bluuebunny/crossref_metadata_2025 huggingface dataset:
COVID-19 challenges to dentistry in the new pandemic epicenter: Brazil
Authors: Moraes Rafael R. , Correa Marcos B. , Queiroz Ana B. , Daneris Ândrea , Lopes João P. , Pereira-Cenci Tatiana , D’Avila Otávio P. , Cenci Maximiliano S. , Lima Giana S. , Demarco Flávio F.
Published: June 2020

A nationwide survey of dentists was carried out in Brazil, a new pandemic epicenter, to analyze how dental coverage has been affected (public versus private networks), changes in routine and burdens, and how the local prevalence of COVID-19 affects dental professionals. Dentists were recruited via email and an Instagram® campaign. Responses to an online questionnaire were collected May 15–24, 2020. COVID-19 case/death counts in the state where respondents work was used to test associations between contextual status and decreases in weekly appointments, fear of contracting COVID-19 at work, and current work status (α=0.05). Over 10 days, 3,122 responses were received, with region, gender, and age distributions similar to those of dentists in Brazil. Work status was affected for 94% of dentists, with less developed regions being more impacted. The impact on routine was high or very high for 84%, leading to varied changes to clinic infrastructure, personal protective equipment use, patient screening, and increased costs. COVID-19 patients had been seen by 5.3% of respondents, and 90% reported fearing contracting COVID-19 at work. Multilevel statistics showed that greater case and death rates (1000 cases or 100 deaths/million inhabitants) in one’s state increased the odds of being fearful of contracting the disease (by 18% and 25%). For each additional 1000 cases or 100 deaths, the odds of currently not working or treating emergencies increased by 36% and 58%. The reduction in patients seen weekly per dentist was greater in public (38.7±18.6) than in private clinics (22.5±17.8). This study provides early evidence of three major impacts of the pandemic on dentistry in Brazil: increasing inequalities due to coverage differences between public and private networks; adoption of new clinical routines, which are associated with an economic burden; and associations of regional COVID-19 incidence and mortality with fear of contracting the disease at work.
Transformed time series analysis of first-wave COVID-19: universal similarities found in the Group of Twenty (G20) Countries
Authors: Kim Albert S
Published: June 2020

As of April 30, 2020, the number of cumulative confirmed coronavirus disease 2019 (COVID-19) cases exceeded 3 million worldwide and 1 million in the US with an estimated fatality rate of more than 7 percent. Because the patterns of the occurrence of new confirmed cases and deaths over time are complex and seemingly country-specific, estimating the long-term pandemic spread is challenging. I developed a simple transformation algorithm to investigate the characteristics of the case and death time series per nation, and described the universal similarities observed in the transformed time series of 19 nations in the Group of Twenty (G20). To investigate the universal similarities among the cumulative profiles of confirmed cases and deaths of 19 individual nations in the G20, a transformation algorithm of the time series data sets was developed with open-source software programs. The algorithm was used to extract and analyze statistical information from daily updated COVID-19 pandemic data sets from the European Centre for Disease Prevention and Control (ECDC). Two new parameters for each nation were suggested as factors for time-shifting and time-scaling to define reduced time, which was used to quantify the degree of universal similarities among nations. After the cumulative confirmed case and death profiles of a nation were transformed by using reduced time, most of the 19 nations, with few exceptions, had transformed profiles that closely converged to those of Italy after the onset of cases and deaths. The initial profiles of the cumulative confirmed cases per nation universally showed 3 – 4 week latency periods, during which the total number of cases remained at approximately ten. The latency period of the cumulative number of deaths was approximately half the latency number of cumulative cases, and subsequent uncontrollable increases in human deaths seemed unavoidable because the coronavirus had already widely spread. Immediate governmental actions, including responsive public-health policy-making and enforcement, are observed to be critical to minimize (and possibly stop) further infections and subsequent deaths. In the pandemic spread of infectious viral diseases, such as COVID-19 studied in this work, different nations show dissimilar and seemingly uncorrelated time series profiles of infected cases and deaths. After these statistical phenomena were viewed as identical events occurring at a distinct rate in each country, the reported algorithm of the data transformation using the reduced time revealed a nation-independent, universal profile (especially initial periods of the pandemic spread) from which a nation-specific, predictive estimation could be made and used to assist in immediate public-health policy-making.
Integrating genotypes and phenotypes improves long-term forecasts of seasonal influenza A/H3N2 evolution
Authors: Huddleston John , Barnes John R. , Rowe Thomas , Xu Xiyan , Kondor Rebecca , Wentworth David E. , Whittaker Lynne , Ermetal Burcu , Daniels Rodney S. , McCauley John W. , Fujisaki Seiichiro , Nakamura Kazuya , Kishida Noriko , Watanabe Shinji , Hasegawa Hideki , Barr Ian , Subbarao Kanta , Neher Richard A. , Bedford Trevor
Published: June 2020

Seasonal influenza virus A/H3N2 is a major cause of death globally. Vaccination remains the most effective preventative. Rapid mutation of hemagglutinin allows viruses to escape adaptive immunity. This antigenic drift necessitates regular vaccine updates. Effective vaccine strains need to represent H3N2 populations circulating one year after strain selection. Experts select strains based on experimental measurements of antigenic drift and predictions made by models from hemagglutinin sequences. We developed a novel influenza forecasting framework that integrates phenotypic measures of antigenic drift and functional constraint with previously published sequence-only fitness estimates. Forecasts informed by phenotypic measures of antigenic drift consistently outperformed previous sequence-only estimates, while sequence-only estimates of functional constraint surpassed more comprehensive experimentally-informed estimates. Importantly, the best models integrated estimates of both functional constraint and either antigenic drift phenotypes or recent population growth.
A systematic and quantitative comparison of lattice and Gaussian light-sheets
Authors: Chang Bo-Jui , Dean Kevin M. , Fiolka Reto
Published: June 2020

The axial resolving power of a light-sheet microscope is determined by the thickness of the illumination beam and the numerical aperture of its detection optics. Bessel-based optical lattices have generated significant interest owing to their potentially narrow beam waist and propagation-invariant characteristics. Yet, despite their significant use in Lattice Light-Sheet Microscopy, and recent incorporation into commercialized systems, there are very few quantitative reports on their physical properties and how they compare to standard Gaussian illumination beams. Here, we systematically measure the beam properties in transmission of dithered square lattices, which is the most commonly used variant of Lattice Light-Sheet Microscopy, and Gaussian-based light-sheets. After a systematic analysis, we find that square lattices are very similar to Gaussian-based light-sheets in terms of thickness, confocal parameter and propagation length.
Reproductive barriers as a byproduct of gene network evolution
Authors: Yang Chia-Hung , Scarpino Samuel V.
Published: June 2020

Molecular analyses of closely related taxa have increasingly revealed the importance of higher-order genetic interactions in explaining the observed pattern of reproductive isolation between populations. Indeed, both empirical and theoretical studies have linked the process of speciation to complex genetic interactions. Gene Regulatory Networks (GRNs) capture the inter-dependencies of gene expression and encode information about an individual’s phenotype and development at the molecular level. As a result, GRNs can–in principle–evolve via natural selection and play a role in non-selective, evolutionary forces. Here, we develop a network-based model, termed the pathway framework, that considers GRNs as a functional representation of coding sequences. We then simulated the dynamics of GRNs using a simple model that included natural selection, genetic drift, and sexual reproduction and found that reproductive barriers can develop rapidly between allopatric populations experiencing identical selection pressure. Further, we show that alleles involved in reproductive isolation can predate the allopatric separation of populations and that the number of interacting loci involved in genetic incompatibilities, i.e., the order, is often high simply as a by-product of the networked structure of GRNs. Finally, we discuss how results from the pathway framework are consistent with observed empirical patterns for genes putatively involved in post-zygotic isolation. Taken together, this study adds support for the central role of gene networks in speciation and in evolution more broadly.
Interpretation of the morphological adaptations associated with viviparity in the Tsetse fly (Glossina morsitans) by three dimensional analysis
Authors: Attardo GM , Tam N , Parkinson DY , Mack LK , Zahnle XJ , Arguellez J , Takáč P , Malacrida AR
Published: June 2020

Tsetse flies (genusGlossina), the sole vectors of African trypanosomiasis, are distinct from other disease vectors, and most other insects, due to dramatic morphological and physiological adaptations required to support their unique life histories. These evolutionary adaptations are driven by demands associated with their strict dietary and reproductive requirements. Tsetse reproduce by obligate viviparity which entails obligate intrauterine larval development and provisioning of nutrients for the developing larvae. Viviparous reproduction reduces reproductive capacity/rate which also drives increased inter- and intra-sexual competition. Here, we use phase contrast microcomputed tomography (pcMicroCT) to perform a three-dimensional (3D) analysis of viviparity associated morphological adaptations of tsetse female reproductive tract. These include 1) abdominal modifications facilitating the extreme abdominal distention required during blood feeding and pregnancy; 2) abdominal and uterine musculature required for parturition of developed larvae; 3) reduction of ovarian structure and capacity; 4) structural features of the spermatophore form in the female uterus to enhance semen/sperm delivery and inhibition of insemination by competing males; 5) uterine morphological features facilitating expansion and contraction before, during and after pregnancy; 6) milk gland structural optimizations facilitating nutrient incorporation and transfer into the uterus. The use of pcMicroCT provides unprecedented opportunities for examination and discovery of internal morphological features not possible with traditional microscopy techniques and new opportunities for comparative morphological analyses over time and between species.
Ranking microbial metabolomic and genomic links in the NPLinker framework using complementary scoring functions
Authors: Eldjárn Grímur Hjörleifsson , Ramsay Andrew , van der Hooft Justin J. J. , Duncan Katherine R. , Soldatou Sylvia , Rousu Juho , Daly Rónán , Wandy Joe , Rogers Simon
Published: June 2020

Specialised metabolites from microbial sources are well-known for their wide range of biomedical applications, particularly as antibiotics. When mining paired genomic and metabolomic data sets for novel specialised metabolites, establishing links between Biosynthetic Gene Clusters (BGCs) and metabolites represents a promising way of finding such novel chemistry. However, due to the lack of detailed biosynthetic knowledge for the majority of predicted BGCs, and the large number of possible combinations, this is not a simple task. This problem is becoming ever more pressing with the increased availability of paired omics data sets. Current tools are not effective at identifying valid links automatically, and manual verification is a considerable bottleneck in natural product research.

We demonstrate that using multiple link-scoring functions together makes it easier to prioritise true links relative to others. Based on standardising a commonly used score, we introduce a new, more effective score, and introduce a novel score using an Input-Output Kernel Regression approach. Finally, we present NPLinker, a software framework to link genomic and metabolomic data. Results are verified using publicly available data sets that include validated links.

Author summary

In this article, we introduce NPLinker, a software framework to link genomic and metabolomic data, to link microbial secondary metabolites to their producing genomic regions.

Two of the major approaches for such linking are analysis of the correlation between sets of strains, and analysis of predicted features of the molecules. While these methods are usually used separately, we demonstrate that they are in fact complementary, and show a way to combine them to improve their performance.

We begin by demonstrating a weakness in the most common method of strain correlation analysis, and suggest an improvement. We then introduce a new feature-based analysis method which, unlike most such methods, does not directly depend on the natural prodcut compound class. Finally, we demonstrate that the two are complementary and proceed to combine them into a single scoring function for genomic and metabolomic links, which shows improved performance over either of the individual approaches.

Verification is done using curated databases of genomic and metabolomic data, as well as public data sets of microbial data including verified links.
Multivalent Clustering of Adhesion Ligands in Nanofiber-Nanoparticle Composites
Authors: Dems Dounia , Freeman Ronit , Coradin Thibaud , Stupp Samuel I. , Aimé Carole
Published: June 2020

Because the positioning and clustering of biomolecules within the extracellular matrix dictates cell behaviors, the engineering of biomaterials incorporating bioactive epitopes with spatial organization tunable at the nanoscale is of primary importance. Here we used a highly modular composite approach combining peptide amphiphile (PA) nanofibers and silica nanoparticles, which are both easily functionalized with one or several bioactive signals. We show that the surface of silica nanoparticles allows the clustering of RGDS bioactive signals leading to improved adhesion and spreading of fibroblast cells on composite hydrogels at an epitope concentration much lower than in PA-only based matrices. Most importantly, by combining the two integrin-binding sequences RGDS and PHSRN on nanoparticle surfaces, we improved cell adhesion on the PA nanofiber/particle composite hydrogels, which is attributed to synergistic interactions known to be effective only for peptide intermolecular distance ofca. 5 nm. Such composites with soft and hard nanostructures offer a strategy for the design of advanced scaffolds to display multiple signals and control cell behavior.
DeepEMhancer: a deep learning solution for cryo-EM volume post-processing
Authors: Sanchez-Garcia R , Gomez-Blanco J , Cuervo A , Carazo JM , Sorzano COS , Vargas J
Published: June 2020

Cryo-EM maps are valuable sources of information for protein structure modeling. However, due to the loss of contrast at high frequencies, they generally need to be post-processed to improve their interpretability. Most popular approaches, based on B-factor correction, suffer from limitations. For instance, they ignore the heterogeneity in the map local quality that reconstructions tend to exhibit. Aiming to overcome these problems, we present DeepEMhancer, a deep learning approach designed to perform automatic post-processing of cryo-EM maps. Trained on a dataset of pairs of experimental maps and maps sharpened using their respective atomic models, DeepEMhancer has learned how to post-process experimental maps performing masking-like and sharpening-like operations in a single step. DeepEMhancer was evaluated on a testing set of 20 different experimental maps, showing its ability to obtain much cleaner and more detailed versions of the experimental maps. Additionally, we illustrated the benefits of DeepEMhancer on the structure of the SARS-CoV-2 RNA polymerase.
Immunoresolvents Support Skeletal Myofiber Regeneration via Actions on Myeloid and Muscle Stem Cells
Authors: Markworth James F. , Brown Lemuel A. , Lim Eunice , Floyd Carolyn , Larouche Jaqueline , Castor-Macias Jesus A. , Sugg Kristoffer B. , Sarver Dylan C. , Macpherson Peter C. D. , Davis Carol , Aguilar Carlos A. , Maddipati Krishna Rao , Brooks Susan V.
Published: June 2020

Specialized pro-resolving mediators (SPMs) actively limit inflammation and expedite its resolution. Here we profiled intramuscular lipid mediators following injury and investigated the role of SPMs in skeletal muscle inflammation and repair. Both eicosanoids and SPMs increased following myofiber damage induced by intramuscular injection of barium chloride or functional overload. Daily systemic administration of resolvin D1 (RvD1) limited the degree and duration of inflammation, enhanced regenerating myofiber growth, and improved recovery of muscle strength. RvD1 suppressed inflammatory cytokines, enhanced polymorphonuclear cell clearance, modulated muscle stem cells, and polarized macrophages to a more pro-regenerative subset. RvD1 had minimal direct impact onin-vitromyogenesis but directly suppressed myokine production and stimulated macrophage phagocytosis, showing that SPMs influence modulate both infiltrating myeloid and resident muscle cells. These data reveal the efficacy of immunoresolvents as a novel alternative to classical anti-inflammatory interventions in the management of muscle injuries to modulate inflammation while stimulating tissue repair.
Microengineered three-dimensional collagen fiber landscapes with independently tunable anisotropy and directionality
Authors: Ahmed Adeel , Joshi Indranil M. , Mansouri Mehran , Larson Stephen , Gholizadeh Shayan , Allahyari Zahra , Forouzandeh Farzad , Borkholder David A. , Gaborski Thomas R. , Abhyankar Vinay V.
Published: June 2020

Fibrillar collagens are structural proteins in the extracellular matrix (ECM), and cellular processes, including differentiation, proliferation, and migration, have been linked to the orientation (directionality) and alignment (anisotropy) of collagen fibers. Given the importance of cell-substrate interactions in driving biological functions, several microfluidic approaches have demonstrated three-dimensional (3D) collagen gels with defined fiber properties that enable quantitative correlations between structural cues and observed cell responses. Although existing methods provide excellent definition over collagen fiber anisotropy, independent control over both anisotropy and directionality (that we collectively refer to as the collagen landscape) has not been demonstrated. Therefore, to advance collagen microengineering capabilities, we present a user-friendly approach that uses controlled fluid flows within a non-uniform microfluidic channel network to create well-defined collagen landscapes. We demonstrate capabilities including i) control over fiber anisotropy, ii) spatial gradients in fiber anisotropy, iii) defined fiber directionality, and iv) multi-material interfaces. We then show that cells respond to the microengineered topographic cues by aligning along the anisotropy domains and following fiber directionality. Finally, this platform’s modular capability is demonstrated by integrating an ultrathin porous parylene (UPP) membrane on the microengineered collagen as a mask to control cell-substrate interactions.
Repurposing the antidepressant sertraline as SHMT inhibitor to suppress serine/glycine synthesis addicted breast tumor growth
Authors: Geeraerts Shauni L. , Kampen Kim R. , Rinaldi Gianmarco , Gupta Purvi , Planque Mélanie , De Cremer Kaat , De Brucker Katrijn , Vereecke Stijn , Verbelen Benno , Vermeersch Pieter , Cassiman David , Fendt Sarah-Maria , Voet Arnout , Cammue Bruno P.A. , Thevissen Karin , De Keersmaecker Kim
Published: June 2020

Metabolic rewiring is a hallmark of cancer that supports tumor growth, survival and chemotherapy resistance. While normal cells often rely on extracellular serine and glycine supply, a significant subset of cancers becomes addicted to intracellular serine/glycine synthesis, offering an attractive drug target. Previously developed inhibitors of serine/glycine synthesis enzymes did not reach clinical trials due to unfavorable pharmacokinetic profiles, implying that further efforts to identify clinically applicable drugs targeting this pathway are required. In this study, we aimed to develop therapies that can rapidly enter the clinical practice by focusing on drug repurposing, as their safety and cost-effectiveness have been optimized before. Using a yeast model system, we repurposed two compounds, sertraline and thimerosal, for their selective toxicity against serine/glycine synthesis addicted breast cancer and T-cell acute lymphoblastic leukemia cell lines. Isotope tracer metabolomics, computational docking studies and an enzymatic activity assay revealed that sertraline and thimerosal inhibit serine/glycine synthesis enzymes serine hydroxymethyltransferase and phosphoglycerate dehydrogenase, respectively. In addition, we demonstrated that sertraline’s anti-proliferative activity was further aggravated by mitochondrial inhibitors, such as the antimalarial artemether, by causing G1-S cell cycle arrest. Most notably, this combination also resulted in serine-selective antitumor activity in breast cancer mouse xenografts. Collectively, this study provides molecular insights into the repurposed mode-of-action of the antidepressant sertraline and allows to delineate a hitherto unidentified group of cancers being particularly sensitive to treatment with sertraline. Furthermore, we highlight the simultaneous inhibition of serine/glycine synthesis and mitochondrial metabolism as a novel treatment strategy for serine/glycine synthesis addicted cancers.
Evidence for an expanded repertoire of electron acceptors for the anaerobic oxidation of methane in authigenic carbonates in the Atlantic and Pacific Ocean
Authors: Beckmann Sabrina , Farag Ibrahim F. , Zhao Rui , Christman Glenn D , Prouty Nancy G , Biddle Jennifer F
Published: June 2020

Authigenic carbonates represent a significant microbial sink for methane, yet little is known about the microbiome responsible for the methane removal. We identify carbonate microbiomes distributed over 21 locations hosted by 7 different cold seeps in the Pacific and Atlantic Oceans by carrying out a gene-based survey using 16S rRNA- andmcrA gene sequencing coupled with metagenomic analyses. These sites were dominated by bacteria affiliated to the Firmicutes, Alpha- and Gammaproteobacteria. ANME-1 and −2 clades were abundant in the carbonates yet their typical syntrophic partners, sulfate reducing bacteria, were not significantly present. Our analysis indicated that methane oxidizers affiliated to the ANME-1 and −2 as well as to theCandidatusMethanoperedens clades, are capable of performing complete methane- and potentially short-chain alkane oxidations independently using oxidized sulfur and nitrogen compounds as terminal electron acceptors. Gammaproteobacteria are hypothetically capable of utilizing oxidized nitrogen compounds in potential syntrophy with methane oxidizing archaea. Carbonate structures represent a window for a more diverse utilization of electron acceptors for anaerobic methane oxidation along the Atlantic and Pacific Margin.
Cargo competition for a dimerization interface stabilizes a protease adaptor inCaulobacter crescentus
Authors: Kuhlmann Nathan J. , Doxsey Dylan , Chien Peter
Published: June 2020

Bacterial protein degradation is a regulated process aided by protease adaptors that alter specificity of energy dependent proteases. InCaulobacter crescentus, cell-cycle dependent protein degradation depends on a hierarchy of adaptors, such as the dimeric RcdA adaptor which binds multiple cargo and delivers substrates to the ClpXP protease. RcdA itself is degraded in the absence of cargo and how RcdA recognizes its targets is unknown. Here we show that RcdA dimerization and cargo binding compete for a common interface. Cargo binding separates RcdA dimers and a monomeric variant of RcdA fails to be degraded, suggesting that RcdA degradation is a result of self-delivery. Based on HDX-MS studies showing that different cargo rely on different regions of the dimerization interface, we generate RcdA variants that are selective for specific cargo and show cellular defects consistent with changes in selectivity. Using the same interface for dimerization and cargo binding offers an ability to limit excess protease adaptors by self-degradation, while providing capacity for binding a range of substrates.

Significance Statement

Energy-dependent proteases broadly regulate bacterial physiology and development. Adaptor proteins tune the substrate specificity of proteases to only degrade selective substrates during the bacterial life cycle and during times of cellular stress. In the process of delivering cargo to their respective proteases, adaptor proteins are inherently protected from degradation until the delivery is complete. How protease adaptors can recognize a wide range of cargo while maintaining stringent specificity and how this process results in stabilization of adaptors remains unclear. Here, we show that direct competition for distinct regions of the dimer interface of the RcdA adaptor by its cargo protects RcdA from degradation by the ClpXP protease, and that this interface can be selectively perturbed in a rational manner with biochemical and physiological consequences.

Highlights

Cargo binding of RcdA cargo competes with dimerization

Dimerization of RcdA is necessary for self-degradation by ClpXP

RcdA can deliver either cargo or other RcdA subunits to ClpXP

Different regions of the dimerization interface are needed for different cargo
Drift and termination of spiral waves in optogenetically modified cardiac tissue at sub-threshold illumination
Authors: Hussaini Sayedeh , Venkatesan Vishalini , Biasci Valentina , Romero Sepúlveda José M. , Quiñonez Uribe Raúl A. , Sacconi Leonardo , Bub Gil , Richter Claudia , Krinski Valentin , Parlitz Ulrich , Majumder Rupamanjari , Luther Stefan
Published: June 2020

The development of new approaches to control cardiac arrhythmias requires a deep understanding of spiral wave dynamics. Optogenetics offers new possibilities for this. Preliminary experiments show that sub-threshold illumination affects electrical wave propagation in the mouse heart. However, a systematic exploration of these effects is technically challenging. Here, we use state-of-the-art computer models to study the dynamic control of spiral waves in a two-dimensional model of the adult mouse ventricle, using stationary and non-stationary patterns of sub-threshold illumination. Our results indicate a light intensity-dependent increase in cellular resting membrane potentials, which together with diffusive cell-cell coupling leads to the development of spatial voltage gradients over differently illuminated areas. A spiral wave drifts along the positive gradient. These gradients can be strategically applied to ensure drift-induced termination of a spiral wave, both in optogenetics and in conventional methods of electrical defibrillation.
Electro-Steric Mechanism of CLC-2 Chloride Channel Activation
Authors: De Jesús-Pérez José J. , Méndez-Maldonado G. Arlette , Gonzalez-Hernandez Irma L. , De la Rosa Victor , Gastélum-Garibaldi Roberto , Sánchez-Rodríguez Jorge E. , Arreola Jorge
Published: June 2020

Two-pore voltage-gated CLC chloride channels control neuronal and muscle excitability. They share a dimeric structure but their activation mechanism remains unresolved. Here we determine the step-by-step activation mechanism of the broadly expressed CLC-2 channel using homology modelling, molecular dynamic simulations and functional studies. We establish that a two-leaf gate formed by Tyr561-H2O-Glu213 flanked by Lys568/Glu174 and Lys212 closes the canonical pore. Activation begins when a hyperpolarization-propelled intracellular chloride occupies the pore and splits Tyr561-H2O-Glu213 by electrostatic/steric repulsion. Unrestrained Glu213 rotates outwardly to bind Lys212 but the pore remains closed. Protonation breaks the Glu213-Lys212 interaction while another chloride occupies the pore thus catalysing chloride exit via Lys212. Also, we found that the canonical pore is uncoupled from a cytosolic cavity by a Tyr561-containing hydrophobic gate that prevents Glu213 protonation by intracellular protons. Our data provide atomistic details about CLC-2 activation but this mechanism might be common to other CLC channels.
Adipose tissue macrophages orchestrate β cell adaptation in obesity through secreting miRNA-containing extracellular vesicles
Authors: Gao Hong , Luo Zhenlong , Jin Zhongmou , Ji Yudong , Ying Wei
Published: June 2020

Obesity induces an adaptive expansion of β cell mass and insulin secretion abnormality. Here, we explore a novel role of adipose tissue macrophages (ATMs) in mediating obesity-induced β cell function and proliferation through releasing miRNA-containing extracellular vesicles (EVs). ATM EVs derived from obese mice notably suppress insulin secretion in bothin vivoandin vitroexperiments, whereas there are more proliferating β cells in the islets treated with obese ATM EVs. Depletion of miRNAs blunts the ability of obese ATM EVs to regulate β cell responses. miR-155, a highly enriched miRNA within obese ATM EVs, exerts profound regulation on β cell functions, as evidenced by impaired insulin secretion and increased β cell proliferation after miR-155 overexpression in β cells. By contrast, knockout of miR-155 can attenuate the regulation of obese ATM EVs on β cell responses. We further demonstrate that the miR-155-Mafbaxis plays a critical role in controlling β cell responses. Taken together, these studies show a novel mechanism by which ATM-derived EVs act as endocrine cargoes delivering miRNAs and subsequently mediating β cell adaptation and functional dysfunction in obesity.
CK2 inhibits TIMELESS nuclear export and modulates CLOCK transcriptional activity to regulate circadian rhythms
Authors: Cai Yao D. , Xue Yongbo , Truong Cindy C. , Del Carmen-Li Jose , Ochoa Christopher , Vanselow Jens T. , Murphy Katherine A. , Li Ying H. , Liu Xianhui , Kunimoto Ben L. , Zheng Haiyan , Zhao Caifeng , Zhang Yong , Schlosser Andreas , Chiu Joanna C.
Published: June 2020

Circadian clocks orchestrate daily rhythms in organismal physiology and behavior to promote optimal performance and fitness. InDrosophila, key pacemaker proteins PERIOD (PER) and TIMELESS (TIM) are progressively phosphorylated to perform phase-specific functions. Whereas PER phosphorylation has been extensively studied, systematic analysis of site-specific TIM phosphorylation is lacking. Here, we identified phosphorylation sites of PER-bound TIM by mass spectrometry, given the importance of TIM as a modulator of PER function in the oscillator. Among the twelve TIM phosphorylation sites we identified, at least two of them are critical for circadian timekeeping as mutants expressing non-phosphorylatable mutations exhibit altered behavioral rhythms. In particular, we observed that CK2-dependent phosphorylation of TIM(S1404) promotes nuclear accumulation of PER-TIM heterodimers by inhibiting the interaction of TIM and nuclear export component, Exportin 1 (XPO1). We postulate that proper level of nuclear PER-TIM accumulation is necessary to facilitate kinase recruitment for the regulation of daily phosphorylation rhythm and phase-specific transcriptional activity of CLOCK (CLK). Our results highlight the contribution of phosphorylation-dependent nuclear export of PER-TIM heterodimers to the maintenance of circadian periodicity and identify a new mechanism by which the negative elements of the circadian oscillator (PER-TIM) regulate the positive elements (CLK-CYC). Finally, since the molecular phenotype oftim(S1404A) non-phosphorylatable mutant exhibits remarkable similarity to that of a mutation in humantimelessthat underlies Familial Advanced Sleep Phase Syndrome (FASPS), our results revealed an unexpected parallel between the functions ofDrosophilaand human TIM and may provide new insights into the molecular mechanisms underlying human FASPS.

Significance Statement

Phosphorylation is a central mechanism important for the regulation of circadian physiology across organisms. The molecular oscillator is composed of pacemaker proteins that undergo elaborate phosphorylation programs to regulate phase-specific functions. InDrosophila, phosphorylation of TIMELESS (TIM) has been recognized as critical for its function in the oscillator, but a systematic analysis of TIM phosphorylation is lacking. Here, we identified twelveDrosophilaTIM phosphorylation sites by mass spectrometry and showed that phosphorylation at TIM(S1404) is necessary for maintaining 24-hour rhythms. Finally, since the molecular phenotype oftim(S1404A) non-phosphorylatable fly mutant exhibits remarkable similarity to that of a mutation in humantimelessthat underlies FASPS, our results may provide new insights into the molecular underpinnings of human FASPS.
Changes in the distribution of fitness effects and adaptive mutational spectra following a single first step towards adaptation
Authors: Aggeli Dimitra , Li Yuping , Sherlock Gavin
Published: June 2020

The fitness effects of random mutations are contingent upon the genetic and environmental contexts in which they occur, and this contributes to the unpredictability of evolutionary outcomes at the molecular level. Despite this unpredictability, the rate of adaptation in homogeneous environments tends to decrease over evolutionary time, due to diminishing returns epistasis, causing relative fitness gains to be predictable over the long term. Here, we studied the extent of diminishing returns epistasis and the changes in the adaptive mutational spectra after yeast populations have already taken their first adaptive mutational step. We used three distinct adaptive clones that arose under identical conditions from a common ancestor, from which they diverge by a single point mutation, to found populations that we further evolved. We followed the evolutionary dynamics of these populations by lineage tracking and determined adaptive outcomes using fitness assays and whole genome sequencing. We found compelling evidence for diminishing returns: fitness gains during the 2ndstep of adaptation are smaller than those of the 1ststep, due to a compressed distribution of fitness effects in the 2ndstep. We also found strong evidence for historical contingency at the genic level: the beneficial mutational spectra of the 2nd-step adapted genotypes differ with respect to their ancestor and to each other, despite the fact that the three founders’ 1st-step mutations provided their fitness gains due to similar phenotypic improvements. While some targets of selection in the second step are shared with those seen in the common ancestor, other targets appear to be contingent on the specific first step mutation, with more phenotypically similar founding clones having more similar adaptive mutational spectra. Finally, we found that disruptive mutations, such as nonsense and frameshift, were much more common in the first step of adaptation, contributing an additional way that both diminishing returns and historical contingency are evident during 2ndstep adaptation.
Single-cell transcriptomic analysis of SARS-CoV-2 reactive CD4+T cells
Authors: Meckiff Benjamin J. , Ramírez-Suástegui Ciro , Fajardo Vicente , Chee Serena J , Kusnadi Anthony , Simon Hayley , Grifoni Alba , Pelosi Emanuela , Weiskopf Daniela , Sette Alessandro , Ay Ferhat , Seumois Grégory , Ottensmeier Christian H , Vijayanand Pandurangan
Published: June 2020

The contribution of CD4+T cells to protective or pathogenic immune responses to SARS-CoV-2 infection remains unknown. Here, we present large-scale single-cell transcriptomic analysis of viral antigen-reactive CD4+T cells from 32 COVID-19 patients. In patients with severe disease compared to mild disease, we found increased proportions of cytotoxic follicular helper (TFH) cells and cytotoxic T helper cells (CD4-CTLs) responding to SARS-CoV-2, and reduced proportion of SARS-CoV-2 reactive regulatory T cells. Importantly, the CD4-CTLs were highly enriched for the expression of transcripts encoding chemokines that are involved in the recruitment of myeloid cells and dendritic cells to the sites of viral infection. Polyfunctional T helper (TH)1 cells and TH17 cell subsets were underrepresented in the repertoire of SARS-CoV-2-reactive CD4+T cells compared to influenza-reactive CD4+T cells. Together, our analyses provide so far unprecedented insights into the gene expression patterns of SARS-CoV-2 reactive CD4+T cells in distinct disease severities.
Single-cell profiling of Ebola virus infectionin vivoreveals viral and host transcriptional dynamics
Authors: Kotliar Dylan , Lin Aaron E. , Logue James , Hughes Travis K. , Khoury Nadine M. , Raju Siddharth S. , Wadsworth Marc H. , Chen Han , Kurtz Jonathan R. , Dighero-Kemp Bonnie , Bjornson Zach B. , Mukherjee Nilanjan , Sellers Brian A. , Tran Nancy , Bauer Matthew R. , Adams Gordon C. , Adams Ricky , Rinn John L. , Melé Marta , Nolan Garry P. , Barnes Kayla G. , Hensley Lisa E. , McIlwain David R. , Shalek Alex K. , Sabeti Pardis C. , Bennett Richard S.
Published: June 2020

Ebola virus (EBOV) causes epidemics with high case fatality rates, yet remains understudied due to the challenge of experimentation in high-containment and outbreak settings. To better understand EBOV infectionin vivo, we used single-cell transcriptomics and CyTOF-based single-cell protein quantification to characterize peripheral immune cell activity during EBOV infection in rhesus monkeys. We obtained 100,000 transcriptomes and 15,000,000 protein profiles, providing insight into pathogenesis. We find that immature, proliferative monocyte-lineage cells with reduced antigen presentation capacity replace conventional circulating monocyte subsets within days of infection, while lymphocytes upregulate apoptosis genes and decline in abundance. By quantifying viral RNA abundance in individual cells, we identify molecular determinants of tropism and examine temporal dynamics in viral and host gene expression. Within infected cells, we observe that EBOV down-regulatesSTAT1mRNA and interferon signaling, and up-regulates putative pro-viral genes (e.g.,DYNLL1andHSPA5), nominating cellular pathways the virus manipulates for its replication. Overall, this study sheds light on EBOV tropism, replication dynamics, and elicited immune response, and provides a framework for characterizing interactions between hosts and emerging viruses in a maximum containment setting.
An electron transfer competent structural ensemble of membrane-bound cytochrome P450 1A1 and cytochrome P450 oxidoreductase
Authors: Mukherjee Goutam , Nandekar Prajwal P. , Wade Rebecca C.
Published: June 2020

Cytochrome P450 (CYP) heme monooxygenases require two electrons for their catalytic cycle. For mammalian microsomal CYPs, key enzymes for xenobiotic metabolism and steroidogenesis and important drug targets and biocatalysts, the electrons are transferred by NADPH-cytochrome P450 oxidoreductase (CPR). No structure of a mammalian CYP-CPR complex has been solved experimentally, hindering understanding of the determinants of electron transfer (ET), which is often rate-limiting for CYP reactions. Here, we investigated the interactions between membrane-bound CYP 1A1, an antitumor drug target, and CPR by a multiresolution computational approach. We find that upon binding to CPR, the CYP 1A1 catalytic domain becomes less embedded in the membrane and reorients, indicating that CPR may affect ligand passage to the CYP active site. Despite the constraints imposed by membrane binding, we identify several arrangements of CPR around CYP 1A1 that are compatible with ET. In the complexes, the interactions of the CPR FMN domain with the proximal side of CYP 1A1 are supplemented by more transient interactions of the CPR NADP domain with the distal side of CYP 1A1. Computed ET rates and pathways agree well with available experimental data and suggest why the CYP-CPR ET rates are low compared to those of soluble bacterial CYPs.
Crystal structure of inhibitor-bound human MSPL that can activate high pathogenic avian influenza
Authors: Ohno Ayako , Maita Nobuo , Tabata Takanori , Nagano Hikaru , Arita Kyohei , Ariyoshi Mariko , Uchida Takayuki , Nakao Reiko , Ulla Anayt , Sugiura Kosuke , Kishimoto Koji , Teshima-Kondo Shigetada , Okumura Yuushi , Nikawa Takeshi
Published: June 2020

Infection of certain influenza viruses is triggered when its hemagglutinin (HA) is cleaved by host cell proteases such as proprotein convertases and type II transmembrane serine proteases (TTSP). HA with a monobasic motif is cleaved by trypsin-like proteases, including TMPRSS2 and HAT, while the multibasic motif found in high pathogenicity avian influenza HA is cleaved by furin, PC5/6, or MSPL. MSPL belongs to the TMPRSS family and preferentially cleaves [R/K]-K-K-R↓ sequences. Here, we solved the crystal structure of the extracellular region of human MSPL in complex with an irreversible substrate-analog inhibitor. The structure revealed three domains clustered around the C-terminal α-helix of the SPD. The inhibitor structure and its putative model show that the P1-Arg inserts into the S1 pocket, whereas the P2-Lys and P4-Arg interacts with the Asp/Glu-rich 99-loop that is unique to MSPL. Based on the structure of MSPL, we also constructed a homology model of TMPRSS2, which is essential for the activation of the SARS-CoV-2 spike protein and infection. The model may provide the structural insight for the drug development for COVID-19.
Autoregulatory control of microtubule binding in the oncogene, doublecortin-like kinase 1
Authors: Rogers Melissa M. , Ramkumar Amrita , Downing Ashlyn M. , Bodin Hannah , Castro Julia , Nowakowski Dan W. , Ori-McKenney Kassandra M.
Published: June 2020

The microtubule-associated protein (MAP), doublecortin-like kinase 1 (DCLK1), is highly expressed in a range of cancers and is a prominent therapeutic target for the development of kinase inhibitors. However, the physiological roles of its kinase activity and how DCLK1 kinase activity is regulated remain elusive. Here we employ in vitro reconstitution with purified proteins to analyze the role of DCLK1 kinase activity in regulating microtubule binding. We find that DCLK1 autophosphorylates a single residue within its C-terminal tail to restrict its kinase activity and prevent aberrant hyperphosphorylation within its microtubule-binding domain. Removal of the C-terminal tail or mutation of this residue causes an increase in phosphorylation largely within the doublecortin 2 (DC2) domain, which dramatically reduces the microtubule affinity of DCLK1. Therefore, autophosphorylation at specific sites within DCLK1 have diametric effects on the molecule’s ability to associate with microtubules. Overall, our results suggest a mechanism by which DCLK1 modulates its own kinase activity to tune its microtubule binding affinity, providing molecular insights into a unique form of autoregulatory control over microtubule binding activity within the broader family of MAPs. These results provide useful molecular insights for future therapeutic efforts related to DCLK1’s role in cancer development and progression.
The impact of interneurons on nonlinear synaptic integration in the neocortex
Authors: Dorsett Christopher , Philpot Benjamin , Smith Spencer LaVere , Smith Ikuko T.
Published: June 2020

Excitatory inputs arriving at the dendrites of a neuron can engage active mechanisms that nonlinearly amplify the depolarizing currents. Interneuron-mediated inhibition can modulate this active process, in a subtype-dependent manner. For example, dendrite-targeting inhibition is hypothesized to increase the amplitude of synaptic input required to activate voltage-dependent nonlinear synaptic integration. To examine how inhibition influences active synaptic integration, we optogenetically manipulated the activity of two different subtypes of interneurons: dendrite-targeting somatostatin-expressing (SOM) and perisomatic-targeting parvalbumin-expressing (PV) interneurons. In acute slices of mouse primary visual cortex, electrical stimulation evoked nonlinear synaptic integration that depended onN-methyl-D-aspartate (NMDA) receptors. Optogenetic activation of SOM neurons in conjunction with electrical stimulation resulted in predominantly divisive inhibitory gain control, reducing the magnitude of the nonlinear response without affecting its threshold. PV activation, on the other hand, had a minimal effect on dendritic nonlinearities, resulting in a small subtractive effect. Furthermore, we found that mutual inhibition among SOM interneurons was strong and more prevalent than previously thought, while mutual inhibition among PV interneurons was minimal. These results challenge previous models of inhibitory modulation of active synaptic integration. The major effect of SOM inhibition is not a shift in threshold for activation of nonlinear integration, but rather a decrease the amplitude of the nonlinear response.
Ultra-rapid metagenotyping of the human gut microbiome
Authors: Shi Zhou Jason , Dimitrov Boris , Zhao Chunyu , Nayfach Stephen , Pollard Katherine S.
Published: June 2020

Sequence variation is used to quantify population structure and identify genetic determinants of phenotypes that vary within species. In the human microbiome and other environments, single nucleotide polymorphisms (SNPs) are frequently detected by aligning metagenomic sequencing reads to catalogs of genes or genomes. But this requires high-performance computing and enough read coverage to distinguish SNPs from sequencing errors. We solved these problems by developing the GenoTyper for Prokaytotes (GT-Pro), a suite of novel methods to catalog SNPs from genomes and use exact k-mer matches to perform ultra-fast reference-based SNP calling from metagenomes. Compared to read alignment, GT-Pro is more accurate and two orders of magnitude faster. We discovered 104 million SNPs in 909 human gut species, characterized their global population structure, and tracked pathogenic strains. GT-Pro democratizes strain-level microbiome analysis by making it possible to genotype hundreds of metagenomes on a personal computer.

Software availability

GT-Pro is available athttps://github.com/zjshi/gt-pro.