Urban Aerobiome and Effects on Human Health: A Systematic Review and Missing Evidence

Urban air pollutants are a major public health concern and include biological matters which composes about 25% of the atmospheric aerosol particles. Airborne microorganisms were traditionally characterized by culture-based methods recognizing just 1.5–15.3% of the total bacterial diversity that was evaluable by genome signature in the air environment (aerobiome). Despite the large number of exposed people, urban aerobiomes are still weakly described even if recently advanced literature has been published. This paper aims to systematically review the state of knowledge on the urban aerobiome and human health effects. A total of 24 papers that used next generation sequencing (NGS) techniques for characterization and comprised a seasonal analysis have been included. A core of Proteobacteria, Actinobacteria, Firmicutes, and Bacteroides and various factors that influenced the community structure were detected. Heterogenic methods and results were reported, for both sampling and aerobiome diversity analysis, highlighting the necessity of in-depth and homogenized assessment thus reducing the risk of bias. The aerobiome can include threats for human health, such as pathogens and resistome spreading; however, its diversity seems to be protective for human health and reduced by high levels of air pollution. Evidence of the urban aerobiome effects on human health need to be filled up quickly for urban public health purposes

The Interaction among Microbiota, Epigenetic Regulation, and Air Pollutants in Disease Prevention

open6noEnvironmental pollutants can influence microbiota variety, with important implications for the general wellbeing of organisms. In subjects at high-risk of cancer, gut, and lung microbiota are distinct from those of low-risk subjects, and disease progression is associated with microbiota alterations. As with many inflammatory diseases, it is the combination of specific host and environmental factors in certain individuals that provokes disease outcomes. The microbiota metabolites influence activity of epigenetic enzymes. The knowledge of the mechanisms of action of environmental pollution now includes not only the alteration of the gut microbiota but also the interaction between different human microbiota niches such as the lung–gut axis. The epigenetic regulations can reprogram differentiated cells in response to environmental changes. The microbiota can play a major role in the progression and suppression of several epigenetic diseases. Accordingly, the maintenance of a balanced microbiota by monitoring the environmental stimuli provides a novel preventive approach for disease prevention. Metagenomics technologies can be utilized to establish new mitigation approaches for diseases induced by polluted environments. The purpose of this review is to examine the effects of particulate matter exposure on the progression of disease outcomes as related to the alterations of gut and lung microbial communities and consequent epigenetic modificationsopenAlessandra Pulliero, Deborah Traversi, Elena Franchitti, Martina Barchitta, Alberto Izzotti, Antonella AgodiPulliero, Alessandra; Traversi, Deborah; Franchitti, Elena; Barchitta, Martina; Izzotti, Alberto; Agodi, Antonell

Analyses of Methanogenic Population as Key Indicator for Anaerobic Digestion: A Case-Study in the Organic Fraction of Municipal Solid Waste Treatment

Purpose The anaerobic digestion of the organic fraction of municipal solid waste (OFMSW) is a treatment biologically optimizable. The analysis of the microbial balance within the digester allows not only to describe and improve the efficiency of the system but also to foresee potential variations after biochemical interventions. This work aims to highlight methanogenic population variations in two similar parallel digesters to identify bio-indicators for digestion performance after the inclusion of an additive. Methods The analysed industrial case study involved the two parallel, pilot-scale, bio-digesters of ACEA Pinerolese Industriale. They had analogous design and fed by the same OFMSW except for an additive inclusion. The analyses by qRT-PCR, on both bio-digesters, have been performed to determine an impact of the additive on the growth and metabolic activity of total methanogens, Methanosarcina spp., Methanocorpuscolum spp., and Methanospirillus spp. Results Collected data showed that the addition of biopolymers extracted from compost produced both total methanogens and Methanosarcina decrease (7.67 vs. 7.48 and 6.05 vs. 5.69 Log gene copies/mL sludge respectively, T-test p < 0.01) affecting slightly the methane yield (-8%). Methanosarcina was the highest expressed methanogen; however, the results suggested the involvement of a highly complex and heterogeneous methanogen community. Conclusions Total methanogens and active Methanosarcina modulations are able to highlight major bio-methane production even if their shift is slight. Globally only 3–4% of the present and 12–13% of the active methanogens were described. However, biological approach can supply a proxy of production performance of the digester also concerning the feeding peculiarities

Gut microbiota, behavior, and nutrition after type 1 diabetes diagnosis: A longitudinal study for supporting data in the metabolic control

Introduction: Type 1 diabetes (T1D) risk involves genetic susceptibility but also epigenetics, environment, and behaviors. Appropriate metabolic control, especially quickly after the diagnosis, is crucial for the patient quality of life. Methods: This study aimed to produce a quantitative comparison of the behavior, nutrition habits, and gut microbiota composition between the onset and the 1-year follow-up in 35 children with T1D. Results and discussion: At follow-up, with the metabolic control, many parameters improved significantly, with respect to the onset, such as glycated hemoglobin (-19%), body mass index (BMI), and also nutritional behaviors, such as normal calorie intake (+6%), carbohydrate intake (-12%), extra portion request (-4%), and meals distribution during the day. Moreover, glycated hemoglobin decrement correlated with both total and rapid absorption carbohydrate intake (Spearman's rho = 0.288, 95% CI 0.066-0.510, p = 0.013), showing as the nutritional behavior supported the insulin therapy efficiency. The next-generation sequencing (NGS) analysis of microbiota revealed abundance differences for Ruminococcus bromii and Prevotella copri (higher at onset, p < 0.001) and the genera Succinivibrio and Faecalibacterium (lower at onset, p < 0.001), as a consequence of nutritional behavior, but it was not the only changing driver. The qRT-PCR analysis showed significant variations, in particular for Bacteroidetes and Bifidobacterium spp. (+1.56 log gene copies/g stool at follow-up, p < 0.001). During the year, in 11% of the patients, severe clinical episodes occurred (hypoglycemic or ketoacidosis). The likelihood of a severe hypoglycemic episode was modulated when the Methanobrevibacter smithii amount increased (odds ratio 3.7, 95% CI 1.2-11.4, p = 0.026). Integrated evaluation, including nutritional behavior and microbiota composition, could be considered predictive of the metabolic control management for children cohort with a recent diagnosis of T1D