On the lag phase and initial decline of microbial growth curves

2007 ◽  
Vol 244 (3) ◽  
pp. 511-517 ◽  
Author(s):  
George T. Yates ◽  
Thomas Smotzer
2016 ◽  
Vol 1 (2) ◽  
pp. 63 ◽  
Author(s):  
Ji-Dong Gu

Bacterial growth is a very important piece of information in a wide range of investigation and, in most of the time the data are simply shown directly without any further processing. In a single factor investigation without comparative information to be extracted, this simple approach can be used together with other data to form a comprehensive set of results. When comparison is involved, such direct showing of bacterial growth curves without processing cannot warrant a meaningful comparison thoroughly and further processing of data is necessary. In addition, there is little, if any, quantitative data for the comparison from the display of growth curves and description of a number of curves is not a simple task, especially in a meaningful way for assimilation of the data to readers. With this in mind, I would like to remind of those who plan to show such data as growth curves for their potential publication to carry this further to generate comparative results for a much meaningful interpretation by modeling and calculation from the raw growth data over time of incubation. By calculating with existing equations, the lag phase, growth rate and the biomass can be derived from a series of growth curves for a more effective and meaningful analysis. This approach is not new, but remembrance of such available tool is more important so that research data are shown professionally and also scientifically for meaning presentation and effective assimilation.


2007 ◽  
Vol 1064 ◽  
Author(s):  
Somesree GhoshMitra ◽  
Tong Cai ◽  
Santaneel Ghosh ◽  
Arup Neogi ◽  
Zhibing Hu ◽  
...  

ABSTRACTQuantum dots (QDs) are now used extensively for labeling in biomedical research due to their unique photoluminescence behavior, involving size-tunable emission color, a narrow and symmetric emission profile and a broad excitation range [1]. Uncoated QDs made of CdTe core are toxic to cells because of release of Cd2+ ions into the cellular environment. This problem can be partially solved by encapsulating QDs with polymers, like poly(N-isopropylacrylamide) (PNIPAM) or poly(ethylene glycol) (PEG). Based on biological compatibility, fast response as well as pH, temperature and magnetic field dependent swelling properties, hydrogel nanospheres has become carriers of drugs, fluorescence labels, magnetic particles for hyperthermia applications and particles that have strong optical absorption profiles for optical excitation. The toxicity of uncoated QDs are known; however, there have been a very limited number of studies specially designed to assess thoroughly the toxicity of nanosphere encapsulated QDs against QD density and dosing level.In this work, we present preliminary studies of biological effects of a novel QD based nanomaterial system on Escherichia coli (E. coli) bacteria. Cadmium chalcogenide QDs provide the most attractive fluorescence labels in comparison with routine dyes or metal complexes. Nanospheres on the other hand are the most commonly used carriers of fluorescence labels for fluorescence detection. The integration of fluorescent QDs in nanospheres therefore provides a new generation of fluorescence markers for biological assays. Hydrogels based on PNIPAM is a well known thermoresponsive polymer that undergoes a volume phase transition across the low critical solution (LCST) [2]. Therefore, the inherent temperature-sensitive swelling properties of PNIPAM offer the potentiality to control QD density within the nanospheres. In the present work, E. coli growth was monitored as E. coli served as a representation of how cells might respond in the presence of hydrogel encapsulated QDs in their growth environment. The present work describes the successful encapsulation of CdTe QDs in PNIPAM gel network. Microgel encapsulated QDs were synthesized by first preparing PNIPAM microspheres with cystaminebisacrylamide as a crosslinker and CdTe QDs capped with a stabilizer. The CdTe QDs were bonded into PNIPAM microgels through the replacement of CdTe's stabilizer inside PNIPAM microspheres. Growth curves were generated for E. coli growing in 20 mL of LB media containing hydrogel encapsulated QD nanospheres (400 nm diameter) at relatively higher (0.5mg/mL) and lower (0.01mg/mL) concentration of solution. From the growth curves, there was no evidence at lower concentration (0.01mg/mL) that the hydrogel encapsulated QDs prevent the microbial cells from growing but at higher concentration (0.5mg/mL), microbial growth was inhibited. Transmission Electron Microscopy (TEM) was used to characterize QD size and density inside the hydrogel nanospheres. Scanning Electron Microscopy (SEM) was used to observe size and morphology of the hydrogel particles. Further investigation is going on cell growth response at different QD density and to evaluate the limiting hydrogel concentration for different QD densities.


2016 ◽  
Vol 14 (03) ◽  
pp. 1650007 ◽  
Author(s):  
Matthias Gerstgrasser ◽  
Sarah Nicholls ◽  
Michael Stout ◽  
Katherine Smart ◽  
Chris Powell ◽  
...  

Biolog phenotype microarrays (PMs) enable simultaneous, high throughput analysis of cell cultures in different environments. The output is high-density time-course data showing redox curves (approximating growth) for each experimental condition. The software provided with the Omnilog incubator/reader summarizes each time-course as a single datum, so most of the information is not used. However, the time courses can be extremely varied and often contain detailed qualitative (shape of curve) and quantitative (values of parameters) information. We present a novel, Bayesian approach to estimating parameters from Phenotype Microarray data, fitting growth models using Markov Chain Monte Carlo (MCMC) methods to enable high throughput estimation of important information, including length of lag phase, maximal “growth” rate and maximum output. We find that the Baranyi model for microbial growth is useful for fitting Biolog data. Moreover, we introduce a new growth model that allows for diauxic growth with a lag phase, which is particularly useful where Phenotype Microarrays have been applied to cells grown in complex mixtures of substrates, for example in industrial or biotechnological applications, such as worts in brewing. Our approach provides more useful information from Biolog data than existing, competing methods, and allows for valuable comparisons between data series and across different models.


2021 ◽  
Author(s):  
Milanka Radulovic ◽  
◽  
Svetlana Mitrovski

Peat is a natural substrate for growth of microorganisms because it is rich in compounds that microorganisms can use as sources of carbon, nitrogen and growth factors. Peat originating from Vlasina lake in Eastern Serbia is especially rich in organic matter. The content of humic substances (humic acid, fulvic acid and humine) is almost twice that found in other peat-rich regions of similar origin and geochemical age. Humic and fluvic acids are known to promote microbial growth. In this work, humic and fulvic acids were first extracted from Vlasina lake peat and then added to minimal medium (synthetic, low ionic strength medium). The humic substances were added separately and combined in a 1:1 ratio by mass to study their individual and combined effect on microbial growth of Escherichia coli ATCC 25922 (Gr–), Staphyloccocus aureus (Gr+) i Aureobasidium pullulans, strain CH-1. The microbial growth was measured microspectrophotometrically over a 24-hour period and growth curves were obtained for a range of acid concentrations between 25 µg cm-3 and 100 µg cm-3. It was found that both humic and fulvic acids promote the growth of all three microorganisms by up to a maximum of 40%-80% the extent of which varied with the concentration of the acid and the identity of the microorganism. In general, humic acid was found to result in higher microbial growth (at highest concentrations, up to ~80% for all three microbial species).


2019 ◽  
Vol 9 (23) ◽  
pp. 5019 ◽  
Author(s):  
Theofania Tsironi ◽  
Athina Ntzimani ◽  
Eleni Gogou ◽  
Maria Tsevdou ◽  
Ioanna Semenoglou ◽  
...  

The aim of the study was the evaluation and mathematical modeling of the effect of active modified atmosphere packaging (MAP), by the incorporation of CO2 emitters in the package, on the microbial stability and shelf life of gutted sea bass during refrigerated storage. Gutted sea bass samples were packaged in modified atmosphere (50% CO2–40% N2–10% O2) with and without CO2 emitters (ACT-MAP, MAP) (gas/product volume ratio 3:1) and stored at isothermal conditions: 0 °C, 5 °C, and 10 °C. The gas concentration in the package headspace (%CO2, %O2) and microbial growth (total viable count, TVC, Pseudomonas spp., Enterobacteriaceae spp., lactic acid bacteria) were monitored during storage. The microbial growth was modeled using the Baranyi growth model, and the kinetic parameters (microbial growth rate, lag phase) were estimated at the tested temperature and packaging conditions. The results showed that the ACT-MAP samples presented significantly lower microbial growth compared to the MAP samples. The growth rate of the total viable count at 0 °C was 0.175 and 0.138 d−1 for the MAP and ACT-MAP sea bass, respectively (p < 0.05). The shelf life of the MAP sea bass at 0–10 °C (based on a final TVC value: 7 log CFU g−1) was extended 4–7 days with the addition of a CO2 emitter in the package. The CO2 concentration in the ACT-MAP samples was stabilized at approximately 60%, while the CO2 in the MAP samples was approximately 40% at the end of the shelf life.


1983 ◽  
Vol 46 (7) ◽  
pp. 610-613 ◽  
Author(s):  
R. J. H. GRAY ◽  
D. G. HOOVER ◽  
A. M. MUIR

Four species of fish from Atlantic waters, Meronia americanus (perch), Cynoscion regalis (seatrout), Micropogon undulatis (croaker) and Pomatomus saltatrix (bluefish), were processed (gutted or filleted), packaged under carbon dioxide and refrigerated. Stability of the fish under the modified atmosphere preservation (MAP) system was compared to that of fish stored conventionally. Use of the MAP system resulted in a 45 to 55% increase in stability, primarily due to an extension in the lag phase of psychrotrophic organisms and to their reduced growth rate in the logarithmic phase. By the 10th day of storage, the conventionally packed fish always exhibited a 100-fold higher psychrotroph count than the CO2-packed fish. Levels of Vibrio parahaemolyticus were negligible in this MAP system and no Salmonella spp. or Staphylococcus aureus was detected, even at an abuse temperature (10°C) of storage. Positive evidence for preformed Clostridium botulinum toxin was lacking.


2019 ◽  
Vol 10 ◽  
Author(s):  
David C. Vuono ◽  
Bruce Lipp ◽  
Carl Staub ◽  
Evan Loney ◽  
Zoë R. Harrold ◽  
...  

2003 ◽  
Author(s):  
Johnathan J. Vadasz

Accounting for metabolic mass transfer and abiotic resource dynamics is not common in modeling microbial population growth. In this paper it is demonstrated that the latter is an essential feature that needs to be considered if reliable results are sought. The results of a model that takes the metabolic mass transfer and abiotic resource dynamics into account are shown to capture a variety of features that appear in experiments such as a Lag phase, a Logarithmic Inflection Point, growth followed by decline and oscillations. The results have a wide variety of implications and applications, from food microbiology and wine fermentation, up to human cell growth, where the latter includes tumor growth.


2019 ◽  
Vol 116 (29) ◽  
pp. 14698-14707 ◽  
Author(s):  
Yoav Ram ◽  
Eynat Dellus-Gur ◽  
Maayan Bibi ◽  
Kedar Karkare ◽  
Uri Obolski ◽  
...  

Determining the fitness of specific microbial genotypes has extensive application in microbial genetics, evolution, and biotechnology. While estimates from growth curves are simple and allow high throughput, they are inaccurate and do not account for interactions between costs and benefits accruing over different parts of a growth cycle. For this reason, pairwise competition experiments are the current “gold standard” for accurate estimation of fitness. However, competition experiments require distinct markers, making them difficult to perform between isolates derived from a common ancestor or between isolates of nonmodel organisms. In addition, competition experiments require that competing strains be grown in the same environment, so they cannot be used to infer the fitness consequence of different environmental perturbations on the same genotype. Finally, competition experiments typically consider only the end-points of a period of competition so that they do not readily provide information on the growth differences that underlie competitive ability. Here, we describe a computational approach for predicting density-dependent microbial growth in a mixed culture utilizing data from monoculture and mixed-culture growth curves. We validate this approach using 2 different experiments withEscherichia coliand demonstrate its application for estimating relative fitness. Our approach provides an effective way to predict growth and infer relative fitness in mixed cultures.


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