Direct whole-genome sequencing of HIV-1 for clinical drug-resistance analysis and public health surveillance.

BACKGROUND: Human Immunodeficiency virus type 1 (HIV-1) remains a significant global health threat partly due to its ability to develop resistance to anti-retroviral therapies. HIV-1 genotype and drug resistance analysis of the polymerase (pol) sequence is a mainstay of its clinical and public health management. However, as new treatments and resistances evolve, analysis methods must change accordingly. In this study, we outline the development and implementation of a direct whole-genome sequencing approach (dWGS) using probe-capture target-enrichment for HIV-1 genotype and drug resistance analysis. METHODS: We implemented dWGS and performed parallel pol Sanger sequencing for clinical samples, followed by comparative genotype and drug-resistance analysis. These HIV-1 WGS sequences were also utilised for a novel partitioned phylogenetic analysis. RESULTS: Optimised nucleic acid extraction and DNAse I treatment significantly increased HIV-1 whole-genome coverage and depth, and improved recovery of high-quality genomes from low viral load clinical samples, enabling routine sequencing of viral loads as low as 1000 copies/mL. Overall, dWGS was robust, accurate and more sensitive for detecting low-frequency variants at drug-resistance sites compared to Sanger sequencing. Analysis of multiple sequence regions improved phylogenetic reconstruction for recombinant HIV-1 sequences compared to analysis of pol sequence alone. CONCLUSIONS: These findings demonstrate dWGS enhances HIV-1 drug-resistance analysis by quantitative variant detection and improves reconstruction of HIV-1 phylogenies compared to traditional pol sequencing. This work supports that HIV-1 dWGS is a viable option to replace Sanger sequencing for clinical and public health applications.

Variable preterm oral microbiome stabilizes and reflects a full-term infant profile within three months.

BACKGROUND: Preterm infants suffer higher morbidity and mortality rates compared to full-term infants, but little is known about how changes to oral and respiratory tract microbiota may impact disease development. METHODS: Here, very preterm neonates (n = 50) were selected to study oral and respiratory microbiota development during the first few months post-birth, where 26 individuals were diagnosed with BPD and/or sepsis. These infants were compared to 14 healthy full-term infants and 16 adults. Microbiota diversity, composition, and species abundances were calculated from 16S ribosomal RNA gene sequences in buccal swabs and tracheal aspirates at two time points (within a week and 1-3 months post-birth). RESULTS: Collection time point was the biggest factor to significantly influence the preterm oral microbial diversity and composition. In addition, BPD and sepsis were linked to distinct preterm oral microbiota diversity and composition, and opportunistic pathogens previously associated with these diseases were identified in the initial sample for both healthy preterm neonates and those with the disease. Compared to the full-term infant and adult dataset, preterm infant diversity and composition was initially significantly different, but resembled full-term infant diversity and composition over time. CONCLUSION: Overall, consequences of microbiota development need further examination in preterm infant infections and later development. IMPACT: Non-gut microbiota research on preterm infants is limited. At one week post-birth, preterm infants harbor distinct oral microbiota that are not shared with full-term children or adults, eventually becoming similar to full-term infants at 36 weeks postmenstrual age. DNA from potential opportunistic pathogens was observed in the mouth and lungs of preterm infants within a week of birth, and microbes associated with BPD were identified in the lungs. Oral microbiota in preterm infants over the first 2-3 months is unique and may be connected to short- and long-term health outcomes in these children.

Type 1 diabetes, periodontal health, and a familial history of hyperlipidaemia is associated with oral microbiota in children: a cross-sectional study.

BACKGROUND: Hyperlipidaemia may play a significant role in the interrelationship between type 1 diabetes (T1D) and periodontal disease. A potential mechanism that links these three aspects together is the oral microbiota. We wanted to determine if there is an association between hyperlipidaemia, periodontal disease, and the oral microbiota of children with T1D, as this has not yet been explored. METHODS: In a post-hoc, cross-sectional study using 16S rRNA gene sequencing, we explored links between oral bacterial diversity and composition of gingival swab samples from 72 children with T1D to periodontal risk factors and hyperlipidaemia status of first-degree relatives. While multiple periodontal risk factors were assessed, we used periodontal pocket depth of 3 mm to characterise periodontal risk. As periodontal pocket depth confounded the analysis of familial history of hyperlipidaemia, a multivariate analyses were performed (i.e., no periodontal risk markers in children with or without a family history of hyperlipidaemia were compared to counterparts who did not have periodontal risk markers) to examine linkages between these factors and diversity and composition of the microbiome. RESULTS: In participants with no periodontitis risk, children with a family history of dyslipidemia had different bacterial diversity and composition compared to those without a familar hisitory. In contrast, such differences did not exist in the children with periodontal risk, whether or not they had a family history of hyperlipidaemia. Co-occurrence networks showed that these differences in children with no periodontists risk were linked to the presence of fewer oral microbial networks, but more microbes linked to mature plaque structures. In contrast, children with periodontal risk markers, regardless of family history of hyperlipidaemia, contained co-occurrence networks that were associated with microbes linked to periodontal disease. CONCLUSIONS: In children diagnosed with T1D, our findings support an association between oral microbiota and two different exposure variables: familial history of hyperlipidaemia and periodontal risk factors.

Schoolyard Biodiversity Determines Short-Term Recovery of Disturbed Skin Microbiota in Children.

Creating biodiverse urban habitat has been proposed, with growing empirical support, as an intervention for increasing human microbial diversity and reducing associated diseases. However, ecological understanding of urban biodiversity interventions on human skin microbiota remains limited. Here, we experimentally test the hypotheses that disturbed skin microbiota recover better in outdoor schoolyard environments and that greater biodiversity provides a greater response. Repeating the experiment three times, we disturbed skin microbiota of fifty-seven healthy 10-to-11-year-old students with a skin swab (i.e., cleaning), then exposed them to one school environment-either a 'classroom' (n = 20), 'sports field' (n = 14), or biodiverse 'forest' (n = 23)-for 45 min. Another skin swab followed the exposure to compare 'before' and 'after' microbial communities. After 45 min, the disturbance immediately followed by outdoor exposure, especially the 'forest', had an enriching and diversifying effect on skin microbiota, while 'classroom' exposure homogenised inter-personal variability. Each effect compounded over consecutive days indicating longer-term exposure outcomes. The experimental disturbance also reduced the core skin microbiota, and only outdoor environments were able to replenish lost species richness to core membership (n species > 50% prevalent). Overall, we find that environmental setting, especially including biodiversity, is important in human microbiota recovery periods and that the outdoors provide resilience to skin communities. This work also has implications for the inclusion of short periods of outside or forest exposure in school scheduling. Future investigations of the health impacts of permanent urban biodiversity interventions are needed.

Rare genera differentiate urban green space soil bacterial communities in three cities across the world.

Vegetation complexity is potentially important for urban green space designs aimed at fostering microbial biodiversity to benefit human health. Exposure to urban microbial biodiversity may influence human health outcomes via immune training and regulation. In this context, improving human exposure to microbiota via biodiversity-centric urban green space designs is an underused opportunity. There is currently little knowledge on the association between vegetation complexity (i.e. diversity and structure) and soil microbiota of urban green spaces. Here, we investigated the association between vegetation complexity and soil bacteria in urban green spaces in Bournemouth, UK; Haikou, China; and the City of Playford, Australia by sequencing the 16S rRNA V4 gene region of soil samples and assessing bacterial diversity. We characterized these green spaces as having 'low' or 'high' vegetation complexity and explored whether these two broad categories contained similar bacterial community compositions and diversity around the world. Within cities, we observed significantly different alpha and beta diversities between vegetation complexities; however, these results varied between cities. Rare genera (<1% relative abundance individually, on average 35% relative abundance when pooled) were most likely to be significantly different in sequence abundance between vegetation complexities and therefore explained much of the differences in microbial communities observed. Overall, general associations exist between soil bacterial communities and vegetation complexity, although these are not consistent between cities. Therefore, more in-depth work is required to be done locally to derive practical actions to assist the conservation and restoration of microbial communities in urban areas.

Early markers of periodontal disease and altered oral microbiota are associated with glycemic control in children with type 1 diabetes.

OBJECTIVES: To determine the relationship between periodontal disease and glycemic control in children with type 1 diabetes and to characterize the diversity and composition of their oral microbiota. METHODS: Cross-sectional study including children with type 1 diabetes recruited from clinics at the Women's and Children's Hospital (Australia). Participants had a comprehensive dental assessment, periodontal examination, and buccal and gingival samples collected for 16S rRNA sequencing. RESULTS: Seventy-seven participants (age 13.3 ± 2.6 years, 38 males, BMI z-score 0.81 ± 0.75) had a diabetes duration of 5.6 ± 3.9 years and median HbA1c of 8.5% (range 5.8-13.3), 69.4 mmol/mol (range 39.9-121.9). Thirty-eight (49%) had early markers of periodontal disease. HbA1c was positively correlated with plaque index (Rho = 0.34, P = 0.002), gingival index (Rho = 0.30, P = 0.009), bleeding on probing (Rho = 0.44, P = 0.0001) and periodontal pocket depth >3 mm (Rho = 0.21, P = 0.06). A 1% increase in HbA1c was independently associated with an average increase in bleeding on probing of 25% (P = 0.002) and with an increase in the rate of sites with pocket depth >3 mm of 54% (P = 0.003). Higher HbA1c was independently related to increased phylogenetic alpha diversity (P = 0.008) and increased compositional variation (beta diversity P = 0.02) in gingival, but not buccal, microbiota. Brushing frequency, plaque index, and gingival index had a significant effect on microbiota composition, independent of HbA1c. CONCLUSIONS: Children with type 1 diabetes showed a continuous relationship between less favorable glycemic control and increased early markers of periodontal disease. Glycemic control was also related to the complexity and richness of the plaque microbiota, with diversity increasing as HbA1c levels increase.

Transfer of environmental microbes to the skin and respiratory tract of humans after urban green space exposure.

BACKGROUND: In industrialized countries, non-communicable diseases have been increasing in prevalence since the middle of the 20th century. While the causal mechanisms remain poorly understood, increased population density, pollution, sedentary behavior, smoking, changes in diet, and limited outdoor exposure have all been proposed as significant contributors. Several hypotheses (e.g. Hygiene, Old Friends, and Biodiversity Hypotheses) also suggest that limited environmental microbial exposures may underpin part of this rise in non-communicable diseases. In response, the Microbiome Rewilding Hypothesis proposes that adequate environmental microbial exposures could be achieved by restoring urban green spaces and could potentially decrease the prevalence of non-communicable diseases. However, the microbial interactions between humans and their surrounding environment and the passaging of microbes between both entities remains poorly understood, especially within an urban context. RESULTS: Here, we survey human skin (n = 90 swabs) and nasal (n = 90 swabs) microbiota of three subjects that were exposed to air (n = 15), soil (n = 15), and leaves (n = 15) from different urban green space environments in three different cities across different continents (Adelaide, Australia; Bournemouth, United Kingdom; New Delhi, India). Using 16S ribosomal RNA metabarcoding, we examined baseline controls (pre-exposure) of both skin (n = 16) and nasal (n = 16) swabs and tracked microbiota transfer from the environment to the human body after exposure events. Microbial richness and phylogenetic diversity increased after urban green space exposure in skin and nasal samples collected in two of the three locations. The microbial composition of skin samples also became more similar to soil microbiota after exposure, while nasal samples became more similar to air samples. Nasal samples were more variable between sites and individuals than skin samples. CONCLUSIONS: We show that exposure to urban green spaces can increase skin and nasal microbial diversity and alter human microbiota composition. Our study improves our understanding of human-environmental microbial interactions and suggests that increased exposure to diverse outdoor environments may increase the microbial diversity, which could lead to positive health outcomes for non-communicable diseases.

Microbiome applications for pathology: challenges of low microbial biomass samples during diagnostic testing.

The human microbiome can play key roles in disease, and diagnostic testing will soon have the ability to examine these roles in the context of clinical applications. Currently, most diagnostic testing in pathology applications focuses on a small number of disease-causing microbes and dismisses the whole microbial community that causes or is modulated by disease. Microbiome modifications have already provided clinically relevant insights in gut and oral diseases, such as irritable bowel disease, but there are currently limitations when clinically examining microbiomes outside of these body sites. This is critical, as the majority of microbial samples used in pathology originate from body sites that contain low concentrations of microbial DNA, including skin, tissue, blood, and urine. These samples, also known as low microbial biomass samples, are difficult to examine without careful consideration and precautions to mitigate contamination and biases. Here, we present the limitations when analysing low microbial biomass samples using current protocols and techniques and highlight the advantages that microbiome testing can offer diagnostics in the future, if the proper precautions are implemented. Specifically, we discuss the sources of contamination and biases that may result in false assessments for these sample types. Finally, we provide recommendations to mitigate contamination and biases from low microbial biomass samples during diagnostic testing, which will be especially important to effectively diagnose and treat patients using microbiome analyses.

Laboratory contamination over time during low-biomass sample analysis.

Bacteria are not only ubiquitous on earth but can also be incredibly diverse within clean laboratories and reagents. The presence of both living and dead bacteria in laboratory environments and reagents is especially problematic when examining samples with low endogenous content (e.g., skin swabs, tissue biopsies, ice, water, degraded forensic samples or ancient material), where contaminants can outnumber endogenous microorganisms within samples. The contribution of contaminants within high-throughput studies remains poorly understood because of the relatively low number of contaminant surveys. Here, we examined 144 negative control samples (extraction blank and no-template amplification controls) collected in both typical molecular laboratories and an ultraclean ancient DNA laboratory over 5 years to characterize long-term contaminant diversity. We additionally compared the contaminant content within a home-made silica-based extraction method, commonly used to analyse low endogenous content samples, with a widely used commercial DNA extraction kit. The contaminant taxonomic profile of the ultraclean ancient DNA laboratory was unique compared to modern molecular biology laboratories, and changed over time according to researcher, month and season. The commercial kit also contained higher microbial diversity and several human-associated taxa in comparison to the home-made silica extraction protocol. We recommend a minimum of two strategies to reduce the impacts of laboratory contaminants within low-biomass metagenomic studies: (a) extraction blank controls should be included and sequenced with every batch of extractions and (b) the contributions of laboratory contamination should be assessed and reported in each high-throughput metagenomic study.