Diagnostic microarray for influenza B viruses

Micro and Nanoscale Technologies for Diagnosis of Viral Infections

Viral infection is one of the leading causes of mortality worldwide. The growth of globalization significantly increases the risk of virus spreading, making it a global threat to future public health. In particular, the ongoing coronavirus disease 2019 (COVID-19) pandemic outbreak emphasizes the importance of devices and methods for rapid, sensitive, and cost-effective diagnosis of viral infections in the early stages by which their quick and global spread can be controlled. Micro and nanoscale technologies have attracted tremendous attention in recent years for a variety of medical and biological applications, especially in developing diagnostic platforms for rapid and accurate detection of viral diseases. This review addresses advances of microneedles, microchip-based integrated platforms, and nano- and microparticles for sampling, sample processing, enrichment, amplification, and detection of viral particles and antigens related to the diagnosis of viral diseases. Additionally, methods for the fabrication of microchip-based devices and commercially used devices are described. Finally, challenges and prospects on the development of micro and nanotechnologies for the early diagnosis of viral diseases are highlighted.

Molecular and Immunological Diagnostic Techniques of Medical Viruses

Viral infections are causing serious problems in human population worldwide. The recent outbreak of coronavirus disease 2019 caused by SARS-CoV-2 is a perfect example how viral infection could pose a great threat to global public health and economic sectors. Therefore, the first step in combating viral pathogens is to get a timely and accurate diagnosis. Early and accurate detection of the viral presence in patient sample is crucial for appropriate treatment, control, and prevention of epidemics. Here, we summarize some of the molecular and immunological diagnostic approaches available for the detection of viral infections of humans. Molecular diagnostic techniques provide rapid viral detection in patient sample. They are also relatively inexpensive and highly sensitive and specific diagnostic methods. Immunological-based techniques have been extensively utilized for the detection and epidemiological studies of human viral infections. They can detect antiviral antibodies or viral antigens in clinical samples. There are several commercially available molecular and immunological diagnostic kits that facilitate the use of these methods in the majority of clinical laboratories worldwide. In developing countries including Ethiopia where most of viral infections are endemic, exposure to improved or new methods is highly limited as these methods are very costly to use and also require technical skills. Since researchers and clinicians in all corners of the globe are working hard, it is hoped that in the near future, they will develop good quality tests that can be accessible in low-income countries.

Diagnostic and Vaccination Approaches for Newcastle Disease Virus in Poultry: The Current and Emerging Perspectives

Newcastle disease (ND) is one of the most devastating diseases that considerably cripple the global poultry industry. Because of its enormous socioeconomic importance and potential to rapidly spread to naïve birds in the vicinity, ND is included among the list of avian diseases that must be notified to the OIE immediately upon recognition. Currently, virus isolation followed by its serological or molecular identification is regarded as the gold standard method of ND diagnosis. However, this method is generally slow and requires specialised laboratory with biosafety containment facilities, making it of little relevance under epidemic situations where rapid diagnosis is seriously needed. Thus, molecular based diagnostics have evolved to overcome some of these difficulties, but the extensive genetic diversity of the virus ensures that isolates with mutations at the primer/probe binding sites escape detection using these assays. This diagnostic dilemma leads to the emergence of cutting-edge technologies such as next-generation sequencing (NGS) which have so far proven to be promising in terms of rapid, sensitive, and accurate recognition of virulent Newcastle disease virus (NDV) isolates even in mixed infections. As regards disease control strategies, conventional ND vaccines have stood the test of time by demonstrating track record of protective efficacy in the last 60 years. However, these vaccines are unable to block the replication and shedding of most of the currently circulating phylogenetically divergent virulent NDV isolates. Hence, rationally designed vaccines targeting the prevailing genotypes, the so-called genotype-matched vaccines, are highly needed to overcome these vaccination related challenges. Among the recently evolving technologies for the development of genotype-matched vaccines, reverse genetics-based live attenuated vaccines obviously appeared to be the most promising candidates. In this review, a comprehensive description of the current and emerging trends in the detection, identification, and control of ND in poultry are provided. The strengths and weaknesses of each of those techniques are also emphasised.

Using DNA chips for identification of tephritid pest species

BACKGROUND

The ability correctly to identify species in a rapid and reliable manner is critical in many situations. For insects in particular, the primary tools for such identification rely on adult-stage morphological characters. For a number of reasons, however, there is a clear need for alternatives. This paper reports on the development of a new method employing DNA biochip technology for the identification of pest species within the family Tephritidae.

RESULTS

The DNA biochip developed and tested here quickly and efficiently identifies and discriminates between several tephritid species, except for some that are members of a complex of closely related taxa and that may in fact not represent distinct biological species. The use of these chips offers a number of potential advantages over current methods. Results can be obtained in less than 5 h using material from any stage of the life cycle and with greater sensitivity than other methods currently available.

CONCLUSIONS

This technology provides a novel tool for the rapid and reliable identification of several major pest species that may be intercepted in imported fruits or other commodities. The existing chips can also easily be expanded to incorporate additional markers and species as needed.

Transcriptomic responses of juvenile Pacific whiteleg shrimp, Litopenaeus vannamei, to hypoxia and hypercapnic hypoxia

Estuarine crustaceans are often exposed to low dissolved O2 (hypoxia) accompanied by elevated CO2 (hypercapnia), which lowers water pH. Acclimatory responses to hypoxia have been widely characterized; responses to hypercapnia in combination with hypoxia (hypercapnic hypoxia) are less well known. Here we used oligonucleotide microarrays to characterize changes in global gene expression in the hepatopancreas of Pacific whiteleg shrimp, Litopenaeus vannamei, exposed to hypoxia or hypercapnic hypoxia for 4 or 24 h, compared with time-matched animals held in air-saturated water (normoxia). Unigenes whose expressions were significantly impacted by treatment and/or time were used to build artificial neural networks (ANNs) to identify genes with the greatest sensitivity in pairwise discriminations between treatments at each time point and between times for each treatment. ANN gene sets that discriminated hypoxia or hypercapnic hypoxia from normoxia shared functions of translation, mitochondrial energetics, and cellular defense. GO terms protein modification/phosphorylation/cellular protein metabolism and RNA processing/apoptosis/cell cycling occurred at highest frequency in discriminating hypercapnic hypoxia from hypoxia at 4 and 24 h, respectively. For 75.4% of the annotated ANN genes, exposure to hypercapnic hypoxia for 24 h reduced or reversed the transcriptional response to hypoxia alone. These results suggest that high CO2/low pH may interfere with transcriptionally based acclimation to hypoxia or elicit physiological or biochemical responses that relieve internal hypoxia. Whether these data reflect resilience or sensitivity of L. vannamei in the face of expanding hypoxic zones and rising levels of atmospheric CO2 may be important to understanding the survival of this and other estuarine species.

The use of pyrosequencer-generated sequence-signatures to identify the influenza B-lineage and the subclade of the B/Yamataga-lineage viruses from currently circulating human influenza B viruses

BACKGROUND

Influenza B viruses belong to two antigenically and genetically distinct lineages which co-circulate in varying proportions in many countries.

OBJECTIVE

To develop simple, rapid, accurate and robust methods to detect and differentiate currently circulating B-lineage viruses in respiratory samples and virus isolates.

STUDY DESIGN

Haemagglutinin (HA) gene sequences from more than 6300 influenza B strains were analysed to identify signature sequences that could be used to distinguish between B-lineages and sublineages.

RESULTS

Pyrosequencing and a real time PCR assays were developed to detect the major B-lineages (B/Victoria/2/87 or B/Yamagata/16/88) and pyrosequencing for a unique mutation was used to further differentiate the B/Yamagata viruses into two currently co-circulating subgroups. More than 300 influenza virus-containing samples, including original specimens, cell and egg grown viruses, were tested with a 100% accuracy. Furthermore, when the same PCR primers were used in an rRT-PCR assay, the two lineages could be differentiated by their distinct ranges of melting temperature with an overall accuracy of 99% for 158 samples tested.

CONCLUSIONS

These new pyrosequencing and rRT-PCR methods have the potential to aid the rapid identification of influenza B-lineages for surveillance purposes and to increase the available data for bi-annual selection of viruses for updating influenza vaccines.

The transcriptomic responses of the eastern oyster, Crassostrea virginica, to environmental conditions

Understanding the mechanisms by which organisms adapt to environmental conditions is a fundamental question for ecology and evolution. In this study, we evaluate changes in gene expression of a marine mollusc, the eastern oyster Crassostrea virginica, associated with the physico-chemical conditions and the levels of metals and other contaminants in their environment. The results indicate that transcript signatures can effectively disentangle the complex interactive gene expression responses to the environment and are also capable of disentangling the complex dynamic effects of environmental factors on gene expression. In this context, the mapping of environment to gene and gene to environment is reciprocal and mutually reinforcing. In general, the response of transcripts to the environment is driven by major factors known to affect oyster physiology such as temperature, pH, salinity, and dissolved oxygen, with pollutant levels playing a relatively small role, at least within the range of concentrations found in the studied oyster habitats. Further, the two environmental factors that dominate these effects (temperature and pH) interact in a dynamic and nonlinear fashion to impact gene expression. Transcriptomic data obtained in our study provide insights into the mechanisms of physiological responses to temperature and pH in oysters that are consistent with the known effects of these factors on physiological functions of ectotherms and indicate important linkages between transcriptomics and physiological outcomes. Should these linkages hold in further studies and in other organisms, they may provide a novel integrated approach for assessing the impacts of climate change, ocean acidification and anthropogenic contaminants on aquatic organisms via relatively inexpensive microarray platforms.

Use of consensus sequences for the design of high density resequencing microarrays: the influenza virus paradigm

BACKGROUND

A resequencing microarray called PathogenID v2.0 has been developed and used to explore various strategies of sequence selection for its design. The part dedicated to influenza viruses was based on consensus sequences specific for one gene generated from global alignments of a large number of influenza virus sequences available in databanks.

RESULTS

For each HA (H1, H2, H3, H5, H7 and H9) and NA (N1, N2 and N7) molecular type chosen to be tested, 1 to 3 consensus sequences were computed and tiled on the microarray. A total of 12 influenza virus samples from different host origins (humans, pigs, horses and birds) and isolated over a period of about 50 years were used in this study. Influenza viruses were correctly identified, and in most cases with the accurate information of the time of their emergence.

CONCLUSIONS

PathogenID v2.0 microarray demonstrated its ability to type and subtype influenza viruses, often to the level of viral variants, with a minimum number of tiled sequences. This validated the strategy of using consensus sequences, which do not exist in nature, for our microarray design. The versatility, rapidity and high discriminatory power of the PathogenID v2.0 microarray could prove critical to detect and identify viral genome reassortment events resulting in a novel virus with epidemic or pandemic potential and therefore assist health authorities to make efficient decisions about patient treatment and outbreak management.

Diagnostic microarray for human and animal bacterial diseases and their virulence and antimicrobial resistance genes

Rapid diagnosis and treatment of disease is often based on the identification and characterization of causative agents derived from phenotypic characteristics. Current methods can be laborious and time-consuming, often requiring many skilled personnel and a large amount of lab space. The objective of our study was to develop a spotted microarray for rapid identification and characterization of bacterial pathogens and their antimicrobial resistance genes. Our spotted microarray consists of 489 70mer probes that detect 40 bacterial pathogens of medical, veterinary and zoonotic importance (including 15 NIAID Category A, B and C pathogens); associated genes that encode resistance for antimicrobial and metal resistance; and DNA elements that are important for horizontal gene transfer among bacteria. High specificity and reliability of the microarray was achieved for bacterial pathogens of animal and human importance by validating MDR pathogenic bacteria as pure cultures or by following their inoculation in complex and highly organic sample matrices, such as soil and manure.

Modelling interactions of acid-base balance and respiratory status in the toxicity of metal mixtures in the American oyster Crassostrea virginica

Heavy metals, such as copper, zinc and cadmium, represent some of the most common and serious pollutants in coastal estuaries. In the present study, we used a combination of linear and artificial neural network (ANN) modelling to detect and explore interactions among low-dose mixtures of these heavy metals and their impacts on fundamental physiological processes in tissues of the Eastern oyster, Crassostrea virginica. Animals were exposed to Cd (0.001-0.400 microM), Zn (0.001-3.059 microM) or Cu (0.002-0.787 microM), either alone or in combination for 1 to 27 days. We measured indicators of acid-base balance (hemolymph pH and total CO(2)), gas exchange (Po(2)), immunocompetence (total hemocyte counts, numbers of invasive bacteria), antioxidant status (glutathione, GSH), oxidative damage (lipid peroxidation; LPx), and metal accumulation in the gill and the hepatopancreas. Linear analysis showed that oxidative membrane damage from tissue accumulation of environmental metals was correlated with impaired acid-base balance in oysters. ANN analysis revealed interactions of metals with hemolymph acid-base chemistry in predicting oxidative damage that were not evident from linear analyses. These results highlight the usefulness of machine learning approaches, such as ANNs, for improving our ability to recognize and understand the effects of sub-acute exposure to contaminant mixtures.

Rapid multiplex reverse transcription-PCR typing of influenza A and B virus, and subtyping of influenza A virus into H1, 2, 3, 5, 7, 9, N1 (human), N1 (animal), N2, and N7, including typing of novel swine origin influenza A (H1N1) virus, during the 2009 outbreak in Milwaukee, Wisconsin

A large outbreak of novel influenza A (H1N1) virus (swine origin influenza virus [S-OIV]) infection in Milwaukee, WI, occurred in late April 2009. We had recently developed a rapid multiplex reverse transcription-PCR enzyme hybridization assay (FluPlex) to determine the type (A or B) and subtype (H1, H2, H3, H5, H7, H9, N1 [human], N1 [animal], N2, or N7) of influenza viruses, and this assay was used to confirm the diagnoses for the first infected patients in the state. The analytical sensitivity was excellent at 1.5 to 116 copies/reaction, or 10(-3) to 10(-1) 50% tissue culture infective doses/ml. The testing of all existing hemagglutinin and neuraminidase subtypes of influenza A virus and influenza B virus (41 influenza virus strains) and 24 common respiratory pathogens showed only one low-level H3 cross-reaction with an H10N7 avian strain and only at 5.2 x 10(6) copies/reaction, not at lower concentrations. Comparisons of the FluPlex results with results from multiple validated in-house molecular assays, CDC-validated FDA-approved assays, and gene sequencing demonstrated 100% positive agreement for the typing of 179 influenza A viruses and 3 influenza B viruses, the subtyping of 110 H1N1 (S-OIV; N1 [animal]), 62 H1N1 (human), and 6 H3N2 (human) viruses, and the identification of 24 negative clinical samples and 100% negative agreement for all viruses tested except H1N1 (human) (97.7%). The small number of false-positive H1N1 (human) samples most likely represent increased sensitivity over that of other in-house assays, with four of four results confirmed by the CDC's influenza virus subtyping assay. The FluPlex is a rapid, inexpensive, sensitive, and specific method for the typing and subtyping of influenza viruses and demonstrated outstanding utility during the first 2 weeks of an S-OIV infection outbreak. Methods for rapid detection and broad subtyping of influenza viruses, including animal subtypes, are needed to address public concern over the emergence of pandemic strains. Attempts to automate this assay are ongoing.

A low density oligonucleotide microarray for the detection of viral and atypical bacterial respiratory pathogens

Acute respiratory tract infections are a major cause of morbidity and mortality worldwide and exert a considerable economic burden on healthcare systems. Acute respiratory tract infections of the upper and lower respiratory tract are caused by a wide variety of viral and bacterial pathogens, which require comprehensive laboratory investigations. Conventional serological and immunofluorescence-based diagnostic methods for acute respiratory tract infections lack sensitivity when compared to polymerase chain reaction (PCR)-based approaches and the development of new diagnostic methodologies is required, to provide accurate, sensitive and rapid diagnoses. In the present study, a PCR-based low density oligonucleotide microarray was developed for the detection of 16 viral and two atypical bacterial pathogens. The performance of this DNA microarray-based analysis exhibited comparable sensitivities and specificities to multiplex real-time reverse transcription polymerase chain reactions (rtPCRs) confirming the potential diagnostic utility of the method. In contrast to routine multiplex PCR, the microarray incorporates an intrinsic redundancy as multiple and non-identical probes per target on the array allow direct intra-assay confirmation of positives. This study demonstrates that microarray technology provides a viable alternative to conventional serological-based approaches and multiplex PCR for pathogen identification in acute respiratory tract infections.

A transcriptomic analysis of land-use impacts on the oyster, Crassostrea virginica, in the South Atlantic bight

Increasing utilization and human population density in the coastal zone is widely believed to place increasing stresses on the resident biota, but confirmation of this belief is somewhat lacking. While we have solid evidence that highly disturbed estuarine systems have dramatic changes in the resident biota (black and white if you will), we lack tools that distinguish the shades of grey. In part, this lack of ability to distinguish shades of grey stems from the analytical tools that have been applied to studies of estuarine systems, and perhaps more important, is the insensitivity of the biological end points that we have used to assess these impacts. In this study, we will present data on the phenotypic adjustments as measured by transcriptomic signatures of a resilient organism (oysters) to land-use practices in the surrounding watershed using advanced machine-learning algorithms. We will demonstrate that such an approach can reveal subtle and meaningful shifts in oyster gene expression in response to land use. Further, the data show that gill tissues are far more responsive and provide superior discrimination of land-use classes than hepatopancreas and that transcripts encoding proteins involved in energy production, protein synthesis and basic metabolism are more robust indicators of land use than classic biomarkers such as metallothioneins, GST and cytochrome P-450.

DNA microarrays in the clinic: infectious diseases

We argue that the most-promising area of clinical application of microarrays in the foreseeable future is the diagnostics and monitoring of infectious diseases. Microarrays for the detection and characterization of human pathogens have already found their way into clinical practice in some countries. After discussing the persistent, yet often underestimated, importance of infectious diseases for public health, we consider the technologies that are best suited for the detection and clinical investigation of pathogens. Clinical application of microarray technologies for the detection of mycobacteria, Bacillus anthracis, HIV, hepatitis and influenza viruses, and other major pathogens, as well as the analysis of their drug-resistance patterns, illustrate our main thesis.

Automated analytical microarrays: a critical review

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.

Development of combined DNA-based piezoelectric biosensors for the simultaneous detection and genotyping of high risk Human Papilloma Virus strains

BACKGROUND

Human Papilloma Virus (HPV) is a DNA virus belonging to the Papovavirus family. Genital HPV types have been subdivided into medium-low risk, and high-risk (HPV 16 and 18), frequently associated with cervical cancer. Three DNA-based piezoelectric biosensors were here developed for a quick detection and genotyping of HPV.

METHODS

We developed a method for the detection and genotyping of HPV in human cervical scraping samples based on coupling DNA piezoelectric sensors with Polymerase Chain Reaction (PCR). The novelty of this work was the design and immobilisation of a degenerate probe (chosen in a conserved region of the viral genome) for the simultaneous detection of 16 virus strains and of two specific probes (chosen in a less-conserved region of the viral genome) for genotyping.

RESULTS

The three biosensors were optimised with synthetic oligonucleotides with good reproducibility (HPVdeg CV% (av) 9%, HPV16 CV%(av) 9%; HPV18 CV%(av) 11%) with a detection limit of 50 nM. Cervical scraping samples after PCR amplification (in 40-200 nM range), were tested without the need of label with high selectivity and reproducibility. The results were in agreement with a reference method used in routinary analysis.

CONCLUSION

Piezoelectric biosensors have proven to be suitable for detection and genotyping of HPV.