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1.  The oncogenic RNA-binding protein Musashi1 is regulated by HuR via mRNA translation and stability in glioblastoma cells 
Molecular Cancer Research  2012;10(1):143-155.
Musashi1 (Msi1) is an evolutionarily conserved RNA-binding protein (RBP) that has profound implications in cellular processes such as stem cell maintenance, nervous system development, and tumorigenesis. Msi1 is highly expressed in many cancers, including glioblastoma, while in normal tissues, its expression is restricted to stem cells. Unfortunately, the factors that modulate Msi1 expression and trigger high levels in tumors are largely unknown. Msi1 has a long 3′ untranslated region (UTR) containing several AU- and U-rich sequences. This type of sequence motif is often targeted by HuR, another important RBP known to be highly expressed in tumor tissue such as glioblastoma, and to regulate a variety of cancer-related genes. In this report, we demonstrate an interaction between HuR and the Msi1 3′ UTR, resulting in a positive regulation of Msi1 expression. We show that HuR increased MSI1 mRNA stability and promoted its translation. We also present evidence that expression of HuR and Msi1 correlate positively in glioblastoma lines. Finally, we show that inhibition of cell proliferation, increased apoptosis, and changes in cell cycle profile as a result of silencing HuR are partially rescued when Msi1 is ectopically expressed. In sum, our results suggest that HuR is an important regulator of Msi1 in glioblastoma and that this regulation has important biological consequences during gliomagenesis.
PMCID: PMC3265026  PMID: 22258704
Musashi1; HuR; ELAV; tumorigenesis; cancer; RNA-binding protein; glioblastoma
2.  Before It Gets Started: Regulating Translation at the 5′ UTR 
Translation regulation plays important roles in both normal physiological conditions and diseases states. This regulation requires cis-regulatory elements located mostly in 5′ and 3′ UTRs and trans-regulatory factors (e.g., RNA binding proteins (RBPs)) which recognize specific RNA features and interact with the translation machinery to modulate its activity. In this paper, we discuss important aspects of 5′ UTR-mediated regulation by providing an overview of the characteristics and the function of the main elements present in this region, like uORF (upstream open reading frame), secondary structures, and RBPs binding motifs and different mechanisms of translation regulation and the impact they have on gene expression and human health when deregulated.
PMCID: PMC3368165  PMID: 22693426
3.  A comprehensive in silico expression analysis of RNA binding proteins in normal and tumor tissue 
RNA biology  2009;6(4):426-433.
RNA binding proteins (RBPs) are involved in several post-transcriptional stages of gene expression and dictate the quality and quantity of the cellular proteome. When aberrantly expressed, they can lead to disease states as well as cancers. A basic requirement to understand their role in normal tissue development and cancer is the build of comprehensive gene expression maps. In this direction, we generated a list with 383 human RBPs based on the NCBI and EMSEMBL databases. SAGE and MPSS were then used to verify their levels of expression in normal tissues while SAGE and microarray datasets were used to perform comparisons between normal and tumor tissues. As main outcomes of our studies, we identified clusters of co-expressed or co-regulated genes that could act together in the development and maintenance of specific tissues; we also obtained a high confidence list of RBPs aberrantly expressed in several tumor types. This later list contains potential candidates to be explored as diagnostic and prognostic markers as well as putative targets for cancer therapy approaches.
PMCID: PMC2935330  PMID: 19458496
RNA binding proteins; post-transcriptional regulation; SAGE; MPSS; oncogenomics; cancer; gene expression analysis
4.  Over-represented sequences located on 3' UTRs are potentially involved in regulatory functions 
RNA biology  2008;5(4):255-262.
Eukaryotic gene expression must be coordinated for the proper functioning of biological processes. This coordination can be achieved both at the transcriptional and post-transcriptional levels. In both cases, regulatory sequences placed at either promoter regions or on UTRs function as markers recognized by regulators that can then activate or repress different groups of genes according to necessity. While regulatory sequences involved in transcription are quite well documented, there is a lack of information on sequence elements involved in post-transcriptional regulation. We used a statistical over-representation method to identify novel regulatory elements located on UTRs. An exhaustive search approach was used to calculate the frequency of all possible n-mers (short nucleotide sequences) in 16,160 human genes of NCBI RefSeq sequences and to identify any peculiar usage of n-mers on UTRs. After a stringent filtering process, we identified 2,772 highly over-represented n-mers on 3' UTRs. We provide evidence that these n-mers are potentially involved in regulatory functions. Identified n-mers overlap with previously identified binding sites for HuR and TIA-1 and, ARE and GRE sequences. We determine also that n-mers overlap with predicted miRNA target sites. Finally, a method to cluster n-mer groups allowed the identification of putative gene networks.
PMCID: PMC2732352  PMID: 18971640
3' UTR; post-transcriptional regulation; regulatory sequences; RNA binding proteins; gene networks; translation; mRNA stability
5.  Leveraging cross-link modification events in CLIP-seq for motif discovery 
Nucleic Acids Research  2014;43(1):95-103.
High-throughput protein–RNA interaction data generated by CLIP-seq has provided an unprecedented depth of access to the activities of RNA-binding proteins (RBPs), the key players in co- and post-transcriptional regulation of gene expression. Motif discovery forms part of the necessary follow-up data analysis for CLIP-seq, both to refine the exact locations of RBP binding sites, and to characterize them. The specific properties of RBP binding sites, and the CLIP-seq methods, provide additional information not usually present in the classic motif discovery problem: the binding site structure, and cross-linking induced events in reads. We show that CLIP-seq data contains clear secondary structure signals, as well as technology- and RBP-specific cross-link signals. We introduce Zagros, a motif discovery algorithm specifically designed to leverage this information and explore its impact on the quality of recovered motifs. Our results indicate that using both secondary structure and cross-link modifications can greatly improve motif discovery on CLIP-seq data. Further, the motifs we recover provide insight into the balance between sequence- and structure-specificity struck by RBP binding.
PMCID: PMC4288180  PMID: 25505146
6.  Translation regulation gets its ‘omics’ moment 
The fate of cellular RNA is largely determined by complex networks of protein-RNA interactions through ribonucleoprotein (RNPs) complexes. Despite their relatively short half-life, transcripts associate with many different proteins that process, modify, translate, and degrade the RNA. Following biogenesis some mRNPs are immediately directed to translation and produce proteins, but many are diverted and regulated by processes including miRNA-mediated mechanisms, transport and localization as well as turnover. Because of this complex interplay estimates of steady state expression by methods such as RNAseq alone cannot capture critical aspects of cellular fate, environmental response, tumorigenesis or gene expression regulation. More selective and integrative tools are needed to measure protein-RNA complexes and the regulatory processes involved. One focus area are measurements of the transcriptome associated with ribosomes and translation. These so-called polysome or ribosome profiling techniques can evaluate translation efficiency as well as the interplay between translation initiation, elongation and termination - subject areas not well understood at a systems biology level. Ribosome profiling is a highly promising technique which provides mRNA positional information of ribosome occupancy, potentially bridging the gap between gene expression (i.e. RNAseq and microarray analysis) and protein quantification (i.e. mass spectrometry). In combination with methods such as RNA immunoprecipitation, miRNA profiling, or proteomics, we obtain a fresh view of global post-transcriptional and translational gene regulation. In addition, these techniques also provide new insight into new regulatory elements, such as alternative open reading frames, and translation regulation under different conditions.
PMCID: PMC3797170  PMID: 23677826
Ribosome footprinting; polysome profile; RNA-seq; next-generation sequencing; RIP-seq
7.  Global signatures of protein and mRNA expression levels† 
Molecular bioSystems  2009;5(12):1512-1526.
Cellular states are determined by differential expression of the cell’s proteins. The relationship between protein and mRNA expression levels informs about the combined outcomes of translation and protein degradation which are, in addition to transcription and mRNA stability, essential contributors to gene expression regulation. This review summarizes the state of knowledge about large-scale measurements of absolute protein and mRNA expression levels, and the degree of correlation between the two parameters. We summarize the information that can be derived from comparison of protein and mRNA expression levels and discuss how corresponding sequence characteristics suggest modes of regulation.
PMCID: PMC4089977  PMID: 20023718
8.  A compendium of RNA-binding motifs for decoding gene regulation 
Nature  2013;499(7457):172-177.
RNA-binding proteins are key regulators of gene expression, yet only a small fraction have been functionally characterized. Here we report a systematic analysis of the RNA motifs recognized by RNA-binding proteins, encompassing 205 distinct genes from 24 diverse eukaryotes. The sequence specificities of RNA-binding proteins display deep evolutionary conservation, and the recognition preferences for a large fraction of metazoan RNA-binding proteins can thus be inferred from their RNA-binding domain sequence. The motifs that we identify in vitro correlate well with in vivo RNA-binding data. Moreover, we can associate them with distinct functional roles in diverse types of post-transcriptional regulation, enabling new insights into the functions of RNA-binding proteins both in normal physiology and in human disease. These data provide an unprecedented overview of RNA-binding proteins and their targets, and constitute an invaluable resource for determining post-transcriptional regulatory mechanisms in eukaryotes.
PMCID: PMC3929597  PMID: 23846655
9.  Genomic Analyses Reveal Broad Impact of miR-137 on Genes Associated with Malignant Transformation and Neuronal Differentiation in Glioblastoma Cells 
PLoS ONE  2014;9(1):e85591.
miR-137 plays critical roles in the nervous system and tumor development; an increase in its expression is required for neuronal differentiation while its reduction is implicated in gliomagenesis. To evaluate the potential of miR-137 in glioblastoma therapy, we conducted genome-wide target mapping in glioblastoma cells by measuring the level of association between PABP and mRNAs in cells transfected with miR-137 mimics vs. controls via RIPSeq. Impact on mRNA levels was also measured by RNASeq. By combining the results of both experimental approaches, 1468 genes were found to be negatively impacted by miR-137 – among them, 595 (40%) contain miR-137 predicted sites. The most relevant targets include oncogenic proteins and key players in neurogenesis like c-KIT, YBX1, AKT2, CDC42, CDK6 and TGFβ2. Interestingly, we observed that several identified miR-137 targets are also predicted to be regulated by miR-124, miR-128 and miR-7, which are equally implicated in neuronal differentiation and gliomagenesis. We suggest that the concomitant increase of these four miRNAs in neuronal stem cells or their repression in tumor cells could produce a robust regulatory effect with major consequences to neuronal differentiation and tumorigenesis.
PMCID: PMC3899048  PMID: 24465609
10.  Site identification in high-throughput RNA–protein interaction data 
Bioinformatics  2012;28(23):3013-3020.
Motivation: Post-transcriptional and co-transcriptional regulation is a crucial link between genotype and phenotype. The central players are the RNA-binding proteins, and experimental technologies [such as cross-linking with immunoprecipitation- (CLIP-) and RIP-seq] for probing their activities have advanced rapidly over the course of the past decade. Statistically robust, flexible computational methods for binding site identification from high-throughput immunoprecipitation assays are largely lacking however.
Results: We introduce a method for site identification which provides four key advantages over previous methods: (i) it can be applied on all variations of CLIP and RIP-seq technologies, (ii) it accurately models the underlying read-count distributions, (iii) it allows external covariates, such as transcript abundance (which we demonstrate is highly correlated with read count) to inform the site identification process and (iv) it allows for direct comparison of site usage across cell types or conditions.
Availability and implementation: We have implemented our method in a software tool called Piranha. Source code and binaries, licensed under the GNU General Public License (version 3) are freely available for download from
Supplementary information: Supplementary data available at Bioinformatics online.
PMCID: PMC3509493  PMID: 23024010
11.  The RNA-Binding Protein Musashi1: A Major Player in Intestinal Epithelium Renewal and Colon Cancer Development 
Aberrant gene expression is the cause and the consequence of tumorigenesis. A major component of gene expression is translation regulation; a process whose main players are RNA-binding-proteins (RBPs). More than 800 RBPs have been identified in the human genome and several of them have been shown to control gene networks associated with relevant cancer processes. A more systematic characterization of RBPs starts to reveal that similar to transcription factors, they can function as tumor suppressors or oncogenes. A relevant example is Musashi1 (Msi1), which is emerging as a critical regulator of tumorigenesis in multiple cancer types, including colon cancer. Msi1 is a stem marker in several tissues and is critical in maintaining the balance between self-renewal and differentiation. However, a boost in Msi1 expression can most likely lead cells towards an oncogenic pathway. In this article, we discuss the parallels between Msi1 function in normal renewal of intestinal epithelium and in colon cancer.
PMCID: PMC3728701  PMID: 23914149
Colon cancer; Musashi1; Translation regulation; RNA-binding proteins
12.  Musashi1 as a potential therapeutic target and diagnostic marker for lung cancer 
Oncotarget  2013;4(5):739-750.
Lung cancer remains one of the leading causes of cancer-related deaths worldwide with a 5-year survival rate of less than 20%. One approach to improving survival is the identification of biomarkers to detect early stage disease. In this study, we investigated the potential of the stem cell and progenitor cell marker, Musashi1 (Msi1), as a diagnostic marker and potential therapeutic target for lung cancer. Functional studies in A549 bronchioalveolar carcinoma and NCI-H520 squamous cell carcinoma cells revealed that Msi1 was enriched in spheroid cultures of tumor cells and in the CD133+ cell population. Downregulation of Msi1 by lentivirus-mediated expression of an Msi1 shRNA reduced spheroid colony proliferation. Growth inhibition was associated with reduced nuclear localization of β-catenin and inhibition of the processing of intracellular Notch. In primary lung cancer, Msi1 protein expression was elevated in 86% of 202 tissue microarray specimens, and Msi1 mRNA was increased in 80% of 118 bronchoscopic biopsies, including metastatic disease, but was rarely detected in adjacent normal lung tissue and in non-malignant diseased tissue. Msi1 was expressed in a diffuse pattern in most tumor subtypes, except in squamous cell carcinomas, where it appeared in a focal pattern in 50% of specimens. Thus, Msi1 is a sensitive and specific diagnostic marker for all lung cancer subtypes.
PMCID: PMC3742834  PMID: 23715514
Musashi1; lung cancer; shRNA; β-catenin; notch; numb
The annals of applied statistics  2011;5(1):364-380.
Alternative splicing of gene transcripts greatly expands the functional capacity of the genome, and certain splice isoforms may indicate specific disease states such as cancer. Splice junction microarrays interrogate thousands of splice junctions, but data analysis is difficult and error prone because of the increased complexity compared to differential gene expression analysis. We present Rank Change Detection (RCD) as a method to identify differential splicing events based upon a straightforward probabilistic model comparing the over- or underrepresentation of two or more competing isoforms. RCD has advantages over commonly used methods because it is robust to false positive errors due to nonlinear trends in microarray measurements. Further, RCD does not depend on prior knowledge of splice isoforms, yet it takes advantage of the inherent structure of mutually exclusive junctions, and it is conceptually generalizable to other types of splicing arrays or RNA-Seq. RCD specifically identifies the biologically important cases when a splice junction becomes more or less prevalent compared to other mutually exclusive junctions. The example data is from different cell lines of glioblastoma tumors assayed with Agilent microarrays.
PMCID: PMC3546815  PMID: 23335951
Alternative splicing; gene expression analysis; microarray
14.  MicroRNA-16 and MicroRNA-424 regulate cell-autonomous angiogenic functions in endothelial cells via targeting VEGFR2 and FGFR1 
microRNAs play key roles in modulating a variety of cellular processes by post-transcriptional regulation of their target genes. VEGF, VEGFR-2 and FGFR-1 were identified by bioinformatic approaches and subsequently validated as targets of miR-16 and miR-424 in endothelial cells (ECs).
Mimetics of these microRNAs reduced VEGF, VEGFR-2 and FGFR-1 expression, whereas specific antagonists enhanced their expression. Expression of mature miR-16 and miR-424 was up-regulated upon VEGF or bFGF treatment. This up-regulation was accompanied by a parallel increase in pri-miR-16-1 and pri-miR-16-2 but not in pri-miR-424 levels, indicating a VEGF/bFGF-dependent transcriptional and post-transcriptional regulation of miR-16 and miR-424, respectively. Reduced expression of VEGFR2 and FGFR1 by miR-16 or miR-424 overexpression regulated VEGF and bFGF signaling through these receptors, thereby affecting the activity of downstream components of the pathways. Functionally, miR-16 or miR-424 overexpression reduced proliferation, migration and cord formation of ECs in vitro and, lentiviral overexpression of miR-16 reduced the ability of ECs to form blood vessels in vivo.
We conclude that these miRNAs finely tune the expression of selected endothelial angiogenic mediators in response to these growth factors. Altogether, these findings suggest that miR-16 and miR-424 play important roles in regulating cell-intrinsic angiogenic activity of ECs.
PMCID: PMC3226744  PMID: 21885851
15.  Sequence signatures and mRNA concentration can explain two-thirds of protein abundance variation in a human cell line 
We provide a large-scale dataset on absolute protein and matching mRNA concentrations from the human medulloblastoma cell line Daoy. The correlation between mRNA and protein concentrations is significant and positive (Rs=0.46, R2=0.29, P-value<2e16), although non-linear.Out of ∼200 tested sequence features, sequence length, frequency and properties of amino acids, as well as translation initiation-related features are the strongest individual correlates of protein abundance when accounting for variation in mRNA concentration.When integrating mRNA expression data and all sequence features into a non-parametric regression model (Multivariate Adaptive Regression Splines), we were able to explain up to 67% of the variation in protein concentrations. Half of the contributions were attributed to mRNA concentrations, the other half to sequence features relating to regulation of translation and protein degradation. The sequence features are primarily linked to the coding and 3′ untranslated region. To our knowledge, this is the most comprehensive predictive model of human protein concentrations achieved so far.
mRNA decay, translation regulation and protein degradation are essential parts of eukaryotic gene expression regulation (Hieronymus and Silver, 2004; Mata et al, 2005), which enable the dynamics of cellular systems and their responses to external and internal stimuli without having to rely exclusively on transcription regulation. The importance of these processes is emphasized by the generally low correlation between mRNA and protein concentrations. For many prokaryotic and eukaryotic organisms, <50% of variation in protein abundance variation is explained by variation in mRNA concentrations (de Sousa Abreu et al, 2009).
Given the plethora of regulatory mechanisms involved, most studies have focused so far on individual regulators and specific targets. Particularly in human, we currently lack system-wide, quantitative analyses that evaluate the relative contribution of regulatory elements encoded in the mRNA and protein sequence. Existing studies have been carried out only in bacteria and yeast (Nie et al, 2006; Brockmann et al, 2007; Tuller et al, 2007; Wu et al, 2008). Here, we present the first comprehensive analysis on the impact of translation and protein degradation on protein abundance variation in a human cell line. For this purpose, we experimentally measured absolute protein and mRNA concentrations in the Daoy medulloblastoma cell line, using shotgun proteomics and microarrays, respectively (Figure 1). These data comprise one of the largest such sets available today for human. We focused on sequence features that likely impact protein translation and protein degradation, including length, nucleotide composition, structure of the untranslated regions (UTRs), coding sequence, composition of the translation initiation site, presence of upstream open reading frames putative target sites of miRNAs, codon usage, amino-acid composition and protein degradation signals.
Three types of tests have been conducted: (a) we examined partial Spearman's rank correlation of numerical features (e.g. length) with protein concentration, accounting for variation in mRNA concentrations; (b) for numerical and categorical features (e.g. function), we compared two extreme populations with Welch's t-test and (c) using a Multivariate Adaptive Regression Splines model, we analyzed the combined contributions of mRNA expression and sequence features to protein abundance variation (Figure 1). To account for the non-linearity of many relationships, we use non-parametric approaches throughout the analysis.
We observed a significant positive correlation between mRNA and protein concentrations, larger than many previous measurements (de Sousa Abreu et al, 2009). We also show that the contribution of translation and protein degradation is at least as important as the contribution of mRNA transcription and stability to the abundance variation of the final protein products. Although variation in mRNA expression explains ∼25–30% of the variation in protein abundance, another 30–40% can be accounted for by characteristics of the sequences, which we identified in a comparative assessment of global correlates. Among these characteristics, sequence length, amino-acid frequencies and also nucleotide frequencies in the coding region are of strong influence (Figure 3A). Characteristics of the 3′UTR and of the 5′UTR, that is length, nucleotide composition and secondary structures, describe another part of the variation, leaving 33% expression variation unexplained. The unexplained fraction may be accounted for by mechanisms not considered in this analysis (e.g. regulation by RNA-binding proteins or gene-specific structural motifs), as well as expression and measurement noise.
Our combined model including mRNA concentration and sequence features can explain 67% of the variation of protein abundance in this system—and thus has the highest predictive power for human protein abundance achieved so far (Figure 3B).
Transcription, mRNA decay, translation and protein degradation are essential processes during eukaryotic gene expression, but their relative global contributions to steady-state protein concentrations in multi-cellular eukaryotes are largely unknown. Using measurements of absolute protein and mRNA abundances in cellular lysate from the human Daoy medulloblastoma cell line, we quantitatively evaluate the impact of mRNA concentration and sequence features implicated in translation and protein degradation on protein expression. Sequence features related to translation and protein degradation have an impact similar to that of mRNA abundance, and their combined contribution explains two-thirds of protein abundance variation. mRNA sequence lengths, amino-acid properties, upstream open reading frames and secondary structures in the 5′ untranslated region (UTR) were the strongest individual correlates of protein concentrations. In a combined model, characteristics of the coding region and the 3′UTR explained a larger proportion of protein abundance variation than characteristics of the 5′UTR. The absolute protein and mRNA concentration measurements for >1000 human genes described here represent one of the largest datasets currently available, and reveal both general trends and specific examples of post-transcriptional regulation.
PMCID: PMC2947365  PMID: 20739923
gene expression regulation; protein degradation; protein stability; translation
16.  Mining gene functional networks to improve mass-spectrometry-based protein identification 
Bioinformatics  2009;25(22):2955-2961.
Motivation: High-throughput protein identification experiments based on tandem mass spectrometry (MS/MS) often suffer from low sensitivity and low-confidence protein identifications. In a typical shotgun proteomics experiment, it is assumed that all proteins are equally likely to be present. However, there is often other evidence to suggest that a protein is present and confidence in individual protein identification can be updated accordingly.
Results: We develop a method that analyzes MS/MS experiments in the larger context of the biological processes active in a cell. Our method, MSNet, improves protein identification in shotgun proteomics experiments by considering information on functional associations from a gene functional network. MSNet substantially increases the number of proteins identified in the sample at a given error rate. We identify 8–29% more proteins than the original MS experiment when applied to yeast grown in different experimental conditions analyzed on different MS/MS instruments, and 37% more proteins in a human sample. We validate up to 94% of our identifications in yeast by presence in ground-truth reference sets.
Availability and Implementation: Software and datasets are available at
Supplementary information: Supplementary data are available at Bioinformatics online.
PMCID: PMC2773251  PMID: 19633097
17.  Integrating shotgun proteomics and mRNA expression data to improve protein identification 
Bioinformatics  2009;25(11):1397-1403.
Motivation: Tandem mass spectrometry (MS/MS) offers fast and reliable characterization of complex protein mixtures, but suffers from low sensitivity in protein identification. In a typical shotgun proteomics experiment, it is assumed that all proteins are equally likely to be present. However, there is often other information available, e.g. the probability of a protein's presence is likely to correlate with its mRNA concentration.
Results: We develop a Bayesian score that estimates the posterior probability of a protein's presence in the sample given its identification in an MS/MS experiment and its mRNA concentration measured under similar experimental conditions. Our method, MSpresso, substantially increases the number of proteins identified in an MS/MS experiment at the same error rate, e.g. in yeast, MSpresso increases the number of proteins identified by ∼40%. We apply MSpresso to data from different MS/MS instruments, experimental conditions and organisms (Escherichia coli, human), and predict 19–63% more proteins across the different datasets. MSpresso demonstrates that incorporating prior knowledge of protein presence into shotgun proteomics experiments can substantially improve protein identification scores.
Availability and Implementation: Software is available upon request from the authors. Mass spectrometry datasets and supplementary information are available from
Supplementary Information: Supplementary data website:
PMCID: PMC2682515  PMID: 19318424
18.  A Two-Phase Innate Host Response to Alphavirus Infection Identified by mRNP-Tagging In Vivo 
PLoS Pathogens  2007;3(12):e199.
A concept fundamental to viral pathogenesis is that infection induces specific changes within the host cell, within specific tissues, or within the entire animal. These changes are reflected in a cascade of altered transcription patterns evident during infection. However, elucidation of this cascade in vivo has been limited by a general inability to distinguish changes occurring in the minority of infected cells from those in surrounding uninfected cells. To circumvent this inherent limitation of traditional gene expression profiling methods, an innovative mRNP-tagging technique was implemented to isolate host mRNA specifically from infected cells in vitro as well as in vivo following Venezuelan equine encephalitis virus (VEE) infection. This technique facilitated a direct characterization of the host defense response specifically within the first cells infected with VEE, while simultaneous total RNA analysis assessed the collective response of both the infected and uninfected cells. The result was a unique, multifaceted profile of the early response to VEE infection in primary dendritic cells, as well as in the draining lymph node, the initially targeted tissue in the mouse model. A dynamic environment of complex interactions was revealed, and suggested a two-step innate response in which activation of a subset of host genes in infected cells subsequently leads to activation of the surrounding uninfected cells. Our findings suggest that the application of viral mRNP-tagging systems, as introduced here, will facilitate a much more detailed understanding of the highly coordinated host response to infectious agents.
Author Summary
A major element of viral pathogenesis is the induction of specific changes within the infected host, often reflected in altered gene expression patterns. However, revealing these changes in vivo has been limited by an inability to distinguish changes within the minority of infected cells from that in surrounding uninfected cells. Here we introduce a viral mRNP-tagging system, based on Venezuelan equine encephalitis virus (VEE), that enables the isolation of host mRNA specifically from infected cells in vitro and in vivo, even when they are a small minority. This system allowed us for the first time to monitor the innate response specifically within the cells initially infected in vivo. In combination with simultaneous analysis of the entire tissue response, the result was a multifaceted view of the innate response to VEE in dendritic cells, and in the draining lymph node. The results supported a two-step response in which activation of host genes within infected cells leads to activation of bystander cells, offering insight into the process by which the greater innate immune response to alphaviruses is established in vivo. This system may be employed for a wide variety of pathogens, offering broader implications to the manner in which interactions between pathogens and their hosts are studied.
PMCID: PMC2151086  PMID: 18215114
19.  RNA Binding Protein Sex-Lethal (Sxl) and Control of Drosophila Sex Determination and Dosage Compensation 
In the past two decades, scientists have elucidated the molecular mechanisms behind Drosophila sex determination and dosage compensation. These two processes are controlled essentially by two different sets of genes, which have in common a master regulatory gene, Sex-lethal (Sxl). Sxl encodes one of the best-characterized members of the family of RNA binding proteins. The analysis of different mechanisms involved in the regulation of the three identified Sxl target genes (Sex-lethal itself, transformer, and male specific lethal-2) has contributed to a better understanding of translation repression, as well as constitutive and alternative splicing. Studies using the Drosophila system have identified the features of the protein that contribute to its target specificity and regulatory functions. In this article, we review the existing data concerning Sxl protein, its biological functions, and the regulation of its target genes.
PMCID: PMC193869  PMID: 12966139
20.  Switch in 3′ Splice Site Recognition between Exon Definition and Splicing Catalysis Is Important for Sex-lethal Autoregulation 
Molecular and Cellular Biology  2001;21(6):1986-1996.
Maintenance of female sexual identity in Drosophila melanogaster involves an autoregulatory loop in which the protein Sex-lethal (SXL) promotes skipping of exon 3 from its own pre-mRNA. We have used transient transfection of Drosophila Schneider cells to analyze the role of exon 3 splice sites in regulation. Our results indicate that exon 3 repression requires competition between the 5′ splice sites of exons 2 and 3 but is independent of their relative strength. Two 3′ splice site AG's precede exon 3. We report here that, while the distal site plays a critical role in defining the exon, the proximal site is preferentially used for the actual splicing reaction, arguing for a switch in 3′ splice site recognition between exon definition and splicing catalysis. Remarkably, the presence of the two 3′ splice sites is important for the efficient regulation by SXL, suggesting that SXL interferes with molecular events occurring between initial splice site communication across the exon and the splice site pairing that leads to intron removal.
PMCID: PMC86793  PMID: 11238934

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