1,721,063 research outputs found
Plasticizers determine a deeper reshape of soil virome than microplastics
Full text linkViruses play a crucial role in shaping local and global biogeochemical cycles, supporting bacterial survival in diverse environments by encoding auxiliary metabolic genes involved in energy acquisition, stress tolerance, and the degradation of organics. However, how plastic pollution influences soil viromes remains largely unexplored, in particular when microplastics and plasticizers are involved in the process. In this study, we conducted an incubation experiment where soil samples from rice fields were exposed to microplastics—polyethylene and polyvinyl chloride and the plasticizer diethyl phthalate to assess their effects on viral communities. After controlled incubation, second- and third-generation sequencing, along with advanced bioinformatics, were used to determine whether viral taxa were impacted by these contaminants. Our results revealed that diethyl phthalate exposure led to a 3.15-fold increase in the proportion of viral sequences in the treated samples compared to control soils, significantly surpassing the modest increases observed for polyethylene (13.08%) and polyvinyl chloride (48.59%). These shifts were accompanied by changes in viral diversity, functional gene content, and virus-host interactions. Notably, we identified virus-encoded auxiliary metabolic genes, such as the 3-oxoadipate enol-lactonase (PcaD) gene, which are critical for phthalate degradation. This finding underscores the direct role of phages in facilitating microbial adaptation and pollutant degradation in contaminated soils, suggesting that viral auxiliary metabolic genes could be harnessed for targeted bioremediation strategies to mitigate the environmental impact of plastic pollutants
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Modeling temperature response in bioenergy production: Novel solution to a common challenge of anaerobic digestion
Full text linkTemperature is one of the most crucial state variables in industrial process control, which is particularly true for the biochemical conversion of biomass, as in anaerobic digestion. However, modeling the effects of temperature changes on anaerobic microbial growth are commonly considered in quasi-steady state, neglecting the timely dynamics of microbial adaptation to such phenomena. To address this inflexibility, the current work presents a new way for temperature effect calculation that improves the simulation efficiency of bioconversion models. The calculation was implemented as a function in a dynamic mathematical model of anaerobic digestion, and was validated via the simulation of experimental data from two laboratory-scale continuous experiments, involving both short- and long-term temperature changes. Model validity was further supported by 16s rRNA gene sequencing data. The bioconversion model extended with the new temperature function showed significant improvements in simulating the most important dependent variables of the digestion process, such as methane production rate and volatile fatty acid concentration during temperature variations. Finally, microbial analysis results shed light on the potential reasons for differences between simulated and experimental results. Overall, the dynamic temperature function was found to be an important addition to the reference model, allowing its user to generate more accurate simulations of digestion processes with changing temperature conditions. Furthermore, it can be seen as a step towards advanced time series forecasting, with potential benefits for integrated process design, process energy optimization and predicting the behavior of full-scale operations affected by ambient temperature conditions
Genetic and physiological characterization of oenological Saccharomyces cerevisiae strains for genome sequencing purpose
No full textStrain-resolved metagenomics approaches applied to biogas upgrading
Full text linkGenetic heterogeneity is a common trait in microbial populations, caused by de novo mutations and changes in variant frequencies over time. Microbes can thus differ genetically within the same species and acquire different phenotypes. For instance, performance and stability of anaerobic reactors are linked to the composition of the microbiome involved in the digestion process and to the environmental parameters imposing selective pressure on the metagenome, shaping its evolution. Changes at the strain level have the potential to determine variations in microbial functions, and their characterization could provide new insight into ecological and evolutionary processes driving anaerobic digestion. In this work, single nucleotide variant dynamics were studied in two time-course biogas upgrading experiments, testing alternative carbon sources and the response to exogenous hydrogen addition. A cumulative total of 76,229 and 64,289 high-confidence single nucleotide variants were discerned in the experiments related to carbon substrate availability and hydrogen addition, respectively. By combining complementary bioinformatic approaches, the study reconstructed the precise strain count—two for both hydrogenotrophic archaea—and tracked their abundance over time, while also characterizing tens of genes under strong selection. Results in the dominant archaea revealed the presence of nearly 100 variants within genes encoding enzymes involved in hydrogenotrophic methanogenesis. In the bacterial counterparts, 119 mutations were identified across 23 genes associated with the Wood-Ljungdahl pathway, suggesting a possible impact on the syntrophic acetate-oxidation process. Strain replacement events took place in both experiments, confirming the trends suggested by the variants trajectories and providing a comprehensive understanding of the biogas upgrading microbiome at the strain level. Overall, this resolution level allowed us to reveal fine-scale evolutionary mechanisms, functional dynamics, and strain-level metabolic variation that could contribute to the selection of key species actively involved in the carbon dioxide fixation process
Metapresence: a tool for accurate species detection in metagenomics based on the genome-wide distribution of mapping reads
Full text linkShotgun metagenomics allows comprehensive sampling of the genomic information of microbes in a given environment and is a tool of choice for studying complex microbial systems. Mapping sequencing reads against a set of reference or metagenome-assembled genomes is in principle a simple and powerful approach to define the species-level composition of the microbial community under investigation. However, despite the widespread use of this approach, there is no established way to properly interpret the alignment results, with arbitrary relative abundance thresholds being routinely used to discriminate between present and absent species. Such an approach can be affected by significant biases, especially in the identification of rare species. Therefore, it is important to develop new metrics to overcome these biases. Here, we present Metapresence, a new tool to perform reliable identification of the species in metagenomic samples based on the distribution of mapped reads on the reference genomes. The analysis is based on two metrics describing the breadth of coverage and the genomic distance between consecutive reads. We demonstrate the high precision and wide applicability of the tool using data from various synthetic communities, a real mock community, and the gut microbiome of healthy individuals and antibiotic-associated-diarrhea patients. Overall, our results suggest that the proposed approach has a robust performance in hard-to-analyze microbial communities containing contaminated or closely related genomes in low abundance
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
- …
