The current routine use of adjuvants in human vaccines provides a strong incentive to increase our understanding of how adjuvants differ in their ability to stimulate innate immunity and consequently enhance vaccine immunogenicity. Here, we evaluated gene expression profiles in cells from whole blood elicited in naive subjects receiving the hepatitis B surface antigen formulated with different adjuvants. We identified a core innate gene signature emerging 1 day after the second vaccination and that was shared by the recipients of vaccines formulated with adjuvant systems AS01B, AS01E, or AS03. This core signature associated with the magnitude of the hepatitis B surface-specific antibody response and was characterized by positive regulation of genes associated with interferon-related responses or the innate cell compartment and by negative regulation of natural killer cell–associated genes. Analysis at the individual subject level revealed that the higher immunogenicity of AS01B-adjuvanted vaccine was linked to its ability to induce this signature in most vaccinees even after the first vaccination. Therefore, our data suggest that adjuvanticity is not strictly defined by the nature of the receptors or signaling pathways it activates but by the ability of the adjuvant to consistently induce a core inflammatory signature across individuals.

Investigating the physiology of cyanobacteria cultured under a diel light regime is relevant for a better understanding of the resulting growth characteristics and for specific biotechnological applications that are foreseen for these photosynthetic organisms. Here, we present the results of a multiomics study of the model cyanobacterium Synechocystis sp. strain PCC 6803, cultured in a lab-scale photobioreactor in physiological conditions relevant for large-scale culturing. The culture was sparged with N 2 and CO 2 , leading to an anoxic environment during the dark period. Growth followed the availability of light. Metabolite analysis performed with 1 H nuclear magnetic resonance analysis showed that amino acids involved in nitrogen and sulfur assimilation showed elevated levels in the light. Most protein levels, analyzed through mass spectrometry, remained rather stable. However, several high-light-response proteins and stress-response proteins showed distinct changes at the onset of the light period. Microarray-based transcript analysis found common patterns of ϳ56% of the transcriptome following the diel regime. These oscillating transcripts could be grouped coarsely into genes that were upregulated and downregulated in the dark period. The accumulated glycogen was degraded in the anaerobic environment in the dark. A small part was degraded gradually, reflecting basic maintenance requirements of the cells in darkness. Surprisingly, the largest part was degraded rapidly in a short time span at the end of the dark period. This degradation could allow rapid formation of metabolic intermediates at the end of the dark period, preparing the cells for the resumption of growth at the start of the light period. IMPORTANCEIndustrial-scale biotechnological applications are anticipated for cyanobacteria. We simulated large-scale high-cell-density culturing of Synechocystis sp. PCC 6803 under a diel light regime in a lab-scale photobioreactor. In BG-11 medium, Synechocystis grew only in the light. Metabolite analysis grouped the collected samples according to the light and dark conditions. Proteome analysis suggested that the majority of enzyme-activity regulation was not hierarchical but rather occurred through enzyme activity regulation. An abrupt light-on condition induced high-light-stress proteins. Transcript analysis showed distinct patterns for the light and dark periods. Glycogen gradually accumulated in the light and was rapidly consumed in the last quarter of the dark period. This suggests that the circadian clock primed the cellular machinery for immediate resumption of growth in the light. Understanding cyanobacterial physiology in a diel environment is of interest to understand circadian regulation in general and for the utilization of these organisms in biotechnological applications. Our exploration of the effect of a diel light cycle on a cyanobacterial culture started with the wish to investigate the response of the metabolic network of the cells to the imposed repetitively fluctuating environment,...

BackgroundMost ordinary differential equation (ODE) based modeling studies in systems biology involve a hold-out validation step for model validation. In this framework a pre-determined part of the data is used as validation data and, therefore it is not used for estimating the parameters of the model. The model is assumed to be validated if the model predictions on the validation dataset show good agreement with the data. Model selection between alternative model structures can also be performed in the same setting, based on the predictive power of the model structures on the validation dataset. However, drawbacks associated with this approach are usually under-estimated.ResultsWe have carried out simulations by using a recently published High Osmolarity Glycerol (HOG) pathway from S.cerevisiae to demonstrate these drawbacks. We have shown that it is very important how the data is partitioned and which part of the data is used for validation purposes. The hold-out validation strategy leads to biased conclusions, since it can lead to different validation and selection decisions when different partitioning schemes are used. Furthermore, finding sensible partitioning schemes that would lead to reliable decisions are heavily dependent on the biology and unknown model parameters which turns the problem into a paradox. This brings the need for alternative validation approaches that offer flexible partitioning of the data. For this purpose, we have introduced a stratified random cross-validation (SRCV) approach that successfully overcomes these limitations.ConclusionsSRCV leads to more stable decisions for both validation and selection which are not biased by underlying biological phenomena. Furthermore, it is less dependent on the specific noise realization in the data. Therefore, it proves to be a promising alternative to the standard hold-out validation strategy.Electronic supplementary materialThe online version of this article (doi:10.1186/s12918-015-0180-0) contains supplementary material, which is available to authorized users.