China
Africa
Explore chapters and articles related to this topic
Development of Industrial Strain, Medium Characteristics and Biochemical Pathways
Published in Debabrata Das, Soumya Pandit, Industrial Biotechnology, 2021
Over the years, organisms have been classified into various categories. The most commonly accepted classification of organism is Whittaker’s 5-kingdom classification which was based on cell type (prokaryotic or eukaryotic), cell number (single-celled or multi-celled) and nutritional requirements (autotrophy or heterotrophy). This classification includes: i. Monera (bacteria); ii. Protista (algae and protozoa); iii. Plant; iv. Fungi; v. Animal. The latest classification is by Carl Woese which is based on the 16S ribosomal rRNA sequence of prokaryote and the 18S rRNA sequence in eukaryotes. The reasons for choosing this trait are: the rRNA sequence is essential to the normal functioning of the ribosome and is universally distributed in all organisms. It has a single role irrespective of the cell or organism type. It is evolutionarily conserved and has very little mutation over the years. Thus it has a major role in phylogenetic analysis. This classification has helped in classifying the organisms evolutionarily and finding a common ancestor. It has also been useful in finding the genetic distance between two organisms (Song et al., 2015).
Introduction
Published in Debabrata Das, Debayan Das, Biochemical Engineering, 2019
About two million different kinds of organisms live on earth. It is impossible to study every living organism individually; therefore, they are classified into various groups based on their similarities. The science dealing with the description, identification, naming, and classification of organisms is known as taxonomy. It was first developed by Carl Linnaeus. He is known as the father of taxonomy. For the naming of organisms, he introduced a binomial nomenclature comprising a genus name and a species name. Microorganisms can be classified based on their cell type, phenotypic, genotypic, and analytical. The most widely accepted classification based on cell type is the three-domain system introduced by Carl Woese et al. in 1977. It divides cellular life forms into archaea, bacteria, and eukarya domains (Table 1.2). For each domain, the final scientific hierarchy for classification is as follows: Domain > Kingdom > Phylum > Class > Order > Family > Genus > Species.
Rock mass classifications study with the neural network theory
Published in T. Adachi, K. Tateyama, M. Kimura, Modern Tunneling Science and Technology, 2017
The concept of classification involves the learning of likenesses and differences of patterns that are abstractions of instances of objects in a population of nonidentical objects. When it is determined that an object from a population P belongs to a known subpopulation, a pattern recognition is done. Classification is the process of grouping objects together into classes (subpopulations) according to their perceived likenesses or similarities. The subject area of pattern recognition includes both classification and recognition (Looney 1997).
Microbial community composition in different carbon source types of biofilm A/O-MBR systems with complete sludge retention
Published in Environmental Technology, 2021
Adoonsook Dome, Chia-Yuan Chang, Wongrueng Aunnop, Pumas Chayakorn
Furthermore, paired-end Illumina MiSeq sequencing on an Illumina MiSeq device (Illumina Inc., San Diego, CA, USA) with 600 cycles (12 cycles for the barcode sequence and 300 cycles for each paired read) was carried out by following the manufacturer’s instructions. Routinely, a control library of genomic DNA was mixed from the phage phix to prevent focusing and phasing problems. This was done to increase genetic diversity artificially due to the sequencing of ‘low diversity’ libraries. The 16S-based metagenomics workflow of MiSeq Reporter version 2.6.2.3 (Illumina) was applied to achieve sequence analysis. For the purposes of sequencing on an Illumina MiSeq sequencing system, samples were archived in a specified library which generated pairs of 300 bp reads. Subsequently, sequences were demultiplexed according to the relevant index sequences. For the purposes of accuracy and standardization, FASTQ files with Quality Score Encoding were generated. Additionally, operational taxonomic units clustering and classification at kingdom level, phylum level, class level, order level, family level, genus level, and species level were included in the experimental protocol. Files of the processed data and the raw sequencing data are available at the following website: www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE139113.
Insight into bacterial community profiles of oil shale and sandstone in ordos basin by culture-dependent and culture-independent methods
Published in Journal of Environmental Science and Health, Part A, 2022
Fengdan Wei, Rui Xu, Yuanyuan Xu, Tao Cheng, Yanling Ma
UPARSE software[19] was used to cluster the effective tags of those samples, and sequences with ≥97% similarity were assigned to the same operational taxonomic units (OTUs). The sequence with the highest occurrence frequency in OTUs was selected as the representative sequence of OTUs. Using the Mothur method and SSUrRNA database[20], OTUs sequences were annotated and analyzed (the threshold was set at 0.8 ∼ 1) as well as the taxonomic information was obtained. The community composition of every sample was calculated at the taxonomic classification down to the phylum, class, order, family, genus level. The phylogenetic relationships of all OTUs representative sequences were done with MUSCLE software[21]. Additionally, the data of every sample was homogenized, and the least amount of data in the sample was taken as the standard. The subsequent alpha and beta diversity analysis was based on the homogenized data. Qiime software (Version 1.9.1) was used to calculate the observed OTUs, Chao1, Shannon, Simpson, Ace, Good’s coverage, PD whole tree indices. R software (Version 2.15.3) was used to draw the dilution, rank abundance and species accumulation curves, as well as to analyze the differences of alpha and beta diversity index in those groups. Tukey test and Wilcox test were carried out for the significant difference of alpha diversity index and beta diversity index. The Unifrac distance was calculated by Qiime software (Version 1.9.1), and the UPGMA sample cluster tree was constructed. The principal component analysis (PCA) and principal co-ordinates analysis (PCoA) diagrams were done based on weighted UniFrac distance. Venn diagrams were generated through the packages gplots and limma in R v.4.0.0 (http://www.R-project.org).
Microbial characteristics and potential mechanisms of souring control for a hypersaline oil reservoir
Published in Petroleum Science and Technology, 2023
Bo Wang, Shuyuan Deng, Sanbao Su, Shanshan Sun, Chao Chen, Hao Xu, Hongfei Ma, Ibrahim M. Banat, Yuehui She, Fan Zhang
The raw multiplexed sequence data were analyzed using QIIME (www.qiime.org) and R package that calculated the number of operational taxonomic units and the number of reads in each library (Bokulich et al. 2018). Removing the singleton statistically analyzed the feature table, and the composition of microbial community of samples was visualized as violin at the at the six classification levels of phylum, class, order, family, genus and species. The obtained raw data using 16S rDNA sequencing had been to submit to NCBI database (PRJNA: 683706).