The evolution of developmental patterning under genetic duplication constraints

Of considerable interest are the evolutionary and developmental origins of complex, adaptive structures and the mechanisms that stabilize these structures. We consider the relationship between the evolutionary process of gene duplication and deletion and the stability of morphogenetic patterns produced by interacting activators and inhibitors. We compare the relative stability of patterns with a single activator and inhibitor (two-dimensional system) against a 'redundant' system with two activators or two inhibitors (three-dimensional system). We find that duplication events can both expand and contract the space of patterns. We study developmental robustness in terms of stochastic escape times from this space, also known as a 'canalization potential'. We embed the output of pattern formation into an explicit evolutionary model of gene duplication, gene loss and variation in the steepness of the canalization potential. We find that under all constant conditions, the system evolves towards a preference for steep potentials associated with low phenotypic variability and longer lifespans. This preference leads to an overall decrease in the density of redundant genotypes as developmental robustness neutralizes the advantages of genetic robustness.

Practical and theoretical advances in predicting the function of a protein by its phylogenetic distribution

The gap between the amount of genome information released by genome sequencing projects and our knowledge about the proteins' functions is rapidly increasing. To fill this gap, various 'genomic-context' methods have been proposed that exploit sequenced genomes to predict the functions of the encoded proteins. One class of methods, phylogenetic profiling, predicts protein function by correlating the phylogenetic distribution of genes with that of other genes or phenotypic characteristics. The functions of a number of proteins, including ones of medical relevance, have thus been predicted and subsequently confirmed experimentally. Additionally, various approaches to measure the similarity of phylogenetic profiles and to account for the phylogenetic bias in the data have been proposed. We review the successful applications of phylogenetic profiling and analyse the performance of various profile similarity measures with a set of one microsporidial and 25 fungal genomes. In the fungi, phylogenetic profiling yields high-confidence predictions for the highest and only the highest scoring gene pairs illustrating both the power and the limitations of the approach. Both practical examples and theoretical considerations suggest that in order to get a reliable and specific picture of a protein's function, results from phylogenetic profiling have to be combined with other sources of evidence.

The extracytoplasmic stress factor, sigmaE, is required to maintain cell envelope integrity in Escherichia coli

Extracytoplasmic function or ECF sigma factors are the most abundant class of alternative sigma factors in bacteria. Members of the rpoE subclass of ECF sigma factors are implicated in sensing stress in the cell envelope of Gram-negative bacteria and are required for virulence in many pathogens. The best-studied member of this family is rpoE from Escherichia coli, encoding the σ^E protein. σ^E has been well studied for its role in combating extracytoplasmic stress, and the members of its regulon have been largely defined. σ^E is required for viability of E. coli, yet none of the studies to date explain why σ^E is essential in seemingly unstressed cells. In this work we investigate the essential role of σ^E in E. coli by analyzing the phenotypes associated with loss of σ^E activity and isolating suppressors that allow cells to live in the absence of σ^E. We demonstrate that when σ^E is inhibited, cell envelope stress increases and envelope integrity is lost. Many cells lyse and some develop blebs containing cytoplasmic material along their sides. To better understand the connection between transcription by σ^E and cell envelope integrity, we identified two multicopy suppressors of the essentiality of σ^E, ptsN and yhbW. yhbW is a gene of unknown function, while ptsN is a member of the σ^E regulon. Overexpression of ptsN lowers the basal level of multiple envelope stress responses, but not that of a cytoplasmic stress response. Our results are consistent with a model in which overexpression of ptsN reduces stress in the cell envelope, thereby promoting survival in the absence of σ^E.

Keep your fingers off my DNA: protein-protein interactions mediated by C2H2 zinc finger domains

Cys2-His2 (C2H2) zinc finger domains (ZFs) were originally identified as DNA-binding domains, and uncharacterized domains are typically assumed to function in DNA binding. However, a growing body of evidence suggests an important and widespread role for these domains in protein binding. There are even examples of zinc fingers that support both DNA and protein interactions, which can be found in well-known DNA-binding proteins such as Sp1, Zif268, and Ying Yang 1 (YY1). C2H2 protein-protein interactions (PPIs) are proving to be more abundant than previously appreciated, more plastic than their DNA-binding counterparts, and more variable and complex in their interactions surfaces. Here we review the current knowledge of over 100 C2H2 zinc finger-mediated PPIs, focusing on what is known about the binding surface, contributions of individual fingers to the interaction, and function. An accurate understanding of zinc finger biology will likely require greater insights into the potential protein interaction capabilities of C2H2 ZFs.

Epidermal growth factor mediates spermatogonial proliferation in newt testis

The complex processes of spermatogenesis are regulated by various factors. The aim of the current study is to determine the effect of epidermal growth factor (EGF) on spermatogonial proliferation and clarify the mechanism causing the proliferation in newt testis. In the organ culture, EGF stimulated spermatogonial proliferation, but not their differentiation into spermatocytes. cDNA cloning identified 3 members of the EGF receptors, ErbB1, ErbB2, and ErbB4, in the testis. RT-PCR showed that all the receptors cloned were expressed in both Sertoli and germ cells at the spermatogonial stage. In the organ cultures with inhibitors for the EGF receptors, mitogen-activated protein kinase (MAPK), and phosphoinositide 3-kinase (PI3K), the EGF-induced spermatogonial proliferation was suppressed. Furthermore, when the organ culture was exposed to EGF, the expressions of stem cell factor (SCF), immunoglobulin-like domain containing neuregulin1 (Ig-NRG1), and ErbB4 mRNA were increased. These results suggested that, since the spermatogonia are sequestered within cysts by the blood-testis barrier consisted of Sertoli cells, EGF possibly mediates spermatogonial proliferation in an endocrine manner through the receptors including ErbB1, ErbB2, and ErbB4 expressed on Sertoli cells via activation of MAPK cascade or/and PI3K cascade by elevating the expressions of SCF, Ig-NRG1, and ErbB4.

The influence of genetic variation on gene expression

The view that changes to the control of gene expression rather than alterations to protein sequence are central to the evolution of organisms has become something of a truism in molecular biology. In reality, the direct evidence for this is limited, and only recently have we had the ability to look more globally at how genetic variation influences gene expression, focusing upon inter-individual variation in gene expression and using microarrays to test for differences in mRNA levels. Here, we review the scope of these experimental analyses, what they are designed to tell us about genetic variation, and what are their limitations from both a technical and a conceptual viewpoint. We conclude that while we are starting to understand the impact of this class of genetic variation upon steady-state mRNA levels, we are still far from identifying the potential phenotypic and evolutionary outcomes.

Symbiotic gut microbes modulate human metabolic phenotypes

Humans have evolved intimate symbiotic relationships with a consortium of gut microbes (microbiome) and individual variations in the microbiome influence host health, may be implicated in disease etiology, and affect drug metabolism, toxicity, and efficacy. However, the molecular basis of these microbe-host interactions and the roles of individual bacterial species are obscure. We now demonstrate a"transgenomic" approach to link gut microbiome and metabolic phenotype (metabotype) variation. We have used a combination of spectroscopic, microbiomic, and multivariate statistical tools to analyze fecal and urinary samples from seven Chinese individuals (sampled twice) and to model the microbial-host metabolic connectivities. At the species level, we found structural differences in the Chinese family gut microbiomes and those reported for American volunteers, which is consistent with population microbial cometabolic differences reported in epidemiological studies. We also introduce the concept of functional metagenomics, defined as "the characterization of key functional members of the microbiome that most influence host metabolism and hence health." For example, Faecalibacterium prausnitzii population variation is associated with modulation of eight urinary metabolites of diverse structure, indicating that this species is a highly functionally active member of the microbiome, influencing numerous host pathways. Other species were identified showing different and varied metabolic interactions. Our approach for understanding the dynamic basis of host-microbiome symbiosis provides a foundation for the development of functional metagenomics as a probe of systemic effects of drugs and diet that are of relevance to personal and public health care solutions.

New surveyor tools for charting microbial metabolic maps

The computational reconstruction and analysis of cellular models of microbial metabolism is one of the great success stories of systems biology. The extent and quality of metabolic network reconstructions is, however, limited by the current state of biochemical knowledge. Can experimental high-throughput data be used to improve and expand network reconstructions to include unexplored areas of metabolism? Recent advances in experimental technology and analytical methods bring this aim an important step closer to realization. Data integration will play a particularly important part in exploiting the new experimental opportunities.

Three factors underlying incorrect in silico predictions of essential metabolic genes

BACKGROUND

The indispensability of certain genes in an organism is important for studies of microorganism physiology, antibiotic targeting, and the engineering of minimal genomes. Time and resource intensive genome-wide experimental screens can be conducted to determine which genes are likely essential. For metabolic genes, a reconstructed metabolic network can be used to predict which genes are likely essential. The success rate of these predictions is less than desirable, especially with regard to comprehensively locating essential genes.

RESULTS

We show that genes that are falsely predicted to be non-essential (for growth) share three characteristics across multiple organisms and growth media. First, these genes are on average connected to fewer reactions in the network than correctly predicted essential genes, suggesting incomplete knowledge of the functions of these genes. Second, they are more likely to be blocked (their associated reactions are prohibited from carrying flux in the given condition) than other genes, implying incomplete knowledge of metabolism surrounding these genes. Third, they are connected to less overcoupled metabolites.

CONCLUSION

The results presented herein indicate genes that cannot be correctly predicted as essential have commonalities in different organisms. These elucidated failure modes can be used to better understand the biology of individual organisms and to improve future predictions.

Genetic analysis of the role of peroxisomes in the utilization of acetate and fatty acids in Aspergillus nidulans

Peroxisomes are organelles containing a diverse array of enzymes. In fungi they are important for carbon source utilization, pathogenesis, development, and secondary metabolism. We have studied Aspergillus nidulans peroxin (pex) mutants isolated by virtue of their inability to grow on butyrate or by the inactivation of specific pex genes. While all pex mutants are able to form colonies, those unable to import PTS1 proteins are partially defective in asexual and sexual development. The pex mutants are able to grow on acetate but are affected in growth on fatty acids, indicating a requirement for the peroxisomal localization of beta-oxidation enzymes. However, mislocalization of malate synthase does not prevent growth on either fatty acids or acetate, showing that the glyoxylate cycle does not require peroxisomal localization. Proliferation of peroxisomes is dependent on fatty acids, but not on acetate, and on PexK (Pex11), expression of which is activated by the FarA transcription factor. Proliferation was greatly reduced in a farADelta strain. A mutation affecting a mitochodrial ketoacyl-CoA thiolase and disruption of a mitochondrial hydroxy-acyl-CoA dehydrogenase gene prevented growth on short-chain but not long-chain fatty acids. Together with previous results, this is consistent with growth on even-numbered short-chain fatty acids requiring a mitochondrial as well as a peroxisomal beta-oxidation pathway. The mitochondrial pathway is not required for growth on valerate or for long-chain fatty acid utilization.

Genetic interaction between the Escherichia coli AcpT phosphopantetheinyl transferase and the YejM inner membrane protein

Strain LH530, a mutant of Escherichia coli K-12, was reported by others to show increased outer membrane permeability, temperature-sensitive growth, and reduced synthesis of lipid A. The unmapped mutant gene was found to be suppressed by high-copy-number plasmids carrying the wild-type acpT gene, which encodes a protein that catalyzes a post-translational protein modification, the attachment of 4'-phosphopantetheine. We mapped the strain LH530 mutation to a gene of unknown function, yejM, known to encode an inner membrane protein. The mutation is a yejM nonsense mutation that produces a truncated protein lacking the predicted periplasmic domain. Reconstruction of the mutation gave a strain having the same phenotypes as LH530. In contrast to the nonsense mutants, deletion of the entire yejM gene was lethal. Suppression by AcpT overexpression of the yejM nonsense mutants encoding the truncated proteins was specific to AcpT. Moreover, AcpT overexpression also suppressed the lethality due to deletion of the entire yejM gene and this suppression also did not require that AcpT be enzymatically active. The mechanism whereby overexpression of a specific cytosolic protein bypasses the essentiality of an inner membrane protein is unknown.

Proteomic analysis of rice defense response induced by probenazole

Here, we report the first proteomic analysis of rice defense response induced by probenazole (PBZ), an agricultural chemical that has been widely used to protect rice plants from rice blast and the bacterial blight pathogen. Two-dimensional gel electrophoresis (2-DE) was utilized to identify a total of 40 protein spots including 9 protein spots that are up-regulated by PBZ and 31 abundant protein spots. A total of 11 unique proteins from these 9 spots were identified by LC-MS/MS, and the majority of them were classified and/or possessed orthologs in defense-related functions. Five protein spots with only one protein species identified in each spot appear to be PBZ-regulated proteins. They are a putative glutathione S-transferase GSTU17, a putative phenylalanine ammonia-lyase (PAL, XP_466843), a putative caffeic acid 3-O-methyltransferase (COMT), a putative NADH-ubiquinone oxidoreductase, and a putative glucose-1-phosphate adenyltransferase. However, the other six protein species identified from the remaining four protein spots could not be conclusively described as PBZ-regulated proteins due to either the co-migration of two protein species in one spot or the presence of one protein species in two spots. Through real-time reverse transcription polymerase chain reaction (RT-PCR), it was determined that PAL (XP_466843) is likely regulated at the protein level, whereas GSTU17 and COMT were regulated at the mRNA level after PBZ application. Interestingly, the mRNA transcripts of two PAL paralogs were found to be up-regulated by PBZ. We propose that PAL, COMT, and GSTU17 are likely to confer PBZ-induced disease resistance via such functions as biosynthesis and transport of flavonoid-type phytoalexin and/or lignin biogenesis.

Effects of protein maturation on the noise in gene expression

Fluorescent proteins are frequently used as reporters for gene expression in living cells, either by being expressed in tandem with a protein of interest or through the creation of fusion proteins. The data yielded by the fluorescence output are of considerable interest in efforts to formulate quantitative models of cellular behavior underway in fields such as systems biology and synthetic biology. An often neglected aspect of these proteins, however, is their maturation: Before a fluorescent protein can generate a fluorescent signal, it must mature through a series of steps (folding, cyclization, and oxidation) that may take from many minutes to over a day. The presence of these maturation steps creates a distinction between the observed gene expression profile and the actual profile. We examine this effect through a simplified gene expression model and conclude that fluorescent protein maturation can have significant effects on estimates of both the mean protein levels and the variability in gene expression. The model shows that in many regimes, the observed variability will be increased by the maturation process, but indicates the existence of regimes in which the observed variability will actually be less than the true variability of the target protein. The latter effect arises from a low-pass filtering effect introduced by the chain of maturation reactions. The results suggest that the maturation of fluorescent proteins should be taken into account when using such proteins as quantitative indicators of gene expression levels.

Investigation of regulation of FtsZ assembly by SulA and development of a model for FtsZ polymerization

In Escherichia coli FtsZ organizes into a cytoskeletal ring structure, the Z ring, which effects cell division. FtsZ is a GTPase, but the free energy of GTP hydrolysis does not appear to be used for generation of the constriction force, leaving open the question of the function of the GTPase activity of FtsZ. Here we study the mechanism by which SulA, an inhibitor of FtsZ induced during the SOS response, inhibits FtsZ function. We studied the effects of SulA on the in vitro activities of FtsZ, on Z rings in vivo, and on a kinetic model for FtsZ polymerization in silico. We found that the binding of SulA to FtsZ is necessary but not sufficient for inhibition of polymerization, since the assembly of FtsZ polymers in the absence of the GTPase activity was not inhibited by SulA. We developed a new model for FtsZ polymerization that accounts for the cooperativity of FtsZ and could account for cooperativity observed in other linear polymers. When SulA was included in the kinetic scheme, simulations revealed that SulA with strong affinity for FtsZ delayed, but did not prevent, the assembly of polymers when they were not hydrolyzing GTP. Furthermore, the simulations indicated that SulA controls the assembly of FtsZ by binding to a polymerization-competent form of the FtsZ molecule and preventing it from participating in assembly. In vivo stoichiometry of the disruption of Z rings by SulA suggests that FtsZ may undergo two cooperative transitions in forming the Z ring.

FIONA1 is essential for regulating period length in the Arabidopsis circadian clock

In plants, the circadian clock controls daily physiological cycles as well as daylength-dependent developmental processes such as photoperiodic flowering and seedling growth. Here, we report that FIONA1 (FIO1) is a genetic regulator of period length in the Arabidopsis thaliana circadian clock. FIO1 was identified by screening for a mutation in daylength-dependent flowering. The mutation designated fio1-1 also affects daylength-dependent seedling growth. fio1-1 causes lengthening of the free-running circadian period of leaf movement and the transcription of various genes, including the central oscillators CIRCADIAN CLOCK-ASSOCIATED1, LATE ELONGATED HYPOCOTYL, TIMING OF CAB EXPRESSION1, and LUX ARRHYTHMO. However, period lengthening is not dependent upon environmental light or temperature conditions, which suggests that FIO1 is not a simple input component of the circadian system. Interestingly, fio1-1 exerts a clear effect on the period length of circadian rhythm but has little effect on its amplitude and robustness. FIO1 encodes a novel nuclear protein that is highly conserved throughout the kingdoms. We propose that FIO1 regulates period length in the Arabidopsis circadian clock in a close association with the central oscillator and that the circadian period can be controlled separately from amplitude and robustness.

The Saccharomyces cerevisiae homolog of p24 is essential for maintaining the association of p150Glued with the dynactin complex

Stu1 is the Saccharomyces cerevisiae member of the CLASP family of microtubule plus-end tracking proteins and is essential for spindle formation. A genomewide screen for gene deletions that are lethal in combination with the temperature-sensitive stu1-5 allele identified ldb18Delta. ldb18Delta cells exhibit defects in spindle orientation similar to those caused by a block in the dynein pathway. Consistent with this observation, ldb18Delta is synthetic lethal with mutations affecting the Kar9 spindle orientation pathway, but not with those affecting the dynein pathway. We show that Ldb18 is a component of dynactin, a complex required for dynein activity in yeast and mammalian cells. Ldb18 shares modest sequence and structural homology with the mammalian dynactin component p24. It interacts with dynactin proteins in two-hybrid and co-immunoprecipitation assays, and comigrates with them as a 20 S complex during sucrose gradient sedimentation. In ldb18Delta cells, the interaction between Nip100 (p150(Glued)) and Jnm1 (dynamitin) is disrupted, while the interaction between Jnm1 and Arp1 is not affected. These results indicate that p24 is required for attachment of the p150(Glued) arm to dynamitin and the remainder of the dynactin complex. The genetic interaction of ldb18Delta with stu1-5 also supports the notion that dynein/dynactin helps to generate a spindle pole separating force.

Towards a pathway definition of Parkinson's disease: a complex disorder with links to cancer, diabetes and inflammation

We have previously established a first whole genome transcriptomic profile of sporadic Parkinson's disease (PD). After extensive brain tissue-based validation combined with cycles of iterative data analysis and by focusing on the most comparable cases of the cohort, we have refined our analysis and established a list of 892 highly dysregulated priority genes that are considered to form the core of the diseased Parkinsonian metabolic network. The substantia nigra pathways, now under scrutiny, contain more than 100 genes whose association with PD is known from the literature. Of those, more than 40 genes belong to the highly significantly dysregulated group identified in our dataset. Apart from the complete list of 892 priority genes, we present pathways revealing PD 'hub' as well as 'peripheral' network genes. The latter include Lewy body components or interact with known PD genes. Biological associations of PD with cancer, diabetes and inflammation are discussed and interactions of the priority genes with several drugs are provided. Our study illustrates the value of rigorous clinico-pathological correlation when analysing high-throughput data to make optimal use of the histopathological phenome, or morphonome which currently serves as the key diagnostic reference for most human diseases. The need for systematic human tissue banking, following the highest possible professional and ethical standard to enable sustainability, becomes evident.

Impact of systems biology on metabolic engineering ofSaccharomyces cerevisiae

Industrial biotechnology is a rapidly growing field. With the increasing shift towards a bio-based economy, there is rising demand for developing efficient cell factories that can produce fuels, chemicals, pharmaceuticals, materials, nutraceuticals, and even food ingredients. The yeast Saccharomyces cerevisiae is extremely well suited for this objective. As one of the most intensely studied eukaryotic model organisms, a rich density of knowledge detailing its genetics, biochemistry, physiology, and large-scale fermentation performance can be capitalized upon to enable a substantial increase in the industrial application of this yeast. Developments in genomics and high-throughput systems biology tools are enhancing one's ability to rapidly characterize cellular behaviour, which is valuable in the field of metabolic engineering where strain characterization is often the bottleneck in strain development programmes. Here, the impact of systems biology on metabolic engineering is reviewed and perspectives on the role of systems biology in the design of cell factories are given.

Identification of a spermidine excretion protein complex (MdtJI) in Escherichia coli

A spermidine excretion protein in Escherichia coli was looked for among 33 putative drug exporters thus far identified. Cell toxicity and inhibition of growth due to overaccumulation of spermidine were examined in an E. coli strain deficient in spermidine acetyltransferase, an enzyme that metabolizes spermidine. Toxicity and inhibition of cell growth by spermidine were recovered in cells transformed with pUCmdtJI or pMWmdtJI, encoding MdtJ and MdtI, which belong to the small multidrug resistance family of drug exporters. Both mdtJ and mdtI are necessary for recovery from the toxicity of overaccumulated spermidine. It was also found that the level of mdtJI mRNA was increased by spermidine. The spermidine content in cells cultured in the presence of 2 mM spermidine was decreased, and excretion of spermidine from cells was enhanced by MdtJI, indicating that the MdtJI complex can catalyze excretion of spermidine from cells. It was found that Tyr4, Trp5, Glu15, Tyr45, Tyr61, and Glu82 in MdtJ and Glu5, Glu19, Asp60, Trp68, and Trp81 in MdtI are involved in the excretion activity of MdtJI.

The complete genome sequence of Escherichia coli DH10B: insights into the biology of a laboratory workhorse

Escherichia coli DH10B was designed for the propagation of large insert DNA library clones. It is used extensively, taking advantage of properties such as high DNA transformation efficiency and maintenance of large plasmids. The strain was constructed by serial genetic recombination steps, but the underlying sequence changes remained unverified. We report the complete genomic sequence of DH10B by using reads accumulated from the bovine sequencing project at Baylor College of Medicine and assembled with DNAStar's SeqMan genome assembler. The DH10B genome is largely colinear with that of the wild-type K-12 strain MG1655, although it is substantially more complex than previously appreciated, allowing DH10B biology to be further explored. The 226 mutated genes in DH10B relative to MG1655 are mostly attributable to the extensive genetic manipulations the strain has undergone. However, we demonstrate that DH10B has a 13.5-fold higher mutation rate than MG1655, resulting from a dramatic increase in insertion sequence (IS) transposition, especially IS150. IS elements appear to have remodeled genome architecture, providing homologous recombination sites for a 113,260-bp tandem duplication and an inversion. DH10B requires leucine for growth on minimal medium due to the deletion of leuLABCD and harbors both the relA1 and spoT1 alleles causing both sensitivity to nutritional downshifts and slightly lower growth rates relative to the wild type. Finally, while the sequence confirms most of the reported alleles, the sequence of deoR is wild type, necessitating reexamination of the assumed basis for the high transformability of DH10B.

Plasmid-borne prokaryotic gene expression: sources of variability and quantitative system characterization

One aim of synthetic biology is to exert systematic control over cellular behavior, either for medical purposes or to "program" microorganisms. An engineering approach to the design of biological controllers demands a quantitative understanding of the dynamics of both the system to be controlled and the controllers themselves. Here we focus on a widely used method of exerting control in bacterial cells: plasmid vectors bearing gene-promoter pairs. We study two variants of the simplest such element, an unregulated promoter constitutively expressing its gene, against the varying genomic background of four Escherichia coli cell strains. Absolute protein numbers and rates of expression vary with both cell strain and plasmid type, as does the variability of expression across the population. Total variability is most strongly coupled to the cell division process, and after cell size is scaled away, plasmid copy number regulation emerges as a significant effect. We present simple models that capture the main features of the system behavior. Our results confirm that complex interactions between plasmids and their hosts can have significant effects on both expression and variability, even in deliberately simplified systems.

Drosophila importin alpha1 performs paralog-specific functions essential for gametogenesis

Importin alpha's mediate nuclear transport by linking nuclear localization signal (NLS)-containing proteins to importin beta1. Animal genomes encode three conserved groups of importin alpha's, alpha1's, alpha2's, and alpha3's, each of which are competent to bind classical NLS sequences. Using Drosophila melanogaster we describe the isolation and phenotypic characterization of the first animal importin alpha1 mutant. Animal alpha1's are more similar to ancestral plant and fungal alpha1-like genes than to animal alpha2 and alpha3 genes. Male and female importin alpha1 (Dalpha1) null flies developed normally to adulthood (with a minor wing defect) but were sterile with defects in gametogenesis. The Dalpha1 mutant phenotypes were rescued by Dalpha1 transgenes, but not by Dalpha2 or Dalpha3 transgenes. Genetic interactions between the ectopic expression of Dalpha1 and the karyopherins CAS and importin beta1 suggest that high nuclear levels of Dalpha1 are deleterious. We conclude that Dalpha1 performs paralog-specific activities that are essential for gametogenesis and that regulation of subcellular Dalpha1 localization may affect cell fate decisions. The initial expansion and specialization of the animal importin alpha-gene family may have been driven by the specialized needs of gametogenesis. These results provide a framework for studies of the more complex mammalian importin alpha-gene family.

Effects of molecular memory and bursting on fluctuations in gene expression

Many cellular components are present in such low numbers per cell that random births and deaths of individual molecules can cause substantial "noise" in concentrations. But biochemical events do not necessarily occur in single steps of individual molecules. Some processes are greatly randomized when synthesis or degradation occurs in large bursts of many molecules during a short time interval. Conversely, each birth or death of a macromolecule could involve several small steps, creating a memory between individual events. We present a generalized theory for stochastic gene expression, formulating the variance in protein abundance in terms of the randomness of the individual gene expression events. We show that common types of molecular mechanisms can produce gestation and senescence periods that reduce noise without requiring higher abundances, shorter lifetimes, or any concentration-dependent control loops. We also show that most single-cell experimental methods cannot distinguish between qualitatively different stochastic principles, although this in turn makes such methods better suited for identifying which components introduce fluctuations. Characterizing the random events that give rise to noise in concentrations instead requires dynamic measurements with single-molecule resolution.

Identification of gene interactions associated with disease from gene expression data using synergy networks

Background

Analysis of microarray data has been used for the inference of gene-gene interactions. If, however, the aim is the discovery of disease-related biological mechanisms, then the criterion for defining such interactions must be specifically linked to disease.

Results

Here we present a computational methodology that jointly analyzes two sets of microarray data, one in the presence and one in the absence of a disease, identifying gene pairs whose correlation with disease is due to cooperative, rather than independent, contributions of genes, using the recently developed information theoretic measure of synergy. High levels of synergy in gene pairs indicates possible membership of the two genes in a shared pathway and leads to a graphical representation of inferred gene-gene interactions associated with disease, in the form of a "synergy network." We apply this technique on a set of publicly available prostate cancer expression data and successfully validate our results, confirming that they cannot be due to pure chance and providing a biological explanation for gene pairs with exceptionally high synergy.

Conclusion

Thus, synergy networks provide a computational methodology helpful for deriving "disease interactomes" from biological data. When coupled with additional biological knowledge, they can also be helpful for deciphering biological mechanisms responsible for disease.

Technology Insight: biomarker development in acute kidney injury--what can we anticipate?

Early diagnosis has been the 'Achilles heel' of acute kidney injury (AKI) that has prevented successful implementation of treatment strategies. To date, pharmacological intervention has been largely unsuccessful or equivocal, and morbidity and mortality associated with AKI have remained unacceptably high. Despite their well-known limitations, the most widely used biomarkers for the early diagnosis of AKI are serum creatinine, blood urea nitrogen and urine output. Development of new biomarkers is imperative. A variety of methods have been employed to discover new biomarkers of AKI, including transcriptomics, proteomics, gene arrays, lipidomics and imaging technologies. Clinical trials are underway to establish the validity of the biomarkers discovered using these techniques. This Review summarizes the importance of biomarkers of AKI, from their discovery to clinical practice, from the current perspective and that of what to expect in the future. Great strides forward are being made in breaking down important barriers to the successful prevention and treatment of this devastating disorder.

Stochastic gene expression out-of-steady-state in the cyanobacterial circadian clock

Recent advances in measuring gene expression at the single-cell level have highlighted the stochastic nature of messenger RNA and protein synthesis. Stochastic gene expression creates a source of variability in the abundance of cellular components, even among isogenic cells exposed to an identical environment. Recent integrated experimental and modelling studies have shed light on the molecular sources of this variability. However, many of these studies focus on systems that have reached a steady state and therefore do not address a large class of dynamic phenomena including oscillatory gene expression. Here we develop a general protocol for analysing and predicting stochastic gene expression in systems that never reach steady states. We use this framework to analyse experimentally stochastic expression of genes driven by the Synechococcus elongatus circadian clock. We find that, although the average expression at two points in the circadian cycle separated by 12 hours is identical, the variability at these two time points can be different. We show that this is a general feature of out-of-steady-state systems. We demonstrate how intrinsic noise sources, owing to random births and deaths of mRNAs and proteins, or extrinsic noise sources, which introduce fluctuations in rate constants, affect the cell-to-cell variability. To distinguish experimentally between these sources, we measured how the correlation between expression fluctuations of two identical genes is modulated during the circadian cycle. This quantitative framework is generally applicable to any out-of-steady-state system and will be necessary for understanding the fidelity of dynamic cellular systems.

Gene expression of Clonorchis sinensis metacercaria induced by gamma irradiation

Gamma-rays are a form of ionizing radiation and produce serious cellular damage to nuclei and organelles. Gamma irradiation induces the expressions of genes involved in DNA repair. Clonorchis sinensis resides in and provokes pathophysiologic changes in the bile ducts of mammals. The C. sinensis metacercariae are unsusceptible or resistant to gamma irradiation with LD50 of 16.5 Gy. Using the annealing control primer-based polymerase chain reaction (PCR) method, 19 genes were found to be up-regulated in C. sinensis metacercariae exposed to gamma rays. Contigs of up-regulated genes (URGs) were retrieved in a C. sinensis expressed sequence tag pool and extended by DNA-walking. Of the 13 URGs annotated putatively as functional genes, five URGs were associated with energy metabolism, six with protein processing, and the other two with DNA repair protein RAD23 and inhibitor of apoptosis protein. Four URGs were confirmed up-regulated by gamma irradiation by quantitative real-time PCR. One unknown gene, which was up-regulated to the greatest extent, might contribute to early recovery from gamma-irradiation-induced damage. The up-regulations of genes encoding DNA repair, protein processing, and energy metabolism proteins suggests that increases in gene products orchestrate DNA lesion repair and recover cellular functions in gamma-irradiated C. sinensis metacercariae.

Downregulation of Tsx and OmpW and upregulation of OmpX are required for iron homeostasis in Escherichia coli

Upregulation of outer membrane (OM) proteins was systematically investigated in response to poor iron availability in the host and natural environments, but downregulation of OM proteins was ill-defined in this response. We utilized proteomic methodologies to characterize altered OM proteins in the sarcosine-insoluble fraction of Escherichia coli K12 cultured in LB medium with iron limitation. Notably, three novel proteins, Tsx, OmpW, and OmpX, related to iron homeostasis were identified; Tsx and OmpW were downregulated, and OmpX was upregulated. These alterations were functionally validated with the use of gene overexpression and deletion methods. Of the two downregulated proteins, Tsx was more sensitive to an iron-deficient environment than OmpW. In addition, the significantly negative correlation between Tsx with OmpW was achieved when overexpressed strains were used. These findings strongly indicate that the downregulation of Tsx and OmpW and the upregulation of OmpX are required for iron homeostasis in E. coli.

Genetic interaction screens with ordered overexpression and deletion clone sets implicate the Escherichia coli GTPase YjeQ in late ribosome biogenesis

The Escherichia coli protein YjeQ is a circularly permuted GTPase that is broadly conserved in bacteria. An emerging body of evidence, including cofractionation and in vitro binding to the ribosome, altered polysome profiles after YjeQ depletion, and stimulation of GTPase activity by ribosomes, suggests that YjeQ is involved in ribosome function. The growth of strains lacking YjeQ in culture is severely compromised. Here, we probed the cellular function of YjeQ with genetic screens of ordered E. coli genomic libraries for suppressors and enhancers of the slow-growth phenotype of a delta yjeQ strain. Screening for suppressors using an ordered library of 374 clones overexpressing essential genes and genes associated with ribosome function revealed that two GTPases, Era and initiation factor 2, ameliorated the growth and polysome defects of the delta yjeQ strain. In addition, seven bona fide enhancers of slow growth were identified (delta tgt, delta ksgA, delta ssrA, delta rimM, delta rluD, delta trmE/mnmE, and delta trmU/mnmA) among 39 deletions (in genes associated with ribosome function) that we constructed in the delta yjeQ genetic background. Taken in context, our work is most consistent with the hypothesis that YjeQ has a role in late 30S subunit biogenesis.

The average mutual information profile as a genomic signature

Background

Occult organizational structures in DNA sequences may hold the key to understanding functional and evolutionary aspects of the DNA molecule. Such structures can also provide the means for identifying and discriminating organisms using genomic data. Species specific genomic signatures are useful in a variety of contexts such as evolutionary analysis, assembly and classification of genomic sequences from large uncultivated microbial communities and a rapid identification system in health hazard situations.

Results

We have analyzed genomic sequences of eukaryotic and prokaryotic chromosomes as well as various subtypes of viruses using an information theoretic framework. We confirm the existence of a species specific average mutual information (AMI) profile. We use these profiles to define a very simple, computationally efficient, alignment free, distance measure that reflects the evolutionary relationships between genomic sequences. We use this distance measure to classify chromosomes according to species of origin, to separate and cluster subtypes of the HIV-1 virus, and classify DNA fragments to species of origin.

Conclusion

AMI profiles of DNA sequences prove to be species specific and easy to compute. The structure of AMI profiles are conserved, even in short subsequences of a species' genome, rendering a pervasive signature. This signature can be used to classify relatively short DNA fragments to species of origin.

Cyclic AMP-dependent catabolite repression is the dominant control mechanism of metabolic fluxes under glucose limitation in Escherichia coli

Although a whole arsenal of mechanisms are potentially involved in metabolic regulation, it is largely uncertain when, under which conditions, and to which extent a particular mechanism actually controls network fluxes and thus cellular physiology. Based on (13)C flux analysis of Escherichia coli mutants, we elucidated the relevance of global transcriptional regulation by ArcA, ArcB, Cra, CreB, CreC, Crp, Cya, Fnr, Hns, Mlc, OmpR, and UspA on aerobic glucose catabolism in glucose-limited chemostat cultures at a growth rate of 0.1 h(-1). The by far most relevant control mechanism was cyclic AMP (cAMP)-dependent catabolite repression as the inducer of the phosphoenolpyruvate (PEP)-glyoxylate cycle and thus low tricarboxylic acid cycle fluxes. While all other mutants and the reference E. coli strain exhibited high glyoxylate shunt and PEP carboxykinase fluxes, and thus high PEP-glyoxylate cycle flux, this cycle was essentially abolished in both the Crp and Cya mutants, which lack the cAMP-cAMP receptor protein complex. Most other mutations were phenotypically silent, and only the Cra and Hns mutants exhibited slightly altered flux distributions through PEP carboxykinase and the tricarboxylic acid cycle, respectively. The Cra effect on PEP carboxykinase was probably the consequence of a specific control mechanism, while the Hns effect appears to be unspecific. For central metabolism, the available data thus suggest that a single transcriptional regulation process exerts the dominant control under a given condition and this control is highly specific for a single pathway or cycle within the network.

The genome of Pelotomaculum thermopropionicum reveals niche-associated evolution in anaerobic microbiota

The anaerobic biodegradation of organic matter is accomplished by sequential syntrophic catabolism by microbes in different niches. Pelotomaculum thermopropionicum is a representative syntrophic bacterium that catalyzes the intermediate bottleneck step in the anaerobic-biodegradation process, whereby volatile fatty acids (VFAs) and alcohols produced by upstream fermenting bacteria are converted to acetate, hydrogen, and carbon dioxide (substrates for downstream methanogenic archaea). To reveal genomic features that contribute to our understanding of the ecological niche and evolution of P. thermopropionicum, we sequenced its 3,025,375-bp genome and performed comparative analyses with genomes of other community members available in the databases. In the genome, 2920 coding sequences (CDSs) were identified. These CDSs showed a distinct distribution pattern in the functional categories of the Clusters of Orthologous Groups database, which is considered to reflect the niche of this organism. P. thermopropionicum has simple catabolic pathways, in which the propionate-oxidizing methylmalonyl-CoA pathway constitutes the backbone and is linked to several peripheral pathways. Genes for most of the important catabolic enzymes are physically linked to those for PAS-domain-containing regulators, suggesting that the catabolic pathways are regulated in response to environmental conditions and/or global cellular situations rather than specific substrates. Comparative analyses of codon usages revealed close evolutionary relationships between P. thermopropionicum and other niche members, while it was distant from phylogenetically related sugar-fermenting bacteria. These analyses suggest that P. thermopropionicum has evolved as a syntrophy specialist by interacting with niche-associated microbes.

Probabilistic assembly of human protein interaction networks from label-free quantitative proteomics

Large-scale affinity purification and mass spectrometry studies have played important roles in the assembly and analysis of comprehensive protein interaction networks for lower eukaryotes. However, the development of such networks for human proteins has been slowed by the high cost and significant technical challenges associated with systematic studies of protein interactions. To address this challenge, we have developed a method for building local and focused networks. This approach couples vector algebra and statistical methods with normalized spectral counting (NSAF) derived from the analysis of affinity purifications via chromatography-based proteomics. After mathematical removal of contaminant proteins, the core components of multiprotein complexes are determined by singular value decomposition analysis and clustering. The probability of interactions within and between complexes is computed solely based upon NSAFs using Bayes' approach. To demonstrate the application of this method to small-scale datasets, we analyzed an expanded human TIP49a and TIP49b dataset. This dataset contained proteins affinity-purified with 27 different epitope-tagged components of the chromatin remodeling SRCAP, hINO80, and TRRAP/TIP60 complexes, and the nutrient sensing complex Uri/Prefoldin. Within a core network of 65 unique proteins, we captured all known components of these complexes and novel protein associations, especially in the Uri/Prefoldin complex. Finally, we constructed a probabilistic human interaction network composed of 557 protein pairs.

Predicting biological system objectives de novo from internal state measurements

Background

Optimization theory has been applied to complex biological systems to interrogate network properties and develop and refine metabolic engineering strategies. For example, methods are emerging to engineer cells to optimally produce byproducts of commercial value, such as bioethanol, as well as molecular compounds for disease therapy. Flux balance analysis (FBA) is an optimization framework that aids in this interrogation by generating predictions of optimal flux distributions in cellular networks. Critical features of FBA are the definition of a biologically relevant objective function (e.g., maximizing the rate of synthesis of biomass, a unit of measurement of cellular growth) and the subsequent application of linear programming (LP) to identify fluxes through a reaction network. Despite the success of FBA, a central remaining challenge is the definition of a network objective with biological meaning.

Results

We present a novel method called Biological Objective Solution Search (BOSS) for the inference of an objective function of a biological system from its underlying network stoichiometry as well as experimentally-measured state variables. Specifically, BOSS identifies a system objective by defining a putative stoichiometric "objective reaction," adding this reaction to the existing set of stoichiometric constraints arising from known interactions within a network, and maximizing the putative objective reaction via LP, all the while minimizing the difference between the resultant in silico flux distribution and available experimental (e.g., isotopomer) flux data. This new approach allows for discovery of objectives with previously unknown stoichiometry, thus extending the biological relevance from earlier methods. We verify our approach on the well-characterized central metabolic network of Saccharomyces cerevisiae.

Conclusion

We illustrate how BOSS offers insight into the functional organization of biochemical networks, facilitating the interrogation of cellular design principles and development of cellular engineering applications. Furthermore, we describe how growth is the best-fit objective function for the yeast metabolic network given experimentally-measured fluxes.

Regulatory network reconstruction using an integral additive model with flexible kernel functions

Background

Reconstruction of regulatory networks is one of the most challenging tasks of systems biology. A limited amount of experimental data and little prior knowledge make the problem difficult to solve. Although models that are currently used for inferring regulatory networks are sometimes able to make useful predictions about the structures and mechanisms of molecular interactions, there is still a strong demand to develop increasingly universal and accurate approaches for network reconstruction.

Results

The additive regulation model is represented by a set of differential equations and is frequently used for network inference from time series data. Here we generalize this model by converting differential equations into integral equations with adjustable kernel functions. These kernel functions can be selected based on prior knowledge or defined through iterative improvement in data analysis. This makes the integral model very flexible and thus capable of covering a broad range of biological systems more adequately and specifically than previous models.

Conclusion

We reconstructed network structures from artificial and real experimental data using differential and integral inference models. The artificial data were simulated using mathematical models implemented in JDesigner. The real data were publicly available yeast cell cycle microarray time series. The integral model outperformed the differential one for all cases. In the integral model, we tested the zero-degree polynomial and single exponential kernels. Further improvements could be expected if the kernel were selected more specifically depending on the system.

Profiling the Monascus pilosus proteome during nitrogen limitation

Monascus species have the unique ability to economically produce many secondary metabolites. However, the influence of nitrogen limitation on Monascus secondary metabolite production and metabolic performance remains unclear. Varying the carbon/nitrogen (C/N) ratios in the range from 20 to 60 in cultivation of Monascus pilosus by glucose nitrate medium, our resulting data showed that red pigment production was significantly suppressed and more sensitive to nitrogen limitation than cellular biomass growth at a C/N ratio of 60. Using a comparative proteomic approach, combining two-dimensional gel electrophoresis, matrix-assisted laser desorption ionization time-of-flight/time-of-flight liquid chromatography-mass spectrometry, and tandem mass spectrometry, proteins with modified expression in the nitrogen-limited (C/N ratio 60) Monascus filamentous cells were identified. The results revealed that the deregulated proteins identified were involved in amino acid biosynthesis, protein translation, antioxidant-related enzymes, glycolysis, and transcriptional regulation. The results suggested that, under nitrogen limitation-induced suppression of protein translation and of expression of the related energy-generating enzymes, nitrogen limitation induced a switch of metabolic flux from glycolysis to the tricarboxylic acid (TCA) cycle for maintaining cellular energy homeostasis, resulting in repression of the metabolic shift of the polyketide biosynthesis pathway for red pigment production.

A microfluidic device for temporally controlled gene expression and long-term fluorescent imaging in unperturbed dividing yeast cells

BACKGROUND

Imaging single cells with fluorescent markers over multiple cell cycles is a powerful tool for unraveling the mechanism and dynamics of the cell cycle. Over the past ten years, microfluidic techniques in cell biology have emerged that allow for good control of growth environment. Yet the control and quantification of transient gene expression in unperturbed dividing cells has received less attention.

METHODOLOGY/PRINCIPAL FINDINGS

Here, we describe a microfluidic flow cell to grow Saccharomyces Cerevisiae for more than 8 generations (approximately 12 hrs) starting with single cells, with controlled flow of the growth medium. This setup provides two important features: first, cells are tightly confined and grow in a remarkably planar array. The pedigree can thus be determined and single-cell fluorescence measured with 3 minutes resolution for all cells, as a founder cell grows to a micro-colony of more than 200 cells. Second, we can trigger and calibrate rapid and transient gene expression using reversible administration of inducers that control the GAL1 or MET3 promoters. We then show that periodic 10-20 minutes gene induction pulses can drive many cell division cycles with complete coherence across the cell cluster, with either a G1/S trigger (cln1 cln2 cln3 MET3-CLN2) or a mitotic trigger (cdc20 GALL-CDC20).

CONCLUSIONS/SIGNIFICANCE

In addition to evident cell cycle applications, this device can be used to directly measure the amount and duration of any fluorescently scorable signal-transduction or gene-induction response over a long time period. The system allows direct correlation of cell history (e.g., hysteresis or epigenetics) or cell cycle position with the measured response.

Impact of the solvent capacity constraint on E. coli metabolism

Background

Obtaining quantitative predictions for cellular metabolic activities requires the identification and modeling of the physicochemical constraints that are relevant at physiological growth conditions. Molecular crowding in a cell's cytoplasm is one such potential constraint, as it limits the solvent capacity available to metabolic enzymes.

Results

Using a recently introduced flux balance modeling framework (FBAwMC) here we demonstrate that this constraint determines a metabolic switch in E. coli cells when they are shifted from low to high growth rates. The switch is characterized by a change in effective optimization strategy, the excretion of acetate at high growth rates, and a global reorganization of E. coli metabolic fluxes, the latter being partially confirmed by flux measurements of central metabolic reactions.

Conclusion

These results implicate the solvent capacity as an important physiological constraint acting on E. coli cells operating at high metabolic rates and for the activation of a metabolic switch when they are shifted from low to high growth rates. The relevance of this constraint in the context of both the aerobic ethanol excretion seen in fast growing yeast cells (Crabtree effect) and the aerobic glycolysis observed in rapidly dividing cancer cells (Warburg effect) should be addressed in the future.

Reaching for high-hanging fruit in drug discovery at protein-protein interfaces

Targeting the interfaces between proteins has huge therapeutic potential, but discovering small-molecule drugs that disrupt protein-protein interactions is an enormous challenge. Several recent success stories, however, indicate that protein-protein interfaces might be more tractable than has been thought. These studies discovered small molecules that bind with drug-like potencies to 'hotspots' on the contact surfaces involved in protein-protein interactions. Remarkably, these small molecules bind deeper within the contact surface of the target protein, and bind with much higher efficiencies, than do the contact atoms of the natural protein partner. Some of these small molecules are now making their way through clinical trials, so this high-hanging fruit might not be far out of reach.

The histone-like NF-Y is a bifunctional transcription factor

NF-Y is a trimeric transcription factor containing H2A/H2B-like subunits, which specifically binds to the CCAAT box, a common eukaryotic promoter element. To gain insights into NF-Y-dependent transcriptional regulation, we assessed its relationships with positive histone marks by chromatin immunoprecipitation-on-chip and correlative-profiling studies. Unbiased identification of binding sites shows that the majority of genes are bound by NF-Y in the promoter and/or within the coding region. Parallel analysis of H3K9-14ac and H3K4me3 sites indicates that NF-Y loci can be divided in two distinct clusters: (i) a large cohort contains H3K9-14ac and H3K4me3 marks and correlates with expression and (ii) a sizeable group is devoid of these marks and is found on transcriptionally silent genes. Within this class, we find that NF-Y binding is associated with negative histone marks, such as H4K20me3 and H3K27me3. NF-Y removal by a dominant negative NF-YA leads to a decrease in the transcription of expressed genes associated with H3K4me3 and H3K9-14ac, while increasing the levels of many inactive genes. These data indicate that NF-Y is embedded in positive as well as in negative methyl histone marks, serving a dual function in transcriptional regulation, as an activator or as a repressor.

Liver regeneration

Liver regeneration after partial hepatectomy is a very complex and well-orchestrated phenomenon. It is carried out by the participation of all mature liver cell types. The process is associated with signaling cascades involving growth factors, cytokines, matrix remodeling, and several feedbacks of stimulation and inhibition of growth related signals. Liver manages to restore any lost mass and adjust its size to that of the organism, while at the same time providing full support for body homeostasis during the entire regenerative process. In situations when hepatocytes or biliary cells are blocked from regeneration, these cell types can function as facultative stem cells for each other.

The novel combination of chlorpromazine and pentamidine exerts synergistic antiproliferative effects through dual mitotic action

Combination therapy has proven successful in treating a wide variety of aggressive human cancers. Historically, combination treatments have been discovered through serendipity or lengthy trials using known anticancer agents with similar indications. We have used combination high-throughput screening to discover the unexpected synergistic combination of an antiparasitic agent, pentamidine, and a phenothiazine antipsychotic, chlorpromazine. This combination, CRx-026, inhibits the growth of tumor cell lines in vivo more effectively than either pentamidine or chlorpromazine alone. Here, we report that CRx-026 exerts its antiproliferative effect through synergistic dual mitotic action. Chlorpromazine is a potent and specific inhibitor of the mitotic kinesin KSP/Eg5 and inhibits tumor cell proliferation through mitotic arrest and accumulation of monopolar spindles. Pentamidine treatment results in chromosomal segregation defects and delayed progression through mitosis, consistent with inhibition of the phosphatase of regenerating liver family of phosphatases. We also show that CRx-026 synergizes in vitro and in vivo with the microtubule-binding agents paclitaxel and vinorelbine. These data support a model where dual action of pentamidine and chlorpromazine in mitosis results in synergistic antitumor effects and show the importance of systematic screening for combinations of targeted agents.

Wave-pinning and cell polarity from a bistable reaction-diffusion system

Motile eukaryotic cells polarize in response to external signals. Numerous mechanisms have been suggested to account for this symmetry breaking and for the ensuing robust polarization. Implicated in this process are various proteins that are recruited to the plasma membrane and segregate at an emergent front or back of the polarizing cell. Among these are PI3K, PTEN, and members of the Rho family GTPases such as Cdc42, Rac, and Rho. Many such proteins, including the Rho GTPases, cycle between active membrane-bound forms and inactive cytosolic forms. In previous work, we have shown that this property, together with appropriate crosstalk, endows a biochemical circuit (Cdc42, Rac, and Rho) with the property of inherent polarizability. Here we show that this property is present in an even simpler system comprised of a single active/inactive protein pair with positive feedback to its own activation. The simplicity of this minimal system also allows us to explain the mechanism using insights from mathematical analysis. The basic idea resides in a well-known property of reaction-diffusion systems with bistable kinetics, namely, propagation of fronts. However, it crucially depends on exchange between active and inactive forms of the chemicals with unequal rates of diffusion, and overall conservation to pin the waves into a stable polar distribution. We refer to these dynamics as wave-pinning and we show that this phenomenon is distinct from Turing-instability-generated pattern formation that occurs in reaction-diffusion systems that appear to be very similar. We explain the mathematical basis of the phenomenon, relate it to spatial segregation of Rho GTPases, and show how it can account for spatial amplification and maintenance of polarity, as well as sensitivity to new stimuli typical in polarization of eukaryotic cells.

The evolutionary dynamics of the Saccharomyces cerevisiae protein interaction network after duplication

Gene duplication is an important mechanism in the evolution of protein interaction networks. Duplications are followed by the gain and loss of interactions, rewiring the network at some unknown rate. Because rewiring is likely to change the distribution of network motifs within the duplicated interaction set, it should be possible to study network rewiring by tracking the evolution of these motifs. We have developed a mathematical framework that, together with duplication data from comparative genomic and proteomic studies, allows us to infer the connectivity of the preduplication network and the changes in connectivity over time. We focused on the whole-genome duplication (WGD) event in Saccharomyces cerevisiae. The model allowed us to predict the frequency of intergene interaction before WGD and the post duplication probabilities of interaction gain and loss. We find that the predicted frequency of self-interactions in the preduplication network is significantly higher than that observed in today's network. This could suggest a structural difference between the modern and ancestral networks, preferential addition or retention of interactions between ohnologs, or selective pressure to preserve duplicates of self-interacting proteins.

Dynamic in vivo metabolome response of Saccharomyces cerevisiae to a stepwise perturbation of the ATP requirement for benzoate export

Although much information is available on in vitro role of ATP in regulation, the in vivo kinetics of reactions in which ATP plays a role are only partly known. In order to study such reactions, it is therefore necessary to study the role of ATP in vivo. This study presents an in vivo, targeted perturbation of the ATP flux in aerobic glucose-limited chemostat cultures of Saccharomyces cerevisiae, which was accomplished by transiently (20 min) changing the extracellular undissociated benzoic acid concentration via the pH of the culture. The performed pH shifts resulted in, within about 20 s, a 40% decrease (pH upshift) or a 23% increase (pH downshift) of the calculated ATP consumption rate while the specific glucose uptake rate did not change because of the glucose-limited condition. The pH upshift resulted in a strong decrease in the glycolytic and TCA cycle fluxes; carbon and energy balances indicated an increased flux toward storage carbohydrates. As expected, the pH downshift leads to the opposite effects. Overall, consistent responses were observed in the metabolic fluxes, the off gas concentrations of O(2) and CO(2) and intracellular metabolite concentrations, except for the concentrations of adenosine nucleotides which unexpectedly only showed minor dynamics. This demonstrates that our knowledge of the regulation of the ATP level, the storage metabolism, and central carbon metabolism of yeast is still incomplete. The new dynamic metabolite datasets obtained in this study will prove of great value in developing kinetic models.