DNA self-assembly methods have played a major role in enabling methods for acquiring genetic information without having to resort to sequencing, a relatively slow and costly procedure. However, even self-assembly processes tend to be very slow when they rely upon diffusion on a large scale. Miniaturisation and integration therefore hold the promise of greatly increasing this speed of operation.We have developed a rapid method for implementing the self-assembly of DNA within a microfluidic system by electrically extracting the DNA from an environment containing an uncharged denaturant. By controlling the parameters of the electrophoretic extraction and subsequent analysis of the DNA we are able to control when the hybridisation occurs as well as the degree of hybridisation. By avoiding off-chip processing or long thermal treatments we are able to perform this hybridisation rapidly and can perform hybridisation, sizing, heteroduplex analysis and single-stranded conformation analysis within a matter of minutes. The rapidity of this analysis allows the sampling of transient effects that may improve the sensitivity of mutation detection.We believe that this method will aid the integration of self-assembly methods upon microfluidic chips. The speed of this analysis also appears to provide information upon the dynamics of the self-assembly process. There has been a rapid growth in the number of applications that are based upon DNA self-assembly, ranging from DNA microarrays (e.g. Affymetrix ) in the Microfluidic devices or 'microchips' are photolithographically-defined networks of microchannels in glass where the microchannels are similar in size to conventional capillaries. These microchips provide compelling advantages in terms of speed, reagent usage and integration over conventional capillary or gel-based methods. The potential of the microfluidic chip has led to the use of terms such as "micro-total analysis systems" and "lab-on-a-chip". These microchips have been demonstrated in conjunction with a range of applications that integrate the polymerase chain reaction (PCR) and capillary electrophoresis (CE) methods with some reaching nanolitre or smaller scale volumes. A powerful advantage of the microchip approach is that it can implement much the same molecular biology protocols and reagents as used with conventional equipment, thereby allowing a wealth of established expertise to be transferred to the microscale.Although the most effective method of mutation detection is sequencing, it is also by far the most expensive . The micMicrofluidic chips may enable extremely high throughputs and high levels of integration. The achievement of this goal has been hindered by the lack of successful integrations of methods of mutation analysis based on single-stranded DNA (ssDNA) and double-stranded DNA (dsDNA) – likely due to the difficulties in controlling the degree of hybridisation on chip without time consuming thermal processing. A great advantage would be provided by a method of enabling microchip-based control of a rapid DNA self-assembly process.The term wildtype is used to describe any given genetic sequence that does not contain mutations. Since individuals usually carry two copies of each gene, the genetic sequence of the two copies may be identical (homozygous) or may differ (heterozygous). DNA is normally double stranded, but under some conditions (e.g. high temperature), melts into single strands. Under other conditions, such as a lower temperature, these single strands will self-assemble into the double-stranded form again. The resulting double-stranded DNA is referred to as a homoduplex if the sequences are perfectly complementary, or a heteroduplex if the sequences are nearly complementary (i.e. a mutant sequence paired with a wildtype sequence). The misfit in a heteroduplex creates a "bulge" or "bubble" where the bases do not match and this affects the shape of the assembled molecule, typically lowering its velocity during electrophoretic movement, i.e. the heteroduplexes typically migrate more slowly than the homoduplexes. Any heterozygous sample will generate four different duplexes, two homoduplexes and two heteroduplexes, although the molecules often co-migrate so that fewer than 4 separate electropherogram peaks are resolved.In the HA method, electrophoretic conditions are chosen in order to enhance the velocity differences between the duplexes so that the process of duplex self-assembly can be used to determine the presence of a heterozygous state (hence indicating the presence of a mutation). In SSCP, isolated strands of ssDNA find near-complementary sequences on the same strand, with the result that the strand folds upon itself in a sequence dependent manner forming new conformations. This is a simplistic description since ssDNA without self-similar sequences, and homoduplex dsDNA, may also take complex forms. Techniques such as HA that aim to separate homoduplex fragments from heteroduplex fragments often use some combination of thermally and chemically denaturing conditions to cause the partial melting of the duplex, resulting in a shift in mobility or chromatography column retention time that increases with the degree of mismatch.et al. [et al. achieved 100 % sensitivity by analysing denatured and non-denatured fragments in tandem. Despite being highly effective, the additional sample preparation required by these methods (i.e. separately preparing both single and double stranded DNA and maintaining this strandedness) complicates their implementation on microchips.Many medical diagnostics could be implemented on microchips if an effective implementation of a highly sensitive mutation analysis method could be integrated with PCR/CE. Considerable work has been done in developing SSCP  and HA ,3,12. Anet al.  greatly In this work, we present an electrophoretic method in which DNA is denatured in a microchip (with formamide) and, depending upon the sequence of applied voltages, can be prepared with a widely varying degree of hybridisation . Given the small volumes involved within the microchip, diffusion time plays a small role and the reassembly process can be fast, with dsDNA obtained within minutes. The rapidity of the manipulation possible on this system allows some investigation of the dynamics of the reassembly, indicating that there are well-defined intermediate states where both ssDNA and dsDNA exist in the reassembly process.We have applied our methods to the H63D and S65C mutations from the HFE gene associated with hereditary hemochromatosis (HH). The denaturation technique used enables a combined microchip-based method of HA and SSCP analysis.In our electrophoretic analyses with a double-T chip (described below), the dsDNA arrives at the detection point before the ssDNA . As shown in Fig. As expected, after the addition of formamide the electropherograms showed the presence of ssDNA peaks in addition to the dsDNA peaks Fig. . The dsDIn order to confirm that we are reassembling DNA on chip rather than denaturing to varying degrees we investigated the on-chip production of heteroduplexes from two samples of homoduplexes (i.e. homozygous) samples. Fig. The reassembly of ssDNA can also be shown by denaturating the wildtype and homozygous mutant in separate wells. The two denatured samples were injected simultaneously and their ssDNA mixed in the injection channel of a Y-chip (described below). Subsequent separation and detection showed peak profiles Fig.  similar As will be described in the following section, by varying the electrophoretic parameters we can control the relative amount of dsDNA formed – a significantly larger amount could be obtained.After demonstrating that reassembly occurred within the microchannels after extraction from the formamide-rich sample well, it was of interest to investigate how the sequence and timing of the sample extraction and analysis might affect the degree of rehybridisation. In the work presented thus far we used a 60 s injection  as a means of drawing sample directly from the sample well to the intersection, from whence it could be analysed.After the addition of formamide and an analysis of the resulting sample (60 s injection and 180 s separation), a series of analyses were performed wherein each short injection (10 s) with a lower electric field was followed by a 180 s separation. These short injections sampled DNA that had remained in the microchannel since its extraction during the 60 s injection from the first analysis. The time required for the DNA to travel from the sample well to the intersection with the applied electric field during the 10 s short injections was calculated to be approximately 53 s.  Thus, the two short injections of 10 s each were not enough to bring in fresh samples from the sample well. Fig. Another interesting feature of Fig. et al. [et al. [The integration onto a microchip of an effective means of mutation detection is perhaps one of the most important technological barriers to the implementation of microchip-based medical diagnostics. The best means of attaining sufficiently high sensitivity is by integrating several existing methods of microchip-based mutation detection. The capillary-based analysis procedure developed by Kourkine et al.  is likel [et al.  – througAs demonstrated here, this method also allows on-chip comparisons of one type of DNA with another. A common problem encountered with HA methods is that they cannot distinguish homozygous mutant from homozygous wildtype – the present technique would allow an on-chip comparison of these samples to produce heteroduplexes that will then indicate the mutational status.The on chip denaturation is produced through the addition of formamide. The melting temperature for this sequence of DNA following the addition of formamide was found to be approximately room temperature, as determined bym = 81.5 + 16.6(log M) + 0.41 (% G + C) - 0.72 (% formamide)     (1)Tm is the melting temperature in degrees Celsius, M is the monovalent salt molarity, (% G + C) is the percent of the guanine and cytosine in the DNA strand of interest, and (% formamide) is the percentage of formamide added [where Tde added . The melThe ability to quickly re-hybridise on chip allows for rapid investigation of self-assembly mechanisms. In addition, this re-hybridisation enables the formation of duplexes made from a sample and a set of DNA references – i.e. DNA self-assembly within a microchip could be used to form duplexes that, under electrophoretic analysis, would show the results of comparing the sample DNA with each type of DNA in the reference set. This could avoid the need for DNA sequencing.The rapidity of our method appears to provide additional information upon short-lived conformations. Although we have added a thermal re-annealing step as part of our PCR protocol, that step does not affect the results of analysis after adding formamide – i.e. by re-annealing on-chip the thermal reannealing is not needed. The thermal re-annealing stage was added to allow the direct comparison of heterozygous samples from the PCR with heterozygous samples after on-chip reassembly. After adding formamide, the electropherogram of the first separation analysis following any long injection shows a clearly defined transient peak. For H63D samples the transient peak is a single peak, whereas for S65C the transient peak is clefted. We have found that the transient peaks vary in size significantly depending upon the electrophoretic and PCR protocols used. Initially we had assumed that this transient peak indicated that the reassembly of the DNA was not 'random' but instead hybridised first in a high-melting point region, and only slowly thereafter. In this model, the presence of the split-peak would provide information upon the location of the mutation. This suggests that mutation S65C is within the higher melting point domain, while the H63D is not. However, as determined by the Meltmap program (generously provided by L. Lerman (MIT)), neither the H63D nor S65C mutations were within the high melting point region of the exon (data not shown).et al. [et al. [Several research groups have reported artefacts that arise from ssDNA-primer interactions ,17-19. Ket al. ,18 reporWe therefore suggest that the transient peak is due to the pairing of one product strand with one primer as a result of the renaturation process. The primer-ssDNA complex is primarily ssDNA with a small region of dsDNA at the end(s) of the strand. It is therefore expected to migrate with similar mobility as the ssDNA peaks. The disappearance of the transient peaks with the subsequent short injections may be a result of the complementary single strand binding and displacing the primer. However, the presence of the transient peaks may still provide useful information. The differences in the transient peaks (cleft versus no cleft) between S65C and H63D suggest that their shape may be dependent on the position of the mutation and that the position greatly affects the transport of the transient form of DNA. Thus, the phenomenon of the transient may be a general behaviour that could provide additional mutational information. In corroboration of past work by others ,19, it tWe have developed a method of rapidly disassembling and re-assembling DNA within a microfluidic chip, allowing us control over the relative amount of ss and dsDNA and enabling the performance of rapid hybridisations under electrophoretic control. It has been reported that, when combined, HA and SSCP can provide sensitivities of 100% (e.g. ). In ourThe present work is also an early step towards directing and studying DNA self-assembly within microfluidic systems. The method applied here could be improved significantly by shortening the injection and separation channels and ultimately may even assist in providing the control needed to direct the assembly of DNA-based nanosystems within microfluidic channels.Volunteers who had given informed consent donated lymphocytes from which DNA was extracted and purified by using phenol-chloroform-isoamyl alcohol extractions  or the Q2, 2.5 μL of 10× PCR reaction buffer and 0.5 μL of Platinum Taq DNA Polymerase. All samples were re-annealed following PCR by first heating at 95°C for 3 min, followed by a subsequent ramping down of temperature by 1°C per minute until 65°C. The samples were then stored at -20°C.The two mutations tested were H63D and S65C, from HFE Exon 2. PCR was performed on 25 μL reactions of both mutations. Thermal cycling was performed on all the samples as follows: 94 C for 2 min, 35 cycles of , and finally 72°C for 10 min, 4°C thereafter. For H63D and S65C, the PCRs are performed with 5 μL of 30 ng/μL of genomic template DNA, 2 μL of 5 μmol/L each of HEX-HFE-2F primer and H63DR primer  were obtained from Invitrogen . GeneScan™ polymer was used for microchip electrophoresis and obtained from PE Applied Biosystems . A polymer consisting of 5% GeneScan polymer and 10% glycerol (5GS10G), commonly used for SSCP, was made. Tris borate  with EDTA  was used as the running buffer in concentrations of 1× and 0.1×. Glycerol  is also added to each in 10% and 1% concentrations respectively (1 × TBE10G and 0.1 × TBE1G). De-ionised formamide (minimum 99.5%) was obtained from Sigma . The formamide was aliquotted and kept frozen until required.The microchips were purchased from Micralyne  and unless otherwise mentioned were a 4 port double T design Fig.  consistiThe microchip was loaded with 5GS10G polymer without any pre-treatment. The sample well was loaded with 2.6 μL of 0.1 × TBE1G followed by 0.4 μL of DNA sample and mixed. The remaining wells were loaded with 3 μL of 1 × TBE10G. In the case of the Y-chip, 0.4 μL of wildtype DNA was added to 2.6 μL of 0.1 × TBE1G in the first sample well and mixed. The second sample well was filled with 2.6 μL of 0.1 × TBE1G and 0.4 μL of homozygous mutant. The operation of the μTK (injection and separation) was automated through the use of the LabVIEW interface. LIF detection took place 76 mm downstream from the intersection. We have found that the reproducibility of the peak arrival times is within 2 per cent from one run to the next. As such we have not needed to introduce size standards.The sample DNA was brought from the sample well to the intersection and onto the sample waste well by applying 500 V/cm for 60 s. No initial injection was done with the Y-chip prior to denaturation. During this process the buffer and buffer waste well are left electrically disconnected. In doing so the intersection of the two (three) channels is filled with the sample DNA. This stage is referred to as an injection due to the injection of DNA into the separation channel in the sharply defined volume of the intersection of the channels.Immediately following injection, the DNA caught within the intersection is separated by applying 714 V/cm for 180 s between the buffer and buffer waste wells. During this step, the sample and sample waste wells are left electrically disconnected. The effective separation distance was 76 mm from the intersection.et al. [After the initial run on the 4-port chip, 1.5 μL of the sample mixture was removed and 1.5 μL of formamide was added and mixed. Following Howley et al. , this isYZ performed the experimental work with some assistance from TF. DM performed additional protocol development. CB provided overall direction. All authors contributed to the writing of the manuscript and all made substantial contributions to the work.


A new funding body (the EDCTP) will fund clinical trials in developing countries, particularly in Africa, that help to develop affordable interventions against HIV, TB, and malaria. How is it doing so far? A promising European funding body is stumbling over the details Last year the European Parliament and Council formed the european and Developing Countries Clinical Trials Partnership (EDCTP). The aim of this new funding body, which has a budget of €400 million spread over five years, is a noble one: to fund research in developing countries, particularly in Africa, that contributes to the development of affordable prophylactics and drugs for HIV/AIDS, tuberculosis, and malaria.Unfortunately, the organization has not got off to an auspicious start. Its executive director, Piero Olliaro, was ousted from power at the first EDCTP annual forum at the end of September. There have been rumblings of discontent among grant applicants who say that the first round of grant assessments was administered poorly. And not-for-profit organizations that would like to partner with EDCTP have been left in the dark regarding whom to speak to at the organization.This omission is significant because partnership is one of the key tenets of the EDCTP. European research agencies are slowly beginning to realize that they need to cooperate with each other if they are to be competitive with the United States. The history of many European countries is such that Europe has much stronger ties with Africa than does the United States, so it makes political sense for the European Union to fund research that provides a springboard for European researchers to compete effectively with US scientists.Crucially, the EDCTP was also set up to enable European and African scientists to work together as equal partners. There is increasing recognition that the paternalistic, colonial attitude that pervaded “tropical medicine” in the past just will not do. The EDCTP hoped to change that by having a Partnership Board that contains equal numbers of African and European representatives. However, the EDCTP Assembly, which contains a representative from each of 14 EU member states but none from African countries, has the power to veto the decisions of the Partnership Board, which is supposedly the scientific decision-making authority.Doing clinical trials in Africa is far from easy. There are too few adequately resourced research centers, and those that do consistently perform well are oversubscribed. Therefore, there is a clear need for "capacity building"—development of a research infrastructure, in terms of both equipment and personnel, that is capable of coping with the challenges of clinical trials. The EDCTP hopes to contribute to this essential endeavor by funding clinical trials that are sustainable in the long term. In particular, it believes that the best way to train a new generation of African scientists is by teaching them on the job, that is, involving them fully in the planning and execution of the trial, rather than flying in European experts who leave as soon as the trial is finished.A commitment from European researchers to be engaged for the long term is essential for the success of these projects. In addition, partnerships need to be brokered with national programs in Africa to ensure that the new capacity can be sustained over time. The end goal is to produce centers of excellence that are run by Africans doing internationally recognized research that conforms to Good Clinical Practice guidelines. But this will only happen if African researchers are treated as equal partners and are allowed to be fully engaged in the projects that are taking place in their countries.So can the EDCTP work, or is it doomed to failure? In many ways the organization has a great deal going for it. Although the budget of 3400 million spread over five years is tiny considering the combined burden of HIV/AIDS, tuberculosis, and malaria, it is important to remember that it is the biggest single European project for clinical trials in Africa. In many ways the EDCTP is a demonstration project: if some success can be achieved it is very likely that additional funds will follow. The project is certainly strengthened by the involvement of Pascoal Mocumbi, the former prime minister of Mozambique, as High Representative of the project. Mocumbi is highly respected by the global-health community and carries considerable weight with African politicians. Mobilization of political will within Africa will be essential if research capacity is to be sustained for the long term.On the downside, it seems clear to most insiders that the management structure needs to be radically changed and partnership with other organizations needs to be improved. The EDCTP Assembly met on October 28 and 29 to discuss these issues and to elect a new leader. At the time this editorial went to press, there was still no public announcement of the outcome of this meeting. In addition, the political infighting that pervades European politics at all levels needs to be controlled, or at least managed effectively. This might be a tall order, but it is essential if this worthwhile and high-profile project is to succeed.


The neurophysiological and neuroanatomical foundations of persistent developmental stuttering (PDS) are still a matter of dispute. A main argument is that stutterers show atypical anatomical asymmetries of speech-relevant brain areas, which possibly affect speech fluency. The major aim of this study was to determine whether adults with PDS have anomalous anatomy in cortical speech-language areas.Adults with PDS (n = 10) and controls (n = 10) matched for age, sex, hand preference, and education were studied using high-resolution MRI scans. Using a new variant of the voxel-based morphometry technique (augmented VBM) the brains of stutterers and non-stutterers were compared with respect to white matter (WM) and grey matter (GM) differences.We found increased WM volumes in a right-hemispheric network comprising the superior temporal gyrus , the inferior frontal gyrus (including the pars triangularis), the precentral gyrus in the vicinity of the face and mouth representation, and the anterior middle frontal gyrus. In addition, we detected a leftward WM asymmetry in the auditory cortex in non-stutterers, while stutterers showed symmetric WM volumes.These results provide strong evidence that adults with PDS have anomalous anatomy not only in perisylvian speech and language areas but also in prefrontal and sensorimotor areas. Whether this atypical asymmetry of WM is the cause or the consequence of stuttering is still an unanswered question. Persistent developmental stuttering (PDS) is a relatively severe disturbance characterized by involuntary, audible or silent, repetitions or prolongations of sounds or syllables. These are not readily controllable and often are accompanied by other movements and by negative emotions ,2. DevelSeveral experimental studies have shown that stutterers reveal prolonged manual and vocal reaction times to simple and complex verbal and nonverbal stimuli -10, reduAccording to the present literature four anatomical studies revealed brain abnormalities in stutterers compared to controls. The earliest study examined two left-handed stuttering siblings using CT and revealed an atypical (reduced) anatomical asymmetry of the occipital poles . The firAlthough the aforementioned anatomical studies have focussed on the anatomical foundations of stuttering, several questions are not answered yet. Therefore we re-examined the hypothesis of anatomical differences between stutterers and non-stutterers using voxel-based morphometry (VBM). This approach circumvents the problem of analyzing predetermined regions of interests by analyzing stereotactically normalized brains on a voxel-by-voxels basis with respect to differences in the volume of white matter (WM) or grey matter (GM) ,38. ThisThe sample included adults with PDS (n = 10) and controls (n = 10) matched according to sex, age and education. All subjects were consistent right-handers (CRH) according to the Annett handedness questionnaire (AHQ) [66]. Our sample contained the approximate sex distribution as those reported in population studies of adults who stutter; thus, there were more men (n = 8) than women (n = 2) in this sample. The dysfluent sample was limited to adults with PDS who had been diagnosed with developmental stuttering before the age of 8 years and had undergone treatment at some point, but continued to be dysfluent. None of the subjects was taking centrally acting medications that could have resulted in PDS, and all met the clinical criteria of developmental stuttering – not acquired stuttering. Of the adults who stuttered, 50% had a family history of stuttering; none of the controls had a family history of stuttering. Stuttering severity was determined using the Stuttering Severity Inventory (SSI) [67] with individuals in the sample ranging from mild (2), moderate (7) to severe (1). All participants were native German speakers with no reported history of dyslexia, specific language impairment, attention deficit disorder, traumatic brain injury, substance abuse, or other neuropsychiatric conditions. All participants gave informed consent before participating.) [71]. Preprocessing were guided by the VBM method proposed by Godd et al. . Data were analyzed on a PC workstation using MATLAB 5.3  and SPM 99 .The normalized, smoothed, segmented (and modulated) data were analyzed using statistical parametric mapping (SPM99) employing the framework of the General Linear Model. Regionally specific differences in GM (and WM)  between groups were assessed statistically using a two-tailed contrast. Corrections for the search volume (and implicit multiple comparisons) in terms of the P values were made using Gaussian random field theory, which accommodates spatial correlations inherent in the data and is now established as the conventional approach to inference in smooth spatially extended data. We restricted the search volume to the GM or WM volume enabling us to increase the statistical power of statistical testing. Significance levels for two-sided T statistics were set at T = 5 (corrected for multiple comparisons across the WM or GM volumes) and a spatial extend criterion of k = 50. The spatial extend of k = 50 was introduced because this volume size roughly corresponds to the size of a meaningful anatomical area  including the planum temporale, the precentral gyrus (PrCG), the inferior frontal gyrus (IFG) comprising the pars opercularis (POP), and the middle frontal gyrus (MFD) Table . There w3). The placement pf these ROIs were guided by anatomical landmarks and published probability atlases of the HG and PT [2 = 0.62) and a significant interaction between both factors  = 31.6, p <= 0.001, ETA2 = 0.64). Subsequent Scheffé contrasts and Figure 2 = 0.34; Group: F = 23.6, p <= 0.001, ETA2 = 0.58) and a significant interaction  = 23.9, p <= 0.001, ETA2 = 0.57). The strong interaction is qualified by a between-hemisphere difference found for stutterers (with larger WM volumes on the right compared to the left IFG) while there is no between-hemisphere difference in non-stutterers. For the PrCG we found a significant between-group difference  = 11.1, p = 0.004, ETA2 = 0.38) and a significant interaction  = 31.0, p <= 0.001, ETA2 = 0.64). The pattern of this interaction resembles the interaction found for the IFG with larger WM volumes on the right hemisphere for stutterers than on the left while non-stutterers show similar values for both hemispheres. For the MFG all two main effects as well as the interaction were strongly significant  = 23.5, p <= 0.001, ETA2 = 0.56; Group:  = 13.2, p = 0.002, ETA2 = 0.42; interaction:  = 18.4, p <= 0.001, ETA2 = 0.50). The interaction is due to the fact that stutterers revealed larger WM volumes on the right compared to the left hemisphere.In order to understand the differences between stutterers and non-stutterers with respect to the WM volumes in these anatomical areas more precisely, we placed regions of interest (ROI) in these anatomical areas and the homotopic areas on the left hemisphere. For the auditory cortex we used a rectangular ROI including Heschl's gyrus (HG) and the planum temporale (PT)  and the anatomical peculiarities neither in the context of the VBM nor the ROI analysis.This study was motivated by the question whether stutterers reveal morphological brain anomalies compared to non-stuttering controls. In fact, we found prominent increases of WM in stutterers within a right-hemispheric network including brain structures relevant for language and speech. These areas comprise the STG (including the auditory areas PT and HG), the IFG (including the pars opercularis which is part of Broca's right-sided homologue), the somatosensory area , and the middle frontal gyrus (MFG). Our findings of regionally increased right-hemispheric WM in stutterers might suggest an increased and possibly atypical intrahemispheric communication within these areas via association fibres ,51 possiThree of the brain areas with different WM composition in stutterers are known to be involved in different speech and language functions. For example, the right IFG (including the pars opercularis) is involved in the perception and generation of phonological or prosodic speech features -55 whileThe auditory cortices in the two hemispheres are relatively specialized in normal subjects ,57. ThusThe reported morphological features complement previous morphological studies comparing stutterers and non-stutterers. Firstly, this study shows again that stutterers reveal atypical anatomical lateralisation in speech-relevant areas. In three areas  stutterers reveal more WM volumes on the right than on the left. For the auditory cortex (STG) we found symmetric WM volumes while non-stutterers typically show a leftward asymmetry for this measure. Thus, some kind of hemispheric imbalance seems to be related to persistent developing stuttering. Secondly, using a different method than Foundas et al. , we alsoThese results provide strong evidence that adults with PDS have anomalous anatomy not only in perisylvian speech and language areas but also in prefrontal and sensorimotor areas. These anatomical features might indicate a deficiently working speech system. Whether this atypical asymmetry of WM is the cause or the consequence of stuttering is still an unanswered question.The author(s) declare that they have no competing interests.L.J., J.H. and H.S. conceived the experiment and drafted the manuscript. L.J. and J.H. prepared the exact experimental setup. H.S. supervised data acquisition. J.H. and L.J. performed all data and statistical analyses. All authors read and approved the final manuscript.The pre-publication history for this paper can be accessed here:


Alu elements are short (~300 bp) interspersed elements that amplify in primate genomes through a process termed retroposition. The expansion of these elements has had a significant impact on the structure and function of primate genomes. Approximately 10 % of the mass of the human genome is comprised of Alu elements, making them the most abundant short interspersed element (SINE) in our genome. The majority of Alu amplification occurred early in primate evolution, and the current rate of Alu retroposition is at least 100 fold slower than the peak of amplification that occurred 30–50 million years ago. Alu elements are therefore a rich source of inter- and intra-species primate genomic variation.Alu elements from the Ye subfamily were extracted from the draft sequence of the human genome. Analysis of these elements resulted in the discovery of two new Alu subfamilies, Ye4 and Ye6, complementing the previously described Ye5 subfamily. DNA sequence analysis of each of the Alu Ye subfamilies yielded average age estimates of ~14, ~13 and ~9.5 million years old for the Alu Ye4, Ye5 and Ye6 subfamilies, respectively. In addition, 120 Alu Ye4, Ye5 and Ye6 loci were screened using polymerase chain reaction (PCR) assays to determine their phylogenetic origin and levels of human genomic diversity.A total of 153 Alu Ye lineage appears to have started amplifying relatively early in primate evolution and continued propagating at a low level as many of its members are found in a variety of hominoid  genomes. Detailed sequence analysis of several Alu pre-integration sites indicated that multiple types of events had occurred, including gene conversions, near-parallel independent insertions of different Alu elements and Alu-mediated genomic deletions. A potential hotspot for Alu insertion in the Fer1L3 gene on chromosome 10 was also identified.The  Alu elements has had a significant impact on the architecture of primate genomes [Alu elements have achieved this copy number by duplicating via an RNA intermediate in a process termed retroposition [Alu elements are thought to borrow the factors that are required for their amplification from the LINE (long interspersed element) elements [Alu repeats have been a significant source of new mutations as a result of insertion and post-integration recombination between elements [The proliferation of  genomes . They co genomes . Alu eleposition . During position -6. Whileelements , which eelements ,11. Becaelements ,13.Alu amplification occurred early in primate evolution, and the current rate of Alu retroposition is at least 100 fold slower than the peak of amplification that appears to have occurred 30–50 million years ago [Alu elements within the human genome, only a small number of these elements are capable of movement [Alu elements, a series of discrete subfamilies of Alu elements that share common diagnostic mutations have been identified in the human genome [Alu repeats are so recent in origin that they are present in the human genome and absent from the genomes of non-human primates, with some of the elements being polymorphic with respect to insertion presence/absence in diverse human genomes [Alu subfamilies which arose around the radiation of Subtribe Hominina  four to six million years ago [Alu elements as phylogenetic markers [The majority of ears ago ,14-16. Emovement . As a ren genome -21. A sm genomes -25. Indi genomes -34. For ears ago  were useears ago . Relatio markers ,37-40Alu elements found in the human genome that fall in six distinct lineages, termed Ya, Yb and Yc, Yd, Yg and Yi based upon their diagnostic mutations [Alu subfamilies that are members of the Alu Ye lineage [We have previously characterized a large number of recently integrated utations -52. Here lineage  and are Alu Ye elements were identified in the draft sequence of the human genome using BLAST [Alu Ye specific oligonucleotide . Seventeen of the 25 Alu Ye4 elements were unique . There were also 76 unique Ye5 Alu elements and 23 unique Ye6 Alu subfamily members. Multiple alignments of the Alu elements from each subfamily were constructed and the number of mutations from the consensus sequence for each Alu subfamily was determined. In each case the mutations were divided into those that occur at CpG dinucleotides and those that occur at non-CpG positions without including small insertions or deletions as described previously [To estimate the copy number of the Ye4, Ye5 and Ye6 eviously -49. The eviously  as a reseviously .Alu Ye subfamily. For 17 elements from the Alu Ye4 subfamily, the non-CpG and CpG mutation densities were 2.1% (83/3944) and 12.5 % (106/850). Using a neutral rate of evolution of 0.15% per million years for non-CpG positions [Alu Ye5 subfamily 76 elements were analyzed that contained a total of 17632 non-CpG nucleotides and 3800 CpG nucleotides that contained 351 non-CpG and 431 CpG mutations. The mutation densities of the Ye5 subfamily were 1.99% and 11.34% for the non-CpG and CpG nucleotides yielding age estimates based on the average mutation density of 13.27 and 12.60 million years old. For the Alu Ye6 subfamily 23 elements were analyzed that contained a total of 5336 non-CpG nucleotides and 1150 CpG nucleotides that contained 86 non-CpG and 92 CpG mutations. The mutation densities of the Ye6 subfamily were 1.61% and 8% for the non-CpG and CpG nucleotides yielding age estimates based on the average mutation density of 10.75 and 8.89 million years old.Mutation densities were calculated for each ositions  and 0.9%ositions  along wiAlu Ye4, Ye5 and Ye6 subfamily member, we performed a series of PCR reactions using human and non-human primate DNA samples as templates. Unfortunately, not all of the loci identified in the draft sequence were amenable to PCR analysis, as some of them had inserted into other repetitive regions of the genome making the design of flanking unique sequence PCR primers difficult.In order to determine the approximate time of insertion for each Alu repeats beginning with some elements that are recent in origin and unique to the human genome (e.g. Ye5AH110) and ending with elements that are found within all ape genomes (e.g. Ye5AH148). The distribution of all the Ye elements in various primate genomes is summarized in Additional File 2.For the Ye subfamilies, 120 of the 153 elements identified in the draft human genomic sequence were amplified by PCR. Examination of the orthologous regions of the various species genomes displayed a series of different PCR patterns indicative of the time of retroposition of each of the elements into the primate genomes. Results from a series of these experiments showed a gradient of Ye Alu elements and in other regions of the human genome exerts a significant influence on the accumulation of single nucleotide diversity within the human genome [Alu Ye subfamily members, we compared the sequences of the elements found in the human genome to the consensus sequences of other Alu subfamilies. Using this approach, we identified two Alu Ye5 subfamily members that appeared to have been subjected to partial gene conversion at their 3' ends. Alu Ye5AH70 contains three mutations that are diagnostic for the Yb8/9 subfamily. Similarly, Alu Ye5AH173 contains three Alu Sc mutations. Each of the sequence exchanges occurred in a short contiguous sequence suggesting that they were products of gene conversion rather than homoplasic point mutations.Gene conversion between n genome ,50. To eAlu-containing locus that was involved in full gene conversion/ replacement event, (Ye5AH181). In this case, the orthologous Alu elements have similar flanking sequences and direct repeats, although they are not precisely identical due to the random mutations that accumulated over time. DNA sequence analysis of this locus showed that the Alu element of selected new world monkey genomes  belonged to the Alu Sg subfamily. This suggests that a gene conversion of an older, pre-existing Alu Sg may have introduced the Ye5 sequence in the common ancestor of humans, chimpanzees, gorillas and orangutans. Amplification of this locus was unsuccessful in the old world monkey taxa tested.We identified one Alu Ye elements. These deletions were identified at loci Ye5AH24 and Ye5AH27. In the case of Ye5AH24, the deletion was associated with a gene conversion of an Alu Y in both orangutan and siamang to AluYe5 in human, bonobo, common chimpanzee and gorilla and involved the removal of about 500 bp from the 3' flanking region. For Alu Ye5AH27, the deletion was associated with a gene conversion of an Alu Sx element (orangutan and siamang) to AluYe5  and involved the removal of 142 bp from the 3' flanking region. Based on this data, we estimate the frequency of Alu retroposition mediated deletions of approximately 1.67% (2/120).Two deletions of part of the human genome appeared to be associated with newly inserted Alu integration. If a deletion occurred during the integration of an Alu element in the human genome, then the pre-integration product size calculated computationally would be an underestimate of the true size of the locus. To investigate this possibility, we utilized long template PCR reactions of these loci that would facilitate the amplification of larger (up to 25 kb) products. Unfortunately, PCR amplicons were not generated by any of these loci, suggesting that the retrotransposition of these Alu elements in humans may have generated deletions greater than 25 kb in size. Alternately, the orthologous loci in non-human primate genomes may have undergone additional mutations at the oligonucleotide primer sites, preventing PCR amplification.The pre-integration sites for three elements  did not amplify in any non-human primate species. Previously, the insertion of L1 elements has been shown to be associated with large genomic deletions . Thus, oAlu insertions in human, chimpanzee, gorilla lineage, old world monkey and new world monkey lineages , an Alu Sp has inserted in the 5' flank of the shared Sx element about 58 bp away of the Alu Ye5 present in Hominina. Also, in the woolly and spider monkeys (new world monkeys), there was an independent insertion of an Alu Sx in the 5' flank of the shared Alu Sx. In gibbon, siamang and orangutan, there were no independent Alu insertions at this locus, only the common Alu Sx is present. In orangutan, however, there was an extra 145 bp of genomic sequences inserted inside the old Alu Sx. The pattern discussed suggests that these three independent parallel insertion events occurred sometime after the divergence of these primates from one another. This locus on chromosome 10q23.33 lies in intron 39–40 of the Human Fer1L3 gene, about 50 bp from exon 39. This locus may be considered a hot spot for Alu insertion. An alignment of locus Ye5AH161 is available as .We have also identified one locus (Ye5AH161) that contained multiple paralogous ges Fig. . In the Alu insertion event at human Ye5AH16 locus in all the old world monkey genomes tested , within the same locus where an Alu Ye5 element was located in the human, chimpanzee, gorilla and orangutan genomes. Thus, the near-parallel insertion most likely occurred after the divergence of humans and apes from old world monkeys, but before the radiation of the old world monkeys. The element present in the old world monkey genomes is an Alu Y and is 80 bp from the human insertion site.We also identified another near-parallel independent Alu Ye4, Ye5 and Ye6 subfamily members, we performed a series of PCR reactions on a collection of 80 geographically-diverse human genomes. Using this approach, we identified one new Alu insertion polymorphism (Ye5AH167) from the loci analyzed in this report. The allele frequencies, genotypes and heterozygosities for the Alu insertion polymorphism are shown in Table To determine the human genomic diversity associated with each of the ism Ye5AH67 from tAlu Ye5 subfamily resulted in the recovery of two new Alu subfamilies, Ye4 and Ye6. Each of these Alu subfamilies has a relatively small copy number in the human genome. The proportion of polymorphic elements within each of the subfamilies is quite low with only 0.83% of the Alu Ye elements being polymorphic, only one member of Ye subfamilies (Ye5AD167) is polymorphic with respect to insertion presence/absence in the human genome. In contrast, many other young Alu subfamilies have levels of insertion polymorphism in excess of 20% [Alu subfamilies within the human genome has occurred at a very low rate, and may have recently ceased entirely. The estimated average ages of ~14, ~13 and ~9.5 million years old for the Alu Ye4, Ye5 and Ye6 subfamilies, respectively are consistent with their relatively recent origin in primate genomes. It is also consistent with the master gene model of SINE retroposition which suggests that as a master element accumulates mutations over time, the resulting elements will share those mutations [Our detailed analysis of the utations .Alu Ye lineages are dispersed throughout the genomes of all hominoids  suggesting that this subfamily of Alu elements began to amplify about 15–20 million years ago. Therefore, the Ye subfamily appears to have been retroposition competent during hominoid evolution, but must have been relatively inefficient at producing copies. Although the rate of Ye amplification has not been dramatic within the human lineage, it may be quite interesting to recover Alu Ye subfamily members from other ape genomes and to determine the rate of Ye subfamily amplification in these genomes to see if there has been any differential amplification of these elements in non-human primate genomes. The differential amplification of ID SINEs within various members of the rodent lineage has been reported previously suggesting that the amplification of SINEs within various genomes is subject to changes [Members of the  changes ,62.Alu repeats has been reported previously [Alu Ye subfamily members were quite interesting. In one case (Ye5AH181), the Alu-containing locus was involved in full gene conversion event where Alu Sg in new world monkeys is replaced by an Alu Ye5 in Humans, chimpanzees, gorillas and orangutan. In the other two cases (Ye5AH70 and Ye5AH173), only a small portion of the 3' end of the Ye elements were involved in the gene conversion. This is in good agreement with the molecular nature of gene conversion events recently reported for the Ya5 and Yb8/9 Alu subfamilies [Alu Ye elements suggests that gene conversion of these events has been relatively rare, with a rate of 1.96%. However, this rate is comparable to that reported previously for the Alu Ya5 and Yb8 subfamilies within the human genome, as well as that for the Ta subfamily of human LINE elements [Gene conversion between eviously ,63,64. Tfamilies ,48,64,65elements .Alu family members that were involved in the gene conversion were monomorphic for insertion presence within the human genome. In the partial gene conversion events, the Ye Alu repeats were gene converted by Yb8/9 and Sx Alu elements. The Yb8/9 Alu subfamily was one of the first groups of Alu repeats that was ever reported to be involved in gene conversion, and may be more prone to these types of events as a result of a retroposition rate that is slightly higher than other recently integrated Alu subfamilies in the human genome [Alu elements may in part be a function of the length of time that the individual Alu elements have resided in the human genome [Alu elements allows for pairing between regions of sequence identity of different Alu elements initiating the start of gene conversion before cellular control systems can terminate the process resulting in the production of small gene conversion tracts.In all cases, the Ye n genome ,64,65. Tn genome ,50. Basen genome . It is qAlu insertions involving an Alu Ye element (Ye5AH161) in humans, bonobo, common chimpanzee and gorilla lineage, Alu Sp in old world monkeys lineage and Alu Sx in new world monkeys lineage is also interesting. The paralogous insertion of an Alu repeat into the orthologous regions of human and non-human primate genomes is an independent evolutionary event [Alu elements into identical sites within different genomes. The detection of parallel insertions is a function of the rate of retroposition of Alu elements within various primate lineages and the time since the most recent common ancestor [Alu repeats within primate genomes. Future studies on the integration of different SINE elements in syntenic regions of human and rodent genomes may yield new insight into the molecular nature of hotspots for SINE element integration.The identification of multiple paralogous ry event . To dateancestor . HoweverAlu-mediated deletion that resulted in the inactivation of the human CMP-N-acetylneuraminic acid hydroxylase gene [Alu mediated deletions of noncoding genomic sequences have been identified [Alu retroposition-mediated deletions that may have happened by a mechanism similar to that of the LINE element mediated genomic deletions since Alu and L1 elements utilize a common mobilization pathway [Alu Ye5AH24 and Alu Ye5AH27, the deletion appears to have occurred, after the separation of human, chimpanzee and gorillas from orangutan and Siamang, during the process of gene conversion similar to the lineage specific Alu deletion reported previously [Genomic deletions created upon LINE-1 retrotransposition using cell culture assays have been recently identified . The ratase gene  and Alu entified . Here we pathway ,8,72. Ineviously ,71.Alu retroposition associated genomic deletions as approximately 1.67%. The size of the deleted sequences was over 300 bp on average. New Alu integrations have been estimated to occur in vivo at a frequency of one new event in every 10 to 200 births [Alu retroposition events in vivo, the genomic impact of these events could be substantial. This is not a trivial number of deletions when extrapolated to the copy number of Alu elements in the human genome which is over one million [Alu elements may have been involved in retroposition mediated deletion events within primate genomes. If each of these deletion events removes an average of 300 bp of genomic sequence, this would mean that Alu retroposition mediates the deletion of about 5 Mb of the primate genomic sequences. However, if the Alu associated deletions have involved larger sequences similar to those recently reported for LINE elements [Here, we have estimated the frequency of 0 births . If sizaelements , then thThe Alu Ye lineage has had an extended history of expansion in the human lineage. Its expansion appears to have begun soon after the divergence of the hominoids from the remainder of the catarrhine primates and proceeded at a relatively low level since then. Extended periods of relatively low levels of retrotransposition may allow some mobile elements to retain duplication capability for long periods of time. Despite a relatively low level of retrotransposition, the Alu Ye lineage has contributed to the architecture of the human genome through insertion mutations, retrotransposition associated genomic deletions, and gene conversion.Alu Ye elements in the draft sequence of the human genome , we used Basic Local Alignment Search Tool (BLAST) [Alu elements identified in the searches is located in .To identify  (BLAST)  queries  (BLAST) -49. A coAlu Ye lineage loci analyzed were performed as previously described [Alu Ye lineage members. Diverse human DNA samples were available from previous studies [Pan troglodytes), WES (ATCC CRL1609); gorilla (Gorilla gorilla) lowland gorilla Coriell AG05251B, Ggo-1 (primary gorilla fibroblasts) provided by Dr. Stephen J. O'Brien, National Cancer Institute, Frederick, MD, USA; bonobo (Pan paniscus) Coriell AG05253A; orangutan (Pongo pygmaeus) ATCC CRL6301; green monkey (Chlorocebus aethiops) ATCC CCL70 (old world monkey); and owl monkey (Aotus trivirgatus) OMK (OMKidney) ATCC CRL 1556 (new world monkey). Cell lines were maintained as directed by the source and DNA isolations were performed using Wizard genomic DNA purification (Promega). DNA samples from peripheral lymphocytes or tissue were prepared from the gibbon (Hylobates lar) and siamang (Hylobates syndactylus). Additional non-human primate DNA samples , Macaca nemestrina (old world monkey), Saquinus labiatus (new world monkey), Lagothrix lagotricha (new world monkey), Ateles geoffroyi (new world monkey) and Lemur catta (prosimian) available as a primate phylogenetic panel (PRP00001) were purchased from the Coriell Institute for Medical Research.Oligonucleotide primers and PCR amplification reactions for each of the escribed -49 using studies -49. The Alu element) has been assigned accession numbers AY849282-AY849301. Sequence alignments of the Ye lineage subfamily members were performed using MegAlign software (DNAStar version 3.1.7 for Windows 3.2). The ages for each of the Alu Ye subfamilies were calculated using mutation densities as previously described [DNA sequencing was performed on a gel purified PCR products that had been cloned using the TOPO TA cloning vector (Invitrogen) using chain termination sequencing  on an Apescribed ,47-49,65escribed .AS performed all experimental work for the project, shared in the analysis and interpretation of the results and wrote the first draft of the manuscript. DAR provided assistance with analysis and interpretation of the data and in preparing the manuscript for submission. DJH wrote the software used to extract Ye elements and the associated flanking sequences from the human genome draft sequence. JJ provided assistance with the analysis and interpretation of the data and input on late drafts of the manuscript. MAB provided the initial input for the project as well as valuable input on each draft of the manuscript.This supplemental file represents a sequence alignment for for locus Ye5AH161 in fasta format.Click here for fileThis supplemental table lists all Alu Ye elements recovered with information on PCR conditions, chromosomal location and phylogenetic origin. It is in Microsoft Word format.Click here for file


Sequencing and characterisation of fliC was performed in the development of a molecular serotyping technique.The FliC sequencing of 106 strains revealed two groups; the g-complex included those exhibiting "g" or "m,t" antigenic factors, and the non-g strains which formed a second more diverse group. Variation in fliC was characterised and sero-specific motifs identified. Furthermore, it was possible to identify differences in certain H antigens that are not detected by traditional serotyping. A rapid short sequencing assay was developed to target serotype-specific sequence motifs in fliC. The assay was evaluated for identification of H1 antigens with a panel of 55 strains.FliC sequences were obtained for more than 100 strains comprising 29 different H1 alleles. Unique pyrosequencing profiles corresponding to the H1 component of the serotype were generated reproducibly for the 23 alleles represented in the evaluation panel. Short read sequence assays can now be used to identify fliC alleles in approximately 97% of the 50 medically most important Salmonella in England and Wales. Capability for high throughput testing and automation give these assays considerable advantages over traditional methods. Salmonella express flagellar (H), polysaccharide (O) and capsular (Vi) antigens which determine strain pathogenicity and therefore variation of these antigens has formed the basis for Salmonella serotyping. The Kauffmann-White scheme, first published in 1929, divides Salmonella into more than 2500 serotypes according to their antigenic formulae. Within these, 46 O antigen groups are recognised by Salmonella serotyping. O antigen synthesis and assembly is encoded by the rfb gene cluster which typically contains 12 open reading frames, and ranges in size between serotypes, from approximately 8 kbp to 23 kbp. The variation of O antigens is not due to individual gene sequence variation, but rather to different sets of genes ,g,m, [p], g,p, and g,m,s could be separated using this technique ,g,m, [p] sequences obtained from Salmonella enterica serovar Enteritidis strains. Twenty-three S. Enteritidis strains demonstrated complete conservation in their DNA sequence ). The sequence of B17 was congruent with published S. Enteritidis (M84980) (Enteritidis_a), and exhibited a single amino acid (Ser>Gly at 302) substitution compared to sequence type Enteritidis_b. Published S. Othmarschen (U06455) fliC-g,m, [t] sequence inferred the same amino acid sequence as Enteritidis_a but exhibited a silent mutation at the DNA level. As the fliC sequence for these two serotypes was identical it was apparent that the sequence included here represented an S. Othmarschen strain in which the t factor was absent.The following polymorphisms located in S. Gallinarum sequences demonstrated 100% DNA homology to Enteritidis_b except for a SNP encoding a stop codon in M84975. S. Pullorum and S. Gallinarum are non-motile as they do not express flagella. Antisera to the g factor antigen react strongly with induced-motility S. Pullorum culture, indicating that g epitopes are expressed in these cells ,g,t, g,z51 and biotype S. Pullorum gave unique motifs, l,v and l,z13 shared a motif. Some serotypes for which certain factors may be present or absent (denoted by square brackets in antigenic formulae) were not separated from similar serotypes: [f],g,m, [p], g,m and g,m, [p],s; [f],g,m, [p] and g,m, [t]; g, [s],t and g,t although these could be separated by other DNA polymorphisms as discussed. Two motifs were observed for k, each specific to S. Thompson and IIIb. Two motifs were observed for d, specific to S. Duisberg and S. Muenchen / S. Schwarzengrund. Published sequence data for fliC-m,t, from serotypes S. Banana, S. Oranienburg and S. Pensacola were included in assay design. The polymorphic region targeted by the assay is predicted to differentiate m,t sequences from other g-complex antigens, and also differentiate S. Pensacola from S. Banana and S. Oranienberg. Strains exhibiting factors m,t were not available for testing.The stability of the targeted polymorphisms in fliC genes of g-complex strains was observed. Data produced for this study is congruent with a previous report of g-complex sequences [A high level of sequence homology between equences . The genFull gene sequences were distinct for each antigen analysed in this study. Furthermore, analysis of multiple representatives revealed that some antigens were encoded for by multiple sequences. In these cases DNA sequence based methods are more discriminatory than traditional serotyping methods which do not recognise these as distinct antigens.Assays were designed such that an unknown strain could be identified in respect of its phase 1 flagellar antigen in two steps. The specific PCR acted as the first level of identification and the resultant amplicon was used for the pyrosequencing assay. A positive PCR indicated which of two Pyrosequencing assays to apply. Each assay was uniform in that only one mix of pyrosequencing primers and one dispensation order was needed. All the strains tested were successfully amplified by PCR. As some analyses have been performed on unpublished data, exhaustive testing of the assay will be performed to confirm specificity and typeability of all recognised serotypes.Molecular serotyping will incorporate the desirable properties of serology  together with the advantages of DNA analysis . Antisera production and associated quality control measures would be unnecessary for a DNA sequence based method. Time-consuming flagellar phase reversal to identify both flagellar antigens is not necessary at the genetic level. Other advantages include reduced labour costs, rapid results in comparison to traditional serotyping methods. DNA sequence data is highly portable and easy to interpret. The method described was easily automated by use of the vacuum preparation tool for the DNA strand separation step and could be further automated by use of robotics for PCR set-up. Result output included a pyrogram, raw text and confidence level; automation of data analysis could be achieved by use of a computer script to screen at a set confidence level and cross-check results against a database of recognised motifs.Salmonella strains occurring in England and Wales, the assay can be used now as an economic screen of unknown isolates and alleviate the burden on routine serotyping work. A scheme including the phase 1 flagellar assay and complementary assays for phase 2 flagellar and polysaccharide antigens is currently being piloted and based on incidence data of the top 50 serotypes from 2003, it is anticipated that the scheme will provide a complete molecular serotype for around 80% of isolates and confident prediction of 76% of the remainder.With the capability to identify approximately 97% of phase 1 flagellar antigens from medically important Alternative sero-specific polymorphisms identified in this study could be exploited by similar assays to allow further separation when antigens did not give unique pyrograms.fliC assay to a fljB and rfb assay would allow the full antigenic formulae of Salmonella serotypes to be determined. Common phase 2 flagellar antigens will be selected for sequencing and together with published data will be analysed for sero-specific motifs and a short sequence assay designed with the approach described in this study.The alliance of the et al [Salmonella major serogroups A, B, C2, and D. They based their PCR on the presence/absence of genes or sequence polymorphisms within shared genes. Essentially, only serogroups A and D possess a gene to synthesise tyvelose but serogroup A genes carry an early stop codon and do not produce the sugar itself. Only groups B and C2 possess a gene to synthesise abequose but the sequences are distinct. We have also designed a preliminary pyrosequencing assay to distinguish these serogroups based on amplification and short sequences of these genes (data not shown).In 1993, Luk et al  outlinedIn summary, epitopes are conformational and it is difficult to determine which amino acids would interact from a linear sequence. However, in the g-complex sequences some amino acid changes could be identified as responsible for differences in antigenic factors because variation was minimal. There is no common factor among the non-g antigens and the sequences are much more heterogenous; there are too many substitutions to draw conclusions about epitope specific sequences. Epitope mapping could be used to further investigate epitopes responsible for antigenic specificity.Salmonella Reference Collections A, B and C obtained from the University of Calgary. Multiple isolates of S. Enteritidis phage type 4, and S. Typhimurium phage type DT104 plus a panel of serotyped strains were gratefully received from the Salmonella Reference Laboratory, Health Protection Agency, Colindale .MagNA Pure instrument and Total Nucleic Acid Extraction Kit 1 . PCR reactions contained 1X PCR buffer, 20 pmoles of FL_START2, 20 pmoles rFSa1 , 1 U TaqfliC gene was performed with an 9700 GeneAmp PCR System : 35 cycles of 95°C for 60 sec, 50°C for 60 sec, 72°C for 30 sec followed by a 7 min final extension at 72°C. PCR products were purified with Qiaquick spin columns  and quantitated by gel electrophoresis using Ready-to-Run pre-cast gels . Fifty to one-hundred nanograms of the purified PCR product was used for cycle sequencing, with specific primers .fliC sequences. Some previously published sequences were included  was used to compute a distance matrix from protein sequences and build trees illustrating the relatedness of included . Polymor MOP-UPs  identififliC sequences. Amplicon sizes were approximately 316 bp for g-complex strains, 170 bp – 250 bp, (size varied according to serotype) from non-g strains. The order of nucleotide dispensation was tailored to enable the first two dispensations to act as negative and positive controls.Two multiplex PCRs were designed to amplify polymorphic regions of both g- and non-g complex fliC gene. Fifty microlitres of PCR product was prepared containing 1 U Taq polymerase, 0.25 mM of each dNTP, 4 mM MgCl2. PCR for amplification of g-complex strains used three forward primers: 100 pmol GPYRO-A; 12.5 pmol GPYRO-B; and 12.5 pmol GPYRO-C; and 125 picomoles of reverse biotinylated primer G-REV. PCR for amplification of non-g strains used 14 forward primers  in equal concentrations. Thirteen biotinylated reverse primers  were used in equal concentrations. In each 50 μl reaction 125 pmol of mixed forward primer and 125 pmol mixed reverse primer was used. Primer sequences are detailed in A 1 μl loop of cells was boiled in 100 μl of sterile distilled water for 10 min at 95°C. One microlitre of lysate was used for PCR. Two PCRs were run in parallel to amplify fragments of the Thermocycling was performed with an Applied Biosystems 9700 GeneAmp PCR System using a touch-down programme: initial denaturation step of 94°C for 2 min; followed by 17 cycles of 94°C for 20 sec, 66°C (-1°C per cycle) for 30 sec, 72°C for 30 sec; followed by 20 cycles of 94°C for 20 sec, 54°C for 30 sec, 72°C for 30 sec. The excess primers were removed using a filter plate and vacuum system  before visualising the PCR products on the Ready-To-Run agarose system (as previously). Biotinylated single-stranded DNA was immobilized on streptavidin-coated sepharose beads  with binding buffer. The mixture was agitated at 1400 rpm for 10 min at room temperature. Single stranded DNA bound to beads was isolated from the mixture using a series of wash steps for 5 seconds each in turn, 70% ethanol, 0.2M NaOH and washing buffer. Ninety-six samples were prepared in 2 minutes by automation of strand separation step using a vacuum preparation tool . A combination of pyrosequencing primers was used for each assay; 20 primers for the non-g complex assay, and three for the g-complex assay  into whiSalmonella serotyping and provided strains. CA CM SG TP and JL participated in the design of the study. CA conceived of and coordinated the study. All authors read and approved the final manuscript.CM carried out the sequencing, constructed the multiple alignments and designed the assays. TP carried out the serotyping. TP advised on fliC gene sequences representing 32 H1 alleles. Sequences labelled with _a, _b or _c indicate an H1 allele encoded by multiple sequences . Codon numbering is in reference to the sequence of Typhimurium_a which represents sequenced strain LT2.Amino acid alignment. Amino acid alignment of 106 Click here for filefliC *These primers were also used as pyrosequencing primersPrimers used for PCR and Pyrosequencing. Orientation of the primer is represented by F (forward) or R (reverse) and approximate position is given as nucleotide distance from 5' end of Click here for fileSequences used in this study. Sequences labelled with _a, _b or _c indicate an H1 allele encoded by multiple sequencesClick here for file


Parsing a mental operation into components, characterizing the parallel or serial nature of this flow, and understanding what each process ultimately contributes to response time are fundamental questions in cognitive neuroscience. Here we show how a simple theoretical model leads to an extended set of predictions concerning the distribution of response time and its alteration by simultaneous performance of another task. The model provides a synthesis of psychological refractory period and random-walk models of response time. It merely assumes that a task consists of three consecutive stages—perception, decision based on noisy integration of evidence, and response—and that the perceptual and motor stages can operate simultaneously with stages of another task, while the central decision process constitutes a bottleneck. We designed a number-comparison task that provided a thorough test of the model by allowing independent variations in number notation, numerical distance, response complexity, and temporal asynchrony relative to an interfering probe task of tone discrimination. The results revealed a parsing of the comparison task in which each variable affects only one stage. Numerical distance affects the integration process, which is the only step that cannot proceed in parallel and has a major contribution to response time variability. The other stages, mapping the numeral to an internal quantity and executing the motor response, can be carried out in parallel with another task. Changing the duration of these processes has no significant effect on the variance. The inability to operate two cognitive processes simultaneously - a mental bottleneck - can be explained by a model in which evidence is accumulated stochastically to reach a decision Even the most simple behaviour involves a chain of computations, which link perception, decision making, and action ,2,3. MeaWhen two tasks are presented simultaneously , a delay in the execution of the second task has been systematically observed ,9,10,11.A separate line of psychological research has investigated how the decision to respond is achieved. The decision-making process has been modelled as a noisy integrator that accumulates evidence provided by the sensory system ,23,24,25In the present work, we propose a single assumption that unifies those two lines of research. We postulate that only the integration process establishes a serial bottleneck, while all other stages can proceed in parallel with stages of another task . This moWe designed a behavioural task to test the validity of the model. This number-comparison task involves deciding whether a digit presented on the screen is larger or smaller than 45. Different manipulations of the task render it more difficult, presumably, at different stages of processing. The different task manipulations include notation (whether the number was presented in Arabic digits or in spelled words), distance , and response complexity (whether subjects were asked to tap once or twice to indicate their choice). Previous studies have shown that all of these manipulations change the difficulty of the task: RTs increase when numerical distance decreases and when numbers are presented in spelled words ,29. ThesSubjects were asked to perform a dual task. One of the two tasks was presented visually and involved a number comparison: subjects decided whether a digit presented on the screen was larger or smaller than 45. Hereafter we will refer to it as “number task”. The other was a tone-discrimination task that involved deciding whether the frequency of a single pure tone that was presented for 150 ms was high (880 Hz) or low (440 Hz) (subjects heard both tones repeatedly before the beginning of the experience). Hereafter we will refer to it as “tone task”. Two different populations of subjects performed the task in the two possible orders, tone task followed by number task or vice versa.The number task was our main task of study, and was manipulated using three different factors: notation (whether the number was presented in Arabic digits or in spelled words), distance , and response complexity (whether subjects were asked to tap once or twice to indicate their choice). The tone task was never varied throughout the experiment. The rationale underlying this experimental design is that the tone task is used as a probe to study, through interference experiments, the different stages of processing of the number task. This asymmetry between the two tasks, which might be helpful to keep in mind, was of course not stated to the subjects, who were just asked to attend equally to both tasks.The results section is organized as follows. We first report an analysis of basic measures of central tendency and dispersion. We then address how different manipulations (within the number task or through the interference with the tone task) change the mean RTs and their dispersion. These types of tests allow us to test the additivity of the effects of each factor and, through the interference analysis, whether they affect the perceptual, the central, or the motor stage. A second level of analysis involves a more detailed characterization of the shapes of the distributions of RTs. Fitting the distributions allows us to evaluate the accumulation model of response decision and to relate its components to those identified by their patterns of interference in the first-level analysis.For clarity and as a reference throughout the paper, all the definitions, components of the models, and experimental manipulations are summarized in The first analysis involved studying the effects of the different manipulations of notation, distance, and response complexity on mean RTs and response dispersion on the number task when it came first. Our model predicted that manipulations that affect separate stages should have additive effects on mean RTs, and that only manipulations that affect the central stage should significantly increase response dispersion.For this analysis (and throughout the paper unless otherwise specified) distance, which is the absolute value of the difference between the presented number and 45, was binned in two groups, close (≤12) and far (>12). Central tendency was measured by estimating the mean RT after trimming for outliers, by discarding responses slower than 1,200 ms. Response dispersion was measured by estimating the interquartile range, i.e., the difference between the 75th percentile and 25th percentile of the distribution of RTs. As we expected from several prior experiments ,30, perfInterestingly the effects of the different manipulations on response dispersion did not follow the effects on the mean, indicating that some factors slowed RT but did not significantly increase their dispersion. The distance manipulation resulted in a significant increase of the interquartile range typical of stochastic process, where the dispersion increases with the mean. In contrast, notation and response complexity, while causing an important change in the mean, did not result in a significant increase of the interquartile range B.To fully address whether the number-comparison task involves three separate stages with each experimental factor , a complete “additive factors” experimental design is needed, in which the different factors are crossed and thus all the interactions can be tested. However, such a factorial design, if tested in the double-task experiment, would involve an exceedingly large number of conditions, which would be very difficult to test on a subject by subject basis within a single session. Instead, we ran it as an independent experiment, in which a new group of subjects was asked to perform only the number task.The results of this new experiment, summarized in Taken together with the assumption of our model that only the central stage contributes to response variance, our observations suggest that the numerical distance factor affects the C decision component, while notation and response complexity affect noncentral P or M components.In addition to tests of additivity, a useful experimental technique to address the separable nature of different components and to understand their organization in time, is the interference analysis, in which the task of study (the number-comparison task) is performed together with a probe task (the tone task). The delay in the onset between the two tasks is controlled experimentally, and to achieve a full separation of the three components, the two tasks must be presented in both possible orders . Under tWe begin by describing the mean RT results when the number task  was performed first, and the tone task came second. The PRP model predicts that each of the manipulated variables of notation, distance, and response complexity should have a main effect on the first number-comparison task, but only some of those effects (those that affect P and C components of the first task) should propagate to the RT2, and should do so only at short interstimulus delays (Δ) .To evaluate these predictions, mean RTs were calculated within each condition and each subject, and submitted to ANOVAs with subjects as a random factor and delay and the variable of interest as within-subject factors. The detailed results of those ANOVAs are reported in The ANOVAs on number-comparison RTs (RT1) revealed the expected main effects of number notation , numerical distance , and response complexity . There was no main effect of Δ, and none of the task effects interacted with delay. These results suggest that, as requested, participants performed the number comparison as task 1 independently of the delay of presentation of the subsequent tone task.Similar ANOVAs on tone-decision RTs (RT2) revealed a main effect of delay, characteristic of the PRP phenomenon. As shown in Crucially, our three experimental factors had differential effects on those two segments of the RT curve. Notation and distance showed both a main effect and an interaction with delay .As a further test, we analysed the data for short delays, within the interference regime (Δ ≤ 350 ms) and long delays (Δ ≥ 600 ms) . For thet-tests, where we did not observe a significant difference either in the short delays or in the long delays  came second. In this case the PRP model predicts that there should be no effect of the manipulated variables of notation, distance, and response complexity on the first tone task; in addition, the RT2 should exhibit a constant increase (independent of delay) when the change affects the M and C components and should change only for large delays when the change affects the P component see . As descThe ANOVAs on the tone task RTs  revealed no effects on the task manipulation, as predicted by the PRP model because response to task 1 should be independent of the nature of task 2. The ANOVAs on the number-comparison RTs  again revealed a very significant nonlinear effect of delay characteristic of the PRP effect. In addition, for the distance and response-complexity manipulations, we observed a task effect that did not interact with delay see , typicalt-tests performed for short and long delays. When data were collapsed across all short delays for the distance and motor manipulation, there was a significant effect of both factors (respectively 86 ms and 255 ms). In contrast, there was no significant difference in RT for the number task for the different notations for small delays . In both cases we find that the response is slower when the task is presented first: number task, 756 ms when presented first and 678 ms when presented second; tone task, 720 ms when presented first and 518 ms when presented second. Thus there is a fixed component (independent of delay) of approximately 150 ms, which needs to be added to RT1 to fully explain the data.to, followed by a forced random walk to a threshold T with slope α and diffusion constant σ (to) corresponds to the sum of the P and the M components  was analysed for each task when it was presented first. For the number task we analysed six different cases corresponding to the three different manipulations , and two levels of numerical distance: close distances (≤12) and far distances (>12). For each of these distributions, the histograms of RTs and their cumulative distributions were calculated, and the latter were fitted to a simple model of RTs. The model was based on a fixed onset delay, nstant σ . The fixents see .T can be set to one without loss of generality. For simplicity, we assumed that σ was the same for all six experimental conditions, while α and to could vary . The best-fitting values were determined by exhaustive search using a minimum-squares criterion. The value of 1/α characterizes the integration time , while to captures fixed components that do not contribute to the variance. Thus, our purpose was to test the prediction of our model that the notation and response-complexity manipulations should affect the parameter to while the distance manipulation should affect the parameter α.The applicability of random-walk models to RT data has been widely studied in numerous tasks ,21,22,23to that provided the best fit. We found that the to changes from task to task but does not depend on distance. In contrast, 1/α does not change across tasks but changes with numerical distance (y-intercept at x = 0)  does not differ significantly from zero (p > 0.3) and the value of the intercept differs significantly across tasks (p < 0.001). In contrast, for 1/α the intercept is not significantly different across tasks (p > 0.5) while the slope is significantly different from zero (p < 0.001) Thus, response complexity and notation manipulation affect to, while numerical distance affects 1/α. These results are consistent with the prior analysis, which showed that response complexity and notation manipulations did not significantly affect the interquartile range (another measure of dispersion) while the distance manipulation did significantly change the interquartile range.For a finer-grained analysis, and to test the significance of this phenomenon, we binned the data in 24 different bins based on their distance to the reference 45 used for numerical comparison. For each bin, we calculated the α and distance C. To test x = 0) D. For tHere we try to explain the precise shape of RT2s, by combining, based on the PRP model, the distributions obtained for each task when presented first. If the two tasks were completely sequential, then the resulting distribution would be simply the convolution of the two original distributions. However, the PRP model states that only the C component is sequential, and, thus, because some operations can be done in parallel, the resulting RT2s are shorter than expected from a convolution. The operation performed is not completely trivial and is described step by step in P2 and M1 as free parameters. We found that with these parameters alone, the data could not be fitted . It seemed evident that the problem was that the predicted distributions were shifted in time with respect to the original distributions, and thus we decided to add one parameter, Td, a rigid shift in time of all distributions of RT2 . We then found good fits for the ensemble of distributions  we tried to fit the 20 distributions of RT2  from the distributions of RT1, with P2 and M1. When the number task was second, the parameters are P(Number) and M(Tone). When the tone task was the second, the fit parameters are P(Tone) and M(Number). The obtained values of the square residuals for different parameters were not sufficient to actually calculate precisely each parameter, since the fit was unstable in the P2 − M1 direction , but they were sufficient to calculate their sum (P(Number) + M(Tone) (P(Tone) + M(Number) (P(Tone) + M(Number) (P(Number) + M(Tone) (Each fit provides the parameters heir sum . In agre M(Tone) , left bu(Number) , right. (Number) , left bu M(Tone) , right.to (a fixed delay). As expected from our model, across the different conditions summarized in to is always approximately equal to the sum of the durations of the P and M components, while 1/α is equal to the duration of the C component. This provides further evidence that the process of accumulation of evidence does indeed constitute the characteristic bottleneck (the C component) in dual-task experiments.Finally, the parameters obtained from the interference experiment may be compared to those of the previous fit, which was based on the shape of the distributions of RTs for the first task, and which yielded estimates of 1/α (the time of integration) and We proposed a basic model that relates the organization of parallel and serial components and the process of accumulation of evidence to reach a decision. The model, although simple, results in a wide number of predictions that, as we have shown, hold over a vast variety of manipulations. We show that the perceptual transformation of sensory information into an abstract quantity representation can be carried out in parallel with another task and is a low-variability process (whose variability does not increase with the mean); that the accumulation of evidence establishes a bottleneck and is an intrinsically variable process; and that the execution of the response constitutes yet another parallel, low-variability process. Our data suggest that the integration of evidence in time to reach a decision constitutes the only central process in a simple cognitive task that links perceptions to actions.While dual-task experiments (in which two tasks are presented at variable delays) allow different interpretations, experiments in which one of the two tasks is parametrically manipulated provide a severe test of the PRP model ,13,16. IHere we have tested, within the number-comparison task, three different manipulations, in the two possible orderings of the sequential tasks, thus providing an exhaustive test of the model. Our finding that all manipulations fall reliably within one of the PRP components provides strong evidence of the generality of this phenomenon. In addition, while it had been shown previously that the distribution of dual-task RTs was wider than that predicted by noninterfering processing of the two tasks , preciseA striking result, however, is the duration of the C component, which even in a simple task represents about 70% of the total RT. Considering the simplest version of our task , our results indicate that 180 ms is taken by the sum of P and M components, while a full 550 ms is taken by the C component. Previous event-related potential experiments suggested that it takes approximately 190 ms to identify an Arabic digit and begin to access a quantity representation . The preWhile all the PRP predictions held, the only discrepancy with the model arose from an unexpected slowness of responses to the first task. As predicted, RT1 was independent of the delay. However the mean RT was larger than found previously when subjects performed only the number-comparison task . Even wiHere, as in other PRP experiments, we have designed the tasks in order to maximally separate the inputs and outputs to the system . Under these conditions, as described above, we still find a source of central interference. Moreover we find that the transformation from a word form to an abstract semantic representation does not participate in this central process, nor does the execution of two consecutive and repetitive motor actions. The generality of these findings, however, has obvious bounds. We do not state here that any motor manipulation should result in a change in a parallel component; more complex motor responses, however, might require central supervision and create a bottleneck. Similarly, while we claim that mapping a word form to an abstract number representation can be done in parallel, we do not mean that it would not interfere with any possible stimulus. Finally, under some situations that lead to high automaticity, either through extensive training ,40 or veThere is a vast literature on the analysis of the shape of RT distributions as a source of knowledge about the human information-processing system, and many different models of these distributions have been proposed ,49,50,51A second important type of alternative to our model concerns the nature of the central process. Instead of a unique integrator, there might be a network of interacting integrators with lateral connections, which collectively implement the decision-making process and whose interactions create a functional bottleneck . The exiT. In a more complicated model, the value of the threshold might be changeable. Such a feature might be needed to fit the results of experiments in which one varies the prior probability of a given response or its associated reward (variables that were fixed throughout our experiment). For example, in a go/no-go experiment involving digit comparison, in which the probability of a response was fixed at a controlled probability pgo, it has been shown that pgo affects T, but not the drift rate (α) , where b is the threshold. This problem (of the first hitting time to an absorbing barrier of a Brownian motion) has been widely studied and can be solved analytically using the Fokker–Planck equation. The probability of hitting threshold for the first time at time t is given by the following equation:RTs were fitted to a model based on a fixed delay onset  ×  were fit to a fixed value of Here we describe how RTs for task 2 can be predicted based on the distribution of RTs for both tasks when presented first. Because of the presence of the PRP wait , this operation is not strictly a convolution. Since the method is not trivial and, to our knowledge, it has not been performed elsewhere, we will describe it step by step:1 and R2, the probability of performing the sequence at time T is given byIn a serial sequence of two processes (in which one needs to be finished before the next one starts), each with a probability distribution of RTs given respectively by RThis formula is simply the convolution of the two original distributions.R1*(t) = R1(t + M1). The second modification, because of the nature of the PRP experiment, is that task 2 obviously cannot start until it is presented and thus the onset time is actually given by R1**(t) = max. Thus the real distribution of onsets of task 2 is given by the accumulated probability of a shifted R1 up to Δ (which results in a spike at Δ) followed by the tail of R1*(t). The spike becomes more pronounced as the delay is larger, and thus the two tasks become independent.In a PRP experiment, however, the execution of the two tasks is not serial, since there are both serial  and parallel  components. The first difference is that task 2 waits not for the complete execution of task 1 but rather for the completion of the P and C components of task 1 see . Hence, t is given by R2(t). However, within the interference regime , P2 (or part of it) has been executed by the time that the P and C components of the first task (which corresponds to t − M1) are finished , where t2 = min + t. This formula is only valid for t > Δ, but this is not important because in any case R1**(t) = 0 for t < Δ. The important issue, however, is that this transformation depends on t and thus the sum described in R2* = R2[T − t2(t)] as the probability of completing task 2 in time T − t given that task 1 has been completed in t + M1.The last consideration has to do with the time it takes to respond to task 2. If Δ is sufficiently large (in the independent regime), the probability of executing task 2 at time shed see . The disThe final formula (adapting Td) to the fit. With the inclusion of the parameter Td, the errors, measured as the mean square residual  were consistently below 0.015 , and we observed a parabolic type of distribution, with a clear minimum . As described in Results, this model was not sufficient to fit the data (note that we are simultaneously fitting a family of 30 curves), so we included a third fixed delay parameter (