Analysis Of Composition And Interaction Of Immune Cells In Different Stages Of Traumatic Lung Injury Based On Single-Cell Transcriptome Sequencing

Background:Traumatic lung injury(TLI)is a common complication of trauma,including direct violence-induced lung injury and secondary lung injury caused by multiple injuries to distant organs.The clinical manifestations of TLI are complex,often presenting as hypoxemia accompanied by fractures,tissue damage and distant organ damage.TLI can be diagnosed through imaging examinations such as CT,but some patients with lung injuries may not have imaging findings in the early stage and multiple injuries obscure lung manifestations,leading to missed diagnosis,which can easily miss the opportunity for early treatment.Therefore,dynamic monitoring and timely intervention are of great significance.At present,the pathogenesis of traumatic lung injury is still unclear.Some studies have shown that it is related to epithelial and endothelial cell damage,activation of coagulation and fibrinolytic systems as well as activation of inflammatory reactions.Among them,innate immune response is crucial and myeloid cells play a major role.Therefore,understanding the diversity of immune cell subsets and intercellular interactions is conducive to determining the stage of TLI.Single cell sequencing accurately locates cell function in a single cell dimension.By describing the distribution of immune cell subsets at different stages of disease course,specific genes and proteins can be explored in depth.This technology has been applied to immune related research in various disease fields.Objective:Using single cell transcriptome sequencing technology to delineate the immune cell atlas of TLI patients in acute,progressive and convalescent stages.Analyzing the changes of immune cell subpopulations at various stages of the disease from the perspective of multidimensional bioinformatics analysis such as cell subpopulation distribution,biological function,transcription factor prediction and pseudotime analysis.By these ways to monitor the occurrence and development of TLI dynamically.Finally,exploring the interactions between various immune cell subsets to provide experimental evidence for the pathogenesis.Methods:Three patients with traumatic lung injury and three healthy individuals were recruited from the First Affiliated Hospital of海军军医University from January 2021 to December 2021 according to the inclusion and exclusion criteria.On the first day of admission,the third day of admission and the day before discharged(corresponding to the acute,progressive and convalescent stages of traumatic lung injury respectively),fresh peripheral blood was used for Ficoll density gradient centrifugation to obtain mononuclear cell suspensions and neutrophil suspensions.Then single cells were extracted and single cell transcriptome sequencing was performed according to the BD Rhapsody standard procedure.Finally,bioinformatics analyses were carried out using methods such as biological function enrichment analysis,signal pathway enrichment analysis,single cell regulatory network inference and clustering,pseudotime analysis,quantitative set analysis for gene expression and cell communication analysis.Result:1.In this study,71891 immune cells were extracted from peripheral blood and 24 subsets of immune cells were clustered.Longitudinal bioinformatics analysis revealed that in different stages of TLI,the absolute value of myeloid cells was increased,functions related inflammatory were significantly upregulated and the special cell death modes,including neutrophil extracellular traps was enhanced,ferroptosis was downregulated in TLI-A and returned to normal in TLI-P compared to the healthy control group.2.Conduct in-depth data exploring in neutrophils and recluster them into 13 neutrophil subpopulations.According to the marker genes,neutrophils are divided into immature neutrophil subpopulations(cluster 9,10),high expression of inflammatory response related gene subpopulations(cluster 2,6,7),high expression of interferon related gene subpopulations(cluster 3,8),high expression of chemokine and cytokine related gene subgroups(cluster 4),"hybrid" neutrophil subgroups(cluster 0,1,5)as well as a small number of basophils and platelets.Further analysis combined with the distribution and proportion of various neutrophil subpopulations showed that TLI-A and TLI-P showed emergency myelogenesis.Cluster 6,7,9 and 10 in neutrophils expressed immunosuppressive related genes such as ARG1 and ITGAM while PADI4 assisted the formation of NET which indicated a disorder in the composition of neutrophil subpopulations.Multiple PRRs related signaling pathways,HIF-1 signaling pathways and NF-κB signaling pathways can be seen through biological function enrichment as well as IL-17 signal pathway and Th17 cell differentiation are upregulated in TLI.Transcription factor prediction such as RUNX1,FOS,and JUN were highly expressed in cluster 2,6,and7.E2 F and CEBPE were highly expressed in cluster 9 and 10.Pseudotime analysis showed that the activation state of neutrophil subgroup gene in TLI was significantly changed and the state of Fate1 cells only appeared in TLI.Above bioinformatics analysis indicates that inflammation plays a dominant role in the occurrence and development of TLI.3.Conduct in-depth data explored in monocytes and recluster them into 12 monocyte subpopulations.According to the marker genes,they are divided into high expression activation and regulation of inflammatory response related gene subpopulations(cluster2,5,6),high expression of chemokine and inflammatory factor related gene subpopulations(cluster 0,1,3),high expression of antigen presentation related gene subpopulations(cluster4,8),nonclassical monocytes(cluster 7,9)and dendritic cells(cluster 10,11).Further analysis combined with the distribution and proportion of each monocyte subgroup in TLI-A and TLI-P showed that there was emergency myelogenesis.High levels of PLAC8 and low levels of HLA-DR were expressed in cluster 2,5 and 6.There is a reduced proportion of cluster 7,9,4 and 8 in TLI-A and TLI-P which indicated a decline in antigen presentation related functions.All of above suggested that there were dysfunctional monocyte subgroups in TLI.Through enrichment of biological functions and signal pathways analysis,phagocytosis,ROS response,cytokine signaling pathways,IL-17 signaling pathways and TNF signaling pathways were significantly upregulated.Transcription factor prediction revealed that EGR2,FOS and JUN were highly expressed in cluster 2 and the activated inflammatory classic monocyte subsets.Pseudotime analysis revealed an increase in Pre status and the state of Fate1 mononuclear cells in TLI-A and TLI-P.Above all,we concluded that inflammatory response played a dominant role in the occurrence and development of TLI.4.Interactions between monocytes,subsets of monocytes and immune cells are enhanced in TLI.Mature neutrophils interact less with others while immature neutrophils interact more with other immune cells.Conclusion:1.In TLI-A and TLI-P,emergency myelogenesis occurs which leads to dysregulation and functional disorder of the myeloid cell composition.Mature inflammatory activation subsets exhibit proinflammatory effects,while immature immune cell subsets exhibit decreased phagocytic and antigen presenting functions while impaired oxidative stress responses and immunosuppression.However,inflammatory response related biological functions dominate in TLI-A and TLI-P.2.The bioinformatics analysis suggests that combining NETs and ferroptosis can be used as indicators for dynamic monitoring of TLI.NETs are upregulated with ferroptosis being downregulated in TLI-A while NETs are upregulated with ferroptosis returning to normal levels in TLI-P.3.Interactions between immune cells suggest that immature neutrophils,monocytes and various types of immune cells is enhanced in both TLI-A and TLI-P.And these receptor-ligand interactions exhibit strong inflammatory responses.