Comparing DADA2 and OTU clustering approaches in studying the bacterial communities of atopic dermatitis

Characterising the Tasmanian devil (Sarcophilus harrisii) pouch microbiome in lactating and non-lactating females

Wildlife harbour a diverse range of microorganisms that affect their health and development. Marsupials are born immunologically naïve and physiologically underdeveloped, with primary development occurring inside a pouch. Secretion of immunological compounds and antimicrobial peptides in the epithelial lining of the female's pouch, pouch young skin, and through the milk, are thought to boost the neonate's immune system and potentially alter the pouch skin microbiome. Here, using 16S rRNA amplicon sequencing, we characterised the Tasmanian devil pouch skin microbiome from 25 lactating and 30 non-lactating wild females to describe and compare across these reproductive stages. We found that the lactating pouch skin microbiome had significantly lower amplicon sequence variant richness and diversity than non-lactating pouches, however there was no overall dissimilarity in community structure between lactating and non-lactating pouches. The top five phyla were found to be consistent between both reproductive stages, with over 85% of the microbiome being comprised of Firmicutes, Proteobacteria, Fusobacteriota, Actinobacteriota, and Bacteroidota. The most abundant taxa remained consistent across all taxonomic ranks between lactating and non-lactating pouch types. This suggests that any potential immunological compounds or antimicrobial peptide secretions did not significantly influence the main community members. Of the more than 16,000 total identified amplicon sequence variants, 25 were recognised as differentially abundant between lactating and non-lactating pouches. It is proposed that the secretion of antimicrobial peptides in the pouch act to modulate these microbial communities. This study identifies candidate bacterial clades on which to test the activity of Tasmanian devil antimicrobial peptides and their role in pouch young protection, which in turn may lead to future therapeutic development for human diseases.

The "Dry-Lab" Side of Food Authentication: Benchmark of Bioinformatic Pipelines for the Analysis of Metabarcoding Data

Next Generation Sequencing Technologies (NGS), particularly metabarcoding, are valuable tools for authenticating foodstuffs and detecting eventual fraudulent practices such as species substitution. This technique, mostly used for the analysis of prokaryotes in several environments (including food), is in fact increasingly applied to identify eukaryotes (e.g., fish, mammals, avian, etc.) in multispecies food products. Besides the "wet-lab" procedures (e.g., DNA extraction, PCR, amplicon purification, etc.), the metabarcoding workflow includes a final "dry-lab" phase in which sequencing data are analyzed using a bioinformatic pipeline (BP). BPs play a crucial role in the accuracy, reliability, and interpretability of the metabarcoding results. Choosing the most suitable BP for the analysis of metabarcoding data could be challenging because it might require greater informatics skills than those needed in standard molecular analysis. To date, studies comparing BPs for metabarcoding data analysis in foodstuff authentication are scarce. In this study, we compared the data obtained from two previous studies in which fish burgers and insect-based products were authenticated using a customizable, ASV-based, and command-line interface BP (BP1) by analyzing the same data with a customizable but OTU-based and graphical user interface BP (BP2). The final sample compositions were compared statistically. No significant difference in sample compositions was highlighted by applying BP1 and BP2. However, BP1 was considered as more user-friendly than BP2 with respect to data analysis streamlining, cost of analysis, and computational time consumption. This study can provide useful information for researchers approaching the bioinformatic analysis of metabarcoding data for the first time. In the field of food authentication, an effective and efficient use of BPs could be especially useful in the context of official controls performed by the Competent Authorities and companies' self-control in order to detect species substitution and counterfeit frauds.

Gut microbiota dysbiosis in Parkinson disease: A systematic review and pooled analysis

BACKGROUND AND PURPOSE

The role of the gut microbiome in the pathogenesis of Parkinson disease (PD) is under intense investigation, and the results presented are still very heterogeneous. These discrepancies arise not only from the highly heterogeneous pathology of PD, but also from widely varying methodologies at all stages of the workflow, from sampling to final statistical analysis. The aim of the present work is to harmonize the workflow across studies to reduce the methodological heterogeneity and to perform a pooled analysis to account for other sources of heterogeneity.

METHODS

We performed a systematic review to identify studies comparing the gut microbiota of PD patients to healthy controls. A workflow was designed to harmonize processing across all studies from bioinformatics processing to final statistical analysis using a Bayesian random-effects meta-analysis based on individual patient-level data.

RESULTS

The results show that harmonizing workflows minimizes differences between statistical methods and reveals only a small set of taxa being associated with the pathogenesis of PD. Increased shares of the genera Akkermansia and Bifidobacterium and decreased shares of the genera Roseburia and Faecalibacterium were most characteristic for PD-associated microbiota.

CONCLUSIONS

Our study summarizes evidence that reduced levels of butyrate-producing taxa in combination with possible degradation of the mucus layer by Akkermansia may promote intestinal inflammation and reduced permeability of the gut mucosal layer. This may allow potentially pathogenic metabolites to transit and enter the enteric nervous system.

A simplified bacterial community found within the epidermis than at the epidermal surface of atopic dermatitis patients and healthy controls

There has been considerable research into the understanding of the healthy skin microbiome. Similarly, there is also a considerable body of research into whether specific microbes contribute to skin disorders, with atopic dermatitis (AD) routinely linked to increased Staphylococcus aureus (S. aureus) colonisation. In this study, the epidermal surface of participants was sampled using swabs, while serial tape-stripping (35 tapes) was performed to sample through the stratum corneum. Samples were taken from AD patients and healthy controls, and the bacterial communities were profiled by metabarcoding the universal V3-V4 16S rRNA region. Results show that the majority of bacterial richness is located within the outermost layers of the stratum corneum, however there were many taxa that were found almost exclusively at the very outermost layer of the epidermis. We therefore hypothesise that tape-stripping can be performed to investigate the 'core microbiome' of participants by removing environmental contaminants. Interestingly, significant community variation between AD patients and healthy controls was only observable at the epidermal surface, yet a number of individual taxa were found to consistently differ with AD status across the entire epidermis (i.e. both the epidermal surface and within the epidermis). Sampling strategy could therefore be tailored dependent on the hypothesis, with sampling for forensic applications best performed using surface swabs and outer tapes, while profiling sub-surface communities may better reflect host genome and immunological status.

Evolving approaches to profiling the microbiome in skin disease

Despite its harsh and dry environment, human skin is home to diverse microbes, including bacteria, fungi, viruses, and microscopic mites. These microbes form communities that may exist at the skin surface, deeper skin layers, and within microhabitats such as the hair follicle and sweat glands, allowing complex interactions with the host immune system. Imbalances in the skin microbiome, known as dysbiosis, have been linked to various inflammatory skin disorders, including atopic dermatitis, acne, and psoriasis. The roles of abundant commensal bacteria belonging to Staphylococcus and Cutibacterium taxa and the fungi Malassezia, where particular species or strains can benefit the host or cause disease, are increasingly appreciated in skin disorders. Furthermore, recent research suggests that the interactions between microorganisms and the host's immune system on the skin can have distant and systemic effects on the body, such as on the gut and brain, known as the "skin-gut" or "skin-brain" axes. Studies on the microbiome in skin disease have typically relied on 16S rRNA gene sequencing methods, which cannot provide accurate information about species or strains of microorganisms on the skin. However, advancing technologies, including metagenomics and other functional 'omic' approaches, have great potential to provide more comprehensive and detailed information about the skin microbiome in health and disease. Additionally, inter-species and multi-kingdom interactions can cause cascading shifts towards dysbiosis and are crucial but yet-to-be-explored aspects of many skin disorders. Better understanding these complex dynamics will require meta-omic studies complemented with experiments and clinical trials to confirm function. Evolving how we profile the skin microbiome alongside technological advances is essential to exploring such relationships. This review presents the current and emerging methods and their findings for profiling skin microbes to advance our understanding of the microbiome in skin disease.

Pyrethroids exposure alters the community and function of the internal microbiota in Aedes albopictus

Large amounts of insecticides bring selection pressure and then develop insecticide resistance in Aedes albopictus. This study demonstrated for the first time the effect of pyrethroid exposure on the internal microbiota in Ae. albopictus. 36, 48, 57 strains of virgin adult Ae. albopictus were exposed to the pyrethroids deltamethrin (Dme group), β-cypermethrin (Bcy group), and cis-permethrin (Cper group), respectively, with n-hexane exposure (Hex group) as the controls (n = 36). The internal microbiota community and functions were analyzed based on the metagenomic analysis. The analysis of similarity (ANOSIM) results showed that the Hex/Bcy (p = 0.001), Hex/Cper (p = 0.006), Hex/Dme (p = 0.001) groups were well separated, and the internal microbes of Ae. albopictus vary in the composition and functions depending on the type of pyrethroid insecticide they are applied. Four short chain fatty acid-producing genera, Butyricimonas, Prevotellaceae, Anaerococcus, Pseudorhodobacter were specifically absent in the pyrethroid-exposed mosquitoes. Morganella and Streptomyces were significantly enriched in cis-permethrin-exposed mosquitoes. Wolbachia and Chryseobacterium showed significant enrichment in β-cypermethrin-exposed mosquitoes. Pseudomonas was significantly abundant in deltamethrin-exposed mosquitoes. The significant proliferation of these bacteria may be closely related to insecticide metabolism. Our study recapitulated a specifically enhanced metabolic networks relevant to the exposure to cis-permethrin and β-cypermethrin, respectively. Benzaldehyde dehydrogenase (EC 1.2.1.28), key enzyme in aromatic compounds metabolism, was detected enhanced in cis-permethrin and β-cypermethrin exposed mosquitoes. The internal microbiota metabolism of aromatic compounds may be important influencing factors for pyrethroid resistance. Future work will be needed to elucidate the specific mechanisms by which mosquito microbiota influences host resistance and vector ability.

Benchmarking Bioinformatic Tools for Amplicon-Based Sequencing of Norovirus

In order to survey noroviruses in our environment, it is essential that both wet-lab and computational methods are fit for purpose. Using a simulated sequencing data set, denoising-based (DADA2, Deblur and USEARCH-UNOISE3) and clustering-based pipelines (VSEARCH and FROGS) were compared with respect to their ability to represent composition and sequence information. Open source classifiers (Ribosomal Database Project [RDP], BLASTn, IDTAXA, QIIME2 naive Bayes, and SINTAX) were trained using three different databases: a custom database, the NoroNet database, and the Human calicivirus database. Each classifier and database combination was compared from the perspective of their classification accuracy. VSEARCH provides a robust option for analyzing viral amplicons based on composition analysis; however, all pipelines could return OTUs with high similarity to the expected sequences. Importantly, pipeline choice could lead to more false positives (DADA2) or underclassification (FROGS), a key aspect when considering pipeline application for source attribution. Classification was more strongly impacted by the classifier than the database, although disagreement increased with norovirus GII.4 capsid variant designation. We recommend the use of the RDP classifier in conjunction with VSEARCH; however, maintenance of the underlying database is essential for optimal use. IMPORTANCE In benchmarking bioinformatic pipelines for analyzing high-throughput sequencing (HTS) data sets, we provide method standardization for bioinformatics broadly and specifically for norovirus in situations for which no officially endorsed methods exist at present. This study provides recommendations for the appropriate analysis and classification of norovirus amplicon HTS data and will be widely applicable during outbreak investigations.

PURC Provides Improved Sequence Inference for Polyploid Phylogenetics and Other Manifestations of the Multiple-Copy Problem

Inferring the true biological sequences from amplicon mixtures remains a difficult bioinformatics problem. The traditional approach is to cluster sequencing reads by similarity thresholds and treat the consensus sequence of each cluster as an "operational taxonomic unit" (OTU). Recently, this approach has been improved by model-based methods that correct PCR and sequencing errors in order to infer "amplicon sequence variants" (ASVs). To date, ASV approaches have been used primarily in metagenomics, but they are also useful for determining homeologs in polyploid organisms. To facilitate the usage of ASV methods among polyploidy researchers, we incorporated ASV inference alongside OTU clustering in PURC v2.0, a major update to PURC (Pipeline for Untangling Reticulate Complexes). In addition, PURC v2.0 features faster demultiplexing than the original version and has been updated to be compatible with Python 3. In this chapter we present results indicating that using the ASV approach is more likely to infer the correct biological sequences in comparison to the earlier OTU-based PURC and describe how to prepare sequencing data, run PURC v2.0 under several different modes, and interpret the output.

In-Silico Functional Metabolic Pathways Associated to Chlamydia trachomatis Genital Infection

The advent of high-throughput technologies, such as 16s rDNA sequencing, has significantly contributed to expanding our knowledge of the microbiota composition of the genital tract during infections such as Chlamydia trachomatis. The growing body of metagenomic data can be further exploited to provide a functional characterization of microbial communities via several powerful computational approaches. Therefore, in this study, we investigated the predicted metabolic pathways of the cervicovaginal microbiota associated with C. trachomatis genital infection in relation to the different Community State Types (CSTs), via PICRUSt2 analysis. Our results showed a more rich and diverse mix of predicted metabolic pathways in women with a CST-IV microbiota as compared to all the other CSTs, independently from infection status. C. trachomatis genital infection further modified the metabolic profiles in women with a CST-IV microbiota and was characterized by increased prevalence of the pathways for the biosynthesis of precursor metabolites and energy, biogenic amino-acids, nucleotides, and tetrahydrofolate. Overall, predicted metabolic pathways might represent the starting point for more precisely designed future metabolomic studies, aiming to investigate the actual metabolic pathways characterizing C. trachomatis genital infection in the cervicovaginal microenvironment.

Altered Maturation of the Skin Microbiome in Infants with Atopic Dermatitis

The aim of this study was to investigate the early-life development of the skin microbiome in atopic dermatitis. Nineteen infants with atopic dermatitis and 19 healthy infants were evaluated 3 times, at 3 months intervals, within the first 30 months of life. Tape-strips were collected from volar forearms, cheeks, and eczema lesions, and the skin microbiome was assessed by 16S rRNA sequencing. Both the community structure and richness of the skin microbiome of infants with atopic dermatitis differed significantly from that of healthy infants, with greater richness in healthy infants. For infants with atopic dermatitis, the community composition was not dominated by Staphylococci. For healthy infants, community composition and richness correlated significantly with age, while such a pattern was not revealed in infants with atopic dermatitis. This suggests a slower maturation of the skin microbiome in atopic dermatitis, which precedes the staphylococcal predominance observed in older children and adults.

Airborne fungal and bacterial microbiome in classrooms of elementary schools during the COVID-19 pandemic period: Effects of school disinfection and other environmental factors

The aim of the study was to examine the effects of environmental factors including disinfection on airborne microbiome during the coronavirus disease 2019 pandemic, we evaluated indoor and outdoor air collected from 19 classrooms regularly disinfected. Extracted bacterial and fungal DNA samples were sequenced using the Illumina MiSeq™ platform. Using bacterial DNA copy number concentrations from qPCR analysis, multiple linear regressions including environmental factors as predictors were performed. Microbial diversity and community composition were evaluated. Classrooms disinfected with spray ≤1 week before sampling had lower bacterial DNA concentration (3116 DNA copies/m³ ) than those >1 week (5003 copies/m³ ) (p-values = 0.06). The bacterial DNA copy number concentration increased with temperature and was higher in classrooms in coastal than inland cities (p-values <0.01). Bacterial diversity in outdoor air was higher in coastal than inland cities while outdoor fungal diversity was higher in inland than coastal cities. These outdoor microbiomes affected classroom microbial diversity but bacterial community composition at the genus level in occupied classrooms were similar between coastal and inland cities. Our findings emphasize that environmental conditions including disinfection, climate, and school location are important factors in shaping classroom microbiota. Yet, further research is needed to understand the effects of modified microbiome by disinfection on occupants' health.

The Role of the Gut Microbiota in the Effects of Early-Life Stress and Dietary Fatty Acids on Later-Life Central and Metabolic Outcomes in Mice

Early-life stress (ELS) leads to increased vulnerability for mental and metabolic disorders. We have previously shown that a low dietary ω-6/ω-3 polyunsaturated fatty acid (PUFA) ratio protects against ELS-induced cognitive impairments. Due to the importance of the gut microbiota as a determinant of long-term health, we here study the impact of ELS and dietary PUFAs on the gut microbiota and how this relates to the previously described cognitive, metabolic, and fatty acid profiles. Male mice were exposed to ELS via the limited bedding and nesting paradigm (postnatal day (P)2 to P9 and to an early diet (P2 to P42) with an either high (15) or low (1) ω-6 linoleic acid to ω-3 alpha-linolenic acid ratio. 16S rRNA was sequenced and analyzed from fecal samples at P21, P42, and P180. Age impacted α- and β-diversity. ELS and diet together predicted variance in microbiota composition and affected the relative abundance of bacterial groups at several taxonomic levels in the short and long term. For example, age increased the abundance of the phyla Bacteroidetes, while it decreased Actinobacteria and Verrucomicrobia; ELS reduced the genera RC9 gut group and Rikenella, and the low ω-6/ω-3 diet reduced the abundance of the Firmicutes Erysipelotrichia. At P42, species abundance correlated with body fat mass and circulating leptin (e.g., Bacteroidetes and Proteobacteria taxa) and fatty acid profiles (e.g., Firmicutes taxa). This study gives novel insights into the impact of age, ELS, and dietary PUFAs on microbiota composition, providing potential targets for noninvasive (nutritional) modulation of ELS-induced deficits. IMPORTANCE Early-life stress (ELS) leads to increased vulnerability to develop mental and metabolic disorders; however, the biological mechanisms leading to such programming are not fully clear. Increased attention has been given to the importance of the gut microbiota as a determinant of long-term health and as a potential target for noninvasive nutritional strategies to protect against the negative impact of ELS. Here, we give novel insights into the complex interaction between ELS, early dietary ω-3 availability, and the gut microbiota across ages and provide new potential targets for (nutritional) modulation of the long-term effects of the early-life environment via the microbiota.

Alterations in co-abundant bacteriome in colorectal cancer and its persistence after surgery: a pilot study

There is growing interest in the role of gut microbiome in colorectal cancer (CRC), ranging from screening to disease recurrence. Our study aims to identify microbial markers characteristic of CRC and to examine if changes in bacteriome persist after surgery. Forty-nine fecal samples from 25 non-cancer (NC) individuals and 12 CRC patients, before and 6-months after surgery, were collected for analysis by bacterial 16S rRNA gene sequencing. Bacterial richness and diversity were reduced, while pro-carcinogenic bacteria such as Bacteroides fragilis and Odoribacter splanchnicus were increased in CRC patients compared to NC group. These differences were no longer observed after surgery. Comparison between pre-op and post-op CRC showed increased abundance of probiotic bacteria after surgery. Concomitantly, bacteria associated with CRC progression were observed to have increased after surgery, implying persistent dysbiosis. In addition, functional pathway predictions based on the bacterial 16S rRNA gene data showed that various pathways were differentially enriched in CRC compared to NC. Microbiome signatures characteristic of CRC comprise altered bacterial composition. Elements of these dysbiotic signatures persists even after surgery, suggesting possible field-change in remnant non-diseased colon. Future studies should involve a larger sample size with microbiome data collected at multiple time points after surgery to examine if these dysbiotic patterns truly persist and also correlate with disease outcomes.

Microbiome Analysis via OTU and ASV-Based Pipelines-A Comparative Interpretation of Ecological Data in WWTP Systems

Linking community composition and ecosystem function via the cultivation-independent analysis of marker genes, e.g., the 16S rRNA gene, is a staple of microbial ecology and dependent disciplines. The certainty of results, independent of the bioinformatic handling, is imperative for any advances made within the field. In this work, thermophilic anaerobic co-digestion experimental data, together with primary and waste-activated sludge prokaryotic community data, were analyzed with two pipelines that apply different principles when dealing with technical, sequencing, and PCR biases. One pipeline (VSEARCH) employs clustering methods, generating individual operational taxonomic units (OTUs), while the other (DADA2) is based on sequencing error correction algorithms and generates exact amplicon sequence variants (ASVs). The outcomes of both pipelines were compared within the framework of ecological-driven data analysis. Both pipelines provided comparable results that would generally allow for the same interpretations. Yet, the two approaches also delivered community compositions that differed between 6.75% and 10.81% between pipelines. Inconsistencies were also observed linked to biologically driven variability in the samples, which affected the two pipelines differently. These pipeline-dependent differences in taxonomic assignment could lead to different conclusions and interfere with any downstream analysis made for such mis- or not-identified species, e.g., network analysis or predictions of their respective ecosystem service.

Temporal and Spatial Variation of the Skin-Associated Bacteria from Healthy Participants and Atopic Dermatitis Patients

Several factors have been shown to influence the composition of the bacterial communities inhabiting healthy skin, with variation between different individuals, differing skin depths, and body locations (spatial-temporal variation). Atopic dermatitis (AD) is a chronic skin disease also affecting the skin-associated bacterial communities. While the effects of AD have been studied on these processes individually, few have considered how AD disrupts the spatial-temporal variation of the skin bacteria as a whole (i.e., considered these processes simultaneously). Here, we characterized the skin-associated bacterial communities of healthy volunteers and lesional and nonlesional skin of AD patients by metabarcoding the universal V3-V4 16S rRNA region from tape strip skin samples. We quantified the spatial-temporal variation (interindividual variation, differing skin depths, multiple time points) of the skin-associated bacteria within healthy controls and AD patients, including the relative change induced by AD in each. Interindividual variation correlated with the bacterial community far more strongly than any other factors followed by skin depth and then AD status. There was no significant temporal variation found within either AD patients or healthy controls. The bacterial community was found to vary markedly according to AD severity, and between patients without and with filaggrin mutations. Therefore, future studies may benefit from sampling subsurface epidermal communities and considering AD severity and the host genome in understanding the role of the skin bacterial community within AD pathogenesis rather than considering AD as a presence-absence disorder. IMPORTANCE The bacteria associated with human skin may influence skin barrier function and the immune response. Previous studies have attempted to understand the factors that regulate the skin bacteria, characterizing the spatial-temporal variation of the skin bacteria within unaffected skin. Here, we quantified the effect of AD on the skin bacteria on multiple spatial-temporal factors simultaneously. Although significant community variation between healthy controls and AD patients was observed, the effects of AD on the overall bacterial community were relatively low compared to other measured factors. Results here suggest that changes in specific taxa rather than wholesale changes in the skin bacteria are associated with mild to moderate AD. Further studies would benefit from incorporating the complexity of AD into models to better understand the condition, including AD severity and the host genome, alongside microbial composition.

City-Scale Meta-Analysis of Indoor Airborne Microbiota Reveals that Taxonomic and Functional Compositions Vary with Building Types

Currently, there is a lack of understanding on the variations of the indoor airborne microbiotas of different building types within a city, and how operational taxonomic unit (OTU)- and amplicon sequence variant (ASV)-based analyses of the 16S rRNA gene sequences affect interpretation of the indoor airborne microbiota results. Therefore, in this study, the indoor airborne bacterial microbiotas between commercial buildings, residences, and subways within the same city were compared using both OTU- and ASV-based analytic methods. Our findings suggested that indoor airborne bacterial microbiota compositions were significantly different between building types regardless of the bioinformatics method used. The processes of ecological drift and random dispersal consistently played significant roles in the assembly of the indoor microbiota across building types. Abundant taxa tended to be more centralized in the correlation network of each building type, highlighting their importance. Taxonomic changes between the microbiotas of different building types were also linked to changes in their inferred metabolic function capabilities. Overall, the results imply that customized strategies are necessary to manage indoor airborne bacterial microbiotas for each building type or even within each specific building.

Nutritional and ecological perspectives of the interrelationships between diet and the gut microbiome in multiple sclerosis: Insights from marmosets

Studies in experimental autoimmune encephalomyelitis (EAE), the animal model of multiple sclerosis, have shown potential links between diet components, microbiome composition, and modulation of immune responses. In this review, we reanalyze and discuss findings in an outbred marmoset EAE model in which a yogurt-based dietary supplement decreased disease frequency and severity. We show that although diet has detectable effects on the fecal microbiome, microbiome changes are more strongly associated with the EAE development. Using an ecological framework, we further show that the dominant factors influencing the gut microbiota were marmoset sibling pair and experimental time point. These findings emphasize challenges in assigning cause-and-effect relationships in studies of diet-microbiome-host interactions and differentiating the diet effects from other environmental, stochastic, and host-related factors. We advocate for animal experiments to be designed to allow causal inferences of the microbiota's role in pathology while considering the complex ecological processes that shape microbial communities.