Optimization of MALDI-TOF MS detection for enhanced sensitivity of affinity-captured proteins spanning a 100 kDa mass range

Analysis of complex biological samples by MALDI-TOF mass spectrometry has been generally limited to the detection of low-mass protein (or protein fragment) peaks. We have extended the mass range of MALDI-TOF high-sensitivity detection by an order of magnitude through the combined optimization of instrument parameters, data processing, and sample preparation procedures for affinity capture. WCX, C3, and IMAC magnetic beads were determined to be complementary and most favorable for broad mass range protein profiling. Key instrument parameters for extending mass range included adjustment of the ADC offset and preamplifier filter values of the TOF detector. Data processing was improved by a combination of constant and quadratic down-sampling, preceded by exponential baseline subtraction, to increase sensitivity of signal peaks. This enhancement in broad mass range detection of protein signals will be of direct benefit in MS expression profiling studies requiring full linear range mass detection.     

A review of detection range testing in aquatic passive acoustic telemetry studies

Passive acoustic telemetry provides an important tool to study the spatial ecology and behaviour of organisms in marine and freshwater systems, but understanding the detection range of acoustic receivers is critical for interpreting acoustic data and establishing receiver spacing to maximize study efficiency. This study presents a comprehensive review of how acoustic detection range has been considered and assessed to date, summarizes important variables to monitor when determining the detection range of a receiver array, and provides recommendations to account for detection range during experimental design, analysis and data interpretation. A total of 378 passive acoustic telemetry studies (1986–2012) were scored against a set of pre-defined criteria to provide a standardized assessment of how well detection range was accounted for, from a maximum possible score of 45. Scores ranged from 0 to 39 (11.1 ± 0.4; mean ± 1 SE). Over the past decade mean scores have been consistently between 6.7 and 12.9 which indicates that detection range has not been adequately considered in most contemporary acoustic telemetry studies. Given the highly variable nature of detection range over space and time, it is necessary to create a culture of detection range testing among the scientific community. For robust telemetry studies it is recommended that consideration of detection range should be given a greater focus within study design, execution and data analysis. To aid array design in new systems, short-term detection range tests should be conducted in the most representative area of the study system prior to deployment. As well, fixed distance sentinel tags should ideally be deployed at a representative receiver site within the array to provide a continuous assessment of detection range and influential environmental parameters should be monitored to facilitate modeling of detection range variability over time. When warranted, data analysis should incorporate modeled variation in detection ranges.     

High sensitivity detection of plasma proteins by multiple reaction monitoring of N-glycosites

The detection and quantification of plasma (serum) proteins at or below the ng/ml concentration range are of critical importance for the discovery and evaluation of new protein biomarkers. This has been achieved either by the development of high sensitivity ELISA or other immunoassays for specific proteins or by the extensive fractionation of the plasma proteome followed by the mass spectrometric analysis of the resulting fractions. The first approach is limited by the high cost and time investment for assay development and the requirement of a validated target. The second, although reasonably comprehensive and unbiased, is limited by sample throughput. Here we describe a method for the detection of plasma proteins at concentrations in the ng/ml or sub-ng/ml range and their accurate quantification over 5 orders of magnitude. The method is based on the selective isolation of N-glycosites from the plasma proteome and the detection and quantification of targeted peptides in a quadrupole linear ion trap instrument operated in the multiple reaction monitoring (MRM) mode. The unprecedented sensitivity of the mass spectrometric analysis of minimally fractionated plasma samples is the result of the significantly reduced sample complexity of the isolated N-glycosites compared with whole plasma proteome digests and the selectivity of the MRM process. Precise quantification was achieved via stable isotope dilution by adding (13)C- and/or (15)N-labeled reference analytes. We also demonstrate the possibility of significantly expanding the number of MRM measurements during one single LC-MS run without compromising sensitivity by including elution time constraints for the targeted transitions, thus allowing quantification of large sets of peptides in a single analysis.     

Improved detection of Candida albicans in a blood-culture model

Human blood reduced the numbers of colony-forming units (cfu) of Candida albicans in a blood-culture model so that the detection time was increased by 12 h. Reduction in cfu was accompanied not by reduction in cell mass but by observable clumping of cultures, which was attributable to a heat-stable serum component. The action of the latter component could be negated if the medium were supplemented by a combination of trypsin, 2-phenyl ethanol, liquoid and Tween 80, when a statistically significant improvement was noted in minimum detection time for C. albicans growing in blood-culture medium.     

Post-translational modification detection using metastable ions in reflector matrix-assisted laser desorption/ionization-time of flight mass spectrometry

In addition to protein identification, characterization of post-translational modifications (PTMs) is an essential task in proteomics. PTMs represent the major reason for the variety of protein isoforms and they can influence protein structure and function. Upon matrix-assisted laser desorption/ionization (MALDI) most post-translationally modified peptides form a fraction of labile molecular ions, which lose PTM-specific residues only after acceleration. Compared to fully accelerated ions these fragment ions are defocused and show in reflector mass spectra reduced resolution. A short time Fourier transform using a Hanning window function now uses this difference in resolution to detect the metastable fragments. Its application over the whole mass range yields frequency distributions and amplitudes as a function of mass, where an increased low frequency proportion is highly indicative for metastable fragments. Applications on the detection of metastable losses originating from carboxamidomethylated cysteines, oxidized methionines, phosphorylated and glycosylated amino acid residues are presented. The metastable loss of mercaptoacetamide detected with this procedure represents a new feature and its integration in search algorithms will improve the specificity of MALDI peptide mass fingerprinting.     

Bird carcass detection from integrated trials at multiple wind farms

It is often necessary to estimate the number of wind turbine collision fatalities to assess impacts to birds following construction of wind farms. Detection of bird carcasses at wind turbines in the field is affected by carcass persistence and searcher detection rate. Integrated detection trials, which integrate carcass persistence and searcher detection trials into the periodic fatality search, have been proposed as an effective method for estimating these parameters. The purpose of our study was to test whether and how environmental factors affect integrated detection trial outcomes at multiple wind farms. We conducted this study at 10 wind farms in various environments of Japan. Binary data on trial outcomes in open versus forested areas served as our response variable in a generalized additive mixed model informed by days into trial, carcass body mass, season, whether snow covered the ground, and precipitation. For both ground cover types, days into trial and body mass were included in all the top models, suggesting that these factors most influenced bird carcass detection probability in integrated trials. The best model in open areas included days into trial, body mass, snow, and precipitation, and the best model in forested areas included days into trial, body mass, snow, precipitation, and season. Values of area under the curve indicated high accuracy of the best model for both ground cover types. The survey design needs to be appropriate to the size of the target species and to the environment in which the impacts will occur, such as the site's seasonality, its ground cover, and whether snow will cover the ground. Frequency of post-construction fatality monitoring should also be set cautiously, especially at wind farms located on small-bird migration routes, at wind farms in open areas, in areas with snow-covered ground in winter, or in forested areas during spring and summer because detection probabilities decline fastest under such conditions.     

Emerging nanoproteomics approaches for disease biomarker detection: a current perspective

Availability of genome sequence of human and different pathogens has advanced proteomics research for various clinical applications. One of the prime goals of proteomics is identification and characterization of biomarkers for cancer and other fatal human diseases to aid an early diagnosis and monitor disease progression. However, rapid detection of low abundance biomarkers from the complex biological samples under clinically relevant conditions is extremely difficult, and it requires the development of ultrasensitive, robust and high-throughput technological platform. In order to overcome several technical limitations associated with sensitivity, dynamic range, detection time and multiplexing, proteomics has started integrating several emerging disciplines such as nanotechnology, which has led to the development of a novel analytical platform known as 'nanoproteomics'. Among the diverse classes of nanomaterials, the quantum dots, gold nanoparticles, carbon nanotubes and silicon nanowires are the most promising candidates for diagnostic applications. Nanoproteomics offers several advantages such as ultralow detection, short assay time, high-throughput capability and low sample consumption. In this article, we have discussed the application of nanoproteomics for biomarker discovery in various diseases with special emphasis on various types of cancer. Furthermore, we have discussed the prospects, merits and limitations of nanoproteomics.     

P450-based porous silicon biosensor for arachidonic acid detection

A porous silicon biosensor based on P450 enzyme for arachidonic acid detection was developed. A new transduction method is presented with a simultaneous measurement of refractive index and fluorescence intensity changes when the analyte is binding to an enzyme on the porous silicon surface. A fluorophore bound to a cysteine residue in an allosteric position of the haem domain (BMP) of cytochrome P450 BM3 enhances its fluorescence intensity upon interaction with its substrate arachidonic acid, involved in diseases such as Alzheimer's, liver cancer and cellular inflammation processes. BMP has been anchored on porous silicon surface and the new transduction method has been successfully exploited to develop a biosensor for arachidonic acid, reaching a detection limit of 10 μM arachidonic acid in a dynamic range of 10-200 μM. Moreover, the change of the refractive index has been also monitored at the same time, displaying a higher detection limit of 30 μM. Preliminary test were also conducted in plasma proving the high specificity and selectivity of the sensor even in presence of interferents in the range of 50-100 μM. Here we suggest these two detection systems could be used simultaneously to increase the accuracy and the dynamic range of the sensor avoiding a false positive response.     

Quantitative proteomics: assessing the spectrum of in-gel protein detection methods

Proteomics research relies heavily on visualization methods for detection of proteins separated by polyacrylamide gel electrophoresis. Commonly used staining approaches involve colorimetric dyes such as Coomassie Brilliant Blue, fluorescent dyes including Sypro Ruby, newly developed reactive fluorophores, as well as a plethora of others. The most desired characteristic in selecting one stain over another is sensitivity, but this is far from the only important parameter. This review evaluates protein detection methods in terms of their quantitative attributes, including limit of detection (i.e., sensitivity), linear dynamic range, inter-protein variability, capacity for spot detection after 2D gel electrophoresis, and compatibility with subsequent mass spectrometric analyses. Unfortunately, many of these quantitative criteria are not routinely or consistently addressed by most of the studies published to date. We would urge more rigorous routine characterization of stains and detection methodologies as a critical approach to systematically improving these critically important tools for quantitative proteomics. In addition, substantial improvements in detection technology, particularly over the last decade or so, emphasize the need to consider renewed characterization of existing stains; the quantitative stains we need, or at least the chemistries required for their future development, may well already exist.     

Label-free detection methods for protein microarrays

With the growth of the "-omics" such as functional genomics and proteomics, one of the foremost challenges in biotechnologies has become the development of novel methods to monitor biological process and acquire the information of biomolecular interactions in a systematic manner. To fully understand the roles of newly discovered genes or proteins, it is necessary to elucidate the functions of these molecules in their interaction network. Microarray technology is becoming the method of choice for such a task. Although protein microarray can provide a high throughput analytical platform for protein profiling and protein-protein interaction, most of the current reports are limited to labeled detection using fluorescence or radioisotope techniques. These limitations deflate the potential of the method and prevent the technology from being adapted in a broader range of proteomics applications. In recent years, label-free analytical approaches have gone through intensified development and have been coupled successfully with protein microarray. In many examples of label-free study, the microarray has not only offered the high throughput detection in real time, but also provided kinetics information as well as in situ identification. This article reviews the most significant label-free detection methods for microarray technology, including surface plasmon resonance imaging, atomic force microscope, electrochemical impedance spectroscopy and MS and their applications in proteomics research.     

Highly sensitive feature detection for high resolution LC/MS

Background  

Liquid chromatography coupled to mass spectrometry (LC/MS) is an important analytical technology for e.g. metabolomics experiments. Determining the boundaries, centres and intensities of the two-dimensional signals in the LC/MS raw data is called feature detection. For the subsequent analysis of complex samples such as plant extracts, which may contain hundreds of compounds, corresponding to thousands of features – a reliable feature detection is mandatory.     

The effects of spatially heterogeneous prey distributions on detection patterns in foraging seabirds

Many attempts to relate animal foraging patterns to landscape heterogeneity are focused on the analysis of foragers movements. Resource detection patterns in space and time are not commonly studied, yet they are tightly coupled to landscape properties and add relevant information on foraging behavior. By exploring simple foraging models in unpredictable environments we show that the distribution of intervals between detected prey (detection statistics) is mostly determined by the spatial structure of the prey field and essentially distinct from predator displacement statistics. Detections are expected to be Poissonian in uniform random environments for markedly different foraging movements (e.g. Lévy and ballistic). This prediction is supported by data on the time intervals between diving events on short-range foraging seabirds such as the thick-billed murre (Uria lomvia). However, Poissonian detection statistics is not observed in long-range seabirds such as the wandering albatross (Diomedea exulans) due to the fractal nature of the prey field, covering a wide range of spatial scales. For this scenario, models of fractal prey fields induce non-Poissonian patterns of detection in good agreement with two albatross data sets. We find that the specific shape of the distribution of time intervals between prey detection is mainly driven by meso and submeso-scale landscape structures and depends little on the forager strategy or behavioral responses.     

Automated tracking of wild hummingbird mass and energetics over multiple time scales using radio frequency identification (RFID) technology

We examined the feasibility of automating the collection of hummingbird mass data facilitated by low‐cost, low‐power radio frequency identification (RFID) technology. In a field study in southern Ontario, wild hummingbirds were captured, subcutaneously implanted with passive integrated transponder (PIT) tags, and released over a three‐year period. Tagged hummingbirds were detected at specially designed feeder stations outfitted with low‐cost, low‐power RFID readers coupled with a perch secured to a digital balance. When tagged birds visited the feeder, transponder detection initiated the recording of the perched hummingbird's mass at regular intervals continuing as long as the bird remained. This permitted a nearly continuous record of mass during each visit. Mass data collected from tagged hummingbirds showed consistent trends at multiple temporal scales: the individual feeder visit, single days, and even whole seasons. These results further confirm that RFID technology is safe for use in the smallest birds. The effective detection range is a function of RFID reader power, antenna, and tag size. Yet, we find that careful arrangement of feeders and detectors allows for reliable detection even when detection range is low. When coupled with additional technologies, such as a precision electronic balance, this approach can yield robust serial measures of physiological parameters such as mass, an indicator of energy balance over time.     

Negative mode nanostructure-initiator mass spectrometry for detection of phosphorylated metabolites

The chemical complexity of the metabolome requires the development of new detection methods to enlarge the range of compounds detectable in a biological sample. Recently, a novel matrix-free laser desorption/ionization method called nanostructure-initiator mass spectrometry (NIMS) [Northen et al., Nature 449(7165):1033–1036, 2007] was reported. Here we investigate NIMS in negative ion mode for the detection of endogenous metabolites, namely small phosphorylated molecules. 3-Aminopropyldimethylethoxysilane was found to be suitable as initiator for the analytes studied and a limit of detection in the tens of femtomoles was reached. The detection of different endogenous cell metabolites in a yeast cell extract is demonstrated.     

Highly sensitive detection of E2 activity in ubiquitination using an artificial RING finger

The ubiquitin‐conjugating (E2) enzymes of protein ubiquitination are associated with various diseases such as leukemia, lung cancer, and breast cancer. Rapid and accurate detection of E2 enzymatic activities remains poor. Here, we described the detection of E2 activity on a signal accumulation ISFET biosensor (AMIS sensor) using an artificial RING finger (ARF). The use of ARF enables the simplified detection of E2 activity without a substrate. The high‐sensitivity quantitative detection of E2 activities was demonstrated via real‐time monitoring over a response range of femtomolar to micromolar concentrations. Furthermore, the monitoring of E2 activities was successfully achieved using human acute promyelocytic leukemia cells following treatment with the anticancer drug bortezomib, which allowed the assessment of the pathological conditions. This strategy is extremely simple and convenient, and the present detection could be widely applied to specific E2s for various types of cancers. Copyright © 2017 European Peptide Society and John Wiley & Sons, Ltd.     

Small object detection neurons in female hoverflies

While predators such as dragonflies are dependent on visual detection of moving prey, social interactions make conspecific detection equally important for many non-predatory insects. Specialized 'acute zones' associated with target detection have evolved in several insect groups and are a prominent male-specific feature in many dipteran flies. The physiology of target selective neurons associated with these specialized eye regions has previously been described only from male flies. We show here that female hoverflies (Eristalis tenax) have several classes of neurons within the third optic ganglion (lobula) capable of detecting moving objects smaller than 1 degrees . These neurons have frontal receptive fields covering a large part of the ipsilateral world and are tuned to a broad range of target speeds and sizes. This could make them suitable for detecting targets under a range of natural conditions such as required during predator avoidance or conspecific interactions.     

Determination of lactate dehydrogenase in human erythrocytes by capillary electrophoresis with electrochemical detection

Capillary electrophoresis (CE) was employed to analyze lactate dehydrogenase (LDH) in human erythrocytes using an amperometric detector with a carbon fiber micro-disk bundle electrode. LDH activity was measured by determining the amount of NADH generated by LDH through a enzyme-catalyzed reaction between NAD(+) and lithium lactate. The factors influencing the enzyme-catalyzed reaction, separation and detection were examined and optimized. The following conditions were suitable for the determination of LDH: running buffer, 5.0 x 10(-2)mol/l Tris-HCl (pH 7.5); separation voltage, 20.0 kV; detection potential, 1.00 V (versus saturated calomel electrode (SCE)). The conditions of enzyme-catalyzed reaction were: reaction buffer, 5.0 x 10(-2)mol/l Tris-HCl (pH 9.3); substrates, 5.0 x 10(-2)mol/l lithium lactate and 5.0 x 10(-3)mol/l NAD(+); reaction time, 10 min. The concentration limit of detection (LOD) of the method was 0.017 U/ml at a signal-to-noise (S/N) ratio of 3, which corresponded to 1.10 x 10(-10)mol/l, and the mass LOD was 2 x 10(-20)mol. The linear dynamic range was 0.039-4.65 U/ml for the injection voltage of 5.0 kV and injection time of 10s. The relative standard deviation (R.S.D.) was 0.85% for the migration time and 1.8% for the electrophoretic peak area. The method was applied to determine LDH in human erythrocytes. The recovery of the method was between 98 and 101%.     

铜绿假单胞菌的MALDI-TOF-MS检测方法的建立

目的 建立利用基质辅助激光解吸电离飞行时间质谱仪( MALDI-TOF-MS)对铜绿假单胞菌的快速检测方法.方法 通过MALDI-TOF-MS法对铜绿假单胞菌进行检测分析,并与生化鉴定方法相比较.结果 MALDI-TOF-MS对铜绿假单胞菌的检测后得到肽指纹图片及相关质谱数据,建立MALDI-TOF-MS对铜绿假单胞菌的快速检测方法.结论 MALDI-TOF-MS方法检测铜绿假单胞菌准确快速、操作简单等特点,可发展成为食品检验铜绿假单胞菌的重要(辅助)工具.