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1,3-1,4-beta-D-glucanase is an important endoglycosidase in the brewing and animal feed industries. To achieve high-level expression of recombinant glucanase in Pichia pastoris, we designed sequences encoding the alpha-factor signal peptide from Saccharomyces cerevisiae and the truncated 1,3-1,4-beta-D-glucanase from Fibrobacter succinogenes as a whole. The codons encoding the 52 amino acids of the signal peptide and 106 residues of the glucanase protein were optimized for expression in P. pastoris; 189 nucleotides were changed. The G + C content was adjusted to 48-49%, and AT-rich stretches were eliminated to avoid premature termination. The messenger ribonucleic acid secondary structure near the AUG start codon was also adjusted to ensure efficient translation; the resulting glucanase production was twofold higher compared with that achieved with gene structure optimization alone. We also propose a new fermentation strategy for the induction phase, in which 5/95% glycerol/methanol mixed feed was used in days 1-3 and 100% methanol was used on days 4-6. By comparison with methanol feed and glycerol/methanol-mixed feed alone, the yield of recombinant glucanase increased by 38.5 and 16.5%, respectively. The expressed optimized recombinant 1,3-1,4-beta-D-glucanase constituted approximately 90% of the total secreted protein, reaching up to 3 g l(-1) in the medium.

A genomic DNA library screen yielded the nucleotide sequence of a 12 kb fragment containing a gene (2067 bp) coding a thermostable beta-galactosidase from Alicyclobacillus acidocaldarius ATCC 27009. The beta-galactosidase gene was expressed in Pichia pastoris, and up to 90 mg recombinant beta-galactosidase/l accumulated in shake flask cultures. Using o-nitrophenyl-beta-D: -galactopyranoside as a substrate, the optimum pH and temperature of the purified recombinant beta-galactosidase were 5.8-6.0 and 70 degrees C, respectively. The enzyme retained 90% of its activity when heated at 70 degrees C for 30 min. Approximately 48% of lactose in milk was hydrolyzed following treatment with the recombinant enzyme over 60 min at 65 degrees C.

Androgen deprivation therapy (ADT) for hormone-sensitive prostate cancer (HSPC) and chemotherapy for castration-resistant prostate cancer (CRPC) are considered standard of care. However, there are no clinical tests or factors that can reliably predict treatment responses for the advanced prostate cancer patients. Examination of tumor component in circulation, also known as liquid biopsy, has shown promise for predicting treatment outcomes and survival. To capture the tumor-derived genomic alterations and decrease the surrogacy of using PSA measurements as is currently performed, we propose a Plasma Genomic Abnormality (PGA) score and Treatment Efficacy (TEff) index based on copy number variations as estimated by cell free DNA (cfDNA) in plasma. We first performed whole genome and targeted sequencing (NimbleGen comprehensive cancer panel) to examine plasma cfDNA for tumor-associated genetic and genomic aberrations in 10 HSPC patients receiving ADT and 10 CRPC patients receiving chemotherapy. For each patient, we tested plasma from two time points: pre-treatment and 4 months post-treatment. We then calculated the PGA score by summing the most significant genomic abnormalities with higher PGA score indicating greater tumor DNA content in cfDNA. TEff index was derived from comparison of PGA score difference between treatments with higher TEff index reflecting a better treatment response. The sequencing-based copy number analysis revealed locus-specific gains or losses including those previously reported in prostate cancers, such as 8q gains, AR amplifications, PTEN losses and TMPRSS2-ERG fusions. We found that overall PGA score was significantly higher in CRPC patients than in HSPC patients (p Citation Format: Liang Wang, Shu Xia, Meijun Du, Rachel Ditmar, Tiezheng Yuan, Yongchen Guo, Yuan Wang, Adam Lee, Michael Tschannen, Elizabeth Worthey, Howard Jacobs, Chiang-Ching Huang, Manish Kohli. Plasma genetic and genomic abnormalities predict treatment response and clinical outcome in advanced prostate cancer. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 5231. doi:10.1158/1538-7445.AM2015-5231

A novel phytase gene appA, with upstream and downstream sequences from Citrobacter amalonaticus CGMCC 1696, was cloned by degenerate polymerase chain reaction (PCR), and thermal asymmetric interlaced (TAIL) PCR and was overexpressed in Pichia pastoris. Sequence analysis revealed one open reading frame that consisted of 1311 bp encoding a 436-amino-acid protein, which had a deduced molecular mass of 46.3 kDa. The phytase appA belongs to the histidine acid phosphatase family and exhibits the highest identity (70.1%) with C. braakii phytase. The gene was overexpressed in P. pastoris. The secretion yield of recombinant appA protein was accumulated to approximately 4.2 mg.mL(-1), and the enzyme activity level reached 15,000 U x mL(-1), which is higher than any previous reports. r-appA was glycosylated, as shown by Endo H treatment. r-appA was purified and characterized. The specific activity of r-appA for sodium phytate was 3548 U.mg(-1). The optimum pH and temperature for enzyme activity were 4.5 and 55 degrees C, respectively. r-appA was highly resistant to pepsin or trypsin treatment. This enzyme could be an economic and efficient alternative to the phytases currently used in the feed industry.

PURPOSE: Cell free circulating microvesicles (in particular, exosomes) contain proteins and nuclei acids that may serve as biomarkers for disease diagnosis and prognosis. The goal of this study was to identify exosomal microRNAs that may predict clinical outcome of patients with castrate resistant prostate cancer (CRPC). EXPERIMENTAL DESIGN: In discovery stage, we performed RNA sequencing using plasma exosomal RNAs derived from 36 patients with CRPC. We mapped the sequence reads to known miRbase (Release 19, 2043 entries) and normalized the miRNA abundance by sequence counts per million mappable reads. We applied Cox regression analysis to identify the miRNAs that were associated with overall survival of CRPC. In validation stage, we first examined an exosomal small RNA sequencing dataset consisting of 192 individuals with various health conditions. We used Normfinder and Bestkeeper to select most stably expressed miRNAs as candidates for normalization references. We then applied real-time qRT-PCR assays to test selected candidate reference miRNAs and survival-related miRNAs in additional 100 CRPC patients. From validated miRNAs, we constructed multivariate models to predict overall survival for this group of patients. RESULTS RNA sequencing generated over 6 million mappable reads per patient in the initial discovery cohort. Among these reads, ∼45% were mapped to known miRNAs for a total of 483 known and 275 novel miRNAs with normalized read counts ≥ 5. The median follow-up time for the 36 CRPC patients was 35.6 months during which 10 patients had died. Cox regression analysis identified four microRNAs (miR-1290, -1246, -375 and a predicted miRNA at chromosome 12) that were associated with overall survival (FDR CONCLUSIONS: Plasma exosomal miRNAs provide an easily accessible resource for biomarker development in prognosis of advanced prostate cancer. Exosomal miR-1290 and miR-375 are associated with overall survival in CRPC patients. miR-30a/e-5p, especially the geometric mean of miR-30a/e-5p, are qualified endogenous references for real-time qPCR. Further confirmation of these findings is needed for prognostic and predictive biomarker in development of CRPC stage. Citation Format: Xiaoyi Huang, Tiezheng Yuan, Meihua Liang, Meijun Du, Shu Xia, Rachel Louise Dittmar, Zhifu Sun, Yan Lu, Stephen N. Thibodeau, Lisa Boardman, Manish Kohli, Liang Wang. Exosomal miR-1290 and miR-375 as prognostic markers in metastatic castrate resistant prostate cancer. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 574. doi:10.1158/1538-7445.AM2014-574

260 Background: The purpose of this study was to evaluate cell free nucleic acid based biomarkers for prognosis in mCRPC stage. Methods: Uniformly collected blood from mCRPC patients was processed for plasma which was used for exosomal RNA extraction. RNA sequencing was applied to examine microRNA (miRNA) profiles initially in a discovery cohort of 23 mCRPC patients. The sequences from fastq files were mapped to human miRBase (release 19) for known miRNA read counts. A software package (miRDeep2) was used for novel miRNA prediction. Cox regression was used for association of candidate miRNAs with overall survival (OS), defined as time from development of mCRPC to death or last follow up after adjusting for Gleason Score (GS) and time on androgen deprivation (AD) for hormone sensitive disease. miRNAs significantly associated with OS (FDR10 million mappable reads per specimen in the discovery cohort. Among these reads ~50% were known miRNAs which included 1237 unique RNA sequences. Due to low abundance of most RNA transcripts, only miRNAs (n=250) with >/= 32 reads (on average) were analyzed. Four mRNAs (miR-1290, -1246, -375 and a predicted miRNA on chr. 12) were associated with OS(FDR

Background Exosomes, endosome-derived membrane microvesicles, contain specific RNA transcripts that are thought to be involved in cell-cell communication. These RNA transcripts have great potential as disease biomarkers. To characterize exosomal RNA profiles systemically, we performed RNA sequencing analysis using three human plasma samples and evaluated the efficacies of small RNA library preparation protocols from three manufacturers. In all we evaluated 14 libraries (7 replicates). Results From the 14 size-selected sequencing libraries, we obtained a total of 101.8 million raw single-end reads, an average of about 7.27 million reads per library. Sequence analysis showed that there was a diverse collection of the exosomal RNA species among which microRNAs (miRNAs) were the most abundant, making up over 42.32% of all raw reads and 76.20% of all mappable reads. At the current read depth, 593 miRNAs were detectable. The five most common miRNAs (miR-99a-5p, miR-128, miR-124-3p, miR-22-3p, and miR-99b-5p) collectively accounted for 48.99% of all mappable miRNA sequences. MiRNA target gene enrichment analysis suggested that the highly abundant miRNAs may play an important role in biological functions such as protein phosphorylation, RNA splicing, chromosomal abnormality, and angiogenesis. From the unknown RNA sequences, we predicted 185 potential miRNA candidates. Furthermore, we detected significant fractions of other RNA species including ribosomal RNA (9.16% of all mappable counts), long non-coding RNA (3.36%), piwi-interacting RNA (1.31%), transfer RNA (1.24%), small nuclear RNA (0.18%), and small nucleolar RNA (0.01%); fragments of coding sequence (1.36%), 5′ untranslated region (0.21%), and 3′ untranslated region (0.54%) were also present. In addition to the RNA composition of the libraries, we found that the three tested commercial kits generated a sufficient number of DNA fragments for sequencing but each had significant bias toward capturing specific RNAs. Conclusions This study demonstrated that a wide variety of RNA species are embedded in the circulating vesicles. To our knowledge, this is the first report that applied deep sequencing to discover and characterize profiles of plasma-derived exosomal RNAs. Further characterization of these extracellular RNAs in diverse human populations will provide reference profiles and open new doors for the development of blood-based biomarkers for human diseases.

RNA sequencing (RNA-seq) is emerging as a critical approach in biological research. However, its high-throughput advantage is significantly limited by the capacity of bioinformatics tools. The research community urgently needs user-friendly tools to efficiently analyze the complicated data generated by high throughput sequencers. We developed a standalone tool with graphic user interface (GUI)-based analytic modules, known as eRNA. The capacity of performing parallel processing and sample management facilitates large data analyses by maximizing hardware usage and freeing users from tediously handling sequencing data. The module miRNA identification” includes GUIs for raw data reading, adapter removal, sequence alignment, and read counting. The module “mRNA identification” includes GUIs for reference sequences, genome mapping, transcript assembling, and differential expression. The module “Target screening” provides expression profiling analyses and graphic visualization. The module “Self-testing” offers the directory setups, sample management, and a check for third-party package dependency. Integration of other GUIs including Bowtie, miRDeep2, and miRspring extend the program’s functionality. eRNA focuses on the common tools required for the mapping and quantification analysis of miRNA-seq and mRNA-seq data. The software package provides an additional choice for scientists who require a user-friendly computing environment and high-throughput capacity for large data analysis. eRNA is available for free download at https://sourceforge.net/projects/erna/?source=directory .