AccuCor2 Isotope Natural Abundance Correction for Dual-Isotope Tracer Experiments

Stable isotope labeling techniques have been widely applied in the field of metabolomics and proteomics. Before the measured mass spectrum data can be used for quantitative analysis, it must be accurately corrected for isotope natural abundance and tracer isotopic impurity. Despite the increasing popularity of dual-isotope tracing strategy such as ¹³C-¹⁵N or ¹³C-²H, there is no accurate tool for correcting isotope natural abundance for such experiments. Here, we present AccuCor2 as an R-based tool to perform the correction for ¹³C-¹⁵N or ¹³C-²H labeling experiments. Our results show that the dual-isotope experiments often require a mass resolution that is high enough to resolve ¹³C and ¹⁵N or ¹³C and ²H.Otherwise the labeling pattern is not solvable. However, this mass resolution may not be sufficiently high to resolve other non-tracer elements such as oxygen or sulfur from the tracer elements. Therefore, we design AccuCor2 to perform the correction based on the actual mass resolution of the measurements. Using both simulated and experimental data, we show that AccuCor2 performs accurate and resolution dependent correction for dual-isotope tracer data.

AccuCor2 Isotope Natural Abundance Correction for Dual-Isotope Tracer Experiments

Stable isotope labeling techniques have been widely applied in the field of metabolomics and proteomics. Before the measured mass spectrum data can be used for quantitative analysis, it must be accurately corrected for isotope natural abundance and tracer isotopic impurity. Despite the increasing popularity of dual-isotope tracing strategy such as ¹³C-¹⁵N or ¹³C-²H, there is no accurate tool for correcting isotope natural abundance for such experiments. Here, we present AccuCor2 as an R-based tool to perform the correction for ¹³C-¹⁵N or ¹³C-²H labeling experiments. Our results show that the dual-isotope experiments often require a mass resolution that is high enough to resolve ¹³C and ¹⁵N or ¹³C and ²H.Otherwise the labeling pattern is not solvable. However, this mass resolution may not be sufficiently high to resolve other non-tracer elements such as oxygen or sulfur from the tracer elements. Therefore, we design AccuCor2 to perform the correction based on the actual mass resolution of the measurements. Using both simulated and experimental data, we show that AccuCor2 performs accurate and resolution dependent correction for dual-isotope tracer data.

>Corna - An Open Source Python Tool For Natural Abundance Correction In Isotope Tracer Experiments

BackgroundStable isotope-based approaches are used in the field of metabolomics for quantification and identification of metabolites, discovery of new pathways and measurement of intracellular fluxes. In these experiments, often performed with mass spectrometry (MS), data must be corrected for natural abundance of isotopes. Various stand-alone tools with their own separate data formats and learning curves exist for correction of data collected at different resolutions, for tandem MS, and for different number of tracer elements.ResultsWe present a Python package, Corna, that combines natural abundance correction workflows for several experimental conditions and can be used as a one-stop-shop for stable isotope labeled experiments. We validate the algorithms in Corna with published tools, where available, and include new features, such as correction of two tracer elements, that are not yet implemented in any existing software application as per our knowledge. We also present the integration of Corna with an existing open source peak integration software. The integrated workflow can reduce processing times for a typical stable isotope based workflow from days to hours for a familiar user.ConclusionsAlgorithmic advancements have been keeping up with the developments in mass spectrometry technologies and have been the focus of most existing tools for natural abundance correction. However, in this high throughput era, it is also important to recognize user experience, and integrated and reproducible workflows. Corna has been written in Python and is designed for users who have access to large amounts of data from different kinds of experiments and want to integrate a natural abundance correction tool seamlessly in their pipelines. The latest version of Corna can be accessed at https://github.com/raaisakuk/NA_Correction.

Extraction of Biological Hydroxyapatite from Tuna Fish Bone for Biomedical Applications

Natural hydroxyapatite (HAp) is known for its common use in biomedical applications including in orthopaedic and implantation. HAp can be extracted from natural resources such as eggshells, fish bones and coral. Annually, it is found that huge amount of tuna fish bones were thrown away and being wasted as results from great consumption of tuna fish. In this study, tuna fish bones were extracted and characterised to be used in biomedical applications. Specifically, tuna fish bones were cleaned, and calcined at high temperature of 700 °C, 900 °C and 1100 °C. Powders calcined at 700 °C showed pure HAp compared to powders calcined at 900 °C and 1100 °C which showed the presence of β-TCP. As temperature rising, the morphology of the powders also changes from spherical-shaped to irregular-shaped indicated the substitution of phosphate and calcium from the β-TCP which also influenced the ratio of Ca/P obtained. In this study, powders calcined at 700 °C obtained optimum Ca/P ratio of 1.60. Moreover, EDS analysis showed the presence of tracer elements such as Ca, Mg, Sr Na, K and Zn in all calcined samples. These elements can help improve the biocompatibility of the HAp and beneficial for biomedical applications.

Trace Element Composition of Snow Cover in Vicinity of Coal- Burning and Gas-Burning Boiler Houses as Used Fuel’s Environmental Performance Indicator

Emissions of rural villages’ boiler houses remain insufficiently studied in comparison with emissions of big urban heat power engineering objects. In this paper have been presented the results of comparative analysis for a dust pollution level and trace element composition of solid particles in vicinity of rural villages’ boiler houses distinguishing by technological parameters and the fuel’s type (coal or gas) based on the snow cover’s trace element composition study. It has been established that the dust load value relating to background in vicinity of different coal-burning boiler houses is varying and depends on fuel consumption volumes, availability of dust and gas trapping system, coal depository and vehicle park. The dust load value does not exceeded background in vicinity of gas- burning boiler houses no matter of their technological parameters. It has been demonstrated that the trace elements accumulation level in the samples from vicinity of coal-burning and gas-burning boiler houses depends on type, composition and flow rates of fuel, as well as from the fly ash composition and local emissions sources. Have been marked general tracer elements (Hg, Zn, Ni, Mo, Co, Ba, Sr) and specific ones (Cd, As, Sb, Pb, V) of man-made impact for different coal-burning boiler houses. Hg, As, Cd have been proposed as general tracer elements of man-made impact for coal-burning boiler houses. It has been stated that natural gas is the most environmental friendliness fuel in comparison with coal regardless of boiler house’s technological parameters.

Potential microbial contamination during sampling of permafrost soil assessed by tracers

Drilling and handling of permanently frozen soil cores without microbial contamination is of concern because contamination e.g. from the active layer above may lead to incorrect interpretation of results in experiments investigating potential and actual microbial activity in these low microbial biomass environments. Here, we present an example of how microbial contamination from active layer soil affected analysis of the potentially active microbial community in permafrost soil. We also present the development and use of two tracers: (1) fluorescent plastic microspheres and (2) Pseudomonas putida genetically tagged with Green Fluorescent Protein production to mimic potential microbial contamination of two permafrost cores. A protocol with special emphasis on avoiding microbial contamination was developed and employed to examine how far microbial contamination can penetrate into permafrost cores. The quantity of tracer elements decreased with depth into the permafrost cores, but the tracers were detected as far as 17 mm from the surface of the cores. The results emphasize that caution should be taken to avoid microbial contamination of permafrost cores and that the application of tracers represents a useful tool to assess penetration of potential microbial contamination into permafrost cores.