bluuebunny/crossref_metadata_2025_split huggingface dataset:
Ion transport modulators differentially modulate inflammatory responses in THP-1 derived macrophages
Authors: Mitini-Nkhoma Steven C. , Fernando Narmada , Ishaka G.K.D. , Handunnetti Shiroma M. , Pathirana Sisira L. 
Published: March 2021

AbstractIon transport modulators are most commonly used to treat various non-communicable diseases including diabetes and hypertension. They are also known to bind to receptors on various immune cells, but the immunomodulatory properties of most ion transport modulators have not been fully elucidated. We assessed the effects of thirteen FDA approved ion transport modulators namely ambroxol HCl, amiloride HCl, diazoxide, digoxin, furosemide, hydrochlorothiazide, metformin, omeprazole, pantoprazole, phenytoin, verapamil, drug X and drug Y on superoxide production, nitric oxide production and cytokine expression by THP-1 derived macrophages that had been stimulated with ethanol-inactivatedMycobacterium bovisBCG. Ambroxol HCl, diazoxide, digoxin, furosemide, hydrochlorothiazide, metformin, pantoprazole, phenytoin, verapamil and drug Y had an inhibitory effect on nitric oxide production, while all the test drugs had an inhibitory effect on superoxide production. Amiloride HCl, diazoxide, digoxin, furosemide, phenytoin, verapamil, drug X and drug Y enhanced the expression of IL-1β and TNF-α. Unlike most immunomodulatory compounds currently in clinical use, most of the test drugs inhibited some inflammatory processes while promoting others. Ion pumps and ion channels could therefore serve as targets for more selective immunomodulatory agents which do not cause overt immunosupression.
Protein allocation and utilization in the versatile chemolithoautotrophCupriavidus necator
Authors: Jahn Michael , Crang Nick , Janasch Markus , Hober Andreas , Forsström Björn , Kimler Kyle , Mattausch Alexander , Chen Qi , Asplund-Samuelsson Johannes , Hudson Elton P. 
Published: March 2021

SummaryBacteria must balance the different needs for substrate assimilation, growth functions, and resilience in order to thrive in their environment. Of all cellular macromolecules, the bacterial proteome is by far the most important resource and its size is limited. Here, we investigated how the highly versatile ‘knallgas’ bacteriumCupriavidus necatorreallocates protein resources when grown on different limiting substrates and with different growth rates. We determined protein quantity by mass spectrometry and estimated enzyme utilization by resource balance analysis modeling. We found thatC. necatorinvests a large fraction of its proteome in functions that are hardly utilized. Of the enzymes that are utilized, many are present in excess abundance. One prominent example is the strong expression of CBB cycle genes such as Rubisco during growth on fructose. Modeling and mutant competition experiments suggest that CO2-reassimilation through Rubisco does not provide a fitness benefit for heterotrophic growth, but is rather an investment in readiness for autotrophy.HighlightsA large fraction of theC. necatorproteome is not utilized and not essentialHighly utilized enzymes are more abundant and less variableAutotrophy related enzymes are largely underutilizedRe-assimilation of CO2viathe CBB cycle is unlikely to provide a fitness benefit
Predicting Hosts Based on Early SARS-CoV-2 Samples and Analyzing Later World-wide Pandemic in 2020
Authors: Guo Qian , Li Mo , Wang Chunhui , Guo Jinyuan , Jiang Xiaoqing , Tan Jie , Wu Shufang , Wang Peihong , Xiao Tingting , Zhou Man , Fang Zhencheng , Xiao Yonghong , Zhu Huaiqiu 
Published: March 2021

AbstractThe SARS-CoV-2 pandemic has raised the concern for identifying hosts of the virus since the early-stage outbreak. To address this problem, we proposed a deep learning method, DeepHoF, based on extracting the viral genomic features automatically, to predict host likelihood scores on five host types, including plant, germ, invertebrate, non-human vertebrate and human, for novel viruses. DeepHoF made up for the lack of an accurate tool applicable to any novel virus and overcame the limitation of the sequence similarity-based methods, reaching a satisfactory AUC of 0.987 on the five-classification. Additionally, to fill the gap in the efficient inference of host species for SARS-CoV-2 using existed tools, we conducted a deep analysis on the host likelihood profile calculated by DeepHoF. Using the isolates sequenced in the earliest stage of COVID-19, we inferred minks, bats, dogs and cats were potential hosts of SARS-CoV-2, while minks might be one of the most noteworthy hosts. Several genes of SARS-CoV-2 demonstrated their significance in determining the host range. Furthermore, the large-scale genome analysis, based on DeepHoF’s computation for the later world-wide pandemic in 2020, disclosed the uniformity of host range among SARS-CoV-2 samples and the strong association of SARS-CoV-2 between humans and minks.
LowerVibriospp. abundances inZostera marinaleaf canopies suggest a novel ecosystem function for temperate seagrass beds
Authors: Reusch Thorsten B.H. , Schubert Philipp R. , Marten Silke-Mareike , Gill Diana , Karez Rolf , Busch Kathrin , Hentschel Ute 
Published: March 2021

AbstractSeagrasses, a polyphyletic group of about 60 marine angiosperm species, are the foundation of diverse and functionally important marine habitats along sheltered sedimentary coasts. As a novel ecological function with high societal relevance, a role of the leaf canopy for reducing potentially harmful bacteria has recently been hypothesized. Accordingly, we tested whether or not the abundance of general bacteria and more specifically, those belonging to the genusVibriowere reduced within temperateZostera marina(eelgrass) meadows compared to adjacent sand flats and sampled 5 sites in the south-western Baltic Sea using SCUBA. Compared to non-vegetated area, we found an average reduction of 39% for allVibrioand 63% for the potentially harmfulV. vulnificus/choleraesubtype based on robust plate counting data onVibrioselective agar. The underlying mechanism is currently elusive and clearly merits further study. Our results underline the critical importance of seagrasses in maintaining shallow water ecosystem functioning including water quality and provide further motivation for their protection and restoration.
Polycomb repressive complex 2 coordinates with Sin3 histone deacetylase complex to epigenetically reprogram genome-wide expression ofeffectorsand regulate pathogenicity inMagnaporthe oryzae
Authors: Wu Zhongling , Qiu Jiehua , Shi Huanbin , Lin Chuyu , Yue Jiangnan , Liu Zhiquan , Xie Wei , Kou Yanjun , Tao Zeng 
Published: March 2021

AbstractThe strict suppression and reprogramming of gene expression are necessary at different development stages and/or in response to environment stimuli in eukaryotes. In RiceMagnaporthe oryzaepathosystem,effectorsfrom pathogen are kept transcriptionally silenced in the vegetative growth stage and are highly expressed during invasive growth stage to adapt to the host environment. However, the mechanism of how sucheffectorsare stably repressed in the vegetative stage and its roles during rice blast infection remain unclear so far. Here, we showed that all subunits of Polycomb Repressive Complex 2 are required for such repression by direct H3K27me3 occupancy and pathogenic process inM. oryzae. Suppression of polycomb-mediated H3K27me3 causes an improper induction ofeffectorsduring vegetative growth thus simulating a host environment. Notably, the addition subunit P55 not only acts as the bridge to connect with core subunits to form a complex inM. oryzae, but also recruits Sin3 histone deacetylase complex to prompt H3K27me3 occupancy for stable maintenance of transcriptional silencing of the target genes in the absence of PRC1. In contrast, during invasive growth stage, the repressed state ofeffectorschromatin can be partially erased during pathogenic development resulting in transcriptional activation of effectors therein. Overall, Polycomb repressive complex 2 coordinates with Sin3 histone deacetylase complex to epigenetically reprogram genome-wide expression ofeffectors,which act as molecular switch to memorize the host environment from vegetative to invasive growth, thus contributing to the infection of rice blast.
Neural networks and extreme gradient boosting predict multiple thresholds and trajectories of microbial biodiversity responses due to browning
Authors: Fontaine Laurent , Khomich Maryia , Andersen Tom , Hessen Dag O. , Rasconi Serena , Davey Marie L. , Eiler Alexander 
Published: March 2021

AbstractEcological association studies often assume monotonicity such as between biodiversity and environmental properties although there is growing evidence that non-monotonic relations dominate in nature. Here we apply machine learning algorithms to reveal the non-monotonic association between microbial diversity and an anthropogenic induced large scale change, the browning of freshwaters, along a longitudinal gradient covering 70 boreal lakes in Scandinavia. Measures of bacterial richness and evenness (alpha diversity) showed non-monotonic trends in relation to environmental gradients, peaking at intermediate levels of browning. Depending on the statistical methods, variables indicative for browning could explain 5% of the variance in bacterial community composition (beta diversity) when applying standard methods assuming monotonic relations and up to 45 % with machine learning methods (i.e. extreme gradient boosting and feed-forward neural networks) taking non-monotonicity into account. This non-monotonicity observed at the community level was explained by the complex interchangeable nature of individual taxa responses as shown by a high degree of non-monotonic responses of individual bacterial sequence variants to browning. Furthermore, the non-monotonic models provide the position of thresholds and predict alternative bacterial diversity trajectories in boreal freshwater as a result of ongoing climate and land use changes, which in turn will affect entire ecosystem metabolism and likely greenhouse gas production.
Somewhere I belong: phylogeny and morphological evolution in a species-rich lineage of ectoparasitic flatworms infecting cichlid fishes
Authors: Cruz-Laufer Armando J. , Pariselle Antoine , Jorissen Michiel W. P. , Bukinga Fidel Muterezi , Al Assadi Anwar , Van Steenberge Maarten , Koblmüller Stephan , Sturmbauer Christian , Smeets Karen , Huyse Tine , Artois Tom , Vanhove Maarten P. M. 
Published: March 2021

AbstractA substantial portion of biodiversity evolved through adaptive radiation. However, the effects of explosive speciation on species interactions remain poorly understood. Metazoan parasites infecting radiating host lineages could improve our knowledge because of their intimate host relationships. Yet limited molecular, phenotypic, and ecological data discourage multivariate analyses of evolutionary patterns and encourage the use of discrete characters. Here, we assemble new molecular, morphological, and host range data widely inferred from a species-rich lineage of parasites (Cichlidogyrus, Platyhelminthes: Monogenea) infecting cichlid fishes to address data scarcity. We infer a multi-marker (28S/18S rDNA, ITS1, COI mtDNA) phylogeny of 58/137 species and characterise major lineages through synapomorphies inferred from mapping morphological characters. We predict the phylogenetic position of species without DNA data through shared character states, a combined molecular-morphological phylogenetic analysis, and a classification analysis with support vector machines. Based on these predictions and a cluster analysis, we assess the systematic informativeness of continuous characters, search for continuous equivalents for discrete characters, and suggest new characters for morphological traits not analysed to date. We also model the attachment/reproductive organ and host range evolution using the data of 136/137 described species and multivariate phylogenetic comparative methods (PCMs). We show that discrete characters can mask phylogenetic signals but can be key for characterising species groups. Regarding the attachment organ morphology, a divergent evolutionary regime for at least one lineage was detected and a limited morphological variation indicates host and environmental parameters affecting its evolution. However, moderate success in predicting phylogenetic positions, and a low systematic informativeness and high multicollinearity of morphological characters call for a revaluation of characters included in species characterisations.
Turning movements in real life capture subtle longitudinal and preataxic changes in cerebellar ataxia
Authors: Thierfelder Annika , Seemann Jens , John Natalie , Giese Martin , Schöls Ludger , Timmann Dagmar , Synofzik Matthis , Ilg Winfried 
Published: March 2021

AbstractOBJECTIVESClinical and regulatory acceptance of upcoming molecular treatments in degenerative ataxias might greatly benefit from ecologically valid endpoints which capture change in ataxia severity in patients’ real life. This longitudinal study aimed to unravel quantitative motor biomarkers in degenerative ataxias in real life turning movements which are sensitive for changes both longitudinally and at the preataxic stage.METHODSCombined cross-sectional (n=30) and longitudinal (n=14, 1-year interval) observational study in degenerative cerebellar disease (including 8 pre-ataxic mutation carriers) compared to 23 healthy controls. Turning movements were assessed by three body-worn inertial sensors in three conditions: (1) instructed laboratory assessment, (2) supervised free walking, and (3) unsupervised real-life movements.RESULTSMeasures which quantified dynamic balance during turning – lateral velocity change (LVC) and outward acceleration –, but not general turning measures such as speed, allowed differentiating ataxic against healthy subjects in real life with high effect size (δ=0.68), with LVC also differentiating preataxic against healthy subjects (δ=0.53). LVC was highly correlated with clinical ataxia severity (SARA score, effect size ρ=0.79) and subjective balance confidence (ABC score, ρ=0.66). Moreover, LVC in real life – but not general turning measures, gait measures, or the SARA score – allowed detecting significant longitudinal change in one-year follow-up with high effect size (rprb=0.66).CONCLUSIONSMeasures of turning allow to capture specific changes of dynamic balance in degenerative ataxia in real life, with high sensitivity to longitudinal differences in ataxia severity and to the preataxic stage. They thus present promising ecologically valid motor biomarkers for capturing change in real life, even in the highly treatment-relevant early stages of degenerative cerebellar disease.
Disease-specific eQTL screening reveals an anti-fibrotic effect of AGXT2 in nonalcoholic fatty liver disease
Authors: Yoo Taekyeong , Joo Sae Kyung , Kim Hyo Jung , Kim Hyun Young , Sim Hyungtai , Lee Jieun , Kim Hee-Hoon , Jung Sunhee , Lee Youngha , Jamialahmadi Oveis , Romeo Stefano , Jeong Won-Il , Hwang Geum-Sook , Kang Keon Wook , Kim Jae Woo , Kim Won , Choi Murim 
Published: March 2021

AbstractBackground & AimsNonalcoholic fatty liver disease (NAFLD) poses an impending clinical burden. Genome-wide association studies have revealed a limited contribution of genomic variants to the disease, requiring alternative but robust approaches to identify disease-associated variants and genes. We carried out a disease-specific expression quantitative trait loci (eQTL) screen to identify novel genetic factors that specifically act on NAFLD progression on the basis of genotype.MethodsWe recruited 125 Korean biopsy-proven NAFLD patients and healthy individuals and performed eQTL analyses using 21,272 transcripts and 3,234,941 genotyped and imputed SNPs. We then selected eQTLs that were detected only in the NAFLD group, but not in the control group (i.e., NAFLD-eQTLs). An additional cohort of 162 Korean NAFLD individuals was used for replication. The function of the selected eQTL toward NAFLD development was validated using HepG2, primary hepatocytes and NAFLD mouse models.ResultsThe NAFLD-specific eQTL screening yielded 242 loci. Among them,AGXT2, encoding alanine-glyoxylate aminotransferase 2, displayed decreased expression in NAFLD patients homozygous for the non-reference allele of rs2291702, compared to no-NAFLD subjects with the same genotype (P= 4.79 × 10−6). This change was replicated in an additional 162 individuals, yielding a combinedP-value of 8.05 × 10−8from a total of 245 NAFLD patients and 48 controls.Knockdown ofAGXT2induced palmitate-overloaded hepatocyte death by increasing ER stress, and exacerbated NAFLD diet-induced liver fibrosis in mice. However, overexpression of AGXT2 reversely attenuated liver fibrosis and steatosis as well.ConclusionsWe implicate a new molecular role of AGXT2 in NAFLD. Our overall approach will serve as an efficient tool for uncovering novel genetic factors that contribute to liver steatosis and fibrosis in patients with NAFLD.Lay summaryElucidating causal genes for NAFLD has been challenging due to limited tissue availability and the polygenic nature of the disease. Using liver and blood samples from 125 biopsy-proven NAFLD and no-NAFLD Korean individuals and an additional 162 individuals for replication, we devised a new analytic method to identify causal genes. Among the candidates, we found that AGXT2-rs2291702 protects against liver fibrosis in a genotype-dependent manner with the potential for therapeutic interventions. Our approach enables the discovery of NAFLD causal genes that act on the basis of genotype.
A highly accurate model for screening prostate cancer using propensity index panel of ten genes
Authors: Jain Shipra , Malhotra Kawal Preet Kaur , Patiyal Sumeet , Raghava Gajendra P. S. 
Published: March 2021

AbstractProstate-specific antigen (PSA) is a key biomarker, which is commonly used to screen patients of prostate cancer. There is a significant number of unnecessary biopsies that are performed every year, due to poor accuracy of PSA based biomarker. In this study, we identified alternate biomarkers based on gene expression that can be used to screen prostate cancer with high accuracy. All models were trained and test on gene expression profile of 500 prostate cancer and 51 normal samples. Numerous feature selection techniques have been used to identify potential biomarkers. These biomarkers have been used to develop various models using different machine learning techniques for predicting samples of prostate cancer. Our logistic regression-based model achieved highest AUROC 0.91 with accuracy 82.42% on validation dataset. We introduced a new approach called propensity index, where expression of gene is converted into propensity. Our propensitybased approach improved the performance of classification models significantly and achieved AUROC 0.99 with accuracy 96.36% on validation dataset. We also identified and ranked selected genes which can be used to discriminate prostate cancer patients from health individuals with high accuracy. It was observed that single gene-based biomarkers can only achieve accuracy around 90%. In this study, we got best performance using a panel of 10 genes; random forest model using propensity index.HighlightsApplication of Machine learning techniques to identify Biomarkers for PRAD cancer.Highly accurate models developed for classifying prostate cancer vs. normal sample.Introducing Propensity index concept for enhancing model performance.Top 10 genes identified using feature selection techniques.
Experimental evolution reveals post-transcriptional regulation as a novel driver ofLeishmaniafitness gain
Authors: Piel Laura , Rajan K. Shanmugha , Bussotti Giovanni , Varet Hugo , Legendre Rachel , Proux Caroline , Douché Thibaut , Giai-Gianetto Quentin , Chaze Thibault , Cokelaer Thomas , Vojtkova Barbora , Gordon-Bar Nadav , Doniger Tirza , Cohen-Chalamish Smadar , Rengaraj Praveenkumar , Besse Céline , Boland Anne , Sadlova Jovana , Deleuze Jean-François , Matondo Mariette , Unger Ron , Volf Petr , Michaeli Shulamit , Pescher Pascale , Späth Gerald F. 
Published: March 2021

AbstractThe protozoan parasiteLeishmania donovanicauses fatal human visceral leishmaniasis in absence of treatment. Genome instability has been recognized as a driver inLeishmaniafitness gain in response to environmental change or chemotherapy. How genome instability generates beneficial phenotypes despite potential deleterious gene dosage effects is unknown. Here we address this important open question applying experimental evolution and integrative systems approaches on parasites adapting toin vitroculture. Phenotypic analyses of parasites from early and late stages of culture adaptation revealed an important fitness tradeoff, with selection for accelerated growth in promastigote culture (fitness gain) impairing infectivity (fitness costs). Comparative genomics, transcriptomics and proteomics analyses revealed a complex regulatory network driving parasite fitness, with genome instability causing highly reproducible, gene dosage-dependent changes in protein abundance linked to post-transcriptional regulation. These in turn were associated with a gene dosage-independent reduction in abundance of flagellar transcripts and a coordinated increase in abundance of coding and non-coding RNAs implicated in ribosomal biogenesis and protein translation. We correlated differential expression of small nucleolar RNAs (snoRNAs) with changes in rRNA modification, providing first evidence thatLeishmaniafitness gain in culture may be controlled by post-transcriptional and epitranscriptomic regulation. Our findings propose a novel model forLeishmaniafitness gain in culture, where differential regulation of mRNA stability and the generation of fitness-adapted ribosomes may potentially filter deleterious from beneficial gene dosage effects and provide proteomic robustness to genetically heterogenous, adapting parasite populations. This model challenges the current, genome-centric approach toLeishmaniaepidemiology and identifies theLeishmaniatranscriptome and non-coding small RNome as potential novel sources for the discovery of biomarkers that may be associated with parasite phenotypic adaptation in clinical settings.
Endosperm turgor pressure both promotes and restricts seed growth and size
Authors: Creff Audrey , Ali Olivier , Bayle Vincent , Ingram Gwyneth , Landrein Benoit 
Published: March 2021

AbstractOrgan size depends on complex biochemical and mechanical interactions between cells and tissues. Here, we investigate the control of seed size, a key agronomic trait, by mechanical interactions between two compartments: the endosperm and the testa. By combining experiments with computational modelling, we tested an incoherent mechanical feedforward loop hypothesis in which pressure-induced stresses play two antagonistic roles; directly driving seed growth, but indirectly inhibiting it through mechanosensitive stiffening of the seed coat. We show that our model can recapitulate wild type growth patterns and explain the small seed phenotype of thehaiku2mutant. Our work further reveals that the developmental regulation of endosperm pressure is needed to prevent a precocious reduction of seed growth rate induced by force-dependent seed coat stiffening.