Mutant U2AF1-induced alternative splicing of H2afy (macroH2A1) regulates B-lymphopoiesis in mice.

Somatic mutations in spliceosome genes are found in ∼50% of patients with myelodysplastic syndromes (MDS), a myeloid malignancy associated with low blood counts. Expression of the mutant splicing factor U2AF1(S34F) alters hematopoiesis and mRNA splicing in mice. Our understanding of the functionally relevant alternatively spliced target genes that cause hematopoietic phenotypes in vivo remains incomplete. Here, we demonstrate that reduced expression of H2afy1.1, an alternatively spliced isoform of the histone H2A variant gene H2afy, is responsible for reduced B cells in U2AF1(S34F) mice. Deletion of H2afy or expression of U2AF1(S34F) reduces expression of Ebf1 (early B cell factor 1), a key transcription factor for B cell development, and mechanistically, H2AFY is enriched at the EBF1 promoter. Induced expression of H2AFY1.1 in U2AF1(S34F) cells rescues reduced EBF1 expression and B cells numbers in vivo. Collectively, our data implicate alternative splicing of H2AFY as a contributor to lymphopenia induced by U2AF1(S34F) in mice and MDS.

Plasma metagenomic sequencing to detect and quantify bacterial DNA in ICU patients suspected of sepsis: A proof-of-principle study.

BACKGROUND: Timely recognition of sepsis and identification of pathogens can improve outcomes in critical care patients but microbial cultures have low accuracy and long turnaround times. In this proof-of-principle study, we describe metagenomic sequencing and analysis of nonhuman DNA in plasma. We hypothesized that quantitative analysis of bacterial DNA (bDNA) levels in plasma can enable detection and monitoring of pathogens. METHODS: We enrolled 30 patients suspected of sepsis in the surgical trauma intensive care unit and collected plasma samples at the time of diagnostic workup for sepsis (baseline), and 7 days and 14 days later. We performed metagenomic sequencing of plasma DNA and used computational classification of sequencing reads to detect and quantify total and pathogen-specific bDNA fraction. To improve assay sensitivity, we developed an enrichment method for bDNA based on size selection for shorter fragment lengths. Differences in bDNA fractions between samples were evaluated using t test and linear mixed-effects model, following log transformation. RESULTS: We analyzed 72 plasma samples from 30 patients. Twenty-seven samples (37.5%) were collected at the time of infection. Median total bDNA fraction was 1.6 times higher in these samples compared with samples with no infection (0.011% and 0.0068%, respectively, p < 0.001). In 17 patients who had active infection at enrollment and at least one follow-up sample collected, total bDNA fractions were higher at baseline compared with the next sample (p < 0.001). Following enrichment, bDNA fractions increased in paired samples by a mean of 16.9-fold. Of 17 samples collected at the time when bacterial pathogens were identified, we detected pathogen-specific DNA in 13 plasma samples (76.5%). CONCLUSION: Bacterial DNA levels in plasma are elevated in critically ill patients with active infection. Pathogen-specific DNA is detectable in plasma, particularly after enrichment using selection for shorter fragments. Serial changes in bDNA levels may be informative of treatment response. LEVEL OF EVIDENCE: Epidemiologic/Prognostic, Level V.

A general approach for detecting expressed mutations in AML cells using single cell RNA-sequencing.

Virtually all tumors are genetically heterogeneous, containing mutationally-defined subclonal cell populations that often have distinct phenotypes. Single-cell RNA-sequencing has revealed that a variety of tumors are also transcriptionally heterogeneous, but the relationship between expression heterogeneity and subclonal architecture is unclear. Here, we address this question in the context of Acute Myeloid Leukemia (AML) by integrating whole genome sequencing with single-cell RNA-sequencing (using the 10x Genomics Chromium Single Cell 5' Gene Expression workflow). Applying this approach to five cryopreserved AML samples, we identify hundreds to thousands of cells containing tumor-specific mutations in each case, and use the results to distinguish AML cells (including normal-karyotype AML cells) from normal cells, identify expression signatures associated with subclonal mutations, and find cell surface markers that could be used to purify subclones for further study. This integrative approach for connecting genotype to phenotype is broadly applicable to any sample that is phenotypically and genetically heterogeneous.