bluuebunny/crossref_metadata_2025_split huggingface dataset:
Can the microbiome influence host evolutionary trajectories?
Authors: Henry Lucas P. , Bruijning Marjolein , Forsberg Simon K.G. , Ayroles Julien F. 
Published: July 2019

AbstractThe microbiome shapes many traits in hosts, but we still do not understand how it influences host evolution. To impact host evolution, the microbiome must be heritable and have phenotypic effects on the host. However, the complex inheritance and context-dependence of the microbiome challenges traditional models of organismal evolution. Here, we take a multifaceted approach to identify conditions in which the microbiome influences host evolutionary trajectories. We explore quantitative genetic models to highlight how microbial inheritance and phenotypic effects can modulate host evolutionary responses to selection. We synthesize the literature across diverse taxa to find common scenarios of microbiome driven host evolution. First, hosts may leverage locally adapted microbes, increasing survivorship in stressful environments. Second, microbial variation may increase host phenotypic variation, enabling exploration of novel fitness landscapes. We further illustrate these effects by performing a meta-analysis of artificial selection in Drosophila, finding that bacterial diversity also frequently responds to host selection. We conclude by outlining key avenues of research and experimental procedures to improve our understanding of the complex interplay between hosts and microbiomes. By synthesizing perspectives through multiple conceptual and analytical approaches, we show how microbiomes can influence the evolutionary trajectories of hosts.
Foot shock stress generates persistent widespread hypersensitivity and anhedonic behavior in an anxiety-prone strain of mice
Authors: Wu Pau Yen , Yang Xiaofang , Wright Douglas E. , Christianson Julie A. 
Published: July 2019

AbstractA significant subset of patients with urologic chronic pelvic pain syndrome (UCPPS) suffer from widespread, as well as pelvic, pain and experience mood-related disorders, including anxiety, depression, and panic disorder. Stress is a commonly-reported trigger for symptom onset and exacerbation within these patients. The link between stress and pain is thought to arise, in part, from the hypothalamic-pituitary-adrenal (HPA) axis, which regulates the response to stress and can influence the perception of pain. Previous studies have shown that stress exposure in anxiety-prone rats can induce both pelvic and widespread hypersensitivity. Here, we exposed female A/J mice, an anxiety-prone inbred murine strain, to 10 days of foot shock stress to determine stress-induced effects on sensitivity, anhedonia, and HPA axis regulation and output in. At 1- and 28-days post-foot shock, A/J mice displayed significantly increased bladder sensitivity and hind paw mechanical allodynia. They also displayed anhedonic behavior, measured as reduced nest building scores and a decrease in sucrose preference during the 10-day foot shock exposure. Serum corticosterone was significantly increased at 1-day post-foot shock and bladder mast cell degranulation rates were similarly high in both sham- and shock-exposed mice. Bladder cytokine and growth factor mRNA levels indicated a persistent shift toward a pro-inflammatory environment following foot shock exposure. Together, these data suggest that chronic stress exposure in an anxiety-prone mouse strain may provide a useful translational model for understanding mechanisms that contribute to widespreadness of pain and increased comorbidity in a subset of UCPPS patients.
Zero-shot neural decoding of visual categories without prior exemplars
Authors: O’Connell Thomas P. , Chun Marvin M. , Kreiman Gabriel 
Published: July 2019

AbstractDecoding information from neural responses in visual cortex demonstrates interpolation across repetitions or exemplars. Is it possible to decode novel categories from neural activity without any prior training on activity from those categories? We built zero-shot neural decoders by mapping responses from macaque inferior temporal cortex onto a deep neural network. The resulting models correctly interpreted responses to novel categories, even extrapolating from a single category.
Janggu - Deep learning for genomics
Authors: Kopp Wolfgang , Monti Remo , Tamburrini Annalaura , Ohler Uwe , Akalin Altuna 
Published: July 2019

AbstractMotivationIn recent years, numerous applications have demonstrated the potential of deep learning for an improved understanding of biological processes. However, most deep learning tools developed so far are designed to address a specific question on a fixed dataset and/or by a fixed model architecture. Adapting these models to integrate new datasets or to address different hypotheses can lead to considerable software engineering effort. To address this aspect we have built Janggu, a python library that facilitates deep learning for genomics applications.ResultsJanggu aims to ease data acquisition and model evaluation in multiple ways. Among its key features are special dataset objects, which form a unified and flexible data acquisition and pre-processing framework for genomics data that enables streamlining of future research applications through reusable components. Through a numpy-like interface, the dataset objects are directly compatible with popular deep learning libraries, including keras. Furthermore, Janggu offers the possibility to visualize predictions as genomic tracks or by exporting them to the BIGWIG format. We illustrate the functionality of Janggu on several deep learning genomics applications. First, we evaluate different model topologies for the task of predicting binding sites for the transcription factor JunD. Second, we demonstrate the framework on published models for predicting chromatin effects. Third, we show that promoter usage measured by CAGE can be predicted using DNase hyper-sensitivity, histone modifications and DNA sequence features. We improve the performance of these models due to a novel feature in Janggu that allows us to include high-order sequence features. We believe that Janggu will help to significantly reduce repetitive programming overhead for deep learning applications in genomics, while at the same time enabling computational biologists to assess biological hypotheses more rapidly.AvailabilityJanggu is freely available under a GPL-v3 license on https://github.com/BIMSBbioinfo/janggu or via https://pypi.org/project/janggu
Cryptic genetic variation underpins rapid adaptation to ocean acidification
Authors: Bitter M. C. , Kapsenberg L. , Gattuso J.-P. , Pfister C. A. 
Published: July 2019

AbstractGlobal climate change has intensified the need to assess the capacity for natural populations to adapt to abrupt shifts in the environment. Reductions in seawater pH constitute a conspicuous stressor associated with increasing atmospheric carbon dioxide that is affecting ecosystems throughout the world’s oceans. Here, we quantify the phenotypic and genetic modifications associated with rapid adaptation to reduced seawater pH in the marine mussel,Mytilus galloprovincialis. We reared a genetically diverse larval population in ambient and extreme low pH conditions (pHT8.1 and 7.4) and tracked changes in the larval size and allele frequency distributions through settlement. Additionally, we separated larvae by size to link a fitness-related trait to its underlying genetic background in each treatment. Both phenotypic and genetic data show thatM. galloprovincialiscan evolve in response to a decrease in seawater pH. This process is polygenic and characterized by genotype-environment interactions, suggesting the role of cryptic genetic variation in adaptation to future climate change. Holistically, this work provides insight into the processes underpinning rapid evolution, and demonstrates the importance of maintaining standing variation within natural populations to bolster species’ adaptive capacity as global change progresses.
A targeted multi-omic analysis approach measures protein expression and low abundance transcripts on the single cell level
Authors: Mair Florian , Erickson Jami R. , Voillet Valentin , Simoni Yannick , Bi Timothy , Tyznik Aaron J. , Martin Jody , Gottardo Raphael , Newell Evan W. , Prlic Martin 
Published: July 2019

SummaryHigh throughput single-cell RNA sequencing (sc-RNAseq) has become a frequently used tool to assess immune cell function and heterogeneity. Recently, the combined measurement of RNA and protein expression by sequencing was developed, which is commonly known as CITE-Seq. Acquisition of protein expression data along with transcriptome data resolves some of the limitations inherent to only assessing transcript, but also nearly doubles the sequencing read depth required per single cell. Furthermore, there is still a paucity of analysis tools to visualize combined transcript-protein datasets.Here, we describe a novel targeted transcriptomics approach that combines analysis of over 400 genes with simultaneous measurement of over 40 proteins on more than 25,000 cells. This targeted approach requires only about 1/10 of the read depth compared to a whole transcriptome approach while retaining high sensitivity for low abundance transcripts. To analyze these multi-omic transcript-protein datasets, we adapted One-SENSE for intuitive visualization of the relationship of proteins and transcripts on a single-cell level.
A nanobody that recognizes a 14-residue peptide epitope in the E2 ubiquitin-conjugating enzyme UBC6e modulates its activity
Authors: Ling Jingjing , Cheloha Ross W. , McCaul Nicholas , Sun Zhen-Yu J. , Wagner Gerhard , Ploegh Hidde L. 
Published: July 2019

ABSTRACTA substantial fraction of eukaryotic proteins is folded and modified in the endoplasmic reticulum (ER) prior to export and secretion. Proteins that enter the ER but fail to fold correctly must be degraded, mostly in a process termed ER-associated degradation (ERAD). Both protein folding in the ER and ERAD are essential for proper immune function. Several E2 and E3 enzymes localize to the ER and are essential for various aspects of ERAD, but their functions and regulation are incompletely understood. Here we identify and characterize single domain antibody fragments derived from the variable domain of alpaca heavy chain-only antibodies (VHHs or nanobodies) that bind to the ER-localized E2 UBC6e, an enzyme implicated in ERAD. One such VHH, VHH05 recognizes a 14 residue stretch and enhances the rate of E1-catalyzed ubiquitin E2 loading in vitro and interferes with phosphorylation of UBC6e in response to cell stress. Identification of the peptide epitope recognized by VHH05 places it outside the E2 catalytic core, close to the position of activation-induced phosphorylation on Ser184. Our data thus suggests a site involved in allosteric regulation of UBC6e’s activity. This VHH should be useful not only to dissect the participation of UBC6e in ERAD and in response to cell stress, but also as a high affinity epitope tag-specific reagent of more general utility.Highlights-Identified single domain antibodies (VHHs) that bind to UBC6e with high affinity-VHH binds to a short linear epitope near a phosphorylation site-VHH binding to UBC6e enhances enzymatic activity-VHH binding inhibits UBC6e phosphorylation in cells
Light-sheet engineering using the Field Synthesis theorem
Authors: Chang Bo-Jui , Fiolka Reto 
Published: July 2019

AbstractRecent advances in light-sheet microscopy have enabled sensitive imaging with high spatiotemporal resolution. However, the creation of thin light-sheets for high axial resolution is challenging, as the thickness of the sheet, field of view and confinement of the excitation need to be carefully balanced. Some of the thinnest light-sheets created so far have found little practical use as they excite too much out-of-focus fluorescence. In contrast, the most commonly used lightsheet for subcellular imaging, the square lattice, has excellent excitation confinement at the cost of lower axial resolving power. Here we leverage the recently discovered Field Synthesis theorem to create light-sheets where thickness and illumination confinement can be continuously tuned. Explicitly, we scan a line beam across a portion of an annulus mask on the back focal plane of the illumination objective, which we call it C-light-sheets. We experimentally characterize these light-sheets and their application on biological samples.
Too much, too young? Altered corticolimbic axonal innervation and resting state functional connectivity suggests sex-dependent outcomes in a rat model of early life adversity
Authors: Honeycutt Jennifer A. , Demaestri Camila , Peterzell Shayna , Silveri Marisa M. , Cai Xuezhu , Kulkarni Praveen , Cunningham Miles G. , Ferris Craig F. , Brenhouse Heather C. 
Published: July 2019

AbstractAdverse early experiences significantly alter behavioral and neural trajectories via aberrant brain maturation. Children with a history of early life stress (ELS) exhibit maladaptive behaviors and increased risk of mental illness later in life. Evidence in ELS-exposed humans identifies a role of atypical corticolimbic development; specifically, within amygdala-prefrontal cortex (PFC) circuits, and show precocially mature task-based corticolimbic functional connectivity (FC). However, the neurobiological substrates of such ELS-driven developmental changes remain unknown. Here, we identify putative neurobiological changes to determine the timeline of developmental perturbations following ELS in rats. Anterograde axonal tracing from basolateral amygdala (BLA) to pre- and infralimbic (PL, IL) PFC was quantified at postnatal days (PD)28, 38, and 48, along with anxiety-like behavior, in maternally separated (ELS) or control reared (CON) male and female rats. Resting state (rs)FC was assessed at PD28 and PD48 in a separate cohort. We report that ELS-exposed female rats show early maturation of BLA-PFC innervation at PD28, with ELS-related changes in males not appearing until PD38. ELS disrupted the maturation of rsFC from PD28 to PD48 in females, with enduring relationships between early rsFC and later anxiety-like behavior. Only transient ELS-related changes in rsFC were seen in male PL. Together, these data provide evidence that female rats may be more vulnerable to the effects of ELS via precocial BLA-PFC innervation, which may drive altered corticolimbic rsFC. These data also provide evidence that increased BLA-IL rsFC is associated with behavioral resiliency following ELS in female rats, providing mechanistic insight into the underlying etiology of adversity-induced vulnerability and resiliency.
Phenylacetyl-CoA, not phenylacetic acid, attenuates CepIR-regulated virulence inBurkholderia cenocepacia
Authors: Lightly Tasia Joy , Frejuk Kara L. , Groleau Marie-Christine , Chiarelli Laurent R. , Ras Cor , Buroni Silvia , Déziel Eric , Sorensen John L. , Cardona Silvia T. 
Published: July 2019

AbstractDuring phenylalanine catabolism, phenylacetic acid (PAA) is converted to phenylacetyl-CoA (PAA-CoA) by a ligase, PaaK, and then epoxidized by a multicomponent monooxygenase, PaaABCDE, before further degradation to the TCA cycle. In the opportunistic pathogenBurkholderia cenocepacia,loss ofpaaABCDEattenuates virulence factor expression, which is under control of the LuxIR-like quorum sensing system, CepIR. To further investigate the link between CepIR-regulated virulence and PAA catabolism, we created knockout mutants of the first step of the pathway (PAA-CoA synthesis by PaaK) and characterized them in comparison to apaaABCDEmutant using liquid chromatography/mass spectrometry (LC-MS/MS) and virulence assays. We found that while loss of PaaABCDE decreased virulence, deletion of thepaaKgenes resulted in a more virulent phenotype than the wild type strain. Deletion of eitherpaaKorpaaABCDEled to higher levels of released PAA but no differences in internal accumulation, compared to wild type. While we found no evidence of directcepIRdownregulation by PAA-CoA or PAA, a low virulencecepRmutant reverted to a virulent phenotype upon removal of thepaaKgenes. On the other hand, removal ofpaaABCDEin thecepRmutant did not impact its attenuated phenotype. Together, our results suggest an indirect role for PAA-CoA in supressingB. cenocepaciaCepIR-activated virulence.ImportanceThe opportunistic pathogenBurkholderia cenocepaciauses a chemical signal process called quorum sensing (QS) to produce virulence factors. InB. cenocepacia, QS relies on the presence of the transcriptional regulator CepR, which upon binding QS signal molecules, activates virulence. In this work, we found that even in the absence of CepR,B. cenocepaciacan elicit a pathogenic response if phenylacetyl-CoA, an intermediate of the phenylacetic acid degradation pathway, is not produced. Instead, accumulation of phenylacetyl-CoA appears to attenuate pathogenicity. Therefore, we have discovered that it is possible to trigger virulence in the absence of CepR, challenging the classical view of activation of virulence by this QS mechanism. Our work provides new insight into the relationship between metabolism and virulence in opportunistic bacteria. We propose that, in the event that QS signaling molecules cannot accumulate to trigger a pathogenic response, a metabolic signal can still activate virulence inB. cenocepacia.
The Creative Mind: Blending Oxytocinergic, Dopaminergic and Personality
Authors: Chong Anne , Becker Benjamin , Angeles Dario Cruz , Matos Maria Gutierrez , Yue Xiong , Lai Poh San , Cheung Mike , Lei Zhen , Malavasi Fabio , Chew Soo Hong , Ebstein Richard P. 
Published: July 2019

AbstractIn a fast-changing world, creative thinking (CT) is an extraordinary currency. Oxytocin (OT) is associated with CT and release of OT depends on ADP ribosyl-cyclases (CD38 and CD157). Moreover, CT as well as OT’s mechanism of action are mediated via central dopaminergic pathways. Consequently, we evaluate the roles of CD38, CD157, dopamine receptor D2 (DRD2) and catechol-O-methyltransferase (COMT) peripheral gene expression in CT. Two principal domains of CT, divergent thinking and insight solving problems, were assessed using validated behavioral assessments. To facilitate discriminant validity, two established correlates of CT, trait Openness and fluid intelligence as well as age and sex were included in the regression model. In women, significant main effects (p<0.01) were positively associated with the expression CD38, CD15, and their interaction CD38 x CD157 controlling for Openness, fluid intelligence and age. Subsequent analysis on the subscale-level revealed significant main effects for CD157 and CD38 x CD157 in men specifically for divergent thinking. In women, significant (p<0.01) results are also observed for dopaminergic expression (DRD2, COMT, DRD2 x COMT). The full model (oxytocinergic and dopaminergic gene expressions, Openness, and fluid intelligence) explains a sizable 39% of the variance in females. Significant main effects are observed for CD38, CD157, DRD2 and COMT as well as their interactions (CD38xCD157 and DRD2xCOMT). In conclusion, we show that oxytocinergic and dopaminergic gene expression contribute significantly to the complex CT phenotype suggesting the notion that the perspective gained from examining the peripheral transcriptome meaningfully adds to understanding the landscape of creative thinking.Significance StatementCreative thinking (CT) is a powerful driving force galvanizing progress and civilization. Towards better understanding the neurobiology of CT, we implement a gene expression strategy that is considered to capture not only genomic elements but also environmental signatures. We employ laboratory measures of CT (alternative uses test and insight problem solving), controlling for fluid intelligence and the personality trait of Openness. We focus on oxytocinergic and dopaminergic genes that contribute to the molecular architecture of CT. Oxytocinergic and dopaminergic gene expression significantly explains a robust 39% of the variance in CT. Notably, this study demonstrates the potential of the peripheral transcriptome towards tracing gene pathways underlying some complex cognitive behaviors such as creative thinking.
Detecting task-dependent modulation of spatiotemporal module via tensor decomposition: application to kinematics and EMG data for walking and running at various speed
Authors: Takiyama Ken , Yokoyama Hikaru , Kaneko Naotsugu , Nakazawa Kimitaka 
Published: July 2019

AbstractHow the central nervous system (CNS) controls many joints and muscles is a fundamental question in motor neuroscience and related research areas. An attractive hypothesis is the module hypothesis: the CNS controls groups of joints or muscles (i.e., spatial modules) while providing time-varying motor commands (i.e., temporal modules) to the spatial modules rather than controlling each joint or muscle separately. Another fundamental question is how the CNS generates numerous repertories of movement patterns. One hypothesis is that the CNS modulates the spatial and/or temporal modules depending on the required tasks. It is thus essential to quantify the spatial module, the temporal module, and the task-dependent modulation of those modules. Although previous methods attempted to quantify these aspects, they considered the modulation in only the spatial or temporal module. These limitations were possibly due to the constraints inherent to conventional methods for quantifying the spatial and temporal modules. Here, we demonstrate the effectiveness of tensor decomposition in quantifying the spatial module, the temporal module, and the task-dependent modulation of these modules without such limitations. We further demonstrate that the tensor decomposition provides a new perspective on the task-dependent modulation of spatiotemporal modules: in switching from walking to running, the CNS modulates the peak timing in the temporal module while recruiting proximal muscles in the corresponding spatial module.Author summaryThere are at least two fundamental questions in motor neuroscience and related research areas: 1) how does the central nervous system (CNS) control many joints and muscles and 2) how does the CNS generate numerous repertories of movement patterns. One possible answer to question 1) is that the CNS controls groups of joints or muscles (i.e., spatial modules) while providing time-varying motor commands (i.e., temporal modules) to the spatial modules rather than controlling each joint or muscle separately. One possible answer to question 2) is that the CNS modulates the spatial and/or temporal module depending on the required tasks. It is thus essential to quantify the spatial module, the temporal module, and the task-dependent modulation of those modules. Here, we demonstrate the effectiveness of tensor decomposition in quantifying the modules and those task-dependent modulations while overcoming the shortcomings inherent to previous methods. We further show that the tensor decomposition provides a new perspective on how the CNS switches between walking and running. The CNS modulated the peak timing in the temporal module while recruiting proximal muscles in the corresponding spatial module.