Protein expression, stability, and redox regulation – Saei Lab

Our research program lies at the intersection of chemical proteomics, metabolomics, and computational strategies to uncover the intricate interplay between metabolites, proteins, diet, and gut microbiota in different metabolic disease states.

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Saei lab

We investigate how small molecules interact with proteins to regulate cellular function in cancer and metabolic disease. Our work focuses on metabolites, drugs, and microbiome-derived molecules as underexplored regulators of protein activity, stability, expression, and signaling.

By integrating chemical proteomics, quantitative mass spectrometry, metabolomics, computational biology, and mechanistic validation, we map these interactions directly within complex biological systems and identify molecular mechanisms that can be exploited for therapeutic or biomarker discovery.

Our research

Our biological research spans three closely connected areas.

Cancer metabolism and therapeutic vulnerabilities
We investigate how altered metabolism creates protein-level dependencies in cancer and how metabolites and other small molecules regulate pathways that control tumor growth, survival, and treatment response.

Metabolism and metabolic disease
We study how metabolite–protein interactions contribute to insulin resistance and other metabolic disorders, with a particular focus on adipose tissue biology and mechanisms altered in human disease.

Microbiome–host chemical interactions
We investigate how microbial metabolites interact with host proteins and signaling pathways to understand how the microbiome influences cancer biology and to identify microbiome-derived therapeutic opportunities.

Interaction proteomics
A major focus of the lab is the development and application of proteomics technologies that reveal molecular interactions directly in cells and tissues. These include approaches for measuring changes in protein stability, expression, redox state and proteolytic accessibility, together with deep plasma and tissue proteomics.

Our goal is to connect patient-derived molecular data with mechanistic biology and ultimately translate these insights into new therapeutic strategies and biomarkers.

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Publications

Funding

We gratefully acknowledge financial support for our research from several organizations, including:

  • Cancer Research KI's Task Force Network Grant for 'The Cancer and Microbiome'
  • The Swedish Brain Foundation 
  • Novo Nordisk Foundation Excellence Emerging Investigator Grant – Endocrinology and Metabolism 
  • Cancer Research KI BlueSky Grant
  • The Swedish Cancer Society
  • The Swedish Research Council 
  • Karolinska Institutet Faculty Funds 

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Research

Small molecules are central regulators of cellular physiology, yet the protein targets of many endogenous metabolites, microbiome-derived molecules, and therapeutic compounds remain poorly understood. Our laboratory develops and applies interaction proteomics approaches to systematically identify these interactions and determine how they influence disease.

We integrate mass spectrometry-based proteomics with metabolomics, biochemical and functional validation, computational methods, and human disease models. Our research is organized around five interconnected themes.

Saei lab illustration

Metabolite–protein interactions in cancer

Cancer cells undergo profound metabolic rewiring, resulting in altered metabolite concentrations and dependencies that can influence protein function.

We map metabolite–protein interactions in cancer cells and tissues to uncover previously unrecognized regulatory mechanisms and therapeutic vulnerabilities. By integrating interaction proteomics with functional genomics, biochemical validation, and disease models, we aim to determine which metabolite-regulated proteins are causal drivers of tumor growth and treatment response.

Our work spans several cancer types, with particular emphasis on colorectal and liver cancer.

Metabolism and metabolic disease

Metabolic diseases are characterized by substantial changes in the concentrations and fluxes of endogenous metabolites. However, how these changes directly affect the proteome remains poorly understood.

We investigate how disease-associated metabolites interact with proteins to alter signaling, protein stability, and cellular function, with a particular focus on adipocyte insulin resistance.

By integrating human adipose tissue and plasma profiling with interaction proteomics and mechanistic studies, we aim to link metabolic changes observed in patients to specific protein targets and pathways that can be therapeutically modulated.

Microbiome–host chemical interactions

The microbiome produces thousands of small molecules that can enter host tissues and influence cellular physiology, yet the molecular targets of most of these compounds are unknown.

We study how microbiome-derived metabolites interact with host proteins and signaling pathways, particularly in colorectal cancer. We integrate microbial and patient-derived data with machine learning, metabolomics, interaction proteomics and functional experiments to identify bioactive microbial molecules and elucidate their mechanisms of action.

A long-term goal is to translate these discoveries into microbiome-inspired therapeutic strategies.

Proteomics technology development

We develop proteomics technologies that enable the study of molecular interactions and protein regulation to be studied at the proteome scale.

A central platform in the laboratory is the PISA assay for high-throughput profiling of small-molecule–protein interactions. We have further developed PISA-REX, which integrates measurements of protein stability, expression and redox state, enabling multiple dimensions of proteome regulation to be investigated in response to drugs, metabolites, and other small molecules.

We have also contributed to the development of complementary interaction-proteomics approaches, including HOLSER, which uses limited proteolysis and quantitative mass spectrometry to identify ligand-induced structural changes in proteins, and potentially pinpoint ligand-binding regions on proteins.

These technologies are combined with quantitative proteomics, plasma proteomics, metabolomics, structural biology, and computational analysis to provide orthogonal evidence for molecular interactions and mechanisms.

Deep plasma proteomics and secretome profiling

Circulating proteins provide a dynamic window into disease biology, yet many clinically relevant proteins remain difficult to detect because of the extreme complexity and wide concentration range of plasma. We develop and apply deep plasma proteomics approaches based on small molecule-modulated protein coronas to enrich otherwise difficult-to-detect proteins and expand access to the circulating proteome.

We use these strategies for biomarker discovery, patient stratification, and disease monitoring by integrating plasma proteomics with tissue and molecular data from well-characterized clinical cohorts. In parallel, we develop approaches for deep secretome profiling to characterize proteins released by cells and tissues, including low-abundance signaling molecules and disease-associated factors that are often missed by conventional proteomics.

Together, these technologies enable us to link molecular changes in diseased tissues to measurable signals in circulation and identify candidate biomarkers with diagnostic and translational potential.

Saei Lab illustration
Saei Lab illustration Photo: N/A

From molecular mechanisms to translation

Our research is closely connected to well-characterized patient cohorts and clinical collaborators. We use human tissue, plasma, patient-derived models, and experimental disease systems to iteratively translate clinical observations into mechanistic investigation.

The overarching goal is to translate molecular interaction maps into new therapeutic targets, drug candidates, and biomarkers for cancer and metabolic disease.