Biology subjects

Shi, Z.

Publications and source records attributed to Shi, Z..

At least 109 records · Page 6Linked to original sources

bioRxiv2023

Addressing preferred orientation in single-particle cryo-EM through AI-generated auxiliary particles.

The single-particle cryo-EM field faces the persistent challenge of preferred orientation, lacking general computational solutions. We introduce cryoPROS, an AI-based approach designed to address the above issue. By generating the auxiliary particles with a conditional deep generative model, cryoPROS addresses the intrinsic bias in orientation estimation for the observed particles. We effectively employed cryoPROS in the cryo-EM single particle analysis of the hemagglutinin trimer, showing the ability to restore the near-atomic resolution structure on non-tilt data. Moreover, the enhanced version named cryoPROS-MP significantly improves the resolution of the membrane protein NaX using the no-tilted data that contains the effects of micelles. Compared to the classical approaches, cryoPROS does not need special experimental or image acquisition techniques, providing a purely computational yet effective solution for the preferred orientation problem. Finally, we conduct extensive experiments that establish the low risk of model bias and the high robustness of cryoPROS.

biophysics↗

bioRxiv2023

SHIP1 modulation and proteome characterization of microglia

Microglia, the resident macrophage in brain, has gained significant attention due to their involvement in neurodegenerative diseases. Disease associated microglia (DAM) have been identified at sites of amyloid-beta plaques and neurodegeneration. Understanding microglial states in the aging brain has become crucial, especially with the discovery of numerous Alzheimers disease (AD) risk and protective variants in genes such as TREM2, CD33, APOE, ABCA7, PLCG2, and INPP5D, which are essential to microglia function1. Here we present a thorough examination of microglia-like cell lines and primary mouse microglia at the proteomic and transcriptomic levels to help illuminate the roles these genes and the proteins they encode play in various cell states. This analysis serves as a guide to the exploration of potential therapeutic targets in the context of neurodegeneration. INPP5D, which encodes the SHIP1 protein, is essential for microglia function. SHIP1 has emerged as a target of interest having been nominated as a therapeutic target by three teams within the Accelerating Medicines Partnership for Alzheimers Disease (AMP-AD)2. In this study, we compared the proteomic profiles of wildtype, SHIP1 heterozygous knockout, and homozygous knockout primary microglia. Our findings revealed significant proteomic alterations only in the homozygous knockout of the SHIP1 gene, revealing its impact on the microglial proteome. Additionally, we compared the proteomic and transcriptomic profiles of BV2 and HMC3 cells with primary mouse microglia because these cell lines are often used as microglial cellular models. Our results demonstrated a substantial similarity between the proteome of BV2 cells and mouse primary cells, while notable differences were observed between BV2 and human HMC3 cells, with some shared characteristics. Since SHIP1 functions as a lipid phosphatase that modulates phosphatidylinositol (PI) species, we conducted lipidomic analysis to quantify different phosphatidylinositols (PIs), phosphatidylinositol monophosphate (PIPs), and polyphosphoinositides (PPIs) in the HMC3 and BV2 cells. Under basal conditions, PI(3,4,5)P3 and PI(3,4)P2 species were detected at extremely low levels, making confident quantification challenging; however, PIP species within the overall pool were significantly changed upon SHIP1 overexpression in HMC3. This in-depth proteomic analysis of both mouse and human microglia, complemented by targeted lipidomic studies, enhances our understanding of these cellular models. The similarities between primary mouse microglia and the BV2 cell line is especially encouraging, supporting the use of this model for further investigations into the role that SHIP1 and other potential drug targets may play in the regulation of microglial states.

neuroscience↗

bioRxiv2023

Ketone supplementation dampens subjective and objective responses to alcohol in rats and humans

Previous preclinical and human studies have shown that high-fat ketogenic diet and ketone supplements (KS) are efficacious in reducing alcohol craving, alcohol consumption, and signs of alcohol withdrawal. However, the effects of KS on alcohol sensitivity are unknown. In this single-blind, cross-over study, 10 healthy participants (3 females) were administered a single, oral dose of a KS (25 g of ketones from D-{beta}-hydroxybutyric acid and R-1,3-butanediol) or placebo 30 min prior to an oral alcohol dose (0.25 g/kg for women; 0.31 g/kg for men). Assessments of breath alcohol concentration (BrAC) and blood alcohol levels (BAL) and responses on the Drug Effect Questionnaire were repeatedly obtained over 180 min after alcohol consumption. In a parallel preclinical study, 8 Wistar rats (4 females) received an oral gavage of KS (0.42 g ketones/kg), water, or the sweetener allulose (0.58 g/kg) followed 15 min later by an oral alcohol dose (0.8 g/kg). BAL were monitored for 240 min after alcohol exposure. In humans, the intake of KS prior to alcohol significantly blunted BrAC and BAL, reduced ratings of alcohol liking and wanting, and increased disliking for alcohol. In rats, KS reduced BAL more than either allulose or water. In conclusion, KS altered physiological and subjective responses to alcohol in both humans and rats and the effects were likely not mediated by the sweetener allulose present in the KS drink. Therefore, KS could potentially reduce the intoxicating and rewarding effects of alcohol and thus be a novel intervention for treating alcohol use disorder.

pharmacology and toxicology↗

bioRxiv2023

Comprehensive Metabolomic Analysis of Human Heart Tissue Enabled by Parallel Metabolite Extraction and High-Resolution Mass Spectrometry

The heart contracts incessantly and requires a constant supply of energy, utilizing numerous metabolic substrates such as fatty acids, carbohydrates, lipids, and amino acids to supply its high energy demands. Therefore, a comprehensive analysis of various metabolites is urgently needed for understanding cardiac metabolism; however, complete metabolome analyses remain challenging due to the broad range of metabolite polarities which makes extraction and detection difficult. Herein, we implemented parallel metabolite extractions and high-resolution mass spectrometry (MS)-based methods to obtain a comprehensive analysis of the human heart metabolome. To capture the diverse range of metabolite polarities, we first performed six parallel liquid-liquid extractions (three monophasic, two biphasic, and one triphasic extractions) of healthy human donor heart tissue. Next, we utilized two complementary MS platforms for metabolite detection - direct-infusion ultrahigh-resolution Fourier-transform ion cyclotron resonance (DI-FTICR) and high-resolution liquid chromatography quadrupole time-of-flight tandem MS (LC-Q-TOF MS/MS). Using DI-FTICR MS, 9,521 metabolic features were detected where 7,699 were assigned a chemical formula and 1,756 were assigned an annotated by accurate mass assignment. Using LC-Q-TOF MS/MS, 21,428 metabolic features were detected where 626 metabolites were identified based on fragmentation matching against publicly available libraries. Collectively, 2276 heart metabolites were identified in this study which span a wide range of polarities including polar (benzenoids, alkaloids and derivatives and nucleosides) as well as non-polar (phosphatidylcholines, acylcarnitines, and fatty acids) compounds. The results of this study will provide critical knowledge regarding the selection of appropriate extraction and MS detection methods for the analysis of the diverse classes of human heart metabolites. Table of Contents Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=108 SRC="FIGDIR/small/558013v1_ufig1.gif" ALT="Figure 1"> View larger version (27K): org.highwire.dtl.DTLVardef@1db91c8org.highwire.dtl.DTLVardef@400d81org.highwire.dtl.DTLVardef@136b221org.highwire.dtl.DTLVardef@1e8d3b9_HPS_FORMAT_FIGEXP M_FIG C_FIG

molecular biology↗

bioRxiv2023

Reply to: Contribution of carbon inputs to soil carbon accumulation cannot be neglected

In the accompanying Comment1, He et al. argue that the determinant role of microbial carbon use efficiency in global soil organic carbon (SOC) storage shown in Tao et al. (2023)2 was overestimated because carbon inputs were neglected in our data analysis while they suggest that our model-based analysis could be biased and model-dependent. Their argument is based on a different choice of independent variables in the data analysis and a sensitivity analysis of two process-based models other than that used in our study. We agree that both carbon inputs and outputs (as mediated by microbial processes) matter when predicting SOC storage - the question is their relative contributions. While we encourage further studies to examine how the evaluation of the relative importance of CUE to global SOC storage may vary with different model structures, He et al.s claims about Tao et al. (2023) need to be taken as an alternative, unproven hypothesis until empirical data support their specific parameterization. Here we show that an additional literature assessment of global data does not support He et al.s argument, in contrast to our study, and that further study on this topic is essential.

ecology↗

bioRxiv2023

Building explainable graph neural network by sparse learning for the drug-protein binding prediction

Explainable Graph Neural Networks (GNNs) have been developed and applied to drug-protein binding prediction to identify the key chemical structures in a drug that have active interactions with the target proteins. However, the key structures identified by the current explainable GNN models are typically chemically invalid. Furthermore, a threshold needs to be manually selected to pinpoint the key structures from the rest. To overcome the limitations of the current explainable GNN models, we propose our SLGNN, which stands for using Sparse Learning to Graph Neural Networks. Our SLGNN relies on using a chemical-substructure-based graph (where nodes are chemical substructures) to represent a drug molecule. Furthermore, SLGNN incorporates generalized fussed lasso with message-passing algorithms to identify connected subgraphs that are critical for the drug-protein binding prediction. Due to the use of the chemical-substructure-based graph, it is guaranteed that any subgraphs in a drug identified by our SLGNN are chemically valid structures. These structures can be further interpreted as the key chemical structures for the drug to bind to the target protein. We demonstrate the explanatory power of our SLGNN by first showing all the key structures identified by our SLGNN are chemically valid. In addition, we illustrate that the key structures identified by our SLGNN have more predictive power than the key structures identified by the competing methods. At last, we use known drug-protein binding data to show the key structures identified by our SLGNN contain most of the binding sites. CCS CONCEPTS* Computing methodologies [->] Neural networks; Supervised learning by classification; Neural networks. ACM Reference FormatYang Wang, Zanyu Shi, Timothy Richardson, Kun Huang, Pathum Weerawarna, and Yijie Wang. 2023. Building explainable graph neural network by sparse learning for the drug-protein binding prediction. In Proceedings of Make sure to enter the correct conference title from your rights confirmation email (CNB MAC 2023). ACM, New York, NY, USA, 10 pages. https://doi.org/XXXXXXX.XXXXXXX

bioinformatics↗

bioRxiv2023

Overestimation in time reproduction: Influences of accuracy feedback and attentional sharing

Duration reproduction is often subjective to biases, with a general tendency to overestimate durations, which has been observed in many studies. Yet, this overestimation is frequently dismissed as a nuisance error, and its underlying mechanisms remain elusive. Here, we conducted two experiments to investigate this general overestimation in duration reproduction. To pin down the origin of the error, we manipulated the reproduction output through shortened visual feedback in Experiment 1, while varying the presence of accuracy feedback in Experiment 2. Across both experiments, we observed a consistent overestimation in reproduction when accuracy feedback was absent. This overestimation, amounting to approximately 13.5% on a ratio basis across different durations and sessions, was unaffected by shortened visual feedback. We propose that this consistent overestimation is likely due to the attentional sharing between the action execution and the monitoring of the passage of time during the reproduction process.

neuroscience↗

bioRxiv2023

Spatial and single-nucleus transcriptomic analysis of genetic and sporadic forms of Alzheimer's Disease

The pathogenesis of Alzheimers disease (AD) depends on environmental and heritable factors, with remarkable differences evident between individuals at the molecular level. Here we present a transcriptomic survey of AD using spatial transcriptomics (ST) and single-nucleus RNA-seq in cortical samples from early-stage AD, late-stage AD, and AD in Down Syndrome (AD in DS) donors. Studying AD in DS provides an opportunity to enhance our understanding of the AD transcriptome, potentially bridging the gap between genetic mouse models and sporadic AD. Our analysis revealed spatial and cell-type specific changes in disease, with broad similarities in these changes between sAD and AD in DS. We performed additional ST experiments in a disease timecourse of 5xFAD and wildtype mice to facilitate cross-species comparisons. Finally, amyloid plaque and fibril imaging in the same tissue samples used for ST enabled us to directly link changes in gene expression with accumulation and spread of pathology.

neuroscience↗

bioRxiv2023

Evaluation of gliovascular functions of Aqp4 readthrough isoforms

Aquaporin-4 (AQP4) is a water channel protein that links astrocytic endfeet to the blood-brain barrier (BBB) and regulates water and potassium homeostasis in the brain, as well as the glymphatic clearance of waste products that would otherwise potentiate neurological diseases. Recently, translational readthrough was shown to generate a C-terminally extended variant of AQP4, known as AQP4x, that preferentially localizes around the BBB through interaction with the scaffolding protein -syntrophin, and loss of AQP4x disrupts waste clearance from the brain. To investigate the function of AQP4x, we generated a novel mouse AQP4 line (AllX) to increase relative levels of the readthrough variant above the [~]15% of AQP4 in the brain of wildtype (WT) mice. We validated the line and assessed characteristics that are affected by the presence of AQP4x, including AQP4 and -syntrophin localization, integrity of the BBB, and neurovascular coupling. We compared AllXHom and AllXHet mice to wildtype, and to previously characterized AQP4 NoXHet and NoXHom mice, which cannot produce AQP4x. Increased dose of AQP4x enhanced perivascular localization of - syntrophin and AQP4, while total protein expression of the two were unchanged. However, at 100% readthrough, AQP4x localization and formation of higher-order complexes was disrupted. Electron microscopy showed that overall blood vessel morphology was unchanged except for increased endothelial cell vesicles in NoXHom mice, which may correspond to a leakier BBB or altered efflux that was identified in NoX mice using MRI. These data demonstrate that AQP4x plays a small but measurable role in maintaining BBB integrity as well as recruiting structural and functional support proteins to the blood vessel. This also establishes a new set of genetic tools for quantitatively modulating AQP4x levels. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=115 SRC="FIGDIR/small/549379v1_ufig1.gif" ALT="Figure 1"> View larger version (29K): org.highwire.dtl.DTLVardef@18f8f32org.highwire.dtl.DTLVardef@25afeorg.highwire.dtl.DTLVardef@a3e0e1org.highwire.dtl.DTLVardef@100f2e1_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

bioRxiv2023

A generalized approach to genetic drift and its applications -- I. An example of the evolution of ribosomal RNA genes

Multi-copy gene systems that evolve within, as well as between, individuals are common. They include viruses, mitochondrial DNAs, multi-gene families etc. The paradox is that neutral evolution in two stages should be slower than single-copy systems but the opposite is often true. We now apply the Haldane model, recently generalized as the GH model (1), to quantify genetic drift in mammalian ribosomal RNA genes (rDNAs). On average, the copy number (C) is 150 - 300 per haploid. A neutral mutation in rDNA should take 4NC* generations to become fixed (N, the population size; C *, the effective copy number within individuals). While C > C* >> 1 is expected, the observed fixation time in mouse is < 4N, leading to the paradox of C* < 1. Genetic drift of rRNA genes thus appears 10-100 times stronger than in single-copy genes. The large increases are driven by a host of molecular mechanisms such as gene conversion and unequal crossover. Although each mechanism of drift is very difficult to quantify, the GH model permits the estimation of their total effects that constitute the aggregate "evolutionary noises". In humans, the fixation rate of rRNA genes is higher than the theoretical maximum of drift, hence, justifying the inference of adaptive evolution. In conclusion, the stochastic evolution in multi-copy gene systems, including viruses and others, can be effectively tracked by GH model.

evolutionary biology↗

bioRxiv2023

A Bayesian observer model reveals a prior for natural daylights in hue perception

Incorporating statistical characteristics of stimuli in perceptual processing can be highly beneficial for reliable estimation from noisy sensory measurements but may generate perceptual bias. According to Bayesian inference, perceptual biases arise from integrating internal priors with noisy sensory inputs. We used a Bayesian observer model to derive biases and priors in hue perception based on discrimination data for hue ensembles with varying levels of chromatic noise. For isoluminant stimuli with hue defined by azimuth angle in cone-opponent color space, discrimination thresholds showed a bimodal pattern, with lowest thresholds near a non-cardinal blue-yellow axis that aligns closely with the variation of natural daylights. Perceptual biases showed zero crossings around this axis, indicating repulsion away from yellow and attraction towards blue. The biases could be explained by the Bayesian observer model through a non-uniform prior with a preference for blue. Our results suggest that visual processing exploits knowledge of the distribution of colors in natural environments for hue perception.

neuroscience↗

bioRxiv2023

FOXK2 amplification and overexpression promotes breast cancer development and chemoresistance

Activation of oncogenes through DNA amplification/overexpression plays an important role in cancer initiation and progression. Chromosome 17 has many cancer-associated genetic anomalies. This cytogenetic anomaly is strongly associated with poor prognosis of breast cancer. FOXK2 gene is located on 17q25 and encodes a transcriptional factor with a forkhead DNA binding domain. By integrative analysis of public genomic datasets of breast cancers, we found that FOXK2 is frequently amplified and overexpressed in breast cancers. FOXK2 overexpression in breast cancer patients is associated with poor overall survival. FOXK2 knockdown significantly inhibits cell proliferation, invasion and metastasis, and anchorage-independent growth, as well as causes G0/G1 cell cycle arrest in breast cancer cells. Moreover, inhibition of FOXK2 expression sensitizes breast cancer cells to frontline anti-tumor chemotherapies. More importantly, co-overexpression of FOXK2 and PI3KCA with oncogenic mutations (E545K or H1047R) induces cellular transformation in non-tumorigenic MCF10A cells, suggesting that FOXK2 is an oncogene in breast cancer and is involved in PI3KCA-driven tumorigenesis. Our study identified CCNE2, PDK1, and Estrogen receptor alpha (ESR1) as direct transcriptional targets of FOXK2 in MCF-7 cells. Blocking CCNE2- and PDK1-mediated signaling by using small molecule inhibitors has synergistic anti-tumor effects in breast cancer cells. Furthermore, FOXK2 inhibition by gene knockdown or inhibitors for its transcriptional targets (CCNE2 and PDK1) in combination with PI3KCA inhibitor, Alpelisib, showed synergistic anti-tumor effects on breast cancer cells with PI3KCA oncogenic mutations. In summary, we provide compelling evidence that FOXK2 plays an oncogenic role in breast tumorigenesis and targeting FOXK2-mediated pathways may be a potential therapeutic strategy in breast cancer.

cancer biology↗

bioRxiv2023

The Notch-Pdgfr beta axis suppresses brown adipocyte progenitor differentiation in early postnatal mice

De novo brown adipogenesis holds potential in combating the epidemics of obesity and diabetes. However, the identity of brown adipocyte progenitor cells (APCs) and their regulation have not been extensively studied. Here through in vivo lineage tracing, we observed that PDGFR{beta}+ pericytes give rise to developmental brown adipocytes, but not to those in adult homeostasis. In contrast, TBX18+ pericytes contribute to brown adipogenesis throughout both developmental and adult stages, though in a depot-specific manner. Mechanistically, Notch inhibition in PDGFR{beta}+ pericytes promotes brown adipogenesis through the downregulation of PDGFR{beta}. Furthermore, inhibition of Notch signaling in PDGFR{beta}+ pericytes mitigates HFHS (high-fat, high-sucrose) induced glucose and metabolic impairment in both developmental and adult stages. Collectively, these findings show that the Notch/PDGFR{beta} axis negatively regulates developmental brown adipogenesis, and its repression promotes brown adipose tissue expansion and improves metabolic health. HighlightsO_LIPDGFR{beta}+ pericytes act as an essential developmental brown APC. C_LIO_LITBX18+ pericytes contribute to brown adipogenesis in a depot-specific manner. C_LIO_LIInhibiting Notch-Pdgfr{beta} axis promotes brown APC adipogenesis. C_LIO_LIEnhanced postnatal brown adipogenesis improves metabolic health in adult stage. C_LI

developmental biology↗

bioRxiv2023

Neural Mechanisms of Sequential Dependence in Time Perception: The Impact of Prior Task and Memory Processing

Our perception and decision-making are susceptible to prior context. Such sequential dependence has been extensively studied in the visual domain, but less is known about its impact on time perception. Moreover, there are ongoing debates about whether these sequential biases occur at the perceptual stage or during subsequent post-perceptual processing. Using functional Magnetic Resonance Imaging (fMRI), we investigated neural mechanisms underlying temporal sequential dependence and the role of action in time judgments across trials. Participants performed a timing task where they had to remember the duration of green coherent motion and were cued to either actively reproduce its duration or simply view it passively. We found that sequential biases in time perception were only evident when the preceding task involved active duration reproduction. Merely encoding a prior duration without reproduction failed to induce such biases. Neurally, we observed activation in networks associated with timing, such as striato-thalamo-cortical circuits, and performance monitoring networks, particularly when a "Response" trial was anticipated. Importantly, the hippocampus showed sensitivity to these sequential biases, and its activation negatively correlated with the individuals sequential bias following active reproduction trials. These findings highlight the significant role of memory networks in shaping time-related sequential biases at the post-perceptual stages. Significance StatementOur study explores the neural mechanisms of sequential dependence in time perception and reveals that active reproduction of time duration in the previous trial can bias subsequent estimates, resulting in a sequential dependence effect. In contrast, passive viewing of a stimulus without reproducing its duration does not produce this effect. At the neural level, we observed increased activity in memory regions like the hippocampus when sequential biases were reduced. Furthermore, we found a negative correlation between hippocampal activation and sequential bias following active reproduction trials, suggesting that the involvement of memory networks mediates how we are influenced by past experiences when judging time.

neuroscience↗

bioRxiv2023

Overexpression of the violaxanthin de-epoxidase confers faster NPQ and photosynthesis induction in rice

Plants in the field experience fluctuations in light conditions. Plants with swift responses to dynamic light conditions usually gain competitive advantage in the field. The dynamic photosynthesis can be reflected in dynamic changes in almost all processes in photosynthesis, with dominant factors being dynamic changes in non-photochemical quenching, Rubisco activation and stomatal dynamics. Each of these dynamic responses is controlled by defined mechanisms. In this study, we showed that overexpression of VDE, an enzyme involved in the xanthophyll cycle and non-photochemical quenching, in rice resulted in faster NPQ induction, less photoinhibition, and faster photosynthesis induction, which together caused increased biomass production by about 11[~]16%. This study, demonstrating a previously unnoticed role of VDE in altering the dynamics of photosynthesis induction besides decreasing photoinhibition, offers a potential strategy to improve canopy photosynthesis through capitalizing the ability of plants to use dynamic light. HighlightThe overexpression of VDE in rice resulted in faster NPQ induction, less photoinhibition, and faster photosynthesis induction, which together caused increased biomass in field.

plant biology↗

bioRxiv2023

Conversion of monoclonal IgG to dimeric and secretory IgA restores neutralizing ability and prevents infection of Omicron lineages

The emergence of Omicron lineages and descendent subvariants continues to present a severe threat to the effectiveness of vaccines and therapeutic antibodies. We have previously suggested that an insufficient mucosal IgA response induced by the mRNA vaccines is associated with a surge in breakthrough infections. Here, we further show that the intramuscular mRNA and/or inactivated vaccines cannot sufficiently boost the mucosal sIgA response in uninfected individuals, particularly against the Omicron variant. We thus engineered and characterized recombinant monomeric, dimeric and secretory IgA1 antibodies derived from four neutralizing IgG monoclonal antibodies targeting the receptor-binding domain of the spike protein (01A05, rmAb23, DXP-604 and XG014). Compared to their parental IgG antibodies, dimeric and secretory IgA1 antibodies showed a higher neutralizing activity against different variants of concern (VOCs), in part due to an increased avidity. Importantly, the dimeric or secretory IgA1 form of the DXP-604 antibody significantly outperformed its parental IgG antibody, and neutralized the Omicron lineages BA.1, BA.2 and BA.4/5 with a 50-150-fold increase in potency, reaching the level of the most potent monoclonal antibodies described till date. In hACE2 transgenic mice, a single intranasal dose of the dimeric IgA DXP-604 conferred prophylactic and therapeutic protection against Omicron BA.5. Conversion of IgA and dimerization further enhanced or restored the neutralizing ability against the emerging Omicron sub-variants (DXP-604 for BQ.1, BQ.1.1 and BA2.75; 01A05 for BA2.75, BA.2.75.2 and XBB.1). Thus, dimeric or secretory IgA delivered by nasal administration may potentially be exploited for the treatment and prevention of Omicron infection, thereby providing an alternative tool for combating immune evasion by subvariants and, potentially, future VOCs. One Sentence SummaryEngineered dimeric and secretory IgA1 neutralized Omicron variant with higher potency than parental IgG.

microbiology↗

bioRxiv2023

Electrophysiological signatures of temporal context in the bisection task

Despite relatively accurate time judgment, subjective time is susceptible to various contexts, such as sample spacing and frequency. Several electroencephalographic (EEG) components have been linked to timing, including the contingent negative variation (CNV), offset P2, and late positive component of timing (LPCt). However, the specific role of these components in the contextual modulation of perceived time remains unclear. In this study, we conducted two temporal bisection experiments, where participants had to judge if a test duration was close to a short or long standard. Unbeknownst to participants, the sample spacing (Experiment 1) and frequency (Experiment 2) were altered to create short and long contexts while keeping the test range and standards the same in different sessions. The results showed that the bisection threshold shifted toward the ensemble mean and that CNV and LPCt were sensitive to context modulation. Compared to the long context, the CNV climbing rate increased in the short context, and the amplitude and latency of the LPCt were reduced. These findings suggest the CNV represents an expectancy wave for upcoming decision-making, while LPCt reflects the decision-making process, both influenced by the temporal context.

neuroscience↗

bioRxiv2023

Isolation of ACE2-dependent and -independent sarbecoviruses from Chinese horseshoe bats

While the spike proteins from SARS-CoV and SARS-CoV-2 bind to host ACE2 to infect cells, the majority of bat sarbecoviruses cannot use ACE2 from any species. Despite their discovery almost 20 years ago, ACE2-independent sarbecoviruses have never been isolated from field samples, leading to the assumption these viruses pose little risk to humans. We have previously shown how spike proteins from a small group of ACE2-independent bat sarbecoviruses may possess the ability to infect human cells in the presence of exogenous trypsin. Here, we adapted our earlier findings into a virus isolation protocol, and recovered two new ACE2-dependent viruses, RsYN2012 and RsYN2016, as well as an ACE2-independent virus, RsHuB2019. Although our stocks of RsHuB2019 rapidly acquired a tissue-culture adaption that rendered the spike protein resistant to trypsin, trypsin was still required for viral entry, suggesting limitations on the exogenous entry factors that support bat sarbecoviruses. Electron microscopy revealed ACE2-independent sarbecoviruses have a prominent spike corona and share similar morphology to other coronaviruses. Our findings demonstrate a broader zoonotic threat posed by sarbecoviruses and shed light onto the intricacies of coronavirus isolation and propagation in vitro. SIGNIFICANCESeveral coronaviruses have transmitted from animals to people and 20 years of virus discovery studies have uncovered thousands of new coronavirus sequences in nature. Most of the animal-derived sarbecoviruses have never been isolated in culture due to cell incompatibilities and a poor understanding of the in vitro requirements for their propagation. Here, we built on our growing body of work characterizing viral entry mechanisms of bat sarbecoviruses in human cells and have developed a virus isolation protocol that allows for exploration of these understudied viruses. Our protocol is robust and practical, leading to successful isolation of more sarbecoviruses than previous approaches and from field samples that had been collected over a 10-year longitudinal study.

microbiology↗