No abstract

The ecology of purple sulfur bacteria in a sewage oxidation lagoon was investigated. Chemical changes in the lagoon were investigated by monitoring biochemical oxygen demand (BOD 5 ), sulfide, sulfate, phosphate, total carbohydrates, volatile acids, alkalinity, and p H. Lagoon water temperatures were observed daily. Microbial ecological relationships were deduced by enumerating coliforms, total bacteria other than anaerobes [Tryptone Glucose Extract (TGE) agar], methane formers such as Methanobacterium formicicum , sulfate reducers, purple sulfur bacteria, and algae. Finally, two strains of purple sulfur bacteria were characterized. Two populations, purple sulfur bacteria and total bacteria (TGE agar), reached maximal concentrations in the warmest part of the 1967 summer. Purple sulfur bacteria reached maximal numbers as concentrations of sulfide and volatile acids were depleted, whereas carbohydrates and alkalinity remained unchanged. Low sulfate levels, which were not limiting for sulfate reducers, may be attributable to storage of sulfur within purple sulfur bacteria. No biological, chemical, or physical agent was linked to the removal of coliforms. The increase of algae in the late summer of 1967 may have been related to the low organic content of the lagoon during this period. Although lagoon p H (7.7 to 8.2) was favorable for purple sulfur bacterial growth, temperatures and sulfides were not optimal in the lagoon for these organisms. Chromatium vinosum and Thiocapsa floridana (the predominant lagoon purple sulfur organism in 1967 and 1968) utilized certain carbohydrates, amino acids, volatile acids, and Krebs cycle intermediates. Also purple sulfur bacteria lowered BOD levels as demonstrated by the growth of T. floridana in sterilized sewage.

The correlation between total dissolved phosphorus input concentrations and periphytic chlorophyll a concentrations was examined after a four-week colonization period on artificial substrates in large, continuous-flow microcosms. A significant correlation was established; the data produced a linear regression and substantiated a recently proposed curvilinear regression analysis. The curvilinear equation can be used in future microcosm studies as a predictive aid for regulating phosphorus input concentrations.

Using batch cultures, we determined transformation rates for low concentrations of two toxicants-an insecticide, methyl parathion (O,O-dimethyl O-pnitrophenyl phosphorothioate), and a plasticizer, diethyl phthalate-by aufwuchs, aquatic microbial growth attached to submerged surfaces or suspended in streamers or mats. Aufwuchs samples were collected from field sites, an indoor channel, and a continuous-flow fermentor. Aufwuchs fungi, protozoa, and algae did not transform methyl parathion or diethyl phthalate, but bacteria rapidly transformed both chemicals. Second-order transformation rate coefficients, Kb, based on total plate counts of bacteria in aufwuchs, were determined for potential use in a mathematical model capable of predicting the transport and fate of chemicals in aquatic systems. Kb for both methyl parathion and diethyl phthalate decreased as the concentration of total bacteria, [B], increased in aufwuchs. This effect resulted from the proportion of nontransformer to transformer bacteria increasing as [B] increased and from the rate of transformation per transformer cell decreasing as [B] increased. First-order transformation rate coefficients, K,, were relatively stable per unit of surface area colonized by aufwuchs, because Kb decreased as [B] increased (K1 = Kb X [B]).

The transport, fate and effects of many toxic chemicals in aquatic ecosystems are largely mediated by microbial transformations. In our research, we have assumed that the transformations are a result of enzymatic reactions, and thus follow Michaelis‐Menten kinetics. Using diverse field‐collected and laboratory microcosm microbiota, we obtained sufficient experimental data to reach some general conclusions concerning the strengths and weaknesses of using Michaelis‐Menten kinetics in making environmental predictions. We concluded that this approach is best suited to predicting microbial transformations for pollutant concentrations of approximately 10−7 M or lower. The approach also is applicable to high pollutant concentrations (saturated systems), provided that toxic effects of the pollutant and adaptation are considered. Unfortunately, most experiments have been conducted in the upper 10−7 to 10−4 M pollutant concentration range, which may approach saturation for a portion of enzymatic systems in a mixed population. This range is ideal for analytical purposes, but could be confounded by mixed‐order and multiphasic kinetics, toxic effects of the pollutant and adaptation. Adaptation, mass‐transport effects, multiphasic kinetics of pollutant uptake and transformation, and suppression of transformation by diauxie, biologically produced inhibitors, and other xenobiotic chemicals are some of the factors that we believe need to be more thoroughly evaluated to improve predictive modeling capabilities.