Analysis of environmental transcriptomes by DNA microarrays.
In this work we investigated the correlations between global gene expression patterns and environmental parameters in natural ecosystems. We studied the preferential gene expression of the iron oxidizer bacterium Leptospirillum ferrooxidans to adapt its physiology to changes in the physicochemical parameters in its natural medium. Transcriptome analysis by DNA microarrays can proportionate an instant picture about the preferential gene expression between two different environmental samples. However, this type of analysis is very difficult and complex in natural ecosystems, mainly because of the broad biodiversity and multiple environmental parameters that may affect gene expression. The necessity of high-quality RNA preparations as well as complicated data analysis are also technological limitations. The low prokaryotic diversity of the extremely acidic and iron-rich waters of the Tinto River (Spain) ecosystem, where L. ferrooxidans is abundant, allows the opportunity to achieve global gene expression studies and to associate gene function with environmental parameters. We applied a total RNA amplification protocol validated previously for the amplification of the environmental transcriptome (meta-transcriptome). The meta-transcriptome of two sites from the Tinto River mainly differing in the salt and oxygen contents were amplified and analysed by a L. ferrooxidans DNA microarray. The results showed a clear preferential induction of genes involved in certain physicochemical parameters like: high salinity (ectAB, otsAB), low oxygen concentration (cydAB), iron uptake (fecA-exbBD-tonB), oxidative stress (carotenoid synthesis, oxyR, recG), potassium (kdpBAC) or phosphate concentrations (pstSCAB), etc. We conclude that specific gene expression patterns can be useful indicators for the physiological conditions in a defined ecosystem. Also, the upregulation of certain genes and operons reveals information about the environmental conditions (nutrient limitations, stresses, etc.).
Parro
Víctor
V
Laboratories of Molecular Ecology, Centro de Astrobiología (CSIC-INTA), carretera de Ajalvir km 4, 28850, Torrejón de ardoz, Mardrid, Spain. parrogv@inta.es
Moreno-Paz
Mercedes
M
González-Toril
Elena
E
D001419:Bacteria / Q000187:drug effects / Q000235:genetics* / Q000378:metabolism; D001426:Bacterial Proteins / Q000235:genetics* / Q000378:metabolism / Q000502:physiology; D044822:Biodiversity; D002244:Carbon / Q000378:metabolism; D016000:Cluster Analysis; D017753:Ecosystem; D020869:Gene Expression Profiling; D015964:Gene Expression Regulation, Bacterial / Q000187:drug effects; D008670:Metals / Q000737:chemistry / Q000494:pharmacology; D008957:Models, Genetic; D008969:Molecular Sequence Data; D021141:Nucleic Acid Amplification Techniques; D020411:Oligonucleotide Array Sequence Analysis; D018384:Oxidative Stress / Q000502:physiology; D012333:RNA, Messenger / Q000378:metabolism*; D045483:Rivers / Q000737:chemistry / Q000382:microbiology; D012965:Sodium Chloride / Q000737:chemistry / Q000494:pharmacology
D001426:Bacterial Proteins; D008670:Metals; D012333:RNA, Messenger; D012965:Sodium Chloride; D002244:Carbon