An inventory of the Aspergillus niger secretome by combining in silico predictions with shotgun proteomics data

<p>Abstract</p> <p>Background</p> <p>The ecological niche occupied by a fungal species, its pathogenicity and its usefulness as a microbial cell factory to a large degree depends on its secretome. Protein secretion usually requires the presence of a N-terminal signal peptide (SP) and by scanning for this feature using available highly accurate SP-prediction tools, the fraction of potentially secreted proteins can be directly predicted. However, prediction of a SP does not guarantee that the protein is actually secreted and current <it>in silico </it>prediction methods suffer from gene-model errors introduced during genome annotation.</p> <p>Results</p> <p>A majority rule based classifier that also evaluates signal peptide predictions from the best homologs of three neighbouring <it>Aspergillus </it>species was developed to create an improved list of potential signal peptide containing proteins encoded by the <it>Aspergillus niger </it>genome. As a complement to these <it>in silico </it>predictions, the secretome associated with growth and upon carbon source depletion was determined using a shotgun proteomics approach. Overall, some 200 proteins with a predicted signal peptide were identified to be secreted proteins. Concordant changes in the secretome state were observed as a response to changes in growth/culture conditions. Additionally, two proteins secreted via a non-classical route operating in <it>A. niger </it>were identified.</p> <p>Conclusions</p> <p>We were able to improve the <it>in silico </it>inventory of <it>A. niger </it>secretory proteins by combining different gene-model predictions from neighbouring Aspergilli and thereby avoiding prediction conflicts associated with inaccurate gene-models. The expected accuracy of signal peptide prediction for proteins that lack homologous sequences in the proteomes of related species is 85%. An experimental validation of the predicted proteome confirmed <it>in silico </it>predictions.</p

Aspergillus as a multi-purpose cell factory: current status and perspectives

Aspergilli have a long history in biotechnology as expression platforms for the production of food ingredients, pharmaceuticals and enzymes. The achievements made during the last years, however, have the potential to revolutionize Aspergillus biotechnology and to assure Aspergillus a dominant place among microbial cell factories. This mini-review will highlight most recent breakthroughs in fundamental and applied Aspergillus research with a focus on new molecular tools, techniques and products. New trends and concepts related to Aspergillus genomics and systems biology will be discussed as well as the challenges that have to be met to integrate omics data with metabolic engineering attempts

Genomic sequencing in clinical trials

Human genome sequencing is the process by which the exact order of nucleic acid base pairs in the 24 human chromosomes is determined. Since the completion of the Human Genome Project in 2003, genomic sequencing is rapidly becoming a major part of our translational research efforts to understand and improve human health and disease. This article reviews the current and future directions of clinical research with respect to genomic sequencing, a technology that is just beginning to find its way into clinical trials both nationally and worldwide. We highlight the currently available types of genomic sequencing platforms, outline the advantages and disadvantages of each, and compare first- and next-generation techniques with respect to capabilities, quality, and cost. We describe the current geographical distributions and types of disease conditions in which these technologies are used, and how next-generation sequencing is strategically being incorporated into new and existing studies. Lastly, recent major breakthroughs and the ongoing challenges of using genomic sequencing in clinical research are discussed

Diagnostic and prognostic value of long noncoding RNAs as biomarkers in urothelial carcinoma

Many long noncoding RNAs (lncRNAs) are deregulated in cancer and contribute to oncogenesis. In urothelial carcinoma (UC), several lncRNAs have been reported to be overexpressed and proposed as biomarkers. As most reports have not been confirmed independently in large tissue sets, we aimed to validate the diagnostic and prognostic value of lncRNA upregulation in independent cohorts of UC patients. Thus, expression of seven lncRNA candidates (GAS5, H19, linc-UBC1, MALAT1, ncRAN, TUG1, UCA1) was measured by RT-qPCR in cell lines and tissues and correlated to clinicopathological parameters including follow-up data (set 1: N n = 10; T n = 106). Additionally, publicly available TCGA data was investigated for differential expression in UC tissues (set 2: N n = 19; T n = 252,) and correlation to overall survival (OS). All proposed candidates tended to be upregulated in tumour tissues, with the exception of MALAT1, which was rather diminished in cancer tissues of both data sets. However, strong overexpression was generally limited to individual tumour tissues and statistically significant overexpression was only observed for UCA1, TUG1, ncRAN and linc-UBC1 in tissue set 2, but for no candidate in set 1. Altered expression of individual lncRNAs was associated with overall survival, but not consistently between both patient cohorts. Interestingly, lower expression of TUG1 in a subset of UC patients with muscle-invasive tumours was significantly correlated with worse OS in both cohorts. Further analysis revealed that tumours with low TUG1 expression are characterized by a basal-squamous-like subtype signature accounting for the association with poor outcome. In conclusion, our study demonstrates that overexpression of the candidate lncRNAs is found in many UC cases, but does not occur consistently and strongly enough to provide reliable diagnostic or prognostic value as an individual biomarker. Subtype-dependent expression patterns of lncRNAs like TUG1 could become useful to stratify patients by molecular subtype, thus aiding personalized treatments

Urinary extracellular vesicles: A position paper by the Urine Task Force of the International Society for Extracellular Vesicles

Urine is commonly used for clinical diagnosis and biomedical research. The discovery of extracellular vesicles (EV) in urine opened a new fast-growing scientific field. In the last decade urinary extracellular vesicles (uEVs) were shown to mirror molecular processes as well as physiological and pathological conditions in kidney, urothelial and prostate tissue. Therefore, several methods to isolate and characterize uEVs have been developed. However, methodological aspects of EV separation and analysis, including normalization of results, need further optimization and standardization to foster scientific advances in uEV research and a subsequent successful translation into clinical practice. This position paper is written by the Urine Task Force of the Rigor and Standardization Subcommittee of ISEV consisting of nephrologists, urologists, cardiologists and biologists with active experience in uEV research. Our aim is to present the state of the art and identify challenges and gaps in current uEV-based analyses for clinical applications. Finally, recommendations for improved rigor, reproducibility and interoperability in uEV research are provided in order to facilitate advances in the field

Fungal enzyme sets for plant polysaccharide degradation

Enzymatic degradation of plant polysaccharides has many industrial applications, such as within the paper, food, and feed industry and for sustainable production of fuels and chemicals. Cellulose, hemicelluloses, and pectins are the main components of plant cell wall polysaccharides. These polysaccharides are often tightly packed, contain many different sugar residues, and are branched with a diversity of structures. To enable efficient degradation of these polysaccharides, fungi produce an extensive set of carbohydrate-active enzymes. The variety of the enzyme set differs between fungi and often corresponds to the requirements of its habitat. Carbohydrate-active enzymes can be organized in different families based on the amino acid sequence of the structurally related catalytic modules. Fungal enzymes involved in plant polysaccharide degradation are assigned to at least 35 glycoside hydrolase families, three carbohydrate esterase families and six polysaccharide lyase families. This mini-review will discuss the enzymes needed for complete degradation of plant polysaccharides and will give an overview of the latest developments concerning fungal carbohydrate-active enzymes and their corresponding families

Myceliophthora thermophila M77 utilizes hydrolytic and oxidative mechanisms to deconstruct biomass

Biomass is abundant, renewable and useful for biofuel production as well as chemical priming for plastics and composites. Deconstruction of biomass by enzymes is perceived as recalcitrant while an inclusive breakdown mechanism remains to be discovered. Fungi such as Myceliophthora thermophila M77 appear to decompose natural biomass sources quite well. This work reports on this fungus fermentation property while producing cellulolytic enzymes using natural biomass substrates. Little hydrolytic activity was detected, insufficient to explain the large amount of biomass depleted in the process. Furthermore, this work makes a comprehensive account of extracellular proteins and describes how secretomes redirect their qualitative protein content based on the nature and chemistry of the nutritional source. Fungus grown on purified cellulose or on natural biomass produced secretomes constituted by: cellobiohydrolases, cellobiose dehydrogenase, B-1,3 glucanase, B-glucosidases, aldose epimerase, glyoxal oxidase, GH74 xyloglucanase, galactosidase, aldolactonase and polysaccharide monooxygenases. Fungus grown on a mixture of purified hemicellulose fractions (xylans, arabinans and arabinoxylans) produced many enzymes, some of which are listed here: xylosidase, mixed B-1,3(4) glucanase, B-1,3 glucanases, B-glucosidases, B-mannosidase, B-glucosidases, galactosidase, chitinases, polysaccharide lyase, endo B-1,6 galactanase and aldose epimerase. Secretomes produced on natural biomass displayed a comprehensive set of enzymes involved in hydrolysis and oxidation of cellulose, hemicellulose-pectin and lignin. The participation of oxidation reactions coupled to lignin decomposition in the breakdown of natural biomass may explain the discrepancy observed for cellulose decomposition in relation to natural biomass fermentation experiments.Peer reviewedMicrobiology and Molecular GeneticsBiochemistry and Microbiolog