Rapid characterization of complex viscous samples at molecular levels by neutral desorption extractive electrospray ionization mass spectrometry

In this protocol, the sample (which could be a bulk or heterogeneous fluid, or a greasy surface) is treated with a neutral desorption (ND) sampling gas beam, and the resulting analyte mixtures are directly characterized by extractive electrospray ionization mass spectrometry (EESI-MS). The ND device can be specifically constructed such that the sampling gas beam is bubbled through the liquid sample (microjet sampling) or directed to impact the sample surface (e.g., for the analysis of a material like cheese). The ND-EESI-MS analysis process requires no sample pretreatment because it can tolerate an extremely complex matrix. ND-EESI-MS allows real-time, online chemical profiling of highly viscous samples under ambient conditions. Both volatile and nonvolatile analytes from viscous samples can easily be detected and quantified by ND-EESI-MS, thereby providing an MS-based analytical platform for multiple disciplines (e.g., for the food industry, for drug discovery, and for the biological and life sciences). Here we describe the ND-EESI-MS protocol for viscous sample analysis, including the experimental design, equipment setup, reagent preparation, data acquisition and analysis steps. The data collection process takes <1 min per sample, although the time required for the whole procedure, which largely depends on the experimental preparation processes, might be considerably longer.     

Proteomic analysis of novel marine bacteria using MALDI and ESI mass spectrometry.

The objective of this study was to develop a mass spectrometric protocol to search for proteins related to phototrophy in marine bacteria. The genes that produce proteins involved in conversion of light into energy have been detected by cloning-sequencing from some of these bacteria, but it was previously unknown if these proteins were actually expressed. Attaining this study's goal was complicated by the fact that the samples consisted of miniscule cell pellets, which yielded small amounts of very complex mixtures of proteins. Sample preparation and analysis were tailored to optimize the probability of detecting the proteins of interest. It has been reported that using both matrix-assisted laser desorption/ionization (MALDI) and electrospray ionization (ESI) to analyze a mixture of peptides leads to the identification of more peptides that either technique alone. In order to exploit this complementarity between ESI and MALDI for proteomic analysis, samples were analyzed using both ionization techniques. With correct choices in sample preparation and ionization process, biologically relevant proteins can be identified out of small samples containing whole proteomes.     

Evaluation of the Biological Sampling Kit (BiSKit) for large-area surface sampling

Current surface sampling methods for microbial contaminants are designed to sample small areas and utilize culture analysis. The total number of microbes recovered is low because a small area is sampled, making detection of a potential pathogen more difficult. Furthermore, sampling of small areas requires a greater number of samples to be collected, which delays the reporting of results, taxes laboratory resources and staffing, and increases analysis costs. A new biological surface sampling method, the Biological Sampling Kit (BiSKit), designed to sample large areas and to be compatible with testing with a variety of technologies, including PCR and immunoassay, was evaluated and compared to other surface sampling strategies. In experimental room trials, wood laminate and metal surfaces were contaminated by aerosolization of Bacillus atrophaeus spores, a simulant for Bacillus anthracis, into the room, followed by settling of the spores onto the test surfaces. The surfaces were sampled with the BiSKit, a cotton-based swab, and a foam-based swab. Samples were analyzed by culturing, quantitative PCR, and immunological assays. The results showed that the large surface area (1 m2) sampled with the BiSKit resulted in concentrations of B. atrophaeus in samples that were up to 10-fold higher than the concentrations obtained with the other methods tested. A comparison of wet and dry sampling with the BiSKit indicated that dry sampling was more efficient (efficiency, 18.4%) than wet sampling (efficiency, 11.3%). The sensitivities of detection of B. atrophaeus on metal surfaces were 42 +/- 5.8 CFU/m2 for wet sampling and 100.5 +/- 10.2 CFU/m2 for dry sampling. These results demonstrate that the use of a sampling device capable of sampling larger areas results in higher sensitivity than that obtained with currently available methods and has the advantage of sampling larger areas, thus requiring collection of fewer samples per site.     

A statistical sampling algorithm for RNA secondary structure prediction

An RNA molecule, particularly a long-chain mRNA, may exist as a population of structures. Further more, multiple structures have been demonstrated to play important functional roles. Thus, a representation of the ensemble of probable structures is of interest. We present a statistical algorithm to sample rigorously and exactly from the Boltzmann ensemble of secondary structures. The forward step of the algorithm computes the equilibrium partition functions of RNA secondary structures with recent thermodynamic parameters. Using conditional probabilities computed with the partition functions in a recursive sampling process, the backward step of the algorithm quickly generates a statistically representative sample of structures. With cubic run time for the forward step, quadratic run time in the worst case for the sampling step, and quadratic storage, the algorithm is efficient for broad applicability. We demonstrate that, by classifying sampled structures, the algorithm enables a statistical delineation and representation of the Boltzmann ensemble. Applications of the algorithm show that alternative biological structures are revealed through sampling. Statistical sampling provides a means to estimate the probability of any structural motif, with or without constraints. For example, the algorithm enables probability profiling of single-stranded regions in RNA secondary structure. Probability profiling for specific loop types is also illustrated. By overlaying probability profiles, a mutual accessibility plot can be displayed for predicting RNA:RNA interactions. Boltzmann probability-weighted density of states and free energy distributions of sampled structures can be readily computed. We show that a sample of moderate size from the ensemble of an enormous number of possible structures is sufficient to guarantee statistical reproducibility in the estimates of typical sampling statistics. Our applications suggest that the sampling algorithm may be well suited to prediction of mRNA structure and target accessibility. The algorithm is applicable to the rational design of small interfering RNAs (siRNAs), antisense oligonucleotides, and trans-cleaving ribozymes in gene knock-down studies.     

Ambient molecular imaging by desorption electrospray ionization mass spectrometry

Desorption electrospray ionization (DESI) allows the direct analysis of ordinary objects or pre-processed samples under ambient conditions. Among other applications, DESI is used to identify and record spatial distributions of lipids and drug molecules in biological tissue sections. This technique does not require sample preparation other than production of microtome tissue slices and does not involve the use of ionization matrices. This greatly simplifies the procedure and prevents the redistribution of analytes during matrix deposition. Images are obtained by continuously moving the sample relative to the DESI sprayer and the inlet of the mass spectrometer. The timing of the protocol depends on the size of the surface to be analyzed and on the desired resolution. Analysis of organ tissue slices at 250 microm resolution typically takes between 30 min and 2 h.     

Bayesian Inference of Sampled Ancestor Trees for Epidemiology and Fossil Calibration

Phylogenetic analyses which include fossils or molecular sequences that are sampled through time require models that allow one sample to be a direct ancestor of another sample. As previously available phylogenetic inference tools assume that all samples are tips, they do not allow for this possibility. We have developed and implemented a Bayesian Markov Chain Monte Carlo (MCMC) algorithm to infer what we call sampled ancestor trees, that is, trees in which sampled individuals can be direct ancestors of other sampled individuals. We use a family of birth-death models where individuals may remain in the tree process after sampling, in particular we extend the birth-death skyline model [Stadler et al., 2013] to sampled ancestor trees. This method allows the detection of sampled ancestors as well as estimation of the probability that an individual will be removed from the process when it is sampled. We show that even if sampled ancestors are not of specific interest in an analysis, failing to account for them leads to significant bias in parameter estimates. We also show that sampled ancestor birth-death models where every sample comes from a different time point are non-identifiable and thus require one parameter to be known in order to infer other parameters. We apply our phylogenetic inference accounting for sampled ancestors to epidemiological data, where the possibility of sampled ancestors enables us to identify individuals that infected other individuals after being sampled and to infer fundamental epidemiological parameters. We also apply the method to infer divergence times and diversification rates when fossils are included along with extant species samples, so that fossilisation events are modelled as a part of the tree branching process. Such modelling has many advantages as argued in the literature. The sampler is available as an open-source BEAST2 package (https://github.com/CompEvol/sampled-ancestors).     

Isolation of N-terminal protein sequence tags from cyanogen bromide cleaved proteins as a novel approach to investigate hydrophobic proteins

A novel method for the isolation of protein sequence tags to identify proteins in a complex mixture of hydrophobic proteins is described. The PST (Protein Sequence Tag) technology deals with the isolation and MS/MS based identification of one N-terminal peptide from each polypeptide fragment generated by cyanogen bromide cleavage of a mixture of proteins. PST sampling takes place after sub-cellular fractionation of a complex protein mixture to give enrichment of mitochondrial proteins. The method presented here combines effective sample preparation with a novel peptide isolation protocol involving chemical and enzymatic cleavage of proteins coupled to chemical labeling and selective capture procedures. The overall process has been very successful for the analysis of complex mixtures of hydrophobic proteins, particularly membrane proteins. This method substantially reduces the complexity of a protein digest by "sampling" the peptides present in the digest. The sampled digest is amenable to analysis by liquid chromatography tandem mass spectrometry (LC-MS/MS). Methods of "sampling" protein digests have great value' if they can provide sufficient information to identify substantially all of the proteins in the sample while reducing the complexity of the sample to maximize the efficient usage of LC-MS/MS capacity. The validity of the process is demonstrated for mitochondrial samples from S. cerevisiae. The proteins identified by the PST technology are compared to the proteins identified by the conventional technology 2-D gel electrophoresis as a control.     

Large variation of suction sampling efficiency depending on arthropod groups,species traits,and habitat properties

Suction sampling is widely used to estimate arthropod abundance and diversity. To test the reliability of abundance data derived from suction sampling, we examined sampling efficiency across a wide range of arthropod groups and tested for effects of species traits, vegetation density, and differences between sites. Suction sampling efficiency was quantified by vacuuming an enclosed meadow area and subsequent removal of the turf, which was treated with heat extraction to collect the remaining arthropods. We obtained 250 pairs of suction and turf samples from seven grasslands with variable vegetation density. High suction sampling efficiencies between 49 and 86% were obtained for Auchenorrhyncha, Heteroptera, Araneida, Curculionoidea, Hymenoptera, and Diptera. In contrast, efficiencies were below 30% for Aphidae, Thysanoptera, Staphylinidae and other Coleoptera, and for soil arthropods such as Collembola, Isopoda, Diplopoda, and Formicidae. Efficiency varied significantly among habitats (sites) for most groups, often more than two‐fold. Surprisingly, sampling efficiency for Hymenoptera, Diplopoda, and Collembola increased with vegetation density, probably because aboveground activity of these taxa was higher in dense vegetation. Suction sampling was nearly twice as efficient for spiders living in the vegetation than for spiders living near the soil surface, and cursorial and large‐bodied spider species were more efficiently sampled than web‐builders and small species. Depending on the sampling effort, suction sampling missed between 49% (one sample) and 31% (250 samples) of the spider species present. Suction sampling efficiency varied more strongly among sites and among arthropod groups than previously recognized. Abundance data derived from suction sampling are strongly underestimated, especially for arthropods living near the soil surface. Thus, comparisons of abundance and diversity between sites should be restricted to vegetation‐dwelling species of the most efficiently sampled groups. The positive relationship of sampling efficiency with vegetation density demonstrates that variation in efficiency is mediated by arthropod behaviour.     

Cost analysis of various low pathogenic avian influenza surveillance systems in the Dutch egg layer sector

Background

As low pathogenic avian influenza viruses can mutate into high pathogenic viruses the Dutch poultry sector implemented a surveillance system for low pathogenic avian influenza (LPAI) based on blood samples. It has been suggested that egg yolk samples could be sampled instead of blood samples to survey egg layer farms. To support future decision making about AI surveillance economic criteria are important. Therefore a cost analysis is performed on systems that use either blood or eggs as sampled material.

Methodology/Principal Findings

The effectiveness of surveillance using egg or blood samples was evaluated using scenario tree models. Then an economic model was developed that calculates the total costs for eight surveillance systems that have equal effectiveness. The model considers costs for sampling, sample preparation, sample transport, testing, communication of test results and for the confirmation test on false positive results. The surveillance systems varied in sampled material (eggs or blood), sampling location (farm or packing station) and location of sample preparation (laboratory or packing station). It is shown that a hypothetical system in which eggs are sampled at the packing station and samples prepared in a laboratory had the lowest total costs (i.e. € 273,393) a year. Compared to this a hypothetical system in which eggs are sampled at the farm and samples prepared at a laboratory, and the currently implemented system in which blood is sampled at the farm and samples prepared at a laboratory have 6% and 39% higher costs respectively.

Conclusions/Significance

This study shows that surveillance for avian influenza on egg yolk samples can be done at lower costs than surveillance based on blood samples. The model can be used in future comparison of surveillance systems for different pathogens and hazards.     

Analysis of Volatile and Oxidation Sensitive Compounds Using a Cold Inlet System and Electron Impact Mass Spectrometry

This video presents a protocol for the mass spectrometrical analysis of volatile and oxidation sensitive compounds using electron impact ionization. The analysis of volatile and oxidation sensitive compounds by mass spectrometry is not easily achieved, as all state-of-the-art mass spectrometric methods require at least one sample preparation step, e.g., dissolution and dilution of the analyte (electrospray ionization), co-crystallization of the analyte with a matrix compound (matrix-assisted laser desorption/ionization), or transfer of the prepared samples into the ionization source of the mass spectrometer, to be conducted under atmospheric conditions. Here, the use of a sample inlet system is described which enables the analysis of volatile metal organyls, silanes, and phosphanes using a sector field mass spectrometer equipped with an electron impact ionization source. All sample preparation steps and the sample introduction into the ion source of the mass spectrometer take place either under air-free conditions or under vacuum, enabling the analysis of compounds highly susceptible to oxidation. The presented technique is especially of interest for inorganic chemists, working with metal organyls, silanes, or phosphanes, which have to be handled using inert conditions, such as the Schlenk technique. The principle of operation is presented in this video.     

Rapid sample processing and fast gas chromatography for identification of bacteria by fatty acid analysis

A commercially available system for microbial identification by fatty acid analysis (Microbial Identification System (MIS), MIDI, Newark, DE, USA) requires a four-step sample derivatization procedure in screw-cap test tubes. By using glass tubes in a 96-well format with multichannel pipetting, the time required for sample preparation can be greatly reduced. The standard gas chromatography column, 25 m long by 0.20 mm ID, is replaced with a 10 m long by 0.10 mm ID column, reducing the gas chromatography run time to one third of the standard time. Either or both of these procedures can be easily implemented in any laboratory using the MIDI system, resulting in faster identifications and higher sample throughput.     

Measurement uncertainty from physical sample preparation of moss samples: Estimation of mechanical cleaning vs. rinsing

Next to sampling, the physical sample preparation step is a second large source of uncertainty. To assess the level of uncertainty from sampling, sample preparation and analysis of moss material, 27 combined and duplicate samples of moss species Pleurozium schreberi (Brid.) Mitt were collected and prepared for analysis using two different treatment methods After sampling had been done, samples were dried at an ambient temperature and then each primary and duplicate sample was divided into two sub-samples for preparation. The first sub-sample was manually cleaned whereas the second one was triple rinsed with deionized water and left to dry. Subsequently, the samples were milled and digested in a close microwave system with 8 mL of HNO₃ (1:1) and 1 mL of 30% H₂O₂. In all samples Cu, Fe and Zn were determined using GFAAS and FAAS techniques. Each sample was analyzed twice. Sampling, sample preparation and analytical uncertainty were calculated using ANOVA, RANOVA, modified RANOVA and range statistics methods. Sampling and sample preparation uncertainty varied from 3.8 to 19.8% and from 3.6 to 11.2%, respectively. For all the elements examined analytical uncertainty was below 1.1%. The comparison of element concentrations in manually cleaned and rinsed samples showed that rinsed samples were enriched in Cu and Zn, as opposed to manually cleaned that in turn displayed raised levels of Fe. However, except for Zn, these differences were not statistically significant.     

Bootstrap confidence intervals for adaptive cluster sampling

Consider a collection of spatially clustered objects where the clusters are geographically rare. Of interest is estimation of the total number of objects on the site from a sample of plots of equal size. Under these spatial conditions, adaptive cluster sampling of plots is generally useful in improving efficiency in estimation over simple random sampling without replacement (SRSWOR). In adaptive cluster sampling, when a sampled plot meets some predefined condition, neighboring plots are added to the sample. When populations are rare and clustered, the usual unbiased estimators based on small samples are often highly skewed and discrete in distribution. Thus, confidence intervals based on asymptotic normal theory may not be appropriate. We investigated several nonparametric bootstrap methods for constructing confidence intervals under adaptive cluster sampling. To perform bootstrapping, we transformed the initial sample in order to include the information from the adaptive portion of the sample yet maintain a fixed sample size. In general, coverages of bootstrap percentile methods were closer to nominal coverage than the normal approximation.     

Direct cocktail analysis of drug discovery compounds in pooled plasma samples using liquid chromatography-tandem mass spectrometry

Direct plasma injection technology coupled with a LC-MS/MS assay provides fast and straightforward method development and greatly reduces the time for the tedious sample preparation procedures. In this work, a simple and sensitive bioanalytical method based on direct plasma injection using a single column high-performance liquid chromatography (HPLC) and tandem mass spectrometry (MS/MS) was developed for direct cocktail analysis of double-pooled mouse plasma samples for the quantitative determination of small molecules. The overall goal was to improve the throughput of the rapid pharmacokinetic (PK) screening process for early drug discovery candidates. Each pooled plasma sample was diluted with working solution containing internal standard and then directly injected into a polymer-coated mixed-function column for sample clean-up, enrichment and chromatographic separation. The apparent on-column recovery of six drug candidates in mouse plasma samples was greater than 90%. The single HPLC column was linked to either an atmospheric pressure chemical ionization (APCI) or electrospray ionization (ESI) source as a part of MS/MS system. The total run cycle time using single column direct injection methods can be achieved within 4 min per sample. The analytical results obtained by the described direct injection methods were comparable with those obtained by semi-automated protein precipitation methods within +/- 15%. The advantages and challenges of using direct single column LC-MS/MS methods with two ionization sources in combination of sample pooling technique are discussed.     

Interpreting recruitment limitation in forests

Studies of tree recruitment are many, but they provide few general insights into the role of recruitment limitation for population dynamics. That role depends on the vital rates (transitions) from seed production to sapling stages and on overall population growth. To determine the state of our understanding of recruitment limitation we examined how well we can estimate parameters corresponding to these vital rates. Our two-part analysis consists of (1) a survey of published literature to determine the spatial and temporal scale of sampling that is basis for parameter estimates, and (2) an analysis of extensive data sets to evaluate sampling intensity found in the literature. We find that published studies focus on fine spatial scales, emphasizing large numbers of small samples within a single stand, and tend not to sample multiple stands or variability across landscapes. Where multiple stands are sampled, sampling is often inconsistent. Sampling of seed rain, seed banks, and seedlings typically span <1 yr and rarely last 5 yr. Most studies of seeding establishment and growth consider effects of a single variable and a single life history stage. By examining how parameter estimates are affected by the spatial and temporal extent of sampling we find that few published studies are sufficiently extensive to capture the variability in recruitment stages. Early recruitment stages are especially variable and require samples across multiple years and multiple stands. Ironically, the longest duration data sets are used to estimate mortality rates, which are less variable (in time) than are early life history stages. Because variables that affect recruitment rates interact, studies of these interactions are needed to assess their full impacts. We conclude that greater attention to spatially extensive and longer duration sampling for early life history stages is needed to assess the role of recruitment limitation in forests.     

Processing of ND NMR spectra sampled in polar coordinates: a simple Fourier transform instead of a reconstruction

In order to reduce the acquisition time of multidimensional NMR spectra of biological macromolecules, projected spectra (or in other words, spectra sampled in polar coordinates) can be used. Their standard processing involves a regular FFT of the projections followed by a reconstruction, i.e. a non-linear process. In this communication, we show that a 2D discrete Fourier transform can be implemented in polar coordinates to obtain directly a frequency domain spectrum. Aliasing due to local violations of the Nyquist sampling theorem gives rise to base line ridges but the peak line-shapes are not distorted as in most reconstruction methods. The sampling scheme is not linear and the data points in the time domain should thus be weighted accordingly in the polar FT; however, artifacts can be reduced by additional data weighting of the undersampled regions. This processing does not require any parameter tuning and is straightforward to use. The algorithm written for polar sampling can be adapted to any sampling scheme and will permit to investigate better compromises in terms of experimental time and lack of artifacts.     

Analysis of Polymerase Chain Reaction-Amplified DNA Products by Mass Spectrometry Using Matrix-Assisted Laser Desorption and Electrospray: Current Status

Recent advances in molecular biology are making it possible to diagnose genetic diseases and identify pathogens through the analysis of DNA. As clinical applications for molecular diagnosis increase, rapid, reliable methods for determination of DNA size will be needed. Mass spectrometry offers the potential of analyzing amplified DNA quickly and reliably, without the need for gel-based separation and sample labeling steps that are conventionally employed. Both electrospray ionization and matrix-assisted laser desorption/ionization have been evaluated for the size analysis of DNA using both synthetic oligonucleotides and PCR-amplified samples corresponding to bases 1626 to 1701 of the cystic fibrosis transmembrane conductance regulator gene. Both technologies have been demonstrated to have mass range and sensitivity required for the analysis of PCR-amplified DNA in this size range using minimal sample preparation. Steps required to incorporate either ionization technique into a reliable analytical scheme for the rapid, routine analysis of DNA are outlined.     

Hay-bait traps are a useful tool for sampling of soil dwelling millipedes and centipedes

Some species of centipedes and millipedes inhabit upper soil layers exclusively and are not recorded by pitfall trapping. Because of their sensitivity to soil conditions, they can be sampled quantitatively for evaluation of soil conditions. Soil samples are heavy to transport and their processing is time consuming, and such sampling leads to disturbance of the soil surface which land-owners do not like. We evaluated the use of hay-bait traps to sample soil dwelling millipedes and centipedes. The effectiveness of this method was found to be similar to the effectiveness of soil sampling. Hay-bait traps installed for 8–10 weeks can substitute for direct soil sampling in ecological and inventory studies.     

Improving species occupancy estimation when sampling violates the closure assumption

Site occupancy models that account for imperfect detection of species are increasingly utilized in ecological research and wildlife monitoring. Occupancy models require replicate surveys to estimate detection probability over a time period where the occupancy status at sampled sites is assumed closed. Unlike mark–recapture models, few studies have examined how violations of closure can bias occupancy estimates. Our study design allowed us to differentiate among two processes that violate the closure assumption during a sampling season: 1) repeated destructive sampling events that result in either short‐ or long‐term site avoidance by the target species and 2) sampling occurring over a time period during which non‐random movements of the target species result in variable occupancy status. We used dynamic occupancy models to quantify the potential bias in occupancy estimation associated with these processes for a terrestrial salamander system. Our results provide strong evidence of a systematic decrease in salamander occupancy within a field season. Chronic disturbance due to repeated searches of natural cover objects accelerated natural declines in species occurrence on the forest surface as summer progressed. We also observed a strong but temporary disturbance effect on salamander detection probability associated with repeated sampling within a 24‐h. period. We generalized our findings by conducting a simulation to evaluate how violations of closure can bias occupancy estimates when local extinction occurs within a sampling season. Our simulation study revealed general sensitivity of estimates from single‐season occupancy models to violations of closure, with the strength and direction of bias varying between scenarios. Bias was minimal when extinction proba bility or the number of sample occasions was relatively low. Our research highlights the importance of addressing closure in occupancy studies and we provide multiple solutions, using both design‐ and model‐based frameworks, for minimizing bias associated with non‐random changes in occupancy and repeated sampling disturbances.     

Paper spray ionization mass spectrometry: recent advances and clinical applications

ABSTRACT

Introduction: Paper spray mass spectrometry has provided a rapid, quantitative ambient ionization method for xenobiotic and biomolecule analysis. As an alternative to traditional sample preparation and chromatography, paper spray demonstrates the sampling ionization of a wide range of molecules and significant sensitivity from complex biofluids. The amenability of paper spray with dried blood spots and other sampling types shows strong potential for rapid, point-of-care (POC) analysis without time-consuming separation procedures.

Areas covered: This special report summarizes the current state and advances in paper spray mass spectrometry that relate to its applicability for clinical analysis. It also provides our perspectives on the future development of paper spray mass spectrometry and its potential roles in clinical settings.

Expert commentary: Paper spray has provided the fundamental aspects of ambient ionization needed for implementation at the POC. With further clinical management and standardization, paper spray has the potential to replace traditional complex analysis procedure for rapid quantitative detection of illicit drugs, therapeutic drugs and metabolites. Surface and substrate modifications also offer significant improvement in desorption and ionization efficiencies, resulting in enhanced sensitivity. Comprehensive analysis of metabolites and lipids will further extend the implementation of paper spray ionization mass spectrometry into clinical applications.