bluuebunny/crossref_metadata_2025_split huggingface dataset:
Miniaturization technologies for cost-effective AmpliSeq library preparation for next generation sequencing
Authors: Ogiso-Tanaka Eri , Kaga Akito , Hajika Makita 
Published: November 2018

AbstractPurposeAmpliSeq technology, the target enrichment method for next-generation sequencing (NGS), enables quick and easy detection of the genomic “hot spot” region frequently mutated in species. Even though the cost of NGS has decreased, library preparation cost accounts for a more significant proportion of the total cost. If AmpliSeq library can be prepared at a lower cost, large-scale precision oncology can be more easily carried out. Furthermore, this technology can be widely applied not only to medical research, but also to polymorphism detection in biology. This study aimed to reduce the cost of AmpliSeq library preparation by adopting miniaturization technology.MethodsWe used approximately 10 ng of genomic DNA for ultra-multiplex PCR of 384, 768, 1152, 1920, and 3072 amplicons. Multiplex PCR was performed in a total volume of 1.6, 2.0, and 2.4 μL, using a nano-liter liquid handler, for library preparation.ResultsThe success rate of library construction decreased with decreasing total multiplex PCR reaction volume. Using 1.6-, 2.0-, and 2.4-μL reactions, the success rates of ultra-multiplex PCR were 25%, 95%, and 100%, respectively. We could stably create libraries of the correct amplicon size, with an amplicon number of approximately 1500 or less. As a result of NGS, uniformity of PCR amplification and read length of quality-checked libraries were hardly affected by the number of amplicons.ConclusionHere, we show that the minimum volume for a stable reaction was 2.4 μL and the maximum number of amplicons obtained was approximately 1500. The protocol saved 86.8% in reagent usage and reduced handling time by 85% compared to that required by the manual protocol. Therefore, miniaturization technologies could reduce the cost of AmpliSeq library preparation through minimization of reagents.
Quantified ensemble 3D surface features modeled as a window on centric diatom valve morphogenesis
Authors: Pappas Janice L. 
Published: November 2018

AbstractMorphological surface features are a record of genetic and developmental processes as well as environmental influences. The 3D geometric “terrain” of the surface consists of slopes via tangents, peaks and valleys via normals, smoothness of the transition between peaks and valleys, and point connections as flatness or curvature among all features. Such geometric quantities can be used to indicate morphological changes in valve formation over time. Quantified 3D surface features as geometric pattern ensembles may be representative of structural snapshots of the morphogenetic process.For diatoms, valve formation and pattern morphogenesis has been modeled using Turing-like and other algorithmic techniques to mimic the way in which diatoms exhibit the highly diverse patterns on their valve surfaces. How the created surface features are related to one another is not necessarily determined via such methods. With the diatom valve face structure of layered areolae, cribra, and other morphological characters, valve formation exhibits different combined geometries unfolding as 3D structural ensembles in particular spatial arrangements. Quantifying ensemble 3D surface geometries is attainable via models devised using parametric 3D equations and extracting surface features via partial derivatives for slopes, peaks and valleys, smoothness, and flatness as feature connectedness. Differences in ensemble 3D surface features may be used to assess structural differences among selected diatom genera as indicators of different valve formation sequences in surface generation and morphogenesis.
Genetic selection for small molecule production in competitive microfluidic droplets
Authors: Millet Larry J. , Velez Jessica M. , Michener Joshua K. 
Published: November 2018

AbstractBiosensors can be used to screen or select for small molecule production in engineered microbes. However, mutations to the biosensor that interfere with accurate signal transduction are common, producing an excess of false positives. Strategies have been developed to avoid this limitation by physically separating the production pathway and biosensor, but these approaches have only been applied to screens, not selections. We have developed a novel biosensor-mediated selection strategy using competition between co-cultured bacteria. When applied to biosynthesis ofcis,cis-muconate, we show that this strategy yields a selective advantage to producer strains that outweighs the costs of production. By encapsulating the competitive co-cultures into microfluidic droplets, we successfully enriched for muconate-producing strains from a large population of control non-producers. Facile selections for small molecule production will increase testing throughput for engineered microbes and allow for the rapid optimization of novel metabolic pathways.
Enzymatic and structural characterization of the Naegleria fowleri glucokinase
Authors: Milanes Jillian E. , Suryadi Jimmy , Abendroth Jan , Van Voorhis Wesley C. , Barrett Kayleigh F. , Dranow David M. , Phan Isabelle Q. , Patrick Stephen L. , Rozema Soren D. , Khalifa Muhammad M. , Golden Jennifer E. , Morris James C. 
Published: November 2018

ABSTRACTInfection with the free-living amoeba Naegleria fowleri leads to life-threatening primary amoebic meningoencephalitis. Efficacious treatment options for these infections are limited and the mortality rate is very high (~98%). Parasite metabolism may provide suitable targets for therapeutic design. Like most other organisms, glucose metabolism is critical for parasite viability, being required for growth in culture. The genome of the parasite encodes a single glucose phosphorylating enzyme, a glucokinase (Glck). The products of this enzyme are required for both glycolysis and the pentose phosphate pathway. The N. fowleri Glck (NfGlck) shares limited (25%) amino acid identity with the mammalian host enzyme (HsGlck), suggesting that parasite-specific inhibitors with anti-amoeba activity could be generated. Following heterologous expression, NfGlck was found to have a limited hexose substrate range, with greatest activity observed with glucose. The enzyme had apparent Km values of 42.5 ± 7.3 μM and 141.6 ± 9.9 μM for glucose and ATP, respectively. The NfGlck structure was determined and refined to 2.2 Å resolution, revealing that the enzyme shares greatest structural similarity with the Trypanosoma cruzi Glck. These similarities include binding modes and binding environments for substrates. To identify inhibitors of NfGlck, we screened a small collection of inhibitors of glucose phosphorylating enzymes and identified several small molecules with IC50 values < 1 μM that may prove useful as hit chemotypes for further lead and therapeutic development against N. fowleri.
Family reunion via error correction: An efficient analysis of duplex sequencing data
Authors: Stoler Nicholas , Arbeithuber Barbara , Povysil Gundula , Heinzl Monika , Salazar Renato , Makova Kateryna , Tiemann-Boege Irene , Nekrutenko Anton 
Published: November 2018

AbstractDuplex sequencing is the most accurate approach for identification of sequence variants present at very low frequencies. Its power comes from pooling together multiple descendants of both strands of original DNA molecules, which allows distinguishing true nucleotide substitutions from PCR amplification and sequencing artifacts. This strategy comes at a cost—sequencing the same molecule multiple times increases dynamic range but significantly diminishes coverage, making whole genome duplex sequencing prohibitively expensive. Furthermore, every duplex experiment produces a substantial proportion of singleton reads that cannot be used in the analysis and are, technically, thrown away. In this paper we demonstrate that a significant fraction of these reads contains PCR or sequencing errors within duplex tags. Correction of such errors allows “reuniting” these reads with their respective families increasing the output of the method and making it more cost effective. Additionally, we combine error correction strategy with a number of algorithmic improvements in a new version of the duplex analysis software, Du Novo 2.0, readily available through Galaxy, Bioconda, and as the source code.
Open Humans: A platform for participant-centered research and personal data exploration
Authors: Tzovaras Bastian Greshake , Angrist Misha , Arvai Kevin , Dulaney Mairi , Estrada-Galiñanes Vero , Gunderson Beau , Head Tim , Lewis Dana , Nov Oded , Shaer Orit , Tzovara Athina , Bobe Jason , Ball Mad Price 
Published: November 2018

AbstractBackgroundMany aspects of our lives are now digitized and connected to the internet. As a result, individuals are now creating and collecting more personal data than ever before. This offers an unprecedented chance for human-participant research ranging from the social sciences to precision medicine. With this potential wealth of data come practical problems (such as how to merge data streams from various sources), as well as ethical problems (such as how to best balance risks and benefits when enabling personal data sharing by individuals).ResultsTo begin to address these problems in real time, we present Open Humans, a community-based platform that enables personal data collections across data streams, giving individuals more personal data access and control of sharing authorizations, and enabling academic research as well as patient-led projects. We showcase data streams that Open Humans combines (e.g. personal genetic data, wearable activity monitors, GPS location records and continuous glucose monitor data), along with use cases of how the data facilitates various projects.ConclusionsOpen Humans highlights how a community-centric ecosystem can be used to aggregate personal data from various sources as well as how these data can be used by academic and citizen scientists through practical, iterative approaches to sharing that strive to balance considerations with participant autonomy, inclusion, and privacy.
CAT tails drive on- and off-ribosome degradation of stalled polypeptides
Authors: Sitron Cole S. , Brandman Onn 
Published: November 2018

SummaryStalled translation produces incomplete, ribosome-associated polypeptides that Ribosome-associated Quality Control (RQC) targets for degradation via the ubiquitin ligase Ltn1. During this process, the Rqc2 protein and large ribosomal subunit elongate stalled polypeptides with carboxy-terminal alanine and threonine residues (CAT tails). Failure to degrade CAT-tailed proteins disrupts global protein homeostasis, as CAT-tailed proteins aggregate and sequester chaperones. Why cells employ such a potentially toxic process during RQC is unclear. Here, we developed quantitative techniques to assess how CAT tails affect stalled polypeptide degradation in Saccharomyces cerevisiae. We found that CAT tails improve Ltn1’s efficiency in targeting structured polypeptides, which are otherwise poor Ltn1 substrates. If Ltn1 fails, CAT tails undergo a backup route of ubiquitylation off the ribosome, mediated by the ubiquitin ligase Hul5. Thus, CAT tails functionalize the carboxy-termini of stalled polypeptides to drive their degradation on and off the ribosome.
Unbiased detection of CRISPR off-targets in vivo using DISCOVER-Seq
Authors: Wienert Beeke , Wyman Stacia K , Richardson Christopher D , Yeh Charles D , Akcakaya Pinar , Porritt Michelle J , Morlock Michaela , Vu Jonathan T , Kazane Katelynn R , Watry Hannah L , Judge Luke M , Conklin Bruce R , Maresca Marcello , Corn Jacob E 
Published: November 2018

AbstractGenome editing using nucleases such as CRISPR-Cas induces programmable DNA damage at a target genomic site but can also affect off-target sites. Here, we develop a powerful, sensitive assay for the unbiased identification of off-target sites that we term DISCOVER-Seq. This approach takes advantage of the recruitment of endogenous DNA repair factors for genome-wide identification of Cas-induced double-strand breaks. One such factor, MRE11, is recruited precisely to double-strand breaks, enabling molecular characterization of nuclease cut sites with single-base resolution. DISCOVER-Seq detects off-targets in cellular models and in vivo upon adenoviral gene editing of mouse livers, paving the way for real-time off-target discovery during therapeutic gene editing. DISCOVER-Seq is furthermore applicable to multiple types of Cas nucleases and provides an unprecedented view of events that precede repair of the affected sites.
Geocoding genomic databases using GBIF
Authors: Page Roderic D. M. 
Published: November 2018

AbstractMany nucleotide sequences in the publicly available genomics databases lack spatial information, such as the latitude and longitude coordinates for the locality where the sample for sequencing was taken. In this note I discuss several approaches to geocoding sequence records. The ﬁrst method uses the Global Biodiversity Information Facility (GBIF: https://gbif.org) as a gazetter. The availability of a simple full text search across GBIF data makes it possible to rapidly geocode locality information simply by searching for matching records within GBIF. Hence if a sequence lacks coordinates but has some locality information it could be rapidly geocoded. The second method matches voucher specimen code for sequences with the corresponding specimen records in GBIF, which may be geocoded even if the sequence obtained from that specimen is not. Lastly, there will be cases where sequence records lack either locality or specimen information, but that information is available elsewhere, such as in the published literature or in supplementary data files. The possibility of publishing geocoded sequence records using Github is discussed.
Discovery of volatile biomarkers of Parkinson’s disease from sebum
Authors: Trivedi Drupad K , Sinclair Eleanor , Xu Yun , Sarkar Depanjan , Liscio Camilla , Banks Phine , Milne Joy , Silverdale Monty , Kunath Tilo , Goodacre Royston , Barran Perdita 
Published: November 2018

Parkinson’s disease (PD) is a progressive, neurodegenerative disease that presents with significant motor symptoms, for which there is no diagnostic test (1–3). We have serendipitously identified a hyperosmic individual, a ‘Super Smeller’ that can detect PD by odor alone, and our early pilot studies have indicated that the odor was present in the sebum from the skin of PD subjects(4). Here, we have employed an unbiased approach to investigate the volatile metabolites of sebum samples obtained non-invasively from the upper back of 64 participants in total (21 controls and 43 PD subjects). Our results, validated by an independent cohort, identified a distinct volatiles-associated signature of PD, including altered levels of perillic aldehyde and eicosane, the smell of which was then described as being highly similar to the scent of PD by our ‘Super Smeller’.1 sentence summaryMetabolomics identifies volatile odorous compounds from patient sebum that associate with the smell of Parkinson’s.
Cell-type-specific genomics reveals histone modification dynamics in mammalian meiosis
Authors: Gabriel Lam Kwan-Wood , Brick Kevin , Cheng Gang , Pratto Florencia , Camerini-Otero R. Daniel 
Published: November 2018

AbstractMeiosis is the specialized cell division during which parental genomes recombine to create genotypically unique gametes. Despite its importance, mammalian meiosis cannot be studiedin vitro, greatly limiting mechanistic studies.In vivo, meiocytes progress asynchronously through meiosis and therefore the study of specific stages of meiosis is a challenge. Here, we describe a method for isolating pure sub-populations of nuclei that allows for detailed study of meiotic sub-stages. Interrogating the H3K4me3 landscape revealed dynamic chromatin transitions between sub-stages of meiotic prophase I, both at sites of genetic recombination and at gene promoters. We also leveraged this method to perform the first comprehensive, genome-wide survey of histone marks in meiotic prophase, revealing a heretofore unappreciated complexity of the epigenetic landscape at meiotic recombination hotspots. Ultimately, this study presents a straightforward, scalable framework for interrogating the complexities of mammalian meiosis.
SVXplorer: Identification of structural variants through overlap of discordant clusters
Authors: Kathuria Kunal , Ratan Aakrosh 
Published: November 2018

MotivationThe identification of structural variants using short-read data remains challenging. Most approaches ignore signatures of complex variants such as those generated by trans-posable elements. This can result in lower precision and sensitivity in identification of the more common structural variants such as deletions and duplications.ResultsWe present SVXplorer, which uses a streamlined sequential approach to integrate discordant paired-end alignments with split-reads and read depth information. We show that it outperforms several existing approaches in both reproducibility and accuracy on real and simulated datasets.AvailabilitySVXplorer is available at https://github.com/kunalkathuria/SVXplorer.
Classifying Asian Rice Cultivars (Oryza sativa L.) into Indica and Japonica Using Logistic Regression Model with Publicly Available Phenotypic Data
Authors: Kim Bongsong 
Published: November 2018

AbstractThis article introduces how to implement the logistic regression model (LRM) with phenotypic variables for classifying Asian rice (Oryza sativa L.) cultivars into two pivotal subpopulations, indica and japonica. This study took advantage of publicly available data attached to a previous paper. The classification accuracy was assessed using an area under curve (AUC) of a receiver operating characteristic (ROC) curve. Given 24 phenotypic variables for 280 indica/japonica accessions, the LRMs were fitted with up to six phenotypic variables of all possible combinations; the highest AUC accounts for 0.9977, obtained with six variables including panicle number per plant, seed number per panicle, florets per panicle, panicle fertility, straighthead susceptibility and blast resistance. Overall, the more variables there are, the higher the resulting AUCs are. The ultimate purpose of this study is to demonstrate the indica/japonica prediction ability of the LRM when applied to unclassified Asian rice cultivars. To estimate the indica/japonica prediction accuracy, ten-fold cross-validations were conducted 100 times with the 280 indica/japonica accessions using the LRM with parameters that yielded the highest AUC. The resulting prediction accuracy accounted for 0.9779. This suggests that the LRM promises to be a highly effective indica/japonica prediction tool using phenotypic variables in Asian cultivated rice.
PTPN14 Degradation by High-Risk Human Papillomavirus E7 Limits Keratinocyte Differentiation and Contributes to HPV-Mediated Oncogenesis
Authors: Hatterschide Joshua , Bohidar Amelia E. , Grace Miranda , Nulton Tara J. , Windle Brad , Morgan Iain M. , Munger Karl , White Elizabeth A. 
Published: November 2018

AbstractHigh-risk human papillomavirus (HPV) E7 proteins enable oncogenic transformation of HPV-infected cells by inactivating host cellular proteins. High-risk but not low-risk HPV E7 target PTPN14 for proteolytic degradation, suggesting that PTPN14 degradation may be related to their oncogenic activity. HPV infects human keratinocytes but the role of PTPN14 in keratinocytes and the consequences of PTPN14 degradation are unknown. Using an HPV16 E7 variant that can inactivate RB1 but cannot degrade PTPN14 we found that high-risk HPV E7-mediated PTPN14 degradation impairs keratinocyte differentiation. Deletion ofPTPN14from primary human keratinocytes decreased keratinocyte differentiation gene expression. Related to oncogenic transformation, both HPV16 E7-mediated PTPN14 degradation andPTPN14deletion promoted keratinocyte survival following detachment from a substrate. PTPN14 degradation contributed to high-risk HPV E6/E7-mediated immortalization of primary keratinocytes and HPV-positive but not HPV-negative cancers exhibit a gene expression signature consistent with PTPN14 inactivation. We find that PTPN14 degradation impairs keratinocyte differentiation and propose that this contributes to high-risk HPV E7-mediated oncogenic activity independent of RB1 inactivation.Significance StatementHuman papillomaviruses uncouple proliferation from differentiation in order to enable virus replication in epithelial cells. HPV E7 proteins are well established to promote proliferation by binding to and inactivating retinoblastoma family proteins and other cell cycle inhibitors. However, mechanisms by which high-risk HPV oncoproteins inhibit differentiation have not been defined. This paper identifies the first mechanism by which high-risk HPV E7 inhibit keratinocyte differentiation. The inhibition of differentiation requires degradation of the cellular protein PTPN14 by high-risk HPV E7 and this degradation is related to the ability of high-risk HPV oncoproteins to immortalize keratinocytes and to cause cancer.
Integrative Pharmacogenomics Analysis of Patient Derived Xenografts
Authors: Mer Arvind Singh , Ba-alawi Wail , Smirnov Petr , Wang Yi Xiao , Brew Ben , Ortmann Janosch , Tsao Ming-Sound , Cescon David , Goldenberg Anna , Haibe-Kains Benjamin 
Published: November 2018

ABSTRACTOne of the key challenges in cancer precision medicine is finding robust biomarkers of drug response. Patient-derived tumor xenografts (PDXs) have emerged as reliable preclinical models since they better recapitulate tumor response to chemo- and targeted therapies. However, the lack of standard tools poses a challenge in the analysis of PDXs with molecular and pharmacological profiles. Efficient storage, access and analysis is key to the realization of the full potential of PDX pharmacogenomic data. We have developed Xeva (XEnograft Visualization & Analysis), an open-source software package for processing, visualization and integrative analysis of a compendium ofin vivopharmacogenomic datasets. The Xeva package follows the PDX minimum information (PDX-MI) standards and can handle both replicate-based and 1×1×1 experimental designs. We used Xeva to characterize the variability of gene expression and pathway activity across passages. We found that only a few genes and pathways have passage specific alterations (median intraclass correlation of 0.53 for genes and positive enrichment score for 92.5% pathways). For example, activity of the mRNA 3’-end processing and elongation arrest and recovery pathways were strongly affected by model passaging (gene set enrichment analysis false discovery rate [FDR] <5%). We then leveraged our platform to link the drug response and the pathways whose activity is consistent across passages by mining the Novartis PDX Encyclopedia (PDXE) data containing 1,075 PDXs spanning 5 tissue types and 62 anticancer drugs. We identified 87 pathways significantly associated with response to 51 drugs (FDR < 5%), including associations such as erlotinib response and signaling by EGFR in cancer pathways and MAP kinase activation in TLR cascade and binimetinib response. Among the significant pathway-drug associations, we found novel biomarkers based on gene expressions, Copy Number Aberrations (CNAs) and mutations predictive of drug response (concordance index > 0.60; FDR < 0.05). Xeva provides a flexible platform for integrative analysis of preclinicalin vivopharmacogenomics data to identify biomarkers predictive of drug response, a major step toward precision oncology.