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PubMed2006

Exploring glycopeptide-resistance in Staphylococcus aureus: a combined proteomics and transcriptomics approach for the identification of resistance-related markers.

BACKGROUND: To unravel molecular targets involved in glycopeptide resistance, three isogenic strains of Staphylococcus aureus with different susceptibility levels to vancomycin or teicoplanin were subjected to whole-genome microarray-based transcription and quantitative proteomic profiling. Quantitative proteomics performed on membrane extracts showed exquisite inter-experimental reproducibility permitting the identification and relative quantification of >30% of the predicted S. aureus proteome. RESULTS: In the absence of antibiotic selection pressure, comparison of stable resistant and susceptible strains revealed 94 differentially expressed genes and 178 proteins. As expected, only partial correlation was obtained between transcriptomic and proteomic results during stationary-phase. Application of massively parallel methods identified one third of the complete proteome, a majority of which was only predicted based on genome sequencing, but never identified to date. Several over-expressed genes represent previously reported targets, while series of genes and proteins possibly involved in the glycopeptide resistance mechanism were discovered here, including regulators, global regulator attenuator, hyper-mutability factor or hypothetical proteins. Gene expression of these markers was confirmed in a collection of genetically unrelated strains showing altered susceptibility to glycopeptides. CONCLUSION: Our proteome and transcriptome analyses have been performed during stationary-phase of growth on isogenic strains showing susceptibility or intermediate level of resistance against glycopeptides. Altered susceptibility had emerged spontaneously after infection with a sensitive parental strain, thus not selected in vitro. This combined analysis allows the identification of hundreds of proteins considered, so far as hypothetical protein. In addition, this study provides not only a global picture of transcription and expression adaptations during a complex antibiotic resistance mechanism but also unravels potential drug targets or markers that are constitutively expressed by resistant strains regardless of their genetic background, amenable to be used as diagnostic targets.

Anti-Bacterial Agents↗

PubMed2005

Analysis of expressed sequence tags from the wheat leaf blotch pathogen Mycosphaerella graminicola (anamorph Septoria tritici).

Mycosphaerella graminicola is a major fungal pathogen of wheat as the causal agent of Septoria leaf blotch disease. As a first step toward a greater understanding of the mechanism of host infection we have generated, sequenced, and analyzed three M. graminicola EST libraries from conditions predicted to resemble independent phases of the host infection process, including one library generated from the fungus during interaction with its host. A total of 5180 ESTs were sequenced and clustered into 886 contigs and 2039 singletons to give a set of 2925 unique sequences (unisequences). BLASTX analysis revealed 33% of the unknown M. graminicola unisequences to be orphans. Very limited inter-library overlap of expression was seen with the majority of unisequences (contigs and singletons) being library-specific. Analysis of EST redundancy between libraries demonstrated a significant difference in gene expression in the three conditions. Comparisons made against fully sequenced genomes revealed most M. graminicola sequences to be homologous to genes present in both pathogenic and non-pathogenic Ascomycete filamentous fungi. A range of sequences having significant homology to verified pathogenicity/virulence genes (HvPV-genes) of either plant or mammalian fungal and Oomycete pathogens were also identified (<1e-20). The generation of, and the diversity present within, this EST collection will facilitate future efforts aimed at a more detailed study of the transcriptome of the fungus during host infection.

Ascomycota↗

PubMed2006

Comparative salivary gland transcriptomics of sandfly vectors of visceral leishmaniasis.

BACKGROUND: Immune responses to sandfly saliva have been shown to protect animals against Leishmania infection. Yet very little is known about the molecular characteristics of salivary proteins from different sandflies, particularly from vectors transmitting visceral leishmaniasis, the fatal form of the disease. Further knowledge of the repertoire of these salivary proteins will give us insights into the molecular evolution of these proteins and will help us select relevant antigens for the development of a vector based anti-Leishmania vaccine. RESULTS: Two salivary gland cDNA libraries from female sandflies Phlebotomus argentipes and P. perniciosus were constructed, sequenced and proteomic analysis of the salivary proteins was performed. The majority of the sequenced transcripts from the two cDNA libraries coded for secreted proteins. In this analysis we identified transcripts coding for protein families not previously described in sandflies. A comparative sandfly salivary transcriptome analysis was performed by using these two cDNA libraries and two other sandfly salivary gland cDNA libraries from P. ariasi and Lutzomyia longipalpis, also vectors of visceral leishmaniasis. Full-length secreted proteins from each sandfly library were compared using a stand-alone version of BLAST, creating formatted protein databases of each sandfly library. Related groups of proteins from each sandfly species were combined into defined families of proteins. With this comparison, we identified families of salivary proteins common among all of the sandflies studied, proteins to be genus specific and proteins that appear to be species specific. The common proteins included apyrase, yellow-related protein, antigen-5, PpSP15 and PpSP32-related protein, a 33-kDa protein, D7-related protein, a 39- and a 16.1- kDa protein and an endonuclease-like protein. Some of these families contained multiple members, including PPSP15-like, yellow proteins and D7-related proteins suggesting gene expansion in these proteins. CONCLUSION: This comprehensive analysis allows us the identification of genus- specific proteins, species-specific proteins and, more importantly, proteins common among these different sandflies. These results give us insights into the repertoire of salivary proteins that are potential candidates for a vector-based vaccine.

Amino Acid Sequence↗

PubMed2026

Myeloid landscape of BRAF-mutant papillary thyroid cancer and thyroiditis.

Papillary thyroid cancer (PTC) is less aggressive when associated with lymphocytic thyroiditis (LT), even in the presence of oncogenic BRAF, including smaller tumours, less lymph node involvement and reduced extrathyroidal extension. To investigate possible immune mechanisms underlying this association, we compared the tumour microenvironment of PTC-BRAF with LT and that without LT using single-cell RNA sequencing (scRNA-seq). Single-cell libraries were generated from fresh and fixed tumour samples with post-dissociation viability >70% using the 10x Genomics Chromium Platform and sequenced on an Illumina NovaSeq 6000. We analysed scRNA-seq data from 11 PTC-BRAF tumours: four with LT (one publicly available sample) and seven without LT. Downstream analyses included quality control, batch correction, dimensionality reduction, and differential gene expression analysis. We found that neutrophils were the predominant myeloid cell type in PTCs without LT. Thyrocytes without LT showed significant expression of the neutrophil recruitment chemokine ECRG4. In the absence of LT, neutrophils expressed oncogenic genes with poor clinical outcomes. In contrast, thyrocytes from tumours with LT showed increased expression of MHC-II antigen presentation, consistent with effective immune surveillance. Thyrocytes and macrophages in the presence of LT showed enrichment of interferon gamma response pathways. Our data suggest that LT in thyroid cancer is associated with enhanced antigen presentation and fewer features of pro-tumourigenic innate immune activity. These results identify previously under-recognised innate immune cell population and associated transcriptomic features, which suggest new mechanisms to target immune treatments in PTC refractory to other therapies.

Humans↗

PubMed2026

A novel lactylation-related gene signature deciphers the immunosuppressive microenvironment and stratifies precision therapy in colorectal cancer.

BACKGROUND: Colorectal cancer (CRC) remains a leading cause of cancer mortality, largely due to the heterogeneity of the tumor microenvironment (TME) and the limited efficacy of immunotherapy in microsatellite stable (MSS) tumors. Histone lactylation, a post-translational modification derived from the Warburg effect, serves as a critical bridge linking metabolic reprogramming to gene regulation and immune evasion; however, its specific prognostic value and clinical implications in CRC remain to be fully elucidated. METHODS: In this study, we systematically analyzed transcriptome profiling data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) cohorts, supplemented by single-cell RNA sequencing (scRNA-seq) analysis and Human Protein Atlas (HPA) protein-level validation. By integrating univariate Cox regression, Least Absolute Shrinkage and Selection Operator (LASSO) analysis, and multivariate Cox regression, we constructed a novel lactylation-related gene (LRG) risk signature. We extensively evaluated the association between this risk signature and patient prognosis, immune infiltration patterns, somatic mutations, and therapeutic sensitivity. RESULTS: A robust 9-gene prognostic signature (DHRS7, SPR, MBD2, RBM17, CSRP2, S100A4, TMSB4X, TKT, COPS4) was identified and corroborated at the protein level. Patients with high risk scores exhibited significantly worse overall survival (OS) across the training and two independent validation cohorts. Immunogenomic and scRNA-seq analyses revealed that high-risk tumors were characterized by an immunosuppressive and stromal-dense microenvironment-with stromal cells exhibiting the highest lactylation risk scores-enriched with regulatory T cells (Tregs), and frequently harbored PIK3CA mutations. Differential expression analysis indicated that this immune exclusion is structurally maintained by enriched extracellular matrix (ECM) organization and TGF-β signaling. Conversely, low-risk tumors displayed an inflamed phenotype with active antitumor immunity. Pharmacogenomic prediction identified distinct therapeutic stratifications: low-risk patients exhibited significant sensitivity to standard chemotherapeutics (fluorouracil, oxaliplatin) and EGFR/HER2 inhibitors (e.g., lapatinib, erlotinib). In contrast, high-risk patients showed specific vulnerabilities to novel targeted agents, including PI3K pathway inhibitors (TG-100-115, XL765), microenvironment-modulating agents (sildenafil, GANT-61), and epigenetic inhibitors (UNC0638). CONCLUSION: We established a novel lactylation-related risk signature that effectively stratifies CRC patients by prognosis and TME characteristics. By elucidating the crosstalk between metabolic dysregulation, stromal barriers, and immune exclusion, this study provides potential biomarkers and stratified therapeutic strategies-ranging from standard chemotherapy to targeted metabolic and stromal interventions-to optimize precision medicine for CRC patients.

Colorectal cancer↗

PubMed2005

Anopheles infection responses; laboratory models versus field malaria transmission systems.

The molecular biology of disease vectors, particularly mosquitoes, has experienced a remarkable progress in the past two decades. This is mainly attributed to methodological advances and the emerging genome sequences of vector species, which have brought experimental biology to an unprecedented level. It is now possible to determine the entire transcriptome of Anopheles gambiae at a variety of conditions, with a low per-gene effort and cost. Proteomic profiles can be generated for as small samples as the hemolymph, and transient reverse genetic and stable germ line based transgenic analyses can be performed to analyze gene function. High throughput screening for receptors and ligands can be used to characterize interactions between vectors and pathogens. At the current breathtaking rates of data production it is essential to question and evaluate the relevance of laboratory infection models to the real disease transmission systems. The majority of scientific discoveries in mosquito molecular biology have been based on highly inbred laboratory strains and rodent malaria parasite infection models, which may differ substantially to their counterparts that transmit human malaria in the field. This review addresses the recent advances in high throughput transcription analyses of Anopheles responses to infection, and discusses considerations for the use of laboratory malaria infection models.

Animals↗

PubMed2004

[Strategies for bacterial virulence genes identification].

One of the recent preoccupations of medical microbiology has been to characterise the mechanisms of virulence of bacterial pathogens at the molecular level. One hundred years after Koch, Stanley Falkow proposed a new, molecular version of Koch's postulates to define avirulence gene: (a) the gene confers a certain phenotype to the studied bacteria, (b) inactivation of the gene abolishes the phenotype, (c)reintroduction of the gene restores the wild type to the mutant. Although this strategy, based upon mutagenesis and the use of experimental models, allows the identification of many genes, it is not comprehensive. Other methods can be used to complete the identification of virulence factors such as differential expression, either at the level of transcription (transcriptome) or at the level of protein expression (proteome). All these techniques are now supported by the data from complete genome sequencing projects. The pool of information obtained from these approaches allows the definition of the 'virulome', which is the assembly of factors a pathogen requires for virulence. Understanding the virulome will open the way to the development of new strategies for vaccination or the development of new generation of antimicrobials.

Animals↗

PubMed2005

Comparative genomics of nematodes.

Recent transcriptome and genome projects have dramatically expanded the biological data available across the phylum Nematoda. Here we summarize analyses of these sequences, which have revealed multiple unexpected results. Despite a uniform body plan, nematodes are more diverse at the molecular level than was previously recognized, with many species- and group-specific novel genes. In the genus Caenorhabditis, changes in chromosome arrangement, particularly local inversions, are also rapid, with breakpoints occurring at 50-fold the rate in vertebrates. Tylenchid plant parasitic nematode genomes contain several genes closely related to genes in bacteria, implicating horizontal gene transfer events in the origins of plant parasitism. Functional genomics techniques are also moving from Caenorhabditis elegans to application throughout the phylum. Soon, eight more draft nematode genome sequences will be available. This unique resource will underpin both molecular understanding of these most abundant metazoan organisms and aid in the examination of the dynamics of genome evolution in animals.

Animals↗

PubMed2000

On the optimization of classes for the assignment of unidentified reading frames in functional genomics programmes: the need for machine learning.

At present, the assignment of function to novel genes uncovered by the systematic genome-sequencing programmes is a problem. Many studies anticipate that this can be achieved by analysing patterns of gene expression via the transcriptome, proteome and metabolome. Thus, functional genomics is, in part, an exercise in pattern classification. Because many genes have known functional classes, the problem of predicting their functional class is a supervised learning problem. However, most pattern classification methods that have been applied to the problem have been unsupervised clustering methods. Consequently, the best classification tools have not always been used. Furthermore, the present functional classes are suboptimal and new unsupervised clustering methods are needed to improve them. Better-structured functional classes will facilitate the prediction of biochemically testable functions.

Animals↗

PubMed2003

Genomics of helicobacter 2003.

Research on Helicobacter pylori has been driven by the field of genomics since the release of the first of two complete genome sequences in 1997. In this review we highlight progress made in the last year. New bioinformatics tools and methods promise better functional and strain comparative analyses of individual genes. Sequence-based methods of strain comparison documented the coevolution of H. pylori with human populations. Several comprehensive analyses of the bacterial transcriptome were undertaken as well as two sophisticated studies of the transcriptional response of specific host tissues in response to H. pylori infection using different mouse models of H. pylori diseases. Some progress was made in developing genetic tools for mutational analysis of the genes required for infection. Finally, proteomic approaches were refined to delineate surface exposed and secreted proteins that represent potential antigens. In summary, while we do not have the full story of H. pylori, significant progress in deciphering the genome into functional biology has been made.

Genetic Variation↗

PubMed2026

ELISA (Embedding-Linked Interactive Single-cell Agent): an interpretable hybrid generative Artificial Intelligence agent for expression-grounded discovery in single-cell genomics.

Translating single-cell RNA sequencing (scRNA-seq) data into mechanistic biological hypotheses remains a critical bottleneck, as agentic AI systems lack direct access to transcriptomic representations while expression foundation models remain opaque to natural language. Here, we introduce ELISA (Embedding-Linked Interactive Single-cell Agent), an interpretable framework that unifies single-cell generative pretrained transformer expression embeddings with biomedical bidirectional encoder representations from transformers-based semantic retrieval and large-language model (LLM)-mediated interpretation for interactive single-cell discovery. An automatic query classifier routes inputs to gene marker scoring, semantic matching, or reciprocal rank fusion pipelines depending on whether the query is a gene signature, natural language concept, or mixture of both. Integrated analytical modules perform pathway activity scoring across 60+ gene sets, ligand-receptor interaction prediction using 280+ curated pairs, condition-aware comparative analysis, and cell-type proportion estimation, all operating directly on embedded data without access to the original count matrix. Benchmarked across six diverse scRNA-seq datasets spanning inflammatory lung disease, pediatric and adult cancers, organoid models, healthy tissue, and neurodevelopment, ELISA significantly outperforms CellWhisperer, a classical lexical retriever (BM25), and a random baseline in cell type retrieval (combined permutation test, $p < 2\times 10^{-5}$ for each), with particularly large gains on gene-signature queries (Cohen's $d = 5.98$ for mean reciprocal rank). ELISA replicates published biological findings (mean composite score 0.88), and generates candidate hypotheses through grounded LLM reasoning, bridging the gap between transcriptomic data exploration and biological discovery.

Generative Artificial Intelligence↗

PubMed2005

Midgut and salivary gland transcriptomes of the arbovirus vector Culicoides sonorensis (Diptera: Ceratopogonidae).

Numerous Culicoides spp. are important vectors of livestock or human disease pathogens. Transcriptome information from midguts and salivary glands of adult female Culicoides sonorensis provides new insight into vector biology. Of 1719 expressed sequence tags (ESTs) from adult serum-fed female midguts harvested within 5 h of feeding, twenty-eight clusters of serine proteases were derived. Four clusters encode putative iron binding proteins (FER1, FERL, PXDL1, PXDL2), and two clusters encode metalloendopeptidases (MDP6C, MDP6D) that probably function in bloodmeal catabolism. In addition, a diverse variety of housekeeping cDNAs were identified. Selected midgut protease transcripts were analysed by quantitative real-time PCR (q-PCR): TRY1_115 and MDP6C mRNAs were induced in adult female midguts upon feeding, whereas TRY1_156 and CHYM1 were abundant in midguts both before and immediately after feeding. Of 708 salivary gland ESTs analysed, clusters representing two new classes of protein families were identified: a new class of D7 proteins and a new class of Kunitz-type protease inhibitors. Additional cDNAs representing putative immunomodulatory proteins were also identified: 5' nucleotidases, antigen 5-related proteins, a hyaluronidase, a platelet-activating factor acetylhydrolase, mucins and several immune response cDNAs. Analysis by q-PCR showed that all D7 and Kunitz domain transcripts tested were highly enriched in female heads compared with other tissues and were generally absent from males. The mRNAs of two additional protease inhibitors, TFPI1 and TFPI2, were detected in salivary glands of paraffin-embedded females by in situ hybridization.

Allergens↗

PubMed2026

Biomarker Analysis from Patients with Metastatic PDAC Treated with TGFβ Antibody NIS793 plus Abraxane + Gemcitabine versus Abraxane + Gemcitabine Alone in a Phase II, Open-Label, Randomized Study.

PURPOSE: Transforming growth factor β (TGFβ) plays a dual role in cancer, acting as a tumor suppressor early in the disease but promoting progression and immune evasion when dysregulated. In pancreatic ductal adenocarcinoma (PDAC), TGFβ-driven desmoplasia fosters chemoresistance and immunosuppression, limiting therapeutic efficacy. NIS793, a fully human mAb targeting TGFβ, demonstrated antifibrotic and immunomodulatory activity in preclinical models and early-phase trials. PATIENTS AND METHODS: We conducted a randomized, open-label, phase II study in treatment-naïve patients with metastatic PDAC (mPDAC) to evaluate NIS793 ± spartalizumab (anti-PD-1) combined with nab-paclitaxel (or Abraxane)/gemcitabine (ABRA/GEM) versus ABRA/GEM alone. The primary endpoint was progression-free survival (PFS); secondary endpoints included overall survival (OS), safety, pharmacokinetics, and biomarker analyses. Exploratory assessments included paired tumor RNA sequencing, cell-free DNA profiling, and plasma proteomics. RESULTS: NIS793 demonstrated target engagement and suppression of TGFβ signaling, confirmed by transcriptomic and proteomic analyses. Stromal remodeling was evident, with significant downregulation of cancer-associated fibroblast markers (Acta2, Fap) and collagen-related signatures. Despite proof of mechanism, clinical efficacy was not observed: Median PFS and OS were comparable or numerically worse in the NIS793 arm versus control (HR for OS in NIS793 + ABRA/GEM vs. ABRA/GEM: 1.32; 95% confidence interval, 0.84-2.07). The safety profile was manageable, with no unexpected toxicities. Biomarker data revealed increased expression of neutrophil-related genes after treatment, suggesting potential induction of tumor-promoting inflammation. CONCLUSIONS: NIS793 effectively inhibited TGFβ signaling and led to stromal remodeling but failed to improve outcomes in mPDAC. These findings highlight the complexity of TGFβ biology and caution against its blockade in combination with chemotherapy for PDAC. Future strategies should consider context-dependent effects of TGFβ inhibition.

Humans↗

PubMed2025

Rare variants in MIR184 are a novel genetic cause of Fuchs endothelial corneal dystrophy.

PURPOSE: To identify novel genetic causes of Fuchs endothelial corneal dystrophy (FECD) within a genetically unsolved patient cohort lacking repeat expansions in the TCF4 gene (Exp-). METHODS: A rare variant analysis framework (CoCoRV) was applied to exome data, in combination with in silico modeling, luciferase reporter, and RNA-seq analysis to characterize transcriptome-wide consequences of identified variants. RESULTS: A gene burden analysis identified MIR184, a microRNA encoding gene, to be enriched for rare pathogenic variants within the studied Exp- FECD cohort. In total, 2 noncoding rare variants were identified in 4 unrelated FECD probands: NR_029705.1:n.58G>A and n.73G>T. Both variants altered highly conserved mature sequence residues, were predicted to induce hairpin structural changes, and were experimentally determined to disrupt microRNA-mRNA interactions. RNA-seq of transfected human corneal endothelial cells revealed that the mutants elicited distinct transcriptomic profiles. Enriched KEGG pathways included PI3K-Akt signaling, focal adhesion, and immune response, revealing shared pathogenic mechanisms between MIR184-associated FECD and the more common TCF4 repeat expansion-mediated form of disease. CONCLUSION: MIR184 variants are a novel rare genetic cause of FECD, and common pathways of transcriptomic dysregulation are shared across genetically distinct subtypes of the disease. These pathways may serve as future gene agnostic targets for therapeutic interventions.

Humans↗

PubMed2004

Digital transcriptome analysis in the aging cerebellum.

Serial analysis of gene expression (SAGE) was used to identify and quantify all expressed cerebellar genes in the adult (P92) and aged (P810) C57BL/6J mouse cerebellum. A "closest-neighbor" algorithm was used to differentiate low abundance tags from possible sequencing errors in both libraries. Unique tags were categorized into four groups: (1) novel genes; (2) ESTs; (3) RIKEN, KIA, and hypothetical genes; and (4) known genes. Known genes were further subdivided into functional categories based on the gene ontology classification, using a web-based program developed in this laboratory (MmSAGEClass). Comparison of adult and aged cerebellar libraries revealed several genes that were differentially expressed, including growth hormone and prolactin, both of which were markedly decreased in the aged cerebellum. In addition, several tags showing differential expression were not identified in the Unigene database and are likely to represent novel genes. The present SAGE data on the aged cerebellar transcriptome may reveal candidate genes involved in the aging process.

Aging↗

PubMed2002

Microarray analysis of bacterial pathogenicity.

The DNA microarray, a surface that contains an ordered arrangement of each identified open reading frame of a sequenced genome, is the engine of functional genomics. Its output, the expression profile, provides a genome wide snap-shot of the transcriptome. Refined by array-specific statistical instruments and data-mined by clustering algorithms and metabolic pathway databases, the expression profile discloses, at the transcriptional level, how the microbe adapts to new conditions of growth--the regulatory networks that govern the adaptive response and the metabolic and biosynthetic pathways that effect the new phenotype. Adaptation to host microenvironments underlies the capacity of infectious agents to persist in and damage host tissues. While monitoring the whole genome transcriptional response of bacterial pathogens within infected tissues has not been achieved, it is likely that the complex, tissue-specific response is but the sum of individual responses of the bacteria to specific physicochemical features that characterize the host milieu. These are amenable to experimentation in vitro and whole-genome expression studies of this kind have defined the transcriptional response to iron starvation, low oxygen, acid pH, quorum-sensing pheromones and reactive oxygen intermediates. These have disclosed new information about even well-studied processes and provide a portrait of the adapting bacterium as a 'system', rather than the product of a few genes or even a few regulons. Amongst the regulated genes that compose this adaptive system are transcription factors. Expression profiling experiments of transcription factor mutants delineate the corresponding regulatory cascade. The genetic basis for pathogenicity can also be studied by using microarray-based comparative genomics to characterize and quantify the extent of genetic variability within natural populations at the gene level of resolution. Also identified are differences between pathogen and commensal that point to possible virulence determinants or disclose evolutionary history. The host vigorously engages the pathogen; expression studies using host genome microarrays and bacterially infected cell cultures show that the initial host reaction is dominated by the innate immune response. However, within the complex expression profile of the host cell are components mediated by pathogen-specific determinants. In the future, the combined use of bacterial and host microarrays to study the same infected tissue will reveal the dialogue between pathogen and host in a gene-by-gene and site- and time-specific manner. Translating this conversation will not be easy and will probably require a combination of powerful bioinformatic tools and traditional experimental approaches--and considerable effort and time.

Animals↗

PubMed2005

Oxidative stress response in Paracoccidioides brasiliensis.

Survival of pathogenic fungi inside human hosts depends on evasion from the host immune system and adaptation to the host environment. Among different insults that Paracoccidioides brasiliensis has to handle are reactive oxygen and nitrogen species produced by the human host cells, and by its own metabolism. Knowing how the parasite deals with reactive species is important to understand how it establishes infection and survives within humans. The initiative to describe the P. brasiliensis transcriptome fostered new approaches to study oxidative stress response in this organism. By examining genes related to oxidative stress response, one can evaluate the parasite's ability to face this condition and infer about possible ways to overcome this ability. We report the results of a search of the P. brasiliensis assembled expressed sequence tag database for homologous sequences involved in oxidative stress response. We described several genes coding proteins involved in antioxidant defense, for example, catalase and superoxide dismutase isoenzymes, peroxiredoxin, cytochrome c peroxidase, glutathione synthesis enzymes, thioredoxin, and the transcription factors Yap1 and Skn7. The transcriptome analysis of P. brasiliensis reveals a pathogen that has many resources to combat reactive species. Besides characterizing the antioxidant defense system in P. brasiliensis, we also compared the ways in which different fungi respond to oxidative damage, and we identified the basic features of this response.

Antioxidants↗

PubMed1999

Yeast Upf proteins required for RNA surveillance affect global expression of the yeast transcriptome.

mRNAs are monitored for errors in gene expression by RNA surveillance, in which mRNAs that cannot be fully translated are degraded by the nonsense-mediated mRNA decay pathway (NMD). RNA surveillance ensures that potentially deleterious truncated proteins are seldom made. NMD pathways that promote surveillance have been found in a wide range of eukaryotes. In Saccharomyces cerevisiae, the proteins encoded by the UPF1, UPF2, and UPF3 genes catalyze steps in NMD and are required for RNA surveillance. In this report, we show that the Upf proteins are also required to control the total accumulation of a large number of mRNAs in addition to their role in RNA surveillance. High-density oligonucleotide arrays were used to monitor global changes in the yeast transcriptome caused by loss of UPF gene function. Null mutations in the UPF genes caused altered accumulation of hundreds of mRNAs. The majority were increased in abundance, but some were decreased. The same mRNAs were affected regardless of which of the three UPF gene was inactivated. The proteins encoded by UPF-dependent mRNAs were broadly distributed by function but were underrepresented in two MIPS (Munich Information Center for Protein Sequences) categories: protein synthesis and protein destination. In a UPF(+) strain, the average level of expression of UPF-dependent mRNAs was threefold lower than the average level of expression of all mRNAs in the transcriptome, suggesting that highly abundant mRNAs were underrepresented. We suggest a model for how the abundance of hundreds of mRNAs might be controlled by the Upf proteins.

Adaptor Proteins, Signal Transducing↗