Biology subjects

Yuan, K.

Publications and source records attributed to Yuan, K..

69 records · Page 4Linked to original sources

bioRxiv2021

Treatment with sodium butyrate has therapeutic benefits for Machado-Joseph disease through the induction of autophagy

Spinocerebellar ataxia type 3 (SCA3, also known as Machado Joseph disease) is a fatal neurodegenerative disease caused by expansion of the trinucleotide repeat region within the ATXN3/MJD gene. Mutation of ATXN3 causes formation of ataxin-3 protein aggregates, neurodegeneration and motor deficits. Here we investigated the therapeutic potential and mechanistic activity of sodium butyrate (SB), the sodium salt of butyric acid, a metabolite naturally produced by gut microbiota, on cultured SH-SY5Y cells and transgenic zebrafish expressing human ataxin-3 containing 84 glutamine (Q) residues to model SCA3. SCA3 SH-SY5Y cells were found to contain high molecular weight ataxin-3 species and detergent insoluble protein aggregates. Treatment with SB increased activity of the autophagy protein quality control pathway in the SCA3 cells, decreased presence of ataxin-3 aggregates and presence of high molecular weight ataxin-3 in an autophagy-dependent manner. Treatment with SB was also beneficial in vivo, improving swimming performance, increasing activity of the autophagy pathway and decreasing presence of insoluble ataxin-3 protein species in the transgenic SCA3 zebrafish. Co-treating the SCA3 zebrafish with SB and chloroquine, an autophagy inhibitor, prevented the beneficial effects of SB on zebrafish swimming, indicating that the improved swimming performance was autophagy-dependent. To understand the mechanism by which SB induces autophagy we performed proteomic analysis of protein lysates from the SB treated and untreated SCA3 SH-SY5Y cells. We found that SB treatment had increased activity of Protein Kinase A and AMPK signalling, with immunoblot analysis confirming that SB treatment had increased levels of AMPK protein and its substrates. Together our findings indicate that treatment with SB can increase activity of the autophagy pathway through a PKA/AMPK-dependent process and that this has beneficial effects in vitro and in vivo. We propose that treatment with sodium butyrate warrants further investigation as a potential treatment for neurodegenerative diseases underpinned by mechanisms relating to protein aggregation including SCA3.

neuroscience↗

bioRxiv2020

Piezo2 mediates ultrasonic hearing via cochlear outer hair cells in mice

Ultrasonic hearing is exploited for hunting and navigation as in echolocation by microbats and bottleneck dolphins, and for social communication like ultrasonic vocalization by mice and rats. However, the molecular and cellular basis for ultrasonic hearing is not known yet. Here we show that knockout of the mechanosensitive ion channel PIEZO2 in cochlea disrupts the ultrasonic hearing but not the low-frequency hearing in mice, as shown by audiometry and acoustically-associative freezing behavior. Deletion of Piezo2 in the outer hair cells specifically abolishes the associative learning of the mice upon hearing the ultrasonic frequency. Ex vivo cochlear Ca2+ imaging revealed that the ultrasonic transduction requires both PIEZO2 and the hair-cell mechanotransduction channel. Together, our study demonstrates that the outer hair cells are the effector cells with PIEZO2 as an essential molecule for ultrasonic hearing in mice. Significance StatementSome animals have evolved an incredible ability for vocalizing and hearing ultrasonic frequencies that is inaudible for humans (> 20 kHz). For many years, it has been considered that animals hear ultrasonic frequencies with their cochlear hair cells, using the identical set of mechanotransduction molecules in the hair bundles for hearing audible frequencies. Here, we show that the mice lacking the mechanosensitive ion channel PIEZO2 hardly hear ultrasonic frequencies, while can still be sensitive to audible frequencies. Thus, animals may use a partially different mechanism for sensing physiological ultrasound.

neuroscience↗

bioRxiv2020

The history and evolution of the Denisovan-EPAS1 haplotype in Tibetans

Recent studies suggest that admixture with archaic hominins played an important role in facilitating biological adaptations to new environments. For example, interbreeding with Denisovans facilitated the adaptation to high altitude environments on the Tibetan Plateau. Specifically, the EPAS1 gene, a transcription factor that regulates the response to hypoxia, exhibits strong signatures of both positive selection and introgression from Denisovans in Tibetan individuals. Interestingly, despite being geographically closer to the Denisova cave, East Asian populations do not harbor as much Denisovan ancestry as populations from Melanesia. Recently, two studies have suggested two independent waves of Denisovan admixture into East Asians, one of which is shared with South Asians and Oceanians. Here we leverage data from EPAS1 in 78 Tibetan individuals to interrogate which of these two introgression events introduced the EPAS1 beneficial sequence into the ancestral population of Tibetans, and we use the distribution of introgressed segment lengths at this locus to infer the timing of the introgression and selection event. We find that the introgression event unique to East Asians most likely introduced the beneficial haplotype into the ancestral population of Tibetans around 43,000 (15,700-60,000) years ago, and selection started 12,000 (1,925-50,000) years ago. Our estimates suggest that one of the most convincing examples of adaptive introgression is in fact selection acting on standing archaic variation.

evolutionary biology↗

bioRxiv2020

Effectively control of viral disease outbreak in shrimp culture system by selective predation

Due to the limited understanding of the characteristics of predator-pathogen-prey interactions, few attempts to use selective predation for controlling diseases in prey populations have been successful. The global pandemic of white spot syndrome (WSS), caused by white spot syndrome virus (WSSV), causes devastating economic losses in farmed shrimp production. Currently, there is no effective control for WSS. Here, we determined the transmission dynamics of WSSV and the feeding ability and selectivity of fish on healthy, infected and dead shrimp by experiments and mathematical modeling. Accordingly, we developed a novel and convenient shrimp cultural ecosystem, which that effectively prevented WSS outbreaks, by introducing aquaculture fish species. This provides a scheme for developing control strategies for viral diseases with high transmission rate.

ecology↗

bioRxiv2020

BiCoN: Network-constrained biclustering of patients and omics data

MotivationUnsupervised learning approaches are frequently employed to identify patient subgroups and biomarkers such as disease-associated genes. Thus, clustering and biclustering are powerful techniques often used with expression data, but are usually not suitable to unravel molecular mechanisms along with patient subgroups. To alleviate this, we developed the network-constrained biclustering approach BiCoN (Biclustering Constrained by Networks) which (i) restricts biclusters to functionally related genes connected in molecular interaction networks and (ii) maximizes the difference in gene expression between two subgroups of patients. ResultsOur analyses of non-small cell lung and breast cancer gene expression data demonstrate that BiCoN clusters patients in agreement with known cancer subtypes while discovering gene subnetworks pointing to functional differences between these subtypes. Furthermore, we show that BiCoN is robust to noise and batch effects and can distinguish between high and low load of tumor-infiltrating leukocytes while identifying subnetworks related to immune cell function. In summary, BiCoN is a powerful new systems medicine tool to stratify patients while elucidating the responsible disease mechanism. AvailabilityPyPI package: https://pypi.org/project/bicon Web interface: https://exbio.wzw.tum.de/bicon Contactolga.lazareva@tum.de Supplementary informationSupplementary data are available at Bioinformatics online.

bioinformatics↗

bioRxiv2019

Gold Nanobipyramids as Second Near Infrared Optical Coherence Tomography Contrast Agents for Multiplexed In Vivo Lymphangiography

Developing contrast-enhanced optical coherence tomography (OCT) techniques is important for specific imaging of tissue lesions, molecular imaging, cell-tracking, and highly sensitive microangiography and lymphangiography. Multiplexed OCT imaging in the second near infrared (NIR-II) window is highly desirable since it allows simultaneous imaging and tracking of multiple biological events in high resolution with deeper tissue penetration in vivo. Here we demonstrate that gold nanobipyramids can function as OCT multiplexing contrast agents, allowing the visualization of two separate lymphatic flows occurring simultaneously from different drainage basins into the same lymph node in a live mouse. Contrast-enhanced multiplexed lymphangiography of a melanoma tumor in vivo shows that the peritumoral lymphatic drainage upstream of the tumor is unidirectional, with some drainage directly into the tumor, but the lymphatic drainage from the tumor is multi-directional. We also demonstrate real-time tracking of the contrast agents draining from a melanoma tumor specifically to the sentinel lymph node of the tumor and the three-dimensional distribution of the contrast agents in the lymph node.

bioengineering↗

bioRxiv2018

frenchFISH: Poisson models for quantifying DNA copy-number from fluorescence in situ hybridisation of tissue sections

Chromosomal aberration and DNA copy number change are robust hallmarks of cancer. Imaging of spots generated using fluorescence in situ hybridisation (FISH) of locus specific probes is routinely used to detect copy number changes in tumour nuclei. However, it often does not perform well on solid tumour tissue sections, where partially represented or overlapping nuclei are common. To overcome these challenges, we have developed a computational approach called FrenchFISH, which comprises a nuclear volume correction method coupled with two types of Poisson models: either a Poisson model for improved manual spot counting without the need for control probes; or a homogenous Poisson Point Process model for automated spot counting. We benchmarked the performance of FrenchFISH against previous approaches in a controlled simulation scenario and exemplify its use in 12 ovarian cancer FFPE-tissue sections, for which we assess copy number alterations in three loci (c-Myc, hTERC and SE7). We show that FrenchFISH outperforms standard spot counting approaches and that the automated spot counting is significantly faster than manual without loss of performance. FrenchFISH is a general approach that can be used to enhance clinical diagnosis on sections of any tissue.\n\nAuthor summaryCancer genomes can look very chaotic, because cancer cells are unable to fully repair errors in DNA replication during cell division. While a healthy genome has two copies of every chromosome, in a cancer genome some pieces can be lost completely and others can appear in 50 copies. To diagnose cancers and to decide on the right therapeutic strategy for a patient, it can be very important to know how many copies of a particular piece of DNA exist in a cell. The standard technique used in the clinic to assess DNA copy number is called FISH, short for fluorescence in situ hybridisation. This technique uses fluorescent probes that bind to a DNA piece of interest and show up as glowing spots in a microscopic image. Counting the spots in an image is a labour-and time-intensive process that is generally done by well-trained experts. Here we present a statistical approach to automatically count FISH spots, which outperforms previously proposed methods, and has the potential to substantially speed up clinical diagnostics.

bioinformatics↗

bioRxiv2018

Ccube: A fast and robust method for estimating cancer cell fractions

Estimating and clustering cancer cell fractions of genomic alterations are central tasks for studying intratumour heterogeneity. We present Ccube, a probabilistic framework for inferring the cancer cell fraction of somatic point mutations and the subclonal composition from whole-genome sequencing data. We develop a variational inference method for model fitting, which allows us to handle samples with large number of the variants (more than 2 million) while quantifying uncertainty in a Bayesian fashion. Ccube is available at https://github.com/keyuan/ccube.

bioinformatics↗

bioRxiv2018

Portraits of genetic intra-tumour heterogeneity and subclonal selection across cancer types

Intra-tumor heterogeneity (ITH) is a mechanism of therapeutic resistance and therefore an important clinical challenge. However, the extent, origin and drivers of ITH across cancer types are poorly understood. To address this question, we extensively characterize ITH across whole-genome sequences of 2,658 cancer samples, spanning 38 cancer types. Nearly all informative samples (95.1%) contain evidence of distinct subclonal expansions, with frequent branching relationships between subclones. We observe positive selection of subclonal driver mutations across most cancer types, and identify cancer type specific subclonal patterns of driver gene mutations, fusions, structural variants and copy-number alterations, as well as dynamic changes in mutational processes between subclonal expansions. Our results underline the importance of ITH and its drivers in tumor evolution, and provide an unprecedented pan-cancer resource of comprehensively annotated subclonal events from whole-genome sequencing data.

cancer biology↗

bioRxiv2017

SVclone: inferring structural variant cancer cell fraction

We present SVclone, a computational method for inferring the cancer cell fraction of structural variant breakpoints from whole-genome sequencing data. We validate our approach using simulated and real tumour samples, and demonstrate its utility on 2,778 whole-genome sequenced tumours. We find a subset of liver, breast and ovarian cancer cases with decreased overall survival that have subclonally enriched copy-number neutral rearrangements, an observation that could not be discovered with currently available methods.

cancer biology↗

bioRxiv2017

The evolutionary history of 2,658 cancers

Cancer develops through a process of somatic evolution. Here, we use whole-genome sequencing of 2,778 tumour samples from 2,658 donors to reconstruct the life history, evolution of mutational processes, and driver mutation sequences of 39 cancer types. The early phases of oncogenesis are driven by point mutations in a small set of driver genes, often including biallelic inactivation of tumour suppressors. Early oncogenesis is also characterised by specific copy number gains, such as trisomy 7 in glioblastoma or isochromosome 17q in medulloblastoma. By contrast, increased genomic instability, a nearly four-fold diversification of driver genes, and an acceleration of point mutation processes are features of later stages. Copy-number alterations often occur in mitotic crises leading to simultaneous gains of multiple chromosomal segments. Timing analysis suggests that driver mutations often precede diagnosis by many years, and in some cases decades, providing a window of opportunity for early cancer detection.

cancer biology↗

bioRxiv2017

Interphase-Arrested Drosophila Embryos Initiate Mid-Blastula Transition At A Low Nuclear-Cytoplasmic Ratio

Externally deposited eggs begin development with an immense cytoplasm and a single overwhelmed nucleus. Rapid mitotic cycles restore normality as the ratio of nuclei to cytoplasm (N/C) increases. At the 14th cell cycle in Drosophila embryos, the cell cycle slows, transcription increases, and morphogenesis begins at the Mid-Blastula Transition (MBT). To explore the role of N/C in MBT timing, we blocked N/C-increase by downregulating cyclin/Cdk1 to arrest early cell cycles. Embryos arrested in cell cycle 12 cellularized, initiated gastrulation movements and activated transcription of genes previously described as N/C dependent. Thus, occurrence of these events is not directly coupled to N/C-increase. However, N/C might act indirectly. Increasing N/C promotes cyclin/Cdk1 downregulation which otherwise inhibits many MBT events. By experimentally inducing downregulation of cyclin/Cdk1, we bypassed this input of N/C-increase. We describe a regulatory cascade wherein the increasing N/C downregulates cyclin/Cdk1 to promote increasing transcription and the MBT.\n\nImpact statementBy showing that cell-cycle arrest allows early Drosophila embryos to progress to later stages, this work eliminates numerous models for embryonic timing and shows the dominating influence of cell-cycle slowing.

developmental biology↗

bioRxiv2016

Inference of Multiple-wave Admixtures by Length Distribution of Ancestral Tracks

The ancestral tracks in admixed genomes are of valuable information for population history inference. A few methods have been developed to infer admixture history based on ancestral tracks. Nonetheless, these methods suffered the same flaw that only population admixture history under some specific models can be inferred. In addition, the inference of history might be biased or even unreliable if the specific model is deviated from the real situation. To address this problem, we firstly proposed a general discrete admixture model to describe the admixture history with multiple ancestral populations and multiple-wave admixtures. We next deduced the length distribution of ancestral tracks under the general discrete admixture model. We further developed a new method, MultiWaver, to explore the multiple-wave admixture histories. Our method could automatically determine an optimal admixture model based on the length distribution of ancestral tracks, and estimate the corresponding parameters under this optimal model. Specifically, we used a likelihood ratio test (LRT) to determine the number of admixture waves, and implemented an expectation??maximization (EM) algorithm to estimate parameters. We used simulation studies to validate the reliability and effectiveness of our method. Finally, good performance was observed when our method was applied to real datasets of African Americans, Mexicans, Uyghurs, and Hazaras.

genetics↗

bioRxiv2016

BaalChIP: Bayesian analysis of allele-specific transcription factor binding in cancer genomes

Allele-specific measurements of transcription factor binding from ChIP-seq data are key to dissecting the allelic effects of non-coding variants and their contribution to phenotypic diversity. However, most methods to detect allelic imbalance assume diploid genomes. This assumption severely limits their applicability to cancer samples with frequent DNA copy number changes. Here we present a Bayesian statistical approach called BaalChIP to correct for the effect of background allele frequency on the observed ChIP-seq read counts. BaalChIP allows the joint analysis of multiple ChIP-seq samples across a single variant and outperforms competing approaches in simulations. Using 548 ENCODE ChIP-seq and 6 targeted FAIRE-seq samples we show that BaalChIP effectively corrects allele-specific analysis for copy number variation and increases the power to detect putative cis-acting regulatory variants in cancer genomes.

cancer biology↗

bioRxiv2016

Inference of multiple-wave population admixture by modeling decay of linkage disequilibrium with polynomial functions

To infer the histories of population admixture, one important challenge with methods based on the admixture linkage disequilibrium (ALD) is to get rid of the effect of source LD (SLD) which is directly inherited from source populations. In previous methods, only the decay curve of weighted LD between pairs of sites whose genetic distance were larger than a certain starting distance was fitted by single or multiple exponential functions, for the inference of recent single- or multiple-wave of admixture. However, the effect of SLD has not been well defined and no tool has been developed to estimate the effect of SLD on weighted LD decay. In this study, we defined the SLD in the formularized weighted LD statistic under the two-way admixture model, and proposed polynomial spectrum (p-spectrum) to study the weighted SLD and weighted LD. We also found reference populations could be used to reduce the SLD in weighted LD statistic. We further developed a method, iMAAPs, to infer Multiple-wave Admixture by fitting ALD using Polynomial spectrum. We evaluated the performance of iMAAPs under various admixture models in simulated data and applied iMAAPs into analysis of genome-wide single nucleotide polymorphism data from the Human Genome Diversity Project (HGDP) and the HapMap Project. We showed that iMAAPs is a considerable improvement over other current methods and further facilitates the inference of the histories of complex population admixtures.

evolutionary biology↗