Stochastic scanning events on the GCN4 mRNA 5' untranslated region generate cell-to-cell heterogeneity in the yeast nutritional stress response.

Gene expression stochasticity is inherent in the functional properties and evolution of biological systems, creating non-genetic cellular individuality and influencing multiple processes, including differentiation and stress responses. In a distinct form of non-transcriptional noise, we find that interactions of the yeast translation machinery with the GCN4 mRNA 5'UTR, which underpins starvation-induced regulation of this transcriptional activator gene, manifest stochastic variation across cellular populations. We use flow cytometry, fluorescence-activated cell sorting and microfluidics coupled to fluorescence microscopy to characterize the cell-to-cell heterogeneity of GCN4-5'UTR-mediated translation initiation. GCN4-5'UTR-mediated translation is generally not de-repressed under non-starvation conditions; however, a sub-population of cells consistently manifests a stochastically enhanced GCN4 translation (SETGCN4) state that depends on the integrity of the GCN4 uORFs. This sub-population is eliminated upon deletion of the Gcn2 kinase that phosphorylates eIF2α under nutrient-limitation conditions, or upon mutation to Ala of the Gcn2 kinase target site, eIF2α-Ser51. SETGCN4 cells isolated using cell sorting spontaneously regenerate the full bimodal population distribution upon further growth. Analysis of ADE8::ymRuby3/ GCN4::yEGFP cells reveals enhanced Gcn4-activated biosynthetic pathway activity in SETGCN4 cells under non-starvation conditions. Computational modeling interprets our experimental observations in terms of a novel translational noise mechanism underpinned by natural variations in Gcn2 kinase activity.

Covariance-based vs. correlation-based functional connectivity dissociates healthy aging from Alzheimer disease.

Prior studies of aging and Alzheimer disease have evaluated resting state functional connectivity (FC) using either seed-based correlation (SBC) or independent component analysis (ICA), with a focus on particular functional systems. SBC and ICA both are insensitive to differences in signal amplitude. At the same time, accumulating evidence indicates that the amplitude of spontaneous BOLD signal fluctuations is physiologically meaningful. We systematically compared covariance-based FC, which is sensitive to amplitude, vs. correlation-based FC, which is not, in affected individuals and controls drawn from two cohorts of participants including autosomal dominant Alzheimer disease (ADAD), late onset Alzheimer disease (LOAD), and age-matched controls. Functional connectivity was computed over 222 regions of interest and group differences were evaluated in terms of components projected onto a space of lower dimension. Our principal observations are: (1) Aging is associated with global loss of resting state fMRI signal amplitude that is approximately uniform across resting state networks. (2) Thus, covariance FC measures decrease with age whereas correlation FC is relatively preserved in healthy aging. (3) In contrast, symptomatic ADAD and LOAD both lead to loss of spontaneous activity amplitude as well as severely degraded correlation structure. These results demonstrate a double dissociation between age vs. Alzheimer disease and the amplitude vs. correlation structure of resting state BOLD signals. Modeling results suggest that the AD-associated loss of correlation structure is attributable to a relative increase in the fraction of locally restricted as opposed to widely shared variance.

The Leishmania PABP1-eIF4E4 interface: a novel 5'-3' interaction architecture for trans-spliced mRNAs.

Trans-splicing of trypanosomatid polycistronic transcripts produces polyadenylated monocistronic mRNAs modified to form the 5' cap4 structure (m7Gpppm36,6,2'Apm2'Apm2'Cpm23,2'U). NMR and X-ray crystallography reveal that Leishmania has a unique type of N-terminally-extended cap-binding protein (eIF4E4) that binds via a PAM2 motif to PABP1. This relies on the interactions of a combination of polar and charged amino acid side-chains together with multiple hydrophobic interactions, and underpins a novel architecture in the Leishmania cap4-binding translation factor complex. Measurements using microscale thermophoresis, fluorescence anisotropy and surface plasmon resonance characterize the key interactions driving assembly of the Leishmania translation initiation complex. We demonstrate that this complex can accommodate Leishmania eIF4G3 which, unlike the standard eukaryotic initiation complex paradigm, binds tightly to eIF4E4, but not to PABP1. Thus, in Leishmania, the chain of interactions 5'cap4-eIF4E4-PABP1-poly(A) bridges the mRNA 5' and 3' ends. Exceptionally, therefore, by binding tightly to two protein ligands and to the mRNA 5' cap4 structure, the trypanosomatid N-terminally extended form of eIF4E acts as the core molecular scaffold for the mRNA-cap-binding complex. Finally, the eIF4E4 N-terminal extension is an intrinsically disordered region that transitions to a partly folded form upon binding to PABP1, whereby this interaction is not modulated by poly(A) binding to PABP1.

Translation initiation events on structured eukaryotic mRNAs generate gene expression noise.

Gene expression stochasticity plays a major role in biology, creating non-genetic cellular individuality and influencing multiple processes, including differentiation and stress responses. We have addressed the lack of knowledge about posttranscriptional contributions to noise by determining cell-to-cell variations in the abundance of mRNA and reporter protein in yeast. Two types of structural element, a stem-loop and a poly(G) motif, not only inhibit translation initiation when inserted into an mRNA 5΄ untranslated region, but also generate noise. The noise-enhancing effect of the stem-loop structure also remains operational when combined with an upstream open reading frame. This has broad significance, since these elements are known to modulate the expression of a diversity of eukaryotic genes. Our findings suggest a mechanism for posttranscriptional noise generation that will contribute to understanding of the generally poor correlation between protein-level stochasticity and transcriptional bursting. We propose that posttranscriptional stochasticity can be linked to cycles of folding/unfolding of a stem-loop structure, or to interconversion between higher-order structural conformations of a G-rich motif, and have created a correspondingly configured computational model that generates fits to the experimental data. Stochastic events occurring during the ribosomal scanning process can therefore feature alongside transcriptional bursting as a source of noise.

Minimum-noise production of translation factor eIF4G maps to a mechanistically determined optimal rate control window for protein synthesis.

Gene expression noise influences organism evolution and fitness. The mechanisms determining the relationship between stochasticity and the functional role of translation machinery components are critical to viability. eIF4G is an essential translation factor that exerts strong control over protein synthesis. We observe an asymmetric, approximately bell-shaped, relationship between the average intracellular abundance of eIF4G and rates of cell population growth and global mRNA translation, with peak rates occurring at normal physiological abundance. This relationship fits a computational model in which eIF4G is at the core of a multi-component-complex assembly pathway. This model also correctly predicts a plateau-like response of translation to super-physiological increases in abundance of the other cap-complex factors, eIF4E and eIF4A. Engineered changes in eIF4G abundance amplify noise, demonstrating that minimum stochasticity coincides with physiological abundance of this factor. Noise is not increased when eIF4E is overproduced. Plasmid-mediated synthesis of eIF4G imposes increased global gene expression stochasticity and reduced viability because the intrinsic noise for this factor influences total cellular gene noise. The naturally evolved eIF4G gene expression noise minimum maps within the optimal activity zone dictated by eIF4G's mechanistic role. Rate control and noise are therefore interdependent and have co-evolved to share an optimal physiological abundance point.

On the Stability of BOLD fMRI Correlations.

Measurement of correlations between brain regions (functional connectivity) using blood oxygen level dependent (BOLD) fMRI has proven to be a powerful tool for studying the functional organization of the brain. Recently, dynamic functional connectivity has emerged as a major topic in the resting-state BOLD fMRI literature. Here, using simulations and multiple sets of empirical observations, we confirm that imposed task states can alter the correlation structure of BOLD activity. However, we find that observations of "dynamic" BOLD correlations during the resting state are largely explained by sampling variability. Beyond sampling variability, the largest part of observed "dynamics" during rest is attributable to head motion. An additional component of dynamic variability during rest is attributable to fluctuating sleep state. Thus, aside from the preceding explanatory factors, a single correlation structure-as opposed to a sequence of distinct correlation structures-may adequately describe the resting state as measured by BOLD fMRI. These results suggest that resting-state BOLD correlations do not primarily reflect moment-to-moment changes in cognitive content. Rather, resting-state BOLD correlations may predominantly reflect processes concerned with the maintenance of the long-term stability of the brain's functional organization.

Found in translation: another RNA helicase function.

In a recent issue of Cell, Pisareva et al. (2008) reveal that DHX29, a previously uncharacterized mammalian DExH-box protein, facilitates translation initiation on mRNAs with structured 5' untranslated regions.

Acoustic firearm discharge detection and classification in an enclosed environment.

Two different signal processing algorithms are described for detection and classification of acoustic signals generated by firearm discharges in small enclosed spaces. The first is based on the logarithm of the signal energy. The second is a joint entropy. The current study indicates that a system using both signal energy and joint entropy would be able to both detect weapon discharges and classify weapon type, in small spaces, with high statistical certainty.

Partial covariance based functional connectivity computation using Ledoit-Wolf covariance regularization.

Functional connectivity refers to shared signals among brain regions and is typically assessed in a task free state. Functional connectivity commonly is quantified between signal pairs using Pearson correlation. However, resting-state fMRI is a multivariate process exhibiting a complicated covariance structure. Partial covariance assesses the unique variance shared between two brain regions excluding any widely shared variance, hence is appropriate for the analysis of multivariate fMRI datasets. However, calculation of partial covariance requires inversion of the covariance matrix, which, in most functional connectivity studies, is not invertible owing to rank deficiency. Here we apply Ledoit-Wolf shrinkage (L2 regularization) to invert the high dimensional BOLD covariance matrix. We investigate the network organization and brain-state dependence of partial covariance-based functional connectivity. Although RSNs are conventionally defined in terms of shared variance, removal of widely shared variance, surprisingly, improved the separation of RSNs in a spring embedded graphical model. This result suggests that pair-wise unique shared variance plays a heretofore unrecognized role in RSN covariance organization. In addition, application of partial correlation to fMRI data acquired in the eyes open vs. eyes closed states revealed focal changes in uniquely shared variance between the thalamus and visual cortices. This result suggests that partial correlation of resting state BOLD time series reflect functional processes in addition to structural connectivity.

Rate control in yeast protein synthesis at the population and single-cell levels.

Yeast commits approximately 76% of its energy budget to protein synthesis and the efficiency and control of this process are accordingly critical to organism growth and fitness. We now have detailed genetic, biochemical and biophysical knowledge of the components of the eukaryotic translation machinery. However, these kinds of information do not, in themselves, give us a satisfactory picture of how the overall system is controlled. This is where quantitative system analysis can enable a step-change in our understanding of biological resource management and how this relates to cell physiology and evolution. An important aspect of this more system-oriented approach to translational control is the inherent heterogeneity of cell populations that is generated by gene expression noise. In this short review, we address the fact that, although the vast majority of our knowledge of the translation machinery is based on experimental analysis of samples that each contain hundreds of millions of cells, in reality every cell is unique in terms of its composition and control properties. We have entered a new era in which research into the heterogeneity of cell systems promises to provide answers to many (previously unanswerable) questions about cell physiology and evolution.

Correlating structure with non-linear optical properties in xAs40Se60·(1-x)As40S60 glasses.

A series of xAs40Se60·(100 - x)As40S60 glasses, where x = 0, 25, 33, 50, 67, 75 and 100 mol% As40Se60, has been studied using neutron and X-ray total scattering, Raman spectroscopy and (77)Se MAS-NMR. The results are presented with measurements of non-linear refractive indices, n2, and densities. There is no evidence for the formation of homopolar bonds in these glasses, but neutron correlation functions suggest that there is a non-random distribution of sulfur and selenium atoms in sulfur-rich glasses. The average number of sulfur atoms at a distance of 3-4 Å from a selenium atom, nSeS, deviates from a linear variation with x in glasses containing <50 mol% As40Se60; n2 for these glasses also varies non-linearly with x. Importantly, a direct comparison of n2 and nSeS gives a linear correlation, suggesting that n2 may be related to the distribution of chalcogen atoms in the glasses.

Entropy vs. Energy Waveform Processing: A Comparison Based on the Heat Equation.

Virtually all modern imaging devices collect electromagnetic or acoustic waves and use the energy carried by these waves to determine pixel values to create what is basically an "energy" picture. However, waves also carry "information", as quantified by some form of entropy, and this may also be used to produce an "information" image. Numerous published studies have demonstrated the advantages of entropy, or "information imaging", over conventional methods. The most sensitive information measure appears to be the joint entropy of the collected wave and a reference signal. The sensitivity of repeated experimental observations of a slowly-changing quantity may be defined as the mean variation (i.e., observed change) divided by mean variance (i.e., noise). Wiener integration permits computation of the required mean values and variances as solutions to the heat equation, permitting estimation of their relative magnitudes. There always exists a reference, such that joint entropy has larger variation and smaller variance than the corresponding quantities for signal energy, matching observations of several studies. Moreover, a general prescription for finding an "optimal" reference for the joint entropy emerges, which also has been validated in several studies.

Diauxic shift-dependent relocalization of decapping activators Dhh1 and Pat1 to polysomal complexes.

Dhh1 and Pat1 in yeast are mRNA decapping activators/translational repressors thought to play key roles in the transition of mRNAs from translation to degradation. However, little is known about the physical and functional relationships between these proteins and the translation machinery. We describe a previously unknown type of diauxic shift-dependent modulation of the intracellular locations of Dhh1 and Pat1. Like the formation of P bodies, this phenomenon changes the spatial relationship between components involved in translation and mRNA degradation. We report significant spatial separation of Dhh1 and Pat1 from ribosomes in exponentially growing cells. Moreover, biochemical analyses reveal that these proteins are excluded from polysomal complexes in exponentially growing cells, indicating that they may not be associated with active states of the translation machinery. In contrast, under diauxic growth shift conditions, Dhh1 and Pat1 are found to co-localize with polysomal complexes. This work suggests that Dhh1 and Pat1 functions are modulated by a re-localization mechanism that involves eIF4A. Pull-down experiments reveal that the intracellular binding partners of Dhh1 and Pat1 change as cells undergo the diauxic growth shift. This reveals a new dimension to the relationship between translation activity and interactions between mRNA, the translation machinery and decapping activator proteins.

Local control of a disorder-order transition in 4E-BP1 underpins regulation of translation via eIF4E.

The molecular mechanism underpinning regulation of eukaryotic translation initiation factor eIF4E by 4E-BP1 has remained unclear. We use isothermal calorimetry, circular dichroism, NMR, and computational modeling to analyze how the structure of the eIF4E-binding domain of 4E-BP1 determines its affinity for the dorsal face of eIF4E and thus the ability of this regulator to act as a competitive inhibitor. This work identifies the key role of solvent-facing amino acids in 4E-BP1 that are not directly engaged in interactions with eIF4E. These amino acid residues influence the propensity of the natively unfolded binding motif to fold into a conformation, including a stretch of α-helix, that is required for tight binding to eIF4E. In so doing, they contribute to a free energy landscape for 4E-BP1 folding that is poised so that phosphorylation of S65 at the C-terminal end of the helical region can modulate the propensity of folding, and thus regulate the overall free energy of 4E-BP1 binding to eIF4E, over a physiologically significant range. Thus, phosphorylation acts as an intramolecular structural modulator that biases the free energy landscape for the disorder-order transition of 4E-BP1 by destabilizing the α-helix to favor the unfolded form that cannot bind eIF4E. This type of order-disorder regulatory mechanism is likely to be relevant to other intermolecular regulatory phenomena in the cell.

Reengineering orthogonally selective riboswitches.

The ability to independently control the expression of multiple genes by addition of distinct small-molecule modulators has many applications from synthetic biology, functional genomics, pharmaceutical target validation, through to gene therapy. Riboswitches are relatively simple, small-molecule-dependent, protein-free, mRNA genetic switches that are attractive targets for reengineering in this context. Using a combination of chemical genetics and genetic selection, we have developed riboswitches that are selective for synthetic "nonnatural" small molecules and no longer respond to the natural intracellular ligands. The orthogonal selectivity of the riboswitches is also demonstrated in vitro using isothermal titration calorimetry and x-ray crystallography. The riboswitches allow highly responsive, dose-dependent, orthogonally selective, and dynamic control of gene expression in vivo. It is possible that this approach may be further developed to reengineer other natural riboswitches for application as small-molecule responsive genetic switches in both prokaryotes and eukaryotes.

"Brain age" predicts disability accumulation in multiple sclerosis.

OBJECTIVE: Neurodegenerative conditions often manifest radiologically with the appearance of premature aging. Multiple sclerosis (MS) biomarkers related to lesion burden are well developed, but measures of neurodegeneration are less well-developed. The appearance of premature aging quantified by machine learning applied to structural MRI assesses neurodegenerative pathology. We assess the explanatory and predictive power of "brain age" analysis on disability in MS using a large, real-world dataset. METHODS: Brain age analysis is predicated on the over-estimation of predicted brain age in patients with more advanced pathology. We compared the performance of three brain age algorithms in a large, longitudinal dataset (>13,000 imaging sessions from >6,000 individual MS patients). Effects of MS, MS disease course, disability, lesion burden, and DMT efficacy were assessed using linear mixed effects models. RESULTS: MS was associated with advanced predicted brain age cross-sectionally and accelerated brain aging longitudinally in all techniques. While MS disease course (relapsing vs. progressive) did contribute to advanced brain age, disability was the primary correlate of advanced brain age. We found that advanced brain age at study enrollment predicted more disability accumulation longitudinally. Lastly, a more youthful appearing brain (predicted brain age less than actual age) was associated with decreased disability. INTERPRETATION: Brain age is a technically tractable and clinically relevant biomarker of disease pathology that correlates with and predicts increasing disability in MS. Advanced brain age predicts future disability accumulation.

Mid-infrared spectral broadening in an ultrafast laser inscribed gallium lanthanum sulphide waveguide.

We report the successful fabrication of mid-infrared waveguides written in a gallium lanthanum sulphide (GLS) substrate via the ultrafast laser inscription technique. Single mode guiding at 2485 nm and 3850 nm is observed. Spectral broadening spanning 1500 nm (-15dB points) is demonstrated under 3850 nm excitation.

Translation initiation: variations in the mechanism can be anticipated.

Translation initiation is a critical step in protein synthesis. Previously, two major mechanisms of initiation were considered as essential: prokaryotic, based on SD interaction; and eukaryotic, requiring cap structure and ribosomal scanning. Although discovered decades ago, cap-independent translation has recently been acknowledged as a widely spread mechanism in viruses, which may take place in some cellular mRNA translations. Moreover, it has become evident that translation can be initiated on the leaderless mRNA in all three domains of life. New findings demonstrate that other distinguishable types of initiation exist, including SD-independent in Bacteria and Archaea, and various modifications of 5' end-dependent and internal initiation mechanisms in Eukarya. Since translation initiation has developed through the loss, acquisition, and modification of functional elements, all of which have been elevated by competition with viral translation in a large number of organisms of different complexity, more variation in initiation mechanisms can be anticipated.

Identifying eIF4E-binding protein translationally-controlled transcripts reveals links to mRNAs bound by specific PUF proteins.

eIF4E-binding proteins (4E-BPs) regulate translation of mRNAs in eukaryotes. However the extent to which specific mRNA targets are regulated by 4E-BPs remains unknown. We performed translational profiling by microarray analysis of polysome and monosome associated mRNAs in wild-type and mutant cells to identify mRNAs in yeast regulated by the 4E-BPs Caf20p and Eap1p; the first-global comparison of 4E-BP target mRNAs. We find that yeast 4E-BPs modulate the translation of >1000 genes. Most target mRNAs differ between the 4E-BPs revealing mRNA specificity for translational control by each 4E-BP. This is supported by observations that eap1Δ and caf20Δ cells have different nitrogen source utilization defects, implying different mRNA targets. To account for the mRNA specificity shown by each 4E-BP, we found correlations between our data sets and previously determined targets of yeast mRNA-binding proteins. We used affinity chromatography experiments to uncover specific RNA-stabilized complexes formed between Caf20p and Puf4p/Puf5p and between Eap1p and Puf1p/Puf2p. Thus the combined action of each 4E-BP with specific 3'-UTR-binding proteins mediates mRNA-specific translational control in yeast, showing that this form of translational control is more widely employed than previously thought.

Modeling the relative risk of SARS-CoV-2 infection to inform risk-cost-benefit analyses of activities during the SARS-CoV-2 pandemic.

Risk-cost-benefit analysis requires the enumeration of decision alternatives, their associated outcomes, and the quantification of uncertainty. Public and private decision-making surrounding the COVID-19 pandemic must contend with uncertainty about the probability of infection during activities involving groups of people, in order to decide whether that activity is worth undertaking. We propose a model of SARS-CoV-2 infection probability that can produce estimates of relative risk of infection for diverse activities, so long as those activities meet a list of assumptions, including that they do not last longer than one day (e.g., sporting events, flights, concerts), and that the probability of infection among possible routes of infection (i.e., droplet, aerosol, fomite, and direct contact) are independent. We show how the model can be used to inform decisions facing governments and industry, such as opening stadiums or flying on airplanes; in particular, it allows for estimating the ranking of the constituent components of activities (e.g., going through a turnstile, sitting in one's seat) by their relative risk of infection, even when the probability of infection is unknown or uncertain. We prove that the model is a good approximation of a more refined model in which we assume infections come from a series of independent risks. A linearity assumption governing several potentially modifiable risks factors-such as duration of the activity, density of participants, and infectiousness of the attendees-makes interpreting and using the model straightforward, and we argue that it does so without significantly diminishing the reliability of the model.