Lipocalin-2 expression identifies an intestinal regulatory neutrophil population during acute graft-versus-host disease.

Acute graft-versus-host disease (aGVHD) is a life-threatening complication of allogeneic hematopoietic cell transplantation (allo-HCT), for which therapeutic options are limited. Strategies to promote intestinal tissue tolerance during aGVHD may improve patient outcomes. Using single-cell RNA sequencing, we identified a lipocalin-2 (LCN2)-expressing neutrophil population in mice with intestinal aGVHD. Transfer of LCN2-overexpressing neutrophils or treatment with recombinant LCN2 reduced aGVHD severity, whereas the lack of epithelial or hematopoietic LCN2 enhanced aGVHD severity and caused microbiome alterations. Mechanistically, LCN2 induced insulin-like growth factor 1 receptor (IGF-1R) signaling in macrophages through the LCN2 receptor SLC22A17, which increased interleukin-10 (IL-10) production and reduced major histocompatibility complex class II (MHCII) expression. Transfer of LCN2-pretreated macrophages reduced aGVHD severity but did not reduce graft-versus-leukemia effects. Furthermore, LCN2 expression correlated with IL-10 expression in intestinal biopsies in multiple cohorts of patients with aGVHD, and LCN2 induced IGF-1R signaling in human macrophages. Collectively, we identified a LCN2-expressing intestinal neutrophil population that reduced aGVHD severity by decreasing MHCII expression and increasing IL-10 production in macrophages. This work provides the foundation for administration of LCN2 as a therapeutic approach for aGVHD.

Large-Scale Integration of Amplicon Data Reveals Massive Diversity within Saprospirales, Mostly Originating from Saline Environments.

The order Saprospirales, a group of bacteria involved in complex degradation pathways, comprises three officially described families: Saprospiraceae, Lewinellaceae, and Haliscomenobacteraceae. These collectively contain 17 genera and 31 species. The current knowledge on Saprospirales diversity is the product of traditional isolation methods, with the inherited limitations of culture-based approaches. This study utilized the extensive information available in public sequence repositories combined with recent analytical tools to evaluate the global evidence-based diversity of the Saprospirales order. Our analysis resulted in 1183 novel molecular families, 15,033 novel molecular genera, and 188 K novel molecular species. Of those, 7 novel families, 464 novel genera, and 1565 species appeared in abundances at ≥0.1%. Saprospirales were detected in various environments, such as saline water, freshwater, soil, various hosts, wastewater treatment plants, and other bioreactors. Overall, saline water was the environment showing the highest prevalence of Saprospirales, with bioreactors and wastewater treatment plants being the environments where they occurred with the highest abundance. Lewinellaceae was the family containing the majority of the most prevalent species detected, while Saprospiraceae was the family with the majority of the most abundant species found. This analysis should prime researchers to further explore, in a more targeted way, the Saprospirales proportion of microbial dark matter.

Taxonomy Informed Clustering, an Optimized Method for Purer and More Informative Clusters in Diversity Analysis and Microbiome Profiling.

Bacterial diversity is often analyzed using 16S rRNA gene amplicon sequencing. Commonly, sequences are clustered based on similarity cutoffs to obtain groups reflecting molecular species, genera, or families. Due to the amount of the generated sequencing data, greedy algorithms are preferred for their time efficiency. Such algorithms rely only on pairwise sequence similarities. Thus, sometimes sequences with diverse phylogenetic background are clustered together. In contrast, taxonomic classifiers use position specific taxonomic information in assigning a probable taxonomy to a given sequence. Here we introduce Taxonomy Informed Clustering (TIC), a novel approach that utilizes classifier-assigned taxonomy to restrict clustering to only those sequences that share the same taxonomic path. Based on this concept, we offer a complete and automated pipeline for processing of 16S rRNA amplicon datasets in diversity analyses. First, raw reads are processed to form denoised amplicons. Next, the denoised amplicons are taxonomically classified. Finally, the TIC algorithm progressively assigning clusters at molecular species, genus and family levels. TIC outperforms greedy clustering algorithms like USEARCH and VSEARCH in terms of clusters' purity and entropy, when using data from the Living Tree Project as test samples. Furthermore, we applied TIC on a dataset containing all Bifidobacteriaceae-classified sequences from the IMNGS database. Here, TIC identified evidence for 1000s of novel molecular genera and species. These results highlight the straightforward application of the TIC pipeline and superior results compared to former methods in diversity studies. The pipeline is freely available at: https://github.com/Lagkouvardos/TIC.