PaxDb, a database of protein abundance averages across all three domains of life

Tracking the evolution of 3D gene organization demonstrates its connection to phenotypic divergence

It has recently been shown that the organization of genes in eukaryotic genomes, and specifically in 3D, is strongly related to gene expression and function and partially conserved between organisms. However, previous studies of 3D genomic organization analyzed each organism independently from others. Here, we propose an approach for unified inter-organismal analysis of gene organization based on a network representation of Hi-C data. We define and detect four classes of spatially co-evolving orthologous modules (SCOMs), i.e. gene families that co-evolve in their 3D organization, based on patterns of divergence and conservation of distances. We demonstrate our methodology on Hi-C data from Saccharomyces cerevisiae and Schizosaccharomyces pombe, and identify, among others, modules relating to RNA splicing machinery and chromatin silencing by small RNA which are central to S. pombe's lifestyle. Our results emphasize the importance of 3D genomic organization in eukaryotes and suggest that the evolutionary mechanisms that shape gene organization affect the organism fitness and phenotypes. The proposed algorithms can be utilized in future studies of genome evolution and comparative analysis of spatial genomic organization in different tissues, conditions and single cells.

A thiol probe for measuring unfolded protein load and proteostasis in cells

When proteostasis becomes unbalanced, unfolded proteins can accumulate and aggregate. Here we report that the dye, tetraphenylethene maleimide (TPE-MI) can be used to measure cellular unfolded protein load. TPE-MI fluorescence is activated upon labelling free cysteine thiols, normally buried in the core of globular proteins that are exposed upon unfolding. Crucially TPE-MI does not become fluorescent when conjugated to soluble glutathione. We find that TPE-MI fluorescence is enhanced upon reaction with cellular proteomes under conditions promoting accumulation of unfolded proteins. TPE-MI reactivity can be used to track which proteins expose more cysteine residues under stress through proteomic analysis. We show that TPE-MI can report imbalances in proteostasis in induced pluripotent stem cell models of Huntington disease, as well as cells transfected with mutant Huntington exon 1 before the formation of visible aggregates. TPE-MI also detects protein damage following dihydroartemisinin treatment of the malaria parasites Plasmodium falciparum. TPE-MI therefore holds promise as a tool to probe proteostasis mechanisms in disease.

Proteostasis is maintained through a number of molecular mechanisms, some of which function to protect the folded state of proteins. Here the authors demonstrate the use of TPE-MI in a fluorigenic dye assay for the quantitation of unfolded proteins that can be used to assess proteostasis on a cellular or proteome scale.

The Mechanism of Regulation of Pantothenate Biosynthesis by the PanD-PanZ·AcCoA Complex Reveals an Additional Mode of Action for the Antimetabolite N-Pentyl Pantothenamide (N5-Pan)

The antimetabolite pentyl pantothenamide has broad spectrum antibiotic activity but exhibits enhanced activity against Escherichia coli. The PanDZ complex has been proposed to regulate the pantothenate biosynthetic pathway in E. coli by limiting the supply of β-alanine in response to coenzyme A concentration. We show that formation of such a complex between activated aspartate decarboxylase (PanD) and PanZ leads to sequestration of the pyruvoyl cofactor as a ketone hydrate and demonstrate that both PanZ overexpression-linked β-alanine auxotrophy and pentyl pantothenamide toxicity are due to formation of this complex. This both demonstrates that the PanDZ complex regulates pantothenate biosynthesis in a cellular context and validates the complex as a target for antibiotic development.

Immunoregulation by IL-7R-targeting antibody-drug conjugates: overcoming steroid-resistance in cancer and autoimmune disease

Steroid-resistance is a common complication in the treatment of malignancies and autoimmune diseases. IL-7/IL-7R signaling, which regulates lymphocyte growth and survival, has been implicated in the development of malignancies and autoimmune diseases. However, the biological significance of IL-7/IL-7R signaling in steroid treatment is poorly understood. Here, we identified a novel relationship between IL-7R signaling and steroid-resistance, and showed that an anti-IL-7R antibody conjugated with SN-38 (A7R-ADC-SN-38) has strong anti-tumor effects against both parental and steroid-resistant malignant cells. Furthermore, inflammation in the mouse autoimmune arthritis model was suppressed to greater extent by A7R-ADC conjugated to MMAE than by A7R-ADC-SN-38. Given that an increased proportion of IL-7R-positive cells is a common mechanism underlying the pathogenesis of autoimmunity, we found that specific depletion of this cell population abrogated the progression of disease. This suggests that the cytotoxicity and immunosuppressive capacity of A7R-ADC could be modulated to treat specific malignancies or autoimmune diseases through the introduction of different payloads, and represents a novel alternative to steroid therapy.

Principles of cellular resource allocation revealed by condition-dependent proteome profiling

Growing cells coordinate protein translation with metabolic rates. Central to this coordination is ribosome production. Ribosomes drive cell growth, but translation of ribosomal proteins competes with production of non-ribosomal proteins. Theory shows that cell growth is maximized when all expressed ribosomes are constantly translating. To examine whether budding yeast function at this limit of full ribosomal usage, we profiled the proteomes of cells growing in different environments. We find that cells produce excess ribosomal proteins, amounting to a constant ≈8% of the proteome. Accordingly, ≈25% of ribosomal proteins expressed in rapidly growing cells does not contribute to translation. Further, this fraction increases as growth rate decreases and these excess ribosomal proteins are employed when translation demands unexpectedly increase. We suggest that steadily growing cells prepare for conditions that demand increased translation by producing excess ribosomes, at the expense of lower steady-state growth rate.

Predicting synonymous codon usage and optimizing the heterologous gene for expression in E. coli

Of the 20 common amino acids, 18 are encoded by multiple synonymous codons. These synonymous codons are not redundant; in fact, all of codons contribute substantially to protein expression, structure and function. In this study, the codon usage pattern of genes in the E. coli was learned from the sequenced genomes of E. coli. A machine learning based method, Presyncodon was proposed to predict synonymous codon selection in E. coli based on the learned codon usage patterns of the residue in the context of the specific fragment. The predicting results indicate that Presycoden could be used to predict synonymous codon selection of the gene in the E. coli with the high accuracy. Two reporter genes (egfp and mApple) were designed with a combination of low- and high-frequency-usage codons by the method. The fluorescence intensity of eGFP and mApple expressed by the (egfp and mApple) designed by this method was about 2.3- or 1.7- folds greater than that from the genes with only high-frequency-usage codons in E. coli. Therefore, both low- and high-frequency-usage codons make positive contributions to the functional expression of the heterologous proteins. This method could be used to design synthetic genes for heterologous gene expression in biotechnology.

The MukB-topoisomerase IV interaction is required for proper chromosome compaction

The bacterial condensin MukB and the cellular decatenating enzyme topoisomerase IV interact. This interaction stimulates intramolecular reactions catalyzed by topoisomerase IV, supercoiled DNA relaxation, and DNA knotting but not intermolecular reactions such as decatenation of linked DNAs. We have demonstrated previously that MukB condenses DNA by sequestering negative supercoils and stabilizing topologically isolated loops in the DNA. We show here that the MukB-topoisomerase IV interaction stabilizes MukB on DNA, increasing the extent of DNA condensation without increasing the amount of MukB bound to the DNA. This effect does not require the catalytic activity of topoisomerase IV. Cells carrying a mukB mutant allele that encodes a protein that does not interact with topoisomerase IV exhibit severe nucleoid decompaction leading to chromosome segregation defects. These findings suggest that the MukB-topoisomerase IV complex may provide a scaffold for DNA condensation.

Bicistronic expression strategy for high-level expression of recombinant proteins in Corynebacterium glutamicum

Directly using the promoter associated with 5'-untranslated region of a high-protein-abundance gene from the genome may cause low expression activity of an expression system. A bicistronic expression part containing the short 5' coding sequence of the source gene and an embedded Shine-Dalgarno sequence can cause higher expression levels of the recombinant gene in a bicistronic cassette. Here, we evaluated two methods to construct expression parts and exploited genomic sequence sources to provide specific functional sequences to complete the expression system. The architecture of the bicistronic part increased the expression levels of target genes and performed more reliably than conventional expression parts with the same promoter and 5' untranslated region. For Corynebacterium glutamicum, the strongest bicistronic part, HP-BEP4, was obtained from a heterologous sequence source, leading to a 2.24-fold increase in the expression level of fluorescent protein over constitutively expressed pXMJ19 or the production of more than 100 mg/L single-chain variable fragment (scFv). It could meet the needs of overexpressing key genes in C. glutamicum.

Reactivity of human AGO2 monoclonal antibody 11A9 with the SWI/SNF complex: A case study for rigorously defining antibody selectivity

In this study, we originally aimed to characterize the potential role of Argonaute 2 (AGO2) in the nucleus, a key protein of the miRNA machinery. We combined Chromatin Immunoprecipitation (ChIP) with high throughput sequencing (ChIP-seq) and quantitative mass spectrometry (ChIP-MS) using the broadly used AGO2 11A9 antibody to determine interactions with chromatin and nuclear proteins. We found a previously described interaction between AGO2 and SWI/SNF on chromatin with ChIP-MS and observed enrichment at enhancers and transcription start sites using ChIP-seq. However, antibody specificity issues can produce misleading results for ChIP, RNA-seq and Mass spectrometry. Therefore, we developed a CRISPR/Cas9 engineered AGO2^−/− HEK293T cell line to validate our findings. ChIP-qPCR and immunoprecipitation combined with MS (IP-MS) showed that the 11A9 antibody associates with chromatin and SWI/SNF in the absence of AGO2. Furthermore, stoichiometry, IP-MS and co-IP analysis suggests a direct interaction of this antibody with SMARCC1, a component of the SWI/SNF complex. For this reason, particular care should be taken in performing and interpreting experiments in which the 11A9 antibody is used to study a nuclear role of AGO2.

Improving the phenotype predictions of a yeast genome-scale metabolic model by incorporating enzymatic constraints

Genome-scale metabolic models (GEMs) are widely used to calculate metabolic phenotypes. They rely on defining a set of constraints, the most common of which is that the production of metabolites and/or growth are limited by the carbon source uptake rate. However, enzyme abundances and kinetics, which act as limitations on metabolic fluxes, are not taken into account. Here, we present GECKO, a method that enhances a GEM to account for enzymes as part of reactions, thereby ensuring that each metabolic flux does not exceed its maximum capacity, equal to the product of the enzyme's abundance and turnover number. We applied GECKO to a Saccharomyces cerevisiae GEM and demonstrated that the new model could correctly describe phenotypes that the previous model could not, particularly under high enzymatic pressure conditions, such as yeast growing on different carbon sources in excess, coping with stress, or overexpressing a specific pathway. GECKO also allows to directly integrate quantitative proteomics data; by doing so, we significantly reduced flux variability of the model, in over 60% of metabolic reactions. Additionally, the model gives insight into the distribution of enzyme usage between and within metabolic pathways. The developed method and model are expected to increase the use of model-based design in metabolic engineering.

Proteins evolve on the edge of supramolecular self-assembly

The self-association of proteins into symmetric complexes is ubiquitous in all kingdoms of life. Symmetric complexes possess unique geometric and functional properties, but their internal symmetry can pose a risk. In sickle-cell disease, the symmetry of haemoglobin exacerbates the effect of a mutation, triggering assembly into harmful fibrils. Here we examine the universality of this mechanism and its relation to protein structure geometry. We introduced point mutations solely designed to increase surface hydrophobicity among 12 distinct symmetric complexes from Escherichia coli. Notably, all responded by forming supramolecular assemblies in vitro, as well as in vivo upon heterologous expression in Saccharomyces cerevisiae. Remarkably, in four cases, micrometre-long fibrils formed in vivo in response to a single point mutation. Biophysical measurements and electron microscopy revealed that mutants self-assembled in their folded states and so were not amyloid-like. Structural examination of 73 mutants identified supramolecular assembly hot spots predictable by geometry. A subsequent structural analysis of 7,471 symmetric complexes showed that geometric hot spots were buffered chemically by hydrophilic residues, suggesting a mechanism preventing mis-assembly of these regions. Thus, point mutations can frequently trigger folded proteins to self-assemble into higher-order structures. This potential is counterbalanced by negative selection and can be exploited to design nanomaterials in living cells.

Differential regulation of germ line apoptosis and germ cell differentiation by CPEB family members in C. elegans

Cytoplasmic polyadenylation element binding (CPEB) proteins are evolutionary conserved RNA-binding proteins that control mRNA polyadenylation and translation. Orthologs in humans and other vertebrates are mainly involved in oogenesis. This is also the case for the C. elegans CPEB family member CPB-3, whereas two further CPEB proteins (CPB-1 and FOG-1) are involved in spermatogenesis. Here we describe the characterisation of a new missense allele of cpb-3 and show that loss of cpb-3 function leads to an increase in physiological germ cell death. To better understand the interaction and effect of C. elegans CPEB proteins on processes such as physiological apoptosis, germ cell differentiation, and regulation of gene expression, we characterised changes in the transcriptome and proteome of C. elegans CPEB mutants. Our results show that, despite their sequence similarities CPEB family members tend to have distinct overall effects on gene expression (both at the transcript and protein levels). This observation is consistent with the distinct phenotypes observed in the various CPEB family mutants.

Proteomic and biochemical assays of glutathione-related proteins in susceptible and multiple herbicide resistant Avena fatua L

Extensive herbicide usage has led to the evolution of resistant weed populations that cause substantial crop yield losses and increase production costs. The multiple herbicide resistant (MHR) Avena fatua L. populations utilized in this study are resistant to members of all selective herbicide families, across five modes of action, available for A. fatua control in U.S. small grain production, and thus pose significant agronomic and economic threats. Resistance to ALS and ACCase inhibitors is not conferred by target site mutations, indicating that non-target site resistance mechanisms are involved. To investigate the potential involvement of glutathione-related enzymes in the MHR phenotype, we used a combination of proteomic, biochemical, and immunological approaches to compare their constitutive activities in herbicide susceptible (HS1 and HS2) and MHR (MHR3 and MHR4) A. fatua plants. Proteomic analysis identified three tau and one phi glutathione S-transferases (GSTs) present at higher levels in MHR compared to HS plants, while immunoassays revealed elevated levels of lambda, phi, and tau GSTs. GST specific activity towards 1-chloro-2,4-dinitrobenzene was 1.2-fold higher in MHR4 than in HS1 plants and 1.3- and 1.2-fold higher in MHR3 than in HS1 and HS2 plants, respectively. However, GST specific activities towards fenoxaprop-P-ethyl and imazamethabenz-methyl were not different between untreated MHR and HS plants. Dehydroascorbate reductase specific activity was 1.4-fold higher in MHR than HS plants. Pretreatment with the GST inhibitor NBD-Cl did not affect MHR sensitivity to fenoxaprop-P-ethyl application, while the herbicide safener and GST inducer mefenpyr reduced the efficacy of low doses of fenoxaprop-P-ethyl on MHR4 but not MHR3 plants. Mefenpyr treatment also partially reduced the efficacy of thiencarbazone-methyl or mesosulfuron-methyl on MHR3 or MHR4 plants, respectively. Overall, the GSTs described here are not directly involved in enhanced rates of fenoxaprop-P-ethyl or imazamethabenz-methyl metabolism in MHR A. fatua. Instead, we propose that the constitutively elevated GST proteins and related enzymes in MHR plants are representative of a larger, more global suite of abiotic stress-related changes.

Secreted Proteins Defy the Expression Level-Evolutionary Rate Anticorrelation

The rates of evolution of the proteins of any organism vary across orders of magnitude. A primary factor influencing rates of protein evolution is expression. A strong negative correlation between expression levels and evolutionary rates (the so-called E-R anticorrelation) has been observed in virtually all studied organisms. This effect is currently attributed to the abundance-dependent fitness costs of misfolding and unspecific protein-protein interactions, among other factors. Secreted proteins are folded in the endoplasmic reticulum, a compartment where chaperones, folding catalysts, and stringent quality control mechanisms promote their correct folding and may reduce the fitness costs of misfolding. In addition, confinement of secreted proteins to the extracellular space may reduce misinteractions and their deleterious effects. We hypothesize that each of these factors (the secretory pathway quality control and extracellular location) may reduce the strength of the E-R anticorrelation. Indeed, here we show that among human proteins that are secreted to the extracellular space, rates of evolution do not correlate with protein abundances. This trend is robust to controlling for several potentially confounding factors and is also observed when analyzing protein abundance data for 6 human tissues. In addition, analysis of mRNA abundance data for 32 human tissues shows that the E-R correlation is always less negative, and sometimes nonsignificant, in secreted proteins. Similar observations were made in Caenorhabditis elegans and in Escherichia coli, and to a lesser extent in Drosophila melanogaster, Saccharomyces cerevisiae and Arabidopsis thaliana. Our observations contribute to understand the causes of the E-R anticorrelation.

Quantitative analysis of protein interaction network dynamics in yeast

Many cellular functions are mediated by protein–protein interaction networks, which are environment dependent. However, systematic measurement of interactions in diverse environments is required to better understand the relative importance of different mechanisms underlying network dynamics. To investigate environment‐dependent protein complex dynamics, we used a DNA‐barcode‐based multiplexed protein interaction assay in Saccharomyces cerevisiae to measure in vivo abundance of 1,379 binary protein complexes under 14 environments. Many binary complexes (55%) were environment dependent, especially those involving transmembrane transporters. We observed many concerted changes around highly connected proteins, and overall network dynamics suggested that “concerted” protein‐centered changes are prevalent. Under a diauxic shift in carbon source from glucose to ethanol, a mass‐action‐based model using relative mRNA levels explained an estimated 47% of the observed variance in binary complex abundance and predicted the direction of concerted binary complex changes with 88% accuracy. Thus, we provide a resource of yeast protein interaction measurements across diverse environments and illustrate the value of this resource in revealing mechanisms of network dynamics.

Development of an in silico method for the identification of subcomplexes involved in the biogenesis of multiprotein complexes in Saccharomyces cerevisiae

Background

Large sets of protein-protein interaction data coming either from biological experiments or predictive methods are available and can be combined to construct networks from which information about various cell processes can be extracted. We have developed an in silico approach based on these information to model the biogenesis of multiprotein complexes in the yeast Saccharomyces cerevisiae.

Results

Firstly, we have built three protein interaction networks by collecting the protein-protein interactions, which involved the subunits of three complexes, from different databases. The protein-protein interactions come from different kinds of biological experiments or are predicted. We have chosen the elongator and the mediator head complexes that are soluble and exhibit an architecture with subcomplexes that could be functional modules, and the mitochondrial bc₁ complex, which is an integral membrane complex and for which a late assembly subcomplex has been described. Secondly, by applying a clustering strategy to these networks, we were able to identify subcomplexes involved in the biogenesis of the complexes as well as the proteins interacting with each subcomplex. Thirdly, in order to validate our in silico results for the cytochrome bc1 complex we have analysed the physical interactions existing between three subunits by performing immunoprecipitation experiments in several genetic context.

Conclusions

For the two soluble complexes (the elongator and mediator head), our model shows a strong clustering of subunits that belong to a known subcomplex or module. For the membrane bc₁ complex, our approach has suggested new interactions between subunits in the early steps of the assembly pathway that were experimentally confirmed. Scripts can be downloaded from the site: http://bim.igmors.u-psud.fr/isips.

Electronic supplementary material

The online version of this article (doi:10.1186/s12918-017-0442-0) contains supplementary material, which is available to authorized users.

Thiamine Induces Long-Term Changes in Amino Acid Profiles and Activities of 2-Oxoglutarate and 2-Oxoadipate Dehydrogenases in Rat Brain

Molecular mechanisms of long-term changes in brain metabolism after thiamine administration (single i.p. injection, 400 mg/kg) were investigated. Protocols for discrimination of the activities of the thiamine diphosphate (ThDP)-dependent 2-oxoglutarate and 2-oxoadipate dehydrogenases were developed to characterize specific regulation of the multienzyme complexes of the 2-oxoglutarate (OGDHC) and 2-oxoadipate (OADHC) dehydrogenases by thiamine. The thiamine-induced changes depended on the brain-region-specific expression of the ThDP-dependent dehydrogenases. In the cerebral cortex, the original levels of OGDHC and OADHC were relatively high and not increased by thiamine, whereas in the cerebellum thiamine upregulated the OGDHC and OADHC activities, whose original levels were relatively low. The effects of thiamine on each of the complexes were different and associated with metabolic rearrangements, which included (i) the brain-region-specific alterations of glutamine synthase and/or glutamate dehydrogenase and NADP+-dependent malic enzyme, (ii) the brain-region-specific changes of the amino acid profiles, and (iii) decreased levels of a number of amino acids in blood plasma. Along with the assays of enzymatic activities and average levels of amino acids in the blood and brain, the thiamine-induced metabolic rearrangements were assessed by analysis of correlations between the levels of amino acids. The set and parameters of the correlations were tissue-specific, and their responses to the thiamine treatment provided additional information on metabolic changes, compared to that gained from the average levels of amino acids. Taken together, the data suggest that thiamine decreases catabolism of amino acids by means of a complex and long-term regulation of metabolic flux through the tricarboxylic acid cycle, which includes coupled changes in activities of the ThDP-dependent dehydrogenases of 2-oxoglutarate and 2-oxoadipate and adjacent enzymes.

Ribosome reinitiation can explain length-dependent translation of messenger RNA

Models of mRNA translation usually presume that transcripts are linear; upon reaching the end of a transcript each terminating ribosome returns to the cytoplasmic pool before initiating anew on a different transcript. A consequence of linear models is that faster translation of a given mRNA is unlikely to generate more of the encoded protein, particularly at low ribosome availability. Recent evidence indicates that eukaryotic mRNAs are circularized, potentially allowing terminating ribosomes to preferentially reinitiate on the same transcript. Here we model the effect of ribosome reinitiation on translation and show that, at high levels of reinitiation, protein synthesis rates are dominated by the time required to translate a given transcript. Our model provides a simple mechanistic explanation for many previously enigmatic features of eukaryotic translation, including the negative correlation of both ribosome densities and protein abundance on transcript length, the importance of codon usage in determining protein synthesis rates, and the negative correlation between transcript length and both codon adaptation and 5' mRNA folding energies. In contrast to linear models where translation is largely limited by initiation rates, our model reveals that all three stages of translation-initiation, elongation, and termination/reinitiation-determine protein synthesis rates even at low ribosome availability.

RECQ1 expression is upregulated in response to DNA damage and in a p53-dependent manner

Sensitivity of cancer cells to DNA damaging chemotherapeutics is determined by DNA repair processes. Consequently, cancer cells may upregulate the expression of certain DNA repair genes as a mechanism to promote chemoresistance. Here, we report that RECQ1, a breast cancer susceptibility gene that encodes the most abundant RecQ helicase in humans, is a p53-regulated gene, potentially acting as a defense against DNA damaging agents. We show that RECQ1 mRNA and protein levels are upregulated upon treatment of cancer cells with a variety of DNA damaging agents including the DNA-alkylating agent methylmethanesulfonate (MMS). The MMS-induced upregulation of RECQ1 expression is p53-dependent as it was observed in p53-proficient but not in isogenic p53-deficient cells. The RECQ1 promoter is bound by endogenous p53 and is responsive to p53 in luciferase reporter assays suggesting that RECQ1 is a direct target of p53. Treatment with the chemotherapeutic drugs temozolomide and fotemustine also increased RECQ1 mRNA levels whereas depletion of RECQ1 enhanced cellular sensitivity to these agents. These results identify a previously unrecognized p53-mediated upregulation of RECQ1 expression in response to DNA damage and implicate RECQ1 in the repair of DNA lesions including those induced by alkylating and other chemotherapeutic agents.

Spinal motor neuron protein supersaturation patterns are associated with inclusion body formation in ALS

Amyotrophic lateral sclerosis (ALS) is a heterogeneous degenerative motor neuron disease linked to numerous genetic mutations in apparently unrelated proteins. These proteins, including SOD1, TDP-43, and FUS, are highly aggregation-prone and form a variety of intracellular inclusion bodies that are characteristic of different neuropathological subtypes of the disease. Contained within these inclusions are a variety of proteins that do not share obvious characteristics other than coaggregation. However, recent evidence from other neurodegenerative disorders suggests that disease-affected biochemical pathways can be characterized by the presence of proteins that are supersaturated, with cellular concentrations significantly greater than their solubilities. Here, we show that the proteins that form inclusions of mutant SOD1, TDP-43, and FUS are not merely a subset of the native interaction partners of these three proteins, which are themselves supersaturated. To explain the presence of coaggregating proteins in inclusions in the brain and spinal cord, we observe that they have an average supersaturation even greater than the average supersaturation of the native interaction partners in motor neurons, but not when scores are generated from an average of other human tissues. These results suggest that inclusion bodies in various forms of ALS result from a set of proteins that are metastable in motor neurons, and thus prone to aggregation upon a disease-related progressive collapse of protein homeostasis in this specific setting.

How Changes in Anti-SD Sequences Would Affect SD Sequences in Escherichia coli and Bacillus subtilis

The 3' end of the small ribosomal RNAs (ssu rRNA) in bacteria is directly involved in the selection and binding of mRNA transcripts during translation initiation via well-documented interactions between a Shine-Dalgarno (SD) sequence located upstream of the initiation codon and an anti-SD (aSD) sequence at the 3' end of the ssu rRNA. Consequently, the 3' end of ssu rRNA (3'TAIL) is strongly conserved among bacterial species because a change in the region may impact the translation of many protein-coding genes. Escherichia coli and Bacillus subtilis differ in their 3' ends of ssu rRNA, being GAUCACCUCCUUA3' in E. coli and GAUCACCUCCUUUCU3' or GAUCACCUCCUUUCUA3' in B. subtilis Such differences in 3'TAIL lead to species-specific SDs (designated SD_Ec for E. coli and SD_Bs for B. subtilis) that can form strong and well-positioned SD/aSD pairing in one species but not in the other. Selection mediated by the species-specific 3'TAIL is expected to favor SD_Bs against SD_Ec in B. subtilis, but favor SD_Ec against SD_Bs in E. coli Among well-positioned SDs, SD_Ec is used more in E. coli than in B. subtilis, and SD_Bs more in B. subtilis than in E. coli Highly expressed genes and genes of high translation efficiency tend to have longer SDs than lowly expressed genes and genes with low translation efficiency in both species, but more so in B. subtilis than in E. coli Both species overuse SDs matching the bolded part of the 3'TAIL shown above. The 3'TAIL difference contributes to the host specificity of phages.

Delineating functional principles of the bow tie structure of a kinase-phosphatase network in the budding yeast

Background

Kinases and phosphatases (KP) form complex self-regulating networks essential for cellular signal processing. In spite of having a wealth of data about interactions among KPs and their substrates, we have very limited models of the structures of the directed networks they form and consequently our ability to formulate hypotheses about how their structure determines the flow of information in these networks is restricted.

Results

We assembled and studied the largest bona fide kinase-phosphatase network (KP-Net) known to date for the yeast Saccharomyces cerevisiae. Application of the vertex sort (VS) algorithm on the KP-Net allowed us to elucidate its hierarchical structure in which nodes are sorted into top, core and bottom layers, forming a bow tie structure with a strongly connected core layer. Surprisingly, phosphatases tend to sort into the top layer, implying they are less regulated by phosphorylation than kinases. Superposition of the widest range of KP biological properties over the KP-Net hierarchy shows that core layer KPs: (i), receive the largest number of inputs; (ii), form bottlenecks implicated in multiple pathways and in decision-making; (iii), and are among the most regulated KPs both temporally and spatially. Moreover, top layer KPs are more abundant and less noisy than those in the bottom layer. Finally, we showed that the VS algorithm depends on node degrees without biasing the biological results of the sorted network. The VS algorithm is available as an R package (https://cran.r-project.org/web/packages/VertexSort/index.html).

Conclusions

The KP-Net model we propose possesses a bow tie hierarchical structure in which the top layer appears to ensure highest fidelity and the core layer appears to mediate signal integration and cell state-dependent signal interpretation. Our model of the yeast KP-Net provides both functional insight into its organization as we understand today and a framework for future investigation of information processing in yeast and eukaryotes in general.

Electronic supplementary material

The online version of this article (doi:10.1186/s12918-017-0418-0) contains supplementary material, which is available to authorized users.

Bacterial proteostasis balances energy and chaperone utilization efficiently

Chaperones are protein complexes that help to fold and disaggregate a cell's proteins. It is not understood how four major chaperone systems of Escherichia coli work together in proteostasis: the recognition, sorting, folding, and disaggregating of the cell's many different proteins. Here, we model this machine. We combine extensive data on chaperoning, folding, and aggregation rates with expression levels of proteins and chaperones measured at different growth rates. We find that the proteostasis machine recognizes and sorts a client protein based on two biophysical properties of the client's misfolded state (M state): its stability and its kinetic accessibility from its unfolded state (U state). The machine is energy-efficient (the sickest proteins use the most ATP-expensive chaperones), comprehensive (it can handle any type of protein), and economical (the chaperone concentrations are just high enough to keep the whole proteome folded and disaggregated but no higher). The cell needs higher chaperone levels in two situations: fast growth (when protein production rates are high) and very slow growth (to mitigate the effects of protein degradation). This type of model complements experimental knowledge by showing how the various chaperones work together to achieve the broad folding and disaggregation needs of the cell.

Bicodon bias can determine the role of synonymous SNPs in human diseases

Background

For a long time synonymous single nucleotide polymorphisms were considered as silent mutations. However, nowadays it is well known that they can affect protein conformation and function, leading to altered disease susceptibilities, differential prognosis and/or drug responses, among other clinically relevant genetic traits. This occurs through different mechanisms: by disrupting the splicing signals of precursor mRNAs, affecting regulatory binding-sites of transcription factors and miRNAs, or by modifying the secondary structure of mRNAs.

Results

In this paper we considered 22 human genetic diseases or traits, linked to 35 synonymous single nucleotide polymorphisms in 27 different genes. We performed a local sequence context analysis in terms of the ribosomal pause propensity affected by synonymous single nucleotide polymorphisms. We found that synonymous mutations related to the above mentioned mechanisms presented small pause propensity changes, whereas synonymous mutations that were not related to those mechanisms presented large pause propensity changes. On the other hand, we did not observe large variations in the codon usage of codons associated with these mutations. Furthermore, we showed that the changes in the pause propensity associated with benign sSNPs are significantly lower than the pause propensity changes related to sSNPs associated to diseases.

Conclusions

These results suggest that the genetic diseases or traits related to synonymous mutations with large pause propensity changes, could be the consequence of another mechanism underlying non-silent synonymous mutations. Namely, alternative protein configuration related, in turn, to alterations in the ribosome-mediated translational attenuation program encoded by pairs of consecutive codons, not codons. These findings shed light on the latter mechanism based on the perturbation of the co-translational folding process.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-017-3609-6) contains supplementary material, which is available to authorized users.

Differential bicodon usage in lowly and highly abundant proteins

Degeneracy in the genetic code implies that different codons can encode the same amino acid. Usage preference of synonymous codons has been observed in all domains of life. There is much evidence suggesting that this bias has a major role on protein elongation rate, contributing to differential expression and to co-translational folding. In addition to codon usage bias, other preference variations have been observed such as codon pairs. In this paper, I report that codon pairs have significant different frequency usage for coding either lowly or highly abundant proteins. These usage preferences cannot be explained by the frequency usage of the single codons. The statistical analysis of coding sequences of nine organisms reveals that in many cases bicodon preferences are shared between related organisms. Furthermore, it is observed that misfolding in the drug-transport protein, encoded by MDR1 gene, is better explained by a big change in the pause propensity due to the synonymous bicodon variant, rather than by a relatively small change in codon usage. These findings suggest that codon pair usage can be a more powerful framework to understand translation elongation rate, protein folding efficiency, and to improve protocols to optimize heterologous gene expression.

Human Nup98 regulates the localization and activity of DExH/D-box helicase DHX9

Beyond their role at nuclear pore complexes, some nucleoporins function in the nucleoplasm. One such nucleoporin, Nup98, binds chromatin and regulates gene expression. To gain insight into how Nup98 contributes to this process, we focused on identifying novel binding partners and understanding the significance of these interactions. Here we report on the identification of the DExH/D-box helicase DHX9 as an intranuclear Nup98 binding partner. Various results, including in vitro assays, show that the FG/GLFG region of Nup98 binds to N- and C-terminal regions of DHX9 in an RNA facilitated manner. Importantly, binding of Nup98 stimulates the ATPase activity of DHX9, and a transcriptional reporter assay suggests Nup98 supports DHX9-stimulated transcription. Consistent with these observations, our analysis revealed that Nup98 and DHX9 bind interdependently to similar gene loci and their transcripts. Based on our results, we propose that Nup98 functions as a co-factor that regulates DHX9 and, potentially, other RNA helicases.

A method for high-throughput production of sequence-verified DNA libraries and strain collections

The low costs of array‐synthesized oligonucleotide libraries are empowering rapid advances in quantitative and synthetic biology. However, high synthesis error rates, uneven representation, and lack of access to individual oligonucleotides limit the true potential of these libraries. We have developed a cost‐effective method called Recombinase Directed Indexing (REDI), which involves integration of a complex library into yeast, site‐specific recombination to index library DNA, and next‐generation sequencing to identify desired clones. We used REDI to generate a library of ~3,300 DNA probes that exhibited > 96% purity and remarkable uniformity (> 95% of probes within twofold of the median abundance). Additionally, we created a collection of ~9,000 individually accessible CRISPR interference yeast strains for > 99% of genes required for either fermentative or respiratory growth, demonstrating the utility of REDI for rapid and cost‐effective creation of strain collections from oligonucleotide pools. Our approach is adaptable to any complex DNA library, and fundamentally changes how these libraries can be parsed, maintained, propagated, and characterized.

Mathematical modeling of the effects of CK2.3 on mineralization in osteoporotic bone

Osteoporosis is caused by decreased bone mineral density (BMD) and new treatments for this disease are desperately needed. Bone morphogenetic protein 2 (BMP2) is crucial for bone formation. The mimetic peptide CK2.3 acts downstream of BMP2 and increases BMD when injected systemically into the tail vein of mice. However, the most effective dosage needed to induce BMD in humans is unknown. We developed a mathematical model for CK2.3‐dependent bone mineralization. We used a physiologically based pharmacokinetic (PBPK) model to derive the CK2.3 concentration needed to increase BMD. Based on our results, the ideal dose of CK2.3 for a healthy individual to achieve the maximum increase of mineralization was about 409 µM injected in 500 µL volume, while dosage for osteoporosis patients was about 990 µM. This model showed that CK2.3 could increase the average area of bone mineralization in patients and in healthy adults.

Unsupervised detection of regulatory gene expression information in different genomic regions enables gene expression ranking

Background

The regulation of all gene expression steps (e.g., Transcription, RNA processing, Translation, and mRNA Degradation) is known to be primarily encoded in different parts of genes and in genomic regions in proximity to genes (e.g., promoters, untranslated regions, coding regions, introns, etc.). However, the entire gene expression codes and the genomic regions where they are encoded are still unknown.

Results

Here, we employ an unsupervised approach to estimate the concentration of gene expression codes in different non-coding parts of genes and transcripts, such as introns and untranslated regions, focusing on three model organisms (Escherichia coli, Saccharomyces cerevisiae, and Schizosaccharomyces pombe). Our analyses support the conjecture that regions adjacent to the beginning and end of ORFs and the beginning and end of introns tend to include higher concentration of gene expression information relatively to regions further away. In addition, we report the exact regions with elevated concentration of gene expression codes. Furthermore, we demonstrate that the concentration of these codes in different genetic regions is correlated with the expression levels of the corresponding genes, and with splicing efficiency measurements and meiotic stage gene expression measurements in S. cerevisiae.

Conclusion

We suggest that these discoveries improve our understanding of gene expression regulation and evolution; they can also be used for developing improved models of genome/gene evolution and for engineering gene expression in various biotechnological and synthetic biology applications.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-017-1497-z) contains supplementary material, which is available to authorized users.

Protein Degradation Rate in Arabidopsis thaliana Leaf Growth and Development

We applied ¹⁵N labeling approaches to leaves of the Arabidopsis thaliana rosette to characterize their protein degradation rate and understand its determinants. The progressive labeling of new peptides with ¹⁵N and measuring the decrease in the abundance of >60,000 existing peptides over time allowed us to define the degradation rate of 1228 proteins in vivo. We show that Arabidopsis protein half-lives vary from several hours to several months based on the exponential constant of the decay rate for each protein. This rate was calculated from the relative isotope abundance of each peptide and the fold change in protein abundance during growth. Protein complex membership and specific protein domains were found to be strong predictors of degradation rate, while N-end amino acid, hydrophobicity, or aggregation propensity of proteins were not. We discovered rapidly degrading subunits in a variety of protein complexes in plastids and identified the set of plant proteins whose degradation rate changed in different leaves of the rosette and correlated with leaf growth rate. From this information, we have calculated the protein turnover energy costs in different leaves and their key determinants within the proteome.

An Asymmetrically Balanced Organization of Kinases versus Phosphatases across Eukaryotes Determines Their Distinct Impacts

Protein phosphorylation underlies cellular response pathways across eukaryotes and is governed by the opposing actions of phosphorylating kinases and de-phosphorylating phosphatases. While kinases and phosphatases have been extensively studied, their organization and the mechanisms by which they balance each other are not well understood. To address these questions we performed quantitative analyses of large-scale 'omics' datasets from yeast, fly, plant, mouse and human. We uncovered an asymmetric balance of a previously-hidden scale: Each organism contained many different kinase genes, and these were balanced by a small set of highly abundant phosphatase proteins. Kinases were much more responsive to perturbations at the gene and protein levels. In addition, kinases had diverse scales of phenotypic impact when manipulated. Phosphatases, in contrast, were stable, highly robust and flatly organized, with rather uniform impact downstream. We validated aspects of this organization experimentally in nematode, and supported additional aspects by theoretic analysis of the dynamics of protein phosphorylation. Our analyses explain the empirical bias in the protein phosphorylation field toward characterization and therapeutic targeting of kinases at the expense of phosphatases. We show quantitatively and broadly that this is not only a historical bias, but stems from wide-ranging differences in their organization and impact. The asymmetric balance between these opposing regulators of protein phosphorylation is also common to opposing regulators of two other post-translational modification systems, suggesting its fundamental value.

Protein phosphorylation is a reversible modification that underlies cellular responses to stimuli across organisms. Historically, the study of protein phosphorylation concentrated on the role of kinases, which introduce the phosphate, at the expense of phosphatases, which remove it. Many kinases have been associated with specific phenotypes and considered attractive drug targets, while phosphatases remained far less characterized. It has been unclear whether this discrepancy is due to historical biases or reflects real systemic differences between these enzymes. By analyzing large-scale ‘omics’ datasets across genes, transcripts, proteins, interactions, and organisms, we uncovered an asymmetric architecture of kinases versus phosphatases that balances between them, determines their distinct impact patterns, and affects their therapeutic potential. This architecture is conserved from yeast to human and is partially shared by two other protein modification systems, suggesting it is a general feature of these systems.

Methionine residues around phosphorylation sites are preferentially oxidized in vivo under stress conditions

Protein phosphorylation is one of the most prevalent and well-understood protein modifications. Oxidation of protein-bound methionine, which has been traditionally perceived as an inevitable damage derived from oxidative stress, is now emerging as another modification capable of regulating protein activity during stress conditions. However, the mechanism coupling oxidative signals to changes in protein function remains unknown. An appealing hypothesis is that methionine oxidation might serve as a rheostat to control phosphorylation. To investigate this potential crosstalk between phosphorylation and methionine oxidation, we have addressed the co-occurrence of these two types of modifications within the human proteome. Here, we show that nearly all (98%) proteins containing oxidized methionine were also phosphoproteins. Furthermore, phosphorylation sites were much closer to oxidized methionines when compared to non-oxidized methionines. This proximity between modification sites cannot be accounted for by their co-localization within unstructured clusters because it was faithfully reproduced in a smaller sample of structured proteins. We also provide evidence that the oxidation of methionine located within phosphorylation motifs is a highly selective process among stress-related proteins, which supports the hypothesis of crosstalk between methionine oxidation and phosphorylation as part of the cellular defence against oxidative stress.

K-BILDS: A Kinase Substrate Discovery Tool

Kinases catalyze protein phosphorylation to regulate cell signaling events. However, identifying kinase substrates is challenging due to the often low abundance and dynamic nature of protein phosphorylation. Development of novel techniques to identify kinase substrates is necessary. Here, we report kinase-catalyzed biotinylation with inactivated lysates for discovery of substrates (K-BILDS) as a tool to identify direct substrates of a kinase. As a proof of concept, K-BILDS was applied to cAMP-dependent protein kinase A (PKA) with HeLa cell lysates. Subsequent enrichment and MS/MS analysis identified 279 candidate PKA substrates, including 56 previously known PKA substrates. Of the candidate substrates, nuclear autoantigenic sperm protein (NASP), BCL2-associated athanogene 3 (BAG3), and 14-3-3 protein Tau (YWHAQ) were validated as novel PKA substrates. K-BILDS provides a valuable tool to identify direct substrates of any protein kinase.

Bioinformatics and Drug Discovery

Bioinformatic analysis can not only accelerate drug target identification and drug candidate screening and refinement, but also facilitate characterization of side effects and predict drug resistance. High-throughput data such as genomic, epigenetic, genome architecture, cistromic, transcriptomic, proteomic, and ribosome profiling data have all made significant contribution to mechanismbased drug discovery and drug repurposing. Accumulation of protein and RNA structures, as well as development of homology modeling and protein structure simulation, coupled with large structure databases of small molecules and metabolites, paved the way for more realistic protein-ligand docking experiments and more informative virtual screening. I present the conceptual framework that drives the collection of these high-throughput data, summarize the utility and potential of mining these data in drug discovery, outline a few inherent limitations in data and software mining these data, point out news ways to refine analysis of these diverse types of data, and highlight commonly used software and databases relevant to drug discovery.

Reactive Oxygen Species Link Gonadotropin-Releasing Hormone Receptor Signaling Cascades in the Gonadotrope

Biological rhythms lie at the center of regulatory schemes that control many aspects of living systems. At the cellular level, meaningful responses to external stimuli depend on propagation and quenching of a signal to maintain vigilance for subsequent stimulation or changes that serve to shape and modulate the response. The hypothalamus-pituitary-gonad endocrine axis that controls reproductive development and function relies on control through rhythmic stimulation. Central to this axis is the pulsatile stimulation of the gonadotropes by hypothalamic neurons through episodic release of the neuropeptide gonadotropin-releasing hormone. Alterations in pulsatile stimulation of the gonadotropes result in differential synthesis and secretion of the gonadotropins LH and FSH and changes in the expression of their respective hormone subunit genes. The requirement to amplify signals arising from activation of the gonadotropin-releasing hormone (GnRH) receptor and to rapidly quench the resultant signal to preserve an adaptive response suggests the need for rapid activation and feedback control operating at the level of intracellular signaling. Emerging data suggest that reactive oxygen species (ROS) can fulfill this role in the GnRH receptor signaling through activation of MAP kinase signaling cascades, control of negative feedback, and participation in the secretory process. Results obtained in gonadotrope cell lines or other cell models indicate that ROS can participate in each of these regulatory cascades. We discuss the potential advantage of reactive oxygen signaling for modulating the gonadotrope response to GnRH stimulation and the potential mechanisms for this action. These observations suggest further targets of study for regulation in the gonadotrope.

Salivary and pellicle proteome: A datamining analysis

We aimed to comprehensively compare two compartmented oral proteomes, the salivary and the dental pellicle proteome. Systematic review and datamining was used to obtain the physico-chemical, structural, functional and interactional properties of 1,515 salivary and 60 identified pellicle proteins. Salivary and pellicle proteins did not differ significantly in their aliphatic index, hydrophaty, instability index, or isoelectric point. Pellicle proteins were significantly more charged at low and high pH and were significantly smaller (10–20 kDa) than salivary proteins. Protein structure and solvent accessible molecular surface did not differ significantly. Proteins of the pellicle were more phosphorylated and glycosylated than salivary proteins. Ion binding and enzymatic activities also differed significantly. Protein-protein-ligand interaction networks relied on few key proteins. The identified differences between salivary and pellicle proteins could guide proteome compartmentalization and result in specialized functionality. Key proteins could be potential targets for diagnostic or therapeutic application.

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

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

The Chaperone Activity and Substrate Spectrum of Human Small Heat Shock Proteins

Small heat shock proteins (sHsps) are a ubiquitous family of molecular chaperones that suppress the unspecific aggregation of miscellaneous proteins. Multicellular organisms contain a large number of different sHsps, raising questions as to whether they function redundantly or are specialized in terms of substrates and mechanism. To gain insight into this issue, we undertook a comparative analysis of the eight major human sHsps on the aggregation of both model proteins and cytosolic lysates under standardized conditions. We discovered that sHsps, which form large oligomers (HspB1/Hsp27, HspB3, HspB4/αA-crystallin, and HspB5/αB-crystallin) are promiscuous chaperones, whereas the chaperone activity of the other sHsps is more substrate-dependent. However, all human sHsps analyzed except HspB7 suppressed the aggregation of cytosolic proteins of HEK293 cells. We identified ∼1100 heat-sensitive HEK293 proteins, 12% of which could be isolated in complexes with sHsps. Analysis of their biochemical properties revealed that most of the sHsp substrates have a molecular mass from 50 to 100 kDa and a slightly acidic pI (5.4-6.8). The potency of the sHsps to suppress aggregation of model substrates is correlated with their ability to form stable substrate complexes; especially HspB1 and HspB5, but also B3, bind tightly to a variety of proteins, whereas fewer substrates were detected in complex with the other sHsps, although these were also efficient in preventing the aggregation of cytosolic proteins.

Kinase Inhibition Leads to Hormesis in a Dual Phosphorylation-Dephosphorylation Cycle

Many antimicrobial and anti-tumour drugs elicit hormetic responses characterised by low-dose stimulation and high-dose inhibition. While this can have profound consequences for human health, with low drug concentrations actually stimulating pathogen or tumour growth, the mechanistic understanding behind such responses is still lacking. We propose a novel, simple but general mechanism that could give rise to hormesis in systems where an inhibitor acts on an enzyme. At its core is one of the basic building blocks in intracellular signalling, the dual phosphorylation-dephosphorylation motif, found in diverse regulatory processes including control of cell proliferation and programmed cell death. Our analytically-derived conditions for observing hormesis provide clues as to why this mechanism has not been previously identified. Current mathematical models regularly make simplifying assumptions that lack empirical support but inadvertently preclude the observation of hormesis. In addition, due to the inherent population heterogeneities, the presence of hormesis is likely to be masked in empirical population-level studies. Therefore, examining hormetic responses at single-cell level coupled with improved mathematical models could substantially enhance detection and mechanistic understanding of hormesis.

Hormesis is a highly controversial and poorly understood phenomenon. It describes the idea that an inhibitor molecule, like an anti-cancer or anti-microbial drug, can inadvertently stimulate cell growth instead of suppressing it. This can have a profound effect on human health leading to failures in clinical treatments. Therefore, getting at the mechanistic basis of hormesis is critical for drug development and clinical practice, however molecular mechanisms underpinning hormesis remain poorly understood. In this paper we use a mathematical model to propose a simple and yet general mechanism that could explain why we find hormesis so widely in living systems. In particular, we discover that hormesis is present within a fundamental structure that forms a basic building block of many intracellular signalling pathways found in diverse processes including control of cell reproduction and programmed cell death. The benefits of our study are two-fold. Having simple molecular understanding of the causes of hormetic responses can greatly improve the design of new drug compounds that avoid such responses. Moreover, due to the fundamental nature of the newly proposed mechanism, our findings have a potential broad applicability to both anti-cancer and anti-microbial drugs.

Drift Barriers to Quality Control When Genes Are Expressed at Different Levels

Gene expression is imperfect, sometimes leading to toxic products. Solutions take two forms: globally reducing error rates, or ensuring that the consequences of erroneous expression are relatively harmless. The latter is optimal, but because it must evolve independently at so many loci, it is subject to a stringent "drift barrier"-a limit to how weak the effects of a deleterious mutation s can be, while still being effectively purged by selection, expressed in terms of the population size N of an idealized population such that purging requires s < -1/N In previous work, only large populations evolved the optimal local solution, small populations instead evolved globally low error rates, and intermediate populations were bistable, with either solution possible. Here, we take into consideration the fact that the effectiveness of purging varies among loci, because of variation in gene expression level, and variation in the intrinsic vulnerabilities of different gene products to error. The previously found dichotomy between the two kinds of solution breaks down, replaced by a gradual transition as a function of population size. In the extreme case of a small enough population, selection fails to maintain even the global solution against deleterious mutations, explaining the nonmonotonic relationship between effective population size and transcriptional error rate that was recently observed in experiments on Escherichia coli, Caenorhabditis elegans, and Buchnera aphidicola.

cDNA-library testing identifies transforming genes cooperating with c-myc in mouse pre-B cells

While c-myc often contributes to the generation of B cell transformation, its transgenic overexpression alone does not lead to full transformation of B-lineage cells. Synergistically acting second genes must cooperate. Here, we constructed doxycycline-inducible cDNA-libraries from pre-B cell mRNA. These libraries were retrovirally transduced as single copies into single cells and overexpressed in fetal-liver-derived c-myc-overexpressing pre-B cell lines. We scored transformation by survival and/or expansion of differentiating B-lineage cells in vitro and in vivo. Only one double c-myc/cDNA-library-expressing cell line was found in less than 5 × 10⁶ library-transduced pre-B cells surviving and expressing a cDNA-library-derived transcript in vitro. This transcript was identified as a shortened form of the Exosc1 gene, encoding the RNA exosome complex component CSL4. Transplantations of double c-myc/Exosc1 short-form- or c-myc/Exosc1 full-length-transgenic cells into Rag1^-/- mice resulted in survival, differentiation to CD19⁺ CD93^- sIgM⁺ CD5^low/- CD11b⁺ mature B1 cells and, surprisingly, also vigorous expansion in vivo. Strikingly, after transplantations of c-myc/cDNA-library pre-BI cells the frequencies of double-transgenic pre-B cells and their differentiated progeny, expanding in vivo to heterogeneous phenotypes, was at least tenfold higher than in vitro. In a first analysis Ptprcap, Cacybp, Ndufs7, Rpl18a, and Rpl35a were identified. This suggests a strong influence of the host on B-cell transformation.

Genetic Characteristics of Polycythemia Vera and Essential Thrombocythemia in Korean Patients

BACKGROUND

Despite recent advances in the investigation of myeloproliferative neoplasms (MPN), the impact of genetic heterogeneity on its molecular pathogenesis has not been fully elucidated. Thus, in this study, we aim to characterize the genetic complexity in Korean patients with polycythemia vera (PV) and essential thrombocythemia (ET).

METHODS

We conducted association studies using 84 single-nucleotide polymorphisms (SNPs) in 229 patients (96 with PV and 133 with ET) and 170 controls. Further, whole-genome sequencing was performed in six patients (two with JAK2 V617F and four with wild-type JAK2), and putative somatic mutations were validated in a further 69 ET patients. Clinical and laboratory characteristics were also analyzed.

RESULTS

Several germline SNPs and the 46 haplotype were significantly associated with PV and ET. Three somatic mutations in MPDZ, IQCH, and CALR genes were selected and validated. The frequency of the CALR mutation was 58.0% (40/69) in ET patients, who did not carry JAK2/MPL mutations. Moreover, compared with JAK2 V617F-positive patients, those with CALR mutations showed lower hemoglobin and hematocrit levels (P = 0.004 and P = 0.002, respectively), higher platelet counts (P =0.008), and a lower frequency of cytoreductive therapy (P = 0.014).

CONCLUSION

This study was the first comprehensive investigation of the genetic characteristics of Korean patients with PV and ET. We found that somatic mutations and the 46 haplotype contribute to PV and ET pathogenesis in Korean patients.

Protein turnover measurement using selected reaction monitoring-mass spectrometry (SRM-MS)

Protein turnover represents an important mechanism in the functioning of cells, with deregulated synthesis and degradation of proteins implicated in many diseased states. Therefore, proteomics strategies to measure turnover rates with high confidence are of vital importance to understanding many biological processes. In this study, the more widely used approach of non-targeted precursor ion signal intensity (MS1) quantification is compared with selected reaction monitoring (SRM), a data acquisition strategy that records data for specific peptides, to determine if improved quantitative data would be obtained using a targeted quantification approach. Using mouse liver as a model system, turnover measurement of four tricarboxylic acid cycle proteins was performed using both MS1 and SRM quantification strategies. SRM outperformed MS1 in terms of sensitivity and selectivity of measurement, allowing more confident determination of protein turnover rates. SRM data are acquired using cheaper and more widely available tandem quadrupole mass spectrometers, making the approach accessible to a larger number of researchers than MS1 quantification, which is best performed on high mass resolution instruments. SRM acquisition is ideally suited to focused studies where the turnover of tens of proteins is measured, making it applicable in determining the dynamics of proteins complexes and complete metabolic pathways.This article is part of the themed issue 'Quantitative mass spectrometry'.

Nucleosome distortion as a possible mechanism of transcription activation domain function

After more than three decades since the discovery of transcription activation domains (ADs) in gene-specific activators, the mechanism of their function remains enigmatic. The widely accepted model of direct recruitment by ADs of co-activators and basal transcriptional machinery components, however, is not always compatible with the short size yet very high degree of sequence randomness and intrinsic structural disorder of natural and synthetic ADs. In this review, we formulate the basis for an alternative and complementary model, whereby sequence randomness and intrinsic structural disorder of ADs are necessary for transient distorting interactions with promoter nucleosomes, triggering promoter nucleosome translocation and subsequently gene activation.

A Genome-Scale Investigation of How Sequence, Function, and Tree-Based Gene Properties Influence Phylogenetic Inference

Molecular phylogenetic inference is inherently dependent on choices in both methodology and data. Many insightful studies have shown how choices in methodology, such as the model of sequence evolution or optimality criterion used, can strongly influence inference. In contrast, much less is known about the impact of choices in the properties of the data, typically genes, on phylogenetic inference. We investigated the relationships between 52 gene properties (24 sequence-based, 19 function-based, and 9 tree-based) with each other and with three measures of phylogenetic signal in two assembled data sets of 2,832 yeast and 2,002 mammalian genes. We found that most gene properties, such as evolutionary rate (measured through the percent average of pairwise identity across taxa) and total tree length, were highly correlated with each other. Similarly, several gene properties, such as gene alignment length, Guanine-Cytosine content, and the proportion of tree distance on internal branches divided by relative composition variability (treeness/RCV), were strongly correlated with phylogenetic signal. Analysis of partial correlations between gene properties and phylogenetic signal in which gene evolutionary rate and alignment length were simultaneously controlled, showed similar patterns of correlations, albeit weaker in strength. Examination of the relative importance of each gene property on phylogenetic signal identified gene alignment length, alongside with number of parsimony-informative sites and variable sites, as the most important predictors. Interestingly, the subsets of gene properties that optimally predicted phylogenetic signal differed considerably across our three phylogenetic measures and two data sets; however, gene alignment length and RCV were consistently included as predictors of all three phylogenetic measures in both yeasts and mammals. These results suggest that a handful of sequence-based gene properties are reliable predictors of phylogenetic signal and could be useful in guiding the choice of phylogenetic markers.