384 research outputs found

    Strand Displacement Amplification for Multiplex Detection of Nucleic Acids

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    The identification of various targets such as bacteria, viruses, and other cells remains a prerequisite for point-of-care diagnostics and biotechnological applications. Nucleic acids, as encoding information for all forms of life, are excellent biomarkers for detecting pathogens, hereditary diseases, and cancers. To date, many techniques have been developed to detect nucleic acids. However, most of them are based on polymerase chain reaction (PCR) technology. These methods are sensitive and robust, but they require expensive instruments and trained personnel. DNA strand displacement amplification is carried out under isothermal conditions and therefore does not need expensive instruments. It is simple, fast, sensitive, specific, and inexpensive. In this chapter, we introduce the principles, methods, and updated applications of DNA strand displacement technology in the detection of infectious diseases. We also discuss how robust, sensitive, and specific nucleic acid detection could be obtained when combined with the novel CRISPR/Cas system

    Synthetic Biology

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    Synthetic biology gives us a new hope because it combines various disciplines, such as genetics, chemistry, biology, molecular sciences, and other disciplines, and gives rise to a novel interdisciplinary science. We can foresee the creation of the new world of vegetation, animals, and humans with the interdisciplinary system of biological sciences. These articles are contributed by renowned experts in their fields. The field of synthetic biology is growing exponentially and opening up new avenues in multidisciplinary approaches by bringing together theoretical and applied aspects of science

    Microfluidic-based virus detection methods for respiratory diseases

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    With the recent SARS-CoV-2 outbreak, the importance of rapid and direct detection of respiratory disease viruses has been well recognized. The detection of these viruses with novel technologies is vital in timely prevention and treatment strategies for epidemics and pandemics. Respiratory viruses can be detected from saliva, swab samples, nasal fluid, and blood, and collected samples can be analyzed by various techniques. Conventional methods for virus detection are based on techniques relying on cell culture, antigen-antibody interactions, and nucleic acids. However, these methods require trained personnel as well as expensive equipment. Microfluidic technologies, on the other hand, are one of the most accurate and specific methods to directly detect respiratory tract viruses. During viral infections, the production of detectable amounts of relevant antibodies takes a few days to weeks, hampering the aim of prevention. Alternatively, nucleic acid–based methods can directly detect the virus-specific RNA or DNA region, even before the immune response. There are numerous methods to detect respiratory viruses, but direct detection techniques have higher specificity and sensitivity than other techniques. This review aims to summarize the methods and technologies developed for microfluidic-based direct detection of viruses that cause respiratory infection using different detection techniques. Microfluidics enables the use of minimal sample volumes and thereby leading to a time, cost, and labor effective operation. Microfluidic-based detection technologies provide affordable, portable, rapid, and sensitive analysis of intact virus or virus genetic material, which is very important in pandemic and epidemic events to control outbreaks with an effective diagnosis.Qatar National Research Fun

    Microarrays in the Diagnosis of Human Herpesvirus infections

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    Currently, there are nine known human herpesviruses and these viruses appear to have been a very common companion of humans throughout the millenia. Of human herpesviruses, herpes simplex viruses 1 and 2 (HSV-1, HSV-2), causative agents of herpes labialis and genital herpes, and varicella-zoster virus (VZV), causative agent of chicken pox, are also common causes of central nervous system (CNS) infections. In addition, human cytomegalovirus (CMV), Epstein-Barr virus (EBV) and human herpesviruses 6A, 6B, and 7 (HHV-6A, HHV-6B, HHV-7), all members of the herpesvirus family, can also be associated with encephalitis and meningitis. Accurate diagnostics and fast treatment are essential for patient recovery in CNS infections and therefore sensitive and effective diagnostic methods are needed. The aim of this thesis was to develop new potential detection methods for diagnosing of human herpesvirus infections, especially in immunocompetent patients, using the microarray technique. Therefore, methods based on microarrays were developed for simultaneous detection of HSV-1, HSV-2, VZV, CMV, EBV, HHV-6A, HHV-6B, and HHV-7 nucleic acids, and for HSV-1, HSV-2, VZV, and CMV antibodies from various clinical samples. The microarray methods developed showed potential for efficiently and accurately detecting human herpesvirus DNAs, especially in CNS infections, and for simultaneous detection of DNAs or antibodies for multiple different human herpesviruses from clinical samples. In fact, the microarray method revealed several previously unrecognized co-infections. The microarray methods developed were sensitive and provided rapid detection of human herpesvirus DNA, and therefore the method could be applied to routine diagnostics. The microarrays might also be considered as an economical tool for diagnosing human herpesvirus infections.Herpesvirukset ovat kulkeneet ihmisen kumppaneina vuosituhat toisensa jÀlkeen ja tÀllÀ hetkellÀ tunnetaan yhdeksÀn ihmiselle patogeenista herpesvirusta. Huuli- ja genitaaliherpestÀ aiheuttavat herpes simplex virus 1 ja 2 (HSV-1, HSV-2) sekÀ vesirokkoa aiheuttava varicalla-zoster virus (VZV) ovat ihmisen herpesviruksia, jotka voivat aiheuttaa myös vakavia keskushermostoperÀisiÀ infektioita. Ihmisen herpesviruksista myös ihmisen cytomegalovirus (CMV), Epstein-Barr virus (EBV), ihmisen herpesvirukset 6 ja 7 (HHV-6, HHV-7), voidaan liittÀÀ aivokuumeeseen ja aivokalvontulehdukseen. NÀiden virusten nopea ja tarkka diagnostiikka on oleellista oikean hoidon aloittamiselle sekÀ potilaan toipumiselle varsinkin keskushermostoperÀisissÀ infektioissa. Taudinaiheuttajien diagnosoimiseksi tarvitaan herkkiÀ ja tehokkaita menetelmiÀ. TÀmÀn vÀitöskirjan tavoitteina oli kehittÀÀ uusia mikrosirupohjaisia menetelmiÀ ihmisen herpesvirusten aiheuttamien infektioiden diagnostiikkaan. KehitetyillÀ mikrosiruilla tunnistettiin yhtÀ aikaa kahdeksan eri herpesviruksen nukleiinihappoa erilaisista kliinisistÀ nÀytteistÀ. Toisella serologisella mikrosirulla detektoitiin HSV-1, HSV-2, VZV ja CMV:lle spesifisiÀ vasta-aineita. Herpesvirusten nukleiinihappojen ja vasta-aineiden tunnistamiseen kehitetyt mikrosirumenetelmÀt osoittautuivat soveltuviksi usean herpesviruksen samanaikaiseen diagnosointiin. Varsinkin keskushermostopohjaisten infektioiden tunnistamisessa mikrosiru osoittautui tehokkaaksi. Mikrosirujen avulla tunnistettiin myös mahdollisia useamman viruksen samanaikaisia infektioita

    Computational and Experimental Approaches to Reveal the Effects of Single Nucleotide Polymorphisms with Respect to Disease Diagnostics

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    DNA mutations are the cause of many human diseases and they are the reason for natural differences among individuals by affecting the structure, function, interactions, and other properties of DNA and expressed proteins. The ability to predict whether a given mutation is disease-causing or harmless is of great importance for the early detection of patients with a high risk of developing a particular disease and would pave the way for personalized medicine and diagnostics. Here we review existing methods and techniques to study and predict the effects of DNA mutations from three different perspectives: in silico, in vitro and in vivo. It is emphasized that the problem is complicated and successful detection of a pathogenic mutation frequently requires a combination of several methods and a knowledge of the biological phenomena associated with the corresponding macromolecules

    New strategies for the accurate identification and detection of plant pathogens

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    Kowalchuk, G.A. [Promotor]Schoen, C. [Copromotor

    The art of PCR assay development: data-driven multiplexing

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    The present thesis describes the discovery and application of a novel methodology, named Data-Driven Multiplexing, which uses artificial intelligence and conventional molecular instruments to develop rapid, scalable and cost-effective clinical diagnostic tests. Detection of genetic material from living organisms is a biologically engineered process where organic molecules interact with each other and with chemical components to generate a meaningful signal of the presence, quantity or quality of target nucleic acids. Nucleic acid detection, such as DNA or RNA detection, identifies a specific organism based on its genetic material. In particular, DNA amplification approaches, such as for antimicrobial resistance (AMR) or COVID-19 detection, are crucial for diagnosing and managing various infectious diseases. One of the most widely used methods is Polymerase Chain Reaction (PCR), which can detect the presence of nucleic acids rapidly and accurately. The unique interaction of the genetic material and synthetic short DNA sequences called primers enable this harmonious biological process. This thesis aims to bioinformatically modulate the interaction between primers and genetic material, enhancing the diagnostic capabilities of conventional PCR instruments by applying artificial intelligence processing to the resulting signals. To achieve the goal mentioned above, experiments and data from several conventional platforms, such as real-time and digital PCR, are used in this thesis, along with state-of-the-art and innovative algorithms for classification problems and final application in real-world clinical scenarios. This work exhibits a powerful technology to optimise the use of the data, conveying the following message: the better use of the data in clinical diagnostics enables higher throughput of conventional instruments without the need for hardware modification, maintaining the standard practice workflows. In Part I, a novel method to analyse amplification data is proposed. Using a state-of-the-art digital PCR instrument and multiplex PCR assays, we demonstrate the simultaneous detection of up to nine different nucleic acids in a single-well and single-channel format. This novel concept called Amplification Curve Analysis (ACA) leverages kinetic information encoded in the amplification curve to classify the biological nature of the target of interest. This method is applied to the novel design of PCR assays for multiple detections of AMR genes and further validated with clinical samples collected at Charing Cross Hospital, London, UK. The ACA showed a high classification accuracy of 99.28% among 253 clinical isolates when multiplexing. Similar performance is also demonstrated with isothermal amplification chemistries using synthetic DNA, showing a 99.9% of classification accuracy for detecting respiratory-related infectious pathogens. In Part II, two intelligent mathematical algorithms are proposed to solve two significant challenges when developing a Data-driven multiplex PCR assay. Chapter 7 illustrates the use of filtering algorithms to remove the presence of outliers in the amplification data. This demonstrates that the information contained in the kinetics of the reaction itself provides a novel way to remove non-specific and not efficient reactions. By extracting meaningful features and adding custom selection parameters to the amplification data, we increase the machine learning classifier performance of the ACA by 20% when outliers are removed. In Chapter 8, a patented algorithm called Smart-Plexer is presented. This allows the hybrid development of multiplex PCR assays by computing the optimal single primer set combination in a multiplex assay. The algorithm's effectiveness stands in using experimental laboratory data as input, avoiding heavy computation and unreliable predictions of the sigmoidal shape of PCR curves. The output of the Smart-Plexer is an optimal assay for the simultaneous detection of seven coronavirus-related pathogens in a single well, scoring an accuracy of 98.8% in identifying the seven targets correctly among 14 clinical samples. Moreover, Chapter 9 focuses on applying novel multiplex assays in point-of-care devices and developing a new strategy for improving clinical diagnostics. In summary, inspired by the emerging requirement for more accurate, cost-effective and higher throughput diagnostics, this thesis shows that coupling artificial intelligence with assay design pipelines is crucial to address current diagnostic challenges. This requires crossing different fields, such as bioinformatics, molecular biology and data science, to develop an optimal solution and hence to maximise the value of clinical tests for nucleic acid detection, leading to more precise patient treatment and easier management of infectious control.Open Acces

    Next-generation sequencing of vertebrate experimental organisms

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    Next-generation sequencing technologies are revolutionizing biology by allowing for genome-wide transcription factor binding-site profiling, transcriptome sequencing, and more recently, whole-genome resequencing. While it is currently not possible to generate complete de novo assemblies of higher-vertebrate genomes using next-generation sequencing, improvements in sequence read lengths and throughput, coupled with new assembly algorithms for large data sets, will soon make this a reality. These developments will in turn spawn a revolution in how genomic data are used to understand genetics and how model organisms are used for disease gene discovery. This review provides an overview of the current next-generation sequencing platforms and the newest computational tools for the analysis of next-generation sequencing data. We also describe how next-generation sequencing may be applied in the context of vertebrate model organism genetics

    Functional identification of a Ligase in the Red Sea Atlantis II deepest Layer

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    Red sea, described as one of the unique marine ecosystems, incorporates up to 25 deep-sea brine pools. These pools posses multiple extreme conditions influencing the evolution and survival of their inhabiting microbial community. The combination of maximum depth (2194 m), high temperature (68C), anoxia, high salinity (26%), high pressure and high concentrations of heavy metals in the lower convective layer (LCL) of the Atlantis II brine pool makes it an ideal environment for identification of novel enzymes with unique characteristics and potential biotechnological applications. Here we describe the identification and the preliminary in vivo functional investigation of the ligase domain of an ATP-dependent DNA ligase from the DNA of the prokaryotic community extracted from water samples of the LCL of Atlantis II brine pool. Previously, these water samples were serially filtered on different membranes and the DNA isolated from the 0.1­m filter was subjected to 454 pyrosequencing. A metagenomic dataset was initiated and used in this study to mine for genes encoding DNA ligases through Pfam search of conserved domains. The search and subsequent bioinformatic analysis resulted in the identification of a contig harboring an ORF of 915 bp (305 amino acids) that encodes a putative DNA ligase (LigATII). Homology search of the putative DNA ligase showed highest similarity to Erysiopelotrichaceae Bacterium (39% identity, 54% positive). LigATII displays modular architecture that is similar to two distinct domains-(the adenylation domain of LigD and the oligonucleotide binding (OB) fold domain)-that are conserved in ATP-dependent DNA ligases. Functional annotation of the LigATII ORF, identification of the functional conserved amino acids by the Consurf tool, 3D modeling and comprehensive phylogenetic analysis were conducted. These analyses have revealed the relatedness of LigATII to the family of ATP-dependent DNA ligases that has been recently identified through computational studies to exist in prokaryotes. This family is expected to be involved in the specialized form of genomic DNA repair through the non-homologous end joining pathway which acts to join double-stranded breaks (DSBs) or to promote genetic diversity under conditions of selection pressures. Accordingly, the putative LigATII was amplified from the whole genome DNA amplification of LCL. Sanger sequencing confirmed the sequence of the gene before cloning into pET100 Topo directional expression vector. The cloned LigATII was transformed into a temperature sensitive mutant strain of Escherichia coli; strain GR501, with mutation in the DNA ligase gene. LigATII complemented the temperature sensitive strain at the non-permissive temperature (43ññ€”©C) verifying the in vivo functional activity. The biochemical characteristics of the novel LigATII protein will be described
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