Hydrologic flowpaths influence inorganic and organic nutrient leaching in a forest soil

Hydrologic pathways through soil affect element leaching by determining the relative importance of biogeochemical processes such as sorption and decomposition. We used stable hydrogen isotopes of water (δD) to examine the influence of flowpaths on soil solution chemistry in a mature spruce–hemlock forest in coastal Oregon, USA. Soil solutions (50 cm depth, n = 13) were collected monthly for 1 year and analyzed for δD, major ions and dissolved organic carbon (DOC) and nitrogen (DON). We propose that the variability of δD can be used as an index of flowpath length and contact time. Throughfall variability in δD was much greater than soil solution variability, illustrating that soil solution integrates the variation in inputs. Lysimeters with greater variation in δD presumably have a greater proportion of flow through rapid flowpaths such as macropores. The variation in soil solution δD for individual lysimeters explained up to 53% of the variation in soil solution chemistry, and suggests that flowpaths influence leaching of some constituents. Soil solutions from lysimeters with greater δD variation had higher DOC and DON (r ² = 0.51 and 0.37, respectively), perhaps because transport via macropores reduces interaction of DOM with the soil matrix. In contrast, nitrate concentrations were highest in lysimeters with a small variation in δD, where long contact time and low DOC concentrations may yield higher net nitrification. Our results demonstrate the utility of stable isotopes to link flowpaths and soil solution chemistry, and illustrate how the spatial complexity of soils can influence ecosystem-level nutrient losses.     

Centromere sizes,positions, and movements in the interphase nucleus

Each microspore of the onion Allium fistulosum (n=8) has 8 chromosomes. It is shown that in the microspore the 8 centromeres aggregate to form 2 or 3 centromeric structures. Subsequently, at early mitotic prophase, these aggregates are resolved into 8 separate centromeres and each becomes structurally double. After mitosis the pollen grain contains 2 nuclei, each with 8 separate and distinct centromeres, clustered at the nuclear envelope. As interphase progresses the centromeres of the vegetative nucleus are no longer at the nuclear envelope and they aggregate into 3 or 4 centromeric masses. In the generative nucleus there is less movement. The interphase centromere movements occur in the absence of microtubules. The centromeres range in size from about 0.10 to 0.17 m³ with an average of 0.14 m³ per centromere.     

Enhanced multiplex genome engineering through co-operative oligonucleotide co-selection

Genome-scale engineering of living organisms requires precise and economical methods to efficiently modify many loci within chromosomes. One such example is the directed integration of chemically synthesized single-stranded deoxyribonucleic acid (oligonucleotides) into the chromosome of Escherichia coli during replication. Herein, we present a general co-selection strategy in multiplex genome engineering that yields highly modified cells. We demonstrate that disparate sites throughout the genome can be easily modified simultaneously by leveraging selectable markers within 500 kb of the target sites. We apply this technique to the modification of 80 sites in the E. coli genome.     

Dietary cystine level affects metabolic rate and glycaemic control in adult mice

Plasma total cysteine (tCys) is strongly and independently associated with obesity in large human cohorts, but whether the association is causal is unknown. Dietary cyst(e)ine increases weight gain in some rodent models. We investigated the body composition, metabolic rate and metabolic phenotype of mature C3H/HeH mice assigned to low-cystine (LC) or high-cystine (HC) diets for 12 weeks.Compared to LC mice, HC mice gained more weight (P=.004 for 12-week weight gain %), with increased fat mass and lean mass, and lowered O₂ consumption and CO₂ production by calorimetry. The HC mice had 30% increase in intestinal fat/body weight % (P=.003) and ～twofold elevated hepatic triglycerides (P=.046), with increased expression of hepatic lipogenic factors, peroxisome proliferator-activated receptor-γ and sterol regulatory element binding protein-1. Gene expression of both basal and catecholamine-stimulated lipolytic enzymes, adipose triglyceride lipase and hormone-sensitive lipase was inhibited in HC mice adipose tissue. The HC mice also had elevated fasting glucose (7.0 vs. 4.5 mmol/L, P<.001) and a greater area under the curve (P<.001) in intraperitoneal glucose tolerance tests, with enhanced expression of the negative regulator of insulin signaling, protein tyrosine phosphatase-1B, in liver and adipose tissue.Overall, high cystine intake promotes adiposity and an adverse metabolic phenotype in mice, indicating that the positive association of plasma tCys with obesity in humans may be causal.     

High-order SNP combinations associated with complex diseases: efficient discovery, statistical power and functional interactions

There has been increased interest in discovering combinations of single-nucleotide polymorphisms (SNPs) that are strongly associated with a phenotype even if each SNP has little individual effect. Efficient approaches have been proposed for searching two-locus combinations from genome-wide datasets. However, for high-order combinations, existing methods either adopt a brute-force search which only handles a small number of SNPs (up to few hundreds), or use heuristic search that may miss informative combinations. In addition, existing approaches lack statistical power because of the use of statistics with high degrees-of-freedom and the huge number of hypotheses tested during combinatorial search. Due to these challenges, functional interactions in high-order combinations have not been systematically explored. We leverage discriminative-pattern-mining algorithms from the data-mining community to search for high-order combinations in case-control datasets. The substantially improved efficiency and scalability demonstrated on synthetic and real datasets with several thousands of SNPs allows the study of several important mathematical and statistical properties of SNP combinations with order as high as eleven. We further explore functional interactions in high-order combinations and reveal a general connection between the increase in discriminative power of a combination over its subsets and the functional coherence among the genes comprising the combination, supported by multiple datasets. Finally, we study several significant high-order combinations discovered from a lung-cancer dataset and a kidney-transplant-rejection dataset in detail to provide novel insights on the complex diseases. Interestingly, many of these associations involve combinations of common variations that occur in small fractions of population. Thus, our approach is an alternative methodology for exploring the genetics of rare diseases for which the current focus is on individually rare variations.     

Systems analysis of primary Sjögren's syndrome pathogenesis in salivary glands identifies shared pathways in human and a mouse model

Bone tissue has an exceptional quality to regenerate to native tissue in response to injury. However, the fracture repair process requires mechanical stability or a viable biological microenvironment or both to ensure successful healing to native tissue. An improved understanding of the molecular and cellular events that occur during bone repair and remodeling has led to the development of biologic agents that can augment the biological microenvironment and enhance bone repair. Orthobiologics, including stem cells, osteoinductive growth factors, osteoconductive matrices, and anabolic agents, are available clinically for accelerating fracture repair and treatment of compromised bone repair situations like delayed unions and nonunions. Preclinical and clinical studies using biologic agents like recombinant bone morphogenetic proteins have demonstrated an efficacy similar or better than that of autologous bone graft in acute fracture healing. A lack of standardized outcome measures for comparison of biologic agents in clinical fracture repair trials, frequent off-label use, and a limited understanding of the biological activity of these agents at the bone repair site have limited their efficacy in clinical applications.     

Measuring cation dependent DNA polymerase fidelity landscapes by deep sequencing

High-throughput recording of signals embedded within inaccessible micro-environments is a technological challenge. The ideal recording device would be a nanoscale machine capable of quantitatively transducing a wide range of variables into a molecular recording medium suitable for long-term storage and facile readout in the form of digital data. We have recently proposed such a device, in which cation concentrations modulate the misincorporation rate of a DNA polymerase (DNAP) on a known template, allowing DNA sequences to encode information about the local cation concentration. In this work we quantify the cation sensitivity of DNAP misincorporation rates, making possible the indirect readout of cation concentration by DNA sequencing. Using multiplexed deep sequencing, we quantify the misincorporation properties of two DNA polymerases - Dpo4 and Klenow exo(-) - obtaining the probability and base selectivity of misincorporation at all positions within the template. We find that Dpo4 acts as a DNA recording device for Mn(2+) with a misincorporation rate gain of ～2%/mM. This modulation of misincorporation rate is selective to the template base: the probability of misincorporation on template T by Dpo4 increases >50-fold over the range tested, while the other template bases are affected less strongly. Furthermore, cation concentrations act as scaling factors for misincorporation: on a given template base, Mn(2+) and Mg(2+) change the overall misincorporation rate but do not alter the relative frequencies of incoming misincorporated nucleotides. Characterization of the ion dependence of DNAP misincorporation serves as the first step towards repurposing it as a molecular recording device.     

Genome-scale promoter engineering by coselection MAGE

Multiplex automated genome engineering (MAGE) uses short oligonucleotides to scarlessly modify genomes; however, insertions >10 bases are still inefficient but can be improved substantially by selection of highly modified chromosomes. Here we describe 'coselection' MAGE (CoS-MAGE) to optimize biosynthesis of aromatic amino acid derivatives by combinatorially inserting multiple T7 promoters simultaneously into 12 genomic operons. Promoter libraries can be quickly generated to study gain-of-function epistatic interactions in gene networks.