scholarly journals New trends in bioassessment of aquatic ecosystems: from organisms to DNA-based metrics

2021 ◽  
Vol 4 ◽  
Author(s):  
Jan Pawlowski ◽  
Maria Kahlert

Traditionally, the biological quality of aquatic ecosystems is assessed using selected groups of organisms that can be identified morphologically. Recent advances in high-throughput genomic approaches offered new opportunities to monitor biodiversity and assess ecological status using DNA barcoding and metabarcoding. The DNA-based tools have been used in three different ways: (1) to replace morphological identification of biological quality elements in existing biotic indices, (2) to develop new molecular indices based on morphologically inconspicuous groups of potential environmental indicators, and (3) to predict biotic indices from environmental DNA datasets using machine learning methods (Pawlowski et al. 2018). The next steps need to take advantages and challenges of these different approaches into account in view of their future application in routine bioassessment.The Working Group 2 of DNAqua-Net, Biotic Indices & Metrics, has worked with several task forces tackling different organism groups (fish, macroinvertebrates, diatoms, bacteria, protists, meiofauna), because challenges have been shown to be quite different dependent on the target organisms Kahlert et al. 2019. For the fish the eDNA-metabarcoding methods are well developed and give very good results in terms of species detection. The important question is to see if the semi-quantitative data retrieved from the metabarcoding (proportion in eDNA sequences) could be translated to proportions in biomass/numbers that are now used in many indices. The fish researchers are trying to fit these data in, but some correction factors might be needed to correct for differences between molecular and conventional methodsRegarding the macroinvertebrates, much discussion regarding index development was focusing on the importance of abundance measurements, and it was tested how existing indices would perform if barcoding data would be used instead of morphological data. Still discussion is ongoing on several technical issues, including the use of preservative for DNA extraction from bulk samples, the choice of primers for PCR amplification and the incompleteness of reference databases which impedes the correct assignment of eDNA sequences. Also minimum standards for routine operation are still missing.The diatom group has worked much on practical issues, starting a large initiative to compare diatom metabarcoding protocols used in routine freshwater biomonitoring for standardization (Bailet et al. 2019, Keck et al. 2018, Vasselon et al. 2017). With diatoms, all three approaches to develop molecular indices have been tested and seem promising, i.e. using existing indices with taxa names derived by matching sequences with reference databases, developing new indices based on molecular data only with traditional fixed scores, and using machine-learning techniques (Bailet et al. 2020, Vasselon et al. 2018, Tapolczai et al. 2019, Keck et al. 2018) The micro- and meiobiota group has worked towards an inclusion of microorganisms into aquatic assessment, because the microbial community dynamics are a missing link important for our understanding of rapid changes in the structure and function of aquatic ecosystems, and should be addressed in the future environmental monitoring of freshwater ecosystems (Sagova-Mareckova et al. 2021). Another focus was on how sediment DNA analysis can be integrated into stated goals of routine monitoring applications. It has been an interesting journey, and we WG2 coordinators would like to thank all the people for their engagement! Keep up the good work!

2018 ◽  
Author(s):  
Joeselle M. Serrana ◽  
Yo Miyake ◽  
Maribet Gamboa ◽  
Kozo Watanabe

AbstractConventional morphology-based identification is commonly used for routine assessment of freshwater ecosystems. However, cost and time efficient techniques such as high-throughput sequencing (HTS) based approaches may resolve the constraints encountered in conducting morphology-based surveys. Here, we characterized stream macroinvertebrate species diversity and community composition via metabarcoding and morphological analysis from environmental samples collected from the Shigenobu River Basin in Ehime Prefecture, Japan. We compared diversity metrics and assessed both approaches’ ability to evaluate the relationship between macroinvertebrate community and environmental variables. In total, we morphologically identified 45 taxa (3 families, six subfamilies, 31 genera, and five species) from 8,276 collected individuals from ten study sites. We detected 44 species by metabarcoding, with 35 species collapsed into 11 groups matching the morphologically identified taxa. A significant positive correlation between logged depth (number of HTS reads) and abundance of morphological taxa was observed, which implied that quantitative data can be used for subsequent analyses. Relatively higher estimates of alpha diversity were calculated from the metabarcoding data in comparison to morphology-based data. However, beta diversity estimates between metabarcoding and morphology data based on both incidence and abundance-based matrices were correlated proving that community differences between sampling sites were preserved in the molecular data. Also, both models were significant, but metabarcoding data (93%) explained a relatively higher percentage of variation in the relationship between community composition and the environmental variables than morphological data (91%). Overall, we present both the feasibility and limitations of HTS-driven estimations of taxonomic richness, community composition, and diversity metrics, and that metabarcoding was proven comparable and more sensitive against morphology-based analysis for stream macroinvertebrate biodiversity assessment and environmental monitoring.


2021 ◽  
Author(s):  
Ixchel Gonzalez-Ramirez ◽  
Sergio RS Cevallos-Ferriz ◽  
Carl Rothfels

Premise of study: El Chango is a recently discovered quarry that contains extremely well preserved fossils. The Cenomanian age of the locality corresponds to a time when the global flora was transitioning from gymnosperm- to angiosperm-dominated, yet conifers predominate in this locality. These fossils thus provide a rare opportunity to understand the replacement of conifers by angiosperms as the dominant group of plants. Methods: We collected material from El Chango in annual expeditions (2010 to 2014). We selected the three most abundant and best preserved conifer morphotypes and conducted a total-evidence (i.e., including molecular and morphological data) phylogenetic analysis of a sample of 72 extant conifer species plus the three fossils. We use these results to inform our taxonomic decisions. Results: We obtained four equally most-parsimonious trees (consistency index = 44.1%, retention index = 78.8%). Despite ambiguous relationships among some extant taxa, the three fossil conifers had the same phylogenetic position in all four most parsimonious trees; we describe these species as new: Sequoiadendron helicalancifolium sp. nov. (Cupressaceae), and Microcachrys rhomboidea sp. nov. and Dacrydium bifoliosus sp. nov (Podocarpaceae). The ecosystem is interpreted as a coastal humid mixed forest. Conclusions: Our findings contribute to the understanding of Cenomanian equatorialregions, and support the hypothesis of a geographically and ecologically structured rise of angiosperms, with conifers remaining dominant in brackish-water and angiosperms becoming dominant in freshwater-ecosystems. These fossils fill in gaps in the evolutionary history of lineages like Microcachrys, which we demonstrate occurred in the Northern hemisphere before becoming restricted to its current range (Tasmania).


Phytotaxa ◽  
2021 ◽  
Vol 480 (1) ◽  
pp. 1-21
Author(s):  
SOFIA S. SADOGURSKA ◽  
JOÃO NEIVA ◽  
ANNALISA FALACE ◽  
ESTER A. SERRÃO ◽  
ÁLVARO ISRAEL

Brown algae of the genus Cystoseira sensu lato form the most diverse and productive marine ecosystems throughout the Mediterranean Sea and have equal roles also in the Black Sea where they have been decreasing in the recent years. The taxonomy of Cystoseira s.l. taxa from the Black Sea is still not well understood, and questions arise when related taxa have to be delimited. In addition to morphological descriptions, this study provides for the first time molecular data of the Black Sea Cystoseira s.l. distinct morphologies as an additional tool to clarify their identities and phylogenetic affinities. The analysis of two mitochondrial markers (cytochrome oxidase subunit 1—COI, and 23S-tRNAVal intergenic spacer—mt-spacer) showed that Cystoseira s.l. specimens from the Black Sea belong to two recently resurrected genera, namely Gongolaria and Ericaria. Molecular data confirm the morphological identification of G. barbata, which is characterized by high morphological plasticity in the Black Sea. The morphological data presented in this study support the transition of G. barbata to the genus Gongolaria, which was previously proposed based solely on genetic data. For the Black Sea endemic taxon C. bosphorica, sequence divergence suggests conspecificity with Mediterranean Sea species E. crinita and E. barbatula. However, considering original morphological characteristics of the taxon, its geographical isolation, and endemism, the new combination Ericaria crinita f. bosphorica comb. nov. is proposed.


Toxins ◽  
2018 ◽  
Vol 10 (12) ◽  
pp. 503 ◽  
Author(s):  
Qing Li ◽  
Maren Watkins ◽  
Samuel Robinson ◽  
Helena Safavi-Hemami ◽  
Mark Yandell

Cone snails (genus Conus) are venomous marine snails that inject prey with a lethal cocktail of conotoxins, small, secreted, and cysteine-rich peptides. Given the diversity and often high affinity for their molecular targets, consisting of ion channels, receptors or transporters, many conotoxins have become invaluable pharmacological probes, drug leads, and therapeutics. Transcriptome sequencing of Conus venom glands followed by de novo assembly and homology-based toxin identification and annotation is currently the state-of-the-art for discovery of new conotoxins. However, homology-based search techniques, by definition, can only detect novel toxins that are homologous to previously reported conotoxins. To overcome these obstacles for discovery, we have created ConusPipe, a machine learning tool that utilizes prominent chemical characters of conotoxins to predict whether a certain transcript in a Conus transcriptome, which has no otherwise detectable homologs in current reference databases, is a putative conotoxin. By using ConusPipe on RNASeq data of 10 species, we report 5148 new putative conotoxin transcripts that have no homologues in current reference databases. 896 of these were identified by at least three out of four models used. These data significantly expand current publicly available conotoxin datasets and our approach provides a new computational avenue for the discovery of novel toxin families.


Author(s):  
Maiara Tábatha da Silva Brito ◽  
Leidiane Pereira Diniz ◽  
Ully M. Pozzobom ◽  
Victor Lemes Landeiro ◽  
Francisco Diogo R. Sousa

Studies on Cladocera biodiversity in Brazilian freshwater ecosystems are intensifying. However, the fauna of some hydrographic regions is still poorly known. We investigated the richness and species composition of cladocerans in lakes of the Pantanal from the state of Mato Grosso (Paraguay hydrographic region), Brazil. In addition, we cataloged the known cladoceran species in each hydrographic region of the state. Occurrence data were obtained from the literature and samples collected from 50 lakes in the northern Pantanal. We recorded 120 cladoceran species from eight families in the state of Mato Grosso. The occurrence of these species was recorded in the Amazon and Paraguay hydrographic regions. We are unaware of studies on cladocerans conducted in the Tocantins-Araguaia hydrographic region. We reported 17 new records in the Pantanal samples (Paraguay hydrographic region). Overall, richness estimates reveal that 72.6% of the state's cladoceran fauna is already known, while for the Paraguay hydrographic region this estimate is 72.2%. In general, the cladocerans from the Amazon and Paraguay regions did not differ. Our findings allow us to infer the need for further studies in the different hydrographic regions found in Mato Grosso in order to improve the knowledge of cladoceran biodiversity. We suggest a greater sampling effort, particularly in the littoral zone of aquatic ecosystems in this state, which can harbor great biodiversity.


Author(s):  
Alexander M. Zolotarev ◽  
Brian J. Hansen ◽  
Ekaterina A. Ivanova ◽  
Katelynn M. Helfrich ◽  
Ning Li ◽  
...  

Background: Atrial fibrillation (AF) can be maintained by localized intramural reentrant drivers. However, AF driver detection by clinical surface-only multielectrode mapping (MEM) has relied on subjective interpretation of activation maps. We hypothesized that application of machine learning to electrogram frequency spectra may accurately automate driver detection by MEM and add some objectivity to the interpretation of MEM findings. Methods: Temporally and spatially stable single AF drivers were mapped simultaneously in explanted human atria (n=11) by subsurface near-infrared optical mapping (NIOM; 0.3 mm 2 resolution) and 64-electrode MEM (higher density or lower density with 3 and 9 mm 2 resolution, respectively). Unipolar MEM and NIOM recordings were processed by Fourier transform analysis into 28 407 total Fourier spectra. Thirty-five features for machine learning were extracted from each Fourier spectrum. Results: Targeted driver ablation and NIOM activation maps efficiently defined the center and periphery of AF driver preferential tracks and provided validated annotations for driver versus nondriver electrodes in MEM arrays. Compared with analysis of single electrogram frequency features, averaging the features from each of the 8 neighboring electrodes, significantly improved classification of AF driver electrograms. The classification metrics increased when less strict annotation, including driver periphery electrodes, were added to driver center annotation. Notably, f1-score for the binary classification of higher-density catheter data set was significantly higher than that of lower-density catheter (0.81±0.02 versus 0.66±0.04, P <0.05). The trained algorithm correctly highlighted 86% of driver regions with higher density but only 80% with lower-density MEM arrays (81% for lower-density+higher-density arrays together). Conclusions: The machine learning model pretrained on Fourier spectrum features allows efficient classification of electrograms recordings as AF driver or nondriver compared with the NIOM gold-standard. Future application of NIOM-validated machine learning approach may improve the accuracy of AF driver detection for targeted ablation treatment in patients.


2020 ◽  
Vol 96 (11) ◽  
Author(s):  
Cátia Carreira ◽  
Christian Lønborg ◽  
Michael Kühl ◽  
Ana I Lillebø ◽  
Ruth-Anne Sandaa ◽  
...  

ABSTRACT Microbial mats are compacted, surface-associated microbial ecosystems reminiscent of the first living communities on early Earth. While often considered predominantly prokaryotic, recent findings show that both fungi and viruses are ubiquitous in microbial mats, albeit their functional roles remain unknown. Fungal research has mostly focused on terrestrial and freshwater ecosystems where fungi are known as important recyclers of organic matter, whereas viruses are exceptionally abundant and important in aquatic ecosystems. Here, viruses have shown to affect organic matter cycling and the diversity of microbial communities by facilitating horizontal gene transfer and cell lysis. We hypothesise fungi and viruses to have similar roles in microbial mats. Based on the analysis of previous research in terrestrial and aquatic ecosystems, we outline novel hypotheses proposing strong impacts of fungi and viruses on element cycling, food web structure and function in microbial mats, and outline experimental approaches for studies needed to understand these interactions.


2012 ◽  
Vol 41 (1) ◽  
pp. 35-41 ◽  
Author(s):  
Abdullah Harun Chowdhury ◽  
Roxana Ahmed

A total of 29 genera belonging to 24 families of aquatic macrophytes were recorded. Among these, 25 species were recorded from the freshwater aquatic ecosystems, 4 species from both the shrimp culture ponds and freshwater aquatic ecosystems and only one from the shrimp culture ponds. The physicochemical conditions of both the habitats indicate that very poor number of macrophytes can grow in the shrimp culture ponds due to high salinity of water and soil. Low population and abundance indicate that the macrophytes are in alarming condition in Koyra due to increasing salinity. DOI: http://dx.doi.org/10.3329/bjb.v41i1.11080 Bangladesh J. Bot. 41(1): 35-41, 2012 (June)


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