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Assembly of the ribosome from its protein and RNA constituents has been studied extensively over the past 50 years, and experimental evidence suggests that prokaryotic ribosomal proteins undergo conformational changes during assembly. However, to date, no studies have attempted to elucidate these conformational changes. The present work utilizes computational methods to analyze protein dynamics and to investigate the linkage between dynamics and binding of these proteins during the assembly of the ribosome. Ribosomal proteins are known to be positively charged and we find the percentage of positive residues in r-proteins to be about twice that of the average protein: Lys+Arg is 18.7% for E. coli and 21.2% for T. thermophilus. Also, positive residues constitute a large proportion of RNA contacting residues: 39% for E. coli and 46% for T. thermophilus. This affirms the known importance of charge-charge interactions in the assembly of the ribosome. We studied the dynamics of three primary proteins from E. coli and T. thermophilus 30S subunits that bind early in the assembly (S15, S17, and S20) with atomic molecular dynamic simulations, followed by a study of all r-proteins using elastic network models. Molecular dynamics simulations show that solvent-exposed proteins (S15 and S17) tend to adopt more stable solution conformations than an RNA-embedded protein (S20). We also find protein residues that contact the 16S rRNA are generally more mobile in comparison with the other residues. This is because there is a larger proportion of contacting residues located in flexible loop regions. By the use of elastic network models, which are computationally more efficient, we show that this trend holds for most of the 30S r-proteins.
Ribosomes are complex cellular machines that synthesize new proteins in the cell. The accurate and efficient assembly of ribosomal proteins (r-proteins) and ribosomal RNA (rRNA) to form a functional ribosome is important for cell growth, metabolic reactions, and other cellular processes. Additionally, some antibacterial drugs are believed to target the bacterial ribosome during its construction. Hence, ribosomal assembly has been an active research topic for many years because understanding the assembly mechanisms can provide insight into protein/RNA recognitions important in many other cellular processes, as well as optimize the development of antibacterial therapeutics. Experimental studies thus far have provided still limited understanding about the assembly process. To further understand the assembly process, we have computationally studied the dynamic properties that r-proteins exhibit during assembly and the relationship between dynamics, physical properties, and binding propensity. We observe significant charged interactions between r-proteins and rRNA. We also detect a strong correlation between contact residues and their dynamic mobilities. Protein residues contacting with rRNA are observed to be more mobile in comparison with other residues. We also relate the location of the r-protein in the fully assembled ribosome to its susceptibility for large conformational changes prior to binding.
Citation: Burton B, Zimmermann MT, Jernigan RL, Wang Y (2012) A Computational Investigation on the Connection between Dynamics Properties of Ribosomal Proteins and Ribosome Assembly. PLoS Comput Biol 8(5): e1002530. doi:10.1371/journal.pcbi.1002530
Editor: Marc A. Marti-Renom, Centro de Investigación Príncipe Felipe (CIPF), Spain
Received: October 21, 2011; Accepted: April 10, 2012; Published: May 24, 2012
Copyright: © 2012 Burton et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: This work was partially supported by NIH grants R01-GM073095 and R01- R01GM072014 and NSF grant MCB-1021785. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
Ribosomes are the macromolecular machines that synthesize proteins in all living organisms. They are composed of ribosomal RNA (rRNA) and ribosomal proteins (r-proteins) that self-assemble into functional units. The efficient and accurate self-assembly of the active ribosome in vivo is essential for cell growth because new ribosomes and proteins must be produced in order for cells to grow. It is estimated that approximately 60% of all cellular transcriptional activities have been attributed to the synthesis of rRNA in a rapidly growing cell  and 40% of the total energy of an E. Coli cell is directed towards the synthesis of proteins . It is therefore not surprising that ribosome biogenesis in cells is intricately regulated. Elucidating this complex regulation network has become the focus of a rapidly developing field.
The assembly of the ribosome requires the orchestration of highly coordinated events that involve both rRNA folding and r-protein binding. While many cofactors have been identified that participate in assembly in vivo, active functional units can be assembled in vitro in the absence of these cofactors . The small 30S subunit of the bacterial ribosome (see Figure 1), which is composed of 16S rRNA and 21 r-proteins, has been more extensively studied than other structural assemblages and is a good system to analyze in order to determine what is important for the ribonucleic particle (RNP) assembly. In particular, the 30S subunit was the first to be reconstituted from purified components by the Nomura group in the late 1960's . The reconstituted 30S active particles showed nearly the same activities in all performed biochemical assays. This ability to reconstitute active particles in vitro allows for in-depth exploration of the roles of the individual components in ribosome assembly and their functions by the combinatorial addition and omission of individual components , –. These experiments revealed that the 30S subunit assembles in a sequential and ordered process . The Nomura group also provided a detailed assembly map describing the sequential and interdependent binding of all r-proteins . The map also classified the proteins as primary, secondary, and tertiary binders, depending on their ability to bind to 16S rRNA. The primary proteins bind to bare rRNA, secondary proteins can bind to 16S rRNA after at least one primary protein has already bound, and tertiary proteins require at least one primary and one secondary protein .
Figure 1. The 30S T. thermophilus subunit (1J5E), interface side.
The 16S rRNA and r-proteins of interested are highlighted: 5′ Domain yellow, Central Domain grey, 3′ Major Domain orange, and 3′ Minor Domain purple; S15 blue, S17 dark green, and S20 dark red. The E. coli structure (2AVY) is nearly identical, but slight structural differences for the proteins of interest are discussed in the text and visualized in Figure 2. The remaining r-proteins have been removed for better visualization of the 16S rRNA domains.doi:10.1371/journal.pcbi.1002530.g001
The Nomura assembly map reflects the equilibrium thermodynamics of r-protein binding with 16S rRNA to intermediates. Using chemical probing methods, these binding kinetics were more recently studied by Powers et al.  Based on their experimental results, the r-proteins were divided into early, mid, mid-late and late binders. The kinetics data were partially in agreement with thermodynamic data in that the tertiary binding proteins were consistently found to be late binders. The availability of atomic structures of the 30S subunit – provided tremendous new opportunities to understand the assembly mechanism. Most of the knowledge gained in earlier experimental studies was found to be consistent with the determined structures.
In the meantime, significant progress was made with experimental methods to probe the ribosome assembly mechanism. Time-resolved X-ray-dependent hydroxyl radical footprinting – provides resolution on the order of milliseconds, much shorter than other chemical probing methods . Directed hydroxyl radical probing – allows for the detection of specific interaction sites between proteins and RNA. The Williamson group used PC/QMS (pulse-chase followed with quantitative mass spectrometry) to measure the kinetics of individual protein binding during the assembly of the full ribosomal complex . New experimental data suggest that ribosome assembly proceeds via multiple parallel pathways – rather than a single pathway involving the formation of a single rate-determining “reaction intermediate” RNP . Current understanding of the ribosome assembly process suggests it is similar to protein folding in that it can proceed via multiple pathways across a rugged energy landscape.
Many computational studies have shed light on some important aspects of ribosome structure and function. Molecular dynamics simulations have been performed to analyze ribosome interactions with and the accommodation of transfer RNA (tRNA) during translation –, as well as to characterize the interactions between cognate tRNA codons and their messenger RNA (mRNA) anticodons –. Other simulations and calculations used structures from various stages of translation to study the behavior of incoming mRNA transcripts  and nascent polypeptides in the ribosome's exit tunnel –. Interactions between ribosomes and members of a class of antibiotics called aminoglycosides have been elucidated via computational techniques – and have shed light on important interactions between these small molecules and the decoding center of the ribosome. Investigations of the interactions between the ribosome and important non-ribosomal proteins, such as the elongation factor EFTu, have been performed using MD  and quantum level calculations . Other quantum calculations have been used to address the function of ribosome catalysis, such as the mechanism of and possible transition states in peptide bond synthesis –. These investigations have enriched the current understanding of ribosomal function and additional computational analyses on the dynamical structure of the ribosome and its components can further elucidate the mechanisms by which the ribosomal machinery assembles and operates.
Despite significant progress in recent years, the understanding of ribosome assembly remains limited. One major obstacle in this field is elucidating the mechanisms of coordinated RNA folding, protein binding, and the associated conformational changes of RNA and r-proteins . Although earlier studies suggested  that r-proteins adopt the same structures in solution as in the assembled ribosome, more recent studies suggest  that there are conformational changes in the r-proteins and rRNA upon forming the complexes. Predicting RNA structure is also one of the most challenging topics in structural biology because a single stranded RNA can adopt a variety of secondary and tertiary structures. The 16S rRNA molecule in a ribosome is divided into four domains: the 5′ domain, the central domain, the 3′ major domain and the 3′ minor, each with a well-defined structure (see Figure 1). Magnesium ions are thought to stabilize the secondary structure of RNA and many r-proteins are thought to stabilize the tertiary structures. Many of the r-proteins interact with and bind to only one domain, but a few associate with more than one, such as S20 which interacts with both the 5′ and the 3′ minor domains. The Harvey group  analyzed the atomic contacts of r-proteins with RNA in the 30S subunit structure and reported the interesting observation that most of the late binding r-proteins were found to bind at the 3′ end of 16S RNA. This observation was consistent with the earlier understanding that 16S RNA folds with 5′ to 3′ polarity , . The Harvey group further used coarse-grained representations of RNP structures to examine the potential fluctuations of binding sites when proteins were removed or added. Their study shows that the binding sites of primary proteins are formed first and, once associated, these proteins help organize the late binding sites. Trylska et al.  calculated the binding energy of individual r-proteins with the 16S RNA by solving the Poisson-Boltzmann equation, which accounts for electrostatic interactions. Though the calculated binding energies varied, some late binders were found to have less favorable binding free energies while the early binders were found to be more favorable, an observation consistent with known experimental results. Other studies used various coarse-grained representations to explore the global motions of the ribosome , – and the assembly of the 30S –. Despite the coarse representations of ribosomal structure, some of the known dependencies of r-protein and rRNA binding were captured in these computational studies.
Ribosome assembly remains an active research field. A better understanding of its assembly mechanisms will provide valuable biochemical insight into cellular regulation and will allow for the optimal development of ribosome-targeted drugs. While experimental studies continue to make great progress, computational studies reported so far are still limited. Most of the earlier reported computational studies have used coarse-grained representations of the ribosome. To truly understand the specific binding of r-proteins with 16S RNA, atomistic details need to be considered. Because assembly involves both RNA folding and protein binding, the examination of individual components before and after binding in atomistic detail is necessary. Here we specifically investigate the potential correlation between r-protein dynamics properties and their binding properties. The aim is to answer the following specific questions: what are the key residues that bind to the 16S rRNA? Are these key residues more flexible than the others? Do free r-proteins adopt the same conformations as those found in the assembled 30S subunit? To explore the answers to these questions, we rely on the use of atomistic molecular dynamic simulations of r-proteins as well as other methods developed in our own group.
Ribosomal proteins are enriched with positively charged amino acids
Ribosomal proteins are known to be positively charged and many of these positively charged amino acids, especially those residues on the long extension tails, were found to interact with RNA , –. We performed a simple calculation of the net charge of ribosomal proteins based on the sequences reported for the 2AVY and 1J5E structures, counting Asp and Glu as −1, Lys and Arg as +1, with all other residues treated as neutral. Of course, some of these residues might have some charge because of shifted pKa values due to their location in the tertiary structure, but we will ignore these minor effects at present. Table 1 presents the net charge of r-proteins for the two species. The two r-proteins that are not positively charged could be explained by their special positions in the assembly map: S2 is the last protein to assemble  and S6 is known to form a dimer with S18 –, which is positively charged, before associating with rRNA. The remaining r-proteins are all positively charged. We also note that the charge on r-proteins from T. thermophilus is on average higher than that for the E. coli proteins, which may relate to the general observation that ribosomal subunits for thermophiles such as T. thermophilus are more stable than those of mesophiles such as E. coli . Moreover, ribosomal proteins are enriched with positively charged amino acids. The typical percent of amino acids for Lys, Arg, Glu and Asp are 5% each for cytosolic proteins . However, in the case of r-proteins, the total percentage of Lys and Arg is approximately 20% (18.7% for E. coli and 21.2% for T. thermophilus), while the sum of Glu and Asp percentages remained near 10%. Klein et al had earlier examined the amino acid distributions of r-proteins in the large subunit (50S) and reported a similar bias toward the positively charged amino acids .
Table 1. Net charges of r-proteins.doi:10.1371/journal.pcbi.1002530.t001
We have further examined the contacts made between r-proteins and the RNA based on the atomic structures of the 30S subunit from the two species. Here, a contact is defined as having any atoms of a protein residue within 3.5 Å of any rRNA nucleotide atoms. Table 2 presents the number of contacts made by each r-protein, along with the number of contacts with positively charged residues. It is clear that a high percentage of contacts between r-proteins and rRNA are made by positively charged residues. The total average percentages of contacts made by positively charged residues are 39% for E. coli and 46% for T. thermophilus, and both are significantly higher than the total percentage of the positively charged amino acids in r-proteins for the two species. These results together affirm the known importance of charge-charge interactions in the ribosome , –.
Table 2. Contacts between r-proteins and r-RNA in total and for charged residues.doi:10.1371/journal.pcbi.1002530.t002
Structures and contact residues are more conserved than sequences
Figure 2 shows structural alignments for the three proteins from the two species. The percentages of sequence identity between the two species are 60% for S15, ~40% for S17, and ~28% for S20, but the percentages of conserved residue class are considerably higher: 75% for S15, ~58% for S17, and ~47% for S20. Thus, the structures for the three ribosomal proteins are well conserved, with RMSD values of 1.1 Å for S15, 1.4 Å for S17, and 2.1 Å for S20. In the cases of S17 and S20 from T. thermophilus, there are extra C-terminal regions, as shown in Figures 2b and 2c.
Figure 2. Comparisons of S15, S17, and S20 proteins from two different species.
E. coli proteins are shown in the lighter shade and T. thermophilus in the darker shade. Contact residues are shown as stick representations and some important parts of the proteins, discussed in the text, are labeled.doi:10.1371/journal.pcbi.1002530.g002
Residues that contact rRNA exhibit higher than average sequence conservation. For S15, the percent of conserved contact residues is about 54% (52% for E. coli and 56% for T. thermophilus), which is just under the overall sequence conservation. For S20, the percentage of conserved contact residues is 38% for E. coli and 35% for T. thermophilus, both of which are considerably higher than the overall sequence conservation. For S17, the percentage of conserved E. coli contacting residues (52%) is higher than the overall sequence conservation, whereas that for T. thermophilus contacting residues (31%) is less. The conserved contact residues percentages for S17 and S20 from T. thermophilus are lower than those for E. coli because T. thermophilus has extra C-terminal regions that make several additional non-conserved contacts. (Supplementary Tables S1, S2, S3 present the contact residues for S15, S17 and S20 for the two species, with conserved residue identities in red and conserved side chain types, largely Lys/Arg substitutions, colored green.)
Further analysis of the identities of these contact residues reveals that, aside from the positively charged residues, His, Thr, Ser, and Gln are also common, all of which are polar and can form hydrogen bonds with rRNA. For example, of the twenty-seven E. coli S15 contacts, five are basic (Lys48, Arg54, Arg64, Lys65, and Lys73), five are histidines (His38, His42, His46, His50, and His51), ten are polar (Ser2, Thr5, Thr8, Thr22, Ser24, Gln28, Gln35, Ser52, Ser61, and Gln62), and one is aromatic and polar (Tyr69). The remaining six contacts are acidic (Asp21 and Asp49) or nonpolar (Gly23, Leu31, Leu39, and Gly55). Therefore, most contacts between the r-proteins and the rRNA are either charged interactions, or hydrogen bonds, with few aromatic stacking or nonpolar interactions.
Dynamics and conformational changes of S15
S15 is a primary binding protein which binds in the 3′ major domain of 16S RNA. In the assembled 30S subunit, S15 is solvent-exposed and located on the back of the 30S subunit body. The 16S RNA binding site of S15 is at the three-way junction of helices 20, 21, and 22 in the 16S central domain. The primary, secondary, and tertiary structures of S15 are highly conserved across species: four bundled α-helices are connected by short loops (Figure 2a). All 16S rRNA contact residues are found on one side of S15, located on helices 1, 2 and 3 and the loops connecting the three helices, but helix 4 does not have any contacts with rRNA.
In previous structural studies, X-ray – and NMR – derived structures were reported and the only significantly different conformation reported was in the crystal structure  where helix 1 was rotated 90° away from the remaining bundled helices. Additional studies have been published about the role of S15 in ribosome assembly and antibiotic responses with mutagenesis studies  and MD simulations, studying the effects of Mg2+ ions on the protein alone and with its rRNA binding site . It has been suggested that this protein acts as a bridge between the large and small subunits in the fully assembled ribosome .
Root-mean-square deviations (RMSD) were calculated from the molecular dynamics simulations of the S15 protein and are presented in Figure 3a. The S15 from the two species exhibit relatively low RMSD values during MD simulations, with values remaining below 5 Å. Figure 4 presents the root-mean-square fluctuation (RMSF) values calculated over the period of time from 10 ns until the end of the simulation. Contact residues are shown as solid symbols in the plot. High RMSF values were observed for the loop connecting helices 2 and 3, and several conserved contact residues are located in this loop. The contact residues found on helices 2 and 3 have very low RMSF values, whereas helix 1 and the loop connecting helices 1 and 2 have a few contact residues with moderate RMSF values. Helix 4, which has no contacts with 16S RNA retains its helical structure during the MD simulation and has moderate RMSF values. Representative backbone structures for E. coli and T. thermophilus S15 are depicted in Figure 5. The proteins retain their secondary and tertiary structures during the MD simulations and only small conformational changes are observed for either S15 protein. This indicates that the S15 protein from both organisms is a relatively stable protein in solution and that the conformations observed during the simulations are similar to that of the attached protein in the assembled ribosome.
Figure 3. RMSD values for S15, S17, and S20 proteins.
E. coli proteins are represented by lighter squares and T. thermophilus by darker triangles. The S17 include the RMSD value for just the part of the structure that is homologous (dark green) to E. coli S17 (omitting the extra T. thermophilus C-terminal part). Notably, this C-terminal part of S17 causes the T. thermophilus to greatly increase its overall mobility.doi:10.1371/journal.pcbi.1002530.g003
Figure 4. RMSF values for S15.
E. coli proteins are represented in red with squares indicating contact residues and T. thermophilus proteins are colored blue with triangles for contacts. In these figures, the proteins have been sequentially aligned to demonstrate the behaviors of the conserved structural elements. Aligned Residue Numbers, therefore, do not necessarily reflect the actual residue indices of the protein sequence.doi:10.1371/journal.pcbi.1002530.g004
Figure 5. S15 structural variations during MD simulation.
Backbone snapshots of both proteins are in shades of blue (E. coli light blue; T. thermophilus dark blue). Backbone starting structures are shown in yellow.doi:10.1371/journal.pcbi.1002530.g005
Table 3 compares the average RMSF for contact residues with respect to average RMSF for all residues. The average RMSF value for all E. coli S15 residues is 2.11 Å and for all contact residues is 2.24 Å. For T. thermophilus S15, all residues average RMSF is 1.84 Å and all contacts is 2.37 Å. These differences are small, but statistical analysis shows that S15 contact residues are positively enriched with mobile residues, as indicated by enrichment factors greater than 1 for both species (Table 3; EF = 1.08 and p-value = 0.217 for E. coli; EF = 1.46 and p-value = 0.008 for T. thermophilus, see Methodology for explanation of enrichment factors and the p-value). The P-values for these enrichment factors signify that the mobility enrichment of T. thermophilus contact residues is significant while it may not for E. coli.
Table 3. Average MD RMSF values (in Å; standard deviations in parentheses) and enrichment factors EF.doi:10.1371/journal.pcbi.1002530.t003
Dynamics and conformational changes of S17
In the 30S subunit, S17 is also solvent exposed and is located near S15 in the 5′ domain of the 16S rRNA. To date, no X-ray crystal structures have been determined for S17 alone, but a low resolution NMR solution structure has been presented for Bacillus stearothermophilus S17 . The S17 structure found in the E. coli 30S subunit is comprised of a small β-barrel and an extended ß-hairpin loop (Figure 2b). The contact residues are located on one end of the β-barrel and in the extended ß-hairpin loop. The S17 from T. thermophilus has an extra C-terminal α-helix which makes additional contacts with the 16S rRNA (Figure 2b). Thus, E. coli contact residues exhibit somewhat higher conservation than the overall sequence does, whereas T. thermophilus contact residues are slightly less conserved than the sequence of the full-length proteins. In the E. coli 30S subunit, the S17 ß-hairpin loop is embedded in rRNA and contains five contacts, three of which are found contacting helix 11 of the central domain with two contacting the 5′ domain at helix 21. The axis of the β-barrel is oriented into the main part of the rRNA, and the end of the barrel nearest the RNA contains the remaining contact points, all of which contact the 5′ domain of 16S rRNA along helices 7, 9, and 11. Because these contacting residues associate with both the 5′ domain and the central domain, E. coli S17 is a plausible anchor between them. The T. thermophilus S17 also contacts these two 16S domains but includes an additional ten protein contacting residues in its C-terminal α-helix and coiled tail. These residues have a larger extent of contact with helix 11 and strengthen the association with the central domain at helices 20 and 27. Research indicates that the 30S subunit assembly begins at the 16S rRNA 5′ end  and, S17 appears to organize the 5′ region , so it is clear that the cooperative conformational changes and rRNA binding of this protein are likely to play an important role in the early stages of ribosome formation.
During the MD simulation of E. coli S17, the β-sheet structures remained stable: the average RMSD for this protein was relatively low (below 5 Å; lime green plot, Figure 3b). Conversely, a much higher RMSD was observed for S17 from T. thermophilus (olive green plot, Figure 3b), although the protein did take on a relatively stable conformation after ~80 ns of simulation. Further investigation reveals that the extra α-helix in T. thermophilus S17 is responsible for the high RMSD values. The structurally homologous portions of the proteins have comparable RMSD values (T. thermophilus homolog: dark green plot, Figure 3b), both around 4 Å. The backbones of structurally homologous portions both retain their overall shape during the MD simulations.
S17 RMSF values (Figure 6) were calculated from the MD simulations starting from the 10 ns point until the end of the trajectory. While the T. thermophilus S17 generally exhibited larger deviations from its starting structure than did the E. coli S17, when sequentially aligned, the RMSF values for the structurally homologous portions of the proteins correlate well. For E. coli S17, the loops connecting the ß-strands, the extended ß-hairpin loop, and both termini exhibit comparably high RMSF values, whereas the ß-strands participating in the ß-barrel (valleys in Figure 6) have low RMSF values. The same pattern is true for the homologous portion of the T. thermophilus RMSF plot, and the extra C-terminal region exhibits very large RMSF values. The contact residues in the E. coli S17 are located in the highly mobile ß-hairpin, the moderately mobile Loops 1 and 6, as well as the least mobile ß-strands of ß-barrel: ß5, the last residue of ß1, and the first of ß2. In T. thermophilus S17, there are four regions of the protein with high RMSF (the N-terminus, the ß-hairpin loop, Loop 4, and the C-terminus), all of which contain contact residues. In fact, every residue in Loop 4 is a contact residue, and residues close to each end of the loop also have high RMSF values. The three contact residues in the α-helix have high RMSF and the ten residues in the C-terminal coil have some of the highest RMSF, seven of which are contact residues. The low and moderate contact residues are found in the ß-barrel: ß1, Loop 1, ß2, and ß3.
Figure 6. RMSF values for S17.
E. coli proteins are represented in red with squares indicating contact residues and T. thermophilus proteins are colored blue with triangles for contacts. In these figures, the proteins have been sequentially aligned to demonstrate the behaviors of the conserved structural elements. Aligned Residue Numbers, therefore, do not necessarily reflect the actual residue indices of the protein sequence.doi:10.1371/journal.pcbi.1002530.g006
Representative structures seen throughout the E. coli and T. thermophilus S17 simulations are shown in Figure 7. The RMSF data and these images indicate that the structurally homologous regions of the S17 protein behave similarly in solution and that the ß structures of both homologs retain their overall shape throughout the simulations, whereas the flexible C-terminal α-helix in T. thermophilus loses its helical structure. These data imply that the ß-barrel confers good stability in solution for the two species.
Figure 7. S17 structural variations during MD simulation.
Backbone snapshots of both proteins are in shades of green (E. coli light green; T. thermophilus dark green). Backbone starting structures are shown in yellow.doi:10.1371/journal.pcbi.1002530.g007
Further analyses of the relative mobility of contact residues shows similar trends as S15. The average RMSF (Table 3) for all residues in E. coli S17 is 1.85 Å and 2.28 Å for all contacting residues; for T. thermophilus, the average for all residues is 4.68 Å, and 5.74 Å for all contacting residues. The differences in these values, while small, indicate that contact residues are, on average, more mobile than all residues for both S17 proteins. Enrichment factors for S17 show positive mobility enrichment for contact residues in both species (Table 3; EF = 1.10 with p = 0.199 for E. coli; EF = 1.40 with p = 0.008 for T. thermophilus), with p-values indicating that T. thermophilus enrichment is significant while it may not be for E. coli.
Dynamics and conformational change of S20
In the 30S subunit crystal structures from both species, protein S20 is found deeply embedded in the 16S rRNA. This protein contacts 16S RNA helices 6–9, 11, and13 in the 5′ domain and is the only r-protein to contact helix 44 in the 3′ domain. The structure of S20 consists of a unique set of three bundled α-helices, with helix 1 twice as long as the others, the N-terminus most deeply inserted into the subunit, and only a small portion of the three-helix bundle exposed to solvent. While the E. coli and T. thermophilus S20 proteins have a generally conserved tertiary body (Figure 2c), the T. thermophilus S20 crystal structure is missing its first seven residues and has an additional 15 residue C-terminal tail which the E. coli protein does not have.
The simulation RMSD values for S20 from both species oscillate wildly (Figure 3c), indicating the proteins conformation vary broadly from their starting conformations (up to ~20 Å). Multiple length simulations (at least 200 ns) show that while S20 RMSD may remain within a range of 5–10 Å for a time, the protein does not adopt a solution-stable conformation. The S20 RMSF plots (Figure 8) have similar trends for both E. coli and T. thermophilus S20 proteins, and aside from the first portion of α1, the three α-helices are primarily located at valleys in the plots. The highly flexible region of α1 binds to rRNA helices 6, 7, and 13, whereas the nearby, more stable contact residues in α1 contact the tip of rRNA helix 44, a helix that has no contacts with any other small subunit proteins. The remaining contacts have relatively moderate or low RMSF values. As seen in the other proteins, the loop regions between the stable secondary structures are located at peaks in the RMSF plot, whereas the α-helical regions themselves correspond to the RMSF valleys. Visual inspection of the trajectories suggests that the major contributor to S20 flexibility is helix 1 (Figure 9), which extends deeply into the rRNA. The N-terminal portion of helix 1 bends and swings wildly during the MD simulations. E. coli helix 1 bends near Arg24 and Thr30 and T. thermophilus near Lys29.
Figure 8. RMSF values for S20.
E. coli proteins are represented in red with squares indicating contact residues and T. thermophilus proteins are colored blue with triangles for contacts. In these figures, the proteins have been sequentially aligned to demonstrate the behaviors of the conserved structural elements. Aligned Residue Numbers, therefore, do not necessarily reflect the actual residue indices of the protein sequence.doi:10.1371/journal.pcbi.1002530.g008
Figure 9. S20 structural variations during MD simulation.
Backbone snapshots of both proteins are shown in shades of red (E. coli light red; T. thermophilus dark red). Backbone starting structures are in yellow.doi:10.1371/journal.pcbi.1002530.g009
Previous studies  have shown that the free S20 protein in solution does not exhibit the high percentage of α-helical regions as seen in the crystallized structure. The conformational variation exhibited by S20 in the work here is consistent with this data, and this flexibility coupled with the deep insertion of the protein into the folds of RNA in the fully-assembled ribosome indicate that S20 is stabilized primarily by its large number of contacts with the RNA.
The average RMSF trends (Table 3) for S20 contact residues are generally in agreement with the results presented for S15 and S17. For E. coli, the average RMSF for all residues is 8.82 Å and for all contact residues is 9.14 Å. In T. thermophilus, the average value for all residues is 6.96 Å and 7.62 Å for all contact residues. These data show that the mean RMSF for all contacts is greater than that for the whole structure, consistent with the results for S15 and S17. Both E. coli and T. thermophilus S20 proteins show positive enrichment of mobility in their contact residues (Table 3; EF = 1.06 with p-value = 0.215 for E. coli; EF = 1.15 with p-value = 0.057 for T. thermophilus). However, in this case, the p-values are both greater than 0.05, a typical threshold used for statistical significance test.
General trends based on Elastic Network Modeling
To rapidly assess the potential connection between contacting residues and their mobilities, we use elastic network modeling which compute RMSF values using only a fraction of the computational resources required for the MD simulations. The elastic network models have been applied previously to the ribosome by us , , , , and in general the dynamics calculated via the Anisotropic Network Model – correlate reasonably well with those from the MD simulations. For example, the correlation coefficient between RMSF values calculated for E. coli S15 is 0.57, for S17 is 0.63, and for S20 is 0.81. ANM and MD predict similar patterns of mobility and stability, with most of the discrepancy at the terminal residues and highly flexible regions (such as S20 α-helix 1 and S17 ß-hairpin loop). In fact, if the first two and last two residues of E. coli S15 are excluded, the correlation factor increases to 0.67. The MD simulations typically predict greater terminal residue mobility (except for the highly mobile S20 helix 1) and the ANM calculations consistently predict higher fluctuation values for extended residues in the middle of the protein.
ANM mobility enrichment was calculated for all 19 r-proteins in the two 30S X-ray structures and results are presented in Table 4. Most r-proteins are significantly enriched for mobile residues at the rRNA contact points at the 0.05 level. Contacting residues are not only enriched, but they make up a subset of residues that is near maximal enrichment, for a given structure. Proteins S2, S6, S8, S18 and S19 do not show statistically significant enrichments and are colored red in Table 4. As mentioned earlier, S2 and S6 differ from the rest of r-proteins in that they do not have a net positive charge. Also S6 and S18 are known to form dimers in solution. Hence calculation of their dynamics as monomers may not reflect their true dynamics in solution. S8 is one of the primary binding r-proteins and S19 is one of the secondary binding r-proteins. At present, we do not know specific properties that may make these two proteins differ from the rest. Although their EF values are greater than one (rRNA contacts are more mobile), their p-values do not reach the level of high statistical significance (they are not a maximally enriched subset). In addition to those r-proteins, S14, S17 and S20 are not significantly enriched with mobile residues for E. Coli, but are statistically significant enriched for T. Thermophilus. On average, T. thermophilus proteins show a slightly increased enrichment relative to E. coli; with average enrichment factors of 1.51 and 1.46, respectively, with medians of 1.43 and 1.33. Of the 6 proteins categorized as being early by the Harvey group , two E. coli and five T. thermophilus have mobility enrichments significant at the 0.05 level. Of the six primary proteins identified by Nomura , three E. coli and five T. thermophilus are significant at the 0.05 level. Proteins involved later in assembly are not differentially significant between the two species. This may imply that thermophiles exhibit increased control over the placement of mobile residues within proteins that bind to rRNA.
Table 4. ANM enrichment factors and significance for 30S proteins.doi:10.1371/journal.pcbi.1002530.t004
Several important conclusions can be reached based on the above reported results. First, the positively charged residues on r-proteins must play important roles in binding with 16S rRNA, as noted earlier , –. A significantly higher percentage of contacts between r-proteins and rRNA are formed by these positively charged and hydrogen bonding residues. We also see that r-proteins from a thermophilic species (T. thermophilus) have more positively charged residues than a mesophilic species (E. coli), which correlates with the fact that thermophilic ribosomes must maintain stronger (or a larger number of) interactions in order to function at considerably higher temperatures. Second, as previously discussed , conformational changes of r-proteins could take place during 16S rRNA binding. Our study clearly shows that α-helix 1 of S20 is unstable in solution by itself and exhibits large conformational changes. In contrast, S15 and S17 adopt stable conformations in solution, which agrees with the earlier suggestion  that ribosomal proteins do not undergo structural changes during assembly. We attribute the differences in these behaviors to the extent of solvent exposure the protein experiences within the assembled subunit. In the ribosome, S15 and S17 are primarily solvent exposed so their solution structures would be likely to more closely resemble their bound structures, whereas S20 is deeply embedded in the 16S RNA, and its association with its RNA binding site stabilizes the flexible portion of α-helix 1. Third, analyses of residue mobilities reveal that RMSF values for contact residues are statistically higher than those for other residues. This means that contacting regions are more enriched with mobile residues than non-contacting regions, which supports previous observations  that the flexible regions of ribosomal proteins are usually the locations of RNA contacts. However, this does not mean that all contact residues are located in the flexible loop regions. It is important to point out that there are many contact residues found in α-helices and β-sheets that exhibit low to moderate RMSF values. The trend that contact residues being enriched with mobile residues holds for most of 30S r-proteins, with only a few distinct exceptions like S2, S6, S18. Their exceptions however could be traced to peculiar known facts such as dimerization between S6 and S18. The increased mobility of contact residues could ensure more efficient binding and even aid in the binding site preparation for later binding proteins by actively associating with their 16S binding partners and helping to fold and maintain the appropriate rRNA tertiary structure. The T. thermophilus exhibited higher enrichment factors than the E. Coli, which may point to a novel adaptation of thermophiles – the increased control over the placement of highly mobile residues.
Analysis of contacts in the assembled 30S subunits
In the current study, we analyze the crystal structures of the 30S subunits from the Escherichia coli (PDB  ID 2AVY ) and Thermus thermophilus ribosomes (PDB ID 1J5E ). Structural and sequence alignments of r-proteins found in the two species were done with Molecular Operating Environment (MOE) software (Chemical Computing Group). Contacts between r-proteins and 16S rRNA were analyzed using our own computer program. A contact point was defined as any atom of a protein residue found within a 3.5 Å cut-off distance from any 16S nucleotide atom. That amino acid was labeled as a “contact” residue. The total number of “contacts” between one r-protein and the 16S rRNA may exceed the total number of contacting residues identified in the protein because an amino acid may be within cutoff distance of more than one nucleotide, thus counting as more than one contact. The identity and position of these contact residues found in the assembled 30S subunit were recorded and used for further analysis.
Molecular Dynamics simulations
Molecular dynamics (MD) simulations were run using the AMBER 10 software package  and the parmbsc0 force field , an optimization of the Amber99 force field for nucleic acids and proteins. The starting conformations of r-proteins for the MD were obtained from the crystal structures of the 30S subunits (E. coli 2AVY and T. thermophilus 1J5E). Counterions were added to neutralize the charge of the protein, and an additional 10 potassium and 10 chloride ions were added to create a low salt concentration. The protein systems were then solvated using a rectangular box of TIP3P water . The systems were subjected to two minimization cycles: 1000 steps with the protein fixed and 5000 steps unrestrained. Afterward, a 100 ps warm-up MD simulation was run at constant volume by increasing temperature from 0 to 300 K, with the protein fixed using a restraint constant of 10.0 kcal·mol−1·Å−2. The MD simulation then switched to the NPT ensemble (p = 1.0 bar), using the Langevin thermostat with a collision frequency of 1.0 ps−1, to equilibrate the ions and water density for 2 ns. The restraint force on the protein was then removed and the production run began with the NPT ensemble (p = 1.0 bar) using a time step of 2 fs. All simulations used the SHAKE algorithm – to constrain covalently bonded hydrogen atoms and the Particle Mesh Ewald (PME) method  to calculate long-range electrostatic interactions, with a cutoff distance of 10.0 Å. Histidines are represented as HIE (neutral charge: hydrogenated Nε, aromatic Nδ). Duplicate MD simulations were performed to verify that the reported dynamic behaviors of each protein are representative in the final MD runs. MD production runs were performed for at least 200 ns, which should be of sufficient length to establish the conformational stabilities of proteins of this size.
Using Ptraj to monitor the overall structural changes in reference to the starting structure, the root-mean-square deviation (RMSD) for each protein was calculated as a function of production run time. If the plot of the RMSD versus time forms a plateau, the protein likely adopts a solution-stable conformation; however, a widely fluctuating RMSD plot indicates a flexible protein in solution. To quantify the mobility of each residue, root-mean-square fluctuations (RMSF) were calculated using the average protein conformation as the reference state. The RMSF values presented in this paper are calculated from 10 ns to the end of each simulation (approximately 200 ns) to allow adequate time for the protein to fully adopt its stable solvated conformation, if one was at all achieved. This ensures that the RMSF plot differentiates flexible residues from stationary residues during the time that the protein samples its solution-stable conformations. In both RMSD and RMSF calculations, all atoms were included.
The RMSF is related to the experimental B-factors reported by crystallographers, through a simple relationship (B-factor = (8/3)π2(RMSF)2), which could be compared with the experimental measured B-factors reported in the PDB files of the 30S subunits. However, the experimental B-factors for each r-protein found in the 30S subunits were nearly featureless for individual proteins, probably because the reported B factors reflect the mobility of the atoms within the whole assembled subunit and are not representative of the individual r-proteins. Hence, we did not compare the B-factors calculated from MD simulations with the experimental B-factors.
Snapshots of each protein at various stages throughout the simulations were visualized using Visual Molecular Dynamics  (VMD) to identify the flexible and stable regions of the protein. All images were made with VMD, which is developed with NIH support by the Theoretical and Computational Biophysics group at the Beckman Institute, University of Illinois at Urbana-Champaign.
Elastic network modeling
Because the Molecular Dynamics simulations require significant resources, we have also chosen to model the dynamics of the complete set of 30S ribosomal proteins with the more computationally efficient elastic network model , using the Anisotropic Network Model in particular , , ANM models permit us to investigate the dynamics of all of the 30S proteins more quickly but with less detail in the observed dynamics than MD, but with greater overall certainty about the large-scale motions of the structures. ANM models are constructed using the crystallographic Cα coordinates of each protein and a cutoff of 13 Å. Due to its coarse-grained design, the ANM is subject to the “tip effect” – in which highly extended points (Cα) experience exaggerated motions, which would place disproportionate weight on the most mobile residues. To compensate for this effect, we calculate the RMSF of each residue position in each structure and remove extreme outliers from subsequent analyses. The “tip effect” residues removed in this study are Arg88 and Gly89 from T. thermophilus S15, and Gly8, Val9, Val10, and Val11 from T. thermophilus S17. We also use RMSF to make comparisons between 16S rRNA contacting residues and non-contacting or highly conserved residues. The definition of contacting residues and conserved residues is the same in both the ANM calculations and the MD studies.
Statistical analysis of contact residue mobility
To statistically determine linkages between highly mobile and contacting residues or conserved residues from both ANM calculation and MD simulation, we calculate an enrichment factor for each protein defined as the ratio of the average RMSF for contacting over non-contacting residues. An enrichment factor greater than 1 implies that the contacting residues are more mobile than the non-contacting residues. However, an enrichment factor less than 1 implies the reverse. The statistical significance (p-value) of the enrichment factor is calculated based on the permutation test explained as follows. For a protein of N residues, C of which are contacting, we have an observation of the enrichment of RMSF at the contacting residues relative to the non-contacting residues. Let this ratio be O. We then randomly select C residues from the protein and calculate the analogous ratio between this random set and its compliment. Performing the random selection 10,000 times, we construct a distribution of enrichment values within random sets of C residues. The significance (p-value) of our initial observation, O, is then the proportion of random samples that have an enrichment greater than O. A small p-value (e.g., p<0.01) implies that a random set of C residues is unlikely to have an enrichment factor equal or greater than the observed ratio O. This not only means that the contacting residues are more mobile than the non-contacting residues, but that there are very few subsets of size C exhibiting the same magnitude of mobility.
S15 Contact residues, at 3.5 Å cutoff distance. This table provides the protein residues of S15 in contact with 16S RNA, for both E. coli and T. thermophilus. Residues colored red have conserved identity in the sequence alignment of the two proteins; those in green have conserved type, i.e. basic, acidic, polar, nonpolar, or aromatic. Some residues may contact more than one nucleotide.
S17 Contact residues, at 3.5 Å cutoff distance. This table provides the protein residues of S17 in contact with 16S RNA, for both E. coli and T. thermophilus. Residues colored red have conserved identity in the sequence alignment of the two proteins; those in green have conserved type, i.e. basic, acidic, polar, nonpolar, or aromatic. Some residues may contact more than one nucleotide.
S20 Contact residues, at 3.5 Å cutoff distance. This table provides the protein residues of S20 in contact with 16S RNA, for both E. coli and T. thermophilus. Residues colored red have conserved identity in the sequence alignment of the two proteins; those in green have conserved type, i.e. basic, acidic, polar, nonpolar, or aromatic. Some residues may contact more than one nucleotide.
The authors acknowledge the use of high performance computing facility provided by the University of Memphis, and would like to thank Timothy Robbins, Jesse Ziebarth, and Alex Lott for their countless conversations which helped shape this project.
Conceived and designed the experiments: RLJ YW. Performed the experiments: BB MTZ YW. Analyzed the data: BB MTZ YW. Contributed reagents/materials/analysis tools: BB MTZ YW. Wrote the paper: BB MTZ RLJ YW.
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domain: chemistry


text:
GANSBAAI, South Africa -- One night as my sister and I walked across the rugged yet strangely delicate terrain of a place called Farm 215, the path to our cottage lighted only by the stars and a flashlight, the wine-wobbly beam suddenly illuminated several sets of legs.|
We realized that we were standing in the middle of a small herd of horses, including two mares and their foals, that roam the South African eco-retreat outside Gansbaai.
It was a perfect mother-child moment and a symbol of new beginnings in this Southern Hemisphere spring.
We were on a mother-daughter voyage of our own as we ventured off the beaten track across South Africa's Western Cape province, breaking the confines of Cape Town and entering a wonderfully natural world whose mountains are a cross between the San Gabriels around L.A. and the backdrop of a John Ford Western.
I wanted to show my mother and sister a country that had attached itself to my heart.
On my first trip 10 years ago, I came as the wife of a South African who had left during the depths of apartheid. Five years later, I came as a widow on a solo journey to toss my husband's ashes into the Indian Ocean off the beach town he loved.
This time, I came as a daughter and sister on a trip that turned out to be a celebration of family ties.
Even when we took to the water, we had the mother-child thing going on. We were in the Overberg, a rustic area southeast of Cape Town whose coast is the premier breeding ground of the southern right whale. We saw a mama whale and her baby only a few yards from our boat on the way to a dive in "shark alley."
My sister, Alison, and I had decided to get into a shark cage to see some great whites on their own turf. Our mom was happy to stay on deck.
You get into a cage attached to the side of the boat, and as cold water starts to seep under your wetsuit, you try to remember to keep your hands and feet safe inside the cage, but the buoyancy keeps defeating you.
We saw eight great whites. The biggest, our marine biologist guide Nicola told us, was about 15 feet long and probably a female because of its girth.
The shark-diving outfit, Marine Dynamics Shark Tours, is committed to preserving what it calls the world's most misunderstood animal. I did find sharks less sinister after the trip.
But maybe none was more intent on preservation than the stylish Farm 215, a 2 1/2 hour drive from Cape Town along a gorgeous coastal road.
A nearly 2,000-acre private reserve, Farm 215 is committed to protecting indigenous plants called fynbos. We saw fynbos blooming everywhere -- delicate purple plants that looked and smelled a little like lilacs, and yellow buds that washed over the landscape in front of our postmodern cottage down to the ocean a few miles away.
Farm 215 also emphasizes sustainability when it comes to food and drink. The big chalkboard at its restaurant lists all the bottles on offer from the winery next door, with vineyards so close we could see them from our cottage.
We got into the local spirit with three wine-farm lunches in a province that's a smorgasbord of stunning wine regions.
The first, Bread & Wine, outside the town of Franschhoek, is famous for homemade bread and charcuterie. It's almost as famous for its cozy courtyard dining.
We also enjoyed the veranda at the Black Oystercatcher Winery's restaurant in a new Elim district wine region. It's about half an hour from Farm 215 on a dirt road that had us stopping once to let a herd of cattle cross and again as a tortoise slowly made its way to safety.
My favorite wine-farm lunch, and favorite wine region, was at the Salt of the Earth farm stand and restaurant in the dreamy Hemel-en-Aarde (Heaven and Earth) Valley, near the whale-watching town of Hermanus.
We spent a two-hour lunch on the porch, enjoying the scenery, food and Spotty, the tree-climbing dog. Just up the road is my sister's favorite South African winery, Hamilton Russell, known for its very Burgundian Pinots.
Our most local meal was during our stay at the fabulous Babylonstoren in the Winelands. It was our big splurge, at about $500 a night.
Our cottage was something out of a home design magazine, with traditional Cape Dutch architecture, whitewashed walls and clean lines, but it got playful with the vernacular, adding a glass cube of a kitchen.
Waiting for us on the kitchen table was a box of produce picked that day from the extensive gardens a few steps away. After we explored the beautiful grounds, we roasted the vegetables and tossed them with parmesan and pasta, and then scarfed it down with the local wines that came with the room.
Not everything was so expensive. One of my favorite stays was at Braemar Villa, a self-catering cottage in the slightly boho fishing village of Kalk Bay, on the eastern, False Bay side of Cape Town.
It was a rambling 100-year-old family home with four bedrooms and a view of the harbor from the classic South African veranda, and it cost about $100 a night.
We also had locally sourced meals at the trendy but laid-back Olympia Cafe and a legendary fish-and-chips joint called Kalkies.
Kalk Bay is the ideal base for exploring the peninsula south of Cape Town, including the penguin preserve at Simonstown. On a trip with lots of signs about protecting nature, or protecting yourself from nature, this was my favorite: Warning -- please look under your vehicle for penguins.
Down the road, you reach Cape Point, the most southwesterly point in Africa, a craggy outcropping that seems to look out to eternity. But the southernmost tip of Africa is Cape Agulhas, about a three-hour drive east, where the Atlantic and Indian oceans meet.
As I watched my sister wade slowly into the cold water, I thought about my family and traveling to the end of the Earth together. And I thought about the last time I stepped into the Indian Ocean, to say goodbye to a man who belonged to this beautiful land.
He was lucky. And I was lucky.
I am still lucky.
IF YOU GO
Telephones: To call the numbers below from the U.S., dial 011 (the international dialing code), 27 (country code for South Africa) and the local number.
Where to stay:
Farm 215, near Gansbaai in the Overberg region east of Cape Town; 28-388-0920, farm215.co.za/index.html. Rooms start at about $99 a night to about $163 for the free-standing Fynbos Suites.
Braemar Villa, 6 Harris Road, Kalk Bay, Cape Town; 84-661-0131, From about $75 a night. Four bedrooms.
Babylonstoren, 21-863-38-52, babylonstoren.com. Near Franschhoek in the Winelands, about a 45-minute drive from Cape Town's airport. A double cottage is about $500 a night.
Where to eat
Kalkies, a fish-and-chips cafe on the harbor in Kalk Bay. A meal will cost you $5 or less.
Olympia Cafe, 134 Main Road, Kalk Bay; 21-788-6396. Meal about $10.
Bread & Wine Vineyard Restaurant, Happy Valley Road, Franschhoek; 21-876-3692, moreson.co.za/bread-and-wine/. On the grounds of the Moreson winery. Lunch with wine about $15
Salt of the Earth, R320 Hemel-en-Aarde Valley, Hermanus; 82-922-3815. Lunch with wine about $10.
Black Oystercatcher Restaurant, R317 (Moddervlei Farm), Bredasdorp; 28-482-1618, blackoystercatcher.co.za/index.html. In the Elim wine district not far from Cape Agulhas. Lunch with wine costs about $12.
What to do: Marine Dynamics Shark Tours, 5 Geelbek Street, Kleinbaai; 79-930-96-94, sharkwatchsa.com/en/home/, offers shark dives out of Gansbaai. About $160, including breakfast and snacks.
To learn more: South African Tourism, southafrica.net/sat/content/en/us.
Matherville, IL Details
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domain: geography


text:
Why are murders increasing in the metro Denver area? – ~ News
Criminologists say there are no simple explanations or solutions.
DENVER — 2022 has been a violent year in metro Denver. One major area of concern is the rising number of murders.
There have been 55 murders in Denver this year, 10% more than this time last year, which had the most murders in Denver since at least 1981.
It’s a similar story in Aurora. Last year, the city had 44 murders, the most since at least 2011. This year, there have already been 28 murder victims, nearly 50% more than the same time last year.
Metro State professor Stacey Hervey said the reasons for the rise in murders this year are varied, and she doesn’t see it getting better anytime soon.
“We have a large juvenile population. Juvenile populations tend to drive the crime rate in big cities, and then we have a huge problem with fentanyl and opioids all across the country, but especially in Denver,” Hervey said.
RELATED: ‘What we are seeing is not acceptable’: Denver Police chief concerned over rising crime in LoDo
Hervey also said the increases in murders in Colorado and nationwide this year are, in part, the result of a general shift in policing after the George Floyd protests in 2020.
“We really asked police officers to not be as involved, defund the police, ask them to come up with different ways. And that’s all good, but the reality is crime is still going to occur and there are people out there who are going to take advantage of other people,” Hervey said.
RELATED: Suspect wanted in 2019 death of roommate in Breckenridge
RELATED: Commerce City Police investigating Monday morning homicide
RELATED: Policía investiga homicidio in Commerce City
SUGGESTED VIDEOS: Investigations & Crime

domain: sociology


text:
I used to be a guru in C2, but havent used it for 2 years, coming back I cant figure out for the life of me how to draw a line.
I have the canvas object added to the project. I dont know if this canvas object is part of C2, or some plugin I installed years ago.
Anyway, when I do Canvas-> Draw line from (20,20) to (200,200) with color "black" and line width 1.0
Nothing happens no lines are drawn.
How do you define which layer the canvas is drawn on?
Any ideas? Probably something really simple.

domain: hobby


text:
Big little news, a newsstand and bottle shop adapted to Capitol Hill from the Pike / Pine LGBTQ nightlife entrepreneur Joey burgess and Tracy taylor, the general manager of proximity Elliott Bay Book Co., open this week on E Pike.
How did two of the neighborhood civic and business leaders come up with their plan for a first collaboration by starting a new pike / pine business?
âIt seemed to be in the middle of a pandemic,â Taylor said, âwhy not print and open a small business on Capitol Hill?â
Taylor says the double-faced challenges of the pandemic and a ‘let’s work together on something’ approach grew out of her work with Burgess to represent the neighborhood as Pike / Pine pushes and pulls Seattle City Hall For attention and resources, the bustling but difficult district has faced explosive growth in recent months and years.
âWe worked together on this neighborhood and city thing for a while, but we looked for a project and it just opened up,â Taylor said.
CHS reported here on the newsstand project and the long-standing vintage pike / pine company going live. No Parking as owner Billy Hutchinson decided as a cancer survivor that he was ready to leave the brick and mortar retail business in the era of the pandemic.
Meanwhile, it’s been an era of reading for Capitol Hill’s retail ventures during the pandemic. In December, âlibraryâ store – its titles are organized by theme – Oh hello again open on 15th Ave E. And the local Fuel coffeehouse chain is in the midst of a bookish makeover as it is part of the Ada’s family of companies.
With a twist on the echoes of the past like Broadway News which closed in the summer of 2010, Big Little News offers magazines, periodicals, beer, wine, champagne and other small sundries and has “more than 250 foreign magazines, newspapers and zines and national âwhen it opens.
Taylor, who remains in her role as Executive Director of Elliott Bay and is a major reader, provided an eclectic mix of recommendations, including the ‘phenomenal’ The dog magazine (a “magazine for smart homeownersâ-â You don’t even have to have a dog to appreciate it â, says Taylor) and Playgirl.
âThis year, I read fewer books. I listened to more books. For me, it was all about attention span, âTaylor says. “Magazines kind of fill that niche that isn’t a Tweet.”
Big Little News is now open 11 a.m. to 7 p.m. daily at 1102 E Pike. You can find out more about biglittlenews.com.
DID YOU FIND THIS ARTICLE USEFUL?
Donate money to the CHS and support local journalism dedicated to your neighborhood. REGISTER HERE. Become a subscriber on $ 1 / $ 5 / $ 10 per month to help the CHS provide community news NO PAYWALL. You can also register a single annual payment.

domain: news


text:
Seifu & the Demon Fox Girl
Seifu & the Demon Fox Girl Tags, Control and description
About Seifu & the Demon Fox Girl
You can play Seifu & the Demon Fox Girl free online free games at bullgames.net. It has tags: Adventure,Platform,Fighting,Rpg,2d,Indiegame,Seifu,Demonfox,Poliuxdimension,Demonfoxgirl,Scrollgame,Bossfighting. It has 349 total plays and has been rated 0% (1 like and 0 dislike), find the fun and happy day. If you want to play more free games, we find some of the game: Elastic Girl, Commando Girl, Demon Shift and Fisher Girl. To play other games, check out the new games or best games page.

domain: game


Primates Gut Microbiome is Also Subject To Lifestyle Changes
Primates are an order of mammals belonging to tropical regions, generally as forest dwellers, surviving in a natural habitat with a different diet and lifestyle. …Read more
Ocean Harvest Technology produces seaweed-based functional feed ingredients for animals. Together with BaseClear, the company is now investigating the effects of its seaweed blend on the animal microbiome and health. “On the market you hear a lot of claims about new gut health ingredients, but few of these claims are backed by clear evidence. At Ocean Harvest, we work with BaseClear to create such data so that when we say we have a strong prebiotic, we can prove it.”
Ocean Harvest Technology develops and manufactures animal feed ingredients based on seaweed. Its product range consist of seaweed blends for livestock and companion animals, which are based on a mixture of different species of brown, green and red macroalgae. OceanFeed™ blends contain prebiotic polysaccharides and other natural bioactive components that enhance gut microflora and not only support a positive immune response but also a healthier gut in general.
There is an increasing interest in the status of the gut microflora of animals and the effect of feed on this indicator of gut health. Jason Sands, product portfolio manager at Ocean Harvest Technology in the UK, explains: “For a long time, farmers relied on antibiotics and other chemical additives to ensure animal health. However, the overuse of antibiotics has led to resistance and regulators are now banning them in an increasing number of countries. Farmers are therefore in need of more sustainable solutions to improve the health of their animals. The analysis of the microbiome can play an important role in that, since an animal’s health is strongly affected by the status of its microbiome.”
Derek Butler, commercial director at BaseClear, confirms this. “We are observing an increasing demand for the analysis of the microbiome of animals. While a few years ago, this type of analysis was mainly requested for model animals, now we see a growing interest in the analysis of the microbiome of agricultural animals. Sometimes the questions are related to antibiotic resistance and residual antibiotics, while in other cases it is more related to feed conversion rates.”
Graham Ellis, CEO of Ocean Harvest Technology, expects that in the near term, the analysis and knowledge of the animal microbiome will prevail over the analysis of the human microbiome, although currently the analysis of the human microbiome is technically leading. “We have much better control over the diet and living conditions of animals, while humans have different diets and different stress conditions. It is therefore significantly easier to obtain statistical outcomes from the analysis of the animal microbiome versus that of humans.”
Ocean Harvest Technology started a collaboration with BaseClear in 2018, since they didn’t want to make claims about the prebiotic effects of their animal feed ingredients without having scientific backing. “On the market you hear a lot of claims about new gut health ingredients, but few of these claims are backed by clear evidence. At Ocean Harvest, we work with BaseClear to create such data so that when we say we have a strong prebiotic, we can prove it.” says Ellis. The company has already demonstrated the effect of its seaweed blends on animal performance, but now they also want to show the underlying effect on the animal microbiome.
Within this project, BaseClear started to analyze the microbiome of pigs and poultry using 16S profiling. For this, Ocean Harvest Technology delivered samples of animals that were fed with normal feed and samples of animals that were fed with seaweed-containing feed. Sands elaborates: “There is more and more public information about how a healthy microbiome should look, and there is also growing evidence about how microbiome profiles correlate with the overall performance of animals. That is what we want to use for our research. We want to correlate microbiome profiles to the overall health and performance of animals, such as their feed efficiency, and see how this is affected by our seaweed blends.”
“In principle, we could even go one step further and do a deeper type of characterisation based on metagenomics and transcriptomics. That would provide even more information about what the bacteria in the gut are doing,” Butler elaborates.
When talking about the future vision, the ideal picture would be to use real-time animal microbiome analysis as a tool to offer farmers a customised or variable animal feed blend based on the analysis of their own animals. “This is an exciting idea. But it is therefore necessary to reduce the turnaround times and prices of the microbiome analysis. The state it is in now is fine for research and development, but not for the use as a tool for our clients,” Ellis says. Butler expects that this will indeed be possible in the future. “In fact, the technology for this is already available, namely the Oxford Nanopore sequencing technology, which we also have available in our lab,” he says.
“This collaboration project wouldn’t have been possible without the readymade RNA sample stabilisation tubes that clients of BaseClear can use to send their samples to the BaseClear laboratory”, says Ellis. “Many companies and institutes request clients to send the samples on dry ice or liquid nitrogen, which wasn’t really an option for us. You can’t go to a farmer and ask if he doesn’t mind taking a sample and storing it at minus eighty degrees! It wasn’t widely known that there are alternatives for that. We were very happy to discover that BaseClear were willing to accept sample tubes that can be transported at ambient temperature, which enabled us to do the research in the way that we wanted.”
Ellis concludes: “At Ocean Harvest, we’re very proud to be able to share these type of analyses with our customers and those intending to trial our products. Invariably, it’s the first time that they’ve seen data this clear and conclusive. We’re extremely happy that our collaboration with BaseClear is helping farmers make a confident decision to reformulate away from problematic ingredients like antibiotics, and to use natural options which are fundamentally enhancing the animal’s health and performance.”
If you want to learn more about the analysis of the animal microbiome, you are invited to attend the experts meeting that we have organised on the 28th of November in our auditorium. Jason Sands from Ocean Harvest Technology will be one of the speakers.
For more information about Ocean Harvest Technology visit https://www.oceanharvesttechnology.com/.


text:
Chester B Heisler Jr.
Branch: Air Force
War or Conflict: WWII
Years of Service: 2
Chester Heisler joined the Army Air Corps in August of 1944 at the age of 18. He was trained as a pilot, but when women started to fly, he was retrained as a radar operator. He served in Guam, but was later transferred to Tinian. Chester was on Tinian when the atom bombs came through on the way to Hiroshima and Nagasaki. Chester had nothing to do with the bombs. Instead, the U.S. brought in a specially trained squad for the bomb flights. Chester and the other people on the island knew, however that something big was going on. After Tinain, Chester was transferred to the Philippines. Chester finished his tour of duty after the war ended in the Philippines. Chester left the Army Air Corps in 1946 and returned to Souther California to go to College. He graduated from Whittier College where he graduated Phi Beta Kappa with a major and minors in Phusics, Chemistry, and Calculus. In December 1949, Chester married Jeanne Nelson and then went to the University of Southern California to get his Maters and Doctorate degrees. Chester still reminisces about his days in the Army Air Corps.
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domain: history


First Read is a morning briefing from Meet the Press and the NBC Political Unit on the day's most important political stories and why they matter.
RESEARCH TRIANGLE PARK, N.C. -- After covering the craziest and most dispiriting presidential race of our lifetimes, last night's gubernatorial debate here in one of the other key contests of 2016 was a reminder that politics can be much more civil. The debate between incumbent North Carolina Gov. Pat McCrory (R) and challenger Roy Cooper (D), which was moderated by one of us, produced clashes over the state's anti-LGBT law HB2, the state's economy, health care, policing, voting rights, and even Donald Trump and Hillary Clinton. And guess what: There were no below-the-belt insults, no conspiracies, and no pants-on-fire falsehoods. Indeed, at the end of the debate, both McCrory (the state's governor) and Cooper (the attorney general) pledged to work together in helping North Carolinians affected by Hurricane Matthew's aftermath. It was all a jolting reminder of what American politics can be -- and usually is.
Donald Trump unshackled
Meanwhile, back in the presidential race, here was Donald Trump's Tuesday. He tweeted that "the shackles have been taken off me and I can now fight for America the way I want to." He criticized House Speaker Paul Ryan for essentially declaring the presidential race over. ("Paul Ryan opened borders and amnesty and bad budgets by the way, very, very bad budgets," he told Fox's Bill O'Reilly.). He blasted John McCain for withdrawing his support after the 2005 Access Hollywood video. ("John McCain who has probably the dirtiest mouth in all of the Senate has never heard," he added to O'Reilly.) His campaign released a new TV ad seizing on Hillary Clinton's near-collapse when she was sick with pneumonia. He accused Clinton of invading his space in the last debate, per NBC's Ali Vitali (when it was Trump who was the invading Clinton's space). And to top it all off, Trump told voters at his rally in Florida last night to vote on Nov. 28. (Ummm, Election Day is Nov. 8.)
Clinton camp: Downballot Republican candidates are going to "have to answer" for an unshackled Trump
In a gaggle with reporters yesterday, Clinton campaign chair John Podesta talked about the unshackled Donald Trump. "I guess he fires up the people who got to Alex Jones and Breitbart. But I think it is very unbecoming and I think that the real question, I think, ends up being for down ballot Republicans, people running for the Senate, people running for the House. Are they going to stay in line with this unshackled Donald Trump? A lot of them are deserting him. But I would remind a lot of the people who are deserting him, they propped him up for a very long time. So they have to answer for that." Podesta added, "But they also have to answer about whether they are going to stand with him when he foments and runs a campaign of division, of bigotry and now a race in the sewer. Are they with him? Or are they against him? That is a question they will have to decide. We will be traveling around the country, but other people running or House seats and for people running for Senate seats, they are going to have to say do they subscribe to the Alex Jones, Brietbart, Dave Bossie theory of American politics or do they want something better for our kids and our future."
USA Today analysis: 26% of GOP governors and members of Congress are refusing to back Trump
"Twenty-six percent of Republican governors and members of Congress are refusing to endorse GOP presidential nominee Donald Trump," USA Today says. "Of the 31 Republican governors, 54 GOP senators and the 246 Republican members of the House (331 total), the survey identified 87 who are not endorsing Trump's candidacy as of late Tuesday."
Buzzfeed: Miss Teen USA contestants say Trump walked in while they were changing
"Four women who competed in the 1997 Miss Teen USA beauty pageant said Donald Trump walked into the dressing room while contestants — some as young as 15 — were changing. 'I remember putting on my dress really quick because I was like, "Oh my god, there's a man in here,"' said Mariah Billado, the former Miss Vermont Teen USA," Buzzfeed writes. More: "Trump, she recalled, said something like, 'Don't worry, ladies, I've seen it all before.' Three other women, who asked to remain anonymous for fear of getting engulfed in a media firestorm, also remembered Trump entering the dressing room while girls were changing. Two of them said the girls rushed to cover their bodies, with one calling it 'shocking' and 'creepy.' The third said she was clothed and introduced herself to Trump."
Early voting begins in battleground Ohio
Today, Arizona, Indiana, and Ohio join the states engaged in early in-person/no-excuse absentee voting. Here's the early-voting calendar:
Sept. 23: Idaho (thru 11/4), Minnesota (thru 11/7), South Dakota (thru 11/7), Vermont (thru 11/7), and Wyoming (thru 11/7)
Sept. 24: New Jersey (thru 11/7)
Sept. 29: Illinois (thru 11/7), Iowa (thru 11/8)
Oct. 9: Maine (thru 11/3)
Oct. 10: California (thru 11/8), Nebraska (thru 11/7)
Oct. 11: Montana (thru 11/7), New Mexico (thru 11/5)
Oct. 12: Arizona (thru 11/4), Indiana (thru 11/7), Ohio (thru 11/7)
Oct. 17: Georgia (thru 11/4)
Oct. 19: Kansas (thru 11/7), Tennessee (thru 11/3)
Oct. 20: North Carolina (thru 11/5)
Oct. 22: Nevada (thru 11/4), DC (thru 11/5)
Oct. 24: Alaska (thru 11/8), Arkansas (thru 11/7), Colorado (thru 11/8 mail), Massachusetts (thru 11/4), Texas (thru 11/4), Wisconsin (thru 11/4)
Oct. 25: Hawaii (thru 11/5), Louisiana (thru 11/1)
Oct. 26: Utah (thru 11/4), West Virginia (thru 11/5)
Oct. 27: Maryland (thru 11/3)
Oct. 29: Florida (thru 11/7)
Nov. 3: Oklahoma (thru 11/5)
On the trail
Hillary Clinton campaigns in Pueblo, CO at 3:45 pm ET and then in Las Vegas at 10:30 pm ET… Donald Trump stumps in Ocala, FL at noon ET and then in Lakeland, FL at 3:00 pm ET… Mike Pence hits Virginia and North Carolina… And Bill Clinton is in Iowa.
Countdown to third presidential debate: 7 days
Countdown to Election Day: 27 days


text:
8500 Homes Without Power Following Light ...
Emergency crews are working to restore power supply to about 8,500 people in the Blue Mountains.
Endeavour Energy responded to the outage after lightning strikes struck power lines earlier this afternoon.
Lightning interrupted power to homes and businesses in Springwood, Winmalee, Faulconbridge, Valley Heights, Linden, Hawkesbury Heights and Sun Valley.
“Emergency crews are currently patrolling the area to commence the restoration process,” an Endeavour Energy spokesman told The Daily Telegraph.
“Until these patrols are completed it is not possible to give an estimate of the time it will take to restore power supply to affected customers.”
He urged people who require power for medical equipment to check their battery supply and “consider acting on their back up plan”.
Endeavour Energy thanked residents for their patience as they attempt to restore power.
Source - News archive
Lightning sparks around 100 fires in Sou ...
Firefighters have responded to an estimated 100 lightning-caused fires across the Rogue River-Siskiyou National Forest in southwest Oregon since Sunday. As a result, the U.S. Forest Service is bringing in additional resources, according to a Monday afternoon news release. Fires are also burning in other parts of the state.
The Hendrix fire, which had burned an estimated 170 acres southwest of Ashland as of 3 p.m. Monday, was started by lightning Sunday, according to information from U.S. Forest Service's Facebook page.
Nearby, fires in the Wagner Complex also caused by lightning are burning more than 200 acres.
The Gravel fire, burning 100 acres just 8 miles northwest of Prospect, Oregon, was caused by lightning Sunday, according to Northwest Interagency Coordination Center. The fire was 0 percent contained Monday.
Sunday lightning also started eight new fires in Crater Lake National Park, all a half acre or less in size. The park remains open and visitors are not at risk, according to a Monday evening news release from the park.
Also in southwest Oregon, the Canyon Creek fire is burning about four miles south of Canyonville and is estimated to be around eight acres, according to a news release from Douglas Forest Protective Association. Other small fires are also burning in the southwest region.
The Collawash fire is a 25-acre wildfire discovered Sunday on the Clackamas River Ranger District of the Mt. Hood National Forest. Crews are making progress in building a line around the fire, according to a news release. Fire danger is high across Mt. Hood National Forest, with high temperatures and low humidity providing fires the possibility to grow fast. No closures are in place but visitors should be cautious when driving in the area.
East of Salem, a fire is burning around 27 acres in the southeast corner of Silver Falls State Park. The Silver Creek fire is estimated to be 35 percent contained, according to a Monday afternoon news release. Steep slopes, thick undergrowth and large snags pose challenges for firefighters in the area. No injuries or facility damage have been reported. Smoke was reported Thursday evening and a fire attack was launched Friday, according to the release.
In eastern Oregon, the Currey Canyon fire in Malheur County is 50 percent contained with one residence threatened as of Monday morning. It's burned 3,100 acres so far. Firefighters expect to have it fully contained by Friday.
In Wheeler County, firefighters have contained the Solitude fire, which started July 8 and burned 708 acres near Spray, Oregon.
Source - News archive
On the 21st of August 2011, a thundersto ...
On the 21st of August 2011, a thunderstorm forced the pope to cut short his speech to an estimated 1 million young pilgrims gathered at a Madrid airfield to mark World Youth Day. As rain soaked the crowd and lightning lit up the night sky on Saturday, the 84-year-old pontiff skipped the bulk of the speech and delivered brief greetings in half a dozen languages.
Source - Did you know archive
How Hot Is Lightning?
Lightning is one of the most destructive forces in nature. But for all the folklore and legends amassed over human history on lightning, we know surprisingly little about the inner workings of this powerful phenomenon, including something as simple as how the current that flows through a thunder-inducing flash is related to the temperature of the strike.
"The basic physics of lightning, such as lightning initiation and lightning propagation, is not fully understood at this point," said Robert Moore, a lightning researcher from University of Florida in Gainesville.
"We know the basics, but not the details. So when anybody makes headway, it is major news."
Lightning causes more than $5 billion in damages every year in the U.S., as well as more fatalities than hurricanes.
"A direct hit from a lightning strike can melt a power cable or start a forest fire, where the amount of heat from the lightning plays a major role," said Xiangchao Li, a scientist from China who specializes in lightning research. Li and his team discovered a mathematical relationship between the current intensity and the temperature inside lightning. Their result was published last month in the journal Scientific Reports.
Although there are approximately 100,000 lightning strikes on Earth every single day, the randomness of the occurrences makes it difficult for scientists to study them in an effective or systematic way. So until Thor, the Norse god of lightning as well as other meteorological events, joins a lightning research team, scientists are left to their own devices.
Luckily such a device does exist. Known as an impulse current generator system, the device can create artificial lightning with currents up to tens of thousands of amperes. For perspective, a household or automotive fuse is usually rated well below a hundred amperes, and an electric current of just a few amperes can easily kill you. A natural lightning strike typically carries around 20-30,000 amperes of current. Certainly there are other factors such as size and setting of natural lightning that cannot be replicated in a laboratory, but just in terms of sheer current output, the lightning generated by the device can really give Thor a run for his money.
By using their artificial lightning system, Li and his team were able to dial up lightning strikes at will, with currents between 5,000 to 50,000 amperes. This resulted in artificial lightning strikes with temperatures as high as 17,000 F, twice as hot as the surface of the Sun.
This creates a new problem -- at such high temperatures, a normal thermometer would explode. And even if it didn't, it wouldn't react quickly enough to register the temperature of the lightning strike. Fortunately, there is "light" in "lightning." Li and his team were able to record the lightning's temperature within a millisecond by measuring the intensity of the light at various wavelengths.
After striking lightning at the same place over and over again, they concluded that the relationship between the current and temperature of lightning is a highly logarithmic one, meaning that the temperature difference between lightning strikes with 1,000 and 10,000 amperes is similar to those with 10,000 and 100,000 amperes. This result provides solid evidence for previous theoretical predictions that lacked the support of data.
"The next step would be to compare with measurements from rocket triggered lightning, or natural lightning, which can be done throughout the U.S. or China," Moore suggested.
That's right, rocket-triggered lightning. Essentially a glorified version of Benjamin Franklin's wired kite, scientists today have ways to siphon natural lightning from the sky by launching an electrically grounded rocket, as shown in the video below.
With a better understanding of the physics of lightning, scientists can help engineers to improve current protocols and infrastructures to better deal with lightning -- from weather warning systems to the design of power grids. Perhaps we can one day limit the power of Thor to only smiting Loki on the silver screen.
Source - Did you know archive
Thunderstorm24.com is devoted to thunderstorm and lightning around the European Continent. It offers info and news along with nowcasts and forecasts of convection and lightning. The site is under continuous development, aiming to continuous improvement. To do so, we would greatly appreciate comments and propositions that could help us level up our services.
Please do not hesitate to contact us on firstname.lastname@example.org, facebook and twitter