The SmAP2 RNA binding motif in the 3'UTR affects mRNA stability in the crenarchaeum Sulfolobus solfataricus.

Sm and Sm-like proteins represent an evolutionarily conserved family with key roles in RNA metabolism in Pro- and Eukaryotes. In this study, a collection of 53 mRNAs that co-purified with Sulfolobus solfataricus (Sso) SmAP2 were surveyed for a specific RNA binding motif (RBM). SmAP2 was shown to bind with high affinity to the deduced consensus RNA binding motif (SmAP2-cRBM) in vitro. Residues in SmAP2 interacting with the SmAP2-cRBM were mapped by UV-induced crosslinking in combination with mass-spectrometry, and verified by mutational analyses. The RNA-binding site on SmAP2 includes a modified uracil binding pocket containing a unique threonine (T40) located on the L3 face and a second residue, K25, located in the pore. To study the function of the SmAP2-RBM in vivo, three authentic RBMs were inserted in the 3'UTR of a lacS reporter gene. The presence of the SmAP2-RBM in the reporter-constructs resulted in decreased LacS activity and reduced steady state levels of lacS mRNA. Moreover, the presence of the SmAP2-cRBM in and the replacement of the lacS 3'UTR with that of Sso2194 encompassing a SmAP2-RBM apparently impacted on the stability of the chimeric transcripts. These results are discussed in light of the function(s) of eukaryotic Lsm proteins in RNA turnover

Rarity: Discovering rare cell populations from single-cell imaging data

MOTIVATION: Cell type identification plays an important role in the analysis and interpretation of single-cell data and can be carried out via supervised or unsupervised clustering approaches. Supervised methods are best suited where we can list all cell types and their respective marker genes a priori. While unsupervised clustering algorithms look for groups of cells with similar expression properties. This property permits the identification of both known and unknown cell populations, making unsupervised methods suitable for discovery. Success is dependent on the relative strength of the expression signature of each group as well as the number of cells. Rare cell types therefore present a particular challenge that are magnified when they are defined by differentially expressing a small number of genes. RESULTS: Typical unsupervised approaches fail to identify such rare sub-populations, and these cells tend to be absorbed into more prevalent cell types. In order to balance these competing demands, we have developed a novel statistical framework for unsupervised clustering, named Rarity, that enables the discovery process for rare cell types to be more robust, consistent and interpretable. We achieve this by devising a novel clustering method based on a Bayesian latent variable model in which we assign cells to inferred latent binary on/off expression profiles. This lets us achieve increased sensitivity to rare cell populations while also allowing us to control and interpret potential false positive discoveries. We systematically study the challenges associated with rare cell type identification and demonstrate the utility of Rarity on various IMC data sets. AVAILABILITY: Implementation of Rarity together with examples are available from the Github repository (https://github.com/kasparmartens/rarity). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online

First 230 GHz VLBI Fringes on 3C 279 using the APEX Telescope

We report about a 230 GHz very long baseline interferometry (VLBI) fringe finder observation of blazar 3C 279 with the APEX telescope in Chile, the phased submillimeter array (SMA), and the SMT of the Arizona Radio Observatory (ARO). We installed VLBI equipment and measured the APEX station position to 1 cm accuracy (1 sigma). We then observed 3C 279 on 2012 May 7 in a 5 hour 230 GHz VLBI track with baseline lengths of 2800 M$\lambda$ to 7200 M$\lambda$ and a finest fringe spacing of 28.6 micro-arcseconds. Fringes were detected on all baselines with SNRs of 12 to 55 in 420 s. The correlated flux density on the longest baseline was ~0.3 Jy/beam, out of a total flux density of 19.8 Jy. Visibility data suggest an emission region <38 uas in size, and at least two components, possibly polarized. We find a lower limit of the brightness temperature of the inner jet region of about 10^10 K. Lastly, we find an upper limit of 20% on the linear polarization fraction at a fringe spacing of ~38 uas. With APEX the angular resolution of 230 GHz VLBI improves to 28.6 uas. This allows one to resolve the last-photon ring around the Galactic Center black hole event horizon, expected to be 40 uas in diameter, and probe radio jet launching at unprecedented resolution, down to a few gravitational radii in galaxies like M 87. To probe the structure in the inner parsecs of 3C 279 in detail, follow-up observations with APEX and five other mm-VLBI stations have been conducted (March 2013) and are being analyzed.Comment: accepted for publication in A&

Instrumental drift in untargeted metabolomics: optimizing data quality with intrastudy QC samples

Untargeted metabolomics is an important tool in studying health and disease and is employed in fields such as biomarker discovery and drug development, as well as precision medicine. Although significant technical advances were made in the field of mass-spectrometry driven metabolomics, instrumental drifts, such as fluctuations in retention time and signal intensity, remain a challenge, particularly in large untargeted metabolomics studies. Therefore, it is crucial to consider these variations during data processing to ensure high-quality data. Here, we will provide recommendations for an optimal data processing workflow using intrastudy quality control (QC) samples that identifies errors resulting from instrumental drifts, such as shifts in retention time and metabolite intensities. Furthermore, we provide an in-depth comparison of the performance of three popular batch-effect correction methods of different complexity. By using different evaluation metrics based on QC samples and a machine learning approach based on biological samples, the performance of the batch-effect correction methods were evaluated. Here, the method TIGER demonstrated the overall best performance by reducing the relative standard deviation of the QCs and dispersion-ratio the most, as well as demonstrating the highest area under the receiver operating characteristic with three different probabilistic classifiers (Logistic regression, Random Forest, and Support Vector Machine). In summary, our recommendations will help to generate high-quality data that are suitable for further downstream processing, leading to more accurate and meaningful insights into the underlying biological processes

The OPS-SAT case: A data-centric competition for onboard satellite image classification

OnlinePublWhile novel artificial intelligence and machine learning techniques are evolving and disrupting established terrestrial technologies at an unprecedented speed, their adaptation onboard satellites is seemingly lagging. A major hindrance in this regard is the need for high-quality annotated data for training such systems, which makes the development process of machine learning solutions costly, time-consuming, and inefficient. This paper presents “the OPS-SAT case”, a novel data-centric competition that seeks to address these challenges. The powerful computational capabilities of the European Space Agency’s OPS-SAT satellite are utilized to showcase the design of machine learning systems for space by using only the small amount of available labeled data, relying on the widely adopted and freely available open-source software. The generation of a suitable dataset, design and evaluation of a public data-centric competition, and results of an onboard experimental campaign by using the competition winners’ machine learning model directly on OPS-SAT are detailed. The results indicate that adoption of open standards and deployment of advanced data augmentation techniques can retrieve meaningful onboard results comparatively quickly, simplifying and expediting an otherwise prolonged development period.Gabriele Meoni, Marcus Märtens, Dawa Derksen, Kenneth See, Toby Lightheart, Anthony Sécher, Arnaud Martin, David Rijlaarsdam, Vincenzo Fanizza, and Dario Izz

DNA methylome profiling of human tissues identifies global and tissue-specific methylation patterns

BACKGROUND: DNA epigenetic modifications, such as methylation, are important regulators of tissue differentiation, contributing to processes of both development and cancer. Profiling the tissue-specific DNA methylome patterns will provide novel insights into normal and pathogenic mechanisms, as well as help in future epigenetic therapies. In this study, 17 somatic tissues from four autopsied humans were subjected to functional genome analysis using the Illumina Infinium HumanMethylation450 BeadChip, covering 486 428 CpG sites. RESULTS: Only 2% of the CpGs analyzed are hypermethylated in all 17 tissue specimens; these permanently methylated CpG sites are located predominantly in gene-body regions. In contrast, 15% of the CpGs are hypomethylated in all specimens and are primarily located in regions proximal to transcription start sites. A vast number of tissue-specific differentially methylated regions are identified and considered likely mediators of tissue-specific gene regulatory mechanisms since the hypomethylated regions are closely related to known functions of the corresponding tissue. Finally, a clear inverse correlation is observed between promoter methylation within CpG islands and gene expression data obtained from publicly available databases. CONCLUSIONS: This genome-wide methylation profiling study identified tissue-specific differentially methylated regions in 17 human somatic tissues. Many of the genes corresponding to these differentially methylated regions contribute to tissue-specific functions. Future studies may use these data as a reference to identify markers of perturbed differentiation and disease-related pathogenic mechanisms

DNA methylome profiling of human tissues identifies global and tissue-specific methylation patterns

BACKGROUND: DNA epigenetic modifications, such as methylation, are important regulators of tissue differentiation, contributing to processes of both development and cancer. Profiling the tissue-specific DNA methylome patterns will provide novel insights into normal and pathogenic mechanisms, as well as help in future epigenetic therapies. In this study, 17 somatic tissues from four autopsied humans were subjected to functional genome analysis using the Illumina Infinium HumanMethylation450 BeadChip, covering 486 428 CpG sites. RESULTS: Only 2% of the CpGs analyzed are hypermethylated in all 17 tissue specimens; these permanently methylated CpG sites are located predominantly in gene-body regions. In contrast, 15% of the CpGs are hypomethylated in all specimens and are primarily located in regions proximal to transcription start sites. A vast number of tissue-specific differentially methylated regions are identified and considered likely mediators of tissue-specific gene regulatory mechanisms since the hypomethylated regions are closely related to known functions of the corresponding tissue. Finally, a clear inverse correlation is observed between promoter methylation within CpG islands and gene expression data obtained from publicly available databases. CONCLUSIONS: This genome-wide methylation profiling study identified tissue-specific differentially methylated regions in 17 human somatic tissues. Many of the genes corresponding to these differentially methylated regions contribute to tissue-specific functions. Future studies may use these data as a reference to identify markers of perturbed differentiation and disease-related pathogenic mechanisms