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Stratification of asthma at the molecular level, especially using accessible biospecimens, could greatly enable patient selection for targeted therapy. To determine the value of blood analysis to identify transcriptional differences between clinically defined asthma and nonasthma groups, identify potential patient subgroups based on gene expression, and explore biological pathways associated with identified differences. Transcriptomic profiles were generated by microarray analysis of blood from 610 patients with asthma and control participants in the U-BIOPRED (Unbiased Biomarkers in Prediction of Respiratory Disease Outcomes) study. Differentially expressed genes (DEGs) were identified by analysis of variance, including covariates for RNA quality, sex, and clinical site, and Ingenuity Pathway Analysis was applied. Patient subgroups based on DEGs were created by hierarchical clustering and topological data analysis. A total of 1,693 genes were differentially expressed between patients with severe asthma and participants without asthma. The differences from participants without asthma in the nonsmoking severe asthma and mild/moderate asthma subgroups were significantly related (r = 0.76), with a larger effect size in the severe asthma group. The majority of, but not all, differences were explained by differences in circulating immune cell populations. Pathway analysis showed an increase in chemotaxis, migration, and myeloid cell trafficking in patients with severe asthma, decreased B-lymphocyte development and hematopoietic progenitor cells, and lymphoid organ hypoplasia. Cluster analysis of DEGs led to the creation of subgroups among the patients with severe asthma who differed in molecular responses to oral corticosteroids. Blood gene expression differences between clinically defined subgroups of patients with asthma and individuals without asthma, as well as subgroups of patients with severe asthma defined by transcript profiles, show the value of blood analysis in stratifying patients with asthma and identifying molecular pathways for further study. Clinical trial registered with www.clinicaltrials.gov (NCT01982162).

Emerging studies suggest that low-pass genome sequencing (GS) provides additional diagnostic yield of clinically significant copy-number variants (CNVs) compared with chromosomal microarray analysis (CMA). However, a prospective back-to-back comparison evaluating accuracy, efficacy, and incremental yield of low-pass GS compared with CMA is warranted. A total of 1023 women undergoing prenatal diagnosis were enrolled. Each sample was subjected to low-pass GS and CMA for CNV analysis in parallel. CNVs were classified according to guidelines of the American College of Medical Genetics and Genomics. Low-pass GS not only identified all 124 numerical disorders or pathogenic or likely pathogenic (P/LP) CNVs detected by CMA in 121 cases (11.8%, 121/1023), but also defined 17 additional and clinically relevant P/LP CNVs in 17 cases (1.7%, 17/1023). In addition, low-pass GS significantly reduced the technical repeat rate from 4.6% (47/1023) for CMA to 0.5% (5/1023) and required less DNA (50 ng) as input. In the context of prenatal diagnosis, low-pass GS identified additional and clinically significant information with enhanced resolution and increased sensitivity of detecting mosaicism as compared with the CMA platform used. This study provides strong evidence for applying low-pass GS as an alternative prenatal diagnostic test.

Genomic microarrays used to assess DNA copy number are now recommended as first-tier tests for the postnatal evaluation of individuals with intellectual disability, autism spectrum disorders, and/or multiple congenital anomalies. Application of this technology has resulted in the discovery of widespread copy number variation in the human genome, both polymorphic variation in healthy individuals and novel pathogenic copy number imbalances. To assist clinical laboratories in the evaluation of copy number variants and to promote consistency in interpretation and reporting of genomic microarray results, the American College of Medical Genetics has developed the following professional guidelines for the interpretation and reporting of copy number variation. These guidelines apply primarily to evaluation of constitutional copy number variants detected in the postnatal setting.

Background MicroRNAs (miRNAs) are small noncoding RNAs about 22 nt long that negatively regulate gene expression at the post-transcriptional level. Their key effects on various biological processes, e.g., embryonic development, cell division, differentiation and apoptosis, are widely recognized. Evidence suggests that aberrant expression of miRNAs may contribute to many types of human diseases, including cancer. Here we present a database of differentially expressed miRNAs in human cancers (dbDEMC), to explore aberrantly expressed miRNAs among different cancers. Results We collected the miRNA expression profiles of 14 cancer types, curated from 48 microarray data sets in peer-reviewed publications. The Significance Analysis of Microarrays method was used to retrieve the miRNAs that have dramatically different expression levels in cancers when compared to normal tissues. This database provides statistical results for differentially expressed miRNAs in each data set. A total of 607 differentially expressed miRNAs (590 mature miRNAs and 17 precursor miRNAs) were obtained in the current version of dbDEMC. Furthermore, low-throughput data from the same literature were also included in the database for validation. An easy-to-use web interface was designed for users. Annotations about each miRNA can be queried through miRNA ID or miRBase accession numbers, or can be browsed by different cancer types. Conclusions This database is expected to be a valuable source for identification of cancer-related miRNAs, thereby helping with the improvement of classification, diagnosis and treatment of human cancers. All the information is freely available through http://159.226.118.44/dbDEMC/index.html .

Microarrays provide a powerful analytical tool for the simultaneous detection of multiple analytes in a single experiment. The specific affinity reaction of nucleic acids (hybridization) and antibodies towards antigens is the most common bioanalytical method for generating multiplexed quantitative results. Nucleic acid-based analysis is restricted to the detection of cells and viruses. Antibodies are more universal biomolecular receptors that selectively bind small molecules such as pesticides, small toxins, and pharmaceuticals and to biopolymers (e.g. toxins, allergens) and complex biological structures like bacterial cells and viruses. By producing an appropriate antibody, the corresponding antigenic analyte can be detected on a multiplexed immunoanalytical microarray. Food and water analysis along with clinical diagnostics constitute potential application fields for multiplexed analysis. Diverse fluorescence, chemiluminescence, electrochemical, and label-free microarray readout systems have been developed in the last decade. Some of them are constructed as flow-through microarrays by combination with a fluidic system. Microarrays have the potential to become widely accepted as a system for analytical applications, provided that robust and validated results on fully automated platforms are successfully generated. This review gives an overview of the current research on microarrays with the focus on automated systems and quantitative multiplexed applications. [graphic removed]

Marine algae are one of the largest sources of carbon on the planet. The microbial degradation of algal polysaccharides to their constitutive sugars is a cornerstone in the global carbon cycle in oceans. Marine polysaccharides are highly complex and heterogeneous, and poorly understood. This is also true for marine microbial proteins that specifically degrade these substrates and when characterized, they are frequently ascribed to new protein families. Marine (meta)genomic datasets contain large numbers of genes with functions putatively assigned to carbohydrate processing, but for which empirical biochemical activity is lacking. There is a paucity of knowledge on both sides of this protein/carbohydrate relationship. Addressing this ‘double blind’ problem requires high throughput strategies that allow large scale screening of protein activities, and polysaccharide occurrence. Glycan microarrays, in particular the Comprehensive Microarray Polymer Profiling (CoMPP) method, are powerful in screening large collections of glycans and we described the integration of this technology to a medium throughput protein expression system focused on marine genes. This methodology (Double Blind CoMPP or DB-CoMPP) enables us to characterize novel polysaccharide-binding proteins and to relate their ligands to algal clades. This data further indicate the potential of the DB-CoMPP technique to accommodate samples of all biological sources.

The global spread of H5N1 avian influenza virus has raised concerns that H5N1 might adapt to the human host and cause the next human influenza pandemic. Novel glycan array technologies can rapidly assess the receptor specificity of influenza viruses, detecting changes that might signal human adaptation. New technologies are urgently required for rapid surveillance of the current H5N1 avian influenza A outbreaks to gauge the potential for adaptation of the virus to the human population, a crucial step in the emergence of pandemic influenza virus strains. Owing to the species-specific nature of the interaction between the virus and host glycans, attention has recently focused on novel glycan array technologies that can rapidly assess virus receptor specificity and the potential emergence of human-adapted H5N1 viruses.

The embryonic gonad is the only organ that takes two mutually exclusive differentiating pathways and hence gives rise to two different adult organs: testes or ovaries. The recent application of genomic tools including microarrays, next-generation sequencing approaches, and epigenetics can significantly contribute to decipher the molecular mechanisms involved in the processes of sex determination and sex differentiation. However, in fish, these studies are complicated by the fact that these processes depend, perhaps to a larger extent when compared to other vertebrates, on the interplay of genetic and environmental influences. Here, we review the advances made so far, taking into account different experimental approaches, and illustrate some technical complications deriving from the fact that as development progresses it becomes more and more difficult to distinguish whether changes in gene expression or DNA methylation patterns are the cause or the consequence of such developmental events. Finally, we suggest some avenues for further research in both model fish species and fish species facing specific problems within an aquaculture context.

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.

Exosomes, which are membranous nanovesicles, are actively released by cells and have been attributed to roles in cell-cell communication, cancer metastasis, and early disease diagnostics. The small size (30–100 nm) along with low refractive index contrast of exosomes makes direct characterization and phenotypical classification very difficult. In this work we present a method based on Single Particle Interferometric Reflectance Imaging Sensor (SP-IRIS) that allows multiplexed phenotyping and digital counting of various populations of individual exosomes (>50 nm) captured on a microarray-based solid phase chip. We demonstrate these characterization concepts using purified exosomes from a HEK 293 cell culture. As a demonstration of clinical utility, we characterize exosomes directly from human cerebrospinal fluid (hCSF). Our interferometric imaging method could capture, from a very small hCSF volume (20 uL), nanoparticles that have a size compatible with exosomes, using antibodies directed against tetraspanins. With this unprecedented capability, we foresee revolutionary implications in the clinical field with improvements in diagnosis and stratification of patients affected by different disorders.