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At least 19 records

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↗

Elevated host lipid metabolism revealed by iTRAQ-based quantitative proteomic analysis of cerebrospinal fluid of tuberculous meningitis patients

Purpose: Tuberculous meningitis (TBM) remains to be one of the most deadly infectious diseases. The pathogen interacts with the host immune system, the process of which is largely unknown. Various cellular processes of Mycobacterium tuberculosis (MTB) centers around lipid metabolism. To determine the lipid metabolism related proteins, a quantitative proteomic study was performed here to identify differential proteins in the cerebrospinal fluid (CSF) obtained from TBM patients (n = 12) and healthy controls (n = 12). Methods: CSF samples were desalted, concentrated, labelled with isobaric tags for relative and absolute quantitation (iTRAQ™), and analyzed by multi-dimensional liquid chromatography-tandem mass spectrometry (LC-MS/MS). Gene ontology and proteomic phenotyping analysis of the differential proteins were conducted using Database for Annotation, Visualization, and Integrated Discovery (DAVID) Bioinformatics Resources. ApoE and ApoB were selected for validation by ELISA. Results: Proteomic phenotyping of the 4 differential proteins was invloved in the lipid metabolism. ELISA showed significantly increased ApoB levels in TBM subjects compared to healthy controls. Area under the receiver operating characteristic curve analysis demonstrated ApoB levels could distinguish TBM subjects from healthy controls and viral meningitis subjects with 89.3% sensitivity and 92% specificity. Conclusions: CSF lipid metabolism disregulation, especially elevated expression of ApoB, gives insights into the pathogenesis of TBM. Further evaluation of these findings in larger studies including anti-tuberculosis medicated and unmedicated patient cohorts with other center nervous system infectious diseases is required for successful clinical translation. - Highlights: • The first proteomic study on the cerebrospinal fluid of tuberculous meningitis patients using iTRAQ. • Identify 4 differential proteins invloved in the lipid metabolism. • Elevated expression of ApoB gives insights into the pathogenesis of TBM.

60 APPLIED LIFE SCIENCES↗

Mining the human urine proteome for monitoring renal transplant injury

The human urinary proteome reflects systemic and inherent renal injury perturbations and can be analyzed to harness specific biomarkers for different kidney transplant injury states. 396 unique urine samples were collected contemporaneously with an allograft biopsy from 396 unique kidney transplant recipients. Centralized, blinded histology on the graft was used to classify matched urine samples into categories of acute rejection (AR), chronic allograft nephropathy (CAN), BK virus nephritis (BKVN), and stable graft (STA). Liquid chromatography–mass spectrometry (LC-MS) based proteomics using iTRAQ based discovery (n=108) and global label-free LC-MS analyses of individual samples (n=137) for quantitative proteome assessment were used in the discovery step. Selected reaction monitoring (SRM) was applied to identify and validate minimal urine protein/peptide biomarkers to accurately segregate organ injury causation and pathology on unique urine samples (n=151). A total of 958 proteins were initially quantified by iTRAQ, 87% of which were also identified among 1574 urine proteins detected in LC-MS validation. 103 urine proteins were significantly (p<0.05) perturbed in injury and enriched for humoral immunity, complement activation, and lymphocyte trafficking. A set of 131 peptides corresponding to 78 proteins were assessed by SRM for their significance in an independent sample cohort. A minimal set of 35 peptides mapping to 33 proteins, were modeled to segregate different injury groups (AUC =93% for AR, 99% for CAN, 83% for BKVN). Urinary proteome discovery and targeted validation identified urine protein fingerprints for non-invasive differentiation of kidney transplant injuries, thus opening the door for personalized immune risk assessment and therapy.

Environmental Molecular Sciences Laboratory↗

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.↗

Reproducibility of Differential Proteomic Technologies in CPTAC Fractionated Xenografts

The NCI Clinical Proteomic Tumor Analysis Consortium (CPTAC) employed a pair of reference xenograft proteomes for initial platform validation and ongoing quality control of its data collection for The Cancer Genome Atlas (TCGA) tumors. These two xenografts, representing basal and luminal-B human breast cancer, were fractionated and analyzed on six mass spectrometers in a total of 46 replicates divided between iTRAQ and label-free technologies, spanning a total of 1095 LC-MS/MS experiments. These data represent a unique opportunity to evaluate the stability of proteomic differentiation by mass spectrometry over many months of time for individual instruments or across instruments running dissimilar workflows. We evaluated iTRAQ reporter ions, label-free spectral counts, and label-free extracted ion chromatograms as strategies for data interpretation. From these assessments we found that differential genes from a single replicate were confirmed by other replicates on the same instrument from 61-93% of the time. When comparing across different instruments and quantitative technologies, differential genes were reproduced by other data sets from 67-99% of the time. Projecting gene differences to biological pathways and networks increased the similarities. These overlaps send an encouraging message about the maturity of technologies for proteomic differentiation.

Environmental Molecular Sciences Laboratory↗

Large-scale proteome analysis of abscisic acid and ABSCISIC ACID INSENSITIVE3-dependent proteins related to desiccation tolerance in Physcomitrella patens

Desiccation tolerance is an ancestral feature of land plants and is still retained in non-vascular plants such as bryophytes and some vascular plants. However, except for seeds and spores, this trait is absent in vegetative tissues of vascular plants. Although many studies have focused on understanding the molecular basis underlying desiccation tolerance using transcriptome and proteome approaches, the critical molecular differences between desiccation tolerant plants and non-desiccation plants are still not clear. The moss Physcomitrella patens cannot survive rapid desiccation under laboratory conditions, but if cells of the protonemata are treated by the phytohormone abscisic acid (ABA) prior to desiccation, it can survive 24 h exposure to desiccation and regrow after rehydration. The desiccation tolerance induced by ABA (AiDT) is specific to this hormone, but also depends on a plant transcription factor ABSCISIC ACID INSENSITIVE3 (ABI3). Here we report the comparative proteomic analysis of AiDT between wild type and ABI3 deleted mutant (Δabi3) of P. patens using iTRAQ (Isobaric Tags for Relative and Absolute Quantification). From a total of 1980 unique proteins that we identified, only 16 proteins are significantly altered in Δabi3 compared to wild type after desiccation following ABA treatment. Among this group, three of the four proteins that were severely affected in Δabi3 tissue were Arabidopsis orthologous genes, which were expressed in maturing seeds under the regulation of ABI3. These included a Group 1 late embryogenesis abundant (LEA) protein, a short-chain dehydrogenase, and a desiccation-related protein. Our results suggest that at least three of these proteins expressed in desiccation tolerant cells of both Arabidopsis and the moss are very likely to play important roles in acquisition of desiccation tolerance in land plants. Furthermore, our results suggest that the regulatory machinery of ABA- and ABI3-mediated gene expression for desiccation tolerance might have evolved in ancestral land plants before the separation of bryophytes and vascular plants. - Highlights: • Large-scale proteomics highlighted proteins related to plant desiccation tolerance. • The proteins were regulated by both the phytohormone ABA and ABI3. • The proteins accumulated in desiccation tolerant cells of both Arabidopsis and moss. • Evolutionary origin of regulatory machinery for desiccation tolerance is proposed.

60 APPLIED LIFE SCIENCES↗

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↗

Integrative analyses of miRNA and proteomics identify potential biological pathways associated with onset of pulmonary fibrosis in the bleomycin rat model

To determine miRNAs and their predicted target proteins regulatory networks which are potentially involved in onset of pulmonary fibrosis in the bleomycin rat model, we conducted integrative miRNA microarray and iTRAQ-coupled LC-MS/MS proteomic analyses, and evaluated the significance of altered biological functions and pathways. We observed that alterations of miRNAs and proteins are associated with the early phase of bleomycin-induced pulmonary fibrosis, and identified potential target pairs by using ingenuity pathway analysis. Using the data set of these alterations, it was demonstrated that those miRNAs, in association with their predicted target proteins, are potentially involved in canonical pathways reflective of initial epithelial injury and fibrogenic processes, and biofunctions related to induction of cellular development, movement, growth, and proliferation. Prediction of activated functions suggested that lung cells acquire proliferative, migratory, and invasive capabilities, and resistance to cell death especially in the very early phase of bleomycin-induced pulmonary fibrosis. The present study will provide new insights for understanding the molecular pathogenesis of idiopathic pulmonary fibrosis. - Highlights: • We analyzed bleomycin-induced pulmonary fibrosis in the rat. • Integrative analyses of miRNA microarray and proteomics were conducted. • We determined the alterations of miRNAs and their potential target proteins. • The alterations may control biological functions and pathways in pulmonary fibrosis. • Our result may provide new insights of pulmonary fibrosis.

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↗

Patterns of gene expression associated with recovery and injury in heat-stressed rats

Background: The in vivo gene response associated with hyperthermia is poorly understood. Here, we perform a global, multiorgan characterization of the gene response to heat stress using an in vivo conscious rat model. Results: We heated rats until implanted thermal probes indicated a maximal core temperature of 41.8°C (T c,Max ). We then compared transcriptomic profiles of liver, lung, kidney, and heart tissues harvested from groups of experimental animals at T c,Max , 24 hours, and 48 hours after heat stress to time-matched controls kept at an ambient temperature. Cardiac histopathology at 48 hours supported persistent cardiac injury in three out of six animals. Microarray analysis identified 78 differentially expressed genes common to all four organs at T c,Max . Self-organizing maps identified gene-specific signatures corresponding to protein-folding disorders in heat-stressed rats with histopathological evidence of cardiac injury at 48 hours. Quantitative proteomics analysis by iTRAQ (isobaric tag for relative and absolute quantitation) demonstrated that differential protein expression most closely matched the transcriptomic profile in heat-injured animals at 48 hours. Calculation of protein supersaturation scores supported an increased propensity of proteins to aggregate for proteins that were found to be changing in abundance at 24 hours and in animals with cardiac injury at 48 hours, suggesting a mechanistic association between protein misfolding and the heat-stress response. Conclusions: Pathway analyses at both the transcript and protein levels supported catastrophic deficits in energetics and cellular metabolism and activation of the unfolded protein response in heat-stressed rats with histopathological evidence of persistent heat injury, providing the basis for a systems-level physiological model of heat illness and recovery.

59 BASIC BIOLOGICAL SCIENCES↗

Experimental Systems-Biology Approaches for Clostridia-Based Bioenergy Production

This is the final project report for project "Experimental Systems-Biology Approaches for Clostridia-Based Bioenergy Production" for the funding period of 9/1/12 to 2/28/2015 (three years with a 6-month no-cost extension) OVERVIEW AND PROJECT GOALS The bottleneck of achieving higher rates and titers of toxic metabolites (such as solvents and carboxylic acids that can used as biofuels or biofuel precursors) can be overcome by engineering the stress response system. Thus, understanding and modeling the response of cells to toxic metabolites is a problem of great fundamental and practical significance. In this project, our goal is to dissect at the molecular systems level and build models (conceptual and quantitative) for the stress response of C. acetobutylicum (Cac) to its two toxic metabolites: butanol (BuOH) and butyrate (BA). Transcriptional (RNAseq and microarray based), proteomic and fluxomic data and their analysis are key requirements for this goal. Transcriptional data from mid-exponential cultures of Cac under 4 different levels of BuOH and BA stress was obtained using both microarrays (Papoutsakis group) and deep sequencing (RNAseq; Meyers and Papoutsakis groups). These two sets of data do not only serve to validate each other, but are also used for identification of stress-induced changes in transcript levels, small regulatory RNAs, & in transcriptional start sites. Quantitative proteomic data (Lee group), collected using the iTRAQ technology, are essential for understanding of protein levels and turnover under stress and the various protein-protein interactions that orchestrate the stress response. Metabolic flux changes (Antoniewicz group) of core pathways, which provide important information on the re-allocation of energy and carbon resources under metabolite stress, were examined using 13C-labelled chemicals. Omics data are integrated at different levels and scales. At the metabolic-pathway level, omics data are integrated into a 2nd generation genome-scale model (GSM) (Maranas group). Omics data are also integrated using bioinformatics (Wu and Huang group), whereby regulatory details of gene and protein expression, protein-protein interactions and metabolic flux regulation are incorporated. The PI (Papoutsakis) facilitated project integration through monthly meeting and reports, conference calls, and collaborative manuscript preparation. The five groups collaborated extensively and made a large number of presentations in national and international meetings. It has also published several papers, with several more in the preparation stage. Several PhD, MS and postdoctoral students were trained as part of this collaborative and interdisciplinary project.

09 BIOMASS FUELS↗