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Unraveling Metabolostasis



Metabolism describes the complex network of reactions that enable organisms to generate the energy and molecules, metabolites, they need to thrive. The paramount role metabolites play across the branches of life, as well as their part in various disorders, has been investigated for decades. Yet, only recently it has been revealed that these life-essential building blocks can form cytotoxic aggregates, similar to those found in neurodegenerative disorders such as Alzheimer’s disease and Parkinson's disease.


This discovery raises elementary questions regarding metabolite homeostasis - "metabolostasis" - mechanisms that maintain metabolites in a soluble, non-aggregative, state. Such quality-control mechanisms must allow the sufficient supply of metabolites on one hand, while strictly monitoring their levels and avoiding aggregation on the other. These mechanisms, we believe, have co-evolved with the metabolites themselves, and originated very early in the evolutionary timeline.


Our group aims to resolve this 'metabolite paradox' and elucidate the cellular mechanisms that maintain life-essential metabolites in their soluble and non-toxic state. We tackle these questions by applying advanced multi-omics techniques and state-of-the-art methods for high-throughput genomic screening and spectroscopic imaging. Implemented in both eukaryote and prokaryote models, this integrated system will provide a multi-systemic evolutionary exploration into this uncharted territory and will allow identifying, for the first time, the cellular mechanisms of metabolostasis.


We further aim to decipher how metabolostasis is compromised in different human pathologies, such as inborn errors of metabolism and neurodegenerative diseases. Using a proprietary platform for drug discovery, we aim to discover novel bioactive small molecules that could serve as future therapeutics.



Shon Levkovich
WhatsApp Image 2022-01-24 at 13.17.22.jpeg
Ilana Sogolovsky-Bard
Rahat Behl
Keila Kaplan
Myra Gartner
Maoz Lahav
Lihi Gershon
Poulami Chakraborty, Post Doc

Our Setup
We tackle metabolostasis from an integrative multi-omics approach, using state-of-the-art high-throughput screening tools at the genomic, proteomic, and metabolomics levels. For this purpose, we have established FRANCESCA - a Fluorescent RamAN miCrospEctroscopy SCreening plAtform that uses genome-wide libraries of yeast and bacteria that allow us to systemically investigate the effect of each gene on metabolostasis mechanisms, both for eukaryotes and prokaryotes. 
Our setup includes the Singer ROTOR+, a powerful robot for manipulating arrayed libraries in 96, 384, 1536, and 6144 formats. The ROTOR+ can carry out genome-wide screens using the synthetic genetic array (SGA) methodology to investigate the genetic interactions that underlie the metabolostasis network. It’s so fast that it allows us to replicate the entire yeast or bacterial genome in just under one minute! 
Our custom-designed imaging platform allows, for the first time, the visualization of metabolites and proteins and their interaction at a genome-wide level. Metabolite imaging relies on confocal Raman microspectroscopy - a powerful technique based on vibrational spectroscopy that enables us to specifically investigate the role and fate of virtually any metabolite and cellular component in a label-free manner.

Our imaging platform is based on the WITec alpha300 Ri Inverted Confocal Raman Imaging system that has been optimized for high-throughput confocal fluorescent and Raman imaging. It includes a fiber-coupled Ultra-High-throughput spectrometer with a motorized grating turret including 600 and 1800 lines/mm gratings, that is coupled to a thermoelectrically-cooled back-illuminated CCD camera with extremely high quantum efficiency for high-end Raman imaging.

The imaging system further contains a photomultiplier tube for fluorescence detection, solid-state excitation lasers (457nm and 532nm) with Raman filter sets, a motorized XYZ scanning stage with autofocus module, and up to 100x objectives with coverglass correction with an automatic oil immersion dispensing system.
Data acquisition can be performed either at a single-cell level or at a population level, giving important information concerning the cellular localization of metabolites and proteins and their interplay. Data processing is then performed in an unbiased manner by computerized image analysis algorithms for the generation of correlative fluorescent-Raman images. 

Our Setup



Levkovich, S. A., Gazit, E., Laor Bar-Yosef, D. (2023). The Metabolostasis Network and the Cellular Depository of Aggregation-Prone Metabolites. Angewandte Chemie International Edition, e202217622.

Adsi, H., Levkovich, S.A., Haimov, E., Kreiser, T., Meli, M., Engel, H., Simhaev, L., Karidi-Heller, S., Colombo, G., Gazit, E., Laor Bar-Yosef, D. (2021) Chemical Chaperones Modulate the Formation of Metabolite Assemblies. Int. J. Mol. Sci., 22, 9172. (Featured in the cover of the issue). 

Sade, D., Laor Bar-Yosef, D., Adsi, H., Kreiser, T., Sigal, S., Bera, S., Zaguri, D, Shaham-Niv, S., Oluwatoba, D., Levy, D., Gartner, M., Do, T, Frenkel, D., and Gazit, E. (2021) Homocysteine fibrillar assemblies display cross-talk with Alzheimer's disease β-amyloid polypeptide. Proc. Natl. Acad. Sci. U.S.A. 118, 1-11. 

Levkovich, S. A., Rencus-Lazar, S., Gazit, E., Laor Bar-Yosef, D. (2021) Microbial Prions: Dawn of a New Era. Trends Biochem. Sci. 46, 391-405. 

Levkovich, S. A., Gazit, E., Laor Bar-Yosef, D. (2021) Two Decades of Studying Functional Amyloids in Microorganisms. Trends Microbiol. 29, 251–265. 

Makam, P., Yamijala, S. S. R. K. C., Tao, K., Shimon, L. J. W., Eisenberg, D. S., Sawaya, M. R., Wong, B. M., & Gazit, E. (2019) Nonproteinaceous Hydrolase Comprised of Phenylalanine Metallosupramolecular Amyloid-Like Structure. Nature Catal. 2, 977–985.

Meli, M., Engel, H., Laor, D., Gazit, E., and Colombo, G. (2019) Mechanisms of Metabolite Amyloid Formation: Computational Studies for Drug Design against Metabolic Disorders. ACS Med. Chem. Lett. 10, 666–670. 

Rencus-Lazar, S., DeRowe, Y., Adsi, H., Gazit, E. & Laor, D. (2019) Yeast Models for the Study of Amyloid-Associated Disorders and Development of Future Therapy. Front. Mol. Biosci. 6, 1-10.

Laor D.; Sade D.; Shaham-Niv S.; Zaguri D.; Gartner M.; Basavalingappa V.; Raveh A.; Pichinuk E.; Engel H.; Iwasaki K.; Yamamoto T.; Noothalapati H.; Gazit E. (2019) Fibril formation and therapeutic targeting of amyloid-like structures in a yeast model of adenine accumulation. Nature Commun. 10, 62

Shaham-Niv, S., Adler-Abramovich, L., Schnaider, L., & Gazit, E. (2015) Extension of the Generic Amyloid Hypothesis to Non-Proteinaceous Metabolite Assemblies. Science Adv. 1, e1500137.

Adler-Abramovich, L., Vaks, L., Carny, O., Trudler, D., Frenkel, D., & Gazit, E. (2012) Phenylalanine Assembly into Toxic Fibrils Suggests Amyloid Etiology in Phenylketonuria. Nature Chem. Biol. 8, 701-706. (Featured on the cover of the issue).



Recorded lectures


The Metabolostasis Database

(The information will be available soon on website)

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