Muscling in on microarrays

Effects of Training Status and Exercise Mode on Global Gene Expression in Skeletal Muscle

The aim of this study was to investigate differences in skeletal muscle gene expression of highly trained endurance and strength athletes in comparison to untrained individuals at rest and in response to either an acute bout of endurance or strength exercise. Endurance (ET, n = 8, VO₂max 67 ± 9 mL/kg/min) and strength athletes (ST, n = 8, 5.8 ± 3.0 training years) as well as untrained controls (E-UT and S-UT, each n = 8) performed an acute endurance or strength exercise test. One day before testing (Pre), 30 min (30'Post) and 3 h (180'Post) afterwards, a skeletal muscle biopsy was obtained from the m. vastus lateralis. Skeletal muscle mRNA was isolated and analyzed by Affymetrix-microarray technology. Pathway analyses were performed to evaluate the effects of training status (trained vs. untrained) and exercise mode-specific (ET vs. ST) transcriptional responses. Differences in global skeletal muscle gene expression between trained and untrained were smaller compared to differences in exercise mode. Maximum differences between ET and ST were found between Pre and 180'Post. Pathway analyses showed increased expression of exercise-related genes, such as nuclear transcription factors (NR4A family), metabolism and vascularization (PGC1-α and VEGF-A), and muscle growth/structure (myostatin, IRS1/2 and HIF1-α. The most upregulated genes in response to acute endurance or strength exercise were the NR4A genes (NR4A1, NR4A2, NR4A3). The mode of acute exercise had a significant effect on transcriptional regulation Pre vs. 180'Post. In contrast, the effect of training status on human skeletal muscle gene expression profiles was negligible compared to strength or endurance specialization. The highest variability in gene expression, especially for the NR4A-family, was observed in trained individuals at 180'Post. Assessment of these receptors might be suitable to obtain a deeper understanding of skeletal muscle adaptive processes to develop optimized training strategies.

Assessing the Role of Muscle Protein Breakdown in Response to Nutrition and Exercise in Humans

Muscle protein breakdown (MPB) is an important metabolic component of muscle remodeling, adaptation to training, and increasing muscle mass. Degradation of muscle proteins occurs via the integration of three main systems—autophagy and the calpain and ubiquitin-proteasome systems. These systems do not operate independently, and the regulation is complex. Complete degradation of a protein requires some combination of the systems. Determination of MPB in humans is technically challenging, leading to a relative dearth of information. Available information on the dynamic response of MPB primarily comes from stable isotopic methods with expression and activity measures providing complementary information. It seems clear that resistance exercise increases MPB, but not as much as the increase in muscle protein synthesis. Both hyperaminoacidemia and hyperinsulinemia inhibit the post-exercise response of MPB. Available data do not allow a comprehensive examination of the mechanisms behind these responses. Practical nutrition recommendations for interventions to suppress MPB following exercise are often made. However, it is likely that some degree of increased MPB following exercise is an important component for optimal remodeling. At this time, it is not possible to determine the impact of nutrition on any individual muscle protein. Thus, until we can develop and employ better methods to elucidate the role of MPB following exercise and the response to nutrition, recommendations to optimize post exercise nutrition should focus on the response of muscle protein synthesis. The aim of this review is to provide a comprehensive examination of the state of knowledge, including methodological considerations, of the response of MPB to exercise and nutrition in humans.

Effects of sample size on differential gene expression, rank order and prediction accuracy of a gene signature

Top differentially expressed gene lists are often inconsistent between studies and it has been suggested that small sample sizes contribute to lack of reproducibility and poor prediction accuracy in discriminative models. We considered sex differences (69♂, 65♀) in 134 human skeletal muscle biopsies using DNA microarray. The full dataset and subsamples (n = 10 (5♂, 5♀) to n = 120 (60♂, 60♀)) thereof were used to assess the effect of sample size on the differential expression of single genes, gene rank order and prediction accuracy. Using our full dataset (n = 134), we identified 717 differentially expressed transcripts (p<0.0001) and we were able predict sex with ∼90% accuracy, both within our dataset and on external datasets. Both p-values and rank order of top differentially expressed genes became more variable using smaller subsamples. For example, at n = 10 (5♂, 5♀), no gene was considered differentially expressed at p<0.0001 and prediction accuracy was ∼50% (no better than chance). We found that sample size clearly affects microarray analysis results; small sample sizes result in unstable gene lists and poor prediction accuracy. We anticipate this will apply to other phenotypes, in addition to sex.

Immune response and mitochondrial metabolism are commonly deregulated in DMD and aging skeletal muscle

Duchenne Muscular Dystrophy (DMD) is a complex process involving multiple pathways downstream of the primary genetic insult leading to fatal muscle degeneration. Aging muscle is a multifactorial neuromuscular process characterized by impaired muscle regeneration leading to progressive atrophy. We hypothesized that these chronic atrophying situations may share specific myogenic adaptative responses at transcriptional level according to tissue remodeling. Muscle biopsies from four young DMD and four AGED subjects were referred to a group of seven muscle biopsies from young subjects without any neuromuscular disorder and explored through a dedicated expression microarray. We identified 528 differentially expressed genes (out of 2,745 analyzed), of which 328 could be validated by an exhaustive meta-analysis of public microarray datasets referring to DMD and Aging in skeletal muscle. Among the 328 validated co-expressed genes, 50% had the same expression profile in both groups and corresponded to immune/fibrosis responses and mitochondrial metabolism. Generalizing these observed meta-signatures with large compendia of public datasets reinforced our results as they could be also identified in other pathological processes and in diverse physiological conditions. Focusing on the common gene signatures in these two atrophying conditions, we observed enrichment in motifs for candidate transcription factors that may coordinate either the immune/fibrosis responses (ETS1, IRF1, NF1) or the mitochondrial metabolism (ESRRA). Deregulation in their expression could be responsible, at least in part, for the same transcriptome changes initiating the chronic muscle atrophy. This study suggests that distinct pathophysiological processes may share common gene responses and pathways related to specific transcription factors.

Human papilloma virus strain detection utilising custom-designed oligonucleotide microarrays

Within the past 15 years, the utilisation of microarray technology for the detection of specific pathogen strains has increased rapidly. Presently, it is possible to simply purchase a pre-manufactured "off the shelf " oligonucleotide microarray bearing a wide variety of known signature DNA sequences previously identified in the organism being studied. Consequently, a hybridisation analysis may be used to pinpoint which strain/s is present in any given clinical sample. However, there exists a problem if the study necessitates the identification of novel sequences which are not represented in commercially available microarray chips. Ideally, such investigations require an in situ oligonucleotide microarray platform with the capacity to synthesise microarrays bearing probe sequences designed solely by the researcher. This chapter will focus on the employment of the Combimatrix® B3 CustomArray™ for the synthesis of reusable, bespoke microarrays for the purpose of discerning multiple Human Papilloma Virus strains.