Significance The human microbiota represents the trillions of bacteria that live on the skin, in the oral, nasal, and aural cavities, and throughout the gastrointestinal tract. The species that live in the gastrointestinal tract, the gut microbiota, closely interact with host cells and have a profound impact on health. To develop tools to effectively monitor the gut microbiota and ultimately help in disease diagnosis, we have engineered Escherichia coli to sense and record environmental stimuli, and demonstrated that E. coli with such memory systems can survive and function in the mammalian gut. This work demonstrates that E. coli can be engineered into living diagnostics capable of nondestructively probing the mammalian gut.

Whole-genome knockout collections are invaluable for connecting gene sequence to function, yet traditionally, their construction has required an extraordinary technical effort. Here we report a method for the construction and purification of a curated whole-genome collection of single-gene transposon disruption mutants termed Knockout Sudoku. Using simple combinatorial pooling, a highly oversampled collection of mutants is condensed into a next-generation sequencing library in a single day, a 30- to 100-fold improvement over prior methods. The identities of the mutants in the collection are then solved by a probabilistic algorithm that uses internal self-consistency within the sequencing data set, followed by rapid algorithmically guided condensation to a minimal representative set of mutants, validation, and curation. Starting from a progenitor collection of 39,918 mutants, we compile a quality-controlled knockout collection of the electroactive microbe Shewanella oneidensis MR-1 containing representatives for 3,667 genes that is functionally validated by high-throughput kinetic measurements of quinone reduction.

Glioblastoma multiforme (GBM) is a serious form of brain cancer for which there is currently no effective treatment. Alternative strategies such as adeno-associated virus (AAV) vector mediated-genetic modification of brain tumor cells with genes encoding anti-tumor proteins have shown promising results in preclinical models of GBM, although the transduction efficiency of these tumors is often low. As higher transduction efficiency of tumor cells should lead to enhanced therapeutic efficacy, a means to rapidly engineer AAV vectors with improved transduction efficiency for individual tumors is an attractive strategy. Here we tested the possibility of identifying high-efficiency AAV vectors for human U87 glioma cells by selection in culture of a newly constructed chimeric AAV capsid library generated by DNA shuffling of six different AAV cap genes (AAV1, AAV2, AAV5, AAVrh.8, AAV9, and AAVrh.10). After seven rounds of selection, we obtained a chimeric AAV capsid that transduces U87 cells at high efficiency (97% at a dose of 104 genome copies/cell), and at low doses it was 1.45–1.6-fold better than AAV2, which proved to be the most efficient parental capsid. Interestingly, the new AAV capsid displayed robust gene delivery properties to all glioma cells tested (including primary glioma cells) with relative fluorescence indices ranging from 1- to 14-fold higher than AAV2. The selected vector should be useful for in vitro glioma research when efficient transduction of several cell lines is required, and provides proof-of-concept that an AAV library can be used to generate AAV vectors with enhanced transduction efficiency of glioma cells.

Knockout Sudoku is a method for the construction of whole-genome knockout collections for a wide range of microorganisms with as little as 3 weeks of dedicated labor and at a cost of ∼$10,000 for a collection for a single organism. The method uses manual 4D combinatorial pooling, next-generation sequencing, and a Bayesian inference algorithm to rapidly process and then accurately annotate the extremely large progenitor transposon insertion mutant collections needed to achieve saturating coverage of complex microbial genomes. This method is ∼100× faster and 30× lower in cost than the next comparable method (In-seq) for annotating transposon mutant collections by combinatorial pooling and next-generation sequencing. This method facilitates the rapid, algorithmically guided condensation and curation of the progenitor collection into a high-quality, nonredundant collection that is suitable for rapid genetic screening and gene discovery.