bluuebunny/crossref_metadata_2025 huggingface dataset:
Multi-pronged analysis of pediatric low-grade glioma reveals a unique tumor microenvironment associated with BRAF alterations
Authors: Zahedi Shadi , Riemondy Kent , Griesinger Andrea M. , Donson Andrew M. , Fu Rui , Crespo Michele , DeSisto John , Groat Madeline M. , Bratbak Emil , Green Adam , Hankinson Todd C. , Handler Michael , Vibhakar Rajeev , Willard Nicholas , Foreman Nicholas K. , Levy Jean Mulcahy
Published: April 2024

Pediatric low-grade gliomas (pLGG) comprise 35% of all brain tumors. Despite favorable survival, patients experience significant morbidity from disease and treatments. A deeper understanding of pLGG biology is essential to identify novel, more effective, and less toxic therapies. We utilized single cell RNA sequencing (scRNA-seq), spatial transcriptomics, and cytokine analyses to characterize and understand tumor and immune cell heterogeneity across pLGG. scRNA-seq revealed tumor and immune cells within the tumor microenvironment (TME). Tumor cell subsets revealed a developmental hierarchy with progenitor and mature cell populations. Immune cells included myeloid and lymphocytic cells. There was a significant difference between the prevalence of two major myeloid subclusters between pilocytic astrocytoma (PA) and ganglioglioma (GG). Bulk and single-cell cytokine analyses evaluated the immune cell signaling cascade with distinct immune phenotypes among tumor samples.KIAA1549-BRAFtumors appeared more immunogenic, secreting higher levels of immune cell activators and chemokines, compared toBRAF V600Etumors. Spatial transcriptomics revealed the differential gene expression of these chemokines and their location within the TME. A multi-pronged analysis of pLGG demonstrated the complexity of the pLGG TME and differences between genetic drivers that may influence their response to immunotherapy. Further investigation of immune cell infiltration and tumor-immune interactions is warranted.

Key points

There is a developmental hierarchy in neoplastic population comprising of both progenitor-like and mature cell types in both PA and GG.

A more immunogenic, immune activating myeloid population is present in PA compared to GG.

Functional analysis and spatial transcriptomics show higher levels of immune mobilizing chemokines inKIAA1549-BRAFfusion PA tumor samples compared toBRAFV600E GG samples.

Importance of the Study

While scRNA seq provides information on cellular heterogeneity within the tumor microenvironment (TME), it does not provide a complete picture of how these cells are interacting or where they are located. To expand on this, we used a three-pronged approach to better understand the biology of pediatric low-grade glioma (pLGG). By analyzing scRNA-seq, secreted cytokines and spatial orientation of cells within the TME, we strove to gain a more complete picture of the complex interplay between tumor and immune cells within pLGG. Our data revealed a complex heterogeneity in tumor and immune populations and identified an interesting difference in the immune phenotype among different subtypes.
Testis- and ovary-expressedpolotranscripts and gene duplications affect male fertility when expressed in the germline
Authors: Najera Paola , Dratler Olivia A , Mai Alexander B , Elizarraras Miguel , Vanchinathan Rahul , Gonzales Christopher A. , Meisel Richard P.
Published: April 2024

Polo-like kinases (Plks) are essential for spindle attachment to the kinetochore during prophase and the subsequent dissociation after anaphase in both mitosis and meiosis. There are structural differences in the spindle apparatus between mitosis, male meiosis, and female meiosis. It is therefore possible that alleles of Plk genes could improve kinetochore attachment or dissociation in spermatogenesis or oogenesis, but not both. These opposing effects could result in sexually antagonistic selection at Plk loci. In addition, Plk genes have been independently duplicated in many different evolutionary lineages within animals. This raises the possibility that Plk gene duplication may resolve sexual conflicts over mitotic and meiotic functions. We investigated this hypothesis by comparing the evolution, gene expression, and functional effects of the single Plk gene inDrosophila melanogaster(polo) and the duplicated Plks inDrosophila pseudoobscura(Dpse-poloandDpse-polo-dup1). We found that the protein-coding sequence ofDpse-polo-dup1is evolving significantly faster than a canonicalpologene across all functional domains, yet the essential structure of encoded protein appears to be retained.Dpse-polo-dup1is expressed primarily in testis, while otherpologenes have broader expression profiles. Furthermore, over or ectopic expression ofpoloorDpse-poloin theD. melanogastermale germline results in greater male infertility than ectopic expression ofDpse-polo-dup1. Lastly, ectopic expression ofDpse-poloor an ovary-derived transcript ofpoloin the male germline causes males to sire female-biased broods. However, there is no sex-bias in the progeny whenDpse-polo-dup1is ectopically expressed or a testis-derived transcript ofpolois overexpressed in theD. melanogastermale germline. Our results therefore suggest thatDpse-polo-dup1may have experienced positive selection to improve its regulation of the male meiotic spindle, resolving sexual conflict over meiotic Plk functions. Alternatively,Dpse-polo-dup1may encode a hypomorphic Plk that has reduced deleterious effects when overexpressed in the male germline. Similarly, testis transcripts ofD. melanogaster polomay be optimized for regulating the male meiotic spindle, and we provide evidence that the untranslated regions of thepolotranscript may be involved in sex-specific germline functions.
Cross-subject brain entropy mapping
Authors: Del Mauro G. , Wang Z.
Published: April 2024

We present a method to map the regional similarity between resting state fMRI activities of different individuals. The similarity was measured using cross-entropy. Group level patterns were displayed based on the Human Connectome Project Youth data. While we only showed the cross-subject brain entropy (BEN) mapping results in this manuscript, the same concept can be directly extended to map the cross-sessional BEN and the cross-regional cross-subject or subject-session BEN.
DrosophilaHamlet mediates epithelial tissue assembly of the reproductive system
Authors: Wang Huazhen , Bertonnier-Brouty Ludivine , Artner Isabella , Wen Jiayu , Dai Qi
Published: April 2024

Epithelial tissue fusion requires coordinated molecular events at the ends of two epithelial structures. Regulatory mechanisms controlling these events remain largely elusive. In theDrosophilareproductive system (RS), this fusion unites the gonad and the genital disc-derived tissues, into a continuous tube. This study unveils the pivotal role of Hamlet (Ham), aDrosophilaPR-domain containing transcription factor, in orchestrating epithelial tissue fusion in the RS. Loss ofhamleads to sterility and disconnection between the testes (TE) and seminal vesicles (SV). Systematic analysis of Ham-downstream genes reveals cytoskeletal, metabolic regulators and signaling pathway components. Ham activates genes for epithelial differentiation and remodeling, while repressing genes required for tissue growth and patterning. Using multiplexed in situ hybridization, we demonstrate spatial-temporal gene expression dynamics in contacting epithelia. Key Ham downstream effectors include E-Cadherin (E-Cad), Toll (Tl) and Wnt2 signaling pathways, regulating tissue interaction and fusion. Our findings present a comprehensive gene network crucial for heterotypic epithelial tissue fusion. Mammalian Ham orthologs PRDM3 and PRDM16 are highly expressed in epithelial tissues, suggesting a conserved role across species.
Deep learning-based detection of murine congenital heart defects from µCT scans
Authors: Nguyen Hoa , Desgrange Audrey , Ochandorena-Saa Amaia , Benhamo Vanessa , Meilhac Sigolène M. , Zimmer Christophe
Published: April 2024

Congenital heart defects (CHD) result in high morbidity and mortality rates, but their origins are poorly understood. Mouse models of heart morphogenesis are required to study the pathological mechanisms of heart development compared to normal. In mouse fetuses, CHD can be observed and detected in 3D images obtained by thoracic micro-computed tomography (μCT). However, diagnosis of CHD from μCT scans is a time-consuming process that requires the experience of senior experts. An automated alternative would thus save time, empower less experienced investigators and could broaden analysis to larger numbers of samples.

Here, we describe and validate an approach based on deep learning to automatically segment the heart and screen normal from malformed hearts in mouse μCT scans. In an initial cohort, we collected 139 μCT scans from thorax and abdomen of control and mutant perinatal mice. We trained a self-configurating neural network (nnU-Net) to segment hearts from body μCT scans and validated its performance on expert segmentations, achieving a Dice coefficient of 96%. To identify malformed hearts, we developed and trained a 3D convolutional neural network (CNN) that uses segmented μCT scans as inputs. Despite the relatively small training data size, our diagnosis model achieved a sensitivity, specificity (for a 0.5 threshold), and area under the curve (AUC) of 92%, 96%, and 97% respectively, as determined by 5-fold cross-validation.

As further validation, we analyzed two additional cohorts that were collected after the model was trained: a ‘prospective’ cohort, using the same experimental protocol as the initial cohort, and containing a subset of its genotypes, and a ‘divergent’ cohort in which mice were subjected to a different treatment for heart arrest (cardioplegia) and that contained a new mouse line. Performance on the prospective cohort was excellent, with a sensitivity of 92%, a specificity of 100%, and an AUC of 100%. Performance on the divergent cohort was moderate (sensitivity: 69%, specificity: 80% and AUC: 81%), but was much improved when the model was finetuned on (a subset of) the cohort (sensitivity: 79%, specificity: 88% and AUC: 91%). These results showcase our model’s robustness and adaptability to technical and biological differences in the data, highlighting its usefulness for practical applications.

In order to facilitate the adoption, adaptation and further improvement of these methods, we built a user-friendlyNapari plugin(available atnapari-hub.org/plugins/mousechd-napari) that allows users without programming skills to utilize the segmentation and diagnosis models and re-train the latter on their own data and resources. The plugin also highlights the cardiac regions used for the diagnosis. Our automatic and retrainable pipeline, which can be employed in high-throughput genetic screening, will accelerate diagnosis of heart anomalies in mice and facilitate studies of the mechanisms of CHD.
Variational calculus approach to Zernike polynomials with application to fluorescence correlation spectroscopy
Authors: Gligonov Ivan , Enderlein Jörg
Published: April 2024

Zernike polynomials are a sequence of orthogonal polynomials that play a crucial role in optics and in particular in modeling microscopy systems. Introduced by Frits Zernike in 1934, they are particularly useful in expressing wavefront aberrations and thus imperfections of imaging systems. However, their origin and properties are rarely discussed and proven. Here, we present a novel approach to Zernike polynomials using variational calculus, and apply them to describe aberrations in fluorescence microscopy. In particular, we model the impact of various optical aberrations on the performance of one-photon and two-photon excitation fluorescence microscopy.

SIGNIFICANCE

This manuscript explores the mathematical derivation of Zernike polynomials and highlights their critical role in describing optical wavefronts and aberrations, particularly in the domain of optical microscopy. Special emphasis is placed on their utility in simulating the effects of aberrations on one-photon and two-photon excitation fluorescence correlation spectroscopy.
Positive Selection on Rare Variants Underlying the Cold Adaptation of Wild Boar
Authors: Chen Jianhai , Jakovlić Ivan , Sablin Mikhail , Xia Shengqian , Xu Zhixiang , Guo Yapin , Kuang Renzuo , Zhong Jie , Jia Yangying , Tran Thi Thuy Nhien , Yang Hao , Ma Hong , Šprem Nikica , Han Jianlin , Liu Di , Zhao Yunxia , Zhao Shuhong
Published: April 2024

The wide geographical distribution of Eurasian wild boar (Sus scrofa) offers a natural experiment to study the thermoregulation. Here, we conducted whole-genome resequencing and chromatin profiling experiments on the local populations from cold regions (northern and northeastern Asia) and warm regions (southeastern Asia and southern China). Using genome-wide scans of four methods, we detected candidate genes underlying cold-adaptation with significant enrichment of pathways related to thermogenesis, fat cell development, and adipose tissue regulation. We also found two enhancer variants under positive selection, an intronic variant ofIGF1R(rs341219502) and an exonic variant ofBRD4(rs327139795), which showed the highest differentiation between cold and warm region populations of wild boar and domestic pigs. Moreover, these rare variants were absent in outgroup species and warm-region wild boar but nearly fixed in cold-region populations, suggesting theirde novoorigins in cold-region populations. The experiments of CUT&Tag chromatin profiling showed that rs341219502 ofIGF1Ris associated with the gain of three novel transcription factors involving regulatory changes in enhancer function, while rs327139795 ofBRD4could result in the loss of a phosphorylation site due to amino acid alteration. We also found three genes (SLCO1C1, PDE3A,and TTC28) with selection signals in both wild boar and native human populations from Siberia, which suggests convergent molecular adaptation in mammals. Our study shows the adaptive evolution of genomic molecules underlying the remarkable environmental flexibility of wild boar.
Leveraging cross-source heterogeneity to improve the performance of bulk gene expression deconvolution
Authors: Shen Wenjun , Liu Cheng , Hu Yunfei , Lei Yuanfang , Wong Hau-San , Wu Si , Zhou Xin Maizie
Published: April 2024

A main limitation of bulk transcriptomic technologies is that individual measurements normally contain contributions from multiple cell populations, impeding the identification of cellular heterogeneity within diseased tissues. To extract cellular insights from existing large cohorts of bulk transcriptomic data, we present CSsingle, a novel method designed to accurately deconvolve bulk data into a predefined set of cell types using a scRNA-seq reference. Through comprehensive benchmark evaluations and analyses using diverse real data sets, we reveal the systematic bias inherent in existing methods, stemming from differences in cell size or library size. Our extensive experiments demonstrate that CSsingle exhibits superior accuracy and robustness compared to leading methods, particularly when dealing with bulk mixtures originating from cell types of markedly different cell sizes, as well as when handling bulk and single-cell reference data obtained from diverse sources. Our work provides an efficient and robust methodology for the integrated analysis of bulk and scRNA-seq data, facilitating various biological and clinical studies.
Forebrain neuronal SMC3 regulates body weight and metabolic health partially through regulation of hypothalamic Melanocortin 4 receptor
Authors: Saleev Natalia , Getselter Dmitriy , Bartman Joanna , Gutman Roee , Marco Asaf , Elliott Evan
Published: April 2024

SMC3 is a major component of the cohesin complex that regulates higher-order chromatin organization and gene expression. Mutations in SMC3 gene are found in patients with Cornelia de Lange syndrome (CdLs). This syndrome is characterized by intellectual disabilities, behavioral patterns as self-injury, as well as metabolic dysregulation. Nonetheless, little is known about the role of neuronal SMC3 in gene expression and physiology in adulthood. This study determined the role of SMC3 in adulthood brain, by knocking out Smc3 specifically in adulthood forebrain excitatory neurons. Excitatory conditional neuron-specific SMC3 knockout (cKO) mice displayed a very strong metabolic phenotype in both male and female mice, including a robust overweight phenotype, loss of muscle mass, increased food consumption, lower respiratory exchange ratio, lower energy expenditure and hormonal changes. The hypothalamus displayed dysregulated neuronal morphology and associated transcriptional abnormalities in RNA-seq analysis across various cellular pathways, including decrease of Melanocortin 4 receptor (Mc4r) expression level, a pivotal regulator of appetite and metabolism. Correspondingly, ChIP-seq analysis revealed genome-wide alterations in the binding dynamics of SMC3 of the cKO animals, including Mc4r associated regions. Notably, a significant correlation emerged between multiple sites exhibiting a marked decrease in binding and downregulated genes. The administration of Setmelanotide, an MC4r agonist, to cKO group resulted in a notable reduction in both weight and food consumption in these mice. Therefore, we have identified specific and reversable metabolic parameters that are regulated by neuronal Smc3 in adulthood.
Plasma-based organ-specific aging and mortality models unveil diseases as accelerated aging of organismal systems
Authors: Goeminne Ludger J.E. , Eames Alec , Tyshkovskiy Alexander , Argentieri M. Austin , Ying Kejun , Moqri Mahdi , Gladyshev Vadim N.
Published: April 2024

Aging is a complex process manifesting at the molecular, cell, organ and organismal levels. It leads to functional decline, disease and ultimately death, but the relationship between these fundamental biomedical features remains elusive. By applying machine learning to plasma proteome data of over fifty thousand human subjects in the UK Biobank and other cohorts, we report organ-specific and conventional aging models trained on chronological age, mortality and longitudinal proteome data. We show how these tools predict organ/systems-specific disease through numerous phenotypes. We find that men are biologically older and age faster than women, that accelerated aging of organs leads to diseases in these organs, and that specific diets, lifestyles, professions and medications are associated with accelerated and decelerated aging of specific organs and systems. Altogether, our analyses reveal that age-related chronic diseases epitomize accelerated organ- and system-specific aging, modifiable through environmental factors, advocating for both universal whole-organism and personalized organ/system-specific anti-aging interventions.
Adherence to a healthful plant-based diet and risk of mortality among individuals with chronic kidney disease: A prospective cohort study
Authors: Thompson Alysha S. , Gaggl Martina , Bondonno Nicola P. , Jennings Amy , O’Neill Joshua K. , Hill Claire , Karavasiloglou Nena , Rohrmann Sabine , Cassidy Aedín , Kühn Tilman
Published: April 2024

Background

Plant-rich dietary patterns may protect against negative health outcomes among individuals with chronic kidney disease (CKD), although aspects of plant-based diet quality have not been studied. This study aimed to examine associations between healthful and unhealthful plant-based dietary patterns with risk of mortality among CKD patients for the first time.

Methods

This prospective analysis included 4,807 UK Biobank participants with CKD at baseline. We examined associations of adherence to both the healthful plant-based diet index (hPDI) and unhealthful plant-based diet index (uPDI), calculated from repeated 24-hour dietary assessments, with risk of mortality using multivariable Cox proportional hazard regression models.

Results

Over a 10-year follow-up, 675 deaths were recorded. Participants with the highest hPDI scores had a 33% lower risk of mortality [HRQ4vsQ1(95% CI): 0.67 (0.53-0.84), ptrend= <0.001], while those with the highest uPDI scores had a 49% higher risk [1.49 (1.18-1.89), ptrend= 0.004], compared to participants with the lowest respective scores and following adjustment for other dietary and lifestyle factors. In food group-specific analyses, higher wholegrain intakes were associated with a 29% lower mortality risk, while intakes of refined grains, and sugar-sweetened beverages were associated a 28% and 31% higher risk, respectively.

Conclusions

In CKD patients, a higher intake of healthy plant-based foods was associated with a lower risk of mortality, while a higher intake of unhealthy plant-based foods was associated with a higher risk. These results underscore the importance of plant food quality and support the potential role of healthy plant food consumption in the treatment and management of CKD to mitigate unfavourable outcomes.
A heterogeneous pharmaco-transcriptomic landscape induced by targeting a single oncogenic kinase
Authors: Giglio Ross M. , Hou Nicholas , Wyatt Adeya , Hong Justin , Shi Lingting , Vaikunthan Mathini , Fuchs Henry , Nima Jose Pomarino , Malinowski Seth W. , Ligon Keith L. , McFaline-Figueroa José R. , Yosef Nir , Azizi Elham , McFaline-Figueroa José L.
Published: April 2024

Over-activation of the epidermal growth factor receptor (EGFR) is a hallmark of glioblastoma. However, EGFR-targeted therapies have led to minimal clinical response. While delivery of EGFR inhibitors (EGFRis) to the brain constitutes a major challenge, how additional drug-specific features alter efficacy remains poorly understood. We apply highly multiplex single-cell chemical genomics to define the molecular response of glioblastoma to EGFRis. Using a deep generative framework, we identify shared and drug-specific transcriptional programs that group EGFRis into distinct molecular classes. We identify programs that differ by the chemical properties of EGFRis, including induction of adaptive transcription and modulation of immunogenic gene expression. Finally, we demonstrate that pro-immunogenic expression changes associated with a subset of tyrphostin family EGFRis increase the ability of T-cells to target glioblastoma cells.

One Sentence Summary

Deep chemical genomic profiling reveals heterogeneity in response to the targeting of EGFR via myriad chemical means.
Computationally-informed insights into anhedonia and treatment byκ-opioid receptor antagonism
Authors: Bari Bilal A. , Krystal Andrew D. , Pizzagalli Diego A. , Gershman Samuel J.
Published: April 2024

Anhedonia, the loss of pleasure, is prevalent and impairing. Parsing its computational basis promises to explain its transdiagnostic character. We argue that one manifestation of anhedonia— reward insensitivity—may be linked to limited memory capacity. Further, the need to economize on limited capacity engenders a perseverative bias towards frequently chosen actions. Anhedonia may also be linked with deviations from optimal perseveration for a given memory capacity, a pattern that causesinefficiencybecause it results in less reward for the same memory cost. To test these hypotheses, we perform secondary analysis of a randomized controlled trial testingκ-opioid receptor (KOR) antagonism for anhedonia, as well as analyses of three other datasets. We find that anhedonia is associated with deficits in efficiency but not memory, whereas KOR antagonism (which likely elevates tonic dopamine) increases memory and efficiency. KOR antagonism therefore has distinct cognitive effects, only one related to anhedonia.
Natural language processing charts transcriptome evolution to design combination cancer therapies
Authors: Jassim Amir , Nimmervoll Birgit V. , Terranova Sabrina , Nathan Erica , Masih Katherine E. , Ruff Lisa , Duarte Matilde , Cooper Elizabeth , Hu Linda P. , Katyal Gunjan , Akhbari Melika , Gilbertson Reuben J. , Terhune Colton , Balmus Gabriel , Jackson Stephen P. , Filbin Mariella G. , Hill Anthony , Patrizi Anarita , Dani Neil , Regev Aviv , Lehtinen Maria K. , Gilbertson Richard J.
Published: April 2024

Combination treatment–the mainstay of cancer therapy–often fails because treatment interactions evoke complex resistance mechanisms that are hard to predict. Designing combination therapy to prevent treatment resistance is especially challenging for rare cancers. Here, we introduce REsistance through COntext DRift (RECODR): a computational pipeline that tracks how genes change their transcriptome context across cancer development and drug treatment conditions. By applying RECODR to a genetically modified mouse model of choroid plexus carcinoma–a rare brain tumour of young children–we identified patterns of transcriptome evolution, cellular heterogeneity and treatment targets that emerged as tumours were initiated and resisted combination treatment. This enabled the prediction of treatment resistance mechanisms and the design of highly effective therapeutic protocols that avoided treatment failure. RECODR can describe complex and dynamic changes in normal and diseased tissues that could be applied to multimodal data from a variety of settings, mitigating treatment resistance across cancers and other diseases.
Terrestrial 3D Laser Scanning for Ecosystem and Fire Effects Monitoring
Authors: Murphy Mary Carlton , Loudermilk E. Louise , Pokswinski Scott , Williams Brett , Link Emily , Lienesch Laila , Douglas Leta , Skowronski Nicholas , Gallagher Michael , Maxwell Aaron , Snitker Grant , Hawley Christie , Wallace Derek , Payne Irenee , Yurkiewicz Tim , Sánchez Meador Andrew J. , Anderson Chad , Jackson J. Mark , Parsons Russell , Floca Melissa , Nealey Isaac , Altintas Ilkay , Hiers J. Kevin , Wallace Jon
Published: April 2024

Long-term terrestrial ecosystem monitoring is a critical component of documenting outcomes of land management actions, assessing progress towards management objectives, and guiding realistic long-term ecological goals, all through repeated observation and measurement. Traditional monitoring methods have evolved for specific applications in forestry, ecology, and fire and fuels management. While successful monitoring programs have clear goals, trained expertise, and rigorous sampling protocols, new advances in technology and data management can help overcome the most common pitfalls in data quality and repeatability. This paper presents Terrestrial Laser Scanning (TLS), a specific form of LiDAR (Light Detection and Ranging), as an emerging sampling method that can complement and enhance existing monitoring methods. TLS captures in high resolution the 3D structure of a terrestrial ecosystem (forest, grassland, etc.), and is increasingly efficient and affordable (<$30,000). Integrating TLS into ecosystem monitoring can standardize data collection, improve efficiency, and reduce bias and error. Streamlined data processing pipelines can rigorously analyze TLS data and incorporate constant improvements to inform management decisions and planning. The approach described in this paper utilizes portable, push-button TLS equipment that, when calibrated with initial transect sampling, captures detailed forestry, fuels, and ecological features in less than 5 minutes per plot. We also introduce an interagency automated processing pipeline and dashboard viewer for instant, user-friendly analysis, and data retrieval of hundreds of metrics. Forest metrics and inventories produced with these methods offer effective decision-support data for managers to quantify landscape-scale conditions and respond with efficient action. This protocol further supports interagency compatibility for efficient natural resource monitoring across jurisdictional boundaries with uniform data, language, methods, and data analysis. With continued improvement of scanner capabilities and affordability, these data will shape the future of terrestrial ecosystem monitoring as an important means to address the increasingly fast pace of ecological change facing natural resource managers.
Analysis of endogenous NOTCH1 fromPOFUT1 S162Lpatient fibroblasts reveals the importance of theO-fucose modification on EGF12 in human development
Authors: Matsumoto Kenjiroo , Luther Kelvin B. , Haltiwanger Robert S.
Published: April 2024

NOTCH1 (N1) is a transmembrane receptor interacting with membrane-tethered ligands on opposing cells that mediate the direct cell-cell interaction necessary for many cell fate decisions. ProteinO-fucosyltransferase 1 (POFUT1) addsO-fucose to Epidermal Growth Factor (EGF)-like repeats in the NOTCH1 extracellular domain, which is required for trafficking and signaling activation. We previously showed thatPOFUT1 S162Lcaused a 90% loss of POFUT1 activity and global developmental defects in a patient; however, the mechanism by which POFUT1 contributes to these symptoms is still unclear. Compared to controls,POFUT1 S162Lpatient fibroblast cells had an equivalent amount of N1 on the cell surface but showed a 60% reduction of DLL1 ligand binding and a 70% reduction in JAG1 ligand binding. To determine if the reduction ofO-fucose on N1 inPOFUT1 S162Lpatient fibroblasts was the cause of these effects, we immunopurified endogenous N1 from control and patient fibroblasts and analyzedO-fucosylation using mass spectral glycoproteomics methods. N1 EGF8 to EGF12 comprise the ligand binding domain, andO-fucose on EGF8 and EGF12 physically interact with ligands to enhance affinity. Glycoproteomics of N1 fromPOFUT1 S162Lpatient fibroblasts showed WT fucosylation levels at all sites analyzed except for a large decrease at EGF9 and the complete absence ofO-fucose at EGF12. Since the loss ofO-fucose on EGF12 is known to have significant effects on N1 activity, this may explain the symptoms observed in thePOFUT1 S162Lpatient.
Putative origin ofMyxococcus fulvus124B02 plasmid, pMF1, from a chromosomal segment in anotherMyxococcusspecies
Authors: Jain Shruti , Sharma Gaurav
Published: April 2024

Myxobacteria or order Myxococcales (old nomenclature) or phylum Myxococcota (new terminology) are fascinating organisms well known for their diverse peculiar physiological, taxonomic, and genomic properties. Researchers have long sought to identify plasmids within these organisms, yet thus far, only two organisms from different families have been found to harbor a plasmid. This study delves into the origin and evolution of one of these plasmids, i.e., pMF1 present inM. fulvus124B02 in the suborder Cystobacterineae and family Myxococcaceae. Here we first reannotated the pMF1 plasmid genome sequence and identified two additional genes which were not annotated till now. We further reported that all pMF1 plasmid genes depict homology withM. stipitatusCYD1 draft genome (contig 28) and a chromosomal segment ofM. stipitatusDSM14675 in a syntenic manner, suggesting the presence of plasmid-like structure inM. stipitatusCYD1 but integrated as part of its chromosome. To comprehend the relationship among these three species, we conducted phylogenetic analyses using 16S and concatenated housekeeping genes and GGDC analysis, which confirmed thatM. stipitatusCYD1 is a distinct and novel species within the genusMyxococcus. Overall, this study sheds light on the putative origin of the pMF1 plasmid, which likely originated from a closely related yet distinct species, possibly through the partition from its chromosome as a segment.

Importance

Myxobacteria are not well-known to have plasmids. Till now, only two organisms have been shown to have plasmids, raising a pertinent question about how these plasmids evolved randomly within the phylum Myxococcota. The study presented in this manuscript delves into the origin and evolution of the pMF1 plasmid found inMyxococcus fulvus124B02, a member of the suborder Cystobacterineae and family Myxococcaceae. Our research addresses the intriguing topic of plasmid identification and evolution within Myxobacteria, which are a group of fascinating organisms that have garnered significant interest due to their diverse physiological, taxonomic, and genomic properties.
RNA structures within Venezuelan equine encephalitis virus E1 alter macrophage replication fitness and contribute to viral emergence
Authors: Hickson Sarah E. , Hyde Jennifer L.
Published: April 2024

Venezuelan equine encephalitis virus (VEEV) is a mosquito-borne +ssRNA virus belonging to theTogaviridae. VEEV is found throughout Central and South America and is responsible for periodic epidemic/epizootic outbreaks of febrile and encephalitic disease in equines and humans. Endemic/enzootic VEEV is transmitted between Culex mosquitoes and sylvatic rodents, whereas epidemic/epizootic VEEV is transmitted between mosquitoes and equids, which serve as amplification hosts during outbreaks. Epizootic VEEV emergence has been shown to arise from mutation of enzootic VEEV strains. Specifically, epizootic VEEV has been shown to acquire amino acid mutations in the E2 viral glycoprotein that facilitate viral entry and equine amplification. However, the abundance of synonymous mutations which accumulate across the epizootic VEEV genome suggests that other viral determinants such as RNA secondary structure may also play a role in VEEV emergence. In this study we identify novel RNA structures in the E1 gene which specifically alter replication fitness of epizootic VEEV in macrophages but not other cell types. We show that SNPs are conserved within epizootic lineages and that RNA structures are conserved across different lineages. We also identified several novel RNA-binding proteins that are necessary for altered macrophage replication. These results suggest that emergence of VEEV in nature requires multiple mutations across the viral genome, some of which alter cell-type specific replication fitness in an RNA structure-dependent manner.

AUTHOR SUMMARY

Understanding how viral pathogens emerge is critical for ongoing surveillance and outbreak preparedness. However, our understanding of the molecular mechanisms that drive viral emergence are still not completely understood. Emergence of the mosquito-borne virus Venezuelan equine encephalitis virus (VEEV) is known to require mutations in the viral attachment protein (E2), which drive viremia and transmission. We have observed that emergent strains (epizootic VEEV) also accumulate many silent mutations, suggesting that other determinants independent of protein sequence also contributes to emergence. In this study we identify novel RNA secondary structures associated with epizootic VEEV that alters viral replication in a cell-type dependent manner. We show that these RNA structures are conserved across epizootic viruses and identify host proteins that specifically bind these RNAs. These findings imply that viral emergence requires multiple mutations, a number of which likely alter viral structure in a manner that benefits viral replication and transmission.
Monolayer force generation and transmission is dictated by focal adhesion distribution
Authors: Davis John Robert , Solowiej-Wedderburn Josephine , Vega Sebastián L. , Burdick Jason A. , Dunlop Carina , Tapon Nicolas
Published: April 2024

For tissues to develop and maintain their function, cells must orchestrate their behaviour by generating and transmitting contractile forces. These forces are transmitted to their surrounding matrix or neighbouring cells via adhesion complexes. How tissues reach a force-balance is often assumed to involve intercellular stresses counterbalancing those in the substrate. However, experimental findings indicate that dampening focal adhesions can increase intercellular stresses. As the ECM is rarely uniform in composition or mechanical properties, it is important to understand how focal adhesions alter stress transmission and the force-balance of a tissue. To address this, we confined monolayers on disk or ring adhesive patterns to alter how they were bound to the substrate. Traction force microscopy and laser ablations of cell-cell junctions were used to examine stresses across epithelial monolayers whilst modulating substrate stiffness. We show that monolayers reach different force-balance states depending on focal adhesion distribution, with intercellular stresses not correlated with overall traction stresses on rings. Using an active matter model to examine the force-balance dynamics, we reveal that tissues reach a force-balance by generating non-uniform patterns of contractility linked to adhesion patterning. This work highlights the importance of considering the position and mechanical properties of cell-ECM and cell-cell attachments to capture the mechanical landscape of living tissues.
Recalibrating differential gene expression by genetic dosage variance prioritizes functionally relevant genes
Authors: Rentzsch Philipp , Kollotzek Aaron , Mohammadi Pejman , Lappalainen Tuuli
Published: April 2024

Differential expression (DE) analysis is a widely used method for identifying genes that are functionally relevant for an observed phenotype or biological response. However, typical DE analysis includes selection of genes based on a threshold of fold change in expression under the implicit assumption that all genes are equally sensitive to dosage changes of their transcripts. This tends to favor highly variable genes over more constrained genes where even small changes in expression may be biologically relevant. To address this limitation, we have developed a method to recalibrate each gene’s differential expression fold change based on genetic expression variance observed in the human population. The newly established metric ranks statistically differentially expressed genes not by nominal change of expression, but by relative change in comparison to natural dosage variation for each gene. We apply our method to RNA sequencing datasets from rare disease and in-vitro stimulus response experiments. Compared to the standard approach, our method adjusts the bias in discovery towards highly variable genes, and enriches for pathways and biological processes related to metabolic and regulatory activity, indicating a prioritization of functionally relevant driver genes. With that, our method provides a novel view on DE and contributes towards bridging the existing gap between statistical and biological significance. We believe that this approach will simplify the identification of disease causing genes and enhance the discovery of therapeutic targets.
The impact of big data analytics on innovation capability and sustainability performance of hotels: evidence from an emerging economy
Authors: Aziz Norzalita Abd , Al Mamun Abdullah , Reza Mohammad Nurul Hassan , Naznen Farzana
Published: April 2024

Purpose

This study aimed to examine the role of big data analytics capabilities (BDAC) in fostering organizational innovation capabilities and, consequently, in achieving economic, social and environmental sustainability.

Design/methodology/approach

Through the lens of dynamic capability theory, this study surveyed 115 hotels using purposive sampling to gain in-depth insights regarding the factors affecting organizational sustainability in the hospitality industry. The data analysis was conducted using partial least squares-structural equation modeling (PLS-SEM).

Findings

The findings reported a substantial impact of seven core dimensions (i.e. technology, data, basic resources, technological skills, managerial skills, organizational learning and data-driven culture) in building BDAC among hotels. Moreover, BDAC was also revealed to significantly influence innovation capabilities, positively impacting all three sorts of sustainability performance. Innovation capability also mediated the relationship between BDAC and all sustainability factors.

Practical implications

The findings will assist policymakers and practitioners in developing effective initiatives to enhance the adoption and implementation of data science and technologies, substantially contributing to the “National IR 4.0 Policy” and “Malaysia Digital Economy Blueprint” and achieving sustainable development goals (SDGs).

Originality/value

The originality of this study is established by investigating the interplay between BDAC, innovation capability and sustainability performance, particularly in the context of the hotel industry, whereas the existing studies focus on exploring the advantages of BDA.
Empowering pro-environmental potential among hotel employees: insights from self-determination theory
Authors: Patwary Ataul Karim , Rasoolimanesh S. Mostafa , Hanafiah Mohd Hafiz , Aziz Roslizawati Che , Mohamed Ahmad Edwin , Ashraf Muhammad Umair , Azam Nor Rabiatul Adawiyah Nor
Published: April 2024

Purpose

This research examines the role of green, inclusive leadership, corporate social responsibility, and pro-environmental attitudes on proactive pro-environmental behaviour among hotel employees. It further examines the indirect effects of pro-environmental attitudes between green inclusive leadership, corporate social responsibility, and proactive pro-environmental behaviour, as well as the moderating role of psychological contract breach between pro-environmental attitudes and proactive pro-environmental behaviour.

Design/methodology/approach

The participants of this cross-sectional study were employees in the Malaysian hotel industry, and 374 usable questionnaires were used for data analysis. The data were analysed using Partial Least Squares – Structural Equation Modelling.

Findings

This study found that green, inclusive leadership, corporate social responsibility, and pro-environmental attitudes significantly influence proactive pro-environmental behaviour. For mediating effects, pro-environmental attitudes have been found to mediate the relationship between corporate social responsibility, green inclusive leadership and proactive pro-environmental behaviour.

Research limitations/implications

The research proposes actionable measures to encourage environmentally friendly practices in the hotel sector. For companies to succeed, they must integrate green initiatives with their societal objectives. Pro-environmental mindsets are essential for implementing effective environmental policies, which in turn impact recruitment approaches. The advantages of fostering pro-environmental conduct encompass financial savings, enhanced standing, adherence to regulations, increased innovative thinking and improved workplace well-being.

Originality/value

Over time, environmental degradation has been contributed by individual behaviours and the combined actions of businesses and organisations. This study significantly contributed to a new model underpinned by the Self-determination Theory by including new constructs influencing proactive pro-environmental behaviour.
Innovation in leadership education: inquiry-based pedagogy
Authors: Mueller Robin Alison , Campbell Harrison , Losev Tatiana
Published: April 2024

Purpose

The purpose of our research is to better understand inquiry-based pedagogy in the context of leadership education. Specifically, we sought to learn about how leadership learning is characterized in an immersive inquiry course, and how inquiry-based pedagogy is experienced by students engaged in interdisciplinary leadership learning.

Design/methodology/approach

We used a case study approach as an overarching methodology. The research methods employed to collect data were World Cafe and episodic narrative interview. Further, we used collocation analysis and systematic text condensation as analytical strategies to interpret data.

Findings

Our findings led us to four primary conclusions: (1) inquiry-based learning helps to foster an inquiry mindset amongst leadership education students; (2) the challenges and tensions associated with inquiry-based learning are worth the learning gains for leadership students; (3) the opportunity to learn in relationship is beneficial for leadership development outcomes and (4) students’ experiences of inquiry-based learning in leadership education often included instances of transformation.

Research limitations/implications

Limitations of the research were: (1) it is a case study situated within a unique, particular social and educational context; (2) demographic data were not collected from participants, so results cannot be disaggregated based on particular demographic markers and (3) the small sample size involved in the study makes it impossible to generalize across a broad population.

Practical implications

This research has enabled a deep understanding of structural and relational supports that can enable effective inquiry-based learning in leadership education. It also offers evidence to support institutional shifts to inquiry-based pedagogy in leadership education.

Social implications

Our research demonstrates that use of inquiry-based pedagogy in leadership education has long-lasting positive effects on students' capacity for applied leadership practice. Consequently, participants in this type of leadership learning are better positioned to effectively lead social change that is pressing in our current global context.

Originality/value

There is scant (if any) published research that has focused on using inquiry-based pedagogies in leadership education. This research makes a significant contribution to the scholarship of leadership education.
The impact of investor greed and fear on cryptocurrency returns: a Granger causality analysis of Bitcoin and Ethereum
Authors: Cavalheiro Everton Anger , Vieira Kelmara Mendes , Thue Pascal Silas
Published: April 2024

Purpose

This study probes the psychological interplay between investor sentiment and the returns of cryptocurrencies Bitcoin and Ethereum. Employing the Granger causality test, the authors aim to gauge how extensively the Fear and Greed Index (FGI) can predict cryptocurrency return movements, exploring the intricate bond between investor emotions and market behavior.

Design/methodology/approach

The authors used the Granger causality test to achieve research objectives. Going beyond conventional linear analysis, the authors applied Smooth Quantile Regression, scrutinizing weekly data from July 2022 to June 2023 for Bitcoin and Ethereum. The study focus was to determine if the FGI, an indicator of investor sentiment, predicts shifts in cryptocurrency returns.

Findings

The study findings underscore the profound psychological sway within cryptocurrency markets. The FGI notably predicts the returns of Bitcoin and Ethereum, underscoring the lasting connection between investor emotions and market behavior. An intriguing feedback loop between the FGI and cryptocurrency returns was identified, accentuating emotions' persistent role in shaping market dynamics. While associations between sentiment and returns were observed at specific lag periods, the nonlinear Granger causality test didn't statistically support nonlinear causality. This suggests linear interactions predominantly govern variable relationships. Cointegration tests highlighted a stable, enduring link between the returns of Bitcoin, Ethereum and the FGI over the long term.

Practical implications

Despite valuable insights, it's crucial to acknowledge our nonlinear analysis's sensitivity to methodological choices. Specifics of time series data and the chosen time frame may have influenced outcomes. Additionally, direct exploration of macroeconomic and geopolitical factors was absent, signaling opportunities for future research.

Originality/value

This study enriches theoretical understanding by illuminating causal dynamics between investor sentiment and cryptocurrency returns. Its significance lies in spotlighting the pivotal role of investor sentiment in shaping cryptocurrency market behavior. It emphasizes the importance of considering this factor when navigating investment decisions in a highly volatile, dynamic market environment.