bluuebunny/crossref_metadata_2025_split huggingface dataset:
Laser induced isolation and cultivation of single microbial cells
Authors: Liang Peng , Wang Huan , Wang Yun , Zhao Yinping , Huang Wei E. , Li Bei 
Published: July 2020

AbstractSingle cell isolation and cultivation play an important role in studying physiology, gene expression and functions of microorganisms. Laser Induced Forward Transfer Technique (LIFT) has been applied to isolate single cells but the cell viability after sorting is unclear. We demonstrate that a three-layer LIFT system could be applied to isolate single cells of Gram-negative (E. coli), Gram-positive (Lactobacillus rhamnosusGG, LGG), and eukaryotic microorganisms (Saccharomyces cerevisiae) and the sorted single cells were able to be cultured. The experiment results showed that the average cultivation recovery rate of the ejected single cells were 58% forSaccharomyces cerevisiae, 22% forE. coli, and 74% forLactobacillus rhamnosusGG (LGG). The identities of the cultured cells from single cell sorting were confirmed by using colony PCR with 16S-rRNA for bacteria and large unit rRNA for yeast and subsequent sequencing. This precise sorting and cultivation technique of live single microbial cells can be coupled with other microscopic approaches (e.g. fluorescent and Raman microscopy) to culture single microorganisms with specific functions, revealing their roles in the natural community.ImportanceSingle cell isolation and cultivation are crucial to recover microorganisms for the study of physiology, gene expression and functions. We developed a laser induced cell sorting technology to precisely isolate single microbial cells from a microscopic slide. More importantly, the isolated single microbial cells are still viable for cultivation. We demonstrate to apply the live sorting method to isolate and cultivate single cells of Gram-negative (E. coli), Gram-positive (Lactobacillus rhamnosusGG, LGG), and eukaryotic microorganisms (Saccharomyces cerevisiae). This precise sorting and cultivation technique can be coupled with other microscopic approaches (e.g. fluorescent and Raman microscopy) to culture specifically targeted single microorganisms from microbial community.Abstract Graphic
Eleven Routine Clinical Features Predict COVID-19 Severity
Authors: Zhou Kai , Sun Yaoting , Li Lu , Zang Zelin , Wang Jing , Li Jun , Liang Junbo , Zhang Fangfei , Zhang Qiushi , Ge Weigang , Chen Hao , Sun Xindong , Yue Liang , Wu Xiaomai , Shen Bo , Xu Jiaqin , Zhu Hongguo , Chen Shiyong , Yang Hai , Huang Shigao , Peng Minfei , Lv Dongqing , Zhang Chao , Zhao Haihong , Hong Luxiao , Zhou Zhehan , Chen Haixiao , Dong Xuejun , Tu Chunyu , Li Minghui , Zhu Yi , Chen Baofu , Li Stan Z. , Guo Tiannan 
Published: July 2020

ABSTRACTSeverity prediction of COVID-19 remains one of the major clinical challenges for the ongoing pandemic. Here, we have recruited a 144 COVID-19 patient cohort consisting of training, validation, and internal test sets, longitudinally recorded 124 routine clinical and laboratory parameters, and built a machine learning model to predict the disease progression based on measurements from the first 12 days since the disease onset when no patient became severe. A panel of 11 routine clinical factors, including oxygenation index, basophil counts, aspartate aminotransferase, gender, magnesium, gamma glutamyl transpeptidase, platelet counts, activated partial thromboplastin time, oxygen saturation, body temperature and days after symptom onset, constructed a classifier for COVID-19 severity prediction, achieving accuracy of over 94%. Validation of the model in an independent cohort containing 25 patients achieved accuracy of 80%. The overall sensitivity, specificity, PPV and NPV were 0.70, 0.99, 0.93 and 0.93, respectively. Our model captured predictive dynamics of LDH and CK while their levels were in the normal range. This study presents a practical model for timely severity prediction and surveillance for COVID-19, which is freely available at webserverhttps://guomics.shinyapps.io/covidAI/.
The Impact of COVID-19 on Mental Health outcomes among hospital fever clinic attendants across Nepal: A community-based cross-sectional study
Authors: Devkota Hridaya Raj , Sijali Tula Ram , Bogati Ramji , Ahmad Meraj , Shakya Karuna Laxmi , Adhikary Pratik 
Published: July 2020

AbstractBackgroundThe COVID-19 pandemic has been creating a panic and distressing situations among the entire population globally including Nepal. No study has been conducted assessing the psychological impact of this pandemic on the general public in Nepal. The objective of this study is to assess the mental health status during COVID-19 outbreak and explore the potential influencing factors among the population attending the hospital fever clinics with COVID–19 symptoms.MethodsA cross-sectional survey was conducted between May - June, 2020 with a sample of 645 participants aged 18 and above in 26 hospitals across Nepal. Telephone interviews were conducted using a semi-structured questionnaire along with a validated psychometric tool, the Depression, Anxiety and Stress (DASS-21) scale. The metrics and scores of symptoms and their severity were created and analyzed. Multivariate logistic regression was used to determine the association of potential covariates with outcome variables.ResultsThe prevalence of anxiety, depression and stress were 14%, 7% and 5% respectively. Participants from Bagmati province reported higher level of anxiety (OR 3.87, 95% CI 1.42 – 10.59), while stress (OR 4.78, 95% CI 1.09 – 21.29) and depressive symptoms (OR 3.37, 95% CI 1.10 – 10.35) observed higher among the participants in Province 1. Women were more at risk of anxiety (OR 4.26, 95% CI 2.21 – 8.20) and depression (2.75, 95% CI 1.16 – 6.51) than men. Similarly, people with primary level education found more prone to all factors, stress (OR 20.35, 95% CI 2.06 – 201.19), anxiety (OR 3.10, 95% CI 1.24 – 7.91), and depression (OR 4.41, 95% CI 1.29 – 15.07). More farmers than labors showed higher odds (OR 2.25, 95% CI 1.01 – 5.01) for anxiety, while individuals surveyed who reported their health status as poor-had higher odds (OR 5.95, 95% CI 1.08 – 32.68) for depression. Also, people currently living in rented houses reported more stress (OR 3.11, 95% CI 1.07 – 9.05) and those living far from family reported higher rates of depressive symptoms (OR 3.57, 95% CI 1.01 – 12.58).ConclusionThe study identified increased prevalence of stress, anxiety and depressive symptoms during the initial stage of COVID-19 pandemic in Nepal. Considering the findings, there is urgent need to develop and implement appropriate community-based mental health programs targeting individuals who have had COVID-19 symptoms and who are prone to develop adverse mental health outcomes.
The effective reproductive number (Rt) of COVID-19 and its relationship with social distancing
Authors: Felizola Diniz-Filho José Alexandre , Jardim Lucas , Toscano Cristiana M. , Rangel Thiago Fernando 
Published: July 2020

ABSTRACTThe expansion of the new coronavirus disease (COVID-19) triggered a renewed interest in epidemiological models and on how parameters can be estimated from observed data. Here we investigated the relationship between average number of transmissions though time, the reproductive number Rt, and social distancing index as reported by mobile phone data service inloco, for Goiás State, Brazil, between March and June 2020. We calculated Rt values using EpiEstim package in R-plataform for confirmed cases incidence curve. We found a correlation equal to −0.72 between Rt values and isolation index at a time lag of 8 days. As the Rt values were paired with center of the moving window of 7 days, the delay matches the mean incubation period of the virus. Our findings reinforce that isolation index can be an effective surrogate for modeling and epidemiological analyses and, more importantly, helpful for anticipating the need for early interventions, a critical issue in public health.
Integrating large-scale neuroimaging research datasets: harmonisation of white matter hyperintensity measurements across Whitehall and UK Biobank datasets
Authors: Bordin Valentina , Bertani Ilaria , Mattioli Irene , Sundaresan Vaanathi , McCarthy Paul , Suri Sana , Zsoldos Enikő , Filippini Nicola , Mahmood Abda , Melazzini Luca , Laganà Maria Marcella , Zamboni Giovanna , Singh-Manoux Archana , Kivimäki Mika , Ebmeier Klaus P , Baselli Giuseppe , Jenkinson Mark , Mackay Clare E , Duff Eugene P , Griffanti Ludovica 
Published: July 2020

ABSTRACTLarge scale neuroimaging datasets present the possibility of providing normative distributions for a wide variety of neuroimaging markers, which would vastly improve the clinical utility of these measures. However, a major challenge is our current poor ability to integrate measures across different large-scale datasets, due to inconsistencies in imaging and non-imaging measures across the different protocols and populations. Here we explore the harmonisation of white matter hyperintensity (WMH) measures across two major studies of healthy elderly populations, the Whitehall II imaging sub-study and the UK Biobank. We identify pre-processing strategies that maximise the consistency across datasets and utilise multivariate regression to characterise sample differences contributing to study-level differences in WMH variations. We also present a parser to harmonise WMH-relevant non-imaging variables across the two datasets. We show that we can provide highly calibrated WMH measures from these datasets with: (1) the inclusion of a number of specific standardised processing steps; and (2) appropriate modelling of sample differences through the alignment of demographic, cognitive and physiological variables. These results open up a wide range of applications for the study of WMHs and other neuroimaging markers across extensive databases of clinical data.HIGHLIGHTSWe harmonised measures of WMHs across two studies on healthy ageingSpecific pre-processing strategies can increase comparability across studiesModelling of biological differences is crucial to provide calibrated measures
Lamin C regulates genome organization after mitosis
Authors: Wong X , Hoskins VE , Harr JC , Gordon M , Reddy KL 
Published: July 2020

AbstractThe dynamic 3D organization of the genome is central to the regulation of gene expression and developmental progression, with its disruption being implicated in various diseases. The nuclear lamina, a proteinaceous meshwork underlying the nuclear envelope (NE), provides both structural and regulatory influences on genome organization through the tethering of large inactive genomic regions, called Lamina Associated Domains (LADs), to the nuclear periphery. Evidence suggests that the A type lamins, lamins A and C, are the predominant lamins involved in the peripheral association of LADs, with these two isotypes forming distinct networks and potentially involved in different cellular processes. Here we tested whether lamins A and C have distinct roles in genome organization by examining chromosome architecture in cells in which lamin C or lamin A are specifically down-regulated. We find that lamin C (not lamin A) is required for the 3D organization of LADs and overall chromosome organization in the cell nucleus. Striking differences in the localization of lamin A and lamin C are present as cells exit mitosis that persist through early G1. Whereas lamin A associates with the nascent NE during telophase, lamin C remains in the interior surrounding nucleoplasmic LAD clusters. Lamin C association with the NE is delayed until several hours into G1 and correlates temporally and spatially with the post-mitotic NE association of LADs. Post-mitotic LAD association with the NE, and consequently global 3D genome organization, is perturbed only in cells depleted of lamin C, and not in cells depleted of lamin A. We conclude that lamin C regulates LAD dynamics after mitosis and is a key regulator of genome organization in mammalian cells. These findings reveal an unexpectedly central role for lamin C in genome organization, including both inter-chromosomal LAD-LAD segregation and LAD scaffolding at the NE.
Distinctiveness of genes contributing to growth ofPseudomonas syringaein diverse host plant species
Authors: Helmann Tyler C. , Deutschbauer Adam M. , Lindow Steven E. 
Published: July 2020

AbstractA variety of traits are necessary for bacterial colonization of the interior of plant hosts, including well-studied virulence effectors as well as other phenotypes contributing to bacterial growth and survival within the apoplast. High-throughput methods such as transposon sequencing (TnSeq) are powerful tools to identify such genes in bacterial pathogens. However, there is little information as to the distinctiveness of traits required for bacterial colonization of different hosts. Here, we utilize randomly barcoded TnSeq (RB-TnSeq) to identify the genes that contribute to the ability ofPseudomonas syringaestrain B728a to grow within common bean (Phaseolus vulgaris), lima bean (Phaseolus lunatus), and pepper (Capsicum annuum); species representing two different plant families. The magnitude of contribution of most genes to apoplastic fitness in each of the plant hosts was similar. However, 50 genes significantly differed in their fitness contributions to growth within these species. These genes encoded proteins in various functional categories including polysaccharide synthesis and transport, amino acid metabolism and transport, cofactor metabolism, and phytotoxin synthesis and transport. Six genes that encoded unannotated, hypothetical proteins also contributed differentially to growth in these hosts. The genetic repertoire of a relatively promiscuous pathogen such asP. syringaemay thus be shaped, at least in part, by the conditional contribution of some fitness determinants.
IlvY is an important regulator ofShigellainfectionin vitroandin vivo
Authors: Holly Mayumi K. , Anderson Mark C. , Rabago Lesley M. , Saffarian Azadeh , Marteyn Benoit S. , Arnold Samuel L.M. 
Published: July 2020

AbstractShigellosis results from oral ingestion of the Gram-negative bacteriaShigella, and symptoms include severe diarrhea and dysentery. In the absence of vaccines, small molecule antibacterial drugs have provided treatment options for shigellosis. However,Shigelladrug resistance is rapidly emerging, andShigellastrains with resistance to both third-generation cephalosporins and azithromycin have been identified in Asia. A re-conceptualization is needed regarding the development of therapeutics that target bacterial pathogens in order to reduce resistance development and alteration of gut microbiota, which is depleted upon treatment with wide spectrum antibiotics, thereby increasing susceptibility to subsequent enteric infections. A more organism-specific approach is to develop agents targeting virulence factors such as toxins, adhesins, invasins, quorum sensing, and protein secretion systems. ForShigella, there is interest in targeting transcription factors essential forShigellainfectionin vivorather than specific effectors. Here we describe the importance of theShigellatranscription factor IlvY inShigellavirulencein vitroandin vivo. This work included the development of a novel, oral mouse model ofShigellainfection with wild-type adult mice. Unlike previous models, mice do not require antibiotic pretreatment or diet modifications. This mouse model was used to demonstrate the importance of IlvY forShigella in vivosurvival and that deletion ofilvYimpacts host responses to infection. These results illustrate that IlvY is a potential therapeutic target for the treatment of shigellosis. In addition, the novel mouse model provides an exciting new opportunity to investigate therapeutic efficacy againstShigellainfection and host responses to infection.
Integrating structure-based machine learning and co-evolution to investigate specificity in plant sesquiterpene synthases
Authors: Durairaj Janani , Melillo Elena , Bouwmeester Harro J , Beekwilder Jules , de Ridder Dick , van Dijk Aalt DJ 
Published: July 2020

AbstractSesquiterpene synthases (STSs) catalyze the formation of a large class of plant volatiles called sesquiterpenes. While thousands of putative STS sequences from diverse plant species are available, only a small number of them have been functionally characterized. Sequence identity-based screening for desired enzymes, often used in biotechnological applications, is difficult to apply here as STS sequence similarity is strongly affected by species. This calls for more sophisticated computational methods for functionality prediction. We investigate the specificity of precursor cation formation in these elusive enzymes. By inspecting multi-product STSs, we demonstrate that STSs have a strong selectivity towards one precursor cation. We use a machine learning approach combining sequence and structure information to accurately predict precursor cation specificity for STSs across all plant species. We combine this with a co-evolutionary analysis on the wealth of uncharacterized putative STS sequences, to pinpoint residues and distant functional contacts influencing cation formation and reaction pathway selection. These structural factors can be used to predict and engineer enzymes with specific functions, as we demonstrate by predicting and characterizing two novel STSs fromCitrus bergamia.Author summaryPredicting enzyme function is a popular problem in the bioinformatics field that grows more pressing with the increase in protein sequences, and more attainable with the increase in experimentally characterized enzymes. Terpenes and terpenoids form the largest classes of natural products and find use in many drugs, flavouring agents, and perfumes. Terpene synthases catalyze the biosynthesis of terpenes via multiple cyclizations and carbocation rearrangements, generating a vast array of product skeletons. In this work, we present a three-pronged computational approach to predict carbocation specificity in sesquiterpene synthases, a subset of terpene synthases with one of the highest diversities of products. Using homology modelling, machine learning and co-evolutionary analysis, our approach combines sparse structural data, large amounts of uncharacterized sequence data, and the current set of experimentally characterized enzymes to provide insight into residues and structural regions that likely play a role in determining product specifcity. Similar techniques can be repurposed for function prediction and enzyme engineering in many other classes of enzymes.
Diminazene resistance inTrypanosoma congolenseis linked to reduced mitochondrial membrane potential and not to reduced transport capacity
Authors: Carruthers Lauren V. , Munday Jane C. , Ebiloma Godwin U. , Steketee Pieter , Jayaraman Siddharth , Campagnaro Gustavo D. , Ungogo Marzuq A. , Donachie Anne-Marie , Rowan Tim G. , Peter Rose , Morrison Liam J. , Barrett Michael P. , De Koning Harry P. 
Published: July 2020

AbstractTrypanosoma congolenseis one of the principal agents causing livestock trypanosomiasis in sub-Saharan Africa. This wasting disease is costing these developing economies billions of dollars and undermining food security. Only two old drugs, the diamidine diminazene and the phenanthridine isometamidium are regularly used, and resistance is widespread but poorly understood. We induce diminazene resistance inT. congolenselaboratory strain IL3000 in vitro. Resistance was stable and not deleterious to in vitro growth. There was no cross-resistance with the phenanthridine drugs, with melaminophenyl arsenicals, with two promising new oxaborole trypanocides, nor with other diamidine trypanocides such as pentamidine, except the close structural analogues DB829 and DB75. Fluorescence microscopy showed that accumulation of DB75 was inhibited by folate. Uptake of [3H]-diminazene was also partly inhibited by folate, as well as by competing diamidine drugs, albeit at quite high concentrations, and uptake of tritiated diminazene and pentamidine was slow and low affinity. Uptake of [3H]-folate was in turn partly inhibited by diminazene, and inhibition of diminazene uptake by folate and pentamidine appeared to be additive, indicating multiple low affinity transport mechanisms for the drug. Expression of theT. congolensefolate transporters TcoFT1-3 in diminazene-resistantT. b. bruceisignificantly sensitized the cells to diminazene and DB829, but not to oxaborole AN7973. However, [3H]-diminazene uptake was not different inT. congolenseIL3000 and its diminazene resistant clones and RNAseq and whole-genome sequencing of multiple resistant clones did not reveal major changes in folate transporter sequence or expression. Instead, flow cytometry revealed a strong and stable reduction in the mitochondrial membrane potential Ψm in all resistant clones. We conclude that diminazene uptake inT. congolenseproceed via multiple low affinity mechanisms including folate transporters and that resistance is the result of a reduction in Ψm that limits mitochondrial accumulation of the drug.
coronaSPAdes: from biosynthetic gene clusters to RNA viral assemblies
Authors: Meleshko Dmitry , Hajirasouliha Iman , Korobeynikov Anton 
Published: July 2020

AbstractMotivationThe COVID-19 pandemic has ignited a broad scientific interest in viral research in general and coronavirus research in particular. The identification and characterization of viral species in natural reservoirs typically involvesde novoassembly. However, existing genome, metagenome and transcriptome assemblers often are not able to assemble many viruses (including coronaviruses) into a single contig. Coverage variation between datasets and within dataset, presence of close strains, splice variants and contamination set a high bar for assemblers to process viral datasets with diverse properties.ResultsWe developed coronaSPAdes, a novel assembler for RNA viral species recovery in general and coronaviruses in particular. coronaSPAdes leverages the knowledge about viral genome structures to improve assembly extending ideas initially implemented in biosyntheticSPAdes. We have shown that coronaSPAdes outperforms existing SPAdes modes and other popular short-read metagenome and viral assemblers in the recovery of full-length RNA viral genomes.AvailabilitycoronaSPAdes version used in this article is a part of SPAdes 3.15 release and is freely available athttp://cab.spbu.ru/software/spades.Contacta.korobeynikov@spbu.ruSupplementary informationSupplementary data are available atBioinformatics
The presynaptic glycine transporter GlyT2 is regulated by the Hedgehog pathway in vitro and in vivo
Authors: de la Rocha-Muñoz A. , Núñez E. , Gómez-López S. , López-Corcuera B. , de Juan-Sanz J. , Aragón C. 
Published: July 2020

ABSTRACTThe identity of a glycinergic synapse is maintained presynaptically by the activity of a surface glycine transporter, GlyT2, which recaptures glycine back to presynaptic terminals to preserve vesicular glycine content. GlyT2 loss-of-function mutations cause Hyperekplexia, a rare neurological disease in which loss of glycinergic neurotransmission causes generalized stiffness and strong motor alterations. However, the molecular underpinnings controlling GlyT2 activity remain poorly understood. In this work, we identify the Hedgehog pathway as a robust controller of GlyT2 expression and transport activity. Modulating the activation state of the Hedgehog pathwayin vitroin rodent primary spinal cord neurons orin vivoin zebrafish embryos induced a selective control in GlyT2 expression, regulating GlyT2 transport activity. Our results indicate that activation of Hedgehog reduces GlyT2 expression by decreasing its mRNA levels and increasing its ubiquitination and degradation. This work describes a new molecular link between the Hedgehog signaling pathway and presynaptic glycine availability.