Comparative functional analysis of the Caenorhabditis elegans and Drosophila melanogaster proteomes

Amino acid sequence encodes protein abundance shaped by protein stability at reduced synthesis cost

Understanding what drives protein abundance is essential to biology, medicine, and biotechnology. Driven by evolutionary selection, an amino acid sequence is tailored to meet the required abundance of a proteome, underscoring the intricate relationship between sequence and functional demand. Yet, the specific role of amino acid sequences in determining proteome abundance remains elusive. Here we show that the amino acid sequence alone encodes over half of protein abundance variation across all domains of life, ranging from bacteria to mouse and human. With an attempt to go beyond predictions, we trained a manageable-size Transformer model to interpret latent factors predictive of protein abundances. Intuitively, the model's attention focused on the protein's structural features linked to stability and metabolic costs related to protein synthesis. To probe these relationships, we introduce MGEM (Mutation Guided by an Embedded Manifold), a methodology for guiding protein abundance through sequence modifications. We find that mutations which increase predicted abundance have significantly altered protein polarity and hydrophobicity, underscoring a connection between protein structural features and abundance. Through molecular dynamics simulations we revealed that abundance-enhancing mutations possibly contribute to protein thermostability by increasing rigidity, which occurs at a lower synthesis cost.

Stabilizing selection and adaptation shape cis and trans gene expression variation in C. elegans

An outstanding question in the evolution of gene expression is the relative influence of neutral processes versus natural selection, including adaptive change driven by directional selection as well as stabilizing selection, which may include compensatory dynamics. These forces shape patterns of gene expression variation within and between species, including the regulatory mechanisms governing expression in cis and trans. In this study, we interrogate intraspecific gene expression variation among seven wild C. elegans strains, with varying degrees of genomic divergence from the reference strain N2, leveraging this system's unique advantages to comprehensively evaluate gene expression evolution. By capturing allele-specific and between-strain changes in expression, we characterize the regulatory architecture and inheritance mode of gene expression variation within C. elegans and assess their relationship to nucleotide diversity, genome evolutionary history, gene essentiality, and other biological factors. We conclude that stabilizing selection is a dominant influence in maintaining expression phenotypes within the species, and the discovery that genes with higher overall expression tend to exhibit fewer expression differences supports this conclusion, as do widespread instances of cis differences compensated in trans. Moreover, analyses of human expression data replicate our finding that higher expression genes have less variable expression. We also observe evidence for directional selection driving expression divergence, and that expression divergence accelerates with increasing genomic divergence. To provide community access to the data from this first analysis of allele-specific expression in C. elegans, we introduce an interactive web application, where users can submit gene-specific queries to view expression, regulatory pattern, inheritance mode, and other information: https://wildworm.biosci.gatech.edu/ase/.

Selection Across the Three-Dimensional Structure of Venom Proteins from North American Scolopendromorph Centipedes

Gene duplication followed by nucleotide differentiation is one of the simplest mechanisms to develop new functions for genes. However, the evolutionary processes underlying the divergence of multigene families remain controversial. We used multigene families found within the diversity of toxic proteins in centipede venom to test two hypotheses related to venom evolution: the two-speed mode of venom evolution and the rapid accumulation of variation in exposed residues (RAVER) model. The two-speed mode of venom evolution proposes that different types of selection impact ancient and younger venomous lineages with negative selection being the predominant form in ancient lineages and positive selection being the dominant form in younger lineages. The RAVER hypothesis proposes that, instead of different types of selection acting on different ages of venomous lineages, the different types of selection will selectively contribute to amino acid variation based on whether the residue is exposed to the solvent where it can potentially interact directly with toxin targets. This hypothesis parallels the longstanding understanding of protein evolution that suggests that residues found within the structural or active regions of the protein will be under negative or purifying selection, and residues that do not form part of these areas will be more prone to positive selection. To test these two hypotheses, we compared the venom of 26 centipedes from the order Scolopendromorpha from six currently recognized species from across North America using both transcriptomics and proteomics. We first estimated their phylogenetic relationships and uncovered paraphyly among the genus Scolopendra and evidence for cryptic diversity among currently recognized species. Using our phylogeny, we then characterized the diverse venom components from across the identified clades using a combination of transcriptomics and proteomics. We conducted selection-based analyses in the context of predicted three-dimensional properties of the venom proteins and found support for both hypotheses. Consistent with the two-speed hypothesis, we found a prevalence of negative selection across all proteins. Consistent with the RAVER hypothesis, we found evidence of positive selection on solvent-exposed residues, with structural and less-exposed residues showing stronger signal for negative selection. Through the use of phylogenetics, transcriptomics, proteomics, and selection-based analyses, we were able to describe the evolution of venom from an ancient venomous lineage and support principles of protein evolution that directly relate to multigene family evolution.

Single-tissue proteomics in Caenorhabditis elegans reveals proteins resident in intestinal lysosome-related organelles

The nematode intestine is the primary site for nutrient uptake and storage as well as the synthesis of biomolecules; lysosome-related organelles known as gut granules are important for many of these functions. Aspects of intestine biology are not well understood, including the export of the nutrients it imports and the molecules it synthesizes, as well as the complete functions and protein content of the gut granules. Here, we report a mass spectrometry (MS)-based proteomic analysis of the intestine of the Caenorhabditis elegans and of its gut granules. Overall, we identified approximately 5,000 proteins each in the intestine and the gonad and showed that most of these proteins can be detected in samples extracted from a single worm, suggesting the feasibility of individual-level genetic analysis using proteomes. Comparing proteomes and published transcriptomes of the intestine and the gonad, we identified proteins that appear to be synthesized in the intestine and then transferred to the gonad. To identify gut granule proteins, we compared the proteome of individual intestines deficient in gut granules to the wild type. The identified gut granule proteome includes proteins known to be exclusively localized to the granules and additional putative gut granule proteins. We selected two of these putative gut granule proteins for validation via immunohistochemistry, and our successful confirmation of both suggests that our strategy was effective in identifying the gut granule proteome. Our results demonstrate the practicability of single-tissue MS-based proteomic analysis in small organisms and in its future utility.

Quantitative proteome dynamics across embryogenesis in a model chordate

The evolution of gene expression programs underlying the development of vertebrates remains poorly characterized. Here, we present a comprehensive proteome atlas of the model chordate Ciona, covering eight developmental stages and ∼7,000 translated genes, accompanied by a multi-omics analysis of co-evolution with the vertebrate Xenopus. Quantitative proteome comparisons argue against the widely held hourglass model, based solely on transcriptomic profiles, whereby peak conservation is observed during mid-developmental stages. Our analysis reveals maximal divergence at these stages, particularly gastrulation and neurulation. Together, our work provides a valuable resource for evaluating conservation and divergence of multi-omics profiles underlying the diversification of vertebrates.

Spatiotemporal analysis of mRNA-protein relationships enhances transcriptome-based developmental inference

Elucidating the complex relationships between mRNA and protein expression at high spatiotemporal resolution is critical for unraveling multilevel gene regulation and enhancing mRNA-based developmental analyses. In this study, we conduct a single-cell analysis of mRNA and protein expression of transcription factors throughout C. elegans embryogenesis. Initially, cellular co-presence of mRNA and protein is low, increasing to a medium-high level (73%) upon factoring in delayed protein synthesis and long-term protein persistence. These factors substantially affect mRNA-protein concordance, leading to potential inaccuracies in mRNA-reliant gene detection and specificity characterization. Building on the learned relationship, we infer protein presence from mRNA expression and demonstrate its utility in identifying tissue-specific genes and elucidating relationships between genes and cells. This approach facilitates identifying the role of sptf-1/SP7 in neuronal lineage development. Collectively, this study provides insights into gene expression dynamics during rapid embryogenesis and approaches for improving the efficacy of transcriptome-based developmental analyses.

Advancing Strongyloides omics data: bridging the gap with Caenorhabditis elegans

Among nematodes, the free-living model organism Caenorhabditis elegans boasts the most advanced portfolio of high-quality omics data. The resources available for parasitic nematodes, including Strongyloides spp., however, are lagging behind. While C. elegans remains the most tractable nematode and has significantly advanced our understanding of many facets of nematode biology, C. elegans is not suitable as a surrogate system for the study of parasitism and it is important that we improve the omics resources available for parasitic nematode species. Here, we review the omics data available for Strongyloides spp. and compare the available resources to those for C. elegans and other parasitic nematodes. The advancements in C. elegans omics offer a blueprint for improving omics-led research in Strongyloides. We suggest areas of priority for future research that will pave the way for expansions in omics resources and technologies. This article is part of the Theo Murphy meeting issue 'Strongyloides: omics to worm-free populations'.

Evaluating the Performance of Widely Used Phylogenetic Models for Gene Expression Evolution

Phylogenetic comparative methods are increasingly used to test hypotheses about the evolutionary processes that drive divergence in gene expression among species. However, it is unknown whether the distributional assumptions of phylogenetic models designed for quantitative phenotypic traits are realistic for expression data and importantly, the reliability of conclusions of phylogenetic comparative studies of gene expression may depend on whether the data is well described by the chosen model. To evaluate this, we first fit several phylogenetic models of trait evolution to 8 previously published comparative expression datasets, comprising a total of 54,774 genes with 145,927 unique gene-tissue combinations. Using a previously developed approach, we then assessed how well the best model of the set described the data in an absolute (not just relative) sense. First, we find that Ornstein-Uhlenbeck models, in which expression values are constrained around an optimum, were the preferred models for 66% of gene-tissue combinations. Second, we find that for 61% of gene-tissue combinations, the best-fit model of the set was found to perform well; the rest were found to be performing poorly by at least one of the test statistics we examined. Third, we find that when simple models do not perform well, this appears to be typically a consequence of failing to fully account for heterogeneity in the rate of the evolution. We advocate that assessment of model performance should become a routine component of phylogenetic comparative expression studies; doing so can improve the reliability of inferences and inspire the development of novel models.

PGP-14 establishes a polar lipid permeability barrier within the C. elegans pharyngeal cuticle

The cuticles of ecdysozoan animals are barriers to material loss and xenobiotic insult. Key to this barrier is lipid content, the establishment of which is poorly understood. Here, we show that the p-glycoprotein PGP-14 functions coincidently with the sphingomyelin synthase SMS-5 to establish a polar lipid barrier within the pharyngeal cuticle of the nematode C. elegans. We show that PGP-14 and SMS-5 are coincidentally expressed in the epithelium that surrounds the anterior pharyngeal cuticle where PGP-14 localizes to the apical membrane. pgp-14 and sms-5 also peak in expression at the time of new cuticle synthesis. Loss of PGP-14 and SMS-5 dramatically reduces pharyngeal cuticle staining by Nile Red, a key marker of polar lipids, and coincidently alters the nematode's response to a wide-range of xenobiotics. We infer that PGP-14 exports polar lipids into the developing pharyngeal cuticle in an SMS-5-dependent manner to safeguard the nematode from environmental insult.

Dopaminergic modulation by quercetin: In silico and in vivo evidence using Caenorhabditis elegans as a model

Quercetin is a flavonol widely distributed in plants and has various described biological functions. Several studies have reported on its ability to restore neuronal function in a wide variety of disease models, including animal models of neurodegenerative disorders such as Parkinson's disease. Quercetin per se can act as a neuroprotector/neuromodulator, especially in diseases related to impaired dopaminergic neurotransmission. However, little is known about how quercetin interacts with the dopaminergic machinery. Here we employed the nematode Caenorhabditis elegans to study this putative interaction. After observing behavioral modulation, mutant analysis and gene expression in C. elegans upon exposure to quercetin at a concentration that does not protect against MPTP, we constructed a homology-based dopamine transporter protein model to conduct a docking study. This led to suggestive evidence on how quercetin may act as a dopaminergic modulator by interacting with C. elegans' dopamine transporter and alter the nematode's exploratory behavior. Consistent with this model, quercetin controls C. elegans behavior in a way dependent on the presence of both the dopamine transporter (dat-1), which is up-regulated upon quercetin exposure, and the dopamine receptor 2 (dop-2), which appears to be mandatory for dat-1 up-regulation. Our data propose an interaction with the dopaminergic machinery that may help to establish the effects of quercetin as a neuromodulator.

Evaluating the Performance of Widely Used Phylogenetic Models for Gene Expression Evolution

Phylogenetic comparative methods are increasingly used to test hypotheses about the evolutionary processes that drive divergence in gene expression among species. However, it is unknown whether the distributional assumptions of phylogenetic models designed for quantitative phenotypic traits are realistic for expression data and importantly, the reliability of conclusions of phylogenetic comparative studies of gene expression may depend on whether the data is well-described by the chosen model. To evaluate this, we first fit several phylogenetic models of trait evolution to 8 previously published comparative expression datasets, comprising a total of 54,774 genes with 145,927 unique gene-tissue combinations. Using a previously developed approach, we then assessed how well the best model of the set described the data in an absolute (not just relative) sense. First, we find that Ornstein-Uhlenbeck models, in which expression values are constrained around an optimum, were the preferred model for 66% of gene-tissue combinations. Second, we find that for 61% of gene-tissue combinations, the best fit model of the set was found to perform well; the rest were found to be performing poorly by at least one of the test statistics we examined. Third, we find that when simple models do not perform well, this appears to be typically a consequence of failing to fully account for heterogeneity in the rate of the evolution. We advocate that assessment of model performance should become a routine component of phylogenetic comparative expression studies; doing so can improve the reliability of inferences and inspire the development of novel models.

On the Decoupling of Evolutionary Changes in mRNA and Protein Levels

Variation in gene expression across lineages is thought to explain much of the observed phenotypic variation and adaptation. The protein is closer to the target of natural selection but gene expression is typically measured as the amount of mRNA. The broad assumption that mRNA levels are good proxies for protein levels has been undermined by a number of studies reporting moderate or weak correlations between the two measures across species. One biological explanation for this discrepancy is that there has been compensatory evolution between the mRNA level and regulation of translation. However, we do not understand the evolutionary conditions necessary for this to occur nor the expected strength of the correlation between mRNA and protein levels. Here, we develop a theoretical model for the coevolution of mRNA and protein levels and investigate the dynamics of the model over time. We find that compensatory evolution is widespread when there is stabilizing selection on the protein level; this observation held true across a variety of regulatory pathways. When the protein level is under directional selection, the mRNA level of a gene and the translation rate of the same gene were negatively correlated across lineages but positively correlated across genes. These findings help explain results from comparative studies of gene expression and potentially enable researchers to disentangle biological and statistical hypotheses for the mismatch between transcriptomic and proteomic data.

What do we mean by "aging"? Questions and perspectives revealed by studies in Drosophila

What is the nature of aging, and how best can we study it? Here, using a series of questions that highlight differing perspectives about the nature of aging, we ask how data from Drosophila melanogaster at the organismal, tissue, cellular, and molecular levels shed light on the complex interactions among the phenotypes associated with aging. Should aging be viewed as an individual's increasing probability of mortality over time or as a progression of physiological states? Are all age-correlated changes in physiology detrimental to vigor or are some compensatory changes that maintain vigor? Why do different age-correlated functions seem to change at different rates in a single individual as it ages? Should aging be considered as a single, integrated process across the scales of biological resolution, from organismal to molecular, or must we consider each level of biological scale as a separate, distinct entity? Viewing aging from these differing perspectives yields distinct but complementary interpretations about the properties and mechanisms of aging and may offer a path through the complexities related to understanding the nature of aging.

Decoupling of evolutionary changes in mRNA and protein levels

Variation in gene expression across lineages is thought to explain much of the observed phenotypic variation and adaptation. The protein is closer to the target of natural selection but gene expression is typically measured as the amount of mRNA. The broad assumption that mRNA levels are good proxies for protein levels has been undermined by a number of studies reporting moderate or weak correlations between the two measures across species. One biological explanation for this discrepancy is that there has been compensatory evolution between the mRNA level and regulation of translation. However, we do not understand the evolutionary conditions necessary for this to occur nor the expected strength of the correlation between mRNA and protein levels. Here we develop a theoretical model for the coevolution of mRNA and protein levels and investigate the dynamics of the model over time. We find that compensatory evolution is widespread when there is stabilizing selection on the protein level, which is true across a variety of regulatory pathways. When the protein level is under directional selection, the mRNA level of a gene and its translation rate of the same gene were negatively correlated across lineages but positively correlated across genes. These findings help explain results from comparative studies of gene expression and potentially enable researchers to disentangle biological and statistical hypotheses for the mismatch between transcriptomic and proteomic studies.

Nvp63 and nvPIWIL1 Suppress Retrotransposon Activation in the Sea Anemone Nematostella vectensis

The transcription factors p63 and p73 have high similarity to the tumor suppressor protein p53. While the importance of p53 in DNA damage control is established, the functions of p63 or p73 remain elusive. Here, we analyzed nvp63, the cnidarian homologue of p63, that is expressed in the mesenteries of the starlet sea anemone Nematostella vectensis and that is activated in response to DNA damage. We used ultraviolet light (UV) to induce DNA damage and determined the chromatin-bound proteome with quantitative, bottom-up proteomics. We found that genotoxic stress or nvp63 knockdown recruited the protein nvPIWIL1, a homologue of the piRNA-binding PIWI protein family. Knockdown nvPIWIL1 increased protein expression from open reading frames (ORFs) that overlap with class I and II transposable element DNA sequences in the genome of N. vectensis. UV irradiation induced apoptosis, and apoptosis was reduced in the absence of nvp63 but increased with the loss of nvPIWIL1. Loss of nvp63 increased the presence of class I LTR and non-LTR retrotransposon but not of class II DNA transposon-associated protein products. These results suggest that an evolutionary early function of nvp63 might be to control genome stability in response to activation of transposable elements, which induce DNA damage during reintegration in the genome.

A spatiotemporal reconstruction of the C. elegans pharyngeal cuticle reveals a structure rich in phase-separating proteins

How the cuticles of the roughly 4.5 million species of ecdysozoan animals are constructed is not well understood. Here, we systematically mine gene expression datasets to uncover the spatiotemporal blueprint for how the chitin-based pharyngeal cuticle of the nematode Caenorhabditis elegans is built. We demonstrate that the blueprint correctly predicts expression patterns and functional relevance to cuticle development. We find that as larvae prepare to molt, catabolic enzymes are upregulated and the genes that encode chitin synthase, chitin cross-linkers, and homologs of amyloid regulators subsequently peak in expression. Forty-eight percent of the gene products secreted during the molt are predicted to be intrinsically disordered proteins (IDPs), many of which belong to four distinct families whose transcripts are expressed in overlapping waves. These include the IDPAs, IDPBs, and IDPCs, which are introduced for the first time here. All four families have sequence properties that drive phase separation and we demonstrate phase separation for one exemplar in vitro. This systematic analysis represents the first blueprint for cuticle construction and highlights the massive contribution that phase-separating materials make to the structure.

Exogenous extracellular matrix proteins decrease cardiac fibroblast activation in stiffening microenvironment through CAPG

Controlling fibrosis is an essential part of regenerating the post-ischemic heart. In the post-ischemic heart, fibroblasts differentiate to myofibroblasts that produce collagen-rich matrix to physically stabilize the infarct area. Infarct models in adult mice result in permanent scarring unlike newborn animals which fully regenerate. Decellularized extracellular matrix (dECM) hydrogels derived from early-aged hearts have been shown to be a transplantable therapy that preserves heart function and stimulates cardiomyocyte proliferation and vascularization. In this study, we investigate the anti-fibrotic effects of injectable dECM hydrogels in a cardiac explant model in the context of age-associated tissue compliance. Treatments with adult and fetal dECM hydrogels were tested for molecular effects on cardiac fibroblast activation and fibrosis. Altered sensitivity of fibroblasts to the mechanosignaling of the remodeling microenvironment was evaluated by manipulating the native extracellular matrix in explants and also with elastomeric substrates in the presence of dECM hydrogels. The injectable fetal dECM hydrogel treatment decreases fibroblast activation and contractility and lowers the stiffness-mediated increases in fibroblast activation observed in stiffened explants. The anti-fibrotic effect of dECM hydrogel is most observable at highest stiffness. Experiments with primary cells on elastomeric substrates with dECM treatment support this phenomenon. Transcriptome analysis indicated that dECM hydrogels affect cytoskeleton related signaling including Macrophage capping protein (CAPG) and Leupaxin (LPXN). CAPG was down-regulated by the fetal dECM hydrogel. LPXN expression was decreased by stiffening the explants; however, this effect was reversed by dECM hydrogel treatment. Pharmacological disruption of cytoskeleton polymerization lowered fibroblast activation and CAPG levels. Knocking down CAPG expression with siRNA inhibited fibroblast activation and collagen deposition. Collectively, fibroblast activation is dependent on cooperative action of extracellular molecular signals and mechanosignaling by cytoskeletal integrity.

Comparing mRNA expression and protein abundance in MDR Mycobacterium tuberculosis: Novel protein candidates, Rv0443, Rv0379 and Rv0147 as TB potential diagnostic or therapeutic targets

Tuberculosis (TB) is a sizable public health threat in the world. This study was conducted to determine the differential protein composition between susceptible and MDRTB strains. Tuberculosis proteins were extracted by Triton™ X-114 and ammonium sulfate. Two-dimensional gel electrophoresis protein spots were selected for identification by mass spectrometry and mRNA expression levels were measured by real- time PCR. 2DE-Western blot and T cell epitope prediction for identified proteins were made by the IEDB server. The result shows at least six protein spots (Rv0147, Rv3597c, Rv0379, Rv3699, Rv1392 and Rv0443) were differentially expressed in MDRTB isolates. However, difference in mRNA gene expression was not found in the six mRNA genes. 2DE-Western blot procedures indicated strong reaction against MDRTB proteins corresponds to 13, 16 and 55 kDa areas that might be used as new diagnostic tools. In conclusion, these MDRTB proteins identified in this study could be reliable TB diagnostic candidates or therapeutic targets.

Dual proteomics of Drosophila melanogaster hemolymph infected with the heritable endosymbiont Spiroplasma poulsonii

Insects are frequently infected with heritable bacterial endosymbionts. Endosymbionts have a dramatic impact on their host physiology and evolution. Their tissue distribution is variable with some species being housed intracellularly, some extracellularly and some having a mixed lifestyle. The impact of extracellular endosymbionts on the biofluids they colonize (e.g. insect hemolymph) is however difficult to appreciate because biofluid composition can depend on the contribution of numerous tissues. Here we investigate Drosophila hemolymph proteome changes in response to the infection with the endosymbiont Spiroplasma poulsonii. S. poulsonii inhabits the fly hemolymph and gets vertically transmitted over generations by hijacking the oogenesis in females. Using dual proteomics on infected hemolymph, we uncovered a weak, chronic activation of the Toll immune pathway by S. poulsonii that was previously undetected by transcriptomics-based approaches. Using Drosophila genetics, we also identified candidate proteins putatively involved in controlling S. poulsonii growth. Last, we also provide a deep proteome of S. poulsonii, which, in combination with previously published transcriptomics data, improves our understanding of the post-transcriptional regulations operating in this bacterium.

Factors affecting the rapid changes of protein under short-term heat stress

BACKGROUND

Protein content determines the state of cells. The variation in protein abundance is crucial when organisms are in the early stages of heat stress, but the reasons affecting their changes are largely unknown.

RESULTS

We quantified 47,535 mRNAs and 3742 proteins in the filling grains of wheat in two different thermal environments. The impact of mRNA abundance and sequence features involved in protein translation and degradation on protein expression was evaluated by regression analysis. Transcription, codon usage and amino acid frequency were the main drivers of changes in protein expression under heat stress, and their combined contribution explains 58.2 and 66.4% of the protein variation at 30 and 40 °C (20 °C as control), respectively. Transcription contributes more to alterations in protein content at 40 °C (31%) than at 30 °C (6%). Furthermore, the usage of codon AAG may be closely related to the rapid alteration of proteins under heat stress. The contributions of AAG were 24 and 13% at 30 and 40 °C, respectively.

CONCLUSION

In this study, we analyzed the factors affecting the changes in protein expression in the early stage of heat stress and evaluated their influence.

PhyloQuant approach provides insights into Trypanosoma cruzi evolution using a systems-wide mass spectrometry-based quantitative protein profile

The etiological agent of Chagas disease, Trypanosoma cruzi, is a complex of seven genetic subdivisions termed discrete typing units (DTUs), TcI-TcVI and Tcbat. The relevance of T. cruzi genetic diversity to the variable clinical course of the disease, virulence, pathogenicity, drug resistance, transmission cycles and ecological distribution requires understanding the parasite origin and population structure. In this study, we introduce the PhyloQuant approach to infer the evolutionary relationships between organisms based on differential mass spectrometry-based quantitative features. In particular, large scale quantitative bottom-up proteomics features (MS1, iBAQ and LFQ) were analyzed using maximum parsimony, showing a correlation between T. cruzi DTUs and closely related trypanosomes' protein expression and sequence-based clustering. Character mapping enabled the identification of synapomorphies, herein the proteins and their respective expression profiles that differentiate T. cruzi DTUs and trypanosome species. The distance matrices based on phylogenetics and PhyloQuant clustering showed statistically significant correlation highlighting the complementarity between the two strategies. Moreover, PhyloQuant allows the identification of differentially regulated and strain/DTU/species-specific proteins, and has potential application in the identification of specific biomarkers and candidate therapeutic targets.

The Skyline ecosystem: Informatics for quantitative mass spectrometry proteomics

Skyline is a freely available, open-source Windows client application for accelerating targeted proteomics experimentation, with an emphasis on the proteomics and mass spectrometry community as users and as contributors. This review covers the informatics encompassed by the Skyline ecosystem, from computationally assisted targeted mass spectrometry method development, to raw acquisition file data processing, and quantitative analysis and results sharing.

mRBPome capture identifies the RNA-binding protein TRIM71, an essential regulator of spermatogonial differentiation

Continual spermatogenesis relies on the actions of an undifferentiated spermatogonial population that is composed of stem cells and progenitors. Here, using mouse models, we explored the role of RNA-binding proteins (RBPs) in regulation of the biological activities of this population. Proteins bound to polyadenylated RNAs in primary cultures of undifferentiated spermatogonia were captured with oligo (dT)-conjugated beads after UV-crosslinking and profiled by proteomics (termed mRBPome capture), yielding a putative repertoire of 473 RBPs. From this database, the RBP TRIM71 was identified and found to be expressed by stem and progenitor spermatogonia in prepubertal and adult mouse testes. Tissue-specific deletion of TRIM71 in the male germline led to reduction of the undifferentiated spermatogonial population and a block in transition to the differentiating state. Collectively, these findings demonstrate a key role of the RBP system in regulation of the spermatogenic lineage and may provide clues about the influence of RBPs on the biology of progenitor cell populations in other lineages.

Comparative proteomics of stenotopic caddisfly Crunoecia irrorata identifies acclimation strategies to warming

Species' ecological preferences are often deduced from habitat characteristics thought to represent more or less optimal conditions for physiological functioning. Evolution has led to stenotopic and eurytopic species, the former having decreased niche breadths and lower tolerances to environmental variability. Species inhabiting freshwater springs are often described as being stenotopic specialists, adapted to the stable thermal conditions found in these habitats. Whether due to past local adaptation these species have evolved or have lost intra-generational adaptive mechanisms to cope with increasing thermal variability has, to our knowledge, never been investigated. By studying how the proteome of a stenotopic species changes as a result of increasing temperatures, we investigate if the absence or attenuation of molecular mechanisms is indicative of local adaptation to freshwater springs. An understanding of compensatory mechanisms is especially relevant as spring specialists will experience thermal conditions beyond their physiological limits due to climate change. In this study, the stenotopic species Crunoecia irrorata (Trichoptera: Lepidostomatidae, Curtis 1834) was acclimated to 10, 15 and 20°C for 168 hr. We constructed a homology-based database and via liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based shotgun proteomics identified 1,358 proteins. Differentially abundant proteins and protein norms of reaction revealed candidate proteins and molecular mechanisms facilitating compensatory responses such as trehalose metabolism, tracheal system alteration and heat-shock protein regulation. A species-specific understanding of compensatory physiologies challenges the characterization of species as having narrow tolerances to environmental variability if that characterization is based on occurrences and habitat characteristics alone.

ZIKAVID-Zika virus infection database: a new platform to analyze the molecular impact of Zika virus infection

The recent outbreak of Zika virus (ZIKV) in Brazil and other countries globally demonstrated the relevance of ZIKV studies. During and after this outbreak, there was an intense increase in scientific production on ZIKV infections, especially toward alterations promoted by the infection and related to clinical outcomes. Considering this massive amount of new data, mainly thousands of genes and proteins whose expression is impacted by ZIKV infection, the ZIKA Virus Infection Database (ZIKAVID) was created. ZIKAVID is an online database that comprises all genes or proteins, and associated information, for which expression was experimentally measured and found to be altered after ZIKV infection. The database, available at https://zikavid.org, contains 16,984 entries of gene expression measurements from a total of 7348 genes. It allows users to easily perform searches for different experimental hosts (cell lines, tissues, and animal models), ZIKV strains (African, Asian, and Brazilian), and target molecules (messenger RNA [mRNA] and protein), among others, used in differential expression studies regarding ZIKV infection. In this way, the ZIKAVID will serve as an additional and important resource to improve the characterization of the molecular impact and pathogenesis associated with ZIKV infection.

Exploiting Interdata Relationships in Next-generation Proteomics Analysis

Mass spectrometry based proteomics and other technologies have matured to enable routine quantitative, system-wide analysis of concentrations, modifications, and interactions of proteins, mRNAs, and other molecules. These studies have allowed us to move toward a new field concerned with mining information from the combination of these orthogonal data sets, perhaps called "integromics." We highlight examples of recent studies and tools that aim at relating proteomic information to mRNAs, genetic associations, and changes in small molecules and lipids. We argue that productive data integration differs from parallel acquisition and interpretation and should move toward quantitative modeling of the relationships between the data. These relationships might be expressed by temporal information retrieved from time series experiments, rate equations to model synthesis and degradation, or networks of causal, evolutionary, physical, and other interactions. We outline steps and considerations toward such integromic studies to exploit the synergy between data sets.

Response to Sulfur Dioxide Addition by Two Commercial Saccharomyces cerevisiae Strains

Sulfur dioxide (SO2) is an antioxidant and antimicrobial agent used in winemaking. Its effects on spoilage microorganisms has been studied extensively, but its effects on commercial Saccharomyces cerevisiae strains, the dominant yeast in winemaking, require further investigation. To our knowledge, no previous studies have investigated both the potential SO2 resistance mechanisms of commercial yeasts as well as their production of aroma-active volatile compounds in response to SO2. To study this, fermentations of two commercial yeast strains were conducted in the presence (50 mg/L) and absence (0 mg/L) of SO2. Strain QA23 was more sensitive to SO2 than Strain BRL97, resulting in delayed cell growth and slower fermentation. BRL97 exhibited a more rapid decrease in free SO2, a higher initial production of hydrogen sulfide, and a higher production of acetaldehyde, suggesting that each strain may utilize different mechanisms of sulfite resistance. SO2 addition did not affect the production of aroma-active volatile compounds in QA23, but significantly altered the volatile profiles of the wines fermented by BRL97.

Polysome-profiling in small tissue samples

Polysome-profiling is commonly used to study translatomes and applies laborious extraction of efficiently translated mRNA (associated with >3 ribosomes) from a large volume across many fractions. This property makes polysome-profiling inconvenient for larger experimental designs or samples with low RNA amounts. To address this, we optimized a non-linear sucrose gradient which reproducibly enriches for efficiently translated mRNA in only one or two fractions, thereby reducing sample handling 5-10-fold. The technique generates polysome-associated RNA with a quality reflecting the starting material and, when coupled with smart-seq2 single-cell RNA sequencing, translatomes in small tissues from biobanks can be obtained. Translatomes acquired using optimized non-linear gradients resemble those obtained with the standard approach employing linear gradients. Polysome-profiling using optimized non-linear gradients in serum starved HCT-116 cells with or without p53 showed that p53 status associates with changes in mRNA abundance and translational efficiency leading to changes in protein levels. Moreover, p53 status also induced translational buffering whereby changes in mRNA levels are buffered at the level of mRNA translation. Thus, here we present a polysome-profiling technique applicable to large study designs, primary cells and frozen tissue samples such as those collected in biobanks.

Analysis of essential gene dynamics under antibiotic stress in Streptococcus sanguinis

The paradoxical response of Streptococcus sanguinis to drugs prescribed for dental and clinical practices has complicated treatment guidelines and raised the need for further investigation. We conducted a high throughput study on concomitant transcriptome and proteome dynamics in a time course to assess S. sanguinis behaviour under a sub-inhibitory concentration of ampicillin. Temporal changes at the transcriptome and proteome level were monitored to cover essential genes and proteins over a physiological map of intricate pathways. Our findings revealed that translation was the functional category in S. sanguinis that was most enriched in essential proteins. Moreover, essential proteins in this category demonstrated the greatest conservation across 2774 bacterial proteomes, in comparison to other essential functional categories like cell wall biosynthesis and energy production. In comparison to non-essential proteins, essential proteins were less likely to contain ‘degradation-prone’ amino acids at their N-terminal position, suggesting a longer half-life. Despite the ampicillin-induced stress, the transcriptional up-regulation of amino acid-tRNA synthetases and proteomic elevation of amino acid biosynthesis enzymes favoured the enriched components of essential proteins revealing ‘proteomic signatures’ that can be used to bridge the genotype–phenotype gap of S. sanguinis under ampicillin stress. Furthermore, we identified a significant correlation between the levels of mRNA and protein for essential genes and detected essential protein-enriched pathways differentially regulated through a persistent stress response pattern at late time points. We propose that the current findings will help characterize a bacterial model to study the dynamics of essential genes and proteins under clinically relevant stress conditions.

MINA-1 and WAGO-4 are part of regulatory network coordinating germ cell death and RNAi in C. elegans

Post-transcriptional control of mRNAs by RNA-binding proteins (RBPs) has a prominent role in the regulation of gene expression. RBPs interact with mRNAs to control their biogenesis, splicing, transport, localization, translation, and stability. Defects in such regulation can lead to a wide range of human diseases from neurological disorders to cancer. Many RBPs are conserved between Caenorhabditis elegans and humans, and several are known to regulate apoptosis in the adult C. elegans germ line. How these RBPs control apoptosis is, however, largely unknown. Here, we identify mina-1(C41G7.3) in a RNA interference-based screen as a novel regulator of apoptosis, which is exclusively expressed in the adult germ line. The absence of MINA-1 causes a dramatic increase in germ cell apoptosis, a reduction in brood size, and an impaired P granules organization and structure. In vivo crosslinking immunoprecipitation experiments revealed that MINA-1 binds a set of mRNAs coding for RBPs associated with germ cell development. Additionally, a system-wide analysis of a mina-1 deletion mutant compared with wild type, including quantitative proteome and transcriptome data, hints to a post-transcriptional regulatory RBP network driven by MINA-1 during germ cell development in C. elegans. In particular, we found that the germline-specific Argonaute WAGO-4 protein levels are increased in mina-1 mutant background. Phenotypic analysis of double mutant mina-1;wago-4 revealed that contemporary loss of MINA-1 and WAGO-4 strongly rescues the phenotypes observed in mina-1 mutant background. To strengthen this functional interaction, we found that upregulation of WAGO-4 in mina-1 mutant animals causes hypersensitivity to exogenous RNAi. Our comprehensive experimental approach allowed us to describe a phenocritical interaction between two RBPs controlling germ cell apoptosis and exogenous RNAi. These findings broaden our understanding of how RBPs can orchestrate different cellular events such as differentiation and death in C. elegans.

iTRAQ-based quantitative proteomic analysis identified Eno1 as a cadmium stress response gene in Propsilocerus akamusi (Tokunaga) hemolymph

Propsilocerus akamusi (Tokunaga) is a common species of midge in Siberia, Japan, and China and an important prey species for fish and aquatic birds. Furthermore, this species has been shown to have an extraordinary capacity to resist cadmium (Cd) toxicity. In this study, isobaric tags for relative and absolute quantitation (iTRAQ) coupled liquid chromatography tandem mass spectrometry (LC-MS/MS) was used to analyze relative changes in the P. akamusi hemolymph proteome following exposure to a sublethal concentration of Cd²⁺. The results showed that Cd²⁺ stress affects energy metabolism in P. akamusi. After examining the differentially expressed proteins (DEPs), only one up-regulated protein associated with metabolism, α-enolase (Eno1) was identified and further isolated and characterized. Sequence alignments showed that the deduced P. akamusi Eno1 amino acid sequence is highly conserved, with similarities of 77-95% noted when compared to other Dipteran Eno1 sequences. Furthermore, prolonged Cd²⁺ exposure impacted Eno1 transcription, protein expression and enzyme activity levels. These results suggest that Eno1 may play a role in the response to Cd²⁺ stress in P. akamusi.

Zika Virus Infection of Human Mesenchymal Stem Cells Promotes Differential Expression of Proteins Linked to Several Neurological Diseases

The recent microcephaly outbreak in Brazil has been associated with Zika virus (ZIKV) infection. The current understanding of damage caused by ZIKV infection is still unclear, since it has been implicated in other neurodegenerative and developmental complications. Here, the differential proteome analysis of human mesenchymal stem cells (hMSC) infected with a Brazilian strain of ZIKV was identified by shotgun proteomics (MudPIT). Our results indicate that ZIKV induces a potential reprogramming of the metabolic machinery in nucleotide metabolism, changes in the energy production via glycolysis and other metabolic pathways, and potentially inhibits autophagy, neurogenesis, and immune response by downregulation of signaling pathways. In addition, proteins previously described in several brain pathologies, such as Alzheimer's disease, autism spectrum disorder, amyotrophic lateral sclerosis, and Parkinson's disease, were found with altered expression due to ZIKV infection in hMSC. This potential link between ZIKV and several neuropathologies beyond microcephaly is being described here for the first time and can be used to guide specific follow-up studies concerning these specific diseases and ZIKV infection.

Model system based proteomics to understand the host response during bacterial infections

Infectious diseases caused by bacterial pathogens pose a major concern to public health and, thus, greater attention must be given to providing insightful knowledge on host-pathogen interactions. There are several theories addressing the dynamics of complex mechanisms of host-pathogen interactions. The availability of an ample number of universally accepted model systems, including vertebrates, invertebrates, and mammalian cells, provides in-depth transcriptomics data to evaluate these complex mechanisms during host-pathogen interactions. Recent model system based proteomic studies have addressed the issues related to human diseases by establishing the protein profile of model animals that closely resemble the environment. As a result, model system based proteomics has been widely accepted as a powerful and effective approach to understand the highly complex host-pathogen interfaces at their protein levels. This review offers a snapshot of the contributions of selective model systems on host-bacterial pathogen interactions through proteomic approaches.

Multiplex quantitative SILAC for analysis of archaeal proteomes: a case study of oxidative stress responses

Stable isotope labelling of amino acids in cell culture (SILAC) is a quantitative proteomic method that can illuminate new pathways used by cells to adapt to different lifestyles and niches. Archaea, while thriving in extreme environments and accounting for ∼20%-40% of the Earth's biomass, have not been analyzed with the full potential of SILAC. Here, we report SILAC for quantitative comparison of archaeal proteomes, using Haloferax volcanii as a model. A double auxotroph was generated that allowed for complete incorporation of ¹³ C/¹⁵ N-lysine and ¹³ C-arginine such that each peptide derived from trypsin digestion was labelled. This strain was found amenable to multiplex SILAC by case study of responses to oxidative stress by hypochlorite. A total of 2565 proteins was identified by LC-MS/MS analysis (q-value ≤ 0.01) that accounted for 64% of the theoretical proteome. Of these, 176 proteins were altered at least 1.5-fold (p-value < 0.05) in abundance during hypochlorite stress. Many of the differential proteins were of unknown function. Those of known function included transcription factor homologs related to oxidative stress by 3D-homology modelling and orthologous group comparisons. Thus, SILAC is found to be an ideal method for quantitative proteomics of archaea that holds promise to unravel gene function.

Multiple marker abundance profiling: combining selected reaction monitoring and data-dependent acquisition for rapid estimation of organelle abundance in subcellular samples

Measuring changes in protein or organelle abundance in the cell is an essential, but challenging aspect of cell biology. Frequently-used methods for determining organelle abundance typically rely on detection of a very few marker proteins, so are unsatisfactory. In silico estimates of protein abundances from publicly available protein spectra can provide useful standard abundance values but contain only data from tissue proteomes, and are not coupled to organelle localization data. A new protein abundance score, the normalized protein abundance scale (NPAS), expands on the number of scored proteins and the scoring accuracy of lower-abundance proteins in Arabidopsis. NPAS was combined with subcellular protein localization data, facilitating quantitative estimations of organelle abundance during routine experimental procedures. A suite of targeted proteomics markers for subcellular compartment markers was developed, enabling independent verification of in silico estimates for relative organelle abundance. Estimation of relative organelle abundance was found to be reproducible and consistent over a range of tissues and growth conditions. In silico abundance estimations and localization data have been combined into an online tool, multiple marker abundance profiling, available in the SUBA4 toolbox (http://suba.live).

Intra and Interspecific Variations of Gene Expression Levels in Yeast Are Largely Neutral: (Nei Lecture, SMBE 2016, Gold Coast)

It is commonly, although not universally, accepted that most intra and interspecific genome sequence variations are more or less neutral, whereas a large fraction of organism-level phenotypic variations are adaptive. Gene expression levels are molecular phenotypes that bridge the gap between genotypes and corresponding organism-level phenotypes. Yet, it is unknown whether natural variations in gene expression levels are mostly neutral or adaptive. Here we address this fundamental question by genome-wide profiling and comparison of gene expression levels in nine yeast strains belonging to three closely related Saccharomyces species and originating from five different ecological environments. We find that the transcriptome-based clustering of the nine strains approximates the genome sequence-based phylogeny irrespective of their ecological environments. Remarkably, only ∼0.5% of genes exhibit similar expression levels among strains from a common ecological environment, no greater than that among strains with comparable phylogenetic relationships but different environments. These and other observations strongly suggest that most intra and interspecific variations in yeast gene expression levels result from the accumulation of random mutations rather than environmental adaptations. This finding has profound implications for understanding the driving force of gene expression evolution, genetic basis of phenotypic adaptation, and general role of stochasticity in evolution.

Translational contributions to tissue specificity in rhythmic and constitutive gene expression

Background

The daily gene expression oscillations that underlie mammalian circadian rhythms show striking differences between tissues and involve post-transcriptional regulation. Both aspects remain poorly understood. We have used ribosome profiling to explore the contribution of translation efficiency to temporal gene expression in kidney and contrasted our findings with liver data available from the same mice.

Results

Rhythmic translation of constantly abundant messenger RNAs (mRNAs) affects largely non-overlapping transcript sets with distinct phase clustering in the two organs. Moreover, tissue differences in translation efficiency modulate the timing and amount of protein biosynthesis from rhythmic mRNAs, consistent with organ specificity in clock output gene repertoires and rhythmicity parameters. Our comprehensive datasets provided insights into translational control beyond temporal regulation. Between tissues, many transcripts show differences in translation efficiency, which are, however, of markedly smaller scale than mRNA abundance differences. Tissue-specific changes in translation efficiency are associated with specific transcript features and, intriguingly, globally counteracted and compensated transcript abundance variations, leading to higher similarity at the level of protein biosynthesis between both tissues.

Conclusions

We show that tissue specificity in rhythmic gene expression extends to the translatome and contributes to define the identities, the phases and the expression levels of rhythmic protein biosynthesis. Moreover, translational compensation of transcript abundance divergence leads to overall higher similarity at the level of protein production across organs. The unique resources provided through our study will serve to address fundamental questions of post-transcriptional control and differential gene expression in vivo.

Electronic supplementary material

The online version of this article (doi:10.1186/s13059-017-1222-2) contains supplementary material, which is available to authorized users.

Altered nucleocytoplasmic proteome and transcriptome distributions in an in vitro model of amyotrophic lateral sclerosis

Aberrant nucleocytoplasmic localization of proteins has been implicated in many neurodegenerative diseases. Evidence suggests that cytoplasmic mislocalization of nuclear proteins such as transactive response DNA-binding protein 43 (TDP-43) and fused in sarcoma (FUS) may be associated with neurotoxicity in amyotrophic lateral sclerosis (ALS) and frontotemporal lobar degeneration. This study investigated the changes in nucleocytoplasmic distributions of the proteome and transcriptome in an in vitro model of ALS. After subcellular fractionation of motor neuron-like cell lines expressing wild-type or G93A mutant hSOD1, quantitative mass spectrometry and next-generation RNA sequencing (RNA-seq) were performed for the nuclear and cytoplasmic compartments. A subset of the results was validated via immunoblotting. A total of 1,925 proteins were identified in either the nuclear or cytoplasmic fractions, and 32% of these proteins were quantified in both fractions. The nucleocytoplasmic distribution of 37 proteins was significantly changed in mutant cells with nuclear and cytoplasmic shifts in 13 and 24 proteins, respectively (p<0.05). The proteins shifted towards the nucleus were enriched regarding pathways of RNA transport and processing (Dhx9, Fmr1, Srsf3, Srsf6, Tra2b), whereas protein folding (Cct5, Cct7, Cct8), aminoacyl-tRNA biosynthesis (Farsb, Nars, Txnrd1), synaptic vesicle cycle (Cltc, Nsf), Wnt signalling (Cltc, Plcb3, Plec, Psmd3, Ruvbl1) and Hippo signalling (Camk2d, Plcb3, Ruvbl1) pathways were over-represented in the proteins shifted to the cytoplasm. A weak correlation between the changes in protein and mRNA levels was found only in the nucleus, where mRNA was relatively abundant in mutant cells. This study provides a comprehensive dataset of the nucleocytoplasmic distribution of the proteome and transcriptome in an in vitro model of ALS. An integrated analysis of the nucleocytoplasmic distribution of the proteome and transcriptome demonstrated multiple candidate pathways including RNA processing/transport and protein synthesis and folding that may be relevant to the pathomechanism of ALS.

Proteome and Secretome Analysis Reveals Differential Post-transcriptional Regulation of Toll-like Receptor Responses

The innate immune system is the organism's first line of defense against pathogens. Pattern recognition receptors (PRRs) are responsible for sensing the presence of pathogen-associated molecules. The prototypic PRRs, the membrane-bound receptors of the Toll-like receptor (TLR) family, recognize pathogen-associated molecular patterns (PAMPs) and initiate an innate immune response through signaling pathways that depend on the adaptor molecules MyD88 and TRIF. Deciphering the differences in the complex signaling events that lead to pathogen recognition and initiation of the correct response remains challenging. Here we report the discovery of temporal changes in the protein signaling components involved in innate immunity. Using an integrated strategy combining unbiased proteomics, transcriptomics and macrophage stimulations with three different PAMPs, we identified differences in signaling between individual TLRs and revealed specifics of pathway regulation at the protein level.

β-Integrin de-phosphorylation by the Density-Enhanced Phosphatase DEP-1 attenuates EGFR signaling in C. elegans

Density-Enhanced Phosphatase-1 (DEP-1) de-phosphorylates various growth factor receptors and adhesion proteins to regulate cell proliferation, adhesion and migration. Moreover, dep-1/scc1 mutations have been detected in various types of human cancers, indicating a broad tumor suppressor activity. During C. elegans development, DEP-1 mediates binary cell fate decisions by negatively regulating EGFR signaling. Using a substrate-trapping DEP-1 mutant in a proteomics approach, we have identified the C. elegans β-integrin subunit PAT-3 as a specific DEP-1 substrate. DEP-1 selectively de-phosphorylates tyrosine 792 in the membrane-proximal NPXY motif to promote integrin activation via talin recruitment. The non-phosphorylatable β-integrin mutant pat-3(Y792F) partially suppresses the hyperactive EGFR signaling phenotype caused by loss of dep-1 function. Thus, DEP-1 attenuates EGFR signaling in part by de-phosphorylating Y792 in the β-integrin cytoplasmic tail, besides the direct de-phosphorylation of the EGFR. Furthermore, in vivo FRAP analysis indicates that the αβ-integrin/talin complex attenuates EGFR signaling by restricting receptor mobility on the basolateral plasma membrane. We propose that DEP-1 regulates EGFR signaling via two parallel mechanisms, by direct receptor de-phosphorylation and by restricting receptor mobility through αβ-integrin activation.

On the Dependency of Cellular Protein Levels on mRNA Abundance

The question of how genomic information is expressed to determine phenotypes is of central importance for basic and translational life science research and has been studied by transcriptomic and proteomic profiling. Here, we review the relationship between protein and mRNA levels under various scenarios, such as steady state, long-term state changes, and short-term adaptation, demonstrating the complexity of gene expression regulation, especially during dynamic transitions. The spatial and temporal variations of mRNAs, as well as the local availability of resources for protein biosynthesis, strongly influence the relationship between protein levels and their coding transcripts. We further discuss the buffering of mRNA fluctuations at the level of protein concentrations. We conclude that transcript levels by themselves are not sufficient to predict protein levels in many scenarios and to thus explain genotype-phenotype relationships and that high-quality data quantifying different levels of gene expression are indispensable for the complete understanding of biological processes.

Transient protein-protein interactions perturb E. coli metabolome and cause gene dosage toxicity

Gene dosage toxicity (GDT) is an important factor that determines optimal levels of protein abundances, yet its molecular underpinnings remain unknown. Here, we demonstrate that overexpression of DHFR in E. coli causes a toxic metabolic imbalance triggered by interactions with several functionally related enzymes. Though deleterious in the overexpression regime, surprisingly, these interactions are beneficial at physiological concentrations, implying their functional significance in vivo. Moreover, we found that overexpression of orthologous DHFR proteins had minimal effect on all levels of cellular organization - molecular, systems, and phenotypic, in sharp contrast to E. coli DHFR. Dramatic difference of GDT between 'E. coli's self' and 'foreign' proteins suggests the crucial role of evolutionary selection in shaping protein-protein interaction (PPI) networks at the whole proteome level. This study shows how protein overexpression perturbs a dynamic metabolon of weak yet potentially functional PPI, with consequences for the metabolic state of cells and their fitness.

Importance of Translocon Subunit Tic56 for rRNA Processing and Chloroplast Ribosome Assembly

Toc159-containing complexes at the outer chloroplast envelope membrane form stable supercomplexes with a 1-MD translocon at the inner chloroplast envelope membrane of which Tic56 is one essential subunit. While the single mutants tic56-1 and ppi2 (toc159) have an albino phenotype and are able to grow heterotrophically, we find the double mutant to be embryo lethal. Comprehensive quantitative proteome profiling with both single mutants in combination with GeneChip analyses identified a posttranscriptional defect in the accumulation of plastid ribosomal proteins and diminished expression of plastid encoded proteins. In the tic56-1 mutant, the assembly of functional ribosomes is furthermore hampered by a processing defect of the plastid 23S rRNA. Spectinomycin-treatment of wild-type plants phenocopies the molecular phenotype of plastid proteome accumulation in tic56-1 and to a smaller degree also ppi2 plastids, suggesting that a defect in plastid translation is largely responsible for the phenotype of both import mutants. Import experiments with the tic56-3 mutant revealed no significant defect in the import of small ribosomal protein 16 in the absence of full-length Tic56, suggesting that the defect in ribosome assembly in tic56-1 may be independent of a function of Tic56 in protein import. Our data establish a previously unknown link between plastid protein import, the processing of plastid rRNAs, and the assembly of plastid ribosomes and provide further knowledge on the function of the translocon components and the molecular basis for their albino phenotype.

High-Throughput Proteomics Reveals the Unicellular Roots of Animal Phosphosignaling and Cell Differentiation

Cell-specific regulation of protein levels and activity is essential for the distribution of functions among multiple cell types in animals. The finding that many genes involved in these regulatory processes have a premetazoan origin raises the intriguing possibility that the mechanisms required for spatially regulated cell differentiation evolved prior to the appearance of animals. Here, we use high-throughput proteomics in Capsaspora owczarzaki, a close unicellular relative of animals, to characterize the dynamic proteome and phosphoproteome profiles of three temporally distinct cell types in this premetazoan species. We show that life-cycle transitions are linked to extensive proteome and phosphoproteome remodeling and that they affect key genes involved in animal multicellularity, such as transcription factors and tyrosine kinases. The observation of shared features between Capsaspora and metazoans indicates that elaborate and conserved phosphosignaling and proteome regulation supported temporal cell-type differentiation in the unicellular ancestor of animals.

Benchmarking of protein carbonylation analysis in Caenorhabditis elegans: specific considerations and general advice

Oxidative stress has been extensively studied due to its correlation with cellular disorders and aging. In proteins, one biomarker of oxidative stress is the presence of carbonyl groups, such as aldehyde and ketone, in specific amino acid side chains such as lysine, proline, arginine and threonine, so-called protein carbonylation (PC). PC study is now a growing field in general and medical science since PC accumulation is associated with various pathologies and disorders. At present, enzyme-linked immunosorbent assays (ELISA) seem to be the most robust method of quantifying the presence of carbonyl groups in proteins, despite having some recognised caveats. In parallel, gel-based approaches present cross-comparison difficulties, along with other technical problems. As generic PC analyses still suffer from poor homogeneity, leading to cross-data analysis difficulties and poor results overlap, the need for harmonisation in the field of carbonyl detection is now widely accepted. This study aims to highlight some of the technical challenges in proteomic gel-based multiplexing experiments when dealing with PC in difficult samples like those from Caenorhabditis elegans, from protein extraction to carbonyl detection. We demonstrate that some critical technical parameters, such as labelling time, probe concentration, and total and carbonylated protein recovery rates, should be re-addressed in a sample-specific way. We also defined a procedure to cost-effectively adapt CyDye™-hydrazide-based protocols to specific samples, especially when the experimental interest is focused on studying differences between stimulating conditions with a maximised signal-to-noise ratio. Moreover, we have improved an already-existing powerful solubilisation buffer, making it potentially useful for hard-to-solubilise protein pellets. Lastly, the depicted methodology exemplifies a simple way of normalising carbonyl-related signal to total protein in SDS-PAGE multiplexing experiments. Within that scope, we also proposed a simple way to quantify carbonyl groups by on-gel spotting diluted dye-containing labelling buffer. Proof of the robustness of the procedure was also highlighted by the high linear correlation between the level of carbonyls and the ultraviolet exposure duration of whole worms (R²=0.993). Altogether, these results will help to standardise existing protocols in the growing field of proteomic carbonylation studies.