Microbial growth rates in nature.

1971 ◽  
Vol 35 (1) ◽  
pp. 39-58 ◽  
Author(s):  
T D Brock
2015 ◽  
Vol 81 (17) ◽  
pp. 5662-5670 ◽  
Author(s):  
Onur Ercan ◽  
Markus M. M. Bisschops ◽  
Wout Overkamp ◽  
Thomas R. Jørgensen ◽  
Arthur F. Ram ◽  
...  

ABSTRACTThe current knowledge of the physiology and gene expression of industrially relevant microorganisms is largely based on laboratory studies under conditions of rapid growth and high metabolic activity. However, in natural ecosystems and industrial processes, microbes frequently encounter severe calorie restriction. As a consequence, microbial growth rates in such settings can be extremely slow and even approach zero. Furthermore, uncoupling microbial growth from product formation, while cellular integrity and activity are maintained, offers perspectives that are economically highly interesting. Retentostat cultures have been employed to investigate microbial physiology at (near-)zero growth rates. This minireview compares information from recent physiological and gene expression studies on retentostat cultures of the industrially relevant microorganismsLactobacillus plantarum,Lactococcus lactis,Bacillus subtilis,Saccharomyces cerevisiae, andAspergillus niger. Shared responses of these organisms to (near-)zero growth rates include increased stress tolerance and a downregulation of genes involved in protein synthesis. Other adaptations, such as changes in morphology and (secondary) metabolite production, were species specific. This comparison underlines the industrial and scientific significance of further research on microbial (near-)zero growth physiology.


1971 ◽  
Vol 35 (1) ◽  
pp. 39-58
Author(s):  
T D Brock

1993 ◽  
Vol 76 (3) ◽  
pp. 682-690 ◽  
Author(s):  
Ellen M Anderson ◽  
Gerald N Angyal ◽  
Carol M Weaver ◽  
I Cecil Felkner ◽  
Wayne R Wolf ◽  
...  

Abstract A microbiological technique was developed for quantitating niacin by determining microbial growth rates in response to the amount of vitamin available. Unlike the current official AOAC method, the new procedure for niacin measured the growth rates during the early exponential growth phase rather than during the stationary phase. Lactobacillus plantarum was used to determine niacin to a lower limit of 100 pg/mL. The assay time was approximately 6 h, compared with 16-24 h for the current AOAC method. The extent of microbial growth was determined by differential light scattering of a LASER beam. Multiple photodetectors were integrated with a computer system to collect and analyze the data. The use of differential light scattering to determine 8 water-soluble vitamins under stationary phase conditions demonstrated the potential application of the new technology for microorganisms and foods.


1985 ◽  
Vol 18 (5) ◽  
pp. 1161-1166 ◽  
Author(s):  
G. Bastin ◽  
D. Dochain

2019 ◽  
Author(s):  
Andrew M. Long ◽  
Shengwei Hou ◽  
J. Cesar Ignacio-Espinoza ◽  
Jed A. Fuhrman

AbstractGrowth rates are fundamental to all organisms and essential for characterizing microbial ecologies. Despite this, we do not know the instantaneous nor maximum growth rates of most naturally-occurring microorganisms. Recent reports indicate DNA replication rates can be estimated from metagenomic coverage, and maximum growth rates can be estimated from genomic characteristics. We tested these approaches with native marine bacteria (<0.6 um size fraction) as 10% inoculum grown in unamended virus-free seawater from the San Pedro Channel, California. This allowed microbial growth without grazing and with greatly reduced viral infection. At multiple time points up to 48 h, we sampled for cell abundances and metagenomic analyses. We generated 101 unique Metagenome-assembled genomes (MAGs) including α, β, and γ Proteobacteria, Flavobacteria, Actinobacteria, Verrucomicrobia, Marine Group A/SAR406, MGII archaea, and others. We tracked the growth of each as the fraction of total metagenomic reads mapped to each MAG normalized with length, completeness, and total cell counts. Some MAGs did not grow appreciably, but those we could estimate had growth rates ranging from 0.08 to 5.99 d−1; these are the first reported growth rates for several of the groups. These metagenome-determined growth rates, which often changed within experiments, were compared to (a) DNA replication estimates from the ‘peak-to-trough’ ratio (PTR) as determined by three different approaches, and (b) maximum growth rates predicted from codon usage bias (CUB). For the large majority of taxa, observed growth rates were not correlated to PTR indices (r ~ −0.26 - 0.08), with exceptions being rapidly growing Oceanospirillales and Saccharospirillaceae (r ~ 0.63 - 0.92). However, CUB was moderately well correlated to observed maximum growth rates (r = 0.57). This suggests that maximum growth rates can be reasonably well-estimated from genomic information alone, but current PTR approaches poorly predict actual growth of most marine planktonic bacteria in unamended seawater.


2022 ◽  
pp. gr.275533.121
Author(s):  
Tyler A Joseph ◽  
Philippe Chlenski ◽  
Aviya Litman ◽  
Tal Korem ◽  
Itsik Pe'er

Patterns of sequencing coverage along a bacterial genome---summarized by a peak-to-trough ratio (PTR)---have been shown to accurately reflect microbial growth rates, revealing a new facet of microbial dynamics and host-microbe interactions. Here, we introduce CoPTR (Compute PTR): a tool for computing PTRs from complete reference genomes and assemblies. Using simulations and data from growth experiments in simple and complex communities, we show that CoPTR is more accurate than the current state-of-the-art, while also providing more PTR estimates overall. We further develop theory formalizing a biological interpretation for PTRs. Using a reference database of 2935 species, we applied CoPTR to a case-control study of 1304 metagenomic samples from 106 individuals with inflammatory bowel disease. We show that growth rates are personalized, are only loosely correlated with relative abundances, and are associated with disease status. We conclude by demonstrating how PTRs can be combined with relative abundances and metabolomics to investigate their effect on the microbiome.


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