Liam P. Shaw

DNA hairpins destabilize duplexes primarily by promoting melting rather than by inhibiting hybridization

The effect of secondary structure on DNA duplex formation is poorly understood. Using oxDNA, a nucleotide level coarse-grained model of DNA, we study how hairpins influence the rate and reaction pathways of DNA hybridzation. We compare to experimental systems studied by Gao et al. (1) and find that 3-base pair hairpins reduce the hybridization rate by a factor of 2, and 4-base pair hairpins by a factor of 10, compared to DNA with limited secondary structure, which is in good agreement with experiments. By contrast, melting rates are accelerated by factors of ∼100 and ∼2000. This surprisingly large speed-up occurs because hairpins form during the melting process, and significantly lower the free energy barrier for dissociation. These results should assist experimentalists in designing sequences to be used in DNA nanotechnology, by putting limits on the suppression of hybridization reaction rates through the use of hairpins and offering the possibility of deliberately increasing dissociation rates by incorporating hairpins into single strands.

Transient structural variations have strong effects on quantitative traits and reproductive isolation in fission yeast

Large structural variations (SVs) within genomes are more challenging to identify than smaller genetic variants but may substantially contribute to phenotypic diversity and evolution. We analyse the effects of SVs on gene expression, quantitative traits and intrinsic reproductive isolation in the yeast Schizosaccharomyces pombe. We establish a high-quality curated catalogue of SVs in the genomes of a worldwide library of S. pombe strains, including duplications, deletions, inversions and translocations. We show that copy number variants (CNVs) show a variety of genetic signals consistent with rapid turnover. These transient CNVs produce stoichiometric effects on gene expression both within and outside the duplicated regions. CNVs make substantial contributions to quantitative traits, most notably intracellular amino acid concentrations, growth under stress and sugar utilization in winemaking, whereas rearrangements are strongly associated with reproductive isolation. Collectively, these findings have broad implications for evolution and for our understanding of quantitative traits including complex human diseases.

The global distribution and spread of the mobilized colistin resistance gene mcr-1

Colistin represents one of the few available drugs for treating infections caused by carbapenem-resistant Enterobacteriaceae. As such, the recent plasmid-mediated spread of the colistin resistance gene mcr-1 poses a significant public health threat, requiring global monitoring and surveillance. Here, we characterize the global distribution of mcr-1 using a data set of 457 mcr-1-positive sequenced isolates. We find mcr-1 in various plasmid types but identify an immediate background common to all mcr-1 sequences. Our analyses establish that all mcr-1 elements in circulation descend from the same initial mobilization of mcr-1 by an ISApl1 transposon in the mid 2000s (2002–2008; 95% highest posterior density), followed by a marked demographic expansion, which led to its current global distribution. Our results provide the first systematic phylogenetic analysis of the origin and spread of mcr-1, and emphasize the importance of understanding the movement of antibiotic resistance genes across multiple levels of genomic organization.The recent plasmid-mediated spread of the mobilized colistin resistance gene mcr-1 poses a significant public health threat, requiring worldwide monitoring and surveillance. Here, Wang et al. compile and analyze a data set of 457 mcr-1-positive sequenced isolates to investigate the origin and global distribution of mcr-1.

The Human Salivary Microbiome Is Shaped by Shared Environment Rather than Genetics: Evidence from a Large Family of Closely Related Individuals

ABSTRACT The human microbiome is affected by multiple factors, including the environment and host genetics. In this study, we analyzed the salivary microbiomes of an extended family of Ashkenazi Jewish individuals living in several cities and investigated associations with both shared household and host genetic similarities. We found that environmental effects dominated over genetic effects. While there was weak evidence of geographical structuring at the level of cities, we observed a large and significant effect of shared household on microbiome composition, supporting the role of the immediate shared environment in dictating the presence or absence of taxa. This effect was also seen when including adults who had grown up in the same household but moved out prior to the time of sampling, suggesting that the establishment of the salivary microbiome earlier in life may affect its long-term composition. We found weak associations between host genetic relatedness and microbiome dissimilarity when using family pedigrees as proxies for genetic similarity. However, this association disappeared when using more-accurate measures of kinship based on genome-wide genetic markers, indicating that the environment rather than host genetics is the dominant factor affecting the composition of the salivary microbiome in closely related individuals. Our results support the concept that there is a consistent core microbiome conserved across global scales but that small-scale effects due to a shared living environment significantly affect microbial community composition. IMPORTANCE Previous research shows that the salivary microbiomes of relatives are more similar than those of nonrelatives, but it remains difficult to distinguish the effects of relatedness and shared household environment. Furthermore, pedigree measures may not accurately measure host genetic similarity. In this study, we include genetic relatedness based on genome-wide single nucleotide polymorphisms (SNPs) (rather than pedigree measures) and shared environment in the same analysis. We quantify the relative importance of these factors by studying the salivary microbiomes in members of a large extended Ashkenazi Jewish family living in different locations. We find that host genetics plays no significant role and that the dominant factor is the shared environment at the household level. We also find that this effect appears to persist in individuals who have moved out of the parental household, suggesting that aspects of salivary microbiome composition established during upbringing can persist over a time scale of years. IMPORTANCE Previous research shows that the salivary microbiomes of relatives are more similar than those of nonrelatives, but it remains difficult to distinguish the effects of relatedness and shared household environment. Furthermore, pedigree measures may not accurately measure host genetic similarity. In this study, we include genetic relatedness based on genome-wide single nucleotide polymorphisms (SNPs) (rather than pedigree measures) and shared environment in the same analysis. We quantify the relative importance of these factors by studying the salivary microbiomes in members of a large extended Ashkenazi Jewish family living in different locations. We find that host genetics plays no significant role and that the dominant factor is the shared environment at the household level. We also find that this effect appears to persist in individuals who have moved out of the parental household, suggesting that aspects of salivary microbiome composition established during upbringing can persist over a time scale of years.

Distinguishing the Signals of Gingivitis and Periodontitis in Supragingival Plaque: a Cross-Sectional Cohort Study in Malawi

ABSTRACT Periodontal disease ranges from gingival inflammation (gingivitis) to the inflammation and loss of tooth-supporting tissues (periodontitis). Previous research has focused mainly on subgingival plaque, but supragingival plaque composition is also known to be associated with disease. Quantitative modeling of bacterial abundances across the natural range of periodontal severities can distinguish which features of disease are associated with particular changes in composition. We assessed a cross-sectional cohort of 962 Malawian women for periodontal disease and used 16S rRNA gene amplicon sequencing (V5 to V7 region) to characterize the bacterial compositions of supragingival plaque samples. Associations between bacterial relative abundances and gingivitis/periodontitis were investigated by using negative binomial models, adjusting for epidemiological factors. We also examined bacterial cooccurrence networks to assess community structure. The main differences in supragingival plaque compositions were associated more with gingivitis than periodontitis, including higher bacterial diversity and a greater abundance of particular species. However, even after controlling for gingivitis, the presence of subgingival periodontitis was associated with an altered supragingival plaque. A small number of species were associated with periodontitis but not gingivitis, including members of Prevotella, Treponema, and Selenomonas, supporting a more complex disease model than a linear progression following gingivitis. Cooccurrence networks of periodontitis-associated taxa clustered according to periodontitis across all gingivitis severities. Species including Filifactor alocis and Fusobacterium nucleatum were central to this network, which supports their role in the coaggregation of periodontal biofilms during disease progression. Our findings confirm that periodontitis cannot be considered simply an advanced stage of gingivitis even when only considering supragingival plaque. IMPORTANCE Periodontal disease is a major public health problem associated with oral bacteria. While earlier studies focused on a small number of periodontal pathogens, it is now accepted that the whole bacterial community may be important. However, previous high-throughput marker gene sequencing studies of supragingival plaque have largely focused on high-income populations with good oral hygiene without including a range of periodontal disease severities. Our study includes a large number of low-income participants with poor oral hygiene and a wide range of severities, and we were therefore able to quantitatively model bacterial abundances as functions of both gingivitis and periodontitis. A signal associated with periodontitis remains after controlling for gingivitis severity, which supports the concept that, even when only considering supragingival plaque, periodontitis is not simply an advanced stage of gingivitis. This suggests the future possibility of diagnosing periodontitis based on bacterial occurrences in supragingival plaque.

Whole genome sequencing Mycobacterium tuberculosis directly from sputum identifies more genetic diversity than sequencing from culture

Background Repeated culture reduces within-sample Mycobacterium tuberculosis genetic diversity due to selection of clones suited to growth in culture and/or random loss of lineages, but it is not known to what extent omitting the culture step altogether alters genetic diversity. We compared M. tuberculosis whole genome sequences generated from 33 paired clinical samples using two methods. In one method DNA was extracted directly from sputum then enriched with custom-designed SureSelect (Agilent) oligonucleotide baits and in the other it was extracted from mycobacterial growth indicator tube (MGIT) culture. Results DNA directly sequenced from sputum showed significantly more within-sample diversity than that from MGIT culture (median 5.0 vs 4.5 heterozygous alleles per sample, p=0.04). Resistance associated variants present as HAs occurred in four patients, and in two cases may provide a genotypic explanation for phenotypic resistance. Conclusions Culture-free M. tuberculosis whole genome sequencing detects more within-sample diversity than a leading culture-based method and may allow detection of mycobacteria that are not actively replicating.

Children with cystic fibrosis are infected with multiple subpopulations of Mycobacterium abscessus with different antimicrobial resistance profiles

Background Children with cystic fibrosis (CF) can develop life-threatening infections of Mycobacterium abscessus. These present a significant clinical challenge, particularly when the strains involved are resistant to antibiotics. Recent evidence of within-patient subclones of M. abscessus in adults with CF suggests the possibility that within-patient diversity may be relevant for the treatment of pediatric CF patients. Methods We performed whole genome sequencing (WGS) on 32 isolates of M. abscessus from multiple body sites for two patients with CF undergoing treatment at Great Ormond Street Hospital, UK, in 2015. Results We found evidence of extensive diversity within patients over time. Clustering analysis of single nucleotide variants (SNVs) revealed that each patient harboured multiple subpopulations, which were differentially abundant between sputum, lung samples, chest wounds, and pleural fluid. Sputum isolates did not reflect overall within-patient diversity, including failing to detect subclones with mutations previously associated with macrolide resistance (rrl 2058/2059). Some variants were present at intermediate frequencies before lung transplant. The time of transplant coincided with extensive variation, suggesting that this event is particularly disruptive for the microbial community, but transplant did not clear the M. abscessus infection and both patients died as a result of this infection. Conclusions Isolates of M. abscessus from sputum do not always reflect the entire diversity present within the patient, which can include subclones with differing AMR profiles. Awareness of this phenotypic variability, with sampling of multiple body sites in conjunction with WGS, may be necessary to ensure the best treatment for this vulnerable patient group. Key point summary Children with cystic fibrosis undergoing lung transplant harbour multiple subpopulations of M. abscessus. Subpopulations can have different antimicrobial resistance genotypes. Sputum isolates do not reflect the genetic diversity within a patient.

From Theory to Practice: Translating Whole-Genome Sequencing (WGS) into the Clinic

Hospitals worldwide are facing an increasing incidence of hard-to-treat infections. Limiting infections and providing patients with optimal drug regimens require timely strain identification as well as virulence and drug-resistance profiling. Additionally, prophylactic interventions based on the identification of environmental sources of recurrent infections (e.g., contaminated sinks) and reconstruction of transmission chains (i.e., who infected whom) could help to reduce the incidence of nosocomial infections. WGS could hold the key to solving these issues. However, uptake in the clinic has been slow. Some major scientific and logistical challenges need to be solved before WGS fulfils its potential in clinical microbial diagnostics. In this review we identify major bottlenecks that need to be resolved for WGS to routinely inform clinical intervention and discuss possible solutions.

A perturbation model of the gut microbiome's response to antibiotics

Treatment with antibiotics is one of the most extreme perturbations to the human microbiome. Even standard courses of antibiotics dramatically reduce the microbiome’s diversity and can cause transitions to dysbiotic states. Conceptually, this is often described as a ‘stability landscape’: the microbiome sits in a landscape with multiple stable equilibria, and sufficiently strong perturbations can shift the microbiome from its normal equilibrium to another state. However, this picture is only qualitative and has not been incorporated in previous mathematical models of the effects of antibiotics. Here, we outline a simple quantitative model based on the stability landscape concept and demonstrate its success on real data. Our analytical impulse-response model has minimal assumptions with three parameters. We fit this model in a Bayesian framework to data from a previous study of the year-long effects of short courses of four common antibiotics on the gut and oral microbiomes, allowing us to compare parameters between antibiotics and microbiomes, and further validate our model using data from another study looking at the impact of a combination of last-resort antibiotics on the gut microbiome. Using Bayesian model selection we find support for a long-term transition to an alternative microbiome state after courses of certain antibiotics in both the gut and oral microbiomes. Quantitative stability landscape frameworks are an exciting avenue for future microbiome modelling.Even short courses of antibiotics are known to reduce gut microbiome diversity. However, there has been limited mathematical modelling of the associated dynamical time-response. Here, we take inspiration from a 9stability landscape9 schematic and develop an impulse-response model of antibiotic perturbation. We fit this model to previously published data where individuals took a ten-day course of antibiotics (clindamycin or ciprofloxacin) and were sampled up to a year afterwards. By fitting an extended model allowing for a transition to an alternative stable state, we find support for a long-term transition to an alternative community state one year after taking antibiotics. This implies that a single treatment of antibiotics not only reduces the diversity of the gut flora for up to a year but also alters its composition, possibly indefinitely. Our results provide quantitative support for a conceptual picture of the gut microbiome and demonstrate that simple models can provide biological insight.

The oral microbiome

The human microbiome is receiving a great deal of attention as its role in health and disease becomes ever more apparent. The oral microbiome, perhaps due to the ease with which we can obtain samples, is arguably the most well-studied human microbiome to date. It is obvious, however, that we have only just begun to scratch the surface of the complex bacterial and bacterial–host interactions within this complex community. Here, we describe the factors which are known to influence the development of the seemingly globally conserved, core, oral microbiome and those which are likely to be responsible for the observed differences at the individual level. We discuss the paradoxical situation of maintaining a stable core microbiome which is at the same time incredibly resilient and adaptable to many different stresses encountered in the open environment of the oral cavity. Finally, we explore the interactions of the oral microbiome with the host and discuss the interactions underlying human health and disease.