bluuebunny/crossref_metadata_2025_split huggingface dataset:
Structure-based self-supervised learning enables ultrafast prediction of stability changes upon mutation at the protein universe scale
Authors: Sun Jinyuan , Zhu Tong , Cui Yinglu , Wu Bian 
Published: August 2023

AbstractPredicting free energy changes (ΔΔG) is of paramount significance in advancing our comprehension of protein evolution and holds profound implications for protein engineering and pharmaceutical development. Traditional methods, however, often suffer from limitations such as sluggish computational speed or heavy reliance on biased training datasets. These challenges are magnified when aiming for accurate ΔΔG prediction across the vast universe of protein sequences. In this study, we present Pythia, a self-supervised graph neural network tailored for zero-shot ΔΔG predictions. In comparative benchmarks with other self-supervised pre-training models and force field-based methods, Pythia outshines its contenders with superior correlations while operating with the fewest parameters, and exhibits a remarkable acceleration in computational speed, up to 105-fold. The efficacy of Pythia is corroborated through its application in predicting thermostable mutations of limonene epoxide hydrolase (LEH) with significant higher experimental success rates. This efficiency propels the exploration of 26 million high-quality protein structures. Such a grand-scale application signifies a leap forward in our capacity to traverse the protein sequence space and potentially enrich our insights into the intricacies of protein genotype-phenotype relationships. We provided a web app athttps://pythia.wulab.xyzfor users to conveniently execute predictions. Keywords: self-supervised learning, protein mutation prediction, protein thermostability
Expression patterns of m6A RNA methylation regulators under apoptotic conditions in various human cancer cell lines
Authors: Akçaöz-Alasar Azime , Sağlam Buket , Vatansever Ipek Erdogan , Akgül Bünyamin 
Published: August 2023

AbstractThe emerging evidence suggests that epitranscriptomics changes play a crucial role in the pathogenesis of cancer. However, expression patterns of m6A RNA modifiers under apoptotic conditions are unknown. We measured the transcript abundance of m6A RNA modifiers under cisplatin- and tumor necrosis factor alpha (TNF-α)-induced apoptotic conditions. In general, the abundance of m6A modifiers is increased upon cisplatin treatment whereas TNF-α treatment has led to a reduction in their expression. Specifically, cisplatin-induced apoptosis, but not TNF-α mediated apoptosis, lowered the abundance of METTL14 and FTO transcripts. Additionally, cisplatin treatment plummeted the abundance of IGF2BP2 and IGF2BP3 readers following cisplatin treatment. These results suggest that differential response of cancer cells to apoptotic inducers could be partially due to m6A RNA modifiers.
Exploiting Epigenetic Targets to Overcome Taxane Resistance in Prostate Cancer
Authors: Cevatemre Buse , Bulut Ipek , Dedeoglu Beyza , Isiklar Arda , Syed Hamzah , Yedier Bayram Ozlem , Bagci-Onder Tugba , Acilan Ayhan Ceyda 
Published: August 2023

AbstractThe development of taxane resistance remains a major challenge for castration resistant prostate cancer (CR-PCa), despite the effectiveness of taxanes in prolonging patient survival. To uncover novel targets, we performed an epigenetic drug screen on taxane (docetaxel and cabazitaxel) resistant CR-PCa cells. We identified BRPF reader proteins, along with several epigenetic groups (CBP/p300, Menin-MLL, PRMT5 and SIRT1) that act as targets effectively reversing the resistance mediated by ABCB1. Targeting BRPFs specifically resulted in the resensitization of resistant cells, while no such effect was observed on the sensitive compartment. These cells were successfully arrested at the G2/M phase of cell cycle and underwent apoptosis upon BRPF inhibition, confirming the restoration of taxane susceptibility. Pharmacological inhibition of BRPFs reduced ABCB1 activity, indicating that BRPFs may be involved in an efflux-related mechanism. Indeed, ChIP-qPCR analysis confirmed binding of BRPF1 to the ABCB1 promoter suggesting direct regulation of the ABCB1 gene at the transcriptional level. RNA-seq analysis revealed that BRPF1 knockdown affects the genes enriched in mTORC1 and UPR signaling pathways, revealing potential mechanisms underlying its functional impact, which is further supported by the enhancement of taxane response through the combined inhibition of ABCB1 and mTOR pathways, providing evidence for the involvement of multiple BRPF1-regulated pathways. Beyond clinical attributes (Gleason score, tumor stage, therapy outcome, recurrence), metastatic PCa databases further supported the significance of BRPF1 in taxane resistance, as evidenced by its upregulation in taxane-exposed PCa patients.
Application of a Novel Numerical Simulation to Biochemical Reaction systems
Authors: Sato Takashi 
Published: August 2023

AbstractMotivationOmics data and single-cell analyses have recently produced many biological informatics. These require simple, fast, and flexible numerical/analytical methods such as ordinary differential equations. However, formulating these equations and their computational processescanbe expensive and imprecise for simulating reactions involving genes and a small number of molecular systems. Therefore, developing a straightforward simulation method is necessary.ResultsWe developed a natural number simulation (NNS) method using binomial probability-based stochastic algorithms. Hence, this paper simulated one-gene systems for feedback and feed-forward reactions, allosteric biochemical reactions, and SIR-type population dynamics. Furthermore, NNS can calculate any biological reaction systems written using stoichiometric formula. Thus, NNS provides a comfortable simulation tool for the scientific and engineering fields; algorithms and applications are detailed using Python.Availability and implementationCalculation results and the program are available as supplementary information in binomial_v15.zip inhttps://binomial-simulation.com/en/python-program/.Contactsato@zeon.co.jpSupplementary InformationSupplementary data are available in this pdf file.Graphical Abstract
weIMPUTE: A User-Friendly Web-Based Genotype Imputation Platform
Authors: Tang You , Li Mingliang , Li Zhuo , Li Qi , Hu Xiaodong , Yu Jun , Lin Jian , Bi Chunguang , Yu Helong , Huang Meng 
Published: August 2023

AbstractGenotype imputation is a critical preprocessing step in genome-wide association studies (GWAS), enhancing statistical power for detecting associated single nucleotide polymorphisms (SNPs) by increasing marker size. In response to the needs of researchers seeking user-friendly graphical tools for imputation without requiring informatics or computer expertise, we have developed weIMPUTE, a web-based imputation graphical user interface (GUI). Unlike existing genotype imputation software, weIMPUTE supports multiple imputation software, including SHAPEIT, Eagle, Minimac4, Beagle, and IMPUTE2, while encompassing the entire workflow, from quality control to data format conversion. This comprehensive platform enables both novices and experienced users to readily perform imputation tasks. For reference genotype data owners, weIMPUTE can be installed on a server or workstation, facilitating web-based imputation services without data sharing. weIMPUTE represents a versatile imputation solution for researchers across various fields, offering the flexibility to create personalized imputation servers on different operating systems.
Cross-talk quantification in molecular networks with application to pathway-pathway and cell-cell interactions
Authors: Chiodi A , Pelucchi P , Mosca E 
Published: August 2023

MotivationsDisease phenotypes are interpreted as the consequence of interactions among molecular processes affected by a series of molecular alterations. Current omics approaches underline the importance of such interactions, focusing on molecular mechanisms, by using manually curated pathways or gene sets. As there are no clear boundaries between gene sets, cross-talks between them are relevant to investigate disease phenotypes.Here we present Ulisse, a method to (1) quantify cross-talks between gene sets, with application to pathways and intercellular cross-talks; (2) investigate the role of the genes involved in cross-talks, via functional relevance analysis, in terms of regulated processes/cell types. As a proof-of-concept, we studied pathway and cell-cell cross-talks in normal and tumoral breast samples, and compared the obtained results with other available tools: PathNet for pathway cross-talk, ICELLNET and SingleCellSignalR for intercellular cross-talk.ResultsCross-talk analysis allowed to identify dysregulated interactions between tumor progression key mechanisms, while intercellular cross-talks describe well-known interactions of the tumor with the microenvironment. Through functional relevance analysis, Ulisse was able to pinpoint well known key players of the tumor, as well as potential therapeutic targets. The comparison of Ulisse to other packages highlighted the good performance of our package. In conclusion, Ulisse proved to be a valuable tool to study cross-talks, and provide a newly implemented approach to analyse involved genes.Availability and implementationUlisse is an R package and available athttps://github.com/emosca-cnr/UlisseContactettore.mosca@itb.cnr.itSupplementary informationLink to supplementary tables + reference to on-line supplementary material
Age-specific walking speed during locomotor adaptation leads to more generalization across contexts
Authors: Mariscal Dulce M. , Sombric Carly J. , Torres-Oviedo Gelsy 
Published: August 2023

ABSTRACTPrevious work has shown that compared with young adults, older adults generalize their walking patterns more across environments that impose different motor demands (i.e., split-belt treadmill vs. overground). However, in this previous study, all participants walked at a speed that was more comfortable for older adults than young participants, which leads to the question of whether young adults would generalize more their walking patterns than older adults when exposed to faster speeds that are more comfortable for them. To address this question, we examined the interaction between healthy aging and walking speed on the generalization of a pattern learned on a split-belt treadmill (i.e., legs moving at different speeds) to overground. We hypothesized that walking speed during split-belt walking regulates the generalization of walking patterns in an age-specific manner. To this end, groups of young (<30 y/o) and older (65+ y/o) adults adapted their gait on a split-belt treadmill at either slower or faster walking speeds. We assessed the generalization of movements between the groups by quantifying their aftereffects during overground walking, where larger overground aftereffects represent more generalization, and zero aftereffects represent no generalization. We found an interaction between age and walking speed in the generalization of walking patterns. More specifically, older adults generalized more when adapted at slower speeds, whereas younger adults did so when adapted at faster speeds. These results suggest that comfortable walking speeds lead to more generalization of newly acquired motor patterns beyond the training contexts.
Frequent, infinitesimal bottlenecks maximize the rate of microbial adaptation
Authors: Delaney Oscar , Letten Andrew , Engelstädter Jan 
Published: August 2023

AbstractSerial passaging is a fundamental technique in experimental evolution. The choice of bottleneck severity and frequency poses a dilemma: longer growth periods allow beneficial mutants to arise and grow over more generations, but simultaneously necessitate more severe bottlenecks with a higher risk of those same mutations being lost. Short growth periods require less severe bottlenecks, but come at the cost of less time between transfers for beneficial mutations to establish. The standard laboratory protocol of 24-hour growth cycles with severe bottlenecking has logistical advantages for the experimenter but limited theoretical justification. Here we demonstrate that contrary to standard practice, the rate of adaptive evolution is maximized when bottlenecks are frequent and small, indeed infinitesimally so in the limit of continuous culture. This result derives from revising key assumptions underpinning previous theoretical work, including changing the metric of optimization to incorporate experiment runtime, and using a full binomial distribution for bottlenecking, rather than a Poisson approximation. We also show that adding resource constraints and clonal interference to the model leaves the qualitative results unchanged. Implementing these findings will require liquid-handling robots to perform frequent bottlenecks, or chemostats for continuous culture. Further innovation in and adoption of these technologies has the potential to accelerate the rate of discovery in experimental evolution.
Identification of HPV oncogene and host cell differentiation associated cellular heterogeneity in cervical cancer via single-cell transcriptomic analysis
Authors: Li Yingjie , Wang Cankun , Ma Anjun , Rani Abdul Qawee , Luo Mingjue , Li Jenny , Liu Xuefeng , Ma Qin 
Published: August 2023

AbstractHuman Papillomaviruses (HPVs) are associated with around 5-10% of human cancer, notably nearly 99% of cervical cancer. The mechanisms HPV interacts with stratified epithelium (differentiated layers) during the viral life cycle, and oncogenesis remain unclear. In this study, we used single-cell transcriptome analysis to study viral gene and host cell differentiation-associated heterogeneity of HPV-positive cervical cancer tissue. We examined the HPV16 genes - E1, E6, and E7, and found they expressed differently across nine epithelial clusters. We found that three epithelial clusters had the highest proportion of HPV-positive cells (33.6%, 37.5%, and 32.4%, respectively), while two exhibited the lowest proportions (7.21% and 5.63%, respectively). Notably, the cluster with the most HPV-positive cells deviated significantly from normal epithelial layer markers, exhibiting functional heterogeneity and altered epithelial structuring, indicating that significant molecular heterogeneity existed in cancer tissues and that these cells exhibited unique/different gene signatures compared with normal epithelial cells. These HPV-positive cells, compared to HPV-negative, showed different gene expressions related to the extracellular matrix, cell adhesion, proliferation, and apoptosis. Further, the viral oncogenes E6 and E7 appeared to modify epithelial function via distinct pathways, thus contributing to cervical cancer progression. We investigated the HPV and host transcripts from a novel viewpoint focusing on layer heterogeneity. Our results indicated varied HPV expression across epithelial clusters and epithelial heterogeneity associated with viral oncogenes, contributing biological insights to this critical field of study.
Machine learning of cellular metabolic rewiring
Authors: Xavier Joao B. 
Published: August 2023

AbstractMetabolic rewiring allows cells to adapt their metabolism in response to evolving environmental conditions. Traditional metabolomics techniques, whether targeted or untargeted, often struggle to interpret these adaptive shifts. Here, we introduceMetaboLiteLearner, a machine learning framework that harnesses the detailed fragmentation patterns from electron ionization (EI) collected in scan mode during gas chromatography/mass spectrometry (GC/MS) to predict abundance changes in metabolically adapted cells. When tested on breast cancer cells with different preferences to metastasize to specific organs,MetaboLiteLearnerpredicted the impact of metabolic rewiring on metabolites withheld from the training dataset using only the EI spectra, without metabolite identification or pre-existing knowledge of metabolic networks. The model learned captures shared and unique metabolomic shifts between brain- and lung-homing metastatic lineages, suggesting potential organ-tailored cellular adaptations. Integrating machine learning and metabolomics paves the way for new insights into complex cellular adaptations.SignificanceMetabolic rewiring—the cellular adaptation to shifts in environment and nutrients—plays key roles in many contexts, including cancer metastasis. Traditional metabolomics often falls short of capturing the nuances of these metabolic shifts. This work introducesMetaboLiteLearner, a machine learning approach that harnesses the rich fragmentation patterns from electron ionization collected in scan mode during gas chromatography/mass spectrometry, paving the way for new insights into metabolic adaptations. Demonstrating its robustness on a breast cancer model, we highlightMetaboLiteLearner’s potential to reshape our understanding of metabolic rewiring, with implications in diagnostics, therapeutics, and basic cell biology.
Divergent roles of IREG/Ferroportin transporters from the nickel hyperaccumulatorLeucocroton havanensis
Authors: Gonzalez Dubiel Alfonso , Sanchez Garcia de la Torre Vanesa , Fernandez Rolando Reyes , Barreau Louise , Merlot Sylvain 
Published: August 2023

AbstractIn response to our ever-increasing demand for metals, phytotechnologies are being developed to limit the environmental impact of conventional metal mining. However, the development of these technologies, which rely on plant species able to tolerate and accumulate metals, is partly limited by our lack of knowledge of the underlying molecular mechanisms.In this work, we aimed to identify genes involved in nickel hyperaccumulation in the Euphorbiaceae speciesLeucocroton havanensis. Using transcriptomic data, we identified two homologous genes,LhavIREG1andLhavIREG2, encoding divalent metal transporters of the IREG/ferroportin family. Both genes are expressed at similar levels in shoots, but LhavIREG1 shows higher expression in roots. Heterologous expression of these transporters inA. thalianarevealed that LhavIREG1 is localized to the plasma membrane, whereas LhavIREG2 is located at the vacuole. In addition, expression of each gene induced a significant increase in nickel tolerance. Taken together, our data suggest that LhavIREG2 is involved in nickel sequestration in vacuoles of leaf cells, whereas LhavIREG1 is mainly involved in nickel translocation from roots to shoots, but could also be involved in metal sequestration in cell walls. Our results suggest that paralogous IREG/ferroportin transporters may play complementary roles in nickel hyperaccumulation in plants.HighlightThe nickel hyperaccumulatorLeucocroton havanensisendemic to Cuba, expresses two paralogous metal transporters of the IREG/ferroportin family that play distinct but complementary roles in nickel tolerance and accumulation.
A snakemake toolkit for the batch assembly, annotation, and phylogenetic analysis of mitochondrial genomes and ribosomal genes from genome skims of museum collections
Authors: White Oliver , Hall Andie , Price Ben W. , Williams Suzanne T. , Clark Matt 
Published: August 2023

AbstractLow coverage “genome-skims” are often used to assemble organelle genomes and ribosomal gene sequences for cost effective phylogenetic and barcoding studies. Natural history collections hold invaluable biological information, yet poor preservation resulting in degraded DNA often hinders PCR based analyses. However, with improvements to molecular techniques and sequencing technology, it is possible to use methods developed for working with ancient DNA to generate libraries and sequence the short fragments typical of degraded DNA to generate genome skims from museum collections.Here we introduce a snakemake toolkit comprised of three pipelinesskim2mt,skim2rrnaandgene2phylo, designed to unlock the genomic potential of historical museum specimens using genome skimming. Specifically,skim2mtandskim2rrnaperform the batch assembly, annotation and phylogenetic analysis of mitochondrial genomes and nuclear ribosomal genes, respectively, from low-coverage genome skims. The third pipelinegene2phylotakes a set of gene alignments and performs phylogenetic analysis of individual genes, partitioned analysis of concatenated alignments and a phylogenetic analysis based on gene trees.We benchmark our pipelines with simulated data, followed by testing with a novel genome skimming dataset from both recent and historical solariellid gastropod samples. We show that the toolkit can recover mitochondrial and ribosomal genes from poorly preserved museum specimens of the gastropod family Solariellidae. In addition, the phylogenetic analysis of multiple gene sequences is consistent with our current understanding of taxonomic relationships.The generation of bioinformatic pipelines that facilitate processing large quantities of sequence data from the vast repository of specimens held in natural history museum collections will greatly aid species discovery and exploration of biodiversity over time, ultimately aiding conservation efforts in the face of a changing planet.
Age-linked lung pathology is reduced by immunotherapeutic targeting of isoDGR protein damage
Authors: Kalailingam Pazhanichamy , Mohd-Kahliab Khalilatul-Hanisah , Ngan SoFong Cam , Iyappan Ranjith , Lee Benjamin Sian Teck , Sharma Bhargy , Machan Radek , Bo Sint Thida , Chambers Emma S , Fajardo Val A , Macpherson Rebecca E. K. , Liu Jian , Klentrou Panagiota , Tsiani Evangelia Litsa , Lim Kah Leong , Su I Hsin , Gao Yong-Gui , Richar A Mark , Kalaria Raj N. , Chen Christopher P. , McCarthy Neil E. , Sze Siu Kwan 
Published: August 2023

AbstractAdvancing age is the primary risk factor for pulmonary diseases. Our investigation revealed an 8-fold increase in aging induced isoDGR-damaged proteins in lung tissue from human pulmonary fibrosis patients compared to healthy tissues, accompanied by elevated frequencies of CD68+/CD11b+ macrophages, indicating lung tissue is susceptible to time-dependent accumulation of isoDGR-proteins. To elucidate the mechanisms through which isoDGR-proteins may exacerbate aging lung disorders for potential therapeutic targeting, we assessed the functional role of this isoDGR-motif in naturally-aged mice and mice lacking the corresponding isoDGR repair enzyme (Pcmt1-/-). IsoDGR-protein accumulation in mouse lung tissue and blood vessels correlated with chronic low-grade inflammation, pulmonary edema, and hypoxemia. IsoDGR accretion induced mitochondrial and ribosomal dysfunctions, cellular senescence, and apoptosis, contributing to progressive lung damage over time. Treatment with anti-isoDGR antibodies suppressed TLR pathway activity, mitigated cytokine-driven inflammation, restored mtDNA expression, and significantly reduced lung pathology in-vivo. Similarly, exposure of lung endothelial cells to isoDGR-modified fibronectin impaired oxygen consumption, increased reactive oxygen species levels, and disrupted acidification, but these effects were efficiently reversed by target-specific antibody therapy. Collectively, our findings underscore the significant contribution of isoDGR-damaged proteins to age-linked lung pathology. IsoDGR-specific therapy emerges as a promising treatment approach for pulmonary disorders in older patients.