Human saliva is clinically informative of both oral and general health. Since next generation shotgun sequencing (NGS) is now widely used to identify and quantify bacteria, we investigated the bacterial flora of saliva microbiomes of two healthy volunteers and five datasets from the Human Microbiome Project, along with a control dataset containing short NGS reads from bacterial species representative of the bacterial flora of human saliva. GENIUS, a system designed to identify and quantify bacterial species using unassembled short NGS reads was used to identify the bacterial species comprising the microbiomes of the saliva samples and datasets. Results, achieved within minutes and at greater than 90% accuracy, showed more than 175 bacterial species comprised the bacterial flora of human saliva, including bacteria known to be commensal human flora but also Haemophilus influenzae, Neisseria meningitidis, Streptococcus pneumoniae, and Gamma proteobacteria. Basic Local Alignment Search Tool (BLASTn) analysis in parallel, reported ca. five times more species than those actually comprising the in silico sample. Both GENIUSand BLAST analyses of saliva samples identified major genera comprising the bacterial flora of saliva, but GENIUS provided a more precise description of species composition, identifying to strain in most cases and delivered results at least 10,000 times faster. Therefore, GENIUS offers a facile and accurate system for identification and quantification of bacterial species and/or strains in metagenomic samples.
Sequencing short tandem repeat (STR) loci allows for determination of repeat motif variations within the STR (or entire PCR amplicon) which cannot be ascertained by size-based PCR fragment analysis. Sanger sequencing has been used in research laboratories to further characterize STR loci, but is impractical for routine forensic use due to the laborious nature of the procedure in general and additional steps required to separate heterozygous alleles. Recent advances in library preparation methods enable high-throughput next generation sequencing (NGS) and technological improvements in sequencing chemistries now offer sufficient read lengths to encompass STR alleles. Herein, we present sequencing results from 183 DNA samples, including African American, Caucasian, and Hispanic individuals, at 22 autosomal forensic STR loci using an assay designed for NGS. The resulting dataset has been used to perform population genetic analyses of allelic diversity by length compared to sequence, and exemplifies which loci are likely to achieve the greatest gains in discrimination via sequencing. Within this data set, six loci demonstrate greater than double the number of alleles obtained by sequence compared to the number of alleles obtained by length: D12S391, D2S1338, D21S11, D8S1179, vWA, and D3S1358. As expected, repeat region sequences which had not previously been reported in forensic literature were identified.
For transcription to initiate, RNA polymerase must recognize and melt promoters. Selective binding to the nontemplate strand of the -10 region of the promoter is central to this process. We show that a 48 amino acid (aa) coiled-coil from the beta' subunit (aa 262--309) induces sigma(70) to perform this function almost as efficiently as core RNA polymerase itself. We provide evidence that interaction between the beta' coiled-coil and region 2.2 of sigma(70) promotes an allosteric transition that allows sigma(70) to selectively recognize the nontemplate strand. As the beta' 262--309 peptide can function with the previously crystallized portion of sigma(70), nontemplate recognition can be reconstituted with only 47 kDa, or 1/10 of holoenzyme.
The development of molecular tools to detect and report mitochondrial DNA (mtDNA) heteroplasmy will increase the discrimination potential of the testing method when applied to forensic cases. The inherent limitations of the current state-of-the-art, Sanger-based sequencing, including constrictions in speed, throughput, and resolution, have hindered progress in this area. With the advent of next-generation sequencing (NGS) approaches, it is now possible to clearly identify heteroplasmic variants, and at a much lower level than previously possible. However, in order to bring these approaches into forensic laboratories and subsequently as accepted scientific information in a court of law, validated methods will be required to produce and analyze NGS data. We report here on the development of an optimized approach to NGS analysis for the mtDNA genome (mtgenome) using the Illumina MiSeq instrument. This optimized protocol allows for the production of more than 5 gigabases of mtDNA sequence per run, sufficient for detection and reliable reporting of minor heteroplasmic variants down to approximately 0.5–1.0% when multiplexing twelve samples. Depending on sample throughput needs, sequence coverage rates can be set at various levels, but were optimized here for at least 5,000 reads. In addition, analysis parameters are provided for a commercially available software package that identify the highest quality sequencing reads and effectively filter out sequencing-based noise. With this method it will be possible to measure the rates of low-level heteroplasmy across the mtgenome, evaluate the transmission of heteroplasmy between the generations of maternal lineages, and assess the drift of variant sequences between different tissue types within an individual.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.