Brisk walking compared with an individualised medical fitness programme for patients with type 2 diabetes: a randomised controlled trial

Aims/hypothesis Structured exercise is considered a cornerstone in type 2 diabetes treatment. However, adherence to combined resistance and endurance type exercise or medical fitness intervention programmes is generally poor. Group-based brisk walking may represent an attractive alternative, but its long-term efficacy as compared with an individualised approach such as medical fitness intervention programmes is unknown. We compared the clinical benefits of a 12-month exercise intervention programme consisting of either brisk walking or a medical fitness programme in type 2 diabetes patients.
Introduction
Regular exercise has been identified along with diet and medication as one of the three components of good diabetes therapy [1]. Structured exercise intervention programmes have been reported to be as effective as pharmaceutical strategies in improving glycaemic control [2–5] and/or cardiovascular risk profile [6, 7] in type 2 diabetes patients. Despite the growing body of scientific evidence on the health benefits of exercise intervention, most meta-analyses report a lack of studies that have tried to assess the long-term efficacy of exercise intervention in type 2 diabetes patients [3–5, 7–9]. In general, exercise intervention studies implement endurance and resistance type exercise, supervised by a physical therapist [10–17]. The long-term adherence to these (so-called) medical fitness programmes has been shown to range between 10 and 80% [11, 18–20]. Financial costs per patient are considerable in such programmes. Brisk walking exercise has been proposed as a less expensive alternative, with a good clinical outcome when patients are frequently counselled by motivated, supportive physicians [6, 21, 22]. However, brisk walking programmes mainly consist of endurance type exercise activities. As combined endurance and resistance type exercise training has been reported to be of greater clinical benefit [3, 23], it is conceivable that the long-term efficacy of a medical fitness programme is greater than that of a brisk walking programme.
In the present study, we compared the changes in glycaemic control and cardiovascular risk profile following the prescription of 12 months of either supervised group-based brisk-walking or of a more individualised medical fitness programme in a large population of type 2 diabetes patients (n = 92) in a primary healthcare setting. We report our results for changes in HbA1c values as a primary outcome parameter, with blood pressure, plasma lipid levels, insulin sensitivity by homeostasis model assessment (HOMA), body composition, physical fitness, programme adherence and health-related quality of life as secondary outcome parameters. Given the greater improvements in glycaemic control following combined endurance and resistance type exercise training as opposed to each separately [3, 23], we hypothesised that a medical fitness programme would result in a significantly greater decline in HbA1c than brisk walking.
Methods
Participants
From June till December 2005, 493 patients with type 2 diabetes were preselected from a population of 12,197 patients attending a primary healthcare centre that offers structured and guideline-based [24] diabetes care programmes. After 5 months of active recruitment by two nurse practitioners and four general practitioners, a total of 76 (=15.4%) patients were willing to participate in supervised exercise sessions three times a week for a period of at least 1 year. The type 2 diabetes patients selected had been diagnosed more than 3 months prior to screening according to the WHO criteria [25]. Exclusion criteria were: presence of (silent) cardiac or peripheral vascular disease, orthopaedic limitations and/or diabetic foot ulceration. To increase sample size, the exercise intervention programme was subsequently advertised in local newspapers, which yielded another 26 potential study candidates. In total, 99 type 2 diabetes patients agreed to participate in either brisk walking or medical fitness programmes. Potential study candidates performed a graded exercise test on a cycle ergometer (Medifit; Medifit Systems, Maarn, the Netherlands) using a ramp protocol [26]. Cardiac function was monitored using a 12-lead electrocardiogram and blood pressure was measured to detect malignant hypertension. Of the 99 selected patients, three did not show up and four were excluded because of an abnormal stress-ECG. The remaining 92 volunteers were randomly allocated to either brisk walking (n = 49) or medical fitness (n = 43) programmes, by subsequently drawing a sequentially numbered opaque, sealed envelope (Fig. 1). Laboratory personnel and the physician in charge of the graded exercise tests and randomisation procedure were blinded to the selection outcome of each participant. Drug prescriptions of each patient were recorded through an electronic database system operated through a network of local pharmacies. As part of the diabetes protocol in the healthcare centre, all type 2 diabetes patients consulted a dietitian and/or diabetes nurse educator annually for dietary guidance. Baseline participant characteristics are provided in Table 1. The nature and the risks of the exercise intervention were explained to all participants before written informed consent was obtained. This study was approved by the local Medical Ethical Committee of the Máxima Medical Centre, Veldhoven, the Netherlands. Since the study protocol was planned before 2005, official pre-trial registration at international trial registers was not performed.
Fig. 1Study flow diagramTable 1Participants’ baseline characteristicsCharacteristicTotal (n = 92)Brisk walking (n = 49)Medical fitness (n = 43)Age (years)60 ± 961 ± 959 ± 9Men/women (n)47/4527/2220/23Duration of diabetes (years)5 ± 55 ± 45 ± 5BW (kg)94.3 ± 18.494.1 ± 18.194.5 ± 19.0BMI (kg/m2)32.3 ± 5.532.1 ± 5.232.5 ± 6.0Wmax (W)156 ± 47155 ± 49157 ± 45Estimated  (l/min)2.1 ± 0.62.1 ± 0.62.1 ± 0.6%Pred. 82 ± 1182 ± 1083 ± 11Participants treated with: Diet only (n)1156 Hypoglycaemic agents (n)  Total814437  Metformin432419  Sulfonylurea251312  Thiazolidinedione1046  Insulin1367 Antihypertensive agents (n)  Total593227  ACEI/ARB392019  Beta-blocker17710  Diuretic19109  Calcium-channel blocker954  Other312 Lipid-lowering agents (n)  Total543024  Statin532924  Fibrate110  Other000Data are n (number of participants) or means ± SD.Estimated  was based on Wmax during cycling ergometry and the equation according to Storer et al. [30].Relative age-, height- and sex-adjusted cardio-respiratory fitness (%Pred. ) was based on the equation by Fairbarn et al. [31].ACEI, ACE inhibitor; ARB, angiotensin receptor blocker; BW, body weight
Exercise intervention
Overview Two different exercise intervention programmes were implemented over a 12-month period, during which three brisk walking or medical fitness sessions were performed each week. The exercise load was progressive in nature and had components of resistance and endurance type exercise according to the American Diabetes Association/American College of Sports Medicine guidelines [27].
Brisk walking programme The weekly volume of brisk walking consisted of three 60 min exercise sessions. During the first 3 months participants were supervised by certified exercise trainers and a physical therapist. Group size varied between 15 and 25 patients. After 3 months, certified trainers guided and supervised the training sessions, while the physical therapist was visited on a consultation basis. The endurance type exercise consisted of brisk walking (5–6 km/h), with a focus on interval type endurance exercise training. During the intervention period the intensity was gradually increased and averaged 75 ± 5% of maximum heart frequency, as determined during the maximal cycle ergometer test. The resistance type exercise training consisted of resistance and floor exercises using individual body weight and/or elastic bands (The Hygenic Corporation, Akron, OH, USA). Further details on the brisk walking programme are provided in Electronic supplementary material (ESM) Table 1.
Medical fitness programme The medical fitness programme consisted of three exercise sessions per week. Endurance type exercise consisted of interval type exercise on a home trainer, elliptical trainer or rowing ergometer with an average intensity of 73 ± 2% of maximum heart frequency. All training sessions were tailored to individual performance capacity. Resistance type exercise consisted of a selection of eight different exercises targeting upper and lower body muscle groups. Over a period of 6 months the training volume of the medical fitness programme was progressively increased from three times 30 min per week (90 min/week) towards a total of 180 to 225 min per week. Further details on the medical fitness programme are provided in ESM Table 1.
Energy expenditure and monitoring blood glucose Based on average heart rate and indirect calorimetry measurements performed during either brisk walking [28] or circuit resistance training in elderly [29] participants, energy expenditure in both exercise interventions was estimated to range between 0.23 and 0.33 kJ kg−1 min−1. Given the participants’ bodyweights, the exercise interventions should be regarded as moderate intensity. Participants were provided with blood glucose monitor systems and test strips (A. Menarini Diagnostics, Valkenswaard, the Netherlands) and during the first month of brisk walking or medical fitness were advised to assess capillary blood glucose levels ∼30 min before and after exercise. Patients were instructed to report recurrent hypoglycaemic events to their diabetes nurse educator or general practitioner. For logistic reasons no systematic enquiries on mild hypoglycaemic events were performed.
Financial cost of the intervention programmes Direct yearly costs for the individualised medical fitness programme were Euro 853 per participant and consisted of an ECG-stress test, supervision and consultations by a physical therapist, and the use of fitness centre facilities. The direct costs of the group-based brisk walking programme averaged Euro 396 per participant. Costs consisted of an ECG-stress test, supervision and consultation by a physical therapist, and a brisk walking membership fee. Other healthcare-related costs were not assessed.
Outcome variables
Resting heart rate and blood pressure Resting heart rate and blood pressure were determined in a supine position before and at 6 and 12 months after initiating the exercise programme. Heart rate was stored and averaged through a heart rate monitoring system (CO2ntrol; Tildesign, Zeewolde, the Netherlands). Average systolic and diastolic blood pressure were determined (HEM-907; Omron Healthcare, Hoofddorp, the Netherlands) from five successive measurements.
Physical fitness Before and at 12 months after the start of the exercise programme, peak oxygen uptake capacity () was estimated based on maximum workload capacity (Wmax) during cycling ergometry according to Storer et al. [30]. Relative age-, height- and sex-adjusted cardio-respiratory fitness (%Pred. ) was defined as the ratio between estimated  and predicted  as determined in a healthy non-diabetic population [31].
Blood analyses Two weeks before and at 3, 6, 9 and 12 months after initiating the exercise programme, fasting blood samples were collected. Blood samples collected before and after 3 and 9 months of intervention were analysed for HbA1c and basal glucose concentration. On the evening prior to blood sampling, participants remained fasted from 00:00 hours onwards. They arrived at the laboratory at 08:00 hours, having travelled by car or public transport. After 5 to 10 min of rest, a venous blood sample was collected from an antecubital vein. Blood samples were collected in tubes containing a glycolytic inhibitor (sodium fluoride) and an anticoagulant (potassium oxalate), immediately centrifuged for 5 min at 1,000×g and 4°C, after which aliquots of plasma were immediately frozen in liquid nitrogen and stored at −80°C until analyses. Plasma glucose (dehydrogenase assay), triacylglycerol (lipase/peroxidase assay) concentrations, and total serum cholesterol (peroxidase/cholesterol-esterase assay), HDL-cholesterol (peroxidase esterase assay) and LDL-cholesterol (according to the Friedewald formula if triacylglycerol was <4.5 mmol/l, otherwise through direct peroxidase esterase assay) were analysed (Synchron LX20; Beckman Coulter, Fullerton, CA, USA). Plasma insulin was determined in duplicate by electrochemiluminescence-immunoassay (Elecsys 2010; Roche, Mannheim, Germany). Because of cross-sensitivity in the latter assay, exogenous insulin users were excluded from this analysis. HOMA insulin resistance index [32] was assessed to monitor changes in insulin sensitivity [33]. To determine HbA1c, 3 ml blood samples were collected and analysed by high-performance liquid chromatography (HA8160 Menarini; A. Menarini Diagnostics, Florence, Italy).
Quality-of-life assessment
Health-related quality-of-life was measured with the RAND 36-Item Health Survey 1.0 [34, 35] before and after 12 months of exercise intervention.
Statistical analyses
We calculated that 74 persons (37 per group) were needed to have 80% power to detect a moderate 0.65 SD difference in HbA1c as primary endpoint parameter between brisk walking and medical fitness programme, with an α of 0.05. Sample size was exceeded to allow for an estimated withdrawal of ∼15%. Data were analysed according to the intention-to-treat (ITT) principle. To minimise type I errors and loss of power [36], endpoint analyses according to the last observation carried forward principle were performed for missing values at 12 months follow-up. To assess whether physiological differences existed between the long-term application of brisk walking and medical fitness programme, post hoc analyses were performed for individuals actively participating for 10 months or more. Data are expressed as means ± SD. ANOVA repeated measures was used to determine differences between baseline and status after 12 months of exercise intervention. Unpaired Student’s t, χ2 and Mann–Whitney U tests were used to test whether long-term changes observed in brisk walking differed from those seen in the medical fitness programme. Significance was set at the 0.05 level of confidence. Pearson’s correlation calculation was used to test for linear relationships between long-term changes in dependent variables. All statistical calculations were performed using SPSS 10.1 (SPSS, Chicago, IL, USA).
Results
Characteristics of the study population
Following randomisation there were no significant differences in baseline characteristics, sex and anthropometry between brisk walking and medical fitness programme groups (Table 1).
Programme adherence, follow-up and adverse events
After 6 months of intervention, 22 (45%) brisk walking participants and 13 (30%) medical fitness programme participants (p = 0.15) were no longer participating (ESM Table 2). After 12 months, 18 (37%) brisk walking and 19 (44%) medical fitness participants respectively were still actively participating with mean adherence levels of 75 ± 16% and 68 ± 13% (p > 0.05) for the 156 available exercise sessions (ESM Table 2). Besides motivational reasons (25%), orthopaedic-related co-morbidities, such as overuse injuries and/or subclinical osteoarthritis of the lower extremities, formed the main reason for dropout in 48 and 50% of the brisk walking and medical fitness programme participants, respectively (Fig. 1, Table 2). The distribution of missing data points was similar and not statistically different between groups (p > 0.05).
Table 2Adverse medical eventsEventsBrisk walking (n = 49)Medical fitness (n = 43)Adverse events related to exercise intervention1512 Shoulder pain/chronic tendinopathy of rotator cuff01 (Aggravation of) low back pain22 Aggravation of pre-existing osteoarthritis in hip or knee joint64 Shin splints/lower leg pain10 Chronic tendinopathy of Achilles tendon/plantar fascia31 Other/generalised musculoskeletal discomfort33Adverse events not related to exercise intervention46 Medical event requiring hospitalisationa33 Other serious medical eventb13Participants with adverse event resulting in withdrawal1917Data are number of participating diabetes patients that experienced an adverse event throughout the 12 months follow-up periodaHospitalisations were related to: arthroscopic knee surgery (brisk walking, n = 1), elective surgery for chronic abdominal aortic aneurysm (brisk walking, n = 1), elective cataract surgery (brisk walking, n = 1), elective knee joint replacement (medical fitness, n = 1), bacterial pneumonia (medical fitness, n = 1), elective varicose veins surgery (medical fitness, n = 1, did not result in withdrawal from study).bOther serious medical events requiring medical attention were: otitis externa (brisk walking) n = 1, atrial fibrillation (medical fitness) n = 1, newly diagnosed myocardial ischaemia (medical fitness) n = 1, and newly diagnosed carcinoma of the mammary gland (medical fitness) n = 1
Glycaemic control
According to ITT analyses, changes in HbA1c values following the prescription of brisk walking or medical fitness intervention were identical (95% CI −0.42, 0.43; p = 0.99) (Table 3). A total of 12 patients (brisk walking, n = 5; medical fitness, n = 7) had been prescribed higher doses of blood glucose-lowering medication throughout the follow-up period. When these participants were excluded from our ITT analysis, HbA1c increased by 0.05% (95% CI −0.41, 0.51; p = 0.82) in brisk walking as compared with medical fitness programme. Post hoc analyses of long-term active participants (≥10 months with mean adherence level of 62 ± 17 and 70 ± 18% in brisk walking and medical fitness groups, respectively) showed that, independently of changes in prescribed blood glucose-lowering drugs, HbA1c in the brisk walking group increased by 0.53% (95% CI 0.07, 1.00; p = 0.025) as compared with the medical fitness group (ESM Table 3).
Table 3Changes in diabetes outcome (ITT analysis)VariableChange from baseline to 12 monthsMean ± SDnMean ± SDnDifference95% CIp ValueHbA1c (%) Total7.13 ± 1.36926.99 ± 1.2671   Brisk walking group7.18 ± 1.42497.08 ± 1.3738    Medical fitness group7.08 ± 1.29436.89 ± 1.1333    Intragroup comparisons         Intragroup comparison total    −0.14−0.39, 0.030.153  Intragroup comparison brisk walking    −0.11−0.51, 0.150.464  Intragroup comparison medical fitness    −0.18−0.45, 0.090.176 Brisk walking vs medical fitness    0.00−0.42, 0.430.985BMI (kg/m2) Total32.3 ± 5.59231.8 ± 5.489    Brisk walking group32.1 ± 5.24931.9 ± 5.048    Medical fitness group32.5 ± 6.04331.7 ± 5.941    Intragroup comparisons         Intragroup comparison total    −0.5−1.1, 0.10.108  Intragroup comparison brisk walking    −0.2−0.6, 0.30.471  Intragroup comparison medical fitness    −0.8−2.0, 0.30.152 Brisk walking vs medical fitness    0.7−0.5, 1.90.237Fasting plasma glucose (mmol/l) Total8.44 ± 2.81928.21 ± 2.3771    Brisk walking group8.64 ± 2.83498.33 ± 2.6438    Medical fitness group8.21 ± 2.80438.06 ± 2.0533    Intragroup comparisons         Intragroup comparison total    −0.23−0.72, 0.250.345  Intragroup comparison brisk walking    −0.31−0.96, 0.340.344  Intragroup comparison medical fitness    −0.15−0.91, 0.610.699 Brisk walking vs. medical fitness    −0.16−1.14, 0.820.744HOMAa Total5.55 ± 3.68685.60 ± 3.3854    Brisk walking group5.86 ± 3.56375.75 ± 3.2030    Medical fitness group5.19 ± 3.58315.43 ± 3.6424    Intragroup comparisons         Intragroup comparison total    0.05−0.50, 0.620.833  Intragroup comparison brisk walking    −0.12−1.11, 0.850.794  Intragroup comparison medical fitness    0.24−0.19, 0.740.241 Brisk walking vs medical fitness    −0.40−1.52, 0.720.479Resting heart rate (bpm) Total73.4 ± 11.89169.6 ± 13.977    Brisk walking group72.6 ± 11.84868.3 ± 15.041    Medical fitness group74.4 ± 11.84371.0 ± 12.436    Intragroup comparisons         Intragroup comparison total    −3.9−5.9, −1.80.000  Intragroup comparison brisk walking    −4.3−7.4, −1.10.009  Intragroup comparison medical fitness    −3.4−5.9, −0.90.010 Brisk walking vs medical fitness    −0.9−4.9, 3.20.678Systolic blood pressure (mmHg) Total148.5 ± 18.191137.5 ± 15.577    Brisk walking group150.3 ± 18.948138.9 ± 16.341    Medical fitness group146.3 ± 17.143135.9 ± 14.636    Intragroup comparisons         Intragroup comparison total    −10.9−14.0, −7.80.000  Intragroup comparison brisk walking    −11.4−15.9, −6.80.000  Intragroup comparison medical fitness    −10.4−14.7, 6.20.000 Brisk walking vs medical fitness    −0.9−7.1, 5.3)0.768Diastolic blood pressure (mmHg) Total81.9 ± 10.69176.6 ± 8.377    Brisk walking group81.3 ± 10.84875.9 ± 8.841    Medical fitness group82.6 ± 10.44377.4 ± 7.736    Intragroup comparisons         Intragroup comparison total    −5.3−7.1, −3.60.000  Intragroup comparison brisk walking    −5.4−7.8, 2.90.000  Intragroup comparison medical fitness    −5.2−7.8, −2.70.000 Brisk walking vs medical fitness    −0.1−3.6, 3.40.949Total cholesterol level (mmol/l) Total4.70 ± 0.86884.53 ± 0.9465    Brisk walking group4.83 ± 0.89474.61 ± 0.9235    Medical fitness group4.54 ± 0.12414.44 ± 0.9630    Intragroup comparisons         Intragroup comparison total    −0.16−0.32, −0.010.035  Intragroup comparison brisk walking    −0.22−0.45, 0.010.064  Intragroup comparison medical fitness    −0.10−0.30, 0.100.307 Brisk walking vs medical fitness    −0.12−0.42, 0.190.453LDL-cholesterol level (mmol/l) Total2.83 ± 0.76882.70 ± 0.7964    Brisk walking group2.90 ± 0.82472.72 ± 0.8535    Medical fitness group2.74 ± 0.69412.68 ± 0.7229    Intragroup comparisons         Intragroup comparison total    −0.12−0.26, 0.010.070  Intragroup comparison brisk walking    −0.18−0.38, 0.020.080  Intragroup comparison medical fitness    −0.06–0.25, 0.120.493 Brisk walking vs medical fitness    −0.11−0.38, 0.160.401HDL-cholesterol level (mmol/l) Total1.09 ± 0.28881.10 ± 0.2965    Brisk walking group1.10 ± 0.23471.09 ± 0.2635    Medical fitness group1.07 ± 0.33411.11 ± 0.3230    Intragroup comparisons         Intragroup comparison total    −0.01–0.02, 0.040.570  Intragroup comparison brisk walking    −0.01−0.06, 0.040.629  Intragroup comparison medical fitness    0.03−0.01, 0.080.129 Brisk walking vs medical fitness    −0.05−0.12, 0.020.172Triacylglycerol level (mmol/l) Total1.88 ± 0.99881.79 ± 0.9164    Brisk walking group2.00 ± 1.08471.94 ± 0.9835    Medical fitness group1.74 ± 0.88411.61 ± 0.7929    Intragroup comparisons         Intragroup comparison total    −0.09−0.25, 0.060.239  Intragroup comparison brisk walking    −0.06−0.33, 0.170.646  Intragroup comparison medical fitness    −0.13−0.27, 0.060.120 Brisk walking vs medical fitness    −0.02−0.29, 0.330.892RAND-36 (score 0–100 scale) Total71 ± 158970 ± 1558    Brisk walking group69 ± 154668 ± 1531    Medical fitness group73 ± 154371 ± 1427    Intragroup comparisons         Intragroup comparison total    −0.6−2.4, 1.20.503  Intragroup comparison brisk walking    0.1–2.7, 2.80.969  Intragroup comparison medical fitness    −1.4−3.8, 1.10.261 Brisk walking vs medical fitness    1.4−2.2, 5.00.438Data are means ± SD. n=number of valid measurements. aFor HOMA calculations exogenous insulin users (n = 13) were excluded
Resting heart rate and blood pressure
Following the 12 month exercise intervention, resting heart rate in the brisk walking group was reduced by 0.9 beats per min (bpm) (CI −7.1, 5.3; p = 0.68) as compared with medical fitness group. No significant differences in blood pressure response were observed between the two interventions (Table 3). After excluding participants who were prescribed higher doses of antihypertensive drugs (brisk walking, n = 5; medical fitness, n = 7), mean arterial blood pressure decreased by 0.9 mmHg (95% CI −5.6, 3.9; p = 0.94) in the brisk walking as compared with medical fitness group. A post hoc analysis of 46 long-term active participants showed a non-significant difference in mean arterial blood pressure of −3.5 mmHg (95% CI −9.2, 2.2; p = 0.22) in the brisk walking compared with the medical fitness programme (ESM Table 3).
Blood lipid profile
After 12 months, the overall fasting lipid profile did not differ between the two groups (Table 3). When participants (brisk walking, n = 9, medical fitness, n = 7) who were prescribed more blood lipid-lowering agents were excluded, HDL-cholesterol had changed by −0.05 mmol/l (95% CI −0.12, 0.02; p = 0.17) in the medical fitness compared with the brisk walking group.
Body composition and workload capacity
Body composition (BMI) did not change (Table 3). Workload capacity as measured during cycle ergometry averaged 155 ± 49 and 157 ± 45 W in the brisk walking and medical fitness programme groups, respectively, changing by −4.3 W (95% CI −9.1, 0.5; p = 0.078) in the former and by −2.5 W (95% CI −10, 5.6; p = 0.53) in the latter, with a non-significant difference of −1.8 W (95% CI −10.5, 6.9; p = 0.68) in brisk walking compared with medical fitness programme participants. Maximum heart rates recorded during ergometry averaged 146 ± 22 and 152 ± 19 bpm at baseline, and 152 ± 21 and 149 ± 22 bpm following 12 months of exercise intervention in the brisk walking and medical fitness groups, respectively (p > 0.05). In our long-term active brisk walking participants, Wmax changed by −6.3 W (95% CI −16.5, 3.9; p = 0.22) as compared with their medical fitness programme counterparts. No significant correlations were found between changes in HbA1c values and changes in workload capacity (ΔWmax, Pearson’s R = 0.02, p = 0.93, n = 38) or body weight (Pearson’s R = 0.18, p = 0.225, n = 45).
Quality of life assessment
A total of 89 and 58 participants completed the RAND-36 questionnaire at baseline and after 12 months of intervention, respectively. Reliability and internal consistency was excellent with Cronbach’s alpha of 0.93 and 0.91 respectively. No significant difference in changes of total RAND-36 scores were observed between the two intervention groups (p > 0.05; Table 3).
Discussion
It has been firmly established that physical activity counselling [37] and participation in structured exercise intervention programmes [15, 19] improves glycaemic control. However, long-term intervention studies on the clinical benefits of different types of exercise intervention programmes in type 2 diabetes patients are lacking. In the present study, we compared the clinical benefits of 12 months of a group-based brisk walking programme versus a more individualised medical fitness programme. ITT analysis showed that the prescription of a group-based, brisk walking programme is not necessarily inferior to a more individualised medical fitness programme with regard to glycaemic control and markers for cardiovascular risk profile (Table 3). Our data therefore imply that most patients with type 2 diabetes will achieve more or less equal long-term therapeutic benefits from a low-impact brisk walking programme as opposed to a more individualised medical fitness programme. Nevertheless, long-term programme adherence and the possibility of dropout should be taken into consideration when prescribing either type of exercise intervention for a patient with type 2 diabetes. Independently of the provided level of guidance and infrastructure, 60% of the patients dropped out of the exercise programme during the 12 month intervention period, with no differences in adherence and dropout patterns between brisk walking and medical fitness programme. Although motivational factors explained 25% of the dropout in both exercise programmes, almost 50% of the dropout was attributed to orthopaedic-related co-morbidities and overuse injuries of the lower extremities. The latter was not anticipated, since clinically relevant orthopaedic limitations, such as a history of osteoarthritis of the hip or knee joint, were defined as exclusion criteria for participation in either exercise intervention programme. Apparently, subclinical joint disease and/or degeneration of myotendineous structures become apparent when physical activity levels are increased. Stiffening of connective tissue due to non-enzymatic advanced glycation end-product formation [38], as well as decreased collagen turnover due to ageing and chronic disuse [39], could be responsible for the impaired response to increased musculoskeletal loading in these patients. Although more fundamental clinical research is warranted, the high incidence of overuse injuries in the present study adds to the results described in another study [23], suggesting that in unselected, non-study populations dropout will be even greater. Therefore, it might be advisable to implement a more gradual and less intense exercise regimen to allow myotendineous structures to adapt to increased loading. Moreover, before prescribing therapeutic exercise, diabetes healthcare workers should carefully consider obesity- and diabetes-related musculoskeletal deconditioning [40–42]. Such programmes should probably focus even more on resistance type exercise activities [43, 44] to bring patients to a level at which they are able to participate and adhere to more generic diabetes intervention programmes. It has also been suggested that psychological strategies such as motivational interviewing [45] or booster sessions [21, 46] might help to further improve programme adherence. Nevertheless, more long-term, tailored exercise intervention studies are warranted to further define the most effective and feasible exercise interventional strategy.
The absence of a significant decline in blood HbA1c levels in brisk walking participants does not imply that the prescription of low-impact, endurance type exercise has no therapeutic value [3, 7, 27, 47–49]. In fact, we observed significant improvements in blood pressure control following either type of exercise intervention (Table 3). Although reliable assessment of actual drug use was not possible in the present study, the improvements in blood pressure occurred independently of changes in the prescription of antihypertensive medication. However, the lack of a non-exercise control group in the present study makes it impossible to speculate on cause and effect, since changes in blood pressure from baseline might also, or at least partly, be explained by the Hawthorne effect, for example, or by familiarisation with blood pressure measurement protocols. Nevertheless, our data suggest that the structured application of group-based brisk walking and supervised medical fitness programmes tends to have a similar impact on cardiovascular risk profile.
In conclusion, the prescription of group-based brisk walking represents an equally effective interventional strategy to modulate glycaemic control and cardiovascular risk profile in type 2 diabetes patients compared with a more individualised medical fitness programme. General deconditioning, musculoskeletal overuse injuries and lack of motivation limit the benefits of long-term exercise intervention as an add-on to a comprehensive diabetes care programme. Future diabetes exercise intervention programmes in primary healthcare settings should consider diabetes-related co-morbidities and patient motivation as important factors, which determine both long-term programme adherence and the associated clinical benefits.
Electronic supplementary material
Below is the link to the electronic supplementary material.
Table 1
Exercise programme (PDF 60.7 KB)
Table 2
Individual follow-up data for primary outcome variable (HbA1c) and active programme participation (PDF 69.9 KB)
Table 3
Changes in diabetes outcome in long-term active participants (PDF 160 KB)

exercise
blood pressure
physical fitness
hyperglycaemia
lipid metabolism
randomised controlled clinical trial
type 2 diabetes mellitus


Celastrol inhibits polyglutamine aggregation and toxicity though induction of the heat shock response

Heat shock proteins (hsps) are protective against the harmful effects of mutant expanded polyglutamine repeat proteins that occur in diseases such as Huntington’s, prompting the search for pharmacologic compounds that increase hsp expression in cells as potential treatments for this and related diseases. In this paper, we show that celastrol, a compound recently shown to up-regulate hsp gene expression, significantly decreases killing of cells expressing mutant polyglutamine protein. This effect requires the presence of the transcription factor responsible for mediating inducible hsp gene expression, HSF1, and is correlated with decreased amounts and increased sodium dodecyl sulfate (SDS) solubility of polyglutamine aggregates. These results suggest the potential of celastrol as a therapeutic agent in the treatment of human polyglutamine expansion diseases.
Introduction
A large number of neurodegenerative diseases, including Huntington’s and Kennedy’s diseases, are characterized by expanded polyglutamine repeats in certain proteins leading to their aggregation and toxic effects on the cells expressing them [1, 2]. A number of results suggest that polyglutamine-containing aggregates are important both for the initiation and progression of these diseases [3, 4]. Polyglutamine protein aggregates in brains of patients and transgenic animals have been found to contain various molecular chaperones, ubiquitin, and components of the 20S proteasome [5, 6]. This suggests that neuronal cells recognize the protein aggregates as abnormally folded and try to disaggregate or degrade the mutant proteins by recruiting chaperones and proteasomal components [7]. Consistent with this view, increased expression of hsp70 and other heat shock proteins (hsps) has been found to be effective in reducing the toxicity of mutant polyglutamine proteins, suggesting the potential of pharmacological up-regulation of hsp gene regulation as a means for treating polyglutamine expansion diseases such as Huntington’s [8–11].
Heat Shock Factor 1, HSF1, is the transcription factor responsible for up-regulating the expression of hsp70 and other hsp genes in response to cellular stress [12, 13]. HSF activation involves stress-induced conversion of this factor to its trimeric DNA-binding form [14–17]. The activated trimeric HSF1 then binds to heat shock elements in the promoters of hsp genes to up-regulate their transcription, ultimately leading to elevated levels of cytoprotective hsps in these cells.
The function of HSF1 as a key positive regulator of hsp expression, coupled to the observed ability of hsp proteins to protect cells from polyglutamine toxicity prompted the hypothesis that interventions that lead to activation of HSF1 could provide protection for cells against this toxicity and possibly represent agents that could be useful in treating polyglutamine expansion diseases such as Huntington’s [10, 18]. Consistent with this hypothesis, expression in cells of a constitutively active mutant HSF1 protein results in decreased polyglutamine toxicity and aggregate formation in both cell culture and animal models [19, 20]. These and other results have stimulated the search for pharmacological compounds capable of up-regulating hsp gene expression, as such compounds would theoretically have potential as treatments for these and other diseases of protein misfolding.
Recently, it was demonstrated that a compound called celastrol, which is found in the Celastraceae family of plants and is already being used to treat diseases such as rheumatoid arthritis, bacterial infection, and fever [21, 22], is able to activate HSF1 and up-regulate hsp gene expression [18]. Celastrol has previously been found to inhibit the aggregation of purified Q58-huntingtin 1-171 amino terminal fragment in an in vitro assay, although this study did not examine effects of celastrol on polyglutamine aggregation in cells [23]. Celastrol has also been found to inhibit the cytotoxicity of expanded polyglutamine form of huntingtin exon 1 [24] and androgen receptor [25], but these studies did not examine the mechanism by which celastrol protects cells from expanded polyglutamine protein cytotoxicity.
The results of the experiments presented in this paper demonstrate that celastrol is effective in preventing both the aggregation and toxicity of polyglutamine expression in cells and that it mediates these effects via the HSF1-mediated gene expression pathway. These results support the potential of this drug as a possible therapeutic agent for treating polyglutamine expansion diseases. The results also suggest that other drugs that stimulate HSF1 activity leading to hsp gene expression may also have beneficial activity against these disease states as well as other human diseases that are caused by protein misfolding.
Materials and methods
Plasmids, cell culture, and celastrol
The expression constructs encoding Q19-YFP, Q57-YFP, and Q81-YFP were kindly provided by Dr. James Burke (Duke University). The polyglutamine-YFP (Qn-YFP) vectors were constructed using CAG repeats that were synthesized by polymerase chain reaction (PCR) from human dentatorubral pallidoluysian atrophy (DRPLA) cDNAs containing different CAG repeats. HeLa cells were cultured in Dulbecco’s modified Eagle’s medium (DMEM; Cellgro) supplemented with 10% fetal bovine serum (FBS) and 50 μg/ml gentamicin. PC12 cells were cultured in DMEM medium (Cellgro) supplemented with 5% FBS and 10% heat-inactivated horse serum (Gibco), and 100 units/ml Penicillin-Streptomycin (Gibco). HSF1+/+ and HSF1−/− mouse embryo fibroblast (MEF) cells (kindly provided by Dr. Ivor Benjamin, University of Utah) were cultured in DMEM medium (Cellgro) supplemented with 10% FBS, 1× Penicillin-streptomycin (Gibco), and 1× Non-essential amino acids (Gibco). Transfection was performed using Effectene transfection reagent (Qiagen), following the manufacturer’s protocol. Celastrol (Calbiochem) was dissolved in dimethyl sulphoxide at a stock concentration of 5.54 mM.
Trypan blue cell viability assay
Cells were collected by centrifugation at 1,000 rpm for 10 min at 4°C, and the pellet was washed twice with 1× phosphate-buffered saline (PBS). The cell pellet was then resuspended in 1× PBS to a concentration of approximately 106 cells/ml. A 1:1 dilution of the suspension was prepared using a solution containing 0.4% trypan blue stain (Gibco), and the suspension was then loaded into the counting chamber of a hemocytometer. The number of stained cells as well as the total number of cells was counted, and the percentage of stained cells was taken to represent the percentage of cell death. Experiments were repeated three times.
Fluorescence microscopy
Cells were seeded on coverslips, and 48 h after transfection, Hoechst 33342 and verapamil were added to the medium to final concentrations of 5 and 50 μg/ml, respectively. After incubation at 37°C for 30 min, the medium was removed, and the coverslips washed with 1× PBS for 5 min. A solution containing 3.7% paraformaldehyde in 1× PBS was added, and after 20 min incubation at room temperature, coverslips were washed with 1× PBS for 5 min. Coverslips were washed briefly three times in distilled water and mounted onto a slide spotted with 15 μl Vectashield (Vector Laboratories). Excess fluid was wicked from the coverslip and the edges of the coverslip sealed with fingernail polish. The fluorescence was then visualized using a Nikon fluorescent microscope and pictures taken with a Nikon Spotcam digital-imaging camera. To quantify the formation of polyglutamine aggregates, visual fields which contained similar numbers of cells (based on the density of nuclei stained by Hoechst) were chosen under 20× objective, and then the number of cells that contained aggregates in each field of vision was counted. Three different visual fields were quantified in each case. There were approximately 300 cells in each visual field for the experiments involving HeLa cells and PC12 cells, and approximately 100 cells in the experiments involving MEF cells. We scored a cell as positive if it had any visible aggregates, and the aggregates in the majority of cells appeared to be intranuclear or perinuclear (example shown in Fig. S1).
Extract preparation and Western blot assay
Cell lysis was performed on ice for 30 min in 50 mM Tris–HCl [pH 8.0], 100 mM NaCl, 5 mM MgCl2, 0.5% NP40 lysis buffer [26] containing 1× protease inhibitor cocktail (Roche), and 1 mM phenylmethanesulfonyl fluoride added. To examine hsp70 level, the cell lysate was cleared by centrifugation at 1,000 rpm at 4°C for 10 min, and the protein concentration of the supernatant was then determined by BioRad assay. Five micrograms of protein extract was subjected to sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) and Western blot following standard procedures. The antibodies and dilutions used to probe the Western blots were as follows. Anti-hsp70 (stress-induced form; Stressgen) was used at 1:10,000, anti-β-actin antibody (Sigma) was used at 1:10,000, and the anti-green fluorescent protein (GFP) polyclonal antibody (Bethyl labs) was used at a dilution of 1:4,000. Hsp70 Western blots were quantified using ImageQuant software.
Filtration assay
Cell lysis was performed on ice for 30 min in the lysis buffer described above. The insoluble fraction was obtained by centrifugation of the cell lysate at 14,000 rpm at 4°C for 10 min. The pellet was resuspended in DNase buffer (20 mM Tris–HCl [pH 8.0], 15 mM MgCl2, and 0.5 mg/ml DNase I), followed by incubation at 37°C for 1 h. After DNase treatment, the protein concentration was determined by analyzing an aliquot using the BioRad assay. The incubation was terminated by adjusting the mixtures to 20 mM ethylenediamine tetraacetic acid (EDTA), 2% sodium dodecyl sulfate (SDS), and 50 mM dithiothreitol and boiling for 5 min. Thirty micrograms of protein was diluted into 200 μl 2% SDS, and this was then filtered through a 0.2-μm pore size cellulose acetate membrane (Schleicher & Schuell) that was equilibrated with 2% SDS using a Dot-Blot system (Schleicher & Schuell). Filters were washed twice with 200 μl 0.1% SDS and then subjected to anti-GFP Western blot [27].
SDS solubility assay
To perform the SDS solubility assay, cell lysates were prepared as described above for the filtration assay, including the 14,000 rpm centrifugation of the cell lysate and DNase treatment and protein concentration determination by BioRad assay. Forty micrograms of protein was then adjusted to 2× SDS-PAGE sample buffer (62.5 mM Tris·HCl [pH 6.8], 10% glycerol, 2% SDS, 5% β-mercaptoethanol) and boiled for 5 min after which the sample was analyzed by SDS-PAGE and Western blot with anti-GFP polyclonal antibody.
Statistical analysis
Statistical significance was determined using the Student’s t test. A P value of <0.05 was considered to be statistically significant.
Results
Celastrol protects against polyglutamine toxicity
The experimental system we chose to test for effects of celastrol on polyglutamine aggregation and toxicity is transfection of a Q57-YFP fusion protein into cell lines (gift of Dr. James Burke), which is an established model for the aggregation of polyglutamine containing proteins in vivo [28]. Consistent with this, the Q57-YFP protein forms clearly visible aggregates upon expression in HeLa cells, while cells transfected with Q19-YFP exhibit a diffuse pattern (Fig. S1). A previous study showed that 8 h of celastrol treatment leads to increased levels of the hsp70 protein [18]. As the studies described in this paper include cell death and aggregation assays performed at 48 h after transfection with the Q57-YFP construct, we wanted to ensure that cells treated with celastrol treatment for longer times also exhibit elevated hsp70 expression. As shown in Fig. 1a (upper panel), celastrol treatment of HeLa cells for 24 or 48 h both result in a dose-dependent increase in expression of the hsp70 protein. Quantification of these hsp70 Western blot results indicates that the induction of hsp70 by each celastrol concentration is very similar at 24 and 48 h, showing that treatment with this drug results in a sustained increase in hsp70 levels (lower panel). Next, to test whether treatment with this drug confers protection from polyglutamine toxicity, HeLa cells were transfected with the Q57-YFP construct and then incubated in media containing different concentrations of celastrol. The results of this experiment, shown in Fig. 1b, reveal that celastrol treatment is associated with a significant decrease in death of these cells expressing this mutant polyglutamine protein.
Fig. 1Celastrol treatment reduces Q57-YFP cytotoxicity. a Hsp70 protein level is increased by celastrol treatment. HeLa cells were treated with the indicated concentrations of celastrol for 24 or 48 h, after which cell extracts were made and subjected to Western blot using antibodies against hsp70 or β-actin (upper panel). These results were quantified using the ImageQuant program, and the values for the two treatment times, grouped by celastrol concentration, were graphed (lower panel). b HeLa cells were transfected with Q57-YFP along with celastrol treatment at the concentrations indicated. After 48 h, the amount of cell death was determined by trypan blue assay. Data are shown as means ± SE (*P < 0.007, **P < 0.004, ***P < 0.0001, for each celastrol concentration treatment vs no celastrol)
Celastrol protective effect are correlated with decreased number of cells containing polyglutamine aggregates
To determine whether the ability of celastrol to protect cells from polyQ toxicity could be mediated via effects on polyQ aggregates, we then examined whether celastrol treatment alters the number of polyQ aggregates in cells and/or their solubility. The results of these experiments show that treatment with celastrol is associated both with a decrease in the number of cells containing Q57-YFP aggregates, as quantified by fluorescence microscopy (Fig. 2a), and also with an increase in the amount of Q57-YFP that can be solubilized from aggregates by SDS treatment (Fig. 2b). SDS solubility of aggregates is related with their toxicity, and data from previous studies suggests that molecular chaperones may ameliorate the neurodegenerative effect of mutant polyglutamine protein, at least in part, by increasing the solubility of these proteins [9, 29]. Together, the results shown in Figs. 1 and 2 indicate that celastrol treatment decreases the death of cells expressing mutant polyglutamine protein and also decreases the number of cells containing Q57-YFP-aggregates and the insolubility of Q57-YFP-aggregates.
Fig. 2Celastrol treatment reduces number of cells containing Q57-YFP aggregates and increases Q57-YFP solubility. HeLa cells were transfected with Q57-YFP along with celastrol treatment at the concentrations indicated. a After 48 h of transfection, the formation of Q57-YFP aggregates was quantified using fluorescence microscopy. Visual fields which contained similar numbers of cells (based on the density of nuclei stained by Hoechst) were chosen under 20× objective, and then the number of aggregates in each field of vision was counted. Three different visual fields were quantified in each case, and data are shown as means ± SE (*P < 0.004, **P < 0.001, ***P < 0.0003, for each celastrol concentration treatment vs no celastrol). b To determine the amount of Q57-YFP monomer that could be solubilized from aggregates in lysates of the transfected cells by SDS treatment, the protein concentration of the insoluble fraction of the cell lysates was determined, and then 40 μg of protein was subjected to SDS solubilization treatment, followed by Western blot using anti-GFP antibody
Protective effects of celastrol treatment in PC12 cells
As the deleterious effects of expression of mutant polyglutamine proteins in vivo are observed primarily in cells of neuronal origin, we next sought to test the effect of celastrol treatment on polyglutamine toxicity and aggregation in PC12 cells. As shown in Fig. 3a, PC12 cells are very sensitive to killing by expression of the Q57-YFP protein, but as observed for HeLa cells in Fig. 1b above, celastrol treatment results in a significant decrease in death of these cells. As was observed in the experiments using HeLa cells, treatment of PC12 cells with celastrol resulted in a significant decrease in the number of polyglutamine aggregates in the cells (Fig. 3b) and an increase in the amount of Q57-YFP that can be solubilized from aggregates by SDS treatment (Fig. 3c). Interestingly, the concentrations of celastrol required to achieve these effects on polyglutamine toxicity and number and solubility properties of aggregates in PC12 cells were significantly lower than that needed for HeLa cells.
Fig. 3Celastrol effects on Q57-YFP toxicity and aggregates in PC12 cells. PC12 cells were transfected with Q57-YFP along with celastrol treatment at the concentrations indicated. After 48 h, the amount of cell death was determined by trypan blue assay (a), the number of cells containing Q57-YFP aggregates was quantified using fluorescence microscopy (b), and the amount of Q57-YFP monomer solubilized from aggregates by SDS treatment visualized by Western blot using anti-GFP antibody (c). In a and b, data are shown as means ± SE [*P < 0.0001 and **P < 0.0001 (a), *P < 0.001 and **P < 0.0001 (b), in each case for each celastrol concentration treatment vs no celastrol)
HSF1−/− cells exhibit increased polyglutamine aggregation and toxicity
Inducible hsp expression is thought to be important for the ability of cells to decrease polyglutamine toxicity and aggregation [8–11]. Consistent with this hypothesis, HSF1−/− MEFs [30] that are transfected with Q57-YFP exhibit a higher incidence of cell death than HSF1+/+ MEF cells (Fig. 4a). The HSF1−/− MEFs also show increased Q57-YFP aggregation, both as measured by numbers of aggregates using fluorescence microscopy of cells (Fig. 4b) and by amount of aggregated Q57-YFP protein present in cell extracts detected by filtration assay (Fig. 4c).
Fig. 4HSF1−/− cells exhibit higher Q57-YFP aggregation and cell death. HSF1−/− and wild-type MEF cells were transfected with Q57-YFP, and after 48 h, cell death was examined by trypan blue assay (a), and the number of cells containing Q57-YFP aggregates was quantified using fluorescence microscopy (b), or filtration assay, in which 30 μg of the insoluble fraction was filtered through 0.2 μm cellulose acetate membrane, and the aggregates retained on the membrane were immunoblotted using anti-GFP antibody (c). In a and b, data are shown as means ± SE. *P < 0.008 (a); *P < 0.003 (b)
Protective effects of celastrol require HSF1
Based on previous results showing the ability of celastrol to activate HSF1 leading to increased hsp gene expression [18], we hypothesized that this drug’s ability to decrease polyglutamine toxicity and aggregation shown by the results of Figs. 1, 2, and 3 above could be mediated via the HSF1-regulated gene expression pathway. To test this hypothesis, we compared the effect of celastrol treatment on polyglutamine toxicity and aggregation in the HSF1+/+ vs HSF1−/− MEF cells. Celastrol does not exhibit any toxicity in HeLa cells at 1.6 μM, but we found its optimal concentration in MEF cells to be lower than that of HeLa cells. Thus, for these experiments, we used 0.4 μM celastrol treatment, which has no toxic effect in either HSF1−/− or wild-type MEFs (data not shown). First, Western blot analysis shows that the HSF1−/− cells are unable to up-regulate hsp70 protein expression in response to celastrol treatment, demonstrating that celastrol-induced up-regulation of hsp70 expression is mediated by the HSF1-regulated gene expression pathway (Fig. 5a).
Fig. 5Celastrol decreases Q57-YFP toxicity and aggregation in wild-type but not HSF1−/− MEF cells. a Celastrol treatment does not induce hsp70 expression in HSF1−/− cells. Wild-type and HSF1−/− MEF cells were treated with no celastrol or 0.4 μM celastrol, and after 12 h, cell extracts were made, and 5 μg protein was loaded into each lane for immunoblotting with anti-hsp70 antibodies. b and c Wild-type and HSF1−/− MEF cells were transfected with Q57-YFP, with celastrol at the indicated concentrations added at the same time. After 48 h, cell death was examined by trypan blue assay (b), with data shown as means ± SE (*P < 0.002 for HSF2+/+ 0.4 μM celastrol vs no celastrol; *P < 0.002 for HSF2−/− 0.4 μM celastrol vs no celastrol), and amount of aggregated Q57-YFP was determined by filtration assay followed by anti-GFP Western blot (c)
The results shown above (Figs. 1, 2, 3, and 5a) indicate that celastrol treatment is effective in preventing polyglutamine aggregation and toxicity and that this drug up-regulates hsp70 expression by an HSF1-dependent mechanism. These results suggest that celastrol treatment protects cells by stimulating HSF1-dependent expression of hsps. However, celastrol could also modulate other cellular activities that could contribute to these protective effects. Thus, to test the contribution of HSF1-regulated pathways in these protective effects, we transfected HSF1+/+ and HSF1−/− MEF cells with Q57-YFP in combination with celastrol treatment and then measured the amount of cell death and levels of aggregated Q57-YFP. The results of this experiment show that, as it did for the HeLa and PC12 cells in the experiments of Figs. 1 and 3 above, celastrol treatment resulted in decreased death of HSF1+/+ MEF cells transfected with Q57-YFP, but treatment with this drug did not protect the HSF1−/− cells (Fig. 5b). Consistent with these results, the HSF1+/+ cells, but not the HSF1−/− cells, showed decreased levels of aggregated Q57-YFP upon celastrol treatment, as measured by the filtration assay (Fig. 5c). These results suggest that the HSF1 protein plays an important role in the protective effects of celastrol against polyglutamine toxicity and aggregation.
Discussion
The results described above indicate that the drug celastrol is able to decrease polyglutamine toxicity, supporting the proposal that this drug could potentially be useful in the treatment of Huntington’s disease and possibly other human polyglutamine expansion disorders. In support of this possibility, it has been found that celastrol treatment of mice results in elevation of hsp70 levels in neurons in the brains of these mice [31]. The results also show that lower concentrations of celastrol are required for its protective effects against polyglutamine toxicity in PC12 cells, cells with neuronal characteristics, compared to other cell types. A particularly beneficial aspect of this drug is that it is already being used to treat people with other disorders [21, 22], and thus it could likely be adapted more quickly for use in treating polyglutamine expansion diseases than other drugs not currently being used in humans.
Results presented in this paper indicate that the protective effect of celastrol against polyglutamine toxicity is associated with decreased numbers of cells containing aggregates as well as increased SDS-solubility of the mutant polyglutamine protein. This might seem to be at odds with findings that formation of polyglutamine aggregates can be protective for cells expressing these mutant proteins [32–34]. However, our results are consistent with the findings of a number of studies which indicate that molecular chaperones can reduce the formation of polyglutamine aggregates and increase the solubility of expanded polyglutamine proteins [8–11, 19, 20]. While one study found that hsp40 overexpression, but not hsp70 overexpression, was associated with reduced aggregation [35], the results of a number of studies do suggest that chaperones are able to reduce aggregation of mutant polyglutamine proteins. Molecular chaperones could be acting at multiple levels to reduce polyglutamine toxicity, but one possibility that has been proposed is that these chaperones, and by extension celastrol through its HSF1-mediated up-regulation of chaperones, may be acting at an early step to prevent formation of toxic intermediates before they can become part of larger aggregates [8–11, 19, 20]. This would explain both how celastrol treatment protects cells from polyglutamine toxicity and the effects we observe on polyglutamine aggregates in the celastrol-treated cells. An alternative explanation that must be considered, in keeping with previous studies indicating that aggregate formation can be protective for cells [32–34], is that the results we observe relating celastrol with the numbers of cells containing polyglutamine aggregates could be due, at least in part, to a potential ability of celastrol to enhance the survival of cells that do not contain aggregates, which would then lead to a perceived decrease in the numbers of cells containing aggregates in our experiments. Our data do indicate, however, the protective effects of celastrol with respect to polyglutamine toxicity.
In addition to its ability to its effects on HSF1 activity, celastrol has been found to affect other pathways in the cell, including the NF–κB pathway [18, 21, 22, 36]. However, our results suggest that the beneficial effects of celastrol treatment in decreasing polyglutamine toxicity are mediated through the action of the HSF1-regulated gene expression pathway, based on the finding that celastrol is not protective in Q57-YFP transfected HSF1−/− MEF cells (Fig. 5b). This finding also suggests that other drugs that activate HSF1 could also have potential as candidate therapeutic agents for treating polyglutamine expansion diseases.
Electronic supplementary material

celastrol
polyglutamine
aggregates
heat shock proteins
hsf1
hsp70


Phospholipase D signaling: orchestration by PIP2 and small GTPases

Hydrolysis of phosphatidylcholine by phospholipase D (PLD) leads to the generation of the versatile lipid second messenger, phosphatidic acid (PA), which is involved in fundamental cellular processes, including membrane trafficking, actin cytoskeleton remodeling, cell proliferation and cell survival. PLD activity can be dramatically stimulated by a large number of cell surface receptors and is elaborately regulated by intracellular factors, including protein kinase C isoforms, small GTPases of the ARF, Rho and Ras families and, particularly, by the phosphoinositide, phosphatidylinositol 4,5-bisphosphate (PIP2). PIP2 is well known as substrate for the generation of second messengers by phospholipase C, but is now also understood to recruit and/or activate a variety of actin regulatory proteins, ion channels and other signaling proteins, including PLD, by direct interaction. The synthesis of PIP2 by phosphoinositide 5-kinase (PIP5K) isoforms is tightly regulated by small GTPases and, interestingly, by PA as well, and the concerted formation of PIP2 and PA has been shown to mediate receptor-regulated cellular events. This review highlights the regulation of PLD by membrane receptors, and describes how the close encounter of PLD and PIP5K isoforms with small GTPases permits the execution of specific cellular functions.
Introduction
The activation of membrane receptors by hormones and growth factors results in the localized generation of intracellular second messengers. The hydrolysis of membrane phospholipids and the generation of biologically active products play important roles in the regulation of cell function and cell fate. Well known is the activation of phosphoinositide-specific phospholipase C (PLC) isoforms, which hydrolyze phosphatidylinositol 4,5-bisphosphate (PIP2), a membrane phospholipid found in all eukaryotic cells (Schmidt et al. 2004). Stimulation of PLC isoforms plays a major role in many early and late cellular responses to receptor activation, including smooth muscle contraction, secretion and neuronal signaling as well as fertilization, cell growth and differentiation (Berridge 2005; Nishizuka 2003). Phospholipase D (PLD) was first described 60 years ago as a distinct, phospholipid-specific phosphodiesterase activity in cabbage leaves (Hanahan and Chaikoff 1948). This pioneering research indicated that PLD hydrolyzes phosphatidylcholine to yield phosphatidic acid (PA) and choline. The recognition that PLD is rapidly and dramatically activated in response to extracellular stimuli in cultured animal cells, now 20 years ago (Bocckino et al. 1987; Cockcroft 1984), has brought PLD signaling to the very forefront of current biological and biomedical research. Meanwhile, phosphatidylcholine-hydrolyzing PLD has been identified in bacteria, protozoa, fungi, plants and animals, and, due to this widespread distribution, is assumed to be involved in the regulation of fundamental cellular functions. Indeed, it has now been established that activation of PLD and the generation of PA by a vast number of membrane receptors modulate such a wide array of cellular responses as calcium mobilization, secretion, superoxide production, endocytosis, exocytosis, vesicle trafficking, glucose transport, rearrangements of the actin cytoskeleton, mitogenesis and survival (Cockcroft 2001; Exton 2002b; Jenkins and Frohman 2005; Liscovitch et al. 2000).
PIP2 is a critical cofactor for PLD, and profoundly affects the activity, membrane localization and receptor activation of both PLD isoforms, PLD1 and PLD2 (Brown et al. 1993; Hodgkin et al. 2000; Liscovitch et al. 1994; Pertile et al. 1995; Schmidt et al. 1996d). Thus, reduction of cellular PIP2 levels, for instance via scavenging of PIP2 by the actin-binding protein fodrin (Lukowski et al. 1998) or via forced PIP2 hydrolysis by the phosphatase synaptojanin (Chung et al. 1997), has been shown to inhibit PLD activity. Vice versa, the synthesis of PIP2 by phosphoinositide 5-kinase (PIP5K) isoforms can be directly stimulated by the PLD product PA (Jenkins et al. 1994; Moritz et al. 1992), and this regulation has also been confirmed to occur at the whole cell level (Divecha et al. 2000; Jones et al. 2000b; Skippen et al. 2002). It is now hypothesized that the reciprocal stimulation of PLD and PIP5K enzymes enables rapid feed-forward stimulation loops for a localized and explosive generation of PA and PIP2, which may then govern the recruitment and activation of proteins to execute specific cellular tasks, especially membrane trafficking, and changes in the organization of the actin cytoskeleton. The activity and localization of both PLD and PIP5K are under control of GTPases of the Arf and Rho families, which are well-defined regulators of membrane transport and actin-reorganization processes. The reciprocal stimulation of PIP5K and PLD, and the regulation of these enzymes by ARF and Rho GTPases, point to concerted mechanisms in cellular actions, involving acute, localized PIP2 and PA synthesis (Fig. 1). This review will focus on the regulation of PLD enzymes by membrane receptors and monomeric GTPases, and on how PLD signaling is organized and connected by PIP2 metabolism.
Fig. 1Regulation and cellular roles of PLD and PIP5K. Regulation of PLD and PIP5K by ARF and Rho family GTPases is essentially involved in the regulation of intracellular vesicle trafficking and actin cytoskeleton reorganization. Both PLD and PIP5K are stimulated by cell surface receptors and by conventional PKC isoforms, and the latter can become activated after receptor-induced hydrolysis of PIP2 by PLC. Positive feed-forward regulation is achieved by stimulation of PLD by PIP5K-derived PIP2, and of PIP5K by PLD-derived PA. Activation of ARF-GAPs by PIP2 accelerates the inactivation of ARF proteins, and may terminate a round of PA and PIP2 synthesis
Phosphatidic acid and PLD isoforms
Most cellular responses following PLD activation are probably mediated by the immediate reaction product PA. PA is a multifunctional lipid that can be further metabolized to the bioactive lipids, lysophosphatidic acid (LPA) and diacylglycerol (DAG), can by itself alter membrane curvature, and can serve as a protein attachment site and affect both cellular localization and activity of various proteins, including Raf-1 kinase, protein phosphatase 1, sphingosine kinase 1, and mTOR (mammalian target of rapamycin), a key regulator of cell growth and proliferation (Jenkins and Frohman 2005). PLD enzymes can catalyze a transphosphatidylation reaction in which the phosphatidyl moiety of phosphatidylcholine is accepted by primary alcohols, thereby producing stable phosphatidylalcohol instead of PA. This transphosphatidylation reaction is widely applied to measure PLD activity in biological samples, and quenching of PA synthesis by primary alcohols has proven extremely helpful to identify the involvement of PLD enzymes in cell physiology. In this way, a role for PLD has been demonstrated in a variety of signaling processes, such as activation of phosphoinositide (PI3K, PIP5K) and protein (Akt, ERK1/2) kinases, calcium mobilization, cytoskeleton remodeling, endocytosis, exocytosis, membrane trafficking, superoxide production, glucose transport, cell migration, cell proliferation, and survival signaling (Exton 2002a; Foster and Xu 2003).
There are two mammalian PLD genes, PLD1 and PLD2. PLD1 has a low basal activity and is extensively regulated by conventional protein kinase C (PKCα, -β, -γ) isozymes and small GTPases of the ARF (ARF1 - ARF6) and Rho (RhoA, Rac1, Cdc42) families (Henage et al. 2006). PLD2 has a higher basal activity than PLD1, but has been shown to respond to ARF and PKC as well (Chen and Exton 2004). PIP2 is recognized to be the most important cofactor for PLD, and both PLD isoforms are absolutely dependent on PIP2 for activity. Experiments utilizing inactive PLD mutants and RNA interference have discriminated isoform-specific PLD functions, and showed that PLD1 is involved in agonist-induced secretion, actin organization, and cell adhesion and migration (Exton 2002a; Iyer et al. 2006; Kim et al. 2006; Vitale et al. 2001), and PLD2 in endocytosis and recycling of membrane receptors (Du et al. 2004; Koch et al. 2006; Padrón et al. 2006).
The PLD isoforms, both with two splice variants, share an ~50% amino-acid sequence identity (Colley et al. 1997; Hammond et al. 1995, 1997; Steed et al. 1998). The catalytic core of both PLD enzymes are composed of four conserved domains (domain I-IV), and the HKD motifs in the domains II and IV probably associate together to form a catalytic centre (Xie et al. 2000). PLD1 is characterized by a 116-amino acid loop region following domain II, which has been proposed to function as a negative regulatory element (Sung et al. 1999). PLD1 and PLD2 further possess N-terminal PH (pleckstrin homology) and PX (phox homology) domains. PIP2 binds to the PH domain (Hodgkin et al. 2000), but also to a polybasic PIP2 binding motif within the catalytic core (Sciorra et al. 1999), and interaction of PIP2 with both domains has been suggested to be involved in membrane targeting of PLD as well as stimulation of PLD catalytic activity (Du et al. 2003; Hodgkin et al. 2000; Sciorra et al. 2002). The PX domain of PLD1 has been reported to preferentially bind to phosphatidylinositol-3,4,5-trisphosphate (PIP3) (Lee et al. 2005; Stahelin et al. 2004), but interaction with PI5P has been observed as well (Du et al. 2003). Recently, it was shown that the PX domain of PLD has GTPase-activating protein (GAP) activity towards dynamin, and that PLD supports EGF receptor endocytosis (Lee et al. 2006). The PH and PX domains probably contribute to the proper localization of the PLD enzymes within cells. In line with a role for PLD enzymes in different cellular tasks, PLD1 and PLD2 show a diverse subcellular distribution. PLD1 is found throughout the cell, but primarily localizes to perinuclear endosomes and the Golgi apparatus (Brown et al. 1998; Freyberg et al. 2001; Hughes and Parker 2001). PLD2 is almost exclusively present at the plasma membrane in lipid raft fractions (Czarny et al. 1999). The localization of PLD1 does not seem to be static, and regulated translocation and recycling of the enzyme between cellular compartments may be crucial to its proper functioning. In an elegant study, coordinated subcellular targeting of the lipid binding motifs has been demonstrated to drive this subcellular cycling of PLD1 (Du et al. 2003). Upon stimulation, PLD1 was found to translocate from the intracellular compartments to the plasma membrane, and this process was probably dependent on the polybasic PIP2 binding site. The PH domain then facilitated entry of PLD1 into lipid rafts, a step critical for internalization of the enzyme, whereafter interaction of the PX domain with PI5P may control the efficient return of PLD1 to the endosomes.
PIP2 and PIP5K isoforms
PIP2 is an essential and versatile factor in cellular signaling. Hydrolysis of PIP2 by PLC into the second messengers, inositol-1,4,5-trisphosphate (IP3) and DAG, is a general and well-defined answer of cells in response to stimulation of many membrane receptors (Schmidt et al. 2004). Phosphorylation of PIP2 by PI3K results in the rapid accumulation of PIP3, which recruits and activates mediators involved in actin remodeling, mitogenesis and survival (Vanhaesebroeck et al. 2001). But it is now recognized that PIP2, as well as other phosphoinositides, are signaling molecules by themselves and can, by binding to unique phosphoinositide-binding sequences, such as the PH and PX domains, affect the activity and subcellular localization of many proteins, including many actin regulatory proteins, a wide range of ion channels, and PLD (Niggli 2005; Suh and Hille 2005; Yin and Janmey 2003). In this way, PIP2 can modulate a remarkable variety of cellular processes, including cortical actin organization, membrane ruffling, vesicle trafficking, gene expression, cell migration and cell survival (Ling et al. 2006; Oude Weernink et al. 2004b; Toker 2002). Subsequent dephosphorylation of PIP2 by inositol polyphosphate 5-phosphatases, such as synaptojanin, is believed to terminate local PIP2 signaling, for instance in the process of vesicle trafficking (Majerus et al. 1999).
To execute this variety of functions, PIP2 may be organized in discrete functional pools within cells, but the existence of PIP2 clusters in the plasma membrane is currently under debate. Using green fluorescent protein-tagged PH domains or antibodies to visualize PIP2, the lipid was found to concentrate in highly dynamic, actin-rich regions (Tall et al. 2000) and lipid rafts (Laux et al. 2000; Parmryd et al. 2003) in the plasma membrane, feeding the idea that spatially organized PIP2 synthesis regulates actin polymerization and other cellular processes. The localization of PIP2 in rafts is supported by biochemical data (Pike and Casey 1996); however, specific PIP2 clustering has been disputed (van Rheenen et al. 2005).
PIP2 is generated after phosphorylation of phosphatidylinositol-4-phosphate by PIP5K. In mammals, cDNAs encoding three isoforms of PIP5K (designated Iα, Iβ and Iγ) with alternative splice variants have been cloned and characterized (Ishihara et al. 1996, 1998; Loijens and Anderson 1996). Sequence analysis has shown that PIP5K enzymes are related to PIP4K enzymes, but that they share no identity with most other lipid (PI3K and PI4K) or protein kinases. The sequence similarity between the PIP4Ks and PIP5Ks is clustered in the catalytic core of the kinases (Anderson et al. 1999; Hinchliffe et al. 1998). An activation loop spanning the catalytic domain has been shown to determine both substrate specificity and subcellular targeting of PIP5Ks, which can be swapped by substitution of a single amino acid within this loop (Kunz et al. 2002). In murine PIP5K-Iβ, two dimerization domains were identified, which may contribute to the proper subcellular localization and functioning of the enzyme (Galiano et al. 2002).
The identification of three PIP5K isoforms raised the expectation of a differential regulation of the enzymes by cellular signal transduction components, but up to now the regulatory properties of PIP5K-Iα, Iβ and Iγ appear to be remarkably similar. All PIP5K isoforms are stimulated by PA, are extensively regulated by ARF and Rho GTPases, and inhibited by protein kinase A (PKA) and PI-stimulated autophosphorylation (Oude Weernink et al. 2004b). Nevertheless, evidence has been provided that PIP5K isoforms may selectively control functional PIP2 pools, which may support particular processes in different cell types. Thus, actin reorganization down-stream of Rac1 in platelets specifically involves murine PIP5K-Iα (Tolias et al. 2000). Human PIP5K-Iα was found to localize in Rac1-induced membrane ruffles, and the LIM protein Ajuba has been identified to interact with and stimulate PIP5K-Iα in leading-edge membrane ruffles in migrating cells (Kisseleva et al. 2005). Human PIPK-Iβ was detected primarily in cytosolic vesicular structures (Doughman et al. 2003) and may synthesize the PIP2 pool involved in constitutive endocytosis (Padrón et al. 2003). The long-splice variant of PIP5K-Iγ, PIP5K-Iγ90, is enriched in neurons and is implicated in the regulation of clathrin coat recruitment, actin dynamics (Wenk et al. 2001) and focal adhesion formation (Di Paolo et al. 2002; Ling et al. 2002). In contrast, short PIP5K-Iγ87 seems to be the major producer of the PIP2 pool that supports receptor-induced IP3 generation (Wang et al. 2004).
The execution of specific PIP2-modulated processes is very probably achieved by an orchestration of appropriate signaling partners within discrete subcellular microdomains, and PLD-derived PA as well as the PLD enzymes by themselves can contribute to this organization. Indeed, both PLD1 and PLD2 interact with PIP5K-Iα, and PLD2 recruits PIP5K-Iα to a submembraneous vesicular compartment (Divecha et al. 2000). PLD2-derived PA was shown to stimulate PIP5K-Iγ splice variants, and the subsequent formation of PIP2 to drive the initial stages of integrin-mediated cellular adhesion (Powner et al. 2005). In many processes, the temporal activation and correct localization of PLD and PIP5K isoforms by monomeric GTPases appears crucial to achieve the spatially organized production of PIP2 and PA (Santarius et al. 2006).
ARF GTPases and membrane traffic
Although the direct interaction site on PLD for ARF has not yet been unequivocally defined, it is well established that ARF proteins, particularly ARF1 and ARF6, activate both PLD enzymes, but especially PLD1 (Hammond et al. 1995, 1997). ARF GTPases regulate intracellular vesicle trafficking and actin remodeling. ARF1 is localized to the Golgi complex, and is required for proper Golgi structure and function. The use of primary alcohols has also pointed to a role for PLD in vesicle transport to Golgi (Bi et al. 1997; Ktistakis et al. 1996). PLD activity has been shown to stimulate the release of nascent secretory vesicles from the trans-Golgi network (Chen et al. 1997), and to be required for maintaining the structural integrity and function of the Golgi apparatus, but the precise role for PLD in vesicle formation is still controversial. PIP5K is also a direct effector of ARF1, and an ARF1 mutant that selectively activates PIP5K, but not PLD activity, demonstrated that both PLD-derived PA and direct activation of PIP5K by ARF1 contribute to increased PIP2 synthesis (Skippen et al. 2002). In permeabilized cells, ARF1 has been shown to restore secretion by promoting PIP2 synthesis (Fensome et al. 1996), and ARF1-mediated PIP5K activation (Jones et al. 2000a) and recruitment to the Golgi complex (Godi et al. 1999) appears to be critical in Golgi functioning.
ARF6 regulates vesicular transport, secretion, and cortical actin reorganization. ARF6 activates PLD, and PA has been implicated in the mediation of the effects of ARF6 in vesicular trafficking events. A critical role for PLD1 in exocytosis has been established in different cell types, including neurons (Humeau et al. 2001), neuroendocrine cells (Vitale et al. 2001) and pancreatic β cells (Hughes et al. 2004). PLD2 has recently emerged as a mediator of ARF-dependent internalization of the μ-opioid receptor (Koch et al. 2003), and both PLD isoforms have been implicated in macrophage phagocytosis (Corrotte et al. 2006; Iyer et al. 2004). In addition, PIP5K colocalizes and interacts with, and is directly activated by ARF6 at the plasma membrane (Honda et al. 1999), and ARF6 and PIP2 colocalize on the plasma membrane and on endosomal structures (Brown et al. 2001). ARF6-organized PIP2 turnover at the plasma membrane is apparently involved in regulated secretion (Aikawa and Martin 2003; Brown et al. 2001; Lawrence and Birnbaum 2003). Focal and transient accumulation of PIP2 by PIP5K is required for phagocytosis as well (Botelho et al. 2000; Coppolino et al. 2002; Wong and Isberg 2003), and PIP2 hydrolysis probably dictates the remodeling of actin necessary for completion of phagocytosis (Scott et al. 2005). The synthesis of PIP2 is essential for priming the exocytotic apparatus, and the recruitment and activation of PLD1 by PIP2 seems the primary mechanism for the functional integration of PLD1 into the exocytotic pathway (Vitale et al. 2001; Waselle et al. 2005). Thus, CD16-induced cytolytic granule secretion mediated by ARF6 was shown to involve PIP5K-Iα membrane targeting and activation of both PIP5K and PLD (Galandrini et al. 2005). PIP2 also recruits additional proteins—for instance the endocytic proteins AP-2, epsin and AP180—to initiate clathrin-coat formation preceding endocytosis (Ford et al. 2001; Itoh et al. 2001; Padrón et al. 2003), and CAPS (Grishanin et al. 2004) to initiate dense-core vesicle exocytosis. Direct activation of PIP5K-Iγ by ARF6 has been shown to stimulate clathrin-coat recruitment to synaptic membranes to allow synaptic vesicle recycling (Krauss et al. 2003). PLD-derived PA may directly contribute to vesicle fusion in a biophysical manner, as PLD cleaves the non-fusogenic lipid, PC, to form the fusogenic lipid, PA. But PA also takes a function as an essential cofactor for PIP5K, and disruption of Golgi membranes (Sweeney et al. 2002), blockade of clathrin-coat assembly (Arneson et al. 1999) and inhibition of ARF1-reconstituted secretion (Way et al. 2000) after quenching of PA production could be attributed to inhibited PIP2 synthesis. Thus, both PLD and PIP2 synthesis seem necessary for membrane trafficking aspects in the endo- and exocytotic machinery. But PLD and PIP5K also mediate other processes down-stream of ARF6. Epidermal growth factor (EGF)-induced membrane ruffling requires ARF6-induced PIP5K-Iα translocation to the ruffles and local PIP2 production. This leads to the recruitment of PLD2, and PLD-derived PA and ARF6 may then synergistically activate PIP5K (Honda et al. 1999).
The relationship between ARF and PIP2 is also bidirectional, as phosphoinositides can regulate ARF activity by binding and activating both ARF-specific guanine nucleotide exchange factors (ARF-GEFs) (Klarlund et al. 1998; Paris et al. 1997) and ARF-GTPase-activating proteins (ARF-GAPs) (Kam et al. 2000; Nie et al. 2002) via their PH domains. The fact that ARF-GAPs bind PIP2 with high affinity and specificity offers an attractive feed-back mechanism for terminating ARF activation after a cycle of ARF-induced PIP2 synthesis.
Rho GTPases and actin dynamics
PA formation, especially by PLD1, has been reported to induce stress fibre formation in specific cell types (Cross et al. 1996; Ha and Exton 1993; Kam and Exton 2001; Porcelli et al. 2002). Rho proteins, in particular RhoA, Rac1 and Cdc42, which control actin cytoskeleton reorganization, exclusively activate PLD1 by direct interaction with its C-terminus (Exton 2002b; Powner and Wakelam 2002). Thus, PLD stimulation by RhoA may happen by direct interaction, but may involve indirect, Rho-dependent mechanisms as well. Inactivation of Rho GTPases, with Clostridium difficile toxin B or Clostridium botulinum C3 exoenzyme, reduced cellular PIP2 levels, resulting in inhibiton of receptor-mediated PIP2 hydrolysis by PLC (Schmidt et al. 1996a) as well as diminished PLD stimulation (Schmidt et al. 1996d). As the inhibition of PLD signaling after Rho inactivation could be largely rescued by the addition of PIP2, Rho proteins do seem to affect PLD via PIP5K regulation (Schmidt et al. 1996c,d). PIP2 is well-known to associate with and regulate the activity of a plethora of actin-binding proteins that organize actin dynamics (Hilpela et al. 2004; Yin and Janmey 2003), and PA and PIP2 may act in concert to mediate Rho-dependent actin cytoskeleton remodeling. PIP5K isoforms are, like PLD, under direct control of Rho GTPases. PIP5K isoforms are markedly stimulated by RhoA, Rac1, and Cdc42 (Chong et al. 1994; Hartwig et al. 1995; Oude Weernink et al. 2004a), and physically associate with both RhoA (Ren et al. 1996) and Rac1 (Tolias et al. 2000), but not with Cdc42 (Oude Weernink et al. 2004a; van Hennik et al. 2003). PIP5K isoforms are now seen as critical mediators of RhoA- and Rac1-induced actin organization and remodeling (Doughman et al. 2003; Shibasaki et al. 1997; Tolias et al. 2000). The established Rho effector Rho-kinase, a serine/threonine kinase, is apparently involved in Rho-dependent regulation of both PLD (Schmidt et al. 1999) and PIP5K activities (Oude Weernink et al. 2000), and PIP5K was found to play an essential role as down-stream effector of Rho and Rho-kinase in neurite remodeling (van Horck et al. 2002; Yamazaki et al. 2002) and platelet cytoskeleton assembly (Gratacap et al. 2001; Yang et al. 2004). But Rho may also directly signal to PIP5K independently of Rho-kinase, as RhoA-induced activation of ERM (ezrin, radixin, moesin) proteins, that cross-link actin filaments to plasma membranes, was found to be mediated by PIP5K, but not by Rho-kinase (Matsui et al. 1999). PLD and PIP5K were also demonstrated to collectively mediate Rho-induced changes in the actin cytoskeleton. Thus, myogenic differentiation induced by arginine-vasopressin, which involves actin fiber formation, is mediated by Rho proteins and PLD1, and involves PLD-induced PIP2 synthesis along the actin fibers (Komati et al. 2005). These findings suggest that PLD and PIP5K enzymes may co-operate down-stream of Rho in processes that depend on actin organization.
Another Rho effector, PKC-related protein kinase N (PKN), also directly interacts with PLD (Oishi et al. 2001) and mediates PLD activation by the α1-adrenergic receptor (Parmentier et al. 2002). Interestingly, components of the actin regulatory machinery, β-actin and α-actinin, have been found to directly associate with and inhibit the activity of PLD isoforms (Lee et al. 2001; Park et al. 2000). PLD also binds to and is stimulated by filamentous F-actin, and PLD1 in particular may act as a signal transduction component responsive to dynamic changes of the actin cytoskeleton (Kusner et al. 2002). PKN interacts with α-actinin, and PKN may modulate PLD signaling by reversing the inhibitory effect of α-actinin on PLD1, and by direct interaction with PLD1.
Regulation of PLD and PIP5K by membrane receptors
In line with the critical role of PA in cellular processes, the enzymatic activity of PLD is tightly regulated by a variety of hormones, neurotransmitters, and growth factors. Regulation of PLD enzymes by membrane receptors, including G protein-coupled receptors (GPCRs) and receptor tyrosine kinases (RTKs), is complex and mediated by several cytosolic factors, including PKC as well as ARF, Rho and Ras GTPases (Exton 2002b; Liscovitch et al. 2000; López De Jesús et al. 2006; Powner and Wakelam 2002). Most receptors that stimulate PLD also increase PLC activity, leading to activation of the PLD regulator PKC, and it was assumed that PLD activation might be secondary to PLC activation. A physical association between PLD with PKC isoforms has been reported, resulting in strong activation of in vitro PLD1 activity, and the major interaction site was identified within the N-terminus of PLD1 (Park et al. 1998). Indeed, inhibition of PKC was shown to reduce receptor-induced PLD responses, and PLD1 mutants unresponsive to PKC did respond poorly to activation of GPCRs (Zhang et al. 1999) or to active Gαq proteins (Xie et al. 2002). However, stimulation of PLD in several receptor systems, including M3 muscarinic and α1-adrenergic receptors, was actually PKC-independent (Balboa and Insel 1998; Muthalif et al. 2000; Rümenapp et al. 1997; Schmidt et al. 1994), suggesting that PLD stimulation must not necessarily be secondary to PLC stimulation.
Brefeldin A, an inhibitor of certain ARF-GEFs, reduced receptor signaling to PLD in several cell types, indicating that ARF proteins participate in receptor-mediated PLD stimulation (Fensome et al. 1998; Mitchell et al. 1998; Rümenapp et al. 1995; Shome et al. 2000). Likewise, sequestration of ARF-GEFs by the ARF-related protein ARP inhibited M3 muscarinic receptor signaling to PLD (Schürmann et al. 1999). Clostridial toxins and enzymes that specifically inactivate Rho proteins and expression of inactive Rho mutants have been used to identify the role of Rho in signaling to PLD. Thus, Rho proteins were found to be involved in PLD stimulation by GPCRs (M3 muscarinic, bradykinin, sphingosine-1-phosphate and LPA), RTKs (PDGF, EGF), and immunoglobulin (FcεRI) receptors (Hess et al. 1997; Ojio et al. 1996; Schmidt et al. 1996c).
Stimulation of PLD by GPCRs was shown to be mediated by both pertussis toxin (PTX)-insensitive (Gosau et al. 2002; Schmidt et al. 1994) and PTX-sensitive (Cummings et al. 2002; Fensome et al. 1998) heterotrimeric G proteins. G12 family proteins can stimulate PLD (Plonk et al. 1998), and RGS (regulators of G protein signaling) proteins, that act as α subunit-specific GAPs, have been used to position G12 in PLD activation by the M3 muscarinic (Rümenapp et al. 2001), the PAR1 (Fahimi-Vahid et al. 2002), and the Ca2+-sensing receptor (Huang et al. 2004), as well as mechanical force (Ziembicki et al. 2005). As forskolin and cAMP were shown to cause activation of PLD via PKA and ERK1/2 (Ginsberg et al. 1997; Yoon et al. 2005) or, alternatively, via the cAMP-activated GEF for Ras-like GTPases, Epac and R-Ras (López De Jesús et al. 2006), Gs proteins also mediate stimulation of PLD. PLD activation is also controlled by βγ-subunits, possibly via Src and/or ARF6 (Le Stunff et al. 2000; Ushio-Fukai et al. 1999), but Gβγ can also directly interact with and inhibit PLD (Preininger et al. 2006).
As the precise mechanism of PLD stimulation in intact cells was only poorly understood, during the last 10 years our laboratory in Essen has focused on the regulation of PLD activity by membrane receptors. In HEK-293 cells, signaling to PLD by a typical GPCR, the M3 muscarinic receptor, and an RTK, the EGF receptor, was studied and shown to be executed by several distinct pathways (Fig. 2). In addition, by expressing inactive PLD mutants, the M3 muscarinic and the EGF receptors were found to signal to individual PLD isozymes and to selectively stimulate PLD1 and PLD2 respectively (Han et al. 2001). The M3 muscarinic receptor stimulates both PLC and PLD via PTX-insensitive mechanisms (Offermanns et al. 1994; Peralta et al. 1988; Schmidt et al. 1994). Interestingly, stimulation of PLD by the agonist carbachol was not affected by PKC inhibitors, suggesting that activation of PLD by the M3 muscarinic receptor was rather independent of PLC (Rümenapp et al. 1997; Schmidt et al. 1994). Expression of α-subunits of G proteins and of specific RGS proteins was used to identify the G proteins involved in these pathways, and demonstrated that whereas the M3 receptor signals to PLC via Gq proteins, activation of PLD is mediated by G12 family proteins (Rümenapp et al. 2001). PLD activation by the M3 receptor, but not by the EGF receptor, was further found to be under control of ARF (Rümenapp et al. 1995, 1997) as well as Rho proteins, particularly RhoA (Schmidt et al. 1996c,d). Likewise, regulation of mTOR by LPA, but not PDGF, involved PLD1 activation by Rho GTPases (Kam and Exton 2004). Both ARF1 and RhoA were found to become activated after M3 receptor activation (Keller et al. 1997; Rümenapp et al. 1995), and a role for Rho-kinase in RhoA-controlled PLD stimulation could be demonstrated (Schmidt et al. 1999). In further studies, it was shown that activation of PLD by RhoA and Rho-kinase is mediated by G12 and the tyrosine kinase Pyk2, whereas activation by ARF1 is mediated by G13, PI3K and the Arf-GEF ARNO (Han et al. 2003). In cardiomyocytes, Rho proteins were shown to affect signaling to PLD by both endothelin-1 and thrombin, apparently by controlling PIP2 synthesis, whereas ARF selectively affects signaling by the PAR1 receptor (Fahimi-Vahid et al. 2002).
Fig. 2Regulation of PLD by the M3 muscarinic receptor and receptor tyrosine kinases in HEK-293 cells. In human embryonic kidney (HEK-293) cells, signaling to PLD by the M3 muscarinic receptor and by typical RTKs (EGF, PDGF, insulin) is organized into rather discrete pathways and channeled by particular heterotrimeric G proteins and small GTPases (orange), specific GEF proteins (pink) and further signaling components (green). AC, adenylyl cyclase; ROCK, Rho-kinase
PLD can directly interact with RalA, and a Ras/Ral signaling cascade was shown to regulate PLD responses. In HEK-293 cells, Ras and RalA—but not Rho proteins—were located in RTK signaling to PLD, and this Ras/Ral-dependent signaling cascade was found to be dependent on PKC-α and a Ral-specific GEF (Fig. 2) (Schmidt et al. 1998; Voss et al. 1999). RalA apparently co-operates with ARF (Kim et al. 1998; Xu et al. 2003) and Rho proteins (Frankel et al. 1999; Wilde et al. 2002) to achieve full PLD activation. Likewise, Ras proteins were found to modulate PLD responses by PDGF (Lucas et al. 2000), and RalA to affect EGF receptor signaling to PLD (Lu et al. 2000). It was recently shown that direct activation of Ras-related R-Ras by Epac is involved in PLD stimulation by the M3 muscarinic receptor, apparently by coupling to Gs proteins (López de Jesús et al. 2006), but a contribution of Ral proteins to GPCR-induced PLD activation has not been found (Meacci et al. 2002). Collectively, these data demonstrate that heterotrimeric G proteins as well as small GTPases co-ordinate PLD activation by specific membrane receptors in particular cell types, and these mechanisms probably contribute to the organization of agonist-induced PA production for the execution of diverse cellular signaling tasks.
In addition, the synthesis of PIP2 can be directly stimulated by GPCRs (thrombin, LPA, M3 muscarinic) as well as RTKs (Cochet et al. 1991; Nolan and Lapetina 1990; Pike and Eakes 1987). Receptor activation leads to increased association of PIP5K with the actin cytoskeleton (Grondin et al. 1991; Payrastre et al. 1991), and receptor-induced stimulation and cytoskeletal association of PIP5K may be directly involved in actin cytoskeletal regulation and initialize the assembly of enzymes into signaling complexes. GPCR-induced stimulation of PIP2 synthesis was found to be mediated by pertussis toxin-sensitive Gi proteins (Schmidt et al. 1996b; Stephens et al. 1993), but also by G12 and Gq proteins (Oude Weernink et al. 2003). Enhanced PIP2 synthesis is also caused by conventional PKC isoforms, which may increase PIP5K activity by stimulating PIP5K dephosphorylation by the okadaic acid-sensitive protein phosphatase 1 (Park et al. 2001).
Concluding remarks
In the last decade, PLD has taken a firm position as all-round player in cellular signaling events. It is now appreciated that PLD and PIP5K act together to execute several important cellular functions, including vesicle transport, cytoskeleton dynamics and cell adhesion. Because of the reciprocal stimulation of their activities it seems inappropriate to generally assign a conventional “upstairs-downstairs” relationship to PLD and PIP5K isozymes. The localized generation of the lipid messengers by PLD and PIP5K, PA and PIP2, is clearly co-ordinated by small GTPases of the ARF, Rho and Ras families. The following picture emerges of how PLD and PIP5K may co-operate to execute their cellular tasks. Particular small GTPases, activated by membrane receptors or cellular factors, bind to PIP5K and recruit the enzyme to specific cellular compartments. Subsequent activation of PIP5K catalytic activity triggers the localized generation of PIP2, which now serves as an anchor for specific proteins, including PLD enzymes. The sequestered PLD is activated by PIP2 and the GTPases, and PLD-derived PA now, among other tasks, contributes to the activation of PIP5K. This feed-forward regulation loop depends on both PIP5K and PLD, and quenching of PA formation (by primary alcohols) or reduction of PIP2 levels (by PLC-mediated hydrolysis or dephosphorylation by phosphatases) can interrupt the snowball from rolling. PIP2 dephosphorylation may be important in the cell as a decisive mechanism to terminate the localized reactions before a cellular avalanche develops. Attractive candidates are further specific GEFs and GAPs for the GTPases, some of which have been shown to be directly regulated by PIP2. PIP2-dependent inactivation of the organizing GTPase may then provide the final turn-off signal.

phospholipase d
pip2
phosphatidic acid
ras
arf
rho
phosphoinositide 5-kinase