The Human Microbiome.

Nucleic acid separation is an increasingly important tool for molecular biology. Before modern technologies could be used, nucleic acid separation had been a time- and work-consuming process based on several extraction and centrifugation steps, often limited by small yields and low purities of the separation products, and not suited for automation and up-scaling. During the last few years, specifically functionalised magnetic particles were developed. Together with an appropriate buffer system, they allow for the quick and efficient purification directly after their extraction from crude cell extracts. Centrifugation steps were avoided. In addition, the new approach provided for an easy automation of the entire process and the isolation of nucleic acids from larger sample volumes. This review describes traditional methods and methods based on magnetic particles for nucleic acid purification. The synthesis of a variety of magnetic particles is presented in more detail. Various suppliers of magnetic particles for nucleic acid separation as well as suppliers offering particle-based kits for a variety of different sample materials are listed. Furthermore, commercially available manual magnetic separators and automated systems for magnetic particle handling and liquid handling are mentioned.

Magnetic particles for separation and purification of nucleic acids

International Collaboration on Endocarditis Prospective Cohort Study

OMA is an established resource to elucidate evolutionary relationships among genes from currently 2326 genomes covering all domains of life. OMA provides pairwise and groupwise orthologs, functional annotations, local and global gene order conservation (synteny) information, among many other functions. This update paper describes the reorganisation of the database into gene-, group- and genome-centric pages. Other new and improved features are detailed, such as reporting of the evolutionarily best conserved isoforms of alternatively spliced genes, the inferred local order of ancestral genes, phylogenetic profiling, better cross-references, fast genome mapping, semantic data sharing via RDF, as well as a special coronavirus OMA with 119 viruses from the Nidovirales order, including SARS-CoV-2, the agent of the COVID-19 pandemic. We conclude with improvements to the documentation of the resource through primers, tutorials and short videos. OMA is accessible at https://omabrowser.org.

/pdf/oma-orthology-in-2021-website-overhaul-conserved-isoforms-5502g1uymt.pdf

OMA orthology in 2021: website overhaul, conserved isoforms, ancestral gene order and more.

Bacterial culture and biochemical testing (CBtest) have been the cornerstone of pathogen identification in the diagnostic microbiology laboratory. With the advent of Sanger sequencing and later, next-generation sequencing, 16S rRNA next-generation sequencing (16SNGS) has been proposed to be a plausible platform for this purpose. Nevertheless, usage of the 16SNGS platform has both advantages and limitations. In addition, transition from the traditional methods of CBtest to 16SNGS requires procurement of costly equipment, timely and sustainable maintenance of these platforms, specific facility infrastructure and technical expertise. All these factors pose a challenge for middle-income countries, more so for countries in the lower middle-income range. In this review, we describe the basis for CBtest and 16SNGS, and discuss the limitations, challenges, advantages and future potential of using 16SNGS for bacterial pathogen identification in diagnostic microbiology laboratories of middle-income countries.

Advantages and Limitations of 16S rRNA Next-Generation Sequencing for Pathogen Identification in the Diagnostic Microbiology Laboratory: Perspectives from a Middle-Income Country.

This review provides a state-of-the-art description of the performance of Sanger cycle sequencing of the 16S rRNA gene for routine identification of bacteria in the clinical microbiology laboratory. A detailed description of the technology and current methodology is outlined with a major focus on proper data analyses and interpretation of sequences. The remainder of the article is focused on a comprehensive evaluation of the application of this method for identification of bacterial pathogens based on analyses of 16S multialignment sequences. In particular, the existing limitations of similarity within 16S for genus- and species-level differentiation of clinically relevant pathogens and the lack of sequence data currently available in public databases is highlighted. A multiyear experience is described of a large regional clinical microbiology service with direct 16S broad-range PCR followed by cycle sequencing for direct detection of pathogens in appropriate clinical samples. The ability of proteomics (matrix-assisted desorption ionization-time of flight) versus 16S sequencing for bacterial identification and genotyping is compared. Finally, the potential for whole-genome analysis by next-generation sequencing (NGS) to replace 16S sequencing for routine diagnostic use is presented for several applications, including the barriers that must be overcome to fully implement newer genomic methods in clinical microbiology. A future challenge for large clinical, reference, and research laboratories, as well as for industry, will be the translation of vast amounts of accrued NGS microbial data into convenient algorithm testing schemes for various applications (i.e., microbial identification, genotyping, and metagenomics and microbiome analyses) so that clinically relevant information can be reported to physicians in a format that is understood and actionable. These challenges will not be faced by clinical microbiologists alone but by every scientist involved in a domain where natural diversity of genes and gene sequences plays a critical role in disease, health, pathogenicity, epidemiology, and other aspects of life-forms. Overcoming these challenges will require global multidisciplinary efforts across fields that do not normally interact with the clinical arena to make vast amounts of sequencing data clinically interpretable and actionable at the bedside.

Performance and Application of 16S rRNA Gene Cycle Sequencing for Routine Identification of Bacteria in the Clinical Microbiology Laboratory

Knowledge of species phylogeny is critical to many fields of biology. In an era of genome data availability, the most common way to make a phylogenetic species tree is by using multiple protein-coding genes, conserved in multiple species. This methodology is composed of several steps: orthology inference, multiple sequence alignment and inference of the phylogeny with dedicated tools. This can be a difficult task, and orthology inference, in particular, is usually computationally intensive and error prone if done ad hoc . This tutorial provides protocols to make use of OMA Orthologous Groups, a set of genes all orthologous to each other, to infer a phylogenetic species tree. It is designed to be user-friendly and computationally inexpensive, by providing two options: (1) Using only precomputed groups with species available on the OMA Browser, or (2) Computing orthologs using OMA Standalone for additional species, with the option of using precomputed orthology relations for those present in OMA. A protocol for downstream analyses is provided as well, including creating a supermatrix, tree inference, and visualization. All protocols use publicly available software, and we provide scripts and code snippets to facilitate data handling. The protocols are accompanied with practical examples.

Antoine Gürtler

Papers

Performance and Application of 16S rRNA Gene Cycle Sequencing for Routine Identification of Bacteria in the Clinical Microbiology Laboratory

How to build phylogenetic species trees with OMA