Aging Impairs Recipient T Cell Intrinsic and Extrinsic Factors in Response to Transplantation

As increasing numbers of older people are listed for solid organ transplantation, there is an urgent need to better understand how aging modifies alloimmune responses. Here, we investigated whether aging impairs the ability of donor dendritic cells or recipient immunity to prime alloimmune responses to organ transplantation.Using murine experimental models, we found that aging impaired the host environment to expand and activate antigen specific CD8(+) T cells. Additionally, aging impaired the ability of polyclonal T cells to induce acute allograft rejection. However, the alloimmune priming capability of donor dendritic cells was preserved with aging.Aging impairs recipient responses, both T cell intrinsic and extrinsic, in response to organ transplantation

Predicting Ecological Roles in the Rhizosphere Using Metabolome and Transportome Modeling

The ability to obtain complete genome sequences from bacteria in environmental samples, such as soil samples from the rhizosphere, has highlighted the microbial diversity and complexity of environmental communities. However, new algorithms to analyze genome sequence information in the context of community structure are needed to enhance our understanding of the specific ecological roles of these organisms in soil environments. We present a machine learning approach using sequenced Pseudomonad genomes coupled with outputs of metabolic and transportomic computational models for identifying the most predictive molecular mechanisms indicative of a Pseudomonad's ecological role in the rhizosphere: a biofilm, biocontrol agent, promoter of plant growth, or plant pathogen. Computational predictions of ecological niche were highly accurate overall with models trained on transportomic model output being the most accurate (Leave One Out Validation F-scores between 0.82 and 0.89). The strongest predictive molecular mechanism features for rhizosphere ecological niche overlap with many previously reported analyses of Pseudomonad interactions in the rhizosphere, suggesting that this approach successfully informs a system-scale level understanding of how Pseudomonads sense and interact with their environments. The observation that an organism's transportome is highly predictive of its ecological niche is a novel discovery and may have implications in our understanding microbial ecology. The framework developed here can be generalized to the analysis of any bacteria across a wide range of environments and ecological niches making this approach a powerful tool for providing insights into functional predictions from bacterial genomic data