Despite years of study, it is still not clear how life emerged from inanimate matter and evolved into the complex forms that we observe today. One of the most recognized hypotheses for the origins of life, the RNA World hypothesis, assumes that life was sparked by prebiotic replicating RNA chains. In this paper, we address the problems caused by the interplay between hypothetical prebiotic RNA replicases and RNA parasitic species. We consider the coexistence of parasite RNAs and RNA replicases as well as the impact of parasites on the further evolution of replicases. For these purposes, we used multi-agent modeling techniques that allow for realistic assumptions regarding the movement and spatial interactions of modeled species. The general model used in this study is based on work by Takeuchi and Hogeweg. Our results confirm that the coexistence of parasite RNAs and replicases is possible in a spatially extended system, even if we take into consideration more realistic assumptions than Takeuchi and Hogeweg. However, we also showed that the presence of trade-off that takes into the account an RNA folding process could still pose a serious obstacle to the evolution of replication. We conclude that this might be a cause for one of the greatest transitions in life that took place early in evolution—the separation of the function between DNA templates and protein enzymes, with a central role for RNA species.

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Chronic kidney disease (CKD) is characterized by the progressive loss of functional nephrons. Although cardiovascular disease (CVD) complications and atherosclerosis are the leading causes of morbidity and mortality in CKD, the mechanism by which the progression of CVD accelerates remains unclear. To reveal the molecular mechanisms associated with atherosclerosis linked to CKD, we applied a shotgun lipidomics approach fortified with standard laboratory analytical methods and gas chromatography-mass spectrometry technique on selected lipid components and precursors to analyze the plasma lipidome in CKD and classical CVD patients. The MS-based lipidome profiling revealed the upregulation of triacylglycerols in CKD and downregulation of cholesterol/cholesteryl esters, sphingomyelins, phosphatidylcholines, phosphatidylethanolamines and ceramides as compared to CVD group and controls. We have further observed a decreased abundance of seven fatty acids in CKD with strong inter-correlation. In contrast, the level of glycerol was elevated in CKD in comparison to all analyzed groups. Our results revealed the putative existence of a functional causative link—the low cholesterol level correlated with lower estimated glomerular filtration rate and kidney dysfunction that supports the postulated “reverse epidemiology” theory and suggest that the lipidomic background of atherosclerosis-related to CKD is unique and might be associated with other cellular factors, i.e., inflammation.

BackgroundThe lack of a uniform way for qualitative and quantitative evaluation of vaccine candidates under development led us to set up a standardized scheme for vaccine efficacy and safety evaluation. We developed and implemented molecular and immunology methods, and designed support tools for immunization data storage and analyses. Such collection can create a unique opportunity for immunologists to analyse data delivered from their laboratories.ResultsWe designed and implemented GeVaDSs (Genetic Vaccine Decision Support system) an interactive system for efficient storage, integration, retrieval and representation of data. Moreover, GeVaDSs allows for relevant association and interpretation of data, and thus for knowledge-based generation of testable hypotheses of vaccine responses.ConclusionsGeVaDSs has been tested by several laboratories in Europe, and proved its usefulness in vaccine analysis. Case study of its application is presented in the additional files. The system is available at: http://gevads.cs.put.poznan.pl/preview/(login: viewer, password: password).

Determining amino acid sequences of protein molecules is one of the most important issues in molecular biology. These sequences determine protein structure and functionality. Unfortunately, direct biochemical methods for reading amino acid sequences can be used for reading short sequences only. This is the reason, which makes peptide assembly algorithms an important complement of these methods. In this paper, a genetic algorithm solving the problem of short amino acid sequence assembly is presented. The algorithm has been tested in computational experiment and compared with an existing tabu search method for the same problem. The results clearly show that the genetic algorithm outperformed the tabu search approach.