TET1 may contribute to hypoxia-induced epithelial to mesenchymal transition of endometrial epithelial cells in endometriosis
Background Endometriosis (EMs) is a non-malignant gynecological disease, whose pathogenesis remains to be clarified. Recent studies have found that hypoxia induces epithelial-mesenchymal transition (EMT) as well as epigenetic modification in EMs. However, the relationship between EMT and demethylation modification under hypoxia status in EMs remains unknown. Methods The expression of N-cadherin, E-cadherin and TET1 in normal endometria, eutopic endometria and ovarian endometriomas was assessed by immunohistochemistry and immunofluorescence double staining. 5-hmC was detected by fluorescence-based ELISA kit using a specific 5-hmC antibody. Overexpression and inhibition of TET1 or hypoxia-inducible factor 2α (HIF-2α) were performed by plasmid and siRNA transfection. The expression of HIF-2α, TET1 and EMT markers in Ishikawa (ISK) cells (widely used as endometrial epithelial cells) was evaluated by western blotting. The interaction of HIF-2α and TET1 was analyzed by chromatin immunoprecipitation. Results Demethylation enzyme TET1 (ten-eleven translocation1) was elevated in glandular epithelium of ovarian endometrioma, along with the activation of EMT (increased expression of N-cadherin, and decreased expression of E-cadherin) and global increase of epigenetic modification marker 5-hmC(5-hydroxymethylcytosine). Besides, endometriosis lesions had more TET1 and N-cadherin co-localized cells. Further study showed that ISK cells exhibited enhanced EMT, and increased expression of TET1 and HIF-2α under hypoxic condition. Hypoxia-induced EMT was partly regulated by TET1 and HIF-2α. HIF-2α inhibition mitigated TET1 expression changes provoked by hypoxia. Conclusions Hypoxia induces the expression of TET1 regulated by HIF-2α, thus may promote EMT in endometriosis.
Wu et al. (2020) TET1 may contribute to hypoxia-induced epithelial to mesenchymal transition of endometrial epithelial cells in endometriosis. PeerJ 8:e9950 https://doi.org/10.7717/peerj.9950
Prophet forecasting model: a machine learning approach to predict the concentration of air pollutants (PM2.5, PM10, O3, NO2, SO2, CO) in Seoul, South Korea
Amidst recent industrialization in South Korea, Seoul has experienced high levels of air pollution, an issue that is magnified due to a lack of effective air pollution prediction techniques. In this study, the Prophet forecasting model (PFM) was used to predict both short-term and long-term air pollution in Seoul. The air pollutants forecasted in this study were PM2.5, PM10, O3, NO2, SO2, and CO, air pollutants responsible for numerous health conditions upon long-term exposure. Current chemical models to predict air pollution require complex source lists making them difficult to use. Machine learning models have also been implemented however their requirement of meteorological parameters render the models ineffective as additional models and infrastructure need to be in place to model meteorology. To address this, a model needs to be created that can accurately predict pollution based on time. A dataset containing three years worth of hourly air quality measurements in Seoul was sourced from the Seoul Open Data Plaza. To optimize the model, PFM has the following parameters: model type, changepoints, seasonality, holidays, and error. Cross validation was performed on the 2017–18 data; then, the model predicted 2019 values. To compare the predicted and actual values and determine the accuracy of the model, the statistical indicators: mean squared error (MSE), mean absolute error (MAE), root mean squared error (RMSE), and coverage were used. PFM predicted PM2.5 and PM10 with a MAE value of 12.6 µg/m3 and 19.6 µg/m3, respectively. PFM also predicted SO2 and CO with a MAE value of 0.00124 ppm and 0.207 ppm, respectively. PFM’s prediction of PM2.5 and PM10 had a MAE approximately 2 times and 4 times less, respectively, than comparable models. PFM’s prediction of SO2and CO had a MAE approximately five times and 50 times less, respectively, than comparable models. In most cases, PFM’s ability to accurately forecast the concentration of air pollutants in Seoul up to one year in advance outperformed similar models proposed in literature. This study addresses the limitations of the prior two PFM studies by expanding the modelled air pollutants from three pollutants to six pollutants while increasing the prediction time from 3 days to 1 year. This is also the first research to use PFM in Seoul, Korea. To achieve more accurate results, a larger air pollution dataset needs to be implemented with PFM. In the future, PFM should be used to predict and model air pollution in other regions, especially those without advanced infrastructure to model meteorology alongside air pollution. In Seoul, Seoul’s government can use PFM to accurately predict air pollution concentrations and plan accordingly.
Environmental Contamination and Remediation
Spatial and Geographic Information Science
Shen et al. (2020) Prophet forecasting model: a machine learning approach to predict the concentration of air pollutants (PM2.5, PM10, O3, NO2, SO2, CO) in Seoul, South Korea. PeerJ 8:e9961 https://doi.org/10.7717/peerj.9961
Seasonal and successional dynamics of size-dependent plant demographic rates in a tropical dry forest
Tropical forests are globally important for biodiversity conservation and climate change mitigation but are being converted to other land uses. Conversion of seasonally dry tropical forests (SDTF) is particularly high while their protection is low. Secondary succession allows forests to recover their structure, diversity and composition after conversion and subsequent abandonment and is influenced by demographic rates of the constituent species. However, how these rates vary between seasons for different plant sizes at different successional stages in SDTF is not known. The effect of seasonal drought may be more severe early in succession, when temperature and radiation are high, while competition and density-dependent processes may be more important at later stages, when vegetation is tall and dense. Besides, the effects of seasonality and successional stage may vary with plant size. Large plants can better compete with small plants for limiting resources and may also have a greater capacity to withstand stress. We asked how size-dependent density, species density, recruitment and mortality varied between seasons and successional stages in a SDTF. We monitored a chronosequence in Yucatan, Mexico, over six years in three 0.1 ha plots in each of three successional stages: early (3–5 years-old), intermediate (18–20 years-old) and advanced (>50 years-old). Recruitment, mortality and species gain and loss rates were calculated from wet and dry season censuses separately for large (diameter > 5 cm) and small (1–5 cm in diameter) plants. We used linear mixed-effects models to assess the effects of successional stage, seasonality and their changes through time on demographic rates and on plant and species density. Seasonality affected demographic rates and density of large plants, which exhibited high wet-season recruitment and species gain rates at the early stage and high wet-season mortality at the intermediate stage, resulting in an increase in plant and species density early in succession followed by a subsequent stabilization. Small plant density decreased steadily after only 5 years of land abandonment, whereas species density increased with successional stage. A decline in species dominance may be responsible for these contrasting patterns. Seasonality, successional stage and their changes through time had a stronger influence on large plants, likely because of large among-plot variation of small plants. Notwithstanding the short duration of our study, our results suggest that climate-change driven decreases in rainy season precipitation may have an influence on successional dynamics in our study forest as strong as, or even stronger than, prolonged or severe droughts during the dry season.
Saenz-Pedroza et al. (2020) Seasonal and successional dynamics of size-dependent plant demographic rates in a tropical dry forest. PeerJ 8:e9636 https://doi.org/10.7717/peerj.9636
Rediscovery of Cyperus flavescens (Cyperaceae) on the northeast periphery of its range in Europe
In recent years, three large populations of Cyperus flavescens were found in Poland, the richest occurrence of this species in over 30 years. The goal of this research is to determine the habitat factors lead to the mass occurrence of C. flavescens and the present situation of that species and its habitat in Central Europe. Soil conditions of the three populations were studied. To determine the correlation between the occurrence and abundance of species and the chemical parameters of the soil, the DCA and CCA methods were used. The DCA of environmental Ellenberg values was made for all relevés known from Poland. The occurrence of C. flavescens in plant communities in Central Europe was studied. The maximum entropy method was used for potential distribution analysis of C. flavescens. All analyzed traits are important for this species and none has an advantage over another, so the environmental factor affecting the occurrence of C. flavescens is different from the tested. Analysis on Ellenberg values indicate that the longest gradients are temperature, moisture and nutrients. The analysis of vegetation data involving Cyperus flavescens available from Central Europe indicates that this species occurs mainly in the company of Juncus bufonius and Plantago intermedia, whereas other species of the Isoëto-Nanojuncetea class appear rarely. In MaxEnt analysis based on bioclimatic variables, the most important variable is BIO1 (Annual Mean Temperature). The results of our observation indicate that anthropogenic factors such as grazing livestock have a positive effect on the occurrence of the species. It is also very likely that the species is promoted by very warm summers with only short periods of heavy rains. A map of the potential distribution of C. flavescens in Central Europe created according historical and future data show an extension of the range of potential habitats to the north and east.
Marciniuk et al. (2020) Rediscovery of Cyperus flavescens (Cyperaceae) on the northeast periphery of its range in Europe. PeerJ 8:e9837 https://doi.org/10.7717/peerj.9837
Potential role of cellular miRNAs in coronavirus-host interplay
Host miRNAs are known as important regulators of virus replication and pathogenesis. They can interact with various viruses through several possible mechanisms including direct binding of viral RNA. Identification of human miRNAs involved in coronavirus-host interplay becomes important due to the ongoing COVID-19 pandemic. In this article we performed computational prediction of high-confidence direct interactions between miRNAs and seven human coronavirus RNAs. As a result, we identified six miRNAs (miR-21-3p, miR-195-5p, miR-16-5p, miR-3065-5p, miR-424-5p and miR-421) with high binding probability across all analyzed viruses. Further bioinformatic analysis of binding sites revealed high conservativity of miRNA binding regions within RNAs of human coronaviruses and their strains. In order to discover the entire miRNA-virus interplay we further analyzed lungs miRNome of SARS-CoV infected mice using publicly available miRNA sequencing data. We found that miRNA miR-21-3p has the largest probability of binding the human coronavirus RNAs and being dramatically up-regulated in mouse lungs during infection induced by SARS-CoV.
Nersisyan et al. (2020) Potential role of cellular miRNAs in coronavirus-host interplay. PeerJ 8:e9994 https://doi.org/10.7717/peerj.9994
Unexpected diversity in the host-generalist oribatid mite Paraleius leontonychus (Oribatida, Scheloribatidae) phoretic on Palearctic bark beetles
Bark beetles are feared as pests in forestry but they also support a large number of other taxa that exploit the beetles and their galleries. Among arthropods, mites are the largest taxon associated with bark beetles. Many of these mites are phoretic and often involved in complex interactions with the beetles and other organisms. Within the oribatid mite family Scheloribatidae, only two of the three nominal species of Paraleius have been frequently found in galleries of bark beetles and on the beetles themselves. One of the species, P. leontonychus, has a wide distribution range spanning over three ecozones of the world and is believed to be a host generalist, reported from numerous bark beetle and tree species. In the present study, phylogenetic analyses of one mitochondrial and two nuclear genes identified six well supported, fairly divergent clades within P. leontonychus which we consider to represent distinct species based on molecular species delimitation methods and largely congruent clustering in mitochondrial and nuclear gene trees. These species do not tend to be strictly host specific and might occur syntopically. Moreover, mito-nuclear discordance indicates a case of past hybridization/introgression among distinct Paraleius species, the first case of interspecific hybridization reported in mites other than ticks.
Schäffer et al. (2020) Unexpected diversity in the host-generalist oribatid mite Paraleius leontonychus (Oribatida, Scheloribatidae) phoretic on Palearctic bark beetles. PeerJ 8:e9710 https://doi.org/10.7717/peerj.9710
The impact of climate change on flow conditions and wetland ecosystems in the Lower Biebrza River (Poland)
Water plays a key role in the functioning of wetlands and a shortage or contamination of it leads to changes in habitat conditions and degradation of ecosystems. This article scrutinizes the impact of climate change on the hydrological characteristics of floods (maximum flow, duration, volume) in the River Biebrza wetlands (North-East Poland). We analysed the trends in duration and volume of flood and maximum discharges in the historical period 1970–2000 and predicted these for the future periods 2020–2050 and 2070–2100, respectively. Next we assessed the impact on the wetland ecosystems. The basis of our assessments consists of statistical analyses of hydrographs and calculations by the Soil and Water Assessment Tool hydrological model and considering nine bias-corrected climate models. The results indicate that both volume and duration of winter floods will keep increasing continuously under Representative Concentration Pathways 4.5 and 8.5. The reduction in peak annual floods is expected to decline slightly in both scenarios. On the other hand, the analysis of trends in mean and standard deviation revealed negligible tendencies in the datasets for summer and winter hydrological seasons within the three time frames analysed (1970–2000; 2020–2050; 2070–2100). We foresee several future implications for the floodplain ecosystems. Shifts in transversal ecosystem zonation parallel to the river will likely take place with more highly productive flood tolerant vegetation types. Nutrient availability and algal blooms during spring inundations will likely increase. Slowdown of organic matter turnover later in summer will lead to a higher peat accumulation rate. Logistical problems with summer mowing and removal of bushes in winter may enhance shrub encroachment.
Mirosław-Świątek et al. (2020) The impact of climate change on flow conditions and wetland ecosystems in the Lower Biebrza River (Poland). PeerJ 8:e9778 https://doi.org/10.7717/peerj.9778
Methylase-assisted subcloning for high throughput BioBrick assembly
The BioBrick standard makes possible iterated pairwise assembly of cloned parts without any depletion of unique restriction sites. Every part that conforms to the standard is compatible with every other part, thereby fostering a worldwide user community. The assembly methods, however, are labor intensive or inefficient compared to some newer ones so the standard may be falling out of favor. An easier way to assemble BioBricks is described herein. Plasmids encoding BioBrick parts are purified from Escherichia coli cells that express a foreign site-specific DNA methyltransferase, so that each is subsequently protected in vitro from the activity of a particular restriction endonuclease. Each plasmid is double-digested and all resulting restriction fragments are ligated together without gel purification. The ligation products are subsequently double-digested with another pair of restriction endonucleases so only the desired insert-recipient vector construct retains the capacity to transform E. coli. This 4R/2M BioBrick assembly protocol is more efficient and accurate than established workflows including 3A assembly. It is also much easier than gel purification to miniaturize, automate and perform more assembly reactions in parallel. As such, it should streamline DNA assembly for the existing community of BioBrick users, and possibly encourage others to join.
Matsumura (2020) Methylase-assisted subcloning for high throughput BioBrick assembly. PeerJ 8:e9841 https://doi.org/10.7717/peerj.9841
ProminTools: shedding light on proteins of unknown function in biomineralization with user friendly tools illustrated using mollusc shell matrix protein sequences
Biominerals are crucial to the fitness of many organism and studies of the mechanisms of biomineralization are driving research into novel materials. Biomineralization is generally controlled by a matrix of organic molecules including proteins, so proteomic studies of biominerals are important for understanding biomineralization mechanisms. Many such studies identify large numbers of proteins of unknown function, which are often of low sequence complexity and biased in their amino acid composition. A lack of user-friendly tools to find patterns in such sequences and robustly analyse their statistical properties relative to the background proteome means that they are often neglected in follow-up studies. Here we present ProminTools, a user-friendly package for comparison of two sets of protein sequences in terms of their global properties and motif content. Outputs include data tables, graphical summaries in an html file and an R-script as a starting point for data-set specific visualizations. We demonstrate the utility of ProminTools using a previously published shell matrix proteome of the giant limpet Lottia gigantea.
Skeffington et al. (2020) ProminTools: shedding light on proteins of unknown function in biomineralization with user friendly tools illustrated using mollusc shell matrix protein sequences. PeerJ 8:e9852 https://doi.org/10.7717/peerj.9852
Intergenerational implications of alcohol intake: metabolic disorders in alcohol-naïve rat offspring
Alcohol drinking may be associated with an increased risk of various metabolic diseases. Rat lines selectively bred for alcohol preference and alcohol avoidance constitute an interesting model to study inherited factors related to alcohol drinking and metabolic disorders. The aim of the present study was to compare the levels of selected laboratory biomarkers of metabolic disorders in blood samples from naïve offspring of Warsaw alcohol high-preferring (WHP), Warsaw alcohol low-preferring (WLP), and wild Wistar rats. Blood samples were collected from 3-month old (300–350 g) alcohol-naïve, male offspring of WHP (n = 8) and WLP rats (n = 8), as well as alcohol-naïve, male, wild Wistar rats. Markers of metabolic, hepatic, and pancreatic disorders were analysed (levels of homocysteine, glucose, total cholesterol, triglycerides and γ-glutamyl transferase (GGT), aspartate (AST), alanine aminotransferase (ALT), and amylase serum activities). Alcohol-naïve offspring of WHP, WLP, and wild Wistar rats differed significantly in the levels of triglycerides, total cholesterol, homocysteine, as well as in the activity of GGT, ALT, AST, and amylase enzymes. Most markers in the alcohol-naïve offspring of WHP rats were altered even thought they were never exposed to alcohol pre- or postnatally. This may suggest that parental alcohol abuse can have a detrimental influence on offspring vulnerability to metabolic disorders.
Mierzejewski et al. (2020) Intergenerational implications of alcohol intake: metabolic disorders in alcohol-naïve rat offspring. PeerJ 8:e9886 https://doi.org/10.7717/peerj.9886