Biology subjects

Bader, O.

Publications and source records attributed to Bader, O..

5 recordsLinked to original sources

bioRxiv2025

Small pangenome of Candida parapsilosis reflects overall low intraspecific diversity

Candida parapsilosis is an opportunistic yeast pathogen that can cause life-threatening infections in immunocompromised humans. Whole genome sequencing (WGS) studies of the species have demonstrated remarkably low diversity, with strains typically differing by about 1.5 single nucleotide polymorphisms (SNPs) per 10 kb. However, SNP calling alone does not capture the full extent of genetic variation. Here, we define the pangenome of 372 C. parapsilosis isolates to determine variation in gene content. The pangenome consists of 5,859 genes, of which 48 are not found in the genome of the reference strain. This includes 5,791 core genes (present in [≥] 99.5% of isolates). Four genes, including the allantoin permease gene DAL4, were present in all isolates but were truncated in some strains. The truncated DAL4 was classified as a pseudogene in the reference strain CDC317. CRISPR-Cas9 gene editing showed that removing the early stop codon (producing the full-length Dal4 protein) is associated with improved use of allantoin as a sole nitrogen source. We find that the accessory genome of C. parapsilosis consists of 68 homologous clusters. This includes 38 previously annotated genes, 27 novel paralogs of previously annotated genes and 3 uncharacterised ORFs. Approximately one-third of the accessory genome (24/68 genes) is associated with gene fusions between tandem genes in the major facilitator superfamily (MFS). Additionally, we identified two highly divergent C. parapsilosis strains and find that, despite their increased phylogenetic distance ([~]30 SNPs per 10 kb), both strains have similar gene content to the other 372. ImportanceCandida parapsilosis is a human fungal pathogen, listed in the high priority group by the World Health Organisation. It is an increasing cause of hospital-acquired and drug-resistant infection. Here, we studied the genetic diversity of 372 C. parapsilosis isolates, the largest genomic surveillance of this species to date. We show that there is relatively little genetic variation. However, we identified two more distantly-related isolates from Germany, suggesting that even more sampling may yield more diversity. We find that the pangenome (the cumulative gene content of all isolates) is surprisingly small, compared to other fungal species. Many of the non-core genes are involved in transport. We also find that variations in gene content are associated with nitrogen metabolism, which may contribute to the virulence characteristics of this species.

genomics↗

bioRxiv2024

Effect of Data Heterogeneity in Clinical MALDI-TOF Mass Spectra Profiles on Direct Antimicrobial Resistance Prediction through Machine Learning

The matrix-assisted laser desorption-ionization time-of-flight mass spectrometry has become a powerful tool for accurate species identification in routine diagnostic microbiology. Recently, the application of machine learning models with MALDI-TOF mass spectra data indicated that rapid prediction of antimicrobial resistance patterns might facilitate even timelier and improved antimicrobial treatment. Although MALDI-TOF mass spectra data have proven valuable for clinical decision support, the issue of class imbalance in routine clinical data is often overlooked. This imbalance arises from factors such as local epidemiology, selective pressure from antibiotics, culture conditions, the methodology of phenotypic antimicrobial susceptibility testing, and sample preparation processes. Here, we provide a large mass spectra dataset, MS-UMG, for antimicrobial resistance prediction model training. With previously available public datasets, our dataset is evaluated and validated for usage in AMR prediction. We further explore the mass spectra data and identify informative regions on the spectra profile for AMR prediction. Moreover, we investigate the composition of this clinical dataset and present the implications of data heterogeneity on machine learning model performance. In conclusion, our findings highlight that accurate comprehension of clinical routine data and consideration of diverse hospital protocols are critical for effective clinical decision support systems with machine learning models. Key PointsO_LIIntroduced a large-scale clinical mass spectrometry dataset to the scientific community for research on antimicrobial resistance. C_LIO_LIConducted a comparison and evaluation of this dataset with other existing large-scale MS datasets, highlighting its value for developing and validating predictive models in clinical settings. C_LIO_LIDemonstrated the robustness of machine learning models for antimicrobial resistance prediction using large-scale clinical mass spectra profiles. C_LIO_LIAnalyzed the impact of data heterogeneity on the training and performance of machine learning models, emphasizing the need to account for variability in clinical routine data to enhance model reliability and generalizability. C_LI

bioinformatics↗

bioRxiv2020

Proteogenomics analysis of CUG codon translation in the human pathogen Candida albicans

Candida yeasts causing human infections are spread across the yeast phylum with Candida glabrata being related to Saccharomyces cerevisiae, Candida krusei grouping to Pichia spp., and Candida albicans, Candida parapsilosis and Candida tropicalis belonging to the CTG-clade. The latter lineage contains yeasts with an altered genetic code translating CUG codons as serine using a serine-tRNA with a mutated anticodon. It has been suggested that the CTG-clade CUG codons are mistranslated to a small extent as leucine due to mischarging of the serine-tRNA(CAG). The mistranslation was suggested to result in variable surface proteins explaining fast host adaptation and pathogenicity. Here, we re-assessed this potential mistranslation by high-resolution mass spectrometry-based proteogenomics of multiple CTG-clade yeasts, various C. albicans strains, isolated from colonized and from infected human body sites, and C. albicans grown in yeast and hyphal forms. Our in vivo data do not support CUG codon mistranslation by leucine. Instead, (i) CUG codons are mistranslated only to the extent of ribosomal mistranslation with no preference for specific amino acids, (ii) CUG codons are as unambiguous (or ambiguous) as the related CUU leucine and UCC serine codons, (iii) tRNA anticodon loop variation across the CTG-clade yeasts does not result in any difference of the mistranslation level, and (iv) CUG codon unambiguity is independent of C. albicans strain pathogenicity or growth form.

genomics↗

bioRxiv2020

Biosynthetic gene clusters, secondary metabolite profiles, and cards of virulence in the closest nonpathogenic relatives of Aspergillus fumigatus

Aspergillus fumigatus is a major human pathogen that causes hundreds of thousands of infections yearly with high mortality rates. In contrast, Aspergillus fischeri and the recently described Aspergillus oerlinghausenensis, the two species most closely related to A. fumigatus, are not known to be pathogenic. Some of the "cards of virulence" that A. fumigatus possesses are secondary metabolites that impair the host immune system, protect from host immune cell attacks, or acquire key nutrients. Secondary metabolites and the biosynthetic gene clusters (BGCs) that typically encode them often vary within and between fungal species. To gain insight into whether secondary metabolism-associated cards of virulence vary between A. fumigatus, A. oerlinghausenensis, and A. fischeri, we conducted extensive genomic and secondary metabolite profiling analyses. By analyzing multiple A. fumigatus, one A. oerlinghausenensis, and multiple A. fischeri strains, we identified both conserved and diverged secondary metabolism-associated cards of virulence. For example, we found that all species and strains examined biosynthesized the major virulence factor gliotoxin, consistent with the conservation of the gliotoxin BGC across genomes. However, species differed in their biosynthesis of fumagillin and pseurotin, both contributors to host tissue damage during invasive aspergillosis; these differences were reflected in sequence divergence of the intertwined fumagillin/pseurotin BGCs across genomes. These results delineate the similarities and differences in secondary metabolism-associated cards of virulence between a major fungal pathogen and its nonpathogenic closest relatives, shedding light into the genetic and phenotypic changes associated with the evolution of fungal pathogenicity. ImportanceThe major fungal pathogen Aspergillus fumigatus kills tens of thousands each year. In contrast, the two closest relatives of A. fumigatus, namely Aspergillus fischeri and Aspergillus oerlinghausenensis, are not considered pathogenic. A. fumigatus virulence stems, partly, from its ability to produce small molecules called secondary metabolites that have potent activities during infection. In this study, we examined whether A. fumigatus secondary metabolites and the metabolic pathways involved in their production are conserved in A. oerlinghausenensis and A. fischeri. We found that the nonpathogenic close relatives of A. fumigatus produce some, but not all, secondary metabolites thought to contribute to the success of A. fumigatus in causing human disease and that these similarities and differences were reflected in the underlying metabolic pathways involved in their biosynthesis. Compared to its nonpathogenic close relatives, A. fumigatus produces a distinct cocktail of secondary metabolites, which likely contributes to these organisms vastly different potentials to cause human disease. More broadly, the study of nonpathogenic organisms that have virulence-related traits, but are not currently considered agents of human disease, may facilitate the prediction of species capable of posing future threats to human health.

evolutionary biology↗

bioRxiv2017

Patterns of genomic variation in the opportunistic pathogen Candida glabrata suggest the existence of mating and a secondary association to the human host

Candida glabrata is an opportunistic fungal pathogen that ranks as the second most common cause of systemic candidiasis. Despite its genus name, this yeast is more closely related to the model yeast Saccharomyces cerevisiae than to other Candida pathogens, and hence its ability to infect humans is thought to have emerged independently. Morover, C. glabrata has all the necessary genes to undergo a sexual cycle, but it is considered an asexual organism due to the lack of direct evidence of sexual reproduction. Here, we assessed genomic and phenotypic variation across 33 globally-distributed C. glabrata isolates. We cataloged extensive copy number variation, which particularly affects genes encoding cell-wall associated proteins, including adhesins. The observed level of genetic variation in C. glabrata is significantly larger than that found in Candida albicans. This variation is structured in seven deeply divergent clades, which show recent geographical dispersion and large within-clade genomic and phenotypic differences. We show compelling evidence of recent admixture between differentiated lineages, and of purifying selection on mating genes, which provide fist evidence for the existence of a sexual cycle in this yeast. Altogether, our data point to a recent global spread of previously genetically isolated populations and suggest that humans are only a secondary niche for this yeast.

microbiology↗