Toxin-mediated competition in weakly motile bacteria

Many bacterial species produce toxins that inhibit their competitors. We model this phenomenon by extending classic two-species Lotka-Volterra competition in one spatial dimension to incorporate toxin production by one species. Considering solutions comprising two adjacent single-species colonies, we show how the toxin inhibits the susceptible species near the interface between the two colonies. Moreover, a sufficiently effective toxin inhibits the susceptible species to such a degree that an `inhibition zone' is formed separating the two colonies. In the special case of truly non-motile bacteria, i.e. with zero bacterial diffusivity, we derive analytical expressions describing the bacterial distributions and size of the inhibition zone. In the more general case of weakly motile bacteria, i.e. small bacterial diffusivity, these two-colony solutions become travelling waves. We employ numerical methods to show that the wavespeed is dependent upon both interspecific competition and toxin strength; precisely which colony expands at the expense of the other depends upon the choice of parameter values. In particular, a sufficiently effective toxin allows the producer to expand at the expense of the susceptible, with a wavespeed magnitude that is bounded above as the toxin strength increases. This asymptotic wavespeed is independent of interspecific competition and due to the formation of the inhibition zone; when the colonies are thus separated, there is no longer direct competition between the two species and the producer can invade effectively unimpeded by its competitor. We note that the minimum toxin strength required to produce an inhibition zone increases rapidly with increasing bacterial diffusivity, suggesting that even moderately motile bacteria must produce very strong toxins if they are to benefit in this way

Climate change impact, adaptation, and mitigation in temperate grazing systems: a review

Managed temperate grasslands occupy 25% of the world, which is 70% of global agricultural land. These lands are an important source of food for the global population. This review paper examines the impacts of climate change on managed temperate grasslands and grassland-based livestock and effectiveness of adaptation and mitigation options and their interactions. The paper clarifies that moderately elevated atmospheric CO2 (eCO2) enhances photosynthesis, however it may be restiricted by variations in rainfall and temperature, shifts in plant’s growing seasons, and nutrient availability. Different responses of plant functional types and their photosynthetic pathways to the combined effects of climatic change may result in compositional changes in plant communities, while more research is required to clarify the specific responses. We have also considered how other interacting factors, such as a progressive nitrogen limitation (PNL) of soils under eCO2, may affect interactions of the animal and the environment and the associated production. In addition to observed and modelled declines in grasslands productivity, changes in forage quality are expected. The health and productivity of grassland-based livestock are expected to decline through direct and indirect effects from climate change. Livestock enterprises are also significant cause of increased global greenhouse gas (GHG) emissions (about 14.5%), so climate risk-management is partly to develop and apply effective mitigation measures. Overall, our finding indicates complex impact that will vary by region, with more negative than positive impacts. This means that both wins and losses for grassland managers can be expected in different circumstances, thus the analysis of climate change impact required with potential adaptations and mitigation strategies to be developed at local and regional levels

Treatment with AICAR inhibits blastocyst development, trophectodermdifferentiation and tight junction formation and function in mice

STUDY QUESTION: What is the impact of adenosine monophosphate-activated protein kinase (AMPK) activation on blastocyst formation, gene expression, and tight junction formation and function? SUMMARY ANSWER: AMPK activity must be tightly controlled for normal preimplantation development and blastocyst formation to occur. WHAT IS KNOWN ALREADY: AMPK isoforms are detectable in oocytes, cumulus cells and preimplantation embryos. Cultured embryos are subject to many stresses that can activate AMPK. STUDY DESIGN, SIZE, DURATION: Two primary experiments were carried out to determine the effect of AICAR treatment on embryo development and maintenance of the blastocoel cavity. Embryos were recovered from superovulated mice. First, 2-cell embryos were treated with a concentration series (0-2000 μM) of AICAR for 48 h until blastocyst formation would normally occur. In the second experiment, expanded mouse blastocysts were treated for 9 h with 1000 μM AICAR. PARTICIPANTS/MATERIALS, SETTING, METHODS: Outcomes measured included development to the blastocyst stage, cell number, blastocyst volume, AMPK phosphorylation, Cdx2 and blastocyst formation gene family expression (mRNAs and protein measured using quantitative RT-PCR, immunoblotting, immunofluorescence), tight junction function (FITC dextran dye uptake assay), and blastocyst ATP levels. The reversibility of AICAR treatment was assessed using Compound C (CC), a well-known inhibitor of AMPK, alone or in combination with AICAR. MAIN RESULTS AND THE ROLE OF CHANCE: Prolonged treatment with AICAR from the 2-cell stage onward decreases blastocyst formation, reduces total cell number, embryo diameter, leads to loss of trophectoderm cell contacts and membrane zona occludens-1 staining, and increased nuclear condensation. Treatment with CC alone inhibited blastocyst development only at concentrations that are higher than normally used. AICAR treated embryos displayed altered mRNA and protein levels of blastocyst formation genes. Treatment of blastocysts with AICAR for 9 h induced blastocyst collapse, altered blastocyst formation gene expression, increased tight junction permeability and decreased CDX2. Treated blastocysts displayed three phenotypes: those that were unaffected by treatment, those in which treatment was reversible, and those in which effects were irreversible. LARGE SCALE DATA: Not applicable. LIMITATIONS, REASONS FOR CAUTION: Our study investigates the effects of AICAR treatment on early development. While AICAR does increase AMPK activity and this is demonstrated in our study, AICAR is not a natural regulator of AMPK activity and some outcomes may result from off target non-AMPK AICAR regulated events. To support our results, blastocyst developmental outcomes were confirmed with two other well-known small molecule activators of AMPK, metformin and phenformin. WIDER IMPLICATIONS OF THE FINDINGS: Metformin, an AMPK activator, is widely used to treat type II diabetes and polycystic ovarian disorder (PCOS). Our results indicate that early embryonic AMPK levels must be tightly regulated to ensure normal preimplantation development. Thus, use of metformin should be carefully considered during preimplantation and early post-embryo transfer phases of fertility treatment cycles. STUDY FUNDING AND COMPETING INTEREST(S): Canadian Institutes of Health Research (CIHR) operating funds. There are no competing interests

Towards Robust Data-Driven Control Synthesis for Nonlinear Systems with Actuation Uncertainty

Modern nonlinear control theory seeks to endow systems with properties such as stability and safety, and has been deployed successfully across various domains. Despite this success, model uncertainty remains a significant challenge in ensuring that model-based controllers transfer to real world systems. This paper develops a data-driven approach to robust control synthesis in the presence of model uncertainty using Control Certificate Functions (CCFs), resulting in a convex optimization based controller for achieving properties like stability and safety. An important benefit of our framework is nuanced data-dependent guarantees, which in principle can yield sample-efficient data collection approaches that need not fully determine the input-to-state relationship. This work serves as a starting point for addressing important questions at the intersection of nonlinear control theory and non-parametric learning, both theoretical and in application. We validate the proposed method in simulation with an inverted pendulum in multiple experimental configurations

Guaranteeing Safety of Learned Perception Modules via Measurement-Robust Control Barrier Functions

Modern nonlinear control theory seeks to develop feedback controllers that endow systems with properties such as safety and stability. The guarantees ensured by these controllers often rely on accurate estimates of the system state for determining control actions. In practice, measurement model uncertainty can lead to error in state estimates that degrades these guarantees. In this paper, we seek to unify techniques from control theory and machine learning to synthesize controllers that achieve safety in the presence of measurement model uncertainty. We define the notion of a Measurement-Robust Control Barrier Function (MR-CBF) as a tool for determining safe control inputs when facing measurement model uncertainty. Furthermore, MR-CBFs are used to inform sampling methodologies for learning-based perception systems and quantify tolerable error in the resulting learned models. We demonstrate the efficacy of MR-CBFs in achieving safety with measurement model uncertainty on a simulated Segway system