bluuebunny/crossref_metadata_2025 huggingface dataset:
Integrative studies of cultural evolution: crossing disciplinary boundaries to produce new insights
Authors: Kolodny Oren , Feldman Marcus W. , Creanza Nicole
Published: February 2018

Culture evolves according to dynamics on multiple temporal scales, from individuals' minute-by-minute behaviour to millennia of cultural accumulation that give rise to population-level differences. These dynamics act on a range of entities—including behavioural sequences, ideas and artefacts as well as individuals, populations and whole species—and involve mechanisms at multiple levels, from neurons in brains to inter-population interactions. Studying such complex phenomena requires an integration of perspectives from a diverse array of fields, as well as bridging gaps between traditionally disparate areas of study. In this article, which also serves as an introduction to the current special issue, we highlight some specific respects in which the study of cultural evolution has benefited and should continue to benefit from an integrative approach. We showcase a number of pioneering studies of cultural evolution that bring together numerous disciplines. These studies illustrate the value of perspectives from different fields for understanding cultural evolution, such as cognitive science and neuroanatomy, behavioural ecology, population dynamics, and evolutionary genetics. They also underscore the importance of understanding cultural processes when interpreting research about human genetics, neuroscience, behaviour and evolution.

This article is part of the theme issue ‘Bridging cultural gaps: interdisciplinary studies in human cultural evolution’.
The evolution of the capacity for language: the ecological context and adaptive value of a process of cognitive hijacking
Authors: Kolodny Oren , Edelman Shimon
Published: February 2018

Language plays a pivotal role in the evolution of human culture, yet the evolution of the capacity for language—uniquely within the hominin lineage—remains little understood. Bringing together insights from cognitive psychology, neuroscience, archaeology and behavioural ecology, we hypothesize that this singular occurrence was triggered by exaptation, or ‘hijacking’, of existing cognitive mechanisms related to sequential processing and motor execution. Observed coupling of the communication system with circuits related to complex action planning and control supports this proposition, but the prehistoric ecological contexts in which this coupling may have occurred and its adaptive value remain elusive. Evolutionary reasoning rules out most existing hypotheses regarding the ecological context of language evolution, which focus on ultimate explanations and ignore proximate mechanisms. Coupling of communication and motor systems, although possible in a short period on evolutionary timescales, required a multi-stepped adaptive process, involving multiple genes and gene networks. We suggest that the behavioural context that exerted the selective pressure to drive these sequential adaptations had to be one in which each of the systems undergoing coupling wasindependentlynecessary or highly beneficial, as well as frequent and recurring over evolutionary time. One such context could have been the teaching of tool production or tool use. In the present study, we propose the Cognitive Coupling hypothesis, which brings together these insights and outlines a unifying theory for the evolution of the capacity for language.

This article is part of the theme issue ‘Bridging cultural gaps: interdisciplinary studies in human cultural evolution’.
Current and potential roles of archaeology in the development of cultural evolutionary theory
Authors: Garvey Raven
Published: February 2018

Archaeology has much to contribute to the study of cultural evolution. Empirical data at archaeological timescales are uniquely well suited to tracking rates of cultural change, detecting phylogenetic signals among groups of artefacts, and recognizing long-run effects of distinct cultural transmission mechanisms. Nonetheless, these are still relatively infrequent subjects of archaeological analysis and archaeology's potential to help advance our understanding of cultural evolution has thus far been largely unrealized. Cultural evolutionary models developed in other fields have been used to interpret patterns identified in archaeological records, which in turn provides independent tests of these models' predictions, as demonstrated here through a study of late Prehistoric stone projectile points from the US Southwest. These tests may not be straightforward, though, because archaeological data are complex, often representing events aggregated over many years (or centuries or millennia), while processes thought to drive cultural evolution (e.g. biased learning) operate on much shorter timescales. To fulfil archaeology's potential, we should continue to develop models specifically tailored to archaeological circumstances, and explore ways to incorporate the rich contextual data produced by archaeological research.

This article is part of the theme issue ‘Bridging cultural gaps: interdisciplinary studies in human cultural evolution’.
Copy number variants in clinical WGS: deployment and interpretation for rare and undiagnosed disease
Authors: Gross Andrew M , Ajay Subramanian S. , Rajan Vani , Brown Carolyn , Bluske Krista , Burns Nicole , Chawla Aditi , Coffey Alison J , Malhotra Alka , Scocchia Alicia , Thorpe Erin , Dzidic Natasa , Hovanes Karine , Sahoo Trilochan , Dolzhenko Egor , Lajoie Bryan , Khouzam Amirah , Chowdhury Shimul , Belmont John , Roller Eric , Ivakhno Sergii , Tanner Stephen , McEachern Julia , Hambuch Tina , Eberle Michael , Hagelstrom R Tanner , Bentley David R , Perry Denise L , Taft Ryan J
Published: February 2018

Purpose

Current diagnostic testing for genetic disorders involves serial use of specialized assays spanning multiple technologies. In principle, whole genome sequencing (WGS) has the potential to detect all genomic mutation types on a single platform and workflow. Here we sought to evaluate copy number variant (CNV) calling as part of a clinically accredited WGS test.

Methods

Using a depth-based copy number caller we performed analytical validation of CNV calling on a reference panel of 17 samples, compared the sensitivity of WGS-based variants to those from a clinical microarray, and set a bound on precision using orthogonal technologies. We developed a protocol for family-based analysis, annotation, filtering, visualization of WGS based CNV calls, and deployed this across a clinical cohort of 79 rare and undiagnosed cases.

Results

We found that CNV calls from WGS are at least as sensitive as those from microarrays, while only creating a modest increase in the number of variants interpreted (~10 CNVs per case). We identified clinically significant CNVs in 15% of the first 79 cases analyzed. This pipeline also enabled identification of cases of uniparental disomy (UPD) and a 50% mosaic trisomy 14. Directed analysis of some CNVs enabled break-point level resolution of genomic rearrangements and phasing ofde-novoCNVs.

Conclusion

Robust identification of CNVs by WGS is possible within a clinical testing environment, and further developments will bring improvements in resolution of smaller and more complex CNVs.
Functional organization of motion and disparity sensitivity in human visual cortex
Authors: Kohler Peter J. , Meredith Wesley , Norcia Anthony M.
Published: February 2018

Vision with two eyes makes perception of weak visual contrast signals easier and, due to the lateral separation of the eyes, allows for the triangulation of depth relationships. While binocular summation of contrast signals affords the observer increased sensitivity, binocular summation of spatial cues related to changes in depth is associated with decreased sensitivity to the corresponding retinal image displacements. Perceptual models of contrast and motion-in-depth sensitivity have explained this divergence in sensitivity by proposing that probabilistic neural noise limits summing and differencing operations on small signals. Because these models do not scale well for highly suprathreshold visual signals typical of the natural environment, we approached the question of how dynamic binocular image differences are coded using direct neural measurements. Here we use Steady-State Visual Evoked Potentials in human participants to show that inter-ocular differences in retinal image motion that produce elevated perceptual thresholds generate strongly suppressed evoked response amplitudes compared to motion that is matched between the two eyes. This suppression is strongly dependent on the availability of well-defined spatial references in the image and is highly immature in 5-month-old infants. Because the suppression is of equal strength for horizontal and vertical directions of motion, it is not specific to the perception of motion in depth. Relational image cues play a critical role in early to intermediate perceptual processing stages, and these results suggest that a succession of spatial and inter-ocular differencing operations condition the visual signal representation, prior to the extraction of motion-in-depth.

Significance Statement

The present work underscores the importance of relational spatial cues in both the motion and disparity domains for binocular visual coding. Relative motion and relative disparity cues not only support fine-grain displacement sensitivity but strongly influence suprathreshold responsiveness. Extraction of these cues supports a powerful binocular interaction within the motion pathway that is suppressive in nature and poorly developed in infants. This suppressive interaction is present for both horizontal and vertical directions of motion and is thus not specific to motion-in-depth, as previously believed, but is rather hypothesized to be a pre-processing step, with motion-in-depth being computed at a later or separate stage.
Allele-specific transcription factor binding as a benchmark for assessing variant impact predictors
Authors: Wagih Omar , Merico Daniele , Delong Andrew , Frey Brendan J
Published: February 2018

Genetic variation has long been known to alter transcription factor binding sites, resulting in sometimes major phenotypic consequences. While the performance for current binding site predictors is well characterised, little is known on how these models perform at predicting impact of variants. We collected and curated over 132,000 potential allele-specific binding (ASB) ChIP-seq variants across 101 transcription factors (TFs). We then assessed the accuracy of TF binding models from five different methods on these high-confidence measurements, finding that deep learning methods were best performing yet still have room for improvement. Importantly, machine learning methods were consistently better than the venerable position weight matrix (PWM). Finally, predictions for certain TFs were consistently poor, and our investigation supports efforts to use features beyond sequence, such as methylation, DNA shape, and post-translational modifications. We submit that ASB data is a valuable benchmark for variant impact on TF binding.
Generative adversarial networks as a tool to recover structural information from cryo-electron microscopy data
Authors: Su Min , Zhang Hantian , Schawinski Kevin , Zhang Ce , Cianfrocco Michael A.
Published: February 2018

Cryo-electron microscopy (cryo-EM) is a powerful structural biology technique capable of determining atomic-resolution structures of biological macromolecules. Despite this ability, the low signal-to-noise ratio of cryo-EM data continues to remain a hurdle for assessing raw cryo-EM micrographs and subsequent image analysis. To help address this problem, we have performed proof-of-principle studies with generative adversarial networks, a form of artificial intelligence, to denoise individual particles. This approach effectively recovers global structural information for both synthetic and real cryo-EM data, facilitating per-particle assessment from noisy raw images. Our results suggest that generative adversarial networks may be able to provide an approach to denoise raw cryo-EM images to facilitate particle selection and raw particle interpretation for single particle and tomography cryo-EM data.
Computational Chromosome Conformation Capture by Correlation of ChIP-seq at CTCF motifs
Authors: Ibn-Salem Jonas , Andrade-Navarro Miguel A.
Published: February 2018

We present a computational method to gain knowledge of the three-dimensional structure of the genome from ChIP-seq datasets. While not designed to detect contacts, the ChIP-seq protocol cross-links proteins with each other and with DNA. Consequently, genomic regions that interact with the protein binding-site via chromatin looping are coimmunoprecipitated and sequenced. This produces minor ChIP-seq signals around CTCF motif pairs at loop anchor regions. Together with genomic sequence features, these signals predict whether loop anchors interact or not. Our method, Computational Chromosome Conformation Capture by Correlation of ChIP-seq at CTCF motifs (7C), is available as an R/Bioconductor package: http://bioconductor.org/packages/sevenC
Fatherhood alters gene expression within the MPOA
Authors: Seelke Adele M. H. , Bond Jessica M. , Simmons Trent C. , Joshi Nikhil , Settles Matthew L. , Stolzenberg Danielle , Rhemtulla Mijke , Bales Karen L.
Published: February 2018

Female parenting is obligate in mammals, but fathering behavior among mammals is rare. Only 3–5% of mammalian species exhibit biparental care, including humans, and mechanisms of fathering behavior remain sparsely studied. However, in species where it does exist, paternal care is often crucial to the survivorship of offspring. The present study is the first to identify new gene targets linked to the experience of fathering behavior in a biparental species using RNA sequencing. In order to determine the pattern of gene expression within the medial preoptic area that is specifically associated with fathering behavior, we identified differentially expressed genes in male prairie voles (Microtus ochrogaster)that experienced one of three social conditions: virgin males, pair bonded males, and males with fathering experience. Differentially expressed genes from each comparison (i.e., Virgin vs Paired, Virgin vs Fathers, and Paired vs Fathers) were evaluated using the Gene Ontology enrichment analysis, and Kegg pathways analysis to reveal metabolic pathways associated with specific differentially expressed genes. Using these tools, we identified a group of genes that are differentially expressed in voles with different amounts of social experience. These genes are involved in a variety of processes, with particular enrichment in genes associated with immune function, metabolism, synaptic plasticity, and the remodeling of dendritic spines. The identification of these genes and processes will lead to novel insights into the biological basis of fathering behavior.
Improved pathway reconstruction from RNA interference screens by exploiting off-target effects
Authors: Srivatsa Sumana , Kuipers Jack , Schmich Fabian , Eicher Simone , Emmenlauer Mario , Dehio Christoph , Beerenwinkel Niko
Published: February 2018

Pathway reconstruction has proven to be an indispensable tool for analyzing the molecular mechanisms of signal transduction underlying cell function. Nested effects models (NEMs) are a class of probabilistic graphical models designed to reconstruct signalling pathways from high-dimensional observations resulting from perturbation experiments, such as RNA interference (RNAi). NEMs assume that the short interfering RNAs (siRNAs) designed to knockdown specific genes are always on-target. However, it has been shown that most siRNAs exhibit strong off-target effects, which further confound the data, resulting in unreliable reconstruction of networks by NEMs. Here, we present an extension of NEMs called probabilistic combinatorial nested effects models (pc-NEMs), which capitalize on the ancillary siRNA off-target effects for network reconstruction from combinatorial gene knockdown data. Our model employs an adaptive simulated annealing search algorithm for simultaneous inference of network structure and error rates inherent to the data. Evaluation of pc-NEMs on simulated data with varying number of phenotypic effects and noise levels demonstrates improved reconstruction compared to classical NEMs. Application to Bartonella henselae infection RNAi screening data yielded an eight node network largely in agreement with previous works, and revealed novel binary interactions of direct impact between established components.

Availability: The software used for the analysis is freely available as an R package at https://github.com/cbg-ethz/pcNEM.git

Contact: niko.beerenwinkel@bsse.ethz.ch
Identification of endogenous Adenomatous polyposis coli interaction partners and β-catenin-independent targets by proteomics
Authors: Popow Olesja , Tatham Michael H. , Paulo João A. , Rojas-Fernandez Alejandro , Loyer Nicolas , Newton Ian P. , Januschke Jens , Haigis Kevin M. , Näthke Inke
Published: February 2018

Adenomatous polyposis coli(APC) is the most frequently mutated gene in colorectal cancer. APC negatively regulates the pro-proliferative Wnt signaling pathway by promoting the degradation of β-catenin, but the extent to which APC exerts Wnt/β-catenin-independent tumor suppressive activity is unclear. To identify interaction partners and β-catenin-independent targets of endogenous, full-length APC, we applied label-free and multiplexed TMT mass spectrometry. Affinity enrichment-mass spectrometry revealed over 150 previously unidentified APC interaction partners. Moreover, our global proteomic analysis revealed that roughly half of the protein expression changes that occur in response to APC loss are independent of β-catenin. By combining these two analyses, we identified Misshapen-like kinase 1 (MINK1) as a putative substrate of an alternative APC-containing destruction complex and provide evidence for the potential contribution of MINK1 toAPCmutant phenotypes. Collectively, our results highlight the extent and importance of Wnt-independent APC functions in epithelial biology and disease.
Germline DNA replication timing shapes mammalian genome composition
Authors: Yehuda Yishai , Blumenfeld Britny , Mayorek Nina , Makedonski Kirill , Vardi Oriya , Mansour Yousef , Masika Hagit , Farago Marganit , Baror-Sebban Shulamit , Buganim Yosef , Koren Amnon , Simon Itamar
Published: February 2018

Mammalian DNA is replicated in a highly organized and regulated manner. Large, Mb-sized regions are replicated at defined times along S phase. DNA Replication Timing (RT) has been suggested to play an important role in shaping the mammalian genome by affecting mutation rates. Previous analyses relied on somatic DNA RT profiles, while to fully understand the influences of RT on the mammalian genome, germ cell RT information is necessary, as only germline mutations are passed to offspring and thus affect genomic composition. Using an improved RT mapping technique that allows mapping the RT from limited amounts of cells, we measured RT from two stages in the mouse germline - primordial germ cells (PGCs) and spermatogonial stem cells (SSCs). The germ cell RT profiles were distinct from those of both somatic and embryonic tissues. The correlations between RT and both mutation rate and recombination hotspots were not only confirmed in the germline tissues, but were shown to be stronger compared to correlations with RT of somatic tissues, emphasizing the importance of using RT profiles from the correct tissue of origin. Expanding the analysis to additional genetic features such as GC content, transposable elements (SINEs and LINEs) and gene density, also revealed a stronger correlation with the germ cell RT maps. GC content stratification along with multiple regression analysis revealed the independent contribution of RT to SINE, gene, mutation and recombination hotspot densities. Taken together, our results point to the centrality of RT in shaping multiple levels of mammalian genome composition.
Deterministic response strategies in trial-and-error learning
Authors: Mohr Holger , Zwosta Katharina , Markovic Dimitrije , Bitzer Sebastian , Wolfensteller Uta , Ruge Hannes
Published: February 2018

Trial-and-error learning is a universal strategy for establishing which actions are beneficial or harmful in new environments. However, learning stimulus-response associations solely via trial-and-error is often suboptimal, as in many settings dependencies among stimuli and responses can be exploited to increase learning efficiency. Previous studies have shown that in settings featuring such dependencies, humans typically engage high-level cognitive processes and employ advanced learning strategies to improve their learning efficiency. Here we analyze in detail the initial learning phase of a sample of human subjects (N = 85) performing a trial-and-error learning task with deterministic feedback and hidden stimulus-response dependencies. Using computational modeling, we find that the standard Q-learning model cannot sufficiently explain human learning strategies in this setting. Instead, newly introduced deterministic response models, which are theoretically optimal and transform stimulus sequences unambiguously into response sequences, provide the best explanation for 50.6% of the subjects. Most of the remaining subjects either show a tendency towards generic optimal learning (21.2%) or at least partially exploit stimulus-response dependencies (22.3%), while a few subjects (5.9%) show no clear preference for any of the employed models. After the initial learning phase, asymptotic learning performance during the subsequent practice phase is best explained by the standard Q-learning model. Our results show that human learning strategies in trial-and-error learning go beyond merely associating stimuli and responses via incremental reinforcement. Specifically during initial learning, high-level cognitive processes support sophisticated learning strategies that increase learning efficiency while keeping memory demands and computational efforts bounded. The good asymptotic fit of the Q-learning model indicates that these cognitive processes are successively replaced by the formation of stimulus-response associations over the course of learning.
Type-I interferons inhibit interleukin-10 signaling and favor type 1 diabetes development in NOD mice
Authors: Iglesias Marcos , Arun Anirudh , Chicco Maria , Lam Brandon , Talbot Conover , Ivanova Vera , Lee W. P. A , Brandacher Gerald , Raimondi Giorgio
Published: February 2018

Destruction of insulin-producing β-cells by autoreactive T lymphocytes leads to the development of type 1 diabetes. Type I interferons (TI-IFN) and interleukin-10 (IL-10) have been connected with the pathophysiology of this disease; however, their interplay in the modulation of diabetogenic T cells remains unknown. We have discovered that TI-IFN cause a selective inhibition of IL-10 signaling in effector and regulatory T cells, altering their responses. This correlates with diabetes development in NOD mice, where the inhibition is also spatially localized to T cells of pancreatic and mesenteric lymph nodes. IL-10 signaling inhibition is reversible and can be restored via blockade of TI-IFN/IFN-R interaction, paralleling with the resulting delay in diabetes onset and reduced severity. Overall, we propose a novel molecular link between TI-IFN and IL-10 signaling that helps better understand the complex dynamics of autoimmune diabetes development and reveals new strategies of intervention.

Abbreviations

ALN

axillary lymph nodes

IL-10

interleukin-10

MFI

mean fluorescence intensity

MLN

mesentheric lymph nodes

NOD

nonobese diabetic mice

PLN

pancreatic lymph nodes

TI-IFN

type-1 Interferons

Tmem

memory T cells

Treg

regulatory T cells
AAK1 inhibits WNT signaling by promoting clathrin-mediated endocytosis of LRP6
Authors: Agajanian Megan J. , Walker Matthew P. , Axtman Alison D. , Ruela-de-Sousa Roberta R. , Rabinowitz Alex D. , Graham David M. , Ryan Meagan , Serafin D. Stephen , Bennett James M. , Couñago Rafael M. , Drewry David H. , Elkins Jonathan M. , Gileadi Carina , Gileadi Opher , Godoi Paulo H. , Kapadia Nirav , Müller Susanne , Santiago André S. , Sorrell Fiona J. , Wells Carrow I. , Fedorov Oleg , Willson Timothy M. , Zuercher William J. , Major Michael B.
Published: February 2018

β-catenin-dependent WNT signal transduction governs normal development and adult tissue homeostasis. Inappropriate pathway activity mediates a vast array of human diseases, including bone density disorders, neurodegeneration and cancer. Although several WNT-directed therapeutics are in clinical trials, new targets, compounds and strategies are needed. We performed a gain-of-function screen of the human kinome to identify new druggable regulators of β-catenin-dependent transcription. We found that over-expression of the AP2 Associated Kinase 1 (AAK1) strongly inhibited WNT signaling. Reciprocally, silencing of AAK1 expression or pharmacological inhibition of AAK1 kinase activity using a new, selective and potent small molecule inhibitor activated WNT signaling. This small molecule is a cell active dual AAK1/BMP2K inhibitor that represents the best available tool to study AAK1-dependent signaling pathways. We report that AAK1 and the WNT co-receptor LRP6 physically co-complex and that AAK1 promotes clathrin-mediated endocytosis of LRP6. Collectively, our data support a WNT-induced negative feedback loop mediated by AAK1-driven, clathrin-mediated endocytosis of LRP6.

Summary Statement

A gain-of-function screen of the human kinome revealed AAK1 as a negative regulator of WNT signaling. We show that AAK1 promotes clathrin-mediated endocytosis of LRP6, resulting in downregulation of WNT signaling. We use a new selective and potent AAK1/BMP2K small molecule probe to validate our findings.
Targeted enrichment outperforms other enrichment techniques and enables more multi-species RNA-Seq analyses
Authors: Chung Matthew , Teigen Laura , Liu Hong , Libro Silvia , Shetty Amol , Kumar Nikhil , Zhao Xuechu , Bromley Robin E. , Tallon Luke J. , Sadzewicz Lisa , Fraser Claire M. , Rasko David A. , Filler Scott G. , Foster Jeremy M. , Michalski Michelle L. , Bruno Vincent M. , Dunning Hotopp Julie C.
Published: February 2018

Enrichment methodologies enable analysis of minor members in multi-species transcriptomic analyses. We compared standard enrichment of bacterial and eukaryotic mRNA to targeted enrichment with Agilent SureSelect (AgSS) capture for Brugia malayi, Aspergillus fumigatus, and the Wolbachia endosymbiont of B. malayi (wBm). Without introducing significant systematic bias, the AgSS quantitatively enriched samples, resulting in more reads mapping to the target organism. The AgSS-enriched libraries consistently had a positive linear correlation with its unenriched counterpart (r2=0.559-0.867). Up to a 2,242-fold enrichment of RNA from the target organism was obtained following a power law (r2=0.90), with the greatest fold enrichment achieved in samples with the largest ratio difference between the major and minor members. While using a single total library for prokaryote and eukaryote in a single sample could be beneficial for samples where RNA is limiting, we observed a decrease in reads mapping to protein coding genes and an increase of multi-mapping reads to rRNAs in AgSS enrichments from eukaryotic total RNA libraries as opposed to eukaryotic poly(A)-enriched libraries. Our results support a recommendation of using Agilent SureSelect targeted enrichment on poly(A)-enriched libraries for eukaryotic captures and total RNA libraries for prokaryotic captures to increase the robustness of multi-species transcriptomic studies.
Connecting conceptual and spatial search via a model of generalization
Authors: Wu Charley M. , Schulz Eric , Garvert Mona M. , Meder Björn , Schuck Nicolas W.
Published: February 2018

The idea of a “cognitive map” was originally developed to explain planning and generalization in spatial domains through a representation of inferred relationships between experiences. Recently, new research has suggested similar principles may also govern the representation of more abstract, conceptual knowledge in the brain. We test whether the search for rewards in conceptual spaces follows similar computational principles as in spatial environments. Using a within-subject design, participants searched for both spatially and conceptually correlated rewards in multi-armed bandit tasks. We use a Gaussian Process model combining generalization with an optimistic sampling strategy to capture human search decisions and judgments in both domains, and to simulate human-level performance when specified with participant parameter estimates. In line with the notion of a domain-general generalization mechanism, parameter estimates correlate across spatial and conceptual search, yet some differences also emerged, with participants generalizing less and exploiting more in the conceptual domain.
Sharing is not erring: Pseudo-reciprocity in collective search
Authors: Bouhlel Imen , Wu Charley M. , Hanaki Nobuyuki , Goldstone Robert L.
Published: February 2018

Information sharing in competitive environments may seem counterintuitive, yet it is widely observed in humans and other animals. For instance, the open-source software movement has led to new and valuable technologies being released publicly to facilitate broader collaboration and further innovation. What drives this behavior and under which conditions can it be beneficial for an individual? Using simulations in both static and dynamic environments, we show that sharing information can lead to individual benefits through the mechanisms of pseudo-reciprocity, whereby shared information leads to by-product benefits for an individual without the need for explicit reciprocation. Crucially, imitation with a certain level of innovation is required to avoid a tragedy of the commons, while the mechanism of a local visibility radius allows for the coordination of self-organizing collectives of agents. When these two mechanisms are present, we find robust evidence for the benefits of sharing—even when others do not reciprocate.
A Computational Synaptic Antibody Characterization and Screening Framework for Array Tomography
Authors: Simhal Anish K. , Gong Belvin , Trimmer James S. , Weinberg Richard J. , Smith Stephen J. , Sapiro Guillermo , Micheva Kristina D.
Published: February 2018

Application-specific validation of antibodies is a critical prerequisite for their successful use. Here we introduce an automated framework for characterization and screening of antibodies against synaptic molecules for high-resolution immunofluorescence array tomography (AT). The proposed Synaptic Antibody Screening Tool (SACT), is designed to provide an automatic, robust, flexible, and efficient tool for antibody characterization at scale. By allowing the user to define the molecular composition and size of synapses expected to contain the antigen, the method detects and characterizes puncta and synapses, and outputs automatically computed characteristics such as synapse density and target specificity ratio, which reflect the sensitivity and specificity of immunolabeling with a given antibody. These measurements provide an objective way to characterize and compare the performance of different antibodies against the same target, and can be used to objectively select the antibodies best suited for AT and potentially for other immunolabeling applications.
Transfer learning for biomedical named entity recognition with neural networks
Authors: Giorgi John M , Bader Gary D
Published: February 2018

Motivation

The explosive increase of biomedical literature has made information extraction an increasingly important tool for biomedical research. A fundamental task is the recognition of biomedical named entities in text (BNER) such as genes/proteins, diseases, and species. Recently, a domain-independent method based on deep learning and statistical word embeddings, called long short-term memory network-conditional random field (LSTM-CRF), has been shown to outperform state-of-the-art entity-specific BNER tools. However, this method is dependent on gold-standard corpora (GSCs) consisting of hand-labeled entities, which tend to be small but highly reliable. An alternative to GSCs are silver-standard corpora (SSCs), which are generated by harmonizing the annotations made by several automatic annotation systems. SSCs typically contain more noise than GSCs but have the advantage of containing many more training examples. Ideally, these corpora could be combined to achieve the benefits of both, which is an opportunity for transfer learning. In this work, we analyze to what extent transfer learning improves upon state-of-the-art results for BNER.

Results

We demonstrate that transferring a deep neural network (DNN) trained on a large, noisy SSC to a smaller, but more reliable GSC significantly improves upon state-of-the-art results for BNER. Compared to a state-of-the-art baseline evaluated on 23 GSCs covering four different entity classes, transfer learning results in an average reduction in error of approximately 11%. We found transfer learning to be especially beneficial for target data sets with a small number of labels (approximately 6000 or less).

Availability and implementation

Source code for the LSTM-CRF is available athttps://github.com/Franck-Dernoncourt/NeuroNER/and links to the corpora are available athttps://github.com/BaderLab/Transfer-Learning-BNER-Bioinformatics-2018/.

Contact

john.giorgi@utoronto.ca

Supplementary information

Supplementary data are available atBioinformaticsonline.
Oscillations in working memory and neural binding: a mechanism for multiple memories and their interactions
Authors: Pina Jason E. , Bodner Mark , Ermentrout Bard
Published: February 2018

Neural oscillations have been implicated in many different basic brain and cognitive processes. Oscillatory activity has been suggested to play a role in neural binding, and more recently in the maintenance of information in working memory. This latter work has focused primarily on oscillations in terms of providing a “code” in working memory. However, oscillations may additionally play a fundamental role in essential properties and behaviors that neuronal networks must exhibit in order to produce functional working memory. In the present work, we present a biologically plausible working memory model and demonstrate that specific types of stable oscillatory dynamics may play a critical role in facilitating properties of working memory, including transitions between different memory states and a multi-item working memory capacity. We also show these oscillatory dynamics may facilitate and provide an underlying mechanism to enable a range of different types of binding in the context of working memory.

Author summary

Working memory is a form of short-term memory that is limited in capacity to perhaps 3 – 5 items. Various studies have shown that ensembles of neurons oscillate during working memory retention, and cross-frequency coupling (between, e.g., theta and gamma frequencies) has been conjectured as underlying the observed limited capacity. Binding occurs when different objects or concepts are associated with each other and can persist as working memory representations; neuronal synchrony has been hypothesized as the neural correlate. We propose a novel computational model of a network of oscillatory neuronal populations that capture salient attributes of working memory and binding by allowing for both stable synchronous and asynchronous activity. The oscillatory dynamics we describe may provide a mechanism that can facilitate aspects of working memory, such as maintaining multiple items active at once, creating rich neural representations of memories via binding, and rapidly transitioning activtation patterns based on selective inputs.
State-Switching Probability Reveals Sleep-Related Biological Drives inDrosophila
Authors: Wiggin Timothy D. , Goodwin Patricia R. , Donelson Nathan C. , Liu Chang , Trinh Kien , Sanyal Subhabrata , Griffith Leslie C.
Published: February 2018

Sleep pressure and sleep depth are key regulators of wake and sleep. Current methods of measuring these parameters inDrosophila melanogasterhave low temporal resolution and/or require disrupting sleep. Here we report a novel analysis tool for high-resolution, non-invasive measurement of sleep pressure and depth from movement data. Probability of transitioning to an active state, P(Wake), measures sleep depth while probability of transitioning to an inactive state, P(Doze), measures sleep pressure.In vivoand computational analyses show that P(Wake) and P(Doze) are independent and control the amount of total sleep. Importantly, we demonstrate that these probabilities are tied to specific biological processes. Genetic and environmental perturbations demonstrate that a given amount of sleep can be produced by many combinations of underlying P(Wake) and P(Doze). We show that measuring sleep pressure and depth continuously, without disturbing on-going behavior, provides greater mechanistic insight into behavior than measuring the amount of sleep alone.
Holmes-ITS2: Consolidated ITS2 resources and search engines for plant DNA-based marker analyses
Authors: Li Hongjun , Bai Hong , Yu Shaojun , Han Maozhen , Ning Kang
Published: February 2018

Plants are valuable resources for a variety of products in modern societies. Plant species identification is an integral part of research and practical application on plants. In parallel with high-throughput sequencing technology, the high-throughput screening of species is in high demand. Highly accurate and efficient DNA-based marker identification is essential for the effective analysis of plant species or biological constituents of a mixture of plants as well. Therefore, it is of general interests and significance to generate a comprehensive and accurate DNA-based marker sequence resource, as well as to build efficient sequence search engines, for the accurate and fast identification of plant species.

In this work, we have firstly established a high-quality ITS2 sequence database of plant species containing more than 150,000 entries, through the systematical collection and manually collation of the published ITS2 sequencing data of plant species, data quality control, as well as representative sequence refinement based on clustering method. Secondly, an accurate and efficient plant species identification system based on ITS2 sequence was constructed, which is the proper combination of sequence search algorithms including BLAST and Kraken. Through the deployment of high-performance and frequently updated web service, it’s expected to serve for a wide range of researchers involving the taxonomy classification of plant species, as well as for deciphering of plant mixed systems including herbal materials in TCM preparations.

The Holmes-ITS2 web service is freely accessible at:http://its2.tcm.microbioinformatics.org/. The input of this web service could be multiple sequences in a single fasta format, to search for matching ITS2 biomarker sequences already annotated in the database. This sequence-based search is based on two engines: BLAST, and k-mer based Kraken. Alternatively, users can directly search for species name for the corresponding ITS2 biomarker sequences. The web service has been put to the test by more than 50 experts from China, Denmark and US, and the average running time for the search ranges from 3-30 seconds for up to 100 sequences as a batch query.
Centrality and the shortest path approach on the human interactome
Authors: Rubanova Natalia , Morozova Nadya
Published: February 2018

A network is one of the most convenient way to represent interactions between biological entities in systems biology. A network of molecular interactions is a graph in which the vertices are biological component and the edges correspond to the interactions between them. Many notions and approaches for network analysis came to systems biology from the theory of graphs – a field of mathematics that study graphs. We focused on the study of the shortest path approach in this work. We investigated whether this approach yields valid molecular paths. To perform this, the shortest paths in the human interactome (derived from HPRD and HIPPIE databases) were found between all relevant combinations of proteins taken from eight well-studied highly conserved signaling pathways from the KEGG database (NF-kappa B, MAPK, Jak-STAT, mTOR, ErbB, Wnt, TGF-beta and the signaling part of the apoptotic process). Canonical paths were systematically compared with the shortest counterparts and centrality of vertices and paths in subnetworks induced by the shortest paths were analyzed. We found that the sets of the shortest paths contain the canonical counterparts only for very short canonical paths (length 2-3 interactions). We also found that high centrality vertices tend to belong to canonical counterparts, to less extent this can also be said about high centrality paths.
Mechanistic insight into the interactions of NAP1 with NDP52 and TAX1BP1 for the recruitment of TBK1
Authors: Fu Tao , Liu Jianping , Wang Yingli , Xie Xingqiao , Hu Shichen , Pan Lifeng
Published: February 2018

NDP52 and TAX1BP1, two SKICH domain-containing autophagy recetpors, play crucial roles in selective autophagy. The autophagic functions of NDP52 and TAX1BP1 are regulated by TBK1, which can indirectly associate with them through the adaptor protein NAP1. However, the molecular mechanism governing the interactions of NAP1 with NDP52 and TAX1BP1 as well as the effects induced by TBK1-mediated phosphorylation of NDP52 and TAX1BP1 remain elusive. Here, we reported the first atomic structures of the SKICH regions of NDP52 and TAX1BP1 in complex with NAP1, which not only uncover the mechanismtic basis underpinning the specific interactions of NAP1 with NDP52 and TAX1BP1, but also reveal the first binding mode of a SKICH domain. Moreover, we demonstrated that the phosphorylation of TAX1BP1 SKICH mediated by TBK1 may regulate the interaction between TAX1BP1 and NAP1. In all, our findings provide mechanistic insights into the NAP1-mediated recruitments of TBK1 to NDP52 and TAX1BP1, and are valuable for further understanding the functions of these proteins in selective autophagy.
Bacterial division FtsZ forms liquid condensates with nucleoid-associated Z-ring inhibitor SlmA
Authors: Monterroso Begoña , Zorrilla Silvia , Sobrinos-Sanguino Marta , Robles-Ramos Miguel A. , López-Álvarez Marina , Keating Christine D. , Rivas Germán
Published: February 2018

Macromolecular condensation resulting from biologically regulated liquid-liquid phase transitions is emerging as a mechanism to organize the intracellular space in eukaryotic systems, with broad implications in cell physiology and pathology. Here we show that FtsZ, central element of the division ring in most bacteria, forms condensates when in complex with SlmA, the protein preventing septal ring assembly nearby the chromosome in E. coli. The formation of condensates is promoted by crowding and enhanced by sequence-specific binding of SlmA to DNA. These structures are dynamic and FtsZ within them remains active for GTP-triggered fiber formation. Their location is sensitive to compartmentalization and to the presence of a membrane boundary in microfluidics-based cell mimetic systems, likely affecting their reactivity. We propose that reversible condensation may play a role in the modulation of FtsZ assembly and/or location by SlmA and, hence, in the regulation of ring stability, constituting a singular example of a prokaryotic nucleoprotein complex exhibiting this kind of phase transition.
Early mannitol-triggered changes in the Arabidopsis leaf (phospho)proteome
Authors: Nikonorova Natalia , Van den Broeck Lisa , Zhu Shanshuo , van de Cotte Brigitte , Dubois Marieke , Gevaert Kris , Inzé Dirk , Smet Ive De
Published: February 2018

Drought is one of the most detrimental environmental stresses to which plants are exposed. Especially mild drought is relevant to agriculture and significantly affects plant growth and development. In plant research, mannitol is often used to mimic drought stress and study the underlying responses. In growing leaf tissue of plants exposed to mannitol-induced stress, a highly-interconnected gene regulatory network is induced. However, early signaling and associated protein phosphorylation events that likely precede part of these transcriptional changes are largely unknown. Here, we performed a full proteome and phosphoproteome analysis on growing leaf tissue ofArabidopsisplants exposed to mild mannitol-induced stress and captured the fast (within the first half hour) events associated with this stress. Based on this in-depth data analysis, 167 and 172 differentially regulated proteins and phosphorylated sites were found back, respectively. Additionally, we identified H(+)-ATPASE 2 (AHA2) and CYSTEINE-RICH REPEAT SECRETORY PROTEIN 38 (CRRSP38) as novel regulators of shoot growth under osmotic stress.

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We captured early changes in theArabidopsisleaf proteome and phosphoproteome upon mild mannitol stress and identified AHA2 and CRRSP38 as novel regulators of shoot growth under osmotic stress
Anisotropy enhanced X-ray scattering from solvated transition metal complexes
Authors: Biasin Elisa , van Driel Tim B. , Levi Gianluca , Laursen Mads G. , Dohn Asmus O. , Moltke Asbjørn , Vester Peter , Hansen Frederik B. K. , Kjaer Kasper S. , Harlang Tobias , Hartsock Robert , Christensen Morten , Gaffney Kelly J. , Henriksen Niels E. , Møller Klaus B. , Haldrup Kristoffer , Nielsen Martin M.
Published: February 2018

Time-resolved X-ray scattering patterns from photoexcited molecules in solution are in many cases anisotropic at the ultrafast time scales accessible at X-ray free-electron lasers (XFELs). This anisotropy arises from the interaction of a linearly polarized UV–Vis pump laser pulse with the sample, which induces anisotropic structural changes that can be captured by femtosecond X-ray pulses. In this work, a method for quantitative analysis of the anisotropic scattering signal arising from an ensemble of molecules is described, and it is demonstrated how its use can enhance the structural sensitivity of the time-resolved X-ray scattering experiment. This method is applied on time-resolved X-ray scattering patterns measured upon photoexcitation of a solvated di-platinum complex at an XFEL, and the key parameters involved are explored. It is shown that a combined analysis of the anisotropic and isotropic difference scattering signals in this experiment allows a more precise determination of the main photoinduced structural change in the solute,i.e.the change in Pt—Pt bond length, and yields more information on the excitation channels than the analysis of the isotropic scattering only. Finally, it is discussed how the anisotropic transient response of the solvent can enable the determination of key experimental parameters such as the instrument response function.