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ATCC Corporate Workshop

Association of Molecular Pathology (AMP) Annual Meeting

11/16/2017 — 11/18/2017

The complexities involved in 16S rRNA and shotgun metagenomic analysis methods pose significant challenges for microbiome research and frequently result in the introduction of biases. One of the primary obstacles in assay standardization is the limited availability of reference materials and robust analytical tools. To support this need, ATCC has developed mock microbial communities from fully sequenced and characterized ATCC strains, selected based on their phenotypic and genotypic attributes or relevance in disease-specific research. These mock communities mimic mixed metagenomics samples and offer a universal control for microbiome analyses and assay development.

Abstract: Advancement and accessibility of next-generation sequencing technologies have influenced microbiome analyses in tremendous ways, opening up applications in the areas of clinical, diagnostic, therapeutic, industrial, and environmental research. However, due to the complexity of 16S rRNA and metagenomic sequencing analysis, significant challenges can be posed by biases introduced during sample preparation, DNA extraction, PCR amplification, library preparation, sequencing, or data interpretation. One of the primary challenges in assay standardization is the limited availability of reference materials. To address these biases and provide a measure of standardization within microbiome research and applications, ATCC has developed a set of mock microbial communities comprising fully sequenced, characterized strains selected on the basis of phenotypic and genotypic attributes, such as cell wall type (Gram stain classification), GC content, genome size, unique cell wall characteristics, and spore formation. These mock communities mimic mixed metagenomic samples and offer a universal control for microbiome analyses and assay development. Moreover, these standards have been developed with different levels of mock community complexity (10 or 20 strains per community) with even or staggered relative abundance, including diverse strains that are relevant to a broad range of applications. In addition, to minimize the bias associated with data interpretation, we have developed a data analysis module in collaboration with One Codex. This module provides a user-friendly output in the form of true-positive, relative abundance, and false-negative scores for 16S rRNA community profiling and shotgun metagenomic sequencing.

Abstract: Metagenomics provides an opportunity to understand the microbial population present in a given environment. The development of high-throughput sequencing has made the study of microbiomes increasingly possible. However, with recent increased activity in metagenomics research, there is need for reference materials that enable data accuracy and quality to be assessed. Control materials could enable performance evaluation of sample processing, library preparation, sequencing methods, and data analysis, thus aiding in the comparison of different studies.

Abstract: Molecular tests are becoming more widely used in clinical care, especially in screening, diagnosing, and monitoring certain cancers. By detecting biomarkers relevant for personalized treatment, molecular diagnostics are increasingly relied upon to direct appropriate therapies for individual patients. To ensure the reliability and reproducibility of oncology molecular diagnostic test results, controls with known mutational allelic frequency and gene copy number variation are required. The development of standardized genomic DNA products that have been purified from characterized authenticated cell lines and contain quantified molecular genetic markers provide a reliable and sustainable alternative to variable patient tissue derived controls.

Abstract: The emergence and spread of antibacterial resistance among Gram-negative bacteria has become a global challenge for health care. Multiple programs have been implemented to reduce exposure and spread, but new therapeutics are necessary to combat these challenges. For the discovery and development of novel therapeutic agents to become a reality, multidrug-resistant (MDR) clinical isolates that represent current disease strains from around the globe are required. To support this effort, ATCC has collected and characterized 33 Gram-negative isolates using standard and new technologies.

Abstract: According to the World Health Organization, antimicrobial resistance (AMR) among Gram-negative bacteria continues to increase on a global scale. It is estimated that more than 23,000 people in the U.S. alone die each year from infections with multidrug-resistant (MDR) bacteria. New therapeutic agents are critical to stem this trend, but new technologies are required for shortening the time from discovery to production. To support this effort, ATCC has developed a collection of 33 fully characterized Gram-negative isolates representing current MDR disease strains from around the globe. Strains were evaluated using whole genome sequencing (WGS) and a novel annotation program to identify AMR genes and protein targets. Using public databases, ATCC developed and validated an accurate and efficient bioinformatics pipeline for the automated assembly and annotation of microbial genomes. Next-generation sequencing (NGS) data from all 33 individual isolates in combination with the novel bioinformatics pipeline were used to identify AMR genes and predictive targets that could be associated with the observed phenotype. Using our proprietary bioinformatics pipeline, we created a searchable database of AMR determinants containing the WGS information as well as a list of known AMR genes with their corresponding nucleotide sequences.

Abstract: The complexities involved in 16S rRNA-based and metagenomics analysis methods pose significant challenges for standardization as bias can be introduced during DNA extraction, amplification, library preparation, sequencing, and bioinformatics analysis. One of the primary challenges in assay standardization is the limited availability of reference materials. To address this issue, we evaluated the use of two mock microbial communities in the form of lyophilized, whole-cell standards as full-process controls.

Abstract: A shortcoming in microbiome research is the lack of reference standards to control biases introduced by differential DNA extractability, interference with amplification, library preparation, next-generation sequencing platforms, and data analysis. The aim of this research is to develop and test novel molecular barcodes for use as spike-in reference standards in the form of oligonucleotides or recombinants in microbiome studies.

Abstract: Complexities involved in 16S rRNA and shotgun metagenomic analysis methods pose significant challenges in microbiome research as various biases can be introduced during PCR amplification, library preparation, sequencing, and analysis. One of the primary obstacles in assay standardization is the limited availability of reference materials. To support this need, we developed microbiome reference standards from fully sequenced and characterized ATCC® strains and evaluated their use in a proof-of-concept study. Here, four standards were created comprising mixtures of 10 or 20 genomic DNAs in equal or staggered quantities prepared from a diverse set of bacteria that were selected based on relevant attributes such as Gram stain, genome size, GC content, and other special characteristics. Initially, we performed an inter-laboratory comparison of the 16S rRNA V4 region from three different commercial laboratories. Analysis of the resulting sequencing data using One Codex revealed variability in the number of true positives and false positives as well as the relative abundances. A subsequent comparison of three different regions of the 16S rRNA gene—V1V2 (27f-YM+3 338R), V3V4 (341F & 806R), and V4 (515F & 806R)—revealed that only the analysis of the V1/V2 region using One Codex was able to profile the bacteria to the species level. Following this analysis, we evaluated a shotgun metagenomics approach and compared it to the 16S rRNA V1/V2 results. Here, the shotgun metagenomics approach showed a high correlation between the expected vs. observed ratios as compared to the 16S rRNA results, which had variable correlation for three standards with equal and staggered ratios. These results demonstrate that 16S rRNA community profiling of the V1V2 region and the shotgun metagenomic approach could identify bacterial strains to the species level, with the latter method generating relative abundances statistically close to the expected. Taken together, this proof-of-concept study demonstrates the potential use of ATCC® Microbiome Standards in the identification of potential biases and methodology drawbacks associated with microbiome studies.

Abstract: Complex behavior within eukaryotic cells manifest from layered regulatory networks changing the transcription of many genes. To systematically study these pathways by modulating individual components—or in the case of synthetic biology, building new network architectures by creating DNA circuit—it is critical to control multiple genes simultaneously under tightly regulated or inducible expression. In the case of network construction in Saccharomyces cerevisiae, there has been a lack of both suitable, well-characterized parts (promoters and regulators) as well as a standardized platform for DNA assembly and delivery of gene circuits. Here, we present a framework for building gene circuits as well as a set of fully characterized DNA parts for use in Saccharomyces cerevisiae. The entire procedure of building a gene circuit from more than 10 basic parts took less than 5 days with only a workload of 1-3 hours per day. A diverse promoter collection comprising five different types was generated: constitutive, yeast native inducible, synthetic inducible, synthetic promoters regulated by activators, and synthetic promoters regulated by repressors. Altogether, the range of promoters span 2-fold to 105-fold expression above the background, the new inducible systems allow 11-fold change in expression, and the activators/repressors show a maximum 35-fold and 45-fold change of expression. This study demonstrates the feasibility for the quick and easy construction of gene circuits for delivery into S. cerevisiae and the utility of a fully characterized set of diverse promoters, activators, and repressors. This assembly system combined with DNA parts will be useful for constructing large-scale gene circuit libraries with reliable gene expression and for designing logic operations for a complex network in S. cerevisiae. Moreover, we anticipate that our system will allow for the controlled study of multi-step pathways by enabling manipulation of single protein expression.