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      Inhalable Microorganisms in Beijing’s PM 2.5 and PM 10 Pollutants during a Severe Smog Event

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          Abstract

          Particulate matter (PM) air pollution poses a formidable public health threat to the city of Beijing. Among the various hazards of PM pollutants, microorganisms in PM 2.5 and PM 10 are thought to be responsible for various allergies and for the spread of respiratory diseases. While the physical and chemical properties of PM pollutants have been extensively studied, much less is known about the inhalable microorganisms. Most existing data on airborne microbial communities using 16S or 18S rRNA gene sequencing to categorize bacteria or fungi into the family or genus levels do not provide information on their allergenic and pathogenic potentials. Here we employed metagenomic methods to analyze the microbial composition of Beijing’s PM pollutants during a severe January smog event. We show that with sufficient sequencing depth, airborne microbes including bacteria, archaea, fungi, and dsDNA viruses can be identified at the species level. Our results suggested that the majority of the inhalable microorganisms were soil-associated and nonpathogenic to human. Nevertheless, the sequences of several respiratory microbial allergens and pathogens were identified and their relative abundance appeared to have increased with increased concentrations of PM pollution. Our findings may serve as an important reference for environmental scientists, health workers, and city planners.

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          Fine-particulate air pollution and life expectancy in the United States.

          Exposure to fine-particulate air pollution has been associated with increased morbidity and mortality, suggesting that sustained reductions in pollution exposure should result in improved life expectancy. This study directly evaluated the changes in life expectancy associated with differential changes in fine particulate air pollution that occurred in the United States during the 1980s and 1990s. We compiled data on life expectancy, socioeconomic status, and demographic characteristics for 211 county units in the 51 U.S. metropolitan areas with matching data on fine-particulate air pollution for the late 1970s and early 1980s and the late 1990s and early 2000s. Regression models were used to estimate the association between reductions in pollution and changes in life expectancy, with adjustment for changes in socioeconomic and demographic variables and in proxy indicators for the prevalence of cigarette smoking. A decrease of 10 microg per cubic meter in the concentration of fine particulate matter was associated with an estimated increase in mean (+/-SE) life expectancy of 0.61+/-0.20 year (P=0.004). The estimated effect of reduced exposure to pollution on life expectancy was not highly sensitive to adjustment for changes in socioeconomic, demographic, or proxy variables for the prevalence of smoking or to the restriction of observations to relatively large counties. Reductions in air pollution accounted for as much as 15% of the overall increase in life expectancy in the study areas. A reduction in exposure to ambient fine-particulate air pollution contributed to significant and measurable improvements in life expectancy in the United States. 2009 Massachusetts Medical Society
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            PCR-induced sequence artifacts and bias: insights from comparison of two 16S rRNA clone libraries constructed from the same sample.

            The contribution of PCR artifacts to 16S rRNA gene sequence diversity from a complex bacterioplankton sample was estimated. Taq DNA polymerase errors were found to be the dominant sequence artifact but could be constrained by clustering the sequences into 99% sequence similarity groups. Other artifacts (chimeras and heteroduplex molecules) were significantly reduced by employing modified amplification protocols. Surprisingly, no skew in sequence types was detected in the two libraries constructed from PCR products amplified for different numbers of cycles. Recommendations for modification of amplification protocols and for reporting diversity estimates at 99% sequence similarity as a standard are given.
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              Urban aerosols harbor diverse and dynamic bacterial populations.

              Considering the importance of its potential implications for human health, agricultural productivity, and ecosystem stability, surprisingly little is known regarding the composition or dynamics of the atmosphere's microbial inhabitants. Using a custom high-density DNA microarray, we detected and monitored bacterial populations in two U.S. cities over 17 weeks. These urban aerosols contained at least 1,800 diverse bacterial types, a richness approaching that of some soil bacterial communities. We also reveal the consistent presence of bacterial families with pathogenic members including environmental relatives of select agents of bioterrorism significance. Finally, using multivariate regression techniques, we demonstrate that temporal and meteorological influences can be stronger factors than location in shaping the biological composition of the air we breathe.
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                Author and article information

                Journal
                Environ Sci Technol
                Environ. Sci. Technol
                es
                esthag
                Environmental Science & Technology
                American Chemical Society
                0013-936X
                1520-5851
                23 January 2014
                04 February 2014
                : 48
                : 3
                : 1499-1507
                Affiliations
                []PTN (Peking University-Tsinghua University-National Institute of Biological Sciences) Joint Graduate Program, Center for Synthetic and Systems Biology, TNLIST, MOE Key Laboratory of Bioinformatics, School of Life Sciences, Tsinghua University , Beijing 100084, People’s Republic of China
                []Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases , Hangzhou 310003, People’s Republic of China
                [§ ]Graduate program in School of Life Science, Peking University , Beijing 100871, People’s Republic of China
                []State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University , Beijing 100084, People’s Republic of China
                []State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex , Beijing 100084, People’s Republic of China
                [# ]Center of Biomedical Analysis, School of Life Sciences, Tsinghua University , Beijing 100084, People’s Republic of China
                Author notes
                [* ]Phone: +86-10-62797325 (T.F.Z.); +86-10-62795684 (G.T.); +86-10-62781512 (J.J.). E-mail: tzhu@ 123456biomed.tsinghua.edu.cn (T.F.Z.); tiangeng@ 123456biomed.tsinghua.edu.cn (G.T.); jiangjk@ 123456tsinghua.edu.cn (J.J.).
                Article
                10.1021/es4048472
                3963435
                24456276
                947ba686-2a97-45bb-986f-4e9feeea4f30
                Copyright © 2014 American Chemical Society
                History
                : 30 October 2013
                : 13 January 2014
                : 13 January 2014
                Categories
                Article
                Custom metadata
                es4048472
                es-2013-048472

                General environmental science
                General environmental science

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