Arabidopsis LTR retroelements was identified and relative ages of full-length elements estimated showing that Pseudoviridae are much younger than Metaviridae. The distribution of retroelement insertions across the genome was shown to be non-uniform.The full complement of  Arabidopsis thaliana genome sequence makes it possible to comprehensively characterize retroelement populations and explore factors that contribute to their genomic distribution.Retrotransposons are an abundant component of eukaryotic genomes. The high quality of the A. thaliana long terminal repeat (LTR) retroelements using RetroMap, a software tool that iteratively searches genome sequences for reverse transcriptases and then defines retroelement insertions. Relative ages of full-length elements were estimated by assessing sequence divergence between LTRs: the Pseudoviridae were significantly younger than the Metaviridae. All retroelement insertions were mapped onto the genome sequence and their distribution was distinctly non-uniform. Although both Pseudoviridae and Metaviridae tend to cluster within pericentromeric heterochromatin, this association is significantly more pronounced for all three Metaviridae sublineages (Metavirus, Tat and Athila). Among these, Tat and Athila are strictly associated with pericentromeric heterochromatin.We identified the full complement of Athila and Tat sublineages of the Metaviridae. We predict that, like retroelements in yeast, the Athila and Tat elements target integration to pericentromeric regions by recognizing a specific feature of pericentromeric heterochromatin.The non-uniform genomic distribution of the Pseudoviridae and the Metaviridae can be explained by a variety of factors including target-site bias, selection against integration into euchromatin and pericentromeric accumulation of elements as a result of suppression of recombination. However, comparisons based on the age of elements and their chromosomal location indicate that integration-site specificity is likely to be the primary factor determining distribution of the  Endogenous retroviruses and long terminal repeat (LTR) retrotransposons  generally comprise a significant portion of higher eukaryotic genomes. Dismissed as parasitic or 'junk' DNA, these sequences have traditionally received less attention than sequences contributing to the functional capacity of the organism. This perspective has changed with the completion of several eukaryotic genome sequences. The contributions of retroelements to genome content range from 3% in baker's yeast to 80% in maize ,2. RetroArabidopsis thaliana and Drosophila melanogaster are clustered in pericentromeric heterochromatin [The impact of retroelements on their hosts is not without constraint: the host imposes an environmental landscape (the genome) within which retroelements must develop strategies to persist. Retroelement cDNA insertion directly impacts on the host's genetic material, making this step a likely target for regulatory control. Transposable elements (TEs) in some systems utilize mechanisms that direct integration to specific chromosomal sites or safe havens ,5. For ehromatin ,12. HoweA. thaliana is ideal for exploring processes that influence the chromosomal distribution of retroelements. A. thaliana retroelement diversity has been analyzed previously, preparing the way for this study [Saccharomyces cerevisiae, Schizosaccharomyces pombe and Caenorhabditis elegans, which have relatively few retroelements, A. thaliana has a diverse mobile element population whose physical distribution can be described in detail. Another benefit of A. thaliana stems from the fact that in contrast to most other 'completely sequenced' eukaryotic genomes, the A. thaliana genome sequence better represents chromosomal DNA of all types, including sequences within heterochromatin [A. thaliana to better understand the factors contributing to their genomic distribution.The genome of is study -15. In chromatin . Here weA. thaliana genome were identified by iterated BLAST searches -only hits, and 3,268 solo LTRs . No evidence was found for BEL or DIRS retroelements.Element subtypes (FLE, RT-only and solo LTRs) were sorted into taxonomic groupings using the formal taxonomic nomenclature assigned to retrotransposons ,17. Our elements ,18  and solo LTRs (447 nucleotides) when contrasted with the Pseudoviridae FLEs (5,336 nucleotides) and solo LTRs (187 nucleotides) (data not shown). Among the subgroups of the Metaviridae, the average length of Metaviruses is closer to that of the Pseudoviridae than to the mean lengths of the Athila and Tat lineages. The Pseudoviridae are also more uniformly sized than the Metaviridae. A second factor contributing to the abundance of Metaviridae is that they have approximately six times more solo LTRs than the Pseudoviridae, even though numbers of complete elements are similar between families  for all combinations.We next looked at distribution patterns between element families to determine whether they are similar. On the basis of the retroelement distribution maps Figure , we hypoAthila, Tat and Metavirus) were expected to have similar distributions. This appears to be true, as significant differences were not detected on any chromosome for these sublineages. We then checked whether the FLEs, RT-only hits or solo LTRs displayed different distributions from one another within their respective families. No consistently significant trends were observed for the Pseudoviridae or the Metaviridae. Oddly, the Metaviridae solo LTR distribution displayed significant differences from the FLEs and RT-only hits for chromosome 3.To assess whether the Metaviridae sublineages contributed equally to the observed distribution bias, we tested a model wherein the three sublineages , telomeres and rDNA [Metavirus elements are less tightly associated with heterochromatin than are Tat and Athila, which did not differ significantly from each other. Element subtypes also differed in their distribution with respect to heterochromatin. The major source of differences was the distribution of solo LTRs in the Metaviridae.A feature of pericentromeric regions in oelement . Becausein Table . There aand rDNA -22. We lLTR retroelements have a built-in clock that can be used to estimate the age of given insertions. At the time an element inserts into the genome, the LTRs are typically 100% identical. As time passes, mutations occur within the LTRs at a rate approximating the host's mutation rate. LTR divergence, therefore, can be used to estimate relative ages between elements, assuming that all elements share the same probability of incurring a mutation. Although it is possible to estimate ages for non-LTR retrotransposons by generating a putative ancestral consensus sequence and calculating divergence from the consensus, this method is not directly equivalent to estimating ages by LTR comparisons. Therefore, age comparisons were performed only for the LTR retroelement families. Note that the ages depicted in Figure F = 14.4, df = 3 and 368, p < 0.0001) (Table t = 5.72, df = 368, p < 0.0001). When the Metaviridae sublineages are considered, it is apparent that the Athila elements are responsible for much of the increased age of this family. The difference between Athila and the other two sublineages is significant, with p = 0.0003 being the highest value for sublineage comparisons. Elements within heterochromatic regions were significantly older than those found outside (F = 17.19, df = 1 and 368, p < 0.0001). There was suggestive evidence that the mean element ages varied among chromosomes (F = 2.73, df = 4 and 368, p = 0.0289). However, all pairwise comparisons between chromosomes failed to yield significant results at the 0.05 level using the Tukey-Kramer adjustment (data not shown).Statistically significant age differences were observed among the Pseudoviridae and three Metaviridae sublineages (1) Table . OverallA. thaliana genome is reliably sequenced well into heterochromatic regions and work continues to further define these domains [Completed genome sequences enable comprehensive analyses of retroelement diversity and the exploration of the impact of retroelements on genome organization. Although most large-scale sequencing projects use the shotgun sequencing method, this method makes it particularly difficult to assemble repetitive sequences and to correctly position sequence repeats on the genome scaffold. Consequently, regions of repetitive DNA such as nucleolar-organizing regions (NORs), telomeres and centromeres tend to be skipped, or are sometimes represented by consensus or sampled sequences. The difficulty of cloning repetitive sequences and the drawbacks noted above result in the under- or misrepresentation of the repetitive content of most genomes. Because retroelements frequently comprise a large proportion of the repetitive DNA, 'completed' genome sequences are typically not ideal for studies of retroelement diversity and distribution on a genomic scale. In contrast to these cases, the  domains ,23.Another factor frustrating comprehensive analyses of eukaryotic mobile genetic elements is the inherent difficulty in annotating these sequences. Many mobile element insertions are structurally degenerate, rearranged through recombination or organized in complex arrays. Software tools and databases such as Reputer  and RepbData generated by RetroMap are subject to a few caveats. First, because element searches use reverse transcriptase sequences as queries, elements lacking reverse transcriptase motifs (for whatever reason) will not be identified. Second, when RetroMap encounters nested elements, tandem elements, and other complex arrangements, it does not attempt to delimit the element. Rather, the user is notified that a complex arrangement was encountered and the original reverse transcriptase match and any LTR(s) found are logged as separate entities.Tat and Metavirus), we identified 210 and 128 full-length elements, respectively, whereas Pereira recovered 215 and 130 insertions for these respective element groups. The two studies, however, differed significantly in the number of Athila elements identified. We found 38 insertions, whereas Pereira recovered 219. To reconcile these differences, we independently estimated Athila copy numbers by conducting iterative BLAST searches with a variety of Athila query sequences (data not shown). BLAST hits recovered with each query were then mapped onto the genome sequence. As a result of this analysis, we concluded that RetroMap missed many Athila insertions, either because they are highly degenerate or part of complex arrangements. In contrast to Pereira's approach, RetroMap requires that a reverse transcriptase reside between LTRs, and in many cases reverse transcriptases were absent or not detectable in Athila insertions. This can be resolved in future implementations of RetroMap that enable multiple query sequences to be tested. The Athila elements are large, and our underestimate of the number of Athila elements resulted in a corresponding underestimate of the total amount of retrotransposon DNA in the A. thaliana genome. We calculated 3.36% for this value, whereas Pereira calculated 5.60%. Pereira's estimate is likely to be the more accurate of the two.For the most part, RetroMap was quite effective in identifying LTR retrotransposon insertions. Our results closely agree with the findings of a parallel study conducted by Pereira . For theAthila elements, the observed frequency of insertions in complex arrangements was rare. For example, the Pseudoviridae had only eight nested and five unassignable elements. The small observed number of complex element arrangements in A. thaliana contrasts sharply with observations in grass genomes, where retroelements are usually found in complex nested arrays [A. thaliana (5.60% of the genome) and grasses (up to 80% of some genomes) [With the exception of the d arrays ,30. Thisgenomes) ,28.et al. [A. thaliana (DNA transposons and retroelements). Our analysis extends this work by considering the genomic distribution of specific retroelement lineages. We investigate a model wherein selection and recombination affect element lineages uniformly, and hypothesize that observed deviations in the genomic distribution of specific element lineages reflect unique aspects of their evolutionary history or survival strategies such as targeted integration.Our data on the genomic distribution of retroelements can be considered in the light of theoretical work predicting the distribution of TE populations within genomes. These studies largely focus on the effects of selection and recombination on element insertions ,32. Partet al. , which cA. thaliana. Wright et al. [A. thaliana TE families actually had a small but positive correlation with recombination rate, as was also observed in C. elegans [et al. [A. thaliana retrotransposable element distribution.The ectopic exchange model assumes that inter-element recombination restricts growth of element populations . Elementt et al.  examined elegans . Devos e [et al.  found ecThe ectopic exchange hypothesis makes two unique predictions for retrotransposons: solo LTRs (a product of recombination) should be observed in higher proportions relative to full-length elements outside of heterochromatin; and heterochromatic elements will show a shift toward greater average age than elements elsewhere in the genome. Our consideration of age assumes that the chance of loss by recombination remains steady or increases with element age. However, old elements will have higher sequence divergence, thereby reducing the likelihood that they will recombine. In considering age, we also assume that all elements evolve at the same rates. This is unlikely to be the case, as local, chromosomal and compartmental locations are increasingly found to have different mutation rates ,37.With respect to the distribution of solo LTRs, our data show exactly the opposite bias predicted by the ectopic exchange model: the ratio of Metaviridae solo LTRs to FLEs in heterochromatin was nearly twice that found outside heterochromatin. The frequency of solo LTRs at the centromeres suggests that homologous recombination, at least over short distances (less than 20 kilobases (kb)), occurs frequently in pericentromeric regions.Metaviruses and Tat elements differ significantly in their association with heterochromatin. The ectopic exchange model would predict that the Tat elements should be older; however, these two lineages do not differ significantly in age. Although it is possible that recombinational forces could act differentially on different element sublineages, we view this as unlikely. Rather, forces other than ectopic recombination, such as targeted integration (see below), are responsible for the differential genomic distribution of certain element lineages. This is not to say that ectopic exchange has no role; however, it is unlikely to be the sole or prevailing influence.While we did observe the predicted shift toward older elements within heterochromatin, the data are not consistent with low rates of recombination as the determinant of retrotransposon accumulation at the centromeres. Within the Metaviridae, for example, the A. thaliana, although numerous potential 'seed' insertion sites are observed along the chromosome arms, we did not detect dense clusters of nested elements at these locations.The deleterious insertion model hypothesizes that element insertions are generally harmful to the host, and thus elements accumulate in regions of low gene density, where insertions are least likely to have negative effects on the host. According to this model, abundance of all classes of mobile elements should inversely reflect gene density within the genome. This is supported by the observation that elements are over-represented in gene-poor pericentromeric heterochromatin and are rare over much of the chromosome arms. However, we did not observe an increase in element abundance at other gene-poor heterochromatic regions (such as the telomeres and NORs), which would be predicted by the deleterious insertion hypothesis. This model would also predict that element insertions into gene-rich regions that are tolerated by the host should act as founders or safe havens for future element insertions. This could lead to an ever-expanding area of tightly clustered and frequently nested elements in euchromatin, assuming the overall random insertion rate is greater than the rate of sequence loss through recombination. Nested clusters of elements have been reported in cereals such as maize and barley ,30. In AC. elegans and rice indicate that many retrotranposons are associated with genes (63% and 20% in these species respectively) [D. melanogaster, some retrotransposon-gene associations are preserved in diverse natural populations, consistent with the hypothesis that they confer a positive selective advantage [S. pombe suggest that the Tf1 retrotransposons may regulate expression of adjacent genes [A. thaliana mobile elements, but identifying such a role would require a more refined analysis of element distribution and gene associations.In contrast to the deleterious insertion model, it is important to recognize that some element insertions may provide a selective advantage. Studies in ctively) ,39. In Ddvantage . Furthernt genes . We cannS. cerevisiae insert preferentially into heterochromatin or sites occupied by RNA polymerase III, and in the evolutionarily distant S. pombe genome, retroelements are located preferentially upstream of genes transcribed by RNA polymerase II [The observation that many LTR retroelements have non-uniform genomic distributions suggested that targeted integration may be a driver of retroelement distribution patterns . Neithererase II -9. Retroerase II ,43.A. thaliana retroelements. As in other systems, targeting may occur because elements recognize a specific chromatin state and actively insert into regions with that type of chromatin. A chromatin-targeting model has the following predictions. First, very few elements will be found outside targeted chromatin domains. For example, all heterochromatic regions such as NORs, knobs and telomeres would be occupied by the same lineage of elements if these regions share a chromatin feature recognized by that lineage. Second, different retroelement lineages may be associated with different regions of the genome if they employ different targeting strategies.Targeted integration could contribute significantly to the chromosomal distribution of Athila and Tat lineages, both of which are tightly associated with pericentromeric regions. Athila and Tat elements are not found in heterochromatin regions around the telomeres, however, suggesting that telomeric and centromeric heterochromatin differ. Targeted integration to pericentromeric heterochromatin may be a general feature of the Metaviridae. Members of the Metaviridae are abundant in pericentromeric heterochromatin in many grass species [et al. [The targeting hypothesis is well supported for the Metaviridae, which on a genome-wide basis differ significantly in their chromosomal distribution from the Pseudoviridae and non-LTR retrotransposons. This is particularly true for the  species . Langdon [et al.  suggeste [et al. .De novo integration events have been mapped on a chromosomal level for two tobacco Pseudoviridae elements in heterologous hosts - Tto1 in A. thaliana and Tnt1 in Medicago trunculata. In both cases these elements integrated throughout the genome, displaying some preference for genic regions [The Pseudoviridae and non-LTR retrotransposons differ in their genomic organization from the Metaviridae and are more loosely associated with pericentromeric regions. It may be that these element lineages do not target their integration, or they may recognize other chromosomal features, although we did not observe any association with other genome features or gene classes such as tRNA genes (data not shown).  regions ,48. WhetA. thaliana LTR retroelements revealed that the distribution of the Pseudoviridae and the Metaviridae is non-uniform and that they tend to cluster at the centromeres. The pericentromeric association of three Metaviridae sublineages (Metavirus, Tat and Athila) was significantly more pronounced than for the Pseudoviridae. Several factors are likely to contribute to the centromeric association of these elements, including target-site bias, selection against euchromatin integration and pericentromeric accumulation of elements due to suppression of recombination. For the Tat and Athila lineages, however, target-site specificity appears to be the primary factor determining chromosomal distribution. We predict that, like retroelements in yeast, the Tat and Athila elements target integration to pericentromeric regions by recognizing a specific feature of pericentromeric heterochromatin.Our analysis of the genomic distribution of the A. thaliana chromosomes (TIGR version 7 January 2002) with the tblastn program (E = 1e-10, XML output, filtering disabled) [-10, XML output, filtering disabled) to identify increasingly divergent or degenerate elements. Unique hits identified in the final round of screening were taken to represent the entire complement of retroelements in A. thaliana.Reverse transcriptase amino-acid sequences  . The resMetavirus), Tat and Athila groups on the basis of the highest-scoring match in a BLAST database containing the Metaviridae reverse transcriptase sequences described in [RetroMap assigns putative LTRs where possible for each reverse transcriptase by comparing 10 kb of DNA from each flank. This is accomplished using Blast2Sequences to identify flanking repeats  Figure . Direct ribed in . Putativ-5) using all predicted 5' LTRs of known A. thaliana elements and the FLEs. RetroMap assigns any putative LTR sequence that fails to match or overlap with a predicted FLE LTR as a solo LTR.Solo LTRs and solo LTR fragments were identified with blastn (E < 1eT = d/2k (time (T) = genetic distance (d)/ [2 × substitution rate (k)]), where genetic distance is 1 - (percent identity/100) and the substitution rate is 1.5 × 10-8 [LTRs are identical at the time of retroelement integration, and so relative element ages were estimated from the percentage of identical residues shared between 5' and 3' LTRs for FLEs. The age formula used was 5 × 10-8 .A. thaliana NORs are located at the left (north) ends of chromosomes 2 and 4, and as these regions were only sample sequenced, their boundaries were assigned as the left ends of chromosomes 2 and 4. Heterochromatic knobs and pericentromeric regions were assigned as the outermost physical markers delimiting these regions, as determined by the studies listed above.Chromosome coordinates relative to the left (north) end were used to calculate distances between retroelements and heterochromatic domains. Heterochromatin boundaries were derived from -22 and iA. thaliana retroelement families by element category: reverse transcriptase only (R), full-length (F), and solo LTR (S).A RetroMap-generated datafile was used as the data source for statistical testing. The data file contains chromosomal element coordinates, LTR identity, age and lineage information for all p-value for a test whose null hypothesis is that all element categories of interest have the same chromosomal position distribution. This permutation approach is useful for the chromosomal position data because first, no distributional assumptions are required, second, differences in chromosomal position distributions other than simple location shifts are detectable, and third, the method is not as sensitive to outliers as common parametric approaches.For each element type and each chromosome, a Kendall-Sherman test -55 was cF-tests were used to check for interaction between these three factors and to assess the statistical significance of observed differences among the five chromosomes, among the four lineage/sublineage categories (Pseudoviridae and the three Metaviridae sublineages:Athila, Tat or Metavirus), and between elements inside and outside heterochromatin. The square root of age was used as the response variable in the age analysis so that the variance of the response would be roughly constant across categories defined by combinations of chromosome, lineage/sublineage, and location, as required for standard linear model analyses. Outlying observations were present, but the results of the analysis remained essentially the same with or without the outliers. Thus the reported results are based on the full dataset.For FLEs, linear model analyses were used to assess the effects of the factors 'chromosome', 'lineage/sublineage', and 'location' relative to heterochromatin on the response variable 'element age'. ) must be present. To enable searches for LTRs, NCBI's BLAST 2 Sequences must be locally installed.The following additional data are available with the online version of this article: a Microsoft Excel spreadsheet of data generated by RetroMap for each retrotransposon insertion identified; the data in this file was used for all statistical analyses (Additional data file A Microsoft Excel spreadsheet of data generated by RetroMap for each retrotransposon insertion identified; the data in this file was used for all statistical analysesClick here for additional data fileThe Java application used to generate the LTR and retrotransposon coordinates and to estimate retrotransposon agesClick here for additional data file


The development of miniature sensors that can be unobtrusively attached to the body or can be part of clothing items, such as sensing elements embedded in the fabric of garments, have opened countless possibilities of monitoring patients in the field over extended periods of time. This is of particular relevance to the practice of physical medicine and rehabilitation. Wearable technology addresses a major question in the management of patients undergoing rehabilitation, i.e. have clinical interventions a significant impact on the real life of patients? Wearable technology allows clinicians to gather data where it matters the most to answer this question, i.e. the home and community settings. Direct observations concerning the impact of clinical interventions on mobility, level of independence, and quality of life can be performed by means of wearable systems. Researchers have focused on three main areas of work to develop tools of clinical interest: 1)the design and implementation of sensors that are minimally obtrusive and reliably record movement or physiological signals, 2)the development of systems that unobtrusively gather data from multiple wearable sensors and deliver this information to clinicians in the way that is most appropriate for each application, and 3)the design and implementation of algorithms to extract clinically relevant information from data recorded using wearable technology. Journal of NeuroEngineering and Rehabilitation has devoted a series of articles to this topic with the objective of offering a description of the state of the art in this research field and pointing to emerging applications that are relevant to the clinical practice in physical medicine and rehabilitation. Understanding the impact of clinical interventions on the real life of individuals is an essential component of physical medicine and rehabilitation. While assessments performed in the clinical setting have value, it is difficult to perform thorough, costly evaluations of impairment and functional limitation within the time constraints and limited resources available in outpatient units of rehabilitation hospitals. Furthermore, it is often questioned whether assessments performed in the clinical setting are truly representative of how a given clinical intervention affects the real life of patients. While this observation has fostered a great deal of interest for the development and validation of outcome measures that largely rely on the use of questionnaires , researcA number of clinical applications of wearable systems in physical medicine and rehabilitation emerged in the past few years. They range from simple monitoring of daily activities, for the purpose of assessing mobility and level of independence in individuals, to integrating miniature sensors to enhance the function of devices utilized by patients to perform motor tasks that they would be otherwise unable to accomplish.Monitoring functional motor activities was one of the first goals of research teams interested in clinical applications of wearable technology. The focus was initially on using accelerometers -8 or a cA level of complexity was added when researchers started investigating motor disorders and the possibility of utilizing wearable technology to assess the effect of clinical interventions on the quality of movement observed while patients performed functional tasks. Two applications worth mentioning are the one to assess symptoms and motor complications in patients with Parkinson's disease -14 and tFinally, recent studies have been focused on integrating wearable, miniature sensor technology with orthoses, prostheses, and mobility assistive devices. Sensor technology is particularly appealing in these applications because it allows implementing closed-loop strategies that take advantage of the increased complexity and flexibility that robotics is contributing to the design of orthoses, prostheses, and mobility assistive devices. Namely, the characteristics of such devices can be constantly modified as a function of the task individuals are engaged into and environmental disturbances ,24.In all the emerging applications summarized above, either continuous recording of sensor data or at least monitoring over extended periods of time are necessary to design and implement an effective clinical intervention. Unobtrusive, wearable systems providing ease of data gathering and some processing capabilities are essential to achieve the objective of making the leap between the preliminary results obtained as part of the research carried on so far and the daily clinical practice of physical medicine and rehabilitation. Three areas of work are essential to achieve this objective: 1)the development of wearable sensors that unobtrusively and reliably record movement and other physiological data relevant to rehabilitation; 2)the design and implementation of systems that integrate multiple sensors, record data simultaneously from wearable sensors of different types, and relay sensor data to a remote location at the time and in the way that is most appropriate for the clinical application of interest; and 3)the development of methodologies to manipulate wearable sensor data to extract information in a clinically relevant manner to perform clinical assessments or control devices aimed at enhancing mobility in individuals with conditions that limit their level of independence. A series of papers have been assembled to provide the readership of Journal of NeuroEngineering and Rehabilitation with a description of the state of the art of the application of wearable technology in physical medicine and rehabilitation.A first set of the papers that have been assembled for publication on Journal of NeuroEngineering and Rehabilitation on the topic of wearable technology in physical medicine and rehabilitation has the objective of describing recent advances in wearable sensor technology. Two manuscripts describe attempts by different groups of measuring angular displacements for upper and lower extremity joints by embedding conductive fibers into the fabric of undergarments. The paper by Gibbs and Asada, entitled "Wearable conductive fiber sensors for multi-axis human joint angle measurements", reports encouraging preliminary results concerning monitoring lower limb joint displacements during ambulation by utilizing such technology. The manuscript by Tognetti et al, entitled "Wearable kinesthetic system for capturing and classifying upper limb gesture in post-stroke rehabilitation", describes the design and implementation of a system similar to the one proposed by Gibbs and Asada but geared toward monitoring movements of the upper extremities. The authors also explore the application of these wearable sensors to monitoring motor recovery in post-stroke individuals. Simone and Kamper focus their contribution on unobtrusively measuring finger movements in patients undergoing rehabilitation. Their manuscript "Design considerations for a wearable monitor to measure finger posture" summarizes the authors' recent work toward developing ways to record fine motor control tasks involving manipulation of objects requiring fine motor control of the hand and fingers. This technology has immediate application in patients such as post-stroke individuals undergoing rehabilitation that targets fine motor control skills. While initial research in the area of wearable technology was aimed at combining existing, miniature sensors with special fabrics or wireless technology, recent advances in this field have been focused on the development of sensing elements that can be even more easily embedded in clothing items. An example of such effort is reported in the paper by Dunne et al entitled "Initial development and testing of a novel foam-based pressure sensor for wearable sensing". This paper summarizes positive preliminary results by the research team aimed at measuring shoulder movements, neck movements, and scapular pressure. The sensing elements can also be used to monitor respiratory rate. Devoted to monitoring systemic responses is the last of the papers focused on wearable sensors. In this manuscript, Yan et al describe a new method to reliably measure heart rate and oxygen saturation. The paper is entitled "Reduction of motion artifacts in pulse oximetry by smoothed pseudo Wigner-Ville distribution" and demonstrates how advanced processing techniques may be necessary to derive reliable data when recordings are performed in the field.A second area of research relevant to the application of wearable technology in physical medicine and rehabilitation concerns the integration of wearable sensors into systems. Following the seminal work by Park and Jayaraman , severalA final set of papers is focused on applications that are relevant to physical medicine and rehabilitation. Sherrill et al describe in their paper entitled "A clustering technique to assess feasibility of motor activity identification in COPD patients via analysis of wearable-sensor data" a method to design classifiers of motor activities such as walking and stair climbing. The proposed technique relies on the examination of small datasets via clustering methods. Measures are derived from clusters associated with different motor activities to evaluate whether the set of wearable sensors and features derived from the recorded data are suitable to reliably identify the motor tasks of interest. Wang and Winters put the information gathered via wearable systems into a clinical context via processing that relies on neuro-fuzzy models. Their paper entitled "A dynamic neuro-fuzzy model providing bio-state estimation and prognosis prediction for wearable intelligent assistants" presents encouraging results indicating that the proposed method can put in the correct context dynamic changes observed in post-stroke individuals undergoing rehabilitation. Wang and Kiryu in their manuscript entitled "Personal customizing exercise with a wearable measurement and control unit" summarize their results on customizing machine-based exercise routines on the basis of physiological data that are continuously gathered from individuals performing such routines. Their results demonstrate the feasibility of a closed-loop system that optimally adapts workload. Dozza et al describe a wearable system designed to reduce body sway in individuals with severe vestibular problems. Their manuscript entitled "Influence of a portable audio-feedback device on structural properties of postural sway" summarizes positive results obtained with a prototype wearable system that utilizes audio-feedback to improve balance. Finally, Mavroidis et al describe how miniature sensor technology can be used to design a new generation of smart rehabilitation devices. Three devices are described in their paper entitled "Smart portable rehabilitation devices": a passive motion elbow device, a knee brace that provides variable resistance by controlling damping via the use of an electro-rheological fluid, and a portable knee device that combines electrical stimulation and biofeedback. These devices combine sensing technology and control strategies to enhance rehabilitation.This collection of papers provides an up-to-date description of the state of the art in the field of wearable technology applied to physical medicine and rehabilitation. The field is rapidly advancing and numerous research groups have already demonstrated applications of great clinical relevance. The potential impact of this technology on the clinical practice of physical medicine and rehabilitation is remarkable. A significant shift in focus is possible thanks to wearable technology. While the main focus of clinical assessment techniques is currently on methods that are implemented in the clinical setting, wearable technology has the potential to redirect such focus on field recordings. This is expected to allow clinicians to eventually benefit from both data gathered in the home and the community settings during the performance of activities of daily living and data recorded in the clinical setting under controlled conditions. Complementarities are expected between field and clinical evaluations. Future research will surely address optimal ways to combine these two types of assessment to optimize the design of rehabilitation interventions.


At sites of cell adhesion, proteins exist that not only perform structural tasks but also have a signaling function. Previously, we found that the Lipoma Preferred Partner (LPP) protein is localized at sites of cell adhesion such as focal adhesions and cell-cell contacts, and shuttles to the nucleus where it has transcriptional activation capacity. LPP is a member of the zyxin family of proteins, which contains five members: ajuba, LIMD1, LPP, TRIP6 and zyxin. LPP has three LIM domains (zinc-finger protein interaction domains) at its carboxy-terminus, which are preceded by a proline-rich pre-LIM region containing a number of protein interaction domains.scribble, is a member of the leucine-rich repeat and PDZ (LAP) family of proteins that is involved in the regulation of cell adhesion, cell shape and polarity. In addition, Scrib displays tumor suppressor activity. The binding between Scrib and LPP is mediated by the PDZ domains of Scrib and the carboxy-terminus of LPP. Both proteins localize in cell-cell contacts. Whereas LPP is also localized in focal adhesions and in the nucleus, Scrib could not be detected at these locations in MDCKII and CV-1 cells. Furthermore, our investigations indicate that Scrib is dispensable for targeting LPP to focal adhesions and to cell-cell contacts, and that LPP is not necessary for localizing Scrib in cell-cell contacts. We show that all four PDZ domains of Scrib are dispensable for localizing this protein in cell-cell contacts.To catch the role of LPP at sites of cell adhesion, we made an effort to identify binding partners of LPP. We found the tumor suppressor protein Scrib, which is a component of cell-cell contacts, as interaction partner of LPP. Human Scrib, which is a functional homologue of Drosophila Here, we identified an interaction between one of zyxin's family members, LPP, and the tumor suppressor protein Scrib. Both proteins localize in cell-cell contacts. This interaction links Scrib to a communication pathway between cell-cell contacts and the nucleus, and implicates LPP in Scrib-associated functions. At the heart of structural and functional integrity of multicellular entities is the ability of each and every cell of it to successfully integrate signals arising from soluble factors, cell-substratum adhesion and cell-cell adhesion . CorrectA protein that may play a role in these processes is the LPP (Lipoma Preferred Partner) protein . LPP is LPP gene, as being the preferred translocation partner of the HMGA2 gene in a subgroup of lipomas, which are benign tumors of adipose tissue [HMGA2/LPP fusion transcripts are expressed and identical fusion transcripts have also been found in a subgroup of pulmonary chondroid hamartomas [LPP gene acts as translocation partner of the MLL gene and the tumor expresses MLL/LPP fusion transcripts [Originally, we identified the martomas , in a pamartomas , and in martomas . In a canscripts . All tumnscripts .4")-motifs  via its pre-LIM region that contains an α-actinin binding site located near its N-terminus and two VASP-binding -mifs Fig.  [11]. ReDrosophila Scribble, a tumor suppressor that plays a role in the regulation of cellular adhesion, cell shape and polarity [In an effort to learn more about the molecular function of LPP, we performed a yeast two-hybrid screening experiment to identify potential LPP-interacting proteins. Here, we report that LPP interacts with Scrib, a member of the LAP (leucine-rich repeat and PDZ domain) family of proteins . Scrib ipolarity ,19. In fHIS3 and LacZ whose expression is driven by upstream GAL4 DNA-binding sites. Because all three LIM domains of LPP cooperate to target LPP to focal adhesions [In a previous study , we showdhesions , we initdhesions , this badhesions , but in dhesions . Howeverdhesions , we showWT) containing the third LIM domain and carboxy-terminus of human LPP (amino acids 531–612). Among ~1.0 × 106 yeast cotransformants (Leu+ and Trp+), 56 clones were His+ of which 23 were LacZ+ too. PCR analysis of these His+/LacZ+ clones, using prey-specific insert-flanking primers, revealed that 21 of the 23 obtained clones, contained a prey-construct having a 2 kb cDNA insert (results not shown). Subsequent fragmentation of the obtained 2 kb PCR products, representing the cDNA inserts of the prey-constructs, using the HaeIII restriction enzyme (frequent cutter), indicated that all 21 isolated prey-constructs, having a 2 kb insert, were identical. The 2 kb cDNA insert of one representative prey-construct was completely sequenced and the sequence was submitted to the NCBI database (Genbank accession no. AF271735).A mouse embryonal cDNA library was screened using a bait -search revealed that this mouse prey-construct encoded an amino- and carboxy-terminally truncated protein comprising four PDZ domains that was almost identical to the human Scrib protein Fig. , indicatHIS3 and LacZ reporter genes of the yeast only in the presence of pGBT9-LPPWT, identifying pACT2-mScrib as a true positive , threonine610 (-2 position), aspartate611 (-1 position) and leucine612 (position 0). As prey, we used pACT2-mScrib. As summarized in Table 610 (-2 position) and leucine612 (0 position) of LPP as being essential for binding to Scrib indicating a PDZ domain-mediated specific interaction between Scrib and the carboxy-terminus of LPP.Theoretically, the carboxy-terminus of the LPP protein, being -STDL, thus completely fulfils the criteria for binding to the PDZ domains of Scrib. To evaluate these predictions experimentally and to demonstrate that the binding of LPP to Scrib is specific, we performed yeast two-hybrid experiments using pGBT9-LPPAdditional yeast two-hybrid analysis showed that LPP did not interact with Erbin, PICK1, PSD-95, Syntenin, CASK, or AF6 PDZ domains, as summarized in Table WT, containing GAL4-fused full length wild-type human LPP with an intact NES, was excluded from nuclei, pM-LPPdNESWT, containing GAL4-fused full length human LPP with a deletion of the NES, was accumulating in the nuclei of the cells (results not shown). These results indicate that deletion of the NES in the LPP bait proteins used in this study indeed induce nuclear accumulation of these proteins. To perform the mammalian two-hybrid experiments, we used as baits: pM-LPPdNESWT, containing full length human LPP with a deletion of its NES, and pM-LPPdNEST610A and pM-LPPdNESL612A, which are identical to pM-LPPdNESWT except for a point mutation to alanine introduced at threonine610 (position -2) and leucine612 (position 0), respectively. As determined in the yeast two-hybrid assay, each of the threonine610 and leucine612 residues is critical for the interaction with Scrib. As prey-protein, we used pSNATCH-hScribPDZ containing a part of the human Scrib protein (amino acids 669–1233) encompassing all four PDZ-domains. As summarized in Fig. dNEST610A or pM-LPPdNESL612A were used as baits in combination with Scrib as prey. The "background" levels of luciferase that were detected when pM-LPP-baits were used in combination with pSNATCH (empty prey-vector) as prey, are due to the intrinsic transcriptional activation activity of the LPP protein [We verified the Scrib-LPP interaction, which was identified in yeast cells, in mammalian two-hybrid experiments. Doing the assay in mammalian cells rather than in yeast cells, provides a more physiological environment: proteins are more likely to be in their physiological configuration, i.e. appropriately folded and modified posttranslationally, etc. Interaction between bait- and prey-proteins in a mammalian two-hybrid assay takes place in the nucleus. For an accurate performance of this assay, this means that bait- and prey-proteins should be localized in the nucleus. In contrast to the yeast assays, where we used partial bait-proteins, we wanted to use full length bait-proteins in the mammalian assay. However, since LPP contains a nuclear export signal (NES) (amino acids 117–128) in its pre-LIM region [These results indicate that LPP binds to Scrib PDZ domains and that this binding is abolished when amino acids at position 0 or -2 are mutated.To analyze expression and intracellular distribution of Scrib in cultured cells, we prepared a Scrib-specific antibody (Scrib-472), as described in the Methods section. The Scrib-472 antibody recognized a protein of an apparent molecular mass of more than 200 kDa in a number of different cell extracts Fig. . Scrib wWe have shown before that LPP is localized in cell-cell contacts  and alsoWT containing full length wild-type LPP, or GFP-LPPT610A, which is identical to GFP-LPPWT except for a point mutation to alanine introduced at threonine610, which abolishes binding to Scrib. No difference in focal adhesion localization could be detected between wild-type and mutated GFP-LPP fusion proteins . However, both the full length Scrib-GFP protein as well as the mutated form lacking all four PDZ domains localized equally well in cell-cell contacts . All GST-fusion proteins as well as GST alone were expressed well in E. coli , and tested how efficiently these mutated proteins were pulled down by GST-LPP-LTWT. From the results, which are presented in Fig. WT was almost completely abolished when the carboxylate binding loop of this PDZ domain was destroyed.To further investigate the requirements in the Scrib protein for binding to LPP, we performed additional GST pull-down experiments. From our previously described experiments , it was clear that the PDZ domains of Scrib bind to LPP. These findings were confirmed by using GST pull-down: as shown in Fig. Listeria monocytogenes protein ActA (mito). Expression of this construct was confirmed by Western blotting with the use of an anti-Xpress antibody (results not shown). CV-1 cells were transiently transfected with Xpress-hScrib-mito and full length wild-type or carboxy-terminally mutated LPP green fluorescent protein fusions. Cells were stained with an anti-Xpress antibody and examined by fluorescence microscopy. In all transfected cells, the Xpress-hScrib-mito chimera localized to mitochondria, as shown in Fig. Evidence for an in vivo interaction between Scrib and LPP was obtained by performing mitochondrial targeting experiments. We tested if Scrib was sufficient to recruit LPP to an ectopic location in living cells. The membrane anchor of the ActA sequence has been shown previously to be sufficient to target proteins expressed in mammalian cells to the surface of mitochondria ,28. ThisTo investigate the importance of the PDZ domains of Scrib in this recruitment of LPP, we deleted all four PDZ domains (amino acids 724–1192) from Xpress-hScrib-mito (=Xpress-hScribdPDZ-mito) and tested whether this PDZ-less protein still was able to recruit LPP to mitochondria. As shown in Fig. As mentioned above, the Xpress-hScrib-mito chimera localized to mitochondria in all cells that expressed this protein. However, LPP, which was co-expressed, was only recruited to mitochondria in a small fraction of these cells. This issue will be further addressed in the Discussion section.LPP gene as being rearranged in certain subtypes of these tumors [In the course of our studies of chromosomal aberrations in benign tumors, we have previously discovered the e tumors , and idee tumors . In thisCaenorhabditis elegans (LET-413) [Drosophila melanogaster (Scribble) [Scrib is a member of the LAP (LRR (leucine-rich repeat) and PDZ (PSD-95/Discs-large/ZO-1)) family of membrane-associated proteins that play a role in the regulation of cell polarity . LAP famLET-413) , and in cribble) . LAP procribble) .Drosophila melanogaster. Drosophila Scribble was identified as being required for the apical confinement of polarity determinants in epithelia [Drosophila provided evidence that Scribble is a tumor suppressor and cooperates with two other tumor suppressors, Lethal giant larvae (Lgl) and Discs-large (Dlg) to regulate cell polarity and growth control [Drosophila neuroblasts [Drosophila implicate Scribble in the regulation of synaptic plasticity and synaptic vesicle dynamics [Drosophila [Most information regarding the function of Scrib comes from studies in pithelia . Mutatio control . Recentlroblasts . The rolroblasts , and tharoblasts . Additiodynamics ,39, and osophila .Drosophila scribble protein [As for mammalian Scrib, little information is available at the moment. Relating to the control of cell polarity and proliferation, human Scrib was found to be a functional homologue of the  protein . Polarit protein ,41. HumaIn this regard, it is noteworthy that we observed a remarkable aspect regarding the expression levels of Scrib in a number of mammalian cell lines. As already mentioned before Fig. , we notiDrosophila Scribble [circletail mouse [Circletail is one of only two mouse mutants that exhibit craniorachischisis. The fact that Scrib was identified as the gene that was mutated in this mouse attributes an important role for Scrib in development [In addition to its role as a tumor suppressor, Scrib was also implicated in the regulation of planar cell polarity, a role that is not established for Scribble , and it il mouse . Disruptelopment .Drosophila ancestor Scribble have been mainly addressed in epithelial cells. To our knowledge, nothing is known yet about the function of Scrib in other cell types such as lymphocytes and fibroblasts.We show here that Scrib is expressed equally well in very different cell types, such as Jurkat cells, which are human T lymphocytes, epithelial cells such as 293 and MDCKII cells, and in fibroblasts such as CV-1 cells. As described above, the function of Scrib and its Cas family of signal transducers, which are focal adhesion components [et al. [We show here that LPP specifically binds to and partially co-localizes with Scrib in cell-cell contacts of epithelial and fibroblastic cell lines. Previous studies have shown that PDZ domain proteins play an important role in the targeting of proteins to specific membrane compartments and in the assembly of these proteins into supramolecular complexes . Therefomponents . This inmponents . We also [et al. , who havDrosophila synapses [Taken into account that PDZ domains vary in their range and stringency of specificity , it is nsynapses , and versynapses . These fIn this regard, it is worth mentioning that the binding of LPP to Scrib appears to be regulated. In our mitochondrial targeting experiments Fig. , we notiTaken together the fact that LPP shuttles between cell adhesion sites and the nucleus ,48, and The GFP-LPP construct was described before . A constThe KIAA0147 partial cDNA clone was kindly provided by Takahiro Nagase (Kazusa DNA Research Institute, Japan). In order to obtain full-length 5'-cDNA sequences encoding human Scrib, RNA-linker mediated 5'-RACE (RLM-RACE) was performed according to published protocols  using RNThe Matchmaker Two-Hybrid System 2 was used (Clontech). All experiments were performed in the yeast reporter strain CG-1945. Bait-constructs were made using the vector pGBT9 (Clontech). The prey-constructs pACT2-AF6, pACT2-Erbin, pACT2-PICK1, and pACT2-PSD95 were kindly provided by Jean-Paul Borg (INSERM, Marseille, France), and were described in Audebert and Navarro et al., (AF6, Erbin, PICK1)  and in SHIS3 and a lacZ reporter gene under the control of promoters containing GAL4-binding sites, was transformed with 66 μg of bait-DNA and 33 μg of prey-library-DNA using a LiAc high efficiency transformation protocol [---) agar plates containing 5 mM 3-AT (Sigma).The prey-library was screened as follows: yeast strain CG-1945, containing a protocol . Transfo+ yeast colonies were restreaked on new SD--- agar plates and grown for another 1 to 2 days. Colony-lift filter assays were performed for the qualitative measurement of β-galactosidase activity according to standard protocols.Transformed His2 incubator.Cell lines used included CV-1 (ATCC CCL-70), HEK293 (ATCC CRL-1573), 293T (HEK 293 cells expressing the SV40 T-antigen), Jurkat (ATCC TIB-152), and MDCK strain II . Jurkat cells were grown in RPMI 1640 (Life Technologies) supplemented with 10% fetal bovine serum. All other cell lines were grown in DMEM/F12 (1:1) (Life Technologies, Inc.) supplemented with 10% fetal bovine serum. Cells were cultured at 37°C in a humidified COTransient transfections were performed using FuGene™ 6 Transfection Reagent (Boehringer Mannheim) according to the supplier's instructions. Cells were incubated at 37°C for 18–24 hours before analysis.Stable MDCK strain II cell lines were made expressing wild-type and carboxy-terminally mutated human GFP-LPP proteins, wild-type full length Scrib-GFP, or Scrib-GFP lacking all four PDZ-domains. Transfection of MDCK cells was performed using Lipofectamine 2000 Reagent (Life Technologies) according to the manufacturer's instructions. Transfected cells were selected in medium containing 250 μg/ml G418 (Life Technologies), and resistant colonies were isolated 10–14 days later. Individual clones were screened for expression of the respective GFP fusion proteins by Western blotting using a rabbit polyclonal anti-GFP antibody (Tebu Bio).Bait-constructs were made using pM-vectors , prey-co35S]-methionine-labelled full length human Scrib protein, or a portion of the human Scrib protein encompassing all four PDZ domains (amino acids 616–1490) (wild-type or mutated) in NENT100 buffer (100 mM NaCl, 20 mM Tris-HCl pH = 7.6, 1 mM EDTA, 0.1% NP-40, protease inhibitors). This mixture was tumbled overnight at 4°C. Subsequently the beads were washed 5 times in 500 μl NENT100 buffer, resuspended in 25 μl SDS-PAGE sample buffer and incubated at 95°C for 5 minutes. Proteins were separated by SDS-PAGE and interacting Scrib was detected by autoradiography.All in vitro translation reactions were carried out using the TNT T7 Quick Coupled Transcription/Translation System (Promega) following the manufacturer's instructions. For GST pull-down assays, bacterial expression constructs were made using pGEX-5X vectors (Amersham-Pharmacia Biotech) directing the synthesis of glutathione S-transferase (GST) fusion proteins containing wild-type or mutated forms of human LPP. These fusion proteins were purified according to manufacturer's instructions and verified by SDS-PAGE. GST fusion proteins or GST alone, bound to glutathione-agarose beads, were incubated with in vitro synthesized [1612CSSRRPVRPGRRGLGPVPS1630 . For the detection of endogenous LPP in MDCKII cells, a LPP-specific monoclonal antibody was used (BD Biosciences, Transduction Laboratories). For the detection of GAL4-fusion proteins in immunocytochemistry, a rabbit polyclonal anti-GAL4 DNA-binding domain antibody (Tebu Bio) was used. Vinculin was detected in cells with a monoclonal anti-vinculin antibody (Sigma, clone hVIN-1), Xpress-tagged proteins with a monoclonal anti-Xpress antibody (Life Technologies). Fluorescently-tagged Alexa-antibodies (Molecular Probes) were used as secondary antibodies for immunofluorescence detection.The Scrib-specific polyclonal antiserum Scrib-472 was prepared by Eurogentec by immunization of rabbits with a keyhole limpet hemocyanin (KLH) coupled peptide Eukaryotic cell extracts were prepared by harvesting the cells in PBS , and subsequent lysis of the cell pellets in SDS-PAGE sample buffer (60 mM TRIS-HCl pH = 6.8, 12% glycerol, 4% SDS, 5% β-mercapto-ethanol). Protein concentrations in cell extracts were determined using BCA Protein Assay Reagent (Pierce) according to the manufacturer's instructions. 30 μg of proteins of each cell extract were loaded on 5% SDS-polyacrylamide gels. After size-separation, proteins were electrophoretically transferred to PROTEAN Nitrocellulose Membranes (Schleicher and Schuell). ECL Western blotting was performed using Western Lightning Chemiluminescence Reagent Plus (Perkin Elmer Life Sciences) according to the supplier's instructions.2 and 0.1 mM MgCl2 (PBS++). For GFP-fluorescence, slides were mounted in vectashield mounting medium (Vector Laboratories, Inc.) and analyzed on a Zeiss Axiophot fluorescence microscope equipped with an RT slider SPOT camera (Diagnostic Instruments, Inc.) using SPOT RT Software v3.4, or by confocal microscopy . For indirect immunocytochemistry, after fixation, quenching was performed by incubating the cells for 10 minutes at room temperature in PBS++ containing 50 mM NH4Cl. Cells were then permeabilized with 0.4% Triton-X-100 for 5–10 minutes at room temperature. Unspecific binding was blocked with 0.5% Blocking Reagent (Roche) in PBS++ for 30 minutes at room temperature. Subsequently, the slides were incubated with primary antibodies for 1 hour at room temperature. After washing the cells three times in PBS++, bound primary antibodies were detected with fluorescently labelled secondary antibodies (Molecular Probes) for 30 minutes at room temperature. Following three washes in PBS++, slides were mounted and analyzed as described for GFP-fluorescence.CV-1 or 293T cells seeded on glass coverslips, and MDCKII cells seeded on glass coverslips or on Transwell-Clear polyester membranes (0.4 μm, Costar) were fixed in 4% formaldehyde for 20 minutes at room temperature followed by three washes in PBS containing 0.1 mM CaClMMRP designed the study, performed the yeast and mammalian two-hybrid experiments, as well as the mitochondrial targeting experiments, made the LPP-stable cell lines, performed the confocal microscopy with these cell lines, and prepared the manuscript. SMPM constructed most of the DNA constructs, made the Scrib-stable cell lines, performed the epifluorescence microscopy with these cell lines, and carried out the Western blotting experiments. PA performed the GST pull down experiments, and contributed to the characterization of the Scrib-472 antibodies. TAYA contributed to the establishment of a full length Scrib cDNA clone, and to the writing of the manuscript. EJ contributed to the development of the Scrib-472 antibodies, to the establishment of a full length Scrib cDNA clone, and to the funding of the project. WJMVDV contributed to the writing of the manuscript and to the funding of the project.


Brugia malayi termed abundant larval transcript , expression of which reaches ~5% of total transcript at the time parasites enter the human host.Parasites exploit sophisticated strategies to evade host immunity that require both adaptation of existing genes and evolution of new gene families. We have addressed this question by testing the immunological function of novel genes from helminth parasites, in which conventional transgenesis is not yet possible. We investigated two such novel genes from Leishmania mexicana. We then followed the course of infection in vitro in macrophages and in vivo in mice. Expression of ALT proteins, but not a truncated mutant, conferred greater infectivity of macrophages in vitro, reaching 3-fold higher parasite densities. alt-transfected parasites also caused accelerated disease in vivo, and fewer mice were able to clear infection of organisms expressing ALT. alt-transfected parasites were more resistant to IFN-γ-induced killing by macrophages. Expression profiling of macrophages infected with transgenic L. mexicana revealed consistently higher levels of GATA-3 and SOCS-1 transcripts, both associated with the Th2-type response observed in in vivo filarial infection.To test the hypothesis that ALT proteins modulate host immunity, we adopted an alternative transfection strategy to express these products in the protozoan parasite Leishmania transfection is a tractable and informative approach to determining immunological functions of single genes from heterologous organisms. In the case of the filarial ALT proteins, our data suggest that they may participate in the Th2 bias observed in the response to parasite infection by modulating cytokine-induced signalling within immune system cells. Brugia malayi is a causative agent of the disease lymphatic filariasis, which afflicts over 100 million people in tropical countries. Mosquito-borne infective stage larvae gain entry to the human body during a blood meal, and establish long-lived infections characterised by down-regulation of host T cell and macrophage reactivity [abundant larval transcript  -1 and -2 [alt-like genes are present in other filarial nematode species [Caenorhabditis elegans and C. briggsae but in both cases the acidic domain is absent (Gregory, Maizels and Blaxter, unpublished observation).Pathogens have evolved many ingenious mechanisms to manipulate innate and adaptive host immune responses -6. The nactivity ,8. We ha1 and -2 ,10. The  species ,12 and aALT proteins are stockpiled in the oesophageal glands of infective larvae  and are Leishmania, several species of which are infective to laboratory mice. Leishmania can readily be modified genetically [L. mexicana as it establishes infections in murine macrophages in vitro, providing experimental access to a key cell type known to be modified in filarial infection [L. mexicana will also infect mice, and although the immunological factors determining resistance and susceptibility are not as well-defined as in L. major [in vivo kinetics and consequently is anticipated to be more sensitive to altering factors. Using this model, we show here that transgenic L. mexicana expressing the ALT proteins are more virulent in macrophages in vitro, and that this property is abolished by deletion of the filarial-specific acidic domain. We also show that mice infected with alt-transgenic L. mexicana harbour higher parasite burdens than controls. By studying the responses of macrophages infected with transgenic parasites, we suggest that the ALT products modulate cytokine-induced signalling and render parasites more resistant to IFN-γ-induced killing.Transgenesis and targeted gene deletion have yet to be established for parasitic helminths, so it is not possible to investigate the biological role of ALT proteins by conventional reverse genetics. We reasoned, however, that if ALT function is fulfilled within the host rather than within the parasite, we can validly study these proteins by transgenic expression in a more tractable carrier species. We chose to test this approach with the protozoal parasite etically -20 to yinfection ,21-23. LL. major -26, it oBm-alt-1 and Bm-alt-2 genes were subcloned in their entirety, including endogenous signal peptide sequences, into the recombination vector pSSU, which contains flanking sequences homologous to the 18S small subunit (SSU) rRNA locus [L. mexicana was undertaken, permitting homologous recombination of the alt-1 and -2 sequences downstream of the strong polymerase I promoter into the sequence for the small sub-unit rRNA, which is known to be transcribed in both stages of the life cycle of the parasite. Following puromycin selection, multiple transgenic lines were isolated for each alt gene, from which representative clones were selected containing the correct insert at an appropriate integration site. Transgenic ALT expression in the free-living culture promastigote stage was confirmed in both lines by Western blot (data not shown) and immunofluorescent staining  of animals given transfected L. mexicana compared to 50% (4/8) of those receiving wild-type parasites (p = 0.03, χ2 test)  Figure .alt-transfected parasites not only achieve higher infection levels in unstimulated macrophages (no IFN-γ), but survive better in cells stimulated with intermediate IFN-γ doses (0.01–0.1 U/ml) than do wild-type organisms. Interestingly, the production of nitrite was comparable at each IFN-γ dose in all parasite types . Two independent experiments were performed, and hybridization of [33P]-labelled cDNA was measured by phosphorimaging of spots of interest. Little difference was seen in hybridization for iNOS, IL-10, IL-12 , which was cloned into the pSSU vector and electroporated into L. mexicana. These transfectants expressed immuno-reactive protein . We are now using this system to analyse the gene expression profiles of macrophages infected with MIF-transfected parasites in both in vitro and in vivo settings.We have also extended the use of this transfection system to the analysis of other parasite genes that are hypothesised to be immunomodulatory. For example, filarial parasites produce homologues of mammalian macrophage migration inhibitory factor, MIF ,40, a cyLeishmania transfection system can be used in parallel for in vitro and in vivo experiments, and the importance of an in vivo read-out to assay gene effects within the immune system as a whole. In addition, our work has demonstrated that Leishmania transfection for helminth gene analysis is equally applicable for two completely unrelated, but immunologically important, gene families.These data illustrate the facility with which the L. mexicana is ideally suited to the study of macrophage modulation by genes predicted to function in this environment. Parallel investigations can also be envisaged by transfection of L. major, which will permit a more thorough analysis of T cell modulation to be undertaken. For example, resistance to L. major is clearly associated with development of a parasite-specific Th1 response, and it is possible that parasite genes that inhibit Th1 differentiation will alter the course of L. major infection in vivo. These studies are now under way.The application of this new strategy to transfection of alt-transfected parasites has resonance for initial host susceptibility, and longer-term propensity for chronic infection, as well as the ability to eliminate the blood-borne Mf stage.Macrophages are known to be a critical cell population in the immune response to filarial parasites at successive points in time. First, they participate in innate defences against invading larvae ,36; secoA key outcome of the present study is that ALT expression is associated with up-regulation of GATA-3 and SOCS-1. GATA-3 is a pivotal transcription factor for the development and function of the Th2 pathway ,44 and hLeishmania parasites, because macrophages from SOCS-1 null mice require 100-fold less IFN-γ to clear infection [Leishmania killing  promastigotes were cultured in vitro in semi-defined medium/10% heat inactivated foetal calf serum (hiFCS)/1% penicillin-streptomycin (complete SDM) at 26°C. Amastigotes were cultured axenically at 34°C in Schneider's Drosophila medium (Gibco BLR) supplemented with 20% hiFCS and 3.9 g/l 2-(N-morpholino)ethanesulfonic acid (Sigma, U.K.). Transgenic parasites were cultured under the same conditions with the addition of 20 μg/ml puromycin (Sigma, U.K).Six- to eight-week old female C57BL/6 and CBA mice were used. 2.The murine macrophage cell line J774 was passaged in DMEM containing 10% hiFCS/1% penicillin-streptomycin/1% L-glutamine and cultured at 37°C in 5% COalt-1 and alt-2 from a B. malayi L3 cDNA library. The oligonucleotides used for alt-1 were 5'-CCGCTCGAGATGAACAAATTGCTAATAGCA-3' (sense, initiating codon in bold) and 5'-TGCTCTAGATTACGAGCATTGCCAACTTTC-3' (antisense, terminating codon in bold); and for alt-2, 5'-CCGCTCGAGATGAATAAACTTTTAATAGCA-3' (sense) and 5'-TGCTCTAGACTATGCGCATT GCCAACCTGC-3' (antisense). After an initial denaturation step at 95°C for 5 min the PCR was cycled between 94, 55 and 72°C (1 min each) for 35 rounds, followed by 1 round at 72°C for 10 min. The fragments were digested with XhoI and XbaI and cloned into the pSSU vector (13), yielding pSSU-alt-1 and pSSU-alt-2. Clones were fully sequenced on both strands. DNA was extracted from pSSU-alt-1 and pSSU-alt-2 using the Qiagen Miniprep kit following the manufacturer's instructionsPrimers were designed to amplify the entire coding region of 2 mutant, in which the acidic domain of the protein (amino acids 24–49) were deleted, was generated using the Exite PCR-based site-directed mutagenesis kit (Stratagene, USA) following the manufacturer's instructions. The pSSU-alt-2 construct (see above) was used as the template in a PCR reaction containing two oligonucleotides: 5'-TGATTCTGATACACACGGGAGTGT-3' (antisense, primer phosphorylated) and 5'-TATGTAACCAAAGGGAATTTGTT-3' (sense). The cycling parameters were as follows: 1 cycle of 1 min at 94°C, 4 min at 53°C and 2 min at 72°C; followed by 10 cycles of 1 min at 94°C, 2 min at 55°C (adding 10 s after each cycle) and 1 min at 72°C; and a final cycle of 5 min at 72°C. After the PCR the nonmutated parental plasmids were digested with Dpn restriction enzyme. The undigested linear DNA was then polished with Pfu DNA polymerase and ligated at 37°C for 1 h with T4 DNA ligase. The ligated DNA was then transformed into E. coli, yielding a pSSU-ADD (acidic domain deleted) construct. The insert was sequenced to verify that the intended mutation was correctly constructed.An ALT-7) were electroporated with 10 μg of PmeI linearized fragments of either pSSU-alt-1, pSSU-alt-2 or pSSU-add. Clones were selected on 24-well plates in complete SDM supplemented with 20 μg/ml of puromycin and further propagated in a culture volume of 10 ml.Logarithmic phase promastigotes (4 × 104Cl for 10 min. Wild-type parasites were incubated with dilution buffer (0.1% saponin, 2% goat serum) in the presence of anti-L. mexicana rabbit serum or anti-ALT mouse serum (from C57BL/6 mice) for 45 min. Following 3 washes with wash buffer (0.1% saponin, PBS) the parasites were incubated with either an anti-rabbit-FITC or an anti-mouse-FITC secondary antibody (DAKO, Denmark) for 45 min. They were then washed 3 times before mounting with Cityfluor (Cityfluor Ltd, UK) for microscopy.Promastigotes were washed in PBS, fixed in 2% paraformaldehyde for 30 min at room temperature, and quenched in NH6/ml and fixed without permeabilization in 2% paraformaldehyde for 15 min at room temperature. After two washes in PBS, 10% FCS (FACS wash), the parasites were stained with anti-ALT-1 antibody or normal mouse serum diluted in FACS wash. This was followed by incubation with a FITC anti-mouse secondary antibody (DAKO, Denmark). Flow cytometric analysis was performed using a FACScan (Becton Dickinson) and analysed using CellQuest 3.1 software.Promastigotes were washed in PBS, resuspended at 1 × 105/ml in complete DMEM, supplemented with 20% (v/v) L929 cell-conditioned medium as a source of M-CSF and 20% hiFCS. After 6 days at 37°C, the cells were detached by incubation in PBS containing 3 mM EDTA and 10 mM glucose, plated and cultured in small non-tissue culture Petri dishes at 2.5 × 105/ml in complete DMEM for 24 h at 37°C.BMM were obtained from femurs and tibias of 6- to 8-week old CBA mice by flushing the bones with DMEM (Gibco, BLR) containing 10% hiFCS/1% penicillin-streptomycin/1% L-glutamine. Cells were centrifuged and plated out in non-tissue culture Petri dishes at a density of 5 × 10alt-transfected amastigotes at a ratio of 10 parasites per macrophage. After the period of infection macrophages were harvested as described above, washed with PBS and fixed and permeabilized using a "Fix & Perm kit" (Pharmigen); 1 × 105 cells were centrifuged on to glass slides with a Cytospin. Intracellular Parasites were detected and counted by immunofluorescence as described above. Between 100 and 200 macrophages were counted for each time-point.Day 7 BMM were infected for 24 h or 7 days at 34°C with wild-type or L. mexicana in vivo infections, groups of 8 female C57BL/6 mice were injected subcutaneously in the footpad with 3 × 106 stationary-phase wild-type L. mexicana, alt-1 transfectants and alt-2 transfectants. Lesion size was measured weekly during the course of infection with a dial micrometer and expressed as the difference in size between the infected footpad and the contralateral uninfected footpad.For B. malayi in vivo infections, groups of 5 female C57BL/6 mice were injected intraperitoneally with 200 infective larvae recovered from crushed Aedes aegypti mosquitoes. After the experimental period the mice were euthanized by terminal anaesthetic, and peritoneal cells (PEC) were harvested by thorough washing of the peritoneal cavity with 15 ml of ice-cold RPMI supplemented with 10% FCS. The harvested PEC were plated in 24-well culture plates at 2 × 106 cells/well. Following 3 h at 37°C to allow cells to adhere, both the non-adherent and the adherent macrophage-enriched cell populations were harvested.For The number of parasites in the footpad was estimated by limiting dilution assay. Infected footpads were harvested in cold PBS after removal of the skin. Footpad tissue was dispersed through a cell strainer and resuspended in PBS-1% penicillin/streptomycin. After centrifugation the pellet was resuspended in complete SDM. The cell suspension was then serially diluted in 10-fold steps, in quadruplicate, in 96-well plates. The plates were incubated for 4 days at 27°C; the wells were then observed for parasite growth.5/well) and incubated at 37°C for 24 h. The medium was then removed, the cells were washed twice, and L. mexicana promastigotes were added for 4 h at a ratio of 10 parasites per well. IFN-γ (40 U/ml) and LPS (10 ng/ml) were then added, with or without the arginine analogue N-monomethyl-D-arginine (D-NMMA), 1 mM. Nitrite accumulation in medium over the subsequent 24–48 h was used as an indicator of NO production and was assayed by the Griess reaction in which 100 μl of Griess reagent [2 was used to make a standard curve for each plate reading.J774 macrophages were plated out on 96-well plates (1 × 10 reagent  was adde4) were plated out on glass coverslips in 24-well plates, allowed to adhere for 24 h, and stimulated with 100 ng/ml LPS and the indicated concentrations of IFN-γ. Cells were incubated for 6 h at 37°C before adding stationary phase promastigotes of wild-type L. mexicana or transfected alt-1 and alt-2 parasites at a ratio of 10 parasites per cell. After 72 h at 37°C the cells were stained with Giemsa. The percentage of macrophages infected with parasites was determined by counting 4 samples of 100 cells.BMM  according to the manufacturer's instructions. The RNA was subjected to DNase treatment (Ambion, INC) to eliminate genomic contamination, according to the manufacturer's instructions33P]dCTP. The radiolabelled cDNA probes generated from non-infected and infected cells were hybridized to identical membranes containing the mouse cDNA arrays. Following hybridization, high stringency washes were performed and the membranes were subjected to autoradiography. Quantification was carried out using a PhosphorImager and data analyzed with ImageQuant v1.2.Gene expression was analysed using the Mouse Cytokine Expression Array (R&D systems). The mouse cytokine-specific primers were first annealed to the total RNA, which was then reverse transcribed in the presence of SuperScript II (Invitrogen, Life Technologies) and [α-alt-2 infected macrophages cDNA were used to produce a standard curve in each reaction. The abundances of GATA-3 and SOCS-1 were expressed as ratios of amplified product to the control, mouse S29 ribosomal protein. Primers for RT-PCR analysis were as follows: GATA-3: 5'-CTA CGG TGC AGA GGT ATC C-3' and 5'-GAT GGA CGT CTT GGA GAA GG-3'; SOCS-1: 5'-ACC TTC TTG GTG CGC GAC AGT CGC CAA-3' and 5'-GGA ACT CAG GTA GTC ACG GAG TAC-3'; and S29 ribosomal protein: 5'-ATG GGT CAC CAG CAG CTC TAC-3' and 5'-GTC CAA CTT AAT GAA GCC TAT-3'.Total RNA was extracted in Trizol, as described above, and single-stranded cDNA was synthesized using MMLV reverse transcriptase (Stratagene). Relative quantification of the expression of the genes of interest was measured by real-time PCR using the LightCycler . PCR amplifications were performed in 10 μl volumes containing 1 μl cDNA, 2.5 mM MgCl2, 3 μmM primers and the LightCycler-DNA SYBR Green I mix (Qiagen). The reaction was performed in the following conditions: 15 min activation step at 95°C for one cycle, 15 s denaturation at 95°C, 20 s annealing of primers at 50°C and 15 s elongation at 72°C, for 50 cycles. The fluorescent DNA binding dye SYBR Green was monitored after each cycle at 80°C. Five serial 1:2 dilutions of alt, abundant larval transcript gene or mRNA; BMM, bone marrow-derived macrophages; FACS, fluorescence-activated cell sorter; L3, third-stage infective larva; NO, nitric oxide.ALT, abundant larval transcript protein; Leishmania transfection methodology. TA, CCB and RMM jointly conceived the transfection strategy for Brugia genes, critically assessed progress, and made revisions to the draft manuscript. The overall study was co-ordinated by RMM who also completed the draft of the manuscript. All authors read and approved the final manuscript.NG-E designed and led the experimental work, including molecular constructs, cell transfection, immunological assays, array and RT-PCR analyses. She also drafted the manuscript. CB and LP-L made constructs in pSSU, maintained Leishmania cultures, participated in electroporation procedures, macrophage infection, in vivo infection and dilution assays. TA designed the transfection system and devised the


We establish that the occurrence of protein folds among genomes can be accurately described with a Weibull function. Systems which exhibit Weibull character can be interpreted with reliability theory commonly used in engineering analysis. For instance, Weibull distributions are widely used in reliability, maintainability and safety work to model time-to-failure of mechanical devices, mechanisms, building constructions and equipment.We have found that the Weibull function describes protein fold distribution within and among genomes more accurately than conventional power functions which have been used in a number of structural genomic studies reported to date.β for protein fold distributions varies between genomes and may reflect differences in rates of gene duplication in evolutionary history of organisms.It has also been found that the Weibull reliability parameter The results of this work demonstrate that reliability analysis can provide useful insights and testable predictions in the fields of comparative and structural genomics. Px ≈ xγ-, where x is the number of links connected to each network node and γ is the value of the exponent typically varying in the range of 2–3 [Recent advances in networks theory have demonstrated a key role of uneven distributions occurring in many natural processes. It has been found that seemingly unrelated systems such as economic, professional, sexual and social networks, airline routing, power lines connections, language networks and internet hyperlinks all exhibit a power law decay of the cumulative distribution e of 2–3 . The hetThe applicability of the scale free networks has been examined in numerous structural genomics studies. It has been proposed that the genomic occurrence of protein families, superfamilies and folds can follows an asymptotic power law:SDF(GO) = aGOb -    (1)SDF(GO) is survival distribution function of genomic occurrence GO of a certain protein family, superfamily and fold. These findings have laid the foundation for characterizing the evolution of the protein universe in terms of a growing scale-free system in which individual genes are represented as nodes of a propagating network [, where  network -7.b estimated in the study generally fall below the 2–3 range typical for scale-free systems  .In our previous work , we haveigations ). Table The established lowered values of the power exponent and modest accuracy of the power law dependences (1) encouraged us to seek alternative approaches to more accurately describe protein folds distributions.The Weibull distribution is a general-purpose statistical function defined within Extreme Value Theory  and wideα is a scaling factor and β is a shape parameter also known as the slope [, where he slope .i.e it utilizes time-to-failure (or time under the testing stress) to assess the reliability of a system and to forecast its stability through parameters of the characteristic life span α and shape β. A typical Weibull experiment is based on application of disruptive stress to multiple samples representative of the population until the tested objects achieve a state of failure and produce time-to-failure numbers. The corresponding time-to-failure values form heterogeneous Weibull distributions described by (2).The Weibull analysis operates on life data, i.e. to fail. Considering these analogies, we anticipated that the Weibull logistic can provide some natural explanations for highly heterogeneous abundance of protein folds in genomes. To test this hypothesis we used two independent approaches to examine whether the genomic occurrence of protein topologies and domains can indeed be adequately described by the Weibull function.The distribution of protein folds in a genome can be viewed much like the behavior of a mechanical system under disruptive testing. It is feasible to stipulate that the increase of genomic abundance of any protein fold occurs under evolutionary pressure. Some folds are able to expand their genomic occurrence over a course of evolution others have higher probability to be lost through genetic drift and other random events, SDF(x) of the genomic occurrences of protein topologies and homologous superfamilies into the Weibull dependence (2). The corresponding Weibull shape parameters have been established by solving the equation  while the scaling factors have been calculated as .First of all, we employed the maximum likelihood (ML) method  to fit tSDF(GO) parameters reproduced within equation (2) through α and β values estimated by the ML approach. It is obvious that these computed blue curves labeled as 'Weibull analytical' resemble the experimental distributions (marked in red) very precisely.The ML method allowed very accurate description of the distribution of protein folds among the genomes. Figures α and β values estimated by the ML approach have been collected into Table 2 (see The corresponding le 2 see .SDF(x) leads to the equation of a straight line:The second way of examining applicability of the Weibull function (2) was based on notion that the double logarithmic transformation of the SDF(x)) = β log(x) - β log(α)     (3)log(- log(SDF(GO) data to estimate the Weibull coefficients α and β and squared correlation coefficients r2 which all have also been collected into Table 2 (marked as 'Weibull by plotting').We performed the transformation (3) on the experimental r2 from Table 2 demonstrate very high accuracy of the linear dependences (3) established from the survival distributions of CATH folds in the studied genomes. These parameters also allow comparing the accuracy of double logarithmic dependences (3) with accuracy of simple logarithmic dependences derived from the power law model (1):The values of the estimated squared correlation coefficients log(SDF) = a - b*log(GO)     (4)SDF(GO) functions for individual genomes, superkingdoms and for the combined set of proteins. The comparison of r2 values from Table 2 and Table 1 established from the linear functions (3) and (4) respectively, reveals that for all studies cases  the statistical quality of Weibull dependences (3) is much better than of power law function (4). Figures SDF(x) curves with remarkable accuracy. Apparently, the distributions calculated from (3) (labeled as 'Weibull by plotting') are much closer to the experimental distributions than the power law curves (labeled as 'power law') computed within the conventional power function (1). Apparently, that the Weibull distributions established by the double logarithmic representations (4)  and the preference should, perhaps, be given to more stringent ML-derived data.As it has been mentioned earlier, the dependences (4) have been estimated for the Although the estimated statistical criteria clearly demonstrate the suitability and superiority of a Weibull function over a power function in describing protein fold distributions, we decided to examine several additional criteria characteristic of the Weibull distribution. As it has been suggested by Romeu  there arr2 values from the columns marked as 'Weibull by plotting' are all contained within the range ~0.95–0.98 what demonstrates that the 'Weibull papers' do indeed describe protein folds distribution in the studied genomes with high accuracy. Figures As it can be seen from Table 1 the estimated β derived by analytical maximum likelihood approach.The data from Table 2 demonstrate that the estimated slopes of the 'Weibull papers' are very close to the values of GOβ distributions through the power factors β. The exponential character of the resulting distribution has been examined by several statistical tests and in all cases has been confirmed. The observed medians of the exponential distributions GOβ accumulated in Table 3  from shape and scale parameters [Thus, all four specific criteria studied indicate that the genomic occurrence of protein topologies and domains can be characterized as true Weibull distributions. To support this notion further we have also considered another important property of the he Weibull distribution – the dependence of its median  and analytical (ML) approaches. The corresponding 'MDN Calctd' values have been collected into Table 3 along with the observed medians of the Weibull distributions (marked 'MDN Obsrvd'). The estimated high quality linear dependences between the theoretical and observed medians are present on figures To assess the applicability of this condition, we calculated Weibull medians using sets of Thus, multiple independent tests have demonstrated that occurrence of protein folds in genomes obey the Weibull distribution and therefore can be interpreted in terms of the reliability theory what can provide additional insight into folds evolution.The very fact that we were able to assign the Weibull character to the distributions of the CATH protein topologies and homologous superfamilies within genomes ultimately implies that parameters of genomic occurrence can be classified as extreme values. According to the Extreme Values Theory the Weibull distribution will successfully model life systems for which many competing similar failure processes are "racing" to failure and the first to reach it produces the observed failure time . In regaβ > 1 characterizes a life system that increasingly deteriorates. If the shape parameter is smaller then unity (β <1), there is a reliability growth as the failure rate of the system decreases with time [β does indeed describe the "skewdness" of the fold distribution, for example Caenorhabditis elegans has the lowest calculated value β among the studied organisms, whilst this genome has also been characterized for its recent expansion and duplication of several gene families [β (according to the reliability theory characterizing the genome of C. elegans as the most stable amongst the studied) may reflect the fact that chances of loosing some lower abundant fold families are lower for C. elegans (considering that >70% of the translated ORFs C. elegans genome have been covered by the sequence-structure threading we have assumed that the recently duplicate genes are accordingly represented in the results). In this context, the reliability of a proteome can be viewed as its ability to maintain and expand its composition without loss of protein folds.On another hand, according to reliability theory a Weibull distribution with ith time . It is nfamilies . Presumaβ <1 i.e. to have more balanced (less heterogeneous) folds representation in their genomes. The fact that most β values presented in Table 2 fall below the unity threshold demonstrates that, in general, the reliability of genome fold composition increases with time, i.e. less protein folds reach the failure state (termination of multiplication and, likely, following evolutionary extinction) as an organism evolves.We can speculate that life systems that enjoy evolutionary success will tend to minimize β shape parameters for topologies distributions across the three superkingdoms. All three linear dependences ln(- ln(SDF(GO))) ~ ln(GO) for Bacteria, Eukaryote and Archaea presented on Figures Interestingly, little difference is observed has been found between the i.e. more abundant folds tend to expand their genomic presence even further causing lesser abundant folds to extinct.As it has been already mentioned above, it is difficult to decide at this point whether the observed Weibull character of protein folds distribution can be placed in a larger context. We can only speculate that protein folding preferences may lead to a greater abundance of favorable protein configurations and to extinction of those folds which are less favorable. Such selection may represent a mechanism of evolutionary quest for searching for better protein folds. In any case, the observed phenomenon illustrates the act of natural selection in determination of the protein fold repertoires and that the propagation of protein folds in a genome occurs in a competitive manner, It also remains to be seen whether some other properties of genomes and proteomes can also be described by the Weibull statistics. In our studies we plan to use the Weibull approach to examine other distributions such as genomic occurrence of transcriptional promoters and regulatory elements, levels of gene expression and occurrence of protein domains per gene, among others.etc in the CATH can be adequately described by the Weibull law. Thus, it has been previously demonstrated that another widely used folds library – SCOP does indeed obey the power low [Another possible development for the reliability analysis in structural genomics might be to investigate whether the standard libraries of proteins folds themselves can be adequately described by the Weibull function. As it has been stipulated, in the study we have used the CATH standard library of protein folds, which is one of the most accepted and used protein folds classifications. Ii is not unfeasible, that the representation of protein architectures, topologies, homologous superfamilies, ower low . Such obTo summarize the current work, it is possible to conclude that the use of the Weibull distribution allows more accurate description of protein topologies and domains distributions within and among genomes than power function used in conventional structural genomic studies. In addition, we were able to establish the Extreme Values relationships for protein folds distributions to demonstrate that the protein fold repertoire of an organism most likely occurs as a result of the competition amongst folds. This may reflect a mechanism of natural selection searching for an optimal protein structures when more evolutionary favorable folds tend to populate the entire genomic space and cause the extinction of lesser favorable protein configurations.Use of a Weibull function allows describing cumulative distribution of protein topologies and domains within individual genomes and superkingdoms with higher accuracy compared to the conventional power function used in the related studies. The developed approach may be applied to quantification of the distribution of different properties of genomes and can be particularly useful for assessing and comparing fold distributions between different organisms and possible impact of the "reliability" of organisms due to a higher redundancy in their fold composition.In general, the results of investigation demonstrate the feasibility and importance of using the reliability analysis to improve the bioinformatics analysis of proteomes.The prediction of the protein folds has been conducted using the THREADER2 program . The CATThe translated protein sequences for 33 complete genomes downloaded from the NCBI and ENSEMBL databases have been processed in this manner. The threading computations have been paralleled for processing on a Beowulf cluster consisting of 52 dual processor blades (2 × 1 GHz, 1 G RAM). The automated control was implemented by our own PVM-supporting Perl scripts enabling to distribute and query the individual threading processes over multiple computer servers.GO. At the next step these numbers have been converted into the fractional values. After that the survival distribution functions SDF(x) have been computed for genomes, superfamilies and for the combined set of proteins. The SDF(GO) numbers have been calculated for each integer GO value in the range from 0 to the maximal GO estimated within the set .After the occurrences of distinct classes, architectures, topologies and homologue family representatives have been established within the individual genomes, superkingdoms and in total, the corresponding survival distributions have been computed. First of all, we have established the counts of protein architectures, topologies and domains (homologues families) with a given genomic occurrence SDF(GO)~GO functions has been conducted by the SAS 9.0 statistical package (SAS Inc.). The power law dependences SDF(GO) = aGOb -have been analyzed as a logarithmic transformsThe fitting of the SDF(GO) = a - b*GOLog(where the fitting has been conducted for the linear function.SDF(GO) = exp(-aGOb) have been fitted using both non-linear approximation (by maximum likelihood method) and by the linear fitting of the double logarithmic transform:The Weibull – like dependences SDF(x)) = β log(x) - β log(α)log = a GOClick here for fileα, β and medians  of Weibull distribution of survival functions of genome occurrences  established by maximum likelihood and plotting methods.Parameters Click here for fileStatistical parameters for 'Weibull papers' for genomic occurrences of protein topologies and domains.Click here for file


Antiretroviral drugs change the lives of patients with HIV/AIDS—if they have access to them. Most patients in resource-poor countries cannot afford the drugs. Major initiatives are under way to expand access to antiretrovirals in developing countries, but the number of individuals in need of the drugs currently vastly exceeds the supply, and will continue to do so for the foreseeable future. These circumstances make for difficult decisions about treatment allocation. David Wilson and Sally Blower have shown how it is possible to design an equitable antiretroviral allocation strategy, that is, to come up with a plan that would give each individual with HIV an equal chance of receiving antiretrovirals. Their novel spatial model enables them to model the “spatial diffusion” of antiretrovirals in a resource-constrained country.Based on the premise that only a limited number of drugs will be available and only a limited number of health-care facilities can be used for drug distribution (each of them serving the population in a specific area), they determine an optimal equitable allocation strategy. They then apply this approach to a practical example—the equitable allocation of antiretrovirals to patients with HIV/AIDS in the South African province of KwaZulu–Natal. Using data from a detailed rollout plan for antiretrovirals designed by the South African government, they come up with an allocation strategy that differs substantially from the current governmental plan for the province.KwaZulu–Natal has a total of 54 health-care facilities, of which 17 are assigned to allocate antiretrovirals under the current plan. It is the largest province in South Africa, with a population of about 9.4 million, and it has more people with HIV than any other province . Wilson and Blower assume that the available amount of antiretrovirals can treat 10% of the individuals with HIV in KwaZulu–Natal. Modeling the 17 health-care facilities and the 51 communities of individuals with HIV, they determine the amount of drugs to allocate to each facility to achieve equitable access by patients throughout the province. They then extend the analysis assuming that additional health-care facilities could be made available to distribute drugs. They conclude that in order to achieve the greatest degree of treatment equality, all 54 health-care facilities should be used, and they should, on average, each serve the population within a radius of 50 km.Wilson and Blower discuss how their model can be adjusted and therefore used by policy makers in resource-constrained countries to determine a scientifically based allocation strategy for limited resources based on a number of specific objectives. They also recognize that there are other considerations that influence ethical treatment allocation besides equity, for example, the desire to maximize epidemic reduction, or the imperative to give priority to the least advantaged individuals They believe that their model can be adjusted and therefore “used by policy makers to determine an optimal scientifically based allocation strategy” for a number of specific objectives. Another possibility would be to apply the equity strategy to allocate drugs to particular health-care facilities , and then take additional ethical considerations into account at the community level.