Publications

2024

Sollier, J., Basler, M., Broz, P., Dittrich, P. S., Drescher, K., Egli, A., Harms, A., Hierlemann, A., Hiller, S., King, C. G., McKinney, J. D., Moran-Gilad, J., Neher, R. A., Page, M. G. P., Panke, S., Persat, A., Picotti, P., Rentsch, K. M., Rivera-Fuentes, P., … Dehio, C. (2024). Revitalizing antibiotic discovery and development through in vitro modelling of in-patient conditions. Nature Microbiology, 9(1), 1–3. https://doi.org/10.1038/s41564-023-01566-w

2023

Gomez Solsona, B., Horn, H., Schmitt, A., Xu, W., Bucher, P., Heinrich, A., Kalmbach, S., Kreienkamp, N., Franke, M., Wimmers, F., Schuhknecht, L., Rosenwald, A., Zampieri, M., Ott, G., Lenz, G., Schulze-Osthoff, K., & Hailfinger, S. (2023). Inhibition of glutaminase-1 in DLBCL potentiates venetoclax-induced antitumor activity by promoting oxidative stress. Blood Advances, 7(24), 7433–7444. https://doi.org/10.1182/bloodadvances.2023010964
Schmitt, A., Grimm, M., Kreienkamp, N., Junge, H., Labisch, J., Schuhknecht, L., Schönfeld, C., Görsch, E., Tibello, A., Menck, K., Bleckmann, A., Lengerke, C., Rosenbauer, F., Grau, M., Zampieri, M., Schulze-Osthoff, K., Klener, P., Dolnikova, A., Lenz, G., & Hailfinger, S. (2023). BRD4 inhibition sensitizes diffuse large B-cell lymphoma cells to ferroptosis. Blood, 142(13), 1143–1155. https://doi.org/10.1182/blood.2022019274

2022

Ortmayr, K., & Zampieri, M. (2022). Sorting‐free metabolic profiling uncovers the vulnerability of fatty acid β‐oxidation in in vitro quiescence models. Molecular Systems Biology, 18(9), e10716. https://doi.org/10.15252/msb.202110716
Ortmayr, K., De La Cruz Moreno, R., & Zampieri, M. (2022). Expanding the search for small-molecule antibacterials by multidimensional profiling. Nature Chemical Biology, 18(6), 584–595. https://doi.org/10.1038/s41589-022-01040-4
Anglada-Girotto, M., Handschin, G., Ortmayr, K., Campos, A. I., Gillet, L., Manfredi, P., Mulholland, C. V., Berney, M., Jenal, U., Picotti, P., & Zampieri, M. (2022). Combining CRISPRi and metabolomics for functional annotation of compound libraries. Nature Chemical Biology, 18(5), 482–491. https://doi.org/10.1038/s41589-022-00970-3

2021

Zampieri, M. (2021). The genetic underground of antibiotic resistance. Science, 371(6531), 783–784. https://doi.org/10.1126/science.abf7922
Fuentes, D. A. F., Manfredi, P., Jenal, U., & Zampieri, M. (2021). Pareto optimality between growth-rate and lag-time couples metabolic noise to phenotypic heterogeneity in Escherichia coli. Nature Communications, 12(1), 3204. https://doi.org/10.1038/s41467-021-23522-0
Trauner, A., Banaei-Esfahani, A., Gygli, S. M., Warmer, P., Feldmann, J., Zampieri, M., Borrell, S., Collins, B. C., Beisel, C., Aebersold, R., & Gagneux, S. (2021). Expression Dysregulation as a Mediator of Fitness Costs in Antibiotic Resistance. Antimicrobial Agents and Chemotherapy, 65(9), e00504-21. https://doi.org/10.1128/AAC.00504-21

2020

Øyås, O., Borrell, S., Trauner, A., Zimmermann, M., Feldmann, J., Liphardt, T., Gagneux, S., Stelling, J., Sauer, U., & Zampieri, M. (2020). Model-based integration of genomics and metabolomics reveals SNP functionality in Mycobacterium tuberculosis. Proceedings of the National Academy of Sciences, 117(15), 8494–8502. https://doi.org/10.1073/pnas.1915551117

2019

Ortmayr, K., Dubuis, S., & Zampieri, M. (2019). Metabolic profiling of cancer cells reveals genome-wide crosstalk between transcriptional regulators and metabolism. Nature Communications, 10(1), 1841. https://doi.org/10.1038/s41467-019-09695-9
Campos, A. I., & Zampieri, M. (2019). Metabolomics-Driven Exploration of the Chemical Drug Space to Predict Combination Antimicrobial Therapies. Molecular Cell, 74(6), 1291-1303.e6. https://doi.org/10.1016/j.molcel.2019.04.001
Zampieri, M., Hörl, M., Hotz, F., Müller, N. F., & Sauer, U. (2019). Regulatory mechanisms underlying coordination of amino acid and glucose catabolism in Escherichia coli. Nature Communications, 10(1), 3354. https://doi.org/10.1038/s41467-019-11331-5

2018

Zampieri, M., Szappanos, B., Buchieri, M. V., Trauner, A., Piazza, I., Picotti, P., Gagneux, S., Borrell, S., Gicquel, B., Lelievre, J., Papp, B., & Sauer, U. (2018). High-throughput metabolomic analysis predicts mode of action of uncharacterized antimicrobial compounds. Science Translational Medicine, 10(429), eaal3973. https://doi.org/10.1126/scitranslmed.aal3973
Zampieri, M. (2018). From the metabolic profiling of drug response to drug mode of action. Current Opinion in Systems Biology, 10, 26–33. https://doi.org/10.1016/j.coisb.2018.05.005
Dubuis, S., Ortmayr, K., & Zampieri, M. (2018). A framework for large-scale metabolome drug profiling links coenzyme A metabolism to the toxicity of anti-cancer drug dichloroacetate. Communications Biology, 1(1), 101. https://doi.org/10.1038/s42003-018-0111-x

2017

Fuhrer, T., Zampieri, M., Sévin, D. C., Sauer, U., & Zamboni, N. (2017). Genomewide landscape of gene–metabolome associations in Escherichia coli. Molecular Systems Biology, 13(1), 907. https://doi.org/10.15252/msb.20167150
Gonçalves, E., Raguz Nakic, Z., Zampieri, M., Wagih, O., Ochoa, D., Sauer, U., Beltrao, P., & Saez-Rodriguez, J. (2017). Systematic Analysis of Transcriptional and Post-transcriptional Regulation of Metabolism in Yeast. PLOS Computational Biology, 13(1), e1005297. https://doi.org/10.1371/journal.pcbi.1005297
Zampieri, M., Sekar, K., Zamboni, N., & Sauer, U. (2017). Frontiers of high-throughput metabolomics. Current Opinion in Chemical Biology, 36, 15–23. https://doi.org/10.1016/j.cbpa.2016.12.006
Zampieri, M., Enke, T., Chubukov, V., Ricci, V., Piddock, L., & Sauer, U. (2017). Metabolic constraints on the evolution of antibiotic resistance. Molecular Systems Biology, 13(3), 917. https://doi.org/10.15252/msb.20167028
Zampieri, M., Zimmermann, M., Claassen, M., & Sauer, U. (2017). Nontargeted Metabolomics Reveals the Multilevel Response to Antibiotic Perturbations. Cell Reports, 19(6), 1214–1228. https://doi.org/10.1016/j.celrep.2017.04.002
Zampieri, M., & Sauer, U. (2017). Metabolomics-driven understanding of genotype-phenotype relations in model organisms. Current Opinion in Systems Biology, 6, 28–36. https://doi.org/10.1016/j.coisb.2017.08.007

2016

Zampieri, M., & Sauer, U. (2016). Model-based media selection to minimize the cost of metabolic cooperation in microbial ecosystems. Bioinformatics, 32(11), 1733–1739. https://doi.org/10.1093/bioinformatics/btw062

2015

Oliveira, A. P., Ludwig, C., Zampieri, M., Weisser, H., Aebersold, R., & Sauer, U. (2015). Dynamic phosphoproteomics reveals TORC1-dependent regulation of yeast nucleotide and amino acid biosynthesis. Science Signaling, 8(374). https://doi.org/10.1126/scisignal.2005768

2014

Schulz, J. C., Zampieri, M., Wanka, S., Von Mering, C., & Sauer, U. (2014). Large-scale functional analysis of the roles of phosphorylation in yeast metabolic pathways. Science Signaling, 7(353). https://doi.org/10.1126/scisignal.2005602

2012

Schuetz, R., Zamboni, N., Zampieri, M., Heinemann, M., & Sauer, U. (2012). Multidimensional Optimality of Microbial Metabolism. Science, 336(6081), 601–604. https://doi.org/10.1126/science.1216882
Beg, Q. K., Zampieri, M., Klitgord, N., Collins, S. B., Altafini, C., Serres, M. H., & Segrè, D. (2012). Detection of transcriptional triggers in the dynamics of microbial growth: application to the respiratorily versatile bacterium Shewanella oneidensis. Nucleic Acids Research, 40(15), 7132–7149. https://doi.org/10.1093/nar/gks467
Facchetti, G., Zampieri, M., & Altafini, C. (2012). Predicting and characterizing selective multiple drug treatments for metabolicdiseases and cancer. BMC Systems Biology, 6(1), 115. https://doi.org/10.1186/1752-0509-6-115

2011

Zampieri, M., Altafini, C., Eduati, F., Di Camillo, B., Toffolo, G., & De Palo, G. (2011). Adaptation as a genome-wide autoregulatory principle in the stress response of yeast. IET Systems Biology, 5(4), 269–279. https://doi.org/10.1049/iet-syb.2009.0050
Zampieri, M., Legname, G., Segrè, D., & Altafini, C. (2011). A system-level approach for deciphering the transcriptional response to prion infection. Bioinformatics, 27(24), 3407–3414. https://doi.org/10.1093/bioinformatics/btr580

2010

Benetti, F., Gasperini, L., Zampieri, M., & Legname, G. (2010). Gene expression profiling to identify druggable targets in prion diseases. Expert Opinion on Drug Discovery, 5(2), 177–202. https://doi.org/10.1517/17460440903544449

2009

Zampieri, M., Legname, G., & Altafini, C. (2009). Investigating the Conformational Stability of Prion Strains through a Kinetic Replication Model. PLoS Computational Biology, 5(7), e1000420. https://doi.org/10.1371/journal.pcbi.1000420
Bicciato, S., Spinelli, R., Zampieri, M., Mangano, E., Ferrari, F., Beltrame, L., Cifola, I., Peano, C., Solari, A., & Battaglia, C. (2009). A computational procedure to identify significant overlap of differentially expressed and genomic imbalanced regions in cancer datasets †. Nucleic Acids Research, 37(15), 5057–5070. https://doi.org/10.1093/nar/gkp520
Soranzo, N., Zampieri, M., Farina, L., & Altafini, C. (2009). mRNA stability and the unfolding of gene expression in the long-period yeast metabolic cycle. BMC Systems Biology, 3(1), 18. https://doi.org/10.1186/1752-0509-3-18

2008

Zampieri, M., Soranzo, N., & Altafini, C. (2008). Discerning static and causal interactions in genome-wide reverse engineering problems. Bioinformatics, 24(13), 1510–1515. https://doi.org/10.1093/bioinformatics/btn220
Zampieri, M., Soranzo, N., Bianchini, D., & Altafini, C. (2008). Origin of Co-Expression Patterns in E.coli and S.cerevisiae Emerging from Reverse Engineering Algorithms. PLoS ONE, 3(8), e2981. https://doi.org/10.1371/journal.pone.0002981