Mighty small: Observing and modeling individual microbes becomes big science

Progress in microbiology has always been driven by technological advances, ever since Antonie van Leeuwenhoek discovered bacteria by making an improved compound microscope. However, until very recently we have not been able to identify microbes and record their mostly invisible activities, such as nutrient consumption or toxin production on the level of the single cell, not even in the laboratory. This is now changing with the rapid rise of exciting new technologies for single-cell microbiology (1, 2), which enable microbiologists to do what plant and animal ecologists have been doing for a long time: observe who does what, when, where, and next to whom. Single cells taken from the environment can be identified and even their genomes sequenced. Ex situ, their size, elemental, and biochemical composition, as well as other characteristics can be measured with high-throughput and cells sorted accordingly. Even better, individual microbes can be observed in situ with a range of novel microscopic and spectroscopic methods, enabling localization, identification, or functional characterization of cells in a natural sample, combined with detecting uptake of labeled compounds. Alternatively, they can be placed into fabricated microfluidic environments, where they can be positioned, exposed to stimuli, monitored, and their interactions controlled “in microfluido.” By introducing genetically engineered reporter cells into a fabricated landscape or a microcosm taken from nature, their reproductive success or activity can be followed, or their sensing of their local environment recorded.

Ocean acidification shows negligible impacts on high-latitude bacterial community structure in coastal pelagic mesocosms

The impact of ocean acidification and carbonation on microbial community structure was assessed during a large-scale in situ costal pelagic mesocosm study, included as part of the EPOCA 2010 Arctic campaign. The mesocosm experiment included ambient conditions (fjord) and nine mesocosms with pCO(2) levels ranging from similar to 145 to similar to 1420 mu atm. Samples for the present study were collected at ten time points (t-1, t1, t5, t7, t12, t14, t18, t22, t26 to t28) in seven treatments (ambient fjord (similar to 145), 2x similar to 185, similar to 270, similar to 685, similar to 820, similar to 1050 mu atm) and were analysed for "small" and "large" size fraction microbial community composition using 16S rRNA (ribosomal ribonucleic acid) amplicon sequencing. This high-throughput sequencing analysis produced similar to 20 000 000 16S rRNA V4 reads, which comprised 7000OTUs. The main variables structuring these communities were sample origins (fjord or mesocosms) and the community size fraction (small or large size fraction). The community was significantly different between the unenclosed fjord water and enclosed mesocosms (both control and elevated CO2 treatments) after nutrients were added to the mesocosms, suggesting that the addition of nutrients is the primary driver of the change in mesocosm community structure. The relative importance of each structuring variable depended greatly on the time at which the community was sampled in relation to the phytoplankton bloom. The sampling strategy of separating the small and large size fraction was the second most important factor for community structure. When the small and large size fraction bacteria were analysed separately at different time points, the only taxon pCO(2) was found to significantly affect were the Gammaproteobacteria after nutrient addition. Finally, pCO(2) treatment was found to be significantly correlated (non-linear) with 15 rare taxa, most of which increased in abundance with higher CO2.

A novel diagnostic test detects a low frequency of the hemicentin Gln5345Arg variant among Northern Irish age related macular degeneration patients.

Purpose: Age related macular degeneration (AMD) is a common cause of severe vision loss. Identification of genes involved in AMD will facilitate early detection and ultimately help to identify pathways for treatment for this disorder. The A16,263G mutation in the HEMICENTIN-1 gene produces a non-conservative substitution of arginine for glutamine at codon 5345 which has been implicated in familial AMD. The aim of this study is to develop a rapid diagnostic assay for the detection of this mutation and to evaluate its frequency in a sample of AMD patients. Methods: A primer probe set was designed from exon 104 of the HEMICENTIN-1 gene to differentiate between mutant and wild type alleles. A region spanning the mutation was amplified by PCR using a LightCycler (Roche Diagnostic). The mutation was then detected by melt curve analysis of the hybrid formed between the PCR product and a specific fluorescent probe. The frequency of the mutation within the Northern Ireland population was evaluated by assaying 508 affected AMD patients, 25 possibly affected and 163 controls. Results: This assay clearly discriminates between the A16,263G mutant and wild type HEMICENTIN-1 alleles. The wild type sequence has a single base mismatch with the probe which decreases the stability of the hybrid, resulting in a lower TM (TM=51.27 °C) than that observed for the perfectly matched mutant allele (TM=59.9 °C). The mutant allele was detected in only one of the 696 subjects, an affected AMD patient. Conclusions: We describe a rapid assay for the genotyping of the Gln5345Arg mutation using real-time fluorescence PCR to facilitate rapid processing of samples through combined amplification and detection steps. These characteristics are suitable for a clinical setting where high throughput diagnostic procedures are required. The frequency of this mutation within the Northern Ireland population has been estimated at 0.2%, concurring with previous findings that this mutation is a rare variant associated with AMD. A rapid diagnostic assay will facilitate a reliable and convenient evaluation of the frequency of the Gln5345Arg mutation and its association with AMD within other populations.

Area-efficient high-speed 3D DWT processor architecture

An area-efficient high-throughput architecture based on distributed arithmetic is proposed for 3D discrete wavelet transform (DWT). The 3D DWT processor was designed in VHDL and mapped to a Xilinx Virtex-E FPGA. The processor runs up to 85 MHz, which can process the five-level DWT analysis of a 128 x 128 x 128 fMRI volume image in 20 ms.

Density-viscosity product of small-volume ionic liquid samples using quartz crystal impedance analysis

Quartz crystal impedance analysis has been developed as a technique to assess whether room-temperature ionic liquids are Newtonian fluids and as a small-volume method for determining the values of their viscosity-density product, rho eta. Changes in the impedance spectrum of a 5-MHz fundamental frequency quartz crystal induced by a water-miscible room-temperature ionic liquid, 1-butyl-3-methylimidazolium. trifluoromethylsulfonate ([C(4)mim][OTf]), were measured. From coupled frequency shift and bandwidth changes as the concentration was varied from 0 to 100% ionic liquid, it was determined that this liquid provided a Newtonian response. A second water-immiscible ionic liquid, 1-butyl-3-methylimidazolium bis(trifluoromethanesulfonyl)imide [C(4)mim][NTf2], with concentration varied using methanol, was tested and also found to provide a Newtonian response. In both cases, the values of the square root of the viscosity-density product deduced from the small-volume quartz crystal technique were consistent with those measured using a viscometer and density meter. The third harmonic of the crystal was found to provide the closest agreement between the two measurement methods; the pure ionic liquids had the largest difference of similar to 10%. In addition, 18 pure ionic liquids were tested, and for 11 of these, good-quality frequency shift and bandwidth data were obtained; these 12 all had a Newtonian response. The frequency shift of the third harmonic was found to vary linearly with square root of viscosity-density product of the pure ionic liquids up to a value of root(rho eta) approximate to 18 kg m(-2) s(-1/2), but with a slope 10% smaller than that predicted by the Kanazawa and Gordon equation. It is envisaged that the quartz crystal technique could be used in a high-throughput microfluidic system for characterizing ionic liquids.

Development of a Diagnostic Genetic Test for Simplex and Autosomal Recessive Retinitis Pigmentosa

PURPOSE: Retinitis pigmentosa (RP) causes hereditary blindness in adults (prevalence, approximately 1 in 4000). Each of the more than 30 causative genes identified to date are responsible for only a small percentage of cases. Genetic diagnosis via traditional methods is problematic, and a single test with a higher probability of detecting the causative mutation would be very beneficial for the clinician. The goal of this study therefore was to develop a high-throughput screen capable of detecting both known mutations and novel mutations within all genes implicated in autosomal recessive or simplex RP. DESIGN: Evaluation of diagnostic technology. PARTICIPANTS AND CONTROLS: Participants were 56 simplex and autosomal recessive RP patients, with 360 population controls unscreened for ophthalmic disease. METHODS: A custom genechip capable of resequencing all exons containing known mutations in 19 disease-associated genes was developed (RP genechip). A second, commercially available arrayed primer extension (APEX) system was used to screen 501 individual previously reported variants. The ability of these high-throughput approaches to identify pathogenic variants was assessed in a cohort of simplex and autosomal recessive RP patients. MAIN OUTCOME MEASURES: Number of mutations and potentially pathogenic variants identified. RESULTS: The RP genechip identified 44 sequence variants: 5 previously reported mutations; 22 known single nucleotide polymorphisms (SNPs); 11 novel, potentially pathogenic variants; and 6 novel SNPs. There was strong concordance with the APEX array, but only the RP genechip detected novel variants. For example, identification of a novel mutation in CRB1 revealed a patient, who also had a single previously known CRB1 mutation, to be a compound heterozygote. In some individuals, potentially pathogenic variants were discovered in more than one gene, consistent with the existence of disease modifier effects resulting from mutations at a second locus. CONCLUSIONS: The RP genechip provides the significant advantage of detecting novel variants and could be expected to detect at least one pathogenic variant in more than 50% of patients. The APEX array provides a reliable method to detect known pathogenic variants in autosomal recessive RP and simplex RP patients and is commercially available. High-throughput genotyping for RP is evolving into a clinically useful genetic diagnostic tool.

Monoclonal antibody development for acrylamide-adducted human haemoglobin; A biomarker of dietary acrylamide exposure

The spontaneous formation of the neurotoxic carcinogen acrylamide in a wide range of cooked foods has recently been discovered, leading to dietary exposure estimates of 30.8 mu g of acrylamide day(-1) for an average 77 kg human male. This is considerably higher than the European legal limit of acrylamide in drinking water, which is approximately 0.2 mu g of acrylamide person(-1) day(-1). A recent study of 62,573 women over 11.3 years has observed an increased risk of postmenopausal endometrial and ovarian cancer (but not breast cancer) with increasing dietary acrylamide intake, demonstrating significant risk to human health. As individual acrylamide exposure is affected by dietary habits, cooking methods, and cigarette consumption; accurate extrapolation from estimated dietary exposure is extremely difficult. Quantifying biomarkers of acrylamide exposure therefore remains the most effective means of rapidly determining individual exposure to acrylamide, and correlating exposure with lifestyle choices. Current methodologies for the analysis of blood biomarkers of acrylamide are focused on expensive, slower chromatographic techniques such as GC and LC coupled to mass spectrometry. This paper describes the first successful development of two monoclonal antibodies specific to acrylamide-adducted haemoglobin (IC50 of 94 ng ml(-1) and 198 ng ml(-1)), that are suitable for use in a high-throughput biomarker immunoassay to determine individual acrylamide exposure. Further development of acrylamide-haemoglobin standards with defined levels of acrylamide adduction will enable a fully quantitative assay, and allow sensitivity comparisons with alternative chromatographic methods of analysis. (C) 2008 Elsevier B.V. All rights reserved.

Inferring the conservative causal core of gene regulatory networks

Background
Inferring gene regulatory networks from large-scale expression data is an important problem that received much attention in recent years. These networks have the potential to gain insights into causal molecular interactions of biological processes. Hence, from a methodological point of view, reliable estimation methods based on observational data are needed to approach this problem practically.

Results
In this paper, we introduce a novel gene regulatory network inference (GRNI) algorithm, called C3NET. We compare C3NET with four well known methods, ARACNE, CLR, MRNET and RN, conducting in-depth numerical ensemble simulations and demonstrate also for biological expression data from E. coli that C3NET performs consistently better than the best known GRNI methods in the literature. In addition, it has also a low computational complexity. Since C3NET is based on estimates of mutual information values in conjunction with a maximization step, our numerical investigations demonstrate that our inference algorithm exploits causal structural information in the data efficiently.

Conclusions
For systems biology to succeed in the long run, it is of crucial importance to establish methods that extract large-scale gene networks from high-throughput data that reflect the underlying causal interactions among genes or gene products. Our method can contribute to this endeavor by demonstrating that an inference algorithm with a neat design permits not only a more intuitive and possibly biological interpretation of its working mechanism but can also result in superior results.

Comparison of ELISA and SPR biosensor technology for the detection of paralytic shellfish poisoning toxins

An enzyme labeled immunosorbent assay (ELISA) and surface plasmon resonance (SPR) biosensor assay for the detection of paralytic shellfish poisoning (PSP) toxins were developed and a comparative evaluation was performed. A polyclonal antibody (BC67) used in both assay formats was raised to saxitoxin–jeffamine–BSA in New Zealand white rabbits. Each assay format was designed as an inhibition assay. Shellfish samples (n = 54) were evaluated by each method using two simple rapid extraction procedures and compared to the AOAC high performance liquid chromatography (HPLC) and the mouse bioassay (MBA). The results of each assay format were comparable with the HPLC and MBA methods and demonstrate that an antibody with high sensitivity and broad specificity to PSP toxins can be applied to different immunological techniques. The method of choice will depend on the end-users needs. The reduced manual labor and simplicity of operation of the SPR biosensor compared to ELISA, ease of sample extraction and superior real time semi-quantitative analysis are key features that could make this technology applicable in a high-throughput monitoring unit.

Towards accurate estimation of the proportion of true null hypotheses in multiple testing

Background

Biomedical researchers are now often faced with situations where it is necessary to test a large number of hypotheses simultaneously, eg, in comparative gene expression studies using high-throughput microarray technology. To properly control false positive errors the FDR (false discovery rate) approach has become widely used in multiple testing. The accurate estimation of FDR requires the proportion of true null hypotheses being accurately estimated. To date many methods for estimating this quantity have been proposed. Typically when a new method is introduced, some simulations are carried out to show the improved accuracy of the new method. However, the simulations are often very limited to covering only a few points in the parameter space.

Results

Here I have carried out extensive in silico experiments to compare some commonly used methods for estimating the proportion of true null hypotheses. The coverage of these simulations is unprecedented thorough over the parameter space compared to typical simulation studies in the literature. Thus this work enables us to draw conclusions globally as to the performance of these different methods. It was found that a very simple method gives the most accurate estimation in a dominantly large area of the parameter space. Given its simplicity and its overall superior accuracy I recommend its use as the first choice for estimating the proportion of true null hypotheses in multiple testing.

Fully hardware based WFQ architecture for high-speed QoS packet scheduling

A full hardware implementation of a Weighted Fair Queuing (WFQ) packet scheduler is proposed. The circuit architecture presented has been implemented using Altera Stratix II FPGA technology, utilizing RLDII and QDRII memory components. The circuit can provide fine granularity Quality of Service (QoS) support at a line throughput rate of 12.8Gb/s in its current implementation. The authors suggest that, due to the flexible and scalable modular circuit design approach used, the current circuit architecture can be targeted for a full ASIC implementation to deliver 50 Gb/s throughput. The circuit itself comprises three main components; a WFQ algorithm computation circuit, a tag/time-stamp sort and retrieval circuit, and a high throughput shared buffer. The circuit targets the support of emerging wireline and wireless network nodes that focus on Service Level Agreements (SLA's) and Quality of Experience.

Structural influence of gene networks on their inference: analysis of C3NET

Background: The availability of large-scale high-throughput data possesses considerable challenges toward their functional analysis. For this reason gene network inference methods gained considerable interest. However, our current knowledge, especially about the influence of the structure of a gene network on its inference, is limited.

Comparison of biosensor platforms for surface plasmon resonance based detection of paralytic shellfish toxins

Paralytic shellfish poisoning (PSP) toxins are produced by certain marine dinoflagellates and may accumulate in bivalve molluscs through filter feeding. The Mouse Bioassay (MBA) is the internationally recognised reference method of analysis, but it is prone to technical difficulties and regarded with increasing disapproval due to ethical reasons. As such, alternative methods are required. A rapid surface plasmon resonance (SPR) biosensor inhibition assay was developed to detect PSP toxins in shellfish by employing a saxitoxin polyclonal antibody (R895). Using an assay developed for and validated on the Biacore Q biosensor system, this project focused on transferring the assay to a high-throughput, Biacore T100 biosensor in another laboratory. This was achieved using a prototype PSP toxin kit and recommended assay parameters based on the Biacore Q method. A monoclonal antibody (GT13A) was also assessed. Even though these two instruments are based on SPR principles, they vary widely in their mode of operation including differences in the integrated mu-fluidic cartridges, autosampler system, and sensor chip compatibilities. Shellfish samples (n = 60), extracted using a simple, rapid procedure, were analysed using each platform, and results were compared to AOAC high performance liquid chromatography (HPLC) and MBA methods. The overall agreement, based on statistical 2 x 2 comparison tables, between each method ranged from 85% to 94.4% using R895 and 77.8% to 100% using GT13A. The results demonstrated that the antibody based assays with high sensitivity and broad specificity to PSP toxins can be applied to different biosensor platforms. (C) 2011 Elsevier B.V. All rights reserved.

Circulating and synovial antibody profiling of juvenile arthritis patients by nucleic acid programmable protein arrays.

Introduction Juvenile idiopathic arthritis (JIA) is a heterogeneous disease characterized by chronic joint inflammation of unknown cause in children. JIA is an autoimmune disease and small numbers of auto-antibodies have been reported in JIA patients. The identification of antibody markers could improve the existing clinical management of patients. Methods A pilot study was performed on the application of a high-throughput platform, nucleic acid programmable protein arrays (NAPPA), to assess the levels of antibodies present in the systemic circulation and synovial joint of a small cohort of juvenile arthritis patients. Plasma and synovial fluid from ten JIA patients was screened for antibodies against 768 proteins on NAPPA. Results Quantitative reproducibility of NAPPA was demonstrated with >0.95 intra- and inter- array correlations. A strong correlation was also observed for the levels of antibodies between plasma and synovial fluid across the study cohort (r=0.96). Differences in the levels of 18 antibodies were revealed between sample types across all patients. Patients were segregated into two clinical subtypes with distinct antibody signatures by unsupervised hierarchical cluster analysis. Conclusions NAPPA provides a high-throughput quantitatively reproducible platform to screen for disease specific autoantibodies at the proteome level on a microscope slide. The strong correlation between the circulating antibody levels and those of the inflamed joint represents a novel finding and provides confidence to use plasma for discovery of autoantibodies in JIA, thus circumventing the challenges associated with joint aspiration. We expect that autoantibody profiling of JIA patients on NAPPA could yield antibody markers that can act as criteria to stratify patients, predict outcomes and understand disease etiology at the molecular level.

Use of NMR metabolomic plasma profiling methodologies to identify illicit growth-promoting administrations

Detection of growth-promoter use in animal production systems still proves to be an analytical challenge despite years of activity in the field. This study reports on the capability of NMR metabolomic profiling techniques to discriminate between plasma samples obtained from cattle treated with different groups of growth-promoting hormones (dexamethasone, prednisolone, oestradiol) based on recorded metabolite profiles. Two methods of NMR analysis were investigated—a Carr–Purcell–Meiboom–Gill (CPMG)-pulse sequence technique and a conventional 1H NMR method using pre-extracted plasma. Using the CPMG method, 17 distinct metabolites could be identified from the spectra. 1H NMR analysis of extracted plasma facilitated identification of 23 metabolites—six more than the alternative method and all within the aromatic region. Multivariate statistical analysis of acquired data from both forms of NMR analysis separated the plasma metabolite profiles into distinct sample cluster sets representative of the different animal study groups. Samples from both sets of corticosteroid-treated animals—dexamethasone and prednisolone—were found to be clustered relatively closely and had similar alterations to identified metabolite panels. Distinctive metabolite profiles, different from those observed within plasma from corticosteroid-treated animal plasma, were observed in oestradiol-treated animals and samples from these animals formed a cluster spatially isolated from control animal plasma samples. These findings suggest the potential use of NMR methodologies of plasma metabolite analysis as a high-throughput screening technique to aid detection of growth promoter use.