Next-generation sequencing technologies: An overview

De novo genome assembly depicts the immune genomic characteristics of cattle

Immunogenomic loci remain poorly understood because of their genetic complexity and size. Here, we report the de novo assembly of a cattle genome and provide a detailed annotation of the immunogenomic loci. The assembled genome contains 143 contigs (N50 ~ 74.0 Mb). In contrast to the current reference genome (ARS-UCD1.2), 156 gaps are closed and 467 scaffolds are located in our assembly. Importantly, the immunogenomic regions, including three immunoglobulin (IG) loci, four T-cell receptor (TR) loci, and the major histocompatibility complex (MHC) locus, are seamlessly assembled and precisely annotated. With the characterization of 258 IG genes and 657 TR genes distributed across seven genomic loci, we present a detailed depiction of immune gene diversity in cattle. Moreover, the MHC gene structures are integrally revealed with properly phased haplotypes. Together, our work describes a more complete cattle genome, and provides a comprehensive view of its complex immune-genome.

Identification of Genetic Variants Associated with Severe Myocardial Bridging through Whole-Exome Sequencing

Myocardial bridging (MB) is a congenital coronary artery anomaly and an important cause of angina. The genetic basis of MB is currently unknown. This study used a whole-exome sequencing technique and analyzed genotypic differences. Eight coronary angiography-confirmed cases of severe MB and eight age- and sex-matched control patients were investigated. In total, 139 rare variants that are potentially pathogenic for severe MB were identified in 132 genes. Genes with multiple rare variants or co-predicted by ClinVar and CADD/REVEL for severe MB were collected, from which heart-specific genes were selected under the guidance of tissue expression levels. Functional annotation indicated significant genetic associations with abnormal skeletal muscle mass, cardiomyopathies, and transmembrane ion channels. Candidate genes were reviewed regarding the functions and locations of each individual gene product. Among the gene candidates for severe MB, rare variants in DMD, SGCA, and TTN were determined to be the most crucial. The results suggest that altered anchoring proteins on the cell membrane and intracellular sarcomere unit of cardiomyocytes play a role in the development of the missed trajectory of coronary vessels. Additional studies are required to support the diagnostic application of cardiac sarcoglycan and dystroglycan complexes in patients with severe MB.

Predictive Clinical and Biological Criteria for Gene Panel Positivity in Suspected Inherited Autoinflammatory Diseases: Insights from a Case-Control Study

In order to assess the clinical and biological criteria that predict gene panel positivity in patients with a suspected inherited genetic autoinflammatory disease, we conducted a case-control study. These new selection criteria could replace the national multidisciplinary staff approval before performing genetic testing that has been required since 2019. The study involved 119 positive gene panels matched by panel sizes to 119 randomly selected negative gene panels. The patients were referred to our laboratory for genetic testing between June 2012, and March 2023. The clinical and biological criteria were extracted from a prospectively filled database. We focused our evaluation on accuracy and the positive predictive value. Neonatal symptom onset and deafness had the highest accuracies among all criteria associated with the positivity panel, with 92.9% (88.6; 96.0) and 92.6% (88.5; 95.6), respectively. However, it is important to note that the associated Positive Predictive Values (PPVs) cannot exceed 50%. Despite finding a statistical association between clinical and biological criteria and panel positivity, the predictive values of these criteria were not sufficient to recommend Next-Generation Sequencing (NGS) gene panel testing without the national multidisciplinary staff evaluation.

The use of precision diagnostics for monogenic diabetes: a systematic review and expert opinion

BACKGROUND

Monogenic diabetes presents opportunities for precision medicine but is underdiagnosed. This review systematically assessed the evidence for (1) clinical criteria and (2) methods for genetic testing for monogenic diabetes, summarized resources for (3) considering a gene or (4) variant as causal for monogenic diabetes, provided expert recommendations for (5) reporting of results; and reviewed (6) next steps after monogenic diabetes diagnosis and (7) challenges in precision medicine field.

METHODS

Pubmed and Embase databases were searched (1990-2022) using inclusion/exclusion criteria for studies that sequenced one or more monogenic diabetes genes in at least 100 probands (Question 1), evaluated a non-obsolete genetic testing method to diagnose monogenic diabetes (Question 2). The risk of bias was assessed using the revised QUADAS-2 tool. Existing guidelines were summarized for questions 3-5, and review of studies for questions 6-7, supplemented by expert recommendations. Results were summarized in tables and informed recommendations for clinical practice.

RESULTS

There are 100, 32, 36, and 14 studies included for questions 1, 2, 6, and 7 respectively. On this basis, four recommendations for who to test and five on how to test for monogenic diabetes are provided. Existing guidelines for variant curation and gene-disease validity curation are summarized. Reporting by gene names is recommended as an alternative to the term MODY. Key steps after making a genetic diagnosis and major gaps in our current knowledge are highlighted.

CONCLUSIONS

We provide a synthesis of current evidence and expert opinion on how to use precision diagnostics to identify individuals with monogenic diabetes.

Integrating Internal Fragments in the Interpretation of Top-Down Sequencing Data of Larger Oligonucleotides

In the context of direct top-down analysis or concerted bottom-up characterization of nucleic acid samples, the waning yield of terminal fragments as a function of precursor ion size poses a significant challenge to the gas-phase sequencing of progressively larger oligonucleotides. In this report, we examined the behavior of oligoribonucleotide samples ranging from 20 to 364 nt upon collision-induced dissociation (CID). The experimental data showed a progressive shift from terminal to internal fragments as a function of size. The systematic evaluation of experimental factors, such as collision energy, precursor charge, sample temperature, and the presence of chaotropic agents, showed that this trend could be modestly alleviated but not suppressed. This inexorable effect, which has been reported also for other activation techniques, prompted a re-examination of the features that have traditionally discouraged the utilization of internal fragments as a source of sequence information in data interpretation procedures. Our simulations highlighted the ability of internal fragments to produce self-consistent ladders with either end corresponding to each nucleotide in the sequence, which enables both proper alignment and correct recognition of intervening nucleotides. In turn, contiguous ladders display extensive overlaps with one another and with the ladders formed by terminal fragments, which unambiguously constrain their mutual placement within the analyte sequence. The experimental data borne out the predictions by showing ladders with extensive overlaps, which translated into uninterrupted "walks" covering the entire sequence with no gaps from end to end. More significantly, the results showed that combining the information afforded by internal and terminal ladders resulted in much a greater sequence coverage and nucleotide coverage depth than those achievable when either type of information was considered separately. The examination of a series of 58-mer oligonucleotides with high sequence homology showed that the assignment ambiguities engendered by internal fragments did not significantly exceed those afforded by the terminal ones. Therefore, the balance between potential benefits and perils of including the former makes a compelling argument for the development of integrated data interpretation strategies, which are better equipped for dealing with the changing fragmentation patterns obtained from progressively larger oligonucleotides.

NMD targets experience deadenylation during their maturation and endonucleolytic cleavage during their decay

Premature stop codon-containing mRNAs can produce truncated and dominantly acting proteins that harm cells. Eukaryotic cells protect themselves by degrading such mRNAs via the Nonsense-Mediated mRNA Decay (NMD) pathway. The precise reactions by which cells attack NMD target mRNAs remain obscure, precluding a mechanistic understanding of NMD and hampering therapeutic efforts to control NMD. A key step in NMD is the decay of the mRNA, which is proposed to occur via several competing models including deadenylation, exonucleolytic decay, and/or endonucleolytic decay. We set out to clarify the relative contributions of these decay mechanisms to NMD, and to identify the role of key factors. Here, we modify and deploy single-molecule nanopore mRNA sequencing to capture full-length NMD targets and their degradation intermediates, and we obtain single-molecule measures of splicing isoform, cleavage state, and poly(A) tail length. We observe robust endonucleolytic cleavage of NMD targets in vivo that depends on the nuclease SMG-6 and we use the occurence of cleavages to identify several known NMD targets. We show that NMD target mRNAs experience deadenylation, but similar to the extent that normal mRNAs experience as they enter the translational pool. Furthermore, we show that a factor (SMG-5) that historically was ascribed a function in deadenylation, is in fact required for SMG-6-mediated cleavage. Our results support a model in which NMD factors act in concert to degrade NMD targets in animals via an endonucleolytic cleavage near the stop codon, and suggest that deadenylation is a normal part of mRNA (and NMD target) maturation rather than a facet unique to NMD. Our work clarifies the route by which NMD target mRNAs are attacked in an animal.

Microfluidic design in single-cell sequencing and application to cancer precision medicine

Single-cell sequencing (SCS) is a crucial tool to reveal the genetic and functional heterogeneity of tumors, providing unique insights into the clonal evolution, microenvironment, drug resistance, and metastatic progression of cancers. Microfluidics is a critical component of many SCS technologies and workflows, conferring advantages in throughput, economy, and automation. Here, we review the current landscape of microfluidic architectures and sequencing techniques for single-cell omics analysis and highlight how these have enabled recent applications in oncology research. We also discuss the challenges and the promise of microfluidics-based single-cell analysis in the future of precision oncology.

Comparison of de novo assembly using long-read shotgun metagenomic sequencing of viruses in fecal and serum samples from marine mammals

Introduction

Viral diseases of marine mammals are difficult to study, and this has led to a limited knowledge on emerging known and unknown viruses which are ongoing threats to animal health. Viruses are the leading cause of infectious disease-induced mass mortality events among marine mammals.

Methods

In this study, we performed viral metagenomics in stool and serum samples from California sea lions (Zalophus californianus) and bottlenose dolphins (Tursiops truncates) using long-read nanopore sequencing. Two widely used long-read de novo assemblers, Canu and Metaflye, were evaluated to assemble viral metagenomic sequencing reads from marine mammals.

Results

Both Metaflye and Canu assembled similar viral contigs of vertebrates, such as Parvoviridae, and Poxviridae. Metaflye assembled viral contigs that aligned with one viral family that was not reproduced by Canu, while Canu assembled viral contigs that aligned with seven viral families that was not reproduced by Metaflye. Only Canu assembled viral contigs from dolphin and sea lion fecal samples that matched both protein and nucleotide RefSeq viral databases using BLASTx and BLASTn for Anelloviridae, Parvoviridae and Circoviridae families. Viral contigs assembled with Canu aligned with torque teno viruses and anelloviruses from vertebrate hosts. Viruses associated with invertebrate hosts including densoviruses, Ambidensovirus, and various Circoviridae isolates were also aligned. Some of the invertebrate and vertebrate viruses reported here are known to potentially cause mortality events and/or disease in different seals, sea stars, fish, and bivalve species.

Discussion

Canu performed better by producing the most viral contigs as compared to Metaflye with assemblies aligning to both protein and nucleotide databases. This study suggests that marine mammals can be used as important sentinels to surveil marine viruses that can potentially cause diseases in vertebrate and invertebrate hosts.

Benchmarking multi-platform sequencing technologies for human genome assembly

Genome assembly is a computational technique that involves piecing together deoxyribonucleic acid (DNA) fragments generated by sequencing technologies to create a comprehensive and precise representation of the entire genome. Generating a high-quality human reference genome is a crucial prerequisite for comprehending human biology, and it is also vital for downstream genomic variation analysis. Many efforts have been made over the past few decades to create a complete and gapless reference genome for humans by using a diverse range of advanced sequencing technologies. Several available tools are aimed at enhancing the quality of haploid and diploid human genome assemblies, which include contig assembly, polishing of contig errors, scaffolding and variant phasing. Selecting the appropriate tools and technologies remains a daunting task despite several studies have investigated the pros and cons of different assembly strategies. The goal of this paper was to benchmark various strategies for human genome assembly by combining sequencing technologies and tools on two publicly available samples (NA12878 and NA24385) from Genome in a Bottle. We then compared their performances in terms of continuity, accuracy, completeness, variant calling and phasing. We observed that PacBio HiFi long-reads are the optimal choice for generating an assembly with low base errors. On the other hand, we were able to produce the most continuous contigs with Oxford Nanopore long-reads, but they may require further polishing to improve on quality. We recommend using short-reads rather than long-reads themselves to improve the base accuracy of contigs from Oxford Nanopore long-reads. Hi-C is the best choice for chromosome-level scaffolding because it can capture the longest-range DNA connectedness compared to 10× linked-reads and Bionano optical maps. However, a combination of multiple technologies can be used to further improve the quality and completeness of genome assembly. For diploid assembly, hifiasm is the best tool for human diploid genome assembly using PacBio HiFi and Hi-C data. Looking to the future, we expect that further advancements in human diploid assemblers will leverage the power of PacBio HiFi reads and other technologies with long-range DNA connectedness to enable the generation of high-quality, chromosome-level and haplotype-resolved human genome assemblies.

Local read haplotagging enables accurate long-read small variant calling

Long-read sequencing technology has enabled variant detection in difficult-to-map regions of the genome and enabled rapid genetic diagnosis in clinical settings. Rapidly evolving third-generation sequencing platforms like Pacific Biosciences (PacBio) and Oxford nanopore technologies (ONT) are introducing newer platforms and data types. It has been demonstrated that variant calling methods based on deep neural networks can use local haplotyping information with long-reads to improve the genotyping accuracy. However, using local haplotype information creates an overhead as variant calling needs to be performed multiple times which ultimately makes it difficult to extend to new data types and platforms as they get introduced. In this work, we have developed a local haplotype approximate method that enables state-of-the-art variant calling performance with multiple sequencing platforms including PacBio Revio system, ONT R10.4 simplex and duplex data. This addition of local haplotype approximation makes DeepVariant a universal variant calling solution for long-read sequencing platforms.

Comparisons of the Oral Microbiota from Seven Species of Wild Venomous Snakes in Taiwan Using the High-Throughput Amplicon Sequencing of the Full-Length 16S rRNA Gene

A venomous snake's oral cavity may harbor pathogenic microorganisms that cause secondary infection at the wound site after being bitten. We collected oral samples from 37 individuals belonging to seven species of wild venomous snakes in Taiwan, including Naja atra (Na), Bungarus multicinctus (Bm), Protobothrops mucrosquamatus (Pm), Trimeresurus stejnegeri (Ts), Daboia siamensis (Ds), Deinagkistrodon acutus (Da), and alpine Trimeresurus gracilis (Tg). Bacterial species were identified using full-length 16S rRNA amplicon sequencing analysis, and this is the first study using this technique to investigate the oral microbiota of multiple Taiwanese snake species. Up to 1064 bacterial species were identified from the snake's oral cavities, with 24 pathogenic and 24 non-pathogenic species among the most abundant ones. The most abundant oral bacterial species detected in our study were different from those found in previous studies, which varied by snake species, collection sites, sampling tissues, culture dependence, and analysis methods. Multivariate analysis revealed that the oral bacterial species compositions in Na, Bm, and Pm each were significantly different from the other species, whereas those among Ts, Ds, Da, and Tg showed fewer differences. Herein, we reveal the microbial diversity in multiple species of wild snakes and provide potential therapeutic implications regarding empiric antibiotic selection for wildlife medicine and snakebite management.

Tutorial: a statistical genetics guide to identifying HLA alleles driving complex disease

The human leukocyte antigen (HLA) locus is associated with more complex diseases than any other locus in the human genome. In many diseases, HLA explains more heritability than all other known loci combined. In silico HLA imputation methods enable rapid and accurate estimation of HLA alleles in the millions of individuals that are already genotyped on microarrays. HLA imputation has been used to define causal variation in autoimmune diseases, such as type I diabetes, and in human immunodeficiency virus infection control. However, there are few guidelines on performing HLA imputation, association testing, and fine mapping. Here, we present a comprehensive tutorial to impute HLA alleles from genotype data. We provide detailed guidance on performing standard quality control measures for input genotyping data and describe options to impute HLA alleles and amino acids either locally or using the web-based Michigan Imputation Server, which hosts a multi-ancestry HLA imputation reference panel. We also offer best practice recommendations to conduct association tests to define the alleles, amino acids, and haplotypes that affect human traits. Along with the pipeline, we provide a step-by-step online guide with scripts and available software ( https://github.com/immunogenomics/HLA_analyses_tutorial ). This tutorial will be broadly applicable to large-scale genotyping data and will contribute to defining the role of HLA in human diseases across global populations.

Comparing assembly strategies for third-generation sequencing technologies across different genomes

The recent advent of long-read sequencing technologies, such as Pacific Biosciences (PacBio) and Oxford Nanopore technology (ONT), has led to substantial accuracy and computational cost improvements. However, de novo whole-genome assembly still presents significant challenges related to the computational cost and the quality of the results. Accordingly, sequencing accuracy and throughput continue to improve, and many tools are constantly emerging. Therefore, selecting the correct sequencing platform, the proper sequencing depth and the assembly tools are necessary to perform high-quality assembly. This paper evaluates the primary assembly reconstruction from recent hybrid and non-hybrid pipelines on different genomes. We find that using PacBio high-fidelity long-read (HiFi) plays an essential role in haplotype construction with respect to ONT reads. However, we observe a substantial improvement in the correctness of the assembly from high-fidelity ONT datasets and combining it with HiFi or short-reads.

Functional annotation and comparative genomics analysis of Balamuthia mandrillaris reveals potential virulence-related genes

Balamuthia mandrillaris is a pathogenic protozoan that causes a rare but almost always fatal infection of the central nervous system and, in some cases, cutaneous lesions. Currently, the genomic data for this free-living amoeba include the description of several complete mitochondrial genomes. In contrast, two complete genomes with draft quality are available in GenBank, but none of these have a functional annotation. In the present study, the complete genome of B. mandrillaris isolated from a freshwater artificial lagoon was sequenced and assembled, obtaining an assembled genome with better assembly quality parameter values than the currently available genomes. Afterward, the genome mentioned earlier, along with strains V039 and 2046, were subjected to functional annotation. Finally, comparative genomics analysis was performed, and it was found that homologous genes in the core genome potentially involved in the virulence of Acanthamoeba spp. and Trypanosoma cruzi. Moreover, eleven of fifteen genes were identified in the three strains described as potential target genes to develop new treatment approaches for B. mandrillaris infections. These results describe proteins in this protozoan's complete genome and help prioritize which target genes could be used to develop new treatments.

Inferring microbial co-occurrence networks from amplicon data: a systematic evaluation

Microbes commonly organize into communities consisting of hundreds of species involved in complex interactions with each other. 16S ribosomal RNA (16S rRNA) amplicon profiling provides snapshots that reveal the phylogenies and abundance profiles of these microbial communities. These snapshots, when collected from multiple samples, can reveal the co-occurrence of microbes, providing a glimpse into the network of associations in these communities. However, the inference of networks from 16S data involves numerous steps, each requiring specific tools and parameter choices. Moreover, the extent to which these steps affect the final network is still unclear. In this study, we perform a meticulous analysis of each step of a pipeline that can convert 16S sequencing data into a network of microbial associations. Through this process, we map how different choices of algorithms and parameters affect the co-occurrence network and identify the steps that contribute substantially to the variance. We further determine the tools and parameters that generate robust co-occurrence networks and develop consensus network algorithms based on benchmarks with mock and synthetic data sets. The Microbial Co-occurrence Network Explorer, or MiCoNE (available at https://github.com/segrelab/MiCoNE) follows these default tools and parameters and can help explore the outcome of these combinations of choices on the inferred networks. We envisage that this pipeline could be used for integrating multiple data sets and generating comparative analyses and consensus networks that can guide our understanding of microbial community assembly in different biomes. IMPORTANCE Mapping the interrelationships between different species in a microbial community is important for understanding and controlling their structure and function. The surge in the high-throughput sequencing of microbial communities has led to the creation of thousands of data sets containing information about microbial abundances. These abundances can be transformed into co-occurrence networks, providing a glimpse into the associations within microbiomes. However, processing these data sets to obtain co-occurrence information relies on several complex steps, each of which involves numerous choices of tools and corresponding parameters. These multiple options pose questions about the robustness and uniqueness of the inferred networks. In this study, we address this workflow and provide a systematic analysis of how these choices of tools affect the final network and guidelines on appropriate tool selection for a particular data set. We also develop a consensus network algorithm that helps generate more robust co-occurrence networks based on benchmark synthetic data sets.

No Clear Clustering Dysbiosis from Salivary Microbiota Analysis by Long Sequencing Reads in Patients Affected by Oral Squamous Cell Carcinoma: A Single Center Study

BACKGROUND

Advancements in DNA sequencing technology have facilitated the assessment of the connection between the oral microbiome and various diseases. The aim of the present study was to investigate the salivary microbiota composition employing for the first time in the literature the Oxford Nanopore Technology in patients affected by oral squamous cell carcinoma (OSCC).

METHODS

Unstimulated saliva samples of 31 patients were collected (24 OSCC patients and 7 controls). DNA was extracted using the QIAamp DNA Blood Kit and metagenomic long sequencing reads were performed using the MinION device.

RESULTS

In the OSCC group, 13 were males and 11 were females, with a mean age of 65.5 ± 13.9 years; in the control group, 5 were males and 2 were females, with a mean age of 51.4 ± 19.2 years. The border of the tongue was the most affected OSCC site. The microorganisms predominantly detected in OSCC patients were Prevotella, Chlamydia, Tissierellia, Calothrix, Leotiomycetes, Firmicutes and Zetaproteobacteria.

CONCLUSIONS

This study confirmed the predominance of periodontopathic bacteria in the salivary microbiome in the OSCC group. If a direct correlation between oral dysbiosis and OSCC onset was proven, it could lead to new prevention strategies and early diagnostic tools.

Ocular Surface Allostasis-When Homeostasis Is Lost: Challenging Coping Potential, Stress Tolerance, and Resilience

The loss of ocular surface (OS) homeostasis characterizes the onset of dry eye disease. Resilience defines the ability to withstand this threat, reflecting the ability of the ocular surface to cope with and bounce back after challenging events. The coping capacity of the OS defines the ability to successfully manage cellular stress. Cellular stress, which is central to the outcome of the pathophysiology of dry eye disease, is characterized by intensity, continuity, and receptivity, which lead to the loss of homeostasis, resulting in a phase of autocatalytic dysregulation, an event that is not well-defined. To better define this event, here, we present a model providing a potential approach when homeostasis is challenged and the coping capacities have reached their limits, resulting in the stage of heterostasis, in which the dysregulated cellular stress mechanisms take over, leading to dry eye disease. The main feature of the proposed model is the concept that, prior to the initiation of the events leading to cellular stress, there is a period of intense activation of all available coping mechanisms preventing the imminent dysregulation of ocular surface homeostasis. When the remaining coping mechanisms and resilience potential have been maximally exploited and have, finally, been exceeded, there will be a transition to manifest disease with all the well-known signs and symptoms, with a shift to allostasis, reflecting the establishment of another state of balance. The intention of this review was to show that it is possibly the phase of heterostasis preceding the establishment of allostasis that offers a better chance for therapeutic intervention and optimized recovery. Once allostasis has been established, as a new steady-state of balance at a higher level of constant cell stress and inflammation, treatment may be far more difficult, and the potential for reversal is drastically decreased. Homeostasis, once lost, can possibly not be fully recovered. The processes established during heterostasis and allostasis require different approaches and treatments for their control, indicating that the current treatment options for homeostasis need to be adapted to a more-demanding situation. The loss of homeostasis necessarily implies the establishment of a new balance; here, we refer to such a state as allostasis.

A High-Quality Genome Sequence of the Penicillium oxalicum 5-18 Strain Isolated from a Poplar Plantation Provides Insights into Its Lignocellulose Degradation

Studies on the degradation of plant cell wall polysaccharides by fungal extracellular enzymes have attracted recent attention from researchers. Xylan, abundant in hemicellulose, that play great role in connection between cellulose and lignin, has seen interest in its hydrolytic enzymatic complex. In this study, dozens of fungus species spanning genera were isolated from rotting leaves based on their ability to decompose xylan. Among these isolates, a strain with strong xylanase-producing ability was selected for further investigation by genome sequencing. Based on phylogenetic analysis of ITS (rDNA internal transcribed spacer) and LSU (Large subunit 28S rDNA) regions, the isolate was identified as Penicillium oxalicum. Morphological analysis also supported this finding. Xylanase activity of this isolated P. oxalicum 5-18 strain was recorded to be 30.83 U/mL using the 3,5-dinitro-salicylic acid (DNS) method. Further genome sequencing reveals that sequenced reads were assembled into a 30.78 Mb genome containing 10,074 predicted protein-encoding genes. In total, 439 carbohydrate-active enzymes (CAZymes) encoding genes were predicted, many of which were associated with cellulose, hemicellulose, pectin, chitin and starch degradation. Further analysis and comparison showed that the isolate P. oxalicum 5-18 contains a diverse set of CAZyme genes involved in degradation of plant cell wall components, particularly cellulose and hemicellulose. These findings provide us with valuable genetic information about the plant biomass-degrading enzyme system of P. oxalicum, facilitating a further exploration of the repertoire of industrially relevant lignocellulolytic enzymes of P. oxalicum 5-18.

Comparison of 6 DNA extraction methods for isolation of high yield of high molecular weight DNA suitable for shotgun metagenomics Nanopore sequencing to detect bacteria

BACKGROUND

Oxford Nanopore Technologies (ONT) offers an accessible platform for long-read sequencing, which improves the reconstruction of genomes and helps to resolve complex genomic contexts, especially in the case of metagenome analysis. To take the best advantage of long-read sequencing, DNA extraction methods must be able to isolate pure high molecular weight (HMW) DNA from complex metagenomics samples, without introducing any bias. New methods released on the market, and protocols developed at the research level, were specifically designed for this application and need to be assessed.

RESULTS

In this study, with different bacterial cocktail mixes, analyzed as pure or spiked in a synthetic fecal matrix, we evaluated the performances of 6 DNA extraction methods using various cells lysis and purification techniques, from quick and easy, to more time-consuming and gentle protocols, including a portable method for on-site application. In addition to the comparison of the quality, quantity and purity of the extracted DNA, the performance obtained when doing Nanopore sequencing on a MinION flow cell was also tested. From the obtained results, the Quick-DNA HMW MagBead Kit (Zymo Research) was selected as producing the best yield of pure HMW DNA. Furthermore, this kit allowed an accurate detection, by Nanopore sequencing, of almost all the bacterial species present in a complex mock community.

CONCLUSION

Amongst the 6 tested methods, the Quick-DNA HMW MagBead Kit (Zymo Research) was considered as the most suitable for Nanopore sequencing and would be recommended for bacterial metagenomics studies using this technology.

CamPype: an open-source workflow for automated bacterial whole-genome sequencing analysis focused on Campylobacter

BACKGROUND

The rapid expansion of Whole-Genome Sequencing has revolutionized the fields of clinical and food microbiology. However, its implementation as a routine laboratory technique remains challenging due to the growth of data at a faster rate than can be effectively analyzed and critical gaps in bioinformatics knowledge.

RESULTS

To address both issues, CamPype was developed as a new bioinformatics workflow for the genomics analysis of sequencing data of bacteria, especially Campylobacter, which is the main cause of gastroenteritis worldwide making a negative impact on the economy of the public health systems. CamPype allows fully customization of stages to run and tools to use, including read quality control filtering, read contamination, reads extension and assembly, bacterial typing, genome annotation, searching for antibiotic resistance genes, virulence genes and plasmids, pangenome construction and identification of nucleotide variants. All results are processed and resumed in an interactive HTML report for best data visualization and interpretation.

CONCLUSIONS

The minimal user intervention of CamPype makes of this workflow an attractive resource for microbiology laboratories with no expertise in bioinformatics as a first line method for bacterial typing and epidemiological analyses, that would help to reduce the costs of disease outbreaks, or for comparative genomic analyses. CamPype is publicly available at https://github.com/JoseBarbero/CamPype .

Transcriptome analysis of Macrobrachium rosenbergii hemocytes in response to Staphylococcus aureus infection

The aquaculture industry has suffered significant financial losses as a result of disease outbreaks. In particular, disease outbreaks have become a major problem that can seriously affect the sustainable development of the Macrobrachium rosenbergii aquaculture industry. It is crucial to determine the defense mechanism of the host after pathogenic invasion in order to provide effective defense measures after disease outbreaks. Shrimp, like other invertebrates, primarily depend on their innate immune systems to defend against pathogens, and recognize and resist pathogens through humoral and cellular immune responses. In this investigation, we used RNA-seq technology to investigate the transcriptome of hemocytes from M. rosenbergii induced by Staphylococcus aureus. Our main targets were immune pathways and genes related to innate immunity. RNA-seq identified 209,069 and 204,775 unigenes in the control and experimental groups, respectively. In addition, we identified 547 and 1734 differentially expressed genes (DEGs) following S. aureus challenge after 6 and 12 h (h), respectively. GO and KEGG enrichment analysis revealed that the DEGs were significantly enriched in several biological signalling pathways, including NOD-like receptor, PI3K-Akt, Toll and Imd, IL-17, TGF-beta, RIG-I-like receptor, cAMP, apoptosis, and C-type lectin receptor. Sixteen DEGs were chosen at random for qPCR verification; these results concurred with those from sequencing. Our findings revealed that immune-related genes play an important role in antibacterial activities and have specific functions for gram-positive bacteria. These results provide more data for the prevention of M. rosenbergii diseases and offer a basis for the better prevention of diseases.

The multifaceted roles of mass spectrometric analysis in nucleic acids drug discovery and development

The deceptively simple concepts of mass determination and fragment analysis are the basis for the application of mass spectrometry (MS) to a boundless range of analytes, including fundamental components and polymeric forms of nucleic acids (NAs). This platform affords the intrinsic ability to observe first-hand the effects of NA-active drugs on the chemical structure, composition, and conformation of their targets, which might affect their ability to interact with cognate NAs, proteins, and other biomolecules present in a natural environment. The possibility of interfacing with high-performance separation techniques represents a multiplying factor that extends these capabilities to cover complex sample mixtures obtained from organisms that were exposed to NA-active drugs. This report provides a brief overview of these capabilities in the context of the analysis of the products of NA-drug activity and NA therapeutics. The selected examples offer proof-of-principle of the applicability of this platform to all phases of the journey undertaken by any successful NA drug from laboratory to bedside, and provide the rationale for its rapid expansion outside traditional laboratory settings in support to ever growing manufacturing operations.

Progress in genome-inspired treatment decisions for multifocal lung adenocarcinoma

INTRODUCTION

Multifocal lung adenocarcinoma (MFLA) is becoming increasingly recognized as a distinct subset of lung cancer, with unique biology, disease course, and treatment outcomes. While definitions remain controversial, MFLA is characterized by the development and concurrent presence of multiple independent (non-metastatic) lesions on the lung adenocarcinoma spectrum. Disease progression typically follows an indolent course measured in years, with a lower propensity for nodal and distant metastases than other more common forms of non-small cell lung cancer.

AREAS COVERED

Traditional imaging and histopathological analyses of tumor biopsies are frequently unable to fully characterize the disease, prompting interest in molecular diagnosis. We highlight some of the key questions in the field, including accurate definitions to identify and stage MLFA, molecular tests to stratify patients and treatment decisions, and the lack of clinical trial data to delineate best management for this poorly understood subset of lung cancer patients. We review the existing literature and progress toward a genomic diagnosis for this unique disease entity.

EXPERT OPINION

Multifocal lung adenocarcinoma behaves differently than other forms of non-small cell lung cancer. Progress in molecular diagnosis may enhance potential for accurate definition, diagnosis, and optimizing treatment approach.

Alternative Splicing, RNA Editing, and the Current Limits of Next Generation Sequencing

The advent of next generation sequencing (NGS) has fostered a shift in basic analytic strategies of a gene expression analysis in diverse pathologies for the purposes of research, pharmacology, and personalized medicine. What was once highly focused research on individual signaling pathways or pathway members has, from the time of gene expression arrays, become a global analysis of gene expression that has aided in identifying novel pathway interactions, the discovery of new therapeutic targets, and the establishment of disease-associated profiles for assessing progression, stratification, or a therapeutic response. But there are significant caveats to this analysis that do not allow for the construction of the full picture. The lack of timely updates to publicly available databases and the "hit and miss" deposition of scientific data to these databases relegate a large amount of potentially important data to "garbage", begging the question, "how much are we really missing?" This brief perspective aims to highlight some of the limitations that RNA binding/modifying proteins and RNA processing impose on our current usage of NGS technologies as relating to cancer and how not fully appreciating the limitations of current NGS technology may negatively affect therapeutic strategies in the long run.

Sole microbiome progression in a hatchery life cycle, from egg to juvenile

Recirculating aquaculture systems (RAS) pose unique challenges in microbial community management since they rely on a stable community with key target groups, both in the RAS environment and in the host (in this case, Solea senegalensis). Our goal was to determine how much of the sole microbiome is inherited from the egg stage, and how much is acquired during the remainder of the sole life cycle in an aquaculture production batch, especially regarding potentially probiotic and pathogenic groups. Our work comprises sole tissue samples from 2 days before hatching and up to 146 days after hatching (-2 to 146 DAH), encompassing the egg, larval, weaning, and pre-ongrowing stages. Total DNA was isolated from the different sole tissues, as well as from live feed introduced in the first stages, and 16S rRNA gene was sequenced (V6-V8 region) using the Illumina MiSeq platform. The output was analysed with the DADA2 pipeline, and taxonomic attribution with SILVAngs version 138.1. Using the Bray-Curtis dissimilarity index, both age and life cycle stage appeared to be drivers of bacterial community dissimilarity. To try to distinguish the inherited (present since the egg stage) from the acquired community (detected at later stages), different tissues were analysed at 49, 119 and 146 DAH (gill, intestine, fin and mucus). Only a few genera were inherited, but those that were inherited accompany the sole microbiome throughout the life cycle. Two genera of potentially probiotic bacteria (Bacillus and Enterococcus) were already present in the eggs, while others were acquired later, in particularly, forty days after live feed was introduced. The potentially pathogenic genera Tenacibaculum and Vibrio were inherited from the eggs, while Photobacterium and Mycobacterium seemed to be acquired at 49 and 119 DAH, respectively. Significant co-occurrence was found between Tenacibaculum and both Photobacterium and Vibrio. On the other hand, significantly negative correlations were detected between Vibrio and Streptococcus, Bacillus, Limosilactobacillus and Gardnerella. Our work reinforces the importance of life cycle studies, which can contribute to improve production husbandry strategies. However, we still need more information on this topic as repetition of patterns in different settings is essential to confirm our findings.

Phylogenetic Analysis of Allotetraploid Species Using Polarized Genomic Sequences

Phylogenetic analysis of polyploid hybrid species has long posed a formidable challenge as it requires the ability to distinguish between alleles of different ancestral origins in order to disentangle their individual evolutionary history. This problem has been previously addressed by conceiving phylogenies as reticulate networks, using a two-step phasing strategy that first identifies and segregates homoeologous loci and then, during a second phasing step, assigns each gene copy to one of the subgenomes of an allopolyploid species. Here, we propose an alternative approach, one that preserves the core idea behind phasing-to produce separate nucleotide sequences that capture the reticulate evolutionary history of a polyploid-while vastly simplifying its implementation by reducing a complex multistage procedure to a single phasing step. While most current methods used for phylogenetic reconstruction of polyploid species require sequencing reads to be pre-phased using experimental or computational methods-usually an expensive, complex, and/or time-consuming endeavor-phasing executed using our algorithm is performed directly on the multiple-sequence alignment (MSA), a key change that allows for the simultaneous segregation and sorting of gene copies. We introduce the concept of genomic polarization that, when applied to an allopolyploid species, produces nucleotide sequences that capture the fraction of a polyploid genome that deviates from that of a reference sequence, usually one of the other species present in the MSA. We show that if the reference sequence is one of the parental species, the polarized polyploid sequence has a close resemblance (high pairwise sequence identity) to the second parental species. This knowledge is harnessed to build a new heuristic algorithm where, by replacing the allopolyploid genomic sequence in the MSA by its polarized version, it is possible to identify the phylogenetic position of the polyploid's ancestral parents in an iterative process. The proposed methodology can be used with long-read and short-read high-throughput sequencing data and requires only one representative individual for each species to be included in the phylogenetic analysis. In its current form, it can be used in the analysis of phylogenies containing tetraploid and diploid species. We test the newly developed method extensively using simulated data in order to evaluate its accuracy. We show empirically that the use of polarized genomic sequences allows for the correct identification of both parental species of an allotetraploid with up to 97% certainty in phylogenies with moderate levels of incomplete lineage sorting (ILS) and 87% in phylogenies containing high levels of ILS. We then apply the polarization protocol to reconstruct the reticulate histories of Arabidopsis kamchatica and Arabidopsis suecica, two allopolyploids whose ancestry has been well documented. [Allopolyploidy; Arabidopsis; genomic polarization; homoeologs; incomplete lineage sorting; phasing; polyploid phylogenetics; reticulate evolution.].

The ideal reporting of RAS testing in colorectal adenocarcinoma: a pathologists' perspective

RAS gene mutational status represents an imperative predictive biomarker to be tested in the clinical management of metastatic colorectal adenocarcinoma. Even if it is one of the most studied biomarkers in the era of precision medicine, several pre-analytical and analytical factors may still impasse an adequate reporting of RAS status in clinical practice, with significant therapeutic consequences. Thus, pathologists should be aware on the main topics related to this molecular evaluation: (i) adopt diagnostic limit of detections adequate to avoid the interference of sub-clonal cancer cell populations; (ii) choose the most adequate diagnostic strategy according to the available sample and its qualification for molecular testing; (iii) provide all the information regarding the mutation detected, since many RAS mutation-specific targeted therapeutic approaches are in development and will enter into routine clinical practice. In this review, we give a comprehensive description of the current scenario about RAS gene mutational testing in the clinic focusing on the pathologist's role in patient selection for targeted therapies.

Next-Generation Sequencing and Triple-Negative Breast Cancer: Insights and Applications

The poor survival of triple-negative breast cancer (TNBC) is due to its aggressive behavior, large heterogeneity, and high risk of recurrence. A comprehensive molecular investigation of this type of breast cancer using high-throughput next-generation sequencing (NGS) methods may help to elucidate its potential progression and discover biomarkers related to patient survival. In this review, the NGS applications in TNBC research are described. Many NGS studies point to TP53 mutations, immunocheckpoint response genes, and aberrations in the PIK3CA and DNA repair pathways as recurrent pathogenic alterations in TNBC. Beyond their diagnostic and predictive/prognostic value, these findings suggest potential personalized treatments in PD -L1-positive TNBC or in TNBC with a homologous recombination deficit. Moreover, the comprehensive sequencing of large genomes with NGS has enabled the identification of novel markers with clinical value in TNBC, such as AURKA, MYC, and JARID2 mutations. In addition, NGS investigations to explore ethnicity-specific alterations have pointed to EZH2 overexpression, BRCA1 alterations, and a BRCA2-delaAAGA mutation as possible molecular signatures of African and African American TNBC. Finally, the development of long-read sequencing methods and their combination with optimized short-read techniques promise to improve the efficiency of NGS approaches for future massive clinical use.

'Compressed Baby Head': A New 'Abusive Head Trauma' Entity?

BACKGROUND

Child abuse represents an important issue in the medico-legal and social context. In the last few decades, various aspects and mechanisms have been identified in child abuse case studies; however, constant research is needed in the field. With this paper, the authors will present a case of a new entity of Abusive Head Trauma that has come to the attention of medico-legal experts.

DISCUSSION

The trauma analysis performed on the cranio-encephalic district of the baby revealed quite peculiar lesions that led the authors to exclude that the injuries had been solely caused by violent shaking of the baby's head, as suggested by Shaken Baby Syndrome. Instead, the authors hypothesised that another lesion mechanism had been added to this one, namely latero-lateral cranial compression. The comprehensive and exhaustive analysis of the case led the authors to present a new possible entity in child abuse trauma, namely 'Compressed Baby Head'.

CONCLUSIONS

To the best of our knowledge, in the current literature, no similar clinical cases have ever been described. Thus, the case's uniqueness deserves to be brought to the attention of experts and the entire scientific community, as well as medical personnel, paediatricians, and reanimators. These professional figures are the first individuals who may encounter complex clinical cases such as the one presented in this paper; thus, they need to know how to properly manage the case and ensure protection for the abused infants and children.

Oxford nanopore technologies-a valuable tool to generate whole-genome sequencing data for in silico serotyping and the detection of genetic markers in Salmonella

Bacteria of the genus Salmonella pose a major risk to livestock, the food economy, and public health. Salmonella infections are one of the leading causes of food poisoning. The identification of serovars of Salmonella achieved by their diverse surface antigens is essential to gain information on their epidemiological context. Traditionally, slide agglutination has been used for serotyping. In recent years, whole-genome sequencing (WGS) followed by in silico serotyping has been established as an alternative method for serotyping and the detection of genetic markers for Salmonella. Until now, WGS data generated with Illumina sequencing are used to validate in silico serotyping methods. Oxford Nanopore Technologies (ONT) opens the possibility to sequence ultra-long reads and has frequently been used for bacterial sequencing. In this study, ONT sequencing data of 28 Salmonella strains of different serovars with epidemiological relevance in humans, food, and animals were taken to investigate the performance of the in silico serotyping tools SISTR and SeqSero2 compared to traditional slide agglutination tests. Moreover, the detection of genetic markers for resistance against antimicrobial agents, virulence, and plasmids was studied by comparing WGS data based on ONT with WGS data based on Illumina. Based on the ONT data from flow cell version R9.4.1, in silico serotyping achieved an accuracy of 96.4 and 92% for the tools SISTR and SeqSero2, respectively. Highly similar sets of genetic markers comparing both sequencing technologies were identified. Taking the ongoing improvement of basecalling and flow cells into account, ONT data can be used for Salmonella in silico serotyping and genetic marker detection.

coiaf: Directly estimating complexity of infection with allele frequencies

In malaria, individuals are often infected with different parasite strains. The complexity of infection (COI) is defined as the number of genetically distinct parasite strains in an individual. Changes in the mean COI in a population have been shown to be informative of changes in transmission intensity with a number of probabilistic likelihood and Bayesian models now developed to estimate the COI. However, rapid, direct measures based on heterozygosity or FwS do not properly represent the COI. In this work, we present two new methods that use easily calculated measures to directly estimate the COI from allele frequency data. Using a simulation framework, we show that our methods are computationally efficient and comparably accurate to current approaches in the literature. Through a sensitivity analysis, we characterize how the distribution of parasite densities, the assumed sequencing depth, and the number of sampled loci impact the bias and accuracy of our two methods. Using our developed methods, we further estimate the COI globally from Plasmodium falciparum sequencing data and compare the results against the literature. We show significant differences in the estimated COI globally between continents and a weak relationship between malaria prevalence and COI.

When Everything Becomes Bigger: Big Data for Big Poultry Production

In future decades, the demand for poultry meat and eggs is predicted to considerably increase in pace with human population growth. Although this expansion clearly represents a remarkable opportunity for the sector, it conceals a multitude of challenges. Pollution and land erosion, competition for limited resources between animal and human nutrition, animal welfare concerns, limitations on the use of growth promoters and antimicrobial agents, and increasing risks and effects of animal infectious diseases and zoonoses are several topics that have received attention from authorities and the public. The increase in poultry production must be achieved mainly through optimization and increased efficiency. The increasing ability to generate large amounts of data ("big data") is pervasive in both modern society and the farming industry. Information accessibility-coupled with the availability of tools and computational power to store, share, integrate, and analyze data with automatic and flexible algorithms-offers an unprecedented opportunity to develop tools to maximize farm profitability, reduce socio-environmental impacts, and increase animal and human health and welfare. A detailed description of all topics and applications of big data analysis in poultry farming would be infeasible. Therefore, the present work briefly reviews the application of sensor technologies, such as optical, acoustic, and wearable sensors, as well as infrared thermal imaging and optical flow, to poultry farming. The principles and benefits of advanced statistical techniques, such as machine learning and deep learning, and their use in developing effective and reliable classification and prediction models to benefit the farming system, are also discussed. Finally, recent progress in pathogen genome sequencing and analysis is discussed, highlighting practical applications in epidemiological tracking, and reconstruction of microorganisms' population dynamics, evolution, and spread. The benefits of the objective evaluation of the effectiveness of applied control strategies are also considered. Although human-artificial intelligence collaborations in the livestock sector can be frightening because they require farmers and employees in the sector to adapt to new roles, challenges, and competencies-and because several unknowns, limitations, and open-ended questions are inevitable-their overall benefits appear to be far greater than their drawbacks. As more farms and companies connect to technology, artificial intelligence (AI) and sensing technologies will begin to play a greater role in identifying patterns and solutions to pressing problems in modern animal farming, thus providing remarkable production-based and commercial advantages. Moreover, the combination of diverse sources and types of data will also become fundamental for the development of predictive models able to anticipate, rather than merely detect, disease occurrence. The increasing availability of sensors, infrastructures, and tools for big data collection, storage, sharing, and analysis-together with the use of open standards and integration with pathogen molecular epidemiology-have the potential to address the major challenge of producing higher-quality, more healthful food on a larger scale in a more sustainable manner, thereby protecting ecosystems, preserving natural resources, and improving animal and human welfare and health.

Integrated Full-Length Transcriptome and Metabolome Profiling Reveals Flavonoid Regulation in Response to Freezing Stress in Potato

Cold stress impairs plant growth and development, resulting in crop failure. Cultivated potato (Solanum tuberosum L.) is sensitive to freezing, while its wild relative, S. commersonii, has a strong freezing tolerance. To decipher the anti-freezing mechanism of CM, we carried out a transcriptomic and metabolomic analysis of an anti-freezing variety of CM (a type of S. commersonii) and a freeze-sensitive variety of DM (a type of Solanum tuberosum L.). A total of 49,232 high-quality transcripts from 12,811 gene loci, including 46,772 coding sequences and 2018 non-coding RNAs, were identified. KEEG enrichment analysis of differentially expressed genes (DEGs) between the two varieties showed that the flavonoid biosynthesis pathway was strongly induced by freezing stress, which was proven by flavonoid metabolome analysis. Consistent with the accumulation of more flavonoids, nearly all the pathway genes were significantly upregulated in CM than those in DM. The transcript levels of two chalcone synthase (CHS-1) isoforms and four isoforms of flavonoid 3'-hydroxylase (F3'H-1) were confirmed by qRT-PCR. Co-expression analysis identified one Myb-related and three UGTs (UDP-glycosyltransferase) that were significantly upregulated in CM during freezing stress. Our findings support that the flavonoid pathway was significantly enhanced by freezing stress and the greater accumulation ofglycosylatedflavonoids in resistant types than that of sensitive types, maybe accounting for the increased freezing tolerance of freeze-resistant potato varieties.

Discovering pathway biomarkers of hepatocellular carcinoma occurrence and development by dynamic network entropy analysis

OBJECTIVE

Gene expression profiling techniques measure the transcription of thousands of genes in a parallel manner. With more and more hepatocellular carcinoma (HCC) transcriptomic data becoming available, the high-throughput data provides an unprecedented opportunity to discover HCC diagnostic biomarkers. In this work, we propose a bioinformatics method based on dynamic network entropy analysis, called DNEA, to identify potential pathway biomarkers for HCC occurrence and development by integrating transcriptome and interactome.

METHODS

We firstly collect the pathways documented in different knowledge-bases and then impose the genome-wide human transcriptomic data of multistage cancerous tissues during the development and progression of HCC. After linking the gene sets of pathways into individual connected networks, we map the corresponding gene expression information onto these pathways. The dynamic network entropy of individual pathways is calculated to evaluate its activities and dysfunctionalities during the disease occurrence and development. We use the overall significant difference in the entropic dynamics during the time course to prioritize distinctive pathways during disease progression. Then machine learning classification methods are employed to screen out pathway biomarkers with the classification ability to distinguish different-stage samples of HCC progression.

RESULTS

Pathway biomarkers discovered based on DNEA demonstrate good classification performance in measuring HCC progression. The classification accuracy is as follows: DNA replication pathway (mean AUC= 0.82, 20 genes) from KEGG, FMLP pathway (mean AUC=0.84, 14 genes) from BioCarta, and downstream signaling of activated FGFR pathway (mean AUC =0.80, 15 genes) from Reactome. At the same time, previous studies have shown that these genes and pathways screened are closely related to the occurrence and development of HCC in terms of oncogenesis dysfunctions.

CONCLUSIONS

Our method for cancer biomarker discovery based on dynamic network entropy analysis is effective and efficient in identifying pathway biomarkers related to the progression of complex diseases.

Current and emerging trends in techniques for plant pathogen detection

Plant pathogenic microorganisms cause substantial yield losses in several economically important crops, resulting in economic and social adversity. The spread of such plant pathogens and the emergence of new diseases is facilitated by human practices such as monoculture farming and global trade. Therefore, the early detection and identification of pathogens is of utmost importance to reduce the associated agricultural losses. In this review, techniques that are currently available to detect plant pathogens are discussed, including culture-based, PCR-based, sequencing-based, and immunology-based techniques. Their working principles are explained, followed by an overview of the main advantages and disadvantages, and examples of their use in plant pathogen detection. In addition to the more conventional and commonly used techniques, we also point to some recent evolutions in the field of plant pathogen detection. The potential use of point-of-care devices, including biosensors, have gained in popularity. These devices can provide fast analysis, are easy to use, and most importantly can be used for on-site diagnosis, allowing the farmers to take rapid disease management decisions.

Comparative Genomic Analysis and Species Delimitation: A Case for Two Species in the Zoonotic Cestode Dipylidium caninum

Dipylidium caninum (Linnaeus, 1758) is a common zoonotic cestode of dogs and cats worldwide. Previous studies have demonstrated the existence of largely host-associated canine and feline genotypes based on infection studies, differences at the 28S rDNA gene, and complete mitochondrial genomes. There have been no comparative genome-wide studies. Here, we sequenced the genomes of a dog and cat isolate of Dipylidium caninum from the United States using the Illumina platform at mean coverage depths of 45× and 26× and conducted comparative analyses with the reference draft genome. Complete mitochondrial genomes were used to confirm the genotypes of the isolates. Genomes of D. caninum canine and feline genotypes generated in this study, had an average identity of 98% and 89%, respectively, when compared to the reference genome. SNPs were 20 times higher in the feline isolate. Comparison and species delimitation using universally conserved orthologs and protein-coding mitochondrial genes revealed that the canine and feline isolates are different species. Data from this study build a base for future integrative taxonomy. Further genomic studies from geographically diverse populations are necessary to understand implications for taxonomy, epidemiology, veterinary clinical medicine, and anthelmintic resistance.

MEGAnnotator2: a pipeline for the assembly and annotation of microbial genomes

The reconstruction of microbial genome sequences by bioinformatic pipelines and the consequent functional annotation of their genes' repertoire are fundamental activities aiming at unveiling their biological mechanisms, such as metabolism, virulence factors, and antimicrobial resistances. Here, we describe the development of the MEGAnnotator2 pipeline able to manage all next-generation sequencing methodologies producing short- and long-read DNA sequences. Starting from raw sequencing data, the updated pipeline can manage multiple analyses leading to the assembly of high-quality genome sequences and the functional classification of their genetic repertoire, providing the user with a useful report constituting features and statistics related to the microbial genome. The updated pipeline is fully automated from the installation to the delivery of the output, thus requiring minimal bioinformatics knowledge to be executed.

Screening of marine sediment-derived microorganisms and their bioactive metabolites: a review

Marine sediments are one of the largest habitats on Earth, and their unique ecology, such as high salinity, high pressure, and hypoxia, may activate certain silent genes in marine microbes, resulting in microbes, enzymes, active products, and specific metabolic pathways that can adapt to these specific ecological environments. Marine sediment-derived microorganisms and their bioactive metabolites are of great significance and have potential commercial development prospects for food, pharmaceutical, chemical industries, agriculture, environmental protection and human nutrition and health. In recent years, although there have been numerous scientific reports surrounding marine sediment-derived microorganisms and their bioactive metabolites, a comprehensive review of their research progress is lacking. This paper presents the development and renewal of traditional culture-dependent and omics analysis techniques and their application to the screening of marine sediment-derived microorganisms producing bioactive substances. It also highlights recent research advances in the last five years surrounding the types, functional properties and potential applications of bioactive metabolites produced by marine sediment-derived microorganisms. These bioactive metabolites mainly include antibiotics, enzymes, enzyme inhibitors, sugars, proteins, peptides, and some other small molecule metabolites. In addition, the review ends with concluding remarks on the challenges and future directions for marine sediment-derived microorganisms and their bioactive metabolites. The review report not only helps to deepen the understanding of marine sediment-derived microorganisms and their bioactive metabolites, but also provides some useful information for the exploitation and utilization of marine microbial resources and the mining of new compounds with potential functional properties.

Identification and Functional Analysis of APOB Variants in a Cohort of Hypercholesterolemic Patients

Mutations in APOB are the second most frequent cause of familial hypercholesterolemia (FH). APOB is highly polymorphic, and many variants are benign or of uncertain significance, so functional analysis is necessary to ascertain their pathogenicity. Our aim was to identify and characterize APOB variants in patients with hypercholesterolemia. Index patients (n = 825) with clinically suspected FH were analyzed using next-generation sequencing. In total, 40% of the patients presented a variant in LDLR, APOB, PCSK9 or LDLRAP1, with 12% of the variants in APOB. These variants showed frequencies in the general population lower than 0.5% and were classified as damaging and/or probably damaging by 3 or more predictors of pathogenicity. The variants c.10030A>G;p.(Lys3344Glu) and c.11401T>A;p.(Ser3801Thr) were characterized. The p.(Lys3344Glu) variant co-segregated with high low-density lipoprotein (LDL)-cholesterol in 2 families studied. LDL isolated from apoB p.(Lys3344Glu) heterozygous patients showed reduced ability to compete with fluorescently-labelled LDL for cellular binding and uptake compared with control LDL and was markedly deficient in supporting U937 cell proliferation. LDL that was carrying apoB p.(Ser3801Thr) was not defective in competing with control LDL for cellular binding and uptake. We conclude that the apoB p.(Lys3344Glu) variant is defective in the interaction with the LDL receptor and is causative of FH, whereas the apoB p.(Ser3801Thr) variant is benign.

A Systematic Review of the use of Precision Diagnostics in Monogenic Diabetes

Monogenic forms of diabetes present opportunities for precision medicine as identification of the underlying genetic cause has implications for treatment and prognosis. However, genetic testing remains inconsistent across countries and health providers, often resulting in both missed diagnosis and misclassification of diabetes type. One of the barriers to deploying genetic testing is uncertainty over whom to test as the clinical features for monogenic diabetes overlap with those for both type 1 and type 2 diabetes. In this review, we perform a systematic evaluation of the evidence for the clinical and biochemical criteria used to guide selection of individuals with diabetes for genetic testing and review the evidence for the optimal methods for variant detection in genes involved in monogenic diabetes. In parallel we revisit the current clinical guidelines for genetic testing for monogenic diabetes and provide expert opinion on the interpretation and reporting of genetic tests. We provide a series of recommendations for the field informed by our systematic review, synthesizing evidence, and expert opinion. Finally, we identify major challenges for the field and highlight areas for future research and investment to support wider implementation of precision diagnostics for monogenic diabetes.

A Novel Variant in VPS13B Underlying Cohen Syndrome

Pathogenic variants in vacuolar protein sorting 13 homolog B (VPS13B) cause Cohen syndrome (CS), a clinically diverse neurodevelopmental disorder. We used whole exome and Sanger sequencing to identify disease-causing variants in a Pakistani family with intellectual disability, microcephaly, facial dysmorphism, neutropenia, truncal obesity, speech delay, motor delay, and insomnia. We identified a novel homozygous nonsense variant c.8841G > A: p.(W2947∗) in VPS13B (NM_017890.5) which segregated with the disease. Sleep disturbances are commonly seen in neurodevelopmental disorders and can exacerbate medical issues if left untreated. We demonstrate that individuals with Cohen syndrome may also be affected by sleep disturbances. In conclusion, we expand the genetic and phenotypic features of Cohen syndrome in the Pakistani population.

Spatiotemporal dissection of tumor microenvironment via in situ sensing and monitoring in tumor-on-a-chip

Real-time monitoring in the tumor microenvironment provides critical insights of cancer progression and mechanistic understanding of responses to cancer treatments. However, clinical challenges and significant questions remain regarding assessment of limited clinical tissue samples, establishment of validated, controllable pre-clinical cancer models, monitoring of static versus dynamic markers, and the translation of insights gained from in vitro tumor microenvironments to systematic investigation and understanding in clinical practice. State-of-art tumor-on-a-chip strategies will be reviewed herein, and emerging real-time sensing and monitoring platforms for on-chip analysis of tumor microenvironment will also be examined. The integration of the sensors with tumor-on-a-chip platforms to provide spatiotemporal information of the tumor microenvironment and the associated challenges will be further evaluated. Though optimal integrated systems for in situ monitoring are still in evolution, great promises lie ahead that will open new paradigm for rapid, comprehensive analysis of cancer development and assist clinicians with powerful tools to guide the diagnosis, prognosis and treatment course in cancer.

Benchmarking datasets for assembly-based variant calling using high-fidelity long reads

BACKGROUND

Recent advances in long-read sequencing technologies have enabled accurate identification of all genetic variants in individuals or cells; this procedure is known as variant calling. However, benchmarking studies on variant calling using different long-read sequencing technologies are still lacking.

RESULTS

We used two Caenorhabditis elegans strains to measure several variant calling metrics. These two strains shared true-positive genetic variants that were introduced during strain generation. In addition, both strains contained common and distinguishable variants induced by DNA damage, possibly leading to false-positive estimation. We obtained accurate and noisy long reads from both strains using high-fidelity (HiFi) and continuous long-read (CLR) sequencing platforms, and compared the variant calling performance of the two platforms. HiFi identified a 1.65-fold higher number of true-positive variants on average, with 60% fewer false-positive variants, than CLR did. We also compared read-based and assembly-based variant calling methods in combination with subsampling of various sequencing depths and demonstrated that variant calling after genome assembly was particularly effective for detection of large insertions, even with 10 × sequencing depth of accurate long-read sequencing data.

CONCLUSIONS

By directly comparing the two long-read sequencing technologies, we demonstrated that variant calling after genome assembly with 10 × or more depth of accurate long-read sequencing data allowed reliable detection of true-positive variants. Considering the high cost of HiFi sequencing, we herein propose appropriate methodologies for performing cost-effective and high-quality variant calling: 10 × assembly-based variant calling. The results of the present study may facilitate the development of methods for identifying all genetic variants at the population level.

Exploring the sheep (Ovis aries) immunoglobulin repertoire by next generation sequencing

Next-generation sequencing (NGS) has revolutionized the way we determine the antibody repertoires encoded by B cells in the blood or lymphoid organs and transformed our understanding of adaptive immune responses in many species. Sheep (Ovis aries) have been widely used as a host for therapeutic antibody production since the early 1980s, however, little is known about their immune repertoires or immunological processes affecting the antibody generation. The objective of this study was to employ NGS for a comprehensive analysis of immunoglobulin heavy and light chain repertoires in four healthy sheep. We obtained > 90 % complete antibody sequences and nearly 130,000, 48,000 and 218,000 unique CDR3 reads for the heavy chain (IGH), kappa chain (IGK), and lambda chain (IGL) loci, respectively. Consistent with other species, we observed biased usage of germline variable (V), diversity (D) and joining (J) genes in the heavy and kappa loci, but not in the lambda loci. Moreover, the enormous diversity of CDR3 sequences was observed through sequence clustering and convergent recombination. These data will build a foundation for future studies investigating immune repertoires in health and disease as well as contribute to further refinement of ovine-derived therapeutic antibody drugs.

Profiling DNA Ligase Substrate Specificity with a Pacific Biosciences Single-Molecule Real-Time Sequencing Assay

DNA ligases catalyze the joining of breaks in nucleic acid backbones and are essential enzymes for in vivo genome replication and repair across all domains of life. These enzymes are also critically important to in vitro manipulation of DNA in applications such as cloning, sequencing, and molecular diagnostics. DNA ligases generally catalyze the formation of a phosphodiester bond between an adjacent 5'-phosphate and 3'-hydroxyl in DNA, but they exhibit different substrate structure preferences, sequence-dependent biases in reaction kinetics, and variable tolerance for mismatched base pairs. Information on substrate structure and sequence specificity can inform both biological roles and molecular biology applications of these enzymes. Given the high complexity of DNA sequence space, testing DNA ligase substrate specificity on individual nucleic acid sequences in parallel rapidly becomes impractical when a large sequence space is investigated. Here, we describe methods for investigating DNA ligase sequence bias and mismatch discrimination using Pacific Biosciences Single-Molecule Real-Time (PacBio SMRT) sequencing technology. Through its rolling-circle amplification methodology, SMRT sequencing can give multiple reads of the same insert. This feature permits high-quality top- and bottom-strand consensus sequences to be determined while preserving information on top-bottom strand mismatches that can be obfuscated or lost when using other sequencing methods. Thus, PacBio SMRT sequencing is uniquely suited to measuring substrate bias and enzyme fidelity through multiplexing a diverse set of sequences in a single reaction. The protocols describe substrate synthesis, library preparation, and data analysis methods suitable for measuring fidelity and bias of DNA ligases. The methods are easily adapted to different nucleic acid substrate structures and can be used to characterize many enzymes under a variety of reaction conditions and sequence contexts in a rapid and high-throughput manner. © 2023 New England Biolabs and The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Preparation of overhang DNA substrates for ligation Basic Protocol 2: Preparation of ligation fidelity libraries Support Protocol 1: Preparation of ligation libraries for PacBio Sequel II sequencing Support Protocol 2: Loading and sequencing of a prepared library on the Sequel II instrument Basic Protocol 3: Computational processing of ligase fidelity sequencing data.

Current and Emerging Diagnostic Approaches to Bacterial Diseases of Ruminants

The diagnostic approaches and methods to detect bacterial pathogens in ruminants are discussed, with a focus on cattle. Conventional diagnostic methods using culture, isolation, and characterization are being replaced or supplemented with new methods. These include molecular diagnostics such as real-time polymerase chain reaction and whole-genome sequencing. In addition, methods such as matrix-assisted laser desorption ionization-time-of-flight mass spectrometry enable rapid identification and enhanced pathogen characterization. These emerging diagnostic tools can greatly enhance the ability to detect and characterize pathogens, but performance and interpretation vary greatly across sample and pathogen types, disease syndromes, assay performance, and other factors.

Nano-RECall provides an integrated pipeline for HIV-1 drug resistance testing from Oxford Nanopore sequence data

OBJECTIVES

Low-capital-layout sequencing options from Oxford Nanopore Technologies (ONT) could assist in expanding HIV drug resistance testing to resource-limited settings. HIV drug resistance mutations often occur as mixtures, but current ONT pipelines provide a consensus sequence only. Moreover, there is no integrated pipeline that provides a drug resistance report from an ONT sequence file without intervention from skilled bioinformaticists. We therefore investigated Nano-RECall, which provides seamless drug resistance interpretation while requiring low-read coverage ONT sequence data from affordable Flongle or MinION flow cells and which provides mutation mixtures similar to Sanger Sequencing.

METHODS

We compared Sanger sequencing to ONT sequencing of the same HIV-1 subtype C polymerase chain reaction (PCR) amplicons, respectively using RECall and the novel Nano-RECall bioinformatics pipelines. Amplicons were from separate assays: (a) Applied Biosystems HIV-1 Genotyping Kit (ThermoFisher) spanning protease (PR) to reverse transcriptase (RT) (PR-RT) (n = 46) and (b) homebrew integrase (IN) (n = 21). The agreement between Sanger sequences and ONT sequences was assessed at nucleotide level, and at codon level for Stanford HIV drug resistance database mutations at an optimal ONT read depth of 400 reads only.

RESULTS

The average sequence similarity between ONT and Sanger sequences was 99.3% (95% CI: 99.1%-99.4%) for PR-RT and 99.6% (95% CI: 99.4%-99.7%) for INT. Drug resistance mutations did not differ for 21 IN specimens; 8 mutations were detected by both ONT- and Sanger sequencing. For the 46 PR and RT specimens, 245 mutations were detected by either ONT or Sanger, of these 238 (97.1%) were detected by both.

CONCLUSIONS

The Nano-RECall pipeline, freely available as a downloadable application on a Windows computer, provides Sanger-equivalent HIV drug resistance interpretation. This novel pipeline combined with a simple workflow and multiplexing samples on ONT flow-cells would contribute to making HIV drug resistance sequencing feasible for resource-limited settings.

Pangenomic analysis identifies structural variation associated with heat tolerance in pearl millet

Pearl millet is an important cereal crop worldwide and shows superior heat tolerance. Here, we developed a graph-based pan-genome by assembling ten chromosomal genomes with one existing assembly adapted to different climates worldwide and captured 424,085 genomic structural variations (SVs). Comparative genomics and transcriptomics analyses revealed the expansion of the RWP-RK transcription factor family and the involvement of endoplasmic reticulum (ER)-related genes in heat tolerance. The overexpression of one RWP-RK gene led to enhanced plant heat tolerance and transactivated ER-related genes quickly, supporting the important roles of RWP-RK transcription factors and ER system in heat tolerance. Furthermore, we found that some SVs affected the gene expression associated with heat tolerance and SVs surrounding ER-related genes shaped adaptation to heat tolerance during domestication in the population. Our study provides a comprehensive genomic resource revealing insights into heat tolerance and laying a foundation for generating more robust crops under the changing climate.

[Next Generation Sequencing (NGS) for beginners]

Genetic diagnoses have progressed through the development of Next Generation Sequencing (NGS), which enables improved patient care and more precise genetic counseling. NGS techniques analyze DNA regions of interest in view accurately determining the relevant nucleotide sequence. Different kinds of analysis apply NGS : multigene panel testing, Whole Exome Sequencing (WES) and Whole Genome Sequencing (WGS). While regions of interest depend on the type of analysis (multigene panels testing studies the exons of genes implicated in a particular phenotype, WES studies all exons of all genes, and WGS studies all exons and introns), the technical protocol remains similar. Clinical/biological interpretation is based on a body of evidence allowing categorization of variants into five groups (from benign to pathogenic) in accordance with an international classification, which takes into account segregation criteria (variant detected in affected relatives, but absent in healthy relatives), matching phenotype, databases, scientific literature, prediction scores and data drawn from functional studies. Clinical/biological interaction and expertise are essential during this interpretative step. Pathogenic and probably pathogenic variants are returned to the clinician. Variants of unknown significance can likewise be returned, if they are liable to be reclassified through further analysis as pathogenic or benign. Variant classifications may change, as new data emerge suggesting or ruling out pathogenicity.