bluuebunny/crossref_metadata_2025_split huggingface dataset:
Appearance of synthetic vector-associated antibiotic resistance genes in next-generation sequences
Authors: Taiaroa George , Cook Gregory M. , Williamson Deborah A 
Published: August 2018

SynopsisBackgroundNext-generation sequencing methods have broad application in addressing increasing antibiotic resistance, with identification of antibiotic resistance genes (ARGs) having direct clinical relevance.ObjectivesHere, we describe the appearance of synthetic vector-associated ARGs in major public next-generation sequence data sets and assemblies, including in environmental samples and high priority pathogenic microorganisms.MethodsA search of selected databases – the National Centre for Biotechnology Information (NCBI) nucleotide collection, NCBI whole genome shotgun sequence contigs and literature-associated European Nucleotide Archive (ENA) datasets, was carried out using sequences characteristic of pUC-family synthetic vectors as a query in BLASTn. Identified hits were confirmed as being of synthetic origin, and further explored through alignment and comparison to primary read sets.ResultsSynthetic vectors are attributed to a range of organisms in each of the NCBI databases searched, including examples belonging to each Kingdom of life. These synthetic vectors are associated with various ARGs, primarily those encoding resistance to beta-lactam antibiotics and aminoglycosides. Synthetic vector associated ARGs are also observed in multiple environmental meta-transcriptome datasets, as shown through analysis of associated ENA primary reads, and are proposed to have led to incorrect statements being made in the literature on the abundance of ARGs.ConclusionsAppearance of synthetic vector-associated ARGs can confound the study of antimicrobial resistance in varied settings, and may have clinical implications in the nearfuture.
High-throughput amplicon sequencing of the full-length 16S rRNA gene with single-nucleotide resolution
Authors: Callahan Benjamin J , Wong Joan , Heiner Cheryl , Oh Steve , Theriot Casey M , Gulati Ajay S , McGill Sarah K , Dougherty Michael K 
Published: August 2018

AbstractTargeted PCR amplification and high-throughput sequencing (amplicon sequencing) of 16S rRNA gene fragments is widely used to profile microbial communities. New long-read sequencing technologies can sequence the entire 16S rRNA gene, but higher error rates have limited their attractiveness when accuracy is important. Here we present a high-throughput amplicon sequencing methodology based on PacBio circular consensus sequencing and the DADA2 sample inference method that measures the full-length 16S rRNA gene with single-nucleotide resolution and a near-zero error rate.In two artificial communities of known composition, our method recovered the full complement of full-length 16S sequence variants from expected community members without residual errors. The measured abundances of intra-genomic sequence variants were in the integral ratios expected from the genuine allelic variants within a genome. The full-length 16S gene sequences recovered by our approach allowedE. colistrains to be correctly classified to the O157:H7 and K12 sub-species clades. In human fecal samples, our method showed strong technical replication and was able to recover the full complement of 16S rRNA alleles in severalE. colistrains.There are likely many applications beyond microbial profiling for which high-throughput amplicon sequencing of complete genes with single-nucleotide resolution will be of use.
Hidden Markov Models Lead to Higher Resolution Maps of Mutation Signature Activity in Cancer
Authors: Huang Xiaoqing , Sason Itay , Wojtowicz Damian , Kim Yoo-Ah , Leiserson Mark D.M. , Przytycka Teresa M. , Sharan Roded 
Published: August 2018

AbstractKnowing the activity of the mutational processes shaping a cancer genome may provide insight into tumorigenesis and personalized therapy. It is thus important to uncover the characteristicsignaturesof active mutational processes in patients from their patterns of single base substitutions. However, mutational processes do not act uniformly on the genome and are biased by factors such as the genome’s chromatin structure or replication origins. These factors may lead to statistical dependencies among neighboring mutations, calling for modeling approaches that can account for such dependencies to better estimate mutational process activities.Here we develop the first sequence-dependent models for mutation signatures. We apply these models to characterize genomic and other factors that influence the activity of previously validated mutation signatures in breast cancer. We find that our tool, SigMa, can accurately assign genomic mutations to mutation signatures, yielding assignments that are of higher likelihood than those obtained with models that assume independence between signatures and align better with current biological knowledge. Our analysis resolves a controversy related to the dependency of APOBEC signatures on replication time and links Signatures 18 and 30 to oxidative damage.Modeling the sequential dependencies of mutation signatures leads to improved estimates of mutation signature activity both at the tumor-level and within specific genomic regions, yielding higher resolution maps of mutation signature activity in cancer.
BAMM-SC: A Bayesian mixture model for clustering droplet-based single cell transcriptomic data from population studies
Authors: Sun Zhe , Chen Li , Xin Hongyi , Huang Qianhui , Cillo Anthony R , Tabib Tracy , Ding Ying , Kolls Jay K , Bruno Tullia C , Lafyatis Robert , Vignali Dario AA , Chen Kong , Hu Ming , Chen Wei 
Published: August 2018

AbstractThe recently developed droplet-based single cell transcriptome sequencing (scRNA-seq) technology makes it feasible to perform a population-scale scRNA-seq study, in which the transcriptome is measured for tens of thousands of single cells from multiple individuals. Despite the advances of many clustering methods, there are few tailored methods for population-scale scRNA-seq studies. Here, we have developed a BAyesiany Mixture Model for Single Cell sequencing (BAMM-SC) method to cluster scRNA-seq data from multiple individuals simultaneously. Specifically, BAMM-SC takes raw data as input and can account for data heterogeneity and batch effect among multiple individuals in a unified Bayesian hierarchical model framework. Results from extensive simulations and application of BAMM-SC to in-house scRNA-seq datasets using blood, lung and skin cells from humans or mice demonstrated that BAMM-SC outperformed existing clustering methods with improved clustering accuracy and reduced impact from batch effects. BAMM-SC has been implemented in a user-friendly R package with a detailed tutorial available on www.pitt.edu/~Cwec47/singlecell.html.
Positive selection in Europeans and East-Asians at the ABCA12 gene
Authors: Sirica Roberto , Buonaiuto Marianna , Petrella Valeria , Sticco Lucia , Tramontano Donatella , Antonini Dario , Missero Caterina , Guardiola Ombretta , Andolfi Gennaro , Kumar Heerman , Ayub Qasim , Xue Yali , Tyler-Smith Chris , Salvemini Marco , D’Angelo Giovanni , Colonna Vincenza 
Published: August 2018

AbstractNatural selection acts on genetic variants by increasing the frequency of alleles responsible for a cellular function that is favorable in a certain environment. In a previous genome-wide scan for positive selection in contemporary humans, we identified a signal of positive selection in European and Asians at the genetic variant rs10180970. The variant is located in the second intron of the ABCA12 gene, which is implicated in the lipid barrier formation and down-regulated by UVB radiation. We studied the signal of selection in the genomic region surrounding rs10180970 in a larger dataset that includes DNA sequences from ancient samples. We also investigated the functional consequences of gene expression of the alleles of rs10180970 and another genetic variant in its proximity in healthy volunteers exposed to similar UV radiation.We confirmed the selection signal and refine its location that extends over 35 kb and includes the first intron, the first two exons and the transcription starting site of ABCA12. We found no obvious effect of rs10180970 alleles on ABCA12 gene expression. We reconstructed the trajectory of the T allele over the last 80,000 years to discover that it was specific to H. sapiens and frequent among non-Africans already 45,000 years ago.
Estimation of narrowband amplitude and phase from electrophysiology signals for phase-amplitude coupling studies: a comparison of methods
Authors: Soto Juan L.P. , Prado Felipe V.D. , Combrisson Etienne , Jerbi Karim 
Published: August 2018

AbstractMany functional connectivity studies based on electrophysiological measurements, such as electro- and magnetoencephalography (EEG/MEG), start their investigations by extracting a narrowband representation of brain activity time series, and then computing their envelope amplitudes and instantaneous phases, which serve as inputs to subsequent data processing. The two most popular approaches for obtaining these narrowband amplitudes and phases are: bandpass filtering followed by Hilbert transform (we call this the Hilbert approach); and convolution with wavelet kernels (the wavelet approach). In this work, we investigate how these two approaches perform in detecting the phenomenon of phase-amplitude coupling (PAC), whereby the amplitude of a high-frequency signal is driven by the phase of a low-frequency signal. The comparison of both approaches is carried out by means of simulated brain activity, from which we run receiver operating characteristic (ROC) analyses, and of experimental MEG data from a visuomotor coordination study. The ROC analyses show that both approaches have comparable accuracy, except in the presence of interfering signals with frequencies near the high-frequency band. As for the visuomotor data, the most noticeable impact of the choice of approach was observed when evaluating task-based changes in PAC between the delta (2-5 Hz) and the high-gamma (60-90 Hz) frequency bands, as we were able to identify widespread brain areas with statistically significant effects only with the Hilbert approach. These results provide preliminary evidence of the advantages of the Hilbert approach over the wavelet approach, at least in the context of PAC estimates.
Improving the classification of neuropsychiatric conditions using gene ontology terms as features
Authors: Quinn Thomas P. , Lee Samuel C. , Venkatesh Svetha , Nguyen Thin 
Published: August 2018

AbstractAlthough neuropsychiatric disorders have a well-established genetic background, their specific molecular foundations remain elusive. This has prompted many investigators to design studies that identify explanatory biomarkers, and then use these biomarkers to predict clinical outcomes. One approach involves using machine learning algorithms to classify patients based on blood mRNA expression from high-throughput transcriptomic assays. However, these endeavours typically fail to achieve the high level of performance, stability, and generalizability required for clinical translation. Moreover, these classifiers can lack interpretability because informative genes do not necessarily have relevance to researchers. For this study, we hypothesized that annotation-based classifiers can improve classification performance, stability, generalizability, and interpretability. To this end, we evaluated the performance of four classification algorithms on six neuropsychiatric data sets using four annotation databases. Our results suggest that the Gene Ontology Biological Process database can transform gene expression into an annotation-based feature space that improves the performance and stability of blood-based classifiers for neuropsychiatric conditions. We also show how annotation features can improve the interpretability of classifiers: since annotation databases are often used to assign biological importance to genes, annotation-based classifiers are easy to interpret because the biological importance of the features are the features themselves. We found that using annotations as features improves the performance and stability of classifiers. We also noted that the top ranked annotations tend contain the top ranked genes, suggesting that the most predictive annotations are a superset of the most predictive genes. Based on this, and the fact that annotations are used routinely to assign biological importance to genetic data, we recommend transforming gene-level expression into annotation-level expression prior to the classification of neuropsychiatric conditions.
Sample Preparation by Easy Extraction and Digestion (SPEED) - A Universal, Rapid, and Detergent-free Protocol for Proteomics based on Acid Extraction
Authors: Doellinger Joerg , Schneider Andy , Hoeller Marcell , Lasch Peter 
Published: August 2018

SUMMARYMass spectrometry is the method of choice for deep and comprehensive analysis of proteomes and has become a key technology to support the progress in life science and biomedicine. However, sample preparation in proteomics is not standardized and contributes to a lack of reproducibility. The main challenge is to extract all proteins in a manner that enables efficient digestion into peptides and is compatible with subsequent mass spectrometric analysis. Current methods are based on the idea of removing detergents or chaotropic agents during sample processing, which are essential for protein extraction but interfere with digestion and LC-MS. These multi-step preparations are prone to losses, biases and contaminations, while being time-consuming and labor-intensive.We report a universal detergent-free method, named Sample Preparation by Easy Extraction and Digestion (SPEED), which is based on a simple three-step procedure, acidification, neutralization and digestion. SPEED is a one-pot method for peptide generation from various sources and is easily applicable even for lysis-resistant sample types as pure trifluoroacetic acid (TFA) is used for highly efficient protein extraction. SPEED-based sample processing is highly reproducible, provides exceptional peptide yields and enables preparation even of tissue samples with less than 15 min hands-on time and without any special equipment. Evaluation of SPEED performance revealed, that the number of quantified proteins and the quantitative reproducibility are superior compared to the well-established sample processing protocols FASP, ISD-Urea and SP3 for various sample types, including human cells, bacteria and tissue, even at low protein starting amounts.
Putative pore-forming subunits of the mechano-electrical transduction channel, Tmc1/2b, require Tmie to localize to the site of mechanotransduction in zebrafish sensory hair cells
Authors: Pacentine Itallia V. , Nicolson Teresa 
Published: August 2018

AbstractMutations in transmembrane inner ear (TMIE) cause deafness in humans; previous studies suggest involvement in the mechano-electrical transduction (MET) complex in sensory hair cells, but TMIE’s precise role is unclear. In tmie zebrafish mutants, we observed that GFP-tagged Tmc1 and Tmc2b, which are putative subunits of the MET channel, fail to target to the hair bundle. In contrast, overexpression of Tmie strongly enhances the targeting of Tmc2b-GFP to stereocilia. To identify the motifs of Tmie underlying the regulation of the Tmcs, we systematically deleted or replaced peptide segments. We then assessed localization and functional rescue of each mutated/chimeric form of Tmie in tmie mutants. We determined that the first putative helix was dispensable and identified a novel critical region of Tmie, the extracellular region and transmembrane domain, which mediates both mechanosensitivity and Tmc2b-GFP expression in bundles. Collectively, our results suggest that Tmie’s role in sensory hair cells is to target and stabilize Tmc subunits to the site of MET.Author summaryHair cells mediate hearing and balance through the activity of a pore-forming channel in the cell membrane. The transmembrane inner ear (TMIE) protein is an essential component of the protein complex that gates this so-called mechanotransduction channel. While it is known that loss of TMIE results in deafness, the function of TMIE within the complex is unclear. Using zebrafish as a deafness model, Pacentine and Nicolson demonstrate that Tmie is required for the localization of other essential complex members, the transmembrane channel-like (Tmc) proteins, Tmc1/2b. They then evaluate twelve unique versions of Tmie, each containing mutations to different domains of Tmie. This analysis reveals that some mutations in Tmie cause dysfunctional gating of the channel as demonstrated through reduced hair cell activity, and that these same dysfunctional versions also display reduced Tmc expression at the normal site of the channel. These findings link hair cell activity with the levels of Tmc in the bundle, reinforcing the currently-debated notion that the Tmcs are the pore-forming subunits of the mechanotransduction channel. The authors conclude that Tmie, through distinct regions, is involved in both trafficking and stabilizing the Tmcs at the site of mechanotransduction.
No evidence for transvection in vivo by a superenhancer:promoter pair integrated into identical open chromatin at the Rosa26 locus
Authors: Tanimoto Keiji , Matsuzaki Hitomi , Okamura Eiichi , Ushiki Aki , Fukamizu Akiyoshi , Engel James Douglas 
Published: August 2018

AbstractLong-range associations between enhancers and their target gene promoters have been shown to play critical roles in executing genome function. Recent variations of chromosome capture technology have revealed a conprehensive view of intra- and inter-chromosomal contacts between specific genomic sites. The locus control region of the β-globin genes (β-LCR) is a super-enhancer that is capable of activating all of the β-like globin genes within the locus in cis through physical interaction by forming DNA loops. CTCF helps to mediate loop formation between LCR-HS5 and 3’HS1 in the human β-globin locus, in this way thought to contribute to the formation of a “chromatin hub”. The β-globin locus is also in close physical proximity to other erythrocyte-specific genes located long distances away on the same chromosome. In this case, erythrocyte-specific genes gather together at a shared “transcription factory” for co-transcription. Theoretically, enhancers could also activate target gene promoters on different chromosomes in trans, a phenomenon originally described as transvection in Drosophilla. Although close physical proximity has been reported for the β-LCR and the β-like globin genes when integrated at the mouse homologous loci in trans, their structural and functional interactions were found to be rare, possibly because a lack of suitable regulatory elements that might facilitate trans interactions. Therefore, we re-evaluated presumptive transvection-like enhancer-promoter communication by introducing CTCF binding sites and erythrocyte-specific transcription units into both LCR-enhancer and β-promoter alleles, each inserted into the mouse ROSA26 locus on separate chromosomes. Following cross-mating of mice to place the two mutant loci at the identical chromosomal position and into active chromation in trans, their transcriptional output was evaluated. The results demonstrate that there was no significant functional association between the LCR and the β-globin gene in trans even in this idealized experimental context.
Regulation by HSP70/90 in the different tissues and testis development of male cattle (Cattle-yak and Yak)
Authors: Liu Penggang , Yu Sijiu , Cui Yan , He Junfeng , Zhang Qian , Liu Jun , Song Liangli , Xu Yuanfang , Wang Ting , Zou Shengnan , Li Hui 
Published: August 2018

AbstractHSP70/90 play important role in testis develop and spermatozoa regulation, but the contact of HSP70/90 with infertility in cattle is unclear. Here, we focus on male cattle-yak and yak, which to investigate the expression and localization of HSP70/90 in different tissues, and explore the influence of HSP70/90 to infertility. In our study, a total of 54 cattle (24 cattle-yak and 30 yak) were examined. The HSP90 mRNA of cattle-yak was cloned first and found amino acid variation in HSP90, which led to difference at protein spatial structure compare with yak. To investigate whether the expression of HSP70/90 mRNA and protein are different in cattle-yak and yak, we used real-time quantitative PCR (qRT-PCR) and Western blot (WB) to examine them. We found that the expression level of HSP70/90 mRNA and protein are disparity in different tissues and testis development stages, and obviously high expression was observed in testicle during juvenile and adult, Moreover, it‘s interestingly in which the HSP70 expression is significant high in yak whereas HSP90 in cattle-yak (P<0.01). On this bases, we detect the location of HSP70/90 in testis by immunohistochemical (IHC) and immunofluorescence (IF), the results demonstrate that HSP70/90 were located in the epithelial cells, spermatogenic cells and mesenchymal cells. In summary, our study proved the expression of HSP70/90 are different in tissues, and the expression of HSP90 is obviously high in testis of cattle-yak, which propose that the infertility of cattle-yak may cause from up-regulating of HSP90.
In vivo detection of optically-evoked opioid peptide release
Authors: Al-Hasanil Ream , Wong Jenny-Marie T. , Mabrouk Omar S. , McCall Jordan G. , Schmitz Gavin P. , Porter-Stransky Kirsten A. , Aragona Brandon J. , Kennedy Robert T. , Bruchas Michael R. 
Published: August 2018

AbstractThough the last decade has seen accelerated advances in techniques and technologies to perturb neuronal circuitry in the brain, we are still poorly equipped to adequately dissect endogenous peptide release in vivo. To this end we developed a system that combines in vivo optogenetics with microdialysis and a highly sensitive mass spectrometry-based assay to measure opioid peptide release in freely moving rodents.
The identification of DNA binding regions of the σ54 factor using artificial neural network
Authors: Ferreira L. , Raittz R. T. , Marchaukoski J. N. , Weiss V. A. , Santos-Wiess I. C. R. , Costa P. A. B. , Voyceik R. , Rigo L. U. 
Published: August 2018

AbstractTranscription of many bacterial genes is regulated by alternative RNA polymerase sigma factors as the sigma 54 (σ54). A single essential σ promotes transcription of thousands of genes and many alternative σ factors promote transcription of multiple specialized genes required for coping with stress or development. Bacterial genomes have two families of sigma factors, sigma 70 (σ70) and sigma 54 (σ54). σ54 uses a more complex mechanism with specialized enhancers-binding proteins and DNA melting and is well known for its role in regulation of nitrogen metabolism in proteobacteria. The identification of these regulatory elements is the main step to understand the metabolic networks. In this study, we propose a supervised pattern recognition model with neural network to identify Transcription Factor Binding Sites (TFBSs) for σ54. This approach is capable of detecting σ54 TFBSs with sensitivity higher than 98% in recent published data. False positives are reduced with the addition of ANN and feature extraction, which increase the specificity of the program. We also propose a free, fast and friendly tool for σ54 recognition and a σ54 related genes database, available for consult. S54Finder can analyze from short DNA sequences to complete genomes and is available online. The software was used to determine σ54 TFBSs on the complete bacterial genomes database from NCBI and the result is available for comparison. S54Finder does the identification of σ54 regulated genes for a large set of genomes allowing evolutionary and conservation studies of the regulation system between the organisms.