bluuebunny/crossref_metadata_2025_split huggingface dataset:
The 4T1 breast carcinoma model possesses hybrid epithelial/mesenchymal traits linked to a highly metastatic phenotype
Authors: Herndon Mary E. , Gibson-Corley Katherine , Wallrath Lori L. , Henry Michael D. , Stipp Christopher S. 
Published: February 2024

AbstractEpithelial-mesenchymal transitions (EMTs) have emerged as a mechanism for carcinomas to gain metastatic capabilities. As classically defined, EMTs entail downregulation of E-cadherin, viewed as a master enforcer of an epithelial phenotype, and upregulation of mesenchymal markers such as N-cadherin and vimentin. Contrary to this, E-cadherin appears to be retained in many invasive carcinomas and promote collective cell invasion. Therefore, major questions remain concerning the role of E-cadherin in metastasis. To investigate how E-cadherin regulates metastasis, we selected murine 4T1 breast carcinoma cells, a widely utilized model of stage IV metastatic breast cancer that retains E-cadherin expression. Using RNA interference and constitutive expression, we demonstrate that the expression level of E-cadherin does not determine 4T1 metastatic capacity in mice. Despite high levels of expression, E-cadherin is unable to confer an epithelial phenotype with stable organized cell-cell junctions. Moreover, orthotopic 4T1 tumors in mice display co-expression of E-cadherin and vimentin and contain subregions of EMT-like loss of E-cadherin. In addition, we find that 4T1 cells co-express epithelial and mesenchymal isoforms of p120-catenin. These findings support 4T1 cells as a model for carcinomas that possess hybrid traits of epithelial and mesenchymal states that promote invasion and metastasis. As such, the 4T1 model provides a platform for investigating strategies to reinstate E-cadherin’s ability to promote stable cell-cell junctions in E-cadherin-positive cancers, and for identifying which aspects of an epithelial phenotype may serve to facilitate the macroscopic growth of metastatic colonies.
Genetic Studies Highlight the Role of TET2 and INO80 in DNA Damage Response and Kidney Disease Pathogenesis
Authors: Liang Xiujie , Liu Hongbo , Hu Hailong , Zhou Jianfu , Abedini Amin , Navarro Andrea Sanchez , Klötzer Konstantin A. , Susztak Katalin 
Published: February 2024

AbstractGenome-wide association studies (GWAS) have identified over 800 loci associated with kidney function, yet the specific genes, variants, and pathways involved remain elusive. By integrating kidney function GWAS, human kidney expression and methylation quantitative trait analyses, we identified Ten-Eleven Translocation (TET) DNA demethylase 2: TET2 as a novel kidney disease risk gene. Utilizing single-cell chromatin accessibility and CRISPR-based genome editing, we highlight GWAS variants that influenceTET2expression in kidney proximal tubule cells.Experiments using kidney-tubule-specificTet2knockout mice indicated its protective role in cisplatin-induced acute kidney injury, as well as chronic kidney disease and fibrosis, induced by unilateral ureteral obstruction or adenine diet. Single-cell gene profiling of kidneys fromTet2knockout mice andTET2-knock-down tubule cells revealed the altered expression of DNA damage repair and chromosome segregation genes, notably includingINO80, another kidney function GWAS target gene itself.Remarkably bothTET2-null andINO80-null cells exhibited an increased accumulation of micronuclei after injury, leading to the activation of cytosolic nucleotide sensor cGAS-STING. Genetic deletion of cGAS or STING in kidney tubules or pharmacological inhibition of STING protected TET2 null mice from disease development. In conclusion, our findings highlight TET2 and INO80 as key genes in the pathogenesis of kidney diseases, indicating the importance of DNA damage repair mechanisms.
DeepSLICEM: Clustering CryoEM particles using deep image and similarity graph representations
Authors: Palukuri Meghana V. , Marcotte Edward M. 
Published: February 2024

AbstractFinding the 3D structure of proteins and their complexes has several applications, such as developing vaccines that target viral proteins effectively. Methods such as cryogenic electron microscopy (cryo-EM) have improved in their ability to capture high-resolution images, and when applied to a purified sample containing copies of a macromolecule, they can be used to produce a high-quality snapshot of different 2D orientations of the macromolecule, which can be combined to reconstruct its 3D structure. Instead of purifying a sample so that it contains only one macromolecule, a process that can be difficult, time-consuming, and expensive, a cell sample containing multiple particles can be photographed directly and separated into its constituent particles using computational methods.Previous work, SLICEM, has separated 2D projection images of different particles into their respective groups using 2 methods, clustering a graph with edges weighted by pairwise similarities of common lines of the 2D projections. In this work, we develop DeepSLICEM, a pipeline that clusters rich representations of 2D projections, obtained by combining graphical features from a similarity graph based on common lines, with additional image features extracted from a convolutional neural network. DeepSLICEM explores 6 pretrained convolutional neural networks and one supervised Siamese CNN for image representation, 10 pretrained deep graph neural networks for similarity graph node representations, and 4 methods for clustering, along with 8 methods for directly clustering the similarity graph. On 6 synthetic and experimental datasets, the DeepSLICEM pipeline finds 92 method combinations achieving better clustering accuracy than previous methods from SLICEM. Thus, in this paper, we demonstrate that deep neural networks have great potential for accurately separating mixtures of 2D projections of different macromolecules computationally.
Building and analyzing metacells in single-cell genomics data
Authors: Bilous Mariia , Hérault Léonard , Gabriel Aurélie AG , Teleman Matei , Gfeller David 
Published: February 2024

AbstractThe advent of high-throughput single-cell genomics technologies has fundamentally transformed biological sciences. Currently, millions of cells from complex biological tissues can be phenotypically profiled across multiple modalities. The scaling of computational methods to analyze such data is a constant challenge and tools need to be regularly updated, if not redesigned, to cope with ever-growing numbers of cells. Over the last few years, metacells have been introduced to reduce the size and complexity of single-cell genomics data while preserving biologically relevant information. Here, we review recent studies that capitalize on the concept of metacells – and the many variants in nomenclature that have been used. We further outline how and when metacells should (or should not) be used to study single-cell genomics data and what should be considered when analyzing such data at the metacell level. To facilitate the exploration of metacells, we provide a comprehensive tutorial on construction and analysis of metacells from single-cell RNA-seq data (https://github.com/GfellerLab/MetacellAnalysisTutorial) as well as a fully integrated pipeline to rapidly build, visualize and evaluate metacells with different methods (https://github.com/GfellerLab/MetacellAnalysisToolkit).
Extrachromosomal DNA in cutaneous squamous cell carcinoma is associated with increased nodal disease
Authors: Bencomo Tomas , Thind Amarinder , Ashford Bruce , Ranson Marie , Lee Carolyn S. 
Published: February 2024

AbstractExtrachromosomal DNA (ecDNA) is a mechanism of oncogene amplification that occurs in many cancers and has been linked to worse patient outcomes. While ecDNA has previously been identified in cutaneous melanoma, it has yet to be described in cutaneous squamous cell carcinoma (cSCC). Using whole genome sequencing and transcriptomic data of primary and metastatic cSCC tumors, we establish the presence of ecDNA in cSCC and confirm elevated expression of ecDNA-associated genes. We also find that the presence of ecDNA correlates with a higher lymph node ratio, a measure of disease severity. Together, these findings are the first to report ecDNA in cSCC and suggest that ecDNA gene amplifications promote an aggressive cSCC phenotype.
What is the correct genomic structure of the complex chromosomal rearrangement at theFmlocus in Silkie chicken?
Authors: Sharma Ashutosh , Vijay Nagarjun 
Published: February 2024

SummaryARISING FROM Zhu, F., Yin, ZT., Zhao, QS. et al. Communications Biologyhttps://doi.org/10.1038/s42003-023-05619-y(2023)High-quality chromosome-level genome assemblies for numerous avian species promise to address longstanding questions in bird evolution and biology. In a recent issue ofCommunications Biology, Zhu, F., Yin, ZT., Zhao, QS. et al. (ZYZSJ)1presented a chromosome-level assembly for the Silkie chicken using a multi-platform high-coverage dataset to obtain accurate and complete sequences spanning the entire genome. A key finding from their genomic analysis is the reconstruction of the structure of the complex rearrangement at theFmlocus, the primary genetic change underlying the rare and conspicuous dermal hyperpigmentation phenotype generally called Fibromelanosis. However, in contrast to their identification of the*Fm_1scenario, several previously published studies2–6claim that*Fm_2is the valid scenario. Our re-analysis of ZYZSJ’s new assembly (CAU_Silkie) using long-read data from multiple black-bone chickens demonstrates that*Fm_2is the correct scenario. The*Fm_1scenario favoured by ZYZSJ results from an assembly error caused by mosaic haplotypes generated during the de novo assembly step. We recommend post-assembly validation and correction in genome projects to prevent misinterpretation due to assembly artefacts. Enhancing the assembly of haplotypes in such complex regions is essential for unravelling the genetic foundations of traits governed by genes within these areas.
Extensive novel diversity and phenotypic associations in the dromedary camel microbiome are revealed through deep metagenomics and machine learning
Authors: Mubaraki Fathi A 
Published: February 2024

AbstractThe dromedary camel, also known as one-humped camel or Arabian camel, is an iconic and economically important feature of Arabian society. Its contemporary importance in commerce and transportation, along with the historical and modern use of its milk and meat products for dietary health and wellness, make it an ideal subject of scientific scrutiny. The gut microbiome has recently been associated with numerous aspects of health, diet, lifestyle, and disease in livestock and humans alike, as well as serving as an exploratory and diagnostic marker of many physical characteristics. Our initial pilot analysis of 55 camel gut microbiomes from the Fathi Camel Microbiome Project using deep metagenomic shotgun sequencing reveals substantial novel species-level microbial diversity, for which we have generated an extensive catalog of prokaryotic metagenome-assembled microorganisms (MAGs) as a foundational microbial reference database for future comparative analysis. Exploratory correlation analysis exhibits substantial correlation structure among the collected subject-level metadata, including physical characteristics. Machine learning using these novel microbial markers, as well as statistical testing, demonstrates strong predictive performance of microbes to distinguish between multiple dietary and lifestyle characteristics in dromedary camels. We derive strongly predictive models for camel age, diet (including wheat), level of captivity. These findings and resources represent substantial strides toward understanding the camel microbiome and pave the way for a deeper understanding of the camel microbiome, as well as the nuanced factors that shape camel health.
A mathematical framework for understanding the spontaneous emergence of complexity applicable to growing multicellular systems
Authors: Zhang Lu , Xue Gang , Zhou Xiaolin , Huang Jiandong , Li Zhiyuan 
Published: February 2024

AbstractIn embryonic development and organogenesis, cells sharing identical genetic codes acquire diverse gene expression states in a highly reproducible spatial distribution, crucial for multicellular formation and quantifiable through positional information. To understand the spontaneous growth of complexity, we constructed a one-dimensional division-decision model, simulating the growth of cells with identical genetic networks from a single cell. Our findings highlight the pivotal role of cell division in providing positional cues, escorting the system toward states rich in information. Moreover, we pinpointed lateral inhibition as a critical mechanism translating spatial contacts into gene expression. Our model demonstrates that the spatial arrangement resulting from cell division, combined with cell lineages, imparts positional information, specifying multiple cell states with increased complexity—illustrated through examples inC.elegans. This study constitutes a foundational step in comprehending developmental intricacies, paving the way for future quantitative formulations to construct synthetic multicellular patterns.
Novel multi-omics deconfounding variational autoencoders can obtain meaningful disease subtyping
Authors: Li Zuqi , Katz Sonja , Saccenti Edoardo , Fardo David W. , Claes Peter , Martins dos Santos Vitor A.P. , Van Steen Kristel , Roshchupkin Gennady V. 
Published: February 2024

AbstractUnsupervised learning, particularly clustering, plays a pivotal role in disease subtyp- ing and patient stratification, especially with the abundance of large-scale multi-omics data. Deep learning models, such as variational autoencoders (VAEs), can enhance clustering algorithms by leveraging inter-individual heterogeneity. However, the impact of confounders - external factors unrelated to the condition, e.g. batch effect or age - on clustering is often overlooked, introducing bias and spurious biological conclusions. In this work, we introduce four novel VAE-based deconfounding frameworks tailored for clustering multi-omics data. These frameworks effectively mitigate confounding effects while preserving genuine biological patterns. The deconfounding strategies employed include: i) removal of latent features correlated with confounders ii) a conditional variational autoencoder, iii) adversarial training, and iv) adding a regularization term to the loss function. Using real-life multi-omics data from TCGA, we simulated various confounding effects (linear, non-linear, categorical, mixed) and assessed model performance across 50 repetitions based on reconstruction error, clustering stability, and deconfounding efficacy. Our results demonstrate that our novel models, particularly the conditional multi-omics VAE (cXVAE), successfully handle simulated confounding effects and recover biologically-driven clustering structures. cXVAE accurately identifies patient labels and unveils meaningful pathological associations among cancer types, validating deconfounded representations. Furthermore, our study suggests that some of the proposed strategies, such as adversarial training, prove insufficient in confounder removal. In summary, our study contributes by proposing innovative frameworks for simultaneous multi-omics data integration, dimensionality reduction, and deconfounding in clustering. Benchmarking on open-access data offers guidance to end-users, facilitating meaningful patient stratification for optimized precision medicine.
Unlocking the secrets of kangaroo locomotor energetics: Postural adaptations underpin increased tendon stress in hopping kangaroos
Authors: Thornton Lauren H. , Dick Taylor J.M. , Hutchinson John R. , Lichtwark Glen A. , McGowan Craig P. , Rubenson Jonas , Wiktorowicz-Conroy Alexis , Clemente Christofer J. 
Published: February 2024

AbstractHopping kangaroos exhibit remarkably little change in their rate of metabolic energy expenditure with locomotor speed compared to other running animals. This phenomenon may be related to greater elastic energy savings due to increasing tendon stress; however, the mechanisms which enable the rise in stress remain poorly understood. In this study, we created a three-dimensional (3D) kangaroo musculoskeletal model, integrating 3D motion capture and force plate data, to analyse the kinematics and kinetics of hopping red and grey kangaroos. Using our model, we evaluated how body mass and speed influence (i) hindlimb posture, (ii) effective mechanical advantage (EMA), and (iii) the associated tendon stress in the ankle extensors and (iv) ankle work during hopping. We found that increasing ankle dorsiflexion and metatarsophalangeal plantarflexion likely played an important role in decreasing ankle EMA by altering both the muscle and external moment arms, which subsequently increased energy absorption and peak tendon stress at the ankle. Surprisingly, kangaroo hindlimb posture appeared to contribute to increased tendon stress, thereby elucidating a potential mechanism behind the increase in stress with speed. These posture-mediated increases in elastic energy savings could be a key factor enabling kangaroos to achieve energetic benefits at faster hopping speeds, but may limit the performance of large kangaroos due to the risk of tendon rupture.
A comparative study of circulating tumor cell isolation and enumeration technologies in lung cancer
Authors: Saini Volga M , Oner Ezgi , Ward Mark , Hurley Sinead , Henderson Brian David , Lewis Faye , Finn Stephen P , O’Leary John , O’Toole Sharon , O’Driscoll Lorraine , Gately Kathy 
Published: February 2024

AbstractCirculating tumor cells (CTCs) have potential as diagnostic, prognostic and predictive biomarkers in solid tumors. Despite FDA approval of CTC devices in various cancers, their rarity and limited comparison between analysis methods hinder their clinical integration for lung cancer. This study aimed to evaluate five CTC isolation technologies using a standardized spike-in protocol: the CellMag™ (EpCAM-based enrichment), EasySep™ and RosetteSep™ (blood cell depletion), and the Parsortix® PR1 and next generation Parsortix® Plus (PX+) (size-based enrichment). The Parsortix® systems were also evaluated for any difference in recovery rates between cell harvest versus in- cassette staining. Healthy donor blood (5 mL) was spiked with 100 fluorescently labeled H1975 lung adenocarcinoma cell line, processed through each system and the isolation efficiency was calculated. All tested systems yielded discordant recovery rates with the CellMag™ having the highest mean recovery (70 ± 14%) followed by the PR1 (in-cassette staining) with a recovery of 49 ± 2% while the EasySep™ had the lowest recovery (18 ± 8%). The CellMag™ and Parsortix® PR1 may have potential clinical applications for lung cancer patients, albeit needing further optimization and validation.
Collective dynamical regimes predict invasion success and impacts in microbial communities
Authors: Hu Jiliang , Barbier Matthieu , Bunin Guy , Gore Jeff 
Published: February 2024

AbstractInvasions of microbial communities by species such as pathogens can have significant impacts on ecosystem services and human health1–9. Predicting the outcomes of these invasions, however, remains a challenge. Various theories propose that these outcomes depend on either characteristics of the invading species10–12or attributes of the resident community13–16, including its composition and biodiversity3,17–19. Here we used a combination of experiments and theory to show that the interplay between dynamics, interaction strength, and diversity determine the invasion outcome in microbial communities. We found that the communities with fluctuations in species abundance are both more invasible and more diverse than stable communities, leading to a positive diversity-invasibility relationship among communities assembled in the same environment. As predicted by theory, increasing interspecies interaction strength and species pool size leads to a decrease of invasion probability in our experiment. Although diversity-invasibility relationships are qualitatively different depending upon how the diversity is changed, we provide a unified perspective on the diversity-invasibility debate by showing a universal positive correspondence between invasibility and survival fraction of resident species across all conditions. Communities composed of strongly interacting species can exhibit an emergent priority effect in which invader species are less likely to colonize than species in the original pool. However, in this regime of strong interspecies interactions, if an invasion is successful, it causes larger ecological effects on the resident community than when interactions are weak. Our results demonstrate that the invasibility and invasion effect are emergent properties of interacting species, which can be predicted by simple community-level features.
The molecular basis for functional divergence of duplicated SOX factors controlling endoderm formation and left-right patterning in zebrafish
Authors: Johal Simaran , Elsayed Randa , Panfilio Kristen A. , Nelson Andrew C. 
Published: February 2024

AbstractEndoderm, one of three primary germ layers of vertebrate embryos, makes major contributions to the respiratory and gastrointestinal tracts and associated organs, including liver and pancreas. In mammals, the transcription factorSOX17is vital for endoderm organ formation and can induce endoderm progenitor identity. Duplication of ancestralsox17in the teleost lineage produced the paraloguessox32andsox17in zebrafish. Sox32 is required for specification of endoderm and progenitors of the left-right organiser (Kupffer’s Vesicle, KV), with Sox17 a downstream target of Sox32 that is implicated in further KV development. Phenotypic evidence therefore suggests functional similarities between zebrafish Sox32 and Sox17 and mammalian SOX17. Here, we directly compare these orthologues and paralogues, using the early zebrafish embryo as a biological platform for functional testing. Our results indicate that, unlike Sox32, human SOX17 cannot induce endoderm specification in zebrafish. Furthermore, using hybrid protein functional analyses, we show that Sox32 specificity for the endoderm gene regulatory network is linked to evolutionary divergence in its DNA-binding HMG domain from its paralogue Sox17. Additionally, changes in the C-terminal regions of Sox32 and Sox17 underpin their differing target specificities. Finally, we establish that specific conserved peptides in the C-terminal domain are essential for the role of Sox17 in establishing correct organ asymmetry. Overall, our results illuminate the molecular basis for functional divergence of Sox32 and Sox17 in vertebrate endoderm development and left-right patterning, and the evolution of SoxF transcription factor function.
How did vertebrate visual opsins diversify? - putting the last pieces of the puzzle together
Authors: Lagman David , Bergqvist Christina A. , Kuraku Shigehiro 
Published: February 2024

AbstractA crucial event in the evolution of compex vertebrate vision was the expansion of the visual opsin family in the ancestral vertebrate. However, it has been controversial whether the expansion was achieved through whole genome duplications or in tandem gene duplications. We here performed a vertebrate-wide genome comparison, including jawless vertebrates, which strongly favors the latter scenario. Our analyses uncovered frequent paralogy underlying homologous phenotypes caused by massive gene losses and distinct paralog utilization between jawless and jawed vertebrates.