Biology subjects

Lausted, C.

Publications and source records attributed to Lausted, C..

3 recordsLinked to original sources

bioRxiv2025

Multiomics Reveals Compartmentalized Immune Responses and Tissue-Vascular Signatures in Lyme Disease

Lyme disease (LD) is growing in incidence, with nearly 500,000 cases diagnosed annually in the United States. Despite treatment, some patients experience persistent symptoms. The immune mechanisms underlying LD remain poorly understood. We conducted a multiomic longitudinal analysis of 49 LD patients and matched controls, integrating plasma proteomics, metabolomics, PBMC immunophenotyping, and a meta-analysis of skin lesions. We identified compartmentalized immune responses in acute LD, with coordinated alterations in circulating plasma proteins and metabolites linked to endothelial barrier stability, metabolic reprogramming, and symptom severity, predominantly traced to tissue and vascular immune processes at the site of infection. In contrast, PBMCs remained largely quiescent, revealing a disconnect between localized tissue responses and systemic immunity. These findings provide novel insights into LD pathophysiology and highlight the potential for diagnostics leveraging tissue and vascular immune markers detectable in blood. They also provide a resource for biomarker discovery and predictive modeling to improve LD management.

immunology↗

bioRxiv2020

Multiomic Immunophenotyping of COVID-19 Patients Reveals Early Infection Trajectories

Host immune responses play central roles in controlling SARS-CoV2 infection, yet remain incompletely characterized and understood. Here, we present a comprehensive immune response map spanning 454 proteins and 847 metabolites in plasma integrated with single-cell multi-omic assays of PBMCs in which whole transcriptome, 192 surface proteins, and T and B cell receptor sequence were co-analyzed within the context of clinical measures from 50 COVID19 patient samples. Our study reveals novel cellular subpopulations, such as proliferative exhausted CD8+ and CD4+ T cells, and cytotoxic CD4+ T cells, that may be features of severe COVID-19 infection. We condensed over 1 million immune features into a single immune response axis that independently aligns with many clinical features and is also strongly associated with disease severity. Our study represents an important resource towards understanding the heterogeneous immune responses of COVID-19 patients and may provide key information for informing therapeutic development.

immunology↗

bioRxiv2017

Novel metrics for quantifying bacterial genome composition skews

BackgroundBacterial genomes have characteristic compositional skews, which are differences in nucleotide frequency between the leading and lagging DNA strands across a segment of a genome. It is thought that these strand asymmetries arise as a result of mutational biases and selective constraints, particularly for energy efficiency. Analysis of compositional skews in a diverse set of bacteria provides a comparative context in which mutational and selective environmental constraints can be studied. These analyses typically require finished and well-annotated genomic sequences.\n\nResultsWe present three novel metrics for examining genome composition skews; all three metrics can be computed for unfinished or partially-annotated genomes. The first two metrics, (dot-skew and cross-skew) depend on sequence and gene annotation of a single genome, while the third metric (residual skew) highlights unusual genomes by subtracting a GC content-based model of a library of genome sequences. We applied these metrics to all 7738 available bacterial genomes, including partial drafts, and identified outlier species. A number of these outliers (i.e., Borrelia, Ehrlichia, Kinetoplastibacterium, and Phytoplasma) display similar skew patterns despite only distant phylogenetic relationship. While unrelated, some of the outlier bacterial species share lifestyle characteristics, in particular intracellularity and biosynthetic dependence on their hosts.\n\nConclusionsOur novel metrics appear to reflect the effects of biosynthetic constraints and adaptations to life within one or more hosts on genome composition. We provide results for each analyzed genome, software and interactive visualizations at http://db.systemsbiology.net/gestalt/skew_metrics.

genomics↗