Chemiluminescence microflow injection analysis system on a chip for the determination of uric acid without enzyme.

A new microflow injection analysis (microFIA) system on a chip coupled with chemiluminescence (CL) for the non-enzymatic determination of uric acid is described. The microFIA system produced by using two transparent poly(methylmethacrylate) (PMMA) chips measured 50 x 40 x 5 mm, the microchannels, etched by CO2 laser, were 200 microm wide and 100 microm deep, and the volume of the reaction area (RA) was about 1.2 microL. The injection pump, with accurate time control, monitored all reagents, including the sample. The uric acid was sensed by the chemiluminescence reaction between luminol and ferricyanide. The linear range of the uric acid concentration was 0.8-30 mg/L and the detection limit was 0.5 mg/L (S/N = 3). The relative standard deviation was 4.42% for 5 mg/L uric acid (n = 8). The proposed method has been successfully applied to the non-separation determination of uric acid in human serum and urine.     

Flow‐based analysis using microfluidics–chemiluminescence systems

This review will discuss various approaches and techniques in which analysis using microfluidics–chemiluminescence systems (MF–CL) has been reported. A variety of applications is examined, including environmental, pharmaceutical, biological, food and herbal analysis. Reported uses of CL reagents, sample introduction techniques, sample pretreatment methods, CL signal enhancement and detection systems are discussed. A hydrodynamic pumping system is predominately used for these applications. However, several reports are available in which electro‐osmotic (EO) pumping has been implemented. Various sample pretreatment methods have been used, including liquid–liquid extraction, solid‐phase extraction and molecularly imprinted polymers. A wide range of innovative techniques has been reported for CL signal enhancement. Most of these techniques are based on enhancement of the mixing process in the microfluidics channels, which leads to enhancement of the CL signal. However, other techniques are also reported, such as mirror reaction, liquid core waveguide, on‐line pre‐derivatization and the use of an opaque white chip with a thin transparent seal. Photodetectors are the most commonly used detectors; however, other detection systems have also been used, including integrated electrochemiluminescence (ECL) and organic photodiodes (OPDs). Copyright © 2012 John Wiley & Sons, Ltd.     

Stability of the spatio-temporal distribution and niche overlap in neotropical earthworm assemblages

The spatial distribution of soil invertebrates is aggregated with high-density patches alternating with low-density zones. A high degree of spatio-temporal organization generally exists with identified patches of specific species assemblages, in which species coexist according to assembly rules related to competitive mechanisms for spatial and trophic resources occur. However, these issues have seldom been addressed. The spatio-temporal structure of a native earthworm community in a natural savanna and a grass–legume pasture in the Colombian “Llanos” was studied during a 2-year-period. A spatially explicit sampling design (regular grid) was used to discern the distribution pattern of species assemblages in both systems. Earthworms were collected from small soil pits at three different sampling dates. Data collected from 1 m² soil monoliths were also used in the present study. Data were analyzed with the partial triadic analysis (PTA) and correlograms, while niche overlap was computed with the Pianka index. The PTA and correlogram analysis revealed that earthworm communities displayed a similar stable spatial structure in both systems during the 2-year study period. An alternation of population patches where different species' assemblages dominated was common to all sampling dates. The medium-sized Andiodrilus sp. and Glossodrilus sp. exhibited a clear spatial opposition in natural savanna and the grass–legume pasture for the duration of the study. The Pianka index showed a high degree of niche overlapping in several dimensions (vertical distribution, seasonality of population density) between both species. The inclusion of space-time data analysis tools as the PTA and the use of classical ecological indices (Pianka) in soil ecology studies may improve our knowledge of earthworm assemblages' dynamics.     

Stability of the spatio-temporal distribution and niche overlap in neotropical earthworm assemblages

The spatial distribution of soil invertebrates is aggregated with high-density patches alternating with low-density zones. A high degree of spatio-temporal organization generally exists with identified patches of specific species assemblages, in which species coexist according to assembly rules related to competitive mechanisms for spatial and trophic resources occur. However, these issues have seldom been addressed. The spatio-temporal structure of a native earthworm community in a natural savanna and a grass–legume pasture in the Colombian “Llanos” was studied during a 2-year-period. A spatially explicit sampling design (regular grid) was used to discern the distribution pattern of species assemblages in both systems. Earthworms were collected from small soil pits at three different sampling dates. Data collected from 1 m² soil monoliths were also used in the present study. Data were analyzed with the partial triadic analysis (PTA) and correlograms, while niche overlap was computed with the Pianka index. The PTA and correlogram analysis revealed that earthworm communities displayed a similar stable spatial structure in both systems during the 2-year study period. An alternation of population patches where different species' assemblages dominated was common to all sampling dates. The medium-sized Andiodrilus sp. and Glossodrilus sp. exhibited a clear spatial opposition in natural savanna and the grass–legume pasture for the duration of the study. The Pianka index showed a high degree of niche overlapping in several dimensions (vertical distribution, seasonality of population density) between both species. The inclusion of space-time data analysis tools as the PTA and the use of classical ecological indices (Pianka) in soil ecology studies may improve our knowledge of earthworm assemblages' dynamics.     

Modeling and simulation: tools for metabolic engineering.

Mathematical modeling is one of the key methodologies of metabolic engineering. Based on a given metabolic model different computational tools for the simulation, data evaluation, systems analysis, prediction, design and optimization of metabolic systems have been developed. The currently used metabolic modeling approaches can be subdivided into structural models, stoichiometric models, carbon flux models, stationary and nonstationary mechanistic models and models with gene regulation. However, the power of a model strongly depends on its basic modeling assumptions, the simplifications made and the data sources used. Model validation turns out to be particularly difficult for metabolic systems. The different modeling approaches are critically reviewed with respect to their potential and benefits for the metabolic engineering cycle. Several tools that have emerged from the different modeling approaches including structural pathway synthesis, stoichiometric pathway analysis, metabolic flux analysis, metabolic control analysis, optimization of regulatory architectures and the evaluation of rapid sampling experiments are discussed.     

Assessing equilibration and convergence in biomolecular simulations

If molecular dynamics simulations are used to characterize the folding of peptides or proteins, a wide range of conformational states needs to be sampled. This study reports an analysis of peptide simulations to identify the best methods for assessing equilibration and sampling in these systems where there is significant conformational disorder. Four trajectories of a beta peptide in methanol and four trajectories of an alpha peptide in water, each of 5 ns in length, have been studied. Comparisons have also been made with two 50-ns trajectories of the beta peptide in methanol. The convergence rates of quantities that probe both the extent of conformational sampling and the local dynamical properties have been characterized. These include the numbers of hydrogen bonds populated, clusters identified, and main chain torsion angle transitions in the trajectories. The relative equilibrium rates of different quantities are found to vary significantly between the two systems studied reflecting both the differences in peptide primary structure and the different solvents used. A cluster analysis of the simulation trajectories is identified as a very effective method for judging the convergence of the simulations. This is particularly the case if the analysis includes a comparison of multiple trajectories calculated for the same system from different starting structures.     

Relationship between population genetic structure and riparian habitat as revealed by RAPD analysis of the rheophyte Acorus gramineus Soland. (Araceae) in Taiwan

Acorus gramineus Soland. (Araceae) is a rheophyte and is distributed in southeastern Asia. Its populations are restricted to riparian habitats. The discontinuous distribution might result in high genetic diversification among plants of different river systems. In the present study, leaf samples were collected from populations along six river systems in western Taiwan and the genetic variation was investigated by employing RAPD markers. A total of 255 samples from 17 sampling sites was studied. Eighty random 10-mer primers were screened and six of them, which showed better amplification results, were selected to analyse all of the samples. Data of 34 high-intensity and highly reproducible polymorphic fragments were used in statistical analyses. The results of AMOVA analyses indicated that, of the total variation, 46.84% was attributable to differences among river systems, 16.88% to differences among sampling sites within river systems, and 36.28% to differences among individuals within sampling sites. The results of cluster analysis and principal coordinate analysis revealed that sampling sites of each river system formed distinct clusters and the sampling sites of six river systems were clustered into three main groups according to latitudinal relationships. The results of the present study indicated that the population genetic structure of the plants of different river systems is highly diversified, which seems to imply that the gene flow among them is very limited.     

HMM sampling and applications to gene finding and alternative splicing

The standard method of applying hidden Markov models to biological problems is to find a Viterbi (maximal weight) path through the HMM graph. The Viterbi algorithm reduces the problem of finding the most likely hidden state sequence that explains given observations, to a dynamic programming problem for corresponding directed acyclic graphs. For example, in the gene finding application, the HMM is used to find the most likely underlying gene structure given a DNA sequence. In this note we discuss the applications of sampling methods for HMMs. The standard sampling algorithm for HMMs is a variant of the common forward-backward and backtrack algorithms, and has already been applied in the context of Gibbs sampling methods. Nevetheless, the practice of sampling state paths from HMMs does not seem to have been widely adopted, and important applications have been overlooked. We show how sampling can be used for finding alternative splicings for genes, including alternative splicings that are conserved between genes from related organisms. We also show how sampling from the posterior distribution is a natural way to compute probabilities for predicted exons and gene structures being correct under the assumed model. Finally, we describe a new memory efficient sampling algorithm for certain classes of HMMs which provides a practical sampling alternative to the Hirschberg algorithm for optimal alignment. The ideas presented have applications not only to gene finding and HMMs but more generally to stochastic context free grammars and RNA structure prediction.     

Spatiotemporal Variation in Fish Assemblage Structure in Tropical Floodplain Creeks

Biotic assemblages of aquatic floodplain systems have great potential to randomly reshuffle during annual flood periods, and have been described both as stochastically and deterministically assembled. However, only a limited number of studies have been conducted in relatively few habitat types. To evaluate large-bodied fish assemblage structure of floodplain creeks, we used experimental gill nets to sample fishes at sites spaced at even intervals within three creeks in consecutive dry seasons. A total of 60 species were collected, 41 of which were collected both years. The most frequently collected species were piscivores and algivores/detritivores. Multivariate analysis suggested non-random patterns of assemblage structure in both years. Correspondence analysis (CA) of the species abundance-by-site matrix for 2001 suggests species assemblages were most similar among sites within the same creek regardless of depth or longitudinal position. Discriminant function analysis (DFA) correctly predicted 100% of samples based on creek identity, and species ordination scores revealed creek-specific species subsets. In 2002, CA and DFA did not distinguish creeks based on species assemblages. Instead, we observed a significant positive relationship between assemblage composition and site depth and position along the creek longitudinal gradient. Assemblages were most similar among sites of comparable depth and longitudinal position, regardless of creek identity. Predators occurred almost exclusively at mouth and mid-reach sites. Flood duration prior to our 2002 sampling period was prolonged due to abnormally heavy rainfall in November and December 2001 (typically the falling-water period), and may account for the observed inter-annual variation in fish assemblage structure.     

Resources and costs for microbial sequence analysis evaluated using virtual machines and cloud computing

Background

The widespread popularity of genomic applications is threatened by the “bioinformatics bottleneck” resulting from uncertainty about the cost and infrastructure needed to meet increasing demands for next-generation sequence analysis. Cloud computing services have been discussed as potential new bioinformatics support systems but have not been evaluated thoroughly.

Results

We present benchmark costs and runtimes for common microbial genomics applications, including 16S rRNA analysis, microbial whole-genome shotgun (WGS) sequence assembly and annotation, WGS metagenomics and large-scale BLAST. Sequence dataset types and sizes were selected to correspond to outputs typically generated by small- to midsize facilities equipped with 454 and Illumina platforms, except for WGS metagenomics where sampling of Illumina data was used. Automated analysis pipelines, as implemented in the CloVR virtual machine, were used in order to guarantee transparency, reproducibility and portability across different operating systems, including the commercial Amazon Elastic Compute Cloud (EC2), which was used to attach real dollar costs to each analysis type. We found considerable differences in computational requirements, runtimes and costs associated with different microbial genomics applications. While all 16S analyses completed on a single-CPU desktop in under three hours, microbial genome and metagenome analyses utilized multi-CPU support of up to 120 CPUs on Amazon EC2, where each analysis completed in under 24 hours for less than $60. Representative datasets were used to estimate maximum data throughput on different cluster sizes and to compare costs between EC2 and comparable local grid servers.

Conclusions

Although bioinformatics requirements for microbial genomics depend on dataset characteristics and the analysis protocols applied, our results suggests that smaller sequencing facilities (up to three Roche/454 or one Illumina GAIIx sequencer) invested in 16S rRNA amplicon sequencing, microbial single-genome and metagenomics WGS projects can achieve cost-efficient bioinformatics support using CloVR in combination with Amazon EC2 as an alternative to local computing centers.     

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。     

Screening protein refolding using surface plasmon resonance

Surface plasmon resonance (SPR) measurements were used to screen refolding conditions to identify a physicochemical environment which gives an acceptable refolding yield for samples of glutathione-S-transferase (GST) denatured in 6 M guanidine hydrochloride and 32 mM dithiothreitol. The SPR measurements were performed on carboxymethylcellulose coated chips that could accommodate two separate flow paths. One side of the chip was derivatized with immobilized glutathione and the other with goat anti-GST antibody. This created a dual-derivatized chip capable of showing both the presence of GST and providing a measure of enzyme activity. The dual-derivatized chip could be regenerated using a two-step washing procedure and reused to analyze multiple samples from a screening study of protein refolding conditions. SPR measurements have been shown to be suitable for screening protein refolding conditions due to the high sensitivity, ease of chip regeneration and the ability to incorporate a control in the experimental design. The combination of such advantages with the high-throughput automated SPR systems currently available may be a valuable approach to determine conditions suitable for protein refolding following insoluble expression in a bacterial host.     

Viral composition and context in metagenomes from biofilm and suspended growth municipal wastewater treatment plants

Wastewater treatment plants (WWTPs) contain high density and diversity of viruses which can significantly impact microbial communities in aquatic systems. While previous studies have investigated viruses in WWTP samples that have been specifically concentrated for viruses and filtered to exclude bacteria, little is known about viral communities associated with bacterial communities throughout wastewater treatment systems. Additionally, differences in viral composition between attached and suspended growth wastewater treatment bioprocesses are not well characterized. Here, shotgun metagenomics was used to analyse wastewater and biomass from transects through two full-scale WWTPs for viral composition and associations with bacterial hosts. One WWTP used a suspended growth activated sludge bioreactor and the other used a biofilm reactor (trickling filter). Myoviridae, Podoviridae and Siphoviridae were the dominant viral families throughout both WWTPs, which are all from the order Caudovirales. Beta diversity analysis of viral sequences showed that samples clustered significantly both by plant and by specific sampling location. For each WWTP, the overall bacterial community structure was significantly different than community structure of bacterial taxa associated with viral sequences. These findings highlight viral community composition in transects through different WWTPs and provide context for dsDNA viral sequences in bacterial communities from these systems.     

Inherent intractability of the ascertainment problem for pedigree data: a general likelihood framework.

The problem of ascertainment in segregation analysis arises when families are selected for study through ascertainment of affected individuals. In this case, ascertainment must be corrected for in data analysis. However, methods for ascertainment correction are not available for many common sampling schemes, e.g., sequential sampling of extended pedigrees (except in the case of "single" selection). Concerns about whether ascertainment correction is even required for large pedigrees, about whether and how multiple probands in the same pedigree can be taken into account properly, and about how to apply sequential sampling strategies have occupied many investigators in recent years. We address these concerns by reconsidering a central issue, namely, how to handle pedigree structure (including size). We introduce a new distinction, between sampling in such a way that observed pedigree structure does not depend on which pedigree members are probands (proband-independent [PI] sampling) and sampling in such a way that observed pedigree structure does depend on who are the probands (proband-dependent [PD] sampling). This distinction corresponds roughly (but not exactly) to the distinction between fixed-structure and sequential sampling. We show that conditioning on observed pedigree structure in ascertained data sets obtained under PD sampling is not in general correct (with the exception of "single" selection), while PI sampling of pedigree structures larger than simple sibships is generally not possible. Yet, in practice one has little choice but to condition on observed pedigree structure. We conclude that the problem of genetic modeling in ascertained data sets is, in most situations, literally intractable. We recommend that future efforts focus on the development of robust approximate approaches to the problem.     

Development of low-cost microfluidic systems for lab-on-a-chip biosensor applications

In this work, we develop low-cost microfluidic systems based on polydimethylsiloxane (PDMS) for lab-on-a-chip applications. PDMS microfluidic structures have been fabricated by micromolding, PDMS casting, and plasma bonding processes. The micromolding technique is used to fabricate PDMS slabs with micro-sized grooves, and the complete microchannel is formed by bonding PDMS slab with glass or PDMS substrate. The molding procedure using SU-8 photoresist patterning on silicon wafer, PDMS microchannel fabrication, and PDMS surface treatment using oxygen plasma and TiO₂ coating, are discussed. The various parameters for oxygen plasma treatment including RF power and treatment time are studied in order to obtain conditions for good bonding with the glass substrate. The best condition for plasma treatment is found to be the low RF power (8 W) with 5 min treatment time. In addition, TiO₂ coating with oxygen plasma treatment has been applied to make PDMS surface more hydrophilic to improve aqueous solution compatilbility. The microfluidic channels for various applications, including sample injection cross channel, micropump channel, T and Y sample mixers, PCR thermocyling chamber and channel, capillary electrophoresis flow channel, and conductimetric systems have been fabricated. Finally, a typical application of the PDMS chip in a flow injection conductimetric system for sodium chloride detection has been demonstrated.     

Novel application of surface plasmon resonance biosensor chips for measurement of advanced glycation end products in serum of Zucker diabetic fatty rats

Advanced glycation end products (AGEs) have been implicated in diabetic complications. To measure AGEs, especially N-(carboxymethyl)lysine (CML), in sera from Zucker diabetic fatty rats (ZDF) and Zucker lean rats (ZL), we used a novel method of protein chip and surface plasmon resonance imaging (SPRI). Serum samples were obtained from male ZDF and ZL rats at 20 weeks of age. Antibodies to AGEs or CML were immobilized on a gold surface, which was modified by cysteine-tagged, protein-G constructs. The gold chip upon which the serum was spotted was optically coupled with a prism coupler. The reflected images from the gold chip were obtained using a charge-coupled device (CCD) camera. The direct analysis of the glycated proteins and products using SPRI showed that AGEs and CML levels were elevated in ZDF serum, compared with ZL serum. The lowest detection limit of AGEs was 10 ng/ml, with a working range covering the physiological range. These results indicate that the protein chip and SPRI system is very suitable for the measurement of glycated proteins and end products in serum samples. This system offers high sensitivity without any fluorescent or other labeling of the components and saves a substantial amount of time, resources, and labor. Our results suggest that SPRI systems can be used as a tool to diagnose diabetic complications.     

Fragment replica-exchange method for efficient protein conformation sampling

The native structure of proteins corresponds to the global minimum of the free energy. The replica-exchange method (REM) has been recently used to search for the energy minimum in a wide protein conformation space. For large systems, however, applying REM can be costly because the number of replicas required for conformational sampling increases. We have developed a variant of REM called fragment REM, which is based on the existence of correlations between the local amino acid sequence and the local structure. Equilibrium distributions for two peptides were computed by conventional molecular dynamics, REM and the proposed REM simulations. We found that the modified REM successfully reduces the number of replicas needed for the simulation.     

Habitat amount hypothesis and passive sampling explain mammal species composition in Amazonian river islands

Nested structures of species assemblages have been frequently associated with patch size and isolation, leading to the conclusion that colonization–extinction dynamics drives nestedness. The ‘passive sampling’ model states that the regional abundance of species randomly determines their occurrence in patches. The ‘habitat amount hypothesis’ also challenges patch size and isolation effects, arguing that they occur because of a ‘sample area effect’. Here, we (a) ask whether the structure of the mammal assemblages of fluvial islands shows a nested pattern, (b) test whether species’ regional abundance predicts species’ occurrence on islands, and (c) ask whether habitat amount in the landscape and matrix resistance to biological flow predict the islands’ species composition. We quantified nestedness and tested its significance using null models. We used a regression model to analyze whether a species’ relative regional abundance predicts its incidence on islands. We accessed islands’ species composition by an NMDS ordination and used multiple regression to evaluate how species composition responds to habitat amount and matrix resistance. The degree of nestedness did not differ from that expected by the passive sampling hypothesis. Likewise, species’ regional abundance predicted its occurrence on islands. Habitat amount successfully predicted the species composition on islands, whereas matrix resistance did not. We suggest the application of habitat amount hypothesis for predicting species composition in other patchy systems. Although the island biogeography perspective has dominated the literature, we suggest that the passive sampling perspective is more appropriate for explaining the assemblages’ structure in this and other non‐equilibrium patch systems. Abstract in Portuguese is available with online material.