Genome-inspired molecular identification in organic matter via Raman spectroscopy

Rapid, non-destructive characterization of molecular level chemistry for organic matter (OM) is experimentally challenging. Raman spectroscopy is one of the most widely used techniques for non-destructive chemical characterization, although it currently does not provide detailed identification of molecular components in OM, due to the combination of diffraction-limited spatial resolution and poor applicability of peak-fitting algorithms. Here, we develop a genome-inspired collective molecular structure fingerprinting approach, which utilizes ab initio calculations and data mining techniques to extract molecular level chemistry from the Raman spectra of OM. We illustrate the power of such an approach by identifying representative molecular fingerprints in OM, for which the molecular chemistry is to date inaccessible using non-destructive characterization techniques. Chemical properties such as aromatic cluster size distribution and H/C ratio can now be quantified directly using the identified molecular fingerprints. Our approach will enable non-destructive identification of chemical signatures with their correlation to the preservation of biosignatures in OM, accurate detection and quantification of environmental contamination, as well as objective assessment of OM with respect to their chemical contents

From mass to structure: An aromaticity index for high-resolution mass data of natural organic matter

Recent progress in Fourier transform ion cyclotron resonance mass spectrometry (FTICRMS) provided extensive molecular mass data for complex natural organic matter (NOM). Structural information can be deduced solely from the molecular masses for ions with extreme molecular element ratios, in particular low H/C ratios, which are abundant in thermally altered NOM (e.g. black carbon). In this communication we propose a general aromaticity index (AI) and two threshold values as unequivocal criteria for the existence of either aromatic (AI > 0.5) or condensed aromatic structures (AI >= 0.67) in NOM. AI can be calculated from molecular formulae which are derived from exact molecular masses of naturally occurring compounds containing C, H, O, N, S and P and is especially applicable for substances with aromatic cores and few alkylations. In order to test the validity of our model index, AI is applied to FTICRMS data of a NOM deep-water sample from the Weddell Sea (Antarctica), a fulvic acid standard and an artificial dataset of all theoretically possible molecular formulae. For graphical evaluation a ternary plot is suggested for four-dimensional data representation. The proposed aromaticity index is a step towards structural identification of NOM and the molecular identification of black carbon in the environment

Isolation and Molecular Identification of Entomopathogenic Nematodes (Steinernema and Heterorhabditis) From East Java and Bali

Entomopathogenic nematode of the families Steinernematidae and Heterorhabditidae is one of the best biological control agents of insect pests. Native isolates maybe more efficacious in controlling insect pests than imported ones because they have adapted to local environment. This study aimed to isolate and identify both nematode families from East Java and Baliusing DNA analysis. Sixty eight soil samples obtained from sandy soils in 16 sites of coastal regions and agricultural fields were tested for the presence of nematodes by baiting method with mealworm larvae (Tenebrio molitor). Five Heterorhabditis and two Steinernema were recovered from 7 soil samples (10% of total samples) of 7 sites (44% of total sites). Sequence analysis ofinternal transcribed spacer (ITS) 1 and 2 regions of ribosomal DNA revealed that all Heterorhabditis belonged to indica species, with 99–100% nucleotide sequence similarities to published sequences. One of the Steinernema isolates had short infective juvenile body length (360 μm to 547 μm) and shared 99% nucleotide similarity to that of S. huense, a member of “carpocapsae” group. The other Steinernema isolate (DKS1) showed longer infective juvenile body length (from 548 μm to 762 μm) and shared 95% nucleotide similarity to the sequence of S. Pakistanense, which belongs to “bicornutum” group. More detailed studies with respect to morphology are required for species confirmation of DKS1 isolate. Further exploration todiverse habitat will likely to result in more previously unrecorded entomopathogenic nematode species in Indonesia

Resistance to bleomycin increases the chronological life of cells

The identification of genes involved in chronological aging could have a potential utility as molecular markers in the chemotherapy treatment of cancer. The aim of this work is to study the relationship between the chronological aging and the resistance to Bleomycin for the purpose of establish the basic interactions between these phenomenons for further investigation of molecular markers.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Non-Destructive Identification of Cold and Extremely Localized Single Molecular Ions

A simple and non-destructive method for identification of a single molecular ion sympathetically cooled by a single laser cooled atomic ion in a linear Paul trap is demonstrated. The technique is based on a precise determination of the molecular ion mass through a measurement of the eigenfrequency of a common motional mode of the two ions. The demonstrated mass resolution is sufficiently high that a particular molecular ion species can be distinguished from other equally charged atomic or molecular ions having the same total number of nucleons

Some spectrometric results from the NASA 1968 Airborne Auroral Expedition and tentative identification of several N2 c prime /1 Sigma u plus/ yields a /1 Pi g/ bands in auroras

Spectrophotometric results from NASA 1968 Airborne Auroral Expedition and tentative identification of several molecular nitrogen emission band

New model for datasets citation and extraction reproducibility in VAMDC

In this paper we present a new paradigm for the identification of datasets extracted from the Virtual Atomic and Molecular Data Centre (VAMDC) e-science infrastructure. Such identification includes information on the origin and version of the datasets, references associated to individual data in the datasets, as well as timestamps linked to the extraction procedure. This paradigm is described through the modifications of the language used to exchange data within the VAMDC and through the services that will implement those modifications. This new paradigm should enforce traceability of datasets, favour reproducibility of datasets extraction, and facilitate the systematic citation of the authors having originally measured and/or calculated the extracted atomic and molecular data.Comment: 48 page

Comparative Analysis of Molecular Clouds in M31, M33 and the Milky Way

We present BIMA observations of a 2\arcmin field in the northeastern spiral arm of M31. In this region we find six giant molecular clouds that have a mean diameter of 57$\pm$13 pc, a mean velocity width of 6.5$\pm$1.2 \kms, and a mean molecular mass of 3.0 $\pm$ 1.6 $\times$ 10$^5$\Msun. The peak brightness temperature of these clouds ranges from 1.6--4.2 K. We compare these clouds to clouds in M33 observed by \citet{wilson90} using the OVRO millimeter array, and some cloud complexes in the Milky Way observed by \cite{dame01} using the CfA 1.2m telescope. In order to properly compare the single dish data to the spatially filtered interferometric data, we project several well-known Milky Way complexes to the distance of Andromeda and simulate their observation with the BIMA interferometer. We compare the simulated Milky Way clouds with the M31 and M33 data using the same cloud identification and analysis technique and find no significant differences in the cloud properties in all three galaxies. Thus we conclude that previous claims of differences in the molecular cloud properties between these galaxies may have been due to differences in the choice of cloud identification techniques. With the upcoming CARMA array, individual molecular clouds may be studied in a variety of nearby galaxies. With ALMA, comprehensive GMC studies will be feasible at least as far as the Virgo cluster. With these data, comparative studies of molecular clouds across galactic disks of all types and between different galaxy disks will be possible. Our results emphasize that interferometric observations combined with the use of a consistent cloud identification and analysis technique will be essential for such forthcoming studies that will compare GMCs in the Local Group galaxies to galaxies in the Virgo cluster.Comment: Accepted for Publication in the Astrophysical Journa

A Systematic Approach to Identifying Protein-Ligand Binding Profiles on a Proteome Scale

Identification of protein-ligand interaction networks on a proteome scale is crucial to address a wide range of biological problems such as correlating molecular functions to physiological processes and designing safe and efficient therapeutics. We have developed a novel computational strategy to identify ligand binding profiles of proteins across gene families and applied it to predicting protein functions, elucidating molecular mechanisms of drug adverse effects, and repositioning safe pharmaceuticals to treat different diseases

Molecular diagnosis by PCR-DHPLC technique of wood-decay fungi in historical buildings in Italy

Wood inhabiting fungi cause real problems in the preservation of wooden surfaces and are responsible for the deterioration of cultural heritage. The identification of fungi based on morphological characteristics are still a topical issue. Nevertheless, they are limited for characterization and identification on an intraspecific level and even sometimes on an interspecific level. It is not always evident and thus many fungi remain unnamed or confused. The objective of this study was to circumvent these limitations by using a new molecular approach allowing fungal detection and identification in historic buildings in Italy. Fungal colonization was assessed by using PCR amplification and amplicons separation by Denaturing High Performance Liquid Chromatography. Due to its high sensitivity, the PCR-DHPLC technique was optimised to profile fungal communities in wood decay as well as ubiquitous contaminants. (Résumé d'auteur