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With age, the immune system becomes less effective, causing increased susceptibility to infection. Chronic CMV infection further impairs immune function and is associated with increased mortality in the elderly. CMV exposure elicits massive CD8+ T cell clonal expansions and diminishes the cytotoxic T cell response to subsequent infections, leading to the hypothesis that to maintain homeostasis, T cell clones are expelled from the repertoire, reducing T cell repertoire diversity and diminishing the ability to combat new infections. However, in humans, the impact of CMV infection on the structure and diversity of the underlying T cell repertoire remains uncharacterized. Using TCR β-chain immunosequencing, we observed that the proportion of the peripheral blood T cell repertoire composed of the most numerous 0.1% of clones is larger in the CMV seropositive and gradually increases with age. We found that the T cell repertoire in the elderly grows to accommodate CMV-driven clonal expansions while preserving its underlying diversity and clonal structure. Our observations suggest that the maintenance of large CMV-reactive T cell clones throughout life does not compromise the underlying repertoire. Alternatively, we propose that the diminished immunity in elderly individuals with CMV is due to alterations in cellular function rather than a reduction in CD8+ T cell repertoire diversity.

Summary Multi-omic profiling of human peripheral blood is increasingly utilized to identify biomarkers and pathophysiologic mechanisms of disease. The importance of these platforms in clinical and translational studies led us to investigate the impact of delayed blood processing on the numbers and state of peripheral blood mononuclear cells (PBMC) and on the plasma proteome. Similar to previous studies, we show minimal effects of delayed processing on the numbers and general phenotype of PBMC up to 18 hours. In contrast, profound changes in the single-cell transcriptome and composition of the plasma proteome become evident as early as 6 hours after blood draw. These reflect patterns of cellular activation across diverse cell types that lead to progressive distancing of the gene expression state and plasma proteome from native in vivo biology. Differences accumulating during an overnight rest (18 hours) could confound relevant biologic variance related to many underlying disease states., Graphical abstract, Highlights • Studies of human blood cells and plasma are highly sensitive to process variability • Time variability distorts biology in cutting-edge single-cell and multiplex assays • Longitudinal, multi-modal, and aligned data enable data qualification and exploration • Dataset holds potential novel, multi-modal biological correlations and hypotheses, Molecular Physiology ; Immunology ; Proteomics ; Transcriptomics

Over the last decade, multiple studies have shown that signaling proteins activated in different temporal patterns—such as oscillatory, transient, and sustained—can result in distinct gene expression patterns or cell fates. However, the molecular events that ensure appropriate stimulus- and dose-dependent dynamics are not often understood and are difficult to investigate. Here, we used single-cell analysis to dissect the mechanisms underlying the stimulus- and dose-encoding patterns in the innate immune signaling network. We found that Toll-like receptor (TLR) and interleukin-1 receptor (IL-1R) signaling dynamics relied on a dose-dependent, auto-inhibitory loop that rendered cells refractory to further stimulation. Using inducible gene expression and optogenetics to perturb the network at different levels, we identified the IL-1R–associated kinase1 (IRAK1) as the dose-sensing node responsible for limiting signal flow during the innate immune response. Although the kinase activity of IRAK1 was not required for signal propagation, it played a critical role in inhibiting the nucleocytoplasmic oscillations of the transcription factor NF-κB. Thus, protein activities that may be “dispensable” from a topological perspective can nevertheless be essential in shaping the dynamic response to the external environment.

During the course of a bacterial infection, cells are exposed simultaneously to a range of bacterial and host factors, which converge on the central transcription factor nuclear factor (NF)-κB. How do single cells integrate and process these converging stimuli? Here we tackle the question of how cells process combinatorial signals by making quantitative single-cell measurements of the NF-κB response to combinations of bacterial lipopolysaccharide and the stress cytokine tumor necrosis factor. We found that cells encode the presence of both stimuli via the dynamics of NF-κB nuclear translocation in individual cells, suggesting the integration of NF-κB activity for these stimuli occurs at the molecular and pathway level. However, the gene expression and cytokine secretion response to combinatorial stimuli were more complex, suggesting that other factors in addition to NF-κB contribute to signal integration at downstream layers of the response. Taken together, our results support the theory that during innate immune threat assessment, a pathogen recognized as both foreign and harmful will recruit an enhanced immune response. Our work highlights the remarkable capacity of individual cells to process multiple input signals and suggests that a deeper understanding of signal integration mechanisms will facilitate efforts to control dysregulated immune responses.

Most features of NF-κB activation dynamics vary significantly with respect to ligand type and concentration. The distribution of the time between two nuclear entries is an invariant feature in populations but not individual cells, suggesting an additional level of control, which regulates the overall distribution of translocation timing., The activation dynamics of nuclear factor (NF)-κB have been shown to affect downstream gene expression. On activation, NF-κB shuttles back and forth across the nuclear envelope. Many dynamic features of this shuttling have been characterized, and most features vary significantly with respect to ligand type and concentration. Here, we report an invariant feature with regard to NF-κB dynamics in cellular populations: the distribution—the average, as well as the variance—of the time between two nuclear entries (the period). We find that this period is conserved, regardless of concentration and across several different ligands. Intriguingly, the distributions observed at the population level are not observed in individual cells over 20-h time courses. Instead, the average period of NF-κB nuclear translocation varies considerably among single cells, and the variance is much smaller within a cell than that of the population. Finally, analysis of daughter-cell pairs and isogenic populations indicates that the dynamics of the NF-κB response is heritable but diverges over multiple divisions, on the time scale of weeks to months. These observations are contrary to the existing theory of NF-κB dynamics and suggest an additional level of control that regulates the overall distribution of translocation timing at the population level.

Whole-cell modeling promises to facilitate scientific inquiry by prioritizing future experiments based on existing datasets. To test this promise, we compared simulated growth rates with new measurements for all viable single-gene disruption strains in Mycoplasma genitalium. The discrepancies between simulations and experiments led to novel model predictions about specific kinetic parameters that we subsequently validated. These findings represent the first application of whole-cell modeling to accelerate biological discovery.

Recent genome-wide screens of host genetic requirements for viral infection have reemphasized the critical role of host metabolism in enabling the production of viral particles. In this review, we highlight the metabolic aspects of viral infection found in these studies, and focus on the opportunities these requirements present for metabolic engineers. In particular, the objectives and approaches that metabolic engineers use are readily comparable to the behaviors exhibited by viruses during infection. As a result, metabolic engineers have a unique perspective that could lead to novel and effective methods to combat viral infection.

Background Lipopolysaccharide (LPS), found in the outer membrane of gram-negative bacteria, elicits a strong response from the transcription factor family Nuclear factor (NF)-κB via Toll-like receptor (TLR) 4. The cellular response to lipopolysaccharide varies depending on the source and preparation of the ligand, however. Our goal was to compare single-cell NF-κB dynamics across multiple sources and concentrations of LPS. Methodology/Principal Findings Using live-cell fluorescence microscopy, we determined the NF-κB activation dynamics of hundreds of single cells expressing a p65-dsRed fusion protein. We used computational image analysis to measure the nuclear localization of the fusion protein in the cells over time. The concentration range spanned up to nine orders of magnitude for three E. coli LPS preparations. We find that the LPS preparations induce markedly different responses, even accounting for potency differences. We also find that the ability of soluble TNF receptor to affect NF-κB dynamics varies strikingly across the three preparations. Conclusions/Significance Our work strongly suggests that the cellular response to LPS is highly sensitive to the source and preparation of the ligand. We therefore caution that conclusions drawn from experiments using one preparation may not be applicable to LPS in general.

SummaryUnderstanding how complex phenotypes arise from individual molecules and their interactions is a primary challenge in biology that computational approaches are poised to tackle. We report a whole-cell computational model of the life cycle of the human pathogen Mycoplasma genitalium that includes all of its molecular components and their interactions. An integrative approach to modeling that combines diverse mathematics enabled the simultaneous inclusion of fundamentally different cellular processes and experimental measurements. Our whole-cell model accounts for all annotated gene functions and was validated against a broad range of data. The model provides insights into many previously unobserved cellular behaviors, including in vivo rates of protein-DNA association and an inverse relationship between the durations of DNA replication initiation and replication. In addition, experimental analysis directed by model predictions identified previously undetected kinetic parameters and biological functions. We conclude that comprehensive whole-cell models can be used to facilitate biological discovery.

Recent reports have indicated that mesenchymal stromal cells (MSCs) from bone marrow have a potential in vascular remodeling and angiogenesis. Here, we report a unique phenomenon that under serum-deprived conditions MSCs survive and replicate. Secretome analysis of MSCs grown under serum-deprived conditions (SD-MSCs) identified a significant upregulation of prosurvival and angiogenic factors including VEGF-A, ANGPTs, IGF-1, and HGF. An ex vivo rat aortic assay demonstrated longer neovascular sprouts generated from rat aortic rings cultured in SD-MSC-conditioned media compared to neovascular sprouts from aortas grown in MSC-conditioned media. With prolonged serum deprivation, a subpopulation of SD-MSCs began to exhibit an endothelial phenotype. This population expressed endothelial-specific proteins including VEGFR2, Tie2/TEK, PECAM/CD31, and eNOS and also demonstrated the ability to uptake acetylated LDL. SD-MSCs also exhibited enhanced microtubule formation in an in vitro angiogenesis assay. Modified chick chorioallantoic membrane (CAM) angiogenesis assays showed significantly higher angiogenic potential for SD-MSCs compared to MSCs. Analysis of CAMs grown with SD-MSCs identified human-specific CD31-positive cells in vascular structures. We conclude that under the stress of serum deprivation MSCs are highly angiogenic and a population of these cells has the potential to differentiate into endothelial-like cells.