title: StressChip as a high-throughput tool for assessing microbial community responses to environmental stresses.
abstract: Microbial community responses to environmental stresses are critical for microbial growth, survival, and adaptation. To fill major gaps in our ability to discern the influence of environmental changes on microbial communities from engineered and natural environments, a functional gene-based microarray, termed StressChip, has been developed. First, 46 functional genes involved in microbial responses to environmental stresses such as changes to temperature, osmolarity, oxidative status, nutrient limitation, or general stress response were selected and curated. A total of 22,855 probes were designed, covering 79,628 coding sequences from 985 bacterial, 76 archaeal, and 59 eukaryotic species/strains. Probe specificity was computationally verified. Second, the usefulness of functional genes as indicators of stress response was examined by surveying their distribution in metagenome data sets. The abundance of individual stress response genes is consistent with expected distributions based on respective habitats. Third, the StressChip was used to analyze marine microbial communities from the Deepwater Horizon oil spill. That functional stress response genes were detected in higher abundance (p < 0.05) in oil plume compared to nonplume samples indicated shifts in community composition and structure, consistent with previous results. In summary, StressChip provides a new tool for accessing microbial community functional structure and responses to environmental changes.
authors.affiliation: Institute for Environmental Genomics, Department of Microbiology and Plant Biology, University of Oklahoma , Norman, Oklahoma 73019, United States.
authors.forename: Aifen
authors.initials: A
authors.lastname: Zhou
authors.forename: Zhili
authors.initials: Z
authors.lastname: He
authors.forename: Yujia
authors.initials: Y
authors.lastname: Qin
authors.forename: Zhenmei
authors.initials: Z
authors.lastname: Lu
authors.forename: Ye
authors.initials: Y
authors.lastname: Deng
authors.forename: Qichao
authors.initials: Q
authors.lastname: Tu
authors.forename: Christopher L
authors.initials: CL
authors.lastname: Hemme
authors.forename: Joy D
authors.initials: JD
authors.lastname: Van Nostrand
authors.forename: Liyou
authors.initials: L
authors.lastname: Wu
authors.forename: Terry C
authors.initials: TC
authors.lastname: Hazen
authors.forename: Adam P
authors.initials: AP
authors.lastname: Arkin
authors.forename: Jizhong
authors.initials: J
authors.lastname: Zhou
mesh_terms: D001105:Archaea / Q000235:genetics* / Q000378:metabolism; D001419:Bacteria / Q000235:genetics* / Q000378:metabolism; D019295:Computational Biology / Q000379:methods; D004784:Environmental Monitoring / Q000379:methods*; D056890:Eukaryota / Q000235:genetics* / Q000378:metabolism; D019766:Genes, Archaeal / Q000187:drug effects; D005798:Genes, Bacterial / Q000187:drug effects; D060851:Gulf of America; D054892:Metagenome / Q000187:drug effects; D046228:Microarray Analysis / Q000379:methods*; D064307:Microbiota / Q000187:drug effects; D015341:Nucleic Acid Probes / Q000378:metabolism; D012623:Seawater / Q000382:microbiology; D013312:Stress, Physiological
chemical_list: D015341:Nucleic Acid Probes