A survey of the year 2002 commercial optical biosensor literature

We have compiled 819 articles published in the year 2002 that involved commercial optical biosensor technology. The literature demonstrates that the technology's application continues to increase as biosensors are contributing to diverse scientific fields and are used to examine interactions ranging in size from small molecules to whole cells. Also, the variety of available commercial biosensor platforms is increasing and the expertise of users is improving. In this review, we use the literature to focus on the basic types of biosensor experiments, including kinetics, equilibrium analysis, solution competition, active concentration determination and screening. In addition, using examples of particularly well-performed analyses, we illustrate the high information content available in the primary response data and emphasize the impact of including figures in publications to support the results of biosensor analyses.     

Survey of the 1999 surface plasmon resonance biosensor literature

The application of surface plasmon resonance biosensors in life sciences and pharmaceutical research continues to increase. This review provides a comprehensive list of the commercial 1999 SPR biosensor literature and highlights emerging applications that are of general interest to users of the technology. Given the variability in the quality of published biosensor data, we present some general guidelines to help increase confidence in the results reported from biosensor analyses.     

Survey of the year 2005 commercial optical biosensor literature

We identified 1113 articles (103 reviews, 1010 primary research articles) published in 2005 that describe experiments performed using commercially available optical biosensors. While this number of publications is impressive, we find that the quality of the biosensor work in these articles is often pretty poor. It is a little disappointing that there appears to be only a small set of researchers who know how to properly perform, analyze, and present biosensor data. To help focus the field, we spotlight work published by 10 research groups that exemplify the quality of data one should expect to see from a biosensor experiment. Also, in an effort to raise awareness of the common problems in the biosensor field, we provide side-by-side examples of good and bad data sets from the 2005 literature.     

Survey of the year 2006 commercial optical biosensor literature

We identified 1219 articles published in 2006 that described work performed using commercial optical biosensor platforms. It is interesting to witness how the biosensor market is maturing with an increased number of instrument manufacturers offering a wider variety of platforms. However, it is clear from a review of the results presented that the advances in technology are outpacing the skill level of the average biosensor user. While we can track a gradual improvement in the quality of the published work, we clearly have a long way to go before we capitalize on the full potential of biosensor technology. To illustrate what is right with the biosensor literature, we highlight the work of 10 groups who have their eye on the ball. To help out the rest of us who have the lights on but nobody home, we use the literature to address common myths about biosensor technology.     

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.     

Grading the commercial optical biosensor literature—Class of 2008: ‘The Mighty Binders’

Optical biosensor technology continues to be the method of choice for label‐free, real‐time interaction analysis. But when it comes to improving the quality of the biosensor literature, education should be fundamental. Of the 1413 articles published in 2008, less than 30% would pass the requirements for high‐school chemistry. To teach by example, we spotlight 10 papers that illustrate how to implement the technology properly. Then we grade every paper published in 2008 on a scale from A to F and outline what features make a biosensor article fabulous, middling or abysmal. To help improve the quality of published data, we focus on a few experimental, analysis and presentation mistakes that are alarmingly common. With the literature as a guide, we want to ensure that no user is left behind. Copyright © 2009 John Wiley & Sons, Ltd.     

Survey of the year 2004 commercial optical biosensor literature

The year 2004 represents a milestone for the biosensor research community: in this year, over 1000 articles were published describing experiments performed using commercially available systems. The 1038 papers we found represent an approximately 10% increase over the past year and demonstrate that the implementation of biosensors continues to expand at a healthy pace. We evaluated the data presented in each paper and compiled a 'top 10' list. These 10 articles, which we recommend every biosensor user reads, describe well-performed kinetic, equilibrium and qualitative/screening studies, provide comparisons between binding parameters obtained from different biosensor users, as well as from biosensor- and solution-based interaction analyses, and summarize the cutting-edge applications of the technology. We also re-iterate some of the experimental pitfalls that lead to sub-optimal data and over-interpreted results. We are hopeful that the biosensor community, by applying the hints we outline, will obtain data on a par with that presented in the 10 spotlighted articles. This will ensure that the scientific community at large can be confident in the data we report from optical biosensors.     

Survey of the 2009 commercial optical biosensor literature

We took a different approach to reviewing the commercial biosensor literature this year by inviting 22 biosensor users to serve as a review committee. They set the criteria for what to expect in a publication and ultimately decided to use a pass/fail system for selecting which papers to include in this year's reference list. Of the 1514 publications in 2009 that reported using commercially available optical biosensor technology, only 20% passed their cutoff. The most common criticism the reviewers had with the literature was that "the biosensor experiments could have been done better." They selected 10 papers to highlight good experimental technique, data presentation, and unique applications of the technology. This communal review process was educational for everyone involved and one we will not soon forget.     

Survey of the 1998 optical biosensor literature

The utilization of optical biosensors to study molecular interactions continues to expand. In 1998, 384 articles relating to the use of commercial biosensors were published in 130 different journals. While significant strides in new applications and methodology were made, a majority of the biosensor literature is of rather poor quality. Basic information about experimental conditions is often not presented and many publications fail to display the experimental data, bringing into question the credibility of the results. This review provides suggestions on how to collect, analyze and report biosensor data.     

The use of multiple-strain algal sensor chips for the detection and identification of volatile organic compounds

Although biosensors detecting a great variety of toxicants have been developed during the last decades, the simultaneous detection and identification of several targets by one biosensor is not possible in the majority of the biosensor systems. In our study we proved the concept of the detection and identification of two different volatile toxic compounds with a non-selective biochip-based algal biosensor. For that purpose we produced array plate biochips to utilise three membrane-immobilised algal strains of genus Klebsormidium and Chlorella in one biosensor system. A novel IMAGING-PAM chlorophyll fluorometer was applied to measure the impact of volatile organic compounds (VOC) on photosynthesis of chip-immobilized algae in terms of quantum efficiency of electron transport (DeltaF/F'm). Formaldehyde (FA) vapour was detectable with statistical significance in concentrations relevant to human health from 10 ppb to 10 ppm. The biosensor response recorded within minutes was concentration-dependent and reversible. Moreover, vapours of formaldehyde (0.05-1 ppm) and methanol (MeOH) (200-1000 ppm) were significantly identified by the compound-specific response rate as a quotient of the biosensor responses of the respective algal strains. Using the IMAGING-PAM chlorophyll fluorometer, data sampling proved to be highly efficient. Based on our results we conclude that the principle of the algal sensor chip (ASC) suggests further research on the detection and identification of VOCs and other toxic substances in gaseous environment with that biochip system.     

Real-time kinetic studies on the interaction of transforming growth factor alpha with the epidermal growth factor receptor extracellular domain reveal a conformational change model

Transforming growth factor alpha (TGF-alpha), epidermal growth factor (EGF), and related factors mediate their biological effects by binding to the extracellular domain of the EGF receptor, which leads to activation of the receptor's cytoplasmic tyrosine kinase activity. Much remains to be determined, however, about the detailed molecular mechanism involved in this ligand-induced receptor activation. The determination of the binding mechanism and the related thermodynamic and kinetic parameters are of prime importance. To do so, we have used a surface plasmon resonance-based biosensor (the BIAcore) that allows the real-time recording of the interaction between TGF-alpha and the extracellular domain of the EGF receptor. By immobilizing different biotinylated derivatives of TGF-alpha on the sensor chip surface, we demonstrated that the N-terminus of TGF-alpha is not directly involved in receptor binding. By optimizing experimental conditions and interpreting the biosensor results by several data analysis methods, we were able to show that the data do not fit a simple binding model. Through global analysis of the data using a numerical integration method, we tested several binding mechanisms for the TGF-alpha/EGF receptor interaction and found that a conformational change model best fits the biosensor data. Our results, combined with other analyses, strongly support a receptor activation mechanism in which ligand binding results in a conformation-driven exposure of a dimerization site on the receptor.     

Biosensors for determination of total and natural antioxidant capacity of red and white wines: comparison with other spectrophotometric and fluorimetric methods

Research was carried out to experimentally evaluate the antioxidant capacity of several red and white wines using a superoxide dismutase (SOD) biosensor recently developed by the present authors. Measurements were performed by comparing the biosensor response to increasing concentration of the superoxide radical produced in solution by the xanthine/xanthine oxidase system, both in the presence and absence of the test sample.The results were compared with those of two traditional spectrophotometric methods and of a spectrofluorimetric method described in literature.Lastly, also the polyphenol, sulfite and ascorbic acid contents of the different wine samples examined were measured using a tyrosinase biosensor, a sulfite oxidase biosensor and an ascorbate oxidase biosensor, respectively.     

Genetic Programming as a tool for identification of analyte-specificity from complex response patterns using a non-specific whole-cell biosensor

Whole-cell biosensors are mostly non-specific with respect to their detection capabilities for toxicants, and therefore offering an interesting perspective in environmental monitoring. However, to fully employ this feature, a robust classification method needs to be implemented into these sensor systems to allow further identification of detected substances. Substance-specific information can be extracted from signals derived from biosensors harbouring one or multiple biological components. Here, a major task is the identification of substance-specific information among considerable amounts of biosensor data. For this purpose, several approaches make use of statistical methods or machine learning algorithms. Genetic Programming (GP), a heuristic machine learning technique offers several advantages compared to other machine learning approaches and consequently may be a promising tool for biosensor data classification. In the present study, we have evaluated the use of GP for the classification of herbicides and herbicide classes (chemical classes) by analysis of substance-specific patterns derived from a whole-cell multi-species biosensor. We re-analysed data from a previously described array-based biosensor system employing diverse microalgae (Podola and Melkonian, 2005), aiming on the identification of five individual herbicides as well as two herbicide classes. GP analyses were performed using the commercially available GP software 'Discipulus', resulting in classifiers (computer programs) for the binary classification of each individual herbicide or herbicide class. GP-generated classifiers both for individual herbicides and herbicide classes were able to perform a statistically significant identification of herbicides or herbicide classes, respectively. The majority of classifiers were able to perform correct classifications (sensitivity) of about 80-95% of test data sets, whereas the false positive rate (specificity) was lower than 20% for most classifiers. Results suggest that a higher number of data sets may lead to a better classification performance. In the present paper, GP-based classification was combined with a biosensor for the first time. Our results demonstrate GP was able to identify substance-specific information within complex biosensor response patterns and furthermore use this information for successful toxicant classification in unknown samples. This suggests further research to assess perspectives and limitations of this approach in the field of biosensors.     

Split-intein mediated re-assembly of genetically encoded Ca(2+) indicators

While genetically encoded Ca(2+) indicators (GECIs) allow Ca(2+) imaging in model organisms, the gene expression is often under the control of a single promoter that may drive expression beyond, the cell types of interest. To enable more cell-type specific targeting, GECIs can be brought under the, control of the intersecting expression from two promoters. Here, we present the splitting and, reassembly of two representative GECIs (TN-XL and GCaMP2) mediated by the split intein from Nostoc, punctiforme (NpuDnaE). While the split TN-XL biosensor offered ratiometric Ca(2+) imaging, it had a, diminished Ca(2+) response relative to the native TN-XL biosensor. In contrast, the split GCaMP2, biosensor retained similar Ca(2+) response to the native GCaMP2. The split GCaMP2 biosensor was, further targeted to the pharyngeal muscles of Caenorhabditis elegans where Ca(2+) signals from feeding C. elegans, were imaged. Thus, we envision that increased cell-type targetability of GECIs is feasible with two, complementary promoters.     

Au-nanocluster emission based glucose sensing

Fabrication of a glucose biosensor based on Au-cluster emission quenching in the UV region is reported. The glucose biosensor is highly sensitive to β-d-glucose in 2.5-25.0mM range as confirmed from a linear calibration plot between Au-cluster colloid emission intensity as a function of β-d-glucose concentration. The interaction of β-d-glucose with l-cysteine capped Au cluster colloids has been confirmed from their Fourier transformed infrared spectroscopy (FTIR) measurements. It has been found that the biomolecules present in the serum such as ascorbic and uric acids, proteins and peptides do not interfere and affect in glucose estimation as confirmed from their absorption and fluorescence (FL) emission measurements. Practical utility of this sensor based on FL quenching method has been demonstrated by estimating the glucose level in human serum that includes diabetes and the data were found to be comparable or more accurate than those of the pathological data obtained from a local hospital. In addition, this biosensor is useful to detect glucose level over a wide range with sensor response time of the order of nano to picoseconds that is emission lifetime of Au clusters.     

The strategy of signal amplification for ultrasensitive detection of hIgE based on aptamer-modified poly(di-acetylene) supramolecules

Herein, we demonstrate three strategies of signal amplification for ultrasensitive detection of human immunoglobulin E (hIgE) based on poly(di-acetylene) supramolecules. To fabricate the ultrasensitive PDA biosensor, ethylenediamine as an interlinker and aptamer as a receptor were introduced into the chip fabrication process. Using the prepared PDA liposome biosensor, the hIgE could be detected up to below 1.0 ng/ml by a primary response. In order to accomplish more ultrasensitive detection of protein on a PDA biosensor, polyclonal hIgE antibody was employed as an external mechanical force for the inducement of a secondary response. As a result, a PDA liposome biosensor sensitivity as high as 0.01 ng/ml for the target hIgE was obtained, with a sensitivity which is one hundred times of that of the method without signal amplification. These results indicate that the proposed strategies were capable of ultrasensitive quantitative and qualitative analyses of biomolecules without non-specific binding of non-target proteins.     

Comparison of techniques for monitoring antibody fragment production in E. coli fermentation cultures

The use of an optical biosensor for monitoring antibody fragment accumulation following induction in a batch fermentation of recombinant E. coli is compared to the more traditional method of ELISA quantification. Using the biosensor, concentration data can be obtained within minutes of sample addition to the device, compared to an average assay time of 3-4 h for the ELISA. We describe two biosensor assays developed as an alternative to ELISA and compare them with ELISA in the ability to provide quantitative product accumulation profiles during fermentation. Discrepancies in titers recorded by the assays are explained by a combination of differences in product variants detected by each assay and interference from sample contaminants. Method of sample preparation is also shown to be important if accurate concentration data is required. Both biosensor assays are shown to be capable of providing product accumulation profiles comparable to those obtained by ELISA. The use of a rapid extraction technique would allow such data to be obtained during process operation, enabling improved fermentation control and more rapid process development.     

A kinetic study of analyte-receptor binding and dissociation for biosensor applications: a fractal analysis for two different DNA systems

A fractal analysis of DNA binding and dissociation kinetics on biosensor surfaces is presented. The fractal approach provides an attractive, convenient method to model the kinetic data taking into account the effects of surface heterogeneity brought about by ligand immobilization. The fractal technique can be used in conjunction or as an alternate approach to conventional modeling techniques, such as the Langmuir model, saturation model, etc. Examples analyzed include a DNA molecular beacon biosensor and a plasmid DNA-(cationic polymer) interaction biosensor. The molecular beacon example provides some insights into the nature of the surface and how it influences the binding rate coefficients. The DNA-cationic polymer interaction example provides some quantitative results on the binding and dissociation rate coefficients. Data taken from the literature may be modeled, in the case of binding, using a single-fractal analysis or a dual-fractal analysis. The dual-fractal analysis results indicate a change in the binding mechanism as the reaction progresses on the surface. A single-fractal analysis is adequate to model the dissociation kinetics in the example presented. Relationships are presented for the binding rate coefficients as a function of their corresponding fractal dimension, D(f), which is an indication of the degree of heterogeneity that exists on the surface. When analyte-receptor binding is involved, an increase in the heterogeneity of the surface (increase in D(f)) leads to an increase in the binding rate coefficient.     

Expanding the ProteOn XPR36 biosensor into a 36-ligand array expedites protein interaction analysis

Here we demonstrate methods to expand the throughput of the ProteOn XPR36 biosensor allowing for the simultaneous kinetic characterization of several multiplexed formats, such as 36 disparate antibodies targeting the same antigen, and facilitating detailed epitope binning and mapping studies. The kinetic rate constants determined by these methods correlated with those obtained on Biacore 2000 and the absolute parameter values obtained on the ProteOn’s alginate-based GLC chip agreed closer with those from Biacore’s flat C1 chip than Biacore’s dextran-based CM4 chip. Pairwise epitope binning data from the ProteOn 36-ligand array format and those generated on an orthogonal array-based biosensor, the Octet QK384, gave similar results. In an epitope mapping study using biotinylated peptides, all three biosensor platforms were similar in their ability to identify antibodies that bound to linear epitopes. We apply alternative formats of the ProteOn array that enable a significantly higher number of assays to be conducted simultaneously than previously anticipated on this platform.     

A rapidly new-typed detection of norovirus based on F<Subscript>0</Subscript>F<Subscript>1</Subscript>-ATPase molecular motor biosensor

In order to adapt port rapid detection of food borne norovirus, presently we developed a new typed detection method based on F₀F₁-ATPase molecular motor biosensor. A specific probe was encompassed the conservative region of norovirus and F₀F₁-ATPase within chromatophore was constructed as a molecular motor biosensor through the “ε-subunit antibody-streptomycin-biotin-probe” system. Norovirus was captured based on probe-RNA specific binding. Our results demonstrated that the Limit of Quantification (LOQ) is 0.005 ng/mL for NV RNA and also demonstrated that this method possesses specificity and none cross-reaction for food borne virus. What’s more, the experiment used this method could be accomplished in 1 h. We detected 10 samples by using this method and the results were consistent with RT-PCR results. Overall, based on F₀F₁-ATPase molecular motors biosensor system we firstly established a new typed detection method for norovirus detection and demonstrated that this method is sensitive and specific and can be used in the rapid detection for food borne virus.