bluuebunny/crossref_metadata_2025_split huggingface dataset:
ATP-competitive and allosteric inhibitors induce differential conformational changes at the autoinhibitory interface of Akt
Authors: Shaw Alexandria L , Parson Matthew AH , Truebestein Linda , Jenkins Meredith L , Leonard Thomas A , Burke John E 
Published: July 2022

AbstractThe protein kinase Akt is a master regulator of pro-growth signalling in the cell. Akt is activated through its targeted recruitment to phosphoinositides, leading to disruption of the autoinhibitory interface between the kinase and pleckstrin homology (PH) domains. Hyper activation of Akt is common in oncogenic transformation, with multiple oncogenic activating mutants identified in Akt. This has led to the development of potent and selective ATP-competitive and allosteric inhibitors for Akt. Paradoxically, some ATP-competitive Akt inhibitors cause hyperphosphorylation of Akt. Here, using hydrogen deuterium exchange mass spectrometry (HDX-MS), we interrogated the conformational changes upon binding to the Akt active site inhibitor A-443654, and the Akt allosteric inhibitor MK-2206. We compared the conformational changes that occurred for each inhibitor under three different states of Akt: i-inactive monophosphorylated, ii-partially active tris-phosphorylated [T308, T450, S473], and iii-fully activated, tris-phosphorylated bound to PIP3 membranes. The allosteric MK-2206 inhibitor results in large scale allosteric conformational changes in all states, and restricts membrane binding through sequestration of the PH domain. Binding of the A-443654 inhibitor led to large scale allosteric conformational changes in both the monophosphorylated and phosphorylated states, leading to an alteration in the autoinhibitory PH-kinase interface. We also observed increased protection in the PH domain upon membrane binding in the presence of A-443654, suggesting that the PH domain is more accessible for membrane binding. This work provides unique insight into the autoinhibitory conformation of the PH and kinase domain and dynamic conformational changes induced by Akt inhibitors, and has important implications for the design of Akt targeted therapeutics.
A low-cost and open-source solution to automate imaging and analysis of cyst nematode infection assays for Arabidopsis thaliana
Authors: Kranse Olaf Prosper , Ko Itsuhiro , Healey Roberta , Sonawala Unnati , Wei Siyuan , Senatori Beatrice , De Batté Francesco , Zhou Ji , Eves-van den Akker Sebastian 
Published: July 2022

AbstractBackgroundCyst nematodes are one of the major groups of plant-parasitic nematode, responsible for considerable crop losses worldwide. Improving genetic resources, and therefore resistant cultivars, is an ongoing focus of many pest management strategies. One of the major bottlenecks in identifying the plant genes that impact the infection, and thus the yield, is phenotyping. The current available screening method is slow, has unidimensional quantification of infection limiting the range of scorable parameters, and does not account for phenotypic variation of the host. The ever-evolving field of computer vision may be the solution for both the above-mentioned issues. To utilise these tools, a specialised imaging platform is required to take consistent images of nematode infection in quick succession.ResultsHere, we describe an open-source, easy to adopt, imaging hardware and trait analysis software method based on a pre-existing nematode infection screening method in axenic culture. A cost-effective, easy-to-build and -use, 3D-printed imaging device was developed to acquire images of the root system of Arabidopsis thaliana infected with the cyst nematode Heterodera schachtii, replacing costly microscopy equipment. Coupling the output of this device to simple analysis scripts allowed the measurement of some key traits such as nematode number and size from collected images, in a semi-automated manner. Additionally, we used this combined solution to quantify an additional trait, root area before infection, and showed both the confounding relationship of this trait on nematode infection and a method to account for it.ConclusionTaken together, this manuscript provides a low-cost and open-source method for nematode phenotyping that includes the biologically relevant nematode size as a scorable parameter, and a method to account for phenotypic variation of the host. Together these tools highlight great potential in aiding our understanding of nematode parasitism.
SARS-CoV-2 BA.4 infection triggers more cross-reactive neutralizing antibodies than BA.1
Authors: Richardson Simone I. , Motlou Thopisang , van der Mescht Mieke A. , Lambson Bronwen E. , Everatt Josie , Amoako Daniel Gyamfi , Gottberg Anne von , Wolter Nicole , de Beer Zelda , de Villiers Talita Roma , Bodenstein Annie , van den Berg Gretha , Rossouw Theresa M. , Boswell Michael T. , Ueckermann Veronica , Bhiman Jinal N. , Moore Penny L. 
Published: July 2022

AbstractSARS-CoV-2 variants of concern (VOCs) differentially trigger neutralizing antibodies with variable cross-neutralizing capacity. Here we show that unlike SARS-CoV-2 Omicron BA.1, which triggered neutralizing antibodies with limited cross-reactivity, BA.4/5 infection triggers highly cross-reactive neutralizing antibodies. Cross-reactivity was observed both in the absence of prior vaccination and also in breakthrough infections following vaccination. This suggests that next-generation vaccines incorporating BA.4, which is spreading globally, might result in enhanced neutralization breadth.
Systematic Bayesian Posterior Analysis Guided by Kullback-Leibler Divergence Facilitates Hypothesis Formation
Authors: Huber Holly A. , Georgia Senta K. , Finley Stacey D. 
Published: July 2022

AbstractBayesian inference produces a posterior distribution for the parameters and predictions from a mathematical model that can be used to guide the formation of hypotheses; specifically, the posterior may be searched for evidence of alternative model hypotheses, which serves as a starting point for hypothesis formation and model refinement. Previous approaches to search for this evidence are largely qualitative and unsystematic; further, demonstrations of these approaches typically stop at hypothesis formation, leaving the questions they raise unanswered. Here, we introduce a Kullback-Leibler (KL) divergence-based ranking to expedite Bayesian hypothesis formation and investigate the hypotheses it generates, ultimately generating novel, biologically significant insights. Our approach uses KL divergence to rank parameters by how much information they gain from experimental data. Subsequently, rather than searching all model parameters at random, we use this ranking to prioritize examining the posteriors of the parameters that gained the most information from the data for evidence of alternative model hypotheses. We test our approach with two examples, which showcase the ability of our approach to systematically uncover different types of alternative hypothesis evidence. First, we test our KL divergence ranking on an established example of Bayesian hypothesis formation.Our top-ranked parameter matches the one previously identified to produce alternative hypotheses. In the second example, we apply our ranking in a novel study of a computational model of prolactin-induced JAK2-STAT5 signaling, a pathway that mediates beta cell proliferation. Here, we cluster our KL divergence rankings to select only a subset of parameters to examine for qualitative evidence of alternative hypotheses, thereby expediting hypothesis formation. Within this subset, we find a bimodal posterior revealing two possible ranges for the prolactin receptor degradation rate. We go on to refine the model, incorporating new data and determining which degradation rate is most plausible. Overall, we demonstrate that our approach offers a novel quantitative framework for Bayesian hypothesis formation and use it to produce a novel, biologically-significant insight.
Ending transmission of SARS-CoV-2: sterilizing immunity using an intranasal subunit vaccine
Authors: Leekha Ankita , Saeedi Arash , Sefat Samiur Rahman , Kumar Monish , Martinez-Paniagua Melisa , Damian Adrian , Kulkarni Rohan , Rezvan Ali , Mosoumi Shalaleh , Liu Xinli , Cooper Laurence JN , Sebastian Manu , Hurst Brett , Varadarajan Navin 
Published: July 2022

ABSTRACTImmunization programs against SARS-CoV-2 with commercial intramuscular (IM) vaccines prevent disease but not infections. The continued evolution of variants of concern (VOC) like Delta and Omicron has increased infections even in countries with high vaccination coverage. This is due to commercial vaccines being unable to prevent viral infection in the upper airways and exclusively targeting the spike (S) protein that is subject to continuous evolution facilitating immune escape. Here we report a multi-antigen, intranasal vaccine, NanoSTING-NS that yields sterilizing immunity and leads to the rapid and complete elimination of viral loads in both the lungs and the nostrils upon viral challenge with SARS-CoV-2 VOC. We formulated vaccines with the S and nucleocapsid (N) proteins individually to demonstrate that immune responses against S are sufficient to prevent disease whereas combination immune responses against both proteins prevents viral replication in the nasal compartment. Studies with the highly infectious Omicron VOC showed that even in vaccine-naïve animals, a single dose of NanoSTING-NS significantly reduced transmission. These observations have two implications: (1) mucosal multi-antigen vaccines present a pathway to preventing transmission and ending the pandemic, and (2) an explanation for why hybrid immunity in humans is superior to vaccine-mediated immunity by current IM vaccines.
TLR4/NF-κB Signaling Contributes to the Inflammation in Ovary and Inguinal Fats of Polycystic Ovary Syndrome
Authors: Sun Bo , Pan Zimeng , Kuang Hongying , Feng Xiaoling , Hou Lihui , Xu Fang , Song Feifei , Sun Miao 
Published: July 2022

AbstractBackgroundPolycystic ovary syndrome (PCOS) is a complex reproductive endocrine disorder. It has highly heterogeneous clinical manifestations which are characterized by biochemical hyperandrogenemia, obesity, insulin resistance, dyslipidemia, anovulation, and polycystic ovaries. However, the etiologies of PCOS are still unclear. Recently, studies have found that the low-grade inflammation contributed to the occurrence of PCOS, and as a critical biomarker indicated the endocrine disruptions in PCOS.ObjectiveThis study is aimed to investigate the processes and mediators of inflammation in contributing to the development of PCOS.MethodsLetrozole (LET) induced PCOS rat model was used in this study. Body weight, body temperature, inguinal fats weight, fasting glucose level, ovarian morphology, NF-κB signaling target genes in ovary, and protein expression levels of TLR4 and NF-κB in ovarian and inguinal fats were measured in rats with placebo and LET administrations for 6 and 12 weeks.ResultsPCOS rats, especially with LET intervention for 12 weeks, had higher body weight, inguinal fats weight and fasting glucose level compared to control group. The protein expression levels of TLR4 and NF-κB in cytoplasm of ovarian and inguinal fats were increased in LET-induced PCOS rats compared to control groups, while NF-κB in nucleus were reduced in PCOS rats. The expressions of ACTB, C3, CXCL3, NQO1 and SELP in ovarian were statistically different in PCOS rats induced by LET compared to control groups.ConclusionThese findings indicated that stimulating TLR4/NF-κB pathway in inguinal fats and ovary tissues contributed to the increased inflammation in LET-induced PCOS rats, which, in turn, exacerbated the phenotype of PCOS including weight gain, adipose tissue accumulation, hyperglycemia and follicular dysplasia.
A phylogenomic approach to resolving interrelationships of polyclad flatworms, with implications for life history evolution
Authors: Goodheart Jessica A. , Collins Allen G. , Cummings Michael P. , Egger Bernhard , Rawlinson Kate A. 
Published: July 2022

ABSTRACTPlatyhelminthes (flatworms) are a diverse invertebrate phylum that are useful for exploring life history evolution. Within Platyhelminthes, only two clades develop through a larval stage: free-living polyclads and parasitic neodermatans. Neodermatan larvae are considered evolutionarily derived, whereas polyclad larvae are hypothesized to be retained from the last common ancestor of Platyhelminthes – and Spiralia – due to ciliary band similarities among polyclad and other spiralian larvae. However, larval evolution has been challenging to investigate within polyclads due to low support for deeper phylogenetic relationships. To investigate polyclad life history evolution, we generated transcriptomic data for 21 species of polyclads to build a well-supported phylogeny for the group. We then used ancestral state reconstruction to investigate ancestral modes of development (direct vs indirect) within Polycladida, and flatworms in general. The resulting tree provides strong support for deeper nodes and we recover a new monophyletic clade of early branching cotyleans. Early branching clades of acotyleans and cotyleans possess diverse modes of development, suggesting a complex history of larval evolution in polyclads that likely includes multiple losses and/or multiple gains. Our ancestral state reconstructions in a previous platyhelminth phylogeny also suggests that similarities in larval morphology between flatworms and other phyla may have re-emerged secondarily or are convergently evolved.
Fast-local and slow-global neural ensembles in the mouse brain
Authors: Delaney Thomas J , O’Donnell Cian 
Published: July 2022

ABSTRACTEnsembles of neurons are thought to be co-active when participating in brain computations. However, it is unclear what principles determine whether an ensemble remains localised within a single brain region, or spans multiple brain regions. To address this, we analysed electrophysiological neural population data from hundreds of neurons recorded simultaneously across nine brain regions in awake mice. At fast sub-second timescales, spike count correlations between pairs of neurons in the same brain region were stronger than for pairs of neurons spread across different brain regions. In contrast at slower timescales, within- and between-region spike count correlations were similar. Correlations between high-firing-rate neuron pairs showed a stronger dependence on timescale than low-firing-rate neuron pairs. We applied an ensemble detection algorithm to the neural correlation data and found that at fast timescales each ensemble was mostly contained within a single brain region, whereas at slower timescales ensembles spanned multiple brain regions. These results suggest that the mouse brain may perform fast-local and slow-global computations in parallel.AUTHOR SUMMARYIn this study we analysed publicly available neural population electrophysiology data from nine brain regions in awake mice. To discover neural ensembles, we applied community detection algorithms to the spike count correlation matrices estimated from the data. We repeated the analysis at different timescales, ranging from 10 milliseconds to 3 seconds. We found that at fast timescales<1 s, neural ensembles tended to be localised within single brain regions. In contrast at slower timescales of>1 s, ensembles tended to be include neurons spread across multiple brain regions. Most of this effect was due to high-firing-rate neurons.
A statistical censoring approach accounts for hook competition in abundance indices from longline surveys
Authors: Watson Joe , Edwards Andrew M. , Auger-Méthé Marie 
Published: July 2022

AbstractFishery-independent longline surveys provide valuable data to monitor fish populations. However, competition for bait on the finite number of hooks leads to biased estimates of relative abundance when using simple catch-per-unit-effort methods. Numerous bias-correcting instantaneous-catch-rate methods have been proposed, modelling the bait removal times as independent random variables. However, experiments have cast doubts on the many assumptions required for these to accurately infer relative abundance. We develop a new approach by treating some observations as right-censored, acknowledging that observed catch counts are lower bounds of what they would have been in the absence of hook competition. Through simulation experiments we confirm that our approach consistently outperforms previous methods. We demonstrate performance of all methods on longline survey data of eleven species. Accounting for hook competition leads to large differences in relative indices (often −50% to +100%), with effects of hook competition varying between species (unlike other methods). Our method can be applied using existing statistical packages and can include environmental influences, making it a general and reliable method for analyzing longline survey data.
Efficient 3D light-sheet imaging of very large-scale optically cleared human brain and prostate tissue samples
Authors: Schueth Anna , Hildebrand Sven , Samarska Iryna , Sengupta Shubharthi , Kiessling Annemarie , Herrler Andreas , Hausen Axel zur , Capalbo Michael , Roebroeck Alard 
Published: July 2022

AbstractThe ability to image human tissue samples in 3D, with both cellular resolution and a large field of view (FOVs), can improve fundamental and clinical investigations. Here, we demonstrate the feasibility of light-sheet imaging of ∼5 cm3sized formalin fixed human brain and up to ∼7 cm3sized formalin fixed paraffin embedded (FFPE) prostate cancer samples, processed with the FFPE-MASH protocol. We present a light-sheet microscopy prototype, the cleared-tissue dual view Selective Plane Illumination Microscope (ct-dSPIM), capable of fast, 3D high-resolution acquisitions, of cubic centimetre sized cleared tissue. We used Mosaic scans for fast 3D overview scans of entire tissue samples or higher resolution overviews of large ROIs with various speeds: a) Mosaic 16 (16.4 µm isotropic resolution, ∼ 1.7 hr/cm3), b) Mosaic 4 (4.1 µm isotropic resolution, ∼ 5 hr/cm3) and c) Mosaic 0.5 (0.5 µm near isotropic resolution, ∼15.8 hr/cm3). We could visualise ROIs around the border of human brain area V1/V2, and could demonstrate suitable imaging quality for Gleason score grading in prostate cancer samples. We show that ct-dSPIM imaging is an excellent technique to quantitatively assess entire MASH prepared large-scale human tissue samples in 3D, with considerable future clinical potential in prostate cancer.
Advected percolation in the actomyosin cortex drives amoeboid cell motility
Authors: García-Arcos Juan Manuel , Ziegler Johannes , Grigolon Silvia , Reymond Loïc , Shajepal Gaurav , Cattin Cédric J. , Lomakin Alexis , Müller Daniel , Ruprecht Verena , Wieser Stefan , Voituriez Raphael , Piel Matthieu 
Published: July 2022

AbstractSpontaneous locomotion is a common feature of most metazoan cells, generally attributed to the fundamental properties of the actomyosin network. This force-producing machinery has been studied down to the most minute molecular details, especially in lamellipodium-driven migration. Nevertheless, how actomyosin networks work inside contraction-driven amoeboid cells still lacks unifying principles. Here, using stable motile blebs as a model amoeboid motile system, we image the dynamics of the actin cortex at the single filament level and reveal the co-existence of three phases of the actin network with distinct rheological properties. Physical modelling shows that these three phases organize spontaneously due to a rigidity percolation transition combined with an active advection of the percolated network. This spontaneous spatial organization of the mechanical properties of the actin network, which we propose to call advected percolation, constitutes a minimal and generic locomotion mechanism. It explains, down to the single actin filament level and up to the scale of the entire cell, how amoeboid cells can propel efficiently through complex 3D environments, a feature shared by immune and cancer cells.
Small non-coding RNA Interactome Capture reveals pervasive, carbon source-dependent tRNA engagement of yeast glycolytic enzymes
Authors: Asencio Claudio , Schwarzl Thomas , Sahadevan Sudeep , Hentze Matthias W. 
Published: July 2022

AbstractSmall non-coding RNAs fulfill key functions in cellular and organismal biology, typically working in concert with RNA-binding proteins (RBPs). While proteome-wide methodologies have enormously expanded the repertoire of known RBPs, these methods do not distinguish RBPs binding to small non-coding RNAs from the rest. To specifically identify this relevant subclass of RBPs, we developed small non-coding RNA interactome capture (snRIC2C) based on the differential RNA-binding capacity of silica matrices (2C). We define the S. cerevisiae proteome of nearly 300 proteins that specifically binds to RNAs smaller than 200 nucleotides in length (snRBPs), identifying informative distinctions from the total RNA-binding proteome determined in parallel. Strikingly, the snRBPs include most glycolytic enzymes from yeast. With further methodological developments using silica matrices, 12 tRNAs were identified as specific binders of the glycolytic enzyme GAPDH. We show that tRNA engagement of GAPDH is carbon source-dependent and regulated by the RNA polymerase III repressor Maf1, suggesting a regulatory interaction between glycolysis and RNA polymerase III activity. We conclude that snRIC2C and other 2C-derived methods greatly facilitate the study of RBPs, revealing previously unrecognised interactions.
Comparison of bacterial suppression by phage cocktails, dual-receptor generalists, and coevolutionarily trained phages
Authors: Borin Joshua M. , Lee Justin J. , Gerbino Krista R. , Meyer Justin R. 
Published: July 2022

AbstractThe evolution and spread of antibiotic resistant bacteria have renewed interest in phage therapy, the use of bacterial viruses (phages) to combat bacterial infections. The delivery of phages in cocktails where constituent phages target different modalities (e.g., receptors) may improve treatment outcomes by making it more difficult for bacteria to evolve resistance. However, the multipartite nature of cocktails may lead to unintended evolutionary and ecological outcomes. Here, we compare a 2-phage cocktail with a largely unconsidered group of phages: generalists that can infect through multiple, independent receptors. We find that both generalists and cocktails that target the same receptors suppress bacteria similarly for ~2 d. Yet a “trained” generalist phage, which previously adapted to its host via 28 d of coevolution, demonstrated superior suppression. To understand why the trained generalist was more effective, we measured the resistance of bacteria against each of our phages. We find that, when bacteria were assailed by 2 phages in the cocktail, they evolved mutations in manXYZ, a host inner-membrane transporter that λ uses to move its DNA across the periplasmic space and into the cell for infection. This provided crossresistance against the cocktail and untrained generalist. However, these mutations were ineffective at blocking the trained generalist because, through coevolutionary training, it evolved to bypass manXYZ resistance. The trained generalist’s past experiences in training make it exceedingly difficult for bacteria to evolve resistance, further demonstrating the utility of coevolutionary phage training for improving the therapeutic properties of phages.