bluuebunny/crossref_metadata_2025_split huggingface dataset:
Inference of differential gene regulatory networks from gene expression data using boosted differential trees
Authors: Galindez Gihanna , List Markus , Baumbach Jan , Blumenthal David B. , Kacprowski Tim 
Published: September 2022

AbstractDiseases can be caused by molecular perturbations that induce specific changes in regulatory interactions and their coordinated expression, also referred to as network rewiring. However, the detection of complex changes in regulatory connections remains a challenging task and would benefit from the development of novel non-parametric approaches. We developed a new ensemble method called BoostDiff (boosted differential regression trees) to infer a differential network discriminating between two conditions. BoostDiff builds an adaptively boosted (AdaBoost) ensemble of differential trees with respect to a target condition. To build the differential trees, we propose differential variance improvement as a novel splitting criterion. Variable importance measures derived from the resulting models are used to reflect changes in gene expression predictability and to build the output differential networks. BoostDiff outperforms existing differential network methods on simulated data evaluated in two different complexity settings. We then demonstrate the power of our approach when applied to real transcriptomics data in COVID-19 and Crohn’s disease. BoostDiff identifies context-specific networks that are enriched with genes of known disease-relevant pathways and complements standard differential expression analyses. BoostDiff is available athttps://github.com/gihannagalindez/boostdiff_inference.Author SummaryGene regulatory networks, which comprise the collection of regulatory relationships between transcription factors and their target genes, are important for controlling various molecular processes. Diseases can induce perturbations in normal gene co-expression patterns in these networks. Detecting differentially co-expressed or rewired edges between disease and healthy biological states can be thus useful for investigating the link between specific disease-associated molecular alterations and phenotype. We developed BoostDiff (boosted differential trees), an ensemble method to derive differential networks between two biological contexts. Our approach applies a boosting scheme using differential trees as base learner. A differential tree is a new tree structure that is built from two expression datasets using a splitting criterion called the differential variance improvement. The resulting BoostDiff model learns the most differentially predictive features which are then used to build the directed differential networks. BoostDiff outperforms other differential network methods on simulated data and outputs more biologically meaningful results when evaluated on real transcriptomics datasets. BoostDiff can be applied to gene expression data to reveal new disease mechanisms or identify potential therapeutic targets.
Nanobodies for the treatment of SARS-CoV-2 in animals: a meta-analysis
Authors: Jiao Jiao , Lin Shulan , Liang Zhenqi , Wu Peng 
Published: September 2022

AbstractThis meta-analysis aimed to find the effect of variable domain of heavy-chain antibodies (VHHs) for the treatment of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) in animals. The databases of the PubMed, China National Knowledge Infrastructure (CNKI), Wan fang data, Cochrane Library, and Embase were searched for articles published before August 2022 on the protective effects of VHHs in animals. The articles retrieved were screened using inclusion and exclusion criteria. The data were analyzed using Review Manager 5.4. Six articles were selected from 667 articles based on the inclusion and exclusion criteria in VHHs. A forest plot showed that VHHs could offer protection against SARS-CoV-2 infection in animals [Mantel-Haenszel (MH) = 172.94, 95% confidence interval (CI) = (43.96, 678.42), P < 0.00001]. There was almost no heterogeneity in this study (I2 = 0). A funnel plot showed that the bias of the data analysis was small. This is a special meta-analysis proved that VHHs could treat and prevent SARS-CoV-2 in animals.
Rejuvenation strategies share gene expression programs of reduced inflammation and downstream restored fatty acid metabolism
Authors: Landsberger Tomer , Amit Ido , Alon Uri 
Published: September 2022

AbstractUnderstanding the mechanism of rejuvenation is central to aging research. No study has compared the effects of the four major rejuvenation strategies: senolytics, caloric restriction,in vivopartial cellular reprogramming and young/old blood factor exchange, which operate via different modalities. We use mice transcriptional data to compare them to each other and to normal aging. We find a shared gene expression program common to all rejuvenation strategies, in which inflammation declines and metabolism, especially of fatty acids, increases. An inverse signature occurs in normal aging. To test whether inflammation is upstream of the metabolic signature, we studied chronic inflammation in three different organs in young mice. Chronic inflammation was associated with a similar decline in metabolism, suggesting that inflammation is upstream of the metabolic signature. We find that inflammation may also underlie human transcriptional age calculator. We conclude that a core mechanism of rejuvenation acts through reduction of inflammation with downstream effects that enhance metabolism, attenuating the most robust age-related changes. This supports a notion of directly targeting genes associated with these pathways to mitigate age-related deterioration.
Prorenin from renal tubules is a major driver of diabetic kidney disease
Authors: Federlein Anna , Lehrmann Claudia , Tauber Philipp , Todorov Vladimir , Schweda Frank 
Published: September 2022

AbstractThe renin-angiotensin-system (RAS) plays a critical role in diabetic nephropathy, and inhibitors of the RAS are central components in its therapy. Renin circulates in the blood in its active form but also in the form of its enzymatically inactive precursor prorenin. In humans, the plasma prorenin concentration exceeds that of active renin several times. While the plasma concentration of active renin is unchanged or even reduced in diabetic patients, the prorenin concentration increases significantly and it has been shown that high prorenin levels are associated with diabetic microvascular damage. Why prorenin increases in diabetes while active renin is reduced is unclear. Previous studies suggest that there may be formation of prorenin in the tubular system of diabetic kidneys. To investigate the functional consequences of possible tubular renin formation in diabetes, we generated mice with inducible tubule-specific deletion of the renin gene (tubule-renin KO).Under control conditions, tubule-renin KO had no apparent phenotype and plasma and tissue levels of renin and prorenin were similar to those of mice with intact tubular renin (control mice). In control mice type-1 diabetes (streptozotocin, STZ) for 8 to 12 weeks stimulated tubular renin mRNA and protein expression, especially in distal nephron segments including collecting ducts. This increase in renin synthesis in renal tubules was markedly attenuated or even absent in tubule-renin KO mice. Similar to diabetic patients, plasma prorenin was markedly elevated in diabetic control mice. This stimulation of plasma prorenin was absent in mice with tubule-specific deletion of the renin gene. Moreover, the high prorenin levels in renal tissue, which were observed in diabetic control mice, were markedly reduced in tubule-renin KO. Noteworthy, plasma renin activity was not reduced in tubule-renin KO compared with controls, suggesting that renal tubules of diabetic mice mainly release prorenin. Kidneys of control mice with intact tubular renin showed classical signs of diabetic renal damage, such as albuminuria, mesangial expansion, fibrosis, inflammation and capillary rarefaction. All of these parameters were significantly ameliorated in tubule-renin KO, indicating that tubular renin, most likely in its prorenin form, significantly aggravates renal damage in diabetes.These data provide clear evidence for the first time that the tubular renin system is an additional source for circulating prorenin in diabetes, hereby providing an explanation for the paradox regulation of active renin and prorenin in diabetes. Moreover, the data show that tubular renin markedly contributes to the progression of diabetic nephropathy.
IBRAP: Integrated Benchmarking Single-cell RNA-sequencing Analytical Pipeline
Authors: Knight Connor H. , Khan Faraz , Gill Upkar , Wang Jun 
Published: September 2022

AbstractSingle-cell RNA-sequencing (scRNA-seq) is a powerful tool to study cellular heterogeneity. The high dimensional data generated from this technology are complex and require specialised expertise for analysis and interpretation. The core of scRNA-seq data analysis contains several key analytical steps, which include pre-processing, QC, normalisation, dimensionality reduction, integration, and clustering. Each step often has many algorithms developed with varied underlying assumptions and implications. With such a diverse choice of tools available, benchmarking analyses have compared their performances and demonstrated that tools differentially operate according to the data types and complexity. Here, we present Integrated Benchmarking scRNA-seq Analytical Pipeline (IBRAP) – a tool, which contains a range of analytical components that can be interchanged throughout the pipeline alongside multiple benchmarking metrics that enables users to compare results and determine the optimal pipeline combinations for their data. We apply IBRAP to single and multi-sample integration analysis using pancreas, cell line and simulated data accompanied with ground truth cell labels, demonstrating the interchangeable and benchmarking functionality of IBRAP. Our results confirm that the optimal pipelines are dependant of individual samples and studies, further supporting the rationale and necessity of our tool. We then compare reference-based cell annotation with unsupervised analysis, both included in IBRAP, and demonstrate the superiority of the reference-based method in identifying robust major and minor cell types. Thus, IBRAP presents a valuable tool to integrate multiple samples and studies to create reference maps of normal and diseased tissues, facilitating novel biological discovery using the vast volume of scRNA-seq data available.
Sequencing of Monkeypox virus from infected patients reveals viral genomes with APOBEC3-like editing, gene inactivation, and bacterial agents of skin superinfection
Authors: Colson Philippe , Penant Gwilherm , Delerce Jeremy , Boschi Céline , Wurtz Nathalie , Branger Stéphanie , Lagier Jean-Christophe , Cassir Nadim , Tissot-Dupont Hervé , Million Matthieu , Aherfi Sarah , Scola Bernard LA 
Published: September 2022

AbstractAn epidemic of Monkeypox virus (MPX virus) infections has arisen in May 2022 in non-endemic countries particularly in Europe among men having sex with men, whose extent is unprecedented. Since May 2022 we implemented MPX virus diagnosis by real-time PCR at university hospitals of Marseille, southern France. Here, we performed DNA metagenomic analyses of clinical samples from MPX virus-infected patients between June and July 2022, using next-generation sequencing with Illumina or Nanopore technologies. Twenty-five samples from 25 patients were studied. This allowed obtaining a MPX virus genome for 18 patients, essentially from genital skin lesions and rectal swabbing. All 18 genomes were classified in the MPX virus B.1 lineage, and we delineated five sublineages (A-E). We detected a high number of mutations (66-73) scattered along the MPX virus genomes relatively to the genome obtained from a human in Nigeria in 2018. Some non-synonymous mutations occurred in genes encoding central proteins, among which transcription factors and core and envelope proteins. They included two mutations that truncate RNA polymerase subunit RPO132 and a phospholipase D-like protein, which suggests gene inactivation. In addition, we identified that a large majority of nucleotide substitutions (94%) in the 18 MPX virus genomes were G>A or C>T, suggesting the action of human APOBEC3 enzymes. Finally, while we did not detect reads matching with main bacterial agents of sexually transmitted infections, >1,000 reads identified Staphylococcus aureus and Streptococcus pyogenes for 7 and 17 samples, respectively. These findings warrant a close genomic monitoring of MPX virus to get a better picture of this virus’ genetic evolution and mutational patterns, and they point out the common presence in monkeypox lesions of bacterial agents of skin superinfection, which warrants a close clinical monitoring in monkeypox patients.
PBP1A directly interacts with the divisome complex to promote septal peptidoglycan synthesis in Acinetobacter baumannii
Authors: Kang Katie N. , Boll Joseph M. 
Published: September 2022

AbstractThe class A penicillin-binding proteins (aPBPs), PBP1A and PBP1B, are major peptidoglycan synthases that synthesize more than half of the peptidoglycan per generation in Escherichia coli. Whereas aPBPs have distinct roles in peptidoglycan biosynthesis during growth (i.e., elongation and division), they are semi-redundant; disruption of either is rescued by the other to maintain envelope homeostasis and promote proper growth. Acinetobacter baumannii is a nosocomial pathogen that demonstrated a high propensity to overcome antimicrobial treatment. A. baumannii encodes both PBP1A and PBP1B (encoded by mrcA and mrcB, respectively), but only mrcA deletion decreased fitness and contributed to colistin resistance through inactivation of lipooligosaccharide biosynthesis, indicating that PBP1B was not functionally redundant with PBP1A activity. While previous studies suggested a distinct role for PBP1A in division, it was unknown if its role in septal peptidoglycan biosynthesis was direct. Here, we show that A. baumannii PBP1A has a direct role in division through interactions with divisome components. PBP1A localizes to septal sites during growth, where it interacts with the transpeptidase, PBP3, an essential division component that regulates daughter cell formation. PBP3 overexpression was sufficient to rescue the division defect in ΔmrcA A. baumannii; however, PBP1A overexpression was not sufficient to rescue the septal defect when PBP3 was inhibited, suggesting their activity is not redundant. Overexpression of a major DD-carboxypeptidase, PBP5, also restored the canonical A. baumannii coccobacilli morphology in ΔmrcA cells. Together, these data support a direct role for PBP1A in A. baumannii division and highlights its role as a septal peptidoglycan synthase.ImportancePeptidoglycan biosynthesis is a validated target of β-lactam antibiotics, and it is critical that we understand essential processes in multidrug resistant pathogens such as Acinetobacter baumannii. While model systems such as Escherichia coli have shown that PBP1A is associated with side wall peptidoglycan synthesis, we show herein that A. baumannii PBP1A directly interacts with the divisome component PBP3 to promote division, suggesting a unique role for the enzyme in the highly drug resistant nosocomial pathogen. A. baumannii demonstrated unanticipated resistance and tolerance to envelope-targeting antibiotics, which may be driven by rewired peptidoglycan machinery, and may underlie therapeutic failure during antibiotic treatment.
Are Maximum Yields sustainable? Effect of intra-annual time-scales on MSY, stability and resilience
Authors: Ricouard Antoine , Lehuta Sigrid , Mahévas Stéphanie 
Published: September 2022

AbstractThe concept of Maximum Sustainable Yield (MSY) have been lying at the core of the theory of sustainable harvesting a fishery for decades and have become a key reference point for many fishing administrations, including the European Union. However, the existence of a MSY relies on the stability of a population equilibrium. This hypothesis, though always true in the original Schaeffer model, is still challenging in more realistic and recent population models. However, recent advances shows that fish population can exhibit complex dynamics that are ill described by the classical theory. In particular, processes occurring at intra-annual time scales can affect the stability of a population equilibrium even in a strictly single species case. Associated to stability, the resilience of the equilibrium (defined as an inverse return-time following a perturbation) also matters in a management purpose. Here, we introduce an analytical single population model in discrete time with a monthly time-step allowing temporal distinction between maturation and recruitment with density-dependent mortality and fishing exploitation. We show that, thanks to an appropriate population structure, we can easily derive inter-annual population equilibrium, and study their resilience and stability properties. Then, we show that under classical hypothesis concerning density-dependence, equilibrium stability is not guaranteed and that MSY can, in theory, be associated to unstable or low resilient states. However such destabilisation seems unlikely with realistic sets of parameters. Finally, a numerical illustration for sole (Solea solea) of the Bay of Biscay suggests that the value of MSY was sensitive to maturation period whereas viability, stability and resilience was more sensitive to timing of recruitment. The value ofFMSYappeared robust to uncertainty concerning maturation and recruitment. We conclude by saying that even if the risk of destabilisation is low for real populations, the risk of decreased resilience near the border of extinction should be cared of.
Ten new high-quality genome assemblies for diverse bioenergy sorghum genotypes
Authors: Voelker William G. , Krishnan Krittika , Chougule Kapeel , Alexander Louie C. , Lu Zhenyuan , Olson Andrew , Ware Doreen , Songsomboon Kittikun , Ponce Cristian , Brenton Zachary W. , Boatwright J. Lucas , Cooper Elizabeth A. 
Published: September 2022

AbstractSorghum (Sorghum bicolor (L.) Moench) is an agriculturally and economically important staple crop that has immense potential as a bioenergy feedstock due to its relatively high productivity on marginal lands. To capitalize on and further improve sorghum as a potential source of sustainable biofuel, it is essential to understand the genomic mechanisms underlying complex traits related to yield, composition, and environmental adaptations. Expanding on a recently developed mapping population, we generated de novo genome assemblies for 10 parental genotypes from this population and identified a comprehensive set of over 24 thousand large structural variants (SVs) and over 10.5 million single nucleotide polymorphisms (SNPs).These resources can be integrated into both ongoing and future mapping and trait discovery for sorghum and its myriad uses including food, feed, bioenergy, and increasingly as a carbon dioxide removal mechanism. We show that SVs and nonsynonymous SNPs are enriched in different gene categories, emphasizing the need for long read sequencing in crop species to identify novel variation. Furthermore, we highlight SVs and SNPs occurring in genes and pathways with known associations to critical bioenergy-related phenotypes and characterize the landscape of genetic differences between sweet and cellulosic genotypes.
A national professional development program fills mentoring gaps for postdoctoral researchers
Authors: Sun Ting , Drane Denise , McGee Richard , Campa Henry , Goldberg Bennett B , Hokanson Sarah Chobot 
Published: September 2022

AbstractThe Postdoc Academy: Succeeding as a Postdocwas designed to build postdocs’ skills in career transition, career planning, collaborative research, resilience, and self-reflection. This study examined self-reported changes in five skills as learners progressed through the course. Data were collected from participants who responded to both pre- and post-surveys and engaged with the course learning activities. Results from repeated measures multivariate analysis of variance revealed that all of the self-reported perceptions of skills improved significantly upon completion of the course. Hierarchical regressions revealed that underrepresented minority learners had greater gains in their development of skills in career planning, resilience, and self-reflection. Qualitative analysis of learners’ responses to learning activities found that postdocs perceived networking and mentor support as contributing factors to their skill advancement while tensions among multiple obligations and concerns of uncertainties were significant challenges to applying those skills.
ATR protects centromere identity by promoting DAXX association with PML nuclear bodies
Authors: Trier Isabelle , Joo Yoon Ki , Black Elizabeth , Kabeche Lilian 
Published: September 2022

SummaryCentromere protein A (CENP-A) defines centromere identity and nucleates kinetochore formation for mitotic chromosome segregation. Here, we show that Ataxia telangiectasia and Rad3-related (ATR) kinase, a master regulator of the DNA damage response, protects CENP-A occupancy at interphase centromeres in a DNA damage-independent manner. As ATR localizes to promyelocytic leukemia nuclear bodies (PML NBs) in unperturbed cells, we hypothesized that ATR protects CENP-A occupancy by regulating the localization of the histone H3.3 chaperone and PML NB component, DAXX. Indeed, we found that ATR inhibition reduces DAXX association with PML NBs, resulting in the DAXX-dependent loss of CENP-A from interphase centromeres. Lastly, we demonstrate that CENP-A occupancy is not restored until G1 of the following cell cycle, leading to increased mitotic chromosome segregation defects. These findings demonstrate a novel mechanism by which ATR protects centromere identity and genome stability.
Socioeconomics and biogeography jointly drive geographic biases in our knowledge of plant traits: a global assessment of the Raunkiærian shortfall in plants
Authors: Maitner Brian , Gallagher Rachael , Svenning Jens-Christian , Tietje Melanie , Wenk Elizabeth H. , Eiserhardt Wolf L. 
Published: September 2022

SummaryThe traits of plants determine how they interact with each other and their environment, constituting key knowledge for diverse fields. The lack of comprehensive knowledge of plant traits (the “Raunkiærian shortfall”) poses a major, cross-disciplinary, barrier to scientific advancement. Spatial biases in trait coverage may also lead to erroneous conclusions affecting ecosystem management and conservation planning. Thus, there is an urgent need to assess the spatial completeness of plant trait data, understand drivers of geographic biases, and to identify solutions for filling regional gaps. Here, we leverage a comprehensive set of regional species checklists for vascular plants and trait data for 2,027 traits and 128,929 plant species from the TRY database to assess trait data completeness across the globe. We show that trait data availability in TRY is associated with socioeconomic and biological factors influencing sampling likelihood: trait completeness was positively associated with mean species range size, research expenditure, and human population density and negatively associated with endemism and vascular plant species richness. Integration of a second, regional trait database (AusTraits) more than doubled trait completeness for the continent covered, indicating that the creation and integration of regional databases can rapidly expand trait completeness.Plain Language SummaryThe traits of plants determine how they interact with each other and their environment. Our knowledge of plant traits is incomplete, limiting scientific advancement as well as our ability to manage ecosystems and plan conservation actions. We show that there are large biases in trait data availability which are associated with both biological factors (range size, endemism, species richness) and socioeconomic factors (research expenditure, human population density). We also show how regionally-focused efforts can help rapidly expand trait data availability.