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600 results for “Contamination”
Data from: Amplicon pyrosequencing late Pleistocene permafrost: the removal of putative contaminant sequences and small-scale reproducibility
DNA sequencing of ancient permafrost samples can be used to reconstruct past plant, animal and bacterial communities. In this study, we assess the small-scale reproducibility of taxonomic composition obtained from sequencing four molecular markers (mitochondrial 12S ribosomal DNA (rDNA), prokaryote 16S rDNA, mitochondrial cox1 and chloroplast trnL intron) from two soil cores sampled 10 cm apart. In addition, sequenced control reactions were used to produce a contaminant library that was used to filter similar sequences from sample libraries. Contaminant filtering resulted in the removal of 1% of reads or 0.3% of operational taxonomic units. We found similar richness, overlap, abundance and taxonomic diversity from the 12S, 16S and trnL markers from each soil core. Jaccard dissimilarity across the two soil cores was highest for metazoan taxa detected by the 12S and cox1 markers. Taxonomic community distances were similar for each marker across the two soil cores when the chi-squared metric was used; however, the 12S and cox1 markers did not cluster well when the Goodall similarity metric was used. A comparison of plant macrofossil vs. read abundance corroborates previous work that suggests eastern Beringia was dominated by grasses and forbs during cold stages of the Pleistocene, a habitat that is restricted to isolated sites in the present-day Yukon.
Data from: Parasite infection of public databases: a data mining approach to identify apicomplexan contaminations in animal genome and transcriptome assemblies
Background: Contaminations from various exogenous sources are a common problem in next-generation sequencing. Another possible source of contaminating DNA are endogenous parasites. On the one hand, undiscovered contaminations of animal sequence assemblies may lead to erroneous interpretation of data; on the other hand, when identified, parasite-derived sequences may provide a valuable source of information. Results: Here we show that sequences deriving from apicomplexan parasites can be found in many animal genome and transcriptome projects, which in most cases derived from an infection of the sequenced host specimen. The apicomplexan sequences were extracted from the sequence assemblies using a newly developed bioinformatic pipeline (ContamFinder) and tentatively assigned to distinct taxa employing phylogenetic methods. We analysed 920 assemblies and found 20,907 contigs of apicomplexan origin in 51 of the datasets. The contaminating species were identified as members of the apicomplexan taxa Gregarinasina, Coccidia, Piroplasmida, and Haemosporida. For example, in the platypus genome assembly, we found a high number of contigs derived from a piroplasmid parasite (presumably Theileria ornithorhynchi). For most of the infecting parasite species, no molecular data had been available previously, and some of the datasets contain sequences representing large amounts of the parasite's gene repertoire. Conclusion: Our study suggests that parasite-derived contaminations represent a valuable source of information that can help to discover and identify new parasites, and provide information on previously unknown host-parasite interactions. We, therefore, argue that uncurated assembly data should routinely be made available in addition to the final assemblies.
The 1.1 Å Structure of the Periplasmic Phosphate-Binding Protein from Stenotrophomonas maltophilia - a crystallisation contaminant identified by molecular replacement using the entire protein database (X-ray diffraction images).
<p>During efforts to crystallise the enzyme 2,4-dihydroxyacetophenone dioxygenase (DAD) from <em>Alcaligenes</em> sp. 4HAP, a small number of strongly diffracting protein crystals were obtained after two years of crystal growth in one condition. The crystals diffracted synchrotron radiation to almost 1.0 Å resolution and were, until recently, assumed to be formed by the DAD protein. However, when another crystal form of this enzyme was eventually solved at lower resolution, molecular replacement using this structure as the search model did not give a convincing solution with the original atomic resolution dataset. Hence we considered that these crystals might be due to a protein impurity, although molecular replacement using the structures of common crystallisation contaminants as search models again failed. A script to perform molecular replacement using MOLREP (Vagin, A. & Teplyakov, A. (2010). Acta Crystallogr. D 66, 22-25.) in which the first chain of every structure in the PDB was used as a search model was run on a multi-core cluster. This identified a number of prokaryotic phosphate binding proteins as scoring highly in the MOLREP peak lists. Calculation of an electron density map at 1.1 Å resolution allowed most of the amino acids to be identified visually and built into the model. A BLAST search then indicated that the molecule was most probably a phosphate binding protein from <em>Stenotrophomonas maltophilia</em> (UniProt ID: B4SL31; gene ID: Smal_2208) and fitting of the corresponding sequence to the atomic resolution map fully corroborated this. Proteins in this family have been linked with the virulence of antibiotic resistant strains of pathogenic bacteria and with biofilm formation. The structure has been refined to an R-factor of 10.15 % and an R-free of 12.46 % at 1.1 Å resolution. The molecule adopts the type-II periplasmic binding protein fold with a number of extensively elaborated loop regions. A fully-dehydrated phosphate anion is bound tightly between the two domains of the protein and interacts with conserved residues and a number of helix dipoles. </p>
FIGURE 2 in Larvae of Hydropsyche angustipennis (Trichoptera, Hydropsychidae) as indicators of stream contamination by heavy metals in Łódź agglomeration
FIGURE 2. Annual results of the measured water parameters at given sampling sites.
FIGURE 5 in Larvae of Hydropsyche angustipennis (Trichoptera, Hydropsychidae) as indicators of stream contamination by heavy metals in Łódź agglomeration
FIGURE 5. Presence of heavy metals in whole bodies and in water at given sampling sites.
FIGURE 1 in Larvae of Hydropsyche angustipennis (Trichoptera, Hydropsychidae) as indicators of stream contamination by heavy metals in Łódź agglomeration
FIGURE 1. Study area with sampling sites.
FIGURE 4 in Larvae of Hydropsyche angustipennis (Trichoptera, Hydropsychidae) as indicators of stream contamination by heavy metals in Łódź agglomeration
FIGURE 4. Annual content of heavy metals in larval bodies at given sampling sites.
FIGURE 3 in Larvae of Hydropsyche angustipennis (Trichoptera, Hydropsychidae) as indicators of stream contamination by heavy metals in Łódź agglomeration
FIGURE 3. Hierarchical cluster analysis for abiotic and biotic parameters in given sampling sites.
Removal of contaminants of emerging concern from the supernatant of anaerobically digested sludge by O3 and O3/H2O2: Ozone requirements, effects of the matrix, and toxicity
<p>Digestate is a rich source of nutrients that can be applied in agricultural fields as fertilizer or irrigation water.<br>However, most of the research about application of digestate have focused on its agronomic properties and<br>neglected the potential harm of the presence of contaminants of emerging concern (CECs). Aadvanced oxidation processes (AOPs) have proved to be effective for removing these compounds from drinking water, yet there are some constrains to treat wastewater and digestate mainly due to their complex matrix. In this study, the feasibility to remove different CECs from digestate using O3 and O3/H2O2 was assessed, and the general effect of the matrix in the oxidation was explained. While the lab-scale ozonation provided an ozone dose of 1.49 mg O3/mg DOC in 5 h treatment, almost all the compounds were removed at a lower ozone dose of maximum 0.48 mg O3/ mg DOC; only ibuprofen required a higher dose of 1.1 mg O3/mg DOC to be oxidized. The digestate matrix slowed down the kinetic ozonation rate to approximately 1% compared to the removal rate in demineralized water. The combined treatment (O3/H2O2) showed the additional contribution of H2O2 by decreasing the ozone demand by 59–75% for all the compounds. The acute toxicity of the digestate, measured by the inhibition of Vibrio fisheries luminescence, decreased by 18.1% during 5 h ozonation, and by 34% during 5 h O3/H2O2 treatment. Despite the high ozone consumption, the ozone dose (mg O3/mg DOC) required to remove all CECs from digestate supernatant was in the range or lower than what has been reported for other (waste-)water matrix, implying that ozonation can be considered as a post-AD treatment to produce cleaner stream for agricultural purposes.</p>
Joint identification of groundwater contamination source and heterogeneous hydrogeological parameters in LNAPL contaminated site based on deep convolutional encoder-decoder neural networks
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Data for "Time domain induced polarization data acquisition at contaminated sites"
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Squeegee: de novo identification of reagent and laboratory induced microbial contaminants in low biomass microbiomes
<p> </p> <p>Computational analysis of host-associated microbiomes has opened the door to numerous discoveries relevant to human health and disease. However, contaminant sequences in metagenomic samples can potentially impact the interpretation of findings reported in microbiome studies, especially in low biomass environments. Our hypothesis is that contamination from DNA extraction kits or sampling lab environments will leave taxonomic "bread crumbs” across multiple distinct sample types, allowing for the detection of microbial contaminants when negative controls are unavailable. To test this hypothesis we implemented Squeegee, a de novo contamination detection tool. We tested Squeegee on simulated and real low biomass metagenomic datasets. On the low biomass samples, we compared Squeegee predictions to experimental negative control data and show that Squeegee accurately recovers known contaminants. We also analyzed 749 metagenomic datasets from the Human Microbiome Project and identified likely previously unreported kit contamination. Collectively, our results highlight that Squeegee can identify microbial contaminants with high precision.</p>
Dataset for contaminant risk assesment in groundwater
<p><span>This data that helps in mapping groundwater contaminant risk (nitrate and phosphate) using the DRASTIC model for a case study in Ethiopia. The data contains a total of </span>9<span> parameters, each having data points ranging from 10 to 33 (196 records in total).</span></p>
Squeegee: de novo identification of reagent and laboratory induced microbial contaminants in low biomass microbiomes, simulation dataset 0.5% spike-in contaminant sequences
<p>Computational analysis of host-associated microbiomes has opened the door to numerous discoveries relevant to human health and disease. However, contaminant sequences in metagenomic samples can potentially impact the interpretation of findings reported in microbiome studies, especially in low biomass environments. Our hypothesis is that contamination from DNA extraction kits or sampling lab environments will leave taxonomic "bread crumbs” across multiple distinct sample types, allowing for the detection of microbial contaminants when negative controls are unavailable. To test this hypothesis we implemented Squeegee, a de novo contamination detection tool. We tested Squeegee on simulated and real low biomass metagenomic datasets. On the low biomass samples, we compared Squeegee predictions to experimental negative control data and show that Squeegee accurately recovers known contaminants. We also analyzed 749 metagenomic datasets from the Human Microbiome Project and identified likely previously unreported kit contamination. Collectively, our results highlight that Squeegee can identify microbial contaminants with high precision.</p> <p> </p> <p>Simulation Dataset 0.5% contaminant spike-in. </p>
The contamination legacy of a decommissioned iron smelter in the Italian Alps
<p>Supplementary material from: The contamination legacy of a decommissioned iron smelter in the Italian Alps</p> <p>Journal of Geochemical Exploration, GEXPLO6064 (PII:S0375-6742(17)30432-6)<br> <br> Soils: collected at a 5, 10, 15, 20 and 25 cm depth, sieved through a 2 mm mesh</p> <p>Study area: former SISMA steel plant of Villadossola (46°04′25″N, 08°16′01″E)</p>
Deepurify: a multi-modal deep language model to remove contamination from metagenome-assembled genomes
<p>The SIM2 testing set.</p>
Figure 2 in Comparative effectiveness of EDTA and citric acid assisted phytoremediation of Ni contaminated soil by using canola (Brassica napus)
Figure 2. The role of EDTA and citric acid on (a) transpiration rate and (b) Stomatal conductance at vegetative stage for phytoremediation of Ni by using canola plant and the role of EDTA and CA on (c) leaf water potential (Ψw) and (d) leaf osmotic potential (Ψs) at vegetative stage for phytoremediation of Ni by using canola plant.
Figure 2 in Harbor seal pup dispersal and individual morphology, hematology, and contaminant factors affecting survival
Figure 2. Proportion of tags still transmitting by week post deployment separated by location of deployment: SF = San Francisco Bay, TB = Tomales Bay, and TMMC = The Marine Mammal Center. Tags that were permanently ashore were considered to be no longer transmitting.
Figure 4 in Harbor seal pup dispersal and individual morphology, hematology, and contaminant factors affecting survival
Figure 4. The relationship between total tag deployment time and dispersal distance per day for satellite tagged seal pups.
Evaluating Heavy Metal Mobility in Contaminated Soils Amended with Biochar: A Kinetic Perspective
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