UC Berkeley

Microbial activities are key to our planet's habitability and sustainability since they play essential roles in shaping and controlling virtually every natural system including our atmosphere, oceans, soils, and every plant and animal. Microbes exist in different metabolic states in these systems: growing, active, dormant, and recently deceased. These metabolic states correspond to different degrees of influence that a microbe can have on its environment. Therefore, to understand the relationships between microbial community patterns and ecosystem functions, it is important to accurately associate microbial identity with concurrent metabolic state. Through my research I strive to improve our understanding of microbial population, community, and process dynamics in soils and how to apply this information to better predict changes in ecosystem function. I applied a combination of community molecular analyses, chemical and physical characterizations, and process measurements to explore microbial mechanisms, interactions, and responses to changes in their environment.

Nucleic acid analysis has proven to be an effective avenue for characterizing the phylogenetic, taxonomic, and functional structure of microbial assemblages, but this approach has limitations when attempting to assess current metabolic state. Ribosomal RNA genes (rRNA genes) have frequently been used to identify microorganisms present in environmental samples regardless of metabolic state, while ribosomal RNA (rRNA) has been widely applied to identify the active fraction of microbes. Chapter 1 re-evaluates utilizing rRNA as an indicator of microbial activity in environmental samples. A growing body of evidence indicates that the general use of rRNA as an indicator of metabolic state in microbial assemblages has serious limitations. This chapter highlights the complex and often contradictory relationships between rRNA, growth, and activity. Potential mechanisms for confounding rRNA patterns are discussed, including differences in life histories, life strategies, and non-growth activities. Ways in which rRNA data can be used for meaningful characterization of microbial assemblages are presented.

Chapter 2 presents direct measurements of growth, mortality, and survival for bacteria and fungi following the rewetting of dry soil. The rapid stimulation of microbial activity that occurs when a dry soil is rewetted has been well documented and is of great interest due to implications of changing precipitation patterns on soil C dynamics. Many studies have characterized net changes in microbial populations, but gross population dynamics for bacteria and fungi following wet-up are not well understood. Here, DNA stable isotope probing with H₂¹⁸O was coupled with quantitative PCR to characterize new growth, survival, and mortality for bacteria and fungi following the rewetting of a seasonally dried California annual grassland soil. This study documents both net and gross changes that bacterial and fungal populations underwent over the course of 7 days after wet-up. A pulse of non-growth activity appears to immediately follow wet-up followed by linear growth for both bacteria and fungi. Mortality dynamics indicate that dead microbial bodies provide a large pool of available C and nutrients, thus offering insight into possible C sources fueling the CO₂ pulse following wet-up. Results reveal that a vibrant assemblage of growing and dying organisms may comprise a seemingly static microbial community following a change in the environment.

The bacterial growth stimulated by the rewetting of dry soil was further characterized using high throughput sequencing of 16S rRNA genes, and results are presented in Chapter 3. Of the 25 different phyla present in the pre-wet community, members of the Firmicutes Bacillales order were the only detectable early responders with close to a 5% increase in relative abundance from growth in the first 3 h after wet up. The second group of growers detected at 24 h included only Betaproteobacteria and Bacteroidetes. Members of the Burkholderiales order in the Betaproteobacteria phylum were by far the dominant growers during this period with a 21% increase in relative abundance. The highest richness of growing bacteria was detected during the third time-period (between 24-72 h), with significant changes in relative abundance due to growth found in 11 phyla. Nonmetric multidimensional ordination of community composition data through time shows a somewhat cyclical pattern for phylogenetic composition of growing bacteria with composition at 3 hours differing slightly from the pre-wet community, differing greatly at 24 h, and then becoming progressively more similar to the pre-wet community at 72 and 168 h. This suggests a degree of community resilience in response to this abrupt environmental change. However, some net compositional changes were observed following wet-up. Actinobacteria were the most dominant pre-wet phylum, but Proteobacteria became the most dominant phylum by 168 h. This change in composition was likely driven by new growth since Proteobacteria were found to grow in abundance for most of the incubation while Actinobacteria only grew during two later time periods and with smaller increases in relative abundance. Sequential growth patterns found at the phylum and order level suggest that ecologically coherent response was observable at a high taxonomic level.

Chapter 4 shifts emphasis to anaerobic oxidation of methane (AOM) in Tropical and Boreal soils. AOM is a considerable sink for the greenhouse gas methane (CH₄) in marine systems, but the importance of this process in terrestrial systems is less clear. Lowland boreal soils and wet tropical soils are two hotspots for CH₄ cycling, yet AOM has been essentially uncharacterized in these systems. We investigated AOM in soils from sites in Alaska and Puerto Rico. Isotope tracers were utilized in vitro to enable the simultaneous quantification of CH₄ production and consumption without use of biological inhibitors. Boreal peat soil and tropical mineral soil oxidized small but significant quantities of CH₄ to CO₂ under anoxic conditions. Potential AOM rates were 21 ± 2 nmol g_dw^-1 d^-1 and 2.9 ± 0.5 nmol g_dw^-1 d^-1 for the boreal and tropical soils, respectively. The addition of terminal electron acceptors (NO₃^-, Fe(III), and SO₄^2-) inhibited AOM and methanogenesis in both soils. In all incubations, CH₄ production occurred simultaneously with AOM, and CH₄ production rates were always greater than AOM rates. There was a strong correlation between the quantity of CH₄ produced and the amount of CH₄ oxidized under anoxic conditions. CH₄ oxidation under anoxic conditions was biological and likely mediated by methanogenic archaea. While only a small percentage of the total CH₄ produced in these soils was oxidized under anoxic conditions (0.3% and 0.8% for Alaskan and Puerto Rican soils), this process is important to understand since it could play a measurable role in controlling net CH₄ flux.