Chemistry

The apoprotein of flavodoxin from Desulfovibrio vulgaris forms a complex with riboflavin. The ability to bind riboflavin distinguishes this flavodoxin from other short-chain flavodoxins which require the phosphate of FMN for flavin binding. The redox potential of the semiquinone/ ...

The side chain of aspartate 95 in flavodoxin from DesulfoVibrio Vulgaris provides the closest negative charge to N(1) of the bound FMN in the protein. Site-directed mutagenesis was used to substitute alanine, asparagine, or glutamate for this amino acid to assess the effect of this charge on the semiquinone/ hydroquinone redox potential (E 1) of the FMN cofactor. The D95A mutation shifts the E 1 redox potential positively by 16 mV, while a negative shift of 23 mV occurs in the oxidized/semiquinone midpoint redox potential (E 2). The crystal structures of the oxidized and semiquinone forms of this mutant are similar to the corresponding states of the wild-type protein. In contrast to the wild-type protein, a further change in structure occurs in the D95A mutant in the hydroquinone form. The side chain of Y98 flips into an energetically more favorable edge-to-face interaction with the bound FMN. Analysis of the structural changes in the D95A mutant, taking into account electrostatic interactions at the FMN binding site, suggests that the π-π electrostatic repulsions have only a minor contribution to the very low E 1 redox potential of the FMN cofactor when bound to apoflavodoxin. Substitution of D95 with glutamate causes only a slight perturbation of the two one-electron redox potentials of the FMN cofactor. The structure of the D95E mutant reveals a large movement of the 60-loop (residues 60-64) away from the flavin in the oxidized structure. Reduction of this mutant to the hydroquinone causes the conformation of the 60-loop to revert back to that occurring in the structures of the wild-type protein. The crystal structures of the D95E mutant imply that electrostatic repulsion between a carboxylate on the side chain at position 95 and the phenol ring of Y98 prevents rotation of the Y98 side chain to a more energetically favorable conformation as occurs in the D95A mutant. Replacement of D95 with asparagine has no effect on E 2 but causes E 1 to change by 45 mV. The D95N mutant failed to crystallize. The K d values of the protein FMN complex in all three oxidation-reduction states differ from those of the wild-type complexes. Molecular modeling showed that the conformational energy of the protein changes with the redox state, in qualitative agreement with the observed changes in K d , and allowed the electrostatic interactions between the FMN and the surrounding groups on the protein to be quantified. † This work was supported in part by grants from BioResearch Ireland. M.A.W. was supported by an EU Institutional Fellowship contract (CT 930485). C.S.V. thanks the BBSRC for support. ‡ Atomic coordinates and structure factors for the structures described in this work have been deposited in the Protein Data Bank: 1AKQ for D95A ox, 1AKV for D95A sq, 1AKU for D95A hq, 1C7F for D95E ox, and 1C7E for D95E hq.

Cell culture media used in industrial mammalian cell culture are complex aqueous solutions that are inherently difficult to analyze comprehensively. The analysis of media quality and variance is of utmost importance in efficient manufacturing. We are exploring the use of rapid “holistic” analytical methods that can be used for routine screening of cell culture media used in industrial biotechnology. The application of rapid fluorescence spectroscopic techniques to the routine analysis of cell culture media (Chinese Hamster Ovary cell based manufacture) was investigated. We have developed robust methods which can be used to identify compositional changes and ultimately predict the efficacy of individual fed batch media in terms of downstream protein product yield with an accuracy of =/- 0.13 g/L. This is achieved through the implementation of chemometric methods such as multiway robust principal component analysis (MROBPCA), n-way partial least squares-discriminant analysis and regression (NPLS-DA and NPLS). This ability to observe compositional changes and predict product yield before media use has enormous potential and should permit the effective elimination of one of the major process variables leading to more consistent product quality and improved yield. These robust and reliable methods have the potential to become an important part of upstream biopharmaceutical quality control and analysis.

Time-resolved fluorescence data was collected from a series of 23 bulk crude petroleum oils and six microscopic hydrocarbon-bearing fluid inclusions (HCFI). The data was collected using a diode laser fluorescence lifetime microscope (DLFLM) over the 460-700 nm spectral range using a 405 nm excitation source. The correlation between intensity averaged lifetimes (τ) and chemical and physical parameters was examined with a view to developing a quantitative model for predicting the gross chemical composition of hydrocarbon liquids trapped in HCFI. It was found that τ is nonlinearly correlated with the measured polar and corrected alkane concentrations and that oils can be classified on this basis. However, these correlations all show a large degree of scatter, preventing accurate quantitative prediction of gross chemical composition of the oils. Other parameters such as API gravity and asphaltene, aromatic, and sulfur concentrations do not correlate well with τ measurements. Individual HCFI were analyzed using the DLFLM, and time-resolved fluorescence measurements were compared with τ data from the bulk oils. This enabled the fluid within the inclusions to be classified as either low alkane/high polar or high alkane/low polar. Within the high alkane/low polar group, it was possible to clearly discriminate HCFI from different locales and to see differences in the trapped hydrocarbon fluids from a single geological source. This methodology offers an alternative method for classifying the hydrocarbon content of HCFI and observing small variations in the trapped fluid composition that is less sensitive to fluctuations in the measurement method than fluorescence intensity based methods.

We report a novel fluorescence-lifetime-based pH sensing method that utilizes acridine incorporated into Nafion (AcNaf) as the fluorescent indicator. The AcNaf sensor is excited using a 380 nm light emitting diode (LED) and the fluorescence lifetimes are measured at 450 and 500 nm. The fluorescence behavior of acridine as a function of pH in aqueous phosphate buffers and incorporated into the Nafion membrane has been investigated. The results show that incorporating acridine into Nafion changes the apparent ground-state pKa from ~5.45 to ~9, while the apparent excited-state pKa* is only slightly changed (~9.4 in 0.1 M phosphate buffer). The AcNaf film shows a good pH response with a change in average lifetime of ~19 ns (at an emission wavelength of 450 nm) over the pH 8 to 10 range. We also show that excited-state protonation does not occur in the AcNaf sensor film and that chloride quenching cannot occur because of the permselective nature of Nafion. We also discuss how the unique structure of Nafion affects the fluorescence behavior of acridine at various pH values and examine the impact of buffer concentration on apparent pKa and pH sensing ability.

Raman spectroscopy offers the potential for the identification of illegal narcotics in seconds by inelastic scattering of light from molecular vibrations. In this study cocaine, heroin, and MDMA were analyzed using near-IR (785 nm excitation) micro-Raman spectroscopy. Narcotics were dispersed in solid dilutants of different concentrations by weight. The dilutants investigated were foodstuffs (flour, baby milk formula), sugars (glucose, lactose, maltose, mannitol), and inorganic materials (Talc powder, NaHCO3, MgSO4·7H2O). In most cases it was possible to detect the presence of drugs at levels down to ∼10% by weight. The detection sensitivity of the Raman technique was found to be dependent on a number of factors such as the scattering cross-sections of drug and dilutant, fluorescence of matrix or drug, complexity of dilutant Raman spectrum, and spectrometer resolution.

Raman spectra from a series of 20 mixtures of cocaine and glucose (0–100% by weight cocaine) were collected and analyzed using multivariate analysis methods. An accurate prediction model was generated using a Partial Least Squares (PLS) algorithm that can predict the concentration of cocaine in solid glucose from a single Raman spectrum with a root mean standard error of prediction of 2.3%.

Nanochemistry offers stimulating opportunities for a wide variety of applications in the biosciences. Understanding of the interaction of nanoparticles with biomolecules such as proteins is very important as it can help better design and fabricate nanocomposites for applications in diagnostics, drug delivery, and cell monitoring. In this work, the interaction of Bovine Serum Albumin (BSA) and two types of metal oxide nanoparticles (titanium and tin) have been studied using the intrinsic fluorescence of tryptophan residue from the proteins measured by steady state and time resolved fluorescence techniques. The nanoparticles which were fabricated using a novel synthetic process have average sizes of ~2 nm (SnO2) and ~6 nm (estimated for TiO2) and have very high solubilities in a variety of solvents. The Stern-Volmer plots indicate an effective quenching process by TiO2 nanoparticles whereas SnO2 nanoparticles have a lower quenching efficiency for BSA fluorescence. Static quenching is the major contribution in the overall process which may indicate a high degree of association between protein and nanoparticles. The difference in BSA fluorescence quenching efficiency between the two types of nanoparticles can be explained by the non-covalent interaction differences and the thermal stability of protein-nanoparticle associated species for both materials.

The use of Raman spectroscopy coupled with chemometrics for the rapid identification, characterisation, and quality assessment of complex cell culture media components used for industrial mammalian cell culture was investigated.  Raman spectroscopy offers significant advantages for the analysis of complex, aqueous based materials used in biotechnology because there is no need for sample preparation and water is a weak Raman scatterer.  We demonstrate the efficacy of the method for the routine analysis of dilute aqueous solution of five different chemically defined, commercial media components used in a Chinese Hamster Ovary (CHO) cell manufacturing process for recombinant proteins. 
The chemometric processing of the Raman spectral data is the key factor in developing robust methods.  Here we discuss the optimum methods for eliminating baseline drift, background fluctuations and other instrumentation artefacts to generate reproducible spectral data.  Principal component analysis (PCA) and soft independent modelling of class analogy (SIMCA) were then employed in the development of a robust routine for both identification and quality evaluation of the five different media components.  These methods have the potential to be extremely useful in an industrial context for “in house” sample handling, tracking and quality control.

The quantitative analysis of illicit materials using Raman spectroscopy is of widespread interest for law enforcement and healthcare applications. One of the difficulties faced when analysing illicit mixtures is the fact that the narcotic can be mixed with many different cutting agents. This obviously complicates the development of quantitative analytical methods. In this work we demonstrate some preliminary efforts to try and account for the wide variety of potential cutting agents, by discrimination between the target substance and a wide range of excipients. Near-infrared Raman spectroscopy (785 nm excitation) was employed to analyse 217 samples, a number of them consisting of a target analyte (acetaminophen) mixed with excipients of different concentrations by weight. The excipients used were sugars (maltose, glucose, lactose, sorbitol), inorganic materials (talcum powder, sodium bicarbonate, magnesium sulphate), and food products (caffeine, flour). The spectral data collected was subjected to a number of pre-treatment statistical methods including first derivative and normalisation transformations, to make the data more suitable for analysis. Various methods were then used to discriminate the target analytes, these included Principal Component Analysis (PCA), Principal Component Regression (PCR) and Support Vector Machines.