High-throughput glycomics: optimization of sample preparation.

Glycosylation affects structure, folding, and function of numerous proteins. Aberrant glycosylation has been shown to be associated with different diseases. A wide range of analytical methods is available for glycan analysis of antibodies (mainly IgG), but analysis of plasma glycans is less established due to additional challenges encountered with higher complexity of the sample. Here we describe development and optimization of a high-throughput sample preparation method for hydrophilic interaction liquid chromatography and ultra-performance liquid chromatography analysis of plasma N-glycans. Clean-up of labeled glycans was found to be the largest source of variation, and we tested cellulose, silica gel, Bio-Gel, and hydrophilic GHP filter as stationary phases for solid-phase extraction. All stationary phases were shown to be suitable for purification of labeled glycans, but GHP filter plate in combination with cold 96% acetonitrile had the highest reproducibility and was easiest to work with. The method was further optimized with Plackett-Burman screening design and validated in terms of analysis of major step variation and between-day and between-person variation. The developed method is fast, cost-effective, and easy to perform, and it has very good reproducibility during long period of time, enabling the detection of biological variability of the plasma N-glycome.

Sarcoidosis and tuberculosis in South Croatia: are there epidemiological similarities or not?

OBJECTIVE: Tuberculosis and sarcoidosis are chronic granulomatous diseases. Clinical, pathologic and immunologic aspects are similar although different. The authors were interested to highlight possible epidemiological similarities of these two granulomatous diseases. The objective of this study was to evaluate incidence rate as well as age, sex and geographic distribution of sarcoidosis in South Croatia and to compare it with these epidemiological characteristics of tuberculosis. STUDY DESIGN: Retrospective. METHODS: The study was including ten years follow up period (1997-2006), and was performed in Split-Dalmatia County, Croatia. All data were collected retrospectively and analyzed using Statistica 7 programme. RESULTS: The mean annual incidence of sarcoidosis was 3.3/100,000 inhabitants with a mean of 15,6 cases per year. Woman accounted for 61% of all sarcoidosis cases. The mean sarcoidosis patient age was 44.94 ± 11.85 years. The peak age group was 40-49 years (31%). Significant difference according to incidence rate on the islands comparing to the rates on the coast and the mainland was observed (P = 0.003). The mean sarcoidosis mortality rate was 1.2/100,000. Statistically significant differences between sarcoidosis and tuberculosis were observed according the higher number of tuberculosis patients (P < 0.000), among males (P < 0.000), and females, too (P < 0.000) as well as in mortality rates (P = 0.401). Significantly more patients had tuberculosis on the mainland (P < 0.000) and on the coast (P < 0.000), but not in the islands (P = 0.260). CONCLUSIONS: The results from this study showed dissimilarities in classic epidemiological patterns between sarcoidosis and tuberculosis, incidence rates, as well as sex and geographic distribution. Our findings resulted from this study might be starting point for the future epidemiological, genetic, and immunological studies.

Constraints on microbial metabolism drive evolutionary diversification in homogeneous environments.

Understanding the evolution of microbial diversity is an important and current problem in evolutionary ecology. In this paper, we investigated the role of two established biochemical trade-offs in microbial diversification using a model that connects ecological and evolutionary processes with fundamental aspects of biochemistry. The trade-offs that we investigated are as follows:(1) a trade-off between the rate and affinity of substrate transport; and (2) a trade-off between the rate and yield of ATP production. Our model shows that these biochemical trade-offs can drive evolutionary diversification under the simplest possible ecological conditions: a homogeneous environment containing a single limiting resource. We argue that the results of a number of microbial selection experiments are consistent with the predictions of our model.

Transmission rates and adaptive evolution of pathogens in sympatric heterogeneous plant populations.

Diversification in agricultural cropping patterns is widely practised to delay the build-up of virulent races that can overcome host resistance in pathogen populations. This can lead to balanced polymorphism, but the long-term consequences of this strategy for the evolution of crop pathogen populations are still unclear. The widespread occurrence of sibling species and reproductively isolated sub-species among fungal and oomycete plant pathogens suggests that evolutionary divergence is common. This paper develops a mathematical model of host-pathogen interactions using a simple framework of two hosts to analyse the influences of sympatric host heterogeneity on the long-term evolutionary behaviour of plant pathogens. Using adaptive dynamics, which assumes that sequential mutations induce small changes in pathogen fitness, we show that evolutionary outcomes strongly depend on the shape of the trade-off curve between pathogen transmission on sympatric hosts. In particular, we determine the conditions under which the evolutionary branching of a monomorphic into a dimorphic population occurs, as well as the conditions that lead to the evolution of specialist (single host range) or generalist (multiple host range) pathogen populations.

Spatial heterogeneity, social structure and disease dynamics of animal populations.

Social groupings, population dynamics and population movements of animals all give rise to spatio-temporal variations in population levels. These variations may be of crucial importance when considering the spread of infectious diseases since infection levels do not increase unless there is a sufficient pool of susceptible individuals. This paper explores the impact of social groupings on the potential for an endemic disease to develop in a spatially explicit model system. Analysis of the model demonstrates that the explicit inclusion of space allows asymmetry between groups to arise when this was not possible in the equivalent spatially homogeneous system. Moreover, differences in movement behaviours for susceptible and infected individuals gives rise to different spatial profiles for the populations. These profiles were not observed in previous work on an epidemic system. The results are discussed in an ecological context with reference to furious and dumb strains of infectious diseases.

Evolution of sibling fungal plant pathogens in relation to host specialization.

ABSTRACT Sibling plant pathogens can be grouped according to their host rangesthe following groups: group 1, sibling pathogens with nonoverlapping host ranges; group 2, sibling pathogens with both overlapping and nonoverlapping host ranges; and group 3, sibling pathogens with overlapping host ranges. Using the adaptive dynamics methodology, we investigated the evolution of sibling pathogens in relation to host specialization for groups 1 to 3. In particular, we focused on the role of multiple host niches and a trade-off in infectivity of pathogens to these hosts on the evolutionary outcome. We have shown that this ecological mechanism can explain only the evolution of sibling pathogens in group 1 and that other ecological and epidemiological mechanisms must be responsible for the evolution of sibling pathogens in the other two groups.

The effects of spatial movement and group interactions on disease dynamics of social animals.

The effects of spatial movements of infected and susceptible individuals on disease dynamics is not well understood. Empirical studies on the spatial spread of disease and behaviour of infected individuals are few and theoretical studies may be useful to explore different scenarios. Hence due to lack of detail in empirical studies, theoretical models have become necessary tools in investigating the disease influence in host-pathogen systems. In this paper we developed and analysed a spatially explicit model of two interacting social groups of animals of the same species. We investigated how the movement scenarios of susceptible and infected individuals together with the between-group contact parameter affect the survival rate of susceptible individuals in each group. This work can easily be applied to various host-pathogen systems. We define bounds on the number of susceptibles which avoid infection once the disease has died out as a function of the initial conditions and other model parameters. For example, once disease has passed through the populations, a larger diffusion coefficient for each group can result in higher population levels when there is no between-group interaction but in lower levels when there is between-group interaction. Numerical simulations are used to demonstrate these bounds and behaviours and to describe the different outcomes in ecological terms.