bluuebunny/crossref_metadata_2025_split huggingface dataset:
A suite of transgenic driver and reporter mouse lines with enhanced brain cell type targeting and functionality
Authors: Daigle Tanya L. , Madisen Linda , Hage Travis A. , Valley Matthew T. , Knoblich Ulf , Larsen Rylan S. , Takeno Marc M. , Huang Lawrence , Gu Hong , Larsen Rachael , Mills Maya , Bosma-Moody Alice , Siverts La’Akea , Walker Miranda , Graybuck Lucas T. , Yao Zizhen , Fong Olivia , Garren Emma , Lenz Garreck , Chavarha Mariya , Pendergraft Julie , Harrington James , Hirokawa Karla E. , Harris Julie A. , McGraw Medea , Ollerenshaw Douglas R. , Smith Kimberly , Baker Christopher A. , Ting Jonathan T. , Sunkin Susan M. , Lecoq Jerome , Lin Michael Z. , Boyden Edward S. , Murphy Gabe J. , da Costa Nuno , Waters Jack , Li Lu , Tasic Bosiljka , Zeng Hongkui 
Published: November 2017

SUMMARYModern genetic approaches are powerful in providing access to diverse types of neurons within the mammalian brain and greatly facilitating the study of their function. We here report a large set of driver and reporter transgenic mouse lines, including 23 new driver lines targeting a variety of cortical and subcortical cell populations and 26 new reporter lines expressing an array of molecular tools. In particular, we describe the TIGRE2.0 transgenic platform and introduce Cre-dependent reporter lines that enable optical physiology, optogenetics, and sparse labeling of genetically-defined cell populations. TIGRE2.0 reporters broke the barrier in transgene expression level of single-copy targeted-insertion transgenesis in a wide range of neuronal types, along with additional advantage of a simplified breeding strategy compared to our first-generation TIGRE lines. These novel transgenic lines greatly expand the repertoire of high-precision genetic tools available to effectively identify, monitor, and manipulate distinct cell types in the mouse brain.
Deciphering eukaryotic cis-regulatory logic with 100 million random promoters
Authors: de Boer Carl G. , Vaishnav Eeshit Dhaval , Sadeh Ronen , Abeyta Esteban Luis , Friedman Nir , Regev Aviv 
Published: November 2017

AbstractDeciphering cis-regulation, the code by which transcription factors (TFs) interpret regulatory DNA sequence to control gene expression levels, is a long-standing challenge. Previous studies of native or engineered sequences have remained limited in scale. Here, we use random sequences as an alternative, allowing us to measure the expression output of over 100 million synthetic yeast promoters. Random sequences yield a broad range of reproducible expression levels, indicating that the fortuitous binding sites in random DNA are functional. From these data we learn models of transcriptional regulation that predict over 94% of the expression driven from independent test data and nearly 89% from sequences from yeast promoters. These models allow us to characterize the activity of TFs and their interactions with chromatin, and help refine cis-regulatory motifs. We find that strand, position, and helical face preferences of TFs are widespread and depend on interactions with neighboring chromatin. Such massive-throughput regulatory assays of random DNA provide the diverse examples necessary to learn complex models of cis-regulatory logic.
Improving bioinformatics prediction of microRNA targets by ranks aggregation
Authors: Quillet Aurélien , Saad Chadi , Ferry Gaētan , Anouar Youssef , Vergne Nicolas , Lecroq Thierry , Dubessy Christophe 
Published: November 2017

AbstractmicroRNAs are non-coding RNAs which down-regulate a large number of target mRNAs and modulate cell activity. Despite continued progress, bioinformatics prediction of microRNA targets remains a challenge since available softwares still suffer from a lack of accuracy and sensitivity. Moreover, these tools show fairly inconsistent results from one another. Thus, in an attempt to circumvent these difficulties, we aggregated all human results of three important prediction algorithms (miRanda, PITA and SVmicrO) showing additional characteristics in order to rerank them into a single list. This database is freely available through a webtool called miRabel (http://bioinfo.univ-rouen.fr/mirabel/) which can take either a list of miRNAs, genes or signaling pathways as search inputs. Receiver Operating Characteristic curves and Precision-Recall curves analysis carried out using experimentally validated data and very large datasets show that miRabel significantly improves the prediction of miRNA targets compared to the three algorithms used separatly. Moreover, using the same analytical methods, miRabel shows significantly better predictions than other popular algorithms such as MBSTAR and miRWalk. Interestingly, a F-score analysis revealed that miRabel also significantly improves the relevance of the top results. The aggregation of results from different databases is therefore a powerful and generalizable approach to many other species to improve miRNA target predictions. Thus, miRabel is an efficient tool to accurately identify miRNA targets and integrate them into a biological context.
Brain Modularity Mediates the Relation between Task Complexity and Performance
Authors: Yue Qiuhai , Martin Randi , Fischer-Baum Simon , Ramos-Nuñez Aurora I. , Ye Fengdan , Deem Michael W. 
Published: November 2017

AbstractRecent work in cognitive neuroscience has focused on analyzing the brain as a network, rather than as a collection of independent regions. Prior studies taking this approach have found that individual differences in the degree of modularity of the brain network relate to performance on cognitive tasks. However, inconsistent results concerning the direction of this relationship have been obtained, with some tasks showing better performance as modularity increases and other tasks showing worse performance. A recent theoretical model (Chen & Deem, 2015) suggests that these inconsistencies may be explained on the grounds that high-modularity networks favor performance on simple tasks whereas low-modularity networks favor performance on more complex tasks. The current study tests these predictions by relating modularity from resting-state fMRI to performance on a set of simple and complex behavioral tasks. Complex and simple tasks were defined on the basis of whether they did or did not draw on executive attention. Consistent with predictions, we found a negative correlation between individuals’ modularity and their performance on a composite measure combining scores from the complex tasks but a positive correlation with performance on a composite measure combining scores from the simple tasks. These results and theory presented here provide a framework for linking measures of whole brain organization from network neuroscience to cognitive processing.
Modularity of the metabolic gene network as a prognostic biomarker for hepatocellular carcinoma
Authors: Ye Fengdan , Jia Dongya , Lu Mingyang , Levine Herbert , Deem Michael W 
Published: November 2017

AbstractAbnormal metabolism is an emerging hallmark of cancer. Cancer cells utilize both aerobic glycolysis and oxidative phosphorylation (OXPHOS) for energy production and biomass synthesis. Understanding the metabolic reprogramming in cancer can help design therapies to target metabolism and thereby to improve prognosis. We have previously argued that more malignant tumors are usually characterized by a more modular expression pattern of cancer-associated genes. In this work, we analyzed the expression patterns of metabolism genes in terms of modularity for 371 hepatocellular carcinoma (HCC) samples from the Cancer Genome Atlas (TCGA). We found that higher modularity significantly correlated with glycolytic phenotype, later tumor stages, higher metastatic potential, and cancer recurrence, all of which contributed to poorer prognosis. Among patients with recurred tumor, we found the correlation of higher modularity with worse prognosis during early to mid-progression. Furthermore, we developed metrics to calculate individual modularity, which was shown to be predictive of cancer recurrence and patients’ survival and therefore may serve as a prognostic biomarker. Our overall conclusion is that more aggressive HCC tumors, as judged by decreased host survival probability, had more modular expression patterns of metabolic genes. These results may be used to identify cancer driver genes and for drug design.
Interaction of lecithin-cholesterol acyltransferase with lipid surfaces and apolipoprotein A-I derived peptides: implications for the cofactor mechanism of apolipoprotein A-I
Authors: Casteleijn Marco G. , Parkkila Petteri , Viitala Tapani , Koivuniemi Artturi 
Published: November 2017

AbstractLecithin-cholesterol acyltransferase (LCAT) is an enzyme responsible for the formation of cholesteryl esters from cholesterol (CHOL) and phospholipid (PL) molecules in high-density lipoprotein (HDL) particles that play a crucial role in the reverse cholesterol transport and the development of coronary heart disease (CHD). However, it is poorly understood how LCAT interacts with lipoprotein surfaces and how apolipoprotein A-I (apoA-I) activates it. Thus, here we have studied the interactions between LCAT and lipids through extensive atomistic and coarse-grained molecular dynamics simulations to reveal mechanistic details behind the cholesterol esterification process catalyzed by LCAT. In addition, we studied the binding of LCAT to apoA-I derived peptides, and their effect on LCAT lipid association utilizing experimental surface sensitive biophysical methods. Our simulations show that LCAT anchors itself to lipoprotein surfaces by utilizing non-polar amino acids located in the membrane-binding domain and the active site tunnel opening. Meanwhile, the membrane anchoring hydrophobic amino acids attract cholesterol molecules next to them. The results also highlight the role of the lid-loop in the lipid binding and conformation of LCAT with respect to the lipid surface. The apoA-I derived peptides from the LCAT activating region bind to LCAT and promote its lipid surface interactions, although some of these peptides do not bind lipids individually. By means of free-energy calculations we provided a hypothetical explanation for this mechanism. We also found that the transfer free-energy of PL to the active site is consistent with the activation energy of LCAT. Furthermore, the entry of CHOL molecules into the active site becomes highly favorable by the acylation of SER181. The results provide substantial mechanistic insights concerning the activity of LCAT that may lead to the development of novel pharmacological agents preventing CHD in the future.
Control of bacterial population density with population feedback and molecular sequestration
Authors: McCardell Reed D. , Huang Shan , Green Leopold N. , Murray Richard M. 
Published: November 2017

AbstractGenetic engineering technology has become sophisticated enough to allow precise manipulation of bacterial genetic material. Engineering efforts with these technologies have created modified bacteria for various medical, industrial, and environmental purposes, but organisms designed for specific functions require improvements in stability, longevity, or efficiency of function. Most bacteria live in multispecies communities, whose composition may be closely linked to the effect the community has on the environment. Bacterial engineering efforts will benefit from building communities with regulated compositions, which will enable more stable and powerful community functions.We present a design of a synthetic two member bacterial community capable of maintaining its composition at a defined ratio of [cell type 1]: [cell type 2]. We have constructed the genetic motif that will act in each cell in the two member community, containing an AHL-based negative feedback loop that activates ccdB toxin, which caps population density with increasing feedback strength. It also contains one of two ccdB sequestration modules, either the ccdA protein antitoxin, or an RNA device which prevents transcription and translation of ccdB mRNA, that rescues capped population density with induction. We compare absorbance and colony counting methods of estimating bacterial population density, finding that absorbance-based methods overestimate viable population density when ccdB toxin is used to control population density.Prior modeling results show that two cell types containing this genetic circuit motif that reciprocally activate the other’s ccdB sequestration device will establish a steady state ratio of cell types. Experimental testing and tuning the full two member community will help us improve our modeling of multi-member bacterial communities, learn more about the strengths and weaknesses of our design for community composition control, and identify general principles of design of compositionally-regulated microbial communities.
AtRsgAfromArabidopsis thalianacontrols maturation of the small subunit of the chloroplast ribosome
Authors: Janowski Marcin , Zoschke Reimo , Scharff Lars , Jaime Silvia Martinez , Ferrari Camilla , Proost Sebastian , Omranian Nooshin , Musialak-Lange Magdalena , Nikoloski Zoran , Graf Alexander , Schöttler Mark A. , Sampathkumar Arun , Vaid Neha , Mutwil Marek 
Published: November 2017

SummaryPlastid ribosomes are very similar in structure and function to ribosomes of their bacterial ancestors. Since ribosome biogenesis is not thermodynamically favourable at biological conditions, it requires activity of many assembly factors. Here, we have characterized a homolog of bacterialrsgAinArabidopsis thalianaand show that it can complement the bacterial homolog. Functional characterization of a strong mutant in Arabidopsis revealed that the protein is essential for plant viability, while a weak mutant produced dwarf, chlorotic plants that incorporated immature pre-16S ribosomal RNA into translating ribosomes. Physiological analysis of the mutant plants revealed smaller, but more numerous chloroplasts in the mesophyll cells, reduction of chlorophyllaandb, depletion of proplastids from the rib meristem and decreased photosynthetic electron transport rate and efficiency. Comparative RNA-sequencing and proteomic analysis of the weak mutant and wild-type plants revealed that various biotic stress-related, transcriptional regulation and post-transcriptional modification pathways were repressed in the mutant. Intriguingly, while nuclear- and chloroplast-encoded photosynthesis-related proteins were less abundant in the mutant, the corresponding transcripts were upregulated, suggesting an elaborate compensatory mechanism, potentially via differentially active retrograde signalling pathways. To conclude, this study reveals a new chloroplast ribosome assembly factor and outlines the transcriptomic and proteomic responses of the compensatory mechanism activated during decreased chloroplast function.Significance statementAtRsgA is an assembly factor necessary for maturation of the small subunit of the chloroplast ribosome. Depletion of AtRsgA leads to dwarfed, chlorotic plants and smaller, but more numerous chloroplasts. Large-scale transcriptomic and proteomic analysis revealed that chloroplast-encoded and - targeted proteins were less abundant, while the corresponding transcripts were upregulated in the mutant. We analyse the transcriptional responses of several retrograde signalling pathways to suggest a mechanism underlying this compensatory response.
Cell-free prototyping strategies for enhancing the sustainable production of polyhydroxyalkanoates bioplastics
Authors: Kelwick Richard , Ricci Luca , Chee Soo Mei , Bell David , Webb Alexander J. , Freemont Paul S. 
Published: November 2017

ABSTRACTThe polyhydroxyalkanoates are a group of microbially-produced biopolymers that have been proposed as sustainable alternatives to several oil-derived plastics. However, polyhydroxyalkanoates are currently more expensive to produce than oil-derived plastics and therefore, more efficient production processes would be desirable. Cell-free transcription-translation-based metabolic engineering strategies have been previously used to optimise several different biosynthetic pathways but not the polyhydroxyalkanoates biosynthetic pathways. Here we have developed several Escherichia coli cell-free transcription-translation-based systems for in vitro prototyping of polyhydroxyalkanoates biosynthetic operons, and also for screening relevant metabolite recycling enzymes. These cell-free transcription-translation reactions were customised through the addition of whey permeate, an industrial waste that has been previously used as a low-cost feedstock for optimising in vivo polyhydroxyalkanoates production. We found that the inclusion of an optimal concentration of whey permeate enhanced relative cell-free GFPmut3b production by ~20% compared to control reactions that did not include whey permeate. An analysis of pH in our cell-free reactions suggests that the observed increase in GFPmut3b production was likely through enhanced ATP generation, as a consequence of the glycolytic processing of lactose present in whey permeate. We also found that whey permeate enhanced cell-free reactions produced ~3μM (R)-3HB-CoA, whilst, coupled cell-free biotransformation/transcription-translation reactions produced a ten-fold greater yield of (R)-3HB-CoA. These reactions were also used to characterise a Clostridium propionicum propionyl CoA transferase enzyme that can recycle Acetyl-CoA. Together our data demonstrate that cell-free approaches can be used to complement in vivo workflows for identifying additional strategies for optimising polyhydroxyalkanoates production.
Decrease of Nibrin expression in chronic hypoxia is associated with hypoxia-induced chemoresistance in medulloblastoma cells
Authors: Cowman Sophie , Fan Yuen Ngan , Pizer Barry , Sée Violaine 
Published: December 2017

AbstractSolid tumours are less oxygenated than normal tissues. This is called tumour hypoxia and leads to resistance to radiotherapy and chemotherapy. The molecular mechanisms underlying such resistance have been investigated in a range of tumour types, including the adult brain tumours glioblastoma, yet little is known for paediatric brain tumours. Medulloblastoma (MB) is the most common malignant brain tumour in children. Here we used a common MB cell line (D283-MED), to investigate the mechanisms of chemo and radio-resistance in MB, comparing to another MB cell line (MEB-Med8A) and to a widely used glioblastoma cell line (U87MG). In D283-MED and U87MG, chronic hypoxia (5 days), but not acute hypoxia (24 h) induced resistance to etoposide and X-ray irradiation. This acquired resistance upon chronic hypoxia was much less pronounced in MEB-Med8A cells. Using a transcriptomic approach in D283-MED cells, we found a large transcriptional remodelling upon long term hypoxia, in particular the expression of a number of genes involved in detection and repair of double strand breaks (DSB) was altered. The levels of Nibrin (NBN) and MRE11, members of the MRN complex (MRE11/Rad50/NBN) responsible for DSB recognition, were significantly down-regulated. This was associated with a reduction of Ataxia Telangiectasia Mutated (ATM) activation by etoposide, indicating a profound dampening of the DNA damage signalling in hypoxic conditions. As a consequence, p53 activation by etoposide was reduced, and cell survival enhanced. Whilst U87MG shared the same dampened p53 activity, upon chemotherapeutic drug treatment in chronic hypoxic conditions, these cells used a different mechanism, independent of the DNA damage pathway. Together our results demonstrate a new mechanism explaining hypoxia-induced resistance involving the alteration of the response to DSB, but also highlight the cell type to cell type diversity and the necessity to take into account the differing tumour genetic make-up when considering re-sensitisation therapeutic protocols.
High resolution genetic mapping of causal regulatory interactions in the human genome
Authors: Kumasaka Natsuhiko , Knights Andrew , Gaffney Daniel 
Published: December 2017

AbstractPhysical interaction of distal regulatory elements in three-dimensional space poses a significant challenge for studies of common disease, because noncoding risk variants may be substantial distances from the genes they regulate. Experimental methods to capture these interactions, such as chromosome conformation capture (CCC), usually cannot assign causal direction of effect between regulatory elements, an important component of disease fine-mapping. Here, we developed a statistical model that uses Mendelian Randomisation within a Bayesian hierarchical model framework, and applied it to a novel ATAC-seq data from 100 individuals mapping over 15,000 putatively causal interactions between distal regions of open chromatin. Strikingly, the majority (>60%) of interactions we detected were over distances of <20Kb, a range where CCC-based methods perform poorly. Because we can infer the direction of causal interactions, the model also significantly improves our ability to fine-map: when we applied it to an eQTL data set we reduced the number of variants in the 90% credible set size by half. We experimentally validate one of our associations using CRISPR engineering of the BLK/FAM167A locus, which is associated with risk for a range of autoimmune diseases and show that the causal variant is likely to be a non-coding insertion within a CTCF binding motif. Our study suggests that many regulatory variants will be challenging to map to their cognate genes using CCC-based techniques, but association genetics of chromatin state can provide a powerful complement to these approaches.
Implications of the privatization of sallie mae
Authors: Dean John E. , Moskowitz Saul L. , Cipriani Karen L. 
Published: December 2017

In 1997, Congress enacted legislation to transition the Student Loan Marketing Association (Sallie Mae) from status as a government-sponsored enterprise (GSE) to a fully-private, non-federally chartered organization. The process through which this legislation was enacted will have precedential value for future legislation affecting other GSEs.
This article reviews the unique context in which the Sallie Mae Privatization Act was considered and enacted. Sallie Mae was an active participant in the development of the privatization legislation, and Congress had little precedent in considering the diverse interests of stakeholders such as other entities involved in student loans, taxpayers, and Sallie Mae shareholders. Full assessment of the 1997 legislation requires a review of how the “privatizing” of Sallie Mae changes the student loan marketplace.