Molecular chaperones DnaK and DnaJ share predicted binding sites on most proteins in the E. coli proteome

In Escherichia coli, the molecular chaperones DnaK and DnaJ cooperate to assist the folding of newly synthesized or unfolded polypeptides. DnaK and DnaJ bind to hydrophobic motifs in these proteins and they also bind to each other. Together, this system is thought to be sufficiently versatile to act on the entire proteome, which creates interesting challenges in understanding the interactions between DnaK, DnaJ and their thousands of potential substrates. To address this question, we computationally predicted the number and frequency of DnaK- and DnaJ-binding motifs in the E. coli proteome, guided by free energy-based binding consensus motifs. This analysis revealed that nearly every protein is predicted to contain multiple DnaK- and DnaJ-binding sites, with the DnaJ sites occurring approximately twice as often. Further, we found that an overwhelming majority of the DnaK sites partially or completely overlapped with the DnaJ-binding motifs. It is well known that high concentrations of DnaJ inhibit DnaK-DnaJ-mediated refolding. The observed overlapping binding sites suggest that this phenomenon may be explained by an important balance in the relative stoichiometry of DnaK and DnaJ. To test this idea, we measured the chaperone-assisted folding of two denatured substrates and found that the distribution of predicted DnaK- and DnaJ-binding sites was indeed a good predictor of the optimal stoichiometry required for folding. These studies provide insight into how DnaK and DnaJ might cooperate to maintain global protein homeostasis.     

Three RNA recognition motifs participate in RNA recognition and structural organization by the pro-apoptotic factor TIA-1

T-cell intracellular antigen-1 (TIA-1) regulates developmental and stress-responsive pathways through distinct activities at the levels of alternative pre-mRNA splicing and mRNA translation. The TIA-1 polypeptide contains three RNA recognition motifs (RRMs). The central RRM2 and C-terminal RRM3 associate with cellular mRNAs. The N-terminal RRM1 enhances interactions of a C-terminal Q-rich domain of TIA-1 with the U1-C splicing factor, despite linear separation of the domains in the TIA-1 sequence. Given the expanded functional repertoire of the RRM family, it was unknown whether TIA-1 RRM1 contributes to RNA binding as well as documented protein interactions. To address this question, we used isothermal titration calorimetry and small-angle X-ray scattering to dissect the roles of the TIA-1 RRMs in RNA recognition. Notably, the fas RNA exhibited two binding sites with indistinguishable affinities for TIA-1. Analyses of TIA-1 variants established that RRM1 was dispensable for binding AU-rich fas sites, yet all three RRMs were required to bind a polyU RNA with high affinity. Small-angle X-ray scattering analyses demonstrated a "V" shape for a TIA-1 construct comprising the three RRMs and revealed that its dimensions became more compact in the RNA-bound state. The sequence-selective involvement of TIA-1 RRM1 in RNA recognition suggests a possible role for RNA sequences in regulating the distinct functions of TIA-1. Further implications for U1-C recruitment by the adjacent TIA-1 binding sites of the fas pre-mRNA and the bent TIA-1 shape, which organizes the N- and C-termini on the same side of the protein, are discussed.     

Prediction of Disease Causing Non-Synonymous SNPs by the Artificial Neural Network Predictor NetDiseaseSNP

We have developed a sequence conservation-based artificial neural network predictor called NetDiseaseSNP which classifies nsSNPs as disease-causing or neutral. Our method uses the excellent alignment generation algorithm of SIFT to identify related sequences and a combination of 31 features assessing sequence conservation and the predicted surface accessibility to produce a single score which can be used to rank nsSNPs based on their potential to cause disease. NetDiseaseSNP classifies successfully disease-causing and neutral mutations. In addition, we show that NetDiseaseSNP discriminates cancer driver and passenger mutations satisfactorily. Our method outperforms other state-of-the-art methods on several disease/neutral datasets as well as on cancer driver/passenger mutation datasets and can thus be used to pinpoint and prioritize plausible disease candidates among nsSNPs for further investigation. NetDiseaseSNP is publicly available as an online tool as well as a web service: http://www.cbs.dtu.dk/services/NetDiseaseSNP     

Language Differences in the Brain Network for Reading in Naturalistic Story Reading and Lexical Decision

Differences in how writing systems represent language raise important questions about whether there could be a universal functional architecture for reading across languages. In order to study potential language differences in the neural networks that support reading skill, we collected fMRI data from readers of alphabetic (English) and morpho-syllabic (Chinese) writing systems during two reading tasks. In one, participants read short stories under conditions that approximate natural reading, and in the other, participants decided whether individual stimuli were real words or not. Prior work comparing these two writing systems has overwhelmingly used meta-linguistic tasks, generally supporting the conclusion that the reading system is organized differently for skilled readers of Chinese and English. We observed that language differences in the reading network were greatly dependent on task. In lexical decision, a pattern consistent with prior research was observed in which the Middle Frontal Gyrus (MFG) and right Fusiform Gyrus (rFFG) were more active for Chinese than for English, whereas the posterior temporal sulcus was more active for English than for Chinese. We found a very different pattern of language effects in a naturalistic reading paradigm, during which significant differences were only observed in visual regions not typically considered specific to the reading network, and the middle temporal gyrus, which is thought to be important for direct mapping of orthography to semantics. Indeed, in areas that are often discussed as supporting distinct cognitive or linguistic functions between the two languages, we observed interaction. Specifically, language differences were most pronounced in MFG and rFFG during the lexical decision task, whereas no language differences were observed in these areas during silent reading of text for comprehension.     

Changes in Biomass, Aboveground Net Primary Production, and Peat Accumulation following Permafrost Thaw in the Boreal Peatlands of Manitoba, Canada

Permafrost thaw resulting from climate warming may dramatically change the succession and carbon dynamics of northern ecosystems. To examine the joint effects of regional temperature and local species changes on peat accumulation following thaw, we studied peat accumulation across a regional gradient of mean annual temperature (MAT). We measured aboveground net primary production (AGNPP) and decomposition over 2 years for major functional groups and used these data to calculate a simple index of net annual aboveground peat accumulation. In addition, we collected cores from six adjacent frozen and thawed bog sites to document peat accumulation changes following thaw over the past 200 years. Aboveground biomass and decomposition were more strongly controlled by local succession than regional climate. AGNPP for some species differed between collapse scars and associated permafrost plateaus and was influenced by regional MAT. A few species, such as Picea mariana trees on frozen bogs and Sphagnum mosses in thawed bogs, sequestered a disproportionate amount of peat; in addition, changes in their abundance following thaw changed peat accumulation. ²¹⁰Pb-dated cores indicated that peat accumulation doubles following thaw and that the accumulation rate is affected by historical changes in species during succession. Peat accumulation in boreal peatlands following thaw was controlled by a complex mix of local vegetation changes, regional climate, and history. These results suggest that northern ecosystems may show responses more complex than large releases of carbon during transient warming. Received 8 August 2000; accepted 12 January 2001.     

Structural and functional analysis of slit and heparin binding to immunoglobulin-like domains 1 and 2 of Drosophila Robo

Recognition of the secreted protein Slit by transmembrane receptors of the Robo family provides important signals in the development of the nervous system and other organs, as well as in tumor metastasis and angiogenesis. Heparan sulfate (HS) proteoglycans serve as essential co-receptors in Slit-Robo signaling. Previous studies have shown that the second leucinerich repeat domain of Slit, D2, binds to the N-terminal immunoglobulin-like domains of Robo, IG1-2. Here we present two crystal structures of Drosophila Robo IG1-2, one of which contains a bound heparin-derived oligosaccharide. Using structure-based mutagenesis of a Robo IG1-5 construct we identified key Slit binding residues (Thr-74, Phe-114, Arg-117) forming a conserved patch on the surface of IG1; mutation of similarly conserved residues in IG2 had no effect on Slit binding. Mutation of conserved basic residues in IG1 (Lys-69, Arg-117, Lys-122, Lys-123), but not in IG2, reduced binding of Robo IG1-5 to heparin, in full agreement with the Robo-heparin co-crystal structure. Our collective results, together with a recent crystal structure of a minimal human Slit-Robo complex ( Morlot, C., Thielens, N. M., Ravelli, R. B., Hemrika, W., Romijn, R. A., Gros, P., Cusack, S., and McCarthy, A. A. (2007) Proc. Natl. Acad. Sci. U.S.A. 104, 14923-14928 ), reveal a contiguous HS/heparin binding surface extending across the Slit-Robo interface. Based on the size of this composite binding site, we predict that at least five HS disaccharide units are required to support Slit-Robo signaling.     

Snow depth manipulation and its influence on soil frost and water dynamics in a northern hardwood forest

Climate change will likelyresult in warmer winter temperatures leading toless snowfall in temperate forests. Thesechanges may lead to increases in soil freezingbecause of lack of an insulating snow cover andchanges in soil water dynamics during theimportant snowmelt period. In this study, wemanipulated snow depth by removing snow for twowinters, simulating the late development of thesnowpack as may occur with global warming, toexplore the relationships between snow depth,soil freezing, soil moisture, and infiltration.We established four sites, each with two pairedplots, at the Hubbard Brook Experimental Forest(HBEF) in New Hampshire, U.S.A. and instrumentedall eight plots with soil and snow thermistors,frost tubes, soil moisture probes, and soillysimeters. For two winters, we removed snowfrom the designated treatment plots untilFebruary. Snow in the reference plots wasundisturbed. The treatment winters (1997/1998 and1998/1999) were relatively mild, withtemperatures above the seasonal norm and snowdepths below average. Results show the treatedplots accumulated significantly less snow andhad more extensive soil frost than referenceplots. Snow depth was a strong regulator ofsoil temperature and frost depth at all sites.Soil moisture measured by time domainreflectometry probes and leaching volumescollected in lysimeters were lower in thetreatment plots in March and April compared tothe rest of the year. The ratio of leachatevolumes collected in the treatment plots tothat in the reference plots decreased as thesnow ablation seasons progressed. Our data showthat even mild winters with low snowfall,simulated by snow removal, will result inincreased soil freezing in the forests at theHBEF. Our results suggest that a climate shifttoward less snowfall or a shorter duration ofsnow on the ground will produce increases insoil freezing in northern hardwood forests.Increases in soil freezing will haveimplications for changes in soil biogeochemicalprocesses.     

Population coding of stimulus location in rat somatosensory cortex.

This study explores the nature of population coding in sensory cortex by applying information theoretic analyses to neuron pairs recorded simultaneously from rat barrel cortex. We quantified the roles of individual spikes and spike patterns in encoding whisker stimulus location. 82%-85% of the total information was contained in the timing of individual spikes: first spike time was particularly crucial. Spike patterns within neurons accounted for the remaining 15%-18%. Neuron pairs located in the same barrel column coded redundantly, whereas pairs in neighboring barrel columns coded independently. The barrel cortical population code for stimulus location appears to be the time of single neurons' first poststimulus spikes-a fast, robust coding mechanism that does not rely on "synergy" in crossneuronal spike patterns.     

Oligonucleotide biological activity: Relationship to the cell cycle and nuclear transport

Previous studies suggest that oligodeoxynucleotide (ODN) cellular uptake is cell cycle-dependent which may have important implications in cancer cell targeting. To further our understanding of ODN transport and activity, this study examines the relationships between the cell cycle, ODN cellular uptake, intracellular transport, and activity. An antisense c-myc ODN 21-mer was used to study ODN cellular uptake in Rauscher erythroleukemia cells synchronized by either chemical methods or flow cytometry. ODN uptake was examined using subcellular fractionation and confocal fluorescence microscopy. Western blot analysis was used to measure ODN-mediated decreases in c-myc protein levels. Intracellular ODN distribution and extent of uptake was influenced by the phase of the cell cycle, but the mechanism of uptake was not. The relative activity of the antisense ODN was positively correlated to ODN distribution to the cytosol, but negatively correlated to total cellular uptake. Although ODN total cellular uptake is positively influenced by the cell cycle, retention of the ODN in the cytosol (presumably extra-vesicularly) appeared to be relevant in determining the activity of an antisense ODN. Novel methods to target cytosol-acting drugs to the cytoplasm may therefore be warrented.     

Measurement of Mesoscale Conformational Dynamics of Freely Diffusing Molecules with Tracking FCS

Few techniques are suited to probe the structure and dynamics of molecular complexes at the mesoscale level ($～$100–1000 nm). We have developed a single-molecule technique that uses tracking fluorescence correlation spectroscopy (tFCS) to probe the conformation and dynamics of mesoscale molecular assemblies. tFCS measures the distance fluctuations between two fluorescently labeled sites within an untethered, freely diffusing biomolecule. To achieve subdiffraction spatial resolution, we developed a feedback scheme that allows us to maintain the molecule at an optimal position within the laser intensity gradient for fluorescence correlation spectroscopy. We characterized tFCS spatial sensitivity by measuring the Brownian end-to-end dynamics of DNA molecules as short as 1000 bp. We demonstrate that tFCS detects changes in the compaction of reconstituted nucleosome arrays and can assay transient protein-mediated interactions between distant sites in an individual DNA molecule. Our measurements highlight the applicability of tFCS to a wide variety of biochemical processes involving mesoscale conformational dynamics.