The Energy Cost of Sitting versus Standing Naturally in Man.

PURPOSE: Prolonged sitting is a major health concern, targeted via government policy and the proliferation of height-adjustable workstations and wearable technologies to encourage standing. Such interventions have the potential to influence energy balance and thus facilitate effective management of body/fat mass. It is therefore remarkable that the energy cost of sitting versus standing naturally remains unknown. METHODS: Metabolic requirements were quantified via indirect calorimetry from expired gases in 46 healthy men and women (age, 27 ± 12 yr; mass, 79.3 ± 14.7 kg; body mass index, 24.7 ± 3.1 kg·m, waist/hip, 0.81 ± 0.06) under basal conditions (i.e., resting metabolic rate) and then, in a randomized and counterbalanced sequence, during lying, sitting and standing. Critically, no restrictions were placed on natural/spontaneous bodily movements (i.e., fidgeting) to reveal the fundamental contrast between sitting and standing in situ while maintaining a comfortable posture. RESULTS: The mean (95% confidence interval [CI]) increment in energy expenditure was 0.18 (95% CI, 0.06-0.31 kJ·min) from resting metabolic rate to lying was 0.15 (95% CI, 0.03-0.27 kJ·min) from lying to sitting and 0.65 (95% CI, 0.53-0.77 kJ·min) from sitting to standing. An ancillary observation was that the energy cost of each posture above basal metabolic requirements exhibited marked interindividual variance, which was inversely correlated with resting heart rate for all postures (r = -0.5; -0.7 to -0.1) and positively correlated with self-reported physical activity levels for lying (r = 0.4; 0.1 to 0.7) and standing (r = 0.6; 0.3-0.8). CONCLUSIONS: Interventions designed to reduce sitting typically encourage 30 to 120 min·d more standing in situ (rather than perambulation), so the 12% difference from sitting to standing reported here does not represent an effective strategy for the treatment of obesity (i.e., weight loss) but could potentially attenuate any continued escalation of the ongoing obesity epidemic at a population level.

Cell-free prediction of protein expression costs for growing cells.

Translating heterologous proteins places significant burden on host cells, consuming expression resources leading to slower cell growth and productivity. Yet predicting the cost of protein production for any given gene is a major challenge, as multiple processes and factors combine to determine translation efficiency. To enable prediction of the cost of gene expression in bacteria, we describe here a standard cell-free lysate assay that provides a relative measure of resource consumption when a protein coding sequence is expressed. These lysate measurements can then be used with a computational model of translation to predict the in vivo burden placed on growing E. coli cells for a variety of proteins of different functions and lengths. Using this approach, we can predict the burden of expressing multigene operons of different designs and differentiate between the fraction of burden related to gene expression compared to action of a metabolic pathway.

R2oDNA designer: computational design of biologically neutral synthetic DNA sequences.

R2oDNA Designer is a web application that stochastically generates orthogonal sets of synthetic DNA sequences designed to be biologically neutral. Biologically neutral sequences may be used for directing efficient DNA assembly by overlap-directed methods, as a negative control for functional DNA, as barcodes, or potentially as spacer regions to insulate biological parts from local context. The software creates optimized sequences using a Monte Carlo simulated annealing approach followed by the elimination of sequences homologous to host genomes and commonly used biological parts. An orthogonal set is finally determined by using a network elimination algorithm. Design constraints can be defined using either a web-based graphical user interface (GUI) or uploading a file containing a set of text commands.