bluuebunny/crossref_metadata_2025 huggingface dataset:
Segregation and Group Threat: Specifying Hispanic-White Punishment Disparity
Authors: Zvonkovich Jordan , Ulmer Jeffery T
Published: June 2023

Evidence of racial disparity in punishment has been pervasive in the U.S. criminal justice system. Furthermore, a growing body of literature suggests that racial and ethnic disparities in criminal punishment, typically motivated by group threat perspectives, vary in relation to social and contextual conditions of court jurisdictions. One important factor relevant to minority threat and intergroup contact is segregation, yet research on social contexts and criminal sentencing has largely ignored this feature of local social structure. However, segregation might condition the effects of minority population size on dominant group threat responses in social control. Focusing on Hispanic-White segregation, we assess competing hypotheses regarding segregation’s role in conditioning Hispanic-White punishment disadvantage. Pennsylvania, which has recently undergone significant population change related to these processes, presents a unique and valuable context for study. Analyses of statewide sentencing data from 2013–2017 along with Census and American Community Survey data, reveal that Hispanic-White residential segregation seems to foster greater Hispanic punishment disadvantage. Moreover, segregation specifies the association between local Hispanic population size and Hispanic-White incarceration disparity. In counties with both greater than average Hispanic population share and greater segregation, Hispanic defendants faced even greater incarceration disparities.
Artificial Intelligence Supports Automated Characterization of Differentiated Human Pluripotent Stem Cells
Authors: Marzec-Schmidt Katarzyna , Ghosheh Nidal , Stahlschmidt Sören Richard , Küppers-Munther Barbara , Synnergren Jane , Ulfenborg Benjamin
Published: June 2023

Revolutionary advances in AI and deep learning in recent years have resulted in an upsurge of papers exploring applications within the biomedical field. Within stem cell research, promising results have been reported from analyses of microscopy images to, that is, distinguish between pluripotent stem cells and differentiated cell types derived from stem cells. In this work, we investigated the possibility of using a deep learning model to predict the differentiation stage of pluripotent stem cells undergoing differentiation toward hepatocytes, based on morphological features of cell cultures. We were able to achieve close to perfect classification of images from early and late time points during differentiation, and this aligned very well with the experimental validation of cell identity and function. Our results suggest that deep learning models can distinguish between different cell morphologies, and provide alternative means of semi-automated functional characterization of stem cell cultures.
Advancing the science of policy implementation: a call to action for the implementation science field
Authors: Chriqui Jamie F , Asada Yuka , Smith Natalie Riva , Kroll-Desrosiers Aimee , Lemon Stephenie C
Published: June 2023

Public policies have been essential in addressing many of the most pressing public health problems in the USA and around the world. A large and convincing body of multidisciplinary research has established the impacts or effectiveness of public policies, such as smoke-free air laws and nutrition standards, on improving health outcomes and behaviors. Most of this research assumes that because an evidence-based policy is adopted or takes effect, it is implemented as intended. This assumption, however, is often incorrect. Like with clinical guidelines and other interventions, implementation science has an important role to play in promoting the uptake and implementation of evidence-based public policies that promote public health. To realize this potential, there remains a critical need to first establish a common understanding of what public policy is, the role of specific policies in the context of implementation (i.e., is it the evidence-based intervention or the implementation strategy?), and to establish an appropriate methodological foundation for the field of policy implementation science. We recommend that the field must evolve to (i) include policy experts and actors on policy implementation science study teams; (ii) identify theories, models, and frameworks that are suitable for policy implementation science; (iii) identify policy implementation strategies; (iv) adapt and/or identify study designs best suited for policy implementation science research; and (v) identify appropriate policy implementation outcome measures.
Local adaptation to aridity in a widely distributed angiosperm tree species is mediated by seasonal increase of sugars and reduced growth
Authors: Piper Frida I , Fajardo Alex
Published: June 2023

Trees in dry climates often have higher concentrations of total non-structural carbohydrates (NSC = starch + soluble sugars [SS]) and grow less than conspecifics in more humid climates. This pattern might result from the growth being more constrained by aridity than the carbon (C) gain, or reflect local adaptation to aridity, since NSC fuel metabolism and ensure adequate osmoregulation through the supply of SS, while low growth reduces water and C demands. It has been further proposed that C allocation to storage could come at the expense of growth (i.e., a growth–storage trade-off). We examined whether NSC and growth reflect the local adaptation to aridity in Embothrium coccineum J. R. Forst & G. Forst. (Proteaceae), a species with an exceptionally wide niche. To control for any influence of phenotypic plasticity on NSC and growth, we collected seeds from dry (46° 16′S, 71° 55′W, 500 mm year−1) and moist (45° 24′S, 72° 40′W, >2500 mm year−1) climates and grew seedlings in a common garden experiment for 3 years. We then compared the NSC and SS concentrations and pools (i.e., total contents) and the biomass of seedlings at spring, summer and fall. Seedlings from the dry climate had significantly lower biomass and similar NSC concentrations and pools as seedlings from moist climate, suggesting that reduced growth in arid environments does not result from a prioritization of C allocation to storage but that it confers advantages under aridity (e.g., lower transpiration area). Across organs, starch and NSC decreased similarly in seedlings from both climates from spring onward. However, root and stem SS concentrations increased during the growing season, and these increases were significantly higher in seedlings from the dry climate. The greater SS accumulation in seedlings from the dry climate compared with those from the moist climate demonstrates ecotypic differentiation in the seasonal dynamics of SS, suggesting that SS underlie local adaptation to aridity.
The retinal RNA editome is concentrated in photoreceptor-specific genes and genetically linked to vision loss
Authors: Ansell B RE , Bonelli R , Thomas S N , Manda A , Ratnapriya R , Pinelli M , Swaroop A , diBernardo D , Banfi S , Bahlo M
Published: June 2023

BACKGROUND

Conversion of adenosine in RNA to inosine by ADAR enzymes, termed ‘RNA editing’, occurs at thousands of sites across the transcriptome, and is required for healthy development of the central nervous system. RNA editing can modify protein sequences, and dampen the innate immune response. RNA editing is tissue-specific and partly genetically determined. Modifications of RNA editing sites contribute to multiple diseases, particularly neurodevelopmental and neuropsychiatric diseases. Despite the importance of RNA editing in the brain, nothing is known about this process in the human retina. We describe the landscape of retinal editing revealing its importance in key biological processes that underpin vision.

METHODS & RESULTS

We analysed the transcriptomes of >500 donor retinae and identified ∼153,000 high-confidence RNA editing sites. Some 80% of editing sites occurred within protein-coding RNA, with the majority in intronicAlurepeats, and 3’ UTR sequence. Novel retina-specific sites were concentrated in genes related to photoreceptor function and which cause retinitis pigmentosa, most notably in PDE6A. Exonic, protein recoding sites were enriched in zinc-finger domains. AMD subjects exhibit relatively few differences in RNA editing compared to controls, consistent with limited gene expression differences. We identified ∼10,000 editing QTLs. The genetic architecture of editing in the retina resembles the brain, whereas editing and expression QTLs in the retina show modest genetic overlap. We report colocalization between edQTLs and retinal disease GWAS peaks for age-related macular degeneration, glaucoma and macular telangiectasia. These findings provide new insights into epi-transcriptomic regulation of genes critical for vision, and elaborate putative genetic disease driver mechanisms that appear to be independent of changes in gene expression.
Transcriptomic Enrichment of Ferroptosis-Related GeneACSL4in Advanced Hepatic Fibrosis/Cirrhosis: Bioinformatics Analysis and Experimental validation
Authors: Zhang Shuya , Liu Ying , Chen Liping , Liu Yuxuan , Guo Yuqi , Cheng Jilin , Huang Jun
Published: June 2023

Background

Liver fibrosis is a critical part of the clinical process of liver disease that progresses to cirrhosis and even liver cancer, and effective treatment and clinical biomarkers are urgently needed to manage liver fibrosis. Ferroptosis, a notable biological phenomenon that has received attention because of the role it performs in liver fibrosis. The objective of this research is in order to identify key ferroptosis genes related to advanced liver fibrosis/cirrhosis.

Methods

Gene expression differences were analyzed in liver fibrosis liver tissue of hepatitis B virus(HBV)infection patients, non-alcoholic steatohepatitis (NASH) patients and alcoholic hepatitis (AH) patients to obtain overlapping ferroptosis-related genes that are significantly up-regulated. A multigroup comparison was performed to evaluate the diagnostic clinical importance of ferroptosis-related genes of patients in differential degrees of liver fibrosis, and confirmed via gene expression trend analysis.

The differential expression of candidate ferroptosis-related genes through classical carbon tetrachloride (CCl4) induced advanced liver fibrosis mice model were validated by real-time quantitative PCR (qPCR). Correlation analysis was conducted to tentatively identify the connections between hepatic ferroptosis-related genes and key genes participating in functional pathways relevant to liver fibrosis.

Results

We screened and obtained 10 genes related to ferroptosis, all of which were significantly up-regulated in liver tissue from liver fibrosis patients of different etiologies, and identified acyl-CoA synthetase long chain family member 4 (ACSL4) was transcriptomic enriched in patients with HBV infection, NASH, AH-associated advanced liver fibrosis and cirrhotic tissue adjacent to hepatocellular carcinoma (HCC). In CCl4induced advanced liver fibrosis mice model, the hepaticACSL4expression was significantly up-regulated when compared to normal controls. In our study, we also suggest a significant association betweenACSL4and representative genes in liver fibrosis-related pathway.

Conclusion

We found thatACSL4mRNA can effectively differentiate the severity of liver fibrosis, suggesting its potential clinical diagnostic value in patients with liver fibrosis regardless of its etiology.ACSL4may be a promising biomarker, which deserves further research.
Systems immunology of transcriptional responses to viral infection identifies conserved antiviral pathways across macaques and humans
Authors: Ratnasiri Kalani , Zheng Hong , Toh Jiaying , Yao Zhiyuan , Duran Veronica , Donato Michele , Roederer Mario , Kamath Megha , Todd John-Paul M. , Gagne Matthew , Foulds Kathryn E. , Francica Joseph R. , Corbett Kizzmekia S. , Douek Daniel C. , Seder Robert A. , Einav Shirit , Blish Catherine A. , Khatri Purvesh
Published: June 2023

Viral pandemics and epidemics pose a significant global threat, with emerging and re-emerging viruses responsible for four pandemics in the 21st century alone. While macaques have been utilized as a model for understanding viral disease in a controlled setting, it remains unclear how conserved the antiviral responses to diverse viruses are between macaques and humans. To address this critical knowledge gap, we conducted a comprehensive cross-species analysis of transcriptomic data from over 6000 blood samples from macaques and humans infected with one of 31 viruses, including Lassa, Ebola, Marburg, Zika, and dengue. Our findings demonstrate that irrespective of primate or viral species, there are conserved antiviral responses which are consistent regardless of infection phase (acute, chronic, or latent) and viral genome type (DNA or RNA viruses). Moreover, by leveraging longitudinal data from experimental challenges, we identified virus-specific response dynamics such as host responses to Coronaviridae and Orthomyxoviridae infections peaking 1-3 days earlier than responses to Filoviridae and Arenaviridae viral infections. Additionally, through comparative analysis of immune responses across viruses, we identified a unique enrichment of lymphoid cellular response modules in macaque Flaviviridae infection that persists in human responses to dengue. Our results underscore macaque studies as a powerful tool for gaining new insights into viral pathogenesis and immune responses that translate to humans, which can inform viral therapeutic development and enable pandemic preparedness.

One sentence summary

Using longitudinal macaque viral challenge studies, we identified shared and virus-specific responses to infection that replicate in human viral disease - thereby demonstrating the utility of macaque models of viral infection to understand antiviral biology and for pandemic preparedness.
Weak interactions cause poor performance of common network inference models
Authors: Sadykova Dinara , Yearsley Jon M. , Aderhold Andrej , Dondelinger Frank , White Hannah J. , Sanchez Lupe Leon , Ilić Maja , Sadykov Alexander , Emmerson Mark , Caplat Paul
Published: June 2023

Network inference models have been widely applied in ecological, genetic and social studies to infer unknown interactions. However, little is known about how well the models perform and whether they produce reliable results when confronted with networks where weak interactions predominate and for different amounts of data. This is an important consideration as empirical interaction strengths are commonly skewed towards weaker interactions, which is especially relevant in ecological networks, and a number of studies suggest the importance of weak interactions for ensuring the dynamic stability of a system.

Here we investigate four commonly used network methods (Bayesian Networks, Graphical Gaussian Models, L1-regularised regression with the least absolute shrinkage and selection operator, and Sparse Bayesian Regression) and employ network simulations with different interaction strengths to assess their accuracy and reliability.

The results show poor performance, in terms of the ability to discriminate between existing relationships and no relationships, in the presence of weak interactions, for all the selected network inference methods.

Our findings suggest that though these models have some promise for network inference with networks that consist of medium or strong interactions and larger amounts of data, data with weak interactions does not provide enough information for the models to reliably identify interactions. Therefore, networks inferred from data of that type should be interpreted with caution.
A mean-field to capture asynchronous irregular dynamics of conductance-based networks of adaptive quadratic integrate-and-fire neuron models
Authors: Alexandersen Christoffer G. , Duprat Chloé , Ezzati Aitakin , Houzelstein Pierre , Ledoux Ambre , Liu Yuhong , Saghir Sandra , Destexhe Alain , Tesler Federico , Depannemaecker Damien
Published: June 2023

Mean-field models are a class of models used in computational neuroscience to study the behaviour of large populations of neurons. These models are based on the idea of representing the activity of a large number of neurons as the average behaviour of “mean field” variables. This abstraction allows the study of large-scale neural dynamics in a computationally efficient and mathematically tractable manner. One of these methods, based on a semi-analytical approach, has previously been applied to different types of single-neuron models, but never to models based on a quadratic form. In this work, we adapted this method to quadratic integrate-and-fire neuron models with adaptation and conductance-based synaptic interactions. We validated the mean-field model by comparing it to the spiking network model. This mean-field model should be useful to model large-scale activity based on quadratic neurons interacting with conductance-based synapses.
DeepRank-GNN-esm: A Graph Neural Network for Scoring Protein-Protein Models using Protein Language Model
Authors: Xu X. , Bonvin A. M. J. J.
Published: June 2023

Motivation

Protein-Protein interactions (PPIs) play critical roles in numerous cellular processes. By modelling the three-dimensional structures of the correspond protein complexes valuable insights can be obtained, providing, for example, starting points for drug and protein design. One challenge in the modelling process is however the identification of near-native models from the large pool of generated models. To this end we previously developed DeepRank-GNN, a graph neural network that integrates structural and sequence information to enable effective pattern learning at PPI interfaces. Its main features are related to the Position Specific Scoring Matrices (PSSM), which are computationally expensive to generate and significantly limit the algorithm’s usability.

Results

We introduce here DeepRank-GNN-esm that includes as additional features protein language model embeddings from the EMS-2 model. We show that the ESM-2 embeddings can actually replace the PSSM features at no cost in-, or even better performance on two PPI-related tasks: scoring docking poses and detecting crystal artifacts. This new DeepRank version bypasses thus the need of generating PSSM, greatly improving the usability of the software and opening new application opportunities for systems for which PSSM profiles cannot be obtained or are irrelevant (e.g. antibody-antigen complexes).

Availability and implementation

DeepRank-GNN-esm is freely available fromhttps://github.com/DeepRank/DeepRank-GNN-esm
Fine-tuning Protein Embeddings for Generalizable Annotation Propagation
Authors: Dickson Andrew M. , Mofrad Mohammad R. K.
Published: June 2023

A central goal of bioinformatics research is to understand proteins on a functional level, typically by extrapolating from experimental results with the protein sequence information. One strategy is to assume that proteins with similar sequences will also share function. This has the benefit of being interpretable; it gives a very clear idea of why a protein might have a particular function by comparing with the most similar reference example. However, direct machine learning classifiers now outperform pure sequence similarity methods in raw prediction ability. A hybrid method is to use pre-trained language models to create protein embeddings, and then indirectly predict protein function using their relative similarity. We find that fine-tuning an auxiliary objective on protein function indirectly improves these hy-brid methods, to the point that they are in some cases better than direct classifiers. Our empirical results demonstrate that interpretable protein comparison models can be developed using fine-tuning techniques, without cost, or even with some benefit, to overall performance. K-nearest neighbors (KNN) embedding-based models also offer free generalization to previously unknown classes, while continuing to outperform only pre-trained models, further demonstrating the potential of fine-tuned embeddings outside of direct classification.

Significance Statement

For the purposes of biological understanding, or engineering, it is particularly important that protein annotation is done through interpretable means, such as comparison to existing proteins with known properties. Our work builds upon previous efforts to do so by embedding proteins into high-dimensional vectors with pre-trained protein language models. We demonstrate that further training of these models on protein function classification drastically improves their performance, while allowing for exactly the same similarity based classifications on both known and novel potential functions.
Rocket-miR, a Translational Launchpad for miRNA-based Antimicrobial Drug Development
Authors: Neff Samuel L. , Hampton Thomas H. , Koeppen Katja , Sarkar Sharanya , Latario Casey J. , Ross Benjamin D. , Stanton Bruce A.
Published: June 2023

Developing software tools that leverage biological datasets to accelerate drug discovery is an important aspect of bioinformatics research. Here we present a novel example: a web application called Rocket-miR that applies an existing bioinformatics algorithm (IntaRNA) to predict cross-species miRNA-mRNA interactions and identify human miRNAs with potential antimicrobial activity against antibiotic resistant bacterial infections. Rocket-miR is the logical extension of our prior finding that human miRNA let-7b-5p impairs the ability of the ubiquitous opportunistic pathogenP. aeruginosato form biofilms and resist the bactericidal effect of beta lactam antibiotics. Rocket-miR’s point and click interface enables researchers without programming expertise to predict additional human-miRNA-pathogen interactions. Identified miRNAs can be developed into novel antimicrobials effective against the 24 clinically relevant pathogens, implicated in diseases of the lung, gut and other organs, that are included in the application. The manuscript incorporates three case studies contributed by microbiologists that study human pathogens to demonstrate the usefulness and usability of the application. Rocket-miR is accessible at the following link:http://scangeo.dartmouth.edu/RocketmiR/.

Importance

Antimicrobial resistant infections contribute to millions of deaths worldwide every year. In particular, the group of bacteria collectively known as ESKAPE (Enterococcus faecium,Staphylococcus aureus,Klebsiella pneumoniae,Acinetobacter baumannii,Pseudomonas aeruginosa andEnterobacter sp.)pathogens are of considerable medical concern due to their virulence and exceptional ability to develop antibiotic resistance. New kinds of antimicrobial therapies are urgently needed to treat patients for whom existing antibiotics are ineffective. The Rocket-miR application predicts targets of human miRNAs in bacterial and fungal pathogens, rapidly identifying candidate miRNA-based antimicrobials. The application’s target audience is microbiologists that have the laboratory resources to test the application’s predictions. The Rocket-miR application currently supports 24 recognized human pathogens that are relevant to numerous diseases including CF, COPD, urinary tract infections and pneumonia. Furthermore, the application code was designed to be easily extendible to other human pathogens that commonly cause hospital-acquired infections.
Pollen thermotolerance of a widespread plant in response to climate warming: possible local adaptation of populations from different elevations
Authors: Hrubá Karolína , Biella Paolo , Klečka Jan
Published: June 2023

One of the most vulnerable phases in the plant life cycle is sexual reproduction, which depends on effective pollen transfer, but also on the thermotolerance of pollen grains. Pollen thermotolerance is temperature-dependent and may be reduced by increasing temperature associated with global warming. A growing body of research has focused on the effect of increased temperature on pollen thermotolerance in crops to understand the possible impact of temperature extremes on yield. Yet, little is known about the effects of temperature on pollen thermotolerance of wild plant species. To fill this gap, we selectedLotus corniculatuss.l. (Fabaceae), a species common to many European habitats and conducted laboratory experiments to test its pollen thermotolerance in response to artificial increase in temperature. To test for possible local adaptation of pollen thermal tolerance, we compared data from six lowland (389 - 451 m a.s.l.) and six highland (841 - 1030 m a.s.l.) populations. We observed pollen germinationin vitroat 15, 25, 30, and 40°C. While lowland plants had stable germination rate at a wide range of temperatures between 15 and 30°C, with reduced germination rate observed only at extremely high temperatures (i.e., 40°C), the germination rate of highland plants was reduced already when the temperature reached 30°C, temperature commonly exceeded in the lowland during warm summers. This suggests that lowland populations ofL. corniculatusmay be locally adapted to higher temperature for pollen germination. On the other hand, pollen tube length decreased with increasing temperature in a similar way in lowland and highland plants. The overall average pollen germination rate significantly differed between lowland and highland populations, with highland populations displaying higher germination rate. On the other hand, the average pollen tube length was slightly smaller in highland populations. In conclusion, we found that pollen thermotolerance ofL. corniculatusis reduced at high temperature and that the germination of pollen from plant populations growing at higher elevations is more sensitive to increased temperature, which suggests possible local adaptation of pollen thermotolerance.
The universal suppressor mutation in the HSV-1 nuclear egress complex restores membrane budding defects by stabilizing the oligomeric lattice
Authors: Draganova Elizabeth B. , Wang Hui , Wu Melanie , Liao Shiqing , Vu Amber , Gonzalez-Del Pino Gonzalo L. , Zhou Z. Hong , Roller Richard J. , Heldwein Ekaterina E.
Published: June 2023

Nuclear egress is an essential process in herpesviral replication whereby nascent capsids translocate from the nucleus to the cytoplasm. This initial step of nuclear egress – budding at the inner nuclear membrane – is coordinated by the nuclear egress complex (NEC). Composed of the viral proteins UL31 and UL34, NEC deforms the membrane around the capsid as the latter buds into the perinuclear space. NEC oligomerization into a hexagonal membrane-bound lattice is essential for budding because mutations designed to perturb lattice interfaces reduce its budding ability. Previously, we identified an NEC suppressor mutation capable of restoring budding to a mutant with a weakened hexagonal lattice. Here, we show that the suppressor mutation can restore budding to a broad range of budding-deficient NEC mutants thereby acting as a universal suppressor. We demonstrate that the suppressor mutation indirectly promotes the formation of new contacts between the NEC hexamers that, ostensibly, stabilize the hexagonal lattice. This stabilization strategy is powerful enough to override the otherwise deleterious effects of mutations that destabilize the NEC lattice by different mechanisms, resulting in a functional NEC hexagonal lattice and restoration of membrane budding.
Opto-seq reveals input-specific immediate early gene induction in ventral tegmental area cell types
Authors: Simon Rhiana C. , Loveless Mary C. , Yee Joshua X. , Hashikawa Koichi , Stuber Garret D. , Zweifel Larry S. , Soden Marta E.
Published: June 2023

The ventral tegmental area (VTA) is a critical node in circuits governing motivated behavior and is home to diverse populations of neurons that release dopamine, GABA, glutamate, or combinations of these neurotransmitters. The VTA receives inputs from many brain regions, but a comprehensive understanding of input-specific activation of VTA neuronal subpopulations is lacking. To address this, we combined optogenetic stimulation of select VTA inputs with single-nucleus RNA sequencing (snRNAseq) and highly multiplexedin situhybridization to identify distinct neuronal clusters and characterize their spatial distribution and activation patterns. Quantification of immediate early gene (IEG) expression revealed that different inputs activated select VTA subpopulations, which demonstrated cell-type specific IEG programs. Within dopaminergic subpopulations IEG induction levels correlated with differential expression of ion channel genes. This new transcriptomics-guided circuit analysis reveals the diversity of VTA activation driven by distinct inputs and provides a resource for future analysis of VTA cell types.
DNA binding activity of CAMTA3 is essential for its function: Identification of critical amino acids for its transcriptional activity
Authors: Prasad Kasavajhala V.S.K. , Abdel-Hameed Amira , Jiang Qiyan , Reddy Anireddy S.N.
Published: June 2023

Calmodulin-binding transcription activators (CAMTAs), a small family of highly conserved transcription factors, function in calcium-mediated signaling pathways. Of the six CAMTAs in Arabidopsis, CAMTA3 (also referred to as SR1) regulates diverse biotic and abiotic stress responses. A recent study has shown that CAMTA3 is a guardee of NLR ((nucleotide-binding, leucine-rich repeat domain) immune receptors in modulating plant immunity, thereby suggesting that CAMTA3 transcriptional activity is not necessary for its function. Here, we show that the DNA-binding activity of CAMTA3 is essential for its role in mediating plant immune responses. Analysis of the DNA binding (CG-1) domain of CAMTAs in plants and animals showed strong conservation of several amino acids. We mutated several conserved amino acids in the CG-1 domain to investigate their role in CAMTA3 function. Electrophoretic mobility shift assays using these mutants with a promoter of its target gene identified critical amino acid residues necessary for DNA binding activity. Furthermore, transient assays showed that these residues are essential for the CAMTA3 function in activating theRSRE(Rapid Stress Response Element)-driven reporter gene expression. In line with this, transgenic lines expressing the CG-1 mutants of CAMTA3 in thecamta3mutant failed to rescue the mutant phenotype and restore the expression of CAMTA3 downstream target genes. Collectively, our results provide biochemical and genetic evidence that the transcriptional activity of CAMTA3 is indispensable for its function.
Particle deformability enables control of interactions between membrane-anchored nanoparticles
Authors: Nambiar Nikhil , Loyd Zachary A. , Abel Steven M.
Published: June 2023

Nanoparticles adsorbed on a membrane can induce deformations of the membrane that give rise to effective interactions between the particles. Previous studies have focused primarily on rigid nanoparticles with fixed shapes. However, DNA origami technology has enabled the creation of deformable nanostructures with controllable shapes and mechanical properties, presenting new opportunities to modulate interactions between particles adsorbed on deformable surfaces. Here we use coarse-grained molecular dynamics simulations to investigate deformable, hinge-like nanostructures anchored to lipid membranes via cholesterol anchors. We characterize deformations of the particles and membrane as a function of the hinge stiffness. Flexible particles adopt open configurations to conform to a flat membrane, whereas stiffer particles induce deformations of the membrane. We further show that particles spontaneously aggregate and that cooperative effects lead to changes in their shape when they are close together. Using umbrella sampling methods, we quantify the effective interaction between two particles and show that stiffer hinge-like particles experience stronger and longer-ranged attraction. Our results demonstrate that interactions between de-formable, membrane-anchored nanoparticles can be controlled by modifying mechanical properties of the particles, suggesting new ways to modulate the self-assembly of particles on deformable surfaces.
Life on the edge: a new toolbox for population-level climate change vulnerability assessments
Authors: Barratt Christopher D. , Onstein Renske E. , Pinsky Malin L. , Steinfartz Sebastian , Kühl Hjalmar S. , Forester Brenna R. , Razgour Orly
Published: June 2023

Global change is impacting biodiversity across all habitats on earth. New selection pressures from changing climatic conditions and other anthropogenic activities are creating heterogeneous ecological and evolutionary responses across many species’ geographic ranges. Yet we currently lack standardised and reproducible tools to effectively predict the resulting patterns in species vulnerability to declines or range changes.

We developed an informatic toolbox that integrates ecological, environmental and genomic data and analyses (environmental dissimilarity, species distribution models, landscape connectivity, neutral and adaptive genetic diversity and genotype-environment associations) to estimate population vulnerability. In our toolbox, functions and data structures are coded in a standardised way so that it is applicable to any species or geographic region where appropriate data are available, for example individual or population sampling and genomic datasets (e.g. RAD-seq, ddRAD-seq, whole genome sequencing data) representing environmental variation across the species geographic range.

We apply our toolbox to a georeferenced genomic dataset for the East African spiny reed frog (Afrixalus fornasini) to predict population vulnerability, as well as demonstrating that range loss projections based on adaptive variation can be accurately reproduced using data for two European bat species (Myotis escalerai, andM. crypticus).

Our framework sets the stage for large scale, multi-species genomic datasets to be leveraged in a novel climate change vulnerability framework to quantify intraspecific differences in genetic diversity, local adaptation, range shifts and population vulnerability based on exposure, sensitivity, and range shift potential.
The Tabulae Paralytica:Multimodal single-cell and spatial atlases of spinal cord injury
Authors: Skinnider Michael A. , Gautier Matthieu , Teo Alan Yue Yang , Kathe Claudia , Hutson Thomas H. , Laskaratos Achilleas , de Coucy Alexandra , Regazzi Nicola , Aureli Viviana , James Nicholas D. , Schneider Bernard , Sofroniew Michael V. , Barraud Quentin , Bloch Jocelyne , Anderson Mark A. , Squair Jordan W. , Courtine Grégoire
Published: June 2023

Here, we introduce theTabulae Paralytica—a compilation of four atlases of spinal cord injury (SCI) comprising a single-nucleus transcriptome atlas of half a million cells; a multiome atlas pairing transcriptomic and epigenomic measurements within the same nuclei; and two spatial transcriptomic atlases of the injured spinal cord spanning four spatial and temporal dimensions. We integrated these atlases into a common framework to dissect the molecular logic that governs the responses to injury within the spinal cord. TheTabulae Paralyticaexposed new biological principles that dictate the consequences of SCI, including conserved and divergent neuronal responses to injury; the priming of specific neuronal subpopulations to become circuit-reorganizing neurons after injury; an inherent trade-off between neuronal stress responses and the activation of circuit reorganization programs; the necessity of reestablishing a tripartite neuroprotective barrier between immune-privileged and extra-neural environments after SCI; and a catastrophic failure to form this barrier in old mice. We leveraged theTabulae Paralyticato develop a rejuvenative gene therapy that reestablished this tripartite barrier, and restored the natural recovery of walking after paralysis in old mice. TheTabulae Paralyticaprovides an unprecedented window into the pathobiology of SCI, while establishing a framework for integrating multimodal, genome-scale measurements in four dimensions to study biology and medicine.
Peak-agnostic high-resolution cis-regulatory circuitry mapping using single cell multiome data
Authors: Zhang Zidong , Ruf-Zamojski Frederique , Zamojski Michel , Bernard Daniel J. , Chen Xi , Troyanskaya Olga G. , Sealfon Stuart C.
Published: June 2023

Single same cell RNAseq/ATACseq multiome data provide unparalleled potential to develop high resolution maps of the cell-type specific transcriptional regulatory circuitry underlying gene expression. We present CREMA, a framework that recovers the full cis-regulatory circuitry by modeling gene expression and chromatin activity in individual cells without peak-calling or cell type labeling constraints. We demonstrate that CREMA overcomes the limitations of existing methods that fail to identify about half of functional regulatory elements which are outside the called chromatin “peaks”. These circuit sites outside called peaks are shown to be important cell type specific functional regulatory loci, sufficient to distinguish individual cell types. Analysis of mouse pituitary data identifies a Gata2-circuit for the gonadotrope-enriched disease-associated Pcsk1 gene, which is experimentally validated by reduced gonadotrope expression in a gonadotrope conditional Gata2-knockout model. We present a web accessible human immune cell regulatory circuit resource, and provide CREMA as an R package.
MOCHA: advanced statistical modeling of scATAC-seq data enables functional genomic inference in large human disease cohorts
Authors: Zaim Samir Rachid , Pebworth Mark-Phillip , McGrath Imran , Okada Lauren , Weiss Morgan , Reading Julian , Czartoski Julie L. , Torgerson Troy R. , McElrath M. Juliana , Bumol Thomas F. , Skene Peter J. , Li Xiao-jun
Published: June 2023

Single-cell assay for transposase-accessible chromatin using sequencing (scATAC-seq) has been increasingly used to study gene regulation. However, major analytical gaps limit its utility in studying gene regulatory programs in complex diseases. We developed MOCHA (Model-based single cell Open CHromatin Analysis) with major advances over existing analysis tools, including: 1) improved identification of sample-specific open chromatin, 2) proper handling of technical drop-out with zero-inflated methods, 3) mitigation of false positives in single cell analysis, 4) identification of alternative transcription-starting-site regulation, and 5) transcription factor–gene network construction from longitudinal scATAC-seq data. These advances provide a robust framework to study gene regulatory programs in human disease. We benchmarked MOCHA with four state-of-the-art tools to demonstrate its advances. We also constructed cross-sectional and longitudinal gene regulatory networks, identifying potential mechanisms of COVID-19 response. MOCHA provides researchers with a robust analytical tool for functional genomic inference from scATAC-seq data.
SWI/SNF chromatin remodeling determines brassinosteroid-induced transcriptional activation
Authors: Zhu Tao , Wei Chuangqi , Yu Yaoguang , Zhu Jiameng , Liang Zhenwei , Cui Yuhai , Wang Zhi-Yong , Li Chenlong
Published: June 2023

The brassinosteroid (BR) hormone is a central modulator of plant growth, development, and responses to stresses by activating or repressing the expression of thousands of genes through the transcription factor BRASSINAZOLE-RESISTANT 1 (BZR1) and its homologues. However, the molecular mechanism that determines the transcriptional activation versus repression activity of BZR1 remains largely unclear. Here, we show that BZR1-responsive transcriptional activation at thousands of loci requires the Switch defective/sucrose non-fermentable (SWI/SNF)-complexes-mediated chromatin accessibility regulation. BR-activated BZR1 controls the activation or repression of thousands of BZR1 target genes through reprograming genome-wide chromatin accessibility landscape inArabidopsis thaliana. BZR1 physically interacts with theBRAHMA (BRM)-AssociatedSWI/SNF complexes (BAS), co-localizes with BRM on the genome, and enhances BRM occupancy at sites of increased accessibility by BR. Loss of BRM abrogates the capacity of BZR1 to increase but not decrease chromatin accessibility, blocks BR-induced hypocotyl elongation, and diminishes BZR1-mediated transcriptional activation rather than repression. Together, our work reveals that the BAS chromatin remodeling complex is a critical epigenetic regulatory partner in dictating BZR1-mediated transcriptional activation ability, thus providing a long sought mechanistic explanation for how BR signaling activates gene transcription in shaping diverse developmental programs.

Teaser

BZR1-responsive transcriptional activation activity at thousands of loci requires the SWI/SNF-complexes-mediated chromatin accessibility regulation.
Bioinformatic Surveillance Leads to Discovery of Two Novel Putative Bunyaviruses Associated with Black Soldier Fly
Authors: Walt Hunter K. , Kooienga Emilia , Cammack Jonathan A. , Tomberlin Jeffery K. , Jordan Heather , Meyer Florencia , Hoffmann Federico G.
Published: June 2023

The black soldier fly (Hermetia illucens,BSF) has emerged as an industrial insect of high promise because of its ability to convert organic waste into nutritious feedstock, making it an environmentally sustainable alternative protein source. As global interest rises, rearing efforts are also upscaled, which is highly conducive to pathogen transmission. Viral epidemics have stifled mass-rearing efforts of other insects of economic importance, such as crickets, silkworms, and honeybees, but little is known about the viruses that associate with BSF. Although it is thought that BSF are unusually resistant to pathogens because of their expansive antimicrobial gene repertoire, surveillance techniques could be useful to identify emerging pathogens and common BSF microbes. In this study, we used high-throughput sequencing data to survey BSF larvae and frass samples, and we identified two novel bunyavirus-like sequences. Our phylogenetic analyses grouped one in the familyNairoviridae, and the other with two unclassified bunyaviruses. We describe these putative novel viruses as BSF Nairovirus-like 1 and BSF uncharacterized bunyavirus-like 1. We identified candidate segments for the full BSF Nairovirus-like 1 genome using a technique based on transcript co-occurrence, and only a partial genome for BSF uncharacterized bunyavirus-like 1. These results emphasize the value of routine BSF colony surveillance and add to the number of viruses associated with BSF.
Parasite-Induced IFN-γ Regulates Host Defense via CD115 and mTOR-Dependent Mechanism of Tissue-Resident Macrophage Death
Authors: Martin Andrew T , Giri Shilpi , Safronova Alexandra , Eliseeva Sophia I , Kwok Samantha F , Yarovinsky Felix
Published: June 2023

Host resistance to a common protozoan parasiteToxoplasma gondiirelies on a coordinated immune response involving multiple cell types, including macrophages. Embryonically seeded tissue-resident macrophages (TRMs) play a critical role in maintaining tissue homeostasis but their role in parasite clearance is poorly understood. In this study, we uncovered a crucial aspect of host defense againstT. gondiimediated by TRMs. Through the use of neutralizing antibodies and conditional IFN-γ receptor-deficient mice, we demonstrated that IFN-γ directly mediated the elimination of TRMs. Mechanistically, IFN-γ stimulation rendered macrophages unresponsive to macrophage colony-stimulating factor (M-CSF) and inactivated mTOR signaling by causing the shedding of CD115 (CSFR1), the receptor for M-CSF. Further experiments revealed the essential role of macrophage IFN-γ responsiveness in host resistance toT. gondii.The elimination of peritoneal TRMs emerged as a host defense mechanism aimed at limiting the parasite’s reservoir. The identified mechanism, involving IFN-γ-induced CD115 and mTOR-dependent cell death, provides insights into the adaptation of macrophage subsets during infection and highlights a crucial aspect of host defense against intracellular pathogens.
WRNIP1 prevents transcription-associated genomic instability
Authors: Valenzisi Pasquale , Marabitti Veronica , Pichierri Pietro , Franchitto Annapaola
Published: June 2023

R-loops are non-canonical DNA structures that form during transcription and play diverse roles in various physiological processes. Disruption of R-loop homeostasis can lead to genomic instability and replication impairment, contributing to several human diseases, including cancer. Although the molecular mechanisms that protect cells against such events are not fully understood, recent research has identified fork protection factors and DNA damage response proteins as regulators of R-loop dynamics. In this study, we identify the Werner helicase-interacting protein 1 (WRNIP1) as a novel factor that counteracts transcription-associated DNA damage upon replication perturbation. Loss of WRNIP1 leads to R-loop accumulation, resulting in collisions between the replisome and transcription machinery. We observe co-localization of WRNIP1 with transcription/replication complexes and R-loops after replication perturbation, suggesting its involvement in resolving transcription-replication conflicts. Moreover, WRNIP1-deficient cells show impaired replication restart from transcription-induced fork stalling. Notably, transcription inhibition and RNase H1 overexpression rescue all the defects caused by loss of WRNIP1. Importantly, our findings highlight the critical role of WRNIP1 ubiquitin-binding zinc finger (UBZ) domain in preventing pathological persistence of R-loops and limiting DNA damage, thereby safeguarding genome integrity.
A synthetic biology approach to assemble and reboot clinically-relevantPseudomonas aeruginosatailed phages
Authors: IPOUTCHA Thomas , RACHARAKS Ratanachat , HUTTELMAIER Stefanie , WILSON Cole , OZER Egon A , HARTMANN Erica M
Published: June 2023

The rise in frequency of antibiotic resistance has made bacterial infections, specificallyPseudomonas aeruginosa, a cause for greater concern. Phage therapy is a promising solution that uses naturally isolated phages to treat bacterial infections. Ecological limitations, which stipulate a discrete host range and the inevitable evolution of resistance, may be overcome through a better understanding of phage biology and the utilization of engineered phages. In this study, we developed a synthetic biology approach to construct tailed phages that naturally target clinically-relevant strains ofPseudomonas aeruginosa. As proof of concept, we successfully cloned and assembled the JG024 and DMS3 phage genomes in yeast using transformation-associated recombination (TAR) cloning and rebooted these two phage genomes in two different strains ofP. aeruginosa. We identified factors that affected phage reboot efficiency like the phage species or the presence of antiviral defense systems in the bacterial strain. We have successfully extended this method to two other phage species and observed that the method enables the reboot of phages that are naturally unable to infect the strain used for reboot. This research represents a critical step towards the construction of clinically-relevant, engineeredP. aeruginosaphages.

Importance

Pseudomonas aeruginosais a bacterium responsible for severe infections and a common major complication in cystic fibrosis. The use of antibiotics to treat bacterial infections has become increasingly difficult as antibiotic resistance has become more prevalent. Phage therapy is an alternative solution that is already being used in some European countries, but its use is limited by narrow host range due to the phage receptor specificity, the presence of antiviral defense systems in the bacterial strain, and the possible emergence of phage resistance. In this study, we demonstrate the use of a synthetic biology approach to construct and reboot clinically-relevantP. aeruginosatailed phages. This method enables a significant expansion of possibilities through the construction of engineered phages for therapy applications.