Biology subjects

Blaum, E. M.

Publications and source records attributed to Blaum, E. M..

3 recordsLinked to original sources

bioRxiv2021

Longitudinal characterization of circulating neutrophils uncovers distinct phenotypes associated with disease severity in hospitalized COVID-19 patients

Multiple studies have identified an association between neutrophils and COVID-19 disease severity; however, the mechanistic basis of this association remains incompletely understood. Here we collected 781 longitudinal blood samples from 306 hospitalized COVID-19+ patients, 78 COVID-19- acute respiratory distress syndrome patients, and 8 healthy controls, and performed bulk RNA-sequencing of enriched neutrophils, plasma proteomics, cfDNA measurements and high throughput antibody profiling assays to investigate the relationship between neutrophil states and disease severity or death. We identified dynamic switches between six distinct neutrophil subtypes using non-negative matrix factorization (NMF) clustering. At days 3 and 7 post-hospitalization, patients with severe disease had an enrichment of a granulocytic myeloid derived suppressor cell-like state gene expression signature, while non-severe patients with resolved disease were enriched for a progenitor-like immature neutrophil state signature. Severe disease was associated with gene sets related to neutrophil degranulation, neutrophil extracellular trap (NET) signatures, distinct metabolic signatures, and enhanced neutrophil activation and generation of reactive oxygen species (ROS). We found that the majority of patients had a transient interferon-stimulated gene signature upon presentation to the emergency department (ED) defined here as Day 0, regardless of disease severity, which persisted only in patients who subsequently died. Humoral responses were identified as potential drivers of neutrophil effector functions, as enhanced antibody-dependent neutrophil phagocytosis and reduced NETosis was associated with elevated SARS-CoV-2-specific IgG1-to-IgA1 ratios in plasma of severe patients who survived. In vitro experiments confirmed that while patient-derived IgG antibodies mostly drove neutrophil phagocytosis and ROS production in healthy donor neutrophils, patient-derived IgA antibodies induced a predominant NETosis response. Overall, our study demonstrates neutrophil dysregulation in severe COVID-19 and a potential role for IgA-dominant responses in driving neutrophil effector functions in severe disease and mortality.

immunology↗

bioRxiv2021

High-throughput RNA isoform sequencing using programmable cDNA concatenation

Alternative splicing is a core biological process that enables profound and essential diversification of gene function. Short-read RNA sequencing approaches fail to resolve RNA isoforms and therefore primarily enable gene expression measurements - an isoform unaware representation of the transcriptome. Conversely, full-length RNA sequencing using long-read technologies are able to capture complete transcript isoforms, but their utility is deeply constrained due to throughput limitations. Here, we introduce MAS-ISO-seq, a technique for programmably concatenating cDNAs into single molecules optimal for long-read sequencing, boosting the throughput >15 fold to nearly 40 million cDNA reads per run on the Sequel IIe sequencer. We validated unambiguous isoform assignment with MAS-ISO-seq using a synthetic RNA isoform library and applied this approach to single-cell RNA sequencing of tumor-infiltrating T cells. Results demonstrated a >30 fold boosted discovery of differentially spliced genes and robust cell clustering, as well as canonical PTPRC splicing patterns across T cell subpopulations and the concerted expression of the associated hnRNPLL splicing factor. Methods such as MAS-ISO-seq will drive discovery of novel isoforms and the transition from gene expression to transcript isoform expression analyses.

genetics↗

bioRxiv2021

Combined tumor and immune signals from genomes or transcriptomes predict outcomes of checkpoint inhibition in melanoma

Cancer immunotherapy with checkpoint blockade (CPB) leads to improved outcomes in melanoma and other tumor types, but a majority of patients do not respond. High tumor mutation burden (TMB) and high levels of tumor-infiltrating T cells have been associated with response to immunotherapy, but integrative models to predict clinical benefit using DNA or RNA alone have not been comprehensively explored. We sequenced DNA and RNA from melanoma patients receiving CPB, and aggregated previously published data, yielding whole exome sequencing data for 189 patients and bulk RNA sequencing data for 178 patients. Using these datasets, we derived genomic and transcriptomic factors that predict overall survival (OS) and response to immunotherapy. Using whole-exome DNA data alone, we calculated T cell burden (TCB) and B cell burden (BCB) based on rearranged TCR/Ig DNA sequences and found that patients whose melanomas have high TMB together with either high TCB or high BCB survived longer and had higher response rates as compared to patients with either low TMB or TCB/BCB. Next, using bulk RNA-Seq data, differential expression analysis identified 83 genes associated with high or low OS. By combining pairs of immune-expressed genes with tumor-expressed genes, we identified three gene pairs associated with response and survival (Bonferroni P<0.05). All three gene pair models were validated in an independent cohort (n=180) (Bonferroni P<0.05). The best performing gene pair model included the lymphocyte-expressed MAP4K1 (Mitogen- Activated Protein Kinase Kinase Kinase Kinase 1) combined with the transcription factor TBX3 (T-Box Transcription Factor 3) which is overexpressed in poorly differentiated melanomas. We conclude that RNA-based (MAP4K1&TBX3) or DNA-based (TCB&TMB) models combining immune and tumor measures improve predictions of outcome after checkpoint blockade in melanoma.

genomics↗