Implications of multiple freeze-thawing on respiratory samples for culture-independent analyses

Effects of Different Preservation Methods on the Structure and Diversity of Intestinal Microbiota of Marine Fishes

The fish intestine is a complex ecosystem where microbial communities are dynamic and influenced by various factors. Preservation conditions during field collection can introduce biases affecting the microbiota amplified during sequencing. Therefore, establishing effective, standardized methods for sampling fish intestinal microbiota is crucial. This study used hybrid groupers (Epinephelus fuscoguttatus ♀ × E. lanceolatus ♂) to examine the effects of six preservation methods: dry ice (1 day), dry ice (1 day) followed by - 80 °C storage (5 days), liquid nitrogen (1 day), liquid nitrogen (1 day) with subsequent - 80 °C storage (5 days), refrigeration at 4 °C (3 days), and freezing at - 20 °C (3 days), with fresh samples as controls. High-throughput 16S rRNA sequencing assessed microbial diversity, community structure, dominant species, and OTU abundance across treatments. Results indicated that dry ice and liquid nitrogen methods, especially with - 80 °C storage, had minimal impact on microbial diversity and structure. Compared to other preservation methods, refrigeration at 4 °C and freezing at - 20 °C may result in suboptimal reproducibility and altered community structure, particularly affecting rare microbial taxa. This study underscores the need for standardized preservation techniques to ensure accurate fish intestinal microbiota analysis and provides a foundation for future research.

Subtracting the background by reducing cell-free DNA's confounding effects on Mycobacterium tuberculosis quantitation and the sputum microbiome

DNA characterisation in people with tuberculosis (TB) is critical for diagnostic and microbiome evaluations. However, extracellular DNA, more frequent in people on chemotherapy, confounds results. We evaluated whether nucleic acid dyes [propidium monoazide (PMA), PEMAX] and DNaseI could reduce this. PCR [16S Mycobacterium tuberculosis complex (Mtb) qPCR, Xpert MTB/RIF] was done on dilution series of untreated and treated (PMA, PEMAX, DNaseI) Mtb. Separately, 16S rRNA gene qPCR and sequencing were done on untreated and treated sputa before (Cohort A: 11 TB-negatives, 9 TB-positives; Cohort B: 19 TB-positives, PEMAX only) and 24-weeks after chemotherapy (Cohort B). PMA and PEMAX reduced PCR-detected Mtb DNA for dilution series and Cohort A sputum versus untreated controls, suggesting non-intact Mtb is present before treatment-start. PEMAX enabled sequencing-based Mycobacterium-detection in 7/12 (58%) TB-positive sputa where no such reads otherwise occurred. In Cohort A, PMA- and PEMAX-treated versus untreated sputa had decreased α- and increased β-diversities. In Cohort B, β-diversity differences between timepoints were only detected with PEMAX. DNaseI had negligible effects. PMA and PEMAX (but not DNaseI) reduced extracellular DNA in PCR and improved pathogen detection by sequencing. PEMAX additionally detected chemotherapy-associated taxonomic changes that would otherwise be missed. Dyes enhance microbiome evaluations especially during chemotherapy.

Field and laboratory guidelines for reliable bioinformatic and statistical analysis of bacterial shotgun metagenomic data

Shotgun metagenomics is an increasingly cost-effective approach for profiling environmental and host-associated microbial communities. However, due to the complexity of both microbiomes and the molecular techniques required to analyze them, the reliability and representativeness of the results are contingent upon the field, laboratory, and bioinformatic procedures employed. Here, we consider 15 field and laboratory issues that critically impact downstream bioinformatic and statistical data processing, as well as result interpretation, in bacterial shotgun metagenomic studies. The issues we consider encompass intrinsic properties of samples, study design, and laboratory-processing strategies. We identify the links of field and laboratory steps with downstream analytical procedures, explain the means for detecting potential pitfalls, and propose mitigation measures to overcome or minimize their impact in metagenomic studies. We anticipate that our guidelines will assist data scientists in appropriately processing and interpreting their data, while aiding field and laboratory researchers to implement strategies for improving the quality of the generated results.

The Metabolic Potential of the Human Lung Microbiome

The human lung microbiome remains largely underexplored, despite its potential implications in the pharmacokinetics of inhaled drugs and its involvement in lung diseases. Interactions within these bacterial communities and with the host are complex processes which often involve microbial small molecules. In this study, we employed a computational approach to describe the metabolic potential of the human lung microbiome. By utilizing antiSMASH and BiG-SCAPE software, we identified 1831 biosynthetic gene clusters for the production of specialized metabolites in a carefully compiled genome database of lung-associated bacteria and fungi. It was shown that RiPPs represent the largest class of natural products within the bacteriome, while NRPs constitute the largest class of natural products in the lung mycobiome. All predicted BGCs were further categorized into 767 gene cluster families, and a subsequent network analysis highlighted that these families are widely distributed and contain many uncharacterized members. Moreover, in-depth annotation allowed the assignment of certain gene clusters to putative lung-specific functions within the microbiome, such as osmoadaptation or surfactant synthesis. This study establishes the lung microbiome as a prolific source for secondary metabolites and lays the groundwork for detailed investigation of this unique environment.

Ecological patterns and processes of temporal turnover within lung infection microbiota

BACKGROUND

Chronic infection and consequent airway inflammation are the leading causes of morbidity and early mortality for people living with cystic fibrosis (CF). However, lower airway infections across a range of chronic respiratory diseases, including in CF, do not follow classical 'one microbe, one disease' concepts of infection pathogenesis. Instead, they are comprised of diverse and temporally dynamic lung infection microbiota. Consequently, temporal dynamics need to be considered when attempting to associate lung microbiota with changes in disease status. Set within an island biogeography framework, we aimed to determine the ecological patterns and processes of temporal turnover within the lung microbiota of 30 paediatric and adult CF patients prospectively sampled over a 3-year period. Moreover, we aimed to ascertain the contributions of constituent chronic and intermittent colonizers on turnover within the wider microbiota.

RESULTS

The lung microbiota within individual patients was partitioned into constituent chronic and intermittent colonizing groups using the Leeds criteria and visualised with persistence-abundance relationships. This revealed bacteria chronically infecting a patient were both persistent and common through time, whereas intermittently infecting taxa were infrequent and rare; respectively representing the resident and transient portions of the wider microbiota. It also indicated that the extent of chronic colonization was far greater than could be appreciated with microbiological culture alone. Using species-time relationships to measure temporal turnover and Vellend's rationalized ecological processes demonstrated turnover in the resident chronic infecting groups was conserved and underpinned principally by the deterministic process of homogenizing dispersal. Conversely, intermittent colonizing groups, representing newly arrived immigrants and transient species, drove turnover in the wider microbiota and were predominately underpinned by the stochastic process of drift. For adult patients, homogenizing dispersal and drift were found to be significantly associated with lung function. Where a greater frequency of homogenizing dispersal was observed with worsening lung function and conversely drift increased with better lung function.

CONCLUSIONS

Our work provides a novel ecological framework for understanding the temporal dynamics of polymicrobial infection in CF that has translational potential to guide and improve therapeutic targeting of lung microbiota in CF and across a range of chronic airway diseases. Video Abstract.

Airway bacterial community composition in persons with advanced cystic fibrosis lung disease

BACKGROUND

The progression of lung disease in people with cystic fibrosis (pwCF) has been associated with a decrease in the diversity of airway bacterial communities. How often low diversity communities occur in advanced CF lung disease and how they may be associated with clinical outcomes is not clear, however.

METHODS

We sequenced a region of the bacterial 16S ribosomal RNA gene to characterize bacterial communities in sputum from 190 pwCF with advanced lung disease (FEV1≤40% predicted), with particular attention to the prevalence and relative abundance of dominant genera. We evaluated relationships between community diversity and clinical outcomes.

RESULTS

Although most of the 190 pwCF with advanced lung disease had airway bacterial communities characterized by low diversity with a dominant genus, a considerable minority (40%) did not. The absence of a dominant genus, presence of methicillin-susceptible Staphylococcus aureus, and greater bacterial richness positively correlated with lung function. Higher relative abundance of the dominant genus and greater antimicrobial use negatively correlated with lung function. PwCF with a low diversity community and dominant genus had reduced lung transplant-free survival compared to those without (median survival of 1.6 vs 2.9 years).

CONCLUSIONS

A considerable proportion of pwCF with advanced lung disease do not have airway bacterial communities characterized by low diversity and a dominant genus and these individuals had better survival. An understanding of the antecedents of low diversity airway communities- and the impact these may have on lung disease trajectory - may provide avenues for improved management strategies.

Sputum handling for rheology

The rheology of sputum is viewed as a powerful emerging biophysical marker for monitoring muco-obstructive pulmonary diseases such as cystic fibrosis (CF) and non-CF bronchiectasis (NCFB). However, there is no unified practice to process sputa from collection to analysis, which can lead to highly variable, and sometimes inconsistent results. The main objective of this study is to bring light into the handling of sputum samples to establish a standardised and robust protocol before rheological measurements. Sputum collected from 22 CF and 10 NCFB adults, was divided into control (vortexed and fresh: non-heated and non-frozen) and three treated conditions (either non-vortexed, heated or frozen). In addition, 6 CF expectorations were used to study the dynamics of ageing over 24 h. Sputum's mechanical properties were measured with a rotational rheometer to obtain their properties at rest, elastic ([Formula: see text]) and viscous moduli ([Formula: see text]), and at the onset of flow, critical deformation ([Formula: see text]) and critical stress ([Formula: see text]). We demonstrate that heating sputum is completely destructive while freezing sputa at [Formula: see text] has no discernible effect on their rheology. We also show that the variability of rheological measurements largely resulted from the sample's macroscopic heterogeneity, and can be greatly reduced by non-destructive vortex homogenisation. Finally, we observed contrasted ageing effects as a fonction of purulence: while the viscoelasticity of purulent samples reduced by half within 6 h after collection, semi-purulent samples did not evolve. These results guide towards a robust unified protocol for simple sputum handling in rheometry. We therefore suggest to vortex and snap freeze sputum samples immediately after collection when direct testing is not possible.

There Is More to Wounds than Bacteria: Fungal Biofilms in Chronic Wounds

Purpose of Review

The management of chronic wounds, a debilitating condition, presents a considerable challenge to healthcare professionals and a significant burden on services. When these wounds are exposed to the external environment, they are susceptible to microbial infection, which further complicates their management and worsens clinical outcomes.

Recent Findings

Bacteria typically exist in wounds as part of a biofilm, which is often polymicrobial in nature, alongside bacteria and fungi that are described as being more virulent and tolerant towards antimicrobials and antiseptics. Despite advancing knowledge in polymicrobial biofilm wound infections with respect to bacteria, the role of fungi is largely ignored, and their influence in chronicity and clinical management is not fully appreciated or understood.

Summary

The purpose of this review is to explore the significance of fungi within chronic wound environments and, in doing so, understand the importance of interkingdom interactions in wound management.

Bacterial Culture Underestimates Lung Pathogen Detection and Infection Status in Cystic Fibrosis

Microbiological surveillance of airway secretions is central to clinical care in cystic fibrosis (CF). However, the efficacy of microbiological culture, the diagnostic gold standard for pathogen detection, has been increasingly questioned. Here we compared culture with targeted quantitative PCR (QPCR) for longitudinal detection of 2 key pathogens, Pseudomonas aeruginosa and Staphylococcus aureus. Prospectively collected respiratory samples taken from 20 pediatric and 20 adult CF patients over a period of 3-years were analyzed. Patients were eligible if considered free of chronic Pseudomonas infection within 12-months prior to start of study. QPCR revealed high levels of infection with both pathogens not apparent from culture alone. Pseudomonas and Staphylococcus were detected by culture on at least one sampling occasion in 12 and 29 of the patients, respectively. Conversely, both pathogens were detected in all 40 patients by QPCR. Classification of infection status also significantly altered in both pediatric and adult patients, where the number of patients deemed chronically infected with Pseudomonas and Staphylococcus increased from 1 to 28 and 9 to 34, respectively. Overall, Pseudomonas and Staphylococcus infection status classification changed respectively for 36 and 27 of all patients. In no cases did molecular identification lead to a patient being in a less clinically serious infection category. Pathogen detection and infection status classification significantly increased when assessed by QPCR in comparison to culture. This could have implications for clinical care of CF patients, including accuracy of infection diagnosis, relevant and timely antibiotic selection, antimicrobial resistance development, establishment of chronic infection, and cross-infection control. IMPORTANCE Chronic lung infection is the leading cause of morbidity and early mortality for people with cystic fibrosis (pwCF). Microbiological surveillance to detect lung pathogens is recommended as best practise in CF patient care. Here we studied pathogen detection in 40 pwCF over several years. We found that microbiological culture, the diagnostic gold standard, was significantly disparate to targeted culture-independent approaches for detection and determination of chronic infection status of two important pathogens in CF. Pathogen detection was significantly lower by culture and consequently infection status was also misclassified in most cases. In particular, the extent of chronic infection by both P. aeruginosa and S. aureus not realized with culture was striking. Our findings have implications for the development of infection and clinical care of pwCF. Future longitudinal studies with greater patient numbers will be needed to establish the full extent of the clinical implications indicated from this study.

Towards standardized and reproducible research in skin microbiomes

Skin is a complex organ serving a critical role as a barrier and mediator of interactions between the human body and its environment. Recent studies have uncovered how resident microbial communities play a significant role in maintaining the normal healthy function of the skin and the immune system. In turn, numerous host-associated and environmental factors influence these communities' composition and diversity across the cutaneous surface. In addition, specific compositional changes in skin microbiota have also been connected to the development of several chronic diseases. The current era of microbiome research is characterized by its reliance on large data sets of nucleotide sequences produced with high-throughput sequencing of sample-extracted DNA. These approaches have yielded new insights into many previously uncharacterized microbial communities. Application of standardized practices in the study of skin microbial communities could help us understand their complex structures, functional capacities, and health associations and increase the reproducibility of the research. Here, we overview the current research in human skin microbiomes and outline challenges specific to their study. Furthermore, we provide perspectives on recent advances in methods, analytical tools and applications of skin microbiomes in medicine and forensics.

The microbiome of common bedding materials before and after use on commercial dairy farms

Background

Bovine mastitis is one of the most economically important diseases affecting dairy cows. The choice of bedding material has been identified as an important risk factor contributing to the development of mastitis. However, few reports examine both the culturable and nonculturable microbial composition of commonly used bedding materials, i.e., the microbiome. Given the prevalence of nonculturable microbes in most environments, this information could be an important step to understanding whether and how the bedding microbiome acts as a risk factor for mastitis. Therefore, our objective was to characterize the microbiome composition and diversity of bedding material microbiomes, before and after use.

Methods

We collected 88 bedding samples from 44 dairy farms in the U.S. Unused (from storage pile) and used (out of stalls) bedding materials were collected from four bedding types: new sand (NSA), recycled manure solids (RMS), organic non-manure (ON) and recycled sand (RSA). Samples were analyzed using 16S rRNA sequencing of the V3–V4 region.

Results

The overall composition as well as the counts of several microbial taxa differed between bedding types, with Proteobacteria, Actinobacteria, Bacteroidetes and Firmicutes dominating across all types. Used bedding contained a significantly different microbial composition than unused bedding, but the magnitude of this difference varied by bedding type, with RMS bedding exhibiting the smallest difference. In addition, positive correlations were observed between 16S rRNA sequence counts of potential mastitis pathogens (bacterial genera) and corresponding bedding bacterial culture data.

Conclusion

Our results strengthen the role of bedding as a potential source of mastitis pathogens. The consistent shift in the microbiome of all bedding types that occurred during use by dairy cows deserves further investigation to understand whether this shift promotes pathogen colonization and/or persistence, or whether it can differentially impact udder health outcomes. Future studies of bedding and udder health may be strengthened by including a microbiome component to the study design.

Supplementary Information

The online version contains supplementary material available at 10.1186/s42523-022-00171-2.

Comparing different sample collection and storage methods for field-based skin microbiome research

OBJECTIVES

The skin, as well as its microbial communities, serves as the primary interface between the human body and the surrounding environment. In order to implement the skin microbiome into human biology research, there is a need to explore the effects of different sample collection and storage methodologies, including the feasibility of conducting skin microbiome studies in field settings.

METHODS

We collected 99 skin microbiome samples from nine infants living in Veracruz, Mexico using a dual-tipped "dry" swab on the right armpit, palm, and forehead and a "wet" swab (0.15 M NaCl and 0.1% Tween 20) on the same body parts on the left side of the body. One swab from each collection method was stored in 95% ethanol while the other was frozen at -20°C. 16S rRNA amplicon sequencing generated data on bacterial diversity and community composition, which were analyzed using PERMANOVA, linear mixed effects models, and an algorithm-based classifier.

RESULTS

Treatment (wet_ethanol, wet_freezer, dry_ethanol, and dry_freezer) had an effect (~10% explanatory power) on the bacterial community diversity and composition of skin samples, although body site exhibited a stronger effect (~20% explanatory power). Within treatments, the collection method (wet vs. dry) affected measures of bacterial diversity to a greater degree than did the storage method (ethanol vs. freezer).

CONCLUSIONS

Our study provides novel information on skin microbiome sample collection and storage methods, suggesting that ethanol storage is suitable for research in resource-limited settings. Our results highlight the need for future study design to account for interbody site microbial variation.

Lung function and microbiota diversity in cystic fibrosis

BACKGROUND

Chronic infection and concomitant airway inflammation is the leading cause of morbidity and mortality for people living with cystic fibrosis (CF). Although chronic infection in CF is undeniably polymicrobial, involving a lung microbiota, infection surveillance and control approaches remain underpinned by classical aerobic culture-based microbiology. How to use microbiomics to direct clinical management of CF airway infections remains a crucial challenge. A pivotal step towards leveraging microbiome approaches in CF clinical care is to understand the ecology of the CF lung microbiome and identify ecological patterns of CF microbiota across a wide spectrum of lung disease. Assessing sputum samples from 299 patients attending 13 CF centres in Europe and the USA, we determined whether the emerging relationship of decreasing microbiota diversity with worsening lung function could be considered a generalised pattern of CF lung microbiota and explored its potential as an informative indicator of lung disease state in CF.

RESULTS

We tested and found decreasing microbiota diversity with a reduction in lung function to be a significant ecological pattern. Moreover, the loss of diversity was accompanied by an increase in microbiota dominance. Subsequently, we stratified patients into lung disease categories of increasing disease severity to further investigate relationships between microbiota characteristics and lung function, and the factors contributing to microbiota variance. Core taxa group composition became highly conserved within the severe disease category, while the rarer satellite taxa underpinned the high variability observed in the microbiota diversity. Further, the lung microbiota of individual patient were increasingly dominated by recognised CF pathogens as lung function decreased. Conversely, other bacteria, especially obligate anaerobes, increasingly dominated in those with better lung function. Ordination analyses revealed lung function and antibiotics to be main explanators of compositional variance in the microbiota and the core and satellite taxa. Biogeography was found to influence acquisition of the rarer satellite taxa.

CONCLUSIONS

Our findings demonstrate that microbiota diversity and dominance, as well as the identity of the dominant bacterial species, in combination with measures of lung function, can be used as informative indicators of disease state in CF. Video Abstract.

Systematic Analysis of Impact of Sampling Regions and Storage Methods on Fecal Gut Microbiome and Metabolome Profiles

The contribution of human gastrointestinal (GI) microbiota and metabolites to host health has recently become much clearer. However, many confounding factors can influence the accuracy of gut microbiome and metabolome studies, resulting in inconsistencies in published results. In this study, we systematically investigated the effects of fecal sampling regions and storage and retrieval conditions on gut microbiome and metabolite profiles from three healthy children. Our analysis indicated that compared to homogenized and snap-frozen samples (standard control [SC]), different sampling regions did not affect microbial community alpha diversity, while a total of 22 of 176 identified metabolites varied significantly across different sampling regions. In contrast, storage conditions significantly influenced the microbiome and metabolome. Short-term room temperature storage had a minimal effect on the microbiome and metabolome profiles. Sample storage in RNALater showed a significant level of variation in both microbiome and metabolome profiles, independent of the storage or retrieval conditions. The effect of RNALater on the metabolome was stronger than the effect on the microbiome, and individual variability between study participants outweighed the effect of RNALater on the microbiome. We conclude that homogenizing stool samples was critical for metabolomic analysis but not necessary for microbiome analysis. Short-term room temperature storage had a minimal effect on the microbiome and metabolome profiles and is recommended for short-term fecal sample storage. In addition, our study indicates that the use of RNALater as a storage medium of stool samples for microbial and metabolomic analyses is not recommended.IMPORTANCE The gastrointestinal microbiome and metabolome can provide a new angle to understand the development of health and disease. Stool samples are most frequently used for large-scale cohort studies. Standardized procedures for stool sample handling and storage can be a determining factor for performing microbiome or metabolome studies. In this study, we focused on the effects of stool sampling regions and stool sample storage conditions on variations in the gut microbiome composition and metabolome profile.

Systematic Analysis of Impact of Sampling Regions and Storage Methods on Fecal Gut Microbiome and Metabolome Profiles

The gastrointestinal microbiome and metabolome can provide a new angle to understand the development of health and disease. Stool samples are most frequently used for large-scale cohort studies. Standardized procedures for stool sample handling and storage can be a determining factor for performing microbiome or metabolome studies. In this study, we focused on the effects of stool sampling regions and stool sample storage conditions on variations in the gut microbiome composition and metabolome profile.

The contribution of human gastrointestinal (GI) microbiota and metabolites to host health has recently become much clearer. However, many confounding factors can influence the accuracy of gut microbiome and metabolome studies, resulting in inconsistencies in published results. In this study, we systematically investigated the effects of fecal sampling regions and storage and retrieval conditions on gut microbiome and metabolite profiles from three healthy children. Our analysis indicated that compared to homogenized and snap-frozen samples (standard control [SC]), different sampling regions did not affect microbial community alpha diversity, while a total of 22 of 176 identified metabolites varied significantly across different sampling regions. In contrast, storage conditions significantly influenced the microbiome and metabolome. Short-term room temperature storage had a minimal effect on the microbiome and metabolome profiles. Sample storage in RNALater showed a significant level of variation in both microbiome and metabolome profiles, independent of the storage or retrieval conditions. The effect of RNALater on the metabolome was stronger than the effect on the microbiome, and individual variability between study participants outweighed the effect of RNALater on the microbiome. We conclude that homogenizing stool samples was critical for metabolomic analysis but not necessary for microbiome analysis. Short-term room temperature storage had a minimal effect on the microbiome and metabolome profiles and is recommended for short-term fecal sample storage. In addition, our study indicates that the use of RNALater as a storage medium of stool samples for microbial and metabolomic analyses is not recommended.

IMPORTANCE The gastrointestinal microbiome and metabolome can provide a new angle to understand the development of health and disease. Stool samples are most frequently used for large-scale cohort studies. Standardized procedures for stool sample handling and storage can be a determining factor for performing microbiome or metabolome studies. In this study, we focused on the effects of stool sampling regions and stool sample storage conditions on variations in the gut microbiome composition and metabolome profile.

The Mycobiome in Health and Disease: Emerging Concepts, Methodologies and Challenges

Fungal disease is an increasingly recognised global clinical challenge associated with high mortality. Early diagnosis of fungal infection remains problematic due to the poor sensitivity and specificity of current diagnostic modalities. Advances in sequencing technologies hold promise in addressing these shortcomings and for improved fungal detection and identification. To translate such emerging approaches into mainstream clinical care will require refinement of current sequencing and analytical platforms, ensuring standardisation and consistency through robust clinical benchmarking and its validation across a range of patient populations. In this state-of-the-art review, we discuss current diagnostic and therapeutic challenges associated with fungal disease and provide key examples where the application of sequencing technologies has potential diagnostic application in assessing the human ‘mycobiome’. We assess how ready access to fungal sequencing may be exploited in broadening our insight into host–fungal interaction, providing scope for clinical diagnostics and the translation of emerging mycobiome research into clinical practice.

Understanding and overcoming the pitfalls and biases of next-generation sequencing (NGS) methods for use in the routine clinical microbiological diagnostic laboratory

Recent advancements in next-generation sequencing (NGS) have provided the foundation for modern studies into the composition of microbial communities. The use of these NGS methods allows for the detection and identification of (‘difficult-to-culture’) microorganisms using a culture-independent strategy. In the field of routine clinical diagnostics however, the application of NGS is currently limited to microbial strain typing for epidemiological purposes only, even though the implementation of NGS for microbial community analysis may yield clinically important information. This lack of NGS implementation is due to many different factors, including issues relating to NGS method standardization and result reproducibility. In this review article, the authors provide a general introduction to the most widely used NGS methods currently available (i.e., targeted amplicon sequencing and shotgun metagenomics) and the strengths and weaknesses of each method is discussed. The focus of the publication then shifts toward 16S rRNA gene NGS methods, which are currently the most cost-effective and widely used NGS methods for research purposes, and are therefore more likely to be successfully implemented into routine clinical diagnostics in the short term. In this respect, the experimental pitfalls and biases created at each step of the 16S rRNA gene NGS workflow are explained, as well as their potential solutions. Finally, a novel diagnostic microbiota profiling platform (‘MYcrobiota’) is introduced, which was developed by the authors by taking into consideration the pitfalls, biases, and solutions explained in this article. The development of the MYcrobiota, and future NGS methodologies, will help pave the way toward the successful implementation of NGS methodologies into routine clinical diagnostics.

'Candidatus Ornithobacterium hominis': insights gained from draft genomes obtained from nasopharyngeal swabs

'Candidatus Ornithobacterium hominis' represents a new member of the Flavobacteriaceae detected in 16S rRNA gene surveys of people from South-East Asia, Africa and Australia. It frequently colonizes the infant nasopharynx at high proportional abundance, and we demonstrate its presence in 42 % of nasopharyngeal swabs from 12-month-old children in the Maela refugee camp in Thailand. The species, a Gram-negative bacillus, has not yet been cultured, but the cells can be identified in mixed samples by fluorescent hybridization. Here, we report seven genomes assembled from metagenomic data, two to improved draft standard. The genomes are approximately 1.9 Mb, sharing 62 % average amino acid identity with the only other member of the genus, the bird pathogen Ornithobacterium rhinotracheale. The draft genomes encode multiple antibiotic-resistance genes, competition factors, Flavobacterium johnsoniae-like gliding motility genes and a homologue of the Pasteurella multocida mitogenic toxin. Intra- and inter-host genome comparison suggests that colonization with this bacterium is both persistent and strain exclusive.

Optimisation of a propidium monoazide based method to determine the viability of microbes in faecal slurries for transplantation

The efficacy of faecal microbiota transplantation (FMT) as a therapeutic intervention may depend on the viability of the microorganisms in faecal slurries (FS) prepared from donor stool. However, determining the viability of these organisms is challenging. Most microorganisms in stool are refractory to culture using standard techniques, and culture-independent PCR-based methods derive signal from both viable and non-viable cells. Propidium monoazide (PMA) treatment has been shown to be effective in preventing PCR amplification of DNA from non-viable bacteria in a range of contexts. However, this methodology can be sensitive to factors such as bacterial load and sample turbidity. We describe the optimisation of a PMA treatment methodology for FS that restricts quantitative PCR-based bacterial enumeration to viable cells. When applied to concentrated FS (10-25% stool content), PMA treatment at 100 μM concentration was ineffective in preventing DNA amplification from heat-killed cells. Efficacy was not significantly improved by doubling the PMA concentration. However, PMA treatment efficacy was improved markedly following 10-fold sample dilution, and was found to be optimal at 100-fold dilution. Substantial reductions in viable bacterial load could be observed following both freeze-thaw and heat-treatment of FS. This method successfully prevented DNA amplification of heat-killed Pseudomonas and Staphylococcus spiked into stool and could reliably determine the proportion of live bacteria and viable E. coli counts present in fresh and heat-treated stool. With appropriate sample dilution, PMA treatment excluded >97% of non-viable cells from amplification in all assays, without significantly affecting the amplification of DNA from viable cells. This method can be applied to optimise sample processing of FMT donor material, and to characterise bacterial viability within faecal samples more widely.

The contribution of respiratory microbiome analysis to a treatable traits model of care

The composition of the airway microbiome in patients with chronic airway diseases, such as severe asthma, chronic obstructive pulmonary disease (COPD), bronchiectasis and cystic fibrosis (CF), has the potential to inform a precision model of clinical care. Patients with these conditions share overlapping disease characteristics, including airway inflammation and airflow limitation. The clinical management of chronic respiratory conditions is increasingly moving away from a one-size-fits-all model based on primary diagnosis, towards care targeting individual disease traits, and is particularly useful for subgroups of patients who respond poorly to conventional therapies. Respiratory microbiome analysis is an important potential contributor to such a 'treatable traits' approach, providing insight into both microbial drivers of airways disease, and the selective characteristics of the changing lower airway environment. We explore the potential to integrate respiratory microbiome analysis into a treatable traits model of clinical care and provide a practical guide to the application and clinical interpretation of respiratory microbiome analysis.

Performing Skin Microbiome Research: A Method to the Madness

Growing interest in microbial contributions to human health and disease has increasingly led investigators to examine the microbiome in both healthy skin and cutaneous disorders, including acne, psoriasis, and atopic dermatitis. The need for common language, effective study design, and validated methods is critical for high-quality standardized research. Features, unique to skin, pose particular challenges when conducting microbiome research. This review discusses microbiome research standards and highlights important factors to consider, including clinical study design, skin sampling, sample processing, DNA sequencing, control inclusion, and data analysis.

Mycobiome in the Lower Respiratory Tract - A Clinical Perspective

Recently the paradigm that the healthy lung is sterile was challenged and it is now believed that the lungs harbor a diverse microbiota also contributing to the pathogenesis of various diseases. Most of the research studies targeting the respiratory microbiome have focused on bacteria and their impact on lung health and lung diseases. Recently, also the mycobiome has gained attention. Lower respiratory tract (LRT) diseases (e.g., cystic fibrosis) and other diseases or conditions (e.g., HIV infection, lung transplantation, and treatment at intensive care units) have been investigated with regard to possible involvement of mycobiome in development or progression of diseases. It has been shown that diversities of mycobiome in the LRT vary in different populations and conditions. It has been proposed that the mycobiome diversity associated with LRT can vary with different stages of diseases. Overall, Candida was the dominant fungal genus in LRT samples. In this review, we summarize the recent findings regarding the human LRT mycobiome from a clinical perspective focussing on characterization of investigated patient groups and healthy controls as well as sampling techniques. From these data, clinical implications for further studies or routine practice are drawn. To obtain clinically relevant answers efforts should be enhanced to collect well characterized and described patient groups as well as healthy individuals for comparative data analysis and to apply thorough sampling techniques. We need to proceed with elucidation of the role of mycobiota in healthy LRT and LRT diseases to hopefully improve patient care.

Tiny microbes, enormous impacts: what matters in gut microbiome studies?

Many factors affect the microbiomes of humans, mice, and other mammals, but substantial challenges remain in determining which of these factors are of practical importance. Considering the relative effect sizes of both biological and technical covariates can help improve study design and the quality of biological conclusions. Care must be taken to avoid technical bias that can lead to incorrect biological conclusions. The presentation of quantitative effect sizes in addition to P values will improve our ability to perform meta-analysis and to evaluate potentially relevant biological effects. A better consideration of effect size and statistical power will lead to more robust biological conclusions in microbiome studies.

Data Mining of Lung Microbiota in Cystic Fibrosis Patients

The major therapeutic strategy used to treat exacerbated cystic fibrosis (CF) is antibiotic treatment. As this approach easily generates antibiotic-resistant strains of opportunistic bacteria, optimized antibiotic therapies are required to effectively control chronic and recurrent bacterial infections in CF patients. A promising future for the proper use of antibiotics is the management of lung microbiota. However, the impact of antibiotic treatments on CF microbiota and vice versa is not fully understood. This study analyzed 718 sputum samples from 18 previous studies to identify differences between CF and uninfected lung microbiota and to evaluate the effects of antibiotic treatments on exacerbated CF microbiota. A reference-based OTU (operational taxonomic unit) picking method was used to combine analyses of data generated using different protocols and platforms. Findings show that CF microbiota had greater richness and lower diversity in the community structure than uninfected control (NIC) microbiota. Specifically, CF microbiota showed higher levels of opportunistic bacteria and dramatically lower levels of commensal bacteria. Antibiotic treatment affected exacerbated CF microbiota notably but only transiently during the treatment period. Limited decrease of the dominant opportunistic bacteria and a dramatic decrease of commensal bacteria were observed during the antibiotic treatment for CF exacerbation. Simultaneously, low abundance opportunistic bacteria were thriving after the antibiotic treatment. The inefficiency of the current antibiotic treatment against major opportunistic bacteria and the detrimental effects on commensal bacteria indicate that the current empiric antibiotic treatment on CF exacerbation should be reevaluated and optimized.

Different next generation sequencing platforms produce different microbial profiles and diversity in cystic fibrosis sputum

BACKGROUND

Cystic fibrosis (CF) is an autosomal recessive disease characterized by recurrent lung infections. Studies of the lung microbiome have shown an association between decreasing diversity and progressive disease. 454 pyrosequencing has frequently been used to study the lung microbiome in CF, but will no longer be supported. We sought to identify the benefits and drawbacks of using two state-of-the-art next generation sequencing (NGS) platforms, MiSeq and PacBio RSII, to characterize the CF lung microbiome. Each has its advantages and limitations.

METHODS

Twelve samples of extracted bacterial DNA were sequenced on both MiSeq and PacBio NGS platforms. DNA was amplified for the V4 region of the 16S rRNA gene and libraries were sequenced on the MiSeq sequencing platform, while the full 16S rRNA gene was sequenced on the PacBio RSII sequencing platform. Raw FASTQ files generated by the MiSeq and PacBio platforms were processed in mothur v1.35.1.

RESULTS

There was extreme discordance in alpha-diversity of the CF lung microbiome when using the two platforms. Because of its depth of coverage, sequencing of the 16S rRNA V4 gene region using MiSeq allowed for the observation of many more operational taxonomic units (OTUs) and higher Chao1 and Shannon indices than the PacBio RSII. Interestingly, several patients in our cohort had Escherichia, an unusual pathogen in CF. Also, likely because of its coverage of the complete 16S rRNA gene, only PacBio RSII was able to identify Burkholderia, an important CF pathogen.

CONCLUSION

When comparing microbiome diversity in clinical samples from CF patients using 16S sequences, MiSeq and PacBio NGS platforms may generate different results in microbial community composition and structure. It may be necessary to use different platforms when trying to correctly identify dominant pathogens versus measuring alpha-diversity estimates, and it would be important to use the same platform for comparisons to minimize errors in interpretation.

Studying the Human Microbiota

There are a range of methodologies available to study the human microbiota, ranging from traditional approaches such as culturing through to state-of-the-art developments in next generation DNA sequencing technologies. The advent of molecular techniques in particular has opened up tremendous new avenues for research, and has galvanised interest in the study of our microbial inhabitants. Given the dazzling array of available options, however, it is important to understand the inherent advantages and limitations of each technique so that the best approach can be employed to address the particular research objective. In this chapter we cover some of the most widely used current techniques in human microbiota research and highlight the particular strengths and caveats associated with each approach.

The lung mycobiome: an emerging field of the human respiratory microbiome

The lung microbiome, which is believed to be stable or at least transient in healthy people, is now considered as a poly-microorganism component contributing to disease pathogenesis. Most research studies on the respiratory microbiome have focused on bacteria and their impact on lung health, but there is evidence that other non-bacterial organisms, comprising the viruses (virome) and fungi (mycobiome), are also likely to play an important role in healthy people as well as in patients. In the last few years, the lung mycobiome (previously named the fungal microbiota or microbiome) has drawn closer attention. There is growing evidence that the lung mycobiome has a significant impact on clinical outcome of chronic respiratory diseases (CRD) such as asthma, chronic obstructive pulmonary disease, cystic fibrosis, and bronchiectasis. Thanks to advances in culture independent methods, especially next generation sequencing, a number of fungi not detected by culture methods have been molecularly identified in human lungs. It has been shown that the structure and diversity of the lung mycobiome vary in different populations (healthy and different diseased individuals) which could play a role in CRD. Moreover, the link between lung mycobiome and different biomes of other body sites, especially the gut, has also been unraveled. By interacting with the bacteriome and/or virome, the respiratory mycobiome appears to be a cofactor in inflammation and in the host immune response, and therefore may contribute to the decline of the lung function and the disease progression. In this review, we report the recent limited explorations of the human respiratory mycobiome, and discuss the mycobiome’s connections with other local microbial communities, as well as the relationships with the different biomes of other body sites. These studies suggest several outlooks for this understudied emerging field, which will certainly call for a renewal of our understanding of pulmonary diseases.