Screening of Chelidonium majus isoquinoline alkaloids reveals berberine and chelidonine as selective ligands for the nuclear receptors RORß and HNF4α, respectively.

The nuclear receptors hepatocyte nuclear factor 4α (HNF4α) and retinoic acid receptor-related orphan receptor-ß (RORß) are ligand-regulated transcription factors and potential drug targets for metabolic disorders. However, there is a lack of small molecular, selective ligands to explore the therapeutic potential in further detail. Here, we report the discovery of greater celandine (Chelidonium majus) isoquinoline alkaloids as nuclear receptor modulators: Berberine is a selective RORß inverse agonist and modulated target genes involved in the circadian clock, photoreceptor cell development, and neuronal function. The structurally related chelidonine was identified as a ligand for the constitutively active HNF4α receptor, with nanomolar potency in a cellular reporter gene assay. In human liver cancer cells naturally expressing high levels of HNF4α, chelidonine acted as an inverse agonist and downregulated genes associated with gluconeogenesis and drug metabolism. Both berberine and chelidonine are promising tool compounds to further investigate their target nuclear receptors and for drug discovery.

Multichannel Microfluidic Platform for Temporal-Spatial Investigation of Niche Roles of Pseudomonas aeruginosa and Escherichia coli within a Dual-Species Biofilm.

In natural or man-made environments, microorganisms exist predominantly as biofilms forming surface-associated bacterial communities embedded in extracellular polymeric substances (EPSs). Often, biofilm reactors used for endpoint and disruptive analyses of biofilm are not suitable for periodic observation of biofilm formation and development. In this study, a microfluidic device designed with multiple channels and a gradient generator was used for high-throughput analysis and real-time monitoring of dual-species biofilm formation and development. We compared the structural parameters of monospecies and dual-species biofilms containing Pseudomonas aeruginosa (expressing mCherry) and Escherichia coli (expressing green fluorescent protein [GFP]) to understand the interactions in the biofilm. The rate of biovolume increase of each species in monospecies biofilm (2.7 × 105 µm3) was higher than those in a dual-species biofilm (9.68 × 104 µm3); however, synergism was still observed in the dual-species biofilm due to overall increases in biovolume for both species. Synergism was also observed in a dual-species biofilm, where P. aeruginosa forms a "blanket" over E. coli, providing a physical barrier against shear stress in the environment. The microfluidic chip was useful for monitoring the dual-species biofilm in the microenvironment, indicating that different species in a multispecies biofilm exhibit different niches for the survival of the biofilm community. Finally, we demonstrated that the nucleic acids can be extracted from the dual-species biofilm in situ after biofilm imaging analysis. In addition, gene expression supported that the activation and suppression of different quorum sensing genes resulted in the different phenotype seen in the biofilm. This study showed that the integration of microfluidic device with microscopy analysis and molecular techniques could be a promising tool for studying biofilm structure and gene quantification and expression simultaneously. IMPORTANCE In natural or man-made environments, microorganisms exist predominantly as biofilms forming surface-associated bacterial communities embedded in extracellular polymeric substances (EPSs). Often, biofilm reactors used for endpoint and disruptive analyses of biofilm are not suitable for periodic observation of biofilm formation and development. Here, we demonstrate that a microfluidic device with multiple channels and a gradient generator can be useful for high-throughput analysis and real-time monitoring of dual-species biofilm formation and development. Our study revealed synergism in the dual-species biofilm, where P. aeruginosa forms a "blanket" over E. coli, providing a physical barrier against shear stress in the environment. Furthermore, different species in a multispecies biofilm exhibit different niches for the survival of the biofilm community. This study showed that the integration of microfluidic device with microscopy analysis and molecular techniques could be a promising tool for studying biofilm structure and gene quantification and expression simultaneously.

A Quantitative Metagenomic Sequencing Approach for High-Throughput Gene Quantification and Demonstration with Antibiotic Resistance Genes.

Comprehensive microbial risk assessment requires high-throughput quantification of diverse microbial risks in the environment. Current metagenomic next-generation sequencing approaches can achieve high-throughput detection of genes indicative of microbial risks but lack quantitative capabilities. This study developed and tested a quantitative metagenomic next-generation sequencing (qmNGS) approach. Numerous xenobiotic synthetic internal DNA standards were used to determine the sequencing yield (Yseq) of the qmNGS approach, which can then be used to calculate absolute concentration of target genes in environmental samples based on metagenomic sequencing results. The qmNGS approach exhibited excellent linearity as indicated by a strong linear correlation (r2 = 0.98) between spiked and detected concentrations of internal standards. High-throughput capability of the qmNGS approach was demonstrated with artificial Escherichia coli mixtures and cattle manure samples, for which 95 ± 3 and 208 ± 4 types of antibiotic resistance genes (ARGs) were detected and quantified simultaneously. The qmNGS approach was further compared with quantitative real-time PCR (qPCR) and demonstrated comparable levels of accuracy and less variation for the quantification of six target genes (16S, tetO, sulI, tetM, ermB, and qnrS). IMPORTANCE Monitoring and comprehensive assessment of microbial risks in the environment require high-throughput gene quantification. The quantitative metagenomic NGS (qmNGS) approach developed in this study incorporated numerous xenobiotic and synthetic DNA internal standard fragments into metagenomic NGS workflow, which are used to determine a new parameter called sequencing yield that relates sequence base reads to absolute concentration of target genes in the environmental samples. The qmNGS approach demonstrated excellent method linearity and comparable performance as the qPCR approach with high-throughput capability. This new qmNGS approach can achieve high-throughput and accurate gene quantification in environmental samples and has the potential to become a useful tool in monitoring and comprehensively assessing microbial risks in the environment.

Savitzky-Golay smoothing and differentiation for polymerase chain reaction quantification.

In quantitative PCR (qPCR), replicates can minimize the impact of intra-assay variation; however, inter-assay variations must be minimized to obtain a robust quantification method. The method proposed in this study uses Savitzky-Golay smoothing and differentiation (SGSD) to identify a derivative-maximum-based cycle of quantification. It does not rely on curve modeling, as is the case with many existing techniques. PCR fluorescence data sets challenged for inter-assay variations (different thermocycler units, different reagents batches, different operators, different standard curves, and different labs) were used for the evaluation. The algorithm was compared with a four-parameter logistic model (4PLM) method, the Cy0 method, and the threshold method. The SGSD method compared favourably with all methods in terms of inter-assay variation. SGSD was statistically different from the 4PLM (P = 0.03), Cy0 (P = 0.05), and threshold (P = 0.004) methods on relative error comparison basis. For intra-assay variations, SGSD outperformed the threshold method (P = 0.005) and equalled the 4PLM and Cy0 methods (P > 0.05) on relative error basis. Our results demonstrate that the SGSD method could potentially be an alternative to sigmoid modeling based methods (4PLM and Cy0) when PCR data are challenged for inter-assay variations.

The effect of kinetic heat shock on bovine oocyte maturation and subsequent gene expression of targeted genes.

The exposure of oocytes to heat stress during the maturation process results in harmful effects to their internal organelles, low fertilization capability and higher embryonic losses. In the present experiment the effect of heat shock (HS) during the maturation process was assessed. In Assay 1, oocytes from winter (December-March; n = 100) and summer (June-September; n = 100) months were collected and matured to analyse their HS tolerance. Total RNA was extracted from matured oocytes and cDNA synthesis was performed, followed by qPCR for selected genes (Cx43, CDH1, DNMT1, HSPA14), compared with two reference genes (GAPDH and SDHA). In Assay 2, oocytes collected during the winter were subjected to kinetic HS by stressing them at 39.5°C for 6, 12, 18 or 24 h and were afterwards matured at control temperature (38.5°C), and subsequently subjected to the previously described gene analysis procedure. Results of Assay 1 show that summer-collected oocytes exhibited lower maturation rate than winter-collected oocytes, which may be due to the down-regulation of the HSPA 14 gene. Assay 2 showed that 6 h of HS had no effect on gene regulation. CDH1 and DNMT1 up-regulation was observed starting at 12 h, which may represent the effect of heat shock on oocyte development.

Rapid detection of pathological mutations and deletions of the haemoglobin beta gene (HBB) by High Resolution Melting (HRM) analysis and Gene Ratio Analysis Copy Enumeration PCR (GRACE-PCR).

OBJECTIVES: Inherited disorders of haemoglobin are the world's most common genetic diseases, resulting in significant morbidity and mortality. The large number of mutations associated with the haemoglobin beta gene (HBB) makes gene scanning by High Resolution Melting (HRM) PCR an attractive diagnostic approach. However, existing HRM-PCR assays are not able to detect all common point mutations and have only a very limited ability to detect larger gene rearrangements. The aim of the current study was to develop a HBB assay, which can be used as a screening test in highly heterogeneous populations, for detection of both point mutations and larger gene rearrangements. METHODS: The assay is based on a combination of conventional HRM-PCR and a novel Gene Ratio Analysis Copy Enumeration (GRACE) PCR method. HRM-PCR was extensively optimised, which included the use of an unlabelled probe and incorporation of universal bases into primers to prevent interference from common non-pathological polymorphisms. GRACE-PCR was employed to determine HBB gene copy numbers relative to a reference gene using melt curve analysis to detect rearrangements in the HBB gene. The performance of the assay was evaluated by analysing 410 samples. RESULTS: A total of 44 distinct pathological genotypes were detected. In comparison with reference methods, the assay has a sensitivity of 100 % and a specificity of 98 %. CONCLUSION: We have developed an assay that detects both point mutations and larger rearrangements of the HBB gene. This assay is quick, sensitive, specific and cost effective making it suitable as an initial screening test that can be used for highly heterogeneous cohorts.

Gene expression, oocyte nuclear maturation and developmental competence of bovine oocytes and embryos produced after in vivo and in vitro heat shock.

Three assays were performed. In assay 1, oocytes harvested during the winter months were subjected to kinetic heat shock by stressing the oocytes at 39.5°C (HS1) or at 40.5°C (HS2) for either 6, 12, 18 or 24 h and then matured at control temperature (38.5°C). The nuclear maturation rates (NMR) of all oocytes were recorded after 24 h. In assay 2, oocytes collected year-round maturated, were implanted via in vitro fertilization (IVF) and developed for 9 days. Gene expression analysis was performed on target genes (Cx43, CDH1, DNMT1, HSPA14) with reference to the two housekeeping genes (GAPDH and SDHA) in embryos. Similarly, in assay 3, genetic analysis was performed on the embryos produced from heat-stressed oocytes (from HS1 and HS2). In assay 1, the duration of heat stress resulted in a significant decline in NMR (P < 0.05) with HS1 for maturated oocytes at 86.4 ± 4.3; 65.5 ± 0.7; 51.3 ± 0.9; 38.1 ± 1.9 and 36.3 ± 0.9, for control, 6 h, 12 h, 18 h and 24 h, respectively. For assays 2 and 3, results demonstrated that DNMT1, Cx43 and HSPA14 were down-regulated in the embryos produced in the warm with respect to the cold months (P < 0.05). A constant up- and down-regulation of DNMT1 and HSPA14 genes were observed in both HS-treated samples. Also, an inconsistent pattern of gene expression was observed in Cx43 and CDH1 genes (P < 0.05). Targeted gene expression was aberrant in embryo development, which can provide evidence on early embryo arrest and slowed embryo development.

Quantitative PCR versus metagenomics for monitoring antibiotic resistance genes: balancing high sensitivity and broad coverage.

The widespread occurrence of clinically relevant antibiotic resistance within humans, animals, and environment motivates the development of sensitive and accurate detection and quantification methods. Metagenomics and quantitative PCR (qPCR) are amongst the most used approaches. In this study, we aimed to evaluate and compare the performance of these methods to screen antibiotic resistance genes in animal faecal, wastewater, and water samples. Water and wastewater samples were from hospital effluent, different treatment stages of two treatment plants, and of the receiving river at the discharge point. The animal samples were from pig and chicken faeces. Antibiotic resistance gene coverage, sensitivity, and usefulness of the quantitative information were analyzed and discussed. While both methods were able to distinguish the resistome profiles and detect gradient stepwise mixtures of pig and chicken faeces, qPCR presented higher sensitivity for the detection of a few antibiotic resistance genes in water/wastewater. In addition, the comparison of predicted and observed antibiotic resistance gene quantifications unveiled the higher accuracy of qPCR. Metagenomics analyses, while less sensitive, provided a markedly higher coverage of antibiotic resistance genes compared to qPCR. The complementarity of both methods and the importance of selecting the best method according to the study purpose are discussed.

Endpoint Recombinase Polymerase Amplification (RPA) Assay for Enumeration of Thiocyanate-degrading Bacteria.

An endpoint recombination amplification reaction (RPA) assay for assessing the abundance of the gene encoding thiocyanate dehydrogenase (TcDH) in Thiohalobacter has been developed. The RPA reaction was performed at 37°C for 30| |min, terminated by the addition of sodium dodecyl sulfate (SDS) solution, and the DNA concentration of the RPA product was fluorometrically measured. The abundance of TcDH in 22 activated sludge samples and 7 thiocyanate-degrading enrichment cultures ranged between 2.5×103 and 1.5×106 copies µL-1, showing a linear relationship (R2=0.83) with those measured using a conventional quantitative PCR assay.

Metagenomic Quantification of Genes with Internal Standards.

We demonstrate that an assembly-independent and spike-in facilitated metagenomic quantification approach can be used to screen and quantify over 2,000 genes simultaneously, while delivering absolute gene concentrations comparable to those for quantitative PCR (qPCR). DNA extracted from dairy manure slurry, digestate, and compost was spiked with genomic DNA from a marine bacterium and sequenced using the Illumina HiSeq4000. We compared gene copy concentrations, in gene copies per mass of sample, of five antimicrobial resistance genes (ARGs) generated with (i) our quantitative metagenomic approach, (ii) targeted qPCR, and (iii) a hybrid quantification approach involving metagenomics and qPCR-based 16S rRNA gene quantification. Although qPCR achieved lower quantification limits, the metagenomic method avoided biases caused by primer specificity inherent to qPCR-based methods and was able to detect orders of magnitude more genes than is possible with qPCR assays. We used the approach to simultaneously quantify ARGs in the Comprehensive Antimicrobial Resistance Database (CARD). We observed that the total abundance of tetracycline resistance genes was consistent across different stages of manure treatment on three farms, but different samples were dominated by different tetracycline resistance gene families.IMPORTANCE qPCR and metagenomics are central molecular techniques that have offered insights into biological processes for decades, from monitoring spatial and temporal gene dynamics to tracking ARGs or pathogens. Still needed is a tool that can quantify thousands of relevant genes in a sample as gene copies per sample mass or volume. We compare a quantitative metagenomic approach with traditional qPCR approaches in the quantification of ARG targets in dairy manure samples. By leveraging the benefits of nontargeted community genomics, we demonstrate high-throughput absolute gene quantification of all known ARG sequences in environmental samples.

MetaFunPrimer: an Environment-Specific, High-Throughput Primer Design Tool for Improved Quantification of Target Genes.

Genes belonging to the same functional group may include numerous and variable gene sequences, making characterizing and quantifying difficult. Therefore, high-throughput design tools are needed to simultaneously create primers for improved quantification of target genes. We developed MetaFunPrimer, a bioinformatic pipeline, to design primers for numerous genes of interest. This tool also enables gene target prioritization based on ranking the presence of genes in user-defined references, such as environment-specific metagenomes. Given inputs of protein and nucleotide sequences for gene targets of interest and an accompanying set of reference metagenomes or genomes, MetaFunPrimer generates primers for ranked genes of interest. To demonstrate the usage and benefits of MetaFunPrimer, a total of 78 primer pairs were designed to target observed ammonia monooxygenase subunit A (amoA) genes of ammonia-oxidizing bacteria (AOB) in 1,550 publicly available soil metagenomes. We demonstrate computationally that these amoA-AOB primers can cover 94% of the amoA-AOB genes observed in the 1,550 soil metagenomes compared with a 49% estimated coverage by previously published primers. Finally, we verified the utility of these primer sets in incubation experiments that used long-term nitrogen fertilized or unfertilized soils. High-throughput quantitative PCR (qPCR) results and statistical analyses showed significant differences in relative quantification patterns between the two soils, and subsequent absolute quantifications also confirmed that target genes enumerated by six selected primer pairs were significantly more abundant in the nitrogen-fertilized soils. This new tool gives microbial ecologists a new approach to assess functional gene abundance and related microbial community dynamics quickly and affordably. IMPORTANCE Amplification-based gene characterization allows for sensitive and specific quantification of functional genes. There is often a large diversity of genes represented for functional gene groups, and multiple primers may be necessary to target associated genes. Current primer design tools are limited to designing primers for only a few genes of interest. MetaFunPrimer allows for high-throughput primer design for various genes of interest and also allows for ranking gene targets by their presence and abundance in environmental data sets. Primers designed by this tool improve the characterization and quantification of functional genes in broad gene amplification platforms and can be powerful with high-throughput qPCR approaches.

Profiling of emerging contaminants and antibiotic resistance in sewage treatment plants: An Indian perspective.

In India, sewage (partially-treated/ untreated) is randomly used for irrigation because of easy availability and presence of residual organics and nutrients. However, data on the occurrence of contaminants of emerging concerns (CECs) such as pharmaceuticals and personal care products (PPCPs) and antibiotic resistant bacteria (ARB) and antibiotic resistant genes (ARGs) in sewage is scarce in Indian perspective. Herein, for the first time, we present a quantitative contamination profiling of selected PPCPs and antibiotic resistance in untreated and biologically-treated sewage from three different sewage treatment plants, located in northern and central part of India. Profiling of PPCPs were done using LC-ESI-MS/MS whereas antibiotic resistance was analyzed using gradient PCR and qPCR techniques. PPCPs were detected both in untreated and treated samples (0.4 - 1340 µg/L). A reduction in ARB and ARG load (2-3 log) and an increase in ARG copy number with respect to beta lactams and tetracycline were observed in treated sewage. Triclosan, estrone and 17α-ethynylestradiol, ubiquitous in all samples, could be used as markers for performance monitoring of sewage treatment facilities. The results obtained in this study help evaluate health and ecological risks associated with the presence of CECs in treated sewage used for irrigation and frame future policies.

Multiplex gene quantification as digital markers for extremely rapid evaluation of chemo-drug sensitivity.

Current administrations for precision drug uses are limited in evaluation speed. Here, we propose the use of multiplex gene-based digital markers for the extremely rapid personalized prediction of individual sensitivity to cancer drugs. We first screen the transcriptional profiles by applying two to three gene filters and scoring genes by their impact on drug sensitivity and finalize the gene lists by K-nearest neighbors cross-validation. The digital markers are cancer type dependent, are composed of tens to hundreds of gene expressions, and are rapidly quantified by reverse transcription quantitative real-time PCR (qRT-PCR) within 1-3 h after tumor sampling. The area under the receiver operating characteristic curve reached 0.88 when testing the performance of digital markers on organoids derived from colorectal cancer patient tumors. The algorithm and corresponding graphic user interface were developed to demonstrate the promise of digital markers for extremely rapid drug recommendation.

scBFA: modeling detection patterns to mitigate technical noise in large-scale single-cell genomics data.

Technical variation in feature measurements, such as gene expression and locus accessibility, is a key challenge of large-scale single-cell genomic datasets. We show that this technical variation in both scRNA-seq and scATAC-seq datasets can be mitigated by analyzing feature detection patterns alone and ignoring feature quantification measurements. This result holds when datasets have low detection noise relative to quantification noise. We demonstrate state-of-the-art performance of detection pattern models using our new framework, scBFA, for both cell type identification and trajectory inference. Performance gains can also be realized in one line of R code in existing pipelines.

37Cl-compound specific isotope analysis and assessment of functional genes for monitoring monochlorobenzene (MCB) biodegradation under aerobic conditions.

A laboratory approach was adopted in this study to explore the potential of 37Cl-CSIA in combination with 13C-CSIA and Biological Molecular Tools (BMTs) to estimate the occurrence of monochloroenzene (MCB) aerobic biodegradation. A new analytical method for 37Cl-CSIA of MCB was developed in this study. This methodology using a GC-IRMS allowed to determine δ37Cl values within an internal error of ±0.3‰. Samples from a heavily MCB contaminated site were collected and MCB aerobic biodegradation microcosms with indigenous cultures in natural and enhanced conditions were set up. The microcosms data show a negligible fractionation for 13C associated to MCB mass decrease of >95% over the incubation time. Conversely, an enrichment factor of -0.6±0.1‰ was estimated for 37Cl, which is a reflection of a secondary isotope effect. Moreover, the dual isotope approach showed a pattern for aerobic degradation which differ from the theoretical trend for reductive dehalogenation. Quantitative Polymerase Chain Reaction (qPCR) results showed a significant increase in todC gene copy number with respect to its initial levels for both natural attenuation and biostimulated microcosms, suggesting its involvement in the MCB aerobic degradation, whereas phe gene copy number increased only in the biostimulated ones. Indeed, 37Cl fractionation in combination with the dual carbon­chlorine isotope approach and the todC gene copy number represent valuable indicators for a qualitative assessment of MCB aerobic biodegradation in the field.

Computational Analysis of RNA-Seq Data from Airway Epithelial Cells for Studying Lung Disease.

Airway epithelial cells (AECs) play a central role in the pathogenesis of many lung diseases. Consequently, advancements in our understanding of the underlying causes of lung diseases, and the development of novel treatments, depend on continued detailed study of these cells. Generation and analysis of high-throughput gene expression data provide an indispensable tool for carrying out the type of broad-scale investigations needed to identify the key genes and molecular pathways that regulate, distinguish, and predict distinct pulmonary pathologies. Of the available technologies for generating genome-wide expression data, RNA sequencing (RNA-seq) has emerged as the most powerful. Hence many researchers are turning to this approach in their studies of lung disease. For the relatively uninitiated, computational analysis of RNA-seq data can be daunting, given the large number of methods and software packages currently available. The aim of this chapter is to provide a broad overview of the major steps involved in processing and analyzing RNA-seq data, with a special focus on methods optimized for data generated from AECs. We take the reader from the point of obtaining sequence reads from the lab to the point of making biological inferences with expression data. Along the way, we discuss the statistical and computational considerations one typically confronts during different phases of analysis and point to key methods, software packages, papers, online guides, and other resources that can facilitate successful RNA-seq analysis.

Fluorescent in Situ Hybridization and Real-Time Quantitative Polymerase Chain Reaction to Evaluate HER-2/neu Status in Breast Cancer.

BACKGROUND: Breast cancer remains the most common and second lethal cancer in females. HER-2/neu is one of the most important amplified oncogene in breast cancer. The amplification of HER-2 is correlated with decreased survival, metastasis, and early recurrence. The amplification of HER-2/neu gene and synthesis of the protein are reported in 10%-34% of breast cancer cases associated with tumor size, advanced tumor stage, high-grade tumor, young age at diagnosis, absence of steroid hormone receptor, and lymph node involvement. METHODS: Fluorescence in situ hybridization (FISH) and immunohistochemistry (IHC) methods are options to evaluate HER-2 expression. The current study aimed at identifying the correlation between FISH and real-time polymerase chain reaction (PCR) in measuring HER-2 expression. RESULTS: The study investigated the performance of the real-time PCR as measured against FISH method in IHC +2 borderline cases. In a total of 120 IHC 2+ samples, 58.3% were negative and 41.6% positive for HER-2 gene, confirmed by FISH as a gold standard method. The real-time PCR ratio was <1.8 for a majority (82.8%) of the tumor samples with unamplified HER-2 gene by FISH as a gold standard assay. CONCLUSION: Despite the fact that real-time PCR is a promising method to evaluate HER-2 over expression and a supplementary array to FISH, according to the results of the present study it cannot be utilized instead of gold standard techniques; therefore, additional studies should be carried out to appraise the value of this method to evaluate HER-2 over expression.

Selection and Validation of Appropriate Reference Genes for Quantitative Real-Time PCR Analysis of Gene Expression in Lycoris aurea.

Lycoris aurea (L' Hér.) Herb, a perennial grass species, produces a unique variety of pharmacologically active Amaryllidaceae alkaloids. However, the key enzymes and their expression pattern involved in the biosynthesis of Amaryllidaceae alkaloids (especially for galanthamine) are far from being fully understood. Quantitative real-time polymerase chain reaction (qRT-PCR), a commonly used method for quantifying gene expression, requires stable reference genes to normalize its data. In this study, to choose the appropriate reference genes under different experimental conditions, 14 genes including YLS8 (mitosis protein YLS8), CYP2 (Cyclophilin 2), CYP 1 (Cyclophilin 1), TIP41 (TIP41-like protein), EXP2 (Expressed protein 2), PTBP1 (Polypyrimidine tract-binding protein 1), EXP1 (Expressed protein 1), PP2A (Serine/threonine-protein phosphatase 2A), ß-TUB (ß-tubulin), α-TUB (α-tubulin), EF1-α (Elongation factor 1-α), UBC (Ubiquitin-conjugating enzyme), ACT (Actin) and GAPDH (Glyceraldehyde 3-phosphate dehydrogenase) were selected from the transcriptome datasets of L. aurea. And then, expressions of these genes were assessed by qRT-PCR in various tissues and the roots under different treatments. The expression stability of the 14 candidates was analyzed by three commonly used software programs (geNorm, NormFinder, and BestKeeper), and their results were further integrated into a comprehensive ranking based on the geometric mean. The results show the relatively stable genes for each subset as follows: (1) EXP1 and TIP41 for all samples; (2) UBC and EXP1 for NaCl stress; (3) PTBP1 and EXP1 for heat stress, polyethylene glycol (PEG) stress and ABA treatment; (4) UBC and CYP2 for cold stress; (5) PTBP1 and PP2A for sodium nitroprusside (SNP) treatment; (6) CYP1 and TIP41 for methyl jasmonate (MeJA) treatment; and (7) EXP1 and TIP41 for various tissues. The reliability of these results was further enhanced through comparison between part qRT-PCR result and RNA sequencing (RNA-seq) data. In summary, our results identified appropriate reference genes for qRT-PCR in L. aurea, and will facilitate gene expression studies under these conditions.

Effects of chlortetracycline and copper supplementation on the prevalence, distribution, and quantity of antimicrobial resistance genes in the fecal metagenome of weaned pigs.

Use of in-feed antibiotics such as chlortetracycline (CTC) in food animals is fiercely debated as a cause of antimicrobial resistance in human pathogens; as a result, alternatives to antibiotics such as heavy metals have been proposed. We used a total community DNA approach to experimentally investigate the effects of CTC and copper supplementation on the presence and quantity of antimicrobial resistance elements in the gut microbial ecology of pigs. Total community DNA was extracted from 569 fecal samples collected weekly over a 6-week period from groups of 5 pigs housed in 32 pens that were randomized to receive either control, CTC, copper, or copper plus CTC regimens. Qualitative and quantitative PCR were used to detect the presence of 14 tetracycline resistance (tet) genes and to quantify gene copies of tetA, tetB, blaCMY-2 (a 3rd generation cephalosporin resistance gene), and pcoD (a copper resistance gene), respectively. The detection of tetA and tetB decreased over the subsequent sampling periods, whereas the prevalence of tetC and tetP increased. CTC and copper plus CTC supplementation increased both the prevalence and gene copy numbers of tetA, while decreasing both the prevalence and gene copies of tetB. In summary, tet gene presence was initially very diverse in the gut bacterial community of weaned pigs; thereafter, copper and CTC supplementation differentially impacted the prevalence and quantity of the various tetracycline, ceftiofur and copper resistance genes resulting in a less diverse gene population.

Tentacle: distributed quantification of genes in metagenomes.

BACKGROUND: In metagenomics, microbial communities are sequenced at increasingly high resolution, generating datasets with billions of DNA fragments. Novel methods that can efficiently process the growing volumes of sequence data are necessary for the accurate analysis and interpretation of existing and upcoming metagenomes. FINDINGS: Here we present Tentacle, which is a novel framework that uses distributed computational resources for gene quantification in metagenomes. Tentacle is implemented using a dynamic master-worker approach in which DNA fragments are streamed via a network and processed in parallel on worker nodes. Tentacle is modular, extensible, and comes with support for six commonly used sequence aligners. It is easy to adapt Tentacle to different applications in metagenomics and easy to integrate into existing workflows. CONCLUSIONS: Evaluations show that Tentacle scales very well with increasing computing resources. We illustrate the versatility of Tentacle on three different use cases. Tentacle is written for Linux in Python 2.7 and is published as open source under the GNU General Public License (v3). Documentation, tutorials, installation instructions, and the source code are freely available online at: http://bioinformatics.math.chalmers.se/tentacle.