TIPS: trajectory inference of pathway significance through pseudotime comparison for functional assessment of single-cell RNAseq data

B cell receptor repertoire analysis in primary Sjogren's syndrome salivary glands identifies repertoire features associated with clinical activity

BACKGROUND

Primary Sjogren's syndrome (pSS) is a complex autoimmune disease featuring damage to salivary and lacrimal glands, with the possibility of manifestations across multiple organs. Antibody-producing B cells have long been appreciated to play a significant role in pSS pathogenesis, with a number of autoreactive antibody species having been identified to be elevated in pSS patients. While several studies have attempted to characterize the BCR repertoires of peripheral blood B cells in pSS patients, much remains unknown about the repertoire characteristics of gland-infiltrating B cells.

METHODS

Through paired scRNAseq and scBCRseq, we profiled the BCR repertoires of both infiltrating and circulating B cells in a small cohort of patients. We further utilize receptor reconstruction analyses to further investigate repertoire characteristics in a wider cohort of pSS patients previously profiled through RNAseq.

RESULTS

Via integrated BCR and transcriptome analysis of B cell clones, we generate a trajectory progression pattern for infiltrated memory B cells in pSS. We observe significant differences in BCR repertoires between the peripheral blood and labial gland B cells of pSS patients in terms of relative expansion, isotype usage, and BCR clustering. We further observe significant decreases in IgA2 isotype usage among pSS patient labial and parotid gland B cells these analyses relative to controls as well as a positive correlation between kappa/lambda light chain usage and clinical disease activity.

CONCLUSIONS

Through BCR repertoire analysis of pSS patient salivary glands, we identify a number of novel repertoire characteristics that may serve as useful indicators of clinical disease and disease activity. By collecting these BCR repertoires into an accessible database, we hope to also enable comparative analysis of patient repertoires in pSS and potentially other autoimmune disorders.

Screening single-cell trajectories via continuity assessments for cell transition potential

Advances in single-cell sequencing and data analysis have made it possible to infer biological trajectories spanning heterogeneous cell populations based on transcriptome variation. These trajectories yield a wealth of novel insights into dynamic processes such as development and differentiation. However, trajectory analysis relies on an assumption of trajectory continuity, and experimental limitations preclude some real-world scenarios from meeting this condition. The current lack of assessment metrics makes it difficult to ascertain if/when a given trajectory deviates from continuity, and what impact such a divergence would have on inference accuracy is unclear. By analyzing simulated breaks introduced into in silico and real single-cell data, we found that discontinuity caused precipitous drops in the accuracy of trajectory inference. We then generate a simple scoring algorithm for assessing trajectory continuity, and found that continuity assessments in real-world cases of intestinal stem cell development and CD8 + T cells differentiation efficiently identifies trajectories consistent with empirical knowledge. This assessment approach can also be used in cases where a priori knowledge is lacking to screen a pool of inferred lineages for their adherence to presumed continuity, and serve as a means for weighing higher likelihood trajectories for validation via empirical studies, as exemplified by our case studies in psoriatic arthritis and acute kidney injury. This tool is freely available through github at qingshanni/scEGRET.

Integrated mass spectrometry imaging and single-cell transcriptome atlas strategies provide novel insights into taxoid biosynthesis and transport in Taxus mairei stems

Taxol, which is a widely used important chemotherapeutic agent, was originally isolated from Taxus stem barks. However, little is known about the precise distribution of taxoids and the transcriptional regulation of taxoid biosynthesis across Taxus stems. Here, we used MALDI-IMS analysis to visualize the taxoid distribution across Taxus mairei stems and single-cell RNA sequencing to generate expression profiles. A single-cell T. mairei stem atlas was created, providing a spatial distribution pattern of Taxus stem cells. Cells were reordered using a main developmental pseudotime trajectory which provided temporal distribution patterns in Taxus stem cells. Most known taxol biosynthesis-related genes were primarily expressed in epidermal, endodermal, and xylem parenchyma cells, which caused an uneven taxoid distribution across T. mairei stems. We developed a single-cell strategy to screen novel transcription factors (TFs) involved in taxol biosynthesis regulation. Several TF genes, such as endodermal cell-specific MYB47 and xylem parenchyma cell-specific NAC2 and bHLH68, were implicated as potential regulators of taxol biosynthesis. Furthermore, an ATP-binding cassette family transporter gene, ABCG2, was proposed as a potential taxoid transporter candidate. In summary, we generated a single-cell Taxus stem metabolic atlas and identified molecular mechanisms underpinning the cell-specific transcriptional regulation of the taxol biosynthesis pathway.

Obeticholic acid and 5β-cholanic acid 3 exhibit anti-tumor effects on liver cancer through CXCL16/CXCR6 pathway

Hepatocellular carcinoma (HCC) is the most common type of liver malignancy with a high incidence and mortality rate. Previous in vitro and in vivo studies have confirmed that liver sinusoidal endothelial cells (LSEC) secrete CXCL16, which acts as a messenger to increase the hepatic accumulation of CXCR6⁺ natural killer T (NKT) cells and exert potent antitumor effects. However, evidence for this process in humans is lacking and its clinical significance is still unclear. In this study, by dissecting the human HCC single-cell RNA-seq data, we verified this process through cellphoneDB. NKT cells in patients with high expression of CXCL16 exhibited a higher activation state and produced more interferon-γ (IFN-γ) compared with those with low expression. We next investigated the signaling pathways between activated (CD69 high) and unactivated NKT cells (CD69 low) using NKT cell-developmental trajectories and functional enrichment analyses. In vivo experiments, we found that farnesoid X receptor agonist (obeticholic acid) combined with the takeda G protein coupled receptor 5 antagonist (5β-cholanic acid 3) exhibited significant tumor suppressive effects in the orthotopic liver tumor model and this result may be related to the CXCL16/CXCR6 axis. In conclusion, our study provides the basis and potential strategies for HCC immunotherapy based on NKT cells.

Insights Gained and Future Outlook From scRNAseq Studies in Autoimmune Rheumatic Diseases

Autoimmune rheumatic diseases have a major impact on public health as one of the most common morbidities, and many of these disorders involve both local and systemic manifestations with severe consequences for patient health and quality of life. However, treatment options for many of these diseases remain inadequate for a substantial portion of patients, and progress in developing novel therapeutics has been slow. This lack of progress can be largely attributed to an insufficient understanding of the complex mechanisms driving pathogenesis. Recently, the emergence of single-cell RNA sequencing (scRNAseq) has offered a powerful new tool for interrogating rheumatic diseases, with the potential to assess biological heterogeneity and individual cell function in rheumatic diseases. In this review, we discuss the major insights gained from current scRNAseq interrogations of human rheumatic diseases. We highlight novel cell populations and key molecular signatures uncovered, and also raise a number of hypotheses for follow-up study that may be of interest to the field. We also provide an outlook into two emerging single-cell technologies (repertoire sequencing and spatial transcriptomics) that have yet to be utilized in the field of rheumatic diseases, but which offer immense potential in expanding our understanding of immune and stromal cell behavior. We hope that scRNAseq may serve as a wellspring for the generation and interrogation of novel hypotheses regarding autoreactive lymphocytes and tissue infiltration patterns, and help uncover novel avenues for therapeutic development.

Trajectory mapping of primary Sjögren's syndrome via transcriptome learning demonstrates limitations of peripheral blood sequencing

Primary Sjögren's syndrome (pSS) is a complex autoimmune disease characterized by aberrant immune cell action against secretory glands throughout the body. A number of studies have previously identified unique characteristics in the circulating expression profile of white blood cells of pSS patients. However, the molecular progression pattern of pSS is unclear. Through a systematic analysis of pSS transcriptome information, we found that pSS transcriptomes display broad heterogeneity, but cannot be distinguished from the broad range of possible profiles of healthy controls. Instead, only sample learning using a subset of pre-identified signature genes could achieve partial separation through a trajectory governed by interferon activity. Interestingly, this trajectory is correlated with a decrease in dendritic cell counts. Our study thus highlights a major limitation to the utility of broad blood transcriptome analysis in the context of pSS, while also identifying several factors that influence the divergence between patient samples.