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1.
mBio ; 14(5): e0184323, 2023 Oct 31.
Article in English | MEDLINE | ID: mdl-37791787

ABSTRACT

IMPORTANCE: S. elongatus is an important cyanobacterial model organism for the study of its prokaryotic circadian clock, photosynthesis, and other biological processes. It is also widely used for genetic engineering to produce renewable biochemicals. Our findings reveal an SeAgo-based defense mechanism in S. elongatus against the horizontal transfer of genetic material. We demonstrate that deletion of the ago gene facilitates genetic studies and genetic engineering of S. elongatus.


Subject(s)
Circadian Clocks , Synechococcus , Synechococcus/genetics , Plasmids/genetics , Genetic Engineering , Bacterial Proteins/genetics
2.
Nat Biotechnol ; 41(10): 1424-1433, 2023 Oct.
Article in English | MEDLINE | ID: mdl-36805559

ABSTRACT

Pure bacterial cultures remain essential for detailed experimental and mechanistic studies in microbiome research, and traditional methods to isolate individual bacteria from complex microbial ecosystems are labor-intensive, difficult-to-scale and lack phenotype-genotype integration. Here we describe an open-source high-throughput robotic strain isolation platform for the rapid generation of isolates on demand. We develop a machine learning approach that leverages colony morphology and genomic data to maximize the diversity of microbes isolated and enable targeted picking of specific genera. Application of this platform on fecal samples from 20 humans yields personalized gut microbiome biobanks totaling 26,997 isolates that represented >80% of all abundant taxa. Spatial analysis on >100,000 visually captured colonies reveals cogrowth patterns between Ruminococcaceae, Bacteroidaceae, Coriobacteriaceae and Bifidobacteriaceae families that suggest important microbial interactions. Comparative analysis of 1,197 high-quality genomes from these biobanks shows interesting intra- and interpersonal strain evolution, selection and horizontal gene transfer. This culturomics framework should empower new research efforts to systematize the collection and quantitative analysis of imaging-based phenotypes with high-resolution genomics data for many emerging microbiome studies.


Subject(s)
Genomics , Microbiota , Humans , Genomics/methods , Microbiota/genetics , Bacteria , Automation , Machine Learning
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