bluuebunny/crossref_metadata_2025_split huggingface dataset:
Global picoplankton biogeography revealed by metagenomic and climatic data integration
Authors: Salazar Vinícius W. , Verbruggen Heroen , Marcelino Vanessa Rossetto , Cao Kim-Anh Lê 
Published: November 2024

AbstractMicrobial plankton play fundamental roles in biogeochemical cycles, driving nutrient cycling that influences the global climate and supports life on Earth. Picoplankton are the smallest and most abundant planktonic organisms. The distribution and ecology of these organisms is determined by environmental factors and their biogeography is largely shaped by basin-scale patterns of physicochemical composition of ocean waters. The increased availability of high-throughput sequencing data of microbial communities has enabled the description of how the global oceans are partitioned into distinct microbial biogeographical provinces. However, the key attributes associated with such provinces are still unclear. Here we present a model of picoplankton biogeography based on 1454 metagenomes from multiple sampling consortia, resulting in the largest integrated surface ocean metagenome analysis to date. We identify ten distinct groups based on metagenomic dissimilarity, divided into three categories: polar (Arctic and Antarctic), temperate (coastal temperate, temperate/subtropical transition, oceanic temperate, Mediterranean-like) and tropical (tropical low nutrient, tropical high nutrient, subtropical oceanic gyres). Using machine learning and omics data integration techniques, we predict province areas across the surface oceans and describe their environmental, taxonomical, and functional features. We quantify the relationship between environmental factors and each biogeographical province, identify their main representative taxa and the importance of carbon degradation and antimicrobial resistance pathways in functional community composition, and discuss implications for establishing a model for global picoplankton biogeography.
ON-OFF nanopores for optical control of transmembrane ionic communication
Authors: Wang Xingzao , Kerckhoffs Aidan , Riexinger Jorin , Cornall Matthew , Langton Matthew J. , Bayley Hagan , Qing Yujia 
Published: November 2024

[Abstract]Nanoscale photoswitchable proteins could facilitate precise spatiotemporal control of transmembrane communication and support studies in synthetic biology, neuroscience, and bioelectronics. Through covalent modification of the α-hemolysin protein pore with arylazopyrazole photoswitches, we have produced “photopores” that transition between iontronic resistor and diode modes in response to irradiation at orthogonal wavelengths. In the diode mode, a low-leak OFF-state nanopore exhibits a reversible increase in unitary conductance of more than 20-fold upon irradiation at 365 nm. A rectification ratio of >5 was achieved with photopores in the diode state by either direct or alternating voltage input. Unlike conventional electronic phototransistors with intensity-dependent photoelectric responses, the photopores regulated current output solely based on the wavelength(s) of monochromatic or dual-wavelength irradiation. Dual-wavelength irradiation at various relative intensities allowed graded adjustment of photopore conductance. By using these properties, photonic signals were converted into ionic signals, highlighting the potential applications of photopores as components of smart devices in synthetic biology.
In-silicomodeling and interpretation of RBP binding disentangle m6A-RBP interaction
Authors: Liu Jianche , Zhu Xinlu , Yin Yang , Xu Zhoutong , He Jialin , Xiong Xushen 
Published: November 2024

AbstractRNA binding protein (RBP) binding andN6-methyladenosine (m6A) are both essential post-transcriptional regulatory layers for RNA fate decisions. However, the intricate mechanism underlying the interaction between m6A and RBP binding remains underexplored. Here, we develop TransRBP, an interpretable deep learning framework, to model the base-resolution binding of RBPs from RNA sequences and to subsequently investigate the interaction between m6A and RBPs. TransRBP achieves a median accuracy of 0.59 across 32 m6A-related RBPs, representing a 28% increase over the state-of-the-art model. Using gradient-based interpretation, we demonstrate that the binding motifs of the m6A-related RBPs strongly enrich for splicing consensus, laying a foundation for studying the RBP-dependent crosstalk between m6A and splicing. Moreover, we develop anin-silicomutagenesis assay to assess the impact of m6A on RBPs, and utilize the self-attention mechanism to elucidate the interplay between RBP binding and m6A. We further uncover 1,806 variant-RBP combinations with thein-silicomutagenesis, revealing variants that strongly alter RBP binding for genetic diseases including Parkinson’s disease, autism, and cardiomyopathy. In particular, we identify m6Acis-acting variants that alter RBP binding in an m6A-proximal manner, including the binding of UPF1 that contributes to Alzheimer’s disease, and the DDX3X binding to cardiomyopathy and muscular dystrophy. Together, TransRBP accurately models the binding of RBP and its interaction with m6A, shedding light on the m6A-RBP dynamics and providing multi-layer mechanistic insights for genetic diseases.
Cacao genome sequence reveals insights into the flavonoid biosynthesis
Authors: Marin Recinos Maria Fernanda , Winnier Sarah , Lagerhausen Kiersten , Ajayi Blessing , Wolff Katharina , Friedhoff Ronja , Dassow Chiara Marie , Choudhary Nancy , Pucker Boas 
Published: November 2024

AbstractTheobroma cacaois well known for its role in producing cacao. Many different cacao varieties are cultivated in equatorial regions, each distinguished by unique phenotypic traits. An instance of this is the pod color variation, which has been linked to differences in anthocyanin content. Anthocyanins are produced by one branch of the flavonoid biosynthesis. The highly continuous genome sequence and comprehensive gene set generated in this study enabled an investigation of the genetic basis of the flavonoid biosynthesis. Expression differences between paralogs in the proanthocyanidin biosynthesis suggest subfunctionalization. In pod husks, one copy of the leucoanthocyanidin reductase gene (LAR) displayed substantially higher expression than the other copy.
Evaluating the predictive power of combined gene expression dynamics from single cells on antibiotic survival
Authors: Alnahhas Razan N. , Andreani Virgile , Dunlop Mary J. 
Published: November 2024

AbstractHeteroresistance can allow otherwise drug-susceptible bacteria to survive and resume growth after antibiotic exposure. This temporary form of antibiotic tolerance can be caused by the upregulation of stress response genes or a decrease in cell growth rate. However, it is not clear how expression of multiple genes contributes to the tolerance phenotype. By using fluorescent reporters for stress related genes, we conducted real time measurements of expression prior to, during, and after antibiotic exposure. We first identified relationships between growth rate and reporter levels based on auto and cross correlation analysis, revealing consistent patterns where changes in growth rate were anticorrelated with fluorescence following a delay. We then used pairs of stress gene reporters and time lapse fluorescence microcopy to measure the growth rate and reporter levels in cells that survived or died following antibiotic exposure. Using these data, we asked whether combined information about reporter expression and growth rate could improve our ability to predict whether a cell would survive or die following antibiotic exposure. We developed a Bayesian inference model to predict how the combination of dual reporter expression levels and growth rate impact ciprofloxacin survival inEscherichia coli. We found clear evidence of the impact of growth rate and thegadXpromoter activity on survival. Unexpectedly, our results also revealed examples where additional information from multiple genes decreased prediction accuracy, highlighting an important and underappreciated effect that can occur when integrating data from multiple simultaneous measurements.
Tertiary lymphoid structure as a therapeutic target of Crohn’s disease: modulation by TNFα blockade
Authors: Nagase Yoshihiro , Okano Soh , Furukawa Asuka , Kanazawa Takumi , Yamamoto Kouhei , Yamamoto Kurara , Ohashi Kenichi , Yamana Tetsuo , Nojiri Shuko , Suzuki Yutaka , Kanai Akinori , Yao Takashi , Abe Keiko , Ohteki Toshiaki , Kodama Makoto 
Published: November 2024

ABSTRACTInflammatory diseases, such as Crohn’s disease (CD), are primarily treated with therapies aimed at alleviating inflammation. Notably, biological agents like TNFα inhibitors have transformed the management of these conditions. Previous research has indicated that TNFα inhibitors affect the cells in the lamina propria. However, this study demonstrates that infliximab, a type of TNFα inhibitor, reduces the presence of tertiary lymphoid structures (TLS) and alleviates inflammation of CD by targeting follicular dendritic cells and macrophages within these structures. TLS could also be a potential target for various biological agents used to treat inflammatory diseases beyond CD. Furthermore, our study suggests that the status of TLS may serve as a predictor for the response to TNFα inhibitor treatment. Our research could pave the way for new treatment strategies and the advancement of personalized medicine for inflammatory diseases.
Cell-specific oxidative metabolism of the renal cortex
Authors: Feola Kyle , Venable Andrea H. , Broomfield Tatyana , Llamas Claire B. , Mishra Prashant , Huen Sarah C. 
Published: November 2024

AbstractThe metabolic health of the kidney is a primary determinant of the risk of progressive kidney disease. Our understanding of the metabolic processes that fuel kidney functions is limited by the kidney’s structural and functional heterogeneity. As the kidney contains many different cell types, we hypothesize that intra-renal mitochondrial heterogeneity contributes to cell-specific metabolism. To interrogate this, we utilized a recently developed mitochondrial tagging technique to isolate kidney cell-type specific mitochondria. Here, we investigate mitochondrial functional capacities and the metabolomes of the early and late proximal tubule (PT) and the distal convoluted tubule (DCT). The conditional MITO-Tag allele was combined withSlc34a1-CreERT2,Ggt1-Cre, orPvalb-Crealleles to generate mouse models capable of cell-specific isolation of hemagglutinin (HA)-tagged mitochondria from the early PT, late PT, or the DCT, respectively. Functional assays measuring mitochondrial respiratory and fatty acid oxidation (FAO) capacities and metabolomics were performed on anti-HA immunoprecipitated mitochondria from kidneys of ad libitum fed and 24-hour fasted male mice. The renal MITO-Tag models targeting the early PT, late PT, and DCT revealed differential mitochondrial respiratory and FAO capacities which dynamically changed during fasting conditions. Changes with mitochondrial metabolomes induced by fasting suggest that the late PT significantly increases FAO during fasting. The renal MITO-Tag model captured differential mitochondrial metabolism and functional capacities across the early PT, late PT, and DCT at baseline and in response to fasting.Translational StatementWhile the renal cortex is often considered a single metabolic compartment, we discovered significant diversity of mitochondrial metabolomes and functional capacities across the proximal tubule and the distal convoluted tubule. As mitochondrial dysfunction is a major biochemical pathway related to kidney disease progression, understanding the differences in mitochondrial metabolism across distinct kidney cell populations is thus critical in the development of effective and targeted therapeutic therapies for acute and chronic kidney disease.
Combined inhibition of S100A4 and TIGIT suppresses late-stage breast cancer metastasis to the lung by activating T and NK cells
Authors: Leu Jia-Shiun , Deng Hui , Tran Han Nhat , Wei Xiong , Hashiomoto Chihiro , Leonard Fransisca , Wong Thomas , Abdelfattah Nourhan , Benítez Salazar José M , Kang Reece , Maldonado Jose A , Cristobal Carlo D. , Lee Hyun Kyoung , An Zhiqiang , Zhang Ningyan , Yun Kyuson 
Published: November 2024

AbstractCancer metastasis is responsible for approximately 90% of cancer-related deaths, but very few treatment options exist currently. While the role of S100A4 in promoting metastasis has been known for decades, this knowledge has not been translated in the clinic. Here, we report that a novel monoclonal antibody against the human S100A4 protein (S1004-11) effectively suppresses breast cancer metastasis in two different mouse models. Importantly, a novel combination of ant-TIGIT and S100A4-11 can suppress lung metastases even in late-stage disease after the lung premetastatic niche (PMN) has already been established similar to a stage when many breast cancer patients are diagnosed. Mechanistically, S1004-11 mAb treatment block the formation of PMN by suppressing neutrophil infiltration and activating natural killer (NK) and T cells in the lung. Single-cell RNA-sequencing and cell:cell communication analyses indicate that TIGIT signaling suppresses NK cells, which is reversed in S100A4-11 treated PMN. In summary, this study provides compelling evidence for a novel mechanism of S100A4 function in PMN formation and the feasibility of using S100A4-11 monoclonal antibody to suppress metastases at different stages of breast cancer progression.
Adipose-derived Mesenchymal Stem Cells and Retinal Pigment Epithelial Cells Interactions in Stress Environment via Tunneling Nanotubes
Authors: Gozel Merve , Senkoylu Karya , Kesim Cem , Hasanreisoglu Murat 
Published: November 2024

AbstractThis study aims to demonstrate the formation of TNTs between AdMSCs and RPE-1 and their alterations in response to experimental stress conditions. Serum starvation was employed as a stress condition to induce TNTs between the AdMSC and RPE-1. The presence of TNTs was demonstrated through immunofluorescence microscopy while scanning electron microscopy was utilized to determine the average thickness. Cell viabilities were assessed after stress by CTG, and H2DCFH-DA probes evaluated the cells’ reactive oxygen species (ROS) levels. Further, JC-1 labeled mitochondrial exchange between cells via TNTs was supported by videos. A transmembrane culture system was employed to inhibit TNT formation. In this study, we investigated the role of TNTs in facilitating intercellular communication and mitochondrial transfer between AdMSCs and RPE-1 under stress. We found that TNT-mediated mitochondrial transfer from AdMSCs to RPE-1 helps to reduce ROS levels and improve cell viability. We demonstrated that direct interaction between AdMSCs and RPE-1 was crucial for stress recovery. Co-culture enhanced viability and sustained retinal epithelial cell function after stress-induced damage. Mechanical inhibition of TNT formation decreased cell viability and increased ROS levels, indicating the importance of TNTs in cellular protection. The findings can provide a new perspective on the therapeutic potential of stem cell-based therapy in protecting RPE against stress-induced damage and promoting tissue regeneration.
The effectiveness of Large Language Models with RAG for auto-annotating phenotype descriptions
Authors: Kainer David 
Published: November 2024

AbstractOntologies are highly prevalent in biology and medicine and are always evolving. Annotating biological text, such as observed phenotype descriptions, with ontology terms is a challenging and tedious task. The process of annotation requires a contextual understanding of the input text and of the ontological terms available. While text-mining tools are available to assist they are largely based on directly matching words and phrases and so lack understanding of the meaning of the query item and of the ontology term labels. Large Language Models (LLMs), however, excel at tasks that require semantic understanding of input text and therefore may provide an improvement for the auto-annotation of text with ontological terms. Here we describe a series of workflows incorporating OpenAI GPT’s capabilities to annotateArabidopsis thalianaand forest tree phenotypic observations with ontology terms, aiming for results that resemble manually curated annotations. These workflows make use of an LLM to intelligently parse phenotypes into short concepts, followed by finding appropriate ontology terms via embedding vector similarity or via Retrieval-Augmented Generation (RAG). The RAG model is a state-of-the-art approach that augments conversational prompts to the LLM with context-specific data to empower it beyond its pre-trained parameter space. We show that the RAG produces the most accurate automated annotations that are often highly similar or identical to expert-curated annotations.Short descriptionLarge Language Models excel at tasks that require semantic understanding of text. Here we use that capability to auto-annotate plant phenotypes with ontological terms and compare to expert annotation.
High-fidelityin vitropackaging of diverse synthetic cargo into encapsulin protein cages
Authors: Szyszka Taylor N. , Siddiquee Rezwan , Loustau Alex , Adamson Lachlan S. R. , Rennie Claire , Huang Tiancheng , Young Reginald , Care Andrew , Lau Yu Heng 
Published: November 2024

AbstractCargo-filled protein cages are powerful tools in biotechnology with demonstrated potential as catalytic nanoreactors and vehicles for targeted drug delivery. While endogenous biomolecules can be packaged into protein cages during their expression and self-assembly inside cells, synthetic cargo molecules are typically incompatible with live cells and must be packagedin vitro. Here we report a fusion-basedin vitroassembly method for packaging diverse synthetic cargo into encapsulin protein cages that outperforms standardin celluloassembly, producing cages with superior uniformity and thermal stability. Fluorescent dyes, proteins and cytotoxic drug molecules can all be selectively packaged with high efficiencyviaa peptide-mediated targeting process. The exceptional fidelity and broad compatibility of ourin vitroassembly platform enables generalisable access to cargo-filled protein cages that host novel synthetic functionality for diverse biotechnological applications.
The Virtual Brain links transcranial magnetic stimulation evoked potentials and inhibitory neurotransmitter changes in major depressive disorder
Authors: Hofsähs Timo , Pille Marius , Kern Lucas , Negi Anuja , Meier Jil Mona , Ritter Petra 
Published: November 2024

AbstractBackgroundTranscranial magnetic stimulation evoked potentials (TEPs) show promise as a biomarker in major depressive disorder (MDD), but the origin of the increased TEP amplitude in these patients remains unclear. Gamma aminobutyric acid (GABA) may be involved, as TEP peak amplitude is known to increase with GABAergic activity, but paradoxically MDD patients exhibit reduced GABA levels. We employed a computational modeling approach to investigate this contradiction.MethodsWhole-brain simulations in ‘The Virtual Brain’ (thevirtualbrain.org), employing the Jansen and Rit neural mass model, were optimized to simulate TEPs of healthy individuals (Nsubs=20, 14 females, 24.5±4.9 years). To mimic MDD, a GABAergic deficit was introduced to the simulations by altering one of two selected inhibitory parameters, the inhibitory synaptic time constantbor the number of inhibitory synapsesC4. The TEP amplitude was quantified and compared for all simulations.ResultsBoth parameters, the inhibitory synaptic time constant (r=-0.6, p<0.001) and the number of inhibitory synapses (r=-0.79, p<0.001), showed a significant negative linear correlation to the TEP amplitude. Thus, under local parameter changes, we were able to alter the TEP amplitude towards pathological levels, i.e. creating an MDD-like increase of the global mean field amplitude in line with empirical results.ConclusionsOur model suggests specific GABAergic deficits as the cause of increased TEP amplitude in MDD patients, which may serve as therapeutic targets. This work highlights the potential of whole-brain simulations in the investigation of neuropsychiatric diseases.
Vocal grooming in meerkats: weakly bonded subordinates call more in response to dominants
Authors: Demartsev Vlad , Gall Gabriella , Strandburg-Peshkin Ariana , Manser Marta B 
Published: November 2024

ABSTRACTPhysical grooming is often used to maintain social bonds in animal groups but the time available for grooming each group member may be limited. Vocal exchanges have been proposed to serve as a solution for sustaining social bonds without the need for physical proximity. To explore this possible social function of vocal exchanges, we examined the effect of dominance and dyadic bond strength of the interacting partners on the intensity of vocal interaction in meerkats (Suricata suricatta). Focusing on “sunning calls”, socially facilitated vocalisations produced when meerkats warm themselves in the sun, we conducted experiments, where we played sunning calls to individuals and recorded their responses. Subordinates increased their call rate in response to calls from dominants with whom they had weak associations during sunning periods and to calls from subordinates with whom they had strong associations. These patterns support the notion of meerkat sunning calls having a social regulatory function, potentially as a bonding or appeasing signal. Our results reflect the dichotomy between the subordinate and dominant individuals and underscore the strategic nature of social relationships within a despotic society. Engaging in continuous reciprocal interactions can signify commitment, promoting tolerance and cooperation. Investing in such interaction with influential dominants could lower the chances of aggression and would fit the “vocal grooming” functionality of such call exchanges. Accumulation of evidence of vocal exchanges reflecting social relationships, together with establishing a causal link between them, would demonstrate that remote “vocal grooming” is a fundamental mechanism for maintaining social affinity in nature.
Embryonic Signatures of Intergenerational Inheritance across Paternal Environments and Genetic Backgrounds
Authors: Dura Mathilde , Ranjan Bobby , Paribeni Rossella , Paribeni Violetta , Serrano Joana B. , Villacorta Laura , Benes Vladimir , Boruc Olga , Boskovic Ana , Hackett Jamie A. 
Published: November 2024

AbstractThe paternal preconception environment has been implicated as a modulator of phenotypic traits and disease risk in F1offspring. However, the prevalence and mechanisms of such intergenerational epigenetic inheritance (IEI) in mammals remain poorly defined. Moreover, the interplay between paternal exposure, genetics, and age on emergent offspring features is unexplored. Here, we measure the quantitative impact of three paternal environments on early embryogenesis across genetic backgrounds. Usingin vitrofertilisation (IVF) at scale, we capture batch-robust transcriptomic signatures of IEI with single-blastocyst resolution. Amongst these, paternal gut microbiota dysbiosis is linked with aberrant expression of lineage regulators in blastocysts, particularly affecting extra-embryonic tissues. Conversely, paternal low-protein high-sugar diet associates with subtle preimplantation developmental delay. We further identify gene expression variability as a paternally-induced F1phenotype, and highlight confounding issues for IEI such as batch-effects and under-sampling. Finally, paternal genetic background and age exert a dominant influence over the inherited environmental signature. This study systematically characterises how paternal conditioning programmes subtle but detectable molecular responses in early embryos, and suggests guiding principles to dissect intergenerational phenomenology.