It has been thought that Clostridium difficile infection is transmitted predominantly within health care settings. However, endemic spread has hampered identification of precise sources of infection and the assessment of the efficacy of interventions. From September 2007 through March 2011, we performed whole-genome sequencing on isolates obtained from all symptomatic patients with C. difficile infection identified in health care settings or in the community in Oxfordshire, United Kingdom. We compared single-nucleotide variants (SNVs) between the isolates, using C. difficile evolution rates estimated on the basis of the first and last samples obtained from each of 145 patients, with 0 to 2 SNVs expected between transmitted isolates obtained less than 124 days apart, on the basis of a 95% prediction interval. We then identified plausible epidemiologic links among genetically related cases from data on hospital admissions and community location. Of 1250 C. difficile cases that were evaluated, 1223 (98%) were successfully sequenced. In a comparison of 957 samples obtained from April 2008 through March 2011 with those obtained from September 2007 onward, a total of 333 isolates (35%) had no more than 2 SNVs from at least 1 earlier case, and 428 isolates (45%) had more than 10 SNVs from all previous cases. Reductions in incidence over time were similar in the two groups, a finding that suggests an effect of interventions targeting the transition from exposure to disease. Of the 333 patients with no more than 2 SNVs (consistent with transmission), 126 patients (38%) had close hospital contact with another patient, and 120 patients (36%) had no hospital or community contact with another patient. Distinct subtypes of infection continued to be identified throughout the study, which suggests a considerable reservoir of C. difficile. Over a 3-year period, 45% of C. difficile cases in Oxfordshire were genetically distinct from all previous cases. Genetically diverse sources, in addition to symptomatic patients, play a major part in C. difficile transmission. (Funded by the U.K. Clinical Research Collaboration Translational Infection Research Initiative and others.)

The rise of antibiotic-resistant bacteria has led to an urgent need for rapid detection of drug resistance in clinical samples, and improvements in global surveillance. Here we show how de Bruijn graph representation of bacterial diversity can be used to identify species and resistance profiles of clinical isolates. We implement this method for Staphylococcus aureus and Mycobacterium tuberculosis in a software package (‘Mykrobe predictor’) that takes raw sequence data as input, and generates a clinician-friendly report within 3 minutes on a laptop. For S. aureus, the error rates of our method are comparable to gold-standard phenotypic methods, with sensitivity/specificity of 99.1%/99.6% across 12 antibiotics (using an independent validation set, n=470). For M. tuberculosis, our method predicts resistance with sensitivity/specificity of 82.6%/98.5% (independent validation set, n=1,609); sensitivity is lower here, probably because of limited understanding of the underlying genetic mechanisms. We give evidence that minor alleles improve detection of extremely drug-resistant strains, and demonstrate feasibility of the use of emerging single-molecule nanopore sequencing techniques for these purposes.

A robust high-throughput multilocus sequence typing (MLST) scheme for Clostridium difficile was developed and validated using a diverse collection of 50 reference isolates representing 45 different PCR ribotypes and 102 isolates from recent clinical samples. A total of 49 PCR ribotypes were represented overall. All isolates were typed by MLST and yielded 40 sequence types (STs). A web-accessible database was set up ( http://pubmlst.org/cdifficile/ ) to facilitate the dissemination and comparison of C. difficile MLST genotyping data among laboratories. MLST and PCR ribotyping were similar in discriminatory abilities, having indices of discrimination of 0.90 and 0.92, respectively. Some STs corresponded to a single PCR ribotype (32/40), other STs corresponded to multiple PCR ribotypes (8/40), and, conversely, the PCR ribotype was not always predictive of the ST. The total number of variable nucleotide sites in the concatenated MLST sequences was 103/3,501 (2.9%). Concatenated MLST sequences were used to construct a neighbor-joining tree which identified four phylogenetic groups of STs and one outlier (ST-11; PCR ribotype 078). These groups apparently correlate with clades identified previously by comparative genomics. The MLST scheme was sufficiently robust to allow direct genotyping of C. difficile in total stool DNA extracts without isolate culture. The direct (nonculture) MLST approach may prove useful as a rapid genotyping method, potentially benefiting individual patients and informing hospital infection control.

Patterns and bottlenecks: A year into the severe acute respiratory syndrome coronavirus 2 pandemic, we are experiencing waves of new variants emerging. Some of these variants have worrying functional implications, such as increased transmissibility or antibody treatment escape. Lythgoe et al. have undertaken in-depth sequencing of more than 1000 hospital patients' isolates to find out how the virus is mutating within individuals. Overall, there seem to be consistent and reproducible patterns of within-host virus diversity. The authors observed only one or two variants in most samples, but a few carried many variants. Although the evidence indicates strong purifying selection, including in the spike protein responsible for viral entry, the authors also saw evidence for transmission clusters associated with households and other possible superspreader events. After transmission, most variants fizzled out, but occasionally some initiated ongoing transmission and wider dissemination. Science , this issue p. eabg0821

Whole-genome sequencing (WGS) could potentially provide a single platform for extracting all the information required to predict an organism's phenotype. However, its ability to provide accurate predictions has not yet been demonstrated in large independent studies of specific organisms. In this study, we aimed to develop a genotypic prediction method for antimicrobial susceptibilities. The whole genomes of 501 unrelated Staphylococcus aureus isolates were sequenced, and the assembled genomes were interrogated using BLASTn for a panel of known resistance determinants (chromosomal mutations and genes carried on plasmids). Results were compared with phenotypic susceptibility testing for 12 commonly used antimicrobial agents (penicillin, methicillin, erythromycin, clindamycin, tetracycline, ciprofloxacin, vancomycin, trimethoprim, gentamicin, fusidic acid, rifampin, and mupirocin) performed by the routine clinical laboratory. We investigated discrepancies by repeat susceptibility testing and manual inspection of the sequences and used this information to optimize the resistance determinant panel and BLASTn algorithm. We then tested performance of the optimized tool in an independent validation set of 491 unrelated isolates, with phenotypic results obtained in duplicate by automated broth dilution (BD Phoenix) and disc diffusion. In the validation set, the overall sensitivity and specificity of the genomic prediction method were 0.97 (95% confidence interval [95% CI], 0.95 to 0.98) and 0.99 (95% CI, 0.99 to 1), respectively, compared to standard susceptibility testing methods. The very major error rate was 0.5%, and the major error rate was 0.7%. WGS was as sensitive and specific as routine antimicrobial susceptibility testing methods. WGS is a promising alternative to culture methods for resistance prediction in S. aureus and ultimately other major bacterial pathogens.

The control of Clostridium difficile infections is an international clinical challenge. The incidence of C difficile in England declined by roughly 80% after 2006, following the implementation of national control policies; we tested two hypotheses to investigate their role in this decline. First, if C difficile infection declines in England were driven by reductions in use of particular antibiotics, then incidence of C difficile infections caused by resistant isolates should decline faster than that caused by susceptible isolates across multiple genotypes. Second, if C difficile infection declines were driven by improvements in hospital infection control, then transmitted (secondary) cases should decline regardless of susceptibility. Regional (Oxfordshire and Leeds, UK) and national data for the incidence of C difficile infections and antimicrobial prescribing data (1998-2014) were combined with whole genome sequences from 4045 national and international C difficile isolates. Genotype (multilocus sequence type) and fluoroquinolone susceptibility were determined from whole genome sequences. The incidence of C difficile infections caused by fluoroquinolone-resistant and fluoroquinolone-susceptible isolates was estimated with negative-binomial regression, overall and per genotype. Selection and transmission were investigated with phylogenetic analyses. National fluoroquinolone and cephalosporin prescribing correlated highly with incidence of C difficile infections (cross-correlations >0·88), by contrast with total antibiotic prescribing (cross-correlations 0·2). Restricting fluoroquinolone prescribing appears to explain the decline in incidence of C difficile infections, above other measures, in Oxfordshire and Leeds, England. Antimicrobial stewardship should be a central component of C difficile infection control programmes. UK Clinical Research Collaboration (Medical Research Council, Wellcome Trust, National Institute for Health Research); NIHR Oxford Biomedical Research Centre; NIHR Health Protection Research Unit on Healthcare Associated Infection and Antimicrobial Resistance (Oxford University in partnership with Public Health England [PHE]), and on Modelling Methodology (Imperial College, London in partnership with PHE); and the Health Innovation Challenge Fund.