bluuebunny/crossref_metadata_2025_split huggingface dataset:
Selection of appropriate metagenome taxonomic classifiers for ancient microbiome research
Authors: Velsko Irina M. , Frantz Laurent A. F. , Herbig Alexander , Larson Greger , Warinner Christina 
Published: February 2018

AbstractMetagenomics enables the study of complex microbial communities from myriad sources, including the remains of oral and gut microbiota preserved in archaeological dental calculus and paleofeces, respectively. While accurate taxonomic assignment is essential to this process, DNA damage, characteristic to ancient samples (e.g. reduction in fragment size), may reduce the accuracy of read taxonomic assignment. Using a set of in silico-generated metagenomic datasets we investigated how the addition of ancient DNA (aDNA) damage patterns influences microbial taxonomic assignment by five widely-used profilers: QIIME/UCLUST, MetaPhlAn2, MIDAS, CLARK-S, and MALT (BLAST-X-mode). In silico-generated datasets were designed to mimic dental plaque, consisting of 40, 100, and 200 microbial species/strains, both with and without simulated aDNA damage patterns. Following taxonomic assignment, the profiles were evaluated for species presence/absence, relative abundance, alpha-diversity, beta-diversity, and specific taxonomic assignment biases. Unifrac metrics indicated that both MIDAS and MetaPhlAn2 provided the most accurate community structure reconstruction. QIIME/UCLUST, CLARK-S, and MALT had the highest number of inaccurate taxonomic assignments; however, filtering out species present at <0.1% abundance greatly increased the accuracy of CLARK-S and MALT. All programs except CLARK-S failed to detect some species from the input file that were in their databases. Ancient DNA damage resulted in minimal differences in species detection and relative abundance between simulated ancient and modern datasets for most programs. In conclusion, taxonomic profiling biases are program-specific rather than damage-dependent, and the choice of taxonomic classification program to use should be tailored to the research question.ImportanceAncient biomolecules from oral and gut microbiome samples have been shown to preserve in the archaeological record. Studying ancient microbiome communities using metagenomic techniques offer a unique opportunity to reconstruct the evolutionary trajectories of microbial communities through time. DNA accumulates specific damage over time, which could potentially affect taxonomic classification and our ability to reconstruct community assemblages accurately. It is therefore necessary to assess whether ancient DNA (aDNA) damage patterns affect metagenomic taxonomic profiling. Here, we assessed biases in community structure, diversity, species detection, and relative abundance estimates by five popular metagenomic taxonomic classification programs using in silico-generated datasets with aDNA damage. Age-related damage patterns had minimal impact on the taxonomic profiles produced by each program, and biases were intrinsic to each program. Therefore, an appropriate classification program should be chosen that minimizes the biases related to the questions being addressed.
Automatic Cell Segmentation by Adaptive Thresholding (ACSAT) for large scale calcium imaging datasets
Authors: Shen Simon P. , Tseng Hua-an , Hansen Kyle R. , Wu Ruofan , Gritton Howard , Si Jennie , Han Xue 
Published: February 2018

AbstractAdvances in calcium imaging have made it possible to record from an increasingly larger number of neurons simultaneously. Neuroscientists can now routinely image hundreds to thousands of individual neurons. With the continued neurotechnology development effort, it is expected that millions of neurons could soon be simultaneously measured. An emerging technical challenge that parallels the advancement in imaging such a large number of individual neurons is the processing of correspondingly large datasets, an important step of which is the identification of individual neurons. Traditional methods rely mainly on manual or semi-manual inspection, which cannot be scaled to processing large datasets. To address this challenge, we have developed an automated cell segmentation method, which is referred to as Automated Cell Segmentation by Adaptive Thresholding (ACSAT). ACSAT includes an iterative procedure that automatically calculates global and local threshold values during each iteration based on image pixel intensities. As such, the algorithm is capable of handling morphological variations and dynamic changes in fluorescence intensities in different calcium imaging datasets. In addition, ACSAT computes adaptive threshold values based on a time-collapsed image that is representative of the image sequence, and thus ACSAT provides segmentation results at a fast speed. We tested the algorithm on wide-field calcium imaging datasets in the brain regions of hippocampus and striatum in mice. ACSAT achieved precision and recall rates of approximately 80% when compared to individual neurons that are verified by human inspection. Additionally, ACSAT successfully detected low-intensity neurons that were initially undetected by humans.SignificanceACSAT automatically segments cells in large scale wide-field calcium imaging datasets. It is based on adaptive thresholding at both global and local levels, implemented in an iterative process to identify individual neurons in a time-collapsed image from an image sequence. It is therefore capable of handling variation in cell morphology and dynamic changes between different calcium imaging datasets at a fast speed. Based on tests performed on two datasets from mouse hippocampus and striatum, ACSAT performed comparable to human referees and was even able to detect low-intensity neurons that were initially undetected by human referees.
The critical role of ASD-related gene CNTNAP3 in regulating synaptic development and social behavior in mice
Authors: Tong Da-li , Chen Rui-guo , Lu Yu-lan , Li Wei-ke , Zhang Yue-fang , Lin Jun-kai , He Ling-jie , Dang Ting , Shan Shi-fang , Xu Xiao-Hong , Zhang Yi , Zhang Chen , Du Ya-Song , Zhou Wen-Hao , Wang Xiaoqun , Qiu Zilong 
Published: February 2018

AbstractAccumulated genetic evidences indicate that the contactin associated protein-like (CNTNAP) family is implicated in autism spectrum disorders (ASD). In this study, we identified genetic mutations in the CNTNAP3 gene from Chinese Han ASD cohorts and Simons Simplex Collections. We found that CNTNAP3 interacted with synaptic adhesion proteins Neuroligin1 and Neuroligin2, as well as scaffolding proteins PSD95 and Gephyrin. Significantly, we found that CNTNAP3 played an opposite role in controlling the development of excitatory and inhibitory synapses in vitro and in vivo, in which ASD mutants exhibited loss-of-function effects. In this study, we showed that Cntnap3-null mice exhibited deficits in social interaction, spatial learning and prominent repetitive behaviors. These evidences elucidate the pivotal role of CNTNAP3 in synapse development and social behaviors, providing the mechanistic insights for ASD.
Additional Essential Oils with High Activity against Stationary PhaseBorrelia burgdorferi
Authors: Feng Jie , Shi Wanliang , Miklossy Judith , Zhang Ying 
Published: February 2018

ABSTRACTLyme disease is the most common vector borne-disease in the US. While the majority of the Lyme disease patients can be cured with 2-4 week antibiotic treatment, about 10-20% of patients continue to suffer from persisting symptoms. While the cause of this condition is unclear, persistent infection was proposed as one possibility. It has recently been shown thatB. burgdorferidevelops dormant persisters in stationary phase cultures that are not killed by the current Lyme antibiotics, and there is interest to identify novel drug candidates that more effectively kill such forms. We previously evaluated 34 essential oils and identified some highly active candidates with excellent activity against biofilm and stationary phaseB. burgdorferi.Here we screened another 35 essential oils and found 10 essential oils (garlic, allspice, cumin, palmarosa, myrrh, hedycheim, amyris, thyme white, litsea cubeba, lemon eucalyptus) and the active component of cinnamon bark cinnamaldehyde (CA) at a low concentration of 0.1% to have high activity against stationary phaseB. burgdorferi.At a very low 0.05% concentration, garlic, allspice, palmarosa and CA still exhibited strong activity against the stationary phaseB. burgdorferi. CA also showed strong activity against replicatingB. burgdorferi, with a MIC of 0.02% (or 0.2 μg/mL). In subculture studies, the top 5 hits garlic, allspice, myrrh, hedycheim, and litsea cubeba completely eradicated allB. burgdorferistationary phase cells at 0.1%, while palmarosa, lemon eucalyptus, amyris, cumin, and thyme white failed to do so as shown by visible spirochetal growth after 21-day subculture. At 0.05% concentration, only garlic essential oil and CA sterilized theB. burgdorferistationary phase culture as shown by no regrowth during subculture, while allspice, myrrh, hedycheim and litsea cubeba all had visible growth during subculture. Future studies are needed to determine if these highly active essential oils could eradicate persistentB. burgdorferiinfection in vivo.
First Efficient Transfection in Choanoflagellates using Cell-Penetrating Peptides
Authors: Li Ruibao , Neundorf Ines , Nitsche Frank 
Published: February 2018

ABSTRACTOnly recently, based on phylogenetic studies choanoflagellates have been confirmed to form the sister group to metazoan. The mechanisms and genes behind the step from single to multicellular organisation and as a consequence the evolution of metazoan multicellularity could not be verified yet, as no reliable and efficient method for transfection of choanoflagellates was available. Here we present cell-penetrating peptides (CPPs) as an alternative to conventional transfection methods. In a series of experiments with the choanoflagellate Diaphanoeca grandis we proof for the first time that the use of CPPs is a reliable and highly efficient method for the transfection of choanoflagellates. We were able to silence the silicon transporter gene (SIT) by siRNA, and hence, to suppress the lorica (characteristic siliceous basket) formation. High gene silencing efficiency was determined and measured by light microscope and RT-qPCR. In addition, only low cytotoxic effects of CPP were detected. Our new method allows the reliable and efficient transfection of choanoflagellates, finally enabling us to verify the function of genes, thought to be involved in cell adhesion or cell signaling by silencing them via siRNA. This is a step stone for the research on the origin of multicellularity in metazoans.
Vasohibin1, a new IRES trans-acting factor for induction of (lymph)angiogenic factors in early hypoxia
Authors: Hantelys Fransky , Godet Anne-Claire , David Florian , Tatin Florence , Renaud-Gabardos Edith , Pujol Françoise , Diallo Leila , Ader Isabelle , Ligat Laetitia , Henras Anthony K. , Sato Yasufumi , Parini Angelo , Lacazette Eric , Garmy-Susini Barbara , Prats Anne-Catherine 
Published: February 2018

ABSTRACTHypoxia, a major inducer of angiogenesis, is known to trigger major changes of gene expression at the transcriptional level. Furthermore, global protein synthesis is blocked while internal ribosome entry sites (IRES) allow specific mRNAs to be translated. Here we report the transcriptome and translatome signatures of (lymph)angiogenic genes in hypoxic HL-1 cardiomyocytes: most genes are not induced at the transcriptome-, but at the translatome level, including all IRES-containing mRNAs. Our data reveal activation of (lymph)angiogenic mRNA IRESs in early hypoxia. We identify vasohibin1 (VASH1) as an IRES trans-acting factor (ITAF) able to activate FGF1 and VEGFD IRESs in hypoxia while it inhibits several IRESs in normoxia. Thus this new ITAF may have opposite effects on IRES activities. These data suggest a generalized process of IRES-dependent translational induction of (lymph)angiogenic growth factors expression in early hypoxia, whose pathophysiological relevance is to trigger formation of new functional vessels in ischemic heart. VASH1 is not always required, indicating that the IRESome composition is variable, thus allowing subgroups of IRESs to be activated under the control of different ITAFs.
Evolutionary pathways for the generation of new self-incompatibility haplotypes in a non-self recognition system
Authors: Bod’bvá Katarína , Priklopil Tadeas , Field David L. , Barton Nicholas H. , Pickup Melinda 
Published: February 2018

AbstractSelf-incompatibility (SI) is a genetically based recognition system that functions to prevent self-fertilization and mating among related plants. An enduring puzzle in SI is how the high diversity observed in nature arises and is maintained. Based on the underlying recognition mechanism, SI can be classified into two main groups: self- and non-self recognition. Most work has focused on diversification within self-recognition systems despite expected differences between the two groups in the evolutionary pathways and outcomes of diversification. Here, we use a deterministic population genetic model and stochastic simulations to investigate how novel S-haplotypes evolve in a gametophytic non-self recognition (SRNase/S Locus F-box (SLF)) SI system. For this model the pathways for diversification involve either the maintenance or breakdown of SI and can vary in the order of mutations of the female (SRNase) and male (SLF) components. We show analytically that diversification can occur with high inbreeding depression and self-pollination, but this varies with evolutionary pathway and level of completeness (which determines the number of potential mating partners in the population), and in general is more likely for lower haplotype number. The conditions for diversification are broader in stochastic simulations of finite population size. However, the number of haplotypes observed under high inbreeding and moderate to high self-pollination is less than that commonly observed in nature. Diversification was observed through pathways that maintain SI as well as through self-compatible intermediates. Yet the lifespan of diversified haplotypes was sensitive to their level of completeness. By examining diversification in a non-self recognition SI system, this model extends our understanding of the evolution and maintenance of haplotype diversity observed in a recognition system common in flowering plants.
Allele frequency-free inference of close familial relationships from genotypes or low depth sequencing data
Authors: Waples Ryan K , Albrechtsen Anders , Moltke Ida 
Published: February 2018

AbstractKnowledge of how individuals are related is important in many areas of research and numerous methods for inferring pairwise relatedness from genetic data have been developed. However, the majority of these methods were not developed for situations where data is limited. Specifically, most methods rely on the availability of population allele frequencies, the relative genomic position of variants, and accurate genotype data. But in studies of non-model organisms or ancient human samples, such data is not always available. Motivated by this, we present a new method for pairwise relatedness inference, which requires neither allele frequency information nor information on genomic position. Furthermore, it can be applied to both genotype data and to low-depth sequencing data where genotypes cannot be accurately called. We evaluate it using data from SNP arrays and low-depth sequencing from a range of human populations and show that it can be used to infer close familial relationships with a similar accuracy as a widely used method that relies on population allele frequencies. Additionally, we show that our method is robust to SNP ascertainment, which is important for application to a diverse range of populations and species.
Proteomic analysis of chemosensory organs in the honey bee parasite Varroa destructor: a comprehensive examination of the potential carriers for semiochemicals
Authors: Iovinella Immacolata , McAfee Alison , Mastrobuoni Guido , Kempa Stefan , Foster Leonard J. , Pelosi Paolo , Dani Francesca Romana 
Published: February 2018

AbstractThe mite Varroa destructor is the major parasite of the honey bee and is responsible for great economical losses. The biochemical tools used by Varroa to detect semiochemicals produced by the host are still largely unknown. We have performed proteomic analysis on chemosensory organs of this species in order to identify putative soluble carriers for pheromones and other olfactory cues emitted by the host. In particular, we have analysed forelegs, mouthparts (palps, chelicera and hypostome) and the second pair of legs (as control tissue) in reproductive and phoretic stages of the Varroa life cycle. We identified 958 Varroa proteins, most of them common to organs and stages. Sequence analysis shows that four proteins can be assigned to the odorant-binding protein (OBP)-like class, which bear some similarity to insect OBPs, but so far are only reported in some Chelicerata. In addition, we have detected the presence of two proteins belonging to the Niemann-Pick family, type C2 (NPC2), which have been suggested to act as semiochemical carriers. This work contributes to elucidating the chemical communication systems in Varroa with the aim of understanding how detection of semiochemicals has evolved in terrestrial non-hexapod Arthropoda. Data are available via ProteomeXchange with identifier PXD008679.
Identification of parallel and divergent optimization solutions for homologous metabolic enzymes
Authors: Standaert Robert F. , Giannone Richard J. , Michener Joshua K. 
Published: February 2018

AbstractMetabolic pathway assembly typically involves the expression of enzymes from multiple organisms in a single heterologous host. Ensuring that each enzyme functions effectively can be challenging, since many potential factors can disrupt proper pathway flux. These challenges are amplified when the enzymes are expressed at single copy from the chromosome. We have explored these issues using 4-hydroxybenzoate monooxygenase homologs heterologously expressed in Escherichia coli. Initial chromosomal enzyme expression was insufficient to support consistent growth with 4-hydroxybenzoate. Experimental evolution identified mutations that improved pathway activity. One set of mutations was common between homologs, while a second class of mutations was homolog-specific. Ultimately, we were able to identify a set of mutations that provided sufficient activity for growth with 4-hydroxybenzoate while maintaining or improving growth with protocatechuate. These findings demonstrate the potential for flexible, scalable chromosomal pathway engineering, as well as the value of directed evolution strategies to rapidly identify and overcome diverse factors limiting enzyme activity.
Long-read sequencing reveals the complex splicing profile of the psychiatric risk gene CACNA1C in human brain
Authors: Clark Michael B , Wrzesinski Tomasz , Garcia Aintzane B , Hall Nicola A. L. , Kleinman Joel E , Hyde Thomas , Weinberger Daniel R , Harrison Paul J , Haerty Wilfried , Tunbridge Elizabeth M 
Published: February 2018

AbstractRNA splicing is a key mechanism linking genetic variation with psychiatric disorders. Splicing profiles are particularly diverse in brain and difficult to accurately identify and quantify. We developed a new approach to address this challenge, combining long-range PCR and nanopore sequencing with a novel bioinformatics pipeline. We identify the full-length coding transcripts of CACNA1C in human brain. CACNA1C is a psychiatric risk gene that encodes the voltage-gated calcium channel CaV1.2. We show that CACNA1C’s transcript profile is substantially more complex than appreciated, identifying 38 novel exons and 241 novel transcripts. Importantly, many of the novel variants are abundant, and predicted to encode channels with altered function. The splicing profile varies between brain regions, especially in cerebellum. We demonstrate that human transcript diversity (and thereby protein isoform diversity) remains under-characterised, and provide a feasible and cost-effective methodology to address this. A detailed understanding of isoform diversity will be essential for the translation of psychiatric genomic findings into pathophysiological insights and novel psychopharmacological targets.
A Chemical Biology Toolbox for the Study of Protein Methyltransferases and Epigenetic Signaling
Authors: Scheer Sebastian , Ackloo Suzanne , Medina Tiago S. , Schapira Matthieu , Li Fengling , Ward Jennifer A. , Lewis Andrew M. , Northrop Jeffrey P. , Richardson Paul L. , Kaniskan H. Ümit , Shen Yudao , Liu Jing , Smil David , Luo Minkui , Jin Jian , Barsyte-Lovejoy Dalia , Huber Kilian V. M. , De Carvalho Daniel D. , Vedadi Masoud , Zaph Colby , Brown Peter J. , Arrowsmith Cheryl H. 
Published: February 2018

SUMMARYProtein methyltransferases (PMTs) comprise a major class of epigenetic regulatory enzymes with therapeutic relevance. Here we present a collection of chemical probes and associated reagents and data to elucidate the function of human and murine PMTs in cellular studies. Our collection provides inhibitors and antagonists that together modulate most of the key regulatory methylation marks on histones H3 and H4, providing an important resource for modulating cellular epigenomes. We describe a comprehensive and comparative characterization of the probe collection with respect to their potency, selectivity, and mode of inhibition. We demonstrate the utility of this collection in CD4+ T cell differentiation assays revealing the remarkable potential of individual probes to alter multiple T cell subpopulations with important implications for T cell-mediated processes such as inflammation and immuno-oncology. In particular, we demonstrate a role for DOT1L in limiting Th1 cell differentiation and maintaining lineage integrity.
RECAP reveals the true statistical significance of ChIP-seq peak calls
Authors: Chitpin Justin G. , Awdeh Aseel , Perkins Theodore J. 
Published: February 2018

AbstractMotivationChlP-seq is used extensively to identify sites of transcription factor binding or regions of epigenetic modifications to the genome. A key step in ChIP-seq analysis is peak calling, where genomic regions enriched for ChIP versus control reads are identified. Many programs have been designed to solve this task, but nearly all fall into the statistical trap of using the data twice—once to determine candidate enriched regions, and again to assess enrichment by classical statistical hypothesis testing. This double use of the data invalidates the statistical significance assigned to enriched regions, and as a consequence, invalidates false discovery rate estimates. Thus, the true significance or reliability of peak calls remains unknown.ResultsUsing simulated and real ChIP-seq data sets, we show that three well-known peak callers, MACS, SICER and diffReps, output optimistically biased p-values, and therefore optimistic false discovery rate estimates—in some cases, many orders of magnitude too optimistic. We propose a wrapper algorithm, RECAP, that uses resampling of ChIP-seq and control data to estimate and correct for biases built into peak calling algorithms. P-values recalibrated by RECAP are approximately uniformly distributed when applied to null hypothesis data, in which ChIP-seq and control come from the same genomic distributions. When applied to non-null data, RECAP p-values give a better estimate of the true statistical significance of candidate peaks and better false discovery rate estimates, which correlate better with empirical reproducibility. RECAP is a powerful new tool for assessing the true statistical significance of ChIP-seq peak calls.AvailabilityThe RECAP software is available on github at https://github.com/theodorejperkins/RECAP.Contacttperkins@ohri.ca