DIFFERENCES IN RUNNING BIOMECHANICS OF ELITE SPRINTERS, NON-ELITE SPRINTERS AND NON-RUNNERS

The aim of the study was to investigate key predictors of fast sprinting. For this purpose, three groups of subjects were evaluated: elite sprinters, non-elite sprinters and non-runners. The analyzed groups consisted of 7, 9 and 11 subjects, respectively. Biomechanical running parameters were collected during the 30-meter acceleration up to maximum speed achievable by the subject. The obtained results revealed clear differences in running biomechanics among the all groups (contact time and step length normalised to body height). Also group results for «step length\u3ebody height» and «RSI\u3e1 showed, that the values of these parameters are available only for elite sprinters and non- elite sprinters groups. Date also showed step length normalised to body height to be a highly informative predictor of sprint performance (its correlation coefficient with maximum speed being 0.81)

Using expression arrays for copy number detection: an example from E. coli.

BACKGROUND: The sequencing of many genomes and tiling arrays consisting of millions of DNA segments spanning entire genomes have made high-resolution copy number analysis possible. Microarray-based comparative genomic hybridization (array CGH) has enabled the high-resolution detection of DNA copy number aberrations. While many of the methods and algorithms developed for the analysis microarrays have focused on expression analysis, the same technology can be used to detect genetic alterations, using for example standard commercial Affymetrix arrays. Due to the nature of the resultant data, standard techniques for processing GeneChip expression experiments are inapplicable. RESULTS: We have developed a robust and flexible methodology for high-resolution analysis of DNA copy number of whole genomes, using Affymetrix high-density expression oligonucleotide microarrays. Copy number is obtained from fluorescence signals after processing with novel normalization, spatial artifact correction, data transformation and deletion/duplication detection. We applied our approach to identify deleted and amplified regions in E. coli mutants obtained after prolonged starvation. CONCLUSION: The availability of Affymetrix expression chips for a wide variety of organisms makes the proposed array CGH methodology useful more generally.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

Dormant non-culturable Mycobacterium tuberculosis retains stable low-abundant mRNA

BACKGROUND: Dormant Mycobacterium tuberculosis bacilli are believed to play an important role in latent tuberculosis infection. Previously, we have demonstrated that cultivation of M. tuberculosis in K(+)-deficient medium resulted in generation of dormant cells. These bacilli were non-culturable on solid media (a key feature of dormant M. tuberculosis in vivo) and characterized by low metabolism and tolerance to anti-tuberculosis drugs. The dormant bacteria demonstrated a high potential to reactivation after K(+) reintroduction even after prolonged persistence under rifampicin. In this work, we studied the transcriptome and stability of transcripts in persisting dormant bacilli under arrest of mRNA de novo synthesis. RESULTS: RNA-seq-based analysis of the dormant non-culturable population obtained under rifampicin exposure revealed a 30–50-fold decrease of the total mRNA level, indicating global transcriptional repression. However, the analysis of persisting transcripts displayed a cohort of mRNA molecules coding for biosynthetic enzymes, proteins involved in adaptation and repair processes, detoxification, and control of transcription initiation. This ‘dormant transcriptome’ demonstrated considerable stability during M. tuberculosis persistence and mRNA de novo synthesis arrest. On the contrary, several small non-coding RNAs showed increased abundance on dormancy. Interestingly, M. tuberculosis entry into dormancy was accompanied by the cleavage of 23S ribosomal RNA at a specific point located outside the ribosome catalytic center. CONCLUSIONS: Dormant non-culturable M. tuberculosis bacilli are characterized by a global transcriptional repression. At the same time, the dormant bacilli retain low-abundant mRNAs, which are considerably stable during in vitro persistence, reflecting their readiness for translation upon early resuscitation steps. Increased abundance of non-coding RNAs on dormancy may indicate their role in the entry into and maintenance of M. tuberculosis dormant non-culturable state. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12864-015-2197-6) contains supplementary material, which is available to authorized users

Non-linear analysis of GeneChip arrays

The application of microarray hybridization theory to Affymetrix GeneChip data has been a recent focus for data analysts. It has been shown that the hyperbolic Langmuir isotherm captures the shape of the signal response to concentration of Affymetrix GeneChips. We demonstrate that existing linear fit methods for extracting gene expression measures are not well adapted for the effect of saturation resulting from surface adsorption processes. In contrast to the most popular methods, we fit background and concentration parameters within a single global fitting routine instead of estimating the background before obtaining gene expression measures. We describe a non-linear multi-chip model of the perfect match signal that effectively allows for the separation of specific and non-specific components of the microarray signal and avoids saturation bias in the high-intensity range. Multimodel inference, incorporated within the fitting routine, allows a quantitative selection of the model that best describes the observed data. The performance of this method is evaluated on publicly available datasets, and comparisons to popular algorithms are presented

Transcriptional profiling of MnSOD-mediated lifespan extension in Drosophila reveals a species-general network of aging and metabolic genes.

BACKGROUND: Several interventions increase lifespan in model organisms, including reduced insulin/insulin-like growth factor-like signaling (IIS), FOXO transcription factor activation, dietary restriction, and superoxide dismutase (SOD) over-expression. One question is whether these manipulations function through different mechanisms, or whether they intersect on common processes affecting aging. RESULTS: A doxycycline-regulated system was used to over-express manganese-SOD (MnSOD) in adult Drosophila, yielding increases in mean and maximal lifespan of 20%. Increased lifespan resulted from lowered initial mortality rate and required MnSOD over-expression in the adult. Transcriptional profiling indicated that the expression of specific genes was altered by MnSOD in a manner opposite to their pattern during normal aging, revealing a set of candidate biomarkers of aging enriched for carbohydrate metabolism and electron transport genes and suggesting a true delay in physiological aging, rather than a novel phenotype. Strikingly, cross-dataset comparisons indicated that the pattern of gene expression caused by MnSOD was similar to that observed in long-lived Caenorhabditis elegans insulin-like signaling mutants and to the xenobiotic stress response, thus exposing potential conserved longevity promoting genes and implicating detoxification in Drosophila longevity. CONCLUSION: The data suggest that MnSOD up-regulation and a retrograde signal of reactive oxygen species from the mitochondria normally function as an intermediate step in the extension of lifespan caused by reduced insulin-like signaling in various species. The results implicate a species-conserved net of coordinated genes that affect the rate of senescence by modulating energetic efficiency, purine biosynthesis, apoptotic pathways, endocrine signals, and the detoxification and excretion of metabolites.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

Explaining differences in saturation levels for Affymetrix GeneChip® arrays

The experimental spike-in studies of microarray hybridization conducted by Affymetrix demonstrate a nonlinear response of fluorescence intensity signal to target concentration. Several theoretical models have been put forward to explain these data. It was shown that the Langmuir adsorption isotherm recapitulates a general trend of signal response to concentration. However, this model fails to explain some key properties of the observed signal. In particular, according to the simple Langmuir isotherm, all probes should saturate at the same intensity level. However, this effect was not observed in the publicly available Affymetrix spike-in data sets. On the contrary, it was found that the saturation intensities vary greatly and can be predicted based on the probe sequence composition. In our experimental study, we attempt to account for the unexplained variation in the observed probe intensities using customized fluidics scripts. We explore experimentally the effect of the stringent wash, target concentration and hybridization time on the final microarray signal. The washing effect is assessed by scanning chips both prior to and after the stringent wash. Selective labeling of both specific and non-specific targets allows the visualization and investigation of the washing effect for both specific and non-specific signal components. We propose a new qualitative model of the probe-target hybridization mechanism that is in agreement with observed hybridization and washing properties of short oligonucleotide microarrays. This study demonstrates that desorption of incompletely bound targets during the washing cycle contributes to the observed difference in saturation levels

doi:10.1093/nar/gkl435 Non-linear analysis of GeneChip arrays

The application of microarray hybridization theory to Affymetrix GeneChip data has been a recent focus for data analysts. It has been shown that the hyperbolic Langmuir isotherm captures the shape of the signal response to concentration of Affymetrix GeneChips. We demonstrate that existing linear fit methods for extracting gene expression measures are not well adapted for the effect of saturation resulting from surface adsorption processes. In contrast to the most popular methods, we fit background and concentration parameters within a single global fitting routine instead of estimating the background before obtaining gene expression measures. We describe a non-linear multi-chip model of the perfect match signal that effectively allows for the separation of specific and non-specific components of the microarray signal and avoids saturation bias in the high-intensity range. Multimodel inference, incorporated within the fitting routine, allows a quantitative selection of the model that best describes the observed data. The performance of this method is evaluated on publicly available datasets, and comparisons to popular algorithms are presented