Comparative proteomic and transcriptomic profiling of the fission yeast Schizosaccharomyces pombe

Effects of ScRgt1-Like DNA-binding transcription factor SpRgt1 (SPCC320.03) on Hexose transporters gene expression in Schizosaccharomyces pombe

Glucose, which plays an essential role in carbon and energy metabolism in eukaryotes, is vital in directing various energy-consuming cellular processes. In S. cerevisiae, transcription factors involved in regulating hexose transporters and their mechanisms of action under different carbon sources were revealed in detail. However, there is limited information on these processes in S. pombe. In this study, the effect of SPCC320.03 (named SpRgt1), the ortholog of ScRgt1 whose molecular mechanism is known in detail in S. cerevisiae, on the transcriptional regulation of hexose transporters (ght1-8) dependent on different carbon sources was investigated. We measured the transcript levels of ght1-8 using the qPCR technique and performed relative evaluation in S. pombe strains (parental, rgt1 deleted mutant, rgt1 overexpressed, and vectoral rgt1 carrying mutant). We aimed to investigate the transcriptional changes caused by the protein product of the rgt1 (SPCC320.03) gene in terms of ght1-8 genes in strains that are grown in different carbon sources (2% glucose, 2% glycerol + 0.1% glucose, and 2% gluconate). Here, we show that SpRgt1 is involved in the regulation of the ght3, ght4, ght6, and ght7 genes but that the ght1, ght2, ght5, and ght8 gene expression vary depending on carbon sources, independently of SpRgt1.

Proteome effects of genome-wide single gene perturbations

Protein abundance is controlled at the transcriptional, translational and post-translational levels, and its regulatory principles are starting to emerge. Investigating these principles requires large-scale proteomics data and cannot just be done with transcriptional outcomes that are commonly used as a proxy for protein abundance. Here, we determine proteome changes resulting from the individual knockout of 3308 nonessential genes in the yeast Schizosaccharomyces pombe. We use similarity clustering of global proteome changes to infer gene functionality that can be extended to other species, such as humans or baker's yeast. Furthermore, we analyze a selected set of deletion mutants by paired transcriptome and proteome measurements and show that upregulation of proteins under stable transcript expression utilizes optimal codons.

Growth-rate-dependent and nutrient-specific gene expression resource allocation in fission yeast

Cellular resources are limited and their relative allocation to gene expression programmes determines physiological states and global properties such as the growth rate. Here, we determined the importance of the growth rate in explaining relative changes in protein and mRNA levels in the simple eukaryote Schizosaccharomyces pombe grown on non-limiting nitrogen sources. Although expression of half of fission yeast genes was significantly correlated with the growth rate, this came alongside wide-spread nutrient-specific regulation. Proteome and transcriptome often showed coordinated regulation but with notable exceptions, such as metabolic enzymes. Genes positively correlated with growth rate participated in every level of protein production apart from RNA polymerase II-dependent transcription. Negatively correlated genes belonged mainly to the environmental stress response programme. Critically, metabolic enzymes, which represent ∼55-70% of the proteome by mass, showed mostly condition-specific regulation. In summary, we provide a rich account of resource allocation to gene expression in a simple eukaryote, advancing our basic understanding of the interplay between growth-rate-dependent and nutrient-specific gene expression.

Bioinformatic Analysis of Temporal and Spatial Proteome Alternations During Infections

Microbial pathogens have evolved numerous mechanisms to hijack host's systems, thus causing disease. This is mediated by alterations in the combined host-pathogen proteome in time and space. Mass spectrometry-based proteomics approaches have been developed and tailored to map disease progression. The result is complex multidimensional data that pose numerous analytic challenges for downstream interpretation. However, a systematic review of approaches for the downstream analysis of such data has been lacking in the field. In this review, we detail the steps of a typical temporal and spatial analysis, including data pre-processing steps (i.e., quality control, data normalization, the imputation of missing values, and dimensionality reduction), different statistical and machine learning approaches, validation, interpretation, and the extraction of biological information from mass spectrometry data. We also discuss current best practices for these steps based on a collection of independent studies to guide users in selecting the most suitable strategies for their dataset and analysis objectives. Moreover, we also compiled the list of commonly used R software packages for each step of the analysis. These could be easily integrated into one's analysis pipeline. Furthermore, we guide readers through various analysis steps by applying these workflows to mock and host-pathogen interaction data from public datasets. The workflows presented in this review will serve as an introduction for data analysis novices, while also helping established users update their data analysis pipelines. We conclude the review by discussing future directions and developments in temporal and spatial proteomics and data analysis approaches. Data analysis codes, prepared for this review are available from https://github.com/BabuLab-UofR/TempSpac, where guidelines and sample datasets are also offered for testing purposes.

Biology and Physics of Heterochromatin-Like Domains/Complexes

The hallmarks of constitutive heterochromatin, HP1 and H3K9me2/3, assemble heterochromatin-like domains/complexes outside canonical constitutively heterochromatic territories where they regulate chromatin template-dependent processes. Domains are more than 100 kb in size; complexes less than 100 kb. They are present in the genomes of organisms ranging from fission yeast to human, with an expansion in size and number in mammals. Some of the likely functions of domains/complexes include silencing of the donor mating type region in fission yeast, preservation of DNA methylation at imprinted germline differentially methylated regions (gDMRs) and regulation of the phylotypic progression during vertebrate development. Far cis- and trans-contacts between micro-phase separated domains/complexes in mammalian nuclei contribute to the emergence of epigenetic compartmental domains (ECDs) detected in Hi-C maps. A thermodynamic description of micro-phase separation of heterochromatin-like domains/complexes may require a gestalt shift away from the monomer as the "unit of incompatibility" that determines the sign and magnitude of the Flory-Huggins parameter, χ. Instead, a more dynamic structure, the oligo-nucleosomal "clutch", consisting of between 2 and 10 nucleosomes is both the long sought-after secondary structure of chromatin and its unit of incompatibility. Based on this assumption we present a simple theoretical framework that enables an estimation of χ for domains/complexes flanked by euchromatin and thereby an indication of their tendency to phase separate. The degree of phase separation is specified by χN, where N is the number of "clutches" in a domain/complex. Our approach could provide an additional tool for understanding the biophysics of the 3D genome.

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.

Proteomic profiling and integrated analysis with transcriptomic data bring new insights in the stress responses of Kluyveromyces marxianus after an arrest during high-temperature ethanol fermentation

BACKGROUND

The thermotolerant yeast Kluyveromyces marxianus is a potential candidate for high-temperature fermentation. When K. marxianus was used for high-temperature ethanol fermentation, a fermentation arrest was observed during the late fermentation stage and the stress responses have been investigated based on the integration of RNA-Seq and metabolite data. In order to bring new insights into the cellular responses of K. marxianus after the fermentation arrest during high-temperature ethanol fermentation, quantitative proteomic profiling and integrated analysis with transcriptomic data were performed in this study.

RESULTS

Samples collected at 14, 16, 18, 20 and 22 h during high-temperature fermentation were subjected to isobaric tags for relative and absolute quantitation (iTRAQ)-based proteomic profiling and integrated analysis with transcriptomic data. The correlations between transcripts and proteins for the comparative group 16 h vs 14 h accounted for only 4.20% quantified proteins and 3.23% differentially expressed proteins (DEPs), respectively, much higher percentages of correlations (30.56%-59.11%) were found for other comparative groups (i.e., 18 h vs 14 h, 20 h vs 14 h, and 22 h vs 14 h). According to Spearman correlation tests between transcriptome and proteome (the absolute value of a correlation coefficient between 0.5 and 1 indicates a strong correlation), poor correlations were found for all quantified proteins (R = - 0.0355 to 0.0138), DEPs (R = - 0.0079 to 0.0233) and the DEPs with opposite expression trends to corresponding differentially expressed genes (DEGs) (R = - 0.0478 to 0.0636), whereas stronger correlations were observed in terms of the DEPs with the same expression trends as the correlated DEGs (R = 0.5593 to 0.7080). The results of multiple reaction monitoring (MRM) verification indicate that the iTRAQ results were reliable. After the fermentation arrest, a number of proteins involved in transcription, translation, oxidative phosphorylation and fatty acid metabolism were down-regulated, some molecular chaperones and proteasome proteins were up-regulated, the ATPase activity significantly decreased, and the total fatty acids gradually accumulated. In addition, the contents of palmitic acid, oleic acid, C16, C18, C22 and C24 fatty acids increased by 16.77%, 28.49%, 14.14%, 26.88%, 628.57% and 125.29%, respectively.

CONCLUSIONS

This study confirmed some biochemical and enzymatic alterations provoked by the stress conditions in the specific case of K. marxianus: such as decreases in transcription, translation and oxidative phosphorylation, alterations in cellular fatty acid composition, and increases in the abundance of molecular chaperones and proteasome proteins. These findings provide potential targets for further metabolic engineering towards improvement of the stress tolerance in K. marxianus.

Correlation Analyses Reveal a Limited Role of Transcription in Genome-Wide Differential MicroRNA Expression in Mammals

Transcription initiates the cascade of gene expression and is often assumed to play a predominant role in determining how much gene products are ultimately expressed. The relationship between mRNA levels and protein levels has been studied extensively to reveal the degrees of transcriptional and post-transcriptional regulation of protein expression. The extent to which transcription globally controls the differential expression of non-coding RNAs, however, is poorly defined. MicroRNAs (miRNAs) are a class of small, non-coding RNAs whose biogenesis involves transcription followed by extensive processing. Here, using hundreds of datasets produced from the ENCODE (Encyclopedia of DNA Elements) project we calculated the correlations between transcriptional activity and mature miRNA expression in diverse human cells, human tissues, and mouse tissues. While correlations vary among samples, most correlation coefficients are small. Interestingly, excluding miRNAs that were discovered later or weighting miRNA expression improves the correlations. Our results suggest that transcription contributes only modestly to differential miRNA expression at the genome-wide scale in mammals.

Integrated Analysis of Proteomic and Transcriptomic Data Highlights Late Fetal Muscle Maturation Process

In pigs, the perinatal period is the most critical time for survival. Piglet maturation, which occurs at the end of gestation, is an important determinant of early survival. Skeletal muscle plays a key role in adaptation to extra-uterine life, e.g. motor function and thermoregulation. Progeny from two breeds with extreme neonatal mortality rates were analyzed at 90 and 110 days of gestation (dg). The Large White breed is a highly selected breed for lean growth and exhibits a high rate of neonatal mortality, whereas the Meishan breed is fatter and more robust and has a low neonatal mortality. Our aim was to identify molecular signatures underlying late fetal longissimus muscle development. First, integrated analysis was used to explore relationships between co-expression network models built from a proteomic data set (bi-dimensional electrophoresis) and biological phenotypes. Second, correlations with a transcriptomic data set (microarrays) were investigated to combine different layers of expression with a focus on transcriptional regulation. Muscle glycogen content and myosin heavy chain polymorphism were good descriptors of muscle maturity and were used for further data integration analysis. Using 89 identified unique proteins, network inference, correlation with biological phenotypes and functional enrichment revealed that mitochondrial oxidative metabolism was a key determinant of neonatal muscle maturity. Some proteins, including ATP5A1 and CKMT2, were important nodes in the network related to muscle metabolism. Transcriptomic data suggest that overexpression of mitochondrial PCK2 was involved in the greater glycogen content of Meishan fetuses at 110 dg. GPD1, an enzyme involved in the mitochondrial oxidation of cytosolic NADH, was overexpressed in Meishan. Thirty-one proteins exhibited a positive correlation between mRNA and protein levels in both extreme fetal genotypes, suggesting transcriptional regulation. Gene ontology enrichment and Ingenuity analyses identified PPARGC1A and ESR1 as possible transcriptional factors positively involved in late fetal muscle maturation.

Comparative Proteome Analysis in Schizosaccharomyces pombe Identifies Metabolic Targets to Improve Protein Production and Secretion

Protein secretion in yeast is a complex process and its efficiency depends on a variety of parameters. We performed a comparative proteome analysis of a set of Schizosaccharomyces pombe strains producing the α-glucosidase maltase in increasing amounts to investigate the overall proteomic response of the cell to the burden of protein production along the various steps of protein production and secretion. Proteome analysis of these strains, utilizing an isobaric labeling/two dimensional LC-MALDI MS approach, revealed complex changes, from chaperones and secretory transport machinery to proteins controlling transcription and translation. We also found an unexpectedly high amount of changes in enzyme levels of the central carbon metabolism and a significant up-regulation of several amino acid biosyntheses. These amino acids were partially underrepresented in the cellular protein compared with the composition of the model protein. Additional feeding of these amino acids resulted in a 1.5-fold increase in protein secretion. Membrane fluidity was identified as a second bottleneck for high-level protein secretion and addition of fluconazole to the culture caused a significant decrease in ergosterol levels, whereas protein secretion could be further increased by a factor of 2.1. In summary, we show that high level protein secretion causes global changes of protein expression levels in the cell and that precursor availability and membrane composition limit protein secretion in this yeast. In this respect, comparative proteome analysis is a powerful tool to identify targets for an efficient increase of protein production and secretion in S. pombe Data are available via ProteomeXchange with identifiers PXD002693 and PXD003016.

Identifying Aspects of the Post-Transcriptional Program Governing the Proteome of the Green Alga Micromonas pusilla

Micromonas is a unicellular motile alga within the Prasinophyceae, a green algal group that is related to land plants. This picoeukaryote (<2 μm diameter) is widespread in the marine environment but is not well understood at the cellular level. Here, we examine shifts in mRNA and protein expression over the course of the day-night cycle using triplicated mid-exponential, nutrient replete cultures of Micromonas pusilla CCMP1545. Samples were collected at key transition points during the diel cycle for evaluation using high-throughput LC-MS proteomics. In conjunction, matched mRNA samples from the same time points were sequenced using pair-ended directional Illumina RNA-Seq to investigate the dynamics and relationship between the mRNA and protein expression programs of M. pusilla. Similar to a prior study of the marine cyanobacterium Prochlorococcus, we found significant divergence in the mRNA and proteomics expression dynamics in response to the light:dark cycle. Additionally, expressional responses of genes and the proteins they encoded could also be variable within the same metabolic pathway, such as we observed in the oxygenic photosynthesis pathway. A regression framework was used to predict protein levels from both mRNA expression and gene-specific sequence-based features. Several features in the genome sequence were found to influence protein abundance including codon usage as well as 3’ UTR length and structure. Collectively, our studies provide insights into the regulation of the proteome over a diel cycle as well as the relationships between transcriptional and translational programs in the widespread marine green alga Micromonas.

Capparis ovata treatment suppresses inflammatory cytokine expression and ameliorates experimental allergic encephalomyelitis model of multiple sclerosis in C57BL/6 mice

Since ancient times, Capparis species have been widely used in traditional medicine to treat various diseases. Our recent investigations have suggested Capparis ovata's potential anti-neuroinflammatory application for the treatment of multiple sclerosis (MS). The present study was designed to precisely determine the underlying mechanism of its anti-neuroinflammatory effect in a mouse model of MS. C. ovata water extract (COWE) was prepared using the plant's fruit, buds, and flower parts (Turkish Patent Institute, PT 2012/04,093). We immunized female C57BL/6J mice with MOG35-55/CFA. COWE was administered at a daily dose of 500mg/kg by oral gavage either from the day of immunization (T1) or at disease onset (T2) for 21days. Gene expression analysis was performed using a Mouse Multiple Sclerosis RT² Profiler PCR Array, and further determinations and validations of the identified genes were performed using qPCR. Whole-genome transcriptome profiling was analyzed using Agilent SurePrint G3 Mouse GE 8X60K microarrays. Immunohistochemical staining was applied to brain sections of the control and treated mice to examine the degree of degeneration. COWE was further fractionated and analyzed phytochemically using the Zivak Tandem Gold Triple Quadrupole LC/MS-MS system. COWE remarkably suppressed the development of EAE in T1, and the disease activity was completely inhibited. In the T2 group, the maximal score was significantly reduced compared with that of the parallel EAE group. The COWE suppression of EAE was associated with a significantly decreased expression of genes that are important in inflammatory signaling, such as TNFα, IL6, NF-κB, CCL5, CXCL9, and CXCK10. On the other hand, the expression of genes involved in myelination/remyelination was significantly increased. Immunohistochemical analysis further supported these effects, showing that the number of infiltrating immune cells was decreased in the brains of COWE-treated animals. In addition, differential expression profiling of the transcriptome revealed that COWE treatment caused the down regulation of a group of genes involved in the immune response, inflammatory response, antigen processing and presentation, B-cell-mediated immunity and innate immune response. Collectively, these results suggest anti-neuroinflammatory mechanisms by which COWE treatment delayed and suppressed the development of EAE and ameliorated the disease in mice with persistent clinical signs.

Yeast Interspecies Comparative Proteomics Reveals Divergence in Expression Profiles and Provides Insights into Proteome Resource Allocation and Evolutionary Roles of Gene Duplication

Omics analysis is a versatile approach for understanding the conservation and diversity of molecular systems across multiple taxa. In this study, we compared the proteome expression profiles of four yeast species (Saccharomyces cerevisiae, Saccharomyces mikatae, Kluyveromyces waltii, and Kluyveromyces lactis) grown on glucose- or glycerol-containing media. Conserved expression changes across all species were observed only for a small proportion of all proteins differentially expressed between the two growth conditions. Two Kluyveromyces species, both of which exhibited a high growth rate on glycerol, a nonfermentative carbon source, showed distinct species-specific expression profiles. In K. waltii grown on glycerol, proteins involved in the glyoxylate cycle and gluconeogenesis were expressed in high abundance. In K. lactis grown on glycerol, the expression of glycolytic and ethanol metabolic enzymes was unexpectedly low, whereas proteins involved in cytoplasmic translation, including ribosomal proteins and elongation factors, were highly expressed. These marked differences in the types of predominantly expressed proteins suggest that K. lactis optimizes the balance of proteome resource allocation between metabolism and protein synthesis giving priority to cellular growth. In S. cerevisiae, about 450 duplicate gene pairs were retained after whole-genome duplication. Intriguingly, we found that in the case of duplicates with conserved sequences, the total abundance of proteins encoded by a duplicate pair in S. cerevisiae was similar to that of protein encoded by nonduplicated ortholog in Kluyveromyces yeast. Given the frequency of haploinsufficiency, this observation suggests that conserved duplicate genes, even though minor cases of retained duplicates, do not exhibit a dosage effect in yeast, except for ribosomal proteins. Thus, comparative proteomic analyses across multiple species may reveal not only species-specific characteristics of metabolic processes under nonoptimal culture conditions but also provide valuable insights into intriguing biological principles, including the balance of proteome resource allocation and the role of gene duplication in evolutionary history.

Accounting for experimental noise reveals that mRNA levels, amplified by post-transcriptional processes, largely determine steady-state protein levels in yeast

Cells respond to their environment by modulating protein levels through mRNA transcription and post-transcriptional control. Modest observed correlations between global steady-state mRNA and protein measurements have been interpreted as evidence that mRNA levels determine roughly 40% of the variation in protein levels, indicating dominant post-transcriptional effects. However, the techniques underlying these conclusions, such as correlation and regression, yield biased results when data are noisy, missing systematically, and collinear---properties of mRNA and protein measurements---which motivated us to revisit this subject. Noise-robust analyses of 24 studies of budding yeast reveal that mRNA levels explain more than 85% of the variation in steady-state protein levels. Protein levels are not proportional to mRNA levels, but rise much more rapidly. Regulation of translation suffices to explain this nonlinear effect, revealing post-transcriptional amplification of, rather than competition with, transcriptional signals. These results substantially revise widely credited models of protein-level regulation, and introduce multiple noise-aware approaches essential for proper analysis of many biological phenomena.

Accounting for experimental noise reveals that mRNA levels, amplified by post-transcriptional processes, largely determine steady-state protein levels in yeast

Cells respond to their environment by modulating protein levels through mRNA transcription and post-transcriptional control. Modest observed correlations between global steady-state mRNA and protein measurements have been interpreted as evidence that mRNA levels determine roughly 40% of the variation in protein levels, indicating dominant post-transcriptional effects. However, the techniques underlying these conclusions, such as correlation and regression, yield biased results when data are noisy, missing systematically, and collinear---properties of mRNA and protein measurements---which motivated us to revisit this subject. Noise-robust analyses of 24 studies of budding yeast reveal that mRNA levels explain more than 85% of the variation in steady-state protein levels. Protein levels are not proportional to mRNA levels, but rise much more rapidly. Regulation of translation suffices to explain this nonlinear effect, revealing post-transcriptional amplification of, rather than competition with, transcriptional signals. These results substantially revise widely credited models of protein-level regulation, and introduce multiple noise-aware approaches essential for proper analysis of many biological phenomena.

Proteomic analysis of posttranslational modifications using iTRAQ in Leishmania

iTRAQ is a high coverage quantitative proteomics technique identifies and quantitates abundance changes of multiple (up to eight) distinct protein samples. To date, one iTRAQ-MS/MS assay can identify up to quarter of cells proteome. Each of the eight tags covalently binds to the N-terminus as well as arginine and lysine side chains of peptides, enabling labeling of the entire peptide population in each sample. Following tagging, the various protein samples are mixed and subjected to LC-MS/MS analysis. In the first round identical peptides from the different protein populations focus in a single pick. Subsequently, sequence of each peptide is determined. The tags whose m/z is similar to that of natural amino acids are used to determine relative abundance. To date, iTRAQ enabled identification of almost 2,000 Leishmania proteins. Here, we provide protocols for protein abundance changes and for phosphoproteomics analysis in Leishmania parasites.

Statistical detection of quantitative protein biomarkers provides insights into signaling networks deregulated in acute myeloid leukemia

The increasing coverage and sensitivity of LC-MS/MS-based proteomics have expanded its applications in systems medicine. In particular, label-free quantitation approaches are enabling biomarker discovery in terms of statistical comparison of proteomic profiles across large numbers of clinical samples. However, it still remains poorly understood how much protein markers can add novel insights compared to markers derived from mRNA transcriptomic profiling. Using paired label-free LC-MS/MS and gene expression microarray measurements from primary samples of patients with acute myeloid leukemia (AML), we demonstrate here that while the quantitative proteomic and transcriptomic profiles were highly correlated, in general, the marker panels showing statistically significant expression changes across the disease and healthy groups were profoundly different between protein and mRNA levels. In particular, the proteomic assay enabled unique links to known leukemic processes, which were missed when using the transcriptomic profiling alone, as well as identified additional links to metabolic regulators and chromatin remodelers, such as GPX1, fumarate hydratase, and SET oncogene, which have subsequently been evaluated in independent AML samples. Overall, these results highlighted the complementary and informative view obtained from the quantitative LC-MS/MS approach into the AML deregulated signaling networks.

A proteomic strategy for global analysis of plant protein complexes

Global analyses of protein complex assembly, composition, and location are needed to fully understand how cells coordinate diverse metabolic, mechanical, and developmental activities. The most common methods for proteome-wide analysis of protein complexes rely on affinity purification-mass spectrometry or yeast two-hybrid approaches. These methods are time consuming and are not suitable for many plant species that are refractory to transformation or genome-wide cloning of open reading frames. Here, we describe the proof of concept for a method allowing simultaneous global analysis of endogenous protein complexes that begins with intact leaves and combines chromatographic separation of extracts from subcellular fractions with quantitative label-free protein abundance profiling by liquid chromatography-coupled mass spectrometry. Applying this approach to the crude cytosolic fraction of Arabidopsis thaliana leaves using size exclusion chromatography, we identified hundreds of cytosolic proteins that appeared to exist as components of stable protein complexes. The reliability of the method was validated by protein immunoblot analysis and comparisons with published size exclusion chromatography data and the masses of known complexes. The method can be implemented with appropriate instrumentation, is applicable to any biological system, and has the potential to be further developed to characterize the composition of protein complexes and measure the dynamics of protein complex localization and assembly under different conditions.

Absolute proteome and phosphoproteome dynamics during the cell cycle of Schizosaccharomyces pombe (Fission Yeast)

To quantify cell cycle-dependent fluctuations on a proteome-wide scale, we performed integrative analysis of the proteome and phosphoproteome during the four major phases of the cell cycle in Schizosaccharomyces pombe. In highly synchronized cells, we identified 3753 proteins and 3682 phosphorylation events and relatively quantified 65% of the data across all phases. Quantitative changes during the cell cycle were infrequent and weak in the proteome but prominent in the phosphoproteome. Protein phosphorylation peaked in mitosis, where the median phosphorylation site occupancy was 44%, about 2-fold higher than in other phases. We measured copy numbers of 3178 proteins, which together with phosphorylation site stoichiometry enabled us to estimate the absolute amount of protein-bound phosphate, as well as its change across the cell cycle. Our results indicate that 23% of the average intracellular ATP is utilized by protein kinases to phosphorylate their substrates to drive regulatory processes during cell division. Accordingly, we observe that phosphate transporters and phosphate-metabolizing enzymes are phosphorylated and therefore likely to be regulated in mitosis.

Modelling the efficiency of codon-tRNA interactions based on codon usage bias

The tRNA adaptation index (tAI) is a widely used measure of the efficiency by which a coding sequence is recognized by the intra-cellular tRNA pool. This index includes among others weights that represent wobble interactions between codons and tRNA molecules. Currently, these weights are based only on the gene expression in Saccharomyces cerevisiae. However, the efficiencies of the different codon–tRNA interactions are expected to vary among different organisms. In this study, we suggest a new approach for adjusting the tAI weights to any target model organism without the need for gene expression measurements. Our method is based on optimizing the correlation between the tAI and a measure of codon usage bias. Here, we show that in non-fungal the new tAI weights predict protein abundance significantly better than the traditional tAI weights. The unique tRNA–codon adaptation weights computed for 100 different organisms exhibit a significant correlation with evolutionary distance. The reported results demonstrate the usefulness of the new measure in future genomic studies.

Systems analysis of the prostate tumor suppressor NKX3.1 supports roles in DNA repair and luminal cell differentiation

NKX3.1 is a homeobox transcription factor whose function as a prostate tumor suppressor remains insufficiently understood because neither the transcriptional program governed by NKX3.1, nor its interacting proteins have been fully revealed. Using affinity purification and mass spectrometry, we have established an extensive NKX3.1 interactome which contains the DNA repair proteins Ku70, Ku80, and PARP, thus providing a molecular underpinning to previous reports implicating NKX3.1 in DNA repair. Transcriptomic profiling of NKX3.1-negative prostate epithelial cells acutely expressing NKX3.1 revealed a rapid and complex response that is a near mirror image of the gene expression signature of human prostatic intraepithelial neoplasia (PIN). Pathway and network analyses suggested that NKX3.1 actuates a cellular reprogramming toward luminal cell differentiation characterized by suppression of pro-oncogenic c-MYC and interferon-STAT signaling and activation of tumor suppressor pathways. Consistently, ectopic expression of NKX3.1 conferred a growth arrest depending on TNFα and JNK signaling. We propose that the tumor suppressor function of NKX3.1 entails a transcriptional program that maintains the differentiation state of secretory luminal cells and that disruption of NKX3.1 contributes to prostate tumorigenesis by permitting luminal cell de-differentiation potentially augmented by defects in DNA repair.

Entrainment to periodic initiation and transition rates in a computational model for gene translation

Periodic oscillations play an important role in many biomedical systems. Proper functioning of biological systems that respond to periodic signals requires the ability to synchronize with the periodic excitation. For example, the sleep/wake cycle is a manifestation of an internal timing system that synchronizes to the solar day. In the terminology of systems theory, the biological system must entrain or phase-lock to the periodic excitation. Entrainment is also important in synthetic biology. For example, connecting several artificial biological systems that entrain to a common clock may lead to a well-functioning modular system. The cell-cycle is a periodic program that regulates DNA synthesis and cell division. Recent biological studies suggest that cell-cycle related genes entrain to this periodic program at the gene translation level, leading to periodically-varying protein levels of these genes. The ribosome flow model (RFM) is a deterministic model obtained via a mean-field approximation of a stochastic model from statistical physics that has been used to model numerous processes including ribosome flow along the mRNA. Here we analyze the RFM under the assumption that the initiation and/or transition rates vary periodically with a common period . We show that the ribosome distribution profile in the RFM entrains to this periodic excitation. In particular, the protein synthesis pattern converges to a unique periodic solution with period . To the best of our knowledge, this is the first proof of entrainment in a mathematical model for translation that encapsulates aspects such as initiation and termination rates, ribosomal movement and interactions, and non-homogeneous elongation speeds along the mRNA. Our results support the conjecture that periodic oscillations in tRNA levels and other factors related to the translation process can induce periodic oscillations in protein levels, and may suggest a new approach for re-engineering genetic systems to obtain a desired, periodic, protein synthesis rate.

The Role of Mass Spectrometry in the "Omics" Era

Mass spectrometry (MS) is one of the key analytical technology on which the emerging ''-omics'' approaches are based. It may provide detection and quantization of thousands of proteins and biologically active metabolites from a tissue, body fluid or cell culture working in a ''global'' or ''targeted'' manner, down to ultra-trace levels. It can be expected that the high performance of MS technology, coupled to routine data handling, will soon bring fruit in the request for a better understanding of human diseases, leading to new molecular biomarkers, hence affecting drug targets and therapies. In this review, we focus on the main advances in the MS technologies, influencing genomics, transcriptomics, proteomics, lipidomics and metabolomics fields, up to the most recent MS applications to meta-omic studies.

Estrogen receptor alpha is expressed in mesenteric mesothelial cells and is internalized in caveolae upon Freund's adjuvant treatment

Transformation of epithelial cells into connective tissue cells (epithelial-mesenchymal transition, EMT) is a complex mechanism involved in tumor metastasis, and in normal embryogenesis, while type II EMT is mainly associated with inflammatory events and tissue regenaration.

In this study we examined type II EMT at the ultrastructural and molecular level during the inflammatory process induced by Freund's adjuvant treatment in rat mesenteric mesothelial cells. We found that upon the inflammatory stimulus mesothelial cells lost contact with the basal lamina and with each other, and were transformed into spindle-shaped cells. These morphological changes were accompanied by release of interleukins IL-1alpha, -1beta and IL-6 and by secretion of transforming growth factor beta (TGF-β) into the peritoneal cavity. Mesothelial cells also expressed estrogen receptor alpha (ER-α) as shown by immunolabeling at the light and electron microscopical levels, as well as by quantitative RT-PCR. The mRNA level of ER-α showed an inverse correlation with the secretion of TGF-β. At the cellular and subcellular levels ER-α was colocalized with the coat protein caveolin-1 and was found in the plasma membrane of mesothelial cells, in caveolae close to multivesicular bodies (MVBs) or in the membrane of these organelles, suggesting that ER-α is internalized via caveola-mediated endocytosis during inflammation. We found asymmetric, thickened, electron dense areas on the limiting membrane of MVBs (MVB plaques) indicating that these sites may serve as platforms for collecting and organizing regulatory proteins. Our morphological observations and biochemical data can contribute to form a potential model whereby ER-α and its caveola-mediated endocytosis might play role in TGF-β induced type II EMT in vivo.

Global features of gene expression on the proteome and transcriptome levels in S. coelicolor during germination

Streptomycetes have been studied mostly as producers of secondary metabolites, while the transition from dormant spores to an exponentially growing culture has largely been ignored. Here, we focus on a comparative analysis of fluorescently and radioactively labeled proteome and microarray acquired transcriptome expressed during the germination of Streptomyces coelicolor. The time-dynamics is considered, starting from dormant spores through 5.5 hours of growth with 13 time points. Time series of the gene expressions were analyzed using correlation, principal components analysis and an analysis of coding genes utilization. Principal component analysis was used to identify principal kinetic trends in gene expression and the corresponding genes driving S. coelicolor germination. In contrast with the correlation analysis, global trends in the gene/protein expression reflected by the first principal components showed that the prominent patterns in both the protein and the mRNA domains are surprisingly well correlated. Analysis of the number of expressed genes identified functional groups activated during different time intervals of the germination.

New universal rules of eukaryotic translation initiation fidelity

The accepted model of eukaryotic translation initiation begins with the scanning of the transcript by the pre-initiation complex from the 5′end until an ATG codon with a specific nucleotide (nt) context surrounding it is recognized (Kozak rule). According to this model, ATG codons upstream to the beginning of the ORF should affect translation. We perform for the first time, a genome-wide statistical analysis, uncovering a new, more comprehensive and quantitative, set of initiation rules for improving the cost of translation and its efficiency. Analyzing dozens of eukaryotic genomes, we find that in all frames there is a universal trend of selection for low numbers of ATG codons; specifically, 16–27 codons upstream, but also 5–11 codons downstream of the START ATG, include less ATG codons than expected. We further suggest that there is selection for anti optimal ATG contexts in the vicinity of the START ATG. Thus, the efficiency and fidelity of translation initiation is encoded in the 5′UTR as required by the scanning model, but also at the beginning of the ORF.

The observed nt patterns suggest that in all the analyzed organisms the pre-initiation complex often misses the START ATG of the ORF, and may start translation from an alternative initiation start-site. Thus, to prevent the translation of undesired proteins, there is selection for nucleotide sequences with low affinity to the pre-initiation complex near the beginning of the ORF. With the new suggested rules we were able to obtain a twice higher correlation with ribosomal density and protein levels in comparison to the Kozak rule alone (e.g. for protein levels r = 0.7 vs. r = 0.31; p<10⁻¹²).

Gene translation is an important step of the intra-cellular protein synthesis, which is a central process in all living organisms. Thus, understanding how translation efficiency is encoded in transcripts has ramifications to every biomedical discipline. The aim of the current study is to decipher the way translation initiation fidelity is encoded in eukaryotic transcripts, and how evolution shapes the beginning of transcripts. Based on the genomes of dozens of organisms we were able to derive a new, more precise, set of rules related to this process, facilitating a high resolution view of the mechanisms aiding translation initiation fidelity. Among others, we show that there is a universal trend of selection for low numbers of ATG codons upstream, but also in the 5–11 codons downstream of the START ATG, presumably to prevent translation of alternative ORFs over the main one. With the new suggested rules we were able to obtain a twice higher correlation with ribosomal density and protein levels in comparison to the previous translation initiation efficiency rule.

Frac-seq reveals isoform-specific recruitment to polyribosomes

Pre-mRNA splicing is required for the accurate expression of virtually all human protein coding genes. However, splicing also plays important roles in coordinating subsequent steps of pre-mRNA processing such as polyadenylation and mRNA export. Here, we test the hypothesis that nuclear pre-mRNA processing influences the polyribosome association of alternative mRNA isoforms. By comparing isoform ratios in cytoplasmic and polyribosomal extracts, we determined that the alternative products of ∼30% (597/1954) of mRNA processing events are differentially partitioned between these subcellular fractions. Many of the events exhibiting isoform-specific polyribosome association are highly conserved across mammalian genomes, underscoring their possible biological importance. We find that differences in polyribosome association may be explained, at least in part by the observation that alternative splicing alters the cis-regulatory landscape of mRNAs isoforms. For example, inclusion or exclusion of upstream open reading frames (uORFs) in the 5′UTR as well as Alu-elements and microRNA target sites in the 3′UTR have a strong influence on polyribosome association of alternative mRNA isoforms. Taken together, our data demonstrate for the first time the potential link between alternative splicing and translational control of the resultant mRNA isoforms.

Extensive mass spectrometry-based analysis of the fission yeast proteome: the Schizosaccharomyces pombe PeptideAtlas

We report a high quality and system-wide proteome catalogue covering 71% (3,542 proteins) of the predicted genes of fission yeast, Schizosaccharomyces pombe, presenting the largest protein dataset to date for this important model organism. We obtained this high proteome and peptide (11.4 peptides/protein) coverage by a combination of extensive sample fractionation, high resolution Orbitrap mass spectrometry, and combined database searching using the iProphet software as part of the Trans-Proteomics Pipeline. All raw and processed data are made accessible in the S. pombe PeptideAtlas. The identified proteins showed no biases in functional properties and allowed global estimation of protein abundances. The high coverage of the PeptideAtlas allowed correlation with transcriptomic data in a system-wide manner indicating that post-transcriptional processes control the levels of at least half of all identified proteins. Interestingly, the correlation was not equally tight for all functional categories ranging from r(s) >0.80 for proteins involved in translation to r(s) <0.45 for signal transduction proteins. Moreover, many proteins involved in DNA damage repair could not be detected in the PeptideAtlas despite their high mRNA levels, strengthening the translation-on-demand hypothesis for members of this protein class. In summary, the extensive and publicly available S. pombe PeptideAtlas together with the generated proteotypic peptide spectral library will be a useful resource for future targeted, in-depth, and quantitative proteomic studies on this microorganism.

Genetic mapping and characteristics of genes specifically or preferentially expressed during fiber development in cotton

Cotton fiber is an ideal model to study cell elongation and cell wall construction in plants. During fiber development, some genes and proteins have been reported to be specifically or preferentially expressed. Mapping of them will reveal the genomic distribution of these genes, and will facilitate selection in cotton breeding. Based on previous reports, we designed 331 gene primers and 164 protein primers, and used single-strand conformation polymorphism (SSCP) to map and integrate them into our interspecific BC₁ linkage map. This resulted in the mapping of 57 loci representing 51 genes or proteins on 22 chromosomes. For those three markers which were tightly linked with quantitative trait loci (QTLs), the QTL functions obtained in this study and gene functions reported in previous reports were consistent. Reverse transcription-polymerase chain reaction (RT-PCR) analysis of 52 polymorphic functional primers showed that 21 gene primers and 17 protein primers had differential expression between Emian22 (Gossypium hirsutum) and 3–79 (G. barbadense). Both RT-PCR and quantitative real-time PCR (qRT-PCR) analyses of the three markers tightly linked with QTLs were consistent with QTL analysis and field experiments. Gene Ontology (GO) categorization revealed that almost all 51 mapped genes belonged to multiple categories that contribute to fiber development, indicating that fiber development is a complex process regulated by various genes. These 51 genes were all specifically or preferentially expressed during fiber cell elongation and secondary wall biosynthesis. Therefore, these functional gene-related markers would be beneficial for the genetic improvement of cotton fiber length and strength.

Quantitative analysis of fission yeast transcriptomes and proteomes in proliferating and quiescent cells

Data on absolute molecule numbers will empower the modeling, understanding, and comparison of cellular functions and biological systems. We quantified transcriptomes and proteomes in fission yeast during cellular proliferation and quiescence. This rich resource provides the first comprehensive reference for all RNA and most protein concentrations in a eukaryote under two key physiological conditions. The integrated data set supports quantitative biology and affords unique insights into cell regulation. Although mRNAs are typically expressed in a narrow range above 1 copy/cell, most long, noncoding RNAs, except for a distinct subset, are tightly repressed below 1 copy/cell. Cell-cycle-regulated transcription tunes mRNA numbers to phase-specific requirements but can also bring about more switch-like expression. Proteins greatly exceed mRNAs in abundance and dynamic range, and concentrations are regulated to functional demands. Upon transition to quiescence, the proteome changes substantially, but, in stark contrast to mRNAs, proteins do not uniformly decrease but scale with cell volume.

Toward a genome-wide landscape of translational control

Genome-wide analysis of translational control has taken strides in recent years owing to the advent of high-throughput technologies, including DNA microarrays and deep sequencing. Global studies have unraveled a principal role, among posttranscriptional mechanisms, for mRNA translation in determining protein levels in the cell. The impact of translational control in dynamic regulation of the proteome under different conditions is increasingly appreciated. Here we review genome-wide studies that use high-throughput techniques and bioinformatics to assess the role of mRNA translation in the regulation of protein levels; we also discuss how genome-wide data on mRNA translation can be obtained, analyzed, and used to identify mechanisms of translational control.

Is central dogma a global property of cellular information flow?

The central dogma of molecular biology has come under scrutiny in recent years. Here, we reviewed high-throughput mRNA and protein expression data of Escherichia coli, Saccharomyces cerevisiae, and several mammalian cells. At both single cell and population scales, the statistical comparisons between the entire transcriptomes and proteomes show clear correlation structures. In contrast, the pair-wise correlations of single transcripts to proteins show nullity. These data suggest that the organizing structure guiding cellular processes is observed at omics-wide scale, and not at single molecule level. The central dogma, thus, globally emerges as an average integrated flow of cellular information.

On the steady-state distribution in the homogeneous ribosome flow model

A central biological process in all living organisms is gene translation. Developing a deeper understanding of this complex process may have ramifications to almost every biomedical discipline. Reuveni et al. recently proposed a new computational model of gene translation called the Ribosome Flow Model (RFM). In this paper, we consider a particular case of this model, called the Homogeneous Ribosome Flow Model (HRFM). From a biological viewpoint, this corresponds to the case where the transition rates of all the coding sequence codons are identical. This regime has been suggested recently based on experiments in mouse embryonic cells. We consider the steady-state distribution of the HRFM. We provide formulas that relate the different parameters of the model in steady state. We prove the following properties: 1) the ribosomal density profile is monotonically decreasing along the coding sequence; 2) the ribosomal density at each codon monotonically increases with the initiation rate; and 3) for a constant initiation rate, the translation rate monotonically decreases with the length of the coding sequence. In addition, we analyze the translation rate of the HRFM at the limit of very high and very low initiation rate, and provide explicit formulas for the translation rate in these two cases. We discuss the relationship between these theoretical results and biological findings on the translation process.

Stability analysis of the ribosome flow model

Gene translation is a central process in all living organisms. Developing a better understanding of this complex process may have ramifications to almost every biomedical discipline. Recently, Reuveni et al. proposed a new computational model of this process called the ribosome flow model (RFM). In this study, we show that the dynamical behavior of the RFM is relatively simple. There exists a unique equilibrium point e and every trajectory converges to e. Furthermore, convergence is monotone in the sense that the distance to e can never increase. This qualitative behavior is maintained for any feasible set of parameter values, suggesting that the RFM is highly robust. Our analysis is based on a contraction principle and the theory of monotone dynamical systems. These analysis tools may prove useful in studying other properties of the RFM as well as additional intracellular biological processes.

Comparison of in-gel protein separation techniques commonly used for fractionation in mass spectrometry-based proteomic profiling

Fractionation of complex samples at the cellular, subcellular, protein, or peptide level is an indispensable strategy to improve the sensitivity in mass spectrometry-based proteomic profiling. This study revisits, evaluates, and compares the most common gel-based protein separation techniques i.e. 1D SDS-PAGE, 1D preparative SDS-PAGE, IEF-IPG, and 2D-PAGE in their performance as fractionation approaches in nano LC-ESI-MS/MS analysis of a mixture of protein standards and mitochondrial extracts isolated from rat liver. This work demonstrates that all the above techniques provide complementary protein identification results, but 1D SDS-PAGE and IEF-IPG had the highest number of identifications. The IEF-IPG technique resulted in the highest average number of detected peptides per protein. The 2D-PAGE was evaluated as a protein fractionation approach. This work shows that the recovery of proteins and resulting proteolytic digests is highly dependent on the total volume of the gel matrix. The performed comparison of the fractionation techniques demonstrates the potential of a combination of orthogonal 1D SDS-PAGE and IEF-IPG for the improved sensitivity of profiling without significant decrease in throughput.

Heat induction of a novel Rad9 variant from a cryptic translation initiation site reduces mitotic commitment

Exposure of human cells to heat switches the activating signal of the DNA damage checkpoint from genotoxic to temperature stress. This change reduces mitotic commitment at the expense of DNA break repair. The thermal alterations behind this switch remain elusive despite the successful use of heat to sensitise cancer cells to DNA breaks. Rad9 is a highly conserved subunit of the Rad9-Rad1-Hus1 (9-1-1) checkpoint-clamp that is loaded by Rad17 onto damaged chromatin. At the DNA, Rad9 activates the checkpoint kinases Rad3(ATR) and Chk1 to arrest cells in G2. Using Schizosaccharomyces pombe as a model eukaryote, we discovered a new variant of Rad9, Rad9-M50, whose expression is specifically induced by heat. High temperatures promote alternative translation from a cryptic initiation codon at methionine-50. This process is restricted to cycling cells and is independent of the temperature-sensing mitogen-activated protein kinase (MAPK) pathway. While full-length Rad9 delays mitosis in the presence of DNA lesions, Rad9-M50 functions in a remodelled checkpoint pathway to reduce mitotic commitment at elevated temperatures. This remodelled pathway still relies on Rad1 and Hus1, but acts independently of Rad17. Heat-induction of Rad9-M50 ensures that the kinase Chk1 remains in a hypo-phosphorylated state. Elevated temperatures specifically reverse the DNA-damage-induced modification of Chk1 in a manner dependent on Rad9-M50. Taken together, heat reprogrammes the DNA damage checkpoint at the level of Chk1 by inducing a Rad9 variant that can act outside of the canonical 9-1-1 complex.

Conjugated linoleic acids attenuate FSH- and IGF1-stimulated cell proliferation; IGF1, GATA4, and aromatase expression; and estradiol-17β production in buffalo granulosa cells involving PPARγ, PTEN, and PI3K/Akt

Conjugated linoleic acid (CLA) has drawn much interest in last two decades in the area ranging from anticancer activity to obesity. A number of research papers have been published recently with regard to CLA's additional biological functions as reproductive benefits. However, not much is known how this mixture of isomeric compounds mediates its beneficial effects particularly on fertility. In this study, we demonstrated the cross talk between downstream signaling of CLA and important hormone regulators of endocrine system, i.e. FSH and IGF1, on buffalo granulosa cell function (proliferation and steroidogenesis). Experiments were performed in primary serum-free buffalo granulosa cell culture, where cells were incubated with CLA in combination with FSH (25 ng/ml) and IGF1 (50  ng/ml). Results showed that 10 μM CLA inhibits FSH- and IGF1-induced granulosa cell proliferation; aromatase, GATA4, and IGF1 mRNA; and estradiol-17β production. Western blot analysis of total cell lysates revealed that CLA intervenes the IGF1 signaling by decreasing p-Akt. In addition, CLA was found to upregulate peroxisome proliferator-activated receptor-gamma (PPARG) and phosphatase and tensin homolog (PTEN) level in granulosa cells. Further study using PPARG- and PTEN-specific inhibitors supports the potential role of CLA in granulosa cell proliferation and steroidogenesis involving PPARG, PTEN, and PI3K/Akt pathway.

Dual modification of Alzheimer's disease PHF-tau protein by lysine methylation and ubiquitylation: a mass spectrometry approach

In sporadic Alzheimer’s disease (AD), neurofibrillary lesion formation is preceded by extensive post-translational modification of the microtubule associated protein tau. To identify the modification signature associated with tau lesion formation at single amino acid resolution, immunopurified paired helical filaments were isolated from AD brain and subjected to nanoflow liquid chromatography–tandem mass spectrometry analysis. The resulting spectra identified monomethylation of lysine residues as a new tau modification. The methyl-lysine was distributed among seven residues located in the projection and microtubule binding repeat regions of tau protein, with one site, K254, being a substrate for a competing lysine modification, ubiquitylation. To characterize methyl lysine content in intact tissue, hippocampal sections prepared from post mortem late-stage AD cases were subjected to double-label confocal fluorescence microscopy using anti-tau and anti-methyl lysine antibodies. Anti-methyl lysine immunoreactivity colocalized with 78 ± 13% of neurofibrillary tangles in these specimens. Together these data provide the first evidence that tau in neurofibrillary lesions is post-translationally modified by lysine methylation.

Label-free protein quantitation using weighted spectral counting

Mass spectrometry (MS)-based shotgun proteomics allows protein identifications even in complex biological samples. Protein abundances can then be estimated from the counts of MS/MS spectra attributable to each protein, provided that one corrects for differential MS-detectability of the contributing peptides. We describe the use of a method, APEX, which calculates Absolute Protein EXpression levels based on learned correction factors, MS/MS spectral counts, and each protein's probability of correct identification.The APEX-based calculations consist of three parts: (1) Using training data, peptide sequences and their sequence properties, a model is built that can be used to estimate MS-detectability (O (i)) for any given protein. (2) Absolute abundances of proteins measured in an MS/MS experiment are calculated with information from spectral counts, identification probabilities and the learned O (i)-values. (3) Simple statistics allow for significance analysis of differential expression in two distinct biological samples, i.e., measuring relative protein abundances. APEX-based protein abundances span more than four orders of magnitude and are applicable to mixtures of hundreds to thousands of proteins from any type of organism.

Genome-scale analysis of translation elongation with a ribosome flow model

We describe the first large scale analysis of gene translation that is based on a model that takes into account the physical and dynamical nature of this process. The Ribosomal Flow Model (RFM) predicts fundamental features of the translation process, including translation rates, protein abundance levels, ribosomal densities and the relation between all these variables, better than alternative ('non-physical') approaches. In addition, we show that the RFM can be used for accurate inference of various other quantities including genes' initiation rates and translation costs. These quantities could not be inferred by previous predictors. We find that increasing the number of available ribosomes (or equivalently the initiation rate) increases the genomic translation rate and the mean ribosome density only up to a certain point, beyond which both saturate. Strikingly, assuming that the translation system is tuned to work at the pre-saturation point maximizes the predictive power of the model with respect to experimental data. This result suggests that in all organisms that were analyzed (from bacteria to Human), the global initiation rate is optimized to attain the pre-saturation point. The fact that similar results were not observed for heterologous genes indicates that this feature is under selection. Remarkably, the gap between the performance of the RFM and alternative predictors is strikingly large in the case of heterologous genes, testifying to the model's promising biotechnological value in predicting the abundance of heterologous proteins before expressing them in the desired host.

Different effects of night versus day high temperature on rice quality and accumulation profiling of rice grain proteins during grain filling

High temperature has adverse effects on rice yield and quality. The different influences of night high temperature (NHT) and day high temperature (DHT) on rice quality and seed protein accumulation profiles during grain filling in indica rice '9311' were studied in this research. The treatment temperatures of the control, NHT, and DHT were 28°C/20°C, 27°C/35°C, and 35°C/27°C, respectively, and all the treatments were maintained for 20 days. The result of rice quality analysis indicated that compared with DHT, NHT exerted less effect on head rice rate and chalkiness, whereas greater effect on grain weight. Moreover, the dynamic accumulation change profiles of 61 protein spots, differentially accumulated and successfully identified under NHT and DHT conditions, were performed by proteomic approach. The results also showed that the different suppressed extent of accumulation amount of cyPPDKB might result in different grain chalkiness between NHT and DHT. Most identified isoforms of proteins, such as PPDK and pullulanase, displayed different accumulation change patterns between NHT and DHT. In addition, compared with DHT, NHT resulted in the unique accumulation patterns of stress and defense proteins. Taken together, the mechanisms of seed protein accumulation profiles induced by NHT and DHT during grain filling should be different in rice, and the potential molecular basis is discussed in this study.

Quantitative time-course profiling of parasite and host cell proteins in the human malaria parasite Plasmodium falciparum

Studies of the Plasmodium falciparum transcriptome have shown that the tightly controlled progression of the parasite through the intra-erythrocytic developmental cycle (IDC) is accompanied by a continuous gene expression cascade in which most expressed genes exhibit a single transcriptional peak. Because the biochemical and cellular functions of most genes are mediated by the encoded proteins, understanding the relationship between mRNA and protein levels is crucial for inferring biological activity from transcriptional gene expression data. Although studies on other organisms show that <50% of protein abundance variation may be attributable to corresponding mRNA levels, the situation in Plasmodium is further complicated by the dynamic nature of the cyclic gene expression cascade. In this study, we simultaneously determined mRNA and protein abundance profiles for P. falciparum parasites during the IDC at 2-hour resolution based on oligonucleotide microarrays and two-dimensional differential gel electrophoresis protein gels. We find that most proteins are represented by more than one isoform, presumably because of post-translational modifications. Like transcripts, most proteins exhibit cyclic abundance profiles with one peak during the IDC, whereas the presence of functionally related proteins is highly correlated. In contrast, the abundance of most parasite proteins peaks significantly later (median 11 h) than the corresponding transcripts and often decreases slowly in the second half of the IDC. Computational modeling indicates that the considerable and varied incongruence between transcript and protein abundance may largely be caused by the dynamics of translation and protein degradation. Furthermore, we present cyclic abundance profiles also for parasite-associated human proteins and confirm the presence of five human proteins with a potential role in antioxidant defense within the parasites. Together, our data provide fundamental insights into transcript-protein relationships in P. falciparum that are important for the correct interpretation of transcriptional data and that may facilitate the improvement and development of malaria diagnostics and drug therapy.

Statistical methods and models for bridging Omics data levels

Multiple Omics datasets (for example, high throughput mRNA and protein measurements for the same set of genes) are beginning to appear more widely within the fields of bioinformatics and computational biology. There are many tools available for the analysis of single datasets but two (or more) sets of coupled observations present more of a challenge. I describe some of the methods available - from classical statistical techniques to more recent advances from the fields of Machine Learning and Pattern Recognition for linking Omics data levels with particular focus on transcriptomics and proteomics profiles.

Multiple levels of gene regulation mediate differentiation of the intracellular pathogen Leishmania

For many years, mRNA abundance has been used as the surrogate measure of gene expression in biological systems. However, recent genome-scale analyses in both bacteria and eukaryotes have revealed that mRNA levels correlate with steady-state protein abundance for only 50-70% of genes, indicating that translation and post-translation processes also play important roles in determining gene expression. What is not yet clear is whether dynamic processes such as cell cycle progression, differentiation, or response to environmental changes change the relationship between mRNA and protein abundance. Here, we describe a systems approach to interrogate promastigote-to-amastigote differentiation in the obligatory intracellular parasitic protozoan Leishmania donovani. Our results indicate that regulation of mRNA levels plays a major role early in the differentiation process, while translation and post-translational regulation are more important in the latter part. In addition, it appears that the differentiation signal causes a transient global increase in the rate of protein synthesis, which is subsequently down-regulated by phosphorylation of α-subunit of translation initiation factor 2. Thus, Leishmania dynamically changes the relationship between mRNA and protein abundance as it adapts to new environmental circumstances. It is likely that similar mechanisms play a more important role than previously recognized in regulation of gene expression in other organisms.

Quantitative proteomics and transcriptomics addressing the estrogen receptor subtype-mediated effects in T47D breast cancer cells exposed to the phytoestrogen genistein

The present study addresses, by transcriptomics and quantitative stable isotope labeling by amino acids in cell culture (SILAC)-based proteomics, the estrogen receptor α (ERα) and β (ERβ)-mediated effects on gene and protein expression in T47D breast cancer cells exposed to the phytoestrogen genistein. Using the T47D human breast cancer cell line with tetracycline-dependent ERβ expression (T47D-ERβ), the effect of a varying intracellular ERα/ERβ ratio on genistein-induced gene and protein expression was characterized. Results obtained reveal that in ERα-expressing T47D-ERβ cells with inhibited ERβ expression genistein induces transcriptomics and proteomics signatures pointing at rapid cell growth and migration by dynamic activation of cytoskeleton remodeling. The data reveal an interplay between integrins, focal adhesion kinase, CDC42, and actin cytoskeleton signaling cascades, occurring upon genistein treatment, in the T47D-ERβ breast cancer cells with low levels of ERα and no expression of ERβ. In addition, data from our study indicate that ERβ-mediated gene and protein expression counteracts ERα-mediated effects because in T47D-ERβ cells expressing ERβ and exposed to genistein transcriptomics and proteomics signatures pointing at a clear down-regulation of cell growth and induction of cell cycle arrest and apoptosis were demonstrated. These results suggest that ERβ decreases cell motility and metastatic potential as well as cell survival of the breast cancer cell line. It is concluded that the effects of genistein on proteomics and transcriptomics end points in the T47D-ERβ cell model are comparable with those reported previously for estradiol with the ultimate estrogenic effect being dependent on the relative affinity for both receptors and on the receptor phenotype (ERα/ERβ ratio) in the cells or tissue of interest.

Global proteomics reveal an atypical strategy for carbon/nitrogen assimilation by a cyanobacterium under diverse environmental perturbations

Cyanobacteria, the only prokaryotes capable of oxygenic photosynthesis, are present in diverse ecological niches and play crucial roles in global carbon and nitrogen cycles. To proliferate in nature, cyanobacteria utilize a host of stress responses to accommodate periodic changes in environmental conditions. A detailed knowledge of the composition of, as well as the dynamic changes in, the proteome is necessary to gain fundamental insights into such stress responses. Toward this goal, we have performed a large-scale proteomic analysis of the widely studied model cyanobacterium Synechocystis sp. PCC 6803 under 33 different environmental conditions. The resulting high-quality dataset consists of 22,318 unique peptides corresponding to 1955 proteins, a coverage of 53% of the predicted proteome. Quantitative determination of protein abundances has led to the identification of 1198 differentially regulated proteins. Notably, our analysis revealed that a common stress response under various environmental perturbations, irrespective of amplitude and duration, is the activation of atypical pathways for the acquisition of carbon and nitrogen from urea and arginine. In particular, arginine is catabolized via putrescine to produce succinate and glutamate, sources of carbon and nitrogen, respectively. This study provides the most comprehensive functional and quantitative analysis of the Synechocystis proteome to date, and shows that a significant stress response of cyanobacteria involves an uncommon mode of acquisition of carbon and nitrogen.