Simplified proteomics approach to discover protein-ligand interactions

Identifying targets of biologically active small molecules is an essential but still challenging task in drug research and chemical genetics. Energetics-based target identification is an approach that utilizes the change in the conformational stabilities of proteins upon ligand binding in order to identify target proteins. Different from traditional affinity-based capture approaches, energetics-based methods do not require any labeling or immobilization of the test molecule. Here, we report a surprisingly simple version of energetics-based target identification, which only requires ion exchange chromatography, SDS PAGE, and minimal use of mass spectrometry. The complexity of a proteome is reduced through fractionation by ion exchange chromatography. Urea-induced unfolding of proteins in each fraction is then monitored by the significant increase in proteolytic susceptibility upon unfolding in the presence and the absence of a ligand. Proteins showing a different degree of unfolding with the ligand are identified by SDS PAGE followed by mass spectrometry. Using this approach, we identified ATP-binding proteins in the Escherichia coli proteome. In addition to known ATP-binding proteins, we also identified a number of proteins that were not previously known to interact with ATP. To validate one such finding, we cloned and purified phosphoglyceromutase, which was not previously known to bind ATP, and confirmed that ATP indeed stabilizes this protein. The combination of fractionation and pulse proteolysis offers an opportunity to investigate protein-drug or protein-metabolite interactions on a proteomic scale with minimal instrumentation and without modification of a molecule of interest.     

Membrane association of the PTEN tumor suppressor: molecular details of the protein-membrane complex from SPR binding studies and neutron reflection

The structure and function of the PTEN phosphatase is investigated by studying its membrane affinity and localization on in-plane fluid, thermally disordered synthetic membrane models. The membrane association of the protein depends strongly on membrane composition, where phosphatidylserine (PS) and phosphatidylinositol diphosphate (PI(4,5)P₂) act pronouncedly synergistic in pulling the enzyme to the membrane surface. The equilibrium dissociation constants for the binding of wild type (wt) PTEN to PS and PI(4,5)P₂ were determined to be K_d∼12 µM and 0.4 µM, respectively, and K_d∼50 nM if both lipids are present. Membrane affinities depend critically on membrane fluidity, which suggests multiple binding sites on the protein for PI(4,5)P₂. The PTEN mutations C124S and H93R show binding affinities that deviate strongly from those measured for the wt protein. Both mutants bind PS more strongly than wt PTEN. While C124S PTEN has at least the same affinity to PI(4,5)P₂ and an increased apparent affinity to PI(3,4,5)P₃, due to its lack of catalytic activity, H93R PTEN shows a decreased affinity to PI(4,5)P₂ and no synergy in its binding with PS and PI(4,5)P₂. Neutron reflection measurements show that the PTEN phosphatase “scoots" along the membrane surface (penetration <5 Å) but binds the membrane tightly with its two major domains, the C2 and phosphatase domains, as suggested by the crystal structure. The regulatory C-terminal tail is most likely displaced from the membrane and organized on the far side of the protein, ∼60 Å away from the bilayer surface, in a rather compact structure. The combination of binding studies and neutron reflection allows us to distinguish between PTEN mutant proteins and ultimately may identify the structural features required for membrane binding and activation of PTEN.     

Mirror,Mirror on the Wall,How Does My Brain Recognize My Image at All?

For decades researchers have used mirrors to study self-recognition. However, attempts to identify neural processes underlying this ability have used photographs instead. Here we used event related potentials (ERPs) to compare self-face recognition in photographs versus mirrors and found distinct neural signatures. Measures of visual self-recognition are therefore not independent of the medium employed.     

Breast cancer biomarkers predict weight loss after gastric bypass surgery

Background

Infections with polyomavirus BK virus (BKV) are a common cause of renal dysfunction after renal transplantation and may also be harmful in surgical patients with shock. The aim of the present study was to determine the frequency of BKV viremia in critically ill surgical patients with septic or hemorrhagic shock, and, if viremia is detectable, whether viremia may be associated with renal dysfunction.

Findings

A total of 125 plasma samples from 44 critically ill surgical patients with septic or hemorrhagic shock were tested by real-time polymerase chain reaction (PCR) for BKV DNA during their stay on the intensive care unit (ICU). BKV viremia occurred in four patients, i.e. in three of the septic and in one of the hemorrhagic shock group. There was no association between viremia and renal dysfunction. All positive samples contained a low viral load (< 500 copies/ml).

Conclusions

Since BK viremia was rarely found and with low viral load only in critically ill surgical patients with shock, it is very unlikely that BK viremia results in BK nephropathy later on.     

Obesity negatively impacts aerobic capacity improvements both acutely and 1-year following cardiac rehabilitation

Cardiac rehabilitation (CR) produces a host of health benefits related to modifiable cardiovascular risk factors. The purpose of the present investigation was to determine the influence of body weight, assessed through BMI, on acute and long-term improvements in aerobic capacity following completion of CR. Three thousand nine hundred and ninety seven subjects with coronary artery disease (CAD) participated in a 12-week multidisciplinary CR program. Subjects underwent an exercise test to determine peak estimated metabolic equivalents (eMETs) and BMI assessment at baseline, immediately following CR completion and at 1-year follow-up. Normal weight subjects at 1-year follow-up demonstrated the greatest improvement in aerobic fitness and best retention of those gains (gain in peak METs: 0.95 ± 1.1, P < 0.001). Although the improvement was significant (P < 0.001), subjects who were initially classified as obese had the lowest aerobic capacity and poorest retention in CR fitness gains at 1-year follow-up (gain in peak eMETs: 0.69 ± 1.2). Subjects initially classified as overweight by BMI had a peak eMET improvement that was also significantly better (P < 0.05) than obese subjects at 1-year follow-up (gain in peak eMETs: 0.82 ± 1.1). Significant fitness gains, one of the primary beneficial outcomes of CR, can be obtained by all subjects irrespective of BMI classification. However, obese patients have poorer baseline fitness and are more likely to "give back" fitness gains in the long term. Obese CAD patients may therefore benefit from additional interventions to enhance the positive adaptations facilitated by CR.     

You look familiar: how Malaysian Chinese recognize faces

East Asian and white Western observers employ different eye movement strategies for a variety of visual processing tasks, including face processing. Recent eye tracking studies on face recognition found that East Asians tend to integrate information holistically by focusing on the nose while white Westerners perceive faces featurally by moving between the eyes and mouth. The current study examines the eye movement strategy that Malaysian Chinese participants employ when recognizing East Asian, white Western, and African faces. Rather than adopting the Eastern or Western fixation pattern, Malaysian Chinese participants use a mixed strategy by focusing on the eyes and nose more than the mouth. The combination of Eastern and Western strategies proved advantageous in participants' ability to recognize East Asian and white Western faces, suggesting that individuals learn to use fixation patterns that are optimized for recognizing the faces with which they are more familiar.     

Korarchaeota diversity, biogeography, and abundance in Yellowstone and Great Basin hot springs and ecological niche modeling based on machine learning

Over 100 hot spring sediment samples were collected from 28 sites in 12 areas/regions, while recording as many coincident geochemical properties as feasible (>60 analytes). PCR was used to screen samples for Korarchaeota 16S rRNA genes. Over 500 Korarchaeota 16S rRNA genes were screened by RFLP analysis and 90 were sequenced, resulting in identification of novel Korarchaeota phylotypes and exclusive geographical variants. Korarchaeota diversity was low, as in other terrestrial geothermal systems, suggesting a marine origin for Korarchaeota with subsequent niche-invasion into terrestrial systems. Korarchaeota endemism is consistent with endemism of other terrestrial thermophiles and supports the existence of dispersal barriers. Korarchaeota were found predominantly in >55°C springs at pH 4.7-8.5 at concentrations up to 6.6×10(6) 16S rRNA gene copies g(-1) wet sediment. In Yellowstone National Park (YNP), Korarchaeota were most abundant in springs with a pH range of 5.7 to 7.0. High sulfate concentrations suggest these fluids are influenced by contributions from hydrothermal vapors that may be neutralized to some extent by mixing with water from deep geothermal sources or meteoric water. In the Great Basin (GB), Korarchaeota were most abundant at spring sources of pH<7.2 with high particulate C content and high alkalinity, which are likely to be buffered by the carbonic acid system. It is therefore likely that at least two different geological mechanisms in YNP and GB springs create the neutral to mildly acidic pH that is optimal for Korarchaeota. A classification support vector machine (C-SVM) trained on single analytes, two analyte combinations, or vectors from non-metric multidimensional scaling models was able to predict springs as Korarchaeota-optimal or sub-optimal habitats with accuracies up to 95%. To our knowledge, this is the most extensive analysis of the geochemical habitat of any high-level microbial taxon and the first application of a C-SVM to microbial ecology.     

Waist circumference adjusted for body mass index and intra-abdominal fat mass

Background

The association between waist circumference (WC) and mortality is particularly strong and direct when adjusted for body mass index (BMI). One conceivable explanation for this association is that WC adjusted for BMI is a better predictor of the presumably most harmful intra-abdominal fat mass (IAFM) than WC alone. We studied the prediction of abdominal subcutaneous fat mass (ASFM) and IAFM by WC alone and by addition of BMI as an explanatory factor.

Methodology/Principal Findings

WC, BMI and magnetic resonance imaging data from 742 men and women who participated in clinical studies in Canada and Finland were pooled. Total adjusted squared multiple correlation coefficients (R²) of ASFM and IAFM were calculated from multiple linear regression models with WC and BMI as explanatory variables. Mean BMI and WC of the participants in the pooled sample were 30 kg/m² and 102 cm, respectively. WC explained 29% of the variance in ASFM and 51% of the variance in IAFM. Addition of BMI to WC added 28% to the variance explained in ASFM, but only 1% to the variance explained in IAFM. Results in subgroups stratified by study center, sex, age, obesity level and type 2 diabetes status were not systematically different.

Conclusion/Significance

The prediction of IAFM by WC is not improved by addition of BMI.