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Recent experimental studies indicate that mitochondria in mammalian cells are maintained at temperatures of at least 50 °C. While acknowledging the limitations of current experimental methods and their interpretation, we here consider the ramifications of this finding for cellular functions and for evolution. We consider whether mitochondria as heat-producing organelles had a role in the origin of eukaryotes and in the emergence of homeotherms. The homeostatic responses of mitochondrial temperature to externally applied heat imply the existence of a molecular heat-sensing system in mitochondria. While current findings indicate high temperatures for the innermost compartments of mitochondria, those of the mitochondrial surface and of the immediately surrounding cytosol remain to be determined. We ask whether some aspects of mitochondrial dynamics and motility could reflect changes in the supply and demand for mitochondrial heat, and whether mitochondrial heat production could be a factor in diseases and immunity., (© 2024 The Author(s). The FEBS Journal published by John Wiley & Sons Ltd on behalf of Federation of European Biochemical Societies.)

Autotrophy is the basis for complex life on Earth. Central to this process is rubisco-the enzyme that catalyzes almost all carbon fixation on the planet. Yet, with only a small fraction of rubisco diversity kinetically characterized so far, the underlying biological factors driving the evolution of fast rubiscos in nature remain unclear. We conducted a high-throughput kinetic characterization of over 100 bacterial form I rubiscos, the most ubiquitous group of rubisco sequences in nature, to uncover the determinants of rubisco's carboxylation velocity. We show that the presence of a carboxysome CO 2 concentrating mechanism correlates with faster rubiscos with a median fivefold higher rate. In contrast to prior studies, we find that rubiscos originating from α-cyanobacteria exhibit the highest carboxylation rates among form I enzymes (≈10 s -1 median versus <7 s -1 in other groups). Our study systematically reveals biological and environmental properties associated with kinetic variation across rubiscos from nature., (© 2024. The Author(s).)

Importance: Optimal quarantine length for COVID-19 infection is unclear, in part owing to limited empirical data., Objective: To assess postquarantine transmission risk for various quarantine lengths and potential associations between quarantine strictness and transmission risk., Design, Setting, and Participants: Retrospective cohort study in 4 US universities from September 2020 to February 2021, including 3641 university students and staff who were identified as close contacts to individuals who tested positive for SARS-CoV-2 infection. Individuals were tested throughout the 10 to 14-day quarantine, and follow-up testing continued at least weekly throughout the 2020-2021 academic year., Exposures: Strict quarantine, including designated housing with a private room, private bathroom, and meal delivery, vs nonstrict, which potentially included interactions with household members., Main Outcomes and Measures: Dates of last known exposure, last negative test result, and first positive test result during quarantine., Results: This study included 301 quarantined university students and staff who tested SARS-CoV-2-positive (of 3641 quarantined total). These 301 individuals had a median (IQR) age of 22.0 (20.0-25.0) years; 131 (43.5%) identified as female; and 20 (6.6%) were staff. Of the 287 self-reporting race and ethnicity according to university-defined classifications, 21 (7.3%) were African American or Black, 60 (20.9%) Asian, 17 (5.9%) Hispanic or Latinx, 174 (60.6%) White, and 15 (5.2%) other (including multiracial and/or multiethnic). Of the 301 participants, 40 (13.3%; 95% CI, 9.9%-17.6%) had negative test results and were asymptomatic on day 7 compared with 15 (4.9%; 95% CI, 3.0%-8.1%) and 4 (1.4%; 95% CI, 0.4%-3.5%) on days 10 and 14, respectively. Individuals in strict quarantine tested positive less frequently than those in nonstrict quarantine (10% vs 12%; P = .04)., Conclusions and Relevance: To maintain the 5% transmission risk used as the basis for US Centers for Disease Control and Prevention's 7-day test-based quarantine guidance, our data suggest that quarantine with quantitative polymerase chain reaction testing 1 day before intended release should be 10 days for nonstrict quarantine and 8 days for strict quarantine, as ongoing exposure during quarantine may be associated with the higher rate of positive test results following nonstrict quarantine.

Asymptomatic surveillance testing together with COVID-19-related research can lead to positive SARS-CoV-2 tests resulting not from true infections, but non-infectious, non-hazardous by-products of research (amplicons). Amplicons can be widespread and persistent in lab environments and can be difficult to distinguish for true infections. We discuss prevention and mitigation strategies., (© 2021 The Authors.)

α-Synuclein (α-Syn) is a protein implicated in the pathogenesis of Parkinson's disease (PD). It is an intrinsically disordered protein that binds acidic phospholipids. Growing evidence supports a role for α-Syn in membrane trafficking, including, mechanisms of endocytosis and exocytosis, although the exact role of α-Syn in these mechanisms is currently unclear. Here we investigate the associations of α-Syn with the acidic phosphoinositides (PIPs), phosphatidylinositol 4,5-bisphosphate (PI(4,5)P 2 ) and phosphatidylinositol 3,4-bisphosphate (PI(3,4)P 2 ). Our results show that α-Syn colocalizes with PIP 2 and the phosphorylated active form of the clathrin adaptor protein 2 (AP2) at clathrin-coated pits. Using endocytosis of transferrin as an indicator for clathrin-mediated endocytosis (CME), we find that α-Syn involvement in endocytosis is specifically mediated through PI(4,5)P 2 levels on the plasma membrane. In accord with their effects on PI(4,5)P 2 levels, the PD associated A30P, E46K, and A53T mutations in α-Syn further enhance CME in neuronal and nonneuronal cells. However, lysine to glutamic acid substitutions at the KTKEGV repeat domain of α-Syn, which interfere with phospholipid binding, are ineffective in enhancing CME. We further show that the rate of synaptic vesicle (SV) endocytosis is differentially affected by the α-Syn mutations and associates with their effects on PI(4,5)P 2 levels, however, with the exception of the A30P mutation. This study provides evidence for a critical involvement of PIPs in α-Syn-mediated membrane trafficking., Competing Interests: Conflict of interest—The authors declare that they have no conflict of interest with the contents of this article., (© 2020 Schechter et al.)

CO 2 is converted into biomass almost solely by the enzyme rubisco. The poor carboxylation properties of plant rubiscos have led to efforts that made it the most kinetically characterized enzyme, yet these studies focused on < 5% of its natural diversity. Here, we searched for fast-carboxylating variants by systematically mining genomic and metagenomic data. Approximately 33,000 unique rubisco sequences were identified and clustered into ≈ 1,000 similarity groups. We then synthesized, purified, and biochemically tested the carboxylation rates of 143 representatives, spanning all clusters of form-II and form-II/III rubiscos. Most variants (> 100) were active in vitro, with the fastest having a turnover number of 22 ± 1 s -1 -sixfold faster than the median plant rubisco and nearly twofold faster than the fastest measured rubisco to date. Unlike rubiscos from plants and cyanobacteria, the fastest variants discovered here are homodimers and exhibit a much simpler folding and activation kinetics. Our pipeline can be utilized to explore the kinetic space of other enzymes of interest, allowing us to get a better view of the biosynthetic potential of the biosphere., (©2020 The Authors. Published under the terms of the CC BY 4.0 license.)

α-Synuclein (α-Syn) protein is implicated in the pathogenesis of Parkinson disease (PD). It is primarily cytosolic and interacts with cell membranes. α-Syn also occurs in the nucleus. Here we investigated the mechanisms involved in nuclear translocation of α-Syn. We analyzed alterations in gene expression following induced α-Syn expression in SH-SY5Y cells. Analysis of upstream regulators pointed at alterations in transcription activity of retinoic acid receptors (RARs) and additional nuclear receptors. We show that α-Syn binds RA and translocates to the nucleus to selectively enhance gene transcription. Nuclear translocation of α-Syn is regulated by calreticulin and is leptomycin-B independent. Importantly, nuclear translocation of α-Syn following RA treatment enhances its toxicity in cultured neurons and the expression levels of PD-associated genes, including ATPase cation transporting 13A2 (ATP13A2) and PTEN-induced kinase1 (PINK1). The results link a physiological role for α-Syn in the regulation of RA-mediated gene transcription and its toxicity in the synucleinopathies., Competing Interests: Declaration of Interests The authors declare that they have no competing interests., (Copyright © 2020 The Author(s). Published by Elsevier Inc. All rights reserved.)

Rubisco is the primary carboxylase of the Calvin cycle, the most abundant enzyme in the biosphere, and one of the best-characterized enzymes. On the basis of correlations between Rubisco kinetic parameters, it is widely posited that constraints embedded in the catalytic mechanism enforce trade-offs between CO 2 specificity, S C/O , and maximum carboxylation rate, k cat,C . However, the reasoning that established this view was based on data from ≈20 organisms. Here, we re-examine models of trade-offs in Rubisco catalysis using a data set from ≈300 organisms. Correlations between kinetic parameters are substantially attenuated in this larger data set, with the inverse relationship between k cat,C and S C/O being a key example. Nonetheless, measured kinetic parameters display extremely limited variation, consistent with a view of Rubisco as a highly constrained enzyme. More than 95% of k cat,C values are between 1 and 10 s -1 , and no measured k cat,C exceeds 15 s -1 . Similarly, S C/O varies by only 30% among Form I Rubiscos and <10% among C 3 plant enzymes. Limited variation in S C/O forces a strong positive correlation between the catalytic efficiencies ( k cat / K M ) for carboxylation and oxygenation, consistent with a model of Rubisco catalysis in which increasing the rate of addition of CO 2 to the enzyme-substrate complex requires an equal increase in the O 2 addition rate. Altogether, these data suggest that Rubisco evolution is tightly constrained by the physicochemical limits of CO 2 /O 2 discrimination.

How does environmental complexity affect the evolution of single genes? Here, we measured the effects of a set of Bacillus subtilis glutamate dehydrogenase mutants across 19 different environments-from phenotypically homogeneous single-cell populations in liquid media to heterogeneous biofilms, plant roots and soil populations. The effects of individual gene mutations on organismal fitness were highly reproducible in liquid cultures. However, 84% of the tested alleles showed opposing fitness effects under different growth conditions (sign environmental pleiotropy). In colony biofilms and soil samples, different alleles dominated in parallel replica experiments. Accordingly, we found that in these heterogeneous cell populations the fate of mutations was dictated by a combination of selection and drift. The latter relates to programmed prophage excisions that occurred during biofilm development. Overall, for each condition, a wide range of glutamate dehydrogenase mutations persisted and sometimes fixated as a result of the combined action of selection, pleiotropy and chance. However, over longer periods and in multiple environments, nearly all of this diversity would be lost-across all the environments and conditions that we tested, the wild type was the fittest allele.

Background: Controlled glycemic concentrations are associated with a lower risk of conditions such as cardiovascular disease and diabetes. Models commonly used to guide interventions to control the glycemic response to food have low efficacy, with recent clinical guidelines arguing for the use of personalized approaches., Objective: We tested the efficacy of a predictive model of personalized postprandial glycemic response to foods that was developed with an Israeli cohort and that takes into consideration food components and specific features, including the microbiome, when applied to individuals from the Midwestern US., Design: We recruited 327 individuals for this study. Participants provided information regarding lifestyle, dietary habits, and health, as well as a stool sample for characterization of their gut microbiome. Participants were connected to continuous glucose monitors for 6 d, and the glycemic response to meals logged during this time was computed. The ability of a model trained using meals logged by the Israeli cohort to correctly predict glycemic responses in the Midwestern cohort was assessed and compared with that of a model trained using meals logged by both cohorts., Results: When trained on the Israeli cohort meals only, model performance for predicting responses of individuals in the Midwestern cohort was better (R = 0.596) than that observed for models taking into consideration the carbohydrate (R = 0.395) or calorie content of the meals alone (R = 0.336). Performance increased (R = 0.618) when the model was trained on meals from both cohorts, likely because of the observed differences in age distribution, diet, and microbiome., Conclusions: We show that the modeling framework described in Zeevi et al. for an Israeli cohort is applicable to a Midwestern population, and outperforms commonly used approaches for the control of blood glucose responses. The adaptation of the model to the Midwestern cohort further enhances performance and is a promising means for designing effective nutritional interventions to control glycemic responses to foods. This trial was registered at clinicaltrials.gov as NCT02945514., (Copyright © American Society for Nutrition 2019.)

Importance: Emerging evidence suggests that postprandial glycemic responses (PPGRs) to food may be influenced by and predicted according to characteristics unique to each individual, including anthropometric and microbiome variables. Interindividual diversity in PPGRs to food requires a personalized approach for the maintenance of healthy glycemic levels., Objectives: To describe and predict the glycemic responses of individuals to a diverse array of foods using a model that considers the physiology and microbiome of the individual in addition to the characteristics of the foods consumed., Design, Setting, and Participants: This cohort study using a personalized predictive model enrolled 327 individuals without diabetes from October 11, 2016, to December 13, 2017, in Minnesota and Florida to be part of a study lasting 6 days. The study measured anthropometric variables, described the gut microbial composition, and assessed blood glucose levels every 5 minutes using a continuous glucose monitor. Participants logged their food and activity information for the duration of the study. A predictive model of individualized PPGRs to a diverse array of foods was trained and applied., Main Outcomes and Measures: Glycemic responses to food consumed over 6 days for each participant. The predictive model of personalized PPGRs considered individual features, including the microbiome, in addition to the features of the foods consumed., Results: Postprandial response to the same foods varied across 327 individuals (mean [SD] age, 45 [12] years; 78.0% female). A model predicting each individual's responses to food that considers several individual factors in addition to food features had better overall performance (R = 0.62) than current standard-of-care approaches using nutritional content alone (R = 0.34 for calories and R = 0.40 for carbohydrates) to control postprandial glycemic levels., Conclusions and Relevance: Across the cohort of adults without diabetes who were examined, a personalized predictive model that considers unique features of the individual, such as clinical characteristics, physiological variables, and the microbiome, in addition to nutrient content was more predictive than current dietary approaches that focus only on the calorie or carbohydrate content of foods. Providing individuals with tools to manage their glycemic responses to food based on personalized predictions of their PPGRs may allow them to maintain their blood glucose levels within limits associated with good health.

While protein tags are ubiquitously utilized in molecular biology, they harbor the potential to interfere with functional traits of their fusion counterparts. Systematic evaluation of the effect of protein tags on function would promote accurate use of tags in experimental setups. Here we examine the effect of green fluorescent protein tagging at either the N or C terminus of budding yeast proteins on subcellular localization and functionality. We use a competition-based approach to decipher the relative fitness of two strains tagged on the same protein but on opposite termini and from that infer the correct, physiological localization for each protein and the optimal position for tagging. Our study provides a first of a kind systematic assessment of the effect of tags on the functionality of proteins and provides a step toward broad investigation of protein fusion libraries., (Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Background: Low blood ALT, Alanine aminotransferase activity and high FRAIL (Fatigue, Resistance, Ambulation, Illnesses and Loss of Weight) questionnaire scores were previously shown to be associated with frailty and increased risk of mortality. We aimed to correlate these tools with mortality and each other in patients hospitalized in an internal medicine department., Methods: This is a prospective study in a large tertiary hospital. We assessed the predictive value for clinical outcomes of both low ALT blood activity and the pre-frail and frail categories of the "FRAIL" questionnaire., Results: During a 15 months study, 179 consecutive patients were recruited, of whom 20 died. When all study participants were divided to three groups according to admission ALT levels (below 10 IU/L, 11 to 19 IU/L and above 20 IU/L) we found a statistically significant difference in the rate of mortality: 4 patients died within the group of ALT < 10 IU/L, 14 patients died in the group of 10 IU/L < ALT < 19 IU/L and in the group of patients with ALT > 20 IU/L, only 2 patients died ( p = 0.042). A higher score on the FRAIL questionnaire was associated, with statistical significance, with higher risk of mortality ( p = 0.029). There was a significant correlation ( p = 0.038) between blood ALT activity and the pre-frailty and frailty classifications by the FRAIL Questionnaire., Conclusions: Both the FRAIL questionnaire and blood ALT activity are simple and practical tools for frailty assessment and risk stratification of patients hospitalized in the internal medicine department. Both tool's results also correlate with each other.

Enzymes catalyze a vast range of reactions. Their catalytic performances, mechanisms, global folds, and active-site architectures are also highly diverse, suggesting that enzymes are shaped by an entire range of physiological demands and evolutionary constraints, as well as by chemical and physicochemical constraints. We have attempted to identify signatures of these shaping demands and constraints. To this end, we describe a bird's-eye view of the enzyme space from two angles: evolution and chemistry. We examine various chemical reaction parameters that may have shaped the catalytic performances and active-site architectures of enzymes. We test and weigh these considerations against physiological and evolutionary factors. Although the catalytic properties of the "average" enzyme correlate with cellular metabolic demands and enzyme expression levels, at the level of individual enzymes, a multitude of physiological demands and constraints, combined with the coincidental nature of evolutionary processes, result in a complex picture. Indeed, neither reaction type (a chemical constraint) nor evolutionary origin alone can explain enzyme rates. Nevertheless, chemical constraints are apparent in the convergence of active-site architectures in independently evolved enzymes, although significant variations within an architecture are common.

Yeast libraries revolutionized the systematic study of cell biology. To extensively increase the number of such libraries, we used our previously devised SWAp-Tag (SWAT) approach to construct a genome-wide library of ~5,500 strains carrying the SWAT NOP1promoter-GFP module at the N terminus of proteins. In addition, we created six diverse libraries that restored the native regulation, created an overexpression library with a Cherry tag, or enabled protein complementation assays from two fragments of an enzyme or fluorophore. We developed methods utilizing these SWAT collections to systematically characterize the yeast proteome for protein abundance, localization, topology, and interactions.

Understanding the evolution of a new metabolic capability in full mechanistic detail is challenging, as causative mutations may be masked by non-essential "hitchhiking" mutations accumulated during the evolutionary trajectory. We have previously used adaptive laboratory evolution of a rationally engineered ancestor to generate an Escherichia coli strain able to utilize CO 2 fixation for sugar synthesis. Here, we reveal the genetic basis underlying this metabolic transition. Five mutations are sufficient to enable robust growth when a non-native Calvin-Benson-Bassham cycle provides all the sugar-derived metabolic building blocks. These mutations are found either in enzymes that affect the efflux of intermediates from the autocatalytic CO 2 fixation cycle toward biomass (prs, serA, and pgi), or in key regulators of carbon metabolism (crp and ppsR). Using suppressor analysis, we show that a decrease in catalytic capacity is a common feature of all mutations found in enzymes. These findings highlight the enzymatic constraints that are essential to the metabolic stability of autocatalytic cycles and are relevant to future efforts in constructing non-native carbon fixation pathways.

Enzyme kinetics are fundamental to an understanding of cellular metabolism and for crafting synthetic biology applications. For decades, enzyme characterization has been based on in vitro enzyme assays. However, kinetic parameters are only available for <10% of reactions, and this data scarcity limits the predictive power of metabolic models. Here we review recent studies that leverage quantitative proteomics to gain insight into in vivo enzyme kinetics. We discuss findings on the relationship between in vivo and in vitro enzyme catalysis and show how proteomics can be used to characterize the efficiency of enzyme utilization across conditions. Lastly, the efficient use of enzymes is shown to rationalize preference for low energy-yield metabolic strategies, such as aerobic fermentation at high growth rate., (Copyright © 2017 Elsevier Ltd. All rights reserved.)

α-Synuclein is a protein involved in the pathogenesis of synucleinopathies, including Parkinson's disease (PD), dementia with Lewy bodies (DLB) and multiple system atrophy (MSA). We investigated the role of neuronal α-Syn in myelin composition and abnormalities. The phospholipid content of purified myelin was determined by 31 P NMR in two mouse lines modeling PD, PrP-A53T α-Syn and Thy-1 wt-α-Syn. Significantly higher levels of phospholipids were detected in myelin purified from brains of these α-Syn transgenic mouse models than in control mice. Nevertheless, myelin ultrastructure appeared intact. To further investigate the effect of α-Syn on myelin abnormalities, we systematically analyzed the striatum, a brain region associated with neurodegeneration in PD. An age and disease-dependent loss of myelin basic protein (MBP) signal was detected by immunohistochemistry in striatal striosomes (patches). The age-dependent loss of MBP signal was associated with lower P25α levels in oligodendrocytes. In addition, we found that α-Syn inhibited oligodendrocyte maturation and the formation of membranous sheets in vitro. Based on these results we concluded that neuronal α-Syn is involved in the regulation and/or maintenance of myelin phospholipid. However, axonal hypomyelination in the PD models is evident only in progressive stages of the disease and associated with α-Syn toxicity.

A set of chemical reactions that require a metabolite to synthesize more of that metabolite is an autocatalytic cycle. Here, we show that most of the reactions in the core of central carbon metabolism are part of compact autocatalytic cycles. Such metabolic designs must meet specific conditions to support stable fluxes, hence avoiding depletion of intermediate metabolites. As such, they are subjected to constraints that may seem counter-intuitive: the enzymes of branch reactions out of the cycle must be overexpressed and the affinity of these enzymes to their substrates must be relatively weak. We use recent quantitative proteomics and fluxomics measurements to show that the above conditions hold for functioning cycles in central carbon metabolism of E. coli . This work demonstrates that the topology of a metabolic network can shape kinetic parameters of enzymes and lead to seemingly wasteful enzyme usage.

Bacterial growth depends crucially on metabolic fluxes, which are limited by the cell's capacity to maintain metabolic enzymes. The necessary enzyme amount per unit flux is a major determinant of metabolic strategies both in evolution and bioengineering. It depends on enzyme parameters (such as kcat and KM constants), but also on metabolite concentrations. Moreover, similar amounts of different enzymes might incur different costs for the cell, depending on enzyme-specific properties such as protein size and half-life. Here, we developed enzyme cost minimization (ECM), a scalable method for computing enzyme amounts that support a given metabolic flux at a minimal protein cost. The complex interplay of enzyme and metabolite concentrations, e.g. through thermodynamic driving forces and enzyme saturation, would make it hard to solve this optimization problem directly. By treating enzyme cost as a function of metabolite levels, we formulated ECM as a numerically tractable, convex optimization problem. Its tiered approach allows for building models at different levels of detail, depending on the amount of available data. Validating our method with measured metabolite and protein levels in E. coli central metabolism, we found typical prediction fold errors of 4.1 and 2.6, respectively, for the two kinds of data. This result from the cost-optimized metabolic state is significantly better than randomly sampled metabolite profiles, supporting the hypothesis that enzyme cost is important for the fitness of E. coli. ECM can be used to predict enzyme levels and protein cost in natural and engineered pathways, and could be a valuable computational tool to assist metabolic engineering projects. Furthermore, it establishes a direct connection between protein cost and thermodynamics, and provides a physically plausible and computationally tractable way to include enzyme kinetics into constraint-based metabolic models, where kinetics have usually been ignored or oversimplified., Competing Interests: The authors have declared that no competing interests exist.

Can a heterotrophic organism be evolved to synthesize biomass from CO2 directly? So far, non-native carbon fixation in which biomass precursors are synthesized solely from CO2 has remained an elusive grand challenge. Here, we demonstrate how a combination of rational metabolic rewiring, recombinant expression, and laboratory evolution has led to the biosynthesis of sugars and other major biomass constituents by a fully functional Calvin-Benson-Bassham (CBB) cycle in E. coli. In the evolved bacteria, carbon fixation is performed via a non-native CBB cycle, while reducing power and energy are obtained by oxidizing a supplied organic compound (e.g., pyruvate). Genome sequencing reveals that mutations in flux branchpoints, connecting the non-native CBB cycle to biosynthetic pathways, are essential for this phenotype. The successful evolution of a non-native carbon fixation pathway, though not yet resulting in net carbon gain, strikingly demonstrates the capacity for rapid trophic-mode evolution of metabolism applicable to biotechnology. PAPERCLIP., (Copyright © 2016 The Author(s). Published by Elsevier Inc. All rights reserved.)

Turnover numbers, also known as kcat values, are fundamental properties of enzymes. However, kcat data are scarce and measured in vitro, thus may not faithfully represent the in vivo situation. A basic question that awaits elucidation is: how representative are kcat values for the maximal catalytic rates of enzymes in vivo? Here, we harness omics data to calculate kmax(vivo), the observed maximal catalytic rate of an enzyme inside cells. Comparison with kcat values from Escherichia coli, yields a correlation ofr(2)= 0.62 in log scale (p < 10(-10)), with a root mean square difference of 0.54 (3.5-fold in linear scale), indicating that in vivo and in vitro maximal rates generally concur. By accounting for the degree of saturation of enzymes and the backward flux dictated by thermodynamics, we further refine the correspondence between kmax(vivo) and kcat values. The approach we present here characterizes the quantitative relationship between enzymatic catalysis in vitro and in vivo and offers a high-throughput method for extracting enzyme kinetic constants from omics data.

Genetically identical cells exposed to the same environment display variability in gene expression (noise), with important consequences for the fidelity of cellular regulation and biological function. Although population average gene expression is tightly coupled to growth rate, the effects of changes in environmental conditions on expression variability are not known. Here, we measure the single-cell expression distributions of approximately 900 Saccharomyces cerevisiae promoters across four environmental conditions using flow cytometry, and find that gene expression noise is tightly coupled to the environment and is generally higher at lower growth rates. Nutrient-poor conditions, which support lower growth rates, display elevated levels of noise for most promoters, regardless of their specific expression values. We present a simple model of noise in expression that results from having an asynchronous population, with cells at different cell-cycle stages, and with different partitioning of the cells between the stages at different growth rates. This model predicts non-monotonic global changes in noise at different growth rates as well as overall higher variability in expression for cell-cycle-regulated genes in all conditions. The consistency between this model and our data, as well as with noise measurements of cells growing in a chemostat at well-defined growth rates, suggests that cell-cycle heterogeneity is a major contributor to gene expression noise. Finally, we identify gene and promoter features that play a role in gene expression noise across conditions. Our results show the existence of growth-related global changes in gene expression noise and suggest their potential phenotypic implications., (© 2015 Keren et al.; Published by Cold Spring Harbor Laboratory Press.)

Proteomics techniques generate an avalanche of data and promise to satisfy biologists' long-held desire to measure absolute protein abundances on a genome-wide scale. However, can this knowledge be translated into a clearer picture of how cells invest their protein resources? This article aims to give a broad perspective on the composition of proteomes as gleaned from recent quantitative proteomics studies. We describe proteomaps, an approach for visualizing the composition of proteomes with a focus on protein abundances and functions. In proteomaps, each protein is shown as a polygon-shaped tile, with an area representing protein abundance. Functionally related proteins appear in adjacent regions. General trends in proteomes, such as the dominance of metabolism and protein production, become easily visible. We make interactive visualizations of published proteome datasets accessible at www.proteomaps.net. We suggest that evaluating the way protein resources are allocated by various organisms and cell types in different conditions will sharpen our understanding of how and why cells regulate the composition of their proteomes.

Plaque analysis allows the determination of phage titer and multiplicity of infection. Yet, this overnight assay provides only endpoint results, ignoring kinetic aspects. We introduce an alternative high-throughput and rapid method for kinetic analysis of lytic coliphage activity. Escherichia coli was infected with serial dilutions of MS2 coliphage, and bacterial growth was monitored using a multi-well plate reader providing within hours the equivalent data as obtained overnight. Additional information is yielded, including phage replication rate, progeny size per cycle, and viral propagation during bacterial growth. This method offers further insights into physicochemical mechanisms of lytic coliphage infection and temporal control. It also provides a virus-host interaction acumen., (Copyright © 2013 Elsevier Inc. All rights reserved.)

Background: The oligomeriztion of α-synuclein (α-syn) into ordered assemblies is associated with the symptoms of Parkinson's Disease (PD). Yet, it is still debatable whether oligomers are formed as part of a multistep process towards amyloid fibril formation or alternatively as "off-pathway" aggregates., Methods: 100μM α-syn was incubated with decreasing amounts of cinnamon extract precipitation (CEppt). The fibril formation was measured using spectroscopy and microscopy analyses and oligomers were detected using western blot analysis. The secondary structure of the protein was analyzed using CD. Drosophila brains were studied using immunostaining and confocal microscopy., Results: Here we probed the inhibition pattern of oligomeric and fibrillar forms of α-syn, using a natural substance, CEppt which was previously shown to effectively inhibit aggregation of β-amyloid polypeptide. We demonstrated that CEppt has a differential inhibitory effect on the formation of soluble and insoluble aggregates of α-synuclein in vitro. This inhibition pattern revokes the possibility of redirection to "off-pathway" oligomers. When administering to Drosophila fly model expressing mutant A53T α-syn in the nervous system, a significant curative effect on the behavioral symptoms of the flies and on α-syn aggregation in their brain was observed., Conclusions: We conclude that CEppt affects the process of aggregation of α-syn without changing its secondary structure and suggest that increasing amounts of CEppt slow this process by stabilizing the soluble oligomeric phase. When administered to Drosophila fly model, CEppt appears to have a curative effect on the defective flies., General Significance: Our results indicate that CEppt can be a potential therapeutic agent for PD., (Copyright © 2012 Elsevier B.V. All rights reserved.)

Motivation: The laws of thermodynamics describe a direct, quantitative relationship between metabolite concentrations and reaction directionality. Despite great efforts, thermodynamic data suffer from limited coverage, scattered accessibility and non-standard annotations. We present a framework for unifying thermodynamic data from multiple sources and demonstrate two new techniques for extrapolating the Gibbs energies of unmeasured reactions and conditions., Results: Both methods account for changes in cellular conditions (pH, ionic strength, etc.) by using linear regression over the ΔG(○) of pseudoisomers and reactions. The Pseudoisomeric Reactant Contribution method systematically infers compound formation energies using measured K' and pK(a) data. The Pseudoisomeric Group Contribution method extends the group contribution method and achieves a high coverage of unmeasured reactions. We define a continuous index that predicts the reversibility of a reaction under a given physiological concentration range. In the characteristic physiological range 3μM-3mM, we find that roughly half of the reactions in Escherichia coli's metabolism are reversible. These new tools can increase the accuracy of thermodynamic-based models, especially in non-standard pH and ionic strengths. The reversibility index can help modelers decide which reactions are reversible in physiological conditions., Availability: Freely available on the web at: http://equilibrator.weizmann.ac.il. Website implemented in Python, MySQL, Apache and Django, with all major browsers supported. The framework is open-source (code.google.com/p/milo-lab), implemented in pure Python and tested mainly on Linux., Contact: ron.milo@weizmann.ac.il, Supplementary Information: Supplementary data are available at Bioinformatics online.

Parkinson's disease is a common neurodegenerative disorder with the pathology of α-synuclein aggregation in Lewy bodies. Currently, there is no available therapy that arrests the progression of the disease. Therefore, the need of animal models to follow α-synuclein aggregation is crucial. Drosophila melanogaster has been researched extensively as a good genetic model for the disease, with a cognitive phenotype of defective climbing ability. The assay for climbing ability has been demonstrated as an effective tool for screening new therapeutic agents for Parkinson's disease. However, due to the assay's many limitations, there is a clear need to develop a better behavioral test. Courtship, a stereotyped, ritualized behavior of Drosophila, involves complex motor and sensory functions in both sexes, which are controlled by large number of neurons; hence, behavior observed during courtship should be sensitive to disease processes in the nervous system. We used a series of traits commonly observed in courtship and an additional behavioral trait-nonsexual encounters-and analyzed them using a data mining tool. We found defective behavior of the Parkinson's model male flies that were tested with virgin females, visible at a much younger age than the climbing defects. We conclude that this is an improved behavioral assay for Parkinson's model flies.

The kinetic parameters of enzymes are key to understanding the rate and specificity of most biological processes. Although specific trends are frequently studied for individual enzymes, global trends are rarely addressed. We performed an analysis of k(cat) and K(M) values of several thousand enzymes collected from the literature. We found that the "average enzyme" exhibits a k(cat) of ~0 s(-1) and a k(cat)/K(M) of ~10(5) s(-1) M(-1), much below the diffusion limit and the characteristic textbook portrayal of kinetically superior enzymes. Why do most enzymes exhibit moderate catalytic efficiencies? Maximal rates may not evolve in cases where weaker selection pressures are expected. We find, for example, that enzymes operating in secondary metabolism are, on average, ~30-fold slower than those of central metabolism. We also find indications that the physicochemical properties of substrates affect the kinetic parameters. Specifically, low molecular mass and hydrophobicity appear to limit K(M) optimization. In accordance, substitution with phosphate, CoA, or other large modifiers considerably lowers the K(M) values of enzymes utilizing the substituted substrates. It therefore appears that both evolutionary selection pressures and physicochemical constraints shape the kinetic parameters of enzymes. It also seems likely that the catalytic efficiency of some enzymes toward their natural substrates could be increased in many cases by natural or laboratory evolution.

Background: Asthma is the most common chronic disease amongst children., Objective: To find the prevalence of positive allergy skin tests amongst children having asthma attending the asthma clinic in Barzilai Medical Center in Ashkelon Israel., Study Design: Retrospective study. All medical files of the asthmatic children attending the asthma clinic in Barzilai Medical Center in Ashkelon, Israel, were reviewed. Data regarding their clinical status, past medical history, socioeconomic and familial medical history were collected., Results: One thousand three hundred and fifty three medical files including all the information necessary for the study were reviewed. Amongst the children 1,238 lived in urban areas and towns and 115 lived in rural areas. It was found that most of the children have positive allergy skin tests for house dust mite and mold. Among the urban children 86.2% were found to have positive allergy skin tests for house dust mite compared with 48% of the rural children (P < 0.02). Positive allergy skin tests for mold were found among 63.1% of the urban children compared with 44% of the rural children (p < 0.04). Positive allergy skin tests for most allergens were found to be more prevalent amongst the children living in urban areas compared with the children living in rural areas. The positive allergy skin tess are not related to parental smoking habits or house pets amongst these findings., Conclusion: Most of the children living in the Ashkelon region and positive allergy skin tests for house dust mite. This tendency is more common among the children living in urban areas as compared with children living in rural areas. The reason for this difference has to be studied.