bluuebunny/crossref_metadata_2025_split huggingface dataset:
Qoala-T: A supervised-learning tool for quality control of automatic segmented MRI data
Authors: Klapwijk Eduard T. , van de Kamp Ferdi , van der Meulen Mara , Peters Sabine , Wierenga Lara M. 
Published: March 2018

AbstractPerforming quality control to detect image artifacts and data-processing errors is crucial in structural magnetic resonance imaging, especially in developmental studies. Currently, many studies rely on visual inspection by trained raters for quality control. The subjectivity of these manual procedures lessens comparability between studies, and with growing study sizes quality control is increasingly time consuming. In addition, both inter-rater as well as intra-rater variability of manual quality control is high and may lead to inclusion of poor quality scans and exclusion of scans of usable quality. In the current study we present the Qoala-T tool, which is an easy and free to use supervised-learning model to reduce rater bias and misclassification in manual quality control procedures. First, we manually rated quality of N = 784 FreeSurfer-processed T1-weighted scans. Different supervised-learning models were then compared to predict manual quality ratings. Results show that the Qoala-T tool using random forests is able to predict scan quality with both high sensitivity and specificity (mean area under the curve (AUC) = 0.98). In addition, the Qoala-T tool was also able to adequately predict the quality of a novel unseen dataset (N = 112; mean AUC = 0.95). These outcomes indicate that using Qoala-T in other datasets could greatly reduce the time needed for quality control. More importantly, this procedure could further help to reduce variability related to manual quality control, thereby benefiting the comparability of data quality between studies.
RppH can faithfully replace TAP to allow cloning of 5’-triphosphate carrying small RNAs
Authors: Almeida Miguel Vasconcelos , de Jesus Domingues António Miguel , Lukas Hanna , Mendez-Lago Maria , Ketting René F. 
Published: March 2018

AbstractRNA interference was first described in the nematode Caenorhabditis elegans. Ever since, several new endogenous small RNA pathways have been described and characterized to different degrees. Much like plants, but unlike Drosophila and mammals, worms have RNA-dependent RNA Polymerases (RdRPs) that directly synthesize small RNAs using other transcripts as a template. The very prominent secondary small interfering RNAs, also called 22G-RNAs, produced by the RdRPs RRF-1 and EGO-1 in C. elegans, maintain the 5’ triphosphate group, stemming from RdRP activity, also after loading into an Argonaute protein. This creates a technical issue, since 5’PPP groups decrease cloning efficiency for small RNA sequencing. To increase cloning efficiency of these small RNA species, a common practice in the field is the treatment of RNA samples, prior to library preparation, with Tobacco Acid pyrophosphatase (TAP). Recently, TAP production and supply was discontinued, so an alternative must be devised. We turned to RNA 5’ pyrophosphohydrolase (RppH), a commercially available pyrophosphatase isolated from E. coli. Here we directly compare TAP and RppH in their use for small RNA library preparation. We show that RppH-treated samples faithfully recapitulate TAP-treated samples. Specifically, there is enrichment for 22G-RNAs and mapped small RNA reads show no small RNA transcriptome-wide differences between RppH and TAP treatment. We propose that RppH can be used as a small RNA pyrophosphatase to enrich for triphosphorylated small RNA species and show that RppH- and TAP-derived datasets can be used in direct comparison.
High-resolution analysis of the pneumococcal transcriptome under a wide range of infection-relevant conditions
Authors: Aprianto Rieza , Slager Jelle , Holsappel Siger , Veening Jan-Willem 
Published: March 2018

ABSTRACTStreptococcus pneumoniae is an opportunistic human pathogen that typically colonizes the nasopharyngeal passage and causes lethal disease in other host niches such as the lung or the meninges. How pneumococcal genes are expressed and regulated at the different stages of its life cycle, as commensal or as pathogen, has not been entirely described. To chart the transcriptional responses of S. pneumoniae, we quantified the transcriptome under 22 different infection-relevant conditions. The transcriptomic compendium exposed a high level of dynamic expression and, strikingly, all annotated pneumococcal genomic features were expressed in at least one of the studied conditions. By computing the correlation of gene expression of every two genes across all studied conditions, we created a co-expression matrix that provides valuable information on both operon structure and regulatory processes. The co-expression data is highly consistent with well-characterized operons and regulons, such as the PyrR, ComE and ComX regulons, and has allowed us to identify a new member of the competence regulon. Finally, we created an interactive data center named PneumoExpress (www.veeninglab.com/pneumoexpress) that enables users to access the expression data as well as the co-expression matrix in an intuitive and efficient manner, providing a valuable resource to the pneumococcal research community.
Identification ofciselements for spatio-temporal control of DNA replication
Authors: Sima Jiao , Chakraborty Abhijit , Dileep Vishnu , Michalski Marco , Rivera-Mulia Juan Carlos , Trevilla-Garcia Claudia , Klein Kyle N. , Bartlett Daniel , Washburn Brian K. , Paulsen Michelle T. , Vera Daniel , Nora Elphège P. , Kraft Katerina , Mundlos Stefan , Bruneau Benoit G. , Ljungman Mats , Fraser Peter , Ay Ferhat , Gilbert David M. 
Published: March 2018

SUMMARYThe temporal order of DNA replication (replication timing, RT) is highly coupled with genome architecture, butcis-elements regulating spatio-temporal control of replication have remained elusive. We performed an extensive series of CRISPR mediated deletions and inversions and high-resolution capture Hi-C of a pluripotency associated domain (DppA2/4) in mouse embryonic stem cells. Whereas CTCF mediated loops and chromatin domain boundaries were dispensable, deletion of three intra-domain prominent CTCF-independent 3D contact sites caused a domain-wide delay in RT, shift in sub-nuclear chromatin compartment and loss of transcriptional activity, These “early replication control elements” (ERCEs) display prominent chromatin features resembling enhancers/promoters and individual and pair-wise deletions of the ERCEs confirmed their partial redundancy and interdependency in controlling domain-wide RT and transcription. Our results demonstrate that discretecis-regulatory elements mediate domain-wide RT, chromatin compartmentalization, and transcription, representing a major advance in dissecting the relationship between genome structure and function.Highlightscis-elements (ERCEs) regulate large scale chromosome structure and functionMultiple ERCEs cooperatively control domain-wide replicationERCEs harbor prominent active chromatin features and form CTCF-independent loopsERCEs enable genetic dissection of large-scale chromosome structure-function.
A chemoproteomic portrait of the oncometabolite fumarate
Authors: Kulkarni Rhushikesh A. , Bak Daniel W. , Wei Darmood , Bergholtz Sarah E. , Briney Chloe A. , Shrimp Jonathan H. , Thorpe Abigail L. , Bavari Arissa , Alpsoy Aktan , Levy Michaella , Florens Laurence , Washburn Michael P. , Dykhuizen Emily C. , Frizzell Norma , Weerapana Eranthie , Linehan W. Marston , Meier Jordan L. 
Published: March 2018

AbstractHereditary cancer disorders often provide an important window into novel mechanisms supporting tumor growth and survival. Understanding these mechanisms and developing biomarkers to identify their presence thus represents a vital goal. Towards this goal, here we report a chemoproteomic map of the covalent targets of fumarate, an oncometabolite whose accumulation marks the genetic cancer predisposition syndrome hereditary leiomyomatosis and renal cell carcinoma (HLRCC). First, we validate the ability of known and novel chemoproteomic probes to report on fumarate reactivity in vitro. Next, we apply these probes in concert with LC-MS/MS to identify cysteine residues sensitive to either fumarate treatment or fumarate hydratase (FH) mutation in untransformed and human HLRCC cell models, respectively. Mining this data to understand the structural determinants of fumarate reactivity reveals an unexpected anti-correlation with nucleophilicity, and the discovery of a novel influence of pH on fumarate-cysteine interactions. Finally, we show that many fumarate-sensitive and FH-regulated cysteines are found in functional protein domains, and perform mechanistic studies of a fumarate-sensitive cysteine in SMARCC1 that lies at a key protein-protein interface in the SWI-SNF tumor suppressor complex. Our studies provide a powerful resource for understanding the influence of fumarate on reactive cysteine residues, and lay the foundation for future efforts to exploit this distinct aspect of oncometabolism for cancer diagnosis and therapy.
Quantitative variation in female sensory structures supports species recognition and intraspecific mate choice functions in damselflies
Authors: Barnard Alexandra A. , Masly John P. 
Published: March 2018

AbstractMales and females exchange signals prior to mating that convey information such as sex, species identity, or individual condition. Tactile signals relayed during physical contact between males and females before and during mating appear to be important for mate choice and reproductive isolation in some animals. However, compared to our understanding of visual, auditory, and chemical signals, we know little about the importance of tactile signals in mating decisions. Among North American damselflies in the genusEnallagma(Odonata: Coenagrionidae) species-specific tactile stimulation contributes to reproductive isolation between species and may also be important for intraspecific mate choice. We quantified several mechanosensory sensilla phenotypes on the female thorax among multiple sympatric and allopatric populations of twoEnallagmaspecies that occasionally interbreed in nature. Although each species differed in features of sensilla distribution within the thoracic plates, we found no strong evidence of reproductive character displacement among the sensilla traits we measured in regions of sympatry. However, substantial variation of sensilla traits was observed within populations of both species. Our results suggest that species-specific placement of female mechanoreceptors appears sufficient for species recognition, but mechanosensor variation among females within species may be important for mate choice.
Phenotypes associated with genes encoding drug targets are predictive of clinical trial side effects
Authors: Nguyen Phuong A. , Deaton Aimee M. , Nioi Paul , Ward Lucas D. 
Published: March 2018

ABSTRACTBiomedical scientists face major challenges in developing novel drugs for unmet medical needs. Only a small fraction of early drug programs progress to the market, due to safety and efficacy failures, despite extensive efforts to predict drug and target safety as early as possible using a variety of assays in vitro and in preclinical species. In principle, characterizing the effect of natural variation in the genes encoding drug targets should present a powerful alternate approach to predict not only whether a protein will be an effective drug target, but also whether a protein will be an inherently safe drug target, while avoiding the challenges of translating biology from experiments in non-human species. We have embarked on a retrospective analysis, demonstrating for the first time a statistical link between the organ systems involved in genetic syndromes of drug target genes and the organ systems in which side effects are observed clinically. Across 1,819 drugs and 21 organ system phenotype categories analyzed, drug side effects are more likely to occur in organ systems where there is genetic evidence of a link between the drug target and a phenotype involving that organ system, compared to when there is no such genetic evidence (30.0% vs 19.2%; OR = 1.80). Conversely, we find that having genetic evidence of a Mendelian syndrome involving a drug target in which a certain organ system is unaffected decreases the likelihood that side effects will manifest in that organ system, relative to having no informative syndrome (18.5% vs 20.2%; OR = 0.89). We find a relationship between genetics and side effects even when controlling for known confounders such as drug delivery route and indication. We highlight examples where genetics of drug targets could have anticipated side effects observed during clinical trials. This result suggests that human genetic data should be routinely used to predict potential safety issues associated with novel drug targets. This may lead to selection of better targets, appropriate monitoring of putative side effects early in development, reduction of the use of preclinical animal experiments, and ultimately increased success of molecules. Furthermore, deeply phenotyping human knockouts will be critically important to understand the full spectrum of effects that a new drug may elicit.
Inferring Disease Risk Genes from Sequencing Data in Multiplex Pedigrees Through Sharing of Rare Variants
Authors: Bureau Alexandre , Begum Ferdouse , Taub Margaret A. , Hetmanski Jacqueline , Parker Margaret M. , Albacha-Hejazi Hasan , Scott Alan F. , Murray Jeffrey C. , Marazita Mary L. , Bailey-Wilson Joan E. , Beaty Terri H. , Ruczinski Ingo 
Published: March 2018

AbstractWe previously demonstrated how sharing of rare variants (RVs) in distant affected relatives can be used to identify variants causing a complex and heterogeneous disease. This approach tested whether single RVs were shared by all sequenced affected family members. However, as with other study designs, joint analysis of several RVs (e.g. within genes) is sometimes required to obtain sufficient statistical power. Further, phenocopies can lead to false negatives for some causal RVs if complete sharing among affecteds is required. Here we extend our methodology (Rare Variant Sharing, RVS) to address these issues. Specifically, we introduce gene-based analyses, refine RV definition based on haplotypes, and introduce a partial sharing test based on RV sharing probabilities for subsets of affected family members. RVS also has the desirable features of not requiring external estimates of variant frequency or control samples, provides functionality to assess and address violations of key assumptions, and is available as open source software for genome-wide analysis. Simulations including phenocopies, based on the families of an oral cleft study, revealed the partial and complete sharing versions of RVS achieved similar statistical power compared to alternative methods (RareIBD and the Gene-Based Segregation Test), and had superior power compared to the pedigree Variant Annotation, Analysis and Search Tool (pVAAST) linkage statistic. In studies of multiplex cleft families, analysis of rare single nucleotide variants in the exome of 151 affected relatives from 54 families revealed no significant excess sharing in any one gene, but highlighted different patterns of sharing revealed by the complete and partial sharing tests.
DNA-Encircled Lipid Bilayers
Authors: Iric Katarina , Subramanian Madhumalar , Oertel Jana , Agarwal Nayan P. , Matthies Michael , Periole Xavier , Sakmar Thomas P. , Huber Thomas , Fahmy Karim , Schmidt Thorsten-Lars 
Published: March 2018

ABSTRACTLipid bilayers and lipid-associated proteins play a crucial role in biology. As in vivo studies and manipulation are inherently difficult, several membrane-mimetic systems have been developed to enable investigation of lipidic phases, lipid-protein interactions, membrane protein function and membrane structure in vitro. Controlling the size and shape, or site-specific functionalization is, however, difficult to achieve with established membrane mimetics based on membrane scaffolding proteins, polymers or peptides. In this work, we describe a route to leverage the unique programmability of DNA nanotechnology and create DNA-encircled bilayers (DEBs), which are made of multiple copies of an alkylated oligonucleotide hybridized to a single-stranded minicircle. To stabilize the hydrophobic rim of the lipid bilayer, and to prevent formation of lipid vesicles, we introduced up to 2 alkyl chains per helical that point to the inside of the toroidal DNA ring and interact with the hydrophobic side chains of the encapsulated lipid bilayer. The DEB approach described herein provides unprecedented control of size, and allows the orthogonal functionalizations and arrangement of engineered membrane nanoparticles and will become a valuable tool for biophysical investigation of lipid phases and lipid-associated proteins and complexes including structure determination of membrane proteins and pharmacological screenings of membrane proteins.
MechRNA: prediction of lncRNA mechanisms from RNA-RNA and RNA-protein interactions
Authors: Gawronski Alexander R. , Uhl Michael , Zhang Yajia , Lin Yen-Yi , Niknafs Yashar S. , Ramnarine Varune R. , Malik Rohit , Feng Felix , Chinnaiyan Arul M. , Collins Colin C. , Sahinalp S. Cenk , Backofen Rolf 
Published: March 2018

AbstractMotivationLong non-coding RNAs (lncRNAs) are defined as transcripts longer than 200 nucleotides that do not get translated into proteins. Often these transcripts are processed (spliced, capped, polyadenylated) and some are known to have important biological functions. However, most lncRNAs have unknown or poorly understood functions. Nevertheless, because of their potential role in cancer, lncRNAs are receiving a lot of attention, and the need for computational tools to predict their possible mechanisms of action is more than ever. Fundamentally, most of the known lncRNA mechanisms involve RNA-RNA and/or RNA-protein interactions. Through accurate predictions of each kind of interaction and integration of these predictions, it is possible to elucidate potential mechanisms for a given lncRNA.ApproachHere we introduce MechRNA, a pipeline for corroborating RNA-RNA interaction prediction and protein binding prediction for identifying possible lncRNA mechanisms involving specific targets or on a transcriptome-wide scale. The first stage uses a version of IntaRNA2 with added functionality for efficient prediction of RNA-RNA interactions with very long input sequences, allowing for large-scale analysis of lncRNA interactions with little or no loss of optimality. The second stage integrates protein binding information pre-computed by GraphProt, for both the lncRNA and the target. The final stage involves inferring the most likely mechanism for each lncRNA/target pair. This is achieved by generating candidate mechanisms from the predicted interactions, the relative locations of these interactions and correlation data, followed by selection of the most likely mechanistic explanation using a combined p-value.ResultsWe applied MechRNA on a number of recently identified cancer-related lncRNAs (PCAT1, PCAT29, ARLnc1) and also on two well-studied lncRNAs (PCA3 and 7SL). This led to the identification of hundreds of high confidence potential targets for each lncRNA and corresponding mechanisms. These predictions include the known competitive mechanism of 7SL with HuR for binding on the tumor suppressor TP53, as well as mechanisms expanding what is known about PCAT1 and ARLn1 and their targets BRCA2 and AR, respectively. For PCAT1-BRCA2, the mechanism involves competitive binding with HuR, which we confirmed using HuR immunoprecipitation assays.AvailabilityMechRNA is available for download athttps://bitbucket.org/compbio/mechrnaContactbackofen@informatik.uni-freiburg.de,cenksahi@indiana.eduSupplementary informationSupplementary data are available atBioinformaticsonline.
A specific, glycomimetic Langerin ligand for human Langerhans cell targeting
Authors: Wamhoff Eike-Christian , Schulze Jessica , Bellmann Lydia , Bachem Gunnar , Fuchsberger Felix F. , Rademacher Juliane , Hermann Martin , Del Frari Barbara , van Dalen Rob , Hartmann David , van Sorge Nina M. , Seitz Oliver , Stoitzner Patrizia , Rademacher Christoph 
Published: March 2018

AbstractLangerhans cells are a subset of dendritic cells residing in the epidermis of the human skin. As such, they are key mediators of immune regulation and have emerged as prime targets for novel transcutaneous cancer vaccines. Importantly, the induction of protective T cell immunity by these vaccines requires the efficient and specific delivery of both tumor-associated antigens and adjuvants. Langerhans cells uniquely express Langerin (CD207), an endocytic C-type lectin receptor. Here, we report the discovery of a specific, glycomimetic Langerin ligand employing a heparin-inspired design strategy that integrated NMR spectroscopy and molecular docking. The conjugation of these glycomimetics to liposomes enabled the specific and efficient targeting of Langerhans cells in the human skin. This delivery platform provides superior versatility and scalability over antibody-based approaches and thus addresses current limitations of dendritic cell-based immunotherapies.
A novel pollen-tracking method: using quantum dots as pollen labels
Authors: Minnaar Corneile , Anderson Bruce 
Published: March 2018

ABSTRACTTo understand the evolution of flowers and mating systems in animal-pollinated plants, we have to directly address the function for which flowers evolved—the movement of pollen from anthers to stigmas. However, despite a long history of making significant advances in our understanding natural selection and evolution, the field of pollination biology has largely studied pollen movement indirectly (e.g., pollen analogues or paternity assignment to seeds) due to a lack of suitable pollen tracking methods. Here, we develop and test a novel pollen-tracking technique using quantum dots as pollen-grain labels. Quantum dots are semiconductor nanocrystals so small in size that they behave like artificial atoms. When exposed to UV light, they emit extremely bright light in a range of different colours. Their photostability, broad excitation range, and customisable binding-li-gands make quantum dots ideal bio-labels. We tested the suitability of CuInSexS2-x/ZnS (core/shell) quantum dots with oleic acid (zinc-oleate complex) ligands as pollen-grain labels. We found that quantum dots attach to pollen grains of four different species even after agitation in a polar solvent, suggesting that the oleic acid ligands on quantum dots bind to pollenkitt surrounding pollen grains. We also showed that most pollen grains within anthers of the same four species are labelled with quantum dots after applying sufficient quantum-dot solution to anthers. To test whether quantum-dot pollen-labels influenced pollen transport, we conducted pollen transfer trials on Sparaxis villosa (Iridaceae) using captively reared honeybees. We found no difference in pollen transport between labelled and unlabelled pollen grains. Our experiments therefore demonstrate the potential for quantum dots to be used as easily applied pollen labels, which allow subsequent tracking of the fates of pollen grains in the field. The ability to track pollen grain movement in situ, may finally allow us to address an historically neglected aspect of plant reproductive ecology and evolution.