Deep sequencing in pre- and clinical vaccine research

Quantum vaccinomics platforms to advance in vaccinology

The opinion flows from Introduction to the immunological quantum that requires a historical perspective, to Quantum vaccine algorithms supported by a bibliometric analysis, to Quantum vaccinomics describing from our perspective the different vaccinomics and quantum vaccinomics algorithms. Finally, in the Discussion and conclusions we propose novel platforms and algorithms developed to further advance on quantum vaccinomics. In the paper we refer to protective epitopes or immunological quantum for the design of candidate vaccine antigens, which may elicit a protective response through both cellular and antibody mediated mechanisms of the host immune system. Vaccines are key interventions for the prevention and control of infectious diseases affecting humans and animals worldwide. Biophysics led to quantum biology and quantum immunology reflecting quantum dynamics within living systems and their evolution. In analogy to quantum of light, immune protective epitopes were proposed as the immunological quantum. Multiple quantum vaccine algorithms were developed based on omics and other technologies. Quantum vaccinomics is the methodological approach with different platforms used for the identification and combination of immunological quantum for vaccine development. Current quantum vaccinomics platforms include in vitro, in music and in silico algorithms and top trends in biotechnology for the identification, characterization and combination of candidate protective epitopes. These platforms have been applied to different infectious diseases and in the future should target prevalent and emerging infectious diseases with novel algorithms.

An exploration of assembly strategies and quality metrics on the accuracy of the rewarewa (Knightia excelsa) genome

We used long read sequencing data generated from Knightia excelsa, a nectar-producing Proteaceae tree endemic to Aotearoa (New Zealand), to explore how sequencing data type, volume and workflows can impact final assembly accuracy and chromosome reconstruction. Establishing a high-quality genome for this species has specific cultural importance to Māori and commercial importance to honey producers in Aotearoa. Assemblies were produced by five long read assemblers using data subsampled based on read lengths, two polishing strategies and two Hi-C mapping methods. Our results from subsampling the data by read length showed that each assembler tested performed differently depending on the coverage and the read length of the data. Subsampling highlighted that input data with longer read lengths but perhaps lower coverage constructed more contiguous, kmers and gene-complete assemblies than short read length input data with higher coverage. The final genome assembly was constructed into 14 pseudochromosomes using an initial flye long read assembly, a racon/medaka/pilon combined polishing strategy, salsa2 and allhic scaffolding, juicebox curation, and Macadamia linkage map validation. We highlighted the importance of developing assembly workflows based on the volume and read length of sequencing data and established a robust set of quality metrics for generating high-quality assemblies. Scaffolding analyses highlighted that problems found in the initial assemblies could not be resolved accurately by Hi-C data and that assembly scaffolding was more successful when the underlying contig assembly was of higher accuracy. These findings provide insight into how quality assessment tools can be implemented throughout genome assembly pipelines to inform the de novo reconstruction of a high-quality genome assembly for nonmodel organisms.

Molecular and genetic inflammation networks in major human diseases

It has been well-recognized that inflammation alongside tissue repair and damage maintaining tissue homeostasis determines the initiation and progression of complex diseases. Albeit with the accomplishment of having captured the most critical inflammation-involved molecules, genetic susceptibilities, epigenetic factors, and environmental factors, our schemata on the role of inflammation in complex diseases remain largely patchy, in part due to the success of reductionism in terms of research methodology per se. Omics data alongside the advances in data integration technologies have enabled reconstruction of molecular and genetic inflammation networks which shed light on the underlying pathophysiology of complex diseases or clinical conditions. Given the proven beneficial role of anti-inflammation in coronary heart disease as well as other complex diseases and immunotherapy as a revolutionary transition in oncology, it becomes timely to review our current understanding of the molecular and genetic inflammation networks underlying major human diseases. In this review, we first briefly discuss the complexity of infectious diseases and then highlight recently uncovered molecular and genetic inflammation networks in other major human diseases including obesity, type II diabetes, coronary heart disease, late onset Alzheimer's disease, Parkinson's disease, and sporadic cancer. The commonality and specificity of these molecular networks are addressed in the context of genetics based on genome-wide association study (GWAS). The double-sword role of inflammation, such as how the aberrant type 1 and/or type 2 immunity leads to chronic and severe clinical conditions, remains open in terms of the inflammasome and the core inflammatome network features. Increasingly available large Omics and clinical data in tandem with systems biology approaches have offered an exciting yet challenging opportunity toward reconstruction of more comprehensive and dynamic molecular and genetic inflammation networks, which hold great promise in transiting network snapshots to video-style multi-scale interplays of disease mechanisms, in turn leading to effective clinical intervention.

Sequence-Independent, Single-Primer Amplification Next-Generation Sequencing of Hantaan Virus Cell Culture-Based Isolates

Hantaan virus (HTNV), identified in the striped field mouse (Apodemus agrarius), belongs to the genus Hantavirus of the family Bunyaviridae and contains tripartite RNA genomes, small (S), medium (M), and large (L) segments. HTNV is a major causative for hemorrhagic fever with renal syndrome (HFRS) with fatality rates ranging from 1% to 15% in the Republic of Korea (ROK) and China. Defining of HTNV whole-genome sequences and isolation of the infectious particle play a critical role in the characterization and preventive and therapeutic strategies of hantavirus outbreaks. Next-generation sequencing (NGS) provides an advanced tool for massive genomic sequencing of viruses. However, the isolation of viral infectious particles is a huge obstacle to investigate and develop anti-virals for hantaviruses. Here, we report 12 HTNV isolates from lung tissues of the striped field mouse in the highly HFRS-endemic areas. Sequence-independent, single-primer amplification (SISPA) NGS was attempted to recover the genomic sequences of HTNV isolates. The nucleotide sequence of HTNV S, M, and L segments were covered up to 99.4-100%, 97.5-100%, and 95.6-99.8%, respectively, based on the full length of the prototype HTNV 76-118. The whole-genome sequencing of HTNV isolates was accomplished by additional reverse transcription polymerase chain reaction (RT-PCR) and rapid amplification cDNA ends (RACE) PCR. In conclusion, this study will lead to the attempt and usage of SISPA NGS technologies to delineate the whole-genome sequence of hantaviruses, providing a new era of viral genomics for the surveillance, trace, and disease risk management of HFRS incidents.

Impact of host genetic polymorphisms on vaccine induced antibody response

Many host- and vaccine-specific factors modulate an antibody response. Host genetic polymorphisms, in particular, modulate the immune response in multiple ways on different scales. This review article describes how information on host genetic polymorphisms and corresponding immune cascades may be used to generate personalized vaccine strategies to optimize the antibody response.

Value of a newly sequenced bacterial genome

Next-generation sequencing (NGS) technologies have made high-throughput sequencing available to medium- and small-size laboratories, culminating in a tidal wave of genomic information. The quantity of sequenced bacterial genomes has not only brought excitement to the field of genomics but also heightened expectations that NGS would boost antibacterial discovery and vaccine development. Although many possible drug and vaccine targets have been discovered, the success rate of genome-based analysis has remained below expectations. Furthermore, NGS has had consequences for genome quality, resulting in an exponential increase in draft (partial data) genome deposits in public databases. If no further interests are expressed for a particular bacterial genome, it is more likely that the sequencing of its genome will be limited to a draft stage, and the painstaking tasks of completing the sequencing of its genome and annotation will not be undertaken. It is important to know what is lost when we settle for a draft genome and to determine the “scientific value” of a newly sequenced genome. This review addresses the expected impact of newly sequenced genomes on antibacterial discovery and vaccinology. Also, it discusses the factors that could be leading to the increase in the number of draft deposits and the consequent loss of relevant biological information.