Plant-Microbial Interactions and Smart Agricultural Biotechnology

2021 ◽  
Author(s):  
Swati Tyagi ◽  
Robin Kumar ◽  
Baljeet Singh Saharan ◽  
Ashok Kumar Nadda
2020 ◽  
Vol 48 (2) ◽  
pp. 399-409
Author(s):  
Baizhen Gao ◽  
Rushant Sabnis ◽  
Tommaso Costantini ◽  
Robert Jinkerson ◽  
Qing Sun

Microbial communities drive diverse processes that impact nearly everything on this planet, from global biogeochemical cycles to human health. Harnessing the power of these microorganisms could provide solutions to many of the challenges that face society. However, naturally occurring microbial communities are not optimized for anthropogenic use. An emerging area of research is focusing on engineering synthetic microbial communities to carry out predefined functions. Microbial community engineers are applying design principles like top-down and bottom-up approaches to create synthetic microbial communities having a myriad of real-life applications in health care, disease prevention, and environmental remediation. Multiple genetic engineering tools and delivery approaches can be used to ‘knock-in' new gene functions into microbial communities. A systematic study of the microbial interactions, community assembling principles, and engineering tools are necessary for us to understand the microbial community and to better utilize them. Continued analysis and effort are required to further the current and potential applications of synthetic microbial communities.


2019 ◽  
Author(s):  
Jihyun Kim ◽  
◽  
Chandler Noyes ◽  
Ambria Dell'Oro ◽  
Rebecca Tyne ◽  
...  

2019 ◽  
Vol 38 (4) ◽  
pp. 251-264 ◽  
Author(s):  
Jason M. Koontz ◽  
Blair C. R. Dancy ◽  
Cassandra L. Horton ◽  
Jonathan D. Stallings ◽  
Valerie T. DiVito ◽  
...  

There is overwhelming evidence that the microbiome must be considered when evaluating the toxicity of chemicals. Disruption of the normal microbial flora is a known effect of toxic exposure, and these disruptions may lead to human health effects. In addition, the biotransformation of numerous compounds has been shown to be dependent on microbial enzymes, with the potential for different host health outcomes resulting from variations in the microbiome. Evidence suggests that such metabolism of environmental chemicals by enzymes from the host's microbiota can affect the toxicity of that chemical to the host. Chemical-microbial interactions can be categorized into two classes: Microbiome Modulation of Toxicity (MMT) and Toxicant Modulation of the Microbiome (TMM). MMT refers to transformation of a chemical by microbial enzymes or metabolites to modify the chemical in a way that makes it more or less toxic. TMM is a change in the microbiota that results from a chemical exposure. These changes span a large magnitude of effects and may vary from microbial gene regulation, to inhibition of a specific enzyme, to the death of the microbes. Certain microbiomes or microbiota may become associated with different health outcomes, such as resistance or susceptibility to exposure to certain toxic chemicals, the ability to recover following a chemical-induced injury, the presence of disease-associated phenotypes, and the effectiveness of immune responses. Future work in toxicology will require an understanding of how the microbiome interacts with toxicants to fully elucidate how a compound will affect a diverse, real-world population.


2008 ◽  
Vol 25 (No. 5) ◽  
pp. 272-282 ◽  
Author(s):  
D. Liptáková ◽  
Ľ. Valík ◽  
A. Lauková ◽  
V. Strompfová

The combined effect of initial amount of 18 h <i>L. rhamnosus</i> VT1 inoculum and incubation temperature on the growth of <i>Candida maltosa</i> YP1, an oxidative food spoilage yeast strain, was primarily modelled and studied by standard response surface methodology. This study resulted in the following linear regression equations characterising lag time and growth rate of <i>C. maltosa</i> YP1 in milk in competition with the potentially protective lactobacillus strain. Lag-phase of <i>C. maltosa</i> was strongly influenced by the amount of lactobacillus inoculum (<i>V</i><sub>0</sub>) and incubation temperature (1/<i>T</i>). The synergic effect of both these factors was also evident as results from the equation lag = –33.50 + 186.38 × <i>V</i><sub>0</sub> × 1/<i>T</i> + 512.27 × 1/<i>T</i> – 5.511 × <i>V</i><sub>0</sub> (<i>R</i><sup>2</sup><sub>(λ)</sub> = 0.849). The growth rate was sufficiently described by the linear relation: <i>Gr</i><sub>Cm</sub> = –0.00046 + 0.0033 × <i>T</i> – 0.0016 × <i>V</i><sub>0 (<i>R</i><sup>2</sup><sub>(Gr)</sub> = 0.847). On the basis of these equations, the mutual microbial interactions and the potential application of the lactobacillus strains to food protection are discussed.


Marine Drugs ◽  
2021 ◽  
Vol 19 (8) ◽  
pp. 424
Author(s):  
Osama G. Mohamed ◽  
Sadaf Dorandish ◽  
Rebecca Lindow ◽  
Megan Steltz ◽  
Ifrah Shoukat ◽  
...  

The antibiotic-resistant bacteria-associated infections are a major global healthcare threat. New classes of antimicrobial compounds are urgently needed as the frequency of infections caused by multidrug-resistant microbes continues to rise. Recent metagenomic data have demonstrated that there is still biosynthetic potential encoded in but transcriptionally silent in cultivatable bacterial genomes. However, the culture conditions required to identify and express silent biosynthetic gene clusters that yield natural products with antimicrobial activity are largely unknown. Here, we describe a new antibiotic discovery scheme, dubbed the modified crowded plate technique (mCPT), that utilizes complex microbial interactions to elicit antimicrobial production from otherwise silent biosynthetic gene clusters. Using the mCPT as part of the antibiotic crowdsourcing educational program Tiny Earth®, we isolated over 1400 antibiotic-producing microbes, including 62, showing activity against multidrug-resistant pathogens. The natural product extracts generated from six microbial isolates showed potent activity against vancomycin-intermediate resistant Staphylococcus aureus. We utilized a targeted approach that coupled mass spectrometry data with bioactivity, yielding a new macrolactone class of metabolite, desertomycin H. In this study, we successfully demonstrate a concept that significantly increased our ability to quickly and efficiently identify microbes capable of the silent antibiotic production.


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