Fine needle aspiration of human lymph nodes reveals cell populations and soluble interactors pivotal to immunological priming.
Nicholas M ProvineAdam Al-DiwaniDevika AgarwalKyla DooleyAmelia HeslingtonAndrew G MurchisonLucy C GarnerFintan SheerinPaul KlenermanSarosh R IraniPublished in: European journal of immunology (2024)
Lymph node (LN) fine needle aspiration (LN FNA) represents a powerful technique for minimally invasive sampling of human LNs in vivo and has been used effectively to directly study aspects of the human germinal center response. However, systematic deep phenotyping of the cellular populations and cell-free proteins recovered by LN FNA has not been performed. Thus, we studied human cervical LN FNAs as a proof-of-concept and used single-cell RNA-sequencing and proteomic analysis to benchmark this compartment, define the purity of LN FNA material, and facilitate future studies in this immunologically pivotal environment. Our data provide evidence that LN FNAs contain bone-fide LN-resident innate immune populations, with minimal contamination of blood material. Examination of these populations reveals unique biology not predictable from equivalent blood-derived populations. LN FNA supernatants represent a specific source of lymph- and lymph node-derived proteins, and can, aided by transcriptomics, identify likely receptor-ligand interactions. This represents the first description of the types and abundance of immune cell populations and cell-free proteins that can be efficiently studied by LN FNA. These findings are of broad utility for understanding LN physiology in health and disease, including infectious or autoimmune perturbations, and in the case of cervical nodes, neuroscience.
Keyphrases
- fine needle aspiration
- lymph node
- single cell
- cell free
- endothelial cells
- ultrasound guided
- induced pluripotent stem cells
- minimally invasive
- healthcare
- sentinel lymph node
- public health
- pluripotent stem cells
- rna seq
- neoadjuvant chemotherapy
- genetic diversity
- multiple sclerosis
- risk assessment
- bone marrow
- stem cells
- squamous cell carcinoma
- early stage
- drinking water
- bone mineral density
- mental health
- radiation therapy
- social media
- heavy metals
- machine learning
- mesenchymal stem cells
- microbial community
- big data
- health risk
- deep learning
- postmenopausal women
- artificial intelligence
- soft tissue
- health promotion