bluuebunny/crossref_metadata_2025_split huggingface dataset:
Validation of scRNA-seq by scRT-ddPCR using the example ofErbB2in MCF7 cells
Authors: Lange Tobias , Groß Tobias , Jeney Ábris , Scherzinger Julia , Sinkala Elly , Niemöller Christoph , Zimmermann Stefan , Koltay Peter , Stetten Felix von , Zengerle Roland , Jeney Csaba 
Published: June 2022

AbstractSingle-cell RNA sequencing (scRNA-seq) can unmask transcriptional heterogeneity facilitating the detection of rare subpopulations at unprecedented resolution. In response to challenges related to coverage and quantity of transcriptome analysis, the lack of unbiased and absolutely quantitative validation methods hampers further improvements. Digital PCR (dPCR) represents such a method as we could show that the inherent partitioning enhances molecular detections by increasing effective mRNA concentrations. We developed a scRT-ddPCR method and validated it using two breast cancer cell lines, MCF7 and BT-474, and bulk methods.ErbB2, a low-abundant transcript in MCF7 cells, suffers from dropouts in scRNA-seq and thus calculated fold changes are biased. Using our scRT-ddPCR, we could improve the detection ofErbB2and based on the absolute counts obtained we could validate the scRNA-seq fold change. We think this workflow is a valuable addition to the single-cell transcriptomic research toolbox and could even become a new standard in fold change validation because of its reliability, ease of use and increased sensitivity.
Discrimination of conspecific head orientations and learning set formation in Bengalese finches
Authors: Chen Wei , Kamijo Makiko , okanoya Kazuo 
Published: June 2022

AbstractAnimals detect others’ gaze direction, such as predators, prey, and courtship mates, to enable adaptive behavior. However, head movements play a more significant role in gaze shifts in birds than eye movement because of the flat eye shape. Additionally, most birds with laterally placed eyes usually turn the lateral face to the target. Therefore, we used Bengalese finches to examine whether songbirds can discriminate between conspecific frontal and lateral faces and divide head orientations in different angles into two categories. In experiments, birds were trained by operant conditioning to discriminate stimuli consisting of conspecific frontal and lateral head images. Eight out of nine birds finished discrimination training and test sessions. The results indicate that Bengalese finches can discriminate gaze direction by the head orientations. Furthermore, as the number of stimuli set increased, fewer trials were needed to achieve the criteria, which suggests that birds have developed a learning set during the training. However, we did not find a clear discrimination boundary for head orientation categorization.
Structure-based identification of novel histone deacetylase 4 (HDAC4) inhibitors
Authors: Agarwal Rupesh , Pattarawat Pawat , Duff Michael R. , Wang Hwa-Chain Robert , Baudry Jerome , Smith Jeremy C. 
Published: June 2022

AbstractHistone deacetylases (HDACs) are important cancer drug targets. Existing FDA-approved drugs target the catalytic pocket of HDACs, which is conserved across subfamilies (classes) of HDAC. Here, we use molecular modeling approaches to identify and target potential novel pockets specific to Class IIA HDAC-HDAC4 at the interface between HDAC4 and the NCOR protein. These pockets were then targeted using an ensemble docking approach combined with consensus scoring to identify compounds with a different mechanism of binding than the currently known HDAC modulators. Using this approach, 18 compounds predicted in silico to bind to HDAC4’s novel pockets were tested in vivo testing on two cancer cell lines. Of these, 5 compounds decreased cell viability to less than 60%. One inhibited the catalytic activity of HDAC4 but not HDAC3, which belongs to a different family of HDACs (Class I). The most potent compound has an IC50 comparable to the FDA-approved compound SAHA (Vorinostat). While there are currently no known inhibitors reported to bind highly selectively to HDAC4, the present result suggests potential mechanistic and chemical approaches for the development of selective HDAC4 modulators.
Spatiotemporal modeling reveals geometric dependence of AMPAR dynamics on dendritic spine morphology
Authors: Bell M. K. , Lee C. T. , Rangamani P. 
Published: June 2022

AbstractThe modification of neural circuits depends on the strengthening and weakening of synaptic connections. Synaptic strength is often correlated to the density of the ionotropic, glutamateric receptors, AMPAR, (α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor) at the postsynaptic density (PSD). While AMPAR density is known to change based on complex biological signaling cascades, the effect of geometric factors such as dendritic spine shape, size, and curvature remain poorly understood. In this work, we developed a deterministic, spatiotemporal model to study the dynamics of AMPAR during long term potentiation (LTP). This model includes a minimal set of biochemical events that represent the upstream signaling events, trafficking of AMPAR to and from the PSD, lateral diffusion in the plane of the spine membrane, and the presence of an extrasynaptic AMPAR pool. Using idealized and realistic spine geometries, we show that the dynamics and increase of bound AMPAR at the PSD depends on a combination of endo- and exocytosis, membrane diffusion, availability of free AMPAR, and intracellular signaling interactions. We also found non-monotonic relationships between spine volume and change in AMPAR at the PSD, suggesting that spines restrict changes in AMPAR to optimize resources and prevent runaway potentiation.Significance StatementSynaptic plasticity involves dynamic biochemical and physical remodeling of small protrusions called dendritic spines along the dendrites of neurons. Proper synaptic functionality within these spines requires changes in receptor number at the synapse, which has implications for down-stream neural functions, such as learning and memory formation. In addition to being signaling subcompartments, spines also have unique morphological features that can play a role in regulating receptor dynamics on the synaptic surface. We have developed a spatiotemporal model that couples biochemical signaling and receptor trafficking modalities in idealized and realistic spine geometries to investigate the role of biochemical and biophysical factors in synaptic plasticity. Using this model, we highlight the importance of spine size and shape in regulating bound AMPAR dynamics that govern synaptic plasticity, and predict how spine shape might act to reset synaptic plasticity as a built-in resource optimization and regulation tool.
Achieving single nucleotide sensitivity in direct hybridization genome imaging
Authors: Wang Yanbo , Cottle Wayne T. , Wang Haobo , Gavrilov Momcilo , Zou Roger S. , Bailey Scott , Ha Taekjip 
Published: June 2022

AbstractDirect visualization of point mutations in situ can be informative for studying genetic diseases and nuclear biology. We describe a direct hybridization genome imaging method with single-nucleotide sensitivity, sgGOLDFISH, which leverages the high cleavage specificity of enhanced Cas9 combined with a single extended guide RNA to load a superhelicase and reveal probe binding sites through local denaturation. Using sgGOLDFISH, we identified base-editor-modified and unmodified progeroid fibroblasts from a heterogeneous population, validated the identification through progerin immunofluorescence, and demonstrated accurate sub-nuclear localization of point mutations.
Working memory and reaction time variability mediate the relationship between polygenic risk and ADHD traits in a general population sample
Authors: Moses Mia , Tiego Jeggan , Demontis Ditte , Walters G. Bragi , Stefansson Hreinn , Stefansson Kari , Børglum Anders D. , Arnatkeviciute Aurina , Bellgrove Mark A. 
Published: June 2022

AbstractEndophenotypes are heritable and quantifiable traits indexing genetic liability for a disorder. Here, we examined three potential endophenotypes, working memory function, response inhibition and reaction time variability, for attention-deficit hyperactivity disorder (ADHD) measured as a dimensional latent trait in a large general population sample derived from the Adolescent Brain and Cognition Developmental study. The genetic risk for ADHD was estimated using polygenic risk scores (PRS) whereas ADHD traits were quantified as a dimensional continuum using Bartlett factor score estimates, derived from Attention Problems items from the Child Behaviour Checklist and Effortful Control items from the Early Adolescent Temperament Questionnaire-Revised. The three candidate cognitive endophenotypes were quantified using task-based performance measures. Higher ADHD PRSs were associated with higher ADHD traits, as well as poorer working memory performance and increased reaction time variability. Lower working memory performance, poorer response inhibition, and increased reaction time variability were associated with more pronounced ADHD traits. Working memory and reaction time variability partially statistically mediated the relationship between ADHD PRS and ADHD traits, explaining 14% and 16% of the association, respectively. The mediation effect was specific to the genetic risk for ADHD and did not generalise to genetic risk for four other major psychiatric disorders. Together, these findings provide robust evidence from a large general population sample that working memory and reaction time variability can be considered endophenotypes for ADHD that mediate the relationship between ADHD PRS and ADHD traits.
Whole-genome and mitogenome based in silico analysis of select Plasmodium and identification of a novel drug molecule against the malaria parasite
Authors: Sarkar Indrani , Rathore Saurabh Singh , Singh Gyan Dev , Singh Ram Pratap 
Published: June 2022

AbstractMalaria, caused by a parasite known as Plasmodium, is one of the leading causes of death, worldwide, especially in the third world countries of Africa and Asia. Plasmodium does not only infect humans but also reptiles, birds and other mammals. However, they are the secondary hosts for this parasite. The primary host of Plasmodium is female Anopheles mosquitoes. Long term researchers have formulated drugs against this deadly pathogen but the current emergence of multi-drug resistance strains of Plasmodium has created a recurring concern. Identification of new drug molecules and understanding their mechanism of action is an urgent need to combat this battle. However, for that, we need to first understand the genomic strategies taken up by Plasmodium to survive the host immune system. With the advancement of high-throughput sequencing techniques, the whole genomes of Plasmodium have been sequenced which can help us in advancing our strategies against Plasmodium. In this study, we performed a thorough analysis of the genomic features of Plasmodium along with its evolution. This revealed a codon biased co-evolution among the parasite and respective hosts. Reverse ecology and protein-protein interactions were studied among Plasmodium and Homo sapiens revealing a complex biological interaction among them governing the host-parasite interaction as well as drug resistance capability among Plasmodium. The molecular docking and simulation studies have found a new drug-target site within mitogenome coding proteins. Those sites were targeted with Cymbopogonol, a phyto-compound derived from Cymbopogon (Lemongrass). Along with Cymbopogonol few other Cymbopogon derived compounds were also found to be effective as new anti-malarial drug molecules. This is the first report on the effect of Cymbopogon derived compounds on Plasmodium and is open for a clinical trial.
Role of the drug efflux pump in the intrinsic cefiderocol resistance of Pseudomonas aeruginosa
Authors: Ikawa Sota , Yamasaki Seiji , Morita Yuji , Nishino Kunihiko 
Published: June 2022

AbstractCefiderocol is a novel siderophore cephalosporin antibiotic exhibiting activities against carbapenem-resistant Gram-negative bacteria including Pseudomonas aeruginosa and Enterobacteriaceae. Drug efflux pumps are reportedly involved in both intrinsic and acquired drug resistance, although their role in bacterial cefiderocol susceptibility remains poorly understood. In this study, we investigated how drug efflux pumps contribute to bacterial cefiderocol susceptibility using the efflux pump(s)-deficient and overexpressing strains of P. aeruginosa, Escherichia coli, and Salmonella enterica. We observed that the mexAB-oprM-deficient P. aeruginosa mutant displayed increased cefiderocol susceptibility compared to the wild-type strain. The overexpression of mexAB-oprM or mexXY-oprM in the mexAB-oprM-deficient mutant increased the MIC value of cefiderocol. Furthermore, the pump inhibitor phenylalanine-arginine β-naphthylamide increased cefiderocol susceptibility in wild-type P. aeruginosa whereas it did not affect the susceptibility of the mexAB-oprM-deficient mutant. These data indicate that the MexAB-OprM drug efflux system contributes to the intrinsic cefiderocol resistance of P. aeruginosa. In addition, MexXY-OprM partially complemented the function of MexAB-OprM in the cefiderocol susceptibility, when expressed.
The kinetic landscape of human transcription factors
Authors: Mamrak Nicholas E , Alerasool Nader , Griffith Daniel , Holehouse Alex S , Taipale Mikko , Lionnet Timothée 
Published: June 2022

AbstractCell-to-cell variability is shaped by transcription dynamics because genes are transcribed in bursts interspersed with inactive periods. The stochasticity of bursting means that genes transcribed in rare bursts exhibit more heterogeneity at the single cell level than genes that burst often 1, 2. Transcription starts with the binding of Transcription Factors (TFs) to specific sequence motifs where they recruit the transcription machinery 3. In some systems, individual TF binding events temporally correlate with the firing of transcriptional bursts, defining the target gene’s frequency and duration 4–6. However, in the absence of methods that assess the impact of different TFs on transcription dynamics at the same genetic loci, it remains unclear whether DNA binding kinetics are the sole determinant of bursting. Here we develop an imaging-based synthetic recruitment assay, CRISPRburst, and measure how 92 human TFs impact bursting kinetics. We show that TFs recruited to chromatin under identical conditions generate diverse bursting signatures, some TFs increasing the probability of the gene turning on while others increase the number of mRNA molecules transcribed per burst. We find that the association of TFs with specific protein partners determines their bursting output, and train a model to predict the kinetic signatures of all human TFs. These kinetic signatures can be used as a TF classification system complementary to existing families based on DNA binding domains. Additionally, kinetic signatures provide a rational framework to design synthetic activators, model transcription regulation, and understand expression heterogeneity.
Effect of channel density, inverse solutions and connectivity measures on EEG resting-state networks: a simulation study
Authors: Allouch Sahar , Kabbara Aya , Duprez Joan , Khalil Mohamad , Modolo Julien , Hassan Mahmoud 
Published: June 2022

AbstractAlong with the study of brain activity evoked by external stimuli, the past two decades witnessed an increased interest in characterizing the spontaneous brain activity occurring during resting conditions. The identification of the connectivity patterns in this so-called “resting-state” has been the subject of a great number of electrophysiology-based studies, using the Electro/Magneto-Encephalography (EEG/MEG) source connectivity method. However, no consensus has been reached yet regarding a unified (if possible) analysis pipeline, and several involved parameters and methods require cautious tuning. This is particularly challenging when different choices induce significant discrepancy in results and drawn conclusions, thereby hindering reproducibility of neuroimaging research. Hence, our objective in this study was to evaluate some of the parameters related to the EEG source connectivity analysis and shed light on their implications on the accuracy of the resulting networks. We simulated, using neural mass models, EEG data corresponding to two of the resting-state networks (RSNs), namely the default mode network (DMN) and the dorsal attentional network (DAN). We investigated the impact of five channel densities (19, 32, 64, 128, 256), three inverse solutions (weighted minimum norm estimate (wMNE), exact low resolution brain electromagnetic tomography (eLORETA), and linearly constrained minimum variance (LCMV) beamforming) and four functional connectivity measures (phase-locking value (PLV), phase-lag index (PLI), and amplitude envelope correlation (AEC) with and without source leakage correction), on the correspondence between reconstructed and reference networks. We showed that, with different analytical choices, a high variability is present in the results. More specifically, our results show that a higher number of EEG channels significantly increased the accuracy of the reconstructed networks. Additionally, our results showed a significant variability in the performance of the tested inverse solutions and connectivity measures. In our specific simulation context, eLORETA and wMNE combined with AEC computed between orthogonalized time series exhibited the highest performance in terms of similarity between reconstructed and reference connectivity matrices. Results were similar for both DMN and DAN. We believe that this work could be useful for the field of electrophysiology connectomics, by shedding light on the challenge of analytical variability and its consequences on the reproducibility of neuroimaging studies.
Assessing the influence of the Mediterranean diet on dental calculus microbiome composition: a pilot study
Authors: Innocenti Gabriel , Martino Maria Elena , Stellini Edoardo , di Fiore Adolfo , Quagliariello Andrea 
Published: June 2022

AbstractHuman oral microbiome harbours hundreds of bacterial species, which, during evolution, assembled in different niches, such as the microbiome of saliva, tongue, hard palate, gingiva and dental plaque. Among these, saliva has been the most studied ecological niche of the oral microbiome. In this frame, scientific research has demonstrated that several factors concur to determine the saliva microbial composition, including diet, systemic diseases and drugs. However, the influence of such variables on other oral niches, such as the dental calculus, a calcified derivative of dental plaque, is still unexplored.During the last decade, dental calculus has become the primary target for evolutionary microbiome studies because of its ability to keep both bacterial DNA and dietary molecules (i.e., proteins and starch). As a consequence, dental calculus is now considered a powerful tool for obtaining information about oral microbiome composition, diet and individual health status in past populations, making it also appealing for clinical research.Here, we provide the first clinical study, to our knowledge, assessing the inter-variability of dental calculus microbiome in 40 patients. Samples were collected during routine dental inspection and analysed through 16S amplicon sequencing. In addition, we investigated the relationship between oral microbiome and host. Specifically, we tested the influence of Mediterranean diet style on the composition and functional pathways of oral bacteria, with the aim to test the dental calculus as a clinical bio-marker for diet impact and health status.
Normalizing need not be the norm: count-based math for analyzing single-cell data
Authors: Church Samuel H. , Mah Jasmine L. , Wagner Günter , Dunn Casey W. 
Published: June 2022

AbstractCounting transcripts of mRNA is a key method of observation in modern biology. With advances in counting transcripts in single cells (single-cell RNA sequencing or scRNA-seq), these data are routinely used to identify cells by their transcriptional profile, and to identify genes with differential cellular expression. Because the total number of transcripts counted per cell can vary for technical reasons, the first step of standard scRNA-seq workflows is to normalize by sequencing depth, transforming counts into proportional abundances. The primary objective of this step is to reshape the data such that cells with similar biological proportions of transcripts end up with similar transformed measurements. But there is growing concern that normalization and other transformations result in unintended distortions that hinder both analyses and the interpretation of results. This has led to an intense focus on optimizing methods for normalization and transformation of scRNA-seq data. Here we take an alternative approach, by avoiding normalization altogether. We abandon the use of distances to compare cells, and instead use a restricted algebra, motivated by measurement theory and abstract algebra, that preserves the count nature of the data. We demonstrate that this restricted algebra is sufficient to draw meaningful and practical comparisons of gene expression through the use of the dot product and other elementary operations. This approach sidesteps many of the problems with common transformations, and has the added benefit of being simpler and more intuitive. We implement our approach in the package countland, available in python and R. By explicitly considering counts in terms of their measurement process, we avoid and overcome many challenges in modern RNA-seq and open new avenues for the analysis of these data.
RPTPγ is a redox-regulated suppressor of promigratory EGFR signaling
Authors: Joshi Maitreyi S. , Stanoev Angel , Soetje Birga , Huebinger Jan , Zorina Veronika , Roßmannek Lisaweta , Michel Kirsten , Bastiaens Philippe I. H. 
Published: June 2022

AbstractSpatially-organized interaction dynamics between proto-oncogenic epidermal growth factor receptor (EGFR) and protein tyrosine phosphatases (PTPs) determine EGFR’s phosphorylation response to growth factors and thereby cellular behavior within developing tissues. We show here, that and how the coupling between EGFR and RPTPγ activity leads to migratory signaling responses to very low, physiological growth factor stimuli while suppressing aberrant, spontaneous signaling. Single cell imaging of EGFR phosphorylation and PTP oxidation revealed that RPTPγ fully suppresses spontaneous EGFR phosphorylation, while EGF-induced NADPH-oxidase activity enables promigratory signaling responses at the plasma membrane by H2O2-mediated oxidative inhibition of RPTPγ’s phosphatase activity. The EGF-dependent toggle switch dynamics between interacting EGFR monomers and RPTPγ thereby enables autocatalytically amplified phosphorylation responses to very low, physiological, EGF levels even at sparse receptor expression. This signaling mechanism is distinct from the proliferative signaling stemming from liganded endosomal EGFR complexes at high growth factor concentrations. Accordingly, RPTPγ knock-out results in spontaneous promigratory EGFR signaling but loss of proliferative signaling. We thereby provide evidence of RPTPγ’s suppressor function of oncogenic, promigratory EGFR-signaling from the plasma membrane.