Table of contents

Volume 6, Issue 3, pp. 142 - 183, March 2019

Issue cover
Cover: Close-up of what is referred to as a string test (KOH test), which was being performed on a droplet of sample that was harvested from a Petri dish growing suspected colonies of Vibrio cholerae bacteria. Note the mucoid string still clinging to the wire inoculating loop, indicating a positive string test result (image by Centers for Disease Control and Prevention, USA; Public Health Image Library, image ID #3909); image modified by MIC. The cover is published under the Creative Commons Attribution (CC BY) license. Enlarge issue cover


Microevolution of the pathogenic yeasts Candida albicans and Candida glabrata during antifungal therapy and host infection

Pedro Pais, Mónica Galocha, Romeu Viana, Mafalda Cavalheiro, Diana Pereira, Miguel Cacho Teixeira

page 142-159 | 10.15698/mic2019.03.670 | Full text | PDF | Abstract

Infections by the pathogenic yeasts Candida albicans and Candida glabrata are among the most common fungal diseases. The success of these species as human pathogens is contingent on their ability to resist antifungal therapy and thrive within the human host. C. glabrata is especially resilient to azole antifungal treatment, while C. albicans is best known for its wide array of virulence features. The core mechanisms that underlie antifungal resistance and virulence in these pathogens has been continuously addressed, but the investigation on how such mechanisms evolve according to each environment is scarcer. This review aims to explore current knowledge on microevolution experiments to several treatment and host-associated conditions in C. albicans and C. glabrata. The analysis of adaptation strategies that evolve over time will allow to better understand the mechanisms by which Candida species are able to achieve stable phenotypes in real-life scenarios, which are the ones that should constitute the most interesting drug targets.

Research Articles

Genome-wide analysis of yeast expression data based on a priori generated co-regulation cliques

Siyuan Sima, Lukas Schmauder and Klaus Richter

page 160-176 | 10.15698/mic2019.03.671 | Full text | PDF | Abstract

DNA microarrays are highly sensitive tools to evaluate the gene expression status of organismic samples and standardized array formats exist for many different sample types. Differential expression studies usually utilize the strongest up- or downregulated genes to generate networks visualizing the relationships among these genes. To include all yeast genes in one analysis and to get broader information on all cellular responses, we test a priori input of predefined genome-wide expression cliques and subsequent statistical analysis of the expression data. To this end, we generate a set of 72 co-regulation cliques using the information from 3196 microarray experiments. The obtained cliques performed highly significant in gene ontology and transcription factor enrichment analyses. We then tested the clique set on individual microarray experiments reporting on responses to pheromone, glycerol versus glucose based growth and the cellular response to heat. In all cases a highly significant determination of affected expression cliques was possible based on their average expression differences, the positions of their genes within hit rankings (UpRegScore) or the enrichment of the Top200 hits in certain cliques. The 72 cliques were finally used to compare experiments, which reported on the transcriptional response to polyglutamine proteins of different lengths. Using the predefined clique set it is possible to identify with high sensitivity and good significance sample and condition specific changes to gene expression. We thus conclude that an analysis, starting with these 72 preformed expression cliques, can complement traditional microarray analyses by visualizing the entire response on a static genome-wide gene set.

Research Reports

Simultaneous profiling of sexually transmitted bacterial pathogens, microbiome, and concordant host response in cervical samples using whole transcriptome sequencing analysis

Catherine M. O'Connell, Hayden Brochu, Jenna Girardi, Erin Harrell, Aiden Jones, Toni Darville, Arlene C. Seña and Xinxia Peng

page 177-183 | 10.15698/mic2019.03.672 | Full text | PDF | Abstract

Pelvic inflammatory disease (PID) is a female upper genital tract inflammatory disorder that arises after sexually transmitted bacterial infections (STI). Factors modulating risk for reproductive sequelae include co-infection, microbiota, host genetics and physiology. In a pilot study of cervical samples obtained from women at high risk for STIs, we examined the potential for unbiased characterization of host, pathogen and microbiome interactions using whole transcriptome sequencing analysis of ribosomal RNA-depleted total RNAs (Total RNA-Seq). Only samples from women with STI infection contained pathogen-specific sequences (3 to 38% transcriptome coverage). Simultaneously, we identified and quantified their active microbial communities. After integration with host-derived reads from the same data, we detected clustering of host transcriptional profiles that reflected microbiome differences and STI infection. Together, our study suggests that total RNA profiling will advance understanding of the interplay of pathogen, host and microbiota during natural infection and may reveal novel, outcome-relevant biomarkers.

By continuing to use the site, you agree to the use of cookies. more information

The cookie settings on this website are set to "allow cookies" to give you the best browsing experience possible. If you continue to use this website without changing your cookie settings or you click "Accept" below then you are consenting to this. Please refer to our "privacy statement" and our "terms of use" for further information.