Session Title：Trans-Omics workshop – The 3rd International Symposium for TransOmics –Organizers：Shinya Kuroda (University of Tokyo, Japan) Mariko Okada (OsakaUniversity, Japan)
Synopsis：The life system is a "trans-omic" network, consisting of interactions between
numerous molecules across multi-omic layers, such as genome, transcriptome, proteome,and metabolome. Lifestyle diseases can be regarded as complex multifactorial diseases
caused by breakdowns in a trans-omic network rather than breakdown of a single
molecule. Due to recent advances in methods of measurements and analyses for singleomic layers, trans-omic analyses integrating multi-omic data are in state-of-the-art
development. We hold this workshop to discuss new trans-omic technologies and advanced
interpretation of multi-omics data.
Program（speakers and allotted time)：
14:00 ~ 14:05 Opening Remarks (5 min)
14:05 ~ 15:05 Session I (2 talks)
14:05 ~ 14:40 Matthias Heinemann (Univ. Groningen, Netherlands)
Title: Unraveling the traffic through the highways of metabolism
The metabolic fluxes in cells emerge from environmental factors and various regulatory
mechanisms. Knowing these fluxes, i.e. traffic through the highways of metabolism, is key
for fundamental and applied research. However, our current methods to experimentallyresolve metabolic fluxes, based on 13C labeling experiments, still have a number of severe
limitations. Here, I will introduce a new method to map the metabolic fluxes withunprecedented precision. In this method, we integrate metabolome, physiological and 13Clabeling data with reaction stoichiometry, thermodynamic laws and constraints, using
highly complex regression and sampling approaches. At this point, where we then know
the metabolic fluxes, I will show results of our recent effort towards understanding thelogic of the ‘traffic control system’ that governs metabolism. Specifically, I will present
evidence that cellular metabolism might be constrained by the rate at which cells candissipate Gibbs energy to the environment. This newly identified constraint has topotential to lead us to a radically new understanding of how cells function.
14:40 ~ 15:05 Mariko Okada (Osaka Univ., Japan)
Title: Analyze immune response using Omics and imaging
Gene expression is controlled by multi-omics layers. To understand gene regulatory
mechanism, we analyze omics data using a mathematical model by focusing ontranscription factor dynamics in B cell. Our study combined with bioinformatics andmodeling and validation analysis using live cell imaging indicated that the cooperativity inenhancer regulation is important for quantitative control of target gene expression in B
cell differentiation.
15:05 ~ 15:20 Coffee Break (15 min)15:20 ~ 16:45 Session II (3 talks)
15:20 ~ 15:45 Shinpei Kawaoka (Kyoto Univ., Japan)

Title: Dissecting significance of single gene expression rhythm via enhancer genetics andmulti-omics analyses
Circadian gene expression rhythm is disrupted in various diseases. We recently found thatbreast cancers distantly rewire hepatic circadian transcriptiome and cause a series ofphysiological alterations such as hepatomegaly (enlarged liver). Yet, whether the rewired
circadian rhythm is a cause for physiological alterations remains unknown. To address thisissue, we aimed to disrupt expression rhythm of single gene via deletion of genomic
enhancers. Enhancers are non-coding genomic elements that determine spatio-temporalgene expression patterns. Enhancer deletion when properly done enables us to ablate
specific gene regulation for example rhythmic expression in vivo. We successfully obtained
single rhythm-deficient mice and performed multi-omics analyses on the mutant. In the talk,I would like to discuss how the deficiency of single gene expression rhythm impacts liver
physiology (multi-layered network) at the gene, protein, metabolite, and phenotypic levels.
References1) Hojo, H., Enya, S., Arai, M., Suzuki, Y., Nojiri, T., Kangawa, K., Koyama, S.,
and Kawaoka, S.: Oncotarget. 8(21), 34128-34140, 20172) Enya, S., Kawakami, K., Suzuki, Y., and Kawaoka, S.: Dis. Model Mech., 11, dmm032383,
20183) Hojo, M.A., Masuda, K., Hojo, H., Nagahata, K., Yasuda, K., Ohara, D., Takeuchi, Y.,
Hirota, K.,
Suzuki, Y., Kawamoto, H., Kawaoka, S.: Nat. Commun., 10, 2603, 201915:45 ~ 16:10 Fumio Matsuda (Osaka Univ., Japan)
Title: Trans-omic analysis of the central metabolism of Saccharomyces cerevisiae by
integration of metabolome, metabolic flux, and proteome data
Introduction: In the living organisms, homeostasis of the central metabolism is maintainedby coordinated regulation of the metabolic system. A failure of the metabolic homeostasis
would cause severe cellular phenotypes. However, a relationship among the gene deletion,
the metabolic adaptations to maintain the homeostasis, and resultant phenotypes such as
slow rates of cell growth remains unclear. To address the relationship, we investigatedmetabolic adaptation mechanisms in the knockout strains of S. cerevisiae lacking thecentral metabolism-related genes.
Results and discussions: A transomics dataset including fermentation profile, intracellular
metabolic flux distribution, enzyme abundance, and metabolite concentration wasobtained from a wild type S. cerevisiae and 11 single-gene deletion strains. The transomics
data confirmed that the ATP homeostasis was one of the core homeostasis since the ATPconcentration was the least fluctuating metabolic features. The data also showed that thesingle gene deletion strains commonly employed two metabolic adaptation mechanisms. Inpfk1Δ and gcr1Δ, ATP shortage by the malfunction of the EMP pathway wascomplemented by activation of the oxidative phosphorylation. In other mutant strains,their growth was voluntarily reduced to avoid metabolic imbalance such as by the Gcn4p
dependent control of the cell component biosynthesis.
16:10 ~ 16:45 Jason Locasale (Duke Univ., USA)
Title: Using metabolomics and computational biology to study metabolism in health andcancer
This presentation will discuss efforts to understand glucose and amino acid metabolism incancer biology using metabolomics approaches and mathematical modeling. First I will
discuss new work on mechanisms of de novo acetate production in mammals. I will discusswork on dietary influences on the activity of metabolic pathway and relations to metabolic
health and cancer. As an example, I will discuss how methionine restricted diets may
allow for interventions in cancer treatment will also be discussed. This concept also
provides a link between nutrient status and chromatin biology which I will briefly touchupon.
16:45 ~ 16:55 Coffee Break (10 min)
16:55 ~ 17:55 Session III (2 talks)
16:55 ~ 17:20 Katsuyuki Yugi (RIKEN, Japan)
Title: Dose-selective metabolic regulation by insulin across multiple omic layers
Insulin selectively regulates multiple cellular functions via its concentrations and temporal
patterns. However, the cellular network that realizes selective responses to the insulin
concentrations remains poorly understood. Here we reconstructed dose-selective networks
of insulin action over multiple omic layers based on time-series measurements ofphosphoproteome, transcriptome, and metabolome in rat hepatoma Fao cells stimulated bymultiple insulin doses. In the reconstructed network, we identified two ‘trans-omic’
regulatory axes that respond to high and low doses of insulin in a mutually exclusive
manner: a high-dose responsive ERK regulatory axis and a low-dose responsive AKT
regulatory axis. High dose insulin signals were transmitted by ERK via the immediate earlygenes (IEG) to the upregulated genes. On the other hand, the low-dose insulin signal wastransmitted by AKT to its target genes. Furthermore, we found that the ERK regulatory
axis mainly regulates gene expression at the transcription level, whereas the AKT
regulatory axis regulates gene expression at the translation level. This study reveals thesystem by which the liver cells interpret physiological insulin signals and regulate various
cellular functions.
17:20 ~ 17:55 Uwe Sauer (ETH Zurich, Switzerland)
Title: Metabolic Coordination Through Metabolite-Protein Interactions
How do bacteria know what goes on in their environment and how do they makeappropriate decisions? While some bona fide extracellular sensors are known, there are far
more environmental conditions and cellular responses than could possibly be dealt withthrough dedicated sensors. Instead, most microbial responses are based on direct
intracellular consequences of environmental changes. One of the first affected networks tojust about any extracellular change is metabolism that passively responds to nutritional orchemical/physical challenges. Since fluxes and intracellular metabolite levels respondwithin seconds, allosteric binding of metabolites to regulatory proteins and enzymes is ahighly effective and rapid sensing mechanism. Different from well-establish methods toassess physical interaction between proteins and between proteins and nucleic acids,
however, methods to assess metabolite-protein interactions are still in their infancy. At
present we know on the order of 1500 unique regulatory metabolite-protein interactions (1).
Using limited proteolysis mass spectrometry (2) and NMR (3), we have recently begun tosystematically map out the physical interactions space in E. coli. Even for the wellinvestigated central metabolism we more than doubled the known metabolite-protein
interactions (3). Beyond mapping the regulation network, I will focus on the even morechallenging and conceptual problem: understanding which of the many regulation
mechanisms actually matter for a given adaptation to elicit an appropriate physiologicalresponse.
1.
2.
3.

Reznik, Christodoulou, Goldford, Briars, Sauer, Segre & Noor. Cell Reports 20:
2666-2677 (2017).
Piazza, Kochanowski, Cappelletti, Fuhrer, Noor, Sauer & Picotti. Cell 72:358372 (2018).
Diether, Nikolaev, Allain & Sauer. Molecular Systems Biology 15:e9008 (2019).

17:55 ~ 18:00 Closing Remarks (5 min)
Registration ：No registration is needed