Proton and cadmium adsorption by the archaeon Thermococcus zilligii: Generalising the contrast between thermophiles and mesophiles as sorbents

Adsorption by microorganisms can play a significant role in the fate and transport of metals in natural systems. Surface complexation models (SCMs) have been applied extensively to describe metal adsorption by mesophilic bacteria, and several recent studies have extended this framework to thermophilic bacteria. We conduct acid-base titrations and batch experiments to characterise proton and Cd adsorption onto the thermophilic archaeon Thermococcus zilligii. The experimental data and the derived SCMs indicate that the archaeon displays significantly lower overall sorption site density compared to previously studied thermophilic bacteria such Anoxybacillus flavithermus, Geobacillus stearothermophilus, G. thermocatenulatus, and Thermus thermophilus. The thermophilic bacteria and archaea display lower sorption site densities than the mesophilic microorganisms that have been studied to date, which points to a general pattern of total concentration of cell wall adsorption sites per unit biomass being inversely correlated to growth temperature

Single-cell protein dynamics reproduce universal fluctuations in cell populations

Protein variability in single cells has been studied extensively in populations, but little is known about temporal protein fluctuations in a single cell over extended times. We present here traces of protein copy number measured in individual bacteria over multiple generations and investigate their statistical properties, comparing them to previously measured population snapshots. We find that temporal fluctuations in individual traces exhibit the same universal features as those previously observed in populations. Scaled fluctuations around the mean of each trace exhibit the same universal distribution shape as found in populations measured under a wide range of conditions and in two distinct microorganisms. Additionally, the mean and variance of the traces over time obey the same quadratic relation. Analyzing the temporal features of the protein traces in individual cells, reveals that within a cell cycle protein content increases as an exponential function with a rate that varies from cycle to cycle. This leads to a compact description of the protein trace as a 3-variable stochastic process - the exponential rate, the cell-cycle duration and the value at the cycle start - sampled once each cell cycle. This compact description is sufficient to preserve the universal statistical properties of the protein fluctuations, namely, the protein distribution shape and the quadratic relationship between variance and mean. Our results show that the protein distribution shape is insensitive to sub-cycle intracellular microscopic details and reflects global cellular properties that fluctuate between generations

Calculation of disease dynamics in a population of households

Early mathematical representations of infectious disease dynamics assumed a single, large, homogeneously mixing population. Over the past decade there has been growing interest in models consisting of multiple smaller subpopulations (households, workplaces, schools, communities), with the natural assumption of strong homogeneous mixing within each subpopulation, and weaker transmission between subpopulations. Here we consider a model of SIRS (susceptible-infectious-recovered-suscep​tible) infection dynamics in a very large (assumed infinite) population of households, with the simplifying assumption that each household is of the same size (although all methods may be extended to a population with a heterogeneous distribution of household sizes). For this households model we present efficient methods for studying several quantities of epidemiological interest: (i) the threshold for invasion; (ii) the early growth rate; (iii) the household offspring distribution; (iv) the endemic prevalence of infection; and (v) the transient dynamics of the process. We utilize these methods to explore a wide region of parameter space appropriate for human infectious diseases. We then extend these results to consider the effects of more realistic gamma-distributed infectious periods. We discuss how all these results differ from standard homogeneous-mixing models and assess the implications for the invasion, transmission and persistence of infection. The computational efficiency of the methodology presented here will hopefully aid in the parameterisation of structured models and in the evaluation of appropriate responses for future disease outbreaks

Distinct forms of synaptic inhibition and neuromodulation regulate calretinin positive neuron excitability in the spinal cord dorsal horn

The dorsal horn (DH) of the spinal cord contains a heterogenous population of neurons that process incoming sensory signals before information ascends to the brain. We have recently characterized calretinin-expressing (CR+) neurons in the DH and shown that they can be divided into excitatory and inhibitory subpopulations. The excitatory population receives high-frequency excitatory synaptic input and expresses delayed firing action potential discharge, whereas the inhibitory population receives weak excitatory drive and exhibits tonic or initial bursting discharge. Here, we characterize inhibitory synaptic input and neuromodulation in the two CR+ populations, in order to determine how each is regulated. We show that excitatory CR+ neurons receive mixed inhibition from GABAergic and glycinergic sources, whereas inhibitory CR+ neurons receive inhibition, which is dominated by glycine. Noradrenaline and serotonin produced robust outward currents in excitatory CR+ neurons, predicting an inhibitory action on these neurons, but neither neuromodulator produced a response in CR+ inhibitory neurons. In contrast, enkephalin (along with selective mu and delta opioid receptor agonists) produced outward currents in inhibitory CR+ neurons, consistent with an inhibitory action but did not affect the excitatory CR+ population. Our findings show that the pharmacology of inhibitory inputs and neuromodulator actions on CR+ cells, along with their excitatory inputs can define these two subpopulations further, and this could be exploited to modulate discrete aspects of sensory processing selectively in the DH

Modeling Infection with Multi-agent Dynamics

Developing the ability to comprehensively study infections in small populations enables us to improve epidemic models and better advise individuals about potential risks to their health. We currently have a limited understanding of how infections spread within a small population because it has been difficult to closely track an infection within a complete community. The paper presents data closely tracking the spread of an infection centered on a student dormitory, collected by leveraging the residents' use of cellular phones. The data are based on daily symptom surveys taken over a period of four months and proximity tracking through cellular phones. We demonstrate that using a Bayesian, discrete-time multi-agent model of infection to model real-world symptom reports and proximity tracking records gives us important insights about infec-tions in small populations

Low Surface Brightness Galaxies in the SDSS: the link between environment, star-forming properties and AGN

Using the Sloan Digital Sky Survey (SDSS) data release 4 (DR 4), we investigate the spatial distribution of low and high surface brightness galaxies (LSBGs and HSBGs, respectively). In particular, we focus our attention on the influence of interactions between galaxies on the star formation strength in the redshift range $0.01 < z < 0.1$. With cylinder counts and projected distance to the first and fifth-nearest neighbor as environment tracers, we find that LSBGs tend to have a lack of companions compared to HSBGs at small scales ($<2$ Mpc). Regarding the interactions, we have evidence that the fraction of LSBGs with strong star formation activity increases when the distance between pairs of galaxies ($r_{p}$) is smaller than about four times the Petrosian radius ($r_{90}$) of one of the components. Our results suggest that, rather than being a condition for their formation, the isolation of LSBGs is more connected with their survival and evolution. The effect of the interaction on the star formation strength, measured by the average value of the birthrate parameter $b$, seems to be stronger for HSBGs than for LSBGs. The analysis of our population of LSBGs and HSBGs hosting an AGN show that, regardless of the mass range, the fraction of LSBGs having an AGN is lower than the corresponding fraction of HSBGs with an AGN. Also, we observe that the fraction of HSBGs and LSBGs having an AGN increases with the bulge luminosity. These results, and those concerning the star-forming properties of LSBGs as a function of the environment, fit with the scenario proposed by some authors where, below a given threshold of surface mass density, low surface brightness disks are unable to propagate instabilities, preventing the formation and evolution of massive black holes in the centers of LSBGs.Comment: 33 pages, 13 Figures, 2 Tables. Accepted for publication in The Astrophysical Journal (January 2011 Issue