Testing Foundations of Biological Scaling Theory Using Automated Measurements of Vascular Networks

Scientists have long sought to understand how vascular networks supply blood and oxygen to cells throughout the body. Recent work focuses on principles that constrain how vessel size changes through branching generations from the aorta to capillaries and uses scaling exponents to quantify these changes. Prominent scaling theories predict that combinations of these exponents explain how metabolic, growth, and other biological rates vary with body size. Nevertheless, direct measurements of individual vessel segments have been limited because existing techniques for measuring vasculature are invasive, time consuming, and technically difficult. We developed software that extracts the length, radius, and connectivity of in vivo vessels from contrast-enhanced 3D Magnetic Resonance Angiography. Using data from 20 human subjects, we calculated scaling exponents by four methods—two derived from local properties of branching junctions and two from whole-network properties. Although these methods are often used interchangeably in the literature, we do not find general agreement between these methods, particularly for vessel lengths. Measurements for length of vessels also diverge from theoretical values, but those for radius show stronger agreement. Our results demonstrate that vascular network models cannot ignore certain complexities of real vascular systems and indicate the need to discover new principles regarding vessel lengths.     

Back to the future: transgenerational transmission of xenobiotic-induced epigenetic remodeling

Epigenetics, or regulation of gene expression independent of DNA sequence, is the missing link between genotype and phenotype. Epigenetic memory, mediated by histone and DNA modifications, is controlled by a set of specialized enzymes, metabolite availability, and signaling pathways. A mostly unstudied subject is how sub-toxic exposure to several xenobiotics during specific developmental stages can alter the epigenome and contribute to the development of disease phenotypes later in life. Furthermore, it has been shown that exposure to low-dose xenobiotics can also result in further epigenetic remodeling in the germ line and contribute to increase disease risk in the next generation (multigenerational and transgenerational effects). We here offer a perspective on current but still incomplete knowledge of xenobiotic-induced epigenetic alterations, and their possible transgenerational transmission. We also propose several molecular mechanisms by which the epigenetic landscape may be altered by environmental xenobiotics and hypothesize how diet and physical activity may counteract epigenetic alterations.     

Identification of differentially methylated markers among cytogenetic risk groups of acute myeloid leukemia

Aberrant DNA methylation is known to occur in cancer, including hematological malignancies such as acute myeloid leukemia (AML). However, less is known about whether specific methylation profiles characterize specific subcategories of AML. We examined this issue by using comprehensive high-throughput array-based relative methylation analysis (CHARM) to compare methylation profiles among patients in different AML cytogenetic risk groups. We found distinct profiles in each group, with the high-risk group showing overall increased methylation compared with low- and mid-risk groups. The differentially methylated regions (DMRs) distinguishing cytogenetic risk groups of AML were enriched in the CpG island shores. Specific risk-group associated DMRs were located near genes previously known to play a role in AML or other malignancies, such as MN1, UHRF1, HOXB3, and HOXB4, as well as TRIM71, the function of which in cancer is not well characterized. These findings were verified by quantitative bisulfite pyrosequencing and by comparison with results available at the TCGA cancer genome browser. To explore the potential biological significance of the observed methylation changes, we correlated our findings with gene expression data available through the TCGA database. The results showed that decreased methylation at HOXB3 and HOXB4 was associated with increased gene expression of both HOXB genes specific to the mid-risk AML, while increased DNA methylation at DCC distinctive to the high-risk AML was associated with increased gene expression. Our results suggest that the differential impact of cytogenetic changes on AML prognosis may, in part, be mediated by changes in methylation.     

Acid Hydrolysis and Molecular Density of Phytoglycogen and Liver Glycogen Helps Understand the Bonding in Glycogen α (Composite) Particles

Phytoglycogen (from certain mutant plants) and animal glycogen are highly branched glucose polymers with similarities in structural features and molecular size range. Both appear to form composite α particles from smaller β particles. The molecular size distribution of liver glycogen is bimodal, with distinct α and β components, while that of phytoglycogen is monomodal. This study aims to enhance our understanding of the nature of the link between liver-glycogen β particles resulting in the formation of large α particles. It examines the time evolution of the size distribution of these molecules during acid hydrolysis, and the size dependence of the molecular density of both glucans. The monomodal distribution of phytoglycogen decreases uniformly in time with hydrolysis, while with glycogen, the large particles degrade significantly more quickly. The size dependence of the molecular density shows qualitatively different shapes for these two types of molecules. The data, combined with a quantitative model for the evolution of the distribution during degradation, suggest that the bonding between β into α particles is different between phytoglycogen and liver glycogen, with the formation of a glycosidic linkage for phytoglycogen and a covalent or strong non-covalent linkage, most probably involving a protein, for glycogen as most likely. This finding is of importance for diabetes, where α-particle structure is impaired.     

Antiviral Activity of the Human Cathelicidin,LL-37, and Derived Peptides on Seasonal and Pandemic Influenza A Viruses

Human LL-37, a cationic antimicrobial peptide, was recently shown to have antiviral activity against influenza A virus (IAV) strains in vitro and in vivo. In this study we compared the anti-influenza activity of LL-37 with that of several fragments derived from LL-37. We first tested the peptides against a seasonal H3N2 strain and the mouse adapted H1N1 strain, PR-8. The N-terminal fragment, LL-23, had slight neutralizing activity against these strains. In LL-23V9 serine 9 is substituted by valine creating a continuous hydrophobic surface. LL-23V9 has been shown to have increased anti-bacterial activity compared to LL-23 and we now show slightly increased antiviral activity compared to LL-23 as well. The short central fragments, FK-13 and KR-12, which have anti-bacterial activity did not inhibit IAV. In contrast, a longer 20 amino acid central fragment of LL-37 (GI-20) had neutralizing activity similar to LL-37. None of the peptides inhibited viral hemagglutination or neuraminidase activity. We next tested activity of the peptides against a strain of pandemic H1N1 of 2009 (A/California/04/09/H1N1 or “Cal09”). Unexpectedly, LL-37 had markedly reduced activity against Cal09 using several cell types and assays of antiviral activity. A mutant viral strain containing just the hemagglutinin (HA) of 2009 pandemic H1N1 was inhibited by LL-37, suggested that genes other than the HA are involved in the resistance of pH1N1. In contrast, GI-20 did inhibit Cal09. In conclusion, the central helix of LL-37 incorporated in GI-20 appears to be required for optimal antiviral activity. The finding that GI-20 inhibits Cal09 suggests that it may be possible to engineer derivatives of LL-37 with improved antiviral properties.     

Cell Signaling-Based Classifier Predicts Response to Induction Therapy in Elderly Patients with Acute Myeloid Leukemia

Single-cell network profiling (SCNP) data generated from multi-parametric flow cytometry analysis of bone marrow (BM) and peripheral blood (PB) samples collected from patients >55 years old with non-M3 AML were used to train and validate a diagnostic classifier (DX_SCNP) for predicting response to standard induction chemotherapy (complete response [CR] or CR with incomplete hematologic recovery [CRi] versus resistant disease [RD]). SCNP-evaluable patients from four SWOG AML trials were randomized between Training (N = 74 patients with CR, CRi or RD; BM set = 43; PB set = 57) and Validation Analysis Sets (N = 71; BM set = 42, PB set = 53). Cell survival, differentiation, and apoptosis pathway signaling were used as potential inputs for DX_SCNP. Five DX_SCNP classifiers were developed on the SWOG Training set and tested for prediction accuracy in an independent BM verification sample set (N = 24) from ECOG AML trials to select the final classifier, which was a significant predictor of CR/CRi (area under the receiver operating characteristic curve AUROC = 0.76, p = 0.01). The selected classifier was then validated in the SWOG BM Validation Set (AUROC = 0.72, p = 0.02). Importantly, a classifier developed using only clinical and molecular inputs from the same sample set (DX_CLINICAL2) lacked prediction accuracy: AUROC = 0.61 (p = 0.18) in the BM Verification Set and 0.53 (p = 0.38) in the BM Validation Set. Notably, the DX_SCNP classifier was still significant in predicting response in the BM Validation Analysis Set after controlling for DX_CLINICAL2 (p = 0.03), showing that DX_SCNP provides information that is independent from that provided by currently used prognostic markers. Taken together, these data show that the proteomic classifier may provide prognostic information relevant to treatment planning beyond genetic mutations and traditional prognostic factors in elderly AML.