Negentropy and the evolution of chemical recruitment in ants (Hymenoptera: Formicidae)

The applicability of the concept of negentropy to the study of evolution is tested by tracing the phylogeny of the information content of the communication systems used for recruitment in the Formicidae. Data from the literature is reviewed and ordered around theoretical evolutionary routes based on increasing negentropy of the chemical communication systems used. One pathway presupposes the development of chemical orientation prior to chemical attraction, i.e. signalling the presence of food; whereas the others begin with the chemical attraction of nestmates without orientation with chemical cues to the food. The results suggest that the Myrmicinae, Ponerinae, Dolichoderinae, Pseudomyrmycinae and possibly Dorylinae evolved chemical recruitment via chemical attraction, whereas the Formicinae evolved chemical recruitment via chemical orientation. These alternative patterns permit the establishment of phyletic trends based on glandular evolution for chemical recruitment. The results are compared with phylogenetic studies based on morphological and chemical characters, and it emerges that the recruitment behaviour proves to be a particularly conservative characteristic, in that it is evident in the same form in a wider range of species. The conclusion is reached that the negentropy content of living systems is a powerful tool in phylogenetic studies, even of small taxonomic groups.     

Chemical variability of the volatile metabolites from the Caribbean corals of the genus Gorgonia

The chemical composition of the investigated gorgonians showed a high level of individual variation and the colonies, according to their major contributors, were assigned to 10 distinct chemical profiles, among which A, C, E, and G were the most abundant ones. From the metabolites identified in the present study, either by means of GC/MS or using NMR techniques after conventional separation procedures, the novel cyclic ether 5,10-epoxymuurolane is found in significant quantities in D and I chemical profiles. Furanotriene, isofuranotriene and furanodiene could be referred as the most common metabolites of the genus, since they are found in 6 out of 10 chemical profiles. Isosericenine is, also, a significant contributor of H and I chemical profiles. A number of sesquiterpene hydrocarbons, such as curzerene, bicyclogermacrene, valencene, beta-bourbonene and beta-elemene, along with the oxygenated sesquiterpenes elemanolide and furoventalene, are present at varying concentrations in the majority of the chemical profiles. Metabolites of high discriminant value are: alpha-himachalene for the K chemical profile, alpha-santalene and its oxygenated derivatives for the G chemical profile and the three geometrical isomers of germacrone for the F chemical profile. Several chemical profiles showed narrow geographic distribution. Most of the chemical profiles are located in the north, while F inhabits mainly southern sites and the others are equally distributed. Finally, 91% of the chemical profiles of the gorgonian colonies appeared to grow in all depths, while 9% did not inhabit deep-water environments. Most chemical profiles are less frequent at higher water depths with the exception of chemical profiles A and C.     

Random coil chemical shift for intrinsically disordered proteins: effects of temperature and pH

Secondary chemical shift analysis is the main NMR method for detection of transiently formed secondary structure in intrinsically disordered proteins. The quality of the secondary chemical shifts is dependent on an appropriate choice of random coil chemical shifts. We report random coil chemical shifts and sequence correction factors determined for a GGXGG peptide series following the approach of Schwarzinger et al. (J Am Chem Soc 123(13):2970–2978, 2001). The chemical shifts are determined at neutral pH in order to match the conditions of most studies of intrinsically disordered proteins. Temperature has a non-negligible effect on the ¹³C random coil chemical shifts, so temperature coefficients are reported for the random coil chemical shifts to allow extrapolation to other temperatures. The pH dependence of the histidine random coil chemical shifts is investigated in a titration series, which allows the accurate random coil chemical shifts to be obtained at any pH. By correcting the random coil chemical shifts for the effects of temperature and pH, systematic biases of the secondary chemical shifts are minimized, which will improve the reliability of detection of transient secondary structure in disordered proteins.     

植物-微生物联合修复化学农药污染土壤的研究进展

化学农药的高毒性、生物积累性和扩散性极易对环境及人类健康造成危害,环境中化学农药的去除尤为重要。植物-微生物联合修复技术因其高效、环境友好和修复成本低等优点受到越来越多的关注,植物-微生物联合修复化学农药污染土壤是一种很有前景的方法。植物为根际和内生细菌提供养分,而细菌通过化学农药的降解和解毒来支持植物生长。本文综述了影响化学农药在植物体内吸收和转运的因素以及植物-微生物修复技术的原理,并讨论了植物与微生物在化学农药污染土壤修复中的协同效应,并对植物-微生物联合修复法在化学农药污染土壤修复中的应用前景进行了展望。     

PPM: a side-chain and backbone chemical shift predictor for the assessment of protein conformational ensembles

The combination of the wide availability of protein backbone and side-chain NMR chemical shifts with advances in understanding of their relationship to protein structure makes these parameters useful for the assessment of structural-dynamic protein models. A new chemical shift predictor (PPM) is introduced, which is solely based on physical?Cchemical contributions to the chemical shifts for both the protein backbone and methyl-bearing amino-acid side chains. To explicitly account for the effects of protein dynamics on chemical shifts, PPM was directly refined against 100?ns long molecular dynamics (MD) simulations of 35 proteins with known experimental NMR chemical shifts. It is found that the prediction of methyl-proton chemical shifts by PPM from MD ensembles is improved over other methods, while backbone C??, C??, C??, N, and H^N chemical shifts are predicted at an accuracy comparable to the latest generation of chemical shift prediction programs. PPM is particularly suitable for the rapid evaluation of large protein conformational ensembles on their consistency with experimental NMR data and the possible improvement of protein force fields from chemical shifts.     

昆虫的化学感觉机理

昆虫是通过化学感觉器与其周围环境中的大量化学信息发生联系的。通过特定的化学感觉机制 ,昆虫可感知来自种内和种间 ,以及无机环境中的各种化学信息 ,并由此而作出相应的行为反应 ,从而为其自身寻找适宜的食物、配偶以及生存与繁殖场所 (如躲避天敌、避免或减少竞争等等 ) ,达到最大的繁殖成功。阐明昆虫的化学感觉机理 ,不仅可在理论上进一步加深对昆虫与植物、昆虫与昆虫相互关系的了解 ,而且可在实践上为开发害虫治理的新途径提供理论指导。本文将根据目前的最新研究成果 ,主要就昆虫的化学感觉机理 ,包括嗅觉和味觉机理作一综述 ,以期…     

DGGE analysis of 16S rDNA of ammonia-oxidizing bacteria in chemical–biological flocculation and chemical coagulation systems

Microbial community DNA was extracted from activated sludge samples taken from a chemical bioflocculation process and a chemical coagulation process in Shanghai, China. 16S rDNA of ammonia-oxidizing bacteria (AOB)was amplified by nested polymerase chain reaction and fingerprinted by denaturing gradient gel electrophoresis for microbial structure analysis. The Shannon diversity index of each sample was determined. The results indicated that the microbial structure of AOB in chemical bioflocculation process was comparable at two operational conditions. The ammonia-oxidizing bacterial communities were similar in three channels of the chemical bioflocculation process and in three serial tanks in the chemical coagulation process at the same condition. The diversity of microbial structures in the chemical bioflocculation process was higher than in the chemical coagulation process, in which the microbial structure was similar to that in the influent. Although the microbial study provides insights to the nitrification removal, higher microbial diversity of AOB does not necessarily mean higher ammonia oxidization. Molecular analysis should be combined with chemical assays to optimize operational conditions.     

Chemical signaling processes in the marine environment

Understanding the mechanisms by which environmental chemical signals, chemical defenses, and other chemical agents mediate various life-history processes can lead to important insights about the forces driving the ecology and evolution of marine systems. For chemical signals released into the environment, establishing the principles that mediate chemical production and transport is critical for interpreting biological responses to these stimuli within appropriate natural, historical contexts. Recent technological advancements provide outstanding opportunities for new discoveries, thus allowing quantification of interactions between hydrodynamic, chemical, and biological factors at numerous spatial and temporal scales. Past work on chemically mediated processes involving organisms and their environment have emphasized habitat colonization by larvae and trophic relationships. Future research priorities should include these topics as well as courtship and mating, fertilization, competition, symbiosis, and microbial chemical ecology. There are now vast new opportunities for determining how organisms respond to chemical signals and employ chemical defenses under environmentally realistic conditions. Integrating these findings within a larger ecological and evolutionary framework should lead to improved understanding of natural physicochemical phenomena that constrain biological responses at the individual, population, and community levels of organization.     

Nearest-neighbor effects on backbone alpha and beta carbon chemical shifts in proteins

We present a method for analyzing the chemical shift database to yield information on nearest-neighbor effects on carbon-13 chemical shift values for alpha and beta carbons of amino acids in proteins. For each amino acid sequence XYZ, we define two correction factors, Delta(XY) s and Delta(YZ) s , representing the effects on (delta13 Calpha-delta13 Cbeta) for residue Y from the preceding residue (X) and the following residue (Z), where X, Y, and Z represent one of the 20 naturally occurring amino acids, Delta designates the change in value or the correction factor (in ppm), and s is an index standing for one of three "pseudo secondary structure states" derived from chemical shift dispersions, which we show represent residues in primarily alpha-helix, beta-strand, and non-alphabeta(coil). The correction factors were obtained from maximum likelihood fitting of (delta13 Calpha-delta13 Cbeta) values from the chemical shifts of 651 proteins to a mixture of three Gaussians. These correction factors were derived strictly from the analysis of assigned chemical shifts, without regard to the three-dimensional structures of these proteins. The corrections factors were found to differ according to the secondary structural environment of the central residue (deduced from the chemical shift distribution) as well as by different identities of the nearest neighboring residues in the sequence. The areas subsumed by the sequence-dependent chemical shift distributions report on the relative energies of the sequences in different pseudo secondary structural environments, and the positions of the peaks indicate the chemical shifts of lowest energy conformations. As such, these results have potential applications to the determination of dihedral angle restraints from chemical shifts for structure determination and to more accurate predictions of chemical shifts in proteins of known structure. From a database of chemical shifts associated well-defined three-dimensional structures, comparisons were made between DSSP designations derived from three-dimensional structure and pseudo secondary structure designations derived from nearest-neighbor corrected chemical shift analysis. The high level of agreement between the two approaches to classifying secondary structure provides a measure of confidence in this chemical shift-based approach to the analysis of protein structure.     

Relationship between nuclear magnetic resonance chemical shift and protein secondary structure

An analysis of the 1H nuclear magnetic resonance chemical shift assignments and secondary structure designations for over 70 proteins has revealed some very strong and unexpected relationships. Similar studies, performed on smaller databases, for 13C and 15N chemical shifts reveal equally strong correlations to protein secondary structure. Among the more interesting results to emerge from this work is the finding that all 20 naturally occurring amino acids experience a mean alpha-1H upfield shift of 0.39 parts per million (from the random coil value) when placed in a helical configuration. In a like manner, the alpha-1H chemical shift is found to move downfield by an average of 0.37 parts per million when the residue is placed in a beta-strand or extended configuration. Similar changes are also found for amide 1H, carbonyl 13C, alpha-13C and amide 15N chemical shifts. Other relationships between chemical shift and protein conformation are also uncovered; in particular, a correlation between helix dipole effects and amide proton chemical shifts as well as a relationship between alpha-proton chemical shifts and main-chain flexibility. Additionally, useful relationships between alpha-proton chemical shifts and backbone dihedral angles as well as correlations between amide proton chemical shifts and hydrogen bond effects are demonstrated.     

What should and what can biotechnology contribute to chemical bulk production?

Abstract: In terms of the chemical industry most biotech products have a fine chemical or even speciality character. Nevertheless there is at least one striking example of a fermentation-derived bulk chemical, bio-ethanol, which provides an excellent case study of the economic and technological prerequisites which biotechnology has to attain as a supplier to the chemical marketplace. The competitive position of existing and new products produced from renewable resources through biotechnological conversion methods will depend on its market acceptance - overall environmental compatibility and cost performance. In order to provide significant contributions to chemical bulk production beyond 2000, biotechnologists and chemical engineers are requested to search for new products, new processes to existing products and new technologies to overcome present cost constraints in fermentation, bioconversion and downstream processing.     

Field programmable chemistry: integrated chemical and electronic processing of informational molecules towards electronic chemical cells

The topic addressed is that of combining self-constructing chemical systems with electronic computation to form unconventional embedded computation systems performing complex nano-scale chemical tasks autonomously. The hybrid route to complex programmable chemistry, and ultimately to artificial cells based on novel chemistry, requires a solution of the two-way massively parallel coupling problem between digital electronics and chemical systems. We present a chemical microprocessor technology and show how it can provide a generic programmable platform for complex molecular processing tasks in Field Programmable Chemistry, including steps towards the grand challenge of constructing the first electronic chemical cells. Field programmable chemistry employs a massively parallel field of electrodes, under the control of latched voltages, which are used to modulate chemical activity. We implement such a field programmable chemistry which links to chemistry in rather generic, two-phase microfluidic channel networks that are separated into weakly coupled domains. Electric fields, produced by the high-density array of electrodes embedded in the channel floors, are used to control the transport of chemicals across the hydrodynamic barriers separating domains. In the absence of electric fields, separate microfluidic domains are essentially independent with only slow diffusional interchange of chemicals. Electronic chemical cells, based on chemical microprocessors, exploit a spatially resolved sandwich structure in which the electronic and chemical systems are locally coupled through homogeneous fine-grained actuation and sensor networks and play symmetric and complementary roles. We describe how these systems are fabricated, experimentally test their basic functionality, simulate their potential (e.g. for feed forward digital electrophoretic (FFDE) separation) and outline the application to building electronic chemical cells.     

Chemical States of Bacterial Spores: Dry-Heat Resistance

Mature bacterial spores can be manipulated by chemical pretreatments between states sensitive and resistant to dry heat. The two chemical forms of the spore differ in dry-heat resistance by about an order of magnitude. Log survivor curves for each chemical state were approximately straight lines. The temperature dependence of dry-heat resistance for each chemical state was similar to that usually found for dry-heat resistance. A method of testing spore resistance to dry heat has been designed to minimize artifacts resulting from (i) change of chemical state during the test, (ii) effects of water vapor activity, (iii) incomplete recovery of spores from the test container and clumping of spores. Implications of the existence of different chemical resistance states for experimental strategy and testing of dry-heat resistance are discussed.     

De novo protein structure generation from incomplete chemical shift assignments

NMR chemical shifts provide important local structural information for proteins. Consistent structure generation from NMR chemical shift data has recently become feasible for proteins with sizes of up to 130 residues, and such structures are of a quality comparable to those obtained with the standard NMR protocol. This study investigates the influence of the completeness of chemical shift assignments on structures generated from chemical shifts. The Chemical-Shift-Rosetta (CS-Rosetta) protocol was used for de novo protein structure generation with various degrees of completeness of the chemical shift assignment, simulated by omission of entries in the experimental chemical shift data previously used for the initial demonstration of the CS-Rosetta approach. In addition, a new CS-Rosetta protocol is described that improves robustness of the method for proteins with missing or erroneous NMR chemical shift input data. This strategy, which uses traditional Rosetta for pre-filtering of the fragment selection process, is demonstrated for two paramagnetic proteins and also for two proteins with solid-state NMR chemical shift assignments. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Systemtheoretische analyse der chemischen atmungsregulation unter berücksichtigung ihres mehrdimensionalen charakters

The chemical control of respiration provides for the maintanence of energy and substance equilibrium primarily and for the homoeostatic stability of the chemical blood parameters secondarily. Based on results having been obtained from an appropriate state space model some findings on respiration can be reproduced. In addition to the true qualitative reflecting the steady state at work performance, the contribute of separate chemical drives to the whole ventilation are represented correctly, suggesting the unnecessarity of any additional specific work drives. Nervous influences of ventilation besides of its chemical control are not suitable to guarantee its controlability, they represent only disturbaces mobilizing it. Coupled organ systems take part on transmitting primary afferent infromation about the chemical condition of the total metabolism, which proved to be necessary and sufficient for the chemical control activity.     

植物种间和种内的化学作用

植物间相互作用是生态学基础科学问题之一,植物能感受和识别共存同种或异种植物,进而调整生长、繁殖和防御策略。植物种间和种内的感受和识别大多是由植物产生释放的次生物质所介导,这类化学识别通讯可以启动相应的植物化感作用机制。近年发现,植物亲属间也存在着化学识别、地下根系通讯调控地上开花繁殖等植物种间和种内的化学作用关系。目前植物通过地上挥发物介导的植物化学作用已基本澄清,但根分泌物介导的植物地下化学作用机制及其信号物质还所知甚少。地下化学作用不仅决定根系侵入(接近)和躲避(排斥)行为,也能调控地上开花时间和花期。这样,植物间的化学作用还涉及植物地下和地上的协调互作。本文以植物化感作用和植物化学识别通讯及相应的化感物质和信号物质为基点,从植物亲属识别、根系化学识别和行为模式、地下化学作用调控地上开花繁殖3个方面综述植物种间和种内化学作用的研究进展,为全面理解植物间相互作用提供新视野。     

Watershed ‘chemical cocktails’: forming novel elemental combinations in Anthropocene fresh waters

In the Anthropocene, watershed chemical transport is increasingly dominated by novel combinations of elements, which are hydrologically linked together as ‘chemical cocktails.’ Chemical cocktails are novel because human activities greatly enhance elemental concentrations and their probability for biogeochemical interactions and shared transport along hydrologic flowpaths. A new chemical cocktail approach advances our ability to: trace contaminant mixtures in watersheds, develop chemical proxies with high-resolution sensor data, and manage multiple water quality problems. We explore the following questions: (1) Can we classify elemental transport in watersheds as chemical cocktails using a new approach? (2) What is the role of climate and land use in enhancing the formation and transport of chemical cocktails in watersheds? To address these questions, we first analyze trends in concentrations of carbon, nutrients, metals, and salts in fresh waters over 100 years. Next, we explore how climate and land use enhance the probability of formation of chemical cocktails of carbon, nutrients, metals, and salts. Ultimately, we classify transport of chemical cocktails based on solubility, mobility, reactivity, and dominant phases: (1) sieved chemical cocktails (e.g., particulate forms of nutrients, metals and organic matter); (2) filtered chemical cocktails (e.g., dissolved organic matter and associated metal complexes); (3) chromatographic chemical cocktails (e.g., ions eluted from soil exchange sites); and (4) reactive chemical cocktails (e.g., limiting nutrients and redox sensitive elements). Typically, contaminants are regulated and managed one element at a time, even though combinations of elements interact to influence many water quality problems such as toxicity to life, eutrophication, infrastructure corrosion, and water treatment. A chemical cocktail approach significantly expands evaluations of water quality signatures and impacts beyond single elements to mixtures. High-frequency sensor data (pH, specific conductance, turbidity, etc.) can serve as proxies for chemical cocktails and improve real-time analyses of water quality violations, identify regulatory needs, and track water quality recovery following storms and extreme climate events. Ultimately, a watershed chemical cocktail approach is necessary for effectively co-managing groups of contaminants and provides a more holistic approach for studying, monitoring, and managing water quality in the Anthropocene.     

A probabilistic model for secondary structure prediction from protein chemical shifts

Protein chemical shifts encode detailed structural information that is difficult and computationally costly to describe at a fundamental level. Statistical and machine learning approaches have been used to infer correlations between chemical shifts and secondary structure from experimental chemical shifts. These methods range from simple statistics such as the chemical shift index to complex methods using neural networks. Notwithstanding their higher accuracy, more complex approaches tend to obscure the relationship between secondary structure and chemical shift and often involve many parameters that need to be trained. We present hidden Markov models (HMMs) with Gaussian emission probabilities to model the dependence between protein chemical shifts and secondary structure. The continuous emission probabilities are modeled as conditional probabilities for a given amino acid and secondary structure type. Using these distributions as outputs of first‐ and second‐order HMMs, we achieve a prediction accuracy of 82.3%, which is competitive with existing methods for predicting secondary structure from protein chemical shifts. Incorporation of sequence‐based secondary structure prediction into our HMM improves the prediction accuracy to 84.0%. Our findings suggest that an HMM with correlated Gaussian distributions conditioned on the secondary structure provides an adequate generative model of chemical shifts. Proteins 2013; © 2012 Wiley Periodicals, Inc.     

Heavy metal accumulation of Danube river aquatic plants — indication of chemical contamination

In this paper, the ecological status of a section of the Danube River flowing through Serbia from Bezdan to Djerdap was evalutated. Using the chemical composition of water, sediment samples from the littoral zone and dominant aquatic macrophytes, the level of chemical pollution was ascertained. Chemical analyses of the water and sediment indicated that the tributaries flowing into the Danube significantly influenced the chemical load of the water and as a direct consequence, the sediment. The concentration of heavy metals including Cu, Mn and Cd found in plants of the Potamogeton genus, further indicated significant chemical pollution, establishing a clear link between the chemical composition of plant tissues and the chemical composition of water and sediment. This paper therefore describes how the chemical composition of aquatic plants can be used as a reliable indicator for heavy metal pollution of aquatic ecosystems.