PhD Peter Spégel
email: peter.spegel@med.lu.se

Siri Malmgren

Vladimir V Sharoyko

Philip Newsholme

Thomas Koeck

Hindrik Mulder

Metabolomic analyses reveal profound differences in glycolytic and tricarboxylic acid cycle metabolism in glucose-responsive andunresponsive clonal -cell lines

Keywords: Hypoxia-induced factor, HIF, pancreatic islets, insulin, Type 2 Diabetes, mitochondria

Insulin secretion from pancreatic ß-cells is controlled by complex metabolic and energetic changes provoked by exposure to metabolic fuels. Perturbations in these processes lead to impaired insulin secretion, the ultimate cause of Type 2 Diabetes. To increase our understanding of stimulus-secretion coupling and metabolic processes potentially involved in the pathogenesis of Type 2 Diabetes, a comprehensive investigation of the metabolic response in the glucoseresponsive INS-1 832/13 and glucose-unresponsive INS-1 832/2 -cell lines was performed. For this metabolomics analysis, we used gas chromatography/mass spectrometry combined with multivariate statistics. We found that perturbed secretion in the 832/2 line was characterized by disturbed coupling of glycolytic and TCA-cycle metabolism. The importance of this metabolic coupling was reinforced by our observation that insulin secretion partially could be reinstated by stimulation of the cells with mitochondrial fuels which bypass glycolytic metabolism. Furthermore, metabolic and functional profiling of additional ß-cell lines (INS-1, INS-1 832/1) confirmed the important role of coupled glycolytic and TCA-cycle metabolism in stimulussecretion coupling. Dependence of the unresponsive clones on glycolytic metabolism was paralleled by increased stabilization of hypoxia-induced factor 1 (HIF-1 ). The relevance of a similar perturbation for human Type 2 Diabetes was suggested by increased expression of HIF-1 target genes in islets from Type 2 Diabetes patients.

INTRODUCTION

Failure of the pancreatic -cells to release insulin appropriately is a major pathogenetic abnormality in Type 2 Diabetes. Insulin secretion from -cells is controlled by two different mechanisms: the triggering (K ATP -dependent) and the amplifying (K ATP -independent) pathways [1]. While the triggering pathway has been thoroughly characterized [2,3], the mechanisms and signals underlying the amplifying pathway remain largely unknown [4,5]. Yet, several metabolites, mainly originating from mitochondrial metabolism, have been implicated as potential coupling factors in the amplifying pathway of glucose-stimulated insulin secretion (GSIS). These include long-chain acyl-CoAs [6], glutamate [7], and NADPH [8,9].

In the present study, the metabolome of two clonal -cell lines, the glucose-responsive 832/13 and the glucose-unresponsive 832/2 line, both derived from the INS-1 rat insulinoma cell line [10], were examined. This enabled us to investigate possible differences in metabolic regulation that underlie perturbed function of the 832/2 cells. Expression of several glycolytic and tricarboxylic acid (TCA) cycle enzymes has previously been found to differ between these cell lines [11]. Most strikingly, the 832/2 cells were found to express lactate dehydrogenase A (LDH-A) and release lactate. Hence, the glucose-unresponsive 832/2 line relied heavily on glycolytic metabolism, while the robust insulin secretor, the 832/13 line, exhibited strong glucose concentration-dependent coupling of cytosolic and mitochondrial fuel metabolism. Moreover, it has previously been shown that 832/13 cells are characterized by an active anaplerotic pathway, which is less pronounced in 832/2 cells [12]. Nevertheless, a detailed analysis of the impact of these metabolic differences on the levels of individual metabolites and how they are controlled has not yet been performed.

To date, the bulk of investigations on the coupling of -cell metabolism to insulin secretion has been performed in a univariate fashion. One or a few metabolites or metabolic enzymes have been studied at a time. Due to the complexity of the metabolic networks, univariate investigations are likely to be insufficient. An unbiased characterization of metabolism is therefore warranted. Thus, in the present study, gas chromatography/mass spectrometry (GC/MS)-based metabolomics [13-15] combined with multivariate statistical analyses [16] were applied to investigate the metabolome. These metabolomic analyses generated hypotheses, which we aimed to verify with functional studies and analysis of human islets.

A prominent finding was the lacking response of levels of late glycolytic and TCA cycle intermediates in the unresponsive 832/2 cell line despite an increase in extracellular glucose. The perturbed coupling of cytosolic and mitochondrial metabolism could partially be circumvented by specifically stimulating mitochondrial metabolism. This manoeuvre reinstated fuel-stimulated mitochondrial respiration and insulin secretion. Interestingly, we found that hypoxia-inducible factor 1 (HIF-1 ), a transcription factor regulating the balance between glycolytic and mitochondrial metabolism, was stabilized in the glucose-unresponsive cells.

EXPERIMENTAL Metabolomics

Clonal ß-cell lines INS-1 832/2 and INS-1 832/13 were stimulated with either 2.8 or 16.7 mM glucose for 1 h followed by an unbiased analysis of the metabolome using GC/MS. The generated data were normalized and evaluated using multivariate statistics to highlight alterations in metabolite levels unique to or shared between the two cell lines. To validate the finding in the 832/2 and 832/13 clones, a metabolite profiling of the glucose responsive INS-1 and the glucose unresponsive INS-1 832/1 clones was undertaken. Details of the metabolomics protocols are found in the Supplemental information.

Insulin secretion

INS-1, 832/1, 832/2 and 832/13 clones were cultured in 24-well culture plates to reach 90-95 % confluency, whereafter insulin was assayed as previously described in detail [10]. Insulin secretion was measured after incubation for 1 h in 2.8 mM glucose, 16.7 mM glucose or 10 mM leucine and 10 mM glutamine.

Oxygen consumption

The oxygen consumption rate (OCR) was measured in the 832/2 and 832/13 clones using the Extracellular flux (XF) analyzer XF24 (Seahorse Bioscience, Billerica, MA), as previously described in detail [11]. Following a pre-incubation at 2.8 mM glucose for 2 h, the OCR was assayed at 2.8 mM glucose subsequent to a transition to 16.7 mM glucose or 2.8 mM glucose together with 10 mM leucine and 10 mM glutamine. OCRs were first normalized by protein content and then by the average basal OCR at 2.8 mM glucose. An area under the curve analysis was performed for fuel-stimulation conditions.

Glucose uptake

The cells were prepared as for analysis of insulin secretion [10]. After removing the secretion assay buffer (SAB), 500 µl of SAB containing 3-O-methyl-D-[3H(N)]glucose (specific activity, 80.2 Ci/mmol; PerkinElmer Life Sciences) and 3-O-methyl-D-glucose to a final concentration of 2.8 or 16.7 mM 3-O-methyl-D-glucose, respectively, were added to each well. Cells were incubated for 10 min at 37 °C. Next, 250 µl of lysis buffer containing 200 mM NaCl, 2 mM EDTA, 50 mM Tris-HCl (pH 7.4) and 1% SDS were added. Subsequently, 150 µl of lysate were transferred into scintillation vials. Protein content was determined by the bicinchoninic acid (BCA) method. 3-O-methyl-D-[3H(N)]glucose content was measured by liquid scintillation spectrometry [17].

Western blotting

Whole cells were solubilized in homogenization buffer (100 mM HEPES, 9 M urea, 1% Triton X-100, 2 mM EDTA, pH 7.2) mixed 1:100 (v/v) with protease inhibitor cocktail (Sigma, St. Louis, MO). Protein content was determined by the BCA method. Samples were mixed 1:10 (v/v) with loading buffer (100 mM HEPES, 10% SDS, 10% dithiothreitol, 20% glycerol, pH 7.2). 40 g protein were run on an 8% SDS-PAGE gel, and subsequently blotted onto PVDF membranes. HIF-1 protein was detected with a primary mouse anti-HIF-1 monoclonal antibody (Abcam, Cambridge, UK) in dilution 1:500 (v/v). -Tubulin was detected with a primary rabbit polyclonal antibody (Santa Cruz Biotechnology, Santa Cruz, CA, USA) in dilution of 1:400 (v/v). Horse-radish peroxidase-coupled goat-anti-rabbit IgG (1:8000, v/v), goat-anti-mouse IgG (1:6000, v/v), and donkey-anti-goat IgG (1:8000, v/v) (Santa Cruz Biotechnology, Santa Cruz, CA) were used as secondary antibodies. Blots were developed with enhanced chemiluminescence (ECL) and detection was by Amersham Hyperfilm ECL (Amersham Biosciences, Uppsala, SE). Films were scanned using the Bio-Rad GS-800 Calibrated Densitometer (Bio-Rad, Sundbyberg, SE). Measurements obtained for HIF-1 were corrected for protein loading with -tubulin. For loading control blots were stripped with 2% SDS, 100 mM 2-mercaptoethanol, 62.5 mM Tris-HCl, pH 6.7.

Human islets

Human pancreatic islets from 55 non-diabetic and 9 T2D deceased donors were obtained from the Human Tissue Laboratory at Lund University Diabetes Centre. The 29 male and 26 female nondiabetic donors were aged 56.7± 9.8 years, had a BMI of 25.9 ± 3.6 kg/m 2 and HbA 1 c of 5.7 ± 0.8. The 5 male and 4 female T2D donors were aged 57.0 ± 13.1 years, had a BMI of 28.5 ± 4.7 kg/m 2 and HbA 1 c of 7.3 ± 1.2. Islets were prepared by collagenase digestion and density gradient purification. After isolation, islets were cultured free floating in CMRL 1066 culture medium (ICN Biomedicals, Costa Mesa, CA, USA) supplemented with 10 mmol/l HEPES, 2 mmol/l 1-glutamine, 50 µg/ml gentamicin, 0.25 µg/ml Fungizone (GIBCO BRL, Gaithersburg, MD, USA), 20 µg/ml ciprofloxacin (Bayer Healthcare, Leverkusen, Germany), and 10 mmol/l nicotinamide at 37°C (5% CO 2 ) prior to RNA and DNA preparation. The donor before death or her/his relatives upon admission to Intensive Care Unit (ICU) had given their consent to donate organs and the local ethics committees approved the protocols.

Total RNA was isolated with the AllPrep DNA/RNA Mini Kit (Qiagen GmbH, Hilden, Germany). The microarrays were performed following the Affymetrix standard protocol. Briefly, 200 ng total RNA were processed following the GeneChip® Expression 3'-Amplification Reagents Onecycle cDNA synthesis kit instructions (Affymetrix Inc, Santa Clara, CA, US) to produce doublestranded cDNA. This was used as a template to generate biotin-targeted cRNA following 's specifications. 15 g of the biotin labeled cRNA were fragmented to strands between 35 and 200 bases in length, 10 g of which were hybridized onto the GeneChip® Human Gene 1.0 ST whole transcript based assay overnight in the GeneChip® Hybridization oven 6400 using standard procedures. The arrays were washed and stained in a GeneChip® Fluidics Station 450. Scanning was carried out with the GeneChip® Scanner 3000 and image analysis was performed using GeneChip® Operating Software. The array data were summarized and normalized with Robust Multi-array Analysis (RMA) method using the software "Expression Console" (Affymetrix).

Statistical analysis

All data are shown as mean ± standard deviation or standard error of the mean for indicated number of experiments. A Mann-Whitney U-test was used to compare data from human islets. Unless stated otherwise, Student's t-test was used when comparing two groups. The Kruskal-Wallis test in combination with Mann-Whitney followed by Bonferroni´s test post hoc was applied for the analysis of HIF-1 protein expression.

RESULTS

Metabolomics

Multivariate statistical calculations were performed to identify which metabolites out of the 164 detected were uniquely regulated by the glucose stimulation in the INS-1 832/2 and the INS-1 832/13 clones (see Supplemental information). These analyses revealed a unique regulation of the late glycolytic and TCA-cycle intermediates in the 832/13 clone (Figure 1A andB). Whereas glucose-6phosphate was found to exhibit a glucose-stimulated increase in both cell lines, downstream intermediates 3-phosphoglycerate, 2-phosphoglycerate, phosphoenolpyruvate and pyruvate were found to increase exclusively in the glucose responsive 832/13 clone. This lack of response in the 832/2 clone was reflected also by the levels of the TCA-cycle intermediates; levels of all measured TCA-cycle intermediates increased in the 832/13 clone whereas they were unaltered in the 832/2 clone (Figure 1B). The fold of the glucose-stimulated increase in lactate was similar in the two clones (Figure 1A), although the levels were significantly higher in the un-responsive clone (see Supplementary Figures S4 andS8). The level of the pentose phosphate shunt intermediate ribose-5phosphate rose more in the glucose responsive 832/13 clone.

Oxygen consumption

Given the lack of rise in TCA-cycle intermediates in the 832/2 clone in response to glucose, we were interested to find out whether this had any further functional implications. To this end, we chose to assess oxygen consumption, which reflects overall mitochondrial activity. Based on an area under the curve analysis, glucose stimulation caused a sustained 1.84 ± 0.26-fold (n=7) increase in OCR in the 832/13-clone, whereas no change in OCR was observed upon glucose stimulation of the 832/2-clone (Figure 2A,C). However, leucine and glutamine increased the OCR in both clones; OCR was significantly increased 1.81 ± 0.18-fold (n=6) and 1.26 ± 0.07-fold (n=6) in 832/13 and 832/2 cells, respectively (Figure 2B,C), compared with respiration at 2.8 mM glucose alone.

Insulin secretion

The lack of a glucose-stimulated response in levels of TCA-cycle intermediates in the glucoseunresponsive 832/2 clone is likely to constrain insulin secretion via both the triggering pathway, which is dependent on the mitochondrial ATP production, and the amplifying pathway, which has been suggested to be coupled to TCA-cycle metabolism. Basal insulin secretion at 2.8 mM glucose was 15.9 ± 1.8 (n=8) and 8.39 ± 1.96 (n=6) ng/mg/h for 832/13 and 832/2 cells, respectively. Indeed, while stimulation with 16.7 mM glucose yielded a 12.6 ± 1.3-fold (n=8) increase of insulin secretion in the glucose-responsive 832/13 cell, no rise in GSIS was observed in the glucose-unresponsive 832/2 line (Figure 2D). Leucine and glutamine, on the other hand, significantly stimulated insulin secretion in 832/2 cells (2.88 ± 0.22-fold (n=6) increase vs. basal), whereas the same stimulus yielded a 14.1 ± 5.5fold (n=6) increase in the glucose-responsive 832/13 line (Figure 2D).

Metabolite profiling of additional clonal ß-cell lines

The results generated from the study of the glucose responsive 832/13-clone and the glucose unresponsive 832/2 clone suggested that insufficient coupling of glycolytic and TCA-cycle metabolism may be a factor underlying perturbed GSIS. To investigate whether this phenotype is unique for the glucose unresponsiveness of the 832/2 clone or a more general phenomenon in ß-cells, two additional ß-cell lines were investigated. To this end, the glucose-responsive INS-1 line and the glucose-unresponsive INS-1 832/1 sub-clone were examined. A targeted metabolite profiling revealed a significantly lower fold-change of glucose-stimulated alterations in glycolytic and TCA-cycle metabolite levels in the unresponsive clone (Figure 3), reminiscent of the metabolic phenotype of the 832/2 clone (Figure 1A-B).

Functional characterization of additional clonal ß-cell lines

Next, the functional consequences of the reduced response in the glycolytic and TCA-cycle intermediates upon glucose stimulation were assessed. Glucose was found to stimulate insulin secretion 6.6±2.6 fold (n=3) in the INS-1 parental clone, whereas insulin secretion from the 832/1 subclone was not stimulated by the hexose (1.2±0.3 fold, n=3). To investigate whether stimulus secretion coupling was intact and the observed lack of response in the 832/1 clone was due to insufficient coupling of glycolytic and TCA-cycle metabolism, insulin secretion in response to leucine and glutamine was also assessed. Indeed, leucine and glutamine provoked a significant (p<0.05) 7.8±2.4 fold and a 3.1±1.0 fold increase in insulin secretion in the INS-1 and the 832/1-clone, respectively.

Glucose uptake

To investigate whether differences in glucose uptake could account for the observed metabolic differences between the glucose-responsive and -unresponsive ß-cell clones, uptake of the nonmetabolizable analogue of D-glucose, 3-O-methyl-D-glucose, was assessed. No significant differences between the four clones could be observed (see Supplementary Figure S9), indicating that differences in glucose uptake alone can not explain the perturbed metabolic response in the glucose unresponsive clones.

Stabilization of HIF-1

The metabolomics data suggested that the lacking response of the 832/2-clone to glucose stimulation may be caused by impaired aerobic glycolysis concurrent with lactate production and a perturbation in the coupling between cytosolic and TCA-cycle metabolism. This together with the fact that the celllines are tumour derived [10] suggested involvement of HIF-1 . Stabilization of this protein may account for a switch of cellular metabolism to dependence on glycolysis, the so called Warburg-effect [START_REF] Warburg | On the origin of cancer cells[END_REF]. To explore this possibility, we determined the presence of HIF-1 by Western blotting. Indeed, while HIF-1 was present in all INS-1 clones, its protein levels were e.g. 227 30 % (p=0.006) higher in the glucose-unresponsive 832/2 clone, in comparison to the glucose-responsive 832/13 clone (Figure 4A-B).

It has recently been shown that a low level of -ketoglutarate in the presence of a high level of succinate stabilizes HIF-1 [START_REF] Mole | 2-oxoglutarate analogue inhibitors of HIF prolyl hydroxylase[END_REF][START_REF] Mackenzie | Cell-permeating alpha-ketoglutarate derivatives alleviate pseudohypoxia in succinate dehydrogenase-deficient cells[END_REF]. To assess whether such a mechanism is operating in the clonal cell lines, we plotted the HIF-1 protein levels against the ratios of -ketoglutarate and succinate (fold responses of the metabolite levels to glucose stimulation were employed; Figure 4C). Indeed, we observed that the lower the ratios of -ketoglutarate to succinate, the higher the protein level of HIF-1 . Next, we examined whether the change in HIF-1 protein levels coincided with metabolic changes. To this end, we plotted HIF-1 protein levels against the ratios of citrate to pyruvate (Figure 4D). The rationale for this analysis is that this ratio may reflect coupling of glycolysis and TCA-cycle activities. A low ratio would imply a low level of TCA-cycle activity, suggesting that coupling of glycolysis and TCA-cycle is perturbed. The plot clearly shows that high HIF-1 protein levels coincided with a low ratio of citrate to pyruvate in the clonal ß-cell-lines. This translated into impaired GSIS, as shown in figure 4E.

Expression of HIF-1 target genes in human islets

Stabilization of HIF-1 can establish a pseudo-hypoxic metabolic phenotype under normoxic conditions. This involves primarily increased expression of glycolytic enzymes. Thus, to investigate whether our findings in the clonal cell-lines are of relevance for the pathogenesis of Type 2 Diabetes in humans, we first analyzed expression of HIF-1 in human islets. Although HIF-1 was expressed at the mRNA-level, we did not observe any differences between human islets from healthy controls and patients with Type 2 Diabetes (data not shown). This is in agreement with the fact that signalling through HIF-1 requires stabilisation on the protein level, a phenomenon which occurs independent of changes in mRNA-level of HIF-1 [START_REF] Lendahl | Generating specificity and diversity in the transcriptional response to hypoxia[END_REF]. Instead, to ascertain whether regulation by HIF-1 occurs in human islets, we examined expression of HIF-1 target genes in human islets from healthy controls and patients with Type 2 Diabetes. Indeed, we found increased mRNA levels for hexokinase 2, lactate dehydrogenase, and phosphofructokinase-2/fructose-2,6-bisphosphatase-3. Unexpectedly, there were minor, but significant, decreases in pyruvate dehydrogenase kinase-1 ( 13%) and enolase ( 22%) mRNA levels.

DISCUSSION

The complexity of -cell metabolism prompts novel analytical approaches that allow analyses of more than one or a few metabolites at time. In the present study, metabolomics allowed the simultaneous analysis of 164 putative metabolites, out of which 44 could be identified. Analyses of four clonalcell-lines with variable glucose responsiveness and hence stimulated insulin secretion pinpointed a fundamental disruption of metabolism in the glucose-unresponsive clones. The disruption appeared to be at the level of coupling glycolysis to TCA-cycle metabolism. As metabolism moved down the path of glycolysis, the weaker the glucose-stimulated response in metabolite levels became. In fact, even lactate, a metabolite not thought to be compatible with robust -cell function, was increasingly produced in glucose-unresponsive cell-lines [11].

To explore whether this observed metabolic perturbation impacted mitochondrial activity, we analyzed OCR in presence of either glucose, which requires glycolytic metabolism, or a combination of leucine and glutamine, which directly activates TCA-cycle metabolism. In agreement with the metabolomics data, glucose was ineffective to stimulate oxygen consumption in glucose-unresponsive cells with the observed block of coupling between glycolysis and TCA-cycle metabolism. In contrast, fuels that were directly metabolized in the TCA-cycle increased oxygen consumption also in glucoseunresponsive cells, albeit not to the same extent as in glucose-responsive cells. This suggests that TCA-cycle metabolism and oxidative phosphorylation in the glucose-unresponsive cell-lines have adapted to a metabolic situation where provision of fuels from glycolysis is constrained. In support of this notion, we have previously shown that respiratory complex activities and protein expression of key subunits of the complexes are decreased in 832/2 versus 832/13 cells [11]. Nevertheless, when mitochondrial fuels are provided, a metabolic response from mitochondria can still be provoked. Accordingly, fuels metabolized directly in the TCA-cycle were able to stimulate insulin secretion also in the clones totally lacking a secretory response to glucose.

At this point, the question remained how the adaptive transition from coupled glycolytic and TCA-cycle metabolism to an increasing dependence on glycolysis was regulated. As we previously observed [11], metabolism in the 832/2 line exhibits Warburg-like features. Moreover, the metabolite profiling revealed that TCA-cycle intermediates, particularly succinate, that can inhibit proline hydroxylases when coinciding with low levels of -ketoglutarate, were increasingly abundant in cells with low glucose responsiveness. Proline hydroxylases hydroxylate HIF-1 , priming it for proteolytic degradation. The inhibition of this process is an important component of the Warburg transition establishing a pseudohypoxic normoxic condition. HIF-1 serves a transcription factor, enhancing expression of genes in the glycolytic pathway. Hereby energy homeostasis is maintained under hypoxic conditions, a situation commonly found in tumour-derived cells even under normoxic conditions. Indeed, the cell lines examined in this study are of tumour origin, originally derived from a transplantable rat insulinoma [START_REF] Asfari | Establishment of 2-mercaptoethanol-dependent differentiated insulin-secreting cell lines[END_REF]. Accordingly, we found that HIF-1 protein was present in all the clonal cell lines, being most abundant in the cell lines with the lowest level of glucose responsiveness. In support of this observation, we found that increased levels of HIF-1 protein coincided with a perturbed coupling of glycolysis and TCA-cycle metabolism as evident from the citrate to pyruvate © 2011 The Authors Journal compilation © 2011 Portland Press Limited ratio. Moreover, higher HIF-1 protein levels corresponded to impaired GSIS. Collectively, these observations suggest that HIF-1 is a key regulator of the balance between glycolytic and TCA-cycle metabolism in -cells. In this capacity, HIF-1 could serve as a regulator of -cell stimulus-secretion coupling. However, while our experiments have established a relation between HIF-1 and glucose responsiveness, it remains to be shown that this is a casual effect. Supporting a casual relationship are recent findings showing that genetic targeting of the von Hippel-Lindau factor in mouse -cells stabilizes HIF-1 resulting in impaired glucose tolerance and perturbed insulin secretion [START_REF] Cantley | The hypoxia response pathway and beta-cell function[END_REF]. Yet another study shows that HIF-1 present at low levels in mouse -cells under normoxic conditions is required for proper -cell function [START_REF] Cheng | Hypoxia-inducible factor-1alpha regulates beta cell function in mouse and human islets[END_REF]. This circumstance could explain why we also found HIF-1 protein in the glucose-responsive cell-lines, albeit at very low levels.

The relevance of our findings for the pathogenesis of Type 2 Diabetes is supported by studies of animal models for the disease. For instance, lactate production has been shown to be increased in the Goto-Kakizaki (GK) rat [START_REF] Ling | Glucose metabolism in Goto-Kakizaki rat islets[END_REF]. Moreover, it has previously been shown that leucine-stimulated glutamate metabolism is intact in the GK rat and that the combination of these amino acids stimulates insulin secretion [START_REF] Giroix | Decreased pancreatic islet response to Lleucine in the spontaneously diabetic GK rat: enzymatic, metabolic and secretory data[END_REF]; the latter is reminiscent of what we observed in the glucose-unresponsive cell lines. In fact, although patients with Type 2 Diabetes exhibit severely perturbed GSIS, glutamineleucine-stimulated insulin secretion is largely preserved [START_REF] Fernandez-Alvarez | Enzymatic, metabolic and secretory patterns in human islets of Type 2 (non-insulin-dependent) diabetic patients[END_REF]. Substantiating our findings on HIF-1 , it has previously been reported that the protein is expressed in human islets [START_REF] Cheng | Hypoxia-inducible factor-1alpha regulates beta cell function in mouse and human islets[END_REF]. Using our repository of human islets, we could confirm this finding. However, there was no difference between patients with Type 2 Diabetes and healthy controls. This was no surprise given that HIF-1 mRNA levels are not thought to contribute to its regulatory function. Instead, this is controlled by its stabilization at the protein level. Therefore, we explored expression of HIF-1 target genes in human islets. Indeed, we found that some of the known targets of this transcription factor, e.g. hexokinase 2, lactate dehydrogenase, and 6-phosphofructo-2-kinase/fructose-2,6-bisphosphatase-3 were up-regulated in islets from patients with Type 2 Diabetes. While these data are compelling, there should be call for caution. The human islets used in our studies, as well as in any other studies, have been cultured for different lengths of time. In this situation, the circulation in the islets has been compromised. This implies that hypoxia may prevail in these islets, particularly in the core of the islets. Clearly, such hypoxia could stabilize HIF-1 . This notwithstanding, we did observe a difference between healthy controls and patients with Type 2 Diabetes.

In conclusion, we have used metabolomics analysis to identify a profound perturbation in stimulus-secretion coupling in clonal -cells. The metabolite profile suggested to us that HIF-1 could play a role in the observed transition of metabolism to dependence on glycolysis. The functional studies as well as observations in human islets suggest that an improper alignment of glycolysis with TCA-cycle metabolism may underlie perturbed GSIS. As such it may play a role in the pathogenesis of human Type 2 Diabetes. Further work is required to establish a casual relationship of these phenomena.

FIGURE LEGENDS

Figure 1 Glucose-stimulated fold changes in metabolite levels. Fold changes of metabolite levels after glucose stimulation were calculated by dividing the peak areas for the metabolite levels at 16.7 and 2.8 mM glucose derived from the glucose-unresponsive INS-1 832/2 and the glucose-responsive INS-1 832/13 lines, respectively. (A) Glycolytic and related metabolites. (B) TCA-cycle and related intermediates. The data are represented as mean SEM. Statistical comparisons were made by t-test (*p<0.05, **p<0.01, ***p<0.001). Abbreviations: Rib5Pribose-5-phosphate; Glu6P1 -glucose-6-phosphate peak 1; Glu6P2 -glucose-6-phosphate peak 2; GlyA3P -3-phosphoglycerate; GlyA2P -2-phosphoglycerate; PEP -phosphoenol pyruvate; Pyrpyruvate; Lac -lactate; Cit -citrate; Aco -aconitate; AKGA --ketoglutarate; Succ -succinate; Fumfumarate; Mal -malate. A targeted metabolite profiling was performed to investigate whether the observed metabolic perturbation was present also in other clonal ß-cell lines. Fold-changes were calculated and compared as described in legend to Figure 1; (*p<0.05, **p<0.01, ***p<0.001). Abbreviations as in Figure 1.

Biochemical

  Journal Immediate Publication. Published on 06 Jan 2011 as manuscript BJ20100655 THIS IS NOT THE VERSION OF RECORD -see doi:10.1042/BJ20100655 A c c e p t e d M a n u s c r i p t Licenced copy. Copying is not permitted, except with prior permission and as allowed by law. © 2011 The Authors Journal compilation © 2011 Portland Press Limited

Biochemical

  Journal Immediate Publication. Published on 06 Jan 2011 as manuscript BJ20100655 THIS IS NOT THE VERSION OF RECORD -see doi:10.1042/BJ20100655 A c c e p t e d M a n u s c r i p t Licenced copy. Copying is not permitted, except with prior permission and as allowed by law. © 2011 The Authors Journal compilation © 2011 Portland Press Limited

  manufacturer

  Biochemical Journal Immediate Publication. Published on 06 Jan 2011 as manuscript BJ20100655 THIS IS NOT THE VERSION OF RECORD -see doi:10.1042/BJ20100655 A c c e p t e d M a n u s c r i p t Licenced copy. Copying is not permitted, except with prior permission and as allowed by law. © 2011 The Authors Journal compilation © 2011 Portland Press Limited

Biochemical

  Journal Immediate Publication. Published on 06 Jan 2011 as manuscript BJ20100655 THIS IS NOT THE VERSION OF RECORD -see doi:10.1042/BJ20100655 A c c e p t e d M a n u s c r i p t Licenced copy. Copying is not permitted, except with prior permission and as allowed by law. © 2011 The Authors Journal compilation © 2011 Portland Press Limited

Biochemical

  Journal Immediate Publication. Published on 06 Jan 2011 as manuscript BJ20100655 THIS IS NOT THE VERSION OF RECORD -see doi:10.1042/BJ20100655A c c e p t e d M a n u s c r i p t Licenced copy. Copying is not permitted, except with prior permission and as allowed by law.

Figure 2

 2 Figure 2Respiration and insulin secretion in glucose-responsive 832/13 and glucoseunresponsive 832/2 cells. Oxygen consumption rate (OCR) in INS-1 832/13 (closed triangles) and 832/2 (open triangles) cells after addition of metabolic fuels. (A) 16.7 mM glucose or (B) 10 mM leucine + 10 mM glutamine. (C) Fuel-stimulated OCR during the stimulation period normalized to protein content and basal OCR at 2.8 mM glucose; calculated based on an area under curve (AUC) analysis[START_REF] Eto | Role of NADH shuttle system in glucose-induced activation of mitochondrial metabolism and insulin secretion[END_REF]. (D) Fold-change of insulin secretion in INS-1 832/13 and INS-1 832/2 -cells at 16.7 mM glucose and 10 mM of leucine + 10 mM of glutamine relative 2.8 mM glucose. Data are presented as means ±SEM (*p<0.05, **p<0.01, ***p<0.001).

Figure 3

 3 Figure 3 Targeted metabolite profiling of the glucose -responsive INS-1 parental clone and the glucose-unresponsive INS-1 832/1 sub-clone.A targeted metabolite profiling was performed to investigate whether the observed metabolic perturbation was present also in other clonal ß-cell lines. Fold-changes were calculated and compared as described in legend to Figure1; (*p<0.05, **p<0.01, ***p<0.001). Abbreviations as in Figure1.

Figure 4

 4 Figure 4 Stabilization and functional relations of HIF-1 with metabolic and functional parameters in clonal ß-cell lines. HIF-1 stabilisation was examined by Western-blotting as described in Experimental Procedures. n=3-6; data were compared by Kruskal-Wallis test in combination with Mann-Whitheny test followed by Bonferroni's test post hoc. (A) Western blot data. (B) Quantified levels of HIF-1 . (C) Stabilization of HIF-1 in relation to the ratio of -ketoglutarate (AKGA) to succinate (Succ) (calculated as the ratio of their fold-changes to stimulatory glucose). (D) Stabilization of HIF-1 in relation to fold-changes of citrate (Cit) to pyruvate (Pyr) (see C). (E) Relationship between the foldchange of GSIS and HIF-1 stabilization.

Figure 5

 5 Figure 5Islet mRNA expression from patients with Type 2 Diabetes and healthy controls. Expression of islet mRNA, derived from microarray analysis, of hexokinase 2 (HK2), enolase (ENO2), phosphofructokinase-2/fructose-2,6-bisphosphatase-3 (PFKFB3), pyruvate dehydrogenase kinase-1 (PDK1), and lactate dehydrogenase (LDHA). Data are given as means standard deviation and were compared with a Mann-Whitney U-test; (*p<0.05, **p<0.01, ***p<0.001).

Figure 6

 6 Figure 6Cartoon of the suggested involvement of HIF-1 in ß-cell stimulus-secretion coupling.The cartoons show the proposed different modes of metabolic regulation in the glucoseresponsive and -unresponsive clonal ß-cell lines involving hypoxia-induced factor 1 (HIF-1 ).-ketoglutarate -AKGA; hypoxia response element -HRE; lactate dehydrogenase -LDH; mitochondrion -M; nucleus -N; proline hydroxylases -PHD; pyruvate dehydrogenase -PDH; PDH kinase 1 -PDK1; oxidative phosphorylation -OXPHOS; succinate -suc; tricarboxylic acid cycle -TCA; von Hippel-Lindau factor -VHL

  Figure 4

Licenced copy. Copying is not permitted, except with prior permission and as allowed by law.© 2011 The Authors Journal compilation © 2011 Portland Press Limited

ACKNOWLEDGEMENTS

We thank the Nordic Center for Islet Transplantation in Uppsala, Sweden for providing us with human islets. Charlotte Ling is acknowledged for analyzing expression data from human islets, and Jalaal Taneera and Thomas Lang for performing the microarray analyses.

FUNDING

This work was supported by grants from Swedish Research Council (14196-06-3), the Crafoord Foundation, the European Foundation for the Study of Diabetes, Lars Hierta, Fredrik and Ingrid Thuring, Åke Wiberg, Albert Påhlsson, O.E. and Edla Johansson Foundations, Knut and Alice

AUTHOR CONTRIBUTION

Peter Spégel performed metabolomics analyses and wrote the first draft of the manuscript. Siri Malmgren performed insulin secretion and oxygen consumption measurements. Vladimir Sharoyko performed glucose uptake measurement, provided feedback on results and the manuscript and, assisted in metabolite extraction. Thomas Koeck determined HIF-1 stabilization, performed oxygen consumption measurements, and provided feedback on results and the manuscript. Philip Newsholme provided feedback on results and the manuscript throughout the project. Hindrik Mulder conceived and directed the project and finalized the paper.


Claire E Chivers

Apurba L Koner

Edward D Lowe

Mark Howarth
email: mark.howarth@bioch.ox.ac.uk

How the biotin-streptavidin interaction was made even stronger: investigation via crystallography and a chimeric tetramer

Keywords: Protein engineering, Avidin, Ultra-stable, Monovalent, High affinity, Femtomolar D, dead streptavidin subunit, L, loop number, rmsd, root mean squared deviation, SA, streptavidin, Tr, traptavidin

come

How the biotin-streptavidin interaction was made even stronger: investigation via crystallography and a chimeric tetramer

INTRODUCTION

The capture of the small-molecule biotin (vitamin H/ vitamin B 7 ) by the bacterial protein streptavidin is both a powerful tool in biology and a model system for the study of high-affinity protein-ligand interactions. The key features are the femtomolar affinity, high specificity, fast on-rate and the resilience of streptavidin to pH, temperature and denaturant [START_REF] Sano | Genetic engineering of streptavidin, a versatile affinity tag[END_REF][START_REF] Stayton | Streptavidin-biotin binding energetics[END_REF][START_REF] Laitinen | Genetically engineered avidins and streptavidins[END_REF]. It is also important that biotin protein ligases can attach biotin to specific lysines in vitro or in living cells [START_REF] De Boer | Efficient biotinylation and single-step purification of tagged transcription factors in mammalian cells and transgenic mice[END_REF][START_REF] Howarth | Targeting quantum dots to surface proteins in living cells with biotin ligase[END_REF]. Streptavidin's applications include imaging [START_REF] Howarth | Monovalent, reduced-size quantum dots for single molecule imaging of receptors in living cells[END_REF], nano-assembly [START_REF] Kattah | HIT: a versatile proteomics platform for multianalyte phenotyping of cytokines, intracellular proteins and surface molecules[END_REF], and pre-targeted cancer immunotherapy [START_REF] Goldenberg | Antibody pretargeting advances cancer radioimmunodetection and radioimmunotherapy[END_REF]. As a favoured model in biophysics and protein engineering, this protein-ligand interaction has been investigated by at least 200 point mutations of streptavidin [START_REF] Laitinen | Genetically engineered avidins and streptavidins[END_REF][START_REF] Avrantinis | Dissecting the streptavidinbiotin interaction by phage-displayed shotgun scanning[END_REF][START_REF] Aslan | Engineered single-chain dimeric streptavidins with an unexpected strong preference for biotin-4-fluorescein[END_REF][START_REF] Levy | Directed evolution of streptavidin variants using in vitro compartmentalization[END_REF], more than 30 alternative small molecule ligands [START_REF] Sano | Genetic engineering of streptavidin, a versatile affinity tag[END_REF][12][START_REF] Wilbur | Development of new biotin/streptavidin reagents for pretargeting[END_REF][START_REF] Weber | Structure-Based Design of Synthetic Azobenzene Ligands for Streptavidin[END_REF], computational simulation [START_REF] Grubmuller | Ligand binding: molecular mechanics calculation of the streptavidin-biotin rupture force[END_REF][START_REF] Dechancie | The origins of femtomolar protein-ligand binding: hydrogen-bond cooperativity and desolvation energetics in the biotin-(strept)avidin binding site[END_REF][START_REF] Cerutti | Dynamics of the streptavidinbiotin complex in solution and in its crystal lattice: distinct behavior revealed by molecular simulations[END_REF][START_REF] Miyamoto | Absolute and relative binding free energy calculations of the interaction of biotin and its analogs with streptavidin using molecular dynamics/free energy perturbation approaches[END_REF], crystallography [START_REF] Stayton | Streptavidin-biotin binding energetics[END_REF], and singlemolecule force dynamics [START_REF] Moy | Intermolecular forces and energies between ligands and receptors[END_REF].

Despite the strength of streptavidin-biotin binding, the interaction can and does fail under challenging conditions. Biotin dissociation becomes significant and sometimes rapid in response to the low pH of the endosomes [START_REF] Bruneau | Identification of nicotinic acetylcholine receptor recycling and its role in maintaining receptor density at the neuromuscular junction in vivo[END_REF], the high temperatures used for DNA amplification [START_REF] Dressman | Transforming single DNA molecules into fluorescent magnetic particles for detection and enumeration of genetic variations[END_REF], attachment to nanoparticles [START_REF] Swift | A two-photon excitation fluorescence crosscorrelation assay for a model ligand-receptor binding system using quantum dots[END_REF], and shear forces from flow [START_REF] Pierres | Dissecting streptavidin-biotin interaction with a laminar flow chamber[END_REF]. The slow off-rate of wild-type streptavidin for biotin-conjugates was improved upon recently, when we found that the S52G R53D mutant of streptavidin, named traptavidin, had more than ten-fold slower biotin dissociation than wild-type streptavidin, as well as enhanced mechanical and thermal stability [START_REF] Chivers | A streptavidin variant with slower biotin dissociation and increased mechanostability[END_REF]. The stronger binding of traptavidin enabled us to generate a challenging road-block for one of the fastest known linear molecular motors, FtsK, in order to evaluate the coordination of firing around the hexameric ring as FtsK translocated on DNA [START_REF] Chivers | A streptavidin variant with slower biotin dissociation and increased mechanostability[END_REF][START_REF] Crozat | Separating speed and ability to displace roadblocks during DNA translocation by FtsK[END_REF].

To understand the basis of traptavidin's resilient binding and stability to high temperatures, here we solved the crystal structures of both apo-traptavidin and biotin-traptavidin and compared these with existing structures of streptavidin. In addition we purified a monovalent traptavidin, to investigate the role of inter-subunit effects in traptavidin stability and also to characterize a tool which enables ultra-stable binding of biotinylated targets without cross-linking.

EXPERIMENTAL Traptavidin purification

Traptavidin protein (S52G R53D core streptavidin with a C-terminal His 6 tag, GenBank GU952124) was purified from Escherichia coli by inclusion body isolation, refolding, and Ni-NTA chromatography, as described previously [START_REF] Chivers | A streptavidin variant with slower biotin dissociation and increased mechanostability[END_REF]. Prior to crystal tray set-up, we performed sizeexclusion chromatography (XK 26 column, GE Healthcare), eluting with 50 mM Tris-HCl, 0.5 M NaCl, 10 mM EDTA pH 7.5.

Monovalent traptavidin (Tr1D3) was generated by the mixed refolding of traptavidin (Tr) and dead streptavidin (D) subunits (N23A, S27D, S45A core streptavidin with no His 6 tag). Purification was as previously described for monovalent streptavidin [START_REF] Howarth | A monovalent streptavidin with a single femtomolar biotin binding site[END_REF], except that the order of SDS-PAGE mobility was reversed (mobility of Tr2D2 >Tr1D3>D4). A tetramer of dead streptavidin subunits (D4) was generated from the refolding of D from inclusion bodies into PBS, and ammonium sulfate precipitation [START_REF] Howarth | A monovalent streptavidin with a single femtomolar biotin binding site[END_REF].

Apo-traptavidin crystallization

Crystals were obtained by the sitting-drop vapour-diffusion method at 291 K. Apo-traptavidin crystals (space group I 4 1 ; a = b = 57.59 Å, c = 183.35 Å, with two traptavidin monomers in the asymmetric unit) were obtained from a 4 µl drop of 19 mg/ml solution and a reservoir solution of 12% PEG 8000, 9% ethylene glycol, 0.1 M HEPES pH 7.5. Crystals appeared after 2 days and reached optimum size after 4 days. Prior to data collection, crystals were briefly soaked in a cryoprotectant solution of 12% PEG 8000, 30% ethylene glycol, 0.1 M HEPES pH 7.5 before immersion into liquid nitrogen.

Biotin-traptavidin crystallization

Biotin-bound traptavidin was obtained by incubation of traptavidin with biotin (Acros Organics) in 4fold molar excess compared to the number of binding sites at 4C overnight. Biotin-bound crystals (space group P 4 2 2 1 2; a = b = 57.34 Å, c= 77.55 Å, with one monomer in the asymmetric unit) were obtained from a 4 µl drop of 19 mg/ml solution and a reservoir solution of 27% PEG 4000, 0.25 M MgCl 2 , 0.1 M Tris-HCl pH 8.5. Crystals appeared after 2 days and reached optimum size after 4 days. Prior to data collection, crystals were briefly soaked in a cryoprotectant solution of 27% PEG 4000, 0.25 M MgCl 2 , 0.1 M Tris-HCl, 25% glycerol pH 8.5 before immersion into liquid nitrogen. streptavidin search model (1swb) [START_REF] Freitag | Structural studies of the streptavidin binding loop[END_REF] with the program Phaser. The crystal contained two monomers in the asymmetric unit. Five percent of the reflection data were set aside using the Freerflag program in CCP4 and used for the calculation of R free . The model was built in Coot and refined in PHENIX refine, with incorporation of the twinning operator (-h, k, -l) with a twinning fraction of 49.7%. Throughout the refinement, all data were included from 27.47 Å resolution to the highest limit (1.45 Å) and anisotropic temperature factors were refined. The model was evaluated with MolProbity, which gave Ramachandran statistics with 98% of residues in favoured regions and no outliers. The diffraction-data precision indicator (DPI), indicating the agreement between the model and the x-ray data, for apo-traptavidin was 0.056 Å. The refinement statistics are shown in Table 1.

Structure solution and refinement: biotin-traptavidin

Data were indexed and integrated using MOSFLM, and scaled and merged using SCALA from the CCP4 program suite. Intensities were converted to structure factors using the truncate program in CCP4 and no signs of twinning were observed in the data. The structure was phased by molecular replacement using the apo-traptavidin search model and Phaser. The crystal contained one monomer in the asymmetric unit. Five percent of the reflection data were set aside using the Freerflag program in CCP4 and used for the calculation of R free . Model building was performed in Coot and refinement, including rounds of simulated annealing refinement, in PHENIX refine. Throughout the refinement, all data were included from 38.78 Å resolution to the highest limit (1.49 Å) and anisotropic temperature factors were refined. The presence of a well defined biotin model in the binding pocket was clearly visible in the initial F obs -F calc electron density maps. Biotin coordinates from 1mk5 [START_REF] Hyre | Cooperative hydrogen bond interactions in the streptavidin-biotin system[END_REF] were used as a template for the refinement and the weighting of coordinate refinement was optimized by PHENIX refine as the refinement progressed. The model was evaluated with MolProbity, which gave Ramachandran statistics with 98% of residues in favoured regions and no outliers. The diffraction-data precision indicator (DPI), indicating the agreement between the model and the x-ray data, for biotin-traptavidin was 0.051 Å. The refinement statistics are shown in Table 1. To assess if model bias was introduced into the biotin-traptavidin model by using the apo-traptavidin structure as a search model for molecular replacement, a simulated annealing composite omit map was calculated using PHENIX AutoBuild [START_REF] Terwilliger | Iterative model building, structure refinement and density modification with the PHENIX AutoBuild wizard[END_REF], with the starting phases provided by the apo-traptavidin structure.

Structure Analysis

Structural overlays and colouring according to B factor were done in PyMOL (DeLano Scientific). Alignments were calculated from main-chain atoms of apo-traptavidin chain A, biotin-traptavidin, apo-streptavidin 1swa, apo-streptavidin 1swb, apo-streptavidin 1swc, and biotin-streptavidin 1swe [START_REF] Freitag | Structural studies of the streptavidin binding loop[END_REF]. Plots of mean B factors of main-chain atoms against residue number were produced using the "baverage" program in CCP4. The diffraction-data precision indicator was assessed using the program SFCHECK from CCP4.

Biotin-conjugate off-rate assay

The off-rate of biotin-4-fluorescein was measured from the fluorescence increase on unbinding at 37 ºC with competing free biotin, as previously [START_REF] Howarth | A monovalent streptavidin with a single femtomolar biotin binding site[END_REF][START_REF] Kada | Accurate measurement of avidin and streptavidin in crude biofluids with a new, optimized biotin-fluorescein conjugate[END_REF].

Thermostability analysis

3 μM dead streptavidin, tetravalent traptavidin or monovalent traptavidin in PBS was heated at the indicated temperature for 3 min in a DNA Engine® Peltier Thermal Cycler (Bio-Rad). SDS-PAGE to discriminate monomers was performed as described [START_REF] Howarth | A monovalent streptavidin with a single femtomolar biotin binding site[END_REF]. The band intensities were quantified using a ChemiDoc XRS imager and QuantityOne 4.6 software (Bio-Rad). Percentages were calculated as 100 × (summed intensity of monomer bands at the indicated temperature -summed intensity of monomer bands at 25 ºC) / (summed intensity of monomer bands after 95 ºC with SDS). A c c e p t e d M a n u s c r i p t Licenced copy. Copying is not permitted, except with prior permission and as allowed by law.

RESULTS

Biochemical

Loop L3/4 of traptavidin is closed even without biotin

We determined the crystal structures at high resolution of traptavidin with and without biotin (1.45 Å for apo-traptavidin, PDB 2y3e; 1.49 Å for biotin-traptavidin, PDB 2y3f) (Table 1). Both structures were solved by molecular replacement; the apo-streptavidin structure (1swb) was used as a search model for the apo-traptavidin structure [START_REF] Freitag | Structural studies of the streptavidin binding loop[END_REF]. The subsequent apo-traptavidin structure was used as the search model for biotin-bound traptavidin. To determine whether model bias was introduced into the biotin-traptavidin structure by using the apo-traptavidin structure as a search model for molecular replacement, a simulated annealing composite omit map was calculated. Alignment of this map with the biotin-traptavidin and apo-traptavidin models revealed the final biotin-traptavidin model fitted the omit map much better (correlation coefficient of 0.73 for side-chain atoms) than the apo-traptavidin model (correlation coefficient of 0.47 for side-chain atoms) (Supplementary Figure 1), thus indicating that the solution of the biotin-traptavidin structure was not biased by the search model.

We observed two subunits in the asymmetric unit for apo-traptavidin and one subunit in the asymmetric unit for biotin-traptavidin. We applied symmetry transformations to view the complete tetramer (Figure 1A). Streptavidin/traptavidin subunits are 8-stranded antiparallel β-barrels, with the biotin binding site located at one end of the barrel. Each subunit binds one biotin molecule and the subunits come together to form a tetramer that can be considered a dimer of dimers. The electron density for the biotin bound to traptavidin was unambiguous (Figure 1B). A striking difference between traptavidin and streptavidin was seen in the loop connecting -strands 3 and 4 (L3/4). The L3/4 loop is commonly disordered in apo-streptavidin ('open' conformation) [START_REF] Freitag | Structural studies of the streptavidin binding loop[END_REF], but becomes ordered on biotin-binding, closing over the binding pocket and forming a 'lid' over the bound biotin ('closed' conformation) (Figure 2A). However, in apo-traptavidin, all the L3/4 loops of the tetramer were already in the 'closed' conformation. The L3/4 loops remained in this closed conformation in biotin-traptavidin (Figure 2A). Apo-streptavidin structures 1swa and 1swb had only one out of four subunits while 1swc had two out of four subunits (1swc) with an ordered L3/4 loop in the tetramer (1swa, 1swb and 1swc have 4 subunits in the asymmetric unit) [START_REF] Freitag | Structural studies of the streptavidin binding loop[END_REF]. We emphasise that the fact that apo-traptavidin had 2 subunits in the asymmetric unit does not mean that the 3 rd and 4 th subunits were less clearly defined than if there were 4 subunits in the asymmetric unit; rather the crystallographic symmetry tells us that the 3 rd and 4 th subunits are identical to the 1 st and 2 nd subunits.

Structural alignments of these apo-streptavidin structures with apo-traptavidin revealed the closed loops in the apo-streptavidin structures are comparable to L3/4 in apo-traptavidin; the root mean squared deviation (rmsd) from apo-traptavidin chain A for residues 45-52 is 0.24 Å for 1swa chain A and 0.20 Å for 1swb chain A. The presence of one 'closed' loop in the apo-streptavidin tetramer suggests that the L3/4 loop is dynamic in the absence of biotin. The L3/4 loop in the 1swc apo-streptavidin structure is an exception, with an alternative open conformation, projecting away from the binding site, and is not comparable to L3/4 in apo-traptavidin (rmsd 2.2 Å compared to 1swc chain B) [START_REF] Freitag | Structural studies of the streptavidin binding loop[END_REF].

The whole structure of traptavidin is pre-formed for biotin binding

Streptavidin does not show cooperativity in biotin binding between the four subunits [START_REF] Jones | Noncooperativity of biotin binding to tetrameric streptavidin[END_REF] but there is a substantial conformational change when biotin binds, involving flattening and tighter wrapping of the β-barrels, altered dimer-dimer packing and loop ordering [START_REF] Weber | Structural origins of high-affinity biotin binding to streptavidin[END_REF]. This conformational change is consistent with an observed increase in thermostability of the biotin-bound tetramer [START_REF] Bayer | Sodium dodecyl sulfatepolyacrylamide gel electrophoretic method for assessing the quaternary state and comparative thermostability of avidin and streptavidin[END_REF]. Upon aligning the apo-traptavidin and biotin-traptavidin structures, we found that the conformational change in traptavidin upon biotin binding is much smaller than for streptavidin (rmsd 0.21 Å for traptavidin, 0.36 Å for streptavidin) (Figure 2B). Differences in the apo-and biotin-bound conformations of streptavidin were clearly shown by calculating alignments of the loops connecting the -strands (Table 2). It was not just the L3/4 loop which moved less upon biotin binding in traptavidin than streptavidin, but also 5 out of 6 of the other loops. To analyze the flexibility and dynamics of apo-traptavidin and biotin-traptavidin, we plotted the mean B factors for main-chain atoms against residue number (Figure 3). Relative B factors within a structure are informative, but it is not straightforward to compare directly the absolute values of B factors between streptavidin and traptavidin, because of different resolutions, data collection conditions and refinement methods.

Changes in the flexibility of traptavidin

The B factors for each of the two monomers in the asymmetric unit of apo-traptavidin were plotted to indicate the internal variation. This showed the expected low dynamics in the β-sheet regions and some flexibility in all the loop sections (Figure 3A). The main difference between chains A and B of apo-traptavidin occurs at L5/6 and may result from one chain being involved in crystal contacts at this loop. There is some flexibility in L3/4 for apo-traptavidin but clearly it is less than in apo-streptavidin structures where the loop is not resolved. If L3/4 in apo-traptavidin did not have some flexibility then it is likely that the traptavidin on-rate would be too slow for practical application. The most striking change in the biotin-traptavidin B factors is the loss of flexibility in L3/4, with values comparable to adjacent β-sheets 3 and 4 (Figure 3B), which is consistent with the exceptionally low biotin dissociation rate.

Hydrogen bonding to biotin and Ser-45 in traptavidin and streptavidin

The extensive hydrogen-bonding network from streptavidin to biotin plays a key role in generating the large ΔG°' of biotin binding [START_REF] Stayton | Streptavidin-biotin binding energetics[END_REF]. We compared all the hydrogen bonds to biotin for traptavidin and streptavidin, paying particular attention to Ser-45 and Asn-49, which are present on the L3/4 loop close to the residues mutated in traptavidin. Factoring in the variation seen in the different chains of the different structures of streptavidin, the hydrogen bonds lengths to biotin are comparable between traptavidin and streptavidin (Supplementary Figure 2).

The published structures of streptavidin allude to the probable dynamic nature of this hydrogen bond network to biotin. In some crystal structures of streptavidin (1swe), each Ser-45 residues has its side-chain hydroxyl directed towards the biotin N3' nitrogen, and hydrogen bonds are formed (although the distance in subunits 1 and 4 in 1swe is at the limit for a hydrogen bond between such atoms, at 3.2 Å) (Figure 4A and Supplementary Figure 2). However, in the streptavidin structure of 1swd, the Ser-45 side-chains point away from the N3' nitrogen and so cannot hydrogen bond (Figure 4A and Supplementary Figure 2). In the traptavidin-biotin structure, the Ser-45 side-chain is clearly orientated towards the N3' nitrogen (Figure 4A), with a hydrogen bond length of 3.0 Å. Gly-52 in traptavidin undergoes little change upon biotin binding (Figure 4B). The peculiar importance of the S52G mutation for biotin binding stability is likely to relate to Ser-52 stabilizing an alternative open conformation of L3/4, thereby destabilizing the Ser-45 hydrogen bond to biotin. In this rival conformation, Ser-52's main-chain carbonyl forms a hydrogen bond to the main-chain N-H of Ser-45, while the Ser-52 side-chain makes a hydrogen-bond to the main-chain N-H of Ala-46 (Figure 4B). This competing pairing is seen in apo-streptavidin structures with an undefined L3/4 loop (1swa) [START_REF] Freitag | Structural studies of the streptavidin binding loop[END_REF], but could well form transiently even in the presence of biotin, so contributing to the rare biotin dissociation events from streptavidin.

The network of polar and non-polar interactions made to biotin by streptavidin changes biotin's structure from the conformation reported to apply in solution [START_REF] Li | Electronic structure, binding energy, and solvation structure of the streptavidin-biotin supramolecular complex: ONIOM and 3D-RISM study[END_REF]. In avidin and streptavidin there are 3 residues which are positioned to hydrogen bond to the carbonyl oxygen of biotin, suggesting that this oxygen is partially charged and that this polarization may contribute to the exceptional affinity of biotin binding [START_REF] Dechancie | The origins of femtomolar protein-ligand binding: hydrogen-bond cooperativity and desolvation energetics in the biotin-(strept)avidin binding site[END_REF]. The bond lengths and bond angles of biotin were similar between streptavidin and traptavidin (data not shown), indicating that changes in biotin's electronic structure in the binding site are not likely to contribute to the difference in biotin off-rate.

Generating monovalent traptavidin shows that altered intersubunit contacts do not explain traptavidin's increased stability

We created tetramers with exactly one traptavidin subunit and three "dead" subunits which do not bind biotin [START_REF] Howarth | A monovalent streptavidin with a single femtomolar biotin binding site[END_REF], to give monovalent traptavidin (Tr1D3) (Figure 5A). We previously showed that monovalent streptavidin had equivalent biotin binding stability to tetravalent streptavidin [START_REF] Howarth | A monovalent streptavidin with a single femtomolar biotin binding site[END_REF]. Here we used monovalent traptavidin to explore whether the increased stability of wild-type traptavidin (Tr4) over streptavidin depended upon the presence of neighbouring traptavidin subunits. The off-rate of biotin-4-fluorescein was compared for tetravalent traptavidin, monovalent traptavidin and tetravalent streptavidin (Figure 5B). Monovalent traptavidin had equivalent off-rate to tetravalent traptavidin, showing that it is the binding by the traptavidin subunit and not any altered intersubunit interaction that is the dominant factor in traptavidin's improved biotin binding stability.

Traptavidin stays tetrameric and remains bound to biotin-conjugates at higher temperatures than streptavidin [START_REF] Chivers | A streptavidin variant with slower biotin dissociation and increased mechanostability[END_REF]. We tested the thermostability of monovalent traptavidin by incubating at a range of temperatures and testing by SDS-PAGE what fraction remained tetrameric (Figure 5C). Monovalent streptavidin is known to show equivalent thermostability to wild-type streptavidin [START_REF] Howarth | A monovalent streptavidin with a single femtomolar biotin binding site[END_REF]. We compared monovalent traptavidin to tetravalent traptavidin and a tetramer composed entirely of dead subunits (D4). Tetravalent traptavidin was ~10ºC more stable than the dead tetramer. The thermostability of monovalent traptavidin was similar to D4, consistent with the least stable subunit dominating the stability of the tetramer.

DISCUSSION

Streptavidin's binding to biotin is one of the strongest known non-covalent protein-ligand interactions and yet the mutant protein traptavidin has 10-fold greater binding stability [START_REF] Chivers | A streptavidin variant with slower biotin dissociation and increased mechanostability[END_REF]. The crystal structures of apo-and biotin-bound traptavidin described here show the basis for traptavidin's tenacious ligand binding. The key differences between traptavidin and streptavidin are the decreased flexibility of the L3/4 loop, the increased stability of the Ser-45 hydrogen bond to biotin, and the reduced conformational change upon biotin binding.

The crystal structure of D128A streptavidin and molecular dynamic simulations [START_REF] Grubmuller | Ligand binding: molecular mechanics calculation of the streptavidin-biotin rupture force[END_REF][START_REF] Freitag | A structural snapshot of an intermediate on the streptavidin-biotin dissociation pathway[END_REF][START_REF] Hyre | Early mechanistic events in biotin dissociation from streptavidin[END_REF]] led to a model whereby a water molecule initiates biotin dissociation, by competing with the Asp-128 hydrogen bond to biotin and so promoting cooperative breakage of other biotin hydrogen bonds. However, we note that in wild-type streptavidin the Asp-128 hydrogen bond to biotin is always in place, but the Ser-45 hydrogen bond is often broken [START_REF] Freitag | Structural studies of the streptavidin binding loop[END_REF]. Hence we suggest that breakage of the Ser-45 hydrogen bond to biotin is frequent and is the first event in biotin dissociation. The mutations that led to a higher stability mutant, traptavidin, further support this revised model: in traptavidin, the Ser-45 hydrogen bond to biotin was clearly present, while the residue that competes with biotin for hydrogen bonding to Ser-45, Ser-52, is mutated to Gly. Arg-53 does not have direct interactions with residues binding to biotin, so the R53D mutation is likely to exert its effects by further reducing L3/4 loop mobility.

The L3/4 loop is always in a 'closed' conformation in biotin-bound structures of streptavidin, acting like a lid over the binding pocket and contributing to the low rate of biotin dissociation. For avidin, the L3/4 loop is ordered when bound to free biotin, but disordered when bound to biotinconjugates: this explains why avidin binds biotin-conjugates much more weakly than biotin [START_REF] Pazy | Ligand exchange between proteins. Exchange of biotin and biotin derivatives between avidin and streptavidin[END_REF]. A restrained L3/4 loop may also be important in enabling high affinity biotin binding by the dimeric rhizavidin [START_REF] Meir | Crystal structure of rhizavidin: insights into the enigmatic high-affinity interaction of an innate biotin-binding protein dimer[END_REF]. In a series of structures solved in the pH range 2.0-3.1 [START_REF] Katz | Binding of biotin to streptavidin stabilizes intersubunit salt bridges between Asp61 and His87 at low pH[END_REF], the L3/4 loop was closed in apo-streptavidin, but in the apo-streptavidin structures solved in the more physiologically relevant pH range 4.5-7.5, the L3/4 loop is disordered, in two (1swc) or three (1swa and 1swb) of the subunits of the tetramer [START_REF] Freitag | Structural studies of the streptavidin binding loop[END_REF]. The stability of the L3/4 loop in the closed conformation in apo-traptavidin indicates that in biotin-traptavidin the occasional fluctuations that lead to lid opening and so facilitate biotin dissociation are similarly suppressed. Since we found that the hydrogen bond lengths to biotin and conformation of biotin are equivalent in traptavidin and streptavidin, this indicates that it is not subtle differences in the ground-state binding conformation that explain the change in stability, but a change in the frequency of alternative protein conformations with weakened binding. The L3/4 loop conformation in apo-traptavidin also rationalizes the decreased on-rate of traptavidin [START_REF] Chivers | A streptavidin variant with slower biotin dissociation and increased mechanostability[END_REF], since it will be harder for biotin to enter the binding site with the loop shut. For Streptomyces avidinii, one can hypothesize that evolution would favour a streptavidin with a fast on-rate as well as a slow offrate, but for laboratory applications in anchoring and bridging [START_REF] Chivers | A streptavidin variant with slower biotin dissociation and increased mechanostability[END_REF] the off-rate is more important.

Streptavidin is a highly thermostable protein (72 ºC for subunit dissociation without biotin), even though the protein derives from a mesophilic bacterium [START_REF] Sano | Genetic engineering of streptavidin, a versatile affinity tag[END_REF][START_REF] Stayton | Streptavidin-biotin binding energetics[END_REF][START_REF] Bayer | Sodium dodecyl sulfatepolyacrylamide gel electrophoretic method for assessing the quaternary state and comparative thermostability of avidin and streptavidin[END_REF]. This thermostability relates to reducing the rare subunit unfolding events that would contribute to ligand dissociation, or, from an energetic perspective, rigid binding sites having a reduced entropic cost for providing an inflexible A c c e p t e d M a n u s c r i p t Licenced copy. Copying is not permitted, except with prior permission and as allowed by law. ligand binding site [START_REF] Moghaddam | Host-guest complexes with protein-ligandlike affinities: computational analysis and design[END_REF]. Any fleeting disruption of the interaction between biotin and Trp-120 of the neighbouring subunit should transiently increase the rate of biotin dissociation 10 4 -fold [START_REF] Chilkoti | Site-directed mutagenesis studies of the highaffinity streptavidin-biotin complex: contributions of tryptophan residues 79, 108, and 120[END_REF]. Traptavidin is 10 ºC more thermostable than streptavidin [START_REF] Chivers | A streptavidin variant with slower biotin dissociation and increased mechanostability[END_REF] and one might think that this thermostability would contribute to the increased ligand binding stability, by further reducing the frequency of conformational fluctuations that disrupt the protein structure or subunit packing. The equivalent off-rate of monovalent and tetravalent traptavidin demonstrated that the change in traptavidin's biotin binding stability is not mediated through altered subunit interactions. The tetravalent nature of traptavidin interferes with many applications: for example in imaging cellsurface proteins, tetravalency can induce receptor cross-linking and activate cell signaling [START_REF] Howarth | Monovalent, reduced-size quantum dots for single molecule imaging of receptors in living cells[END_REF][START_REF] Howarth | A monovalent streptavidin with a single femtomolar biotin binding site[END_REF]. Monovalent traptavidin (and divalent or trivalent traptavidin, which could be generated, as before [START_REF] Howarth | A monovalent streptavidin with a single femtomolar biotin binding site[END_REF]) should be valuable in diverse applications, including nanoassembly and the targeting of quantum dots for photostable single-molecule imaging [START_REF] Howarth | Targeting quantum dots to surface proteins in living cells with biotin ligase[END_REF][START_REF] Howarth | Monovalent, reduced-size quantum dots for single molecule imaging of receptors in living cells[END_REF].

The stability of the interaction between biotin and avidin/streptavidin is paradoxical, given the known binding energy that can be obtained from a given number of hydrogen-bonds and from a given surface area, allowing hydrophobic and van der Waals interactions [START_REF] Kuntz | The maximal affinity of ligands[END_REF][START_REF] Houk | Binding affinities of host-guest, protein-ligand, and protein-transition-state complexes[END_REF]. The mutations that generated a higher stability variant of streptavidin were in the second shell of residues around biotin, pointing to the difficulty of optimizing this kind of high affinity interaction computationally. Although we have sufficient knowledge to enable computational and structure-guided design of protein-ligand interactions with micromolar and sometimes nanomolar affinity [START_REF] Houk | Binding affinities of host-guest, protein-ligand, and protein-transition-state complexes[END_REF][START_REF] Das | Macromolecular modeling with rosetta[END_REF][START_REF] Holm | Electrophilic affibodies forming covalent bonds to protein targets[END_REF], the factors responsible for increasing affinity into the picomolar and femtomolar range are still enigmatic [START_REF] Midelfort | Substantial energetic improvement with minimal structural perturbation in a high affinity mutant antibody[END_REF][START_REF] Foote | Breaking the affinity ceiling for antibodies and T cell receptors[END_REF]. Hydrogen/deuterium exchange mass spectrometry, now possible with single residue resolution, may be able to build upon our crystal structures for further enlightenment on the "perfect storm" of molecular events required for biotin to overcome the large activation barrier to dissociate from traptavidin [START_REF] Rand | Protein hydrogen exchange measured at single-residue resolution by electron transfer dissociation mass spectrometry[END_REF]. As well as suggesting how to improve further the applications of biotin as an affinity tag, the structures of traptavidin shed light on the origins of extreme-affinity interactions, with implications for the rational design of drugs with improved efficacy.

TABLES Table 1 Data collection and refinement statistics for crystal structures of apo-traptavidin and biotin-traptavidin

Values in parentheses are for the highest-resolution shell.

Apo

  Journal Immediate Publication. Published on 18 Jan 2011 as manuscript BJ20101593 THIS IS NOT THE VERSION OF RECORD -see doi:10.1042/BJ20101593

  Biochemical Journal Immediate Publication. Published on 18 Jan 2011 as manuscript BJ20101593 THIS IS NOT THE VERSION OF RECORD -see doi:10.1042/BJ20101593A c c e p t e d M a n u s c r i p t Licenced copy. Copying is not permitted, except with prior permission and as allowed by law.

Biochemical

  Journal Immediate Publication. Published on 18 Jan 2011 as manuscript BJ20101593 THIS IS NOT THE VERSION OF RECORD -see doi:10.1042/BJ20101593

Figure 1

 1 Figure 1 Crystal structures of traptavidin

Figure 2

 2 Figure 2 The L3/4 loop of traptavidin is shut with and without biotin

Figure 3

 3 Figure 3 Traptavidin flexibility

Figure 4

 4 Figure 4 Hydrogen bonding by Ser-45 in traptavidin

Figure 5

 5 Figure 5 Monovalent traptavidin off-rate and thermostability

Table 2 Structural alignments of loop regions (

 2 A) Loops of apo-traptavidin were aligned to biotin-traptavidin and apo/biotin-streptavidin. Residues comprising each loop are shown in parentheses. (B) Loops of apo-streptavidin were aligned to biotinstreptavidin and apo/biotin-traptavidin. Only main-chain atoms were used to calculate the alignments. *The loop of 1swa was compared only for the resolved residues of 45 and 49-52, since 46-48 were disordered.

		-traptavidin (PDB 2y3e)	Biotin-traptavidin (PDB 2y3f)
	DATA COLLECTION
	Space group	I 4 1	P 4 2 2 1 2
	Cell dimensions
	a, b, c (Å)	57.59, 57.59, 183.35	57.34, 57.34, 77.55
	, ,  ()	90.00, 90.00, 90.00	90.00, 90.00, 90.00
	Resolution (Å)	27.47 -1.45 (1.53 -1.45)	38.78 -1.49 (1.57 -1.49)
	R merge	0.052 (0.619)	0.069 (0.085)
	I / I	13.6 (2.0)	26.0 (19.6)
	Completeness (%)	97.8 (87.1)	100.0 (100.0)
	Multiplicity	3.6 (3.2)	7.0 (7.1)
	REFINEMENT
	Resolution (Å)	27.47 -1.45	32.12 -1.49
	No. reflections	48,884	21,581
	R work / R free	0.134 / 0.178	0.135 / 0.152
	No. atoms
	Protein	1,855	954
	Biotin	n/a	16
	Glycerol	18	18
	Water	321	142
	B factors
	(mean of all atoms, Å 2 )
	Protein	33.41	10.10
	Biotin	n/a	5.83
	Glycerol	44.14	28.31
	Water	38.19	27.92
	Rmsd
	Bond length rmsd (Å)	0.005	0.009
	Bond angle rmsd ()	0.93	1.48
	Twinning
	Twin operator	-h, k, -l	n/a
	Twin fraction	0.497	n/a

Licenced copy. Copying is not permitted, except with prior permission and as allowed by law.

© 2011 The Authors Journal compilation © 2011 Portland Press Limited

© 2011 The Authors Journal compilation © 2011 Portland Press Limited

A c c e p t e d M a n u s c r i p t Licenced copy. Copying is not permitted, except with prior permission and as allowed by law. © 2011 The Authors Journal compilation © 2011 Portland Press Limited

Licenced copy. Copying is not permitted, except with prior permission and as allowed by law.© 2011 The Authors Journal compilation © 2011 Portland Press Limited

ACKNOWLEDGEMENTS

We thank Sonja Baumli for assistance in crystal freezing. Traptavidin is subject to a UK priority patent application (0919102.4) filed on 30 th October 2009.

FUNDING Funding was provided by the Wellcome Trust (A.L.K. and M.H.), the Biotechnology and Biological Sciences Research Council (C.E.C.), Oxford University (E.D.L.), and Worcester College Oxford (M.H.). Biochemical Journal Immediate Publication. Published on 18 Jan 2011 as manuscript BJ20101593 THIS IS NOT THE VERSION OF RECORD -see doi:10.1042/BJ20101593

A c c e p t e d M a n u s c r i p t Licenced copy. Copying is not permitted, except with prior permission and as allowed by law.