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Objective Fasting regimens can promote health, mitigate chronic immunological disorders, and improve age-related pathophysiological parameters in animals and humans. Several ongoing clinical trials are using fasting as a potential therapy for various conditions. Fasting alters metabolism by acting as a reset for energy homeostasis, but the molecular mechanisms underlying the beneficial effects of short-term fasting (STF) are not well understood, particularly at the systems or multiorgan level. Methods We performed RNA-sequencing in nine organs from mice fed ad libitum (0 h) or subjected to fasting five times (2–22 h). We applied a combination of multivariate analysis, differential expression analysis, gene ontology, and network analysis for an in-depth understanding of the multiorgan transcriptome. We used literature mining solutions, LitLab™ and Gene Retriever™, to identify the biological and biochemical terms significantly associated with our experimental gene set, which provided additional support and meaning to the experimentally derived gene and inferred protein data. Results We cataloged the transcriptional dynamics within and between organs during STF and discovered differential temporal effects of STF among organs. Using gene ontology enrichment analysis, we identified an organ network sharing 37 common biological pathways perturbed by STF. This network incorporates the brain, liver, interscapular brown adipose tissue, and posterior-subcutaneous white adipose tissue; hence, we named it the brain-liver-fats organ network. Using Reactome pathways analysis, we identified the immune system, dominated by T cell regulation processes, as a central and prominent target of systemic modulations during STF in this organ network. The changes we identified in specific immune components point to the priming of adaptive immunity and parallel the fine-tuning of innate immune signaling. Conclusions Our study provides a comprehensive multiorgan transcriptomic profiling of mice subjected to multiple periods of STF and provides new insights into the molecular modulators involved in the systemic immunotranscriptomic changes that occur during short-term energy loss.

A powerful feature of single-cell RNA-sequencing data analysis is the possibility to identify novel rare cell types. However, rare cell types are often missed by standard clustering approaches. We have developed CIARA (Cluster Independent Algorithm for the identification of markers of RAre cell types), a computational tool available in R and Python that outperforms existing methods for rare cell type detection. With CIARA, we found a small group of precursor cells among mouse embryonic stem cells and previously uncharacterized rare populations of cells in a human gastrula.

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The sense of smell helps us navigate the environment, but its anatomical logic remains unknown. The spatial location of odorant receptor genes (Olfrs) in the nose is widely thought to be independent of the structural diversity of the odorants they detect. Using spatial transcriptomics, we created a genome-wide 3D atlas of the mouse olfactory mucosa (OM), and identified key genes differentially expressed in space. Expression maps reveal that Olfrs are distributed in a continuous and overlapping fashion over five broad zones in the OM. The spatial locations of Olfrs correlate with the mucus solubility of the odorants they recognize. Thus, we provide direct evidence for the chromatographic theory of olfaction, and elucidate the basic logic for the peripheral representation of smell.