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In Gram-negative bacteria, the outer membrane is composed of an asymmetric lipid bilayer of phopspholipids and lipopolysaccharides, and the transmembrane proteins that reside in this membrane are almost exclusively β-barrel proteins. These proteins are inserted into the membrane by a highly conserved and essential machinery, the BAM complex. It recognizes its substrates, unfolded outer membrane proteins (OMPs), through a C-terminal motif that has been speculated to be species-specific, based on theoretical and experimental results from only two species, Escherichia coli and Neisseria meningitidis, where it was shown on the basis of individual sequences and motifs that OMPs from the one cannot easily be over expressed in the other, unless the C-terminal motif was adapted. In order to determine whether this species specificity is a general phenomenon, we undertook a large-scale bioinformatics study on all predicted OMPs from 437 fully sequenced proteobacterial strains.
We were able to verify the incompatibility reported between Escherichia coli and Neisseria meningitidis, using clustering techniques based on the pairwise Hellinger distance between sequence spaces for the C-terminal motifs of individual organisms. We noticed that the amino acid position reported to be responsible for this incompatibility between Escherichia coli and Neisseria meningitidis does not play a major role for determining species specificity of OMP recognition by the BAM complex. Instead, we found that the signal is more diffuse, and that for most organism pairs, the difference between the signals is hard to detect. Notable exceptions are the Neisseriales, and Helicobacter spp. For both of these organism groups, we describe the specific sequence requirements that are at the basis of the observed difference.
Based on the finding that the differences between the recognition motifs of almost all organisms are small, we assume that heterologous overexpression of almost all OMPs should be feasible in E. coli and other Gram-negative bacterial model organisms. This is relevant especially for biotechnology applications, where recombinant OMPs are used e.g. for the development of vaccines. For the species in which the motif is significantly different, we identify the residues mainly responsible for this difference that can now be changed in heterologous expression experiments to yield functional proteins.
Keywords:Outer membrane β-barrel protein biogenesis; Clustering; Hellinger distance; CLANS; Species specificity; Short linear motifs; GLAM2; C-terminal β-strand; BamA; β-barrel assembly machinery; Gram-negative bacteria; Outer membrane; Principal component analysis; Frequency plots
In Gram-negative bacteria, the cytoplasm is surrounded by inner membrane (IM) and outer membrane (OM), which are separated by an inter-membrane space, called the periplasm. Most of the newly synthesized proteome remains in the cytoplasm, but in addition, different machineries are involved in the translocation of non-cytoplasmic proteins to different subcellular localizations, including the inner or outer membrane, the periplasmic space, or the extracellular space. Some of these machineries recognize their substrate proteins by an N-terminal signal peptide (SP) for the translocation process, while other machineries are SP-independent. The IM, which is a phospholipid lipid bilayer, is mostly occupied by transmembrane α-helical proteins, by inner membrane lipoproteins on its periplasmic side, and by other membrane associated proteins on both sides of the membrane. In contrast, the asymmetric OM, which consists of phospholipids only in the inner leaflet of the membrane and lipopolysaccharides in the outer leaflet, is mostly occupied by transmembrane (outer membrane) β-barrel proteins, and by outer membrane lipoproteins on its periplasmic side [1].
The biogenesis of an outer membrane β-barrel protein (OMP) begins with the translocation of the newly synthesized, unfolded protein across the IM into the periplasm via the Sec translocation machinery, which requires a cleavable general SP. Once the unfolded OMP reaches the periplasm, it uses the SurA or Skp-DegP pathway to reach the OM. SurA, Skp and DegP are periplasmic chaperones, which interact with unfolded OMPs by protecting them from aggregation and thus help them to reach the OM [2,3]. It has been shown that the SurA pathway and the Skp/DegP pathway can work in parallel, but that the SurA pathway plays an important role when the cell is under normal growth conditions, while under stress conditions, the Skp-DegP pathway plays the major role [4,5].
Once periplasmic chaperones deliver the OMPs to the OM, the folding and insertion of the protein into the membrane is mediated by the β-barrel assembly machinery (BAM), without an external energy source [6] such as ATP or ion gradients. This machinery involves an essential multi-domain protein, BamA (Omp85), which consists of a 16-stranded transmembrane β-barrel domain, and of a large periplasmic part that consists of five POTRA (polypeptide transport-associated) domains. BamA is highly conserved in Gram-negative bacteria and also has homologues in mitochondria (Sam50) and chloroplasts (Toc75-V) [2]. In addition, the BAM complex, at least in E. coli, consists of four lipoproteins, BamB, BamC, BamD and BamE, among which only BamD is essential and conserved in most Gram-negative bacteria [2]. Recent HMM-based sequence analysis by Anwari et al. [7] showed that BamB and BamE are mainly present in α-, β- and γ-proteobacteria, while BamC is present only in β- and γ-proteobacteria. They also found a new lipoprotein subunit in the BAM complex, named BamF, which is present exclusively in α-proteobacteria.The BAM complex recognizes OMPs as its substrates via binding to an amphipathic C-terminal β-strand of the unfolded β-barrel [8], but the exact binding mode is still not clear. It was suggested that C-terminal β-strand binds to BamD [9], once the unfolded OMPs are delivered to the BAM complex by periplasmic chaperones. But a recent BamC and BamD subcomplex crystal structure shows that the unstructured N-terminus of BamC binds to the proposed substrate binding site of BamD [4]. The C-terminal β-strand of an OMP β-barrel domain typically contains an aromatic residue at its C-terminus. It has been reported that deletion or substitution of this C-terminal residue negatively affects the biogenesis of OMPs [10,11]. Also, in vitro studies showed that the E. coli OM porin PhoE, when lacking its C-terminal Phe residue, fails to open the Omp85/BamA channel [8]. In both studies, overexpression of the mutant OMP was lethal to the cells. At lower concentration, the mutant protein was tolerated and got inserted into the membrane. This leads to the suggestion that a weak insertion signal other than the C-terminal residue or β-strand is present [8].
Robert et al.[8] observed that the N. meningitidis OM porin PorA or its C-terminal β-strand did not open the E. coli Omp85/BamA channel, and the comparison of the C-terminal β-strands from N. meningitidis and E. coli OMPs showed a high preference of positive amino acids at the penultimate (+2) position in neisserial OMPs. When they mutated E. coli PhoE or its C-terminal β-strand, changing Gln for Lys at the +2 position, it did not open the channel any more; in contrast, a Neisseria PorA peptide with Gln instead of Lys increased the channel activity considerably. These studies and the fact that high concentrations of neisserial OMPs were lethal in E. coli cells, lead to the conclusion that the C-terminal insertion signal is species-specific and that the residues at the +2 position were important for this phenomenon. The number of peptides/proteins used in the comparison in the study [8] was very low, compared to the total number of OMPs present in the E. coli or N. meningitidis genomes; moreover, the phenomenon was only compared between two organisms, one β- and one γ-proteobacterial species. Since neisserial OMPs could be expressed in E. coli at low expression rates, either the neisserial C-terminal insertion signal is weakly recognized by E. coli BAM complex, or other β-strands in the full length protein might act as a weak insertion signal.
Thus, there seems to be at least some overlap in the peptide recognition. The intention of this study was to use computational methods to quantify this overlap, and to find out whether the observed (partial) species specificity of the insertion signal is exhibited by all Gram-negative bacterial organisms.
Results and discussion
We identified 22,447 OMPs from 437 Gram-negative bacteria using PSORTb [12], CELLO [13] and HHomp [14] as described in the methods section. These OMPs can be classified into different outer membrane protein (OMP) classes/families based on their function and the number of β-strands present in them, as these two features are usually coupled [14-17]. We used HHomp [14] to classify the proteins into different OMP families. A brief summary of the OMP classification obtained from HHomp [14] for our data set is shown in Table 1. We then used ProfTMB [18] and PSIPRED [19] annotations to identify and extract the C-terminal β-strands from the OMPs. To evaluate the phenomenon of species specificity, we initially tried to cluster the C-terminal β-strands using different methods, such as sequence based clustering in CLANS [20] and organism-specific PSSM profile-based hierarchical clustering. Since the sequences were highly similar and very short, the results obtained from these methods were not helpful to our analysis. We then used chemical descriptors and represented each amino acid in the peptides by five-dimensional vectors, thus representing each 10-residue peptide as a 50-dimensional vector. Next, we used dimensionality reduction techniques (principal component analysis) to reduce the dimensions to 12 (the lowest number of dimensions that still contains most of the difference information, see Methods). We then used all peptide vectors from an organism to derive a multivariate Gaussian distribution, which we describe as the 'peptide sequence space' of the organism. The overlap between these multidimensional peptide sequence spaces (multivariate Gaussian distributions) was calculated using a statistical theory method, the Hellinger distance. As described in the methods section, the pairwise overlaps between organism sequence spaces were used to cluster them in CLANS [20].
Table 1. Dataset classified based on OMP class
Clustering of organisms based on C-terminal β-strands
The pairwise comparison of the overlap between sequence spaces should help us to predict the similarity between the C-terminal insertion signal peptides, and how high the probability is that the protein of one organism can be recognized by the insertion machinery of another organism. When there is a complete overlap of sequence space between two organisms, we assume that all C-terminal insertion signals from one organism will be recognized and functionally expressed by another organism's BAM complex and vice-versa. When there is only little overlap between the sequence spaces of two organisms, we assume that only a small number of C-terminal insertion signals from one organism will be recognized by another organism's BAM complex. When there is no overlap, we assume that there is a general incompatibility.
As described in the methods section, we examined the overlap of peptide sequence spaces between 437 Gram-negative bacterial organisms and used the pairwise overlap measurement to cluster the organisms. Since the C-terminal β-strands are highly conserved between all OMPs [21], it was very difficult to select a particular cut-off for the distance measure. Thus, the clustering was carried out using all the distance measures obtained from the calculations. In the resulting 2D cluster map (Figure 1A), each node is one out of the 437 organisms, and they are colored based on the taxonomic classes (see the figure legend). During clustering with default clustering parameters in CLANS [20], the organisms tended to collapse into a single point, which illustrates that there is large overlap between the peptide sequence spaces. Thus, we introduced very high repulsion values and minimum attraction values in CLANS [20] during clustering. With these settings the organisms formed a central big cluster, but separated crudely according to their taxonomic classes. We repeated the clustering multiple times to ensure that this separation is reproducible. In the cluster map (Figure 1A), β- and γ-Proteobacteria form two sub-clusters, separated by the α-Proteobacteria. The very few δ-Proteobacteria in our data set cluster in the periphery of the γ-proteobacterial cluster. In the cluster map, E. coli strains cluster along with other γ-Proteobacteria. Even though Neisseria species cluster along with other β-Proteobacteria, they form a sub-cluster and are found in the periphery of the β-proteobacterial cluster. Note also that in this map, Helicobacter species form a distinct cluster well separated from the rest of the organisms. This core cluster includes H. pylori strains, H. acinonychis and H. felis, but not H. hepaticus and H. mustelae species. The remaining ε-proteobacteria species are scattered in the periphery of the cluster map. The distinct cluster formed by most Helicobacter species demonstrates that the sequence spaces of Helicobacter species are significantly different from rest of the organisms. The neisserial cluster had only very few strong connections even with other β-proteobacterial organisms, which means the overlap or similarity of peptide sequence space between Neisseriales with rest of the β-Proteobacteria is comparatively low. When we used stringent thresholds for the distance measure, we noticed that the Neisseria and Helicobacter clusters started to move even further away from the center of the cluster map.
Figure 1. Cluster map based on 437 sequenced Gram-negative organisms. In the cluster map each node represents one organism. The Hellinger distance was used to calculate the pairwise overlap between the multi-dimensional peptide sequence spaces of organisms. The calculated similarity or overlap was used to cluster the organism in CLANS. Figure 1A is colored by taxonomic class and Figure 1B is colored by the number of peptides in each organism.
Control experiments for clustering: randomly shuffled peptide sequences lose the signal for clustering
We noticed that the organisms seen at the periphery of the cluster map had a lower overall number of peptides, while organisms with more peptides are typically seen at the center of the circle. The cluster map in Figure 1B is colored based on the number of extracted peptides per organism. In Figure 1B, there are 99 organisms which have ≤ 30 peptides (colored in pink), 77 organisms with 31 to 40 peptides (colored in blue), 136 organisms with 41 to 60 peptides (colored in green), 66 organisms with 61 to 80 peptides (colored in red), and 59 organisms with more than 80 peptides (colored in brown). Even though H. pylori strains have a comparably high number of peptides (43 to 51 peptides), they still form a separate cluster in the periphery of the cluster map; therefore there must be an underlying organism-specific signal from the contributing peptides at least in this case.
To confirm the presence of the organism-specific signal, we took peptides from all the organisms and shuffled the positions of their amino acids randomly, and derived a new similarity matrix as mentioned in the method section which we clustered in CLANS [20]. Figure 2A shows the results from this test, where one can notice the taxonomic specific separations were completely lost. The cluster map in Figure 2B, colored based on the abundance of OMPs in an organism, shows that organisms with more peptides are in the center, and organisms with fewer peptides move to the outer rim of the cluster map. This test confirms that the there is a species-specific signal for which the position of the individual amino acids is important; this is lost when the residues in the peptides are shuffled randomly.
High preference of positively charged residues at the +2 position in Neisseria species
The comparison of the C-terminal peptide sequences in the β-barrel of selected OMPs of E. coli and N. meningitidis peptides by Robert el al [8] showed a strong preference for positively charged amino acids (Arg and Lys) at the +2 position in neisserial OMPs, which led to the suggestion of a distinct species specificity of the C-terminal β-strand recognition. Since the comparison was made from 11 and 9 OMPs from E. coli and N.meningitidis, respectively, we wanted to confirm this with a larger set of OMPs from the same bacterial species. The frequency plots in Figure 3A and B were created from 171 (E. coli) and 50 (N.meningitidis) unique C-terminal β-strands. Comparison between these plots demonstrates the high preference of Arg and Lys at the +2 position in neisserial OMPs. When we checked the frequency of amino acids at the +2 position for 22,447 peptides from all 437 organisms, we noticed that in the complete dataset, Arg and Lys are the top two preferred residues at the +2 position, and that they are present in 31.62% (3996 + 3102) of the peptides. A similar frequency of Arg and Lys (31.32% (2262 + 1794 out of 12,949 unique peptides)) is observed when only taking unique peptides into account (i.e. when duplicates are removed from the database). Figure 4 shows the percentage of Arg and Lys at the +2 position in 437 organisms; in this plot, Neisseria strains stand apart even from other β-proteobacterial organisms, and also from all other proteobacterial organisms. Neisseria strains (and a few α-proteobacterial organisms) have more than 60% of peptides with positively charged residues at the +2 position. Note, though, that also in all other organisms, positive charges are abundant there; for example, different Escherichia strains also have 25-40% of peptides with Arg and Lys at the +2 position. Thus, when these proteins are expressed, the Escherichia BAM complex should be able to recognize proteins with positively charged residues at +2 positions. As a matter of fact, there is experimental evidence for the functional expression of OMPs with positively charged residues at the +2 position in E. coli [22].
Figure 3. Frequency plots derived from unique C-terminal insertion signal peptides for Escherichia (Figure 3A) and Neisseria (Figure 3B) strains. Frequency plots were made from 188 unique peptides of 31 Escherichia strains and 50 unique peptides of 7 Neisseria strains. The +2 position is indicated by the arrow in the figure. Escherichia strains (Figure 3A) have no strong preference for any amino acid at the +2 position, whereas Neisseria strains (Figure 3B) have a strong preference for positively charged amino acids (Arg and Lys) at the +2 position. Hydrophobic residues are colored in blue and polar residues are colored in red.
Figure 4. Percentage of Arg and Lys at +2 positions. We calculated the percentage of Arg and Lys residues at the +2 position from all unique peptides from the 437 organisms; color is based on taxonomic class. The Neisseria strains show a high preference for positively charged amino acids at the +2 position compared to other organisms.
High preference of Histidine at the +3 position in porins (16-stranded OMPs) from β-proteobacteria
In the frequency plots (Figure 5) generated for each taxonomic class of Proteobacteria, we observed that the frequency of amino acids in the +2 positions were comparable, with the possible exception of the Neisseriae. In contrast to that, we observed a prevalence (up to 57% frequency) of His at the +3 position for β-proteobacteria, while the other taxonomic classes shared a similar, low (<15%) frequency of His in that position (Figure 6). 80% of the peptides with His at the +3 position belong to the β-proteobacteria and more than 92% of these peptides stem from 16-stranded β-barrel proteins (Porins, denoted as the OMP.16 class by HHOmp). None of the Escherichia C-terminal β-strands in our database have His at the +3 position, and experiments by Robert et al. were done with a Neisseria PorA peptide with a His at the +3 position. This might be the true reason why E. coli BamA didn't recognize neisserial peptides. When we further examined the available structures of porins from Neisseria, and we found the His at the +3 position to be present in the trimerization interface of the porins. Since the vast majority of the His residues at the +3 position of the C-terminal motifs were from 16-stranded porins that typically trimerize, this position might be relevant for trimerization in neisserial porins.
Figure 5. Frequency plots of C-terminal β-strands from Proteobacteria. Frequency plots generated from unique peptides of α-proteobacteria are shown in Figure 5A, of β-Proteobacteria in Figure 5B, of γ-Proteobacteria in Figure 5C, of δ-Proteobacteria in Figure 5D and of ε-Proteobacteria in Figure 5E. The frequency plots are overall very similar; an exception is the high frequency of His at the +3 position in β-Proteobacteria and of Tyr at the +5 position in ε-Proteobacteria.
Figure 6. Frequency of His at the +3 position. The percentage of His at +3 was calculated from all unique peptides from 437 organisms. A high preference for His at +3 is observed for 16-stranded OMPs of β-Proteobacteria. Since there is a high number of 16-stranded OMPs in Burkholderia strains (see Additional file 1 and Additional file 2), they were also annotated in the plot.
Additional file 1. The figure shows the number the over representation of OMP.16 proteins among β-proteobacteria and OMP.22 among α-proteobacteria.
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Additional file 2. The table lists the number of OMPs in an organism present in different OMP classes.
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High preference of Tyrosine at the +5 position in Helicobacter species
The separate cluster formed by Helicobacter species was an interesting observation for us, because it forms a more distinct cluster than Neisseria. This means that the peptide sequence space of Helicobacter species is more different from the rest of the organisms than even the one of Neisseriales. But the frequency plots (Figure 7A and B), generated from unique peptides of all Helicobacter species and H. pylori strains respectively, did not show a strong preference for any amino acid at either the +2 position and the strong preference of Tyr at +3 position is common among the c-terminal insertion signals. But, we noticed an uncommon strong preference of Tyr at the +5 position. The presence of a hydrophobic residue is common at +5 positions, but the presence of aromatic hydrophobic amino acids (especially Tyr) at the +5 position are highly preferred in H. pylori strains compared to other organisms (Figure 8A and B). Since the peptide sequence space depends upon the entire sequence, we cannot confirm that the separate cluster formed by the H. pylori is exclusively due to the residues at this one particular position. There is experimental evidence that the expression of various H. pylori OMPs in E. coli is problematic [23]. Fisher et al. noticed that as long as the expressed H. pylori OMP remains in the cytoplasm of E. coli, it is not lethal, but that once it is secreted to the periplasm by the Sec machinery, it becomes lethal to E. coli. They also mentioned - without showing data - that removal of the C-terminal β-barrel region resulted in toleration of the proteins in the periplasmic space. This probably means that the E. coli BAM complex didn't recognize the C-terminal β-strands of the H. pylori OMPs, and the subsequent aggregation of the OMPs in the periplasm and the blockage of the BAM complex lead to the lethality. The authors concluded that the difference in OM lipid composition of Helicobacter, which contains cholesteryl glycosides [24], might have imposed some structural constraints on the OMP structure, and that this structural change is not tolerated by other organisms resulting in the observed lethality of such constructs.
Figure 7. Frequency plot of unique C-terminal β-strands from Helicobacter species. 163 unique C-terminal insertion signals from 14 Helicobacter strains were used to generate this plot. The +5 position which has the strong preference of Tyr is marked with the arrow.
Figure 8. The percentage of Tyr (Figure 8A) and aromatic hydrophobic amino acids (Figure 8B) at the +5 position. For Figure 8A, we calculated the percentage of Tyr at the +5 position from all unique peptides from 437 organisms and for Figure 8B, we calculated the frequency of Tyr, Phe and Trp at the +5 position from all unique peptides from 437 organisms. In both plots Helicobacter strains shows a high preference of Tyr and aromatic amino acids at the +5 position.
OMP class-specific and taxonomy class-specific signals
We noticed that in some organisms, certain OMP classes of proteins are over-represented (see figure in Additional file 1). Examples are the prevalence of 16-stranded β-barrels in the genomes of some β-proteobacteria and 22-stranded β-barrels in the genomes of some α-proteobacteria (see Additional file 2). Moreover, of the 22,447 sequences in the data set, 33.82% (7591) sequences were annotated as OMP.nn by HHomp [14], which means there was no closely related homolog of known structure found for these proteins and thus, the number of β-strands in them is unknown. Thus, it is not possible to filter the dataset based on OMP class alone. But, as a control, we removed one OMP class at a time from the dataset and checked for differences in the clustering. When removing OMP.8 (Figure 9A) and OMP.12 (Figure 9B), two OMP classes that are not overrepresented in any of the taxonomy classes; this did not visibly affect the clustering. But when we removed the OMP.16 (Figure 9C) or the OMP.22 (Figure 9D) class, which have a high prevalence in β-proteobacteria and α-proteobacteria, respectively, this changed the clustering behavior of the respective taxonomic classes significantly; the organisms got scattered away from their position in the cluster compared to the situation in Figure 1A. This shows that the over-representation of certain OMP classes can influence the peptide sequence space, but since the proteins from over-represented OMP classes still contribute to the real sequence space of the organisms, we decided not to correct for this effect and used all peptides from the organisms in our experiments.
Figure 9. Control experiments to show the influence of overrepresented OMP classes. OMP classes OMP.8 (Figure 9A), OMP.12 (Figure 9B), OMP.16 (Figure 9C) and OMP.22 (Figure 9D) were removed and only organisms with more than 20 unique peptides were used in the clustering. Peptides belonging to OMP.nn and OMP.hypo (OMPs with unknown strand number and function) were not removed from the data set during the control experiments. Color legends are similar to the Figure 1A.
We also examined whether there is a more general signal from OMP classes, other than the signal from the over-representation of an individual OMP class that would influence the observed organism-specific signal. For this, we separated the peptides from an organism based on the OMP classification and selected the entities which had more than five unique peptides for further analysis. From this, we created two data sets of entities; one data set containing organisms from all taxonomic classes, but with C-terminal insertion signals only from 22-stranded OMPs, and a second data set containing organisms only from γ-proteobacteria, but in which individual organisms were split into multiple entities, each representing an OMP class that contained more than five unique C-terminal insertion signals. We clustered these data sets separately and the resulting cluster maps are shown in Figure 10A and B. In the cluster map in Figure 10A, each node is an organism, but only the C-terminal insertion signals from 22-stranded OMP class were considered for the clustering. In this cluster map, all the organisms clustered based on their taxonomic classes. In the cluster map in Figure 10B, all organisms are from γ-proteobacteria, but organisms with multiple OMP classes with more than five unique C-terminal insertion signals per class will result in multiple representative nodes. These nodes which belong to different OMP classes clustered based on the OMP classes. This confirms that there are independent contributions to the overall signal, from both the OMP classes and from taxonomy. Within one OMP class, there still is divergence in accordance with different taxonomic classes; but overrepresentation of a single OMP class in an organism influences the average motif of an organism.
Figure 10. CLANS cluster map of OMP-Organism class based entities. In figure 10A and figure 10B, each node is a representative of OMP-Organism entities that have more than five unique peptides of a single OMP class from an individual organism. In Figure 10A, entities are only from the OMP.22 class, which includes entities from all proteobacterial taxonomic classes. In Figure 10B, entities are only from γ-Proteobacteria and include different OMP classes.
In our study, we were able to reproduce the difference between E. coli and Neisseria C-terminal β-strands as found by Robert et al., which suggests a species-specific insertion signal for OMPs. But in contrast to the earlier report, we show that positively charged amino acids at the +2 position can not be the reason for the experimentally observed species specificity between these organisms, as Escherichia also contains C-terminal β-strands with positively charged amino acids at the +2 position. Moreover, there is experimental evidence which shows the functional expression of a heterologous OMP, YadA of Yersinia enterocolitica, with a positively charged amino acids at the +2 position, in E. coli[22]. The neisserial PorA protein and the neisserial C-terminal β-strands used by Robert et al. contained His at the +3 position, which is common for many OMP.16 proteins from β-proteobacteria and is not found in Escherichia OMPs; this might be the true difference in the recognition of C-terminal β-strands by the Escherichia BAM complex. Furthermore we found that Helicobacter strains form a distinct cluster in the cluster map, which is due to their very different composition of C-terminal β-strands. There is experimental evidence showing that expression of H. pylori OMPs in E. coli is lethal, and that this lethality can be suppressed by removing the C-terminal strand. When we looked at the frequency motifs from Helicobacter strains we did not notice a strong preference of any amino acid at the +2 or the +3 position, however we observed a strong preference of Tyr at the +5 position, which is not common in Escherichia or other Proteobacteria. We assume that this position may play an important role in the rejection of these C-terminal β-strands by the E. coli BAM complex. The examples of Neisseria and Helicobacter show that different positions in the C-terminal recognition motif can be relevant for heterologous expression of OMPs. We predict that in certain group of species the highly preferred residues in certain positions of the C-terminal insertion signals are responsible for the inadequate recognition of the C-terminal insertion signals by the E. coli BAM complex. In the future, mutation studies will have to be performed to prove the importance of these residues in the recognition step in the OMPs biogenesis.
As a result of our study, we have shown that there is a large overlap between the signals from C-terminal insertion peptides of different organisms, which suggests that in most cases, heterologous expression should be possible. OMPs can fold in vitro even without the help of any other proteins [25]. The BAM complex is an enzyme that makes the folding of OMPs into the outer membrane more efficient by increasing the reaction rate of a natural process. Enzymes modify reaction rates by changing the reaction route to lower the activation energy, and binding/recognition is part of this changed route. Thus, it is also important to consider expression rates: poor recognition might still lead to properly folded OMPs in the outer membrane of a heterologous host at low expression rates. But under overexpression conditions, the BAM machinery can probably not cope with poorly recognized signals that would lead to lower overall folding rates (considering that recognition is the first and probably in some cases rate-limiting step of the folding process). Different classes of OMPs have different folding rates, where small OMPs fold faster and more efficiently (again in vitro) than larger ones, which might explain why large OMPs seem to depend more heavily on an intact BAM machinery than small ones [26,27].
Since there are two different signals that contribute to the observed average motifs, from OMP class and from taxonomy, it is problematic to use averaged motifs or sequence logos to determine the compatibility of a given protein-organism pair. The main problem here is the overrepresentation of certain OMP classes in some organism groups; this overrepresentation shifts the average signals. It is more useful to determine for an individual C-terminal motif form a protein to be expressed, whether it is also present in any of the OMPs of the host organism.
The taxonomy-based specificity we observed here based on sequence space depends upon the entire peptide sequence, but at the functional level, these peptides are recognized based on the interacting residue positions in the C-terminal insertion signal peptide. The PDZ domain of the bacterial periplasmic stress sensor, DegS, also recognizes the C-terminal YxF motif in the last β strand of misfolded OMPs. This leads to the activation of the proteolytic pathway and the expression of DegP, which degrades misfolded OMPs [28,29]. Since the C-terminal β-strand is recognized by both the PDZ domain of the DegS protein and by the BAM complex, studying the co-evolution of interacting residues in both cases would help in understanding the divergence of the C-terminal β-strands between different Gram-negative bacterial organisms. Unfortunately, co-crystal structures of the BAM complex with its substrates are not available yet. With more experimental evidence about the substrate recognition sites for the C-terminal insertion signal peptide in the BAM complex, the co-evolution of the interacting amino acids can hopefully be studied in the future, which may shed more light on into the evolution of the BAM machinery in different Proteobacteria, and on its ability to recognize heterologous substrates for biotechnology applications.
Predicting outer membrane β-barrel proteins
In a previous study [30] to annotate the subcellular localizations (SCLs) for the proteomes of 607 Gram-negative bacteria, we developed the program/database ClubSub-P, in which we used programs like CELLO [13], PSORTb [12] and HHomp [14] to annotate OMPs. CELLO [13] and PSORTb [12] use support vector classifiers to annotate different SCLs of query sequences and are much faster than HHomp [14] which uses HMM-HMM-based search algorithms to predict and classify OMPs. Thus we used CELLO and PSORTb to scan all the sequences in the clusters of the ClubSub-P database. A random protein was selected from a cluster where CELLO or PSORTb had a positive hit for an outer membrane protein, and the sequence was analyzed with HHomp. When HHomp predicted a protein with more than 90% probability to be an OMP, we considered all the proteins in the cluster to be OMPs. We in addition selected all singleton sequences with positive prediction from CELLO or PSORTb and analyzed them with HHomp.
Finding the C-terminal β-strands
HHomp annotates/classifies OMPs based on the number of β-stands present in them. HHomp calculates/predicts this from homologous structures of OMPs. We transferred this annotation from the best hit in HHomp runs to the query sequences. HHomp also annotates secondary structure and β-barrel strand predictions using PSIPRED [19] and ProfTMB [18], which was used to extract the C-terminal (last) β-strand/motif for each OMP. The last β-strand predicted by ProfTMB [18] was extracted as the C-terminal motif from representative sequences and singletons, and further filters were applied to reduce the false positive rate; 1) 70% of the amino acids in the motif should have a β-strand prediction from PSIPRED [19], 2) If the C-terminal of the protein is more than 4 residues away from the C-terminus of the motif, we extended the predicted motif by up to 4 amino acids to find an aromatic hydrophobic residue [F,Y,W], else we extended the C-terminus of the motif to the end of the protein itself. 3) Additionally, if the motif length was less than 10 residues, we extended the motif towards its N-terminus. 4) Furthermore with the regular expression.
[^C][YFWKLHVITMADGRE][^C][YFWKLHVITMADGRE][^C][YFWKLHVITMADGRE][^C].[^C][YFWHILM] (an updated version of BOMP [31] C-terminal pattern), we searched for the existence of the alternating hydrophobic pattern in the motif which is typical for transmembrane β-strands.
Using the information from this representative C-terminal motif, we extracted C-terminal motifs from the rest of the sequences in the clusters. We used MAFFT [32] to align the sequences from the cluster, and used the start and end coordinates of the C-terminal motif discovered above in the representative sequences randomly selected from the clusters. Motifs were extended on the both sides, in cases where we encountered gaps in the alignment. The gaps were removed and then resulting motifs were subjected to alternating hydrophobic pattern matching.
The peptides we collected vary in length from 10 to 21 residues (only six of the peptides were longer than 21). We then applied GLAM2 [33], a gapped motif discovery algorithm, to find the strongest motif with a length of 10 from this dataset. We found 24,626 motif instances in 25,454 sequences, and only 232 motifs in this alignment had gaps. The gapped motifs were removed before further analysis. 20,135 of the motif instances were C-terminal to the protein itself (which means there were no additional domains at the C-terminal end of the β-barrel proteins). 437 organisms had more than 20 unique C-terminal β-strands, ranging from 21 to 171 peptides in different organisms. In total, the 437 organisms yielded 22,447 peptides, of which 12,949 are unique peptides.
Sequence based clustering
Since all of the peptides are 10 amino acids in length by default, we used the PAM30 substitution matrix for an all-against-all BLAST, with an E-value cut-off of 1000 and used the pairwise P-values to cluster the sequences in CLANS [20].
PSSM profile-based hierarchical clustering
The relative frequencies of the 20 amino acids were calculated for all 10 positions in the peptides from an organism. To obtain odds scores, the relative frequencies were simply divided by each residue's background frequency, which was calculated by shuffling the amino acid sequence in all the peptides from all organisms, and log base 2 was applied to obtain a PSSM matrix. The 20 x 10 PSSM matrices obtained for each organism were stored in a single 437x200 PSSM matrix, and correlation distances were calculated between each organism and agglomerative hierarchical clustering (average method) was performed via the pvclust [34], which calculates two types of p-values, AU (Approximately Unbiased) p-value and BP (Bootstrap Probability) value to indicate the likelihood of the cluster formation.
Peptide sequence space-based clustering
Chemical descriptors
To generate a peptide sequence space, each amino acid in the peptide sequences was represented by five chemical descriptors that are the first five principal components derived from 26 physiochemical descriptor variables using dimensionality reduction techniques [35]. The initial 26 physiochemical descriptor variables include the molecular weight, experimentally determined retention values from seven thin-layer chromatography runs, van der Waals volume of the side chain, three nuclear magnetic resonance shift variables, log P, six variables for semiempirical molecular orbitals, three variables for total, polar and nonpolar surface area, two variables for side chain charge and two variables for hydrogen bond donor and acceptor [35]. The five principal components derived from these 26 variables contain the maximal variations in the data set and they can be interpreted as the size, polarizability, and the lipophilic, steric, and electronic properties of all the amino acids [35]. The amino acid descriptors were originally derived for use as design variables in peptide design, and in the construction of combinatorial libraries to effectively search chemical property space [35]. Here we used them to describe the space occupied by the C-terminal β-strands and to measure how strongly peptide sequences of different organisms overlap. Using the chemical descriptors, each amino acid in the peptide was converted into a 5-dimensional vector; thereby, each 10aa peptide was represented as a 50-dimensional vector. Thus, the whole set of 22,447 peptides were converted to a 22,447 x 50 matrix.
Principal component analysis
Since the dimensionality of the data set (50) is larger than the sample size (minimum 21 peptides per organism), the dimensionality of the peptide vectors had to be reduced below the sample size (i.e., below 21 in our dataset) for further statistical analysis [36]. Principal component analysis (PCA) is a mathematical technique to reduce the dimensionality of data sets, while retaining most of the variation in the data set. This is achieved by projecting the original data vectors along the directions of maximal variation, called principal components (PCs). The first PC captures the maximum variation; the variation associated with consecutive PCs decreases rapidly. Thus, the original data set can be mapped into a lower dimensional space by projecting the original data on those PCs representing most of the variation [36,37]. We used PCA to reduce the dimensionality of our peptide sequences (22,447 x 50 matrix) by projecting the 50 dimensional chemical descriptor vectors onto the first 12 principal components, which represent 69.05% of the total variation in the data. We thereby obtained a 22,447 x 12 matrix that did not suffer from any problems in sample size.
Multivariate Gaussian fitting and Hellinger distance
Next, we fit a multivariate Gaussian distribution for each individual organism by calculating a 12-dimensional mean vector and covariance matrix, (e.g., for E. coli 536 which has 66 unique peptides, the Gaussian will be fitted based on a 66 x 12 matrix).
The Euclidean distance between means of peptide sequence spaces is not suitable for measuring the similarity between the C-terminal β-strands of different organisms. Instead, the similarity measure should also represent how strongly their associated sequence spaces overlap. To achieve this we used the Hellinger distance between the fitted Gaussian distributions [38]. In statistical theory, the Hellinger distance measures the similarity between two probability distribution functions, by calculating the overlap between the distributions. For a better understanding, Figure 11 illustrates the difference between the Euclidean distance and the Hellinger distance for one-dimensional Gaussian distributions. The Hellinger distance, DH(Org1,Org2), between two distributions Org1(x) and Org2(x) is symmetric and falls between 0 and 1. DH(Org1, Org2) is 0 when both distributions are identical; it is 1 if the distributions do not overlap [39]. Therefore we have for the squared Hellinger distance DH2(Org1, Org2) = 1 – overlap(Org1,Org2). The following equation (1) was derived to calculate the pairwise Hellinger distance between the multivariate Gaussian distributions, Org1 and Org2, where μ1 and μ2 are the mean vectors and Σ1 and Σ2 are the covariance matrices of Org1 and Org2, and d is the dimension of the sequence space, i.e. d=12
Figure 11. Illustration of the difference between the Euclidean distance and the Hellinger distance for one-dimensional Gaussian distributions. Two Gaussian distributions are shown as black lines for different choices of μ and σ. The grey area indicates the overlap between both distributions. |μ1−μ2| is the Euclidean distance between the centers of the Gaussians, DH is the Hellinger distance (equation 1). Both values are indicated in the title of panels A-D. A: For μ1 = μ2 = 0, σ1 = σ2 = 1, the Euclidean distance and the Hellinger distance are both zero. B: For μ1 = μ2 = 0, σ1 =1, σ2 = 5 the Euclidean distance is zero, whereas the Hellinger distance is larger than zero because the distributions do not overlap perfectly (the second Gaussian is wider than the first). C: For μ1 =0, μ2 = 5, σ1 = σ2 = 1, the Euclidean distance is five, whereas the Hellinger distance almost attains its maximum because the distributions only overlap little. D: For μ1 =0, μ2 = 5, σ1 =1, σ2 =5, the Euclidean distance is still five as in C because the means did not change. However, the Hellinger distance is larger than in C because the second Gaussian is wider, which leads to a larger overlap between the distributions.
Next, the Hellinger distance was used to define a dissimilarity matrix for all pairs of organisms. The dissimilarity matrix was converted to P-values, which were then used as input in CLANS [20] to compute a cluster map showing all organisms. CLANS is a graph-based clustering method that represents sequences as nodes. All nodes are connected by weighted edges where the pairwise similarity between the sequences determines the strength of the weight [20]. In our study, individual organisms were considered as nodes and the weight of the edges connecting the nodes was based on the pairwise Hellinger distance (pairwise overlap of sequence space) between the organisms. Hence stronger connections represent a larger overlap/similarity between the peptide sequence spaces, while organisms with high divergence in their C-terminal motifs are only weakly connected or completely disconnected in the cluster map. Initially the nodes are randomly placed in a 2D space and experience attraction forces according to how strongly they are connected with the other nodes. In an iterative refinement scheme, nodes move towards similar nodes with an attractive force proportional to the similarity between them. A small, overall repulsive force is applied to all pairs of nodes to keep them from collapsing into a single node. Since CLANS [20] uses non-deterministic dynamics, each run performed with the same dataset will result in a similar but not necessarily identical clustering. Thus, multiple clustering runs were performed to check the reproducibility of the final clustering. Because initial tests showed that with the default attraction and repulsion values nodes (organisms) were collapsing, we used very small attraction values (up to 0.1) and high repulsion values (up to 500) to avoid collapse of nodes and to obtain visually better clusters.
Frequency plot
The WebLogo [40] online tool was used to create the frequency plots, using custom colors. Only unique peptide sequences were used to generate all the frequency plots. The amino acid percentage plots were created using R version 2.13.1 [41].
Competing interests
There is no competing interest.
Authors' contributions
NP generated and analyzed the data. MH provided the initial script for pairwise Hellinger distance calculation. DL conceived the initial idea about the project and helped in drafting the manuscript. NP wrote the manuscript, MH and DL read and improved the manuscript. All authors approved the manuscript.
We are grateful for helpful discussions with Vikram Alva, Iwan Grin, Jack Leo and other department members; continuing support by the Max Planck Society, and specifically by Andrei Lupas, is gratefully acknowledged.
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Monday, 11 November 2013
How Do You Want to Live?
In last Monday's post, I told you that I was in Providence, Rhode Island for a conference on "Connected Aging" at the Business Innovation Factory (BIF) and that the overall issue to be addressed was the need for our culture
"to look at aging differently, that by framing aging through the lens of care and increasing weakness, we're missing whole opportunities to facilitate healthy aging – ones that support optimal personal choice in how we age..."
Among many interesting comments, Frank Paynter of Listics Review responded:
"That bit about seeing 'aging through the lens of care and increasing weakness' really spoke to me. How do we realistically re-frame that perspective while taking into account the limitations that have been piling up over the last few decades? I'm looking forward to your report!"
It will take more than one report to fill you in on what was for me an exciting day of new perspectives about aging.
To begin, I often write here about how, in retirement, we lose the daily camaraderie of the workplace, that can contribute to isolation and loneliness if we don't find other ways to connect with people.
Last Monday, I discovered that - at least for me (and probably many of you) - it's not just the general day-to-day, give-and-take of office banter. More importantly, I desperately miss the ongoing exchange of ideas that can't be avoided with a bunch of really smart, interested and interesting people. I got to do that again on Monday and it was thrilling to be in that milieu again.
Along with five talented and knowledgeable BIF facilitators, we were 12 invited participants from around the U.S. Without meaning to slight any others, here are a few:
• a woman who runs a dance class for aging Parkinson's patients
• a woman who for the past four years has been sharing a real-life Golden Girls home
• a man living in a condo that is a naturally occurring retirement community who for 12 years there has made it his daily job to show his neighbors how to enjoy their lives – with amazing results
• a man who teaches poetry writing at an assisted living center who says it is his work to "connect the dots in life"
• a woman who runs a rural non-profit where volunteers, mostly old women, make urgently needed home repairs such as roofing for those who can't afford them
• a corporate manager who is creating new visual experience and design solutions to aid elders and others navigate large retail stores
Most of these people are elders themselves – or they can hear it knocking on their door – and in the coming weeks and months, I'll do my best to get some of them to sit still for an interview for TGB so we all can benefit from their ideas and perspectives. You will find every one of them an inspiration.
There are so many new thoughts running about in my head that I will need to parcel them out one post at time.
One big takeaway from the meeting is that old and old-ish people all over America are individually "reframing the care and weakness lens" of aging by applying their knowledge and experience to enhance the lives of other people, often elders who may not be equipped, either physically or constitutionally, to do it for themselves.
Or, they are experimenting with new ways of being old – the Parkinson's dance class; community living arrangements; other projects that refuse to operate under the decline and disease definition of old age by focusing on people's assets rather than their debits.
These dynamic people I met are putting their personal talents, past training and experience to work on a small, sometimes individual, one-on-one scale to improve the experience of aging for others and, thereby, for themselves. The BIF people want to harness their innovation to apply on a larger scale.
Sometime during the afternoon session, there emerged a question that embodied the day's goal of finding new ways for us to continue to contribute, to grow, to stay connected and maintain purpose as we age.
When I heard it I said, "YES" in as big a way as that looks in print because in six simple words, the question makes clear everything I've been trying to say about old age for the past decade.
Here it is: How do you want to live?
It can be applied broadly to the public policy sphere as would include Frank Paynter's (and my own) concern with accounting for the inevitable exigencies of age without defining old age by them and it is equally relevant to personal, individual lives.
Either and both ways, it is a crucial question. Nothing can change in regard to aging without find good answers to it.
Therefore, if you are so inclined today, I would like you to take a whack at that question and consider what it means to you personally, to your community or to our overall culture - or all three.
Does thinking about it change what you personally want in your elderhood? Does it give you some ideas about how we might work to change the culture of aging? What new ways could we find for elders to continue to use their experience and knowledge to contribute?
Give it a try. There are no dumb answers.
At The Elder Storytelling Place today, Henry Lowenstern: Armistice Day
Posted by Ronni Bennett at 05:30 AM | Permalink | Email this post
Well, this really gets my blood going! I'd love to read interviews with such interesting seniors doing such good work. I know what you mean about missing the exchange of smart interesting people and surely blogs can be just that. I'm writing these days in answer to your essential question on how I want to live. We're the ones who will change the culture of aging by finding good answers to this question.
What a rush! I miss that conversation, especially with other women. One of the ways to remedy that is to get back out in our communities in some way. Great information Ronni.
Ronni, these are fantastic ideas.
Tell us everything.
The head librarian at my local library read my book and asked me to present a motivational seminar on any topic.
I haven't done this for 10 years.
Thought of a title:
"Get A Move On."
Meaning, seniors, take your collective life skills and put them to use. Where? In a school, food bank, senior home, animal shelter, everywhere you can make a difference.
"Uncle Sam Wants You."
(In Canada, it would be..
"Follow the Moose.")
Ronnie, this is fabulous. I can't wear to hear about the women with a "golden girls" house. I've been thinking and thinking about how to find one of those - especially on my limited income. Can't wait to hear what she has to say.
I want to live
in a small village type setting where I can walk out my door to a place with a cafe, library and shops
near the ocean
where I can meet up with people who enjoy getting together
where I can live within the means I will have
with less stuff to take care of than I have now
and a fenced in yard for my cats!
Holy crap! Maybe we're completely, 100% wrong about how we view aging. I mean, wrong in a way we've never seen before. Maybe we shouldn't treat age as different. Younger people need certain things to be physically and mentally well - how different is it for elders? Not at all! Why then have we been seeing ourselves as different, as a separate class or group? At all ages, and within age groups, humans differ greatly from each other. Maybe age is an artificial distinction. I am speechless at the possibilities of this new idea. Thanks, Ronni and BIF.
I think that I have a handle on life as I age....with a few changes. Perhaps a one story cottage instead of a three story condo. How about finding new ways of lifting books at my volunteer job. More laughter, more blogging, more writing, and more photography will make Mage less of a dull girl. Thanks for going to this, and thanks for stirring us all up.
I disagree - not with your enthusiasm but with the thought that elders are no different from five-year-olds, 25-year-olds and 55-year-olds, etc.
Our personal concerns are different. Our health is different. Our needs are different as is our experience, knowledge and our status in society.
You would not expect a teenager to be as responsible or take on as much in life as a 40-year old and to say that age is an artificial distinction is to deny reality of aging.
Nevertheless, we can find ways to take waning health (yes, it will happen to you, too, if you live enough) into consideration without making it the primary definition of getting old as we do now.
More to come over time.
This is all very exciting! I would be interested in follow-up information, links to websites or what ever is available to learn more about the programs these people are describing. I am especially interested in the one about rural women doing home repairs. Though my husband and I recently found ourselves in "retirement" years before we had expected to, we are looking for something more. Perhaps some of these ideas could help. Please keep sharing more about this, Ronni!
I have found I MUST have work in my life. Volunteering fills that bill for me, and the online work I do for a national Cairn terrier rescue keeps my computer skills growing. I returned to painting and I'm enjoying learning more than I ever got in college. I'm fortunate to have a few friends who enjoy a lively conversation about ideas, but I'm always on the look out for more. When I hear someone say they're bored, I'm puzzled as to how that can be. I guess I am living the life I want to live! Now that I've had that little revelation (thank you, Ronni) I think I'll take a break from picking on myself for all the stuff I'd like to do but don't seem to have time for.
Ronni, I disagree with your disagreement with Lynne. Each of us has to find our own reality within our minds. How we each perceive our world can help us cope with our aging reality (been there). We can either wallow in our fears or expand into life.
How do I want to live? I want to be useful to my family and my friends and the less fortunate.
I always thought that a great time to have lived would have been during the early days of film, working with the giants of that new industry--learning, developing film's potential, exploring ideas, grabbing the world's attention...and having a lot of fun, too. That's just how I feel about what it means to be older today -- so many people like you and those you met at BIF have been turning the world on its head about what aging means and so many of us are eagerly embracing it. We won't be around to see how good I trust and pray it will continue to get, but without the pioneers of today, the movement and momentum wouldn't have even gotten started. You are a true inspiration.
I'd like to see cooperatives of artists, writers, and craftspeople like those seen in Sweden. Everyone has their own private space but studio space, common areas, as well as household duties, cooking and meals are shared. Many in suburban areas have flower and kitchen gardens, and keep hens for eggs.
This provides companionship, mental stimulation, useful employment and conversation, as well as mutual support.
I keep writing about this idea on my blog but it seems that Americans and Canadians are essentially terrified of living in community. sigh...
I ask this sort of question every time I visit my mother at her assisted living facility. She should be at home but at 95 and going blind with macular d she couldn't stay there. I looked into costs of 24/7 help and it was prohibitive. It's one thing to be in your 60's, 70's and 80's and still be healthy. The golden girls home life is a great idea. If mom could have had this, I think she would have liked it. Someone who still drives, someone who likes to cook or can assist vision impaired roomies with cooking...being able to do something meaningful instead of looking forward to your three meals a day and watching TV. This current formula is not what I want. Yes, the facilities try to incorporate music, games, trips to the store and lunch, but you come back to your "room" that isn't your home. A lot of people die around you. Not a pleasant experience. I would like to see a concept like the 55 and older developments where you can age in place and still have amenities like the pool, gym, walking paths for use until you can't do it. Then stay in your home or buddy up. There would have to be nursing care incorporated into the development and it would have to be affordable.
Good for you on making the trip, taking the time to be there and share with us. Most elusive is how we find in-person opportunities to have these conversations with our peers.
Just a caveat here in geriatric studies.....It seemed that all the classes I took set about in the beginning dispelling myths about the elderly and aging. However, as our studies and projects developed it seemed that the myths began to get perpetuated...and we ended up back where we had started. It was very disheartening and I think almost an unconscious consequence. Perhaps looking at the assets of aging instead of the liabilities will carry us into the future with a reduction in our agism attitudes and perceptions.
Three versions of how do I want to live:
I want to have the maximum possible control over my own life.
I want to have the maximum possible control over how to meet my basic needs and over activities to give my life enriched meaning.
I want to live in a safe environment which affords me the maximum possible ability to make choices about meeting my basic needs, as well as those activities which give my life enriched meaning.
I did not think about how I wanted to live. But I retired to Cape Cod five years ago and today, at 75, I can say I'm living the life I want to live. I am active in an adult education community and in a quilt guild.I have a daughter, a granddaughter and 3 great-grandchildren nearby who respect my lifestyle and who could count on should I have physical disabilities (which I don't, for now). I live in a beautiful place, I have enough money to be comfortable although not to do some of the traveling I wish I could. But I traveled a great deal earlier so I don't feel deprived. I am mentally alive, physically able, and have a support network, I am giving to my chosen community. I'll keep on doing what I'm doing until I can't.
Where to start? I want to live by managing my own health (including Type 2 diabetes); staying mentally and physically active; having a good life with my new "old" husband; staying in our small house and having some improvements made; and reading and writing. I want to continue to drive (at least to the super-market and back). So far, so good.
I love this post. I am now living the way I always wanted to live but couldn't because of the pressure of a demanding job. I am a free-lance writer, covering art events in the SF Bay Area. I also advocate for justice in the arts; my latest columns are about the German government's lack of honestly about the 1 billion dollar treasure trove of Nazi era loot that was recently discovered. I also paint and do calligraphy. I walk every day and am looking for a dance/ exercise class for "seniors." I will be 69 in month and while there are health issues, life has never been better. Like many here, I will do what I am doing until I no longer can.
This is a most important topic. I know that I want to live in a caring community with plenty of opportunities to interact with all ages. I volunteer at a small library and this is a wonderful place for me to do my own contributions. I am healthy and strong and I hope to stay that way for a long while, but if I don't ,I do hope I will find another way to contribute something to my community.
Last week my 88 year old friend moved into a senior living apartment. I'm looking forward to seeing it.
I keep a close watch on where my friends go, and reflect on why they chose their new home.
I can't seem to put myself in any of these "boxes." Boxes mean places with rules, army style, no personal space or privacy.
"Zero fun sir."
Maybe it's because I worked in a profession that was run by the sound of bells. There is absolutely no privacy in a school.
We live in the house we renovated, a short walk to bus stop. We volunteer, swim, pilates, badminton, walk, ride in a cycling group, travel, go downtown every weekend.
We're busy every day.
Not bored.
Our cohorts are adamant about not going into a senior home, but who can predict the future?
I tell my mom "there is no finish line," that I will be the last one to leave the dance floor.
Is that just big talk?
So far, there is no building out there that we are attracted to for future living.
We don't want to be alone, yet we like our privacy.
We wish to be useful.
We don't want to be treated like toddlers.
If I end up a widow, I'd rather live in a tiny, one room home with garden, than a mini space on the 12th floor of a condo.
Of course I'd want a cat or two. Senior cats. With attitude.
And I'd want to live close to bus stop, library, stores, rec center.
So far I don't see little homes like that around Montreal.
But you never know.
I would LOVE to work on an all-female renovation team.
Where do I sign up for that?
Absolutely love this…
"to look at aging differently, that by framing aging through the lens of care and increasing weakness, we're missing whole opportunities to facilitate healthy aging – ones that support optimal personal choice in how we age…"
There appears to be this culture of sorrow once we hit 30.
Ageing provides continuous opportunities for strenght and empowerment.
Thank you
I've talked briefly about living in a 'commune' situation with my mates as we get older. At this stage I would still want my own space, but have friends close by for companionship and help.
I want to live as the creative curious woman that I am, not conforming to anyone's ideas of how I should act, dress or be at a certain age. I cherish this time of my life when I can do as I wish within my small means.
Hi, Ronni,
Thanks for all you do! and all you will do!
I am an RN with two extra years of study in Social Gerontology. I think the most important way we can change the ageing millieu is by learning to differentiate between aging and illness. We look at illness and call it aging. We need to be better educated. Old is not synonymous with illness....and illness brings a whole different ball game to anybody regardless of age. It is true we see more illness among the aging and aged, but illness is no respecter of age. The young can become ill and die.
And many of us will not experience crushing illness as we age. Many of us will experience cruching illness, but that is a separate issue than ageing. What to do if I get sick (?) is a far different question than how am I going to chose to live as an old person while I am well enough to keep truckin'? How am I going to deal with the changes that will surround me as I age?
One old woman gave me the best advice I ever got: "You just do what life calls on you to do."
Ronni, despite the travails of air travel today, I'm glad you were able to go to this conference. It seems to have accentuated the possibilities and assets of older age rather than the negatives and liabilities (we all hear plenty about those!). I don't have a lot to add since I'm late to the comments.
I think everyone has to find her/his own way, but I couldn't agree more with Riverwatch. Just because we're older doesn't necessarily mean we're disabled or ill (often interpreted as incompetent or less-than). It's true that age brings some limitations and that disability and/or serious illness may well be down the road if we live long enough. Still, these need not define elders as a group or as individuals until/unless they happen.
I also vote with the readers who noted that control over how we live (and I will add, for me personally, how I die) is vital. The old woman Riverwatch quotes at the end of her post probably had it pretty close to right on.
I want to get old surrounded by friends. From the workplace or someplace else. I don't want to transform in a grumpy old man that shouts at young people for living their lives.
Ronni, this post has gone over and over in my mind since reading yesterday morning.
Do I stay in my cottage by the woods, enjoying all I do and I am slowing down and isolated. I love it at this time. A healthy nonstop lady who just turned 79 or spend my last years in the big city and closer to children, grandchildren and people?
I have put my name on a waiting list of a retirement home with a 2 year waiting list - just in case. So will see how "this ones" life continues...
I am so happy that a friend referred me to this site. I have just retired from working in senior living for over 25 years. I retired because of my husband's declining health and wanting to spend more time with him - I am glad I can afford to do this, but at 67 I was certainly planning on working much longer - I loved my work and feeling that I made a difference in lives around me. Now I will be searching for that fulfillment in other ways - and hoping I can be a blessing to others.
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'Knocked Up' Freak Flies to 'Adventureland'
The project is written and directed by Greg Mottola, who also directed Starr's late summer cameo in "Superbad."
Beyond his basic casting, Variety offers no info on what, exactly, Starr will be doing in "Adventureland." We know that the film is set in 1987 and focuses on a recent college grad (Jesse Eisenberg) who takes a minimum wage job at an amusement park in order to pay for his dream European vacation.
In addition to "Superbad," Mottola and Starr previously worked together on an episode of "Undeclared." Although still best known to dedicated fans as Bill Haverchuck from "Freaks and Geeks," Starr reached a whole new audience this summer as the beard-growing Martin in "Knocked Up."


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OT - smoking. Angry rants welcome, support appreciated
DD - June 2011 TTC #2
Comments (8)
good luck..Im a smoker so I give you credit for quiting...if you did it once you can do it again :) and dont hate on yourself for having a moment (or weekend) of weakness
Bronwyn~Mommy to Jordan 05/2000,Rainbow Logan 6/2011, Rainbow Kaiyus 09/2013
"Maby you should eat makeup so you can try and be pretty on the inside"
Well, what's done is done!
Just don't go it, keep yourself distracted!
It's not just going to harm just you but your baby too.
It stays on your clothing & your hair.
I used to be a smoker.
I stopped & i gave in about a month after i had stopped & my DH got very upset with me. And I haven't had a smoke since then. It's been about 5 years now & in all honesty I'm completely grossed out by the smell on other peoples clothing. Especially here in Canada in winter. It's by far the nastiest smell EVER!!
Does your state have a quitline? That has helped me in the past..
Currently I smoke, quit twice on Chantix but like you life events lead me back to smoking.
I been researching e cigs, might try that route next.
2 big girls +1 little boy = Done!
I talk to walls. (#)
Thanks for responding.
Melissa, I'll look into the quitline. It's annoying because the second I smoke, I remember how much I love it and even though I know it's terrible, I just want to keep smoking.
DD - June 2011 TTC #2
I don't have much experience with that, since I have never been a smoker. (Besides the occasional cigarette while drinking back in college.) But, I understand that it must be SO hard for you. My grandmother hadn't smoked in over 40 years, but she used to say that she still loved the smell and never lost the urge to smoke one again. (She didn't, but it made me understand the addiction better.)
Just keep your sweet little girls smile in the front of your mind and imagine what her life would be like without you. :)
Remind yourself why you quit in the first place. Its still in your childs best interest if you do for many reasons.
I LOVED smoking. Like LOOOOVVEEEDDD...but I remind myself of how O would feel if I got cancer from smoking andwould leavemy kids w/o a mothers. Of course it could still happen, but the guilt of questioning whether I could have prevented it if I hadnt smoked would be devastating.
Its a lifelong battle for an ex-smoker. But you can do it again!
Good Luck:)
DS Cohen James 2008
DD Nova Lynn 2011 VBAC!
I second the quitline. Here they will offer you counselling, literature, and free nicotine patches. I have never had to quit smoking but I have friends who have used the quitline recently with some success.
My friend's dad used a lower dose of Wellbutrin (it has a different name when used for smoking cessation, but it's the same drug) to quit and it worked for him. He had smoked for over 40 years and is still smoke free 8 years later. It may be something to consider if you really can't break the craving. The side effect profile is pretty low and it apparently works well.
Good luck!
"I would be honoured to drink maple syrup in your igloos and chase wild beavers across the tundra while enjoying the politeness of your people" -Hasty
You smoked, you took a step backwards. Remember, it can very negatively effect your child if you choose to continue smoking. Just go through the withdraws now, before it gets harder (and it will if you keep smoking).
You'll be even more upset with yourself if you continue!!!
LadyBug 6/5/2011
HoneyBee 4/2013


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November 22, 2014
A purchase out of necessity. my son needed one for camp so i bought it. the price was a bit steep for what you get.
October 20, 2014
Good value
October 08, 2014
There is a lot of great first aid components and really is compact.
September 25, 2014
Got everything in it which you would want in a first aid kit.
September 14, 2014
Dose wot it says on the tin.
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The Giant Beastcast: Episode 06
Become Premium to Watch
Her Story is a bold and largely successful experiment in interactive crime fiction.
Rocksteady's gorgeous-looking third Arkham game refines its open-world format a bit and lets you drive a whole hell of a lot of Batmobile.
It's squid kids and ink blasting abound in Nintendo's exceptionally fun new online shooter.
Game »
consists of 15 releases.
Released Oct 10, 1994
Hard Reset is the debut game from a new Polish development studio, Flying Wild Hog. The player controls a cyborg, Major Fletcher, who must use a pair of transforming weapons to defeat an army of malfunctioning robots that endanger the "cyberpunk megacity" of Bezoar.
The latest expansion in the Painkiller franchise sees the return of Daniel Garner (from the original game) and Belial (from Overdose). It's being developed by Eggtooth, a Polish team that made third-party mods for previous games in the series.
Developed with a Catholic priest advising, Painkiller returns in this new sequel.
The year is 1916. Young American joins UK Army to experience an adventure of his life and soon realizes that greater evil is hiding beneath the Great War storm. He has to face the underground world of vampires, demons, evil genius creatures and even become one of the demons to rescue the human and vampire kind from forces of darkness.
This Xbox version of Painkiller features a remix of levels from the original game and the expansion pack, Battle out of Hell, as well as exclusive new levels designed for the console game.
A console-exclusive installment in the Serious Sam series.
Painkiller is a fast-paced first-person-shooter that hearkens back to the early years of shooters. Telling a hellish story about a man fighting his way out of Purgatory and foregoing modern conventions of realism, Painkiller brings back the over-the-top twitch gameplay that is quickly becoming a thing of the past.
Tron 2.0 is a story-driven first-person shooter that takes place in a computer world. It stands as a video game sequel to the 1982 movie 'Tron'. Bruce Boxleitner reprises his role as Alan Bradley, with the game's main character being his son, Jet Bradley.
Will Rock must save his girlfriend from Zeus and his cronies in this fast-paced first-person shooter by Saber Interactive.
Serious Sam on the Xbox packs in the first two PC releases along with slick graphical makeover and new multi-player options.
Alien Resurrection is a science fiction first person shooter based on the movie of the same name. It was generally considered a commercial failure and received mixed reviews from publications worldwide.
Kiss: Psycho Circus - The Nightmare Child is a sci-fi FPS, based on Todd McFarlane's comic book series of the same moniker.
A commercial total conversion of Doom 2. A failure on the market, but a landmark release for modders, it helped launch the careers of several artists and level designers.
Monolith Productions' official expansion pack to Blood, featuring one new episode, six new enemies, a variety of bug fixes and a bloodbath level modeled after Monolith's corporate office.
The followup to 1995's Dark Forces, Star Wars Jedi Knight: Dark Forces II is a first-person shooter set within the Star Wars universe. Its story revolves around Kyle Katarn, who must discover his latent connection to the Force in order to combat seven powerful Sith Lords.
Kill countless aliens while rescuing babes as Duke Nukem in this critically acclaimed first-person shooter.
Disruptor, a sci-fi first person shooter, is the first game developed by Insomniac Games. The player uses special psychic implants called 'Psionics' to heal and deliver electric shocks to stop mutants, space marines and aliens.
A Doom clone for the Amiga
Hexen is a fantasy first-person shooter that builds upon its predecessor, Heretic, by incorporating three character classes, multi-level puzzles, and eight-player network play.
A first person shooter with integrated video scenes originally developed for the 3DO console.
In this Saturn FPS, you control a state-of-the-art Laocorn (codenamed Robotica) attempting to regain control of the WSSS space station Daedalus.
An arcade-style over-the-top spiritual sequel to Wolfenstein 3D that introduced various features to the first-person shooter genre.
When Sparky the dog is kidnapped by aliens, his owner chases after them to rescue his dog.
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Press release from Business Wire
Guidance Software Named a Leader in IDC MarketScape on Early Case Assessment

 EnCase® eDiscovery Uniquely Enables Legal Teams to Conduct Early Case Assessment at Any Point in the Process with Pre-Collection Analytics

Wednesday, October 05, 2011
Guidance Software Named a Leader in IDC MarketScape on Early Case Assessment08:35 EDT Wednesday, October 05, 2011 PASADENA, Calif. (Business Wire) -- Industry analyst firm IDC has named Guidance Software, Inc. (NASDAQ: GUID) a leader in early case assessment (ECA) in a new report, the "IDC MarketScape: Worldwide Standalone Early Case Assessment Applications 2011 Vendor Analysis." The report is IDC's first in-depth analysis of early case assessment applications, a fast-growing segment of the electronic discovery (e-discovery) market. IDC expects revenue for the standalone ECA applications market will total $400.8 million in 2011 and will reach $857.0 million in 2015.1 The need for early case assessment tools has grown in recent years as costs associated with e-discovery have escalated. ECA applications can help organizations achieve substantial cost and time-savings by enabling legal teams to have the metrics and insights needed to make informed decisions about case merits, risks and expected costs at the outset of a legal event. "The value of early case assessment rests in its ability to enable better, faster case strategy decisions," said Victor Limongelli, president and chief executive officer, Guidance Software. "With EnCase, organizations can do case assessment truly early – including before and during collection and preservation. This unique capability gives our customers a clear advantage with assessment before collection, compared to other solutions that need to first have collection and processing complete, which could take weeks." The IDC MarketScape evaluated early case assessment application vendors; reviewing their current capabilities and individual long-term strategies that impact their ability to meet evolving requirements, execute their go-to-market and product strategies, and gain market share going forward. The IDC MarketScape document scored and ranked vendors based on qualitative and quantitative criteria. The IDC report highlights specific Guidance Software product strengths: "Ability to deliver average cull rates of 90 percent using EnCase eDiscovery." "Relatively light footprint of the EnCase agent, especially when used as part of an EnCase Enterprise platform deployment. In this scenario, customers are able to use a common infrastructure to support its internal audit, forensics and security investigations (incident management), and e-discovery collections activities." "No distinction between an internal investigation and a legal matter, which enables organizations to use a single solution for all their cases." "Ability to conduct remote and, sometimes, stealth collections of individual files, while preserving metadata over geographically dispersed networks." "APIs, which enable integration with third-party legal spend management, billing, matter management, and legal project management applications." "Support for granular nested proximity search. One customer tested nesting capability to 64 levels deep." Download a complimentary excerpt from the report: http://www.guidancesoftware.com/Document.aspx?did=1000017580&cmpid=newsrelease. About IDC MarketScape IDC MarketScape vendor analysis model is designed to provide an overview of the competitive fitness of ICT (information and communications technology) suppliers in a given market. The research methodology utilizes a rigorous scoring methodology based on both qualitative and quantitative criteria that results in a single graphical illustration of each vendor's position within a given market. IDC MarketScape provides a clear framework in which the product and service offerings, capabilities and strategies, and current and future market success factors of IT and telecommunications vendors can be meaningfully compared. The framework also provides technology buyers with a 360-degree assessment of the strengths and weaknesses of current and prospective vendors. About Guidance Software, Inc. Guidance Software is recognized worldwide as the industry leader in digital investigative solutions. Its EnCase® platform provides the foundation for government, corporate and law enforcement organizations to conduct thorough, network-enabled, and court-validated computer investigations of any kind, such as responding to e-discovery requests, conducting internal investigations, responding to regulatory inquiries or performing data and compliance auditing - all while maintaining the integrity of the data. There are more than 40,000 licensed users of the EnCase technology worldwide, the EnCase® Enterprise platform is used by more than 60 of the Fortune 100, and thousands attend Guidance Software's renowned training programs annually. For more information about Guidance Software, visit www.guidancesoftware.com/. Follow Guidance Software on Twitter at www.twitter.com/encase and on Facebook at www.facebook.com/guidancesoftware. EnCase®, EnCE®, EnCEP®, EnScript®, FastBloc®, Guidance Software™ and Tableau™ are registered trademarks or trademarks owned by Guidance Software in the United States and other jurisdictions and may not be used without prior written permission. All other marks and brands may be claimed as the property of their respective owners. Forward Looking Statements This news release contains forward-looking statements within the meaning of the safe harbor provisions of the Private Securities Litigation Reform Act of 1995. Investors are cautioned that forward-looking statements in this release involve risks and uncertainties that could cause actual results to differ materially from current expectations. There can be no assurance that demand for the Guidance Software's products will continue at current or greater levels, or that the Company will continue to grow revenues, or be profitable. There are also risks that the Guidance Software's pursuit of providing network security and eDiscovery technology might not be successful, or that if successful, it will not materially enhance the Guidance Software's financial performance; that the Company could fail to retain key employees; that changes in customer requirements and other general economic and political uncertainties could impact the Guidance Software's relationship with its customers; and that delays in product development, competitive pressures or technical difficulties could impact timely delivery of next-generation products; and other risks and uncertainties that are described from time to time in Guidance Software's periodic reports and registration statements filed with the Securities and Exchange Commission. The Company specifically disclaims any responsibility for updating these forward-looking statements. GUID-F 1 IDC, MarketScape for Worldwide Standalone Early Case Assessment Applications 2011 Vendor Analysis, Doc # #229928, September 2011 Guidance Software, Inc.Cas firstname.lastname@example.com


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Results 1 to 2 of 2
Thread: line art, tatoo-esque
November 5th, 2003 #1
line art, tatoo-esque
some recent line art:
and: the happiest drwaing EVER!
feel free to color either of these.
" 'You might want to sit down..this is going to feel unpleasantly like being drunk'
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'Whats so bad about being drunk?'
'Ask a glass of water' "
Hide this ad by registering as a memberNovember 21st, 2003 #2
Aww, he looks so hungry though... is he going to eat a butterfly? Seriously though, nice linework.
The Patron Saint of Forgotten Posts
"As iron sharpens iron, so one man sharpens another. Unfortunately the resulting sparks set fire to any nearby artworks."