bluuebunny/crossref_metadata_2025 huggingface dataset:
Simulation of Karyotype Evolution and Biodiversity in Asexual and Sexual Reproduction
Authors: Ying Andrew Y. , Ye Christine J. , Jiang Hui , Horne Steven D. , Abdallah Batoul Y. , Liu Guo , Ying Hao , Heng Henry H.Q.
Published: November 2018

Whether sexual reproduction increases biodiversity remains controversial. Traditionally, sex within a species has been thought to increase genetic diversity, inferring an acceleration of macro-evolution, promoting biodiversity. Recently, it was suggested that the main function of sex is to maintain genome integrity, rather than increase genetic diversity or purify deleterious genes within populations, as the karyotype encodes/safeguards the genomic blueprint. As such, the contribution of sex to biodiversity needs to be re-examined. Since many simulation studies focus only on gene-level selection, it is important to investigate how sexual and asexual reproduction differentially impact patterns of genome-level evolution and biodiversity. Based on the key difference between sexual and asexual reproduction, that sexual individuals are required to mate with a partner of the same genome for successful reproduction, we have performed a simulation to illustrate how such differences impact genome-mediated biodiversity. Asexual populations displayed high genome-level diversity whereas sexual populations evidenced low genome-level diversity. Further analysis demonstrated that the requirement of finding a partner possessing a compatible genome prevents new sexual species from emerging, which may explain why geographic isolation can promote speciation: by increasing mating and survival-domination opportunities. This study challenges the traditional concepts of speciation and the function of sex.
A novel polyphasic identification system for genus Trichoderma
Authors: Dou Kai , Lu Zhixiang , Wu Qiong , Ni Mi , Yu Chuanjin , Wang Meng , Li Yaqian , Wang Xinhua , Xie Huilan , Chen Jie
Published: November 2018

As the rapid-changing inTrichodermataxonomy, an efficient identification ofTrichodermaspecies is an urgent issue forTrichoderma-based research. In this study, based on the current taxonomy ofTrichoderma, we constructed curated databases including 338 ITS sequences, 435 TEF1 sequences, 415 RPB2 sequences and 28 phenotypic characters. In addition, a polyphasic identification system (PIST) was developed. Within PIST, the resolution ability of molecular and phenotype characters could be combined for species identification in a step-by-step way. Compared with other identification systems, the involvedTrichodermaspecies were extended from 88 to 252 species and 175 from 188 testedTrichodermaspecies could be identified within PIST. In most tested cases, three nucleotide markers and phenotypic characters showed improved identification performance. The TEF1 sequences have superior resolution than other characters.

Importance

The genusTrichodermais important to human society with a wide application in industry, agriculture and environment bio-remediation. Thus, a quick and accurate identification ofTrichodermaspp. is paramount since it is usually the first step to conduct aTrichoderma-based scientific research and is an obstruction especially for those researchers as nematologist, chemists, nutritionist and the like, lacking of taxonomic knowledge of fungi.
Eye-movements as a signature of age-related differences in global planning strategies for spatial navigation
Authors: Tartaglia Elisa M. , Boucly Celine , Tatur Guillaume , Arleo Angelo
Published: November 2018

The ability to efficiently find alternatives routes when faced with unexpected obstacles along our path is among the most compelling evidence of the flexibility of human behaviour. Although a plethora of plausible computations have been put forward to elucidate how the brain accomplishes efficient goal-oriented navigation, the mechanisms that guide an effective re-planning when facing obstructions are still largely undetermined. There is a fair consensus in postulating that possible alternatives routes are internally replayed sampling from past experiences, however, there is currently no account of the criterion according to which those memories are replayed. Here, we posit that paths, which are expected to be more rewarding are replayed more often and that eye movements are the explicit manifestation of this re-planning strategy. In other words, the visual sampling statistics reflects the retrieval of available routes on a mental representation of the environment.

To test our hypothesis, we measured the ability of both young and old human subjects to solve a virtual version of the Tolman maze, while we recorded their eye movements. We used reinforcement learning (RL) to corroborate that eye movements statistics was crucially subtending the decision making process involved in re-planning and that the incorporation of this additional information to the algorithm was necessary to reproduce the behavioral performance of both screened populations.
Detecting HTS Barcode Contamination
Authors: Clark Mallory A. , Stankiewicz Sara H. , Barronette Vincent , Ricke Darrell O.
Published: November 2018

DNA barcoding enables multiple samples to be characterized in parallel with high throughput sequencing (HTS) experiments for cost efficiencies. Cross-contamination of DNA barcode reagents can result in the detection of HTS sequences for barcodes that were not originally added to a particular sample. Cross-contamination of data between multiplexed samples can also occur. Avoidance and detection of contaminated barcodes is relevant for DNA forensic samples analysis, accurate cancer diagnosis, clinical research applications, metagenomic analysis, etc. We present recommendations for the avoidance of contamination and a tool, TallyBarcodes, to aid in the detection of DNA barcode contamination.
PUMA: A tool for processing 16S rRNA taxonomy data for analysis and visualization
Authors: Mitchell Keith , Dao Christopher , Freise Amanda , Mangul Serghei , Parker Jordan Moberg
Published: November 2018

Microbial community profiling and functional inference via 16S rRNA analysis is quickly expanding across various areas of microbiology due to improvements to technology. There are numerous platforms for producing 16S rRNA taxonomic data which often vary in file and sequence formatting, creating a common barrier in microbiome studies. Additionally, many of the methods for analyzing and visualizing this sequencing data each require their own specific formatting. As a result, efficient and reproducible comparative analysis of taxonomic data and corresponding metadata in multiple programs remains a challenge in the investigation of microbial communities. PUMA, the Program for Unifying Microbiome Analysis, alleviates this problem in microbiome studies by allowing users to take advantage of numerous 16S rRNA taxonomic identification platforms and analysis tools in an efficient manner. PUMA accepts sequencing results from several taxonomic identification platforms and then automates configuration of data and file types for analysis and visualization via many popular tools. The protocol accomplishes this by producing a variety of properly configured, annotated, and altered files for both analysis and visualization of taxonomic community profiles and inferred functional profiles. PUMA provides an easy and flexible interface to accommodate for a variety of users to produce all files needed for all-inclusive analysis of targeted amplicon sequencing studies. PUMA is an unprecedented open-source solution for unifying multiple microbiome analysis softwares and uses an adaptable implementation with the potential to improve and consolidate the state of microbiome research.

Body/Findings
Adaptive Identification of Cortical and Subcortical Imaging Markers of Early Life Stress and Posttraumatic Stress Disorder
Authors: Salminen Lauren E. , Morey Rajendra A. , Riedel Brandalyn C. , Jahanshad Neda , Dennis Emily L. , Thompson Paul M.
Published: November 2018

Background and Purpose

Posttraumatic stress disorder (PTSD) is a heterogeneous condition associated with a range of brain imaging abnormalities. Early life stress (ELS) contributes to this heterogeneity, but we do not know how a history of ELS influences traditionally defined brain signatures of PTSD. Here we used a novel machine learning method - evolving partitions to improve classification (EPIC) - to identify shared and unique structural neuroimaging markers of ELS and PTSD in 97 combat-exposed military veterans.

Methods

We used EPIC with repeated cross-validation to determine how combinations of cortical thickness, surface area, and subcortical brain volumes could contribute to classification of PTSD (n=40) versus controls (n=57), and classification of ELS within the PTSD (ELS+ n=16; ELS-n=24) and control groups (ELS+ n=16; ELS- n=41). Additional inputs included intracranial volume, age, sex, adult trauma, and depression.

Results

On average, EPIC classified PTSD with 69% accuracy (SD=5%), and ELS with 64% accuracy in the PTSD group (SD=10%), and 62% accuracy in controls (SD=6%). EPIC selected unique sets of individual features that classified each group with 75-85% accuracy in post hoc analyses; combinations of regions marginally improved classification from the individual atlas-defined brain regions. Across analyses, surface area in the right posterior cingulate was the only variable that was repeatedly selected as an important feature for classification of PTSD and ELS.

Conclusions

EPIC revealed unique patterns of features that distinguished PTSD and ELS in this sample of combat-exposed military veterans, which may represent distinct biotypes of stress-related neuropathology.
Bottom-up sensory processing can decrease activity and functional connectivity in the default mode like network in rats
Authors: Hinz Rukun , Peeters Lore M. B. , Shah Disha , Missault Stephan , Belloy Michaël , Vanreusel Verdi , Malekzadeh Meriam , Verhoye Marleen , Van der Linden Annemie , Keliris Georgios A.
Published: November 2018

The default mode network is a large-scale brain network that is active during rest and internally focused states and deactivates as well as desynchronizes during externally oriented (top-down) attention demanding cognitive tasks. However, it is not sufficiently understood if unpredicted salient stimuli, able to trigger bottom-up attentional processes, could also result in similar reduction of activity and functional connectivity in the DMN. In this study, we investigated whether bottom-up sensory processing could influence the default mode like network (DMLN) in rats. DMLN activity was examined using block-design visual functional magnetic resonance imaging (fMRI) while its synchronization was investigated by comparing functional connectivity during a resting versus a continuously stimulated brain state by unpredicted light flashes. We demonstrated that activity in DMLN regions was decreased during visual stimulus blocks and increased during blanks. Furthermore, decreased inter-network functional connectivity between the DMLN and visual networks as well as decreased intra-network functional connectivity within the DMLN was observed during the continuous visual stimulation. These results suggest that triggering of bottom-up attention mechanisms in anesthetized rats can lead to a cascade similar to top-down orienting of attention in humans and is able to deactivate and desynchronize the DMLN.
Evaluating the Genome and Resistome of Extensively Drug-Resistant Klebsiella pneumoniae using Native DNA and RNA Nanopore Sequencing
Authors: Pitt Miranda E. , Nguyen Son H. , Duarte Tânia P.S. , Blaskovich Mark A.T. , Cooper Matthew A. , Coin Lachlan J.M.
Published: November 2018

Klebsiella pneumoniae frequently harbour multidrug resistance and current methodologies are struggling to rapidly discern feasible antibiotics to treat these infections. While rapid DNA sequencing has been proposed for prediction of resistance profile; the role of rapid RNA sequencing has yet to be fully explored. The MinION sequencer can sequence native DNA and RNA in real-time, providing an opportunity to contrast the utility of DNA and RNA for prediction of drug susceptibility. This study interrogated the genome and transcriptome of four extensively drug-resistant (XDR) K. pneumoniae clinical isolates. The majority of acquired resistance (≥75%) resided on plasmids including several megaplasmids (≥100 kbp). DNA sequencing identified most resistance genes (≥70%) within 2 hours of sequencing. Direct RNA sequencing (with a ∼6x slower pore translocation) was able to identify ≥35% of resistance genes, including aminoglycoside, β-lactam, trimethoprim and sulphonamide and also quinolone, rifampicin, fosfomycin and phenicol in some isolates, within 10 hours of sequencing. Polymyxin-resistant isolates showed a heightened transcription of phoPQ (≥2-fold) and the pmrHFIJKLM operon (≥8-fold). Expression levels estimated from direct RNA sequencing displayed strong correlation (Pearson: 0.86) compared to qRT-PCR across 11 resistance genes. Overall, MinION sequencing rapidly detected the XDR K. pneumoniae resistome and direct RNA sequencing revealed differential expression of these genes.
Active Receptor Tyrosine Kinases, but not Brachyury, are sufficient to trigger chordoma in zebrafish
Authors: D‘Agati Gianluca , Cabello Elena María , Frontzek Karl , Rushing Elisabeth J. , Klemm Robin , Robinson Mark D. , White Richard M. , Mosimann Christian , Burger Alexa
Published: November 2018

The aberrant activation of developmental processes triggers diverse cancer types. Chordoma is a rare, aggressive tumor arising from transformed notochord remnants. Several potentially oncogenic factors, including several receptor tyrosine kinase (RTK) genes, have been found deregulated in chordoma, yet causation remains uncertain. In particular, sustained expression of the developmental notochord transcription factor Brachyury is hypothesized as key driver of chordoma; nonetheless, experimental evidence for an oncogenic role of Brachyury in chordoma and its prognostic impact remains missing. Here, we developed and applied a zebrafish chordoma model to identify the notochord-transforming potential of implicated genesin vivo. We find that Brachyury, including a form with augmented transcriptional activity, is insufficient to initiate notochord hyperplasia. In contrast, the chordoma-implicated RTKs EGFR and KDR/VEGFR2 are sufficient to transform notochord cells within two to five days of development. Transcriptome and structural analysis of transformed notochords revealed that the aberrant activation of RTK/Ras signaling attenuates processes required for notochord differentiation, including of the unfolded protein response. Our results provide firstin vivoindication against a tumor-initiating potential of Brachyury in the notochord, and imply activated RTK signaling as possibly initiating event in chordoma. These results provide a mechanistic framework for the pursuit of chemotherapeutic compounds to combat this aggressive tumor type.
Integrative isotopic Paleoecology (δ13C, δ18O) of a Late Pleistocene vertebrate community from Sergipe, NE Brazil
Authors: Trindade Dantas Mário André , Cherkinsky Alexander , Lessa Carlos Micael Bonfim , Santos Luciano Vilaboim , Cozzuol Mario Alberto , Omena Érica Cavalcante , Silva Jorge Luiz Lopes da , Sial Alcides Nóbrega , Bocherens Hervé
Published: November 2018

Isotopes are one of the best tools to reconstruct the Paleoecology of extinct taxa, yielding insights about their diet (through carbon; C3and C4plants), niche breadth (BA) and the environment in which they lived. In the present work we go deeper in the use of isotopes and explore a mathematical mixing model with the stable isotopes of two elements (carbon and oxygen) to (1) suggest the relative contribution of four types of food resources (leaves, fruits, roots and C4grass) for meso- and megaherbivores (weight > 100 kg) that lived in the Late Pleistocene of Poço Redondo, Sergipe, Brasil, and (2) evaluate which of these herbivores could be the potential prey for the carnivoresSmilodon populatorandCaiman latirostris. To explore the intra/interspecific competition of these fauna, we generate weight estimation, standardized niche breadth (BA) for the meso-megamammals from Sergipe and compare with data from the meso-megaherbivores from Africa, concluding thatEremotherium laurillardiandToxodon platensiswere the best resource competitors in the Late Pleistocene of Sergipe, and reinforcing their importance as key species in this extinct community. Finally, we reconstructed the paleoenvironment in which the vertebrate community of Sergipe lived, estimating Mean Annual Temperature (°C), Mean Annual Precipitation, Biomass and Energy Expendidure, noting that environments in the Late Pleistocene of Sergipe were similar to those of Africa nowadays, but hotter and with more energy expenditure for these meso-megamammals.
Spatial structure increases the benefits of antibiotic production in Streptomyces griseus
Authors: Westhoff Sanne , Otto Simon B. , Swinkels Aram , Bode Bo , van Wezel Gilles P. , Rozen Daniel E.
Published: November 2018

Bacteria in the soil compete for limited resources to survive and proliferate. One of the ways they might do this is by producing antibiotics, but the costs of antibiotic production and their low concentrations in soils have led to uncertainty about the role of these natural products for the bacteria that produce them. Here, we examine the fitness effects of streptomycin production by the filamentous soil bacterium Streptomyces griseus and the conditions that modify its ability to invade competitors. Using pairwise competion assays, we first provide direct evidence that streptomycin production enables S. griseus to kill and invade a population of the susceptible species, S. coelicolor, but not a streptomycin-resistant mutant of this species. Next we show that the fitness benefits of streptomycin production are density-dependent, because production scales positively with cell number, and frequency-dependent, with a threshold of invasion of S. griseus at around 1%. Finally, using serial transfer experiments where spatial structure is either maintained or periodically destroyed, we show that spatial structure reduces the threshold frequency of invasion by more than 100-fold, indicating that antibiotic production can permit invasion from extreme rarity. Our results provide clear evidence that streptomycin is both an offensive and defensive weapon that facilitates invasion into occupied habitats and also protects against invasion by competitors. They also indicate that the benefits of antibiotic production rely on ecological interactions occurring at small local scales, suggesting that low antibiotic concentrations in bulk soil are unlikely to be representative of their effective concentrations in nature.
Prediction Interval Ranking Score: Identification of Invariant Expression from Time Series
Authors: Crowell Alexander M , Loros Jennifer J. , Dunlap Jay C
Published: November 2018

Motivation

Identification of constitutive reference genes is critical for analysis of gene expression. Large numbers of high throughput time series expression data are available, but current methods for identifying invariant expression are not tailored for time series. Identification of reference genes from these data sets can benefit from methods which incorporate the additional information they provide.

Results

Here we show that we can improve identification of invariant expression from time series by modelling the time component of the data. We implement the Prediction Interval Ranking Score (PIRS) software, which screens high throughput time series data and provides a ranked list of reference candidates. We expect that PIRS will improve the quality of gene expression analysis by allowing researchers to identify the best reference genes for their system from publicly available time series.

Availability

PIRS can be downloaded and installed with dependencies using ‘pip install pirs’ and Python code and documentation is available for download at https://github.com/aleccrowell/PIRS.

Contact

alexander.m.crowell@gmail.com
Bioinformatics Approach to Identify Diseasome and Co-morbidities Effect of Mitochondrial Dysfunctions on the Progression of Neurological Disorders
Authors: Satu Md. Shahriare , Howlader Koushik Chandra , Ullah Akhund Tajim Md. Niamat , Huq Fazlul , Quinn Julian M.W. , Moni Mohammad Ali
Published: November 2018

Mitochondrial dysfunction can cause various neurological diseases. We therefore developed a quantitative framework to explore how mitochondrial dysfunction may influence the progression of Alzheimer’s, Parkinson’s, Huntington’s and Lou Gehrig’s diseases and cerebral palsy through analysis of genes showing altered expression in these conditions. We sought insights about the gene profiles of mitochondrial and associated neurological diseases by investigating gene-disease networks, KEGG pathways, gene ontologies and protein-protein interaction network. Gene disease networks were constructed to connect shared genes which are commonly found between the neurological diseases and Mitochondrial Dysfunction. We also generated KEGG pathways and gene ontologies to explore functional enrichment among them, and protein-protein interaction networks to identify the shared protein groups of these diseases. Finally, we verified our biomarkers using gold benchmark databases (e.g., OMIM and dbGaP) which identified effective reasons of it. Our network-based methodologies are useful to investigate disease mechanisms, predictions for comorbidities and identified distinct similarities among different neurological disorders for mitochondrial dysfunction.
A simple approximation to bias in the genetic effect estimates when multiple disease states share a clinical diagnosis
Authors: Lobach Iryna , Kim Inyoung , Alekseyenko Alexander , Lobach Siarhei , Zhang Li
Published: November 2018

Case-control genome-wide association (CC-GWAS) studies might provide valuable clues to the underlying pathophysiologic mechanisms of complex diseases, such as neurodegenerative disease, cancer. A commonly overlooked complication is that multiple distinct disease states might present with the same set of symptoms and hence share a clinical diagnosis. These disease states can only be distinguished in a biomarker evaluation that might not be feasible on the whole set of cases in the large number of samples that are typically needed for CC-GWAS. Instead, the biomarkers are measured on a subset of cases. Or an external reliability study estimates frequencies of the disease states of interest within the clinically diagnosed set of cases. These frequencies often vary by the genetic and/or non-genetic variables. We derive a simple approximation that relates the genetic effect estimates obtained in a logistic regression model with the clinical diagnosis as an outcome variable to the estimates in the relationship to the true disease state of interest. We performed simulation studies to assess accuracy of the approximation that we’ve derived. We next applied the derived approximation to the analysis of the genetic basis of innate immune system of Alzheimer’s disease.
A learned embedding for efficient joint analysis of millions of mass spectra
Authors: Bittremieux Wout , May Damon H. , Bilmes Jeffrey , Noble William Stafford
Published: November 2018

Computational methods that aim to exploit publicly available mass spectrometry repositories primarily rely on unsupervised clustering of spectra. Here, we propose to train a deep neural network in a supervised fashion based on previous assignments of peptides to spectra. The network, called “GLEAMS,” learns to embed spectra into a low-dimensional space in which spectra generated by the same peptide are close to one another. We use GLEAMS as the basis for a large-scale spectrum clustering, detecting groups of unidentified, proximal spectra representing the same peptide, and we show how to use these clusters to explore the dark proteome of repeatedly observed yet consistently unidentified mass spectra. We provide a software implementation of our approach, along with a tool to quickly embed additional spectra using a pre-trained model, to facilitate large-scale analyses.
Asymmetric secretion in budding yeast reinforces daughter cell identity
Authors: Thomas Valerie N. , Weiss Eric L. , Brace Jennifer L.
Published: November 2018

Asymmetric segregation of cellular factors during cell division produces two cells with different identities. This asymmetry underlies cell fate decisions as well as the ability to self-renew. Asymmetric segregation of protein and RNA to the growing bud ofSaccharomyces cerevisiaegenerates a daughter cell with features distinct from its mother. For example, asymmetric segregation of the transcription factor Ace2 to the newly formed daughter cell activates a gene expression program unique to daughters. Ace2 activates a cohort of genes, including degradative enzymes, which facilitate cell separation exclusively from the daughter. This asymmetric secretion leaves a characteristic ‘bud scar’ chitin ring on the mother. We sought to determine the sufficiency of Ace2 to define a daughter cell state by generating anACE2allele which localizes to both mother and daughter nuclei. When Ace2 asymmetry is lost, Ace2 target gene transcription and translation occur in both mother and daughter cells. However, we find that mother cells retain bud scars and maintain asymmetric daughter-specific secretion of the wall degrading enzyme Cts1. These findings demonstrate that while mothers are competent to transcribe and translate Ace2 targets, additional intrinsic factors reinforce the daughter cell state.

TOC Summary

Asymmetric segregation of the transcription factor Ace2 drives daughter-specific cell separation after cytokinesis. Cells engineered to express Ace2 targets symmetrically produce the cell separation enzyme Cts1. However, secretion remains asymmetric suggesting other daughter-specific factors are required to reinforce the daughter cell identity.
Low oxygen post conditioning improves stroke-induced cognitive impairment
Authors: Zhao Zidan , Ong Lin Kooi , Pietrogrande Giovanni , Bezanilla Sonia Sanchez , Warren Kirby , Ilicic Marina , Kluge Murielle G. , TeBay Clifford , Ottersen Ole P. , Johnson Sarah J , Nilsson Michael , Walker Frederick R
Published: November 2018

Post-stroke cognitive impairment has proven to be notoriously difficult to treat. In the current study, we sought to both better understand cellular changes that underpin cognitive deficits and to consider the potential restorative benefits of low oxygen post conditioning (LOPC). We were motivated to use LOPC as an intervention as it is one of the few experimental interventions previously shown to improve cognitive function post-stroke. Experimental stroke was induced by photothrombotic occlusion in adult male C57BL/6 mice. Mice were randomly assigned to either a normal atmospheric air exposure or low oxygen (11% O2) exposure groups three days post-occlusion. On day 17 post-stroke, mice were euthanized for histology or biochemical analyses. Stroked mice exposed to LOPC was associated with marked reductions in amyloid-beta both in its absolute level and in the extent of its oligomerization. Exposure to LOPC post-stroke also improved cellular deficits induced by stroke including an increase in vessel density, a reduction in vascular leakage, and restoration of AQP4 polarisation. Critically, stroked mice exposed to LOPC exhibited robust improvements in cognitive function post-stroke, assessed using a touchscreen based paired- associate learning task. These findings provide compelling pre-clinical evidence of the potential clinical utility of LOPC for enhancing recovery post-stroke.
Polymorphism-aware species trees with advanced mutation models, bootstrap and rate heterogeneity
Authors: Schrempf Dominik , Minh Bui Quang , Haeseler Arndt von , Kosiol Carolin
Published: November 2018

Molecular phylogenetics has neglected polymorphisms within present and ancestral populations for a long time. Recently, multispecies coalescent based methods have increased in popularity, however, their application is limited to a small number of species and individuals. We introduced a polymorphism-aware phylogenetic model (PoMo), which overcomes this limitation and scales well with the increasing amount of sequence data while accounting for present and ancestral polymorphisms. PoMo circumvents handling of gene trees and directly infers species trees from allele frequency data. Here, we extend the PoMo implementation in IQ-TREE and integrate search for the statistically best-fit mutation model, the ability to infer mutation rate variation across sites, and assessment of branch support values. We exemplify an analysis of a hundred species with ten haploid individuals each, showing that PoMo can perform inference on large data sets. While PoMo is more accurate than standard substitution models applied to concatenated alignments, it is almost as fast. We also providebmm-simulate, a software package that allows simulation of sequences evolving under PoMo. The new options consolidate the value of PoMo for phylogenetic analyses with population data.
3D Structural Connectivity in Healthy Adults: Detecting Structural Connections and Their Underlying Substrates for Olfactory Saccadic Pathway
Authors: Elumalai Ganesh , Syed Imran Shareef , Chatterjee Harshita , Brown Valencia , Sober Lekesha Adele , Surya Nitya Akarsha , Ghanta Venkata , Chandrasekhar Pradeep , Venkatesan Anbarasan , Sewram Nadira , Muthukumaran Nitesh Raj , Harkrishna Golla , Vamsi Nanduri Mojess , Osakwe Nneoma Somtochukwu
Published: November 2018

This confirmatory study aimed to unravel the neural structural connectivity of Olfactory-Saccadic pathways extending between Piriform and Entorhinal Cortices to Frontal Eye Field (FEF), and to correlate its functional importance with possible clinical implications, using Diffusion Imaging fiber Tractography. The confirmatory observational analysis used thirty-two healthy adults, ultra-high b-value, diffusion imaging datasets from an Open access platform in Human Connectome Project (HCP). In all the datasets from both the sexes, fibers were traced and the neural structural connectivity was confirmed. The hemispheric differences between male and female subjects were anaNumber of tracts refers to a bundle of fibres having lysed using independent sample t-test. Thus, the study confirmed the structural existences of Olfactory-saccadic pathways that may be involved in influencing the movements of the neck and eyeball gaze (saccadic eye movement), towards the spatial orientation of olfactory stimulus.
Sex differences in gene expression in the human fetal brain
Authors: O’Brien Heath E. , Hannon Eilis , Jeffries Aaron R. , Davies William , Hill Matthew J. , Anney Richard J. , O’Donovan Michael C. , Mill Jonathan , Bray Nicholas J.
Published: November 2018

Widespread structural, chemical and molecular differences have been reported between the male and female human brain. Although several neurodevelopmental disorders are more commonly diagnosed in males, little is known regarding sex differences in early human brain development. Here, we used RNA sequencing data from a large collection of human brain samples from the second trimester of gestation (N = 120) to assess sex biases in gene expression within the human fetal brain. In addition to 43 genes (102 Ensembl transcripts) transcribed from the Y-chromosome in males, we detected sex differences in the expression of 2558 autosomal genes (2723 Ensembl transcripts) and 155 genes on the X-chromosome (207 Ensembl transcripts) at a false discovery rate (FDR) < 0.1. Genes exhibiting sex-biased expression in human fetal brain are enriched for high-confidence risk genes for autism and other developmental disorders. Male-biased genes are enriched for expression in neural progenitor cells, whereas female-biased genes are enriched for expression in Cajal-Retzius cells and glia. All gene- and transcript-level data are provided as an online resource (available at http://fgen.psycm.cf.ac.uk/FBSeq1) through which researchers can search, download and visualize data pertaining to sex biases in gene expression during early human brain development.
Extent of the annual Gulf of Mexico hypoxic zone influences microbial community structure
Authors: Campbell Lauren Gillies , Thrash J. Cameron , Rabalais Nancy N. , Mason Olivia U.
Published: November 2018

Rich geochemical datasets generated over the past 30 years have provided fine-scale resolution on the northern Gulf of Mexico (nGOM) coastal hypoxic (≤ 2 mg of O2L-1) zone. In contrast, little is known about microbial community structure and activity in the hypoxic zone despite the implication that microbial respiration is responsible for forming low dissolved oxygen (DO) conditioXSns. Here, we hypothesized that the extent of the hypoxic zone is a driver in determining microbial community structure, and in particular, the abundance of ammonia-oxidizing archaea (AOA). Samples collected across the shelf for two consecutive hypoxic seasons in July 2013 and 2014 were analyzed using 16S rRNA gene sequencing, oligotyping, microbial co-occurrence analysis and quantification of thaumarchaeal 16S rRNA and archaeal ammonia-monooxygenase (amoA) genes. In 2014 Thaumarchaeota were enriched and inversely correlated with DO while Cyanobacteria, Acidimicrobiia and Proteobacteria where more abundant in oxic samples compared to hypoxic. Oligotyping analysis ofNitrosopumilus16S rRNA gene sequences revealed that one oligotype was significantly inversely correlated with dissolved oxygen (DO) in both years and that low DO concentrations, and the high Thaumarchaeota abundances, influenced microbial co-occurrence patterns. Taken together, the data demonstrated that the extent of hypoxic conditions could potentially influence patterns in microbial community structure, with two years of data revealing that the annual nGOM hypoxic zone is emerging as a low DO adapted AOA hotspot.
A computational solution to improve biomarker reproducibility during long-term projects
Authors: Feng Feng , Thompson Morgan P. , Thomas Beena E. , Duffy Elizabeth R. , Kim Jiyoun , Kurosawa Shinichiro , Tashjian Joseph Y. , Wei Yibing , Andry Chris , Stearns-Kurosawa D.J.
Published: November 2018

Biomarkers are fundamental to basic and clinical research outcomes by reporting host responses and providing insight into disease pathophysiology. Measuring biomarkers with research-use ELISA kits is universal, yet lack of kit standardization and unexpected lot-to-lot variability presents analytic challenges for long-term projects. During an ongoing two-year project measuring plasma biomarkers in cancer patients, control concentrations for one biomarker (PF) decreased significantly after changes in ELISA kit lots. A comprehensive operations review pointed to standard curve shifts with the new kits, an analytic variable that jeopardized data already collected on hundreds of patient samples. After excluding other reasonable contributors to data variability, a computational solution was developed to provide a uniform platform for data analysis across multiple ELISA kit lots. The solution (ELISAtools) was developed within open-access R software in which variability between kits is treated as a batch effect. A defined best-fit Reference standard curve is modelled, a unique Shift factor “S” is calculated for every standard curve and data adjusted accordingly. The averaged S factors for PF ELISA kit lots #1-5 ranged from −0.086 to 0.735, and reduced control inter-assay variability from 62.4% to <9%, within quality control limits. S factors calculated for four other biomarkers provided a quantitative metric to monitor ELISAs over the 10 month study period for quality control purposes. Reproducible biomarker measurements are essential, particularly for long-term projects with valuable patient samples. Use of research-use ELISA kits is ubiquitous and judicious use of this computational solution maximizes biomarker reproducibility.
Exploring differentially expressed key genes related to development of follicle by RNA-seq in Peking ducks (Anas Platyrhynchos)
Authors: Ren Jindong , Sun Changsen , Chen Li , Hu Jianhong , Huang Xuetao , Liu Xiaolin , Lu Lizhi
Published: November 2018

Duck follicle enter different reproductive phases throughout life, and follicle gene expression patterns differ according to these phases. In particular, differentially expressed genes and related to development of follicle (mRNAs) play an important role to explore the key genes in this process; however, the expression profiles of these genes remain unclear. In this study, transcriptome sequencing was used to investigate the expression levels of duck ovarian genes, and comparative transcriptional analysis was carried out to identify differential genes, cluster them into groups and function identification. The results showed differential expression of 593 coding genes between young and laying ducks, and of 518 coding genes between laying and old ducks. In further GO analysis, 35 genes from the comparison bewtween old ducks and laying ducks have significant been changed involved in hormones related to follicle development. They include up-regulated genes StAR, CYP17, EPOX, 3β-HSD, CYP1B1 CYP19A1 and down-regulated genes SR-B1 in laying ducks hormone synthesis than old ducks. Among which EPOX is a key gene for time special highly expression during egg laying stage, and other key regulatory genes’ highly expression showed in young and laying stage and lower expression showing with follicular development stopping. Therefore, EPOX is key regulator for duck follicle development in laying period, when its expression level decrease 98% the follicular development will stopping in duck life cycle.
Synthetic Biology - Mapping the Patent Landscape
Authors: Oldham Paul , Hall Stephen
Published: November 2018

This article presents the global patent landscape for synthetic biology as a new and emerging area of science and technology. The aim of the article is to provide an overview of the emergence of synthetic biology in the patent system and to contribute to future research by providing a high quality tagged core dataset with 7,424 first filings and 71,887 family members. This dataset is intended to assist with evidence based exploration of synthetic biology in the patent system and with advancing methods for the analysis of new and emerging areas of science and technology.

The starting point for the research is recognition that traditional methods of patent landscape analysis based on key word searches face limitations when addressing new and emerging areas of science and technology. Synthetic biology can be broadly described as involving the design, synthesis and assembly of biological parts, circuits, pathways, cells and genomes. As such synthetic biology can be understood as emerging from a combination of overlaps and convergences between existing fields and disciplines, such as biotechnology, genetic engineering, protein engineering and systems biology. More precisely, synthetic biology can be understood as thesynthetic phaseof molecular biology and genetic engineering. This presents the problem that key word strategies may radically overestimate activity because they involve terms that are widely used in underlying fields that are contributing to synthetic biology.

In response to this problem we combined anthropology, scientometrics and data science to map authors from scientific publications on synthetic biology into the international patent system. We mapped 10,816 authors into the international patent system and identified 2,450 authors of articles on synthetic biology who are also inventors in the period to December 2017. By combining this data with citation information and a baseline keyword strategy we are able to describe the global patent landscape for synthetic biology and the wider patent universe in which synthetic biology is situated.

This article describes the main features of the global landscape and provides the tagged dataset as a contribution to evidence based debate on intellectual property and synthetic biology and methodological development. We anticipate that the data will prove useful in informing international policy debates on synthetic biology under the United Nations Convention on Biological Diversity.
Epigenetic mapping of the Arabidopsis metabolome reveals mediators of the epigenotype-phenotype map
Authors: Kooke Rik , Morgado Lionel , Becker Frank , van Eekelen Henriëtte , Hazarika Rashmi , Zheng Qunfeng , de Vos Ric C.H. , Johannes Frank , Keurentjes Joost J.B.
Published: November 2018

Identifying the sources of natural variation underlying metabolic differences between plants will enable a better understanding of plant metabolism and provide insights into the regulatory networks that govern plant growth and morphology. So far, however, the contribution of epigenetic variation to metabolic diversity has been largely ignored. In the present study, we utilized a panel of Arabidopsis thaliana epigenetic recombinant inbred lines (epiRILs) to assess the impact of epigenetic variation on the metabolic composition. Thirty epigenetic QTL (QTLepi) were detected, which partly overlap with QTLepi linked to growth and morphology. In an effort to identify causal candidate genes in the QTLepi regions and their putative trans-targets, we performed in silico small RNA and qPCR analyses. Differentially expressed genes were further studied by phenotypic and metabolic analyses of knockout mutants. Three genes were detected that recapitulated the detected QTLepi effects, providing evidence for epigenetic regulation in cis and in trans. These results indicate that epigenetic mechanisms impact metabolic diversity, possibly via small RNAs, and thus aid in further disentangling the complex epigenotype-phenotype map.
Crystal structures of two stilbazole derivatives: bis{(E)-4-[4-(diethylamino)styryl]-1-methylpyridin-1-ium} tetraiodidocadmium(II) and (E)-4-[4-(diethylamino)styryl]-1-methylpyridin-1-ium 4-methoxybenzenesulfonate monohydrate
Authors: Antony Priya , Inglebert S. Antony , Ramaclus Jerald V. , Sundaram S. John , Sagayaraj P.
Published: November 2018

The title molecular salts, (C18H23N2)2[CdI4], (I), and C18H23N2
+·C7H7O4S−·H2O, (II), are stilbazole, or 4-styrylpyridine, derivatives. The cation, (E)-4-[4-(diethylamino)styryl]-1-methylpyridin-1-ium, has a methyl group attached to pyridine ring and a diethyl amine group attached to the benzene ring. The asymmetric unit of salt (I), comprises one cationic molecule and half a CdI4 dianion. The Cd atom is situated on a twofold rotation axis and has a slightly distorted tetrahedral coordination sphere. In (II), the anion consists of a 4-methoxybenzenesulfonate and it crystallizes as a monohydrate. In both salts, the cations adopt an E configuration with respect to the C=C bond and the pyridine and benzene rings are inclined to each other by 10.7 (4)° in (I) and 4.6 (2)° in (II). In the crystals of both salts, the packing is consolidated by offset π–π stacking interactions involving the pyridinium and benzene rings, with centroid–centroid distances of 3.627 (4) Å in (I) and 3.614 (3) Å in (II). In the crystal of (II), a pair of 4-methoxybenzenesulfonate anions are bridged by Owater—H...Osulfonate hydrogen bonds, forming loops with an R
2
4(8) motif. These four-membered units are then linked to the cations by a number of C—H...O hydrogen bonds, forming slabs lying parallel to the ab plane.
Determining the amphipol distribution within membrane-protein fibre samples using small-angle neutron scattering
Authors: Arunmanee Wanatchaporn , Heenan Richard K. , Lakey Jeremy H.
Published: November 2018

Detergent micelles can solubilize membrane proteins, but there is always a need for a pool of free detergent at the critical micellar concentration to maintain the micelle–monomer equilibrium. Amphipol polymeric surfactants (APols) have been developed to replace conventional detergents in membrane-protein studies, but the role of free amphipol is unclear. It has previously been shown that the removal of free APol causes monodisperse outer membrane protein F (OmpF) to form long filaments. However, any remaining APol could not be resolved using electron microscopy. Here, small-angle neutron scattering with isotope contrast matching was used to separately determine the distributions of membrane protein and amphipol in a mixed sample. The data showed that after existing free amphipol had been removed from monodisperse complexes, a new equilibrium was established between protein–amphipol filaments and a pool of newly liberated free amphipol. The filaments consisted of OmpF proteins surrounded by a belt of Apol, whilst free oblate spheroid micelles of Apol were also present. No indications of long-range order were observed, suggesting a lack of defined structure in the filaments.
Introducing SEC–SANS for studies of complex self-organized biological systems
Authors: Johansen Nicolai Tidemand , Pedersen Martin Cramer , Porcar Lionel , Martel Anne , Arleth Lise
Published: November 2018

Small-angle neutron scattering (SANS) is maturing as a method for studying complex biological structures. Owing to the intrinsic ability of the technique to discern between 1H- and 2H-labelled particles, it is especially useful for contrast-variation studies of biological systems containing multiple components. SANS is complementary to small-angle X-ray scattering (SAXS), in which similar contrast variation is not easily performed but in which data with superior counting statistics are more easily obtained. Obtaining small-angle scattering (SAS) data on monodisperse complex biological structures is often challenging owing to sample degradation and/or aggregation. This problem is enhanced in the D2O-based buffers that are typically used in SANS. In SAXS, such problems are solved using an online size-exclusion chromatography (SEC) setup. In the present work, the feasibility of SEC–SANS was investigated using a series of complex and difficult samples of membrane proteins embedded in nanodisc particles that consist of both phospholipid and protein components. It is demonstrated that SEC–SANS provides data of sufficient signal-to-noise ratio for these systems, while at the same time circumventing aggregation. By combining SEC–SANS and SEC–SAXS data, an optimized basis for refining structural models of the investigated structures is obtained.
Membrane-protein crystals for neutron diffraction
Authors: Sørensen Thomas Lykke-Møller , Hjorth-Jensen Samuel John , Oksanen Esko , Andersen Jacob Lauwring , Olesen Claus , Møller Jesper Vuust , Nissen Poul
Published: November 2018

Neutron macromolecular crystallography (NMX) has the potential to provide the experimental input to address unresolved aspects of transport mechanisms and protonation in membrane proteins. However, despite this clear scientific motivation, the practical challenges of obtaining crystals that are large enough to make NMX feasible have so far been prohibitive. Here, the potential impact on feasibility of a more powerful neutron source is reviewed and a strategy for obtaining larger crystals is formulated, exemplified by the calcium-transporting ATPase SERCA1. The challenges encountered at the various steps in the process from crystal nucleation and growth to crystal mounting are explored, and it is demonstrated that NMX-compatible membrane-protein crystals can indeed be obtained.
Polymorph of (E)-N′-(4-chlorobenzylidene)isonicotinohydrazide monohydrate
Authors: Stondus Jigmat , Anthal Sumati , Jayashree A. , Narayana B. , Sarojini B. K. , Kant Rajni
Published: November 2018

The title hydrate, C13H10ClN3O·H2O, is the orthorhombic polymorph of the previously reported monoclinic compound [Fun et al. (2012). Acta Cryst. E68, o2303–o2304). In the title compound, the dihedral angle between the pyridine and benzene rings is 18.0 (2)°. In the crystal, the Schiff base molecules and water molecules are linked via O—H...O, N—H...O and O—H...N hydrogen bonds, forming a two-dimensional network parallel to (001). In addition, the Schiff base molecules are linked end-to-end by weak C—H...Cl hydrogen along the c-axis direction, forming an overall three-dimensional network. Weak C—H...π interactions are also observed.