bluuebunny/crossref_metadata_2025_split huggingface dataset:
Incipient local adaptation in a fungus: evolution of heavy metal tolerance through allelic and copy-number variation
Authors: Bazzicalupo Anna L. , Ruytinx Joske , Ke Yi-Hong , Coninx Laura , Colpaert Jan V. , Nguyen Nhu H. , Vilgalys Rytas , Branco Sara 
Published: November 2019

AbstractHuman-altered environments can shape the evolution of organisms. Fungi are no exception, though little is known about how they withstand anthropogenic pollution. Here, we document incipient polygenic local adaptation in the mycorrhizal fungus Suillus luteus driven by recent soil heavy metal contamination. Genome scans across individuals from recently polluted and nearby unpolluted soils in Belgium revealed no evidence of population structure but detected allelic divergence and gene copy number variation in genes involved in metal exclusion, storage, immobilization, and reactive oxygen species detoxification. Standing genetic variation included multiple alleles of small effects contributing to heavy metal tolerance, suggesting the existence of different strategies to withstand contamination. These variants were shared across the whole population but under selection in isolates exposed to pollution. Together, our results point to S. luteus undergoing the initial steps of adaptive divergence and contribute to understanding the processes underlying local adaptation under strong environmental selection.
Detecting (un)seen change: The neural underpinnings of (un)conscious prediction errors
Authors: Rowe Elise G. , Tsuchiya Naotsugu , Garrido Marta I. 
Published: November 2019

ABSTRACTDetecting changes in the environment is fundamental for our survival. According to predictive coding theory, detecting these irregularities relies both on incoming sensory information and our top-down prior expectations (or internal generative models) about the world. Prediction errors (PEs), detectable in event-related potentials (ERPs), occur when there is a mismatch between the sensory input and our internal model (i.e., a surprise event). Many changes occurring in our environment are irrelevant for survival and may remain unseen. Such changes, even if subtle, can nevertheless be detected by the brain without emerging into consciousness. What remains unclear is how these changes are processed in the brain at the network level. Here, we used a visual oddball paradigm, in which participants engaged in a central letter task during electroencephalographic (EEG) recordings while presented with task-irrelevant high- or low-coherence background, random-dot motion. Critically, once in a while, the direction of the dots changed. After the EEG session, we confirmed that changes in motion direction at high- and low-coherence were visible and invisible, respectively, using psychophysical measurements. ERP analyses revealed that changes in motion direction elicited PE regardless of the visibility, but with distinct spatiotemporal patterns. To understand these responses, we applied Dynamic Causal Modelling (DCM) to the EEG data. Bayesian Model Averaging showed visible PE relied on a release from adaptation (repetition suppression) within bilateral MT+, whereas invisible PE relied on adaptation at bilateral V1 (and left MT+). Furthermore, while feedforward upregulation was present for invisible PE, the visible change PE also included downregulation of feedback between right MT+ to V1. Our findings reveal a complex interplay of modulation in the generative network models underlying visible and invisible motion changes.
Multi-sensory integration in the mouse cortical connectome using a network diffusion model
Authors: Shadi Kamal , Dyer Eva , Dovrolis Constantine 
Published: November 2019

AbstractHaving a structural network representation of connectivity in the brain is instrumental in analyzing communication dynamics and information processing in the brain. In this work, we make steps towards understanding multi-sensory information flow and integration using a network diffusion approach. In particular, we model the flow of evoked activity, initiated by stimuli at primary sensory regions, using theAsynchronous Linear Threshold (ALT) diffusion model. The ALT model captures how evoked activity that originates at a given region of the cortex “ripples through” other brain regions (referred to as anactivation cascade). By comparing the model results to functional datasets based on Voltage Sensitive Dye (VSD) imaging, we find that in most cases the ALT model predicts the temporal ordering of an activation cascade correctly. Our results on the Mouse Connectivity Atlas from the Allen Institute for Brain Science show that a small number of brain regions are involved in many primary sensory streams – the claustrum and the parietal temporal cortex being at the top of the list. This suggests that the cortex relies on anhourglass architectureto first integrate and compress multi-sensory information from multiple sensory regions, before utilizing that lower-dimensionality representation in higher-level association regions and more complex cognitive tasks.
Sustained Activation of PV+ Interneurons in Core Auditory Cortex Enables Robust Divisive Gain Control for Complex and Naturalistic Stimuli
Authors: Gothner Tina , Gonçalves Pedro J. , Sahani Maneesh , Linden Jennifer F. , Hildebrandt K. Jannis 
Published: November 2019

ABSTRACTSensory cortices must flexibly adapt their operations to internal states and external requirements. Modulation of specific inhibitory interneurons may provide a network-level mechanism for adjustments on behaviourally relevant timescales. Understanding of the computational roles of such modulation has mostly been restricted to phasic optogenetic activation and short, transient stimuli. Here, we aimed to extend the understanding of modulation of cortical inhibition by using sustained, network-wide optogenetic activation of parvalbumin-positive interneurons in core auditory cortex to study modulation of responses to transient, sustained, and naturalistic stimuli. We found highly conserved spectral and temporal tuning, despite profoundly reduced overall network activity. This reduction was predominantly divisive, and consistent across simple, complex, and naturalistic stimuli. A recurrent network model with power-law input-output functions replicated our results. We conclude that modulation of parvalbumin-positive interneurons on timescales typical of more sustained neuromodulation may provide a means for robust divisive gain control conserving stimulus representations.
The hair cycle underlies regulation of Langerhans cell renewal
Authors: Voisin Benjamin , Chartoire Dimitri , Devouassoux Caroline , Kowalczyk-Quintas Christine , Clauss François , Lezot Frédéric , Schneider Pascal , Flacher Vincent , Mueller Christopher G. 
Published: November 2019

ABSTRACTIn the epidermis, Langerhans cells (LCs) provide an essential link between the innate and adaptive immune systems. They self-renew in situ and continuously transport antigen from skin to lymph node (LN) T cells in the steady state. The cyclic renewal of hair follicles (HF) causes profound alterations in the cutaneous microenvironment, however little is known about its impact on LC homeostasis. Here we show that mouse LCs developed normally in the absence of hair but perceived critical transition periods in the hair cycle. LCs underwent a proliferation burst during the HF growth phase (anagen). Reinitiation or abolishment of anagen as well as loss of the HF had direct consequences on LC self-renewal. Because dividing LCs were found close to the anagen HF, we searched for the proliferative signal within this structure and identified increased Il34 expression by HF stem cells and their progeny. Inhibition of the IL-34 receptor CSF-1R at the onset of anagen completely and specifically blocked LC proliferation. Altogether, our findings demonstrate that the hair cycle directly oversees LC self-renewal and migration.
Ecological divergence of DNA methylation patterns at distinct spatial scales
Authors: De Kort H. , Panis B. , Deforce D. , Van Nieuwerburgh F. , Honnay O. 
Published: November 2019

ABSTRACTAdaptive trait divergence between populations is regulated by genetic and non-genetic processes. Compared to genetic change, epigenetic change is unstable and short-lived, questioning its contribution to long-term adaptive potential. However, epigenetic change can accumulate over time, and may result in beneficial epigenetic memories where environments are heterogeneous. Diverging epigenetic memories have been observed across large spatial scales, and can persist through multiple generations even in the absence of the causative environmental stressor. It is unknown, however, how and to what extent epigenetic memories contribute to fine-scale population structure and evolution. Here, we performed whole genome bisulfite sequencing on 30 Fragaria vesca F1 plants originating from distinct ecological settings and grown in a controlled environment. Specifically, we compared methylation patterns between a steep, altitudinal gradient (<2 km) and a wide spatial gradient (>500 km). If epigenetic variation is random, arising from errors during replication and without evolutionary implications, one would expect similar amounts of epigenetic variation across populations and no spatial scale-effect. Here, we find that epigenetic memories arise even at fine spatial scale, and that both parallel and non-parallel biological processes underpin epigenetic divergence at distinct spatial scales. For example, demethylation of transposable elements consistently occurred at the large but not the small spatial scale, while methylation differentiation for most biological processes were shared between spatial scales. Acute drought stress did not result in significant epigenetic differentiation, indicating that repeated historical stress levels associated with heterogeneous environmental conditions are required for acquiring a stable epigenetic memory and for coping with future environmental change.
Impaired phagocytic function in CX3CR1+ tissue-resident skeletal muscle macrophages prevents muscle recovery after influenza A virus-induced pneumonia in aged mice
Authors: Runyan Constance E. , Welch Lynn C. , Lecuona Emilia , Shigemura Masahiko , Amarelle Luciano , Abdala-Valencia Hiam , Joshi Nikita , Lu Ziyan , Nam Kiwon , Markov Nikolay S. , McQuattie-Pimentel Alexandra C. , Piseaux-Aillon Raul , Politanska Yuliya , Sichizya Lango , Watanabe Satoshi , Williams Kinola J.N. , Budinger GR Scott , Sznajder Jacob I. , Misharin Alexander V. 
Published: November 2019

ABSTRACTSkeletal muscle dysfunction in survivors of pneumonia is a major cause of lasting morbidity that disproportionately affects older individuals. We found that skeletal muscle recovery was impaired in aged compared with young mice after influenza A virus-induced pneumonia. In young mice, recovery of muscle loss was associated with expansion of tissue-resident skeletal muscle macrophages and downregulation of MHC II expression, followed by a proliferation of muscle satellite cells. These findings were absent in aged mice and in mice deficient in Cx3cr1. Transcriptomic profiling of tissue-resident skeletal muscle macrophages from aged compared with young mice showed downregulation of pathways associated with phagocytosis and proteostasis, and persistent upregulation of inflammatory pathways. Consistently, skeletal muscle macrophages from aged mice failed to downregulate MHCII expression during recovery from influenza A virus induced pneumonia and showed impaired phagocytic function in vitro. Like aged animals, mice deficient in the phagocytic receptor Mertk showed no macrophage expansion, MHCII downregulation or satellite cell proliferation and failed to recover skeletal muscle function after influenza A pneumonia. Our data suggest that a loss of phagocytic function in a CX3CR1+ tissue-resident skeletal muscle macrophage population in aged mice precludes satellite cell proliferation and recovery of skeletal muscle function after influenza A pneumonia.
Estradiol-induced progesterone synthesis develops post-puberty in the rostral hypothalamus and coincides with post-pubertal changes in the steroidogenic pathway in female mouse hypothalamic astrocytes
Authors: Mohr M.A. , Keshishian T. , Falcy B.A. , Laham B.J. , Wong AM , Micevych P.E 
Published: November 2019

ABSTRACTThe development of estrogen positive feedback is a hallmark of female puberty. Both estrogen and progesterone signaling are required for the functioning of this neuroendocrine feedback loop but the physiological changes that underlie the emergence of positive feedback remain unknown. Only after puberty does estradiol (E2) facilitate progesterone synthesis in the rat female hypothalamus (neuroP), an event critical for positive feedback and the LH surge. We hypothesize that prior to puberty, these astrocytes have low levels of membrane estrogen receptor alpha (ERα), which is needed for facilitation of neuroP synthesis. Thus, we hypothesized that prepubertal astrocytes are unable to respond to E2 with increased neuroP synthesis due a lack of membrane ERα. To test this, hypothalamic tissues and enriched primary hypothalamic astrocyte cultures were acquired from pre-pubertal (postnatal week 3) and post- pubertal (week 8) female mice. E2-facilitated progesterone was measured in the hypothalamus pre- and post-puberty, and hypothalamic astrocyte responses were measured after treatment with E2. Prior to puberty, E2-facilitated progesterone synthesis did not occur in the hypothalamus, and mERα expression was low in hypothalamic astrocytes, but E2-facilitated progesterone synthesis in the rostral hypothalamus and mERα expression increased post- puberty. The increase in mERα expression in hypothalamic astrocytes corresponded with an increase in caveolin-1 protein, PKA phosphorylation, and a more rapid [Ca2+]i flux in response to E2. Together, results from the present study indicate that E2-facilitated neuroP synthesis occurs in the rostral hypothalamus, develops during puberty, and corresponds to a post-pubertal increase in mERα levels in hypothalamic astrocytes.SIGNIFICANCE STATEMENTEstradiol facilitation of hypothalamic neuroprogesterone synthesis is necessary for the positive feedback of the LH surge. The present study localized the increase of neuroprogesterone to the rostral hypothalamus, a region that mediates estrogen positive feedback. Across pubertal development, hypothalamic astrocytes increase levels of membrane ERα and the cell signaling responses needed to facilitate neuroprogesterone synthesis that triggers the LH surge demonstrating a mechanism for pubertal maturation resulting in reproductive competence.
Facultative social exploitation amongMyxoccocusbacteria due to non-responsive local competition
Authors: smith jeff , Velicer Gregory J. 
Published: November 2019

AbstractMicrobes cooperate in many ways, but it is unclear to what extent they also have adaptations to detect and exploit unrelated social partners. Experimental data often cannot discriminate between social exploitation caused by complex adaptive traits and exploitation caused by simple deleterious mutations. Here we demonstrate facultative social exploitation amongMyxococcusbacteria due to simple non-responsive local competition. We show that the time dynamics of developmental exploitation by a tan phase variant are consistent with a model where cells do not respond to the presence of other genotypes but simply compete for some shared resource necessary to produce spores. The model also predicts the frequency-dependent responses of strains to genetic chimerism in multicellular fruiting bodies. Interactions between naturally occuring soil isolates, on the other hand, are consistent with strong interference competition where the winner almost completely prevents the loser from producing any spores. These results show how facultative social exploitation does not require elaborate mechanisms to detect and respond to foreign genotypes but can instead be caused by simple competition acting on a local scale.Myxococcuscells, like social insects, cooperate in some ways while simultaneously competing in others.
Resolving intrinsic ambiguities of the fMRI signal in the human brain
Authors: Liu Eulanca Y. , Haist Frank , Shin David , Buxton Richard B. 
Published: November 2019

AbstractFunctional magnetic resonance imaging (fMRI) using the blood oxygenation level dependent (BOLD) signal is a standard tool in human neuroscience studies. However, the BOLD signal is physiologically complex, depending on the baseline state of the brain and the balance of changes in blood flow and oxygen metabolism in response to a change in neural activity. Interpretation of the magnitude of the BOLD response is thus problematic; specifically, group differences of the BOLD response to a standard task or stimulus, or a change after administration of a drug, could be due to a change in the neural response, neurovascular coupling, or the baseline state. While changes in oxygen metabolism can serve as a biomarker of neural activity change, reflecting the energy cost of activity, oxygen metabolism cannot be estimated from BOLD measurements alone. Here we used the effects of caffeine as a test case to show that a suite of additional noninvasive measurements, requiring no manipulation of inhaled gases, makes it possible to untangle the underlying effects of caffeine on blood flow and oxygen metabolism. After caffeine administration, the BOLD response to a standard motor task was reduced, but oxygen metabolism was not reduced; rather, caffeine reduced the balance of blood flow relative to oxygen metabolism, both in the baseline state and in response to the task. The MRI methods used required only an additional 12 minutes of scanning, can be implemented on any MRI system, and painted a more complete picture of the physiological effects of caffeine. In addition to the assessment of drug effects in the human brain, these methods make it possible to resolve ambiguities of the BOLD signal in studies of development, aging, and disease. (Duplicated from first paragraph of manuscript)
Microbial community structure and ecology in sediments of a pristine mangrove forest
Authors: Santana C.O. , Spealman P. , Melo V.M.M , Gresham D. , Jesus T.B. , Chinalia F.A. 
Published: November 2019

ABSTRACTMangrove forests are coastal intertidal ecosystems, characterized by mangrove trees growing in slow moving saline waters, that constitute a large portion of the coastline in the tropical and subtropical regions. The dynamic water regime created by the tides results in different microhabitats in which microbial communities play an essential role in the functioning and maintenance of the mangrove ecosystem. However, little is known about the diversity of taxa within these micro-habitats and their functional roles, as only a small fraction of these organisms can be cultured in the laboratory. In this study, we characterized the microbial community present in three distinct regions of mangrove sediments from the Serinhaém estuary, part of the Atlantic Forest biome within the Environmental Protection Area of Pratigi. We sampled sediments from regions below the tidal waterline (submerged), intertidal regions (intertidal), and regions above the tidal waterline (seco). More than 85% of all the sequences in the samples belonged to 6 of 42 identified phyla:Proteobacteria(30.6%),Firmicutes(30%),Chloroflexi(8.7%),Planctomycetes(5.7%),Crenarchaeota(5.4%) andActinobacteria(5.3%). Diversity indices show that the submerged regions of the mangrove forest exhibit the greatest diversity and richness relative to the other regions. Notably, the intertidal region has the least diversity, suggesting that the dynamics of environmental variables in this region has an important influence on microbial diversity. Furthermore, distance metrics indicate that submerged sediments are more homogeneous while the seco region exhibits greater variability between locations. Finally, we found that the most abundant microbial families in the sediments are associated with nutrient cycling consistent with the essential role of the microbiome in maintaining the health of the mangrove ecology.
Analysis of polyclonal vector integration sites using Nanopore sequencing as a scalable, cost-effective platform
Authors: Zhang Ping , Ganesamoorthy Devika , Nguyen Son Hoang , Au Raymond , Coin Lachlan J. , Tey Siok-Keen 
Published: November 2019

AbstractVector integration site analysis can be important in the follow-up of patients who received gene-modified cells, but current platforms based on next-generation sequencing are expensive and relatively inaccessible. We analyzed polyclonal T cells transduced by a gammaretroviral vector, SFG.iCasp9.2A.ΔCD19, from a clinical trial. Following restriction enzyme digestion, the unknown flanking genomic sequences were amplified by inverse polymerase chain reaction (PCR) or cassette ligation PCR. Nanopore sequencing could identify thousands of unique integration sites within polyclonal samples, with cassette ligation PCR showing less bias. The assay is scalable and requires minimum capital, which together enable cost-effective and timely analysis.
Genetic Genealogical Methods Used to Identify African American Diaspora Relatives in the Study of Family Identity among Ghanaian Members of the Kassena Ethnic Group
Authors: David LaKisha Tawanda , Jones Leia 
Published: November 2019

AbstractWithin the phenomenon of families that were separated during the Transatlantic Slave Trade reuniting using genetic genealogy, the methods for identifying ancestral extended relatives has not been explicitly agreed upon within social sciences. Our manuscript is a methodological paper that illustrates the use of autosomal genetic genealogy to identify ancestral extended relatives within the GEDmatch database. We used a sample of nine parent-offspring dyads residing in Ghana along with AncestryDNA, GEDmatch, family-based phasing, and identical by descent (IBD) segment sharing to identify African American ancestral extended relatives of our Ghanaian participants. This method supports the claim that families that were separated during the Transatlantic Slave Trade are reuniting.
Learning the properties of adaptive regions with functional data analysis
Authors: Mughal Mehreen R. , Koch Hillary , Huang Jinguo , Chiaromonte Francesca , DeGiorgio Michael 
Published: November 2019

AbstractIdentifying regions of positive selection in genomic data remains a challenge in population genetics. Most current approaches rely on comparing values of summary statistics calculated in windows. We present an approach termed SURFDAWave, which translates measures of genetic diversity calculated in genomic windows to functional data. By transforming our discrete data points to be outputs of continuous functions defined over genomic space, we are able to learn the features of these functions that signify selection. This enables us to confidently identify complex modes of natural selection, including adaptive introgression. We are also able to predict important selection parameters that are responsible for shaping the inferred selection events. By applying our model to human population-genomic data, we recapitulate previously identified regions of selective sweeps, such as OCA2 in Europeans, and predict that its beneficial mutation reached a frequency of 0.02 before it swept 1,802 generations ago, a time when humans were relatively new to Europe. In addition, we identify BNC2 in Europeans as a target of adaptive introgression, and predict that it harbors a beneficial mutation that arose in an archaic human population that split from modern humans within the hypothesized modern human-Neanderthal divergence range.