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Tuliebieke T, Abdullah, Zhang H, Yan R, Li H, Zhang Y, Zhang T, Ahmed I, Li T, Tian X. Exploring the biological diversity and source species of medicinal horseflies through metabarcoding. Gene 2024; 913:148356. [PMID: 38462022 DOI: 10.1016/j.gene.2024.148356] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2023] [Revised: 02/22/2024] [Accepted: 03/07/2024] [Indexed: 03/12/2024]
Abstract
Horseflies from the Tabanidae family play a significant role in traditional Chinese medicine to treat various health conditions, including coronary heart disease, stroke, headaches, liver cirrhosis, psoriasis, and hepatic carcinoma. There are 27 species of Tabaninae (Tabanidae) used as medicine, and they showed high morphological similarities with those for which medicinal properties have not been reported. Nonetheless, there have been reports suggesting that medicinal crude drugs sometimes contain irrelevant or false species, impacting the drug's efficacy. In this current study, we collected 14 batches, totaling 13,528 individuals, from various provinces in China. Instead of "classic" DNA barcoding strategy, we employed a high-throughput metabarcoding approach to assess the biological composition of crude drug mixtures derived from horseflies. Our analysis identified 40 Amplicon Sequence Variants (ASVs) with similarity percentages ranging from 92% to 100% with 12 previously reported species. Species delimitation methods revealed the presence of 11 Molecular Operational Taxonomic Units (MOTUs), with ten belonging to the Tabanus genus and one to Hybomitra. Tabanus sp6 displayed the highest relative abundance, and its ASVs showed close resemblance to Tabanus pleski. Our investigations revealed that the medicinal batches were biologically composed of 6 to 12 species. Some batches contained ASVs that closely resembled species previously associated with false Tabanus species. In conclusion, our findings offer valuable insights into the biological composition of crude drugs derived from horseflies and have the potential to enhance the quality of these traditional medicines.
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Affiliation(s)
- Tenukeguli Tuliebieke
- State Key Laboratory of Component-Based Chinese Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin 301617, China; Haihe Laboratory of Modern Chinese Medicine, Tianjin 301617, China.
| | - Abdullah
- State Key Laboratory of Component-Based Chinese Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin 301617, China; Haihe Laboratory of Modern Chinese Medicine, Tianjin 301617, China.
| | - Huanyu Zhang
- School of Pharmaceutical Science and Technology, Tianjin University, Tianjin, China.
| | - Rushan Yan
- State Key Laboratory of Component-Based Chinese Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin 301617, China; Haihe Laboratory of Modern Chinese Medicine, Tianjin 301617, China.
| | - Hui Li
- State Key Laboratory of Component-Based Chinese Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin 301617, China; Haihe Laboratory of Modern Chinese Medicine, Tianjin 301617, China.
| | - Yue Zhang
- State Key Laboratory of Component-Based Chinese Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin 301617, China; Haihe Laboratory of Modern Chinese Medicine, Tianjin 301617, China.
| | - Tingting Zhang
- State Key Laboratory of Component-Based Chinese Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin 301617, China; Haihe Laboratory of Modern Chinese Medicine, Tianjin 301617, China.
| | - Ibrar Ahmed
- Alpha Genomics Private Limited, Islamabad 45710, Pakistan; Microbiological Analysis Team, Group for Biometrology, Korea Research Institute of Standards Band Science (KRISS), Daejeon 34113, Republic of Korea.
| | - Tianxiang Li
- State Key Laboratory of Component-Based Chinese Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin 301617, China; Haihe Laboratory of Modern Chinese Medicine, Tianjin 301617, China.
| | - Xiaoxuan Tian
- State Key Laboratory of Component-Based Chinese Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin 301617, China; Haihe Laboratory of Modern Chinese Medicine, Tianjin 301617, China.
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2
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Pawlowski J, Bruce K, Panksep K, Aguirre FI, Amalfitano S, Apothéloz-Perret-Gentil L, Baussant T, Bouchez A, Carugati L, Cermakova K, Cordier T, Corinaldesi C, Costa FO, Danovaro R, Dell'Anno A, Duarte S, Eisendle U, Ferrari BJD, Frontalini F, Frühe L, Haegerbaeumer A, Kisand V, Krolicka A, Lanzén A, Leese F, Lejzerowicz F, Lyautey E, Maček I, Sagova-Marečková M, Pearman JK, Pochon X, Stoeck T, Vivien R, Weigand A, Fazi S. Environmental DNA metabarcoding for benthic monitoring: A review of sediment sampling and DNA extraction methods. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 818:151783. [PMID: 34801504 DOI: 10.1016/j.scitotenv.2021.151783] [Citation(s) in RCA: 23] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/11/2021] [Revised: 11/06/2021] [Accepted: 11/14/2021] [Indexed: 06/13/2023]
Abstract
Environmental DNA (eDNA) metabarcoding (parallel sequencing of DNA/RNA for identification of whole communities within a targeted group) is revolutionizing the field of aquatic biomonitoring. To date, most metabarcoding studies aiming to assess the ecological status of aquatic ecosystems have focused on water eDNA and macroinvertebrate bulk samples. However, the eDNA metabarcoding has also been applied to soft sediment samples, mainly for assessing microbial or meiofaunal biota. Compared to classical methodologies based on manual sorting and morphological identification of benthic taxa, eDNA metabarcoding offers potentially important advantages for assessing the environmental quality of sediments. The methods and protocols utilized for sediment eDNA metabarcoding can vary considerably among studies, and standardization efforts are needed to improve their robustness, comparability and use within regulatory frameworks. Here, we review the available information on eDNA metabarcoding applied to sediment samples, with a focus on sampling, preservation, and DNA extraction steps. We discuss challenges specific to sediment eDNA analysis, including the variety of different sources and states of eDNA and its persistence in the sediment. This paper aims to identify good-practice strategies and facilitate method harmonization for routine use of sediment eDNA in future benthic monitoring.
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Affiliation(s)
- J Pawlowski
- Department of Genetics and Evolution, University of Geneva, Geneva, Switzerland; Institute of Oceanology, Polish Academy of Sciences, 81-712 Sopot, Poland; ID-Gene Ecodiagnostics, 1202 Geneva, Switzerland
| | - K Bruce
- NatureMetrics Ltd, CABI Site, Bakeham Lane, Egham TW20 9TY, UK
| | - K Panksep
- Institute of Technology, University of Tartu, Tartu 50411, Estonia; Chair of Hydrobiology and Fishery, Institute of Agricultural and Environmental Sciences, Estonian University of Life Sciences, Tartu, Estonia; Chair of Aquaculture, Institute of Veterinary Medicine and Animal Sciences, Estonian University of Life Sciences, Estonia
| | - F I Aguirre
- Water Research Institute, National Research Council of Italy (IRSA-CNR), Monterotondo, Rome, Italy
| | - S Amalfitano
- Water Research Institute, National Research Council of Italy (IRSA-CNR), Monterotondo, Rome, Italy
| | - L Apothéloz-Perret-Gentil
- Department of Genetics and Evolution, University of Geneva, Geneva, Switzerland; ID-Gene Ecodiagnostics, 1202 Geneva, Switzerland
| | - T Baussant
- Norwegian Research Center AS, NORCE Environment, Marine Ecology Group, Mekjarvik 12, 4070 Randaberg, Norway
| | - A Bouchez
- INRAE, CARRTEL, 74200 Thonon-les-Bains, France
| | - L Carugati
- Department of Life and Environmental Sciences, Polytechnic University of Marche, Via Brecce Bianche, Ancona 60131, Italy
| | - K Cermakova
- ID-Gene Ecodiagnostics, 1202 Geneva, Switzerland
| | - T Cordier
- Department of Genetics and Evolution, University of Geneva, Geneva, Switzerland; NORCE Climate, NORCE Norwegian Research Centre AS, Bjerknes Centre for Climate Research, Jahnebakken 5, 5007 Bergen, Norway
| | - C Corinaldesi
- Department of Materials, Environmental Sciences and Urban Planning, Polytechnic University of Marche, Via Brecce Bianche, Ancona 60131, Italy
| | - F O Costa
- Centre of Molecular and Environmental Biology (CBMA), Department of Biology, University of Minho, Campus de Gualtar, 4710-057 Braga, Portugal; Institute of Science and Innovation for Bio-Sustainability (IB-S), University of Minho, Campus de Gualtar, 4710-057 Braga, Portugal
| | - R Danovaro
- Department of Life and Environmental Sciences, Polytechnic University of Marche, Via Brecce Bianche, Ancona 60131, Italy
| | - A Dell'Anno
- Department of Life and Environmental Sciences, Polytechnic University of Marche, Via Brecce Bianche, Ancona 60131, Italy
| | - S Duarte
- Centre of Molecular and Environmental Biology (CBMA), Department of Biology, University of Minho, Campus de Gualtar, 4710-057 Braga, Portugal; Institute of Science and Innovation for Bio-Sustainability (IB-S), University of Minho, Campus de Gualtar, 4710-057 Braga, Portugal
| | - U Eisendle
- University of Salzburg, Dept. of Biosciences, 5020 Salzburg, Austria
| | - B J D Ferrari
- Swiss Centre for Applied Ecotoxicology (Ecotox Centre), EPFL ENAC IIE-GE, 1015 Lausanne, Switzerland
| | - F Frontalini
- Department of Pure and Applied Sciences, Urbino University, Urbino, Italy
| | - L Frühe
- Technische Universität Kaiserslautern, Ecology Group, D-67663 Kaiserslautern, Germany
| | - A Haegerbaeumer
- Bielefeld University, Animal Ecology, 33615 Bielefeld, Germany
| | - V Kisand
- Institute of Technology, University of Tartu, Tartu 50411, Estonia
| | - A Krolicka
- Norwegian Research Center AS, NORCE Environment, Marine Ecology Group, Mekjarvik 12, 4070 Randaberg, Norway
| | - A Lanzén
- AZTI, Marine Research, Basque Research and Technology Alliance (BRTA), Pasaia, Gipuzkoa, Spain; IKERBASQUE, Basque Foundation for Science, Bilbao, Bizkaia, Spain
| | - F Leese
- University of Duisburg-Essen, Faculty of Biology, Aquatic Ecosystem Research, Germany
| | - F Lejzerowicz
- Center for Microbiome Innovation, University of California, San Diego, La Jolla, CA, USA
| | - E Lyautey
- Univ. Savoie Mont Blanc, INRAE, CARRTEL, 74200 Thonon-les-Bains, France
| | - I Maček
- Biotechnical Faculty, University of Ljubljana, Jamnikarjeva 101, 1000 Ljubljana, Slovenia; Faculty of Mathematics, Natural Sciences and Information Technologies (FAMNIT), University of Primorska, Glagoljaška 8, 6000 Koper, Slovenia
| | - M Sagova-Marečková
- Czech University of Life Sciences, Dept. of Microbiology, Nutrition and Dietetics, Prague, Czech Republic
| | - J K Pearman
- Coastal and Freshwater Group, Cawthron Institute, Private Bag 2, Nelson 7042, New Zealand
| | - X Pochon
- Coastal and Freshwater Group, Cawthron Institute, Private Bag 2, Nelson 7042, New Zealand; Institute of Marine Science, University of Auckland, Warkworth 0941, New Zealand
| | - T Stoeck
- Technische Universität Kaiserslautern, Ecology Group, D-67663 Kaiserslautern, Germany
| | - R Vivien
- Swiss Centre for Applied Ecotoxicology (Ecotox Centre), EPFL ENAC IIE-GE, 1015 Lausanne, Switzerland
| | - A Weigand
- National Museum of Natural History Luxembourg, 25 Rue Münster, L-2160 Luxembourg, Luxembourg
| | - S Fazi
- Water Research Institute, National Research Council of Italy (IRSA-CNR), Monterotondo, Rome, Italy.
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Nagai S, Sildever S, Nishi N, Tazawa S, Basti L, Kobayashi T, Ishino Y. Comparing PCR-generated artifacts of different polymerases for improved accuracy of DNA metabarcoding. METABARCODING AND METAGENOMICS 2022. [DOI: 10.3897/mbmg.6.77704] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Accuracy of PCR amplification is vital for obtaining reliable amplicon-sequencing results by metabarcoding. Here, we performed a comparative analysis of error profiles in the PCR products by 14 different PCR kits using a mock eukaryotic community DNA sample mimicking metabarcoding analysis. To prepare a mock eukaryotic community from the marine environment, equal amounts of plasmid DNA from 40 microalgal species were mixed and used for amplicon-sequencing by a high-throughput sequencing approach. To compare the differences in PCR kits used for this experiment, we focused on the following seven parameters: 1) Quality, 2) Chimera, 3) Blast top hit accuracy, 4) Deletion, 5) Insertion, 6) Base substitution and 7) Amplification bias amongst species. The results showed statistically significant differences (p < 0.05) for all of the seven parameters depending on the PCR kits used. These differences may result from the different DNA polymerases included in each kit, although the result can also be influenced by PCR reaction conditions. Simultaneous analysis of several parameters suggested that kits containing KOD plus Neo (TOYOBO) and HotStart Taq DNA polymerase (BiONEER, CA, US) at the annealing temperature of 65 °C displayed better results in terms of parameters associated with chimeras, top hit similarity and deletions.
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4
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Wang HB, Wu YH, Luo LW, Yu T, Xu A, Xue S, Chen GQ, Ni XY, Peng L, Chen Z, Wang YH, Tong X, Bai Y, Xu YQ, Hu HY. Risks, characteristics, and control strategies of disinfection-residual-bacteria (DRB) from the perspective of microbial community structure. WATER RESEARCH 2021; 204:117606. [PMID: 34500181 PMCID: PMC8390064 DOI: 10.1016/j.watres.2021.117606] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/25/2021] [Revised: 08/19/2021] [Accepted: 08/23/2021] [Indexed: 05/19/2023]
Abstract
The epidemic of COVID-19 has aroused people's particular attention to biosafety. A growing number of disinfection products have been consumed during this period. However, the flaw of disinfection has not received enough attention, especially in water treatment processes. While cutting down the quantity of microorganisms, disinfection processes exert a considerable selection effect on bacteria and thus reshape the microbial community structure to a great extent, causing the problem of disinfection-residual-bacteria (DRB). These systematic and profound changes could lead to the shift in regrowth potential, bio fouling potential, as well as antibiotic resistance level and might cause a series of potential risks. In this review, we collected and summarized the data from the literature in recent 10 years about the microbial community structure shifting of natural water or wastewater in full-scale treatment plants caused by disinfection. Based on these data, typical DRB with the most reporting frequency after disinfection by chlorine-containing disinfectants, ozone disinfection, and ultraviolet disinfection were identified and summarized, which were the bacteria with a relative abundance of over 5% in the residual bacteria community and the bacteria with an increasing rate of relative abundance over 100% after disinfection. Furthermore, the phylogenic relationship and potential risks of these typical DRB were also analyzed. Twelve out of fifteen typical DRB genera contain pathogenic strains, and many were reported of great secretion ability. Pseudomonas and Acinetobacter possess multiple disinfection resistance and could be considered as model bacteria in future studies of disinfection. We also discussed the growth, secretion, and antibiotic resistance characteristics of DRB, as well as possible control strategies. The DRB phenomenon is not limited to water treatment but also exists in the air and solid disinfection processes, which need more attention and more profound research, especially in the period of COVID-19.
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Affiliation(s)
- Hao-Bin Wang
- Environmental Simulation and Pollution Control State Key Joint Laboratory, State Environmental Protection Key Laboratory of Microorganism Application and Risk Control (SMARC), School of Environment, Tsinghua University, Room 524, Beijing 100084, PR China; Beijing Laboratory for Environmental Frontier Technologies, Beijing 100084, PR China
| | - Yin-Hu Wu
- Environmental Simulation and Pollution Control State Key Joint Laboratory, State Environmental Protection Key Laboratory of Microorganism Application and Risk Control (SMARC), School of Environment, Tsinghua University, Room 524, Beijing 100084, PR China; Beijing Laboratory for Environmental Frontier Technologies, Beijing 100084, PR China.
| | - Li-Wei Luo
- Environmental Simulation and Pollution Control State Key Joint Laboratory, State Environmental Protection Key Laboratory of Microorganism Application and Risk Control (SMARC), School of Environment, Tsinghua University, Room 524, Beijing 100084, PR China; Beijing Laboratory for Environmental Frontier Technologies, Beijing 100084, PR China
| | - Tong Yu
- School of Environmental and Municipal Engineering, Qingdao University of Technology, Qingdao 266000, PR China
| | - Ao Xu
- Environmental Simulation and Pollution Control State Key Joint Laboratory, State Environmental Protection Key Laboratory of Microorganism Application and Risk Control (SMARC), School of Environment, Tsinghua University, Room 524, Beijing 100084, PR China; Beijing Laboratory for Environmental Frontier Technologies, Beijing 100084, PR China; Research Institute for Environmental Innovation (Suzhou), Tsinghua, Suzhou Jiangsu 215163, PR China
| | - Song Xue
- Environmental Simulation and Pollution Control State Key Joint Laboratory, State Environmental Protection Key Laboratory of Microorganism Application and Risk Control (SMARC), School of Environment, Tsinghua University, Room 524, Beijing 100084, PR China; Beijing Laboratory for Environmental Frontier Technologies, Beijing 100084, PR China
| | - Gen-Qiang Chen
- Environmental Simulation and Pollution Control State Key Joint Laboratory, State Environmental Protection Key Laboratory of Microorganism Application and Risk Control (SMARC), School of Environment, Tsinghua University, Room 524, Beijing 100084, PR China; Beijing Laboratory for Environmental Frontier Technologies, Beijing 100084, PR China
| | - Xin-Ye Ni
- Environmental Simulation and Pollution Control State Key Joint Laboratory, State Environmental Protection Key Laboratory of Microorganism Application and Risk Control (SMARC), School of Environment, Tsinghua University, Room 524, Beijing 100084, PR China; Beijing Laboratory for Environmental Frontier Technologies, Beijing 100084, PR China
| | - Lu Peng
- Shenzhen Environmental Science and New Energy Technology Engineering Laboratory, Tsinghua-Berkeley Shenzhen Institute, Shenzhen 518055, PR China
| | - Zhuo Chen
- Environmental Simulation and Pollution Control State Key Joint Laboratory, State Environmental Protection Key Laboratory of Microorganism Application and Risk Control (SMARC), School of Environment, Tsinghua University, Room 524, Beijing 100084, PR China; Beijing Laboratory for Environmental Frontier Technologies, Beijing 100084, PR China
| | - Yun-Hong Wang
- Environmental Simulation and Pollution Control State Key Joint Laboratory, State Environmental Protection Key Laboratory of Microorganism Application and Risk Control (SMARC), School of Environment, Tsinghua University, Room 524, Beijing 100084, PR China; Beijing Laboratory for Environmental Frontier Technologies, Beijing 100084, PR China
| | - Xin Tong
- Environmental Simulation and Pollution Control State Key Joint Laboratory, State Environmental Protection Key Laboratory of Microorganism Application and Risk Control (SMARC), School of Environment, Tsinghua University, Room 524, Beijing 100084, PR China; Beijing Laboratory for Environmental Frontier Technologies, Beijing 100084, PR China
| | - Yuan Bai
- Environmental Simulation and Pollution Control State Key Joint Laboratory, State Environmental Protection Key Laboratory of Microorganism Application and Risk Control (SMARC), School of Environment, Tsinghua University, Room 524, Beijing 100084, PR China; Beijing Laboratory for Environmental Frontier Technologies, Beijing 100084, PR China
| | - Yu-Qing Xu
- Environmental Simulation and Pollution Control State Key Joint Laboratory, State Environmental Protection Key Laboratory of Microorganism Application and Risk Control (SMARC), School of Environment, Tsinghua University, Room 524, Beijing 100084, PR China; Beijing Laboratory for Environmental Frontier Technologies, Beijing 100084, PR China
| | - Hong-Ying Hu
- Environmental Simulation and Pollution Control State Key Joint Laboratory, State Environmental Protection Key Laboratory of Microorganism Application and Risk Control (SMARC), School of Environment, Tsinghua University, Room 524, Beijing 100084, PR China; Beijing Laboratory for Environmental Frontier Technologies, Beijing 100084, PR China; Shenzhen Environmental Science and New Energy Technology Engineering Laboratory, Tsinghua-Berkeley Shenzhen Institute, Shenzhen 518055, PR China.
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Dzhembekova N, Rubino F, Nagai S, Zlateva I, Slabakova N, Ivanova P, Slabakova V, Moncheva S. Comparative analysis of morphological and molecular approaches integrated into the study of the dinoflagellate biodiversity within the recently deposited Black Sea sediments - benefits and drawbacks. Biodivers Data J 2020; 8:e55172. [PMID: 32903988 PMCID: PMC7447646 DOI: 10.3897/bdj.8.e55172] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2020] [Accepted: 07/27/2020] [Indexed: 11/23/2022] Open
Abstract
One of the assets, assigned to the phytoplankton resting stages, is that of serving as the “memory” of the aquatic ecosystems and preserved biodiversity in the course of time. However, an accurate cyst identification proves to be a more difficult and extremely challenging process, even today. In order to gain a better taxonomic coverage of cyst assemblages in the Black Sea, an integrated approach of the classical morphological identification with metabarcoding methods (MySeq sequencing of V7-V9 regions of the 18S rDNA) was applied on thirteen surface sediment samples collected from different sites. A total number of 112 dinoflagellate taxa was detected at the species level and ascribed to 51 genera. In general, it is the molecular analysis that yields a higher number of taxa as compared to those obtained through the morphological taxonomy (66 taxa based on the DNA sequences versus 56 morphologically-identified taxa). Besides, it should be pointed out that the integrated dataset includes 14 potentially toxic dinoflagellate species. Discerned, subsequently, was a good dataset consistency for ten species, followed by some discrepancies as to a number of taxa, identified with one of the methods only, due to specific methodological biases. On the whole, it could be concluded that the combination of morphological and molecular methods is likely to increase the potential for a more reliable taxonomic assessment of phytoplankton diversity in marine sediments which, in turn, proves conclusively the utmost importance of the integrated approach.
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Affiliation(s)
- Nina Dzhembekova
- Institute of Oceanology "Fridtjof Nansen", Marine Biology and Ecology Department, Bulgarian Academy of Sciences, Varna, Bulgaria Institute of Oceanology "Fridtjof Nansen", Marine Biology and Ecology Department, Bulgarian Academy of Sciences Varna Bulgaria
| | - Fernando Rubino
- Water Research Institute, Unit Talassografico "A. Cerruti", National Research Council CNR-IRSA, Taranto, Italy Water Research Institute, Unit Talassografico "A. Cerruti", National Research Council CNR-IRSA Taranto Italy
| | - Satoshi Nagai
- National Research Institute of Fisheries Science, Research Center for Aquatic Genomics, Fisheries Research and Education Agency, Yokohama Kanagawa, Japan National Research Institute of Fisheries Science, Research Center for Aquatic Genomics, Fisheries Research and Education Agency Yokohama Kanagawa Japan
| | - Ivelina Zlateva
- Institute of Oceanology "Fridtjof Nansen", Marine Biology and Ecology Department, Bulgarian Academy of Sciences, Varna, Bulgaria Institute of Oceanology "Fridtjof Nansen", Marine Biology and Ecology Department, Bulgarian Academy of Sciences Varna Bulgaria
| | - Nataliya Slabakova
- Institute of Oceanology "Fridtjof Nansen", Marine Biology and Ecology Department, Bulgarian Academy of Sciences, Varna, Bulgaria Institute of Oceanology "Fridtjof Nansen", Marine Biology and Ecology Department, Bulgarian Academy of Sciences Varna Bulgaria
| | - Petya Ivanova
- Institute of Oceanology "Fridtjof Nansen", Marine Biology and Ecology Department, Bulgarian Academy of Sciences, Varna, Bulgaria Institute of Oceanology "Fridtjof Nansen", Marine Biology and Ecology Department, Bulgarian Academy of Sciences Varna Bulgaria
| | - Violeta Slabakova
- Institute of Oceanology "Fridtjof Nansen", Ocean Technologies Department, Bulgarian Academy of Sciences, Varna, Bulgaria Institute of Oceanology "Fridtjof Nansen", Ocean Technologies Department, Bulgarian Academy of Sciences Varna Bulgaria
| | - Snejana Moncheva
- Institute of Oceanology "Fridtjof Nansen", Marine Biology and Ecology Department, Bulgarian Academy of Sciences, Varna, Bulgaria Institute of Oceanology "Fridtjof Nansen", Marine Biology and Ecology Department, Bulgarian Academy of Sciences Varna Bulgaria
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Hirai J, Tachibana A, Tsuda A. Large-scale metabarcoding analysis of epipelagic and mesopelagic copepods in the Pacific. PLoS One 2020; 15:e0233189. [PMID: 32407365 PMCID: PMC7224477 DOI: 10.1371/journal.pone.0233189] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2020] [Accepted: 04/29/2020] [Indexed: 12/12/2022] Open
Abstract
A clear insight into the large-scale community structure of planktonic copepods is critical to understanding the mechanisms controlling diversity and biogeography of marine taxa in terms of their high abundance, ubiquity, and sensitivity to environmental changes. Here, we applied a 28S metabarcoding approach to large-scale communities of epipelagic and mesopelagic copepods at 70 stations across the Pacific Ocean and three stations in the Arctic Ocean. Major patterns of community structure and diversity, influenced by water mass structures, agreed with results from previous morphology-based studies. However, a large-scale metabarcoding approach could detect community changes even under stable environmental conditions, including changes in the north/south subtropical gyres and east/west areas within each subtropical gyre. There were strong effects of the epipelagic environment on mesopelagic communities, and community subdivisions were observed in the environmentally stable mesopelagic layer. In each sampling station, higher operational taxonomic unit (OTU) numbers and lower phylogenetic diversity were observed in the mesopelagic layer than in the epipelagic layer, indicating a recent rapid increase in species numbers in the mesopelagic layer. The phylogenetic analysis utilizing representative sequences of OTUs revealed trends of recent emergence of cold-water OTUs, which are mainly distributed at high latitudes with low water temperatures. Conversely, the high diversity of copepods at low latitudes was suggested to have been formed through long evolution under high water temperature conditions. The metabarcoding results suggest that evolutionary processes have strong impacts on current patterns of copepod diversity, and support the “out of the tropics” theory explaining latitudinal diversity gradients of copepods. Diversity patterns in both epipelagic and mesopelagic copepods was highly correlated to sea surface temperature; thus, predicted global warming may have a significant impact on copepod diversity in both layers.
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Affiliation(s)
- Junya Hirai
- Atmosphere and Ocean Research Institute, The University of Tokyo, Chiba, Japan
- * E-mail:
| | - Aiko Tachibana
- Department of Ocean Sciences, Tokyo University of Marine Science and Technology, Tokyo, Japan
| | - Atsushi Tsuda
- Atmosphere and Ocean Research Institute, The University of Tokyo, Chiba, Japan
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7
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Zhang Q, Geng Z, Li D, Ding Z. Characterization and discrimination of microbial community and co-occurrence patterns in fresh and strong flavor style flue-cured tobacco leaves. Microbiologyopen 2020; 9:e965. [PMID: 31808296 PMCID: PMC7002102 DOI: 10.1002/mbo3.965] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2019] [Revised: 10/22/2019] [Accepted: 10/28/2019] [Indexed: 11/24/2022] Open
Abstract
Fermentation, also known as aging, is vital for enhancing the quality of flue-cured tobacco leaves (FTLs). Aged FTLs demonstrate high-quality sensory characteristics, while unaged FTLs do not. Microbes play important roles in the FTL fermentation process. However, the eukaryotic microbial community diversity is poorly understood, as are microbial associations within FTLs. We aimed to characterize and compare the microbiota associated with two important categories, fresh and strong flavor style FTLs, and to reveal correlations between the microbial taxa within them. Based on 16S and 18S rRNA Illumina MiSeq sequencing, the community richness and diversity of prokaryotes were almost as high as that of eukaryotes. The dominant microbes of FTLs belonged to seven genera, including Pseudomonas, Bacillus, Methylobacterium, Acinetobacter, Sphingomonas, Neophaeosphaeria, and Cladosporium, of the Proteobacteria, Firmicutes, and Ascomycota phyla. According to partial least square discriminant analysis (PLS-DA), Xanthomonas, Franconibacter, Massilia, Quadrisphaera, Staphylococcus, Cladosporium, Lodderomyces, Symmetrospora, Golovinomyces, and Dioszegia were significantly positively correlated with fresh flavor style FTLs, while Xenophilus, Fusarium, unclassified Ustilaginaceae, Tilletiopsis, Cryphonectria, Colletotrichum, and Cyanodermella were significantly positively correlated with strong flavor style FTLs. Network analysis identified seven hubs, Aureimonas, Kocuria, Massilia, Brachybacterium, Clostridium, Dietzia, and Vishniacozyma, that may play important roles in FTL ecosystem stability, which may be destroyed by Myrmecridium. FTL microbiota was found to be correlated with flavor style. Species present in lower numbers than the dominant microbes might be used as microbial markers to discriminate different flavor style samples and to stabilize FTL microbial communities. This research advances our understanding of FTL microbiota and describes a means of discriminating between fresh and strong flavor FTLs based on their respective stable microbiota.
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Affiliation(s)
- Qianying Zhang
- Technical Research CenterChina Tobacco Sichuan Industrial Co., Ltd.ChengduChina
- National Engineering Laboratory for Cereal Fermentation TechnologySchool of BiotechnologyJiangnan UniversityWuxiChina
| | - Zongze Geng
- Technical Research CenterChina Tobacco Sichuan Industrial Co., Ltd.ChengduChina
| | - Dongliang Li
- Technical Research CenterChina Tobacco Sichuan Industrial Co., Ltd.ChengduChina
| | - Zhongyang Ding
- National Engineering Laboratory for Cereal Fermentation TechnologySchool of BiotechnologyJiangnan UniversityWuxiChina
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Li Q, Yu S, Li L, Liu G, Gu Z, Liu M, Liu Z, Ye Y, Xia Q, Ren L. Microbial Communities Shaped by Treatment Processes in a Drinking Water Treatment Plant and Their Contribution and Threat to Drinking Water Safety. Front Microbiol 2017; 8:2465. [PMID: 29312177 PMCID: PMC5733044 DOI: 10.3389/fmicb.2017.02465] [Citation(s) in RCA: 49] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2017] [Accepted: 11/27/2017] [Indexed: 12/02/2022] Open
Abstract
Bacteria play an important role in water purification in drinking water treatment systems. On one hand, bacteria present in the untreated water may help in its purification through biodegradation of the contaminants. On the other hand, some bacteria may be human pathogens and pose a threat to consumers. The present study investigated bacterial communities using Illumina MiSeq sequencing of 16S rRNA genes and their functions were predicted using PICRUSt in a treatment system, including the biofilms on sand filters and biological activated carbon (BAC) filters, in 4 months. In addition, quantitative analyses of specific bacterial populations were performed by real-time quantitative polymerase chain reaction (qPCR). The bacterial community composition of post-ozonation effluent, BAC effluent and disinfected water varied with sampling time. However, the bacterial community structures at other treatment steps were relatively stable, despite great variations of source water quality, resulting in stable treatment performance. Illumina MiSeq sequencing illustrated that Proteobacteria was dominant bacterial phylum. Chlorine disinfection significantly influenced the microbial community structure, while other treatment processes were synergetic. Bacterial communities in water and biofilms were distinct, and distinctions of bacterial communities also existed between different biofilms. By contrast, the functional composition of biofilms on different filters were similar. Some functional genes related to pollutant degradation were found widely distributed throughout the treatment processes. The distributions of Mycobacterium spp. and Legionella spp. in water and biofilms were revealed by real-time quantitative polymerase chain reaction (qPCR). Most bacteria, including potential pathogens, could be effectively removed by chlorine disinfection. However, some bacteria presented great resistance to chlorine. qPCRs showed that Mycobacterium spp. could not be effectively removed by chlorine. These resistant bacteria and, especially potential pathogens should receive more attention. Redundancy analysis (RDA) showed that turbidity, ammonia nitrogen and total organic carbon (TOC) exerted significant effects on community profiles. Overall, this study provides insight into variations of microbial communities in the treatment processes and aids the optimization of drinking water treatment plant design and operation for public health.
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Affiliation(s)
- Qi Li
- State Key Laboratory of Pollution Control and Resource Reuse, College of Environmental Science and Engineering, Tongji University, Shanghai, China
| | - Shuili Yu
- State Key Laboratory of Pollution Control and Resource Reuse, College of Environmental Science and Engineering, Tongji University, Shanghai, China
| | - Lei Li
- State Key Laboratory of Pollution Control and Resource Reuse, College of Environmental Science and Engineering, Tongji University, Shanghai, China
| | - Guicai Liu
- State Key Laboratory of Pollution Control and Resource Reuse, College of Environmental Science and Engineering, Tongji University, Shanghai, China
| | - Zhengyang Gu
- State Key Laboratory of Pollution Control and Resource Reuse, College of Environmental Science and Engineering, Tongji University, Shanghai, China
| | - Minmin Liu
- State Key Laboratory of Pollution Control and Resource Reuse, College of Environmental Science and Engineering, Tongji University, Shanghai, China
| | - Zhiyuan Liu
- State Key Laboratory of Pollution Control and Resource Reuse, College of Environmental Science and Engineering, Tongji University, Shanghai, China
| | - Yubing Ye
- State Key Laboratory of Pollution Control and Resource Reuse, College of Environmental Science and Engineering, Tongji University, Shanghai, China
| | - Qing Xia
- State Key Laboratory of Pollution Control and Resource Reuse, College of Environmental Science and Engineering, Tongji University, Shanghai, China
| | - Liumo Ren
- State Key Laboratory of Pollution Control and Resource Reuse, College of Environmental Science and Engineering, Tongji University, Shanghai, China
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