Atmo-ecometabolomics : a novel atmospheric particle chemical characterization methodology for ecological research

Aerosol particles play important roles in processes controlling the composition of the atmosphere and function of ecosystems. A better understanding of the composition of aerosol particles is beginning to be recognized as critical for ecological research to further comprehend the link between aerosols and ecosystems. While chemical characterization of aerosols has been practiced in the atmospheric science community, detailed methodology tailored to the needs of ecological research does not exist yet. In this study, we describe an efficient methodology (atmo-ecometabolomics), in step-by-step details, from the sampling to the data analyses, to characterize the chemical composition of aerosol particles, namely atmo-metabolome. This method employs mass spectrometry platforms such as liquid and gas chromatography mass spectrometries (MS) and Fourier transform ion cyclotron resonance MS (FT-ICR-MS). For methodology evaluation, we analyzed aerosol particles collected during two different seasons (spring and summer) in a low-biological-activity ecosystem. Additionally, to further validate our methodology, we analyzed aerosol particles collected in a more biologically active ecosystem during the pollination peaks of three different representative tree species. Our statistical results showed that our sampling and extraction methods are suitable for characterizing the atmo-ecometabolomes in these two distinct ecosystems with any of the analytical platforms. Datasets obtained from each mass spectrometry instrument showed overall significant differences of the atmo-ecometabolomes between spring and summer as well as between the three pollination peak periods. Furthermore, we have identified several metabolites that can be attributed to pollen and other plant-related aerosol particles. We additionally provide a basic guide of the potential use ecometabolomic techniques on different mass spectrometry platforms to accurately analyze the atmo-ecometabolomes for ecological studies. Our method represents an advanced novel approach for future studies in the impact of aerosol particle chemical compositions on ecosystem structure and function and biogeochemistry

Community proteogenomics reveals the systemic impact of phosphorus availability on microbial functions in tropical soil.

Phosphorus is a scarce nutrient in many tropical ecosystems, yet how soil microbial communities cope with growth-limiting phosphorus deficiency at the gene and protein levels remains unknown. Here, we report a metagenomic and metaproteomic comparison of microbial communities in phosphorus-deficient and phosphorus-rich soils in a 17-year fertilization experiment in a tropical forest. The large-scale proteogenomics analyses provided extensive coverage of many microbial functions and taxa in the complex soil communities. A greater than fourfold increase in the gene abundance of 3-phytase was the strongest response of soil communities to phosphorus deficiency. Phytase catalyses the release of phosphate from phytate, the most recalcitrant phosphorus-containing compound in soil organic matter. Genes and proteins for the degradation of phosphorus-containing nucleic acids and phospholipids, as well as the decomposition of labile carbon and nitrogen, were also enhanced in the phosphorus-deficient soils. In contrast, microbial communities in the phosphorus-rich soils showed increased gene abundances for the degradation of recalcitrant aromatic compounds, transformation of nitrogenous compounds and assimilation of sulfur. Overall, these results demonstrate the adaptive allocation of genes and proteins in soil microbial communities in response to shifting nutrient constraints

Identification of a putative protein-profile associating with tamoxifen therapy-resistance in breast cancer

Tamoxifen-resistance is a major cause of death in patients with recurrent breast cancer. Current clinical parameters can correctly predict therapy response in only half of the treated patients. Identification of proteins that associate with tamoxifen-resistance is a first step towards better response prediction and tailored treatment of patients. In the present study we aimed to identify putative protein biomarkers indicative of tamoxifen therapy-resistance in breast cancer, using nanoLC-FTICR MS. Comparative proteome analysis was performed on ~5,500 pooled tumor cells obtained through laser capture microdissection from two independently processed data sets (n=24 and n=27) of tamoxifen therapy-sensitive and -resistant tumors. Peptide and protein identifications were acquired by matching mass and elution time features to information in previously generated accurate mass and time tag reference data bases. A total of 17,263 unique peptides were identified that corresponded to 2,556 non-redundant proteins identified with >=2 peptides. From this total, 1,713 protein

An Empirical Strategy for Characterizing Bacterial Proteomes across Species in the Absence of Genomic Sequences

Global protein identification through current proteomics methods typically depends on the availability of sequenced genomes. In spite of increasingly high throughput sequencing technologies, this information is not available for every microorganism and rarely available for entire microbial communities. Nevertheless, the protein-level homology that exists between related bacteria makes it possible to extract biological information from the proteome of an organism or microbial community by using the genomic sequences of a near neighbor organism. Here, we demonstrate a trans-organism search strategy for determining the extent to which near-neighbor genome sequences can be applied to identify proteins in unsequenced environmental isolates. In proof of concept testing, we found that within a CLUSTAL W distance of 0.089, near-neighbor genomes successfully identified a high percentage of proteins within an organism. Application of this strategy to characterize environmental bacterial isolates lacking sequenced genomes, but having 16S rDNA sequence similarity to Shewanella resulted in the identification of 300–500 proteins in each strain. The majority of identified pathways mapped to core processes, as well as to processes unique to the Shewanellae, in particular to the presence of c-type cytochromes. Examples of core functional categories include energy metabolism, protein and nucleotide synthesis and cofactor biosynthesis, allowing classification of bacteria by observation of conserved processes. Additionally, within these core functionalities, we observed proteins involved in the alternative lactate utilization pathway, recently described in Shewanella

Photoelectron Spectra, MNDO Calculations and Electronic Structure of Some Saturated Steroids

Photoelectron (PE) spectra in conection with semiempirical MNDO SCF MO calculations (assuming validity of Koopmans\u27theorem) and empirical arguments (i. e. composite molecule method) are used to derive (valence) electron structure of 5a-androstane (1), 5a-androstan-3-one (2), 5a-androstan-11-one (3), 5aandrostan- 17-one (4), 5a-androstane-3,17-dione (5) and 5a-androstane-3,11,17-trione (6)

High mass accuracy and high mass resolving power FT-ICR secondary ion mass spectrometry for biological tissue imaging

Biological tissue imaging by secondary ion mass spectrometry has seen rapid development with the commercial availability of polyatomic primary ion sources. Endogenous lipids and other small bio-molecules can now be routinely mapped on the sub-micrometer scale. Such experiments are typically performed on time-of-flight mass spectrometers for high sensitivity and high repetition rate imaging. However, such mass analyzers lack the mass resolving power to ensure separation of isobaric ions and the mass accuracy for elemental formula assignment based on exact mass measurement. We have recently reported a secondary ion mass spectrometer with the combination of a C60 primary ion gun with a Fourier transform ion cyclotron resonance mass spectrometer (FT-ICR MS) for high mass resolving power, high mass measurement accuracy, and tandem mass spectrometry capabilities. In this work, high specificity and high sensitivity secondary ion FT-ICR MS was applied to chemical imaging of biological tissue. An entire rat brain tissue was measured with 150 μm spatial resolution (75 μm primary ion spot size) with mass resolving power (m/Δm50%) of 67,500 (at m/z 750) and rootmean- square measurement accuracy less than two partsper- million for intact phospholipids, small molecules and fragments. For the first time, ultra-high mass resolving power SIMS has been demonstrated, with m/Δm50%> 3,000,000. Higher spatial resolution capabilities of the platform were tested at a spatial resolution of 20 μm. The results represent order of magnitude improvements in mass resolving power and mass measurement accuracy for SIMS imaging and the promise of the platform for ultra-high mass resolving power and high spatial resolution imaging

High mass accuracy and high mass resolving power FT-ICR secondary ion mass spectrometry for biological tissue imaging

Biological tissue imaging by secondary ion mass spectrometry has seen rapid development with the commercial availability of polyatomic primary ion sources. Endogenous lipids and other small bio-molecules can now be routinely mapped on the sub-micrometer scale. Such experiments are typically performed on time-of-flight mass spectrometers for high sensitivity and high repetition rate imaging. However, such mass analyzers lack the mass resolving power to ensure separation of isobaric ions and the mass accuracy for elemental formula assignment based on exact mass measurement. We have recently reported a secondary ion mass spectrometer with the combination of a C60 primary ion gun with a Fourier transform ion cyclotron resonance mass spectrometer (FT-ICR MS) for high mass resolving power, high mass measurement accuracy, and tandem mass spectrometry capabilities. In this work, high specificity and high sensitivity secondary ion FT-ICR MS was applied to chemical imaging of biological tissue. An entire rat brain tissue was measured with 150 μm spatial resolution (75 μm primary ion spot size) with mass resolving power (m/Δm50%) of 67,500 (at m/z 750) and rootmean- square measurement accuracy less than two partsper- million for intact phospholipids, small molecules and fragments. For the first time, ultra-high mass resolving power SIMS has been demonstrated, with m/Δm50%> 3,000,000. Higher spatial resolution capabilities of the platform were tested at a spatial resolution of 20 μm. The results represent order of magnitude improvements in mass resolving power and mass measurement accuracy for SIMS imaging and the promise of the platform for ultra-high mass resolving power and high spatial resolution imaging