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Ling, X.

Publications and source records attributed to Ling, X..

22 records · Page 2Linked to original sources

Disease associated protein-protein interaction network reconstruction based on comprehensive influence analysis

Proteins and their interactions are fundamental to biological system. With the scientific paradigm shifting to systems biology, functional study of proteins from a network viewpoint to get a deep understanding of their roles in human life and diseases being increasingly essential. Although several methods already existed for protein-protein interaction (PPI) network building, the precise reconstruction of disease associated PPI network remains a challenge. In this paper we introduce a novel concept of comprehensive influence of proteins in network, in which direct and indirect connections are adopted for the calculation of influential effects of a protein with different weights. With the optimized weights, we calculate and select the important proteins and their interactions to reconstruct the PPI network for further validation and confirmation. To evaluate the performance of the method, we compared our model with the six existed ones by using five standard data sets. The results indicated that our method outperforms the existed ones. We then applied our model to prostate cancer and Parkinsons disease to predict novel disease associated proteins for the future experimental validation. Author SummaryThe diverse protein-protein interaction networks have dramatic effects on biological system. The disease associated PPI networks are generally reconstructed from experimental data with computational models but with limited accuracy. We developed a novel concept of comprehensive influence of proteins in network for reconstructing the PPI network. Our model outperforms the state-of-the-art ones and we then applied our model to identify novel interactions for further validation.

bioinformatics↗

Rapid, selective and single cell electrical detection of antibiotic resistant bacteria

The rapid increase in antibiotic resistant pathogenic bacteria has become a global threat, which besides the development of new drugs, requires rapid, cheap, scalable, and accurate diagnostics. Label free biosensors relying on electrochemical, mechanical, and mass based detection of whole bacterial cells have attempted to meet these requirements. However, the trade-off between selectivity and sensitivity of such sensors remains a key challenge. In particular, point-of-care diagnostics that are able to reduce and/or prevent unneeded antibiotic prescriptions require highly specific probes with sensitive and accurate transducers that can be miniaturized and multiplexed, and that are easy to operate and cheap. Towards achieving this goal, we present a number of advances in the use of graphene field effect transistors (G-FET) including the first use of peptide probes to electrically detect antibiotic resistant bacteria in a highly specific manner. In addition, we dramatically reduce the needed concentration for detection by employing dielectrophoresis for the first time in a G-FET, allowing us to monitor changes in the Dirac point due to individual bacterial cells. Specifically, we realized rapid binding of bacterial cells to a G-FET by electrical field guiding to the device to realize an overall 3 order of magnitude decrease in cell-concentration enabling a single-cell detection limit, and 9-fold reduction in needed time to 5 minutes. Utilizing our new biosensor and procedures, we demonstrate the first selective, electrical detection of the pathogenic bacterial species Staphylococcus aureus and antibiotic resistant Acinetobacter baumannii on a single platform.

microbiology↗

Comparative molecular life history of spontaneous canine and human gliomas

Sporadic gliomas in companion dogs provide a window on the interaction between tumorigenic mechanisms and host environment. We compared the molecular profiles of canine gliomas with those of human pediatric and adult gliomas to characterize evolutionarily conserved mammalian mutational processes in gliomagenesis. Employing whole genome-, exome-, transcriptome-and methylation-sequencing of 81 canine gliomas, we found alterations shared between canine and human gliomas such as the receptor tyrosine kinases, p53 and cell cycle pathways, and IDH1 R132. Canine gliomas showed high similarity with human pediatric gliomas per robust aneuploidy, mutational rates, relative timing of mutations, and DNA methylation patterns. Our cross-species comparative genomic analysis provides unique insights into glioma etiology and the chronology of glioma-causing somatic alterations.\n\nSignificanceDiffuse gliomas are the most common malignant brain tumors, with high-grade tumors carrying a dismal prognosis. Preclinical models have proven themselves as poor predictors of clinical efficacy. Spontaneous glioma in dogs provides an attractive alternative model, because of their comparable tumor microenvironment and tumor life history. We determined the similarities and differences between human and canine gliomas through genomic profiling, and leveraged our datasets to identify conserved somatic drivers, mutational processes and temporal ordering of somatic glioma events across species. We show that canine gliomas resemble human gliomas at (epi-)genetic levels and are more reminiscent of pediatric than adult disease, thus rationalizing sporadic canine glioma as a preclinical model tailored to measuring treatment efficacies in patients with canine or human glioma.

cancer biology↗

Identification of brain metastasis genes and therapeutic evaluation of histone deacetylase inhibitors in a clinically relevant model of breast cancer brain metastasis

Breast cancer brain metastasis remains largely incurable. While several mouse models have been developed to investigate the genes and mechanisms regulating breast cancer brain metastasis, these models often lack clinical relevance since they require the use of immune-compromised mice and/or are poorly metastatic to brain from the mammary gland. We describe the development and characterisation of an aggressive brain metastatic variant of the 4T1 syngeneic model (4T1Br4) that spontaneously metastasises to multiple organs, but is selectively more metastatic to the brain from the mammary gland than parental 4T1 tumours. By immunohistochemistry, 4T1Br4 tumours and brain metastases display a triple negative phenotype, consistent with the high propensity of this breast cancer subtype to spread to brain. In vitro assays indicate that 4T1Br4 cells have an enhanced ability to adhere to or migrate across a brain-derived endothelial monolayer and greater invasive response to brain-derived soluble factors compared to 4T1 cells. These properties are likely to contribute to the brain-selectivity of 4T1Br4 tumours. Expression profiling and gene set enrichment analyses demonstrate the clinical relevance of the 4T1Br4 model at the transcriptomic level. Pathway analyses implicate tumour-intrinsic immune regulation and vascular interactions in successful brain colonisation, revealing potential therapeutic targets. Evaluation of two histone deacetylase inhibitors, SB939 and 1179.4b, shows partial efficacy against 4T1Br4 metastasis to brain and other sites in vivo and potent radio-sensitising properties in vitro. The 4T1Br4 model provides a clinically relevant tool for mechanistic studies and to evaluate novel therapies against brain metastasis.\n\nSUMMARY STATEMENTWe introduce a new syngeneic mouse model of spontaneous breast cancer brain metastasis, demonstrate its phenotypic, functional and transcriptomic relevance to human TNBC brain metastasis and test novel therapies.

cancer biology↗