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Amir Zadok Mitchell PhD

TitleAssociate Professor
InstitutionUMass Chan Medical School
DepartmentSystems Biology
AddressUMass Chan Medical School
55 Lake Avenue North
Worcester MA 01655
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    Other Positions
    InstitutionT.H. Chan School of Medicine
    DepartmentBiochemistry and Molecular Biotechnology

    InstitutionT.H. Chan School of Medicine
    DepartmentMolecular, Cell and Cancer Biology

    InstitutionT.H. Chan School of Medicine
    DepartmentProgram in Microbial Dynamics

    InstitutionT.H. Chan School of Medicine
    DepartmentProgram in Molecular Medicine

    InstitutionT.H. Chan School of Medicine
    DepartmentSystems Biology

    InstitutionMorningside Graduate School of Biomedical Sciences
    DepartmentBiophysical Chemical and Computational Biology

    InstitutionMorningside Graduate School of Biomedical Sciences
    DepartmentCancer Biology

    InstitutionMorningside Graduate School of Biomedical Sciences
    DepartmentInterdisciplinary Graduate Program

    InstitutionMorningside Graduate School of Biomedical Sciences
    DepartmentMD/PhD Program

    InstitutionMorningside Graduate School of Biomedical Sciences
    DepartmentSystems Computational and Quantitative Biology


    Collapse Biography 
    Collapse education and training
    Tel Aviv University, Tel Aviv, , IsraelMSZoology
    Weizmann Institute of Science, Rehovot, , IsraelPHDMolecular Genetics
    Collapse awards and honors
    2020Dean’s Award for Outstanding Contribution to Curricular Development, University of Massachusetts Chan Medical Schoo
    2018Dean’s Award for Outstanding Contribution to Curricular Development, University of Massachusetts Chan Medical School
    2012Program for Breakthrough in Biomedical Research, University of California, San Francisco
    2010 - 2011Postdoctoral fellowship , European Molecular Biology Organization
    2010Haim Holtzman Memorial Prize of excellence for PhD research, Weizmann Institute of Science
    2010Award for PhD research, TThe Israeli Society for Biochemistry and Molecular Biology
    2000 - 2003Lautman interdisciplinary program for outstanding students , Tel Aviv University

    Collapse Overview 
    Collapse overview

    Read more at the Mitchell lab website

    Overview

    Our lab studies how cells decode, respond, and adapt to external stimuli in the context of multi-lateral host-drug-microbiome interactions such as in the tumor-microbiome. We address this complexity challenge by reconstituting multi-member systems with varying levels of complexity from individual parts that are well-understood on their own (model organisms, clonal cell-lines, drugs, and metabolites). This bottom-up approach allows us to investigate the unique properties that emerge in complex systems using tractable host-drug-microbiome models. Our experimental work leverages on genomics, transcriptomics, and quantitative high-throughput microscopy and is complemented by computational approaches and mathematical modeling.

    Bacteria-drug interactions

    The human gut microbiome is a central factor influencing the efficacy of host-targeted drugs. This impact is facilitated by a myriad of complex host-drug-microbiome interactions that are gradually and slowly being characterized. An important force impacting host-drug-microbiome interactions is the selection force host-targeted drugs apply on the microbiome, which in turn can lead to impactful ecological and evolutionary adaptations in the microbiome itself. However, while the impact of many host-targeted drugs on the microbiome is widely appreciated, the bacterial targets of these drugs remain mostly unknown. In our study, we are screening large drug libraries to identify host-targeted drugs that inhibit bacterial growth and are aiming to identify the bacterial targets of these drugs. Such systematic understanding will reveal which host-targeted drugs resemble known categories of antibiotic drugs and if host-targeted drugs can point to new bacterial pathways that can be targeted by yet-to-be developed antibiotics.

    Bacteria-host interactions

    The human microbiome emerges as a major player in cancer biology. Groundbreaking studies in recent years uncovered clinically relevant associations between human microbiota and therapy success, and have identified mechanisms facilitating these interactions. Recent research of patient tumors revealed that many tumors harbor their own microbiome. These exciting findings lead to the appreciation that personalized cancer treatment should be tailored by the genetic makeup of both tumor and the microbiome. Our research of the tumor-microbiome is not anthropo-centric but microbial-centric, and aims to understand how do bacteria within tumors adapt to this unique microenvironment. We are investigating these evolutionary questions in diverse experimental systems and using both model bacterial lab species and clinical isolates cultured directly from tumors.

    Updated information can be found at the Mitchell lab website

     


    Collapse Rotation Projects

    We are looking for rotation students to visit our lab and participate in one of our ongoing research projects. Different aspects of the projects require different toolsets ranging from experimental biology to quantitative biology and mathematical modeling. Rotation students will have a chance to acquire new skill-sets and develop expertise required for implementing a quantitative approach for understanding cell regulation, signaling and evolution. Interested students should email Amir directly and briefly describe their academic background, future plans and interest in the lab.

    Current rotation projects:

    • Investigating bacterial response to host-targeted drugs: As part of our research into the tumor-microbiome (tumor assosiated bacteria), we are testing how bacterial growth is inhibited by cytotoxic drugs that target cancer cells. Rotation students will run genetic screens in bacteria to identify bacterial toxicity and resistance mechanisms. In addition the students will test if bacteria can rapidly become drug resistance by evolutionary adaptation.

    • Monitoring recovery dynamcis of melanoma cells in response to targeted therapy: The project involves examining and quantifying different aspects of cell behavior, population dynamics and adaptive resistance to targeted therapy. Rotation students will examine cellular behavior of established cell-lines and will clone and engineer new live-cell reporters for microscopy based assays.

     
     


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    Collapse Bibliographic 
    Collapse selected publications
    Publications listed below are automatically derived from MEDLINE/PubMed and other sources, which might result in incorrect or missing publications. Faculty can login to make corrections and additions.
    Newest   |   Oldest   |   Most Cited   |   Most Discussed   |   Timeline   |   Field Summary   |   Plain Text
    PMC Citations indicate the number of times the publication was cited by articles in PubMed Central, and the Altmetric score represents citations in news articles and social media. (Note that publications are often cited in additional ways that are not shown here.) Fields are based on how the National Library of Medicine (NLM) classifies the publication's journal and might not represent the specific topic of the publication. Translation tags are based on the publication type and the MeSH terms NLM assigns to the publication. Some publications (especially newer ones and publications not in PubMed) might not yet be assigned Field or Translation tags.) Click a Field or Translation tag to filter the publications.
    1. Noto Guillen M, Li C, Rosener B, Mitchell A. Antibacterial activity of nonantibiotics is orthogonal to standard antibiotics. Science. 2024 Apr 05; 384(6691):93-100. PMID: 38484036.
      Citations:    
    2. Sayin S, Mitchell A. Functional Assay for Measuring Bacterial Degradation of Gemcitabine Chemotherapy. Bio Protoc. 2023 Sep 05; 13(17):e4797. PMID: 37719072.
      Citations:    
    3. Sayin S, Rosener B, Li CG, Ho B, Ponomarova O, Ward DV, Walhout AJM, Mitchell A. Evolved bacterial resistance to the chemotherapy gemcitabine modulates its efficacy in co-cultured cancer cells. Elife. 2023 02 03; 12. PMID: 36734518.
      Citations: 4     Fields:    Translation:HumansCells
    4. Noto Guillen M, Rosener B, Sayin S, Mitchell A. Assembling stable syntrophic Escherichia coli communities by comprehensively identifying beneficiaries of secreted goods. Cell Syst. 2021 11 17; 12(11):1064-1078.e7. PMID: 34469744.
      Citations: 15     Fields:    Translation:Cells
    5. Khoshkenar P, Lowry E, Mitchell A. Rapid signaling reactivation after targeted BRAF inhibition predicts the proliferation of individual melanoma cells from an isogenic population. Sci Rep. 2021 07 29; 11(1):15473. PMID: 34326399.
      Citations:    Fields:    Translation:HumansCells
    6. Rosener B, Sayin S, Oluoch PO, Garc?a Gonz?lez AP, Mori H, Walhout AJ, Mitchell A. Evolved bacterial resistance against fluoropyrimidines can lower chemotherapy impact in the Caenorhabditis elegans host. Elife. 2020 11 30; 9. PMID: 33252330.
      Citations: 9     Fields:    Translation:AnimalsCells
    7. Xavier JB, Young VB, Skufca J, Ginty F, Testerman T, Pearson AT, Macklin P, Mitchell A, Shmulevich I, Xie L, Caporaso JG, Crandall KA, Simone NL, Godoy-Vitorino F, Griffin TJ, Whiteson KL, Gustafson HH, Slade DJ, Schmidt TM, Walther-Antonio MRS, Korem T, Webb-Robertson BM, Styczynski MP, Johnson WE, Jobin C, Ridlon JM, Koh AY, Yu M, Kelly L, Wargo JA. The Cancer Microbiome: Distinguishing Direct and Indirect Effects Requires a Systemic View. Trends Cancer. 2020 03; 6(3):192-204. PMID: 32101723.
      Citations: 90     Fields:    Translation:HumansAnimalsCellsPHPublic Health
    8. Dahan O, Dorfman BS, Sayin S, Rosener B, Hua T, Yarden A, Mitchell A. Harnessing robotic automation and web-based technologies to modernize scientific outreach. PLoS Biol. 2019 06; 17(6):e3000348. PMID: 31242174.
      Citations: 1     Fields:    Translation:Humans
    9. Shraga A, Olshvang E, Davidzohn N, Khoshkenar P, Germain N, Shurrush K, Carvalho S, Avram L, Albeck S, Unger T, Lefker B, Subramanyam C, Hudkins RL, Mitchell A, Shulman Z, Kinoshita T, London N. Covalent Docking Identifies a Potent and Selective MKK7 Inhibitor. Cell Chem Biol. 2019 01 17; 26(1):98-108.e5. PMID: 30449673.
      Citations: 22     Fields:    Translation:HumansAnimalsCells
    10. Bugaj LJ, Sabnis AJ, Mitchell A, Garbarino JE, Toettcher JE, Bivona TG, Lim WA. Cancer mutations and targeted drugs can disrupt dynamic signal encoding by the Ras-Erk pathway. Science. 2018 08 31; 361(6405). PMID: 30166458.
      Citations: 70     Fields:    Translation:HumansCells
    11. Mitchell A, Lim W. Cellular perception and misperception: Internal models for decision-making shaped by evolutionary experience. Bioessays. 2016 09; 38(9):845-9. PMID: 27461864.
      Citations: 14     Fields:    Translation:AnimalsCells
    12. Mitchell A, Wei P, Lim WA. Oscillatory stress stimulation uncovers an Achilles' heel of the yeast MAPK signaling network. Science. 2015 Dec 11; 350(6266):1379-83. PMID: 26586187.
      Citations: 43     Fields:    Translation:AnimalsCells
    13. Yona AH, Manor YS, Herbst RH, Romano GH, Mitchell A, Kupiec M, Pilpel Y, Dahan O. Chromosomal duplication is a transient evolutionary solution to stress. Proc Natl Acad Sci U S A. 2012 Dec 18; 109(51):21010-5. PMID: 23197825.
      Citations: 176     Fields:    Translation:AnimalsCells
    14. Mitchell A, Pilpel Y. A mathematical model for adaptive prediction of environmental changes by microorganisms. Proc Natl Acad Sci U S A. 2011 Apr 26; 108(17):7271-6. PMID: 21487001.
      Citations: 29     Fields:    Translation:AnimalsCells
    15. Mitchell A, Romano GH, Groisman B, Yona A, Dekel E, Kupiec M, Dahan O, Pilpel Y. Adaptive prediction of environmental changes by microorganisms. Nature. 2009 Jul 09; 460(7252):220-4. PMID: 19536156.
      Citations: 215     Fields:    Translation:AnimalsCells
    16. Mitchell A, Graur D. Inferring the pattern of spontaneous mutation from the pattern of substitution in unitary pseudogenes of Mycobacterium leprae and a comparison of mutation patterns among distantly related organisms. J Mol Evol. 2005 Dec; 61(6):795-803. PMID: 16315108.
      Citations: 9     Fields:    Translation:HumansAnimalsCells
    17. Mayrose I, Mitchell A, Pupko T. Site-specific evolutionary rate inference: taking phylogenetic uncertainty into account. J Mol Evol. 2005 Mar; 60(3):345-53. PMID: 15871045.
      Citations: 18     Fields:    Translation:Cells
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