Enrichment of human nasopharyngeal bacteriome with bacteria from dust after short-term exposure to indoor environment: a pilot study
Language English Country Great Britain, England Media electronic
Document type Journal Article, Research Support, Non-U.S. Gov't
PubMed
37525095
PubMed Central
PMC10391871
DOI
10.1186/s12866-023-02951-5
PII: 10.1186/s12866-023-02951-5
Knihovny.cz E-resources
- Keywords
- 16S rRNA, Bacteriome, Dust, Exposure, Hospital, Household, Indoor environment, Nasopharynx, Sequencing,
- MeSH
- Bacteria genetics MeSH
- Child MeSH
- Humans MeSH
- Nasopharynx MeSH
- Pilot Projects MeSH
- Dust * analysis MeSH
- RNA, Ribosomal, 16S genetics analysis MeSH
- Pregnancy MeSH
- Air Pollution, Indoor * analysis MeSH
- Check Tag
- Child MeSH
- Humans MeSH
- Pregnancy MeSH
- Female MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
- Names of Substances
- Dust * MeSH
- RNA, Ribosomal, 16S MeSH
BACKGROUND: Indoor dust particles are an everyday source of human exposure to microorganisms and their inhalation may directly affect the microbiota of the respiratory tract. We aimed to characterize the changes in human nasopharyngeal bacteriome after short-term exposure to indoor (workplace) environments. METHODS: In this pilot study, nasopharyngeal swabs were taken from 22 participants in the morning and after 8 h of their presence at the workplace. At the same time points, indoor dust samples were collected from the participants' households (16 from flats and 6 from houses) and workplaces (8 from a maternity hospital - NEO, 6 from a pediatric hospital - ENT, and 8 from a research center - RCX). 16S rRNA sequencing analysis was performed on these human and environmental matrices. RESULTS: Staphylococcus and Corynebacterium were the most abundant genera in both indoor dust and nasopharyngeal samples. The analysis indicated lower bacterial diversity in indoor dust samples from flats compared to houses, NEO, ENT, and RCX (p < 0.05). Participants working in the NEO had the highest nasopharyngeal bacterial diversity of all groups (p < 0.05). After 8 h of exposure to the workplace environment, enrichment of the nasopharynx with several new bacterial genera present in the indoor dust was observed in 76% of study participants; however, no significant changes were observed at the level of the nasopharyngeal bacterial diversity (p > 0.05, Shannon index). These "enriching" bacterial genera overlapped between the hospital workplaces - NEO and ENT but differed from those in the research center - RCX. CONCLUSIONS: The results suggest that although the composition of nasopharyngeal bacteriome is relatively stable during the day. Short-term exposure to the indoor environment can result in the enrichment of the nasopharynx with bacterial DNA from indoor dust; the bacterial composition, however, varies by the indoor workplace environment.
Global Change Research Institute of the Czech Academy of Sciences Bělidla 986 4a Brno Czech Republic
RECETOX Faculty of Science Masaryk University Kotlarska 2 Brno Czech Republic
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Leung MHY, Lee PKH. The roles of the outdoors and occupants in contributing to a potential pan-microbiome of the built environment: a review. Microbiome. 2016;4:21. 10.1186/s40168-016-0165-2 PubMed DOI PMC
Prussin AJ, Marr LC. Sources of airborne microorganisms in the built environment. Microbiome. 2015;3:78. 10.1186/s40168-015-0144-z PubMed DOI PMC
Adams RI, Miletto M, Lindow SE, Taylor JW, Bruns TD. Airborne bacterial communities in residences: similarities and differences with fungi. PLoS One. 2014;9(3):e91283. 10.1371/journal.pone.0091283 PubMed DOI PMC
Bowers RM, McLetchie S, Knight R, Fierer N. Spatial variability in airborne bacterial communities across land-use types and their relationship to the bacterial communities of potential source environments. ISME J. 2011;5:601–12. 10.1038/ismej.2010.167 PubMed DOI PMC
Rocchi S, Reboux G, Scherer E, Laboissiere A, Zaros C, Rouzet A, et al. Indoor microbiome: quantification of exposure and association with geographical location, meteorological factors, and land use in france. Microorganisms. 2020;8:341. 10.3390/microorganisms8030341 PubMed DOI PMC
Weikl F, Tischer C, Probst AJ, Heinrich J, Markevych I, Jochner S, et al. Fungal and bacterial communities in indoor dust follow different environmental determinants. PLoS One. 2016;11:e0154131. 10.1371/journal.pone.0154131 PubMed DOI PMC
Barberán A, Dunn RR, Reich BJ, Pacifici K, Laber EB, Menninger HL, et al. The ecology of microscopic life in household dust. Proc R Soc B Biol Sci. 1814;2015(282):20151139. PubMed PMC
Meadow JF, Altrichter AE, Kembel SW, Kline J, Mhuireach G, Moriyama M, et al. Indoor airborne bacterial communities are influenced by ventilation, occupancy, and outdoor air source. Indoor Air. 2014;24:41–8. 10.1111/ina.12047 PubMed DOI PMC
Hospodsky D, Qian J, Nazaroff WW, Yamamoto N, Bibby K, Rismani-Yazdi H, et al. Human occupancy as a source of indoor airborne bacteria. PLoS One. 2012;7:e34867. 10.1371/journal.pone.0034867 PubMed DOI PMC
Qian J, Ferro AR. Resuspension of dust particles in a chamber and associated environmental factors. Aerosol Sci Technol. 2008;42:566–78.10.1080/02786820802220274 DOI
Veillette M, Knibbs LD, Pelletier A, Charlebois R, Blais Lecours P, He C, et al. Microbial contents of vacuum cleaner bag dust and emitted bioaerosols and their implications for human exposure Indoors. Appl Environ Microbiol. 2013;79:6331–6. 10.1128/AEM.01583-13 PubMed DOI PMC
Hanson B, Zhou Y, Bautista EJ, Urch B, Speck M, Silverman F, et al. Characterization of the bacterial and fungal microbiome in indoor dust and outdoor air samples: a pilot study. Environ Sci Process Impacts. 2016;18:713–24. 10.1039/C5EM00639B PubMed DOI PMC
Hewitt KM, Gerba CP, Maxwell SL, Kelley ST. Office space bacterial abundance and diversity in three metropolitan areas. PLoS One. 2012;7(5):e37849. 10.1371/journal.pone.0037849 PubMed DOI PMC
Zhou Z-C, Liu Y, Lin Z-J, Shuai X-Y, Zhu L, Xu L, et al. Spread of antibiotic resistance genes and microbiota in airborne particulate matter, dust, and human airways in the urban hospital. Environ Int. 2021;153:106501. 10.1016/j.envint.2021.106501 PubMed DOI
Kampf G. Antibiotic resistance can be enhanced in gram-positive species by some biocidal agents used for disinfection. Antibiotics. 2019;8:13. 10.3390/antibiotics8010013 PubMed DOI PMC
Dunn RR, Fierer N, Henley JB, Leff JW, Menninger HL. Home life: factors structuring the bacterial diversity found within and between homes. PLoS One. 2013;8(5):e64133. 10.1371/journal.pone.0064133 PubMed DOI PMC
Dannemiller KC, Gent JF, Leaderer BP, Peccia J. Influence of housing characteristics on bacterial and fungal communities in homes of asthmatic children. Indoor Air. 2016;26:179–92. 10.1111/ina.12205 PubMed DOI PMC
Ciaccio CE, Barnes C, Kennedy K, Chan M, Portnoy J, Rosenwasser L. Home dust microbiota is disordered in homes of low-income asthmatic children. J Asthma. 2015;52:873–80. 10.3109/02770903.2015.1028076 PubMed DOI PMC
Ding L-J, Zhou X-Y, Zhu Y-G. Microbiome and antibiotic resistome in household dust from Beijing China. Environ Int. 2020;139:105702. 10.1016/j.envint.2020.105702 PubMed DOI
Shan Y, Wu W, Fan W, Haahtela T, Zhang G. House dust microbiome and human health risks. Int Microbiol Off J Span Soc Microbiol. 2019;22:297–304. PubMed
Thompson JR, Argyraki A, Bashton M, Bramwell L, Crown M, Hursthouse AS, et al. Bacterial diversity in house dust: characterization of a core indoor microbiome. Front Environ Sci. 2021;9:754657.
Guo J, Xiong Y, Kang T, Xiang Z, Qin C. Bacterial community analysis of floor dust and HEPA filters in air purifiers used in office rooms in ILAS. Beijing Sci Rep. 2020;10:6417. 10.1038/s41598-020-63543-1 PubMed DOI PMC
Chase J, Fouquier J, Zare M, Sonderegger DL, Knight R, Kelley ST, et al. Geography and location are the primary drivers of office microbiome composition. mSystems. 2016;1:e00022-16. 10.1128/mSystems.00022-16 PubMed DOI PMC
Fu X, Norbäck D, Yuan Q, Li Y, Zhu X, Hashim JH, et al. Indoor microbiome, environmental characteristics and asthma among junior high school students in Johor Bahru Malaysia. Environ Int. 2020;138:105664. 10.1016/j.envint.2020.105664 PubMed DOI
Nygaard AB, Charnock C. Longitudinal development of the dust microbiome in a newly opened Norwegian kindergarten. Microbiome. 2018;6(1):159. 10.1186/s40168-018-0553-x PubMed DOI PMC
Beasley DE, Monsur M, Hu J, Dunn RR, Madden AA. The bacterial community of childcare centers: potential implications for microbial dispersal and child exposure. Environ Microbiome. 2022;17:8. 10.1186/s40793-022-00404-6 PubMed DOI PMC
O’Hara NB, Reed HJ, Afshinnekoo E, Harvin D, Caplan N, Rosen G, et al. Metagenomic characterization of ambulances across the USA. Microbiome. 2017;5:125. 10.1186/s40168-017-0339-6 PubMed DOI PMC
Brooks B, Olm MR, Firek BA, Baker R, Geller-McGrath D, Reimer SR, et al. The developing premature infant gut microbiome is a major factor shaping the microbiome of neonatal intensive care unit rooms. Microbiome. 2018;6(1):112. 10.1186/s40168-018-0493-5 PubMed DOI PMC
Poza M, Gayoso C, Gómez MJ, Rumbo-Feal S, Tomás M, Aranda J, et al. Exploring bacterial diversity in hospital environments by GS-FLX Titanium pyrosequencing. PLoS One. 2012;7:e44105. 10.1371/journal.pone.0044105 PubMed DOI PMC
Fernstrom A, Goldblatt M. Aerobiology and its role in the transmission of infectious diseases. J Pathog. 2013;2013:493960. PubMed PMC
Lee MK, Carnes MU, Butz N, Azcarate-Peril MA, Richards M, Umbach DM, et al. Exposures related to house dust microbiota in a U.S. farming population. Environ Health Perspect. 2018;126(6):067001. 10.1289/EHP3145 PubMed DOI PMC
Kirjavainen PV, Karvonen AM, Adams RI, Täubel M, Roponen M, Tuoresmäki P, et al. Farm-like indoor microbiota in non-farm homes protects children from asthma development. Nat Med. 2019;25:1089–95. 10.1038/s41591-019-0469-4 PubMed DOI PMC
Sun Y, Fu X, Li Y, Yuan Q, Ou Z, Lindgren T, et al. Shotgun metagenomics of dust microbiome from flight deck and cabin in civil aviation aircraft. Indoor Air. 2020;30:1199–212. 10.1111/ina.12707 PubMed DOI
Weiss H, Hertzberg VS, Dupont C, Espinoza JL, Levy S, Nelson K, et al. The airplane cabin microbiome. Microb Ecol. 2019;77:87–95. 10.1007/s00248-018-1191-3 PubMed DOI PMC
Korves TM, Piceno YM, Tom LM, Desantis TZ, Jones BW, Andersen GL, et al. Bacterial communities in commercial aircraft high-efficiency particulate air (HEPA) filters assessed by PhyloChip analysis. Indoor Air. 2013;23:50–61. 10.1111/j.1600-0668.2012.00787.x PubMed DOI PMC
Checinska A, Probst AJ, Vaishampayan P, White JR, Kumar D, Stepanov VG, et al. Microbiomes of the dust particles collected from the International Space Station and Spacecraft Assembly Facilities. Microbiome. 2015;3:50. 10.1186/s40168-015-0116-3 PubMed DOI PMC
Park J-H, Lemons AR, Roseman J, Green BJ, Cox-Ganser JM. Bacterial community assemblages in classroom floor dust of 50 public schools in a large city: characterization using 16S rRNA sequences and associations with environmental factors. Microbiome. 2021;9:15. 10.1186/s40168-020-00954-2 PubMed DOI PMC
Barberán A, Ladau J, Leff JW, Pollard KS, Menninger HL, Dunn RR, et al. Continental-scale distributions of dust-associated bacteria and fungi. Proc Natl Acad Sci. 2015;112:5756–61. 10.1073/pnas.1420815112 PubMed DOI PMC
Shin S-K, Kim J, Ha S, Oh H-S, Chun J, Sohn J, et al. Metagenomic insights into the bioaerosols in the indoor and outdoor environments of childcare facilities. PLoS One. 2015;10:e0126960. 10.1371/journal.pone.0126960 PubMed DOI PMC
Gupta S, Hjelmsø MH, Lehtimäki J, Li X, Mortensen MS, Russel J, et al. Environmental shaping of the bacterial and fungal community in infant bed dust and correlations with the airway microbiota. Microbiome. 2020;8:115. 10.1186/s40168-020-00895-w PubMed DOI PMC
Man WH, de Steenhuijsen Piters WAA, Bogaert D. The microbiota of the respiratory tract: gatekeeper to respiratory health. Nat Rev Microbiol. 2017;15:259–70. 10.1038/nrmicro.2017.14 PubMed DOI PMC
Adar SD, Huffnagle GB, Curtis JL. The respiratory microbiome: an underappreciated player in the human response to inhaled pollutants? Ann Epidemiol. 2016;26:355–9. 10.1016/j.annepidem.2016.03.010 PubMed DOI PMC
Hilty M, Burke C, Pedro H, Cardenas P, Bush A, Bossley C, et al. Disordered microbial communities in asthmatic airways. PLoS One. 2010;5:e8578. 10.1371/journal.pone.0008578 PubMed DOI PMC
Zhang Q, Cox M, Liang Z, Brinkmann F, Cardenas PA, Duff R, et al. Airway microbiota in severe asthma and relationship to asthma severity and phenotypes. PLoS One. 2016;11:e0152724. 10.1371/journal.pone.0152724 PubMed DOI PMC
Huang YJ, Nariya S, Harris JM, Lynch SV, Choy DF, Arron JR, et al. The airway microbiome in patients with severe asthma: Associations with disease features and severity. J Allergy Clin Immunol. 2015;136:874–84. 10.1016/j.jaci.2015.05.044 PubMed DOI PMC
Sverrild A, Kiilerich P, Brejnrod A, Pedersen R, Porsbjerg C, Bergqvist A, et al. Eosinophilic airway inflammation in asthmatic patients is associated with an altered airway microbiome. J Allergy Clin Immunol. 2017;140:407-417.e11. 10.1016/j.jaci.2016.10.046 PubMed DOI
Lee SH, Lee Y, Park JS, Cho Y-J, Yoon HI, Lee C-T, et al. Characterization of microbiota in bronchiectasis patients with different disease severities. J Clin Med. 2018;7:E429.10.3390/jcm7110429 PubMed DOI PMC
Huang YJ, LiPuma JJ. The microbiome in cystic fibrosis. Clin Chest Med. 2016;37:59–67. 10.1016/j.ccm.2015.10.003 PubMed DOI PMC
Tunney MM, Einarsson GG, Wei L, Drain M, Klem ER, Cardwell C, et al. Lung microbiota and bacterial abundance in patients with bronchiectasis when clinically stable and during exacerbation. Am J Respir Crit Care Med. 2013;187:1118–26. 10.1164/rccm.201210-1937OC PubMed DOI PMC
Zhong G, Wei W, Liao W, Wang R, Peng Y, Zhou Y, et al. Tumor microbiome in nasopharyngeal carcinoma and its association with prognosis. Front Oncol. 2022;12:859721. 10.3389/fonc.2022.859721 PubMed DOI PMC
Whelan FJ, Verschoor CP, Stearns JC, Rossi L, Luinstra K, Loeb M, et al. The loss of topography in the microbial communities of the upper respiratory tract in the elderly. Ann Am Thorac Soc. 2014;11:513–21. 10.1513/AnnalsATS.201310-351OC PubMed DOI
Morris A, Beck JM, Schloss PD, Campbell TB, Crothers K, Curtis JL, et al. Comparison of the respiratory microbiome in healthy nonsmokers and smokers. Am J Respir Crit Care Med. 2013;187:1067–75. 10.1164/rccm.201210-1913OC PubMed DOI PMC
Tamashiro E, Xiong G, Anselmo-Lima WT, Kreindler JL, Palmer JN, Cohen NA. Cigarette smoke exposure impairs respiratory epithelial ciliogenesis. Am J Rhinol Allergy. 2009;23:117–22. 10.2500/ajra.2009.23.3280 PubMed DOI
Arcavi L, Benowitz NL. Cigarette smoking and infection. Arch Intern Med. 2004;164:2206–16. 10.1001/archinte.164.20.2206 PubMed DOI
Sapkota AR, Berger S, Vogel TM. Human pathogens abundant in the bacterial metagenome of cigarettes. Environ Health Perspect. 2010;118:351–6. 10.1289/ehp.0901201 PubMed DOI PMC
Soumana IH, Carlsten C. Air pollution and the respiratory microbiome. J Allergy Clin Immunol. 2021;148:67–9. 10.1016/j.jaci.2021.05.013 PubMed DOI
Xue Y, Chu J, Li Y, Kong X. The influence of air pollution on respiratory microbiome: a link to respiratory disease. Toxicol Lett. 2020;334:14–20. 10.1016/j.toxlet.2020.09.007 PubMed DOI
Mariani J, Favero C, Buono LD, Motta V, Pergoli L, Cattaneo A, et al. Particulate matter exposure influences respiratory microbiota structure and functions. Eur Respir J. 2017;50(suppl):61.
Giugliano R, Sellitto A, Ferravante C, Rocco T, D’Agostino Y, Alexandrova E, et al. NGS analysis of nasopharyngeal microbiota in SARS-CoV-2 positive patients during the first year of the pandemic in the Campania Region of Italy. Microb Pathog. 2022;165:105506. 10.1016/j.micpath.2022.105506 PubMed DOI PMC
De Boeck I, Wittouck S, Wuyts S, Oerlemans EFM, van den Broek MFL, Vandenheuvel D, et al. Comparing the healthy nose and nasopharynx microbiota reveals continuity as well as niche-specificity. Front Microbiol. 2017;8:2372. 10.3389/fmicb.2017.02372 PubMed DOI PMC
Piler P, Kandrnal V, Kukla L, Andrýsková L, Švancara J, Jarkovský J, et al. Cohort profile: the European Longitudinal Study of Pregnancy and Childhood (ELSPAC) in the Czech Republic. Int J Epidemiol. 2017;46:1379–1379f. PubMed PMC
Sitarik A, Havstad S, Levin A, Lynch SV, Fujimura K, Ownby D, et al. Dog introduction alters the home dust microbiota. Indoor Air. 2018;28:539–47. 10.1111/ina.12456 PubMed DOI PMC
Mäki JM, Kirjavainen PV, Täubel M, Piippo-Savolainen E, Backman K, Hyvärinen A, et al. Associations between dog keeping and indoor dust microbiota. Sci Rep. 2021;11:5341. 10.1038/s41598-021-84790-w PubMed DOI PMC
Adams RI, Bhangar S, Pasut W, Arens EA, Taylor JW, Lindow SE, et al. Chamber bioaerosol study: outdoor air and human occupants as sources of indoor airborne microbes. PLoS One. 2015;10:e0128022. 10.1371/journal.pone.0128022 PubMed DOI PMC
Kumpitsch C, Koskinen K, Schöpf V, Moissl-Eichinger C. The microbiome of the upper respiratory tract in health and disease. BMC Biol. 2019;17:87. 10.1186/s12915-019-0703-z PubMed DOI PMC
Proctor DM, Relman DA. The landscape ecology and microbiota of the human nose, mouth, and throat. Cell Host Microbe. 2017;21:421–32. 10.1016/j.chom.2017.03.011 PubMed DOI PMC
Biesbroek G, Tsivtsivadze E, Sanders EAM, Montijn R, Veenhoven RH, Keijser BJF, et al. Early respiratory microbiota composition determines bacterial succession patterns and respiratory health in children. Am J Respir Crit Care Med. 2014;190:1283–92. 10.1164/rccm.201407-1240OC PubMed DOI
Santee CA, Nagalingam NA, Faruqi AA, DeMuri GP, Gern JE, Wald ER, et al. Nasopharyngeal microbiota composition of children is related to the frequency of upper respiratory infection and acute sinusitis. Microbiome. 2016;4:34. 10.1186/s40168-016-0179-9 PubMed DOI PMC
Nygaard AB, Tunsjø HS, Meisal R, Charnock C. A preliminary study on the potential of Nanopore MinION and Illumina MiSeq 16S rRNA gene sequencing to characterize building-dust microbiomes. Sci Rep. 2020;10:3209. 10.1038/s41598-020-59771-0 PubMed DOI PMC
Henares D, Rocafort M, Brotons P, de Sevilla MF, Mira A, Launes C, et al. Rapid increase of oral bacteria in nasopharyngeal microbiota after antibiotic treatment in children with invasive pneumococcal disease. Front Cell Infect Microbiol. 2021;11:744727. 10.3389/fcimb.2021.744727 PubMed DOI PMC
Hou J, Song Y, Leung ASY, Tang MF, Shi M, Wang EY, et al. Temporal dynamics of the nasopharyngeal microbiome and its relationship with childhood asthma exacerbation. Microbiol Spectr. 2022;10:e00129-e222. 10.1128/spectrum.00129-22 PubMed DOI PMC
Čupr P, Hilscherová K, Vrana B, Melymuk L, Bányiová K, Sharma A, et al. Metodika vzorkování vnitřního prostředí pro analýzy vybraných emergentních polutantů - Certifikovaná metodika (Nmet). 2016.
Callahan BJ, McMurdie PJ, Rosen MJ, Han AW, Johnson AJA, Holmes SP. DADA2: High-resolution sample inference from Illumina amplicon data. Nat Methods. 2016;13:581–3. 10.1038/nmeth.3869 PubMed DOI PMC
Aronesty E. Comparison of sequencing utility programs. Open Bioinforma J. 2013;7:1–8.
Caporaso JG, Kuczynski J, Stombaugh J, Bittinger K, Bushman FD, Costello EK, et al. QIIME allows analysis of high-throughput community sequencing data. Nat Methods. 2010;7:335–6. 10.1038/nmeth.f.303 PubMed DOI PMC
Quast C, Pruesse E, Yilmaz P, Gerken J, Schweer T, Yarza P, et al. The SILVA ribosomal RNA gene database project: improved data processing and web-based tools. Nucleic Acids Res. 2013;41 Database issue:D590-596. PubMed PMC
Aitchison J. The statistical analysis of compositional data. London; New York: Chapman and Hall; 1986.
Martín-Fernández J-A, Hron K, Templ M, Filzmoser P, Palarea-Albaladejo J. Bayesian-multiplicative treatment of count zeros in compositional data sets. Stat Model. 2015;15:134–58.10.1177/1471082X14535524 DOI
R Core Team. R: a language and environment for statistical computing. Foundation for Statistical Computing, Vienna, Austria. 2021. https://www.R-project.org/.
Gentleman R, Carey VJ, Huber W, Hahne F. genefilter: genefilter: methods for filtering genes from high-throughput experiments. 2021.
PERFect: Permutation filtration for microbiome data version 1.4.0 from Bioconductor. https://rdrr.io/bioc/PERFect/. Accessed 11 May 2023.
Palarea-Albaladejo J, Martín-Fernández JA. zCompositions — R package for multivariate imputation of left-censored data under a compositional approach. Chemom Intell Lab Syst. 2015;143:85–96.10.1016/j.chemolab.2015.02.019 DOI
van den Boogaart KG, Tolosana-Delgado R, Bren M. Compositions: compositional data analysis. 2021.
Oksanen J, Blanchet FG, Friendly M, Kindt R, Legendre P, McGlinn D, et al. vegan: community ecology package. 2020.
Warnes GR, Bolker B, Bonebakker L, Gentleman R, Huber W, Liaw A, et al. gplots: various R programming tools for plotting data. 2020.
Conway J, Gehlenborg N. UpSetR: a more scalable alternative to Venn and Euler diagrams for visualizing intersecting sets. 2019.
Murray M, Blume J. FDRestimation: estimate, plot, and summarize false discovery rates. 2020.
Kassambara A. ggpubr: “ggplot2” based publication ready plots. 2020.
Gu Z, Eils R, Schlesner M. Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinforma Oxf Engl. 2016;32:2847–9.10.1093/bioinformatics/btw313 PubMed DOI
Ritchie ME, Phipson B, Wu D, Hu Y, Law CW, Shi W, et al. limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Res. 2015;43:e47. 10.1093/nar/gkv007 PubMed DOI PMC
Resistome in the indoor dust samples from workplaces and households: a pilot study