Metabolic flux analysis and metabolic engineering of microorganisms

Recent advances in metabolic flux analysis including genome-scale constraints-based flux analysis and its applications in metabolic engineering are reviewed. Various computational aspects of constraints-based flux analysis including genome-scale stoichiometric models, additional constraints used for the improved accuracy, and several algorithms for identifying the target genes to be manipulated are described. Also, some of the successful applications of metabolic flux analysis in metabolic engineering are reviewed. Finally, we discuss the limitations that need to be overcome to make the results of genome-scale flux analysis more realistically represent the real cell metabolism.     

Pathway-based Analysis Tools for Complex Diseases:A Review

Genetic studies are traditionally based on single-gene analysis. The use of these analyses can pose tremendous challenges for elucidating complicated genetic interplays involved in complex human diseases. Modern pathway-based analysis provides a technique, which allows a comprehen- sive understanding of the molecular mechanisms underlying complex diseases. Extensive studies uti- lizing the methods and applications for pathway-based analysis have significantly advanced our capacity to explore large-scale omics data, which has rapidly accumulated in biomedical fields. This article is a comprehensive review of the pathway-based analysis methods the powerful methods with the potential to uncover the biological depths of the complex diseases. The general concepts and procedures for the pathway-based analysis methods are introduced and then, a comprehensive review of the major approaches for this analysis is presented. In addition, a list of available path- way-based analysis software and databases is provided. Finally, future directions and challenges for the methodological development and applications of pathway-based analysis techniques are dis- cussed. This review will provide a useful guide to dissect complex diseases.     

On the Three-Taxon Approach to Parsimony Analysis

The following three basic defects for which three-taxon analysis has been rejected as a method for biological systematics are reviewed: (1) character evolution is a priori assumed to be irreversible; (2) basic statements that are not logically independent are treated as if they are; (3) three-taxon statements that are considered as independent support for a given tree may be mutually exclusive on that tree. It is argued that these criticisms only relate to the particular way the three-taxon approach was originally implemented. Four-taxon analysis, an alternative implementation that circumvents these problems, is derived. Four-taxon analysis is identical to standard parsimony analysis except for an unnatural restriction on the maximum amount of homoplasy that may be concentrated in a single character state. This restriction follows directly from the basic tenet of the three-taxon approach, that character state distributions should be decomposed into basic statements that are, in themselves, still informative with respect to relationships. A reconsideration of what constitutes an elementary relevant statement in systematics leads to a reformulation of standard parsimony as two-taxon analysis and to a rejection of four-taxon analysis as a method for biological systematics.     

The state of the art in the analysis of two-dimensional gel electrophoresis images

Software-based image analysis is a crucial step in the biological interpretation of two-dimensional gel electrophoresis experiments. Recent significant advances in image processing methods combined with powerful computing hardware have enabled the routine analysis of large experiments. We cover the process starting with the imaging of 2-D gels, quantitation of spots, creation of expression profiles to statistical expression analysis followed by the presentation of results. Challenges for analysis software as well as good practices are highlighted. We emphasize image warping and related methods that are able to overcome the difficulties that are due to varying migration positions of spots between gels. Spot detection, quantitation, normalization, and the creation of expression profiles are described in detail. The recent development of consensus spot patterns and complete expression profiles enables one to take full advantage of statistical methods for expression analysis that are well established for the analysis of DNA microarray experiments. We close with an overview of visualization and presentation methods (proteome maps) and current challenges in the field. An erratum to this article can be found at     

群落二维格局分析的两种方法

群落二维空间格局研究能够更好地揭示群落的特征,但在分析方法上有较大的困难。用垂直相交的两条样带在两个方向上同时取样的二维取样法,获得数据,用DCA排序与格局分析相结合的方法,得到群落不同格局规模斑块的长、宽及面积,实现二维格局研究。在亚高山草甸群落格局研究中应用表明,两个方法均是有效的。     

Application of capillary isotachophoresis in peptide analysis

This paper gives a broad and detailed review of the applications of one of the modern high-performance electromigration separation techniques — capillary isotachophoresis (ITP) — in peptide analysis. Examples are presented of the utilization of capillary ITP for peptide analysis in the fields of chemistry, general and clinical biochemistry, biology, biotechnology, pharmacy and the food industry. The complete composition of all the electrolyte systems used for peptide ITP analyses in both cationic and anionic techniques is given in tabular form. According to the purpose of analysis the applications are divided into several sections: model studies, determination of physico-chemical characteristics, purity control of both intermediate and final peptide preparations, including the determination of low-molecular-mass ionogenic admixtures, and the analysis of peptides in biological fluids and tissue extracts. In addition to the main applications the theoretical and methodological aspects of peptide ITP analysis are discussed. The basic electromigration properties of peptides (their polyampholyte character, effective and absolute mobilities, acid—base equilibria) are explained and the selection of parameters for peptide ITP analysis is described in detail. The advantages and disadvantages of ITP compared with other electrophoretic and chromatographic methods used for peptide analysis are discussed.     

Challenges and opportunities in proteomics data analysis

Accurate, consistent, and transparent data processing and analysis are integral and critical parts of proteomics workflows in general and for biomarker discovery in particular. Definition of common standards for data representation and analysis and the creation of data repositories are essential to compare, exchange, and share data within the community. Current issues in data processing, analysis, and validation are discussed together with opportunities for improving the process in the future and for defining alternative workflows.     

生物信息学在基因芯片中的应用

生物信息学和基因芯片是生命科学研究领域中的两种新方法和新技术,生物信息学与基因芯片密切相关,生物信息学促进了基因芯片的研究与应用,而基因芯片则丰富了生物信息学的研究内容。本论文探讨生物信息学在基因芯片中的应用,将生物信息学方法运用到高密度基因芯片设计和芯片实验数据管理及分析。从信息学的角度提出基因芯片设计准则,提出寡核苷酸探针的优化设计方法,将该方法运用于再测序型芯片和基因表达型芯片的设计,在此基础上研制出高密度基因芯片设计软件系统和实验结果分析系统。     

Principles for Griffing's combining ability analysis

Griffing's diallel analysis is used in plant improvement programs to identify superior parents for crossing and for characterizing general, specific, and reciprocal effects. Eight different model/method combinations are commonly used in the analysis. The accuracy of the analysis is improved by using the appropriate model and method. In many instances, Model One with Method Three or Four is the most appropriate for obtaining unbiased estimates of combining abilities and gene action. The effective use of Griffing's analysis and the influence of several factors on this analysis are discussed. A personal computer program on this analysis is also made available to interested readers.     

Simple outlier detection for a multi-environmental field trial

The aim of plant breeding trials is often to identify crop variety that are well adapt to target environments. These varieties are identified through genomic prediction from the analysis of multi-environmental field trial (MET) using linear mixed models. The occurrence of outliers in MET is common and known to adversely impact the accuracy of genomic prediction yet the detection of outliers are often neglected. A number of reasons stand for this—first, complex data such as a MET give rise to distinct levels of residuals (eg, at a trial level or individual observation level). This complexity offers additional challenges for an outlier detection method. Second, many linear mixed model software packages that cater for complex variance structures needed in the analysis of MET are not well streamlined for diagnostics by practitioners. We demonstrate outlier detection methods that are simple to implement in any linear mixed model software packages and computationally fast. Although these methods are not optimal methods in outlier detection, they offer practical value for ease of application in the analysis pipeline of regularly collected data. These are demonstrated using simulation based on two real bread wheat yield METs. In particular, models that consider analysis of yield trials either independently or jointly (thus borrowing strength across trials) are considered. Case studies are presented to highlight benefit of joint analysis for outlier detection.     

芦芽山亚高山草甸优势种群和群落的二维格局分析

种群和群落的二维空间格局研究能够更好地揭示群落的空间和结构特征,但在分析方法上有较大的困难。用垂直相交的两条样带在两个方向上同时取样的二维取样法,获得数据,用一维格局分析方法分别分析,可以得到各个种不同格局规模斑块的长、宽及面积,实现二维格局研究。用DCA排序和格局分析方法相结合,可以完成群落的二维格局分析。在山西芦芽山亚高山草甸应用的结果表明这样的垂直样带二维取样及分析方法较好地反映了种群和群落的空间特性,是非常有效的,并且该方法简单易做,具有较大的可操作性。所研究的草甸主要优势种格局斑块的形状比较规则,面积也较大。次要种斑块多为不规则形,面积也较小。群落格局与主要优势种的格局关系密切。     

Dimensional analysis in mathematical biology I. General discussion

Dimensional analysis is discussed from the viewpoint of its basic group properties and shown to be an algebraic Abelian group that is useful for analysis of physical measurements. The application of the method to various types of equations and the formulation of previously unclassified dimensions are discussed. Functional dimensional analysis is applied to the problems of cell size and biomass proliferation; future applications are also noted. A number of dimensionless terms have been formulated for cellular physiochemical phenomena. They apparently represent the first systematic study of biological dimensionless numbers recorded in the literature. A dimensionless proliferation law is suggested. A brief analysis of the physical dimensionality associated with information measures is carried out. Entropy and “information” are shown to be completely different in their dimensional meaning; other informational measures of possible interest in biology are proposed. The dimensional coding and computor analysis of biomathematical equations is suggested.     

Global genetic analysis

The introduction of molecular markers in genetic analysis has revolutionized medicine. These molecular markers are genetic variations associated with a predisposition to common diseases and individual variations in drug responses. Identification and genotyping a vast number of genetic polymorphisms in large populations are increasingly important for disease gene identification, pharmacogenetics and population-based studies. Among variations being analyzed, single nucleotide polymorphisms seem to be most useful in large-scale genetic analysis. This review discusses approaches for genetic analysis, use of different markers, and emerging technologies for large-scale genetic analysis where millions of genotyping need to be performed.     

Association dynamics and lateral transport in biological membranes

A theoretical analysis is presented for the interrelated effects of lateral diffusion and a simple form of molecular association (A + B ? C) in biological membranes. Expressions are derived for the characteristic functions measured in fluorescence redistribution after photobleaching experiments, corresponding to both the Fourier transform analysis of concentration in a plane and the normal mode analysis for a spherical surface. The results are related to the reputed binding of integral membrane proteins to submembranous cytoskeletal elements.     

Synchrotron radiation for direct analysis of metalloproteins on electrophoresis gels

Metalloproteomics requires analytical techniques able to assess and quantify the inorganic species in metalloproteins. The most widely used methods are hyphenated techniques, based on the coupling of a high resolution chromatographic method with a high sensitivity method for metal analysis in solution. An alternative approach is the use of methods for solid sample analysis, combining metalloprotein separation by gel electrophoresis and direct analysis of the gels. Direct methods are based on beam analysis, such as lasers, ion beams or synchrotron radiation beams. The aim of this review article is to present the main features of synchrotron radiation based methods and their applications for metalloprotein analysis directly on electrophoresis gels. Synchrotron radiation X-ray fluorescence has been successfully employed for sensitive metal identification, and X-ray absorption spectroscopy for metal local structure speciation in proteins. Synchrotron based methods will be compared to ion beam and mass spectrometry for direct analysis of metalloproteins in electrophoresis gels.     

Standardisation of DNA quantitation by image analysis: quality control of instrumentation.

BACKGROUND: DNA image analysis is frequently performed in clinical practice as a prognostic tool and to improve diagnosis. The precision of prognosis and diagnosis depends on the accuracy of analysis and particularly on the quality of image analysis systems. It has been reported that image analysis systems used for DNA quantification differ widely in their characteristics (Thunissen et al.: Cytometry 27: 21-25, 1997). This induces inter-laboratory variations when the same sample is analysed in different laboratories. In microscopic image analysis, the principal instrumentation errors arise from the optical and electronic parts of systems. They bring about problems of instability, non-linearity, and shading and glare phenomena. METHODS: The aim of this study is to establish tools and standardised quality control procedures for microscopic image analysis systems. Specific reference standard slides have been developed to control instability, non-linearity, shading and glare phenomena and segmentation efficiency. RESULTS: Some systems have been controlled with these tools and these quality control procedures. Interpretation criteria and accuracy limits of these quality control procedures are proposed according to the conclusions of a European project called PRESS project (Prototype Reference Standard Slide). Beyond these limits, tested image analysis systems are not qualified to realise precise DNA analysis. CONCLUSIONS: The different procedures presented in this work determine if an image analysis system is qualified to deliver sufficiently precise DNA measurements for cancer case analysis. If the controlled systems are beyond the defined limits, some recommendations are given to find a solution to the problem.     

Topological analysis of binary tree structures when occasional multifurcations occur

The occurrence of multifurcations in essentially binary trees is investigated with respect to two methods for testing growth models,viz. subtree partition analysis and vertex analysis. It is shown that under certain conditions multifurcations may be incorporated in the analysis. Although the conditions are more restrictive for subtree partition analysis only minor loss of information occurs if forbidden multifurcations are simply ignored.     

Analysis of Polymerase Chain Reaction-Amplified DNA Products by Mass Spectrometry Using Matrix-Assisted Laser Desorption and Electrospray: Current Status

Recent advances in molecular biology are making it possible to diagnose genetic diseases and identify pathogens through the analysis of DNA. As clinical applications for molecular diagnosis increase, rapid, reliable methods for determination of DNA size will be needed. Mass spectrometry offers the potential of analyzing amplified DNA quickly and reliably, without the need for gel-based separation and sample labeling steps that are conventionally employed. Both electrospray ionization and matrix-assisted laser desorption/ionization have been evaluated for the size analysis of DNA using both synthetic oligonucleotides and PCR-amplified samples corresponding to bases 1626 to 1701 of the cystic fibrosis transmembrane conductance regulator gene. Both technologies have been demonstrated to have mass range and sensitivity required for the analysis of PCR-amplified DNA in this size range using minimal sample preparation. Steps required to incorporate either ionization technique into a reliable analytical scheme for the rapid, routine analysis of DNA are outlined.     

Adapting lacunarity techniques for gradient-based analyses of landscape surfaces

Typically, landscapes are modeled in the form of categorical map patterns, i.e. as mosaics made up of basic elements which are presumed to possess sharp and well-defined boundary lines. Many landscape ecological concepts are based upon this perception. In reality, however, the spatial value progressions of environmental parameters tend to be “gradual” rather than “abrupt”. Therefore, gradient approaches have shifted to the forefront of scientific interest recently. Appropriate methods are needed for the implementation of such approaches. Lacunarity analysis may provide a suitable starting point in this context. We propose adapted versions of standard lacunarity techniques for analyzing ecological gradients in general and the heterogeneity of physical landscape surfaces in particular. A simple way of customizing lacunarity analysis for quantifying the heterogeneity of digital elevation models is to use the value range for defining the box mass used in the calculation process. Furthermore, we demonstrate how lacunarity analysis can be combined with metrics derived from surface metrology, such as the “Average Surface Roughness”. Finally, the “classical” lacunarity approach is used in combination with simple landform indices. The methods are tested using different data sets, including high-resolution digital elevation models. In summary, lacunarity analysis is adopted in order to establish a gradient-based approach for terrain analysis and proves to be a valuable concept for comparing three-dimensional surface patterns in terms of their degree of “heterogeneity”. The proposed developments are meant to serve as a stimulus for making increased use of this simple but effective technique in landscape ecology. They offer a large potential for expanding the methodical spectrum of landscape structure analysis towards gradient-based approaches. Methods like lacunarity analysis are promising, since they do not rely on predefined landscape units or patches and thus enable ecologists to effectively deal with the complexity of natural systems.