Fourier Magnetic Imaging with Nanoscale Resolution and Compressed Sensing Speed-up using Electronic Spins in Diamond

Optically-detected magnetic resonance using Nitrogen Vacancy (NV) color centres in diamond is a leading modality for nanoscale magnetic field imaging, as it provides single electron spin sensitivity, three-dimensional resolution better than 1 nm, and applicability to a wide range of physical and biological samples under ambient conditions. To date, however, NV-diamond magnetic imaging has been performed using real space techniques, which are either limited by optical diffraction to 250 nm resolution or require slow, point-by-point scanning for nanoscale resolution, e.g., using an atomic force microscope, magnetic tip, or super-resolution optical imaging. Here we introduce an alternative technique of Fourier magnetic imaging using NV-diamond. In analogy with conventional magnetic resonance imaging (MRI), we employ pulsed magnetic field gradients to phase-encode spatial information on NV electronic spins in wavenumber or k-space followed by a fast Fourier transform to yield real-space images with nanoscale resolution, wide field-of-view (FOV), and compressed sensing speed-up.Comment: 31 pages, 10 figure

PlantPhos: using maximal dependence decomposition to identify plant phosphorylation sites with substrate site specificity

<p>Abstract</p> <p>Background</p> <p>Protein phosphorylation catalyzed by kinases plays crucial regulatory roles in intracellular signal transduction. Due to the difficulty in performing high-throughput mass spectrometry-based experiment, there is a desire to predict phosphorylation sites using computational methods. However, previous studies regarding <it>in silico </it>prediction of plant phosphorylation sites lack the consideration of kinase-specific phosphorylation data. Thus, we are motivated to propose a new method that investigates different substrate specificities in plant phosphorylation sites.</p> <p>Results</p> <p>Experimentally verified phosphorylation data were extracted from TAIR9-a protein database containing 3006 phosphorylation data from the plant species <it>Arabidopsis thaliana</it>. In an attempt to investigate the various substrate motifs in plant phosphorylation, maximal dependence decomposition (MDD) is employed to cluster a large set of phosphorylation data into subgroups containing significantly conserved motifs. Profile hidden Markov model (HMM) is then applied to learn a predictive model for each subgroup. Cross-validation evaluation on the MDD-clustered HMMs yields an average accuracy of 82.4% for serine, 78.6% for threonine, and 89.0% for tyrosine models. Moreover, independent test results using <it>Arabidopsis thaliana </it>phosphorylation data from UniProtKB/Swiss-Prot show that the proposed models are able to correctly predict 81.4% phosphoserine, 77.1% phosphothreonine, and 83.7% phosphotyrosine sites. Interestingly, several MDD-clustered subgroups are observed to have similar amino acid conservation with the substrate motifs of well-known kinases from Phospho.ELM-a database containing kinase-specific phosphorylation data from multiple organisms.</p> <p>Conclusions</p> <p>This work presents a novel method for identifying plant phosphorylation sites with various substrate motifs. Based on cross-validation and independent testing, results show that the MDD-clustered models outperform models trained without using MDD. The proposed method has been implemented as a web-based plant phosphorylation prediction tool, PlantPhos <url>http://csb.cse.yzu.edu.tw/PlantPhos/</url>. Additionally, two case studies have been demonstrated to further evaluate the effectiveness of PlantPhos.</p

Transcriptome analysis and comparison reveal divergence between two invasive whitefly cryptic species

<p>Abstract</p> <p>Background</p> <p>Invasive species are valuable model systems for examining the evolutionary processes and molecular mechanisms associated with their specific characteristics by comparison with closely related species. Over the past 20 years, two species of the whitefly <it>Bemisia tabaci </it>species complex, Middle East-Asia Minor 1 (MEAM1) and Mediterranean (MED), have both spread from their origin Middle East/Mediterranean to many countries despite their apparent differences in many life history parameters. Previously, we have sequenced the transcriptome of MED. In this study, we sequenced the transcriptome of MEAM1 and took a comparative genomic approach to investigate the transcriptome evolution and the genetic factors underlying the differences between MEAM1 and MED.</p> <p>Results</p> <p>Using Illumina sequencing technology, we generated 17 million sequencing reads for MEAM1. These reads were assembled into 57,741 unique sequences and 15,922 sequences were annotated with an E-value above 10^-5. Compared with the MED transcriptome, we identified 3,585 pairs of high quality orthologous genes and inferred their sequence divergences. The average differences in coding, 5' untranslated and 3' untranslated region were 0.83%, 1.66% and 1.43%, respectively. The level of sequence divergence provides additional support to the proposition that MEAM1 and MED are two species. Based on the ratio of nonsynonymous and synonymous substitutions, we identified 24 sequences that have evolved in response to positive selection. Many of those genes are predicted to be involved in metabolism and insecticide resistance which might contribute to the divergence of the two whitefly species.</p> <p>Conclusions</p> <p>Our data present a comprehensive sequence comparison between the two invasive whitefly species. This study will provide a road map for future investigations on the molecular mechanisms underlying their biological differences.</p

Xenopus as a Model System for the Study of GOLPH2/GP73 Function: Xenopus golph2 Is Required for Pronephros Development

GOLPH2 is a highly conserved protein. It is upregulated in a number of tumors and is being considered as an emerging biomarker for related diseases. However, the function of GOLPH2 remains unknown. The Xenopus model is used to study the function of human proteins. We describe the isolation and characterization of Xenopus golph2, which dimerizes and localizes to the Golgi in a manner similar to human GOLPH2. Xenopus golph2 is expressed in the pronephros during early development. The morpholino-mediated knockdown of golph2 results in edema formation. Additionally, Nephrin expression is enhanced in the glomus, and the expression of pronephric marker genes, such as atp1b1, ClC-K, NKCC2, and NBC1, is diminished in the tubules and duct. Expression patterns of the transcription factors WT1, Pax2, Pax8, Lim1, GATA3, and HNF1β are also examined in the golph2 knockdown embryos, the expression of WT1 is increased in the glomus and expanded laterally in the pronephric region. We conclude that the deletion of golph2 causes an increase in the expression of WT1, which may promote glomus formation and inhibit pronephric tubule differentiation

piggyBac is an effective tool for functional analysis of the Plasmodium falciparum genome

<p>Abstract</p> <p>Background</p> <p>Much of the <it>Plasmodium falciparum </it>genome encodes hypothetical proteins with limited homology to other organisms. A lack of robust tools for genetic manipulation of the parasite limits functional analysis of these hypothetical proteins and other aspects of the <it>Plasmodium </it>genome. Transposon mutagenesis has been used widely to identify gene functions in many organisms and would be extremely valuable for functional analysis of the <it>Plasmodium </it>genome.</p> <p>Results</p> <p>In this study, we investigated the lepidopteran transposon, <it>piggyBac</it>, as a molecular genetic tool for functional characterization of the <it>Plasmodium falciparum </it>genome. Through multiple transfections, we generated 177 unique <it>P. falciparum </it>mutant clones with mostly single <it>piggyBac </it>insertions in their genomes. Analysis of <it>piggyBac </it>insertion sites revealed random insertions into the <it>P. falciparum </it>genome, in regards to gene expression in parasite life cycle stages and functional categories. We further explored the possibility of forward genetic studies in <it>P. falciparum </it>with a phenotypic screen for attenuated growth, which identified several parasite genes and pathways critical for intra-erythrocytic development.</p> <p>Conclusion</p> <p>Our results clearly demonstrate that <it>piggyBac </it>is a novel, indispensable tool for forward functional genomics in <it>P. falciparum </it>that will help better understand parasite biology and accelerate drug and vaccine development.</p

Post hoc pattern matching: assigning significance to statistically defined expression patterns in single channel microarray data

<p>Abstract</p> <p>Background</p> <p>Researchers using RNA expression microarrays in experimental designs with more than two treatment groups often identify statistically significant genes with ANOVA approaches. However, the ANOVA test does not discriminate which of the multiple treatment groups differ from one another. Thus, <it>post hoc </it>tests, such as linear contrasts, template correlations, and pairwise comparisons are used. Linear contrasts and template correlations work extremely well, especially when the researcher has <it>a priori </it>information pointing to a particular pattern/template among the different treatment groups. Further, all pairwise comparisons can be used to identify particular, treatment group-dependent patterns of gene expression. However, these approaches are biased by the researcher's assumptions, and some treatment-based patterns may fail to be detected using these approaches. Finally, different patterns may have different probabilities of occurring by chance, importantly influencing researchers' conclusions about a pattern and its constituent genes.</p> <p>Results</p> <p>We developed a four step, <it>post hoc </it>pattern matching (PPM) algorithm to automate single channel gene expression pattern identification/significance. First, 1-Way Analysis of Variance (ANOVA), coupled with <it>post hoc </it>'all pairwise' comparisons are calculated for all genes. Second, for each ANOVA-significant gene, all pairwise contrast results are encoded to create unique pattern ID numbers. The # genes found in each pattern in the data is identified as that pattern's 'actual' frequency. Third, using Monte Carlo simulations, those patterns' frequencies are estimated in random data ('random' gene pattern frequency). Fourth, a Z-score for overrepresentation of the pattern is calculated ('actual' against 'random' gene pattern frequencies). We wrote a Visual Basic program (StatiGen) that automates PPM procedure, constructs an Excel workbook with standardized graphs of overrepresented patterns, and lists of the genes comprising each pattern. The visual basic code, installation files for StatiGen, and sample data are available as supplementary material.</p> <p>Conclusion</p> <p>The PPM procedure is designed to augment current microarray analysis procedures by allowing researchers to incorporate all of the information from post hoc tests to establish unique, overarching gene expression patterns in which there is no overlap in gene membership. In our hands, PPM works well for studies using from three to six treatment groups in which the researcher is interested in treatment-related patterns of gene expression. Hardware/software limitations and extreme number of theoretical expression patterns limit utility for larger numbers of treatment groups. Applied to a published microarray experiment, the StatiGen program successfully flagged patterns that had been manually assigned in prior work, and further identified other gene expression patterns that may be of interest. Thus, over a moderate range of treatment groups, PPM appears to work well. It allows researchers to assign statistical probabilities to patterns of gene expression that fit <it>a priori </it>expectations/hypotheses, it preserves the data's ability to show the researcher interesting, yet unanticipated gene expression patterns, and assigns the majority of ANOVA-significant genes to non-overlapping patterns.</p

Mining Predicted Essential Genes of Brugia malayi for Nematode Drug Targets

We report results from the first genome-wide application of a rational drug target selection methodology to a metazoan pathogen genome, the completed draft sequence of Brugia malayi, a parasitic nematode responsible for human lymphatic filariasis. More than 1.5 billion people worldwide are at risk of contracting lymphatic filariasis and onchocerciasis, a related filarial disease. Drug treatments for filariasis have not changed significantly in over 20 years, and with the risk of resistance rising, there is an urgent need for the development of new anti-filarial drug therapies. The recent publication of the draft genomic sequence for B. malayi enables a genome-wide search for new drug targets. However, there is no functional genomics data in B. malayi to guide the selection of potential drug targets. To circumvent this problem, we have utilized the free-living model nematode Caenorhabditis elegans as a surrogate for B. malayi. Sequence comparisons between the two genomes allow us to map C. elegans orthologs to B. malayi genes. Using these orthology mappings and by incorporating the extensive genomic and functional genomic data, including genome-wide RNAi screens, that already exist for C. elegans, we identify potentially essential genes in B. malayi. Further incorporation of human host genome sequence data and a custom algorithm for prioritization enables us to collect and rank nearly 600 drug target candidates. Previously identified potential drug targets cluster near the top of our prioritized list, lending credibility to our methodology. Over-represented Gene Ontology terms, predicted InterPro domains, and RNAi phenotypes of C. elegans orthologs associated with the potential target pool are identified. By virtue of the selection procedure, the potential B. malayi drug targets highlight components of key processes in nematode biology such as central metabolism, molting and regulation of gene expression

Identification of target genes for wild type and truncated HMGA2 in mesenchymal stem-like cells

Background The HMGA2 gene, coding for an architectural transcription factor involved in mesenchymal embryogenesis, is frequently deranged by translocation and/or amplification in mesenchymal tumours, generally leading to over-expression of shortened transcripts and a truncated protein. Methods To identify pathways that are affected by sarcoma-associated variants of HMGA2, we have over-expressed wild type and truncated HMGA2 protein in an immortalized mesenchymal stem-like cell (MSC) line, and investigated the localisation of these proteins and their effects on differentiation and gene expression patterns. Results Over-expression of both transgenes blocked adipogenic differentiation of these cells, and microarray analysis revealed clear changes in gene expression patterns, more pronounced for the truncated protein. Most of the genes that showed altered expression in the HMGA2-overexpressing cells fell into the group of NF-κB-target genes, suggesting a central role for HMGA2 in this pathway. Of particular interest was the pronounced up-regulation of SSX1, already implicated in mesenchymal oncogenesis and stem cell functions, only in cells expressing the truncated protein. Furthermore, over-expression of both HMGA2 forms was associated with a strong repression of the epithelial marker CD24, consistent with the reported low level of CD24 in cancer stem cells. Conclusions We conclude that the c-terminal part of HMGA2 has important functions at least in mesenchymal cells, and the changes in gene expression resulting from overexpressing a protein lacking this domain may add to the malignant potential of sarcomas

Inhibition of Neuroblastoma Tumor Growth by Targeted Delivery of MicroRNA-34a Using Anti-Disialoganglioside GD2 Coated Nanoparticles

Neuroblastoma is one of the most challenging malignancies of childhood, being associated with the highest death rate in paediatric oncology, underlining the need for novel therapeutic approaches. Typically, patients with high risk disease undergo an initial remission in response to treatment, followed by disease recurrence that has become refractory to further treatment. Here, we demonstrate the first silica nanoparticle-based targeted delivery of a tumor suppressive, pro-apoptotic microRNA, miR-34a, to neuroblastoma tumors in a murine orthotopic xenograft model. These tumors express high levels of the cell surface antigen disialoganglioside GD2 (GD(2)), providing a target for tumor-specific delivery.Nanoparticles encapsulating miR-34a and conjugated to a GD(2) antibody facilitated tumor-specific delivery following systemic administration into tumor bearing mice, resulted in significantly decreased tumor growth, increased apoptosis and a reduction in vascularisation. We further demonstrate a novel, multi-step molecular mechanism by which miR-34a leads to increased levels of the tissue inhibitor metallopeptidase 2 precursor (TIMP2) protein, accounting for the highly reduced vascularisation noted in miR-34a-treated tumors.These novel findings highlight the potential of anti-GD(2)-nanoparticle-mediated targeted delivery of miR-34a for both the treatment of GD(2)-expressing tumors, and as a basic discovery tool for elucidating biological effects of novel miRNAs on tumor growth