UNLABELLED: Contact with environmental microbial communities primes the human immune system. Factors determining the distribution of microorganisms, such as dispersal, are thus important for human health. Here, we used the relative number of bacteria shared between environmental and human samples as a measure of bacterial dispersal and studied these associations with living environment and lifestyles. We analyzed amplicon sequence variants (ASVs) of the V4 region of 16S rDNA gene from 347 samples of doormat dust as well as samples of saliva, skin swabs, and feces from 53 elderly people in urban and rural areas in Finland at three timepoints. We first enumerated the ASVs shared between doormat and one of the human sample types (i.e., saliva, skin swab, or feces) of each individual subject and calculated the shared ASVs as a proportion of all ASVs in the given sample type of that individual. We observed that the patterns for the proportions of shared ASVs differed among seasons and human sample type. In skin samples, there was a negative association between the proportion of shared ASVs and the coverage of built environment (a proxy for degree of urbanization), whereas in saliva data, this association was positive. We discuss these findings in the context of differing species pools in urban and rural environments. IMPORTANCE: Understanding how environmental microorganisms reach and interact with humans is a key question when aiming to increase human contacts with natural microbiota. Few methods are suitable for studying microbial dispersal at relatively large spatial scales. Thus, we tested an indirect method and studied patterns of bacterial taxa that are shared between humans and their living environment.

• Keywords
• bacteria, biodiversity hypothesis, dispersal, hygiene hypothesis, land cover,
• MeSH
• Bacteria * classification   genetics   isolation & purification   MeSH
• DNA, Bacterial genetics   MeSH
• Feces * microbiology   MeSH
• Skin microbiology   MeSH
• Humans MeSH
• Urban Population MeSH
• Environmental Microbiology MeSH
• Microbiota * MeSH
• Dust analysis   MeSH
• RNA, Ribosomal, 16S * genetics   MeSH
• Aged, 80 and over MeSH
• Aged MeSH
• Saliva * microbiology   MeSH
• Rural Population MeSH
• Check Tag
• Humans MeSH
• Male MeSH
• Aged, 80 and over MeSH
• Aged MeSH
• Female MeSH
• Publication type
• Journal Article MeSH
• Geographicals
• Finland MeSH
• Names of Substances
• DNA, Bacterial MeSH
• Dust MeSH
• RNA, Ribosomal, 16S * MeSH

A resilient immune system is characterized by its capacity to respond appropriately to challenges, such as infections, and it is crucial in vaccine response. Here we report a paired randomized intervention-control trial in which we evaluated the effect of microbially rich soil on immune resilience and pneumococcal vaccine response. Twenty-five age and sex matched pairs of volunteers were randomized to intervention and control groups. The intervention group rubbed hands three times a day in microbially rich soil until participants received a pneumococcal vaccine on day 14. Vaccine response, skin and gut bacteriome and blood cytokine levels were analyzed on days 0, 14 and 35. Peripheral blood mononuclear cells (PBMCs) were stimulated with vaccine components and autoclaved soil for cytokine production. Commensal bacterial community shifted only in the intervention group during the 14-day intervention period. When PBMCs collected on day 14 before the vaccination were stimulated with the vaccine components, IFN-y production increased in the intervention but not in the control group. On day 35, vaccination induced a robust antibody response in both groups. In parallel, gut bacterial community was associated with TGF-β plasma levels and TGF-β decrease in plasma was lower in the intervention group. The results indicate that exposure to microbially rich soil can modulate the cell-mediated immunity to components in pneumococcal vaccine.

• MeSH
• Immunity, Cellular * MeSH
• Cytokines metabolism   blood   MeSH
• Adult MeSH
• Skin * immunology   microbiology   MeSH
• Leukocytes, Mononuclear * immunology   metabolism   MeSH
• Middle Aged MeSH
• Humans MeSH
• Microbiota immunology   MeSH
• Pneumococcal Infections prevention & control   immunology   MeSH
• Pneumococcal Vaccines * immunology   administration & dosage   MeSH
• Soil Microbiology MeSH
• Gastrointestinal Microbiome immunology   MeSH
• Vaccination MeSH
• Check Tag
• Adult MeSH
• Middle Aged MeSH
• Humans MeSH
• Male MeSH
• Female MeSH
• Publication type
• Journal Article MeSH
• Randomized Controlled Trial MeSH
• Names of Substances
• Cytokines MeSH
• Pneumococcal Vaccines * MeSH

Nowadays, when we are facing several strict regulations, the question arises - does higher strictness lead to the desired results? This study addresses the fact that less research attention has focused on the effects of environmental policy stringency (EPS) on perceived health expressing quality of life, and on green international cooperation. In addition, previous research has provided rather mixed results on the impact of EPS on green innovation. Therefore, we fill an interesting research gap and help better understand the relationship between market-based and non-market-based EPS, perceived health, green innovations, and green international cooperation in OECD (Organization for Economic Co-operation and Development) countries. Using three complementary databases provided by OECD, Eurostat, and the World Bank and the classical linear regression model, we confirm hypotheses that strong market-based EPS and green international cooperation have positive effects on perceived health. Surprisingly, contrary to the findings of prior research, we do not confirm the positive effects of market-based and non-market-based EPS on green international cooperation. This study contributes to the literature on the Porter hypothesis, technological collaborations in green technological development, and environmental innovation theory. In addition, this study provides several practical implications for policymakers across OECD countries.

• Keywords
• Environmental policy stringency, International collaboration, Patents, Perceived health, Sustainable development,
• Publication type
• Journal Article MeSH

The metagenomic data presented in this article are related to the published research of "A Placebo-controlled double-blinded test of the biodiversity hypothesis of immune-mediated diseases: Environmental microbial diversity elicits changes in cytokines and increase in T regulatory cells in young children" This database contains 16S ribosomal RNA (rRNA) metagenomics of sandbox sand and skin and gut microbiota of children in the intervention and placebo daycares. In intervention daycares, children aged 3-5 years were exposed to playground sand enriched with microbially diverse soil. In placebo daycares, children were exposed to visually similar as in intervention daycares, but microbially poor sand colored with peat. Sand, skin and gut metagenomics were analyzed at baseline and after 14 and 28 days of intervention by high throughput sequencing of bacterial 16S rRNA gene on the Illumina MiSeq platform. This dataset shows how skin bacterial community composition, including classes Gammaproteobacteria and Bacilli, changed, and how the relative abundance of over 30 bacterial genera shifted on the skin of children in the intervention treatment, while no shifts occurred in the placebo group.

• Keywords
• 16s rRNA metagenome, Biodiversity, Children, Gut bacteria, Human commensal microbiota, Placebo, Skin bacteria,
• Publication type
• Journal Article MeSH

According to the hygiene and biodiversity hypotheses, increased hygiene levels and reduced contact with biodiversity can partially explain the high prevalence of immune-mediated diseases in developed countries. A disturbed commensal microbiota, especially in the gut, has been linked to multiple immune-mediated diseases. Previous studies imply that gut microbiota composition is associated with the everyday living environment and can be modified by increasing direct physical exposure to biodiverse materials. In this pilot study, the effects of rural-second-home tourism were investigated on the gut microbiota for the first time. Rural-second-home tourism, a popular form of outdoor recreation in Northern Europe, North America, and Russia, has the potential to alter the human microbiota by increasing exposure to nature and environmental microbes. The hypotheses were that the use of rural second homes is associated with differences in the gut microbiota and that the microbiota related to health benefits are more diverse or common among the rural-second-home users. Based on 16S rRNA Illumina MiSeq sequencing of stool samples from 10 urban elderly having access and 15 lacking access to a rural second home, the first hypothesis was supported: the use of rural second homes was found to be associated with lower gut microbiota diversity and RIG-I-like receptor signaling pathway levels. The second hypothesis was not supported: health-related microbiota were not more diverse or common among the second-home users. The current study encourages further research on the possible health outcomes or causes of the observed microbiological differences. Activities and diet during second-home visits, standard of equipment, surrounding environment, and length of the visits are all postulated to play a role in determining the effects of rural-second-home tourism on the gut microbiota.

• Keywords
• cottage, elderly, fecal microbiota, gut microbiota, immune-mediated diseases, outdoor recreation, rural areas, second home, stool sample,
• MeSH
• Humans MeSH
• Microbiota * MeSH
• Pilot Projects MeSH
• RNA, Ribosomal, 16S genetics   MeSH
• Aged MeSH
• Check Tag
• Humans MeSH
• Aged MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Geographicals
• Europe MeSH
• Finland MeSH
• Russia MeSH
• North America MeSH
• Names of Substances
• RNA, Ribosomal, 16S MeSH

The human microbiome has emerged as a central research topic in human biology and biomedicine. Current microbiome studies generate high-throughput omics data across different body sites, populations, and life stages. Many of the challenges in microbiome research are similar to other high-throughput studies, the quantitative analyses need to address the heterogeneity of data, specific statistical properties, and the remarkable variation in microbiome composition across individuals and body sites. This has led to a broad spectrum of statistical and machine learning challenges that range from study design, data processing, and standardization to analysis, modeling, cross-study comparison, prediction, data science ecosystems, and reproducible reporting. Nevertheless, although many statistics and machine learning approaches and tools have been developed, new techniques are needed to deal with emerging applications and the vast heterogeneity of microbiome data. We review and discuss emerging applications of statistical and machine learning techniques in human microbiome studies and introduce the COST Action CA18131 "ML4Microbiome" that brings together microbiome researchers and machine learning experts to address current challenges such as standardization of analysis pipelines for reproducibility of data analysis results, benchmarking, improvement, or development of existing and new tools and ontologies.

• Keywords
• ML4Microbiome, biomarker identification, machine learning, microbiome, personalized medicine,
• Publication type
• Journal Article MeSH