Key residues in TLR4-MD2 tetramer formation identified by free energy simulations.

Toll-like receptors (TLRs) play a central role in both the innate and adaptive immune systems by recognizing pathogen-associated molecular patterns and inducing the release of the effector molecules of the immune system. The dysregulation of the TLR system may cause various autoimmune diseases and septic shock. A series of molecular dynamics simulations and free energy calculations were performed to investigate the ligand-free, lipopolysaccharide (LPS)-bound, and neoseptin3-bound (TLR4-MD2)2 tetramers. Compared to earlier simulations done by others, our simulations showed that TLR4 structure was well maintained with stable interfaces. Free energy decomposition by molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) method suggests critical roles that two hydrophobic clusters I85-L87-P88 and I124-L125-P127 of MD2, together with LPS and neoseptin3, may play in TLR4 activation. We propose that 1) direct contacts between TLR4 convex surface and LPS and neoseptin3 at the region around L442 significantly increase the binding and 2) binding of LPS and neoseptin3 in the central hydrophobic cavity of MD2 triggers burial of F126 and exposure of I85-L87-P88 that facilitate formation of (TLR4-MD2)2 tetramer and activation of TLR4 system.

Epidemiological and biomechanical evaluation of airline baggage handling.

OBJECTIVES: Musculoskeletal disorders (MSDs) are prevalent among airline baggage handlers due to manual materials handling. In this study, the Nordic musculoskeletal questionnaire (NMQ), the revised National Institute for Occupational Safety and Health (NIOSH) lifting equation, and the University of Michigan 3D Static Strength Prediction Program™ (3DSSPP) were used to analyze MSDs among baggage handlers. METHODS: The NMQ was filled out by 209 baggage handlers and 46 arbitrarily selected baggage handlers were evaluated using the NIOSH method and 3DSSPP. RESULTS: The obtained results showed that the most common MSDs occurred in the lower back region. The next risky regions included knees, neck, and upper back, respectively. The NIOSH results confirmed that the subjects lifted loads heavier than the permitted limit and their lifting postures were inappropriate. The results of the 3DSSPP also indicated that compression forces exceeded the NIOSH limit in these awkward postures. CONCLUSIONS: Relying on this study, holding compulsory ergonomic lifting training courses could be proposed for workers and regulations adjusting an upper limit for maximum baggage weight must be also enacted in order to improve occupational health and prevent the prevalence of increasing MSDs.

Tetramer-aided sorting and single-cell RNA sequencing facilitate transcriptional profiling of antigen-specific CD8+ T cells.

BACKGROUND: Recent advances in single-cell technologies and an improved understanding of tumor antigens have empowered researchers to investigate tumor antigen-specific CD8+ T cells at the single-cell level. Peptide-MHC I tetramers are often utilized to enrich antigen-specific CD8+ T cells, which however, introduces the undesired risk of altering their clonal distribution or their transcriptional state. This study addresses the feasibility of utilizing tetramers to enrich antigen-specific CD8+ T cells for single-cell analysis. METHODS: HLA-A*02:01-restricted human cytomegalovirus (CMV) pp65 peptide-specific CD8+ T cells were used as a model for analyzing antigen-specific CD8+ T cells. Single-cell RNA sequencing and TCR sequencing were performed to compare the frequency and gene expression profile of pp65-specific TCR clones between tetramer-sorted, unstimulated- and tetramer-stimulated total CD8+ T cells. RESULTS: The relative frequency of pp65-specific TCR clones and their transcriptional profile remained largely unchanged following tetramer-based sorting. In contrast, tetramer-mediated stimulation of CD8+ T cells resulted in significant gene expression changes in pp65-specific CD8+ T cells. An Antigen-Specific Response (ASR) gene signature was derived from tetramer-stimulated pp65-specific CD8+ T cells. The ASR signature had a predictive value and was significantly associated with progression free survival in lung cancer patients treated with anti-PD-L1, anti-VEGF, chemotherapy combination (NCT02366143). The predictive power of the ASR signature was independent of the conventional CD8 effector signature. CONCLUSIONS: Our findings validate the approach of enriching antigen-specific CD8+ T cells through tetramer-aided Fluorescence-Activated Cell Sorting (FACS) sorting for single-cell analysis and also identifies an ASR gene signature that has value in predicting response to cancer immunotherapy.

Single-cell analysis reveals clonally expanded tumor-associated CD57+ CD8 T cells are enriched in the periphery of patients with metastatic urothelial cancer responding to PD-L1 blockade.

BACKGROUND: A growing body of evidence suggests that T-cell responses against neoantigens are critical regulators of response to immune checkpoint blockade. We previously showed that circulating neoantigen-specific CD8 T cells in patients with lung cancer responding to anti-Programmed death-ligand 1 (PD-L1) (atezolizumab) exhibit a unique phenotype with high expression of CD57, CD244, and KLRG1. Here, we extended our analysis on neoantigen-specific CD8 T cells to patients with metastatic urothelial cancer (mUC) and further profiled total CD8 T cells to identify blood-based predictive biomarkers of response to atezolizumab. METHODS: We identified tumor neoantigens from 20 patients with mUC and profiled their peripheral CD8 T cells using highly multiplexed combinatorial tetramer staining. Another set of patients with mUC treated with atezolizumab (n=30) or chemotherapy (n=40) were selected to profile peripheral CD8 T cells by mass cytometry. Using single-cell transcriptional analysis (single-cell RNA sequencing (scRNA-seq)), together with CITE-seq (cellular indexing of transcriptomes and epitopes by sequencing) and paired T-cell receptor (TCR) sequencing, we further characterized peripheral CD8 T cells in a subset of patients (n=16). RESULTS: High frequency of CD57 was observed in neoantigen-specific CD8 T cells in patients with mUC responding to atezolizumab. Extending these findings to bulk CD8 T cells, we found higher frequency of CD57 expressing CD8 T cells before treatment in patients responding to atezolizumab (n=20, p<0.01) but not to chemotherapy. These findings were corroborated in a validation cohort (n=30, p<0.01) and notably were independent of known biomarkers of response. scRNA-seq analysis identified a clonally expanded cluster enriched within CD57+ CD8 T cells in responding patients characterized by higher expression of genes associated with activation, cytotoxicity, and tissue-resident memory markers. Furthermore, compared with CD57- CD8 T cells, TCRs of CD57+ CD8 T cells showed increased overlap with the TCR repertoire of tumor-infiltrating T cells. CONCLUSIONS: Collectively, we show high frequencies of CD57 among neoantigen-specific and bulk CD8 T cells in patients responding to atezolizumab. The TCR repertoire overlap between peripheral CD57+ CD8 T cells and tumor-infiltrating lymphocytes suggest that accumulation of peripheral CD57+ CD8 T cells is reflective of an ongoing antitumor T-cell response. Our findings provide evidence and rationale for using circulating CD8 T cells expressing CD57 as a readily accessible blood-based biomarker for selecting patients with mUC for atezolizumab therapy.