scholarly journals High-throughput Identification of Eukaryotic Parasites and Arboviruses in Mosquitoes

2021 ◽  
Author(s):  
Matthew Vinson Cannon ◽  
Haikel N Bogale ◽  
Devika Bhalerao ◽  
Kalil Keita ◽  
Denka Camara ◽  
...  
Keyword(s):  
High Throughput ◽  
Dna Sequences ◽  
Disease Surveillance ◽  
High Throughput Sequencing ◽  
Emerging Pathogens ◽  
Mortality And Morbidity ◽  
Vector Borne Disease ◽  
Animal Pathogens ◽  
Wide Range ◽  
Vector Borne

Vector-borne pathogens cause many human infectious diseases and are responsible for high mortality and morbidity throughout the world. They can also cause livestock epidemics with dramatic social and economic consequences. Due to the high costs, vector-borne disease surveillance is often limited to current threats, and the investigation of emerging pathogens typically occur after the reports of clinical cases. Here, we use high-throughput sequencing to detect and identify a wide range of parasites and viruses carried by mosquitoes from Cambodia, Guinea, Mali and Maryland. We apply this approach to individual Anopheles mosquitoes as well as pools of mosquitoes captured in traps; and compare the outcomes of this assay when applied to DNA or RNA. We identified known human and animal pathogens and mosquito parasites belonging to a wide range of taxa, insect Flaviviruses, and novel DNA sequences from previously uncharacterized organisms. Our results also revealed that analysis of the content of an entire trap is an efficient approach to monitor and identify potential vector-borne pathogens in large surveillance studies, and that analyses of RNA extracted from mosquitoes is preferable, when possible, over DNA-based analyses. Overall, we describe a flexible and easy-to-customize assay that can provide important information for vector-borne disease surveillance and research studies to efficiently complement current approaches.

scholarly journals High-throughput Detection of Eukaryotic Parasites and Arboviruses in Mosquitoes

Biology Open ◽  
2021 ◽  
Author(s):  
Matthew V. Cannon ◽  
Haikel N. Bogale ◽  
Devika Bhalerao ◽  
Kalil Keita ◽  
Denka Camara ◽  
...  
Keyword(s):  
High Throughput ◽  
Dna Sequences ◽  
Disease Surveillance ◽  
High Throughput Sequencing ◽  
Emerging Pathogens ◽  
Mortality And Morbidity ◽  
Vector Borne Disease ◽  
Animal Pathogens ◽  
Wide Range ◽  
Vector Borne

Vector-borne pathogens cause many human infectious diseases and are responsible for high mortality and morbidity throughout the world. They can also cause livestock epidemics with dramatic social and economic consequences. Due to its high costs, vector-borne disease surveillance is often limited to current threats, and the investigation of emerging pathogens typically occurs after the reports of clinical cases. Here, we use high-throughput sequencing to detect and identify a wide range of parasites and viruses carried by mosquitoes from Cambodia, Guinea, Mali and Maryland. We apply this approach to individual Anopheles mosquitoes as well as pools of mosquitoes captured in traps; and compare the outcomes of this assay when applied to DNA or RNA. We identified known human and animal pathogens and mosquito parasites belonging to a wide range of taxa, as well as novel DNA sequences from previously uncharacterized organisms. Our results also revealed that analysis of the content of an entire trap could be an efficient approach to monitor and identify rare vector-borne pathogens in large surveillance studies. Overall, we describe a high-throughput and easy-to-customize assay to screen for a wide-range of pathogens and efficiently complement current vector-borne disease surveillance approaches.

scholarly journals Identification of Novel Viruses in Amblyomma americanum , Dermacentor variabilis , and Ixodes scapularis Ticks

mSphere ◽  
2018 ◽  
Vol 3 (2) ◽  
Author(s):  
Rafal Tokarz ◽  
Stephen Sameroff ◽  
Teresa Tagliafierro ◽  
Komal Jain ◽  
Simon H. Williams ◽  
...  
Keyword(s):  
New York ◽  
High Throughput ◽  
High Throughput Sequencing ◽  
Ixodes Scapularis ◽  
The United States ◽  
Dermacentor Variabilis ◽  
Amblyomma Americanum ◽  
Animal Pathogens ◽  
Wide Range ◽  
Sequencing Platforms

ABSTRACT Ticks carry a wide range of known human and animal pathogens and are postulated to carry others with the potential to cause disease. Here we report a discovery effort wherein unbiased high-throughput sequencing was used to characterize the virome of 2,021 ticks, including Ixodes scapularis ( n = 1,138), Amblyomma americanum ( n = 720), and Dermacentor variabilis ( n = 163), collected in New York, Connecticut, and Virginia in 2015 and 2016. We identified 33 viruses, including 24 putative novel viral species. The most frequently detected viruses were phylogenetically related to members of the Bunyaviridae and Rhabdoviridae families, as well as the recently proposed Chuviridae . Our work expands our understanding of tick viromes and underscores the high viral diversity that is present in ticks. IMPORTANCE The incidence of tick-borne disease is increasing, driven by rapid geographical expansion of ticks and the discovery of new tick-associated pathogens. The examination of the tick microbiome is essential in order to understand the relationship between microbes and their tick hosts and to facilitate the identification of new tick-borne pathogens. Genomic analyses using unbiased high-throughput sequencing platforms have proven valuable for investigations of tick bacterial diversity, but the examination of tick viromes has historically not been well explored. By performing a comprehensive virome analysis of the three primary tick species associated with human disease in the United States, we gained substantial insight into tick virome diversity and can begin to assess a potential role of these viruses in the tick life cycle.

scholarly journals In silico assessment of primers for eDNA studies using PrimerTree and application to characterize the biodiversity surrounding the Cuyahoga River

2015 ◽  
Author(s):  
M.V. Cannon ◽  
J. Hester ◽  
A. Shalkhauser ◽  
E.R. Chan ◽  
K. Logue ◽  
...  
Keyword(s):  
High Throughput ◽  
Dna Sequences ◽  
Water Samples ◽  
High Throughput Sequencing ◽  
Biological Diversity ◽  
Pcr Amplification ◽  
Environmental Dna ◽  
Asian Carp ◽  
Broad Perspective ◽  
Wide Range

Analysis of environmental DNA (eDNA) enables the detection of species of interest from water and soil samples, typically using species-specific PCR. Here, we describe a method to characterize the biodiversity of a given environment by amplifying eDNA using primer pairs targeting a wide range of taxa and high-throughput sequencing for species identification. We tested this approach on 91 water samples of 40 mL collected along the Cuyahoga River (Ohio, USA). We amplified eDNA using 12 primer pairs targeting mammals, fish, amphibians, birds, bryophytes, arthropods, copepods, plants and several microorganism taxa and sequenced all PCR products simultaneously by high-throughput sequencing. Overall, we identified DNA sequences from 15 species of fish, 17 species of mammals, 8 species of birds, 15 species of arthropods, one turtle and one salamander. Interestingly, in addition to aquatic and semiaquatic animals, we identified DNA from terrestrial species that live near the Cuyahoga River. We also identified DNA from one Asian carp species invasive to the Great Lakes but that had not been previously reported in the Cuyahoga River. Our study shows that analysis of eDNA extracted from small water samples using wide-range PCR amplification combined with high-throughput sequencing can provide a broad perspective on biological diversity.

scholarly journals In Silico Estimation of the Abundance and Phylogenetic Significance of the Composite Oct4-Sox2 Binding Motifs within a Wide Range of Species

Data ◽  
2020 ◽  
Vol 5 (4) ◽  
pp. 111
Author(s):  
Arman Kulyyassov ◽  
Ruslan Kalendar
Keyword(s):  
High Throughput ◽  
Dna Sequences ◽  
High Throughput Sequencing ◽  
Regulatory Elements ◽  
Scoring Method ◽  
Sequencing Technologies ◽  
Wide Range ◽  
Multiple Species ◽  
Eukaryotic Organisms ◽  
The Impact

High-throughput sequencing technologies have greatly accelerated the progress of genomics, transcriptomics, and metagenomics. Currently, a large amount of genomic data from various organisms is being generated, the volume of which is increasing every year. Therefore, the development of methods that allow the rapid search and analysis of DNA sequences is urgent. Here, we present a novel motif-based high-throughput sequence scoring method that generates genome information. We found and identified Utf1-like, Fgf4-like, and Hoxb1-like motifs, which are cis-regulatory elements for the pluripotency transcription factors Sox2 and Oct4 within the genomes of different eukaryotic organisms. The genome-wide analysis of these motifs was performed to understand the impact of their diversification on mammalian genome evolution. Utf1-like, Fgf4-like, and Hoxb1-like motif diversity was evaluated across genomes from multiple species.

scholarly journals Defining ecological regions in Italy based on a multivariate clustering approach: A first step towards a targeted vector borne disease surveillance

PLoS ONE ◽  
2019 ◽  
Vol 14 (7) ◽  
pp. e0219072 ◽  
Author(s):  
Carla Ippoliti ◽  
Luca Candeloro ◽  
Marius Gilbert ◽  
Maria Goffredo ◽  
Giuseppe Mancini ◽  
...  
Keyword(s):  
Disease Surveillance ◽  
Vector Borne Disease ◽  
Ecological Regions ◽  
Clustering Approach ◽  
Vector Borne ◽  
Multivariate Clustering

scholarly journals Advancing the Science of Tick and Tick-Borne Disease Surveillance in the United States

Insects ◽  
2019 ◽  
Vol 10 (10) ◽  
pp. 361 ◽  
Author(s):  
Samantha Wisely ◽  
Gregory Glass
Keyword(s):  
Public Health ◽  
United States ◽  
Workforce Development ◽  
Disease Surveillance ◽  
The United States ◽  
Centers Of Excellence ◽  
Public Health Burden ◽  
Vector Borne Disease ◽  
Tick Borne Disease ◽  
Vector Borne

Globally, vector-borne diseases are an increasing public health burden; in the United States, tick-borne diseases have tripled in the last three years. The United States Centers for Disease Control and Prevention (CDC) recognizes the need for resilience to the increasing vector-borne disease burden and has called for increased partnerships and sustained networks to identify and respond to the most pressing challenges that face vector-borne disease management, including increased surveillance. To increase applied research, develop communities of practice, and enhance workforce development, the CDC has created five regional Centers of Excellence in Vector-borne Disease. These Centers are a partnership of public health agencies, vector control groups, academic institutions, and industries. This special issue on tick and tick-borne disease surveillance is a collection of research articles on multiple aspects of surveillance from authors that are affiliated with or funded by the CDC Centers of Excellence. This body of work illustrates a community-based system of research by which participants share common problems and use integrated methodologies to produce outputs and effect outcomes that benefit human, animal and environmental health.

scholarly journals Accurate detection for a wide range of mutation and editing sites of microRNAs from small RNA high-throughput sequencing profiles

2016 ◽  
Vol 44 (14) ◽  
pp. e123-e123 ◽  
Author(s):  
Yun Zheng ◽  
Bo Ji ◽  
Renhua Song ◽  
Shengpeng Wang ◽  
Ting Li ◽  
...  
Keyword(s):  
High Throughput ◽  
Small Rna ◽  
High Throughput Sequencing ◽  
Accurate Detection ◽  
Wide Range

scholarly journals Microbial Communities Associated with Farmed Genypterus chilensis: Detection in Water Prior to Bacterial Outbreaks Using Culturing and High-Throughput Sequencing

Animals ◽  
2020 ◽  
Vol 10 (6) ◽  
pp. 1055 ◽  
Author(s):  
Arturo Levican ◽  
Jenny C. Fisher ◽  
Sandra L. McLellan ◽  
Ruben Avendaño-Herrera
Keyword(s):  
Bacterial Community ◽  
High Throughput ◽  
Native Species ◽  
High Throughput Sequencing ◽  
Disease Outbreaks ◽  
Emerging Pathogens ◽  
Prophylactic Measures ◽  
Almost All ◽  
Conger Eel ◽  
Genypterus Chilensis

The red conger eel (Genypterus chilensis, Guichenot) is a native species included in the Chilean Aquaculture Diversification Program due to high commercial demand. In the context of intensified farming, prior reports link two disease outbreaks with emerging pathogens in the Vibrio and Tenacibaculum genera. However, the roles remain unclear for the bacterial community and each specific bacterium is associated with the rearing environment for healthy specimens. The success of red conger eel farming therefore warrants research into the bacterial composition of aquaculture conditions and the antimicrobial susceptibilities thereof. This study used culturing methods and high-throughput sequencing to describe the bacterial community associated with water in which G. chilensis was farmed. With culturing methods, the predominant genera were Vibrio (21.6%), Pseudolteromonas (15.7%), Aliivibrio (13.7%), and Shewanella (7.8%). Only a few bacterial isolates showed amylase, gelatinase, or lipase activity, and almost all showed inhibition zones to commonly-used antibiotics in aquaculture. By contrast, high-throughput sequencing established Paraperlucidibaca, Colwellia, Polaribacter, Saprospiraceae, and Tenacibaculum as the predominant genera, with Vibrio ranking twenty-seventh in abundance. High-throughput sequencing also established a link between previous outbreaks with increased relative abundances of Vibrio and Tenacibaculum. Therefore, monitoring the presence and abundance of these potential pathogens could be useful in providing prophylactic measures to prevent future outbreaks.

scholarly journals jackalope: a swift, versatile phylogenomic and high-throughput sequencing simulator

2019 ◽  
Author(s):  
Lucas A. Nell
Keyword(s):  
High Throughput ◽  
High Throughput Sequencing ◽  
Population Genomics ◽  
R Package ◽  
Gene Trees ◽  
Sequencing Platform ◽  
Genomic Variants ◽  
Pacific Biosciences ◽  
Wide Range ◽  
Reference Genomes

AbstractHigh-throughput sequencing (HTS) is central to the study of population genomics and has an increasingly important role in constructing phylogenies. Choices in research design for sequencing projects can include a wide range of factors, such as sequencing platform, depth of coverage, and bioinformatic tools. Simulating HTS data better informs these decisions. However, current standalone HTS simulators cannot generate genomic variants under even somewhat complex evolutionary scenarios, which greatly reduces their usefulness for fields such as population genomics and phylogenomics. Here I present the R package jackalope that simply and efficiently simulates (i) variants from reference genomes and (ii) reads from both Illumina and Pacific Biosciences (PacBio) platforms. Genomic variants can be simulated using phylogenies, gene trees, coalescent-simulation output, population-genomic summary statistics, and Variant Call Format (VCF) files. jackalope can simulate single, paired-end, or mate-pair Illumina reads, as well as reads from Pacific Biosciences. These simulations include sequencing errors, mapping qualities, multiplexing, and optical/PCR duplicates. It can read reference genomes from FASTA files and can simulate new ones, and all outputs can be written to standard file formats. jackalope is available for Mac, Windows, and Linux systems.

scholarly journals Learning Sparse Log-Ratios for High-Throughput Sequencing Data

2021 ◽  
Author(s):  
Elliott Gordon-Rodriguez ◽  
Thomas P. Quinn ◽  
John P. Cunningham
Keyword(s):  
High Throughput ◽  
Latent Variables ◽  
High Throughput Sequencing ◽  
Compositional Data ◽  
Predictive Accuracy ◽  
Learning Algorithm ◽  
Sequencing Data ◽  
Genetic Sequencing ◽  
Wide Range ◽  
Benchmark Datasets

AbstractThe automatic discovery of interpretable features that are associated to an outcome of interest is a central goal of bioinformatics. In the context of high-throughput genetic sequencing data, and Compositional Data more generally, an important class of features are the log-ratios between subsets of the input variables. However, the space of these log-ratios grows combinatorially with the dimension of the input, and as a result, existing learning algorithms do not scale to increasingly common high-dimensional datasets. Building on recent literature on continuous relaxations of discrete latent variables, we design a novel learning algorithm that identifies sparse log-ratios several orders of magnitude faster than competing methods. As well as dramatically reducing runtime, our method outperforms its competitors in terms of sparsity and predictive accuracy, as measured across a wide range of benchmark datasets.

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