Cell origin-dependent cooperativity of mutant Dnmt3a and Npm1 in clonal hematopoiesis and myeloid malignancy.

In adult acute myeloid leukemia (AML), the acquisition of driver somatic mutations may be preceded by a benign state termed clonal hematopoiesis (CH). To develop therapeutic strategies to prevent leukemia development from CH, it is important to understand the mechanisms by which CH-driving and AML-driving mutations cooperate. Here, we use mice with inducible mutant alleles common in human CH (DNMT3AR882; mouse Dnmt3aR878H) and AML (NPM1c; mouse Npm1cA). We find that Dnmt3aR878H/+ hematopoietic stem cells (HSCs), but not multipotent progenitor cell (MPP) subsets, have reduced cytokine expression and proinflammatory transcriptional signatures and a functional competitive advantage over their wild-type counterparts. Dnmt3aR878H/+ HSCs are the most potent cell type transformed by Npm1cA, generating myeloid malignancies in which few additional cooperating somatic mutation events were detected. At a molecular level, Npm1cA, in cooperation with Dnmt3aR878H, acutely increased the accessibility of a distinct set of promoters in HSCs compared with MPP cells. These promoters were enriched for cell cycling, PI3K/AKT/mTOR signaling, stem cell signatures, and targets of transcription factors, including NFAT and the chromatin binding factor HMGB1, which have been implicated in human AML. These results demonstrate cooperativity between preexisting Dnmt3aR878H and Npm1cA at the chromatin level, where specific loci altered in accessibility by Npm1cA are dependent on cell context as well as Dnmt3a mutation status. These findings have implications for biological understanding and therapeutic intervention in the transformation from CH to AML

Distinct tumor necrosis factor alpha receptors dictate stem cell fitness versus lineage output in Dnmt3a-mutant clonal hematopoiesis

UNLABELLED: Clonal hematopoiesis resulting from the enhanced fitness of mutant hematopoietic stem cells (HSC) associates with both favorable and unfavorable health outcomes related to the types of mature mutant blood cells produced, but how this lineage output is regulated is unclear. Using a mouse model of a clonal hematopoiesis-associated mutation, DNMT3AR882/+ (Dnmt3aR878H/+), we found that aging-induced TNFα signaling promoted the selective advantage of mutant HSCs and stimulated the production of mutant B lymphoid cells. The genetic loss of the TNFα receptor TNFR1 ablated the selective advantage of mutant HSCs without altering their lineage output, whereas the loss of TNFR2 resulted in the overproduction of mutant myeloid cells without altering HSC fitness. These results nominate TNFR1 as a target to reduce clonal hematopoiesis and the risk of associated diseases and support a model in which clone size and mature blood lineage production can be independently controlled to modulate favorable and unfavorable clonal hematopoiesis outcomes. SIGNIFICANCE: Through the identification and dissection of TNFα signaling as a key driver of murine Dnmt3a-mutant hematopoiesis, we report the discovery that clone size and production of specific mature blood cell types can be independently regulated. See related commentary by Niño and Pietras, p. 2724. This article is highlighted in the In This Issue feature, p. 2711

Patterns of brain structural connectivity differentiate normal weight from overweight subjects

AbstractBackgroundAlterations in the hedonic component of ingestive behaviors have been implicated as a possible risk factor in the pathophysiology of overweight and obese individuals. Neuroimaging evidence from individuals with increasing body mass index suggests structural, functional, and neurochemical alterations in the extended reward network and associated networks.AimTo apply a multivariate pattern analysis to distinguish normal weight and overweight subjects based on gray and white-matter measurements.MethodsStructural images (N = 120, overweight N = 63) and diffusion tensor images (DTI) (N = 60, overweight N = 30) were obtained from healthy control subjects. For the total sample the mean age for the overweight group (females = 32, males = 31) was 28.77 years (SD = 9.76) and for the normal weight group (females = 32, males = 25) was 27.13 years (SD = 9.62). Regional segmentation and parcellation of the brain images was performed using Freesurfer. Deterministic tractography was performed to measure the normalized fiber density between regions. A multivariate pattern analysis approach was used to examine whether brain measures can distinguish overweight from normal weight individuals.Results1. White-matter classification: The classification algorithm, based on 2 signatures with 17 regional connections, achieved 97% accuracy in discriminating overweight individuals from normal weight individuals. For both brain signatures, greater connectivity as indexed by increased fiber density was observed in overweight compared to normal weight between the reward network regions and regions of the executive control, emotional arousal, and somatosensory networks. In contrast, the opposite pattern (decreased fiber density) was found between ventromedial prefrontal cortex and the anterior insula, and between thalamus and executive control network regions. 2. Gray-matter classification: The classification algorithm, based on 2 signatures with 42 morphological features, achieved 69% accuracy in discriminating overweight from normal weight. In both brain signatures regions of the reward, salience, executive control and emotional arousal networks were associated with lower morphological values in overweight individuals compared to normal weight individuals, while the opposite pattern was seen for regions of the somatosensory network.Conclusions1. An increased BMI (i.e., overweight subjects) is associated with distinct changes in gray-matter and fiber density of the brain. 2. Classification algorithms based on white-matter connectivity involving regions of the reward and associated networks can identify specific targets for mechanistic studies and future drug development aimed at abnormal ingestive behavior and in overweight/obesity

The Cotton Centromere Contains a Ty3-gypsy-like LTR Retroelement

The centromere is a repeat-rich structure essential for chromosome segregation; with the long-term aim of understanding centromere structure and function, we set out to identify cotton centromere sequences. To isolate centromere-associated sequences from cotton, (Gossypium hirsutum) we surveyed tandem and dispersed repetitive DNA in the genus. Centromere-associated elements in other plants include tandem repeats and, in some cases, centromere-specific retroelements. Examination of cotton genomic survey sequences for tandem repeats yielded sequences that did not localize to the centromere. However, among the repetitive sequences we also identified a gypsy-like LTR retrotransposon (Centromere Retroelement Gossypium, CRG) that localizes to the centromere region of all chromosomes in domestic upland cotton, Gossypium hirsutum, the major commercially grown cotton. The location of the functional centromere was confirmed by immunostaining with antiserum to the centromere-specific histone CENH3, which co-localizes with CRG hybridization on metaphase mitotic chromosomes. G. hirsutum is an allotetraploid composed of A and D genomes and CRG is also present in the centromere regions of other AD cotton species. Furthermore, FISH and genomic dot blot hybridization revealed that CRG is found in D-genome diploid cotton species, but not in A-genome diploid species, indicating that this retroelement may have invaded the A-genome centromeres during allopolyploid formation and amplified during evolutionary history. CRG is also found in other diploid Gossypium species, including B and E2 genome species, but not in the C, E1, F, and G genome species tested. Isolation of this centromere-specific retrotransposon from Gossypium provides a probe for further understanding of centromere structure, and a tool for future engineering of centromere mini-chromosomes in this important crop species

Detailed Analysis of a Contiguous 22-Mb Region of the Maize Genome

Most of our understanding of plant genome structure and evolution has come from the careful annotation of small (e.g., 100 kb) sequenced genomic regions or from automated annotation of complete genome sequences. Here, we sequenced and carefully annotated a contiguous 22 Mb region of maize chromosome 4 using an improved pseudomolecule for annotation. The sequence segment was comprehensively ordered, oriented, and confirmed using the maize optical map. Nearly 84% of the sequence is composed of transposable elements (TEs) that are mostly nested within each other, of which most families are low-copy. We identified 544 gene models using multiple levels of evidence, as well as five miRNA genes. Gene fragments, many captured by TEs, are prevalent within this region. Elimination of gene redundancy from a tetraploid maize ancestor that originated a few million years ago is responsible in this region for most disruptions of synteny with sorghum and rice. Consistent with other sub-genomic analyses in maize, small RNA mapping showed that many small RNAs match TEs and that most TEs match small RNAs. These results, performed on ∼1% of the maize genome, demonstrate the feasibility of refining the B73 RefGen_v1 genome assembly by incorporating optical map, high-resolution genetic map, and comparative genomic data sets. Such improvements, along with those of gene and repeat annotation, will serve to promote future functional genomic and phylogenomic research in maize and other grasses

Hand in hand: intrinsic and extrinsic drivers of aging and clonal hematopoiesis.

Over the past 25 years, the importance of hematopoietic stem cell (HSC) aging in overall hematopoietic and immune system health span has been appreciated. Much work has been done in model organisms to understand the intrinsic dysregulation that occurs in HSCs during aging, with the goal of identifying modifiable mechanisms that represent the proverbial fountain of youth. Much more recently, the discovery of somatic mutations that are found to provide a selective advantage to HSCs and accumulate in the hematopoietic system during aging, termed clonal hematopoiesis (CH), inspires revisiting many of these previously defined drivers of HSC aging in the context of these somatic mutations. To truly understand these processes and develop a holistic picture of HSC aging, ongoing and future studies must include investigation of the critical changes that occur in the HSC niche or bone marrow microenvironment with aging, as increasing evidence supports that these HSC-extrinsic alterations provide necessary inflammation, signaling pathway activation or repression, and other selective pressures to favor HSC aging-associated phenotypes and CH. Here, we provide our perspectives based on the past 8 years of our own laboratory\u27s investigations into these mechanisms and chart a path for integrative studies that, in our opinion, will provide an ideal opportunity to discover HSC and hematopoietic health span-extending interventions. This path includes examining when and how aging-associated HSC-intrinsic and HSC-extrinsic changes accumulate over time in different individuals and developing new models to track and test relevant HSC-extrinsic changes, complementary to innovative HSC lineage tracing systems that have recently been developed

Predicting Dangerous Seismic Events in Coal Mines under Distribution Drift

Clonal hematopoiesis (CH) is a common aging-associated condition with increased risk of hematologic malignancy. Knowledge of the mechanisms driving evolution from CH to overt malignancy has been hampered by a lack of in vivo models that orthogonally activate mutant alleles. Here, we develop independently regulatable mutations in DNA methyltransferase 3A (Dnmt3a) and nucleophosmin 1 (Npm1), observed in human CH and AML, respectively. We find Dnmt3a mutation expands hematopoietic stem and multipotent progenitor cells (HSC/MPPs), modeling CH. Induction of mutant Npm1 after development of Dnmt3a-mutant CH causes progression to myeloproliferative disorder (MPD), and more aggressive MPD is observed with longer latency between mutations. MPDs uniformly progress to acute myeloid leukemia (AML) following transplant, accompanied by a decrease in HSC/MPPs and an increase in myeloid-restricted progenitors, the latter of which propagate AML in tertiary recipient mice. At a molecular level, progression of CH to MPD is accompanied by selection for mutations activating Ras/Raf/MAPK signaling. Progression to AML is characterized by additional oncogenic signaling mutations (Ptpn11, Pik3r1, Flt3) and/or mutations in epigenetic regulators (Hdac1, Idh1, Arid1a). Together, our study demonstrates that Npm1 mutation drives evolution of Dnmt3a-mutant CH to AML and rate of disease progression is accelerated with longer latency of CH

Patterns of brain structural connectivity differentiate normal weight from overweight subjects.

BackgroundAlterations in the hedonic component of ingestive behaviors have been implicated as a possible risk factor in the pathophysiology of overweight and obese individuals. Neuroimaging evidence from individuals with increasing body mass index suggests structural, functional, and neurochemical alterations in the extended reward network and associated networks.AimTo apply a multivariate pattern analysis to distinguish normal weight and overweight subjects based on gray and white-matter measurements.MethodsStructural images (N = 120, overweight N = 63) and diffusion tensor images (DTI) (N = 60, overweight N = 30) were obtained from healthy control subjects. For the total sample the mean age for the overweight group (females = 32, males = 31) was 28.77 years (SD = 9.76) and for the normal weight group (females = 32, males = 25) was 27.13 years (SD = 9.62). Regional segmentation and parcellation of the brain images was performed using Freesurfer. Deterministic tractography was performed to measure the normalized fiber density between regions. A multivariate pattern analysis approach was used to examine whether brain measures can distinguish overweight from normal weight individuals.Results1. White-matter classification: The classification algorithm, based on 2 signatures with 17 regional connections, achieved 97% accuracy in discriminating overweight individuals from normal weight individuals. For both brain signatures, greater connectivity as indexed by increased fiber density was observed in overweight compared to normal weight between the reward network regions and regions of the executive control, emotional arousal, and somatosensory networks. In contrast, the opposite pattern (decreased fiber density) was found between ventromedial prefrontal cortex and the anterior insula, and between thalamus and executive control network regions. 2. Gray-matter classification: The classification algorithm, based on 2 signatures with 42 morphological features, achieved 69% accuracy in discriminating overweight from normal weight. In both brain signatures regions of the reward, salience, executive control and emotional arousal networks were associated with lower morphological values in overweight individuals compared to normal weight individuals, while the opposite pattern was seen for regions of the somatosensory network.Conclusions1. An increased BMI (i.e., overweight subjects) is associated with distinct changes in gray-matter and fiber density of the brain. 2. Classification algorithms based on white-matter connectivity involving regions of the reward and associated networks can identify specific targets for mechanistic studies and future drug development aimed at abnormal ingestive behavior and in overweight/obesity