The Candida albicans ENO1 gene encodes a transglutaminase involved in growth, cell division, morphogenesis, and osmotic protection.

Candida albicans is an opportunistic fungus that is part of the normal microflora commonly found in the human digestive tract and the normal mucosa or skin of healthy individuals. However, in immunocompromised individuals, it becomes a serious health concern and a threat to their lives and is ranked as the leading fungal infection in humans worldwide. As existing treatments for this infection are non-specific or under threat of developing resistance, there is a dire necessity to find new targets for designing specific drugs to defeat this fungus. Some authors reported the presence of the transglutaminase activity in Candida and Saccharomyces, but its identity remains unknown. We report here the phenotypic effects produced by the inhibition of transglutaminase enzymatic activity with cystamine, including growth inhibition of yeast cells, induction of autophagy in response to damage caused by cystamine, alteration of the normal yeast division pattern, changes in cell wall, and inhibition of the yeast-to-mycelium transition. The latter phenomenon was also observed in the C. albicans ATCC 26555 strain. Growth inhibition by cystamine was also determined in other Candida strains, demonstrating the importance of transglutaminase in these species. Finally, we identified enolase 1 as the cell wall protein responsible for TGase activity. After studying the inhibition of enzymatic activities with anti-CaEno1 antibodies and through bioinformatics studies, we suggest that the enolase and transglutaminase catalytic sites are localized in different domains of the protein. The aforementioned data indicate that TGase/Eno1 is a putative target for designing new drugs to control C. albicans infection.

Bioinformatics Tools for Proteomics Data Interpretation.

Biological systems function via intricate cellular processes and networks in which RNAs, metabolites, proteins and other cellular compounds have a precise role and are exquisitely regulated (Kumar and Mann, FEBS Lett 583(11):1703-1712, 2009). The development of high-throughput technologies, such as the Next Generation DNA Sequencing (NGS) and DNA microarrays for sequencing genomes or metagenomes, have triggered a dramatic increase in the last few years in the amount of information stored in the GenBank and UniProt Knowledgebase (UniProtKB). GenBank release 210, reported in October 2015, contains 202,237,081,559 nucleotides corresponding to 188,372,017 sequences, whilst there are only 1,222,635,267,498 nucleotides corresponding to 309,198,943 sequences from Whole Genome Shotgun (WGS) projects. In the case of UniProKB/Swiss-Prot, release 2015_12 (December 9, 2015) contains 196,219,159 amino acids that correspond to 550,116 entries. Meanwhile, UniProtKB/TrEMBL (release 2015_12 of December 9 2015) contains 1,838,851,8871 amino acids corresponding to 555,270,679 entries. Proteomics has also improved our knowledge of proteins that are being expressed in cells at a certain time of the cell cycle. It has also allowed the identification of molecules forming part of multiprotein complexes and an increasing number of posttranslational modifications (PTMs) that are present in proteins, as well as the variants of proteins expressed.

Data set of interactomes and metabolic pathways of proteins differentially expressed in brains with Alzheimer׳s disease.

Alzheimer׳s disease is one of the main causes of dementia in the elderly and its frequency is on the rise worldwide. It is considered the result of complex interactions between genetic and environmental factors, being many of them unknown. Therefore, there is a dire necessity for the identification of novel molecular players for the understanding of this disease. In this data article we determined the protein expression profiles of whole protein extracts from cortex regions of brains from patients with Alzheimer׳s disease in comparison to a normal brain. We identified 721 iTRAQ-labeled polypeptides with more than 95% in confidence. We analyzed all proteins that changed in their expression level and located them in the KEGG metabolic pathways, as well as in the mitochondrial complexes of the electron transport chain and ATP synthase. In addition, we analyzed the over- and sub-expressed polypeptides through IPA software, specifically Core I and Biomarkers I modules. Data in this article is related to the research article "Identification of proteins that are differentially expressed in brains with Alzheimer's disease using iTRAQ labeling and tandem mass spectrometry" (Minjarez et al., 2016) [1].

Identification of proteins that are differentially expressed in brains with Alzheimer's disease using iTRAQ labeling and tandem mass spectrometry.

Alzheimer's disease is one of the leading causes of dementia in the elderly. It is considered the result of complex events involving both genetic and environmental factors. To gain further insights into this complexity, we quantitatively analyzed the proteome of cortex region of brains from patients diagnosed with Alzheimer's disease, using a bottom-up proteomics approach. We identified 721 isobaric-tagged polypeptides. From this universe, 61 were found overexpressed and 69 subexpressed in three brains with Alzheimer's disease in comparison to a normal brain. We determined that the most affected processes involving the overexpressed polypeptides corresponded to ROS and stress responses. For the subexpressed polypeptides, the main processes affected were oxidative phosphorylation, organellar acidification and cytoskeleton. We used Drosophila to validate some of the hits, particularly those non-previously described as connected with the disease, such as Sideroflexin and Phosphoglucomutase-1. We manipulated their homolog genes in Drosophila models of Aß- and Tau-induced pathology. We found proteins that can either modify Aß toxicity, Tau toxicity or both, suggesting specific interactions with different pathways. This approach illustrates the potential of Drosophila to validate hits after MS studies and suggest that model organisms should be included in the pipeline to identify relevant targets for Alzheimer's disease. BIOLOGICAL SIGNIFICANCE: We report a set of differentially expressed proteins in three Alzheimer's disease brains in comparison to a normal brain. Our analyses allowed us to identify that the main affected pathways were ROS and stress responses, oxidative phosphorylation, organellar acidification and cytoskeleton. We validated some identified proteins using genetic models of Amyloid-ß and Tau-induced pathology in Drosophila melanogaster. With this approach, Sideroflexin and Phosphoglucomutase-1 were identified as novel proteins connected with Alzheimer's disease.

Data set of the protein expression profiles of Luminal A, Claudin-low and overexpressing HER2(+) breast cancer cell lines by iTRAQ labelling and tandem mass spectrometry.

Breast cancer is the most common and the leading cause of mortality in women worldwide. There is a dire necessity of the identification of novel molecules useful in diagnosis and prognosis. In this work we determined the differentially expression profiles of four breast cancer cell lines compared to a control cell line. We identified 1020 polypeptides labelled with iTRAQ with more than 95% in confidence. We analysed the common proteins in all breast cancer cell lines through IPA software (IPA core and Biomarkers). In addition, we selected the specific overexpressed and subexpressed proteins of the different molecular classes of breast cancer cell lines, and classified them according to protein class and biological process. Data in this article is related to the research article "Determination of the protein expression profiles of breast cancer cell lines by Quantitative Proteomics using iTRAQ Labelling and Tandem Mass Spectrometry" (Calderón-González et al. [1] in press).

Determination of the protein expression profiles of breast cancer cell lines by quantitative proteomics using iTRAQ labelling and tandem mass spectrometry.

Breast cancer is the principal cancer in women worldwide. Although there are serum tumor markers such as CEA and HER2, they are detected in advanced stages of the disease and used as progression and recurrence markers. Therefore, there is a necessity for the identification of new markers that might lead to an early detection and also provide evidence of an effective treatment. The aim of this work was to determine the differential protein expression profiles of four breast cancer cell lines in comparison to a normal control cell line by iTRAQ labelling and tandem mass spectrometry, in order to identify putative biomarkers of the disease. We identified 1,020 iTRAQ-labelled polypeptides with at least one peptide identified with more than 95% in confidence. Overexpressed polypeptides in all cancer cell lines were 78, whilst the subexpressed were 128. We categorised them with PANTHER program into biological processes, being the metabolic pathways the most affected. We detected six groups of proteins with the STRING program involved in DNA topology, glycolysis, translation initiation, splicing, pentose pathway, and proteasome degradation. The main subexpressed protein network included mitochondrial proteins involved in oxidative phosphorylation. We propose BAG6, DDX39, ANXA8 and COX4 as putative biomarkers in breast cancer. BIOLOGICAL SIGNIFICANCE: We report a set of differentially expressed proteins in the MCF7 and T47D (Luminal A), MDA-MB-231 (Claudin low) and SK-BR-3 (HER2(+)) breast cancer cell lines that have not been previously reported in breast cancer disease. From these proteins, we propose BAG6, DDX39, ANXA8 and COX4 as putative biomarkers in breast cancer. On the other hand, we propose sets of unique polypeptides in each breast cancer cell line that can be useful in the classification of different subtypes of breast cancer.