Global transcriptomic profiling using small volumes of whole blood: a cost-effective method for translational genomic biomarker identification in small animals

A single workflow for multi-species blood transcriptomics

BACKGROUND

Blood transcriptomic analysis is widely used to provide a detailed picture of a physiological state with potential outcomes for applications in diagnostics and monitoring of the immune response to vaccines. However, multi-species transcriptomic analysis is still a challenge from a technological point of view and a standardized workflow is urgently needed to allow interspecies comparisons.

RESULTS

Here, we propose a single and complete total RNA-Seq workflow to generate reliable transcriptomic data from blood samples from humans and from animals typically used in preclinical models. Blood samples from a maximum of six individuals and four different species (rabbit, non-human primate, mouse and human) were extracted and sequenced in triplicates. The workflow was evaluated using different wet-lab and dry-lab criteria, including RNA quality and quantity, the library molarity, the number of raw sequencing reads, the Phred-score quality, the GC content, the performance of ribosomal-RNA and globin depletion, the presence of residual DNA, the strandness, the percentage of coding genes, the number of genes expressed, and the presence of saturation plateau in rarefaction curves. We identified key criteria and their associated thresholds to be achieved for validating the transcriptomic workflow. In this study, we also generated an automated analysis of the transcriptomic data that streamlines the validation of the dataset generated.

CONCLUSIONS

Our study has developed an end-to-end workflow that should improve the standardization and the inter-species comparison in blood transcriptomics studies. In the context of vaccines and drug development, RNA sequencing data from preclinical models can be directly compared with clinical data and used to identify potential biomarkers of value to monitor safety and efficacy.

Blood Transcriptomics Analysis of Fish Exposed to Perfluoro Alkyls Substances: Assessment of a Non-Lethal Sampling Technique for Advancing Aquatic Toxicology Research

In contrast to mammals, the blood from other vertebrates such as fish contains nucleated red cells. Using a fathead minnow ( Pimephales promelas) oligonucleotide microarray, we compared altered transcripts in the liver and whole blood after exposure to environmentally relevant concentrations of perfluorooctanesulfonic acid (PFOS) and a mixture of seven types of perfluoro alkyl substances (PFAS), including perfluorooctanoic acid (PFOA). We used quantitative polymerase chain reactions and cell-based assays to confirm the main effects and found that blood responded with a greater number of altered genes than the liver. The exposure to PFAS altered similar genes with central roles in a cellular pathway in both tissues, including estrogen receptor α and peroxisome proliferator activator β and γ, indicating that the genes previously associated with PFAS exposure are differentially expressed in blood and liver. The altered transcripts are involved with cholesterol metabolism and mitochondrial function. Our data confirmed that PFAS are weak xenoestrogens and exert effects on DNA integrity. Gene expression profiling from blood samples not related with the immune system, including very-low-density lipoprotein, vitellogenin, estrogen receptor, and thyroid hormone receptor, demonstrated that blood is a useful tissue for assessing endocrine disruption in non-mammalian vertebrates. We conclude that the use of blood for non-lethal sampling in genomics studies is informative and particularly useful for assessing the effects of pollution in endangered species. Further, using blood will reduce animal use and widen the experimental design options for studying the effects of contaminant exposure on wildlife.

A Gene Expression Classifier from Whole Blood Distinguishes Benign from Malignant Lung Nodules Detected by Low-Dose CT

Low-dose CT (LDCT) is widely accepted as the preferred method for detecting pulmonary nodules. However, the determination of whether a nodule is benign or malignant involves either repeated scans or invasive procedures that sample the lung tissue. Noninvasive methods to assess these nodules are needed to reduce unnecessary invasive tests. In this study, we have developed a pulmonary nodule classifier (PNC) using RNA from whole blood collected in RNA-stabilizing PAXgene tubes that addresses this need. Samples were prospectively collected from high-risk and incidental subjects with a positive lung CT scan. A total of 821 samples from 5 clinical sites were analyzed. Malignant samples were predominantly stage 1 by pathologic diagnosis and 97% of the benign samples were confirmed by 4 years of follow-up. A panel of diagnostic biomarkers was selected from a subset of the samples assayed on Illumina microarrays that achieved a ROC-AUC of 0.847 on independent validation. The microarray data were then used to design a biomarker panel of 559 gene probes to be validated on the clinically tested NanoString nCounter platform. RNA from 583 patients was used to assess and refine the NanoString PNC (nPNC), which was then validated on 158 independent samples (ROC-AUC = 0.825). The nPNC outperformed three clinical algorithms in discriminating malignant from benign pulmonary nodules ranging from 6-20 mm using just 41 diagnostic biomarkers. Overall, this platform provides an accurate, noninvasive method for the diagnosis of pulmonary nodules in patients with non-small cell lung cancer. SIGNIFICANCE: These findings describe a minimally invasive and clinically practical pulmonary nodule classifier that has good diagnostic ability at distinguishing benign from malignant pulmonary nodules.

Transcriptomics of the Vaccine Immune Response: Priming With Adjuvant Modulates Recall Innate Responses After Boosting

Transcriptomic profiling of the immune response induced by vaccine adjuvants is of critical importance for the rational design of vaccination strategies. In this study, transcriptomics was employed to profile the effect of the vaccine adjuvant used for priming on the immune response following re-exposure to the vaccine antigen alone. Mice were primed with the chimeric vaccine antigen H56 of Mycobacterium tuberculosis administered alone or with the CAF01 adjuvant and boosted with the antigen alone. mRNA sequencing was performed on blood samples collected 1, 2, and 7 days after priming and after boosting. Gene expression analysis at day 2 after priming showed that the CAF01 adjuvanted vaccine induced a stronger upregulation of the innate immunity modules compared with the unadjuvanted formulation. The immunostimulant effect of the CAF01 adjuvant, used in the primary immunization, was clearly seen after a booster immunization with a low dose of antigen alone. One day after boost, we observed a strong upregulation of multiple genes in blood of mice primed with H56 + CAF01 compared with mice primed with the H56 alone. In particular, blood transcription modules related to innate immune response, such as monocyte and neutrophil recruitment, activation of antigen-presenting cells, and interferon response were activated. Seven days after boost, differential expression of innate response genes faded while a moderate differential expression of T cell activation modules was appreciable. Indeed, immunological analysis showed a higher frequency of H56-specific CD4+ T cells and germinal center B cells in draining lymph nodes, a strong H56-specific humoral response and a higher frequency of antibody-secreting cells in spleen of mice primed with H56 + CAF01. Taken together, these data indicate that the adjuvant used for priming strongly reprograms the immune response that, upon boosting, results in a stronger recall innate response essential for shaping the downstream adaptive response.

The Potentials and Pitfalls of Microarrays in Neglected Tropical Diseases: A Focus on Human Filarial Infections

Data obtained from expression microarrays enables deeper understanding of the molecular signatures of infectious diseases. It provides rapid and accurate information on how infections affect the clustering of gene expression profiles, pathways and networks that are transcriptionally active during various infection states compared to conventional diagnostic methods, which primarily focus on single genes or proteins. Thus, microarray technologies offer advantages in understanding host-parasite interactions associated with filarial infections. More importantly, the use of these technologies can aid diagnostics and helps translate current genomic research into effective treatment and interventions for filarial infections. Studying immune responses via microarray following infection can yield insight into genetic pathways and networks that can have a profound influence on the development of anti-parasitic vaccines.

Whole Blood RNA as a Source of Transcript-Based Nutrition- and Metabolic Health-Related Biomarkers

Blood cells are receiving an increasing attention as an easily accessible source of transcript-based biomarkers. We studied the feasibility of using mouse whole blood RNA in this context. Several paradigms were studied: (i) metabolism-related transcripts known to be affected in rat tissues and peripheral blood mononuclear cells (PBMC) by fasting and upon the development of high fat diet (HFD)-induced overweight were assessed in whole blood RNA of fasted rats and mice and of HFD-fed mice; (ii) retinoic acid (RA)-responsive genes in tissues were assessed in whole blood RNA of control and RA-treated mice; (iii) lipid metabolism-related transcripts previously identified in PBMC as potential biomarkers of metabolic health in a rat model were assessed in whole blood in an independent model, namely retinoblastoma haploinsufficient (Rb^+/-) mice. Blood was collected and stored in RNAlater^® at -80°C until analysis of selected transcripts by real-time RT-PCR. Comparable changes with fasting were detected in the expression of lipid metabolism-related genes when RNA from either PBMC or whole blood of rats or mice was used. HFD-induced excess body weight and fat mass associated with expected changes in the expression of metabolism-related genes in whole blood of mice. Changes in gene expression in whole blood of RA-treated mice reproduced known transcriptional actions of RA in hepatocytes and adipocytes. Reduced expression of Fasn, Lrp1, Rxrb and Sorl1 could be validated as early biomarkers of metabolic health in young Rb^+/- mice using whole blood RNA. Altogether, these results support the use of whole blood RNA in studies aimed at identifying blood transcript-based biomarkers of nutritional/metabolic status or metabolic health. Results also support reduced expression of Fasn, Lrp1, Rxrb and Sorl1 in blood cells at young age as potential biomarkers of metabolic robustness.

Toxicology Strategies for Drug Discovery: Present and Future

Attrition due to nonclinical safety represents a major issue for the productivity of pharmaceutical research and development (R&D) organizations, especially during the compound optimization stages of drug discovery and the early stages of clinical development. Focusing on decreasing nonclinical safety-related attrition is not a new concept, and various approaches have been experimented with over the last two decades. Front-loading testing funnels in Discovery with in vitro toxicity assays designed to rapidly identify unfavorable molecules was the approach adopted by most pharmaceutical R&D organizations a few years ago. However, this approach has also a non-negligible opportunity cost. Hence, significant refinements to the "fail early, fail often" paradigm have been proposed recently to reflect the complexity of accurately categorizing compounds with early data points without taking into account other important contextual aspects, in particular efficacious systemic and tissue exposures. This review provides an overview of toxicology approaches and models that can be used in pharmaceutical Discovery at the series/lead identification and lead optimization stages to guide and inform chemistry efforts, as well as a personal view on how to best use them to meet nonclinical safety-related attrition objectives consistent with a sustainable pharmaceutical R&D model. The scope of this review is limited to small molecules, as large molecules are associated with challenges that are quite different. Finally, a perspective on how several emerging technologies may impact toxicity evaluation is also provided.