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Hideaki Nagase, Ph.D.
Kennedy Institute of Rheumatology-Centre for Degenerative Diseases, University of Oxford, UK

Osteoarthritis: diagnosis, treatment and challenges

Hideaki Nagase¹, Ngee Han Lim¹, George Bou-Gharios¹, Ernst Meinjohanns²  and Morten Meldal³

1. Kennedy Institute of Rheumatology, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, London, W6 8LH  UK
2. Carlsberg Laboratory, Copenhagen, Denmark,
3. Nano-Science Center, Department of Chemistry, University of Copenhagen, Denmark

Osteoarthritis (OA) is the most prevalent age-related degenerative joint disease. With the expanding ageing population, it imposes a major socio-economic burden on society.  A key feature of OA is a gradual loss of articular cartilage and deformation of bone, resulting in the impairment of joint function. Currently, there is no effective disease-modifying treatment except joint replacement surgery. There are many possible causes of cartilage loss (e.g. mechanical load, injury, reactive oxygen species, aging, etc.) and etiological factors (obesity, genetics), but the degradation of cartilage is primarily caused by elevated levels of active metalloproteinases.  It is therefore attractive to consider proteinase inhibitors as potential therapeutics. However, there are several hurdles to overcome, namely early diagnosis and continuous monitoring of the efficacy of inhibitor therapeutics. We are therefore aiming at developing non-invasive probes to detect cartilage degrading metalloproteinase activities.

We have designed in vivo imaging probes to detect MMP-13 (collagenase 3) activity that participates in OA by degrade cartilage collagen II and MMP-12 (macrophage elastase) activity involved in inflammatory arthritis. These activity-based probes consist of a peptide that is selectively cleaved by the target proteinase, a near-infrared fluorophore and a quencher. The probe’s signal multiplies upon proteolysis.  They were first used to follow the respective enzyme activity in vivo in the mouse model of collagen-induced arthritis and we found MMP-12 activity probe (MMP12AP) activation peaked at 5 days after onset of the disease, whereas MMP13AP activation was observed at 10-15 days. The in vivo activation of these probes was inhibited by specific low molecule inhibitors.  We proceeded to test both probes in the mouse model of OA induced by the surgical destabilization of medial meniscus of the knee joints.  In this model, degradation of knee cartilage is first detected histologically 6 weeks after surgery with significant erosion detectable at 8 weeks. Little activation of MMP12AP was detected, which was expected, as macrophage migration is not obvious in OA. MMP13AP, on the other hand, was significantly activated in the operated knee at 6 weeks compared with the non-operated contralateral knee, but there were no significant differences between the operated and sham-operated knees.  At 8 weeks, however, the signals in the operated knees were significantly higher than both the contralateral and sham-operated controls. Activation of aggrecanases and MMP-13 are observed before structural changes of cartilage. We are therefore currently improving the MMP-13 probe for earlier detection by attaching it to polymers that are retained in  cartilage.

Claudia AM Wheeler-Kingshott, Ph.D.
University Reader in Magnetic Resonance Physics, Department of Neuroinflammation, UCL Institute of Neurology, London, UK

Abstract

Detecting neuronal activity in vivo non-invasively is possible with a number of techniques. Amongst these, in 1990 functional magnetic resonance imaging (fMRI) was proposed as a technique that has a great ability to spatially map brain activity by exploiting the blood oxygenation level dependent (BOLD) contrast mechanism [1, 2]. In fact, neuronal activation triggers a demand for oxygen and induces a localised increase in blood flow and blood volume, which actually exceeds the metabolic needs. This in turns causes an increase of oxyhaemoglobin in the venous compartment, which is a transient phenomenon and is accompanied by a transient change (decrease) in the concentration of deoxyhaemoglobin. Due to its paramagnetic properties, the amount of deoxyhaemoglobin present in the venous blood affects the local magnetic field seen by the spins (protons) and determines the local properties of the MR signal. A decrease in deoxyhaemoglobin during neuronal activity, therefore, induces local variations of this magnetic field that increases the average transverse relaxation time of tissue, measured via the T2* parameter [3]. This means that there is an increase of the MR signal (of the order of a few %, typically <5%) linked to metabolic changes happening during brain function. Activation can be inferred at different brain locations by performing tasks while acquiring the MR signal and comparing periods of rest to periods of activity.

The macroscopic changes of the BOLD signal are well characterised, while the reason for the increased blood supply, exceeding demands, needs further thoughts. Here we will discuss two approaches for explaining the BOLD phenomenon, one that links it to adenosine triphosphate production [4] and enzyme saturation, the other that relates it to the very slow diffusion of oxygen through the blood-brain-barrier with a consequent compensatory high demand of oxygen [5]. Some evidence of restricted oxygen diffusion has been shown by means of hypercapnia [6], although it is not excluded that both mechanisms may be present.

Overall, the BOLD signal changes theory and its physiological basis will be presented and discussed.

References

1. Ogawa, S., et al., Brain magnetic resonance imaging with contrast dependent on blood oxygenation. Proc Natl Acad Sci U S A, 1990. 87(24): p. 9868-72.
2. Kwong, K.K., et al., Dynamic magnetic resonance imaging of human brain activity during primary sensory stimulation. Proc Natl Acad Sci U S A, 1992. 89(12): p. 5675-9.
3. Bandettini PA, et al. Spin-echo and gradient-echo EPI of human brain activation using BOLD contrast: a comparative study at 1.5 T. NMR Biomed. 1994 Mar;7(1-2):12-20
4.  Fox, P.T., et al., Nonoxidative glucose consumption during focal physiologic neural activity. Science, 1988. 241(4864): p. 462-4.
5. Gjedde, A., et al. Reduction of functional capillary density in human brain after stroke. J Cereb Blood Flow Metab, 1990. 10(3): p. 317-26.
6. Hoge, R.D., et al., Linear coupling between cerebral blood flow and oxygen consumption in activated human cortex. Proc Natl Acad Sci U S A, 1999. 96(16): p. 9403-8.

Deepthy Menon, Ph.D.
Associate Professor, Centre for Nanosciences & Molecular Medicine, Health Sciences Campus, Amrita University, Kochi, India

Nanobioengineering of implant materials for improved cellular response and activity

Deepthy Menon, Divyarani V V, Chandini C Mohan, Manitha B Nair, Krishnaprasad C & Shantikumar V Nair

Abstract

Current trends in biomaterials research and development include the use of surfaces with topographical features at the nanoscale (dimensions < 100 nm), which influence biomolecular or cellular level reactions in vitro and in vivo. Progress in nanotechnology now makes it possible to precisely design and modulate the surface properties of materials used for various applications in medicine at the nanoscale. Nanoengineered surfaces, owing to their close resemblance with extracellular matrix, possess the unique capacity to directly affect protein adsorption that ultimately modulates the cellular adhesion and proliferation at the site of implantation. Taking advantage of this exceptional ability, we have nanoengineered metallic surfaces of Titanium (Ti) and its alloys (Nitinol -NiTi), as well as Stainless Steel (SS) by a simple hydrothermal method for generating non-periodic, homogeneous nanostructures. The bio- and hemocompatibility of these nanotextured metallic surfaces suggest their potential use for orthopedic, dental or vascular implants. The applicability of nanotextured Ti implants for orthopedic use was demonstrated in vivo in rat models, wherein early-stage bone formation at the tissue-implant interface without any fibrous tissue intervention was achieved. This nanoscale topography also was found to critically influence bacterial adhesion in vitro, with decreased adherence of staphylococcus aureus. The same surface nanotopography also was found to provide enhanced proliferation and functionality of vascular endothelial cells, suggesting its prospective use for developing an antithrombotic stent surface for coronary applications. Clinical SS & NiTi stents were also modified based on this strategy, which would offer a suitable solution to reduce the probability of late stent thrombosis associated with bare metallic stents. Thus, we demonstrate that nanotopography on implant surfaces has a critical influence on the fate of cells, which in turn dictates the long term success of the implant.

Acknowledgement: Authors gratefully acknowledge the financial support from Department of Biotechnology, Government of India through the Bioengineering program.

Abhijeet Kate, Arpana G Panicker, Diana Writer, Giridharan P, Keshav K V Ramamoorthy, Saji George, Shailendra K Sonawane

Protoplast fusion and transformation: A tool for activation of latent gene clusters

In the quest to discover new bioactive leads for unmet medical needs, actinomycetes present a treasure trove of undiscovered molecules. The ability of actinomycetes to produce antibiotics and other bioactive secondary metabolites has been underestimated due to sparse studies of cryptic gene clusters. These gene clusters can be tapped to explore scaffolds hidden in them. The up-regulation of the dormant genes is one of the most important areas of interest in the bioactive compounds discovery from microbial resources. Genome shuffling is a powerful tool for the activation of such gene clusters. Lei Yu, et al.1, reported enhancement of the lactic acid production in Lactobacillus rhamnosus through genome shuffling brought about by protoplast fusion. D. A. Hopwood et al.2 suggested that an interspecific recombination between strains producing different secondary metabolites, generate producers of ‘hybrid’ antibiotics. They also mentioned that an intraspecific fusion of actinomycetes protoplast bring about random and high frequency recombination. Protoplasts can also be used as recipients for isolated DNA, again in the presence of polyethylene glycol (PEG). In our study we had undertaken random genome shuffling by protoplast fusion of two, rather poorly expressed actinomycetes strains A (Figure 1) & B (Figure 2), mediated by PEG; and also by naked DNA transformation of Strain A protoplast with the DNA of Strain B. We generated eight protoplast fusants and seven transformants from parents considering their morphological difference from the two parent strains. These 15 recombinants were checked for their same colony morphologies for five generations to ensure phenotypic stability. Antibiotic resistance pattern was established by using antibiotic octodisc to generate a marker profile of the recombinants and the parent strains. Eight fusants (AP-18, AP-25, AP-2, AP-11, AP-14, AP-19, AP-11 and AP-27) and four transformants (TAP-30, TAP-31, TAP-32 and TAP-33) (Table 1) have shown a different antibiotic sensitivity pattern as compared to the parent strains. We envisage that these recombinants harbor shuffled gene clusters. To support array of conditions to express such shuffled/cryptic genes the recombinants were fermented in 11 different nutrient stress variants. The extracts generated were subjected to metabolite profiling by HPLC-ELSD, bioactivity screening for cytotoxicity and anti-infective capabilities. Two fusants AP-11 (Figure 3) and AP-25; one transformant TAP-32 (in growth media MBA-5 and MBA-7) displayed antifungal activity unlike parent strains (Table 2) Fusant AP-11 (Table 5) exhibited significant cell growth inhibition of five different cancer cell lines. The parents Strain A and Strain B did not exhibit any cell growth inhibition of these cell lines (Table 5). The metabolite profiling of fusant AP-11 and transformant TAP-32 was done by HPLC-ELSD. AP-11 showed the presence of five additional peaks (Figure 5 & Figure 6); TAP-32 extract from medium MBA-5 (Figure 7 & Figure 8) showed the presence of four additional peaks and TAP-32 extract from MBA-7 (Figure 9 & Figure 10) showed 14 additional peaks as compared to parent strains in similar medium and media controls. The study indicated that protoplast fusion and transformation have not only caused morphological changes but also shuffled genes responsible for synthesis of bioactive molecules. Further characterization of these new peaks is warranted.

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