MIDI Sherlock DNA libraries
Others | 2008 | MIDIInstrumentation
Effective microbial identification underpins diverse fields from clinical diagnostics to environmental monitoring and industrial quality control. Curated DNA libraries targeting conserved ribosomal RNA regions enable rapid, reproducible classification of bacteria and fungi at high taxonomic resolution. The Sherlock DNA libraries version 2.10 represent a strategic resource for laboratories seeking streamlined, standardized sequencebased profiling of microbial communities.
This document describes three complementary DNA reference libraries released in June 2008 by MIDI Inc. Version 2.10 encompasses D16S2 (500 base pair bacterial 16S rRNA amplicon library), MD16S2 (full‐length bacterial 16S rRNA gene library), and FY28S2 (full‐length fungal and yeast 28S rRNA gene library). The primary aim is to deliver expanded taxonomic coverage and updated sequence entries to support accurate identification workflows.
The libraries were assembled through rigorous isolation of taxonomically verified strains and amplification of target rRNA regions using PCR with consensus primers. Sequencing employed Sanger chemistry to generate high-quality reads covering either the V3–V4 segment (D16S2) or entire 16S/28S genes (MD16S2, FY28S2). Curators performed multiple sequence alignments, manual quality checks, and integration of new taxa, resulting in version 2.10 updates across bacterial and fungal lineages.
Version 2.10 introduces dozens of new genera and species into each library, enriching representation of clinically relevant bacteria (for example Acinetobacter, Burkholderia, Streptococcus spp), environmental fungi (Aspergillus, Penicillium) and emerging pathogens. The D16S2 library balances read length with throughput demands, while MD16S2 and FY28S2 provide maximal phylogenetic resolution. Comprehensive lineages span Gram-positive and Gram-negative bacteria, filamentous fungi, yeasts, and Oomycetes.
Ongoing development will likely include expansion into archaeal and viral reference sequences, incorporation of high-throughput long-read data, and integration of whole‐genome markers. Machine learning algorithms trained on enriched rRNA datasets offer potential for accelerated, automated taxonomic assignment. Customizable libraries targeting functional genes may further advance microbiome research and industrial biotechnology.
The Sherlock DNA libraries version 2.10 deliver a comprehensive, expertly curated set of rRNA references for bacteria and fungi. By combining targeted amplicon and full-length gene resources, these libraries empower laboratories with flexible, high-confidence microbial identification tools. Continued updates and community feedback will drive further improvements in coverage and performance.
Software
IndustriesManufacturerMIDI
Summary
Significance of the Topic
Effective microbial identification underpins diverse fields from clinical diagnostics to environmental monitoring and industrial quality control. Curated DNA libraries targeting conserved ribosomal RNA regions enable rapid, reproducible classification of bacteria and fungi at high taxonomic resolution. The Sherlock DNA libraries version 2.10 represent a strategic resource for laboratories seeking streamlined, standardized sequencebased profiling of microbial communities.
Study Overview and Objectives
This document describes three complementary DNA reference libraries released in June 2008 by MIDI Inc. Version 2.10 encompasses D16S2 (500 base pair bacterial 16S rRNA amplicon library), MD16S2 (full‐length bacterial 16S rRNA gene library), and FY28S2 (full‐length fungal and yeast 28S rRNA gene library). The primary aim is to deliver expanded taxonomic coverage and updated sequence entries to support accurate identification workflows.
Methodology and Database Construction
The libraries were assembled through rigorous isolation of taxonomically verified strains and amplification of target rRNA regions using PCR with consensus primers. Sequencing employed Sanger chemistry to generate high-quality reads covering either the V3–V4 segment (D16S2) or entire 16S/28S genes (MD16S2, FY28S2). Curators performed multiple sequence alignments, manual quality checks, and integration of new taxa, resulting in version 2.10 updates across bacterial and fungal lineages.
Main Findings and Discussion
Version 2.10 introduces dozens of new genera and species into each library, enriching representation of clinically relevant bacteria (for example Acinetobacter, Burkholderia, Streptococcus spp), environmental fungi (Aspergillus, Penicillium) and emerging pathogens. The D16S2 library balances read length with throughput demands, while MD16S2 and FY28S2 provide maximal phylogenetic resolution. Comprehensive lineages span Gram-positive and Gram-negative bacteria, filamentous fungi, yeasts, and Oomycetes.
Benefits and Practical Applications
- Rapid identification of bacteria and fungi in clinical, food safety, and environmental samples
- Standardized datasets that integrate seamlessly with common analysis pipelines and commercial instrumentation
- Enhanced species-level resolution for complex microbiomes through complementary short- and full-length rRNA approaches
- Support for quality assurance and regulatory testing with validated taxonomic entries
Future Trends and Opportunities
Ongoing development will likely include expansion into archaeal and viral reference sequences, incorporation of high-throughput long-read data, and integration of whole‐genome markers. Machine learning algorithms trained on enriched rRNA datasets offer potential for accelerated, automated taxonomic assignment. Customizable libraries targeting functional genes may further advance microbiome research and industrial biotechnology.
Conclusion
The Sherlock DNA libraries version 2.10 deliver a comprehensive, expertly curated set of rRNA references for bacteria and fungi. By combining targeted amplicon and full-length gene resources, these libraries empower laboratories with flexible, high-confidence microbial identification tools. Continued updates and community feedback will drive further improvements in coverage and performance.
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