bluuebunny/crossref_metadata_2025 huggingface dataset:
The SERCA residue Glu340 mediates inter-domain communication that guides Ca2+transport
Authors: Geurts Maxwell M. G. , Clausen Johannes D. , Arnou Bertrand , Montigny Cedric , Lenoir Guillaume , Corey Robin A. , Jaxel Christine , Møller Jesper V. , Nissen Poul , Andersen Jens Peter , le Maire Marc , Bublitz Maike
Published: June 2020

The sarco(endo)plasmic reticulum Ca2+-ATPase (SERCA) is a P-type ATPase that transports Ca2+from the cytosol into the SR/ER lumen, driven by ATP. This primary transport activity depends on tight coupling between movements of the transmembrane helices forming the two Ca2+binding sites and of the cytosolic headpiece mediating ATP hydrolysis. We have addressed the molecular basis for this intramolecular communication by analyzing the structure and functional properties of the SERCA mutant E340A. The mutated Glu340 residue is strictly conserved among the P-type ATPase family of membrane transporters and is located at a seemingly strategic position at the interface between the phosphorylation domain and the cytosolic ends of five out of SERCA’s ten transmembrane helices. The mutant displays a marked slowing of the Ca2+-binding kinetics, and its crystal structure in the presence of Ca2+and ATP analogue reveals a rotated headpiece, altered connectivity between the cytosolic domains and altered hydrogen bonding pattern around residue 340. Supported by molecular dynamics simulations, we conclude that the E340A mutation causes a stabilization of the Ca2+sites in a more occluded state, hence displaying slowed dynamics. This finding underpins a crucial role of Glu340 in inter-domain communication between the headpiece and the Ca2+-binding transmembrane region.
Only two out of five articles by New Zealand researchers are free-to-access: a multiple API study of access, citations, cost of Article Processing Charges (APC), and the potential to increase the proportion of open access
Authors: White Richard Kenneth Alistair , Angelo Anton , Fitchett Deborah Jane , Fraser Moira , Hayes Luqman , Howie Jess , Richardson Emma , White Bruce Duncan
Published: June 2020

We studied journal articles published by researchers at all eight of New Zealand universities in 2017 to determine how many were freely accessible on the web. We wrote software code to harvest data from multiple sources, code that we now share to enable others to reproduce our work on their own sample set. In May 2019, we ran our code to determine which of the 2017 articles were open at that time and by what method; where those articles would have incurred an Article Processing Charge (APC) we calculated the cost if those charges had been paid. Where articles were not freely available we determined whether the policies of publishers in each case would have allowed deposit in a non-commercial repository (Green open access). We also examined citation rates for different types of access. We found that, of our 2017 sample set, about two out of every five articles were freely accessible without payment or subscription (41%). Where research was explicitly said to be funded by New Zealand’s major research funding agencies, the proportion was slightly higher at 45%. Where open articles would have incurred an APC we estimated an average cost per article of USD1,682 (for publications where all articles require an APC, that is, Gold open access) and USD2,558 (where APC payment is optional, Hybrid open access) at a total estimated cost of USD1.45m. Of the paid options, Gold is by far more common for New Zealand researchers (82% Gold, 18% Hybrid). In terms of citations, our analysis aligned with previous studies that suggest a correlation between publications being freely accessible and, on balance, slightly higher rates of citation. This is not seen across all types of open access, however, with Diamond OA achieving the lowest rates. Where articles were not freely accessible we found that a very large majority of them (88% or 3089 publications) could have been legally deposited in an institutional repository. Similarly, only in a very small number of cases had a version deposited in the repository of a New Zealand university made the difference between the publication being freely accessible or not (125 publications). Given that most New Zealand researchers support research being open, there is clearly a large gap between belief and practice in New Zealand’s research ecosystem.
Integration of genetic, transcriptomic, and clinical data provides insight into 16p11.2 and 22q11.2 CNV genes
Authors: Vysotskiy Mikhail , Zhong Xue , Miller-Fleming Tyne W. , Zhou Dan ,   Autism Working Group of the Psychiatric Genomics Consortium,   Bipolar Disorder Working Group of the Psychiatric Genomics Consortium,   Schizophrenia Working Group of the Psychiatric Genomics Consortium, Cox Nancy J. , Weiss Lauren A
Published: June 2020

Deletions and duplications of the multigenic 16p11.2 and 22q11.2 copy number variants (CNVs) are associated with brain-related disorders including schizophrenia, intellectual disability, obesity, bipolar disorder, and autism spectrum disorder (ASD). The contribution of individual CNV genes to each of these phenotypes is unknown, as is the contribution of CNV genes to subtler health impacts. Hypothesizing that DNA copy number acts via RNA expression, we attempted a novelin silicofine-mapping approach in non-carriers using both GWAS and biobank data. We first asked whether expression level of a CNV gene impacts risk for a known brain-related phenotype(s). Using transcriptomic imputation, we tested for association within GWAS for schizophrenia, IQ, BMI, bipolar disorder, and ASD. We found individual genes in 16p11.2 associated with schizophrenia, BMI, and IQ (SPN), using conditional analysis to identifyINO80Eas the driver of schizophrenia, andSPNandINO80Eas drivers of BMI. Second, we used a biobank containing electronic health data to compare the medical phenome of CNV carriers to controls within 700,000 individuals to investigate a spectrum of health effects, identifying novel and previously observed traits. Third, we used genotypes for over 48,000 biobank individuals to perform phenome-wide association studies between imputed expressions of 16p11.2 and 22q11.2 genes and over 1,500 health traits, finding seventeen significant gene-trait pairs, including psychosis (NPIPB11, SLX1B) and mood disorders (SCARF2), and overall enrichment of mental traits. Our results demonstrate how integration of genetic and clinical data aids in understanding CNV gene function, and implicate pleiotropy and multigenicity in CNV biology.
N-glycosylation network construction and analysis to modify glycans on the spike S glycoprotein of SARS-CoV-2
Authors: Krishnan Sridevi , Krishnan Giri P
Published: June 2020

Background

The spike S-protein of SARS-CoV-2 is N-glycosylated. The N-glycan structure and composition of this glycoprotein influence how the virus interacts with host cells.

Objective

To identify a putative N-glycan biosynthesis pathway of SARS-CoV-2 (HEK293 cell recombinant) from previously published mass spectrometric studies, and to identify what effect blocking some enzymes has on the overall glycoprotein profile. Finally, our goal was to provide the biosynthesis network, and glycans in easy-to-use format for further glycoinformatics work.

Methods

We reconstructed the glycosylation network based on previously published empirical data using GNAT, a glycosylation network analysis tool. Our compilation of the network tool had 23 glycosyltransferase and glucosidase enzymes, and could infer the pathway of glycosylation machinery based on glycans identified in the virus spike protein. Once the glycan biosynthesis pathway was generated, we simulated the effect of blocking specific enzymes - Mannosidase-II and alpha-1,6-fucosyltransferase to see how they would affect the biosynthesis network.

Results

Of the 23 enzymes, a total of 12 were involved in glycosylation of SARS-CoV-2 - Man-Ia, MGAT1, MGAT2, MGAT4, MGAT5, B4GalT, B4GalT, Man II, SiaT, ST3GalI, ST3GalVI and FucT8. Blocking enzymes resulted in a substantially modified glycan profile of the protein.

Conclusions

A network analysis of N-glycan biosynthesis of SARS-CoV-2 spike protein shows an elaborate enzymatic pathway with several intermediate glycans, along with the ones identified by mass spectrometric studies. Variations in the final N-glycan profile of the virus, given its site-specific microheterogeneity, could be a factor in the host response to the infection and response to antibodies. Here we provide all the resources generated - the glycans derived from mass spectrometry and intermediate glycans in glycoCT xml format, and the biosynthesis network for future drug and vaccine development work.
A classification-based approach to estimate the number of resting fMRI dynamic functional connectivity states
Authors: Saha Debbrata K. , Damaraju Eswar , Rashid Barnaly , Abrol Anees , Plis Sergey M. , Calhoun Vince D.
Published: June 2020

Recent work has focused on the study of dynamic (vs static) brain connectivity in resting fMRI data. In this work, we focus on temporal correlation between time courses extracted from coherent networks or components called functional network connectivity (FNC). Dynamic functional network connectivity (dFNC) is most commonly estimated using a sliding window-based approach to capture short periods of FNC change. These data are then clustered to estimate transient connectivity patterns or states. Determining the number of states is a challenging problem. The elbow criterion is a widely used approach to determine the optimal number of states. In our work, we present an alternative approach that evaluates classification (e.g. healthy controls versus patients) as a measure to select the optimal number of states (clusters). We apply different classification strategies to perform classification between healthy controls (HC) and patients with schizophrenia (SZ) for different numbers of states (i.e. varying the model order in the clustering algorithm). We compute cross-validated accuracy for different model orders to evaluate the classification performance. Our results are consistent with our earlier work which shows that overall accuracy improves when dynamic connectivity measures are used separately or in combination with static connectivity measures. Results also show that the optimal model order for classification is different from that using the standard k-means model selection method and that such optimization improves resulting in cross-validated accuracy. The optimal model order obtained from the proposed approach also gives significantly improved classification performance over the traditional model selection method. In sum, the observed results suggest that if one’s goal is to perform classification, using the proposed approach as a criterion for selecting the optimal number of states in dynamic connectivity analysis leads to improved accuracy in hold-out data.
CoronaHiT: High throughput sequencing of SARS-CoV-2 genomes
Authors: Baker Dave J. , Aydin Alp , Le-Viet Thanh , Kay Gemma L. , Rudder Steven , Martins Leonardo de Oliveira , Tedim Ana P. , Kolyva Anastasia , Diaz Maria , Alikhan Nabil-Fareed , Meadows Lizzie , Bell Andrew , Gutierrez Ana Victoria , Trotter Alexander J. , Thomson Nicholas M. , Gilroy Rachel , Griffith Luke , Adriaenssens Evelien M. , Stanley Rachael , Charles Ian G. , Elumogo Ngozi , Wain John , Prakash Reenesh , Meader Emma , Mather Alison E. , Webber Mark A. , Dervisevic Samir , Page Andrew J. , O’Grady Justin
Published: June 2020

The COVID-19 pandemic has spread to almost every country in the world since it started in China in late 2019. Controlling the pandemic requires a multifaceted approach including whole genome sequencing to support public health interventions at local and national levels. One of the most widely used methods for sequencing is the ARTIC protocol, a tiling PCR approach followed by Oxford Nanopore sequencing (ONT) of up to 96 samples at a time. There is a need, however, for a flexible, platform agnostic, method that can provide multiple throughput options depending on changing requirements as the pandemic peaks and troughs. Here we present CoronaHiT, a method capable of multiplexing up to 96 small genomes on a single MinION flowcell or >384 genomes on Illumina NextSeq, using transposase mediated addition of adapters and PCR based addition of barcodes to ARTIC PCR products. We demonstrate the method by sequencing 95 and 59 SARS-CoV-2 genomes for routine and rapid outbreak response runs, respectively, on Nanopore and Illumina platforms and compare to the standard ARTIC LoCost nanopore method. Of the 154 samples sequenced using the three approaches, genomes with ≥ 90% coverage (GISAID criteria) were generated for 64.3% of samples for ARTIC LoCost, 71.4% for CoronaHiT-ONT, and 76.6% for CoronaHiT-Illumina and have almost identical clustering on a maximum likelihood tree. In conclusion, we demonstrate that CoronaHiT can multiplex up to 96 SARS-CoV-2 genomes per MinION flowcell and that Illumina sequencing can be performed on the same libraries, which will allow significantly higher throughput. CoronaHiT provides increased coverage for higher Ct samples, thereby increasing the number of high quality genomes that pass the GISAID QC threshold. This protocol will aid the rapid expansion of SARS-CoV-2 genome sequencing globally, to help control the pandemic.
Structures of the Cmr-β Complex Reveal the Regulation of the Immunity Mechanism of Type III-B CRISPR-Cas
Authors: Sofos Nicholas , Feng Mingxia , Stella Stefano , Pape Tillmann , Fuglsang Anders , Lin Jinzhong , Huang Qihong , Li Yingjun , She Qunxin , Montoya Guillermo
Published: June 2020

Cmr-β is a Type III-B CRISPR-Cas complex that upon target RNA recognition unleashes a multifaceted immune response against invading genetic elements, including ssDNA cleavage, cyclic oligoadenylate synthesis, and also a unique UA-specific ssRNA hydrolysis by the Cmr2 subunit. Here, we present the structure-function relationship of Cmr-β unveiling how binding of the target RNA regulates the Cmr2 activities. CryoEM analysis revealed the unique subunit architecture of Cmr-β and captured the complex in different conformational stages of the immune response, including the non-cognate and cognate target-RNA bound complexes. The binding of the target RNA induces a conformational change of Cmr2, which together with the complementation between the 5’-handle in the crRNA and the 3’-antitag of the target RNA, activate different configurations in a unique loop of the Cmr3 subunit, which acts as an allosteric sensor signaling the self vs. non-self recognition. These findings highlight the diverse defense strategies of Type III complexes.
Epithelial Morphogenesis Driven by Cell-Matrix vs. Cell-Cell Adhesion
Authors: Wang Shaohe , Matsumoto Kazue , Yamada Kenneth M.
Published: June 2020

Many embryonic organs undergo epithelial morphogenesis to form tree-like hierarchical structures. However, it remains unclear what drives the budding and branching of stratified epithelia, such as in embryonic salivary gland and pancreas. Here, we performed live-organ imaging of mouse embryonic salivary glands at single-cell resolution to reveal that budding morphogenesis is driven by expansion and folding of a distinct epithelial surface cell sheet characterized by strong cell-matrix adhesions and weak cell-cell adhesions. Profiling of single-cell transcriptomes of this epithelium revealed spatial patterns of transcription underlying these cell adhesion differences. We then synthetically reconstituted budding morphogenesis by experimentally suppressing E-cadherin expression and inducing basement membrane formation in 3D spheroid cultures of engineered cells, which required β1 integrin-mediated cell-matrix adhesion for successful budding. Thus, stratified epithelial budding, the key first step of branching morphogenesis, is driven by an overall combination of strong cell-matrix adhesion and weak cell-cell adhesion by peripheral epithelial cells.
DNA origami demonstrate the unique stimulatory power of single pMHCs as T-cell antigens
Authors: Hellmeier Joschka , Platzer Rene , Eklund Alexandra S. , Schlichthärle Thomas , Karner Andreas , Motsch Viktoria , Kurz Elke , Bamieh Victor , Brameshuber Mario , Preiner Johannes , Jungmann Ralf , Stockinger Hannes , Schütz Gerhard J. , Huppa Johannes B. , Sevcsik Eva
Published: June 2020

T-cells detect with their T-cell antigen receptors (TCRs) the presence of rare peptide/MHC complexes (pMHCs) on the surface of antigen presenting cells (APCs). How they convert a biochemical interaction into a signaling response is poorly understood, yet indirect evidence pointed to the spatial antigen arrangement on the APC surface as a critical factor. To examine this, we engineered a biomimetic interface based on laterally mobile functionalized DNA origami platforms, which allow for nanoscale control over ligand distances without interfering with the cell-intrinsic dynamics of receptor clustering. We found that the minimum signaling unit required for efficient T-cell activation consisted of two ligated TCRs within a distance of 20 nanometers, if TCRs were stably engaged by monovalent antibody fragments. In contrast, antigenic pMHCs stimulated T-cells robustly as well-isolated entities. These results identify the minimal requirements for effective TCR-triggering and validate the exceptional stimulatory potency of transiently engaging pMHCs.
In situclassification of cell types in human kidney tissue using 3D nuclear staining
Authors: Woloshuk Andre , Khochare Suraj , Almulhim Aljohara Fahad , McNutt Andrew , Dean Dawson , Barwinska Daria , Ferkowicz Michael , Eadon Michael T. , Kelly Katherine J. , Dunn Kenneth W. , Hasan Mohammad A. , El-Achkar Tarek M. , Winfree Seth
Published: June 2020

To understand the physiology and pathology of disease, capturing the heterogeneity of cell types within their tissue environment is fundamental. In such an endeavor, the human kidney presents a formidable challenge because its complex organizational structure is tightly linked to key physiological functions. Advances in imaging-based cell classification may be limited by the need to incorporate specific markers that can link classification to function. Multiplex imaging can mitigate these limitations, but requires cumulative incorporation of markers, which may lead to tissue exhaustion. Furthermore, the application of such strategies in large scale 3-dimensional (3D) imaging is challenging. Here, we propose that 3D nuclear signatures from a DNA stain, DAPI, which could be incorporated in most experimental imaging, can be used for classifying cells in intact human kidney tissue. We developed an unsupervised approach that uses 3D tissue cytometry to generate a large training dataset of nuclei images (NephNuc), where each nucleus is associated with a cell type label. We then devised various supervised machine learning approaches for kidney cell classification and demonstrated that a deep learning approach outperforms classical machine learning or shape-based classifiers. Specifically, a custom 3D convolutional neural network (NephNet3D) trained on nuclei image volumes achieved a balanced accuracy of 80.26%. Importantly, integrating NephNet3D classification with tissue cytometry allowedin situvisualization of cell type classifications in kidney tissue. In conclusion, we present a tissue cytometry and deep learning approach forin situclassification of cell types in human kidney tissue using only a DNA stain. This methodology is generalizable to other tissues and has potential advantages on tissue economy and non-exhaustive classification of different cell types.
Modulation of A2aR Oligomerisation by Conformational State and PIP2Interactions Revealed by MD Simulations and Markov Models
Authors: Song Wanling , Duncan Anna L. , Sansom Mark S.P.
Published: June 2020

G protein-coupled receptors (GPCRs) play key roles in cellular signalling. GPCRs are suggested to form dimers and higher order oligomers in response to activation. However, we do not fully understand GPCR activation at larger scales and in anin vivocontext. We have characterised oligomeric configurations of the adenosine 2a receptor (A2aR) by combining large-scale molecular dynamics simulations with Markov state models. Receptor activation results in enhanced oligomerisation, more diverse oligomer populations, and a more connected oligomerisation network. The active state conformation of the A2aR shifts protein-protein association interfaces to those involving intracellular loop ICL3 and transmembrane helix TM6. Binding of PIP2to A2aR stabilises protein-protein interactions via PIP2-mediated association interfaces. These results indicate that A2aR oligomerisation is responsive to the local membrane lipid environment. This in turn suggests a modulatory effect on A2aR whereby a given oligomerisation profile favours the dynamic formation of specific supra-molecular signalling complexes.
Noise-induced scaling in skull suture interdigitation
Authors: Naroda Yutoh , Endo Yoshie , Yoshimura Kenji , Ishii Hiroshi , Ei Shin-Ichiro , Miura Takashi
Published: June 2020

Sutures, the thin, soft tissue between skull bones, serve as the major craniofacial growth centers during postnatal development. In a newborn skull, the sutures are straight; however, as the skull develops, the sutures wind dynamically to form an interdigitation pattern. Moreover, the final winding pattern had been shown to have fractal characteristics. Although various molecules involved in suture development have been identified, the mechanism underlying the pattern formation remains unknown. In a previous study, we reproduced the formation of the interdigitation pattern in a mathematical model combining an interface equation and a convolution kernel. However, the generated pattern had a specific characteristic length, and the model was unable to produce a fractal structure with the model.

In the present study, we focused on the anterior part of the sagittal suture and formulated a new mathematical model with time–space-dependent noise that was able to generate the fractal structure. We reduced our previous model to represent the linear dynamics of the centerline of the suture tissue and included a time–space-dependent noise term. We showed theoretically that the final pattern from the model follows a scaling law due to the scaling of the dispersion relation in the full model, which we confirmed numerically. Furthermore, we observed experimentally that stochastic fluctuation of the osteogenic signal exists in the developing skull, and found that actual suture patterns followed a scaling law similar to that of the theoretical prediction.

Author summary

Skull sutures (thin, undifferentiated tissue between bones) act as the growth centers for the skull. Sutures are straight at birth but later develop an interdigitated pattern that ultimately becomes a fractal structure. While our previous mathematical model of sutures generated a periodic pattern, the mechanism underlying the fractal structure formation remained to be elucidated. Here, we focused only on the anterior part of the sagittal suture and formulated a reduced model representing the initial linear phase of pattern formation with the addition of a time–space-dependent noise term. We showed analytically that the model generates patterns with a scaling law. This result was confirmed numerically and experimentally.
Evaluation of origin of driving force for loop formation in a chromatin fiber
Authors: Yokota Hiroshi , Tachikawa Masashi
Published: June 2020

This article has been withdrawn by bioRxiv owing to a technical error that created a duplicate posting of this manuscript. Please see doi:https://doi.org/10.1101/2020.06.24.168757to access the preprint.
Adult survival is reduced when endogenous period deviates from 24h in a non-human primate (Microcebus murinus), depending on sex and season
Authors: Hozer Clara , Perret Martine , Pavard Samuel , Pifferi Fabien
Published: June 2020

Circadian rhythms are ubiquitous attributes across living organisms and allow the coordination of internal biological functions with optimal phases of the environment, suggesting a significant adaptive advantage. The endogenous period calledtaulies close to 24h and is thought to be implicated in individuals’ fitness: according to the circadian resonance theory, fitness is reduced whentaugets far to 24h. In this study, we measured the endogenous period of 142 mouse lemurs (Microcebus. murinus), and analyzed how it affects their survival. We found different effects according to sex and season. No impact oftauon mortality was found in females. However, in males, the deviation oftaufrom 24h substantially increased mortality, particularly during the inactive season (winter). These results, comparable to other observations in mice or drosophila, show that captive gray mouse lemurs enjoy better fitness when their circadian period closely matches the environmental periodicity. In addition to their deep implications in health and aging research, these results raise further ecological and evolutionary issues regarding the relationships between fitness and circadian clock.
Genomes of Thaumarchaeota from deep sea sediments reveal specific adaptations of three independently evolved lineages
Authors: Kerou Melina , Ponce-Toledo Rafael I. , Zhao Rui , Abby Sophie S. , Hirai Miho , Nomaki Hidetaka , Takaki Yoshihiro , Nunoura Takuro , Jørgensen Steffen L. , Schleper Christa
Published: June 2020

Marine sediments represent a vast habitat for complex microbiomes. Among these, ammonia oxidizing archaea (AOA) of the phylum Thaumarchaeota are one of the most common, yet little explored inhabitants, that seem extraordinarily well adapted to the harsh conditions of the subsurface biosphere. We present 11 metagenome-assembled genomes of the most abundant AOA clades from sediment cores obtained from the Atlantic Mid-Ocean ridge flanks and Pacific abyssal plains. Their phylogenomic placement reveals three independently evolved clades within the orderCa.Nitrosopumilales, of which no cultured representative is known yet. In addition to the gene sets for ammonia oxidation and carbon fixation known from other AOA, all genomes encode an extended capacity for the conversion of fermentation products that can be channeled into the central carbon metabolism, as well as uptake of amino acids probably for protein maintenance or as an ammonia source. Two lineages encode an additional (V-type) ATPase and a large repertoire of gene repair systems that may allow to overcome challenges of high hydrostatic pressure. We suggest that the adaptive radiation of AOA into marine sediments occurred more than once in evolution and resulted in three distinct lineages with particular adaptations to this extremely energy limiting and high-pressure environment.
Systems genetic analysis of binge-like eating in a C57BL/6J x DBA/2J-F2 cross
Authors: Yao Emily J. , Babbs Richard K. , Kelliher Julia C. , Luttik Kimberly P. , Damaj M. Imad , Mulligan Megan K. , Bryant Camron D.
Published: June 2020

Objective

Binge eating is a heritable quantitative trait associated with eating disorders (ED) and refers to the rapid consumption of a large quantity of energy-dense food that is associated with loss of control, anxiety, and depression. Binge Eating Disorder is the most common ED in adults in the US; however, the genetic basis is unknown. We previously identified robust mouse inbred strain differences between C57BL/6J and DBA/2J in binge-like eating (BLE) of sweetened palatable food(PF) in an intermittent access, conditioned place preference paradigm.

Methods

To map the genetic basis of BLE, we phenotyped and genotyped 128 C57BL/6J x DBA/2J-F2 mice.

Results

We identified a quantitative trait locus (QTL) on chromosome 13 influencing progressive changes in body weight across training days (LOD = 5.5; 26-39 cM). We also identified two sex-combined QTLs influencing PF intake on chromosome 5 (LOD = 5.6; 1.5-LOD interval = 21-28 cM) and 6 (LOD = 5.3; 1.5-LOD interval = 50-59 cM). Furthermore, sex-specific analyses revealed that the chromosome 6 locus was driven by males (1.5-LOD interval: 52-59 cM) and identified a female-selective QTL for BLE on chromosome 18 (LOD = 4.1; 1.5-LOD interval: 23-35 cM). Systems genetic analysis of the chromosome 6 locus for BLE using GeneNetwork legacy trait datasets from BXD recombinant inbred strains identifiedAdipor2andPlxnd1as two positional, functional, biological candidate genes.

Discussion

We identified genetic loci influencing BLE. Future studies will phenotype BXD recombinant inbred strains to fine map loci and support candidate gene nomination and validation.
Cell cycle checkpoints cooperate to suppress DNA and RNA associated molecular pattern recognition and anti-tumor immune responses
Authors: Chen Jie , Harding Shane M , Natesan Ramakrishnan , Tian Lei , Benci Joseph L , Li Weihua , Minn Andy J , Asangani Irfan A , Greenberg Roger A
Published: June 2020

The DNA dependent pattern recognition receptor, cGAS mediates communication between genotoxic stress and the immune system. Mitotic chromosome missegregation is an established stimulator of cGAS activity, however, it is unclear if progression through mitosis is required for cancer cell intrinsic activation of immune mediated anti-tumor responses. Moreover, it is unknown if disruption of cell cycle checkpoints can restore responses in cancer cells that are recalcitrant to DNA damage induced inflammation. Here we demonstrate that prolonged cell cycle arrest at the G2-mitosis boundary from either CDK1 inhibition or excessive DNA damage prevents inflammatory stimulated gene expression and immune mediated destruction of distal tumors. Remarkably, DNA damage induced inflammatory signaling is restored in a cGAS-and RIG-I-dependent manner upon concomitant disruption of p53 and the G2 checkpoint. These findings link aberrant cell progression and p53 loss to an expanded spectrum of damage associated molecular pattern recognition and have implications for the design of rational approaches to augment antitumor immune responses.
Infrared Nanospectroscopy Reveals the Molecular Interaction Fingerprint of an Aggregation Inhibitor with Single Aβ42 Oligomers
Authors: Ruggeri Francesco Simone , Habchi Johnny , Chia Sean , Vendruscolo Michele , Knowles Tuomas P. J.
Published: June 2020

Very significant efforts have been devoted in the last twenty years to developing compounds that can interfere with the aggregation pathways of proteins related to misfolding disorders, including Alzheimer’s and Parkinson’s diseases. However, no disease-modifying drug has become available for clinical use to date for these conditions. One of the main reasons for this failure is the incomplete knowledge of the molecular mechanisms underlying the process by which small molecules interact with protein aggregates and interfere with their aggregation pathways. Here, we leverage the single molecule level morphological and chemical sensitivity of infrared nanospectroscopy to provide the first direct measurement of the interaction between single Aβ42 oligomeric and fibrillar species and an aggregation inhibitor, bexarotene, originally an anticancer drug capable recently shown to be able to inhibit Aβ42 aggregation in animal models of Alzheimer’s disease. Our results demonstrate that the carbonyl group of this compound interacts with Aβ42 aggregates through a single hydrogen bond. These results establish infrared nanospectroscopy as powerful tool in structure-based drug discovery for protein misfolding diseases.
Membrane interactions accelerate the self-aggregation of huntingtin exon 1 fragments in a polyglutamine length-dependent manner
Authors: Marquette A. , Bechinger B.
Published: June 2020

The accumulation of aggregated protein is a typical hallmark of many human neurodegenerative disorders including Huntington’s disease. Misfolding of the amyloidogenic proteins gives rise to self-assembled complexes and fibers. The huntingtin protein is characterized by a segment of consecutive glutamines, which when exceeding a certain number of residues results in the occurrence of the disease. Furthermore, it has also been demonstrated that the 17-residue amino-terminal domain of the protein (htt17), located upstream of this polyglutamine tract, strongly correlates with aggregate formation and pathology. Here we demonstrate that membrane interactions strongly accelerate the oligomerization and β-amyloid fibril formation of htt17-polyglutamine segments. By using a combination of biophysical approaches the kinetics of fibre formation has been quantitatively investigated and found to be strongly dependent to the presence of lipids, the length of the polyQ expansion and the polypeptide-to-lipid ratio. Finally, the implications for therapeutic approaches are discussed.

Statement of significance

The quantitative analysis of the aggregation kinetics of amino-terminal fragments of huntingtin demonstrate the importance of the 17-residue amino-terminal membrane anchor and a resulting dominant effect of membranes in promoting the aggregation of polyglutamines. Other parameters further modulating the association kinetics are the length of the polyglutamine stretch and the peptide concentration. The findings can have important impact on finding new therapies to treat Huntington’s and other polyglutamine related diseases.
Integration of viral transcriptome sequencing with structure and sequence motifs predicts novel regulatory elements in SARS-CoV-2
Authors: Cox Brian J.
Published: June 2020

In the last twenty years, three separate coronaviruses have left their typical animal hosts and became human pathogens. An area of research interest is coronavirus transcription regulation that uses an RNA-RNA mediated template-switching mechanism. It is not known how different transcriptional stoichiometries of each viral gene are generated. Analysis of SARS-CoV-2 RNA sequencing data from whole RNA transcriptomes identified TRS dependent and independent transcripts. Integration of transcripts and 5’-UTR sequence motifs identified that the pentaloop and the stem-loop 3 were also located upstream of spliced genes. TRS independent transcripts were detected as likely non-polyadenylated. Additionally, a novel conserved sequence motif was discovered at either end of the TRS independent splice junctions. While similar both SARS viruses generated similar TRS independent transcripts they were more abundant in SARS-CoV-2. TRS independent gene regulation requires investigation to determine its relationship to viral pathogenicity.
How does the strength of selection influence genetic correlations ?
Authors: Chantepie Stéphane , Chevin Luis-Miguel
Published: June 2020

Genetic correlations between traits can strongly impact evolutionary responses to selection, and may thus impose constraints on adaptation. Theoretical and empirical work has made it clear that, without strong linkage, genetic correlations at evolutionary equilibrium result from an interplay of correlated pleiotropic effects of mutations, and correlational selection favoring combinations of trait values. However, it is not entirely clear how the strength of stabilizing selection influences this compromise between mutation and selection effects on genetic correlations. Here, we show that the answer to this question crucially depends on the intensity of genetic drift. In large, effectively infinite populations, genetic correlations are unaffected by the strength of selection, regardless of whether the genetic architecture involves common small-effect mutations (Gaussian regime), or rare large-effect mutations (House-of-Cards regime). In contrast in finite populations, the strength of selection does affect genetic correlations, by shifting the balance from drift-dominated to selection-dominated evolutionary dynamics. The transition between these domains depends on mutation parameters to some extent, but with a similar dependence of genetic correlation on the strength of selection. Our results are particularly relevant for understanding how senescence shapes patterns of genetic correlations across ages, and genetic constraints on adaptation during colonization of novel habitats.
Single-axon level automatic segmentation and feature extraction from immuhistochemical images of peripheral nerves
Authors: Tóth Viktor , Jayaprakash Naveen , Abbas Adam , Khan Ariba , Zanos Stavros , Zanos Theodoros P.
Published: June 2020

Quantitative descriptions of the morphology and structure of peripheral nerves is central in the development of bioelectronic devices interfacing the nerves. While histological procedures and microscopy techniques yield high-resolution detailed images of individual axons, automated methods to extract relevant information at the single-axon level are not widely available. We implemented a segmentation algorithm that allows for subsequent feature extraction in immunohistochemistry (IHC) images of peripheral nerves at the single fiber scale. These features include short and long cross-sectional diameters, area, perimeter, thickness of surrounding myelin and polar coordinates of single axons within a nerve or nerve fascicle. We evaluated the performance of our algorithm using manually annotated IHC images of 27 fascicles of the swine cervical vagus; the accuracy of single-axon detection was 82%, and of the classification of fiber myelination was 89%.
JAGGED1 Stimulates Cranial Neural Crest Cell Osteoblast Commitment Pathways and Bone Regeneration Independent of Canonical NOTCH Signaling
Authors: Kamalakar Archana , McKinney Jay M. , Duron Daniel Salinas , Amanso Angelica M. , Ballestas Samir A. , Drissi Hicham M. , Willett Nick J. , Bhattaram Pallavi , García Andrés J. , Wood Levi B. , Goudy Steven L.
Published: June 2020

Craniofacial bone loss is a complex clinical problem with limited regenerative solutions. Currently, BMP2 is used as a bone-regenerative therapy in adults, but in pediatric cases of bone loss, it is not FDA-approved due to concerns of life-threatening inflammation and cancer. Development of a bone-regenerative therapy for children will transform our ability to reduce the morbidity associated with current autologous bone grafting techniques. We discovered that JAGGED1 (JAG1) induces cranial neural crest (CNC) cell osteoblast commitment during craniofacial intramembranous ossification, suggesting that exogenous JAG1 delivery is a potential craniofacial bone-regenerative approach. In this study, we found that JAG1 delivery using synthetic hydrogels containing O9-1 cells, a CNC cell line, into critical-sized calvarial defects in C57BL/6 mice provided robust bone-regeneration. Since JAG1 signals through canonical (Hes1/Hey1) and non-canonical (JAK2) NOTCH pathways in CNC cells, we used RNAseq to analyze transcriptional pathways activated in CNC cells treated with JAG1±DAPT, a NOTCH-canonical pathway inhibitor. JAG1 upregulated expression of multiple NOTCH canonical pathway genes (Hes1), which were downregulated in the presence of DAPT. JAG1 also induced bone chemokines (Cxcl1), regulators of cytoskeletal organization and cell migration (Rhou), signaling targets (STAT5), promoters of early osteoblast cell proliferation (Prl2c2, Smurf1andEsrra), and, inhibitors of osteoclasts (Id1). In the presence of DAPT, expression levels ofHes1andCxcl1were decreased, whereas,Prl2c2, Smurf1, Esrra, RhouandId1remain elevated, suggesting that JAG1 induces osteoblast proliferation through these non-canonical genes. Pathway analysis of JAG1+DAPT-treated CNC cells revealed significant upregulation of multiple non-canonical pathways, including the cell cycle, tubulin pathway, regulators ofRunx2initiation and phosphorylation of STAT5 pathway. In total, our data show that JAG1 upregulates multiple pathways involved in osteogenesis, independent of the NOTCH canonical pathway. Moreover, our findings suggest that JAG1 delivery using a synthetic hydrogel, is a bone-regenerative approach with powerful translational potential.
Variability of dynamic patterns of cortical excitability in schizophrenia: A test-retest TMS-EEG study
Authors: Naim-Feil Jodie , Peled Abraham , Freche Dominik , Hess Shmuel , Grinshpoon Alexander , Levit-Binnun Nava , Moses Elisha
Published: June 2020

Background

Altered stimuli processing is a key feature of schizophrenia. Application of concurrent transcranial magnetic stimulation (TMS) with electroencephalography (TMS-EEG) is an effective stimulus which allows direct measurement of the cortical response within a millisecond time resolution. Test-retest TMS-EEG studies present evidence of high reproducibility in healthy controls (HC), however, this stability of response has not been examined in schizophrenia.

Objective

The current study maps TMS-evoked patterns of cortical excitability in schizophrenia and examine whether these cortical patterns are amenable to change as symptoms of schizophrenia improve.

Methods

One hundred single-pulse TMS and 100 sham pulses were applied to frontal regions of 19 schizophrenia in-patients and 26 HC while electroencephalography data were simultaneously acquired. Medication and schizophrenia symptoms were reported. This protocol was repeated across three sessions (1 week apart) for each participant. The TMS-evoked cortical response of each participant was averaged and compared between groups.

Results

Schizophrenia patients showed reduced cortical excitability at early time-windows and increased excitability at later time-windows. Increased excitability at later windows was associated with heightened symptom severity. Schizophrenia patients showed an increased variability in cortical response over sessions relative to HC. Increased change in cortical response from session 1 to session 3 correlated with symptom improvement.

Conclusions

Schizophrenia patients presented with abnormal patterns of cortical excitability when processing TMS stimuli. These dynamic patterns of cortical response were amenable to change as symptoms of schizophrenia improved. Further research into electrophysiological biomarkers of symptom improvement is hoped to improve current diagnosis and treatment models of schizophrenia.
Validation of questionnaires and rating scales used in medicine: Protocol for a systematic review of burnout self-reported measures
Authors: Marca Sandy Carla , Paatz Paola , Györkös Christina , Cuneo Félix , Bugge Merete Drevvatne , Godderis Lode , Bianchi Renzo , Canu Irina Guseva
Published: June 2020

Background

In the era of evidence-based medicine, decision-making about treatment of individual patients involves conscious, specific, and reasonable use of modern, best evidences. Diagnostic tests are usually obeying to the well-established quality standards of reproducibility and validity. Conversely, it could be tedious to assess the validation studies of tests used for diagnosis of mental and behavioral disorders. This work aims at establishing a methodological reference framework for the validation process of diagnostic tools for mental disorders. We implemented this framework as part of the protocol for the systematic review of burnout self-reported measures. The objectives of this systematic review are (a) to assess the validation processes used in each of the selected burnout measures, and (b) to grade the evidence of the validity and psychometric quality of each burnout measure. The optimum goal is to select the most valid measure(s) for use in medical practice and epidemiological research.

Methods

The review will consist in systematic searches in MEDLINE, PsycINFO, and EMBASE databases. Two independent authors will screen the references in two phases. The first phase will be the title and abstract screening, and the second phase the full-text reading. There will be 4 inclusion criteria for the studies. Studies will have to (a) address the psychometric properties of at least one of the eight validated burnout measures (b) in their original language (c) with sample(s) of working adults (18 to 65 years old) (d) greater than 100. We will assess the risk of bias of each study using the Consensus-based Standards for the selection of health Measurement Instruments checklist. The outcomes of interest will be the face validity, response validity, internal structure validity, convergent validity, discriminant validity, predictive validity, internal consistency, test-retest reliability, and alternate form reliability, enabling assessing the psychometric properties used to validate the eight concerned burnout measures. We will examine the outcomes using the reference framework for validating measures of mental disorders. Results will be synthetized descriptively and, if there is enough homogenous data, using a meta-analysis.

Ethics and dissemination

We will publish this review in a peer-reviewed journal. A report will be prepared for the health practitioners and scientists and disseminated through the Network on the Coordination and Harmonization of European Occupational Cohorts (https://www.cost.eu/actions/CA16216,http://omeganetcohorts.eu/) and the Network of scientists from Swiss universities working in different areas of stress (https://www.stressnetwork.ch/).

PROSPERO registration number

CRD42019124621
Early prediction of liver disease using conventional risk factors and gut microbiome-augmented gradient boosting
Authors: Liu Yang , Meric Guillaume , Havulinna Aki S. , Teo Shu Mei , Ruuskanen Matti , Sanders Jon , Zhu Qiyun , Tripathi Anupriya , Verspoor Karin , Cheng Susan , Jain Mo , Jousilahti Pekka , Vazquez-Baeza Yoshiki , Loomba Rohit , Lahti Leo , Niiranen Teemu , Salomaa Veikko , Knight Rob , Inouye Michael
Published: June 2020

Gut microbiome sequencing has shown promise as a predictive biomarker for a wide range of diseases, including classification of liver disease and severity grading. However, the potential of gut microbiota for prospective risk prediction of liver disease has not been assessed. Here, we utilise shallow gut metagenomic sequencing data of a large population-based cohort (N=>7,115) and ∼15 years of electronic health register follow-up together with machine-learning to investigate the predictive capacity of gut microbial predictors, individually and in conjunction with conventional risk factors, for incident liver disease and alcoholic liver disease. Separately, conventional and microbiome risk factors showed comparable predictive capacity for incident liver disease. However, microbiome augmentation of conventional risk factor models using gradient boosted classifiers significantly improved performance, with average AUROCs of 0.834 for incident liver disease and 0.956 for alcoholic liver disease (AUPRCs of 0.185 and 0.304, respectively). Disease-free survival analysis showed significantly improved stratification using microbiome-augmented risk models as compared to conventional risk factors alone. Investigation of predictive microbial signatures revealed a wide range of bacterial taxa, including those previously associated with hepatic function and disease. This study supports the potential clinical validity of gut metagenomic sequencing to complement conventional risk factors for risk prediction of liver diseases.