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Benthic diatoms have traditionally been used as bioindicators of aquatic ecosystems. Because diatom-based monitoring of water quality is required by European legislation, molecular-based methods had emerged as useful alternatives to classical methods based on morphological identification using light microscopy. The aim of this study was to test the reliability of DNA metabarcoding combined with High-Throughput Sequencing (HTS) techniques in the bioassessment of the trophic status of 22 Mediterranean shallow ponds in NW Spain. For each pond, the Trophic Diatom Index (TDI) was calculated from inventories obtained by identification using light microscopy (LM) followed by high-throughput sequencing (HTS) at the molecular level. Ponds were subsequently classified into five water quality classes. The results showed a good correspondence between both methods, especially after applying a correction factor that depended on the biovolume of the cells. This correspondence led to the assignment to the same quality class in 59% of the ponds. The determination and quantification of valves or DNA sequences was one of the main pitfalls, which mainly included those related to the variability in the relative abundances of some species. Accordingly, ponds with similar relative abundances for the dominant species were assigned to the same quality class. Moreover, other difficulties leading the discrepancies were the misidentification of some species due to the presence of semi-cryptic taxa, the incompleteness of the reference database and the bioinformatic protocol. Thus, the validation of DNA-based methods for the identification of freshwater diatoms represents an important goal, as an alternative to using traditional methods in Mediterranean shallow ponds.
María Borrego-Ramos; Eloy Bécares; Pedro García; Alejandro Nistal; Saúl Blanco. Epiphytic Diatom-Based Biomonitoring in Mediterranean Ponds: Traditional Microscopy versus Metabarcoding Approaches. Water 2021, 13, 1351 .
AMA StyleMaría Borrego-Ramos, Eloy Bécares, Pedro García, Alejandro Nistal, Saúl Blanco. Epiphytic Diatom-Based Biomonitoring in Mediterranean Ponds: Traditional Microscopy versus Metabarcoding Approaches. Water. 2021; 13 (10):1351.
Chicago/Turabian StyleMaría Borrego-Ramos; Eloy Bécares; Pedro García; Alejandro Nistal; Saúl Blanco. 2021. "Epiphytic Diatom-Based Biomonitoring in Mediterranean Ponds: Traditional Microscopy versus Metabarcoding Approaches." Water 13, no. 10: 1351.
Diatoms are important organisms in freshwater ecosystems due to their position as primary producers and therefore, analyzing their assemblages provides relevant information on ecosystem functioning. Diatoms have historically been identified based on morphological traits, which is time-consuming and requires well-trained specialists. Nevertheless, DNA barcoding offers an alternative approach to overcome some limitations of the morphological method. Here, we assess if both approaches are comparable methods to study patterns and mechanisms (including environmental filtering and dispersal limitation) of epiphytic diatom metacommunities using a comprehensive dataset from 22 Mediterranean ponds at different taxonomic resolutions. We used a fragment of rbcL barcode gene combined with High-Throughput Sequencing to infer diatom community composition. The overall degree of correspondence between both approaches was assessed by Procrustean rotation analysis and Procrustean randomization tests, whereas the role of local environmental variables and geographical distances was studied using a comprehensive combination of BIOENV, Mantel tests and distance-based redundancy analysis. Our results showed a relatively poor correspondence in the compositional variation of diatom metacommunity between both approaches. We speculate that the incompleteness of the reference database and the bioinformatics processing are the biases most likely affecting the molecular approach, whereas the limited counting effort and the presence of cryptic species are presumably the major biases related with the morphological method. On the other hand, variation in diatom community composition detected with both approaches was strongly related to the environmental template, which may be related with the narrow community-environment relationships in diatoms. Nevertheless, we found no significant relationship between compositional variation and geographical distances. Overall, our work shows the complementary nature of both approaches and highlights the importance of DNA metabarcoding to address empirical research questions of community ecology in freshwaters, especially once the reference databases include most genotypes of occurring taxa and bioinformatics biases are overcome.
Alejandro Nistal-García; Pedro García-García; Jorge García-Girón; María Borrego-Ramos; Saúl Blanco; Eloy Bécares. DNA metabarcoding and morphological methods show complementary patterns in the metacommunity organization of lentic epiphytic diatoms. Science of The Total Environment 2021, 786, 147410 .
AMA StyleAlejandro Nistal-García, Pedro García-García, Jorge García-Girón, María Borrego-Ramos, Saúl Blanco, Eloy Bécares. DNA metabarcoding and morphological methods show complementary patterns in the metacommunity organization of lentic epiphytic diatoms. Science of The Total Environment. 2021; 786 ():147410.
Chicago/Turabian StyleAlejandro Nistal-García; Pedro García-García; Jorge García-Girón; María Borrego-Ramos; Saúl Blanco; Eloy Bécares. 2021. "DNA metabarcoding and morphological methods show complementary patterns in the metacommunity organization of lentic epiphytic diatoms." Science of The Total Environment 786, no. : 147410.
Benthic diatoms are well known bioindicators of water quality, used in many aquatic ecosystems. Since diatom-based monitoring of water quality is required by European legislation, the search for methods that facilitate this task has become more relevant. The aim of this study was to test the reliability of DNA metabarcoding combined with high-throughput sequencing (HTS) techniques in the bioassessment of 22 Mediterranean shallow ponds in Spain. For each pond, Trophic Diatom Index (TDI) was calculated from inventories obtained by using light microscopy, and then molecular (HTS) methods. Ponds were subsequently classified into five water quality classes. Our results showed a good correspondence between both methods, especially after applying a correction factor depending on the biovolume of the cells. This correspondence led to the assignment to the same quality class in 59% of the ponds. The determination and quantification of valves or DNA sequences was one of the main pitfalls, mainly those related to the variability in the relative abundances of some species. Accordingly, ponds with similar relative abundances for the dominant species were assigned to the same quality class. Moreover, other difficulties leading the discrepancies were the misidentification of some species due to the presence of semi-cryptic taxa, the incompleteness of the reference database and the bioinformatic protocol. Therefore, the validation of DNA-based methods for the identification of freshwater diatoms represents an important goal, as an alternative to traditional ones in Mediterranean shallow ponds.
María Borrego-Ramos; Eloy Bécares; Pedro García-García; Alejandro Nistal; Saúl Blanco. An account of epiphytic diatoms in mediterranean wetlands: comparing morphological and molecular assessments. ARPHA Conference Abstracts 2021, 4, e64948 .
AMA StyleMaría Borrego-Ramos, Eloy Bécares, Pedro García-García, Alejandro Nistal, Saúl Blanco. An account of epiphytic diatoms in mediterranean wetlands: comparing morphological and molecular assessments. ARPHA Conference Abstracts. 2021; 4 ():e64948.
Chicago/Turabian StyleMaría Borrego-Ramos; Eloy Bécares; Pedro García-García; Alejandro Nistal; Saúl Blanco. 2021. "An account of epiphytic diatoms in mediterranean wetlands: comparing morphological and molecular assessments." ARPHA Conference Abstracts 4, no. : e64948.
There have been a number of studies that described a serial of type of teratology occurring in different diatom taxa and that highlight the relation between metal concentration and diatom deformities, but this subject still remain not deeply understood. The present study refers to the effect of metal pollution on the diatom Achnanthidium minutissimum s.l. by describing a new form of teratology. The samples were collected in a mine area, Rosia Montana, from Romania. We observed that, exposed to environmental stress, the frustule of diatom cells appeared altered in several ways, with abnormal forms occurring in different diatom species that presented deformed valve outlines, modifications of the raphe canal system, irregular striation or mixed teratologies. In a particular sampling location where A. minutissimum s.l. was identified as the dominant species, 20.53% of the individuals presented an unreported type of deformity. This kind of teratology affects the cingulum, the valvocopula more exactly, by becoming markedly undulate.
Adriana Olenici; Saul Blanco; Maria Borrego-Ramos; Francisco Jimenez-Gomez; Francisco Guerrero; Laura Momeu; Calin Baciu. Metal-induced abnormalities in diatom girdle bands. 2018, 501619 .
AMA StyleAdriana Olenici, Saul Blanco, Maria Borrego-Ramos, Francisco Jimenez-Gomez, Francisco Guerrero, Laura Momeu, Calin Baciu. Metal-induced abnormalities in diatom girdle bands. . 2018; ():501619.
Chicago/Turabian StyleAdriana Olenici; Saul Blanco; Maria Borrego-Ramos; Francisco Jimenez-Gomez; Francisco Guerrero; Laura Momeu; Calin Baciu. 2018. "Metal-induced abnormalities in diatom girdle bands." , no. : 501619.
Diatom detection has been a challenging task for computer scientist and biologist during past years. In this work, the new state of art techniques based on the deep learning framework have been tested, in order to check whether they are suitable for this purpose. On the one hand, RCNNs (Region based Convolutional Neural Networks), which select candidate regions and applies a convolutional neural network and, on the other hand, YOLO (You Only Look Once), which applies a single neural network over the whole image, have been tested. The first one is able to reach poor results in out experimentation, with an average of 0.68 recall and some tricky aspects, as for example it is needed to apply a bounding box merging algorithm to get stable detections; but the second one gets remarkable results, with an average of 0.84 recall in the evaluation that have been carried out, and less aspects to take into account after the detection has been performed. Future work related to parameter tuning and processing are needed to increase the performance of deep learning in the detection task. However, as for classification it has been probed to provide succesfully performance.
Gloria Bueno; Oscar Déniz; Jesus Ruiz-Santaquiteria; Adriana Olenici; Gabriel Cristobal; Anibal Pedraza; Carlos Sanchez; Saúl Blanco; Maria Borrego-Ramos. Lights and pitfalls of convolutional neural networks for diatom identification. Optics, Photonics, and Digital Technologies for Imaging Applications V 2018, 10679, 106790G .
AMA StyleGloria Bueno, Oscar Déniz, Jesus Ruiz-Santaquiteria, Adriana Olenici, Gabriel Cristobal, Anibal Pedraza, Carlos Sanchez, Saúl Blanco, Maria Borrego-Ramos. Lights and pitfalls of convolutional neural networks for diatom identification. Optics, Photonics, and Digital Technologies for Imaging Applications V. 2018; 10679 ():106790G.
Chicago/Turabian StyleGloria Bueno; Oscar Déniz; Jesus Ruiz-Santaquiteria; Adriana Olenici; Gabriel Cristobal; Anibal Pedraza; Carlos Sanchez; Saúl Blanco; Maria Borrego-Ramos. 2018. "Lights and pitfalls of convolutional neural networks for diatom identification." Optics, Photonics, and Digital Technologies for Imaging Applications V 10679, no. : 106790G.
Many biological objects are barely distinguished with the brightfield microscope because they appear transparent, translucent and colourless. One simple way to make such specimens visible without compromising contrast and resolution is by controlling the amount and the directionality of the illumination light. Oblique illumination is an old technique described by many scientists and microscopists that however has been largely neglected in favour of other alternative methods. Oblique lighting (OL) is created by illuminating the sample by only a portion of the light coming from the condenser. If properly used it can improve the resolution and contrast of transparent specimens such as diatoms. In this paper a quantitative evaluation of OL in brigthfield microscopy is presented. Several feature descriptors were selected for characterising contrast and sharpness showing that in general OL provides better performance for distinguishing minute details compared to other lighting modalities. Oblique lighting is capable to produce directionally shadowed differential contrast images allowing to observe phase details in a similar way to differential contrast images (DIC) but at lower cost. The main advantage of OL is that the resolution of the light microscope can be increased by effectively doubling the angular aperture. OL appears as a cost-effective technique both for the amateur and professional scientist that can be used as a replacement of DIC or phase contrast when resources are scarce.
Carlos Sanchez; Gabriel Cristóbal; Carlos Sanchez Bueno; Saúl Blanco; María Borrego-Ramos; Adriana Olenici; Aníbal Pedraza; Jesus Ruiz-Santaquiteria. Oblique illumination in microscopy: A quantitative evaluation. Micron 2018, 105, 47 -54.
AMA StyleCarlos Sanchez, Gabriel Cristóbal, Carlos Sanchez Bueno, Saúl Blanco, María Borrego-Ramos, Adriana Olenici, Aníbal Pedraza, Jesus Ruiz-Santaquiteria. Oblique illumination in microscopy: A quantitative evaluation. Micron. 2018; 105 ():47-54.
Chicago/Turabian StyleCarlos Sanchez; Gabriel Cristóbal; Carlos Sanchez Bueno; Saúl Blanco; María Borrego-Ramos; Adriana Olenici; Aníbal Pedraza; Jesus Ruiz-Santaquiteria. 2018. "Oblique illumination in microscopy: A quantitative evaluation." Micron 105, no. : 47-54.
This paper deals with automatic taxa identification based on machine learning methods. The aim is therefore to automatically classify diatoms, in terms of pattern recognition terminology. Diatoms are a kind of algae microorganism with high biodiversity at the species level, which are useful for water quality assessment. The most relevant features for diatom description and classification have been selected using an extensive dataset of 80 taxa with a minimum of 100 samples/taxon augmented to 300 samples/taxon. In addition to published morphological, statistical and textural descriptors, a new textural descriptor, Local Binary Patterns (LBP), to characterize the diatom’s valves, and a log Gabor implementation not tested before for this purpose are introduced in this paper. Results show an overall accuracy of 98.11% using bagging decision trees and combinations of descriptors. Finally, some phycological features of diatoms that are still difficult to integrate in computer systems are discussed for future work.
Gloria Bueno; Oscar Deniz; Anibal Pedraza; Jesús Ruiz-Santaquiteria; Jesús Salido; Gabriel Cristóbal; María Borrego-Ramos; Saúl Blanco. Automated Diatom Classification (Part A): Handcrafted Feature Approaches. Applied Sciences 2017, 7, 753 .
AMA StyleGloria Bueno, Oscar Deniz, Anibal Pedraza, Jesús Ruiz-Santaquiteria, Jesús Salido, Gabriel Cristóbal, María Borrego-Ramos, Saúl Blanco. Automated Diatom Classification (Part A): Handcrafted Feature Approaches. Applied Sciences. 2017; 7 (8):753.
Chicago/Turabian StyleGloria Bueno; Oscar Deniz; Anibal Pedraza; Jesús Ruiz-Santaquiteria; Jesús Salido; Gabriel Cristóbal; María Borrego-Ramos; Saúl Blanco. 2017. "Automated Diatom Classification (Part A): Handcrafted Feature Approaches." Applied Sciences 7, no. 8: 753.
Metal pollution of aquatic habitats is a major and persistent environmental problem. Acid mine drainage (AMD) affects lotic systems in numerous and interactive ways. In the present work, a mining area (Roșia Montană) was chosen as study site, and we focused on two aims: (i) to find the set of environmental predictors leading to the appearance of the abnormal diatom individuals in the study area and (ii) to assess the relationship between the degree of valve outline deformation and AMD-derived pollution. In this context, morphological differences between populations of Achnanthidium minutissimum and A. macrocephalum, including normal and abnormal individuals, were evidenced by means of valve shape analysis. Geometric morphometry managed to capture and discriminate normal and abnormal individuals. Multivariate analyses (NMDS, PLS) separated the four populations of the two species mentioned and revealed the main physico-chemical parameters that influenced valve deformation in this context, namely conductivity, Zn, and Cu. ANOSIM test evidenced the presence of statistically significant differences between normal and abnormal individuals within both chosen Achnanthidium taxa. In order to determine the relative contribution of each of the measured physico-chemical parameters in the observed valve outline deformations, a PLS was conducted, confirming the results of the NMDS. The presence of deformed individuals in the study area can be attributed to the fact that the diatom communities were strongly affected by AMD released from old mining works and waste rock deposits.
Adriana Olenici; Saúl Blanco; María Borrego-Ramos; Laura Momeu; Calin Baciu. Exploring the effects of acid mine drainage on diatom teratology using geometric morphometry. Ecotoxicology 2017, 26, 1018 -1030.
AMA StyleAdriana Olenici, Saúl Blanco, María Borrego-Ramos, Laura Momeu, Calin Baciu. Exploring the effects of acid mine drainage on diatom teratology using geometric morphometry. Ecotoxicology. 2017; 26 (8):1018-1030.
Chicago/Turabian StyleAdriana Olenici; Saúl Blanco; María Borrego-Ramos; Laura Momeu; Calin Baciu. 2017. "Exploring the effects of acid mine drainage on diatom teratology using geometric morphometry." Ecotoxicology 26, no. 8: 1018-1030.
Diatoms, a kind of algae microorganisms with several species, are quite useful for water quality determination, one of the hottest topics in applied biology nowadays. At the same time, deep learning and convolutional neural networks (CNN) are becoming an extensively used technique for image classification in a variety of problems. This paper approaches diatom classification with this technique, in order to demonstrate whether it is suitable for solving the classification problem. An extensive dataset was specifically collected (80 types, 100 samples/type) for this study. The dataset covers different illumination conditions and it was computationally augmented to more than 160,000 samples. After that, CNNs were applied over datasets pre-processed with different image processing techniques. An overall accuracy of 99% is obtained for the 80-class problem and different kinds of images (brightfield, normalized). Results were compared to previous presented classification techniques with different number of samples. As far as the authors know, this is the first time that CNNs are applied to diatom classification.
Anibal Pedraza; Gloria Bueno; Oscar Deniz; Gabriel Cristóbal; Saúl Blanco; María Borrego-Ramos. Automated Diatom Classification (Part B): A Deep Learning Approach. Applied Sciences 2017, 7, 460 .
AMA StyleAnibal Pedraza, Gloria Bueno, Oscar Deniz, Gabriel Cristóbal, Saúl Blanco, María Borrego-Ramos. Automated Diatom Classification (Part B): A Deep Learning Approach. Applied Sciences. 2017; 7 (5):460.
Chicago/Turabian StyleAnibal Pedraza; Gloria Bueno; Oscar Deniz; Gabriel Cristóbal; Saúl Blanco; María Borrego-Ramos. 2017. "Automated Diatom Classification (Part B): A Deep Learning Approach." Applied Sciences 7, no. 5: 460.