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ABSTRACT Mechanistic understanding of interactions in many host-microbe systems, including the honey bee microbiome, is limited by a lack of easy-to-use genome engineering approaches. To this end, we demonstrate a one-step genome engineering approach for making gene deletions and insertions in the chromosomes of honey bee gut bacterial symbionts. Electroporation of linear or non-replicating plasmid DNA containing an antibiotic resistance cassette flanked by regions with homology to a symbiont genome reliably results in chromosomal integration. This lightweight approach does not require expressing any exogenous recombination machinery. The high concentrations of large DNAs with long homology regions needed to make the process efficient can be readily produced using modern DNA synthesis and assembly methods. We use this approach to knock out genes, including genes involved in biofilm formation, and insert fluorescent protein genes into the chromosome of the betaproteobacterial bee gut symbiontSnodgrassella alvi. We are also able to engineer the genomes of multiple strains ofS. alviand another species,Snodgrassella communis, which is found in the bumble bee gut microbiome. Finally, we use the same method to engineer the chromosome of another bee symbiont,Bartonella apis, which is an alphaproteobacterium. As expected, gene knockout inS. alviusing this approach isrecA-dependent, suggesting that this straightforward procedure can be applied to other microbes that lack convenient genome engineering methods. IMPORTANCEHoney bees are ecologically and economically important crop pollinators with bacterial gut symbionts that influence their health. Microbiome-based strategies for studying or improving bee health have utilized wild-type or plasmid-engineered bacteria. We demonstrate that a straightforward, single-step method can be used to insert cassettes and replace genes in the chromosomes of multiple bee gut bacteria. This method can be used for investigating the mechanisms of host-microbe interactions in the bee gut community and stably engineering symbionts that benefit pollinator health. 

Abstract Foundational techniques in molecular biology—such as cloning genes, tagging biomolecules for purification or identification, and overexpressing recombinant proteins—rely on introducing non-native or synthetic DNA sequences into organisms. These sequences may be recognized by the transcription and translation machinery in their new context in unintended ways. The cryptic gene expression that sometimes results has been shown to produce genetic instability and mask experimental signals. Computational tools have been developed to predict individual types of gene expression elements, but it can be difficult for researchers to contextualize their collective output. Here, we introduce CryptKeeper, a software pipeline that visualizes predictions of Escherichia coli gene expression signals and estimates the translational burden possible from a DNA sequence. We investigate several published examples where cryptic gene expression in E. coli interfered with experiments. CryptKeeper accurately postdicts unwanted gene expression from both eukaryotic virus infectious clones and individual proteins that led to genetic instability. It also identifies off-target gene expression elements that resulted in truncations that confounded protein purification. Incorporating negative design using CryptKeeper into reverse genetics and synthetic biology workflows can help to mitigate cloning challenges and avoid unexplained failures and complications that arise from unintentional gene expression. 

Abstract Engineered DNA will slow the growth of a host cell if it redirects limiting resources or otherwise interferes with homeostasis. Escape mutants that alleviate this burden can rapidly evolve and take over cell populations, making genetic engineering less reliable and predictable. Synthetic biologists often use genetic parts encoded on plasmids, but their burden is rarely characterized. We measured how 301 BioBrick plasmids affectedEscherichia coligrowth and found that 59 (19.6%) were burdensome, primarily because they depleted the limited gene expression resources of host cells. Overall, no BioBricks reduced the growth rate ofE. coliby >45%, which agreed with a population genetic model that predicts such plasmids should be unclonable. We made this model available online for education (https://barricklab.org/burden-model) and added our burden measurements to the iGEM Registry. Our results establish a fundamental limit on what DNA constructs and genetic modifications can be successfully engineered into cells. 

CRISPR-associated transposons (CASTs) are RNA-guided mobile genetic elements that are widespread in bacterial genomes. Here, we describe the UltraCAST, a suicide vector with the Vibrio cholerae Type I-F CAST system and Golden Gate assembly sites with fluorescent protein gene dropouts for guide RNA and a mini-transposon cargo cloning. We show an example of UltraCAST genome editing by disrupting a gene in the chromosome of Serratia symbiotica CWBI-2.3^T, a culturable relative of aphid endosymbionts. The UltraCAST can be used to flexibly insert DNA into specific genomic sites and facilitates testing this genome editing platform in non-model bacterial species that lack genetic tools. 

Naturally competent bacteria can be engineered into platforms for detecting environmental DNA. This capability could be used to monitor the spread of pathogens, invasive species, and resistance genes, among other applications. Here, we create Acinetobacter baylyi ADP1-ISx biosensors that detect specific target DNA sequences through natural transformation. We tested strains with DNA sensors that consisted of either a mutated antibiotic resistance gene (TEM-1 bla or nptII) or a counterselectable gene flanked by sequences from the fungus Pseudogymnoascus destructans, which causes white-nose syndrome in bats. Upon uptake of homologous DNA, recombination restored antibiotic resistance gene function or removed the counterselectable gene, enabling selection of cells that sensed the target DNA. The antibiotic resistance gene and P. destructans biosensors could detect as few as 3,000 or 5,000,000 molecules of their DNA targets, respectively, and their sensitivity was not affected by excess off-target DNA. These results demonstrate how A. baylyi can be reprogrammed into a modular platform for monitoring environmental DNA. 

Engineered plasmids have been workhorses of recombinant DNA technology for nearly half a century. Plasmids are used to clone DNA sequences encoding new genetic parts and to reprogram cells by combining these parts in new ways. Historically, many genetic parts on plasmids were copied and reused without routinely checking their DNA sequences. With the widespread use of high-throughput DNA sequencing technologies, we now know that plasmids often contain variants of common genetic parts that differ slightly from their canonical sequences. Because the exact provenance of a genetic part on a particular plasmid is usually unknown, it is difficult to determine whether these differences arose due to mutations during plasmid construction and propagation or due to intentional editing by researchers. In either case, it is important to understand how the sequence changes alter the properties of the genetic part. We analyzed the sequences of over 50,000 engineered plasmids using depositor metadata and a metric inspired by the natural language processing field. We detected 217 uncatalogued genetic part variants that were especially widespread or were likely the result of convergent evolution or engineering. Several of these uncatalogued variants are known mutants of plasmid origins of replication or antibiotic resistance genes that are missing from current annotation databases. However, most are uncharacterized, and 3/5 of the plasmids we analyzed contained at least one of the uncatalogued variants. Our results include a list of genetic parts to prioritize for refining engineered plasmid annotation pipelines, highlight widespread variants of parts that warrant further investigation to see whether they have altered characteristics, and suggest cases where unintentional evolution of plasmid parts may be affecting the reliability and reproducibility of science.