Phonological processing in deaf signers and the impact of age of first language acquisition

Just as words can rhyme, the signs of a signed language can share structural properties, such as location. Linguistic description at this level is termed phonology. We report that a left-lateralised fronto-parietal network is engaged during phonological similarity judgements made in both English (rhyme) and British Sign Language (BSL; location). Since these languages operate in different modalities, these data suggest that the neural network supporting phonological processing is, to some extent, supramodal. Activation within this network was however modulated by language (BSL/English), hearing status (deaf/hearing), and age of BSL acquisition (native/non-native). The influence of language and hearing status suggests an important role for the posterior portion of the left inferior frontal gyrus in speech-based phonological processing in deaf people. This, we suggest, is due to increased reliance on the articulatory component of speech when the auditory component is absent. With regard to age of first language acquisition, non-native signers activated the left inferior frontal gyrus more than native signers during the BSL task, and also during the task performed in English, which both groups acquired late. This is the first neuroimaging demonstration that age of first language acquisition has implications not only for the neural systems supporting the first language, but also for networks supporting languages learned subsequently.
Introduction
Phonology describes the level of analysis at which meaningless, contrastive units of language combine to form meaningful units. In spoken languages these are auditory/articulatory elements. Substitution of a single element creates a new lexical item, e.g., in English /pin/–/bin/. The same level of analysis has been applied to signed languages, where phonology is visual, with handshapes, movements and locations combined to form signs (Stokoe, 1960; Brentari, 1999; Sandler and Lillo-Martin, 2006). As with words, the substitution of just one element can create a new sign. For example, the BSL sign NAME is located at the forehead while AFTERNOON differs only in that it is located at the chin (see Fig. 1).
The primary aim of the current study was to examine whether the application of the term ‘phonology’ to signed languages has neurological as well as linguistic and psycholinguistic validity. We address, for the first time, whether similar neural processing is involved in phonological analysis of both signed and spoken languages. We asked participants to judge whether spoken word labels for pictures rhymed or not. Of the phonological parameters of signs, location is one of the primary factors determining whether signs are judged to be similar (Hildebrandt and Corina, 2002). Therefore, we also asked deaf participants to judge if BSL signs for pictured items shared the same location.
Studies of written rhyme judgement by hearing people report reliable activation of the posterior portion of the left inferior frontal gyrus (IFG) and the ventral premotor cortex (Broca's area; Sergent et al., 1992; Poldrack et al., 1999; Kareken et al., 2000; Lurito et al., 2000; Xu et al., 2001; Seghier et al., 2004; Burton et al., 2005). Temporary disruption of this region using transcranial magnetic stimulation (TMS) impairs phonological processing (Gough et al., 2005). Given the well-established role of the posterior IFG in speech production (Ojemann and Mateer, 1979), the contribution of the left posterior IFG and ventral premotor cortex to phonological processing is often attributed to articulatory processes or representations (Démonet et al., 1996). In addition to the left IFG, the left parietal lobe is also recruited during rhyme judgement tasks using written stimuli (e.g., Pugh et al., 1996; Lurito et al., 2000; Xu et al., 2001; Seghier et al., 2004). However, the precise role of this region in phonological processing remains unclear (see Eden et al., 2004) and will be addressed further in the Discussion section. If similar processing is required to make phonological similarity judgements about BSL and English, left inferior frontal and left parietal regions should be recruited during both tasks.
An important feature of the current study was the use of picture stimuli (see Fig. 2). This enabled the same stimuli and response requirements to be used in both the BSL and English tasks. This is not possible in studies contrasting comprehension (e.g., MacSweeney et al., 2002b) or production (e.g., Braun et al., 2001) of speech and sign. Picture stimuli also allowed us to tap individuals' own phonological representations of words and signs. Previous studies of rhyme judgement with hearing people have used auditory or written stimuli, which directly or indirectly provide the phonology of the item. To determine whether rhyme judgements in response to pictures elicit the pattern of activation reported in studies using written words, hearing participants were also tested. Including this group also allowed us to directly contrast activation patterns observed in deaf and hearing participants to determine the effect of hearing status on the neural systems supporting phonological processing.
A second aim of this study was to determine if the neural systems supporting language are influenced by the age of first language acquisition. To address this, deaf native and non-native signers were contrasted. Approximately 5% of deaf people are born to deaf, signing parents (Mitchell and Karchmer, 2004). Typically, these children learn a signed language as their native language, reaching acquisition milestones along the same timescale as hearing children acquiring speech (Morgan and Woll, 2002). However, for nearly all of the 95% of deaf children who are born to hearing parents (non-native signers), exposure to a signed language is delayed.
Deaf native and non-native signers should differ on sign-related tasks since this is the language acquired early or late. In addition, Mayberry et al. have shown that deaf native signers perform better than deaf non-native signers on grammaticality judgements of written English (Mayberry et al., 2002; Mayberry and Lock, 2003). In these studies, both groups encountered written English at the same age. However, what did differ between these groups was their early language experience. Native signers have a well-established first language which can facilitate the acquisition of a later learned language; non-native signers do not. For all deaf people, both native and non-native signers, exposure to spoken language is late and incomplete. This is because speechreading cannot provide full access to speech since many of the articulators of speech are invisible. From this perspective, Mayberry and Lock (2003) have argued that deaf non-native signers can be considered to have ‘no early language’. This is a very different situation to that of hearing people learning a signed language late since they already have a native spoken language. Studies contrasting early and late acquisition of signed language in hearing participants (cf., Newman et al., 2002) cannot therefore be generalised to the deaf population. We examined how the incomplete acquisition of a language early in life is reflected in the brain. Consistent with the behavioural findings of Mayberry et al., we predicted differences between deaf native and non-native signers, on both the BSL and English tasks, despite these groups' similar experience of English.
In summary, in the current study profoundly deaf and hearing adults made phonological similarity judgements in response to picture pairs (see Fig. 2). Participants judged if the spoken English labels rhymed or whether the BSL labels shared the same location (deaf group only). Activation during these experimental conditions was contrasted with a ‘same picture?’ control task. The following research questions were addressed: are the same neural networks recruited during phonological decisions based on signed and spoken language? What is the impact of age of signed language acquisition and hearing status on this network?
Materials and methods
Participants
Twenty-three deaf adults and 24 hearing adults were scanned. All were right-handed and had normal or corrected to normal vision. Of the deaf participants, one was excluded because of excessive movement in the scanner and another two were excluded because they did not complete both the sign and speech tasks. Therefore, 20 deaf and 24 hearing participants, matched on age and non-verbal IQ (Block Design, WAIS-R: p > 0.1), were included in the analyses (see Table 1 for participant characteristics). The deaf participants included in the fMRI study were selected from a larger sample of volunteers. To enhance the likelihood that they would perform the phonological judgement tasks well, those selected were good readers and had performed well on a test of rhyme ability in a previous test session outside the scanner. Therefore, the deaf participants included in the fMRI study were good readers (mean reading age = 15years, 6months) in comparison to the population mean for deaf people, generally considered to be approximately 9 or 10years (see Conrad, 1979; Allen, 1986; Holt, 1993). The deaf participants were also skilled speechreaders, outperforming the hearing participants on the Test of Adult Speechreading (Mohammed et al., 2003; t = 5.1, (34), p < 0.0005). Nevertheless, the hearing group were significantly better readers (Vernon-Warden, 1996: t = − 3.9, (42), p < 0.0005) and had a higher English vocabulary score (shortened version of the Boston Naming Test, Kaplan et al., 1983: t = − 4.1, (42), p < 0.0005) than deaf participants. These differences are accounted for in the fMRI data analyses.
All deaf participants reported being born profoundly deaf and audiograms obtained at the time of testing confirmed that all had a mean hearing loss greater than 92dB in the better ear over four octaves, spanning 500–4000Hz. All deaf participants encountered written English upon entering primary school, aged 4/5. Twelve of the deaf participants were native signers, having acquired BSL from their deaf, signing parents. The remaining eight deaf participants (non-native signers) had hearing parents. One native signer and one non-native signer reported attending schools which used a total communication approach, in which signs are used to support spoken English. The remaining 18 of the 20 deaf participants had attended ‘oral’ schools in which spoken English was the main form of communication. This educational approach was the norm for this generation of deaf adults in the UK, even for those who used BSL as their native language. Of the eight non-native signers, five learned BSL after leaving secondary school, aged 17 to 21. One participant learned BSL at their total communication primary school aged 4/5. Two other participants who attended oral schools reported learning BSL at school; one aged 4/5, the other aged 11. These participants will have been exposed to BSL by their deaf native signing classmates.
The deaf subgroups were well matched. There were no significant differences between deaf native and deaf non-native signers in age (p = 0.06), non-verbal IQ (p > 0.1), reading age (p > 0.1), English vocabulary (p > 0.1) or speechreading skill (p > 0.1). All participants gave informed, written consent to participate in the study, which was approved by the Institute of Psychiatry/South London and Maudsley NHS Trust Research Ethics Committee.
Stimuli
The same pictures were presented in both the rhyme and location judgement tasks (n = 60). All pictures represented highly familiar/frequent, monosyllabic English words. Fifty-eight of the pictures were black and white line drawings, taken predominantly from the Snodgrass and Vanderwart (1980) standardised picture set and other language assessments. Two colour pictures were also included, to represent ‘red’ and ‘blue’.
Rhyme task (shared English phonology pairs)
Thirty pictures were combined as 15 rhyming pairs. Orthography was inconsistent so that rhyme decisions could not be based on spelling, (e.g., chair–bear, tail–whale; see Fig. 2A).
Location task (shared BSL phonology pairs)
The remaining thirty pictures were combined as 15 pairs sharing the same location when signed in BSL, but differing in handshape and movement (e.g., pig–witch; hat–cow, see Fig. 2B). Only signs touching the body or occurring in close proximity to it were considered to have a defined location. Participants were told that any pairs articulated in neutral space in front of the signer's body (see Stokoe, 1960) should receive a ‘no’ response.
The two sets of experimental pictures (rhyme and location pairs) were matched on familiarity (Coltheart, 1981) (t = 0.64, 53, p > 0.1) and concreteness (Coltheart, 1981) (t = − 1.1, 53, p > 0.1) and the English labels were matched on frequency (Kucera and Francis, 1967) (t = 0.92, 56, p > 0.1) and length (t = 1.5, 58, p > 0.1). The ‘no’ (non-shared phonology) trials were established by re-pairing the pictures from the complementary task. Rhyming pictures were re-paired such that there was no overlap in signed or spoken phonology to form the ‘no’ trials in the location task (e.g., chair–whale). Likewise, location pairs were re-paired to form the ‘no’ trials in the rhyme task (e.g., hat–pig). Thus, the same stimuli were presented in both tasks.
The stimuli used in the experimental conditions doubled as their own controls in the ‘same picture?’ control task. Fifteen of the pictures were presented as identical pairs (e.g., chair–chair, see Fig. 2C). Another 30 pictures were re-paired to form different picture trials. The labels for these items did not share any phonological features in either English or BSL. Thus, of the 60 pictures seen in both experimental conditions, 45 were also presented in the ‘same picture?’ control condition. Whether an item was first seen in the experimental or control condition was counterbalanced such that any repetition effects were balanced across conditions.
All participants performed a picture naming pre-test before the scan session. If an unexpected label was generated, the desired English word or BSL sign (deaf participants only) was supplied. Correct naming of these items was checked again at the end of the pre-test session.
Design
Deaf participants performed the rhyme and location similarity judgement tasks in separate, counterbalanced runs. Hearing participants performed only the rhyme task. Each run consisted of six 30-s blocks of the experimental task (rhyme or location), alternating with six 30-s blocks of the ‘same picture?’ control task. Each run lasted 6 min.
In the English phonology task, participants were required to decide whether the English labels for two pictures rhymed. Deaf participants had already been involved in a behavioural study of rhyme awareness as part of a wider project. They were reminded of the concept of rhyme and were given examples and practice trials prior to the start of the experiment in the scanner. In the sign phonology task, signing participants were required to decide if the BSL labels for the two pictures shared the same location. The control condition was interleaved between the same phonology? task blocks. This consisted of deciding if two pictures were the same. The trials in each condition were half ‘yes’ trials and half ‘no’ trials. Subjects indicated their response using a two-choice button box.
A one-syllable task prompt appeared at the bottom of the screen, without a pair of pictures, for 2000ms at the beginning of each block (‘Rhyme?’—rhyme task; ‘Place?’—location task; ‘Same?’—picture matching task). The prompt remained on the screen throughout the block. Each pair of pictures was presented for 5s. This relatively long presentation duration was selected on the basis of pilot studies in which deaf people made self-paced rhyme decisions in response to pictures. The inter-stimulus interval was 500ms. Each 30-s block was a mixture of five ‘yes’ and ‘no’ trials (see Fig. 2).
fMRI parameters
Gradient echo echoplanar MRI data were acquired using a 1.5-T GE NVi MR system (General Electric, Milwaukee, WI, USA) using a standard quadrature head coil. Head movement was minimised by positioning the participant's head between cushioned supports. One hundred and twenty T2⁎-weighted images depicting BOLD contrast were acquired during one experimental session at each of 38 near-axial 3mm thick planes parallel to the intercommissural (AC–PC) line: 0.3mm interslice gap; TR = 3s, TE = 40ms; flip angle = 90°). The field of view for the fMRI runs was 240mm, and the matrix size was 64 × 64, with a resultant in-plane voxel size of 3.75mm. An inversion recovery EPI dataset was also acquired to facilitate registration of individual fMRI datasets to Talairach space (Talairach and Tournoux, 1988). This comprised 43 near-axial 3mm slices (0.3mm interslice gap), which were acquired parallel to the AC–PC line (TR = 16s; TE = 80ms; TI = 180ms; flip angle = 90°). The field of view for the EPI dataset was 240mm, and the matrix size was 128 × 128, with a resultant in-plane voxel size of 1.875mm.
fMRI data analysis
The fMRI data were analysed using an in-house non-parametric software package (XBAM_v3.2) which uses standard preprocessing steps: realignment, normalisation, baseline correction, spatial smoothing, and GLM parameter estimation using a combination of gamma variate basis functions (for details see Brammer et al., 1997; Bullmore et al., 1999, 2001; Suckling and Bullmore, 2004). The data were realigned to minimise artefacts due to subject motion. First, a template was computed by averaging the image intensity over all time points at each voxel. The 3D volumes at each time point for each participant were then realigned to the template by computing the rigid body motion parameters (3 rotations, 3 translations) that maximised the correlation between each volume and the template. Normalisation was conducted using an affine transform and by computing the parameter set that maximised the correlation between the template image (in standard space—Talairach and Tournoux) and the image to be normalised. The data were then smoothed using a Gaussian filter (FWHM 7.2mm). Experimental responses were then analysed by convolving the experimental design with two gamma variate functions (peak responses four and eight seconds) with delays chosen to span the likely range of BOLD delays and computing the least squares fit of the resulting convolution to the time series at each voxel. A goodness of fit statistic was derived by calculating the ratio between the sum of squares due to the model fit and the residual sum of squares (SSQ ratio). The value of this statistic was then tested for significance using the wavelet-based time series permutation method (Bullmore et al., 2001; Suckling and Bullmore, 2004).
Group analysis
Data were transformed into standard space (Talairach and Tournoux, 1988). Voxel size in standard space was 3.3 × 3.3 × 3.3mm. Significant activations were identified using data-driven significance testing of the median activations at each voxel over all members of the group (Brammer et al., 1997). Median statistics were used to minimise outlier effects in the group sizes normally used in fMRI studies. Analysis was extended to the cluster level with the clusterwise false positive threshold set to less than one across the whole brain (Bullmore et al., 1999). Since the XBAM analysis method takes into account first level as well as second level variance, it resembles what Thirion et al. (2007) have called a “pseudo mixed effects analysis”.
Group differences
Differences in activation between groups and conditions were assessed by fitting the following linear model to the data at each voxel, Y = a + bX + e, where Y is the vector of BOLD effect sizes for each individual, X is the contrast matrix for the particular inter-condition/group contrasts required, a is the mean effect across all individuals in the various conditions/groups, b is the computed group/condition difference, and e is a vector of residual errors. The model was fitted by minimising the sum of absolute deviations to reduce outlier effects. The null distribution of b was computed by permuting data between conditions (assuming the null hypothesis of no effect of experimental condition) and refitting the above model. Group difference maps were computed as described above at voxel or cluster level by appropriate thresholding of the null distribution of b.
Conjunction analysis
Conjunction analyses were carried out to identify brain regions in which there was consistent activation across tasks. First, the minimum SSQ ratio (effect/error) at each voxel across conditions was determined. This measure was then tested (at appropriate voxelwise and clusterwise p-values), as described above under Group analysis, to determine whether it was significantly different from zero. Brain areas showing significant levels of activation were considered to show significant conjunctions of brain activation.
Results
Behavioural data
See Table 2 for accuracy and reaction time data.
Deaf participants only
A mixed-model ANOVA was conducted on the accuracy data (Task (rhyme/location/control) × Group (native/non-native signers)). A main effect of Task indicated that the control task was performed better than both experimental tasks (F(2,36) = 25.5, p < 0.0005). There was no significant effect of Group and no interaction. Excluding the control task from the ANOVA yielded no significant main effects and no interaction. Thus, deaf native and non-native signers were equally accurate on both the rhyme and location tasks.
The same mixed-model ANOVAs were applied to the reaction time data. Deaf participants were faster on the control than experimental tasks (F(2,36) = 211.7, p < 0.0005). There were no further significant effects. When the control task was omitted from the model, a main effect of Task (F(1,18) = 9.7, p < 0.01) indicated faster reaction times to the rhyme than location task.
All deaf versus all hearing participants performing the rhyme task
A mixed-model ANOVA was conducted on the accuracy data (Task (rhyme/control) × Group (deaf/hearing)). A main effect of Task indicated better performance in the control than rhyme task (F(1,42) = 52.5, p < 0.0005). A main effect of Group indicated better performance by hearing than deaf participants (F(1,42) = 13.4, p < 0.002). This was qualified by a significant interaction (F(1,42) = 11.4, p < 0.005) indicating that the hearing group performed better than the deaf group on the rhyme task, with no difference on the control task.
With regard to the reaction time data, a main effect of Task (F(1,42) = 744.7, p < 0.0005) indicated faster responses on the control than rhyme task. A significant interaction (F(1,42) = 11.5, p < 0.005) indicated slower performance by deaf than hearing participants to the rhyme task, but no group difference on the control task.
fMRI data
Rhyme and location similarity judgements in deaf participants only
To identify neural systems involved in phonological processing of sign and speech in the deaf group, data from all deaf participants were combined. Analysis of the rhyme (English) and location (BSL) tasks separately, relative to the control task (voxelwise p = 0.025; clusterwise p = 0.01), resulted in remarkably similar patterns of activation (see Figs. 3A and B/Table 3).
A conjunction analysis was performed to clarify the overlap in activation between the two phonological tasks (English rhyme and BSL location) in deaf participants (voxelwise p = 0.05; clusterwise p = 0.025). As in the individual task analyses, a network consisting of three regions was identified. The most extensive activation was in the left frontal cortex (19.41cm3 volume; X = − 40, Y = 30, Z = 17; these Talairach and Tournoux coordinates, and those reported in the text to follow, represent local maxima). This extended from the insula, through the inferior and middle frontal gyri into the ventral precentral gyrus. The second significant activation extended from the superior portion of the supramarginal gyrus (SMG) into the superior parietal lobule (SPL) and the precuneus (11.28cm3 volume; X = −29, Y = −67, Z = 40). Finally, significant activation was identified in the medial portion of the superior frontal gyrus (SFG), incorporating the anterior cingulate (7.37cm3 volume; X = 0, Y = 1, Z = 50). These data suggest that a left-lateralised network of three regions is engaged by deaf participants performing a phonological similarity judgement task, regardless of whether the task is performed in English or BSL.
Differences between the rhyme and location tasks and the effect of age of BSL acquisition in deaf participants
To determine the differences between the networks recruited during the rhyme and location judgement tasks and to examine the effect of age of signed language acquisition, a mixed-model ANOVA was conducted. This included Task (rhyme/location) as a within subjects factor and Age of BSL Acquisition (native/non-native) as a between subjects factor (voxelwise p = 0.025; clusterwise p = 0.005). The main effect of Task showed that two regions were recruited to a greater extent for the rhyme than location task. These were the left dorsal IFG, extending into the precentral gyrus (4.13cm3 volume; X = − 51, Y = − 4, Z = 40; BA 6), and the medial portion of the SFG, at the junction with the anterior cingulate (2.30cm3 volume; X = 0, Y = − 11, Z = 53; BA 6). In contrast, a region in the left parietal lobe was recruited to a greater extent for the location than rhyme task (see Fig. 4). This extended from the superior portion of the SMG, into the SPL and medially to include the precuneus (5.10cm3 volume; X = − 4, Y = − 70, Z = 43; BA 7).
No regions were recruited to a greater extent by native than non-native signers. In contrast, non-native signers recruited the left inferior frontal cortex to a greater extent than native signers (see Fig. 5A; 5.32cm3 volume; X = − 40, Y = 19, Z = 30). This activation extended from the IFG (BA 44/45), into the middle frontal gyrus and precentral gyrus. Follow-up analyses were conducted comparing native and non-native signers on the rhyme and location tasks separately (voxelwise p = 0.025; clusterwise p = 0.005). These analyses confirmed that non-native signers engaged the posterior IFG more than native signers, during both the location task (3.45cm3 volume; X = − 40, Y = 15, Z = 30) and the rhyme task (3.74cm3 volume; X = − 40, Y = 7, Z = 23).
A significant Group × Task interaction was also identified, the focus of which was at the junction of the left IFG (BA 44), the precentral gyrus (BA 6) and the middle frontal gyrus (BA 9; see Fig. 5B; 2.44cm3 volume; X = − 43, Y = 19, Z = 30). Follow-up analyses (voxelwise p = 0.025; clusterwise p = 0.005) demonstrated that there was no significant difference in the extent to which non-native signers recruited this region during the rhyme and location tasks. In contrast, native signers engaged this region more during the rhyme task, performed in English which they learned late, than the location task, performed in their native language (2.87cm3 volume; X = −47, Y = 0, Z = 36, precentral gyrus (BA 6)). The medial portion of the SFG, at the junction with the anterior cingulate, also demonstrated the same effect (2.16cm3 volume; X = 0, Y = 11, Z = 53).
Rhyme similarity judgements in hearing participants (voxelwise p = 0.025; clusterwise p = 0.01)
Hearing participants performing the rhyme task engaged four regions (see Table 3): [1] the left prefrontal cortex extending from the insula, through inferior and middle frontal gyri and into the precentral gyrus, [2] the superior portion of the SMG, extending into the SPL and medially into the precuneus, [3] the anterior medial portion of the SFG and superior portions of the anterior cingulate, and [4] the right inferior occipital gyrus extending into the fusiform gyrus and incorporating superior parts of the cerebellum.
The pattern observed in hearing participants performing the rhyme task was similar to that observed in deaf people performing the rhyme and location tasks. To clarify the overlap in regions recruited during phonological similarity judgements a conjunction analysis was conducted on the data from deaf and hearing participants performing the rhyme task and deaf participants performing the location task (voxelwise p = 0.05; clusterwise p = 0.01). Not surprisingly, given the individual group patterns, this analysis identified three regions as being significantly activated across all tasks/groups: the dorsal portion of the left IFG, extending into the middle frontal gyrus (14.81cm3 volume; X = −40, Y = 7, Z = 33 BA 44/9); the left SPL (5.82cm3 volume; X = −29, Y = −63, Z = 46 BA 7) and the medial portion of the SFG (5.61cm3 volume; X = 0, Y = 11, Z = 50 BA 6). These regions appear to make up a core network involved in phonological processing of both signed and spoken language, recruited by both deaf and hearing participants.
Deaf versus hearing participants performing rhyme task, matched for performance
To determine the effect of hearing status on the neural system supporting phonological processing, we contrasted activation patterns in deaf and hearing participants performing the rhyme task. Since group performance on the rhyme task was poorer in deaf than hearing participants, subsets of 12 participants were selected from each group who were matched on accuracy and reaction time on the rhyme task performed in the scanner. To further control for differences between deaf and hearing participants the subgroups were also matched for age, non-verbal IQ, reading age, and accuracy and reaction time on a more extensive test of rhyme awareness, run prior to the scan session. There were no significant differences between the two groups on any of these variables (all p-values > 0.1; see Table 4).
A between subjects ANOVA (voxelwise p = 0.05; clusterwise p = 0.005) indicated no regions in which hearing participants showed greater activation than deaf participants. The deaf subgroup showed greater activation than the hearing subgroup in the left IFG, extending into the middle frontal and the precentral gyri (7.01cm3 volume; X = −40, Y = 0, Z = 33; BA 44/6) and in a small portion of the SFG, at the junction with the anterior cingulate (1.29cm3 volume; X = − 4, Y = 4, Z = 50; BA 6/32). Further analyses confirmed that the same pattern was observed when deaf native signers and deaf non-native signers were compared separately to matched hearing participants. This suggests that combining native and non-native signers, in order to carefully match subgroups of deaf and hearing participants, did not influence the outcome of this analysis.
Discussion
Our results demonstrate that a very similar neural network supports phonological similarity judgements made in both English and British Sign Language (BSL). Given that these languages operate in such different modalities, these data suggest that this phonological processing network is multimodal or possibly to some extent supramodal: that is, involving representations that in some way ‘transcend’ the sensory modalities (see Fowler, 2004 for discussion). This network, which was also recruited by hearing people making rhyme judgements, consists of the medial portion of the superior frontal gyrus (SFG), the left superior parietal lobule (SPL) incorporating the superior portion of the supramarginal gyrus (SMG), and, most extensively, the left posterior inferior frontal gyrus (IFG) extending into the ventral precentral gyrus. We do not argue that these regions are dedicated to phonological processing. Rather we argue that they act together as a network to support phonological similarity judgements and other linguistic and, it is likely, non-linguistic processes (see Corina and Knapp, 2006). Nevertheless, our data are consistent with prior demonstrations, concerning semantic and syntactic processing, that modality has relatively little influence on the neural systems that support language (Neville et al., 1998; Petitto et al., 2000; Braun et al., 2001; Emmorey et al., 2002; MacSweeney et al., 2002b; Corina et al., 2003; MacSweeney et al., 2006). Demonstrating this in the context of phonological processing is even more striking since awareness of phonology is more directly linked to sensory input (which differs for sign and speech) than either semantic or syntactic processing.
Although the observed network is recruited by both signed and spoken language, we demonstrate that it does not perform identically across languages or groups. Recruitment of different parts of this network is modulated by age of first language acquisition, language modality and hearing status. The impact of age of first language acquisition was explored by comparing deaf native and non-native signers. Non-native signers engaged the left posterior inferior frontal cortex to a greater extent than native signers. This was the case not only during the task performed in BSL, of which both groups had different language experience, but also during the task performed in English, of which both groups had similar experience. The differential recruitment of the left posterior IFG is even more striking given that native and non-native signers were matched on non-verbal IQ, English vocabulary score and reading age and that there were no significant group differences in accuracy or reaction time on the two phonological tasks. These are the first neuroimaging data to demonstrate the impact of age of acquisition of a first language in the brain. Lack of exposure to a fully accessible language early in life has implications for the neural systems supporting not only that language, but also for languages learned subsequently, whether signed or spoken. In conjunction with the behavioural data of Mayberry and colleagues (Mayberry et al., 2002; Mayberry and Lock, 2003) these data highlight the importance of early exposure to an accessible language for those born profoundly deaf. Even when signed, early language leads to the normal establishment of language systems that may then be used to facilitate a later learned language.
Enhanced recruitment of the left posterior IFG has previously been reported during grammaticality judgements performed by late in contrast to early learners of German (Wartenburger et al., 2003) and during semantic judgement tasks in low- in contrast to high-proficiency late language learners (Chee et al., 2001; Wartenburger et al., 2003). Regions within the left IFG are differentially modulated not only by age of language acquisition and proficiency level, but also by extent of language use (Perani et al., 2003), age at time of testing, and task demands (Tatsuno and Sakai, 2005). Thompson-Schill et al. (2005) argue that the left IFG is increasingly engaged as selection demands increase. In particular, it is argued that this region is involved in regulating the cognitive control necessary to resolve competition between incompatible responses (Snyder et al., 2007). It is possible that selection demands increase for bilinguals because responses from both first and second languages are available. This situation applies to native signers (first language: BSL; second language: English), but may apply to a greater extent to non-native signers. Deaf non-native signers have knowledge of both BSL and English; however, both languages are acquired late. Despite equivalent behavioural proficiency on our tasks, both languages are likely to be poorly established in non-native signers, leading to greater conflict between potential responses, possibly resulting in enhanced recruitment of the left IFG.
An alternative, phonology-specific argument can also be made for the role of the posterior IFG. It has been argued that different parts of the left IFG may show preferential engagement in different aspects of language processing: phonological (the dorsal region: BA 44/6), syntactic (the more anterior region: BA 45), and semantic (the ventral portion: BA 47) (Fiez, 1997; Price et al., 1997, Poldrack et al., 1999; Bookheimer, 2002; Devlin et al., 2003). While the baseline task used in the current study did not require picture name retrieval, given the relatively long presentation time (5s) it is likely that participants did name these stimuli (cf. Meyer and Damian, 2007). Furthermore, the network we identify in the current study has been reported in numerous previous studies of phonological processing involving written words (e.g., Lurito et al., 2000; Xu et al., 2001; Seghier et al., 2004). The most parsimonious interpretation of the current data is thus in terms of phonological processing. With regard to the left frontal cortex, as in previous studies, it was specifically the posterior portion of the IFG, extending into the ventral premotor cortex within precentral gyrus, that was the focus of activation involved in the phonological similarity matching tasks reported here. Moreover, this region was engaged to a greater extent by deaf participants during the rhyme than location task and more by deaf than hearing participants performing the rhyme task (see also Aparicio et al., 2007), even when behavioural performance was taken into account. To account for these findings, we suggest that when the auditory component of speech is absent, the articulatory/motoric component makes a greater contribution to speech-based phonological processes. A similar explanation may account for the observed increased involvement of the left IFG during reading in children with developmental dyslexia following phonological remediation (e.g., Temple et al., 2003). Further studies with deaf participants are underway to test this hypothesis. We also found that the posterior portion of the left IFG was engaged more by non-native than native signers during tasks performed in both languages. Broca's area, in left posterior IFG, is engaged in sign production, just as it is in speech production (Braun et al., 2001; Corina et al., 2003; Emmorey et al., 2007). One possibility that may account for the effect of age of first language acquisition in this region is that the articulatory component of both speech and sign is less established in deaf non-native than native signers, leading to enhanced recruitment of this region during both tasks.
From our data, it is not possible to distinguish between phonology-specific and cognitive control/selection demands accounts of the differential engagement of the left IFG by native and non-native signers. Indeed both accounts may apply since the area showing differential activation in all of the contrasts reported here involved both the posterior portion of the left IFG and the ventral premotor cortex, in the precentral gyrus. Snyder et al. (2007) propose that the left IFG is involved in cognitive control, while the ventral premotor cortex demonstrates phonology specific properties. The relative role of these regions in language processing, and phonological processing in particular, will be greatly informed by future studies examining different domains of language (phonology, syntax, semantics) within the same group of deaf late language learners, while manipulating age of acquisition and proficiency.
The left parietal lobe was also recruited during both the location task (deaf participants) and the rhyme task (deaf and hearing participants). In all groups and tasks this activation included the superior portion of the supramarginal gyrus (SMG), extending into the superior parietal lobule (SPL) and medially into the precuneus. Previous studies of rhyme judgement of written words by hearing adults also report activation of this area (Lurito et al., 2000; Xu et al., 2001; Seghier et al., 2004; Snyder et al., 2007). Nevertheless, the exact role of this region in phonological processing remains unclear. It has been proposed that this multimodal integration region may be recruited during mapping between orthographic and phonemic representations (Booth et al., 2002; Eden et al., 2004). The fact that the stimuli in the current study were pictures, not written words, does not necessarily pose a problem for this account (but see Katzir et al., 2005). Hearing adults have been shown to engage this region more than children during auditory rhyme decisions (Booth et al., 2004). In addition, deaf people are more accurate and faster to make rhyme judgements when the labels for picture stimuli share orthography, e.g., cat–mat, than when they do not, e.g., chair–bear (Sterne and Goswami, 2000). Both of these lines of evidence suggest that orthographic representations may be activated in both deaf and hearing participants when making spoken language phonological decisions in response to pictures. Further studies are needed to examine this hypothesis and the role of the left parietal lobe in phonological processing.
Whatever the functional role of the left parietal lobe in spoken language phonological processing, a growing number of studies suggest that this area may play a particularly important role in signed language processing (see Corina and Knapp, 2006). Perception of BSL sentences that involve spatial description engage the left inferior parietal lobule (IPL) and SPL to a greater extent than ‘non-spatial’ sentences in deaf native signers (MacSweeney et al., 2002a). Direct stimulation of the IPL induces phonological errors during sign production (Corina et al., 1999). Emmorey et al. (2007) have reported that sign production engages the left IPL (X = −60, Y = −25, Z = 27) and the left SPL (X = −26, Y = −51, Z = 54) more than speech production. Emmorey et al. (2007) propose that the left IPL may be involved in phonological processing while the left SPL may be involved in proprioceptive monitoring of motor output. In the current study, the observed greater activation in deaf signers during the location task than the rhyme task was located between the two foci reported by Emmorey et al. (2007) and incorporated the superior portion of the SMG in the IPL, extending into the SPL (X = −4, Y = −70, Z = 43). Given the nature of the current task, a phonological account of this activation seems more likely than an account based on proprioceptive monitoring. Corina and Knapp (2006) have argued that the left parietal lobe plays a greater role in signed than spoken language processing because signed language can build on the “...prior existence of a general human system for manual action observation and production” (p. 537). Portions of the parietal lobe are particularly attuned to the location of the hands/body in space (Gerardin et al., 2000; Hermsdorfer et al., 2001). Accordingly, this region may be particularly engaged in tasks that focus on these spatial relationships, including those involving sign phonology. Whether this activation is specifically related to linguistic processing or to more general processing of body-related information requires further investigation, using linguistic tasks exploring both comprehension and production, and non-linguistic tasks.
Examining other parameters of sign phonology, e.g., movement and handshape, is also required. It is not possible to claim a straightforward parallel between rhyme in spoken language and any of the parameters of sign phonology. It has been suggested that when any sign parameter is shared, this is more analogous to alliteration than to rhyme (Sutton-Spence, 2004). Location was chosen in the current study because it has been demonstrated to be important in judging sign similarity (Hildebrandt and Corina, 2002) and because, among the phonological parameters of signed languages, it appears to have the smallest inventory, as do vowels, which are the nucleus of the syllable and crucial for rhyme in spoken languages. However, sign phonologists may argue that movement is more analogous to vowels with respect to syllable structure because a sign is ill-formed without movement, just as a syllable is ill-formed without a vowel (Brentari, 1999; Sandler and Lillo-Martin, 2006). Whether different patterns of activation are observed when different sign parameters are examined or whether any form of sublexical analysis of signs elicits activation in the network reported here remains to be seen.
In summary, these data suggest that phonological processing, at least in the context of a phonological similarity judgement task, is to some degree supramodal. We show that a similar neural network supports phonological processing of both signed and spoken language in signed language users born profoundly deaf. Furthermore, this network was also engaged by hearing non-signers performing the similarity judgement task in English. However, different parts of this network were differentially weighted depending upon language modality, hearing status and, most importantly, age of first language acquisition. These data highlight the importance of learning a language, whether signed or spoken, early in life. Early acquisition of a first language is critical not only for processing that language, but also appears to form a base on which subsequently learned languages can successfully build.

phonology
deaf
rhyming
sign language
inferior frontal gyrus
pictures
age of acquisition
plasticity
phonological awareness


Altered phenotype and gene transcription in endothelial cells, induced by Plasmodium falciparum-infected red blood cells: Pathogenic or protective?

Severe malaria is associated with sequestration of Plasmodium falciparum-infected red blood cells (PRBC) in the microvasculature and elevation of intercellular adhesion molecule-1 (ICAM-1) and TNF. In vitro co-culture of human umbilical vein endothelial cells (HUVEC), with either PRBC or uninfected RBC, required the presence of low level TNF (5 pg/ml) for significant up-regulation of ICAM-1, which may contribute to increased cytoadhesion in vivo. These effects were independent of P. falciparum erythrocyte membrane protein-1 (PfEMP-1)-mediated adhesion but critically dependent on cell–cell contact. Further changes included increases in IL8 release and soluble TNF receptor shedding. Microarray analysis of HUVEC transcriptome following co-culture, using a human Affymetrix microarray chip, showed significant differential regulation of genes which defined gene ontologies such as cell communication, cell adhesion, signal transduction and immune response. Our data demonstrate that endothelial cells have the ability to mobilise immune and pro-adhesive responses when exposed to both PRBC and TNF. In addition, there is also a previously un-described positive regulation by RBC and TNF and a concurrent negative regulation of a range of genes involved in inflammation and cell-death, by PRBC and TNF. We propose that the balance between positive and negative regulation demonstrated in our study will determine endothelial pathology during a malaria infection.
1
Introduction
Pathogenesis of severe malaria has stirred considerable interest over the years, however there are many questions at the mechanistic level that remain unanswered. Severe malaria is characterised, in part, by sequestration of Plasmodium falciparum-infected red blood cells (PRBC) at microvascular sites in the brain tissue, leading ultimately to coma and subsequent death. There is evidence that the sequestration of PRBC on the endothelial surface can result in loss of integrity, thus compromising blood–brain barrier function either directly (Brown et al., 1999a,b, 2001a), by indirect mechanisms including binding via platelets (Wassmer et al., 2004; Combes et al., 2006) or by the production of microparticles from endothelial cells (EC) activated by adhering PRBC (Combes et al., 2005, 2006), and also cytokine-driven modulation of endothelial cell metabolism, but that this is usually a small, transient effect in vivo.
One question is the mechanism underpinning the accumulation of PRBC leading to micro-vascular occlusion as seen in post mortem cerebral malaria (CM) brain tissue, which is believed to be a progressive phenomenon of PRBC sequestration. We suggest that the initial sequestration of PRBC, if maintained for a prolonged period of time, has the ability to activate the endothelium to promote sequestration, leading to deleterious effects on the host. Our studies investigate the direct effects on the endothelium of PRBC retention for prolonged periods of time.
First, sustained exposure of the endothelium to PRBC can result in modulation of the endothelium, thus increasing its responsiveness to low levels of TNF (TNFlow). This may contribute to promoting further cytoadhesion in microvasculature containing sequestered PRBC. This hypothesis is based on previous evidence of endothelial cell activation by abnormal red blood cells in various conditions, including sickle cell disease, diabetes and also malaria (Shiu and McIntire, 2003). Sickle cell RBC (sRBC), diabetic RBC (dRBC) and also PRBCs can all induce expression of adhesion molecules such as intercellular adhesion molecule-1 (ICAM-1) and vascular adhesion molecule-1 (VCAM-1) and E-selectin (Brown et al., 2001b; Shiu and McIntire, 2003; Viebig et al., 2005; Tripathi et al., 2006). In addition, recent co-culture studies have demonstrated PRBC-induced increases in the activity of pro-apoptotic genes involved in the caspase pathway (Pino et al., 2003). Other changes induced on EC by sRBCs include induction of endothelin and prostacyclin production (Shiu et al., 2002) and by PRBC include increased expression of pro-inflammatory genes (Pino et al., 2003) and release of IL6 (Viebig et al., 2005).
Serum levels of IL8 were elevated in severe malaria compared with healthy volunteers (Lyke et al., 2004), correlated with parasite count and severity of disease at the time of admission (Burgmann et al., 1995) and there were no apparent differences between febrile and a-febrile volunteers (Hermsen et al., 2003). IL8 is an endothelial-derived acute response activation marker. Prestored IL8 is exocytosed at a basal level from Wiebel palade bodies in ECs and is rapidly released in response to various stimuli (Wolff et al., 1998; Utgaard et al., 1998; Oynebraten et al., 2004).
Exposure of ECs to sRBCs in vitro resulted in increased sensitivity to the pro-inflammatory cytokine IL1β (Shiu et al., 2000). We propose that local increases in TNF levels occur in the microvasculature in early stages of infection, during shizogony (Bisser et al., 2006). In a similar fashion to that observed with sRBCs, contact between PRBCs and the endothelium could potentially sensitise the ECs to TNF. There is evidence for an important role for TNF receptors (TNFR) in CM pathology, however, most of this comes from studies on animal models. Lucas et al. (1997a) showed a close correlation between absence of TNFR II expression and protection from CM-associated brain damage in TNFR II knock-out mice, while TNFR II was up-regulated on brain endothelium in CM-susceptible mice (Lucas et al., 1997b). Up-regulation of the soluble TNFR I, which is the predominant type in human serum, was reported in the serum of patients with acute P. falciparum infection (Wenisch et al., 1994). Interestingly, EC from CM-susceptible mice had a greater sensitivity to TNF than that of CM-resistant mice. TNF induced up-regulation of TNFR I and II together with an associated increase in IL6, ICAM-1 and VCAM-1 to a greater extent in CM-susceptible mice than in CM-resistant mice (Lou et al., 1998). In addition, there was an absence of ICAM-1 up-regulation in TNFR II knock-out mice, suggesting a link between TNFRs and ICAM-1 up-regulation during malaria infection (Lucas et al., 1997a).
Our aim was to investigate the ability of PRBC to modulate the endothelium in the presence and absence of the inflammatory cytokine, TNF, in a co-culture system. Firstly, functional markers of EC modulation included endothelial expression of ICAM-1, which has been attributed a critical role in parasite adhesion, and the release of IL8. Changes in levels of TNFR I and II, were also investigated as a potential mechanism for any changes in the sensitivity of EC to TNF. Second, we sought to assess the global transcriptional changes in ECs and elucidate the regulation of cellular processes following co-culture under the same conditions, using a human genome Affymetrix (Affymetrix, Santa Clara, CA, USA; http://www.affymetrix.com) chip.
Our results have led us to propose a novel mechanism for the modulation of the endothelium during malaria infection that is dependent on low level TNF and involves a pro-inflammatory component but also a concurrent down-modulation of RBC-induced inflammation due to the presence of the parasite within the infected cell.
2
Materials and methods
2.1
Malarial parasites
Plasmodium falciparum ItG strain was derived from the Brazilian line IT4/25/5 (Ockenhouse et al., 1992). This strain was used for the PRBCs in these studies. The ItG strain is a strong ICAM-1 binder and also binds to CD36 (Gray et al., 2003). The PRBCs were cultured in RPMI-1640 supplemented with 2 mM l-glutamine, 37.5 mM N-2-hydroxyehtylpiperazine-N′-2-ethanesulfonic acid (Hepes), 10 mM glucose, 25 μg/ml gentamicin and 10% human serum, at pH of 7.2 (Trager and Jensen, 1976). All reagents were obtained from Sigma, UK. Human serum was isolated from whole blood obtained from the Royal Liverpool Hospital and was approved by the Liverpool School of Tropical Medicine Ethical Committee.
2.2
Endothelial cells
Pooled human umbilical vein endothelial cells (HUVEC) were obtained from Promocell (Heidelberg, Germany), HUVEC from different batches were used for each experiment, at passages three to five. HUVEC were grown to confluence on 1% gelatin (Sigma, UK) coated flasks and plates. All co-culture experiments were performed in serum-depleted basal HUVEC medium (quiescing medium) which consisted of M199 (Invitrogen, UK) containing 1% FCS. These conditions were designed to increase the signal window, while maintaining the integrity of the HUVEC monolayer (i.e. there was no indication of cell apoptosis or necrosis during the experiments).
For all co-culture studies, ECs were co-cultured with PRBCs and uninfected RBCs in the absence and presence of TNFlow. The sub-optimal dose was verified in separate TNF dose response studies; 5 pg/ml was 1/100th of the dose of TNF used as standard for optimal induction of ICAM-1 on HUVEC in our laboratory (0.5 ng/ml), and had no significant effect on ICAM-1 expression (data not shown). For the positive control a high dose of TNF (TNFhigh) was used (10 ng/ml) to stimulate the HUVEC, while medium alone served as a negative control. All parasite and EC cultures were regularly monitored for mycoplasma using the Takara PCR mycoplasma detection kit (Cambrex Biosciences).
2.3
PRBC-EC co-culture conditions
HUVEC grown to confluence in either 24-well plates or 25 cm2 flasks, for functional studies and microarray studies, respectively, were co-cultured with PRBCs and uninfected RBCs in the absence and presence of TNFlow at 37 °C. The RBC suspension was adjusted to 1% haematocrit. PRBC at the trophozoite stage (20–28 h post-invasion) were used in all co-culture studies; for the functional studies the parasites were synchronised using sorbitol, while for the microarray studies the trophozoites were additionally enriched using plasmagel flotation. In selected experiments, the parasites were retrieved after the 20-h, stained with giemsa and examined by light microscopy. There was no apparent rupture of RBC or change in the parasite stage over this period. For all functional studies the PRBCs were at a parasitaemia of 3% and co-cultured with HUVEC for 20 h. For microarray studies, the PRBCs were enriched on Plasmagel to parasitaemia ranging between 50% and 60% and co-cultured for 6 h. The uninfected RBCs were from the same batches used for parasite culture and were maintained under the same conditions as PRBCs, in separate flasks.
2.4
RNA expression: microarray analysis
Following incubation, the supernatant was aspirated, HUVEC was washed with cold RPMI-1640 and then with 0.02 M EDTA to remove the adherent RBCs and the cells harvested using Trizol (Invitrogen, UK). RNA integrity was evaluated by electrophoresis on a 1% agarose gel and by spectrophotometry using the absorbance ratio at 260/280 nm.
Five micrograms of each complementary biotin-labelled RNA was hybridised on the Affymetrix GeneChip, Human Genome version 2, HGU133plus2.0 (Santa Clara, CA), according to the manufacturer’s instructions. The signal intensity for each feature on the array was determined using the 70th percentile method provided by GCOS software (Affymetrix). Hybridisations were performed for four replicates of each of the seven conditions (control, RBC, PRBC, RBC + TNFlow, PRBC + TNFlow, TNFlow and TNFhigh).
Data analysis was performed using Bioconductor (Gentleman et al., 2004). The microarrays were pre-processed using a Robust Multiarray Averaging program (Irizarry et al., 2003). The expression values were calculated using the R statistical computing environment (http://www.r-project.org/) with the “affy” package (Gautier et al., 2004). The differential expression was assessed and variability estimated by fitting a linear model to the data that fully models the systematic part of each gene, using the “limma” package. From the “limma” output, log-fold changes from one condition compared with another, P-values corrected for a 5% false discovery rate (Hochberg and Benjamini, 1990), together with B-statistic (log-odds that a gene is differentially expressed) can be obtained and used to determine up- and down-regulation of genes. Due to the complexity of the microarray design (i.e. four replicates, seven conditions); for non-hierarchical clustering, the 47,000 transcripts present on the human chip were filtered down to 8105, based on their moderated F-statistic at P-value <0.001. These were then clustered by similarity. The unsupervised clustering program enabled us to discriminate biological clusters (ArrayMiner, OptimalDesign). For each cluster Gene Ontology (GO; http://www.geneontology.org) assignments were extracted using the GOstats package (http://bioconductor.org/packages/1.9/bioc/html/GOstats.html). The gene list of each cluster was used to identify all the unique GO terms in order to determine whether genes that comprise a given cluster have a common function, process or location in the cell. For each GO term, GOstats analysed whether that term was being significantly over-represented in the data, using a P-value cut-off of P ⩽ 0.05.
2.5
ICAM-1 protein expression
HUVEC grown to confluence in 24-well plates were co-cultured with PRBC and uninfected RBC at a haematocrit of 1% and a parasitaemia of 3% and suspended in M199 supplemented with 1% FCS in the absence and presence of 5 pg/ml TNF (TNFlow) for 20 h at 37 °C. Following the incubation period, the supernatant was removed, centrifuged at 300g for 3 min to remove any RBCs and stored at −80 °C.
The HUVECs were washed once with cold RPMI-1640 and then with 0.02 M EDTA to remove the adherent RBCs and subsequently harvested by trypsinisation for analysis by flow cytometry. FACS ICAM-1 expression on HUVEC was determined by staining the cells using a fluorescein isothiocyanate (FITC)-conjugated mouse anti-human ICAM-1 antibody (MCA1615F; Serotec) using standard staining protocols and the cells fixed in 2% paraformaldehyde and analysed by flow cytometry. ICAM-1 expression was expressed as geometric mean of the fluorescence intensity.
2.6
IL-8 and TNF receptor expression
The supernatants stored from the co-culture studies were analysed using a standard sandwich ELISA kit (IDS), using a horse-radish peroxidise based colorimetric detection system, to quantify IL8 released from ECs. IL8 production was expressed as a concentration in pg per ml.
Similarly, soluble TNFR I, sTNFR I (p55) and soluble TNFR II, sTNFR II (p75), were detected using sTNFR I (KAC1761) and sTNFR II (KAC1771) ELISA kits (Biosource). TNFR level was expressed as TNFR concentration in ng per ml.
In order to understand the kinetics of TNFR expression on the surface of ECs in response to co-culture with PRBCs, the ECs were co-cultured with PRBCs and uninfected RBCs for 0.5, 1, 2 and 3 h. Following the incubation period, HUVECs were harvested and dual stained for surface TNFRs with monoclonal anti-human RII-FITC (FAB226F) and monoclonal anti-human RI-PE (FAB226F) antibodies (R&D Systems Europe). The receptor expression was expressed as the geometric mean of the fluorescence intensity.
2.7
Trypsin digestion of RBC
The ability of PRBCs to induce changes in surface ICAM-1 levels following trypsinisation was determined. PRBCs and uninfected RBCs were washed twice with PBS and incubated with 0.1 mg/ml trypsin in PBS for 15 min at room temperature with gentle mixing (modified from Chaiyaroj et al., 1994). After incubation the trypsin was inhibited with FCS at a final concentration of 10%. Conditions for trypsinisation were optimised to prevent cell lysis and the cells were stained with giemsa before and after trypsinisation to confirm RBC integrity was maintained. The RBCs were washed three times in PBS and resuspended in M199 supplemented with 1% FCS and co-cultured with HUVEC, as described.
We also analysed adhesion of PRBCs to microslides coated with 50 μg/ml Fc-tagged recombinant ICAM-1, ICAM-1-Fc (Gray et al., 2003), under laminar flow conditions at shear stress of 0.05 Pa, before and after trypsinisation, in order to evaluate PfEMP-1 mediated cytoadhesion.
2.8
Transwell experiments
Confluent HUVECs were co-cultured with PRBCs separated using a 0.4 μm transwell filter (Falcon), which prevents contact between HUVECs and RBCs but allows soluble factors to diffuse through. This set-up allowed us to determine whether contact between RBCs and ECs was necessary for induction of ICAM-1 expression on the ECs.
3
Results
3.1
Up-regulation of ICAM-1 expression following co-culture with infected and uninfected RBC
ICAM-1 is expressed constitutively at low levels on the surface of HUVEC in culture. Neither PRBCs nor uninfected RBCs was capable of inducing appreciable ICAM-1 expression over 20 h (Fig. 1). However, exposure to both PRBCs and TNFlow simultaneously, resulted in significant up-regulation of ICAM-1 expression (P < 0.05). TNFlow alone was incapable of inducing ICAM-1 expression (Fig. 1).
3.2
Up-regulation of IL-8 release following co-culture with infected and uninfected RBC
Following incubation with either PRBCs or uninfected RBCs for 20 h, IL8 levels in the supernatant were increased over basal levels (P < 0.01) (Fig. 2). When the HUVECs were concurrently exposed to PRBCs and TNFlow, IL8 release was further amplified over basal levels (P < 0.0002). Uninfected RBCs in combination with TNFlow induced similar levels of IL8 release (P < 0.001) (Fig. 2).
3.3
Up-regulation of soluble TNF receptor release and down-regulation of surface expression following co-culture with infected and uninfected RBC
Soluble forms of both TNFR I (p55) and TNFR II (p75) were significantly increased by 35% (P < 0.05) following treatment with either PRBCs or uninfected RBCs for 20 h. Thus, the phenomenon of soluble receptor release from the surface of ECs, when co-cultured with RBCs, appeared to be independent of the parasite (Fig. 3a and b).
Surface levels of the TNFRs were monitored over 3 h to understand the dynamics of TNFR expression. Both TNFR I and TNFR II were significantly reduced in response to both PRBCs and uninfected RBCs by 70% (P < 0.05) and 50% (P < 0.01), respectively, within 30 min (Fig. 4a). Interestingly, the levels of the TNFR I, but not TNFR II, fell over time under basal conditions, albeit at a slower rate than co-culture with RBCs. This could be a result of serum depletion when complete medium was replaced with M199/1% FCS for the duration of the co-culture experiment. In the case of both receptors, the observed down-regulation in response to RBCs was significantly greater than that seen under basal conditions.
3.4
Loss of ICAM-1-mediated adhesion phenotype following trypsinisation of PRBC
Following trypsinisation, PRBCs did not lose the ability to up-regulate ICAM-1 expression on co-culture with ECs (Fig. 5a). As before, both PRBCs and uninfected RBCs induced an increase in surface levels of ICAM-1 in the presence of TNFlow. ICAM-1 mediated adhesion under laminar flow, however, was abolished following trypsin treatment of PRBCs (Fig. 5b). In additional experiments, when the PRBCs were separated from the ECs in 24-well plates using 0.4 μm transwell inserts, there was no stimulation of ICAM-1 expression (data not shown). Thus, the EC activation observed in our system was critically dependent on cell–cell contact, although it did not involve specific PfEMP-1-mediated cytoadherence.
3.5
Modulation of the endothelial cell transcriptome following co-culture with infected and uninfected RBC
Using ArrayMiner software (OptimalDesign), seven non-hierarchical clusters were identified (Fig. 6a). As illustrated on the resulting heatmap, there is minimal change in the gene expression profiles with either PRBCs or RBCs compared with controls (Fig. 6b). However, when HUVECs were exposed to either PRBCs or RBCs in combination with TNFlow, differential expression was visible in three out of the seven clusters, compared with control or TNFlow alone (Fig. 6a and b).
A comprehensive analysis of the microarray data was performed and has been submitted to Array Express (Accession No. E-SGRP-3). Our analysis focuses on genes that were differentially and significantly expressed at P < 0.001, compared with control levels. We have concentrated on over-represented gene ontologies and cited genes that best exemplify these GO terms.
In cluster 3, both PRBCs and uninfected RBCs, in combination with TNFlow, produced over-expression (Fig. 6a and b). TNFlow alone, however, produced a significant under-expression. Genes in this cluster included the inflammatory protease, caspase 1, the acute response cytokine, IL8, inflammatory cytokines IFN-γ and lymphotoxin β, adhesion molecules ICAM-1, E-selectin and chemokines, CXCL2, CXCL3, CX3C1 and CXCL6.
In clusters 1 and 2, opposing effects were induced when HUVECs were exposed to either PRBCs or RBCs in combination with TNFlow. Over-expression of genes was observed in response to uninfected RBCs and TNFlow and conversely, PRBCs and TNFlow resulted in under-expression of genes in these clusters (Fig. 6a and b).
In cluster 1, TNFlow on its own had no effect compared with controls, while in cluster 2 TNFlow alone produced a small reduction in gene expression (Fig. 6b). Genes in cluster 1 included the protease calpain 13, toll-like receptor-6 and the junction protein desmocollin 2, while genes in cluster 2 included the junction protein decorin, MHC class II, transferrin, endothelin 3 and endothelin receptor type A. While it is difficult to extrapolate roles for these genes from this in vitro analysis of the transcriptome, we can make some speculations based on recent studies. For instance, transferrin induction may be a mechanism for iron homeostasis to prevent accumulation of iron in endothelial cells which can lead to oxidative damage of the cells (Nanami et al., 2005). Endothelin is a known vasoconstrictor, in vivo; down-regulation of endothelin and its receptor may be a mechanism for maintaining vascular tone and integrity during malaria infection (Basilico et al., 2004). Down-regulation of MHC class II may represent suppression of the host immune response by the parasite.
The genes in each cluster were further analysed and categorised by GO) terms using the GOstats package of R/Bioconductor to understand their basic biological functions. The over-represented GO terms, defining genes in each cluster, in terms of biological process, cellular component and molecular function, showing ⩾2% of the total number of genes being annotated with that term, were evaluated. Fig. 7 illustrates distribution of the over-represented gene ontologies with respect to biological process and cellular component, in clusters 1 and 2, which reflect inflammatory and protective functions in the endothelial cells. The full analysis for all three clusters is detailed in Supplementary Fig. S1(see on-line supplementary data). Whilst some GO terms fell below the 2% cut-off, it is important to note that they were nonetheless significant and have been tabulated for further information (Supplementary Tables 1, 2 and 3; see on-line supplementary data). A wide range of GO terms were over-represented in each cluster within categories of biological process, cellular component and molecular function, with a number of common and parallel themes, including cell communication, signal transduction, cell adhesion, organismal physiological process, ion transport, response to external stimuli and immune response. Interestingly, the genes in each of these clusters were primarily cell membrane-associated, or related to the extracellular region and the extracellular matrix. The molecular functions of the genes in each cluster were wide ranging, although receptor activity, signal transducer activity, ion channel and protein binding activities were parallel themes in all three clusters.
The fold changes for the 8105 genes were calculated for each of the conditions for visualizing the changes in expression, compared with control levels. Expression of ICAM-1 and IL8 RNA was up-regulated, reaching 3.7-fold and 7-fold, respectively, over control levels (P = 0.001), when HUVECs were incubated with a combination of PRBCs and TNFlow. Interestingly, ICAM-1 transcription reached similar levels in the presence of a combination of uninfected RBCs and TNFlow. Table 1 illustrates the changes in ICAM-1 and IL8 expression under the different co-culture conditions.
Table 2 shows the changes in expression of selected genes which illustrate specific biological processes of ECs that may have a role in mediating either pathology or protection, and their respective fold changes in the presence of PRBCs, uninfected RBCs and TNFlow compared with controls. Although the magnitudes of change are relatively small, they are highly reproducible and biologically significant at P < 0.001, over four separate replicates.
The chemokines, CXCL2 (Gro-β), CXCL3 (Gro-γ), CXCL6 and E-selectin were all over-expressed in the presence of PRBCs and TNFlow, with variable increases in expression of CXCL2 and CXCL6 in the presence of uninfected RBCs and TNFlow (Table 2). Gro-β has been shown to have a role in the adhesion of monocytes to ECs (Schwartz et al., 1994) while CXCL6 has similar properties to IL8 and can be co-induced with IL8 (Gijsbers et al., 2005). E-selectin was also over-expressed in response to PRBCs, uninfected RBCs and TNFlow, reaching up to 7-fold over controls with PRBCs and TNFlow.
Molecules involved in cell adhesion such as ICAM-1 and CX3C1 were both over-expressed in PRBCs, uninfected RBCs, and TNFlow, with a greater effect in PRBCs (Table 2). CX3C1 (fractalkine) has recently been implicated in mediating adhesion of PRBCs to ECs (Hatabu et al., 2003). Other adhesion receptors such as desmocollin 2 and integrin β1 were both under-expressed with PRBCs and TNF, and over-expressed with uninfected RBCs and TNF (Table 2).
A number of inflammatory genes such as MHC class I, superoxide dismutase 2 (SOD 2) and lymphotoxin-β were all over-expressed in the presence of PRBCs and TNFlow (Table 2). Whilst both MHC class I and SOD 2 were also over-expressed with uninfected RBCs and TNFlow, lymphotoxin β was under-expressed.
Table 2 illustrates differential expression of molecules such as TNFR-associated factor 1 (TRAF 1), Fas associated factor 1 (FAF-1), prostaglandin receptor 3 and TGF-β3, which all have a role in signal transduction.
A number of cell apoptosis-related genes were differentially regulated in our co-culture system (Table 3). Both caspase 3 and caspase 9, which are believed to be inducers of apoptosis (Ho and Hawkins, 2005), were under-expressed in the presence of PRBCs and TNFlow. In addition, caspase 3 expression was markedly increased in the presence of uninfected RBCs and TNF. Calpains, which are inducers of cell death via a caspase-independent pathway (Utz and Anderson, 2000; Perrin and Huttenlocher, 2002), were also regulated in our system. We looked at the expression of two calpains, 9 and 13. Calpain 9 was under-expressed and there was a small increase in calpain 13 expression in the presence of PRBCs and TNFlow (Fig. 8). Thus, our data does not suggest induction of apoptosis; in fact, there appears to be a trend towards protection from apoptosis and this was supported by our inability to detect any positive staining with annexin V and the absence of any morphological changes in the ECs after co-culture.
4
Discussion
Sequestration of PRBCs at vascular sites is a critical event in the pathogenesis of severe malaria. Here we have investigated the effect of prolonged exposure to PRBCs on the endothelium. We have demonstrated a phenomenon whereby ECs are differentially modulated when co-cultured with PRBCs in the presence of TNFlow, which could occur at microvascular sites early in infection, for instance during schizogony. Unlike previously published work, in our system there was no apparent induction of ICAM-1 or modulation of RNA transcription by PRBCs alone. Significant de novo ICAM-1 induction and differential regulation of gene transcription were dependent on the presence of low levels of TNF. PRBCs alone did modulate certain EC functions such as IL8 release and TNFR shedding from the cell surface, but IL8 release was further enhanced in the presence of TNFlow.
Up-regulation of ICAM-1 was maintained following removal of surface expressed PfEMP-1 by trypsin digestion, but was abolished when cell–cell contact was prevented. This demonstrated that while cell-to-cell contact was crucial for modulating EC function, there was no requirement for adhesion via specific receptors in this model. Despite the differences in the reported effects of PRBCs on ECs, the unifying theme in all the co-culture studies is this critical requirement for close apposition of the two cell types in the co-culture system, in the induction of EC activation. The transwell system, whilst preventing cell-to-cell contact, allowed the movement of parasite-derived soluble factors. Therefore we could exclude the role of soluble parasite-derived factors in EC activation. In all cases, when the cell–cell contact was compromised using a filter, EC activation was abolished (Randolph and Furie, 1996; Pino et al., 2003; Viebig et al., 2005). Thus the variable observations may reflect differences in the respective co-culture conditions, for instance, studies by Viebig et al. (2005) were performed in complete HUVEC culture medium and studies by Pino et al. (2003) were performed in parasite culture media, while our studies were performed in a serum-depleted basal HUVEC medium in order to enhance the signal window for the EC measurements, whilst maintaining EC integrity. It is clear from our work and that of others, that care will need to be taken in interpreting the results of model co-culture systems and that further work will be required to develop ex vivo models of severe disease. It is possible that no single model will be able to reflect the variable pathology represented in malaria infection. Our study is unique in the observation that concomitant presence of low level TNF is necessary for PRBCs to modulate the endothelium, namely HUVECs. Indeed, a recent study also suggested that PRBCs alone do not have the ability to induce ICAM-1 in HUVECs, and that this may be a phenomenon specific to brain-derived ECs (Tripathi et al., 2006).
Using HUVEC as an in vitro model for studying PRBC-EC interactions in vivo, we have demonstrated that close apposition or cell–cell contact of the PRBCs with ECs is a critical factor in mediating this activation. Whilst uninfected RBCs also had an effect on ECs in the presence of low level TNF, it is noteworthy that in vivo, apposition of uninfected RBCs on ECs only occurs secondary to cytoadhesion or as a result of vessel occlusion. The ability of normal RBCs to stick to and modulate ECs in vitro, however, is not a novel observation. Indeed, normal RBCs can bind to ECs mediated by plasma factors such as fibrinogen and fibronectin (Wautier et al., 1983) and the binding can induce low-grade ICAM-1 expression in vitro (Brown et al., 2001b). RBCs express a wide range of molecules on their surface which have been implicated in mediating adhesion to endothelial cells under different conditions. These include: (i) VLA-4 (alpha4beta1) which can bind to endothelial VCAM-1 (Walmet et al., 2003); (ii) the blood group Lutheran molecule (LU) over-expressed on sRBCs can bind to laminin present on cells or in the intercellular space (Eyler and Telen, 2006); (iii) advanced glycation end products (AGEs) present on RBCs bind to their receptor (RAGE) on endothelium (Wautier and Schmidt, 2004), activating endothelial cells; and (iv) a molecule related to blood group Rhesus, ICAM-4 (Hermand et al., 2003) binds to integrins present on leukocytes (CD11–CD18) and on platelets (alpha2beta4) offering a surface which can be involved in thrombosis (reviewed by Wautier and Wautier, 2004). Thus, although PfEMP-1 does not play a role in the induction of ICAM-1 expression seen by us, it would normally be required to bring the PRBCs and ECs together in vivo.
Contrary to our hypothesis that up-regulation of TNFRs in response to PRBCs contributed to the increased sensitivity to TNF, unexpectedly, we observed significant down-regulation of surface TNFR expression and increased receptor shedding. It is possible that the enhancement of the effects of RBCs is at the level of intracellular signal transduction. Rapid TNFR shedding by cleavage of the extracellular region of the receptors as observed in our studies is a common response to various stimuli (Aderka et al., 1998) and may be a mechanism for down-modulation of both TNF receptors. This rapid release of TNFRs in response to an insult to the endothelium or physical cell contact with the endothelium is believed to be a non-specific pro-inflammatory response and up-regulation of soluble TNFR I has been correlated with parasitaemia in the serum of patients with acute P. falciparum infection (Wenisch et al., 1994). The TNFR shedding seen in response to PRBCs or uninfected PRBCs alone, may be part of a non-specific inflammatory response of ECs to prolonged cell–cell contact. Similarly, IL8 release in our system may also represent a non-specific inflammatory response to cell–cell contact with RBCs, as was demonstrated in a monocyte/EC co-culture model and was further shown to be independent of ICAM-1 mediated binding (Lukacs et al., 1995).
Similarly to our direct measurements of ICAM-1, there was no significant change in EC gene transcription in response to PRBCs or RBCs alone but in combination with TNFlow, significant regulation of the EC transcriptome was induced. Analysis of the transcriptome revealed a wide diversity of gene ontologies representing genes that were significantly regulated, however, care must be taken in interpreting the data since there is a high degree of redundancy across GO terms, which was not accounted for in this analysis. IL8, for instance, has diverse biological roles including cell communication, cell adhesion, signal transduction and immune response. In spite of such deficiencies, the GO terms that were over-represented, including cell communication, cell adhesion, signal transduction, ion transport and immune response, fit well with our hypothesis that the infected RBC is able to modulate the host endothelial response.
From previous work, we had expected to see a pro-inflammatory response induced by PRBCs (cluster 3, Fig. 6b). Less predictable was the down-regulation of genes in the presence of PRBCs and TNFlow (clusters 1 and 2, Fig. 6b), which may represent a parasite-specific adaptive response that favours parasite survival and development by protecting the integrity of the host endothelium. Up-regulation of these genes under the same conditions may result in the induction of a pro-adhesive effect that can potentially feed back to reinforce pathological sequestration that is typically seen in the later stages of severe malaria. In addition, induction of an immune response, as in cluster 3, may confer a protective effect on the host. Thus, we propose that the balance between these converse effects of PRBCs and TNF on the endothelium may be the critical factor in determining the response by endothelium and the clinical outcome of a malaria infection in vivo.
The over-expression of genes in response to uninfected RBCs and TNFlow in two of the clusters, whilst unexpected, is a common phenomenon in static in vitro co-culture studies. For instance, normal RBCs can interact with ECs to induce the expression of a variety of pro-inflammatory molecules including ICAM-1 (Brown et al., 2001b), VCAM-1 (Brown et al., 2001b; Wautier et al., 2001) and activation of NADPH oxidase, which mediates the generation of reactive oxygen intermediates (Wautier et al., 2001). This is a potential mechanism to induce expression of genes to counteract the response to PRBCs and may reflect a partially protective host response during a malaria infection, balanced against inducing a pro-adhesive environment, particularly early in infection when systemic inflammation is unlikely to be a major contributor to pathogenesis.
Modulation of host cells has been demonstrated in other co-culture models, for instance tyrosine phosphorylation of scyncitiotrophoblasts in a model of placental malaria (Lucchi et al., 2006) and ecto-phosphorylation of CD36 following the initial PRBC attachment which is believed to further enhance CD36-mediated cytoadhesion (Yipp et al., 2003). While co-culture models give useful insights into mechanisms of action of PRBCs on host cells in malaria pathogenesis, care must be taken in the interpretation and extrapolation of this data to pathogenesis in vivo, since these mechanisms may not be reflected in the in vivo situation.
In summary, our co-culture model identifies a novel mechanism whereby PRBCs, whilst mobilizing a pro-inflammatory and a seemingly pro-adhesive effect on the host endothelium, have the additional ability to suppress gene expression pathways involved in signal transduction, apoptosis and immune response as part of a mechanism to support parasite survival through maintaining the overall integrity of the host EC. This fits well with histo-pathological observations in severe malaria where transient dysfunction of the blood–brain barrier is observed (Brown et al., 1999a) but the overall health of the endothelium seems to be maintained despite the presence of many adherent PRBCs (Medana and Turner, 2006). Our suggestion is that the host response to sequestration is complex and involves a balance between pro- and anti-inflammatory pathways, both mediated by apposition of the PRBC, and interacting with other mechanisms of host response to malaria infection variably throughout an infection. This balance is critical to the health of an EC and the resulting pathology associated with severe malaria.

severe malaria
icam-1
co-culture
microarray
vascular endothelium
tumour necrosis factor