The effect of cold stress on the proteome of the marine bacterium Pseudomonas fluorescens BA3SM1 and its ability to cope with metal excess

This study examined the effect of cold stress on the proteome and metal tolerance of Pseudomonas fluorescens BA3SM1, a marine strain isolated from tidal flat sediments. When cold stress (+10 °C for 36 h) was applied before moderate metal stress (0.4 mM Cd, 0.6 mM Cd, 1.5 mM Zn, and 1.5 mM Cu), growth disturbances induced by metal, in comparison with respective controls, were reduced for Cd and Zn while they were pronounced for Cu. This marine strain was able to respond to cold stress through a number of changes in protein regulation. Analysis of the predicted differentially expressed protein functions demonstrated that some mechanisms developed under cold stress were similar to those developed in response to Cd, Zn, and Cu. Therefore, pre-cold stress could help this strain to better counteract toxicity of moderate concentrations of some metals. P. fluorescens BA3SM1 was able to remove up to 404.3 mg Cd/g dry weight, 172.5 mg Zn/g dry weight, and 11.3 mg Cu/g dry weight and its metal biosorption ability seemed to be related to the bacterial growth phase. Thus, P. fluorescens BA3SM1 appears as a promising agent for bioremediation processes, even at low temperatures.

Low probability of initiating nirS transcription explains observed gas kinetics and growth of bacteria switching from aerobic respiration to denitrification

In response to impending anoxic conditions, denitrifying bacteria sustain respiratory metabolism by producing enzymes for reducing nitrogen oxyanions/-oxides (NO_x) to N₂ (denitrification). Since denitrifying bacteria are non-fermentative, the initial production of denitrification proteome depends on energy from aerobic respiration. Thus, if a cell fails to synthesise a minimum of denitrification proteome before O₂ is completely exhausted, it will be unable to produce it later due to energy-limitation. Such entrapment in anoxia is recently claimed to be a major phenomenon in batch cultures of the model organism Paracoccus denitrificans on the basis of measured e⁻-flow rates to O₂ and NO_x. Here we constructed a dynamic model and explicitly simulated actual kinetics of recruitment of the cells to denitrification to directly and more accurately estimate the recruited fraction (). Transcription of nirS is pivotal for denitrification, for it triggers a cascade of events leading to the synthesis of a full-fledged denitrification proteome. The model is based on the hypothesis that nirS has a low probability (, h⁻¹) of initial transcription, but once initiated, the transcription is greatly enhanced through positive feedback by NO, resulting in the recruitment of the transcribing cell to denitrification. We assume that the recruitment is initiated as [O₂] falls below a critical threshold and terminates (assuming energy-limitation) as [O₂] exhausts. With  = 0.005 h⁻¹, the model robustly simulates observed denitrification kinetics for a range of culture conditions. The resulting (fraction of the cells recruited to denitrification) falls within 0.038–0.161. In contrast, if the recruitment of the entire population is assumed, the simulated denitrification kinetics deviate grossly from those observed. The phenomenon can be understood as a ‘bet-hedging strategy’: switching to denitrification is a gain if anoxic spell lasts long but is a waste of energy if anoxia turns out to be a ‘false alarm’.

In response to oxygen-limiting conditions, denitrifying bacteria produce a set of enzymes to convert / to N₂ via NO and N₂O. The process (denitrification) helps generate energy for survival and growth during anoxia. Denitrification is imperative for the nitrogen cycle and has far-reaching consequences including contribution to global warming and destruction of stratospheric ozone. Recent experiments provide circumstantial evidence for a previously unknown phenomenon in the model denitrifying bacterium Paracoccus denitrificans: as O₂ depletes, only a marginal fraction of its population appears to switch to denitrification. We hypothesise that the low success rate is due to a) low probability for the cells to initiate the transcription of genes (nirS) encoding a key denitrification enzyme (NirS), and b) a limited time-window in which NirS must be produced. Based on this hypothesis, we constructed a dynamic model of denitrification in Pa. denitrificans. The simulation results show that, within the limited time available, a probability of 0.005 h⁻¹ for each cell to initiate nirS transcription (resulting in the recruitment of 3.8–16.1% cells to denitrification) is sufficient to adequately simulate experimental data. The result challenges conventional outlook on the regulation of denitrification in general and that of Pa. denitrificans in particular.

Analyses of flooding tolerance of soybean varieties at emergence and varietal differences in their proteomes

Flooding of fields due to heavy and/or continuous rainfall influences soybean production. To identify soybean varieties with flooding tolerance at the seedling emergence stage, 128 soybean varieties were evaluated using a flooding tolerance index, which is based on plant survival rates, the lack of apparent damage and lateral root development, and post-flooding radicle elongation rate. The soybean varieties were ranked according to their flooding tolerance index, and it was found that the tolerance levels of soybean varieties exhibit a continuum of differences between varieties. Subsequently, tolerant, moderately tolerant and sensitive varieties were selected and subjected to comparative proteomic analysis to clarify the tolerance mechanism. Proteomic analysis of the radicles, combined with correlation analysis, showed that the ratios of RNA binding/processing related proteins and flooding stress indicator proteins were significantly correlated with flooding tolerance index. The RNA binding/processing related proteins were positively correlated in untreated soybeans, whereas flooding stress indicator proteins were negatively correlated in flooded soybeans. These results suggest that flooding tolerance is regulated by mechanisms through multiple factors and is associated with abundance levels of the identified proteins.

Sperm membrane proteome in wild Japanese macaque (Macaca fuscata) and Sika deer (Cervus nippon)

Whereas recent advances in proteome-related techniques have accumulated a lot of information about sperm proteins in model animals, the information in non-model wildlife species is absolutely deficient, although this knowledge would be valuable to regulate wildlife overabundance. To characterize the repertoires of sperm membrane proteins in Japanese overpopulated wildlife, our study focuses on the following two species: Macaca fuscata and Cervus nippon. We enriched sperm membrane proteins by the phase partitioning with Triton X-114, and then separated them by two-dimensional electrophoresis, and, finally, they were comprehensively identified by peptide mass fingerprinting. Sperm membrane proteins were successfully enriched. They included some proteins with unknown function and fertility-related proteins that work in sperm development, motility, capacitation, transport, protection, acrosome reaction, and fertilization. Additionally, beta-defensin 126 and epithelial chloride channel were strongly detected in M. fuscata but not in C. nippon, whereas lactadherin and NADH-cytochrome b5 reductase 1 were strongly detected in C. nippon alone. This study is an initiative case showing that the sperm of wildlife conserve major fertility-related proteins, but express some proteins in a species-specific manner. In the development of a practical method for fertility control, this aspect may be taken into consideration.

Transcriptional and proteomic responses to carbon starvation in Paracoccidioides

Background

The genus Paracoccidioides comprises human thermal dimorphic fungi, which cause paracoccidioidomycosis (PCM), an important mycosis in Latin America. Adaptation to environmental conditions is key to fungal survival during human host infection. The adaptability of carbon metabolism is a vital fitness attribute during pathogenesis.

Methodology/Principal Findings

The fungal pathogen Paracoccidioides spp. is exposed to numerous adverse conditions, such as nutrient deprivation, in the human host. In this study, a comprehensive response of Paracoccidioides, Pb01, under carbon starvation was investigated using high-resolution transcriptomic (RNAseq) and proteomic (NanoUPLC-MS^E) approaches. A total of 1,063 transcripts and 421 proteins were differentially regulated, providing a global view of metabolic reprogramming during carbon starvation. The main changes were those related to cells shifting to gluconeogenesis and ethanol production, supported by the degradation of amino acids and fatty acids and by the modulation of the glyoxylate and tricarboxylic cycles. This proposed carbon flow hypothesis was supported by gene and protein expression profiles assessed using qRT-PCR and western blot analysis, respectively, as well as using enzymatic, cell dry weight and fungus-macrophage interaction assays. The carbon source provides a survival advantage to Paracoccidioides inside macrophages.

Conclusions/Significance

For a complete understanding of the physiological processes in an organism, the integration of approaches addressing different levels of regulation is important. To the best of our knowledge, this report presents the first description of the responses of Paracoccidioides spp. to host-like conditions using large-scale expression approaches. The alternative metabolic pathways that could be adopted by the organism during carbon starvation can be important for a better understanding of the fungal adaptation to the host, because systems for detecting and responding to carbon sources play a major role in adaptation and persistence in the host niche.

The species of the Paracoccidioides genus, a neglected human pathogen, represent the causative agents of paracoccidioidomycosis (PCM), one of the most frequent systemic mycoses in Latin America. Despite being phagocytosed, the fungus conidia differentiate into the parasitic yeast form that subverts the normally harsh intraphagosomal environment and survives and replicates into murine and human macrophages. It has been suggested that alternative carbon metabolism plays a role in the survival and virulence of Paracoccidioides spp. within host cells. We used large-scale transcriptome and proteome approaches to better characterize the responses of Paracoccidioides, Pb01, yeast parasitic cells, to carbon starvation. We aimed to identify important molecules used by the fungus to adapt to these hostile conditions. The shift to a starvation mode, including gluconeogenesis and ethanol increases, activation of fatty acids, and amino acid degradation are the strategies used by the pathogen to persist under this stress. Our study provides a detailed map of Paracoccidioides spp. responses under carbon starvation conditions and contributes to further investigations of the importance of alternative carbon adaptation during fungus pathogenesis.

Proteome labeling and protein identification in specific tissues and at specific developmental stages in an animal

Identifying the proteins synthesized at specific times in cells of interest in an animal will facilitate the study of cellular functions and dynamic processes. Here we introduce stochastic orthogonal recoding of translation with chemoselective modification (SORT-M) to address this challenge. SORT-M involves modifying cells to express an orthogonal aminoacyl-tRNA synthetase/tRNA pair to enable the incorporation of chemically modifiable analogs of amino acids at diverse sense codons in cells in rich media. We apply SORT-M to Drosophila melanogaster fed standard food to label and image proteins in specific tissues at precise developmental stages with diverse chemistries, including cyclopropene-tetrazine inverse electron demand Diels-Alder cycloaddition reactions. We also use SORT-M to identify proteins synthesized in germ cells of the fly ovary without dissection. SORT-M will facilitate the definition of proteins synthesized in specific sets of cells to study development, and learning and memory in flies, and may be extended to other animals.

The effect of colostrum intake on blood plasma proteome profile in newborn lambs: low abundance proteins

BACKGROUND

Colostrum intake by newborn lambs plays a fundamental role in the perinatal period, ensuring lamb survival. In this study, blood plasma samples from two groups of newborn lambs (Colostrum group and Delayed Colostrum group) at 2 and 14 h after birth were treated to reduce the content of high abundance proteins and analyzed using Two-Dimensional Differential in Gel Electrophoresis and MALDI MS/MS for protein identification in order to investigate low abundance proteins with immune function in newborn lambs.

RESULTS

The results showed that four proteins were increased in the blood plasma of lambs due to colostrum intake. These proteins have not been previously described as increased in blood plasma of newborn ruminants by colostrum intake. Moreover, these proteins have been described as having an immune function in other species, some of which were previously identified in colostrum and milk.

CONCLUSIONS

In conclusion, colostrum intake modified the low abundance proteome profile of blood plasma from newborn lambs, increasing the concentration of apolipoprotein A-IV, plasminogen, serum amyloid A and fibrinogen, demonstrating that colostrum is essential, not only for the provision of immunoglobulins, but also because of increases in several low abundance proteins with immune function.

Time-varying causal inference from phosphoproteomic measurements in macrophage cells

Cellular signaling circuitry in eukaryotes can be studied by analyzing the regulation of protein phosphorylation and its impact on downstream mechanisms leading to a phenotype. A primary role of phosphorylation is to act as a switch to turn "on" or "off" a protein activity or a cellular pathway. Specifically, protein phosphorylation is a major leit motif for transducing molecular signals inside the cell. Errors in transferring cellular information can alter the normal function and may lead to diseases such as cancer; an accurate reconstruction of the "true" signaling network is essential for understanding the molecular machinery involved in normal and pathological function. In this study, we have developed a novel framework for time-dependent reconstruction of signaling networks involved in the activation of macrophage cells leading to an inflammatory response. Several signaling pathways have been identified in macrophage cells, but the time-varying causal relationship that can produce a dynamic directed graph of these molecules has not been explored in detail. Here, we use the notion of Granger causality, and apply a vector autoregressive model to phosphoprotein time-course data in RAW 264.7 macrophage cells. Through the reconstruction of the phosphoprotein network, we were able to estimate the directionality and the dynamics of information flow. Significant interactions were selected through statistical hypothesis testing ( t-test) of the coefficients of a linear model and were used to reconstruct the phosphoprotein signaling network. Our approach results in a three-stage phosphoprotein network that represents the evolution of the causal interactions in the intracellular signaling pathways.

Nep1-like protein from Moniliophthora perniciosa induces a rapid proteome and metabolome reprogramming in cells of Nicotiana benthamiana

NEP1 (necrosis- and ethylene-inducing peptide 1)-like proteins (NLPs) have been identified in a variety of taxonomically unrelated plant pathogens and share a common characteristic of inducing responses of plant defense and cell death in dicotyledonous plants. Even though some aspects of NLP action have been well characterized, nothing is known about the global range of modifications in proteome and metabolome of NLP-treated plant cells. Here, using both proteomic and metabolomic approaches we were able to identify the global molecular and biochemical changes in cells of Nicotiana benthamiana elicited by short-term treatment with MpNEP2, a NLP of Moniliophthora perniciosa, the basidiomycete responsible for the witches' broom disease on cocoa (Theobroma cacao L.). Approximately 100 protein spots were collected from 2-DE gels in each proteome, with one-third showing more than twofold differences in the expression values. Fifty-three such proteins were identified by mass spectrometry (MS)/MS and mapped into specific metabolic pathways and cellular processes. Most MpNEP2 upregulated proteins are involved in nucleotide-binding function and oxidoreductase activity, whereas the downregulated proteins are mostly involved in glycolysis, response to stress and protein folding. Thirty metabolites were detected by gas spectrometry (GC)/MS and semi-quantified, of which eleven showed significant differences between the treatments, including proline, alanine, myo-inositol, ethylene, threonine and hydroxylamine. The global changes described affect the reduction-oxidation reactions, ATP biosynthesis and key signaling molecules as calcium and hydrogen peroxide. These findings will help creating a broader understanding of NLP-mediated cell death signaling in plants.

Interaction proteome of human Hippo signaling: modular control of the co-activator YAP1

Tissue homeostasis is controlled by signaling systems that coordinate cell proliferation, cell growth and cell shape upon changes in the cellular environment. Deregulation of these processes is associated with human cancer and can occur at multiple levels of the underlying signaling systems. To gain an integrated view on signaling modules controlling tissue growth, we analyzed the interaction proteome of the human Hippo pathway, an established growth regulatory signaling system. The resulting high-resolution network model of 480 protein-protein interactions among 270 network components suggests participation of Hippo pathway components in three distinct modules that all converge on the transcriptional co-activator YAP1. One of the modules corresponds to the canonical Hippo kinase cassette whereas the other two both contain Hippo components in complexes with cell polarity proteins. Quantitative proteomic data suggests that complex formation with cell polarity proteins is dynamic and depends on the integrity of cell-cell contacts. Collectively, our systematic analysis greatly enhances our insights into the biochemical landscape underlying human Hippo signaling and emphasizes multifaceted roles of cell polarity complexes in Hippo-mediated tissue growth control.

Proteins involved in distinct phases of cold hardening process in frost resistant winter barley (Hordeum vulgare L.) cv Luxor

Winter barley is an economically important cereal crop grown in higher latitudes and altitudes where low temperatures represent an important environmental constraint limiting crop productivity. In this study changes in proteome of leaves and crowns in a frost tolerant winter barley cv. Luxor in relation to short and long term periods of cold followed by a brief frost treatment were studied in order to disclose proteins responsible for the cold hardening process in distinct plant tissues. The mentioned changes have been monitored using two dimensional difference gel electrophoresis (2D-DIGE) with subsequent peptide-mapping protein identification. Regarding approximately 600–700 distinct protein spots detected on 2D gels, there has been found at least a two-fold change after exposure to low temperatures in about 10% of proteins in leaves and 13% of proteins in crowns. Protein and nitrogen metabolic processes have been influenced by low temperature to a similar extent in both tissues while catabolism, carbohydrate metabolism and proteins involved in stress response have been more affected in crowns than in leaves. The range of changes in protein abundance was generally higher in leaves and chloroplast proteins were frequently affected which suggests a priority to protect photosynthetic apparatus. Overall, our data proved existence of slightly different response strategies to low temperature stress in crowns and leaves, i.e., tissues with different biological role. Moreover, there have been found several proteins with large increase in accumulation, e.g., 33 kDa oxygen evolving protein of photosystem II in leaves and “enhanced disease susceptibility 1” in crowns; these proteins might have potential to indicate an enhanced level of frost tolerance in barley.

Microbial interactions in building of communities

Establishment of a community is considered to be essential for microbial growth and survival in the human oral cavity. Biofilm communities have increased resilience to physical forces, antimicrobial agents and nutritional variations. Specific cell-to-cell adherence processes, mediated by adhesin-receptor pairings on respective microbial surfaces, are able to direct community development. These interactions co-localize species in mutually beneficial relationships, such as streptococci, veillonellae, Porphyromonas gingivalis and Candida albicans. In transition from the planktonic mode of growth to a biofilm community, microorganisms undergo major transcriptional and proteomic changes. These occur in response to sensing of diffusible signals, such as autoinducer molecules, and to contact with host tissues or other microbial cells. Underpinning many of these processes are intracellular phosphorylation events that regulate a large number of microbial interactions relevant to community formation and development.

Proteome adaptation to high temperatures in the ectothermic hydrothermal vent Pompeii worm

Taking advantage of the massive genome sequencing effort made on thermophilic prokaryotes, thermal adaptation has been extensively studied by analysing amino acid replacements and codon usage in these unicellular organisms. In most cases, adaptation to thermophily is associated with greater residue hydrophobicity and more charged residues. Both of these characteristics are positively correlated with the optimal growth temperature of prokaryotes. In contrast, little information has been collected on the molecular 'adaptive' strategy of thermophilic eukaryotes. The Pompeii worm A. pompejana, whose transcriptome has recently been sequenced, is currently considered as the most thermotolerant eukaryote on Earth, withstanding the greatest thermal and chemical ranges known. We investigated the amino-acid composition bias of ribosomal proteins in the Pompeii worm when compared to other lophotrochozoans and checked for putative adaptive changes during the course of evolution using codon-based Maximum likelihood analyses. We then provided a comparative analysis of codon usage and amino-acid replacements from a greater set of orthologous genes between the Pompeii worm and Paralvinella grasslei, one of its closest relatives living in a much cooler habitat. Analyses reveal that both species display the same high GC-biased codon usage and amino-acid patterns favoring both positively-charged residues and protein hydrophobicity. These patterns may be indicative of an ancestral adaptation to the deep sea and/or thermophily. In addition, the Pompeii worm displays a set of amino-acid change patterns that may explain its greater thermotolerance, with a significant increase in Tyr, Lys and Ala against Val, Met and Gly. Present results indicate that, together with a high content in charged residues, greater proportion of smaller aliphatic residues, and especially alanine, may be a different path for metazoans to face relatively 'high' temperatures and thus a novelty in thermophilic metazoans.

Pathogenesis of hepatic fibrosis analyzed at the proteome level

Proteomic technologies have provided effective approaches to the analysis of the pathogenesis of hepatic fibrosis. A large number of proteins that have been revealed by this technology play a critical role in various aspects of pathological liver fibrosis. Comprehensive evaluations of these proteins have led to the understanding that the mechanisms of hepatic fibrosis can be stratified into several broad classifications. Here, we describe the mechanisms of action that are defined as being related to 1) oxidative stress and mitochondrial damage, 2) inflammatory response and immune injury, 3) abnormal cell proliferation and apoptosis, 4) abnormal metabolism, 5) abnormal cellular signal transduction, and 6) abnormal extracellular matrix metabolism.

The capture of phosphoproteins by 14-3-3 proteins mediates actions of insulin

How does signalling via PI3K-PKB (AKT)-mTORC1-p70S6K and ERK-p90RSK mediate wide-ranging physiological responses to insulin? Quantitative proteomics and biochemical experiments are revealing that these signalling pathways induce the phosphorylation of large and overlapping sets of proteins, which are then captured by phosphoprotein-binding proteins named 14-3-3s. The 14-3-3s are dimers that dock onto dual-phosphorylated sites in a configuration with special signalling and mechanical properties. They interact with the Rab GTPase-activating proteins AS160 and TBC1D1 to regulate glucose uptake into target tissues in response to insulin and energy stress. Dynamic patterns in the 14-3-3-binding phosphoproteome are providing new insights into how insulin triggers coherent shifts in metabolism that are integrated with other cellular response systems.

Quantitative subcellular proteome and secretome profiling of influenza A virus-infected human primary macrophages

Influenza A viruses are important pathogens that cause acute respiratory diseases and annual epidemics in humans. Macrophages recognize influenza A virus infection with their pattern recognition receptors, and are involved in the activation of proper innate immune response. Here, we have used high-throughput subcellular proteomics combined with bioinformatics to provide a global view of host cellular events that are activated in response to influenza A virus infection in human primary macrophages. We show that viral infection regulates the expression and/or subcellular localization of more than one thousand host proteins at early phases of infection. Our data reveals that there are dramatic changes in mitochondrial and nuclear proteomes in response to infection. We show that a rapid cytoplasmic leakage of lysosomal proteins, including cathepsins, followed by their secretion, contributes to inflammasome activation and apoptosis seen in the infected macrophages. Also, our results demonstrate that P2X₇ receptor and src tyrosine kinase activity are essential for inflammasome activation during influenza A virus infection. Finally, we show that influenza A virus infection is associated with robust secretion of different danger-associated molecular patterns (DAMPs) suggesting an important role for DAMPs in host response to influenza A virus infection. In conclusion, our high-throughput quantitative proteomics study provides important new insight into host-response against influenza A virus infection in human primary macrophages.

Influenza A viruses are negative-stranded RNA viruses that are capable of infecting a variety of avian and mammalian species. These viruses are responsible for the annual epidemics that cause severe illnesses in millions of people worldwide. The initial innate immune responses to influenza A viruses have to restrict virus spread before the adaptive immune responses fully develop. Macrophages are the key players of innate immune system and they have a central role in the activation of host response during viral infections. However, the host factors that are involved in the activation of innate immune response during influenza A virus infection are incompletely understood. Here, we have characterized in detail the nuclear, mitochondrial and cytoplasmic proteomes, as well as the secretome from influenza A virus-infected human primary macrophages to get a global view of host factors that are affected by the infection. Our approach allowed us to identify several novel host factors that contribute to innate immune system during influenza A virus infections. These include lysomal proteases cathepsins, P2X₇ receptor, src family tyrosine kinases as well as several danger-associated molecular patterns.

Quantitative proteomic analysis of the interaction between the endophytic plant-growth-promoting bacterium Gluconacetobacter diazotrophicus and sugarcane

Gluconacetobacter diazotrophicus is a plant-growth-promoting bacterium that colonizes sugarcane. In order to investigate molecular aspects of the G. diazotrophicus-sugarcane interaction, we performed a quantitative mass spectrometry-based proteomic analysis by (15)N metabolic labeling of bacteria, root samples, and co-cultures. Overall, more than 400 proteins were analyzed and 78 were differentially expressed between the plant-bacterium interaction model and control cultures. A comparative analysis of the G. diazotrophicus in interaction with two distinct genotypes of sugarcane, SP70-1143 and Chunee, revealed proteins with fundamental roles in cellular recognition. G. diazotrophicus presented proteins involved in adaptation to atypical conditions and signaling systems during the interaction with both genotypes. However, SP70-1143 and Chunee, sugarcane genotypes with high and low contribution of biological nitrogen fixation, showed divergent responses in contact with G. diazotrophicus. The SP70-1143 genotype overexpressed proteins from signaling cascades and one from a lipid metabolism pathway, whereas Chunee differentially synthesized proteins involved in chromatin remodeling and protein degradation pathways. In addition, we have identified 30 bacterial proteins in the roots of the plant samples; from those, nine were specifically induced by plant signals. This is the first quantitative proteomic analysis of a bacterium-plant interaction, which generated insights into early signaling of the G. diazotrophicus-sugarcane interaction.

Information-theoretic model of evolution over protein communication channel

In this paper, we propose a communication model of evolution and investigate its information-theoretic bounds. The process of evolution is modeled as the retransmission of information over a protein communication channel, where the transmitted message is the organism's proteome encoded in the DNA. We compute the capacity and the rate distortion functions of the protein communication system for the three domains of life: Archaea, Bacteria, and Eukaryotes. The tradeoff between the transmission rate and the distortion in noisy protein communication channels is analyzed. As expected, comparison between the optimal transmission rate and the channel capacity indicates that the biological fidelity does not reach the Shannon optimal distortion. However, the relationship between the channel capacity and rate distortion achieved for different biological domains provides tremendous insight into the dynamics of the evolutionary processes of the three domains of life. We rely on these results to provide a model of genome sequence evolution based on the two major evolutionary driving forces: mutations and unequal crossovers.

(Not) Keeping the stem straight: a proteomic analysis of maritime pine seedlings undergoing phototropism and gravitropism

BACKGROUND

Plants are subjected to continuous stimuli from the environment and have evolved an ability to respond through various growth and development processes. Phototropism and gravitropism responses enable the plant to reorient with regard to light and gravity.

RESULTS

We quantified the speed of maritime pine seedlings to reorient with regard to light and gravity over 22 days. Seedlings were inclined at 15, 30 and 45 degrees with vertical plants as controls. A lateral light source illuminated the plants and stem movement over time was recorded. Depending on the initial angle of stem lean, the apical response to the lateral light source differed. In control and 15° inclined plants, the apex turned directly towards the light source after only 2 h. In plants inclined at 30° and 45°, the apex first reoriented in the vertical plane after 2 h, then turned towards the light source after 24 h. Two-dimensional gel electrophoresis coupled with mass spectrometry was then used to describe the molecular response of stem bending involved in photo- and gravi-tropism after 22 hr and 8 days of treatment. A total of 486 spots were quantitatively analyzed using image analysis software. Significant changes were determined in the protein accumulation of 68 protein spots. Early response gravitropic associated proteins were identified, which are known to function in energy related and primary metabolism. A group of thirty eight proteins were found to be involved in primary metabolism and energy related metabolic pathways. Degradation of Rubisco was implicated in some protein shifts.

CONCLUSIONS

Our study demonstrates a rapid gravitropic response in apices of maritime pine seedlings inclined >30°. Little or no response was observed at the stem bases of the same plants. The primary gravitropic response is concomitant with a modification of the proteome, consisting of an over accumulation of energy and metabolism associated proteins, which may allow the stem to reorient rapidly after bending.

Advances in protein turnover analysis at the global level and biological insights

The concept of a dynamic state of body constituents, a precursor of the modern term of proteome dynamics, was conceived over a century ago. But, not until recently can we examine the dynamics of individual "constituents" for example, proteins at a truly global level. The path of advancement in our understanding of protein turnover at the global level is marked by the introduction of some key technological innovations. These methods include the isotopic tracer technique in the 1930s, the two-dimensional gel electrophoresis technique in the 1970s, the sector mass spectrometer that could analyze isotopomers of peptides in the early 1990s, the 2D gel/MALDI-TOF proteomics technology in the late 1990s, the booming liquid chromatography/mass spectrometry proteomics technology in this decade, and the recently emerging protein-tagging approaches that offer single-cell resolution for protein turnover measurements. The long-standing inquiry raised in the 1950s about the existence of a dynamic state in different organisms at different physiological conditions can now be answered with an individual "constituent" resolution on a truly global scale. Now it appears that protein degradation is not necessarily an end to the protein function. Rather, it can be the start of a new function because protein degradation clears the way for the action of other proteins. Protein turnover participates in a multi-layer complex regulatory network and shares equal importance with gene transcription and protein translation. The advances in technologies for protein turnover analysis and the improved understanding of the biological role of protein turnover will likely help to solve some long-standing biomedical problems such as the tuberculosis disease that at the present day still affects one-third of the world population.

A two-dimensional proteomic profile of Tetrahymena thermophila whole cell lysate

Tetrahymena thermophila is a unicellular eukaryotic model organism used for a variety of biochemical, molecular and biological studies. According to its macronucleus genome sequence, it is expected to contain more than 27,000 protein-coding genes, although only a small proportion of them have information published specifically about them. Here, we present a reference map for whole cell lysate of T. thermophila obtained using two-dimensional gel electrophoresis (2-DE) combined with mass spectrometry. Although (2-DE) is one of the most efficient techniques for resolving complex protein mixtures and revealing the relative high-abundance proteins, it has not yet been applied generally to ciliates. In order to obtain qualitative protein samples for analysis, an appropriate homogenization method is required. Optimization of the homogenization method led to the analysis of nearly 4500 protein spots, the final identification of 375 different proteins using Mascot software and an additional 258 gene products using a newly developed web service, called Peptide Finder, resulting in a total of 631 different gene products that are considered to constitute the proteomic profile of the whole cell lysate of T. thermophila.

Metabolica: a statistical research tool for analyzing metabolic networks

Steady state flux balance analysis (FBA) for cellular metabolism is used, e.g., to seek information on the activity of the different pathways under equilibrium conditions, or as a basis for kinetic models. In metabolic models, the stoichiometry of the system, commonly completed with bounds on some of the variables, is used as the constraint in the search of a meaningful solution. As model complexity and number of constraints increase, deterministic approach to FBA is no longer viable: a multitude of very different solutions may exist, or the constraints may be in conflict, implying that no precise solution can be found. Moreover, the solution may become overly sensitive to parameter values defining the constraints. Bayesian FBA treats the unknowns as random variables and provides estimates of their probability density functions. This stochastic setting naturally represents the variability which can be expected to occur over a population and helps to circumvent the drawbacks of the classical approach, but its implementation can be quite tedious for users without background in statistical computations. This article presents a software package called Metabolica for performing Bayesian FBA for complex multi-compartment models and visualization of the results.

Serum pattern profiling for analyzing different types of stress by protein chip technology: a preliminary study

ProteinChip is a widely accepted tool for exploring serum pattern profile to evaluate the risk of somatic diseases from different stressors. In this study, by using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-ToF), the serum proteome from mice under restraint and thermal stresses were profiled in detail and compared with the control group. Around 150 characteristic peaks were detected in all three groups, with m/z ranging from 1500 to 50,000, with most peaks being within the 2000 m/z to 20,000 m/z range. Compared with the control group, three significant protein peaks with m/z values of 2780, 3303 and 3450 appeared specifically in the restrained stress group and four other peaks with m/z values of 7500, 7811, 29,950 and 38,565 in the thermal stress group. Unexpectedly, no universal positive stress peaks were detected. These preliminary results clearly suggested that there might not be a common mechanism shared by various psychophysiological disorders under different stressors. By fast serum proteomics profiling, SELDI-ToF may be a convenient tool for evaluating the risk of stress-induced illness.

Elucidating novel mechanisms of brain injury following subarachnoid hemorrhage: an emerging role for neuroproteomics

Subarachnoid hemorrhage (SAH) is a devastating neurological injury associated with significant patient morbidity and death. Since the first demonstration of cerebral vasospasm nearly 60 years ago, the preponderance of research has focused on strategies to limit arterial narrowing and delayed cerebral ischemia following SAH. However, recent clinical and preclinical data indicate a functional dissociation between cerebral vasospasm and neurological outcome, signaling the need for a paradigm shift in the study of brain injury following SAH. Early brain injury may contribute to poor outcome and early death following SAH. However, elucidation of the complex cellular mechanisms underlying early brain injury remains a major challenge. The advent of modern neuroproteomics has rapidly advanced scientific discovery by allowing proteome-wide screening in an objective, nonbiased manner, providing novel mechanisms of brain physiology and injury. In the context of neurosurgery, proteomic analysis of patient-derived CSF will permit the identification of biomarkers and/or novel drug targets that may not be intuitively linked with any particular disease. In the present report, the authors discuss the utility of neuroproteomics with a focus on the roles for this technology in understanding SAH. The authors also provide data from our laboratory that identifies high-mobility group box protein-1 as a potential biomarker of neurological outcome following SAH in humans.