<i>Cryptococcus neoformans</i>
            α Strains Preferentially Disseminate to the Central Nervous System during Coinfection

Nielsen, Kirsten; Cox, Gary M.; Litvintseva, Anastasia P.; Mylonakis, Eleftherios; Malliaris, Stephanie D.; Benjamin, Daniel K.; Giles, Steven S.; Mitchell, Thomas G.; Casadevall, Arturo; Perfect, John R.; Heitman, Joseph

doi:10.1128/iai.73.8.4922-4933.2005

Cited by 132 publications

(132 citation statements)

References 81 publications

(75 reference statements)

Supporting

Mentioning

117

Contrasting

Unclassified

Order By: Relevance

“…grubii strain KN99a was equivalent to KN99a in virulence. However, KN99a cells more readily penetrate the blood-brain barrier than KN99a cells during co-infection (Nielsen et al 2005). Thus, differences in virulence potential between a and a strains in var.…”

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Interaction Between Genetic Background and the Mating-Type Locus in Cryptococcus neoformans Virulence Potential

Nielsen

Marra²,

Hagen

et al. 2005

Genetics

Self Cite

View full text Add to dashboard Cite

The study of quantitative traits provides a window on the interactions between multiple unlinked genetic loci. The interaction between hosts and pathogenic microbes, such as fungi, involves aspects of quantitative genetics for both partners in this dynamic equilibrium. One important pathogenic fungus is Cryptococcus neoformans, a basidiomycete yeast that can infect the human brain and whose mating system has two mating type alleles, a and a. The a mating-type allele has previously been linked to increased virulence potential. Here congenic C. neoformans strains were generated in the two well-characterized genetic backgrounds B3501a and NIH433a to examine the potential influence of genes outside of the mating-type locus on the virulence potential of mating type. The congenic nature of these new strain pairs was established by karyotyping, amplified fragment length polymorphism genotyping, and whole-genome molecular allele mapping (congenicity mapping). Virulence studies revealed that virulence was equivalent between the B3501 a and a congenic strains but the a strain was more virulent than its a counterpart in the NIH433 genetic background. These results demonstrate that genomic regions outside the mating type locus contribute to differences in virulence between a and a cells. The congenic strains described here provide a foundation upon which to elucidate at genetic and molecular levels how mating-type and other unlinked loci interact to enable microbial pathogenesis.

show abstract

Section: Discussionmentioning

confidence: 99%

“…However, following co-infection with the var. grubii congenic strains, the a strain more efficiently colonized the central nervous system than the a mating-type strain and provided evidence for a contribution of the MAT locus at least during co-infection (Nielsen et al 2005).…”

mentioning

confidence: 95%

Interaction Between Genetic Background and the Mating-Type Locus in Cryptococcus neoformans Virulence Potential

Nielsen

Marra²,

Hagen

et al. 2005

Genetics

Self Cite

View full text Add to dashboard Cite

show abstract

“…It has been reported that MATα is more virulent than the opposite type MATa 29 . Moreover, in coinfection with both mating types, the MATα strains more likely disseminate to the central nervous system which might explain the prevalence among the clinical isolates 40 .…”

Section: Discussionmentioning

confidence: 99%

Genotyping, serotyping and determination of mating-type of Cryptococcus neoformans clinical isolates from São Paulo State, Brazil

Matsumoto

Fusco‐Almeida

Baeza

et al. 2007

Rev. Inst. Med. trop. S. Paulo

View full text Add to dashboard Cite

SUMMARYThe basidiomycetous yeast Cryptococcus neoformans is an important fungal pathogen mainly in immunocompromised patients. In this study, 47 clinical isolates of C. neoformans from regions of São Paulo State were studied serologically by using the Crypto Check Iatron RM 304-K kit, their genetic diversity was estimated by PCR-fingerprinting with a microsatellite-specific sequence (GACA) 4 , RAPD with primer 6 (Amersham Pharmacia Biotech), PCR-restriction fragment length polymorphism (RFLP) analysis of the phospholipase B gene (PLB1) digested with AvaI and mating type analysis by PCR. All 47 strains isolated from HIV positive patients included in this study were serotype A and MATα. The majority of the isolates (45/47) were VNI and only two were VNII by PCR-fingerprinting and PCR-RFLP analysis. High degree of homogeneity was observed when (GACA) 4 was used, being highly correlated (> 0.9). In contrast, the RAPD analysis was more heterogeneous with higher number of molecular profiles. By PCR-RFLP, no new molecular type was found, enhancing the suggestion that the differences based on conserved gene as PLB1, can be resultant of ongoing divergent evolution within the C. neoformans complex, into the current eight subtypes. Our results furnish new information on the molecular epidemiology of C. neoformans in the southeast region of Brazil.

show abstract

“…Strains were made in C. neoformans KN99α (Nielsen et al 2005) with standard growth at 30°C in yeast peptone dextrose (YPD) medium. For capsule induction, an overnight culture in YPD was washed, resuspended in DMEM, and grown at 37°C in 5% CO 2 .…”

Section: Materials Strains and Cell Growthmentioning

confidence: 99%

Model-driven mapping of transcriptional networks reveals the circuitry and dynamics of virulence regulation

et al. 2015

View full text Add to dashboard Cite

Key steps in understanding a biological process include identifying genes that are involved and determining how they are regulated. We developed a novel method for identifying transcription factors (TFs) involved in a specific process and used it to map regulation of the key virulence factor of a deadly fungus-its capsule. The map, built from expression profiles of 41 TF mutants, includes 20 TFs not previously known to regulate virulence attributes. It also reveals a hierarchy comprising executive, midlevel, and "foreman" TFs. When grouped by temporal expression pattern, these TFs explain much of the transcriptional dynamics of capsule induction. Phenotypic analysis of TF deletion mutants revealed complex relationships among virulence factors and virulence in mice. These resources and analyses provide the first integrated, systems-level view of capsule regulation and biosynthesis. Our methods dramatically improve the efficiency with which transcriptional networks can be analyzed, making genomic approaches accessible to laboratories focused on specific physiological processes.[Supplemental material is available for this article.]In this paper we present an efficient means of comprehensively mapping the network of transcription factors (TFs) that regulate a particular physiological process. Our approach cycles through deletion of TFs, expression profiling of TF mutants, model construction, and model-directed selection of TFs for the next round of deletion. This predictive genetics approach identifies TFs that affect the process of interest, providing a valuable complement to undirected mutagenesis and screening. Simultaneously, it builds a network model that explains how the TFs affect the process, yielding novel insights into the biological system under study.Mapping the network that regulates a specific process requires knowing which TFs affect that process. One way to identify such TFs is to screen comprehensive mutant libraries, but generating such libraries is not always feasible. Furthermore, genome-scale screening assays must be fast and scalable; such assays may not exist for the process of interest or may be less sensitive than other, more laborious assays. An alternative approach is to map the targets of all TFs encoded in a genome by using methods such as chromatin-immunoprecipitation (ChIP) or large-scale TF deletion and expression analysis. However, undirected, genome-wide approaches are costly and inefficient for probing a specific biological process in detail. We report a model-guided approach that addresses all of these problems by focusing experimental effort on the TFs most likely to be involved in the process of interest. Furthermore, our approach generates a network that provides mechanistic explanations for the phenotypes of TF deletion mutants.Our approach alternates network building by using an algorithm we call NetProphet with identifying relevant TFs by using an algorithm we call PhenoProphet. NetProphet is a validated method for mapping direct, functional regulation that significantly out...

show abstract

Cryptococcus neoformans α Strains Preferentially Disseminate to the Central Nervous System during Coinfection

Cited by 132 publications

References 81 publications

Interaction Between Genetic Background and the Mating-Type Locus in Cryptococcus neoformans Virulence Potential

Interaction Between Genetic Background and the Mating-Type Locus in Cryptococcus neoformans Virulence Potential

Genotyping, serotyping and determination of mating-type of Cryptococcus neoformans clinical isolates from São Paulo State, Brazil

Model-driven mapping of transcriptional networks reveals the circuitry and dynamics of virulence regulation

Contact Info

Product

Resources

About