High-throughput DNA Sequencing Techniques Research Articles

Unraveling the Properties of Phage Display Fab Libraries and Their Use in the Selection of Gliadin-Specific Probes by Applying High-Throughput Nanopore Sequencing.

Directed evolution is a pivotal strategy for new antibody discovery, which allowed the generation of high-affinity Fabs against gliadin from two antibody libraries in our previous studies. One of the libraries was exclusively derived from celiac patients' mRNA (immune library) while the other was obtained through a protein engineering approach (semi-immune library). Recent advances in high-throughput DNA sequencing techniques are revolutionizing research across genomics, epigenomics, and transcriptomics. In the present work, an Oxford Nanopore in-lab sequencing device was used to comprehensively characterize the composition of the constructed libraries, both at the beginning and throughout the phage-mediated selection processes against gliadin. A customized analysis pipeline was used to select high-quality reads, annotate chain distribution, perform sequence analysis, and conduct statistical comparisons between the different selection rounds. Some immunological attributes of the most representative phage variants after the selection process were also determined. Sequencing results revealed the successful transfer of the celiac immune response features to the immune library and the antibodies derived from it, suggesting the crucial role of these features in guiding the selection of high-affinity recombinant Fabs against gliadin. In summary, high-throughput DNA sequencing has improved our understanding of the selection processes aimed at generating molecular binders against gliadin.

Research advances in genetic polymorphisms in Kawasaki disease

Kawasaki disease (KD) is a systemic inflammatory vascular disorder that predominantly affects children and is the leading cause of acquired heart disease in children. Although the etiology of this disease remains unclear, genome-wide association and genome-wide linkage studies have shown that some susceptible genes and chromosomal regions are associated with the development and progression of KD. With the advancement of high-throughput DNA sequencing techniques, more and more genomic information related to KD is being discovered. Understanding the genes involved in the pathogenesis of KD may provide novel insights into the diagnosis and treatment of KD. By analyzing related articles and summarizing related research advances, this article mainly discusses the T cell activation-enhancing genes that have been confirmed to be closely associated with the development and progression of KD and reveals their association with the pathogenesis of KD and coronary artery lesions.

Technological and computational advances driving high-throughput oncology.

Engineering and computational advances have opened many new avenues in cancer research, particularly when being exploited in interdisciplinary approaches. For example, the combination of microfluidics, novel sequencing technologies, and computational analyses has been crucial to enable single-cell assays, giving a detailed picture of tumor heterogeneity for the very first time. In a similar way, these 'tech' disciplines have been elementary for generating large data sets in multidimensional cancer 'omics' approaches, cell-cell interaction screens, 3D tumor models, and tissue level analyses. In this review we summarize the most important technology and computational developments that have been or will be instrumental for transitioning classical cancer research to a large data-driven, high-throughput, high-content discipline across all biological scales.

Network-based gut microbiome analysis in dogs

A growing number of studies in the last decade described the microbial populations in different niches of the organism thank to High-throughput DNA sequencing techniques, that are easily accessible to researchers. Furthermore, network analysis allows characterisation of bacteria that are indirectly linked to outcomes such as disease, diet and host sex through their association with other taxa. The present work on the gut microbiome follows previous research in which data were collected from 8 in-house dietary intervention studies in healthy dogs. Animals were divided according to diet and sex. The process of sample collection, storage, DNA extraction and sequencing, bioinformatic and statistical analysis followed a tailored, internally defined pipeline. The extracted DNA was prepared for sequencing of the V3 and V4 regions of the 16 rRNA gene. Correlation network analysis was performed by calculating pairwise relationships between taxa using the Sparse Correlations for Compositional Data (SparCC) algorithm. First, we identified candidate bacteria that were highly abundant in the microbial community, and second, we examined taxa that were directly related to diet and sex factors. In summary, this study underpins the network structure of the gut microbiome of dogs categorised by diet and sex and provides a better explanation for the interactions between bacteria that led to the grouping of dogs based on environmental or genetic factors. Specifically, this study has provided the basis for understanding how the bacterial community in the gut is interconnected and functions as a function of diet composition and sex. Highlights Network analysis could allow indirect association between bacteria composing the gut microbiome and outcomes, such as disease, diet and sex of the host. This research put the basis on the definition of enterotypes also in dogs, a concept already applied in humans. Positively correlated bacteria, belonging to modules could help to modulate diets and therapies for the treatment of enteropathies or gut-related pathologies linked to a dysbiosis status of the host.

Investigating differential abundance methods in microbiome data: A benchmark study.

The development of increasingly efficient and cost-effective high throughput DNA sequencing techniques has enhanced the possibility of studying complex microbial systems. Recently, researchers have shown great interest in studying the microorganisms that characterise different ecological niches. Differential abundance analysis aims to find the differences in the abundance of each taxa between two classes of subjects or samples, assigning a significance value to each comparison. Several bioinformatic methods have been specifically developed, taking into account the challenges of microbiome data, such as sparsity, the different sequencing depth constraint between samples and compositionality. Differential abundance analysis has led to important conclusions in different fields, from health to the environment. However, the lack of a known biological truth makes it difficult to validate the results obtained. In this work we exploit metaSPARSim, a microbial sequencing count data simulator, to simulate data with differential abundance features between experimental groups. We perform a complete comparison of recently developed and established methods on a common benchmark with great effort to the reliability of both the simulated scenarios and the evaluation metrics. The performance overview includes the investigation of numerous scenarios, studying the effect on methods' results on the main covariates such as sample size, percentage of differentially abundant features, sequencing depth, feature variability, normalisation approach and ecological niches. Mainly, we find that methods show a good control of the type I error and, generally, also of the false discovery rate at high sample size, while recall seem to depend on the dataset and sample size.

Life is in the air: An expedition into the Amazonian atmosphere

Biological particles suspended in the atmosphere have a crucial role in the dynamics of the biosphere underneath. Although much attention is paid for the chemical and physical properties of these particles, their biological taxonomic identity, which is relevant for ecological research, remains little studied. We took air samples at 300 meters above the forest in central Amazonia, in seven periods of 7 days, and used high-throughput DNA sequencing techniques to taxonomically identify airborne fungal and plant material. The use of a molecular identification technique improved taxonomic resolution when compared to morphological identification. This first appraisal of airborne diversity showed that fungal composition was strikingly different from what has been recorded in anthropogenic regions. For instance, basidiospores reached 30% of the OTUs instead of 3–5% as found in the literature; and the orders Capnodiales and Eurotiales—to which many allergenic fungi and crop pathogens belong—were much less frequently recorded than Pleosporales, Polyporales, and Agaricales. Plant OTUs corresponded mainly to Amazonian taxa frequently present in pollen records such as the genera Helicostilys and Cecropia and/or very abundant in the region such as Pourouma and Pouteria. The origin of extra-Amazonian plant material is unknown, but they belong to genera of predominantly wind-pollinated angiosperm families such as Poaceae and Betulaceae. Finally, the detection of two bryophyte genera feeds the debate about the role of long distance dispersal in the distribution of these plants.

The evolutionary history of vines in a neotropical biodiversity hotspot: Phylogenomics and biogeography of a large passion flower clade (Passiflora section Decaloba)

Because of their extraordinary flower and leaf morphology, passion flowers (Passifloraceae) have fascinated naturalists since their discovery. Within the large, diverse (600 species) genus Passiflora is an especially enigmatic and species-rich (120 spp.) subclade, Section Decaloba, which occurs in the Neotropics and has its center of diversity in Andean montane forests. A recent phylogenetic study of Passifloraceae showed that Section Decaloba was monophyletic, but was unable to resolve relationships within the clade, thus preventing inferences of evolutionary history and biogeography. The goal of this study was to elucidate the phylogeny and biogeography of Section Decaloba. We sampled 206 accessions representing 91 of the ~ 120 known species in section Decaloba and four outgroups, with samples derived predominantly from herbarium specimens. We generated DNA sequences using a high-throughput DNA sequencing technique called 2b-RAD, reconstructed the phylogeny, and conducted ancestral area reconstructions to infer the biogeographic history of the group. We recovered predominantly well-supported trees in which species were grouped into two main clades: 1) the Central American clade, within which the majority of nodes well supported and species were monophyletic and 2) the South American clade, a large clade that showed overall lower resolution and included several polyphyletic species and species complexes that need additional research. RASP analysis showed that section Decaloba originated in Central America around 10.4 Ma, and then dispersed to South America, the Greater Antilles, and the Bahamas. The South American clade diversified in the Northern Andes and then dispersed to the rest of South America, and Lesser Antilles. Results suggest that both long-distance dispersal and colonization of newly available habitats (i.e., in the Andes) likely promoted diversification of this clade. This study also illustrates how using herbarium specimens and a RAD-seq approach can produce phylogenies for broadly distributed, highly diverse, and poorly accessible groups of plants where field collections would be unfeasible.

Relative importance of climate, vegetation, and spatial factors in the community and functional composition of wood-inhabiting fungi in discontinuously distributed subalpine spruce forests

Wood-inhabiting fungi are critically important for the decomposition of coarse woody debris (CWD). To evaluate the relative importance of climate, vegetation, and spatial factors in the functional composition of fungal communities that inhabit CWD in discontinuously distributed subalpine Hondo spruce (Picea jezoensis (Sieb. & Zucc.) Carr. var. hondoensis (Mayr) Rehder) forests, a metabarcoding analysis was conducted on spruce deadwood samples obtained from six subalpine forests in central Japan using a high-throughput DNA sequencing technique. We detected 454 fungal operational taxonomic units (OTUs) from 67 spruce CWDs and determined that spatial factors explained a larger fraction of community variation than environmental (climate and vegetation) factors at all six study sites. However, environmental factors explained a larger fraction than spatial factors if we excluded data from one site that is geographically distant from other study sites. The OTU number and the occurrence of brown-rot fungi were positively associated with mean annual temperature and negatively associated with mean annual precipitation. Similarly, the principal component of forest vegetation significantly affected the OTU number and occurrence of brown-rot fungi. Precipitation seasonality was positively associated with the OTU number of undefined saprotrophs. These results suggest that fungal OTUs belonging to different functional groups respond differently to environmental variables.

Local Tree Diversity Suppresses Foliar Fungal Infestation and Decreases Morphological But Not Molecular Richness in a Young Subtropical Forest.

Leaf fungal pathogens alter their host species’ performance and, thus, changes in fungal species composition can translate into effects at the tree community scale. Conversely, the functional diversity of tree species in a host tree’s local neighbourhood can affect the host’s foliar fungal infestation. Therefore, understanding the factors that affect fungal infestations is important to advance our understanding of biodiversity-ecosystem functioning (BEF) relationships. Here we make use of the largest BEF tree experiment worldwide, the BEF-China experiment, where we selected tree host species with different neighbour species. Identifying fungal taxa by microscopy and by high-throughput DNA sequencing techniques based on the internal transcribed spacer (ITS) rDNA region, we analysed the fungal richness and infestation rates of our target trees as a function of local species richness. Based on the visual microscopic assessment, we found that a higher tree diversity reduced fungal richness and host-specific fungal infestation in the host’s local neighbourhood, while molecular fungal richness was unaffected. This diversity effect was mainly explained by the decrease in host proportion. Thus, the dilution of host species in the local neighbourhood was the primary mechanism in reducing the fungal disease severity. Overall, our study suggests that diverse forests will suffer less from foliar fungal diseases compared to those with lower diversity.

Blood Microbiome: A New Marker of Gut Microbial Population in Dogs?

The characterization of the microbial population in different compartments of the organism, such as the gastrointestinal tract, is now possible thanks to the use of high-throughput DNA sequencing technique. Several studies in the companion animals field have already investigated the fecal microbiome in healthy or sick subjects; however, the methodologies used in the different laboratories and the limited number of animals recruited in each experiment do not allow a straight comparison among published results. Previously, our research focused on the characterization of the microbial taxa variability in 340 fecal samples from 132 healthy dogs, collected serially from several in-house experiments. The results supported the responsiveness of microbiota to dietary and sex factors and allowed us to cluster dogs with high accuracy. For the present study, intestinal and blood microbiota of healthy dogs from different breeds, genders, ages and food habits were collected, with three principal aims: firstly, to confirm the results of our previous study regarding the fecal microbiome affected by the different type of diet; secondly, to investigate the existence of a blood microbial population, even in heathy subjects; and thirdly, to seek for a possible connection between the fecal and the blood microbiota. Limited researches have been published on blood microbiota in humans, and this is the first evidence of the presence of a bacterial population in the blood of dogs. Moreover, gut and blood microbiota can discriminate the animals by factors such as diet, suggesting some relationship between them. These preliminary results make us believe in the use of the blood microbiome for diagnostic purposes, such as researching and preventing gut inflammatory diseases.

Learning machine approach reveals microbial signatures of diet and sex in dog.

The characterization of the microbial population of many niches of the organism, as the gastrointestinal tract, is now possible thanks to the use of high-throughput DNA sequencing technique. Several studies in the companion animals field already investigated faecal microbiome in healthy or affected subjects, although the methodologies used in the different laboratories and the limited number of animals recruited in each experiment does not allow a straight comparison among published results. In the present study, we report data collected from several in house researches carried out in healthy dogs, with the aim to seek for a variability of microbial taxa in the faeces, caused by factors such as diet and sex. The database contains 340 samples from 132 dogs, collected serially during dietary intervention studies. The procedure of samples collection, storage, DNA extraction and sequencing, bioinformatic and statistical analysis followed a standardized pipeline. Microbial profiles of faecal samples have been analyzed applying dimensional reduction discriminant analysis followed by random forest analysis to the relative abundances of genera in the feces as variables. The results supported the responsiveness of microbiota at a genera taxonomic level to dietary factor and allowed to cluster dogs according this factor with high accuracy. Also sex factor clustered dogs, with castrated males and spayed females forming a separated group in comparison to intact dogs, strengthening the hypothesis of a bidirectional interaction between microbiota and endocrine status of the host. The findings of the present analysis are promising for a better comprehension of the mechanisms that regulate the connection of the microorganisms living the gastrointestinal tract with the diet and the host. This preliminary study deserves further investigation for the identification of the factors affecting faecal microbiome in dogs.

Tasting the differences: Microbiota analysis of different insect-based novel food

Traceability, quality and safety of edible insects are important both for the producers and the consumers. Today, alongside the burst of edible insects in western countries, we are facing a gap of knowledge of insect microbiota associated with the microbial ecosystems of insect-based products. In this context, High-Throughput DNA Sequencing (HTS) techniques can give insight into the carryover of insect microbiota into final food products. In this study, we investigated the microbiota composition of insect-based commercial food products, applying HTS techniques coupled with bioinformatic analysis. The work aimed to analyse the microbiota variability of different categories of some insect-based commercial food products made of A. domesticus (house cricket), T. molitor (mealworm beetle), and A. diaperinus (lesser mealworm or litter beetle), including commercial raw materials and processed food items, purchased via e-commerce from different companies. Our data revealed that samples cluster per insect species based on microbiota profile and preliminary results suggested that a small number of prevalent bacteria formed a “core microbiota” characterizing the products depending on the insect. This microbial signature can be recognized despite the different food processing levels, rearing conditions and selling companies. Furthermore, differences between raw and processed food made of the same insect or similar product produced by different companies was found.These results support the application of HTS analysis for studying the composition of insect-based commercial food products in a wider perspective, for food traceability and food quality control.

Modified Methods for Loading of High-Throughput DNA Extraction Plates Reduce Potential for Contamination.

High-throughput DNA sequencing techniques have contributed substantially to advances in our understanding of relationships among microbial communities, host characteristics, and broader ecosystem functions. With this rapid increase in breadth and depth of sequencing capabilities have come methods to extract, amplify, analyze, and interpret environmental DNA successfully with maximum efficiency. Unfortunately, performing DNA extractions quickly can come at the cost of increasing the risk of contamination among samples. In particular, high-throughput extractions that are based on samples contained in a 96-well plate offer a relatively quick method, compared to single-tube extractions, but also increase opportunities for well-to-well cross-contamination. To minimize the risk of cross-contamination among samples, while retaining the benefits of high-throughput extraction techniques, we developed a new method for loading environmental samples into 96-well plates. We used pierceable PCR sealing films to cover each plate while loading samples and added samples first to PCR tubes before moving them into wells; together, these practices reduce the risk of sample drift and unintended double loading of wells. The method outlined in this paper provides researchers with an approach to maximize available high-throughput extraction techniques while reducing the risk of cross-contamination inherent to 96-well plates. We provide a detailed step by step outline of how to move from sample collection to DNA extraction while minimizing the risk of unwanted cross-contamination.

A Guide to Carrying Out a Phylogenomic Target Sequence Capture Project.

High-throughput DNA sequencing techniques enable time- and cost-effective sequencing of large portions of the genome. Instead of sequencing and annotating whole genomes, many phylogenetic studies focus sequencing effort on large sets of pre-selected loci, which further reduces costs and bioinformatic challenges while increasing coverage. One common approach that enriches loci before sequencing is often referred to as target sequence capture. This technique has been shown to be applicable to phylogenetic studies of greatly varying evolutionary depth. Moreover, it has proven to produce powerful, large multi-locus DNA sequence datasets suitable for phylogenetic analyses. However, target capture requires careful considerations, which may greatly affect the success of experiments. Here we provide a simple flowchart for designing phylogenomic target capture experiments. We discuss necessary decisions from the identification of target loci to the final bioinformatic processing of sequence data. We outline challenges and solutions related to the taxonomic scope, sample quality, and available genomic resources of target capture projects. We hope this review will serve as a useful roadmap for designing and carrying out successful phylogenetic target capture studies.

The era of 'omics' technologies in the study of microbiologically influenced corrosion.

Efforts to elucidate the relationships between microorganisms and metal corrosion were mainly directed to understanding the formation of biofilm structures grown on corroded surfaces. The emergence of high throughput DNA sequencing techniques has helped in the description of microbial species involved directly and indirectly in the corrosion processes of alloys. Coupled with sequencing from environmental samples, other methodologies such as metatranscriptome, metaproteomics and metabolomics have allowed a new horizon to be opened on the understanding of the role of corrosive microbial biofilm. Several groups of bacteria and archaea were identified, showing the dominance of Proteobacteria in several samples analyzed and members of groups that previously received less attention, such as Firmicutes and Bacteroidetes. Our research also shows that metagenomic studies describe the presence of various Archaea domain thermophilic and methanogenic groups associated with metal corrosion. Thus, opening the prospect of describing new microbial groups as possible participants in this current global concern.

The Microbial Antarctic Resource System: Integrating discoverability and preservation of environmentally-annotated microbial 'omics data

Microbial organisms - including Archaea, Bacteria and unicellular Eukaryota - collectively dominate the Earth in terms of bio- and functional diversity. Their study, often constrained by technology, has strongly benefited from the recent advancements in high-throughput DNA sequencing techniques. The vast amounts of microbial data generated in the wake of these developments, however, remains severely underrepresented on open access biodiversity data repositories (e.g. the Global Biodiversity Information Facility; GBIF). Moreover, when sequencing data has been made publicly available, is often poorly annotated with metadata and environmental variables, making it difficult to find or query. Therefore, the microbial Antarctic Resource System (mARS) aims to fill this lacuna by documenting and geo-referencing microbial datasets and linking the sequence data in the International Nucleotide Sequence Database Collaboration (INSDC) repositories with the associated environmental measurements on mARS, which is aimed to be interoperable with both INSDC and GBIF. This way, mARS helps to preserve environmental data and the metadata that is crucial for the correct processing and interpretation of sequence data, while it also connects researchers via its webportal to the existing wealth of molecular information, and allows these datasets to be more effectively accessed. Given the general complexity of microbial ecological datasets, mARS needs to operate between different data archiving standards, such as MIxS (see https://press3.mcs.anl.gov/gensc/mixs/), which is oriented towards DNA sequence data, and the biodiversity-based DarwinCore standard. Currently, mARS tries to address the challenges of integrating microbial data with these existing systems as well as connecting with the communities behind them, by documenting the datasets on GBIF's extensions or investigate the feasibility of routinely processing raw sequence data into occurrence datasets using the open computing facilities offered by the European Molecular Biology Laboratory's (EMBL) MGnify resource.

Functional coding and non-coding variants in human BRCA1 gene and their use in genetic screening.

BRCA1 is involved in double-strand DNA damage repair pathways, and mutations in the gene are associated with hereditary breast and ovarian cancers. With great help of the development of high-throughput DNA sequencing techniques numerous single-nucleotide polymorphisms (SNPs) and insertion deletion (Indel) mutations are detected on both coding and non-coding/regulatory regions of the BRCA1. Mutations may cause pathogenic or benign changes on the protein function or affect its expression. In the last decade, use of genetic screening tests to detect mutations on such genes has become greatly popular. However, it is very important to know the effect of the detected mutations, which is mostly possible by the use of predictive softwares, and also the related family history to be able to correctly analyse the screening results and to inform the patient. Therefore, use of in silico and in vitro techniques to score the pathogenicity of detected variants on genes like BRCA1 is now of great importance. Otherwise, results obtained from screening tests and family history cannot be analysed precisely.

Differentially expressed genes of the shrimp Marsupenaeus japonicus in response to infection by white spot syndrome virus or Vibrio alginolyticus

This is the first study to use a next-generation high-throughput DNA sequencing technique, the Illumina Hiseq2000 method, to analyze the transcriptome from hemocytes of Marsupenaeus japonicus. A total of 80,929,652 Illumina reads, including 79,525,942 high quality reads were obtained in this study. From these, 40,231 unigenes with a mean length of 1557 bp were assembled using Trinity de novo software and 28,746 cDNA were matched in the NCBI database. Then we compared the transcriptome changes after white spot syndrome virus (WSSV) or Vibrio alginolyticus infection. A total of 19,872 putative proteins were classified functionally into 25 molecular families in the cluster of orthologous groups. KEGG pathway analysis identified that the metabolic pathway possessed more unigenes (1358 unigenes), followed by biosynthesis of secondary metabolites, Huntington's disease and RNA transport. Important immune functions like apoptosis, phagocytosis, and lysosomes were in response to WSSV and V. alginolyticus early infection. Only 26 transcripts were significantly up-regulated or down-regulated after WSSV infection showed compared with V. alginolyticus. Crustin-like protein, endonuclease-reverse transcriptase, putative nuclease HARBI1-like, diphthamide biosynthesis protein 7 and hormone receptor 3 were involved in the immune response to WSSV or V. alginolyticus infection. These transcriptome datasets accelerate our understanding of the innate immune mechanisms in M. japonicus and other crustaceans.

Large-Scale, Quantitative Protein Assays on a High-Throughput DNA Sequencing Chip

High-throughput DNA sequencing techniques haveenabled diverse approaches for linking DNA sequence to biochemical function. In contrast, assays of protein function have substantial limitations in terms of throughput, automation, and widespread availability. We have adapted an Illumina high-throughput sequencing chip to display an immense diversity of ribosomally translated proteins and peptides and then carried out fluorescence-based functional assays directly on this flow cell, demonstrating that a single, widely available high-throughput platform can perform both sequencing-by-synthesis and protein assays. We quantified the binding of the M2 anti-FLAG antibody to a library of 1.3× 104 variant FLAG peptides, exploring non-additive effects of combinations of mutations and discovering a "superFLAG" epitope variant. We also measured the enzymatic activity of 1.56× 105 molecular variants of full-length human O6-alkylguanine-DNA alkyltransferase (SNAP-tag). This comprehensive corpus of catalytic rates revealed amino acid interactionnetworks and cooperativity, linked positive cooperativity to structural proximity, and revealed ubiquitous positively cooperative interactions with histidine residues.

Fungal spore involvement in the resuspension of radiocaesium in summer

We observed the atmospheric resuspension of radiocaesium, derived from the Fukushima Dai-ichi Nuclear Power Plant accident, at Namie, a heavily contaminated area of Fukushima, since 2012. During the survey periods from 2012 to 2015, the activity concentrations of radiocaesium in air ranged from approximately 10−5 to 10−2 Bq per m3 and were higher in the warm season than in the cold season. Electron microscopy showed that the particles collected on filters in summer were predominantly of biological origin (bioaerosols), with which the observed radiocaesium activity concentration varied. We conducted an additional aerosol analysis based on fluorescent optical microscopic observation and high-throughput DNA sequencing technique to identify bioaerosols at Namie in 2015 summer. The concentrations of bioaerosols fluctuated the order of 106 particles per m3, and the phyla Basidiomycota and Ascomycota (true Fungi) accounted for approximately two-thirds of the bioaerosols. Moreover, the fungal spore concentration in air was positively correlated with the radiocaesium concentration at Namie in summer 2016. The bioaerosol emissions from Japanese mixed forests in the temperate zone predominately included fungal cells, which are known to accumulate radiocaesium, and should be considered an important scientific issue that must be addressed.