ribo-seq-bacteria-sample-collection-library-preparation-protocol-for

RIBO-seq in Bacteria: a Sample Collection and Library Preparation Protocol for NGS Sequencing

The ribosome profiling technique (RIBO-seq) is currently the most effective tool for studying the process of protein synthesis in vivo. The advantage of ...

Maria Curie-Sklodowska University

Fourier Transform Infrared (FT-IR) spectroscopy and imaging combined with hierarchical cluster analysis (HCA) was applied to analyse biochemical properties of Early Middle Ages hemp ( L.) bast fibres collected from lake bottom sediment of lake Słone. The examined plant macrofossil material constitutes residues of the hemp retting process that took place in the 7th-8th century. By comparison of three samples: untreated isolated bast fibres, and fibres incubated overnight at 4 and 37 °C, we were able to mimic the retting conditions. Using FT-IR qualitative and semi-quantitative assessment of the primary polysaccharides content, total protein content, and their spatial distribution was performed within the hemp fibres. The concentration of cellulose remained vastly unchanged, while the concentration of lignin and pectin was the highest in the untreated sample. The spatial distributions of compounds were heterogeneous in the untreated and 4 °C-incubated samples, and homogenous in the specimen processed at 37 °C. Interestingly, a higher amide content was detected in the latter sample indicating the highest degree of enzymatic degradation. In this study, we show that the spectroscopic methods allow for a non-destructive evaluation of biochemical composition of plant fibres without preparation, which can be an appropriate approach for studying ancient plant remains.

Vibrational Spectroscopic Analyses and Imaging of the Early Middle Ages Hemp Bast Fibres Recovered from Lake Sediments.

European  and Asian  honeybees are essential crop pollinators. Microbiome studies can provide complex information on health and fitness of these insects in relation to environmental changes, and plant availability. Amplicon sequencing of variable regions of the 16S rRNA from bacteria and the internally transcribed spacer (ITS) regions from fungi and plants allow identification of the metabiome. These methods provide a tool for monitoring otherwise uncultured microbes isolated from the gut of the honeybees. They also help monitor the composition of the gut fungi and, intriguingly, pollen collected by the insect. Here, we present data from amplicon sequencing of the 16S rRNA from bacteria and ITS2 regions from fungi and plants derived from honeybees collected at various time points from anthropogenic landscapes such as urban areas in Poland, UK, Spain, Greece, and Thailand. We have analysed microbial content of honeybee intestine as well as fungi and pollens. Furthermore, isolated DNA was used as the template for screening pathogens: , , , tracheal mite (), any organism in the parasitic order Trypanosomatida, including Crithidia spp. (i.e., ), neogregarines including  and  spp. (i.e., ). We conclude that differences between samples were mainly influenced by the bacteria, plant pollen and fungi, respectively. Moreover, honeybees feeding on a sugar based diet were more prone to fungal pathogens () and neogregarines. In most samples  sp. and neogregarines parasitized the host bee at the same time. A higher load of fungi, and bacteria groups such as Firmicutes (); -proteobacteria, Neisseriaceae, and other unidentified bacteria was observed for  and neogregarine infected honeybees. Healthy honeybees had a higher load of plant pollen, and bacteria groups such as: , , , and Enterobacteriaceae. Finally, the period when honeybees switch to the winter generation (longer-lived forager honeybees) is the most sensitive to diet perturbations, and hence pathogen attack, for the whole beekeeping season. It is possible that evolutionary adaptation of bees fails to benefit them in the modern anthropomorphised environment.

Amplicon Sequencing of Variable 16S rRNA from Bacteria and ITS2 Regions from Fungi and Plants, Reveals Honeybee Susceptibility to Diseases Results from Their Forage Availability under Anthropogenic Landscapes.

Forager  honeybees were collected from four localities located in Europe, i.e.: London, UK; Athens, Greece; Marchamalo, Spain and Lublin, Poland. Furthermore, from Asia we have collected  as well as  foragers form Chiang Mai in Thailand We used next generation sequencing (NGS) to analyse the 16S rRNA bacterial gene amplicons based on the V3-V4 region and the ITS2 region from fungi and plants derived from honeybee samples. Amplicon libraries, were prepared using the 16S Metagenomic Sequencing Library Preparation, Preparing 16S Ribosomal RNA Gene Amplicons for the Illumina MiSeq System (Illumina®) protocol. NGS raw data are available at https://www.ncbi.nlm.nih.gov/bioproject/PRJNA686953. Furthermore, isolated DNA was used as the template for screening pathogens: , tracheal mite (), any organism in the parasitic order Trypanosomatida, including  spp. (i.e., ), neogregarines including  and  spp. (i.e., ). The presented data can be used to compare the metagenomic samples from different honeybee population all over the world. A higher load of fungi, and bacteria groups such as: Firmicutes ();  proteobacteria Neisseriaceae and other unidentified bacteria was observed for  and neogregarines infected honeybees. Healthy honeybees had a higher load of plant pollens, and bacteria groups such as:  and Enterobacteriaceae More details can be found in research article [1] Ptaszyńska et al. 2021.

Dataset of the next-generation sequencing of variable 16S rRNA from bacteria and ITS2 regions from fungi and plants derived from honeybees kept under anthropogenic landscapes.

Agata L. Starosta

Laboratory of Gene Expression,
ECOTECH-COMPLEX,
Department of Molecular Biology,
Institute of Biological Sciences,
Laboratory of Gene Expression, ECOTECH-Complex,
Department of Molecular Biology, Institute of Biological Sciences

Maria Curie-Sklodowska University

RIBO-seq in Bacteria: a Sample Collection and Library Preparation Protocol for NGS Sequencing