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

Using molecular tools to differentiate closely related blackfly species of the genus Simulium

Biodiversity data are the foundation for conservation and managemet and taxonomy provides the reference system, skills and tools used to identify organisms. Species level data such as species richness, composition and diversity are common metrics. However, species level identification of organisms tends to be neglected within ecological work, especially within monitoring programmes, but also in conservation biology (Giangrande, 2003). This is because collection of species level data is time consuming, with identification of species-specific characteristics traditionally involving lengthy examination of samples using microscopy. In addition it is costly and species level data is almost impossible to collect if the taxa involved are species rich and difficult to identify (Báldi 1999). Other reasons why species level identification is neglected include the fact that sample collection can damage organisms, so diagnostic morphological features are lost, or that individuals may be in a life history stage or of a sex that does not have diagnostic morphological characteristics. Furthermore, the numbers of available expert taxonomists needed for species identification are in decline and have been for several decades. Species identification using molecular taxonomy where DNA is used as a marker is championed as a tool for resolving a range of morphological problems, such as the association of all life history stages, correlating male and female specimens to the same species and identifying partial specimens. Traditional taxonomy is built around morphological variations between species, with systematic inferences based upon shared physical characters. In molecular taxonomy on the other hand, proteins and genes are used to determine evolutionary relationships. ’DNA barcoding’ aims to provide an efficient method for species-level identification and it is thought that it will provide a powerful tool for taxonomic and biodiversity research (Hajibabaei et al. 2007). Cited strengths of a molecular based approach to species identification include the potential universality and objective nature of DNA data as taxonomic information, the usefulness of molecular data in animal groups characterized by morphological cryptic characters and the use of DNA sequence information to determine otherwise ‘unidentifiable’ biological material (such as incomplete specimens or immature specimens). Its aim is to increase the speed, precision and efficiency of field studies involving diverse and difficult to identify taxa and it has the potential to be automated to provide a rapid and consistently accurate supplementary identification system to traditional taxonomy. This project was a proof-of-concept study that investigated the feasibility of using DNA barcodes to differentiate closely related blackfly species of the genus Simulium. The longer term objective would be to apply such molecular approaches to organisms used in water quality monitoring and to biodiversity studies to provide a quick, robust but practical and cost effective tool for species identification. Great Britain is currently home to 33 morphospecies of blackfly many of which are morphologically close to other species and have been the cause of much systematic revision. In addition to evaluating the use of DNA barcodes in species identification, a non-destructive DNA extraction method was developed to preserve voucher pecimens that will allow a complete morphological classification to be carried after DNA extraction. Using molecular tools to differentiate closely related blackfly species of the genus Simulium v Finding an effective DNA barcode for an individual species involves accurate taxonomic identification and the retention of voucher specimens for future morphological studies. A rapid non-destructive method for DNA extraction from small insects was developed where no clean-up step was required prior to amplification and it was possible to extract DNA of sufficient quality in minutes retaining diagnostic morphological characteristics. For any molecular tool used for species discrimination, an important consideration is defining the specific genetic loci (e.g. the position of genes on a chromosome) to be monitored. All blackfly species in this study were successfully amplified with the standard barcoding coxI gene primer pair LCO1490 5'-GGT CAA CAA ATC ATA AAG ATA TTG G-3' and HCO2198 5'-TAA ACT TCA GGG TGA CCA AAA AAT CA-3' (Folmer et al. 1994) and we did not need to optimise or redesign the primer sequence

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

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

Acute Myeloid Leukemia

Acute myeloid leukemia (AML) is the most common type of leukemia. The Cancer Genome Atlas Research Network has demonstrated the increasing genomic complexity of acute myeloid leukemia (AML). In addition, the network has facilitated our understanding of the molecular events leading to this deadly form of malignancy for which the prognosis has not improved over past decades. AML is a highly heterogeneous disease, and cytogenetics and molecular analysis of the various chromosome aberrations including deletions, duplications, aneuploidy, balanced reciprocal translocations and fusion of transcription factor genes and tyrosine kinases has led to better understanding and identification of subgroups of AML with different prognoses. Furthermore, molecular classification based on mRNA expression profiling has facilitated identification of novel subclasses and defined high-, poor-risk AML based on specific molecular signatures. However, despite increased understanding of AML genetics, the outcome for AML patients whose number is likely to rise as the population ages, has not changed significantly. Until it does, further investigation of the genomic complexity of the disease and advances in drug development are needed. In this review, leading AML clinicians and research investigators provide an up-to-date understanding of the molecular biology of the disease addressing advances in diagnosis, classification, prognostication and therapeutic strategies that may have significant promise and impact on overall patient survival

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

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

Astronomical identification of CN-, the smallest observed molecular anion

We present the first astronomical detection of a diatomic negative ion, the cyanide anion CN-, as well as quantum mechanical calculations of the excitation of this anion through collisions with para-H2. CN- is identified through the observation of the J = 2-1 and J = 3-2 rotational transitions in the C-star envelope IRC +10216 with the IRAM 30-m telescope. The U-shaped line profiles indicate that CN-, like the large anion C6H-, is formed in the outer regions of the envelope. Chemical and excitation model calculations suggest that this species forms from the reaction of large carbon anions with N atoms, rather than from the radiative attachment of an electron to CN, as is the case for large molecular anions. The unexpectedly large abundance derived for CN-, 0.25 % relative to CN, makes likely its detection in other astronomical sources. A parallel search for the small anion C2H- remains so far unconclusive, despite the previous tentative identification of the J = 1-0 rotational transition. The abundance of C2H- in IRC +10216 is found to be vanishingly small, < 0.0014 % relative to C2H.Comment: 5 pages, 4 figures; accepted for publication in A&A Letter