Generations of sequencing technologies

Using EMBL-EBI Services via Web Interface and Programmatically via Web Services

The European Bioinformatics Institute (EMBL-EBI)'s Job Dispatcher framework provides access to a wide range of core databases and analysis tools that are of key importance in bioinformatics. As well as providing web interfaces to these resources, web services are available using REST and SOAP protocols that enable programmatic access and allow their integration into other applications and analytical workflows and pipelines. This article describes the various options available to researchers and bioinformaticians who would like to use our resources via the web interface employing RESTful web services clients provided in Perl, Python, and Java or who would like to use Docker containers to integrate the resources into analysis pipelines and workflows. © 2024 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Retrieving data from EMBL-EBI using Dbfetch via the web interface Alternate Protocol 1: Retrieving data from EMBL-EBI using WSDbfetch via the REST interface Alternate Protocol 2: Retrieving data from EMBL-EBI using Dbfetch via RESTful web services with Python client Support Protocol 1: Installing Python REST web services clients Basic Protocol 2: Sequence similarity search using FASTA search via the web interface Alternate Protocol 3: Sequence similarity search using FASTA via RESTful web services with Perl client Support Protocol 2: Installing Perl REST web services clients Basic Protocol 3: Sequence similarity search using NCBI BLAST+ RESTful web services with Python client Basic Protocol 4: Sequence similarity search using HMMER3 phmmer REST web services with Perl client and Docker Support Protocol 3: Installing Docker and running the EMBL-EBI client container Basic Protocol 5: Protein functional analysis using InterProScan 5 RESTful web services with the Python client and Docker Alternate Protocol 4: Protein functional analysis using InterProScan 5 RESTful web services with the Java client Support Protocol 4: Installing Java web services clients Basic Protocol 6: Multiple sequence alignment using Clustal Omega via web interface Alternate Protocol 5: Multiple sequence alignment using Clustal Omega with Perl client and Docker Support Protocol 5: Exploring the RESTful API with OpenAPI User Inferface.

Forensic DNA phenotyping using Oxford Nanopore Sequencing system

In forensic science, the demand for precision, consistency, and cost-effectiveness has driven the exploration of next-generation sequencing technologies. This study investigates the potential of Oxford Nanopore Sequencing (ONT) Technology for analyzing the HIrisPlex-S panel, a set of 41 single nucleotide polymorphism (SNP) markers used to predict eye, hair, and skin color. Using ONT sequencing, we assessed the accuracy and reliability of ONT-generated data by comparing it with conventional capillary electrophoresis (CE) in 18 samples. The Guppy v6.1 was used as a basecaller, and sample profiles were obtained using Burrows-Wheeler Aligner, Samtools, BCFtools, and Python. Comparing accuracy with CE, we found that 62% of SNPs in ONT-unligated samples were correctly genotyped, with 36% showing allele dropout, and 2% being incorrectly genotyped. In the ONT-ligated samples, 85% of SNPs were correctly genotyped, with 10% showing allele dropout, and 5% being incorrectly genotyped. Our findings indicate that ONT, particularly when combined with ligation, enhances genotyping accuracy and coverage, thereby reducing allele dropouts. However, challenges associated with the technology's error rates and the impact on genotyping accuracy are recognized. Phenotype predictions based on ONT data demonstrate varying degrees of success, with the technology showing high accuracy in several cases. Although ONT technology holds promise in forensic genetics, further optimization and quality control measures are essential to harness its full potential. This study contributes to the ongoing efforts to refine sequence read tuning and improve correction tools in the context of ONT technology's application in forensic genetics.

Selective Sensing of DNA Nucleobases with Angular Discrimination

The fast and precise selective sensing of DNA nucleobases is a long-pursued method that can lead to huge advances in the field of genomics and have an impact on aspects such as the prevention of diseases, health enhancement, and, in general, all types of medical treatments. We present here a new type of nanoscale sensor based on carbon nanotubes with a specific geometry that can discriminate the type of nucleobase and also its angle of orientation. The proper differentiation of nucleobases is essential to clearly sequence DNA chains, while angular discrimination is key to improving the sensing selectivity. We perform first-principle and quantum transport simulations to calculate the transmission, conductance, and current of the nanotube-based nanoscale sensor in the presence of the four nucleotides (A, C, G, and T), each of them rotated 0, 90, 180, or 270°. Our results show that this system is able to effectively discriminate between the four nucleotides and their angle of orientation. We explain these findings in terms of the interaction between the phosphate group of the nucleotide and the nanotube wall. The phosphate specifically distorts the electronic structure of the nanotube depending on the distance and the orientation and leads to nontrivial changes in the transmission. This work provides a method for finer and more precise sequential DNA chains.

RBS: A Rotational Coding Based on Blocking Strategy for DNA Storage

The data volume of global information has grown exponentially in recent years, but the development of silicon-based memory has entered a bottleneck period. Deoxyribonucleic acid (DNA) storage is drawing attention owing to its advantages of high storage density, long storage time, and easy maintenance. However, the base utilization and information density of existing DNA storage methods are insufficient. Therefore, this study proposes a rotational coding based on blocking strategy (RBS) for encoding digital information such as text and images in DNA data storage. This strategy satisfies multiple constraints and produces low error rates in synthesis and sequencing. To illustrate the superiority of the proposed strategy, it was compared and analyzed with existing strategies in terms of entropy value change, free energy size, and Hamming distance. The experimental results show that the proposed strategy has higher information storage density and better coding quality in DNA storage, so it will improve the efficiency, practicality, and stability of DNA storage.

Raman spectromics method for fast and label-free genotype screening

It is now understood that genes and their various mutations are associated with the onset and progression of diseases. However, routine genetic testing techniques are limited by their high cost, time consumption, susceptibility to contamination, complex operation, and data analysis difficulties, rendering them unsuitable for genotype screening in many cases. Therefore, there is an urgent need to develop a rapid, sensitive, user-friendly, and cost-effective method for genotype screening and analysis. In this study, we propose and investigate a Raman spectroscopic method for achieving fast and label-free genotype screening. The method was validated using spontaneous Raman measurements of wild-type Cryptococcus neoformans and its six mutants. An accurate identification of different genotypes was achieved by employing a one-dimensional convolutional neural network (1D-CNN), and significant correlations between metabolic changes and genotypic variations were revealed. Genotype-specific regions of interest were also localized and visualized using a gradient-weighted class activation mapping (Grad-CAM)-based spectral interpretable analysis method. Furthermore, the contribution of each metabolite to the final genotypic decision-making was quantified. The proposed Raman spectroscopic method demonstrated huge potential for fast and label-free genotype screening and analysis of conditioned pathogens.

Systems Biology of Ageing

The ageing process is highly complex involving multiple processes operating at different biological levels. Systems Biology presents an approach using integrative computational and laboratory study that allows us to address such complexity. The approach relies on the computational analysis of knowledge and data to generate predictive models that may be validated with further laboratory experimentation. Our understanding of ageing is such that translational opportunities are within reach and systems biology offers a means to ensure that optimal decisions are made. We present an overview of the methods employed from bioinformatics and computational modelling and describe some of the insights into ageing that have been gained.

Relevant biomarkers of kidney allograft rejection

This review focuses on the new relevant biomarkers proposed for the diagnosis of different types of allograft rejections. The immune response against the transplanted tissues can lead to rejection. Kidney allograft rejection occurs when the recipient component's immune system reacts against the donor's cells. MicroRNAs, dd-cf DNA, CD103 markers, CXCR3 chemokine receptor, IP-10, KIR genes, HLA antibodies, the perforin and granzyme B molecules - the constant assessment of all these parameters could prevent acute rejection episodes and kidney injuries. In this way, both immune response and tissue destruction biomarkers are essential for the long-term survival of kidney-transplanted patients. They also contribute to personalizing treatments, precisely personalized immunosuppressive regiments.

Research on safety and compliance of imported microbial inoculants using high-throughput sequencing

Microbial inoculants are widely used in wastewater treatment, soil remediation, and biological control. Safety and compliance for active constituents are considered to be the most important measures of imported microbial inoculants. Microbial inoculants composition was commonly identified by phenotypic culture, which is time-consuming and labor intense with occasionally false negative results provided, and can only be tested for specific species. High-throughput sequencing (HTS), known for its non-targeted detection of unknown species composition in samples, is suitable for composition consistency identification and biosafety analysis of imported microbial inoculants. In this study, the application of HTS for microflora distribution and resistance gene was verified in microbial inoculants for environmental protection and then applicated in imported microbial inoculants. Both Illumina- and Nanopore-based HTS methods identified the same dominant bacterial species successfully in the imported microbial inoculants. The main component of bacterial species was Bacillus subtilis, Bacillus amyloliquefaciens, Bacillus licheniformis, and Enterococcus faecium, and further confirmed with traditional methods. The antibiotic resistance genes Bacillus subtilis mprF, bcrA, blt, lmrB, rphB, tet(L), tmrB, vmlR, ykkC, and ykkD were detected in all samples. Our results indicated that HTS processes the application potential to identify the active ingredients of microbial inoculants. Therefore, rapid and accurate identification of the microbial compositions in microbial formulation products is of high importance for port biosafety supervision.

Artificial Intelligence in Biological Sciences

Artificial intelligence (AI), currently a cutting-edge concept, has the potential to improve the quality of life of human beings. The fields of AI and biological research are becoming more intertwined, and methods for extracting and applying the information stored in live organisms are constantly being refined. As the field of AI matures with more trained algorithms, the potential of its application in epidemiology, the study of host–pathogen interactions and drug designing widens. AI is now being applied in several fields of drug discovery, customized medicine, gene editing, radiography, image processing and medication management. More precise diagnosis and cost-effective treatment will be possible in the near future due to the application of AI-based technologies. In the field of agriculture, farmers have reduced waste, increased output and decreased the amount of time it takes to bring their goods to market due to the application of advanced AI-based approaches. Moreover, with the use of AI through machine learning (ML) and deep-learning-based smart programs, one can modify the metabolic pathways of living systems to obtain the best possible outputs with the minimal inputs. Such efforts can improve the industrial strains of microbial species to maximize the yield in the bio-based industrial setup. This article summarizes the potentials of AI and their application to several fields of biology, such as medicine, agriculture, and bio-based industry.

Application of next-generation sequencing in the diagnosis of gastric cancer

Objectives: Gastric cancer (GC) is a disease with high mortality, poor prognosis and numerous risk factors. GC has an asymptomatic nature in early stages of the diseases, making timely diagnosis complicated using common conventional approaches, namely pathological examinations and imaging tests. Recently, molecular profiling of GC using next generation sequencing (NGS) has opened new doors to efficient prognostic, diagnostic, and therapeutic strategies. The current review aims to thoroughly discuss and compare the current NGS techniques and commercial platforms utilized for GC diagnosis and treatment, highlighting the most recent NGS-based GC studies. Furthermore, this review addresses the challenges of clinical implementation of NGS in GC.Materials and methods: This review was conducted according to the eligible studies identified via search of Web of Science, PubMed, Scopus, Embase and the Cochrane Library. In the present study, data on gastric cancer patients and NGS methods used to diagnose the disease were reviewed.Conclusion: Given the ever-rising advancements in NGS technologies, bioinformatics, healthcare guidelines and refined classifications, it is hoped that these technologies can actualize their advantages and optimize GC patients' experience.

Metagenomic Analysis Using Phylogenetic Placement-A Review of the First Decade

Phylogenetic placement refers to a family of tools and methods to analyze, visualize, and interpret the tsunami of metagenomic sequencing data generated by high-throughput sequencing. Compared to alternative (e. g., similarity-based) methods, it puts metabarcoding sequences into a phylogenetic context using a set of known reference sequences and taking evolutionary history into account. Thereby, one can increase the accuracy of metagenomic surveys and eliminate the requirement for having exact or close matches with existing sequence databases. Phylogenetic placement constitutes a valuable analysis tool per se, but also entails a plethora of downstream tools to interpret its results. A common use case is to analyze species communities obtained from metagenomic sequencing, for example via taxonomic assignment, diversity quantification, sample comparison, and identification of correlations with environmental variables. In this review, we provide an overview over the methods developed during the first 10 years. In particular, the goals of this review are 1) to motivate the usage of phylogenetic placement and illustrate some of its use cases, 2) to outline the full workflow, from raw sequences to publishable figures, including best practices, 3) to introduce the most common tools and methods and their capabilities, 4) to point out common placement pitfalls and misconceptions, 5) to showcase typical placement-based analyses, and how they can help to analyze, visualize, and interpret phylogenetic placement data.

Functional Metagenomics for Identification of Antibiotic Resistance Genes (ARGs)

The identification of antibiotic resistance genes (ARGs) in microbial communities is one of the most challenging tasks in biology. The evolution and improvement of genome sequencing techniques, combined with the improvement of computational analysis techniques, have allowed us to acquire increasingly detailed information on the complex and varied microbial community that coexists and coevolves in the most heterogeneous environment. This chapter describes how to identify and quantify ARGs, using specific tools (Bowtie2, Bedtools for coverage, G/C content, and the estimated number of reads mapping each open reading frame; RGI tool, with the support of CARD database, to inspect the distribution of antibiotic resistance genes). Once this information is obtained, scientists would be able to highlight the relative abundance of ARGs in the metagenome analyzed and be able to understand how antibiotic resistance mechanisms evolve in microbial communities.

Exploring the global metagenome for plastic-degrading enzymes

Plastics are extensively used in our daily life, but they are also a major pollutant of our biosphere accumulating in both the ocean and the land. In the recent years, few enzymes and microorganisms have been discovered with the ability to degrade even fewer synthetic polymers. Nevertheless, more active species and enzymes need to be discovered and described in order to gain more knowledge about protein adaptation to the degradation of not-naturally-occurring polymers. Within this chapter, we focus on efficient methods to identify novel polyethylene terephthalate-degrading enzymes (PETases) from culturable and non-culturable microorganisms by a combination of sequence- and function-based screening. This protocol can be adapted to discover other plastic hydrolases and in general for other enzymes, for which not many characterized specimens are yet available.

Harnessing the plant microbiome to promote the growth of agricultural crops

The rhizosphere microbiome is composed of diverse microbial organisms, including archaea, viruses, fungi, bacteria as well as eukaryotic microorganisms, which occupy a narrow region of soil directly associated with plant roots. The interactions between these microorganisms and the plant can be commensal, beneficial or pathogenic. These microorganisms can also interact with each other, either competitively or synergistically. Promoting plant growth by harnessing the soil microbiome holds tremendous potential for providing an environmentally friendly solution to the increasing food demands of the world's rapidly growing population, while also helping to alleviate the associated environmental and societal issues of large-scale food production. There recently have been many studies on the disease suppression and plant growth promoting abilities of the rhizosphere microbiome; however, these findings largely have not been translated into the field. Therefore, additional research into the dynamic interactions between crop plants, the rhizosphere microbiome and the environment are necessary to better guide the harnessing of the microbiome to increase crop yield and quality. This review explores the biotic and abiotic interactions that occur within the plant's rhizosphere as well as current agricultural practices, and how these biotic and abiotic factors, as well as human practices, impact the plant microbiome. Additionally, some limitations, safety considerations, and future directions to the study of the plant microbiome are discussed.

Genomic Profiling: The Strengths and Limitations of Chloroplast Genome-Based Plant Variety Authentication

Genomic profiling is a suitable tool for variety authentication and has applications in both operational quality and regulatory raw material control. It can be used to differentiate species or varieties and to identify admixtures as well as field contaminants. To establish a molecular profile, reliable and very accurate sequence data are required. As a result of the influence of the pollinator plant, nuclear genome-based authentication is in most cases not suitable for a direct application on the fruit. Sequences must be used that come exclusively from the localized mother plant. Parts of the fruit of maternal origin, e.g., components derived from the blossom, are suitable as a basis for this. Alternatively, DNA from cell organelles that are maternally inherited, such as mitochondria or chloroplasts, can be used. The latter will be discussed in this review in closer detail. Although individual gene segments on the chloroplast genome are already used for species differentiation in barcoding studies on plants, little is known about the usefulness of the entire chloroplast genome for intraspecies differentiation in general and for differentiation between modern varieties in particular. Results from the literature as well as from our own work suggest that chloroplast genome sequences are indeed very well-suited for the differentiation of old varieties. On the other hand, they are less or not suitable for the genetic differentiation of modern cultivars, because they are often too closely related.

Cancer gene expression profiles associated with clinical outcomes to chemotherapy treatments

Background

Machine learning (ML) methods still have limited applicability in personalized oncology due to low numbers of available clinically annotated molecular profiles. This doesn’t allow sufficient training of ML classifiers that could be used for improving molecular diagnostics.

Methods

We reviewed published datasets of high throughput gene expression profiles corresponding to cancer patients with known responses on chemotherapy treatments. We browsed Gene Expression Omnibus (GEO), The Cancer Genome Atlas (TCGA) and Tumor Alterations Relevant for GEnomics-driven Therapy (TARGET) repositories.

Results

We identified data collections suitable to build ML models for predicting responses on certain chemotherapeutic schemes. We identified 26 datasets, ranging from 41 till 508 cases per dataset. All the datasets identified were checked for ML applicability and robustness with leave-one-out cross validation. Twenty-three datasets were found suitable for using ML that had balanced numbers of treatment responder and non-responder cases.

Conclusions

We collected a database of gene expression profiles associated with clinical responses on chemotherapy for 2786 individual cancer cases. Among them seven datasets included RNA sequencing data (for 645 cases) and the others – microarray expression profiles. The cases represented breast cancer, lung cancer, low-grade glioma, endothelial carcinoma, multiple myeloma, adult leukemia, pediatric leukemia and kidney tumors. Chemotherapeutics included taxanes, bortezomib, vincristine, trastuzumab, letrozole, tipifarnib, temozolomide, busulfan and cyclophosphamide.

ARDEP, a Rapid Degenerate Primer Design Pipeline Based on k-mers for Amplicon Microbiome Studies

The survey of microbial diversity in various environments has relied upon the widespread use of well-evaluated amplification primers for taxonomic marker genes (e.g., prokaryotic 16S and fungal ITS). However, it is urgent to develop a fast and accurate bioinformatic program to design primers for microbial functional genes to explore more mechanisms in the microbial community. Here, we provide a rapid degenerate primer design pipeline (ARDEP) based on the k-mer algorithm, which can bypass the time-consuming step of sequence alignment to greatly reduce run times while ensuring accuracy. In addition, we developed an open-access platform for the implementation of primer design projects that could also calculate the amplification product length, GC content, Annealing Temperature (Tm), and ΔG of primer self-folding, and identify covered species and functional groups. Using this new platform, we designed primers for several functional genes in the nitrogen cycle, including napA and amoA. Our newly designed primers achieved higher coverage than the commonly used primers for all tested genes. The program and the associated platform that applied the k-mer algorithm could greatly enhance the design and evaluation of primers for environmental microbiome studies.

LncRNA H19 Regulates BMP2-Induced Hypertrophic Differentiation of Mesenchymal Stem Cells by Promoting Runx2 Phosphorylation

Objectives

Bone morphogenetic protein 2 (BMP2) triggers hypertrophic differentiation after chondrogenic differentiation of mesenchymal stem cells (MSCs), which blocked the further application of BMP2-mediated cartilage tissue engineering. Here, we investigated the underlying mechanisms of BMP2-mediated hypertrophic differentiation of MSCs.

Materials and Methods

In vitro and in vivo chondrogenic differentiation models of MSCs were constructed. The expression of H19 in mouse limb was detected by fluorescence in situ hybridization (FISH) analysis. Transgenes BMP2, H19 silencing, and overexpression were expressed by adenoviral vectors. Gene expression was determined by reverse transcription and quantitative real-time PCR (RT-qPCR), Western blot, and immunohistochemistry. Correlations between H19 expressions and other parameters were calculated with Spearman’s correlation coefficients. The combination of H19 and Runx2 was identified by RNA immunoprecipitation (RIP) analysis.

Results

We identified that H19 expression level was highest in proliferative zone and decreased gradually from prehypertrophic zone to hypertrophic zone in mouse limbs. With the stimulation of BMP2, the highest expression level of H19 was followed after the peak expression level of Sox9; meanwhile, H19 expression levels were positively correlated with chondrogenic differentiation markers, especially in the late stage of BMP2 stimulation, and negatively correlated with hypertrophic differentiation markers. Our further experiments found that silencing H19 promoted BMP2-triggered hypertrophic differentiation through in vitro and in vivo tests, which indicated the essential role of H19 for maintaining the phenotype of BMP2-induced chondrocytes. In mechanism, we characterized that H19 regulated BMP2-mediated hypertrophic differentiation of MSCs by promoting the phosphorylation of Runx2.

Conclusion

These findings suggested that H19 regulates BMP2-induced hypertrophic differentiation of MSCs by promoting the phosphorylation of Runx2.

Simultaneous Detection of Gene Fusions and Base Mutations in Cancer Tissue Biopsies by Sequencing Dual Nucleic Acid Templates in Unified Reaction

BACKGROUND

Targeted next-generation sequencing is a powerful method to comprehensively identify biomarkers for cancer. Starting material is currently either DNA or RNA for different variations, but splitting to 2 assays is burdensome and sometimes unpractical, causing delay or complete lack of detection of critical events, in particular, potent and targetable fusion events. An assay that analyzes both templates in a streamlined process is eagerly needed.

METHODS

We developed a single-tube, dual-template assay and an integrated bioinformatics pipeline for relevant variant calling. RNA was used for fusion detection, whereas DNA was used for single-nucleotide variations (SNVs) and insertion and deletions (indels). The reaction chemistry featured barcoded adaptor ligation, multiplexed linear amplification, and multiplexed PCR for noise reduction and novel fusion detection. An auxiliary quality control assay was also developed.

RESULTS

In a 1000-sample lung tumor cohort, we identified all major SNV/indel hotspots and fusions, as well as MET exon 14 skipping and several novel or rare fusions. The occurrence frequencies were in line with previous reports and were verified by Sanger sequencing. One noteworthy fusion event was HLA-DRB1-MET that constituted the second intergenic MET fusion ever detected in lung cancer.

CONCLUSIONS

This method should benefit not only a majority of patients carrying core actionable targets but also those with rare variations. Future extension of this assay to RNA expression and DNA copy number profiling of target genes such as programmed death-ligand 1 may provide additional biomarkers for immune checkpoint therapies.

Applications of the Soil, Plant and Rumen Microbiomes in Pastoral Agriculture

The production of dairy, meat, and fiber by ruminant animals relies on the biological processes occurring in soils, forage plants, and the animals' rumens. Each of these components has an associated microbiome, and these have traditionally been viewed as distinct ecosystems. However, these microbiomes operate under similar ecological principles and are connected via water, energy flows, and the carbon and nitrogen nutrient cycles. Here, we summarize the microbiome research that has been done in each of these three environments (soils, forage plants, animals' rumen) and investigate what additional benefits may be possible through understanding the interactions between the various microbiomes. The challenge for future research is to enhance microbiome function by appropriate matching of plant and animal genotypes with the environment to improve the output and environmental sustainability of pastoral agriculture.

Acute Vector-Borne Viral Infection: Zika and MinION Surveillance

The MinION sequencer was launched by the Oxford Nanopore Technologies start-up as a disruptive technology for genome sequencing based on single-molecule synthesis. Its characteristics as a portable device, low cost, and simple library preparation have made it a good candidate for field researchers. MinION has been used to sequence a number of microorganisms, such as bacteria, viruses, and fungi. Based on the experience that characterized the Ebola virus genetic diversity in Guinea during the 2014-2015 outbreak, the ZiBRA (Zika in Brazil Real-time Analysis) project aimed to sequence a large number of Zika virus genomes during a mobile laboratory trip in northeast Brazil to provide important epidemiological information about the spread of this disease in this country. In response to the positive and rapid results obtained by the ZiBRA project, the Brazilian Ministry of Health and many leading institutions, such as the Pan American Health Organization and WHO, have shown interest in expanding the strategy used in this project to other countries dealing with arbovirus infection. *This article is part of a curated collection.

Using EMBL-EBI Services via Web Interface and Programmatically via Web Services

The European Bioinformatics Institute (EMBL-EBI) provides access to a wide range of core databases and analysis tools that are of key importance in bioinformatics. As well as providing web interfaces to these resources, web services are available using REST and SOAP protocols that enable programmatic access and allow their integration into other applications and analytical workflows and pipelines. This article describes the various options available to researchers and bioinformaticians who would like to use our resources via the web interface employing RESTful web service clients provided in Perl, Python, and Java, or would like to use Docker containers to integrate the resources into analysis pipelines and workflows. © 2019 by John Wiley & Sons, Inc.

Epstein-Barr virus latent gene EBNA-1 genetic diversity among transplant patients compared with patients with infectious mononucleosis

INTRODUCTION

As a step toward evaluating the association between Epstein-Barr virus genetic diversity and post-transplant lymphoproliferative disorder (PTLD), we conducted a preliminary study to compare the genetic diversity of the EBNA-1 gene among transplant patients and patients with infectious mononucleosis (IM).

METHODS

We sequenced the EBNA-1 gene in blood samples from study subjects using Sanger methodology. The sequences were aligned with a reference strain and compared with publicly available sequences.

RESULTS

We analyzed 33 study samples and 25 publicly available sequences along with the reference strain B95-8. The evaluable samples were from sixteen patients with IM (median age 14.0 years, range 2-24) and 17 transplant patients. There were six children without PTLD (median age 1.93 years, range 0.79-7.46) and 11 who developed PTLD (median age 5.67 years, range 0.96-17.45). A predominant EBNA-1 variant (P-thr) was identified across the study groups. Differences were observed between the samples from the IM patients compared with the transplant samples.

CONCLUSION

The predominant EBNA-1 strain is in contrast to reports of the predominant strain in North America. The results suggest differences between the EBNA-1 strains among the study groups. Further studies will examine the relationship between EBNA-1 strains and PTLD occurrence and outcomes.

Chicken Gut Microbiota: Importance and Detection Technology

Sustainable poultry meat and egg production is important to provide safe and quality protein sources in human nutrition worldwide. The gastrointestinal (GI) tract of chickens harbor a diverse and complex microbiota that plays a vital role in digestion and absorption of nutrients, immune system development and pathogen exclusion. However, the integrity, functionality, and health of the chicken gut depends on many factors including the environment, feed, and the GI microbiota. The symbiotic interactions between host and microbe is fundamental to poultry health and production. The diversity of the chicken GI microbiota is largely influenced by the age of the birds, location in the digestive tract and diet. Until recently, research on the poultry GI microbiota relied on conventional microbiological techniques that can only culture a small proportion of the complex community comprising the GI microbiota. 16S rRNA based next generation sequencing is a powerful tool to investigate the biological and ecological roles of the GI microbiota in chicken. Although several challenges remain in understanding the chicken GI microbiome, optimizing the taxonomic composition and biochemical functions of the GI microbiome is an attainable goal in the post-genomic era. This article reviews the current knowledge on the chicken GI function and factors that influence the diversity of gut microbiota. Further, this review compares past and current approaches that are used in chicken GI microbiota research. A better understanding of the chicken gut function and microbiology will provide us new opportunities for the improvement of poultry health and production.

A Next-Generation Sequencing-Based Platform for Quantitative Detection of Hepatitis B Virus Pre-S Mutants in Plasma of Hepatocellular Carcinoma Patients

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related death worldwide. Early diagnosis and treatment of HCC remain a key goal for improving patient survival. Chronic hepatitis B virus (HBV) infection is a major risk factor for HCC development. Pre-S mutants harboring deletions in HBV large surface antigen have been well demonstrated as HBV oncoproteins that dysregulate multiple signaling pathways in hepatocytes, leading to HCC formation. The presence of pre-S mutants in plasma represents important predictive and prognostic markers for HCC in patients with chronic HBV infection. However, the method to detect pre-S mutants remains to be optimized. In this study, we developed a platform, based on the next-generation sequencing (NGS) technology, for detection of pre-S mutants in plasma of HBV-related HCC patients. Compared to the current TA cloning-based analysis, the NGS-based analysis could detect pre-S deletion quantitatively, and the detection rate was significantly more sensitive in 49 plasma analyzed (McNemar's paired proportion test, P value < 0.0001; simple kappa coefficient, κ = 0.29 (95% CI, 0.12 to 0.46)). Our data suggest that the NGS-based platform may hold a promise for improving the clinical application of pre-S mutants in serving as predictive and prognostic markers for HBV-related HCC.

Panorama general de los organismos genéticamente modificados en Colombia y en el mundo: Capacidad nacional de detección

Los organismos genéticamente modificados (OGM) y en particular los cultivos genéticamente modificados (GM), son el resultado de la modificación de la información genética de una especie a partir del uso de la biotecnología moderna para proporcionar nuevas características que su contraparte no modificada no posee, tales como resistencia a insectos, tolerancia a herbicidas, contenido de nutrientes entre otros. La mayor parte de estos cultivos se concentran en cuatro productos: soya (Glycine max), maíz (Zea Mays), canola (Brassica napus) y algodón (Gossypium hirsutum); y los principales productores son Estados Unidos, Brasil, Argentina, India y Canadá. Por su parte, Colombia ocupa el puesto 18 con cultivos de maíz, algodón y claveles azules. La introducción de estas especies en cualquier mercado está limitada por la legislación propia del país destino, así como por los estudios que permiten establecer su efecto sobre el medio ambiente, la salud humana y animal; en este sentido, la precisión y confianza de las técnicas analíticas empleadas en la evaluación del contenido de OGM son un elemento importante para la toma de decisiones basadas en evidencias objetivas, especialmente frente al debate en torno a su uso. Este documento presenta una revisión de las tecnologías de análisis más importantes disponibles a nivel mundial, frente a las capacidades nacionales para su detección.

Bioinformatical identification of key pathways and genes in human hepatocellular carcinoma after CSN5 depletion

Hepatocellular carcinoma (HCC) is the most common type of primary liver cancer. It has been previously reported that CSN5 depletion is an effective method in human HCC. In the current study, we aimed to uncover gene signatures and key pathways during HCC. Gene expression profiles of GSE26485 were downloaded from GEO database. Totally, 101 differentially expressed genes (DEGs) were up-regulated and 146 ones were down-regulated. Biological processes (BP) and Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) analysis showed that the DEGs were mainly enriched in regulation of cell growth, oxidation-reduction process, mitotic cytokinesis, negative regulation of macroautophagy, endosome organization, lysosome, biosynthesis of antibiotics, small cell lung cancer and glutathione metabolism and so on (P < 0.05). Protein-protein interaction (PPI) network, Kaplan-Meier, log-rank method, western blot, immunohistochemistry and encyclopedia of DNA elements (ENCODE) analysis showed that CSN5 depletion took effects through down-regulation of SMAD5-related pathways which include EXO1, CENPA and NCAPG, resulting in the inactivation of H3K4me3 and H3K36me3. Those genes represent the promising targets for therapeutic intervention in HCC patients.

Necessary Sequencing Depth and Clustering Method to Obtain Relatively Stable Diversity Patterns in Studying Fish Gut Microbiota

The 16S rRNA gene is one of the most commonly used molecular markers for estimating bacterial diversity during the past decades. However, there is no consistency about the sequencing depth (from thousand to millions of sequences per sample), and the clustering methods used to generate OTUs may also be different among studies. These inconsistent premises make effective comparisons among studies difficult or unreliable. This study aims to examine the necessary sequencing depth and clustering method that would be needed to ensure a stable diversity patterns for studying fish gut microbiota. A total number of 42 samples dataset of Siniperca chuatsi (carnivorous fish) gut microbiota were used to test how the sequencing depth and clustering may affect the alpha and beta diversity patterns of fish intestinal microbiota. Interestingly, we found that the sequencing depth (resampling 1000-11,000 per sample) and the clustering methods (UPARSE and UCLUST) did not bias the estimates of the diversity patterns during the fish development from larva to adult. Although we should acknowledge that a suitable sequencing depth may differ case by case, our finding indicates that a shallow sequencing such as 1000 sequences per sample may be also enough to reflect the general diversity patterns of fish gut microbiota. However, we have shown in the present study that strict pre-processing of the original sequences is required to ensure reliable results. This study provides evidences to help making a strong scientific choice of the sequencing depth and clustering method for future studies on fish gut microbiota patterns, but at the same time reducing as much as possible the costs related to the analysis.

A Combined PLS and Negative Binomial Regression Model for Inferring Association Networks from Next-Generation Sequencing Count Data

A major challenge of genomics data is to detect interactions displaying functional associations from large-scale observations. In this study, a new cPLS-algorithm combining partial least squares approach with negative binomial regression is suggested to reconstruct a genomic association network for high-dimensional next-generation sequencing count data. The suggested approach is applicable to the raw counts data, without requiring any further pre-processing steps. In the settings investigated, the cPLS-algorithm outperformed the two widely used comparative methods, graphical lasso, and weighted correlation network analysis. In addition, cPLS is able to estimate the full network for thousands of genes without major computational load. Finally, we demonstrate that cPLS is capable of finding biologically meaningful associations by analyzing an example data set from a previously published study to examine the molecular anatomy of the craniofacial development.

Massive Sequencing: A New Tool for the Control of Alcoholic Fermentation in Wine?

In wine industry, there is a prevalent use of starter cultures to promote a controlled and efficient alcoholic fermentation preventing the growth of spoilage microbes. However, current trends in enology aim to combine the guaranteed success of monitored process and the complexity of fermentations either by inoculating autochthonous starters or by performing spontaneously to produce distinctive wines. To understand the complex roles of microorganisms on wine fermentation, we must understand their population dynamics and their relationships with wine quality and metabolome. Current metagenomics techniques based on massive sequencing are gaining relevance to study the diversity and evolution of microbial population on every stage of the wine making process. This new tool and technique increases the throughput and sensitivity to study microbial communities. This review focuses on the current knowledge about wine alcoholic fermentation, the contribution of massive sequencing techniques and the possibility of using this tool for microbial control.

Origins of biological function in DNA and RNA hairpin loop motifs from replica exchange molecular dynamics simulation

Temperature REMD reveals how local chemical changes can result in markedly differing conformational landscapes for DNA and RNA hairpin loops.

Comparative immunogenomics of molluscs

Comparative immunology, studying both vertebrates and invertebrates, provided the earliest descriptions of phagocytosis as a general immune mechanism. However, the large scale of animal diversity challenges all-inclusive investigations and the field of immunology has developed by mostly emphasizing study of a few vertebrate species. In addressing the lack of comprehensive understanding of animal immunity, especially that of invertebrates, comparative immunology helps toward management of invertebrates that are food sources, agricultural pests, pathogens, or transmit diseases, and helps interpret the evolution of animal immunity. Initial studies showed that the Mollusca (second largest animal phylum), and invertebrates in general, possess innate defenses but lack the lymphocytic immune system that characterizes vertebrate immunology. Recognizing the reality of both common and taxon-specific immune features, and applying up-to-date cell and molecular research capabilities, in-depth studies of a select number of bivalve and gastropod species continue to reveal novel aspects of molluscan immunity. The genomics era heralded a new stage of comparative immunology; large-scale efforts yielded an initial set of full molluscan genome sequences that is available for analyses of full complements of immune genes and regulatory sequences. Next-generation sequencing (NGS), due to lower cost and effort required, allows individual researchers to generate large sequence datasets for growing numbers of molluscs. RNAseq provides expression profiles that enable discovery of immune genes and genome sequences reveal distribution and diversity of immune factors across molluscan phylogeny. Although computational de novo sequence assembly will benefit from continued development and automated annotation may require some experimental validation, NGS is a powerful tool for comparative immunology, especially increasing coverage of the extensive molluscan diversity. To date, immunogenomics revealed new levels of complexity of molluscan defense by indicating sequence heterogeneity in individual snails and bivalves, and members of expanded immune gene families are expressed differentially to generate pathogen-specific defense responses.

Construction & establishment of two minigenome rescue systems for Chandipura virus driven by recombinant vaccinia virus expressing T7 polymerase

Background & objectives:

Chandipura virus (CHPV) is an emerging pathogenic rhabdovirus with a high case fatality rate. There are no reports of a minigenome system for CHPV, which could help its study without having to use the infectious agent. This study was, therefore, undertaken for the establishment of T7 polymerase-driven minigenome system for CHPV.

Methods:

The minigenome rescue system for CHPV consists of three helper plasmids expressing the nucleocapsid protein (N), phosphoprotein (P) and large protein (L) based on a recombinant vaccinia virus expressing bacteriophage T7 polymerase (vTF7-3). The minigenome construct is composed of a reporter gene, flanked by the non-coding regions of CHPV. Two minigenomes were constructed in an antigenome or complimentary sense, expressing luciferase or green fluorescent protein (GFP). The minigenome system was evaluated by co-transfection of the minigenome construct and three helper plasmids into CV-1 cells and analysis of the reporter gene activity.

Results:

All the helper proteins were expressed from the helper plasmids confirmed by Western blotting. Expression of reporter genes was observed from both the GFP and luciferase-based minigenomes. Green fluorescence could be visualized directly in live CV-1 cells. Luciferase activity was found to be significantly different from control.

Interpretation & conclusions:

The results showed that the helper plasmids provided all the necessary viral structural proteins required for the production of minigenome mRNA template, which in turn could rescue the expression of reporter genes. Thus, these minigenomes can be applied to mimic the manifestation of CHPV life cycle.

Whole-genome sequencing approaches for conservation biology: Advantages, limitations and practical recommendations

Whole-genome resequencing (WGR) is a powerful method for addressing fundamental evolutionary biology questions that have not been fully resolved using traditional methods. WGR includes four approaches: the sequencing of individuals to a high depth of coverage with either unresolved or resolved haplotypes, the sequencing of population genomes to a high depth by mixing equimolar amounts of unlabelled-individual DNA (Pool-seq) and the sequencing of multiple individuals from a population to a low depth (lcWGR). These techniques require the availability of a reference genome. This, along with the still high cost of shotgun sequencing and the large demand for computing resources and storage, has limited their implementation in nonmodel species with scarce genomic resources and in fields such as conservation biology. Our goal here is to describe the various WGR methods, their pros and cons and potential applications in conservation biology. WGR offers an unprecedented marker density and surveys a wide diversity of genetic variations not limited to single nucleotide polymorphisms (e.g., structural variants and mutations in regulatory elements), increasing their power for the detection of signatures of selection and local adaptation as well as for the identification of the genetic basis of phenotypic traits and diseases. Currently, though, no single WGR approach fulfils all requirements of conservation genetics, and each method has its own limitations and sources of potential bias. We discuss proposed ways to minimize such biases. We envision a not distant future where the analysis of whole genomes becomes a routine task in many nonmodel species and fields including conservation biology.

Diagnosis of mycobacteria in bovine milk: an overview

Tuberculosis remains as the world's biggest threat. In 2014, human tuberculosis ranked as a major infectious disease by the first time, overcoming HIV death rates. Bovine tuberculosis is a chronic disease of global distribution that affects animals and can be transmitted to humans by the consumption of raw milk, representing a serious public health concern. Despite the efforts of different countries to control and eradicate bovine tuberculosis, the high negative economic impact on meat and milk production chains remains, given the decreased production efficiency (approximately 25%), the high number of condemned carcasses, and increased animal culling rates. This scenario has motivated the establishment of official programs based on regulations and diagnostic procedures. Although Mycobacterium tuberculosis and Mycobacterium bovis are the major pathogenic species to humans and bovines, respectively, nontuberculous mycobacteria within the Mycobacterium genus have become increasingly important in recent decades due to human infections, including the ones that occur in immunocompetent people. Diagnosis of mycobacteria can be performed by microbiological culture from tissue samples (lymph nodes, lungs) and secretions (sputum, milk). In general, these pathogens demand special nutrient requirements for isolation/growth, and the use of selective and rich culture media. Indeed, within these genera, mycobacteria are classified as either fast- or slow-growth microorganisms. Regarding the latter ones, incubation times can vary from 45 to 90 days. Although microbiological culture is still considered the gold standard method for diagnosis, molecular approaches have been increasingly used. We describe here an overview of the diagnosis of Mycobacterium species in bovine milk.

The Grapevine and Wine Microbiome: Insights from High-Throughput Amplicon Sequencing

From the time when microbial activity in wine fermentation was first demonstrated, the microbial ecology of the vineyard, grape, and wine has been extensively investigated using culture-based methods. However, the last 2 decades have been characterized by an important change in the approaches used for microbial examination, due to the introduction of DNA-based community fingerprinting methods such as DGGE, SSCP, T-RFLP, and ARISA. These approaches allowed for the exploration of microbial community structures without the need to cultivate, and have been extensively applied to decipher the microbial populations associated with the grapevine as well as the microbial dynamics throughout grape berry ripening and wine fermentation. These techniques are well-established for the rapid more sensitive profiling of microbial communities; however, they often do not provide direct taxonomic information and possess limited ability to detect the presence of rare taxa and taxa with low abundance. Consequently, the past 5 years have seen an upsurge in the application of high-throughput sequencing methods for the in-depth assessment of the grapevine and wine microbiome. Although a relatively new approach in wine sciences, these methods reveal a considerably greater diversity than previously reported, and identified several species that had not yet been reported. The aim of the current review is to highlight the contribution of high-throughput next generation sequencing and metagenomics approaches to vineyard microbial ecology especially unraveling the influence of vineyard management practices on microbial diversity.

Genome Sequencing

Genome sequencing is an important step toward correlating genotypes with phenotypic characters. Sequencing technologies are important in many fields in the life sciences, including functional genomics, transcriptomics, oncology, evolutionary biology, forensic sciences, and many more. The era of sequencing has been divided into three generations. First generation sequencing involved sequencing by synthesis (Sanger sequencing) and sequencing by cleavage (Maxam-Gilbert sequencing). Sanger sequencing led to the completion of various genome sequences (including human) and provided the foundation for development of other sequencing technologies. Since then, various techniques have been developed which can overcome some of the limitations of Sanger sequencing. These techniques are collectively known as "Next-generation sequencing" (NGS), and are further classified into second and third generation technologies. Although NGS methods have many advantages in terms of speed, cost, and parallelism, the accuracy and read length of Sanger sequencing is still superior and has confined the use of NGS mainly to resequencing genomes. Consequently, there is a continuing need to develop improved real time sequencing techniques. This chapter reviews some of the options currently available and provides a generic workflow for sequencing a genome.

apex: phylogenetics with multiple genes

Genetic sequences of multiple genes are becoming increasingly common for a wide range of organisms including viruses, bacteria and eukaryotes. While such data may sometimes be treated as a single locus, in practice, a number of biological and statistical phenomena can lead to phylogenetic incongruence. In such cases, different loci should, at least as a preliminary step, be examined and analysed separately. The r software has become a popular platform for phylogenetics, with several packages implementing distance-based, parsimony and likelihood-based phylogenetic reconstruction, and an even greater number of packages implementing phylogenetic comparative methods. Unfortunately, basic data structures and tools for analysing multiple genes have so far been lacking, thereby limiting potential for investigating phylogenetic incongruence. In this study, we introduce the new r package apex to fill this gap. apex implements new object classes, which extend existing standards for storing DNA and amino acid sequences, and provides a number of convenient tools for handling, visualizing and analysing these data. In this study, we introduce the main features of the package and illustrate its functionalities through the analysis of a simple data set.

Molecular Strain Typing of Mycobacterium tuberculosis: a Review of Frequently Used Methods

Tuberculosis, caused by the bacterium Mycobacterium tuberculosis, remains one of the most serious global health problems. Molecular typing of M. tuberculosis has been used for various epidemiologic purposes as well as for clinical management. Currently, many techniques are available to type M. tuberculosis. Choosing the most appropriate technique in accordance with the existing laboratory conditions and the specific features of the geographic region is important. Insertion sequence IS6110-based restriction fragment length polymorphism (RFLP) analysis is considered the gold standard for the molecular epidemiologic investigations of tuberculosis. However, other polymerase chain reaction-based methods such as spacer oligonucleotide typing (spoligotyping), which detects 43 spacer sequence-interspersing direct repeats (DRs) in the genomic DR region; mycobacterial interspersed repetitive units-variable number tandem repeats, (MIRU-VNTR), which determines the number and size of tandem repetitive DNA sequences; repetitive-sequence-based PCR (rep-PCR), which provides high-throughput genotypic fingerprinting of multiple Mycobacterium species; and the recently developed genome-based whole genome sequencing methods demonstrate similar discriminatory power and greater convenience. This review focuses on techniques frequently used for the molecular typing of M. tuberculosis and discusses their general aspects and applications.

Genomic and functional techniques to mine the microbiome for novel antimicrobials and antimicrobial resistance genes

Microbial communities contain diverse bacteria that play important roles in every environment. Advances in sequencing and computational methodologies over the past decades have illuminated the phylogenetic and functional diversity of microbial communities from diverse habitats. Among the activities encoded in microbiomes are the abilities to synthesize and resist small molecules, yielding antimicrobial activity. These functions are of particular interest when viewed in light of the public health emergency posed by the increase in clinical antimicrobial resistance and the dwindling antimicrobial discovery and approval pipeline, and given the intimate ecological and evolutionary relationship between antimicrobial biosynthesis and resistance. Here, we review genomic and functional methods that have been developed for accessing the antimicrobial biosynthesis and resistance capacity of microbiomes and highlight outstanding examples of their applications.

A metagenomic comparison of endemic viruses from broiler chickens with runting-stunting syndrome and from normal birds

Runting-stunting syndrome (RSS) in broiler chickens is an enteric disease that causes significant economic losses to poultry producers worldwide due to elevated feed conversion ratios, decreased body weight during growth, and excessive culling. Of specific interest are the viral agents associated with RSS which have been difficult to fully characterize to date. Past research into the aetiology of RSS has implicated a wide variety of RNA and DNA viruses however, to date, no individual virus has been identified as the main agent of RSS and the current opinion is that it may be caused by a community of viruses, collectively known as the virome. This paper attempts to characterize the viral pathogens associated with 2–3-week-old RSS-affected and unaffected broiler chickens using next-generation sequencing and comparative metagenomics. Analysis of the viromes identified a total of 20 DNA and RNA viral families, along with 2 unidentified categories, comprised of 31 distinct viral genera and 7 unclassified genera. The most abundant viral families identified in this study were the Astroviridae, Caliciviridae, Picornaviridae, Parvoviridae, Coronaviridae, Siphoviridae, and Myoviridae. This study has identified historically significant viruses associated with the disease such as chicken astrovirus, avian nephritis virus, chicken parvovirus, and chicken calicivirus along with relatively novel viruses such as chicken megrivirus and sicinivirus 1 and will help expand the knowledge related to enteric disease in broiler chickens, provide insights into the viral constituents of a healthy avian gut, and identify a variety of enteric viruses and viral communities appropriate for further study.

Reflection on Molecular Approaches Influencing State-of-the-Art Bioremediation Design: Culturing to Microbial Community Fingerprinting to Omics

Bioremediation is generally viewed as a cost effective and sustainable technology because it relies on microbes to transform pollutants into benign compounds. Advances in molecular biological analyses allow unprecedented microbial detection and are increasingly incorporated into bioremediation. Throughout history, state-of-the-art techniques have informed bioremediation strategies. However, the insights those techniques provided were not as in depth as those provided by recently developed omics tools. Advances in next generation sequencing (NGS) have now placed metagenomics and metatranscriptomics within reach of environmental engineers. As NGS costs decrease, metagenomics and metatranscriptomics have become increasingly feasible options to rapidly scan sites for specific degradative functions and identify microorganisms important in pollutant degradation. These omic techniques are capable of revolutionizing biological treatment in environmental engineering by allowing highly sensitive characterization of previously uncultured microorganisms. Omics enables the discovery of novel microorganisms for use in bioaugmentation and supports systematic optimization of biostimulation strategies. This review describes the omics journey from roots in biology and medicine to its current status in environmental engineering including potential future directions in commercial application.