scholarly journals Transcriptome and proteome profiling reveals complex adaptations of Candida parapsilosis cells assimilating hydroxyaromatic carbon sources

2021 ◽  
Author(s):  
Andrea Cillingová ◽  
Renáta Tóth ◽  
Anna Mojáková ◽  
Igor Zeman ◽  
Romana Vrzoňová ◽  
...  
Keyword(s):  
Candida Parapsilosis ◽  
Expression Profiles ◽  
Glyoxylate Cycle ◽  
Carbon Sources ◽  
Gene Clusters ◽  
Fungal Species ◽  
Yeast Cells ◽  
Gentisate Pathway ◽  
Proteomic Investigation ◽  
Pathway Regulation

Many fungal species utilize hydroxyderivatives of benzene and benzoic acid as carbon sources. The yeast Candida parapsilosis metabolizes these compounds via the 3-oxoadipate and gentisate pathways, whose components are encoded by two metabolic gene clusters. In this study, we determine the chromosome level assembly of the C. parapsilosis strain CLIB214 and use it for transcriptomic and proteomic investigation of cells cultivated on hydroxyaromatic substrates. We demonstrate that the genes coding for enzymes and plasma membrane transporters involved in the 3-oxoadipate and gentisate pathways are highly upregulated and their expression is controlled in a substrate-specific manner. However, regulatory proteins involved in this process are not known. Using the knockout mutants, we show that putative transcriptional factors encoded by the genes OTF1 and GTF1 located within these gene clusters function as transcriptional activators of the 3-oxoadipate and gentisate pathway, respectively. We also show that the activation of both pathways is accompanied by upregulation of genes for the enzymes involved in β-oxidation of fatty acids, glyoxylate cycle, amino acid metabolism, and peroxisome biogenesis. Transcriptome and proteome profiles of the cells grown on 4-hydroxybenzoate and 3-hydroxybenzoate, which are metabolized via the 3-oxoadipate and gentisate pathway, respectively, reflect their different connection to central metabolism. Yet we find that the expression profiles differ also in the cells assimilating 4-hydroxybenzoate and hydroquinone, which are both metabolized in the same pathway. This finding is consistent with the phenotype of the Otf1p-lacking mutant, which exhibits impaired growth on hydroxybenzoates, but still utilizes hydroxybenzenes, thus indicating that additional, yet unidentified transcription factor could be involved in the 3-oxoadipate pathway regulation. Moreover, we propose that bicarbonate ions resulting from decarboxylation of hydroxybenzoates also contribute to differences in the cell responses to hydroxybenzoates and hydroxybenzenes. Finally, our phylogenetic analysis highlights evolutionary paths leading to metabolic adaptations of yeast cells assimilating hydroxyaromatic substrates.

scholarly journals Mitochondrial Carriers Link the Catabolism of Hydroxyaromatic Compounds to the Central Metabolism in Candida parapsilosis

2016 ◽  
Vol 6 (12) ◽  
pp. 4047-4058 ◽  
Author(s):  
Igor Zeman ◽  
Martina Neboháčová ◽  
Gabriela Gérecová ◽  
Kornélia Katonová ◽  
Eva Jánošíková ◽  
...  
Keyword(s):  
Cellular Localization ◽  
Candida Parapsilosis ◽  
Tricarboxylic Acid Cycle ◽  
Gene Clusters ◽  
Yeast Cells ◽  
Central Metabolism ◽  
Pathogenic Yeast ◽  
Expression Of Genes ◽  
Coa Transferase ◽  
Gentisate Pathway

Abstract The pathogenic yeast Candida parapsilosis metabolizes hydroxyderivatives of benzene and benzoic acid to compounds channeled into central metabolism, including the mitochondrially localized tricarboxylic acid cycle, via the 3-oxoadipate and gentisate pathways. The orchestration of both catabolic pathways with mitochondrial metabolism as well as their evolutionary origin is not fully understood. Our results show that the enzymes involved in these two pathways operate in the cytoplasm with the exception of the mitochondrially targeted 3-oxoadipate CoA-transferase (Osc1p) and 3-oxoadipyl-CoA thiolase (Oct1p) catalyzing the last two reactions of the 3-oxoadipate pathway. The cellular localization of the enzymes indicates that degradation of hydroxyaromatic compounds requires a shuttling of intermediates, cofactors, and products of the corresponding biochemical reactions between cytosol and mitochondria. Indeed, we found that yeast cells assimilating hydroxybenzoates increase the expression of genes SFC1, LEU5, YHM2, and MPC1 coding for succinate/fumarate carrier, coenzyme A carrier, oxoglutarate/citrate carrier, and the subunit of pyruvate carrier, respectively. A phylogenetic analysis uncovered distinct evolutionary trajectories for sparsely distributed gene clusters coding for enzymes of both pathways. Whereas the 3-oxoadipate pathway appears to have evolved by vertical descent combined with multiple losses, the gentisate pathway shows a striking pattern suggestive of horizontal gene transfer to the evolutionarily distant Mucorales.

scholarly journals Intracellular Acetyl Unit Transport in Fungal Carbon Metabolism

2010 ◽  
Vol 9 (12) ◽  
pp. 1809-1815 ◽  
Author(s):  
Karin Strijbis ◽  
Ben Distel
Keyword(s):  
Carbon Metabolism ◽  
Citrate Synthase ◽  
Current Knowledge ◽  
Glyoxylate Cycle ◽  
Carbon Sources ◽  
Fungal Species ◽  
Special Focus ◽  
Acetyl Coa ◽  
Content Type ◽  
Dependent Pathway

ABSTRACT Acetyl coenzyme A (acetyl-CoA) is a central metabolite in carbon and energy metabolism. Because of its amphiphilic nature and bulkiness, acetyl-CoA cannot readily traverse biological membranes. In fungi, two systems for acetyl unit transport have been identified: a shuttle dependent on the carrier carnitine and a (peroxisomal) citrate synthase-dependent pathway. In the carnitine-dependent pathway, carnitine acetyltransferases exchange the CoA group of acetyl-CoA for carnitine, thereby forming acetyl-carnitine, which can be transported between subcellular compartments. Citrate synthase catalyzes the condensation of oxaloacetate and acetyl-CoA to form citrate that can be transported over the membrane. Since essential metabolic pathways such as fatty acid β-oxidation, the tricarboxylic acid (TCA) cycle, and the glyoxylate cycle are physically separated into different organelles, shuttling of acetyl units is essential for growth of fungal species on various carbon sources such as fatty acids, ethanol, acetate, or citrate. In this review we summarize the current knowledge on the different systems of acetyl transport that are operational during alternative carbon metabolism, with special focus on two fungal species: Saccharomyces cerevisiae and Candida albicans.

scholarly journals Carbon Catabolite Control in Candida albicans: New Wrinkles in Metabolism

mBio ◽  
2013 ◽  
Vol 4 (1) ◽  
Author(s):  
Michael C. Lorenz
Keyword(s):  
Candida Albicans ◽  
Carbon Source ◽  
Phosphoenolpyruvate Carboxykinase ◽  
Isocitrate Lyase ◽  
Glyoxylate Cycle ◽  
Carbon Sources ◽  
Fungal Species ◽  
Content Type ◽  
Catabolite Control

ABSTRACTMost microorganisms maintain strict control of nutrient assimilation pathways to ensure that they preferentially use compounds that generate the most energy or are most efficiently catabolized. In doing so, they avoid potentially inefficient conflicts between parallel catabolic and metabolic pathways. The regulation of carbon source utilization in a wide array of bacterial and fungal species involves both transcriptional and posttranscriptional mechanisms, and while the details can vary significantly, carbon catabolite control is widely conserved. In many fungi, the posttranslational aspect (carbon catabolite inactivation [CCI]) involves the ubiquitin-mediated degradation of catabolic enzymes for poor carbon sources when a preferred one (glucose) becomes available. A recent article presents evidence for a surprising exception to CCI in the fungal pathogenCandida albicans, an organism that makes use of gluconeogenic carbon sources during infection (D. Sandai, Z. Yin, L. Selway, D. Stead, J. Walker, M. D. Leach, I. Bohovych, I. V. Ene, S. Kastora, S. Budge, C. A. Munro, F. C. Odds, N. A. Gow, and A. J. Brown,mBio3[6]:e00495-12).In vitro, addition of glucose to cells grown in a poor carbon source rapidly represses transcripts encoding gluconeogenic and glyoxylate cycle enzymes, such as phosphoenolpyruvate carboxykinase (Pck1p) and isocitrate lyase (Icl1p), in bothC. albicansandSaccharomyces cerevisiae. Yet, uniquely, theC. albicansproteins persist, permitting parallel assimilation of multiple carbon sources, likely because they lack consensus ubiquitination sites found in the yeast homologs. Indeed, the yeast proteins are rapidly degraded when expressed inC. albicans, indicating a conservation of the machinery needed for CCI. How this surprising metabolic twist contributes to fungal commensalism or pathogenesis remains an open question.

scholarly journals Integrated Genomic Analysis of Sézary Syndrome

2011 ◽  
Vol 2011 ◽  
pp. 1-13 ◽  
Author(s):  
Xin Mao ◽  
Tracy Chaplin ◽  
Bryan D. Young
Keyword(s):  
Copy Number ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Genomic Analysis ◽  
Gene Clusters ◽  
Sézary Syndrome ◽  
Sezary Syndrome ◽  
Snp Microarray ◽  
The Impact ◽  
Chromosome Regions

Sézary syndrome (SS) is a rare variant of primary cutaneous T-cell lymphoma. Little is known about the underlying pathogenesis of S. To address this issue, we used Affymetrix 10K SNP microarray to analyse 13 DNA samples isolated from 8 SS patients and qPCR with ABI TaqMan SNP genotyping assays for the validation of the SNP microarray results. In addition, we tested the impact of SNP loss of heterozygosity (LOH) identified in SS cases on the gene expression profiles of SS cases detected with Affymetrix GeneChip U133A. The results showed: (1) frequent SNP copy number change and LOH involving 1, 2p, 3, 4q, 5q, 6, 7p, 8, 9, 10, 11, 12q, 13, 14, 16q, 17, and 20, (2) reduced SNP copy number at FAT gene (4q35) in 75% of SS cases, and (3) the separation of all SS cases from normal control samples by SNP LOH gene clusters at chromosome regions of 9q31q34, 10p11q26, and 13q11q12. These findings provide some intriguing information for our current understanding of the molecular pathogenesis of this tumour and suggest the possibility of presence of functional SNP LOH in SS tumour cells.

The Cloning and Mapping of ADR6, a Gene Required for Sporulation and for Expression of the Alcohol Dehydrogenase II Isozyme From Saccharomyces cerevisiae

Genetics ◽  
1987 ◽  
Vol 116 (4) ◽  
pp. 531-540
Author(s):  
Aileen K W Taguchi ◽  
Elton T Young
Keyword(s):  
Saccharomyces Cerevisiae ◽  
Alcohol Dehydrogenase ◽  
Single Gene ◽  
Carbon Sources ◽  
Transcription Unit ◽  
Yeast Cells ◽  
Recessive Mutation ◽  
Yeast Saccharomyces Cerevisiae ◽  
Upstream Activating Sequence ◽  
A Site

ABSTRACT The alcohol dehydrogenase II (ADH2) gene of the yeast, Saccharomyces cerevisiae, is not transcribed during growth on fermentable carbon sources such as glucose. Growth of yeast cells in a medium containing only nonfermentable carbon sources leads to a marked increase or derepression of ADH2 expression. The recessive mutation, adr6-1, leads to an inability to fully derepress ADH2 expression and to an inability to sporulate. The ADR6 gene product appears to act directly or indirectly on ADH2 sequences 3' to or including the presumptive TATAA box. The upstream activating sequence (UAS) located 5' to the TATAA box is not required for the Adr6- phenotype. Here, we describe the isolation of a recombinant plasmid containing the wild-type ADR6 gene. ADR6 codes for a 4.4-kb RNA which is present during growth both on glucose and on nonfermentable carbon sources. Disruption of the ADR6 transcription unit led to viable cells with decreased ADHII activity and an inability to sporulate. This indicates that both phenotypes result from mutations within a single gene and that the adr6-1 allele was representative of mutations at this locus. The ADR6 gene mapped to the left arm of chromosome XVI at a site 18 centimorgans from the centromere.

22 Characterization of tRNA Expression Profiles in Large Offspring Syndrome

2021 ◽  
Vol 99 (Supplement_3) ◽  
pp. 13-14
Author(s):  
Anna K Goldkamp ◽  
Yahan Li ◽  
Rocio M Rivera ◽  
Darren Hagen
Keyword(s):  
Skeletal Muscle ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Tumor Development ◽  
Gene Clusters ◽  
Tissue Type ◽  
Trna Genes ◽  
Translational Machinery ◽  
Trna Species

Abstract Differentially methylated regions (DMRs) have been associated with Large Offspring Syndrome (LOS) in cattle. Some DMRs overlap transfer RNA (tRNA) gene clusters, potentially altering tRNA expression patterns uniquely by treatment group or tissue type. tRNAs are classified as adapter molecules, serving a key role in the translational machinery implementing genetic code. Variation in tRNA expression has been identified in several disease pathways suggesting an important role in the regulation of biological processes. tRNAs also serve as a source of small non-coding RNAs. To better understand the role of tRNA expression in LOS, total RNA was extracted from skeletal muscle and liver of 105-day fetuses and the tRNAs sequenced. Although there are nearly three times the number of tRNA genes in cattle as compared to human (1,659 vs 597), there is a shared occurrence of transcriptionally silent tRNA genes in both species. This study detected expression of 474 and 487 bovine tRNA genes in skeletal muscle and liver, respectively, with the remainder being very lowly expressed or transcriptionally silent. Eleven tRNA isodecoders are transcriptionally silent in both skeletal muscle and liver and another isodecoder is silent in the liver (SerGGA). Further, the highest expressed isodecoders differ by treatment or tissue type with roughly half correlated to codon frequency. While the absence of certain isodecoders may be relieved by wobble base pairing, missing tRNA species could likely increase the likelihood of mistranslation or mRNA degradation. Differential expression of tissue- and treatment-specific tRNA genes may modulate translation during protein homeostasis or cellular stress, altering regulatory products targeting genes associated with overgrowth in skeletal muscle and/or tumor development in the liver of LOS individuals.

scholarly journals Vibrio gazogenes inhibits aflatoxin production through downregulation of aflatoxin biosynthetic genes in Aspergillus flavus

2022 ◽  
Author(s):  
Shyam L. Kandel ◽  
Rubaiya Jesmin ◽  
Brian M. Mack ◽  
Rajtilak Majumdar ◽  
Matthew K. Gilbert ◽  
...  
Keyword(s):  
Secondary Metabolites ◽  
Secondary Metabolite ◽  
Aspergillus Flavus ◽  
Fungal Biomass ◽  
Expression Profiles ◽  
Health Hazard ◽  
Gene Clusters ◽  
Aflatoxin Contamination ◽  
Aflatoxin Biosynthesis ◽  
Control Samples

Aspergillus flavus is an opportunistic pathogen of oilseed crops such as maize, peanut, cottonseed, and tree nuts and produces carcinogenic secondary metabolites known as aflatoxins during seed colonization. Aflatoxin contamination not only reduces the value of the produce but also is a health hazard to humans and animals. Previously, we observed inhibition of A. flavus aflatoxin biosynthesis upon exposure to the marine bacterium, Vibrio gazogenes (Vg). In this study, we used RNA sequencing to examine the transcriptional profiles of A. flavus treated with both live and heat-inactivated dead Vg and control samples. Fungal biomass, total accumulated aflatoxins, and expression profiles of genes constituting secondary metabolite biosynthetic gene clusters were determined at 24, 30, and 40 h after treatment. Statistically significant reductions in total aflatoxins were detected in Vg-treated samples as compared to control samples at 40 h. But no statistical difference in fungal biomass was observed upon these treatments. The Vg treatments were most effective on aflatoxin biosynthesis as was reflected in significant downregulation of majority of the genes in the aflatoxin gene cluster including the aflatoxin pathway regulator gene, aflR. Along with aflatoxin genes, we also observed significant downregulation in some other secondary metabolite gene clusters including cyclopiazonic acid and aflavarin, suggesting that the treatment may inhibit other secondary metabolites as well. Finally, a weighted gene correlation network analysis identified an upregulation of ten genes that were most strongly associated with Vg-dependent aflatoxin inhibition and provide a novel start-point in understanding the mechanisms that result in this phenomenon.

scholarly journals Linkage between Carbon Metabolism, Redox Status and Cellular Physiology in the Yeast Saccharomyces cerevisiae Devoid of SOD1 or SOD2 Gene

Genes ◽  
2020 ◽  
Vol 11 (7) ◽  
pp. 780 ◽  
Author(s):  
Roman Maslanka ◽  
Renata Zadrag-Tecza ◽  
Magdalena Kwolek-Mirek
Keyword(s):  
Saccharomyces Cerevisiae ◽  
Carbon Metabolism ◽  
Redox Homeostasis ◽  
Carbon Sources ◽  
Pyridine Nucleotide ◽  
Redox Status ◽  
Yeast Cells ◽  
Yeast Saccharomyces Cerevisiae ◽  
Cellular Physiology ◽  
Respiratory Conditions

Saccharomyces cerevisiae yeast cells may generate energy both by fermentation and aerobic respiration, which are dependent on the type and availability of carbon sources. Cells adapt to changes in nutrient availability, which entails the specific costs and benefits of different types of metabolism but also may cause alteration in redox homeostasis, both by changes in reactive oxygen species (ROS) and in cellular reductant molecules contents. In this study, yeast cells devoid of the SOD1 or SOD2 gene and fermentative or respiratory conditions were used to unravel the connection between the type of metabolism and redox status of cells and also how this affects selected parameters of cellular physiology. The performed analysis provides an argument that the source of ROS depends on the type of metabolism and non-mitochondrial sources are an important pool of ROS in yeast cells, especially under fermentative metabolism. There is a strict interconnection between carbon metabolism and redox status, which in turn has an influence on the physiological efficiency of the cells. Furthermore, pyridine nucleotide cofactors play an important role in these relationships.

Gene expression profiles based flux balance model to predict the carbon source for Bacillus subtilis

2019 ◽  
Author(s):  
Kulwadee Thanamit ◽  
Franziska Hoerhold ◽  
Marcus Oswald ◽  
Rainer Koenig
Keyword(s):  
Gene Expression ◽  
Carbon Source ◽  
Drug Targets ◽  
Expression Profiles ◽  
Carbon Sources ◽  
Gene Expression Profiles ◽  
Fast Method ◽  
Flux Balance ◽  
Metabolic Fluxes

ABSTRACTFinding drug targets for antimicrobial treatment is a central focus in biomedical research. To discover new drug targets, we developed a method to identify which nutrients are essential for microorganisms. Using 13C labeled metabolites to infer metabolic fluxes is the most informative way to infer metabolic fluxes to date. However, the data can get difficult to acquire in complicated environments, for example, if the pathogen homes in host cells. Although data from gene expression profiling is less informative compared to metabolic tracer derived data, its generation is less laborious, and may still provide the relevant information. Besides this, metabolic fluxes have been successfully predicted by flux balance analysis (FBA). We developed an FBA based approach using the stoichiometric knowledge of the metabolic reactions of a cell combining them with expression profiles of the coding genes. We aimed to identify essential drug targets for specific nutritional uptakes of microorganisms. As a case study, we predicted each single carbon source out of a pool of eight different carbon sources for B. subtilis based on gene expression profiles. The models were in good agreement to models basing on 13C metabolic flux data of the same conditions. We could well predict every carbon source. Later, we applied successfully the model to unseen data from a study in which the carbon source was shifted from glucose to malate and vice versa. Technically, we present a new and fast method to reduce thermodynamically infeasible loops, which is a necessary preprocessing step for such model-building algorithms.SIGNIFICANCEIdentifying metabolic fluxes using 13C labeled tracers is the most informative way to gain insight into metabolic fluxes. However, obtaining the data can be laborious and challenging in a complex environment. Though transcriptional data is an indirect mean to estimate the fluxes, it can help to identify this. Here, we developed a new method employing constraint-based modeling to predict metabolic fluxes embedding gene expression profiles in a linear regression model. As a case study, we used the data from Bacillus subtilis grown under different carbon sources. We could well predict the correct carbon source. Additionally, we established a novel and fast method to remove thermodynamically infeasible loops.

scholarly journals Application of Gene Shaving and Mixture Models to Cluster Microarray Gene Expression Data

2007 ◽  
Vol 5 ◽  
pp. 117693510700500
Author(s):  
K-A. Do ◽  
G.J. McLachlan ◽  
R. Bean ◽  
S. Wen
Keyword(s):  
Gene Expression ◽  
Expression Profiles ◽  
Lymphoblastic Leukemia ◽  
Gene Clusters ◽  
Gene Clustering ◽  
Expression Data ◽  
Colon Tissue ◽  
Data Set ◽  
Tissue Samples ◽  
Gene Shaving

Researchers are frequently faced with the analysis of microarray data of a relatively large number of genes using a small number of tissue samples. We examine the application of two statistical methods for clustering such microarray expression data: EMMIX-GENE and GeneClust. EMMIX-GENE is a mixture-model based clustering approach, designed primarily to cluster tissue samples on the basis of the genes. GeneClust is an implementation of the gene shaving methodology, motivated by research to identify distinct sets of genes for which variation in expression could be related to a biological property of the tissue samples. We illustrate the use of these two methods in the analysis of Affymetrix oligonucleotide arrays of well-known data sets from colon tissue samples with and without tumors, and of tumor tissue samples from patients with leukemia. Although the two approaches have been developed from different perspectives, the results demonstrate a clear correspondence between gene clusters produced by GeneClust and EMMIX-GENE for the colon tissue data. It is demonstrated, for the case of ribosomal proteins and smooth muscle genes in the colon data set, that both methods can classify genes into co-regulated families. It is further demonstrated that tissue types (tumor and normal) can be separated on the basis of subtle distributed patterns of genes. Application to the leukemia tissue data produces a division of tissues corresponding closely to the external classification, acute myeloid meukemia (AML) and acute lymphoblastic leukemia (ALL), for both methods. In addition, we also identify genes specific for the subgroup of ALL-Tcell samples. Overall, we find that the gene shaving method produces gene clusters at great speed; allows variable cluster sizes and can incorporate partial or full supervision; and finds clusters of genes in which the gene expression varies greatly over the tissue samples while maintaining a high level of coherence between the gene expression profiles. The intent of the EMMIX-GENE method is to cluster the tissue samples. It performs a filtering step that results in a subset of relevant genes, followed by gene clustering, and then tissue clustering, and is favorable in its accuracy of ranking the clusters produced.

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