Laser capture microdissection (LCM) and whole genome amplification (WGA) of DNA from normal breast tissue --- optimization for genome wide array analyses

<p>Abstract</p> <p>Background</p> <p>Laser capture microdissection (LCM) can be applied to tissues where cells of interest are distinguishable from surrounding cell populations. Here, we have optimized LCM for fresh frozen normal breast tissue where large amounts of fat can cause problems during microdissection. Since the amount of DNA needed for genome wide analyses, such as single nucleotide polymorphism (SNP) arrays, is often greater than what can be obtained from the dissected tissue, we have compared three different whole genome amplification (WGA) kits for amplification of DNA from LCM material. In addition, the genome wide profiling methods commonly used today require extremely high DNA quality compared to PCR based techniques and DNA quality is thus critical for successful downstream analyses.</p> <p>Findings</p> <p>We found that by using FrameSlides without glass backing for LCM and treating the slides with acetone after staining, the problems caused by excessive fat could be significantly decreased. The amount of DNA obtained after extraction from LCM tissue was not sufficient for direct SNP array analysis in our material. However, the two WGA kits based on Phi29 polymerase technology (Repli-g^®(Qiagen) and GenomiPhi (GE Healthcare)) gave relatively long amplification products, and amplified DNA from Repli-g^®gave call rates in the subsequent SNP analysis close to those from non-amplified DNA. Furthermore, the quality of the input DNA for WGA was found to be essential for successful SNP array results and initial DNA fragmentation problems could be reduced by switching from a regular halogen lamp to a VIS-LED lamp during LCM.</p> <p>Conclusions</p> <p>LCM must be optimized to work satisfactorily in difficult tissues. We describe a work flow for fresh frozen normal breast tissue where fat is inclined to cause problems if sample treatment is not adapted to this tissue. We also show that the Phi29-based Repli-g^®WGA kit (Qiagen) is a feasible approach to amplify DNA of high quality prior to genome wide analyses such as SNP profiling.</p

Quantification of lentiviral vector copy numbers in individual hematopoietic colony-forming cells shows vector dose-dependent effects on the frequency and level of transduction

Lentiviral vectors are effective tools for gene transfer and integrate variable numbers of proviral DNA copies in variable proportions of cells. The levels of transduction of a cellular population may therefore depend upon experimental parameters affecting the frequency and/or the distribution of vector integration events in this population. Such analysis would require measuring vector copy numbers (VCN) in individual cells. To evaluate the transduction of hematopoietic progenitor cells at the single-cell level, we measured VCN in individual colony-forming cell (CFC) units, using an adapted quantitative PCR (Q-PCR) method. The feasibility, reproducibility and sensitivity of this approach were tested with characterized cell lines carrying known numbers of vector integration. The method was validated by correlating data in CFC with gene expression or with calculated values, and was found to slightly underestimate VCN. In spite of this, such Q-PCR on CFC was useful to compare transduction levels with different infection protocols and different vectors. Increasing the vector concentration and re-iterating the infection were two different strategies that improved transduction by increasing the frequency of transduced progenitor cells. Repeated infection also augmented the number of integrated copies and the magnitude of this effect seemed to depend on the vector preparation. Thus, the distribution of VCN in hematopoietic colonies may depend upon experimental conditions including features of vectors. This should be carefully evaluated in the context of ex vivo hematopoietic gene therapy studies

Socioeconomic Inequality in the Prevalence of Autism Spectrum Disorder: Evidence from a U.S. Cross-Sectional Study

This study was designed to evaluate the hypothesis that the prevalence of autism spectrum disorder (ASD) among children in the United States is positively associated with socioeconomic status (SES).A cross-sectional study was implemented with data from the Autism and Developmental Disabilities Monitoring Network, a multiple source surveillance system that incorporates data from educational and health care sources to determine the number of 8-year-old children with ASD among defined populations. For the years 2002 and 2004, there were 3,680 children with ASD among a population of 557,689 8-year-old children. Area-level census SES indicators were used to compute ASD prevalence by SES tertiles of the population.Prevalence increased with increasing SES in a dose-response manner, with prevalence ratios relative to medium SES of 0.70 (95% confidence interval [CI] 0.64, 0.76) for low SES, and of 1.25 (95% CI 1.16, 1.35) for high SES, (P<0.001). Significant SES gradients were observed for children with and without a pre-existing ASD diagnosis, and in analyses stratified by gender, race/ethnicity, and surveillance data source. The SES gradient was significantly stronger in children with a pre-existing diagnosis than in those meeting criteria for ASD but with no previous record of an ASD diagnosis (p<0.001), and was not present in children with co-occurring ASD and intellectual disability.The stronger SES gradient in ASD prevalence in children with versus without a pre-existing ASD diagnosis points to potential ascertainment or diagnostic bias and to the possibility of SES disparity in access to services for children with autism. Further research is needed to confirm and understand the sources of this disparity so that policy implications can be drawn. Consideration should also be given to the possibility that there may be causal mechanisms or confounding factors associated with both high SES and vulnerability to ASD

Talking Less during Social Interactions Predicts Enjoyment: A Mobile Sensing Pilot Study

Can we predict which conversations are enjoyable without hearing the words that are spoken? A total of 36 participants used a mobile app, My Social Ties, which collected data about 473 conversations that the participants engaged in as they went about their daily lives. We tested whether conversational properties (conversation length, rate of turn taking, proportion of speaking time) and acoustical properties (volume, pitch) could predict enjoyment of a conversation. Surprisingly, people enjoyed their conversations more when they spoke a smaller proportion of the time. This pilot study demonstrates how conversational properties of social interactions can predict psychologically meaningful outcomes, such as how much a person enjoys the conversation. It also illustrates how mobile phones can provide a window into everyday social experiences and well-being

Evolution of protein-coupled RNA dynamics during hierarchical assembly of ribosomal complexes

Assembly of 30S ribosomes involves the hierarchical addition of ribosomal proteins that progressively stabilize the folded 16S rRNA. Here, we use three-color single molecule FRET to show how combinations of ribosomal proteins uS4, uS17 and bS20 in the 16S 5&apos; domain enable the recruitment of protein bS16, the next protein to join the complex. Analysis of real-time bS16 binding events shows that bS16 binds both native and non-native forms of the rRNA. The native rRNA conformation is increasingly favored after bS16 binds, explaining how bS16 drives later steps of 30S assembly. Chemical footprinting and molecular dynamics simulations show that each ribosomal protein switches the 16S conformation and dampens fluctuations at the interface between rRNA subdomains where bS16 binds. The results suggest that specific protein-induced changes in the rRNA dynamics underlie the hierarchy of 30S assembly and simplify the search for the native ribosome structure

Huntingtin mediates dendritic transport of β-actin mRNA in rat neurons

Transport of mRNAs to diverse neuronal locations via RNA granules serves an important function in regulating protein synthesis within restricted sub-cellular domains. We recently detected the Huntington's disease protein huntingtin (Htt) in dendritic RNA granules; however, the functional significance of this localization is not known. Here we report that Htt and the huntingtin-associated protein 1 (HAP1) are co-localized with the microtubule motor proteins, the KIF5A kinesin and dynein, during dendritic transport of β-actin mRNA. Live cell imaging demonstrated that β-actin mRNA is associated with Htt, HAP1, and dynein intermediate chain in cultured neurons. Reduction in the levels of Htt, HAP1, KIF5A, and dynein heavy chain by lentiviral-based shRNAs resulted in a reduction in the transport of β-actin mRNA. These findings support a role for Htt in participating in the mRNA transport machinery that also contains HAP1, KIF5A, and dynein

The Secrets of a Functional Synapse – From a Computational and Experimental Viewpoint

BACKGROUND: Neuronal communication is tightly regulated in time and in space. The neuronal transmission takes place in the nerve terminal, at a specialized structure called the synapse. Following neuronal activation, an electrical signal triggers neurotransmitter (NT) release at the active zone. The process starts by the signal reaching the synapse followed by a fusion of the synaptic vesicle and diffusion of the released NT in the synaptic cleft; the NT then binds to the appropriate receptor, and as a result, a potential change at the target cell membrane is induced. The entire process lasts for only a fraction of a millisecond. An essential property of the synapse is its capacity to undergo biochemical and morphological changes, a phenomenon that is referred to as synaptic plasticity. RESULTS: In this survey, we consider the mammalian brain synapse as our model. We take a cell biological and a molecular perspective to present fundamental properties of the synapse:(i) the accurate and efficient delivery of organelles and material to and from the synapse; (ii) the coordination of gene expression that underlies a particular NT phenotype; (iii) the induction of local protein expression in a subset of stimulated synapses. We describe the computational facet and the formulation of the problem for each of these topics. CONCLUSION: Predicting the behavior of a synapse under changing conditions must incorporate genomics and proteomics information with new approaches in computational biology