bluuebunny/crossref_metadata_2025 huggingface dataset:
Properties of the full random effect modelling approach with missing covariates
Authors: Nyberg Joakim , Jonsson E. Niclas , Karlsson Mats O. , Häggström Jonas ,   members of the HBGDki Community
Published: June 2019

Two full model approaches was compared with respect to their ability to handle missing covariate information. The reference data analysis approach was the full model method in which the covariate effects are estimated conventionally using fixed effects, and missing covariate data is imputed with the median of the non-missing covariate information. This approach was compared to a novel full model method which treats the covariate data as observed data and estimates the covariates as random effects. A consequence of this way of handling the covariates is that no covariate imputation is required and that any missingness in the covariates is handled implicitly. The comparison between the two analysis methods was based on simulated data from a model of height for age z-scores as a function of age. Data was simulated with increasing degrees of randomly missing covariate information (0-90%) and analyzed using each of the two analysis approaches. Not surprisingly, the precision in the parameter estimates from both methods decreased with increasing degrees of missing covariate information. However, while the bias in the parameter estimates increased in a similar fashion for the reference method, the full random effects approach provided unbiased estimates for all degrees of covariate missingness.
hypeR: An R Package for Geneset Enrichment Workflows
Authors: Federico Anthony , Monti Stefano
Published: June 2019

Geneset enrichment is a popular method for annotating high-throughput sequencing data. Existing tools fall short in providing the flexibility to tackle the varied challenges researchers face in such analyses, particularly when analyzing many signatures across multiple experiments. We present a comprehensive R package for geneset enrichment workflows that offers multiple enrichment, visualization, and sharing methods in addition to novel features such as hierarchical geneset analysis and built-in markdown reporting. hypeR is a one-stop solution to performing geneset enrichment for a wide audience and range of use cases.

Availability and implementation

The most recent version of the package is available at https://github.com/montilab/hypeR.

Supplementary information

Comprehensive documentation and tutorials, are available at https://montilab.github.io/hypeR-docs.
Resistance to change? The impact of group medication on AMR gene dynamics during commercial pig production
Authors: Pollock Jolinda , Muwonge Adrian , Hutchings Michael R. , Mainda Geoffrey , Bronsvoort Barend M. , Duggan Laura C. , Gally David L. , Corbishley Alexander
Published: June 2019

The anthropogenic selection of antimicrobial resistance (AMR) genes is under intense scrutiny, particularly in livestock production, where group antimicrobial administration is used to control disease. Whilst large epidemiological studies provide important data on the diversity and distribution of AMR genes, we have little insight into how group antimicrobial administration impacts AMR gene abundance and diversity within a system. Here, faecal microbiome and AMR gene dynamics were tracked for six months through a standard production cycle on a commercial pig unit. Our results demonstrate that specific AMR genes have reached an equilibrium across this farming system to the extent that the levels measured were maintained from suckling through to slaughter, despite increases in microbiome diversity in early development. These levels were not influenced by antibiotic use, either during the production cycle or following whole herd medication. Some AMR genes were found at levels higher than that of the bacterial 16S rRNA gene, indicating widespread distribution across the most common bacterial genera. The targeted AMR genes were also detected in nearby soil samples, several with decreasing abundance with increasing distance from the unit, demonstrating that the farm acts as a point source of AMR gene ‘pollution’. Metagenomic sequencing of a subset of samples identified 144 AMR genes, with higher gene diversity in the piglet samples compared to the sow samples. Critically, despite overwhelming and stable levels of resistance alleles against the main antimicrobials used on this farm, these compounds continue to control the bacterial pathogens responsible for production losses and compromised welfare.

Importance

Group antibiotic treatment has been used for decades to control bacterial diseases that reduce the productivity and compromise the welfare of livestock. Recent increases in antibiotic resistant infections in humans has resulted in concerns that antibiotic use in livestock may contribute to the development of untreatable bacterial infections in humans. There is however little understanding as to how the genes that bacteria require to become resistant to antibiotics respond during and after group antibiotic treatment of livestock, particularly in systems where high levels of antibiotics have been used for a prolonged period of time. We show that in such a system, levels of specific antibiotic resistance genes are high irrespective of group antibiotic treatments, whilst dramatic reductions in antibiotic use also fail to reduce the levels of these genes. These findings have important implications for public policy relating to the use of antibiotic in livestock farming.
Large-scalein-vitroproduction of red blood cells from human peripheral blood mononuclear cells
Authors: Heshusius Steven , Heideveld Esther , Burger Patrick , Thiel-Valkhof Marijke , Sellink Erica , Varga Eszter , Ovchynnikova Elina , Visser Anna , Martens Joost H.A. , von Lindern Marieke , van den Akker Emile
Published: June 2019

Transfusion of donor-derived red blood cells is the most common form of cellular therapy. Donor availability and the potential risk of alloimmunization and other transfusion-related complications may, however, limit the availability of transfusion units especially for chronically transfused patients.In-vitrocultured, customizable red blood cells would negate these concerns and introduce precision medicine. Large-scale, cost effective production depends on optimization of culture conditions. We developed a defined medium and adapted our protocols to GMP culture requirements, which reproducibly provided pure erythroid cultures from peripheral blood mononuclear cells without prior CD34+isolation, and a 3×107-fold increase in erythroblasts in 25 days. Expanded erythroblast cultures could be differentiated to CD71dimCD235a+CD44+CD117−DRAQ5−red blood cells in 12 days. More than 90% of the cells enucleated and expressed adult hemoglobin as well as the correct blood group antigens. Deformability and oxygen binding capacity of cultured red blood cells was comparable toin-vivoreticulocytes. Daily RNA sampling during differentiation followed by RNA-seq provided a high-resolution map/resource of changes occurring during terminal erythropoiesis. The culture process was compatible with upscaling using a G-Rex bioreactor with a capacity of 1L per reactor, allowing transition towards clinical studies and small-scale applications.
Single-Cell Signalling Analysis of Heterocellular Organoids
Authors: Qin Xiao , Sufi Jahangir , Vlckova Petra , Kyriakidou Pelagia , Acton Sophie E. , Li Vivian S. W. , Nitz Mark , Tape Christopher J.
Published: June 2019

Organoids are powerful biomimetic tissue models. Despite their widespread adoption, methods to analyse cell-type specific post-translational modification (PTM) signalling networks in organoids are absent. Here we report multivariate single-cell analysis of cell-type specific signalling networks in organoids and organoid co-cultures. Simultaneous measurement of 28 PTMs in >1 million single small intestinal organoid cells by mass cytometry reveals cell-type and cell-state specific signalling networks in stem, Paneth, enteroendocrine, tuft, goblet cells, and enterocytes. Integrating single-cell PTM analysis with Thiol-reactive Organoid Barcoding in situ (TOBis) enables high-throughput comparison of signalling networks between organoid cultures. Multivariate cell-type specific PTM analysis of colorectal cancer tumour microenvironment organoids reveals that shApc, KrasG12D, and Trp53R172H cell-autonomously mimic signalling states normally induced by stromal fibroblasts and macrophages. These results demonstrate how standard mass cytometry workflows can be modified to perform high-throughput multivariate cell-type specific signalling analysis of healthy and cancerous organoids.
New approach and new program for analyses of false negatives-contaminated data in medicine and biology
Authors: Flegr Jaroslav , Tureček Petr
Published: June 2019

Background

No serological assay has 100% sensitivity. Statistically, the concentration of specific antibodies against antigens of parasites decreases with the duration of infection. This can result in false negative outputs of diagnostic tests for the subjects with old infectiong, e.g., for individuals infected in childhood. When a property of seronegative and seropositive subjects is compared under these circumstances, the statistical tests can detect no significant difference between these two groups of subjects, despite the fact that infected and noninfected subjects differ. When the effect of the infection has a cumulative character and subjects with an older infection (potential false negatives) are affected to a greater degree, we can even get paradoxical result of the comparison – the seronegative subjects have on average lower value of certain traits, e.g. IQ, despite the infection having a negative effect on the trait. A permutation test for the contaminated data, implemented, e.g., in the program Treept or available as a comprehensibly commented R function in the supplement of this paper, can be used to reveal and to eliminate the effect of false negatives.

Methods

We used a Monte Carlo simulation in the program R to show that the permutation test implemented in the programs Treept and PTPT is a conservative test.

Results

We showed that the test could provide false negative but not false positive results if the studied population contains no subpopulation of false negative subjects. We also introduced R version of the test expanded by skewness analysis, which helps to estimate the proportion of false negative subjects based on the assumption of equal data skewness in groups of healthy and infected individuals.

Conclusions

Based on the results of simulations and our experience with empirical studies we recommend the usage of permutation test for contaminated data whenever seronegative and seropositive individuals are compared.
Electrophysiological correlates of syntactic structures
Authors: Artoni Fiorenzo , d’Orio Piergiorgio , Catricalà Eleonora , Conca Francesca , Bottoni Franco , Pelliccia Veronica , Sartori Ivana , Russo Giorgio Lo , Cappa Stefano F. , Micera Silvestro , Moro Andrea
Published: June 2019

Syntax is traditionally defined as a specifically human way to pair sound with meaning: words are assembled in a recursive way generating a potentially infinite set of sentences1,2. There can be different phrasal structures depending on the types of words involved, for example, “noun phrases” (NP), combining an article and a noun, vs. “verb phrases” (VP), combining a verb and a complement. Although it is known that the combination of an increasing number of words in sequences correlates with an increasing electrophysiological activity3,4, the specific electrophysiological correlates of the syntactic operation generating NPs vs. VPs remain unknown. A major confounding factor is the fact that syntactic information is inevitably intertwined with the acoustic information contained in words even during inner speech5. Here, we addressed this issue in a novel way by designing a paradigm to factor out acoustic information and isolate the syntactic component. In particular, we construed phrases that have exactly the same acoustic content but that are interpreted as NPs or VPs depending on their syntactic context (homophonous phrases). By performing stereo-electro-encephalographic (SEEG) recordings in epileptic patients6we show that VPs are associated with a higher activity in the high gamma band (150-300Hz frequency), an index of cortical activity associated with linguistic processing, with respect to NPs in multiple cortical areas in both hemispheres, including language areas and their homologous in the non-dominant hemisphere. Our findings pave the way to a deeper understanding of the electrophysiological mechanisms underlying syntax and contribute to the ultimate far reaching goal of a complete neural decoding of linguistic structures from the brain2.
Machine learning reveals bilateral distribution of somatic L1 insertions in human neurons and glia
Authors: Zhu Xiaowei , Zhou Bo , Pattni Reenal , Gleason Kelly , Tan Chunfeng , Kalinowski Agnieszka , Sloan Steven , Fiston-Lavier Anna-Sophie , Mariani Jessica ,   Brain Somatic Mosaicism Network, Abyzov Alexej , Petrov Dimitri , Barres Ben A. , Vogel Hannes , Moran John V. , Vaccarino Flora M. , Tamminga Carol A. , Levinson Douglas F. , Urban Alexander E.
Published: June 2019

Active retrotransposons in the human genome (L1,Aluand SVA elements) can create genomic mobile element insertions (MEIs) in both germline and somatic tissue1. Specific somatic MEIs have been detected at high levels in human cancers2, and at lower to medium levels in human brains3. Dysregulation of somatic retrotransposition in the human brain has been hypothesized to contribute to neuropsychiatric diseases4, 5. However, individual somatic MEIs are present in small proportions of cells at a given anatomical location, and thus standard whole-genome sequencing (WGS) presents a difficult signal-to-noise problem, while single-cell approaches suffer from limited scalability and experimental artifacts introduced by enzymatic whole-genome amplification6. Previous studies produced widely differing estimates for the somatic retrotransposition rates in human brain3, 6–8. Here, we present a highly precise machine learning method (RetroSom) to directly identify somatic L1 andAluinsertions in <1% cells from 200× deep WGS, which allows circumventing the restrictions of whole-genome amplification. Using RetroSom we confirmed a lower rate of retrotransposition for individual somatic L1 insertions in human neurons. We discovered that anatomical distribution of somatic L1 insertion is as widespread in glia as in neurons, and across both hemispheres of the brain, indicating retrotransposition occurs during early embryogenesis. We characterized two of the detected brain-specific L1 insertions in great detail in neurons and glia from a donor with schizophrenia. Both insertions are within introns of genes active in brain (CNNM2,FRMD4A) in regions with multiple genetic associations with neuropsychiatric disorders9–11. Gene expression was significantly reduced by both somatic insertions in a reporter assay. Our results provide novel insights into the potential for pathological effects of somatic retrotransposition in the human brain, now including the large glial fraction. RetroSom has broad applicability in all disease states where somatic retrotransposition is expected to play a role, such as autoimmune disorders and cancer.
Resting-state “Physiological Networks”
Authors: Chen Jingyuan E. , Lewis Laura D. , Chang Catie , Fultz Nina E. , Ohringer Ned A. , Rosen Bruce R. , Polimeni Jonathan R.
Published: June 2019

Slow changes in systemic brain physiology can elicit large fluctuations in fMRI time series, which may manifest as structured spatial patterns of temporal correlations between distant brain regions. These correlations can appear similar to large-scale networks typically attributed to coupled neuronal activity. However, little effort has been devoted to a systematic investigation of such “physiological networks”—sets of segregated brain regions that exhibit similar physiological responses—and their potential influence on estimates of resting-state brain networks. Here, by analyzing a large group of subjects from the 3T Human Connectome Project database, we demonstrate brain-wide and noticeably heterogenous dynamics attributable to either respiratory variation or heart rate changes. We show that these physiologic dynamics can give rise to apparent “connectivity” patterns that resemble previously reported resting-state networks derived from fMRI data. Further, we show that this apparent “physiological connectivity” cannot be removed by the use of a single nuisance regressor for the entire brain (such as global signal regression) due to the clear regional heterogeneity of the physiological responses. Possible mechanisms causing these apparent “physiological networks”, and their broad implications for interpreting functional connectivity studies are discussed.
Deformed wing virus type A, a major honey bee pathogen, is vectored by the mite Varroa destructor in a non-propagative manner
Authors: Posada-Florez Francisco , Childers Anna K. , Heerman Matthew C. , Egekwu Noble I. , Cook Steven C. , Chen Yanping , Evans Jay D. , Ryabov Eugene V.
Published: June 2019

Honey bees, the primary managed insect pollinator, suffer considerable losses due to Deformed wing virus (DWV), an RNA virus vectored by the mite Varroa destructor. Mite vectoring has resulted in the emergence of virulent DWV variants. The basis for such changes in DWV is poorly understood. Most importantly, it remains unclear whether replication of DWV occurs in the mite. In this study, we exposed Varroa mites to DWV type A via feeding on artificially infected honey bees. A significant, 357-fold increase in DWV load was observed in these mites after 2 days. However, after 8 additional days of passage on honey bee pupae with low viral loads, the DWV load dropped by 29-fold. This decrease significantly reduced the mites’ ability to transmit DWV to honey bees. Notably, negative-strand DWV RNA, which could indicate viral replication, was detected only in mites collected from pupae with high DWV levels but not in the passaged mites. We also found that Varroa mites contain honey bee mRNAs, consistent with the acquisition of honey bee cells which would additionally contain DWV replication complexes with negative-strand DWV RNA. We propose that transmission of DWV type A by Varroa mites occurs in a non-propagative manner.
proDA: Probabilistic Dropout Analysis for Identifying Differentially Abundant Proteins in Label-Free Mass Spectrometry
Authors: Ahlmann-Eltze Constantin , Anders Simon
Published: June 2019

Protein mass spectrometry with label-free quantification (LFQ) is widely used for quantitative proteomics studies. Nevertheless, well-principled statistical inference procedures are still lacking, and most practitioners adopt methods from transcriptomics. These, however, cannot properly treat the principal complication of label-free proteomics, namely many non-randomly missing values.

We present proDA, a method to perform statistical tests for differential abundance of proteins. It models missing values in an intensity-dependent probabilistic manner. proDA is based on linear models and thus suitable for complex experimental designs, and boosts statistical power for small sample sizes by using variance moderation. We show that the currently widely used methods based on ad hoc imputation schemes can report excessive false positives, and that proDA not only overcomes this serious issue but also offers high sensitivity. Thus, proDA fills a crucial gap in the toolbox of quantitative proteomics.
Spontaneous eye blink rate predicts individual differences in exploration and exploitation during reinforcement learning
Authors: Van Slooten Joanne C. , Jahfari Sara , Theeuwesu Jan
Published: June 2019

Spontaneous eye blink rate (sEBR) has been linked to striatal dopamine function and to how individuals make value-based choices after a period of reinforcement learning (RL). While sEBR is thought to reflect how individuals learn from the negative outcomes of their choices, this idea has not been tested explicitly. This study assessed how individual differences in sEBR relate to learning by focusing on the cognitive processes that drive RL. Using Bayesian latent mixture modelling to quantify the mapping between RL behaviour and its underlying cognitive processes, we were able to differentiate low and high sEBR individuals at the level of these cognitive processes. Further inspection of these cognitive processes indicated that sEBR uniquely indexed explore-exploit tendencies during RL: lower sEBR predicted exploitative choices for high valued options, whereas higher sEBR predicted exploration of lower value options. This relationship was additionally supported by a network analysis where, notably, no link was observed between sEBR and how individuals learned from negative outcomes. Our findings challenge the notion that sEBR predicts learning from negative outcomes during RL, and suggest that sEBR predicts individual explore-exploit tendencies. These then influence value sensitivity during choices to support successful performance when facing uncertain reward.
A hidden gene in astroviruses encodes a cell-permeabilizing protein involved in virus release
Authors: Lulla Valeria , Firth Andrew E.
Published: June 2019

Human astroviruses are small nonenveloped viruses with positive-sense single-stranded RNA genomes that contain three main open reading frames: ORF1a, ORF1b and ORF2. Astroviruses cause acute gastroenteritis in children worldwide and have been associated with encephalitis and meningitis in immunocompromised individuals. Through comparative genomic analysis of >400 astrovirus sequences, we identified a conserved “ORFX” overlapping the capsid-encoding ORF2 in genogroup I, III and IV astroviruses. ORFX appears to be subject to purifying selection, consistent with it encoding a functional protein product, termed XP. Using ribosome profiling of cells infected with human astrovirus 1, we confirm initiation at the ORFX AUG. XP-knockout astroviruses are strongly attenuated and after passaging can partly restore viral titer via pseudo-reversions, thus demonstrating that XP plays an important role in virus growth. To further investigate XP, we developed an astrovirus replicon system. We demonstrate that XP has only minor effects on RNA replication and structural protein production. Instead, XP associates with the plasma membrane with an extracellular N-terminus topology and promotes efficient virus release. Using two different assays, we show that expression of human or related astrovirus XPs leads to cell permeabilization, suggesting a viroporin-like activity. The discovery of XP advances our knowledge of these important human viruses and opens a new direction of research into astrovirus replication and pathogenesis.
Molecular characterization of the stress network in the human brain
Authors: Meijer Mandy , Keo Arlin , van Leeuwen Judith M.C. , Dzyubachyk Oleh , Meijer Onno C. , Vinkers Christiaan H. , Mahfouz Ahmed
Published: June 2019

The biological mechanisms underlying inter-individual differences in human stress reactivity remain poorly understood. We aimed to identify the molecular underpinning of neural stress sensitivity. Linking mRNA expression data from the Allen Human Brain Atlas to task-based fMRI revealed 201 differentially expressed genes in cortex-specific brain regions differentially activated by stress in individuals with low or high stress sensitivity. These genes are associated with stress-related psychiatric disorders (e.g. schizophrenia and anxiety) and include markers for specific neuronal populations (e.g.ADCYAP1, GABRB1, SSTR1, andTNFRSF12A), neurotransmitter receptors (e.g.GRIN3A, SSTR1, GABRB1, andHTR1E), and signaling factors that interact with the corticosteroid receptor and hypothalamic-pituitary-adrenal axis (e.g. ADCYAP1,IGSF11, and PKIA). Overall, the identified genes potentially underlie altered stress reactivity in individuals at risk for psychiatric disorders and play a role in mounting an adaptive stress response, making them potentially druggable targets for stress-related diseases.
Fine-grained simulations of the microenvironment of vascularized tumours
Authors: Fredrich Thierry , Rieger Heiko , Chignola Roberto , Milotti Edoardo
Published: June 2019

One of many important features of the tumour microenvironment is that it is a place of active Darwinian selection where different tumour clones become adapted to the variety of ecological niches that make up the microenvironment. These evolutionary processes turn the microenvironment into a powerful source of tumour heterogeneity and contribute to the development of drug resistance in cancer. Here, we describe a computational tool to study the ecology of the microenvironment and report results about the ecology of the tumour microenvironment and its evolutionary dynamics.
Automated Microfossil Identification and Segmentation Using a Deep Learning Approach
Authors: Carvalho L.E , Fauth G. , Baecker Fauth S. , Krahl G. , Moreira A. C. , Fernandes C.P. , von Wangenheim A
Published: June 2019

The applicability of computational analysis to paleontological images ranges from the study of the animals, plants and evolution of microorganisms to the simulation of the habitat of living beings of a given epoch. It also can be applied in several niches, such as oil exploration, where there are several factors to be analyzed in order to minimize the expenses related to the oil extraction process. One factor is the characterization of the environment to be explored. This analysis can occur in several ways: use of probes, extraction of samples for petrophysical components evaluation, the correlation with logs of other drilling wells and so on. In the samples extraction part the Computed Tomography (CT) is of importance because it preserves the sample and makes it available for several analyzes. Based on 3D images generated by CT, several analyzes and simulations can be performed and processes, currently performed manually and exhaustively, can be automated. In this work we propose and validate a method for fully automated microfossil identification and extraction. A pipeline is proposed that begins in the scanning process and ends in an identification process. For the identification a Deep Learning approach was developed, which resulted in a high rate of correct microfossil identification (98% of Intersection Over Union). The validation was performed both through an automated quantitative analysis based upon ground truths generated by specialists in the micropaleontology field and visual inspection by these specialists. We also present the first fully annotated MicroCT-acquired publicly available microfossils dataset.
Hippocampal subfields and limbic white matter jointly predict learning rate in older adults
Authors: Bender Andrew R. , Brandmaier Andreas M. , Düzel Sandra , Keresztes Attila , Pasternak Ofer , Lindenberger Ulman , Kühn Simone
Published: June 2019

Age-related memory impairments have been linked to differences in structural brain parameters, including cerebral white matter (WM) microstructure and hippocampal (HC) volume, but their combined influences are rarely investigated. In a population-based sample of 337 older participants 61–82 years of age (Mage=69.66, SDage=3.92 years) we modeled the independent and joint effects of limbic WM microstructure and HC subfield volumes on verbal learning. Participants completed a verbal learning task over five learning trials and underwent magnetic resonance imaging (MRI), including structural and diffusion scans. We segmented three HC subregions on high-resolution MRI data and sampled mean fractional anisotropy (FA) from bilateral limbic WM tracts identified via deterministic fiber tractography. Using structural equation modeling, we evaluated the associations between learning rate and latent factors representing FA sampled from limbic WM tracts, and HC subfield volumes, as well as their latent interaction. Results showed limbic WM and the interaction of HC and WM – but not HC volume alone – predicted verbal learning rates. Model decomposition revealed HC volume is only positively associated with learning rate in individuals with higher levels of WM anisotropy. We conclude that structural characteristics of limbic WM regions and HC volume jointly contribute to verbal learning in older adults.
Convergent Hybrid Phase Ligation Strategy for Efficient Total Synthesis of Large Proteins Demonstrated for 212-residue Linker Histone H1.2
Authors: Hong Ziyong Z. , Yu Ruixuan R. , Zhang Xiaoyu , Webb Allison M. , Burge Nathaniel L. , Poirier Michael G. , Ottesen Jennifer J.
Published: June 2019

Simple and efficient total chemical synthesis of large proteins remains a significant challenge. Here, we report development of a convergent hybrid phase native chemical ligation (CHP-NCL) strategy that should be generally applicable for facile preparation of large proteins. Key to the strategy is the use of sequential ligation on the solid phase for the directed assembly of ~100-residue segments from short, synthetically accessible peptide components. These segments can then be assembled via convergent solution phase ligation, exploiting o-aminoaniline as a chemically flexible cryptic thioester with multiple activation modalitiies on resin and in situ. We demonstrate the feasibility of our approach through the total synthesis of 212-residue linker histone H1.2 in unmodified, phosphorylated, and citrullinated forms, each from eight component peptide segments. We further demonstrate that fully synthetic H1.2 replicates the binding interactions of linker histones to intact mononucleosomes, as a proxy for the essential function of linker histones in the formation and regulation of higher order chromatin structure.
Multiple memories can be simultaneously reactivated during sleep as effectively as a single memory
Authors: Schechtman Eitan , Antony James W. , Lampe Anna , Wilson Brianna J. , Norman Kenneth A. , Paller Ken A.
Published: June 2019

Memory consolidation involves the reactivation of memory traces during sleep. If many memories are reactivated each night, how much do they interfere with one another? To explore this question, we examined whether reactivating multiple memories incurs a cost to sleep-related benefits by contrasting reactivation of multiple memories versus single memories during sleep. First, participants learned the on-screen location of different images. Each image was part of a semantically interconnected group (e.g., images of different cats). Groups were comprised of either one, two, or six images. During sleep, group-related sounds (e.g., “meow”) were unobtrusively presented to reactivate memories for half of the groups. The benefit in location recall for cued versus non-cued items was independent of the number of items in the group, suggesting that reactivation occurs in a simultaneous, promiscuous manner. Intriguingly, sleep spindles and delta-theta power modulations were sensitive to group size and reflected the extent of previous learning. Our results demonstrate that multiple memories may be consolidated in parallel without compromising each memory’s sleep-related benefit, suggesting that the brain’s capacity for reactivation is not strictly limited by separate resources needed for individual memories. These findings highlight alternative models for parallel consolidation that should be considered in future studies.
Fine-mapping complex inversion breakpoints and investigating somatic pairing in theAnopheles gambiaespecies complex using proximity-ligation sequencing
Authors: Corbett-Detig Russell B. , Said Iskander , Calzetta Maria , Genetti Max , McBroome Jakob , Maurer Nicholas W. , Petrarca Vincenzo , Torre Alessandra della , Besansky Nora J.
Published: June 2019

Chromosomal inversions are fundamental drivers of genome evolution. In the main afro-tropical malaria vector species, belonging to theAnopheles gambiaespecies complex, inversions play an important role in local adaptation and have a rich history of cytological study. Despite the importance and ubiquity of some chromosomal inversions across the species complex, inversion breakpoints are often challenging to map molecularly due to the presence of large repetitive regions. Here, we develop an approach that uses Hi-C sequencing data to molecularly fine-map the breakpoints of inversions 2Rbc and 2Rd inA. coluzzii. We found that inversion breakpoints occur in large repetitive regions, and strikingly among three inversions analyzed, two breakpoints appear to be reused in two separate inversions. Additionally, we use heterozygous individuals to quantitatively investigate somatic pairing disruption in the regions immediately surrounding inversion breakpoints, and we find that pairing disruption is undetectable beyond approximately 250 Kb from the inversion breakpoints.
Biomarker discovery in inflammatory bowel diseases using network-based feature selection
Authors: Abbas Mostafa , Matta John , Le Thanh , Bensmail Halima , Obafemi-Ajayi Tayo , Honavar Vasant , EL-Manzalawy Yasser
Published: June 2019

Reliable identification of inflammatory biomarkers from metagenomics data is a promising direction for developing non-invasive, cost-effective, and rapid clinical tests for early diagnosis of IBD. We present an integrative approach to Network-Based Biomarker Discovery (NBBD) which integrates network analyses methods for prioritizing potential biomarkers and machine learning techniques for assessing the discriminative power of the prioritized biomarkers. Using a large dataset of new-onset pediatric IBD metagenomics biopsy samples, we compare the performance of Random Forest (RF) classifiers trained on features selected using a representative set of traditional feature selection methods against NBBD framework, configured using five different tools for inferring networks from metagenomics data, and nine different methods for prioritizing biomarkers as well as a hybrid approach combining best traditional and NBBD based feature selection. We also examine how the performance of the predictive models for IBD diagnosis varies as a function of the size of the data used for biomarker identification. Our results show that (i) NBBD is competitive with some of the state-of-the-art feature selection methods including Random Forest Feature Importance (RFFI) scores; and (ii) NBBD is especially effective in reliably identifying IBD biomarkers when the number of data samples available for biomarker discovery is small.
Inferring the landscape of recombination using recurrent neural networks
Authors: Adrion Jeffrey R. , Galloway Jared G. , Kern Andrew D.
Published: June 2019

Accurately inferring the genome-wide landscape of recombination rates in natural populations is a central aim in genomics, as patterns of linkage influence everything from genetic mapping to understanding evolutionary history. Here we describe ReLERNN, a deep learning method for estimating a genome-wide recombination map that is accurate even with small numbers of pooled or individually sequenced genomes. Rather than use summaries of linkage disequilibrium as its input, ReLERNN takes columns from a genotype alignment, which are then modeled as a sequence across the genome using a recurrent neural network. We demonstrate that ReLERNN improves accuracy and reduces bias relative to existing methods and maintains high accuracy in the face of demographic model misspecification, missing genotype calls, and genome inaccessibility. We apply ReLERNN to natural populations of AfricanDrosophila melanogasterand show that genome-wide recombination landscapes, while largely correlated among populations, exhibit important population-specific differences. Lastly, we connect the inferred patterns of recombination with the frequencies of major inversions segregating in naturalDrosophilapopulations.
A Bayesian Framework for Detecting Gene Expression Outliers in Individual Samples
Authors: Vivian John , Eizenga Jordan , Beale Holly C. , Morozova-Vaske Olena , Paten Benedict
Published: June 2019

Objective

Many antineoplastics are designed to target upregulated genes, but quantifying upregulation in a single patient sample requires an appropriate set of samples for comparison. In cancer, the most natural comparison set is unaffected samples from the matching tissue, but there are often too few available unaffected samples to overcome high inter-sample variance. Moreover, some cancer samples have misidentified tissues or origin, or even composite-tissue phenotypes. Even if an appropriate comparison set can be identified, most differential expression tools are not designed to accommodate comparing to a single patient sample.

Materials and Methods

We propose a Bayesian statistical framework for gene expression outlier detection in single samples. Our method uses all available data to produce a consensus background distribution for each gene of interest without requiring the researcher to manually select a comparison set. The consensus distribution can then be used to quantify over- and under-expression.

Results

We demonstrate this method on both simulated and real gene expression data. We show that it can robustly quantify overexpression, even when the set of comparison samples lacks ideally matched tissues samples. Further, our results show that the method can identify appropriate comparison sets from samples of mixed lineage and rediscover numerous known gene-cancer expression patterns.

Conclusions

This exploratory method is suitable for identifying expression outliers from comparative RNA-seq analysis for individual samples and Treehouse, a pediatric precision medicine group that leverages RNA-seq to identify potential therapeutic leads for patients, plans to explore this method for processing their pediatric cohort.
High risk of the Fall Armyworm invading into Japan and the Korean Peninsula via overseas migration
Authors: Ma Jian , Wang Yun-Ping , Wu Ming-Fei , Gao Bo-Ya , Liu Jie , Lee Gwan-Seok , Otuka Akira , Hu Gao
Published: June 2019

The fall armyworm, Spodoptera frugiperda (J.E. Smith) is an emerging and most severe pest species in the Old World. It is originally native in the Americas. Since 2016 it has spread widely and rapidly to throughout Africa, the Middle East, India, Southeast Asia and most recently southern China. By May 2019 it has appeared in 13 provinces in most southern China and would spread further to northern China. It is highly likely that S. frugiperda would enter into Japan and Korea via overseas migrations as many other migratory pests did before. To evaluate the invasion risk of S. frugiperda into Japan and Korean Peninsula, we modelled the rate of expansion and future potential migratory range of the insect by a trajectory analytical approach with flight behaviour of S. frugiperda implemented, and meteorological data of past five years (2014–2018) used. Our results predicted that S. frugiperda would migrate from southern and eastern China into Japan and Korea soon. Most likely, Japan would be invaded from Fujian and Zhejiang on 1 June – 15 July, and Kyushu, Shikoku and south-western Honshu could face the highest risk of S. frugiperda’s invasion. Korea would be most possibly reached by S. frugiperda from northern Zhejiang, Jiangsu, Anhui, and Shandong on 1 June – 15 July and later. Our results indicated a very high risk that S. frugiperda would annually invade Japan and the Korean Peninsula and cause a possible significant decrease in agricultural productivity.
Inactivation of genes in oxidative respiration and iron acquisition pathways in pediatric clinical isolates of small-colony variantEnterobactericeae
Authors: Greninger Alexander L. , Addetia Amin , Tao Yue , Adler Amanda , Qin Xuan
Published: June 2019

Isolation of bacterial small colony variants (SCVs) from clinical specimens is not uncommon and can fundamentally change the outcome of the associated infections. Bacterial SCVs often emerge with their normal colony phenotype (NCV) co-isolates in the same sample. The genetic and biochemical basis of SCV emergencein vivois not well understood in Gram-negative bacteria. In this study, we interrogated the causal genetic lesions of SCV growth in three pairs of NCV and SCV co-isolates ofEscherichia coli, Citrobacter freundii, andEnterobacter hormaechei. We confirmed the isogenic basis of SCV emergence, as there were only 4 single nucleotide variants in SCV forE. coli, 5 inC. freundii, and 8 inE. hormaechei, with respect to their NCV co-isolate. In addition, a 10.2kb chromosomal segment containing 11 genes was deleted in theE. hormaecheiSCV isolate. Intriguingly, each SCV had at least one coding change in a gene associated with bacterial oxidative respiration and another involved iron capture. Chemical rescue confirmed the causal role of heme biosynthesis inE. coliandC. freundiiand lipoic acid inE. hormaecheiSCV isolates. Genetic rescue restored normal growth under aerobic conditions forfesandhemLinC. freundii;hemLinE. coli; andlipAinE. hormaecheiSCV isolates. Prototrophic growth in all 3 SCVEnterobacteriaceaespecies was unaffected under anaerobic culture conditionsin vitro, illustrating how SCVs may persistin vivoby abandoning the highly energetic lifestyle in an iron-limiting environment. We propose that the selective loss of functions in oxidative respiration and iron acquisition is indicative of bacterial virulence attenuation for niche specialization and persistencein vivo.

Importance

Small colony variant (SCV) bacteria are routinely isolated in the clinical microbiology laboratory and can be notoriously difficult to treat. Most studies of the genetic underpinnings of SCV clinical isolates have examinedStaphylococcus aureusand few have looked at how SCV emerge in Gram-negative bacteria. Here, we undertook detailed characterization of three clinical isolates of SCV inEscherichia coli, Citrobacter freundii, andEnterobacter hormaecheialong with their NCV co-isolates. Genomic sequencing revealed that each SCV had at least one coding change in genes involved in both bacterial oxidative respiration and iron capture. Chemical and genetic rescue revealed that both pathways could be responsible for the small colony variant. Each of the SCV showed no growth defect compared to NCV when incubated under anaerobic conditions, indicating a potential mechanism for SCV survivalin vivo. We hypothesize that by retreating to anaerobic environments and avoiding escalating iron competition with the host, SCV have adapted to live to see another day.
CX3CL1 binding protein-2 (CBP2) of Plasmodium falciparum binds nucleic acids
Authors: Saxena Ritu , Kaur Jasweer , Hora Rachna , Singh Palwinder , Singh Vineeta , Mishra Prakash Chandra
Published: June 2019

Several exported Plasmodium falciparum(Pf) proteins contribute to malaria biology through their involvement in cytoadherence, immune evasion and host cell remodelling. Many of these exported proteins and other host molecules are present in iRBC (infected red blood cell) generated extracellular vesicles (EVs), which are responsible for host cell modification and parasite development. CX3CL1 binding proteins (CBPs) present on the surface of iRBC have been reported to contribute to cytoadhesion by binding with the chemokine ‘CX3CL1’ via their extracellular domains. Here, we have characterized the cytoplasmic domain of CBP2to understand its function in parasite biology using biochemical and biophysical methods. Recombinant cytoplasmic CBP2 (rcCBP2) binds nucleic acids showing interaction with DNA/RNA. rcCBP2 shows dimer formation under non-reducing conditions highlighting the role of disulphide bonds in oligomerization while ATP binding leads to structural changes in the protein. In vitro interaction studies depict its binding with a Maurer’s cleft resident protein ‘PfSBP1’, which is influenced by ATP binding of rcCBP2. Our results suggest CBP2 as a two-transmembrane (2TM) receptor responsible for targeting EVs and delivering cargo to host endothelial cells. We propose CBP2 as an important molecule having roles in cytoadherence and immune modulation through its extracellular and cytoplasmic domains respectively.
Quantitative modeling links in vivo microstructural and macrofunctional organization of human and macaque insular cortex, and predicts cognitive control abilities
Authors: Menon Vinod , Guillermo Gallardo , Pinsk Mark A. , Nguyen Van-Dang , Li Jing-Rebecca , Cai Weidong , Wassermann Demian
Published: June 2019

The human insular cortex is a heterogenous brain structure which plays an integrative role in guiding behavior. The cytoarchitectonic organization of the human insula has been investigated over the last century using postmortem brains but there has been little progress in noninvasive in vivo mapping of its microstructure and large-scale functional circuitry. Quantitative modeling of multi-shell diffusion MRI (dMRI) data from 440 HCP participants revealed that human insula microstructure differs significantly across its functionally defined dorsal anterior, ventral anterior, and posterior insula subdivisions that serve distinct cognitive and affective functions. The microstructural organization of the insula was mirrored in its functionally interconnected circuits with the anterior cingulate cortex that anchor the salience network, a system important for adaptive switching of cognitive control systems. Novel validation of the human insula findings came from quantitative dMRI modeling in macaques which revealed microstructural features consistent with known primate insula cytoarchitecture. Theoretical analysis and computer simulations, using realistic 3-dimensional models of neuronal morphology from postmortem tissue, demonstrated that dMRI signals reflect the cellular organization of cortical gray matter, and that these signals are sensitive to cell size and the presence of large neurons such as the von Economo neurons. Crucially, insular microstructural features were linked to behavior and predicted individual differences in cognitive control ability. Our findings open new possibilities for probing psychiatric and neurological disorders impacted by insular cortex dysfunction, including autism, schizophrenia, and fronto-temporal dementia.

Statement of Significance

The human insular cortex is a heterogenous brain structure which plays an integrative role in identifying salient sensory, affective, and cognitive cues for guiding attention and behavior. It is also is one of the most widely activated brain regions in all of human neuroimaging research. Here we use novel quantitative tools with in vivo diffusion MRI in large group (N=440) of individuals to uncover several unique microstructural features of the human insula and its macrofunctional circuits. Crucially, microstructural properties of the insular cortex predicted human cognitive control abilities, in agreement with its crucial role in adaptive human behaviors. Our findings open new possibilities for probing psychiatric and neurological disorders impacted by insular dysfunction, including autism, schizophrenia, and fronto-temporal dementia.
CA-170 – a potent small-molecule PD-L1 inhibitor or not?
Authors: Musielak Bogdan , Kocik Justyna , Skalniak Lukasz , Magiera-Mularz Katarzyna , Sala Dominik , Czub Mirosława , Holak Tad A. , Plewka Jacek
Published: June 2019

CA-170is currently the only small-molecule modulator in clinical trials targeting PD-L1 and VISTA proteins – important negative checkpoint regulators of immune activation. The reported therapeutic results to some extent mimic those of FDA-approved monoclonal antibodies overcoming the limitations of the high production costs and adverse effects of the latter. However, no conclusive biophysical evidence proving the binding to hPD-L1 has ever been presented. Using well-knownin vitromethods: NMR binding assay, HTRF and cell-based activation assays, we clearly show that there is no direct binding betweenCA-170and PD-L1. To strengthen our reasoning, we performed control experiments onAUNP-12– a 29-mer peptide, which is a precursor ofCA-170. Positive controls consisted of the well-documented small-molecule PD-L1 inhibitors:BMS-1166and peptide p57.