1H NMR-based metabolite profiling as a potential selection tool for breeding passive resistance against Fusarium head blight (FHB) in wheat

¹H NMR measurements on protein-free extracts from wheat leaf and stem tissue were used to investigate the biochemical correlates of partial resistance to fungal species implicated in the Fusarium head blight (FHB) disease complex. The wheat genotypes included five commercial wheat cultivars and 116 wheat genotypes, from the CIMMYT international FHB breeding programme in Mexico, that had been bred for FHB disease resistance, utilizing exotic, typically Chinese, resistance sources. Principal component analysis of the nuclear magentic resonance (NMR)-derived metabolite profiles revealed distinct separation of the commercial wheat cultivars from the majority of the CIMMYT wheat genotypes with the commercial cultivars exhibiting markedly higher carbohydrate concentrations. A cross-validated partial least squares (PLS) regression model of the metabolite profile against the partial disease resistance component latent period (delay in sporulation of the fungus on the plant tissue) predicted latent periods that were significantly correlated with the experimentally determined values ( R ² = 0.34, P  < 0.001). Identified metabolites that were found in plants with shorter latent periods (higher disease susceptibility) included choline, the single most influential metabolite in the PLS model, betaine, the amino acids glutamine, glutamate and alanine, trans -aconitate and sucrose. Metabolites related to increased disease resistance included glucose and unassigned resonances in the carbohydrate and aromatic regions of the NMR spectra. The current study has demonstrated the potential of metabolite profiling as a tool for marker-assisted selection in commercial breeding for resistance to FHB in wheat.     

Predictive metabolite profiling applying hierarchical multivariate curve resolution to GC-MS data--a potential tool for multi-parametric diagnosis

A method for predictive metabolite profiling based on resolution of GC-MS data followed by multivariate data analysis is presented and applied to three different biofluid data sets (rat urine, aspen leaf extracts, and human blood plasma). Hierarchical multivariate curve resolution (H-MCR) was used to simultaneously resolve the GC-MS data into pure profiles, describing the relative metabolite concentrations between samples, for multivariate analysis. Here, we present an extension of the H-MCR method allowing treatment of independent samples according to processing parameters estimated from a set of training samples. Predictions or inclusion of the new samples, based on their metabolite profiles, into an existing model could then be carried out, which is a requirement for a working application within, e.g., clinical diagnosis. Apart from allowing treatment and prediction of independent samples the proposed method also reduces the time for the curve resolution process since only a subset of representative samples have to be processed while the remaining samples can be treated according to the obtained processing parameters. The time required for resolving the 30 training samples in the rat urine example was approximately 13 h, while the treatment of the 30 test samples according to the training parameters required only approximately 30 s per sample (approximately 15 min in total). In addition, the presented results show that the suggested approach works for describing metabolic changes in different biofluids, indicating that this is a general approach for high-throughput predictive metabolite profiling, which could have important applications in areas such as plant functional genomics, drug toxicity, treatment efficacy and early disease diagnosis.     

Transcriptome profiling in crustaceans as a tool for ecotoxicogenomics

Chemicals released into the environment have the potential to affect various species and it is important to evaluate such chemical effect on ecosystems, including aquatic organisms. Among aquatic organisms, Daphnia magna has been used extensively for acute toxicity or reproductive toxicity tests. Although these types of tests can provide information on hazardous concentrations of chemicals, they provide no information on their mode of action. Recent advances in toxicogenomics, the integration of genomics with toxicology, have the potential to afford a better understanding of the responses of aquatic organisms to pollutants. In a previous study, we developed an oligonucleotide-based DNA microarray with high reproducibility using a Daphnia expressed sequence tag (EST) database. In this study, we increased the number of genes on the array and used it for a careful ecotoxicogenomic assessment of Daphnia magna. The DNA microarray was used to evaluate gene expression profiles of neonate daphnids exposed to beta-naphthoflavone (bNF). Exposure to this chemical resulted in a characteristic gene expression pattern. As the number of the genes on an array was increased, the number of genes that were found to respond to the chemicals was also increased, which made the classification of the toxic chemicals easier and more accurate. This newly developed DNA microarray can be useful for a obtaining a better mechanistic understanding of chemical toxicity effects on a common freshwater organism.     

Antibody-based tissue profiling as a tool for clinical proteomics

Here, we show a strategy for high-throughput antibody-based tissue profiling with the aim to create an atlas of protein expression patterns in normal human tissues and cancer tissues representing the 20 most prevalent cancer types. A set of standardized tissue microarrays (TMAs) was produced to allow for rapid screening of a multitude of different cells and tissues using immunohistochemistry. Eight TMA blocks were produced containing 48 different normal human tissues in triplicate and cancer tissue from 216 individually different tumors in duplicate. Sections from these blocks were immunohistochemically stained using five commercial and five in-house generated antibodies. Digital images for annotation of expression profiles were generated using a semiautomated approach. Five hundred seventy-six images and annotation data corresponding to a total of 30 Gbytes of data were collected for each antibody. The data presented here suggest that antibody-based profiling of protein expression in tissues can be used as a valuable tool in clinical proteomics.     

Metabolic profiling as a tool for prioritizing antimicrobial compounds

Metabolomics is an analytical technique that allows scientists to globally profile low molecular weight metabolites between samples in a medium- or high-throughput environment. Different biological samples are statistically analyzed and correlated to a bioactivity of interest, highlighting differentially produced compounds as potential biomarkers. Here, we review NMR- and MS-based metabolomics as technologies to facilitate the identification of novel antimicrobial natural products from microbial sources. Approaches to elicit the production of poorly expressed (cryptic) molecules are thereby a key to allow statistical analysis of samples to identify bioactive markers, while connection of compounds to their biosynthetic gene cluster is a determining step in elucidating the biosynthetic pathway and allows downstream process optimization and upscaling. The review focuses on approaches built around NMR-based metabolomics, which enables efficient dereplication and guided fractionation of (antimicrobial) compounds.     

Gene expression and metabolite profiling of Populus euphratica growing in the Negev desert

Background

Plants growing in their natural habitat represent a valuable resource for elucidating mechanisms of acclimation to environmental constraints. Populus euphratica is a salt-tolerant tree species growing in saline semi-arid areas. To identify genes involved in abiotic stress responses under natural conditions we constructed several normalized and subtracted cDNA libraries from control, stress-exposed and desert-grown P. euphratica trees. In addition, we identified several metabolites in desert-grown P. euphratica trees.

Results

About 14,000 expressed sequence tag (EST) sequences were obtained with a good representation of genes putatively involved in resistance and tolerance to salt and other abiotic stresses. A P. euphratica DNA microarray with a uni-gene set of ESTs representing approximately 6,340 different genes was constructed. The microarray was used to study gene expression in adult P. euphratica trees growing in the desert canyon of Ein Avdat in Israel. In parallel, 22 selected metabolites were profiled in the same trees.

Conclusion

Of the obtained ESTs, 98% were found in the sequenced P. trichocarpa genome and 74% in other Populus EST collections. This implies that the P. euphratica genome does not contain different genes per se, but that regulation of gene expression might be different and that P. euphratica expresses a different set of genes that contribute to adaptation to saline growth conditions. Also, all of the five measured amino acids show increased levels in trees growing in the more saline soil.     

Genetic transformation of Populus trichocarpa genotype Nisqually-1: a functional genomic tool for woody plants

We report here the Agrobacterium-mediated genetic transformation of Nisqually-1, a Populus trichocarpa genotype whose genome was recently sequenced. Several systems were established. Internodal stem segments from vigorously growing greenhouse plants are the explants most amenable to transformation. For the most efficient system, approximately 40% of the stem segments infected with pBI121-containing Agrobacterium tumefaciens C58 produced transgenic calli, as confirmed by beta-glucuronidase (GUS) staining. The regeneration efficiency of independent transgenic plants was approximately 13%, as revealed by genomic Southern analysis. Some transgenic plants were produced in as little as 5 months after co-cultivation. This system may help to facilitate studies of gene functions in tree growth and development at a genome level.     

Giant otter alarm calls as potential mechanisms for individual discrimination and sexual selection

Acoustic variation can convey identity information, facilitate social interactions among individuals and may be useful in identifying sex and group affiliation of senders. Giant otters live in highly cohesive groups with exclusive territories along water bodies defended by the entire group by means of acoustic and chemical signals. Snorts are harsh alarm calls, emitted in threat contexts, which commonly elicit the cohesion and the alert behaviour of the members of the group. The aim of this study was to determine whether giant otter snorts have potential to be used for individual discrimination. We tested this hypothesis by verifying if the acoustic characteristics of snorts vary between two study areas, among social groups and individuals, and between males and females. Snort acoustic variables did not differ significantly among study areas, but varied significantly among groups, individuals and between sexes, with higher discrimination between sexes. The frequency of formants (F1–F5) and formant dispersion (DF) potentially allow identity coding among groups, individuals and sexes. The stronger sex discrimination of snorts may be related to information on body size carried by formant frequencies and dispersion, indicating acoustic sexual dimorphism in giant otters. Acoustic differences among groups and individuals are more likely learned, since we did not find evidence for a genetic signal encoded in the snort variables measured. We conclude that the snorts carry information that could be used for individual or group recognition.     

MassCode liquid arrays as a tool for multiplexed high-throughput genetic profiling

Multiplexed detection assays that analyze a modest number of nucleic acid targets over large sample sets are emerging as the preferred testing approach in such applications as routine pathogen typing, outbreak monitoring, and diagnostics. However, very few DNA testing platforms have proven to offer a solution for mid-plexed analysis that is high-throughput, sensitive, and with a low cost per test. In this work, an enhanced genotyping method based on MassCode technology was devised and integrated as part of a high-throughput mid-plexing analytical system that facilitates robust qualitative differential detection of DNA targets. Samples are first analyzed using MassCode PCR (MC-PCR) performed with an array of primer sets encoded with unique mass tags. Lambda exonuclease and an array of MassCode probes are then contacted with MC-PCR products for further interrogation and target sequences are specifically identified. Primer and probe hybridizations occur in homogeneous solution, a clear advantage over micro- or nanoparticle suspension arrays. The two cognate tags coupled to resultant MassCode hybrids are detected in an automated process using a benchtop single quadrupole mass spectrometer. The prospective value of using MassCode probe arrays for multiplexed bioanalysis was demonstrated after developing a 14plex proof of concept assay designed to subtype a select panel of Salmonella enterica serogroups and serovars. This MassCode system is very flexible and test panels can be customized to include more, less, or different markers.     

Rapid milk progesterone assay as a tool for the selection of potential donor cows prior to superovulation

This study investigated the accuracy of a commercially available rapid milk progesterone (P(4)) assay (RMPA) and its usefulness for the screening of potential donor cows prior to superovulatory treatment. Superovulation was induced in 90 lactating Holstein-Friesian crossbred dairy cows with twice daily injections over a 4-day period for a total of 40 mg follicle stimulating hormone (FSH-P), starting 9 to 13 d post estrus. Prior to induction of superovulation, a milk sample was collected and assayed for a P(4) level using the RMPA. The test determines P(4) by a simple visual color inspection of the respective sample, which is compared to a standard containing 10.5 ng/ml of P(4). All animals were divided into six groups according to the color intensity of their sample; three groups had a lower level, one group had an equal level and two groups had a higher P(4) level than the standard. Results of the semiquantitative RMPA were verified by a quantitative enzymeimmunoassay (EIA). Samples evaluated as equivalent to the standard had a mean P(4) level of 10.7 +/- 1.3 ng/ml (x +/- SEM). In total, P(4) levels differed (P<0.05) among groups, except in those with lower P(4) concentrations (1.1 +/- 0.0; 1.0 +/- 0.0; 3.7 +/- 1.5; 10.7 +/- 1.3; 13.8 +/- 1.3; 19.0 +/- 1.5 ng/ml, respectively). The correlation between RMPA-groups and EIA P(4) levels was 0.69 (P<0.001). Donors classified as having less P(4) than the standard yielded fewer corpora lutea (CL) (P<0.005), ova and embryos (P<0.05), and transferable embryos (P<0.05) compared with donors having similar or higher P(4) levels (3.4 +/- 1.0 vs 10.8 +/- 0.7 CL; 1.7 +/- 0.8 vs 6.2 +/- 0.9 ova and embryos; 1.2 +/- 0.7 vs 2.8 +/- 0.4 transferable embryos). Our results indicate that RMPA determines milk P(4) levels with sufficient accuracy and is a simple and useful tool for the screening of potential donor cows.     

Urine metabolite profiling offers potential early diagnosis of oral cancer

Oral cancer is the sixth most common human cancer, with a high morbidity rate and an overall 5-year survival rate of less than 50%. It is often not diagnosed until it has reached an advanced stage. Therefore, an early diagnostic and stratification strategy is of great importance for oral cancer. In the current study, urine samples of patients with oral squamous cell carcinoma (OSCC, n = 37), oral leukoplakia (OLK, n = 32) and healthy subjects (n = 34) were analyzed by gas chromatography-mass spectrometry (GC–MS). Using multivariate statistical analysis, the urinary metabolite profiles of OSCC, OLK and healthy control samples can be clearly discriminated and a panel of differentially expressed metabolites was obtained. Metabolites, valine and 6-hydroxynicotic acid, in combination yielded an accuracy of 98.9%, sensitivity of 94.4%, specificity of 91.4%, and positive predictive value of 91.9% in distinguishing OSCC from the controls. The combination of three differential metabolites, 6-hydroxynicotic acid, cysteine, and tyrosine, was able to discriminate between OSCC and OLK with an accuracy of 92.7%, sensitivity of 85.0%, specificity of 89.7%, and positive predictive value of 91.9%. This study demonstrated that the metabolite markers derived from this urinary metabolite profiling approach may hold promise as a diagnostic tool for early stage OSCC and its differentiation from other oral conditions.     

Metabolic profiling as a tool for revealing Saccharomyces interactions during wine fermentation

The multi-yeast strain composition of wine fermentations has been well established. However, the effect of multiple strains of Saccharomyces spp. on wine flavour is unknown. Here, we demonstrate that multiple strains of Saccharomyces grown together in grape juice can affect the profile of aroma compounds that accumulate during fermentation. A metabolic footprint of each yeast in monoculture, mixed cultures or blended wines was derived by gas chromatography - mass spectrometry measurement of volatiles accumulated during fermentation. The resultant ion spectrograms were transformed and compared by principal-component analysis. The principal-component analysis showed that the profiles of compounds present in wines made by mixed-culture fermentation were different from those where yeasts were grown in monoculture fermentation, and these differences could not be produced by blending wines. Blending of monoculture wines to mimic the population composition of mixed-culture wines showed that yeast metabolic interactions could account for these differences. Additionally, the yeast strain contribution of volatiles to a mixed fermentation cannot be predicted by the population of that yeast. This study provides a novel way to measure the population status of wine fermentations by metabolic footprinting.     

Molecular simulations as a tool for selection of kinetic hydrate inhibitors

Natural gas hydrates are ice-like structures in which water molecules form a cage around gas molecules. They have been a problem in the petroleum industry. The heavy cost of alcohol and glycol injections needed to suppress the formation of hydrates has spurred an interest in so-called “kinetic inhibitors”, able to slow down the hydrate formation rather than prevent it. An earlier work (Kvamme, B. et al. 1997, Mol. Phys., 90, p. 979) proposed a simulation-based scheme to assess the comparative performance of prospective inhibitors and select the best candidates for experimental testing. In this work, we employed molecular dynamics simulations to test several kinetic inhibitors in a multiphase water–hydrate system with rigid hydrate interface. In addition, a long-scale run was implemented for a system where the hydrate was free to melt and reform. Our conclusion that PVCap inhibitor will outperform PVP as a kinetic hydrate inhibitor is supported by experimental data. We demonstrate that numerical experiments can be a valuable tool for selecting kinetic inhibitors as well as provide insight into mechanisms of kinetic inhibition and hydrate melting and reformation.     

Proteomics as a tool for tapping potential of entomopathogens as microbial insecticides

Biopesticides are collective pest control harnessing the knowledge of the target pest and its natural enemies that minimize the risks of synthetic pesticides. A subset of biopesticides; bioinsecticides, are specifically used in controlling insect pests. Entomopathogens (EPMs) are micro‐organisms sought after as subject for bioinsecticide development. However, lack of understanding of EPM mechanism of toxicity and pathogenicity slowed the progress of bioinsecticide development. Proteomics is a useful tool in elucidating the interaction of entomopathogenic fungi, entomopathogenic bacteria, and entomopathogenic virus with their target host. Collectively, proteomics shed light onto insect host response to EPM infection, mechanism of action of EPM’s toxic proteins and secondary metabolites besides characterizing secreted and membrane‐bound proteins of EPM that more precisely describe relevant proteins for host recognition and mediating pathogenesis. However, proteomics requires optimized protein extraction methods to maximize the number of proteins for analysis and availability of organism's genome for a more precise protein identification.     

The Sensory Gating Inventory as a potential diagnostic tool for attention-deficit hyperactivity disorder

Diagnoses of attention-deficit hyperactivity disorder (ADHD) are often made rapidly in physicians' offices without thorough assessment. We examined whether adults diagnosed with ADHD would score differently from controls on a modified Sensory Gating Inventory (SGI: Hetrick et al. in Schizophr Bull 38:178-191, 2012; Kisley et al. in Psychophysiol 41:604-612, 2004), which would facilitate rapid and easy preliminary assessment of ADHD status. The modified SGI was administered to 22 controls and 22 adults with physician diagnoses of ADHD. Analysis was performed on the 17 SGI items and the three categories to which they belong (Perceptual Modulation, Distractibility, and Over-Inclusion). The Distractibility category, and its individual items, showed large group differences. In spite of a relatively small sample size, we found large effect sizes between those with and without ADHD diagnoses. The SGI is a simple, quick, paper/pencil method that may be used to facilitate accurate diagnosis of individuals experiencing ADHD symptoms, which may be especially useful when evaluations are made in settings such as physicians' offices.     

Bacterial motility as a potential tool for rapid toxicity assays

Summary Bacterial motility was evaluated as a potential tool for the rapid assay of the toxicity of chemicals to microorganisms. The level of toxicity was evaluated by the chemical concentration which caused a 50% reduction in motile bacteria at the 60 s of exposure to toxicants. Assay results showed a good correlation with those obtained from a conventional growth inhibition test.     

The growing potential of diagnostic reference levels as a dynamic tool for dose optimization

Diagnostic Reference Levels (DRLs) is an important tool that can improve radiation safety in medical imaging. However, there are certain aspects that need improvement and several obstacles that should be overcome before DRLs are fully implemented in practice. It is the authors belief that DRLs should be a dynamic tool that follows the development of clinical practice and technology advances. The establishment of adult and paediatric DRLs based on clinical indications should be considered as a priority. A common methodology and terminology is needed to allow for their clinical use. Dose monitoring systems can improve and accelerate the establishment, update and use of DRLs. However, certain steps need to be taken for proper collection. organization and analysis of big data. Availability of clinically qualified medical physicists in medical imaging departments, awareness on the importance of dose optimization and proper cooperation of relevant stakeholders are important prerequisites for the successful establishment and use of DRLs.