Peptoids as tools and sensors.

A review of molecular tools and sensors assembled on N-substituted glycine, or α-peptoid, oligomers between 2013 and November 2018 with the following sections: (a) Peptoids as crystal growth modifiers, (b) Peptoids as catalysts, (c) Ion and molecule sequestration and transport, (d) Peptoid sensors, (e) Macromolecule recognition, (f) Cellular transporters, (g) Medical imaging, (h) Future direction and (i) Summary and outlook. Peptoids are a promising class of peptide mimic making them an excellent platform for functional molecule preparation. Attributes of peptoid oligomers include: (a) the ease of precise sequence definition and mono-dispersity; (b) access to a vast chemical space within simple and repeating chemical preparative steps and (c) thermal, chemical and biological stability all lending support for their application in a number of areas, with some that have been realised to date. The peptoid tool and sensor examples selected have realised practical utility. They serve to illustrate the rapidity of new insight that can generate in many disparate areas of science and technology, enabling the quick assembly of design criteria for efficient peptoid molecular tools and sensors.

A spectroscopic study of substituted anthranilic acids as sensitive environmental probes for detecting cancer cells.

Small-molecule fluorescent reporters of disease states are highly sought after, yet they remain elusive. Anthranilic acids are extremely sensitive environmental probes, and hold promise as general but selective agents for cancer-cell detection if they can be equipped with the appropriate targeting groups. The optical properties of a small library of N-isopropyl invariant anthranilic acids were investigated in methanol and chloroform. Points of variation included: fluoro, trifluoromethyl, or cyano substitution on the aromatic ring, and derivitization of the parent carboxylic acid as esters or secondary carboxamides. Phenylboronic acid conjugation at the carboxylic acid alongside un-, mono-, and dimethylated 2-amino groups was also explored. The boron-containing anthranilic acids were also evaluated as sensitive fluorescent probes for cancer cells using laser scanning confocal microscopy. In general, the compounds produced blue fluorescence that was strongly influenced by substitution and environment. 4-Trifluoromethyl and 4-cyano esters proved to be the most sensitive environmental probes with quantum yields as large as 100% in chloroform, and enhancements of up to 30-fold on going from methanol to chloroform. Stokes shifts ranged from 63 to 120nm, generally increasing with ortho-substitution and environmental polarity. It was demonstrated that phenylboronic acid conjugation was an attractive method for cancer cell detection via boronate ester formation with overexpressed glycoproteins (with no interference from normal, healthy cells), presumably due to favorable boron-sialic acid interactions.

Metal-Free, Acid-Catalyzed ortho-Directed Synthesis of Anthranilic Acid Derivatives Using Carbodiimides.

One-pot syntheses of fluorescent o-aminobenzoates, o-aminopyridine carboxylates, and a 2'-amino-[1,1'-biphenyl]-2-carboxylic acid are described. Carbodiimides are used as the source of the 2-amino function which inserts onto an aromatic ring using S(N)Ar reaction conditions. This method proceeds regiospecifically with a range of 2-fluoroaromatic acids or esters bearing further aryl fluorine, trifluoromethyl, and cyano substituents.

Metabolic Effects of Known and Novel HDAC and SIRT Inhibitors in Glioblastomas Independently or Combined with Temozolomide.

Inhibition of protein deacetylation enzymes, alone or in combination with standard chemotherapies, is an exciting addition to cancer therapy. We have investigated the effect of deacetylase inhibition on the metabolism of glioblastoma cells. 1H NMR metabolomics analysis was used to determine the major metabolic changes following treatment of two distinct glioblastoma cell lines, U373 and LN229, with five different histone deacetylase (HDAC) inhibitors, as well as one inhibitor of NAD+-dependent protein deacetylases (SIRT). The addition of the standard glioblastoma chemotherapy agent, temozolomide, to the HDAC and SIRT treatments led to a reduction in cell survival, suggesting a possibility for combined treatment. This study shows that distinct glioblastoma cell lines, with different metabolic profiles and gene expression, experience dissimilar changes following treatment with protein deacetylase inhibitors. The observed effects of inhibitors on mitochondrial metabolism, glycolysis and fatty acid synthesis suggest possible roles of protein deacetylases in metabolism regulation. Metabolic markers of the effectiveness of anti-protein deacetylase treatments have been explored. In addition to known deacetylation inhibitors, three novel inhibitors have been introduced and tested. Finally, 1H NMR analysis of cellular metabolism is shown to be a fast, inexpensive method for testing drug effects.

Small head-to-tail macrocyclic α-peptoids.

A convenient and efficient methodology for the head-to-tail macrocyclization of small 3-mer, 4-mer, and 5-mer α-peptoid acids (9-, 12-, and 15-atom N-substituted glycine oligomers) is described. The cyclic trimer has a ccc amide sequence in the crystal structure, whereas the tetramer has ctct and the pentamer has ttccc stereochemistry. NMR analysis reveals rigid structures in solution. These synthetic macrocycles may prove useful in medicinal and materials applications.

¹H NMR metabolomics analysis of the effect of dichloroacetate and allopurinol on breast cancers.

Metabolomics analysis was used to determine the effect of two well known, non-proprietary metabolic modulators, dichloroacetate and allopurinol on breast cancer cell lines. Dichloroacetate, a pyruvate dehydrogenase kinase inhibitor and allopurinol, a xanthine oxidase/dehydrogenase inhibitor, have been previously explored as chemotherapeutics showing potential in some cancer subtypes while at the same time leading to unexpected increase in proliferation in others. In this work, metabolic effects of these drugs, applied singly and in combination, were explored in three different breast cell lines including cancer cells, MDA-MB-231 and MCF-7 and normal control cell line, MCF-10A. The metabolic changes induced by these drugs were monitored by (1)H NMR metabolic profiling. Analyses were performed on complete spectral data as well as quantified metabolic data in intracellular fractions and extracellular media leading to the determination of the most significantly affected metabolites. The effect of dichloroacetate and allopurinol is the most apparent in the metabolic profile of extracellular media. In MCF-7 cells, dichloroacetate treatment is dominant with only a minor observed influence of allopurinol in combined treatment. In MDA-MB-231 cells, both allopurinol and DCA lead to a metabolic shift with the allopurinol change dominating the effect of combined treatment. Results show the power of metabolomics as a tool for fast molecular profiling of drug effects in cells. In summary, treatments of breast cancer cells with DCA and allopurinol result in larger changes in metabolites found in extracellular medium than intracellular pools.

1H NMR metabolomics analysis of glioblastoma subtypes: correlation between metabolomics and gene expression characteristics.

Glioblastoma multiforme (GBM) is the most common form of malignant glioma, characterized by unpredictable clinical behaviors that suggest distinct molecular subtypes. With the tumor metabolic phenotype being one of the hallmarks of cancer, we have set upon to investigate whether GBMs show differences in their metabolic profiles. (1)H NMR analysis was performed on metabolite extracts from a selection of nine glioblastoma cell lines. Analysis was performed directly on spectral data and on relative concentrations of metabolites obtained from spectra using a multivariate regression method developed in this work. Both qualitative and quantitative sample clustering have shown that cell lines can be divided into four groups for which the most significantly different metabolites have been determined. Analysis shows that some of the major cancer metabolic markers (such as choline, lactate, and glutamine) have significantly dissimilar concentrations in different GBM groups. The obtained lists of metabolic markers for subgroups were correlated with gene expression data for the same cell lines. Metabolic analysis generally agrees with gene expression measurements, and in several cases, we have shown in detail how the metabolic results can be correlated with the analysis of gene expression. Combined gene expression and metabolomics analysis have shown differential expression of transporters of metabolic markers in these cells as well as some of the major metabolic pathways leading to accumulation of metabolites. Obtained lists of marker metabolites can be leveraged for subtype determination in glioblastomas.

MetaboHunter: an automatic approach for identification of metabolites from 1H-NMR spectra of complex mixtures.

BACKGROUND: One-dimensional 1H-NMR spectroscopy is widely used for high-throughput characterization of metabolites in complex biological mixtures. However, the accurate identification of individual compounds is still a challenging task, particularly in spectral regions with higher peak densities. The need for automatic tools to facilitate and further improve the accuracy of such tasks, while using increasingly larger reference spectral libraries becomes a priority of current metabolomics research. RESULTS: We introduce a web server application, called MetaboHunter, which can be used for automatic assignment of 1H-NMR spectra of metabolites. MetaboHunter provides methods for automatic metabolite identification based on spectra or peak lists with three different search methods and with possibility for peak drift in a user defined spectral range. The assignment is performed using as reference libraries manually curated data from two major publicly available databases of NMR metabolite standard measurements (HMDB and MMCD). Tests using a variety of synthetic and experimental spectra of single and multi metabolite mixtures show that MetaboHunter is able to identify, in average, more than 80% of detectable metabolites from spectra of synthetic mixtures and more than 50% from spectra corresponding to experimental mixtures. This work also suggests that better scoring functions improve by more than 30% the performance of MetaboHunter's metabolite identification methods. CONCLUSIONS: MetaboHunter is a freely accessible, easy to use and user friendly 1H-NMR-based web server application that provides efficient data input and pre-processing, flexible parameter settings, fast and automatic metabolite fingerprinting and results visualization via intuitive plotting and compound peak hit maps. Compared to other published and freely accessible metabolomics tools, MetaboHunter implements three efficient methods to search for metabolites in manually curated data from two reference libraries.

Development and experimental validation of a 20K Atlantic cod (Gadus morhua) oligonucleotide microarray based on a collection of over 150,000 ESTs.

The collapse of Atlantic cod (Gadus morhua) wild populations strongly impacted the Atlantic cod fishery and led to the development of cod aquaculture. In order to improve aquaculture and broodstock quality, we need to gain knowledge of genes and pathways involved in Atlantic cod responses to pathogens and other stressors. The Atlantic Cod Genomics and Broodstock Development Project has generated over 150,000 expressed sequence tags from 42 cDNA libraries representing various tissues, developmental stages, and stimuli. We used this resource to develop an Atlantic cod oligonucleotide microarray containing 20,000 unique probes. Selection of sequences from the full range of cDNA libraries enables application of the microarray for a broad spectrum of Atlantic cod functional genomics studies. We included sequences that were highly abundant in suppression subtractive hybridization (SSH) libraries, which were enriched for transcripts responsive to pathogens or other stressors. These sequences represent genes that potentially play an important role in stress and/or immune responses, making the microarray particularly useful for studies of Atlantic cod gene expression responses to immune stimuli and other stressors. To demonstrate its value, we used the microarray to analyze the Atlantic cod spleen response to stimulation with formalin-killed, atypical Aeromonas salmonicida, resulting in a gene expression profile that indicates a strong innate immune response. These results were further validated by quantitative PCR analysis and comparison to results from previous analysis of an SSH library. This study shows that the Atlantic cod 20K oligonucleotide microarray is a valuable new tool for Atlantic cod functional genomics research.

Solid-phase synthesis of N-substituted glycine oligomers (alpha-peptoids) and derivatives.

Peptoids (N-substituted polyglycines and extended peptoids with variant backbone amino-acid monomer units) are oligomeric synthetic polymers that are becoming a valuable molecular tool in the biosciences. Of particular interest are their applications to the exploration of peptoid secondary structures and drug design. Major advantages of peptoids as research and pharmaceutical tools include the ease and economy of synthesis, highly variable backbone and side-chain chemistry possibilities. At the same time, peptoids have been demonstrated as highly active in biological systems while resistant to proteolytic decay. This review with 227 references considers the solid-phase synthetic aspects of peptoid preparation and utilization up to 2010 from the instigation, by R. N. Zuckermann et al., of peptoid chemistry in 1992.

Cell culture metabolomics: applications and future directions.

Metabolomics represents a global quantitative assessment of metabolites within a biological system. The metabolic analysis of cell cultures has many potential applications and advantages to currently used methods for cell line testing. Metabolite concentrations represent sensitive markers of both genomic and phenotypic changes. Consequently, the development of robust metabolomic platforms will greatly facilitate various applications of cell cultures - including, for example, the understanding of the in vitro and in vivo actions of drugs - and aid in their rapid incorporation into novel therapeutic settings. In addition, metabolomic analysis of cell lines provides information, either independently or in conjunction with other omics measurements, essential for system level analysis and modeling of biological systems. This review outlines some of the applications of metabolomics in cell culture analysis and some of the issues that need to be addressed to make this approach more relevant.

NMR metabolic analysis of samples using fuzzy K-means clustering.

The global analysis of metabolites can be used to define the phenotypes of cells, tissues or organisms. Classifying groups of samples based on their metabolic profile is one of the main topics of metabolomics research. Crisp clustering methods assign each feature to one cluster, thereby omitting information about the multiplicity of sample subtypes. Here, we present the application of fuzzy K-means clustering method for the classification of samples based on metabolomics 1D (1)H NMR fingerprints. The sample classification was performed on NMR spectra of cancer cell line extracts and of urine samples of type 2 diabetes patients and animal models. The cell line dataset included NMR spectra of lipophilic cell extracts for two normal and three cancer cell lines with cancer cell lines including two invasive and one non-invasive cancers. The second dataset included previously published NMR spectra of urine samples of human type 2 diabetics and healthy controls, mouse wild type and diabetes model and rat obese and lean phenotypes. The fuzzy K-means clustering method allowed more accurate sample classification in both datasets relative to the other tested methods including principal component analysis (PCA), hierarchical clustering (HCL) and K-means clustering. In the cell line samples, fuzzy clustering provided a clear separation of individual cell lines, groups of cancer and normal cell lines as well as non-invasive and invasive tumour cell lines. In the diabetes dataset, clear separation of healthy controls and diabetics in all three models was possible only by using the fuzzy clustering method.

Fast deprotection of synthetic oligodeoxyribonucleotides using standard reagents under microwave irradiation.

Fast methods for the removal of permanent amide exo-cyclic protective groups widely used in phosphoramidite-method DNA synthesis are desirable for many genomics and proteomics applications. In this communication, we present a method for the deprotection of a range of N-acyl deoxyribonucleosides (T, dA Bz, dC Bz, dC Ac, dG ibu, dG PAC) and synthetic oligodeoxyribonucleotides, ranging in length from 5-mer to 50-mer. Oligodeoxyribonucleotides were synthesized using standard amide protecting groups (dA Bz, dC Bz, dG ibu) and phosphoramidite chemistry on cis-diol solid phase support. This deprotection method utilizes 29% aqueous ammonia solution at 170 degrees C for 5 minutes under monomode microwave irradiation at a 20-nmole reaction scale. Reaction products were analyzed by TLC, RP-HPLC, CE, ESI-MS, real-time PCR, agarose gel electrophoresis, and by DNA uracil glycosylase (UDG) and phosphodiesterase I (PDE) enzymatic digestions.

Integrated analysis of transcriptomics and metabolomics profiles.

BACKGROUND: Integrated analysis of transcriptomics and metabolomics data has the potential greatly to increase our understanding of metabolic networks and biological systems leading to various potential clinical applications. OBJECTIVE: The aim is to present different applications as well as analysis tools utilized for the parallel study of gene and metabolite expressions. METHODS: Publications dealing with integrated analysis of gene and metabolite expression data as well as publications describing tools that can be used for integrated analysis are reviewed. RESULTS/CONCLUSION: The full benefit of integrated analysis can be achieved only if data from all utilized methods are treated equally by multidisciplinary teams. This approach can lead to advances in functional genomics with possible clinical developments in diagnostics and improved drug target selection.

Carbohydrate microarrays: survey of fabrication techniques.

Carbohydrate microarrays are being developed in order to decipher the information content of the glycome. This postgenomic activity is necessary because of the complexity of protein biosynthesis and post-translational modifications that cannot currently be detected at the genome level. This review looks, in detail, at the experimental approaches that have been taken in the fabrication and preparation of carbohydrate microarrays, glycan arrays and glyco-chips. Tether structures, glycan solution preparation, detection methods and applications have been gathered together in a tabular format.

Microarray analysis of alternative splicing.

Alternative splicing, defined as the generation of multiple RNA transcript species from a common mRNA precursor, is one of the mechanisms for the diversification and expansion of cellular proteins from a smaller set of genes. Current estimates indicate that at least 60% of genes in the human genome exhibit alternative splicing. Over the past decade, alternative splicing has increasingly been recognized as a major regulatory process with a critical role in normal development. Furthermore, the importance of alternative splicing in disease development and treatment is starting to be appreciated. Therefore, an increasing number of high-throughput genomics and proteomics studies are being performed in order to delineate (a) the changes in alternative splicing under various conditions; (b) the properties and functions of protein isoforms; and (c) the splicing and alternative splicing regulation process. Strategies for the parallel analysis of alternative splice forms by microarray experiments have been conceived, and examples have been published. In addition to the differences in microarray probe design, the analysis of microarrays with probes for exons, exon/exon junctions as well as specific splice forms is significantly different from the standard experiment. Several methods are being developed in order to address the particular needs of alternative splicing microarrays. Many reviews have already dealt with alternative splicing. However, high-throughput analysis methods that are becoming increasingly popular have not received much attention. Here, we will provide an overview of the tools and analysis methods that were developed specifically for alternative splicing microarrays described in terms of specific experiments.

Data analysis of alternative splicing microarrays.

The importance of alternative splicing in drug and biomarker discovery is best understood through several example genes. For most genes, the identification, detection and particularly quantification of isoforms in different tissues and conditions remain to be carried out. As a result, the focus in drug and biomarker development is increasingly on high-throughput studies of alternative splicing. Initial strategies for the parallel analysis of alternative splicing by microarrays have been recently published. The design specificities and goals of alternative splicing microarrays, in terms of identification and quantification of multiple mRNAs from one gene, are promoting the development of novel methods of analysis.