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In this study, we used CRISPR/Cas9 genome-editing technology to generate a drug resistant MEK1Q56P mutation within the A375 melanoma cell line which naturally harbors the BRAFV600E mutation. We validated this new isogenic cell model using both molecular and biofunctional approaches. Drug responses to BRAF- and MEK1-specific inhibitors and non-specific chemotherapy drugs were compared between the A375 MEK1Q56P cell line and the parental cell line in 2D and 3D culture environments. Results demonstrated that the isogenic MEK1Q56P cell line showed significant and specific resistance to BRAF inhibitors in comparison to the A375 line. This new approach to cell line development provides direct, in vitro, bio-functional evidence of a drug-resistant gene that drives tumor cell survival under targeted anti-cancer treatments. Furthermore, the A375 MEK1Q56P cell line represents a new type of drug resistance model that contains a defined genetic resistance mechanism.

Mutations in Isocitrate dehydrogenase (IDH) have been linked to human cancers such as glioma and acute myeloid leukemia (AML). We sought to use CRISPR/Cas9 gene-editing technology to create two in vitro disease models that harbor either the IDH1 or IDH2 mutations. An IDH1R132H mutation was introduced in the U-87 MG cell line, and an IDH2R140Q mutation was introduced in the TF-1 cell line. The IDH1R132H mutant U-87 MG Isogenic Cell Line showed an increase in D-2HG and elevated level of histone methylation. In the IDH2R140Q mutant TF-1 Isogenic Cell Line, an increase in D-2HG was also observed. In response to IDH2-specific inhibitors, we demonstrated that IDH2R140Q TF-1 cells exhibited decreases in both D-2HG and histone methylation levels. These data demonstrate that isogenic in vitro models are valuable tools for elucidating mechanisms involved in tumorigenesis and use in screening anti-cancer compounds for drug discovery.

Human induced pluripotent stem cells (iPSC)-derived neural progenitor cells (NPCs) and neurons are an attractive in vitro model to study neurological development and neurotoxicity and to model diseases. We investigated the expression of genes associated with the differentiation of NPCs during three weeks in dopaminergic differentiation media. To validate that our NPCs and dopaminergic neuron differentiation media are suitable for drug screening, we conducted neurotoxicity screenings in three types of NPCs and NPCs-derived neurons using Reliablue™ cell viability reagent assay and high content imaging analysis. This study demonstrates that ATCC NPCs and dopaminergic differentiation media are suitable for studying neurological development and neurotoxicity screening.

Kidney transporter cell models using well-characterized hTERT-immortalized primary renal proximal tubule epithelial cells (RPTEC) that stably overexpress either the OAT1, OCT2, or OAT3 gene were generated. We verified that the overexpressed transporters have normal transport activities using 6-CF and EAM-1 uptake assays in a high throughput format. Uptake of these compounds is blocked in a dose dependent manner by well-known SLC inhibitors, indicating that the overexpressed kidney transporters functioned as expected. These data demonstrate that modified RPTEC maintain kidney transporter expression over time, and provide physiologically relevant, highly sensitive models of human kidney transporter functions.

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: 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: 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: 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 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: 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.