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Energy-dependent protein degradation by the AAA+ ClpXP protease helps maintain protein homeostasis in bacteria and eukaryotic organelles of bacterial origin. In Escherichia coli and many other proteobacteria, the SspB adaptor assists ClpXP in degrading ssrA-tagged polypeptides produced as a consequence of tmRNA-mediated ribosome rescue. By tethering these incomplete ssrA-tagged proteins to ClpXP, SspB facilitates their efficient degradation at low substrate concentrations. How this process occurs structurally is unknown. Here, we present a cryo-EM structure of the SspB adaptor bound to a GFP-ssrA substrate and to ClpXP. This structure provides evidence for simultaneous contacts of SspB and ClpX with the ssrA tag within the tethering complex, allowing direct substrate handoff concomitant with the initiation of substrate translocation. Furthermore, our structure reveals that binding of the substrate·adaptor complex induces unexpected conformational changes within the spiral structure of the AAA+ ClpX hexamer and its interaction with the ClpP tetradecamer.

Energy-dependent protein degradation by the AAA+ClpXP protease helps maintain protein homeostasis in organisms ranging from simple bacteria to humans. InE. coliand many other proteobacteria, the SspB adaptor assists ClpXP in degrading ssrA-tagged polypeptides produced as a consequence of tmRNA-mediated ribosome rescue. By tethering these incomplete ssrA-tagged proteins to ClpXP, SspB facilitates their efficient degradation at low substrate concentrations. How this process occurs structurally is unknown. Here, we present a cryo-EM structure of the SspB adaptor bound to a GFP-ssrA substrate and to ClpXP. This structure provides evidence for simultaneous contacts of SspB and ClpX with the ssrA tag within the tethering complex, allowing direct substrate handoff concomitant with the initiation of substrate translocation. Furthermore, our structures reveal that binding of the substrate•adaptor complex induces unexpected conformational changes within the spiral structure of the AAA+ClpX hexamer and its interaction with the ClpP tetradecamer.SIGNIFICANCEIntercellular proteases, including ClpXP, degrade damaged or unneeded proteins. Peptide tags allow specific protein substrates to be recognized by the ClpX unfoldase/translocase component of ClpXP and by an adaptor, SspB, which tethers itself to ClpX and enhances ClpXP degradation of the tagged protein. Our cryo-EM structure of ClpXP bound to SspB and a tagged substrate shows that SspB and ClpX simultaneously contact the degradation tag and reveal changes in the structure of ClpX and its interaction with ClpP. These structural changes appear to be a prelude to an initial ClpX translocation step that pulls the substrate away from SspB and initiates degradation by allowing substrate unfolding and further translocation of the unfolded substrate into the proteolytic chamber of ClpP.

Predicting long-term equity market returns is of great importance for investors to strategically allocate their assets. The authors explore machine learning (ML) methods to forecast 10-year-ahead US stock returns and compare the results with the traditional Shiller regression-based forecasts more commonly used in the asset-management industry. The authors find that ML techniques can only modestly improve the forecast accuracy of a traditional Shiller cyclically adjusted price-to-earnings ratio model, and they actually result in worse performance than the vector autoregressive model (VAR)–based two-step approach. The authors then implement this approach with ML techniques and allow for unspecified nonlinear relationships (a hybrid ML-VAR approach). They find about 50% improvement in real-time forecast accuracy for 10-year annualized US stock returns. TOPICS:Security analysis and valuation, big data/machine learning, quantitative methods, statistical methods, performance measurement Key Findings ▪ Applying machine learning (ML) techniques within a robust economic framework such as Davis et al.’s (2018) two-step approach is superior than applying such techniques in isolation (directly forecasting equity returns). ▪ Using the two-step approach, integrating ML with the vector autoregressive model (ML-VAR) to dynamically forecast earning yields reduces dramatically out-of-sample forecast errors, yielding an improvement of about 50% in forecast accuracy for long-horizon U.S. stock market returns. ▪ Among the ML algorithms tested, the ensemble method, which averages all other model forecasts, consistently provides improved predictive power.

Intracellular proteases must be specific to avoid degrading the wrong proteins. Here, we present cryo-EM structures of E. coli ClpXP, a AAA+ protease, which reveal that the axial channel of ClpX is closed prior to the binding and subsequent translocation of a protein substrate. An open-channel ClpX mutation stimulates degradation of casein, a non-specific substrate, indicating that channel closure contributes to increased degradation specificity. We demonstrate that ClpX activates ClpP cleavage of a degron-free decapeptide by a channel-independent mechanism, in which the peptide substrate appears to pass through a symmetry mismatched gap in the interface between ClpX and ClpP before entering the degradation chamber via the axial portal of ClpP. The peptide products of ClpXP protein degradation are likely to exit the chamber by the reverse route.

Ribosome assembly is orchestrated by many assembly factors, including ribosomal RNA methyltransferases whose precise role is poorly understood. Here, we leverage the power of cryo-EM and machine learning to discover that the bacterial methyltransferase KsgA performs a novel “proofreading” function in assembly of the ribosomal small subunit by recognizing and partially disassembling particles that have matured but are not competent for translation. We propose that this activity allows inactive particles an opportunity to reassemble into an active state, thereby increasing overall assembly fidelity. Detailed structural quantifications in our datasets additionally enabled expansion of the Nomura assembly map to highlight rRNA helix and r-protein interdependencies, which newly details how binding and docking of these elements are tightly coupled. These results have wide-ranging implications in our understanding of the quality control mechanisms governing ribosome biogenesis, and showcase the power of heterogeneity analysis in cryo-EM to unveil functionally relevant information in biological systems.

Cryo-electron microscopy (cryo-EM) single-particle analysis has proven powerful in determining the structures of rigid macromolecules. However, many imaged protein complexes exhibit conformational and compositional heterogeneity that poses a major challenge to existing three-dimensional reconstruction methods. Here, we present cryoDRGN, an algorithm that leverages the representation power of deep neural networks to directly reconstruct continuous distributions of 3D density maps and map per-particle heterogeneity of single-particle cryo-EM datasets. Using cryoDRGN, we uncovered residual heterogeneity in high-resolution datasets of the 80S ribosome and the RAG complex, revealed a new structural state of the assembling 50S ribosome, and visualized large-scale continuous motions of a spliceosome complex. CryoDRGN contains interactive tools to visualize a dataset’s distribution of per-particle variability, generate density maps for exploratory analysis, extract particle subsets for use with other tools and generate trajectories to visualize molecular motions. CryoDRGN is open-source software freely available at http://cryodrgn.csail.mit.edu . CryoDRGN is an unsupervised machine learning algorithm that reconstructs continuous distributions of three-dimensional density maps from heterogeneous single-particle cryo-EM data.

In motile cilia, a mechanoregulatory network is responsible for converting the action of thousands of dynein motors bound to doublet microtubules into a single propulsive waveform. Here, we use two complementary cryo-EM strategies to determine structures of the major mechanoregulators that bind ciliary doublet microtubules in Chlamydomonas reinhardtii. We determine structures of isolated radial spoke RS1 and the microtubule-bound RS1, RS2 and the nexin-dynein regulatory complex (N-DRC). From these structures, we identify and build atomic models for 30 proteins, including 23 radial-spoke subunits. We reveal how mechanoregulatory complexes dock to doublet microtubules with regular 96-nm periodicity and communicate with one another. Additionally, we observe a direct and dynamically coupled association between RS2 and the dynein motor inner dynein arm subform c (IDAc), providing a molecular basis for the control of motor activity by mechanical signals. These structures advance our understanding of the role of mechanoregulation in defining the ciliary waveform.

Single-particle cryogenic electron microscopy (cryo-EM) has emerged as a powerful technique to visualize the structural landscape sampled by a protein complex. However, algorithmic and computational bottlenecks in analyzing heterogeneous cryo-EM datasets have prevented the full realization of this potential. CryoDRGN is a machine learning system for heterogeneous cryo-EM reconstruction of proteins and protein complexes from single-particle cryo-EM data. Central to this approach is a deep generative model for heterogeneous cryo-EM density maps, which we empirically find is effective in modeling both discrete and continuous forms of structural variability. Once trained, cryoDRGN is capable of generating an arbitrary number of 3D density maps, and thus interpreting the resulting ensemble is a challenge. Here, we showcase interactive and automated processing approaches for analyzing cryoDRGN results. Specifically, we detail a step-by-step protocol for the analysis of an existing assembling 50S ribosome dataset, including preparation of inputs, network training and visualization of the resulting ensemble of density maps. Additionally, we describe and implement methods to comprehensively analyze and interpret the distribution of volumes with the assistance of an associated atomic model. This protocol is appropriate for structural biologists familiar with processing single-particle cryo-EM datasets and with moderate experience navigating Python and Jupyter notebooks. It requires 3-4 days to complete. CryoDRGN is open source software that is freely available.

Cryo-EM single-particle analysis has proven powerful in determining the structures of rigid macromolecules. However, many protein complexes are flexible and can change conformation and composition as a result of functionally-associated dynamics. Such dynamics are poorly captured by current analysis methods. Here, we present cryoDRGN, an algorithm that for the first time leverages the representation power of deep neural networks to efficiently reconstruct highly heterogeneous complexes and continuous trajectories of protein motion. We apply this tool to two synthetic and three publicly available cryo-EM datasets, and we show that cryoDRGN provides an interpretable representation of structural heterogeneity that can be used to identify discrete states as well as continuous conformational changes. This ability enables cryoDRGN to discover previously overlooked structural states and to visualize molecules in motion.

The accuracy of U.S. stock return forecasts based on the cyclically-adjusted P/E (CAPE) ratio has deteriorated since 1985. A primary reason has been that traditional CAPE regressions assume the CAPE ratio reverts mechanically to its long-run average, regardless of the macroeconomic environment. In this article, the authors propose an enhancement to standard CAPE-based forecasts that conditions mean reversion in the CAPE ratio on real (not nominal) bond yields, expected inflation rates, and financial volatility in a VAR model. The forecasted results are promising for both real and nominal returns, with out-of-sample forecast errors approximately 50% lower than traditional approaches. The differences are economically meaningful and statistically significant over the forecast period examined. At present, low real bond yields imply low real earnings yields and an above-average “fair-value” CAPE ratio. Nevertheless, with Shiller’s CAPE ratio now well above its fair value, the model proposed by the author predicts nominal U.S. stock returns centered near 5% over the next decade.

We identify the longest expansion in U.S. history, a recession-free 16-year period from 1841 to 1856 that we call America's First Great Moderation. Using newer data on industrial production, we show that the record-long expansion was primarily driven by a boom in transportation-goods investment following the discovery of gold in California. Furthermore, the low volatility of industrial production and stock returns during the First Great Moderation, which occurred during a period without a U.S. central bank, is similar to that observed for the Second Great Moderation (1984–2007).

We present a strategy for tackling preferred particle orientation in single-particle cryogenic electron microscopy (cryo-EM) by employing tilts during data collection, and we quantify the resulting directional resolution and density isotropy using a new 3D Fourier Shell Correlation (FSC) algorithm. These techniques enabled structure determination of the influenza hemagglutinin (HA) trimer, which adopts a highly preferred orientation, to near-atomic resolution. They also improved both isotropy and global resolution for ribosomal biogenesis intermediates, which adopt a moderately preferred orientation. We propose that data collection at tilts is generally applicable to single-particle analysis, and furthermore, that quantitative isotropy estimation should be employed to evaluate cryo-EM density maps.

The persistent downturn in productivity growth during the past two decades has cast doubts on global economic prospects. Frequently cited causes include a dearth of productivity-enhancing ideas, an aging population, and a shift to service-based economies. While we acknowledge the role each of these has played, our research shows that productivity is fundamentally driven by a virtuous cycle of idea generation, diffusion, and proliferation of ideas, which has recently accelerated after years of stagnation. In this paper, we take a step back from the traditional approach of leveraging patents as a proxy for intellectual/technical advancement and focus instead on the sharing of ideas. We introduce what we have termed the “Idea Multiplier” and the “Idea Diffusion” metrics, time series of academic paper citations within and across industries (Idea Multiplier) and countries (Idea Diffusion) based on nearly 2 billion records of journal citations. We find that greater idea sharing has tended to lead to periods of stronger productivity growth, and given that each metric has been increasing in recent years, that the recent era of low productivity growth will eventually end.

YphC and YsxC are GTPases in Bacillus subtilis that facilitate the assembly of the 50S ribosomal subunit, however their roles in this process are still uncharacterized. To explore their function, we used strains in which the only copy of the yphC or ysxC genes were under the control of an inducible promoter. Under depletion conditions, they accumulated incomplete ribosomal subunits that we named 45SYphC and 44.5SYsxC particles. Quantitative mass spectrometry analysis and the 5-6 A resolution cryo-EM maps of the 45SYphC and 44.5SYsxC particles revealed that the two GTPases participate in the maturation of the central protuberance, GTPase associated region and key RNA helices in the A, P and E functional sites of the 50S subunit. We observed that YphC and YsxC bind specifically to the two immature particles, suggesting that they represent either on-pathway intermediates or that their structure has not significantly diverged from that of the actual substrate. These results describe the nature of these immature particles, a widely used tool to study the assembly process of the ribosome. They also provide the first insights into the function of YphC and YsxC in 50S subunit assembly and are consistent with this process occurring through multiple parallel pathways, as it has been described for the 30S subunit.

Our understanding regarding the function of YjeQ (also called RsgA), RbfA, RimM and Era in ribosome biogenesis has been derived in part from the study of immature 30S particles that accumulate in null strains lacking one of these factors. However, their mechanistic details are still unknown. Here, we demonstrate that these immature particles are not dead-end products of assembly, but progress into mature 30S subunits. Mass spectrometry analysis revealed that in vivo the occupancy level of these factors in these immature 30S particles is below 10% and that the concentration of factors does not increase when immature particles accumulate in cells. We measured by microscale thermophoresis that YjeQ and Era binds to the mature 30S subunit with high affinity. However, the binding affinity of these factors to the immature particles and of RimM and RbfA to mature or immature particles was weak, suggesting that binding is not occurring at physiological concentrations. These results suggest that in the absence of these factors, the immature particles evolve into a thermodynamically stable intermediate that exhibits low affinity for the assembly factors. These results imply that the true substrates of YjeQ, RbfA, RimM and Era are immature particles that precede the ribosomal particles accumulating in the knockouts strains.

SUMMARYTo reveal the role of the essential protein Era in the assembly of the 30S ribosomal subunit, we analyzed assembly intermediates that accumulated in Era-depletedEscherichia colicells using quantitative mass spectrometry, cryo-electron microscopy and in-cell footprinting. Our combined approach allowed for visualization of the small subunit as it assembled and revealed that with the exception of key helices in the platform domain, all other 16S rRNA domains were able to fold even in the absence of Era. Notably, the maturing particles did not stall while waiting for the platform domain to mature and instead re-routed their folding pathway to enable concerted maturation of other structural motifs spanning multiple rRNA domains. We also found that binding of Era to the mature 30S subunit destabilized helix 44 and the decoding center preventing binding of YjeQ, another assembly factor. This work establishes Era’s role in ribosome assembly and suggests new roles in maintaining ribosome homeostasis.

Predicting long-term equity market returns is of great importance for investors to strategically allocate their assets. We apply machine learning methods to forecast 10-year-ahead U.S. stock returns and compare the results to traditional Shiller regression-based forecasts more commonly used in the asset-management industry. Machine-learning forecasts have similar forecast errors to a traditional return forecast model based on lagged CAPE ratios. However, machine-learning forecasts have higher forecast errors than the regression-based, two-step approach of Davis et al [2018] that forecasts the CAPE ratio based on macroeconomic variables and then imputes stock returns. When we combine our two-step approach with machine learning to forecast CAPE ratios (a hybrid ML-VAR approach), U.S. stock return forecasts are statistically and economically more accurate than all other approaches. We discuss why and conclude with some best practices for both data scientists and economists in making real-world investment return forecasts. A more updated paper with a clearer description of methodology and longer time series can be found here: https://jfds.pm-research.com/content/3/2/9

Bacterial ribosome biogenesis has been an active area of research for more than 30 years and has served as a test-bed for the development of new biochemical, biophysical and structural techniques to understand macromolecular assembly generally. Recent work inspecting the process in vivo has advanced our understanding of the role of ribosome biogenesis factors, the co-transcriptional nature of assembly, the kinetics of the process under sub-optimal conditions, and the rRNA folding and ribosome protein binding pathways. Additionally, new structural work enabled by single-particle electron microscopy has helped to connect in vitro ribosomal protein binding maps to the underlying RNA. This review summarizes the state of these in vivo studies, provides a kinetic model for ribosome assembly under sub-optimal conditions, and describes a framework to compare newly emerging assembly intermediate structures. This article is part of the themed issue ‘Perspectives on the ribosome’.

A high impact mentoring program at a community college connected professionals from the special education and early intervention fields with small groups of teacher education students. Two federal grants from U.S. Department of Education funded tuition scholarships and mentoring for 76 Special Education students and 78 Early Childhood Education/Early Intervention students in associate degree programs. The mentor programs consisted of individual monitoring by project staff, consistent contact with a mentor from the professional community and with other students in mentor groups, and structured monthly dinner meetings. Students who participated in the mentoring programs showed increased persistence and higher grade point average when compared with the general population of similar majors. Within each grant-funded population, students who showed low participation in the mentor programming presented lower retention rates and lower GPA than grant-funded students who took full advantage of the mentoring program.

By studying the number and method of homicidal poisoning in Miami-Dade County, Florida; New York City, NY; Oakland County, Michigan; and Sweden, we have confirmed that this is an infrequently established crime.Several difficulties come with the detection of homicidal poisonings. Presenting symptoms and signs are often misdiagnosed as natural disease, especially if the crime is committed in a hospital environment, suggesting that an unknown number of homicides go undetected.In the reported cases analyzed, the lethal agent of choice has changed over the years. In earlier years, traditional poisons such as arsenic, cyanide, and parathion were frequently used. Such poisonings are nowadays rare, and instead, narcotics are more commonly detected in victims of this crime.

The accuracy of U.S. stock return forecasts based on the cyclically-adjusted P/E (CAPE) ratio has deteriorated since 1985. The issue is not the CAPE ratio, but CAPE regressions that assume it reverts mechanically to its long-run average. Our approach conditions mean reversion in the CAPE ratio on real (not nominal) bond yields, reducing out-of-sample forecast errors by as much as 50%. At present, low real bond yields imply low real earnings yields and an above-average “fair-value” CAPE ratio. Nevertheless, with Shiller’s CAPE ratio now well above its fair value, our model predicts muted U.S. stock returns over the next decade. We believe that our framework should be adopted by the investment profession when forecasting stock returns for strategic asset allocation.

Forensic pathology is not simply autopsy pathology. Rather, the determination of why someone died is dependent upon the findings of a competent autopsy interpreted within the context of an excellent investigation of the circumstances of death. It is important that medical examiners remember the critical distinction between “dying with” and “dying of” something. Furthermore, our determination of “the” cause of death may not explain “why” someone died; identifying the underlying cause of death may not explain the mechanism through which the person died.

A natural death is one which is not caused by accident, by suicide, or by homicide. Natural deaths are those caused by disease. Diseases may be infectious, metabolic, degenerative, congenital, or neoplastic. The number of diseases causing death are innumerable. Coding manuals used by vital statisticians cover thousands of subcategories of diseases which are known to cause or accelerate death. Natural diseases investigated by police are relatively few in number and likewise involve limited subsets of our society. There are also geographic and ethnic variations in different parts of the world.

Forensic pathology, as a scientific discipline, must depend upon generally accepted procedural standards in order to be useful in court. Procedural standards should assist investigations and determination of proper decisions necessary for the administration of justice.

We have generated a series of variable-strength, constitutive, bacterial promoters that act predictably in different sequence contexts, span two orders of magnitude in strength and contain convenient sites for cloning and the introduction of downstream open-reading frames. Importantly, their design insulates these promoters from the stimulatory or repressive effects of many 5′- or 3′-sequence elements. We show that different promoters from our library produce constant relative levels of two different proteins in multiple genetic contexts. This set of promoters should be a useful resource for the synthetic-biology community., National Institutes of Health (U.S.) (NIH Grant AI-15706), National Institutes of Health (U.S.) (NIH Grant AI-16892)

Practical Applications Summary In Improving U.S. Stock Return Forecasts: A “Fair-Value” CAPE Approach , published in the Winter 2018 issue of The Journal of Portfolio Management , authors Joseph Davis, Roger Aliaga-Diaz, Harshdeep Ahluwalia (all with the Vanguard Group ), and Ravi Tolani (of Duke University ) introduce a new method of forecasting equity returns in real time (not in sample) using the cyclically adjusted price-to-earnings(CAPE) ratio. They call the result a “fair-value CAPE model” to distinguish it from traditional approaches that use CAPE ratios to forecast future equity returns. The authors demonstrate that their fair-value CAPE provides a better tool for forecasting of future stock returns in real time than the original CAPE and its subsequent variants. The new twist in the fair-value CAPE model is the use of bond yields, inflation, and volatility in calculating the ratio. The authors forecast (as of July 2017) that the return on U.S. stocks over a 10-year period would be 4.9%, which is lower than the long-term historical average.

ClpXP is an ATP-fueled molecular machine that unfolds and degrades target proteins. ClpX, an AAA+ enzyme, recognizes specific proteins, and then uses cycles of ATP hydrolysis to denature any native structure and to translocate the unfolded polypeptide into ClpP for degradation. Here, we develop and apply single-molecule fluorescence assays to probe the kinetics of protein denaturation and degradation by ClpXP. These assays employ a single-chain variant of the ClpX hexamer, linked via a single biotin to a streptavidin-coated surface, and fusion substrates with an N-terminal fluorophore and a C-terminal GFP-titin-ssrA module. In the presence of adenosine 5′-[γ-thio]triphosphate (ATPγS), ClpXP degrades the titin-ssrA portion of these substrates but stalls when it encounters GFP. Exchange into ATP then allows synchronous resumption of denaturation and degradation of GFP and any downstream domains. GFP unfolding can be monitored directly, because intrinsic fluorescence is quenched by denaturation. The time required for complete degradation coincides with loss of the substrate fluorophore from the protease complex. Fitting single-molecule data for a set of related substrates provides time constants for ClpX unfolding, translocation, and a terminal step that may involve product release. Comparison of these single-molecule results with kinetics measured in bulk solution indicates similar levels of microscopic and macroscopic ClpXP activity. These results support a stochastic engagement/unfolding mechanism that ultimately results in highly processive degradation and set the stage for more detailed single-molecule studies of machine function.

Facile control of targeted intracellular protein degradation has many potential uses in basic science and biotechnology. One promising approach to this goal is to redesign adaptor proteins, which can regulate proteolytic specificity by tethering substrates to energy-dependent AAA+ proteases. Using the ClpXP protease, we have probed the minimal biochemical functions required for adaptor function by designing and characterizing variant substrates, adaptors, and ClpX enzymes. We find that substrate tethering mediated by heterologous interaction domains and a small bridging molecule mimics substrate delivery by the wild-type system. These results show that simple tethering is sufficient for synthetic adaptor function. In our engineered system, tethering and proteolysis depend on the presence of the macrolide rapamycin, providing a foundation for engineering highly specific degradation of target proteins in cells. Importantly, this degradation is regulated by a small molecule without the need for new adaptor or enzyme biosynthesis.

This article examines various strategies aimed at repositioning an equity portfolio to a more defensive stance in anticipation of a recession or bear market. We examine the factors for success and document several critical reasons as to why implementing these strategies can undermine relative performance. In the end we find a balanced portfolio to be a viable alternative to many defensively minded tactical strategies.

Conventional wisdom maintains that small-cap active equity funds have had higher excess returns than their larger-cap counterparts because the small-cap market is less efficient and provides greater stock-selection opportunities. This article reexamines the widely touted historical out-performance of small-cap funds through formal returns-based style analysis under alternative benchmarks using a large survivorship-bias-free mutual fund database. The authors find that small-cap alpha is not robust across equity style benchmarks, is concentrated among small-cap growth funds in the years surrounding the U.S. equity market bubble, and is strongly associated with a “buy-past-winners” momentum factor that primarily reflects a Russell reconstitution effect. Under MSCI benchmarks, the relative performance of the median small-cap fund manager is zero before costs, and is economically and statistically negative after costs. Finally, the authors show that the historical probability of an active small-cap fund achieving positive alpha is equivalent to a coin toss before costs, even if the fund outperformed in the previous year. This lack of persistence demonstrates that indexing is a powerful strategy among small-cap stocks.

The heme cofactor in soluble guanylate cyclase (sGC) is a selective receptor for NO, an important signaling molecule in eukaryotes. The sGC heme domain has been localized to the N-terminal 194 amino acids of the beta1 subunit of sGC and is a member of a family of conserved hemoproteins, called the H-NOX family (Heme-Nitric Oxide and/or OXygen-binding domain). Three new members of this family have now been cloned and characterized, two proteins from Legionella pneumophila (L1 H-NOX and L2 H-NOX) and one from Nostoc punctiforme (Np H-NOX). Like sGC, L1 H-NOX forms a 5-coordinate Fe(II)-NO complex. However, both L2 H-NOX and Np H-NOX form temperature-dependent mixtures of 5- and 6-coordinate Fe(II)-NO complexes; at low temperature, they are primarily 6-coordinate, and at high temperature, the equilibrium is shifted toward a 5-coordinate geometry. This equilibrium is fully reversible with temperature in the absence of free NO. This process is analyzed in terms of a thermally labile proximal Fe(II)-His bond and suggests that in both the 5- and 6-coordinate Fe(II)-NO complexes of L2 H-NOX and Np H-NOX, NO is bound in the distal heme pocket of the H-NOX fold. NO dissociation kinetics for L1 H-NOX and L2 H-NOX have been determined and support a model in which NO dissociates from the distal side of the heme in both 5- and 6-coordinate complexes.

As a remedy for the notorious deficiency of pre-Civil War U. S. macroeconomic data, this study introduces an annual index of American industrial production consistently defined from 1790 until World War I. The index incorporates 43 quantity-based annual series (most entirely new) in the manufacturing and mining industries in a manner similar to the Federal Reserve Board's monthly industrial production index. The index changes our view of the growth and volatility of the U. S. economy before World War I. A direct implication of the index is that antebellum-postbellum differences in industrial volatility are statistically indistinguishable. The index also demonstrates that the pernicious deflationary depressions that purportedly followed the financial panics in 1837 and 1873 were actually rather mild recessions when expressed in real output.

Based on analysis of private equity performance, this article challenges the widespread assumption that private equity investments can provide both exceptional returns and enhanced diversification. Private equity investments entail significant and unique risks, including a necessarily long investment horizon, rigid liquidity constraints, and high bankruptcy rates among portfolio companies, that can make it difficult for investors to realize the potentially superior performance of private equity investments. Furthermore, the article stresses that diversification should not be considered a major benefit of private equity investing. Rather, private equity should be treated as but one small component of a portfolio9s allocation to all equity investments, private and public.

Financial planners employ one of two statistical procedures to generate estimates of future asset values: historical simulation and Monte Carlo simulation. Through an application of statistical analysis, financial simulation, and intuition, this paper appraises the relative merits and limitations of these disparate approaches. In short, Monte Carlo simulators possess distinct advantages, but overall they do not offer a superior alternative to appropriately conducted historical simulations.

While small molecule inhibitors of the bacterial ribosome have been instrumental in understanding protein translation, no such probes exist to study ribosome biogenesis. We screened a diverse chemical collection that included previously approved drugs for compounds that induced cold sensitive growth inhibition in the model bacterium Escherichia coli. Among the most cold sensitive was lamotrigine, an anticonvulsant drug. Lamotrigine treatment resulted in the rapid accumulation of immature 30S and 50S ribosomal subunits at 15°C. Importantly, this was not the result of translation inhibition, as lamotrigine was incapable of perturbing protein synthesis in vivo or in vitro. Spontaneous suppressor mutations blocking lamotrigine activity mapped solely to the poorly characterized domain II of translation initiation factor IF2 and prevented the binding of lamotrigine to IF2 in vitro. This work establishes lamotrigine as a widely available chemical probe of bacterial ribosome biogenesis and suggests a role for E. coli IF2 in ribosome assembly. DOI: http://dx.doi.org/10.7554/eLife.03574.001, eLife digest Inside cells, molecular machines called ribosomes make proteins from instructions that are provided by genes. The ribosomes themselves are made up of about 50 proteins and three RNA molecules that need to be assembled like a 3-D jigsaw. In bacteria, a group of proteins called ribosome biogenesis factors help to assemble these pieces correctly. To study how a biological process works, scientists often look at what happens when a component is missing or not working properly. However, this approach cannot be used to study how ribosomes are made because stopping protein production entirely will kill the cell. Another approach is to use chemicals to temporarily stop or slow down a biological process, but researchers are yet to find a chemical that can do this for ribosome assembly. To address this problem, Stokes et al. ‘screened’ 30,000 chemicals in an effort to find one or more that could affect ribosome assembly in bacteria. The screen revealed that a drug called lamotrigine—which is used to treat epilepsy and other conditions in humans—could stop the assembly of ribosomes, but did not affect the production of proteins by completed ribosomes. The experiments also suggest that initiation factor 2, a protein that is involved in the production of other proteins, may also have a role in ribosome assembly. Another recent study found that the equivalent of initiation factor 2 in yeast acts as a quality control checkpoint during ribosome assembly, so the bacterial version may also perform a similar role. It is also be possible that lamotrigine might be used to help develop a novel mechanistic class of antibiotics. DOI: http://dx.doi.org/10.7554/eLife.03574.002

Despite the identification of many factors that facilitate ribosome assembly, the molecular mechanisms by which they drive ribosome biogenesis are poorly understood. Here, we analyze the late stages of assembly of the 50S subunit using Bacillus subtilis cells depleted of RbgA, a highly conserved GTPase. We found that RbgA-depleted cells accumulate late assembly intermediates bearing sub-stoichiometric quantities of ribosomal proteins L16, L27, L28, L33a, L35 and L36. Using a novel pulse labeling/quantitative mass spectrometry technique, we show that this particle is physiologically relevant and is capable of maturing into a complete 50S particle. Cryo-electron microscopy and chemical probing revealed that the central protuberance, the GTPase associating region and tRNA-binding sites in this intermediate are unstructured. These findings demonstrate that key functional sites of the 50S subunit remain unstructured until late stages of maturation, preventing the incomplete subunit from prematurely engaging in translation. Finally, structural and biochemical analysis of a ribosome particle depleted of L16 indicate that L16 binding is necessary for the stimulation of RbgA GTPase activity and, in turn, release of this co-factor, and for conversion of the intermediate to a complete 50S subunit.

Summary The ribosome is a complex macromolecular machine and serves as an ideal system for understanding biological macromolecular assembly. Direct observation of ribosome assembly in vivo is difficult, as few intermediates have been isolated and thoroughly characterized. Herein, we deploy a genetic system to starve cells of an essential ribosomal protein, which results in the accumulation of assembly intermediates that are competent for maturation. Quantitative mass spectrometry and single-particle cryo-electron microscopy reveal 13 distinct intermediates, which were each resolved to ∼4–5 A resolution and could be placed in an assembly pathway. We find that ribosome biogenesis is a parallel process, that blocks of structured rRNA and proteins assemble cooperatively, and that the entire process is dynamic and can be "re-routed" through different pathways as needed. This work reveals the complex landscape of ribosome assembly in vivo and provides the requisite tools to characterize additional assembly pathways for ribosomes and other macromolecular machines.