How a neutral evolutionary ratchet can build cellular complexity

Complex cellular machines and processes are commonly believed to be products of selection, and it is typically understood to be the job of evolutionary biologists to show how selective advantage can account for each step in their origin and subsequent growth in complexity. Here, we describe how complex machines might instead evolve in the absence of positive selection through a process of "presuppression," first termed constructive neutral evolution (CNE) more than a decade ago. If an autonomously functioning cellular component acquires mutations that make it dependent for function on another, pre-existing component or process, and if there are multiple ways in which such dependence may arise, then dependence inevitably will arise and reversal to independence is unlikely. Thus, CNE is a unidirectional evolutionary ratchet leading to complexity, if complexity is equated with the number of components or steps necessary to carry out a cellular process. CNE can explain "functions" that seem to make little sense in terms of cellular economy, like RNA editing or splicing, but it may also contribute to the complexity of machines with clear benefit to the cell, like the ribosome, and to organismal complexity overall. We suggest that CNE-based evolutionary scenarios are in these and other cases less forced than the selectionist or adaptationist narratives that are generally told.     

Very different performance of the power Doppler modalities of several ultrasound machines ascertained by a microvessel flow phantom

Introduction

In many patients with rheumatoid arthritis (RA) subclinical disease activity can be detected with ultrasound (US), especially using power Doppler US (PDUS). However, PDUS may be highly dependent on the type of machine. This could create problems both in clinical trials and in daily clinical practice. To clarify how the PDUS signal differs between machines we created a microvessel flow phantom.

Methods

The flow phantom contained three microvessels (150, 1000, 2000 microns). A syringe pump was used to generate flows. Five US machines were used. Settings were optimised to assess the lowest detectable flow for each US machine.

Results

The minimal detectable flow velocities showed very large differences between the machines. Only two of the machines may be able to detect the very low flows in the capillaries of inflamed joints. There was no clear relation with price. One of the lower-end machines actually performed best in all three vessel sizes.

Conclusions

We created a flow phantom to test the sensitivity of US machines to very low flows in small vessels. The sensitivity of the power Doppler modalities of 5 different machines was very different. The differences found between the machines are probably caused by fundamental differences in processing of the PD signal or internal settings inaccessible to users. Machines considered for PDUS assessment of RA patients should be tested using a flow phantom similar to ours. Within studies, only a single machine type should be used.     

Single-molecule imaging and manipulation of biomolecular machines and systems

Background

Biological molecular machines support various activities and behaviors of cells, such as energy production, signal transduction, growth, differentiation, and migration.

Structural biology of cellular machines

Multi-component macromolecular machines contribute to all essential biological processes, from cell motility and signal transduction to information storage and processing. Structural analysis of assemblies at atomic resolution is emerging as the field of structural cell biology. Several recent studies, including those focused on the ribosome, the acrosomal bundle and bacterial flagella, have demonstrated the ability of a hybrid approach that combines imaging, crystallography and computational tools to generate testable atomic models of fundamental biological machines. A complete understanding of cellular and systems biology will require the detailed structural understanding of hundreds of biological machines. The realization of this goal demands a concerted effort to develop and apply new strategies for the systematic identification, isolation, structural characterization and mechanistic analysis of multi-component assemblies at all resolution ranges. The establishment of a database describing the structural and dynamic properties of protein assemblies will provide novel opportunities to define the molecular and atomic mechanisms controlling overall cell physiology.     

Predicting the coupling specificity of GPCRs to G-proteins by support vector machines

G-protein coupled receptors （GPCRs） represent one of the most important classes of drug targets for pharmaceutical industry and play important roles in cellular signal transduction. Predicting the coupling specificity of GPCRs to G-proteins is vital for further understanding the mechanism of signal transduction and the function of the receptors within a cell, which can provide new clues for pharmaceutical research and development. In this study, the features of amino acid compositions and physiochemical properties of the full-length GPCR sequences have been analyzed and extracted. Based on these features, classifiers have been developed to predict the coupling specificity of GPCRs to G-protelns using support vector machines. The testing results show that this method could obtain better prediction accuracy.     

Torsins: not your typical AAA+ ATPases

Abstract

Torsin ATPases (Torsins) belong to the widespread AAA+ (ATPases associated with a variety of cellular activities) family of ATPases, which share structural similarity but have diverse cellular functions. Torsins are outliers in this family because they lack many characteristics of typical AAA+ proteins, and they are the only members of the AAA+ family located in the endoplasmic reticulum and contiguous perinuclear space. While it is clear that Torsins have essential roles in many, if not all metazoans, their precise cellular functions remain elusive. Studying Torsins has significant medical relevance since mutations in Torsins or Torsin-associated proteins result in a variety of congenital human disorders, the most frequent of which is early-onset torsion (DYT1) dystonia, a severe movement disorder. A better understanding of the Torsin system is needed to define the molecular etiology of these diseases, potentially enabling corrective therapy. Here, we provide a comprehensive overview of the Torsin system in metazoans, discuss functional clues obtained from various model systems and organisms and provide a phylogenetic and structural analysis of Torsins and their regulatory cofactors in relation to disease-causative mutations. Moreover, we review recent data that have led to a dramatically improved understanding of these machines at a molecular level, providing a foundation for investigating the molecular defects underlying the associated movement disorders. Lastly, we discuss our ideas on how recent progress may be utilized to inform future studies aimed at determining the cellular role(s) of these atypical molecular machines and their implications for dystonia treatment options.     

The key to unlock the Hsp100/Clp protein degradation machines of Mycobacterium

Hsp100/Clp protease complexes are molecular machines important for cellular protein homeostasis and are concurrently embedded in the control of various signal transduction networks by regulatory proteolysis. In Mycobacteria, the genes encoding the components of these Hsp100/Clp protease complexes are essential for growth and were identified as targets for antibiotics, with a new antimicrobial mechanism, that are active on slow growing or even dormant cells. Schmitz and Sauer (2014) report the biochemical characterization of mycobacterial Hsp100/Clp protease complexes actively degrading folded substrate proteins. Their results suggest an unusual activation mechanism for this protease complex and will set the stage for further mechanistic studies of antibiotics acting on this new cellular target.     

Support vector machines for prediction of protein signal sequences and their cleavage sites

Given a nascent protein sequence, how can one predict its signal peptide or "Zipcode" sequence? This is an important problem for scientists to use signal peptides as a vehicle to find new drugs or to reprogram cells for gene therapy (see, e.g. K.C. Chou, Current Protein and Peptide Science 2002;3:615-22). In this paper, support vector machines (SVMs), a new machine learning method, is applied to approach this problem. The overall rate of correct prediction for 1939 secretary proteins and 1440 nonsecretary proteins was over 91%. It has not escaped our attention that the new method may also serve as a useful tool for further investigating many unclear details regarding the molecular mechanism of the ZIP code protein-sorting system in cells.     

心肌细胞肥大的信号转导通路

心肌肥厚是肥大刺激诱导核内基因异常表达的结果,细胞内信号转导通路是肥大刺激与核内基因转录活化的偶联环节。然而,淡同刺激诱导的心肌肥大可能具有不同的“分子表型”,这主要取决于它们启动的信号转导通路。对心肌肥大信号转导通路的深入认识,不仅胡助于阐明心肌肥厚的细胞分子机制,而且可为药物干预防治心肌肥厚提供新思路。     

Cellular signal transduction and the reversal of malignancy

Animal cells contain only a few defined molecular systems that transduce hormonal and growth signals from the external environment to the intracellular milieu to regulate cellular growth and differentiation. Among the most ubiquitous of these "second messenger" pathways are those utilizing cyclic AMP and phosphatidylinositide turnover. The former activates protein kinase A, while the latter leads to the activation of protein kinase C and mobilization of intracellular calcium. Lesions induced by oncogenes in signal transduction systems may be responsible for the cancerous transformation of cells. In many tumor cell lines, including some transformed by the ras and sis oncogenes, activation of protein kinase A by elevation of cyclic AMP or activation of protein kinase C by addition of phorbol esters can restore many normal aspects of growth and morphology. Such "reverse transformation" is accompanied by the phosphorylation of unique cellular proteins and alterations in the phosphoinositide cycle. Molecular mechanisms by which activation of signal transduction systems can attenuate the malignant phenotype are considered in the context of cellular growth and differentiation.     

A Probabilistic Model of Perception

The development of electronic computers has made it possible to transfer to them a number of the "intellectual" functions of man. At present such machines are being employed to model broader and broader regions of man's psychological activity. One of the most important problems in this connection is the building of "perceptive machines," such as reading machines, "the printing phonograph" and so forth. Perceptive machines are a necessary element in the development of automatic equipment to operate in complicated environments.     

A probabilistic view of immunology: drawing parallels with physics

Regulating the strength and class of an immune response requires lymphocytes to act as complex signal integrating "machines", taking information from multiple sources while making decisions that affect the final outcome. Describing and understanding the decision-making behaviour of lymphocytes within the context of the dynamic multifaceted immune system appears immensely complicated. In this article I contrast two alternative frameworks, the deterministic and the probabilistic as competing paths to achieve successful quantitative immune models. As the two alternatives are traditional scientific rivals, I use the probabilistic fields in physics to highlight the potential value of the probabilistic perspective in immunology.     

Reactive oxygen species in cell signaling

Reactive oxygen species (ROS) are generated as by-products of cellular metabolism, primarily in the mitochondria. When cellular production of ROS overwhelms its antioxidant capacity, damage to cellular macromolecules such as lipids, protein, and DNA may ensue. Such a state of "oxidative stress" is thought to contribute to the pathogenesis of a number of human diseases including those of the lung. Recent studies have also implicated ROS that are generated by specialized plasma membrane oxidases in normal physiological signaling by growth factors and cytokines. In this review, we examine the evidence for ligand-induced generation of ROS, its cellular sources, and the signaling pathways that are activated. Emerging concepts on the mechanisms of signal transduction by ROS that involve alterations in cellular redox state and oxidative modifications of proteins are also discussed.     

The exosome and RNA quality control in the nucleus

To control the quality of RNA biogenesis in the nucleus, cells use sophisticated molecular machines. These machines recognize and degrade not only RNA trimmings--the leftovers of RNA processing--but also incorrectly processed RNAs that contain defects. By using this mechanism, cells ensure that only high-quality RNAs are engaged in protein synthesis and other cellular processes. The exosome--a complex of several exoribonucleolytic and RNA-binding proteins--is the central 3'-end RNA degradation and processing factor in this surveillance apparatus. The exosome operates with auxiliary factors that stimulate its activity and recruit its RNA substrates in the crowded cellular environment. In this review, we discuss recent structural and functional data related to the nuclear quality-control apparatus, including the long-awaited structure of the human exosome and its activity.     

Anthony Hyman: from unlikely scientist to Royal Society Fellow. Interview by Ruth Williams

Hyman tinkers with cellular machines in his Dresden workshop     

New directions in incidence-dose modeling

Many cellular responses are quantal; that is, they either take place or they do not. Examples of "either-or" responses include cell replication, differentiation and apoptosis. Surprisingly, induction of suites of genes and coordinated phenotypic changes in cells are also often quantal, where embedded molecular circuitry creates on-off switches. Mechanistic incidence-dose (ID) models need to account for the quantal characteristics of cellular switches that contribute, in turn, to dose thresholds and to the incidence of biological responses in individuals. Interdisciplinary systems biology approaches create mechanistic ID models based on: (i) detailed knowledge of the cellular circuitry controlling signal transduction; (ii) evolving biological modeling tools describing cellular circuits and their perturbations by chemicals and (iii) high throughput, high coverage "omic" screens for examining cell signaling pathways and biological responses. These interdisciplinary approaches should produce novel, quantitative ID models for biological responses and greatly improve the biological basis of safety and risk assessments.     

Escherichia coli and its chromosome

The Escherichia coli chromosome is a circular DNA molecule that is approximately 1000 times compacted in the living cell, where it occupies approximately 15% of the cellular volume. The genome is organized in a way that facilitates chromosome maintenance and processing. Despite huge efforts, until recently little has been known about how the chromosome is organized within cells, where replication takes place, and how DNA is segregated before cell division. New techniques for labeling genetic loci and molecular machines are allowing the simultaneous tracking of genetic loci and such machines in living cells over time. These studies reveal remarkable organization, yet a highly dynamic flux of genetic loci and macromolecules. It seems likely that the cellular positioning of chromosomal loci is the outcome of the formation of two chromosome arms (replichores) by replication, followed by sequential chromosome segregation, rather than from the presence of cellular positioning markers.     

The cellular roles of molecular motors in fungi

Motors are molecular machines that move their cargo along F-actin or microtubules. Fungal representatives of myosin, kinesin and dynein motors support many cellular processes including polar growth, cell division and mitosis. Recent progress in understanding their cellular roles has revealed common principles. However, it has become obvious that fungi have also developed diverse strategies to cope with long-distance organelle transport.