The atrial and ventricular myocardial proteome of end-stage lamin heart disease.

Lamins A/C (encoded by LMNA gene) can lead to dilated cardiomyopathy (DCM). This pilot study sought to explore the postgenomic phenotype of end-stage lamin heart disease. Consecutive patients with end-stage lamin heart disease (LMNA-group, n = 7) and ischaemic DCM (ICM-group, n = 7) undergoing heart transplantation were prospectively enrolled. Samples were obtained from left atrium (LA), left ventricle (LV), right atrium (RA), right ventricle (RV) and interventricular septum (IVS), avoiding the infarcted myocardial segments in the ICM-group. Samples were analysed using a discovery 'shotgun' proteomics approach. We found that 990 proteins were differentially abundant between LMNA and ICM samples with the LA being most perturbed (16-fold more than the LV). Abundance of lamin A/C protein was reduced, but lamin B increased in LMNA LA/RA tissue compared to ICM, but not in LV/RV. Carbonic anhydrase 3 (CA3) was over-abundant across all LMNA tissue samples (LA, LV, RA, RV, and IVS) when compared to ICM. Transthyretin was more abundant in the LV/RV of LMNA compared to ICM, while sarcomeric proteins such as titin and cardiac alpha-cardiac myosin heavy chain were generally less abundant in RA/LA of LMNA. Protein expression profiling and enrichment analysis pointed towards sarcopenia, extracellular matrix remodeling, deficient myocardial energetics, redox imbalances, and abnormal calcium handling in LMNA samples. Compared to ICM, end-stage lamin heart disease is a biventricular but especially a biatrial disease appearing to have an abundance of lamin B, CA3 and transthyretin, potentially hinting to compensatory responses.

Elovanoid-N34 modulates TXNRD1 key in protection against oxidative stress-related diseases.

The thioredoxin (TXN) system is an NADPH + H+/FAD redox-triggered effector that sustains homeostasis, bioenergetics, detoxifying drug networks, and cell survival in oxidative stress-related diseases. Elovanoid (ELV)-N34 is an endogenously formed lipid mediator in neural cells from omega-3 fatty acid precursors that modulate neuroinflammation and senescence gene programming when reduction-oxidation (redox) homeostasis is disrupted, enhancing cell survival. Limited proteolysis (LiP) screening of human retinal pigment epithelial (RPE) cells identified TXNRD1 isoforms 2, 3, or 5, the reductase of the TXN system, as an intracellular target of ELV-N34. TXNRD1 silencing confirmed that the ELV-N34 target was isoform 2 or 3. This lipid mediator induces TXNRD1 structure changes that modify the FAD interface domain, leading to its activity modulation. The addition of ELV-N34 decreased membrane and cytosolic TXNRD1 activity, suggesting localizations for the targeted reductase. These results show for the first time that the lipid mediator ELV-N34 directly modulates TXNRD1 activity, underling its protection in several pathologies when uncompensated oxidative stress (UOS) evolves.

The Essentials of Multiomics.

Within the last decade, the science of molecular testing has evolved from single gene and single protein analysis to broad molecular profiling as a standard of care, quickly transitioning from research to practice. Terms such as genomics, transcriptomics, proteomics, circulating omics, and artificial intelligence are now commonplace, and this rapid evolution has left us with a significant knowledge gap within the medical community. In this paper, we attempt to bridge that gap and prepare the physician in oncology for multiomics, a group of technologies that have gone from looming on the horizon to become a clinical reality. The era of multiomics is here, and we must prepare ourselves for this exciting new age of cancer medicine.

The metabolic growth limitations of petite cells lacking the mitochondrial genome.

Eukaryotic cells can survive the loss of their mitochondrial genome, but consequently suffer from severe growth defects. 'Petite yeasts', characterized by mitochondrial genome loss, are instrumental for studying mitochondrial function and physiology. However, the molecular cause of their reduced growth rate remains an open question. Here we show that petite cells suffer from an insufficient capacity to synthesize glutamate, glutamine, leucine and arginine, negatively impacting their growth. Using a combination of molecular genetics and omics approaches, we demonstrate the evolution of fast growth overcomes these amino acid deficiencies, by alleviating a perturbation in mitochondrial iron metabolism and by restoring a defect in the mitochondrial tricarboxylic acid cycle, caused by aconitase inhibition. Our results hence explain the slow growth of mitochondrial genome-deficient cells with a partial auxotrophy in four amino acids that results from distorted iron metabolism and an inhibited tricarboxylic acid cycle.

Slow Growth and Increased Spontaneous Mutation Frequency in Respiratory Deficient afo1- Yeast Suppressed by a Dominant Mutation in ATP3.

A yeast deletion mutation in the nuclear-encoded gene, AFO1, which codes for a mitochondrial ribosomal protein, led to slow growth on glucose, the inability to grow on glycerol or ethanol, and loss of mitochondrial DNA and respiration. We noticed that afo1- yeast readily obtains secondary mutations that suppress aspects of this phenotype, including its growth defect. We characterized and identified a dominant missense suppressor mutation in the ATP3 gene. Comparing isogenic slowly growing rho-zero and rapidly growing suppressed afo1- strains under carefully controlled fermentation conditions showed that energy charge was not significantly different between strains and was not causal for the observed growth properties. Surprisingly, in a wild-type background, the dominant suppressor allele of ATP3 still allowed respiratory growth but increased the petite frequency. Similarly, a slow-growing respiratory deficient afo1- strain displayed an about twofold increase in spontaneous frequency of point mutations (comparable to the rho-zero strain) while the suppressed strain showed mutation frequency comparable to the respiratory-competent WT strain. We conclude, that phenotypes that result from afo1- are mostly explained by rapidly emerging mutations that compensate for the slow growth that typically follows respiratory deficiency.

Induction of ER Stress by an AAV5 BDD FVIII Construct Is Dependent on the Strength of the Hepatic-Specific Promoter.

Adeno-associated virus 5 (AAV5)-human factor VIII-SQ (hFVIII-SQ; valoctocogene roxaparvovec) is an AAV-mediated product under evaluation for treatment of severe hemophilia A, which contains a B-domain-deleted hFVIII (hFVIII-SQ) transgene and a hybrid liver-specific promotor (HLP). To increase FVIII-SQ expression and reduce the vector dose required, a stronger promoter may be considered. However, because FVIII-SQ is a protein known to be difficult to fold and secrete, this could potentially induce endoplasmic reticulum (ER) stress. We evaluated the effect of two AAV5-hFVIII-SQ vectors with different liver-specific promoter strength (HLP << 100ATGB) on hepatic ER stress in mice. Five weeks after receiving vehicle or vector, the percentage of transduced hepatocytes and levels of liver hFVIII-SQ DNA and RNA increased dose dependently for both vectors. At lower doses, plasma hFVIII-SQ protein levels were higher for 100ATGB. This difference was attenuated at the highest dose. For 100ATGB, liver hFVIII-SQ protein accumulated dose dependently, with increased expression of ER stress markers at the highest dose, suggesting hepatocytes reached or exceeded their capacity to fold/secrete hFVIII-SQ. These data suggest that weaker promoters may require relatively higher doses to distribute expression load across a greater number of hepatocytes, whereas relatively stronger promoters may produce comparable levels of FVIII in fewer hepatocytes, with potential for ER stress.

Lysine harvesting is an antioxidant strategy and triggers underground polyamine metabolism.

Both single and multicellular organisms depend on anti-stress mechanisms that enable them to deal with sudden changes in the environment, including exposure to heat and oxidants. Central to the stress response are dynamic changes in metabolism, such as the transition from the glycolysis to the pentose phosphate pathway-a conserved first-line response to oxidative insults1,2. Here we report a second metabolic adaptation that protects microbial cells in stress situations. The role of the yeast polyamine transporter Tpo1p3-5 in maintaining oxidant resistance is unknown6. However, a proteomic time-course experiment suggests a link to lysine metabolism. We reveal a connection between polyamine and lysine metabolism during stress situations, in the form of a promiscuous enzymatic reaction in which the first enzyme of the polyamine pathway, Spe1p, decarboxylates lysine and forms an alternative polyamine, cadaverine. The reaction proceeds in the presence of extracellular lysine, which is taken up by cells to reach concentrations up to one hundred times higher than those required for growth. Such extensive harvest is not observed for the other amino acids, is dependent on the polyamine pathway and triggers a reprogramming of redox metabolism. As a result, NADPH-which would otherwise be required for lysine biosynthesis-is channelled into glutathione metabolism, leading to a large increase in glutathione concentrations, lower levels of reactive oxygen species and increased oxidant tolerance. Our results show that nutrient uptake occurs not only to enable cell growth, but when the nutrient availability is favourable it also enables cells to reconfigure their metabolism to preventatively mount stress protection.

Ice-Age Climate Adaptations Trap the Alpine Marmot in a State of Low Genetic Diversity.

Some species responded successfully to prehistoric changes in climate [1, 2], while others failed to adapt and became extinct [3]. The factors that determine successful climate adaptation remain poorly understood. We constructed a reference genome and studied physiological adaptations in the Alpine marmot (Marmota marmota), a large ground-dwelling squirrel exquisitely adapted to the "ice-age" climate of the Pleistocene steppe [4, 5]. Since the disappearance of this habitat, the rodent persists in large numbers in the high-altitude Alpine meadow [6, 7]. Genome and metabolome showed evidence of adaptation consistent with cold climate, affecting white adipose tissue. Conversely, however, we found that the Alpine marmot has levels of genetic variation that are among the lowest for mammals, such that deleterious mutations are less effectively purged. Our data rule out typical explanations for low diversity, such as high levels of consanguineous mating, or a very recent bottleneck. Instead, ancient demographic reconstruction revealed that genetic diversity was lost during the climate shifts of the Pleistocene and has not recovered, despite the current high population size. We attribute this slow recovery to the marmot's adaptive life history. The case of the Alpine marmot reveals a complicated relationship between climatic changes, genetic diversity, and conservation status. It shows that species of extremely low genetic diversity can be very successful and persist over thousands of years, but also that climate-adapted life history can trap a species in a persistent state of low genetic diversity.

Machine Learning Predicts the Yeast Metabolome from the Quantitative Proteome of Kinase Knockouts.

A challenge in solving the genotype-to-phenotype relationship is to predict a cell's metabolome, believed to correlate poorly with gene expression. Using comparative quantitative proteomics, we found that differential protein expression in 97 Saccharomyces cerevisiae kinase deletion strains is non-redundant and dominated by abundance changes in metabolic enzymes. Associating differential enzyme expression landscapes to corresponding metabolomes using network models provided reasoning for poor proteome-metabolome correlations; differential protein expression redistributes flux control between many enzymes acting in concert, a mechanism not captured by one-to-one correlation statistics. Mapping these regulatory patterns using machine learning enabled the prediction of metabolite concentrations, as well as identification of candidate genes important for the regulation of metabolism. Overall, our study reveals that a large part of metabolism regulation is explained through coordinated enzyme expression changes. Our quantitative data indicate that this mechanism explains more than half of metabolism regulation and underlies the interdependency between enzyme levels and metabolism, which renders the metabolome a predictable phenotype.

Proteotype profiling unmasks a viral signalling network essential for poxvirus assembly and transcriptional competence.

To orchestrate context-dependent signalling programmes, poxviruses encode two dual-specificity enzymes, the F10 kinase and the H1 phosphatase. These signalling mediators are essential for poxvirus production, yet their substrate profiles and systems-level functions remain enigmatic. Using a phosphoproteomic screen of cells infected with wild-type, F10 and H1 mutant vaccinia viruses, we systematically defined the viral signalling network controlled by these enzymes. Quantitative cross-comparison revealed 33 F10 and/or H1 phosphosites within 17 viral proteins. Using this proteotype dataset to inform genotype-phenotype relationships, we found that H1-deficient virions harbour a hidden hypercleavage phenotype driven by reversible phosphorylation of the virus protease I7 (S134). Quantitative phosphoproteomic profiling further revealed that the phosphorylation-dependent activity of the viral early transcription factor, A7 (Y367), underlies the transcription-deficient phenotype of H1 mutant virions. Together, these results highlight the utility of combining quantitative proteotype screens with mutant viruses to uncover proteotype-phenotype-genotype relationships that are masked by classical genetic studies.

Cost-effective generation of precise label-free quantitative proteomes in high-throughput by microLC and data-independent acquisition.

Quantitative proteomics is key for basic research, but needs improvements to satisfy an increasing demand for large sample series in diagnostics, academia and industry. A switch from nanoflowrate to microflowrate chromatography can improve throughput and reduce costs. However, concerns about undersampling and coverage have so far hampered its broad application. We used a QTOF mass spectrometer of the penultimate generation (TripleTOF5600), converted a nanoLC system into a microflow platform, and adapted a SWATH regime for large sample series by implementing retention time- and batch correction strategies. From 3 µg to 5 µg of unfractionated tryptic digests that are obtained from proteomics-typical amounts of starting material, microLC-SWATH-MS quantifies up to 4000 human or 1750 yeast proteins in an hour or less. In the acquisition of 750 yeast proteomes, retention times varied between 2% and 5%, and quantified the typical peptide with 5-8% signal variation in replicates, and below 20% in samples acquired over a five-months period. Providing precise quantities without being dependent on the latest hardware, our study demonstrates that the combination of microflow chromatography and data-independent acquisition strategies has the potential to overcome current bottlenecks in academia and industry, enabling the cost-effective generation of precise quantitative proteomes in large scale.

Variable repeats in the eukaryotic polyubiquitin gene ubi4 modulate proteostasis and stress survival.

Ubiquitin conjugation signals for selective protein degradation by the proteasome. In eukaryotes, ubiquitin is encoded both as a monomeric ubiquitin unit fused to a ribosomal gene and as multiple ubiquitin units in tandem. The polyubiquitin gene is a unique, highly conserved open reading frame composed solely of tandem repeats, yet it is still unclear why cells utilize this unusual gene structure. Using the Saccharomyces cerevisiae UBI4 gene, we show that this multi-unit structure allows cells to rapidly produce large amounts of ubiquitin needed to respond to sudden stress. The number of ubiquitin units encoded by UBI4 influences cellular survival and the rate of ubiquitin-proteasome system (UPS)-mediated proteolysis following heat stress. Interestingly, the optimal number of repeats varies under different types of stress indicating that natural variation in repeat numbers may optimize the chance for survival. Our results demonstrate how a variable polycistronic transcript provides an evolutionary alternative for gene copy number variation.Eukaryotic cells rely on the ubiquitin-proteasome system for selective degradation of proteins, a process vital to organismal fitness. Here the authors show that the number of repeats in the polyubiquitin gene is evolutionarily unstable within and between yeast species, and that this variability may tune the cell's capacity to respond to sudden environmental perturbations.

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.

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

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 (H2 O2 , 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.

Analysis of Drosophila melanogaster proteome dynamics during embryonic development by a combination of label-free proteomics approaches.

During embryogenesis, organisms undergo considerable cellular remodelling requiring the combined action of thousands of proteins. In case of the well-studied model Drosophila melanogaster, transcriptomic studies, most notably from the modENCODE project, have described in detail changes in gene expression at the mRNA level across development. Although such data are clearly very useful to understand how the genome is regulated during embryogenesis, it is important to understand how changes in gene expression are reflected at the level of the proteome. In this study, we describe a combination of two quantitative label-free approaches, SWATH and data-dependent acquisition, to monitor changes in protein expression across a timecourse of D. melanogaster embryonic development. We demonstrate that both approaches provide robust and reproducible methods for the analysis of proteome changes. In a preliminary analysis of Drosophila embryogenesis, we identified several pathways, including the heat-shock response, nuclear protein import and energy production that are regulated during embryo development. In some cases changes in protein expression mirrored transcript levels across development, whereas other proteins showed signatures of post-transcriptional regulation. Taken together, our pilot study provides a solid platform for a more detailed exploration of the embryonic proteome.

Methionine Metabolism Alters Oxidative Stress Resistance via the Pentose Phosphate Pathway.

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.

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 other's 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.

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.

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

BACKGROUND: While 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. RESULTS: We 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. CONCLUSIONS: The 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.

Mitochondria in ageing: there is metabolism beyond the ROS.

Mitochondria are responsible for a series of metabolic functions. Superoxide leakage from the respiratory chain and the resulting cascade of reactive oxygen species-induced damage, as well as mitochondrial metabolism in programmed cell death, have been intensively studied during ageing in single-cellular and higher organisms. Changes in mitochondrial physiology and metabolism resulting in ROS are thus considered to be hallmarks of ageing. In this review, we address 'other' metabolic activities of mitochondria, carbon metabolism (the TCA cycle and related underground metabolism), the synthesis of Fe/S clusters and the metabolic consequences of mitophagy. These important mitochondrial activities are hitherto less well-studied in the context of cellular and organismic ageing. In budding yeast, they strongly influence replicative, chronological and hibernating lifespan, connecting the diverse ageing phenotypes studied in this single-cellular model organism. Moreover, there is evidence that similar processes equally contribute to ageing of higher organisms as well. In this scenario, increasing loss of metabolic integrity would be one driving force that contributes to the ageing process. Understanding mitochondrial metabolism may thus be required for achieving a unifying theory of eukaryotic ageing.