[{"article_number":"173","project":[{"grant_number":"V00738","name":"Bacterial toxin-antitoxin systems as antiphage defense mechanisms","call_identifier":"FWF","_id":"26956E74-B435-11E9-9278-68D0E5697425"}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","citation":{"chicago":"Nikolic, Nela, Martina Sauert, Tanino G. Albanese, and Isabella Moll. “Quantifying Heterologous Gene Expression during Ectopic MazF Production in Escherichia Coli.” BMC Research Notes. Springer Nature, 2022. https://doi.org/10.1186/s13104-022-06061-9.","ista":"Nikolic N, Sauert M, Albanese TG, Moll I. 2022. Quantifying heterologous gene expression during ectopic MazF production in Escherichia coli. BMC Research Notes. 15, 173.","mla":"Nikolic, Nela, et al. “Quantifying Heterologous Gene Expression during Ectopic MazF Production in Escherichia Coli.” BMC Research Notes, vol. 15, 173, Springer Nature, 2022, doi:10.1186/s13104-022-06061-9.","ieee":"N. Nikolic, M. Sauert, T. G. Albanese, and I. Moll, “Quantifying heterologous gene expression during ectopic MazF production in Escherichia coli,” BMC Research Notes, vol. 15. Springer Nature, 2022.","short":"N. Nikolic, M. Sauert, T.G. Albanese, I. Moll, BMC Research Notes 15 (2022).","ama":"Nikolic N, Sauert M, Albanese TG, Moll I. Quantifying heterologous gene expression during ectopic MazF production in Escherichia coli. BMC Research Notes. 2022;15. doi:10.1186/s13104-022-06061-9","apa":"Nikolic, N., Sauert, M., Albanese, T. G., & Moll, I. (2022). Quantifying heterologous gene expression during ectopic MazF production in Escherichia coli. BMC Research Notes. Springer Nature. https://doi.org/10.1186/s13104-022-06061-9"},"title":"Quantifying heterologous gene expression during ectopic MazF production in Escherichia coli","author":[{"id":"42D9CABC-F248-11E8-B48F-1D18A9856A87","first_name":"Nela","orcid":"0000-0001-9068-6090","full_name":"Nikolic, Nela","last_name":"Nikolic"},{"first_name":"Martina","full_name":"Sauert, Martina","last_name":"Sauert"},{"first_name":"Tanino G.","last_name":"Albanese","full_name":"Albanese, Tanino G."},{"first_name":"Isabella","last_name":"Moll","full_name":"Moll, Isabella"}],"article_processing_charge":"No","external_id":{"pmid":["35562780"]},"acknowledgement":"We acknowledge the Max Perutz Labs FACS Facility together with Thomas Sauer. NN is grateful to Călin C. Guet for his support.\r\nThis work was funded by the Elise Richter grant V738 of the Austrian Science Fund (FWF), and the FWF Lise Meitner grant M1697, to NN; and by the FWF grant P22249, FWF Special Research Program RNA-REG F43 (subproject F4316), and FWF doctoral program RNA Biology (W1207), to IM. Open access funding provided by the Austrian Science Fund.","publisher":"Springer Nature","quality_controlled":"1","oa":1,"day":"13","publication":"BMC Research Notes","has_accepted_license":"1","year":"2022","date_published":"2022-05-13T00:00:00Z","doi":"10.1186/s13104-022-06061-9","date_created":"2022-08-01T09:04:27Z","_id":"11713","status":"public","keyword":["General Biochemistry","Genetics and Molecular Biology","General Medicine"],"article_type":"letter_note","type":"journal_article","tmp":{"legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)"},"ddc":["570"],"date_updated":"2022-08-01T09:27:40Z","file_date_updated":"2022-08-01T09:24:42Z","department":[{"_id":"CaGu"}],"pmid":1,"oa_version":"Published Version","abstract":[{"lang":"eng","text":"Objective: MazF is a sequence-specific endoribonuclease-toxin of the MazEF toxin–antitoxin system. MazF cleaves single-stranded ribonucleic acid (RNA) regions at adenine–cytosine–adenine (ACA) sequences in the bacterium Escherichia coli. The MazEF system has been used in various biotechnology and synthetic biology applications. In this study, we infer how ectopic mazF overexpression affects production of heterologous proteins. To this end, we quantified the levels of fluorescent proteins expressed in E. coli from reporters translated from the ACA-containing or ACA-less messenger RNAs (mRNAs). Additionally, we addressed the impact of the 5′-untranslated region of these reporter mRNAs under the same conditions by comparing expression from mRNAs that comprise (canonical mRNA) or lack this region (leaderless mRNA).\r\nResults: Flow cytometry analysis indicates that during mazF overexpression, fluorescent proteins are translated from the canonical as well as leaderless mRNAs. Our analysis further indicates that longer mazF overexpression generally increases the concentration of fluorescent proteins translated from ACA-less mRNAs, however it also substantially increases bacterial population heterogeneity. Finally, our results suggest that the strength and duration of mazF overexpression should be optimized for each experimental setup, to maximize the heterologous protein production and minimize the amount of phenotypic heterogeneity in bacterial populations, which is unfavorable in biotechnological processes."}],"month":"05","intvolume":" 15","scopus_import":"1","file":[{"file_id":"11714","checksum":"008156e5340e9789f0f6d82bde4d347a","success":1,"access_level":"open_access","relation":"main_file","content_type":"application/pdf","date_created":"2022-08-01T09:24:42Z","file_name":"2022_BMCResearchNotes_Nikolic.pdf","creator":"dernst","date_updated":"2022-08-01T09:24:42Z","file_size":1545310}],"language":[{"iso":"eng"}],"publication_identifier":{"issn":["1756-0500"]},"publication_status":"published","related_material":{"link":[{"relation":"erratum","url":"https://doi.org/10.1186/s13104-022-06152-7"}]},"volume":15,"license":"https://creativecommons.org/licenses/by/4.0/"},{"article_number":"385","citation":{"ista":"Glover G, Voliotis M, Łapińska U, Invergo BM, Soanes D, O’Neill P, Moore K, Nikolic N, Petrov P, Milner DS, Roy S, Heesom K, Richards TA, Tsaneva-Atanasova K, Pagliara S. 2022. Nutrient and salt depletion synergistically boosts glucose metabolism in individual Escherichia coli cells. Communications Biology. 5, 385.","chicago":"Glover, Georgina, Margaritis Voliotis, Urszula Łapińska, Brandon M. Invergo, Darren Soanes, Paul O’Neill, Karen Moore, et al. “Nutrient and Salt Depletion Synergistically Boosts Glucose Metabolism in Individual Escherichia Coli Cells.” Communications Biology. Springer Nature, 2022. https://doi.org/10.1038/s42003-022-03336-6.","ieee":"G. Glover et al., “Nutrient and salt depletion synergistically boosts glucose metabolism in individual Escherichia coli cells,” Communications Biology, vol. 5. Springer Nature, 2022.","short":"G. Glover, M. Voliotis, U. Łapińska, B.M. Invergo, D. Soanes, P. O’Neill, K. Moore, N. Nikolic, P. Petrov, D.S. Milner, S. Roy, K. Heesom, T.A. Richards, K. Tsaneva-Atanasova, S. Pagliara, Communications Biology 5 (2022).","apa":"Glover, G., Voliotis, M., Łapińska, U., Invergo, B. M., Soanes, D., O’Neill, P., … Pagliara, S. (2022). Nutrient and salt depletion synergistically boosts glucose metabolism in individual Escherichia coli cells. Communications Biology. Springer Nature. https://doi.org/10.1038/s42003-022-03336-6","ama":"Glover G, Voliotis M, Łapińska U, et al. Nutrient and salt depletion synergistically boosts glucose metabolism in individual Escherichia coli cells. Communications Biology. 2022;5. doi:10.1038/s42003-022-03336-6","mla":"Glover, Georgina, et al. “Nutrient and Salt Depletion Synergistically Boosts Glucose Metabolism in Individual Escherichia Coli Cells.” Communications Biology, vol. 5, 385, Springer Nature, 2022, doi:10.1038/s42003-022-03336-6."},"user_id":"4359f0d1-fa6c-11eb-b949-802e58b17ae8","author":[{"last_name":"Glover","full_name":"Glover, Georgina","first_name":"Georgina"},{"last_name":"Voliotis","full_name":"Voliotis, Margaritis","first_name":"Margaritis"},{"first_name":"Urszula","full_name":"Łapińska, Urszula","last_name":"Łapińska"},{"first_name":"Brandon M.","full_name":"Invergo, Brandon M.","last_name":"Invergo"},{"full_name":"Soanes, Darren","last_name":"Soanes","first_name":"Darren"},{"last_name":"O’Neill","full_name":"O’Neill, Paul","first_name":"Paul"},{"first_name":"Karen","full_name":"Moore, Karen","last_name":"Moore"},{"id":"42D9CABC-F248-11E8-B48F-1D18A9856A87","first_name":"Nela","full_name":"Nikolic, Nela","orcid":"0000-0001-9068-6090","last_name":"Nikolic"},{"full_name":"Petrov, Peter","last_name":"Petrov","first_name":"Peter"},{"first_name":"David S.","full_name":"Milner, David S.","last_name":"Milner"},{"first_name":"Sumita","full_name":"Roy, Sumita","last_name":"Roy"},{"first_name":"Kate","full_name":"Heesom, Kate","last_name":"Heesom"},{"first_name":"Thomas A.","full_name":"Richards, Thomas A.","last_name":"Richards"},{"first_name":"Krasimira","last_name":"Tsaneva-Atanasova","full_name":"Tsaneva-Atanasova, Krasimira"},{"full_name":"Pagliara, Stefano","last_name":"Pagliara","first_name":"Stefano"}],"article_processing_charge":"No","external_id":{"pmid":["35444215"],"isi":["000784143400001"]},"title":"Nutrient and salt depletion synergistically boosts glucose metabolism in individual Escherichia coli cells","acknowledgement":"G.G. was supported by an EPSRC DTP PhD studentship (EP/M506527/1). M.V. and K.T.A. gratefully acknowledge financial support from the EPSRC (EP/N014391/1). U.L. was supported through a BBSRC grant (BB/V008021/1) and an MRC Proximity to Discovery EXCITEME2 grant (MCPC17189). This work was further supported by a Royal Society Research Grant (RG180007) awarded to S.P. and a QUEX Initiator grant awarded to S.P. and K.T.A.. D.S.M., T.A.R. and S.P.’s work in this area is also supported by a Marie Skłodowska-Curie project SINGEK (H2020-MSCA-ITN-2015-675752) and the Gordon and Betty Moore Foundation Marine Microbiology Initiative (GBMF5514). B.M.I. acknowledges support from a Wellcome Trust Institutional Strategic Support Award to the University of Exeter (204909/Z/16/Z). This project utilised equipment funded by the Wellcome Trust Institutional Strategic Support Fund (WT097835MF), Wellcome Trust Multi User Equipment Award (WT101650MA) and BBSRC LOLA award (BB/K003240/1).","publisher":"Springer Nature","quality_controlled":"1","oa":1,"has_accepted_license":"1","isi":1,"year":"2022","day":"20","publication":"Communications Biology","doi":"10.1038/s42003-022-03336-6","date_published":"2022-04-20T00:00:00Z","date_created":"2022-05-01T22:01:41Z","_id":"11339","type":"journal_article","article_type":"original","tmp":{"legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)"},"status":"public","date_updated":"2023-08-03T06:45:26Z","ddc":["570"],"department":[{"_id":"CaGu"}],"file_date_updated":"2022-05-02T06:26:26Z","abstract":[{"lang":"eng","text":"The interaction between a cell and its environment shapes fundamental intracellular processes such as cellular metabolism. In most cases growth rate is treated as a proximal metric for understanding the cellular metabolic status. However, changes in growth rate might not reflect metabolic variations in individuals responding to environmental fluctuations. Here we use single-cell microfluidics-microscopy combined with transcriptomics, proteomics and mathematical modelling to quantify the accumulation of glucose within Escherichia coli cells. In contrast to the current consensus, we reveal that environmental conditions which are comparatively unfavourable for growth, where both nutrients and salinity are depleted, increase glucose accumulation rates in individual bacteria and population subsets. We find that these changes in metabolic function are underpinned by variations at the translational and posttranslational level but not at the transcriptional level and are not dictated by changes in cell size. The metabolic response-characteristics identified greatly advance our fundamental understanding of the interactions between bacteria and their environment and have important ramifications when investigating cellular processes where salinity plays an important role."}],"pmid":1,"oa_version":"Published Version","scopus_import":"1","month":"04","intvolume":" 5","publication_identifier":{"eissn":["2399-3642"]},"publication_status":"published","file":[{"file_name":"2022_CommBiology_Glover.pdf","date_created":"2022-05-02T06:26:26Z","file_size":2827723,"date_updated":"2022-05-02T06:26:26Z","creator":"dernst","success":1,"file_id":"11342","checksum":"7c6f76ab17393d650825cc240edc84b3","content_type":"application/pdf","relation":"main_file","access_level":"open_access"}],"language":[{"iso":"eng"}],"volume":5},{"intvolume":" 65","month":"02","scopus_import":"1","oa_version":"Published Version","abstract":[{"lang":"eng","text":"Autoregulation is the direct modulation of gene expression by the product of the corresponding gene. Autoregulation of bacterial gene expression has been mostly studied at the transcriptional level, when a protein acts as the cognate transcriptional repressor. A recent study investigating dynamics of the bacterial toxin–antitoxin MazEF system has shown how autoregulation at both the transcriptional and post-transcriptional levels affects the heterogeneity of Escherichia coli populations. Toxin–antitoxin systems hold a crucial but still elusive part in bacterial response to stress. This perspective highlights how these modules can also serve as a great model system for investigating basic concepts in gene regulation. However, as the genomic background and environmental conditions substantially influence toxin activation, it is important to study (auto)regulation of toxin–antitoxin systems in well-defined setups as well as in conditions that resemble the environmental niche."}],"ec_funded":1,"volume":65,"issue":"1","language":[{"iso":"eng"}],"file":[{"date_created":"2019-02-06T07:50:58Z","file_name":"2019_CurrentGenetics_Nikolic.pdf","date_updated":"2020-07-14T12:44:47Z","file_size":776399,"creator":"dernst","checksum":"6779708b0b632a1a6ed28c56f5161142","file_id":"5930","content_type":"application/pdf","access_level":"open_access","relation":"main_file"}],"publication_status":"published","status":"public","tmp":{"legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)"},"type":"journal_article","_id":"138","department":[{"_id":"CaGu"}],"file_date_updated":"2020-07-14T12:44:47Z","ddc":["570"],"date_updated":"2023-09-08T13:23:42Z","oa":1,"publisher":"Springer","quality_controlled":"1","date_created":"2018-12-11T11:44:50Z","doi":"10.1007/s00294-018-0879-8","date_published":"2019-02-01T00:00:00Z","page":"133-138","publication":"Current Genetics","day":"01","year":"2019","isi":1,"has_accepted_license":"1","project":[{"name":"International IST Postdoc Fellowship Programme","grant_number":"291734","_id":"25681D80-B435-11E9-9278-68D0E5697425","call_identifier":"FP7"}],"title":"Autoregulation of bacterial gene expression: lessons from the MazEF toxin–antitoxin system","external_id":{"isi":["000456958800017"]},"article_processing_charge":"Yes (via OA deal)","author":[{"orcid":"0000-0001-9068-6090","full_name":"Nikolic, Nela","last_name":"Nikolic","id":"42D9CABC-F248-11E8-B48F-1D18A9856A87","first_name":"Nela"}],"publist_id":"7785","user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","citation":{"apa":"Nikolic, N. (2019). Autoregulation of bacterial gene expression: lessons from the MazEF toxin–antitoxin system. Current Genetics. Springer. https://doi.org/10.1007/s00294-018-0879-8","ama":"Nikolic N. Autoregulation of bacterial gene expression: lessons from the MazEF toxin–antitoxin system. Current Genetics. 2019;65(1):133-138. doi:10.1007/s00294-018-0879-8","ieee":"N. Nikolic, “Autoregulation of bacterial gene expression: lessons from the MazEF toxin–antitoxin system,” Current Genetics, vol. 65, no. 1. Springer, pp. 133–138, 2019.","short":"N. Nikolic, Current Genetics 65 (2019) 133–138.","mla":"Nikolic, Nela. “Autoregulation of Bacterial Gene Expression: Lessons from the MazEF Toxin–Antitoxin System.” Current Genetics, vol. 65, no. 1, Springer, 2019, pp. 133–38, doi:10.1007/s00294-018-0879-8.","ista":"Nikolic N. 2019. Autoregulation of bacterial gene expression: lessons from the MazEF toxin–antitoxin system. Current Genetics. 65(1), 133–138.","chicago":"Nikolic, Nela. “Autoregulation of Bacterial Gene Expression: Lessons from the MazEF Toxin–Antitoxin System.” Current Genetics. Springer, 2019. https://doi.org/10.1007/s00294-018-0879-8."}},{"project":[{"_id":"3AC91DDA-15DF-11EA-824D-93A3E7B544D1","call_identifier":"FWF","name":"FWF Open Access Fund"}],"author":[{"first_name":"Nela","id":"42D9CABC-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0001-9068-6090","full_name":"Nikolic, Nela","last_name":"Nikolic"},{"id":"2C471CFA-F248-11E8-B48F-1D18A9856A87","first_name":"Tobias","last_name":"Bergmiller","orcid":"0000-0001-5396-4346","full_name":"Bergmiller, Tobias"},{"full_name":"Vandervelde, Alexandra","last_name":"Vandervelde","first_name":"Alexandra"},{"last_name":"Albanese","full_name":"Albanese, Tanino","first_name":"Tanino"},{"full_name":"Gelens, Lendert","last_name":"Gelens","first_name":"Lendert"},{"first_name":"Isabella","full_name":"Moll, Isabella","last_name":"Moll"}],"external_id":{"isi":["000429009500021"]},"article_processing_charge":"Yes (in subscription journal)","title":"Autoregulation of mazEF expression underlies growth heterogeneity in bacterial populations","citation":{"mla":"Nikolic, Nela, et al. “Autoregulation of MazEF Expression Underlies Growth Heterogeneity in Bacterial Populations.” Nucleic Acids Research, vol. 46, no. 6, Oxford University Press, 2018, pp. 2918–31, doi:10.1093/nar/gky079.","ieee":"N. Nikolic, T. Bergmiller, A. Vandervelde, T. Albanese, L. Gelens, and I. Moll, “Autoregulation of mazEF expression underlies growth heterogeneity in bacterial populations,” Nucleic Acids Research, vol. 46, no. 6. Oxford University Press, pp. 2918–2931, 2018.","short":"N. Nikolic, T. Bergmiller, A. Vandervelde, T. Albanese, L. Gelens, I. Moll, Nucleic Acids Research 46 (2018) 2918–2931.","ama":"Nikolic N, Bergmiller T, Vandervelde A, Albanese T, Gelens L, Moll I. Autoregulation of mazEF expression underlies growth heterogeneity in bacterial populations. Nucleic Acids Research. 2018;46(6):2918-2931. doi:10.1093/nar/gky079","apa":"Nikolic, N., Bergmiller, T., Vandervelde, A., Albanese, T., Gelens, L., & Moll, I. (2018). Autoregulation of mazEF expression underlies growth heterogeneity in bacterial populations. Nucleic Acids Research. Oxford University Press. https://doi.org/10.1093/nar/gky079","chicago":"Nikolic, Nela, Tobias Bergmiller, Alexandra Vandervelde, Tanino Albanese, Lendert Gelens, and Isabella Moll. “Autoregulation of MazEF Expression Underlies Growth Heterogeneity in Bacterial Populations.” Nucleic Acids Research. Oxford University Press, 2018. https://doi.org/10.1093/nar/gky079.","ista":"Nikolic N, Bergmiller T, Vandervelde A, Albanese T, Gelens L, Moll I. 2018. Autoregulation of mazEF expression underlies growth heterogeneity in bacterial populations. Nucleic Acids Research. 46(6), 2918–2931."},"user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","quality_controlled":"1","publisher":"Oxford University Press","oa":1,"page":"2918-2931","doi":"10.1093/nar/gky079","date_published":"2018-04-06T00:00:00Z","date_created":"2018-12-11T11:46:29Z","has_accepted_license":"1","isi":1,"year":"2018","day":"06","publication":"Nucleic Acids Research","type":"journal_article","tmp":{"legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)"},"status":"public","pubrep_id":"971","_id":"438","department":[{"_id":"CaGu"}],"file_date_updated":"2020-07-14T12:46:27Z","date_updated":"2024-02-21T13:44:45Z","ddc":["576"],"scopus_import":"1","month":"04","intvolume":" 46","abstract":[{"lang":"eng","text":"The MazF toxin sequence-specifically cleaves single-stranded RNA upon various stressful conditions, and it is activated as a part of the mazEF toxin–antitoxin module in Escherichia coli. Although autoregulation of mazEF expression through the MazE antitoxin-dependent transcriptional repression has been biochemically characterized, less is known about post-transcriptional autoregulation, as well as how both of these autoregulatory features affect growth of single cells during conditions that promote MazF production. Here, we demonstrate post-transcriptional autoregulation of mazF expression dynamics by MazF cleaving its own transcript. Single-cell analyses of bacterial populations during ectopic MazF production indicated that two-level autoregulation of mazEF expression influences cell-to-cell growth rate heterogeneity. The increase in growth rate heterogeneity is governed by the MazE antitoxin, and tuned by the MazF-dependent mazF mRNA cleavage. Also, both autoregulatory features grant rapid exit from the stress caused by mazF overexpression. Time-lapse microscopy revealed that MazF-mediated cleavage of mazF mRNA leads to increased temporal variability in length of individual cells during ectopic mazF overexpression, as explained by a stochastic model indicating that mazEF mRNA cleavage underlies temporal fluctuations in MazF levels during stress."}],"oa_version":"Published Version","issue":"6","related_material":{"record":[{"relation":"popular_science","status":"public","id":"5569"}]},"volume":46,"publication_status":"published","file":[{"access_level":"open_access","relation":"main_file","content_type":"application/pdf","file_id":"5151","checksum":"3ff4f545c27e11a4cd20ccb30778793e","creator":"system","date_updated":"2020-07-14T12:46:27Z","file_size":5027978,"date_created":"2018-12-12T10:15:30Z","file_name":"IST-2018-971-v1+1_2018_Nikoloc_Autoregulation_of.pdf"}],"language":[{"iso":"eng"}]},{"month":"02","publisher":"Institute of Science and Technology Austria","oa":1,"oa_version":"Published Version","abstract":[{"text":"Nela Nikolic, Tobias Bergmiller, Alexandra Vandervelde, Tanino G. Albanese, Lendert Gelens, and Isabella Moll (2018)\r\n“Autoregulation of mazEF expression underlies growth heterogeneity in bacterial populations” Nucleic Acids Research, doi: 10.15479/AT:ISTA:74;\r\nmicroscopy experiments by Tobias Bergmiller; image and data analysis by Nela Nikolic.","lang":"eng"}],"date_published":"2018-02-07T00:00:00Z","doi":"10.15479/AT:ISTA:74","related_material":{"record":[{"id":"438","status":"public","relation":"research_paper"}]},"date_created":"2018-12-12T12:31:35Z","license":"https://creativecommons.org/publicdomain/zero/1.0/","file":[{"checksum":"61ebb92213cfffeba3ddbaff984b81af","file_id":"5637","content_type":"application/zip","access_level":"open_access","relation":"main_file","date_created":"2018-12-12T13:04:39Z","file_name":"IST-2018-74-v1+2_15-11-05.zip","date_updated":"2020-07-14T12:47:04Z","file_size":3558703796,"creator":"system"},{"content_type":"application/zip","access_level":"open_access","relation":"main_file","file_id":"5638","checksum":"bf26649af310ef6892d68576515cde6d","date_updated":"2020-07-14T12:47:04Z","file_size":1830422606,"creator":"system","date_created":"2018-12-12T13:04:55Z","file_name":"IST-2018-74-v1+3_15-07-31.zip"},{"file_size":2140849248,"date_updated":"2020-07-14T12:47:04Z","creator":"system","file_name":"IST-2018-74-v1+4_Images_for_analysis.zip","date_created":"2018-12-12T13:05:11Z","content_type":"application/zip","relation":"main_file","access_level":"open_access","file_id":"5639","checksum":"8e46eedce06f22acb2be1a9b9d3f56bd"}],"day":"07","has_accepted_license":"1","year":"2018","datarep_id":"74","status":"public","keyword":["microscopy","microfluidics"],"type":"research_data","tmp":{"image":"/images/cc_0.png","legal_code_url":"https://creativecommons.org/publicdomain/zero/1.0/legalcode","name":"Creative Commons Public Domain Dedication (CC0 1.0)","short":"CC0 (1.0)"},"_id":"5569","title":"Time-lapse microscopy data","file_date_updated":"2020-07-14T12:47:04Z","department":[{"_id":"CaGu"}],"publist_id":"7385","author":[{"first_name":"Tobias","id":"2C471CFA-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0001-5396-4346","full_name":"Bergmiller, Tobias","last_name":"Bergmiller"},{"orcid":"0000-0001-9068-6090","full_name":"Nikolic, Nela","last_name":"Nikolic","id":"42D9CABC-F248-11E8-B48F-1D18A9856A87","first_name":"Nela"}],"article_processing_charge":"No","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","ddc":["579"],"date_updated":"2024-02-21T13:44:45Z","citation":{"mla":"Bergmiller, Tobias, and Nela Nikolic. Time-Lapse Microscopy Data. Institute of Science and Technology Austria, 2018, doi:10.15479/AT:ISTA:74.","short":"T. Bergmiller, N. Nikolic, (2018).","ieee":"T. Bergmiller and N. Nikolic, “Time-lapse microscopy data.” Institute of Science and Technology Austria, 2018.","apa":"Bergmiller, T., & Nikolic, N. (2018). Time-lapse microscopy data. Institute of Science and Technology Austria. https://doi.org/10.15479/AT:ISTA:74","ama":"Bergmiller T, Nikolic N. Time-lapse microscopy data. 2018. doi:10.15479/AT:ISTA:74","chicago":"Bergmiller, Tobias, and Nela Nikolic. “Time-Lapse Microscopy Data.” Institute of Science and Technology Austria, 2018. https://doi.org/10.15479/AT:ISTA:74.","ista":"Bergmiller T, Nikolic N. 2018. Time-lapse microscopy data, Institute of Science and Technology Austria, 10.15479/AT:ISTA:74."}},{"title":"MazF activation promotes translational heterogeneity of the grcA mRNA in Escherichia coli populations","author":[{"last_name":"Nikolic","orcid":"0000-0001-9068-6090","full_name":"Nikolic, Nela","first_name":"Nela","id":"42D9CABC-F248-11E8-B48F-1D18A9856A87"},{"full_name":"Didara, Zrinka","last_name":"Didara","first_name":"Zrinka"},{"first_name":"Isabella","full_name":"Moll, Isabella","last_name":"Moll"}],"publist_id":"7172","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","citation":{"apa":"Nikolic, N., Didara, Z., & Moll, I. (2017). MazF activation promotes translational heterogeneity of the grcA mRNA in Escherichia coli populations. PeerJ. PeerJ. https://doi.org/10.7717/peerj.3830","ama":"Nikolic N, Didara Z, Moll I. MazF activation promotes translational heterogeneity of the grcA mRNA in Escherichia coli populations. PeerJ. 2017;2017(9). doi:10.7717/peerj.3830","ieee":"N. Nikolic, Z. Didara, and I. Moll, “MazF activation promotes translational heterogeneity of the grcA mRNA in Escherichia coli populations,” PeerJ, vol. 2017, no. 9. PeerJ, 2017.","short":"N. Nikolic, Z. Didara, I. Moll, PeerJ 2017 (2017).","mla":"Nikolic, Nela, et al. “MazF Activation Promotes Translational Heterogeneity of the GrcA MRNA in Escherichia Coli Populations.” PeerJ, vol. 2017, no. 9, 3830, PeerJ, 2017, doi:10.7717/peerj.3830.","ista":"Nikolic N, Didara Z, Moll I. 2017. MazF activation promotes translational heterogeneity of the grcA mRNA in Escherichia coli populations. PeerJ. 2017(9), 3830.","chicago":"Nikolic, Nela, Zrinka Didara, and Isabella Moll. “MazF Activation Promotes Translational Heterogeneity of the GrcA MRNA in Escherichia Coli Populations.” PeerJ. PeerJ, 2017. https://doi.org/10.7717/peerj.3830."},"article_number":"3830","date_created":"2018-12-11T11:47:33Z","date_published":"2017-09-21T00:00:00Z","doi":"10.7717/peerj.3830","publication":"PeerJ","day":"21","year":"2017","has_accepted_license":"1","oa":1,"quality_controlled":"1","publisher":"PeerJ","acknowledgement":"Austrian Science Fund (FWF): M1697, P22249; Swiss National Science Foundation (SNF): 145706; European Commission;FWF Special Research Program: RNA-REG F43","file_date_updated":"2020-07-14T12:47:24Z","department":[{"_id":"CaGu"}],"ddc":["579"],"date_updated":"2021-01-12T08:06:48Z","pubrep_id":"909","status":"public","tmp":{"legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)"},"type":"journal_article","_id":"624","volume":2017,"issue":"9","language":[{"iso":"eng"}],"file":[{"file_id":"4908","checksum":"3d79ae6b6eabc90b0eaaed82ff3493b0","content_type":"application/pdf","relation":"main_file","access_level":"open_access","file_name":"IST-2017-909-v1+1_peerj-3830.pdf","date_created":"2018-12-12T10:11:51Z","file_size":682064,"date_updated":"2020-07-14T12:47:24Z","creator":"system"}],"publication_status":"published","publication_identifier":{"issn":["21678359"]},"intvolume":" 2017","month":"09","scopus_import":1,"oa_version":"Published Version","abstract":[{"text":"Bacteria adapt to adverse environmental conditions by altering gene expression patterns. Recently, a novel stress adaptation mechanism has been described that allows Escherichia coli to alter gene expression at the post-transcriptional level. The key player in this regulatory pathway is the endoribonuclease MazF, the toxin component of the toxin-antitoxin module mazEF that is triggered by various stressful conditions. In general, MazF degrades the majority of transcripts by cleaving at ACA sites, which results in the retardation of bacterial growth. Furthermore, MazF can process a small subset of mRNAs and render them leaderless by removing their ribosome binding site. MazF concomitantly modifies ribosomes, making them selective for the translation of leaderless mRNAs. In this study, we employed fluorescent reporter-systems to investigate mazEF expression during stressful conditions, and to infer consequences of the mRNA processing mediated by MazF on gene expression at the single-cell level. Our results suggest that mazEF transcription is maintained at low levels in single cells encountering adverse conditions, such as antibiotic stress or amino acid starvation. Moreover, using the grcA mRNA as a model for MazF-mediated mRNA processing, we found that MazF activation promotes heterogeneity in the grcA reporter expression, resulting in a subpopulation of cells with increased levels of GrcA reporter protein.","lang":"eng"}]},{"project":[{"grant_number":"291734","name":"International IST Postdoc Fellowship Programme","call_identifier":"FP7","_id":"25681D80-B435-11E9-9278-68D0E5697425"}],"article_number":"e1007122","title":"Cell-to-cell variation and specialization in sugar metabolism in clonal bacterial populations","author":[{"last_name":"Nikolic","orcid":"0000-0001-9068-6090","full_name":"Nikolic, Nela","first_name":"Nela","id":"42D9CABC-F248-11E8-B48F-1D18A9856A87"},{"full_name":"Schreiber, Frank","last_name":"Schreiber","first_name":"Frank"},{"full_name":"Dal Co, Alma","last_name":"Dal Co","first_name":"Alma"},{"first_name":"Daniel","last_name":"Kiviet","full_name":"Kiviet, Daniel"},{"first_name":"Tobias","id":"2C471CFA-F248-11E8-B48F-1D18A9856A87","last_name":"Bergmiller","full_name":"Bergmiller, Tobias","orcid":"0000-0001-5396-4346"},{"last_name":"Littmann","full_name":"Littmann, Sten","first_name":"Sten"},{"full_name":"Kuypers, Marcel","last_name":"Kuypers","first_name":"Marcel"},{"full_name":"Ackermann, Martin","last_name":"Ackermann","first_name":"Martin"}],"publist_id":"7275","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","citation":{"ista":"Nikolic N, Schreiber F, Dal Co A, Kiviet D, Bergmiller T, Littmann S, Kuypers M, Ackermann M. 2017. Cell-to-cell variation and specialization in sugar metabolism in clonal bacterial populations. PLoS Genetics. 13(12), e1007122.","chicago":"Nikolic, Nela, Frank Schreiber, Alma Dal Co, Daniel Kiviet, Tobias Bergmiller, Sten Littmann, Marcel Kuypers, and Martin Ackermann. “Cell-to-Cell Variation and Specialization in Sugar Metabolism in Clonal Bacterial Populations.” PLoS Genetics. Public Library of Science, 2017. https://doi.org/10.1371/journal.pgen.1007122.","ama":"Nikolic N, Schreiber F, Dal Co A, et al. Cell-to-cell variation and specialization in sugar metabolism in clonal bacterial populations. PLoS Genetics. 2017;13(12). doi:10.1371/journal.pgen.1007122","apa":"Nikolic, N., Schreiber, F., Dal Co, A., Kiviet, D., Bergmiller, T., Littmann, S., … Ackermann, M. (2017). Cell-to-cell variation and specialization in sugar metabolism in clonal bacterial populations. PLoS Genetics. Public Library of Science. https://doi.org/10.1371/journal.pgen.1007122","ieee":"N. Nikolic et al., “Cell-to-cell variation and specialization in sugar metabolism in clonal bacterial populations,” PLoS Genetics, vol. 13, no. 12. Public Library of Science, 2017.","short":"N. Nikolic, F. Schreiber, A. Dal Co, D. Kiviet, T. Bergmiller, S. Littmann, M. Kuypers, M. Ackermann, PLoS Genetics 13 (2017).","mla":"Nikolic, Nela, et al. “Cell-to-Cell Variation and Specialization in Sugar Metabolism in Clonal Bacterial Populations.” PLoS Genetics, vol. 13, no. 12, e1007122, Public Library of Science, 2017, doi:10.1371/journal.pgen.1007122."},"publisher":"Public Library of Science","quality_controlled":"1","oa":1,"date_published":"2017-12-18T00:00:00Z","doi":"10.1371/journal.pgen.1007122","date_created":"2018-12-11T11:47:04Z","day":"18","publication":"PLoS Genetics","has_accepted_license":"1","year":"2017","status":"public","pubrep_id":"959","type":"journal_article","tmp":{"legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)"},"_id":"541","file_date_updated":"2020-07-14T12:46:46Z","department":[{"_id":"CaGu"}],"ddc":["576","579"],"date_updated":"2023-02-23T14:10:34Z","month":"12","intvolume":" 13","scopus_import":1,"oa_version":"Published Version","abstract":[{"text":"While we have good understanding of bacterial metabolism at the population level, we know little about the metabolic behavior of individual cells: do single cells in clonal populations sometimes specialize on different metabolic pathways? Such metabolic specialization could be driven by stochastic gene expression and could provide individual cells with growth benefits of specialization. We measured the degree of phenotypic specialization in two parallel metabolic pathways, the assimilation of glucose and arabinose. We grew Escherichia coli in chemostats, and used isotope-labeled sugars in combination with nanometer-scale secondary ion mass spectrometry and mathematical modeling to quantify sugar assimilation at the single-cell level. We found large variation in metabolic activities between single cells, both in absolute assimilation and in the degree to which individual cells specialize in the assimilation of different sugars. Analysis of transcriptional reporters indicated that this variation was at least partially based on cell-to-cell variation in gene expression. Metabolic differences between cells in clonal populations could potentially reduce metabolic incompatibilities between different pathways, and increase the rate at which parallel reactions can be performed.","lang":"eng"}],"volume":13,"issue":"12","related_material":{"record":[{"relation":"research_data","status":"public","id":"9844"},{"relation":"research_data","id":"9845","status":"public"},{"relation":"research_data","id":"9846","status":"public"}]},"ec_funded":1,"file":[{"file_name":"IST-2018-959-v1+1_2017_Nikolic_Cell-to-cell.pdf","date_created":"2018-12-12T10:14:35Z","creator":"system","file_size":1308475,"date_updated":"2020-07-14T12:46:46Z","checksum":"22426d9382f21554bad5fa5967afcfd0","file_id":"5088","relation":"main_file","access_level":"open_access","content_type":"application/pdf"}],"language":[{"iso":"eng"}],"publication_identifier":{"issn":["15537390"]},"publication_status":"published"},{"publisher":"Public Library of Science","month":"12","abstract":[{"text":"Estimates of 13 C-arabinose and 2 H-glucose uptake from the fractions of heavy isotopes measured\tin single cells","lang":"eng"}],"oa_version":"None","related_material":{"record":[{"id":"541","status":"public","relation":"used_in_publication"}]},"date_published":"2017-12-18T00:00:00Z","doi":"10.1371/journal.pgen.1007122.s017","date_created":"2021-08-09T13:31:51Z","year":"2017","day":"18","type":"research_data_reference","status":"public","_id":"9845","author":[{"orcid":"0000-0001-9068-6090","full_name":"Nikolic, Nela","last_name":"Nikolic","first_name":"Nela","id":"42D9CABC-F248-11E8-B48F-1D18A9856A87"},{"full_name":"Schreiber, Frank","last_name":"Schreiber","first_name":"Frank"},{"full_name":"Dal Co, Alma","last_name":"Dal Co","first_name":"Alma"},{"last_name":"Kiviet","full_name":"Kiviet, Daniel","first_name":"Daniel"},{"last_name":"Bergmiller","full_name":"Bergmiller, Tobias","orcid":"0000-0001-5396-4346","first_name":"Tobias","id":"2C471CFA-F248-11E8-B48F-1D18A9856A87"},{"last_name":"Littmann","full_name":"Littmann, Sten","first_name":"Sten"},{"last_name":"Kuypers","full_name":"Kuypers, Marcel","first_name":"Marcel"},{"full_name":"Ackermann, Martin","last_name":"Ackermann","first_name":"Martin"}],"article_processing_charge":"No","department":[{"_id":"CaGu"}],"title":"Mathematical model","date_updated":"2023-02-23T12:25:04Z","citation":{"mla":"Nikolic, Nela, et al. Mathematical Model. Public Library of Science, 2017, doi:10.1371/journal.pgen.1007122.s017.","apa":"Nikolic, N., Schreiber, F., Dal Co, A., Kiviet, D., Bergmiller, T., Littmann, S., … Ackermann, M. (2017). Mathematical model. Public Library of Science. https://doi.org/10.1371/journal.pgen.1007122.s017","ama":"Nikolic N, Schreiber F, Dal Co A, et al. Mathematical model. 2017. doi:10.1371/journal.pgen.1007122.s017","ieee":"N. Nikolic et al., “Mathematical model.” Public Library of Science, 2017.","short":"N. Nikolic, F. Schreiber, A. Dal Co, D. Kiviet, T. Bergmiller, S. Littmann, M. Kuypers, M. Ackermann, (2017).","chicago":"Nikolic, Nela, Frank Schreiber, Alma Dal Co, Daniel Kiviet, Tobias Bergmiller, Sten Littmann, Marcel Kuypers, and Martin Ackermann. “Mathematical Model.” Public Library of Science, 2017. https://doi.org/10.1371/journal.pgen.1007122.s017.","ista":"Nikolic N, Schreiber F, Dal Co A, Kiviet D, Bergmiller T, Littmann S, Kuypers M, Ackermann M. 2017. Mathematical model, Public Library of Science, 10.1371/journal.pgen.1007122.s017."},"user_id":"6785fbc1-c503-11eb-8a32-93094b40e1cf"},{"publisher":"Public Library of Science","month":"12","oa_version":"Published Version","date_published":"2017-12-18T00:00:00Z","related_material":{"record":[{"relation":"used_in_publication","id":"541","status":"public"}]},"doi":"10.1371/journal.pgen.1007122.s016","date_created":"2021-08-09T13:35:17Z","year":"2017","day":"18","type":"research_data_reference","status":"public","_id":"9846","author":[{"full_name":"Nikolic, Nela","orcid":"0000-0001-9068-6090","last_name":"Nikolic","id":"42D9CABC-F248-11E8-B48F-1D18A9856A87","first_name":"Nela"},{"full_name":"Schreiber, Frank","last_name":"Schreiber","first_name":"Frank"},{"full_name":"Dal Co, Alma","last_name":"Dal Co","first_name":"Alma"},{"first_name":"Daniel","full_name":"Kiviet, Daniel","last_name":"Kiviet"},{"orcid":"0000-0001-5396-4346","full_name":"Bergmiller, Tobias","last_name":"Bergmiller","id":"2C471CFA-F248-11E8-B48F-1D18A9856A87","first_name":"Tobias"},{"last_name":"Littmann","full_name":"Littmann, Sten","first_name":"Sten"},{"last_name":"Kuypers","full_name":"Kuypers, Marcel","first_name":"Marcel"},{"first_name":"Martin","last_name":"Ackermann","full_name":"Ackermann, Martin"}],"article_processing_charge":"No","title":"Supplementary methods","department":[{"_id":"CaGu"}],"date_updated":"2023-02-23T12:25:04Z","citation":{"ista":"Nikolic N, Schreiber F, Dal Co A, Kiviet D, Bergmiller T, Littmann S, Kuypers M, Ackermann M. 2017. Supplementary methods, Public Library of Science, 10.1371/journal.pgen.1007122.s016.","chicago":"Nikolic, Nela, Frank Schreiber, Alma Dal Co, Daniel Kiviet, Tobias Bergmiller, Sten Littmann, Marcel Kuypers, and Martin Ackermann. “Supplementary Methods.” Public Library of Science, 2017. https://doi.org/10.1371/journal.pgen.1007122.s016.","apa":"Nikolic, N., Schreiber, F., Dal Co, A., Kiviet, D., Bergmiller, T., Littmann, S., … Ackermann, M. (2017). Supplementary methods. Public Library of Science. https://doi.org/10.1371/journal.pgen.1007122.s016","ama":"Nikolic N, Schreiber F, Dal Co A, et al. Supplementary methods. 2017. doi:10.1371/journal.pgen.1007122.s016","short":"N. Nikolic, F. Schreiber, A. Dal Co, D. Kiviet, T. Bergmiller, S. Littmann, M. Kuypers, M. Ackermann, (2017).","ieee":"N. Nikolic et al., “Supplementary methods.” Public Library of Science, 2017.","mla":"Nikolic, Nela, et al. Supplementary Methods. Public Library of Science, 2017, doi:10.1371/journal.pgen.1007122.s016."},"user_id":"6785fbc1-c503-11eb-8a32-93094b40e1cf"},{"oa_version":"Published Version","month":"12","publisher":"Public Library of Science","day":"18","year":"2017","related_material":{"record":[{"id":"541","status":"public","relation":"used_in_publication"}]},"doi":"10.1371/journal.pgen.1007122.s018","date_published":"2017-12-18T00:00:00Z","date_created":"2021-08-09T13:27:16Z","_id":"9844","status":"public","type":"research_data_reference","user_id":"6785fbc1-c503-11eb-8a32-93094b40e1cf","date_updated":"2023-02-23T12:25:04Z","citation":{"chicago":"Nikolic, Nela, Frank Schreiber, Alma Dal Co, Daniel Kiviet, Tobias Bergmiller, Sten Littmann, Marcel Kuypers, and Martin Ackermann. “Source Data for Figures and Tables.” Public Library of Science, 2017. https://doi.org/10.1371/journal.pgen.1007122.s018.","ista":"Nikolic N, Schreiber F, Dal Co A, Kiviet D, Bergmiller T, Littmann S, Kuypers M, Ackermann M. 2017. Source data for figures and tables, Public Library of Science, 10.1371/journal.pgen.1007122.s018.","mla":"Nikolic, Nela, et al. Source Data for Figures and Tables. Public Library of Science, 2017, doi:10.1371/journal.pgen.1007122.s018.","short":"N. Nikolic, F. Schreiber, A. Dal Co, D. Kiviet, T. Bergmiller, S. Littmann, M. Kuypers, M. Ackermann, (2017).","ieee":"N. Nikolic et al., “Source data for figures and tables.” Public Library of Science, 2017.","ama":"Nikolic N, Schreiber F, Dal Co A, et al. Source data for figures and tables. 2017. doi:10.1371/journal.pgen.1007122.s018","apa":"Nikolic, N., Schreiber, F., Dal Co, A., Kiviet, D., Bergmiller, T., Littmann, S., … Ackermann, M. (2017). Source data for figures and tables. Public Library of Science. https://doi.org/10.1371/journal.pgen.1007122.s018"},"department":[{"_id":"CaGu"}],"title":"Source data for figures and tables","author":[{"first_name":"Nela","id":"42D9CABC-F248-11E8-B48F-1D18A9856A87","full_name":"Nikolic, Nela","orcid":"0000-0001-9068-6090","last_name":"Nikolic"},{"first_name":"Frank","last_name":"Schreiber","full_name":"Schreiber, Frank"},{"full_name":"Dal Co, Alma","last_name":"Dal Co","first_name":"Alma"},{"first_name":"Daniel","full_name":"Kiviet, Daniel","last_name":"Kiviet"},{"id":"2C471CFA-F248-11E8-B48F-1D18A9856A87","first_name":"Tobias","full_name":"Bergmiller, Tobias","orcid":"0000-0001-5396-4346","last_name":"Bergmiller"},{"full_name":"Littmann, Sten","last_name":"Littmann","first_name":"Sten"},{"full_name":"Kuypers, Marcel","last_name":"Kuypers","first_name":"Marcel"},{"full_name":"Ackermann, Martin","last_name":"Ackermann","first_name":"Martin"}],"article_processing_charge":"No"}]