bluuebunny/crossref_metadata_2025 huggingface dataset:
Adaptation across a precipitation gradient from niche center to niche edge
Authors: vanDeurs Samantha , Reutimann Oliver , Luqman Hirzi , Lifshitz Dikla , Gati Einav Mayzlish , Alexander Jake , Fior Simone
Published: April 2024

Evaluating the potential for species to adapt to changing climate relies on an appreciation of current patterns of adaptive variation and selection, which might vary in intensity across a species’ niche, affecting our inference of where adaptation might be most important in the future. Here we investigate the genetic basis of adaptation inLactuca serriola, the wild relative of the common lettuce, growing along a steep precipitation gradient in Israel approaching the species’ arid niche limit, and used candidate loci to inform predictions of its past and future adaptive evolution. Environmental association analyses combined with generalized dissimilarity models revealed 98 candidate genes showing non-linear shifts in allele frequencies across the gradient, with a large proportion under strong directional selection near the dry niche edge. Selection acts on genes with separate suites of biological functions, specifically related to osmotic stress and phenological adjustments at the dry edge, and related to biotic interactions at the niche center. The adaptive genetic composition of populations, as inferred through polygenic risk scores, indicates that intensified selection may be the key determinant of the dry niche edge. However, inference of past and future evolutionary change suggests larger adaptive shifts in the mesic part of the range, which is most affected by climate change. Our study highlights that non-linear spatial variation in selection has implications for predicting past and future responses to climate change.
Fetal Kidney Transplantation for In Utero Fetuses
Authors: Morimoto Keita , Yamanaka Shuichiro , Matsui Kenji , Kinoshita Yoshitaka , Inage Yuka , Yamamoto Shutaro , Koda Nagisa , Matsumoto Naoto , Saito Yatsumu , Takamura Tsuyoshi , Fujimoto Toshinari , Fukunaga Shohei , Tajiri Susumu , Matsumoto Kei , Ozawa Katsusuke , Wada Seiji , Kobayashi Eiji , Yokoo Takashi
Published: April 2024

Potter sequence, characterized by bilateral renal agenesis, oligohydramnios, and consequent pulmonary hypoplasia, presents a significant challenge in the management of affected neonates. Due to their prematurity and associated abdominal complications, these infants often fail to reach a stage where dialysis can be safely initiated and sustained, leading to an exceedingly high mortality rate. Therefore, there is hopeful anticipation that interventions serving as a bridge to achieve a state where dialysis can be safely performed will markedly improve life expectancy. We have developed a unique approach of “transplantation of fetal kidneys from a different species during the fetal period” as a bridge therapy until stable dialysis therapy can be implemented. This is a new concept of fetal therapy, targeting the fetus in utero and utilizing fetal kidneys of an appropriate size for transplantation.

In this study, we first validated the approach using allogeneic transplantation. Fetal kidneys with bladders from GFP-expressing rats (gestational age 14.0-16.5 days) were transplanted subcutaneously into allogeneic rat fetuses in utero (gestational age 18.0-18.5 days) using a special needle transuterinally, and live pups were successfully obtained. The transplanted fetal kidneys with bladders were confirmed to have urine production capability. By periodic aspiration of the subcutaneous urinary cyst after birth, urine produced by the transplanted fetal kidney was successfully drained outside the body for an extended period (up to 150 days). Biochemical tests confirmed the solute removal capacity of the transplanted fetal kidney. Furthermore, despite allogeneic transplantation, long-term urine production was sustained without the use of immunosuppressants, confirming that organ transplantation into fetuses is associated with lower rejection compared to adult transplantation. Next, xenotransplantation was performed. When GFP-expressing mouse fetal kidneys (gestational age 13.0-13.5 days) were transplanted into rat fetuses in utero, maturation of renal tissue structures was confirmed even in the interspecies setting.
STEP: Spatial Transcriptomics Embedding Procedure for Multi-scale Biological Heterogeneities Revelation in Multiple Samples
Authors: Li Lounan , Li Zhong , Yin Xiao-ming , Xu Xiaojiang
Published: April 2024

In the realm of spatially resolved transcriptomics (SRT) and single-cell RNA sequencing (scRNA-seq), addressing the intricacies of complex tissues, integration across non-contiguous sections, and scalability to diverse data resolutions remain paramount challenges. We introduce STEP (Spatial Transcriptomics Embedding Procedure), a novel foundation AI architecture for SRT data, elucidating the nuanced correspondence between biological heterogeneity and data characteristics. STEP’s innovation lies in its modular architecture, combining a Transformer andβ-VAE based backbone model for capturing transcriptional variations, a novel batch-effect model for correcting inter-sample variations, and a graph convolutional network (GCN)-based spatial model for incorporating spatial context—all tailored to reveal biological heterogeneities with un-precedented fidelity. Notably, STEP effectively scales the newly proposed 10x Visium HD technology for both cell type and spatial domain identifications. STEP also significantly improves the demarcation of liver zones, outstripping existing methodologies in accuracy and biological relevance. Validated against leading benchmark datasets, STEP redefines computational strategies in SRT and scRNA-seq analysis, presenting a scalable and versatile framework to the dissection of complex biological systems.
Patient-derived lymphomoids preserve the tumor architecture and allow to assess response to therapies in lymphoma
Authors: Santamaria-Martinez Albert , Epiney Justine , Srivastava Divyanshu , Tavernari Daniele , Varrone Marco , Milowich Dina , Letovanec Igor , Krueger Thorsten , Duran Rafael , Ciriello Giovanni , Cairoli Anne , Oricchio Elisa
Published: April 2024

The efficacy of anti-cancer therapies depends on the genomic composition of the tumor, its microenvironment, spatial organization, and intra-tumor heterogeneity. B cell lymphomas are a heterogeneous group of tumors emerging from B cells at different stages of differentiation and exhibiting tumor-specific interactions with the tumor microenvironment. Thus, to measure response to therapy in lymphoma, it is critical to preserve the tumor composition and functional interactions among immune cells. Here, we developed a platform to maintain small fragments of human lymphoma tissue in culture for several days, and use them to test response to therapies. We collected 25 patient samples representative of different lymphoma subtypes, and established ex vivo tissue fragments that retained histological, cellular, and molecular characteristics of the original tissue, here referred to as lymphomoids. Using lymphomoids, we tested sensitivity to several clinically approved small molecule inhibitors in parallel and examined tissue remodeling upon treatment. Importantly, when this information was available, we showed that sensitivity to therapy observed in lymphomoids was consistent with patient's response in the clinic. Lymphomoids are an innovative tool to assess treatment efficacy in clinically relevant contexts and could be used to uncover novel aspects of lymphoma biology.
CircRNA_012164/MicroRNA-9-5p axis mediates cardiac fibrosis in diabetic cardiomyopathy
Authors: Wang Honglin , Feng Biao , Wang Eric , Chakrabarti Subrata
Published: April 2024

Noncoding RNAs play a part in many chronic diseases and interact with each other to regulate gene expression. MicroRNA-9-5p (miR9) has been thought to be a potential inhibitor of diabetic cardiomyopathy. Here we examined the role of miR9 in regulating cardiac fibrosis in the context of diabetic cardiomyopathy. We further expanded our studies through investigation of a regulatory circularRNA, circRNA_012164, on the action of miR9. We showed at both thein vivoandin vitrolevel that glucose induced downregulation of miR9 and upregulation of circRNA_012164 resulted in the subsequent upregulation of downstream fibrotic genes. Further, knockdown of circRNA_012164 shows protective effects in cardiac endothelial cells and reverses increased transcription of genes associated with fibrosis and fibroblast proliferation through a regulatory axis with miR9. This study presents a novel regulatory axis involving noncoding RNA that is evidently important in the development of cardiac fibrosis in diabetic cardiomyopathy.
GiardiaIncreases Macrophage Production of the Anti-Inflammatory Cytokine Interleukin-10 in Response to Lipopolysaccharide via Macrophage Galactose Binding Lectin (MGL1)
Authors: Angelova V , Darmadi M , Miskovsky E , Fink M , Menegas S , Wexelblatt H , Singer S
Published: April 2024

Giardia duodenalisis an intestinal protozoan parasite, common in low- and middle-income countries. Infection is frequently subclinical, even when it is associated with other pathologies like growth stunting in children. Recent longitudinal cohort studies have foundGiardiamore frequently in patients with milder symptoms and have even suggested thatGiardiareduces rotavirus symptom severity. One potential mechanism for limiting disease severity due to other enteropathogens is the promotion of anti-inflammatory responses that limit pathology. Our lab previously showed thatGiardiareduced production of IL-12 by dendritic cells stimulated with TLR agonists. In this study, we show thatGiardiaincreases the production of the anti-inflammatory cytokine IL-10 by mouse peritoneal macrophages in response to bacterial LPS. This potentiation is specific to IL-10, as no changes were seen in the production of the pro-inflammatory cytokine TNF-□. Moreover, peritoneal macrophages from mice lacking macrophage galactose-binding lectin (MGL1), a pathogen recognition receptor that has been previously shown to bind N-acetylgalactosamine, failed to increase IL-10 production after stimulation withGiardiaand LPS.Giardia’s immunoregulation of the IL-10 response may help us understand the parasite’s role in reducing diarrheal severity.
Cancer cell-derived extracellular matrix promotes differentiation of fibroblasts into cancer-associated fibroblasts
Authors: Yondem Eyup , Pesen-Okvur Devrim
Published: April 2024

Breast cancer is the most common cancer and the leading cause of cancer-related mortality in women. In addition to cancer cells, the bulk of a breast tumor comprises a range of stromal cell types, including fibroblasts. Cancer-associated fibroblasts (CAF) are crucial players in the tumor microenvironment; however, the process by which fibroblasts differentiate into CAFs is not fully understood. Extracellular matrix (ECM) is known to modulate cell phenotypes. Decellularized ECM (dECM) is a useful tool for studyingin-vitrocell-ECM interactions. Yet, whether cancer cell-derived ECM (ccECM) has a role in CAF formation is not known. Here, we optimized the culture duration (5 days) and the extraction method (freeze-thaw) for obtaining ccECM. We confirmed the presence of ccECM using coomassie blue staining and scanning electron microscopy. We showed that ccECM contained fibronectin and laminin using immunofluorescence staining. In addition, we showed that the presence of ccECM but not glass surface or TGFβ promoted the initial adhesion of fibroblasts, as expected. Finally, using quantitative immunofluorescence microscopy, we demonstrated that in contrast to fibroblasts cultured on glass surfaces in the presence and absence of TGFβ, fibroblasts cultured on ccECM showed increased expression of CAF markers vimentin (2.8 fold), FAP (3.4 fold) and PDGFR β (1.8 fold), but not FSP1/s100A4. Overall, our results indicate that ccECM promotes the differentiation of fibroblasts into CAFs.
A Quantitative Metric of Confidence For Segmentation of Nuclei in Large Spatially Variable Image Volumes
Authors: Wu Liming , Chen Alain , Salama Paul , Dunn Kenneth W , Winfree Seth , Delp Edward J
Published: April 2024

Nuclei segmentation is an important step for quantitative analysis of fluorescence microscopy images. A large volume generally has many different regions containing nuclei with varying spatial characteristics. Automatically identifying nuclei that are challenging to segment can speed up the analysis of biological tissues. Here we show a segmentation technique that provides a metric of segmentation "confidence" for each segmented object in an image volume. This confidence metric can be used either to generate a "confidence map" for visual distinction of reliable from unreliable regions, or in the data space to identify questionable measurements that can be analyzed separately or eliminated from analysis. In an analysis of nuclei in a 3-dimensional image volume, we show that the confidence map correlates well with visual evaluations of segmentation quality, and that the confidence metric correlates well with F1 scores within subregions of the image volume. In addition, we also describe three visualization methods that can visualize the segmentation differences between a segmented volume and a reference volume.
Propofol overcome Tamoxifen resistance in breast cancer by modulating tumorogenesis, immune response and metabolism
Authors: Yin Runyang , Gao Jing , Guo Chunyan , Liu Yang
Published: April 2024

Although 70% of estrogen receptor (ER)-positive breast cancer patients benefit from Tamoxifen therapy, the developing resistance to Tamoxifen leads to high rates of metastasis and poor prognosis. Propofol, a commonly used anesthetic, has been shown to inhibit the occurrence and development of breast cancer. However, its role in anti-endocrine resistance in ER-positive breast cancer remains unclear. In this study, we found that Propofol significantly promotes cell cycle arrest, induces apoptosis, and inhibits proliferation in Tamoxifen-resistant breast cancer cells. Furthermore, transcriptome sequencing analysis revealed 1065 differentially expressed genes (DEGs) between Propofol-treated Tamoxifen-resistant MCF-7 (MCF7-TR) cells and none-treated MCF7-TR cells. Gene ontology annotation enrichment analysis (GO), Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis (KEGG), and gene set enrichment analysis (GSEA) showed that Propofol affects the expression of genes located in the plasma membrane and cell periphery, mainly regulating signals involved in cell cycle regulation, immune response modulation, and metabolism. Our results provide new insights into the mechanism by which Propofol controls resistance to Tamoxifen in breast cancer progression and offer a theoretical basis for clinical treatment.
Deciphering the Immune Subtypes and Signature Genes: A Novel Approach Towards Diagnosing and Prognosticating Severe Asthma through Interpretable Machine Learning
Authors: Hu Yue , Lin Yating , Peng Bo , Xiang Chunyan , Tang Wei
Published: April 2024

Asthma, a pervasive pulmonary disorder, affects countless individuals globally. Characterized by chronic inflammation of the bronchial passages, its symptoms include cough, wheezing, dyspnea, and chest tightness. While many manage their symptoms through pharmaceutical interventions and self-care, a significant subset grapples with severe asthma, posing therapeutic challenges. This study delves into the intricate etiology of asthma, emphasizing the pivotal roles of immune cells such as T cells, eosinophils, and mast cells in its pathogenesis. The recent emergence of monoclonal antibodies, including Mepolizumab, Reslizumab, and Benralizumab, offers therapeutic promise, yet their efficacy varies due to the heterogeneous nature of asthma. Recognizing the potential of personalized medicine, this research underscores the need for a comprehensive understanding of asthma’s immunological diversity. We employ ssGSEA and LASSO algorithms to identify differentially expressed immune cells and utilize machine learning techniques, including XGBoost and Random Forest, to predict severe asthma outcomes and identify key genes associated with immune cells. Using a murine asthma model and an online database, we aim to elucidate distinct immune-centric asthma subtypes. This study seeks to provide novel insights into the diagnosis and classification of severe asthma through a transcriptomic lens.
That’s not a Hybrid: How to Distinguish Patterns of Admixture and Isolation-by-Distance
Authors: Wiens Ben J. , Colella Jocelyn P.
Published: April 2024

Describing naturally occurring genetic variation is a fundamental goal of molecular phylogeography and population genetics. Popular methods for this task includeSTRUCTURE, a model-based algorithm that assigns individuals to genetic clusters, and Principal Component Analysis (PCA), a parameter-free method. The ability ofSTRUCTUREto infer mixed ancestry makes it popular for documenting natural hybridization, which is of considerable interest to evolutionary biologists, given that such systems provide a window into the speciation process. YetSTRUCTUREcan produce misleading results when its underlying assumptions are violated, like when genetic variation is distributed continuously. To test the ability ofSTRUCTUREand PCA to accurately distinguish admixture from continuous variation, we use forward-time simulations to generate population genetic data under three demographic scenarios: two involving admixture and one with isolation-by-distance (IBD).STRUCTUREand PCA alone cannot distinguish admixture from IBD, but complementing these analyses with triangle plots, which visualize hybrid index against interclass heterozygosity, provides more accurate inference of demographic history. We demonstrate that triangle plots are robust to missing data, whileSTRUCTUREand PCA are not, and show that setting a low allele frequency difference threshold for AIM identification can accurately characterize the relationship between hybrid index and interclass heterozygosity across demographic histories of admixture and range expansion. WhileSTRUCTUREand PCA provide useful summaries of genetic variation, results should be paired with triangle plots before admixture is inferred.
Pervasive gene flow despite strong and varied reproductive barriers in swordtails
Authors: Aguillon Stepfanie M. , Haase Cox Sophia K. , Langdon Quinn K. , Gunn Theresa R. , Baczenas John J. , Banerjee Shreya M. , Donny Alexandra E. , Moran Benjamin M. , Gutiérrez-Rodríguez Carla , Ríos-Cárdenas Oscar , Morris Molly R. , Powell Daniel L. , Schumer Molly
Published: April 2024

One of the mechanisms that can lead to the formation of new species occurs through the evolution of reproductive barriers. However, recent research has demonstrated that hybridization has been pervasive across the tree of life even in the presence of strong barriers. Swordtail fishes (genusXiphophorus) are an emerging model system for studying the interface between these barriers and hybridization. We document overlapping mechanisms that act as barriers between closely related species,X. birchmanniandX. cortezi, by combining genomic sequencing from natural hybrid populations, artificial crosses, behavioral assays, sperm performance, and developmental studies. We show that strong assortative mating plays a key role in maintaining subpopulations with distinct ancestry in natural hybrid populations. Lab experiments demonstrate that artificial F1crosses experience dysfunction: crosses withX. birchmannifemales were largely inviable and crosses withX. cortezifemales had a heavily skewed sex ratio. Using F2hybrids we identify several genomic regions that strongly impact hybrid viability. Strikingly, two of these regions underlie genetic incompatibilities in hybrids betweenX. birchmanniand its sister speciesX. malinche. Our results demonstrate that ancient hybridization has played a role in the origin of this shared genetic incompatibility. Moreover, ancestry mismatch at these incompatible regions has remarkably similar consequences for phenotypes and hybrid survival inX. corteziÔX. birchmannihybrids as inX. malincheÔX. birchmannihybrids. Our findings identify varied reproductive barriers that shape genetic exchange between naturally hybridizing species and highlight the complex evolutionary outcomes of hybridization.

Significance Statement

Biologists are fascinated by how the diverse species we see on Earth have arisen and been maintained. One driver of this process is the evolution of reproductive barriers between species. Despite the commonality of these barriers, many species still exchange genes through a process called hybridization. Here, we show that related species can have a striking array of reproductive barriers—from genetic interactions that harm hybrids to mate preferences that reduce hybridization in the first place. However, we also find that genetic exchange between these species is very common, and may itself play an important role in the evolution of reproductive barriers. Together, our work highlights the complex web of interactions that impact the origin and persistence of distinct species.
Transcriptional regulation in the absence of Inositol Trisphosphate Receptor Calcium Signaling
Authors: Young Michael , Booth David M. , Smith David , Tigano Marco , Hajnόczky Gyӧrgy , Joseph Suresh K.
Published: April 2024

The activation of IP3receptor (IP3R) Ca2+channels generates agonist-mediated Ca2+signals that regulate a wide range of biological processes. It is therefore surprising that CRISPR induced loss of all three IP3R isoforms (TKO) in HEK293 and HeLa cell lines yields cells that can survive, grow and divide, albeit more slowly than wild-type cells. In an effort to understand the adaptive mechanisms involved, we have examined the activity of key Ca2+dependent transcription factors (NFAT, CREB, AP-1 and NFκb) and signaling pathways using luciferase-reporter assays, phosphoprotein immunoblots and whole genome transcriptomic studies. In addition the role of protein kinase C (PKC) was investigated with inhibitors and siRNA knockdown. The data showed that agonist-mediated NFAT activation was lost but CREB activation was maintained in IP3R TKO cells. Under base-line conditions transcriptome analysis indicated the differential expression (DEG) of 828 and 311 genes in IP3R TKO HEK293 or HeLa cells, respectively, with only 18 genes being in common. In summary three main adaptations in TKO cells are identified in this study: 1) increased basal activity of NFAT, CREB, AP-1 and NFκb; 2) an increased reliance on Ca2+-insensitive PKC isoforms; and 3) increased production of reactive oxygen species and upregulation of antioxidant defense enzymes. We suggest that whereas wild-type cells rely on a Ca2+and DAG signal to respond to stimuli, the TKO cells utilize the adaptations to allow key signaling pathways (e.g. PKC, Ras/MAPK, CREB) to transition to the activated state using a DAG signal alone.
GWASBrewer: An R Package for Simulating Realistic GWAS Summary Statistics
Authors: Morrison Jean
Published: April 2024

1

Many statistical genetics analysis methods make use of GWAS summary statistics. Best statistical practice requires evaluating these methods in simulations against a known truth. Ideally, these simulations should be as realistic as possible. However, simulating summary statistics by first simulating individual genotype and phenotype data is extremely computationally demanding, especially when large sample sizes or many traits are required. We presentGWASBrewer, an open source R package for direct simulation of GWAS summary statistics. We show that statistics simulated byGWASBrewerhave the same distribution as statistics generated from individual level data, and can be produced at a fraction of the computational expense. Additionally,GWASBrewercan simulate standard error estimates, something that is typically not done when sampling summary statistics directly.GWASBreweris highly flexible, allowing the user to simulate data for multiple traits connected by causal effects and with complex distributions of effect sizes. We demonstrate example uses ofGWASBrewerfor evaluating Mendelian randomization, polygenic risk score, and heritability estimation methods.
Physical cell-cell interactions regulate transcriptional programmes that control the responses of high grade serous ovarian cancer patients to therapy
Authors: Hameed Sodiq A. , Kolch Walter , Brennan Donal J. , Zhernovkov Vadim
Published: April 2024

The tumour microenvironment is composed of a complex cellular network involving cancer, stromal and immune cells in dynamic interactions. A large proportion of this network relies on direct physical interactions between cells, which may impact patient responses to clinical therapy. Doublets in scRNA-seq are usually excluded from analysis. However, they may represent directly interacting cells. To decipher the physical interaction landscape in relation to clinical prognosis, we inferred a physical cell-cell interaction (PCI) network from ‘biological’ doublets in a scRNA-seq dataset of approximately 18,000 cells, obtained from 7 treatment-naive ovarian cancer patients. Focusing on cancer-stromal PCIs, we uncovered molecular interaction networks and transcriptional landscapes that stratified patients in respect to their clinical responses to standard therapy. Good responders featured PCIs involving immune cells interacting with other cell types including cancer cells. Poor responders lacked immune cell interactions, but showed a high enrichment of cancer-stromal PCIs. To explore the molecular differences between cancer-stromal PCIs between responders and non-responders, we identified correlating gene signatures. We constructed ligand-receptor interaction networks and identified associated downstream pathways. The reconstruction of gene regulatory networks and trajectory analysis revealed distinct transcription factor (TF) clusters and gene modules that separated doublet cells by clinical outcomes. Our results indicate (i) that transcriptional changes resulting from PCIs predict the response of ovarian cancer patients to standard therapy, (ii) that immune reactivity of the host against the tumour enhances the efficacy of therapy, and (iii) that cancer-stromal cell interaction can have a dual effect either supporting or inhibiting therapy responses.
Dense Investigation of Variability in Affect (DIVA): A Neuroimaging Study of Premenopausal Female Participants
Authors: Bottenhorn Katherine L. , Salo Taylor , Peraza Julio A. , Riedel Michael C. , Flannery Jessica S. , Kimbler Adam , Toll Alfredo , Suarez Diego , Cruz Francis M. , Zagales Israel , Caldes Nayade , Dolan Olivia , Zagales Ruth , Sutherland Matthew T. , Laird Robert W. , Laird Angela R.
Published: April 2024

The rise of large neuroimaging datasets and multi-dataset mega-analyses brings the power to study interindividual differences in brain structure and function on a heretofore unseen scale. However, unknown and poorly characterized intra-individual variability continues to undermine the detection of robust brain-behavior associations and, ultimately, our understanding of the brain on the whole. Women’s and reproductive health underlie variability in more than half of the population, but have long been overlooked in the study of both inter- and intra-individual differences in the brain. To this end, the Dense Investigation of Variability in Affect (DIVA) Study was designed to study intra-individual variability in the brain and behavior across the menstrual cycle in a small cohort of premenopausal female participants. The DIVA Study acquired weekly actigraphy, self-report, biospecimen, and both functional and structural magnetic resonance imaging data with concurrent peripheral physiological recordings. These data facilitate the study of several common sources of variability in the brain and behavior: the menstrual cycle and ovarian hormones, sleep, stress, exercise, and exogenous sources of hemodynamic variability.
NovoBoard: a comprehensive framework for evaluating the false discovery rate and accuracy of de novo peptide sequencing
Authors: Tran Ngoc Hieu , Qiao Rui , Mao Zeping , Pan Shengying , Zhang Qing , Li Wenting , Xin Lei , Li Ming , Shan Baozhen
Published: April 2024

De novo peptide sequencing is a fundamental research area in mass spectrometry (MS) based proteomics. However, those methods have often been evaluated using a couple of simple metrics that do not fully reflect their overall performance. Moreover, there has not been an established method to estimate the false discovery rate (FDR) and the significance of de novo peptide-spectrum matches (PSMs). Here we propose NovoBoard, a comprehensive framework to evaluate the performance of de novo peptide sequencing methods. The framework consists of diverse benchmark datasets (including tryptic, nontryptic, immunopeptidomics, and different species), and a standard set of accuracy metrics to evaluate the fragment ions, amino acids, and peptides of the de novo results. More importantly, a new approach is designed to evaluate de novo peptide sequencing methods on target-decoy spectra and to estimate their FDRs. Our results thoroughly reveal the strengths and weaknesses of different de novo peptide sequencing methods, and how their performances depend on specific applications and the types of data. Our FDR estimation also shows that some tools may perform better than the others in distinguishing between de novo PSMs and random matches, and can be used to assess the significance of de novo PSMs.
HELP: A computational framework for labelling and predicting human common and context-specific essential genes
Authors: Granata Ilaria , Maddalena Lucia , Manzo Mario , Guarracino Mario Rosario , Giordano Maurizio
Published: April 2024

Machine learning-based approaches are particularly suitable for identifying essential genes as they allow the generation of predictive models trained on features from multi-source data. Gene essentiality is neither binary nor static but determined by the context. The databases for essential gene annotation do not permit the personalisation of the context, and their update can be slower than the publication of new experimental data. We propose HELP (Human GeneEssentialityLabelling &Prediction), a computational framework for labelling and predicting essential genes. Its double scope allows for identifying genes based on dependency or not on experimental data. The effectiveness of the labelling method was demonstrated by comparing it with other approaches in overlapping the reference sets of essential gene annotations, where HELP demonstrated the best compromise between false and true positive rates. The gene attributes, including multi-omics and network embedding features, lead to high-performance prediction of essential genes while confirming the existence of essentiality nuances.

Author summary

Essential genes (EGs) are commonly defined as those required for an organism or cell’s growth and survival. The essentiality is strictly dependent on both environmental and genetic conditions, determining a difference between those considered common EGs (cEGs), essential in most of the contexts considered, and those essential specifically to one or few contexts (context-specific EGs, csEGs). In this paper, we present a library of tools and methodologies to address the identification and prediction of cEGs and csEGs. Furthermore, we attempt to experimentally explore the statement that essentiality is not a binary property by identifying, predicting and analysing an intermediate class between the Essential (E) and Not Essential (NE) genes. Among the multi-source data used to predict the EGs, we found the best attributes combination to capture the essentiality. We demonstrated that the additional class of genes we defined as “almost Essential” shows differences in these attributes from the E and NE genes. We believe that investigating the context-specificity and the dynamism of essentiality is particularly relevant to unravelling crucial insights into biological mechanisms and suggesting new candidates for precision medicine.
A Computational Algorithm for Optimal Design of Bioartificial Organ Scaffold Architectures
Authors: Bukač Martina , Čanić Sunčica , Muha Boris , Wang Yifan
Published: April 2024

We develop a computational algorithm based on a diffuse interface approach to study the design of bioartificial organ scaffold architectures. These scaffolds, composed of poroelastic hydrogels housing transplanted cells, are linked to the patient’s blood circulation via an anastomosis graft. Before entering the scaffold, the blood flow passes through a filter, and the resulting filtered blood plasma transports oxygen and nutrients to sustain the viability of transplanted cells over the long term. A key issue in maintaining cell viability is the design of ultrafiltrate channels within the hydrogel scaffold to facilitate advection-enhanced oxygen supply ensuring oxygen levels remain above a critical threshold to prevent hypoxia. In this manuscript, we develop a computational algorithm to analyze the plasma flow and oxygen concentration within hydrogels featuring various channel geometries. Our objective is to identify the optimal hydrogel channel architecture that sustains oxygen concentration throughout the scaffold above the critical hypoxic threshold.

The computational algorithm we introduce here employs a diffuse interface approach to solve a multi-physics problem. The corresponding model couples the time-dependent Stokes equations, governing blood plasma flow through the channel network, with the time-dependent Biot equations, characterizing Darcy velocity, pressure, and displacement within the poroelastic hydrogel containing the transplanted cells. Subsequently, the calculated plasma velocity is utilized to determine oxygen concentration within the scaffold using a diffuse interface advection-reaction-diffusion model. Our investigation yields a scaffold architecture featuring a hexagonal channel network geometry that meets the desired oxygen concentration criteria. Unlike classical sharp interface approaches, the diffuse interface approach we employ is particularly adept at addressing problems with intricate interface geometries, such as those encountered in bioartificial organ scaffold design. This study is significant because recent developments in hydrogel fabrication make it now possible to control hydrogel rheology [20, 14], and utilize computational results to generate optimized scaffold architectures.

MSC codes

76S05; 76-04; 76D05; 92-10; 92-04
Warming-induced excess deaths of infected animals depend on pathogen kingdom and evolutionary history
Authors: Li Jingdi , Guttmann Nele , Drew Georgia , Hector Tobias , Wolinska Justyna , King Kayla
Published: April 2024

Climate change is causing extreme heating events. Simultaneously, climate change and human activities are leading to more prolonged and intense infectious disease outbreaks. The extent to which warming and infection may together impact host species persistence is, however, unclear. Using a meta-analysis of >190 effect sizes representing 101 ectothermic animal host-pathogen systems, we provide broad evidence that experimentally increased temperatures drove higher pathogen virulence, specifically pathogen-induced host mortality. Such pattern was mainly driven by excess host death caused by bacterial infections combined with warming, particularly if the pathogenic bacteria were naturally established within the host species, though novel infections without known host-pathogen evolutionary history were more lethal at lower temperatures. Importantly, larger temperature increases were associated with more host deaths hinting at the escalating threat for animal species as the world continues to warm. We found that the virulence of fungal pathogens increased only when temperatures were shifted upwards towards their thermal optimum. The magnitude of these effects was not impacted by host life-stage, immune complexity, or variable experimental protocols. Overall, our findings reveal distinct patterns of pathogen virulence change under warmer temperatures, suggesting that the impact of global warming on infectious disease outcomes would depend on pathogen traits (taxonomic kingdom, thermal tolerance) and host-pathogen evolutionary history.

Author Summary

Human-induced climate warming is one of the biggest challenges in our times. Simultaneously, climate change is associated with more intense infectious disease outbreaks, suggesting that temperature rises also influence disease dynamics. Growing numbers of studies have investigated the effect of warming on disease severity (or pathogen virulence) in different animal host-pathogen systems. However, individual studies did not always agree with each other, and how increased temperature and pathogen infection together impact animal survival remains unclear. Here, we resolved this uncertainty by conducting a meta-analysis of >190 effect sizes representing 101 animal host-pathogen systems. We provided broad evidence that, higher temperatures caused more deaths of infected animals, particularly for animals with bacterial infections under warmer conditions. We found that larger temperature rises were associated with more animal deaths, suggesting the increased threat for host species as the world continues to warm. We also found that pathogenic fungi were more sensitive to heat than bacterial pathogens, and temperature changes the virulence of fungal pathogens in relation to their thermal optimum.
Healthy carriage of Salmonella within cattle lymph nodes is a key source of ground beef contamination with strains of clinical significance
Authors: Delgado-Suarez Enrique Jesus , Garcia-Meneses Abril Viridiana , Ponce-Hernandez Elfrego Adrian , Hernandez-Perez Cindy Fabiola , Rubio-Lozano Maria Salud , Ballesteros-Nova Nayarit Emerita , Soberanis-Ramos Orbelin
Published: April 2024

This study assessed the genetic relatedness, evolutionary dynamics, and virulence profile of Salmonella isolated from lymph nodes and ground beef from apparently healthy cattle over two years. For this purpose, we used a set of isolates of nine different serovars: Anatum (n=23), Reading (n=22), Typhimurium (n=10), London (n=9), Kentucky (n=6), Fresno (n=4), Give, Muenster, and monophasic 1,4,[5],12:i- (n=1 each). These isolates were subjected to whole genome sequencing, and assembled and annotated genomes were used for downstream bioinformatic analyses. Although lymph nodes and ground beef were collected and analyzed separately, we still observed clonality between isolates from both sources. This finding suggests that some Salmonella circulating in the gut may reach the lymphatic system, creating a dual reservoir for ground beef contamination. We also found evidence of Salmonella persistence across cattle cohorts, as we observed clonality between isolates collected in different years. Variation in the virulence and pathogenicity island profiles was limited, with minor differences that could not be associated with attenuated virulence in the bovine host. Conversely, isolates of all serovars, except Fresno, were genetically close to strains involved in human salmonellosis in different countries, highlighting the risk to public health posed by strains associated with the carrier state in cattle. Further research is needed to reveal the mechanisms by which Salmonella causes subclinical infections in cattle and persists for long periods within farm environments.
Tandem-repeat proteins introduce tuneable properties to engineered biomolecular condensates
Authors: Chris Ng Tin Long , Hoare Mateo P. , Maristany M. Julia , Wilde Ellis J. , Sneideris Tomas , Huertas Jan , Agbetiameh Belinda K. , Furukawa Mona , Joseph Jerelle A. , Knowles Tuomas P.J. , Collepardo-Guevara Rosana , Itzhaki Laura S. , Kumita Janet R.
Published: April 2024

The cell’s ability to rapidly partition biomolecules into biomolecular condensates is linked to a diverse range of cellular functions. Understanding how the structural attributes of biomolecular condensates are linked with their biological roles can be facilitated by the development synthetic condensate systems that can be manipulated in a controllable and predictable way. Here, we design and characterise a tuneable synthetic biomolecular condensate platform fusing modular consensus-designed tetratricopeptide repeat (CTPR) proteins to intrinsically-disordered domains. Trends between the CTPR structural attributes and condensate propensity were recapitulated across different experimental conditions and byin silicomodelling, demonstrating that the CTPR domain can systematically affect the condensates in a predictable manner. Moreover, we show that incorporating short binding motifs into the CTPR domain results in specific target-protein recruitment into the condensates. Our model system can be rationally designed in a versatile manner to both tune condensate propensity and endow the condensates with new functions.
Calculating Protein-Ligand Residence Times Through State Predictive Information Bottleneck based Enhanced Sampling
Authors: Lee Suemin , Wang Dedi , Seeliger Markus A. , Tiwary Pratyush
Published: April 2024

Understanding drug residence times in target proteins is key to improving drug efficacy and understanding target recognition in biochemistry. While drug residence time is just as important as binding affinity, atomiclevel understanding of drug residence times through molecular dynamics (MD) simulations has been difficult primarily due to the extremely long timescales. Recent advances in rare event sampling have allowed us to reach these timescales, yet predicting protein-ligand residence times remains a significant challenge. Here we present a semi-automated protocol to calculate the ligand residence times across 12 orders of magnitudes of timescales. In our proposed framework, we integrate a deep learning-based method, the state predictive information bottleneck (SPIB), to learn an approximate reaction coordinate (RC) and use it to guide the enhanced sampling method metadynamics. We demonstrate the performance of our algorithm by applying it to six different protein-ligand complexes with available benchmark residence times, including the dissociation of the widely studied anti-cancer drug Imatinib (Gleevec) from both wild-type Abl kinase and drug-resistant mutants. We show how our protocol can recover quantitatively accurate residence times, potentially opening avenues for deeper insights into drug development possibilities and ligand recognition mechanisms.

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Toxic Effects of Biogenic and Synthesized Silver Nanoparticles on Sea UrchinEchinometra lucunterEmbryos
Authors: Bruni Mariana , Ottoni Cristiane , Abessa Denis
Published: April 2024

Due to their broad-spectrum antimicrobial action and ease of synthesis, silver nanoparticles (AgNPs) are one of the most widely used nanomaterials in different industrial and ecological areas. AgNPs are released into marine ecosystems; however, their ecotoxicological effects have been overlooked. In this study, we evaluated the toxic effects of biogenic and synthesized AgNPs on sea urchinEchinometra lucunterembryos and compared them to those of AgNO3. Fertilized eggs were exposed to five concentrations of the test compounds and a negative control for 48 h under controlled conditions. The EC50-48h of biogenic and synthetic AgNPs and AgNO3were 0.31, 4.095, and 0.01 μg L-1, evidencing that AgNPs are less toxic than AgNO3, and that synthetic AgNP is less toxic. Toxicity toE. lucunterembryos could be explained by the fact that Ag affects DNA replication and induces the formation of pores in the cellular wall, leading to apoptosis.
Regional Glymphatic Dysfunction is linked to Spinocerebellar Ataxia Type 3 pathophysiology
Authors: Hua Lin , Xu Manxi , Zhang Linwei , Gao Fei , Zeng Xinglin , Yang Aocai , Luan Jixin , Shmuel Amir , Ma Guolin , Yuan Zhen
Published: April 2024

Spinocerebellar ataxia type 3 (SCA3) involves neuroinflammation and imbalance between production and clearance of proteins which affects the glymphatic system, the lymphatic-like, fluid-transport system in the brain. However, it is unclear whether SCA3 is related to impairments in glymphatic function. Using multimodal imaging data, 34 SCA3 patients and 36 age-, sex- and educational matched healthy controls (HCs) were compared using multiple glymphatic measurements, including choroid plexus (CP) and cerebrospinal fluid (CSF) volume, diffusion tensor imaging along the perivascular (DTI-ALPS) index, and coupling relationship between blood-oxygen-level-dependent signals and CSF flow (BOLD-CSF coupling). Then, we evaluated regional glymphatic function by dividing DTI-ALPS and BOLD-CSF coupling into anterior, middle, posterior, and cerebellum regions, thereby identifying the spatial variation of glymphatic function in the two groups. We demonstrated that compared with HCs, larger CP and CSF volumes were found in SCA3 patients. More importantly, for DTI-ALPS index and BOLD-CSF coupling, these surrogate markers for glymphatic clearance were weaker in SCA3 patients. Furthermore, altered regional glymphatic functions were most prominent in midbrain, cerebellum and middle regions. Crucially, the altered midbrain, cerebellum, middle and global glymphatic functions were accompanied by the severity of ataxia and other SCA3 symptoms. Similar to other neurodegenerative disorders, the association between multiple glymphatic indexes and SCA3 symptoms suggested that waste clearance is disrupted in SCA3 patients, which shed light on the pathogenesis of this disease from a glymphatic lens. Our findings highlighted the dysregulated glymphatic function as a novel diagnostic marker for SCA3.
Bessel Beam Optical Coherence Microscopy Enables Multiscale Assessment of Cerebrovascular Network Morphology and Function
Authors: Glandorf Lukas , Wittmann Bastian , Droux Jeanne , Glück Chaim , Weber Bruno , Wegener Susanne , El Amki Mohamad , Leitgeb Rainer , Menze Bjoern , Razansky Daniel
Published: April 2024

Understanding the morphology and function of large-scale cerebrovascular networks is crucial for studying brain health and disease. However, reconciling the demands for imaging on a broad scale with the precision of high-resolution volumetric microscopy has been a persistent challenge. In this study, we introduce Bessel beam optical coherence microscopy with an extended focus to capture the full cortical vascular hierarchy in mice over 1000 × 1000 × 360 μm3field-of-view at capillary level resolution. The post-processing pipeline leverages a supervised deep learning approach for precise 3D segmentation of high-resolution angiograms, hence permitting reliable examination of microvascular structures at multiple spatial scales. Coupled with high-sensitivity Doppler optical coherence tomography, our method enables the computation of both axial and transverse blood velocity components as well as vessel-specific blood flow direction, facilitating a detailed assessment of morpho-functional characteristics across all vessel dimensions. Through graph-based analysis, we deliver insights into vascular connectivity, all the way from individual capillaries to broader network interactions, a task traditionally challenging forin vivostudies. The new imaging and analysis framework extends the frontiers of research into cerebrovascular function and neurovascular pathologies.
The genetic diversity ofStrongyloides papillosusin Pakistani goats revealed by whole genome sequencing
Authors: Afshan Kiran , Liu Yuchen , Viney Mark
Published: April 2024

Strongyloidesnematodes are parasites of livestock, andS. papillosusinfects ruminant livestock that can cause disease. Recent genomic analysis of severalStrongyloidesspecies is now facilitating the population genomic analyses of naturalStrongyloidesinfections, for example finding thatS. rattiin wild UK rats exists as an assemblage of long-lived, asexual lineages. Here we have initiated an investigation into the population genomics ofS. papillosusin goats in Pakistan. We find thatS. papillosusis common, with a prevalence of 28%; that the population is genetically diverse and that individual goats commonly have mixed-genotype infections; and that there is evidence of only limited admixture. These results now provoke further questions about the host range of differentS. papillosusgenotypes that can in the future be investigated by further population genomic analyses.