The hyperthermophilic bacterium Thermotoga maritima MSB8 was grown on a variety of carbohydrates to determine the influence of carbon and energy source on differential gene expression. Despite the fact that T. maritima has been phylogenetically characterized as a primitive microorganism from an evolutionary perspective, results here suggest that it has versatile and discriminating mechanisms for regulating and effecting complex carbohydrate utilization. Growth of T. maritima on monosaccharides was found to be slower than growth on polysaccharides, although growth to cell densities of 10 8 to 10 9 cells/ml was observed on all carbohydrates tested. Differential expression of genes encoding carbohydrate-active proteins encoded in the T. maritima genome was followed using a targeted cDNA microarray in conjunction with mixed model statistical analysis. Coordinated regulation of genes responding to specific carbohydrates was noted. Although glucose generally repressed expression of all glycoside hydrolase genes, other sugars induced or repressed these genes to varying extents. Expression profiles of most endo-acting glycoside hydrolase genes correlated well with their reported biochemical properties, although exo-acting glycoside hydrolase genes displayed less specific expression patterns. Genes encoding selected putative ABC sugar transporters were found to respond to specific carbohydrates, and in some cases putative oligopeptide transporter genes were also found to respond to specific sugar substrates. Several genes encoding putative transcriptional regulators were expressed during growth on specific sugars, thus suggesting functional assignments. The transcriptional response of T. maritima to specific carbohydrate growth substrates indicated that sugar backbone-and linkage-specific regulatory networks are operational in this organism during the uptake and utilization of carbohydrate substrates. Furthermore, the wide ranging collection of such networks in T. maritima suggests that this organism is capable of adapting to a variety of growth environments containing carbohydrate growth substrates.

Maltose-limited, continuous growth of the hyperthermophile Thermotoga maritima at different temperatures and dilution rates (80°C/0.25 h ؊1 , 80°C/0.17 h ؊1 , and 85°C/0.25 h ؊1 ) showed that transcriptome-wide variation in gene expression within mechanical steady states was minimal compared to that between steady states, supporting the efficacy of chemostat-based approaches for functional genomics studies.Continuous culture can be an effective tool for determining global transcriptional patterns in functional genomics studies (5). It may also be useful for examining the fluctuation in gene expression that arises within a specific environmental context or growth condition. It is not clear yet whether biovariability in gene expression in unperturbed cells impacts the interpretation of transcriptional response to intended perturbations. Thus, some of the variation between experimental conditions could reflect the variation within an experimental condition. This issue was examined by using a whole-genome cDNA microarray for Thermotoga maritima, an obligately anaerobic, hyperthermophilic, heterotrophic bacterium growing optimally at 80°C (2, 4, 8). Chemostat-based transcriptional response experiments with whole-genome cDNA microarrays were used to investigate sources of variance that contribute to the observed patterns of differential gene expression both within and between mechanical steady states (temperature and dilution rate) by using three common procedures used to assign differential gene expression.Experimental overview. A full-genome Thermotoga maritima DNA microarray constructed from PCR products (3) was used to measure transcriptional variation during continuous cultivation (6). Three mechanical steady states chosen to reflect perturbations within the normal growth range of the organism were examined: 80°C at a dilution rate of 0.25 h Ϫ1 (six samples taken at 103.7, 109.3, 127.7, 133.4, 151.8, and 157.5 h [19.4 generations]), 85°C at a dilution rate of 0.25 h Ϫ1 (four samples taken at 435.4, 459.6, 483.4, and 501.7 h [23.9 generations]), and 80°C at a dilution rate of 0.17 h Ϫ1 (three samples taken at 879.0, 958.5, and 1,000.0 h [29.7 generations]) (Fig. 1). Isolation of total RNA, hybridizations and washes were performed as described previously (9). Slides were scanned with a Scanarray 4000 scanner (Perkin Elmer, Fremont, CA) and the raw intensity data were processed as described previously (1). The hybridization scheme was arranged according to a loop design strategy, which allows statistically efficient comparisons between samples (11).Simple "fold change" criteria and estimate-based probabilities. Differential gene expression calls based on simple fold change criteria were evaluated by pairwise t tests derived from least-squares mean estimates from log 2 -transformed raw signal intensity data and mixed model analyses (1). The log 2 -transformed analysis is referred to as "unnormalized" because systematic global variation remained confounded with growth state effects; important sources of variation wer...

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