Immune cell identifier and classifier (ImmunIC) for single cell transcriptomic readouts.

Single cell RNA sequencing has a central role in immune profiling, identifying specific immune cells as disease markers and suggesting therapeutic target genes of immune cells. Immune cell-type annotation from single cell transcriptomics is in high demand for dissecting complex immune signatures from multicellular blood and organ samples. However, accurate cell type assignment from single-cell RNA sequencing data alone is complicated by a high level of gene expression heterogeneity. Many computational methods have been developed to respond to this challenge, but immune cell annotation accuracy is not highly desirable. We present ImmunIC, a simple and robust tool for immune cell identification and classification by combining marker genes with a machine learning method. With over two million immune cells and half-million non-immune cells from 66 single cell RNA sequencing studies, ImmunIC shows 98% accuracy in the identification of immune cells. ImmunIC outperforms existing immune cell classifiers, categorizing into ten immune cell types with 92% accuracy. We determine peripheral blood mononuclear cell compositions of severe COVID-19 cases and healthy controls using previously published single cell transcriptomic data, permitting the identification of immune cell-type specific differential pathways. Our publicly available tool can maximize the utility of single cell RNA profiling by functioning as a stand-alone bioinformatic cell sorter, advancing cell-type specific immune profiling for the discovery of disease-specific immune signatures and therapeutic targets.

Gut microbiome in people living with HIV is associated with impaired thiamine and folate syntheses.

People living with HIV have a high incidence of cardiovascular and neurological diseases as comorbid disorders that are commonly linked to inflammation. While microbial translocation can augment inflammation during HIV infection, functional microbiome shifts that may increase pro-inflammatory responses have not been fully characterized. In addition, defining HIV-induced microbiome changes has been complicated by high variability among individuals. Here we conducted functional annotation of previously-published 16S ribosomal RNA gene sequences of 305 HIV positive and 249 negative individuals, with adjustment for geographic region, sex, sexual behavior, and age. Metagenome profiles were inferred from these individuals' 16S data. HIV infection was associated with impaired microbial vitamin B synthesis; around half of the gene families in thiamine and folate biosynthesis pathways were significantly less abundant in the HIV positive group than the negative control. These results are consistent with the high prevalence of thiamine and folate deficiencies in HIV infections. These HIV-induced microbiota shifts have the potential to influence cardiovascular and neurocognitive diseases, given the documented associations between B-vitamin deficiencies, inflammation, and these diseases. We also observed that most essential amino acid biosynthesis pathways were downregulated in the microbiome of HIV-infected individuals. Microbial vitamin B and amino acid synthesis pathways were not significantly recovered by antiretroviral treatment when we compared 262 ART positive and 184 ART negative individuals. Our meta-analysis provides a new outlook for understanding vitamin B and amino acid deficiencies in HIV patients, suggesting that interventions for reversing HIV-induced microbiome shifts may aid in lessening the burdens of HIV comorbidities.