NOTCH1 Signaling Promotes Human T-Cell Acute Lymphoblastic Leukemia Initiating Cell Regeneration in Supportive Niches

Leukemia initiating cells (LIC) contribute to therapeutic resistance through acquisition of mutations in signaling pathways, such as NOTCH1, that promote self-renewal and survival within supportive niches. Activating mutations in NOTCH1 occur commonly in T cell acute lymphoblastic leukemia (T-ALL) and have been implicated in therapeutic resistance. However, the cell type and context specific consequences of NOTCH1 activation, its role in human LIC regeneration, and sensitivity to NOTCH1 inhibition in hematopoietic microenvironments had not been elucidated.We established humanized bioluminescent T-ALL LIC mouse models transplanted with pediatric T-ALL samples that were sequenced for NOTCH1 and other common T-ALL mutations. In this study, CD34(+) cells from NOTCH1(Mutated) T-ALL samples had higher leukemic engraftment and serial transplantation capacity than NOTCH1(Wild-type) CD34(+) cells in hematopoietic niches, suggesting that self-renewing LIC were enriched within the NOTCH1(Mutated) CD34(+) fraction. Humanized NOTCH1 monoclonal antibody treatment reduced LIC survival and self-renewal in NOTCH1(Mutated) T-ALL LIC-engrafted mice and resulted in depletion of CD34(+)CD2(+)CD7(+) cells that harbor serial transplantation capacity.These results reveal a functional hierarchy within the LIC population based on NOTCH1 activation, which renders LIC susceptible to targeted NOTCH1 inhibition and highlights the utility of NOTCH1 antibody targeting as a key component of malignant stem cell eradication strategies

Genome-Wide Identification of MicroRNAs in Response to Low Nitrate Availability in Maize Leaves and Roots

BACKGROUND: Nitrate is the major source of nitrogen available for many crop plants and is often the limiting factor for plant growth and agricultural productivity especially for maize. Many studies have been done identifying the transcriptome changes under low nitrate conditions. However, the microRNAs (miRNAs) varied under nitrate limiting conditions in maize has not been reported. MiRNAs play important roles in abiotic stress responses and nutrient deprivation. METHODOLOGY/PRINCIPAL FINDINGS: In this study, we used the SmartArray™ and GeneChip® microarray systems to perform a genome-wide search to detect miRNAs responding to the chronic and transient nitrate limiting conditions in maize. Nine miRNA families (miR164, miR169, miR172, miR397, miR398, miR399, miR408, miR528, and miR827) were identified in leaves, and nine miRNA families (miR160, miR167, miR168, miR169, miR319, miR395, miR399, miR408, and miR528) identified in roots. They were verified by real time stem loop RT-PCR, and some with additional time points of nitrate limitation. The miRNAs identified showed overlapping or unique responses to chronic and transient nitrate limitation, as well as tissue specificity. The potential target genes of these miRNAs in maize were identified. The expression of some of these was examined by qRT-PCR. The potential function of these miRNAs in responding to nitrate limitation is described. CONCLUSIONS/SIGNIFICANCE: Genome-wide miRNAs responding to nitrate limiting conditions in maize leaves and roots were identified. This provides an insight into the timing and tissue specificity of the transcriptional regulation to low nitrate availability in maize. The knowledge gained will help understand the important roles miRNAs play in maize responding to a nitrogen limiting environment and eventually develop strategies for the improvement of maize genetics

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

Two ultraviolet radiation datasets that cover China

Ultraviolet (UV) radiation has significant effects on ecosystems, environments, and human health, as well as atmospheric processes and climate change. Two ultraviolet radiation datasets are described in this paper. One contains hourly observations of UV radiation measured at 40 Chinese Ecosystem Research Network stations from 2005 to 2015. CUV3 broadband radiometers were used to observe the UV radiation, with an accuracy of 5%, which meets the World Meteorology Organization's measurement standards. The extremum method was used to control the quality of the measured datasets. The other dataset contains daily cumulative UV radiation estimates that were calculated using an all-sky estimation model combined with a hybrid model. The reconstructed daily UV radiation data span from 1961 to 2014. The mean absolute bias error and root-mean-square error are smaller than 30% at most stations, and most of the mean bias error values are negative, which indicates underestimation of the UV radiation intensity. These datasets can improve our basic knowledge of the spatial and temporal variations in UV radiation. Additionally, these datasets can be used in studies of potential ozone formation and atmospheric oxidation, as well as simulations of ecological processes

Temporal Small RNA Expression Profiling under Drought Reveals a Potential Regulatory Role of Small Nucleolar RNAs in the Drought Responses of Maize

Small RNAs (sRNAs) are short noncoding RNAs that play roles in many biological processes, including drought responses in plants. However, how the expression of sRNAs dynamically changes with the gradual imposition of drought stress in plants is largely unknown. We generated time-series sRNA sequence data from maize ( L.) seedlings under drought stress (DS) and under well-watered (WW) conditions at the same time points. Analyses of length, functional annotation, and abundance of 736,372 nonredundant sRNAs from both DS and WW data, as well as genome copy numbers at the corresponding genomic regions, revealed distinct patterns of abundance and genome organization for different sRNA classes. The analysis identified 6646 sRNAs whose regulation was altered in response to drought stress. Among drought-responsive sRNAs, 1325 showed transient downregulation by the seventh day, coinciding with visible symptoms of drought stress. The profiles revealed drought-responsive microRNAs, as well as other sRNAs that originated from ribosomal RNAs (rRNAs), splicing small nuclear RNAs, and small nucleolar RNAs (snoRNA). Expression profiles of their sRNA derivers indicated that snoRNAs might play a regulatory role through regulating the stability of rRNAs and splicing small nuclear RNAs under drought condition