基因芯片技术用于细菌检测的研究

将待检测的细菌标本与已制备好的细菌基因芯片进行杂交,采用芯片扫描仪可检测细菌耐药性基因、细菌基因表达水平和未知细菌。     

Thermodynamic and metabolic effects on the scaling of production and population energy use

Ecosystem properties result in part from the characteristics of individual organisms. How these individual traits scale to impact ecosystem‐level processes is currently unclear. Because metabolism is a fundamental process underlying many individual‐ and population‐level variables, it provides a mechanism for linking individual characteristics with large‐scale processes. Here we use metabolism and ecosystem thermodynamics to scale from physiology to individual biomass production and population‐level energy use. Temperature‐corrected rates of individual‐level biomass production show the same body‐size dependence across a wide range of aerobic eukaryotes, from unicellular organisms to mammals and vascular plants. Population‐level energy use for both mammals and plants are strongly influenced by both metabolism and thermodynamic constraints on energy exchange between trophic levels. Our results show that because metabolism is a fundamental trait of organisms, it not only provides a link between individual‐ and ecosystem‐level processes, but can also highlight other important factors constraining ecological structure and dynamics.     

Thermodynamic principles of the behavior of biological systems

A theory of the behavior of biological systems is proposed which is an extension of the conception of biological evolution (Gladyshev, 1977, Gladyshev, 1978) based on classical (equilibrium) thermodynamics. A thermodynamic theory of homeostasis is presented, in accordance with which homeostatic mechanisms of regulation are connected with a compensative shift of a fundamental quasi-equilibrium. The principle of least compulsion is formulated on the basis of thermodynamic laws and describes behavior of biological systems. A fundamental thermodynamic equation of behavioral processes is introduced. The Weber-Fechner law is shown to be a corollary of the fundamental thermodynamic equation.     

Characterization of mismatch and high-signal intensity probes associated with Affymetrix genechips

MOTIVATION: For Affymetrix microarray platforms, gene expression is determined by computing the difference in signal intensities between perfect match (PM) and mismatch (MM) probesets. Although the use of PM is not controversial, MM probesets have been associated with variance and ultimately inaccurate gene expression calls. A principal focus of this study was to investigate the nature of the MM signal intensities and demonstrate its contribution to the experimental results. RESULTS: While most MM intensities were likely associated with random noise, a subset of approximately 20% (99,485) of the MM probes displayed relatively high signal intensities to the corresponding PM probes (MM > PM) in a non-random fashion; 13,440 of these probes demonstrated exceptionally high 'outlier' intensities. About 15,938 PM probes also demonstrated exceptionally high outlier intensities consistently across all hybridizations. About 92% of the MM > PM probes had either a dThymidine (dT) or a dCytidine (dC) at the 13th position of the probe sequence. MM and PM probes displaying extremely high outlier intensities contained high dC rich nucleotides, and low dA contents at other nucleotides positions along the 25mer probe sequence. Differentially expressed genes generated using Genechip Operating System (GCOS) or modified PM-only methods were also examined. Of those candidate genes identified in the PM-only method, 157 of them were designated by GCOS as absent across all datasets and many others contained probes with MM > PM signal intensities. Our data suggests that MM intensity from PM signal can be a major source of error analysis, leading to fewer potentially biologically important candidate genes. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.     

Thermodynamic and spectroscopic features of the behavior of amphotericin B in aqueous medium

The interaction between amphotericin B molecules in aqueous medium solution was studied using absorption and circular dichroism approaches. The results showed that at concentrations below 1 microM of amphotericin B, an equilibrium between the monomer and aggregate occurred with a constant of approximately 0.6x10(6) M(-1). The aggregate formation constant was dependent on the experimental conditions of the medium: its value increased at acidic pH values, while alkaline medium induced the equilibrium displacement to the monomer formation. Either neutral salts or chaotropic agents such as urea prevented the formation of the aggregate. The presence of net electrical charge on the amine and carboxyl groups plays a role in the thermodynamic stability of the aggregate. A hydrophobic effect was also found between the monomer form and the water molecules of neighbours. In the aggregate formation water molecules were released contributing to an increase in the entropic change.     

Carrying capacity and demographic stochasticity: scaling behavior of the stochastic logistic model

The stochastic logistic model is the simplest model that combines individual-level demography with density dependence. It explicitly or implicitly underlies many models of biodiversity of competing species, as well as non-spatial or metapopulation models of persistence of individual species. The model has also been used to study persistence in simple disease models. The stochastic logistic model has direct relevance for questions of limiting similarity in ecological systems. This paper uses a biased random walk heuristic to derive a scaling relationship for the persistence of a population under this model, and discusses its implications for models of biodiversity and persistence. Time to extinction of a species under the stochastic logistic model is approximated by the exponential of the scaling quantity U=(R-1)(2) N/R(R+1), where N is the habitat size and R is the basic reproductive number.     

Metabolic scaling in turtles

Bennett and Dawson (1976) presented an analysis of the relationship of metabolic rate (MR) and body mass among turtles, based on 10 studies, but unlike most of other groups of ectotherms, there has been no update to include the many later reports on turtles. Here I present a review of the data on turtle metabolic rates at 20, 25, and 30 °C, along with regression equations and graphical analyses from a large number of studies. Two generalities emerge: (1) reported metabolic rates for sea turtles are higher than for other chelonians, although it is not certain whether this is an intrinsic characteristic of sea turtles or an artifact related to experimental conditions (such as greater activity of sea turtles in metabolic chambers and the fact that a number of studies were done with the turtles out of water), and (2) the slopes of the log–log plots of metabolic rate (MR) vs. body mass [b in the allometric equation MR = a(mass)^b] are mostly lower than previously reported in smaller studies.     

Influence of local and residual structures on the scaling behavior and dimensions of unfolded proteins

Although recent spectroscopic studies of chemically denatured proteins hint at significant nonrandom residual structure, the results of extensive small angle X-ray scattering studies suggest random coil behavior, calling for a coherent understanding of these seemingly contradicting observations. Here, we report the results of a Monte Carlo study of the effects of two types of local structures, alpha helix and Polyproline II (PPII) helix, on the dimensions of random coil polyalanine chains viewed as a model of highly denatured proteins. We find that although Flory's power law scaling, long regarded as a signature of random coil behavior, holds for chains containing up to 90% alpha or PPII helix, the absolute magnitude of the chain dimensions is sensitive to helix content. As residual alpha helix content increases, the chain contracts until it reaches a minimum radius at approximately 70% helix, after which the chain dimensions expand rapidly. With an alpha helix content of approximately 20%, corresponding to the Ramachandran probability of being in the helical basin, experimentally observed radii of gyration are recovered. Experimental radii are similarly recovered at an alpha helix content of approximately 87%, providing an explanation for the previously puzzling experimental finding that the dimensions of the highly helical methanol-induced unfolded state are experimentally indistinguishable from those of the helix-poor urea-unfolded state. In contrast, the radius of gyration increases monotonically with increasing PPII content, and is always more expanded than the dimensions observed experimentally. These results suggest that PPII is unlikely the sole, dominant preferred conformation for unfolded proteins.     

Thermodynamic nonequilibrium phase change behavior and thermal properties of biological solutions for cryobiology applications

Understanding the phase change behavior of biomaterials during freezing/thawing including their thermal properties at low temperatures is essential to design and improve cryobiology applications such as cryopreservation and cryosurgery. However, knowledge of phase change behavior and thermal properties of various biomaterials is still incomplete, especially at cryogenic temperatures (< or = -40 degrees C). Moreover, in these applications, chemicals are often added to improve their outcome, which can result in significant variation in the phase change behavior and thermal properties from those of the original biomaterials. These chemical additives include cryoprotective agents (CPAs), antifreeze protein (AFP), or cryosurgical adjuvants like sodium chloride (NaCl). In the present study, phase change behavior and thermal properties of saline solutions--either water-NaCl or phosphate buffered saline (PBS)--with various chemical additives were investigated. The chemical additives studied are glycerol and raffinose as CPAs, an AFP (Type III, molecular weight = 6500), and NaCl as a cryosurgical adjuvant. The phase change behavior was investigated using a differential scanning calorimeter (DSC) and a cryomicroscope. The specific and latent heat of these solutions were also measured with the DSC. The saline solutions have two distinct phase changes--water/ice and eutectic phase changes. During freezing, eutectic solidification of both water-NaCl and PBS are significantly supercooled below their thermodynamic equilibrium eutectic temperatures. However, their melting temperatures are close to thermodynamic equilibrium during thawing. These eutectic phase changes disappear when even a small amount (0.1 M glycerol) of CPA was added, but they are still observed after the addition of an AFP. The specific heats of these solutions are close to that of ice at very low temperatures (< or = -100 degrees C) regardless of the additives, but they increase between -100 degrees C and -30 degrees C with the addition of CPAs. The amount of latent heat, which is evaluated with sample weight, generally decreases with the addition of the additives, but can be normalized to approximately 300 J/g based on the weight of water which participates in the phase change. This illustrates that thermal properties, especially latent heat, of a biomaterial should be evaluated based on the understanding of its phase change behavior. The results of the present study are discussed in the context of the implications for cryobiology applications.     

Molar scaling in strepsirrhine primates

We examined how maxillary molar dimensions change with body and skull size estimates among 54 species of living and subfossil strepsirrhine primates. Strepsirrhine maxillary molar areas tend to scale with negative allometry, or possibly isometry, relative to body mass. This observation supports several previous scaling analyses showing that primate molar areas scale at or slightly below geometric similarity relative to body mass. Strepsirrhine molar areas do not change relative to body mass(0.75), as predicted by the metabolic scaling hypothesis. Relative to basicranial length, maxillary molar areas tend to scale with positive allometry. Previous claims that primate molar areas scale with positive allometry relative to body mass appear to rest on the incorrect assumption that skull dimensions scale isometrically with body mass. We identified specific factors that help us to better understand these observed scaling patterns. Lorisiform and lemuriform maxillary molar scaling patterns did not differ significantly, suggesting that the two infraorders had little independent influence on strepsirrhine scaling patterns. Contrary to many previous studies of primate dental allometry, we found little evidence for significant differences in molar area scaling patterns among frugivorous, folivorous, and insectivorous groups. We were able to distinguish folivorous species from frugivorous and insectivorous taxa by comparing M1 lengths and widths. Folivores tend to have a mesiodistally elongated M1 for a given buccolingual M1 width when compared to the other two dietary groups. It has recently been shown that brain mass has a strong influence on primate dental eruption rates. We extended this comparison to relative maxillary molar sizes, but found that brain mass appears to have little influence on the size of strepsirrhine molars. Alternatively, we observed a strong correlation between the relative size of the facial skull and relative molar areas among strepsirrhines. We hypothesize that this association may be underlain by a partial sharing of the patterning of development between molar and facial skull elements.     

Fractal scaling mechanisms in biomembranes

A modified model of the Cohen-Turnbull free volume theory for lateral transport processes in biomembranes is presented. The model which is based on renormalization group theoretical concepts incorporates fractal rather than Markovian diffusion kinetics. It predicts harmonic oscillations in the lateral diffusion coefficient around a dominant power-law trend and clarifies, in addition, recently observed deviations from the Cohen-Turnbull exponential law.     

Metabolic scaling in modular animals

Metabolic scaling is the relationship between organismal metabolic rate and body mass. Understanding the patterns and causes of metabolic scaling provides a powerful foundation for predicting biological processes at the level of individuals, populations, communities, and ecosystems. Despite intense interest in, and debate on, the mechanistic basis of metabolic scaling, relatively little attention has been paid to metabolic scaling in clonal animals with modular construction, such as colonial cnidarians, bryozoans, and colonial ascidians. Unlike unitary animals, modular animals are structural individuals subdivided into repeated morphological units, or modules, each able to acquire, process, and share resources. A modular design allows flexibility in organism size and shape with consequences for metabolic scaling. Furthermore, with careful consideration of the biology of modular animals, the size and shape of individual colonies can be experimentally manipulated to test competing theories pertaining to metabolic scaling. Here, we review metabolic scaling in modular animals and find that a wide range of scaling exponents, rather than a single value, has been reported for a variety of modular animals. We identify factors influencing variation in intraspecific scaling in this group that relate to the general observation that not all modules within a colony are identical. We highlight current gaps in our understanding of metabolic scaling in modular animals, and suggest future research directions, such as manipulating metabolic states and comparisons among species that differ in extent of module integration.     

Dental scaling in the callitrichinae

Callitrichines share several morphological features that appear to be derived among anthropoid primates. One view maintains that some of them are the consequence of a rapid reduction in body size in the common ancestor of callitrichines. This hypothesis predicts that callitrichines should have relatively large teeth for their body size in comparison to other platyrrhines. Dental metric data from 18 platyrrhine species, including 4 callitrichines, is used to test this hypothesis. Callitrichine tooth size is compared both to empirical regressions of tooth size against body weight for noncallitrichine platyrrhines and to a prediction of geometric similarity. In neither comparison do callitrichines as a group show significantly greater tooth size than other platyrrhines. In fact, three of the four genera seem to have relatively small teeth for their body size. While this study fails to support the hypothesis that the common ancestor of callitrichines underwent a rapid reduction in body size, it neither proves nor disproves the hypothesis that they are smaller than their last common ancestor.     

Cryptic individual scaling relationships and the evolution of morphological scaling

Morphological scaling relationships between organ and body size—also known as allometries—describe the shape of a species, and the evolution of such scaling relationships is central to the generation of morphological diversity. Despite extensive modeling and empirical tests, however, the modes of selection that generate changes in scaling remain largely unknown. Here, we mathematically model the evolution of the group‐level scaling as an emergent property of individual‐level variation in the developmental mechanisms that regulate trait and body size. We show that these mechanisms generate a “cryptic individual scaling relationship” unique to each genotype in a population, which determines body and trait size expressed by each individual, depending on developmental nutrition. We find that populations may have identical population‐level allometries but very different underlying patterns of cryptic individual scaling relationships. Consequently, two populations with apparently the same morphological scaling relationship may respond very differently to the same form of selection. By focusing on the developmental mechanisms that regulate trait size and the patterns of cryptic individual scaling relationships they produce, our approach reveals the forms of selection that should be most effective in altering morphological scaling, and directs researcher attention on the actual, hitherto overlooked, targets of selection.     

Thermodynamic redox behavior of the heme centers in A-type heme-copper oxygen reductases: comparison between the two subfamilies

The study of the thermodynamic redox behavior of the hemes from two members of the A family of heme-copper oxygen reductases, Paracoccus denitrificans aa₃ (A1 subfamily) and Rhodothermus marinus caa₃ (A2 subfamily) enzymes, is presented. At different pH values, midpoint reduction potentials and interaction potentials were obtained in the framework of a pairwise model for two interacting redox centers. In both enzymes, the hemes have different reduction potentials. For the A1-type enzyme, it was shown that heme a has a pH-dependent midpoint reduction potential, whereas that of heme a₃ is pH independent. For the A2-type enzyme the opposite was observed. The midpoint reduction potential of heme c from subunit II of the caa₃ enzyme was determined by fitting the data with a single-electron Nernst curve, and it was shown to be pH dependent. The results presented here for these A-type enzymes are compared with those previously obtained for representative members of the B and C families.     

Performance and scaling behavior of bioinformatic applications in virtualization environments to create awareness for the efficient use of compute resources

The large amount of biological data available in the current times, makes it necessary to use tools and applications based on sophisticated and efficient algorithms, developed in the area of bioinformatics. Further, access to high performance computing resources is necessary, to achieve results in reasonable time. To speed up applications and utilize available compute resources as efficient as possible, software developers make use of parallelization mechanisms, like multithreading. Many of the available tools in bioinformatics offer multithreading capabilities, but more compute power is not always helpful. In this study we investigated the behavior of well-known applications in bioinformatics, regarding their performance in the terms of scaling, different virtual environments and different datasets with our benchmarking tool suite BOOTABLE. The tool suite includes the tools BBMap, Bowtie2, BWA, Velvet, IDBA, SPAdes, Clustal Omega, MAFFT, SINA and GROMACS. In addition we added an application using the machine learning framework TensorFlow. Machine learning is not directly part of bioinformatics but applied to many biological problems, especially in the context of medical images (X-ray photographs). The mentioned tools have been analyzed in two different virtual environments, a virtual machine environment based on the OpenStack cloud software and in a Docker environment. The gained performance values were compared to a bare-metal setup and among each other. The study reveals, that the used virtual environments produce an overhead in the range of seven to twenty-five percent compared to the bare-metal environment. The scaling measurements showed, that some of the analyzed tools do not benefit from using larger amounts of computing resources, whereas others showed an almost linear scaling behavior. The findings of this study have been generalized as far as possible and should help users to find the best amount of resources for their analysis. Further, the results provide valuable information for resource providers to handle their resources as efficiently as possible and raise the user community’s awareness of the efficient usage of computing resources.     

Allometric scaling in animals and plants

In this paper we give a derivation for the allometric scaling relation between the metabolic rate and the mass of animals and plants. We show that the characteristic scaling exponent of 3/4 occurring in this relation is a result of the distribution of sources and sinks within the living organism. We further introduce a principle of least mass and discuss the kind of flows that arise from it.     

Thermodynamic redox behavior of the heme centers of cbb3 heme-copper oxygen reductase from Bradyrhizobium japonicum

A comprehensive study of the thermodynamic redox behavior of the hemes from the cbb3 oxygen reductase from Bradyrhizobium japonicum was performed. This enzyme is a member of the C-type heme-copper oxygen reductase superfamily and has three subunits with six redox centers: four low-spin hemes and a high-spin heme and one copper ion, composing the site where oxygen is reduced. In this analysis, the visible spectra and redox properties of the five heme centers were deconvoluted. Their redox profiles and the pH dependence of the midpoint reduction potentials (redox-Bohr effect) were investigated. The reference reduction potentials (defined for a state where all centers are reduced) and homotropic interaction potentials were determined in the framework of a model of pairwise interacting redox centers. At pH 7.7, the reference reduction potentials for the three hemes c are 390, 300, and 220 mV, with low interaction potentials between them, weaker than -15 mV. For hemes b and b3, reference reduction potentials of 375 and 290 mV, respectively, were obtained; these two redox centers show an interaction potential weaker than -60 mV. The midpoint reduction potentials of all five hemes are pH-dependent. The study of these thermodynamic parameters is important in understanding the coupling mechanism of the redox and chemical processes during oxygen reduction. The analysis of the thermodynamic redox behavior of the cbb3 oxygen reductase contributes to the investigation of the mechanism of electron transfer and proton translocation by heme-copper oxygen reductases in general and indicates a thermodynamic coupling for the electron and proton transfer mechanisms.