Biology subjects

Ni, X.

Publications and source records attributed to Ni, X..

4 recordsLinked to original sources

bioRxiv2018

Multi-omics analysis of AML cells treated with azacitidine reveals highly variable cell surface proteome remodeling

Myelodysplastic syndromes (MDS) and acute myeloid leukemia (AML) are diseases of abnormal hematopoietic differentiation with aberrant epigenetic alterations. Azacitidine (AZA) is a DNA methyltransferase inhibitor (DNMTi) widely used to treat MDS and AML, yet the impact of AZA on the cell surface proteome has not been defined. To identify potential therapeutic targets for use in combination with AZA in AML patients, we investigated the effects of AZA treatment on four AML cell lines (KG1a, HL60, HNT34, and AML193), representing different stages of differentiation. The effect of AZA treatment on these cell lines was characterized at three levels: the DNA methylome (methylation array), the transcriptome (gene expression array), and the cell surface proteome (glycoprotein capture with SILAC labeling). Untreated AML cell lines showed substantial overlap in their methylomes, transcriptomes, and cell surface proteomes. AZA treatment globally reduced DNA methylation in all cell lines, but changes in the transcriptome and surface proteome were subtle and differed among the cell lines. Transcriptome analysis identified five commonly up-regulated coding genes upon AZA treatment in all four cell lines, TRPM4 being the only gene encoding a surface protein, and surface proteomics analysis found no commonly regulated proteins. Gene Set Enrichment Analysis (GSEA) of differentially-regulated RNA and surface proteins showed a decrease in metabolism pathways and an increase in immune defense response pathways. As such, AZA treatment in four AML cell lines had diverse effects at the individual gene and protein level, but converged to regulation of metabolism and immune response at the pathway level. Given the heterogeneous response of AZA in the four cell lines at the gene and protein level, we discuss potential therapeutic strategies for combinations with AZA.

cancer biology↗

bioRxiv2018

TRAF6 directs Foxp3 localization and facilitates Treg function through K63-type ubiquitination

Regulatory T cells (Treg) are crucial mediators of immune control. The characteristic gene expression and suppressive function of Treg depend considerably on the stable expression and activity of the transcription factor Foxp3. While transcriptional regulation of the Foxp3 gene has been studied in depth, both the expression and function of Foxp3 are also modulated at the protein level. However, the molecular players involved in posttranslational Foxp3 regulation are just beginning to be elucidated. Here we found TRAF6-deficient Tregs were dysfunctional in vivo; mice with Treg-restricted deletion of TRAF6 were resistant to B16 melanomas and displayed enhanced anti-tumor immunity. We further determined that Foxp3 undergoes lysine-63 chain (K63) ubiquitination at lysine 262 mediated by the E3 ligase TRAF6. When deprived of TRAF6 activity or rendered insensitive to K63 ubiquitination, Foxp3 displayed aberrant, perinuclear accumulation, disrupted function. Thus, Foxp3 ubiquitination by TRAF6 ensures proper localization of Foxp3 and facilitates Foxp3s gene-regulating activity in Tregs. These results implicate TRAF6 as a key posttranslational, Treg-stabilizing force that may be targeted in novel tolerance-breaking therapies.

immunology↗

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

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↗