Microorganism biomass measurement

The deconvolution of spectra is the topic of a paper by Vaidyanathan et al.58 The authors use the somewhat complex matrix of mycelial bioprocesses for a model. Throughout the reactions of five different unicellular microorganisms, biomass, external proteins, penicillin, T-sugars, and ammonium were measured vs. time. Each analyte was justified from spectral interpretation. The spectral range used was from 700 to 2500 nm, with specific regions used for each experiment. 

The fundamental aspects as well as design and operations of SSF have been well elaborated by Pandey et al. [3, 4, 11]. These include the selection of the microorganism, specific growth rate, biomass measurement, and so on, which also have been described by several other authors [12-15]. 

P, mainly in the form of RNA and DNA, polyphosphates and phospholipids, with minor amounts of other P-containing cell biochemicals like adenosine phosphates. Measurement of the P content of the microbial biomass is an essential prerequisite for assessing its role in the P cycle, and its effect on plant nutrition. Until very recently, estimates of microbial P have had to be made from microbial biomass measurements, and literature values for the P contents of laboratory cultured microorganisms which can vary widely depending on growth conditions. ... 

Temperature, pH, and feed rate are often measured and controlled. Dissolved oxygen (DO) can be controlled using aeration, agitation, pressure, and/or feed rate. Oxygen consumption and carbon dioxide formation can be measured in the outgoing air to provide insight into the metaboHc status of the microorganism. No rehable on-line measurement exists for biomass, substrate, or products. Most optimization is based on empirical methods simulation of quantitative models may provide more efficient optimization of fermentation. 

Chlorophyll a (Chi a) functions as the primary light harvesting pigment in marine oxygenic phototrophs. Even though the C Chl a ratio of photoautotrophic cells varies considerably as a function of environmental conditions and growth rate (Laws et al., 1983), measurements of Chi a have been used extensively to estimate the biomass of photoautotrophic microorganisms in the sea. 

If such enzymes occur at the same levels in relevant microbial populations, Vmax may be directly related to other metrics of biomass presence such as cell numbers, biomass dry weight, or protein concentrations. In an attempt to enable extending results from one system to another (e.g., from laboratory observations to field situations), one often normalizes Fmax by such biomass parameters. For example, in Table 17.7, the observed Vmax values are normalized to the protein contents of the tested microbial populations or isolated enzymes, and the result is given as values Vmax (the prime is added to emphasize the normalization). To apply such information to new situations, one must multiply the normalized maximum velocities by a measure of the relevant enzyme concentration or biomass protein in the new system of interest (e.g., Vmax x microbial protein content in new case involving intact microorganisms). Of course, one is assuming that the ratio of enzyme to total protein is the same in the old and new situation. 

Bakken, L.R. and Olsen, R.A., 1983. Buoyant densities and dry-matter contents of microorganisms conversion of a measured biovolume into biomass. Appl. Environ. Microbiol., 45 1188-1195. 

Measurement of soil activity there are a number of laboratory methods which are suitable for measuring the biological activity of the soil. In principle, a distinction is made between direct and indirect methods for the determination of soil activity. The biomass in the soil, for example, can be estimated by counting the individual organisms in the soil, or the measurement of respiration after the addition of a nutrient in excess can provide an indication of active biomass. Moreover, in determinations of activity, a distinction is made between actual and potential activity. Actual activity values are values measured at the time that the sample was taken. Determinations of potential activity, on the other hand, show the level of performance that microorganisms are capable of under optimum experimental conditions, after the addition of a nutrient substrate and prolonged incubation. 

Equation (2) expresses the metaboHc activity of the microorganism, measured in the presence of the particular solvent, relative to the positive control, that is, when the metabohsm of the microorganism is uninhibited. Both of these values are corrected for any changes in the biomass concentration that might have occurred due to stress or any other process (es), with exception of the utilization of carbon and energy source. This is done by subtracting Xiegative control- After aU the Z values are calculated, these are plotted as a function of the respective log P values. This is demonstrated for a hypothetical MO in Fig. 8.2. 

In conclusion, we have to outline the limits of respiratory methods. Indeed, in the metabolic reaction, polymer carbon is used by microorganisms to produce not only C02, but also oligomers and new biomass. Thus, a single measurement of C02 (or, what is worse, consumed 02) is not sufficient to clearly indicate the amount of transformed polymer. Dissolved organic carbon (DOC) is sometimes measured at the end of the test and indicates the amount of oligomer remaining in the medium. This procedure should be obligatory in order to make the balance of carbon, and to check if there are no unexpected losses. 

Approximate ranges of subsurface bacterial biomass and metabolic activity from the literature are shown in Table II. There have been few studies of relative measures of biomass or activity at contaminated versus uncontaminated sites. It is clear that certain functional classes of bacteria appear to increase in organic-rich environments (11-121 There are substantial problems associated with determining microbial activity in contaminated environments due to the diversity of types of microorganisms and chemical interferences with assay procedure. 

The heat produced during the growth of microorganisms can be also be used for biomass concentration estimation. Different calorimetric devices (external-flow, twin-type, and heat-flux calorimeters) and different calorimetric techniques (dynamic and continuous calorimetry) have been used for on-line biomass estimation [8j. In most cases, the experimental setup is complicated and measurements are restricted to relatively small volumes (less than 1 L). Larger devices (continuous calorimeters for volumes up to 14 L) were studied by Luong and Volesky [123-125]. One of the best devices seems to be the heat-flux calorimeter developed by Marison and von Stockar. Several applications to bioprocess monitoring are given by the authors [126-129]. 

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