Biology subjects

Fu, Y.

Publications and source records attributed to Fu, Y..

At least 217 records · Page 12Linked to original sources

bioRxiv2023

Does the territorial behaviour of the Amur tiger affect the accuracy of occupancy estimation?

1. Accurate estimates of wildlife distributions and population persistence are essential for conservation programs. Occupancy models that account for detection probability have been used to characterize the occupancy and habitat selection of imperilled species. However, failure to distinguish between true-presence and pseudo-presence associated with territorial behaviour can result in the overestimation of the occupancy probability of target species in unsuitable habitats, and this can have major implications for the development of conservation strategies. 2. For highly territorial wildlife species requiring high-quality habitat for survival, occasional Presence in unsuitable areas might be related to dispersal or migration, but this does not reflect actual occupancy and habitat use. True-Presence and Pseudo-Presence should be distinguished for target species to better reflect their actual occupancy and habitat use. 3. To investigate the effect of True-Presence and Pseudo-Presence on wildlife occupancy estimation, we developed a modified model (Mm) that considers the territorial behaviour of the Amur tiger in northeast China, which distinguished between True-Presence and Pseudo-Presence. We compared two models, Mm and M0 (conventional occupancy model), and assessed model performance using goodness-of-fit evaluation, detection and occupancy probability, and favourable variable selection. 4. We found that Mm, which has fewer favourable variables, is more powerful than M0 for estimating detection and occupancy probability, as well as characterizing the effect of various factors on the habitat use of Amur tigers. Furthermore, Mm significantly reduced the overestimation of occupancy probability outside the home range compared with M0, and detection probability estimates did not significantly differ between M0 and Mm. Finally, Mm provided more empirical habitat selection variables for the Amur tiger. 5. Our results revealed how True-Presence and Pseudo-Presence affect the occupancy probability and habitat selection of Amur tigers. Our method improves the accuracy of occupancy models; it can also be used to characterize the habitat selection and distribution of wildlife species and be applied to other territorial species.

ecology↗

bioRxiv2023

Bromodomain-containing Protein 4 Regulates Innate Inflammation in Airway Epithelial Cells via Modulation of Alternative Splicing

Bromodomain-containing Protein 4 (BRD4) is a transcriptional regulator which coordinates gene expression programs controlling cancer biology, inflammation, and fibrosis. In airway viral infection, non-toxic BRD4-specific inhibitors (BRD4i) block the release of pro-inflammatory cytokines and prevent downstream remodeling. Although the chromatin modifying functions of BRD4 in inducible gene expression have been extensively investigated, its roles in post-transcriptional regulation are not as well understood. Based on its interaction with the transcriptional elongation complex and spliceosome, we hypothesize that BRD4 is a functional regulator of mRNA processing. To address this question, we combine data-independent analysis - parallel accumulation-serial fragmentation (diaPASEF) with RNA-sequencing to achieve deep and integrated coverage of the proteomic and transcriptomic landscapes of human small airway epithelial cells exposed to viral challenge and treated with BRD4i. The transcript-level data was further interrogated for alternative splicing analysis, and the resulting data sets were correlated to identify pathways subject to post-transcriptional regulation. We discover that BRD4 regulates alternative splicing of key genes, including Interferon-related Developmental Regulator 1 (IFRD1) and X-Box Binding Protein 1 (XBP1), related to the innate immune response and the unfolded protein response, respectively. These findings extend the transcriptional elongation-facilitating actions of BRD4 in control of post-transcriptional RNA processing in innate signaling.

systems biology↗

bioRxiv2023

Reconstruction of 3-dimensional tissue organization at the single-cell resolution

Recent advances in spatial transcriptomics (ST) have allowed for the mapping of tissue heterogeneity, but this technique lacks the resolution to investigate gene expression patterns, cell-cell communications and tissue organization at the single-cell resolution. ST data contains a mixed transcriptome from multiple heterogeneous cells, and current methods predict two-dimensional (2D) coordinates for individual cells within a predetermined space, making it difficult to reconstruct and study three-dimensional (3D) tissue organization. Here we present a new computational method called scHolography that uses deep learning to map single-cell transcriptome data to 3D space. Unlike existing methods, which generate a projection between transcriptome data and 2D spatial coordinates, scHolography uses neural networks to create a high-dimensional transcriptome-to-space map that preserves the distance information between cells, allowing for the construction of a cell-cell proximity matrix beyond the 2D ST scaffold. Furthermore, the neighboring cell profile of a given cell type can be extracted to study spatial cell heterogeneity. We apply scHolography to human skin, human skin cancer and mouse brain datasets, providing new insights into gene expression patterns, cell-cell interactions and spatial microenvironment. Together, scHolography offers a computational solution for digitizing transcriptome and spatial information into high-dimensional data for neural network-based mapping and the reconstruction of 3D tissue organization at the single-cell resolution.

bioinformatics↗

bioRxiv2022

MicroRNA-205 promotes hair regeneration by modulating mechanical properties of hair follicle stem cells

Stiffness and actomyosin contractility are intrinsic mechanical properties of animal cells required for the shaping of tissues. However, whether tissue stem cells (SCs) and progenitors located within SC niche have different mechanical properties that govern their size and functions remains unclear. We show that hair follicle SCs in the bulge are stiff with high actomyosin contractility and resistant to size change, whereas hair germ (HG) progenitors are soft and periodically enlarge and contract during quiescence. During activation, HGs reduce contraction and more frequently enlarge, a process that is associated with weakening of the actomyosin network, nuclear YAP accumulation and cell cycle re-entry. Induction of miR-205, a novel regulator of the actomyosin cytoskeleton, reduces actin contractility, decreases the stiffness of the bulge and HG, and activates hair regeneration in young and old mice. This study reveals the control of tissue SC size and activities by spatiotemporally compartmentalized mechanical properties and demonstrates the possibility to stimulate tissue regeneration by fine-tuning cell mechanics.

genetics↗

bioRxiv2022

The arms race in noncoding regions of transposable element: the evolution of anti-silencing and RNAi

Transposable elements (TEs) are among the most dynamic parts of genomes. Since TEs are potentially deleterious, eukaryotes silence them through epigenetic mechanisms such as DNA methylation and RNAi. We have previously reported that Arabidopsis TEs, called VANDALs, counteract epigenetic silencing through a group of sequence-specific anti-silencing proteins, VANCs. VANC proteins bind to noncoding regions of specific VANDAL copies and induce a loss of silent chromatin marks. Sequence-specific anti-silencing allows these TEs to proliferate with minimum host damage. Here, we show that RNAi efficiently targets noncoding regions of VANDAL TEs to silence them de novo. Target motifs of VANC, in turn, evolved to escape RNAi. Escaping RNAi could be the primary event leading to the differentiation of sequence-specific anti-silencing systems. We propose that this selfish behaviour of TEs paradoxically could make them less harmful to the host.

genetics↗

bioRxiv2022

Open-3DSIM: an Open-source three-dimensional structured illumination microscopy reconstruction platform

With optical section and defocus removal effect, three-dimensional structured illumination microscopy (3DSIM) can get a whole sight of intracellular organelle. Here, Open-3DSIM is reported as an open-source reconstruction platform with double improvement on lateral and axial resolution. MATLAB code, ImageJ version and Exe application are provided for biologists and engineers to maximize its user-friendliness and prompt its further development. Through adaptive parameter estimation and spectrum filter optimization, we demonstrate its superior performance of artifact suppression and defocus elimination over other algorithms on various specimens, under gradient signal-to-noise levels. Moreover, with the capacity to extract the dipole orientation, Open-3DSIM paves a new avenue for interpreting the subcellular structures in six dimensions (xyz{theta}{lambda}t).

bioengineering↗

bioRxiv2022

Integrating deep mutational scanning and low-throughput mutagenesis data to predict the impact of amino acid variants

Evaluating the impact of amino acid variants has been a critical challenge for studying protein function and interpreting genomic data. High-throughput experimental methods like deep mutational scanning (DMS) can measure the effect of large numbers of variants in a target protein, but because DMS studies have not been performed on all proteins, researchers also model DMS data computationally to estimate variant impacts by predictors. In this study, we extended a linear regression-based predictor to explore whether incorporating data from alanine scanning (AS), a widely-used low-throughput mutagenesis method, would improve prediction results. To evaluate our model, we collected 146 AS datasets, mapping to 54 DMS datasets across 22 distinct proteins. We show that improved model performance depends on the compatibility of the DMS and AS assays, and the scale of improvement is closely related to the correlation between DMS and AS results.

bioinformatics↗

bioRxiv2022

Progressive loss of conserved spike protein neutralizing antibody sites in Omicron sublineages is balanced by preserved T-cell recognition epitopes

The continued evolution of the SARS-CoV-2 Omicron variant has led to the emergence of numerous sublineages with different patterns of evasion from neutralizing antibodies. We investigated neutralizing activity in immune sera from individuals vaccinated with SARS-CoV-2 wild-type spike (S) glycoprotein-based COVID-19 mRNA vaccines after subsequent breakthrough infection with Omicron BA.1, BA.2, or BA.4/BA.5 to study antibody responses against sublineages of high relevance. We report that exposure of vaccinated individuals to infections with Omicron sublineages, and especially with BA.4/BA.5, results in a boost of Omicron BA.4.6, BF.7, BQ.1.1, and BA.2.75 neutralization, but does not efficiently boost neutralization of sublineages BA.2.75.2 and XBB. Accordingly, we found in in silico analyses that with occurrence of the Omicron lineage a large portion of neutralizing B-cell epitopes were lost, and that in Omicron BA.2.75.2 and XBB less than 12% of the wild-type strain epitopes are conserved. In contrast, HLA class I and class II presented T-cell epitopes in the S glycoprotein were highly conserved across the entire evolution of SARS-CoV-2 including Alpha, Beta, and Delta and Omicron sublineages, suggesting that CD8+ and CD4+ T-cell recognition of Omicron BQ.1.1, BA.2.75.2, and XBB may be largely intact. Our study suggests that while some Omicron sublineages effectively evade B-cell immunity by altering neutralizing antibody epitopes, S protein-specific T-cell immunity, due to the very nature of the polymorphic cell-mediated immune, response is likely to remain unimpacted and may continue to contribute to prevention or limitation of severe COVID-19 manifestation.

immunology↗

bioRxiv2022

The more synthetic polymer types pollute the soil, the stronger the growth suppression of invasive alien and native plants

Although most studies on the ecological effects of microplastic pollution focus on a single type of synthetic polymer and a single species, most organisms will be exposed to multiple polymer types simultaneously and the effects may vary among species. To test the effects of polymer diversity on plants, we grew single plants of eight invasive and eight native species in pots with substrate polluted by 0, 1, 3 and 6 types of micro-sized synthetic polymers. We found that the growth suppression by microplastic pollution became stronger with the number of polymer types the plants were exposed to. This tended to be particularly the case for invasive species, whose biomass advantage over natives diminished with the number of polymer types. Our study thus shows that the negative effects of microplastic pollution on plant growth increase with the number of polymer types, and that these effects differ between invasive and native species.

ecology↗

bioRxiv2022

Integrated proteomics reveals the landscape of autophagy degradation in human neurons and autophagy receptors regulating neuronal activity

Autophagy is a catabolic and self-degradative process crucial for maintaining cellular homeostasis. Malfunctional autophagy is implicated in neurodevelopmental and neurodegenerative diseases. However, the exact role and targets of autophagy in human neurons remain elusive. Here we reported a systematic investigation of neuronal autophagy targets through integrated proteomics. Deep proteomic profiling of multiple autophagy-deficient lines of human induced neurons, mouse brains, and LC3-interactome uncovers a role of neuronal autophagy in targeting primarily endoplasmic reticulum (ER), mitochondria, endosome, Golgi apparatus, synaptic vesicle (SV) proteins, and cAMP-PKA pathway, for degradation. Tubular ER and specific SV proteins are significant autophagy cargos in the axons. Functional validation identified calumenin as an ER resident autophagy receptor and illuminated a role of autophagy in regulating PKA and neuronal activity through AKAP11-mediated degradation. Our study thus reveals the landscape of autophagy degradation in human neurons and offers molecular insight into mechanisms of neurological disorders linked to autophagy deficiency. HighlightO_LIIntegrated proteomics reveals the landscape of autophagy degradation in human neurons C_LIO_LIAutophagy clears tubular ER and selective ER and synaptic vesicle proteins in neurons C_LIO_LICalumenin is an ER resident autophagy receptor C_LIO_LIAutophagy controls PKA pathway and neuronal activity through autophagy receptor AKAP11 C_LI

neuroscience↗

bioRxiv2022

Peptide-MHC Structure Prediction With Mixed Residue and Atom Graph Neural Network

Neoantigen-targeting vaccines have achieved breakthrough success in cancer immunotherapy by eliciting immune responses against neoantigens, which are proteins uniquely produced by cancer cells. During the immune response, the interactions between peptides and major histocompatibility complexes (MHC) play an important role as peptides must be bound and presented by MHC to be recognised by the immune system. However, only limited experimentally determined peptide-MHC (pMHC) structures are available, and in-silico structure modelling is therefore used for studying their interactions. Current approaches mainly use Monte Carlo sampling and energy minimisation, and are often computationally expensive. On the other hand, the advent of large high-quality proteomic data sets has led to an unprecedented opportunity for deep learning-based methods with pMHC structure prediction becoming feasible with these trained protein folding models. In this work, we present a graph neural network-based model for pMHC structure prediction, which takes an amino acid-level pMHC graph and an atomic-level peptide graph as inputs and predicts the peptide backbone conformation. With a novel weighted reconstruction loss, the trained model achieved a similar accuracy to AlphaFold 2, requiring only 1.7M learnable parameters compared to 93M, representing a more than 98% reduction in the number of required parameters.

bioinformatics↗

bioRxiv2022

Population structure and genetic diversity of Salmonella Typhimurium in avian hosts

Within-host evolution of bacterial pathogens can lead to host-associated variants of the same species or serovar. Identification and characterization of closely related variants from diverse host species are crucial to public health and host-pathogen adaptation research. However, the work remained largely underexplored at a strain level until the advent of whole-genome sequencing (WGS). Here, we performed WGS-based subtyping and analyses of Salmonella enterica serovar Typhimurium (n = 787) from different wild birds across 18 countries over a 75-year period. We revealed seven avian host-associated S. Typhimurium variants/lineages. These lineages emerged globally over short timescales and presented genetic features distinct from S. Typhimurium lineages circulating among humans and domestic animals. We further showed that, in terms of virulence, host adaptation of these variants was driven by genome degradation. Our results provide a snapshot of the population structure and genetic diversity of S. Typhimurium within avian hosts. We also demonstrate the value of WGS-based subtyping and analyses in unravelling closely related variants at the strain level.

microbiology↗

bioRxiv2022

Rapid iPSC inclusionopathy models shed light on formation, consequence and molecular subtype of alpha-synuclein inclusions

Intracellular inclusions accompanying neurodegeneration are histopathologically and ultrastructurally heterogeneous but the significance of this heterogeneity is unclear. iPSC models, while promising for disease modeling, do not form inclusions in a reasonable timeframe and suffer from limited tractability. Here, we developed an iPSC toolbox utilizing piggyBac-based or targeted transgenes to rapidly induce CNS cells with concomitant expression of aggregation-prone proteins. This system is amenable to screening and longitudinal tracking at single-cell and single-inclusion resolution. For proof-of-principle, cortical neuron -synuclein "inclusionopathy" models were engineered to form inclusions through exogenous seeding or -synuclein mutation. These models recapitulated known fibril- and lipid-rich inclusion subtypes, uncovering dynamic interactions between them, and refined the classification of inclusions in postmortem brain. Genetic-modifier and protein-interaction screens pinpointed proteins like RhoA whose sequestration into specific inclusion subtypes is likely to be toxic. This iPSC platform should enhance our understanding of proteinaceous pathologies in neurodegeneration and facilitate therapeutics development.

neuroscience↗

bioRxiv2022

Site of vulnerability on SARS-CoV-2 spike induces broadly protective antibody to antigenically distinct omicron SARS-CoV-2 subvariants

The rapid evolution of SARS-CoV-2 Omicron variants has emphasized the need to identify antibodies with broad neutralizing capabilities to inform future monoclonal therapies and vaccination strategies. Herein, we identify S728-1157, a broadly neutralizing antibody (bnAb) targeting the receptor-binding site (RBS) and derived from an individual previously infected with SARS-CoV-2 prior to the spread of variants of concern (VOCs). S728-1157 demonstrates broad cross-neutralization of all dominant variants including D614G, Beta, Delta, Kappa, Mu, and Omicron (BA.1/BA.2/BA.2.75/BA.4/BA.5/BL.1). Furthermore, it protected hamsters against in vivo challenges with wildtype, Delta, and BA.1 viruses. Structural analysis reveals that this antibody targets a class 1 epitope via multiple hydrophobic and polar interactions with its CDR-H3, in addition to common class 1 motifs in CDR-H1/CDR-H2. Importantly, this epitope is more readily accessible in the open and prefusion state, or in the hexaproline (6P)-stabilized spike constructs, as compared to diproline (2P) constructs. Overall, S728-1157 demonstrates broad therapeutic potential, and may inform target-driven vaccine design against future SARS-CoV-2 variants.

immunology↗

bioRxiv2022

The protist ubiquitin ligase effector PbE3-2 targets RD21A to impede plant immunity

Clubroot caused by the soil-borne protist pathogen Plasmodiophora brassicae is one of the most devastating diseases of Brassica oil and vegetable crops worldwide. Understanding the pathogen infection strategy is crucial for the development of disease control. However, the molecular mechanism by which this pathogen promotes infection remains largely unknown. Here, we identified a P. brassicae-secreted effector PbE3-2 that impedes plant immunity by ubiquitinating the immune regulator RD21A for degradation. Overexpression of PbE3-2 in Arabidopsis thaliana resulted in higher susceptibility to P. brassicae and decreases in chitin-triggered reactive oxygen species burst and expression of marker genes in salicylic acid signaling. PbE3-2 interacted with and ubiquitinated RD21A in vitro and in vivo. Mutant plants deficient in RD21A exhibited similar susceptibility and compromsied immune responses as in PbE3-2 overexpression plants. These results suggest that P. brassicae promotes clubroot disease through RD21A degradation mediated by the effector PbE3-2. As PbE3-2 is widely conserved across different P. brassicae pathotypes, the degradation of RD21A by PbE3-2 might be a prevalent infection strategy in this pathogen.

microbiology↗

bioRxiv2022

mtDNA breaks compromise mitochondrial membrane ultrastructure and trigger an integrated stress response

Double-strand breaks in mitochondrial DNA (mtDSBs) lead to the degradation of the circular genomes and a reduction in copy number. However, it is unclear how mtDSBs are sensed and what signaling pathways are activated in response to mtDNA damage. In this study, we used mitochondrial-targeted restriction enzymes to investigate the cellular response to mtDSBs. Our results showed that a subset of cells with mtDSBs exhibited defects in mitochondrial protein import, reduced respiratory complexes, and loss of membrane potential. Electron microscopy revealed compromised mitochondrial membrane and cristae ultrastructure. We also found that mtDSBs activated the integrated stress response (ISR) through the phosphorylation of eIF2 by DELE1 and HRI. Notably, inhibition of the ISR exacerbated the mitochondrial import defect and delayed the recovery of mtDNA copy number following break formation. These findings suggest that the ISR plays a role in mitigating mitochondrial dysfunction following mtDNA damage and is critical to promoting mtDNA repopulation. Last, we used proteomics to survey the proteins present in the nucleoids shortly after mtDSBs and identified ATAD3A, a membrane-anchored protein interacting with nucleoids, as a potential factor in transmitting the signal from damaged genomes to the inner mitochondrial membrane. In summary, our study reveals the sequence of events linking damaged mitochondrial genomes with the cytoplasm and highlights the unexpected role of the ISR in reestablishing homeostasis in response to mitochondrial genome instability.

cell biology↗

bioRxiv2022

Hybrid Synthesis of bioplastics polyhydroxybutyrate from carbon dioxide

The accelerating environmental crisis has intensified the demand for switching from traditional economy to a renewable one with a reduced carbon footprint. Here we reported a hybrid system, coupling chemical process of CO2 hydrogen reduction and biological process for polyhydroxybutyrate (PHB) synthesis, that utilized CO2 as a raw material to produce PHB in vitro. The synthetic pathway of PHB was optimized by screening more efficient methanol oxidases, high activity mutants of glycolaldehyde synthase and coordinating enzyme dosages in the pathway, which achieved the carbon yield of 93.6% for producing PHB from methanol. Finally, by combining with the chemical process from CO2 to methanol, a scaling-up bio-system was performed to convert CO2 into PHB, yielding 5.8 g/L with the productivity of 1.06 g-1L-1h-1. This approach represents a promising carbon-neutral way to produce biodegradable plastics.

synthetic biology↗

bioRxiv2022

DeepDetect: deep learning of peptide detectability enhanced by peptide digestibility

In tandem mass spectrometry-based proteomics, proteins are digested by specific protease(s) into peptides, but generally only a fraction of theoretical peptides can be detected. To explore the characteristics of proteotypic peptides, we have developed a series of methods for peptide digestibility and detectability prediction, and this is the latest one of them. Specifically, we propose here a bidirectional long short-term memory (BiLSTM)-based algorithm, named DeepDetect, for the prediction of peptide detectability enhanced by peptide digestibility. Compared with existing algorithms, DeepDetect is featured by its improved accuracy of prediction and wide applicability to commonly used proteases covering Trypsin, ArgC, Chymotrypsin, GluC, LysC, AspN, LysN, and LysargiNase. On eleven independent test data sets, DeepDetect achieved AUCs of 0.858~0.957, superior to the state-of-the-art algorithms, AP3 and PepFormer, which either used conventional machine learning methods or disregarded the digestibility feature. As an application, the predicted peptide detectability was utilized to re-rank and validate the peptide-spectrum matches, and showed the potential to promote the sensitivity of peptide identification.

bioinformatics↗