Biology subjects

Yu, T.

Publications and source records attributed to Yu, T..

At least 91 records · Page 5Linked to original sources

bioRxiv2022

13C ENDOR Spectroscopy-Guided MD Computations Reveals the Structure of the Enzyme-Substrate Complex of an Active, N-linked Glycosylated Lipoxygenase

Lipoxygenases (LOXs) are enzymes responsible for producing important cell signaling mediators and have been extensively studied for their potential clinical relevance as well as to advance our understanding of enzyme catalysis. The common inability to capture and characterize LOX-substrate complexes by Xray co-crystallography requires the development of alternative structural methods. We previously reported the integration of 13C/1H electron nuclear double resonance (ENDOR) spectroscopy and molecular dynamics (MD) to visualize the complex structure of the paradigmatic LOX from soybean, SLO, with substrate linoleic acid (LA). However, this required substitution of the catalytic mononuclear, nonheme iron by the structurally faithful, yet inactive Mn2+ ion as a spin-probe. Unlike canonical Fe-LOXs from plants and animals, LOXs from pathogenic fungi contain active mononuclear manganese metallocentres. Here, we report the ground-state active-site structure of the native, fully glycosylated fungal LOX from M. oryzae, MoLOX complexed with LA obtained through the 13C/1H ENDOR-guided MD approach. The Mn-oxygen-to-LA donor carbon distance (DAD) for MoLOX-LA, 3.4 {+/-} 0.3 [A], matches the distance in the single representative X-ray co-structure of an animal 8R-LOX with its natural fatty acid substrate, and slightly elongated from that of the SLO-LA complex, 3.1 {+/-} 0.2 [A], despite its carboxylate-out substrate binding orientation versus carboxylate-in for SLO. The results provide unique insight into the evolutionary divergence of the ground-state DAD in the LOX family, which influences the activation barrier for hydrogen tunneling, and give a structural basis for guiding development of MoLOX inhibitors. The work highlights the robustness of ENDOR-guided MD approach to describe LOX-substrate structures that elude conventional X-ray techniques.

biochemistry↗

bioRxiv2022

Taxonomic and carbon metabolic diversification of Bathyarchaeia during its co-evolution history with the early Earth surface environment

Bathyarchaeia, as one of the most abundant microorganisms on Earth, play vital roles in the global carbon cycle. However, our understanding of their origin, evolution and ecological functions remains poorly constrained. Based on the phylogeny of the present largest dataset of Bathyarchaeia metagenome assembled genome (MAG), we reclassified Bathyarchaeia into eight order-level units and corresponded to the former subgroup system. Highly diversified and versatile carbon metabolisms were discovered among different orders, particularly atypical C1 metabolic pathways, indicating that Bathyarchaeia represent overlooked important methylotrophs. Molecular dating results indicate that Bathyarchaeia diverged at [~]3.3 Ga, followed by three major diversifications at [~]3.0 Ga, [~]2.5 Ga and [~]1.8-1.7 Ga, likely driven by continental emergence, growth and intensive submarine volcanism, respectively. The lignin-degrading Bathyarchaeia clade emerged at [~]300 Ma and perhaps contributed to the sharply decreased carbon sequestration rate during the Late Carboniferous period. The evolutionary pathway of Bathyarchaeia potentially have been shaped by geological forces, which in turn impacted the Earths surface environment. TeaserThe origin and divergence of Bathyarchaeia linked to the early Earth tectonics and surface environment changes

microbiology↗

bioRxiv2022

Cultivation of widespread Bathyarchaeia reveals a novel methyltransferase system utilizing lignin-derived aromatics

Anaerobic lignin degradation is a major process in the global carbon cycle that would significantly influence estimates of carbon flux in both terrestrial and marine ecosystems. The ubiquitous Bathyarchaeia, one of the most abundant taxa in marine sediments, have been proposed to be key players in this process. However, the mechanism of Bathyarchaeial lignin degradation is unclear due to the lack of cultured strains. Here we report the cultivation of Candidatus Marisediminiarchaeum ligniniphilus DL1YTT001, a Bathyarchaeial representative from nearshore marine sediments that can grow with lignin as the sole organic carbon source under mesophilic and anaerobic conditions. Strain DL1YTT001 possesses and highly expresses a novel and specific methyltransferase system for O-demethylation of lignin-derived methoxylated aromatic compounds (ArOCH3). The key gene, methyltransferase 1 (MtgB), is not homologous to any other lineages. Enzymatic activity was confirmed through the heterologous expression of the MtgB gene, showing O-demethylation activity with guaiacol as the substrate. Considering that Bathyarchaeial lineages carrying this specific methyltransferase system are widely distributed in diverse anoxic environments, especially lignin-rich nearshore sediments, Bathyarchaeia-mediated O-demethylation is likely a key step in global anaerobic lignin remineralization.

microbiology↗

bioRxiv2022

SynBOLD-DisCo: Synthetic BOLD images for distortion correction of fMRI without additional calibration scans

The blood oxygen level dependent (BOLD) signal from functional magnetic resonance imaging (fMRI) is a noninvasive technique that has been widely used in research to study brain function. However, fMRI suffers from susceptibility-induced off resonance fields which may cause geometric distortions and mismatches with anatomical images. State-of-the-art correction methods require acquiring reverse phase encoded images or additional field maps to enable distortion correction. However, not all imaging protocols include these additional scans and thus cannot take advantage of these susceptibility correction capabilities. As such, in this study we aim to enable state-of-the-art distortion correction with FSLs topup algorithm of historical and/or limited fMRI data that include only a structural image and single phase encoded fMRI. To do this, we use 3D U-net models to synthesize undistorted fMRI BOLD contrast images from the structural image and use this undistorted synthetic image as an anatomical target for distortion correction with topup. We evaluate the efficacy of this approach, named SynBOLD-DisCo (synthetic BOLD images for distortion correction), and show that BOLD images corrected using our approach are geometrically more similar to structural images than the distorted BOLD data and are practically equivalent to state-of-the-art correction methods which require reverse phase encoded data. Future directions include additional validation studies, integration with other preprocessing operations, retraining with broader pathologies, and investigating the effects of spin echo versus gradient echo images for training and distortion correction. In summary, we demonstrate SynBOLD-DisCo corrects distortion of fMRI when reverse phase encoding scans or field maps are not available.

bioengineering↗

bioRxiv2022

Tree and shrub richness modify subtropical tree productivity by modulating the diversity and community composition of soil bacteria and archaea

BackgroundDeclines in plant biodiversity often have negative consequences for plant community productivity, and it becomes increasingly acknowledged that this may be driven by shifts in soil microbial community composition. These relationships have been well-established in grasslands, and few studies also indicate that fungi play a role in driving tree diversity-productivity relationships in forests. However, the role of bacteria and archaea, which are also highly abundant in forest soils and perform pivotal ecosystem functions, has been largely overlooked. Here, we investigated how tree and shrub richness affects stand-level tree productivity via modulating bacterial and archaeal community diversity and composition. We used a landscape-scale, subtropical tree biodiversity experiment (BEF-China) where tree (1, 2 or 4 species) and shrub richness (0, 2, 4, 8 species) were modified. ResultsOur results showed that tree and shrub species richness affected bacterial diversity, community composition, and co-occurrence networks, but such effects were marginal for archaea. Both tree and shrub species richness increased stand-level tree productivity by modulating soil microbial community composition, with the effects being mediated via increases in soil C:N ratios. ConclusionsOur findings imply the importance of bacterial and archaeal communities in driving the relationship between plant diversity and productivity in subtropical forests and highlight that we may require better a understanding of prokaryotic communities in forest soils.

ecology↗

bioRxiv2022

Community assessment of methods to deconvolve cellular composition from bulk gene expression

We evaluate deconvolution methods, which infer levels of immune infiltration from bulk expression of tumor samples, through a community-wide DREAM Challenge. We assess six published and 22 community-contributed methods using in vitro and in silico transcriptional profiles of admixed cancer and healthy immune cells. Several published methods predict most cell types well, though they either were not trained to evaluate all functional CD8+ T cell states or do so with low accuracy. Several community-contributed methods address this gap, including a deep learning-based approach, whose strong performance establishes the applicability of this paradigm to deconvolution. Despite being developed largely using immune cells from healthy tissues, deconvolution methods predict levels of tumor-derived immune cells well. Our admixed and purified transcriptional profiles will be a valuable resource for developing deconvolution methods, including in response to common challenges we observe across methods, such as sensitive identification of functional CD4+ T cell states.

bioinformatics↗

bioRxiv2022

scMinerva: a GCN-featured Interpretable Framework for Single-cell Multi-omics Integration with Random Walk on Heterogeneous Graph

Single-cell multi-omics is a rapidly growing field in biomedicine, where multiple biological contents, such as the epigenome, genome, and transcriptome, can be measured simultaneously. Despite its potential, the integrated analysis and prediction of cellular states based on this complex multi-omics data pose significant challenges due to data sparsity, high noise, and computational overhead. To address these challenges, we developed scMinerva, an unsupervised framework for single-cell multi-omics integrated analysis. The learned embeddings from the multi-omics data enable accurate integrated classification of cell types and stages. Specifically, we construct a heterogeneous graph from multiple omics and propose a novel biased random walk algorithm omics2vec, which can learn the heterogeneous biological graph in a way that balances both local and global network structures. scMinerva successfully outperforms existing unsupervised methods on various simulated and real-world datasets when fine-tuned by very few labels. Additionally, scMinerva demonstrates strong label efficiency, is robust to fluctuation in data quality, allows one omics to compensate for weakness in others and could effectively classify cells with different annotation granularities. Furthermore, we showcase scMinervas ability to accurately provide prospective biomarkers and predict cell differentiation trends for COVID-19-infected cells, through the joint analysis of multi-omics data.

bioinformatics↗

bioRxiv2022

A Neuropsin-based Optogenetic Tool for Precise Control of Gq signaling

Gq-coupled receptors regulate numerous physiological processes by activating enzymes and inducing intracellular Ca2+ signals. There is a strong need for an optogenetic tool that enables powerful experimental control over Gq signaling. Here, we present chicken opsin 5 (cOpn5) as the long sought-after, single-component optogenetic tool that mediates ultra-sensitive optical control of intracellular Gq signaling with high temporal and spatial resolution. Expressing cOpn5 in mammalian cells enables blue light-triggered, Gq-dependent Ca2+ release from intracellular stores and protein kinase C activation. Strong Ca2+ transients were evoked by brief light pulses of merely 10 ms duration and at 3 orders lower light intensity of that for common optogenetic tools. Photostimulation of cOpn5-expressing cells at the subcellular and single-cell levels generated intracellular and intercellular Ca2+ wave propagation, respectively, thus demonstrating the high spatial precision of cOpn5 optogenetics. The cOpn5-mediated optogenetics could also be applied to activate neurons and control animal behavior in a circuit-dependent manner. We further revealed that optogenetic activation of cOpn5-expressing astrocytes induced massive ATP release and modulation neuronal activation in the brain of awake, behaving mice. cOpn5 optogenetics may find broad applications in studying the mechanisms and functional relevance of Gq signaling in both non-excitable cells and excitable cells in all major organ systems.

neuroscience↗

bioRxiv2022

Deep sequencing of yeast and mouse tRNAs and tRNA fragments using OTTR

Among the major classes of RNAs in the cell, tRNAs remain the most difficult to characterize via deep sequencing approaches, as tRNA secondary structure and nucleotide modifications can both interfere with cDNA synthesis by commonly-used reverse transcriptases (RTs). Here, we benchmark a recently-developed RNA cloning protocol, termed Ordered Two-Template Relay (OTTR), to characterize intact tRNAs and tRNA fragments in budding yeast and in mouse tissues. We find that OTTR robustly captures full-length tRNAs in budding yeast and in mouse testis, with relatively low levels of premature termination at known barriers - 1-methylguanine, N2,N2-dimethylguanine, and 1-methyladenine - to typical reverse transcriptases. Moreover, these and several other nucleotide modifications leave misincorporation signatures in OTTR datasets which enables their detection without any additional protocol steps. Turning to analysis of small RNAs such as tRNA cleavage products, we compare OTTR with several standard small RNA-Seq protocols, finding that OTTR provides the most accurate picture of tRNA fragment levels by comparison to "ground truth" Northern blots. Applying this protocol to mature mouse spermatozoa, our data dramatically alter our understanding of the small RNA cargo of mature mammalian sperm, revealing a far more complex population of tRFs - including both 5 and 3 tRNA halves derived from the majority of tRNAs - than previously appreciated. Taken together, our data confirm the superior performance of OTTR to commercial protocols in analysis of tRNA fragments, and force a reappraisal of potential epigenetic functions of the sperm small RNA payload.

genomics↗

bioRxiv2022

conST: an interpretable multi-modal contrastive learning framework for spatial transcriptomics

MotivationSpatially resolved transcriptomics (SRT) shows its impressive power in yielding biological insights into neuroscience, disease study, and even plant biology. However, current methods do not sufficiently explore the expressiveness of the multi-modal SRT data, leaving a large room for improvement of performance. Moreover, the current deep learning based methods lack interpretability due to the "black box" nature, impeding its further applications in the areas that require explanation. ResultsWe propose conST, a powerful and flexible SRT data analysis framework utilizing contrastive learning techniques. conST can learn low-dimensional embeddings by effectively integrating multi-modal SRT data, i.e. gene expression, spatial information, and morphology (if applicable). The learned embeddings can be then used for various downstream tasks, including clustering, trajectory and pseudotime inference, cell-to-cell interaction, etc. Extensive experiments in various datasets have been conducted to demonstrate the effectiveness and robustness of the proposed conST, achieving up to 10% improvement in clustering ARI in the commonly used benchmark dataset. We also show that the learned embedding can be used in complicated scenarios, such as predicting cancer progression by analyzing the tumour microenvironment and cell-to-cell interaction (CCI) of breast cancer. Our framework is interpretable in that it is able to find the correlated spots that support the clustering, which matches the CCI interaction pairs as well, providing more confidence to clinicians when making clinical decisions.

bioinformatics↗

bioRxiv2021

Insights from the IronTract challenge: optimal methods for mapping brain pathways from multi-shell diffusion MRI

Limitations in the accuracy of brain pathways reconstructed by diffusion MRI (dMRI) tractography have received considerable attention. While the technical advances spearheaded by the Human Connectome Project (HCP) led to significant improvements in dMRI data quality, it remains unclear how these data should be analyzed to maximize tractography accuracy. Over a period of two years, we have engaged the dMRI community in the IronTract Challenge, which aims to answer this question by leveraging a unique dataset. Macaque brains that have received both tracer injections and ex vivo dMRI at high spatial and angular resolution allow a comprehensive, quantitative assessment of tractography accuracy on state-of-the-art dMRI acquisition schemes. We find that, when analysis methods are carefully optimized, the HCP scheme can achieve similar accuracy as a more time-consuming, Cartesian-grid scheme. Importantly, we show that simple pre- and post-processing strategies can improve the accuracy and robustness of many tractography methods. Finally, we find that fiber configurations that go beyond crossing (e.g., fanning, branching) are the most challenging for tractography. The IronTract Challenge remains open and we hope that it can serve as a valuable validation tool for both users and developers of dMRI analysis methods.

neuroscience↗

bioRxiv2021

Contrastive Cycle Adversarial Autoencoders for Single-cell Multi-omics Alignment and Integration

We have entered the multi-omics era, and we can measure cells from different aspects. When dealing with such multi-omics data, the first step is to determine the correspondence among different omics. In other words, we should match data from different spaces corresponding to the same object. This problem is particularly challenging in the single-cell multi-omics scenario because such data are very sparse with extremely high dimensions. Secondly, matched single-cell multi-omics data are rare and hard to collect. Furthermore, due to the limitations of the experimental environment, the data are usually highly noisy. To promote the single-cell multi-omics research, we overcome the above challenges, proposing a novel framework to align and integrate single-cell RNA-seq data and single-cell ATAC-seq data. Our approach can efficiently map the above data with high sparsity and noise from different spaces to a low-dimensional manifold in a unified space, making the downstream alignment and integration straightforward. Compared with the other state-of-the-art methods, our method performs better on both simulated and real single-cell data. On the real data, the performance improvement on accuracy over the previous methods is up to 55.7% regarding scRNA-seq and scATAC-seq data integration. Downstream trajectory inference analysis shows that our tool can transfer the labels from scRNA-seq to scATAC-seq with very high accuracy, which indicates our methods effectiveness.

bioinformatics↗

bioRxiv2021

Severe fever with thrombocytopenia syndrome virus and parthenogenetic Asian longhorned tick Haemaphysalis longicornis (Acari: Ixodidae)

Severe fever with thrombocytopenia syndrome virus (SFTSV) is spreading rapidly in Asia. It is transmitted by Haemaphysalis longicornis (Asian longhorned tick, ALT), which has both parthenogenetically and sexually reproducing populations. Parthenogenetic populations were found in at least 15 provinces in China and strongly correlated with the distribution of SFTS. The distribution of SFTS cases was however poorly correlated with the distribution of populations of bisexual ALTs. Phylogeographic analysis suggested that the parthenogenetic population spread much faster than bisexual population because colonization is independent of sexual reproduction. A higher proportion of parthenogenetic ALTs were collected from migratory birds captured at an SFTS endemic area, implicating the contribution to the long-range movement of ALTs in China. The SFTSV susceptibility of parthenogenetic females was like that of bisexual females under laboratory conditions. These results suggest that parthenogenetic ALT, probably transported by migratory birds, play a major role in the rapid spread of SFTSV. Article Summary LineThe parthenogenetic population of Asian longhorned tick is broadly distributed in China and plays a major role in the long-distance spread of SFTSV and perhaps future invasion of countries outside of Asia.

evolutionary biology↗

bioRxiv2021

Solid optical clearing agents based through-Intact-Skull (TIS) window technique for long-term observation of cortical structure and function in mice

In vivo cortical optical imaging needs to overcome the scattering of skull. Compared to the traditional transcranial surgery-based open-skull glass window and thinned-skull preparation, chemical tissue optical clearing techniques can provide a skull-remained optical access to the brain while maintaining its original environment. However, previously demonstrated skull optical clearing windows could only maintain transparency for a couple of hours and hardly capable for high-resolution monitoring of awake animals. Here, we developed a convenient and easy-handling chronic skull optical clearing technique, named "Through-Intact-Skull (TIS) window", which was compatible with long-term observation at high resolution, and yielded large imaging depth of 900 m for cortical neurovascular visualization. In addition, our TIS window could monitor neuron activity in awake mice for a long term. Therefore, our bio-compatible and non-invasive TIS window is a new promising approach for intravital brain microscopy with great potential for basic research in neuroscience.

neuroscience↗

bioRxiv2021

Beneficial Effects of Celastrol on Immune Balance by Modulating Gut Microbiota in Dextran Sodium Sulfate-Induced Ulcerative Colitis

Ulcerative colitis (UC) is a chronic inflammatory bowel disease caused by multi-factors including colonic inflammation and microbiota dysbiosis. Previous studies have indicated that Celastrol (CSR) has strong anti-inflammatory and immune-inhibitory effects. Here, we investigated the effects of CSR on colonic inflammation and the mucosal immunity in an experimental colitis model, and addressed the mechanism by which CSR preforms the protective effect. We characterized the therapeutic effects and the potential mechanism of CSR in treating UC using histological staining, intestinal permeability assay, cytokine assay, flow cytometry, fecal microbiota transplantation (FMT), 16S rRNA sequencing, untargeted metabolomics, and cell differentiation approaches. CSR administration significantly ameliorated DSS-induced colitis, as evidenced by the recovery of body weight and colon length, decreased disease activity index (DAI) score, as well as decreased intestinal permeability. CSR down-regulated the secretion of proinflammatory cytokines, upregulated the anti-inflammatory mediators, and improved the balances of Treg/Th1 and Treg/Th17 to maintain colonic immune homeostasis. However, the protective effects of CSR disappeared when the antibiotic cocktail was applied to deplete the gut microbiota, and the gut microbiota-mediated effect was confirmed by FMT. Furthermore, CSR treatment increased the gut microbiota diversity and composition, and raised the metabolic productions of pyruvate and adenosine, which probably involve in gut microbiota mediated protective effect. In conclusion, CSR ameliorates colonic inflammation in a gut microbiota-dependent manner. The underlying protective mechanism is associated with the rectified Treg/Th1 and Treg/Th17 balance, and increased pyruvate and adenosine production. The study provided the solid evidence that CSR might be a promising therapeutic drug for UC.

microbiology↗

bioRxiv2021

Peptide fusion improves prime editing efficiency

Prime editing enables search-and-replace genome editing but is limited by low editing efficiency. We present a high-throughput approach, PepSEq, to measure how fusion of 12,000 85-amino acid peptides derived from human DNA repair-related proteins influences prime editing efficiency. We show that peptide fusion can enhance prime editing, prime-enhancing peptides combine productively, and a top dual peptide-prime editor increases prime editing significantly in multiple cell lines across dozens of target sites.

bioengineering↗

bioRxiv2021

Renal Interstitial Cells Promote Nephron Regeneration by Secreting Prostaglandin E2

In organ regeneration, progrnitor and stem cells reside in their native microenvironment, which provides dynamic physical and chemical cues essential to their survival, proliferation and differentiation. However, what kind of cells provide a native microenvironment for renal progenitor cells has not been clarified. Here, single-cell sequencing of zebrafish kidney revealed that fabp10 was a marker of renal interstitial cells (RICs), and the Tg(fabp10a:GFP) transgenic line can specifically label RICs in zebrafish kidney. The formation of RICs and nephrons are closely accompanied during nephron regeneration. RICs form a network to wrap the renal progenitor cell aggregates. RICs in close contact with cell aggregates express cyclooxygenase 2 and secrete prostaglandin 2 (PGE2). Inhibiting PGE2 production prevented nephrogenesis by reducing the proliferation and differentiation of progenitor cell aggregates. PGE2 promoted maturation of the nephron by activating the WNT signaling pathway in progenitor cell aggregates in cooperation with Wnt4a. These findings suggest that RICs provide a necessary microenvironment for rapid nephrogenesis during nephron regeneration.

developmental biology↗

bioRxiv2021

Mutations in PIKFYVE cause autosomal dominant congenital cataract

Congenital cataract, an ocular disease predominantly occurring within the first decade of life, is one of the leading causes of blindness in children. Through whole exome sequencing of a Chinese family with congenital cataract, we identified a disease-causing mutation (p.G1943E) in PIKFYVE, which affecting the PIP kinase domain of the PIKfyve protein. We demonstrated that heterozygous/homozygous disruption of PIKfyve kinase domain, instead of overexpression of PIKFYVEG1943E in zebrafish mimicked the cataract defect in human patients, suggesting that haploinsufficiency, rather than dominant-negative inhibition of PIKfyve activity caused the disease. Phenotypical analysis of pikfyve zebrafish mutants revealed that loss of Pikfyve caused aberrant vacuolation (accumulation of Rab7+Lc3+ amphisomes) in lens cells, which was significantly alleviated by treatment with the V-ATPase inhibitor bafilomycin A1 (Baf-A1). Collectively, we identified PIKFYVE as a novel causative gene for congenital cataract and demonstrated the potential application of Baf-A1 in treatment of congenital cataract.

genomics↗