We used ApoE-/-Irgm1+/+, ApoE-/-Irgm1+/- mice and chimeric mice to establish a model of advanced atherosclerosis. The results of pathological experiments showed that Irgm1 caused plaque necrosis. The ratio of neutral lipids and cholesterol crystals increases, while the content of collagen fibers decreases, aggravating the destabilization of atherosclerotic plaques. In vitro, we used multiple approaches to confirm that Irgm1 promotes macrophage apoptosis by promoting the production of reactive oxygen species and activating the MAPK signaling pathway. ConclusionsIRGM may be a potential risk factor for PR. Mechanistic studies have shown that IRGM/Irgm1 contributes to the formation and rupture of fragile plaques. This is partly mediated by the induction of macrophage apoptosis via the MAPK signaling pathway. IRGM may offer new strategies for early treatment of ACS. Translation viewOur findings indicate that IRGM/Irgm1 contributes to formation and rupture of vulnerable plaques. It suggests that IRGM may provide a new target for the early treatment of ACS.

pathology↗

bioRxiv2021

Moment-based approximations for the Wright-Fisher model of population dynamics under natural selection at two linked loci

Properly modelling genetic recombination and local linkage has been shown to bring significant improvement to the inference of natural selection from time series data of allele frequencies under a Wright-Fisher model. Existing approaches that can account for genetic recombination and local linkage are built on either the diffusion approximation or a moment-based approximation of the Wright-Fisher model. However, methods based on the diffusion approximation are likely to require much higher computational cost, whereas moment-based approximations may suffer from the distribution support issue: for example, the normal approximation can seriously affect computational accuracy. In the present work, we introduce two novel moment-based approximations of the Wright-Fisher model on a pair of linked loci, both subject to natural selection. Our key innovation is to extend existing methods to account for both the mean and (co)variance of the two-locus Wright-Fisher model with selection. We devise two approximation schemes, using a logistic normal distribution and a hierarchical beta distribution, respectively, by matching the first two moments of the Wright-Fisher model and the approximating model. As compared with the diffusion approximation, our approximations enable the approximate computation of the transition probabilities of the Wright-Fisher model at a far smaller computational cost. We can also avoid the distribution support issue found in the normal approximation.

genetics↗

bioRxiv2020

A high-quality genome of the mangrove Aegiceras corniculatum aids investigation of molecular adaptation to intertidal environments

Mangroves have colonized extreme intertidal environments characterized by high salinity, hypoxia, and other abiotic stresses. During millions of years of evolution, mangroves have adapted to these habitats, evolving a series of highly specialized traits. Aegiceras corniculatum, a pioneer mangrove species that evolved salt secretion and crypto-vivipary, is an attractive ecological model to investigate molecular mechanisms underlying adaptation to intertidal environments. Here we report a high-quality reference genome of A. corniculatum using the PacBio SMRT sequencing technology, comprising 827 Megabases (Mb) and containing 32,092 protein-coding genes. The longest scaffold and N50 for the assembled genome are 13.76 Mb and 3.87 Mb. Comparative and evolutionary analyses revealed that A. corniculatum experienced a whole-genome duplication (WGD) event around 35 million years ago after the divergence between Aegiceras and Primula. We inferred that maintenance of cellular environmental homeostasis is an important adaptive process in A. corniculatum. The 14-3-3 protein-coding genes were retained after the recent WGD event, decoding a calcium signal to regulate Na+ homeostasis. A. corniculatum has more H+-ATPase coding genes, essential for the maintenance of low Na+ concentration in the cells, than its relatives. Photosynthesis and oxidative-phosphorylation pathways are overrepresented among significantly expanded gene families and might supply the energy needed for salt secretion. Genes involved in natural antioxidant biosynthesis, contributing to scavenging reactive oxygen species against high salinity, have also increased in copy number. We also found that all homologs of DELAY OF GERMINATION1 (DOG1), a pivotal regulator of seed dormancy, lost their heme-binding ability in A. corniculatum. This loss may contribute to crypto-vivipary. Our study provides a valuable resource to investigate molecular adaptation to extreme environments in mangroves.

genomics↗

bioRxiv2020

Validation of a novel associative transcriptomics pipeline in Brassica oleracea: Identifying candidates for vernalisation response

Associative transcriptomics has been used extensively in Brassica napus to enable the rapid identification of markers correlated with traits of interest. However, within the important vegetable crop species, Brassica oleracea, the use of associative transcriptomics has been limited due to a lack of fixed genetic resources and the difficulties in generating material due to self-incompatibility. Within Brassica vegetables, the harvestable product can be vegetative or floral tissues and therefore synchronisation of the floral transition is an important goal for growers and breeders. Vernalisation is known to be a key determinant of the floral transition, yet how different vernalisation treatments influence flowering in B. oleracea is not well understood. Here, we present results from phenotyping a diverse set of 69 B. oleracea accessions for heading and flowering traits under different environmental conditions. We developed a new associative transcriptomics pipeline, and inferred and validated a population structure, for the phenotyped accessions. A genome-wide association study identified miR172D as a candidate for the vernalisation response. Gene expression marker association identified variation in expression of BoFLC.C2 as a further candidate for vernalisation response. This study provides insights into the genetic basis of vernalisation response in B. oleracea through associative transcriptomics and confirms its characterisation as a complex G x E trait. Candidate leads were identified in miR172D and BoFLC.C2. These results could facilitate marker-based breeding efforts to produce B. oleracea lines with more synchronous heading dates, potentially leading to improved yields.

plant biology↗

bioRxiv2020

Ngn2 induces diverse neuronal lineages from human pluripotency

Human neurons engineered from induced pluripotent stem cells (iPSCs) through Neurogenin 2 (Ngn2) overexpression are widely used to study neuronal differentiation mechanisms and to model neurological diseases. However, the differentiation paths and heterogeneity of emerged neurons have not been fully explored. Here we used single-cell transcriptomics to dissect the cell states that emerge during Ngn2 overexpression across a time course from pluripotency to neuron functional maturation. We find a substantial molecular heterogeneity in the neuron types generated, with at least two populations that express genes associated with neurons of the peripheral nervous system. Neuron heterogeneity is observed across multiple iPSC clones and lines from different individuals. We find that neuron fate acquisition is sensitive to Ngn2 expression level and the duration of Ngn2 forced expression. Our data reveals that Ngn2 dosage can regulate neuron fate acquisition, and that Ngn2-iN heterogeneity can confound results that are sensitive to neuron type.

neuroscience↗

bioRxiv2020

A deep learning framework with hybrid encoding for protein coding regions prediction in biological sequences

Protein coding regions prediction is a very important but overlooked subtask for tasks such as prediction of complete gene structure, coding/noncoding RNA. Many machine learning methods have been proposed for this problem, they first encode a biological sequence into numerical values and then feed them into a classifier for final prediction. However, encoding schemes directly influence the classifiers capability to capture coding features and how to choose a proper encoding scheme remains uncertain. Recently, we proposed a protein coding region prediction method in transcript sequences based on a bidirectional recurrent neural network with non-overlapping 3-mer feature, and achieved considerable improvement over existing methods, but there is still much room to improve the performance. First, 3-mer feature that counts the occurrence frequency of trinucleotides in a biological sequence only reflect local sequence order information between the most contiguous nucleotides, which loses almost all the global sequence order information. Second, kmer features of length k larger than three (e.g., hexamer) may also contain useful information. Based on the two points, we here present a deep learning framework with hybrid encoding for protein coding regions prediction in biological sequences, which effectively exploit global sequence order information, non-overlapping gapped kmer (gkm) features and statistical dependencies among coding labels. 3-fold cross-validation tests on human and mouse biological sequences demonstrate that our proposed method significantly outperforms existing state-of-the-art methods.

bioinformatics↗

bioRxiv2020

Genetic determinants of COVID-19 drug efficacy revealed by genome-wide CRISPR screens

Immunomodulatory agents dexamethasone and colchicine, antiviral drugs remdesivir, favipiravir and ribavirin, as well as antimalarial drugs chloroquine phosphate and hydroxychloroquine are currently used in the combat against COVID-191-16. However, whether some of these drugs have clinical efficacy for COVID-19 is under debate. Moreover, these drugs are applied in COVID-19 patients with little knowledge of genetic biomarkers, which will hurt patient outcome. To answer these questions, we designed a screen approach that could employ genome-wide sgRNA libraries to systematically uncover genes crucial for these drugs action. Here we present our findings, including genes crucial for the import, export, metabolic activation and inactivation of remdesivir, as well as genes that regulate colchicine and dexamethasones immunosuppressive effects. Our findings provide preliminary information for developing urgently needed genetic biomarkers for these drugs. Such biomarkers will help better interpret COVID-19 clinical trial data and point to how to stratify COVID-19 patients for proper treatment with these drugs.

pharmacology and toxicology↗

bioRxiv2020

Duple extinguishment of COVID-19: single compound synergized inhibition of SARS-CoV-2 replication and direct suppression of inflammatory cytokines in vitro/vivo

We firstly disclose single compound yields better therapeutic outcome than Remdesivir in COVID-19 hamster treatments as it is armed with direct inhibition viral replication and intrinsic suppression inflammatory cytokines expression. Crystal data reveals that Au (I), released from Au22Glutathione18 (GA), covalently binds thiolate of Cys145 of SARS-CoV-2 Mpro. GA directly decreases SARS-CoV-2 viral replication (EC50: ~0.24 M) and intrinsically down-regulates NF{kappa}B pathway therefore significantly inhibiting expression of inflammatory cytokines in cells. The lung viral load and inflammatory cytokines in GA-treated COVID-19 transgenic mice are found to be significantly lower than that of control mice. When COVID-19 golden hamsters are treated by GA, the lung inflammatory cytokines levels are significantly lower than that of Remdesivir while their lung viral load are decreased to same level. The pathological results show that GA treatment significantly reduce lung inflammatory injuries when compared to that of Remdesivir-treated COVID-19 golden hamsters. One Sentence SummaryWe found that gold cluster molecule directly inhibits SARS-CoV-2 replication and intrinsically suppresses inflammatory cytokines expression in COVID-19 transgenic mouse and golden hamster model, gold cluster providing a better lung injury protection than Remdesivir in COVID-19 golden hamsters via intranasally dropping administration.

microbiology↗

bioRxiv2020

A comparative transcriptional landscape of two castor cultivars obtained by single-molecule sequencing comparative analysis

Background and ObjectivesCastor (Ricinus communis L.) is an important non-edible oilseed crop. Lm type female strains and normal amphiprotic strains are important castor cultivars, and are mainly different in inflorescence structures and leaf shapes. To better understand the mechanisums underling these differences at the molecular level, we performed comparative transcriptional analysis. Materials and MethodsFull-length transcriptome sequencing and short-read RNA sequencing were employed. ResultsA total of 76,068 and 44,223 non-redundant transcripts were obtained from high-quality transcripts of Lm type female strains and normal amphiprotic strains, respectively. In Lm female strain and normal amphiprotic strains 51,613 and 20,152 alternative splicing events were found, respectively. There were 13,239 transcription factors identified from the full-length transcriptomes. Comparative analysis showed great different gene expression of common and unique transcription factors between the two cultivars. Meanwhile, functional analysis of isoform was conducted. Full-length sequences were used as a reference genome, and short-read RNA sequencing analysis was performed to conduct differential gene analysis. Furthermore, the function of DEGs were performed to annotation analysis. ConclusionsThe results revealed considerable difference and expression diversity between two cultivars, well beyond what was reported in previous studies, likely reflecting the differences in architecture between these two cultivars. HighlightUsing the full-length transcriptome sequencing technology, we performed comparative analysis of transcription factors of two castor cultivars, analyzed alternative splicing events, and identified their lncRNAs.

genomics↗

bioRxiv2020

An evolutionarily acquired microRNA shapes development of mammalian cortical projections

The corticospinal tract is unique to mammals and the corpus callosum is unique to placental mammals (eutherians). The emergence of these structures is thought to underpin the evolutionary acquisition of complex motor and cognitive skills. Corticospinal motor neurons (CSMN) and callosal projection neurons (CPN) are the archetypal projection neurons of the corticospinal tract and corpus callosum, respectively. Although a number of conserved transcriptional regulators of CSMN and CPN development have been identified in vertebrates, none are unique to mammals and most are co-expressed across multiple projection neuron subtypes. Here, we discover seventeen CSMN-enriched microRNAs (miRNAs), fifteen of which map to a single genomic cluster that is exclusive to eutherians. One of these, miR-409-3p, promotes CSMN subtype identity in part via repression of LMO4, a key transcriptional regulator of CPN development. In vivo, miR-409-3p is sufficient to convert deep-layer CPN into CSMN. This is the first demonstration of an evolutionarily acquired miRNA in eutherians that refines cortical projection neuron subtype development. Our findings implicate miRNAs in the eutherians increase in neuronal subtype and projection diversity, the anatomic underpinnings of their complex behavior. Significance StatementThe mammalian central nervous system contains unique projections from the cerebral cortex thought to underpin complex motor and cognitive skills, including the corticospinal tract and corpus callosum. The neurons giving rise to these projections - corticospinal and callosal projection neurons - develop from the same progenitors, but acquire strikingly different fates. The broad evolutionary conservation of known genes controlling cortical projection neuron fates raises the question of how the more narrowly conserved corticospinal and callosal projections evolved. We identify a microRNA cluster selectively expressed by corticospinal projection neurons and exclusive to placental mammals. One of these microRNAs promotes corticospinal fate via regulation of the callosal gene LMO4, suggesting a mechanism whereby microRNA regulation during development promotes evolution of neuronal diversity.

neuroscience↗

bioRxiv2020

CyAnno: A semi-automated approach for cell type annotation of mass cytometry datasets

For immune system monitoring in large-scale studies at the single-cell resolution using CyTOF, (semi-)automated computational methods are applied for annotating live cells of mixed cell types. Here, we show that the live cell pool can be highly enriched with undefined heterogeneous cells, i.e. ungated cells, and that current (semi-)automated approaches ignore their modeling resulting in misclassified annotations. Therefore, we introduce CyAnno, a novel semi-automated approach for deconvoluting the unlabeled cytometry dataset based on a machine learning framework utilizing manually gated training data that allows the integrative modeling of gated cell types and the ungated cells. By applying this framework on several CyTOF datasets, we demonstrated that including the ungated cells can lead to a significant increase in the prediction accuracy of the gated cell types. CyAnno can be used to identify even a single cell type, including rare cells, with higher efficacy than current state-of-the-art semi-automated approaches.

bioinformatics↗

bioRxiv2020

Feature selection and causal analysis for microbiome studies in the presence of confounding using standardization

BackgroundMicrobiome studies have uncovered associations between microbes and human, animal, and plant health outcomes. This has led to an interest in developing microbial interventions for treatment of disease and optimization of crop yields which requires identification of microbiome features that impact the outcome in the population of interest. That task is challenging because of the high dimensionality of microbiome data and the confounding that results from the complex and dynamic interactions among host, environment, and microbiome. In the presence of such confounding, variable selection and estimation procedures may have unsatisfactory performance in identifying microbial features with an effect on the outcome. ResultsIn this manuscript, we aim to estimate population-level effects of individual microbiome features while controlling for confounding by a categorical variable. Due to the high dimensionality and confounding-induced correlation between features, we propose feature screening, selection, and estimation conditional on each stratum of the confounder followed by a standardization approach to estimation of population-level effects of individual features. Comprehensive simulation studies demonstrate the advantages of our approach in recovering relevant features. Utilizing a potential-outcomes framework, we outline assumptions required to ascribe causal, rather than associational, interpretations to the identified microbiome effects. We conducted an agricultural study of the rhizosphere microbiome of sorghum in which nitrogen fertilizer application is a confounding variable. In this study, the proposed approach identified microbial taxa that are consistent with biological understanding of potential plant-microbe interactions. ConclusionsStandardization enables more accurate identification of individual microbiome features with an effect on the outcome of interest compared to other variable selection and estimation procedures when there is confounding by a categorical variable.

microbiology↗

bioRxiv2020

A valid protective immune response elicited in rhesus macaques by an inactivated vaccine is capable of defending against SARS-CoV-2 infection

With the relatively serious global epidemic outbreak of SARS-CoV-2 infection, public concerns focus on not only clinical therapeutic measures and public quarantine for this disease but also the development of vaccines. The technical design of our SARS-CoV-2 inactivated vaccine provides a viral antigen that enables the exposure of more than one structural protein based upon the antibody composition of COVID-19 patients convalescent serum. This design led to valid immunity with increasing neutralizing antibody titers and a CTL response detected post-immunization of this vaccine by two injections in rhesus macaques. Further, this elicited immunoprotection in macaques enables not only to restrain completely viral replication in tissues of immunized animals, compared to the adjuvant control and those immunized by an RBD peptide vaccine, but also to significantly alleviate inflammatory lesion in lung tissues in histo-pathologic detection, compared to the adjuvant control with developed interstitial pneumonia. The data obtained from these macaques immunized with the inactivated vaccine or RBD peptide vaccine suggest that immunity with a clinically protective effect against SARS-CoV-2 infection should include not only specific neutralizing antibodies but also specific CTL responses against at least the S and N antigens.

immunology↗

bioRxiv2020

Ocular Dominance Plasticity: Measurement Reliability and Variability

AO_SCPLOWBSTRACTC_SCPLOWIn the last decade, studies have shown that short-term monocular deprivation strengthens the deprived eyes contribution to binocular vision. However, the magnitude of the change in eye dominance after monocular deprivation (i.e., the patching effect) has been found to be different between for different methods and within the same method. There are three possible explanations for the discrepancy. First, the mechanisms underlying the patching effect that are probed by different measurement tasks might exist at different neural sites. Second, test-retest variability in the measurement might have led to inconsistencies, even within the same method. Third, the patching effect itself in the same subject might fluctuate across separate days or experimental sessions. To explore these possibilities, we assessed the test-retest reliability of the three most commonly used tasks (binocular rivalry, binocular combination, and dichoptic masking) and the repeatability of the shift in eye dominance after short-term monocular deprivation for each of the task. Two variations for binocular phase combination were used, at one and many contrasts of the stimuli. Also, two variations of the dichoptic masking task was tested, in which the orientation of the mask grating was either horizontal or vertical. This makes five different measurement methods in all. We hope to resolve some of the inconsistencies reported in the literature concerning this form of visual plasticity. In this study, we also aim to recommend a measurement method that will allow us to better understand its physiological basis and the underpinning of visual disorders.

neuroscience↗

bioRxiv2020

An organoid and multi-organ developmental cell atlas reveals multilineage fate specification in the human intestine

Human intestinal organoids (HIOs) generated from pluripotent stem cells provide extraordinary opportunities to explore development and disease. Here, we generate a single-cell transcriptome reference atlas from HIOs and from multiple developing human organs to quantify the specificity of HIO cell fate acquisition, and to explore alternative fates. We identify epithelium-mesenchyme interactions, transcriptional regulators involved in cell fate specification, and stem cell maturation features in the primary tissue that are recapitulated in HIOs. We use an HIO time course to reconstruct the molecular dynamics of intestinal stem cell emergence, as well as the specification of multiple mesenchyme subtypes. We find that the intestinal master regulator CDX2 correlates with distinct phases of epithelial and mesenchymal development, and CDX2 deletion perturbs the differentiation of both intestinal epithelium and mesenchyme. Collectively our data provides a comprehensive and quantitative assessment of HIO development, and illuminates the molecular machinery underlying endodermal and mesodermal cell fate specification.

developmental biology↗

bioRxiv2020

Numerical simulation of the two-locus Wright-Fisher stochastic differential equation with application to approximating transition probability densities

Over the past decade there has been an increasing focus on the application of the Wright-Fisher diffusion to the inference of natural selection from genetic time series. A key ingredient for modelling the trajectory of gene frequencies through the Wright-Fisher diffusion is its transition probability density function. Recent advances in DNA sequencing techniques have made it possible to monitor genomes in great detail over time, which presents opportunities for investigating natural selection while accounting for genetic recombination and local linkage. However, most existing methods for computing the transition probability density function of the Wright-Fisher diffusion are only applicable to one-locus problems. To address two-locus problems, in this work we propose a novel numerical scheme for the Wright-Fisher stochastic differential equation of population dynamics under natural selection at two linked loci. Our key innovation is that we reformulate the stochastic differential equation in a closed form that is amenable to simulation, which enables us to avoid boundary issues and reduce computational costs. We also propose an adaptive importance sampling approach based on the proposal introduced by Fearnhead (2008) for computing the transition probability density of the Wright-Fisher diffusion between any two observed states. We show through extensive simulation studies that our approach can achieve comparable performance to the method of Fearnhead (2008) but can avoid manually tuning the parameter{rho} to deliver superior performance for different observed states.

genetics↗

bioRxiv2020

An Antioxidant Enzyme Therapeutic for COVID-19

The COVID-19 pandemic has taken a significant toll on people worldwide, and there are currently no specific antivirus drugs or vaccines. We report herein a therapeutic based on catalase, an antioxidant enzyme that can effectively breakdown hydrogen peroxide and minimize the downstream reactive oxygen species, which are excessively produced resulting from the infection and inflammatory process. Catalase assists to regulate production of cytokines, protect oxidative injury, and repress replication of SARS-CoV-2, as demonstrated in human leukocytes and alveolar epithelial cells, and rhesus macaques, without noticeable toxicity. Such a therapeutic can be readily manufactured at low cost as a potential treatment for COVID-19.

biochemistry↗