The AGT M235T (RS699, 4072T>C) polymorphism is not associated with elite weightlifting performance

It is now well established that genetic background influences an athlete’s ability to excel in different sport disciplines. Previous studies have demonstrated that among power athletes, single nucleotide polymorphism (SNP) in the AGT genotype (Thr-Thr), was significantly more prevalent among weightlifters compared to sprinters and jumpers indicating that despite the common features of these sport subtypes (short and very intense), they vary in their strength and speed abilities, as well as in their genetic make-up. The aim of the present study was to assess whether the AGT SNP can be used also to distinguish elite from national levels weightlifters. The AGT M235T genotype frequencies were assessed in 47 weightlifters (30 elite, 17 national level) and 86 non-athletes control. The Thr-Thr genotype was significantly higher among weightlifters (29.8%) compared to controls (12.8%) (p=0.048). Thr allele frequency was significantly higher among weightlifters (55.3%) compared to controls (37.8%) (p=0.021). However, there was no difference in the prevalence of the polymorphism between national level and elite athletes. In conclusion, the results suggest that the AGT polymorphism cannot predict elite competitive weightlifting performance

Practical uses of genetic profile assessment in athletic training – an illustrative case study

Recent studies suggested that several potential genes may explain athletic success. However, while genetic assessment will probably become part of future talent identification, at present, genetic testing predictive value is poor, mainly because athletic success depends on a combination of genetic, physiological, behavioral and environmental factors (including coaching, medical, nutritional, psychological, equipment, facilities and administrative aspects). However, one should consider genetic testing not only for talent identification or sport event selection, but also for possible assistance in the training process itself. In the present case study we show an example of potential practical use of genetic profile assessment for improving the athletic training process. We deliberately chose a case study of a national-level athlete to show that genetic aid should not be limited to top world-class athletes

Frequency of the IGF A/G rs7136446 polymorphism and athletic performance

Previous studies have shown that carrying the minor T allele of the IGF C-1245T polymorphism was associated with higher circulating IGF-I levels, greater muscle mass and improved power athletic performance. The aim of the present study was to assess the frequency distribution of another IGF-I single nucleotide polymorphism (SNP), the A/G rs7136446, among Israeli athletes. The IGF A/G rs7136446 polymorphism was determined in 185 short (n=72) and long-distance (n=113) runners, 94 short (n=44) and long-distance (n=50) swimmers, 54 weight-lifters and 111 controls. There were no significant differences in GG carriers, previously described as associated with higher maximal force production, between the athletes and controls. The only statistical significant difference in GG carriers was found between the sprinters (24%) and weight-lifters (9%; p<0.05). Although a single polymorphism cannot determine an athlete’s ability to succeed or fail in sports, the present findings suggest a potential importance of IGF-I polymorphisms mainly to power sports and in particular to speed sport performance

Prevalence of ACSL (rs6552828) polymorphism among runners

The ACSL A/G polymorphism is associated with endurance trainability. Previous studies have demonstrated that homozygotes of the minor AA allele had a reduced maximal oxygen consumption response to training compared to the common GG allele homozygotes, and that the ACSL A/G single nucleotide polymorphism explained 6.1% of the variance in the VO2max response to endurance training. The contribution of ACSL single nucleotide polymorphism to endurance trainability was shown in nonathletes, however, its potential role in professional athletes is not clear. Moreover, the genetic basis to anaerobic trainability is even less studied. Therefore, the aim of the present study was to examine the prevalence of ACSL single nucleotide polymorphism among professional Israeli long distance runners (n=59), middle distance runners (n=31), sprinters and jumpers (n=48) and non-athletic controls (n=60). The main finding of the present study was that the ACSL1 AA genotype, previously shown to be associated with reduced endurance trainability, was not higher among sprinters and jumpers (15%) compared to middle- (16%) and long-distance runners (15%). This suggests that in contrast to previous studies indicating that the ACSL1 single nucleotide polymorphism may influence endurance trainability among non-athletic individuals, the role of this polymorphism among professional athletes is still not clear

Changes in Aerobic and Anaerobic Performance Capabilities Following Different Interval-Training Programs

The aim of the study was to compare the effect of an increasing-distance interval-training program and a decreasing-distance interval-training program, matched for total distance, on aerobic and anaerobic performance capabilities. Forty physical education students were randomly assigned to either increasing- or decreasing-distance interval-training group (ITG and DTG), and completed two similar sets of tests before and after six weeks of training. One training program consisted of 100 – 200 – 300 – 400 – 500m running intervals, and the other 500 – 400 – 300 – 200 - 100m. While both training programs led to a significant improvement in 2000m run (ES = 0.02-0.68), the improvement in the DTG was significantly greater than in the ITG (18.3 ± 3.6 vs. 12.2 ± 3.2 %, p< 0.05). In addition, while both training programs led to a significant improvement in 300m run (ES = 0.25-0.73), the improvement in the DTG was significantly greater than in the ITG (21.1 ± 1.8 vs. 15.4 ± 1.1 %, p< 0.05). The findings indicate that beyond the significant positive effects of both training programs, the DTG showed significant superiority over the ITG in improving aerobic and anaerobic performance capabilities. Athletes should acknowledge that, in spite of identical total work, interval-training program might induce different physiological impacts if order of intervals is different

Dynamic Proteomics: a database for dynamics and localizations of endogenous fluorescently-tagged proteins in living human cells

Recent advances allow tracking the levels and locations of a thousand proteins in individual living human cells over time using a library of annotated reporter cell clones (LARC). This library was created by Cohen et al. to study the proteome dynamics of a human lung carcinoma cell-line treated with an anti-cancer drug. Here, we report the Dynamic Proteomics database for the proteins studied by Cohen et al. Each cell-line clone in LARC has a protein tagged with yellow fluorescent protein, expressed from its endogenous chromosomal location, under its natural regulation. The Dynamic Proteomics interface facilitates searches for genes of interest, downloads of protein fluorescent movies and alignments of dynamics following drug addition. Each protein in the database is displayed with its annotation, cDNA sequence, fluorescent images and movies obtained by the time-lapse microscopy. The protein dynamics in the database represents a quantitative trace of the protein fluorescence levels in nucleus and cytoplasm produced by image analysis of movies over time. Furthermore, a sequence analysis provides a search and comparison of up to 50 input DNA sequences with all cDNAs in the library. The raw movies may be useful as a benchmark for developing image analysis tools for individual-cell dynamic-proteomics. The database is available at http://www.dynamicproteomics.net/

Oscillations and variability in the p53 system

Understanding the dynamics and variability of protein circuitry requires accurate measurements in living cells as well as theoretical models. To address this, we employed one of the best-studied protein circuits in human cells, the negative feedback loop between the tumor suppressor p53 and the oncogene Mdm2. We measured the dynamics of fluorescently tagged p53 and Mdm2 over several days in individual living cells. We found that isogenic cells in the same environment behaved in highly variable ways following DNA-damaging gamma irradiation: some cells showed undamped oscillations for at least 3 days (more than 10 peaks). The amplitude of the oscillations was much more variable than the period. Sister cells continued to oscillate in a correlated way after cell division, but lost correlation after about 11 h on average. Other cells showed low-frequency fluctuations that did not resemble oscillations. We also analyzed different families of mathematical models of the system, including a novel checkpoint mechanism. The models point to the possible source of the variability in the oscillations: low-frequency noise in protein production rates, rather than noise in other parameters such as degradation rates. This study provides a view of the extensive variability of the behavior of a protein circuit in living human cells, both from cell to cell and in the same cell over time

Protein Dynamics in Individual Human Cells: Experiment and Theory

A current challenge in biology is to understand the dynamics of protein circuits in living human cells. Can one define and test equations for the dynamics and variability of a protein over time? Here, we address this experimentally and theoretically, by means of accurate time-resolved measurements of endogenously tagged proteins in individual human cells. As a model system, we choose three stable proteins displaying cell-cycle–dependant dynamics. We find that protein accumulation with time per cell is quadratic for proteins with long mRNA life times and approximately linear for a protein with short mRNA lifetime. Both behaviors correspond to a classical model of transcription and translation. A stochastic model, in which genes slowly switch between ON and OFF states, captures measured cell–cell variability. The data suggests, in accordance with the model, that switching to the gene ON state is exponentially distributed and that the cell–cell distribution of protein levels can be approximated by a Gamma distribution throughout the cell cycle. These results suggest that relatively simple models may describe protein dynamics in individual human cells

Protein Dynamics in Individual Human Cells: Experiment and Theory

A current challenge in biology is to understand the dynamics of protein circuits in living human cells. Can one define and test equations for the dynamics and variability of a protein over time? Here, we address this experimentally and theoretically, by means of accurate time-resolved measurements of endogenously tagged proteins in individual human cells. As a model system, we choose three stable proteins displaying cell-cycle–dependant dynamics. We find that protein accumulation with time per cell is quadratic for proteins with long mRNA life times and approximately linear for a protein with short mRNA lifetime. Both behaviors correspond to a classical model of transcription and translation. A stochastic model, in which genes slowly switch between ON and OFF states, captures measured cell–cell variability. The data suggests, in accordance with the model, that switching to the gene ON state is exponentially distributed and that the cell–cell distribution of protein levels can be approximated by a Gamma distribution throughout the cell cycle. These results suggest that relatively simple models may describe protein dynamics in individual human cells

Dynamic Proteomics of Individual Cancer Cells in Response to a Drug

Why do seemingly identical cells respond differently to a drug? To address this, we studied the dynamics and variability of the protein response of human cancer cells to a chemotherapy drug, camptothecin. We present a dynamic-proteomics approach that measures the levels and locations of nearly 1000 different endogenously tagged proteins in individual living cells at high temporal resolution. All cells show rapid translocation of proteins specific to the drug mechanism, including the drug target (topoisomerase-1), and slower, wide-ranging temporal waves of protein degradation and accumulation. However, the cells differ in the behavior of a subset of proteins. We identify proteins whose dynamics differ widely between cells, in a way that corresponds to the outcomes—cell death or survival. This opens the way to understanding molecular responses to drugs in individual cells