Expression and function of PML-RARA in the hematopoietic progenitor cells of Ctsg-PML-RARA mice

Because PML-RARA-induced acute promyelocytic leukemia (APL) is a morphologically differentiated leukemia, many groups have speculated about whether its leukemic cell of origin is a committed myeloid precursor (e.g. a promyelocyte) versus an hematopoietic stem/progenitor cell (HSPC). We originally targeted PML-RARA expression with CTSG regulatory elements, based on the early observation that this gene was maximally expressed in cells with promyelocyte morphology. Here, we show that both Ctsg, and PML-RARA targeted to the Ctsg locus (in Ctsg-PML-RARA mice), are expressed in the purified KLS cells of these mice (KLS = Kit(+)Lin(-)Sca(+), which are highly enriched for HSPCs), and this expression results in biological effects in multi-lineage competitive repopulation assays. Further, we demonstrate the transcriptional consequences of PML-RARA expression in Ctsg-PML-RARA mice in early myeloid development in other myeloid progenitor compartments [common myeloid progenitors (CMPs) and granulocyte/monocyte progenitors (GMPs)], which have a distinct gene expression signature compared to wild-type (WT) mice. Although PML-RARA is indeed expressed at high levels in the promyelocytes of Ctsg-PML-RARA mice and alters the transcriptional signature of these cells, it does not induce their self-renewal. In sum, these results demonstrate that in the Ctsg-PML-RARA mouse model of APL, PML-RARA is expressed in and affects the function of multipotent progenitor cells. Finally, since PML/Pml is normally expressed in the HSPCs of both humans and mice, and since some human APL samples contain TCR rearrangements and express T lineage genes, we suggest that the very early hematopoietic expression of PML-RARA in this mouse model may closely mimic the physiologic expression pattern of PML-RARA in human APL patients

The Origin and Evolution of Mutations in Acute Myeloid Leukemia

SummaryMost mutations in cancer genomes are thought to be acquired after the initiating event, which may cause genomic instability and drive clonal evolution. However, for acute myeloid leukemia (AML), normal karyotypes are common, and genomic instability is unusual. To better understand clonal evolution in AML, we sequenced the genomes of M3-AML samples with a known initiating event (PML-RARA) versus the genomes of normal karyotype M1-AML samples and the exomes of hematopoietic stem/progenitor cells (HSPCs) from healthy people. Collectively, the data suggest that most of the mutations found in AML genomes are actually random events that occurred in HSPCs before they acquired the initiating mutation; the mutational history of that cell is “captured” as the clone expands. In many cases, only one or two additional, cooperating mutations are needed to generate the malignant founding clone. Cells from the founding clone can acquire additional cooperating mutations, yielding subclones that can contribute to disease progression and/or relapse

Mortality prediction in chronic obstructive pulmonary disease comparing the GOLD 2015 and GOLD 2019 staging: a pooled analysis of individual patient data

In 2019, The Global Initiative for Chronic Obstructive Lung Disease (GOLD) modified the grading system for patients with COPD, creating 16 subgroups (1A–4D). As part of the COPD Cohorts Collaborative International Assessment (3CIA) initiative, we aim to compare the mortality prediction of the 2015 and 2019 COPD GOLD staging systems. We studied 17 139 COPD patients from the 3CIA study, selecting those with complete data. Patients were classified by the 2015 and 2019 GOLD ABCD systems, and we compared the predictive ability for 5-year mortality of both classifications. In total, 17 139 patients with COPD were enrolled in 22 cohorts from 11 countries between 2003 and 2017; 8823 of them had complete data and were analysed. Mean±sd age was 63.9±9.8 years and 62.9% were male. GOLD 2019 classified the patients in milder degrees of COPD. For both classifications, group D had higher mortality. 5-year mortality did not differ between groups B and C in GOLD 2015; in GOLD 2019, mortality was greater for group B than C. Patients classified as group A and B had better sensitivity and positive predictive value with the GOLD 2019 classification than GOLD 2015. GOLD 2015 had better sensitivity for group C and D than GOLD 2019. The area under the curve values for 5-year mortality were only 0.67 (95% CI 0.66–0.68) for GOLD 2015 and 0.65 (95% CI 0.63–0.66) for GOLD 2019

Global maps of soil temperature

Research in global change ecology relies heavily on global climatic grids derived from estimates of air temperature in open areas at around 2 m above the ground. These climatic grids do not reflect conditions below vegetation canopies and near the ground surface, where critical ecosystem functions occur and most terrestrial species reside. Here, we provide global maps of soil temperature and bioclimatic variables at a 1-km2 resolution for 0–5 and 5–15 cm soil depth. These maps were created by calculating the difference (i.e. offset) between in situ soil temperature measurements, based on time series from over 1200 1-km2 pixels (summarized from 8519 unique temperature sensors) across all the world\u27s major terrestrial biomes, and coarse-grained air temperature estimates from ERA5-Land (an atmospheric reanalysis by the European Centre for Medium-Range Weather Forecasts). We show that mean annual soil temperature differs markedly from the corresponding gridded air temperature, by up to 10°C (mean = 3.0 ± 2.1°C), with substantial variation across biomes and seasons. Over the year, soils in cold and/or dry biomes are substantially warmer (+3.6 ± 2.3°C) than gridded air temperature, whereas soils in warm and humid environments are on average slightly cooler (−0.7 ± 2.3°C). The observed substantial and biome-specific offsets emphasize that the projected impacts of climate and climate change on near-surface biodiversity and ecosystem functioning are inaccurately assessed when air rather than soil temperature is used, especially in cold environments. The global soil-related bioclimatic variables provided here are an important step forward for any application in ecology and related disciplines. Nevertheless, we highlight the need to fill remaining geographic gaps by collecting more in situ measurements of microclimate conditions to further enhance the spatiotemporal resolution of global soil temperature products for ecological applications

Global maps of soil temperature

Research in global change ecology relies heavily on global climatic grids derived from estimates of air temperature in open areas at around 2 m above the ground. These climatic grids do not reflect conditions below vegetation canopies and near the ground surface, where critical ecosystem functions occur and most terrestrial species reside. Here, we provide global maps of soil temperature and bioclimatic variables at a 1-km² resolution for 0–5 and 5–15 cm soil depth. These maps were created by calculating the difference (i.e., offset) between in-situ soil temperature measurements, based on time series from over 1200 1-km² pixels (summarized from 8500 unique temperature sensors) across all the world’s major terrestrial biomes, and coarse-grained air temperature estimates from ERA5-Land (an atmospheric reanalysis by the European Centre for Medium-Range Weather Forecasts). We show that mean annual soil temperature differs markedly from the corresponding gridded air temperature, by up to 10°C (mean = 3.0 ± 2.1°C), with substantial variation across biomes and seasons. Over the year, soils in cold and/or dry biomes are substantially warmer (+3.6 ± 2.3°C) than gridded air temperature, whereas soils in warm and humid environments are on average slightly cooler (-0.7 ± 2.3°C). The observed substantial and biome-specific offsets emphasize that the projected impacts of climate and climate change on near-surface biodiversity and ecosystem functioning are inaccurately assessed when air rather than soil temperature is used, especially in cold environments. The global soil-related bioclimatic variables provided here are an important step forward for any application in ecology and related disciplines. Nevertheless, we highlight the need to fill remaining geographic gaps by collecting more in-situ measurements of microclimate conditions to further enhance the spatiotemporal resolution of global soil temperature products for ecological applications

Global maps of soil temperature.

Research in global change ecology relies heavily on global climatic grids derived from estimates of air temperature in open areas at around 2 m above the ground. These climatic grids do not reflect conditions below vegetation canopies and near the ground surface, where critical ecosystem functions occur and most terrestrial species reside. Here, we provide global maps of soil temperature and bioclimatic variables at a 1-km2 resolution for 0-5 and 5-15 cm soil depth. These maps were created by calculating the difference (i.e. offset) between in situ soil temperature measurements, based on time series from over 1200 1-km2 pixels (summarized from 8519 unique temperature sensors) across all the world's major terrestrial biomes, and coarse-grained air temperature estimates from ERA5-Land (an atmospheric reanalysis by the European Centre for Medium-Range Weather Forecasts). We show that mean annual soil temperature differs markedly from the corresponding gridded air temperature, by up to 10°C (mean = 3.0 ± 2.1°C), with substantial variation across biomes and seasons. Over the year, soils in cold and/or dry biomes are substantially warmer (+3.6 ± 2.3°C) than gridded air temperature, whereas soils in warm and humid environments are on average slightly cooler (-0.7 ± 2.3°C). The observed substantial and biome-specific offsets emphasize that the projected impacts of climate and climate change on near-surface biodiversity and ecosystem functioning are inaccurately assessed when air rather than soil temperature is used, especially in cold environments. The global soil-related bioclimatic variables provided here are an important step forward for any application in ecology and related disciplines. Nevertheless, we highlight the need to fill remaining geographic gaps by collecting more in situ measurements of microclimate conditions to further enhance the spatiotemporal resolution of global soil temperature products for ecological applications

Effect of Circadian Clock Gene Mutations on Nonvisual Photoreception in the Mouse

Mice with outer retinal degeneration lacking cryptochromes show reduced nonvisual responses to light. This effect is not specific to cryptochromes, but is common to multiple mutations that eliminate free-running circadian rhythms. The pupillary light response is under circadian regulation

Biome representational in silico karyotyping

Metagenomic characterization of complex biomes remains challenging. Here we describe a modification of digital karyotyping—biome representational in silico karyotyping (BRISK)—as a general technique for analyzing a defined representation of all DNA present in a sample. BRISK utilizes a Type IIB DNA restriction enzyme to create a defined representation of 27-mer DNAs in a sample. Massively parallel sequencing of this representation allows for construction of high-resolution karyotypes and identification of multiple species within a biome. Application to normal human tissue demonstrated linear recovery of tags by chromosome. We apply this technique to the biome of the oral mucosa and find that greater than 25% of recovered DNA is nonhuman. DNA from 41 microbial species could be identified from oral mucosa of two subjects. Of recovered nonhuman sequences, fewer than 30% are currently annotated. We characterized seven prevalent unknown sequences by chromosome walking and find these represent novel microbial sequences including two likely derived from novel phage genomes. Application of BRISK to archival tissue from a nasopharyngeal carcinoma resulted in identification of Epstein-Barr virus infection. These results suggest that BRISK is a powerful technique for the analysis of complex microbiomes and potentially for pathogen discovery

A supervised heatmap of 11 developmentally-regulated myeloid genes.

<p>Using the expression data from the Affymetirix Mouse Exon 1.0ST arrays, we created a supervised heatmap with SPOTFIRE using z-score averaging of the probeset with the highest average expression for each of 11 developmentally-regulated myeloid genes across all of our flow-sorted bone marrow cell samples. The legend is shown below the heatmap with downregulated genes in green and upregulated genes in red.</p

A supervised heatmap of the 22 genes significantly dysregulated in both the CMP and GMP compartments.

<p>We created a supervised clustering using SPOTFIRE of the 22 genes that were significantly dysregulated (unadjusted p value<0.001, fold change ≥2) in both the CMP and GMP ANOVA results comparing WT vs. <i>Ctsg-PML-RARA</i> samples. The supervised heatmap was created by plotting the relative expression of each of these genes to each other as a relative percentage, rather than z-score averaging, since the differences in expression levels between some genes was large, and z-score averaging inappropriately highlighted the genes with the highest expression levels. The legend is shown below the heatmap, with minimally expressed genes in green, and highly expressed genes in red.</p