The development of molecular tools that permit diagnosis of the physiological status of key members of subsurface microbial communities is expected to reduce the degree of “trial-and-error” in designing strategies to manipulate microbial activity to enhance bioremediation (
27). The uranium bioremediation field study site in Rifle, CO, has provided a good opportunity to develop such techniques because the subsurface community during effective uranium bioremediation is not diverse (
2,
23,
32). In multiple field experiments at this site, microbial reduction of soluble U(VI) to poorly soluble U(IV) has been accelerated with the addition of acetate (
2,
32). This consistently stimulates the growth of
Geobacter species, which are considered to be responsible for the U(VI) reduction and can account for more than 90% of the microbial community during the height of uranium bioremediation. High abundances of
Geobacter species are often noted in other subsurface environments when dissimilatory metal reduction is an important process (
1,
8,
17,
36,
39). The development of molecular strategies for diagnosing the metabolic status of subsurface
Geobacter species has been facilitated by the availability of multiple
Geobacter species whose genomes are available, and in some cases genome-scale metabolic models (
9,
29).
Initial attempts to diagnose the physiological status of
Geobacter species in the subsurface focused on quantifying the abundance of transcripts for key genes whose expression changes in response to important shifts in metabolic state. For example, studies with
Geobacter sulfurreducens demonstrated that transcript abundance for
gltA, which encodes the tricarboxylic acid (TCA) cycle enzyme citrate synthase, was proportional to rates of metabolism and analysis of the transcript abundance for the
gltA of the subsurface
Geobacter community during uranium bioremediation revealed major shifts in metabolism of the subsurface
Geobacter community in response to acetate availability (
21). Analysis of transcript abundance within the subsurface community for genes with increased expression in response to the need to fix nitrogen (
20,
32), a limitation in iron available for assimilation (
37), phosphate (
34) or ammonium (
32) limitation, oxidative (
31) or heavy metal (
22) stress, and electron donor or acceptor utilization (
13,
18) has provided important insights into
Geobacter physiology during bioremediation.
However, quantifying
in situ gene transcript abundance is technically difficult and with present technologies may be better suited as a research tool rather than for routine diagnosis of metabolic status. Furthermore, there may be instances in which changes in transcript abundance are not reflected in similar modifications in protein abundance as the result of posttranscriptional regulation. Global analysis of proteins may be an alternative, and application of this approach to the study of uranium bioremediation at the Rifle site has been useful in revealing important changes in
Geobacter strains during the bioremediation process (
11,
44,
45). One limitation of this approach is the requirement for large (500 liters) groundwater samples, making it difficult to sample discreet zones in the subsurface and potentially disrupting subsurface geochemical gradients. Another consideration is that only a few specially equipped laboratories are capable of such sophisticated analyses. Furthermore, determining actual protein concentrations by using this approach is problematic.
An alternative approach is to quantify the abundance of key proteins expected to be diagnostic of physiological status. We report that here it is possible to track the abundance of important Geobacter metabolic proteins in groundwater during bioremediation of groundwater contaminated with uranium or aromatic hydrocarbons. It is expected that this method should be applicable to other microbial communities involved in bioremediation.