Jakob Vowinckel

The beauty of being (label)-free: sample preparation methods for SWATH-MS and next-generation targeted proteomics

The combination of qualitative analysis with label-free quantification has greatly facilitated the throughput and flexibility of novel proteomic techniques. However, such methods rely heavily on robust and reproducible sample preparation procedures. Here, we benchmark a selection of in gel, on filter, and in solution digestion workflows for their application in label-free proteomics. Each procedure was associated with differing advantages and disadvantages. The in gel methods interrogated were cost effective, but were limited in throughput and digest efficiency. Filter-aided sample preparations facilitated reasonable processing times and yielded a balanced representation of membrane proteins, but led to a high signal variation in quantification experiments. Two in solution digest protocols, however, gave optimal performance for label-free proteomics. A protocol based on the detergent RapiGest led to the highest number of detected proteins at second-best signal stability, while a protocol based on acetonitrile-digestion, RapidACN, scored best in throughput and signal stability but came second in protein identification. In addition, we compared label-free data dependent (DDA) and data independent (SWATH) acquisition on a TripleTOF 5600 instrument. While largely similar in protein detection, SWATH outperformed DDA in quantification, reducing signal variation and markedly increasing the number of precisely quantified peptides.The combination of qualitative analysis with label-free quantification has greatly facilitated the throughput and flexibility of novel proteomic techniques. However, such methods rely heavily on robust and reproducible sample preparation procedures. Here, we benchmark a selection of in gel, on filter, and in solution digestion workflows for their application in label-free proteomics. Each procedure was associated with differing advantages and disadvantages. The in gel methods interrogated were cost effective, but were limited in throughput and digest efficiency. Filter-aided sample preparations facilitated reasonable processing times and yielded a balanced representation of membrane proteins, but led to a high signal variation in quantification experiments. Two in solution digest protocols, however, gave optimal performance for label-free proteomics. A protocol based on the detergent RapiGest led to the highest number of detected proteins at second-best signal stability, while a protocol based on acetonitrile-digestion, RapidACN, scored best in throughput and signal stability but came second in protein identification. In addition, we compared label-free data dependent (DDA) and data independent (SWATH) acquisition on a TripleTOF 5600 instrument. While largely similar in protein detection, SWATH outperformed DDA in quantification, reducing signal variation and markedly increasing the number of precisely quantified peptides.

Novel roles for biogenic monoamines: from monoamines in transglutaminase-mediated post-translational protein modification to monoaminylation deregulation diseases

Functional protein serotonylation is a newly recognized post‐translational modification with the primary biogenic monoamine (PBMA) serotonin (5‐HT). This covalent protein modification is catalyzed by transglutaminases (TGs) and, for example, acts in the constitutive activation of small GTPases. Multiple physiological roles have been identified since its description in 2003 and, importantly, deregulated serotonylation was shown in the etiology of bleeding disorders, primary pulmonary hypertension and diabetes. The PBMAs 5‐HT, histamine, dopamine, and norepinephrine all act as neurotransmitters in the nervous system and as hormones in non‐neuronal tissues, which points out their physiological importance. In analogy to serotonylation we have found that also the other PBMAs act through the TG‐catalyzed mechanisms of ‘histaminylation’, ‘dopaminylation’ and ‘norepinephrinylation’. Therefore, PBMAs deploy a considerable portion of their effects via protein monoaminylation in addition to their canonical receptor‐mediated signaling. Here, the implications of these newly identified post‐translational modifications are presented and discussed. Furthermore, the potential regulatory roles of protein monoaminylation in small GTPase, heterotrimeric G‐protein and lipid signaling, as well as in modulating metabolic enzymes and nuclear processes, are critically assessed.

The metabolic background is a global player in Saccharomyces gene expression epistasis

The regulation of gene expression in response to nutrient availability is fundamental to the genotype–phenotype relationship. The metabolic–genetic make-up of the cell, as reflected in auxotrophy, is hence likely to be a determinant of gene expression. Here, we address the importance of the metabolic–genetic background by monitoring transcriptome, proteome and metabolome in a repertoire of 16 Saccharomyces cerevisiae laboratory backgrounds, combinatorially perturbed in histidine, leucine, methionine and uracil biosynthesis. The metabolic background affected up to 85% of the coding genome. Suggesting widespread confounding, these transcriptional changes show, on average, 83% overlap between unrelated auxotrophs and 35% with previously published transcriptomes generated for non-metabolic gene knockouts. Background-dependent gene expression correlated with metabolic flux and acted, predominantly through masking or suppression, on 88% of transcriptional interactions epistatically. As a consequence, the deletion of the same metabolic gene in a different background could provoke an entirely different transcriptional response. Propagating to the proteome and scaling up at the metabolome, metabolic background dependencies reveal the prevalence of metabolism-dependent epistasis at all regulatory levels. Urging a fundamental change of the prevailing laboratory practice of using auxotrophs and nutrient supplemented media, these results reveal epistatic intertwining of metabolism with gene expression on the genomic scale.

Using the canary genome to decipher the evolution of hormone-sensitive gene regulation in seasonal singing birds

BackgroundWhile the song of all songbirds is controlled by the same neural circuit, the hormone dependence of singing behavior varies greatly between species. For this reason, songbirds are ideal organisms to study ultimate and proximate mechanisms of hormone-dependent behavior and neuronal plasticity.ResultsWe present the high quality assembly and annotation of a female 1.2-Gbp canary genome. Whole genome alignments between the canary and 13 genomes throughout the bird taxa show a much-conserved synteny, whereas at the single-base resolution there are considerable species differences. These differences impact small sequence motifs like transcription factor binding sites such as estrogen response elements and androgen response elements. To relate these species-specific response elements to the hormone-sensitivity of the canary singing behavior, we identify seasonal testosterone-sensitive transcriptomes of major song-related brain regions, HVC and RA, and find the seasonal gene networks related to neuronal differentiation only in the HVC. Testosterone-sensitive up-regulated gene networks of HVC of singing males concerned neuronal differentiation. Among the testosterone-regulated genes of canary HVC, 20% lack estrogen response elements and 4 to 8% lack androgen response elements in orthologous promoters in the zebra finch.ConclusionsThe canary genome sequence and complementary expression analysis reveal intra-regional evolutionary changes in a multi-regional neural circuit controlling seasonal singing behavior and identify gene evolution related to the hormone-sensitivity of this seasonal singing behavior. Such genes that are testosterone- and estrogen-sensitive specifically in the canary and that are involved in rewiring of neurons might be crucial for seasonal re-differentiation of HVC underlying seasonal song patterning.

Tpo1-mediated spermine and spermidine export controls cell cycle delay and times antioxidant protein expression during the oxidative stress response

Cells counteract oxidative stress by altering metabolism, cell cycle and gene expression. However, the mechanisms that coordinate these adaptations are only marginally understood. Here we provide evidence that timing of these responses in yeast requires export of the polyamines spermidine and spermine. We show that during hydrogen peroxide (H2O2) exposure, the polyamine transporter Tpo1 controls spermidine and spermine concentrations and mediates induction of antioxidant proteins, including Hsp70, Hsp90, Hsp104 and Sod1. Moreover, Tpo1 determines a cell cycle delay during adaptation to increased oxidant levels, and affects H2O2 tolerance. Thus, central components of the stress response are timed through Tpo1‐controlled polyamine export.

A mammalianized synthetic nitroreductase gene for high-level expression

BackgroundThe nitroreductase/5-(azaridin-1-yl)-2,4-dinitrobenzamide (NTR/CB1954) enzyme/prodrug system is considered as a promising candidate for anti-cancer strategies by gene-directed enzyme prodrug therapy (GDEPT) and has recently entered clinical trials. It requires the genetic modification of tumor cells to express the E. coli enzyme nitroreductase that bioactivates the prodrug CB1954 to a powerful cytotoxin. This metabolite causes apoptotic cell death by DNA interstrand crosslinking. Enhancing the enzymatic NTR activity for CB1954 should improve the therapeutical potential of this enzyme-prodrug combination in cancer gene therapy.MethodsWe performed de novo synthesis of the bacterial nitroreductase gene adapting codon usage to mammalian preferences. The synthetic gene was investigated for its expression efficacy and ability to sensitize mammalian cells to CB1954 using western blotting analysis and cytotoxicity assays.ResultsIn our study, we detected cytoplasmic protein aggregates by expressing GFP-tagged NTR in COS-7 cells, suggesting an impaired translation by divergent codon usage between prokaryotes and eukaryotes. Therefore, we generated a synthetic variant of the nitroreductase gene, called ntro, adapted for high-level expression in mammalian cells. A total of 144 silent base substitutions were made within the bacterial ntr gene to change its codon usage to mammalian preferences. The codon-optimized ntro either tagged to gfp or c-myc showed higher expression levels in mammalian cell lines. Furthermore, the ntro rendered several cell lines ten times more sensitive to the prodrug CB1954 and also resulted in an improved bystander effect.ConclusionOur results show that codon optimization overcomes expression limitations of the bacterial ntr gene in mammalian cells, thereby improving the NTR/CB1954 system at translational level for cancer gene therapy in humans.

Methionine Metabolism Alters Oxidative Stress Resistance via the Pentose Phosphate Pathway

Abstract Nutrient uptake and metabolism have a significant impact on the way cells respond to stress. The amino acid methionine is, in particular, a key player in the oxidative stress response, and acting as a reactive oxygen species scavenger, methionine is implicated in caloric restriction phenotypes and aging. We here provide evidence that some effects of methionine in stress situations are indirect and caused by altered activity of the nicotinamide adenine dinucleotide phosphate (NADPH) producing oxidative part of the pentose phosphate pathway (PPP). In Saccharomyces cerevisiae, both methionine prototrophic (MET15) and auxotrophic (met15Δ) cells supplemented with methionine showed an increase in PPP metabolite concentrations downstream of the NADPH producing enzyme, 6-phosphogluconate dehydrogenase. Proteomics revealed this enzyme to also increase in expression compared to methionine self-synthesizing cells. Oxidant tolerance was increased in cells preincubated with methionine; however, this effect was abolished when flux through the oxidative PPP was prevented by deletion of its rate limiting enzyme, ZWF1. Stress resistance phenotypes that follow methionine supplementation hence involve the oxidative PPP. Effects of methionine on oxidative metabolism, stress signaling, and aging have thus to be seen in the context of an altered activity of this NADP reducing pathway. Antioxid. Redox Signal. 24, 543–547.

MitoLoc: A method for the simultaneous quantification of mitochondrial network morphology and membrane potential in single cells.

Mitochondria assemble into flexible networks. Here we present a simple method for the simultaneous quantification of mitochondrial membrane potential and network morphology that is based on computational co-localisation analysis of differentially imported fluorescent marker proteins. Established in, but not restricted to, Saccharomyces cerevisiae, MitoLoc reproducibly measures changes in membrane potential induced by the uncoupling agent CCCP, by oxidative stress, in respiratory deficient cells, and in ∆fzo1, ∆ref2, and ∆dnm1 mutants that possess fission and fusion defects. In combination with super-resolution images, MitoLoc uses 3D reconstruction to calculate six geometrical classifiers which differentiate network morphologies in ∆fzo1, ∆ref2, and ∆dnm1 mutants, under oxidative stress and in cells lacking mtDNA, even when the network is fragmented to a similar extent. We find that mitochondrial fission and a decline in membrane potential do regularly, but not necessarily, co-occur. MitoLoc hence simplifies the measurement of mitochondrial membrane potential in parallel to detect morphological changes in mitochondrial networks. Marker plasmid open-source software as well as the mathematical procedures are made openly available.

Self-establishing communities enable cooperative metabolite exchange in a eukaryote

Metabolite exchange among co-growing cells is frequent by nature, however, is not necessarily occurring at growth-relevant quantities indicative of non-cell-autonomous metabolic function. Complementary auxotrophs of Saccharomyces cerevisiae amino acid and nucleotide metabolism regularly fail to compensate for each others deficiencies upon co-culturing, a situation which implied the absence of growth-relevant metabolite exchange interactions. Contrastingly, we find that yeast colonies maintain a rich exometabolome and that cells prefer the uptake of extracellular metabolites over self-synthesis, indicators of ongoing metabolite exchange. We conceived a system that circumvents co-culturing and begins with a self-supporting cell that grows autonomously into a heterogeneous community, only able to survive by exchanging histidine, leucine, uracil, and methionine. Compensating for the progressive loss of prototrophy, self-establishing communities successfully obtained an auxotrophic composition in a nutrition-dependent manner, maintaining a wild-type like exometabolome, growth parameters, and cell viability. Yeast, as a eukaryotic model, thus possesses extensive capacity for growth-relevant metabolite exchange and readily cooperates in metabolism within progressively establishing communities. DOI: http://dx.doi.org/10.7554/eLife.09943.001

Cell-to-cell heterogeneity emerges as consequence of metabolic cooperation in a synthetic yeast community

Abstract Cells that grow together respond heterogeneously to stress even when they are genetically similar. Metabolism, a key determinant of cellular stress tolerance, may be one source of this phenotypic heterogeneity, however, this relationship is largely unclear. We used self‐establishing metabolically cooperating (SeMeCo) yeast communities, in which metabolic cooperation can be followed on the basis of genotype, as a model to dissect the role of metabolic cooperation in single‐cell heterogeneity. Cells within SeMeCo communities showed to be highly heterogeneous in their stress tolerance, while the survival of each cell under heat or oxidative stress, was strongly determined by its metabolic specialization. This heterogeneity emerged for all metabolite exchange interactions studied (histidine, leucine, uracil, and methionine) as well as oxidant (H2O2, diamide) and heat stress treatments. In contrast, the SeMeCo community collectively showed to be similarly tolerant to stress as wild‐type populations. Moreover, stress heterogeneity did not establish as sole consequence of metabolic genotype (auxotrophic background) of the single cell, but was observed only for cells that cooperated according to their metabolic capacity. We therefore conclude that phenotypic heterogeneity and cell to cell differences in stress tolerance are emergent properties when cells cooperate in metabolism.