Comparative viral metagenomics from chicken feces and farm dust in the Netherlands

ABSTRACTLivestock animals housed in close proximity to humans can act as sources or intermediate hosts facilitating animal-to-human transmission of zoonotic diseases. Understanding virus diversity in livestock is important for identifying potential zoonotic threats and for ensuring animal health and safe livestock production. Here, we report viral metagenomic characterization of chicken feces (N=51) and paired farm dust samples (N=13) using metagenomic deep sequencing. Samples were collected at 4-5 time points in three broiler farms in the Netherlands. Viruses in the Parvoviridae and Picornaviridae families were the most prevalent, detected in all feces and dust samples and in all feces and 85% of dust samples, respectively. Virus composition found in chicken feces and corresponding dust samples were similar. Great genomic diversity was identified in Picornaviridae and 46 sequences from five picornavirus genera (Sicinivirus, Megrivirus, Anatvirus, Gallivirus and Avisvirus) were detected. For calicivirus, Basovirus and an unclassified novel chicken calicivirus were identified in 13 fecal and 1 dust samples. Two distinct types of chicken astroviruses were identified. Phylogenetic analyses of identified virus sequences from Picornaviridae, Astroviridae and Caliciviridae suggested that viral sequences obtained from different farms are often more closely related to each other than global reference sequences, and sequences from feces and paired dust samples also clustered together. Importantly, our sequencing methodology enabled the recover viral genome sequences from farm dusts, allowing the tracking of virus chatter between livestock animals and their farm environment. This study, albeit relative sample size, does expand current knowledge of virus communities in chickens and surrounding dusts.IMPORTANCEChickens may harbor various zoonotic pathogens, some of which can cause severe clinical outcomes in animals and humans. Farm dust can act as vector to facilitate zoonoses transmission. Here, we report the metagenomic characterization of virus communities of chicken feces and paired farm dust samples collected at multiple time points during the production cycle in broiler farms in the Netherlands. Parvoviridae and Picornaviridae were most frequently detected. We also identified novel astrovirus and calicivirus sequences that would inform future virus taxonomy classification. This is the first study to characterize virus communities in farmed chickens and paired farm dust samples. We also describe a dust sequencing strategy that can be adapted for future dust metagenomic characterization. Our study could help setting up a surveillance baseline for tracking virus flow between chickens and their farm environment which could guide zoonotic outbreak preparedness and health risk assessment of farm exposure.

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Characterization of directed differentiation by high-throughput single-cell RNA-Seq

10.1101/003236 ◽

2014 ◽

Cited By ~ 102

Author(s):

Magali Soumillon ◽

Davide Cacchiarelli ◽

Stefan Semrau ◽

Alexander van Oudenaarden ◽

Tarjei S Mikkelsen

Keyword(s):

Gene Expression ◽

Disease Modeling ◽

Single Cells ◽

Adipogenic Differentiation ◽

Digital Gene Expression ◽

Multiple Time ◽

Directed Differentiation ◽

Time Points

Directed differentiation of cells in vitro is a powerful approach for dissection of developmental pathways, disease modeling and regenerative medicine, but analysis of such systems is complicated by heterogeneous and asynchronous cellular responses to differentiation-inducing stimuli. To enable deep characterization of heterogeneous cell populations, we developed an efficient digital gene expression profiling protocol that enables surveying of mRNA in thousands of single cells at a time. We then applied this protocol to profile 12,832 cells collected at multiple time points during directed adipogenic differentiation of human adipose-derived stem/stromal cells in vitro. The resulting data reveal the major axes of cell-to-cell variation within and between time points, and an inverse relationship between inflammatory gene expression and lipid accumulation across cells from a single donor.

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Characterization of myocardial edema in rats with acute reperfused myocardial infarction at multiple time points by 7 T MR

Journal of Cardiovascular Magnetic Resonance ◽

10.1186/1532-429x-18-s1-p65 ◽

2016 ◽

Vol 18 (S1) ◽

Author(s):

Wei Chen ◽

Ziqian Xu ◽

Yushu Chen ◽

Ruzhi Zhang ◽

Jie Zheng ◽

...

Keyword(s):

Myocardial Infarction ◽

Myocardial Edema ◽

Multiple Time ◽

Reperfused Myocardial Infarction ◽

Time Points ◽

Multiple Time Points

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Quantitative Checklist for Autism in Toddlers (Q-CHAT). A population screening study with follow-up: the case for multiple time-point screening for autism

BMJ Paediatrics Open ◽

10.1136/bmjpo-2020-000700 ◽

2021 ◽

Vol 5 (1) ◽

pp. e000700

Author(s):

Carrie Allison ◽

Fiona E Matthews ◽

Liliana Ruta ◽

Greg Pasco ◽

Renee Soufer ◽

...

Keyword(s):

Phase 1 ◽

Autism Spectrum ◽

Population Screening ◽

Diagnostic Assessment ◽

Test Accuracy ◽

Multiple Time ◽

Phase 2 ◽

Time Points ◽

Screening Study

ObjectiveThis is a prospective population screening study for autism in toddlers aged 18–30 months old using the Quantitative Checklist for Autism in Toddlers (Q-CHAT), with follow-up at age 4.DesignObservational study.SettingLuton, Bedfordshire and Cambridgeshire in the UK.Participants13 070 toddlers registered on the Child Health Surveillance Database between March 2008 and April 2009, with follow-up at age 4; 3770 (29%) were screened for autism at 18–30 months using the Q-CHAT and the Childhood Autism Spectrum Test (CAST) at follow-up at age 4.InterventionsA stratified sample across the Q-CHAT score distribution was invited for diagnostic assessment (phase 1). The 4-year follow-up included the CAST and the Checklist for Referral (CFR). All with CAST ≥15, phase 1 diagnostic assessment or with developmental concerns on the CFR were invited for diagnostic assessment (phase 2). Standardised diagnostic assessment at both time-points was conducted to establish the test accuracy of the Q-CHAT.Main outcome measuresConsensus diagnostic outcome at phase 1 and phase 2.ResultsAt phase 1, 3770 Q-CHATs were returned (29% response) and 121 undertook diagnostic assessment, of whom 11 met the criteria for autism. All 11 screened positive on the Q-CHAT. The positive predictive value (PPV) at a cut-point of 39 was 17% (95% CI 8% to 31%). At phase 2, 2005 of 3472 CASTs and CFRs were returned (58% response). 159 underwent diagnostic assessment, including 82 assessed in phase 1. All children meeting the criteria for autism identified via the Q-CHAT at phase 1 also met the criteria at phase 2. The PPV was 28% (95% CI 15% to 46%) after phase 1 and phase 2.ConclusionsThe Q-CHAT can be used at 18–30 months to identify autism and enable accelerated referral for diagnostic assessment. The low PPV suggests that for every true positive there would, however, be ~4–5 false positives. At follow-up, new cases were identified, illustrating the need for continued surveillance and rescreening at multiple time-points using developmentally sensitive instruments. Not all children who later receive a diagnosis of autism are detectable during the toddler period.

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Genomic Characterization of the Three Balkan Livestock Guardian Dogs

Sustainability ◽

10.3390/su13042289 ◽

2021 ◽

Vol 13 (4) ◽

pp. 2289

Author(s):

Mateja Janeš ◽

Minja Zorc ◽

Maja Ferenčaković ◽

Ino Curik ◽

Peter Dovč ◽

...

Keyword(s):

Conservation Management ◽

Diversity Management ◽

Genomic Diversity ◽

Mountainous Areas ◽

Autosomal Snps ◽

The Balkans ◽

Gray Wolves ◽

Low Diversity ◽

Genomic Characterization

Balkan Livestock Guardian Dogs (LGD) were bred to help protect sheep flocks in sparsely populated, remote mountainous areas in the Balkans. The aim of this study was genomic characterization (107,403 autosomal SNPs) of the three LGD breeds from the Balkans (Karst Shepherd, Sharplanina Dog, and Tornjak). Our analyses were performed on 44 dogs representing three Balkan LGD breeds, as well as on 79 publicly available genotypes representing eight other LGD breeds, 70 individuals representing seven popular breeds, and 18 gray wolves. The results of multivariate, phylogenetic, clustering (STRUCTURE), and FST differentiation analyses showed that the three Balkan LGD breeds are genetically distinct populations. While the Sharplanina Dog and Tornjak are closely related to other LGD breeds, the Karst Shepherd is a slightly genetically distinct population with estimated influence from German Shepard (Treemix analysis). Estimated genomic diversity was high with low inbreeding in Sharplanina Dog (Ho = 0.315, He = 0.315, and FROH>2Mb = 0.020) and Tornjak (Ho = 0.301, He = 0.301, and FROH>2Mb = 0.033) breeds. Low diversity and high inbreeding were estimated in Karst Shepherds (Ho = 0.241, He = 0.222, and FROH>2Mb = 0.087), indicating the need for proper diversity management. The obtained results will help in the conservation management of Balkan LGD dogs as an essential part of the specific grazing biocultural system and its sustainable maintenance.

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Use of TanDEM-X and SRTM-C Data for Detection of Deforestation Caused by Bark Beetle in Central European Mountains

Remote Sensing ◽

10.3390/rs13153042 ◽

2021 ◽

Vol 13 (15) ◽

pp. 3042

Author(s):

Kateřina Gdulová ◽

Jana Marešová ◽

Vojtěch Barták ◽

Marta Szostak ◽

Jaroslav Červenka ◽

...

Keyword(s):

Bark Beetle ◽

Synergistic Effects ◽

Canopy Height ◽

Surface Model ◽

Multiple Time ◽

Central European ◽

Time Points ◽

Bohemian Forest ◽

Multiple Time Points ◽

Surrounding Areas

The availability of global digital elevation models (DEMs) from multiple time points allows their combination for analysing vegetation changes. The combination of models (e.g., SRTM and TanDEM-X) can contain errors, which can, due to their synergistic effects, yield incorrect results. We used a high-resolution LiDAR-derived digital surface model (DSM) to evaluate the accuracy of canopy height estimates of the aforementioned global DEMs. In addition, we subtracted SRTM and TanDEM-X data at 90 and 30 m resolutions, respectively, to detect deforestation caused by bark beetle disturbance and evaluated the associations of their difference with terrain characteristics. The study areas covered three Central European mountain ranges and their surrounding areas: Bohemian Forest, Erzgebirge, and Giant Mountains. We found that vertical bias of SRTM and TanDEM-X, relative to the canopy height, is similar with negative values of up to −2.5 m and LE90s below 7.8 m in non-forest areas. In forests, the vertical bias of SRTM and TanDEM-X ranged from −0.5 to 4.1 m and LE90s from 7.2 to 11.0 m, respectively. The height differences between SRTM and TanDEM-X show moderate dependence on the slope and its orientation. LE90s for TDX-SRTM differences tended to be smaller for east-facing than for west-facing slopes, and varied, with aspect, by up to 1.5 m in non-forest areas and 3 m in forests, respectively. Finally, subtracting SRTM and NASA DEMs from TanDEM-X and Copernicus DEMs, respectively, successfully identified large areas of deforestation caused by hurricane Kyril in 2007 and a subsequent bark beetle disturbance in the Bohemian Forest. However, local errors in TanDEM-X, associated mainly with forest-covered west-facing slopes, resulted in erroneous identification of deforestation. Therefore, caution is needed when combining SRTM and TanDEM-X data in multitemporal studies in a mountain environment. Still, we can conclude that SRTM and TanDEM-X data represent suitable near global sources for the identification of deforestation in the period between the time points of their acquisition.

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Genetic Diversity of Leuconostoc mesenteroides Isolates from Traditional Montenegrin Brine Cheese

Microorganisms ◽

10.3390/microorganisms9081612 ◽

2021 ◽

Vol 9 (8) ◽

pp. 1612

Author(s):

Werner Ruppitsch ◽

Andjela Nisic ◽

Patrick Hyden ◽

Adriana Cabal ◽

Jasmin Sucher ◽

...

Keyword(s):

Genetic Diversity ◽

Safety Evaluation ◽

Gene Clusters ◽

Northern Region ◽

Genomic Diversity ◽

High Genetic Diversity ◽

Pathogenic Factors ◽

Flavor Development ◽

Genomic Characterization

In many dairy products, Leuconostoc spp. is a natural part of non-starter lactic acid bacteria (NSLAB) accounting for flavor development. However, data on the genomic diversity of Leuconostoc spp. isolates obtained from cheese are still scarce. The focus of this study was the genomic characterization of Leuconostoc spp. obtained from different traditional Montenegrin brine cheeses with the aim to explore their diversity and provide genetic information as a basis for the selection of strains for future cheese production. In 2019, sixteen Leuconostoc spp. isolates were obtained from white brine cheeses from nine different producers located in three municipalities in the northern region of Montenegro. All isolates were identified as Ln. mesenteroides. Classical multilocus sequence tying (MLST) and core genome (cg) MLST revealed a high diversity of the Montenegrin Ln. mesenteroides cheese isolates. All isolates carried genes of the bacteriocin biosynthetic gene clusters, eight out of 16 strains carried the citCDEFG operon, 14 carried butA, and all 16 isolates carried alsS and ilv, genes involved in forming important aromas and flavor compounds. Safety evaluation indicated that isolates carried no pathogenic factors and no virulence factors. In conclusion, Ln. mesenteroides isolates from Montenegrin traditional cheeses displayed a high genetic diversity and were unrelated to strains deposited in GenBank.

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Emergence of Salmonid Alphavirus Genotype 2 in Norway—Molecular Characterization of Viral Strains Circulating in Norway and Scotland

Viruses ◽

10.3390/v13081556 ◽

2021 ◽

Vol 13 (8) ◽

pp. 1556

Author(s):

Monika J. Hjortaas ◽

Elena Fringuelli ◽

Adérito L. Monjane ◽

Aase B. Mikalsen ◽

Christine M. Jonassen ◽

...

Keyword(s):

Full Length ◽

Genomic Diversity ◽

Last Common Ancestor ◽

Source Of Infection ◽

New Variant ◽

Genotype 2 ◽

Boat Traffic ◽

Horizontal Spread ◽

Full Length Genome

Pancreas disease (PD) and sleeping disease (SD), caused by an alphavirus, are endemic in European salmonid aquaculture, causing significant mortality, reduced growth and poor flesh quality. In 2010, a new variant of salmonid alphavirus emerged in Norway, marine salmonid alphavirus genotype 2 (SAV2). As this genotype is highly prevalent in Scotland, transmission through well boat traffic was hypothesized as one possible source of infection. In this study, we performed full-length genome sequencing of SAV2 sampled between 2006 and 2012 in Norway and Scotland, and present the first comprehensive full-length characterization of Norwegian marine SAV2 strains. We analyze their relationship with selected Scottish SAV2 strains and explore the genetic diversity of SAV. Our results show that all Norwegian marine SAV2 share a recent last common ancestor with marine SAV2 circulating in Scotland and a higher level of genomic diversity among the Scottish marine SAV2 strains compared to strains from Norway. These findings support the hypothesis of a single introduction of SAV2 to Norway sometime from 2006–2010, followed by horizontal spread along the coast.

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Meta-analysis of effect sizes reported at multiple time points: A multivariate approach

Clinical Trials ◽

10.1177/1740774512453218 ◽

2012 ◽

Vol 9 (5) ◽

pp. 610-620 ◽

Cited By ~ 28

Author(s):

Thomas A Trikalinos ◽

Ingram Olkin

Keyword(s):

Random Effects ◽

Treatment Effects ◽

Multivariate Analyses ◽

Meta Analysis ◽

Effect Sizes ◽

Multiple Time ◽

Time Points ◽

Fixed And Random Effects ◽

Multiple Time Points ◽

Meta Analyses

Background Many comparative studies report results at multiple time points. Such data are correlated because they pertain to the same patients, but are typically meta-analyzed as separate quantitative syntheses at each time point, ignoring the correlations between time points. Purpose To develop a meta-analytic approach that estimates treatment effects at successive time points and takes account of the stochastic dependencies of those effects. Methods We present both fixed and random effects methods for multivariate meta-analysis of effect sizes reported at multiple time points. We provide formulas for calculating the covariance (and correlations) of the effect sizes at successive time points for four common metrics (log odds ratio, log risk ratio, risk difference, and arcsine difference) based on data reported in the primary studies. We work through an example of a meta-analysis of 17 randomized trials of radiotherapy and chemotherapy versus radiotherapy alone for the postoperative treatment of patients with malignant gliomas, where in each trial survival is assessed at 6, 12, 18, and 24 months post randomization. We also provide software code for the main analyses described in the article. Results We discuss the estimation of fixed and random effects models and explore five options for the structure of the covariance matrix of the random effects. In the example, we compare separate (univariate) meta-analyses at each of the four time points with joint analyses across all four time points using the proposed methods. Although results of univariate and multivariate analyses are generally similar in the example, there are small differences in the magnitude of the effect sizes and the corresponding standard errors. We also discuss conditional multivariate analyses where one compares treatment effects at later time points given observed data at earlier time points. Limitations Simulation and empirical studies are needed to clarify the gains of multivariate analyses compared with separate meta-analyses under a variety of conditions. Conclusions Data reported at multiple time points are multivariate in nature and are efficiently analyzed using multivariate methods. The latter are an attractive alternative or complement to performing separate meta-analyses.

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