Diverse mechanisms control amino acid-dependent environmental alkalization by Candida albicans

Candida albicans has the capacity to neutralize acidic growth environments by releasing ammonia derived from the catabolism of amino acids. The molecular components underlying alkalization and its physiological significance remain poorly understood. Here, we present an integrative model with the cytosolic NAD+-dependent glutamate dehydrogenase (Gdh2) as the principal ammonia-generating component. We show that alkalization is dependent on the SPS-sensor-regulated transcription factor STP2 and the proline-responsive activator Put3. These factors function in parallel to derepress GDH2 and the two proline catabolic enzymes PUT1 and PUT2. Consistently, a double mutant lacking STP2 and PUT3 exhibits a severe alkalization defect that nearly phenocopies that of a gdh2-/- strain. Alkalization is dependent on mitochondrial activity and in wild-type cells occurs as long as the conditions permit respiratory growth. Strikingly, Gdh2 levels decrease and cells transiently extrude glutamate as the environment becomes more alkaline. Together, these processes constitute a rudimentary regulatory system that counters and limits the negative effects associated with ammonia generation. These findings align with Gdh2 being dispensable for virulence, and based on a whole human blood virulence assay, the same is true for C. glabrata and C. auris. Using a transwell co-culture system, we observed that the growth and proliferation of Lactobacillus crispatus, a common component of the acidic vaginal microenvironment and a potent antagonist of C. albicans, is unaffected by fungal-induced alkalization. Consequently, although Candida spp. can alkalinize their growth environments, other fungal-associated processes are more critical in promoting dysbiosis and virulent fungal growth.

A combined molecular approach utilizing microbial DNA and microRNAs in a qPCR multiplex for the classification of five forensically relevant body fluids

Body fluid identification is an essential step in the forensic biology workflow that can assist DNA analysts in determining where to collect DNA evidence. Current presumptive tests lack the specificity that molecular techniques can achieve; therefore, molecular methods, including microRNA (miRNA) and microbial signature characterization, have been extensively researched in the forensic community. Limitations of each method suggest combining molecular markers to increase the discrimination efficiency of multiple body fluids from a single assay. While microbial signatures have been successful in identifying fluids with high bacterial abundances, microRNAs have shown promise in fluids with low microbial abundance (blood and semen). This project synergized the benefits of microRNAs and microbial DNA to identify multiple body fluids using DNA extracts. A reverse transcription (RT)-qPCR duplex targeting miR-891a and let-7g was validated, and miR-891a differential expression was significantly different between blood and semen. The miRNA duplex was incorporated into a previously reported qPCR multiplex targeting 16S rRNA genes of Lactobacillus crispatus, Bacteroides uniformis, and Streptococcus salivarius to presumptively identify vaginal/menstrual secretions, feces, and saliva, respectively. The combined classification regression tree model resulted in the presumptive classification of five body fluids with 94.6% overall accuracy, now including blood and semen identification. These results provide proof of concept that microRNAs and microbial DNA can classify multiple body fluids simultaneously at the quantification step of the current forensic DNA workflow.

Design and optimization of a 16S microbial qPCR multiplex for the presumptive identification of feces, saliva, vaginal and menstrual secretions

Molecular methods for body fluid identification have been extensively researched in the forensic community over the last decade, mostly focusing on RNA‐based methods. Microbial DNA analysis has long been used for forensic applications, such as postmortem interval estimations, but only recently has it been applied to body fluid identification. High‐throughput sequencing of the 16S ribosomal RNA gene by previous research groups revealed that microbial signatures and abundances vary across human body fluids at the genus and/or species taxonomic level. Since quantitative PCR is still the current technique used in forensic DNA analysis, the purpose of this study was to design a qPCR multiplex targeting the 16S gene of Bacteroides uniformis, Streptococcus salivarius, and Lactobacillus crispatus that can distinguish between feces, saliva, and vaginal/menstrual secretions, respectively. Primers and probes were designed at the species level because these bacteria are highly abundant within their respective fluid. The validated 16S triplex was evaluated in DNA extracts from thirty donors of each body fluid. A classification regression tree model resulted in 96.5% classification accuracy of the population data, which demonstrates the ability of this 16S triplex to presumptively identify these fluids with high confidence at the quantification step of the forensic workflow using minimal input volume of DNA extracted from evidentiary samples.