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Mathematical and live meningococcal models for simple sequence repeat dynamics - coherent predictions and observations.

ABSTRACT: Evolvability by means of simple sequence repeat (SSR) instability is a feature under the constant influence of opposing selective pressures to expand and compress the repeat tract and is mechanistically influenced by factors that affect genetic instability. In addition to direct selection for protein expression and structural integrity, other factors that influence tract length evolution were studied. The genetic instability of SSRs that switch the expression of antibiotic resistance ON and OFF was modelled mathematically and monitored in a panel of live meningococcal strains. The mathematical model showed that the SSR length of a theoretical locus in an evolving population may be shaped by direct selection of expression status (ON or OFF), tract length dependent (?) and tract length independent factors (?). According to the model an increase in ? drives the evolution towards shorter tracts. An increase in ? drives the evolution towards a normal distribution of tract lengths given that an upper and a lower limit are set. Insertion and deletion biases were shown to skew allelic distributions in both directions. The meningococcal SSR model was tested in vivo by monitoring the frequency of spectinomycin resistance OFF?ON switching in a designed locus. The instability of a comprehensive panel of the homopolymeric SSRs, constituted of a range of 5-13 guanine nucleotides, was monitored in wildtype and mismatch repair deficient backgrounds. Both the repeat length itself and mismatch repair deficiency were shown to influence the genetic instability of the homopolymeric tracts. A possible insertion bias was observed in tracts ?G10. Finally, an inverse correlation between the number of tract-encoded amino acids and growth in the presence of ON-selection illustrated a limitation to SSR expansion in an essential gene associated with the designed model locus and the protein function mediating antibiotic resistance.

SUBMITTER: Alfsnes K

PROVIDER: S-EPMC4085013 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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Mathematical and live meningococcal models for simple sequence repeat dynamics - coherent predictions and observations.

Alfsnes Kristian K Raynaud Xavier X Tønjum Tone T Ambur Ole Herman OH

PloS one 20140707 7

Evolvability by means of simple sequence repeat (SSR) instability is a feature under the constant influence of opposing selective pressures to expand and compress the repeat tract and is mechanistically influenced by factors that affect genetic instability. In addition to direct selection for protein expression and structural integrity, other factors that influence tract length evolution were studied. The genetic instability of SSRs that switch the expression of antibiotic resistance ON and OFF ...[more]

PMID: 24999629

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Project description:BackgroundMicrosatellites, or simple sequence repeats (SSRs), are tandemly repeated DNA sequences, including tandem copies of specific sequences no longer than six bases, that are distributed in the genome. SSR has been used as a molecular marker because it is easy to detect and is used in a range of applications, including genetic diversity, genome mapping, and marker assisted selection. It is also very mutable because of slipping in the DNA polymerase during DNA replication. This unique mutation increases the insertion/deletion (INDELs) mutation frequency to a high ratio - more than other types of molecular markers such as single nucleotide polymorphism (SNPs).SNPs are more frequent than INDELs. Therefore, all designed algorithms for sequence alignment fit the vast majority of the genomic sequence without considering microsatellite regions, as unique sequences that require special consideration. The old algorithm is limited in its application because there are many overlaps between different repeat units which result in false evolutionary relationships.FindingsTo overcome the limitation of the aligning algorithm when dealing with SSR loci, a new algorithm was developed using PERL script with a Tk graphical interface. This program is based on aligning sequences after determining the repeated units first, and the last SSR nucleotides positions. This results in a shifting process according to the inserted repeated unit type.When studying the phylogenic relations before and after applying the new algorithm, many differences in the trees were obtained by increasing the SSR length and complexity. However, less distance between different linage had been observed after applying the new algorithm.ConclusionsThe new algorithm produces better estimates for aligning SSR loci because it reflects more reliable evolutionary relations between different linages. It reduces overlapping during SSR alignment, which results in a more realistic phylogenic relationship.

Project description:Upon infection of a new host, human immunodeficiency virus (HIV) replicates in the mucosal tissues and is generally undetectable in circulation for 1-2 weeks post-infection. Several interventions against HIV including vaccines and antiretroviral prophylaxis target virus replication at this earliest stage of infection. Mathematical models have been used to understand how HIV spreads from mucosal tissues systemically and what impact vaccination and/or antiretroviral prophylaxis has on viral eradication. Because predictions of such models have been rarely compared to experimental data, it remains unclear which processes included in these models are critical for predicting early HIV dynamics. Here we modified the "standard" mathematical model of HIV infection to include two populations of infected cells: cells that are actively producing the virus and cells that are transitioning into virus production mode. We evaluated the effects of several poorly known parameters on infection outcomes in this model and compared model predictions to experimental data on infection of non-human primates with variable doses of simian immunodifficiency virus (SIV). First, we found that the mode of virus production by infected cells (budding vs. bursting) has a minimal impact on the early virus dynamics for a wide range of model parameters, as long as the parameters are constrained to provide the observed rate of SIV load increase in the blood of infected animals. Interestingly and in contrast with previous results, we found that the bursting mode of virus production generally results in a higher probability of viral extinction than the budding mode of virus production. Second, this mathematical model was not able to accurately describe the change in experimentally determined probability of host infection with increasing viral doses. Third and finally, the model was also unable to accurately explain the decline in the time to virus detection with increasing viral dose. These results suggest that, in order to appropriately model early HIV/SIV dynamics, additional factors must be considered in the model development. These may include variability in monkey susceptibility to infection, within-host competition between different viruses for target cells at the initial site of virus replication in the mucosa, innate immune response, and possibly the inclusion of several different tissue compartments. The sobering news is that while an increase in model complexity is needed to explain the available experimental data, testing and rejection of more complex models may require more quantitative data than is currently available.

Project description:BackgroundMalaria has recently been identified as a candidate for global eradication. This process will take the form of a series of national eliminations. Key issues must be considered specifically for elimination strategy when compared to the control of disease. Namely the spread of drug resistance, data scarcity and the adverse effects of failed elimination attempts. Mathematical models of various levels of complexity have been produced to consider the control and elimination of malaria infection. If available, detailed data on malaria transmission (such as the vector life cycle and behaviour, human population behaviour, the acquisition and decay of immunity, heterogeneities in transmission intensity, age profiles of clinical and subclinical infection) can be used to populate complex transmission models that can then be used to design control strategy. However, in many malaria countries reliable data are not available and policy must be formed based on information like an estimate of the average parasite prevalence.MethodsA simple deterministic model, that requires data in the form of a single estimate of parasite prevalence as an input, is developed for the purpose of comparison with other more complex models. The model is designed to include key aspects of malaria transmission and integrated control.ResultsThe simple model is shown to have similar short-term dynamic behaviour to three complex models. The model is used to demonstrate the potential of alternative methods of delivery of controls. The adverse effects on clinical infection and spread of resistance are predicted for failed elimination attempts. Since elimination strategies present an increased risk of the spread of drug resistance, the model is used to demonstrate the population level protective effect of multiple controls against this very serious threat.ConclusionA simple model structure for the elimination of malaria is suitable for situations where data are sparse yet strategy design requirements are urgent with the caveat that more complex models, populated with new data, would provide more information, especially in the long-term.

Dataset Information

Mathematical and live meningococcal models for simple sequence repeat dynamics - coherent predictions and observations.

Publications

Mathematical and live meningococcal models for simple sequence repeat dynamics - coherent predictions and observations.

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