An Overview of DNA-Based Applications for the Assessment of Benthic Macroinvertebrates Biodiversity in Mediterranean Aquatic Ecosystems
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DNA Metabarcoding of Microbial Communities for Healthcare I
Reviews ISSN 1993-6842 (on-line); ISSN 0233-7657 (print) Biopolymers and Cell. 2016. Vol. 32. N 1. P 3–8 doi: http://dx.doi.org/10.7124/bc.000906 UDC 577.25 + 579.61 DNA metabarcoding of microbial communities for healthcare I. Ye. Zaets1, O. V. Podolich1, O. N. Reva2, N. O. Kozyrovska1 1 Institute of Molecular Biology and Genetics, NAS of Ukraine, 150, Akademika Zabolotnoho Str., Kyiv, Ukraine, 03680 2 Department of Biochemistry, Bioinformatics and Computational Biology Unit, University of Pretoria Lynnwood road, Hillcrest, Pretoria, South Africa, 0002 [email protected], [email protected], [email protected] High-throughput sequencing allows obtaining DNA barcodes of multiple species of microorganisms from a single environmental sample. Next Generation Sequencing (NGS)-based profiling provides new opportunities to evaluate the human health effect of microbial community members affiliated to probiotics. DNA metabar- coding may serve as a quality control of microbial communities, comprising complex probiotics and other fermented foods. A detailed inventory of complex communities is a pre-requisite of understanding their func- tionality as whole entities that makes it possible to design more effective bio-products by precise replacement of one community member by others. The present paper illustrates how the NGS-based DNA metabarcoding allows profiling of both wild and hybrid multi-microbial communities with the example of a kombucha probi- otic beverage fermented by yeast-bacterial partners. Keywords: DNA metabarcoding, microbial communities, healthcare, -
Metagenomics Approaches for the Detection and Surveillance of Emerging and Recurrent Plant Pathogens
microorganisms Review Metagenomics Approaches for the Detection and Surveillance of Emerging and Recurrent Plant Pathogens Edoardo Piombo 1,2 , Ahmed Abdelfattah 3,4 , Samir Droby 5, Michael Wisniewski 6,7, Davide Spadaro 1,8,* and Leonardo Schena 9 1 Department of Agricultural, Forest and Food Sciences (DISAFA), University of Torino, 10095 Grugliasco, Italy; [email protected] 2 Department of Forest Mycology and Plant Pathology, Uppsala Biocenter, Swedish University of Agricultural Sciences, P.O. Box 7026, 75007 Uppsala, Sweden 3 Institute of Environmental Biotechnology, Graz University of Technology, Petersgasse 12, 8010 Graz, Austria; [email protected] 4 Department of Ecology, Environment and Plant Sciences, University of Stockholm, Svante Arrhenius väg 20A, 11418 Stockholm, Sweden 5 Department of Postharvest Science, Agricultural Research Organization (ARO), The Volcani Center, Rishon LeZion 7505101, Israel; [email protected] 6 U.S. Department of Agriculture—Agricultural Research Service (USDA-ARS), Kearneysville, WV 25430, USA; [email protected] 7 Department of Biological Sciences, Virginia Technical University, Blacksburg, VA 24061, USA 8 AGROINNOVA—Centre of Competence for the Innovation in the Agroenvironmental Sector, University of Torino, 10095 Grugliasco, Italy 9 Department of Agriculture, Università Mediterranea, 89122 Reggio Calabria, Italy; [email protected] * Correspondence: [email protected]; Tel.: +39-0116708942 Abstract: Globalization has a dramatic effect on the trade and movement of seeds, fruits and vegeta- bles, with a corresponding increase in economic losses caused by the introduction of transboundary Citation: Piombo, E.; Abdelfattah, A.; plant pathogens. Current diagnostic techniques provide a useful and precise tool to enact surveillance Droby, S.; Wisniewski, M.; Spadaro, protocols regarding specific organisms, but this approach is strictly targeted, while metabarcoding D.; Schena, L. -
Wisconsin's Water Quality Monitoring Strategy 2015-2020 Page 1 A
A Product of the 2013‐14 Monitoring Success Workgroup for the Water Division and USEPA Photo by Richard Hurd, Sunset at Big Spring, 05‐11‐2014 Water from Big Spring, in the University of Wisconsin‐Madison Arboretum, Wisconsin’s Water Quality MonitoringFlowing Strategy toward Lake2015 Wingra‐2020 on a spring evening at sunset Page 1 Wisconsin’s Water Monitoring Strategy 2015 to 2020 Water Quality Monitoring Coordination Team Team Sponsor Susan Sylvester, Water Quality Bureau Director Team Leader Tim Asplund, Monitoring Section Chief Monitoring Workgroup Steering Team Tim Asplund, Katie Hein, Lisa Helmuth, Ruth Person, Mike Shupryt Wisconsin Monitoring Workgroup and Contributors Citizen Monitoring: Kris Stepenuck, Laura Herman, Christina Anderson, Lindsey Albright Field Biologists: Mark Hazuga, Jim Amrhein, Mary Gansberg, Jim Kreitlow Fisheries Management: Tim Simonson, Lori Tate, Candy Schrank Groundwater Management: Mel Vollbrecht Lakes and Rivers: Carroll Schaal, Scott Van Egeren, Maureen Ferry Mississippi River Unit: John Sullivan, Sara Strassman, James Fischer Monitoring: Mike Shupryt, Katie Hein, Mike Miller, Tom Bernthal, Elizabeth Haber, Lisa Helmuth, Tom Bernthal Office of the Great Lakes: Andy Fayram, Donalea Dinsmore, Steve Galarneau Science Services: Matt Diebel, John Lyons, Ron Arneson Water Evaluation: Brian Weigel, Aaron Larson, Kristi Minahan, Water Resources Supervisors: Greg Searle, Paul LaLiberte, James Hansen Wastewater: Diane Figiel Water Use: Shaili Pfeiffer, Jeff Helmuth Watershed Management: Corinne Billings, Heidi Kennedy, Pat Trochlell, Cheryl Laatsch USEPA: Ed Hammer, Linda Holst, Pete Jackson EGAD #3200‐2016‐01 This document can be found on the WDNR Website at: http://dnr.wi.gov/topic/surfacewater/monitoring.html The Wisconsin Department of Natural Resources provides equal opportunity in its employment, programs, services, and functions under an Affirmative Action Plan. -
Cristescu TREE 2014.Pdf
TREE-1853; No. of Pages 6 Opinion From barcoding single individuals to metabarcoding biological communities: towards an integrative approach to the study of global biodiversity Melania E. Cristescu Department of Biology, McGill University, Montreal, QC H3A 1B1, Canada DNA-based species identification, known as barcoding, introduced by Arnot et al. [6] and was firmly advanced transformed the traditional approach to the study of and standardized by Hebert et al. [7]. The simple idea of biodiversity science. The field is transitioning from bar- using a short DNA fragment as a barcode (see Glossary) for coding individuals to metabarcoding communities. This identifying species across the Metazoa has been both revolution involves new sequencing technologies, bio- strongly embraced and vigorously scrutinized over the past informatics pipelines, computational infrastructure, and decade [8,9]. Nevertheless, the efforts led by Paul Hebert, experimental designs. In this dynamic genomics land- and supported by the Consortium for the Barcode of Life scape, metabarcoding studies remain insular and biodi- (CBoL; http://www.barcodeoflife.org/) resulted in a global versity estimates depend on the particular methods enterprise that combined molecular tools with valuable but used. In this opinion article, I discuss the need for a scarce taxonomic expertise [10,11]. Today, DNA barcodes coordinated advancement of DNA-based species identi- are being used commonly to identify specimens and the fication that integrates taxonomic and barcoding infor- approach has wide applications in biodiversity conserva- mation. Such an approach would facilitate access to tion, environmental management, invasion biology, the almost 3 centuries of taxonomic knowledge and 1 de- study of trophic interactions, and food safety [12–14]. -
Edna in a Bottleneck: Obstacles to Fish Metabarcoding Studies in Megadiverse Freshwater 3 Systems 4 5 Authors: 6 Jake M
bioRxiv preprint doi: https://doi.org/10.1101/2021.01.05.425493; this version posted January 7, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC 4.0 International license. 1 Title: 2 eDNA in a bottleneck: obstacles to fish metabarcoding studies in megadiverse freshwater 3 systems 4 5 Authors: 6 Jake M. Jackman1, Chiara Benvenuto1, Ilaria Coscia1, Cintia Oliveira Carvalho2, Jonathan S. 7 Ready2, Jean P. Boubli1, William E. Magnusson3, Allan D. McDevitt1* and Naiara Guimarães 8 Sales1,4* 9 10 Addresses: 11 1Environment and Ecosystem Research Centre, School of Science, Engineering and Environment, 12 University of Salford, Salford, M5 4WT, UK 13 2Centro de Estudos Avançados de Biodiversidade, Instituto de Ciências Biológicas, Universidade 14 Federal do Pará, Belém, Brazil 15 3Coordenação de Biodiversidade, Instituto Nacional de Pesquisas da Amazônia, Manaus, 16 Amazonas, Brazil 17 4CESAM - Centre for Environmental and Marine Studies, Departamento de Biologia Animal, 18 Faculdade de Ciências da Universidade de Lisboa, Lisbon, Portugal 19 20 *Corresponding authors: 21 Naiara Guimarães Sales, [email protected] 22 Allan McDevitt, [email protected] 23 24 Running title: Obstacles to eDNA surveys in megadiverse systems 25 26 Keywords: Amazon, barcoding gap, freshwater, MiFish, Neotropics, reference database, 27 taxonomic resolution 28 1 bioRxiv preprint doi: https://doi.org/10.1101/2021.01.05.425493; this version posted January 7, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. -
Metabarcoding in the Abyss: Uncovering Deep-Sea Biodiversity Through Environmental
Metabarcoding in the abyss : uncovering deep-sea biodiversity through environmental DNA Miriam Isabelle Brandt To cite this version: Miriam Isabelle Brandt. Metabarcoding in the abyss : uncovering deep-sea biodiversity through environmental DNA. Agricultural sciences. Université Montpellier, 2020. English. NNT : 2020MONTG033. tel-03197842 HAL Id: tel-03197842 https://tel.archives-ouvertes.fr/tel-03197842 Submitted on 14 Apr 2021 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. THÈSE POUR OBTENIR LE GRADE DE DOCTEUR DE L’UNIVERSITÉ DE M ONTPELLIER En Sciences de l'Évolution et de la Biodiversité École doctorale GAIA Unité mixte de recherche MARBEC Pourquoi Pas les Abysses ? L’ADN environnemental pour l’étude de la biodiversité des grands fonds marins Metabarcoding in the abyss: uncovering deep - sea biodiversity through environmental DNA Présentée par Miriam Isabelle BRANDT Le 10 juillet 2020 Sous la direction de Sophie ARNAUD-HAOND et Daniela ZEPPILLI Devant le jury composé de Sofie DERYCKE, Senior researcher/Professeur rang A, ILVO, Belgique Rapporteur -
Aquatic Biomonitoring Programme for Tweefontein Complex
Tweefontein Biomonitoring Programme: Wet Season Survey (April 2015) AQUATIC BIOMONITORING PROGRAMME FOR TWEEFONTEIN COMPLEX 2015 POST WET SEASON BIOMONITORING SURVEY Report reference: TFN/A/2015 Prepared by: Dr. P. Kotze (Pr.Sci.Nat. 400413/04) Mr. A. Strydom Clean Stream Biological Services P.O.Box 1358 Malalane 1320 Cell: 082-890-6452 Email: [email protected] Fax: 086-628-6926 Clean Stream Biological Services Tweefontein Biomonitoring Programme: Wet Season Biomonitoring Survey (April 2015) EXECUTIVE SUMMARY This report is based on the results of the biomonitoring and aquatic biodiversity survey conducted during April 2015 on selected sites in the Tweefontein Complex surface rights area. Where applicable, reference is also made previous surveys in order to establish temporal trends. The primary objective of the biomonitoring survey was to monitor the potential impacts of the Tweefontein Complex activities on the receiving water bodies. Sites were selected strategically in the Tweefontein Spruit, Zaaiwater Spruit and its tributaries, pan wetlands and pollution control facilities within the study area. This survey included the application of various protocols, such as aquatic macro-invertebrate sampling (SASS5), habitat assessment and toxicity testing of selected water sources in the study area. Some of the sampling sites were dry at the time of sampling and therefore no biomonitoring protocols could be applied, limiting spatial and temporal trend analyses. The following conclusions were drawn from the April 2015 biomonitoring survey at Tweefontein complex, with reference to long-term trends where applicable: Tweefontein Spruit catchment: Due to the lack of flow during the April 2015 survey selected biomonitoring protocols could not be applied at the biomonitoring sites. -
Experimental Quantification of Pollen with DNA Metabarcoding Using
www.nature.com/scientificreports OPEN Experimental quantifcation of pollen with DNA metabarcoding using ITS1 and trnL Sandra Baksay 1*, André Pornon1, Monique Burrus1, Jérôme Mariette2, Christophe Andalo1 & Nathalie Escaravage1 Although the use of metabarcoding to identify taxa in DNA mixtures is widely approved, its reliability in quantifying taxon abundance is still the subject of debate. In this study we investigated the relationships between the amount of pollen grains in mock solutions and the abundance of high- throughput sequence reads and how the relationship was afected by the pollen counting methodology, the number of PCR cycles, the type of markers and plant species whose pollen grains have diferent characteristics. We found a signifcant positive relationship between the number of DNA sequences and the number of pollen grains in the mock solutions. However, better relationships were obtained with light microscopy as a pollen grain counting method compared with fow cytometry, with the chloroplastic trnL marker compared with ribosomal ITS1 and with 30 when compared with 25 or 35 PCR cycles. We provide a list of recommendations to improve pollen quantifcation. Environmental DNA metabarcoding is a molecular method that consists of investigating environmental DNA samples made of complex mixtures of genomes from numerous organisms1. Due to new sequencing technologies and bioinformatics tools, metabarcoding has been increasingly used to identify taxa in environmental samples1 to monitor biodiversity2–4, to investigate ecosystem functioning5 and interaction networks6–8, in both aquatic and terrestrial ecosystems. Nevertheless, its reliability in quantitative approaches, which depend on the match between counts of high-throughput sequence reads and the amount of sampled biological material2, is still the subject of debate9,10. -
Aquatic Biomonitoring at Greens Creek Mine, 2006 by James D
Technical Report No. 07-02 Aquatic Biomonitoring at Greens Creek Mine, 2006 by James D. Durst Laura L. Jacobs May 2007 Alaska Department of Natural Resources Office of Habitat Management and Permitting Cover: Benthic macroinvertebrate sampling at Upper Greens Creek Site 48, 2006. ADNR/OHMP photo. The Alaska Department of Natural Resources administers all programs and activities free from discrimination based on race, color, national origin, age, sex, religion, marital status, pregnancy, parenthood, or disability. The department administers all programs and activities in compliance with Title VI of the Civil Rights Act of 1964, Section 504 of the Rehabilitation Act of 1973, Title II of the Americans with Disabilities Act of 1990, the Age Discrimination Act of 1975, and Title IX of the Education Amendments of 1972. If you believe you have been discriminated against in any program, activity, or facility, or if you desire further information please write to DNR, 1300 College Road, Fairbanks, Alaska 99701; U.S. Fish and Wildlife Service, 4040 N. Fairfax Drive, Suite 300 Webb, Arlington, VA 22203; or O.E.O., U.S. Department of the Interior, Washington DC 20240. For information on alternative formats for this and other department publications, please contact the department ADA Coordinator at (voice) 907-269-8549 or (TDD) 907-269-8411. Aquatic Biomonitoring at Greens Creek Mine, 2006 Technical Report No. 07-02 by James D. Durst Laura L. Jacobs May 2007 Kerry Howard, Executive Director Office of Habitat Management and Permitting Alaska Department of Natural Resources Juneau, AK Suggested Citation: Durst, James D., and Laura L. Jacobs. -
Ontario Benthos Biomonitoring Network
ONTARIO BENTHOS BIOMONITORING NETWORK PROTOCOL MANUAL Version 1.0 May 2004 Ontario Benthos Biomonitoring Network Protocol Manual Version 1.0 May 2004 Report prepared by: C. Jones1, K.M. Somers1, B. Craig2, and T. Reynoldson3 1Ontario Ministry of Environment, Environmental Monitoring and Reporting Branch, Biomonitoring Section, Dorset Environmental Science Centre, 1026 Bellwood Acres Road, P.O. Box 39, Dorset, ON, P0A 1E0 2Environment Canada, EMAN Coordinating Office, 867 Lakeshore Road, Burlington, ON, L7R 4A6 3Acadia Centre for Estuarine Research, Box 115 Acadia University, Wolfville, Nova Scotia, B4P 2R6 2 1 Executive Summary The main purpose of the Ontario Benthos Biomonitoring Network (OBBN) is to enable assessment of aquatic ecosystem condition using benthos as indicators of water and habitat quality. This manual is a companion to the OBBN Terms of Reference, which detail the network’s objectives, deliverables, development schedule, and implementation plan. Herein we outline recommended sampling, sample processing, and analytical procedures for the OBBN. To test whether an aquatic system has been impaired by human activity, a reference condition approach (RCA) is used to compare benthos at “test sites” (where biological condition is in question) to benthos from multiple, minimally impacted “reference sites”. Because types and abundances of benthos are determined by environmental attributes (e.g., catchment size, substrate type), a combination of catchment- and site-scale habitat characteristics are used to ensure test sites are compared to appropriate reference sites. A variety of minimally impacted sites must be sampled in order to evaluate the wide range of potential test sites in Ontario. We detail sampling and sample processing methods for lakes, streams, and wetlands. -
Characterization of Bacterial Communities Associated
www.nature.com/scientificreports OPEN Characterization of bacterial communities associated with blood‑fed and starved tropical bed bugs, Cimex hemipterus (F.) (Hemiptera): a high throughput metabarcoding analysis Li Lim & Abdul Hafz Ab Majid* With the development of new metagenomic techniques, the microbial community structure of common bed bugs, Cimex lectularius, is well‑studied, while information regarding the constituents of the bacterial communities associated with tropical bed bugs, Cimex hemipterus, is lacking. In this study, the bacteria communities in the blood‑fed and starved tropical bed bugs were analysed and characterized by amplifying the v3‑v4 hypervariable region of the 16S rRNA gene region, followed by MiSeq Illumina sequencing. Across all samples, Proteobacteria made up more than 99% of the microbial community. An alpha‑proteobacterium Wolbachia and gamma‑proteobacterium, including Dickeya chrysanthemi and Pseudomonas, were the dominant OTUs at the genus level. Although the dominant OTUs of bacterial communities of blood‑fed and starved bed bugs were the same, bacterial genera present in lower numbers were varied. The bacteria load in starved bed bugs was also higher than blood‑fed bed bugs. Cimex hemipterus Fabricus (Hemiptera), also known as tropical bed bugs, is an obligate blood-feeding insect throughout their entire developmental cycle, has made a recent resurgence probably due to increased worldwide travel, climate change, and resistance to insecticides1–3. Distribution of tropical bed bugs is inclined to tropical regions, and infestation usually occurs in human dwellings such as dormitories and hotels 1,2. Bed bugs are a nuisance pest to humans as people that are bitten by this insect may experience allergic reactions, iron defciency, and secondary bacterial infection from bite sores4,5. -
Introduction to Bioinformatics Analysis of Metabarcoding Data
Introduction to Bioinformatics analysis of Metabarcoding data Theoretical part Alvaro Sebastián Yagüe www.sixthresearcher.com @SixthResearcher • Experimental design • Sampling • Sample processing • Sequencing • Sequence processing www.sixthresearcher.com @SixthResearcher • Experimental design • Sampling • Sample processing • Sequencing • Sequence processing www.sixthresearcher.com @SixthResearcher What do we want to sequence? Whole genome sequencing (WGS) ChIP-seq Amplicon sequencing (AS) Whole exome sequencing (WES) RNA-seq Mass spectrometry www.sixthresearcher.com @SixthResearcher How do we want to sequence? Green,E.D. (2001) Strategies for the systematic sequencing of complex www.sixthresearcher.com genomes. Nat. Rev. Genet., 2, 573–583. @SixthResearcher Metagenomics - Shotgun sequencing www.sixthresearcher.com @SixthResearcher Metagenomics - High-throughput sequencing DNA extraction DNA fragmentation and sequencing Read mapping to reference genome De novo assembly Chimeras! www.sixthresearcher.com @SixthResearcher Metabarcoding - Amplicon sequencing 1. PCR amplification and sample tagging Barcode 1 Barcode 2 Barcode 3 2. Sequencing of PCR products 3. De-multiplexing of reads Samples 1 2 3 4 5 6 Barcode 1 Barcode 2 Barcode 3 www.sixthresearcher.com @SixthResearcher Metabarcoding vs Metagenomics Kress, W. J., & Erickson, D. L. (2008). DNA barcodes: genes, genomics, and bioinformatics. Proceedings of the National Academy of Sciences of the United States of America, 105(8), 2761–2. www.sixthresearcher.com @SixthResearcher Metabarcoding vs Metagenomics http://luckylion.de/2015/10/11/dna-metabarcoding-vs-metagenomics/ www.sixthresearcher.com @SixthResearcher • Experimental design • Sampling • Sample processing • Sequencing • Sequence processing www.sixthresearcher.com @SixthResearcher ➢ Where? Variability in abundance within soil and plant. Consider vertical and horizontal distribution of fungi. ➢ When? Temporal dynamics over short and long term. For complete community census, sample across multiple seasons.