bluuebunny/crossref_metadata_2025_split huggingface dataset:
Quantification of bacterial DNA in blood using droplet digital PCR: a pilot study
Authors: Tedim Ana P. , Merino Irene , Ortega Alicia , Domínguez-Gil Marta , Eiros José Maria , Bermejo-Martín Jesús F. 
Published: December 2022

AbstractAimTo use genus/species-specific genes droplet digital PCR (ddPCR) assays to detect/quantify bacterial DNA fromEscherichia coli,Klebsiella pneumoniae,Staphylococcus aureusandEnterococcusspp in blood samples.Methods and ResultsBacterial DNA from clinical strains (4<n<12) was extracted, quantified and diluted (10-0.0001ng/μL) and ddPCR assays were performed in triplicate. These ddPCR assays showed low replication variability, low detection limit (1–0.1pg/μL) and high genus/species specificity. ddPCR assays were also used to quantify bacterial DNA obtained from spiked blood (1×104-1CFU/mL) of each bacterial genus/species. Comparison between ddPCR assays and bacterial culture was performed by Pearson correlation. There was an almost perfect correlation (r≥0.997, p≤0.001) between the number of CFU/mL from bacterial culture and the number of gene copies/mL detected by ddPCR. The time from sample preparation to results was determined to be 3.5-4h.ConclusionsThe results demonstrated the quantification capacity and specificity of the ddPCR assays to detect/quantify four of the most important bloodstream infection (BSI) bacterial pathogens directly from blood.Significance and ImpactThis pilot study results reinforce the potential of ddPCR for the diagnosis and/or severity stratification of BSI. Applied to patients’ blood samples it can improve diagnosis and diminish sample-to-results time, improving patient care.
Chloroplast DNA methylation in the kelpSaccharina latissimais determined by origin and influenced by cultivation
Authors: Scheschonk Lydia , Nilsen Anne M.L. , Bischof Kai , Jueterbock Alexander 
Published: December 2022

AbstractDNA cytosine methylation is an important epigenetic mechanism in genomic DNA, but absent in the chloroplast DNA of most land plants. We detected methylation in the chloroplast DNA of the kelpSaccharina latissima, a non-model macroalgal species of high ecological (wild populations) and economic importance. Since the functional role of the chloroplast methylome is yet largely unknown, we compared for the first time the chloroplast DNA cytosine methylation between wild and cultured kelp from different climatic origins (High- Arctic (79 °N) and temperate (54 °N), laboratory samples at 5 °C, 10 °C and 15 °C). Our results suggest genome-wide differences in methylated sites, and methylation level, between the origins, and a strong effect of cultivation. Functions related to photosynthesis showed differential methylation only between origins. Significant differences in methylation between cultivated and wild samples of genes related to transcription and translation were unique to the high-arctic samples. Both findings indicate that origin and cultivation strongly, but differently affect the chloroplast methylome. Similar methylomes for samples from the same origin – independent from whether they grow in the wild or in the lab – suggest that origin- specific methylation marks on the chloroplast genome are inherited. Given that DNA- methylation affects gene expression, our study suggests that lab-cultivation alters epigenetically determined kelp chloroplast characteristics at least to the same degree as ecotypic differentiation does, but likely on a much shorter timescale. This indicates the capacity for rapid non-genetic adaptation in the kelpSaccharina latissima.
CRMnet: a deep learning model for predicting gene expression from large regulatory sequence datasets
Authors: Ding Ke , Dixit Gunjan , Parker Brian J. , Wen Jiayu 
Published: December 2022

ABSTRACTRecent large datasets measuring the gene expression of millions of possible gene promoter sequences provide a resource to design and train optimised deep neural network architectures to predict expression from sequences. High predictive performance due to the modelling of dependencies within and between regulatory sequences is an enabler for biological discoveries in gene regulation through model interpretation techniques.To understand the regulatory code that delineates gene expression, we have designed a novel deep-learning model (CRMnet) to predict gene expression inSaccharomyces cerevisiae. Our model outperforms the current benchmark models and achieves a Pearson correlation coefficient of 0.971. Interpretation of informative genomic regions determined from model saliency maps, and overlapping the saliency maps with known yeast motifs, support that our model can successfully locate the binding sites of transcription factors that actively modulate gene expression. We compare our model’s training times on a large compute cluster with GPUs and Google TPUs to indicate practical training times on similar datasets.
Effect of rectified gap junctional electrical coupling and spatial distribution of biologically engineered pacemaking cells on ventricular excitation
Authors: Li Yacong , Li Qince , Liu Jun , Ma Lei , Wang Kuanquan , Zhang Henggui 
Published: December 2022

AbstractAimBiologically engineered pacemaker, or bio-pacemaker, is a promising replacement for electronic pacemakers for treating cardiac dysfunction. Previous animal experimental studies, however, have not been able to accurately demonstrate the stability and efficiency of the bio-pacemaker yet. This study aimed to elucidate the underlying factors that affect bio-pacemaker’s performance and to discover possible optimising solutions to enable the potential use of bio-pacemaker therapy.Methods and resultsThe human ventricular myocytes model in this study followed the ten Tussucher’s model in 2006, and the bio-pacemaker single cell model was modified based on it as what has been expatiated in our previous work. In tissue model, two factors were primarily evaluated for their effects on bio-pacemakers to pace and drive surrounding cardiac tissue: gap junction between bio-pacemaker cells (PMs) and adjacent ventricular myocytes (VMs) and the spatial distribution of bio-pacemakers. A suppressed gap junctional electrical coupling between and heterotypic gap junctions were simulated and a combination of them led to the best performance of the bio-pacemaker. Then, the pacemaking behaviours of three kinds of idealised PM-VM slices were simulated, in which an electrically isolated distribution of bio-pacemaker showed optimal drive capacities. Finally, a real human ventricular slice model was used to verified the conclusions in idealized tissues.ConclusionThis study develops a theory that weak-rectified electrical coupling and electrically isolated distribution can enhance the pacemaking efficiency of bio-pacemakers, which lays the groundwork for future research into therapeutic applications of bio-pacemakers.Author summaryBiologically engineered pacemakers are expected to be a substitute for electronic pacemakers because of their physiological superiority, but how to transform them for practical application remains challenging. In this paper, we presented a theoretical perspective on optimising biological pacemaking capability based on a computational simulation approach. By manipulating the gap junctional electrical coupling among bio-pacemaking cells and between the pacemaker and their surrounding cells, and controlling spatial distribution of bio-pacemaker, we demonstrated that an enhanced capacity of a bio-pacemaker can be achieved. The results of this study may provide a theoretical basis for the further clinical development of bio-pacemakers.
Identification of a forkhead box protein transcriptional network induced in human neutrophils in response to inflammatory stimuli
Authors: Ismailova Aiten , Salehi-Tabar Reyhaneh , Dimitrov Vassil , Memari Babak , Barbier Camille , White John H. 
Published: December 2022

AbstractNeutrophils represent the largest proportion of circulating leukocytes and, in response to inflammatory stimuli, are rapidly recruited to sites of infection where they neutralize pathogens. We have identified a novel neutrophil transcription network induced in response to inflammatory stimuli. We performed the first RNAseq analysis of human neutrophils exposed to lipopolysaccharide (LPS), followed by a meta-analysis of our dataset and previously published studies of LPS-challenged neutrophils. This revealed a robustly enhanced transcriptional network driven by forkhead box (FOX) transcription factors. The network is enriched in genes encoding proinflammatory cytokines and transcription factors, includingMAFFandATF3, which are implicated in responses to stress, survival and inflammation. Expression of transcription factors FOXP1 and FOXP4 is induced in neutrophils exposed to inflammatory stimuli, and potential FOXP1/FOXP4 binding sites were identified in several genes in the network, all located in chromatin regions consistent with neutrophil enhancer function. Chromatin immunoprecipitation (ChIP) assays in neutrophils confirmed enhanced binding of FOXP4, but not FOXP1, to multiple sites in response to LPS. Binding to numerous motifs and transactivation of network genes were also observed when FOXP proteins were transiently expressed in HEK293 cells. In addition to LPS, the transcriptional network is induced by other inflammatory stimuli, indicating it represents a general neutrophil response to inflammation. Collectively, these findings reveal a role for the FOXP4 transcription network as a regulator of responses to inflammatory stimuli in neutrophils.Author SummaryIn response to pathogens, neutrophils, the most abundant white blood cells in the body, are the first to be recruited to sites of infection. However, defects in neutrophil responses lead to common chronic inflammatory conditions such as atherosclerosis, chronic obstructive lung disease and autoimmune disorders. As such, it is critical to uncover the molecular players implicated in neutrophil responses to signals that induce inflammation. Here we profile how bacterial lipopolysaccharide (LPS), which is derived from the cell walls of bacteria and is a commonly used agent to mimic inflammation, alters gene transcription in isolated human neutrophils. We also combined our data with those of other published studies to identify conserved molecular pathways stimulated in LPS-exposed neutrophils. This analysis revealed a network of genes whose transcription is regulated by members of the so-called forkhead box (FOX) transcription factors. We provide evidence that FOXP4 regulates transcription of genes within the network in neutrophils. We also find that the same network of genes is induced by other inflammatory stimuli, suggesting it plays a role in neutrophil responses to inflammation.
Phenotype-based single-cell transcriptomics reveal compensatory pathways involved in Golgi organization and associated transport
Authors: Singh Sanjana , Zukowska Joanna , Halavatyi Aliaksandr , Landry Jonathan J. M. , Pepperkok Rainer 
Published: December 2022

AbstractThe Golgi is a dynamic organelle with a unique morphology that has implications on its function. How the structural integrity of the Golgi is maintained despite its dynamic nature has been a long-standing question. Several siRNA-based screens have addressed this question and have identified a number of key players required for Golgi integrity. Interestingly, they also reported heterogeneity of phenotypic responses with regards to Golgi morphology. Although never systematically investigated, this variability has generally been attributed to poor transfection efficiency or cell cycle specific responses. Here we show that this heterogeneity is the result of differential response to the siRNA knockdown in different Golgi phenotypes, independent of transfection efficiency or cell cycle phases. To characterize the observed Golgi phenotype-specific responses at the molecular level we have developed an automated assay which enables microscopy-based phenotype classification followed by phenotype-specific single-cell transcriptome analysis. Application of this novel approach to the siRNA mediated knockdown of USO1, a key trafficking protein at the ER to Golgi boundary, surprisingly suggests a key involvement of the late endosomal/endocytic pathways in the regulation of Golgi organization. Our pipeline is the first of its kind developed to study Golgi organization, but can be applied to any biological problem that stands to gain from correlating morphology with single-cell readouts. Moreover, its automated and modular nature allows for uncomplicated scaling up, both in throughput and in complexity, helping the user achieve a systems level understanding of cellular processes.
Estimating the fitness cost and benefit of antimicrobial resistance from pathogen genomic data
Authors: Helekal David , Keeling Matt , Grad Yonatan H , Didelot Xavier 
Published: December 2022

ABSTRACTIncreasing levels of antibiotic resistance in many bacterial pathogen populations is a major threat to public health. Resistance to an antibiotic provides a fitness benefit when the bacteria is exposed to this antibiotic, but resistance also often comes at a cost to the resistant pathogen relative to susceptible counterparts. We lack a good understanding of these benefits and costs of resistance for many bacterial pathogens and antibiotics, but estimating them could lead to better use of antibiotics in a way that reduces or prevents the spread of resistance. Here, we propose a new model for the joint epidemiology of susceptible and resistant variants, which includes explicit parameters for the cost and benefit of resistance. We show how Bayesian inference can be performed under this model using phylogenetic data from susceptible and resistant lineages and that by combining data from both we are able to disentangle and estimate the resistance cost and benefit parameters separately. We applied our inferential methodology to several simulated datasets to demonstrate good scalability and accuracy. We analysed a dataset ofNeisseria gonorrhoeaegenomes collected between 2000 and 2013 in the USA. We found that two unrelated lineages resistant to fluoroquinolones shared similar epidemic dynamics and resistance parameters. Fluoroquinolones were abandoned for the treatment of gonorrhoea due to increasing levels of resistance, but our results suggest that they could be used to treat a minority of around 10% of cases without causing resistance to grow again.
Molecular signatures of alternative fitness strategies in a facultatively social hover wasp
Authors: Taylor Benjamin A. , Taylor Daisy , Bodrug-Schepers Alexandrina , Câmara Ferreira Francisco , Stralis-Pavese Nancy , Himmelbauer Heinz , Guigó Roderic , Reuter Max , Sumner Seirian 
Published: December 2022

AbstractSocial insect queens and workers represent ideal models with which to understand the expression and regulation of alternative reproductive phenotypes. Most research in this area has focused on the molecular regulation of reproductive castes in obligately social taxa with complex social systems, while relatively few studies have addressed the molecular basis of caste in species in which the division of reproductive labour is more plastic. As a result, it is not clear whether, and to what extent, the mechanisms of caste in species with reproductive plasticity are the same as those that exist at the highest levels of social complexity. To address this knowledge gap, we analyse brain transcriptomic data for non-reproductives and reproductives of the facultatively social hover wasp Liostenogaster flavolineata, a representative of one of the simplest forms of social living. By experimentally manipulating the reproductive ‘queues’ exhibited by social groups of this species, we show that reproductive division of labour in this species is associated with surprisingly distinct transcriptomic signatures, similar to those observed in more complex social taxa; that variation in gene expression among non-reproductives reflects their investment into foraging effort more than their social rank; and that distinct co-expressed gene sets are associated with differential investment into alternative reproductive strategies. These results elucidate robust transcriptomic signals that represent the proximate basis of division of labour at the simplest level of insect sociality, and show these signals to be remarkably similar to those in more derived species.
Accurate quantification of single-cell and single-nucleus RNA-seq transcripts using distinguishing flanking k-mers
Authors: Eldjárn Hjörleifsson Kristján , Sullivan Delaney K. , Swarna Nikhila P. , Holley Guillaume , Melsted Páll , Pachter Lior 
Published: December 2022

AbstractIn single-cell and single-nucleus RNA sequencing, the coexistence of nascent (unprocessed) and mature (processed) mRNA poses challenges in accurate read mapping and the interpretation of count matrices. The traditional transcriptome reference, defining the ‘region of interest’ in bulk RNA-seq, restricts its focus to mature mRNA transcripts. This restriction leads to two problems: reads originating outside of the ‘region of interest’ are prone to mismapping within this region, and additionally, such external reads cannot be matched to specific transcript targets. Expanding the ‘region of interest’ to encompass both nascent and mature mRNA transcript targets provides a more comprehensive framework for RNA-seq analysis. Here, we introduce the concept of distinguishing flankingk-mers (DFKs) to improve mapping of sequencing reads. We have developed an algorithm to identify DFKs, which serve as a sophisticated ‘background filter’, enhancing the accuracy of mRNA quantification. This dual strategy of an expanded region of interest coupled with the use of DFKs enhances the precision in quantifying both mature and nascent mRNA molecules, as well as in delineating reads of ambiguous status.
Posterior marginalization accelerates Bayesian inference for dynamical systems
Authors: Raimúndez Elba , Fedders Michael , Hasenauer Jan 
Published: December 2022

AbstractBayesian inference is an important method in the life and natural sciences for learning from data. It provides information about parameter uncertainties, and thereby the reliability of models and their predictions. Yet, generating representative samples from the Bayesian posterior distribution is often computationally challenging. Here, we present an approach that lowers the computational complexity of sample generation for problems with scaling, offset and noise parameters. The proposed method is based on the marginalization of the posterior distribution, which reduces the dimensionality of the sampling problem. We provide analytical results for a broad class of problems and show that the method is suitable for a large number of applications. Subsequently, we demonstrate the benefit of the approach for various application examples from the field of systems biology. We report a substantial improvement up to 50 times in the effective sample size per unit of time, in particular when applied to multi-modal posterior problems. As the scheme is broadly applicable, it will facilitate Bayesian inference in different research fields.
Waterlogging shifts ontogenic hormone dynamics in tomato leaves and petioles
Authors: Geldhof B. , Novák O. , Van de Poel B. 
Published: December 2022

AbstractWaterlogging leads to hypoxic conditions in the root zone that subsequently cause systemic adaptive responses in the shoot, including leaf epinasty. Waterlogging-induced epinasty in tomato has long been ascribed to the coordinated action of ethylene and auxins. However, other hormonal signals have largely been neglected, despite evidence of their importance in leaf posture control. To adequately cover a large group of growth regulators, we performed a tissue-specific and time-dependent hormonomics analysis. This analysis revealed that multiple hormones are differentially affected throughout a 48 h waterlogging treatment, and, more importantly, that leaf development defines a framework in which this hormonal control is regulated. In addition, we could distinguish early hormonal signals that might contribute to fast responses towards oxygen deprivation from those that potentially sustain the waterlogging response. For example, abscisic acid (ABA) levels peak in petioles within the first 12 h of the treatment, while its metabolites only rise much later, suggesting ABA transport is altered. At the same time, cytokinins (CK) and their derivatives drastically decline during waterlogging in leaves of all ages. This drop in CK possibly releases the inhibition of ethylene and auxin mediated cell elongation to establish epinastic bending. Auxins themselves rise substantially in the petiole of mature leaves, but mostly after 48 h of root hypoxia. Based on our hormone profiling, we propose that ethylene and ABA might act synergistically to dynamically fine-tune the balance of IAA and CK in the petiole, ultimately leading to differential growth and epinasty during waterlogging.
The Utility of Ancestral and Derived Allele Sharing for Genome-Wide Inferences of Introgression
Authors: Peede David , Ortega-Del Vecchyo Diego , Huerta-Sánchez Emilia 
Published: December 2022

AbstractThe past decade has ushered in a resurgence of studies highlighting the importance of introgression throughout the Tree of Life. Several methods exist for detecting and quantifying introgression on a genomic scale, yet the majority of these methods primarily utilize signals of derived allele sharing between donor and recipient populations. In this study, we exploit the fact that introgression will not only result in derived allele sharing but also the reintroduction of ancestral alleles to derive new estimators of the admixture proportion. Using coalescent simulations, we assess the performance of our new methods and the methods proposed inLopez Fang et al. 2022to assess the utility of incorporating shared ancestral variation into genome-wide inferences of introgression. Using coalescent theory, simulations, and applying our methods to human and canid data, we find that methods incorporating ancestral allele sharing are comparable to their derived allele sharing counterparts, in turn providing researchers with the opportunity to utilize more of the genomic signature of introgression.
From a different angle: genetic diversity underlies differentiation of waterlogging-induced epinasty in tomato
Authors: Geldhof B. , Pattyn J. , Van de Poel B. 
Published: December 2022

AbstractIn tomato, downward leaf bending is a morphological adaptation towards waterlogging, which has been shown to induce a range of metabolic and hormonal changes. This kind of functional trait is often the result of a complex interplay of regulatory processes starting at the gene level, gated through a plethora of signaling cascades and modulated by environmental cues. Through phenotypical screening of a population of 54 tomato accessions in a Genome Wide Association Study (GWAS), we have identified target genes potentially involved in plant growth and survival during waterlogging and subsequent recovery. Changes in both plant growth rate and epinastic descriptors revealed several associations to genes possibly supporting metabolic activity in low oxygen conditions in the root zone. In addition to this general reprogramming, some of the targets were specifically associated to leaf angle dynamics, indicating these genes might play a role in the induction, maintenance or recovery of differential petiole elongation in tomato during waterlogging.