Detection and analysis of fine particulate matter and microbial aerosol in chicken houses in Shandong Province, China

Detection and analysis of fine particulate matter and microbial aerosol in chicken houses in... Abstract Bacteria and fungi are primary constituents of airborne microbes in fine particulate matter and harmful to health. To evaluate the environmental quality of different poultry houses in Shandong Province, China, the airborne aerobic bacteria, airborne fungi, and airborne Escherichia coli were collected by the Andersen-6 air microorganism sampler. The fine particulate matter was collected by a ZR-3920 ambient air particulate matter sampler, and bacterial and fungal diversities and relative abundances analyzed using high-throughput sequencing. Results showed that the concentrations of airborne aerobic bacteria, airborne fungi, and airborne Escherichia coli in poultry houses were 0.167 to 4.484 × 104 CFU/m3, 0.236 to 4.735 × 103 CFU/m3, and 0 to 33.0 CFU/m3, respectively. 11.4 to 34.3% of aerobic bacteria and 16.8 to 37.5% of fungi were distributed at levels 5 and 6 (0.6 to 2.1 μm, the particle sizes similar to fine particulate matter) in the Andersen sampler. The concentration of fine particulate matter in the poultry houses was 114 to 230 μg/m3, which was higher than the safety value 10 specified by WHO. In fine particulate matter, the main bacteria at phylum level were Firmicutes, Bacteroidetes, and Proteobacteria, whereas the dominant phylum of fungus was Ascomycota and Basidiomycota. Importantly, the relative abundances of Escherichia and Corynebacterium in the broiler houses were greater than those in layer houses. However, the percentages of Aspergillus and Penicillium were 13.5 and 0.56%, with a relatively high level in the layer houses. Altogether, results revealed that the ambient air quality in the poultry houses sampled had a relatively high abundance of conditional pathogenic bacteria and concentration of fine particulate matter, which could threaten the health of animals and workers in those environments. INTRODUCTION Severe indoor environmental pollution arising from intensive poultry farming has caused serious harm to poultry and human health in those environments, primarily due to suspended particles in the air, including total suspended particulate and respirable particulate matter. Numerous studies have shown that long-term exposure to high concentrations of airborne particles increases both the morbidity and mortality of human diseases and reduces the life expectancy of humans (Hunt et al., 2003; Pope et al., 2009). In particular, fine particulate matter considerably threatens human health by entering the trachea and penetrating deep into the lungs, bronchi, and alveoli (Brook et al., 2004). As a result of the normal activities of chickens and breeders, microorganisms and chemical particles in the environments of chicken farms can form aerosols, which can be divided into biological and non-biological components. Bioaerosol, primarily derived from animal dander and feces, as well as feed (Radon et al., 2002; Cambralópez et al., 2010), account for more than 25% of aerosols (Jaenicke, 2005). Among microbial components, fungal spores and bacteria with diameters of 1 to 30 μm and 0.25 to 8 μm, respectively, form part of respirable particulate matter (Comrie and Thomson, 1906; Stanley and Linskens, 1974). Multiple studies have shown that concentrations of airborne microbes at poultry farms often exceed 106 CFU/m3 (Radon et al., 2002; Bakutis et al., 2004). For both poultry and humans, long-term exposure to high concentrations of microbial aerosols in particular can cause upper respiratory tract irritation, chronic bronchitis, and organic dust toxicity syndrome, among other respiratory symptoms (Donham et al., 2000). However, few studies have focused on fine particulate matter in poultry houses in China. Although the concentrations of fine particulate matter in the chicken houses were measured, biological properties of the environmental quality remain unmeasured (Lim et al., 2003; Cambral-LóPez et al., 2009). At the same time, at least one study has demonstrated that the impacts of particulate matter on humans and animals relate not only to the concentrations of particulate matter and microbes, but also the composition of microorganisms (Aarnink et al., 2010). In response to both strands of research, in this study, concentrations and compositions of microbial aerosols and fine particulate matter at chicken farms in Shandong Province, China, using different feeding modes, were monitored, the bacteria and fungi in the fine particulate matter were identified, and air quality was evaluated. MATERIALS AND METHODS Chicken Farms Six chicken farms (Table 1) were selected from the area surrounding Tai’an, Shandong, China. Table 1. Description of poultry houses. Poultry house  Time (year month)  Animals  Temperature  Relative humidity (%)  Ventilation  Clean up feces  Aa  15.04  broiler  26°C  80  bad  4 to 5 d/time  B  15.06  broiler  25°C  70  good  3 to 4 d/time  C  15.07  broiler  35°C  78  good  2 to 3 d/time  Db  15.07  layer  25°C  85  good  1 d/time  E  15.08  layer  32°C  76  good  1 d/time  F  15.10  layer  21°C  40  good  1 d/time  Poultry house  Time (year month)  Animals  Temperature  Relative humidity (%)  Ventilation  Clean up feces  Aa  15.04  broiler  26°C  80  bad  4 to 5 d/time  B  15.06  broiler  25°C  70  good  3 to 4 d/time  C  15.07  broiler  35°C  78  good  2 to 3 d/time  Db  15.07  layer  25°C  85  good  1 d/time  E  15.08  layer  32°C  76  good  1 d/time  F  15.10  layer  21°C  40  good  1 d/time  aHeated by coal stove. bWetted by water curtain. View Large Content Determination of Airborne Bacteria and Escherichia Coli Samples were collected on an Andersen-6 microbial sample collector (Andersen, 1958) using 5% blood agar medium for airborne bacteria and eosin-methylene blue medium for airborne Escherichia coli (E. coli) as the sampling media. The E. coli colony is bluish green with a metallic luster. The sample collector was centered in each chicken house at a height of 30 to 40 cm above the ground (i.e., the height of the chicken's nasal cavity) with an airflow rate of 28.3 L/min. Six replicate samples were collected from each chicken house. To accommodate different health conditions, the driving time was set at 1 to 5 min and 5 to 15 min for bacteria and E. coli, respectively, and the number of colonies per level was 30 to 300. After aerobically culturing the culture medium 37°C for 24 to 48 h, colonies were counted, and the bacteria and E. coli content (CFU/m3) were calculated according to correction table (Andersen, 1958). Content Determination of Airborne Fungi Samples were collected on an Andersen-6 microbial sample collector (Andersen, 1958) using Sabouraud agar as the sampling medium, and an airflow rate of 28.3 L/min. The sample collector was centered in each chicken house at a height of 30 to 40 cm above the ground. Six replicate samples were collected from each chicken house. To accommodate different health conditions, the driving time was set at 1 to 5 minutes. After aerobically culturing the culture medium at 25°C for 5 to 7 d, colonies were counted, and fungus content (CFU/m3) was calculated according to correction table (Andersen, 1958). Identification of Airborne Bacteria at Levels 5 and 6 of the Andersen-6 Sampler Single colonies at levels 5 and 6 of the Andersen-6 sampler were isolated and cultured in 5% blood agar. The bacteria were identified by the 16S rRNA sequence analysis. The primers were 27F-AGAGTTTGATCCTGGCTCAG and 1492R-ACGGCTACCTTGTTACGACTT. The 16S rRNA sequences were blasted in NCBI (Kolbert and Persing, 1999; Relman, 1999; Clarridge, 2004). Sample Collection and Analysis of Fine Particulate Matter Samples of fine particulate matter were collected by waterproof air sampling filters (HaoChenTianCheng Ltd., Beijing, China) with typical aerosol retention of 99.99%, using a ZR-3920 ambient air particulate matter (total suspended particulate/inhalable particles/fine particulate matter) sampler (Zhongrui Ltd., Qingdao, China). The filters were baked in a furnace at 500 °C for at least 6 h prior to sampling. Airflow rate was set at 100 L/min, the sampling height was 1 m, and the acquisition time was 48 hours. Three replicate samples were collected from each chicken house. The concentration of fine particulate matter (μg/m3) was calculated according to the equation: C = (W1-W0)/(t × F). The blank filters were weighted on a Microbalance (W0). After sampling, the filters with fine particulate matter samples were weighted to obtain (W1). The t is collection time, and the F is air flow of the sample. Total genomic DNA was extracted directly from fine particulate matter samples using FastDNA® spin kit (MP biomedicals, Santa Ana, CA) following the manufacturer's protocol. The V3-V4 region of bacterial 16S rRNA and the Internal Transcribed Spacer (Lawniczekwalczyk et al., 2013) regions of fungi were sequenced using the upgraded HiSeq sequencing platform, and sequences were analyzed with the Quantitative Insights Into Microbial Ecology software package (http://qiime.org/index.html) and UPARSE pipeline (http://drive5.com/uparse/). The reads were first filtered with Quantitative Insights Into Microbial Ecology quality filters using default settings for Illumina processing. The UCLUST method was used to cluster sequences into operational taxonomic units (OTU) at an identity threshold of 97%, while the RDP classifier was used to assign each OTU to a taxonomic level (Table 2). Additional analyses for rarefaction curves and Shannon index were performed with Quantitative Insights Into Microbial Ecology. Table 2. Sequencing data of bacterial and fungi in all samples.     Bacteria  Fungi  House name  Sample name  Clean reads  OUT  Clean reads  OUT    1  50,843  1421  55,132  440  A  2  52,649  1335  51,088  400    3  49,716  1291  50,111  393    1  53,178  1230  50,984  289  B  2  52,189  1378  51,201  252    3  48,909  1419  53,320  255    1  59,010  1145  55,018  350  C  2  51,398  1356  51,144  326    3  54,946  1259  50,619  307    1  43,393  1570  52,189  378  D  2  48,067  1486  58,397  365    3  41,764  1299  59,718  345    1  40,458  1338  40,011  459  E  2  49,103  1183  45,696  406    3  46,893  1295  45,171  389    1  52,340  1780  40,191  251  F  2  58,901  1377  39,443  258    3  48,914  1267  39,319  283      Bacteria  Fungi  House name  Sample name  Clean reads  OUT  Clean reads  OUT    1  50,843  1421  55,132  440  A  2  52,649  1335  51,088  400    3  49,716  1291  50,111  393    1  53,178  1230  50,984  289  B  2  52,189  1378  51,201  252    3  48,909  1419  53,320  255    1  59,010  1145  55,018  350  C  2  51,398  1356  51,144  326    3  54,946  1259  50,619  307    1  43,393  1570  52,189  378  D  2  48,067  1486  58,397  365    3  41,764  1299  59,718  345    1  40,458  1338  40,011  459  E  2  49,103  1183  45,696  406    3  46,893  1295  45,171  389    1  52,340  1780  40,191  251  F  2  58,901  1377  39,443  258    3  48,914  1267  39,319  283  View Large Data Analyses The median of concentrations was used to represent the aerosol concentration, whereas the maximum and minimum values were used for the range of aerosol concentrations. A Student's t test was performed to examine significant differences among treatments using Statistical Package for the Social Sciences 19.0 software (IBM, Chicago, IL). RESULTS Airborne Bacteria and Fungi The concentrations of the airborne aerobic bacteria were 0.385 to 4.484 × 104 CFU/m3 in the broiler houses and 0.167 to 0.742 × 104 CFU/m3 in the layer houses (Figure 1A), whereas the concentrations of airborne E. coli were 0 to 33.0 CFU/m3 in the broiler houses and 0 to 14.1CFU/m3 in the layer houses (Figure 1B). Concentrations of airborne fungi were 0.236 to 4.735 × 103 CFU/m3 in the broiler houses and 1.319 to 2.326 × 103 CFU/m3 in layer houses (Figure 1C). Figure 1. View largeDownload slide Box plot of the concentration of airborne bacteria and fungi in poultry houses. (A) Concentration of airborne aerobic bacteria, (B) airborne E. coli, and (C) airborne fungi. Boxes correspond to the interquartile range between the 25th and 75th percentiles, and central lines represent the 50th percentile. Whiskers correspond to the maximum and minimum values. Figure 1. View largeDownload slide Box plot of the concentration of airborne bacteria and fungi in poultry houses. (A) Concentration of airborne aerobic bacteria, (B) airborne E. coli, and (C) airborne fungi. Boxes correspond to the interquartile range between the 25th and 75th percentiles, and central lines represent the 50th percentile. Whiskers correspond to the maximum and minimum values. Distribution of Airborne Bacteria and Fungi on the Andersen-6 Sampler Results of measuring the distribution of airborne bacteria and fungi on the Andersen sampler on the 6 chicken farms revealed 17.6 to 49.7% distribution of aerobes at level 1 (> 7 μm) and level 2 (4.7 to μm), 29.8 to 51.2% at level 3 (3.3 to 4.7 μm) and level 4 (2.1 to 3.3 μm), and 11.4 to 34.3% at level 5 (1.1 to 2.1 μm) and level 6 (0.6 to 1.1 μm), as Figure 2A shows. Distributions of fungi were 15.6 to 32.0% at levels 1 and 2, 39.6 to 54% at levels 3 and 4, and 16.8 to 37.5% at levels 5 and 6 (Figure 2B). Figure 2. View largeDownload slide Size distributions of airborne bacteria and fungi at sampling locations in the poultry house. (A) Size distributions of airborne bacteria and (B) airborne fungi; aerodynamic diameter ranges for the viable particle sizing sampler were > 7.0 μm (first stage), 4.7 to 7.0 μm (second stage), 3.3 to 4.7 μm (fourth stage), 2.1 to 3.3 μm (fourth stage), 1.1 to 2.1 μm (fifth stage), and 0.6 to 1.1 μm (sixth stage). Figure 2. View largeDownload slide Size distributions of airborne bacteria and fungi at sampling locations in the poultry house. (A) Size distributions of airborne bacteria and (B) airborne fungi; aerodynamic diameter ranges for the viable particle sizing sampler were > 7.0 μm (first stage), 4.7 to 7.0 μm (second stage), 3.3 to 4.7 μm (fourth stage), 2.1 to 3.3 μm (fourth stage), 1.1 to 2.1 μm (fifth stage), and 0.6 to 1.1 μm (sixth stage). Bacteria Composition at Levels 5 and 6 of the Andersen-6 Sampler Bacteria collected at levels 5 and 6 of the Andersen sampler included 25 strains from House A, 27 strains from House B, 25 from House C, 18 from House D, 25 from House E, and 16 from House F, all composed of 10 Gram-negative and 103 Gram-positive bacteria. The predominant genera of bacteria were Staphylococcus, Corynebacterium, and Macrococcus, which accounted for 50.0 to 81.5% of identified strains (Table 3). Table 3. Bacteria of the levels 5 and 6 of the Andersen sampler. A  B  C  D  E  F  Bacterial family  Number  Bacterial family  Number  Bacterial family  Number  Bacterial family  Number  Bacterial family  Number  Bacterial family  number  Staphylococcus epidermidis  2  Corynebacterium jeikeium  1  macrococcus caseolyticus  11  Staphylococcus saprophyticus  2  Brevibacterium Otitidis  1  Corynebacterium xerosis canis  2  Staphylococcus  4  Brevibacterium  1  Enterococcus faecalis  1  Enterococcus faecalis  1  Corynebacterium  2  Rothia nasimurium  1  Klebsiella pneumoniae  1  Corynebacterium  9  Staphylococcus kloosii  1  Bacillus simplex  1  Staphylococcus  1  Staphylococcus sciuri  1  Enterococcus faecalis  1  Corynebacterium amycolatum  2  Rhodococcus ruber  1  Micrococcus luteus  2  Micrococcus luteus  1  Exiguobacterium acetylicum  1  Corynebacterium  6  Staphylococcus saprophyticus  1  Staphylococcus hominis  2  Staphylococcus equorum  2  Bacillus subtilis  1  Micrococcus luteus  1  Brachybacterium  1  Aerococcus viridans  1  Staphylococcus epidermidis  2  macrococcus caseolyticus  3  Brachybacterium  2  Brachybacterium nesterenkoii  1  Bacillus licheniformis  1  Bacillus  1  Exiguobacterium acetylicum  1  Corynebacterium  2  Staphylococcus saprophyticus  3  Microbacterium  1  Exiguobacterium acetylicum  1  Staphylococcus epidermidis  3  Streptomyces zaomyceticus  1  Exiguobacterium acetylicum  1  Staphylococcus gallinarum  1  Corynebacterium jeikeium  1  Staphylococcus caprae  2  Staphylococcus chromogenes  2  Psychrobacter cibarius  1  Staphylococcus sciuri  2  macrococcus caseolyticus  4  Staphylococcus saprophyticus  1  Corynebacterium xerosis  2  Staphylococcus  1  Acinetobacter radioresistens  1  Aerococcus viridans  1  Micrococcus  2  Bacillus licheniformis  1  macrococcus caseolyticus  3  Corynebacterium xerosis  1  Acinetobacter calcoaceticus  1  Klebsiella pneumoniae  1  Staphylococcus caprae  1  Brevibacterium luteolum  1  Brevibacterium  1  Staphylococcus hominis  2  Streptomyces netropsis  1      Corynebacterium jeikeium  3  Staphylococcus chromogenes  2      Enterococcus cecorum  1  Acinetobacter radioresistens  1      Staphylococcus lentus  1  Corynebacterium xerosis  1      paracoccus solventivorans  1          Staphylococcus epidermidis  1  Streptomyces griseoaurantiacus  1                  Pseudomonas stutzeri  1      A  B  C  D  E  F  Bacterial family  Number  Bacterial family  Number  Bacterial family  Number  Bacterial family  Number  Bacterial family  Number  Bacterial family  number  Staphylococcus epidermidis  2  Corynebacterium jeikeium  1  macrococcus caseolyticus  11  Staphylococcus saprophyticus  2  Brevibacterium Otitidis  1  Corynebacterium xerosis canis  2  Staphylococcus  4  Brevibacterium  1  Enterococcus faecalis  1  Enterococcus faecalis  1  Corynebacterium  2  Rothia nasimurium  1  Klebsiella pneumoniae  1  Corynebacterium  9  Staphylococcus kloosii  1  Bacillus simplex  1  Staphylococcus  1  Staphylococcus sciuri  1  Enterococcus faecalis  1  Corynebacterium amycolatum  2  Rhodococcus ruber  1  Micrococcus luteus  2  Micrococcus luteus  1  Exiguobacterium acetylicum  1  Corynebacterium  6  Staphylococcus saprophyticus  1  Staphylococcus hominis  2  Staphylococcus equorum  2  Bacillus subtilis  1  Micrococcus luteus  1  Brachybacterium  1  Aerococcus viridans  1  Staphylococcus epidermidis  2  macrococcus caseolyticus  3  Brachybacterium  2  Brachybacterium nesterenkoii  1  Bacillus licheniformis  1  Bacillus  1  Exiguobacterium acetylicum  1  Corynebacterium  2  Staphylococcus saprophyticus  3  Microbacterium  1  Exiguobacterium acetylicum  1  Staphylococcus epidermidis  3  Streptomyces zaomyceticus  1  Exiguobacterium acetylicum  1  Staphylococcus gallinarum  1  Corynebacterium jeikeium  1  Staphylococcus caprae  2  Staphylococcus chromogenes  2  Psychrobacter cibarius  1  Staphylococcus sciuri  2  macrococcus caseolyticus  4  Staphylococcus saprophyticus  1  Corynebacterium xerosis  2  Staphylococcus  1  Acinetobacter radioresistens  1  Aerococcus viridans  1  Micrococcus  2  Bacillus licheniformis  1  macrococcus caseolyticus  3  Corynebacterium xerosis  1  Acinetobacter calcoaceticus  1  Klebsiella pneumoniae  1  Staphylococcus caprae  1  Brevibacterium luteolum  1  Brevibacterium  1  Staphylococcus hominis  2  Streptomyces netropsis  1      Corynebacterium jeikeium  3  Staphylococcus chromogenes  2      Enterococcus cecorum  1  Acinetobacter radioresistens  1      Staphylococcus lentus  1  Corynebacterium xerosis  1      paracoccus solventivorans  1          Staphylococcus epidermidis  1  Streptomyces griseoaurantiacus  1                  Pseudomonas stutzeri  1      View Large Identification of Bacteria with 16S rRNA High-throughput Sequencing As shown in Figure 3A, 21 species of known bacteria, 5 species of unknown bacteria, and a species of Archaea were identified at the phylum level in fine particulate matter samples. By quantity, the top 10 species were of Firmicutes, Bacteroidetes, Proteobacteria, Actinobacteria, Cyanobacteria, Fusobacteria, Tenericutes, Acidobacteria, and Chloroflexi. Among them, Firmicutes accounted for the highest proportion (48.41 to 78.90%), followed by Bacteroidetes (3.05 to 21.15%), Proteobacteria (5.38 to 15.28%), and Actinobacteria (6.27 to 13.24%). At the family level, 146 species were known bacteria, and 16 species were unknown bacteria. The top 10 species were of Ruminococcaceae, Lachnospiraceae, Bacteroidaceae, Enterobacteriaceae, Lactobacillaceae, Micrococcaceae, Fusobacteriaceae, Coriobacteriaceae, Veillonellaceae, and Erysipelotrichaceae. Ruminococcaceae, Lachnospiraceae, and Lactobacillaceae accounted for 15.14 to 44.36%, 10.15 to 16.88%, and 1.09 to 10.94% of the species, respectively (Figure 3B). At the genus level, 224 were of known strains and 9 were of unknown strains. By quantity, the top 10 species were of Faecalibacterium, Bacteroides, Escherichia, Lactobacillus, Micrococcus, Oscillospira, Kocuria, Ruminococcus, Corynebacterium, and Megamonas. The dominant species were Faecalibacterium (5.77 to 31.63%), Bacteroides (1.08 to 10.83%), Lactobacillus (4.03 to 6.49%), and Escherichia (0.80 to 6.92%), as shown in Figure 3C. The relative abundance of Escherichia in the broiler houses was 5.17%, which was greater than its 0.99% in layer houses (P < 0.05), as Figure 3D shows. Similarly, the relative abundance of Corynebacterium in broiler houses was 1.94%, which was higher than that in layer houses (P > 0.05; Figure 3E). Figure 3. View largeDownload slide Relative abundance of bacteria in poultry houses. (A) Relative abundance of sequences belonging to the top 10 bacteria at the phylum level. (B) Relative abundance at the family level. (C) Relative abundance at the genus level. (D) Relative abundance of genera Escherichia and (E) Corynebacterium. Bars were expressed as means ± SD (n = 3). Student's t test was conducted to examine differences. *, P < 0.05. Figure 3. View largeDownload slide Relative abundance of bacteria in poultry houses. (A) Relative abundance of sequences belonging to the top 10 bacteria at the phylum level. (B) Relative abundance at the family level. (C) Relative abundance at the genus level. (D) Relative abundance of genera Escherichia and (E) Corynebacterium. Bars were expressed as means ± SD (n = 3). Student's t test was conducted to examine differences. *, P < 0.05. Identification of Fungi with ITS1 High-throughput Sequencing At the phylum level, 5 species were known, whereas 5 were unknown. By quantity, the top 10 species were of Ascomycota, Basidiomycota, un–s-Fungi sp, un–s-fungal sp K6, un–s-fungal sp 38 CC 06_28, Chytridiomycota, Glomeromycota, Zygomycota, un–s-fungal sp APA_2013, un–s-Cystobasidium, and Pallidum. The dominant fungi were of Ascomycota (39.49 to 68.22%) and Basidiomycota (3.54 to 37.49%), as shown in Figure 4A. At the family level, 83 species were known, and 110 species were unknown. By quantity, the top 10 species were of Trichocomaceae, un-s-Agaricomycetes sp, un-s-Agaricales sp, Davidiellaceae, Pleosporaceae, un-s-Polyporalessp, un-s-Ascomycota sp, un-s-Hypocrealessp, un-s-Hymenochaetales sp, and Hypocreaceae (Figure 4B). Lastly, at the genus level, 75 species were known, and 175 species were unknown. Also by quantity, the top 10 main species were of Aspergillus, un-s-Agaricomycetes sp, un-s-Agaricalessp, un-S-Pleosporaceae sp RS_5, un-s -Polyporalessp, Davidiella, un-s-Ascomycota sp, un-s-Trichocomaceae sp, Cladosporium, and un-s-Hypocreales sp. (Figure 4C). The relative abundance of Aspergillus was 19.35% in layer houses, compared to 4.74% in broiler houses (Figure 4D), whereas the relative abundance of Penicillium was 0.88% in layer houses, which was higher than that in the broiler houses (Figure 4E). Figure 4. View largeDownload slide Relative abundance of fungi in the poultry houses. (A) Relative abundance of sequences belonging to top 10 fungi at the phylum level. (B) Relative abundance at the family level. (C) Relative abundance at the genus level. (D) Relative abundance of genera Aspergillus and (E) Penicillium. Bars were expressed as means ± SD (n = 3). Student's t test was conducted to examine differences. *, P < 0.05. Figure 4. View largeDownload slide Relative abundance of fungi in the poultry houses. (A) Relative abundance of sequences belonging to top 10 fungi at the phylum level. (B) Relative abundance at the family level. (C) Relative abundance at the genus level. (D) Relative abundance of genera Aspergillus and (E) Penicillium. Bars were expressed as means ± SD (n = 3). Student's t test was conducted to examine differences. *, P < 0.05. Fine Particulate Matter Concentration and Microbial Diversity Analysis Concentrations of fine particulate matter in chicken houses ranged from 114 to 230 μg/m3 (Table 4), and there was no significant difference between layer and broiler houses (P > 0.05). Per Shannon diversity analysis, bacterial diversity was greater in broiler houses, for a Shannon value of 7.83, compared to 6.92 in layer houses (P < 0.05). By contrast, the diversity of the fungal species in layer houses was greater than in broiler houses (Table 5). Table 4. Quality and concentration of fine particulate matter in poultry houses Poultry house  A  B  C  D  E  F  Quality (mg)  45.8  46.9  49.0  32.8  46.9  66.2  Concentration (μg/m3)  159  163  170  114  150  230  Poultry house  A  B  C  D  E  F  Quality (mg)  45.8  46.9  49.0  32.8  46.9  66.2  Concentration (μg/m3)  159  163  170  114  150  230  View Large Table 5. Shannon and Simpson indices of bacteria and fungi in broiler and layer houses.   Bacteria  Fungus    Shannon  Simpson  Shannon  Simpson  Broiler house  7.83 ± 0.30a  0.99  4.15 ± 0.57  0.86 ± 0.04  Layer house  6.917 ± 0.57b  0.9465 ± 0.04  4.23 ± 0.51  0.90 ± 0.01    Bacteria  Fungus    Shannon  Simpson  Shannon  Simpson  Broiler house  7.83 ± 0.30a  0.99  4.15 ± 0.57  0.86 ± 0.04  Layer house  6.917 ± 0.57b  0.9465 ± 0.04  4.23 ± 0.51  0.90 ± 0.01  Data are presented as means ± SD (n = 3). a,bValues with different superscripts in the same column differ significantly (P < 0.05). Student's t test was conducted to examine differences. View Large DISCUSSION Aerosols particulate matter originating from biological sources, such as bacteria, fungi, pollen, and animal and plant debris, constituted up to 25% of the total atmospheric aerosols (Jaenicke, 2005), and many scholars have proved that the concentrations of aerosol bacterial and fungal in poultry houses are higher than in other animal houses (Radon et al., 2002; Bakutis et al., 2004). Previous study has shown that, after the flock entered the clean poultry house, the concentrations of culturable bacteria and fungi increased up to the level of 2.6 × 106 CFU/m3 and 1.8 × 105 CFU/m3, respectively (Lawniczekwalczyk et al., 2013). In our research, the concentrations of airborne bacteria and fungi in chicken houses were 0.167 to 4.484 × 104 CFU/m3 and 0.236 to 4.735 × 103 CFU/m3, respectively. The concentration of aerosols obtained in all houses except House A was slightly lower than the limit recorded (2.5 × 104 CFU/m3) in the Farmland Environmental Quality Evaluation Standards for Livestock and Poultry Production (N/YT 388–1999) by the Ministry of Environmental Protection of the People's Republic of China. Of all chicken houses, the concentrations of airborne bacteria, fungi, and E. coli were greatest in House A, perhaps because sampling in House A occurred in early spring, when the ambient temperature was low and the ventilation poor. The concentration of bacteria in the air was generally greater than that of fungi, which aligns with the findings of a previous study (Lawniczekwalczyk et al., 2013). The breeding mode of poultry is an important factor for the formation of microbial aerosols; whereas laying hens are cage rearing, broilers are floor rearing. Broilers have a broader range of activity, which facilitates microbial aerosol formation. A direct cause-effect relationship between animal activity and dust concentration was obtained (Calvet et al., 2009). The particle size of specimens at levels 5 and 6 is equivalent to fine particulate matter. Fine particulate matter is more likely to penetrate and deposit deeper into the tracheobronchial and alveolar regions, and cause bronchitis, asthma, cardiovascular disease, and other diseases in humans and animals (Yao et al., 2002). In this study, the proportions of bacteria and fungi at levels 5 and 6 of the Andersen-6 sampler were 11.4 to 34.3% and 16.8 to 37.5%, respectively. Similar research shows that the smallest bacterial particles (0.65 to 2.1 μm) constituted a significant fraction (65 to 78%) of all bacterial particles in the composting plants, with the dominant fractions of fungal particles (1.1 to 2.1 μm) accounting for 22 to 38% (Gutarowska et al., 2015). Conditional pathogenic bacteria including Klebsiella pneumoniae, Staphylococcus epidermidis, Enterococcus, and Aerococcus viridans were cultured at levels 5 and 6. The bacteria obtained in the presented study are identified in poultry and swine house by other authors as well (Bakutis et al., 2004; Jo and Kang, 2005; Nehme et al., 2008; Brooks et al., 2010; Kristiansen et al., 2012; Lawniczekwalczyk et al., 2013; Roque et al., 2016), which indicates that these conditional pathogenic bacteria are ubiquitous in livestock and poultry houses. For one, Klebsiella pneumoniae can cause high mortality from systemic infection, pneumonia, meningitis, liver abscess, endophthalmitis, urinary system inflammation, wound infection, and systemic sepsis (Zhang et al., 2008). By contrast, Enterococcus widely exists in the intestinal tract in humans and animals, where it causes urinary tract infection, endocarditis, and wound and abdominal infection (Wisplinghoff et al., 2004). By still greater contrast, Aerococcus viridans is a model species of Aerococcus (Zaria, 1993), which can cause endocarditis, urinary tract infection, bacteremia, sepsis, meningitis, septic arthritis, and other diseases, particularly when immune function is low or dysfunctional (Untereker and Hanna, 1976; Jiang et al., 2013). Lastly, Staphylococcus epidermidis often exists on the surface of human or animal skin and mucous membrane, where it causes dermatitis in humans and animals (El-Asrar et al., 2000). On the whole, such conditional pathogens pose a serious risk to the health of animals and workers in and around chicken houses. The concentration of fine particulate matter in the chicken houses ranged from 114 μg/m3 to 230 μg/m3. The annual average guideline value of 10 μg/m3 for fine particulate matter was chosen to represent the lower end of the range over which significant effects on survival have been observed in the American Cancer Society (ACS) study (Iii et al., 2002). According to the Air Quality Guidelines formulated by the World Health Organization (WHO), when the 24-hour mean of fine particulate matter is more than 37.5 μg/m3, short-term mortality increased by 1.2% (Organization, 2014). Study has shown that the average concentration of fine particulate matter in chicken houses can be 69 μg/m3, and the average emission of each chicken was 3.738 mg/bird1/day1. The concentration of fine particulate matter showed an increase with age of the birds, as did emissions (Cambral-LóPez et al., 2009). Other research also pointed out that daily mean fine particulate matter concentration was 39 ± 8.0 μg/m3 in poultry houses (Lim et al., 2003). Apparently, the concentration of fine particulate matter obtained in the presented study is significantly higher than previous studies, which poses more potential threat to human and animal health. In this study, we also observed bacterial and fungal communities in fine particulate matter. The most phylum bacteria in fine particulate matter were Firmicutes (62.6%), Bacteroidetes (10.2%), Proteobacteria (9.4%), and Actinobacteria (8.5%). Studies have shown that the proportion of Firmicutes and Proteobacteria is 15.3 to 28.2% and 33.0 to 74.1% in air (Bowers et al., 2013; Gou et al., 2016; Du et al., 2017), which is remarkably different from poultry houses in our research. Analyses of the bacterial diversity of pig houses revealed that the dominant species was Firmicutes, which can account for 77% in the phylum level (Kristiansen et al., 2011). It has been reported that, compared with the out-group office environment, bioaerosols in the animal confinement buildings had a relatively higher abundance of Firmicutes, up to 76.6% in turkey houses (Hong et al., 2012). Firmicutes has been identified as the dominant phylum (∼60%) in the intestinal microbiota of chickens, followed by Bacteroidetes accounting for 22%, and Proteobacteria for 17% of the total microbiota (Videnska et al., 2014; Neira et al., 2017). It can thus be deduced that feces is the primary source of aerosols in poultry houses. At the genus level, the relative abundance of Escherichia was 5.17% in broiler houses and thus greater than that in layer houses (P > 0.05), which resembled the results of concentration of Escherichia from the Andersen sample collector. The high content of Escherichia poses a potential threat to the health of breeders and chickens, and might have factored into the high rate of E. coli infection in broiler houses. At the same time, the relative abundance of Corynebacterium, as a conditional pathogenic bacterium, was greater in broiler houses than in layer houses. It has been reported that Aspergillus, Cladosporium, and Penicillium were the most prevalent fungal genera in chicken houses (Jo and Kang, 2005). In this study, the content of Aspergillus was 13.5% at the genus level, which was significantly greater in layer houses than in broiler houses. Other studies have reported that, among a dozen poultry fungal diseases, the most dangerous pathogen is Aspergillus (Pinello et al., 1977; SO et al., 1978; Sauter et al., 1981a), which also can infect humans. Similarly, the relative abundance of Penicillium was greater in layer houses than in broiler houses. In previous researches, Escherichia, Aspergillus, and Penicillium were detected in poultry house (Jo and Kang, 2005; Lawniczekwalczyk et al., 2013; Roque et al., 2016). In addition, previous study has shown that 9 genera of molds were identified with over one-half of all isolates being either Aspergillus or Penicillium by plate counts (Sauter et al., 1981b). Furthermore, Aspergillus and Penicillium have been strongly associated with allergic respiratory diseases, such as allergenic rhinitis and asthma (Halonen et al., 1997; Ostro et al., 2001; Flannigan et al., 2011). Studies show that professional activities in poultry house are associated with constant exposure to bioaerosol, which may pose a health hazard to workers and animals (Jo and Kang, 2005; Nimmermark et al., 2009; Hong et al., 2012; Zhao et al., 2016). The present study confirms the importance of microbiological monitoring and control in fine particulate matter of animal husbandry to ensure animal and worker welfare. All bacteria and fungi are detected in the fine particulate matter samples via high-throughput sequencing, which can be qualitatively analyzed at the phylum, class, order, family, genus, and species levels. However, quantitatively characterized data of bacteria and fungi are obtained using a method involving the Andersen sampler only. Therefore, the Andersen sampler still is necessary for the detection of airborne microbes. Altogether, in the fine particulate matter samples, bacteria were more diverse in broiler houses, whereas fungi were more diverse in layer houses. The composition of microbial communities also differed between layer and broiler houses. As mentioned, the chief source of microorganisms in the air was feces, and the composition of microbial communities in the intestinal tracts of animals related closely to the species, given different nutritional requirements, feed composition, and feed modes for different species. Therefore, the composition of the microbial community differs in layer and broiler houses, and the communities have certain specie-related characteristics. SUPPLEMENTARY DATA Supplementary data are available at Poultry Science online. 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Detection and analysis of fine particulate matter and microbial aerosol in chicken houses in Shandong Province, China

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Oxford University Press
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© 2017 Poultry Science Association Inc.
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0032-5791
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1525-3171
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10.3382/ps/pex388
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Abstract

Abstract Bacteria and fungi are primary constituents of airborne microbes in fine particulate matter and harmful to health. To evaluate the environmental quality of different poultry houses in Shandong Province, China, the airborne aerobic bacteria, airborne fungi, and airborne Escherichia coli were collected by the Andersen-6 air microorganism sampler. The fine particulate matter was collected by a ZR-3920 ambient air particulate matter sampler, and bacterial and fungal diversities and relative abundances analyzed using high-throughput sequencing. Results showed that the concentrations of airborne aerobic bacteria, airborne fungi, and airborne Escherichia coli in poultry houses were 0.167 to 4.484 × 104 CFU/m3, 0.236 to 4.735 × 103 CFU/m3, and 0 to 33.0 CFU/m3, respectively. 11.4 to 34.3% of aerobic bacteria and 16.8 to 37.5% of fungi were distributed at levels 5 and 6 (0.6 to 2.1 μm, the particle sizes similar to fine particulate matter) in the Andersen sampler. The concentration of fine particulate matter in the poultry houses was 114 to 230 μg/m3, which was higher than the safety value 10 specified by WHO. In fine particulate matter, the main bacteria at phylum level were Firmicutes, Bacteroidetes, and Proteobacteria, whereas the dominant phylum of fungus was Ascomycota and Basidiomycota. Importantly, the relative abundances of Escherichia and Corynebacterium in the broiler houses were greater than those in layer houses. However, the percentages of Aspergillus and Penicillium were 13.5 and 0.56%, with a relatively high level in the layer houses. Altogether, results revealed that the ambient air quality in the poultry houses sampled had a relatively high abundance of conditional pathogenic bacteria and concentration of fine particulate matter, which could threaten the health of animals and workers in those environments. INTRODUCTION Severe indoor environmental pollution arising from intensive poultry farming has caused serious harm to poultry and human health in those environments, primarily due to suspended particles in the air, including total suspended particulate and respirable particulate matter. Numerous studies have shown that long-term exposure to high concentrations of airborne particles increases both the morbidity and mortality of human diseases and reduces the life expectancy of humans (Hunt et al., 2003; Pope et al., 2009). In particular, fine particulate matter considerably threatens human health by entering the trachea and penetrating deep into the lungs, bronchi, and alveoli (Brook et al., 2004). As a result of the normal activities of chickens and breeders, microorganisms and chemical particles in the environments of chicken farms can form aerosols, which can be divided into biological and non-biological components. Bioaerosol, primarily derived from animal dander and feces, as well as feed (Radon et al., 2002; Cambralópez et al., 2010), account for more than 25% of aerosols (Jaenicke, 2005). Among microbial components, fungal spores and bacteria with diameters of 1 to 30 μm and 0.25 to 8 μm, respectively, form part of respirable particulate matter (Comrie and Thomson, 1906; Stanley and Linskens, 1974). Multiple studies have shown that concentrations of airborne microbes at poultry farms often exceed 106 CFU/m3 (Radon et al., 2002; Bakutis et al., 2004). For both poultry and humans, long-term exposure to high concentrations of microbial aerosols in particular can cause upper respiratory tract irritation, chronic bronchitis, and organic dust toxicity syndrome, among other respiratory symptoms (Donham et al., 2000). However, few studies have focused on fine particulate matter in poultry houses in China. Although the concentrations of fine particulate matter in the chicken houses were measured, biological properties of the environmental quality remain unmeasured (Lim et al., 2003; Cambral-LóPez et al., 2009). At the same time, at least one study has demonstrated that the impacts of particulate matter on humans and animals relate not only to the concentrations of particulate matter and microbes, but also the composition of microorganisms (Aarnink et al., 2010). In response to both strands of research, in this study, concentrations and compositions of microbial aerosols and fine particulate matter at chicken farms in Shandong Province, China, using different feeding modes, were monitored, the bacteria and fungi in the fine particulate matter were identified, and air quality was evaluated. MATERIALS AND METHODS Chicken Farms Six chicken farms (Table 1) were selected from the area surrounding Tai’an, Shandong, China. Table 1. Description of poultry houses. Poultry house  Time (year month)  Animals  Temperature  Relative humidity (%)  Ventilation  Clean up feces  Aa  15.04  broiler  26°C  80  bad  4 to 5 d/time  B  15.06  broiler  25°C  70  good  3 to 4 d/time  C  15.07  broiler  35°C  78  good  2 to 3 d/time  Db  15.07  layer  25°C  85  good  1 d/time  E  15.08  layer  32°C  76  good  1 d/time  F  15.10  layer  21°C  40  good  1 d/time  Poultry house  Time (year month)  Animals  Temperature  Relative humidity (%)  Ventilation  Clean up feces  Aa  15.04  broiler  26°C  80  bad  4 to 5 d/time  B  15.06  broiler  25°C  70  good  3 to 4 d/time  C  15.07  broiler  35°C  78  good  2 to 3 d/time  Db  15.07  layer  25°C  85  good  1 d/time  E  15.08  layer  32°C  76  good  1 d/time  F  15.10  layer  21°C  40  good  1 d/time  aHeated by coal stove. bWetted by water curtain. View Large Content Determination of Airborne Bacteria and Escherichia Coli Samples were collected on an Andersen-6 microbial sample collector (Andersen, 1958) using 5% blood agar medium for airborne bacteria and eosin-methylene blue medium for airborne Escherichia coli (E. coli) as the sampling media. The E. coli colony is bluish green with a metallic luster. The sample collector was centered in each chicken house at a height of 30 to 40 cm above the ground (i.e., the height of the chicken's nasal cavity) with an airflow rate of 28.3 L/min. Six replicate samples were collected from each chicken house. To accommodate different health conditions, the driving time was set at 1 to 5 min and 5 to 15 min for bacteria and E. coli, respectively, and the number of colonies per level was 30 to 300. After aerobically culturing the culture medium 37°C for 24 to 48 h, colonies were counted, and the bacteria and E. coli content (CFU/m3) were calculated according to correction table (Andersen, 1958). Content Determination of Airborne Fungi Samples were collected on an Andersen-6 microbial sample collector (Andersen, 1958) using Sabouraud agar as the sampling medium, and an airflow rate of 28.3 L/min. The sample collector was centered in each chicken house at a height of 30 to 40 cm above the ground. Six replicate samples were collected from each chicken house. To accommodate different health conditions, the driving time was set at 1 to 5 minutes. After aerobically culturing the culture medium at 25°C for 5 to 7 d, colonies were counted, and fungus content (CFU/m3) was calculated according to correction table (Andersen, 1958). Identification of Airborne Bacteria at Levels 5 and 6 of the Andersen-6 Sampler Single colonies at levels 5 and 6 of the Andersen-6 sampler were isolated and cultured in 5% blood agar. The bacteria were identified by the 16S rRNA sequence analysis. The primers were 27F-AGAGTTTGATCCTGGCTCAG and 1492R-ACGGCTACCTTGTTACGACTT. The 16S rRNA sequences were blasted in NCBI (Kolbert and Persing, 1999; Relman, 1999; Clarridge, 2004). Sample Collection and Analysis of Fine Particulate Matter Samples of fine particulate matter were collected by waterproof air sampling filters (HaoChenTianCheng Ltd., Beijing, China) with typical aerosol retention of 99.99%, using a ZR-3920 ambient air particulate matter (total suspended particulate/inhalable particles/fine particulate matter) sampler (Zhongrui Ltd., Qingdao, China). The filters were baked in a furnace at 500 °C for at least 6 h prior to sampling. Airflow rate was set at 100 L/min, the sampling height was 1 m, and the acquisition time was 48 hours. Three replicate samples were collected from each chicken house. The concentration of fine particulate matter (μg/m3) was calculated according to the equation: C = (W1-W0)/(t × F). The blank filters were weighted on a Microbalance (W0). After sampling, the filters with fine particulate matter samples were weighted to obtain (W1). The t is collection time, and the F is air flow of the sample. Total genomic DNA was extracted directly from fine particulate matter samples using FastDNA® spin kit (MP biomedicals, Santa Ana, CA) following the manufacturer's protocol. The V3-V4 region of bacterial 16S rRNA and the Internal Transcribed Spacer (Lawniczekwalczyk et al., 2013) regions of fungi were sequenced using the upgraded HiSeq sequencing platform, and sequences were analyzed with the Quantitative Insights Into Microbial Ecology software package (http://qiime.org/index.html) and UPARSE pipeline (http://drive5.com/uparse/). The reads were first filtered with Quantitative Insights Into Microbial Ecology quality filters using default settings for Illumina processing. The UCLUST method was used to cluster sequences into operational taxonomic units (OTU) at an identity threshold of 97%, while the RDP classifier was used to assign each OTU to a taxonomic level (Table 2). Additional analyses for rarefaction curves and Shannon index were performed with Quantitative Insights Into Microbial Ecology. Table 2. Sequencing data of bacterial and fungi in all samples.     Bacteria  Fungi  House name  Sample name  Clean reads  OUT  Clean reads  OUT    1  50,843  1421  55,132  440  A  2  52,649  1335  51,088  400    3  49,716  1291  50,111  393    1  53,178  1230  50,984  289  B  2  52,189  1378  51,201  252    3  48,909  1419  53,320  255    1  59,010  1145  55,018  350  C  2  51,398  1356  51,144  326    3  54,946  1259  50,619  307    1  43,393  1570  52,189  378  D  2  48,067  1486  58,397  365    3  41,764  1299  59,718  345    1  40,458  1338  40,011  459  E  2  49,103  1183  45,696  406    3  46,893  1295  45,171  389    1  52,340  1780  40,191  251  F  2  58,901  1377  39,443  258    3  48,914  1267  39,319  283      Bacteria  Fungi  House name  Sample name  Clean reads  OUT  Clean reads  OUT    1  50,843  1421  55,132  440  A  2  52,649  1335  51,088  400    3  49,716  1291  50,111  393    1  53,178  1230  50,984  289  B  2  52,189  1378  51,201  252    3  48,909  1419  53,320  255    1  59,010  1145  55,018  350  C  2  51,398  1356  51,144  326    3  54,946  1259  50,619  307    1  43,393  1570  52,189  378  D  2  48,067  1486  58,397  365    3  41,764  1299  59,718  345    1  40,458  1338  40,011  459  E  2  49,103  1183  45,696  406    3  46,893  1295  45,171  389    1  52,340  1780  40,191  251  F  2  58,901  1377  39,443  258    3  48,914  1267  39,319  283  View Large Data Analyses The median of concentrations was used to represent the aerosol concentration, whereas the maximum and minimum values were used for the range of aerosol concentrations. A Student's t test was performed to examine significant differences among treatments using Statistical Package for the Social Sciences 19.0 software (IBM, Chicago, IL). RESULTS Airborne Bacteria and Fungi The concentrations of the airborne aerobic bacteria were 0.385 to 4.484 × 104 CFU/m3 in the broiler houses and 0.167 to 0.742 × 104 CFU/m3 in the layer houses (Figure 1A), whereas the concentrations of airborne E. coli were 0 to 33.0 CFU/m3 in the broiler houses and 0 to 14.1CFU/m3 in the layer houses (Figure 1B). Concentrations of airborne fungi were 0.236 to 4.735 × 103 CFU/m3 in the broiler houses and 1.319 to 2.326 × 103 CFU/m3 in layer houses (Figure 1C). Figure 1. View largeDownload slide Box plot of the concentration of airborne bacteria and fungi in poultry houses. (A) Concentration of airborne aerobic bacteria, (B) airborne E. coli, and (C) airborne fungi. Boxes correspond to the interquartile range between the 25th and 75th percentiles, and central lines represent the 50th percentile. Whiskers correspond to the maximum and minimum values. Figure 1. View largeDownload slide Box plot of the concentration of airborne bacteria and fungi in poultry houses. (A) Concentration of airborne aerobic bacteria, (B) airborne E. coli, and (C) airborne fungi. Boxes correspond to the interquartile range between the 25th and 75th percentiles, and central lines represent the 50th percentile. Whiskers correspond to the maximum and minimum values. Distribution of Airborne Bacteria and Fungi on the Andersen-6 Sampler Results of measuring the distribution of airborne bacteria and fungi on the Andersen sampler on the 6 chicken farms revealed 17.6 to 49.7% distribution of aerobes at level 1 (> 7 μm) and level 2 (4.7 to μm), 29.8 to 51.2% at level 3 (3.3 to 4.7 μm) and level 4 (2.1 to 3.3 μm), and 11.4 to 34.3% at level 5 (1.1 to 2.1 μm) and level 6 (0.6 to 1.1 μm), as Figure 2A shows. Distributions of fungi were 15.6 to 32.0% at levels 1 and 2, 39.6 to 54% at levels 3 and 4, and 16.8 to 37.5% at levels 5 and 6 (Figure 2B). Figure 2. View largeDownload slide Size distributions of airborne bacteria and fungi at sampling locations in the poultry house. (A) Size distributions of airborne bacteria and (B) airborne fungi; aerodynamic diameter ranges for the viable particle sizing sampler were > 7.0 μm (first stage), 4.7 to 7.0 μm (second stage), 3.3 to 4.7 μm (fourth stage), 2.1 to 3.3 μm (fourth stage), 1.1 to 2.1 μm (fifth stage), and 0.6 to 1.1 μm (sixth stage). Figure 2. View largeDownload slide Size distributions of airborne bacteria and fungi at sampling locations in the poultry house. (A) Size distributions of airborne bacteria and (B) airborne fungi; aerodynamic diameter ranges for the viable particle sizing sampler were > 7.0 μm (first stage), 4.7 to 7.0 μm (second stage), 3.3 to 4.7 μm (fourth stage), 2.1 to 3.3 μm (fourth stage), 1.1 to 2.1 μm (fifth stage), and 0.6 to 1.1 μm (sixth stage). Bacteria Composition at Levels 5 and 6 of the Andersen-6 Sampler Bacteria collected at levels 5 and 6 of the Andersen sampler included 25 strains from House A, 27 strains from House B, 25 from House C, 18 from House D, 25 from House E, and 16 from House F, all composed of 10 Gram-negative and 103 Gram-positive bacteria. The predominant genera of bacteria were Staphylococcus, Corynebacterium, and Macrococcus, which accounted for 50.0 to 81.5% of identified strains (Table 3). Table 3. Bacteria of the levels 5 and 6 of the Andersen sampler. A  B  C  D  E  F  Bacterial family  Number  Bacterial family  Number  Bacterial family  Number  Bacterial family  Number  Bacterial family  Number  Bacterial family  number  Staphylococcus epidermidis  2  Corynebacterium jeikeium  1  macrococcus caseolyticus  11  Staphylococcus saprophyticus  2  Brevibacterium Otitidis  1  Corynebacterium xerosis canis  2  Staphylococcus  4  Brevibacterium  1  Enterococcus faecalis  1  Enterococcus faecalis  1  Corynebacterium  2  Rothia nasimurium  1  Klebsiella pneumoniae  1  Corynebacterium  9  Staphylococcus kloosii  1  Bacillus simplex  1  Staphylococcus  1  Staphylococcus sciuri  1  Enterococcus faecalis  1  Corynebacterium amycolatum  2  Rhodococcus ruber  1  Micrococcus luteus  2  Micrococcus luteus  1  Exiguobacterium acetylicum  1  Corynebacterium  6  Staphylococcus saprophyticus  1  Staphylococcus hominis  2  Staphylococcus equorum  2  Bacillus subtilis  1  Micrococcus luteus  1  Brachybacterium  1  Aerococcus viridans  1  Staphylococcus epidermidis  2  macrococcus caseolyticus  3  Brachybacterium  2  Brachybacterium nesterenkoii  1  Bacillus licheniformis  1  Bacillus  1  Exiguobacterium acetylicum  1  Corynebacterium  2  Staphylococcus saprophyticus  3  Microbacterium  1  Exiguobacterium acetylicum  1  Staphylococcus epidermidis  3  Streptomyces zaomyceticus  1  Exiguobacterium acetylicum  1  Staphylococcus gallinarum  1  Corynebacterium jeikeium  1  Staphylococcus caprae  2  Staphylococcus chromogenes  2  Psychrobacter cibarius  1  Staphylococcus sciuri  2  macrococcus caseolyticus  4  Staphylococcus saprophyticus  1  Corynebacterium xerosis  2  Staphylococcus  1  Acinetobacter radioresistens  1  Aerococcus viridans  1  Micrococcus  2  Bacillus licheniformis  1  macrococcus caseolyticus  3  Corynebacterium xerosis  1  Acinetobacter calcoaceticus  1  Klebsiella pneumoniae  1  Staphylococcus caprae  1  Brevibacterium luteolum  1  Brevibacterium  1  Staphylococcus hominis  2  Streptomyces netropsis  1      Corynebacterium jeikeium  3  Staphylococcus chromogenes  2      Enterococcus cecorum  1  Acinetobacter radioresistens  1      Staphylococcus lentus  1  Corynebacterium xerosis  1      paracoccus solventivorans  1          Staphylococcus epidermidis  1  Streptomyces griseoaurantiacus  1                  Pseudomonas stutzeri  1      A  B  C  D  E  F  Bacterial family  Number  Bacterial family  Number  Bacterial family  Number  Bacterial family  Number  Bacterial family  Number  Bacterial family  number  Staphylococcus epidermidis  2  Corynebacterium jeikeium  1  macrococcus caseolyticus  11  Staphylococcus saprophyticus  2  Brevibacterium Otitidis  1  Corynebacterium xerosis canis  2  Staphylococcus  4  Brevibacterium  1  Enterococcus faecalis  1  Enterococcus faecalis  1  Corynebacterium  2  Rothia nasimurium  1  Klebsiella pneumoniae  1  Corynebacterium  9  Staphylococcus kloosii  1  Bacillus simplex  1  Staphylococcus  1  Staphylococcus sciuri  1  Enterococcus faecalis  1  Corynebacterium amycolatum  2  Rhodococcus ruber  1  Micrococcus luteus  2  Micrococcus luteus  1  Exiguobacterium acetylicum  1  Corynebacterium  6  Staphylococcus saprophyticus  1  Staphylococcus hominis  2  Staphylococcus equorum  2  Bacillus subtilis  1  Micrococcus luteus  1  Brachybacterium  1  Aerococcus viridans  1  Staphylococcus epidermidis  2  macrococcus caseolyticus  3  Brachybacterium  2  Brachybacterium nesterenkoii  1  Bacillus licheniformis  1  Bacillus  1  Exiguobacterium acetylicum  1  Corynebacterium  2  Staphylococcus saprophyticus  3  Microbacterium  1  Exiguobacterium acetylicum  1  Staphylococcus epidermidis  3  Streptomyces zaomyceticus  1  Exiguobacterium acetylicum  1  Staphylococcus gallinarum  1  Corynebacterium jeikeium  1  Staphylococcus caprae  2  Staphylococcus chromogenes  2  Psychrobacter cibarius  1  Staphylococcus sciuri  2  macrococcus caseolyticus  4  Staphylococcus saprophyticus  1  Corynebacterium xerosis  2  Staphylococcus  1  Acinetobacter radioresistens  1  Aerococcus viridans  1  Micrococcus  2  Bacillus licheniformis  1  macrococcus caseolyticus  3  Corynebacterium xerosis  1  Acinetobacter calcoaceticus  1  Klebsiella pneumoniae  1  Staphylococcus caprae  1  Brevibacterium luteolum  1  Brevibacterium  1  Staphylococcus hominis  2  Streptomyces netropsis  1      Corynebacterium jeikeium  3  Staphylococcus chromogenes  2      Enterococcus cecorum  1  Acinetobacter radioresistens  1      Staphylococcus lentus  1  Corynebacterium xerosis  1      paracoccus solventivorans  1          Staphylococcus epidermidis  1  Streptomyces griseoaurantiacus  1                  Pseudomonas stutzeri  1      View Large Identification of Bacteria with 16S rRNA High-throughput Sequencing As shown in Figure 3A, 21 species of known bacteria, 5 species of unknown bacteria, and a species of Archaea were identified at the phylum level in fine particulate matter samples. By quantity, the top 10 species were of Firmicutes, Bacteroidetes, Proteobacteria, Actinobacteria, Cyanobacteria, Fusobacteria, Tenericutes, Acidobacteria, and Chloroflexi. Among them, Firmicutes accounted for the highest proportion (48.41 to 78.90%), followed by Bacteroidetes (3.05 to 21.15%), Proteobacteria (5.38 to 15.28%), and Actinobacteria (6.27 to 13.24%). At the family level, 146 species were known bacteria, and 16 species were unknown bacteria. The top 10 species were of Ruminococcaceae, Lachnospiraceae, Bacteroidaceae, Enterobacteriaceae, Lactobacillaceae, Micrococcaceae, Fusobacteriaceae, Coriobacteriaceae, Veillonellaceae, and Erysipelotrichaceae. Ruminococcaceae, Lachnospiraceae, and Lactobacillaceae accounted for 15.14 to 44.36%, 10.15 to 16.88%, and 1.09 to 10.94% of the species, respectively (Figure 3B). At the genus level, 224 were of known strains and 9 were of unknown strains. By quantity, the top 10 species were of Faecalibacterium, Bacteroides, Escherichia, Lactobacillus, Micrococcus, Oscillospira, Kocuria, Ruminococcus, Corynebacterium, and Megamonas. The dominant species were Faecalibacterium (5.77 to 31.63%), Bacteroides (1.08 to 10.83%), Lactobacillus (4.03 to 6.49%), and Escherichia (0.80 to 6.92%), as shown in Figure 3C. The relative abundance of Escherichia in the broiler houses was 5.17%, which was greater than its 0.99% in layer houses (P < 0.05), as Figure 3D shows. Similarly, the relative abundance of Corynebacterium in broiler houses was 1.94%, which was higher than that in layer houses (P > 0.05; Figure 3E). Figure 3. View largeDownload slide Relative abundance of bacteria in poultry houses. (A) Relative abundance of sequences belonging to the top 10 bacteria at the phylum level. (B) Relative abundance at the family level. (C) Relative abundance at the genus level. (D) Relative abundance of genera Escherichia and (E) Corynebacterium. Bars were expressed as means ± SD (n = 3). Student's t test was conducted to examine differences. *, P < 0.05. Figure 3. View largeDownload slide Relative abundance of bacteria in poultry houses. (A) Relative abundance of sequences belonging to the top 10 bacteria at the phylum level. (B) Relative abundance at the family level. (C) Relative abundance at the genus level. (D) Relative abundance of genera Escherichia and (E) Corynebacterium. Bars were expressed as means ± SD (n = 3). Student's t test was conducted to examine differences. *, P < 0.05. Identification of Fungi with ITS1 High-throughput Sequencing At the phylum level, 5 species were known, whereas 5 were unknown. By quantity, the top 10 species were of Ascomycota, Basidiomycota, un–s-Fungi sp, un–s-fungal sp K6, un–s-fungal sp 38 CC 06_28, Chytridiomycota, Glomeromycota, Zygomycota, un–s-fungal sp APA_2013, un–s-Cystobasidium, and Pallidum. The dominant fungi were of Ascomycota (39.49 to 68.22%) and Basidiomycota (3.54 to 37.49%), as shown in Figure 4A. At the family level, 83 species were known, and 110 species were unknown. By quantity, the top 10 species were of Trichocomaceae, un-s-Agaricomycetes sp, un-s-Agaricales sp, Davidiellaceae, Pleosporaceae, un-s-Polyporalessp, un-s-Ascomycota sp, un-s-Hypocrealessp, un-s-Hymenochaetales sp, and Hypocreaceae (Figure 4B). Lastly, at the genus level, 75 species were known, and 175 species were unknown. Also by quantity, the top 10 main species were of Aspergillus, un-s-Agaricomycetes sp, un-s-Agaricalessp, un-S-Pleosporaceae sp RS_5, un-s -Polyporalessp, Davidiella, un-s-Ascomycota sp, un-s-Trichocomaceae sp, Cladosporium, and un-s-Hypocreales sp. (Figure 4C). The relative abundance of Aspergillus was 19.35% in layer houses, compared to 4.74% in broiler houses (Figure 4D), whereas the relative abundance of Penicillium was 0.88% in layer houses, which was higher than that in the broiler houses (Figure 4E). Figure 4. View largeDownload slide Relative abundance of fungi in the poultry houses. (A) Relative abundance of sequences belonging to top 10 fungi at the phylum level. (B) Relative abundance at the family level. (C) Relative abundance at the genus level. (D) Relative abundance of genera Aspergillus and (E) Penicillium. Bars were expressed as means ± SD (n = 3). Student's t test was conducted to examine differences. *, P < 0.05. Figure 4. View largeDownload slide Relative abundance of fungi in the poultry houses. (A) Relative abundance of sequences belonging to top 10 fungi at the phylum level. (B) Relative abundance at the family level. (C) Relative abundance at the genus level. (D) Relative abundance of genera Aspergillus and (E) Penicillium. Bars were expressed as means ± SD (n = 3). Student's t test was conducted to examine differences. *, P < 0.05. Fine Particulate Matter Concentration and Microbial Diversity Analysis Concentrations of fine particulate matter in chicken houses ranged from 114 to 230 μg/m3 (Table 4), and there was no significant difference between layer and broiler houses (P > 0.05). Per Shannon diversity analysis, bacterial diversity was greater in broiler houses, for a Shannon value of 7.83, compared to 6.92 in layer houses (P < 0.05). By contrast, the diversity of the fungal species in layer houses was greater than in broiler houses (Table 5). Table 4. Quality and concentration of fine particulate matter in poultry houses Poultry house  A  B  C  D  E  F  Quality (mg)  45.8  46.9  49.0  32.8  46.9  66.2  Concentration (μg/m3)  159  163  170  114  150  230  Poultry house  A  B  C  D  E  F  Quality (mg)  45.8  46.9  49.0  32.8  46.9  66.2  Concentration (μg/m3)  159  163  170  114  150  230  View Large Table 5. Shannon and Simpson indices of bacteria and fungi in broiler and layer houses.   Bacteria  Fungus    Shannon  Simpson  Shannon  Simpson  Broiler house  7.83 ± 0.30a  0.99  4.15 ± 0.57  0.86 ± 0.04  Layer house  6.917 ± 0.57b  0.9465 ± 0.04  4.23 ± 0.51  0.90 ± 0.01    Bacteria  Fungus    Shannon  Simpson  Shannon  Simpson  Broiler house  7.83 ± 0.30a  0.99  4.15 ± 0.57  0.86 ± 0.04  Layer house  6.917 ± 0.57b  0.9465 ± 0.04  4.23 ± 0.51  0.90 ± 0.01  Data are presented as means ± SD (n = 3). a,bValues with different superscripts in the same column differ significantly (P < 0.05). Student's t test was conducted to examine differences. View Large DISCUSSION Aerosols particulate matter originating from biological sources, such as bacteria, fungi, pollen, and animal and plant debris, constituted up to 25% of the total atmospheric aerosols (Jaenicke, 2005), and many scholars have proved that the concentrations of aerosol bacterial and fungal in poultry houses are higher than in other animal houses (Radon et al., 2002; Bakutis et al., 2004). Previous study has shown that, after the flock entered the clean poultry house, the concentrations of culturable bacteria and fungi increased up to the level of 2.6 × 106 CFU/m3 and 1.8 × 105 CFU/m3, respectively (Lawniczekwalczyk et al., 2013). In our research, the concentrations of airborne bacteria and fungi in chicken houses were 0.167 to 4.484 × 104 CFU/m3 and 0.236 to 4.735 × 103 CFU/m3, respectively. The concentration of aerosols obtained in all houses except House A was slightly lower than the limit recorded (2.5 × 104 CFU/m3) in the Farmland Environmental Quality Evaluation Standards for Livestock and Poultry Production (N/YT 388–1999) by the Ministry of Environmental Protection of the People's Republic of China. Of all chicken houses, the concentrations of airborne bacteria, fungi, and E. coli were greatest in House A, perhaps because sampling in House A occurred in early spring, when the ambient temperature was low and the ventilation poor. The concentration of bacteria in the air was generally greater than that of fungi, which aligns with the findings of a previous study (Lawniczekwalczyk et al., 2013). The breeding mode of poultry is an important factor for the formation of microbial aerosols; whereas laying hens are cage rearing, broilers are floor rearing. Broilers have a broader range of activity, which facilitates microbial aerosol formation. A direct cause-effect relationship between animal activity and dust concentration was obtained (Calvet et al., 2009). The particle size of specimens at levels 5 and 6 is equivalent to fine particulate matter. Fine particulate matter is more likely to penetrate and deposit deeper into the tracheobronchial and alveolar regions, and cause bronchitis, asthma, cardiovascular disease, and other diseases in humans and animals (Yao et al., 2002). In this study, the proportions of bacteria and fungi at levels 5 and 6 of the Andersen-6 sampler were 11.4 to 34.3% and 16.8 to 37.5%, respectively. Similar research shows that the smallest bacterial particles (0.65 to 2.1 μm) constituted a significant fraction (65 to 78%) of all bacterial particles in the composting plants, with the dominant fractions of fungal particles (1.1 to 2.1 μm) accounting for 22 to 38% (Gutarowska et al., 2015). Conditional pathogenic bacteria including Klebsiella pneumoniae, Staphylococcus epidermidis, Enterococcus, and Aerococcus viridans were cultured at levels 5 and 6. The bacteria obtained in the presented study are identified in poultry and swine house by other authors as well (Bakutis et al., 2004; Jo and Kang, 2005; Nehme et al., 2008; Brooks et al., 2010; Kristiansen et al., 2012; Lawniczekwalczyk et al., 2013; Roque et al., 2016), which indicates that these conditional pathogenic bacteria are ubiquitous in livestock and poultry houses. For one, Klebsiella pneumoniae can cause high mortality from systemic infection, pneumonia, meningitis, liver abscess, endophthalmitis, urinary system inflammation, wound infection, and systemic sepsis (Zhang et al., 2008). By contrast, Enterococcus widely exists in the intestinal tract in humans and animals, where it causes urinary tract infection, endocarditis, and wound and abdominal infection (Wisplinghoff et al., 2004). By still greater contrast, Aerococcus viridans is a model species of Aerococcus (Zaria, 1993), which can cause endocarditis, urinary tract infection, bacteremia, sepsis, meningitis, septic arthritis, and other diseases, particularly when immune function is low or dysfunctional (Untereker and Hanna, 1976; Jiang et al., 2013). Lastly, Staphylococcus epidermidis often exists on the surface of human or animal skin and mucous membrane, where it causes dermatitis in humans and animals (El-Asrar et al., 2000). On the whole, such conditional pathogens pose a serious risk to the health of animals and workers in and around chicken houses. The concentration of fine particulate matter in the chicken houses ranged from 114 μg/m3 to 230 μg/m3. The annual average guideline value of 10 μg/m3 for fine particulate matter was chosen to represent the lower end of the range over which significant effects on survival have been observed in the American Cancer Society (ACS) study (Iii et al., 2002). According to the Air Quality Guidelines formulated by the World Health Organization (WHO), when the 24-hour mean of fine particulate matter is more than 37.5 μg/m3, short-term mortality increased by 1.2% (Organization, 2014). Study has shown that the average concentration of fine particulate matter in chicken houses can be 69 μg/m3, and the average emission of each chicken was 3.738 mg/bird1/day1. The concentration of fine particulate matter showed an increase with age of the birds, as did emissions (Cambral-LóPez et al., 2009). Other research also pointed out that daily mean fine particulate matter concentration was 39 ± 8.0 μg/m3 in poultry houses (Lim et al., 2003). Apparently, the concentration of fine particulate matter obtained in the presented study is significantly higher than previous studies, which poses more potential threat to human and animal health. In this study, we also observed bacterial and fungal communities in fine particulate matter. The most phylum bacteria in fine particulate matter were Firmicutes (62.6%), Bacteroidetes (10.2%), Proteobacteria (9.4%), and Actinobacteria (8.5%). Studies have shown that the proportion of Firmicutes and Proteobacteria is 15.3 to 28.2% and 33.0 to 74.1% in air (Bowers et al., 2013; Gou et al., 2016; Du et al., 2017), which is remarkably different from poultry houses in our research. Analyses of the bacterial diversity of pig houses revealed that the dominant species was Firmicutes, which can account for 77% in the phylum level (Kristiansen et al., 2011). It has been reported that, compared with the out-group office environment, bioaerosols in the animal confinement buildings had a relatively higher abundance of Firmicutes, up to 76.6% in turkey houses (Hong et al., 2012). Firmicutes has been identified as the dominant phylum (∼60%) in the intestinal microbiota of chickens, followed by Bacteroidetes accounting for 22%, and Proteobacteria for 17% of the total microbiota (Videnska et al., 2014; Neira et al., 2017). It can thus be deduced that feces is the primary source of aerosols in poultry houses. At the genus level, the relative abundance of Escherichia was 5.17% in broiler houses and thus greater than that in layer houses (P > 0.05), which resembled the results of concentration of Escherichia from the Andersen sample collector. The high content of Escherichia poses a potential threat to the health of breeders and chickens, and might have factored into the high rate of E. coli infection in broiler houses. At the same time, the relative abundance of Corynebacterium, as a conditional pathogenic bacterium, was greater in broiler houses than in layer houses. It has been reported that Aspergillus, Cladosporium, and Penicillium were the most prevalent fungal genera in chicken houses (Jo and Kang, 2005). In this study, the content of Aspergillus was 13.5% at the genus level, which was significantly greater in layer houses than in broiler houses. Other studies have reported that, among a dozen poultry fungal diseases, the most dangerous pathogen is Aspergillus (Pinello et al., 1977; SO et al., 1978; Sauter et al., 1981a), which also can infect humans. Similarly, the relative abundance of Penicillium was greater in layer houses than in broiler houses. In previous researches, Escherichia, Aspergillus, and Penicillium were detected in poultry house (Jo and Kang, 2005; Lawniczekwalczyk et al., 2013; Roque et al., 2016). In addition, previous study has shown that 9 genera of molds were identified with over one-half of all isolates being either Aspergillus or Penicillium by plate counts (Sauter et al., 1981b). Furthermore, Aspergillus and Penicillium have been strongly associated with allergic respiratory diseases, such as allergenic rhinitis and asthma (Halonen et al., 1997; Ostro et al., 2001; Flannigan et al., 2011). Studies show that professional activities in poultry house are associated with constant exposure to bioaerosol, which may pose a health hazard to workers and animals (Jo and Kang, 2005; Nimmermark et al., 2009; Hong et al., 2012; Zhao et al., 2016). The present study confirms the importance of microbiological monitoring and control in fine particulate matter of animal husbandry to ensure animal and worker welfare. All bacteria and fungi are detected in the fine particulate matter samples via high-throughput sequencing, which can be qualitatively analyzed at the phylum, class, order, family, genus, and species levels. However, quantitatively characterized data of bacteria and fungi are obtained using a method involving the Andersen sampler only. Therefore, the Andersen sampler still is necessary for the detection of airborne microbes. Altogether, in the fine particulate matter samples, bacteria were more diverse in broiler houses, whereas fungi were more diverse in layer houses. The composition of microbial communities also differed between layer and broiler houses. As mentioned, the chief source of microorganisms in the air was feces, and the composition of microbial communities in the intestinal tracts of animals related closely to the species, given different nutritional requirements, feed composition, and feed modes for different species. Therefore, the composition of the microbial community differs in layer and broiler houses, and the communities have certain specie-related characteristics. SUPPLEMENTARY DATA Supplementary data are available at Poultry Science online. 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Poultry ScienceOxford University Press

Published: Mar 1, 2018

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