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Lymphatic transport of molecules and migration of myeloid cells to lymph nodes (LNs) continuously inform lymphocytes on changes in drained tissues. Here, using LN transplantation, single-cell RNA-seq, spectral flow cytometry, and a transgenic mouse model for photolabeling, we showed that tissue-derived unconventional T cells (UTCs) migrate via the lymphatic route to locally draining LNs. As each tissue harbored a distinct spectrum of UTCs with locally adapted differentiation states and distinct T cell receptor repertoires, every draining LN was thus populated by a distinctive tissue-determined mix of these lymphocytes. By making use of single UTC lineage-deficient mouse models, we found that UTCs functionally cooperated in interconnected units and generated and shaped characteristic innate and adaptive immune responses that differed between LNs that drained distinct tissues. Lymphatic migration of UTCs is, therefore, a key determinant of site-specific immunity initiated in distinct LNs with potential implications for vaccination strategies and immunotherapeutic approaches., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2022 Elsevier Inc. All rights reserved.)

Aggresomes are subcellular perinuclear structures where misfolded proteins accumulate by retrograde transport on microtubules. Different methods are available to monitor aggresome formation, but they are often laborious, time-consuming, and not quantitative. Proteostat is a red fluorescent molecular rotor dye, which becomes brightly fluorescent when it binds to protein aggregates. As this reagent was previously validated to detect aggresomes, we have miniaturized its use in 384-well plates and developed a method for high-throughput imaging and quantification of aggresomes. Two different image analysis methods, including one with machine learning, were evaluated. They lead to similar robust data to quantify cells having aggresome, with satisfactory Z' factor values and reproducible EC 50 values for compounds known to induce aggresome formation, like proteasome inhibitors. We demonstrated the relevance of this phenotypic assay by screening a chemical library of 1280 compounds to find aggresome modulators. We obtained hits that present similarities in their structural and physicochemical properties. Interestingly, some of them were previously described to modulate autophagy, which could explain their effect on aggresome structures. In summary, we have optimized and validated the Proteostat detection reagent to easily measure aggresome formation in a miniaturized, automated, quantitative, and high-content assay. This assay can be used at low, middle, or high throughput to quantify changes in aggresome formation that could help in the understanding of chemical compound activity in pathologies such as protein misfolding disorders or cancer.