A solution state NMR study of the structure and ligand binding properties of the human C-type lectin DC-SIGNR

The protein DC-SIGNR (Dendritic-cell specific ICAM3 grabbing non-integrin related) is a C-type (calcium-dependent) lectin, which binds highly-branched mannose oligosaccharides. DC-SIGNR interacts with a range of deadly diseases via surface glycans on pathogenic glycoproteins, and the ability of DC-SIGNR to increase the rate of infection of viruses including human immunodeficiency virus (HIV) and hepatitis C virus (HCV) makes the study of DC-SIGNR/oligosaccharide interactions very attractive. The research described in this thesis sought to gain insight into the calcium and ligand binding properties of the DC-SIGNR carbohydrate recognition domain (CRD) in solution by utilising solution state nuclear magnetic resonance spectroscopy (NMR). A protocol for the production of uniformly 15N /13C labelled DC-SIGNR CRD was developed, allowing the acquisition of heteronuclear NMR experiments and the first assignment of the calcium-bound (holo) DC-SIGNR CRD to be reported. The assignment has allowed investigation of calcium and glycan binding, as well as the pH dependence of the DC-SIGNR CRD. The data presented in this thesis reveal that the DC-SIGNR CRD is highly dynamic in the calcium-free state, with the addition of calcium resulting in global conformational and dynamic changes throughout the CRD. While calcium binding hinders the protein dynamics (particularly in the calcium binding regions), a large degree of mobility remains. The evidence that ligands are released at low pH suggests that DC-SIGNR may act as an endocytic receptor. In addition to calcium binding, interactions of the DC-SIGNR CRD with a range of ligands were investigated. In particular, interactions with the oligosaccharide Man9GlcNAc (present on the HIV viral envelope) are described, representing the first direct study of the CRD interacting with a diseaseassociated ligand. The glycans employed in this study all bind to the primary calcium binding site, supporting previous crystal data. However, each glycan displays distinct patterns of chemical shift perturbations implying that they each have different, extended binding modes. Particularly striking is the difference between the disease-associated Man9GlcNAc ligand and the ligand present in a previously published crystal structure, (GlcNAc)2Man3. An investigation of the dynamics of the CRD in the holo form and bound to the ligand Man5 shows that the CRD is highly dynamic and that glycan binding further hinders, but does not abolish, the molecular motions. The dynamics data also suggests that a ligand-induced conformational change may occur and indicates potential new binding sites which are not present in any published crystal structures. The dynamic nature of the DC-SIGNR CRD may explain the wide range of ligand specificities and affinities of the C-type lectin scaffold and suggests that the study of the ligand binding properties and dynamics of proteins such as DC-SIGNR in solution is essential to further understanding of this class of proteins

New analytical methods focusing on polar metabolite analysis in mass spectrometry and NMR-based metabolomics

Following in the footsteps of genomics and proteomics, metabolomics has revolutionised the way we investigate and understand biological systems. Rapid development in the last 25 years has been driven largely by technical innovations in mass spectrometry and nuclear magnetic resonance spectroscopy. However, despite the modest size of metabolomes relative to proteomes and genomes, methodological capabilities for robust, comprehensive metabolite analysis remain a major challenge. Therefore, development of new methods and techniques remains vital for progress in the field. Here, we review developments in LC-MS, GC-MS and NMR methods in the last few years that have enhanced quantitative and comprehensive metabolome coverage, highlighting the techniques involved, their technical capabilities, relative performance, and potential impact

Plasma nuclear magnetic resonance metabolomics discriminates between high and low endoscopic activity and predicts progression in a prospective cohort of patients with ulcerative colitis

Background and Aims Endoscopic assessment of ulcerative colitis [UC] is one of the most accurate measures of disease activity, but frequent endoscopic investigations are disliked by patients and expensive for the healthcare system. A minimally invasive test that provides a surrogate measure of endoscopic activity is required. Methods Plasma nuclear magnetic resonance [NMR] spectra from 40 patients with UC followed prospectively over 6 months were analysed with multivariate statistics. NMR metabolite profiles were compared with endoscopic [Ulcerative Colitis Endoscopic Index of Severity: UCEIS], histological [Nancy Index] and clinical [Simple Clinical Colitis Activity Index: SCCAI] severity indices, along with routine blood measurements. Results A blinded principal component analysis spontaneously separated metabolite profiles of patients with low [≤3] and high [>3] UCEIS. Orthogonal partial least squares discrimination analysis identified low and high UCEIS metabolite profiles with an accuracy of 77 ± 5%. Plasma metabolites driving discrimination included decreases in lipoproteins and increases in isoleucine, valine, glucose and myo-inositol in high compared to low UCEIS. This same metabolite profile distinguished between low [Nancy 0–1] and high histological activity [Nancy 3–4] with a modest although significant accuracy [65 ± 6%] but was independent of SCCAI and all blood parameters measured. A different metabolite profile, dominated by changes in lysine, histidine, phenylalanine and tyrosine, distinguished between improvement in UCEIS [decrease ≥1] and worsening [increase ≥1] over 6 months with an accuracy of 74 ± 4%. Conclusion Plasma NMR metabolite analysis has the potential to provide a low-cost, minimally invasive technique that may be a surrogate for endoscopic assessment, with predictive capacity

Repeated administration of L-alanine to mice, reduces behavioural despair and increases hippocampal mTOR signalling: analysis of gender and metabolic effects

Background: The amino acid, L-alanine, has been shown to be elevated in biofluids in major depression but its relevance remains unexplored. Aim: We have investigated the effects of repeated L-alanine administration on emotional behaviours and central gene expression in mice. Methods: Mice received a daily, 2-week intraperitoneal injection of either saline or alanine at 100mg/kg or 200mg/kg, and exposed to the open field, light-dark box and forced swim test. The expression of L-alanine transporters (asc-1, ASCT2), glycine receptor subunits (GlyRs), NMDA receptor subunits (GluNs) mRNAs were measured, together with western blots of the signalling protein mTOR. Since L-alanine modulates glucose homeostasis, peripheral and central metabolomes were evaluated with 1H-NMR. Results: L-alanine administration at 100mg/kg, but not at 200mg/kg, to both male and female mice increased latency to float and reduced floating time in the forced swim test, but had no effect on anxious behaviour in the open field and light-dark box tests. There was a significant reduction in mRNAs encoding asc-1 and ASCT2 and GluN2B in the hippocampus of mice following 100mg/kg L-alanine only. On western blots, hippocampal GluN2B immunoreactivity was reduced but, mTOR signalling was increased in the 100mg/kg L-alanine group. 1H-NMR revealed gender-specific changes in the forebrain, plasma and liver metabolomes only at 200mg/kg of L-alanine. Conclusions: Our data suggest that L-alanine may have antidepressant-like effect that may involve the modulation of glutamate neurotransmission independently of metabolism. In major depression, therefore, elevated L-alanine may be a homeostatic response to pathophysiological processes, though this will require further investigation

Unique pathways downstream of TLR-4 and TLR-7 activation: sex-dependent behavioural, cytokine, and metabolic consequences

Introduction: Post-infection syndromes are characterised by fatigue, muscle pain, anhedonia, and cognitive impairment; mechanistic studies exploring these syndromes have focussed on pathways downstream of Toll-like receptor (TLR) 4 activation. Here, we investigated the mechanistic interplay between behaviour, metabolism, and inflammation downstream of TLR-7 activation compared to TLR-4 activation in male and female CD1 mice. Methods: Animals received either a TLR-4 (LPS; 0.83 mg/kg) or TLR-7 (R848, 5 mg/kg) agonist, or saline, and behaviour was analysed in an Open Field (OF) at 24 h (n = 20/group). Plasma, liver, and prefrontal cortex (PFC) were collected for gene expression analysis at 24 h and 1H-NMR metabolomics. Results: TLR-4 and TLR-7 activation decreased distance travelled and rearing in the OF, but activation of each receptor induced distinct cytokine responses and metabolome profiles. LPS increased IL-1β expression and CXCL1 in the PFC, but TLR7 activation did not and strongly induced PFC CXCL10 expression. Thus, TLR7 induced sickness behaviour is independent of IL-1β expression. In both cases, the behavioural response to TLR activation was sexually dimorphic: females were more resilient. However, dissociation was observed between the resilient female mice behaviour and the levels of gene cytokine expression, which was, in general, higher in the female mice. However, the metabolic shifts induced by immune activation were better correlated with the sex-dependent behavioural dimorphisms; increased levels of antioxidant potential in the female brain are intrinsic male/female metabolome differences. A common feature of both TLR4 and TLR7 activation was an increase in N-acetyl aspartate (NAA) in the PFC, which is likely be an allostatic response to the challenges as sickness behaviour is inversely correlated with NAA levels. Discussion: The results highlight how the cytokine profile induced by one PAMP cannot be extrapolated to another, but they do reveal how the manipulation of the conserved metabolome response might afford a more generic approach to the treatment of post-infection syndromes

Lesion level and severity acutely influence metabolomic profiles in spinal cord injury

Changes in the peripheral metabolome, particularly in the blood, may provide biomarkers for assessing lesion severity and predicting outcomes after spinal cord injury (SCI). Using principal component analysis (PCA) and Orthogonal Partial Least Squares Discriminatory Analysis (OPLS-DA), we sought to discover how SCI severity and location acutely affect the nuclear magnetic resonance-acquired metabolome of the blood, spinal cord, and liver at 6 h post-SCI in mice. Unsupervised PCA of the spinal cord metabolome separated mild (30 kdyne) and severe (70 kdyne) contusion injury groups but did not distinguish between lesion level. However, OPLS-DA could discriminate thoracic level T2 from T9 lesions in both blood plasma (accuracy 86 ± 6%) and liver (accuracy 89 ± 5%) samples. These differences were dependent on alterations in energy metabolites (lactate and glucose), lipoproteins, and lipids. Lactate was the most discriminatory between mild and severe injury at T2, whereas overlapping valine/proline resonances were most discriminatory between injury severities at T9. Plasma lactate correlated with blood-spinal cord barrier breakdown and plasma glucose with microglial density. We propose that peripheral biofluid metabolites can serve as biomarkers of SCI severity and associated pathology at the lesion site; their predictive value is most accurate when the injury level is also considered

Ex-Vivo 13 C NMR Spectroscopy of Rodent Brain: TNF Restricts Neuronal Utilization of Astrocyte-Derived Metabolites

Tumor necrosis factor (TNF) has well-established roles in neuroinflammatory disorders, but the effect of TNF on the biochemistry of brain cells remains poorly understood. Here, we microinjected TNF into the brain to study its impact on glial and neuronal metabolism (glycolysis, pentose phosphate pathway, citric acid cycle, pyruvate dehydrogenase, and pyruvate carboxylase pathways) using 13C NMR spectroscopy on brain extracts following intravenous [1,2-13C]-glucose (to probe glia and neuron metabolism), [2-13C]-acetate (probing astrocyte-specific metabolites), or [3-13C]-lactate. An increase in [4,5-13C]-glutamine and [2,3-13C]-lactate coupled with a decrease in [4,5-13C]-glutamate was observed in the [1,2-13C]-glucose-infused animals treated with TNF. As glutamine is produced from glutamate by astrocyte-specific glutamine synthetase the increase in [4,5-13C]-glutamine reflects increased production of glutamine by astrocytes. This was confirmed by infusion with astrocyte substrate [2-13C]-acetate. As lactate is metabolized in the brain to produce glutamate, the simultaneous increase in [2,3-13C]-lactate and decrease in [4,5-13C]-glutamate suggests decreased lactate utilization, which was confirmed using [3-13C]-lactate as a metabolic precursor. These results suggest that TNF rearranges the metabolic network, disrupting the energy supply chain perturbing the glutamine-glutamate shuttle between astrocytes and the neurons. These insights pave the way for developing astrocyte-targeted therapeutic strategies aimed at modulating effects of TNF to restore metabolic homeostasis in neuroinflammatory disorders

Unique pathways downstream of TLR-4 and TLR-7 activation: sex-dependent behavioural, cytokine, and metabolic consequences

IntroductionPost-infection syndromes are characterised by fatigue, muscle pain, anhedonia, and cognitive impairment; mechanistic studies exploring these syndromes have focussed on pathways downstream of Toll-like receptor (TLR) 4 activation. Here, we investigated the mechanistic interplay between behaviour, metabolism, and inflammation downstream of TLR-7 activation compared to TLR-4 activation in male and female CD1 mice.MethodsAnimals received either a TLR-4 (LPS; 0.83 mg/kg) or TLR-7 (R848, 5 mg/kg) agonist, or saline, and behaviour was analysed in an Open Field (OF) at 24 h (n = 20/group). Plasma, liver, and prefrontal cortex (PFC) were collected for gene expression analysis at 24 h and 1H-NMR metabolomics.ResultsTLR-4 and TLR-7 activation decreased distance travelled and rearing in the OF, but activation of each receptor induced distinct cytokine responses and metabolome profiles. LPS increased IL-1β expression and CXCL1 in the PFC, but TLR7 activation did not and strongly induced PFC CXCL10 expression. Thus, TLR7 induced sickness behaviour is independent of IL-1β expression. In both cases, the behavioural response to TLR activation was sexually dimorphic: females were more resilient. However, dissociation was observed between the resilient female mice behaviour and the levels of gene cytokine expression, which was, in general, higher in the female mice. However, the metabolic shifts induced by immune activation were better correlated with the sex-dependent behavioural dimorphisms; increased levels of antioxidant potential in the female brain are intrinsic male/female metabolome differences. A common feature of both TLR4 and TLR7 activation was an increase in N-acetyl aspartate (NAA) in the PFC, which is likely be an allostatic response to the challenges as sickness behaviour is inversely correlated with NAA levels.DiscussionThe results highlight how the cytokine profile induced by one PAMP cannot be extrapolated to another, but they do reveal how the manipulation of the conserved metabolome response might afford a more generic approach to the treatment of post-infection syndromes

NMR analysis reveals significant differences in the plasma metabolic profiles of Niemann Pick C1 patients, heterozygous carriers, and healthy controls.

Niemann-Pick type C1 (NPC1) disease is a rare autosomal recessive, neurodegenerative lysosomal storage disorder, which presents with a range of clinical phenotypes and hence diagnosis remains a challenge. In view of these difficulties, the search for a novel, NPC1-specific biomarker (or set of biomarkers) is a topic of much interest. Here we employed high-resolution 1H nuclear magnetic resonance spectroscopy coupled with advanced multivariate analysis techniques in order to explore and seek differences between blood plasma samples acquired from NPC1 (untreated and miglustat treated), heterozygote, and healthy control subjects. Using this approach, we were able to identify NPC1 disease with 91% accuracy confirming that there are significant differences in the NMR plasma metabolic profiles of NPC1 patients when compared to healthy controls. The discrimination between NPC1 (both miglustat treated and untreated) and healthy controls was dominated by lipoprotein triacylglycerol 1H NMR resonances and isoleucine. Heterozygote plasma samples displayed also increases in the intensities of selected lipoprotein triacylglycerol 1H NMR signals over those of healthy controls. The metabolites identified could represent useful biomarkers in the future and provide valuable insight in to the underlying pathology of NPC1 disease

A blood-based metabolomics test to distinguish relapsing–remitting and secondary progressive multiple sclerosis: addressing practical considerations for clinical application

The transition from relapsing–remitting multiple sclerosis (RRMS) to secondary progressive MS (SPMS) represents a huge clinical challenge. We previously demonstrated that serum metabolomics could distinguish RRMS from SPMS with high diagnostic accuracy. As differing sample-handling protocols can affect the blood metabolite profile, it is vital to understand which factors may influence the accuracy of this metabolomics-based test in a clinical setting. Herein, we aim to further validate the high accuracy of this metabolomics test and to determine if this is maintained in a ‘real-life’ clinical environment. Blood from 31 RRMS and 28 SPMS patients was subjected to different sample-handling protocols representing variations encountered in clinics. The effect of freeze–thaw cycles (0 or 1) and time to erythrocyte removal (30, 120, or 240 min) on the accuracy of the test was investigated. For test development, samples from the optimised protocol (30 min standing time, 0 freeze–thaw) were used, resulting in high diagnostic accuracy (mean ± SD, 91.0 ± 3.0%). This test remained able to discriminate RRMS and SPMS samples that had experienced additional freeze–thaw, and increased standing times of 120 and 240 min with accuracies ranging from 85.5 to 88.0%, because the top discriminatory metabolite biomarkers from the optimised protocol remained discriminatory between RRMS and SPMS despite these sample-handling variations. In conclusion, while strict sample-handling is essential for the development of metabolomics-based blood tests, the results confirmed that the RRMS vs. SPMS test is resistant to sample-handling variations and can distinguish these two MS stages in the clinics