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author:("gosling, Mark")
1.  Identification of tubular injury microRNA biomarkers in urine: comparison of next-generation sequencing and qPCR-based profiling platforms 
BMC Genomics  2014;15(1):485.
Background
MicroRNAs (miRNAs) are small, non-coding RNAs that regulate protein levels post-transcriptionally. miRNAs play important regulatory roles in many cellular processes and have been implicated in several diseases. Recent studies have reported significant levels of miRNAs in a variety of body fluids, raising the possibility that miRNAs could serve as useful biomarkers. Next-generation sequencing (NGS) is increasingly employed in biomedical investigations. Although concordance between this platform and qRT-PCR based assays has been reported in high quality specimens, information is lacking on comparisons in biofluids especially urine. Here we describe the changes in miRNA expression patterns in a rodent model of renal tubular injury (gentamicin). Our aim is to compare RNA sequencing and qPCR based miRNA profiling in urine specimen from control and rats with confirmed tubular injury.
Results
Our preliminary examination of the concordance between miRNA-seq and qRT-PCR in urine specimen suggests minimal agreement between platforms probably due to the differences in sensitivity. Our results suggest that although miRNA-seq has superior specificity, it may not detect low abundant miRNAs in urine samples. Specifically, miRNA-seq did not detect some sequences which were identified by qRT-PCR. On the other hand, the qRT-PCR analysis was not able to detect the miRNA isoforms, which made up the majority of miRNA changes detected by NGS.
Conclusions
To our knowledge, this is the first time that miRNA profiling platforms including NGS have been compared in urine specimen. miRNAs identified by both platforms, let-7d, miR-203, and miR-320, may potentially serve as promising novel urinary biomarkers for drug induced renal tubular epithelial injury.
doi:10.1186/1471-2164-15-485
PMCID: PMC4079956  PMID: 24942259
Next-generation sequencing; NGS; Small RNA; TruSeq; qRT-PCR; Urine; miRNA; Gentamicin; Kidney injury
2.  Transcriptomic analysis of genetically defined autism candidate genes reveals common mechanisms of action 
Molecular Autism  2013;4:45.
Background
Austism spectrum disorder (ASD) is a heterogeneous behavioral disorder or condition characterized by severe impairment of social engagement and the presence of repetitive activities. The molecular etiology of ASD is still largely unknown despite a strong genetic component. Part of the difficulty in turning genetics into disease mechanisms and potentially new therapeutics is the sheer number and diversity of the genes that have been associated with ASD and ASD symptoms. The goal of this work is to use shRNA-generated models of genetic defects proposed as causative for ASD to identify the common pathways that might explain how they produce a core clinical disability.
Methods
Transcript levels of Mecp2, Mef2a, Mef2d, Fmr1, Nlgn1, Nlgn3, Pten, and Shank3 were knocked-down in mouse primary neuron cultures using shRNA constructs. Whole genome expression analysis was conducted for each of the knockdown cultures as well as a mock-transduced culture and a culture exposed to a lentivirus expressing an anti-luciferase shRNA. Gene set enrichment and a causal reasoning engine was employed to identify pathway level perturbations generated by the transcript knockdown.
Results
Quantification of the shRNA targets confirmed the successful knockdown at the transcript and protein levels of at least 75% for each of the genes. After subtracting out potential artifacts caused by viral infection, gene set enrichment and causal reasoning engine analysis showed that a significant number of gene expression changes mapped to pathways associated with neurogenesis, long-term potentiation, and synaptic activity.
Conclusions
This work demonstrates that despite the complex genetic nature of ASD, there are common molecular mechanisms that connect many of the best established autism candidate genes. By identifying the key regulatory checkpoints in the interlinking transcriptional networks underlying autism, we are better able to discover the ideal points of intervention that provide the broadest efficacy across the diverse population of autism patients.
doi:10.1186/2040-2392-4-45
PMCID: PMC4176301  PMID: 24238429
3.  GenSensor Suite: A Web-Based Tool for the Analysis of Gene and Protein Interactions, Pathways, and Regulation 
Advances in Bioinformatics  2011;2011:271563.
The GenSensor Suite consists of four web tools for elucidating relationships among genes and proteins. GenPath results show which biochemical, regulatory, or other gene set categories are over- or under-represented in an input list compared to a background list. All common gene sets are available for searching in GenPath, plus some specialized sets. Users can add custom background lists. GenInteract builds an interaction gene list from a single gene input and then analyzes this in GenPath. GenPubMed uses a PubMed query to identify a list of PubMed IDs, from which a gene list is extracted and queried in GenPath. GenViewer allows the user to query one gene set against another in GenPath. GenPath results are presented with relevant P- and q-values in an uncluttered, fully linked, and integrated table. Users can easily copy this table and paste it directly into a spreadsheet or document.
doi:10.1155/2011/271563
PMCID: PMC3238354  PMID: 22194743
4.  Spatial mapping of thymic stromal microenvironments reveals unique features influencing T lymphoid differentiation 
Immunity  2009;31(6):999-1009.
Summary
Interaction of hematopoietic progenitors with the thymic stromal microenvironment induces them to proliferate, adopt the T cell fate, and asymmetrically diverge into multiple T lineages. Progenitors at various developmental stages are stratified among different regions of the thymus, implying that the corresponding microenvironments differ from one another, and provide unique sets of signals to progenitors migrating between them. The nature of these differences remains undefined. Here we use novel physical and computational approaches to characterize these stromal subregions, distinguishing gene expression in microdissected tissues from that of their lymphoid constituents. Using this approach, we comprehensively map gene expression in functionally distinct stromal microenvironments, and identify clusters of genes that define each region. Quite unexpectedly, we find that the central cortex lacks distinctive features of its own, and instead appears to function by sequestering unique microenvironments found at the cortical extremities, and modulating the relative proximity of progenitors moving between them.
doi:10.1016/j.immuni.2009.09.024
PMCID: PMC2807413  PMID: 20064453
5.  The Role of Hypoxia in 2-Butoxyethanol–Induced Hemangiosarcoma 
Toxicological Sciences  2009;113(1):254-266.
To understand the molecular mechanisms underlying compound-induced hemangiosarcomas in mice, and therefore, their human relevance, a systems biology approach was undertaken using transcriptomics and Causal Network Modeling from mice treated with 2-butoxyethanol (2-BE). 2-BE is a hemolytic agent that induces hemangiosarcomas in mice. We hypothesized that the hemolysis induced by 2-BE would result in local tissue hypoxia, a well-documented trigger for endothelial cell proliferation leading to hemangiosarcoma. Gene expression data from bone marrow (BM), liver, and spleen of mice exposed to a single dose (4 h) or seven daily doses of 2-BE were used to develop a mechanistic model of hemangiosarcoma. The resulting mechanistic model confirms previous work proposing that 2-BE induces macrophage activation and inflammation in the liver. In addition, the model supports local tissue hypoxia in the liver and spleen, coupled with increased erythropoeitin signaling and erythropoiesis in the spleen and BM, and suppression of mechanisms that contribute to genomic stability, events that could be contributing factors to hemangiosarcoma formation. Finally, an immunohistochemistry method (Hypoxyprobe) demonstrated that tissue hypoxia was present in the spleen and BM. Together, the results of this study identify molecular mechanisms that initiate hemangiosarcoma, a key step in understanding safety concerns that can impact drug decision processes, and identified hypoxia as a possible contributing factor for 2-BE–induced hemangiosarcoma in mice.
doi:10.1093/toxsci/kfp213
PMCID: PMC2794330  PMID: 19812364
hemangiosarcoma; hypoxia; angiogenesis; endothelial cells; endothelial precursor cells; mechanism of action; human relevance; 2-butoxyethanol
6.  Importance of cis Determinants and Nitrogenase Activity in Regulated Stability of the Klebsiella pneumoniae Nitrogenase Structural Gene mRNA 
Journal of Bacteriology  1999;181(12):3751-3760.
The Klebsiella pneumoniae nitrogen fixation (nif) mRNAs are unusually stable, with half-lives of 20 to 30 min under conditions favorable to nitrogen fixation (limiting nitrogen, anaerobiosis, temperatures of 30°C). Addition of O2 or fixed nitrogen or temperature increases to 37°C or more result in the dramatic destabilization of the nif mRNAs, decreasing the half-lives by a factor of 3 to 5. A plasmid expression system, independent of nif transcriptional regulation, was used to define cis determinants required for the regulated stability of the 5.2-kb nifHDKTY mRNA and to test the model suggested by earlier work that NifA is required in trans to stabilize nif mRNA under nif-derepressing conditions. O2 regulation of nifHDKTY mRNA stability is impaired in a plasmid containing a deletion of a 499-bp region of nifH, indicating that a site(s) required for the O2-regulated stability of the mRNA is located within this region. The simple model suggested from earlier work that NifA is required for stabilizing nif mRNA under conditions favorable for nitrogen fixation was disproved, and in its place, a more complicated model involving the sensing of nitrogenase activity as a component of the system regulating mRNA stability is proposed. Analysis of nifY mutants and overexpression suggests a possible involvement of the protein in this sensing process.
PMCID: PMC93853  PMID: 10368150

Results 1-6 (6)