bluuebunny/crossref_metadata_2025_split huggingface dataset:
ALegionella pneumophilaeffector impedes host gene silencing to promote virulence
Authors: Toinon Justine , Rolando Monica , Charvin Magali , Filopon Didier , Schiavolin Lionel , Sy Khadeeja Adam , Vu Hai-Chi , Gallois-Montbrun Sarah , Alam Antoine , Barraud Pierre , Rusniok Christophe , Lombard Bérangère , Loew Damarys , Buchrieser Carmen , Navarro Lionel 
Published: November 2022

AbstractRNA silencing is a gene silencing mechanism directed by small RNAs. Human miRNAs act as central regulators of host-bacteria interactions. However, it is unknown whether human pathogenic bacteria could impede RNA silencing to promote virulence. Here, we show that theLegionella pneumophilatype IV-secreted effector LegK1 efficiently suppresses siRNA and miRNA activities in human cells. This effect depends on its known kinase activity, but also on its novel capacity, found here, to bind Argonaute (Ago) proteins. We further demonstrate that the ability of LegK1 to activate NF-κB signaling is required for RNA silencing suppression, establishing a link between effector-mediated NF-κB signaling and RNA silencing suppression. LegK1 also promotesL. pneumophilagrowth in both amoeba and human macrophages, supporting a role for this effector in virulence. Finally, we show that, in infected-macrophages, the latter activity relies, in part, on the genetic targeting of human Ago4. These findings indicate that aL. pneumophilaeffector has evolved to suppress RNA silencing to promote virulence.Significance StatementIt is now well established that mammalian viruses suppress RNAi to promote their replication in host cells. However, whether mammalian pathogenic bacteria use a similar virulence strategy remains unknown. Here, we show that the LegK1 effector fromLegionella pneumophia, the causal agent of Legionnaires’ disease, efficiently suppresses RNAi in human cells. This effect depends on its ability to interact with Argonaute (Ago) proteins and to activate NF-κB signaling. In addition, LegK1 promotes virulence in infected-macrophages through the genetic targeting of human Ago4. Based on the lack of NF-κB-related factors in amoebae, and on the presence of canonical Ago proteins in these naturalL. pneumophilahosts, we propose that the RNAi suppression activity of LegK1 represents its primary virulence function.
Rewiring of the promoter-enhancer interactome and regulatory landscape in glioblastoma orchestrates gene expression underlying neurogliomal synaptic communication
Authors: Chakraborty Chaitali , Nissen Itzel , Vincent Craig A. , Hägglund Anna-Carin , Hörnblad Andreas , Remeseiro Silvia 
Published: November 2022

AbstractChromatin organization controls transcription by modulating 3D-interactions between enhancers and promoters in the nucleus. Alterations in epigenetic states and 3D-chromatin organization result in gene expression changes contributing to cancer pathogenesis. Here, we mapped the promoter-enhancer interactome and regulatory landscape of glioblastoma, the most aggressive primary brain tumour. Our data reveals profound rewiring of promoter-enhancer interactions, chromatin accessibility and redistribution of histone marks across the four glioblastoma subtypes. This leads to loss of long-range regulatory interactions and overall activation of promoters, which orchestrate changes in the expression of genes associated to glutamatergic synapses, axon guidance, axonogenesis and chromatin remodeling. SMAD3 and PITX1 emerge as the major transcription factors controlling genes related to synapse organization and axon guidance. Inhibition of SMAD3 and neuronal activity stimulation cooperate to promote cell proliferation of glioblastoma cells in co-culture with glutamatergic neurons. Our findings provide mechanistic insight into the regulatory networks that mediate neurogliomal synaptic communication.
Inhibition of Centrosome Clustering Reduces Cystogenesis and Improves Kidney Function in Autosomal Dominant Polycystic Kidney Disease
Authors: Cheng Tao , Mariappan Aruljothi , Langner Ewa , Shim Kyuhwan , Gopalakrishnan Jay , Mahjoub Moe R. 
Published: November 2022

AbstractAutosomal Dominant Polycystic Kidney Disease (ADPKD) is an inherited monogenic disorder accounting for ∼5% of patients with renal failure. Yet, therapeutics for the treatment of ADPKD remain limited. ADPKD tissues display defects in the biogenesis of the centrosome which causes genome instability, aberrant ciliary signaling, and secretion of pro-inflammatory factors that drive cyst growth and fibrosis. Cystic cells form excess centrosomes via a process termed centrosome amplification (CA), which often causes abnormal multipolar spindle configurations, mitotic catastrophe, and reduced cell viability. However, cells with CA can suppress multipolarity via “centrosome clustering”, a key mechanism by which cells circumvent apoptosis. Here, we demonstrate that inhibiting centrosome clustering can counteract the proliferation of renal cystic cells with high incidences of CA. Using ADPKD human cells and mouse models, we show that blocking centrosome clustering with two inhibitors, CCB02 and PJ34, blocks cyst initiation and growthin vitroandin vivo. Inhibition of centrosome clustering activates a p53-mediated mitotic surveillance mechanism leading to apoptosis, reduced cyst expansion, interstitial fibrosis, and improved kidney function. Transcriptional analysis of kidneys from treated mice identified pro-inflammatory signaling pathways implicated in CA-mediated cystogenesis and fibrosis. Our results provide the first evidence that centrosome clustering is a cyst-selective target for the improvement of renal morphology and function in ADPKD.
Formamide significantly enhances the efficiency of chemical adenylation of RNA sequencing ligation adaptors
Authors: Hildebrand Samuel R. , Hedger Adam K. , Watts Jonathan K. , Khvorova Anastasia 
Published: November 2022

AbstractPre-adenylated single-stranded DNA ligation adaptors are essential reagents in many next generation RNA sequencing library preparation protocols. These oligonucleotides can be adenylated enzymatically or chemically. Enzymatic adenylation reactions have high yield but are not amendable to scale up. In chemical adenylation, Adenosine 5□-phosphorimidazolide (ImpA) reacts with 5′ phosphorylated DNA. It is easily scalable but gives poor yields, requiring labor-intensive cleanup steps. Here, we describe an improved chemical adenylation method using 95% formamide as the solvent, which results in the adenylation of oligonucleotides with >90% yield. In standard conditions, with water as the solvent, hydrolysis of the starting material to adenosine monophosphate limits the yields. To our surprise, we find that rather than increasing adenylation yields by decreasing the rate of ImpA hydrolysis, formamide does so by increasing the reaction rate between ImpA and 5′-phosphorylated DNA by ∼10 fold. The method described here enables straightforward preparation of chemically adenylated adapters with higher than 90% yield, simplifying reagent preparation for NGS.
Examining Anxiety and Risk-taking in Healthy Male and Female Wistar Rats using Spatial and Temporal Analysis of Elevated Plus Maze
Authors: Sharma Sakshi , Pandey Jyotsna , Jain Suman , Singh Varsha 
Published: November 2022

AbstractThe Elevated Plus Maze (EPM) offers a standard set up for understanding anxiety, unconditioned risk-avoidance in rodents. The animal shows a preference for enclosed safe arms and avoids risky, open arms that evoke anxiety due to elevated platform (unconditioned response to elevation). A few rodent studies aiming to understand sex-skewed representation in anxiety disorders use the maze and report that more females compared to males show high levels of anxiety and risk-avoidance on an elevated platform. Ethograms derived from examining animal behaviour in the EPM provide precise measures of behaviour of interest, enabling objective assessment of anxiety and risk behaviour. We report two new parameters that might be critical for quantitative analysis of EPM task as a measure of anxiety with reference to sex-differences in risk-taking: (a) spatial preference for arms (open & closed) (b) temporal shift in arm preference in task trials. We first report results from the conventionally derived measures confirming that males spent more time in the open arms indicating low anxiety and higher risk-taking. Preferences for the two open and two closed arms were non-uniform for males and females; male showed stronger preference for one of the two risky open arms, and females showed a stronger preference for one of the two safe closed arms. Temporal analyses indicated that males spent more time in open arms in 3 out of 6 time bins (time blocks), and females spent more time in the closed arms in 5 out of 6 time bins (time blocks), however, counter-intuitively, females showed larger increase in time spent in open arms in the last phase potentially indicating greater regulation of anxiety and increased risk-taking. Inclusion of spatial and temporal parameters in EPM studies might improve our understanding of cognitive and biological sex-differences pertaining to anxiety, and risky behaviour.
Predicting Antimicrobial Activity for Untested Peptide-Based Drugs Using Collaborative Filtering and Link Prediction
Authors: Medvedeva Angela , Teimouri Hamid , Kolomeisky Anatoly B. 
Published: November 2022

AbstractThe increase of bacterial resistance to currently available antibiotics has underlined the urgent need to develop new antibiotic drugs. Antimicrobial peptides (AMPs), alone or in combination with other peptides and/or existing antibiotics, have emerged as promising candidates for this task. However, given that there are thousands of known AMPs and an even larger number can be synthesized, it is inefficient to comprehensively test all of them using standard wet lab experimental methods. These observations stimulated an application of machine-learning methods to identify promising AMPs. Currently, machine learning studies frequently combine very different bacteria without considering bacteria-specific features or interactions with AMPs. In addition, the sparsity of current AMP data sets of antimicrobial activity disqualifies the application of traditional machine-learning methods or renders the results unreliable. Here we present a new approach, featuring neighborhood-based collaborative filtering, to predict with high accuracy a given bacteria’s response to untested AMPs, AMP-AMP combinations, and AMP-antibiotic combinations based on similarities between bacterial responses. Furthermore, we also developed a complementary bacteria-specific link approach that can be used to visualize networks of AMP-antibiotic combinations, enabling us to suggest new combinations that are likely to be effective. Our theoretical analysis of AMP physico-chemical features suggests that there is an optimal similarity between two different AMPs that exhibit strong synergistic behavior. This principle, alongside with our specific results, can be applied to find or design effective AMP-AMP combinations that are target-specific.Author summaryIt is well known that combinations of different antimicrobial peptides (AMPs), in comparison to single AMP species, can lead to more efficient antimicrobial activity, but the large number of possible combinations requires the application of efficient machine-learning methods. We developed a new approach consisting of collaborative filtering, link prediction, and AMP feature analysis to predict previously-unknown, bacteria-specific activity of AMP combinations, suggest novel synergistic AMP-antibiotic combinations, and guide future design of effective AMP-AMP combinations.
Variation in diet and microbial exposure shape the performance of the Asian tiger mosquito,Aedes albopictus
Authors: Raquin Vincent , Martin Edwige , Minard Guillaume , Moro Claire Valiente 
Published: November 2022

ABSTRACTAlong their life cycle, mosquitoes colonize different ecological niches with various microorganisms and diet sources that likely modulate their performance(i.e.a set of mosquito fitness-related traits). However, which ecological parameters and how their variations modulate mosquito performance is not completely understood. In this study, we usedAe. albopictussurface-sterilized eggs re-associated or not to conventional bacterial microbiota upon a range of diet concentrations and addressed the impact of microbial inoculum and diet concentration variation on several mosquito performance traits. Results showed that mosquito juvenile survival depends on the interaction between bacterial inoculum load and diet concentration in the breeding water. Exposure to bacteria in rearing water shorten larval development time although it impacted larvae survival in an inoculum and diet concentration-dependent manner. Bacterial composition of larval rearing water was mainly structured by the bacterial inoculum concentration, with some Operational Taxonomic Units abundances correlating with larval traits.Ae. albopictussurvival, development and bacterial community patterns upon gradients of diet and bacterial inoculum illustrated the complex impact of diet-microbiota interaction on mosquito performance. These findings argue the importance of deciphering host-microbe-environment interactions and open promising perspectives to improveAe. albopictuscontrol measures in the field.IMPORTANCEMicrobiota is increasingly recognized as a driving force of metazoan biology, impacting diverse traits including nutrition, behaviour or reproduction. The microbial impact on host nutrition is among the most studied host-microbe interactions although it remains poorly understood in arthropod vectors like mosquitoes. Here, we manipulated mosquito microbiota using gnotobiology to decipher the impact of bacteria and diet on the Asian tiger mosquito,Ae. albopictus.These results are key to understand the link between diet and bacteria concentration on juvenile mosquitoes as well as carry-over effects in adults. They unveil some specific aspects of mosquito-bacteria interactions while opening interesting avenues for vector management of this vector of arboviruses.
Major revisions in pancrustacean phylogeny with recommendations for resolving challenging nodes
Authors: Bernot James P. , Owen Christopher L. , Wolfe Joanna M. , Meland Kenneth , Olesen Jørgen , Crandall Keith A. 
Published: November 2022

AbstractThe clade Pancrustacea, comprising crustaceans and hexapods, is the most diverse group of animals on earth, containing over 80% of animal species. It has been the subject of several recent phylogenomic analyses, but despite analyzing hundreds of genes, relationships within Pancrustacea show a notable lack of stability. Here, the phylogeny is estimated with expanded taxon sampling, particularly of malacostracans, using a precise tree-based approach to infer orthology. Our results show that small changes in taxon sampling have a large impact on phylogenetic estimation. By analyzing only shared orthologs between two slightly different taxon sets, we show that the differences in the resulting topologies are due to the effects of taxon sampling on the phylogenetic reconstruction method, not on ortholog identification. We compare trees resulting from our phylogenomic analyses with those from the literature to explore the large tree space of pancrustacean phylogenetic hypotheses and find that statistical topology tests reject the previously published trees in favor of the ML trees produced here. Our results reject several clades including Caridoida, Eucarida, Multicrustacea, Vericrustacea, and Syncarida. We recover a novel relationship between decapods, euphausiids, and syncarids that we refer to as the Syneucarida. With denser taxon sampling, we find Stomatopoda sister to this clade, which we name Stomatocaridea, dividing Malacostraca into three clades: Leptostraca, Peracarida, and Stomatocaridea. A new Bayesian divergence time estimation is conducted using 13 vetted fossils. We review our results in the context of other pancrustacean phylogenetic hypotheses and highlight the key taxa to sample in future studies.
Quality control for the target decoy approach for peptide identification
Authors: Debrie Elke , Malfait Milan , Gabriels Ralf , Declerq Arthur , Sticker Adriaan , Martens Lennart , Clement Lieven 
Published: November 2022

AbstractReliable peptide identification is key in mass spectrometry (MS) based proteomics. To this end, the target-decoy approach (TDA) has become the cornerstone for extracting a set of reliable peptide-to-spectrum matches (PSMs) that will be used in downstream analysis. Indeed, TDA is now the default method to estimate the false discovery rate (FDR) for a given set of PSMs, and users typically view it as a universal solution for assessing the FDR in the peptide identification step. However, the TDA also relies on a minimal set of assumptions, which are typically never verified in practice. We argue that a violation of these assumptions can lead to poor FDR control, which can be detrimental to any downstream data analysis. We here therefore first clearly spell out these TDA assumptions, and introduce TargetDecoy, a Bioconductor package with all the necessary functionality to control the TDA quality and its underlying assumptions for a given set of PSMs.TOC Graphic
Buffering of genetic dominance by allele-specific protein complex assembly
Authors: Badonyi Mihaly , Marsh Joseph A 
Published: November 2022

AbstractProtein complex assembly often begins while at least one of the subunits is still in the process of being translated. When such cotranslational assembly occurs for homomeric complexes, made up of multiple copies of the same subunit, this will result in complexes whose subunits were translated off of the same mRNA in an allele-specific manner. It has therefore been hypothesised that cotranslational assembly may be able to counter the assembly-mediated dominant-negative effect, whereby the co-assembly of mutant and wild-type subunits “poison” the activity of a protein complex. Here, we address this, showing first that subunits that undergo cotranslational assembly are much less likely to be associated with autosomal dominant relative to recessive disorders. Moreover, we observe that subunits with dominant-negative disease mutations are significantly depleted in cotranslational assembly compared to those associated with loss-of-function mutations. Consistent with this, we also find that complexes with known dominant-negative effects tend to expose their interfaces late during translation, lessening the likelihood of cotranslational assembly. Finally, by combining protein complex properties with other protein-level features, we trained a computational model for predicting proteins likely to be associated with dominant-negative or gain-of-function molecular mechanisms, which we believe will be of considerable utility for protein variant interpretation.
All-or-None Evaluation of Prediction Certainty in Autism
Authors: Reisli Seydanur , Crosse Michael J. , Molholm Sophie 
Published: November 2022

ABSTRACTThe brain generates predictions to prepare for upcoming events. As life is not always 100% predictable, it also estimates a level of certainty for these predictions. Given that autistic individuals resist even small changes in everyday life, we hypothesized impaired tuning of prediction certainty in autism. To study this, EEG was recorded from adolescents and young adults with autism while they performed a probabilistic prediction task in which cue validity was parametrically manipulated. A fully predictable condition (100% cue validity) was contrasted with less predictable conditions (84, 67 and 33% cue validity). Well characterized brain potentials were examined to assess the influence of cue validity on target anticipation (contingent negative variation; CNV), the evaluation of target statistics (P3), and prediction model updating (slow wave; SW). As expected, cue validity systematically influenced the amplitudes of the CNV, P3 and SW in controls. In contrast, cue-validity effects on CNV and SW were substantially reduced in autism. This suggests that although target statistics are accurately registered in autism, as indicated by intact modulation of the P3, they are not effectively applied to generate expectations for upcoming input or model updating. Contrasting the fully predictable with the less predictable conditions, our data suggest that autistic individuals adopted an all-or-none evaluation of certainty of their environment, rather than adjusting certainty of predictions to different levels of environmental statistics. Social responsiveness scores were associated with flexibility in representing prediction certainty, suggesting that impaired representation and updating of prediction certainty may contribute to social difficulties in autism.SIGNIFICANCE STATEMENTThe ability to make predictions is integral to everyday life. Yet, as life is not always 100% predictable and it is also essential to adjust the certainty of these predictions based on the current context. This study reveals that individuals with autism are less efficient in adjusting the certainty of their predictions to the level of predictability of events. Instead, they may adopt an all-or-none evaluation of certainty. Our findings reveal novel insights into the processes underlying impaired predictive processing in autism, which may open the door to developing targeted behavioral interventions and/or non-invasive brain stimulation therapies that help autistic individuals make more accurate predictions to ease social- and rigidity-based symptoms.
Career-washing? Unpacking employer brand promises on social media platforms
Authors: Marcet Alonso Julia , Parsons Elizabeth , Pirani Daniela 
Published: November 2022

Purpose
This paper aims to explore how a global fashion retailer uses a social media platform to build an appeal via a process of online employer branding.

Design/methodology/approach
The study involved a narrative and thematic analysis of posts of a global fashion retailer on LinkedIn. The authors sampled organisational posts and the responses they received over a six-month period.

Findings
The organisation uses carefully curated success stories of “ideal” existing employees to build an appeal based on the values of growth and belonging. While varied, the responses of platform users tend to be limited to brief contributions, questioning the success of the organisation’s attempts at creating an appeal.

Research limitations/implications
The authors argue that employer branding literature needs a new conceptual toolbox, which better reflects the mediated, affective and networked nature of platforms.

Practical implications
To avoid career-washing, employer brands should engage with the networked nature of platforms, fostering authentic conversations with users rather than using platforms merely as a billboard to post content.

Originality/value
The authors theorise the appeal of the employer brand through the concept of the “employer brand promise”. Furthermore, they show how, on social networks, this promise attempts to create value through meaningful engagement. They also conclude by observing how the employer brand promise can act as a form of career-washing, where there is a significant dis-connect between the promise offered and the reality of retail work on the ground.