bluuebunny/crossref_metadata_2025 huggingface dataset:
Identification of inflammatory biomarkers in IgA nephropathy using the NanoString technology: a validation study
Authors: Gaumond Laurence , Lamarche Caroline , Beauchemin Stéphanie , Henley Nathalie , Elftouh Naoual , Gerarduzzi Casimiro , Laurin Louis-Philippe
Published: September 2023

Objective and design

Immunoglobulin A nephropathy (IgAN) is a kidney disease characterized by the accumulation of IgA deposits in the glomeruli of the kidney, leading to inflammation and damage to the kidney. The inflammatory markers involved in IgAN remain to be defined. Gene expression analysis platforms, such as the NanoString nCounter system, are promising screening and diagnostic tools, especially in the oncology field, but its role as a diagnostic and prognostic tool in IgAN remains scarce. In this study, we aimed to validate the use of NanoString technology to identify potential inflammatory biomarkers involved in the progression of IgAN.

Subjects

A total of 30 patients with biopsy-proven IgAN and 7 cases of antineutrophil cytoplasmic antoantibodies (ANCA) associated pauci-immune glomerulonephritis were included for gene expression measurement. For the immunofluorescence validation experiments, a total of 6 IgAN patients and 3 healthy controls were included.

Methods

Total RNA was extracted from formalin-fixed-paraffin-embedded kidney biopsy specimens, and a customized 48-plex human gene CodeSet was used to study 29 genes implicated in different biological pathways. Comparisons in gene expression were made between IgAN and ANCA-associated pauci-immune glomerulonephritis patients to delineate an expression profile specific to IgAN. Gene expression was compared between patients with low and moderate risk of progression. Genes for which RNA expression was associated with disease progression were analyzed for protein expression by immunofluorescence, and compared with healthy controls.

Results

IgAN patients had a distinct gene expression profile with decreased expression in genesIL-6, INFGandC1QBcompared to ANCA patients.C3andTNFR2were identified as potential biomarkers for IgAN progression in patients early in their disease course. Protein expression for those 2 candidate genes was upregulated in IgAN patients compared to controls. Expression of genes implicated in fibrosis (PTEN, CASPASE 3, TGM2, TGFB1, IL2, andTNFRSF1B) was more pronounced in IgAN patient with severe fibrosis compared to those with none.

Conclusions

Our findings validate our NanoString mRNA profiling by examining protein expression levels of two candidate genes,C3andTNFR2, in IgAN patients and healthy controls. We were also able to identify several upregulated mRNA transcripts implicated in the development of fibrosis that may be considered as fibrotic markers within IgAN patients.
The extrafollicular B cell response is a hallmark of childhood idiopathic nephrotic syndrome
Authors: Al-Aubodah Tho-Alfakar , Aoudjit Lamine , Pascale Giuseppe , Perinpanayagam Maneka A. , Langlais David , Bitzan Martin , Samuel Susan M. , Piccirillo Ciriaco A. , Takano Tomoko
Published: September 2023

An autoimmune B cell origin for childhood idiopathic nephrotic syndrome (INS) is predicted based on the efficacy of rituximab (RTX) at maintaining long-term remission from proteinuria. Knowledge regarding the nature of the culprit B cell response is very limited. Using single-cell RNA-sequencing, we demonstrate that a B cell transcriptional program poised for effector functions represents the major immune perturbation in the blood of children with active INS. This was conferred by the engagement of an extrafollicular B cell response marked by the expansion of atypical B cells (atBCs), marginal zone-like B cells, and antibody-secreting cells (ASCs). In flow-based analyses of blood from 13 children with active INS and 24 healthy donors, this was reflected by the proliferation of RTX-sensitive extrafollicular (CXCR5−) CD21lowT-bet+CD11c+atBCs, and short-lived T-bet+ASCs. Together, our study provides evidence for an extrafollicular origin for humoral immunity in active INS.
Ensembling Unets, sparse representation and low dimensional visualization for rare chromosomal aberration detection in light microscopy images
Authors: Deschemps Antonin , Grégoire Eric , Martinez Juan S. , Vaurijoux Aurélie , Fernandez Pascale , Dugue Delphine , Bobyk Laure , Valente Marco , Gruel Gaëtan , Moebel Emmanuel , Benadjaoud Mohamed Amine , Kervrann Charles
Published: September 2023

Abstract

In biological dosimetry, a radiation dose is estimated using the average number of chromosomal aberration per peripheral blood lymphocytes. To achieve an adequate precision in the estimation of this average, hundreds of cells must be analyzed in 2D microscopy images. Currently, this analysis is performed manually, as conventional computer vision techniques struggle with the wide variety of shapes showcased by chromosomes. The false discovery rate of current automated detection systems is high and variable, depending on small variations in data quality (chromosome spread, illumination variations …), which makes using it in a fully automated fashion impossible. Automating chromosomal aberration is needed to reduce diagnosis time. Furthermore, an automated system can process more images, which improves confidence intervals around the estimated radiation dose. We build an object detection model to automate chromosomal aberration detection using recent advances in deep convolutional neural networks and statistical learning. We formulated the problem of rare aberration detection as a heatmap regression problem requiring the minimization of a sparsity-promoting loss to reduce the false alarm rate. Our Unet-based approach is analoguous to a one-stage object detector, and keeps the number of hyperparameters to a minimum. Finally, we demonstrate large performance improvements using an ensemble of checkpoints collected during a single run of training. A PCA-based strategy is used to provide cues for interpretation of our deep neural network-based model. The methodology is demonstrated on real, large, and challenging datasets depicting rare chromosomal aberrations and is favorably compared to a reference dosimetry technique.
Discovery of a functionally selective serotonin 5-HT1Areceptor agonist for the treatment of pain
Authors: Ullrich Annika , Schneider Johannes , Braz João M. , Neu Eduard , Staffen Nico , Stanek Markus , Bláhová Jana , Hove Tamsanqa , Albert Tamara , Allikalt Anni , Löber Stefan , Bhardwaj Karnika , Rodriguez-Rosado Sian , Fink Elissa , Rasmussen Tim , Hübner Harald , Inoue Asuka , Shoichet Brian K. , Basbaum Allan J. , Böttcher Bettina , Weikert Dorothee , Gmeiner Peter
Published: September 2023

The G protein-coupled serotonin receptor 5-HT1AR mediates antinociception and may serve as a valuable target for the treatment of pain. Starting from a chemical library, ST171, a bitopic chemotype activating 5-HT1AR was evolved.In vitropharmacological investigations of ST171 revealed potent and selective Giactivation (EC50= 0.3 nM), with marginal Gsand β-arrestin recruitment. Preclinical studies in mice showed that ST171 was effective in acute and chronic (inflammatory and neuropathic) pain models, without causing sedation. Comparison of cryo-EM structures of a 5-HT1AR-Gicomplex bound to the functionally biased agonist ST171, with a structure bound to the functionally balanced agonist befiradol, showed that both ligands bind to the same orthosteric site, but address different exo-sites. The individual poses are associated with ligand-specific helical dispositions and rearrangements of microdomains. Complementation of these studies with molecular dynamics simulations allowed us to derive structural features associated with ST171’s functional selectivity, a phenomenon that may be crucial to the discovery of more effective and safe GPCR drugs.
Guided Diffusion for molecular generation with interaction prompt
Authors: Wu Peng , Du Huabin , Yan Yingchao , Lee Tzong-Yi , Bai Chen , Wu Song
Published: September 2023

Molecular generative models have demonstrated their potential in designing molecules from scratch with high binding affinities in a pre-determined protein pocket and could be combined with traditional structural based drug design strategy. However, the generative processes of such models are random and the atomic interaction information between ligand and protein are ignored. On the other hand, the ligand has high propensity to bind with residues called hotspots. Hotspot residues contribute to the majority of the binding free energies and have been recognized as appealing targets for designed molecules. In this work, we develop an interaction prompt guided diffusion model-InterDiff to deal with the challenges. Four kinds of atomic interactions are involved in our model and represented as learnable vector embeddings. These embeddings serve as conditions for each residue to guide the molecular generative process. Comprehensive in-silico experiments evince that our model could generate molecules with desired ligand-protein interactions in a guidable way. Furthermore, we validate InterDiff on two realistic protein-based therapeutic agents. Results show that InterDiff could generate molecules with better or similar binding mode compared to known targeted drugs.
Improving the discovery of rare variants associated with alcohol problems by leveraging machine learning phenotype prediction and functional information
Authors: Ahangari Mohammad , Gentry Amanda Elswick , Hassan Mohammed F. , Nguyen Tan Hoang , Kendler Kenneth S. , Bacanu Silviu-Alin , Peterson Roseann E. , Riley Brien P. , Webb Bradley T.
Published: September 2023

Alcohol use disorder (AUD) is moderately heritable with significant social and economic impact. Genome-wide association studies (GWAS) have identified common variants associated with AUD, however, rare variant investigations have yet to achieve well-powered sample sizes. In this study, we conducted an interval-based exome-wide analysis of the Alcohol Use Disorder Identification Test Problems subscale (AUDIT-P) using both machine learning (ML) predicted risk and empirical functional weights. This research has been conducted using the UK Biobank Resource (application number 30782.) Filtering the 200k exome release to unrelated individuals of European ancestry resulted in a sample of 147,386 individuals with 51,357 observed and 96,029 unmeasured but predicted AUDIT-P for exome analysis. Sequence Kernel Association Test (SKAT/SKAT-O) was used for rare variant (Minor Allele Frequency (MAF) < 0.01) interval analyses using default and empirical weights. Empirical weights were constructed using annotations found significant by stratified LD Score Regression analysis of predicted AUDIT-P GWAS, providing prior functional weights specific to AUDIT-P. Using only samples with observed AUDIT-P yielded no significantly associated intervals. In contrast,ADH1CandTHRAgene intervals were significant (False discovery rate (FDR) <0.05) using default and empirical weights in the predicted AUDIT-P sample, with the most significant association found using predicted AUDIT-P and empirical weights in theADH1Cgene (SKAT-OPDefault= 1.06 x 10-9andPEmpiricalweight= 6.25 x 10-11). These findings provide evidence for rare variant association of theADH1Cgene with the AUDIT-P and highlight the successful leveraging of ML to increase effective sample size and prior empirical functional weights based on common variant GWAS data to refine and increase the statistical significance in underpowered phenotypes.
Uncertainty quantified discovery of chemical reaction systems via Bayesian scientific machine learning
Authors: Nieves Emily , Dandekar Raj , Rackauckas Chris
Published: September 2023

1

The recently proposed Chemical Reaction Neural Network (CRNN) discovers chemical reaction pathways from time resolved species concentration data in a deterministic manner. Since the weights and biases of a CRNN are physically interpretable, the CRNN acts as a digital twin of a classical chemical reaction network. In this study, we employ a Bayesian inference analysis coupled with neural ordinary differential equations (ODEs) on this digital twin to discover chemical reaction pathways in a probabilistic manner. This allows for estimation of the uncertainty surrounding the learned reaction network. To achieve this, we propose an algorithm which combines neural ODEs with a preconditioned stochastic gradient langevin descent (pSGLD) Bayesian framework, and ultimately performs posterior sampling on the neural network weights. We demonstrate the successful implementation of this algorithm on several reaction systems by not only recovering the chemical reaction pathways but also estimating the uncertainty in our predictions. We compare the results of the pSGLD with that of the standard SGLD and show that this optimizer more efficiently and accurately estimates the posterior of the reaction network parameters. Additionally, we demonstrate how the embedding of scientific knowledge improves extrapolation accuracy by comparing results to purely data-driven machine learning methods. Together, this provides a new framework for robust, autonomous Bayesian inference on unknown or complex chemical and biological reaction systems.
Simultaneous multimodal three-photon and optical coherence microscopy of the mouse brain in the 1700 nm optical windowin vivo
Authors: Yang Xusan , Liu Siyang , Xia Fei , Wu Meiqi , Adie Steven , Xu Chris
Published: September 2023

Multimodal microscopy combining various imaging approaches can provide complementary information about tissue in a single imaging session. Here, we demonstrate a multimodal approach combining three-photon microscopy (3PM) and spectral-domain optical coherence microscopy (SD-OCM). We show that an optical parametric chirped-pulse amplification (OPCPA) laser source, which is the standard source for three-photon fluorescence excitation and third harmonic generation (THG), can be used for simultaneous OCM, 3-photon (3P) fluorescence and THG imaging. We validated the system performance in deep mouse brainsin vivowith an OPCPA source operating at 1620 nm center wavelength. We visualized small structures such as myelinated axons, neurons, and large fiber tracts in white matter with high spatial resolution non-invasively using linear and nonlinear contrast at >1 mm depth in intact adult mouse brain. Our results showed that simultaneous OCM and 3PM at the long wavelength window can be conveniently combined for deep tissue imagingin vivo.
Tissue-specific transfer-learning enables retasking of a general comprehensive model to a specific domain
Authors: Li Qing , Perera Deshan , Chen Zhishan , Wen Wanqing , Wang Dinghao , Yan Jun , Shu Xiao-Ou , Zheng Wei , Guo Xingyi , Long Quan
Published: September 2023

Machine learning (ML) has proven successful in biological data analysis. However, may require massive training data. To allow broader use of ML in the full spectrum of biology and medicine, including sample-sparse domains, re-directing established models to specific tasks by add-on training via a moderate sample may be promising. Transfer learning (TL), a technique migrating pre-trained models to new tasks, fits in this requirement. Here, by TL, we retasked Enformer, a comprehensive model trained by massive data, tailored to breast cancers using breast-specific data. Its performance has been validated through statistical accuracy of predictions, annotation of genetic variants, and mapping of variants associated with breast cancer. By allowing the flexibility of adding dedicated training data, our TL protocol unlocks future discovery within specific domains with moderate add-on samples by standing on the shoulders of giant models.
Predicting photosynthetic pathway from anatomy using machine learning
Authors: Gilman Ian S. , Heyduk Karolina , Maya-Lastra Carlos A. , Hancock Lillian P. , Edwards Erika J.
Published: September 2023

- Plants with Crassulacean acid metabolism (CAM) have long been associated with a specialized anatomy, including succulence and thick photosynthetic tissues. Firm, quantitative boundaries between non-CAM and CAM plants have yet to be established – if they indeed exist.

- Using novel computer vision software to measure anatomy, we combined new measurements with published data across flowering plants. We then used machine learning and phylogenetic comparative methods to investigate relationships between CAM and anatomy.

- We found significant differences in photosynthetic tissue anatomy between plants with differing CAM phenotypes. Machine learning based classification was over 95% accurate in differentiating CAM from non-CAM anatomy, and had over 70% recall of distinct CAM phenotypes. Phylogenetic least squares regression and threshold analyses revealed that CAM evolution was significantly correlated with increased mesophyll cell size, thicker leaves, and decreased intercellular airspace.

- Our findings suggest that machine learning may be used to aid the discovery of new CAM species and that the evolutionary trajectory from non-CAM to strong, obligate CAM requires continual anatomical specialization.
IL-23 receptor signaling licenses group 3-like innate lymphoid cells to restrict a live-attenuated oral Chlamydia vaccine in the gut
Authors: He Ying , Wang Yihui , He Rongze , Abdelsalam Ahmed Mohamed , Zhong Guangming
Published: September 2023

An IFNγ-susceptible mutant ofChlamydia muridarumis attenuated in pathogenicity in the genital tract and recently licensed as anintracellularOral vaccinevector or intrOv. Oral delivery of intrOv induces transmucosal protection in the genital tract but intrOv itself is cleared from the gut (without shedding any infectious particles externally) by IFNγ from group 3-like innate lymphoid cells (ILC3s). We further characterized the intrOv interactions with ILC3s in the current study since the interactions may impact both the safety and efficacy of intrOv as an oral Chlamydia vaccine. Intracolonic inoculation with intrOv induced IFNγ that in return inhibited intrOv. The intrOv-IFNγ interactions were dependent on RORγt, a signature transcriptional factor of ILC3s. Consistently, transfer of oral intrOv-induced ILC3s from RORγt-GFP reporter mice to IFNγ-deficient mice rescued the inhibition of intrOv. Thus, IFNγ produced by intrOv-induced ILC3s is likely responsible for inhibiting intrOv, which is further supported by the observation that oral intrOv did induce significant levels of IFNγ-producing LC3s (IFNγ+ILC3s). Interestingly, IL-23 receptor knockout (IL-23R-/-) mice no longer inhibited intrOv, which was accompanied with reduced colonic IFNγ. Transfer of oral intrOv-induced ILC3s rescued the IL-23R-/-mice to inhibit intrOv, validating the dependence of ILC3s on IL-23R signaling for inhibiting intrOv. Clearly, intrOv induces intestinal IFNγ+ILC3s for its own inhibition in the gut, which is facilitated by IL-23R signaling. These findings have provided a mechanism for ensuring the safety of intrOv as an oral Chlamydia vaccine and a platform for investigating how oral intrOv induces transmucosal protection in the genital tract.

Significance

Despite the extensive efforts, no subunit vaccine is available for protecting humans againstC. trachomatisinfection and pathogenicity. Recent studies have led to a licensed live-attenuated oral vaccine (intrOv) that is both effective in inducing transmucosal protection in the genital tract and safe due to its susceptibility to IFNγ delivered by ILC3s. Characterization of the intrOv interactions with IFNγ-producing ILC3s in the current study has revealed a critical role of IL-23 receptor signaling in facilitating ILC3s to clear intrOv from the gut, which has provided a mechanism for ensuring the safety of intrOv and laid a foundation for further revealing the mechanisms by which oral intrOv induces transmucosal immunity in the genital tract since ILC3s can also function as antigen presenting cells.
Friday excess of overall mortality in three German subpopulations
Authors: Wackermann Jiří
Published: September 2023

We studied variations of all-cause human mortality during the weekly cycle, using deathdates collected from death notices published in regional or local newspapers in three distinct regions in Germany (South Baden, North Bavaria, Saarland), total database sizeN≈ 44000. Probability distributions of death on different days of the week show significant (P= 0.0155) departures from the uniformity hypothesis. The day of maximum mortality is Friday (probability of dying = 0.148), whereas minimum mortality is observed on Sundays and Mondays (probability of dying = 0.140 for both days). This ‘Friday excess’ effect seems to be a novel phenomenon, unrelated to other findings on weekly modulation of human mortality.
Allo: Accurate allocation of multi-mapped reads enables regulatory element analysis at repeats
Authors: Morrissey Alexis , Shi Jeffrey , James Daniela Q. , Mahony Shaun
Published: September 2023

Transposable elements (TEs) and other repetitive regions have been shown to contain gene regulatory elements, including transcription factor binding sites. Unfortunately, regulatory elements harbored by repeats have proven difficult to characterize using short-read sequencing assays such as ChIP-seq or ATAC-seq. Most regulatory genomics analysis pipelines discard “multi-mapped” reads that align equally well to multiple genomic locations. Since multi-mapped reads arise predominantly from repeats, current analysis pipelines fail to detect a substantial portion of regulatory events that occur in repetitive regions. To address this shortcoming, we developed Allo, a new approach to allocate multi-mapped reads in an efficient, accurate, and user-friendly manner. Allo combines probabilistic mapping of multi-mapped reads with a convolutional neural network that recognizes the read distribution features of potential peaks, offering enhanced accuracy in multi-mapping read assignment. Allo also provides read-level output in the form of a corrected alignment file, making it compatible with existing regulatory genomics analysis pipelines and downstream peak-finders. In a demonstration application on CTCF ChIP-seq data, we show that Allo results in the discovery of thousands of new CTCF peaks. Many of these peaks contain the expected cognate motif and/or serve as TAD boundaries. We additionally apply Allo to a diverse collection of ENCODE ChIP-seq datasets, resulting in multiple previously unidentified interactions between transcription factors and repetitive element families. Finally, we show that Allo may be particularly effective in identifying ChIP-seq peaks in younger TEs, which hold evolutionary significance due to their emergence during human evolution from primates.
Investigating structural variant, indel and single nucleotide polymorphism differentiation between locally adapted Atlantic salmon populations
Authors: Lecomte Laurie , Árnyasi Mariann , Ferchaud Anne-Laure , Kent Matthew , Lien Sigbjørn , Stenløkk Kristina , Sylvestre Florent , Mérot Claire , Bernatchez Louis
Published: September 2023

Genomic structural variants (SVs) are now recognized as an integral component of intraspecific polymorphism and are known to contribute to evolutionary processes in various organisms. However, they are inherently difficult to detect and genotype from readily available short-read sequencing data, and therefore remain poorly documented in wild populations. Salmonid species displaying strong interpopulation variability in both life history traits and habitat characteristics, such as Atlantic salmon (Salmo salar), offer a prime context for studying adaptive polymorphism, but the contribution of SVs to fine-scale local adaptation has yet to be explored. Here, we performed a comparative analysis of SVs, single nucleotide polymorphisms (SNPs) and small indels (< 50 bp) segregating in the Romaine and Puyjalon salmon, two putatively locally adapted populations inhabiting neighboring rivers (Québec, Canada) and showing pronounced variation in life history traits, namely growth, fecundity, and age at maturity and at smoltification. We first catalogued polymorphism using a hybrid SV characterization approach pairing both short (16X) and long-read sequencing (20X) for variant discovery with graph-based genotyping of SVs across 60 salmon genomes, along with characterization of SNPs and small indels from short reads. We thus identified 115,907 SVs, 8,777,832 SNPs and 1,089,321 short indels, with SVs covering 4.8 times more base pairs than SNPs. All three variant types revealed a highly congruent population structure and similar patterns ofFSTand density variation along the genome. Finally, we performed outlier detection and redundancy analysis (RDA) to identify variants of interest in the putative local adaptation of Romaine and Puyjalon salmon. Genes located near these variants were enriched for biological processes related to nervous system function, suggesting that observed variation in traits such as age at smoltification could arise from differences in neural development. This study therefore demonstrates the feasibility of large-scale SV characterization and highlights its relevance for salmonid population genomics.
Unpacking Unstructured Data: A Pilot Study on Extracting Insights from Neuropathological Reports of Parkinson’s Disease Patients using Large Language Models
Authors: Stroganov Oleg , Schedlbauer Amber , Lorenzen Emily , Kadhim Alex , Lobanova Anna , Lewis David A. , Glausier Jill R.
Published: September 2023

Objective

The aim of this study was to make unstructured neuropathological data, located in the NeuroBioBank (NBB), follow FAIR principles, and investigate the potential of Large Language Models (LLMs) in wrangling unstructured neuropathological reports. By making the currently inconsistent and disparate data findable, our overarching goal was to enhance research output and speed.

Materials and Methods

The NBB catalog currently includes information from medical records, interview results, and neuropathological reports. These reports contain crucial information necessary for conducting in-depth analysis of NBB data but have multiple formats that vary across different NBB biorepositories and change over time. In this study we focused on a subset of 822 donors with Parkinson’s disease (PD) from 7 NBB biorepositories. We developed a data model with combined Brain Region and Pathological Findings data at its core. This approach made it easier to build an extraction pipeline and was flexible enough to convert resulting data to Common Data Elements (CDEs), a standardized data collection tools used by the neuroscience community to improve consistency and facilitate data sharing across studies.

Results

This pilot study demonstrated the potential of LLMs in structuring unstructured neuropathological reports of PD patients available in the NBB. The pipeline enabled successful extraction of detailed tissue-level (microscopic) and gross anatomical (macroscopic) observations, along with staging information from pathology reports, with extraction quality comparable to manual curation results. To our knowledge, this is the first attempt to automatically standardize neuropathological information at this scale. The collected data has the potential to serve as a valuable resource for PD researchers, facilitating integration with clinical information and genetic data (such as genome-wide genotyping and whole genome sequencing) available through the NBB, hereby enabling a more comprehensive understanding of the disease.
OBIA: An Open Biomedical Imaging Archive
Authors: Jin Enhui , Zhao Dongli , Wu Gangao , Zhu Junwei , Wang Zhonghuang , Wei Zhiyao , Zhang Sisi , Wang Anke , Tang Bixia , Chen Xu , Sun Yanling , Zhang Zhe , Zhao Wenming , Meng Yuanguang
Published: September 2023

With the development of artificial intelligence (AI) technologies, biomedical imaging data play an important role in scientific research and clinical application, but the available resources are limited. Here we present Open Biomedical Imaging Archive (OBIA), a repository for archiving biomedical imaging and related clinical data. OBIA adopts five data objects (Collection, Individual, Study, Series, and Image) for data organization, accepts the submission of biomedical images of multiple modalities, organs, and diseases. In order to protect personal privacy, OBIA has formulated a unified de-identification and quality control process. In addition, OBIA provides friendly and intuitive web interface for data submission, browsing and retrieval, as well as image retrieval. As of September 2023, OBIA has housed data for a total of 937 individuals, 4136 studies, 24,701 series, and 1,938,309 images covering 9 modalities and 30 anatomical sites. Collectively, OBIA provides a reliable platform for biomedical imaging data management and offers free open access to all publicly available data to support research activities throughout the world. OBIA can be accessed athttps://ngdc.cncb.ac.cn/obia.
Resilience assessment in complex natural systems
Authors: Sguotti Camilla , Vasilakopoulos Paraskevas , Tzanatos Evangelos , Frelat Romain
Published: September 2023

Ecological resilience is the capability of an ecosystem to maintain the same structure and function and to avoid crossing catastrophic tipping points. While fundamental for management, concrete ways to estimate and interpret resilience in real ecosystems are still lacking. Here, we develop an empirical approach to estimate resilience based on the stochasticcuspmodel derived from catastrophe theory. OurCusp Resilience Assessment(CUSPRA) has three characteristics: i) it provides estimates on how likely a system is to cross a tipping point characterized by hysteresis, ii) it assesses resilience in relation to multiple external drivers, and iii) it produces straightforward results for ecosystem-based management. We validated our approach using simulated data and demonstrated its application using empirical time-series of an Atlantic cod population and of marine ecosystems in the North and the Mediterranean Sea. We show that CUSPRA provides a powerful method to empirically estimate resilience in support of a sustainable management of our constantly adapting ecosystems under global climate change.
Cancer-associated Fibroblast Spatial Heterogeneity andEMILIN1Expression in Cancer Stroma Modulate TGF-β Activity and CD8+T-Cell Infiltration in Breast Cancer
Authors: Honda Chikako , Kurozumi Sasagu , Fujii Takaaki , Pourquier Didier , Khellaf Lakhdar , Boissiere Florence , Horiguchi Jun , Oyama Tetsunari , Shirabe Ken , Colinge Jacques , Yokobori Takehiko , Turtoi Andrei
Published: September 2023

The tumor microenvironment (TME) and its multifaceted interactions with cancer cells are major targets for cancer treatment. Single-cell technologies have brought major insights into the TME, but the resulting complexity frequently precludes conclusions on function. Therefore, we combined single-cell RNA sequencing and spatial transcriptomic data to explore the relationship between different cancer-associated fibroblast (CAF) populations and immune cell exclusion in breast tumors. Our data show for the first time the degree of spatial organization of different CAF populations in breast cancer. We found that IL-iCAFs, Detox-iCAFs, and IFNγ-iCAFs tended to cluster together, while Wound-myCAFs, TGFβ-myCAFs, and ECM-myCAFs formed another group that overlapped with elevated TGF-β signaling. Differential gene expression analysis of areas with CD8+T-cell infiltration/exclusion within the TGF-β signaling-rich zones identified elastin microfibrillar interface protein 1 (EMILIN1) as a top modulated gene.EMILIN1, a TGF-β inhibitor, was upregulated in IFNγ-iCAFs directly modulating TGFβ immunosuppressive function. Histological analysis of 74 breast cancer samples confirmed that high EMILIN-1 expression in the tumor margins was related to high CD8+T-cell infiltration, consistent with our spatial gene expression analysis. High EMILIN-1 expression was also associated with better prognosis of patients with breast cancer, underscoring its functional significance for the recruitment of cytotoxic T cells into the tumor area. In conclusion, our data show that correlating TGF-β signaling to a CAF subpopulation is not enough because proteins with TGF-β-modulating activity originating from other CAF subpopulations can alter its activity. Therefore, therapeutic targeting should remain focused on biological processes rather than on specific CAF subtypes.
Enkephalin-mediated modulation of basal somatic sensitivity by regulatory T cells in mice
Authors: Aubert Nicolas , Purcarea Madeleine , Novarino Julien , Schopp Julien , Audibert Alexis , Li Wangtianrui , Fornier Marie , Cagnet Léonie , Naturel Marie , Casrouge Armanda , Dieu-Nosjean Marie-Caroline , Blanchard Nicolas , Dietrich Gilles , Peirs Cedric , Marodon Gilles
Published: September 2023

CD4+CD25+Foxp3+regulatory T cells (Treg) have been implicated in pain modulation in various inflammatory conditions. However, whether Treg cells hamper pain at steady state and by which mechanism is still unclear. From a meta-analysis of the transcriptomes of murine Treg and conventional T cells (Tconv), we observe that the proenkephalin gene (Penk), encoding the precursor of analgesic opioid peptides, ranks among the top 25 genes most enriched in Treg cells. We then present various evidence suggesting thatPenkis regulated in part by members of the TNF receptor family and the transcription factor Batf. Using mice in which the promoter activity ofPenkcan be tracked with a fluorescent reporter, we also show thatPenkexpression is mostly detected in Treg and activated Tconv in non-inflammatory conditions in the colon and skin. Functionally, Treg cells proficient or deficient forPenksuppress equally well the proliferation of effector T cellsin vitroand autoimmune colitisin vivo. In contrast, inducible ablation ofPenkin Treg leads to heat hyperalgesia in both male and female mice. Overall, our results indicate that Treg might play a key role at modulating basal somatic sensitivity in mice through the production of analgesic opioid peptides.
Non fire-adapted dry forest of Northwestern Madagascar: escalating and devastating trends revealed by remote-sensing data
Authors: Percival Joseph Emile Honour , Sato Hiroki , Razanaparany Tojotanjona Patrick , Harilalao Ando Rakotomamonjy , Razafiarison Zo Lalaina , Kitajima Kaoru
Published: September 2023

Ankarafantsika National Park (ANP), the last significant remnant of Northwestern Madagascar’s tropical dry forests, is facing rapid degradation due to increased incidences of fire. This poses severe threats to biodiversity, local livelihoods, and vital ecosystem services. Our study, conducted on 3052 ha of ANP’s pristine forests, employed advanced remote-sensing techniques to assess fire impacts during the past 37 years. Our aims were to understand historical fire patterns and evaluate forest recovery and susceptibility to repeated fires following initial burns. Using data from multiple Landsat satellite sensors, we constructed a time series of fire events since 1985, which revealed no fire activity before 2014. The Global Ecosystem Dynamics Investigation (GEDI) lidar sensor data were used to observe forest structure in both post-fire areas and undisturbed zones for comparison. We recorded six fire incidents from 2014-2021, during which the fire-affected area exponentially grew. A significant fire incident in October 2021 impacted 1052 hectares, 59% of which had experienced at least one fire in 2-4 years prior, with 60% experiencing 2 preceding incidents: one in 2017 and another in 2019. The initial fire drastically reduced plant cover and tree height, with subsequent fires causing minor additional loss. Post-fire recovery was negligible within the initial four years, even in patches without recurrent fires. The likelihood for an initial burn to trigger subsequent fires within a few years was high, leading to larger, more severe fires. We conclude that ANP’s dry forests exhibit high vulnerability and low resilience to anthropogenic fires. Prompt preventive measures are essential to halt further fire spread and conserve the park’s unique and invaluable biodiversity.
Engineering an artificial catch bond using mechanical anisotropy
Authors: Liu Zhaowei , Liu Haipei , Vera Andrés M. , Yang Byeongseon , Tinnefeld Philip , Nash Michael A.
Published: September 2023

Catch bonds are a rare class of protein-protein interactions where the bond lifetime increases under an external pulling force. Here, we report how modification of anchor geometry generates catch bonding behavior for the mechanostable Dockerin G:Cohesin E (DocG:CohE) adhesion complex found on human gut bacteria. Using AFM single-molecule force spectroscopy in combination with bioorthogonal click chemistry, we mechanically dissociated the complex using five precisely controlled anchor geometries. When tension was applied through residue #13 on CohE and the N-terminus of DocG, the complex behaved as a two-state catch bond, while in all other tested pulling geometries, including the native configuration, it behaved as a slip bond. We used a kinetic Monte Carlo model with experimentally derived parameters to simulate rupture force and lifetime distributions, achieving strong agreement with experiments. Single-molecule FRET measurements further demonstrated that the complex does not exhibit dual binding mode behavior at equilibrium but unbinds along multiple pathways under force. Together, these results show how mechanical anisotropy and anchor point selection can be used to engineer artificial catch bonds.
Rampant Reticulation in a Rapid Radiation of Tropical Trees - Insights fromInga(Fabaceae)
Authors: Schley Rowan J. , Piñeiro Rosalía , Nicholls James A. , Pezzini Flávia Fonseca , Kidner Catherine , Farbos Audrey , Ringelberg Jens J. , Twyford Alex D. , Dexter Kyle G. , Pennington R. Toby
Published: September 2023

Evolutionary radiations underlie much of the species diversity of life on Earth, particularly within the world’s most species-rich tree flora – that of the Amazon rainforest. Hybridisation occurs in many radiations, with effects ranging from homogenisation of species to generation of genetic and phenotypic novelty that fuels speciation, but the influence of hybridisation on Amazonian tree radiations has been little studied. We address this using the ubiquitous, species-rich, neotropical tree genusInga, which typifies rapid radiations of rainforest trees. We assess patterns of gene tree incongruence to ascertain whether hybridisation was associated with rapid radiation inInga.Given the importance of insect herbivory in structuring rainforest tree communities (and hence the potential for hybridisation to promote adaptation through admixture of defence traits), we also test whether introgression of loci underlying chemical defences against herbivory occurred during the radiation ofInga.Our phylogenomic analyses of 189/288Ingaspecies using >1300 target capture loci showed widespread introgression inInga. Specifically, we found widespread phylogenetic incongruence explained by introgression, with phylogenetic networks recovering multiple introgression events acrossIngaand up to 20% of shared, likely introgressed, genetic variation between some species. In addition, most defence chemistry loci showed evidence of positive selection and marginally higher levels of introgression. Overall, our results suggest that introgression has occurred widely over the course ofInga’shistory, likely facilitated by extensive dispersal across Amazonia, and that in some cases introgression of chemical defence loci may influence adaptation inInga.
Syntrichia ruralis: Emerging model moss genome reveals a conserved and previously unknown regulator of desiccation in flowering plants
Authors: Zhang Xiaodan , Ekwealor Jenna T. B. , Silva Anderson T. , Yu Li’ang , Jones Andrea K. , Mishler Brent D. , Nelson Andrew D. L. , Oliver Melvin J.
Published: September 2023

Water scarcity poses a significant threat to ecosystems in the face of global climate change.Syntrichia ruralis, a dryland moss known for its desiccation tolerance, provides valuable insights into surviving water-limited conditions. In this study, the genome ofS. ruraliswas sequenced and assembled into 12 chromosomes encompassing 21,169 protein-coding genes. Additionally, 3,199 unplaced scaffolds were identified as non-nuclear and symbiont DNA. Transposable elements (TEs) constitute 51.24% of the genome. Notably, chromosome 12, the largest in size due to its high TE load, was identified as the putative sex chromosome. Comparative analysis with the closely relatedSyntrichia caninervisgenome reveals significant large-scale synteny yet some rearrangements, as well as the occurrence of older duplication events that are shared by both. Desiccation and drought tolerance associated gene families, such as early light-inducible proteins (ELIPs) and late embryogenesis abundant (LEA) proteins, were characterized. In addition to a subset of LEA genes being species-specific, a comparative transcriptomic analysis revealed that some shared LEA genes respond differently to dehydration in these two species. Many ELIPs (9 out of 30) are the product of tandem duplication events. As expected, our analyses revealed the importance of the phytohormone abscisic acid (ABA) in the desiccation response ofS. ruralis. A significant number of ABA responsive genes were found to be regulated byS. ruralisorthologs of ABA insensitive 3 (ABI3) and abscisic acid responsive element binding factor 2 (AREB2). Markedly, an uncharacterized, but deeply conserved MYB transcription factor, appears to act as a negative regulator of AREB2 inS. ruralis. Interestingly, we determined that the orthologous MYB TF is also involved in an ABA-dependent stress response in the model flowering plantA. thaliana. In sum, the new genomic resources from this emerging model moss offer new insights into the evolution of desiccation tolerance in land plants.
Nanopore translocation reveals electrophoretic force on non-canonical RNA:DNA double helix
Authors: Bošković Filip , Maffeo Christopher , Patiño-Guillén Gerardo , Tivony Ran , Aksimentiev Aleksei , Keyser Ulrich F.
Published: September 2023

Electrophoretic transport plays a pivotal role in advancing sensing technologies. So far, systematic studies have focused on translocation of canonical B-form or A-form nucleic acids, while direct RNA analysis is emerging as the new frontier for nanopore sensing and sequencing. Here, we compare the less-explored dynamics of non-canonical RNA:DNA hybrids in electrophoretic transport with the well-researched transport of B-form DNA. Using DNA/RNA nanotechnology and solid-state nanopores, the translocation of RNA:DNA (RD) and DNA:DNA (DD) duplexes was examined. Notably, RD duplexes were found to translocate through nanopores faster than DD duplexes, despite containing the same number of base pairs. Our experiments reveal that RD duplexes present a non-canonical helix with distinct transport properties from B-form DD molecules. We find RD and DD molecules with the same contour length move with comparable velocity through nanopores. We examined the physical characteristics of both duplex forms using atomic force microscopy, atomistic molecular dynamics simulations, agarose gel electrophoresis, and dynamic light scattering measurements. With the help of coarse-grained and molecular dynamics simulations, we find the effective force per unit length applied by the electric field to a fragment of RD or DD duplex in nanopores with various geometries or shapes to be approximately the same within experimental errors. Our results shed light on the significance of helical form in nucleic acid translocation, with implications for RNA sensing, sequencing, and molecular understanding of electrophoretic transport.
Approaches to Species Distribution Modelling in Dinosaurs and Other Fossil Organisms
Authors: Stockdale Maximilian T.
Published: September 2023

SDM describes a family of methods aiming to predict the geographic distribution of organisms using environmental data such as climate variables. It is a versatile tool in estimating ecological communities and interactions both spatially and through time. However, it has had limited utility in predicting the geographic distribution of fossil organisms. Due to preservation and sampling biases, fossil data does not satisfy the assumptions of species distribution models. Here is presented an analysis proposing a new methodology, which substitutes the conventional pseudoabsence data for fossil occurrences from non-target species. This approach eliminates variation in preservation and sampling, and returns a SDM which performs better than a conventional example. This model concludes that the ceratopsian Triceratops may have been widespread across North America, and beyond the region where its fossils have been recovered. The geographic distribution of Triceratops appears to have been governed by seasonality in temperature and temperature of the coldest month.
Simple, reference-independent analyses help optimize hybrid assembly of microbial community metagenomes
Authors: Smith Garrett J. , van Alen Theo , van Kessel Maartje , Lücker Sebastian
Published: September 2023

Hybrid metagenomic assembly, leveraging both long- and short-read sequencing technologies, of microbial communities is becoming an increasingly accessible approach, yet its widespread application faces several challenges. High-quality references may not be available for assembly accuracy comparisons common for benchmarking, and certain aspects of hybrid assembly may require dataset-dependent, empirically-guided optimization rather than application of a uniform approach. In this study, several simple, reference-free characteristics – gene lengths and read recruitment – were analyzed as reliable proxies of assembly quality to guide hybrid assembly optimization. These characteristics were further explored in relation to reference-dependent genome- and gene-centric analyses that are common for microbial community metagenomic studies. Here, two laboratory-scale bioreactors were sequenced with short and long read platforms, and assembled with commonly used software packages. Following long read assembly, long read correction and short read polishing were iterated to resolve errors. Each iteration in this process was shown so have a substantial effect on gene- and genome-centric community composition. Simple, reference-free assembly characteristics, specifically changes in gene fragmentation and short read recruitment, explored throughout this process replicated patterns of more advanced analyses seen in published comparative studies, and therefore are suitable proxies for hybrid metagenome assembly accuracy to save computational resources. Hybrid metagenomic sequencing approaches will likely remain relevant due to the low costs of short read sequencing, therefore it is imperative that users are equipped to estimate assembly accuracy prior to downstream gene- and genome-centric analyses.