bluuebunny/crossref_metadata_2025 huggingface dataset:
Macrosystem community change in lake phytoplankton and its implications for diversity and function
Authors: Weigel Benjamin , Kotamäki Niina , Malve Olli , Vuorio Kristiina , Ovaskainen Otso
Published: March 2022

The combined effects of eutrophication, land-use and climate change are major threats to aquatic ecosystems, their biodiversity and integrity in sustaining ecosystem functions. Disentangling the mechanisms by which environmental change contributes to community assembly processes and species niches remains challenging, especially at macro-ecological scales. Here, we collated phytoplankton community data including 853 lakes along a 1200km latitudinal gradient, monitored over four decades, to quantify the spatio-temporal and scale-dependent environmental impacts on species niches and assembly processes while accounting for species traits and phylogenetic constraints. Our results demonstrate the emergence of novel and widespread community composition clusters in previously more uniform communities. While total species richness remained relatively stable, changes in community weighted mean traits of the clusters indicate functional differences. A robust phylogenetic signal of species responses to the environment indicates strong niche conservatism and low taxonomic dispersion. Our findings imply profound spatio-temporal structuring of species co-occurrence patterns and highlight emerging functional differences of lake phytoplankton communities to environmental change over space and time.
The network makeup artist (NORMA-2.0): Distinguishing annotated groups in a network using innovative layout strategies
Authors: Karatzas Evangelos , Koutrouli Mikaela , Baltoumas Fotis , Papanikolopoulou Katerina , Bouyioukos Costas , Pavlopoulos Georgios A.
Published: March 2022

Motivation

Network biology is a dominant player in today’s multi-omics era. Therefore, the need for visualization tools which can efficiently cope with intra-network heterogeneity emerges.

Results

NORMA-2.0 is a web application which uses efficient layouts to group together areas of interest in a network. In this version, NORMA-2.0 utilizes three different strategies to make such groupings as distinct as possible while it preserves all of the properties from its first version where one can handle multiple networks and annotation files simultaneously.

Availability

The web resource is available at http://norma.pavlopouloslab.info/

The source code is freely available at https://github.com/PavlopoulosLab/NORMA

Contact

pavlopoulos@fleming.gr
Robust Inference of Bi-Directional Causal Relationships in Presence of Correlated Pleiotropy with GWAS Summary Data
Authors: Xue Haoran , Pan Wei
Published: March 2022

To infer a causal relationship between two traits, several correlation-based causal direction (CD) methods have been proposed with the use of SNPs as instrumental variables (IVs) based on GWAS summary data for the two traits; however, none of the existing CD methods can deal with SNPs with correlated pleiotropy. Alternatively, reciprocal Mendelian randomization (MR) can be applied, which however may perform poorly in the presence of (unknown) invalid IVs, especially for bi-directional causal relationships. In this paper, first, we propose a CD method that performs better than existing methods regardless of the presence of correlated pleiotropy. Second, along with a simple but yet effective IV screening rule, we propose applying a closely related and state-of-the-art MR method in reciprocal MR, showing its almost identical performance to that of the new CD method when their model assumptions hold; however, if the modeling assumptions are violated, the new CD method is expected to better control type I errors. Notably bi-directional causal relationships impose some unique challenges beyond those for uni-directional ones, and thus requiring special treatments. For example, we point out for the first time several scenarios where a bi-directional relationship, but not a uni-directional one, can unexpectedly cause the violation of some weak modeling assumptions commonly required by many robust MR methods. Finally we applied the proposed methods to 12 risk factors and 4 common diseases, confirming mostly well-known uni-directional causal relationships, while identifying some novel and plausible bi-directional ones such as between BMI and T2D, and between BMI and CAD.
Bumblebees navigate using path integration while walking
Authors: Patel Rickesh N. , Kempenaers Julian , Heinze Stanley
Published: March 2022

Path integration is a computational strategy that allows an animal to maintain an internal estimate of its position relative to a point of origin. Many species use path integration to navigate back to specific locations, typically their homes, after lengthy and convoluted excursions. Hymenopteran insects are impressive path integrators, directly returning to their hives after hundreds of meters of outward travel. Recent neurobiological insights have established hypotheses for how path integration may be mediated by the brains of bees, but clear ways to test these hypotheses in the laboratory are currently unavailable. Here we report that the bumblebee, Bombus terrestris, uses path integration while walking over short distances in an indoor arena. They estimate accurate vector distances after displacement and orient by artificial celestial cues. Walking bumblebees also exhibited systematic search patterns when home vectors failed to lead them accurately back to the nest, closely resembling searches performed by other species in natural conditions. We thus provide a robust experimental system to test navigation behavior in the laboratory that reflects most aspects of natural path integration. Importantly, we established this assay in an animal that is both readily available and resilient to invasive manipulations. In the future, our behavioral assay therefore can be combined with current electrophysiological techniques, opening a path towards directly probing the neural basis of the sophisticated vector navigation abilities of bees.
Cellular and clinical impact of Protein Phosphatase Enzyme epigenetic silencing in multiple cancer tissues
Authors: Joshi Ricky S. , Esteller Manel
Published: March 2022

Protein Phosphatase Enzymes (PPE) and protein kinases simultaneously control phosphorylation mechanisms that tightly regulate intracellular signaling pathways and stimulate cellular responses. In human malignancies, PPE and protein kinases are frequently mutated resulting in uncontrolled kinase activity and PPE suppression, leading to cell proliferation, migration and resistance to anti-cancer therapies. Cancer associated DNA hypermethylation at PPE promoters gives rise to transcriptional silencing (epimutations) and is a hallmark of cancer. Despite recent advances in sequencing technologies, data availability and computational capabilities, only a fraction of PPE have been reported as transcriptionally inactive as a consequence of epimutations. Using the Infinium HumanMethylation450 BeadChip, we compared DNA methylation profiles from 705 cancer patients across 5 major tissues and 3 cancer cell models against a cohort of healthy controls. Here, we report epimutations in PPE (and their interacting proteins or PPEIP) are a frequent occurrence in the cancer genome and manifest independent of transcriptional activity. We observed that different tumors have varying susceptibility to epimutations and identify specific cellular signalling networks that are primarily affected by epimutations. Additionally, RNA-seq analysis showed the negative impact of epimutations on most (not all) Protein Tyrosine Phosphatase transcription. Finally, we detected novel clinical biomarkers that inform on patient mortality and anti-cancer treatment sensitivity. We propose that DNA hypermethylation marks at PPEIP frequently contribute to the pathogenesis of malignancies and within the precision medicine space, hold promise as biomarkers to inform on clinical features such as patient survival and therapeutic response.
Broadly neutralizing anti-S2 antibodies protect against all three human betacoronaviruses that cause severe disease
Authors: Zhou Panpan , Song Ge , He Wan-ting , Beutler Nathan , Tse Longping V. , Martinez David R. , Schäfer Alexandra , Anzanello Fabio , Yong Peter , Peng Linghang , Dueker Katharina , Musharrafieh Rami , Callaghan Sean , Capozzola Tazio , Yuan Meng , Liu Hejun , Limbo Oliver , Parren Mara , Garcia Elijah , Rawlings Stephen A. , Smith Davey M. , Nemazee David , Jardine Joseph G. , Wilson Ian A. , Safonova Yana , Rogers Thomas F. , Baric Ralph S. , Gralinski Lisa E. , Burton Dennis R. , Andrabi Raiees
Published: March 2022

Pan-betacoronavirus neutralizing antibodies may hold the key to developing broadly protective vaccines against coronaviruses that cause severe disease, for anticipating novel pandemic-causing viruses, and to respond more effectively to SARS-CoV-2 variants. The emergence of the Omicron variant of SARS-CoV-2 has illustrated the limitations of solely targeting the receptor binding domain (RBD) of the envelope Spike (S)-protein. Here, we isolated a large panel of broadly neutralizing antibodies (bnAbs) from SARS-CoV-2 recovered-vaccinated donors that target a conserved S2 region in the fusion machinery on betacoronavirus spikes. Select bnAbs show broadin vivoprotection against all three pathogenic betacoronaviruses, SARS-CoV-1, SARS-CoV-2 and MERS-CoV, that have spilled over into humans in the past 20 years to cause severe disease. The bnAbs provide new opportunities for antibody-based interventions and key insights for developing pan-betacoronavirus vaccines.
Improved mammalian retromer cryo-EM structures reveal a new assembly interface
Authors: Kendall Amy K. , Chandra Mintu , Xie Boyang , Wan William , Jackson Lauren P.
Published: March 2022

Retromer (VPS26/VPS35/VPS29 subunits) assembles with multiple sorting nexin (SNX) proteins on membranes to mediate endosomal recycling of transmembrane protein cargoes. Retromer has been implicated in other cellular events, including mitochondrial homeostasis, nutrient sensing, autophagy, and fission events. Mechanisms for mammalian retromer assembly remain undefined, and retromer engages multiple sorting nexin proteins to sort cargoes to different destinations. Published structures demonstrate mammalian retromer forms oligomers in vitro, but several structures were poorly resolved. We report here improved retromer oligomer structures using single particle cryo-electron microscopy (cryo-EM) by combining data collected from tilted specimens with multiple improvements in data processing, including using a three-dimensional (3D) starting model for improved automated particle picking in RELION. A retromer mutant (3KE retromer) that breaks VPS35-mediated interfaces was used to determine a structure of a new assembly interface formed by the VPS26A and VPS35 N-termini. The interface reveals how an N-terminal VPS26A arrestin saddle can link retromer chains by engaging a neighboring VPS35 N-terminus, on the opposite side from the well-characterized C-VPS26/N-VPS35 interaction observed within heterotrimers. The new interaction interface exhibits substantial buried surface area (∼7,000 Å2) and further suggests metazoan retromer may serve as an adaptable scaffold.
Effect of repeated explicit instructions on visuomotor adaptation and intermanual transfer
Authors: Werner Susen , Strüder Heiko K.
Published: March 2022

The aim of the present study was to investigate the effect of repeated explicit instructions on visuomotor adaptation, awareness, and intermanual transfer. In a comprehensive study design, 48 participants performed center-out reaching movements before and during exposure to a 60° rotation of visual feedback. Awareness and intermanual transfer were then determined. Twelve participants each were assigned to one of the following adaptation conditions: gradual adaptation, sudden adaptation without instructions, sudden adaptation with a single instruction before adaptation, and sudden adaptation with multiple instructions before and during adaptation. The explicit instructions explained the nature of the visual feedback perturbation and were given using an illustration of a clock face. Analysis of adaptation indices revealed neither increased nor decreased adaptation after repeated instructions compared with a single instruction. Our data also show less adaptation with gradual than with sudden adaptation and less adaptation without than with instruction. These differences were pronounced at the beginning of adaptation; however, by the end of adaptation, all four groups reached similar levels of adaptation. In addition, we found significant group differences for the awareness index, with lower awareness after gradual adaptation than after sudden, instructed adaptation. Intermanual transfer did not differ between groups. However, we found a significant correlation between the awareness and intermanual transfer indices. We conclude that the magnitude of the explicit process cannot be further increased by repeated instruction and that intermanual transfer appears to be largely related to the explicit adaptation process.
A mass spectrometry-based atlas of extracellular matrix proteins across 25 mouse organs
Authors: McCabe Maxwell C. , Saviola Anthony J. , Hansen Kirk C.
Published: March 2022

The extracellular matrix is a critical non-cellular component of multi-cellular organisms containing a variety of proteins, glycoproteins, and proteoglycans which has been implicated in a wide variety of essential biological processes, including development, wound healing, and aging. Due to low solubility, many ECM proteins have been underrepresented in previous proteomics datasets. Using an optimized 3-step decellularization and ECM extraction method involving chaotrope extraction and digestion via hydroxylamine hydrochloride, we have generated coverage of the matrisome across 25 organs. We observe that the top 100 most abundant proteins from the ECM fractions of all tissues are generally present in all tissues, indicating that tissue matrices are principally composed of a shared set of ECM proteins. However, these proteins vary up to 4,000-fold between tissues, resulting in highly unique matrix profiles even with the same primary set of proteins. A data reduction approach was used to reveal related networks of expressed ECM proteins across varying tissues, including basement membrane and collagen subtypes.
Classification of plant growth-promoting bacteria inoculation status and prediction of growth-related traits in tropical maize using hyperspectral image and genomic data
Authors: Yassue Rafael Massahiro , Galli Giovanni , Fritsche-Neto Roberto , Morota Gota
Published: March 2022

Recent technological advances in high-throughput phenotyping have created new opportunities for the prediction of complex traits. In particular, phenomic prediction using hyper-spectral reflectance could capture various signals that affect phenotypes genomic prediction might not explain. A total of 360 inbred maize lines with or without plant growth-promoting bacterial inoculation management under nitrogen stress were evaluated using 150 spectral wavelengths ranging from 386 to 1021 nm and 13,826 single-nucleotide polymorphisms. Six prediction models were explored to assess the predictive ability of hyperspectral and genomic data for inoculation status and plant growth-related traits. The best models for hyperspectral prediction were partial least squares and automated machine learning. The Bayesian ridge regression and BayesB were the best performers for genomic prediction. Overall, hyper-spectral prediction showed greater predictive ability for shoot dry mass and stalk diameter, whereas genomic prediction was better for plant height. The prediction models that simultaneously accommodated both hyperspectral and genomic data resulted in a predictive ability as high as that of phenomics or genomics alone. Our results highlight the usefulness of hyperspectral-based phenotyping for management and phenomic prediction studies.

Core ideas

Hyperspectral reflectance data can classify plant growth-promoting bacteria inoculation status

Phenomic prediction performs better than genomic prediction depending on the target phenotype

AutoML is a promising approach for automating hyperparameter tuning for classification and prediction
Protein-Ligand Interaction Graphs: Learning from Ligand-Shaped 3D Interaction Graphs to Improve Binding Affinity Prediction
Authors: Moesser Marc A. , Klein Dominik , Boyles Fergus , Deane Charlotte M. , Baxter Andrew , Morris Garrett M.
Published: March 2022

Graph Neural Networks (GNNs) have recently gained in popularity, challenging molecular fingerprints or SMILES-based representations as the predominant way to represent molecules for binding affinity prediction. Although simple ligand-based graphs alone are already useful for affinity prediction, better performance on multi-target datasets has been achieved with models that incorporate 3D structural information. Most recent advances utilize complex GNN architectures to capture 3D protein-ligand information by incorporating ligand-interacting protein atoms as additional nodes in the graphs; or by building a second protein-based graph in parallel. This expands the graph considerably while obfuscating the shape of the underlying ligand, diminishing the advantage that GNNs have when encoding molecular structures. There is therefore a need for a simple and elegant molecular graph representation that retains the topology of the ligand while simultaneously encoding 3D protein-ligand interactions.

We present Protein-Ligand Interaction Graphs (PLIGs): a simple way of representing atom-atom contacts of 3D protein-ligand complexes as node features for GNNs. PLIGs featurize an atom node in the molecular graph by describing each atom’s properties as well as all atom-atom contacts made with protein atoms within a distance threshold. The edges of the graph are therefore identical to ligand-based graphs, but the nodes encode the 3D protein-ligand contacts. Since PLIGs are applicable to any GNN architecture, we have benchmarked their performance with six different GNN architectures, and compared them to conventional ligand-based graphs and fingerprint-based multi-layer perceptron (MLP) models using the CASF-2016 benchmark set where we found PLIG-based Graph Attention Networks (GATNet) to be the best performing model (ρ=0.84, RMSE=1.22 pK). In summary, we created a novel graph-based representation that incorporates 3D structural information into the node features of ligand-shaped molecular graphs. The PLIG representation is simple, elegant, flexible and easily customizable, opening up many possibilities of incorporating other 2D and 3D properties into the graph.

Access

The code and implementation for PLIGs and all models can be found at github.com/MarcMoesser/Protein-Ligand-Interaction-Graphs.
Pliable synaptic fidelity and excitatory inter-synaptic crosstalk in the intact brain
Authors: Reynolds James P. , Jensen Thomas P. , Rama Sylvain , Zheng Kaiyu , Savtchenko Leonid P. , Rusakov Dmitri A.
Published: March 2022

Memory formation in neural circuits may involve changes in synaptic efficacy and in cell intrinsic excitability, yet how this process unfolds in the living brain has remained elusive. Here, we employed multiplexed imaging of genetically encoded indicators of glutamate and Ca2+ in mouse barrel cortex to detect increased fidelity coupled with reduced excitation of thalamocortical connections that undergo whisker-stimulation induced LTP. High-resolution imaging revealed that whisker stimuli trigger excitatory synaptic activity that generates extrasynaptic glutamate transients reaching the bulk of neighbouring synapses in the target cortical area. Our findings pave the way to understanding basic plasticity features of the synaptic connectome while revealing a significant component of volume-transmitted glutamatergic signalling among cells in the intact brain.

One Sentence Summary

Sensory-stimulation LTP increases fidelity while reducing excitation at individual thalamocortical connections which generate spatially intersecting glutamate discharges
Soluble P2X7 receptor is elevated in the plasma of COVID-19 patients and correlates with disease severity
Authors: García-Villalba Julio , Hurtado-Navarro Laura , Peñín-Franch Alejandro , Molina-López Cristina , Martínez-Alarcón Laura , Angosto-Bazarra Diego , Baroja-Mazo Alberto , Pelegrín Pablo
Published: March 2022

Inflammation is a tightly coordinated response against bacterial and viral infections, triggered by the production of pro-inflammatory cytokines. SARS-CoV-2 infection induces COVID-19 disease, characterized by an inflammatory response mediated through the activation of the NLRP3 inflammasome, which results in the production of IL-1β and IL-18 along with pyroptotic cell death. The NLRP3 inflammasome could be also triggered by sterile danger signals such as extracellular ATP triggering the purinergic P2X7 receptor. Severe inflammation in the lungs of SARS-CoV-2 infected individuals is associated with pneumonia, hypoxia and acute respiratory distress syndrome, these being the causes of death associated with COVID-19. Both the P2X7 receptor and NLRP3 have been considered as potential pharmacological targets for treating inflammation in COVID-19. However, there is no experimental evidence of the involvement of the P2X7 receptor during COVID-19 disease. In the present study we determined the concentration of different cytokines and the P2X7 receptor in the plasma of COVID-19 patients and found that along with the increase in IL-6, IL-18 and the IL-1 receptor antagonist in the plasma of COVID-19 patients, there was also an increase in the purinergic P2X7 receptor. Increase in COVID-19 severity and C-reactive protein concentration positively correlated with increased concentration of the P2X7 receptor in the plasma, but not with IL-18 cytokine. The P2X7 receptor was found in the supernatant of human peripheral blood mononuclear cells after inflammasome activation. Therefore, our data suggest that determining levels of the P2X7 receptor in the plasma could be a novel biomarker of COVID-19 severity.
Gain, not concomitant changes in spatial receptive field properties, improves task performance in a neural network attention model
Authors: Fox Kai J , Birman Daniel , Gardner Justin L
Published: March 2022

Attention allows us to focus sensory processing on behaviorally relevant aspects of the visual world. One potential mechanism of attention is a change in the gain of sensory responses. However, changing gain at early stages could have multiple downstream consequences for visual processing. Which, if any, of these effects can account for the benefits of attention for detection and discrimination? Using a model of primate visual cortex we document how a Gaussian-shaped gain modulation results in changes to spatial tuning properties. Forcing the model to use only these changes failed to produce any benefit in task performance. Instead, we found that gain alone was both necessary and sufficient to explain category detection and discrimination during attention. Our results show how gain can give rise to changes in receptive fields which are not necessary for enhancing task performance.
Evidence for adaptive morphological plasticity in the Caribbean coral,Acropora cervicornis
Authors: Million Wyatt C. , Ruggeri Maria , O’Donnell Sibelle , Bartels Erich , Krediet Cory J. , Kenkel Carly D.
Published: March 2022

Genotype-by-environment interactions (GxE) indicate that variation in organismal traits cannot be explained by fixed effects of genetics or site-specific plastic responses alone. For tropical coral reefs experiencing dramatic environmental change, identifying the contributions of genotype, environment, and GxE on coral performance will be vital for both predicting persistence and developing restoration strategies. We quantified the impacts of G, E, and GxE on the morphology and survival of the endangered coral,A. cervicornis, through an in situ transplant experiment exposing common garden (nursery) raised clones of ten genotypes to nine reef sites in the Florida Keys. By fate-tracking outplants over one year with colony-level 3D photogrammetry, we uncovered significant GxE on coral size and survivorship indicating that no universal winner exists in terms of colony performance. Moreover, the presence of GxE also implies the existence of intraspecific variation in phenotypic plasticity. Rather than differences in mean trait values, we find that individual-level morphological plasticity is adaptive in that the most plastic individuals also exhibited the fastest growth and highest survival. This indicates that adaptive morphological plasticity may continue to evolve, influencing the success ofA. cervicornisand resulting reef communities in a changing climate. As focal reefs are active restoration sites, the knowledge that variation in phenotype is an important predictor of performance can be directly applied to restoration planning. Taken together, these results establishA. cervicornisas a system for studying the eco-evolutionary dynamics of phenotypic plasticity that also can inform genetic- and environment-based strategies for coral restoration.
Evoking the N400 Event-Related Potential (ERP) Component Using a Publicly Available Novel Set of Sentences with Semantically Incongruent or Congruent Eggplants (Endings)
Authors: Toffolo Kathryn K. , Freedman Edward G. , Foxe John J.
Published: March 2022

During speech comprehension, the ongoing context of a sentence is used to predict sentence outcome by limiting subsequent word likelihood. Neurophysiologically, violations of context-dependent predictions result in amplitude modulations of the N400 event-related potential (ERP) component. While N400 is widely used to measure semantic processing and integration, no publicly-available auditory stimulus set is available to standardize approaches across the field. Here, we developed an auditory stimulus set of 404 sentences that utilized the semantic anomaly paradigm, provided cloze probability for all stimuli, and was developed for both children and adults. With 20 neurotypical adults, we validated that this set elicits robust N400’s, as well as two additional semantically-related ERP components: the late positivity component and the recognition potential. This stimulus set and the 20 high-density (128-channel) electrophysiological datasets are made publicly available here to promote data sharing and reuse. Future studies that use this stimulus set to investigate sentential semantic comprehension in both control and clinical populations may benefit from the increased comparability and reproducibility within this field of research.
Rhythmic firing of neurons in the medulla of conscious freely behaving rats: rhythmic coupling with baroreceptor input
Authors: Kocsis Bernat , Topchiy Irina
Published: March 2022

Recent investigations emphasized the importance of neural control of cardiovascular adjustments in complex behaviors, including stress, exercise, arousal, sleep-wake states, and different tasks. Baroreceptor feedback is an essential component of this system acting on different time scales from maintaining stable levels of cardiovascular parameters on the long-term to rapid alterations according to behavior. The baroreceptor input is essentially rhythmic, reflecting periodic fluctuations in arterial blood pressure. Cardiac rhythm is a prominent feature of the autonomic control system, present on different levels, including neuron activity in central circuits. The mechanism of rhythmic entrainment of neuron firing by the baroreceptor input was studied in great detail under anesthesia but recordings of sympathetic-related neuron firing in freely moving animals remain extremely scarce. In this study we recorded multiple single neuron activity in the reticular formation of the medulla in freely moving rats during natural behavior. Neurons firing in synchrony with the cardiac rhythm were detected in each experiment (n=4). In agreement with prior observations in anesthetized cats, we found that neurons in this area exhibited high neuron-to-neuron variability and temporal flexibility in their coupling to cardiac rhythm in freely moving rats, as well. This included firing in bursts at multiples of cardiac cycles, but not directly coupled to the heartbeat, supporting the concept of baroreceptor input entraining intrinsic neural oscillations rather than imposing a rhythm of solely external origin on these networks. It may also point to a mechanism of maintaining the basic characteristics of sympathetic neuron activity, i.e. burst-discharge and cardiac-related rhythmicity, on the background of behavior-related adjustments in their firing rate.
AI-powered pan-species computational pathology: bridging clinic and wildlife care
Authors: AbdulJabbar Khalid , Castillo Simon P. , Hughes Katherine , Davidson Hannah , Boddy Amy M. , Abegglen Lisa M. , Murchison Elizabeth P. , Graham Trevor A. , Spiro Simon , Palmieri Chiara , Yuan Yinyin
Published: March 2022

Cancers occur across species. Understanding what is consistent and varies across species can provide new insights into cancer initiation and evolution, with significant implications for animal welfare and wildlife conservation. We built the pan-species cancer digital pathology atlas (PANCAD) and conducted the first pan-species study of computational comparative pathology using a supervised convolutional neural network algorithm trained on human samples. The artificial intelligence algorithm achieves high accuracy in measuring immune response through single-cell classification for two transmissible cancers (canine transmissible venereal tumour, 0.94; Tasmanian devil facial tumour disease, 0.88). Furthermore, in 18 other vertebrate species (mammalia=11, reptilia=4, aves=2, and amphibia=1), accuracy (0.57-0.94) was influenced by cell morphological similarity preserved across different taxonomic groups, tumour sites, and variations in the immune compartment. A new metric, named morphospace overlap, was developed to guide veterinary pathologists towards rational deployment of this technology on new samples. This study provides the foundation and guidelines for transferring artificial intelligence technologies to veterinary pathology based on a new understanding of morphological conservation, which could vastly accelerate new developments in veterinary medicine and comparative oncology.
Sex and estrous cycle affect experience-dependent plasticity in mouse primary visual cortex
Authors: Schecter Rachel W. , Jensen Cambria M. , Gavornik Jeffrey P.
Published: March 2022

Sex hormones can affect cellular physiology and modulate synaptic plasticity, but it is not always clear whether or how sex-dependent differences identifiedin vitroexpress themselves as functional dimorphisms in the brain. Historically, most experimental neuroscience has been conducted using only male animals and the literature is largely mute about whether including female mice in will introduce variability due to inherent sex differences or endogenous estrous cycles. Though this is beginning to change following an NIH directive that sex should be included as a factor in vertebrate research, the lack of information raises practical issues around how to design experimental controls and apply existing knowledge to more heterogeneous populations. Various lines of research suggest that visual processing can be affected by sex and estrous cycle stage. For these reasons, we performed a series ofin vivoelectrophysiological experiments to characterize baseline visual function and experience-dependent plasticity in the primary visual cortex (V1) of male and female mice. We find that sex and estrous stage have no statistically significant effect on baseline acuity measurements, but that both sex and estrous stage have can modulate two mechanistically distinct forms of experience dependent cortical plasticity. We also demonstrate that resulting variability can be largely controlled with appropriate normalizations. These findings suggest that V1 plasticity can be used for mechanistic studies focusing on how sex hormones effect experience dependent plasticity in the mammalian cortex.
Goal-specific brain MRI harmonization
Authors: An Lijun , Chen Jianzhong , Chen Pansheng , Zhang Chen , He Tong , Chen Christopher , Zhou Juan Helen , Yeo B.T. Thomas ,   the Alzheimer’s Disease Neuroimaging Initiative,   the Australian Imaging Biomarkers and Lifestyle Study of Aging
Published: March 2022

There is significant interest in pooling magnetic resonance image (MRI) data from multiple datasets to enable mega-analysis. Harmonization is typically performed to reduce heterogeneity when pooling MRI data across datasets. Most MRI harmonization algorithms do not explicitly consider downstream application performance during harmonization. However, the choice of downstream application might influence what might be considered as study-specific confounds. Therefore, ignoring downstream applications during harmonization might potentially limit downstream performance. Here we propose a goal-specific harmonization framework that utilizes downstream application performance to regularize the harmonization procedure. Our framework can be integrated with a wide variety of harmonization models based on deep neural networks, such as the recently proposed conditional variational autoencoder (cVAE) harmonization model. Three datasets from three different continents with a total of 2787 participants and 10085 anatomical T1 scans were used for evaluation. We found that cVAE removed more dataset differences than the widely used ComBat model, but at the expense of removing desirable biological information as measured by downstream prediction of mini mental state examination (MMSE) scores and clinical diagnoses. On the other hand, our goal-specific cVAE (gcVAE) was able to remove as much dataset differences as cVAE, while improving downstream cross-sectional prediction of MMSE scores and clinical diagnoses.
Emergence of hyper insecticide-resistant dengue vectors in Indochina Peninsula: threats of concomitant knockdown resistance mutations
Authors: Kasai Shinji , Itokawa Kentaro , Uemura Nozomi , Takaoka Aki , Furutani Shogo , Maekawa Yoshihide , Kobayashi Daisuke , Imanishi-Kobayashi Nozomi , Amoa-Bosompem Michael , Murota Katsunori , Higa Yukiko , Kawada Hitoshi , Minakawa Noboru , Cuong Tran Chi , Yen Nguyen Thi , Phong Tran Vu , Keo Sath , Kang Kroesna , Miura Kozue , Ng Lee Ching , Teng Hwa-Jen , Dadzie Samuel , Subekti Sri , Mulyatno Kris Cahyo , Sawabe Kyoko , Tomita Takashi , Komagata Osamu
Published: March 2022

Aedes aegypti(Linnaeus, 1762) is the main mosquito vector for dengue and other arboviral infectious diseases. Control of this important vector highly relies on the use of insecticides, especially pyrethroids. Nevertheless, the development of pyrethroid resistance is a major obstacle to mosquito/disease control worldwide. Here, we focused on the mutations in the target site of pyrethroid insecticides, voltage-sensitive sodium channel (Vssc), and found thatAe. aegypticollected from Vietnam has the L982W allele in theVsscat a high frequency (>79%). L982W mutation is located in the highly conserved region ofVsscthat is associated with sodium–ion selectivity and permeation rate. Strains having the L982W allele showed similar or even higher levels of resistance to pyrethroids than those having V1016G, a typical knockdown resistance allele in Asia. Furthermore, concomitant mutations L982W+F1534C and V1016G+F1534C were confirmed, and strains having these multipleVsscmutations exhibited incomparably higher levels of pyrethroid resistance than any other field population ever reported. Molecular modeling analysis confirmed that these concomitant mutant alleles could interfere with approaching pyrethroid toVssc. Remarkably, >90% ofVsscofAe. aegyptiwere occupied by these hyper insecticide-resistant haplotypes in Phnom Penh city, Cambodia. Analysis of wholeVssccoding genes suggested thatVsscs have evolved into stronger resistant forms efficiently through gene recombination events. At this point, L982W has never been detected inVsscofAe. aegyptifrom any other neighboring countries. We strongly emphasize the need to be vigilant about these strong resistance genes spreading to the world through Indochina Peninsula.

Significance Statement

The high frequency (>78%) of the L982W allele was detected at the target site of the pyrethroid insecticide, the voltage-sensitive sodium channel (Vssc) ofAedes aegypticollected from Vietnam and Cambodia. Haplotypes having concomitant mutations L982W+F1534C and V1016G+F1534C were also confirmed in both countries, and their frequency was high (>90%) in Phnom Penh, Cambodia. Strains having these haplotypes exhibited substantially higher levels of pyrethroid resistance than any other field population ever reported. The L982W mutation has never been detected in any country of the Indochina Peninsula except Vietnam and Cambodia, but it may be spreading to other areas of Asia, which can cause an unprecedentedly serious threat to the control of dengue fever as well as otherAedes-borne infectious diseases.
Soft disorder modulates the assembly path of protein complexes
Authors: Seoane Beatriz , Carbone Alessandra
Published: March 2022

The relationship between interactions, flexibility and disorder in proteins has been explored from many angles over the years: folding upon binding, flexibility of the core relative to the periphery, entropy changes, etc. In this work, we provide statistical evidence for the involvement of highly mobile and disordered regions in complex assembly. We ordered the entire set of X-ray crystallographic structures in the Protein Data Bank into hierarchies of progressive interactions involving identical or very similar protein chains, yielding 40205 hierarchies of protein complexes with increasing numbers of partners. We then examine them as proxies for the assembly pathways. Using this database, we show that upon oligomerisation, the new interfaces tend to be observed at residues that were characterised as softly disordered (flexible, amorphous or missing residues) in the complexes preceding them in the hierarchy. We also rule out the possibility that this correlation is just a surface effect by restricting the analysis to residues on the surface of the complexes. Interestingly, we find that the location of soft disordered residues in the sequence changes as the number of partners increases. Our results show that there is a general mechanism for protein assembly that involves soft disorder and modulates the way protein complexes are assembled. This work highlights the difficulty of predicting the structure of large protein complexes from sequence and emphasises the importance of linking predictors of soft disorder to the next generation of predictors of complex structure. Finally, we investigate the relationship between the Alphafold2’s confidence metric pLDDT for structure prediction in unbound versus bound structures, and soft disorder. We show a strong correlation between Alphafold2 low confidence residues and the union of all regions of soft disorder observed in the hierarchy. This paves the way for using the pLDDT metric as a proxy for predicting interfaces and assembly paths.

Availability

All the data used for these analyses (hierarchies of interactions and soft disorder) are available at the websitehttp://www.lcqb.upmc.fr/softdisorder-assembly/.

Author summary

Both flexibility and intrinsic disorder are used as regulatory mechanisms in proteins. They can alter the spatial positions of important recognition sites, and increased mobility appears to facilitate ligand binding through conformational selection. In this work, we show statistical evidence that soft disorder is directly involved in the process of protein assembly and that migration of soft disorder after binding gives rise to new or altered functions in the protein complex. Given the impressive progress that AlphaFold2 has made in protein structure prediction in recent years, this work highlights the importance of also correctly predicting conformational heterogeneity, mobility and intrinsic disorder in order to access the full functional repertoire and interaction network of a given protein.
Pudendal, but not tibial, nerve stimulation modulates vulvar blood perfusion in anesthetized rodents
Authors: Bottorff Elizabeth C. , Bruns Tim M.
Published: March 2022

Introduction and Hypothesis

Preclinical studies have shown that neuromodulation can increase vaginal blood perfusion, but the effect on vulvar blood perfusion is unknown. We hypothesized that pudendal and tibial nerve stimulation could evoke an increase in vulvar blood perfusion.

Methods

We used female Sprague-Dawley rats for non-survival procedures under urethane anesthesia. We measured perineal blood perfusion in response to twenty-minute periods of pudendal and tibial nerve stimulation using laser speckle contrast imaging (LSCI). After a thoracic-level spinalization and a rest period, we repeated each stimulation trial. We calculated average blood perfusion before, during, and after stimulation for three perineal regions (vulva, anus, and inner thigh), for each nerve target and spinal cord condition.

Results

We observed a significant increase in vulvar, anal, and inner thigh blood perfusion during pudendal nerve stimulation in spinally intact and spinalized rats. Tibial nerve stimulation had no effect on perineal blood perfusion for both spinally intact and spinalized rats.

Conclusions

This is the first study to examine vulvar hemodynamics with LSCI in response to nerve stimulation. This study demonstrates that pudendal nerve stimulation modulates vulvar blood perfusion, indicating the potential of pudendal neuromodulation to improve genital blood flow as a treatment for women with sexual dysfunction. This study provides further support for neuromodulation as a treatment for women with sexual arousal disorders. Studies in unanesthetized animal models with genital arousal disorders are needed to obtain further insights into the mechanisms of neural control over genital hemodynamics.

Brief Summary

In an anesthetized rodent model, electrical stimulation of the pudendal nerve will drive increases in vulvar blood perfusion while tibial nerve stimulation will not.
Engineering of Sr33 and Sr50 plant immune receptors to alter recognition specificity and autoactivity
Authors: Tamborski Janina , Seong Kyungyong , Liu Furong , Staskawicz Brian , Krasileva Ksenia V
Published: March 2022

Plants possess cytoplasmic immune receptors called nucleotide-binding leucine-rich repeat receptors (NLRs) that recognize the presence of a pathogen through a range of mechanisms: direct binding of effectors or indirect recognition of effector actions. The direct binding of effectors has been shown to be mediated through the NLR’s leucine-rich repeat (LRR) domain. Accurate prediction of amino acids involved in these direct interactions can greatly enhance understanding of effector recognition and inform efforts to engineer new resistance. In this study, we utilized two homologous NLR resistance genes from wheat, Sr33 and Sr50, that recognize distinct effectors by directly binding to them through their LRR domain. While the effector recognized by Sr50 is known and described as AvrSr50, the effector recognized by Sr33 remains unknown. Through a combination of phylogenetics, allele diversity analysis in the LRR and structural modeling, we identified the amino acids in Sr50 likely to physically interact with its effector. Mutation of these sites helped identify 12 amino acids we hypothesized to be sufficient to mediate effector binding in Sr50. Changing these 12 corresponding amino acids in Sr33, we showed AvrSr50-dependent initiation of cell death in wheat protoplasts and Nicotiana benthamiana. Furthermore, we were able to pinpoint and change amino acid residues that govern autoactivity of Sr50 in the wheat protoplast cell death assay. These findings are a major advance towards the successful engineering of new effector recognition specificities in direct binder NLRs.
Potent universal-coronavirus therapeutic activity mediated by direct respiratory administration of a Spike S2 domain-specific human neutralizing monoclonal antibody
Authors: Piepenbrink Michael S. , Park Jun-Gyu , Desphande Ashlesha , Loos Andreas , Ye Chengjin , Basu Madhubanti , Sarkar Sanghita , Chauvin David , Woo Jennifer , Lovalenti Philip , Erdmann Nathaniel B. , Goepfert Paul A. , Truong Vu L. , Bowen Richard A. , Walter Mark R. , Martinez-Sobrido Luis , Kobie James J.
Published: March 2022

Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) marks the third novel β-coronavirus to cause significant human mortality in the last two decades. Although vaccines are available, too few have been administered worldwide to keep the virus in check and to prevent mutations leading to immune escape. To determine if antibodies could be identified with universal coronavirus activity, plasma from convalescent subjects was screened for IgG against a stabilized pre-fusion SARS-CoV-2 spike S2 domain, which is highly conserved between human β-coronavirus. From these subjects, several S2-specific human monoclonal antibodies (hmAbs) were developed that neutralized SARS-CoV-2 with recognition of all variants of concern (VoC) tested (Beta, Gamma, Delta, Epsilon, and Omicron). The hmAb 1249A8 emerged as the most potent and broad hmAb, able to recognize all human β-coronavirus and neutralize SARS-CoV and MERS-CoV. 1249A8 demonstrated significant prophylactic activity in K18 hACE2 mice infected with SARS-CoV-2 lineage A and lineage B Beta, and Omicron VoC. 1249A8 delivered as a single 4 mg/kg intranasal (i.n.) dose to hamsters 12 hours following infection with SARS-CoV-2 Delta protected them from weight loss, with therapeutic activity further enhanced when combined with 1213H7, an S1-specific neutralizing hmAb. As little as 2 mg/kg of 1249A8 i.n. dose 12 hours following infection with SARS-CoV Urbani strain, protected hamsters from weight loss and significantly reduced upper and lower respiratory viral burden. These results indicate in vivo cooperativity between S1 and S2 specific neutralizing hmAbs and that potent universal coronavirus neutralizing mAbs with therapeutic potential can be induced in humans and can guide universal coronavirus vaccine development.
Effects of immunomodulatory peptides derived from a soil bacterium on cecal microbiota of broilers challenged with Clostridium perfringens
Authors: Li Xiaoying , Li Guiguan , Peng Qianning , Sun Yuli , Li Yong , Li Haitao , Ren Jun
Published: March 2022

Brevibacillus texasporus peptide (BT peptide) is immunomodulatory in poultry as a feed additive to substitute antibiotics. In the present study we performed 16S rRNA gene sequencing to compare development of the cecal microbial communities in Clostridium perfringens-challenged broilers fed basal diet only or with either BT peptide (48 ppm) or antibiotics mixture (20 ppm bacitracin zinc and 40 ppm colistin sulfate). 240 chicks were randomly assigned into each treatment and a total of 65 cecal samples were collected at the beginning, during seven challenge days and one week post challenge. The composition of microbial communities was clearly distinguishable over time. Treatments with challenge and the antibiotics mixture were associated with increased diversity and with higher relative abundances of Alistipes sp. CHKCI003 and Faecalibacterium and lower abundance of Escherichia coli (all p < 0.05). At the termination of the trial, the cecal microbiota in broilers supplemented with BT peptide was dominated by members of Bacteroidaceae. Predicted function analysis reveals significant enrichment of genes involved in ion-coupled transporters and sugar and biotin metabolism in the BT peptide treatment. Taken together, our results suggest that BT peptide and commonly used antibiotics have different influences on modulating the composition of cecal microbiota in broilers.