Brobergwilkins2265

Drug-resistant tuberculosis (TB) is a major public health problem. Clinical Mycobacterium tuberculosis (MTB) isolate with Extensively drug-resistant tuberculosis (MTB-XDR) profile was subjected to whole-genome sequencing using a next-generation sequencing platform (NGS) Roche 454 GS FLX+ followed by bioinformatics sequence analysis. Quality of read was checked by FastQC, paired-end reads were trimmed using Trimmomatic. De novo genome assembly was conducted using Velvet v.1.2.10. The assembled genome of XDR-TB-1599 strain was functionally annotated using the PATRIC platform. Analysis of de novo assembled genome was performed using ResFinder, CARD, CASTB and TB-Profiler tools. MIRU_VNTR genotyping on 12 loci and spoligotyping have been performed for XDR-TB-1599 isolate. M. tuberculosis XDR-TB-1599 strain yielded an average read depth of 21-fold with overall 4 199 325 bp. The assembled genome contains 5528 protein-coding genes, including key drug resistance and virulence-associated genes and GC content of 65.4%. We identified that all proteins encoded by this strain contain conserved domains associated with the first-line anti-tuberculosis drugs such as rifampicin, isoniazid, streptomycin and ethionamide. TB-Profiler had higher average concordance results with phenotypic DST (drug susceptibility testing) in comparison with ResFinder, CARD, CASTB profiling to first-line (75% vs 50%) and second-line (25% vs 0%) of anti-TB drugs, correspondingly. To our knowledge, this is the first report of a highly annotated and characterized whole-genome sequence and de novo assembled XDR-TB M.tuberculosis strain isolated from a sputum of new TB case-patient from Kazakhstan performed on Roche 454 GS FLX+ platform. This report highlights an important role of whole-genome sequencing technology and analysis as an advanced approach for drug-resistance investigations of circulated TB isolates.It is known that the rumen microbiome directly or indirectly contributes to animal production, and may be a prospective target for mitigation of greenhouse gas emissions [1]. At the same time, feed types and components of diet can influence the composition of the rumen microbiome [2,3]. Fluctuations in the composition of the digestive tract microbiota can alter the development, health, and productivity of cattle [4]. Many studies of cattle microbiomes have focussed on the rumen microbiota, whereas the faecal microbiota has received less attention [5], [6], [7]. Therefore, the features of the faecal and the ruminal microbiomes in different cattle breeds are yet to be studied. click here Here, we provided 16S rRNA gene amplicon data of the ruminal and the faecal microbiomes from Yakutian and Kalmyk cattle living in the Republic of Sakha, Yakutia, Russia. Total DNA was extracted from 13 faecal and 13 ruminal samples, and DNA libraries were prepared and sequenced on an Illumina MiSeq platform. Paired-end raw reads were processed, and final operational taxonomic units (OTUs) were assigned to the respective prokaryotic taxa using the RDP (Ribosomal Database Project) database. Analysis of the microbiome composition at the phylum level revealed very similar faecal microbiota between the introduced Kalmyk breed and the indigenous Yakutian breed, whereas the ruminal microbiomes of these breeds differed substantially in terms of relative abundance of some prokaryotic phyla. We believe that the data obtained may provide new insights into the dynamics of the ruminal and the faecal microbiota of cattle as well as disclose breed-specific features of ruminal microbiomes. Besides, these data will contribute to our understanding of the ruminal microbiome structure and function, and might be useful for the management of cattle feeding and ruminal methane production.This dataset presents data collected from household surveys from Upper Madi Watershed of Nepal describing the benefits of non-timber forest products (NTFPs) to people of mountain ecosystems, their perceptions of climate change, and perceived impacts of climate change on NTFPs ecosystem services. The data were collected from 278 households that were randomly selected from the four villages in the watershed during the period September to December 2019. The survey assessed socio-demographic information; collected and utilized NTFPs; perceptions of climate change, and; perceived impacts of climate change on NTFPs ecosystem services. These data are important in understanding the benefits of non-timber forest products in mountain ecosystems and the impacts of climate change as the benefits and impacts are currently not well understood. The data will be helpful in formulation and implementation of adaptation strategies to sustain the supply, protection, and management of NTFPs in mountain ecosystems.The Chaco-Pampean Plain (Argentina) is the strongest economic region and the most inhabited in the country, comprising approximately 66% of the country's population (26,500 million) [1]. In this region, surface slopes are very low ( less then 0.1%) and due to the current climatological features, floods and droughts alternate over time. Salinity and alkalinity of water and soil increase towards the flattest sector of the basin, as well as the contents of arsenic and fluoride, which restrict their human use. Worldwide, population growth and global warming, in addition to political decisions, are leading to abrupt land use changes. Under this premise, identifying and quantifying the hydrological processes that control water quantity and its chemical quality become an imperative task [2]. This data article provides a long-term hydrological dataset from a sector of the Chaco-Pampean Plain, the Del Azul creek basin. Hydrological data such as flow rates and piezometric levels, and physical-chemical (i.e., major and xtensive plain.Non-invasive foetal electrocardiography (fECG) can be obtained at different gestational ages by means of surface electrodes applied on the maternal abdomen. The signal-to-noise ratio (SNR) of the fECG is usually low, due to the small size of the foetal heart, the foetal-maternal compartment, the maternal physiological interferences and the instrumental noise. Even after powerful fECG extraction algorithms, a post-processing step could be required to improve the SNR of the fECG signal. In order to support the researchers in the field, this work presents an annotated dataset of real and synthetic signals, which was used for the study "Wavelet Denoising as a Post-Processing Enhancement Method for Non-Invasive Foetal Electrocardiography" [1]. Specifically, 21 15 s-long fECG, dual-channel signals obtained by multi-reference adaptive filtering from real electrophysiological recordings were included. The annotation of the foetal R peaks by an expert cardiologist was also provided. Recordings were performed on 17 voluntary pregnant women between the 21st and the 27th week of gestation. The raw recordings were also included for the researchers interested in applying a different fECG extraction algorithm. Moreover, 40 10 s-long synthetic non-invasive fECG were provided, simulating the electrode placement of one of the abdominal leads used for the real dataset. The annotation of the foetal R peaks was also provided, as generated by the FECGSYN tool used for the signals' creation. Clean fECG signals were also included for the computation of indexes of signal morphology preservation. All the signals are sampled at 2048 Hz. The data provided in this work can be used as a benchmark for fECG post-processing techniques but can also be used as raw signals for researchers interested in foetal QRS detection algorithms and fECG extraction methods.A dataset of chemical-gene interactions was created by extracting data from the Comparative Toxicogenomics Database (CTD) with the following filtering criteria data was extracted only from experiments that used human, rat, or mouse cells/tissues and used high-throughput approaches for gene expression analysis. Genes not present in genomes of all three species were filtered out. The resulting dataset included 591,084 chemical-gene interaction. All chemical compounds in the database were annotated for their major uses. For every gene in the database number of chemical-gene interactions was calculated and used as a metric of gene sensitivity to a variety of chemical exposures. The lists of genes with corresponding numbers of chemical-gene interactions were used in gene-set enrichment analysis (GSEA) to identify potential sensitivity to chemical exposures of molecular pathways in Hallmark, KEGG and Reactome collections. Thus, data presented here represent unbiased and searchable datasets of sensitivity of genes and molecular pathways to a broad range of chemical exposures. As such the data can be used for a diverse range of toxicological and regulatory applications. Approach for the identification of molecular mechanisms sensitive to chemical exposures may inform regulatory toxicology about best toxicity testing strategies. Analysis of sensitivity of genes and molecular pathways to chemical exposures based on these datasets was published in Chemosphere (Suvorov et al., 2021) [1].Metal(loid) pollution in aquatic ecosystems has become a cause for concern, particularly in areas where communities depend on services from these systems for their livelihood. This dataset presents the metal(loi) concentrations recorded in the water column, bottom sediment, and tissues of Oreochromis mossambicus and Labeo rosae from Flag Boshielo Dam, an impoundment in one of the most polluted river systems in Southern Africa, the Olifants River. The concentrations of metal(loid)s were measured using inductively coupled plasma-optical emission spectrophotometry (ICP-OES; Perkin Elmer, Optima 2100DV). The data generated attest that in aquatic ecosystems, metal(loid)s do not remain in suspension in the water column, but sink down to the bottom sediment where they accumulate or get taken up by receptor organisms such as fish. It further confirm that there is a clear separation on the extent to which metal(loid)s are accumulating in different tissues and liver mostly accumulate higher concentration followed by gills and muscle, respectively. These data can be useful to guide future studies aiming to understand the dynamics, pathways and fate of metal(loid)s in relation to water, sediment and fish tissues. These data can also be used for decision making in relation to the establishment of freshwater fisheries in dams receiving metal(loid)s from different land use activities.The leaf inclination angle distribution is an important parameter in models useful for understanding forest canopy processes of photosynthesis, evapotranspiration, radiation transmission, and spectral reflectance. Yet, despite the strong sensitivity of many of these models to variability in leaf inclination angle distribution, relatively few measurements have been reported for different tree species in literature and databases such as TRY, and various assumptions about leaf inclination angle distribution are often made by modellers. Here we provide a dataset of leaf inclination angles for 71 different Australia-native Eucalyptus species measured in 13 botanical gardens around the world. Leaf inclination angles were measured using a leveled digital camera approach. The leaf angle measurements were used to estimate corresponding Beta distribution parameters and to assign the appropriate classic type of leaf inclination angle distribution. The data can be used to parameterize leaf angle distributions in e.g., physically-based reflectance models, land surface models, and regional carbon cycle models.