Biology subjects

Feng, X.

Publications and source records attributed to Feng, X..

233 records · Page 13Linked to original sources

bioRxiv2018

Inherited defects in natural killer cells shape tumor immune microenvironment, clinical outcome and immunotherapy response

Tumor immune microenvironment (TIME) plays an important role in metastasis and immunotherapy. However, it has been not much known how to classify TIMEs and how TIMEs are genetically regulated. Here we showed that tumors were classified into TIME-rich, -intermediate and -poor subtypes which had significant differences in clinical outcomes, abundances of tumor-infiltrating lymphocytes (TILs), the degree of key immune programs activation, and immunotherapy response across 13 common cancer types (n= [~]6,000). Furthermore, TIME-intermediate/-poor patients had significantly more inherited genetic defects (i.e., functional germline variants) in natural killer (NK) cells, antigen processing and presentation (APP) and Wnt signaling pathways than TIME-rich patients, and so did cancer patients than non-cancer individuals (n=4,500). These results suggested that individuals who had more inherited defects in NK cells, APP and Wnt pathways had a higher risk of developing cancers. Moreover, in the 13 common cancers the number of inheritably defected genes of NK cells was significantly negative-correlated with patients survival, TILs abundance in TIMEs and immunotherapy response, suggesting that inherited defects in NK cells alone were sufficient to shape TILs recruitment, clinical outcome, and immunotherapy response, highlighting that NK cell activation was required in the 13 cancer types to drive the recruitment of immune troops into TIMEs. Thus, we proposed that cancer was a disease of NK cell inherited deficiencies. These results had implications in identifying of high-risk individuals based on germline genomes, implementing precision cancer prevention by adoptive transfer of healthy NK cells, and improving existing immunotherapies by combining of adoptive NK cell transfer (i.e., converting TIME-intermediate/-poor tumors into TIME-rich tumors) and anti-PD-1 or CAR-T therapy.\n\nContactEW (edwin.wang@ucalgary.ca)

cancer biology↗

bioRxiv2018

Differential phase partition of a PICS complex is required for piRNA processing and chromosome segregation in C. elegans

Piwi-interacting RNAs (piRNAs) play significant roles in suppressing transposons and non-self nucleic acids, maintaining genome integrity, defending against viral infections, and are essential for fertility in a variety of organisms. In C. elegans, most piRNA precursors are transcribed by RNA polymerase II in the nucleus and are subjected to a number of processing and maturation steps. However, the biogenesis of piRNAs are still not fully understood. We used functional proteomics to study piRNA biogenesis in C. elegans and identified a PICS complex that is required for piRNA processing and chromosome segregation. The PICS complex contains two known piRNA biogenesis factors TOFU-6 and PID-1, and three new proteins PICS-1, TOST-1, and ERH-2, which exhibit dynamic localization among different subcellular compartments. In the germline of gravid animals, the PICS complex contains TOFU-6/PICS-1/ERH-2/PID-1 and largely concentrate at the perinuclear granule zone and engages in piRNA processing. During early embryogenesis, the TOFU-6/PICS-1/ERH-2/TOST-1 complex accumulates in the nucleus and play essential roles in chromosome segregation and cell division. Interestingly, the function of these factors in mediating chromosome segregation is independent of piRNA production. Therefore, we speculate that a differential phase partition of PICS factors may help cells to coordinate distinct cellular processes.

genetics↗

bioRxiv2018

Deep Learning on MRI Affirms the Prominence of the Hippocampal Formation in Alzheimer’s Disease Classification

Deep learning techniques on MRI scans have demonstrated great potential to improve the diagnosis of neurological diseases. Here, we investigate the application of 3D deep convolutional neural networks (CNNs) for classifying Alzheimers disease (AD) based on structural MRI data. In particular, we take on two challenges that are under-explored in the literature on deep learning for neuroimaging. First deep neural networks typically require large-scale data that is not always available in medical studies. Therefore, we explore the use of including longitudinal scans in classification studies, greatly increasing the amount of data for training and improving the generalization performance of our classifiers. Moreover, previous studies applying deep learning to classifying Alzheimers disease from neuroimaging have typically addressed classification based on whole brain volumes but stopped short of performing in-depth regional analyses to localize the most predictive areas. Additionally, we show a deep net trained to distinguish between AD and cognitively normal subjects can be applied to classify mild cognitive impairment patients, with classification scores aligning empirically with the likelihood of progression to AD. Our initial results demonstrate both that we can classify AD with an area under the receiver operator characteristic curve (AUROC) of .990 and that we can predict conversion to AD among patients in the MCI subgroup with an AURUC of 0.787. We then localize the predictive regions, by performing both saliency-based interpretation and rigorous slice and lobar level ablation studies. Interestingly, our regional analyses identified the hippocampal formation, including the entorhinal cortex, to be the most predictive region for our models. This finding adds evidence that the hippocampal formation is an anatomical seat of AD and a prominent feature in its diagnosis. Together, the results of this study further demonstrate the potential of deep learning to impact AD classification and to identify ADs structural neuroimaging signatures. The proposed classification and regional analyses methods constitute a general framework that can easily be applied to other disorders and imaging modalities.\n\nAcronyms

neuroscience↗

bioRxiv2018

Natural depletion of H1 in sex cells causes DNA demethylation, heterochromatin decondensation and transposon activation

Transposable elements (TEs), the movement of which can damage the genome, are epigenetically silenced in eukaryotes. Intriguingly, TEs are activated in the sperm companion cell - vegetative cell (VC) - of the flowering plant Arabidopsis thaliana. However, the extent and mechanism of this activation are unknown. Here we show that about 100 heterochromatic TEs are activated in VCs, mostly by DEMETER-catalyzed DNA demethylation. We further demonstrate that DEMETER access to some of these TEs is permitted by the natural depletion of linker histone H1 in VCs. Ectopically expressed H1 suppresses TEs in VCs by reducing DNA demethylation and via a methylation-independent mechanism. We demonstrate that H1 is required for heterochromatin condensation in plant cells and show that H1 overexpression creates heterochromatic foci in the VC progenitor cell. Taken together, our results demonstrate that the natural depletion of H1 during male gametogenesis facilitates DEMETER-directed DNA demethylation, heterochromatin relaxation, and TE activation.

plant biology↗

bioRxiv2018

Quantitative reconstruction of time-varying 3D cell forces with traction force optical coherence microscopy

Cellular traction forces (CTFs) play an integral role in both physiological processes and disease, and are a topic of interest in mechanobiology. Traction force microscopy (TFM) is a family of methods used to quantify CTFs in a variety of settings. State-of-the-art 3D TFM methods typically rely on confocal fluorescence microscopy, which can impose limitations on acquisition speed, volumetric coverage, and temporal sampling or coverage. In this report, we present the first quantitative implementation of a new TFM technique: traction force optical coherence microscopy (TF-OCM). TF-OCM leverages the capabilities of optical coherence microscopy and computational adaptive optics (CAO) to enable the quantitative reconstruction of 3D CTFs in scattering media with minute-scale temporal resolution. We applied TF-OCM to quantify CTFs exerted by isolated NIH-3T3 fibroblasts embedded in Matrigel, with five-minute temporal sampling, using images which spanned a 500x500x500 m3 field-of-view. Due to the reliance of TF-OCM on computational imaging methods, we have provided extensive discussion of the underlying equations, assumptions, and failure modes of these methods. TF-OCM has the potential to advance studies of biomechanical behavior in scattering media, and may be especially well-suited to the study of cell collectives such as spheroids, a prevalent model in mechanobiology research.

bioengineering↗

bioRxiv2018

FT/FD-GRF5 repression loop directs growth to increase soybean yield

Major advances in crop yield are eternally needed to cope with population growth. To balance vegetative and reproductive growth plays an important role in agricultural yield. To extend vegetative phase can increase crop yield, however, this strategy risks loss of yield in the field as crops may not mature in time before winter come. Here, we identified a repression feedback loop between GmFTL/GmFDL and GmGRF5-1 (Glycine-max-Flowering-Locus-T/Glycine-max-FDL and Glycine-max-GROWTH-REGULATING-FACTOR5-1), which functions as a pivotal regulator in balancing vegetative and reproductive phases in soybean. GmFTL/GmFDL and GmGRF5-1 directly repress gene expression each other. Additionally, GmGRF5-1 enhances vegetative growth by directly enhancing expression of photosynthesis- and auxin synthesis-related genes. To modulate the loop, such as fine-tuning GmFTL expression to trade-off vegetative and reproductive growth, increases substantially soybean yield in the field. Our findings not only uncover the mechanism balancing vegetative and reproductive growth, but open a new window to improve crop yield.

plant biology↗

bioRxiv2018

The USTC complex co-opts an ancient machinery to drive piRNA transcription in C. elegans

Piwi-interacting RNAs (piRNAs) engage Piwi proteins to suppress transposons and non-self nucleic acids, maintain genome integrity, and are essential for fertility in a variety of organisms. In C. elegans most piRNA precursors are transcribed from two genomic clusters that contain thousands of individual piRNA transcription units. While a few genes have been shown to be required for piRNA biogenesis the mechanism of piRNA transcription remains elusive. Here we used functional proteomics approaches to identify an upstream sequence transcription complex (USTC) that is essential for piRNA biogenesis. The USTC complex contains PRDE-1, TOFU-4, TOFU-5 and SNPC-4. The USTC complex form a unique piRNA foci in germline nuclei and coat the piRNA cluster genomic loci. USTC factors associate with the Ruby motif just upstream of type I piRNA genes. USTC factors are also mutually dependent for binding to the piRNA clusters and to form the piRNA foci. Interestingly, USTC components bind differentially to piRNAs in the clusters and other non-coding RNA genes. These results reveal USTC as a striking example of the repurposing of a general transcription factor complex to aid in genome defence against transposons.

developmental biology↗

bioRxiv2018

Genomic underpinnings of lifespan allow prediction and reveal basis in modern risks

We use a multi-stage genome-wide association of 1 million parental lifespans of genotyped subjects and data on mortality risk factors to validate previously unreplicated findings near CDKN2B-AS1, ATXN2/BRAP, FURIN/FES, ZW10, PSORS1C3, and 13q21.31, and identify and replicate novel findings near GADD45G, KCNK3, LDLR, POM121C, ZC3HC1, and ABO. We also validate previous findings near 5q33.3/EBF1 and FOXO3, whilst finding contradictory evidence at other loci. Gene set and tissue-specific analyses show that expression in foetal brain cells and adult dorsolateral prefrontal cortex is enriched for lifespan variation, as are gene pathways involving lipid proteins and homeostasis, vesicle-mediated transport, and synaptic function. Individual genetic variants that increase dementia, cardiovascular disease, and lung cancer -but not other cancers-explain the most variance, possibly reflecting modern susceptibilities, whilst cancer may act through many rare variants, or the environment. Resultant polygenic scores predict a mean lifespan difference of around five years of life across the deciles.

genomics↗

bioRxiv2017

The PTPRT pseudo-phosphatase domain is a denitrase

Protein tyrosine nitration occurs under both physiological and pathological conditions1. However, enzymes that remove this protein modification have not yet been identified. Here we report that the pseudo-phosphatase domain of protein tyrosine receptor T (PTPRT) is a denitrase that removes nitro-groups from tyrosine residues in paxillin. PTPRT normally functions as a tumor suppressor and is frequently mutated in a variety of human cancers including colorectal cancer2,3. We demonstrate that some of the tumor-derived mutations located in the pseudophosphatase domain impair the denitrase activity. Moreover, PTPRT mutant mice that inactivate the denitrase activity are susceptible to carcinogen-induced colon tumor formation. This study uncovers a novel enzymatic activity that is involved in tumor suppression.

cancer biology↗

bioRxiv2017

A cytoplasmic Argonaute protein promotes the inheritance of RNAi

RNAi-elicited gene silencing is heritable and can persist for multiple generations after its initial induction in C. elegans. However, the mechanism by which parental-acquired trait-specific information from RNAi is inherited by the progenies is not fully understood. Here, we identified a cytoplasmic Argonaute protein, WAGO-4, necessary for the inheritance of RNAi. WAGO-4 exhibits asymmetrical translocation to the germline during early embryogenesis, accumulates at the perinuclear foci in the germline, and is required for the inheritance of exogenous RNAi targeting both germline- and soma-expressed genes. WAGO-4 binds to 22G-RNAs and their mRNA targets. Interestingly, WAGO-4-associated endogenous 22G-RNAs target the same cohort of germline genes as CSR-1 and contain untemplated addition of uracil at the 3 ends. The poly(U) polymerase CDE-1 is required for the untemplated uridylation of 22G-RNAs and inheritance of RNAi. Therefore, we conclude that, in addition to the nuclear RNAi pathway, the cytoplasmic RNAi machinery also promotes RNAi inheritance.

genetics↗

bioRxiv2017

Advanced NeuroGPS-Tree: dense reconstruction of brain-wideneuronal population close to ground truth

Recent progresses allow imaging specific neuronal populations at single-axon level across mouse brain. However, digital reconstruction of neurons in large dataset requires months of human labor. Here, we developed a tool to solve this problem. Our tool offers a special error-screening system for fast localization of submicron errors in densely packed neurites and along long projection across the whole brain, thus achieving reconstruction close to the ground-truth. Moreover, our tool equips algorithms that significantly reduce intensive manual interferences and achieve high-level automation, with speed 5 times faster compared to semi-automatic tools. We also demonstrated reconstruction of 35 long projection neurons around one injection site of a mouse brain at an affordable time cost. Our tool is applicable with datasets of 10 TB or higher from various light microscopy, and provides a starting point for the reconstruction of neuronal population for neuroscience studies at a single-cell level.

neuroscience↗

bioRxiv2017

Sexual lineage specific DNA methylation regulates Arabidopsis meiosis

DNA methylation controls eukaryotic gene expression and is extensively reprogrammed to regulate animal development. However, whether developmental methylation reprogramming during the sporophytic life cycle of flowering plants regulates genes is presently unknown. Here we report a distinctive, gene-targeted RNA-directed DNA methylation (RdDM) activity in the Arabidopsis thaliana male sexual lineage that regulates gene expression in meiocytes. Loss of sexual lineage-specific RdDM causes mis-splicing of the MPS1/PRD2 gene, thereby disrupting meiosis. Our results establish a regulatory paradigm in which de novo methylation creates a cell-lineage-specific epigenetic signature that controls gene expression and contributes to cellular function in flowering plants.

plant biology↗

bioRxiv2017

Separating an allele associated with late flowering and slow maturation of Arabidopsis thaliana from population structure

Genome-wide association analysis is a powerful tool to identify genomic loci underlying complex traits. However, the application in natural populations comes with challenges, especially power loss due to population stratification. Here, we introduce a bivariate analysis approach to a GWAS dataset of Arabidopsis thaliana. We demonstrate the efficiency of double-phenotype analysisto uncover hidden genetic loci masked by population structure via a series of simulations. In real data analysis, acommon allele, strongly confounded with population structure, is discovered to be associated with late flowering and slow maturation of the plant. The discovered genetic effect on flowering time is further replicated in independent datasets. Using Mendelian randomization analysis based on summary statistics from our GWAS and expression QTL scans, we predicted and replicated a candidate gene AT1G11560 that potentially causes this association. Further analysis indicates that this locusis co-selected with flowering-time-related genes. The discovered pleiotropic genotypephenotype map provides new insights into understanding the genetic correlation of complex traits.

genetics↗

bioRxiv2017

Targeting posttranslational modifications of RioK1 inhibits the progression of colorectal and gastric cancers

RioK1 has recently been shown to play important roles in cancers, but its posttranslational regulation is largely unknown. Here we report that RioK1 is methylated at K411 by SETD7 methyltransferase, and that lysine-specific demethylase 1 (LSD1) reverses its methylation. The mutated RioK1 (K411R) that cannot be methylated exhibits a longer half-life than does the methylated RioK1. FBXO6 specifically interacts with K411-methylated RioK1 through its FBA domain to induce RioK1 ubiquitination. Casein kinase 2 (CK2) phosphorylates RioK1 at T410, which stabilizes RioK1 by antagonizing K411 methylation and impeding the recruitment of FBXO6 to RioK1. Functional experiments demonstrate the RioK1 methylation reduces the tumor growth and metastasis in CRC and GC. Importantly, the protein levels of CK2 and LSD1 show an inverse correlation with FBXO6 and SETD7 expression in human CRC tissues. Therefore, this study highlights the importance of a RioK1 methylation-phosphorylation switch in determining CRC and GC development.

cancer biology↗

bioRxiv2017

DeepMetabolism: A Deep Learning System To Predict Phenotype From Genome Sequencing

Life science is entering a new era of petabyte-level sequencing data. Converting such \"big data\" to biological insights represents a huge challenge for computational analysis. To this end, we developed DeepMetabolism, a biology-guided deep learning system to predict cell phenotypes from transcriptomics data. By integrating unsupervised pre-training with supervised training, DeepMetabolism is able to predict phenotypes with high accuracy (PCC>0.92), high speed (<30 min for >100 GB data using a single GPU), and high robustness (tolerate up to 75% noise). We envision DeepMetabolism to bridge the gap between genotype and phenotype and to serve as a springboard for applications in synthetic biology and precision medicine.

systems biology↗

bioRxiv2017

Data-Driven Prediction of CRISPR-Based Transcription Regulation for Programmable Control of Metabolic Flux

Multiplex and multi-directional control of metabolic pathways is crucial for metabolic engineering to improve product yield of fuels, chemicals, and pharmaceuticals. To achieve this goal, artificial transcriptional regulators such as CRISPR-based transcription regulators have been developed to specifically activate or repress genes of interest. Here, we found that by deploying guide RNAs to target on DNA sites at different locations of genetic cassettes, we could use just one synthetic CRISPR-based transcriptional regulator to simultaneously activate and repress gene expressions. By using the pairwise datasets of guide RNAs and gene expressions, we developed a data-driven predictive model to rationally design this system for fine-tuning expression of target genes. We demonstrated that this system could achieve programmable control of metabolic fluxes when using yeast to produce versatile chemicals. We anticipate that this master CRISPR-based transcription regulator will be a valuable addition to the synthetic biology toolkit for metabolic engineering, speeding up the \"design-build-test\" cycle in industrial biomanufacturing as well as generating new biological insights on the fates of eukaryotic cells.

synthetic biology↗

bioRxiv2017

Discovery and reporting of clinically-relevant germline variants in advanced cancer patients assessed using whole-exome sequencing

PurposeIn precision cancer care, WES-based analysis of tumor-normal samples helps reveal somatic alterations but can also identify cancer-associated germline variants important for disease surveillance, treatment choice and cancer prevention. WES can also identify germline secondary findings impacting risk of cardiac, neurodegenerative or metabolic diseases. In patients with advanced cancer, the frequency of reportable secondary findings encountered with WES is not well defined.\n\nMethodsTo address this question, we analyzed a cohort of 343 patients with advanced, metastatic cancer for whom we have performed tumor and germline WES interrogating more than 21,000 genes using a CLIA/CLEP approved assay.\n\nResults17% of patients in our cohort have one or more reportable germline variants, including patients with pathogenic variants in the BRCA1 and BRCA2 genes. The frequency of non-cancer clinically relevant germline variants (8.8%) was within the range of two control non-cancer cohorts (11.0% and 6.5%). The frequency of variants in cancer-associated genes was significantly higher (p<0.0005) in our advanced cancer cohort (8.2%) compared to control cohorts (2.7% and 3.8%). More than 50% of patients with reportable germline cancer variants had a family history of cancer.\n\nConclusionthese results stress the importance of returning germline results found during somatic genomic tumor testing.

genomics↗