SELINA: Single-cell Assignment using Multiple-Adversarial Domain Adaptation Network with Large-scale References

The rapid accumulation of single-cell RNA-seq data has provided rich resources to characterize various human cell types. Cell type annotation is the critical step in analyzing single-cell RNA-seq data. However, accurate cell type annotation based on public references is challenging due to the inconsistent annotations, batch effects, and poor characterization of rare cell types. Here, we introduce SELINA (single cELl identity NAvigator), an integrative annotation transferring framework for automatic cell type annotation. SELINA optimizes the annotation for minority cell types by synthetic minority over-sampling, removes batch effects among reference datasets using a multiple-adversarial domain adaptation network (MADA), and fits the query data with reference data using an autoencoder. Finally, SELINA affords a comprehensive and uniform reference atlas with 1.7 million cells covering 230 major human cell types. We demonstrated the robustness and superiority of SELINA in most human tissues compared to existing methods. SELINA provided a one-stop solution for human single- cell RNA-seq data annotation with the potential to extend for other species.

Towards Tabula Gallus

The Tabula Gallus is a proposed project that aims to create a map of every cell type in the chicken body and chick embryos. Chickens (Gallus gallus) are one of the most recognized model animals that recapitulate the development and physiology of mammals. The Tabula Gallus will generate a compendium of single-cell transcriptome data from Gallus gallus, characterize each cell type, and provide tools for the study of the biology of this species, similar to other ongoing cell atlas projects (Tabula Muris and Tabula Sapiens/Human Cell Atlas for mice and humans, respectively). The Tabula Gallus will potentially become an international collaboration between many researchers. This project will be useful for the basic scientific study of Gallus gallus and other birds (e.g., cell biology, molecular biology, developmental biology, neuroscience, physiology, oncology, virology, behavior, ecology, and evolution). It will eventually be beneficial for a better understanding of human health and diseases.

Analysis of the Effects of Food Additives on Porphyromonas gingivalis

This study aims to investigate six food additives (octanoic acid, decanoic acid, acesulfame K, aspartame, saccharin, and sucralose) used in foods for the elderly or people with dysphagia because of the effect of these food additives on Porphyromonas gingivalis (P. gingivalis), which is a keystone pathogen of periodontal diseases. The growth of P. gingivalis was inhibited by 5 mM octanoic acid, 1.25 mM decanoic acid, 1.25% acesulfame K, 0.0625% aspartame, 0.03125% saccharin, and 0.625% sucralose. In addition, these food additives showed bactericidal activity for planktonic P. gingivalis (5 mM octanoic acid, 5 mM decanoic acid, 0.25% aspartame, 0.25% saccharin, and 5% sucralose). Moreover, biofilm formation was inhibited by 10 mM octanoic acid, 10 mM decanoic acid, 10% acesulfame K, 0.35% aspartame, 0.5% saccharin, and 7.5% sucralose. Moreover, the same concentration of these food additives without aspartame killed P. gingivalis in the biofilm. Aspartame and sucralose did not show cytotoxicity to human cell lines at concentrations that affected P. gingivalis. These findings may be useful in clarifying the effects of food additives on periodontopathogenic bacteria.

Star-like poly(peptoid)s with selective antibacterial activity

We developed new macromolecular engineering approaches enabling the preparation of star-like polypeptoids by ring-opening polymerization. Parallely to the evaluation of their cytotoxicity of the HepG2 human cell line, their screening...