bluuebunny/crossref_metadata_2025_split huggingface dataset:
Integrated transcriptomic meta-analysis provides novel insights into breast cancer molecular subtypes
Authors: Bajpai Akhilesh Kumar , Davuluri Sravanthi , Thirumurugan Kavitha , Acharya Kshitish K. 
Published: August 2021

AbstractBreast cancer is the most common cancer in women worldwide. There are four major breast cancer subtypes (luminal A, luminal B, HER2-enriched and triple-negative/TNBC). TNBC is the most aggressive form with the worst prognosis. However, the differences among the subtypes have not been completely established at the molecular level, thereby limiting therapeutic and diagnostic options for TNBC. We performed a meta-analysis of microarray and RNA-sequencing data to identify candidate genes with an expression-based association in each molecular subtype of breast cancer. The protein interaction network of the candidate genes was analyzed to discover functionally significant gene clusters and hub genes. Potential therapeutic candidates for TNBC were explored through gene-miRNA interactions. We identified 316, 347, 382, and 442 candidate genes in luminal A, luminal B, HER2 and TNBC subtypes, respectively. A total of 135 (26 up- and 109 down-regulated) candidate genes were shared by all four subtypes. Functional analysis of the candidate genes indicated up-regulation of ‘cell cycle’ and ‘p53 signaling’ pathways and down-regulation of multiple signaling pathways. COL10A1 was found to be highly up-regulated in all subtypes. It may be a good target for research towards multiple types of applications, including therapeutics. KIF4A, a commonly up-regulated X-chromosome gene was significantly associated with the survival of breast cancer patients. Protein interaction network and centrality analysis revealed that low-moderately differentially regulated genes play an important role in functional cascades across proteins in breast cancer subtypes and may be potential candidates for therapeutics. Targeting FN1 (fibronectin 1), the key up-regulated hub gene by miR-1271 5p may be an important molecular event to be targeted for potential therapeutic application in TNBC.
Robust bacterial co-occurence community structures are independent of r- and K-selection history
Authors: Pettersen Jakob Peder , Gundersen Madeleine S. , Almaas Eivind 
Published: August 2021

ABSTRACTSelection for bacteria which are K-strategists instead of r-strategists has been shown to improve fish health and survival in aquaculture. We considered an experiment where microcosms were inoculated with natural seawater and the selection regime was switched from K-selection (by continuous feeding) to r-selection (by pulse feeding) and vice versa. We found the networks of significant co-occurrences to contain clusters of taxonomically related bacteria having positive associations. Comparing this with the time dynamics, we found that the clusters most likely were results of similar niche preferences of the involved bacteria. In particular, the distinction between r- or K-strategists was evident. Each selection regime seemed to give rise to a specific pattern, to which the community converges regardless of its prehistory. Furthermore, the results proved robust to parameter choices in the analysis, such as the filtering threshold, level of random noise, replacing absolute abundances with relative abundances, and the choice of similarity measure. Even though our data and approaches cannot directly predict ecological interactions, our approach provides insights on how the selection regime affects the composition and workings of the microbial community, providing a basis for aquaculture experiments targeted at eliminating opportunistic fish pathogens.
High glucose enhances antigen-independent CTL killing via TRAIL
Authors: Yang Wenjuan , Denger Andreas , Diener Caroline , Küppers Frederic , Soriano-Baguet Leticia , Schäfer Gertrud , Yanamandra Archana K. , Zhao Renping , Knörck Arne , Schwarz Eva C. , Hart Martin , Lammert Frank , Roma Leticia Prates , Brenner Dirk , Christidis Grigorios , Helms Volkhard , Meese Eckart , Hoth Markus , Qu Bin 
Published: August 2021

AbstractCytotoxic T lymphocytes (CTLs) are involved in development of diabetes. However, the impact of excessive glucose on CTL-mediated antigen-independent killing remains elusive. Here, we report that TNF-related apoptosis inducing ligand (TRAIL) is substantially up- regulated in CTLs in environments with high glucose (HG) both in vitro and in vivo. The PI3K- Akt-NFκB axis and non-mitochondrial reactive oxygen species are essential in HG-induced TRAIL upregulation in CTLs. TRAILhigh CTLs induce apoptosis of pancreatic beta cell line 1.4E7. Metformin and Vitamin D synergistically reduce HG-enhanced expression of TRAIL in CTLs and coherently protect 1.4E7 cells from TRAIL-mediated apoptosis. Notably, in patients with diabetes, correlation between Vitamin D concentrations in plasma and glucose levels is linked to HG-enhanced TRAIL expression on CTLs. Microarray data reveal that OXCT2, an important enzyme in ketone body catabolism, is a promising target in response to vitamin D. Our work not only reveals a novel mechanism of CTL involvement in progression of diabetes, but also establishes CTLs as a target for combined metformin and vitamin D therapy to protect pancreatic beta cells of diabetic patients.
Molecular Evolution across Mouse Spermatogenesis
Authors: Kopania Emily E. K. , Larson Erica L. , Callahan Colin , Keeble Sara , Good Jeffrey M. 
Published: August 2021

AbstractGenes involved in spermatogenesis tend to evolve rapidly, but we still lack a clear understanding of how different components of molecular evolution vary across this complex developmental process. We used fluorescence activated cell sorting (FACS) to generate expression data for both early (meiotic) and late (postmeiotic) cell types across thirteen inbred strains of mice (Mus) spanning ~7 million years of evolution. We used these comparative developmental data to investigate the evolution of lineage-specific expression, protein-coding sequences, and expression levels. We found increased lineage specificity and more rapid protein-coding and expression divergence during late spermatogenesis, suggesting that signatures of rapid testis molecular evolution are punctuated across sperm development. Despite strong overall developmental parallels in these components of molecular evolution, protein and expression divergences were only weakly correlated across genes. We detected more rapid protein evolution on the X chromosome relative to the autosomes, while X-linked gene expression tended to be relatively more conserved likely reflecting chromosome-wide regulatory constraints. Using allele-specific FACS expression data from crosses between four strains, we found that the relative contributions of different regulatory mechanisms also differed between cell-types. Genes showingcis-regulatory changes were more common late in spermatogenesis, and tended to be associated with larger differences in expression levels and greater expression divergence between species. In contrast, genes withtrans-acting changes were more common early and tended to be more conserved across species. Our findings advance understanding of gene evolution across spermatogenesis and underscore the fundamental importance of developmental context in molecular evolutionary studies.
Using adopted individuals to partition maternal genetic effects into prenatal and postnatal effects on offspring phenotypes
Authors: Hwang Liang-Dar , Moen Gunn-Helen , Evans David M. 
Published: August 2021

AbstractMaternal genetic effects can be defined as the effect of a mother’s genotype on the phenotype of her offspring, independent of the offspring’s genotype. Maternal genetic effects can act via the intrauterine environment during pregnancy and/or via the postnatal environment. In this manuscript, we present a simple extension to the basic adoption design that uses structural equation modelling (SEM) to partition maternal genetic effects into prenatal and postnatal effects. We assume that in biological families, offspring phenotypes are influenced prenatally by their mother’s genotype and postnatally by both parents’ genotypes, whereas adopted individuals’ phenotypes are influenced prenatally by their biological mother’s genotype and postnatally by their adoptive parents’ genotypes. Our SEM framework allows us to model the (potentially) unobserved genotypes of biological and adoptive parents as latent variables, permitting us in principle to leverage the thousands of adopted singleton individuals in the UK Biobank. We examine the power, utility and type I error rate of our model using simulations and asymptotic power calculations. We apply our model to polygenic scores of educational attainment and birth weight associated variants, in up to 5178 adopted singletons, 983 trios, 3650 mother-offspring pairs, 1665 father-offspring pairs and 350330 singletons from the UK Biobank. Our results show the expected pattern of maternal genetic effects on offspring birth weight, but unexpectedly large prenatal maternal genetic effects on offspring educational attainment. Sensitivity and simulation analyses suggest this result may be at least partially due to adopted individuals in the UK Biobank being raised by their biological relatives. We show that accurate modelling of these sorts of cryptic relationships is sufficient to bring type I error rate under control and produce unbiased estimates of prenatal and postnatal maternal genetic effects. We conclude that there would be considerable value in following up adopted individuals in the UK Biobank to determine whether they were raised by their biological relatives, and if so, to precisely ascertain the nature of these relationships. These adopted individuals could then be incorporated into informative statistical genetics models like the one described in our manuscript to further elucidate the genetic architecture of complex traits and diseases.
PixR, a novel activator of conjugative transfer of IncX4 resistance plasmids, mitigates the fitness cost of mcr-1 carriage in Escherichia coli
Authors: Yi Lingxian , Durand Romain , Grenier Frédéric , Yang Jun , Yu Kaiyang , Burrus Vincent , Liu Jian-Hua 
Published: August 2021

ABSTRACTThe emergence of the plasmid-borne colistin resistance gene mcr-1 threats public health. IncX4-type plasmids are one of the most epidemiologically successful vehicles for spreading mcr-1 worldwide. Since MCR-1 is known for imposing a fitness cost to its host bacterium, the successful spread of mcr-1-bearing plasmids might be linked to high conjugation frequency, which would enhance the maintenance of the plasmid in the host without antibiotic selection. However, the mechanism of IncX4 plasmids conjugation remains unclear. In this study, we used high-density transposon mutagenesis to identify factors required for IncX4 plasmid transfer and 18 genes were identified, including five with annotations unrelated to conjugation. The Cappable-seq and RNA-seq analysis confirmed that a novel transcriptional regulator gene, pixR, directly regulates the transfer of IncX4 plasmids by binding the promoter of 13 essential transfer genes to increase their transcription. Plasmid invasion and co-culture competition assays revealed that pixR is essential for the spread and persistence of mcr-1-bearing IncX4 plasmids in bacterial populations, and effective conjugation is crucial for alleviating the fitness cost exerted by mcr-1 carriage. The existence of the IncX4-specific pixR gene increases plasmid transmissibility while promoting the invasion and persistence of mcr-1-bearing plasmids in bacterial populations, which helps explain their global prevalence.IMPORTANCEThe spread of clinical important antibiotic resistance genes is frequently related to some epidemic plasmids. However, the underlying molecular mechanisms contributing to the successful spread of these epidemic plasmids remains unclear. The significant of our research indicated that efficient conjugation could promote the invasion and persistence of plasmids within a bacterial population, resulting in the successful dissemination of epidemic plasmids in nature. Our data also highlight the importance of developing plasmid conjugation inhibitors to solve the antibiotic resistance crisis.
Energetics of a protein disorder-order transition in small molecule recognition
Authors: Mendoza-Martinez Cesar , Papadourakis Michail , Llabrés Salomé , Gupta Arun A. , Barlow Paul N. , Michel Julien 
Published: August 2021

AbstractMany proteins recognise other proteins via mechanisms that involve the folding of intrinsically disordered regions upon complex formation. Here we investigate how the selectivity of a drug-like small molecule arises from its modulation of a protein disorder-to-order transition. Binding of the compound AM-7209 has been reported to confer order upon an intrinsically disordered ‘lid’ region of the oncoprotein MDM2. Calorimetric measurements revealed that truncation of the lid region of MDM2 increases the apparent dissociation constant of AM-7209 250-fold. By contrast, lid truncation has little effect on the binding of the ligand Nutlin-3a. Insights into these differential binding energetics were obtained via a complete thermodynamic analysis that featured adaptive absolute alchemical free energy of binding calculations with enhanced-sampling molecular dynamics simulations. The simulations reveal that in apo MDM2 the ordered lid state is energetically disfavoured. AM-7209, but not Nutlin-3a, shows a significant energetic preference for ordered lid conformations, thus shifting the balance towards ordering of the lid in the AM-7209/MDM2 complex. The methodology reported herein should facilitate broader targeting of intrinsically disordered regions in medicinal chemistry.
Genes for tRNA recycling are upregulated in response to infection with Theiler’s mouse encephalitis virus
Authors: Seki Mineaki , Komuro Akihiko , Ishikawa Tatsuya , Takahashi Masayuki , Nashimoto Masayuki 
Published: August 2021

ABSTRACTThe concept of tRNA recycling has recently emerged from the studies of ribosome-associated quality control. Therein tRNase ZS removes the 2′, 3′>p from the ANKZF1-cleaved tRNA and the subsequent TRNT1 action re-generates the intact tRNA. To know the roles of the tRNA recycling in vivo, we investigated how viral infection affects the tRNA recycling system by analyzing the mRNA levels of tRNase ZS and TRNT1. We found that both genes in HeLa cells are upregulated in response to infection of Theiler’s mouse encephalitis virus but not to that of an influenza A virus. Upregulation was also observed in cells infected with encephalomyocarditis virus with reduced efficiency. The levels of the IFN-β mRNA appeared to positively correlate with those of the tRNase ZS and TRNT1 mRNAs. The tRNase ZS gene may be regulated post-transcriptionally in the cells infected with Theiler’s mouse encephalitis virus.
Cellular heterogeneity and molecular reprogramming of host response during influenza acute lung injury
Authors: Guo Kai , Kalenda Yombo Dan Justin , Schmit Taylor , Wang Zhihan , Ghosh Sumit , Sathish Venkatachelem , Mathur Ramkumar , Wu Min , Hur Junguk , Khan M. Nadeem 
Published: August 2021

AbstractAcute lung injury (ALI) caused by influenza A virus (IAV or influenza) manifests from dysregulated cellular interactions between hematopoietic and non-hematopoietic cells that develop into a pathologic host response. However, the lung’s diverse cellular framework that dictates the pathologic host response and acute lung injury remains incompletely understood. We performed a single-cell RNA-seq (scRNA-seq) analysis of total lung cells in mice from severe influenza to examine the cellular heterogeneity and cell-specific regulation of host response. We observed that IAV infection resulted in significant myelopoiesis, predominantly monocyte, and macrophage subsets, which constituted over 50% of total immune cells. IAV infection resulted in the significant loss of endothelial and fibroblast cells, representing the most predominant non-hematopoietic cells and crucial to regulating inflammatory response and barrier integrity. We also show the cell-cell communication dynamics of interferon and chemokine signaling and global regulation of these responses in transition from homeostatic to IAV infection state. These data highlight a robust application of scRNA-seq technology in establishing the atlas of cellular heterogeneity from its homeostatic transition to infection state and the host response regulation in IAV-mediated lung pathology.
Evolution-Inspired Engineering of Anthracycline Methyltransferases
Authors: Dinis Pedro , Tirkkonen Heli , Wandi Benjamin Nji , Siitonen Vilja , Niemi Jarmo , Grocholski Thadée , Metsä-Ketelä Mikko 
Published: August 2021

AbstractStreptomyces soil bacteria produce hundreds of anthracycline anticancer agents with a relatively conserved set of genes. This diversity depends on the rapid evolution of biosynthetic enzymes to acquire novel functionalities. Previous work has identified S-adenosyl-L-methionine-dependent methyltransferase-like proteins that catalyze either 4-O-methylation, 10-decarboxylation or 10-hydroxylation, with additional differences in substrate specificities. Here we focused on four protein regions to generate chimeric enzymes using sequences from four distinct subfamilies to elucidate their influence in catalysis. Combined with structural studies we managed to depict factors that influence gain-of-hydroxylation, loss-of-methylation and substrate selection. The engineering expanded the catalytic repertoire to include novel 9,10-elimination activity, and 4-O-methylation and 10-decarboxylation of unnatural substrates. The work provides an instructive account on how the rise of diversity of microbial natural products may occur through subtle changes in biosynthetic enzymes.
Direct reprogramming of human fibroblasts into insulin-producing cells by transcription factors
Authors: Fontcuberta-PiSunyer Marta , García-Alamán Ainhoa , Prades Èlia , Téllez Noèlia , Figueiredo Hugo , Fernandez-Ruiz Rebeca , Cervantes Sara , Enrich Carlos , Clua Laura , Ramón-Azcón Javier , Broca Christophe , Wojtusciszyn Anne , Novials Anna , Montserrat Nuria , Vidal Josep , Gomis Ramon , Gasa Rosa 
Published: August 2021

ABSTRACTDirect lineage reprogramming of one somatic cell into another bypassing an intermediate pluripotent state has emerged as an alternative to embryonic or induced pluripotent stem cell differentiation to generate clinically relevant cell types. One cell type of clinical interest is the pancreatic β cell that secretes insulin and whose loss and/or dysfunction leads to diabetes. Generation of functional β-like cells from developmentally related somatic cell types (pancreas, liver, gut) has been achieved via enforced expression of defined sets of transcription factors. However, clinical applicability of these findings is challenging because the starting cell types are not easily obtainable. Skin fibroblasts are accessible and easily manipulated cells that could be a better option, but available studies indicate that their competence to give rise to β cells through similar direct reprogramming approaches is limited. Here, using human skin fibroblasts and a protocol that ensures high and consistent expression of adenovirus-encoded reprogramming factors, we show that the transcription factor cocktail consisting of Pdx1, Ngn3, MafA, Pax4 and Nkx2-2 activates key β cell genes and down-regulates the fibroblast transcriptional program. The converted cells produce insulin and exhibit intracellular calcium responses to glucose and/or membrane depolarization. Furthermore, they secrete insulin in response to glucose in vitro and after transplantation in vivo. These findings demonstrate that transcription factor-mediated direct reprogramming of human fibroblasts is a feasible strategy to generate insulin-producing cells.
Cancer Cells Viscoelasticity Measurement by Quantitative Phase and Flow Stress Induction
Authors: Vicar Tomas , Gumulec Jaromir , Chmelik Jiri , Navratil Jiri , Kolar Radim , Chmelikova Larisa , Cmiel Vratislav , Provaznik Ivo , Masarik Michal 
Published: August 2021

ABSTRACTCell viscoelastic properties are affected by the cell cycle, differentiation, pathological processes such as malignant transformation. Therefore, evaluation of the mechanical properties of the cells proved to be an approach to obtaining information on the functional state of the cells. Most of the currently used methods for cell mechanophenotypisation are limited by low robustness or the need for highly expert operation. In this paper, the system and method for viscoelasticity measurement using shear stress induction by fluid flow is described and tested. Quantitative Phase Imaging (QPI) is used for image acquisition because this technique enables to quantify optical path length delays introduced by the sample, thus providing a label-free objective measure of morphology and dynamics. Viscosity and elasticity determination were refined using a new approach based on the linear system model and parametric deconvolution. The proposed method allows high-throughput measurements during live cell experiments and even through a time-lapse, where we demonstrated the possibility of simultaneous extraction of shear modulus, viscosity, cell morphology, and QPI-derived cell parameters like circularity or cell mass. Additionally, the proposed method provides a simple approach to measure cell refractive index with the same setup, which is required for reliable cell height measurement with QPI, an essential parameter for viscoelasticity calculation. Reliability of the proposed viscoelasticity measurement system was tested in several experiments including cell types of different Young/shear modulus and treatment with cytochalasin D or docetaxel, and an agreement with atomic force microscopy was observed. The applicability of the proposed approach was also confirmed by a time-lapse experiment with cytochalasin D washout, where an increase of stiffness corresponded to actin repolymerisation in time.SIGNIFICANCEWe present an approach for viscoelasticity measurement using QPI and shear stress induction by fluid flow. Our system builds and extends a recently published approach by parametric deconvolution, which allows us to eliminate the influence of the fluidic system and reliably measure both the shear modulus and viscosity of the cells in high throughput. Additionally, the proposed method enables to simultaneously determine cell refractive index map, cell dry mass map, and morphology, thereby enabling a multimodal cellular characterisation in a single measurement.
EnGRNT: Inference of gene regulatory networks using ensemble methods and topological feature extraction
Authors: Khojasteh Hakimeh , Olyaee Mohammad Hossein , Khanteymoori Alireza 
Published: August 2021

AbstractThe development of computational methods to predict gene regulatory networks (GRNs) from gene expression data is a challenging task. Many machine learning methods have been developed, including supervised, unsupervised, and semi-supervised to infer gene regulatory networks. Most of these methods ignore the class imbalance problem which can lead to decreasing the accuracy of predicting regulatory interactions in the network. Therefore, developing an effective method considering imbalanced data is a challenging task. In this paper, we propose EnGRNT approach to infer GRNs with high accuracy that uses ensemble-based methods. The proposed approach, as well as the gene expression data, considers the topological features of GRN. We applied our approach to the simulated Escherichia coli dataset. Experimental results demonstrate that the appropriateness of the inference method relies on the size and type of expression profiles in microarray data. Except for multifactorial experimental conditions, the proposed approach outperforms unsupervised methods. The obtained results recommend the application of EnGRNT on the imbalanced datasets.