Differential Response of Human Nasal and Bronchial Epithelial Cells Upon Exposure to Size-Fractionated Dairy Dust

<div><p>Exposure to organic dusts is associated with increased respiratory morbidity and mortality in agricultural workers. Organic dusts in dairy farm environments are complex, polydisperse mixtures of toxic and immunogenic compounds. Previous toxicological studies focused primarily on exposures to the respirable size fraction; however, organic dusts in dairy farm environments are known to contain larger particles. Given the size distribution of dusts from dairy farm environments, the nasal and bronchial epithelia represent targets of agricultural dust exposures. In this study, well-differentiated normal human bronchial epithelial cells and human nasal epithelial cells were exposed to two different size fractions (PM₁₀ and PM_>10) of dairy parlor dust using a novel aerosol-to-cell exposure system. Levels of proinflammatory transcripts (interleukin [IL]-8, IL-6, and tumor necrosis factor [TNF]-α) were measured 2 h after exposure. Lactate dehydrogenase (LDH) release was also measured as an indicator of cytotoxicity. Cell exposure to dust was measured in each size fraction as a function of mass, endotoxin, and muramic acid levels. To our knowledge, this is the first study to evaluate the effects of distinct size fractions of agricultural dust on human airway epithelial cells. Our results suggest that both PM₁₀ and PM_>10 size fractions elicit a proinflammatory response in airway epithelial cells and that the entire inhalable size fraction needs to be considered when assessing potential risks from exposure to agricultural dusts. Further, data suggest that human bronchial cells respond differently to these dusts than human nasal cells, and therefore that the two cell types need to be considered separately in airway cell models of agricultural dust toxicity.</p></div

Shotgun Pyrosequencing Metagenomic Analyses of Dusts from Swine Confinement and Grain Facilities

<div><p>Inhalation of agricultural dusts causes inflammatory reactions and symptoms such as headache, fever, and malaise, which can progress to chronic airway inflammation and associated diseases, e.g. asthma, chronic bronchitis, chronic obstructive pulmonary disease, and hypersensitivity pneumonitis. Although in many agricultural environments feed particles are the major constituent of these dusts, the inflammatory responses that they provoke are likely attributable to particle-associated bacteria, archaebacteria, fungi, and viruses. In this study, we performed shotgun pyrosequencing metagenomic analyses of DNA from dusts from swine confinement facilities or grain elevators, with comparisons to dusts from pet-free households. DNA sequence alignment showed that 19% or 62% of shotgun pyrosequencing metagenomic DNA sequence reads from swine facility or household dusts, respectively, were of swine or human origin, respectively. In contrast only 2% of such reads from grain elevator dust were of mammalian origin. These metagenomic shotgun reads of mammalian origin were excluded from our analyses of agricultural dust microbiota. The ten most prevalent bacterial taxa identified in swine facility compared to grain elevator or household dust were comprised of 75%, 16%, and 42% gram-positive organisms, respectively. Four of the top five swine facility dust genera were assignable (<i>Clostridium, Lactobacillus, Ruminococcus,</i> and <i>Eubacterium</i>, ranging from 4% to 19% relative abundance). The relative abundances of these four genera were lower in dust from grain elevators or pet-free households. These analyses also highlighted the predominance in swine facility dust of <i>Firmicutes</i> (70%) at the phylum level, <i>Clostridia</i> (44%) at the Class level, and <i>Clostridiales</i> at the Order level (41%). In summary, shotgun pyrosequencing metagenomic analyses of agricultural dusts show that they differ qualitatively and quantitatively at the level of microbial taxa present, and that the bioinformatic analyses used for such studies must be carefully designed to avoid the potential contribution of non-microbial DNA, e.g. from resident mammals.</p></div

Taxonomic classification of metagenomic reads from swine confinement facility dust, grain elevator dust and household dust without pets.

<p><b><i>A.</i></b> Domain level; <b><i>B.</i></b> Phylum level. Each pie chart represents relative abundance values expressed as the total number domains (“pre-filtered” dataset) or phyla (“filtered” dataset) from swine confinement facility dust, grain elevator dust and household dust without pets. Other sequences equals reads that align significantly to the M5NR database that are derived from taxa not listed as descendants from one of the domains; Unassigned equal reads that do not align significantly to any M5NR database sequence.</p

Genus abundance ranking of swine confinement facility dust reads in comparison to grain elevator dust and household dust without pets.

<p><i>Relative</i> abundance values are expressed on the ordinate as a fraction of the total number of genera identified in swine dust. The 15 most abundant genera identified using the swine facility dust shotgun metagenomic reads and the M5NR database are shown. Relative abundance values were calculated for these same 15 genera for dust collected from grain elevators and households without pets. See <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0095578#pone.0095578.s004" target="_blank">Figure S4</a> for comparisons at the Phylum, Class, Order, and Family taxonomic levels. Black = Swine dust; Gray = House dust; White = Grain dust.</p

Candidate biomarker analyses based on Genus abundance profiles from dust-derived shotgun metagenomic read datasets.

<p>STAMP Extended Error Graph of the top ranked genera identified in a two-group statistical test comparing MG-RAST Genus abundance profiles generated using the M5NR database for swine facility dust dataset (red) and both household and grain elevator dust datasets (black). Ranking of the genera is based on significance (q) values, which were corrected for multiple testing and show the indicated value for Storey’s false discovery rate. The unclassified genus shown is annotated by MG-RAST as derived from <i>Erysipelotrichaceae</i>.</p

BLASTn screening scheme used for alignment of shotgun metagenomic reads to swine and human genomes.

<p>Post-QC shotgun metagenomic reads from swine facility dust, swine feces, grain elevator dust and household dust without pets were aligned against the swine draft (ssc_ref_Sscrofa10) and human genome (hs_ref_GRCh37.p5) sequence. Reads that aligned against the swine draft and/or the human reference genome sequence with an expect value of less than 10⁻⁵ were subsequently aligned against all finished and draft bacterial genome sequence assemblies currently available at the NCBI FTP site on 11/16/2011. Except were indicated, filtered reads were used in all subsequent bioinformatics analyses. * From the NCBI Sequence Read Archive; E_S/H =  expect values for reads aligned to swine and/or human genomes; E_F =  expect values for reads with poor alignment with swine or human genomes (filtered reads).</p

Principal Component Analysis (PCA) of shotgun metagenomic reads from swine facility dust, grain elevator dust, household dust without pets and swine feces: Relative abundance of Genera.

<p>PCA was performed in STAMP using MG-RAST Genus-level organism abundance profiles that were derived from two swine facility dust samples, two grain elevator dust samples, two household dust samples without pets and three swine feces samples. <i>A.</i> The “filtered” reads from the swine confinement facility dust and the household dust datasets were used in the analyses. <i>B.</i> The “filtered” and “swine/human” reads from the swine confinement facility dust and the household dust datasets, respectively, were used in the analyses. Each symbol represents a sample. • Grain elevator dust (green); ▪ Household dust without pets (“filtered”, yellow); ▴ Swine confinement facility dust (“filtered”, red); ♦ Swine feces (blue).</p

Repetitive inhalant organic dust extract (ODE)-induced airway inflammatory responses were reduced in TLR2 and TLR4 KO mice.

<p>WT, TLR2 KO, and TLR4 KO mice were <i>i</i>.<i>n</i>. treated with ODE daily or saline for 3 weeks whereupon animals were euthanized 5 hrs following final exposure. Neutrophil recruitment (<b>A</b>), IL-6 (<b>B</b>), TNF-α (<b>C</b>), IL-1β (<b>D</b>), CXCL1 (<b>E</b>), and CXCL2 (<b>F</b>) were determined in bronchoalveolar lavage fluid. Bar graphs represent the mean with standard error bars shown (N = minimum of 6 mice/group from 3 independent studies). Statistical significance denoted by asterisks (*p<0.01, **p<0.01, ***p<0.001) as compared to respective saline treatment group. Line denotes statistical significance (#p<0.05, ##p<0.01, ###p<0.001) of WT vs. TLR2 and TLR4 KO mice.</p

Organic dust extract (ODE) promotes osteoclastogenesis <i>in vitro</i> with WT and TLR2 KO, but not TLR4 KO, bone marrow macrophages.

<p>Bone marrow derived cells from C57BL/6 WT mice (<b>A, top panel</b>), TLR2 KO mice (<b>B, middle panel</b>), and TLR4 KO (<b>C, bottom panel</b>) were cultured with M-CSF and RANKL and ± ODE (0.5%). In side-by-side experiments, cells were also cultured with a TLR4 agonist (lipopolysaccharide; LPS; 10 ng) or TLR2 agonist (peptidoglycan; PGN; 1 μg) as additional controls. Membrane receptor activator of NF-κB ligand (mRANKL) expression was determined by flow cytometry analysis. A representative contour plot from each experimental group is shown with a rightward shift demonstrating gating of positive mRANKL expression after exclusion of debris. Bar graphs show the mean with standard error bars of percentage of mRANKL expression (P2 gate). N = 6/group from three separate studies ran in duplicate. Statistical significance denoted by asterisks (***p<0.001) vs. unstimulated control.</p

Increased osteoclast precursor populations (OCP) in murine bone marrow following inhalant ODE treatment is dependent upon TLR4, but not TLR2, signaling pathway.

<p>TLR2 KO (<b>A, top panel</b>) and TLR4 KO (<b>B, bottom panel</b>) mice were <i>i</i>.<i>n</i>. treated with saline or ODE daily for three weeks whereupon mice were euthanized and bone marrow cells were collected and analyzed by flow cytometry. After exclusion of debris and dead cells, triple negative (TN) cells were gated based upon CD45R^-CD3^-CD11b^lo phenotype. Distribution of TN cells are shown as mean percentage with SEM bars of live cells. Distribution of TN cells expressing CD115, CD115CD117, and CD115CD117CD27 are shown as mean percentage with SEM bars of TN cells. N = 4 mice/group. Statistical significance denoted by asterisks (**p<0.01) vs. saline.</p