search.noResults

search.searching

saml.title
dataCollection.invalidEmail
note.createNoteMessage

search.noResults

search.searching

orderForm.title

orderForm.productCode
orderForm.description
orderForm.quantity
orderForm.itemPrice
orderForm.price
orderForm.totalPrice
orderForm.deliveryDetails.billingAddress
orderForm.deliveryDetails.deliveryAddress
orderForm.noItems
LITERATURE UPDATE Collectively, these findings show that


C. auris uses metabolic regulation to eliminate macrophages while remaining immunologically silent to ensure its own survival. Thus, these data suggest that host and pathogen metabolism could represent therapeutic targets for C. auris infections.


Candida auris-macrophage cellular interactions and transcriptional response Miramón P, Pountain AW, Lorenz MC. Infect Immun. 2023 Nov 16; 91 (11): e0027423. doi: 10.1128/iai.00274-23.


The pathogenic yeast Candida auris represents a global threat of the utmost clinical relevance. This emerging fungal species is remarkable in its resistance to commonly used antifungal agents and its persistence in the nosocomial setting. The innate immune system is one the first lines of defence preventing the dissemination of pathogens in the host. C. auris is susceptible to circulating phagocytes, and understanding the molecular details of these interactions may suggest routes to improved therapies.


In this work, the authors examined the interactions of this yeast with macrophages. They found that macrophages avidly phagocytose C. auris; however, intracellular replication is not inhibited, indicating that C. auris resists the killing mechanisms imposed by the phagocyte. Unlike Candida albicans, phagocytosis of C. auris does not induce macrophage lysis. The transcriptional response of C. auris to macrophage phagocytosis is very similar to other members of the CUG clade (C. albicans, C. tropicalis, C. parapsilosis, C. lusitaniae), and involves downregulation of transcription/ translation and upregulation of alternative carbon metabolism pathways, transporters, and induction of oxidative stress response and proteolysis. Gene family expansions are common in this yeast, and the authors found that many of these genes are induced in response to macrophage co- incubation. Among these, amino acid and oligopeptide transporters, as well as lipases and proteases, are upregulated. Thus, C. auris shares key transcriptional signatures with other fungal pathogens and capitalises on the expansion of gene families coding for potential virulence attributes that allow its survival, persistence and evasion of the innate immune system.


Candida auris infection; diagnosis, and resistance mechanism using high- throughput sequencing technology: a


54


case report and literature review Hong H, Ximing Y, Jinghan M et al. Front Cell Infect Microbiol. 2023 Dec 8; 13: 1211626. doi: 10.3389/ fcimb.2023.1211626. eCollection 2023.


Candida auris, a recently developing fungal disease with high virulence, easy transmission, and substantial medication resistance in hospitals, poses a growing danger to human health. In 2009, the initial documentation of this disease was made when it was discovered in the ear canal of an elderly Japanese patient. Since its initial isolation, the presence of C. auris across six continents has been a cause for severe concern among medical professionals and scientists. According to recent findings, C. auris is connected with five geographically different lineages and significant rates of antifungal resistance. Furthermore, C. auris infections in healthcare settings lack appropriate treatment options and standardised strategies for prevention and control. This results in many treatment failures and hinders the elimination of C. auris in healthcare institutions. To examine the drug resistance mechanism of C. auris and to aid in clinical therapy, the authors provide a case of C. auris infection along with a short review of the relevant literature. An 81-year-old female with cerebral haemorrhage was admitted to hospital and diagnosed with a urinary catheter- related C. auris. The sample was evaluated and reported in terms of culture, identification, drug sensitivity, and gene sequencing. The authors also evaluated the relationship between the morphology of the isolated strains and their drug resistance. Whole-genome sequencing yielded the genes ERG11- Y132F, CDR1-E709D, TAC1B-Q503E and TAC1B-A583S; however, no additional loci included alterations of concern. ERG11-Y132F and TAC1B-A583S are drug-resistant gene loci, whereas CDR1-E709D and TAC1B-Q503E are unidentified variants.


In conclusion, the authors discovered


a C. auris case of specific strain in an old female that has some drug-resistant genes, and some genes may be different from already reported gene sites. Gene locus, mutation, and drug resistance mechanism studies may contribute to the creation of innovative drugs and therapeutic treatments. Clinicians and microbiologists must be aware of this globally spreading yeast, which poses substantial hospital diagnostic, treatment and infection control challenges. Future multicentre research must be performed to uncover this health threat and provide new, effective treatments.


Comparing genomic variant identification protocols for Candida auris Li X, Muñoz JF, Gade L et al. Microb Genom. 2023 Apr; 9 (4): mgen000979. doi: 10.1099/mgen.0.000979.


Genomic analyses are widely applied to epidemiological, population genetic and experimental studies of pathogenic fungi. A wide range of methods are employed to carry out these analyses, typically without including controls that gauge the accuracy of variant prediction. The importance of tracking outbreaks at a global scale has raised the urgency of establishing high-accuracy pipelines that generate consistent results between research groups. To evaluate currently employed methods for whole-genome variant detection and elaborate best practices for fungal pathogens, the authors compared how 14 independent variant calling pipelines performed across 35 Candida auris isolates from four distinct clades and evaluated the performance of variant calling, single-nucleotide polymorphism (SNP) counts and phylogenetic inference results. Although these pipelines used different variant callers and filtering criteria, they found high overall agreement of SNPs from each pipeline. This concordance correlated with site quality, as SNPs discovered by a few pipelines tended to show lower mapping quality scores and depth of coverage than those recovered by all pipelines. The authors observed that the major


differences between pipelines were due to variation in read trimming strategies, SNP calling methods and parameters, and downstream filtration criteria. They calculated specificity and sensitivity for each pipeline by aligning three isolates with chromosomal level assemblies and found that the GATK-based pipelines were well balanced between these metrics. Selection of trimming methods had a greater impact on SAMtools- based pipelines than those using GATK. Phylogenetic trees inferred by each pipeline showed high consistency at the clade level, but there was more variability between isolates from a single outbreak, with pipelines that used more stringent cut-offs having lower resolution. This project generated two truth datasets useful for routine benchmarking of C. auris variant calling, a consensus VCF of genotypes discovered by 10 or more pipelines across these 35 diverse isolates and variants for two samples identified from whole-genome alignments. This study provides a foundation for evaluating SNP calling pipelines and developing best practices for future fungal genomic studies.


FEBRUARY 2024 WWW.PATHOLOGYINPRACTICE.COM


Page 1  |  Page 2  |  Page 3  |  Page 4  |  Page 5  |  Page 6  |  Page 7  |  Page 8  |  Page 9  |  Page 10  |  Page 11  |  Page 12  |  Page 13  |  Page 14  |  Page 15  |  Page 16  |  Page 17  |  Page 18  |  Page 19  |  Page 20  |  Page 21  |  Page 22  |  Page 23  |  Page 24  |  Page 25  |  Page 26  |  Page 27  |  Page 28  |  Page 29  |  Page 30  |  Page 31  |  Page 32  |  Page 33  |  Page 34  |  Page 35  |  Page 36  |  Page 37  |  Page 38  |  Page 39  |  Page 40  |  Page 41  |  Page 42  |  Page 43  |  Page 44  |  Page 45  |  Page 46  |  Page 47  |  Page 48  |  Page 49  |  Page 50  |  Page 51  |  Page 52  |  Page 53  |  Page 54  |  Page 55  |  Page 56