Memory shapes microbial populations

Correct decision making is fundamental for all living organisms to thrive under environmental changes. The patterns of environmental variation and the quality of available information define the most favourable strategy among multiple options, from randomly adopting a phenotypic state to sensing and reacting to environmental cues. Cellular memory—the ability to track and condition the time to switch to a different phenotypic state—can help withstand environmental fluctuations. How does memory manifest itself in unicellular organisms? We describe the population-wide consequences of phenotypic memory in microbes through a combination of deterministic modelling and stochastic simulations. Moving beyond binary switching models, our work highlights the need to consider a broader range of switching behaviours when describing microbial adaptive strategies. We show that memory in individual cells generates patterns at the population level coherent with overshoots and non-exponential lag times distributions experimentally observed in phenotypically heterogeneous populations. We emphasise the implications of our work in understanding antibiotic tolerance and, in general, bacterial survival under fluctuating environments

A common gene drive language eases regulatory process and eco-evolutionary extensions

Background Synthetic gene drive technologies aim to spread transgenic constructs into wild populations even when they impose organismal fitness disadvantages. The extraordinary diversity of plausible drive mechanisms and the range of selective parameters they may encounter makes it very difficult to convey their relative predicted properties, particularly where multiple approaches are combined. The sheer number of published manuscripts in this field, experimental and theoretical, the numerous techniques resulting in an explosion in the gene drive vocabulary hinder the regulators' point of view. We address this concern by defining a simplified parameter based language of synthetic drives. Results Employing the classical population dynamics approach, we show that different drive construct (replacement) mechanisms can be condensed and evaluated on an equal footing even where they incorporate multiple replacement drives approaches. Using a common language, it is then possible to compare various model properties, a task desired by regulators and policymakers. The generalization allows us to extend the study of the invasion dynamics of replacement drives analytically and, in a spatial setting, the resilience of the released drive constructs. The derived framework is available as a standalone tool. Conclusion Besides comparing available drive constructs, our tool is also useful for educational purpose. Users can also explore the evolutionary dynamics of future hypothetical combination drive scenarios. Thus, our results appraise the properties and robustness of drives and provide an intuitive and objective way for risk assessment, informing policies, and enhancing public engagement with proposed and future gene drive approaches

STELLA Facilitates Differentiation of Germ Cell and Endodermal Lineages of Human Embryonic Stem Cells

Stella is a developmentally regulated gene highly expressed in mouse embryonic stem (ES) cells and in primordial germ cells (PGCs). In human, the gene encoding the STELLA homologue lies on chromosome 12p, which is frequently amplified in long-term cultured human ES cells. However, the role played by STELLA in human ES cells has not been reported. In the present study, we show that during retinoic acid (RA)-induced differentiation of human ES cells, expression of STELLA follows that of VASA, a marker of germline differentiation. By contrast, human embryonal carcinoma cells express STELLA at a higher level compared with both karyotypically normal and abnormal human ES cell lines. We found that over-expression of STELLA does not interfere with maintenance of the stem cell state of human ES cells, but following retinoic acid induction it leads to up-regulation of germline- and endodermal-associated genes, whereas neural markers PAX6 and NEUROD1 are down-regulated. Further, STELLA over-expression facilitates the differentiation of human ES cells into BE12-positive cells, in which the expression of germline- and endodermal-associated genes is enriched, and suppresses differentiation of the neural lineage. Taken together, this finding suggests a role for STELLA in facilitating germline and endodermal differentiation of human ES cells

Mechanical behaviour of aluminium-lithium alloys

Aluminium-lithium alloys hold promise of providing a breakthrough response to the crying need for lightweight alloys for use as structurals in aerospace applications. Considerable worldwide research has gone into developing a range of these alloys over the last three decades. As a result, substantial understanding has been developed of the microstructure-based micromechanisms of strengthening, of fatigue and fracture as well as of anisotropy in mechanical properties. However, these alloys have not yet greatly displaced the conventionally used denser Al alloys on account of their poorer ductility, fracture toughness and low cycle fatigue resistance. This review aims to summarise the work pertaining to study of structure and mechanical properties with a view to indicate the directions that have been and can be pursued to overcome property limitations

FMEA and Fault Tree based Software Safety Analysis of a Railroad Crossing Critical System

Software for safety-critical systems must deal with the hazards identified by safety analysis in order to make the system safe, risk-free and fail-safe. Certain faults in critical systems can result in catastrophic consequences such as death, injury or environmental harm. The focus of this paper is an approach to software safety analysis based on a combination of two existing fault removal techniques. A comprehensive software safety analysis involving a combination of Failure Modes and Effects Analysis (FMEA) and Fault Tree Analysis (FTA) is conducted on the software functions of the critical system to identify potentially hazardous software faults. A prototype safety-critical system - Railroad Crossing Control System (RCCS), incorporating a microcontroller and software to operate the train on a track circuit is described

A Cyber Physical Systems Perspective on the Real-time and Reliable Dissemination of Information in Intelligent Transportation Systems

Timely and reliable dissemination of traffic-related information to drivers is a key property that intelligent transportation systems (ITS) should support. Numerous impediments stemming due to (a) physical factors, such as mobility and speed of vehicles, density of vehicles, characteristics of the wireless radio channel, and power and bit rate of radio transceivers, and (b) cyber issues, such as MAC layer access point associations and address resolutions (ARP), network layer addressing, routing and handoffs, and transport layer retransmissions lead to unpredictability in the timely and reliable dissemination of information to drivers. This paper presents compelling arguments in favor of new research directions in this area that are based on a cyber-physical systems (CPS) perspective. In particular, this paper makes three contributions. First, it considers a vehicle-centric perspective to survey and study the physics-and cyber-imposed impediments to the timely and reliable dissemination of information. Second, it presents a promising CPS solution to overcome a subset of the impediments discovered. Third, it outlines lessons learned indicating the need for more focused research and realistic testbeds. The evaluations 1 www.macrothink.org/npa Network Protocols and Algorithm

Stochastic slowdown in evolutionary processes

We examine birth--death processes with state dependent transition probabilities and at least one absorbing boundary. In evolution, this describes selection acting on two different types in a finite population where reproductive events occur successively. If the two types have equal fitness the system performs a random walk. If one type has a fitness advantage it is favored by selection, which introduces a bias (asymmetry) in the transition probabilities. How long does it take until advantageous mutants have invaded and taken over? Surprisingly, we find that the average time of such a process can increase, even if the mutant type always has a fitness advantage. We discuss this finding for the Moran process and develop a simplified model which allows a more intuitive understanding. We show that this effect can occur for weak but non--vanishing bias (selection) in the state dependent transition rates and infer the scaling with system size. We also address the Wright-Fisher model commonly used in population genetics, which shows that this stochastic slowdown is not restricted to birth-death processes.Comment: 8 pages, 3 figures, accepted for publicatio

Cellular hysteresis as a principle to maximize the efficacy of antibiotic therapy

Rapid evolution is central to the current antibiotic crisis. Sustainable treatments must thus take account of the bacteria’s potential for adaptation. We identified cellular hysteresis as a principle to constrain bacterial evolution. Cellular hysteresis is a persistent change in bacterial physiology, reminiscent of cellular memory, which is induced by one antibiotic and enhances susceptibility toward another antibiotic. Cellular hysteresis increases bacterial extinction in fast sequential treatments and reduces selection of resistance by favoring responses specific to the induced physiological effects. Fast changes between antibiotics are key, because they create the continuously high selection conditions that are difficult to counter by bacteria. Our study highlights how an understanding of evolutionary processes can help to outsmart human pathogens.Antibiotic resistance has become one of the most dramatic threats to global health. While novel treatment options are urgently required, most attempts focus on finding new antibiotic substances. However, their development is costly, and their efficacy is often compromised within short time periods due to the enormous potential of microorganisms for rapid adaptation. Here, we developed a strategy that uses the currently available antibiotics. Our strategy exploits cellular hysteresis, which is the long-lasting, transgenerational change in cellular physiology that is induced by one antibiotic and sensitizes bacteria to another subsequently administered antibiotic. Using evolution experiments, mathematical modeling, genomics, and functional genetic analysis, we demonstrate that sequential treatment protocols with high levels of cellular hysteresis constrain the evolving bacteria by (i) increasing extinction frequencies, (ii) reducing adaptation rates, and (iii) limiting emergence of multidrug resistance. Cellular hysteresis is most effective in fast sequential protocols, in which antibiotics are changed within 12 h or 24 h, in contrast to the less frequent changes in cycling protocols commonly implemented in hospitals. We found that cellular hysteresis imposes specific selective pressure on the bacteria that disfavors resistance mutations. Instead, if bacterial populations survive, hysteresis is countered in two distinct ways, either through a process related to antibiotic tolerance or a mechanism controlled by the previously uncharacterized two-component regulator CpxS. We conclude that cellular hysteresis can be harnessed to optimize antibiotic therapy, to achieve both enhanced bacterial elimination and reduced resistance evolution