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.

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.

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 (Y_seq) 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.

Metagenomic Quantification of Genes with Internal Standards

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 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.

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 C_y0 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), C_y0 (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 C_y0 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 C_y0) when PCR data are challenged for inter-assay variations.

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), β-TUB (β-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.

Development and validation of a high throughput, closed tube method for the determination of haemoglobin alpha gene (HBA1 and HBA2) numbers by gene ratio assay copy enumeration-PCR (GRACE-PCR)

BACKGROUND

Deletions of the α-globin genes are the most common genetic abnormalities in the world. Currently multiplex Gap-PCRs are frequently used to identify specific sets of common deletions. However, these assays require significant post-amplification hands on time and cannot be used to identify novel or unexpected deletions. The aim of the current study was to develop a rapid screening test for the detection of all deletions of the α-globin genes that can be integrated into a high volume clinical laboratory workflow.

METHODS

A gene ratio assay copy enumeration (GRACE) PCR method was developed by simultaneous amplification of targets in the α-globin genes (HBA1 and HBA2) and the chloride channel voltage sensitive 7 (CLCN7) reference gene. A novel application of High Resolution Melting (HRM) analysis then allowed rapid determination of α-globin gene copy numbers. The assay was validated using 105 samples with previously determined and 62 samples with unknown α-globin genotypes.

RESULTS

The GRACE-PCR assay detected abnormal α-globin gene copy numbers in 108 of the 167 samples evaluated. The results were consistent with those from a commercial reverse hybridization assay and no allele drop out was observed.

CONCLUSIONS

We have successfully developed and validated a GRACE-PCR screening test for the detection of deletions and duplications of the α-globin genes. The assay is based on copy number determination and has the ability to detect both known and novel deletions of the α-globin genes. It is a closed tube technique; consequently the risk of amplicon contamination is negligible. Amplification, detection and analysis can be completed within one hour, making it faster, cheaper and simpler than other existing tests and thus well suited as a rapid first step in a clinical laboratory workflow.

Validation of suitable reference genes for gene expression analysis in the halophyte Salicornia europaea by real-time quantitative PCR

Real-time quantitative polymerase chain reaction (RT-qPCR), a reliable technique for quantifying gene expression, requires stable reference genes to normalize its data. Salicornia europaea, a stem succulent halophyte with remarkable salt resistance and high capacity for ion accumulation, has not been investigated with regards to the selection of appropriate reference genes for RT-qPCR. In this study, the expression of 11 candidate reference genes, GAPDH (Glyceraldehyde 3-phosphate dehydrogenase), Actin, α-Tub (α-tubulin), β-Tub (β-tubulin), EF1-α (Elongation factor 1-α), UBC (Ubiquitin-conjugating enzyme), UBQ (Polyubiquitin), CYP (Cyclophilin), TIP41 (TIP41-like protein), CAC (Clathrin adaptor complexes), and DNAJ (DnaJ-like protein), was analyzed in S. europaea samples, which were classified into groups according to various abiotic stresses (NaCl, nitrogen, drought, cold and heat), tissues and ages. Three commonly used software programs (geNorm, NormFinder and BestKeeper) were applied to evaluate the stability of gene expression, and comprehensive ranks of stability were generated by aggregate analysis. The results show that the relatively stable genes for each group are the following: (1) CAC and UBC for whole samples; (2) CAC and UBC for NaCl stress; (3) Actin and α-Tub for nitrogen treatment; (4) Actin and GAPDH for drought stress; (5) α-Tub and UBC for cold stress; (6) TIP41 and DNAJ for heat stress; (7) UBC and UBQ for different tissues; and (8) UBC and Actin for various developmental stages. These genes were validated by comparing transcriptome profiles. Using two stable reference genes was recommended in the normalization of RT-qPCR data. This study identifies optimal reference genes for RT-qPCR in S. europaea, which will benefit gene expression analysis under these conditions.