Factors contributing to retroviral integration have been intractable because past studies have not precisely located genomic sites of proviruses in sufficient numbers for significant analysis. In this study, 903 murine leukemia virus (MLV) and 379 human immunodeficiency virus-1 (HIV-1) integrations in the human genome were mapped. The data showed that MLV preferred integration near the start of transcriptional units (either upstream or downstream) whereas HIV-1 preferred integration anywhere in the transcriptional unit but not upstream of the transcriptional start. Defining different integration site preferences for retroviruses will have important ramifications for gene therapy and may aid in our understanding of the factors directing the integration process.

The CRISPR-Cas9 system is a powerful and revolutionary genome-editing tool for eukaryotic genomes, but its use in bacterial genomes is very limited. Here, we investigated the use of the Streptococcus pyogenes CRISPR-Cas9 system in editing the genome of Clostridium cellulolyticum, a model microorganism for bioenergy research. Wild-type Cas9-induced double-strand breaks were lethal to C. cellulolyticum due to the minimal expression of nonhomologous end joining (NHEJ) components in this strain. To circumvent this lethality, Cas9 nickase was applied to develop a single-nick-triggered homologous recombination strategy, which allows precise one-step editing at intended genomic loci by transforming a single vector. This strategy has a high editing efficiency (>95%) even using short homologous arms (0.2 kb), is able to deliver foreign genes into the genome in a single step without a marker, enables precise editing even at two very similar target sites differing by two bases preceding the seed region, and has a very high target site density (median interval distance of 9 bp and 95.7% gene coverage in C. cellulolyticum). Together, these results establish a simple and robust methodology for genome editing in NHEJ-ineffective prokaryotes.

ABSTRACTβ-Lactam antibiotics are the drugs of choice to treat pneumococcal infections. The spread of β-lactam-resistant pneumococci is a major concern in choosing an effective therapy for patients. Systematically tracking β-lactam resistance could benefit disease surveillance. Here we developed a classification system in which a pneumococcal isolate is assigned to a “PBP type” based on sequence signatures in the transpeptidase domains (TPDs) of the three critical penicillin-binding proteins (PBPs), PBP1a, PBP2b, and PBP2x. We identified 307 unique PBP types from 2,528 invasive pneumococcal isolates, which had known MICs to six β-lactams based on broth microdilution. We found that increased β-lactam MICs strongly correlated with PBP types containing divergent TPD sequences. The PBP type explained 94 to 99% of variation in MICs both before and after accounting for genomic backgrounds defined by multilocus sequence typing, indicating that genomic backgrounds made little independent contribution to β-lactam MICs at the population level. We further developed and evaluated predictive models of MICs based on PBP type. Compared to microdilution MICs, MICs predicted by PBP type showed essential agreement (MICs agree within 1 dilution) of >98%, category agreement (interpretive results agree) of >94%, a major discrepancy (sensitive isolate predicted as resistant) rate of <3%, and a very major discrepancy (resistant isolate predicted as sensitive) rate of <2% for all six β-lactams. Thus, the PBP transpeptidase signatures are robust indicators of MICs to different β-lactam antibiotics in clinical pneumococcal isolates and serve as an accurate alternative to phenotypic susceptibility testing.