Quantitative lectin-carbohydrate interaction analysis on solid-phase surfaces using biosensor based on surface plasmon resonance

Surface plasmon resonance as a tool to characterize lectin-carbohydrate interactions

Biosensors based on surface plasmon resonance (SPR) monitor changes in refractive index in the vicinity of a surface in a real-time manner, which allows rapid, label-free characterization of the interactions of various types of molecules, from quantitative measurements of binding kinetics, thermodynamics, and concentrations in complex samples to epitope analysis. This method is usually capable of analyzing affinities in the range of millimolar to picomolar and is sensitive (typically, the concentration range of the analyte is 0.1-100×Kd and the typical volumes needed are in the range of 50-150 μL). There are two major applications of SPR biosensors for the analysis of lectin-carbohydrate interactions: detailed characterization of the interaction (e.g., specificity, affinity, kinetics, stoichiometry) and screening of lectin and carbohydrate/glycoconjugate interactions for diagnosis, identification of endogenous ligands, or binding properties of interest. Care should be taken, since the interaction of lectin and carbohydrate on the solid phase is complicated by the nonhomogeneous conditions under which binding occurs. However, this may in fact mimic some biological conditions, such as those occurring in cell-cell interactions.

Measurement of monovalent and polyvalent carbohydrate-lectin binding by back-scattering interferometry

Carbohydrate-protein binding is important to many areas of biochemistry. Here, backscattering interferometry (BSI) has been shown to be a convenient and sensitive method for obtaining quantitative information about the strengths and selectivities of such interactions. The surfaces of glass microfluidic channels were covalently modified with extravidin, to which biotinylated lectins were subsequently attached by incubation and washing. The binding of unmodified carbohydrates to the resulting avidin-immobilized lectins was monitored by BSI. Dose-response curves that were generated within several minutes and were highly reproducible in multiple wash/measure cycles provided adsorption coefficients that showed mannose to bind to concanavalin A (conA) with 3.7 times greater affinity than glucose consistent with literature values. Galactose was observed to bind selectively and with similar affinity to the lectin BS-1. The avidities of polyvalent sugar-coated virus particles for immobilized conA were much higher than monovalent glycans, with increases of 60-200 fold per glycan when arrayed on the exterior surface of cowpea mosaic virus or bacteriophage Qbeta. Sugar-functionalized PAMAM dendrimers showed size-dependent adsorption, which was consistent with the expected density of lectins on the surface. The sensitivity of BSI matches or exceeds that of surface plasmon resonance and quartz crystal microbalance techniques, and is sensitive to the number of binding events, rather than changes in mass. The operational simplicity and generality of BSI, along with the near-native conditions under which the target binding proteins are immobilized, make BSI an attractive method for the quantitative characterization of the binding functions of lectins and other proteins.

Future aspects of bioprocess monitoring

Nature has the impressive ability to efficiently and precisely control biological processes by applying highly evolved principles and using minimal space and relatively simple building blocks. The challenge is to transfer these principles into technically applicable and precise analytical systems that can be used for many applications. This article summarizes some of the new approaches in sensor technology and control strategies for different bioprocesses such as fermentations, biotransformations, and downstream processes. It focuses on bio- and chemosensors, optical sensors, DNA and protein chip technology, software sensors, and modern aspects of data evaluation for improved process monitoring and control.

Application of enzymes, sodium tripolyphosphate and cation exchange resin for the release of extracellular polymeric substances from sewage sludge. Characterization of the extracted polysaccharides/glycoconjugates by a panel of lectins

The study describes extraction of extracellular polymeric substances (EPS) from sewage sludge by applying enzymes and enzymes combined with sodium tripolyphosphate (STPP). Additionally, a systematic study of two non-enzymatic extraction agents is described. The assessment of the released products is made by colorimetrical methods and polysaccharides/glycoconjugates identification by the interaction with four immobilized lectins. Bio-sludge from Helsingborg (Sweden) and Damhusåen (Denmark) were used as two case studies for testing enzymatic extractability and thereby to make useful prediction of sludge bio-digestibility. From Helsingborg sludge the enzymes extracted about 40% more of EPS than from Damhusåen. The polysaccharides/glycoconjugates in both sludges maintained the same level, and showed substantial different interaction motifs with lectins panel. Damhusåen enzymatic extracted EPS had an enhanced amount of suspended material that was post-hydrolysed by the use of polygalacturonase and lysozyme resulting in pectin like polymers and petiptidoglycans. Petiptidoglycan is a marker from bacterial cell debris. STPP and cation exchange resin (CER) released different quantities of EPS. The CER released polysaccharides/glycoconjugates had higher molecular weight and stronger affinity towards Concanavalin A than the one released by the action of STPP. Independent of the extraction conditions, STPP released elevated amounts of polyvalent cations and humic substances in contrast to the very low amounts of released by CER.

Evaluation of α-d-mannopyranoside glycolipid micelles–lectin interactions by surface plasmon resonance method

It is established that achieving higher binding affinities in carbohydrate-protein interactions requires multivalent presentations of the sugar ligands at the receptor binding site. Several inhibition, calorimetric, mass balance, and other studies have reiterated the beneficial effects of molecular level clustering of the sugar ligands for tight binding to the receptors. We have undertaken an effort to study the multivalent effects involving larger assemblies, represented by micelles, and their lectin interactions. The micelles were constituted with monomer bearing one- or two-sugar moieties at the monomolecular level and with varying the distances between the sugar moieties. Micellar aggregation studies and dynamic light scattering (DLS) studies afforded details of the aggregation numbers and the hydrodynamic diameters of various glycolipid (GL) micelles. The GL micelles were used as analytes of surface plasmon resonance (SPR) experiments on a lectin concanavalin A (Con A)-immobilized surface. SPR studies of the micelle-lectin interactions demonstrate that the ligand-receptor binding can be fit into the bivalent analyte model of interaction. Furthermore, micelles formed from two-sugar containing GLs are able to elicit favorable kinetic association rate constants in comparison to the micelles constituted with one-sugar containing GLs. The kinetic rate constants across the micelles and the effect of the sugar valencies in the GLs are discussed.

Survey of the year 2003 commercial optical biosensor literature

In the year 2003 there was a 17% increase in the number of publications citing work performed using optical biosensor technology compared with the previous year. We collated the 962 total papers for 2003, identified the geographical regions where the work was performed, highlighted the instrument types on which it was carried out, and segregated the papers by biological system. In this overview, we spotlight 13 papers that should be on everyone's 'must read' list for 2003 and provide examples of how to identify and interpret high-quality biosensor data. Although we still find that the literature is replete with poorly performed experiments, over-interpreted results and a general lack of understanding of data analysis, we are optimistic that these shortcomings will be addressed as biosensor technology continues to mature.