Transcriptomics in Human Challenge Models

Screening for immune biomarkers associated with infection or protection against Ehrlichia ruminantium by RNA-sequencing analysis

Heartwater is one of the most economically important tick-borne fatal diseases of livestock. The disease is caused by the bacteria Ehrlichia ruminantium transmitted by Amblyomma ticks. Although there is evidence that interferon-gamma controls E. ruminantium growth and that cellular immune responses are protective, an effective recombinant vaccine for this disease is lacking. Analyses of markers associated with infection as well as protection will lead to a better understanding of the E. ruminantium immune response and corresponding pathways induced in sheep peripheral blood mononuclear cells (PBMC) will assist in development of such a vaccine. In this study, Biomarkers of infection (BMI) were identified as uniquely expressed genes during primary infection and biomarkers of protection (BMP) associated with immune to heartwater were identified post challenge. Sheep were experimentally infected and challenged with E. ruminantium infected ticks. The immune phenotypic and transcriptome profile of their PBMC were compared to their own naïve PBMC collected before infection. The study revealed 305 differentially expressed genes (DEGs) as BMI, of these 17 were upregulated at all three time-points investigated. These DEGs, form part of the bacterial invasion of epithelial cells Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway, and others detected from day 1 post infection and are considered predictive markers for early heartwater infection in ruminants. Similarly, a total of 332 DEGs were identified as BMP, of these 100 were upregulated and 75 were downregulated at all three time-points investigated. However, at D1PC most DEGs were downregulated (n = 1312) that correlated with a reduction in the % CD4 and CD8 T cells detected with flow cytometry. KEGG pathway analyses showed complete down regulation of T cell specific pathways possibly due to homing of immune cells to the site of infection after acquired immunity developed. At D4PC, expression levels of most of these downregulated genes increased and by D6PC they were upregulated. This indicates that the sampling time-point for biomarker analyses is important when results for acquired immune responses are inferred. This data identified DEGs that could be considered as biomarkers of protective immunity that can be used for identification of vaccine antigens and provides a strong foundation to further development of heartwater recombinant vaccines.

Blood transcriptomics analysis offers insights into variant-specific immune response to SARS-CoV-2

Bulk RNA sequencing (RNA-seq) of blood is typically used for gene expression analysis in biomedical research but is still rarely used in clinical practice. In this study, we propose that RNA-seq should be considered a diagnostic tool, as it offers not only insights into aberrant gene expression and splicing but also delivers additional readouts on immune cell type composition as well as B-cell and T-cell receptor (BCR/TCR) repertoires. We demonstrate that RNA-seq offers insights into a patient's immune status via integrative analysis of RNA-seq data from patients infected with various SARS-CoV-2 variants (in total 196 samples with up to 200 million reads sequencing depth). We compare the results of computational cell-type deconvolution methods (e.g., MCP-counter, xCell, EPIC, quanTIseq) to complete blood count data, the current gold standard in clinical practice. We observe varying levels of lymphocyte depletion and significant differences in neutrophil levels between SARS-CoV-2 variants. Additionally, we identify B and T cell receptor (BCR/TCR) sequences using the tools MiXCR and TRUST4 to show that-combined with sequence alignments and BLASTp-they could be used to classify a patient's disease. Finally, we investigated the sequencing depth required for such analyses and concluded that 10 million reads per sample is sufficient. In conclusion, our study reveals that computational cell-type deconvolution and BCR/TCR methods using bulk RNA-seq analyses can supplement missing CBC data and offer insights into immune responses, disease severity, and pathogen-specific immunity, all achievable with a sequencing depth of 10 million reads per sample.

Benefits of Combining Molecular Biology and Controlled Human Infection Model Methodologies in Advancing Vaccine Development

Infectious diseases continue to account for a significant portion of global deaths despite the use of vaccines for several centuries. Immunization programs around the world are a testament to the great success of multiple vaccines, yet there are still diseases without vaccines and others that require safer more effective ones. Addressing uncontrolled and emerging disease threats is restrained by the limitations and bottlenecks encountered with traditional vaccine development paradigms. Recent advances in modern molecular biology technologies have enhanced the interrogation of host pathogen interaction and deciphered complex pathways, thereby uncovering the myriad interplay of biological events that generate immune protection against foreign agents. Consequent to insights into the immune system, modern biology has been instrumental in the development and production of next generation 21st century vaccines. As these biological tools, commonly and collectively referred to as 'omics, became readily available, there has been a renewed consideration of Controlled Human Infection Models (CHIMs). Successful and reproducible CHIMs can complement modern molecular biology for the study of infectious diseases and development of effective vaccines in a regulated process that mitigates risk, cost, and time, with capacity to discern immune correlates of protection.

Lung transcriptomics of K18-hACE2 mice highlights mechanisms and genes involved in the MVA-S vaccine-mediated immune response and protection against SARS-CoV-2 infection

Unravelling the molecular mechanism of COVID-19 vaccines through transcriptomic pathways involved in the host response to SARS-CoV-2 infection is key to understand how vaccines work, and for the development of optimized COVID-19 vaccines that can prevent the emergence of SARS-CoV-2 variants of concern (VoCs) and future outbreaks. In this study, we investigated the effects of vaccination with a modified vaccinia virus Ankara (MVA)-based vector expressing the full-length SARS-CoV-2 spike protein (MVA-S) on the lung transcriptome from susceptible K18-hACE2 mice after SARS-CoV-2 infection. One dose of MVA-S regulated genes related to viral infection control, inflammation processes, T-cell response, cytokine production and IFN-γ signalling. Down-regulation of Rhcg and Tnfsf18 genes post-vaccination with one and two doses of MVA-S may represent a mechanism for controlling infection immunity and vaccine-induced protection. One dose of MVA-S provided partial protection with a distinct lung transcriptomic profile to healthy animals, while two doses of MVA-S fully protected against infection with a transcriptomic profile comparable to that of non-vaccinated healthy animals. This suggests that the MVA-S booster generates a robust and rapid antigen-specific immune response preventing virus infection. Notably, down-regulation of Atf3 and Zbtb16 genes in mice vaccinated with two doses of MVA-S may contribute to vaccine control of innate immune system and inflammation processes in the lungs during SARS-CoV-2 infection. This study shows host transcriptomic mechanisms likely involved in the MVA-S vaccine-mediated immune response against SARS-CoV-2 infection, which could help in improving vaccine dose assessment and developing novel, well-optimized SARS-CoV-2 vaccine candidates against prevalent or emerging VoCs.

Blood transcriptomics analysis offers insights into variant-specific immune response to SARS-CoV-2

Bulk RNA sequencing (RNA-seq) of blood is typically used for gene expression analysis in biomedical research but is still rarely used in clinical practice. In this study, we argue that RNA-seq should be considered a routine diagnostic tool, as it offers not only insights into aberrant gene expression and splicing but also delivers additional readouts on immune cell type composition as well as B-cell and T-cell receptor (BCR/TCR) repertoires. We demonstrate that RNA-seq offers vital insights into a patient's immune status via integrative analysis of RNA-seq data from patients infected with various SARS-CoV-2 variants (in total 240 samples with up to 200 million reads sequencing depth). We compare the results of computational cell-type deconvolution methods (e.g., MCP-counter, xCell, EPIC, quanTIseq) to complete blood count data, the current gold standard in clinical practice. We observe varying levels of lymphocyte depletion and significant differences in neutrophil levels between SARS-CoV-2 variants. Additionally, we identify B and T cell receptor (BCR/TCR) sequences using the tools MiXCR and TRUST4 to show that - combined with sequence alignments and pBLAST - they could be used to classify a patient's disease. Finally, we investigated the sequencing depth required for such analyses and concluded that 10 million reads per sample is sufficient. In conclusion, our study reveals that computational cell-type deconvolution and BCR/TCR methods using bulk RNA-seq analyses can supplement missing CBC data and offer insights into immune responses, disease severity, and pathogen-specific immunity, all achievable with a sequencing depth of 10 million reads per sample.

Molecular correlates of vaccine-induced protection against typhoid fever

BACKGROUNDTyphoid fever is caused by the Gram-negative bacterium Salmonella enterica serovar Typhi and poses a substantial public health burden worldwide. Vaccines have been developed based on the surface Vi-capsular polysaccharide of S. Typhi; these include a plain-polysaccharide-based vaccine, ViPS, and a glycoconjugate vaccine, ViTT. To understand immune responses to these vaccines and their vaccine-induced immunological protection, molecular signatures were analyzed using bioinformatic approaches.METHODSBulk RNA-Seq data were generated from blood samples obtained from adult human volunteers enrolled in a vaccine trial, who were then challenged with S. Typhi in a controlled human infection model (CHIM). These data were used to conduct differential gene expression analyses, gene set and modular analyses, B cell repertoire analyses, and time-course analyses at various post-vaccination and post-challenge time points between participants receiving ViTT, ViPS, or a control meningococcal vaccine.RESULTSTranscriptomic responses revealed strong differential molecular signatures between the 2 typhoid vaccines, mostly driven by the upregulation in humoral immune signatures, including selective usage of immunoglobulin heavy chain variable region (IGHV) genes and more polarized clonal expansions. We describe several molecular correlates of protection against S. Typhi infection, including clusters of B cell receptor (BCR) clonotypes associated with protection, with known binders of Vi-polysaccharide among these.CONCLUSIONThe study reports a series of contemporary analyses that reveal the transcriptomic signatures after vaccination and infectious challenge, while identifying molecular correlates of protection that may inform future vaccine design and assessment.TRIAL REGISTRATIONClinicalTrials.gov NCT02324751.

Unconventional MAIT cell responses to bacterial infections

Mucosal Associated Invariant T cells (MAIT) exert potent antimicrobial activity through direct recognition of metabolite-MR1 complexes and indirect activation by inflammatory cytokines. Additionally, via licensing of antigen presenting cells, MAIT cells orchestrate humoral and cellular adaptive immunity. Our recent understanding of molecular mechanisms of MAIT cell activation, and of the signals required to differentiate them in polarised subsets, pave the way for harnessing their functionality through small molecules or adoptive cell therapy.

Controlled Human Infection Models To Accelerate Vaccine Development

The timelines for developing vaccines against infectious diseases are lengthy, and often vaccines that reach the stage of large phase 3 field trials fail to provide the desired level of protective efficacy. The application of controlled human challenge models of infection and disease at the appropriate stages of development could accelerate development of candidate vaccines and, in fact, has done so successfully in some limited cases. Human challenge models could potentially be used to gather critical information on pathogenesis, inform strain selection for vaccines, explore cross-protective immunity, identify immune correlates of protection and mechanisms of protection induced by infection or evoked by candidate vaccines, guide decisions on appropriate trial endpoints, and evaluate vaccine efficacy. We prepared this report to motivate fellow scientists to exploit the potential capacity of controlled human challenge experiments to advance vaccine development. In this review, we considered available challenge models for 17 infectious diseases in the context of the public health importance of each disease, the diversity and pathogenesis of the causative organisms, the vaccine candidates under development, and each model's capacity to evaluate them and identify correlates of protective immunity. Our broad assessment indicated that human challenge models have not yet reached their full potential to support the development of vaccines against infectious diseases. On the basis of our review, however, we believe that describing an ideal challenge model is possible, as is further developing existing and future challenge models.

Transcriptomic profiling in Cutaneous Leishmaniasis patients

INTRODUCTION

Cutaneous leishmaniasis (CL), caused by different Leishmania parasite species, is associated with parasite-induced immune-mediated skin inflammation and ulceration. Whereas many CL studies focus on gene expression signatures in mouse models, the transcriptional response driving human patients in the field is less characterized. Human studies in CL disease provide the opportunity to directly investigate the host-pathogen interaction in the cutaneous lesion site.

AREAS COVERED

Advances in high-throughput sequencing technologies, particularly their application for evaluation of the global gene expression changes, have made transcriptomics as a powerful tool to understand the pathogen-host molecular interactions.

EXPERT COMMENTARY

In this review, we focus on the transcriptomics studies that have been performed so far on human blood or tissue-driven samples to investigate Leishmania parasites interplay with the CL patients. Further, we summarize microarray and RNA-seq studies associated with lesion biopsies of CL patients to discuss how current whole genome analysis along with systems biology approaches have developed novel CL biomarkers for further applications, not only for research, but also for accelerating vaccine development.

The Application of Single-Cell RNA Sequencing in Vaccinology

Single-cell RNA sequencing allows highly detailed profiling of cellular immune responses from limited-volume samples, advancing prospects of a new era of systems immunology. The power of single-cell RNA sequencing offers various opportunities to decipher the immune response to infectious diseases and vaccines. Here, we describe the potential uses of single-cell RNA sequencing methods in prophylactic vaccine development, concentrating on infectious diseases including COVID-19. Using examples from several diseases, we review how single-cell RNA sequencing has been used to evaluate the immunological response to different vaccine platforms and regimens. By highlighting published and unpublished single-cell RNA sequencing studies relevant to vaccinology, we discuss some general considerations how the field could be enriched with the widespread adoption of this technology.

The Current Status of Enteric Fever Diagnostics and Implications for Disease Control

Enteric (typhoid) fever remains a problem in low- and middle-income countries that lack the infrastructure to maintain sanitation and where inadequate diagnostic methods have restricted our ability to identify and control the disease more effectively. As we move into a period of potential disease elimination through the introduction of typhoid conjugate vaccine (TCV), we again need to reconsider the role of typhoid diagnostics in how they can aid in facilitating disease control. Recent technological advances, including serology, transcriptomics, and metabolomics, have provided new insights into how we can detect signatures of invasive Salmonella organisms interacting with the host during infection. Many of these new techniques exhibit potential that could be further explored with the aim of creating a new enteric fever diagnostic to work in conjunction with TCV. We need a sustained effort within the enteric fever field to accelerate, validate, and ultimately introduce 1 (or more) of these methods to facilitate the disease control initiative. The window of opportunity is still open, but we need to recognize the need for communication with other research areas and commercial organizations to assist in the progression of these diagnostic approaches. The elimination of enteric fever is now becoming a real possibility, but new diagnostics need to be part of the equation and factored into future calculations for disease control.

Expansion of Single Cell Transcriptomics Data of SARS-CoV Infection in Human Bronchial Epithelial Cells to COVID-19

Background

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of coronavirus disease 19 (COVID-19) that was emerged as a new member of coronaviruses since December 2019 in Wuhan, China and then after was spread in all continentals. Since SARS-CoV-2 has shown about 77.5% similarity to SARS-CoV, the transcriptome and immunological regulations of SARS-CoV-2 was expected to have high percentage of overlap with SARS-CoV.

Results

In this study, we applied the single cell transcriptomics data of human bronchial epithelial cells (2B4 cell line) infected with SARS-CoV, which was annotated in the Expression Atlas database to expand this data to COVID-19. In addition, we employed system biology methods including gene ontology (GO) and Reactome pathway analyses to define functional genes and pathways in the infected cells with SARS-CoV. The transcriptomics analysis on the Expression Atlas database revealed that most genes from infected 2B4 cell line with SARS-CoV were downregulated leading to immune system hyperactivation, induction of signaling pathways, and consequently a cytokine storm. In addition, GO:0016192 (vesicle-mediated transport), GO:0006886 (intracellular protein transport), and GO:0006888 (ER to Golgi vesicle-mediated transport) were shown as top three GOs in the ontology network of infected cells with SARS-CoV. Meanwhile, R-HAS-6807070 (phosphatase and tensin homolog or PTEN regulation) showed the highest association with other Reactome pathways in the network of infected cells with SARS-CoV. PTEN plays a critical role in the activation of dendritic cells, B- and T-cells, and secretion of proinflammatory cytokines, which cooperates with downregulated genes in the promotion of cytokine storm in the COVID-19 patients.

Conclusions

Based on the high similarity percentage of the transcriptome of SARS-CoV with SARS-CoV-2, the data of immunological regulations, signaling pathways, and proinflammatory cytokines in SARS-CoV infection can be expanded to COVID-19 to have a valid platform for future pharmaceutical and vaccine studies.

The combination of artificial intelligence and systems biology for intelligent vaccine design

INTRODUCTION

A new body of evidence depicts the applications of artificial intelligence and systems biology in vaccine design and development. The combination of both approaches shall revolutionize healthcare, accelerating clinical trial processes and reducing the costs and time involved in drug research and development.

AREAS COVERED

This review explores the basics of artificial intelligence and systems biology approaches in the vaccine development pipeline. The topics include a detailed description of epitope prediction tools for designing epitope-based vaccines and agent-based models for immune system response prediction, along with a focus on their potentiality to facilitate clinical trial phases.

EXPERT OPINION

Artificial intelligence and systems biology offer the opportunity to avoid the inefficiencies and failures that arise in the classical vaccine development pipeline. One promising solution is the combination of both methodologies in a multiscale perspective through an accurate pipeline. We are entering an 'in silico era' in which scientific partnerships, including a more and more increasing creation of an 'ecosystem' of collaboration and multidisciplinary approach, are relevant for addressing the long and risky road of vaccine discovery and development. In this context, regulatory guidance should be developed to qualify the in silico trials as evidence for intelligent vaccine development.

Immune and Metabolic Signatures of COVID-19 Revealed by Transcriptomics Data Reuse

The current pandemic of coronavirus disease 19 (COVID-19) has affected millions of individuals and caused thousands of deaths worldwide. The pathophysiology of the disease is complex and mostly unknown. Therefore, identifying the molecular mechanisms that promote progression of the disease is critical to overcome this pandemic. To address such issues, recent studies have reported transcriptomic profiles of cells, tissues and fluids from COVID-19 patients that mainly demonstrated activation of humoral immunity, dysregulated type I and III interferon expression, intense innate immune responses and inflammatory signaling. Here, we provide novel perspectives on the pathophysiology of COVID-19 using robust functional approaches to analyze public transcriptome datasets. In addition, we compared the transcriptional signature of COVID-19 patients with individuals infected with SARS-CoV-1 and Influenza A (IAV) viruses. We identified a core transcriptional signature induced by the respiratory viruses in peripheral leukocytes, whereas the absence of significant type I interferon/antiviral responses characterized SARS-CoV-2 infection. We also identified the higher expression of genes involved in metabolic pathways including heme biosynthesis, oxidative phosphorylation and tryptophan metabolism. A BTM-driven meta-analysis of bronchoalveolar lavage fluid (BALF) from COVID-19 patients showed significant enrichment for neutrophils and chemokines, which were also significant in data from lung tissue of one deceased COVID-19 patient. Importantly, our results indicate higher expression of genes related to oxidative phosphorylation both in peripheral mononuclear leukocytes and BALF, suggesting a critical role for mitochondrial activity during SARS-CoV-2 infection. Collectively, these data point for immunopathological features and targets that can be therapeutically exploited to control COVID-19.

Response to a DNA vaccine against the H5N1 virus depending on the chicken line and number of doses

Background

Avian influenza virus infections cause significant economic losses on poultry farms and pose the threat of a possible pandemic outbreak. Routine vaccination of poultry against avian influenza is not recommended in Europe, however it has been ordered in some other countries, and more countries are considering use of the avian influenza vaccine as a component of their control strategy. Although a variety of such vaccines have been tested, most research has concentrated on specific antibodies and challenge experiments.

Methods

We monitored the transcriptomic response to a DNA vaccine encoding hemagglutinin from the highly pathogenic H5N1 avian influenza virus in the spleens of broiler and layer chickens. Moreover, in layer chickens the response to one and two doses of the vaccine was compared.

Results

All groups of birds immunized with two doses of the vaccine responded at the humoral level by producing specific anti-hemagglutinin antibodies. A response to the vaccine was also detected in the spleen transcriptomes. Differential expression of many genes encoding noncoding RNA and proteins functionally connected to the neuroendocrine-immune system was observed in different immunized groups.

Conclusion

Broiler chickens showed a higher number and wider range of fold-changes in the transcriptional response than laying hens.

The Ratiometric Transcript Signature MX2/GPR183 Is Consistently Associated With RTS,S-Mediated Protection Against Controlled Human Malaria Infection

The RTS,S/AS01 vaccine provides partial protection against Plasmodium falciparum infection but determinants of protection and/or disease are unclear. Previously, anti-circumsporozoite protein (CSP) antibody titers and blood RNA signatures were associated with RTS,S/AS01 efficacy against controlled human malaria infection (CHMI). By analyzing host blood transcriptomes from five RTS,S vaccination CHMI studies, we demonstrate that the transcript ratio MX2/GPR183, measured 1 day after third immunization, discriminates protected from non-protected individuals. This ratiometric signature provides information that is complementary to anti-CSP titer levels for identifying RTS,S/AS01 immunized people who developed protective immunity and suggests a role for interferon and oxysterol signaling in the RTS,S mode of action.

Use of gene expression studies to investigate the human immunological response to malaria infection

Background

Transcriptional profiling of the human immune response to malaria has been used to identify diagnostic markers, understand the pathogenicity of severe disease and dissect the mechanisms of naturally acquired immunity (NAI). However, interpreting this body of work is difficult given considerable variation in study design, definition of disease, patient selection and methodology employed. This work details a comprehensive review of gene expression profiling (GEP) of the human immune response to malaria to determine how this technology has been applied to date, instances where this has advanced understanding of NAI and the extent of variability in methodology between studies to allow informed comparison of data and interpretation of results.

Methods

Datasets from the gene expression omnibus (GEO) including the search terms; ‘plasmodium’ or ‘malaria’ or ‘sporozoite’ or ‘merozoite’ or ‘gametocyte’ and ‘Homo sapiens’ were identified and publications analysed. Datasets of gene expression changes in relation to malaria vaccines were excluded.

Results

Twenty-three GEO datasets and 25 related publications were included in the final review. All datasets related to Plasmodium falciparum infection, except two that related to Plasmodium vivax infection. The majority of datasets included samples from individuals infected with malaria ‘naturally’ in the field (n = 13, 57%), however some related to controlled human malaria infection (CHMI) studies (n = 6, 26%), or cells stimulated with Plasmodium in vitro (n = 6, 26%). The majority of studies examined gene expression changes relating to the blood stage of the parasite. Significant heterogeneity between datasets was identified in terms of study design, sample type, platform used and method of analysis. Seven datasets specifically investigated transcriptional changes associated with NAI to malaria, with evidence supporting suppression of the innate pro-inflammatory response as an important mechanism for this in the majority of these studies. However, further interpretation of this body of work was limited by heterogeneity between studies and small sample sizes.

Conclusions

GEP in malaria is a potentially powerful tool, but to date studies have been hypothesis generating with small sample sizes and widely varying methodology. As CHMI studies are increasingly performed in endemic settings, there will be growing opportunity to use GEP to understand detailed time-course changes in host response and understand in greater detail the mechanisms of NAI.

Microarray Gene Expression Dataset Re-analysis Reveals Variability in Influenza Infection and Vaccination

Influenza, a communicable disease, affects thousands of people worldwide. Young children, elderly, immunocompromised individuals and pregnant women are at higher risk for being infected by the influenza virus. Our study aims to highlight differentially expressed genes in influenza disease compared to influenza vaccination, including variability due to age and sex. To accomplish our goals, we conducted a meta-analysis using publicly available microarray expression data. Our inclusion criteria included subjects with influenza, subjects who received the influenza vaccine and healthy controls. We curated 18 microarray datasets for a total of 3,481 samples (1,277 controls, 297 influenza infection, 1,907 influenza vaccination). We pre-processed the raw microarray expression data in R using packages available to pre-process Affymetrix and Illumina microarray platforms. We used a Box-Cox power transformation of the data prior to our down-stream analysis to identify differentially expressed genes. Statistical analyses were based on linear mixed effects model with all study factors and successive likelihood ratio tests (LRT) to identify differentially-expressed genes. We filtered LRT results by disease (Bonferroni adjusted p < 0.05) and used a two-tailed 10% quantile cutoff to identify biologically significant genes. Furthermore, we assessed age and sex effects on the disease genes by filtering for genes with a statistically significant (Bonferroni adjusted p < 0.05) interaction between disease and age, and disease and sex. We identified 4,889 statistically significant genes when we filtered the LRT results by disease factor, and gene enrichment analysis (gene ontology and pathways) included innate immune response, viral process, defense response to virus, Hematopoietic cell lineage and NF-kappa B signaling pathway. Our quantile filtered gene lists comprised of 978 genes each associated with influenza infection and vaccination. We also identified 907 and 48 genes with statistically significant (Bonferroni adjusted p < 0.05) disease-age and disease-sex interactions, respectively. Our meta-analysis approach highlights key gene signatures and their associated pathways for both influenza infection and vaccination. We also were able to identify genes with an age and sex effect. This gives potential for improving current vaccines and exploring genes that are expressed equally across ages when considering universal vaccinations for influenza.

How genomics can be used to understand host susceptibility to enteric infection, aiding in the development of vaccines and immunotherapeutic interventions

Thanks to the modern sequencing era, the extent to which infectious disease imposes selective pressures on the worldwide human population is being revealed. This is aiding our understanding of the underlying immunological and host mechanistic defenses against these pathogens, as well as potentially assisting in the development of vaccines and therapeutics to control them. As a consequence, the workshop "How genomics can be used to understand host susceptibility to enteric infection, aiding in the development of vaccines and immunotherapeutic interventions" at the VASE 2018 meeting, aimed to discuss how genomics and related tools could be used to assist Shigella and ETEC vaccine development. The workshop featured four short presentations which highlighted how genomic applications can be used to assist in the identification of genetic patterns related to the virulence of disease, or host genetic factors that could contribute to immunity or successful vaccine responses. Following the presentations, there was an open debate with workshop attendees to discuss the best ways to utilise such genomic studies, to improve or accelerate the process of both Shigella and ETEC vaccine development. The workshop concluded by making specific recommendations on how genomic research methods could be strengthened and harmonised within the ETEC and Shigella research communities.

Can biomarkers improve the rational use of antibiotics?

PURPOSE OF REVIEW

We aim to review recent literature about the use of biomarkers to guide the initiation and duration of antibiotic treatments for suspected bacterial infections.

RECENT FINDINGS

Several good quality meta-analyses show that procalcitonin can be safely used to guide antibiotic-related decisions, especially for respiratory infections, thereby decreasing unnecessary antibiotic exposure. Furthermore, the use of CRP-based algorithms to guide antibiotic initiation in primary care patients with acute respiratory infections is associated with a reduction in antibiotic use without an increase in adverse events. Regarding neutrophil CD64 and serum amyloid A, more good-quality evidence is needed to assess their utility as biomarkers to tailor antibiotic use. Finally, transcriptomics, metabolomics and proteomics are promising tools for the development of tests to differentiate specific host responses to viral, bacterial and noninfectious stimuli, but such tests still need further validation.

SUMMARY

Evidence shows that the use of biomarkers, procalcitonin and CRP, can safely reduce unnecessary antibiotic prescriptions in certain infectious syndromes. The clinical utility of host-based strategies such as transcriptomics, metabolomics and proteomics for the diagnosis of infectious diseases has yet to be evaluated, as well as considerations such as costs, technical complexity and result turnaround time.

Systems vaccinology and big data in the vaccine development chain

Systems vaccinology has proven a fascinating development in the last decade. Where traditionally vaccine development has been dominated by trial and error, systems vaccinology is a tool that provides novel and comprehensive understanding if properly used. Data sets retrieved from systems‐based studies endorse rational design and effective development of safe and efficacious vaccines. In this review we first describe different omics‐techniques that form the pillars of systems vaccinology. In the second part, the application of systems vaccinology in the different stages of vaccine development is described. Overall, this review shows that systems vaccinology has become an important tool anywhere in the vaccine development chain.

Detection of host pathways universally inhibited after Plasmodium yoelii infection for immune intervention

Malaria is a disease with diverse symptoms depending on host immune status and pathogenicity of Plasmodium parasites. The continuous parasite growth within a host suggests mechanisms of immune evasion by the parasite and/or immune inhibition in response to infection. To identify pathways commonly inhibited after malaria infection, we infected C57BL/6 mice with four Plasmodium yoelii strains causing different disease phenotypes and 24 progeny of a genetic cross. mRNAs from mouse spleens day 1 and/or day 4 post infection (p.i.) were hybridized to a mouse microarray to identify activated or inhibited pathways, upstream regulators, and host genes playing an important role in malaria infection. Strong interferon responses were observed after infection with the N67 strain, whereas initial inhibition and later activation of hematopoietic pathways were found after infection with 17XNL parasite, showing unique responses to individual parasite strains. Inhibitions of pathways such as Th1 activation, dendritic cell (DC) maturation, and NFAT immune regulation were observed in mice infected with all the parasite strains day 4 p.i., suggesting universally inhibited immune pathways. As a proof of principle, treatment of N67-infected mice with antibodies against T cell receptors OX40 or CD28 to activate the inhibited pathways enhanced host survival. Controlled activation of these pathways may provide important strategies for better disease management and for developing an effective vaccine.

Poxvirus-based vector systems and the potential for multi-valent and multi-pathogen vaccines

INTRODUCTION

With the increasing number of vaccines and vaccine-preventable diseases, the pressure to generate multi-valent and multi-pathogen vaccines grows. Combining individual established vaccines to generate single-shot formulations represents an established path, with significant ensuing public health and cost benefits. Poxvirus-based vector systems have the capacity for large recombinant payloads and have been widely used as platforms for the development of recombinant vaccines encoding multiple antigens, with considerable clinical trials activity and a number of registered and licensed products.

AREAS COVERED

Herein we discuss design strategies, production processes, safety issues, regulatory hurdles and clinical trial activities, as well as pertinent new technologies such as systems vaccinology and needle-free delivery. Literature searches used PubMed, Google Scholar and clinical trials registries, with a focus on the recombinant vaccinia-based systems, Modified Vaccinia Ankara and the recently developed Sementis Copenhagen Vector.

EXPERT COMMENTARY

Vaccinia-based platforms show considerable promise for the development of multi-valent and multi-pathogen vaccines, especially with recent developments in vector technologies and manufacturing processes. New methodologies for defining immune correlates and human challenge models may also facilitate bringing such vaccines to market.

Sustainable vaccine development: a vaccine manufacturer's perspective

Vaccination remains the most cost-effective public health intervention after clean water, and the benefits impressively outweigh the costs. The efforts needed to fulfill the steadily growing demands for next-generation and novel vaccines designed for emerging pathogens and new indications are only realizable in a sustainable business model. Vaccine development can be fast-tracked through strengthening international collaborations, and the continuous innovation of technologies to accelerate their design, development, and manufacturing. However, these processes should be supported by a balanced project portfolio, and by managing sustainable vaccine procurement strategies for different types of markets. Collectively this will allow a gradual shift to a more streamlined and profitable vaccine production, which can significantly contribute to the worldwide effort to shape global health.