cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.1483474
title: Fostering Conceptual Understanding in Mathematical Statistics

description: In many undergraduate statistics programs, the two-semester calculus-based mathematical statistics sequence is the cornerstone of the curriculum. However, 10 years after the release of the Guidelines for the Assessment and Instruction in Statistics Education (GAISE) College Report, 2005, and the subsequent movement to stress conceptual understanding and foster active learning in statistics classrooms, the sequence still remains a traditional, lecture-intensive course. In this article, we discuss various instructional approaches, activities, and assessments that can be used to foster active learning and emphasize conceptual understanding while still covering the necessary theoretical content students need to be successful in subsequent statistics or actuarial science courses. In addition, we share student reflections on these course enhancements. The course revision we suggest doesn’t require substantial changes in content, so other mathematical statistics instructors can implement these strategies without sacrificing concepts in probability and inference that are fundamental to the needs of their students. Supplementary materials, including code used to generate class plots and activity handouts, are available online. Received December 2014. Revised June 2015.
DOI: 10.6084/m9.figshare.1483479.v2
title: The multicopy sRNA LhrC controls expression of the oligopeptide-binding protein OppA in <i>Listeria monocytogenes</i>

description: <i>Listeria monocytogenes</i> is the causative agent of the foodborne disease listeriosis. During infection, <i>L. monocytogenes</i> produces an array of non-coding RNAs, including the multicopy sRNA LhrC. These five, nearly identical sRNAs are highly induced in response to cell envelope stress and target the virulence adhesin <i>lapB</i> at the post-transcriptional level. Here, we demonstrate that LhrC controls expression of additional genes encoding cell envelope-associated proteins with virulence function. Using transcriptomics and proteomics, we identified a set of genes affected by LhrC in response to cell envelope stress. Three targets were significantly down-regulated by LhrC at both the RNA and protein level: <i>lmo2349, tcsA</i> and <i>oppA</i>. All three genes encode membrane-associated proteins: A putative substrate binding protein of an amino acid ABC transporter (Lmo2349); the CD4+ T cell-stimulating antigen TcsA, and the oligopeptide binding protein OppA, of which the latter 2 are required for full virulence of <i>L. monocytogenes</i>. For OppA, we show that LhrC acts by direct base paring to the ribosome binding site of the <i>oppA</i> mRNA, leading to an impediment of its translation and a decreased mRNA level. The sRNA-mRNA interaction depends on 2 of 3 CU-rich regions in LhrC allowing binding of 2 <i>oppA</i> mRNAs to a single LhrC molecule. Finally, we found that LhrC contributes to infection in macrophage-like cells. These findings demonstrate a central role for LhrC in controlling the level of OppA and other virulence-associated cell envelope proteins in response to cell envelope stress.
DOI: 10.6084/m9.figshare.1483473
title: Small RNA deep sequencing discriminates subsets of extracellular vesicles released by melanoma cells – Evidence of unique microRNA cargos

description: Melanoma cells release different types of extracellular vesicles (EVs) into the extracellular milieu that are involved with communication and signaling in the tumor microenvironment. Subsets of EVs include exosomes, microvesicles, and apoptotic bodies that carry protein and genetic (RNA) cargos. To define the contribution of the RNA cargo of melanoma cell derived EVs we performed small RNA sequencing to identify different small RNAs in the EV subsets. Using validated centrifugation protocols, we separated these EV subsets released by the melanoma cell line MML-1, and performed RNA sequencing with the Ion Torrent platform. Various, but different, non-coding RNAs were detected in the EV subsets, including microRNA, mitochondrial associated tRNA, small nucleolar RNA, small nuclear RNA, Ro associated Y-RNA, vault RNA and Y-RNA. We identified in total 1041 miRNAs in cells and EV subsets. Hierarchical clustering showed enrichment of specific miRNAs in exosomes, including hsa-miR-214-3p, hsa-miR-199a-3p and hsa-miR-155-5p, all being associated with melanoma progression. Comparison of exosomal miRNAs with miRNAs in clinical melanoma samples indicate that multiple miRNAs in exosomes also are expressed specifically in melanoma tissues, but not in benign naevi. This study shows for the first time the presence of distinct small RNAs in subsets of EVs released by melanoma cells, with significant similarities to clinical melanoma tissue, and provides unique insights into the contribution of EV associated extracellular RNA in cancer.
DOI: 10.6084/m9.figshare.1483477.v2
title: Rationally designed, heterologous <i>S. cerevisiae</i> transcripts expose novel expression determinants

description: Deducing generic causal relations between RNA transcript features and protein expression profiles from endogenous gene expression data remains a major unsolved problem in biology. The analysis of gene expression from heterologous genes contributes significantly to solving this problem, but has been heavily biased toward the study of the effect of 5′ transcript regions and to prokaryotes. Here, we employ a synthetic biology driven approach that systematically differentiates the effect of different regions of the transcript on gene expression up to 240 nucleotides into the ORF. This enabled us to discover new causal effects between features in previously unexplored regions of transcripts, and gene expression in natural regimes. We rationally designed, constructed, and analyzed 383 gene variants of the viral <i>HRSVgp04</i> gene ORF, with multiple synonymous mutations at key positions along the transcript in the eukaryote <i>S. cerevisiae</i>. Our results show that a few silent mutations at the 5′UTR can have a dramatic effect of up to 15 fold change on protein levels, and that even synonymous mutations in positions more than 120 nucleotides downstream from the ORF 5′end can modulate protein levels up to 160%–300%. We demonstrate that the correlation between protein levels and folding energy increases with the significance of the level of selection of the latter in endogenous genes, reinforcing the notion that selection for folding strength in different parts of the ORF is related to translation regulation. Our measured protein abundance correlates notably(correlation up to r = 0.62 (p=0.0013)) with mean relative codon decoding times, based on ribosomal densities (Ribo-Seq) in endogenous genes, supporting the conjecture that translation elongation and adaptation to the tRNA pool can modify protein levels in a causal/direct manner. This report provides an improved understanding of transcript evolution, design principles of gene expression regulation, and suggests simple rules for engineering synthetic gene expression in eukaryotes.
DOI: 10.6084/m9.figshare.1483479.v4
title: The multicopy sRNA LhrC controls expression of the oligopeptide-binding protein OppA in <i>Listeria monocytogenes</i>

description: <i>Listeria monocytogenes</i> is the causative agent of the foodborne disease listeriosis. During infection, <i>L. monocytogenes</i> produces an array of non-coding RNAs, including the multicopy sRNA LhrC. These five, nearly identical sRNAs are highly induced in response to cell envelope stress and target the virulence adhesin <i>lapB</i> at the post-transcriptional level. Here, we demonstrate that LhrC controls expression of additional genes encoding cell envelope-associated proteins with virulence function. Using transcriptomics and proteomics, we identified a set of genes affected by LhrC in response to cell envelope stress. Three targets were significantly down-regulated by LhrC at both the RNA and protein level: <i>lmo2349, tcsA</i> and <i>oppA</i>. All three genes encode membrane-associated proteins: A putative substrate binding protein of an amino acid ABC transporter (Lmo2349); the CD4+ T cell-stimulating antigen TcsA, and the oligopeptide binding protein OppA, of which the latter 2 are required for full virulence of <i>L. monocytogenes</i>. For OppA, we show that LhrC acts by direct base paring to the ribosome binding site of the <i>oppA</i> mRNA, leading to an impediment of its translation and a decreased mRNA level. The sRNA-mRNA interaction depends on 2 of 3 CU-rich regions in LhrC allowing binding of 2 <i>oppA</i> mRNAs to a single LhrC molecule. Finally, we found that LhrC contributes to infection in macrophage-like cells. These findings demonstrate a central role for LhrC in controlling the level of OppA and other virulence-associated cell envelope proteins in response to cell envelope stress.
DOI: 10.6084/m9.figshare.1483475.v1
title: A bacterial homologue YciH of eukaryotic translation initiation factor eIF1 regulates stress-related gene expression and is unlikely to be involved in translation initiation fidelity

description: YciH is a bacterial protein, homologous to eukaryotic translation initiation factor eIF1. Preceding evidence obtained with the aid of <i>in vitro</i> translation initiation system suggested that it may play a role of a translation initiation factor, ensuring selection against suboptimal initiation complexes. Here we studied the effect of <i>Escherichia coli yciH</i> gene inactivation on translation of model mRNAs. Neither the translation efficiency of leaderless mRNAs, nor mRNAs with non AUG start codons, was found to be affected by YciH <i>in vivo</i>. Comparative proteome analysis revealed that <i>yciH</i> gene knockout leads to a more than two-fold increase in expression of 66 genes and a more than two-fold decrease in the expression of 20 genes. Analysis of these gene sets allowed us to suggest a role of YciH as an inhibitor of translation in a stress response rather than the role of a translation initiation factor.
DOI: 10.6084/m9.figshare.1483477.v4
title: Rationally designed, heterologous <i>S. cerevisiae</i> transcripts expose novel expression determinants

description: Deducing generic causal relations between RNA transcript features and protein expression profiles from endogenous gene expression data remains a major unsolved problem in biology. The analysis of gene expression from heterologous genes contributes significantly to solving this problem, but has been heavily biased toward the study of the effect of 5′ transcript regions and to prokaryotes. Here, we employ a synthetic biology driven approach that systematically differentiates the effect of different regions of the transcript on gene expression up to 240 nucleotides into the ORF. This enabled us to discover new causal effects between features in previously unexplored regions of transcripts, and gene expression in natural regimes. We rationally designed, constructed, and analyzed 383 gene variants of the viral <i>HRSVgp04</i> gene ORF, with multiple synonymous mutations at key positions along the transcript in the eukaryote <i>S. cerevisiae</i>. Our results show that a few silent mutations at the 5′UTR can have a dramatic effect of up to 15 fold change on protein levels, and that even synonymous mutations in positions more than 120 nucleotides downstream from the ORF 5′end can modulate protein levels up to 160%–300%. We demonstrate that the correlation between protein levels and folding energy increases with the significance of the level of selection of the latter in endogenous genes, reinforcing the notion that selection for folding strength in different parts of the ORF is related to translation regulation. Our measured protein abundance correlates notably(correlation up to r = 0.62 (p=0.0013)) with mean relative codon decoding times, based on ribosomal densities (Ribo-Seq) in endogenous genes, supporting the conjecture that translation elongation and adaptation to the tRNA pool can modify protein levels in a causal/direct manner. This report provides an improved understanding of transcript evolution, design principles of gene expression regulation, and suggests simple rules for engineering synthetic gene expression in eukaryotes.
DOI: 10.6084/m9.figshare.1483479.v3
title: The multicopy sRNA LhrC controls expression of the oligopeptide-binding protein OppA in <i>Listeria monocytogenes</i>

description: <i>Listeria monocytogenes</i> is the causative agent of the foodborne disease listeriosis. During infection, <i>L. monocytogenes</i> produces an array of non-coding RNAs, including the multicopy sRNA LhrC. These five, nearly identical sRNAs are highly induced in response to cell envelope stress and target the virulence adhesin <i>lapB</i> at the post-transcriptional level. Here, we demonstrate that LhrC controls expression of additional genes encoding cell envelope-associated proteins with virulence function. Using transcriptomics and proteomics, we identified a set of genes affected by LhrC in response to cell envelope stress. Three targets were significantly down-regulated by LhrC at both the RNA and protein level: <i>lmo2349, tcsA</i> and <i>oppA</i>. All three genes encode membrane-associated proteins: A putative substrate binding protein of an amino acid ABC transporter (Lmo2349); the CD4+ T cell-stimulating antigen TcsA, and the oligopeptide binding protein OppA, of which the latter 2 are required for full virulence of <i>L. monocytogenes</i>. For OppA, we show that LhrC acts by direct base paring to the ribosome binding site of the <i>oppA</i> mRNA, leading to an impediment of its translation and a decreased mRNA level. The sRNA-mRNA interaction depends on 2 of 3 CU-rich regions in LhrC allowing binding of 2 <i>oppA</i> mRNAs to a single LhrC molecule. Finally, we found that LhrC contributes to infection in macrophage-like cells. These findings demonstrate a central role for LhrC in controlling the level of OppA and other virulence-associated cell envelope proteins in response to cell envelope stress.
DOI: 10.6084/m9.figshare.1483474.v2
title: Fostering Conceptual Understanding in Mathematical Statistics

description: In many undergraduate statistics programs, the two-semester calculus-based mathematical statistics sequence is the cornerstone of the curriculum. However, 10 years after the release of the Guidelines for the Assessment and Instruction in Statistics Education (GAISE) College Report, 2005, and the subsequent movement to stress conceptual understanding and foster active learning in statistics classrooms, the sequence still remains a traditional, lecture-intensive course. In this article, we discuss various instructional approaches, activities, and assessments that can be used to foster active learning and emphasize conceptual understanding while still covering the necessary theoretical content students need to be successful in subsequent statistics or actuarial science courses. In addition, we share student reflections on these course enhancements. The course revision we suggest doesn’t require substantial changes in content, so other mathematical statistics instructors can implement these strategies without sacrificing concepts in probability and inference that are fundamental to the needs of their students. Supplementary materials, including code used to generate class plots and activity handouts, are available online. Received December 2014. Revised June 2015.
DOI: 10.6084/m9.figshare.1483477.v3
title: Rationally designed, heterologous <i>S. cerevisiae</i> transcripts expose novel expression determinants

description: Deducing generic causal relations between RNA transcript features and protein expression profiles from endogenous gene expression data remains a major unsolved problem in biology. The analysis of gene expression from heterologous genes contributes significantly to solving this problem, but has been heavily biased toward the study of the effect of 5′ transcript regions and to prokaryotes. Here, we employ a synthetic biology driven approach that systematically differentiates the effect of different regions of the transcript on gene expression up to 240 nucleotides into the ORF. This enabled us to discover new causal effects between features in previously unexplored regions of transcripts, and gene expression in natural regimes. We rationally designed, constructed, and analyzed 383 gene variants of the viral <i>HRSVgp04</i> gene ORF, with multiple synonymous mutations at key positions along the transcript in the eukaryote <i>S. cerevisiae</i>. Our results show that a few silent mutations at the 5′UTR can have a dramatic effect of up to 15 fold change on protein levels, and that even synonymous mutations in positions more than 120 nucleotides downstream from the ORF 5′end can modulate protein levels up to 160%–300%. We demonstrate that the correlation between protein levels and folding energy increases with the significance of the level of selection of the latter in endogenous genes, reinforcing the notion that selection for folding strength in different parts of the ORF is related to translation regulation. Our measured protein abundance correlates notably(correlation up to r = 0.62 (p=0.0013)) with mean relative codon decoding times, based on ribosomal densities (Ribo-Seq) in endogenous genes, supporting the conjecture that translation elongation and adaptation to the tRNA pool can modify protein levels in a causal/direct manner. This report provides an improved understanding of transcript evolution, design principles of gene expression regulation, and suggests simple rules for engineering synthetic gene expression in eukaryotes.
DOI: 10.6084/m9.figshare.1483473.v1
title: Small RNA deep sequencing discriminates subsets of extracellular vesicles released by melanoma cells – evidence of unique microRNA cargos

description: <b>Background</b>: Melanoma cells release different types of extracellular vesicles (EVs) into the extracellular milieu that are involved with communication and signaling in the tumor microenvironment. Subsets of EVs include exosomes, microvesicles, and apoptotic bodies that carry protein and genetic (RNA) cargos.<b>Methods</b>: To define the contribution of the RNA cargo of melanoma cell derived EVs we performed small RNA sequencing to identify different small RNAs in the EV subsets. Using validated centrifugation protocols, we separated these EV subsets released by the melanoma cell line MML-1, and performed RNA sequencing with the Ion Torrent platform.<b>Results</b>: Various, but different, non-coding RNAs were detected in the EV subsets, including microRNA, mitochondrial associated transfer RNA, small nucleolar RNA, small nuclear RNA, Ro associated Y-RNA, vault RNA and Y-RNA. We identified in total 1041 miRNAs in cells and EV subsets. Hierarchical clustering showed enrichment of specific miRNAs in exosomes, including hsa-miR-214-3p, hsa-miR-199a-3p and hsa-miR-155-5p, all being associated with melanoma progression. Comparison of exosomal miRNAs with mi RNAs in clinical melanoma samples indicate that multiple miRNAs in exosomes also are expressed specifically in melanoma tissues, but not in benign naevi.<b>Conclusions</b>: This study shows for the first time the presence of distinct small RNAs in subsets of EVs released by melanoma cells, with significant similarities to clinical melanoma tissue, and provides unique insights into the contribution of EV associated extracellular RNA in cancer.
DOI: 10.6084/m9.figshare.1483474.v1
title: <b>Fostering Conceptual Understanding in Mathematical Statistics</b>

description: In many undergraduate statistics programs, the two-semester calculus-based mathematical statistics sequence is the cornerstone of the curriculum. However, ten years after the release of the Guidelines for the Assessment and Instruction in Statistics Education (GAISE) College Report (GAISE, 2005) and the subsequent movement to stress conceptual understanding and foster active learning in statistics classrooms, the sequence still remains a traditional, lecture-intensive course. In this paper, we discuss various instructional approaches, activities and assessments that can be used to foster active learning and emphasize conceptual understanding while still covering the necessary theoretical content students need to be successful in subsequent statistics or actuarial science courses. In addition, we share student reflections on these course enhancements. The course revision we suggest doesn’t require substantial changes in content, so other mathematical statistics instructors can implement these strategies without sacrificing concepts in probability and inference that are fundamental to the needs of their students. (<i>Note: Supplementary materials, including code used to generate class plots and activity handouts, are available online.</i>)
DOI: 10.6084/m9.figshare.1483475.v2
title: A bacterial homolog YciH of eukaryotic translation initiation factor eIF1 regulates stress-related gene expression and is unlikely to be involved in translation initiation fidelity

description: YciH is a bacterial protein, homologous to eukaryotic translation initiation factor eIF1. Preceding evidence obtained with the aid of <i>in vitro</i> translation initiation system suggested that it may play a role of a translation initiation factor, ensuring selection against suboptimal initiation complexes. Here we studied the effect of <i>Escherichia coli yciH</i> gene inactivation on translation of model mRNAs. Neither the translation efficiency of leaderless mRNAs, nor mRNAs with non AUG start codons, was found to be affected by YciH <i>in vivo</i>. Comparative proteome analysis revealed that <i>yciH</i> gene knockout leads to a more than fold2- increase in expression of 66 genes and a more than fold2- decrease in the expression of 20 genes. Analysis of these gene sets allowed us to suggest a role of YciH as an inhibitor of translation in a stress response rather than the role of a translation initiation factor.
DOI: 10.6084/m9.figshare.1483475.v4
title: A bacterial homolog YciH of eukaryotic translation initiation factor eIF1 regulates stress-related gene expression and is unlikely to be involved in translation initiation fidelity

description: YciH is a bacterial protein, homologous to eukaryotic translation initiation factor eIF1. Preceding evidence obtained with the aid of <i>in vitro</i> translation initiation system suggested that it may play a role of a translation initiation factor, ensuring selection against suboptimal initiation complexes. Here we studied the effect of <i>Escherichia coli yciH</i> gene inactivation on translation of model mRNAs. Neither the translation efficiency of leaderless mRNAs, nor mRNAs with non AUG start codons, was found to be affected by YciH <i>in vivo</i>. Comparative proteome analysis revealed that <i>yciH</i> gene knockout leads to a more than fold2- increase in expression of 66 genes and a more than fold2- decrease in the expression of 20 genes. Analysis of these gene sets allowed us to suggest a role of YciH as an inhibitor of translation in a stress response rather than the role of a translation initiation factor.