bluuebunny/crossref_metadata_2025 huggingface dataset:
Resurrecting ancestral genes in bacteria to interpret ancient biosignatures
Authors: Kacar Betul , Guy Lionel , Smith Eric , Baross John
Published: November 2017

Two datasets, the geologic record and the genetic content of extant organisms, provide complementary insights into the history of how key molecular components have shaped or driven global environmental and macroevolutionary trends. Changes in global physico-chemical modes over time are thought to be a consistent feature of this relationship between Earth and life, as life is thought to have been optimizing protein functions for the entirety of its approximately 3.8 billion years of history on the Earth. Organismal survival depends on how well critical genetic and metabolic components can adapt to their environments, reflecting an ability to optimize efficiently to changing conditions. The geologic record provides an array of biologically independent indicators of macroscale atmospheric and oceanic composition, but provides little in the way of the exact behaviour of the molecular components that influenced the compositions of these reservoirs. By reconstructing sequences of proteins that might have been present in ancient organisms, we can downselect to a subset of possible sequences that may have been optimized to these ancient environmental conditions. How can one use modern life to reconstruct ancestral behaviours? Configurations of ancient sequences can be inferred from the diversity of extant sequences, and then resurrected in the laboratory to ascertain their biochemical attributes. One way to augment sequence-based, single-gene methods to obtain a richer and more reliable picture of the deep past, is to resurrect inferred ancestral protein sequences in living organisms, where their phenotypes can be exposed in a complex molecular-systems context, and then to link consequences of those phenotypes to biosignatures that were preserved in the independent historical repository of the geological record. As a first step beyond single-molecule reconstruction to the study of functional molecular systems, we present here the ancestral sequence reconstruction of the beta-carbonic anhydrase protein. We assess how carbonic anhydrase proteins meet our selection criteria for reconstructing ancient biosignatures in the laboratory, which we term palaeophenotype reconstruction.

This article is part of the themed issue ‘Reconceptualizing the origins of life’.
Protoenzymes: the case of hyperbranched polyesters
Authors: Mamajanov Irena , Cody George D.
Published: November 2017

Enzymes are biopolymeric complexes that catalyse biochemical reactions and shape metabolic pathways. Enzymes usually work with small molecule cofactors that actively participate in reaction mechanisms and complex, usually globular, polymeric structures capable of specific substrate binding, encapsulation and orientation. Moreover, the globular structures of enzymes possess cavities with modulated microenvironments, facilitating the progression of reaction(s). The globular structure is ensured by long folded protein or RNA strands. Synthesis of such elaborate complexes has proven difficult under prebiotically plausible conditions. We explore here that catalysis may have been performed by alternative polymeric structures, namely hyperbranched polymers. Hyperbranched polymers are relatively complex structures that can be synthesized under prebiotically plausible conditions; their globular structure is ensured by virtue of their architecture rather than folding. In this study, we probe the ability of tertiary amine-bearing hyperbranched polyesters to form hydrophobic pockets as a reaction-promoting medium for the Kemp elimination reaction. Our results show that polyesters formed upon reaction between glycerol, triethanolamine and organic acid containing hydrophobic groups, i.e. adipic and methylsuccinic acid, are capable of increasing the rate of Kemp elimination by a factor of up to 3 over monomeric triethanolamine.

This article is part of the themed issue ‘Reconceptualizing the origins of life’.
How causal analysis can reveal autonomy in models of biological systems
Authors: Marshall William , Kim Hyunju , Walker Sara I. , Tononi Giulio , Albantakis Larissa
Published: November 2017

Standard techniques for studying biological systems largely focus on their dynamical or, more recently, their informational properties, usually taking either a reductionist or holistic perspective. Yet, studying only individual system elements or the dynamics of the system as a whole disregards the organizational structure of the system—whether there are subsets of elements with joint causes or effects, and whether the system is strongly integrated or composed of several loosely interacting components. Integrated information theory offers a theoretical framework to (1) investigate the compositional cause–effect structure of a system and to (2) identify causal borders of highly integrated elements comprising local maxima of intrinsic cause–effect power. Here we apply this comprehensive causal analysis to a Boolean network model of the fission yeast (
Schizosaccharomyces pombe
) cell cycle. We demonstrate that this biological model features a non-trivial causal architecture, whose discovery may provide insights about the real cell cycle that could not be gained from holistic or reductionist approaches. We also show how some specific properties of this underlying causal architecture relate to the biological notion of autonomy. Ultimately, we suggest that analysing the causal organization of a system, including key features like intrinsic control and stable causal borders, should prove relevant for distinguishing life from non-life, and thus could also illuminate the origin of life problem.

This article is part of the themed issue ‘Reconceptualizing the origins of life’.
Herbicide ingredients change Salmonella enterica sv. Typhimurium and Escherichia coli antibiotic responses
Authors: Kurenbach Brigitta , Gibson Paddy S. , Hill Amy M. , Bitzer Adam S. , Silby Mark W. , Godsoe William , Heinemann Jack A.
Published: November 2017

Herbicides are frequently released into both rural and urban environments. Commercial herbicide formulations induce adaptive changes in the way bacteria respond to antibiotics. Salmonella enterica sv. Typhimurium and Escherichia coli were exposed to common co-formulants of formulations, and S. enterica sv. Typhimurium was exposed to active ingredients dicamba, 2,4-D and glyphosate to determine what ingredients of the commercial formulations caused this effect. Co-formulants Tween80 and carboxymethyl cellulose induced changes in response, but the pattern of the responses differed from the active ingredients, and effect sizes were smaller. A commercial wetting agent did not affect antibiotic responses. Active ingredients induced changes in antibiotic responses similar to those caused by complete formulations. This occurred at or below recommended application concentrations. Targeted deletion of efflux pump genes largely neutralized the adaptive response in the cases of increased survival in antibiotics, indicating that the biochemistry of induced resistance was the same for formulations and specific ingredients. We found that glyphosate, dicamba, and 2,4-D, as well as co-formulants in commercial herbicides, induced a change in susceptibility of the potentially pathogenic bacteria E. coli and S. enterica to multiple antibiotics. This was measured using the efficiency of plating (EOP), the relative survival of the bacteria when exposed to herbicide and antibiotic, or just antibiotic, compared to survival on permissive media. This work will help to inform the use of non-medicinal chemical agents that induce changes in antibiotic responses.
FLIM-based pH measurements reveal incretin-induced rejuvenation of aged insulin secretory granules
Authors: Neukam Martin , Sönmez Anke , Solimena Michele
Published: November 2017

Insulin is stored in dense-core secretory granules (SGs) and is released from beta cells in two distinct phases upon glucose stimulation. Newly synthesized insulin SGs are secreted preferentially, but the underlying mechanism of this phenomenon remains elusive. The relationship of SG age with their intraluminal pH is of particular interest: proinsulin conversion by prohormone convertases follows the acidification of immature SGs by the vacuolar proton-translocating ATPase (v-ATPase). v-ATPases may also participate in the formation of the fusion pore for SG exocytosis, with intraluminal alkalinization inhibiting membrane fusion. Previous studies examined the luminal pH of SGs on a population level only. Here we measured the pH-dependent lifetime changes of eCFP fused to the ICA512-RESP18 homology domain to assess for the first time the luminal pH of individual age-defined SGs in insulinoma INS-1 cells by fluorescence-lifetime imaging microscopy. We show that 2-4-hour-old young SGs have a pH of ~5.5, while 26-28-hour-old SGs have a pH of ~6.2. Remarkably, the GLP-1 receptor agonist Exendin-4 prompted the re-acidification of old SGs in a glutamate-dependent fashion, while it did not affect the pH of young SGs. This study demonstrates that insulin SGs change their pH over time - a change that is reversible by insulin secretagogues. Hence, it provides novel insight into the mechanisms accounting for aging and exocytosis of SGs and suggests that their ‘rejuvenation’ may be exploited to enhance insulin secretion in diabetes.
PAIRUP-MS: Pathway Analysis and Imputation to Relate Unknowns in Profiles from Mass Spectrometry-based metabolite data
Authors: Hsu Yu-Han H. , Churchhouse Claire , Pers Tune H. , Mercader Josep M. , Metspalu Andres , Fischer Krista , Fortney Kristen , Morgen Eric K. , Gonzalez Clicerio , Gonzalez Maria E. , Esko Tonu , Hirschhorn Joel N.
Published: November 2017

Metabolomics is a powerful approach for discovering biomarkers and metabolic quantitative trait loci. While untargeted profiling methods can measure up to thousands of metabolite signals in a single experiment, many signals cannot be readily identified as known metabolites or compared across datasets, making it difficult to infer biology and to conduct well-powered meta-analyses across studies. To deal with these challenges, we developed a suite of computational methods, PAIRUP-MS, to match metabolite signals across mass spectrometry-based profiling datasets using an imputation-based approach and to generate pathway annotations for these signals. We performed meta and pathway analyses for both known and unknown signals in multiple datasets and then validated the results using genetic associations. Finally, we applied the methods to detect metabolite signals and pathways associated with body mass index, demonstrating that our framework is useful for analyzing unknown signals in a robust and biologically meaningful manner and for improving the power of untargeted metabolomics studies.
PRS-on-Spark (PRSoS): a novel, efficient and flexible approach for generating polygenic risk scores
Authors: Chen Lawrence M. , Yao Nelson , Garg Elika , Zhu Yuecai , Nguyen Thao T. T. , Pokhvisneva Irina , Dass Shantala A. Hari , Forest Marie , McEwen Lisa M. , MacIsaac Julia L. , Kobor Michael S. , Greenwood Celia , Silveira Patricia P. , Meaney Michael J. , O’Donnell Kieran J.
Published: November 2017

Motivation

Polygenic risk scores describe the genomic contribution to complex phenotypes and consistently account for a larger proportion of the variance than single nucleotide polymorphisms alone. However, there is little consensus on the optimal data input for generating polygenic risk scores and existing approaches largely preclude the use of imputed posterior probabilities and strand-ambiguous SNPs.

Results

We developed PRS-on-Spark (PRSoS) a polygenic risk score software implemented in Apache Spark and Python that accommodates a variety of data input (e.g., observed genotypes, imputed genotypes, or imputed posterior probabilities) and strand-ambiguous SNPs. We show that PRSoS is flexible and efficient and computes polygenic risk scores at a range of p-value thresholds more quickly than existing software (PRSice). We also show that the use of imputed posterior probabilities and the inclusion of strand-ambiguous SNPs increases the proportion of variance explained by polygenic risk scores for major depression.

Availability and Implementation

PRSoS is written in Apache Spark and Python and is freely available (see https://github.com/MeaneyLab/PRSoS).
An analytical framework for understanding regulatory novelty accompanying allopolyploidization
Authors: Hu Guanjing , Wendel Jonathan F.
Published: November 2017

Allopolyploidy is a prevalent process in plants, having important physiological, ecological, and evolutionary consequences. Massive, genome-wide transcriptomic rewiring in response to genomic merger and doubling has been demonstrated in many allopolyploid systems, encompassing a diversity of phenomena, including homoeolog expression bias, genome dominance, expression-level dominance, and revamping of co-expression networks. Here we present an analytical framework to reconcile these patterns of regulatory novelty as governed by distinct sets of intra- and inter-subgenome cis-trans relationships. This approach is a novel extension of classic allele-specific expression analysis to incorporate and distinguish the separate effects of parental regulatory interactions as well as further complications at the allopolyploid level. We demonstrated that the cis-trans framework devised not only offers new perspective on disentangling genetic from epigenetic and higher-order effects that impact gene expression, but also provides the conceptual basis and tools to unify recently presented models for both genome-wide expression dominance and biased fractionation in allopolyploids.
Exploring biological networks in 3D, stereoscopic 3D and immersive 3D with iCAVE
Authors: Kalaycı Selim , Gümüş Zeynep H.
Published: November 2017

Biological networks are becoming increasingly large and complex, pushing the limits of existing 2D tools. iCAVE is an open source software tool for interactive visual explorations of large and complex networks in 3D, stereoscopic 3D or immersive 3D. It introduces new 3D network layout algorithms and 3D-extensions of popular 2D network layout, clustering and edge bundling algorithms to assists researchers in understanding the underlying patterns in large, multi-layered, clustered or complex networks. This protocol aims to guide new users on the basic functions of iCAVE for loading data, laying out networks (single or multi-layered), bundling edges, clustering networks, visualizing clusters, visualizing data attributes and saving output images or videos. It also provides examples on visualizing networks constrained in physical 3D space (e.g. proteins; neurons; brain). It is accompanied with a new version of iCAVE with an enhanced user interface and highlights new features useful for existing users.

Significance Statement

Network representations assist in systems-level data exploration in many research fields, providing valuable insights. However, with the recent advances in experimental technologies, biological networks are becoming increasingly large and complex, necessitating new data visualization solutions. We have recently developed iCAVE (Liluashvili et al., 2017), an open?source software platform that enables 3D (optionally stereoscopic and or immersive) visualizations of complex, dense or multi?layered biological networks. Users can select from several new 3D network layout and clustering algorithms, bundle network edges and customize network attributes to reveal hidden structures within them. This protocol guides new users on loading, navigating, customizing and saving networks in iCAVE and is accompanied by an updated version of the software.
Bioinformatics Workflow Management With The Wobidisco Ecosystem
Authors: Mondet Sebastien , Aksoy Bulent Arman , Rozenberg Leonid , Hodes Isaac , Hammerbacher Jeff
Published: November 2017

References

To conduct our computational experiments, our team developed a set of workflow-management-related projects: Ketrew, Biokepi, and Coclobas. The family of tools and libraries are designed with reliability and flexibility as main guiding principles. We describe the components of the software stack and explain the choices we made. Every piece of software is free and open-source; the umbrella documentation project is available at https://github.com/hammerlab/wobidisco.
The elephant in the room- Universal coverage for Costly treatments in an upper middle income country
Authors: Kaur RP , Ho GF , Mastura MY , Goh PP , Salowi Mohamad Aziz , Muhd. Radzi AH , Hau Anwar , Sathar Jameela , Robaayah Z , Selladurai Benedict , Suleiman Abu Bakar , Morad Zaki , Ghazali A , Lim TO
Published: November 2017

Background

Upper middle income countries have made substantial progress towards universal health coverage. We investigated whether the coverage extended to diseases that incur catastrophic health spending, the contribution of pooled financing and the factors driving it in Malaysia.

Methods

We adapted the WHO definition of catastrophic health spending to define costly treatment as one that cost, at prevailing market price, more than 10% of the median annual household income in Malaysia. Coverage is defined as the proportion of patients in a year who were in need of a treatment and who received it. Data to estimate coverage and financing were extracted from the published and grey literature, as well as secondary data sources available on disease epidemiology and healthcare in Malaysia.

Results

We found coverage varies from universal for dialysis, cataract surgery, medicines for organ transplant and CML, to practically none for HCV, stroke, psoriasis and epilepsy surgery. Coverage of targeted therapies for solid cancers, knee replacement surgery, anti-TNF for arthritis and coagulation factors for haemophilia were poor while iron chelation for thalassemia, coronary revacularization, epoetin and anti-retrovirals were barely adequate. Coverage correlates negatively (r=-0.82) with health benefits foregone, and is entirely driven by the contribution of pooled financing (r=0.99 p<0.0001). The relative effectiveness of a treatment, its budget impact, media coverage and political influence of the disease area have little influence on financing. Only effectiveness of the leadership representing the therapy area is influential; an increase in one point on the leadership effectiveness scale is associated with 30% increase in the contribution of pooled financing.

Conclusion

Coverage for catastrophically costly treatments is uneven and inequitable in Malaysia, despite most of these are affordable. Decisions on coverage are driven by political-economic consideration.
Effects of single cage housing on stress, cognitive and seizure parameters in the rat and mouse pilocarpine models of epilepsy
Authors: Manouze H , Ghestem A , Poillerat V , Bennis M , Ba-M’hamed S , Benoliel JJ , Becker C , Bernard C
Published: November 2017

Many experimental approaches require housing rodents in individual cages, including in epilepsy research. However, rats and mice are social animals; and individual housing constitutes a stressful situation. The goal of the present study was to determine the effects of individual housing as compared to conditions maintaining social contact on stress markers and epilepsy. Control male mice socially housed during pretest and then transferred to individual cages for six weeks displayed anhedonia, increased anxiety and biological markers of stress as compared to pretest values or mice kept socially housed during six weeks. Pilocarpine-treated mice housed together showed increased levels of anhedonia, anxiety and stress markers as well as decreased cognitive performance as compared to the control group. The differences were more significant in pilocarpine-treated mice housed individually. Anxiety correlated linearly with cognitive performance and stress markers independently of the experimental conditions. In the male rat pilocarpine model, seizures were sixteen times more frequent in singly housed animals as compared to animals kept in pairs. Daily interactions with an experimenter in otherwise singly housed animals was sufficient to produce results identical to those found in animals kept in pairs. We propose that social isolation produces a severe phenotype in terms of stress and seizure frequency as compared to animals maintaining social contact (at least in these two models), a factor that needs to be taken into account for data interpretation, in particular for preclinical studies.

Significance Statement

Many experimental approaches require housing rodents in individual cages, a stressful condition for social animals, even in an enriched environment context. Using the pilocarpine model of epilepsy in rats and mice, we report that singly housing animals develop a more severe phenotype in terms of stress and epilepsy as compared to animals maintaining social contact. We propose that social isolation adds a degree of complexity for the interpretation of data, which may be particularly relevant for preclinical studies.
Improving microbial electrosynthesis of polyhydroxybutyrate (PHB) from CO2byRhodopseudomonas palustrisTIE-1 using an immobilized iron complex modified cathode
Authors: Rengasamy Karthikeyan , Ranaivoarisoa Tahina Onina , Singh Rajesh , Bose Arpita
Published: November 2017

Microbial electrosynthesis (MES) is a promising bioelectrochemical approach to produce biochemicals. A previous study showed thatRhodopseudomonas palustrisTIE-1 can directly use poised electrodes as electron donors for photoautotrophic growth at cathodic potentials that avoid electrolytic H2production (photoelectroautotrophy). To make TIE-1 an effective biocatalyst for MES, we need to improve its electron uptake ability and growth under photoelectroautotrophic conditions. Because TIE-1 interacts with various forms of iron while using it as a source of electrons for photoautotrophy (photoferrotrophy), we tested the ability of iron-based redox mediators to enhance direct electron uptake. Our data show that soluble iron cannot act as a redox mediator for electron uptake by TIE-1 from a cathode poised at +100mV vs. Standard Hydrogen electrode. We then tested whether an immobilized iron-based redox mediator Prussian Blue (PB) can enhance electron uptake by TIE-1. Chronoamperometry indicates that cathodic current uptake by TIE-1 increased from 1.47 ± 0.04 to 5.6 ± 0.09 µA/cm2(3.8 times) and the production of the bioplastic, polyhydroxybutyrate (PHB) improved from 13.5 ± 0.2 g/L to 18.8 ± 0.5 g/L (1.4 times) on electrodes coated with PB. Overall, our data show that immobilized PB can increase direct electron uptake by TIE-1 and enhances PHB production.
Population Differentiation at theHLAGenes
Authors: Brandt Débora Y. C. , César Jônatas , Goudet Jérôme , Meyer Diogo
Published: November 2017

Balancing selection is defined as a class of selective regimes that maintain polymorphism above what is expected under neutrality. Theory predicts that balancing selection reduces population differentiation, as measured by FST. However, balancing selection regimes in which different sets of alleles are maintained in different populations could increase population differentiation. To tackle this issue, we investigated population differentiation at the HLA genes, which constitute the most striking example of balancing selection in humans. We found that population differentiation of single nucleotide polymorphisms (SNPs) at the HLA genes is on average lower than that of SNPs in other genomic regions. However, this result depends on accounting for the differences in allele frequency between selected and putatively neutral sites. Our finding of reduced differentiation at SNPs within HLA genes suggests a predominant role of shared selective pressures among populations at a global scale. However, in pairs of closely related populations, where genome-wide differentiation is low, differentiation at HLA is higher than in other genomic regions. This pattern was reproduced in simulations of overdominant selection. We conclude that population differentiation at the HLA genes is generally lower than genome-wide, but it may be higher for recently diverged population pairs, and that this pattern can be explained by a simple overdominance regime.
Modeling Spatial Genomic Interactions with the Hawkes model
Authors: Bonnet Anna , Rivoirard Vincent , Picard Franck
Published: November 2017

The spatial localization of many DNA-protein interactions is now available thanks to the development of ChIP-Seq, and their investigation calls for adapted statistical methods. Many methods were developped for peak calling, but few were proposed for the downstream analysis of peak-like data, whereas the spatial structure of such data may contain relevant biological information, like binding constraints for instance. Associations between the occurrences of two genomic features are usually assessed by overlaps, but here we propose a statistical model to precisely quantify the spatial interactions between the location of binding events. Our methodology relies on a multivariate spatial process, the Hawkes model, that can also be interpreted in terms of a graphical model to highlightspatial dependencies between genomic features. Using our method, we explore the chromatin landscape of replication origins, and we highlight attractive and repulsive patterns that can be related to the regulation of the spatial program of replication. We compete our method with both pairwise and multivariate approaches, implemented in the packages GenometriCorr and ppstat respectively. We show that our procedure describes with more details the complex patterns of spatial interactions and also provides estimates that are very convenient for interpretation.
Transcriptional Changes of DNA Replication and Repair Factors Over Uveal Melanoma Subtypes
Authors: Kucherlapati Melanie
Published: November 2017

Background

Uncontrolled replication is a process common to all cancers facilitated by the summation of changes accumulated as tumors progress. The aim of this study was to examine small groups of genes with known biology in replication and repair at the transcriptional and genomic levels, correlating alterations with survival in Uveal Melanoma tumor progression. Selected components of Pre-Replication, Pre-Initiation, and Replisome Complexes, DNA Damage Response and Mismatch Repair have been observed.

Methods

We have generated two groups for each gene examined above and below the average alteration level, and compared relative expression and survival across TCGA UVM subtypes based on somatic copy number alteration supported by DNA methylation and mRNA/miRNA/lncRNA expression. Significance between subtypes monosomic or disomic for chromosome 3 was determined by Fisher’s exact test. Kaplan Meier survival distribution based on disease specific survival was compared by log-rank test.

Results

Specific genes with significant alteration include MCM2 MCM4 and MCM5 of the Minichromosome Maintenance helicase complex, CDC45, MCM10, CIZ1, PCNA, FEN1, LIG1, POLD1, POLE, HUS1, CHECK1, ATRIP, MLH3, and MSH6. We found evidence of Exon 4 skipping in CIZ1 previously identified as a cancer variant and reportedly used as an early serum biomarker in lung cancer, accompanied by evidence of instability of a mononucleotide repeat in Intron 3. Mismatch Repair protein MLH3 was found to have splicing variations with deletions to both Exon 5 and Exon 7 simultaneously. PCNA, FEN1, and LIG1 had increased relative expression levels not due to their mutation or to copy number variation.

Conclusion

We have observed differences in relative and differential expression that support the concept that selected replication and repair genes and their products are causally involved in the origin and progression of uveal melanoma, suggesting specific avenues for early biomarker identification and also therapeutic approach.
Toward a Genome Scale Sequence Specific Dynamic Model of Cell-Free Protein Synthesis inEscherichia coli
Authors: Horvath Nicholas , Vilkhovoy Michael , Wayman Joseph A. , Calhoun Kara , Swartz James , Varner Jeffrey D.
Published: November 2017

Cell-free protein expression systems have become widely used in systems and synthetic biology. In this study, we developed an ensemble of dynamicE. colicell-free protein synthesis (CFPS) models. Model parameters were estimated from a training dataset for the cell-free production of a protein product, chloramphenicol acetyltransferase (CAT). The dataset consisted of measurements of glucose, organic acids, energy species, amino acids, and CAT. The ensemble accurately predicted these measurements, especially those of the central carbon metabolism. We then used the trained model to evaluate the optimality of protein production. CAT was produced with an energy efficiency of 12%, suggesting that the process could be further optimized. Reaction group knockouts showed that protein productivity and the metabolism as a whole depend most on oxidative phosphorylation and glycolysis and gluco-neogenesis. Amino acid biosynthesis is also important for productivity, while the overflow metabolism and TCA cycle affect the overall system state. In addition, the translation rate is shown to be more important to productivity than the transcription rate. Finally, CAT production was robust to allosteric control, as was most of the network, with the exception of the organic acids in central carbon metabolism. This study is the first to use kinetic modeling to predict dynamic protein production in a cell-freeE. colisystem, and should provide a foundation for genome scale, dynamic modeling of cell-freeE. coliprotein synthesis.
JQ1 affects BRD2-dependent and independent transcription regulation without disrupting H4-hyperacetylated chromatin states
Authors: Handoko Lusy , Kaczkowski Bogumil , Hon Chung-Chau , Lizio Marina , Wakamori Masatoshi , Matsuda Takayoshi , Ito Takuhiro , Jeyamohan Prashanti , Sato Yuko , Sakamoto Kensaku , Yokoyama Shigeyuki , Kimura Hiroshi , Minoda Aki , Umehara Takashi
Published: November 2017

The bromodomain and extra-terminal domain (BET) proteins are promising drug targets for cancer and immune diseases. However, BET inhibition effects have been studied more in the context of bromodomain-containing protein 4 (BRD4) than BRD2, and the BET protein association to histone H4-hyperacetylated chromatin is not understood at the genome-wide level. Here, we report transcription start site (TSS)-resolution integrative analyses of ChIP-seq and transcriptome profiles in human non-small cell lung cancer (NSCLC) cell line H23. We show that di-acetylation at K5 and K8 of histone H4 (H4K5acK8ac) co-localizes with H3K27ac and BRD2 in the majority of active enhancers and promoters, where BRD2 has a stronger association with H4K5acK8ac than H3K27ac. Interestingly, although BET inhibition by JQ1 led to complete reduction of BRD2 binding to chromatin, only local changes of H4K5acK8ac levels were observed. In addition, a remarkable number of BRD2-bound genes, including MYC and its downstream target genes, were transcriptionally upregulated upon JQ1 treatment. Using BRD2-enriched sites and transcriptional activity analysis, we identified candidate transcription factors potentially involved in the JQ1 response in BRD2-dependent and independent manner.
Resolving outbreak dynamics using Approximate Bayesian Computation for stochastic birth-death models
Authors: Lintusaari Jarno , Blomstedt Paul , Sivula Tuomas , Gutmann Michael U. , Kaski Samuel , Corander Jukka
Published: November 2017

Earlier research has suggested that Approximate Bayesian Computation (ABC) makes it possible to fit simulator-based intractable birth-death models to investigate communicable disease outbreak dynamics with accuracy comparable to that of exact Bayesian methods. However, recent findings have indicated that key parameters such as the reproductive number R may remain poorly identifiable. Here we show that the identifiability issue can be resolved by taking into account disease-specific characteristics of the transmission process in closer detail. Using tuberculosis (TB) in the San Francisco Bay area as a case-study, we consider the situation where the genotype data are generated as a mixture of three stochastic processes, each with their distinct dynamics and clear epidemiological interpretation.

The ABC inference yields stable and accurate posterior inferences about outbreak dynamics from aggregated annual case data with genotype information. We also show that under the proposed model, the infectious population size can be reliably inferred from the data. The estimate is approximately two orders of magnitude smaller compared to assumptions made in the earlier ABC studies, and is much better aligned with epidemiological knowledge about active TB prevalence. Similarly, the reproductive number R related to the primary underlying transmission process is estimated to be nearly three-fold compared with the previous estimates, which has a substantial impact on the interpretation of the fitted outbreak model.
Transcriptional Profiling of Somatostatin Interneurons in the Spinal Dorsal Horn
Authors: Chamessian Alexander , Young Michael , Qadri Yawar , Berta Temugin , Ji Ru-Rong , Van De Ven Thomas
Published: November 2017

The spinal dorsal horn (SDH) is comprised of distinct neuronal populations that process different somatosensory modalities. Somatostatin (SST)-expressing interneurons in the SDH have been implicated specifically in mediating mechanical pain. Identifying the transcriptomic profile of SST neurons could elucidate the unique genetic features of this population and enable selective analgesic targeting. To that end, we combined the Isolation of Nuclei Tagged in Specific Cell Types (INTACT) method and Fluorescence Activated Nuclei Sorting (FANS) to capture tagged SST nuclei in the SDH of adult male mice. Using RNA-sequencing (RNA-seq), we uncovered more than 13,000 genes. Differential gene expression analysis revealed more than 900 genes with at least 2-fold enrichment. In addition to many known dorsal horn genes, we identified and validated several novel transcripts from pharmacologically tractable functional classes: Carbonic Anhydrase 12 (Car12), Phosphodiesterase 11A (Pde11a), Protease-Activated Receptor 3 (F2rl2) and G-protein Coupled Receptor 26 (Gpr26). In situ hybridization of these novel genes revealed differential expression patterns in the SDH, demonstrating the presence of transcriptionally distinct subpopulations within the SST population. Pathway analysis revealed several enriched signaling pathways including cyclic AMP-mediated signaling, Nitric Oxide Synthase signaling, and voltage-gated calcium channels, highlighting the importance of these pathways to SST neuron function. Overall, our findings provide new insights into the gene repertoire of SST dorsal horn neurons and reveal several candidate targets for pharmacological modulation of this pain-mediating population.

Significance Statement

Somatostatin(SST)-expressing interneurons in the spinal dorsal horn (SDH) are required for the perception of mechanical pain. Identifying the distinctive genes expressed by SST neurons could facilitate the development of novel, circuit-targeting analgesics. Thus, we applied cell type-specific RNA-sequencing (RNA-seq) to provide the first transcriptional profile of SST neurons in the SDH. Bioinformatic analysis revealed hundreds of genes enriched in SST neurons, including several previously undescribed genes from druggable classes (Car12, Pde11a, F2rl2 and Gpr26). Taken together, our study unveils a comprehensive transcriptional signature for SST neurons, highlights promising candidate genes for future analgesic development, and establishes a flexible method for transcriptional profiling of any spinal cord cell type.
Identification of stable reference genes for quantitative PCR in koalas
Authors: Sarker N. , Fabijan J. , Emes R.D. , Hemmatzadeh F. , Meers J. , Moreton J. , Owen H. , Seddon J. M. , Simmons G. , Speight N. , Trott D. , Woolford L. , Tarlinton R.E
Published: November 2017

To better understand host and immune response to diseases, gene expression studies require identification of reference genes with stable expression for accurate normalisation. This study describes the selection and testing of reference genes with stable expression profiles in koala lymph node tissues across two genetically distinct koala populations. From the 25 most stable genes identified in transcriptome analysis, 11 genes were selected for verification using reverse transcription quantitative PCR, in addition to the commonly usedACTBandGAPDHgenes. The expression data were analysed using stable genes statistical software - geNorm, BestKeeper, NormFinder, the comparative ΔCt method and RefFinder. All 13 genes showed relative stability in expression in koala lymph node tissues, howeverTmem97andHmg20awere identified as the most stable genes across the two koala populations.
A common framework for the problem of deriving estimates of dynamic functional brain connectivity
Authors: Thompson William Hedley , Fransson Peter
Published: November 2017

The research field of dynamic functional connectivity explores the temporal properties of brain connectivity. To date, many methods have been proposed, which are based on quite different assumptions. In order to understand in which way the results from different techniques can be compared to each other, it is useful to be able to formulate them within a common theoretical framework. In this study, we describe such a framework that is suitable for many of the dynamic functional connectivity methods that have been proposed. Our overall intention was to derive a theoretical framework that was constructed such that a wide variety of dynamic functional connectivity techniques could be expressed and evaluated within the same framework. At the same time, care was given to the fact that key features of each technique could be easily illustrated within the framework and thus highlighting critical assumptions that are made. We aimed to create a common framework which should serve to assist comparisons between different analytical methods for dynamic functional brain connectivity and promote an understanding of their methodological advantages as well as potential drawbacks.

Highlights

Different approaches to compute dynamic functional brain connectivity have been proposed, each with their own assumptions.

We present a theoretical framework that encompasses a large majority of proposed methods.

Our common framework facilitates comparisons between different methods and illustrates their underlying assumptions.
Association between the brain-derived neurotrophic factor Val66Met polymorphism and overweight/obesity in Mexican pediatric population
Authors: Martínez-Ezquerro José Darío , Rendón-Macías Mario Enrique , Zamora-Mendoza Gerardo , Serrano-Meneses Jacobo , Rosales-Rodríguez Beatriz , Escalante-Bautista Deyanira , Rodríguez-Cruz Maricela , Sánchez González Raúl , Arellano-Pineda Yessica , López-Alarcón Mardia , Zampedri María Cecilia , Rosas-Vargas Haydeé
Published: November 2017

Background: The functional brain-derived neurotrophic factor (BDNF) rs6265 (G196A; Val66Met) single nucleotide polymorphism has been associated with eating disorders, BMI and obesity in distinct populations, both adult and pediatric, with contradictory results involving either Val or Met as the risk variant.
Aim of the study: To determine the association between the BDNF Val66Met polymorphism and BMI in Mexican children and adolescents.
Methods: BDNF Val66Met genotyping by restriction fragment length polymorphism and nutritional status characterized by their BMI-for-age z-scores (BAZ) from pediatric volunteers recruited in Mexico City (n=498) were analyzed by Fisher's exact test association analysis. Standardized residuals (R) were used to determine which genotype/allele had the major influence on the significant Fisher's exact test statistic. Odds ratios were analyzed to measure the magnitude and direction of the association between genotype and normal weight (≥ -2 SD < +1 SD) and overweight (≥ +1 SD, including obesity, Ow+Ob) status with 95% confidence intervals to estimate the precision of the effect as well as 95% credible intervals to obtain the most probable estimate.
Results: Comparisons between GG (Val/Val), GA (Val/Met) and AA (Met/Met) genotypes or Met homozygotes vs. Val carriers (combination of GG and GA genotypes) showed significant differences (p=0.034 and p=0.037, respectively) between normal weight and the combined overweight and obese pediatric subjects. Our data showed that children/adolescents homozygous for the A allele have increased risk of overweight compared to the Val carriers (Bayesian OR= 4.2, 95% CI** [1.09-33.1]).
Conclusion: This is the first report showing the significant association between the BDNF rs6265 AA (Met/Met) genotype and overweight/obesity in Mexican pediatric population.
A practical tool for Maximal Information Coefficient analysis
Authors: Albanese Davide , Riccadonna Samantha , Donati Claudio , Franceschi Pietro
Published: November 2017

Background

The ability of finding complex associations in large omics datasets, assessing their significance, and prioritizing them according to their strength can be of great help in the data exploration phase. Mutual Information based measures of association are particularly promising, in particular after the recent introduction of the TICeand MICeestimators, which combine computational efficiency with good bias/variance properties. Despite that, a complete software implementation of these two measures and of a statistical procedure to test the significance of each association is still missing.

Findings

In this paper we present MICtools, a comprehensive and effective pipeline which combines TICeand MICeinto a multi-step procedure that allows the identification of relationships of various degrees of complexity. MICtools calculates their strength assessing statistical significance using a permutation-based strategy. The performances of the proposed approach are assessed by an extensive investigation in synthetic datasets and an example of a potential application on a metagenomic dataset is also illustrated.

Conclusions

We show that MICtools, combining TICeand MICe, is able to highlight associations that would not be captured by conventional strategies. MICtools is implemented in Python, and is available for download athttps://github.com/minepy/mictools.
Genetic structure of a patchily distributed philopatric migrant: implications for management and conservation
Authors: Bounas Anastasios , Tsaparis Dimitris , Efrat Ron , Gradev Gradimir , Gustin Marco , Mikulic Kresimir , Rodríguez Airam , Sarà Maurizio , Kotoulas Georgios , Sotiropoulos Konstantinos
Published: November 2017

Significant demographic fluctuations can have major genetic consequences in wild populations. The Lesser Kestrel (Falco naumanni) has suffered from both population declines and range fragmentation during the second half of the 20th century. In this study we analysed multilocus microsatellite data to assess the genetic structure of the species. Our analysis revealed significant genetic structuring of Lesser Kestrel populations, not only at cross-continental scale, but also regionally within Central and Eastern (CE) Mediterranean. We detected signs of genetic bottlenecks in some of the peripheral populations coupled with small effective population sizes. Values of genetic differentiation among the largest populations were low, albeit significant, whereas the small peripheral CE Mediterranean populations showed higher levels of differentiation from all other populations. Gene flow levels were relatively low among the discontinuously distributed populations of the CE Mediterranean region. We argue that the observed spatial genetic structure can be attributed at some level to the past demographic decline experienced by the species. Finally, we identify management units in the region, and inform the design of conservation actions aiming at the increase of population sizes and dispersal rates among peripheral populations.
Transcriptomic and morphophysiological evidence for a specialized human cortical GABAergic cell type
Authors: Boldog Eszter , Bakken Trygve , Hodge Rebecca D. , Novotny Mark , Aevermann Brian D. , Baka Judith , Bordé Sándor , Close Jennie L. , Diez-Fuertes Francisco , Ding Song-Lin , Faragó Nóra , Kocsis Ágnes K. , Kovács Balázs , McCorrison Jamison M. , Miller Jeremy A. , Molnár Gábor , Oláh Gáspár , Ozsvár Attila , Rózsa Márton , Shehata Soraya , Smith Kimberly A. , Sunkin Susan M. , Tran Danny N. , Venepally Pratap , Wall Abby , Puskás László G. , Barzó Pál , Steemers Frank J. , Schork Nicholas J. , Scheuermann Richard H. , Lasken Roger S. , Lein Ed S. , Tamás Gábor
Published: November 2017

We describe convergent evidence from transcriptomics, morphology and physiology for a specialized GABAergic neuron subtype in human cortex. Using unbiased single nucleus RNA sequencing, we identify ten GABAergic interneuron subtypes with combinatorial gene signatures in human cortical layer 1 and characterize a novel group of human interneurons with anatomical features never described in rodents having large, “rosehip”-like axonal boutons and compact arborization. These rosehip cells show an immunohistochemical profile (GAD1/CCK-positive, CNR1/SST/CALB2/PVALB-negative) matching a single transcriptomically-defined cell type whose molecular signature is not seen in mouse cortex. Rosehip cells make homotypic gap junctions, predominantly target apical dendritic shafts of layer 3 pyramidal neurons and inhibit backpropagating pyramidal action potentials in microdomains of the dendritic tuft. These cells are therefore positioned for potent local control of distal dendritic computation in cortical pyramidal neurons.
Divergent effects of healthy ageing on semantic knowledge and control: Evidence from novel comparisons with semantically-impaired patients
Authors: Hoffman Paul
Published: November 2017

Effective use of semantic knowledge requires a set of conceptual representations and control processes which ensure that currently-relevant aspects of this knowledge are retrieved and selected. It is well-established that levels of semantic knowledge increase across the lifespan. However, the effects of ageing on semantic control processes have not been assessed. I addressed this issue by comparing the performance profiles of young and older people on a verbal comprehension test. Two sets of variables were used to predict accuracy and RT in each group: (a) the psycholinguistic properties of words probed in each trial, (b) the performance on each trial by two groups of semantically-impaired neuropsychological patients. Young people demonstrated poor performance for low frequency and abstract words, suggesting that they had difficulty processing words with intrinsically weak semantic representations. Indeed, performance in this group was strongly predicted by the performance of patients with semantic dementia, who suffer from degradation of semantic knowledge. In contrast, older adults performed poorly on trials where the target semantic relationship was weak and distractor relationships strong – conditions which require high levels of controlled processing. Their performance was not predicted by the performance of semantic dementia patients, but was predicted by the performance of patients with semantic control deficits. These findings indicate that the effects of ageing on semantic cognition are more complex than has previously been assumed. While older people have larger stores of knowledge than young people, they appear to be less skilled at exercising control over the activation of this knowledge.