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Analytical microarrays feature great capabilities for simultaneous detection and quantification of multiple analytes in a single measurement. In this work, we present a rapid and simple method for bulk preparation of microarrays on polycarbonate sheets. Succinylated Jeffamine® ED-2003 was screen printed on polycarbonate sheets to create a polyfunctional shielding layer by baking at 100 °C. After microdispension of capture probes (antibodies, oligonucleotides, or small molecules) in a microarray format, chips were assembled with a flow cell from double-sided tape. It was shown that the shielding layer was firmly coated and suppressed unspecific binding of proteins. Universal applicability was demonstrated by transferring established flow-based chemiluminescence microarray measurement principles from glass slides to polycarbonate chips without loss of analytical performance. Higher chemiluminescence signals could be generated by performing heterogeneous asymmetric recombinase polymerase amplification on polycarbonate chips. Similar results could be shown for sandwich microarray immunoassays. Beyond that, lower inter- and intra-assay variances could be measured for the analysis of Legionella pneumophila Serogroup 1, strain Bellingham-1. Even surface regeneration of indirect competitive immunoassays was possible, achieving a limit of detection of 0.35 ng L−1 for enrofloxacin with polycarbonate microarray chips. Succinylated Jeffamine ED-2003 coated polycarbonate chips have great potential to replace microtiter plates by flow-based chemiluminescence microarrays for rapid analysis. Therefore, it helps analytical microarrays to advance into routine analysis and diagnostics.

Recent advances in molecular biology have resulted in the application of DNA microarrays and next-generation sequencing (NGS) technologies to the field of microbial ecology. This review aims to examine the strengths and weaknesses of each of the methodologies, including depth and ease of analysis, throughput and cost-effectiveness. It also intends to highlight the optimal application of each of the individual technologies toward the study of a particular environment and identify potential synergies between the two main technologies, whereby both sample number and coverage can be maximized. We suggest that the efficient use of microarray and NGS technologies will allow researchers to advance the field of microbial ecology, and importantly, improve our understanding of the role of microorganisms in their various environments.

Routine antimicrobial susceptibility testing (AST) can prevent deaths due to bacteria and reduce the spread of multi-drug-resistance, but cannot be regularly performed in resource-limited-settings due to technological challenges, high-costs, and lack of trained professionals. We demonstrate an automated and cost-effective cellphone-based 96-well microtiter-plate (MTP) reader, capable of performing AST without the need for trained diagnosticians. Our system includes a 3D-printed smartphone attachment that holds and illuminates the MTP using a light-emitting-diode array. An inexpensive optical fiber-array enables the capture of the transmitted light of each well through the smartphone camera. A custom-designed application sends the captured image to a server to automatically determine well-turbidity, with results returned to the smartphone in ~1 minute. We tested this mobile-reader using MTPs prepared with 17 antibiotics targeting Gram-negative bacteria on clinical isolates of Klebsiella pneumoniae, containing highly-resistant antimicrobial profiles. Using 78 patient isolate test-plates, we demonstrated that our mobile-reader meets the FDA-defined AST criteria, with a well-turbidity detection accuracy of 98.21%, minimum-inhibitory-concentration accuracy of 95.12%, and a drug-susceptibility interpretation accuracy of 99.23%, with no very major errors. This mobile-reader could eliminate the need for trained diagnosticians to perform AST, reduce the cost-barrier for routine testing, and assist in spatio-temporal tracking of bacterial resistance.

Purpose Whole-exome (WES) and whole-genome sequencing (WGS) increase the diagnostic yield in autism spectrum disorder (ASD) compared to chromosomal microarray (CMA), but there have been no comprehensive cost analyses. The objective was to perform such an assessment of CMA, WES, and WGS and compare the incremental cost per additional positive finding in hypothetical testing scenarios. Methods Five-year patient and program costs were estimated from an institutional perspective. WES and WGS estimates were based on HiSeq 2500 with an additional WGS estimate for HiSeq X platforms. Parameter uncertainty was assessed with probabilistic and deterministic sensitivity analysis. Results The cost per ASD sample was CAD$1,655 (95% CI: 1,611; 1,699) for WES, CAD$2,851 (95% CI: 2,750; 2,956) for WGS on HiSeq X, and CAD$5,519 (95% CI: 5,244; 5,785) on HiSeq 2500, compared to CAD$744 (95% CI 714, 773) for CMA. The incremental cost was over CAD$25,000 per additional positive finding if CMA was replaced by newer technology. Conclusion While costs for WES and WGS remain high, future reductions in material and equipment costs, and increased understanding of newly discovered variants and variants of unknown significance will lead to improved value.

Abstract Two DNA-based methods were compared for the ability to assign serotype to 139 isolates of Salmonella enterica ssp. I. Intergenic sequence ribotyping (ISR) evaluated single nucleotide polymorphisms occurring in a 5S ribosomal gene region and flanking sequences bordering the gene dkgB. A DNA microarray hybridization method that assessed the presence and the absence of sets of genes was the second method. Serotype was assigned for 128 (92.1%) of submissions by the two DNA methods. ISR detected mixtures of serotypes within single colonies and it cost substantially less than Kauffmann–White serotyping and DNA microarray hybridization. Decreasing the cost of serotyping S. enterica while maintaining reliability may encourage routine testing and research.

Bulk segregant analysis (BSA) using microarrays, and extreme array mapping (XAM) have recently been used to rapidly identify genomic regions associated with phenotypes in multiple species. These experiments, however, require the identification of single feature polymorphisms (SFP) between the cross parents for each new combination of genotypes, which raises the cost of experiments. The availability of the genomic polymorphism data in Arabidopsis thaliana, coupled with the efficient designs of Single Nucleotide Polymorphism (SNP) genotyping arrays removes the requirement for SFP detection and lowers the per array cost, thereby lowering the overall cost per experiment. To demonstrate that these approaches would be functional on SNP arrays and determine confidence intervals, we analyzed hybridizations of natural accessions to the Arabidopsis ATSNPTILE array and simulated BSA or XAM given a variety of gene models, populations, and bulk selection parameters. Our results show a striking degree of correlation between the genotyping output of both methods, which suggests that the benefit of SFP genotyping in context of BSA can be had with the cheaper, more efficient SNP arrays. As a final proof of concept, we hybridized the DNA from bulks of an F2 mapping population of a Sulfur and Selenium ionomics mutant to both the Arabidopsis ATTILE1R and ATSNPTILE arrays, which produced almost identical results. We have produced R scripts that prompt the user for the required parameters and perform the BSA analysis using the ATSNPTILE1 array and have provided them as supplemental data files.

Background With the accelerating development of bioscience, the problem of research cost has become important. We previously devised and developed a novel concept microarray with manageable volumes (MMV) using a soft gel. It demonstrated the great potential of the MMV technology with the examples of 1024-parallel-cell culture and PCR experiments. However, its full potential failed to be expressed, owing to the nature of the material used for the MMV chip. Results In the present study, by developing plastic-based MMVs and associated technologies, we introduced novel technologies such as C2D2P (in which the cells in each well are converted from DNA to protein in 1024-parallel), NGS-non-dependent microbiome analysis, and other powerful applications. Conclusions The reborn MMV-microarray technology has proven to be highly efficient and cost-effective (with approximately 100-fold cost reduction) and enables us to realize hitherto unattainable technologies.

Background Airborne fungi play an important role in causing allergy and infections in susceptible people. Identification of these fungi, based on morphological characteristics, is time-consuming, expertise-demanding, and could be inaccurate. Methods We developed an oligonucleotide array that could accurately identify 21 important airborne fungi (13 genera) that may cause adverse health problems. The method consisted of PCR amplification of the internal transcribed spacer (ITS) regions, hybridization of the PCR products to a panel of oligonucleotide probes immobilized on a nylon membrane, and detection of the hybridization signals with alkaline phosphatase-conjugated antibodies. Results A collection of 72 target and 66 nontarget reference strains were analyzed by the array. Both the sensitivity and specificity of the array were 100%, and the detection limit was 10 pg of genomic DNA per assay. Furthermore, 70 fungal isolates recovered from air samples were identified by the array and the identification results were confirmed by sequencing of the ITS and D1/D2 domain of the large-subunit RNA gene. The sensitivity and specificity of the array for identification of the air isolates was 100% (26/26) and 97.7% (43/44), respectively. Conclusions Identification of airborne fungi by the array was cheap and accurate. The current array may contribute to decipher the relationship between airborne fungi and adverse health effect.

A cost-–effectiveness analysis was performed to assess the potential value of companion diagnostics in supporting treatment decisions for dasatinib and nilotinib in chronic myeloid leukemia. A decision model was developed, and model inputs were taken from the literature and publicly available sources. The perspective of the healthcare sector in the Netherlands was used. Sensitivity and scenario analyses were performed to assess uncertainty in the results. Companion diagnostics could improve health and reduce costs, despite the estimates being uncertain owing to limited evidence for comparative effectiveness between dasatinib and nilotinib. The results were sensitive to the cost of treatment, utility of progression and progression-free survival. This case demonstrates the use of cost-–effectiveness analysis at an early stage of health technology assessment to generate economic evidence for the use of companion diagnostics in treatment decisions and to support decision-making for their development.