bluuebunny/crossref_metadata_2025 huggingface dataset:
Mathematical modeling of Erk activity waves in regenerating zebrafish scales
Authors: Hayden L.D. , Poss K.D. , De Simone A. , Di Talia S.
Published: January 2021

Erk signaling regulates cellular decisions in many biological contexts. Recently, we have reported a series of Erk activity traveling waves that coordinate regeneration of osteoblast tissue in zebrafish scales. These waves originate from a central source region, propagate as expanding rings, and impart cell growth, thus controlling tissue morphogenesis. Here, we present a minimal reaction-diffusion model for Erk activity waves. The model considers three components: Erk, a diffusible Erk-activator, and an Erk-inhibitor. Erk stimulates both its activator and inhibitor, forming a positive and negative feedback loop, respectively. Our model shows that this system can be excitable and propagate Erk activity waves. Waves originate from a pulsatile source which is modeled by adding a localized basal production of the activator that switches the source region from an excitable to an oscillatory state. As Erk activity periodically rises in the source, it can trigger an excitable wave which travels across the entire tissue. Analysis of the model finds that positive feedback controls the properties of the traveling wavefront and that negative feedback controls the duration of Erk activity peak and the period of Erk activity waves. The geometrical properties of the waves facilitate constraints on the effective diffusivity of the activator, indicating that waves are an efficient mechanism to transfer growth factor signaling rapidly across a large tissue.

Significance statement

Signaling waves represent a possible mechanism of spatiotemporal organization of multicellular tissues. We have recently shown that waves of activity of the kinase Erk control osteoblast regeneration in adult zebrafish scales. Here, we present a detailed characterization of a mathematical model of these signaling waves. We show that a source region poised in an oscillatory state can broadcast traveling waves of Erk activity in the surrounding excitable tissue. The dynamics of the source control the number and frequency of waves. Geometrical arguments support the notion that excitable Erk waves are an effective mechanism to transport growth factor signaling across a large regenerating tissue.
Perceptual Weighting of V1 Spikes Revealed by Optogenetic White Noise Stimulation
Authors: Day-Cooney Julian R. , Cone Jackson J. , Maunsell John H.R.
Published: January 2021

During visually guided behaviors, mere hundreds of milliseconds can elapse between a sensory input and its associated behavioral response. How spikes occurring at different times are integrated to drive perception and action remains poorly understood. We delivered random trains of optogenetic stimulation (white noise) to excite inhibitory interneurons in V1 of mice while they performed a visual detection task. We then performed a reverse correlation analysis on the optogenetic stimuli to generate a neuronal-behavioral kernel: an unbiased, temporally-precise estimate of how suppression of V1 spiking at different moments around the onset of a visual stimulus affects detection of that stimulus. Electrophysiological recordings enabled us to capture the effects of optogenetic stimuli on V1 responsivity and revealed that the earliest stimulus-evoked spikes are preferentially weighted for guiding behavior. These data demonstrate that white noise optogenetic stimulation is a powerful tool for understanding how patterns of spiking in neuronal populations are decoded in generating perception and action.

Significance Statement

How the brain decodes dynamic neuronal responses to generate perception and behavior remains uncertain. A critical challenge is determining the relative contribution of spikes that occur at different times on the timescale of brain computations (tens of ms). Optogenetic tools permit causal investigations into neuronal-behavioral relationships, but are generally impractical for obtaining millisecond resolution. We circumvented this by delivering random (white noise) patterns of optogenetic inhibition to the primary visual cortex of behaving mice during visual tasks. Aligning optogenetic stimuli to task outcomes (hit, miss) yielded a neuronal-behavioral kernel – a temporal weighting that describes how inhibition at different moments impacts perception of visual stimuli. Thus, this method is a powerful tool for linking neuronal spiking, perception, and behavior.
Targeted RNA-seq improves efficiency, resolution, and accuracy of allele specific expression for human term placentas
Authors: Wu Weisheng , Lovett Jennie L. , Shedden Kerby , Strassmann Beverly I. , Vincenz Claudius
Published: January 2021

Genomic imprinting is an epigenetic mechanism that results in allele specific expression (ASE) based on parent of origin. It is known to play a role in the prenatal and postnatal allocation of maternal resources in mammals. ASE detected by whole transcriptome RNA-seq (wht-RNAseq) has been widely used to analyze imprinted genes using reciprocal crosses in mice to generate large numbers of informative SNPs. Studies in humans are more challenging due to the paucity of SNPs and the poor preservation of RNA in term placentas and other tissues. Targeted RNA-seq (tar-RNAseq) can potentially mitigate these challenges by focusing sequencing resources on the regions of interest in the transcriptome. Here we compared tar-RNAseq and wht-RNAseq in a study of ASE in known imprinted genes in placental tissue collected from a healthy human cohort in Mali, West Africa. As expected, tar-RNAseq substantially improved the coverage of SNPs. Compared to wht-RNAseq, tar-RNAseq produced on average four times more SNPs in twice as many genes per sample and read depth at the SNPs increased 4-fold. In previous research on humans, discordant ASE values for SNPs of the same gene have limited the ability to accurately quantify ASE. We show that tar-RNAseq reduces this limitation as it unexpectedly increased the concordance of ASE between SNPs of the same gene, even in cases of degraded RNA. Studies aimed at discovering associations between individual variation in ASE and phenotypes in mammals and flowering plants will benefit from the improved power and accuracy of tar-RNAseq.
Microstructure Aware Modeling Of Biochemical Transport In Arterial Blood Clots
Authors: Teeraratkul Chayut , Mukherjee Debanjan
Published: January 2021

Flow-mediated transport of biochemical species is central to thrombotic phenomena. Comprehensive three-dimensional modeling of flow-mediated transport around realistic macroscale thrombi poses challenges owing to their arbitrary heterogeneous microstructure. Here, we develop a microstructure aware model for species transport within and around a macroscale thrombus by devising a custom preconditioned fictitious domain formulation for thrombus-hemodynamics interactions, and coupling it with a fictitious domain advection-diffusion formulation for transport. Microstructural heterogeneities are accounted through a hybrid discrete particle-continuum approach for the thrombus interior. We present systematic numerical investigations on unsteady arterial flow within and around a three-dimensional macroscale thrombus; demonstrate the formation of coherent flow structures around the thrombus which organize advective transport; illustrate the role of the permeation processes at the thrombus boundary and subsequent intra-thrombus transport; and characterize species transport from bulk flow to the thrombus boundary and vice versa.
RBD11, a bioengineered Rab11-binding module for visualizing and analyzing endogenous Rab11
Authors: Osaki Futaba , Matsui Takahide , Hiragi Shu , Homma Yuta , Fukuda Mitsunori
Published: January 2021

The small GTPase Rab11 plays pivotal roles in diverse physiological phenomena, including the recycling of membrane proteins, cytokinesis, neurite outgrowth, and epithelial morphogenesis. One effective method of analyzing the function of endogenous Rab11 is to overexpress a Rab11-binding domain of one of its effectors, e.g., the C-terminal domain of Rab11-FIP2 (Rab11-FIP2-C), as a dominant-negative construct. However, the drawback of this method is the broader Rab binding specificity of the effector domain, because Rab11-FIP2-C binds to Rabs other than Rab11, e.g., to Rab14 and Rab25. In this study, we bioengineered an artificial Rab11-specific binding domain, named RBD11. Expression of RBD11 visualized endogenous Rab11 without affecting its localization or function, whereas expression of a tandem RBD11, named 2×RBD11, inhibited epithelial morphogenesis and induced a multi-lumen phenotype characteristic of Rab11-deficient cysts. We also developed two tools for temporally and reversibly analyzing Rab11-dependent membrane trafficking: tetracycline-inducible 2×RBD11 and an artificially oligomerized domain (FM)-tagged RBD11.
The rapid evolution of flagellar ion-selectivity in experimental populations ofE. coli
Authors: Ridone Pietro , Ishida Tsubasa , Lin Angela , Humphreys David T , Giannoulatou Eleni , Sowa Yoshiyuki , Baker Matthew A. B.
Published: January 2021

Determining which cellular processes facilitate adaptation requires a tractable experimental model where an environmental cue can generate variants which rescue function. The Bacterial Flagellar Motor (BFM) is an excellent candidate – an ancient and highly conserved molecular complex for propulsion which navigates bacteria towards favourable environments. In most species, rotation is powered by H+or Na+ion transit through the torque-generating stator subunit of the motor complex. The ion that drives the rotor has changed over evolutionary timescales but the molecular basis of this selectivity remains unknown.

Here we used CRISPR engineering to replace the nativeEscherichia coliH+-powered stator with Na+-powered stator genes and report the rapid and spontaneous reversion of our edit in a low sodium environment. We followed the evolution of the stators during their reversion to H+-powered motility and used whole genome and transcriptome sequencing to identify both flagellar- and non-flagellar-associated genes involved in the cell’s adaptation. Our transplant of an unfit protein and the cells’ rapid response to this edit demonstrates the adaptability of the stator subunit and highlights the hierarchical modularity of the flagellar motor.
HP1 oligomerization compensates for low-affinity H3K9me recognition and provides a tunable mechanism for heterochromatin-specific localization
Authors: Biswas Saikat , Karslake Joshua D. , Chen Ziyuan , Farhat Ali , Freddolino Peter L. , Biteen Julie S. , Ragunathan Kaushik
Published: January 2021

HP1 proteins bind with low affinity but high specificity to histone H3 lysine 9 methylation (H3K9me), forming transcriptionally inactive genomic compartments referred to as heterochromatin. How HP1 proteins traverse a complex and crowded chromatin landscape on the millisecond timescale and yet recognize H3K9me with high specificity remains paradoxical. Here, we visualize the single-molecule dynamics of an HP1 homolog, the fission yeast Swi6, in its native chromatin environment. By analyzing the motions of individual Swi6 molecules, we identify mobility states that map to discrete biochemical intermediates. Using mutants that perturb Swi6 H3K9me recognition, oligomerization, or nucleic acid binding, we parse the mechanism by which each biochemical property affects protein dynamics. We find that rather than enhancing chromatin binding, nucleic acid interactions, compete with and titrates Swi6 away from heterochromatin. However, as few as four tandem Swi6 chromodomains are necessary and sufficient to restore H3K9me-dependent localization. Our studies propose propose that HP1 oligomerization stabilizes higher-order protein configurations of a defined stoichiometry that facilitates high-specificity H3K9me recognition and outcompetes the inhibitory effects of nucleic acid-binding.
A Developmental Role for Microglial Presenilin 1 in Memory
Authors: Ledo Jose Henrique , Azevedo Estefania P. , Medrihan Lucian , Cheng Jia , Silva Hernandez M. , McCabe Kathryn , Bamkole Michael , Lafaille Juan J. , Friedman Jeffrey M. , Stevens Beth , Greengard Paul
Published: January 2021

Microglia, the macrophages of the brain, are increasingly recognized to play a key role in synaptic plasticity and function; however, the underlying mechanisms remain elusive. Presenilin 1 (PS1) is an essential protein involved in learning and memory, through neuronal mechanisms. Loss of Presenilin function in neurons impairs synapse plasticity and causes cognitive deficits in mice. Surprisingly, here we show memoryenhancementin mice by deleting PS1 selectively in microglia. We further demonstrate increased synapse transmission andin vivoneuronal activity in mice by depleting PS1 during microglial development, but not after microglial maturation. Remarkably, conditional deletion of PS1 in microglia during development increased memory retention in adulthood and was dependent on the NMDA receptor subunit GluN2B. In vivo calcium imaging of freely behaving mice revealed increased amplitude of neuronal Ca2+ transients in the CA1 hippocampus ofPS1 cKOmice compared to control mice, suggesting a greater CA1 engagement during novel object exploration. Finally, loss of PS1 in microglia mitigated synaptic and cognitive deficits in a mouse model of Alzheimer’s disease. Together our results reveal a novel mechanism and function of PS1 in microglia in which modulation can enhance neuronal activity, learning and memory in mice.
Kinetics and correlates of the neutralizing antibody response to SARS-CoV-2
Authors: Vanshylla Kanika , Di Cristanziano Veronica , Kleipass Franziska , Dewald Felix , Schommers Philipp , Gieselmann Lutz , Gruell Henning , Schlotz Maike , Ercanoglu Meryem S , Stumpf Ricarda , Mayer Petra , Heger Eva , Johannis Wibke , Horn Carola , Suárez Isabelle , Jung Norma , Salomon Susanne , Eberhardt Kirsten Alexandra , Fätkenheuer Gerd , Pfeifer Nico , Eggeling Ralf , Augustin Max , Lehmann Clara , Klein Florian
Published: January 2021

A detailed understanding of antibody-based SARS-CoV-2 immunity has critical implications for overcoming the COVID-19 pandemic and for informing on vaccination strategies. In this study, we evaluated the dynamics of the SARS-CoV-2 antibody response in a cohort of 963 recovered individuals over a period of 10 months. Investigating a total of 2,146 samples, we detected an initial SARS-CoV-2 antibody response in 94.4% of individuals, with 82% and 79% exhibiting serum and IgG neutralization, respectively. Approximately 3% of recovered patients demonstrated exceptional SARS-CoV-2 neutralizing activity, defining them as ‘elite neutralizers’. These individuals also possessed effective cross-neutralizing IgG antibodies to SARS-CoV-1 without any known prior exposure to this virus. By applying multivariate statistical modeling, we found that sero-reactivity, age, time since disease onset, and fever are key factors predicting SARS-CoV-2 neutralizing activity in mild courses of COVID-19. Investigating longevity of the antibody response, we detected loss of anti-spike reactivity in 13% of individuals 10 months after infection. Moreover, neutralizing activity had an initial half-life of 6.7 weeks in serum versus 30.8 weeks in purified IgG samples indicating the presence of a more stable and long-term memory IgG B cell repertoire in the majority of individuals recovered from COVID-19. Our results demonstrate a broad spectrum of the initial SARS-CoV-2 neutralizing antibody response depending on clinical characteristics, with antibodies being maintained in the majority of individuals for the first 10 months after mild course of COVID-19.
Do examinations prepare students for higher education? A lesson from the Covid-19 lockdown
Authors: Harriet L Jones , Valentina Zini , Jon R Green , John R Prendergast , Jon Scott
Published: January 2021

The COVID-19 pandemic caused severe disruption to education in the UK in 2020, with most of the school teaching moving online and national school examinations being cancelled. This was particularly disruptive for those taking end of school examinations in preparation for higher education. Biological science courses require students to absorb a lot of new vocabulary and concepts, with examinations traditionally focusing on content recall rather than reasoning. Students who had entered university in September 2019 were compared with those arriving in September 2020 with respect to their knowledge of bioscience vocabulary and understanding of key concepts. Results showed no significant difference between those who had gone through the examination process in 2019 relative to those who had not, in 2020. This suggests the cramming of information for examinations has no detectable effect on the knowledge and understanding of biology that students take with them to university.
Dendritic membrane resistance modulates activity-induced Ca2+influx in oxytocinergic magnocellular neurons of mouse PVN
Authors: Sheng Wanhui , Harden Scott W. , Tan Yalun , Krause Eric G. , Frazier Charles J.
Published: January 2021

Hypothalamic oxytocinergic magnocellular neurons have a fascinating ability to release peptide from both their axon terminals and from their dendrites. Existing data indicates there is a flexible relationship between somatic activity and dendritic release, but the mechanisms governing this relationship are not completely understood. Here we use a combination of electrical and optical recording techniques to quantify activity-dependent calcium influx in proximal vs. distal dendrites of oxytocinergic magnocellular neurons located in the paraventricular nucleus of the hypothalamus (OT-MCNs). Results reveal that the dendrites of OT-MCNs are weak conductors of somatic voltage changes, and yet activity-induced dendritic calcium influx can be robustly regulated by a diverse set of stimuli that open or close ionophores located along the dendritic membrane. Overall, this study reveals that dendritic membrane resistance is a dynamic and endogenously regulated feature of OT-MCNs that is likely to have substantial functional impact on central oxytocin release.

IMPACT STATEMENT

Activity-induced dendritic calcium influx in oxytocinergic magnocellular neurons can be robustly modulated by a highly diverse set of stimuli acting on distinct types of ionophores expressed along the dendritic membrane.
RNA Pore Translocation with Static and Periodic Forces: Effect of Secondary and Tertiary Elements on Process Activation and Duration
Authors: Becchi Matteo , Chiarantoni Pietro , Suma Antonio , Micheletti Cristian
Published: January 2021

We use MD simulations to study the pore translocation properties of a pseudoknotted viral RNA. We consider the 71-nucleotide long xrRNA from Zika virus and establish how it responds when driven through a narrow pore by static or periodic forces applied to either one of the two termini. Unlike the case of fluctuating homopolymers, the onset of translocation is significantly delayed with respect to the application of static driving forces. Because of the peculiar xrRNA architecture, activation times can differ by orders of magnitude at the two ends. Instead, translocation duration is much smaller than activation times and occurs on timescales comparable at the two ends. Periodic forces amplify significantly the differences at the two ends, both for activation times and translocation duration. Finally, we use a waiting-times analysis to examine the systematic slowing-downs in xrRNA translocations and associate them to the hindrance of specific secondary and tertiary elements of xrRNA. The findings ought to be useful as a reference to interpret and design future theoretical and experimental studies of RNA translocation.
Interpretable deep recommender system model for prediction of kinase inhibitor efficacy across cancer cell lines
Authors: Koras Krzysztof , Kizling Ewa , Juraeva Dilafruz , Staub Eike , Szczurek Ewa
Published: January 2021

Computational models for drug sensitivity prediction have the potential to revolutionise personalized cancer medicine. Drug sensitivity assays, as well as profiling of cancer cell lines and drugs becomes increasingly available for training such models. Machine learning methods for drug sensitivity prediction must be optimized for: (i) leveraging the wealth of information about both cancer cell lines and drugs, (ii) predictive performance and (iii) interpretability. Multiple methods were proposed for predicting drug sensitivity from cancer cell line features, some in a multi-task fashion. So far, no such model leveraged drug inhibition profiles. Recent neural network-based recommender systems arise as models capable of predicting cancer cell line response to drugs from their biological features with high prediction accuracy. These models, however, require a tailored approach to model interpretability. In this work, we develop a neural network recommender system for kinase inhibitor sensitivity prediction called DEERS. The model utilizes molecular features of the cancer cell lines and kinase inhibition profiles of the drugs. DEERS incorporates two autoencoders to project cell line and drug features into 10-dimensional hidden representations and a feed-forward neural network to combine them into response prediction. We propose a novel model interpretability approach offering the widest possible assessment of the specific genes and biological processes that underlie the action of the drugs on the cell lines. The approach considers also such genes and processes that were not included in the set of modeled features. Our approach outperforms simpler matrix factorization models, achieving R=0.82 correlation between true and predicted response for the unseen cell lines. Using the interpretability analysis, we evaluate correlation of all human genes with each of the hidden cell line dimensions. Subsequently, we identify 67 biological processes associated with these dimensions. Combined with drug response data, these associations point at the processes that drive the cell line sensitivity to particular compounds. Detailed case studies are shown for PHA-793887, XMD14-99 and Dabrafenib. Our framework provides an expressive, multitask neural network model with a custom interpretability approach for inferring underlying biological factors and explaining cancer cell response to drugs.
Mechanotaxis directsPseudomonas aeruginosatwitching motility
Authors: Kühn Marco J. , Talà Lorenzo , Inclan Yuki , Patino Ramiro , Pierrat Xavier , Vos Iscia , Al-Mayyah Zainebe , MacMillan Henriette , Negrete Jose , Engel Joanne N. , Persat Alexandre
Published: January 2021

The opportunistic pathogenPseudomonas aeruginosaexplores surfaces using twitching motility powered by retractile extracellular filaments called type IV pili. Single cells twitch by successive pili extension, attachment and retraction. However, whether and how single cells control twitching migration remains unclear. We discovered thatP. aeruginosaactively directs twitching in the direction of mechanical input from type IV pili, in a process we call mechanotaxis. The Chp chemotaxis-like system controls the balance of forward and reverse twitching migration of single cells in response to the mechanical signal. On surfaces, Chp senses type IV pili attachment at one pole thereby sensing a spatially-resolved signal. As a result, the Chp response regulators PilG and PilH control the polarization of the extension motor PilB. PilG stimulates polarization favoring forward migration, while PilH inhibits polarization inducing reversal. Subcellular segregation of PilG and PilH efficiently orchestrates their antagonistic functions, ultimately enabling rapid reversals upon perturbations. This distinct localization of response regulators establishes a signaling landscape known as local-excitation, global-inhibition in higher order organisms, identifying a conserved strategy to transduce spatially-resolved signals. Our discovery finally resolves the function of the Chp system and expands our view of the signals regulating motility.
Deep learning-based real-time detection of novel pathogens during sequencing
Authors: Bartoszewicz Jakub M. , Genske Ulrich , Renard Bernhard Y.
Published: January 2021

Novel pathogens evolve quickly and may emerge rapidly, causing dangerous outbreaks or even global pandemics. Next-generation sequencing is the state-of-the-art in open-view pathogen detection, and one of the few methods available at the earliest stages of an epidemic, even when the biological threat is unknown. Analyzing the samples as the sequencer is running can greatly reduce the turnaround time, but existing tools rely on close matches to lists of known pathogens and perform poorly on novel species. Machine learning approaches can predict if single reads originate from more distant, unknown pathogens, but require relatively long input sequences and processed data from a finished sequencing run. Incomplete sequences contain less information, leading to a trade-off between sequencing time and detection accuracy. Using a workflow for real-time pathogenic potential prediction, we investigate which subsequences already allow accurate inference. We train deep neural networks to classify Illumina and Nanopore reads and integrate the models with HiLive2, a real-time Illumina mapper. This approach outperforms alternatives based on machine learning and sequence alignment on simulated and real data, including SARS-CoV-2 sequencing runs. After just 50 Illumina cycles, we observe an 80-fold sensitivity increase compared to real-time mapping. The first 250bp of Nanopore reads, corresponding to 0.5s of sequencing time, are enough to yield predictions more accurate than mapping the finished long reads. The approach could also be used for screening synthetic sequences against biosecurity threats.
Selective uptake into inflamed human intestinal tissue and immune cell targeting by wormlike polymer micelles
Authors: Gardey Elena , Sobotta Fabian H. , Haziri Drilon , Grunert Philip C. , Kuchenbrod Maren T. , Gruschwitz Franka V. , Hoeppener Stephanie , Schumann Michael , Gaßler Nikolaus , Stallmach Andreas , Brendel Johannes C.
Published: January 2021

Over the 21st century, inflammatory bowel disease (IBD) has become a global disease with no causal therapeutic options. Selective targeting of inflamed areas in the gastrointestinal tract could be an effective treatment circumventing severe side effects for healthy tissue. Our study demonstrates that the shape of polymeric nanostructures represents so far rarely addressed key to required tissue selectivity in the intestine.Ex vivoexperiments on human colonic biopsies revealed that crosslinked wormlike micelles featuring a dense poly(ethylene oxide) (PEO) shell exclusively enter the inflamed human mucosa without affecting healthy tissue. Similarly designed spherical micelles (∼25 nm) or vesicles (∼120 nm) penetrate both tissues or were barely uptaken at all, respectively. Moreover, it was found that the particles colocalize with immune cells in the lamina propria facilitating a specific targeting of the main pro-inflammatory cells within the diseased human mucosa. These findings demonstrate an untapped potential in particle design and enable new vistas for an effective treatment of IBD.
Generating novel protein sequences using Gibbs sampling of masked language models
Authors: Johnson Sean R. , Monaco Sarah , Massie Kenneth , Syed Zaid
Published: January 2021

Recently developed language models (LMs) based on deep neural networks have demonstrated the ability to generate fluent natural language text. LMs pre-trained on protein sequences have shown state of the art performance on a variety of downstream tasks. Protein LMs have also been used to generate novel protein sequences. In the present work we use Gibbs sampling of BERT-style LMs, pre-trained on protein sequences using the masked language modeling task, to generate novel protein sequences. We evaluate the quality of the generated sequences by comparing them to natural sequences from the same family. In particular, we focus on proteins from the chorismate mutase type II family, which has been used in previous work as an example target for protein generative models. We find that the Gibbs sampling process on BERT-style models pretrained on millions to billions of protein sequences is able to generate novel sequences that retain key features of related natural sequences. Further, we find that smaller models fine-tuned or trained from scratch on family-specific data are able to equal or surpass the generation quality of large pre-trained models by some metrics. The ability to generate novel natural-like protein sequences could contribute to the development of improved protein therapeutics and protein-catalysts for industrial chemical production.
Computational Analysis of Protein Stability and Allosteric Interaction Networks in Distinct Conformational Forms of the SARS-CoV-2 Spike D614G Mutant: Reconciling Functional Mechanisms through Allosteric Model of Spike Regulation
Authors: Verkhivker Gennady M. , Agajanian Steve , Oztas Denis , Gupta Grace
Published: January 2021

Structural and biochemical studies SARS-CoV-2 spike mutants with the enhanced infectivity have attracted significant attention and offered several mechanisms to explain the experimental data. The development of a unified view and a working model which is consistent with the diverse experimental data is an important focal point of the current work. In this study, we used an integrative computational approach to examine molecular mechanisms underlying functional effects of the D614G mutation by exploring atomistic modeling of the SARS-CoV-2 spike proteins as allosteric regulatory machines. We combined coarse-grained simulations, protein stability and dynamic fluctuation communication analysis along with network-based community analysis to simulate structures of the native and mutant SARS-CoV-2 spike proteins in different functional states. The results demonstrated that the D614 position anchors a key regulatory cluster that dictates functional transitions between open and closed states. Using molecular simulations and mutational sensitivity analysis of the SARS-CoV-2 spike proteins we showed that the D614G mutation can improve stability of the spike protein in both closed and open forms, but shifting thermodynamic preferences towards the open mutant form. The results offer support to the reduced shedding mechanism of S1 domain as a driver of the increased infectivity triggered by the D614G mutation. Through distance fluctuations communication analysis, we probed stability and allosteric communication propensities of protein residues in the native and mutant SARS-CoV-2 spike proteins, providing evidence that the D614G mutation can enhance long-range signaling of the allosteric spike engine. By employing network community analysis of the SARS-CoV-2 spike proteins, our results revealed that the D614G mutation can promote the increased number of stable communities and allosteric hub centers in the open form by reorganizing and enhancing the stability of the S1-S2 inter-domain interactions and restricting mobility of the S1 regions. This study provides atomistic-based view of the allosteric interactions and communications in the SARS-CoV-2 spike proteins, suggesting that the D614G mutation can exert its primary effect through allosterically induced changes on stability and communications in the residue interaction networks.
Evaluation of a Recessive Male Floret Color in Cultivated Northern Wild Rice (Zizania palustrisL.) for Pollen-Mediated Gene Flow Studies
Authors: Gietzel Clare , Duquette Jacques , McGilp Lillian , Kimball Jennifer
Published: January 2021

Northern wild rice (NWR;Zizania palustrisL.) is a wind-pollinated, annual, aquatic grass that grows naturally in the Great Lakes Region (GLR) of the United States and Canada, and is also cultivated in flooded paddies, predominantly in California and Minnesota. A better understanding of pollen-mediated gene flow is needed within the species for both conservation and breeding efforts as cultivation occurs within the species natural range and spatially-isolated, paddy structures are limited within breeding programs. Widely cited pollen travel research in NWR demonstrated that pollen could travel at least 3200m. However, a population segregating for male sterility was used as the pollen recipient in the study and was determined to not be adequate for NWR pollen travel studies. Here, we present the characterization of a recessive white male floret (WMF) population in contrast to the dominant, purple male floret (PMF) color of cultivated NWR along with estimates of pollen-mediated gene flow in a cultivated paddy setting. Studies conducted in 2018 and 2019 revealed that the primary amount of pollen-mediated gene flow occurred within the first 7m from the PMF donor source with no gene flow detected past 63m. These results suggest that the likelihood of pollen-mediated gene flow between cultivated NWR and natural stands remains low. We also identified a strong linkage between male floret, auricle, and culm color. This study demonstrates that the WMF trait is an excellent candidate for use in pollen-mediated gene flow studies in NWR.
STING agonism enhances anti-tumor immune responses and therapeutic efficacy of PARP inhibition inBRCA-associated breast cancer
Authors: Pantelidou Constantia , Jadhav Heta , Kothari Aditi , Liu Renyan , Guerriero Jennifer L. , Shapiro Geoffrey I.
Published: January 2021

Poly (ADP-ribose) polymerase (PARP) inhibitors exert their efficacy by inducing synthetic lethal effects, as well as cGAS/STING-mediated immune responses in BRCA- and other homologous recombination repair-deficient cancer cells. Here we investigated whether the immunologic and therapeutic effects of PARP inhibition in BRCA-deficient breast cancer models could be augmented by synthetic cyclic dinucleotide agonists of STING. Combined PARP inhibition and STING agonism induced a greater degree of STING pathway activation and proinflammatory cytokine production compared to monotherapies in BRCA1-deficient human and mouse triplenegative breast cancer cell lines. In a mouse model of BRCA1-deficient TNBC, the combination also induced an improved immune response compared to either monotherapy alone, evidenced by a greater degree of cytotoxic T cell recruitment and activation, and enhanced dendritic cell activation and antigen presentation. Nanostring mRNA analysis indicated that combinatorial effects were the result of augmented interferon signaling and antigen processing, as well as of heightened leukocyte and dendritic cell functions. Finally, the combination markedly improved anti-tumor efficacyin vivocompared to monotherapy treatment, with evidence of complete tumor clearance and prolongation of survival. These results support the development of combined PARP inhibition and STING agonism inBRCA-associated breast cancer.
Deep Directed Evolution of Solid Binding Peptides for Quantitative Big-data Generation
Authors: Yucesoy Deniz T. , Rath Siddharth S. , Rodriguez Jacob L. , Francis-Landau Jonathan , Nakano-Baker Oliver , Sarikaya Mehmet
Published: January 2021

Proteins have evolved over millions of years to mediate and carry-out biological processes efficiently. Directed evolution approaches have been used to genetically engineer proteins with desirable functions such as catalysis, mineralization, and target-specific binding. Next-generation sequencing technology offers the capability to discover a massive combinatorial sequence space that is costly to sample experimentally through traditional approaches. Since the permutation space of protein sequence is virtually infinite, and evolution dynamics are poorly understood, experimental verifications have been limited. Recently, machine-learning approaches have been introduced to guide the evolution process that facilitates a deeper and denser search of the sequence-space. Despite these developments, however, frequently used high-fidelity models depend on massive amounts of properly labeled quality data, which so far has been largely lacking in the literature. Here, we provide a preliminary high-throughput peptide-selection protocol with functional scoring to enhance the quality of the data. Solid binding dodecapeptides have been selected against molybdenum disulfide substrate, a two-dimensional atomically thick semiconductor solid. The survival rate of the phage-clones, upon successively stringent washes, quantifies the binding affinity of the peptides onto the solid material. The method suggested here provides a fast generation of preliminary data-pool with ∼2 million unique peptides with 12 amino-acids per sequence by avoiding amplification. Our results demonstrate the importance of data-cleaning and proper conditioning of massive datasets in guiding experiments iteratively. The established extensive groundwork here provides unique opportunities to further iterate and modify the technique to suit a wide variety of needs and generate various peptide and protein datasets. Prospective statistical models developed on the datasets to efficiently explore the sequence-function space will guide towards the intelligent design of proteins and peptides through deep directed evolution. Technological applications of the future based on the peptide-single layer solid based bio/nano soft interfaces, such as biosensors, bioelectronics, and logic devices, is expected to benefit from the solid binding peptide dataset alone. Furthermore, protocols described herein will also benefit efforts in medical applications, such as vaccine development, that could significantly accelerate a global response to future pandemics.
Evolutionary selection on synonymous codons in RNA G-quadruplex structural region
Authors: Xu Yuming , Qi Ting , Lu Zuhong , Zhou Tong , Gu Wanjun
Published: January 2021

In addition to the amino acid sequence information, synonymous codons can encode multiple regulatory and structural signals in protein coding region. In this study, we investigated how synonymous codons have been adapted to the formation of RNA G-quadruplex (rG4) structure. We found a universal selective pressure acting on synonymous codons to facilitate rG4 formation in five eukaryotic organisms. WhileG-rich codons are preferred in rG4 structural region,C-rich codons are selectively unpreferred for rG4 structures. Gene’s codon usage bias, nucleotide composition and evolutionary rate can account for the selective variations on synonymous codons among rG4 structures within a species. Moreover, rG4 structures in translational initiation region showed significantly higher selective pressures than those in translational elongation region. These results bring us another dimension of evolutionary selection on synonymous codons for proper RNA structure and function.
Neutralization of SARS-CoV-2 spike 69/70 deletion, E484K, and N501Y variants by BNT162b2 vaccine-elicited sera
Authors: Xie Xuping , Liu Yang , Liu Jianying , Zhang Xianwen , Zou Jing , Fontes-Garfias Camila R. , Xia Hongjie , Swanson Kena A. , Cutler Mark , Cooper David , Menachery Vineet D. , Weaver Scott , Dormitzer Philip R. , Shi Pei-Yong
Published: January 2021

We engineered three SARS-CoV-2 viruses containing key spike mutations from the newly emerged United Kingdom (UK) and South African (SA) variants: N501Y from UK and SA; 69/70-deletion+N501Y+D614G from UK; and E484K+N501Y+D614G from SA. Neutralization geometric mean titers (GMTs) of twenty BTN162b2 vaccine-elicited human sera against the three mutant viruses were 0.81- to 1.46-fold of the GMTs against parental virus, indicating small effects of these mutations on neutralization by sera elicited by two BNT162b2 doses.
Lysosomal-Immune Axis Is Associated with COVID 19 Disease Severity: Insights from Patient Single Cell Data
Authors: Pande Rahul , Teeple Erin , Huang Weixiao , Klinger Katherine W. , Rajpal Deepak , Kumar Dinesh
Published: January 2021

SARS-COV-2 has become a leading cause of illness, hospitalizations, and deaths worldwide yet heterogeneity in disease morbidity remains a conundrum. In this study, we analyzed publicly available single-cell RNA-seq data from 75076 cells sequenced from clinically staged COVID-19 patients using a network approach and identified lysosomal-immune axis as a factor significantly associated with disease severity. Our results suggest modulation of lysosomal-immune pathways may present a novel drug-targeting strategy to attenuate SARS-Cov-2 infections.
Structure of 1,6-anhydro-β-D-glucopyranose in plastic crystal, orientational glass, liquid and ordinary glass forms: molecular modeling and X-ray diffraction studies
Authors: Jurkiewicz Karolina , Glajcar Wojciech , Kamiński Kamil , Temleitner László , Burian Andrzej
Published: January 2021

The structures of the plastic crystal (PC), orientational glass (OTG), liquid (LQ) and ordinary glass (OG) phases of 1,6-anhydro-β-D-glucopyranose (levoglucosan) have been investigated using X-ray diffraction and molecular modeling. The experimental diffraction data in the forms of static structure factors and pair distribution functions are analyzed in reciprocal and real spaces and compared with results of model-based simulations. A new approach to modeling the structure of the disordered phases, taking into account the intermolecular scattering contribution in the form of sharp Bragg peaks, the slowly varying intensity associated with intramolecular correlations and the diffusive component resulting from structural disorder, is applied. In the case of the LQ and OG samples, reverse Monte Carlo simulations are also used. The PC and OTG phases show long-range ordering of the hexagonal close-packed (hcp)-type structure up to 120 Å with random orientation of the molecules. Assuming a rigid molecular skeleton, isotropic free rotations of the molecules about their geometrical center in full and limited angular ranges are generated in theoretical models of the structure. It is demonstrated that the adoption of free rotations of the molecules leads to the best fits to experimental data for each studied phase of levoglucosan. The diffraction patterns of the LQ and OG samples show a relatively sharp first peak originating from quasi-Bragg planes of the densely packed face-centered cubic (fcc) type molecular arrangement. Moreover, the slowly varied intensity component of LQ and OG is practically the same as that of PC and OTG, suggesting that the intramolecular structure of these four phases does not change. Interestingly, structural correlations for the disordered LQ and OG states extend surprisingly far, up to about 50 Å. In addition, for all levoglucosan phases investigated, the paracrystalline disorder imposed on the generated models resulted in better compliance with the experimental data.
Key concepts for dietetic curriculum: An observational study of Australian dietitians' perceptions
Authors: Tweedie Judith , Wright Hattie H. , Palermo Claire , Pelly Fiona E.
Published: January 2021

Aim

A concept‐based approach to dietetic curriculum design has been proposed to prevent content overload and promote critical thinking. Fifty‐six concepts were identified in a previous study. The aim of the present study was to investigate whether the dietetic profession views these concepts as representative of current practice and key for nutrition and dietetics education, and identify any new or emerging concepts.

Methods

Accredited Practising Dietitians (APDs) were invited to participate in a self‐administered online survey that included scale responses on the relevance of the 56 concepts and open‐ended suggestions of additional concepts. Respondent characteristics were also collected.

Results

Ninety‐eight APDs completed the survey. Greater than 65% of respondents agreed/strongly agreed that all 56 concepts were relevant. There was less agreement on the concepts of acid‐base balance; leadership; management; physical activity, exercise and health; quality assurance and improvement; risk; safety; stakeholder; standards; sustainability; systems and technology and health informatics. Respondents working in regional, rural and remote areas were less likely to agree that leadership was a key concept (χ2 = 4.45, P = .035). Respondents working in teaching and education were more likely to agree that sustainability was a key concept (χ2 = 7.02, P = .008). No new concepts were identified.

Conclusions

The existing 56 concepts were considered key for nutrition and dietetics education. Although the respondents to this survey view these concepts as relevant to current practice, this may not represent the entire profession. It is yet to be determined if the concepts will meet future priorities for the dietetic workforce.
Food acculturation experiences of new Iranian skilled migrant mothers in South Australia
Authors: Kavian Foorough , Coveney John , Matwiejczyk Louisa , Mehta Kaye
Published: January 2021

Aim

This research aimed to investigate the food acculturation experiences of Iranian mothers who have migrated to Australia.

Methods

The study used qualitative methodology to interview seven mothers with children aged 5 to 15 years, who: carried primary responsibility for family food provisioning; arrived in Australia within the last 5 years; and spoke reasonably fluent English.

Results

Seven mothers were interviewed, and the findings revealed three broad themes: (a) adjusting to foods/foodways in Australia (b) sociocultural identity and (c) children and intergenerational conflict. The study highlighted psychosocial and economic stresses associated with food acculturation for this immigrant group. The impact of food acculturation on immigrant health is intricately linked to the complex balance between maintaining traditional cultural identity and practices, while at the same time adapting to the food culture and practices of the new home.

Conclusions

Dietitians and healthcare professionals working with such immigrant groups need to consider food acculturation stress as a factor contributing to the health risks of new immigrants.
New model species for arctic‐alpine plant molecular ecology
Authors: Pyhäjärvi Tanja , Mattila Tiina M.
Published: January 2021

Arctic and alpine, high latitude and high elevation environments are one of the most stressful environments for species to inhabit. This harshness manifests itself in lower species richness in comparison to more southern vegetation zones (Francis & Currie, 2003). Furthermore, the climatic oscillations—past and predicted—have the most dramatic effect on these ecosystems. For example, in regions of continental ice sheets—the northernmost part of Western Europe and North America—the Arctic species assemblages are no older than a few thousands of years, which is a relatively short period from an evolutionary perspective. Although similar environments may have existed further south during the Ice Age, allowing some preadaptation for the Arctic species, the current habitat is a unique combination of environmental factors such as the climate, soil, bedrock, and photoperiod. Hence, understanding the evolutionary forces shaping Arctic‐alpine species will be important for predicting these vulnerable environments’ population viability and adaptive potential in the future. In this issue of Molecular Ecology Resources, Nowak et al. (Molecular Ecology Resources) present extensive genome‐wide resources for an Arctic‐alpine plant Draba nivalis. This adds a valuable new member into the cabbage family models for evolutionary genetics and adaptation studies, to accompany e.g., Arabidopsis (Nature Genetics, 43, 476; Nature, 408, 796), Arabis (Nature Plants, 1, 14023) and Capsella (Nature Genetics, 45, 831). A whole new avenue will open up for molecular ecological studies not only for D. nivalis, but the whole large Draba genus with its diverse ecological and evolutionary characteristics.