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Sumner, J. A.

Publications and source records attributed to Sumner, J. A..

2 recordsLinked to original sources

Inferring B cell phylogenies from paired heavy and light chain BCR sequences with Dowser

Antibodies are vital to human immune responses and are composed of genetically variable heavy and light chains. These structures are initially expressed as B cell receptors (BCRs). BCR diversity is shaped through somatic hypermutation and selection during immune responses. This evolutionary process produces B cell clones, cells that descend from a common ancestor but differ by mutations. Phylogenetic trees inferred from BCR sequences can reconstruct the history of mutations within a clone. Until recently, BCR sequencing technologies separated heavy and light chains, but advancements in single cell sequencing now pair heavy and light chains from individual cells. However, it is unclear how these separate genes should be combined to infer B cell phylogenies. In this study, we investigated strategies for using paired heavy and light chain sequences to build phylogenetic trees. We found incorporating light chains significantly improved tree accuracy and reproducibility across all methods tested. This improvement was greater than the difference between tree building methods and persisted even when mixing bulk and single cell sequencing data. However, we also found that many phylogenetic methods estimated significantly biased branch lengths when some light chains were missing, such as when mixing single cell and bulk BCR data. This bias was eliminated using maximum likelihood methods with separate branch lengths for heavy and light chain gene partitions. Thus, we recommend using maximum likelihood methods with separate heavy and light chain partitions, especially when mixing data types. We implemented these methods in the R package Dowser: https://dowser.readthedocs.io.

immunology↗

Exercise Mitigates Flow Recirculation and Activates Mechanosensitive Transcriptome to Uncover Endothelial SCD1-Catalyzed Anti-Inflammatory Metabolites

Exercise modulates vascular plasticity in multiple organ systems; however, the metabolomic transducers underlying exercise and vascular protection in the disturbed flow-prone vasculature remain under-investigated. We simulated exercise-augmented pulsatile shear stress (PSS) to mitigate flow recirculation in the lesser curvature of the aortic arch. When human aortic endothelial cells (HAECs) were subjected to PSS ({tau}ave = 50 dyne{middle dot}cm-2, {partial}{tau}/{partial}t = 71 dyne{middle dot}cm-2{middle dot}s-1, 1 Hz), untargeted metabolomic analysis revealed that Stearoyl-CoA Desaturase (SCD1) in the endoplasmic reticulum (ER) catalyzed the fatty acid metabolite, oleic acid (OA), to mitigate inflammatory mediators. Following 24 hours of exercise, wild-type C57BL/6J mice developed elevated SCD1-catalyzed lipid metabolites in the plasma, including OA and palmitoleic acid (PA). Exercise over a 2-week period increased endothelial SCD1 in the ER. Exercise further modulated the time-averaged wall shear stress (TAWSS or{tau} ave) and oscillatory shear index (OSIave), upregulated Scd1 and attenuated VCAM1 expression in the disturbed flow-prone aortic arch in Ldlr-/- mice on high-fat diet but not in Ldlr-/-Scd1EC-/- mice. Scd1 overexpression via recombinant adenovirus also mitigated ER stress. Single cell transcriptomic analysis of the mouse aorta revealed interconnection of Scd1 with mechanosensitive genes, namely Irs2, Acox1 and Adipor2 that modulate lipid metabolism pathways. Taken together, exercise modulates PSS ({tau}ave and OSIave) to activate SCD1 as a metabolomic transducer to ameliorate inflammation in the disturbed flow-prone vasculature.

physiology↗