Lau Lab Colorado


We have multiple positions available. Contact us to join our team!

Edward is an Assistant Professor at the University of Colorado School of Medicine. Prior to joining Colorado, he received his Bachelor's degree at UC Berkeley, PhD at UCLA, and completed postdoctoral training at Stanford. He has published over 50 papers in areas related to protein regulation, cardiac, and stem cell research. His work has been supported by external funding including an NIH F32 Fellowship, and NHLBI K99/R00 award, and an NIGMS R35 award.

Edward Lau, Ph.D.

Team Lead

Peyton is a life science research professional in the lab. She earned her Bachelor's degree at CU Boulder and is currently working on projects related to cellular crosstalk in the heart.

Peyton Schaal, B.Sc.

Life Science Research Professional

Cheyanne is an incoming PhD student in the Integrated Physiology program of CU Anschutz. Her research explores the use of engineered heart tissues and bioorthogonal click chemistry to identify cellular crosstalk signals.

Cheyanne Durham, B.Sc.

PhD Student

Jay is a second year PhD student in the Integrated Physiology program. Their research focus is to explore long-range communication between the heart and adipose tissues in the body, and how comorbidities of metabolic dysfunction affects cardiac health.

Jay Pavelka, B.Sc.

PhD Student

Lorena is a third-year PhD student in the Pharmacology and Molecular Medicine program. She is interested in developing new subcellular proteomics techniques to understand cellular stress response.

Lorena Alamillo, B.Sc.

PhD Student

Aidan is a second-year master’s student in the BSBT program and will earn a certificate in Biomedical Data Science. He is a UW-Madison alumnus, studied Biology, and spent three years post-graduation in the private sector. Aidan’s research focuses on proteolysis in iPSC-cardiomyocyte maturation.

Aidan Borkan, B.Sc.

Master's Student

Vyshnavi is currently pursuing her masters in Biomedical Sciences and Biotechnology at University of Colorado. She has previously earned her master's degree in Pharmaceutical biotechnology from Manipal University in India.

Vyshnavi Manda, M.Sc.

Student Researcher

Jordan's a Principal Life Science Research professional in the lab. He graduated with a master's student at the University of Colorado BSBT program. He is currently working on developing improved methods to identify secreted proteins in human induced pluripotent stem cell derived cardiac cells.

Jordan Currie, B.Sc.

Principal Life Science Research Professional

Ginkgo is a happy cocker spaniel. She loves to hike and camp in the Colorado mountains.




Himangi Srivastava, Ph.D.

Current Position: Data Scientist, Fred Hutch

Sean Robinson, B.Sc.

Current Position: None

Lauren Li, M.Sc.

Current Position: PhD Student, CU Anschutz BioE

Logan Scott, B.Sc.

Current Position: Med. Lab Manager, CU Anschutz

Gabriel Wu

Current Position: Student, CU Boulder

Nicholas Hulett, M.Sc.

Current Position: PhD Student, CU Anschutz IPHY

Michael Lippincott, B.Sc.

Current Position: PhD Student, CU Anschutz CSD

Marina Pozzoli, M.Sc.

Current Position: Senior PRA, CU Anschutz

Nikhitha Kastury

Current Position: Student, CU Denver

Veronica Hidalgo, M.Sc.

Current Position: Stem Cell Technician, ClinImmune

Abigiya Abate, B.Sc.

Current Position: Student, CU Anschutz


We are interested in the regulation and function of protein turnover, homeostasis, and secretion in development, senescence, and diseases. Our work leverages advances in proteomics, bioinformatics, and human induced pluripotent stem cell (iPSC) models. Two current areas of focus are:

  1. What is the role of protein turnover and homeostasis during cell fate transitions?

    Our lab develops analytical and computational methods that can measure the individual turnover rates and half-life of thousands of protein species in complex systems. These techniques have been used to reveal changes in protein synthesis and degradation in animal models and discover new disease signatures. A current focus is to understand the regulation and function of protein quality control and proteolysis during cellular differentiation, stress, and senescence in iPSC systems.
  2. How do cells in the body communicate through secreted RNAs and proteins?

    In recent work, we have mapped secreted non-coding RNAs from multiple cell types derived from human iPSCs (cardiomyocytes, endothelial cells, fibroblasts) that may function in intercellular communications and that may be harnessed as a quantitative metric to assess the differentiation status and purity of hPSC-derived cardiac cells. In ongoing work, we are leveraging this approach to model the longitudinal changes in cellular communication networks under stress and disease using a combination of computational modeling and proteomics strategies.

Work in the laboratory is supported by funding from an NIH/NIGMS R35 MIRA award, an NIH/NHLBI K99/R00 award, NIH/OD R03 award, as well as the University of Colorado Consortium for Fibrosis Research & Translation. We are looking for undergraduates, post-bacs, and graduate students! Come work with us if you are interested in protein regulations and wish to hone your research skills in a friendly and supportive environment!

Mapping the secretome of cells and tissues

Edward Lau | May 05 2022

Mapping the secretome of cells and tissues

We are interested in applying proteomics and bioinformatics methods to discover secreted proteins and long-range endocrine signals from different cells and tissues.

Predicting RNA-protein correlations

Edward Lau | Aug 03 2021

Predicting RNA-protein correlations

A new study from our lab shows a computational workflow to prioritize useful RNA-seq signatures by considering how well they predict protein changes.

New Projects and Position

Edward Lau | Sep 17 2020

New Projects and Position

We are looking for post-doctoral, post-baccalaureate, and undergraduate researchers to join our team!


Lab News

Jun 12 2023 Our lab has been selected for the CU SOM 2023 Translational Research Scholars Program to support our work on proteome dynamics. Thanks SOM! Link

Jun 07 2023 We would like to welcome our two summer undergraduate students Gabriel Wu (NIGMS Summer Research Student) and Abigiya Abate (CU CORE Program)!

May 01 2023 Thank you Parse Biosciences for highlighting our work on full length iPSC transcriptomes! Link here

Apr 19 2023 Masters student Jordan Currie has successfully defended his work on spatiotemporal proteomics. Congratulations!

Apr 18 2023 Edward has been invited to give a faculty presentation in this year's CU Anschutz School of Medicine Research Day

Mar 07 2023 Congratulations to Jordan for receiving the 2023 HUPO Abstract Travel Award in Chicago!

Oct 14 2022 Congrauations to Veronica who successfully defended her BSBT master's degree today!

Sep 22 2022 Our lab has been awarded a 5-year, 1.8 million R35 award from NIGMS to study protein turnover in induced pluripotent stem cell models! Link here

Sep 01 2022 Postdoctoral fellow Dr. Himangi Srivastava has started a new position as Data Scientist at Fred Hutch in Seattle. Good luck Himangi, you will be missed!

Sep 22 2021 Our lab received an NIH Office of the Director R03 award to use multi-omics data to investigate systems physiology! Link here

Aug 20 2020 Our lab has received an NIH/NHLBI R00 award to study the role of cardiac secreted proteins in human health and disease! Link here

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Selected Publications

Click here for full publication list

  • Proteomics applications in next generation induced pluripotent stem cell models

    V. Manda, J. Pavelka, and E. Lau

    Expert Rev Proteomics, 21(4), 217-228, 2024
    RIS BibTex
  • Simultaneous proteome localization and turnover analysis reveals spatiotemporal features of protein homeostasis disruptions

    J. Currie, V. Manda, S. K. Robinson, C. Lai, V. Agnihotri, V. Hidalgo, R. W. Ludwig, K. Zhang, J. Pavelka, Z. V. Wang, J. W. Rhee, M. P. Y. Lam, and E. Lau

    Nat Commun, 15(1), 2207, 2024
    RIS BibTex
  • The spatial and temporal distributions of proteins are critical to protein function, but cannot be directly assessed by measuring protein abundance. Here we describe a mass spectrometry-based proteomics strategy, Simultaneous Proteome Localization and Turnover (SPLAT), to measure concurrently protein turnover rates and subcellular localization in the same experiment. Applying the method, we find that unfolded protein response (UPR) has different effects on protein turnover dependent on their subcellular location in human AC16 cells, with proteome-wide slowdown but acceleration among stress response proteins in the ER and Golgi. In parallel, UPR triggers broad differential localization of proteins including RNA-binding proteins and amino acid transporters. Moreover, we observe newly synthesized proteins including EGFR that show a differential localization under stress than the existing protein pools, reminiscent of protein trafficking disruptions. We next applied SPLAT to an induced pluripotent stem cell derived cardiomyocyte (iPSC-CM) model of cancer drug cardiotoxicity upon treatment with the proteasome inhibitor carfilzomib. Paradoxically, carfilzomib has little effect on global average protein half-life, but may instead selectively disrupt sarcomere protein homeostasis. This study provides a view into the interactions of protein spatial and temporal dynamics and demonstrates a method to examine protein homeostasis regulations in stress and drug response.

  • Senescence in human AC16 cardiac cells is associated with thymidine kinase induction and histone loss

    N. Kastury, V. Hidalgo, B. Pandi, L. Li, M. P. Y. Lam, and E. Lau

    MicroPubl Biol, 2023, 2023
    RIS BibTex
  • Co-culture with normal and senescent AC16 cardiomyocytes modulates fibrotic response in primary human ventricular fibroblasts

    V. Hidalgo, N. Kastury, C. W. Durham, J. Currie, M. Amaya, M. P. Y. Lam, and E. Lau

    MicroPubl Biol, 2023, 2023
    RIS BibTex
  • Protein prediction models support widespread post-transcriptional regulation of protein abundance by interacting partners

    H. Srivastava, M. J. Lippincott, J. Currie, R. Canfield, M. P. Y. Lam, and E. Lau

    PLoS Comput Biol, 18(11), e1010702, 2022
    RIS BibTex
  • Protein and mRNA levels correlate only moderately. The availability of proteogenomics data sets with protein and transcript measurements from matching samples is providing new opportunities to assess the degree to which protein levels in a system can be predicted from mRNA information. Here we examined the contributions of input features in protein abundance prediction models. Using large proteogenomics data from 8 cancer types within the Clinical Proteomic Tumor Analysis Consortium (CPTAC) data set, we trained models to predict the abundance of over 13,000 proteins using matching transcriptome data from up to 958 tumor or normal adjacent tissue samples each, and compared predictive performances across algorithms, data set sizes, and input features. Over one-third of proteins (4,648) showed relatively poor predictability (elastic net r ≤ 0.3) from their cognate transcripts. Moreover, we found widespread occurrences where the abundance of a protein is considerably less well explained by its own cognate transcript level than that of one or more trans locus transcripts. The incorporation of additional trans-locus transcript abundance data as input features increasingly improved the ability to predict sample protein abundance. Transcripts that contribute to non-cognate protein abundance primarily involve those encoding known or predicted interaction partners of the protein of interest, including not only large multi-protein complexes as previously shown, but also small stable complexes in the proteome with only one or few stable interacting partners. Network analysis further shows a complex proteome-wide interdependency of protein abundance on the transcript levels of multiple interacting partners. The predictive model analysis here therefore supports that protein-protein interaction including in small protein complexes exert post-transcriptional influence on proteome compositions more broadly than previously recognized. Moreover, the results suggest mRNA and protein co-expression analysis may have utility for finding gene interactions and predicting expression changes in biological systems.

  • Harmonizing labeling and analytical strategies to obtain protein turnover rates in intact adult animals

    D. E. Hammond, D. M. Simpson, C. Franco, M. W. Muelas, J. Waters, R. W. Ludwig, M. C. Prescott, J. L. Hurst, R. J. Beynon, and E. Lau

    Mol Cell Proteomics, 21(7), 100252, 2022
    URL RIS BibTex
  • Changes in the abundance of individual proteins in the proteome can be elicited by modulation of protein synthesis (the rate of input of newly synthesized proteins into the protein pool) or degradation (the rate of removal of protein molecules from the pool). A full understanding of proteome changes therefore requires a definition of the roles of these two processes in proteostasis, collectively known as protein turnover. Because protein turnover occurs even in the absence of overt changes in pool abundance, turnover measurements necessitate monitoring the flux of stable isotope-labeled precursors through the protein pool such as labeled amino acids or metabolic precursors such as ammonium chloride or heavy water. In cells in culture, the ability to manipulate precursor pools by rapid medium changes is simple, but for more complex systems such as intact animals, the approach becomes more convoluted. Individual methods bring specific complications, and the suitability of different methods has not been comprehensively explored. In this study, we compare the turnover rates of proteins across four mouse tissues, obtained from the same inbred mouse strain maintained under identical husbandry conditions, measured using either [13C6]lysine or [2H2]O as the labeling precursor. We show that for long-lived proteins, the two approaches yield essentially identical measures of the first-order rate constant for degradation. For short-lived proteins, there is a need to compensate for the slower equilibration of lysine through the precursor pools. We evaluate different approaches to provide that compensation. We conclude that both labels are suitable, but careful determination of precursor enrichment kinetics in amino acid labeling is critical and has a considerable influence on the numerical values of the derived protein turnover rates.

  • Defining the Roles of Cardiokines in Human Aging and Age-Associated Diseases

    H. Srivastava, M. Pozzoli, and E. Lau

    Front Aging, 3, 884321, 2022
    URL RIS BibTex
  • In recent years an expanding collection of heart-secreted signaling proteins have been discovered that play cellular communication roles in diverse pathophysiological processes. This minireview briefly discusses current evidence for the roles of cardiokines in systemic regulation of aging and age-associated diseases. An analysis of human transcriptome and secretome data suggests the possibility that many other cardiokines remain to be discovered that may function in long-range physiological regulations. We discuss the ongoing challenges and emerging technologies for elucidating the identity and function of cardiokines in endocrine regulations

  • JCAST: Sample-specific protein isoform databases for mass spectrometry-based proteomics experiments

  • JCAST is an open-source Python software tool that allows users to easily create custom protein sequence databases for proteogenomic applications. JCAST takes in RNA sequencing data containing alternative splicing junctions as input, models the likely translatable protein isoform sequences within a particular sample, performs in silico translation using annotated open reading frames, and outputs sample-specific protein sequence databases in FASTA format to support downstream mass spectrometry data analysis of protein isoforms. This article describes the functionality and usage of the JCAST software and documents a stable code repository for user access.

  • Transcriptome features of striated muscle aging and predictability of protein level changes

    Y. Han, L. Z. Li, N. L. Kastury, C. T. Thomas, M. P. Y. Lam, and E. Lau

    Mol. Omics, 2021
    URL DOI RIS BibTex
  • We performed total RNA sequencing and multi-omics analysis comparing skeletal muscle and cardiac muscle in young adult (4 months) vs. early aging (20 months) mice to examine the molecular mechanisms of striated muscle aging. We observed that aging cardiac and skeletal muscles both invoke transcriptomic changes in innate immune system and mitochondria pathways but diverge in extracellular matrix processes. On an individual gene level, we identified 611 age-associated signatures in skeletal and cardiac muscles, including a number of myokine and cardiokine encoding genes. Because RNA and protein levels correlate only partially, we reason that differentially expressed transcripts that accurately reflect their protein counterparts will be more valuable proxies for proteomic changes and by extension physiological states. We applied a computational data analysis workflow to estimate which transcriptomic changes are more likely relevant to protein-level regulation using large proteogenomics data sets. We estimate about 48% of the aging-associated transcripts predict protein levels well (r ≥ 0.5). In parallel, a comparison of the identified aging-regulated genes with public human transcriptomics data showed that only 35–45% of the identified genes show an age-dependent expression in corresponding human tissues. Thus, integrating both RNA–protein correlation and human conservation across data sources, we nominate 134 prioritized aging striated muscle signatures that are predicted to correlate strongly with protein levels and that show age-dependent expression in humans. The results here reveal new details into how aging reshapes gene expression in striated muscles at the transcript and protein levels.

  • Atlas of exosomal microRNAs secreted from human iPSC-derived cardiac cell types

    M. Chandy, J. W. Rhee, M. O. Ozen, D. R. Williams, L. Pepic, C. Liu, H. Zhang, J. Malisa, E. Lau, U. Demirci, and J. C. Wu

    Circulation, 142(18), 1794-1796, 2020
    URL RIS BibTex
  • Cardiac-derived exosomes have received intense interest for their roles in paracrine communications and regenerative therapies. However, current understanding of how exosomes mediate cellular signaling is incomplete, in part because the contents of exosomes from different cardiac cell types are poorly defined. To learn what signals cardiac cells release, we examined the microRNA (miRNA) compositions secreted in exosomes from human induced pluripotent stem cells (iPSCs) and 3 major iPSC-derived cardiac cell types.


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