Development and applications of a CRISPR activation system for facile genetic overexpression in Candida albicans.

For the fungal pathogen Candida albicans, genetic overexpression readily occurs via a diversity of genomic alterations, such as aneuploidy and gain-of-function mutations, with important consequences for host adaptation, virulence, and evolution of antifungal drug resistance. Given the important role of overexpression on C. albicans biology, it is critical to develop and harness tools that enable the analysis of genes expressed at high levels in the fungal cell. Here, we describe the development, optimization, and application of a novel, single-plasmid-based CRISPR activation (CRISPRa) platform for targeted genetic overexpression in C. albicans, which employs a guide RNA to target an activator complex to the promoter region of a gene of interest, thus driving transcriptional expression of that gene. Using this system, we demonstrate the ability of CRISPRa to drive high levels of gene expression in C. albicans, and we assess optimal guide RNA targeting for robust and constitutive overexpression. We further demonstrate the specificity of the system via RNA sequencing. We highlight the application of CRISPR activation to overexpress genes involved in pathogenesis and drug susceptibility, and contribute toward the identification of novel phenotypes. Consequently, this tool will facilitate a broad range of applications for the study of C. albicans genetic overexpression.

Association between SNPs in Leptin Pathway Genes and Anthropometric, Biochemical, and Dietary Markers Related to Obesity.

Obesity is one of the main public health problems in Mexico and the world and one from which a large number of pathologies derive. Single nucleotide polymorphisms (SNPs) of various genes have been studied and proven to contribute to the development of multiple diseases. SNPs of the leptin pathway have been associated with the control of hunger and energy expenditure as well as with obesity and type 2 diabetes mellitus. Therefore, the present work focused on determining the association between anthropometric markers and biochemical and dietary factors related to obesity and SNPs of leptin pathway genes, such as the leptin gene (LEP), the leptin receptor (LEPR), proopiomelanocortin (POMC), prohormone convertase 1 (PCSK1), and the melanocortin 4 receptor (MC4R). A population of 574 young Mexican adults of both sexes, aged 19 years old on average and without metabolic disorders previously diagnosed, underwent a complete medical and nutritional evaluation, biochemical determination, and DNA extraction from the blood; DNA samples were subsequently genotyped. Association analyses between anthropometric, biochemical, and dietary variables with SNPs were performed using binary logistic regressions (p-value = 0.05). Although the sampled population did not have previously diagnosed diseases, the evaluation results showed that 33% were overweight or obese according to BMI and 64% had non-clinically elevated levels of body fat. From the 74 SNP markers analyzed from the five previously mentioned genes, 62 showed polymorphisms within the sampled population, and only 35 of these had significant associations with clinical variables. The risk associations (OR > 1) occurred between clinical markers with elevated values for waist circumference, waist−height index, BMI, body fat percentage, glucose levels, insulin levels, HOMA-IR, triglyceride levels, cholesterol levels, LDL-c, low HDL-c, carbohydrate intake, and protein intake and SNPs of the LEP, LEPR, PCSK1, and MC4R genes. On the other hand, the protective associations (OR < 1) were associated with markers including elevated values for insulin, HOMA-IR, cholesterol, c-LDL, energy intake > 2440 Kcal/day, and lipid intake and SNPs of the LEP and LEPR genes and POMC. The present study describes associations between SNPs in leptin pathway genes, revealing positive and negative interactions between reported SNPs and the clinical markers related to obesity in a sampled Mexican population. Hence, our results open the door for the further study of new genetic variants and their influence on obesity.