bluuebunny/crossref_metadata_2025 huggingface dataset:
StrVCTVRE: A supervised learning method to predict the pathogenicity of human genome structural variants
Authors: Sharo Andrew G. , Hu Zhiqiang , Sunyaev Shamil R. , Brenner Steven E.
Published: May 2020

Background

Whole genome sequencing resolves many clinical cases where standard diagnostic methods have failed. However, at least half of these cases remain unresolved after whole genome sequencing. Structural variants (SVs; genomic variants larger than 50 base pairs) of uncertain significance are the genetic cause of a portion of these unresolved cases. As sequencing methods using long or linked reads become more accessible and structural variant detection algorithms improve, clinicians and researchers are gaining access to thousands of reliable SVs of unknown disease relevance. Methods to predict the pathogenicity of these SVs are required to realize the full diagnostic potential of long-read sequencing.

Results

To address this emerging need, we developed StrVCTVRE to distinguish pathogenic SVs from benign SVs that overlap exons. In a random forest classifier, we integrated features that capture gene importance, coding region, conservation, expression, and exon structure. We found that features such as expression and conservation are important but are absent from SV classification guidelines. We leveraged multiple resources to construct a size-matched training set of rare, putatively benign and pathogenic SVs. StrVCTVRE performs accurately across a wide SV size range on independent test sets, which will allow clinicians and researchers to eliminate about half of SVs from consideration while retaining a 90% sensitivity.

Conclusions

We anticipate clinicians and researchers will use StrVCTVRE to prioritize SVs in patients where no SV is immediately compelling, empowering deeper investigation into novel SVs to resolve cases and understand new mechanisms of disease. StrVCTVRE runs rapidly and is available athttps://compbio.berkeley.edu/proj/strvctvre/.
Understanding olfactory dysfunction in COVID-19: Expression of ACE2, TMPRSS2 and Furin in the nose and olfactory bulb in human and mice
Authors: Ueha Rumi , Kondo Kenji , Kagoya Ryoji , Shichino Shigeyuki , Ueha Satoshi , Yamasoba Tatsuya
Published: May 2020

Background

Anosmia is a frequent symptom in coronavirus disease 2019 (COVID-19) patients that generally resolves within weeks. In contrast, the anosmia caused by other upper respiratory infections affects a small proportion of patients and may take months to resolve or never resolve. The mechanisms behind COVID-19-induced olfactory dysfunction remain unknown. Here, we address the unique pathophysiology of COVID-19-associated olfactory dysfunction.

Methods

The expression of ACE2 (virus binding receptor) and TMPRSS2 and Furin (host cell proteases facilitating virus entry) was examined in the nasal mucosa, composed of respiratory mucosa (RM), olfactory mucosa (OM), and olfactory bulb (OB) of mouse and human tissues using immunohistochemistry and gene analyses.

Results

Co-expression of ACE2, TMPRSS2, and Furin was observed in the RM and in the OM, especially in the supporting cells of the olfactory epithelium and the Bowman’s glands. Notably, the olfactory receptor neurons (ORNs) in the OM were positive for ACE2 but almost negative for TMPRSS2 and Furin. Cells in the OB expressed ACE2 strongly and Furin weakly, and did not express TMPRSS2. All three gene expressions were confirmed in the nasal mucosa and OB.

Conclusions

ACE2 was widely expressed in all tissues, whereas TMPRSS2 and Furin were expressed only in certain types of cells and were absent in the ORNs. These findings, together with clinical reports, suggest that COVID-19-related anosmia occurs mainly through sensorineural and central dysfunction and, to some extent, conductive olfactory dysfunction. The expression of ACE2, but not TMPRSS2 or Furin, in ORNs may explain the early recovery from anosmia.
Traffic-derived particulate matter and angiotensin-converting enzyme 2 expression in human airway epithelial cells
Authors: Miyashita L , Foley G , Semple S , Grigg J
Published: May 2020

Background

The mechanism for the association between traffic-derived particulate matter less than 10 microns (PM10) and cases of COVID-19 disease reported in epidemiological studies is unknown. To infect cells, the spike protein of SARS-CoV-2 interacts with angiotensin-converting enzyme 2 (ACE2) on host airway cells. Increased ACE2 expression in lower airway cells in active smokers, suggests a potential mechanism whereby PM10increases vulnerability to COVID-19 disease.

Objective

To assess the effect of traffic-derived PM10on human airway epithelial cell ACE2 expressionin vitro.

Methods

PM10was collected from Marylebone Road (London) using a kerbside impactor. A549 and human primary nasal epithelial cells were cultured with PM10for 2 h, and ACE2 expression (median fluorescent intensity; MFI) assessed by flow cytometry. We included cigarette smoke extract as a putative positive control. Data were analysed by either Mann-Whitney test, or Kruskal-Wallis with Dunn’s multiple comparisons test.

Results

PM10at 10 μg/mL, and 20 μg/mL increased ACE2 expression in A549 cells (P<0.05, 0.01 vs. medium control, respectively). Experiments using a single PM10concentration (10 μg/mL), found increased ACE2 expression in both A549 cells (control vs. PM10, median (IQR) MFI; 470 (0.1 to 1114) vs 6217 (5071 to 8506), P<0.01), and in human primary epithelial cells (0 (0 to 591) vs. 4000 (2610 to 7853), P<0.05). Culture of A549 cells with 5% cigarette smoke extract increased ACE2 expression (n=4, 0 (0 to 28) vs. 9088 (7557 to 15831, P<0.05).

Conclusion

Traffic-related PM10increases the expression of the receptor for SARS-CoV-2 in human respiratory epithelial cells.
Aberrant claudin-6–adhesion signal promotes endometrial cancer progression via estrogen receptor α
Authors: Kojima Manabu , Sugimoto Kotaro , Tanaka Mizuko , Endo Yuta , Ichikawa-Tomikawa Naoki , Kashiwagi Korehito , Kato Hitomi , Honda Tsuyoshi , Furukawa Shigenori , Nishiyama Hiroshi , Watanabe Takafumi , Soeda Shu , Fujimori Keiya , Chiba Hideki
Published: May 2020

Cell adhesion proteins not only maintain tissue integrity but also possess signaling abilities to organize diverse cellular events in physiological and pathological processes; however, the underlying mechanism remains obscure. Among cell adhesion molecules, the claudin (CLDN) family often possesses aberrant expression in various cancers, but the biological relevance and molecular basis have not yet been established. Here, we show that high CLDN6 expression promotes endometrial cancer progression and represents the poor prognostic marker. The second extracellular domain and Y196/200 of CLDN6 were required to recruit and activate Src-family kinases (SFKs) and to stimulate malignant phenotypes. Importantly, we demonstrate that the CLDN6/SFK/PI3K-dependent AKT and SGK (serum- and glucocorticoid-regulated kinase) signalings target Ser518 in the human estrogen receptor α and ligand-independently activate target genes in endometrial cancer cells, resulting in cancer development. The identification of this machinery highlights regulation of the transcription factors by cell adhesion to advance tumor progression.
Pathway-based and phylogenetically adjusted quantification of metabolic interaction between microbial species
Authors: Lam Tony J. , Stamboulian Moses , Han Wontack , Ye Yuzhen
Published: May 2020

Microbial community members exhibit various forms of interactions. Taking advantage of the increasing availability of microbiome data, many computational approaches have been developed to infer bacterial interactions from the co-occurrence of microbes across diverse microbial communities. Additionally, the introduction of genome-scale metabolic models have also enabled the inference of metabolic interactions, such as competition and cooperation, between bacterial species. By nature, phylogenetically similar microbial species are likely to share common functional profiles or biological pathways due to their genomics similarity. Without properly factoring out the phylogenetic relationship, any estimation of the competition and cooperation based on functional/pathway profiles may bias downstream applications.

To address these challenges, we developed a novel approach for estimating the competition and complementarity indices for a pair of microbial species, adjusted by their phylogenetic distance. An automated pipeline, PhyloMint, was implemented to construct competition and complementarity indices from genome scale metabolic models derived from microbial genomes. Application of our pipeline to 2,815 human-gut bacteria showed high correlation between phylogenetic distance and metabolic competition/cooperation indices among bacteria. Using a discretization approach, we were able to detect pairs of bacterial species with cooperation scores significantly higher than the average pairs of bacterial species with similar phylogenetic distances. A network community analysis of high metabolic cooperation but low competition reveals distinct modules of bacterial interactions. Our results suggest that niche differentiation plays a dominant role in microbial interactions, while habitat filtering also plays a role among certain clades of bacterial species.

Author summary

Microbial communities, also known as microbiomes, are formed through the interactions of various microbial species. Utilizing genomic sequencing, it is possible to infer the compositional make-up of communities as well as predict their metabolic interactions. However, because some species are more similarly related to each other, while others are more distantly related, one cannot directly compare metabolic relationships without first accounting for their phylogenetic relatedness. Here we developed a computational pipeline which predicts complimentary and competitive metabolic relationships between bacterial species, while normalizing for their phylogenetic relatedness. Our results show that phylogenetic distances are correlated with metabolic interactions, and factoring out such relationships can help better understand microbial interactions which drive community formation.
Analysis of SARS-CoV-2 RNA-Sequences by Interpretable Machine Learning Models
Authors: Kaden Marika , Bohnsack Katrin Sophie , Weber Mirko , Kudła Mateusz , Gutowska Kaja , Blazewicz Jacek , Villmann Thomas
Published: May 2020

We present an approach to investigate SARS-CoV-2 virus sequences based on alignment-free methods for RNA sequence comparison. In particular, we verify a given clustering result for the GISAID data set, which was obtained analyzing the molecular differences in coronavirus populations by phylogenetic trees. For this purpose, we use alignment-free dissimilarity measures for sequences and combine them with learning vector quantization classifiers for virus type discriminant analysis and classification. Those vector quantizers belong to the class of interpretable machine learning methods, which, on the one hand side provide additional knowledge about the classification decisions like discriminant feature correlations, and on the other hand can be equipped with a reject option. This option gives the model the property of self controlled evidence if applied to new data, i.e. the models refuses to make a classification decision, if the model evidence for the presented data is not given. After training such a classifier for the GISAID data set, we apply the obtained classifier model to another but unlabeled SARS-CoV-2 virus data set. On the one hand side, this allows us to assign new sequences to already known virus types and, on the other hand, the rejected sequences allow speculations about new virus types with respect to nucleotide base mutations in the viral sequences.

Author summary

The currently emerging global disease COVID-19 caused by novel SARS-CoV-2 viruses requires all scientific effort to investigate the development of the viral epidemy, the properties of the virus and its types. Investigations of the virus sequence are of special interest. Frequently, those are based on mathematical/statistical analysis. However, machine learning methods represent a promising alternative, if one focuses on interpretable models, i.e. those that do not act as black-boxes. Doing so, we apply variants of Learning Vector Quantizers to analyze the SARS-CoV-2 sequences. We encoded the sequences and compared them in their numerical representations to avoid the computationally costly comparison based on sequence alignments. Our resulting model is interpretable, robust, efficient, and has a self-controlling mechanism regarding the applicability to data. This framework was applied to two data sets concerning SARS-CoV-2. We were able to verify previously published virus type findings for one of the data sets by training our model to accurately identify the virus type of sequences. For sequences without virus type information (second data set), our trained model can predict them. Thereby, we observe a new scattered spreading of the sequences in the data space which probably is caused by mutations in the viral sequences.
Using a supervised principal components analysis for variable selection in high-dimensional datasets reduces false discovery rates
Authors: Ullah Insha , Mengersen Kerrie , Pettitt Anthony , Liquet Benoit
Published: May 2020

High-dimensional datasets, where the number of variables ‘p’ is much larger compared to the number of samples ‘n’, are ubiquitous and often render standard classification and regression techniques unreliable due to overfitting. An important research problem is feature selection — ranking of candidate variables based on their relevance to the outcome variable and retaining those that satisfy a chosen criterion. In this article, we propose a computationally efficient variable selection method based on principal component analysis. The method is very simple, accessible, and suitable for the analysis of high-dimensional datasets. It allows to correct for population structure in genome-wide association studies (GWAS) which otherwise would induce spurious associations and is less likely to overfit. We expect our method to accurately identify important features but at the same time reduce the False Discovery Rate (FDR) (the expected proportion of erroneously rejected null hypotheses) through accounting for the correlation between variables and through de-noising data in the training phase, which also make it robust to outliers in the training data. Being almost as fast as univariate filters, our method allows for valid statistical inference. The ability to make such inferences sets this method apart from most of the current multivariate statistical tools designed for today’s high-dimensional data. We demonstrate the superior performance of our method through extensive simulations. A semi-real gene-expression dataset, a challenging childhood acute lymphoblastic leukemia (CALL) gene expression study, and a GWAS that attempts to identify single-nucleotide polymorphisms (SNPs) associated with the rice grain length further demonstrate the usefulness of our method in genomic applications.

Author summary

An integral part of modern statistical research is feature selection, which has claimed various scientific discoveries, especially in the emerging genomics applications such as gene expression and proteomics studies, where data has thousands or tens of thousands of features but a limited number of samples. However, in practice, due to unavailability of suitable multivariate methods, researchers often resort to univariate filters when it comes to deal with a large number of variables. These univariate filters do not take into account the dependencies between variables because they independently assess variables one-by-one. This leads to loss of information, loss of statistical power (the probability of correctly rejecting the null hypothesis) and potentially biased estimates. In our paper, we propose a new variable selection method. Being computationally efficient, our method allows for valid inference. The ability to make such inferences sets this method apart from most of the current multivariate statistical tools designed for today’s high-dimensional data.
Transcriptomics and methylomics study on the effect of iodine-containing drug FS-1 onEscherichia coliATCC BAA-196
Authors: Korotetskiy Ilya S. , Jumagaziyeva Ardak B. , Shilov Sergey V. , Kuznetsova Tatyana V. , Myrzabayeva Auyes N. , Iskakbayeva Zhanar A. , Ilin Aleksandr I. , Joubert Monique , Taukobong Setshaba , Reva Oleg N.
Published: May 2020

Background

Recent studies showed promising results on application of iodine-containing nanomicelles, FS-1, against antibiotic resistant pathogens. The effect was studied onEscherichia coliATCC BAA-196.

Materials & methods

RNA sequencing for transcriptomics and the complete genome sequencing by SMRT PacBio RS II technology followed by genome assembly and methylomics study were performed.

Results & conclusions

FS-1 treatedE. colishowed an increased susceptibility to antibiotics ampicillin and gentamicin. The analysis of differential gene regulation showed that possible targets of iodine-containing particles are cell membrane fatty acids and proteins, particularly cytochromes, that leads to oxidative, osmotic and acidic stresses. Cultivation with FS-1 caused gene expression alterations towards anaerobic respiration, increased anabolism and inhibition of many nutrient uptake systems. Identification of methylated nucleotides showed an altered pattern in the FS-1 treated culture. Possible role of transcriptional and epigenetic modifications in the observed increase in susceptibility to gentamicin and ampicillin were discussed.

Lay abstract

New approaches of combatting drug resistance infections are in demand as the development of new antibiotics is in a deep crisis. This study was set out to investigate molecular mechanisms of action of new iodine-containing nano-micelle drug FS-1, which potentially may improve the antibiotic therapy of drug resistant infections. Iodine is one of the oldest antimicrobials and until now there were no reports on development of resistance to iodine. Recent studies showed promising results on application of iodine-containing nano-micelles against antibiotic resistant pathogens as a supplement to antibiotic therapy. The mechanisms of action, however, remain unclear. The collection strainEscherichia coliATCC BAA-196 showing an extended spectrum of resistance to beta-lactam and aminoglycoside antibiotics was used in this study as a model organism. Antibiotic resistance patterns, whole genomes and total RNA sequences of the FS-1 treated (FS) and negative control (NC) variants ofE. coliBAA-196 were obtained and analyzed. FS culture showed an increased susceptibility to antibiotics associated with profound gene expression alterations switching the bacterial metabolism to anaerobic respiration, increased anabolism, osmotic stress response and inhibition of many nutrient uptake systems. Nucleotide methylation pattern were identified in FS and NC cultures. While the numbers of methylated sites in both genomes remained similar, some peculiar alterations were observed in their distribution along chromosomal and plasmid sequences.
CRISPRCasTyper: An automated tool for the identification, annotation and classification of CRISPR-Cas loci
Authors: Russel Jakob , Pinilla-Redondo Rafael , Mayo-Muñoz David , Shah Shiraz A. , Sørensen Søren J.
Published: May 2020

CRISPR-Cas loci encode for highly diversified prokaryotic adaptive defense systems that have recently become popular for their applications in gene editing and beyond. The increasing demand for bioinformatic tools that systematically detect and classify CRISPR-Cas systems has been largely challenged by their complex dynamic nature and rapidly expanding classification. Here, we developed CRISPRCasTyper, a new automated software tool with improved capabilities for identifying and typing CRISPR arrays andcasloci across prokaryotic sequences, based on the latest classification and nomenclature (39 subtypes/variants) (Makarova et al. 2020; Pinilla-Redondo et al. 2019). As a novel feature, CRISPRCasTyper uses a machine learning approach to subtype CRISPR arrays based on the sequences of the direct repeats. This allows the typing of orphan and distant arrays which, for example, are commonly observed in fragmented metagenomic assemblies. Furthermore, the tool provides a graphical output, where CRISPRs andcasoperon arrangements are visualized in the form of colored gene maps, thus aiding annotation of partial and novel systems through synteny. Moreover, CRISPRCasTyper can resolve hybrid CRISPR-Cas systems and detect loci spanning the ends of sequences with a circular topology, such as complete genomes and plasmids. CRISPRCasTyper was benchmarked against a manually curated set of 31 subtypes/variants with a median accuracy of 98.6%. Altogether, we present an up-to-date and freely available software pipeline for significantly improved automated predictions of CRISPR-Cas loci across genomic sequences.

Implementation

CRISPRCasTyper is available through conda and PyPi under the MIT license (https://github.com/Russel88/CRISPRCasTyper), and is also available as a web server (http://cctyper.crispr.dk).
JAG1-NOTCH4 Mechanosensing Drives Atherosclerosis
Authors: Souilhol Celine , Li Xiuying , Canham Lindsay , Roddie Hannah , Pirri Daniela , Ayllon Blanca Tardajos , Chambers Emily V , Dunning Mark J , Ariaans Mark , Li Jin , Fang Yun , Fragiadaki Maria , Ridger Victoria , Serbanovic-Canic Jovana , de Val Sarah , Francis Sheila E. , Chico Timothy JA , Evans Paul C
Published: May 2020

Endothelial cell (EC) sensing of fluid shear stress regulates atherosclerosis, a disease of arteries that causes heart attack and stroke. Atherosclerosis preferentially develops at regions of arteries exposed to low oscillatory shear stress (LOSS), whereas high shear regions are protected. We show using inducible EC-specific genetic deletion in hyperlipidaemic mice that the Notch ligands JAG1 and DLL4 have opposing roles in atherosclerosis. While endothelialJag1promoted atherosclerosis at sites of LOSS, endothelialDll4was atheroprotective. Analysis of porcine and murine arteries and cultured human coronary artery EC exposed to experimental flow revealed that JAG1 and its receptor NOTCH4 are strongly upregulated by LOSS. Functional studies in cultured cells and in mice with EC-specific deletion ofJag1show that JAG1-NOTCH4 signalling drives vascular dysfunction by repressing endothelial repair. These data demonstrate a fundamental role for JAG1-NOTCH4 in sensing LOSS during disease, and suggest therapeutic targeting of this pathway to treat atherosclerosis.
Polarized endosome dynamics engage cytosolic Par-3 and dynein during asymmetric division
Authors: Zhao Xiang , Tong Kai , Chen Xingye , Yang Bin , Li Qi , Dai Zhipeng , Shi Xiaoyu , Seiple Ian B. , Huang Bo , Guo Su
Published: May 2020

Asymmetric cell division (ACD), which produces two daughters with different fates, is fundamental for generating cellular diversity. In the developing embryos of both invertebrates and vertebrates, asymmetrically dividing progenitors generate daughter cells with differential activity of Notch signaling1–7, a key regulator of cell fate decisions8,9. The cell polarity regulator Par-3 is critical for establishing this Notch asymmetry1,4,6, but the underlying mechanisms are not understood. Here, employingin vivotime-lapse imaging in the developing zebrafish forebrain during the mitotic cycle of radial glia, the principal vertebrate neural stem cells10,11, we show that during ACD, endosomes containing the Notch ligand Delta D (Dld) undergo convergent movement toward the cleavage plane, followed by preferential segregation into the posterior (and subsequently basal) Notchhidaughter. This asymmetric segregation requires the activity of Par-3 and the dynein motor complex. Employing label-retention expansion microscopy, we further detect Par-3 in the cytosol in association with the dynein light intermediate chain 1 (DLIC1) on Dld endosomes, suggesting a direct involvement of Par-3 in dynein-mediated polarized transport of Notch signaling endosomes. Our data reveal an unanticipated mechanism by which Par-3 regulates cell fate decision by directly polarizing Notch signaling components during ACD.
The FDA-approved drug Nelfinavir inhibits lytic cell-free transmission of human adenoviruses
Authors: Georgi Fanny , Andriasyan Vardan , Witte Robert , Murer Luca , Hemmi Silvio , Yu Lisa , Grove Melanie , Meili Nicole , Kuttler Fabien , Yakimovich Artur , Turcatti Gerardo , Greber Urs F
Published: May 2020

Adenoviruses (AdVs) are prevalent and give rise to chronic and recurrent disease. The human AdV (HAdV) species B and C, such as HAdV-C2, C5 and B14, cause respiratory disease, and constitute a health threat for immuno-compromised individuals. HAdV-Cs are well known for lysing cells, owing to the E3 CR1-β-encoded adenovirus death protein (ADP). We previously reported a high-throughput image-based screening framework and identified an inhibitor of HAdV-C2 multi-round infection, Nelfinavir Mesylate. Nelfinavir is the active ingredient of Viracept, an FDA-approved inhibitor of the human immuno-deficiency virus (HIV) aspartyl protease, and used to treat acquired immunodeficiency syndrome (AIDS). It is not effective against single round HAdV infections. Here, we show that Nelfinavir inhibits the lytic cell-free transmission of HAdV, indicated by the suppression of comet-shaped infection foci in cell culture. Comet-shaped foci occur upon convection-based transmission of cell-free viral particles from an infected cell to neighbouring uninfected cells. HAdV lacking ADP was insensitive to Nelfinavir, but gave rise to comet-shaped foci indicating that ADP enhances but is not required for cell lysis. This was supported by the notion that HAdV-B14 and B14p1 lacking ADP were highly sensitive to Nelfinavir, although HAdV-A31, B3, B7, B11, B16, B21, D8, D30 or D37 were less sensitive. Conspicuously, Nelfinavir uncovered slow-growing round-shaped HAdV-C2 foci, independent of neutralizing antibodies in the medium, indicative of non-lytic cell-to-cell transmission. Our study demonstrates the repurposing potential of Nelfinavir with post-exposure efficacy against different HAdVs, and describes an alternative non-lytic cell-to-cell transmission mode of HAdV.

Graphical Abstract

Figure 1.
β-catenin perturbations control differentiation programs in mouse embryonic stem cells
Authors: Pedone Elisa , Failli Mario , Gambardella Gennaro , De Cegli Rossella , La Regina Antonella , di Bernardo Diego , Marucci Lucia
Published: May 2020

The Wnt/β-catenin pathway is involved in development, cancer and embryonic stem cell (ESC) maintenance; its dual role in stem cell self-renewal and differentiation is still controversial. Here, by applying anin vitrosystem enabling inducible gene expression control, we report that moderate induction of transcriptionally active exogenous β- catenin in β-catenin null mouse ESCs promotes epiblast-like cell (EpiLC) derivationin vitro. Instead, in wild type cells moderate chemical pre-activation of the Wnt/β-catenin pathway promotes EpiLCin vitroderivation. Finally, we suggest that moderate β- catenin levels in β-catenin null mouse ESCs favour early stem cell commitment towards mesoderm if the exogenous protein is induced only in the ‘ground state’ of pluripotency condition, or endoderm if the induction is maintained during the differentiation. Overall, our results confirm previous findings about the role of β-catenin in pluripotency and differentiation, while indicating a role for its doses in promoting specific differentiation programs.
Spider viscid silk sticks better to superhydrophobic surfaces
Authors: Alicea-Serrano Angela M. , Htut K Zin , Coonfield Alissa J. , Karkosiak Katherine , Dhinojwala Ali , Blackledge Todd A.
Published: May 2020

In a likely coevolutionary arms race, insects evolved a variety of counter strategies to avoid capture by spider webs, while spiders’ evolved innovations web structure and especially their adhesive silks. For instance, insects’ cuticles employ a variety of potential anti-adhesion mechanisms such as the detachable scales of moths and surface waxes and superhydrophobic structures that might resist spreading of glues. In contrast, the viscid capture threads of most spider orb webs are covered with aggregate glue droplets that absorb atmospheric water, tuning glue viscosity to balance the competing demands of surface spreading versus maintaining strong bulk cohesion. Here, we test the hypothesis that superhydrophobicity in insects acts as an anti-adhesion defense against spider silk. We used lotus leaves as a model substrate because its superhydrophobicity outperforms most known insect surfaces. The adhesion of spider capture silk from the web of Larinioides cornutus was studied against three substrates: raw lotus leaves, oxygen plasma treated lotus leaves (hydrophilic lotus), and smooth glass, differing in roughness and chemistry. We found that spider capture silk sticks better to the superhydrophobic lotus than to other surfaces. Both chemistry and physical properties of the leaves contribute to higher adhesion, as raw lotus showed a mean increase in adhesion of 74 % compared to glass, while the similar surface roughness of the hydrophilic lotus increased adhesion by 64 % compared to glass. Thus, evolving a hydrophobic cuticle is unlikely to be a defensive trait used to mitigate the effectiveness of spider webs.
Selective B cell depletion upon intravenous infusion of replication-incompetent anti-CD19 CAR lentivirus
Authors: Rive Craig M. , Yung Eric , Dreolini Lisa , Brown Scott D. , May Christopher G. , Woodsworth Daniel J. , Holt Robert A.
Published: May 2020

Anti-CD19 CAR-T therapy for B cell malignancies has shown clinical success, but a major limitation is the logistical complexity and high cost of manufacturing autologous cell products. If engineered for improved safety, direct infusion of viral gene transfer vectors to initiatein vivoCAR-T transduction, expansion and anti-tumor activity could provide an alternative, universal approach. To explore this approach we administered approximately 20 million replication-incompetent VSV-G lentiviral particles carrying an anti-CD19CAR-2A-GFP transgene comprising either an FMC63 (human) or 1D3 (murine) anti-CD19 binding domain, or a GFP-only control transgene, to wild-type C57BL/6 mice by tail vein infusion. The dynamics of immune cell subsets isolated from peripheral blood were monitored at weekly intervals. We saw emergence of a persistent CAR-transduced CD3+T cell population beginning week 3-4 that reached a maximum of 13.5 +/-0.58% (mean +/-SD) and 7.8 +/-0.76% of the peripheral blood CD3+T cell population in mice infused with ID3-CAR or FMC63-CAR lentivector, respectively, followed by a rapid decline in each case of the B cell content of peripheral blood. Complete B cell aplasia was apparent by week 5 and was sustained until the end of the protocol (week 8). No significant CAR positive populations were observed within other immune cell subsets or other tissues. These results indicate that direct IV infusion of conventional VSV-G pseudotyped lentiviral particles carrying a CD19 CAR transgene can transduce T cells that then fully ablate endogenous B cells in wild type mice.
Clonal Heterogeneity Supports Mitochondrial Metabolism in Pancreatic Cancer
Authors: Halbrook Christopher J. , Thurston Galloway , McCarthy Amy , Nelson Barbara S. , Sajjakulnukit Peter , Krall Abigail S. , Mullen Peter J. , Zhang Li , Batra Sandeep , Viale Andrea , Stanger Ben Z. , Christofk Heather R. , Zhang Ji , di Magliano Marina Pasca , Jorgensen Claus , Lyssiotis Costas A.
Published: May 2020

Pancreatic ductal adenocarcinoma (PDA) is characterized by a heterogenous and densely fibrotic microenvironment. This limits functional vasculature and diffusion of nutrients through the tumor1,2. Accordingly, pancreatic cancer cells develop numerous metabolic adaptations to survive and proliferate in nutrient austere conditions3-7. Subtypes of PDA have been characterized by transcriptional and functional differences8-12, which have been reported to exist within the same tumor13-15. However, it remains unclear if this diversity extends to metabolic programming. Here, using a combination of metabolomic profiling and functional interrogation of metabolic dependencies, we identify two distinct metabolic subclasses within neoplastic populations isolated from a single pancreatic tumor. Furthermore, these populations are poised for metabolic crosstalk, and in examining this, we find an unexpected role for asparagine in maintaining cell proliferation following mitochondrial inhibition. Functionally, when challenged by mitochondrial inhibition, asparagine supplementation increases intracellular levels of asparagine and aspartate, a rate limiting biosynthetic precursor16-18. Conversely, depletion of extracellular asparagine with PEG-asparaginase sensitizes pancreatic tumors to mitochondrial targeting with phenformin. Together, these data extend the concept of metabolic diversity to neoplastic populations within individual tumors, while illustrating a new method of intratumoral communication that supports tumor fitness19,20. Finally, the combination of asparaginase with mitochondrial inhibition could provide a powerful new strategy for this difficult to treat disease.
Polymer modelling unveils the roles of heterochromatin and nucleolar organizing regions in shaping 3D genome organization in Arabidopsis thaliana
Authors: Di Stefano Marco , Nützmann Hans-Wilhelm , Marti-Renom Marc A. , Jost Daniel
Published: May 2020

The 3D genome is characterized by a complex organization made of genomic and epigenomic layers with profound implications on gene regulation and cell function. However, the understanding of the fundamental mechanisms driving the crosstalk between nuclear architecture and (epi)genomic information is still lacking. The plantArabidopsis thalianais a powerful model organism to address these questions owing to its compact genome for which we have a rich collection of microscopy, Chromosome Conformation Capture (Hi-C), and ChIP-seq experiments. Using polymer modelling, we investigate the roles of nucleolus formation and epigenomics-driven interactions in shaping the 3D genome ofA. thaliana. By validation of several predictions with published data, we demonstrate that self-attracting nucleolar organizing regions and repulsive constitutive heterochromatin are major mechanisms to regulate the organization of chromosomes. Simulations also suggest that interphase chromosomes maintain a partial structural memory of the V-shapes, typical of (sub)metacentric chromosomes in anaphase. Additionally, self-attraction between facultative heterochromatin regions facilitates the formation of Polycomb bodies hosting H3K27me3-enriched gene-clusters. Since nucleolus and heterochromatin are highly-conserved in eukaryotic cells, our findings pave the way for a comprehensive characterization of the generic principles that are likely to shape and regulate the 3D genome in many species.
MEKK3-MEK5-ERK5 Signaling Promotes Mitochondrial Degradation
Authors: Craig Jane E. , Miller Joseph N. , Rayavarapu Raju R. , Hong Zhenya , Bulut Gamze B. , Zhuang Wei , Sakurada Sadie Miki , Temirov Jamshid , Low Jonathan A. , Chen Taosheng , Pruett-Miller Shondra M. , Huang Lily Jun-shen , Potts Malia B.
Published: May 2020

Mitochondria are vital organelles that coordinate cellular energy homeostasis and have important roles in cell death. Therefore, the removal of damaged or excessive mitochondria is critical for maintaining proper cellular function. The PINK1-Parkin pathway removes acutely damaged mitochondria through a well-characterized mitophagy pathway, but basal mitochondrial turnover occurs via distinct and less well-understood mechanisms. Here we report that the MEKK3-MEK5-ERK5 kinase cascade is required for mitochondrial degradation in the absence of exogenous damage. We demonstrate that genetic or pharmacological inhibition of the MEKK3-MEK5-ERK5 pathway increases mitochondrial content by reducing lysosome-mediated degradation of mitochondria under basal conditions. We show that the MEKK3-MEK5-ERK5 pathway plays a selective role in basal mitochondrial degradation but is not required for non-selective bulk autophagy, damage-induced mitophagy, or restraint of mitochondrial biogenesis. This illuminates the MEKK3-MEK5-ERK5 pathway as a positive regulator of mitochondrial degradation that acts independently of exogenous mitochondrial stressors.
Favipiravir strikes the SARS-CoV-2 at its Achilles heel, the RNA polymerase
Authors: Shannon A. , Selisko B. , Le NTT , Huchting J. , Touret F. , Piorkowski G. , Fattorini V. , Ferron F. , Decroly E. , Meier C , Coutard B. , Peersen O. , Canard B.
Published: May 2020

The ongoing Corona Virus Disease 2019 (COVID-19) pandemic, caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), has emphasized the urgent need for antiviral therapeutics. The viral RNA-dependent-RNA-polymerase (RdRp) is a promising target with polymerase inhibitors successfully used for the treatment of several viral diseases. Here we show that Favipiravir exerts an antiviral effect as a nucleotide analogue through a combination of chain termination, slowed RNA synthesis and lethal mutagenesis. The SARS-CoV RdRp complex is at least 10-fold more active than any other viral RdRp known. It possesses both unusually high nucleotide incorporation rates and high-error rates allowing facile insertion of Favipiravir into viral RNA, provoking C-to-U and G-to-A transitions in the already low cytosine content SARS-CoV-2 genome. The coronavirus RdRp complex represents an Achilles heel for SARS-CoV, supporting nucleoside analogues as promising candidates for the treatment of COVID-19.
Distinct pathways of homologous recombination controlled by the SWS1-SWSAP1-SPIDR complex
Authors: Prakash Rohit , Sandoval Thomas , Morati Florian , Zagelbaum Jennifer A , Taylor Brett , Wang Raymond , Desclos Emilie C B , Sullivan Meghan R , Rein Hayley L , Bernstein Kara A , Krawczyk Przemek M , Gautier Jean , Modesti Mauro , Vanoli Fabio , Jasin Maria
Published: May 2020

Homology-directed repair (HDR), a critical DNA repair pathway in mammalian cells, is complex, leading to multiple outcomes with different impacts on genomic integrity. However, the factors that control these different outcomes are often not well understood. Here we show that SWS1-SWSAP1-SPIDR controls distinct types of HDR. Despite their requirement for stable assembly of RAD51 recombinase at DNA damage sites, these proteins are not essential for intra-chromosomal HDR, providing insight into why patients and mice with mutations are viable. However, SWS1-SWSAP1-SPIDR is critical for inter-homolog HDR, the first mitotic factor identified specifically for this function. Furthermore, SWS1-SWSAP1-SPIDR drives the high level of sister-chromatid exchange, promotes long-range loss of heterozygosity often involved with cancer initiation, and impels the poor growth of BLM helicase-deficient cells. The relevance of these genetic interactions is evident as SWSAP1 loss prolongsBlm-mutant embryo survival, suggesting a possible druggable target for the treatment of Bloom syndrome.
RADX condenses single-stranded DNA to antagonize RAD51 loading
Authors: Zhang Hongshan , Schaub Jeffrey M. , Finkelstein Ilya J.
Published: May 2020

RADX is a mammalian single-stranded DNA-binding protein that stabilizes telomeres and stalled replication forks. Cellular biology studies have shown that the balance between RADX and Replication Protein A (RPA) activities is critical for DNA replication integrity. RADX is also a negative regulator of RAD51-mediated homologous recombination at stalled forks. However, the mechanism of RADX acting on DNA and its interactions with RPA and RAD51 are enigmatic. Using singlemolecule imaging of the key proteinsin vitro, we reveal that RADX condenses ssDNA filaments, even when the ssDNA is coated with RPA at physiological protein ratios. RADX compacts RPA-coated ssDNA filaments via higher-order assemblies that can capture ssDNAin trans. Furthermore, RADX blocks RPA displacement by RAD51 and prevents RAD51 loading on ssDNA. Our results indicate that RADX is an ssDNA condensation protein that inhibits RAD51 filament formation and may antagonize other ssDNA-binding proteins on RPA-coated ssDNA.
‘Readiness to lead’: a tentative tool for analysis
Authors: Johnston Jenny , Shipway Bradley
Published: May 2020

Purpose

This paper reports on research into Australian school principals' leadership. It explores an emerging construct – that of ‘readiness to lead’ – and showcases the development of a tentative tool for determining school principals' readiness to lead.

Design/methodology/approach

Seven principals from Australian and International Schools were interviewed about their leadership strategies, intentions and expectations for impending school reform. Qualitative analyses using grounded theory and an interpretivist constructivist paradigm were applied.

Findings

The construct of ‘readiness to lead’ emerged during initial analysis and a tool was developed from a compilation of literature on leadership. Findings revealed that five principals were well-aligned with the strategies, intentions and expectations the research literature indicates are characteristic of good leadership. These principals could be regarded as ‘ready to lead’ their schools in significant school reform. An unexpected finding was that the concepts of ‘hope’ and ‘trust’ also played a significant role in leadership. ‘Hope’ appeared important as a major strategy for the less-well aligned principals, whereas mutual ‘trust’ appeared to be evident in the principals with stronger leadership readiness.

Research limitations/implications

The tool warrants peer review and validation; data revealed an emerging construct and review is welcomed. The authors are continuing to research and investigate in this field, and invite further academic dialogue.

Originality/value

The study has explored the fecundity of the tool for analysis, and evaluated the principals' preparedness to lead reform. Having a tool to determine whether and to what degree school principals are ready to lead would be advantageous for the profession.
Cost-risk contingency framework for managing cost overrun in metropolitan projects: using fuzzy-AHP and simulation
Authors: Afzal Farman , Yunfei Shao , Junaid Danish , Hanif Muhammad Shehzad
Published: May 2020

Purpose

Risk analysis plays a vital role in controlling and managing cost overruns in complex construction projects, particularly where uncertainty is high. This study attempts to address an important issue of cost overrun that encountered by metropolitan rapid transit projects in relation to the significance of risk involved under high uncertainty.

Design/methodology/approach

In order to solve cost overrun problems in metropolitan transit projects and facilitate the decision-makers for effective future budgeting, a cost-risk contingency framework has been designed using fuzzy logic, analytical hierarchy process and Monte Carlo simulation.

Findings

Initially, a hierarchical breakdown structure of important complexity-driven risk factors has been conceptualized herein using relative importance index. Later, a proposed cost-risk contingency framework has investigated the expected total construction cost in order to consider the additional budgeted cost required to mitigate the risk consequences for particular project activity. The results of cost-risk analysis imply that poor design issues, an increase in material prices and delays in relocating facilities show higher dependency and increase the risk of cost overrun in metropolitan transit projects.

Practical implications

The findings and implication for project managers could possibly be achieved by assuming the proposed cost-risk contingency framework under high uncertainty of cost found in this research. Furthermore, this procedure may be used by experts from other engineering domains by replacing and considering the complex relationship between complexity-risk factors.

Originality/value

This study contributes to the body of knowledge by providing a practical contingency model to identify and evaluate the additional risk cost required to compute total construction cost for getting stability in future budgeting.
Reliability evaluation of repairable weighted system using interval valued universal generating function
Authors: Bisht Soni , Singh S. B. , Tamta Renu
Published: May 2020

Purpose

To find the reliability characteristics of repairable weighted (u,v)- out-of-(x,y) system using the interval valued universal generating function (IUGF).

Design/methodology/approach

In this paper (u,v)-out-of-(x,y) system is an extension of thek-out-of-nsystem. Here, the interval valued universal generating function (UGF) is present and the corresponding operators are defined.

Findings

The present paper proposes a interval valued universal generating function (IUGF) to compute the reliability indices of the considered system. The current study investigates the reliability and sensitivity of the proposed system with respect to system parameters by applying Markov process with the help of the interval valued UGF approach.

Originality/value

In this work, the considered system, i.e. repairable weighted (u,v)-of-the- (x,y) is the extension ofk-out-of-nsystem for the assessment of reliability characteristics using the interval valued UGF.
Anatomy of an effective workplace health intervention: a comprehensive new model
Authors: Hennessey Sean Peter , Rehman Laurene
Published: May 2020

Purpose

This study proposes a new model, called the Integrated Human Health Model (IHHM), to improve the design and effectiveness of Workplace Health Promotion (WHP) interventions.

Design/methodology/approach

Eighteen participants were purposefully selected from 44 participants in a 2.5-day WHP intervention targeting multiple health behaviours (MHB). The intervention has shown to improve quality of life and health-related behaviours in rigorous studies. Qualitative data collection methods were observations, repeat semi-structured interviews and weekly e-journals collected over three months. Template analysis was used to develop the IHHM describing participants' experiences.

Findings

The IHHM describes the health behaviour change process using eight themes: facilitation, assessment, desired life, barriers, knowledge and skills, insights, action planning, and monitor and support.

Practical implications

With the paucity of evidence informing WHP intervention effectiveness, this study provides a preliminary model serving practitioners to design more effective interventions and scholars to improve evidence.

Originality/value

This study proposes a practical comprehensive model for practitioners and leaders to more effectively design and evaluate successful MHB WHP interventions compared to existing models.