9 research outputs found
Additional file 1 of Improved consolidated bioprocessing for itaconic acid production by simultaneous optimization of cellulase and metabolic pathway of Neurospora crassa
Additional file 1: Figure S1. Main plasmids used in this study. (A) Plasmids pMF-272-Pccg1/Peas/Pcbh1/Pgh6-2/Pgh11-2/Ptef1/Pgpd/Ppda-CAD were used to compare the expression of CAD in N. crassa. (B) Plasmids pMF-272-Pccg1-CBH1/GH6-2/GH5-1/GH3-4/AsBGA/TrCBH2 were used to compare the effects of different cellulases. (C) Plasmids pMF-272-Pccg1-CAD-Pcbh1-CBH1/GH6-2/GH5-1/GH3-4/AsBGA/TrCBH2 were used to compare the effects of different cellulase and CAD co-expression. (D) Plasmid pMF-272-Pccg1-MTK was used to verify the expression of MTK in N. crassa. The plasmids pUC19-MTK-HPH (F) and pMF-272-Pccg1-CAD-Pes-MCL (E) or pMF-272-Pccg1-CAD-Pcbh1-MTTA-Pes-MCL (G) were used to construct N. crassa PMF-CAD-rGS or N. crassa PMF-CAD-MTTA-rGS. (H) Plasmid pMF-272-Pccg1-CAD-Pcbh1-MTTA-Pcbh1-TrCBH2 was used to construct N. crassa PMF-CAD-MTTA-TrCBH2. Figure S2. PCR amplified the promoter sequence. Figure S3. Strain construction process using Pcbh1 as the CAD promoter. (A) Pcbh1 promoter sequence was amplified by PCR. M:Trans2K Plus DNA Marker, 1–6:Pcbh1 (B) PCR identification of vector Blunt-Pcbh1. 1–22: Blunt-Pcbh1 (C) Identification of recombinant plasmid pMF272-CAD. 1–6: pMF272-CAD. (D) Double enzyme digestion of pMF272-CAD recombinant plasmid. (E) Cloning vector Blunt-Pcbh1 double enzyme digestion. (F) Colony PCR identification of recombinant plasmid pMF-CAD-Pcbh1. Figure S4. Construction of cellulase overexpression strain. (A) PCR amplification of Pcbh-1 promoter sequence (1 and 2), gh3-4 sequence (4), and cbh1 sequence (B, 1 and 2). (C) Identification of expression vector containing cbh1 gene. (D) PCR screening of gh3-4 gene expression vectors. (E) Genome PCR for vector transformation screening 1,2,3: cbh1; 4,5: gh3-4. Figure S5. Construction of MTK, MCL expression strain. (A) PCR amplification of MTK (lines 1 ~ 3). (B) Colony PCR for identification of MTK expression cassette (C) PCR amplification of GFP (1) and terminator fragments (2). Identification of expression vector containing cbh1 gene. Genome PCR for MTK expression (D) and MCL expression (E) vector transformation screening. Figure S6. Construction of CAD, MTK and MCL co-expression strain. (A) PCR amplification of 5′ fragment (lines 1 ~ 3). (B) PCR amplification of 3′ fragment (lines 1 ~ 3) and hph fragment (lines 4 and 5). (C) PCR amplification of MTK cassette. (D) Identification of expression vector containing 5′ fragment and hph fragment. Table S1. Plasmids used in this study. Table S2. Strains used in this study. Table S3. Primer list of CAD expression and promoter optimization. Table S4. Primer list of cellulase expression. Table S5. Primer list of CAD and cellulase co-expression. Table S6. Primer list of MTK, MCL and MTTA expression. Table S7. RT-PCR Primers
Table_1_Genome-wide association study of coleoptile length with Shanxi wheat.XLSX
In arid and semi-arid regions, coleoptile length is a vital agronomic trait for wheat breeding. The coleoptile length determines the maximum depth that seeds can be sown, and it is critical for establishment of the crop. Therefore, identifying loci associated with coleoptile length in wheat is essential. In the present study, 282 accessions from Shanxi Province representing wheat breeding for the Loess Plateau were grown under three experimental conditions to study coleoptile length. The results of phenotypic variation indicated that drought stress and light stress could lead to shortening of coleoptile length. Under drought stress the growth rate of environmentally sensitive cultivars decreased more than insensitive cultivars. The broad-sense heritability (H2) of BLUP (best linear unbiased prediction) under various conditions showed G × E interaction for coleoptile length but was mainly influenced by heredity. Correlation analysis showed that correlation between plant height-related traits and coleoptile length was significant in modern cultivars whereas it was not significant in landraces. A total of 45 significant marker-trait associations (MTAs) for coleoptile length in the three conditions were identified using the 3VmrMLM (3 Variance-component multi-locus random-SNP-effect Mixed Linear Model) and MLM (mixed linear model). In total, nine stable genetic loci were identified via 3VmrMLM under the three conditions, explaining 2.94–7.79% of phenotypic variation. Five loci on chromosome 2B, 3A, 3B, and 5B have not been reported previously. Six loci had additive effects toward increasing coleoptile length, three of which are novel. Molecular markers for the loci with additive effects on coleoptile length can be used to breed cultivars with long coleoptiles.</p
Data_Sheet_1_Genome-wide association study of coleoptile length with Shanxi wheat.docx
In arid and semi-arid regions, coleoptile length is a vital agronomic trait for wheat breeding. The coleoptile length determines the maximum depth that seeds can be sown, and it is critical for establishment of the crop. Therefore, identifying loci associated with coleoptile length in wheat is essential. In the present study, 282 accessions from Shanxi Province representing wheat breeding for the Loess Plateau were grown under three experimental conditions to study coleoptile length. The results of phenotypic variation indicated that drought stress and light stress could lead to shortening of coleoptile length. Under drought stress the growth rate of environmentally sensitive cultivars decreased more than insensitive cultivars. The broad-sense heritability (H2) of BLUP (best linear unbiased prediction) under various conditions showed G × E interaction for coleoptile length but was mainly influenced by heredity. Correlation analysis showed that correlation between plant height-related traits and coleoptile length was significant in modern cultivars whereas it was not significant in landraces. A total of 45 significant marker-trait associations (MTAs) for coleoptile length in the three conditions were identified using the 3VmrMLM (3 Variance-component multi-locus random-SNP-effect Mixed Linear Model) and MLM (mixed linear model). In total, nine stable genetic loci were identified via 3VmrMLM under the three conditions, explaining 2.94–7.79% of phenotypic variation. Five loci on chromosome 2B, 3A, 3B, and 5B have not been reported previously. Six loci had additive effects toward increasing coleoptile length, three of which are novel. Molecular markers for the loci with additive effects on coleoptile length can be used to breed cultivars with long coleoptiles.</p
Metformin treatment suppresses macrophage proinflammatory activation.
<p>Bone marrow-derived macrophages were treated with metformin (500 µM) or PBS for 24 hr in the presence or absence of LPS (100 ng/ml) for the last 30 min (A) or 6 hr (B). (A) Macrophage inflammatory signaling was examined using Western blot analyses. (B) Macrophage mRNA levels of proinflammatory cytokines were quantified using real-time PCR. For bar graphs (A and B), data are means ± SE, n = 4–6. <sup>††</sup>, <i>P</i><0.01 LPS vs. PBS (without LPS) in the absence of metformin (A); **, <i>P</i><0.01 Met vs. PBS (without metformin) in the presence of LPS (A) or Met + LPS vs. PBS + LPS (B).</p
Metformin treatment ameliorates HFD-induced insulin resistance and glucose intolerance.
<p>Male C57BL/6J mice, at 5–6 weeks of age, were fed a high-fat diet (HFD) and treated with metformin (Met, 150 mg/kg body weight/d, in phosphate-buffered saline (PBS)) or PBS for the last 4 weeks of HFD feeding. As an additional control, gender- and age-matched mice were fed a low-fat diet (LFD) for 12 weeks and treated only with PBS for the last 4 weeks. Data are means ± SE, n = 6–10. (A) Body weight was monitored weekly during the feeding/treatment regimen. (B) Food intake was calculated based on food consumption per day per mouse. (C) Insulin tolerance tests (ITT). (D) Glucose tolerance tests (GTT). For C and D, mice were fasted for 4 hr and received an intraperitoneal injection of insulin (1 U/kg body weight) (C) or glucose (2 g/kg body weight) (D). *, <i>P</i><0.05 and **, <i>P</i><0.01 HFD-Met vs. HFD-PBS for the same time point (C and D).</p
Metformin treatment ameliorates HFD-induced hepatic steatosis and increases liver AMPK phosphorylation.
<p>Mice were treated as described in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0091111#pone-0091111-g001" target="_blank">Figure 1</a>. After the feeding/treatment regimen, mice were fasted for 4 hr prior to collection of tissue samples. (A) Liver weight (n = 6–10). (B) Liver histology. Top panels, H&E staining; bottom panels, Oil-Red-O staining. (C) Liver AMPK signaling. Liver extracts were subjected to Western blot analyses. Ratios of phosphorylated AMPK to total AMPK (P-AMPK/AMPK) and phosphorylated ACC to total ACC (P-ACC/ACC) were quantified using densitometry and normalized to GAPDH (AU, arbitrary unit). (D) Liver mRNA levels of key lipid metabolic enzymes (genes) were analyzed using real-time PCR. For bar graphs (A, C, and D), data are means ± SE, n = 6–8. <sup>†</sup>, <i>P</i><0.05 and <sup>††</sup>, <i>P</i><0.01 HFD-PBS or HFD-Met vs. LFD-PBS (A, C, and D); *, <i>P</i><0.05 and **, <i>P</i><0.01 HFD-Met vs. HFD-PBS (A, C, and D).</p
Metformin treatment blunts hepatocyte fat deposition, increases AMPK phosphorylation, and decreases inflammatory responses.
<p>(A) Hepatocyte fat deposition. Bottom panels, cells were incubated with palmitate (Pal). (B) Hepatocyte mRNA levels were quantified using real-time PCR. For A and B, H4IIE cells were treated with metformin (500 µM) or PBS in the presence of palmitate (250 µM) or bovine serum albumin (BSA) for 24 hr (B) and stained with Oil-Red-O for the last 1 hr (A). (C) Hepatocyte AMPK signaling and inflammatory signaling were examined using Western blot analyses. H4IIE cells were treated with metformin (500 µM) or PBS for 24 hr in the presence or absence of LPS (100 ng/ml) for the last 30 min. For bar graphs (B and C), data are means ± SE, n = 6–8. <sup>†</sup>, <i>P</i><0.05 and <sup>††</sup>, <i>P</i><0.01 Pal + PBS vs. BSA + PBS (B) or LPS vs. PBS (without LPS) under the same condition (with or without Met) (C); *, <i>P</i><0.05 and **, <i>P</i><0.01 Pal + Met vs. Pal + PBS (B) or Met vs. PBS (without Met) under the same condition (with or without LPS) (C).</p
Metformin treatment ameliorates HFD-induced liver inflammatory responses.
<p>Mice were treated as described in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0091111#pone-0091111-g001" target="_blank">Figure 1</a>. After the feeding/treatment regimen, mice were fasted for 4 hr prior to collection of tissue samples. (A) Liver sections were stained for F4/80<sup>+</sup> cells. (B) Liver inflammatory signaling. Liver extracts were subjected to Western blot analyses. Ratios of phosphorylated JNK1 to total JNK1 (Pp46/p46) and phosphorylated NF-κB p65 to total p65 (Pp65/p65) were quantified using densitometry and normalized to GAPDH. (C) Liver mRNA levels of proinflammatory cytokines were analyzed using real-time PCR. For bar graphs (B and C), data are means ± SE, n = 6–8. <sup>†</sup>, <i>P</i><0.05 and <sup>††</sup>, <i>P</i><0.01 HFD-PBS vs. LFD-PBS; *, <i>P</i><0.05 and **, <i>P</i><0.01 HFD-Met vs. HFD-PBS.</p
Metformin treatment does not alter HFD-induced adiposity and adipose tissue inflammation.
<p>Mice were treated as described in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0091111#pone-0091111-g001" target="_blank">Figure 1</a>. After the feeding/treatment regimen, mice were fasted for 4 hr prior to collection of tissue samples. (A) Adipose tissue histology (H&E staining). (B) Adipose tissue sections were stained for F4/80<sup>+</sup> cells. (C) Adipose tissue macrophage infiltration. Percentages of mature macrophages (F4/80<sup>+</sup> CD11b<sup>+</sup> cells) in adipose tissue stromal cells were calculated using FACS analyses (n = 4–6). (D) Adipose tissue AMPK signaling and inflammatory signaling were examined using Western blot analyses (n = 4–6). (E) The mRNA levels of adipose genes were quantified using real-time PCR (n = 4–6). For bar graphs (C and E), data are means ± SE.</p