bluuebunny/crossref_metadata_2025_split huggingface dataset:
CPT2 mediated fatty acid oxidation is dispensable for humoral immunity
Authors: Li Meilu , Zhou Xian , Zhu Xingxing , Li Yanfeng , Hitosugi Taro , Li Yuzhen , Zeng Hu 
Published: May 2024

ABSTRACTB cell activation is accompanied by dynamic metabolic reprogramming, supported by a multitude of nutrients that include glucose, amino acids and fatty acids. While several studies have indicated that fatty acid mitochondrial oxidation is critical for immune cell functions, contradictory findings have been reported. Carnitine palmitoyltransferase II (CPT2) is a critical enzyme for long-chain fatty acid oxidation in mitochondria. Here, we test the requirement of CPT2 for humoral immunity using a mouse model with a lymphocyte specific deletion of CPT2. Stable13C isotope tracing reveals highly reduced fatty acid-derived citrate production in CPT2 deficient B cells. Yet, CPT2 deficiency has no significant impact on B cell development, B cell activation, germinal center formation, and antibody production upon either thymus-dependent or –independent antigen challenges. Together, our findings indicate that CPT2 mediated fatty acid oxidation is dispensable for humoral immunity, highlighting the metabolic flexibility of lymphocytes.
XistDeletion in B Cells Results in Systemic Lupus Erythematosus Phenotypes
Authors: Lovell Claudia D. , Jiwrajka Nikhil , Amerman Hayley K. , Cancro Michael P. , Anguera Montserrat C. 
Published: May 2024

SUMMARYSystemic lupus erythematosus (SLE) is an autoimmune disease preferentially observed in females. X-linked gene expression in XX females is normalized to that of XY males by X-Chromosome Inactivation (XCI). However, B cells from female SLE patients and mouse models of SLE exhibit mislocalization of Xist RNA, a critical regulator of XCI, and aberrant expression of X-linked genes, suggesting that impairment of XCI may contribute to disease. Here, we find that a subset of female mice harboring a conditional deletion ofXist in B cells (“Xist cKO”) spontaneously develop SLE phenotypes, including expanded activated B cell subsets, disease-specific autoantibodies, and glomerulonephritis. Moreover, pristane-induced SLE-like disease is more severe in Xist cKO mice. Activated B cells from Xist cKO mice with SLE phenotypes have increased expression of proinflammatory X-linked genes implicated in SLE. Together, this work indicates that impaired XCI maintenance in B cells directly contributes to the female-bias of SLE.
Single-cell phylodynamic inference of tissue development and tumor evolution with scPhyloX
Authors: Wang Kun , Lu Zhaolian , Yao Zeqi , He Xionglei , Hu Zheng , Zhou Da 
Published: May 2024

AbstractPhylodynamics inference (PI) is a powerful approach for quantifying population dynamics and evolutionary trajectories of natural species based on phylogenetic trees. The emergence of single-cell lineage tracing technologies now enables the reconstruction of phylogenetic trees for thousands of individual cells within a multicellular organism, opening avenues for employing PI methodologies at the cellular level. However, the intricate process of cell differentiation poses challenges for directly applying current PI frameworks in somatic tissues. Here, we introduce a novel computational approach called single-cell phylodynamic explorer (scPhyloX), designed to model structured cell populations in various cell states, by leveraging single-cell phylogenetic trees to infer dynamics of tissue development and tumor evolution. Our comprehensive simulations demonstrate the high accuracy of scPhyloX across various biological scenarios. Application of scPhyloX to three real datasets of single-cell lineage tracing unveils novel insights into somatic dynamics, such as the overshoot of cycling stem cell populations in fly organ development, clonal expansion of multipotent progenitors of hematopoiesis during human aging, and pronounced subclonal selection in early colorectal tumorigenesis. Thus, scPhyloX is an innovative computational method for investigating the development and evolution of somatic tissues.
The cornerstone of early diagnosis and immunotherapy of prostate cancer:screening characteristic genes
Authors: Shao Bo , Wu Kaixiu , Wan Shui , Sun Pingping , Zuo Yanggen , Xiao Li , Pi Jinbo , Fan Zhengkai , Han Zhongxiong 
Published: May 2024

ABSTRACTBackgroundProstate cancer (PCA) has become a common malignant tumor globally, posing a substantial risk to the health of middle-aged and elderly men. However, there is still a lack of effective strategies for early detection and treatment of prostate cancer. The introduction of gene therapy in recent years has shown promise as a potential approach for cancer diagnosis and treatment.Methodology & Theoretical OrientationThe training set data GSE45016, GSE46602, and GSE69223 from the Gene Expression Omnibus (GEO) dataset, along with validation training set data GSE17951, were utilized. Differentially expressed genes (DEGs) between normal individuals and tumor patients were identified by combining the training set data. Subsequent analyses including Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and gene set enrichment analysis (GSEA) were conducted on the DEGs. WGCNA analysis was then performed on the gene expression matrix to identify module genes highly correlated with PCA, followed by the application of the LASSO algorithm to obtain PCA candidate genes. The candidate genes were validated using the area under the receiver operating characteristic (ROC) curve (AUC) to determine key feature genes. Finally, the relationship between key characteristic genes and immune cells was explored.FindingsA total of 54 DEGs were identified, with 26 down-regulated genes and 28 up-regulated genes. The GO function analysis revealed enrichment in processes such as ‘establishment of protein localization to membrane’ and ‘protein targeting to membrane’. KEGG analysis showed enrichment in pathways like ‘eutrophil degranulation’, ‘neutrophil activation involved in immune response’, and ‘regulation of cell morphogenesis’. GSEA analysis highlighted enrichment in pathways like ‘CTRL_VS_ACT_IL4 AND ANTI_IL12_12H_CD4_TCELL_DN’. Through WGCNA and LASSO regression analysis, key characteristic genes MARCKSL1, TMTC4, and TTLL12 were identified, with AUC values greater than 0.8 in both the training and validation sets, and were found to be closely associated with immune cell infiltration.Conclusion & SignificanceMARCKSL1, TMTC4, and TTLL12 emerge as crucial genes in the process of PCA, showing significant relevance to immune cell infiltration.this study offers valuable clinical insights into the diagnosis and treatment of prostate cancer through the identification of specific genes associated with the disease.
Frequencies of house fly proto-Y chromosomes across populations are predicted by temperature heterogeneity within populations
Authors: Foy Patrick D. , Loetzerich Sara R. , Boxler David , Burgess Edwin R. , Trout Fryxell R. T. , Gerry Alec C. , Hinkle Nancy C. , Machtinger Erika T. , Olds Cassandra , Tarone Aaron M. , Watson Wes , Scott Jeffrey G. , Meisel Richard P. 
Published: May 2024

AbstractSex chromosomes often differ between closely related species and can even be polymorphic within populations. Species with polygenic sex determination segregate for multiple different sex determining loci within populations, making them uniquely informative of the selection pressures that drive the evolution of sex chromosomes. The house fly (Musca domestica) is a model species for studying polygenic sex determination because male determining genes have been identified on all six of the chromosomes, which means that any chromosome can be a “proto-Y” chromosome. In addition, chromosome IV can carry a female-determining locus, making it a W chromosome. The different proto-Y chromosomes are distributed along latitudinal clines on multiple continents, their distributions can be explained by seasonality in temperature, and they have temperature-dependent effects on physiological and behavioral traits. It is not clear, however, how the clinal distributions interact with the effect of seasonality on the frequencies of house fly proto-Y chromosomes across populations. To address this question, we measured the frequencies of house fly Y and W chromosomes across nine populations in the United States of America. We confirmed the clinal distribution along the eastern coast of North America, but it is limited to the eastern coast. In contrast, annual mean daily temperature range is significantly correlated with proto-Y chromosome frequencies across the entire continent. Our results therefore suggest that temperature heterogeneity can explain the distributions of house fly proto-Y chromosomes in a way that does not depend on the cline. These results contribute to our understanding of how ecological factors affect sex chromosome evolution.
mosGraphGen: a novel tool to generate multi-omics signaling graphs to facilitate integrative and interpretable graph AI model development
Authors: Zhang Heming , Cao Dekang , Chen Zirui , Zhang Xiuyuan , Chen Yixin , Sessions Cole , Cruchaga Carlos , Payne Philip , Li Guangfu , Province Michael , Li Fuhai 
Published: May 2024

AbstractMulti-omics data, i.e., genomics, epigenomics, transcriptomics, proteomics, characterize cellular complex signaling systems from multi-level and multi-view and provide a holistic view of complex cellular signaling pathways. However, it remains challenging to integrate and interpret multi-omics data for mining key disease targets and signaling pathways. Graph AI models have been widely used to analyze graph-structure datasets, and are ideal for integrative multi-omics data analysis because they can naturally integrate and represent multi-omics data as a biologically meaningful multi-level signaling graph and interpret multi-omics data via graph node and edge ranking analysis. However, it is non-trivial for graph-AI model developers to pre-analyze multi-omics data and convert the data into biologically meaningful graphs, which can be directly fed into graph-AI models. To resolve this challenge, we developedmosGraphGen(multi-omics signaling graph generator), generating Multi-omics Signaling graphs (mos-graph) of individual samples by mapping multi-omics data onto a biologically meaningful multi-level background signaling network with data normalization by aggregating measurements and aligning to the reference genome. With mosGraphGen, AI model developers can directly apply and evaluate their models using these mos-graphs. In the results, mosGraphGen was used and illustrated using two widely used multi-omics datasets of TCGA and Alzheimer’s disease (AD) samples. The code of mosGraphGen is open-source and publicly available via GitHub:https://github.com/FuhaiLiAiLab/mosGraphGen
Exploring the dynamic ticks-camel-pathogens interaction
Authors: Makwatta JohnMark O. , Ndegwa Paul N. , Oyieke Florence A. , Ahuya Peter , Masiga Daniel K. , Getahun Merid N. 
Published: May 2024

AbstractThe ability of ticks to interact and adapt to different ecologies and hosts determines their vectorial competence for various pathogens, however ticks-livestock-pathogens interaction studies are limited. With our ticks-hosts-pathogens interface studies, we found 14 species of ticks feeding on various livestock. Ticks showed a strong preference for one-humped camels (Camelus dromedarius). The camel nostril was the most preferred predilection site. The most prevalent tick species on camels wasHyalomma rufipes. We found two novelAmblyomma gemmavariants which are distinct both morphologically and genetically from previously describedAmblyomma gemma. The signature odors from camel breath and body were attractive toH. rufipes; demonstrating ticks utilize camel-derived metabolites to find their host. Our research shows thatH. rufipesand camel hosts have unique and shared pathogens showingH. rufipes’ vector and camel’s reservoir host qualities. Our study unravels the dynamic interactions between ticks, pathogens, and camels that all influence the likelihood of pathogen adaptation and transmission dynamics.IMPORTANCETicks are obligatory hematophagous arachnids, serving as vectors for a wide array of pathogens that can be transmitted to animals and humans. The ability of ticks to acquire and transmit various pathogens depends on its attraction to quality reservoir host and the survival of the pathogens in ticks’ gut and other tissues. However, the complex dynamics of tick-pathogens interaction and host-seeking behavior remains understudied. This investigation revealed notable variation in tick preference for domestic animals, camel being the most preferred host. Moreover, our spatial analysis about tick attachment sites showed nostril is the most preferred sites by various tick species. Our epidemiology data showed variation in the pathogens harbored by camel (host) and vector (H. rufipes), demonstrating the camel’s efficiency as reservoir host and ticks’ vector competence for various pathogens. With our behavioral experiment usingH. rufipesand its preferred host’s (camel) breath and body signature odors, we identified novel attractants forH. rufipes, thus offering new avenues for combating TBDs. Overall, our study presents novel insights into how multiple factors shape tick-host-pathogens interaction.
Automated Prediction of Fibroblast Phenotypes Using Mathematical Descriptors of Cellular Features
Authors: Khang Alex , Barmore Abigail , Tseropoulos Georgios , Bera Kaustav , Batan Dilara , Anseth Kristi S. 
Published: May 2024

ABSTRACTFibrosis is caused by pathological activation of resident fibroblasts to myofibroblasts that leads to aberrant tissue stiffening and diminished function of affected organs with limited pharmacological interventions. Despite the prevalence of myofibroblasts in fibrotic tissue, existing methods to grade fibroblast phenotypes are typically subjective and qualitative, yet important for screening of new therapeutics. Here, we develop mathematical descriptors of cell morphology and intracellular structures to identify quantitative and interpretable cell features that capture the fibroblast-to-myofibroblast phenotypic transition in immunostained images. We train and validate models on features extracted from over 2,500 primary heart valve interstitial cells (VICs) and test their predictive performance on VICs treated with the small molecule drug 5-azacytidine, which inhibited myofibroblast activation. Collectively, this work introduces an analytical framework that unveils key features associated with distinct fibroblast phenotypes via quantitative image analysis and is broadly applicable for high-throughput screening assays of candidate treatments for fibrotic diseases.
IB-DNQ and Rucaparib dual treatment alters cell cycle regulation and DNA repair in triple negative breast cancer cells
Authors: Runnebohm Avery M. , Wijeratne H.R. Sagara , Peck Justice Sarah A. , Wijeratne Aruna B. , Roy Gitanjali , Singh Naveen , Hergenrother Paul , Boothman David A. , Motea Edward A. , Mosley Amber L. 
Published: May 2024

ABSTRACTBackgroundTriple negative breast cancer (TNBC), characterized by the lack of three canonical receptors, is unresponsive to commonly used hormonal therapies. One potential TNBC-specific therapeutic target is NQO1, as it is highly expressed in many TNBC patients and lowly expressed in non-cancer tissues. DNA damage induced by NQO1 bioactivatable drugs in combination with Rucaparib-mediated inhibition of PARP1-dependent DNA repair synergistically induces cell death.MethodsTo gain a better understanding of the mechanisms behind this synergistic effect, we used global proteomics, phosphoproteomics, and thermal proteome profiling to analyze changes in protein abundance, phosphorylation and protein thermal stability.ResultsVery few protein abundance changes resulted from single or dual agent treatment; however, protein phosphorylation and thermal stability were impacted. Histone H2AX was among several proteins identified to have increased phosphorylation when cells were treated with the combination of IB-DNQ and Rucaparib, validating that the drugs induced persistent DNA damage. Thermal proteome profiling revealed destabilization of H2AX following combination treatment, potentially a result of the increase in phosphorylation. Kinase substrate enrichment analysis predicted altered activity for kinases involved in DNA repair and cell cycle following dual agent treatment. Further biophysical analysis of these two processes revealed alterations in SWI/SNF complex association and tubulin / p53 interactions.ConclusionsOur findings that the drugs target DNA repair and cell cycle regulation, canonical cancer treatment targets, in a way that is dependent on increased expression of a protein selectively found to be upregulated in cancers without impacting protein abundance illustrate that multi-omics methodologies are important to gain a deeper understanding of the mechanisms behind treatment induced cancer cell death.
Method for isolation of small extracellular vesicles from different biofluids and workflow for Mass Spectrometry based-shotgun proteomics and RNA isolation
Authors: Sharma Pratibha , Dhamija Rajinder K 
Published: May 2024

AbstractSmall extracellular vesicles (sEVs) or exosomes are small-sized (30-150 nm), nanoparticles that are released from almost all cells under normal and pathophysiological conditions. The sEVs have a vital role in biological systems as they communicate and transfer their contents, such as proteins, lipids, and nucleic acids, from the cells of origin to nearby or distant cells. In recent years, there has been a growing interest in isolating sEVs for use in disease mechanisms, clinical diagnoses, and therapeutics. Due to their small size sEVs can be observed using electron microscopy. The size distribution and concentration were checked by Nanoparticle Tracking Analysis. Western blotting confirmed the presence of exosome markers. The ease of obtaining patient samples from biofluids like plasma, saliva, and urine makes them a valuable source for diagnostic purposes by isolating sEVs to diagnose and predict diseases early. However, there is no specific protocol to perform it altogether. We have developed an improved ultracentrifugation method using gradient ultracentrifugation and ultrafiltration, which results in higher sEVs purity and yield. We have tested this method on plasma, saliva, and urine at a single platform, and we have isolated proteins and RNA from exosomes for their downstream applications. Our method is simple to use and can be utilized for clinical research biomarker applications, in understanding disease mechanisms and monitoring its progressions from biofluid sample collections.
Endemic demographics of the Jomon people estimated based on complete mitogenomes reveal their regional diversity
Authors: Yoshida Koki , Wakiyama Yoshiki , Valverde Guido , Tanino Akio , Waku Daisuke , Katsumura Takafumi , Ogawa Motoyuki , Nagaoka Tomohito , Hirata Kazuaki , Koganebuchi Kae , Watanabe Yusuke , Ohashi Jun , Yoneda Minoru , Takahashi Ryuzaburo , Oota Hiroki 
Published: May 2024

AbstractThe Jomon culture that spread across Japanese archipelago began about 16,000 years ago and lasted for over 10,000 years. The genetic diversity of the Jomon people, prehistoric hunter-gatherers bearing the Jomon culture, is of great interest in understanding prehistoric East Eurasians. Until now, their demographic history has been estimated using archaeological sites and present-day genomes, but detailed studies using Jomon genomes have been insufficient. To investigate the Jomon demography, we determined the complete mitochondrial genome (mitogenome) sequences from 13 Jomon individuals and conducted population genetic analysis on 40 Jomon genomes including previously published data. Our results revealed an effective population size increase during the Incipient – Initial phase of the Jomon period, which had not been observed in analysis of mitogenome sequences from present-day Japanese populations. This endemic demographic pattern is pronounced in the eastern part of the archipelago, under the assumption of no gene flow between the Eastern and Western Jomon.
Optimizing Peptide Crosslinks for Cell-Responsive Hydrogels
Authors: Wu Yingjie , Rozans Samuel J. , Moghaddam Abolfazl Salehi , Pashuck E. Thomas 
Published: May 2024

AbstractCells dynamically modify their local extracellular matrix by expressing proteases that degrade matrix proteins. This enables cells to spread and migrate within tissues, and this process is often mimicked in hydrogels through the incorporation of peptide crosslinks that can be degraded by cell-secreted proteases. However, the cleavage of hydrogel crosslinks will also reduce the local matrix mechanical properties, and most crosslinking peptides, such as the widely used GPQGIWGQ “PanMMP” sequence, lead to bulk degradation of the hydrogel. A subset of proteases are localized to the cell membrane and are only active in the pericellular region in the immediate vicinity of the cell surface. These membrane-type proteases have important physiological roles and enable cells to migrate within tissues. In this work we developed an approach to identify and optimize peptide sequences that are specifically degraded by membrane-type proteases. We utilized a proteomic screen to identify peptide targets, and coupled this with a functional assay that both quantifies peptide degradation by individual cell types and can elucidate whether the peptides are primarily cleaved by soluble proteases or membrane-type proteases. We then used a split-and-pool synthesis approach to generate more than 300 variants of the target peptide to improve the degradation behavior. We identified an optimized peptide sequence, KLVADLMASAE, which is primarily degraded by membrane-type proteases, but enables both endothelial cells and stem cells grown in KLVADLMASAE-crosslinked hydrogels to spread and have viabilities similar to the gels crosslinked by the PanMMP peptide. Notably, the biological performance of the KLVADLMASAE peptide-cross linked gels was significantly improved from the initial peptide target found in the proteomic screen. This work introduces a functional approach to identifying and refining protease-substrate peptides as a way to enhance the properties of hydrogel matrices.
Urea amidolyase as the enzyme for urea utilization in algae: functional display inChlamydomonas reinhardtiiand evolution in algae
Authors: Liang Honghao , Lin Senjie , Chen Yuanhao , Wang Jingtian , Aslam Muhammad , Chen Jing , Du Hong , Li Tangcheng 
Published: May 2024

AbstractUrea is a crucial nitrogen nutrient source for algae with the potential to stimulate harmful algal blooms, but the molecular machinery underpinning urea uptake and assimilation by algae is not fully understood. Urease (URE) is commonly regarded as the responsible enzyme, but the urea amidolyase (UAD) system, albeit known to exist, has hardly been studied. Here, the phylogenetic distribution, expression patterns, and functional roles of UAD system are examined, which comprises subunitsDUR1,DUR2, andDUR3. We find a widespread occurrence of UAD, spanning four major phytoplankton lineages, and potentially independent evolution of URE and lineage-specific loss. Besides, a stronger regulation of UAD by environmental nitrogen concentrations compared to URE is uncovered in both global ocean and local dinoflagellate-dominant bloom events. CRISPR-based mutation inChlamydomonas reinhardtiishows that subunitDUR2is essential for urea utilization.DUR2inactivation led to completely growth restriction and upregulation ofDUR1andDUR3A, suggesting its functional interaction with them. In contrast,DUR3Binactivation only partially halted urea uptake and cell growth but significantly reduced gene expression across the entire UAD system. These findings not only reveal the crucial role ofDUR2in urea utilization inC. reinhardtiiand potentially in many other algae, but also suggestDUR2to be a more suitable indicator of urea utilization than urease, and underscore the importance to consider both URE and UAD enzyme systems when urea utilization by algae is assessed.