Essential Genes Predicted in the Genome of Rubrivivax gelatinosus

Adenosine-Monophosphate-Assisted Homogeneous Silica Coating of Silver Nanoparticles in High Yield

In this study, we propose a novel approach for the silica coating of silver nanoparticles based on surface modification with adenosine monophosphate (AMP). Upon AMP stabilization, the nanoparticles can be transferred into 2-propanol, promoting the growth of silica on the particle surfaces through the standard Stöber process. The obtained silica shells are uniform and homogeneous, and the method allows a high degree of control over shell thickness while minimizing the presence of uncoated NPs or the negligible presence of core-free silica NPs. In addition, AMP-functionalized AgNPs could be also coated with a mesoporous silica shell using cetyltrimethylammonium chloride (CTAC) as a template. Interestingly, the thickness of the mesoporous silica coating could be tightly adjusted by either the silica precursor concentration or by varying the CTAC concentration while keeping the silica precursor concentration constant. Finally, the influence of the silica coating on the antimicrobial effect of AgNPs was studied on Gram-negative bacteria (R. gelatinosus and E. coli) and under different bacterial growth conditions, shedding light on their potential applications in different biological environments.

Approaches to genetic tool development for rapid domestication of non-model microorganisms

Non-model microorganisms often possess complex phenotypes that could be important for the future of biofuel and chemical production. They have received significant interest the last several years, but advancement is still slow due to the lack of a robust genetic toolbox in most organisms. Typically, "domestication" of a new non-model microorganism has been done on an ad hoc basis, and historically, it can take years to develop transformation and basic genetic tools. Here, we review the barriers and solutions to rapid development of genetic transformation tools in new hosts, with a major focus on Restriction-Modification systems, which are a well-known and significant barrier to efficient transformation. We further explore the tools and approaches used for efficient gene deletion, DNA insertion, and heterologous gene expression. Finally, more advanced and high-throughput tools are now being developed in diverse non-model microbes, paving the way for rapid and multiplexed genome engineering for biotechnology.

Diversity of Chlorophototrophic Bacteria Revealed in the Omics Era

Because of recent advances in omics methodologies, knowledge of chlorophototrophy (i.e., chlorophyll-based phototrophy) in bacteria has rapidly increased. Chlorophototrophs currently are known to occur in seven bacterial phyla: Cyanobacteria, Proteobacteria, Chlorobi, Chloroflexi, Firmicutes, Acidobacteria, and Gemmatimonadetes. Other organisms that can produce chlorophylls and photochemical reaction centers may still be undiscovered. Here we summarize the current status of the taxonomy and phylogeny of chlorophototrophic bacteria as revealed by genomic methods. In specific cases, we briefly describe important ecophysiological and metabolic insights that have been gained from the application of genomic methods to these bacteria. In the 20 years since the completion of the Synechocystis sp. PCC 6803 genome in 1996, approximately 1,100 genomes have been sequenced, which represents nearly the complete diversity of known chlorophototrophic bacteria. These data are leading to new insights into many important processes, including photosynthesis, nitrogen and carbon fixation, cellular differentiation and development, symbiosis, and ecosystem functionality.

Combining Genome-Scale Experimental and Computational Methods To Identify Essential Genes in Rhodobacter sphaeroides

Knowledge about the role of genes under a particular growth condition is required for a holistic understanding of a bacterial cell and has implications for health, agriculture, and biotechnology. We developed the Tn-seq analysis software (TSAS) package to provide a flexible and statistically rigorous workflow for the high-throughput analysis of insertion mutant libraries, advanced the knowledge of gene essentiality in R. sphaeroides, and illustrated how Tn-seq data can be used to more accurately identify genes that play important roles in metabolism and other processes that are essential for cellular survival.

Rhodobacter sphaeroides is one of the best-studied alphaproteobacteria from biochemical, genetic, and genomic perspectives. To gain a better systems-level understanding of this organism, we generated a large transposon mutant library and used transposon sequencing (Tn-seq) to identify genes that are essential under several growth conditions. Using newly developed Tn-seq analysis software (TSAS), we identified 493 genes as essential for aerobic growth on a rich medium. We then used the mutant library to identify conditionally essential genes under two laboratory growth conditions, identifying 85 additional genes required for aerobic growth in a minimal medium and 31 additional genes required for photosynthetic growth. In all instances, our analyses confirmed essentiality for many known genes and identified genes not previously considered to be essential. We used the resulting Tn-seq data to refine and improve a genome-scale metabolic network model (GEM) for R. sphaeroides. Together, we demonstrate how genetic, genomic, and computational approaches can be combined to obtain a systems-level understanding of the genetic framework underlying metabolic diversity in bacterial species.

IMPORTANCE Knowledge about the role of genes under a particular growth condition is required for a holistic understanding of a bacterial cell and has implications for health, agriculture, and biotechnology. We developed the Tn-seq analysis software (TSAS) package to provide a flexible and statistically rigorous workflow for the high-throughput analysis of insertion mutant libraries, advanced the knowledge of gene essentiality in R. sphaeroides, and illustrated how Tn-seq data can be used to more accurately identify genes that play important roles in metabolism and other processes that are essential for cellular survival.

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