Author

N. Nordholt

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Microbiology· 4

Signature Assays, Organisms & Methods

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Organism:E. coli· 3 Approach:experimental assay· 2 Assay:fluorescence / live-cell microscopy· 2 Organism:human· 2 Approach:statistical model· 2 Organism:bacteria (other)· 1 Research Focus:cell signaling & trafficking· 1 Research Focus:cell type annotation· 1

Frequent Co-Authors

F. J. Bruggeman· 2 shared F. Schreiber· 2 shared J. H. van Heerden· 2 shared A. Doerr· 1 shared B. Ruehle· 1 shared D. V. Lewerenz· 1 shared H. Kempe· 1 shared K. O'Hara· 1 shared

Activity by Year

2017-2022 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 17 mutual co-author links

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2 shared papersMicrobiology

F. J. Bruggeman

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4 papers

Recent·Most cited

A fluorescently labelled quaternary ammonium compound (NBD-DDA) to study mode-of-action and resistance mechanisms in bacteria

N. Nordholt, K. O'Hara, U. Resch-Genger, M. A. T. Blaskovich, B. Ruehle, F. Schreiber

This paper develops a fluorescent QAC analog, NBD-DDA, to study antimicrobial mode-of-action and resistance mechanisms in bacteria.

bioRxiv · Jul 15, 2022Microbiology

Time-kill kinetics reveal heterogeneous tolerance to disinfectants

N. Nordholt, D. V. Lewerenz, F. Schreiber

The paper investigates how phenotypic heterogeneity affects E. coli survival after exposure to disinfectants, finding bimodal kill kinetics for some substances and unimodal for others.

bioRxiv · Jun 22, 2022Microbiology

Integrated biphasic growth rate, gene expression, and cell-size homeostasis behaviour of single B. subtilis cells

N. Nordholt, J. H. van Heerden, F. J. Bruggeman

This study quantifies growth and protein expression dynamics in single B. subtilis cells during the cell cycle, revealing biphasic behavior in growth rate and protein production that compensates for cell division disturbances.

bioRxiv · Jun 9, 2019 · PreprintMicrobiology

Statistics and simulation of growth of single bacterial cells: illustrations with B. subtilis and E. coli

J. H. van Heerden, H. Kempe, A. Doerr, T. Maarleveld, N. Nordholt, F. J. Bruggeman

The paper uses statistical theory and real-time imaging data to predict single-cell growth characteristics and develops a simulation algorithm to reduce computational burden.

bioRxiv · Jun 29, 2017Microbiology