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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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Quantitative iTRAQ-based secretome analysis reveals species-specific and temporal shifts in carbon utilization strategies among manganese(II)-oxidizing Ascomycete fungi

Fungi generate a wide range of extracellular hydrolytic and oxidative enzymes and reactive metabolites, collectively known as the secretome, that synergistically drive plant litter decomposition in the environment. While secretome studies of model organisms have greatly expanded our knowledge of these enzymes, few have extended secretome characterization to environmental isolates or directly compared temporal patterns of enzyme utilization among diverse species. Thus, the mechanisms of carbon (C) degradation by many ubiquitous soil fungi remain poorly understood. Here we use a combination of iTRAQ proteomics and custom bioinformatic analyses to compare the protein composition of the secretomes of four manganese(II)-oxidizing Ascomycete fungi over a three-week time course. We demonstrate that although the fungi produce a similar suite of extracellular enzymes, they exhibit striking differences in the regulation of these enzymes among species and over time, revealing species-specific and temporal shifts in C utilization strategies as they degrade the same substrate. Specifically, our findings suggest that Paraconiothyrium sporulosum AP3s5-JAC2a and Alternaria alternata SRC1lrK2f employ sequential enzyme secretion patterns concomitant with decreasing resource availability, Stagonospora sp. SRC1lsM3a preferentially degrades proteinaceous substrate before switching to carbohydrates, and Pyrenochaeta sp. DS3sAY3a utilizes primarily peptidases to aggressively attack carbon sources in a concentrated burst. This work highlights the diversity of operative metabolic strategies among cellulose-degrading Ascomycetes and enhances our understanding of their role in C turnover in the environment.

59 BASIC BIOLOGICAL SCIENCES↗

Plant iTRAQ-based proteomics

We present a simple one-­pot extraction protocol, which rapidly isolates hydrophyllic metabolites, lipids, and proteins from the same pulverized plant sample. Also detailed is a global plant proteomics sample preparation method utilizing iTRAQ multiplexing reagents that enables deep proteome coverage due to the use of HPLC fractionation of the peptides prior to mass spectrometric analysis. We have successfully used this protocol on several different plant tissues (e.g., roots, stems, leaves) from different plants (e.g., sorghum, poplar, Arabidopsis, soybean), and have been able to successfully detect and quantify thousands of proteins. Multiplexing strategies such as iTRAQ and the bioinformatics strategy outlined here, ultimately provide insight into which proteins are significantly changed in abundance between two or more groups (e.g., control, perturbation). Our bioinformatics strategy yields z-­score values, which normalize the expression data into a format that can easily be cross-­compared with other expression data (i.e., metabolomics, transcriptomics) obtained from different analytical methods and instrumentation.

60 APPLIED LIFE SCIENCES↗

A review of imputation strategies for isobaric labeling-based shotgun proteomics

The throughput efficiency and increased depth of coverage provided by isobaric-labeled proteomics measurements have led to increased usage of these techniques. However, the structure of missing data is uniquely different than unlabeled studies. In this review, we compare the efficacy of nine imputation methods on a CPTAC proteomics iTRAQ dataset. Imputation methods were evaluated with regard to accuracy, variability, statistical hypothesis test inference and run time over datasets consisting of varying number of iTRAQ plexes and percentages of missing data. In general, expectation maximization and random forest imputation methods yielded the best performances, and constant-based methods performed poorly consistently across all dataset sizes and percentages of missing values. For datasets with small sample sizes and higher percentages of missing data, results indicate that statistical inference with no imputation may be preferable. Based on the findings in this review, there are core imputation methods that perform higher for isobaric-labeled proteomics data, but great care and consideration as to whether imputation should be used should be given for datasets comprised of a small number of samples, as well as to factors such as computational time and reproducibility of imputation values.

Bramer, Lisa M.↗

Comparative analysis of methicillin-sensitive and resistant Staphylococcus aureus exposed to emodin based on proteomic profiling

Highlights: • Emodin is effective against methicillin-sensitive and resistant Staphylococcus aureus strains. • Global proteomic profiling revealed 145 and 122 significant changes in MSSA and MRSA after emodin treatment, respectively. • Profiling interaction network analysis demonstrated emodin potentially targeted MRSA via multiple mechanisms. Emodin has a strong antibacterial activity, including methicillin-resistant Staphylococcus aureus (MRSA). However, the mechanism by which emodin induces growth inhibition against MRSA remains unclear. In this study, the isobaric tags for relative and absolute quantitation (iTRAQ) proteomics approach was used to investigate the modes of action of emodin on a MRSA isolate and methicillin-sensitive S. aureus ATCC29213(MSSA). Proteomic analysis showed that expression levels of 145 and 122 proteins were changed significantly in MRSA and MSSA, respectively, after emodin treatment. Comparative analysis of the functions of differentially expressed proteins between the two strains was performed via bioinformatics tools blast2go and STRING database. Proteins related to pyruvate pathway imbalance induction, protein synthesis inhibition, and DNA synthesis suppression were found in both methicillin-sensitive and resistant strains. Moreover, Interference proteins related to membrane damage mechanism were also observed in MRSA. Our findings indicate that emodin is a potential antibacterial agent targeting MRSA via multiple mechanisms.

60 APPLIED LIFE SCIENCES↗

Lenalidomide regulates osteocytes fate and related osteoclastogenesis via IL-1β/NF-κB/RANKL signaling

Highlights: • Lenalidomide regulated IL-1β induced osteocyte fate with decreased expressions of RANKL and Sclerostin. • Lenalidomide inhibited subsequent osteoclastogenesis via osteocytes. • Lenalidomide inactivated NF-κB signaling in osteocytes to reduce osteoclast formation. • Lenalidomide attenuated in vivo osteocyte apoptosis and following osteoclastogenesis in osteoarthritis mice. Osteolytic diseases are closely associated with osteocyte fate, indicating a more efficient and crucial role of osteocyte-targeting strategy in inhibiting osteoclastogenesis. Here, we investigated the effects of lenalidomide (Lena) on osteocyte fate in order to regulate osteoclastogenesis via effective cascade-controlling response. Our data revealed that lenalidomide treatment notably rescued IL-1β induced loss of osteocyte viability by inhibiting osteocyte apoptosis with decreased osteoclast-related factors, RANKL and Sclerostin, as demonstrated by the restricted osteoclast formation and reduced bone resorption. Additionally, iTRAQ assay revealed that IL-1β induced activation of NF-κB inhibitor α/β were remarkably downregulated by lenalidomide, showing that lenalidomide impaired NF-κB signaling in osteocytes for inhibiting the expression of osteoclast specific genes in osteoclasts, which was further confirmed by KEGG pathway analysis and Western blot. More interestingly, the in vivo analysis of osteocyte apoptosis and osteoclastogenesis in osteoarthritis mice model indicated a role of lenalidomide in the regulation of osteocyte fate and the consequent inhibition of RANKL-induced osteoclastogenesis. Together, these results suggest that lenalidomide regulates osteocyte fate by attenuating IL-1β/NF-κB signaling, thereby inhibiting RANKL expression for the attenuated osteoclastogenesis both in vitro and vivo, indicating a more efficient remedy among future anti-osteoclastogenesis approaches.

60 APPLIED LIFE SCIENCES↗

Screening and identification of potential protein biomarkers for evaluating the efficacy of intensive therapy in pulmonary tuberculosis

Highlights: • The one-year cure rate was significantly higher in sputum negative patients after 2-months intensive therapy. • Four potential biomarkers were found for evaluating the efficacy of 2-months intensive therapy in TB patients. • CO7 and ANGT could serve as potential biomarkers to evaluate the bacteriological condition of Mycobacterium tuberculosis after intensive therapy. This research aimed to discover potential biomarkers for evaluating the therapeutic efficacy of intensive therapy in pulmonary tuberculosis (TB). Protein profiles in 2-months intensively treated TB patients, untreated TB patients, and healthy controls were investigated with iTRAQ-2DLC-MS/MS technique. 71 differential proteins were identified in 2-months intensively treated TB patients. Significant differences in complement component C7 (CO7), apolipoprotein A-IV (APOA4), apolipoprotein C-II (APOC2), and angiotensinogen (ANGT) were found by ELISA validation. CO7 and ANGT were also found significantly different in sputum negative patients, compared with sputum positive patients after intensive treatment. Clinical analysis showed that after 2-months intensive treatment several indicators were significantly changed, and the one-year cure rate of sputum negative patients were significantly higher than sputum positive patients. Diagnostic models consisting of APOC2, CO7 and APOA4 were established to distinguish intensively treated TB patients from untreated TB patients and healthy controls with the AUC value of 0.910 and 0.935. Meanwhile, ANGT and CO7 were combined to identify sputum negative and sputum positive TB patients after intensive treatment with 89.36% sensitivity, 71.43% specificity, and the AUC value of 0.853. The results showed that APOC2, CO7, APOA4, and ANGT may be potential biomarkers for evaluating the efficacy of intensive anti-TB therapy.

60 APPLIED LIFE SCIENCES↗

Quantitative phosphoproteomics reveals GTBP-1 regulating C.elegans lifespan at different environmental temperatures

Highlights: • Comprehensive quantitative phosphoproteomics study of C.elegans during aging under different temperatures. • Phosphoproteomics analysis identified important proteins and signaling pathways. • The kinases CK2, MAPK and CAMK2 might play important roles in aging. • Functional experiments confirm that GTBP-1 could regulate C.elegans lifespan. • An important resource for future studies of protein phosphorylation in C.elegans. Temperature is one of the primary environmental factors that affect aging, in which protein phosphorylation is an important regulator. Currently, the understanding of phosphorylation events in regulatory networks during aging has remained rather limited. Herein, the phosphoproteomes of C.elegans of different age groups cultured at 20 °C (natural aging) and 25 °C (accelerated aging) were analyzed. Through using the iTRAQ-labeled phosphoproteomics method, 2375 phosphoproteins and 9063 phosphosites were identified. Volcano plots illustrated that 208 proteins during natural aging and 130 proteins during accelerated aging, were significantly changed. Gene ontology and pathway analysis revealed that these proteins were mainly involved in translation, development, metabolisms, and animal behavior processes. Moreover, our results uncovered those kinases CK2, MAPK and CAMK2 might play important roles in aging regulation. Functional experiments confirm that the candidated phosphoprotein GTBP-1 could regulate C.elegans lifespan at 20 °C or 25 °C and is more resistant to heat and oxidative stresses. In summary, our results provided an important resource for future studies of protein phosphorylation in worms. Data are available via ProteomeXchange with identifier PXD009661.

60 APPLIED LIFE SCIENCES↗

Quality Assessments of Long-Term Quantitative Proteomic Analysis of Breast Cancer Xenograft Tissues

The identification of protein biomarkers requires large-scale analysis of human specimens to achieve statistical significance. In this study, we evaluated the long-term reproducibility of an iTRAQ (isobaric tags for relative and absolute quantification) based quantitative proteomics strategy using one channel for universal normalization across all samples. A total of 307 liquid chromatography tandem mass spectrometric (LC-MS/MS) analyses were completed, generating 107 one-dimensional (1D) LC-MS/MS datasets and 8 offline two-dimensional (2D) LC-MS/MS datasets (25 fractions for each set) for human-in-mouse breast cancer xenograft tissues representative of basal and luminal subtypes. Such large-scale studies require the implementation of robust metrics to assess the contributions of technical and biological variability in the qualitative and quantitative data. Accordingly, we developed a quantification confidence score based on the quality of each peptide-spectrum match (PSM) to remove quantification outliers from each analysis. After combining confidence score filtering and statistical analysis, reproducible protein identification and quantitative results were achieved from LC-MS/MS datasets collected over a 16 month period.

Environmental Molecular Sciences Laboratory↗

Reproducible workflow for multiplexed deep-scale proteome and phosphoproteome analysis of tumor tissues by liquid chromatography–mass spectrometry

Here we present an optimized workflow for global proteome and phosphoproteome analysis of tissues or cell lines that uses isobaric tags (TMT (tandem mass tags)-10) for multiplexed analysis and relative quantification, and provides 3×higher throughput than iTRAQ (isobaric tags for absolute and relative quantification)-4-based methods with high intraand inter-laboratory reproducibility. The workflow was systematically characterized and benchmarked across three independent laboratories using two distinct breast cancer subtypes from patient-derived xenograft models to enable assessment of proteome and phosphoproteome depth and quantitative reproducibility. Each plex consisted of ten samples, each being 300 µg of peptide derived from <50 mg of wet-weight tissue. Of the 10,000 proteins quantified per sample, we could distinguish 7,700 human proteins derived from tumor cells and 3100 mouse proteins derived from the surrounding stroma and blood. The maximum deviation across replicates and laboratories was <7%, and the interlaboratory correlation for TMT ratio–based comparison of the two breast cancer subtypes was r > 0.88. The maximum deviation for the phosphoproteome coverage was <24% across laboratories, with an average of >37,000 quantified phosphosites per sample and differential quantification correlations of r > 0.72. The full procedure, including sample processing and data generation, can be completed within 10 d for ten tissue samples, and 100 samples can be analyzed in ~4 months using a single LC-MS/MS instrument. The high quality, depth, and reproducibility of the data obtained both within and across laboratories should enable new biological insights to be obtained from mass spectrometry-based proteomics analyses of cells and tissues together with proteogenomic data integration.

Mertins, Philipp↗

Biochemical Mechanisms and Associated Biomolecular Signatures Underlying Energy Strategies of Geobacter Sulfurreducens

To provide the scientific understanding required to allow DOE sites to incorporate relevant biological, chemical, and physical processes into decisions concerning environmental remediation, a fundamental understanding of the controls on micro-organism growth in the subsurface is necessary. Specifically, mobility of metals in the environment, including chromium, technetium and uranium, is greatly affected by the process of dissimilatory metal reduction (DMR). DMR has been shown to be an important biological activity controlling contaminant mobility in the subsurface at many DOE sites. Long-term maintenance of DMR at constant rates must rely upon steady fluxes of electron donors to provide the maintenance energy needed by organisms such as Geobacter sulfurreducens to maintain steady state populations in the subsurface. At present, much effort has been put forth to develop biomolecular signatures which inform on the relevant biological processes at DOE field sites. These signatures are also being developed in defined laboratory conditions to which the field data can be compared to. These signatures include metagenomic, metatranscriptomic and proteomic characterization. While the relevant processes involve reduction of metal contaminants, we suggest that the predominant biochemistry that impacts the biomolecular signature is nutrient availability/limitation. As such, the present proposal aims at characterizing the survival strategy of Geobacter and obtaining biomolecular signatures that would reflect on its energy flux status. In addition, we lack the fundamental knowledge needed to answer fundamental questions such as these: What influxes of electron donors are required to maintain a growing versus a non-growing population of Geobacter? How do changes in nutrient availability or other environmental conditions such as pH and ionic strength affect such required electron-donor influxes? How are these electron-donor influxes controlled by availability and nature of electron acceptors? Under survival conditions, where availability of electron acceptors and nutrients are extremely low, what physiological and genetic modifications occur in Geobacter to enable long-term survival? How do these changes affect the required electron-donor influxes? Is it possible to relate the metabolic activities of Geobacter living under survival mode to the required fluxes of electron donors? What conceptual models can be used to predict maintenance energies of Geobacter under different phases of growth when measured under different environmental conditions? How can these models help the DOE predict the long-term evolution of contaminated sites? We outline a strategy to tackle these questions and lay the framework for DOE to make long-term predictions concerning DMR in the subsurface. We will test the following hypothesis: Geobacter requires different fluxes of substrate for metabolism when existing under growth, stationary, or survival modes, and these substrate fluxes can be related to specific metabolic activities utilized under different geochemical conditions. Our project has two specific objectives: i) Determine the survival characteristics of Geobacter under long-term stationary phase by characterize the physiological response of Geobacter in growth, stationary, and survival phases using genomic sequencing, DNA microarray chips and iTRAQ (proteomics) and relate these responses to the measured substrate fluxes; ii) Determination of growth yield and maintenance energy. While site-specific studies are necessary for site-specific remediation, our work will provide the fundamental knowledge necessary for long-term stewardship of all DOE sites where contaminant mobility is affected by dissimilatory metal reduction.

54 ENVIRONMENTAL SCIENCES↗

Identifying a novel pathway for extracellular electron uptake in Methanosarcina barkeri using shotgun

The overarching goal of this project was to identify the genetic and/or enzymatic basis for extracellular electron uptake in Methanosarcina barkeri—an organism we previously characterized to be capable of this process using poised potential electrodes and a range of electrochemical techniques. In our first aim, we will utilized proteomic techniques that labels extracellular proteins with free amine groups with biotin and perform a selective purification of these proteins from the rest of the proteome. These were identified using mass spectrometry, providing us insight into the identity of the cell surface proteins, including redox active proteins present during extracellular electron uptake. We will also used an isobaric tagging technique (iTRAQ labeling) of proteomes from different experiment conditions to look at differential proteins expression and better understand the total pathway involved in extracellular electron uptake coupled to methanogenesis. In our final aim, we will investigated the electrochemical nature of electron uptake in co-cultures, compared to our pure culture data sets. We predict the process of electron uptake from electrodes replicates what goes on in nature when these organisms for co-cultures with electrogenic microbes such as Geobacter, and to test this hypothesis we have begun to probe co-cultures electrochemically during direct interspecies electron transfer. Our final aim took much longer than expected due to challenges replicating co-cultures between Geobacter metallireducens and Methanosarcina barkeri. We found the major problem with this work was the inability of the M. barkeri strain we used (and we tried strains from three different labs) to successfully grow on acetate in the absence of hydrogen. As such, we began to use the strain Methanosarcina acetivorans—another close relative that specializes on acetate growth. We are currently in the process of comparing electrochemical observations of this microorganism between pure and co-culture experiments.

59 BASIC BIOLOGICAL SCIENCES↗