as an international 
 megacity with a population of over 20 million , 
 beijing has been suffering from frequent smog events in recent years .
since the official daily monitoring data became available in 1999 , 
 particulate matter has been shown to be a major air pollutant in beijing , and its impact to the public health may be profound .
categorized by pm2.5 and pm10 ( particulate 
 matter with nominal mean aerodynamic diameters of 2.5 and 
 10 m , respectively ) , pm pollutants of different sizes 
 deposit and affect different regions of the respiratory tract : when 
 inhaled , coarse particles ( pm2.510 ) deposit primarily 
 in the head airways , while fine particles ( pm2.5 ) are more 
 likely to penetrate and deposit deeper in the tracheobronchial and 
 alveolar regions .
historical data suggest 
 that exposure to such atmospheric particulate matter is linked to 
 increases in morbidity and mortality , and decreases in life expectancy . during the period of january 1014 , 2013 , the city 
 of beijing , 

along with the rest of the mideastern region of china experienced 
 a massive , severe smog event .
the highest 
 daily average pm2.5 concentration in beijing measured greater 
 than 500 g / m at times ( 20-fold higher than the 
 who guideline value ) , raising serious public health concerns .
beijing cough  ) 
 and significant increases of outpatient cases related to respiratory 
 diseases have been reported .
here we asked 
 the question of what microorganisms , particularly inhalable allergens 
 and pathogens , are in beijing s pm2.5 and pm10 pollutants and what potential effects they may have on the 
 public health during severe smog events like this .
the public 
 health effects of pm , particularly those of pm2.5 , have 
 been well documented in the literature . while 
 the physical and chemical properties of pm2.5 and pm10 pollutants have been extensively studied , relatively less 

is known about inhalable biological particles such as bacteria , fungi , 
 viruses , pollens , and cell debris in the micrometer to submicrometer 
 size range .
it has been suggested that materials of biological origin 
 may contribute as much as 25% to the atmospheric aerosol , and they are responsible for various diseases 
 and allergies . the abundance of airborne bacteria measured from 10 to 10 cells per m , depending on the 
 environment .
while culture - based methods 
 have been used to detect airborne microorganisms , they are constrained to the identification of a limited 
 number of cultivatable species . although the use of amplicon - based 
 ( e.g. , 16s or 18s ribosomal rna ( rrna ) gene ) sequencing and related 
 techniques have allowed us to detect both cultivatable and noncultivatable 
 microorganisms ( although dna from cell debris may also be detected ) 
 and categorize the microbial populations in airborne particles , it has been challenging to sequence the fine , inhalable pm2.5 samples ( which are more relevant to human health ) due to the low 
 dna yield , unless with amplification of the extracted dna . yet
amplicon - based sequencing methods often 
 result in biases , and most importantly , 
 they are generally limited to categorizing bacteria or fungi at the 
 family or genus level ( without the use of marker genes ) . because microbial species within the same family or genus may differ 
 significantly in pathogenic potential , the discovery of microbial 
 allergens and pathogens
requires the identification of bacteria , fungi , 
 and viruses at the species or even strain level .
thus , microbial metagenomic sequencing represents a powerful 
 alternative for studying complex microbial communities , particularly for its ability to discover clinically 
 relevant microbes at the species level .
pm2.5 and 
 pm10 samples were collected from the roof top of the environmental 
 science building ( 40017n , 1161934e , 
 10 m above the ground , 20 m and 690 m from 
 the nearest river and hospital , respectively ) at tsinghua university , 
 an area without major pollution sources nearby .
sampling was conducted by three high volume air samplers ( thermo 
 electron corp . , ma , u.s . ) , two of which were equipped with pm2.5 fractionating inlets , the third one being equipped with 
 a pm10 fractionating inlet .
ambient air was drawn at an 
 average flow rate of 1.13 m / min for 23 h ( 10:00 am to 
 9:00 am the next day ) per sampling day from january 8 to january 14 
 ( including january 8 as a nonsmog control , according to the chinese 
 class ii standard ) , resulting in approximately 1559 m of 
 air flow - through per sampling day .
particulate matter with aerodynamic 
 diameters of 2.5 and 10 m were collected on 
 20.32  25.4 cm tissuquartz filters ( pall , ny , u.s . ) 
 with 99.9% typical aerosol retention .
all the filters were sterilized 
 by baking in a muffle furnace at 500 c for 5 h prior to sampling . 

each sterilized filter was packaged in sterilized aluminum foil and 
 stored in a sealed bag until being loaded into the filter cartridge . 

the filter holder and all the tools used for changing new filters 
 were cleaned with 75% ethanol or autoclaved every day to avoid contamination . 

the net weight of each filter was recorded at mg accuracy before and 
 after sampling .
the concentrations of pm2.5 and pm10 at our sampling site were estimated by the net weight of 
 each sample ( average weight of the two pm2.5 samples ) divided 
 by the 23 h flow - through volume per sampling day ( to avoid microbial 
 contamination , samples were not kept under 45% relative humidity at 
 20 c as typically required for pm measurements ) .
a 47 mm diameter 
 filter punch was taken from the pm10 sample and one of 
 the pm2.5 samples each day for chemical component and elemental 
 analyses .
the filter punches were kept in size adaptive chambers and 
 stored at 20 c .
all other samples were stored at 80 
 c until downstream analyses were performed . to overcome the issue of low yield during 
 genomic dna extraction , several technical improvements were made to 
 optimize the extraction of high - quality dna from pm samples .
considering 
 the different dna yield of pm2.5 and pm10 samples , 
 1/4 of pm10 filter ( a total of 103.04 cm ) and 1 and 3/4 of the pm2.5 filters ( a total of 721.28 
 cm ) from each sampling day were used for dna extraction . 

the filters were cut into 8.96 11.5 cm pieces and 
 were placed in 50 ml centrifuge tubes filled with sterilized 1x pbs 
 buffer .
the pm samples were then pelleted at 4 c by centrifugation 
 at 200 g for 2 h. after gentle vortexing , the resuspension 
 was filtered with a 0.2 m supor 200 pes membrane disc filter 
 ( pall , ny , u.s . ) , which was then cut into small pieces and used for 
 dna extraction using the mo - bio powersoil dna isolation kit ( carlsbad , 
 ca , u.s . ) .
the samples were then heated to 65 c in powerbead tubes 
 for 10 min followed by vortexing for 2 min .
the remaining steps of 
 the extraction were performed according to the standard mo - bio powersoil 
 dna isolation protocol except for the column purification step , which 
 was replaced with magnetic bead purification ( agencourt ampure xp , 
 beckman , ca , u.s . ) for improved yield .
genomic dna quality and concentration 
 were analyzed by gel electrophoresis and a fluorescent dsdna - binding 
 dye assay ( qubit fluorometer , life technologies , ca , u.s . ) .
blank 
 control samples were collected by placing a sterilized filter inside 
 of the sampler without operation for 23 h , and treated similarly as 
 above .
dna extraction of blank control samples resulted in dna concentrations 
 below the detection limit of our instruments , and library generation 
 efforts failed to generate useable sequencing libraries .
the illumina miseq 
 ( for library validation ) and hiseq 2000 sequencing systems ( illumina , 
 ca , u.s . ) were used for sequencing , and the library preparation kits 
 were purchased from new england biolabs ( ma , u.s . ) .
sequencing library 
 construction and template preparation were performed according to 
 the neb library preparation protocols .
we constructed a paired - end 
 library with insert size of 500 bp for each sample .
an aliquot 
 of 5 ng dna from each sample was used as the starting amount ( except 
 for 3 samples , the total quantities of dna of which were less than 
 5 ng , supporting information ( si ) , table 
 s1 ) for library preparation in order to ensure sample consistency . 
 in order to minimize possible bias introduced by pcr ,
each sample was barcoded and equal 
 quantities of barcoded libraries were used for sequencing ( for index 
 sequences , see si table s1 ) .
adaptor contamination 
 and low - quality reads were discarded from the raw data . in total , 
 98 gb sequence with a uniform read length of 90 bp was obtained 
 and an average of 7 gb high - quality hiseq sequences were generated 
 from each sample ( si table s1 ) .
the rarefaction 
 curve ( analyzed by the metagenomics rast server ( mg - rast , release 
 3.3 ) ) suggested that the sequencing depth 
 of the hiseq data was sufficient to capture most of the microorganisms 
 but not the miseq data ( average data set of 683 mb ) ( si figure s1 ) .
metaphlan ( metagenomic phylogenetic analysis ) was used to estimate the relative abundance 
 of bacteria and archaea with unique clade - specific genes at the species 
 level ( si figures s2 and s3 ) .
the illumina 
 hiseq reads were aligned to a cohort of nonredundant ncbi complete 
 genomes ( 2637 complete genomes , including bacteria , fungi , archaea , 
 and viruses ) using the short oligonucleotide analysis package ( soap ) 
 alignment tool ( release 2.21 t ) to profile 
 the common core species .
we used a 90% identity threshold for bacteria , 
 archaea , and fungi , and 100% identity for viruses due to their smaller 
 genome sizes .
bacterial , fungal , and viral species with coverage of 
 5% , 0.5% ( average alignment of all chromosomes ) , and 
 1% , respectively , in either pm2.5 or pm10 samples of 7 consecutive sampling days were listed in si table s2 .
the genome - size - normalized relative 
 abundance of these species was calculated based on the number of aligned 
 reads normalized by the species genome size ( si figure s4 and table s3 ) .
the variations of the hit abundance 
 of species across 7 sampling days were estimated based on the hit 
 numbers normalized by number of total aligned reads ( si figure s5 ) .
the greengenes 16s rrna gene database was used for 16s rrna phylogenetic analysis 
 with the following alignment parameters : > 97% identity , minimal 
 alignment 
 40 bp .
dna sequence data have been deposited in mg - rast ( http://metagenomics.anl.gov/ ) at the following url : http://metagenomics.anl.gov/linkin.cgi?project=3756 .
the greengenes 
 16s rrna gene database was used for assigning 
 the hiseq reads at > 97% identity threshold ( only uniquely aligned 
 reads were used for following calculations ) .
all of the greengenes 
 database sequences with available information of bacteria habitats 
 were classified into the four categories without overlaps .
in addition , 
 the 16s sequences of previous studies on high - altitude and urban airborne bacteria of milan and new york were 
 assigned to the same habitat categories and compared to our results 
 ( si figure s6 ) .
we sought to sequence 
 the metagenome of inhalable airborne microorganisms in beijing s 
 pm2.5 and pm10 pollutants , after having overcome 
 the technical issues involved in high - volume pm2.5 and 
 pm10 sample collection , dna extraction , and library generation 
 ( for details of the dna extraction methods , see materials 
 and methods ) .
pm2.5 and pm10 samples 
 collected at a beijing tsinghua pm monitoring site ( 40017n , 
 1161934e ) from january 814 , 2013 , during 
 which period beijing s pm2.5 and pm10 pollution indexes rapidly deteriorated from healthy to record - high 
 hazardous levels , were used for sequencing ( figure 1a , si figures s7s9 and 
 table s4 ; air temperatures are typically low in january in beijing , 
 creating a unique high pm , low temperature environment ) .
the illumina 
 hiseq data from a total of 7 daily pm2.5 and 7 pm10 samples is more than 1000-fold larger than those of three previous 
 studies on airborne bacteria combined , from which original sequence data were publicly available 
 ( si table s1 ) . by aligning to the greengenes 
 16s rrna gene database at a 97% identity 
 threshold
, we discovered 255 more bacteria genera than those identified 
 by the three previous studies ( si figure 
 s10 and table s5 ) .
overall , the pm2.5 samples contained 
 86.1% bacterial , 13.0% eukaryotic , 0.8% archaeal , and 0.1% viral reads , 
 while the pm10 samples contained 80.8% bacterial , 18.3% 
 eukaryotic , 0.8% archaeal , and 0.1% viral reads ( figure 1b ) .
the higher relative abundance of eukaryotic reads ( which 
 included those from fungi , plants , algae , and animal debris ) , as well 
 as the higher alpha diversity ( a measurement of species diversity ) 
 found in pm10 compared with those of pm2.5 samples 
 ( figure 1c ) , may in part be attributed to the 
 fact that the aerodynamic diameters of many fungal spore agglomerates 
 were between 2.5 and 10 m .
principal component 
 analysis ( pca ) of the microbial relative abundance ( figure 1d and si table s6 ) and 
 dinucleotide frequency ( si figure s11 ) 
 suggested that the metagenomes of airborne microbes were distinct 
 from those of other environments , though relatively more related to 
 the soil metagenomes .
( a ) daily average pm2.5 and pm10 concentrations 
 estimated from the collected samples during january 814 , 2013 . 

( b ) relative abundance of the mg - rast taxonomic hits at the domain 
 level in pm2.5 and pm10 samples .
( c ) estimated 
 average alpha diversity of the pm2.5 and pm10 samples ( error bars represent sd of the 7 daily pm2.5 and 7 pm10 samples , respectively ) .
( d ) principal component 
 analysis of the relative abundance of microorganisms at the phylum 
 level of the 14 sequenced pm metagenomes ( red ) compared to those of 
 other environments ( other colors ) .
bacteria 
 appeared to be the most abundant prokaryotic microorganisms in pm2.5 and pm10 pollutants . to identify the prokaryotic 
 species and to estimate their relative abundance
, we used the metagenomic 
 phylogenetic analysis ( metaphlan ) toolbox to reveal a picture of complex bacteria and archaea community ( figure 2a and si figure s2 ) . 

we show that the most abundant phyla were actinobacteria , proteobacteria , 
 chloroflexi , firmicutes , bacteroidetes , and euryarchaeota ( relative 
 abundance 1% ) . at the species level
, 1315 distinct bacterial 
 and archaeal species were identified from the 14 samples . an unclassified 
 bacterium in the nitrogen fixing , filamentous bacteria genus frankia 
 appeared to be the most abundant ( figure 2a 
 and si figure s3 ) .
the most abundant classified 
 bacterial species appeared to be geodermatophilus obscurus , a bacterium commonly found in dry soil environments ( si table s7 ) . by aligning to the greengenes 16s 
 database , categorized by terrestrial , fecal , freshwater , and marine - associated 
 bacteria ( see materials and methods ) ,
we show 
 that the majority ( > 85% ) of the categorized bacteria in the collected 
 pm2.5 and pm10 samples were related to fecal 
 and terrestrial sources ( figure 2b and si figure s6 ) .
the proportion of bacteria from 
 terrestrial - related sources appeared to be higher than those identified 
 from the three previous studies ( figure 2c 
 and si figure s6 ) .
this may in part be attributed to the lack 
 of vegetation coverage and abundance of dry , exposed soil , and construction 
 sites in the city of beijing and its surrounding areas , especially 
 during the winter seasons .
in addition , while the proportion of freshwater 
 and marine - associated bacteria remained relatively constant , the fraction 
 of fecal - associated bacteria appeared to have increased ( from 4.5% 
 to as high as 11.4% in pm2.5 samples ) ( figure 2b ) with progressively increased concentrations of 
 pm pollution .
( a ) phylogenetic tree of the bacteria and archaea identified 
 from pm2.5 samples , analyzed by metaphlan .
the sizes of 
 the nodes correspond to the relative abundance at the corresponding 
 levels in the cohort .
the family , genus , and species levels of the 
 most abundant order actinomycetales are plotted . 
 only nodes with 1% relative abundance are labeled .
( b ) original 
 habitats of the identified bacteria in daily pm2.5 and 
 pm10 samples , categorized by terrestrial , fecal , freshwater , 
 and marine sources .
( c ) bacterial and archaeal species in beijing 's 
 pm samples were pooled and compared with those identified from the 
 grip high - altitude , milan urban , and new york subway studies . since not only bacteria , but 
 also fungi and viruses are responsible for various human allergies 
 and diseases , we sought to identify the microbial species including 
 fungi and viruses ( which are currently not supported by the metaphlan 
 toolbox ) in pm2.5 and pm10 pollutants .
we employed 
 the short oligonucleotide analysis package ( soap ) alignment tool to align the hiseq reads from each sample to 
 a cohort of 2637 nonredundant species of ncbi complete genomes , including 
 bacteria , archaea , fungi , and viruses . at a 90% identity threshold 
 and 5% coverage of the complete bacterial genomes ( for a typical 
 bacterial genome of 4 mb
, it corresponds to a minimal alignment length 
 of 200 kb , > 100-fold longer than the 16s rrna gene and 
 thus 
 provides more confidence ) or 0.5% coverage for fungal genomes , 
 the 48 most abundant bacterial and 2 fungal species were identified 
 ( si table s2 ) .
because of the smaller genome 
 size of viruses , we used a more stringent alignment strategy ( i.e. , 
 100% identity and 1% coverage ) , and 3 most abundant viral 
 species were identified .
we next estimated the genome - size - normalized 
 relative abundance ( defined as the number of unique hit reads normalized 
 by genome size ) of each species within the most common ones ( si table s3 ) and analyzed the daily variations 
 of their relative abundance during the 7 sampling days ( figure 3 ) .
consistent with the metaphlan results , the soil - associated 
 bacteria g. obscurus appeared to be the most abundant 
 classified bacterial species ( with an average genome coverage of 42.7% 
 and relative abundance of 14.6% in the pm2.5 samples ) , 
 followed by modestobacter marinus , blastococcus 
 saxobsidens , kocuria rhizophila , and micrococcus luteus , all of which are commonly found in soil 
 habitats and some with the abilities to survive under  tough  
 ( e.g. , uv radiation ) conditions ( si table 
 s7 ) .
although the relative abundance of most of the bacterial species 
 remained stable during the 7 sampling days , as was found in previous 
 studies , some showed considerable variations . for 
 example , the relative abundance of thermobifida fusca , an important bacterial degrader of plant cell walls and commonly 
 found in decaying organic matter ( si table 
 s7 ) , increased 5-fold from an average of 0.7% during the first 
 2 less polluted days to an average of 3.7  2.5% in the 5 heavily 
 polluted days in pm2.5 samples ( si figures s4 and s12 ) .
box plot of the daily variations of the relative abundance 
 of 48 
 most common bacterial , 2 fungal , and 3 viral species in pm samples . 

boxes correspond to the interquartile range between the 25th and 75th 
 percentiles , and the central lines represent the 50th percentile . 

whiskers correspond to the lowest and highest values no more than 
 1.5 times the interquartile range from the box , while dots are the 
 outliers beyond the whiskers .
pm2.5 samples are labeled 
 pink and pm10 are black . among the identified microbial species , 
 several are known to cause human allergies and respiratory diseases , 
 including streptococcus pneumoniae , aspergillus 
 fumigatus , and human adenovirus c ( with average genome coverage 
 of 2.0% , 14.5% , and 6.5% , respectively ) . among them , s. pneumoniae is the most common cause for community - acquired pneumonia ( cap ) , 
 having been isolated from nearly 50% of cap cases .
its representation within the entire bacteria community 
 ( analyzed by metaphlan ) was 0.012% in pm2.5 samples and 
 0.017% in pm10 samples , and the normalized number of hit 
 reads ( hit abundance ) appeared to have increased by 2 fold 
 from an average of 0.024% during the first 2 less polluted days to 
 an average of 0.05  0.02% in the 5 heavily polluted days in 
 pm2.5 samples ( figure 4a ) .
a. fumigatus , likely collected in the form of spores , is 
 known as a major fungal allergen and opportunistic pathogen that causes 
 airway or lung invasion in immunodeficient patients .
its average hit abundance was found to be higher in pm10 than in pm2.5 samples ( 4.5% vs 1.7% ) , most likely 
 because the aerodynamic diameters of the fungal spore agglomerates 
 are between 2.5 and 10 m .
the 
 hit abundance of a. fumigates also appeared to be 
 correlated with the increase of pm pollution levels , increasing 4-fold 
 from an average of 1.5% during the first 2 less polluted days to an 
 average of 5.8  1.8% in the 5 heavily polluted days in pm10 samples ( figure 4b ) . to confirm the 
 existence of a. fumigatus in our samples , we cultured 
 the fungus and validated its existence by sequencing the 18s rrna 
 gene and a species - specific gene ( glii ) ( si table s8 ) , as well as sem imaging ( si figure s13 ) .
human adenovirus , a dsdna virus 
 that accounts for 510% of upper and lower respiratory tract 
 infections in children , was also found 
 ( with 100% sequence matched to human adenovirus c in all 14 samples ) . 

the hit abundance of adenovirus in our samples also appeared to have 
 increased during the heavily polluted days , though with more daily 
 variations than those of s. pneumonia and a. fumigates ( si figure s5 ) .
daily 
 variations of the normalized hit abundance of microbial pathogens 
 and allergens in the collected pm2.5 and pm10 samples .
to put our findings in the context of 
 aerosol chemistry , we analyzed 
 the organic and elemental carbon , water - soluble ions , and elemental 
 composition of the collected samples ( si tables s9s11 ) .
we found that sulfate , ammonium , nitrate , 
 and organic matter were among the most abundant , and altogether their 
 relative abundance in pm2.5 and pm10 samples 
 were 80% and 71% ( w / w ) , respectively .
these results , as well as the 
 high weight ratio of pm2.5 to pm10 ( 0.7 ) , 
 suggested that secondary formation of fine particles likely led to 
 the high pm concentrations during this smog event .
additionally , the high relative humidity ( si figure s8 ) during the period may have contributed to particle 
 growth through water uptake and promoting aqueous redox chemistry 
 ( e.g. , the oxidation of sulfur dioxide to sulfate ) .
this also suggested 
 that most of the particles were rich in water content during the polluted 
 days and thus would favor the survival of microbes .
pm pollution has been 
 studied extensively in the context of aerosol 
 chemistry and physics , and statistical correlations 
 between pm pollution and decreased life expectancy have been made .
so far , no specific components of pm have been 
 conclusively shown to be harmless . in 
 particular ,
previous studies have shown that bioaerosols 
 containing pathogens are responsible for the spread of respiratory 
 diseases , and thus it is crucial to understand the 
 composition of airborne microbes at the species level and to identify 
 the potential microbial allergens and pathogens .
most of the clinically 
 relevant studies on inhalable pathogens were conducted in hospital 
 environments , yet in beijing , a significant increase of outpatient cases related 
 to respiratory diseases during the same severe pm pollution period 
 studied here has been reported .
our results 
 have provided sequence - based evidence for the existence of inhalable 
 microbial allergen and pathogen species in an open environment , and 
 suggested that high pm pollution may pose health threats to the susceptible 
 population ( e.g. , the elderlies and the immunodeficient ) . besides , 
 information on the original habitats of airborne bacteria provides 
 important insights for understanding the source of the biological 
 particles , and may be used as a reference for future urban planning 
 efforts to reduce pm pollution and the spread of airborne microbial 
 allergens and pathogens . in future studies ,
clinical samples ( e.g. , 
 sputum samples from respiratory disease patients ) during severely 
 polluted and unpolluted days can be obtained , and the sequence information 
 can be compared to those from collected pm samples for comparison . 

furthermore , pm exposure studies on animal models can be performed 
 to characterize the effects of pm - associated allergens and pathogens , 
 leading to better understandings of their pathogenicity . using 
 the current methods
, we were able to identify bacterial , 
 archaeal , fungal , and dsdna viral species in the collected pm samples . 

we also attempted to culture other bacteria and fungi species , 
 but not all were successfully cultured ( data not shown ) since some 
 species were slow - growing or difficult to culture , and the samples 
 were stored at 80 c before use .
rna viruses such as 
 rhinovirus and influenza virus are undoubtedly important viral agents 
 that affect the public health . yet in our experience , it appeared 
 to be technically challenging to extract sufficient quantities of 
 rna for reverse transcription and sequencing from pm samples containing 
 various rna - degrading containments such as divalent cations .
low - bias 
 preamplification techniques may be used to generate sufficient libraries 
 for the sequencing of rna viruses in pm samples in future studies . as for human dsdna viruses
, human adenovirus 
 c appeared to be the most abundant in our pm samples based on our 
 sequencing results .
more importantly , the current study was limited 
 by the daily sampling capacity and availability of sampling sites , 
 as well as the trade - off between obtaining high - depth sequence data 
 for species - level characterization vs more sampling days ( 98 gb data 
 from 14 samples ) . in particular ,
though pm pollution levels are typically 
 high in the winter of beijing , low temperatures are often associated 
 with lower overall microbial abundance compared to warmer seasons . 

thus , future longitudinal and multiple location studies to identify 
 airborne microorganisms should be performed to compare with our current 
 results and to provide better insights on the increased incidences 
 of respiratory diseases during urban smog events , and to correlate 
 with meteorological data , chemical components , and clinically obtained 
 pathogen samples .
additionally , the establishment of a monitoring 
 network for airborne microbes can be invaluable during outbreaks of 
 deadly respiratory diseases .
information on the abundance of particular 
 airborne pathogens and their regional and seasonal variations will 
 be of particular importance for the prevention of respiratory diseases 
 at a public scale , in areas such as vaccine design and distribution , 
 as well as for understanding the spread of drug resistant respiratory 
 pathogens .
 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 pm2.5 and pm10 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 . 
Introduction
Materials and Methods
Results
Discussion