41 research outputs found
LKS Asam Basa Berbasis Pendekatan Ilmiah Dalam Meningkatkan KPS Berdasarkan Kognitif Siswa
This research aimed to describe the effectiveness of scientific approach based student worksheets in improving science process skills (SPS) insight from student\u27s cognitive. The method of this research was quasi experimental with 2x2 factorial design. The population of this research was all students of XI IPA SMAN 15 Bandarlampung on 2016/2017. The sample were XI IPA-4 and the XI IPA 2 which taken by purposive sampling. The data of this study were analyzed by using two ways ANOVA test and t test. The result of this research was no interaction between learning with scientific approach based worksheets and cognitive on SPS; learning process using student worksheets scientific approach was effective to improve SPS; SPS high and low cognitive ability with learning using worksheets Scientific Approach wass higher than conventional worksheets; SPS high cognitive ability was higher than low cognitive ability with learning using worksheets scientific approach. Penelitian ini bertujuan mendeskripsikan efektivitas LKS pendekatan ilmiah dalam meningkatkan KPS berdasarkan kognitif siswa. Metode penelitian menggunakan kuasi eksperimen dengan desain faktorial 2x2. Populasi penelitian seluruh siswa kelas XI IPA di SMAN 15 Bandarlampung tahun 2016/2017. Sampel penelitian ini kelas XI IPA 4 dan kelas XI IPA 2 yang diambil dengan teknik purposive sampling. Data penelitian dianalisis menggunakan uji two ways ANOVA dan uji t. Hasil penelitian menunjukan tidak terdapat interaksi antara pembelajaran menggunakan LKS terhadap KPS berdasarkan kemampuan kognitif, pembelajaran menggunakan LKS pendekatan ilmiah efektif untuk meningkatkan KPS, KPS siswa kognitif tinggi dan rendah dengan pembelajaran menggunakan LKS pendekatan ilmiah lebih tinggi dibandingkan LKS konvensional, KPS siswa kognitif tinggi lebih tinggi dibandingkan KPS siswa kognitif rendah menggunakan LKS pendekatan ilmiah
ProteoModlR for functional proteomic analysis
BACKGROUND: High-accuracy mass spectrometry enables near comprehensive quantification of the components of the cellular proteomes, increasingly including their chemically modified variants. Likewise, large-scale libraries of quantified synthetic peptides are becoming available, enabling absolute quantification of chemically modified proteoforms, and therefore systems-level analyses of changes of their absolute abundance and stoichiometry. Existing computational methods provide advanced tools for mass spectral analysis and statistical inference, but lack integrated functions for quantitative analysis of post-translationally modified proteins and their modification stoichiometry. RESULTS: Here, we develop ProteoModlR, a program for quantitative analysis of abundance and stoichiometry of post-translational chemical modifications across temporal and steady-state biological states. While ProteoModlR is intended for the analysis of experiments using isotopically labeled reference peptides for absolute quantitation, it also supports the analysis of labeled and label-free data, acquired in both data-dependent and data-independent modes for relative quantitation. Moreover, ProteoModlR enables functional analysis of sparsely sampled quantitative mass spectrometry experiments by inferring the missing values from the available measurements, without imputation. The implemented architecture includes parsing and normalization functions to control for common sources of technical variation. Finally, ProteoModlR’s modular design and interchangeable format are optimally suited for integration with existing computational proteomics tools, thereby facilitating comprehensive quantitative analysis of cellular signaling. CONCLUSIONS: ProteoModlR and its documentation are available for download at http://github.com/kentsisresearchgroup/ProteoModlR as a stand-alone R package. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12859-017-1563-6) contains supplementary material, which is available to authorized users
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FOXA1 mutations alter pioneering activity, differentiation and prostate cancer phenotypes.
Mutations in the transcription factor FOXA1 define a unique subset of prostate cancers but the functional consequences of these mutations and whether they confer gain or loss of function is unknown1-9. Here, by annotating the landscape of FOXA1 mutations from 3,086 human prostate cancers, we define two hotspots in the forkhead domain: Wing2 (around 50% of all mutations) and the highly conserved DNA-contact residue R219 (around 5% of all mutations). Wing2 mutations are detected in adenocarcinomas at all stages, whereas R219 mutations are enriched in metastatic tumours with neuroendocrine histology. Interrogation of the biological properties of wild-type FOXA1 and fourteen FOXA1 mutants reveals gain of function in mouse prostate organoid proliferation assays. Twelve of these mutants, as well as wild-type FOXA1, promoted an exaggerated pro-luminal differentiation program, whereas two different R219 mutants blocked luminal differentiation and activated a mesenchymal and neuroendocrine transcriptional program. Assay for transposase-accessible chromatin using sequencing (ATAC-seq) of wild-type FOXA1 and representative Wing2 and R219 mutants revealed marked, mutant-specific changes in open chromatin at thousands of genomic loci and exposed sites of FOXA1 binding and associated increases in gene expression. Of note, ATAC-seq peaks in cells expressing R219 mutants lacked the canonical core FOXA1-binding motifs (GTAAAC/T) but were enriched for a related, non-canonical motif (GTAAAG/A), which was preferentially activated by R219-mutant FOXA1 in reporter assays. Thus, FOXA1 mutations alter its pioneering function and perturb normal luminal epithelial differentiation programs, providing further support for the role of lineage plasticity in cancer progression
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Ligand-activated BMP signaling inhibits cell differentiation and death to promote melanoma
Oncogenomic studies indicate that copy number variation (CNV) alters genes involved in tumor progression; however, identification of specific driver genes affected by CNV has been difficult, as these rearrangements are often contained in large chromosomal intervals among several bystander genes. Here, we addressed this problem and identified a CNV-targeted oncogene by performing comparative oncogenomics of human and zebrafish melanomas. We determined that the gene encoding growth differentiation factor 6 (GDF6), which is the ligand for the BMP family, is recurrently amplified and transcriptionally upregulated in melanoma. GDF6-induced BMP signaling maintained a trunk neural crest gene signature in melanomas. Additionally, GDF6 repressed the melanocyte differentiation gene MITF and the proapoptotic factor SOX9, thereby preventing differentiation, inhibiting cell death, and promoting tumor growth. GDF6 was specifically expressed in melanomas but not melanocytes. Moreover, GDF6 expression levels in melanomas were inversely correlated with patient survival. Our study has identified a fundamental role for GDF6 and BMP signaling in governing an embryonic cell gene signature to promote melanoma progression, thus providing potential opportunities for targeted therapy to treat GDF6-positive cancers
Selenoprotein H is an essential regulator of redox homeostasis that cooperates with p53 in development and tumorigenesis
Selenium, an essential micronutrient known for its cancer prevention properties, is incorporated into a class of selenocysteine-containing proteins (selenoproteins). Selenoprotein H (SepH) is a recently identified nucleolar oxidoreductase whose function is not well understood. Here we report that seph is an essential gene regulating organ development in zebrafish. Metabolite profiling by targeted LC-MS/MS demonstrated that SepH deficiency impairs redox balance by reducing the levels of ascorbate and methionine, while increasing methionine sulfoxide. Transcriptome analysis revealed that SepH deficiency induces an inflammatory response and activates the p53 pathway. Consequently, loss of seph renders larvae susceptible to oxidative stress and DNA damage. Finally, we demonstrate that seph interacts with p53 deficiency in adulthood to accelerate gastrointestinal tumor development. Overall, our findings establish that seph regulates redox homeostasis and suppresses DNA damage. We hypothesize that SepH deficiency may contribute to the increased cancer risk observed in cohorts with low selenium levels.National Cancer Institute (U.S.) (Grant R01 DK090311)National Cancer Institute (U.S.) (Grant R24OD017870
The impact of read length on quantification of differentially expressed genes and splice junction detection
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Yap reprograms glutamine metabolism to increase nucleotide biosynthesis and enable liver growth
The Hippo pathway is an important regulator of organ size and tumorigenesis. It is unclear, however, how Hippo signaling provides the cellular building blocks required for rapid growth. Here, we demonstrate that transgenic zebrafish expressing an activated form of the Hippo pathway effector Yap1 (also known as YAP) develop enlarged livers and are prone to liver tumor formation. Transcriptomic and metabolomic profiling identify that Yap1 reprograms glutamine metabolism. Yap1 directly enhances glutamine synthetase (glul) expression and activity, elevating steady-state levels of glutamine and enhancing the relative isotopic enrichment of nitrogen during de novo purine and pyrimidine biosynthesis. Genetic or pharmacological inhibition of GLUL diminishes the isotopic enrichment of nitrogen into nucleotides, suppresses hepatomegaly and the growth of liver cancer cells. Consequently, Yap-driven liver growth is susceptible to nucleotide inhibition. Together, our findings demonstrate that Yap1 integrates the anabolic demands of tissue growth during development and tumorigenesis by reprogramming nitrogen metabolism to stimulate nucleotide biosynthesis
Geospatial Resolution of Human and Bacterial Diversity with City-Scale Metagenomics
The panoply of microorganisms and other species present in our environment influence human health and disease, especially in cities, but have not been profiled with metagenomics at a city-wide scale. We sequenced DNA from surfaces across the entire New York City (NYC) subway system, the Gowanus Canal, and public parks. Nearly half of the DNA (48%) does not match any known organism; identified organisms spanned 1,688 bacterial, viral, archaeal, and eukaryotic taxa, which were enriched for harmless genera associated with skin (e.g., Acinetobacter). Predicted ancestry of human DNA left on subway surfaces can recapitulate U.S. Census demographic data, and bacterial signatures can reveal a station’s history, such as marine-associated bacteria in a hurricane-flooded station. Some evidence of pathogens was found (Bacillus anthracis), but a lack of reported cases in NYC suggests that the pathogens represent a normal, urban microbiome. This baseline metagenomic map of NYC could help long-term disease surveillance, bioterrorism threat mitigation, and health management in the built environment of citie
Decoding Chromatin Accessibility Programs In Cancer
Chromatin accessibility plays an important role in defining cell identity and phenotype. With the emergence of novel methods like ATAC-seq, a sequencing method that maps regions of open chromatin and enables the computational analysis of transcription factor (TF) binding at chromatin accessible sites, we can start to dissect the regulatory landscape in cancer. I present two vignettes that use ATAC-seq to analyze the phenotypes of tumor: 1. Pancreatic cancer is expected to become the 2nd deadliest cancer by 2020 in the US, and few therapeutic options are currently available. Additionally, 50% of pancreatic cancer patients recur within just one year. Previous genomic analyses of pancreatic tumors, including somatic mutation mapping and gene expression profiling, did not explain this difference in recurrence. We hypothesized that epigenetic heterogeneity underlies previously described difference in recurrence. We sorted 54 fresh patient tumor samples based on EpCAM (an epithelial cell marker) to enrich for tumor cells and subjected them to ATAC-seq. Using supervised learning and generalized linear modeling, we were able to characterize the changes in RNA-seq and ATAC-seq between recurrent vs non-recurrent patients. We characterized TF motifs in accessible peaks across all samples and used ridge regression to identify differential TF activity enriched in recurrent patients. Two TF hits, ZSCAN1 and HNF1b, were experimentally validated to predict recurrence in our cohort and in an independent cohort. These results reveal a novel regulatory landscape in recurrent patients of pancreatic cancer and support the development of individualized therapies. 2. Approximately 70% of breast cancers express estrogen receptor (ER) and are treated with ER-blocking endocrine therapy (e.g. fulvestrant). Despite the efficacy of such treatments, resistance to anti-hormonal therapy remains a clinical challenge. We performed an epigenome-wide CRISPR knockout screen on MCF7 ER-positive breast cancer cells, and identified ARID1A to be the top candidate whose loss limits the sensitivity to fulvestrant. To uncover how ARID1A loss confers fulvestrant resistance, we undertook a chromatin-based approach. Analysis from ATAC-seq and RNA-seq assays showed that loss of ARID1A leads to a widespread chromatin remodeling of the breast cancer epigenome to regulate the binding of a series of TF that in concert alter gene expression profiles. This results in a switch from luminal cells to ER independent basal-like cells, which has adverse prognosis for patients on hormone therapy
Additional file 4: Figure S4. of ProteoModlR for functional proteomic analysis
Total ion current normalization corrects for technical variability across measurements in absence of isotopically encoded standards, as demonstrated on simulated data. (A) Quantitation across three replicate measurements of five peptides from a protein of interest (shades of red) and four peptides from reference proteins (shades of blue). (B) ProteoModlR corrects errors introduced by technical and biological variability. (C) Total ion current is also affected by technical variability. (D) If total ion current normalization is chosen, ProteoModlR equalizes the sum of the intensities of all peptides in each sample. (TIF 9017 kb