APRS2017 program - AuPA · P3: Dolly Mushahary, Univ. Nat. Res. Life Sci. Vienna: 2D-DIGE of...

Austrian Proteomic and

Metabolomic Research Symposium Special focus on

Integration of Proteomics and Metabolomics

APRS 2017

Graz, Austria

September 6th

-8th

, 2017

Medical University of Graz, Hörsaalzentrum,

Auenbruggerplatz 15, 8036 Graz

1

APRS 2017 Program

Wed, Sep. 6

th 2017

Registration (& mount posters)

14.00-14.45 Foyer

Opening: Caroline Schober-Trummler, Vice Rector Med.

Univ. Graz

14.45-15.00 Lecture Hall D

Scientific Session 1: Cancer Metabolism

Chairs: Ruth Birner-Gruenberger and Tobias Madl, Med. Univ.

Graz & Omics Center Graz

15:00-18:00 Lecture Hall D

15:00-15:45 Key note lecture 1: Boudewijn MT Burgering,

UMC Utrecht: Metabolic interplay in the stem cell niche of

the small intestine

15:45-16:05 Short talk 1: Besnik Muqaku, Univ. Vienna:

Multi-omics Analysis of Serum Samples Demonstrates

Reprogramming of Organ Functions Via Systemic Calcium

Mobilization and Platelet Activation in Metastatic

Melanoma

16:05-16:25 Short talk 2: Tamara Tomin, Med. Univ. Graz:

Adipose triglyceride lipase (ATGL) promotes oncogenic

signalling resulting in more aggressive cancer phenotype in

lung carcinoma cells

16:25-16:45 Short talk 3: Rupert Mayer, Univ. Vienna: Aging-

related proteome alterations in B cells may predispose for

chronic lymphocytic leukemia

2

16:45-17:05 Short talk 4: Katharina Leitner, Med. Univ. Graz:

Glyceroneogenesis is utilized for biomembrane synthesis in

glucose-deprived cancer cells

17:05-17:50 Key note lecture 2: Michael Wakelam,

Babraham Institute, Cambridge: Lipidomic analysis

identifying potential therapeutic targets

Posters & Drinks (presenters @ posters)

17:50-19:00 Lecture Hall E1

Get together (Food & Drinks)

19:00-21:00 Foyer

Thu, Sep. 7

th 2017

Scientific Session 2: Technologies & Methods

Chair: Taras Stasyk, Univ. Innsbruck


09:00-9:45 Key note lecture 3: Bernd Wollscheid, ETH Zürich:

Decoding Ligand Receptor Interactions

09:45-10:05 Short talk 5: Matthias Schittmayer, Med. Univ.

Graz: Resolution ladder for high resolution mass

spectrometry

10:05-10:25 Short talk 6: Sarah Stryeck, Med. Univ. Graz:

NMR spectroscopy enables simultaneous quantification of

lactulose, sucrose and mannitol in urine for diagnosis of

intestinal and gastric permeability

10:25-10:40 Short talk 7: Kristina Marx, Bruker, Bremen:

Increasing arginine production in C. glutamicum by rational

strain design using a combination of metabolomics and

proteomics

3

Coffee break (& visit company exhibition)

10:40-11:10 Foyer

Scientific Session 3: Data analysis & integration

Chair: Viktoria Dorfer, Univ. Appl. Sciences Upper Austria


11:10-11:55 Key note lecture 4: Juergen Cox, MPI-

Biochemistry, Martinsried: The MaxQuant and Perseus

Computational Platforms for Comprehensive Analysis of

Large-scale (Prote)Omics Data

11:55-12:15 Short talk 8: Sebastian Dorl, Univ. Appl. Sciences

Upper Austria: Comparing true and estimated false

discovery rates in spectral library search

12:15-12:35 Short talk 9: Gerhard Dürnberger, IMP, IMBA &

GMI, Vienna: A generic proteogenomics workflow

12:35-12:55 Short talk 10: Bettina Pucher, Graz Univ.

Technol. & Omics Center Graz: Comparison and evaluation

of integrative methods for the analysis of multiple omics

datasets: A study based on simulated and experimental

datasets

12:55-13:10 Short talk 11: Claire Dauly, Thermo Fisher

Scientific, Courtaboeuf: Metabolomics in an identity crisis?

Am I a feature or a compound?

Lunch

13:10-14:00 Foyer

Practical Workshops

Chairs: AuPA Junior Board & Proteomics Pirates

14:00-18:00 Seminar rooms A1, A2, B1, B2

14:00-15:45 Practical Workshop 1 (parallel sessions)

4

• 1A: Computational Proteomics (Introduction to the

MaxQuant and Perseus software platforms): Juergen

Cox, MPI-Biochemistry, Martinsried

• 1B: Computational MS-Metabolomics – using

COVAIN to analyse metabolomics data: Xiaoliang Sun

and Wolfram Weckwerth, Univ. Vienna

• 1C: Data Processing using Progenesis QI for

Proteomics and automation with Symphony: Martin

Wells, Nonlinear Dynamics, Waters

• 1D: Protein Interaction Networks: Ulrich Stelzl, Univ.

Graz & Omics Center Graz, and Joerg Menche, CeMM,

Vienna


15:45-16:15 Foyer

16:15-18:00 Practical Workshop 2 (parallel sessions)

• 2A: Phosphoproteomics: Christian Preisinger,

Universitätsklinikum Aachen

• 2B: Lipidomics at the Edge of High Throughput:

Harald Köfeler & Jürgen Hartler, Med. Univ. Graz,

Graz Univ. Technol. & Omics Center Graz

• 2C: NMR-based Metabolomics: Tobias Madl, Med.

Univ. Graz & Omics Center Graz

• 2D: Protein Interaction Networks: Ulrich Stelzl, Univ.

Graz & Omics Center Graz, and Joerg Menche, CeMM,

Vienna

General Assembly Austrian Proteomics Association


Conference Dinner (Music by Eddie Luis & Die

GNADENLOSEN)

19:00-22:00 Foyer

5

Fri, Sep. 8th

2017

Scientific Session 4: Post translational modifications

Chair: Ulrich Stelzl, Univ. Graz & Omics Center Graz


09:00-9:45 Key note lecture 5: Markus Ralser, Univ.

Cambridge: The role of enzyme abundance in the global

regulation of cellular metabolism

09:45-10:05 Short talk 12: Tamara Scheidt, University of

Salzburg: Phosphoproteomic changes in human

medulloblastoma cells upon activation and inhibition of the

Hh pathway

10:05-10:25 Short talk 13: Faezeh Vahdati Hassani, Mashhad

University of Medical Sciences: Proteomics and

phosphoproteomics analysis in liver of rats exposed to

bisphenol A

10:25-10:45 Short talk 14: Johannes Stadlmann, IMP, IMBA &

GMI, Vienna: Comparative glycoproteomics of embryonic

stem cells identifies new players in ricin toxicity

10:45-11:05 Short talk 15: Juliane Weißer, CeMM, Vienna:

Identifying oxidation-specific post-translational

modifications in diet-induced liver inflammation


11:05-11:35 Foyer

Scientific Session 5: Protein-small molecule interactions

Chair: Ruth Birner-Gruenberger, Med. Univ. Graz & Omics

Center Graz


6

11:35-12:20 Key note lecture 6: Daniel Nomura, UC Berkeley:

Chemoproteomic Platforms to Map Druggable Hotspots in

Disease

Honorary Lecture: AuPA publication award 2017:

Clemens Grünwald-Gruber, Univ. Nat. Res. Life Sci. Vienna:

Determination of true ratios of different N-glycan structures

in electrospray ionization mass spectrometry (Anal Bioanal

Chem (2017) 409:2519–2530)


Lunch

12:40-13:30 Foyer

Presentation Awards Ceremony & Wrap up


7

List of posters

P1: Angelina Gross, Univ. Graz: Lipid metabolism in the regulation of

autophagy and aging in yeast

P2: Benjamin Bourgeois, Med. Univ. Graz: Metabolic Phenotype of

Dipeptidyl peptidase III knockout mice

P3: Dolly Mushahary, Univ. Nat. Res. Life Sci. Vienna: 2D-DIGE of

extracellular matrix proteome from 3D cultured mesenchymal stem cells,

and its secretome analysis

P4: Garwin Pichler, PreOmics GmbH: The loss-less and nano-flow SPIDER

fractionator for high sensitivity, high coverage proteomics

P5: Gesa Richter, Med. Univ. Graz: Molecular mechanisms of oxidative

stress regulation by the TOR signalling pathway regulator-like protein

P6: Holger Stalz, Agilent Techn. Switzerland AG: Workflow and Results of a

Metabolomics Analysis of Tuberculosis Drug Activity Using High-Resolution

Accurate Mass Spectrometry

P7: Julia Feichtinger, Graz Univ. Technol. & Omics Center Graz:

Comprehensive Analysis of Genomic Data for 16 CHO Cell Lines to

Investigate the (In)stability of the CHO Genome

P8: Juergen Gindlhuber, Med. Univ. Graz & Omics Center Graz:

Mitochndrial fragmentation in fatty liver

P9: Katharina Mayer, Univ. Vet. Med., Vienna: Deciphering Staphylococcus

aureus within-host adaptation in chronic bovine mastitis - A surface

proteomic approach

P10: Laura Liesinger, Med. Univ. Graz & Omics Center Graz: Proteome-wide

impact of oleic and palmitic acid induced steatosis in human liver cells

P11: Lukas Janker, Univ. Vienna: In-depth proteome-profiling to evaluate a

novel combinatory metronomic treatment for therapy-resistant multiple

myeloma patients

8

P12: Marion Janschitz, CCRI Vienna: Two softwares are better than one:

Broadening the horizon of quantitative mass spectrometry data in yeast

phosphoproteomics

P13: Matteo Schiavinato, Univ. Nat. Res. Life Sci. Vienna: Gene prediction

and gene set analysis of Nicotiana benthamiana

P14: Michael Gruber, Med. Univ. Graz: Altered kinetics of nanoparticles in

the presence of plasma proteins at the human placental barrier. An ex-vivo

placental perfusion, proteomics study

P15: Peter Valentin Tomazic, Med. Univ. Graz: Integrative Omics Approach

to Allergic Rhinitis: present state and future perspectives

P16: Petra Krenn, Med. Univ. Graz & Omics Center Graz: The role of

protein-phosphorylation in lipolysis

P17: Rainer Hofstaetter, Shimadzu Manchester UK: Development of a novel

sample preparation approach for bottom-up shotgun proteomics

P18: Zeinab Bedrood, Mashad Univ. Med. Sci.: Evaluation of the effects of

Bisphenol A on memory impairment in rats and on CaMK, ERK, CREB, P-

CaMK, P-ERK and P-CREB protein levels in rat hippocampus and protective

effect of Crocin

P19: KLaus Kratochwill, Med. Univ. Vienna: Effects of alanyl-glutamine

treatment on the peritoneal dialysis effluent proteome reveal

pathomechanism-associated molecular signatures

P20: Noel Fitzgerald, CeMM, Vienna: The identification of the drug targets

of Auranofin using protein-ligand thermal stability by mass spectrometry

9

Abstracts

Keynote Lecture Abstracts

Metabolic interplay in the stem cell niche of the small

intestine

Boudewijn MT Burgering

UMC Utrecht, The Netherlands

The small intestinal epithelium self-renews every 4–5 days. Intestinal stem

cells (Lgr5+CBCs crypt based columnar cells) sustain this renewal and reside

between terminally differentiated Paneth cells (PCs) at the bottom of the

intestinal crypt. The ability to grow in vitro small intestinal organoids that

recapitulate all cel types of the organ in vivo enables detailed analysis of

stem cell function in the context of its niche. The signalling requirements

for maintaining stem cell function and crypt homeostasis are well studied,

yet little is known how metabolism contributes to epithelial homeostasis.

Interestingly freshly isolated Lgr5+CBCs and PCs from mouse small intestine

display different metabolic programs. Compared to PCs, Lgr5+CBCs display

high mitochondrial activity. Inhibition of mitochondrial activity in Lgr5+CBCs

or inhibition of glycolysis in PCs, strongly affects stem cell function as

indicated by impaired organoid formation. In addition PCs support stem cell

function by providing lactate to sustain the enhanced mitochondrial

oxidative phosphorylation (OXPHOS) in the Lgr5+CBCs. Mechanistically

OXPHOS stimulates p38 MAPK activation by mitochondrial reactive oxygen

species (ROS) signalling thereby establishing the mature crypt phenotype.

This initial study revealed not only a critical role for the metabolic identity

ofLgr5+CBCs and PCs in supporting optimal stem cell function, but also

identify mitochondria and ROS signalling as a driving force of cellular

differentiation. We are now extending this paradigm into several new

directions to answer questions such as the role of the micro biome and

specific diets in regulating stem cell function; but also how pathways such

as known metabolic regulators like the PI3K pathway affect stem cell

function.

10

Lipidomic analysis identifying potential therapeutic targets

Michael Wakelam

Babraham Institute, Cambridge, United Kingdom

Lipidomics has developed to permit both targeted and untargeted

determination of lipids in a range of fluids, cells and tissues in a semi-

quantifiable manner. The use of today’s more advanced mass

spectrometers has facilitated the identification of and the determination of

changes in individual lipid molecular species. Bioinformatic analysis of the

data generated by lipid mass spectrometry can now permit detailed

determinations of changes in lipid metabolic and signalling pathways in

appropriate clinical samples.

Data will be presented describing semi-quantifiably the changes in ~600

distinct lipid species in colorectal tumour tissues sampled during tumour

resection; corresponding matched normal tissues were also isolated to

provide appropriate control tissues for each individual tumour sample. The

results highlight distinct tumour associated changes in lipid classes and

individual molecular species, with changes in acyl chain length and

saturation being particularly highlighted, the biochemical basis of this will

be considered.

A similar approach was adopted to define changes in lipid classes and

speciess in human bronchial epithelial cells infected with rhinovirus over a 6

hour period. This analysis identified time-specific transient changes in

particular lipids in response to viral infection and replication.

We have adopted a pathway analysis approach to further mine the mass

spectrometry results. This has allowed us to define particular enzymes

which have the potential to be therapeutic targets in both colorectal cancer

and rhino viral infection. Data will be presented demonstrating the

preliminary success of this approach.

11

Decoding Ligand Receptor Interactions

Bernd Wollscheid

Institute of Molecular Systems Biology & Department of

Health Sciences and Technology, ETH Zurich, Switzerland

Ligand-induced changes in cell surface receptors result in physiological

responses, which constitute the biological activity of various ligands such as

proteins, peptides, pharmaceutical drugs, toxins or whole pathogens.

However, traditional approaches for the ligand-based identification of

corresponding receptors are usually limited to non-transient, high affinity

interactions and highly artificial experimental set-ups. Therefore, many

signaling molecules remain orphan ligands without a known primary

molecular target - invaluable information in understanding the respective

mechanisms of signal transduction, drug action or disease. Previously, we

have developed the cell surface capturing (CSC) technology for the

unbiased identification and quantification of cell surface N-glycoproteomes

by mass spectrometry (MS). This demonstrated the powerful applicability

of chemical reagents in the tagging of cell surface glycoproteins at

carbohydrate groups and the subsequent purification of the corresponding

peptides for MS analysis.

Based on these results we now synthesized a set of trifunctional cross-

linkers for the ligand-based tagging of glycoprotein receptors on living cells

and the purification of receptor-derived peptides for MS analysis. Through

quantitative comparison to a sample generated with an unspecific control

probe, this ligand-based receptor capturing (LRC) approach allows for the

highly specific and sensitive detection of ligand interactions with their

corresponding receptors under near-physiological conditions.

Experiments with ligands ranging from peptide hormones to clinical

antibodies demonstrate the potential of this approach to specifically

identify one or more target receptors for a given ligand with great statistical

power. Advanced discovery-driven applications reveal potential receptors

and receptor panels for ligands ranging from protein domains to intact

viruses.

Together, I will present a short summary of our recent biomedical research

to understand the surfaceome as a cellular signaling gateway and a

chemoproteomic technology for the unbiased detection of ligand-receptor

interactions on living cells.

12

The MaxQuant and Perseus Computational Platforms for

Comprehensive Analysis of Large-scale (Prote)Omics Data

Juergen Cox

Max Planck Institute of Biochemistry, Martinsried, Germany

Currently, a main bottleneck in proteomics is the downstream biological

analysis of highly multivariate quantitative protein abundance data. It will

be shown how the Perseus software supports researchers in interpreting

protein quantification, interaction and posttranslational modification data.

A comprehensive portfolio of statistical tools for high-dimensional omics

data analysis is contained covering normalization, pattern recognition, time

series analysis, cross-omics comparisons and multiple hypothesis testing. A

machine learning module supports classification and validation of patient

groups for diagnosis and prognosis, also detecting predictive protein

signatures. Central to Perseus is a user-friendly, interactive workflow

environment providing complete documentation of computational

methods used in a publication. All activities in Perseus are realized as

plugins and users can extend the software by programming their own,

which can be shared through a plugin store. Perseus combines a powerful

arsenal of algorithms with intuitive usability by biomedical domain experts,

making it suitable for interdisciplinary analysis of complex large datasets.

13

The role of enzyme abundance in the global regulation of

cellular metabolism

Markus Ralser

Dept of Biochemistry and Cambridge Systems Biology

Centre, University of Cambridge, UK; The Francis Crick

Institute, London, UK; [email protected]

Every cell depends on a conserved core set of conserved metabolic

reactions, and necessitates flexibility in the flux through the reactions in

order to adapt to changes in physiology and environment. The regulation of

metabolism is achieved in a series of multilayer interactions between

transcriptome, proteome and metabolome. However, while in the

regulation of metabolism changes in enzyme activity and modifications

have attracted notable attention, the global role of the associated enzyme

abundance changes is still debated.

In order to capture the importance of enzyme abundance changes on the

global scale, we systematically created enzyme-centric proteome profiles to

cover 75% of active metabolic reactions upon the deletion of all non-

essential Saccharomyces signaling kinases, using a high-throughput

implementation of microflow-LC-SWATH-MS. We then exhaustively apply

machine learning over the topology of the metabolic network. We find that

enzyme level changes account for 40% of the total measured proteomic

impact of the kinome, are the consequence of each kinase deletion, and

that they are fundamentally important for achieving the metabolic

phenotype of the cell. Enzyme abundance changes as induced by kinase

perturbation predominantly establish upstream of transcription, are

specific for each kinase deletion, do not orient on the kinase signalling

pathways. Instead, they influence metabolite concentrations specifically

and via acting on the direct enzyme neighbors. We achieve to predict the

concentration of more than 40 measured primary metabolites out of the

enzyme abundance data, which shows that enzyme abundance changes

and the metabolic phenotype of the cell are causally linked. The global

function of metabolism hence essentially depends on the tight and precise

regulation of enzyme abundance, that acts in parallel to the importance of

posttranslational modifications to tune enzyme activities.

14

Chemoproteomic Platforms to Map Druggable Hotspots in

Disease

Daniel Nomura

UC Berkeley, California

The Nomura Research Group is focused on developing and applying

chemoproteomic and metabolomic platforms to discover new therapeutic

targets and therapies for cancer. We currently have five major research

directions. Our first research area focuses on coupling screening of

fragment-based covalent ligand libraries with chemoproteomic platforms to

discover novel druggable hotspots that can be targeted for cancer therapy.

Our second research area focuses on covalent ligand discovery against

druggable hotspots targeted by covalently-acting anti-cancer natural

products using chemoproteomic platforms to discover new therapeutic

targets and synthetically tractable therapies for cancer. Our third research

area focuses on developing and applying chemoproteomic and

metabolomic platforms to discover, characterize, and pharmacologically

target metabolic drivers of cancer. Our fourth research area focuses on

advancing chemoproteomic technologies. Our fifth research area is focused

on using chemoproteomic platforms to map proteome-wide targets and

off-targets of pharmaceutical and environmental chemicals towards

discovering new mechanisms of biological action and toxicity. My talk will

focus on using chemoproteomic and metabolomic platforms to discover,

characterize, and pharmacological target unique and novel drivers of

human disease.

15

Workshop Abstracts

Introduction to the MaxQuant and Perseus software

platforms

Juergen Cox

Max Planck Institute of Biochemistry, Martinsried, Germany

This workshop provides an introduction to the computational proteomics

platform MaxQuant and the downstream bioinformatics platform Perseus.

The first part provides theory and background information to the workflows

and algorithms while the second part is hands-on and participants will be

able to apply the tools to some real-world examples.

16

Computational Metabolomics - using COVAIN to analyze

metabolomics data

Xiaoliang Sun and Wolfram Weckwerth

Univ. Vienna, Austria

Computer-aided data mining in metabolomic studies aims for extracting

information from the data, interpreting the results and inferring the

underlying metabolic mechanisms, thereby playing an essential part in

metabolomics science. In this workshop, we firstly review well-established

GC- and LC-MS based platforms and statistical methods that are widely

used in metabolomics research, pointing out their applicability according to

different data features and specific biological questions, and then introduce

COVAIN, a data mining software integrating the discussed statistical

functions and others with a user-friendly interface. We demonstrate

COVAIN functions by applications to metabolomics data sets.

17

Data Processing using Progenesis QI for Proteomics and

automation with Symphony

Martin Wells, Senior Business Development Manager

Nonlinear Dynamics A Waters Company, UK

Proteomics data analysis using the very latest v4 (2017) version of

Progenesis QI for Proteomics. This will cover both the direct label free

analysis and SILAC comparative quantification using the new Proteolabels

app and show how data pipelines can be automated using Symphony.

The seminar and live software demonstration will cover the complete

Quantify then Identify workflow from the unique co-detection technology

in Progenesis, the Quality Control metrics, peptide identification using both

spectral libraries and traditional search engines through to protein

inference.

This is an ideal opportunity to experience for yourself this intuitive, easy to

use program in action to understand how it could help you.

18

Protein interaction networks @ APRS 2017

Ulrich Stelzl1 and Joerg Menche

2

1University of Graz and Omics Center Graz, Austria

2CeMM Vienna, Austria

Protein interaction networks are fundamental to our understanding of

complex genotype to phenotype relationships. In this work shop we will

discuss various aspects of network biology. The includes analytical

concepts, data generation and the impact of networks in genome and

proteome research, from the understanding of basic molecular

mechanisms and cellular processes, the importance of network approaches

in understanding complex human diseases and drug action and potential

implications in practical medicine. The work shop will be structured in two

parts: Molecular interaction networks (Stelzl) and disease networks

(Menche).

19

Phosphoproteomics

Christian Preisinger,

Universitätsklinikum Aachen, Germany

Reversible protein phosphorylation is one of the key mechanisms in many

regulatory cellular mechanisms such as the orchestration of the cell cycle,

growth, apoptosis and others. Deregulation of these tightly controlled

PTMs is the cause for many pathological conditions, most notably solid

tumors and leukemias. The last two decades have seen numerous attempts

in order to enable and facilitate the analysis of protein phosphorylation

events. To date, phosphoproteomics covers the qualitative and quantitative

investigation of protein phosphorylation ranging from rather small

(targeted analysis of single (or few), purified proteins) to large scale

(unbiased analysis of several hundred/thousand or even >10000

phosphorylation events in cells or tissues).

This workshop will cover the major aspects of the analysis of protein

phosphorylation. a) biological questions and sample source b) current

strategies for phosphopeptide (and phosphoprotein) enrichment c) mass

spectrometry d) data analysis, interpretation and follow-up. This last point

currently represents a severe bottle-neck in most phosphoproteomic

experiments/approaches. Therefore we will put special emphasis on this

particular subject matter.

20

Lipidomics at the Edge of High Throughput

Harald Köfeler1,2

and Jürgen Hartler1,2,3

1Medical University of Graz, Austria

2Omics Center Graz, Austria

3Graz University of Technology, Austria

The lipidome of all biological entities is crucial for understanding the

mechanisms behind their respective functions. Lipidomics research at the

molecular levels provides insights complementary to genomics,

transcriptomics and proteomics research, and contributes as such in the

elucidation of cellular mechanisms. The field is particularly driven by

advances in mass spectrometry. Even though mass spectrometry enables

simultaneous detection of quantitative changes of hundreds to thousands

of lipids in complex mixtures, analysis of the lipidome is handicapped by its

sheer chemical diversity, because molecules consolidated under the term

lipids form a highly heterogeneous set of species. Due to this fact, analytical

protocols are manifold, and none of them offers detection of all lipid

classes in a single MS run. Additionally, the diverse lipid fragmentation

behavior makes structural characterization of lipids a challenging task. On

top of that, consistent reporting standards for lipid species, which would be

crucial for automated high throughput annotation, are only slowly accepted

and implemented by the research community.

In this workshop, we will provide insights into recent developments in lipid

nomenclature and reporting standards, followed by an overview of MS-

based analytical methods. Finally, we will dive into the challenges in lipid

MS data analysis which is complemented by the presentation of an in-

house developed lipid annotation software.

21

NMR-based metabolomics

Tobias Madl

Institute of Molecular Biology and Biochemistry, Medical

University of Graz, and Omics Center Graz, Austria

Hallmarks of technological developments that enabled metabolic research

and are driving increasingly wider applications of metabolomics were the

establishment of powerful analytical instrumentation and tools for

automated statistical data analysis. Currently, nuclear magnetic resonance

spectroscopy (NMR), and mass spectrometry (MS) are the key techniques

for the detection and identification of metabolites. Both techniques are

complementary: on the one hand NMR provides access to unique structural

information, is quantitative and highly reproducible, but less sensitive. On

the other hand, MS is more sensitive than NMR, but suffers from the

ambiguity of spectral signatures and a lower reproducibility.

In this workshop we will focus on recent developments in the field of NMR-

based metabolomics with a particular emphasis on the setup of NMR-based

metabolomics studies and data analysis methods. The workshop will cover

data acquisition and analysis with advanced statistics for more hands-on

participation for attendees, including tips and tricks to avoid common

pitfalls. Examples of real life applications for static and dynamic studies of

metabolite networks will be discussed.

22

Short Talk Abstracts

Multi-omics Analysis of Serum Samples Demonstrates

Reprogramming of Organ Functions Via Systemic Calcium Mobilization and Platelet Activation in Metastatic

Melanoma

Besnik Muqaku1, Martin Eisinger1, Samuel M. Meier1, Ammar Tahir1, Tobias Pukrop2, Sebastian Haferkamp2, Astrid Slany1, Albrecht Reichle3, and Christopher Gerner1

1) Dep. of Analytical Chemistry, Faculty of Chemistry, University of Vienna, Austria 2) Department of Dermatology, University Hospital of Regensburg, Regensburg,

Germany 3) Department of Internal Medicine III, Haematology & Oncology, University Hospital of

Regensburg, Regensburg, Germany

Introduction Pathophysiologies of cancer-associated syndromes such as cachexia are poorly understood and no routine biomarkers have been established, yet. Methods Using shotgun proteomics, known marker molecules including PMEL, CRP, SAA and CSPG4 were found deregulated in patients with metastatic melanoma. Targeted analysis of 58 selected proteins with multiple reaction monitoring was applied for independent data verification. In three patients, two of which suffered from cachexia, a tissue damage signature was determined, consisting of nine proteins, PLTP, CD14, TIMP1, S10A8, S10A9, GP1BA, PTPRJ, CD44 and C4A, as well as increased levels of glycine and asparagine, and decreased levels of polyunsaturated phosphatidylcholine concentrations, as determined by targeted metabolomics. Results and Discussion Remarkably, these molecules are known to be involved in key processes of cancer cachexia. Based on these results, we propose a model how metastatic melanoma may lead to reprogramming of organ functions via formation of platelet activating factors from long-chain polyunsaturated phosphatidylcholines under oxidative conditions and via systemic induction of intracellular calcium mobilization. Calcium mobilization in platelets was demonstrated to alterate levels of several of these marker molecules. Additionally, platelets from melanoma patients proved to be in a rather exhausted state, and platelet-derived eicosanoids implicated in tumor growth were found massively increased in blood from three melanoma patients. Platelets were thus identified as important source of serum protein and lipid alterations in late stage melanoma patients. Innovative aspects

• The proposed model describes the crosstalk between lipolysis of fat tissue and muscle wasting mediated by oxidative stress, resulting in the metabolic deregulations characteristic for cachexia.

23

Adipose triglyceride lipase (ATGL) promotes oncogenic signalling resulting in more aggressive cancer phenotype

in lung carcinoma cells

Tamara Tomin1,2, Katarina Fritz1,2, Jürgen Gindlhuber1,2,3, Bettina Pucher,2,3, Matthias Shittmayer1,2, Gerhard Thallinger,2,3, Daniel Nomura4 and Ruth Birner-Grünberger 1,2

1) Institute of Pathology, Medical University of Graz, Graz, Austria 2) Omics Center Graz, Graz, Austria

3) Dept. of Computational Biotechnology, Graz University of Technology, Graz, Austria 4) UC Berkeley, Carlifornia

Introduction Metabolic switch is one of the main hallmarks of malignant transformation. While much is known about catabolism of sugars, same cannot be said regarding the lipid catabolism in cancer, especially concerning the role of neutral lipases in cancer progression. Here we report that loss of adipose triglyceride lipase (ATGL), the rate limiting triacylglycerol (TAG) hydrolase, can further support aggressive cancer phenotype. Methods On a model system of CRISR/Cas9 ATGL-KO A549 lung carcinoma cells we performed phenotyping experiments that included evaluation of cell growth and migration potential, followed with lipid droplet staining and visualisation. Lipid accumulation was further validated with lipidomics screening carried out on an Agilent QQQ instrument. Protein extracts of the cells were subjected to quantitative proteomics analysis using label free quantification approach on a maXis II ETD QTOF. Main target from proteomics screening was validated with semi-targeted measurements on Orbitrap Velos Pro and by western blot, while its gene expression was addressed by quantitative PCR. Results and Discussion Loss of ATGL slightly increased cell growth but boosted migration potential of the cells. ATGL-KO caused prominent TAG accumulation in form of lipid droplets, which was confirmed by lipidomics screening. In ATGL-KO cells TAGs were the most up-regulated lipid class, followed by several different signalling lipid species. Proteomic analysis has shown that observed phenotype is supported by activation of pro-oncogenic signalling, namely via proto-oncogene kinase SRC. SRC gene and protein expression appeared up-regulated in ATGL-KO cells, as well as activated SRC form (phospho-SRC (Y416)). Intrenstingly, higher migration potential of ATGL-KO cells seems to be SRC dependent, as it is abolished by the treatment with selective SRC inhibitor. Up-regulation of SRC and increase in number of lipid droplets (even as separate events) are known to render more aggressive cancer phenotypes. We believe that graduate loss of ATGL may force the cancer cells invade and migrate better in order to obtain more nutrients, causing a consequent change of their metabolism. Innovative aspects

• Loss of ATGL causes lipid accumulation and boosts migration potential of lung cancer cells by activating pro-oncogenic signalling

• Expression levels of ATGL could act as a prognostic marker for cancer progressiveness

24

Aging-related proteome alterations in B cells may predispose for chronic lymphocytic leukemia

Rupert L. Mayer1,2, Astrid Slany1,2, Andrea Bileck1, Johanna C. Mader1, Samuel M. Meier-

Menches1, Tobias Pukrop3, Albrecht Reichle4, Josef D. Schwarzmeier2, Christopher Gerner1,2

1) Department of Analytical Chemistry, Faculty of Chemistry, University of Vienna, Austria 2) Karl Landsteiner Institute for Bioanalytical Oncology, Karl Landsteiner Society, Austria

3) Department of Dermatology, University Hospital of Regensburg, Regensburg, Germany

4) Department of Internal Medicine III, Haematology & Oncology, University Hospital of Regensburg, Regensburg, Germany

Introduction Chronic lymphocytic leukemia (CLL) as the most common type of leukemia in adults in the western world primarily affects B lymphocytes and manifests itself by accumulation of non-functional, clonal B-cells in peripheral blood, bone marrow and lymphoid tissue. CLL is still incurable and eventually causes repression of other blood cells leading to symptoms like anemia and thrombocytopenia. While many aspects of CLL have been evaluated in great detail resulting in novel therapeutic applications, CLL metabolism has been hardly studied and holds great potential for future clinical intervention strategies.

Methods B lymphocytes isolated from peripheral blood of younger as well as elderly healthy donors and CLL patients were fractionated into cytoplasmic and nuclear fraction. Proteome profiles were generated via HR-MS and data subjected to MaxQuant software for label-free quantification. Targeted metabolomic analyses of corresponding whole cell lysates were performed using the Biocrates AbsoluteIDQ p180 kit for the quantification of 180 metabolites including acylcarnitines, amino acids, biogenic amines, sphingolipids, monosaccharides and glycerophospholipids.

Results and Discussion HR-MS proteomics yielded about 7000 protein identifications for the entire dataset. Relative quantitative comparison between age-matched normal B cells and CLL cells resulted in 426 and 428 significantly regulated proteins (FDR<0.05) for cytoplasmic and nuclear fraction, respectively. Aside from well-known CLL-associated regulations like increased levels of BCL2, many metabolically relevant proteins were found altered in CLL cells. Pathways identified to be particularly affected were glutamine and lipid metabolism. These findings were corroborated on the metabolite level as glutamine and glutamic acid were found to be strongly deregulated within CLL cells along with glycerophospholipids and sphingolipids. Contrasting of B cells from elderly and younger healthy donors revealed a potential predisposition of aged B cells with increased levels of proteins associated with DNA damage repair, inflammatory response, altered metabolism as well as impaired mitochondrial functions. The present proteome profiling study provides evidence for age-related reprogramming of normal B cells potentially pre-disposing for B-CLL based on mitochondrial changes causing increased probability for genetic damages and resulting into differentiation to more long-lived cells. A rather homogenous protein expression pattern of B-CLL cells indicating a gain of stem cell properties with distinct metabolic features indicate previously unrecognized properties of B-CLL cells and may support the development of novel therapeutic targets.

Innovative aspects

• Glutaminolysis as energy supply in CLL

• Predisposition of aged B cells for chronic lymphocytic leukemia

• Stem cell phenotype of CLL B cells

25

Glyceroneogenesis is utilized for biomembrane synthesis in glucose-deprived cancer cells

Katharina Leithner1, Alexander Triebl2, Martin Trötzmüller2, Barbara Hinteregger2, Petra

Leko1, Beatrix Wieser1, Elvira Stacher3, Alessandro Valli4, Ruth Prassl5, Andrea Olschewski6, Adrian L. Harris4, Harald C. Köfeler2, Horst Olschewski1, Andelko Hrzenjak1

1) Division of Pulmonology, Department of Internal Medicine, Medical University of Graz,

Graz, Austria 2) Core Facility Mass Spectrometry and Lipidomics, ZMF, Medical University of Graz,

Graz, Austria 3) Institute of Pathology, Medical University of Graz, Graz, Austria

4) Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK 5) Institute of Biophysics, Medical University of Graz, Graz, Austria

6) Ludwig Boltzmann Institute for Lung Vascular Research, Graz, Austria e-mail: [email protected]

Introduction Cancer cells utilize large amounts of glucose, however the consumption of glucose is frequently not balanced by adequate supply in solid cancers, ultimately leading to a decline in glucose levels. The mitochondrial isoform of the gluconeogenesis enzyme phosphoenolpyruvate carboxykinase, PCK2, has been found by us and others to be functionally expressed in cancer cells of different origin and to enhance cancer cell survival under glucose starvation. However, the metabolic downstream pathways of PCK2 in starved cancer cells are still elusive. We hypothesized, that PCK2 mediates glyceroneogenesis in glucose-deprived cancer cells in order to maintain the biosynthesis of glycerol phosphate for glycerophospholipid synthesis. Methods We utilized 13C5-glutamine and 13C3-lactate as tracers under glucose- and serum-starvation in order to assess, whether glyceroneogenesis occurs in lung cancer cells. Isotopologue abundance of glycerol-containing backbone fragments of phospholipids and glyceroneogenic intermediates, as well as total levels of phospholipids were assessed using liquid chromatography/mass spectrometry. Results and Discussion We found substantial 13C incorporation from 13C-labelled glutamine and 13C-labelled lactate into the glycerol backbone of phospholipids in lung cancer cells under low glucose conditions (0.2 mM). Precursors of glycerol phosphate along the glyceroneogenesis pathway, phosphoenolpyruvate and 3-phosphoglycerate, also showed considerable 13C enrichment. PCK2 silencing led to significantly reduced levels of phosphatidylethanolamine (PE), a cone-shaped phospholipid with multiple cellular functions. We found that lung cancer cell xenograft growth and colony forming capability under glucose deprivation were severely compromised after PCK2 silencing. Exogenous PE partially rescued colony formation. Innovative aspects Our study shows that cancer cells utilize glycolysis in the backwards direction (glyceroneogenesis/gluconeogenesis) via PCK2 in order to maintain phospholipid glycerol backbone synthesis under glucose starvation and that PCK2 is required for in vivo tumorigenesis in H23 lung cancer cells. Thus, PCK2-mediated glyceroneogenesis is a novel metabolic pathway in cancer cells allowing metabolic flexibility under glucose starvation.

26

Resolution ladder for high resolution mass spectrometry

Matthias Schittmayer1,2,3, Ruth Birner-Gruenberger1,3,*

1Medical University of Graz, Austria 2Institute of Molecular Systems Biology, ETH Zürich, 8093 Zürich, Switzerland

3Omics Center Graz, BioTechMed-Graz, 8010 Graz, Austria

Introduction High resolution mass spectrometry has become a key technology in life sciences. Since it is often unfeasible to find pairs of analytes with an appropriate mass difference to actually quantify the resolution experimentally, resolution is usually calculated from the shape of a single mass peak. In this study we show that the commonly employed strategy yields a poor measure of true resolution since it does not account for interactions that take place between ions of very similar mass and might be further distorted by signal processing effects. We present a straightforward and easily adaptable method to create a ladder of mass pairs to experimentally quantify actual mass resolution over a wide m/z range, compare the experimental resolution to the single peak based calculated resolution and demonstrate the applicability of mass resolution ladders to study interactions of similar ions in various types of widely used mass spectrometers. Methods Crafting molecular labels with a given mass difference on a low molecular weight polymer with high polydispersity will result in a ladder of mass pairs with fixed ∆m. Resolution requirements increase stepwise for each increase in polymer number, resulting in a mass resolution ladder. Small mass differences can be introduced through the different mass defects of stable isotopes. Combining several of these differences allows to conveniently cover a wide ∆m range for the resulting pairs. Another important aspect in creating a mass spectrometric resolution ladder is the backbone carrying the mass labels. Low molecular weight polymers with high polydispersity are ideal carriers for the mass labels, however solubility in solvents commonly used in mass spectrometry has to be ensured. The monomer mass defines the spacing between the individual peaks and therefore also the resolution steps. Groups that can be easily ionized in positive and negative mode add sensitivity and flexibility. Finally, the backbone should have functional groups which can be specifically targeted for mass labelling, ideally by simple aqueous chemistry. Results and Discussion It has become de facto standard to calculate instrument resolution from peaks originating from a single, isolated ion cloud. In this study we demonstrate that single peak calculated FWHM based resolution insufficiently reflects true resolution of mass spectrometers. We provide a blueprint on how to create a mass resolution ladder for experimental resolution determination with emphasis on simple synthesis and high adaptability. This new tool can be used to validate FWHM resolution values, to reveal unexpected links of resolution to other instrument parameters and to study space charge effects. We therefore think that our concept of a mass resolution ladder will be highly valuable for scientists and instrument developers alike. Innovative aspects • Experimental determination of mass spectrometric resolution • Simple and cost effective synthesis • Discovery and investigation of over-processed signals and space charge effects

27

NMR spectroscopy enables simultaneous quantification of lactulose, sucrose and mannitol in urine for diagnosis

of intestinal and gastric permeability

Stryeck Sarah1, Angela Horvath2, Bettina Leber2, Vanessa Stadlbauer2, Tobias Madl1 1) Institute of Molecular Biology and Biochemistry, Center of Molecular Medicine, Medical

University of Graz, 8010 Graz, Austria 2) Department of Internal Medicine, Division of Gastroenterology and Hepatology,

Medical University of Graz, 8010 Graz, Austria

Introduction Liver cirrhosis is a major global health burden with a continuously rising incidence.(1) Gut barrier dysfunction plays a crucial role in disease progression and in the pathogenesis of complications of cirrhosis. Therefore analysis of an increased gut permeability is inevitable for preventing profound infections.(2) The current gold standard is the administration of a combination of carbohydrates including mannitol, lactulose, and sucrose. Elevated lactulose and sucrose levels in urine indicate increased intestinal and gastric permeability, respectively. Mannitol serves as a reference compound for sugar intake, which is always excreted via urine in healthy individuals. Sugar-dependent enzymatic assay and chromatographic methods are commonly used in order to detect and quantify these compounds.(3,4) However, these approaches are limited in terms of their accuracy, throughput, and interference with other compounds often present in human urine (e.g. glucose in enzymatic assays). These obstacles can be conquered using an analytical approach providing qualitative and quantitative information about small molecules present in a biological mixture. Methods Here we used NMR spectroscopy with a simple and fast protocol, without any additional sample extraction steps, for straight-forward simultaneous quantification of sugars in urine in order to detect an increased intestinal or gastric permeability. Collected urine samples were diluted in deuterated buffer to record one dimensional 1H CPMG and two dimensional 1H homonuclear J-resolved spectra for quantification. Results and Discussion Our study presents a robust method for a simultaneous and fast detection of sugars down to low micro-molar concentrations and can easily be extended to quantification of other urine metabolites or untargeted metabolomics. These results provide a new analytical technique for the detection of intestinal/gastric permeability in clinical diagnosis. Innovative aspects

• No extraction protocols needed • Simultaneous quantification of different sugars • High-throughput possible

Acknowledgements This work was supported by the Integrative Metabolism Research Center Graz, the Austrian infrastructure program 2016/2017, BioTechMed/Graz, Omics Center Graz, the President’s International Fellowship Initiative of CAS (No. 2015VBB045, to T.M.), the National Natural Science Foundation of China (No. 31450110423, to T.M.), and the Austrian Science Fund (FWF: P28854 and W1226-B18 to T.M.). S.S. was trained within the frame of the PhD Program Molecular Medicine of the Medical University of Graz. References (1) Mokdad AA et al. BMC medicine (2014); (2) Tsiaoussis, et al. World J Hepatol (2015); (3) Lunn PG, et al. Clinica chimica acta (1989); (4) Martinez-Augustin O, et al. Clinical biochemistry (1995)

28

Increasing arginine production in C. glutamicum by rational strain design using a combination of

metabolomics and proteomics

Frederik Walter², Marcus Persicke², Aiko Barsch1, Stephanie Kaspar-Schoenefeld1,Heiko Neuweger1, Matthias Szesny1, Nikolas Kessler1, Jörn Kalinowski2, Kristina Marx1

1) Bruker Daltonik GmbH, Bremen, Germany

2) Bielefeld University, Bielefeld, Germany

Introduction C. glutamicum is a bacterium used for biotechnological production of amino acids and other metabolites. Arginine is of commercial importance in cosmetic and pharmaceutical industries and as food additive. Here we highlight that combining rational strain design with metabolomics and proteomics is a powerful tool to increase production of desired metabolites in a biotechnological, bacterial workhorse. Methods Three mutant strains were compared to wildtype C. glutamicum extracts. Metabolomics and proteomics data have been acquired on an impact II QToF-MS (Bruker Daltonics). The MetaboScape software was used for processing of metabolomics data, whereas MaxQuant was used to process proteomics data. Mapping of detected changes to the arginine pathway enable data interpretation in a biological context. Results and Discussion Metabolomics and proteomics data were acquired to gain insights into changes introduced by rational strain design to increase arginine production in C. glutamicum. Metabolomics data analysis resulted in the tentative identification of an unknown compound — more abundant in the mutant strains — as glutamylvaline. Several known compounds in the arginine biosynthetic pathway could automatically be identified. Proteomics data revealed significant changes of proteins involved in the arginine biosynthesis pathway. Mapping alterations detected by both OMICS approaches on biochemical pathway maps enabled quick formulation of hypotheses for the observed changes in the biological context. Our results demonstrate that combination of non-targeted omics techniques enables in-depth investigation of changes in C. glutamicum caused by rational strain design to increase production of desired metabolites. Innovative aspects

• Combination of non-targeted metabolomics and proteomics workflows link data to biology by pathway mapping

29

Comparing true and estimated false discovery rates in spectral library search

Sebastian Dorl1, Stephan Winkler1, Karl Mechtler2, and Viktoria Dorfer1

1) Bioinformatics Research Group, University of Applied Sciences Upper Austria, Hagenberg, Austria 2) Research Institute of Molecular Pathology (IMP), Institute of Molecular Biotechnology (IMBA), Vienna,

Austria

Introduction Spectral library search uses spectrum-to-spectrum matching for the identification of peptides from fragment ion spectra. This approach is now seeing growing interest in the mass spectrometry community thanks to the increasing number of readily available spectral libraries. Given a suitable library, using spectrum-to-spectrum matching leads to higher sensitivity and faster processing times than database search. However, spectral library search lacks a consensus strategy for validating results and controlling false discovery rates (FDR). The commonly accepted method to estimate false discovery rates in MS/MS experiments is to perform database search using a concatenated target and decoy database, which simulates the occurrences of false positive identifications. Applying the target-decoy approach (TDA) to spectral library search is complicated since the generation of decoy spectra is non-trivial. Suitable decoys need to be different from the real spectra but still similar enough to be mistaken for experimentally observed spectra. Methods Calculating the true FDR needs prior knowledge of the peptides in an experiment, which is inherently difficult. We use HCD MS/MS fragment ion data of synthetic peptides from the ProteomeTools[1] project for searches in the NIST human HCD spectral library. With the list of synthesized peptide sequences, we establish a ground truth and calculate the true FDR for each spectral library search. We evaluate the search performance based on the accuracy of the target-decoy FDR estimate and the distribution of search hits in the target and decoy libraries. We test several different spectral library search engines as well as different methods for the generation of decoy spectral libraries. Results and Discussion To reach a broader acceptance in proteomics research, spectral library search needs a unified standard approach for FDR control. Our comparisons demonstrate the problems in applying the target-decoy approach to spectrum-to-spectrum matching as first results indicate that the TDA for spectral libraries underestimates the FDR. In our experiments, at 1% estimated FDR the calculated true FDR was 7.35% on average. The process by which decoy spectra are generated is of particular importance and still an open issue at this point. Additionally, we set up cross validation searches using redundant spectral library information to verify our results. Furthermore, we compare these results with results from database search under equivalent conditions. Innovative aspects

• Calculating true FDR in spectral library search experiments using synthetic peptide data

• Benchmarking spectral library search engines on high-accuracy fragment ion data References

[1] Zolg DP, Wilhelm M, Schnatbaum K, Zerweck J, Knaute T, Delanghe B, et al. Building ProteomeTools based on a complete synthetic human proteome. Nat Methods. 2017;14:259–62.

30

A generic proteogenomics workflow

Daniel Lengauer1, Karl Mechtler1,2, Gerhard Dürnberger1,2,3 1) Institute of Molecular Pathology (IMP), Vienna, Austria

2) IMBA, Institute of Molecular Biotechnology of the Austrian Academy of Sciences, Vienna, Austria

3) GMI, Gregor Mendel Institute of Molecular Plant Biology, Vienna, Austria

Introduction Proteogenomics is a developing new field in proteomics research. Here, custom protein sequence databases are constructed based on next generation sequencing data. These databases allow to identify mutated peptides after genomic mutations. Furthermore, organisms lacking a reference proteome become accessible to database searching. In addition gene models to predict coding regions within the genome can be refined based on the evidence gained on proteome level. We present a pipeline to assemble protein sequences from RNA seq data. The performance of the pipeline is demonstrated on some initial benchmarks. Methods RNA-Seq data is assembled using Trinity (Grabherr et al). Resulting contigs are translated to potential protein sequences using ORFFinder, which was developed in-house in .NET (version >4.5.2). A graphical user interface for both tools was developed in shiny (shiny.rstudio.com). RNA extracted from HeLa cells was sequenced twice, once using single end sequencing up to a length of 50 nucleotides and using paired-end sequencing up to a length of 125 nucleotides on both ends. Lysate of the same HeLa cells was digested using LysC and trypsin, desalted and fractionated to 96 fractions on an SCX column. Resulting fractions were separated using a 3 hour reverse phase gradient and injected to a Q Exactive HF. The instrument was operated in data-dependent mode acquiring MS2 scans for the ten most abundant ions. Acquired raw data was analysed in Proteome Discoverer 2.1 using MS Amanda (Dorfer et al) and Percolator (Käll et al) searching against SwissProt and fasta databases derived from de-novo assembly of RNA-Seq data. Final results were filtered to a 1% FDR on peptide spectrum match and protein level. Results and Discussion A user-friendly interface to perform RNA assembly in Trinity and subsequent translation to open reading frames was developed. Performance was benchmarked on a HeLa sample measured in-house, comprised of RNA-Seq and proteomics data acquired from the same pool of starting material. A set of parameters considering eukaryotic translation specifics and incomplete assembly were evaluated on this data set. Furthermore “dilution experiments”, sampling from RNA-Seq reads, were performed to estimate required sequencing depth and evaluate the presented pipeline. Based on these initial results the pipeline could already be applied to further data sets. The presented tool suite represents a generic workflow for simple implementation of proteogenomics workflows without relying on a reference genome. Innovative aspects

• Generic and simple to use workflow for proteogenomics

• Initial validation on human samples

31

Comparison and evaluation of integrative methods for the analysis of multiple omics datasets: A study based on

simulated and experimental datasets

Bettina M. Pucher1,2, Oana A. Zeleznik3,4 and Gerhard G. Thallinger1,2 1) Institute of Computational Biotechnology, Graz University of Technology, Graz,

Austria 2) Omics Center Graz, BioTechMed-Graz, Graz, Austria

3) Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, United States

4) Department of Medicine, Harvard Medical School, Boston, United States

Introduction The aim of integrative analysis is to take advantage of the joint exploration of data obtained on multiple cellular levels in order to identify the driving factors of a biological process. As the large amount of produced omics data constantly increases, so does the collection of tools for its analysis. However, comparative studies illustrating differences in performance of methods and benchmarking the biological value of results are rare but in high demand. Methods We present a comprehensive comparison of three integrative analysis approaches, Sparse Canonical Correlation Analysis (sCCA), Non-negative Matrix Factorization (NMF) and Logic Data Mining (MALA), by applying them to simulated and experimental omics data. Results and Discussion Decomposition based methods, sCCA and NMF, are able to identify differentially expressed features in simulated data while the Logic Mining method, MALA, performs modestly. Applied to experimental data we show that in terms of classification accuracy of samples, MALA performs best. Considering the high classification power of prioritized feature sets resulting from individual methods (96.6 – 99.7% accuracy), we expect the identified feature sets to produce a substantial overlap. However, the proportion of features identified by at least one of the other methods is approx. 60% for sCCA and NMF and nearly 30% for MALA and the proportion of features jointly identified by all methods is only around 10%. Similarly, the congruence on more general biological annotation levels (Gene Ontology terms, Reactome pathways) is lower than expected. Furthermore, the agreement of identified feature sets with curated gene signatures relevant to the investigated disease is modest. We point out differences in the concepts of methods and discuss possible reasons for the moderate overlap of identified feature sets with each other and with curated cancer signatures. Innovative aspects

• Comparisons of integrative analysis approaches, taking advantage of multiple information levels provided by multiple omics technologies, are rare but in high demand.

• We benchmark the performance of methods by applying them to comprehensive simulated datasets and review the potential biological value of results.

• We demonstrate that the congruence of method results is modest on the feature level and on more general biological annotation levels as well as with curated cancer signatures.

32

Metabolomics in an identity crisis? Am I a feature or a compound?

Claire Dauly1

1) Thermo Fisher Scientific, Courtaboeuf, France

Abstract The analysis of complex sample matrices is a common challenge in many metabolomics applications and identifying specific compounds of interest is an important step. Here we will describe several novel identification approaches including selective component detection of resolved hyperfine isotopic signatures, the use of complementary fragmentation tools and our highly curated mzCloud spectral library.

33

Phosphoproteomic changes in human medulloblastoma cells upon activation and inhibition of the Hh pathway

Tamara Scheidt1, Humberto Jorge Gonczarowska2, Wolfgang Gruber1, Margherita

Dell’Aica2, Oliver Alka3, Marc Rurik3, Oliver Kohlbacher3, René Zahedi2, Fritz Aberger1, Christian G. Huber1

1) University of Salzburg, Department of Molecular Biology, Salzburg, Austria 2) Leibniz-Institut für Analytische Wissenschaften-ISAS-e.V., Dortmund, Germany

3) University of Tübingen, Applied Bioinformatics, Tübingen, Germany

Introduction Dysfunctions in phosphorylation cascades can promote the development of various diseases such as cancer. The holistic approach of functional phosphoproteomics using HPLC-MS based techniques has become an important research tool to investigate the phosphoprotein composition of tumor cells in a particular state. Within this study the comprehensive attempt should help to better understand the mechanisms of action involved in the function of the oncogenic GLI transcription factor proteins after smoothened (SMO) dependent activation and inhibition of the oncogenic hedgehog (Hh) pathway in human medulloblastoma cells. Methods Hedgehog pathway was induced and inhibited in the human medulloblastoma cell line DAOY. The Hh activator SMO agonist (SAG) and the FDA approved SMO antagonist Vismodegib were applied for 5 and 15 minutes. Treatment with epidermal growth factor (EGF) served as a control for increased early phosphorylation events. After cell lysis, the protein content was isolated and digested with trypsin by filter-aided sample preparation. Differential protein quantification was enabled by using isobaric mass tags (10-plex TMT labels). Enrichment of phosphopeptides was performed with titanium dioxide beads. Hydrophilic interaction chromatography prior to reversed-phase high-performance liquid chromatography mass spectrometry (RP-HPLC-MS) was applied to characterize the phosphoprotein composition. Peptide identification was performed by tandem mass spectrometry (MS2) using data-dependent acquisition. Data analysis and interpretation was performed using Proteome Discoverer, Perseus and the Ingenuity Pathway Analysis Software. Results and Discussion More than 10 000 phosphosites out of 8000 protein groups were identified. Several phosphosites of proteins from the Hedgehog pathway such as SMO, SUFU and protein kinase A were found to be differentially regulated in the smoothened activated cells compared to Vismodegib treatment. Differences in the regulation of several pathways involved in differentiation and proliferation such as the Hippo pathway was observed due to diversity in the phosphorylation of proteins involved in Hedgehog dependent intracellular signalling. Innovative aspects

• Phosphoproteomics of early Hh pathway induction and inhibition

• Comprehensive elucidation of phosphorylation dynamics in human medulloblastoma cells

• Identification of endorsers as new potential targets for cancer therapy

34

Proteomics and phosphoproteomics analysis in liver of rats exposed to bisphenol A

Faezeh Vahdati Hassani1, Khalil Abnous1, Soghra Mehri1, Ruth Birner-Gruenberger3, and

Hossein Hosseinzadeh1 1) Mashhad University of Medical Sciences, Mashhad, Iran

3) Medical University of Graz and Omics Center Graz, Graz, Austria

Introduction Bisphenol A, (BPA), 2,2-bis(4-hydroxyphenyl) propane, is a known endocrine disrupting compound. It has been employed as a monomer to manufacture polycarbonate plastics, in resins lining canned food and beverage containers, in medical equipment, and as an additive in other types of plastics. Previous studies showed that BPA could leach from food and beverage containers and resin-based composites and sealants under normal condition of use. Therefore, the human population is widely exposed to low levels of BPA through oral ingestion. BPA has been implicated to mediate oxidative damage to cells and tissues and to be involved in reproductive disorder, obesity, diabetes. It is well established that determination of proteomic alterations can identify protein biomarkers of xenoestrogen exposure and improve our understanding of the specific mechanism of action. In this study, we determined whether chronic oral exposure of rats to low dose BPA (0.5 mg/kg) induces oxidative stress in the liver and affects the liver proteome and phosphoproteome by untargeted gel-based proteomics. Methods For this purpose, Two-dimensional gel electrophoresis followed by MALDI-TOF/TOF (Matrix Assisted Laser Desorption Ionization-Time of Flight Analyzer) were applied for separation, quantification, and identification of significantly altered proteins caused by BPA treatment in adult male Wistar rats. We annotated the identified significantly altered proteins and phosphoproteins based on molecular functions, biological processes and pathways. Moreover, we confirmed the proteomics results by western blot analysis, which is the most widely, used independent technique for verification of proteomic results. We also analyzed the effects of BPA on oxidative stress by assessing levels of malondialdehyde (MDA), a marker of lipid peroxidation, and reduced glutathione (GSH), a non-enzymatic antioxidant agent, in the liver Results and Discussion Our proteomic and phosphoproteomics analysis shows that low dose BPA is able to efficiently alter (phospho) protein expression involved in metabolism and antioxidant defence in liver of male rats. In addition, the changes in expression of different proteins especially calreticulin, betaine homocysteine s-methyltransferase (BHMT), protein disulfide isomerase (PDI), and 3-oxo-5-beta-steroid 4-dehydrogenase (AKR1D1) are consistent with many pathophysiological conditions such as steatosis and susceptibility to cancer development in the liver. It is well documented that oxidative stress can damage critical cellular macromolecules, modulate gene expression pathways and induce oxidative DNA damage. Along with its impacts on protein expression, low dose BPA administration also induced lipid peroxidation, which was accompanied by a decrease in liver reduced glutathione level. Innovative aspects

• This is the first study that identified specific phosphoprotein to be involved in BPA liver toxicity.

• Chronic oral exposure of rats to BPA leads to major alterations in the liver proteome and phosphoproteome, which may contribute to the pathophysiology of liver diseases.

35

Comparative glycoproteomics of embryonic stem cells identifies new players in ricin toxicity

Johannes Stadlmann 1, Jasmin Taubenschmid 1, Daniel Wenzel 1, Anna Gattinger 1,2, Gerhard Dürnberger 1,2,3, Frederico Dusberger 2, Ulrich Elling 1, Lukas Mach 4, Karl

Mechtler 1,2, Josef M. Penninger 1 1 IMBA, Institute of Molecular Biotechnology of the Austrian Academy of Sciences, Dr.

Bohr Gasse 3, A-1030 Vienna, Austria. 2 Institute of Molecular Pathology (IMP), Dr. Bohr Gasse 7, A-1030 Vienna, Austria.

3 GMI, Gregor Mendel Institute of Molecular Plant Biology, Dr. Bohr Gasse 3, A-1030 Vienna, Austria.

4 University of Natural Resources and Life Sciences, Muthgasse 18, A-1190 Vienna, Austria.

Glycosylation, the covalent attachment of simple or complex sugar structures onto proteins, is the most abundant post-translational modification in biology. Over 50% of human proteins are subject to these dynamic modifications, which alter their activities in fundamental biological processes, such as cell adhesion, nuclear transport, signal transduction, intracellular trafficking, protein localization, host-pathogen interactions, or essential immune functions. However, despite its key importance in biology, the identification and functional validation of the glycosylation profiles of complex glycoproteins has remained largely unexplored. We developed a novel quantitative approach to isolate intact glycopeptides from comparative proteomic data-sets, allowing us to not only infer complex sugar structures but also to directly map them to sites within the associated proteins at the proteome scale. Applying this method to human and murine embryonic stem cells, we provide a first draft of the stem cell glycoproteome, nearly doubled the number of experimentally confirmed glycoproteins, identified previously unknown glycosylation sites and multiple glycosylated stemness factors, and uncovered evolutionarily conserved as well as species-specific glycoproteins in embryonic stem cells. Specificity of our method was confirmed using sister stem cells carrying repairable mutations in enzymes required for fucosylation, Fut9 and Slc35c1. Ablation of fucosylation confers resistance to the bioweapon ricin. We were indeed able to identify proteins that carry a fucosylation-dependent sugar code for ricin toxicity. Genetic mutations disrupting a subset of these proteins rendered cells ricin resistant, identifying new players that orchestrate ricin toxicity. Our novel comparative and high-throughput glycoproteomics platform enables genome-wide insights into protein glycosylation and sugar modifications in complex biological systems.

36

Identifying oxidation-specific post-translational modifications in diet-induced liver inflammation

Juliane Weißer1, Tim Hendrikx2, Christoph J. Binder1,2

1) CeMM Reseach Center for Molecular Medicine of the Austrian Academy of Scienes, Vienna, Austria

2) Department of Laboratory Medicine, Medical University of Vienna, Vienna, Austria

Introduction Oxidative processes are a hallmark of many chronic inflammatory diseases. Increased oxidative stress leads to the generation of highly reactive species that can irreversibly modify proteins and other biomolecules. There is accumulating evidence that oxidative modification of proteins renders them immunogenic and can therefore lead to the perpetuation of an inflammatory process. However, there is little information on the exact epitopes that trigger immunogenicity. Although many oxidation-specific epitopes are targeted by specific antibodies, the exact identity of these epitopes is largely uncharacterized on the molecular level. Methods We are applying an unbiased screening approach to identify previously unrecognized oxidation-derived post-translational modifications (PTMs) that may act as mediators of liver inflammation. LDL-receptor KO mice susceptible diet-induced dyslipidemia are fed a high fat diet, which triggers hepatic inflammation. Livers are subjected to proteomic analysis on an Orbitrap Fusion Lumos Tribrid mass spectrometer, and PTMs are identified using a high-tolerance database search (Chick et al, Nat. Biotechnol. 2015). The main advantage of this approach is that there is no need to have any a priori knowledge of expected PTMs, and therefore it is able to identify novel modifications. Results and Discussion By applying the tolerant database search we were able to identify a set of post-translational modifications that were more abundant in inflamed liver tissue from high fat diet-fed mice than in liver tissue from control mice. In addition, some of these candidate modifications exhibit specific binding towards selected natural IgM antibodies that had been previously cloned for the ability to bind different oxidation-specific epitopes. It is noteworthy that most candidate modifications appear to be derived from reactive aldehydes arising from lipid peroxidation. In conclusion, we provide direct evidence of oxidation-specific epitopes in hepatic inflammation that have the potential to modulate the immunological response. Innovative aspects

• Application of an unbiased PTM mapping strategy to identify potentially novel PTMs

• Direct evidence for possibly aldehyde-derived protein modifications in chronic liver inflammation

37

Poster Abstracts

Lipid metabolism in the regulation of autophagy and aging in yeast

Angelina Gross1, Sabrina Schroeder1, Tobias Pendl1, Andreas Zimmermann1, Sandra Ortonobes Lara1, Hannes Schoenlechner1, Ana Santiso Sanchez1, Laura Lamplmayr1, Kirsten Harmrolfs5, Rolf Mueller5, Sara Stryeck2, Tobias Madl2,3, Oskar Knittelfelder4,

Andrej Shevchenko4 and Tobias Eisenberg1,3 1 Institute of Molecular Biosciences, University of Graz, Graz, Austria

2 Institute of Molecular Biology and Biochemistry, Medical University of Graz, Austria 3 BioTechMed Graz, Graz, Austria

4 Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany 5 HIPS Helmholtz-Institute for Pharmaceutical Research Saarland, Saarland University,

Saarbruecken, Germany

Introduction Autophagy, a cellular process to remove and recycle superfluous and damaged cellular material, is crucial for metabolic homeostasis and has been linked to healthy aging. Previously we showed that nucleo-cytosolic availability of acetyl-CoA functions as a rheostat, regulating autophagy during starvation and aging (1, 2). In our current work we are interested in the role of Acetyl-CoA Carboxylase 1 (Acc1) in aging yeast. Thus, we aim to investigate the mechanisms, by which Acetyl-CoA and fatty acid metabolism are orchestrated to efficiently maintain healthy aging and autophagy. Acc1 catalyses the first step in de novo lipid-biosynthesis by utilizing acetyl-CoA and is thus essential for maintaining lipid homeostasis. Methods We modulate the activity of Acc1 through various genetic and pharmacological means and assess the metabolic and lipidomic consequences and their implications in the regulation of aging and autophagy. Here we present a lipidomic analysis of aging cells after modulation of Acc1 and correlate the observed changes to the respective autophagic activity. Results and Discussion We show that changes in acetyl-CoA associated metabolism are sufficient to modulate autophagy and correlate with the abundance of specific lipid species. This work will help us to understand the complex interplay of central metabolism in maintaining cellular homeostasis and to identify potentially causal lipid molecules in the regulation of autophagy and aging. References:

(1) Eisenberg T et al., Nucleocytosolic depletion of the energy metabolite acetyl-coenzyme A stimulates autophagy and prolongs lifespan. Cell Metab. 2014 Mar 4;19(3):431-44.

(2) Marino et al., Regulation of autophagy by cytosolic acetyl-coenzyme A. Mol Cell. 2014 Mar 6;53(5):710-25

Innovative aspects

• Lipid profiling for the identification of metabolic regulators in autophagy and aging

• Acetyl-CoA carboxylase 1 as a key regulator in autophagy and aging

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Metabolic Phenotype of Dipeptidyl peptidase III knockout mice

Benjamin Bourgeois1, Shalinee Jha2, Peter Macheroux2, and Tobias Madl1

1) Institute of Molecular Biology and Biochemistry, Medical University of Graz, 8010 Graz, Austria

2) Institute of biochemistry, Technical University of Graz, 8010 Graz, Austria

Introduction Dipeptidyl peptidase III (DPP-III) belongs to the M49 family of metallopeptidases. It is a zinc-dependent aminopeptidase which sequentially hydrolyses dipeptides from the N-terminus of oligopeptides ranging from 3 to 10 amino acid residues. The exact function of this peptidase is still unclear. However, a number of studies suggest its contribution in terminal stages of protein turnover. DPP-III is ubiquitously expressed in human tissues and has been linked to several pathophysiological phenomena. Altered expression of DPP-III was observed in primary ovarian carcinoma, oxidative stress, pain, inflammation and cataractogenesis. Therefore, getting more details on the molecular and cellular DPP-III function led to resurgence of interest the past years in order to precise the role of the peptidase in these pathophysiological processes. Methods We used non-targeted NMR-based metabolomics to study DPP-III wild-type versus knock-out mice (serum, urine and tissues samples) in order to get detailed insight into the metabolic phenotype linked to this metallopeptidase and therefore to its cellular function. Results and discussion We show that DPP-III knock-out mice have a significantly different metabolic profile compared to wild-type mice in urine and kidney tissue whereas no differences could be observed in serum samples. DPP-III knock-out mice present decreased level of TCA cycle metabolites in urines samples (α-ketoglutarate, citrate and succinate). Analysis of kidney samples revealed a role of DPP III in the nicotinamide metabolism. Indeed, DPP-III knock-out mice show increased levels of nicotinamide / nicotinamide riboside and decreased levels of NAD+ which might lead to the observed diminution of TCA cycle flux. We also observed decreased levels of indoxyl sulfate in urine samples of DPP-III knock-out mice. Indoxyl sulfate is synthetized in the liver from indole and is normally excreted into urine. Interestingly, a previous study showed that a DPP-IV inhibitor decreases the toxic effect of indoxyl sulfate on kidney tubular cells (Wang WJ et al., 2014). However the exact function of DPP-IV on indoxyl sulfate, metabolism / localization is unknown yet. Taken together our data provide for the first time the metabolic phenotype of DPP-III knock-out mice, an essential step in order to unravel the DPP-III function in cell and its dysfunction in diseases. Innovative aspects

• First metabolomics study of DPP-III knock-out mice

• Untargeted analysis leading to the observation of a broad range of metabolites Wang WJ et al., DPP-4 attenuates toxic effects of indoxyl sulfate on kidney tubular cells. PLoS one (2014)

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2D-DIGE of extracellular matrix proteome from 3D cultured mesenchymal stem cells, and its secretome

analysis

Dolly Mushahary1, Verena Charwat1, Anne Koch2, Martina Marchetti-Deschmann2, and Cornelia Kasper1

1) Department of Biotechnology, University of Natural Resources and Life Sciences, Vienna, Austria

2) Division of Instrumental Analytical Chemistry, Institute of Chemical Technologies and Analytics, Technical University Wien, Vienna, Austria

Introduction Proteins that are secreted from the cells play a crucial role in many physiological and pathological processes. We categorized proteins secreted from the cells into the insoluble extracellular matrix (ECM) and the soluble secreted proteins. It is known that acellular ECMs can be used as scaffolds for stem cell expansion and differentiation. In order to develop more physiologically relevant scaffolds, 3D cultured adipose-derived mesenchymal stem cells (adMSCs) were dissociated into monolayer culture. This spheroid dissociation enhanced the matrix formation by influencing protein expression and biology of matrices. Also, understanding the secretome can give us additional information on cell migration, cell signalling and communication. Since normoxia and hypoxia can modulate expansion and differentiation of cells in culture, the present study focus on the characterization and detection of changes in the ECM proteome and depleted secretome of adMSCs, after normoxic and hypoxic cultivation, by DIGE approach.

Methods Human adMSC spheroids were dissociated and cultured as monolayer under hypoxic (5%) and normoxic (20%) oxygen concentrations. The cultures were decellularized to obtain acellular ECM. Proteins were extracted, TCA precipitated, dissolved in IPG-buffer (6M Urea, 2M Thiourea, 4% CHAPS), labelled with CyDyes and separated on 12.5% gels (HPE Tower, 255x200x0.65 mm, Serva). For secretome analysis, adMSCs were cultivated under different oxygen supply with fetal calf serum (FBS) in a bioreactor. High-abundant protein depletion and low-abundant protein enrichment were applied using a combinatorial peptide library (ProteoMiner, Bio Rad) and depletion columns (Top 12, Pierce). Proteins were separated and visualized by fluorescence (Serva Purple, Serva) and silver staining. For DIGE, samples were minimally labeled with G-Dyes (NH DyeAGNOSTICS) and separated the same way.

Results and Discussion The characterization of acellular ECM from 2D and 3D cultures demonstrated superior protein expression of spheroid-dissociated hypoxic culture, with higher protein concentration as compared to the monolayer culture. Comparative proteomic analysis of both matrix types indicated differential protein expression in all tested culture conditions. It was difficult to detect and visualize low-abundant proteins in secretome analysis. Therefore, high-abundant serum proteins had to be significantly removed using Top12 depletion spin columns. The risk of co-depletion of low abundant proteins was considered to be very likely and hence a combinatorial peptide library was tested, but showed lower efficiency for serum protein removal. We assumed that co-depletion is reduced under these conditions and a more complete coverage of the secretome will be achieved. We therefore further enhanced and evaluated the latter approach to show reproducibility and robustness of sample preparation. It can be concluded that both the methods efficiently reduced high-abundant serum proteins giving access to the interesting secretome of MSCs. Future work will focus on the identification of differentially expressed proteins by mass spectrometry for both the ECM proteome and secretome of MSCs.

40

Innovative aspects

• Understanding the proteome of a more physiologically relevant matrix from spheroid-dissociated hypoxic ECM system.

• Efficient method for analysis of low-abundant secretory proteins which otherwise are difficult to isolate and analyze.

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The loss-less and nano-flow SPIDER fractionator for high sensitivity, high coverage proteomics

Nils Kulak1, Philipp E. Geyer2, Garwin Pichler1, Matthias Mann2

1PreOmics GmbH, Planegg, Germany 2Max Planck Institute of Biochemistry,Planegg, Germany

Introduction Sample preparation workflows are a crucial part of mass spectrometry (MS)-based proteomics measurements. To achieve near-comprehensive identification and quantification of cellular proteomes, the combination of a first HPLC-based peptide fractionation orthogonal to the online LC-MS/MS step has proven to be particularly powerful. Here, were describe a novel approach termed “SPIDER fractionator”, in which the post-column flow of a nanobore chromatography system enters an eight-port flow-selector rotor valve. The valve then switches the flow into different flow channels at constant time intervals, collecting the fractions into autosampler vials of the LC-MS/MS system. The SPIDER system enables loss-less and robust peptide fractionation of sample amounts ranging from 100 µg down to 1 µg while quantifying close to 10,000 proteins. Methods The SPIDER fractionator is a software-controlled fully automated fraction collector based on a rotorvalve system and coupled online to any nanoflow HPLC. Prefractionation is achieved with a first dimension high pH reversed phase column (250 µm i.d., 30 cm length, 1.9µm C18 particle size) to separate peptides by an eight-port flow-selector rotor valve, distributing the sample flow into consecutive tubes for the pooled fractions. The SPIDER collection system is freely configurable and employs loss-less concatenation of the samples into 2 to 96 fractions ensuring equal distribution of the peptides across the analytical gradient with efficient peak separation. The fractionator is highly compatible with most sample preparation workflows and thereby allows in-depth analysis of complex proteomic samples Results and discussion We demonstrate excellent sensitivity of our SPIDER fractionator by decreasing sample amounts from 100 µg to the sub-µg range, without any losses attributable to the fractionation system and while quantifying close to 10,000 proteins. Furthermore, we applied our system to an automated and in-depth characterization of 12 different human cell lines with a median depth of 11,300 proteins. We now routinely apply the SPIDER fractionator to various body fluids such as plasma, urine or CSF, as well as to tissue samples such as brain, heart or liver in order to generate in-depth peptide libraries. Such libraries are then used to transfer the peptide sequence information from the library to the actual sample runs. Thus, we are now able to quantify more than 10,000 proteins in single-shot runs of mouse brain tissue in combination with SPIDER-based peptide prefractionation. Innovative aspects

• The SPIDER fractionator is an easy-to use-technology.

• the first nano-flow fully automated peptide pre-fractionation device

• Enable comprehensive and robust proteome characterization with high sensitivity and minimal sample requirements

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Molecular mechanisms of oxidative stress regulation by the TOR signalling pathway regulator-like protein

Gesa Richter1, Loes van Dam2, Tobias Dansen2, and Tobias Madl1

1) Institute of molecular Biology and Biochemistry, Medical University Graz, Graz, Austria 2) Department Molecular Cancer Research, University

Introduction Reactive oxygen species (ROS) are important signaling molecules, which play important roles in cellular proliferation1, autophagy2 and apoptosis3. High levels of these molecules can cause damage to proteins, lipids and DNA called oxidative stress4. TOR signalling pathway regulator-like (TIPRL) is an inhibitory regulator of protein-phosphatase-2A and we found recently that it responds to high ROS levels in cells by oxidation of its cysteine residues and thus disulfide-dependent oligomerisation. The detailed function of TIPRL, however, remains elusive.

Methods Here we used NMR Spectroscopy as non-destructive, quantitative and highly reproducible technique to investigate metabolic changes in retinal pigment epithelium (RPE) cells, expressing TIPRL with or without cysteine-mutations in a doxycycline-inducible expression system. Harvested cells were lysed and sonicated, lyophilized and re-suspended in NMR metabolomics buffer to record NMR spectra. Data analysis was carried out using a multivariate statistics pipeline.

Results and Discussion We will present metabolic differences under conditions of wildtype TIPRL expression, and expression of a TIPRL construct in which all cysteine residues were mutated to serines (TIPRL∆Cys), and the comparison of wildtype TIPRL versus TIPRL∆Cys. Glutamate, glutamine, O-phosphoycholine and creatine are significantly decreased and branch-chain amino acids significantly increased in RPE cells expressing wildtype TIRPL. RPE cells expressing TIPRL∆Cys show a significant increase in myo-inositol as well as a significant decrease in creatine compared to non-treated cells. Comparing wildtype TIPRL and TIPRL∆Cys expressing RPE cells, we found significant increased levels of glutamate, glutathionine, aspartate, O-phosphocholine, creatine and ADP as well as significantly decreased levels of branch-chain amino acids and phenylalanine in TIPRL∆Cys expressing RPE cells. We have a first metabolic read-out showing that TIPRL cysteine-dependent oligomerization plays a crucial role in cellular ROS response as the TIPRL∆Cys expressing cells show a different metabolic pattern of ROS-related metabolites (aspartate, creatine, glutathionine, glutamate) compared to the wildtype TIPRL expressing cells. Taken together our data present the first metabolic study of TIPRL expressed in human cells allowing to get more insight in TIPRL function in oxidative stress signalling.

Innovative aspects

• NMR Spectroscopy as a highly reproducible and fast tool compatible with targeted and untargeted analysis to detect and quantify metabolites in cells, tissue or biofluids

• First metabolomics study of TIPRL and its regulating effect on ROS References (1) Chui, J. & Dawse, I.W. Trends in Cell Biology 22, 592-601 (2012); (2) Scherz-Shouval, R. Elazar Z. Trends in Biochem Sci 36, 30-38(2011); (3) Simon, H.U. et al. Apoptosis 5, 415-8(2000); (4) BA, F. & JD, C. Biology of disease: free radicals and tissue injury. Lab Invest 47, 412-426 (1982)

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Workflow and Results of a Metabolomics Analysis of Tuberculosis Drug Activity Using High-Resolution

Accurate Mass Spectrometry

Holger Stalz1, Yuqin Dai2 1) Agilent Technologies Switzerland AG, Basel, Switzerland

2) Mass Spec Division, Agilent Technologies Inc., Santa Clara, USA

Introduction Tuberculosis (TB) is both the leading cause of deaths due to an infectious disease and the leading cause of deaths due to a curable disease. However, drug resistance is increasing while the pipeline of new drugs stagnates, and knowledge of existing drugs remains incomplete. Pyrazinamide (PZA) is a frontline TB drug whose mechanism of action remains among the most poorly understood. Here, we present a Q-TOF LC/MS method that has enabled the biologically unbiased study of the impact of PZA on the Mycobacterium tuberculosis metabolome. Coupled with batch feature extraction and multivariate statistical analysis software, this workflow enabled the discovery of activity-specific metabolic changes that may help explain PZA’s unique metabolic effects.

Methods An ion-pairing reversed-phase (IP-RP) chromatography method was used to achieve a wide coverage of metabolite classes and improve retention time reproducibility. LC/MS analyses were performed using an Agilent 1290 Infinity UHPLC system coupled to an Agilent 6545 Q-TOF. For data analysis, a metabolomics workflow was developed. This workflow includes the following steps: 1. Acquisition of high quality data from the tuberculosis cell extracts (three samples/biological group of six biological groups) using the Q-TOF LC/MS in negative ion mode. 2. Find metabolites from raw data using the Profinder Software algorithm with a user-created targeted database containing 111 metabolites. 3. Perform differential analysis using Mass Profiler Professional (MPP) Software and map the differential metabolites to KEGG pathways to gain insight into the mechanistic details of PZA activity.

Results and Discussion Principal Component Analysis (PCA) is one of the most common unsupervised data analysis tools used to identify data patterns and quality. The PCA of the acquired data clearly detected the separation of biological groups with cell growth at two different pH conditions. Furthermore, PCA captures the overall variability in the metabolome of actively dividing cells taken from neutral pH in comparison with the lower variability of the nongrowing condition (pH 5.5). In this study, PZA-treated samples showed dose-response efficacy at pH = 5.5, while at pH = 6.6 (bacteriostatic dose), efficacy was completely lost. To gain insight into PZA’s mechanism of action, a differential analysis using MPP was performed. Fifty-four of the 73 metabolites displayed statistical significance, and 28 of them showed at least 1.5-fold changes in the abundance in the PZA(s)-treated samples compared to the control at pH 5.5. A pathway analysis of the KEGG pathways for Mycobacterium tuberculosis displayed that 23 pathways with at least five or more statistically significant metabolites were affected.

Innovative aspects

• Development of a complete workflow for a Metabolomic Analysis of a drug effect.

• A robust ion-pairing reversed-phase chromatography significantly improves retention time reproducibility.

• Agilent MassHunter Profinder and MPP software enables the identification of a specific metabolic biosignature for PZA-treated Mycobacterium tuberculosis.

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Comprehensive Analysis of Genomic Data for 16 CHO Cell Lines to Investigate the (In)stability of the CHO Genome

Julia Feichtinger1,2, Christoph Fischer1,3, Inmaculada Hernandez4,6, Heena Dhiman5,6,

Nicole Borth5,6, and Gerhard Thallinger1,2 1) Institute of Computational Biotechnology, Graz University of Technology, Graz, Austria

2) Omics Center Graz, BioTechMed Graz, Graz, Austria 3) Institute of Zoology, University of Graz, Graz, Austria

4) Institute of Cellular Medicine, Newcastle University, Newcastle upon Tyne, UK 5) University of Natural Resources and Life Sciences Vienna, Austria.

6) Austrian Centre of Industrial Biotechnology, Vienna, Austria.

Introduction Mammalian cell lines such as Chinese Hamster Ovary (CHO) cells are frequently used as model systems for research applications and as cell factories for production of recombinant proteins, which are increasingly important in clinical applications. One of the main issues in the development of CHO production cell lines, however, is the frequent reduction or even loss of recombinant protein production during long-term culture. Although the underlying changes related to this are not well understood, the unstable nature of the CHO genome has been suggested to cause loss or mutation of transgenes. As mutation rates are not constant across the genome of mammalian cells, we aim to identify stable regions in the genome suitable for targeted integration, which could enable robust production of therapeutic proteins over time. Methods Genomic data of 16 so far published CHO cell lines were included into an analysis to identify the relative density of mutations in all genomic regions. The analysis steps comprise preprocessing, alignment to the reference genome, variant calling and mutation density analysis. Results and Discussion The genome of mammalian cell lines is undergoing continuous and random alterations, which are not necessarily relevant to phenotypic changes induced/observed. This is in agreement with the suggestion that in cancer cells the vast majority of mutations are not necessarily relevant. Our analysis revealed high variation of SNP density in the CHO genome, similar to cancer cells, which are also known for their high mutation rates and high heterogeneity across the genome. Using genomic data of all 16 cell lines, we determined low SNP density regions present across all cell lines. As mutation rates have been shown to be lower in open chromatin and highly expressed regions, possibly due to higher accessibility to repair mechanism, we aim to further refine these stable regions by overlaying RNA-seq and ChIP-seq data. In addition to the identification of suitable regions for targeted integration, we may also be able to identify genomic variants relevant for cell behaviour. Both objectives not only have implications for research in the field but could also have large economical and medical consequences. Innovative aspects

• Genome-wide determination of stable regions.

• Investigation of the contribution of genomic variations towards behaviour and stability of phenotypes.

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Mitochondrial fragmentation in fatty liver

Juergen Gindlhuber1,2, Barbara Darnhofer1,2,3, Bettina Pucher1,2,4, Tamara Tomin1,2, Gerhard Thallinger2,4, and Ruth Birner-Gruenberger1,2,3

1) Dep. of Pathology, Medical University of Graz, Graz, Austria 2) Omics Center Graz, BioTechMed-Graz, Graz, Austria

3) Austrian Center of Industrial Biotechnology, Graz, Austria 4) Dep. of Computational Biotechnology, Graz University of Technology, Graz, Austria

Introduction In periods of high fatty acid load in the plasma, when either a fat rich diet is consumed or when fatty acids are released from adipose tissue to compensate for starvation, the liver acts as buffer by storing fatty acids as triacylglycerol in lipid droplets. These fatty acids can be remobilized for lipoprotein synthesis to provide fatty acids to other organs, burned in liver mitochondria to provide energy for the liver or used for liver cellular membrane biosynthesis or as lipid signaling molecules. Previous data from our group suggested a high plasticity of the mouse liver lipid droplet proteome in dependence of diet. Especially mitochondrial proteins were found to be enriched in primary hepatocyte lipid droplet proteomes isolated from mice fed a high fat diet or fasted as compared to mice fed a regular diet. The aim of this study was to investigate the increased lipid droplet mitochondrial crosstalk under conditions of higher liver lipid load suggested by the data. We thus employed fluorescence microscopy to reveal morphology changes of mitochondria in dependence of lipid droplet volume.

Methods We performed label free quantitative proteomics of lipid droplets of primary hepatocytes isolated from mice fed with regular or high fat diet or fasted overnight to investigate the plasticity of the liver lipid droplet proteome in dependence of diet. To induce lipid droplets in hepatocytes we loaded a human hepatocyte cell line (HepG2) with increasing amounts of fatty acids and determined the lipid droplet volume per cell by fluorescence microscopy. We then analysed the co-localisation of mitochondria and lipid droplets as well as mitochondrial morphology by live cell imaging to avoid artefacts by fixation.

Results and Discussion When we compared lipid droplet proteomes of primary hepatocytes isolated from mice fed with regular or high fat diet or fasted overnight we found mitochondrial proteins to be enriched in mice fed a high fat diet or fasted as compared to mice fed a regular diet. These results could indicate a higher degree of membrane contact between lipid droplets and mitochondria caused by morphological changes induced by the high lipid load. We could not observe increased interactions between mitochondria and lipid droplets by fluorescence microscopy in our cell model. Instead, we noticed profound differences in lipid droplet generation upon saturated versus unsaturated fatty acid feeding coinciding with changes in growth. Palmitic acid, which is a better substrate for mitochondrial beta-oxidation than oleic acid, induced less lipid droplets per cell and less total lipid droplet volume than oleic acid. In addition, it also reduced growth due to its known lipotoxic effects. Using live cell imaging, we visualised that under standard cell culture conditions liver cells display a large interconnected network of mitochondria whereas cells treated with fatty acids show varying stages of mitochondrial fragmentation. This effect is especially prevalent in cells treated with palmitic acid. Mitochondrial fragmentation is a

46

known mechanism to inactivate mitochondria. When cells are treated with fatty acids it may protect them from a high degree of ROS production. The increased co-isolation of mitochondria with lipid droplets under conditions of increased lipid load may be due to the altered mitochondrial morphology.

Innovative aspects

• Mitochondrial fragmentation may protect cells from a high degree of ROS production when treated with fatty acids.

• Increased co-isolation of mitochondria with lipid droplets under conditions of increased lipid load may be due to altered mitochondrial morphology.

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Deciphering Staphylococcus aureus within-host adaptation in chronic bovine mastitis - A surface

proteomic approach

Katharina Mayer1, Martin Kucklick2, Monika Ehling-Schulz1, Susanne Engelmann2, and Tom Grunert1

1) Functional Microbiology, Institute of Microbiology, Dept. of Pathobiology, University of Veterinary Medicine, Vienna, Austria

2) Microbial Proteomics, Helmholtz Centre for Infection Research, Braunschweig, Germany

Introduction Staphylococcus aureus is an opportunistic bacterial pathogen in humans and animals, which frequently causes chronic and persistent mastitis in dairy cattle. Bovine mastitis, an infection of the mammary gland, negatively affects the milk yield and quality and is difficult to treat with antibiotics. Several studies suggest the emergence of specific host-adapted S. aureus subtypes able to survive in the bovine mammary gland, even for years. This project aims to shed light on the mechanisms of S. aureus host-adaptive lifestyles in the progression of chronic bovine mastitis. During three months weekly monitoring of a naturally infected dairy cattle we were able to follow the phenotypic transition of S. aureus adapting to its host. These strains are ideal to analyse factors contributing to the persistence of S. aureus in the bovine mammary gland as the adaptation of the bacteria can exclusively be assigned to the impact of the host. Methods Host adaptive processes of S. aureus were investigated using proteome-based methods specifically targeting the bacterial cell surface. Thus, the initial and host-adapted mastitis isolates were analysed using a surface-shaving and a surface-biotinylation approach. Bacteria were grown under iron-limiting and microaerophilic conditions to mimic the in vivo conditions in the udder. The shaving approach uses the proteolytic cleavage property of immobilized trypsin to collect peptides exposed on the cell surface, whereas the biotinylation approach requires biotin-labelled surface proteins followed by purification using agarose-avidin beads. Metabolic labelling (SILAC) followed by LC-MS/MS was employed to identify relative quantitative differences between the initial and host-adapted mastitis isolates. Results and Discussion The combination of the complementary cell-surface analyses, surface-shaving and surface-biotinylation, will provide a comprehensive insight in the ongoing adaptations by the host-specific immune defence. We hypothesize that qualitative and quantitative changes of the surfactome enables S. aureus to evade the host immune response and to promote the intramammary infection. Newly identified candidate molecules of persistence will be selected and transcriptional analysis (RT-qPCR) as well as targeted gene knock-outs will be performed. Innovative aspects

• Using a unique collection of host-adapted prototype strains, where key factors of persistence can be exclusively assigned to the natural selection process within the host

• Analysis of modifications of S. aureus surface-associated proteins via quantitative surface-shaving and surface-biotinylation

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Proteome-wide impact of oleic and palmitic acid induced steatosis in human liver cells.

Laura Liesinger1,2, Jürgen Gindlhuber1,2, Bettina Pucher2,3, Gerhard Thallinger2,3 and Ruth

Birner-Gruenberger1,2 1Medical University of Graz, Institute of Pathology, Graz, Austria;

2Omics Center Graz, BioTechMed Graz, Graz, Austria 3Institute of Computational Biotechnology, Graz University of Technology, Graz, Austria;

Introduction Treatment of liver cells with fatty acids has been shown to result in steatosis followed by cellular dysfunction and in several cases apoptosis. Palmitic (PA) and oleic acid (OA) are the most abundant fatty acids contained in western diets and found in human plasma. The saturated PA and monounsaturated OA fatty acid have differential effects on cellular mechanisms. Whereas PA enhances lipotoxicity, OA can be protective against it at similarly high fatty acid levels. Therefore proteomic analysis of HepG2 cells treated with increasing concentrations of PA and OA compared to untreated controls should reveal deeper insights and a better understanding of cellular bimolecular consequences of steatosis. Methods Hepatocellular carcinoma cells (HepG2) were incubated with different concentrations of either PA or OA (50 µM, 125 µM, 250 µM and 500 µM) complexed with BSA or BSA alone for 24 h in FBS-free RPMI medium. After cell lysis, protein was digested with trypsin overnight and peptides were analysed by LC-MS/MS. Label-free quantitation was performed using MaxQuant. Protein abundance changes were evaluated by ANOVA,Tukey`s and post-hoc testing. Reactome pathway analysis was performed to depict enriched cellular pathways. Results and Discussion The treatment with either PA or OA resulted in 489 and 112 changed proteins respectively; this already indicates a much higher impact of PA on cellular functions than OA. Deeper insights through Reactome analysis reveal only minor effects on cellular pathways by OA treatment. In contrast the increase of PA leads to an over-representation of several pathways (like signal transduction, gene expression, DNA replication, cell cycle, immune system, disease, programmed cell death and cellular response to stress) which is more pronounced with increasing fatty acid concentration. Innovative aspects

• Liver proteomes in dependence of different concentrations of saturated and unsaturated fatty acid supplementation are investigated.

• Revealed altered proteins and pathways may be involved in pathogenesis of Non Alcoholic Fatty Liver Disease.

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In-depth proteome-profiling to evaluate a novel combinatory metronomic treatment

for therapy-resistant multiple myeloma patients

Janker L.1, Slany A.1, Reichle A.2, and Gerner C.1 1) Department of Analytical Chemistry, University of Vienna, Vienna, Austria 2) Klinik und Poliklinik für Innere Medizin III, University Hospital Regensburg,

Regensburg, Germany

Introduction Multiple myeloma is an incurable plasma cell tumor of the bone-marrow. Despite recent progress, basically all myeloma patients relapse and need second-line therapies and finally become therapy-resistant. Moreover, there are no stratification possibilities to determine the best therapy for each individual patient. Actually, new therapeutic approaches as well as screening methods to assess the status of the tumor cells and the tumor-associated stroma of each individual patient would be of enormous value. In the present work, a novel combinatory metronomic treatment method for therapy-resistant myeloma patients, focusing on tumor and stromal cells, was evaluated. A non-invasive method based on in-depth proteome profiling analyses of blood serum samples was applied to assess the status of tumor cells and stroma of patients before and during therapy, thus allowing monitoring the therapeutic response in an individual fashion. Methods Serum samples of seven patients participating in the clinical study were analyzed, taking samples before and at different time points after the beginning of the therapy. Samples of patients and of three healthy volunteers were depleted, proteins were digested with trypsin and resulting peptides were subjected to a nano-LC-MS/MS analysis using a QExactive orbitrap mass spectrometer for proteome profiling. Identification of proteins, label-free quantification and statistical analyses were performed using the MaxQuant software. Results and Discussion A total of 381 protein groups was quantified across all samples. Multiple comparisons of individual patient profiles and control samples revealed a general regulation of proteins involved in hemostasis, angiogenesis, inflammation, acute phase reaction, proliferation, immunomodulation and tissue remodeling. Interestingly, especially the levels of stromal proteins were affected by the therapy. Prognostic marker proteins as well as markers able to monitor the therapeutic response in each individual patient could be determined, demonstrating the usefulness of the currently presented in-depth proteome profiling method. Innovative aspects

• Possible prognostic markers in regard to therapy response

• Non-invasive monitoring of proteomic changes in serum samples during treatment with metronomic chemotherapy

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Two softwares are better than one: Broadening the horizon of quantitative mass spectrometry data in yeast

phosphoproteomics

Marion Janschitz1, David Hollenstein2, Natalie Romanov3, Gustav Ammerer2, Wolfgang

Reiter2 1) Children’s Cancer Research Institute (CCRI), St.Anna Kinderkrebsforschung, A-1090 Vienna, AUT

2) Department for Biochemistry, Max F. Perutz Laboratories (MFPL), University of Vienna, A-1030 Vienna, AUT

3) Structural&Computational Biology Unit, European Molecular Biology Laboratory (EMBL), 69117 Heidelberg, GER

Introduction High-throughput screening methods are used to globally analyse biological processes. Analogous to genetic screens, quantitative mass spectrometry shotgun approaches enable researchers to unravel signalling networks by monitoring proteome-wide cellular responses to physicochemical stimuli. Although software packages used for quantification use increasingly sophisticated algorithms, the comprehensiveness of large datasets remains challenging, especially when a reasonable overlap of various experiments is necessary. Our group used a quantitative MS-based phosphoproteomics approach to identify substrates of the mitogen-activated protein kinase Hog1, a p38 homolog and key regulator of the high osmolarity glycerol pathway in S.cerevisiae. To increase coverage of quantified phosphorylation sites we used two commonly applied MS-software packages, Proteome Discoverer (PD) and MaxQuant (MQ), and compared their performance on our dataset. Methods Yeast cells were isotopically labeled using SILAC. Proteins were extracted using the TRIzol (Invitrogen) reagent and digested with trypsin. Phosphopeptides were enriched using TiO2 beads and offline fractionated by strong cation exchange chromatography. Peptide samples were analyzed by LC-MS/MS, using an ESI-LTQ-Orbitrap Velos system (Thermo Scientific Fisher). Raw data was analysed using Proteome Discoverer 1.3 and MaxQuant 1.5.2.8, parameter settings are described in the PRIDE database (PXD004294 to PXD004300). Hog1-targets were defined as showing i) increased phosphorylation upon stress treatment (0.5M NaCl), ii) decreased phosphorylation during stress upon Hog1-inhibition Results and Discussion In total, we found 237 proteins to have stress-responsive Hog1-dependent phosphorylation sites, with an overlap of 82 proteins between PD (+56 individual proteins) and MQ (+99 individual proteins). Within the overlap, quantified sites showed a correlation of R > 0.7 for stress behaviour and Hog1-dependency. Focussing on putative direct Hog1 target sites (S/TP-motifs), we found 18 phosphorylation sites corresponding to 16 proteins that were assigned as Hog1-targets in both the PD and MQ search, and additional 28 proteins covered by either one software individually (9 PD, 17 MQ). Noteworthy, most of the putative new Hog1 substrates were validated and tested positive using a protein-protein-proximity assay called M-Track. In summary, analysing a real dataset using two software packages increased the output by ~30%. Our results clearly show the advantages of increased coverage by using multiple programs. For example, we found Hog1-dependency of sphingolipid homoeostasis factor Orm2, which is involved in the usually Hog1-independent Ypk1-mediated hyperosmotic stress response, only in the MQ search. MQ also revealed a strong downregulation of Ypk1 on several sites during hyperosmotic stress and confirmed dynamic phosphorylation at two Hog1 target sites, T1225 of Pan1 and T361 of Nup2.

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Innovative aspects

• Combining two MS-software packages increases the output of quantitative MS-datasets by up to 30%

• Putative interactors derived from quantitative MS data should always be validated via a different screening method, for example a protein-protein-proximity assay

• Sphingolipid homoeostasis factor Orm2, which is involved in the Hog1-independent hyperosmotic stress response (TORC2-Ypk1 signalling), harbours at least one Hog1-dependent phosphorylation site.

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Gene prediction and gene set analysis of Nicotiana benthamiana

Matteo Schiavinato, Richard Strasser, Juliane Dohm, Heinz Himmelbauer [email protected]

BOKU - Universität für Bodenkultur, Muthgasse 18, 1190 Vienna, Austria

Introduction Nicotiana benthamiana is a species of tobacco which has become a popular expression platform for recombinant protein production. Many specific studies have been performed in this plant, and a draft genome assembly (Nb-1) was published in 2012 (1). Despite its growing usage, a comprehensive analysis of the genome, the transcriptome and the proteome is still lacking. Making use of a large amount of transcriptomic sequencing data we aimed to generate a high-quality gene set for this widely used plant species. We also analyzed the functions of the encoded protein sequences and we put them into the context of the Nicotiana genus.

Methods We used the Nb-1 draft genome assembly as reference genome sequence, on which we modeled transposable elements (TEs). N. benthamiana mRNA seq data were downloaded from the Sequence Read Archive SRA (2). Additionally, we generated mRNA-Seq data on the Illumina platform from N. benthamiana breeding lines maintained at BOKU. We mapped the transcriptomic reads making use of two different mapping programs and combined the results. Gene prediction was performed using AUGUSTUS (3) which integrates in silico transcript modelling with evidence-based prediction supplied by mRNA-Seq data. We validated the gene set using benchmarking universal single-copy orthologs (BUSCOs) (4) and we checked its reliability by comparison to already known N. benthamiana protein sequences. We functionally annotated the gene set using custom and public protein sequence databases. We applied stringent thresholds on the E-Value (10E-10), the minimum sequence similarity (90%), the minimum alignment length (70 AA) and the minimum aligned fraction (90%). Finally, we performed an orthogroup study based on sequence similarity with other available proteomes from the Nicotiana genus.

Results and Discussion Using AUGUSTUS, we calculated a N. benthamiana gene catalog comprising 50,516 genes and 62,216 corresponding transcriptional isoforms, with an average encoded protein length of 405 AA. Our validation results show that 98.3% of plant BUSCOs were found in the gene set and that 96.5% of the available N. benthamiana protein sequences deposited in Genbank (5) match a gene set protein with at least 98% of sequence identity. Functional annotation was possible for 79% of the encoded protein sequences. An orthogroup analysis performed together with three other Nicotiana species showed two large clusters: one shared by all the four tested species, the other shared only by the three which are traditionally cultivated for smoking.

References (1) Bombarely, A et al. (2012). Mol Plant Microbe Interact 25, 1523–30.; (2) Leinonen, R et al. (2011). Nuc Acids Res 39, D19-21.; (3) Stanke, M et al. (2006). Nucl Acids Res 34, W435-439.; (4) Simão, FA et al. (2015). Bioinformatics 31, 3210–2. (5) Benson, DA et al. (2017). GenBank. Nucl Acids Res 4;45(D1), D37–42.

53

Altered kinetics of nanoparticles in the presence of plasma proteins at the human placental barrier. An ex-

vivo placental perfusion, proteomics study

Michael Gruber*, Ruth Birner-Gruenberger+, Uwe Lang*, Christian Wadsack* *Department of Obstetrics and Gynecology, Medical University of Graz, Austria

+Institute of Pathology, Medical University of Graz and Omics Center Graz, Austria

Objectives: To understand the exposure of xenobiotic nanoparticles at the placental barrier is progressively important after the increasing number of different applications in pharmaceutical and consumer products. The interaction of nanoparticles with the human placenta in the presence of a physiological protein matrix has not been investigated. The study aimed for the identification of nanoparticle bound proteins which may affect the physicochemical properties, thereby modifying the transfer properties of 80 nm polystyrene particles in an ex-vivo placental perfusion setting. Methods: Placental perfusion experiments were performed with media containing ~10% female human citrate plasma with the specific thrombin inhibitor Argatroban (33 µg/ml) to prevent coagulation. Plasma containing media was used in fetal and maternal circulation in a 6h lasting double closed perfusion setting (N=5). Polystyrene particle concentration over time was measured after perfusion in fetal and maternal circulation by quantification of fluorescence. For proteomics maternal and fetal perfusates were collected at the beginning (0min) and at the end (360 min) of the placental perfusions. Samples were centrifuged through a sucrose cushion and were washed with PBS to remove unbound proteins. Nanoparticle bound proteins were digested with trypsin. Resulting peptides were separated from the nanoparticles by centrifugation through a molecular weight cut off cartridge. Peptide containing media samples were analysed by unlabelled shotgun proteomics. One way ANOVA and paired t-test was used for statistical analysis. Results & Conclusions: Strikingly, our findings demonstrate a significant increase of 80 nm polystyrene nanoparticle transfer across the placenta with human plasma proteins. We could identify a significant difference in the protein corona of nanoparticles sampled from maternal and fetal circulation in the presence of human plasma. Further, we could identify increased vesicular transport proteins associated with particles in the maternal circulation demonstrating a multifactorial transport involvement in nanoparticle tissue interactions.

54

Integrative Omics Approach to Allergic Rhinitis: present state and future perspectives

Peter Valentin Tomazic1, Kornel Golebski2, Doris Lang-Loidolt1, Cornelis van Drunen2 and

Ruth Birner-Gruenberger3,4 1) Dept. of General ORL, H&NS, Medical University of Graz, Graz, Austria

2) Academic Medical Center Amsterdam, Amsterdam, the Netherlands 3) Institute of Pathology, Medical University of Graz, Graz, Austria

4) Omics Center Graz, BioTechMed-Graz, Graz, Austria

Introduction Mucus is the first line defence barrier of the upper respiratory tract and its proper production and transport maintains a healthy airway and protects the epithelium. Mucus mainly consists of polypeptides, cells and cellular debris, but little is known about the distinct proteins that comprise the nasal mucus proteome. As of today many studies on allergic rhinitis focus on the nasal epithelium and its involvement in the disease. However, the first body compartment that allergens reach and may harm upon inhalation is the nasal mucus. Our study aims to investigate the nasal mucus proteome as well as nasal epithelial RNA expression in patients suffering from allergic rhinitis compared to healthy controls. Methods From allergic rhinitis patients and healthy controls nasal mucus, nasal mucosa, and serum is obtained. Nasal mucus is collected with a special suction device equipped with a mucus trap from the middle meatus under endoscopic control without touching the mucosa. Nasal mucosa is obtained through nasal brushes and put into primary culture. Serum is prepared from blood samples. Patients with grass or tree pollen allergy are included and allergic state is determined by skin prick tests and RAST. Samples are obtained in and out of pollen season. Nasal mucus is analyzed by LC-MS/MS mass spectrometry for label free quantitative proteomic analysis and RNA is isolated from nasal epithelial cells for transcriptomic analysis using Affymetrix microarrays. By an integrative omics approach gene and protein expression will be correlated and cross talk between nasal mucus and epithelium will be analysed. Results and Discussion Preliminary proteomic data showed a total of 430 proteins where 327 were detected in allergics and 366 in healthy controls respectively. Of these 203 proteins (47.2%) were newly identified as nasal mucus proteins. In pollen season 10 proteins were significantly more abundant in allergic rhinitis patients than in healthy controls. These were complement C4-B (C4B), alpha-1-acid glycoprotein 2 (ORM2), and phospholipid transfer protein (PLTP), which were not detected in controls; as well as alpha-2-macroglobulin (A2M, 13.2-fold), apolipoprotein A-II (APOA2, 9.4-fold), vitamin D-binding protein (GC, 4.6-fold), complement C3 (C3, 3.6-fold), apolipoprotein A-I (APOA1, 3.6-fold), BPI fold-containing family B member 2 (BPIFB2, 2.9-fold) and clusterin (CLU, 2.6-fold). Contrary to their symptom pattern, allergic rhinitis patients show an increased inflammatory response in their nasal mucus proteome even out of pollen season. In combination with reduced defence mechanisms and an increase in inflammation in season, the nasal mucus proteome of allergic subjects reflects a decreased plasticity and thus inadequate reaction to allergen stress as compared to healthy controls. Integrative comparison of our genomic and proteomic data will allow us to see whether the defective mucus barrier is caused by hampered epithelial gene expression and thus significant defence proteins are not present in the mucus or whether proteins are dysfunctional themselves and probably degraded from outside in through harmful allergen content.

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Innovative aspects

• Nasal mucus proteins as well as epithelial gene expression are integratively analysed in the same patients and controls shedding light on barrier function and the mechanism of its destruction.

• The integrative omics approach enables identification of novel potential biomarkers for future diagnostic or therapeutic strategies.

56

The role of protein-phosphorylation in lipolysis

Petra Krenn1,2, Laura Liesinger1,2, Bettina Pucher2,3, Matthias Schittmayer1,2, Gerhard Thallinger2,3, Jürgen Cox4 and Ruth Birner-Gruenberger1,2

1) Institute of Pathology, Medical University of Graz, Graz, Austria 2) Omics Center Graz, BioTechMed Graz, Graz, Austria

3) Inst. Of Computational Biotechnology, Graz University of Technology, Austria 4) Computational Systems Biochemistry, Max-Planck Institute for Biochemistry,

Martinsried, Germany.

Introduction Recently phosphoproteomics made great success in illuminating working principles of signalling pathways. Here we apply this technique to further deepen the knowledge about lipolysis in adipocytes. Lipolysis is important for the energy homeostasis and thus an understanding of the involved phosphorylations is of importance too. As model system, we are using the well-studied 3T3-L1 cell line which can be differentiated into an adipocyte like phenotype. After activation of the lipolytic process in these cells the phosphorylation pattern is measured. We aim to investigate the process itself e.g. the phosphorylation of directly involved proteins and to further deepen the knowledge about the biological links to other cellular processes. Methods For the cell differentiation, we use insulin, IBMX and dexamethasone. Before the seeding into the vessel for differentiation we split the cells only 1:2. The seeding itself is done without a splitting at about 80% confluency. We grow the cells on glass plates. In doing so we can easily snap freeze the cells and stop the signalling processes in putting the glass plates into liquid nitrogen. To enrich the phosphopeptides of the adipocytes we apply the recently published protocol EasyPhos. The samples are then measured on a Bruker MaXis II ETD using a 2h gradient and label free quantification. The data are searched in MaxQuant and evaluated using Perseus software. Results and Discussion We can measure in lipolysis involved phosphorylation sites. It is already known that perilipin is phosphorylated at multiple sites, which we were able to confirm. These phosphorylation events on multiple sites point towards a complex regulation. The same applies to HSL: we could measure already known phosphorylation sites which intensities are changing upon activation of lipolysis. The next future step is to measure a time series, which will give more information about regulation in time of these phosphorylation sites. Especially we are interested in the changes of the early phosphoproteome. In addition to the directly in lipolysis involved proteins we found phosphorylation sites which are altered upon stimulation too. Using an enrichment test we found that the PKA substrate motif is enriched. Moreover, also PKC and ERK1, ERK2 substrate motifs are enriched in these significant sites. These data suggest an orchestra of regulatory mechanisms to be involved in lipolysis. Again, to further deepen the knowledge about the regulation of these sites it is planned to measure time course data. Another point to discuss is the method of activation of the lipolytic machinery. For the preliminary data, a full activation with 10µM Isoproterenol and 500µM IBMX was chosen. For further experiments, this will be minimized to 100nM Isoproterenol only. Preliminary data already point towards differences between these two conditions for stimulation. Innovative aspects

• We snap freeze the cells immediately after induction and washing with PBS.

• Because of the use of a global phosphoproteomics approach we can investigate how lipolysis is interlinked with other cellular processes.

57

Development of a novel sample preparation approach for bottom-up shotgun proteomics

Simona Salivo1, Tom K. Abban1, Roberto Raso1, Emanuele Barborini2, Matthew E.

Openshaw1 1 Shimadzu, Manchester, UK

2, Tethis SpA, Milan, Italy

Introduction Profiling of proteins and peptides represents a complex analytical problem due to high chemical variability, and aims to provide a better understanding of the function and implication of a species into a given physiological process. A protein profiling strategy, the so-called ‘bottom up’ shotgun approach, involves the proteolytic digestion of a solution of proteins followed by the analysis of the released peptides. When aiming to increase the chance for protein identification, the use of efficient methods of protein digestion becomes indispensable. The present work is based on the evaluation of a target with a modified functionalised surface (Tethis SpA), allowing all stages of sample processing to be performed on the same sample spot. Methods All protein samples, reagents and matrices were purchased from Sigma-Aldrich (St. Louis, MO). During optimization of the on-target sample processing, a suitable amount of protein was loaded onto the target in order to keep the protein-to-enzyme ratio optimal. All the sample processing steps (denaturation, reduction, alkylation and trypsin/PNGase F digestion) have been carried out on-target. MALDI-MS analyses of the intact (native and post-reduction/alkylation) protein as well as of the tryptic and deglycosylation products were conducted on an AXIMA Performance MALDI-TOF-TOF mass spectrometer (Shimadzu, Manchester, UK). We show an example of the exceptional volume capacity of the target which permits to perform an on-target sample processing. Results and Discussion The success of a ‘bottom-up’ protein analysis is dependent on an efficient and complete digestion. Common digestion protocols using trypsin enzyme involve a step of reduction and alkylation (RCM, abbreviated) prior to digestion to improve the trypsin efficiency by allowing it to have easier access to the inner core of the protein. The overall process of a protein digestion can be tedious and time-consuming as each step has to be carefully optimized in order to maximize the digestion efficiency. Our results highlight the capability of the novel, functionalized target to perform on-target trypsin digestion with or without RCM (BSA digest in this example). Good Mascot scores can be appreciated even without conducting the RCM. We show the comparison between the BSA digest from on-target and in-solution (with and without RCM followed by on-target clean-up) digestion. Interestingly, the on-chip trypsin digestion (without RCM) gave a good, slightly better, score in a much shorter time (30 mins vs. overnight).

58

Evaluation of the effects of Bisphenol A on memory impairment in rats and on CaMK, ERK, CREB, P-CaMK, P-ERK and P-CREB protein levels in rat hippocampus and

protective effect of Crocin

Zeinab Bedrood 1, Khalil Abnous 2, Soghra Mehri 3, Faezeh Vahdati Hassani 1, and Hossein Hosseinzadeh3

1) Department of Pharmacodynamy and Toxicology, School of Pharmacy, Mashhad

University of Medical Sciences 2) Department of Medicinal Chemistry, School of Pharmacy, Mashhad University of

Medical Sciences, Mashhad, Iran 3) Pharmaceutical Research Center, Department of Pharmacodynamy and Toxicology,

School of Pharmacy, Mashhad University of Medical, Sciences, Mashhad, Iran

Introduction Crocus sativus L., have an active ingredient, crocin, which is approved to be neuroprotective agent. Bisphenol A, (BPA), 2,2-bis(4-hydroxyphenyl) propane, is a toxic chemical which is used as a monomer in production of plastic products. BPA has endocrine disrupting effect and mediate oxidative damage to different organs like brain. Therefore, the aim of this study was to evaluate the effects of crocin on -induced memory impairment in rat. Additionally, levels of ERK (Extracellular signal-regulated kinases), CaMKII (Calcium(Ca2+)/Calmodulin (CaM)-dependent kinase II),CREB (Cyclic AMP-responsive element-binding protein 1) and P-ERK, P-CaMK, P-CREB in rat hippocampus were determined. Methods Bisphenol A (100 mg/kg) was gavaged and Crocin (10, 20, and 40 mg/kg),was administered intraperitoneally to male Wistar rats for 4 weeks. The effect on memory improvement has been studied using Morris water maze (MWM) test during 7 days. After that the hippocampus has been separated and protein level of ERK, p.ERK, CaMKII, p.CaMKII, CREB and p.CREB have been analized using the western blot test. Results Administration of crocin (20 mg/kg) significantly improved learning and memory impairment which induced by Bisphenol A. Also, administration of Bisphenol A significantly reduced (p<0.01 vs control) protein level of p.ERK, while treatment with crocin (20 mg/kg) recovered the protein level (p<0.01 vs Bisphenol A). No changes were observed in the level of ERK, CaMKII and p.CaMKII following adminestration of Bisphenol A or crocin. Conclusion Administration of crocin (20 mg/kg) improved memory and learning in animals. The effect of crocin in this model in part can be due to change of the level of p.ERK protein in hippocampus. Innovative aspects

• This is the first study that identified the effect chronic oral exposure of rats to BPA on memory impairment by evaluating levels of specific proteins and phosphoproteins in hippocampus.

• Crocin can improve memory impairment induced by BPA.

59

Effects of alanyl-glutamine treatment on the peritoneal dialysis effluent proteome reveal pathomechanism-

associated molecular signatures

Rebecca Herzog1,2, Michael Böhm1, Markus Unterwurzacher1,2, Anja Wagner1,2, Katja Parapatics3, Peter Májek3, André C. Mueller3, Anton Lichtenauer1, Keiryn L. Bennett3,

Seth L. Alper4,5 Andreas Vychytil6, Christoph Aufricht1, and Klaus Kratochwill1,2 1) Division of Pediatric Nephrology and Gastroenterology, Department of Pediatrics and

Adolescent Medicine, Medical University of Vienna, Vienna, Vienna, Austria 2) Christian Doppler Laboratory for Molecular Stress Research in Peritoneal Dialysis,

Department of Pediatrics and Adolescent Medicine, Medical University of Vienna, Vienna, Vienna, Austria

3) CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria

4) Division of Nephrology, Beth Israel Deaconess Medical Center, Boston, MA, USA 5) Department of Medicine, Harvard Medical School, Boston, MA, USA

6) Medical University of Vienna, Department of Medicine III, Division of Nephrology and Dialysis, Vienna, Austria

Introduction Peritoneal dialysis (PD) is a modality of renal replacement therapy in which the high volumes of available PD effluent (PDE) represents a rich source of biomarkers for monitoring disease and therapy. Although this information could help guiding the management of PD patients, little is known about the potential of PDE to define pathomechanism-associated molecular signatures in PD. Methods We therefore subjected PDE to a high-performance multiplex proteomic analysis after depletion of highly-abundant plasma proteins and enrichment of low-abundance proteins. We applied a combination of label-free and isobaric labeling strategies to PDE samples from PD patients (n=20) treated in an open-label, randomized, two-period, cross-over clinical trial with standard PD fluid or with a novel PD fluid supplemented with alanyl-glutamine (AlaGln). Results and Discussion With this workflow, we identified 2506 unique proteins in the PDE proteome, greatly increasing coverage beyond the 171 previously-reported proteins. The proteins identified range from high abundance plasma proteins to low abundance cellular proteins, and are linked to significantly more biological processes and pathways, in part novel for PDE. Interestingly, proteins linked to membrane remodeling and fibrosis are overrepresented in PDE compared to plasma, whereas proteins underrepresented in PDE suggest decreases in host defense, immune-competence and response to stress. Treatment with AlaGln-supplemented PD fluid is associated with reduced activity of membrane injury-associated mechanisms and with restoration of biological processes involved in stress responses and host defense. Innovative aspects

• Our study represents the first application of the PDE proteome in a randomized controlled prospective clinical trial of PD.

• This novel proteomic workflow allowed detection of low abundance biomarkers to define pathomechanism-associated molecular signatures in PD and their alterations by a novel therapeutic intervention.

60

The identification of the drug targets of Auranofin using protein-ligand thermal stability by mass spectrometry

Noel FitzGerald1, Katja Parapatics2, Peter Majek3, Stefan Kubicek2, and Andre C.

Mueller1 1) CeMM, Vienna, Austria, www.cemm.at

Introduction Thermal stabilisation of proteins after ligand binding provides an efficient means to assess and identify the protein/ligand interaction. The cellular thermal-shift assay (CETSA) expanded this concept to the analysis of drug-target engagement in live cells, allowing identification of the cellular drug targets that show an increased thermal stability in the form of drug-ligand complexes. Binding of a ligand to its target protein increases the enthalpy required for unfolding. As a result, the melting temperature (Tm) is shifted. The goal of this study is to I) further validate the action of Methotrexate (published) on its cellular target, Dihydrofolate Reductase, in HAP1 cells and II) elucidate the cellular targets of the drug Auranofin which is also used in the treatment of rheumatoid arthritis. Initial experiments with Methotrexate will be used to set up the experimental workflow and as a positive control. Methods Cells were treated with either drug or DMSO, washed and harvested. Equal amounts of cells were treated with increasing temperatures, lysed and any debris and particulates removed by centrifugation. Equal amounts of supernatant were digested with trypsin and labelled with TMT10-plex, followed by high pH RP offline fractionation and subsequent LC/MS-MS analysis on an Orbitrap Fusion Lumos Tribrid mass spectrometer. Relative TMT abundancies were plotted for the individual identified protein groups and used to calculate melting curves for drug treated versus non-treated cells. Results and Discussion DHFR is stabilised by methotrexate in intact HAP1 cells across a nine-temperature gradient. Stabilitization of DHFR upon drug treatment was visualized by anti-DHFR Western Blotting. Preliminary 1D shotgun data of pooled drug-treated and control samples indicate that of 1144 protein melting curves assessed, 223 proteins indicated increased melting temperatures in drug-treated cells. Melting curve analysis indicated an 8.2° C increase in melting temperature of the target protein DHFR in drug-treated cells. Melting temperature is defined as the temperature point where 50% of the protein (relative abundance) is left compared to the initial 38° C. This work has set the groundwork for the investigation of the cellular targets of the drug Auranofin using the LC-MS/MS based thermal shift assay. Once established, the knowledge attained on Auranofin will be used for potential alternative uses of the drug. The workflow may be applied to investigate the actions of other drugs. Innovative aspects

• Exploitation of the increase in necessary protein enthalpy when bound to ligands causes a shift in protein melting temperature, allowing for identification of ligand target(s).

• Validation work confirmed target of drug Methotrexate, with subsequent investigative work to focus on thus unknown targets of Auranofin.

61

Participants

in alphabetical order of first name

Achim Lass Univ. Graz [email protected]

André C. Müller CeMM Vienna [email protected]

Andrea Hofmann Waters [email protected]

Angelina Gross Univ. Graz [email protected]

Astrid Slany Univ. Vienna [email protected]

Bence M.Nagy Med. Univ. Graz [email protected]

Benedikt Kien Univ. Graz [email protected]

Benjamin Bourgeois Med. Univ. Graz [email protected]

Benjamin Neuditschko Univ. Vienna [email protected]

Bernd Wollscheid ETH Zurich, Switzerland [email protected]

Besnik Muqaku Univ. Vienna [email protected]

Bettina Gürtl CeMM Vienna [email protected]

Bettina Pucher Graz Univ. Technol. [email protected]

Birgit Reiter Med. Univ. Graz [email protected]

Boudewijn Burgering

UMC Utrecht, The

Netherlands [email protected]

Christian Wadsack Med. Univ. Graz [email protected]

Christian Huber Univ. Salzburg [email protected]

Christian Preisinger

Univ.klinikum Aachen,

Germany [email protected]

Christine Pein Med. Univ. Graz [email protected]

Clemens Grünwald-

Gruber

Univ. Nat. Res. Life Sci.

Vienna [email protected] Claire Dauly Thermo Fisher Scientific [email protected]

Daniel Nomura UC Berkeley, CA [email protected]

Darnhofer Barbara Med. Univ. Graz [email protected]

Dolly Mushahary


Vienna [email protected]

Donatella Tesei



Emil Spreitzer Graz Univ. Technol. [email protected]

Evelyn Wals-Philipp Merck [email protected]

Faezeh Vahdati

Hassani Mashhad Univ., Iran [email protected]

Gabriel Zirkovits Graz Univ. Technol. [email protected]

Garwin Pichler Preomics, Germany [email protected]

62

Gerhard Dürnberger IMP Vienna [email protected]

Gerhard Rezniczek Thermo Fisher Scientific [email protected]

Gesa Richter Med. Univ. Graz [email protected]

Gorji Marzban Univ. Nat. Res. Vienna [email protected]

Hananeh Rikhteh

Garan Khamseh Noor Inst., Mashad, Iran [email protected]

Hans Yu Vet. Med. Univ. Vienna [email protected]

Harald Köfeler Med. Univ. Graz [email protected]

Hermann Rausch Agilent [email protected]

Holger Stalz Agilent [email protected]

Horst Schreiner Waters [email protected]

Inge Verstraeten IST Klosterneuburg [email protected]

Ingrid Miller Vet. Med. Univ. Vienna [email protected]

Iskra Ventseslavova

Sainova

Talrose Inst. Moscow,

Russia [email protected]

Joerg Menche CeMM Vienna [email protected]

Johannes Almer Univ. Graz [email protected]

Johannes Stadlmann IMBA Vienna [email protected]

Juergen Cox

MPI Biochem.

Martinsried, Germany [email protected]

Julia Bubis BAS Sofia, Bulgaria [email protected]

Julia Feichtinger Graz Univ. Technol. [email protected]

Julia Sternat Univ. Graz [email protected]

Juliane Weißer CeMM Vienna [email protected]

Jürgen Gindlhuber Univ. Graz [email protected]

Jürgen Hartler Graz Univ. Technol. [email protected]

Jürgen Prasch Med. Univ. Graz [email protected]

Katharina Leithner Med. Univ. Graz [email protected]

Katharina Mayer Vet. Med. Univ. Vienna [email protected]

Katja Parapatics CeMM Vienna [email protected]

Keiryn Bennett Vienna [email protected]

Klaus Kratochwill Med. Univ. Vienna [email protected]

Kristaps Klavins CeMM Vienna [email protected]

Kristina Marx Bruker [email protected]

Laura Liesinger Med. Univ. Graz [email protected]

Laura Niederstätter Univ. Graz [email protected]

Lei Liu Med. Univ. Graz [email protected]

Linda Waldherr Graz Univ. Technol. [email protected]

63

Lukas Janker Univ. Vienna [email protected]

Marion Janschitz CCRI Vienna [email protected]

Markus Ralser Univ. Cambridge, UK [email protected]

Martin Wells Waters [email protected]

Matteo Schiavinato



Matthias Schittmayer Med. Univ. Graz [email protected]

Michael Gruber Med. Univ. Graz [email protected]

Michael Wakelam

Babraham Inst.

Cambridge, UK [email protected]

Monika Oberer Univ. Graz [email protected]

Monika Oberhuber Med. Univ. Vienna [email protected]

Noel Fitzgerald CeMM Vienna [email protected]

Peter Májek CeMM Vienna [email protected]

Peter Valentin

Tomazic Med. Univ. Graz [email protected]

Petra Krenn Med. Univ. Graz [email protected]

Rainer Hofstätter Shimadzu [email protected]

Rupert Mayer Univ. Vienna [email protected]

Ruth Birner-

Gruenberger Med. Univ. Graz [email protected]

Sarah Stryeck Med. Univ. Graz [email protected]

Sebastian Dorl FH Hagenberg [email protected]

Stefan Spoerk Med. Univ. Graz [email protected]

Stefanie Rappold Med. Univ. Graz [email protected]

Tamara Scheidt Univ. Salzburg [email protected]

Tamara Tomin Med. Univ. Graz [email protected]

Taras Stasyk Med. Univ. Innsbruck [email protected]

Tea Pavkov-Keller Univ. Graz [email protected]

Tobias Madl Med. Univ. Graz [email protected]

Tom Grunert Vet. Med. Univ. Vienna [email protected]

Ulrich Stelzl Univ. Graz [email protected]

Veronique Fischer

Université de Strasbourg,

France [email protected]

Viktoria Dorfer FH Hagenberg [email protected]

Wolfram Weckwerth Univ. Vienna [email protected]

Xiaoliang Sun Univ. Vienna [email protected]

Zeinab Bedrood Mashhad Univ., Iran [email protected]

64

Sponsors

Organizing committee

Ruth Birner-Grünberger, Tobias Madl, Ulrich Stelzl, Harald

Köfeler, Jürgen Hartler, Matthias Schittmayer, Karin Osibow

Contact: [email protected]

Date post:	28-Jul-2018
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