scholarly journals Ancient DNA and microfossils reveal dynamics of three harmful dinoflagellate species off Eastern Tasmania, Australia, over the last 9,000 years

2021 ◽  
Author(s):  
Linda Armbrecht ◽  
Bradley Paine ◽  
Christopher J.S. Bolch ◽  
Alan Cooper ◽  
Andrew McMinn ◽  
...  
Keyword(s):  
Ancient Dna ◽  
Algal Blooms ◽  
Surface Sediments ◽  
Reference Sequence ◽  
List Type ◽  
Noctiluca Scintillans ◽  
Alexandrium Catenella ◽  
Hybridization Capture ◽  
Recent Climate ◽  
Gymnodinium Catenatum

AbstractHarmful algal blooms (HABs) have significantly impacted the seafood industry along the Tasmanian east coast over the past three decades, and are expected to change in frequency and magnitude due to climate change induced changing oceanographic conditions. To investigate the long-term history of regional HABs, a combination of palynological and sedimentary ancient DNA (sedaDNA) analyses was applied to marine sediment cores from inshore (up to 145 years old) and offshore (up to ~9,000 years) sites at Maria Island, southeast Tasmania. Analyses focused Paralytic Shellfish Toxin (PST) producing dinoflagellates Alexandrium catenella and Gymnodinium catenatum, and the red-tide dinoflagellate Noctiluca scintillans, which were specifically targeted using a hybridization capture sedaDNA technique. Identification of primulin-stained A. catenella cysts throughout the inshore sediment core, together with sedaDNA evidence of a bloom-phase of Alexandrium ~15 years ago, indicates recent stimulation of a cryptic endemic population. Morphologically similar but unstained Alexandrium cysts were observed throughout the offshore core, with sedaDNA confirming the presence of A. catenella from ~8,300 years ago to present. Gymnodinium catenatum cysts were detected only in inshore surface sediments from 30 years ago to present, supporting previous evidence of a 1970s introduction via shipping ballast water. sedaDNA confirmed the presence of G. catenatum-related sequences in the inshore and offshore cores, however, unambiguous species identification could not be achieved due to limited reference sequence coverage of Gymnodinium. Our hybridization capture sedaDNA data also confirmed the historically recent dispersal of the non-fossilizing dinoflagellate Noctiluca scintillans, detected inshore from ~30 years ago, matching first observations of this species in Tasmanian waters in 1994. At the offshore site, N. scintillans sedaDNA was detected only in surface sediments, confirming a recent climate-driven range expansion this species. This study provides new insights into the distribution and abundance of three HAB species in the Tasmanian region, including clues to past bloom phases. Further research into paleo-environmental conditions and paleo-community structure are required to identify the factors driving bloom phases through time and predict plankton community responses under different future climate scenarios.HighlightsDinocyst and sedaDNA analyses were applied to marine sediments off TasmaniaAlexandrium catenella has been endemic to Australia for at least ~9,000 yearsRecent A. catenella blooms are likely induced by climate and oceanographic changeGymnodinium catenatum cysts in recent (~30y) sediments confirm a 1970s introductionNoctiluca scintillans sedaDNAin recent (~30y) sediments matches a 1994 introduction

Seasonal variations of the dinoflagellate algae Noctiluca scintillans abundance in the western Arabian Sea and the northern Black Sea

2021 ◽  
Author(s):  
Sergey Piontkovski ◽  
Khalid Al Hashmi ◽  
Yuliya Zagorodnaya ◽  
Irina Serikova ◽  
Vladislav Evstigneev ◽  
...  
Keyword(s):  
Black Sea ◽  
Mixed Layer ◽  
Algal Blooms ◽  
Arabian Sea ◽  
Temporal Dynamics ◽  
The Black Sea ◽  
Northeast Monsoon ◽  
Major Peak ◽  
Noctiluca Scintillans ◽  
Upper Mixed Layer

<p>Seasonal variability is a powerful component of the spatio-temporal dynamics of plankton communities, especially in the regions with oxygen-depleted waters. The Arabian Sea and the Black Sea are typical representatives of these regions. In both, the dinoflagellate Noctiluca scintillans (Macartney) Kofoid & Swezy, 1921, is one of the abundant plankton species which forms algal blooms. Sampling on coastal stations in the upper mixed layer by the plankton nets with the 120-140 µm mesh size was carried out in 2004-2010. Monthly data were averaged over years. A comparison of seasonal patterns of Noctiluca abundance pointed to the persistence of a bimodal seasonal cycle in both regions. The major peak was observed during spring in the Black Sea and during the winter (Northeast) monsoon in the Arabian Sea. The timing of the second (minor) peak was different over regions as well. This peak was modulated by advection of seasonally fluctuating velocity of coastal currents which transport waters enriched by nutrients by coastal upwelling. The abundance of Noctiluca of the major peak (with the concentration around 1.5*10<sup>6</sup> cells m<sup>-3</sup>) was from one to two orders as much high in the western Arabian Sea compared to the northern Black Sea. The remotely sensed chlorophyll-a concentration during the time of the major seasonal peak exhibited a fivefold difference over these regions. In terms of nutrient<sub></sub>concentration in the upper mixed layer (in particular, nitrates and silicates), a difference of about one order of magnitude was observed.</p>

Hybridization capture of Larix candidate adaptive genes from sedimentary ancient DNA.

2021 ◽  
Author(s):  
Stefano Meucci ◽  
Luise Schulte ◽  
Kathleen R. Stoof-Leichsenring ◽  
Stefan Kruse ◽  
Konstantin Krutovsky ◽  
...  
Keyword(s):  
Ancient Dna ◽  
Dna Sequences ◽  
Environmental Changes ◽  
Genetic Material ◽  
Siberian Larch ◽  
Shotgun Sequencing ◽  
Adaptive Genetic Variation ◽  
Hybridization Capture ◽  
Sequencing Method ◽  
Larch Species

<p>Siberian larch forests dominate large areas of northern Russia and contribute important roles for the world´s ecosystem. In order to understand the past dynamics of larches and their adaptive genetic variation, sedimentary ancient DNA (sedaDNA) extracted from lake sediment cores is a crucial source of genetic material. The difficulty of retrieving extremely rare DNA sequences from samples reaching back up to 25000 years in age, is challenging. Previous studies (Schulte et al.) showed that the hybridization capture allowed an enrichment of targeted sequences by several orders of magnitude in comparison to shotgun sequencing method. Therefore, we established for the first time, a hybridization capture method targeting 65 candidate adaptive genes laying on the Larix nuclear genome. Our preliminary results showed the ability of our newly established method to enrich extremely rare DNA sequences of the targeted Larix candidate adaptive genes, which were not retrieved by shotgun sequencing method applied on the same samples. Furthermore, the results allowed to detect and compare specific nucleotide polymorphism of adaptive candidate genes among sedaDNA samples distributed in space and time. The establishment of this new method is laying the basis to investigate possible adaptive variation of larch species acquired across the dry and cold conditions of the Last Glacial Maximum (LGM); as well as their possible advantages or disadvantages in relation to the current environmental changes toward dry and warm conditions.</p>

scholarly journals Combined hybridization capture and shotgun sequencing for ancient DNA analysis of extinct wild and domestic dromedary camel

2016 ◽  
Vol 17 (2) ◽  
pp. 300-313 ◽  
Author(s):  
Elmira Mohandesan ◽  
Camilla F. Speller ◽  
Joris Peters ◽  
Hans-Peter Uerpmann ◽  
Margarethe Uerpmann ◽  
...  
Keyword(s):  
Ancient Dna ◽  
Dna Analysis ◽  
Shotgun Sequencing ◽  
Dromedary Camel ◽  
Hybridization Capture ◽  
Ancient Dna Analysis

scholarly journals Comparison of target enrichment strategies for ancient pathogen DNA

2020 ◽  
Author(s):  
Anja Furtwängler ◽  
Judith Neukamm ◽  
Lisa Böhme ◽  
Ella Reiter ◽  
Melanie Vollstedt ◽  
...  
Keyword(s):  
Ancient Dna ◽  
Treponema Pallidum ◽  
Mycobacterium Leprae ◽  
Target Enrichment ◽  
Hybridization Capture ◽  
Research Outcomes ◽  
Pathogen Dna ◽  
Different Characteristics ◽  
Rna And Dna ◽  
Better Than

AbstractIn ancient DNA research, the degraded nature of the samples generally results in poor yields of highly fragmented DNA, and targeted DNA enrichment is thus required to maximize research outcomes. The three commonly used methods – (1) array-based hybridization capture and in-solution capture using either (2) RNA or (3) DNA baits – have different characteristics that may influence the capture efficiency, specificity, and reproducibility. Here, we compared their performance in enriching pathogen DNA of Mycobacterium leprae and Treponema pallidum of 11 ancient and 19 modern samples. We find that in-solution approaches are the most effective method in ancient and modern samples of both pathogens, and RNA baits usually perform better than DNA baits.Method summaryWe compared three targeted DNA enrichment strategies used in ancient DNA research for the specific enrichment of pathogen DNA regarding their efficiency, specificity, and reproducibility for ancient and modern Mycobacterium leprae and Treponema pallidum samples. Array-based capture and in-solution capture with RNA and DNA baits were all tested in three independent replicates.

scholarly journals Deep Learning for Simulating Harmful Algal Blooms Using Ocean Numerical Model

2021 ◽  
Vol 8 ◽  
Author(s):  
Sang-Soo Baek ◽  
JongCheol Pyo ◽  
Yong Sung Kwon ◽  
Seong-Jun Chun ◽  
Seung Ho Baek ◽  
...  
Keyword(s):  
Deep Learning ◽  
Harmful Algal Blooms ◽  
Algal Blooms ◽  
Effective Means ◽  
Ocean Model ◽  
Alexandrium Catenella ◽  
The Public ◽  
Global Issue ◽  
Simulated Distribution ◽  
Classification And Regression

In several countries, the public health and fishery industries have suffered from harmful algal blooms (HABs) that have escalated to become a global issue. Though computational modeling offers an effective means to understand and mitigate the adverse effects of HABs, it is challenging to design models that adequately reflect the complexity of HAB dynamics. This paper presents a method involving the application of deep learning to an ocean model for simulating blooms of Alexandrium catenella. The classification and regression convolutional neural network (CNN) models are used for simulating the blooms. The classification CNN determines the bloom initiation while the regression CNN estimates the bloom density. GoogleNet and Resnet 101 are identified as the best structures for the classification and regression CNNs, respectively. The corresponding accuracy and root means square error values are determined as 96.8% and 1.20 [log(cells L–1)], respectively. The results obtained in this study reveal the simulated distribution to follow the Alexandrium catenella bloom. Moreover, Grad-CAM identifies that the salinity and temperature contributed to the initiation of the bloom whereas NH4-N influenced the growth of the bloom.

Growth performance of Alexandrium catenella from the Chilean fjords under different environmental drivers: plasticity as a response to a highly variable environment

2020 ◽  
Vol 42 (2) ◽  
pp. 119-134 ◽  
Author(s):  
Javier Paredes-Mella ◽  
Daniel Varela ◽  
Pamela Fernández ◽  
Oscar Espinoza-González
Keyword(s):  
Light Intensity ◽  
Growth Performance ◽  
Harmful Algal Blooms ◽  
Algal Blooms ◽  
Optimal Growth ◽  
N:P Ratio ◽  
Environmental Drivers ◽  
Growth Responses ◽  
Variable Environment ◽  
Alexandrium Catenella

Abstract Alexandrium catenella, the main species associated with harmful algal blooms, has progressively increased its distribution through one of the most extensive and highly variable fjord systems in the world. In order to understand this successful expansion, we evaluated the effects of different salinities, light intensity, temperatures, nitrogen (N) forms and nitrogen/phosphate (N:P) ratio levels on the growth performance, using clones isolated from different locations across its wide geographic distribution. Results showed that the growth responses were plastic and, in some cases, different reaction norms among clones were observed. Despite plasticity, the optimal growth of A. catenella (i.e. highest growth rate and highest maximal cells density) was reached within a narrow thermal range (12–15°C), while salinity (20–30 PSU) and light intensity (20–120 μmol m−2 s−1) ranges were wider. These results are partially consistent with the highest cell densities recorded in the field. Furthermore, optimal growth was reached using reduced forms of nitrogen (i.e. urea and NH4+) and in unbalanced N:P ratios (18:1 and 30:1). These characteristics likely allow A. catenella to grow in highly variable environmental conditions and might partly explain the recent expansion of this species.

scholarly journals Determination of Cell Abundances and Paralytic Shellfish Toxins in Cultures of the Dinoflagellate Gymnodinium catenatum by Fourier Transform Near Infrared Spectroscopy

2018 ◽  
Vol 6 (4) ◽  
pp. 147 ◽  
Author(s):  
Marta Lopes ◽  
Ana Amorim ◽  
Cecília Calado ◽  
Pedro Reis Costa
Keyword(s):  
Harmful Algal Blooms ◽  
Algal Blooms ◽  
Near Infrared ◽  
Monitoring Program ◽  
Nir Spectroscopy ◽  
Shellfish Poisoning ◽  
Toxic Algae ◽  
Paralytic Shellfish ◽  
Gymnodinium Catenatum

Harmful algal blooms are responsible worldwide for the contamination of fishery resources, with potential impacts on seafood safety and public health. Most coastal countries rely on an intense monitoring program for the surveillance of toxic algae occurrence and shellfish contamination. The present study investigates the use of near infrared (NIR) spectroscopy for the rapid in situ determination of cell concentrations of toxic algae in seawater. The paralytic shellfish poisoning (PSP) toxin-producing dinoflagellate Gymnodinium catenatum was selected for this study. The spectral modeling by partial least squares (PLS) regression based on the recorded NIR spectra enabled the building of highly accurate (R2 = 0.92) models for cell abundance. The models also provided a good correlation between toxins measured by the conventional methods (high-performance liquid chromatography with fluorescence detection (HPLC-FLD)) and the levels predicted by the PLS/NIR models. This study represents the first necessary step in investigating the potential of application of NIR spectroscopy for algae bloom detection and alerting.

scholarly journals Comparison of target enrichment strategies for ancient pathogen DNA

BioTechniques ◽  
2020 ◽  
Vol 69 (6) ◽  
pp. 455-459
Author(s):  
Anja Furtwängler ◽  
Judith Neukamm ◽  
Lisa Böhme ◽  
Ella Reiter ◽  
Melanie Vollstedt ◽  
...  
Keyword(s):  
Ancient Dna ◽  
Treponema Pallidum ◽  
Mycobacterium Leprae ◽  
Capture Efficiency ◽  
Target Enrichment ◽  
Hybridization Capture ◽  
Research Outcomes ◽  
Pathogen Dna ◽  
Different Characteristics ◽  
Better Than

In ancient DNA research, the degraded nature of the samples generally results in poor yields of highly fragmented DNA; targeted DNA enrichment is thus required to maximize research outcomes. The three commonly used methods – array-based hybridization capture and in-solution capture using either RNA or DNA baits – have different characteristics that may influence the capture efficiency, specificity and reproducibility. Here we compare their performance in enriching pathogen DNA of Mycobacterium leprae and Treponema pallidum from 11 ancient and 19 modern samples. We find that in-solution approaches are the most effective method in ancient and modern samples of both pathogens and that RNA baits usually perform better than DNA baits.

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