The representative images of selected peptide-fluorescent bacteria binding with tissue sections from the mice xenograft.

<p>The scale bar was 20 µm. Data were representative of at least three independent experiments.</p

Sequences of peptides.

<p>Sequences and binding rates of different peptides with A549 cells. Peptides were ordered by frequency in experiments.</p

Characterization of binding ability of fixed bacteria.

<p>(<b>A</b>) Percentage of binding fraction of fresh and fixed monoclonal peptide-fluorescent bacteria with various cells from FACS data. Cells binding to fresh bacteria (black) at ratio 1∶100 and binding to fixed bacteria (gray) at ratio 1∶500. (<b>B</b>) The fluorescence microscope images of A549 cells incubating with fresh bacteria and fixed bacteria at ratio 1∶500, at day 1, day 7 and day 30 after fixation and the scale bar was 20 µm. (<b>C</b>) FACS results of A549 cells binding with fresh and fixed monoclonal peptide-fluorescent bacteria at ratio 1∶500 at different time points. (<b>D</b>) Percentage of binding fraction of fresh and fixed monoclonal peptide-fluorescent bacteria with A549 cells from FACS data Cells binding with fresh bacteria and fixed bacteria at ratio 1∶500 at different time points. Data were mean ± S.D. of at least three independent experiments.</p

The process of screening and enriching the binding peptide library for cancer cells with bacteria surface display methods.

<p>(<b>A</b>) Schematic representation of peptides screening and selection with bacterial display library. 1. Constructed the library by transforming plasmids into <i>E.coli</i> MC1061; 2. Discarded the bacteria binding with normal cells after pre-incubation; 3. Incubated the mixture of cancer cells and residual bacteria; 4. Analyzed the binding effect of cancer cells with bacteria using FACS; 5. Sorted the binding bacteria to cancer cells by flow cytometry and cultured the binding bacteria in medium; 6. Performed the next round binding bacteria screening; 7. Isolated the binding bacteria to cancer cells and sequenced the peptides displayed on the surface of the bacteria. (<b>B</b>) The progress of enrichment of bacteria binding with cancer cells by FACS in 6 screening rounds.</p

The results of selected monoclonal peptide-fluorescent bacteria specifically binding with various cells.

<p>(<b>A</b>) Fluorescence microscope images of bacteria clones incubated with cells. A549<b>^△</b> was incubated with CPX only bacteria and other cells were incubated with selected monoclonal peptide-fluorescent bacteria, the scale bar was 20 µm. (<b>B</b>) FACS results of various cells binding with monoclonal peptide-fluorescent bacteria at ratio 1∶100. (<b>C</b>) Percentage of binding fraction of monoclonal peptide-fluorescent bacteria with various cells from FACS data. Data were mean ± S.D. of at least three independent experiments.</p

Additional file 16: Table S10. of Bile acid is a significant host factor shaping the gut microbiome of diet-induced obese mice

Feed ingredients. (XLSX 10 kb

Prodrug AST-003 Improves the Therapeutic Index of the Multi-Targeted Tyrosine Kinase Inhibitor Sunitinib

<div><p>Patients have responded well to the multi-targeted tyrosine kinase inhibitor (TKI) Sunitinib in the clinic. But the severe toxic side effects associated with Sunitinib limit its therapeutic index. To improve the therapeutic index of Sunitinib, a prodrug strategy was employed to modify Sunitinib. The inactive prodrug AST-003 can be converted to Sunitinib <i>in vitro</i> and <i>in vivo</i>. Compared with Sunitinib, AST-003 has unique biochemical, cellular and pharmacokinetic properties with improved tolerability in mice and yield higher efficacy in tumor xenograft models. This prodrug strategy may constitute a novel paradigm to improve the therapeutic index of Sunitinib and other TKI or anti-angiogenesis drugs in general.</p></div

Additional file 8: Figure S3. of Bile acid is a significant host factor shaping the gut microbiome of diet-induced obese mice

A linear discriminant analysis effect size cladogram representing the significantly different taxa in a tree-like structure. (DOC 249 kb

AST-003 more effectively inhibits tumors than Sunitinib.

<p>Mice transplanted with A549 cells were treated <i>i</i>.<i>p</i>. with AST-003 (circle), Sunitinib (square) or vehicle (triangle) at doses of 1.5 mg/kg <b>(a)</b>, 7.5 mg/kg <b>(b)</b>, and 30 mg/kg <b>(c)</b> (* AST-003 <i>vs</i>. Sunitinib, p<0.05). In a separate experiment, these drugs were orally administered at doses of 5 mg/kg <b>(d)</b>, 15 mg/kg <b>(e)</b>, and 45 mg/kg <b>(f)</b> (* AST-003 <i>vs</i>. Sunitinib, p<0.05). <b>(g)</b> The concentrations of Sunitinib in different tissues were measured after two weeks of compound treatment. All data are the means of replicates from 5 mice, with error bars representing the standard deviation. <b>(h)</b> Mice with established A549 xenografts were orally treated with at 15 mg/kg Sunitinib, AST-003, or vehicle once daily for two days. Tumor samples were retrieved and fixed using the Zinc method. CD31 staining was then performed. Representative figures from 6 independent fields are shown here.</p