红壤微生物量在土壤—黑麦草系统中的肥力意义

研究了红壤微生物量与土壤养分循环及植物生长的内在联系．结果表明,红壤微生物量不仅与土壤有机碳、全氮、有效氮等显著相关,而且与植物干物质产量及吸Ｎ 量也存在着良好的相关性,可作为指示红壤肥力水平和作物产量的重要指标．试验测得的红壤微生物量Ｎ 周转期较短,每年通过微生物周转的Ｎ 素达到微生物量氮含量的１ ．５ 倍到数倍．     

Nutrient uptake and allocation at steady-state nutrition

Ingestad, T. and Ågren, G. I. 1988. Nutrient uptake and allocation at steady-state nutrition. - Physiol. Plant. 72: 450–459. Net nutrient uptake and translocation rates are discussed for conditions of steady-state nutrition and growth. Under these conditions, the relative uptake rate is equal to the relative growth rate, for whole plants as well as for plant parts, since the root/shoot ratio and internal concentrations remain stable. The nutrient productivity and the minimum internal concentration are parameters characteristic for the plant and the nutrient. A conceptual, mathematical model, based on these two fundamental parameters is used for calculation and prediction of the net nutrient uptake rate, which is required to maintain steady-state nutrition at a specified internal nutrient concentration or relative growth rate. When uptake rate is expressed on the basis of the root growth rate, there is, up to optimum, a strong linear relationship between uptake rate and the internal concentration of the limiting nutrient. More complicated and less consistent relationships are obtained when uptake rate is related to root biomass. The limiting factor for suboptimum uptake is the amount of nutrients becoming available at the root surface. When replenishment is efficient, e.g. with vigorous stirring, the concentration requirement at the root surface appears to be extremely low, even at optimum. In the suboptimum range of nutrition, the effect of nutrient status on root growth rate is a critical factor with a strong feed-back on nutrition, growth and allocation. At supraoptimum conditions, the uptake mechanism is interpreted as a protection against too high uptake rates and internal concentrations at high external concentration. In birch (Betula pendula Roth.), the allocation of nitrogen to the shoots is high compared to that of potassium and also to that of phosphorus at low nitrogen or phosphorus status. With decreasing stress, phosphorus allocation becomes more and more similar to nitrogen allocation. The formulation of a mathematical model for calculation of allocation of biomass and nutrients requires more exact information on the quantitative dependence of the growth-regulating processes on nutrition.     

Kinetics of bacterial processes in natural aquatic systems based on biomass as determined by high-resolution flow cytometry

The two primary kinetic constants for describing the concentration dependency of nutrient uptake by microorganisms are shown to be maximal rate of substrate uptake and, rather than the Michaelis constant for transport, specific affinity. Of the two, the specific affinity is more important for describing natural aquatic microbial processes because it can be used independently at small substrate concentrations. Flow cytometry was used to evaluate specific affinities in natural populations of aquatic bacteria because it gives a convenient measure of biomass, which is an essential measurement in the specific-affinity approach to microbial kinetics. Total biomass, biomass in various filter fractions, and the specific affinity of the bacteria in each fraction were determined in samples from a near-arctic lake. The partial growth rate of the pelagic bacteria from the 25 micrograms/liter of dissolved amino acids present (growth rate from the amino acid fraction alone) was determined to be 0.78 per day. By measuring activity in screened and whole-system populations, the biomass of the bacteria associated with particles was computed to be 427 micrograms/liter.     

Nutrient-limited microbial growth kinetics: overview and recent advances

Traditional concepts of nutrient uptake and growth kinetics as linked by cell yield are presented. Phenomena affecting the kinetics are examined along with a discussion of those which lead to ambiguity. Concepts of flux control are presented to help understand the distribution of material along metabolic pathways. Specific affinity is described to relate nutrient accumulation rates to transporter density. It is shown to be a primary kinetic constant and the best available index of nutrient collection ability. As an aid to understanding, specific affinity is reexpressed in terms of membrane permeability. Formulations of nutrient transport rate as a function of cellular composition, particularly transporter and enzyme content and known as janusian kinetics, are described as an improvement to specific affinity theory. Procedures for quantified unidirectional fluxes are reviewed to identify the difference between gross and net transport rates of substrate. Collision frequency theory is used to show that in addition to total biomass, cell size and transporter density should also be included in rate equations describing microbial growth. Theory diversity suggests that one reason for microbial metabolic is that the likelihood of additional collisions of substrate molecules with a cell surface, after an initial collision, requires only a sparse distribution of transporter sites for maximal rate, leaving room for additional transporters able to collect other substrate types.     

Influence of decomposer food web structure and nitrogen availability on plant growth

We studied the sensitivity of soil microbial communities and ecosystem processes to variation in the vertical and horizontal structure of decomposer food web under nitrogen poor and N-enriched conditions. Microcosms with humus and litter layer of boreal forest floor, birch seedlings infected with mycorrhizal fungi, and decomposer food webs with differing trophic group and species composition of soil fauna were constructed. During the second growing period for the birch, we irrigated half of the microcosms with urea solution, and the other half with de-ionised water to create two levels of N concentration in the substrate. During the experiment night time respirations of the microcosms were measured, and the water leached through the microcosms was analysed for concentration of mineral N, and nematode numbers. The microcosms were destructively sampled after 37 weeks for plant biomass and N uptake, structure of soil animal and microbial community (indicated by PLFA profiles), and physical and chemical properties of the humus and litter materials. Predatory mites and nematodes had a negative influence on the biomass of their microbivorous and microbi-detritivorous prey, and microbi-detritivores affected the biomass and community structure of microbes (indicated by PLFA-analysis). Moreover, predatory mites and nematodes increased microbial biomass and changed the microbial community structure. The decomposer food web structure affected also N uptake and growth of plants. Microbi-detritivorous fauna had a positive effect, whereas predators of microbial and detritus feeding fauna exerted a negative influence on plant N uptake and biomass production. The impact of a trophic group on the microbes and plant was also strongly dependent on species composition within the group. Nitrogen addition magnified the influence of food web structure on microbial biomass and plant N uptake. We suggest that addition of urea-N to the soil modified the animal-microbe interaction by increasing microbial growth and altering community structure of microbes. The presence of microbi-detritivores and predators reduced loss of carbon from the microcosms, and the food web structure influenced also water holding capacity of the materials. The changes in plant growth, nutrient cycling, size of N and C pools, and in the physical properties of the soil emphasize the importance and diversity of indirect consequences of decomposer food web structure. This revised version was published online in June 2006 with corrections to the Cover Date.     

Stable adaptive algorithm for simultaneous estimation of time-varying parameters and state variables in aerobic bioprocesses

The application of modern model based control algorithms in the bioprocesses is hampered by the lack of accurate and cheap on-line sensors, capable of providing on-line measurements of the main process variables and parameters. In this paper, a new approach for estimation of immeasurable time-varying parameters and state variable is presented for a class of aerobic bioprocesses using only on-line measurements of the oxygen uptake rate. The approach consists in the design of a new parameter estimator of biomass growth rate and yield coefficient for oxygen consumption on the basis of the theory of adaptive estimation. The dynamical equation of the measurable reaction rate, oxygen uptake rate, is presented as a linear one with respect to the biomass growth rate and the yield coefficient for oxygen consumption. In this way, the structure of the proposed estimator becomes linear time-varying one. After some mathematical transformations, that structure is presented in a form, allowing to be derived the stability conditions using some theoretical results concerning the stability of adaptive observers. The estimates of the yield coefficient for oxygen consumption, the biomass concentration and specific growth rate are obtained then on the basis of the generated estimates using well known kinetic models of bioprocesses. With respect to previous similar approaches, the new estimation algorithm gives stable estimates not only of immeasurable state variable and reaction rates but likewise of an yield coefficient. The behavior of the proposed estimator is studied under inexact initial conditions, step changes of dilution rate and in the presence of measurement noise by simulations using a process model, which belongs to the investigated class of bioprocesses.     

Evaluation of growth yield of Spirulina (Arthrospira) sp. in photoautotrophic, heterotrophic and mixotrophic cultures

In microbial cultures, both cellular growth rate and yield (defined as the degree of substrate conversion into the biomass) are important. Although effect of culture conditions on growth kinetics has been well documented for various microbial strains, there is almost no literature concerning the effect of environmental conditions on growth equilibrium, expressed as biomass yield coefficients from substrate. The present paper discusses the effect of culture conditions: irradiance (physical substrate) and glucose concentration (chemical substrate) on biomass yield coefficients from two chemical substrates: glucose and nitrate-nitrogen in photoautotrophic, heterotrophic and mixotrophic culture of blue-green alga Spirulina (Arthrospira) sp. The efficiency of substrates incorporation into the biomass can be precisely determined only if the elemental composition of the biomass is known. The experimental results showed that culture conditions had a substantial influence on biomass yield coefficients (biomass yield from glucose and nitrate-nitrogen). It was found that, the increase of irradiance favoured increase of biomass yield coefficient from both, glucose and nitrate-nitrogen. However, in the case of yield from nitrogen in mixotrophic culture, the effect was opposite. The effect of glucose concentration was different: the higher the initial glucose concentration, the lower the biomass yield coefficients from chemical substrates.     

土壤微生物碳素利用效率研究进展

土壤微生物碳素利用效率(CUE)是指微生物将吸收的碳(C)转化为自身生物量C的效率,也称为微生物的生长效率。土壤微生物CUE是生态系统C循环中的重要生理生态学参数,影响着生态系统的C固持、周转、土壤矿化以及温室气体排放等过程。在全球环境变化背景下,认识土壤微生物CUE的变异及其影响机制,对于更好的认识生态系统C循环过程及其对全球变化的响应具有重要意义。概述了CUE的定义及其测定方法,重点综述和分析土壤微生物CUE的变异及影响因素取得的研究进展。基于现有研究的分析得出,土壤微生物CUE通常表示为微生物的生长与吸收的比值,分为基于微生物生长速率、微生物生物量、底物吸收速率和底物浓度变化等方法进行测定。土壤微生物CUE在0.2-0.8的范围内变化,这种变异主要受到来自热力学、生态环境因子、底物养分质量和有效性、化学计量平衡以及微生物群落组成的影响。今后土壤微生物CUE的研究应加强对微量代谢组分的定量分析,生物和环境要素交互影响的调控机理解析,以及微生物动态生理响应过程的碳循环模型优化。     

有机无机肥配施提高麦-稻轮作系统中水稻氮肥利用率的机制

采用盆栽试验,研究了有机无机肥配施对麦-稻轮作系统中水稻氮素累积动态和土壤氮素供应动态的影响,并从微生物学角度探讨了有机无机肥协同提高水稻氮肥利用率的机制.结果表明：有机无机肥配施处理的土壤微生物生物量碳、氮和矿质态氮在水稻分蘖期前低于化肥处理,而在抽穗期至灌浆期显著高于其他处理.土壤氮素供应动态与水稻吸收利用氮素规律吻合程度最高,促进了水稻产量、生物量和氮素累积量的增加,显著提高了水稻的氮肥利用率.其主要机制是有机无机肥配施促进了土壤微生物繁殖,使其在水稻生育前期固持了较多的矿质氮,在水稻生育中、后期这些氮素逐渐被释放以供水稻吸收利用,较好地满足了水稻各阶段生长发育对氮素养分的需求.     

Phenomenological Model for Predicting the Catabolic Potential of an Arbitrary Nutrient

The ability of microbial species to consume compounds found in the environment to generate commercially-valuable products has long been exploited by humanity. The untapped, staggering diversity of microbial organisms offers a wealth of potential resources for tackling medical, environmental, and energy challenges. Understanding microbial metabolism will be crucial to many of these potential applications. Thermodynamically-feasible metabolic reconstructions can be used, under some conditions, to predict the growth rate of certain microbes using constraint-based methods. While these reconstructions are powerful, they are still cumbersome to build and, because of the complexity of metabolic networks, it is hard for researchers to gain from these reconstructions an understanding of why a certain nutrient yields a given growth rate for a given microbe. Here, we present a simple model of biomass production that accurately reproduces the predictions of thermodynamically-feasible metabolic reconstructions. Our model makes use of only: i) a nutrient''s structure and function, ii) the presence of a small number of enzymes in the organism, and iii) the carbon flow in pathways that catabolize nutrients. When applied to test organisms, our model allows us to predict whether a nutrient can be a carbon source with an accuracy of about 90% with respect to in silico experiments. In addition, our model provides excellent predictions of whether a medium will produce more or less growth than another () and good predictions of the actual value of the in silico biomass production.     

Microbial community dynamics alleviate stoichiometric constraints during litter decay

Under the current paradigm, organic matter decomposition and nutrient cycling rates are a function of the imbalance between substrate and microbial biomass stoichiometry. Challenging this view, we demonstrate that in an individual‐based model, microbial community dynamics alter relative C and N limitation during litter decomposition, leading to a system behaviour not predictable from stoichiometric theory alone. Rather, the dynamics of interacting functional groups lead to an adaptation at the community level, which accelerates nitrogen recycling in litter with high initial C : N ratios and thus alleviates microbial N limitation. This mechanism allows microbial decomposers to overcome large imbalances between resource and biomass stoichiometry without the need to decrease carbon use efficiency (CUE), which is in contrast to predictions of traditional stoichiometric mass balance equations. We conclude that identifying and implementing microbial community‐driven mechanisms in biogeochemical models are necessary for accurately predicting terrestrial C fluxes in response to changing environmental conditions.     

采油微生物在微驱过程中的生长、运移及分布规律

[目的]深入了解现场微生物驱油机理、效果评价标准及影响因素.[方法]结合现场微生物驱油过程产出液的跟踪监测及室内物模实验对微生物在地层中的生长繁殖、运移及分布规律进行研究.[结果]结果表明,通过从水井注入的外源微生物在油藏中能够有效生长繁殖,而且注入的营养液也能够激活内源微生物,但由于地层渗透率及营养液浓度的影响,产出液菌浓要比注入菌浓低1-2个数量级;葡萄糖的快速降解以及地层对微生物的过滤及吸附作用使大量的微生物停留在近井地带,仅有部分微生物能够从生产井采出,而且其运移速度要比营养液慢.[结论]地层渗透率和产出液中营养物浓度是影响微生物数量及分布的两个关键因素,现场微生物驱油产出液中的菌浓一般很难达到106个/mL以上,该研究结果对微生物驱油技术的发展和应用具有重要意义.     

Limitation of growth rate by two complementary nutrients: some elementary but neglected considerations

Experimental data in the literature show that the yield of biomass from a particular nutrient when that nutrient limits growth rate is often significantly different than the yield from the nutrient when some complementary nutrient limits growth rate. This article explores some possible consequences for bioreactor dynamics of dependence of yield coefficients on the identity of the nutrient that limits growth rate.     

The influence of dissolved nutrients and particulate organic matter quality on microbial respiration and biomass in a forest stream

1. Although dissolved nutrients and the quality of particulate organic matter (POM) influence microbial processes in aquatic systems, these factors have rarely been considered simultaneously. We manipulated dissolved nutrient concentrations and POM type in three contiguous reaches (reference, nitrogen, nitrogen + phosphorus) of a low nutrient, third‐order stream at Hubbard Brook Experimental Forest (U.S.A). In each reach we placed species of leaves (mean C : N of 68 and C : P of 2284) and wood (mean C : N of 721 and C : P of 60 654) that differed in elemental composition. We measured the respiration and biomass of microbes associated with this POM before and after nutrient addition. 2. Before nutrient addition, microbial respiration rates and biomass were higher for leaves than for wood. Respiration rates of microbes associated with wood showed a larger response to increased dissolved nutrient concentrations than respiration rates of microbes associated with leaves, suggesting that the response of microbes to increased dissolved nutrients was influenced by the quality of their substrate. 3. Overall, dissolved nutrients had strong positive effects on microbial respiration and fungal, but not bacterial, biomass, indicating that microbial respiration and fungi were nutrient limited. The concentration of nitrate in the enriched reaches was within the range of natural variation in forest streams, suggesting that natural variation in nitrate among forest streams influences carbon mineralisation and fungal biomass.     

Progressive N limitation of plant response to elevated CO2: a microbiological perspective

A major uncertainty in predicting long-term ecosystem C balance is whether stimulation of net primary production will be sustained in future atmospheric CO₂ scenarios. Immobilization of nutrients (N in particular) in plant biomass and soil organic matter (SOM) provides negative feedbacks to plant growth and may lead to progressive N limitation (PNL) of plant response to CO₂ enrichment. Soil microbes mediate N availability to plants by controlling litter decomposition and N transformations as well as dominating biological N fixation. CO₂-induced changes in C inputs, plant nutrient demand and water use efficiency often have interactive and contrasting effects on microbes and microbially mediated N processes. One critical question is whether CO₂-induced N accumulation in plant biomass and SOM will result in N limitation of microbes and subsequently cause them to obtain N from alternative sources or to alter the ecosystem N balance. We reviewed the experimental results that examined elevated CO₂ effects on microbial parameters, focusing on those published since 2000. These results in general show that increased C inputs dominate the CO₂ impact on microbes, microbial activities and their subsequent controls over ecosystem N dynamics, potentially enhancing microbial N acquisition and ecosystem N retention. We reason that microbial mediation of N availability for plants under future CO₂ scenarios will strongly depend on the initial ecosystem N status, and the nature and magnitude of external N inputs. Consequently, microbial processes that exert critical controls over long-term N availability for plants would be ecosystem-specific. The challenge remains to quantify CO₂-induced changes in these processes, and to extrapolate the results from short-term studies with step-up CO₂ increases to native ecosystems that are already experiencing gradual changes in the CO₂ concentration.     

Prediction of microbial growth rate versus biomass yield by a metabolic network with kinetic parameters

Identifying the factors that determine microbial growth rate under various environmental and genetic conditions is a major challenge of systems biology. While current genome-scale metabolic modeling approaches enable us to successfully predict a variety of metabolic phenotypes, including maximal biomass yield, the prediction of actual growth rate is a long standing goal. This gap stems from strictly relying on data regarding reaction stoichiometry and directionality, without accounting for enzyme kinetic considerations. Here we present a novel metabolic network-based approach, MetabOlic Modeling with ENzyme kineTics (MOMENT), which predicts metabolic flux rate and growth rate by utilizing prior data on enzyme turnover rates and enzyme molecular weights, without requiring measurements of nutrient uptake rates. The method is based on an identified design principle of metabolism in which enzymes catalyzing high flux reactions across different media tend to be more efficient in terms of having higher turnover numbers. Extending upon previous attempts to utilize kinetic data in genome-scale metabolic modeling, our approach takes into account the requirement for specific enzyme concentrations for catalyzing predicted metabolic flux rates, considering isozymes, protein complexes, and multi-functional enzymes. MOMENT is shown to significantly improve the prediction accuracy of various metabolic phenotypes in E. coli, including intracellular flux rates and changes in gene expression levels under different growth rates. Most importantly, MOMENT is shown to predict growth rates of E. coli under a diverse set of media that are correlated with experimental measurements, markedly improving upon existing state-of-the art stoichiometric modeling approaches. These results support the view that a physiological bound on cellular enzyme concentrations is a key factor that determines microbial growth rate.     

Experimental and theoretical investigations of rotating algae biofilm reactors (RABRs): Areal productivity,nutrient recovery,and energy efficiency

Microalgae biofilms have been demonstrated to recover nutrients from wastewater and serve as biomass feedstock for bioproducts. However, there is a need to develop a platform to quantitatively describe microalgae biofilm production, which can provide guidance and insights for improving biomass areal productivity and nutrient uptake efficiency. This paper proposes a unified experimental and theoretical framework to investigate algae biofilm growth on a rotating algae biofilm reactor (RABR). Experimental laboratory setups are used to conduct controlled experiments on testing environmental and operational factors for RABRs. We propose a differential–integral equation-based mathematical model for microalgae biofilm cultivation guided by laboratory experimental findings. The predictive mathematical model development is coordinated with laboratory experiments of biofilm areal productivity associated with ammonia and inorganic phosphorus uptake by RABRs. The unified experimental and theoretical tool is used to investigate the effects of RABR rotating velocity, duty cycle (DC), and light intensity on algae biofilm growth, areal productivity, nutrient uptake efficiency, and energy efficiency in wastewater treatment. Our framework indicates that maintaining a reasonable light intensity range improves biomass areal productivity and nutrient uptake efficiency. Our framework also indicates that faster RABR rotation benefits biomass areal productivity. However, maximizing the nutrient uptake efficiency requires a reasonably low RABR rotating speed. Energy efficiency is strongly correlated with RABR rotating speed and DC.     

Computer controlled transient state in a fed batch culture

Summary A controlled shift down of the specific growth rate in a fed batch culture is proposed for microbial product formation processes. The growth kinetics depend on three preset parameters: initial biomass concentration, initial specific growth rate, and the transient constant (time derivative of the specific growth rate). An experimental example is given.     

Analytical solution for a hybrid Logistic-Monod cell growth model in batch and continuous stirred tank reactor culture

Monod and Logistic growth models have been widely used as basic equations to describe cell growth in bioprocess engineering. In the case of the Monod equation, the specific growth rate is governed by a limiting nutrient, with the mathematical form similar to the Michaelis–Menten equation. In the case of the Logistic equation, the specific growth rate is determined by the carrying capacity of the system, which could be growth-inhibiting factors (i.e., toxic chemical accumulation) other than the nutrient level. Both equations have been found valuable to guide us build unstructured kinetic models to analyze the fermentation process and understand cell physiology. In this work, we present a hybrid Logistic-Monod growth model, which accounts for multiple growth-dependent factors including both the limiting nutrient and the carrying capacity of the system. Coupled with substrate consumption and yield coefficient, we present the analytical solutions for this hybrid Logistic-Monod model in both batch and continuous stirred tank reactor (CSTR) culture. Under high biomass yield (Y_x/s) conditions, the analytical solution for this hybrid model is approaching to the Logistic equation; under low biomass yield condition, the analytical solution for this hybrid model converges to the Monod equation. This hybrid Logistic-Monod equation represents the cell growth transition from substrate-limiting condition to growth-inhibiting condition, which could be adopted to accurately describe the multi-phases of cell growth and may facilitate kinetic model construction, bioprocess optimization, and scale-up in industrial biotechnology.     

Ocean acidification with (de)eutrophication will alter future phytoplankton growth and succession

Human activity causes ocean acidification (OA) though the dissolution of anthropogenically generated CO₂ into seawater, and eutrophication through the addition of inorganic nutrients. Eutrophication increases the phytoplankton biomass that can be supported during a bloom, and the resultant uptake of dissolved inorganic carbon during photosynthesis increases water-column pH (bloom-induced basification). This increased pH can adversely affect plankton growth. With OA, basification commences at a lower pH. Using experimental analyses of the growth of three contrasting phytoplankton under different pH scenarios, coupled with mathematical models describing growth and death as functions of pH and nutrient status, we show how different conditions of pH modify the scope for competitive interactions between phytoplankton species. We then use the models previously configured against experimental data to explore how the commencement of bloom-induced basification at lower pH with OA, and operating against a background of changing patterns in nutrient loads, may modify phytoplankton growth and competition. We conclude that OA and changed nutrient supply into shelf seas with eutrophication or de-eutrophication (the latter owing to pollution control) has clear scope to alter phytoplankton succession, thus affecting future trophic dynamics and impacting both biogeochemical cycling and fisheries.