Targeting mTOR with rapamycin: One dose does not fit all

A puzzling aspect of rapamycin-based therapeutic strategies is the wide disparity in the doses needed to suppress mTOR under different circumstances. A recent study revealing mechanistically how rapamycin suppresses mTOR provides two explanations for the differential sensitivities to rapamycin. First, mTOR exists as two functionally distinct complexes (mTORC1 and mTORC2), and while rapamycin suppresses both, it does so at very different concentrations. Whereas mTORC1 is suppressed by concentrations of rapamycin in the low nM range, mTORC2 generally requires low μM concentrations. Second, the efficacy of rapamycin is dependent on the level of phosphatidic acid (PA), which is required for the assembly of both mTORC1 and mTORC2 complexes. Rapamycin interacts with mTOR in a manner that is competitive with PA. Therefore, elevated levels of PA, which is common in cancer cells, increases the level of rapamycin needed to suppress both mTORC1 and mTORC2. A practical outcome of the recent study is that if PA levels are suppressed, mTORC2 becomes sensitive to concentrations of rapamycin that can be achieved clinically. Since mTORC2 is likely more critical for survival signals in cancer cells, the recent findings suggest new strategies for enhancing the efficacy of rapamycin-based therapeutic approaches in cancer cells.     

One size does not fit all: variation in thermal eco-physiology among Pacific salmonids

Reviews in Fish Biology and Fisheries - Pacific salmonids, cold-water fishes native to the northern hemisphere, span a massive geographic range (~?33° latitude) and are exposed to a wide...     

Metabolic equivalent: one size does not fit all.

The metabolic equivalent (MET) is a widely used physiological concept that represents a simple procedure for expressing energy cost of physical activities as multiples of resting metabolic rate (RMR). The value equating 1 MET (3.5 ml O2 x kg(-1) x min(-1) or 1 kcal x kg(-1) x h(-1)) was first derived from the resting O2 consumption (VO2) of one person, a 70-kg, 40-yr-old man. Given the extensive use of MET levels to quantify physical activity level or work output, we investigated the adequacy of this scientific convention. Subjects consisted of 642 women and 127 men, 18-74 yr of age, 35-186 kg in weight, who were weight stable and healthy, albeit obese in some cases. RMR was measured by indirect calorimetry using a ventilated hood system, and the energy cost of walking on a treadmill at 5.6 km/h was measured in a subsample of 49 men and 49 women (26-45 kg/m2; 29-47 yr). Average VO2 and energy cost corresponding with rest (2.6 +/- 0.4 ml O2 x kg(-1) x min(-1) and 0.84 +/- 0.16 kcal x kg(-1) x h(-1), respectively) were significantly lower than the commonly accepted 1-MET values of 3.5 ml O2 x kg(-1) x min(-1) and 1 kcal x kg(-1) x h(-1), respectively. Body composition (fat mass and fat-free mass) accounted for 62% of the variance in resting VO2 compared with age, which accounted for only 14%. For a large heterogeneous sample, the 1-MET value of 3.5 ml O2 x kg(-1) x min(-1) overestimates the actual resting VO2 value on average by 35%, and the 1-MET of 1 kcal/h overestimates resting energy expenditure by 20%. Using measured or predicted RMR (ml O2 x kg(-1) x min(-1) or kcal x kg(-1) x h(-1)) as a correction factor can appropriately adjust for individual differences when estimating the energy cost of moderate intensity walking (5.6 km/h).     

One size does not fit all: flexible models are required to understand animal movement across scales

1. Large data sets containing precise movement data from free-roaming animals are now becoming commonplace. One means of analysing individual movement data is through discrete, random walk-based models. 2. Random walk models are easily modified to incorporate common features of animal movement, and the ways that these modifications affect the scaling of net displacement are well studied. Recently, ecologists have begun to explore more complex statistical models with multiple latent states, each of which are characterized by a distribution of step lengths and have their own unimodal distribution of turning angles centred on one type of turn (e.g. reversals). 3. Here, we introduce the compound wrapped Cauchy distribution, which allows for multimodal distributions of turning angles within a single state. When used as a single state model, the parameters provide a straightforward summary of the relative contributions of different turn types. The compound wrapped Cauchy distribution can also be used to build multiple state models. 4. We hypothesize that a multiple state model with unimodal distributions of turning angles will best describe movement at finer resolutions, while a multiple state model using our multimodal distribution will better describe movement at intermediate temporal resolutions. At coarser temporal resolutions, a single state model using our multimodal distribution should be sufficient. We parameterize and compare the performance of these models at four different temporal resolutions (1, 4, 12 and 24 h) using data from eight individuals of Loxodonta cyclotis and find support for our hypotheses. 5. We assess the efficacy of the different models in extrapolating to coarser temporal resolution by comparing properties of data simulated from the different models to the properties of the observed data. At coarser resolutions, simulated data sets recreate many aspects of the observed data; however, only one of the models accurately predicts step length, and all models underestimate the frequency of reversals. 6. The single state model we introduce may be adequate to describe movement data at many resolutions and can be interpreted easily. Multiscalar analyses of movement such as the ones presented here are a useful means of identifying inconsistencies in our understanding of movement.     

One size does not fit all: On how Markov model order dictates performance of genomic sequence analyses

The structural simplicity and ability to capture serial correlations make Markov models a popular modeling choice in several genomic analyses, such as identification of motifs, genes and regulatory elements. A critical, yet relatively unexplored, issue is the determination of the order of the Markov model. Most biological applications use a predetermined order for all data sets indiscriminately. Here, we show the vast variation in the performance of such applications with the order. To identify the ‘optimal’ order, we investigated two model selection criteria: Akaike information criterion and Bayesian information criterion (BIC). The BIC optimal order delivers the best performance for mammalian phylogeny reconstruction and motif discovery. Importantly, this order is different from orders typically used by many tools, suggesting that a simple additional step determining this order can significantly improve results. Further, we describe a novel classification approach based on BIC optimal Markov models to predict functionality of tissue-specific promoters. Our classifier discriminates between promoters active across 12 different tissues with remarkable accuracy, yielding 3 times the precision expected by chance. Application to the metagenomics problem of identifying the taxum from a short DNA fragment yields accuracies at least as high as the more complex mainstream methodologies, while retaining conceptual and computational simplicity.     

Quality control for unfolded proteins at the plasma membrane

Cellular protein homeostasis profoundly depends on the disposal of terminally damaged polypeptides. To demonstrate the operation and elucidate the molecular basis of quality control of conformationally impaired plasma membrane (PM) proteins, we constructed CD4 chimeras containing the wild type or a temperature-sensitive bacteriophage λ domain in their cytoplasmic region. Using proteomic, biochemical, and genetic approaches, we showed that thermal unfolding of the λ domain at the PM provoked the recruitment of Hsp40/Hsc70/Hsp90 chaperones and the E2-E3 complex. Mixed-chain polyubiquitination, monitored by bioluminescence resonance energy transfer and immunoblotting, is responsible for the nonnative chimera-accelerated internalization, impaired recycling, and endosomal sorting complex required for transport-dependent lysosomal degradation. A similar paradigm prevails for mutant dopamine D4.4 and vasopressin V2 receptor removal from the PM. These results outline a peripheral proteostatic mechanism in higher eukaryotes and its potential contribution to the pathogenesis of a subset of conformational diseases.     

Monensin does not prevent recycling of plasma membrane glycoconjugates

Plasma membrane glycoconjugates, internalized during fluid-phase pinocytosis in the macrophage cell line, P388D1, were found to be rapidly recycled to the cell surface, also in the case where the cells had been treated with 25 microM monensin for 80 min which resulted in a reduction of the pinocytotic uptake rate to 30%. The result is discussed in terms of the intracellular pathway of internalized membrane.     

Protein quality control at the plasma membrane

Cellular proteostasis (or protein homeostasis) depends on the timely folding and disposal of conformationally damaged polypeptides during their life span at all subcellular locations. This process is particularly important for membrane proteins confined to the cell surface with crucial regulatory role in cellular homoeostasis and intercellular communication. Accumulating evidences indicate that membrane proteins exported from the endoplasmic reticulum (ER) are subjected to peripheral quality control (QC) along the late secretory and endocytic pathways, as well as at the plasma membrane (PM). Recently identified components of the PM QC recognition and effector mechanisms responsible for ubiquitination and lysosomal degradation of conformationally damaged PM proteins uncovered striking similarities to and differences from that of the ER QC machinery. Possible implications of the peripheral protein QC activity in phenotypic modulation of conformational diseases are also outlined.