Prediction of Cell Wall Properties and Response to Deconstruction Using Alkaline Pretreatment in Diverse Maize Genotypes Using Py-MBMS and NIR

In this work, we explore the ability of several characterization approaches for phenotyping to extract information about plant cell wall properties in diverse maize genotypes with the goal of identifying approaches that could be used to predict the plant’s response to deconstruction in a biomass-to-biofuel process. Specifically, a maize diversity panel was subjected to two high-throughput biomass characterization approaches, pyrolysis molecular beam mass spectrometry (py-MBMS) and near-infrared (NIR) spectroscopy, and chemometric models to predict a number of plant cell wall properties as well as enzymatic hydrolysis yields of glucose following either no pretreatment or with mild alkaline pretreatment. These were compared to multiple linear regression (MLR) models developed from quantified properties. We were able to demonstrate that direct correlations to specific mass spectrometry ions from pyrolysis as well as characteristic regions of the second derivative of the NIR spectrum regions were comparable in their predictive capability to partial least squares (PLS) models for p-coumarate content, while the direct correlation to the spectral data was superior to the PLS for Klason lignin content and guaiacyl monomer release by thioacidolysis as assessed by cross-validation. The PLS models for prediction of hydrolysis yields using either py-MBMS or NIR spectra were superior to MLR models based on quantified properties for unpretreated biomass. However, the PLS models using the two high-throughput characterization approaches could not predict hydrolysis following alkaline pretreatment while MLR models based on quantified properties could. This is likely a consequence of quantified properties including some assessments of pretreated biomass, while the py-MBMS and NIR only utilized untreated biomass.     

Transcriptional Analysis of Flowering Time in Switchgrass

Over the past two decades, switchgrass (Panicum virgatum) has emerged as a priority biofuel feedstock. The bulk of switchgrass biomass is in the vegetative portion of the plant; therefore, increasing the length of vegetative growth will lead to an increase in overall biomass yield. The goal of this study was to gain insight into the control of flowering time in switchgrass that would assist in development of cultivars with longer vegetative phases through delayed flowering. RNA sequencing was used to assess genome-wide expression profiles across a developmental series between switchgrass genotypes belonging to the two main ecotypes: upland, typically early flowering, and lowland, typically late flowering. Leaf blades and tissues enriched for the shoot apical meristem (SAM) were collected in a developmental series from emergence through anthesis for RNA extraction. RNA from samples that flanked the SAM transition stage was sequenced for expression analyses. The analyses revealed differential expression patterns between early- and late-flowering genotypes for known flowering time orthologs. Namely, genes shown to play roles in photoperiod response and the circadian clock in other species were identified as potential candidates for regulating flowering time in the switchgrass genotypes analyzed. Based on their expression patterns, many of the differentially expressed genes could also be classified as putative promoters or repressors of flowering. The candidate genes presented here may be used to guide switchgrass improvement through marker-assisted breeding and/or transgenic or gene editing approaches.     

Patterns of divergence across the geographic and genomic landscape of a butterfly hybrid zone associated with a climatic gradient

Hybrid zones are a valuable tool for studying the process of speciation and for identifying the genomic regions undergoing divergence and the ecological (extrinsic) and nonecological (intrinsic) factors involved. Here, we explored the genomic and geographic landscape of divergence in a hybrid zone between Papilio glaucus and Papilio canadensis. Using a genome scan of 28,417 ddRAD SNPs, we identified genomic regions under possible selection and examined their distribution in the context of previously identified candidate genes for ecological adaptations. We showed that differentiation was genomewide, including multiple candidate genes for ecological adaptations, particularly those involved in seasonal adaptation and host plant detoxification. The Z chromosome and four autosomes showed a disproportionate amount of differentiation, suggesting genes on these chromosomes play a potential role in reproductive isolation. Cline analyses of significantly differentiated genomic SNPs, and of species‐diagnostic genetic markers, showed a high degree of geographic coincidence (81%) and concordance (80%) and were associated with the geographic distribution of a climate‐mediated developmental threshold (length of the growing season). A relatively large proportion (1.3%) of the outliers for divergent selection were not associated with candidate genes for ecological adaptations and may reflect the presence of previously unrecognized intrinsic barriers between these species. These results suggest that exogenous (climate‐mediated) and endogenous (unknown) clines may have become coupled and act together to reinforce reproductive isolation. This approach of assessing divergence across both the genomic and geographic landscape can provide insight about the interplay between the genetic architecture of reproductive isolation and endogenous and exogenous selection.     

C Isotopomer Analysis of Glutamate by Tandem Mass Spectrometry

Tandem mass spectrometry allows a compound to be isolated from the rest of the sample and dissociated into smaller fragments. We show here that fragmentation of glutamate mass isotopomers yields additional mass spectral data that significantly improve the analysis of metabolic fluxes compared to full-scan mass spectrometry. In order to validate the technique, tandem and full-scan mass spectrometry were used along with (13)C NMR to analyze glutamate from rat hearts perfused with three substrate mixtures (5 mM glucose plus 5 mM [2-(13)C]acetate, 5 mM [1-(13)C]glucose plus 5 U/L insulin, and 5 mM glucose plus 1 mM [3-(13)C]pyruvate). Analysis by tandem mass spectrometry showed that the enriched substrate contributed 98 +/- 2, 53 +/- 2, and 84 +/- 7%, respectively, of acetyl-coenzyme A while the rate of anaplerotic substrate entry was 7 +/- 3, 25 +/- 8, and 16 +/- 8%. Similar results were obtained with (13)C NMR data, while values from full-scan data had higher error. We believe that this is the first use of tandem mass spectrometry to determine pathway flux using (13)C-enriched substrates. Although analysis of the citric acid cycle by NMR is simpler (and more intuitive), tandem mass spectrometry has the potential to combine high sensitivity with the high information yield previously available only by NMR.     

Mapping the ligand-binding sites and disease-associated mutations on the most abundant protein in the human, type I collagen.

Type I collagen is the most abundant protein in humans, and it helps to maintain the integrity of many tissues via its interactions with cell surfaces, other extracellular matrix molecules, and growth and differentiation factors. Nearly 50 molecules have been found to interact with type I collagen, and for about half of them, binding sites on this collagen have been elucidated. In addition, over 300 mutations in type I collagen associated with human connective tissue disorders have been described. However, the spatial relationships between the known ligand-binding sites and mutation positions have not been examined. To this end, here we have created a map of type I collagen that includes all of its ligand-binding sites and mutations. The map reveals the existence of several hot spots for ligand interactions on type I collagen and that most of the binding sites locate to its C-terminal half. Moreover, on the collagen fibril some potentially relevant relationships between binding sites were observed including the following: fibronectin- and certain integrin-binding regions are near neighbors, which may mechanistically relate to fibronectin-dependent cell-collagen attachment; proteoglycan binding may potentially impact upon collagen fibrillogenesis, cell-collagen attachment, and collagen glycation seen in diabetes and aging; and mutations associated with osteogenesis imperfecta and other disorders show apparently nonrandom distribution patterns within both the monomer and fibril, implying that mutation positions correlate with disease phenotype. These and other observations presented here may provide novel insights into evaluating type I collagen functions and the relationships between its binding partners and mutations.     

Scent Marking in Voles: A Reassessment of Over Marking, Counter Marking, and Self-Advertisement

We conducted a series of experiments to discern among the counter-marking, over-marking, and self-advertisement hypotheses for secondary marking in male prairie voles, Microtus ochrogaster , and meadow voles, M. pennsylvanicus . Secondary scent marks (those placed in an area that has already been marked by a conspecific) were not significantly greater than initial marks placed on clean substrate (a substrate without any previous scent marks) for either species and thus did not support a counter-marking hypothesis. Similarly, overlapping of initial scent marks with secondary marks occurred less often than expected by chance and did not support an over-marking hypothesis. Secondary marks tended to avoid overlap with scent marks previously deposited by a potential competitor. Our results suggest that secondary scent marking functions to self-advertise by maximizing individual identity and avoiding masking or blending with previous donors. Future studies on secondary marking should be designed to quantify the observed and expected frequency and placement of original and secondary marks to discern among alternative hypotheses for the adaptive significance of secondary marking.     

ICA69(null) nonobese diabetic mice develop diabetes, but resist disease acceleration by cyclophosphamide.

ICA69 (islet cell Ag 69 kDa) is a diabetes-associated autoantigen with high expression levels in beta cells and brain. Its function is unknown, but knockout of its Caenorhabditis elegans homologue, ric-19, compromised neurotransmission. We disrupted the murine gene, ica-1, in 129-strain mice. These animals aged normally, but speed-congenic ICA69(null) nonobese diabetic (NOD) mice developed mid-life lethality, reminiscent of NOD-specific, late lethal seizures in glutamic acid decarboxylase 65-deficient mice. In contrast to wild-type and heterozygous animals, ICA69(null) NOD congenics fail to generate, even after immunization, cross-reactive T cells that recognize the dominant Tep69 epitope in ICA69, and its environmental mimicry Ag, the ABBOS epitope in BSA. This antigenic mimicry is thus driven by the endogenous self Ag, and not initiated by the environmental mimic. Insulitis, spontaneous, and adoptively transferred diabetes develop normally in ICA69(null) NOD congenics. Like glutamic acid decarboxylase 65, ICA69 is not an obligate autoantigen in diabetes. Unexpectedly, ICA69(null) NOD mice were resistant to cyclophosphamide (CY)-accelerated diabetes. Transplantation experiments with hemopoietic and islet tissue linked CY resistance to ICA69 deficiency in islets. CY-accelerated diabetes involves not only ablation of lymphoid cells, but ICA69-dependent drug toxicity in beta cells that boosts autoreactivity in the regenerating lymphoid system.     

Continental rain forest fragments in Singapore resist invasion by exotic plants

Abstract Aim In general, the plant communities of oceanic islands suffer more from exotic plant invasions than their continental equivalents. At least part of this difference may be contributed by differences in non‐biological factors, such as the antiquity and intensity of human impacts and the absence of internal barriers to dispersal, rather than differences in inherent invasibility. We tested the resistance of species‐rich continental rain forests to plant invasion on a small, continental island that has been subject to prolonged and intensive human impact. Location Singapore is a 683‐km² equatorial island <1 km from the Asian mainland and with a population of 4 million people. It has a continental biota but has been subject to human impacts as intense as on any oceanic island. Methods We sampled twenty‐nine sites in seven vegetation types, ranging from urban wasteland to fragments of primary lowland rain forest. In each sample plot, all plant species were identified, exotic cover was estimated, and a range of environmental variables measured. Additional qualitative surveys for exotic invasion were made in other forest areas in Singapore. The data were analysed by Spearman's rank correlation coefficient. Results The number of exotic species recorded at a site was unrelated to the number of native species. Across all sites, percentage canopy opening had the highest correlation with the number of exotic species, while soil pH (which largely reflects the incorporation of calcareous construction wastes) had the highest correlation if the mangrove sites were excluded. There were no exotics in mangrove forest and only a tropical American, bird‐dispersed shrub, Clidemia hirta (L.) D. Don (Melastomataceae: Koster's Curse), in primary and tall secondary forest patches. The species‐poor early stages of woody plant succession on highly degraded soils were also very resistant to exotic plant invasion. Main conclusions Long‐isolated rain forest fragments in an exotic‐dominated continental island landscape resist invasion by exotic plants, suggesting that the problems on oceanic islands may reflect an inherently greater invasibility. This study also adds to the increasing evidence that the floras of tropical rain forest fragments in South‐east Asia are remarkably resilient on a time‐scale of decades to a century or more.     

Power Analysis for Real-Time PCR Quantification of Genes in Activated Sludge and Analysis of the Variability Introduced by DNA Extraction

The aims of this study were to determine the power of discrimination of the real-time PCR assay for monitoring fluctuations in microbial populations within activated sludge and to identify sample processing points where methodological changes are needed to minimize the variability in target quantification. DNA was extracted using a commercially available kit from mixed liquor samples taken from the aeration tank of four bench-scale activated-sludge reactors operating at 2-, 5-, 10-, and 20-day solid retention times, with mixed-liquor volatile suspended solid (MLVSS) values ranging from 260 to 2,610 mg/liter. Real-time PCR assays for bacterial and Nitrospira 16S rRNA genes were chosen because they represent, respectively, a highly abundant and a less-abundant bacterial target subject to clustering within the activated sludge matrix. The mean coefficient of variation in DNA yields (measured as microgram of DNA per milligram of MLVSS) in triplicate extractions of 12 different samples was 12.2%. Based on power analyses, the variability associated with DNA extraction had a small impact on the overall variability of the real-time PCR assay. Instead, a larger variability was associated with the PCR assay. The less-abundant target (Nitrospira 16S rRNA gene) had more variability than the highly abundant target (bacterial 16S rRNA gene), and samples from the lower-biomass reactors had more variability than samples from the higher-biomass reactors. Power analysis of real-time PCR assays indicated that three to five samples were necessary to detect a twofold increase in bacterial 16S rRNA genes, whereas three to five samples were required to detect a fivefold increase in Nitrospira 16S rRNA genes.