Karin Lanthaler

Genomic analysis of the secretion stress response in the enzyme-producing cell factory Aspergillus niger.

BackgroundFilamentous fungi such as Aspergillus niger have a high capacity secretory system and are therefore widely exploited for the industrial production of native and heterologous proteins. However, in most cases the yields of non-fungal proteins are significantly lower than those obtained for fungal proteins. One well-studied bottleneck appears to be the result of mis-folding of heterologous proteins in the ER during early stages of secretion, with related stress responses in the host, including the unfolded protein response (UPR). This study aims at uncovering transcriptional and translational responses occurring in A. niger exposed to secretion stress.ResultsA genome-wide transcriptional analysis of protein secretion-related stress responses was determined using Affymetrix DNA GeneChips and independent verification for selected genes. Endoplasmic reticulum (ER)-associated stress was induced either by chemical treatment of the wild-type cells with dithiothreitol (DTT) or tunicamycin, or by expressing a human protein, tissue plasminogen activator (t-PA). All of these treatments triggered the UPR, as shown by the expression levels of several well-known UPR target genes. The predicted proteins encoded by most of the up-regulated genes function as part of the secretory system including chaperones, foldases, glycosylation enzymes, vesicle transport proteins, and ER-associated degradation proteins. Several genes were down-regulated under stress conditions and these included several genes that encode secreted enzymes. Moreover, translational regulation under ER stress was investigated by polysomal fractionation. This analysis confirmed the post-transcriptional control of hacA expression and highlighted that differential translation also occurs during ER stress, in particular for some genes encoding secreted proteins or proteins involved in ribosomal biogenesis and assembly.ConclusionThis is first genome-wide analysis of both transcriptional and translational events following protein secretion stress. Insight has been gained into the molecular basis of protein secretion and secretion-related stress in an effective protein-secreting fungus, and provides an opportunity to identify target genes for manipulation in strain improvement strategies.

Common features and interesting differences in transcriptional responses to secretion stress in the fungi Trichoderma reesei and Saccharomyces cerevisiae.

BackgroundSecretion stress is caused by compromised folding, modification or transport of proteins in the secretory pathway. In fungi, induction of genes in response to secretion stress is mediated mainly by the unfolded protein response (UPR) pathway. This study aims at uncovering transcriptional responses occurring in the filamentous fungi Trichoderma reesei exposed to secretion stress and comparing these to those found in the yeast Saccharomyces cerevisiae.ResultsChemostat cultures of T. reesei expressing human tissue plasminogen activator (tPA) and batch bioreactor cultures treated with dithiothreitol (DTT) to prevent correct protein folding were analysed with cDNA subtraction and cDNA-amplified fragment length polymorphism (AFLP) experiments. ESTs corresponding to 457 unique genes putatively induced under secretion stress were isolated and the expression pattern of 60 genes was confirmed by Northern analysis. Expression of these genes was also studied in a strain over-expressing inositol-requiring enzyme 1 (IREI) protein, a sensor for the UPR pathway. To compare the data with that of S. cerevisiae, published transcriptome profiling data on various stress responses in S. cerevisiae was reanalysed. The genes up-regulated in response to secretion stress included a large number of secretion related genes in both organisms. In addition, analysis of T. reesei revealed up regulation of the cpc1 transcription factor gene and nucleosomal genes. The induction of the cpcA and histone gene H4 were shown to be induced also in cultures of Aspergillus nidulans treated with DTT.ConclusionAnalysis of the genes induced under secretion stress has revealed novel features in the stress response in T. reesei and in filamentous fungi. We have demonstrated that in addition to the previously rather well characterised induction of genes for many ER proteins or secretion related proteins also other types of responses exist.

Global absolute quantification of a proteome: Challenges in the deployment of a QconCAT strategy

In this paper, we discuss the challenge of large‐scale quantification of a proteome, referring to our programme that aims to define the absolute quantity, in copies per cell, of at least 4000 proteins in the yeast Saccharomyces cerevisiae. We have based our strategy on the well‐established method of stable isotope dilution, generating isotopically labelled peptides using QconCAT technology, in which artificial genes, encoding concatenations of tryptic fragments as surrogate quantification standards, are designed, synthesised de novo and expressed in bacteria using stable isotopically enriched media. A known quantity of QconCAT is then co‐digested with analyte proteins and the heavy:light isotopologues are analysed by mass spectrometry to yield absolute quantification. This workflow brings issues of optimal selection of quantotypic peptides, their assembly into QconCATs, expression, purification and deployment.

Further developments towards a genome-scale metabolic model of yeast

BackgroundTo date, several genome-scale network reconstructions have been used to describe the metabolism of the yeast Saccharomyces cerevisiae, each differing in scope and content. The recent community-driven reconstruction, while rigorously evidenced and well annotated, under-represented metabolite transport, lipid metabolism and other pathways, and was not amenable to constraint-based analyses because of lack of pathway connectivity.ResultsWe have expanded the yeast network reconstruction to incorporate many new reactions from the literature and represented these in a well-annotated and standards-compliant manner. The new reconstruction comprises 1102 unique metabolic reactions involving 924 unique metabolites - significantly larger in scope than any previous reconstruction. The representation of lipid metabolism in particular has improved, with 234 out of 268 enzymes linked to lipid metabolism now present in at least one reaction. Connectivity is emphatically improved, with more than 90% of metabolites now reachable from the growth medium constituents. The present updates allow constraint-based analyses to be performed; viability predictions of single knockouts are comparable to results from in vivo experiments and to those of previous reconstructions.ConclusionsWe report the development of the most complete reconstruction of yeast metabolism to date that is based upon reliable literature evidence and richly annotated according to MIRIAM standards. The reconstruction is available in the Systems Biology Markup Language (SBML) and via a publicly accessible database http://www.comp-sys-bio.org/yeastnet/.

Transcriptome analysis of recombinant protein secretion by Aspergillus nidulans and the unfolded-protein response in vivo

ABSTRACT Filamentous fungi have a high capacity for producing large amounts of secreted proteins, a property that has been exploited for commercial production of recombinant proteins. However, the secretory pathway, which is key to the production of extracellular proteins, is rather poorly characterized in filamentous fungi compared to yeast. We report the effects of recombinant protein secretion on gene expression levels in Aspergillus nidulans by directly comparing a bovine chymosin-producing strain with its parental wild-type strain in continuous culture by using expressed sequence tag microarrays. This approach demonstrated more subtle and specific changes in gene expression than those observed when mimicking the effects of protein overproduction by using a secretion blocker. The impact of overexpressing a secreted recombinant protein more closely resembles the unfolded-protein response in vivo.

Implications of the dominant role of transporters in drug uptake by cells

Drug entry into cells was previously believed to be via diffusion through the lipid bilayer of the cell membrane, with the contribution to uptake by transporter proteins being of only marginal importance. Now, however, drug uptake is understood to be mainly transporter-mediated. This suggests that uptake transporters may be a major determinant of idiosyncratic drug response and a site at which drug-drug interactions occur. Accurately modelling drug pharmacokinetics is a problem of Systems Biology and requires knowledge of both the transporters with which a drug interacts and where those transporters are expressed in the body. Current physiology-based pharmacokinetic models mostly attempt to model drug disposition from the biophysical properties of the drug, drug uptake by diffusion being thereby an implicit assumption. It is clear that the incorporation of transporter proteins and their drug interactions into such models will greatly improve them. We discuss methods by which tissue localisations and transporter interactions can be determined. We propose a yeast-based transporter expression system for the initial screening of drugs for their cognate transporters. Finally, the central importance of computational modelling of transporter substrate preferences by structure-activity relationships is discussed.

Role of the bga1-Encoded Extracellular β-Galactosidase of Hypocrea jecorina in Cellulase Induction by Lactose

ABSTRACT Lactose is the only soluble and economically feasible carbon source for the production of cellulases or heterologous proteins regulated by cellulase expression signals by Hypocrea jecorina (Trichoderma reesei). We investigated the role of the major β-galactosidase of H. jecorina in lactose metabolism and cellulase induction. A genomic copy of the bga1 gene was cloned, and this copy encodes a 1,023-amino-acid protein with a 20-amino-acid signal sequence. This protein has a molecular mass of 109.3 kDa, belongs to glycosyl hydrolase family 35, and is the major extracellular β-galactosidase during growth on lactose. Its transcript was abundant during growth on l-arabinose and l-arabinitol but was much less common when the organism was grown on lactose, d-galactose, galactitol, d-xylose, and xylitol. Δbga1 strains grow more slowly and accumulate less biomass on lactose, but the cellobiohydrolase I and II gene expression and the final cellulase yields were comparable to those of the parental strain. Overexpression of bga1 under the control of the pyruvate kinase promoter reduced the lag phase, increased growth on lactose, and limited transcription of cellobiohydrolases. We detected an additional extracellular β-galactosidase activity that was not encoded by bga1 but no intracellular β-galactosidase activity. In conclusion, cellulase production on lactose occurs when β-galactosidase activity levels are low but decreases as the β-galactosidase activities increase. The data indicate that bga1-encoded β-galactosidase activity is a critical factor for cellulase production on lactose.

Absolute Quantification of the Glycolytic Pathway in Yeast: DEPLOYMENT OF A COMPLETE QconCAT APPROACH

The availability of label-free data derived from yeast cells (based on the summed intensity of the three strongest, isoform-specific peptides) permitted a preliminary assessment of protein abundances for glycolytic proteins. Following this analysis, we demonstrate successful application of the QconCAT technology, which uses recombinant DNA techniques to generate artificial concatamers of large numbers of internal standard peptides, to the quantification of enzymes of the glycolysis pathway in the yeast Saccharomyces cerevisiae. A QconCAT of 88 kDa (59 tryptic peptides) corresponding to 27 isoenzymes was designed and built to encode two or three analyte peptides per protein, and after stable isotope labeling of the standard in vivo, protein levels were determined by LC-MS, using ultra high performance liquid chromatography-coupled mass spectrometry. We were able to determine absolute protein concentrations between 14,000 and 10 million molecules/cell. Issues such as efficiency of extraction and completeness of proteolysis are addressed, as well as generic factors such as optimal quantotypic peptide selection and expression. In addition, the same proteins were quantified by intensity-based label-free analysis, and both sets of data were compared with other quantification methods.

Direct and Absolute Quantification of over 1800 Yeast Proteins via Selected Reaction Monitoring

Defining intracellular protein concentration is critical in molecular systems biology. Although strategies for determining relative protein changes are available, defining robust absolute values in copies per cell has proven significantly more challenging. Here we present a reference data set quantifying over 1800 Saccharomyces cerevisiae proteins by direct means using protein-specific stable-isotope labeled internal standards and selected reaction monitoring (SRM) mass spectrometry, far exceeding any previous study. This was achieved by careful design of over 100 QconCAT recombinant proteins as standards, defining 1167 proteins in terms of copies per cell and upper limits on a further 668, with robust CVs routinely less than 20%. The selected reaction monitoring-derived proteome is compared with existing quantitative data sets, highlighting the disparities between methodologies. Coupled with a quantification of the transcriptome by RNA-seq taken from the same cells, these data support revised estimates of several fundamental molecular parameters: a total protein count of ∼100 million molecules-per-cell, a median of ∼1000 proteins-per-transcript, and a linear model of protein translation explaining 70% of the variance in translation rate. This work contributes a “gold-standard” reference yeast proteome (including 532 values based on high quality, dual peptide quantification) that can be widely used in systems models and for other comparative studies.

Quantitative analysis of chaperone network throughput in budding yeast.

The network of molecular chaperones mediates the folding and translocation of the many proteins encoded in the genome of eukaryotic organisms, as well as a response to stress. It has been particularly well characterised in the budding yeast, Saccharomyces cerevisiae, where 63 known chaperones have been annotated and recent affinity purification and MS/MS experiments have helped characterise the attendant network of chaperone targets to a high degree. In this study, we apply our QconCAT methodology to directly quantify the set of yeast chaperones in absolute terms (copies per cell) via SRM MS. Firstly, we compare these to existing quantitative estimates of these yeast proteins, highlighting differences between approaches. Secondly, we cast the results into the context of the chaperone target network and show a distinct relationship between abundance of individual chaperones and their targets. This allows us to characterise the ‘throughput’ of protein molecules passing through individual chaperones and their groups on a proteome‐wide scale in an unstressed model eukaryote for the first time. The results demonstrate specialisations of the chaperone classes, which display different overall workloads, efficiencies and preference for the sub‐cellular localisation of their targets. The novel integration of the interactome data with quantification supports re‐estimates of the level of protein throughout going through molecular chaperones. Additionally, although chaperones target fewer than 40% of annotated proteins we show that they mediate the folding of the majority of protein molecules (∼62% of the total protein flux in the cell), highlighting their importance.