Host-plant induced changes in microbial community structure and midgut gene expression in an invasive polyphage (Anoplophora glabripennis).

Polyphagous insect herbivores possess diverse mechanisms to overcome challenges of feeding in multiple plant species including, but not limited to, transcriptional plasticity and associations with obligate or facultative symbionts. The Asian longhorned beetle (Anoplophora glabripennis) is a polyphagous wood-feeder capable of developing on over 100 tree species and, like other polyphages, its genome contains amplifications of digestive and detoxification genes. This insect also possesses a diverse gut microbial community, which has the metabolic potential to augment digestive physiology. While the genomic repertoires of A. glabripennis and its microbial community have been studied previously, comparatively less is known about how the gut transcriptome and community change in response to feeding in different hosts. In this study, we show that feeding in two suitable hosts (Acer spp. and Populus nigra) altered the expression levels of multicopy genes linked to digestion and detoxification. However, feeding in a host with documented resistance (Populus tomentosa) induced changes in the transcriptome and community beyond what was observed in insects reared in P. nigra, including the downregulation of numerous ß-glucosidases, odorant binding proteins, and juvenile hormone binding proteins, the upregulation of several cuticular genes, and the loss of one major bacterial family from the gut community.

Wood chemistry analysis and expression profiling of a poplar clone expressing a tyrosine-rich peptide.

KEY MESSAGE: Our study has identified pathways and gene candidates that may be associated with the greater flexibility and digestibility of the poplar cell walls. With the goal of facilitating lignin removal during the utilization of woody biomass as a biofuel feedstock, we previously transformed a hybrid poplar clone with a partial cDNA sequence encoding a tyrosine- and hydroxyproline-rich glycoprotein from parsley. A number of the transgenic lines released more polysaccharides following protease digestion and were more flexible than wild-type plants, but otherwise normal in phenotype. Here, we report that overexpression of the tyrosine-rich peptide encoding sequence in these transgenic poplar plants did not significantly alter total lignin quantity or quality (S/G lignin ratio), five- and six-carbon sugar contents, growth rate, or susceptibility to a major poplar fungal pathogen, Septoria musiva. Whole-genome microarray analysis revealed a total of 411 differentially expressed transcripts in transgenic lines, all with decreased transcript abundance relative to wild-type plants. Their corresponding genes were overrepresented in functional categories such as secondary metabolism, amino acid metabolism, and energy metabolism. Transcript abundance was decreased primarily for five types of genes encoding proteins involved in cell-wall organization and in lignin biosynthesis. The expression of a subset of 19 of the differentially regulated genes by qRT-PCR validated the microarray results. Our study has identified pathways and gene candidates that may be the underlying cause for the enhanced flexibility and digestibility of the stems of poplar plants expressing the TYR transgene.

The Populus superoxide dismutase gene family and its responses to drought stress in transgenic poplar overexpressing a pine cytosolic glutamine synthetase (GS1a).

BACKGROUND: Glutamine synthetase (GS) plays a central role in plant nitrogen assimilation, a process intimately linked to soil water availability. We previously showed that hybrid poplar (Populus tremula X alba, INRA 717-1B4) expressing ectopically a pine cytosolic glutamine synthetase gene (GS1a) display enhanced tolerance to drought. Preliminary transcriptome profiling revealed that during drought, members of the superoxide dismutase (SOD) family were reciprocally regulated in GS poplar when compared with the wild-type control, in all tissues examined. SOD was the only gene family found to exhibit such patterns. RESULTS: In silico analysis of the Populus genome identified 12 SOD genes and two genes encoding copper chaperones for SOD (CCSs). The poplar SODs form three phylogenetic clusters in accordance with their distinct metal co-factor requirements and gene structure. Nearly all poplar SODs and CCSs are present in duplicate derived from whole genome duplication, in sharp contrast to their predominantly single-copy Arabidopsis orthologs. Drought stress triggered plant-wide down-regulation of the plastidic copper SODs (CSDs), with concomitant up-regulation of plastidic iron SODs (FSDs) in GS poplar relative to the wild type; this was confirmed at the activity level. We also found evidence for coordinated down-regulation of other copper proteins, including plastidic CCSs and polyphenol oxidases, in GS poplar under drought conditions. CONCLUSIONS: Both gene duplication and expression divergence have contributed to the expansion and transcriptional diversity of the Populus SOD/CCS families. Coordinated down-regulation of major copper proteins in drought-tolerant GS poplars supports the copper cofactor economy model where copper supply is preferentially allocated for plastocyanins to sustain photosynthesis during drought. Our results also extend previous findings on the compensatory regulation between chloroplastic CSDs and FSDs, and suggest that this copper-mediated mechanism represents a common response to oxidative stress and other genetic manipulations, as in GS poplars, that affect photosynthesis.

Black bear parathyroid hormone has greater anabolic effects on trabecular bone in dystrophin-deficient mice than in wild type mice.

Duchenne muscular dystrophy (DMD) is an X-linked neuromuscular disease that has deleterious consequences in muscle and bone, leading to decreased mobility, progressive osteoporosis, and premature death. Patients with DMD experience a higher-than-average fracture rate, particularly in the proximal and distal femur and proximal tibia. The dystrophin-deficient mdx mouse is a model of DMD that demonstrates muscle degeneration and fibrosis and osteoporosis. Parathyroid hormone, an effective anabolic agent for post-menopausal and glucocorticoid-induced osteoporosis, has not been explored for DMD. Black bear parathyroid hormone (bbPTH) has been implicated in the maintenance of bone properties during extended periods of disuse (hibernation). We cloned bbPTH and found 9 amino acid residue differences from human PTH. Apoptosis was mitigated and cAMP was activated by bbPTH in osteoblast cultures. We administered 28nmol/kg of bbPTH 1-84 to 4-week old male mdx and wild type mice via daily (5×/week) subcutaneous injection for 6 weeks. Vehicle-treated mdx mice had 44% lower trabecular bone volume fraction than wild type mice. No changes were found in femoral cortical bone geometry or mechanical properties with bbPTH treatment in wild type mice, and only medio-lateral moment of inertia changed with bbPTH treatment in mdx femurs. However, µCT analyses of the trabecular regions of the distal femur and proximal tibia showed marked increases in bone volume fraction with bbPTH treatment, with a greater anabolic response (7-fold increase) in mdx mice than wild type mice (2-fold increase). Trabecular number increased in mdx long bone, but not wild type bone. Additionally, greater osteoblast area and decreased osteoclast area were observed with bbPTH treatment in mdx mice. The heightened response to PTH in mdx bone compared to wild type suggests a link between dystrophin deficiency, altered calcium signaling, and bone. These findings support further investigation of PTH as an anabolic treatment for DMD-induced osteoporosis.

An efficient method to identify differentially expressed genes in microarray experiments.

MOTIVATION: Microarray experiments typically analyze thousands to tens of thousands of genes from small numbers of biological replicates. The fact that genes are normally expressed in functionally relevant patterns suggests that gene-expression data can be stratified and clustered into relatively homogenous groups. Cluster-wise dimensionality reduction should make it feasible to improve screening power while minimizing information loss. RESULTS: We propose a powerful and computationally simple method for finding differentially expressed genes in small microarray experiments. The method incorporates a novel stratification-based tight clustering algorithm, principal component analysis and information pooling. Comprehensive simulations show that our method is substantially more powerful than the popular SAM and eBayes approaches. We applied the method to three real microarray datasets: one from a Populus nitrogen stress experiment with 3 biological replicates; and two from public microarray datasets of human cancers with 10 to 40 biological replicates. In all three analyses, our method proved more robust than the popular alternatives for identification of differentially expressed genes. AVAILABILITY: The C++ code to implement the proposed method is available upon request for academic use.

Joint analysis of two microarray gene-expression data sets to select lung adenocarcinoma marker genes.

BACKGROUND: Due to the high cost and low reproducibility of many microarray experiments, it is not surprising to find a limited number of patient samples in each study, and very few common identified marker genes among different studies involving patients with the same disease. Therefore, it is of great interest and challenge to merge data sets from multiple studies to increase the sample size, which may in turn increase the power of statistical inferences. In this study, we combined two lung cancer studies using microarray GeneChip, employed two gene shaving methods and a two-step survival test to identify genes with expression patterns that can distinguish diseased from normal samples, and to indicate patient survival, respectively. RESULTS: In addition to common data transformation and normalization procedures, we applied a distribution transformation method to integrate the two data sets. Gene shaving (GS) methods based on Random Forests (RF) and Fisher's Linear Discrimination (FLD) were then applied separately to the joint data set for cancer gene selection. The two methods discovered 13 and 10 marker genes (5 in common), respectively, with expression patterns differentiating diseased from normal samples. Among these marker genes, 8 and 7 were found to be cancer-related in other published reports. Furthermore, based on these marker genes, the classifiers we built from one data set predicted the other data set with more than 98% accuracy. Using the univariate Cox proportional hazard regression model, the expression patterns of 36 genes were found to be significantly correlated with patient survival (p < 0.05). Twenty-six of these 36 genes were reported as survival-related genes from the literature, including 7 known tumor-suppressor genes and 9 oncogenes. Additional principal component regression analysis further reduced the gene list from 36 to 16. CONCLUSION: This study provided a valuable method of integrating microarray data sets with different origins, and new methods of selecting a minimum number of marker genes to aid in cancer diagnosis. After careful data integration, the classification method developed from one data set can be applied to the other with high prediction accuracy.