scholarly journals HU content and dynamics in Escherichia coli during the cell cycle and at different growth rates

2017 ◽  
Vol 364 (19) ◽  
Author(s):  
Anteneh Hailu Abebe ◽  
Alexander Aranovich ◽  
Itzhak Fishov
Keyword(s):  
Escherichia Coli ◽  
Cell Cycle ◽  
Growth Rates

Adaptation of Escherichia coli growth rates to the presence of pBR322

1993 ◽  
Vol 17 (3) ◽  
pp. 139-143 ◽  
Author(s):  
P. J. McDermott ◽  
Pauline Gowland ◽  
P. C. Gowland
Keyword(s):  
Escherichia Coli ◽  
Growth Rates ◽  
Coli Growth

Evaluation of genomic sequence-based growth rate methods for synchronized Synechococcus cultures

2021 ◽  
Author(s):  
Julia Carroll ◽  
Nicolas Van Oostende ◽  
Bess B. Ward
Keyword(s):  
Cell Cycle ◽  
Growth Rate ◽  
Dna Replication ◽  
Growth Rates ◽  
Genomic Sequence ◽  
Niche Differentiation ◽  
Trophic Levels ◽  
Individual Species ◽  
Cell Counts

Standard methods for calculating microbial growth rates (μ) through the use of proxies, such as in situ fluorescence, cell cycle, or cell counts, are critical for determining the magnitude of the role bacteria play in marine carbon (C) and nitrogen (N) cycles. Taxon-specific growth rates in mixed assemblages would be useful for attributing biogeochemical processes to individual species and understanding niche differentiation among related clades, such as found in Synechococcus and Prochlorococcus . We tested three novel DNA sequencing-based methods (iRep, bPTR, and GRiD) for evaluating growth of light synchronized Synechococcus cultures under different light intensities and temperatures. In vivo fluorescence and cell cycle analysis were used to obtain standard estimates of growth rate for comparison with the sequence-based methods (SBM). None of the SBM values were correlated with growth rates calculated by standard techniques despite the fact that all three SBM were correlated with percentage of cells in S phase (DNA replication) over the diel cycle. Inaccuracy in determining the time of maximum DNA replication is unlikely to account entirely for the absence of relationship between SBM and growth rate, but the fact that most microbes in the surface ocean exhibit some degree of diel cyclicity is a caution for application of these methods. SBM correlate with DNA replication but cannot be interpreted quantitatively in terms of growth rate. Importance Small but abundant, cyanobacterial strains such as the photosynthetic Synechococcus spp. are essential because they contribute significantly to primary productivity in the ocean. These bacteria generate oxygen and provide biologically-available carbon, which is essential for organisms at higher trophic levels. The small size and diversity of natural microbial assemblages means that taxon-specific activities (e.g., growth rate) are difficult to obtain in the field. It has been suggested that sequence-based methods (SBM) may be able to solve this problem. We find, however, that SBM can detect DNA replication and are correlated with phases of the cell cycle but cannot be interpreted in terms of absolute growth rate for Synechococcus cultures growing under a day-night cycle, like that experienced in the ocean.

scholarly journals The effect of desferrioxamine on transferrin receptors, the cell cycle and growth rates of human leukaemic cells

1986 ◽  
Vol 236 (1) ◽  
pp. 243-249 ◽  
Author(s):  
A Bomford ◽  
J Isaac ◽  
S Roberts ◽  
A Edwards ◽  
S Young ◽  
...  
Keyword(s):  
Cell Cycle ◽  
Growth Rates ◽  
Iron Chelator ◽  
Scatchard Analysis ◽  
Transferrin Receptors ◽  
Dependent Inhibition ◽  
Leukaemic Cells ◽  
Dose Dependent Inhibition ◽  
And Control ◽  
Initial Binding

The effect of the iron chelator, desferrioxamine, on transferrin binding, growth rates and the cell cycle was investigated in the human leukaemic cell line, K562. At all concentrations of the chelator (2-50 microM) binding of 125I-transferrin was increased by 24 h and reached a maximum at 72-96 h. Maximum binding (6-8-fold increased) occurred in cells treated with 20 microM-desferrioxamine, in contrast with control cells which, at 96 h, showed a 50% decrease over initial binding. Scatchard analysis at 4 degrees C showed that this increased binding was due to an increase in the number of receptors, as the Kd was similar in induced (1.8 nM) and control (1.5 nM) cells. After 96 h cells, cultured with 20 and 50 microM-desferrioxamine accumulated 59Fe from bovine transferrin at over twice the rate found with control cells, reflecting the increase in transferrin receptors. Although iron uptake was unimpaired by the chelator there was a dose-dependent inhibition of cell growth, with control cells completing three divisions in 96 h and those in 10 microM-desferrioxamine only two divisions. At the highest concentration (50 microM), cell division was abrogated although cell viability was maintained (85%). In contrast, DNA synthesis was not markedly affected, except at 50 microM-desferrioxamine when incorporation of [3H]thymidine was 52% of that in control cells. Flow cytometry revealed that there was a progressive accumulation of the cells in the active phases of their cycle (S, G2 + M). Desferrioxamine may increase transferrin receptors in two ways: by chelating a regulatory pool of iron within the cell, and by arresting cells in S phase when receptors are maximally expressed.

scholarly journals Escherichia colipopulations adapt to complex, unpredictable fluctuations without any trade-offs across environments

2016 ◽  
Author(s):  
Shraddha Karve ◽  
Devika Bhave ◽  
Dhanashri Nevgi ◽  
Sutirth Dey
Keyword(s):  
Escherichia Coli ◽  
Growth Rate ◽  
Growth Rates ◽  
Complex Environments ◽  
Multiple Stresses ◽  
Trade Off ◽  
Trade Offs ◽  
Fluctuating Environments ◽  
Laboratory Populations ◽  
Lower Variation

AbstractIn nature, organisms are simultaneously exposed to multiple stresses (i.e. complex environments) that often fluctuate unpredictably. While both these factors have been studied in isolation, the interaction of the two remains poorly explored. To address this issue, we selected laboratory populations ofEscherichia coliunder complex (i.e. stressful combinations of pH, H2O2and NaCl) unpredictably fluctuating environments for ~900 generations. We compared the growth rates and the corresponding trade-off patterns of these populations to those that were selected under constant values of the component stresses (i.e. pH, H2O2and NaCl) for the same duration. The fluctuation-selected populations had greater mean growth rate and lower variation for growth rate over all the selection environments experienced. However, while the populations selected under constant stresses experienced severe tradeoffs in many of the environments other than those in which they were selected, the fluctuation-selected populations could by-pass the across-environment trade-offs completely. Interestingly, trade-offs were found between growth rates and carrying capacities. The results suggest that complexity and fluctuations can strongly affect the underlying trade-off structure in evolving populations.

scholarly journals Lipid synthesis during the Escherichia coli cell cycle.

1981 ◽  
Vol 145 (1) ◽  
pp. 472-478 ◽  
Author(s):  
C E Carty ◽  
L O Ingram
Keyword(s):  
Escherichia Coli ◽  
Cell Cycle ◽  
Lipid Synthesis ◽  
Coli Cell

Regulation of the start of DNA replication in Schizosaccharomyces pombe

1999 ◽  
Vol 112 (6) ◽  
pp. 939-946 ◽  
Author(s):  
C.R. Carlson ◽  
B. Grallert ◽  
T. Stokke ◽  
E. Boye
Keyword(s):  
Cell Cycle ◽  
Flow Cytometry ◽  
Growth Rate ◽  
Schizosaccharomyces Pombe ◽  
Growth Rates ◽  
Cell Separation ◽  
Cell Mass ◽  
Nitrogen Sources ◽  
S Phase ◽  
G1 Phase

Cells of Schizosaccharomyces pombe were grown in minimal medium with different nitrogen sources under steady-state conditions, with doubling times ranging from 2.5 to 14 hours. Flow cytometry and fluorescence microscopy confirmed earlier findings that at rapid growth rates, the G1 phase was short and cell separation occurred at the end of S phase. For some nitrogen sources, the growth rate was greatly decreased, the G1 phase occupied 30–50% of the cell cycle, and cell separation occurred in early G1. In contrast, other nitrogen sources supported low growth rates without any significant increase in G1 duration. The method described allows manipulation of the length of G1 and the relative cell cycle position of S phase in wild-type cells. Cell mass was measured by flow cytometry as scattered light and as protein-associated fluorescence. The extensions of G1 were not related to cell mass at entry into S phase. Our data do not support the hypothesis that the cells must reach a certain fixed, critical mass before entry into S. We suggest that cell mass at the G1/S transition point is variable and determined by a set of molecular parameters. In the present experiments, these parameters were influenced by the different nitrogen sources in a way that was independent of the actual growth rate.

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