SpeciesPrimer: a bioinformatics pipeline dedicated to the design of qPCR primers for the quantification of bacterial species

PUPpy: a primer design pipeline for substrain-level microbial detection and absolute quantification

Characterizing microbial communities at high resolution and with absolute quantification is crucial to unravel the complexity and diversity of microbial ecosystems. This can be achieved with PCR assays, which enable highly selective detection and absolute quantification of microbial DNA. However, a major challenge that has hindered PCR applications in microbiome research is the design of highly specific primer sets that exclusively amplify intended targets. Here, we introduce Phylogenetically Unique Primers in python (PUPpy), a fully automated pipeline to design microbe- and group-specific primers within a given microbial community. PUPpy can be executed from a user-friendly graphical user interface, or two simple terminal commands, and it only requires coding sequence files of the community members as input. PUPpy-designed primers enable the detection of individual microbes and quantification of absolute microbial abundance in defined communities below the strain level. We experimentally evaluated the performance of PUPpy-designed primers using two bacterial communities as benchmarks. Each community comprises 10 members, exhibiting a range of genetic similarities that spanned from different phyla to substrains. PUPpy-designed primers also enable the detection of groups of bacteria in an undefined community, such as the detection of a gut bacterial family in a complex stool microbiota sample. Taxon-specific primers designed with PUPpy showed 100% specificity to their intended targets, without unintended amplification, in each community tested. Lastly, we show the absolute quantification of microbial abundance using PUPpy-designed primers in droplet digital PCR, benchmarked against 16S rRNA and shotgun sequencing. Our data shows that PUPpy-designed microbe-specific primers can be used to quantify substrain-level absolute counts, providing more resolved and accurate quantification in defined communities than short-read 16S rRNA and shotgun sequencing.

IMPORTANCE

Profiling microbial communities at high resolution and with absolute quantification is essential to uncover hidden ecological interactions within microbial ecosystems. Nevertheless, achieving resolved and quantitative investigations has been elusive due to methodological limitations in distinguishing and quantifying highly related microbes. Here, we describe Phylogenetically Unique Primers in python (PUPpy), an automated computational pipeline to design taxon-specific primers within defined microbial communities. Taxon-specific primers can be used to selectively detect and quantify individual microbes and larger taxa within a microbial community. PUPpy achieves substrain-level specificity without the need for computationally intensive databases and prioritizes user-friendliness by enabling both terminal and graphical user interface applications. Altogether, PUPpy enables fast, inexpensive, and highly accurate perspectives into microbial ecosystems, supporting the characterization of bacterial communities in both in vitro and complex microbiota settings.

Design and Validation of Primer Sets for the Detection and Quantification of Antibiotic Resistance Genes in Environmental Samples by Quantitative PCR

The high prevalence of antibiotic resistant bacteria (ARB) in several environments is a great concern threatening human health. Particularly, wastewater treatment plants (WWTP) become important contributors to the dissemination of ARB to receiving water bodies, due to the inefficient management or treatment of highly antibiotic-concentrated wastewaters. Hence, it is vital to develop molecular tools that allow proper monitoring of the genes encoding resistances to these important therapeutic compounds (antibiotic resistant genes, ARGs). For an accurate quantification of ARGs, there is a need for sensitive and robust qPCR assays supported by a good design of primers and validated protocols. In this study, eleven relevant ARGs were selected as targets, including aadA and aadB (conferring resistance to aminoglycosides); ampC, blaTEM, blaSHV, and mecA (resistance to beta-lactams); dfrA1 (resistance to trimethoprim); ermB (resistance to macrolides); fosA (resistance to fosfomycin); qnrS (resistance to quinolones); and tetA(A) (resistance to tetracyclines). The in silico design of the new primer sets was performed based on the alignment of all the sequences of the target ARGs (orthology grade > 70%) deposited in the Kyoto Encyclopedia of Genes and Genomes (KEGG) database, allowing higher coverages of the ARGs' biodiversity than those of several primers described to date. The adequate design and performance of the new molecular tools were validated in six samples, retrieved from both natural and engineered environments related to wastewater treatment. The hallmarks of the optimized qPCR assays were high amplification efficiency (> 90%), good linearity of the standard curve (R2 > 0.980), repeatability and reproducibility across experiments, and a wide linear dynamic range. The new primer sets and methodology described here are valuable tools to upgrade the monitorization of the abundance and emergence of the targeted ARGs by qPCR in WWTPs and related environments.

The impact of gut microbiome enterotypes on ulcerative colitis: identifying key bacterial species and revealing species co-occurrence networks using machine learning

Ulcerative colitis (UC) is a chronic inflammatory intestinal disease affecting the colon and rectum, with its pathogenesis attributed to genetic background, environmental factors, and gut microbes. This study aimed to investigate the role of enterotypes in UC by conducting a hierarchical analysis, determining differential bacteria using machine learning, and performing Species Co-occurrence Network (SCN) analysis. Fecal bacterial data were collected from UC patients, and a 16S rRNA metagenomic analysis was performed using the QIIME2 bioinformatics pipeline. Enterotype clustering was conducted at the family level, and deep neural network (DNN) classification models were trained for UC and healthy controls (HC) in each enterotype. Results from eleven 16S rRNA gut microbiome datasets revealed three enterotypes: Bacteroidaceae (ET-B), Lachnospiraceae (ET-L), and Clostridiaceae (ET-C). Ruminococcus (R. gnavus) abundance was significantly higher in UC subjects with ET-B and ET-C than in those with ET-L. R. gnavus also showed a positive correlation with Clostridia in UC SCN for ET-B and ET-C subjects, with a higher correlation in ET-C subjects. Conversely, Odoribacter (O.) splanchnicus and Bacteroides (B.) uniformis exhibited a positive correlation with tryptophan metabolism and AMP-activated protein kinase (AMPK) signaling pathways, while R. gnavus showed a negative correlation. In vitro co-culture experiments with Clostridium (C.) difficile demonstrated that fecal microbiota from ET-B subjects had a higher abundance of C. difficile than ET-L subjects. In conclusion, the ET-B enterotype predisposes individuals to UC, with R. gnavus as a potential risk factor and O. splanchnicus and B. uniformis as protective bacteria, and those with UC may have ultimately become ET-C.

The Potential Clinical Applications of a Microfluidic Lab-on-a-Chip for the Identification and Antibiotic Susceptibility Testing of Enterococcus faecalis-Associated Endodontic Infections: A Systematic Review

This systematic review evaluated the potential clinical use of microfluidic lab-on-a-chip (LOC) technology in the identification and antibiotic susceptibility testing of E. faecalis in endodontic infections. The search methodology employed in this review adhered to the PRISMA guidelines. Multiple scientific databases, including PubMed/MEDLINE, SCOPUS, and SCIELO, were utilized, along with exploration of grey literature sources. Up to September 2023, these resources were searched using specific keywords and MeSH terms. An initial comprehensive search yielded 202 articles. Ultimately, this systematic review incorporated 12 studies. Out of these, seven aimed to identify E. faecalis, while the remaining five evaluated its susceptibility to different antibiotics. All studies observed that the newly developed microfluidic chip significantly reduces detection time compared to traditional methods. This enhanced speed is accompanied by a high degree of accuracy, efficiency, and sensitivity. Most research findings indicated that the entire process took anywhere from less than an hour to five hours. It is important to note that this approach bypasses the need for minimum inhibitory concentration measurements, as it does not rely on traditional methodologies. Microfluidic devices enable the rapid identification and accurate antimicrobial susceptibility testing of E. faecalis, which are crucial for timely diagnosis and treatment in endodontic infections.

Designing and validation of specific primers for the quantitative detection of bacteria in sugarcane inoculant

Endophytic diazotrophic plant growth-promoting bacteria Herbaspirillum rubrisubalbicans (HCC103), Herbaspirillum seropedicae (HRC54), Paraburkholderia tropica (Ppe8T), Gluconacetobacter diazotrophicus (Pal5T), and Nitrospirillum amazonense (CBAmC) have been used as inoculants for sugarcane. The genome sequences of these strains were used to design a set of specific primers for the real-time PCR (qPCR) assay. Primer specificity was confirmed by conventional PCR using the genomic DNAs of 25 related bacterial species and the five target strains. The qPCR assays were conducted using root and shoot samples from two sugarcane varieties (RB867515 and RB92579). These samples were collected both with and without inoculation, using the target strains specified in this study. The sugarcane plants were grown in a greenhouse, utilizing a substrate composed of sterile sand and vermiculite in a 2:1 ratio, for a duration of 55 days. The primers designed for this study successfully amplified target DNA fragments from each of the bacterial species, enabling their differentiation at the species level. The total bacterial population present in the sugarcane quantified using qPCR was on average 105.2 cells g-1 of fresh tissue. Across both evaluated varieties, it was observed that the population of inoculated bacteria tended to decrease over time and became more concentrated in the sugarcane roots compared to the aerial parts. The qPCR results suggest that both the host and the microbes influence the endophytic population and the bacterial number decreases with plant age.

Development and evaluation of a multiplex polymerase chain reaction in real-time for differential diagnosis of Moraxella-induced keratoconjunctivitis in livestock

Background and Aim

Infectious bovine keratoconjunctivitis (IBK) is a prevalent ocular disease that affects livestock, leading to substantial economic losses due to reduced production and culling of infected animals. Moraxella spp. is common bacterial pathogens that can cause keratoconjunctivitis in livestock. Therefore, rapid and accurate diagnosis is crucial for effective treatment and disease control. This study aimed to develop a multiplex real-time polymerase chain reaction (mRT-PCR) assay for the detection and differentiation of Moraxella bovoculi, Moraxella ovis, and Moraxella bovis.

Materials and Methods

Three reference strains of Moraxella as positive controls and 36 lacrimal swab samples collected from cattle were used to evaluate the developed mRT-PCR assay DNA extraction that was performed using the RIBO-sorb DNA/RNA extraction kit. Primers and probes were designed using the SpeciesPrimer pipeline. The annealing temperature, primer and probe concentrations, and sensitivity and specificity of the assay were optimized.

Results

An mRT-PCR assay was developed to detect pathogens associated with IBK in cattle on the basis of optimized parameters. The specificity and sensitivity of this assay were confirmed using samples containing individual pathogens (O - M. ovis, B - M. bovis, and BO - M. bovoculi), combinations of two pathogens (O-B, B-BO, and O-BO), and when the DNA of all three pathogens was present in a single reaction (O-B-BO). The analytical sensitivity of mRT-PCR for detecting M. ovis and M. bovoculi DNA was 21 copies or 50 fg per reaction, whereas that for M. bovis was 210 copies or 500 fg per reaction. In addition, this assay has been tested on samples isolated from the affected eyes of cattle in the Akmola region of the Republic of Kazakhstan.

Conclusion

For the first time in the Republic of Kazakhstan, the proposed mRT-PCR assay for the simultaneous detection of three Moraxella spp. pathogens has been developed. This assay exhibits the required specificity and high sensitivity for m RT-PCR, facilitating the timely implementation of effective measures for disease control and the prevention of economic losses. These losses are linked to a reduction in livestock breeding value, a reduction in meat and milk production, a reduction in the reproductive performance of heifers, resulting in fewer offspring, as well as costs related to the treatment of affected animals.

Exploring Functional Diversity and Community Structure of Diazotrophic Endophytic Bacteria Associated with Pennisetum glaucum Growing under Field in a Semi-Arid Region

Diazotrophic endophytic bacteria (DEB) are the key drivers of nitrogen fixation in rainfed soil ecosystems and, hence, can influence the growth and yield of crop plants. Therefore, the present work investigated the structure and composition of the DEB community at different growth stages of field-grown pearl millet plants, employing the cultivation-dependent method. Diazotrophy of the bacterial isolates was confirmed by acetylene reduction assay and amplification of the nifH gene. ERIC-PCR-based DNA fingerprinting, followed by 16S rRNA gene analysis of isolates recovered at different time intervals, demonstrated the highest bacterial diversity during early (up to 28 DAS (Days after sowing)) and late (63 DAS onwards) stages, as compared to the vegetative growth stage (28–56 DAS). Among all species, Pseudomonas aeruginosa was the most dominant endophyte. Assuming modulation of the immune response as one of the tactics for successful colonization of P. aeruginosa PM389, we studied the expression of the profile of defense genes of wheat, used as a host plant, in response to P. aeruginosa inoculation. Most of the pathogenesis-related PR genes were induced initially (at 6 h after infection (HAI)), followed by their downregulation at 12 HAI. The trend of bacterial colonization was quantified by qPCR of 16S rRNAs. The results obtained in the present study indicated an attenuated defense response in host plants towards endophytic bacteria, which is an important feature that helps endophytes establish themselves inside the endosphere of roots.

High-throughput qPCR and 16S rRNA gene amplicon sequencing as complementary methods for the investigation of the cheese microbiota

Background

Next-generation sequencing (NGS) methods and especially 16S rRNA gene amplicon sequencing have become indispensable tools in microbial ecology. While they have opened up new possibilities for studying microbial communities, they also have one drawback, namely providing only relative abundances and thus compositional data. Quantitative PCR (qPCR) has been used for years for the quantification of bacteria. However, this method requires the development of specific primers and has a low throughput. The constraint of low throughput has recently been overcome by the development of high-throughput qPCR (HT-qPCR), which allows for the simultaneous detection of the most prevalent bacteria in moderately complex systems, such as cheese and other fermented dairy foods. In the present study, the performance of the two approaches, NGS and HT-qPCR, was compared by analyzing the same DNA samples from 21 Raclette du Valais protected designation of origin (PDO) cheeses. Based on the results obtained, the differences, accuracy, and usefulness of the two approaches were studied in detail.

Results

The results obtained using NGS (non-targeted) and HT-qPCR (targeted) show considerable agreement in determining the microbial composition of the cheese DNA samples studied, albeit the fundamentally different nature of these two approaches. A few inconsistencies in species detection were observed, particularly for less abundant ones. The detailed comparison of the results for 15 bacterial species/groups measured by both methods revealed a considerable bias for certain bacterial species in the measurements of the amplicon sequencing approach. We identified as probable origin to this PCR bias due to primer mismatches, variations in the number of copies for the 16S rRNA gene, and bias introduced in the bioinformatics analysis.

Conclusion

As the normalized microbial composition results of NGS and HT-qPCR agreed for most of the 21 cheese samples analyzed, both methods can be considered as complementary and reliable for studying the microbial composition of cheese. Their combined application proved to be very helpful in identifying potential biases and overcoming methodological limitations in the quantitative analysis of the cheese microbiota.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12866-022-02451-y.

Antimicrobial Susceptibility of Lactobacillus delbrueckii subsp. lactis from Milk Products and Other Habitats

As components of many cheese starter cultures, strains of Lactobacillus delbrueckii subsp. lactis (LDL) must be tested for their antimicrobial susceptibility to avoid the potential horizontal transfer of antibiotic resistance (ABR) determinants in the human body or in the environment. To this end, a phenotypic test, as well as a screening for antibiotic resistance genes (ARGs) in genome sequences, is commonly performed. Historically, microbiological cutoffs (MCs), which are used to classify strains as either 'sensitive' or 'resistant' based on the minimal inhibitory concentrations (MICs) of a range of clinically-relevant antibiotics, have been defined for the whole group of the obligate homofermentative lactobacilli, which includes LDL among many other species. This often leads to inaccuracies in the appreciation of the ABR status of tested LDL strains and to false positive results. To define more accurate MCs for LDL, we analyzed the MIC profiles of strains originating from various habitats by using the broth microdilution method. These strains' genomes were sequenced and used to complement our analysis involving a search for ARGs, as well as to assess the phylogenetic proximity between strains. Of LDL strains, 52.1% displayed MICs that were higher than the defined MCs for kanamycin, 9.9% for chloramphenicol, and 5.6% for tetracycline, but no ARG was conclusively detected. On the other hand, all strains displayed MICs below the defined MCs for ampicillin, gentamycin, erythromycin, and clindamycin. Considering our results, we propose the adaptation of the MCs for six of the tested clinically-relevant antibiotics to improve the accuracy of phenotypic antibiotic testing.

Antibiotic Susceptibility Profiles of Pediococcus pentosaceus from Various Origins and Their Implications for the Safety Assessment of Strains with Food-Technology Applications

ABSTRACT

In the fight against the spread of antibiotic resistance, authorities usually require that strains "intentionally added into the food chain" be tested for their antibiotic susceptibility. This applies to strains used in starter or adjunct cultures for the production of fermented foods, such as many strains of Pediococcus pentosaceus. The European Food Safety Authority recommends testing strains for their antibiotic susceptibility based on both genomic and phenotypic approaches. Furthermore, it proposes a set of antibiotics to assess as well as a list of microbiological cutoffs (MCs), allowing classification of lactic acid bacteria as susceptible or resistant. Accurate MCs are essential not only to avoid false-negative strains, which may carry antibiotic resistance genes and remain unnoticed, but also to avoid false-positive strains, which may be discarded while screening potential candidates for food-technology applications. Because of relatively scarce data, MCs have been defined for the whole Pediococcus genus, although differences between species should be expected. In this study, we investigated the antibiotic susceptibility of 35 strains of P. pentosaceus isolated from various matrices in the past 70 yr. MICs were determined using a standard protocol, and MIC distributions were established. Phenotypic analyses were complemented with genome sequencing and by seeking known antibiotic resistance genes. The genomes of all the strains were free of known antibiotic resistance genes, but most displayed MICs above the currently defined MCs for chloramphenicol, and all showed excessive MICs for tetracycline. Based on the distributions, we calculated and proposed new MCs for chloramphenicol (16 instead of 4 mg/L) and tetracycline (256 instead of 8 mg/L).

HIGHLIGHTS

Development of a High-Throughput Microfluidic qPCR System for the Quantitative Determination of Quality-Relevant Bacteria in Cheese

The composition of the cheese microbiome has an important impact on the sensorial quality and safety of cheese. Therefore, much effort has been made to investigate the microbial community composition of cheese. Quantitative real-time polymerase chain reaction (qPCR) is a well-established method for detecting and quantifying bacteria. High-throughput qPCR (HT-qPCR) using microfluidics brings further advantages by providing fast results and by decreasing the cost per sample. We have developed a HT-qPCR approach for the rapid and cost-efficient quantification of microbial species in cheese by designing qPCR assays targeting 24 species/subspecies commonly found in cheese. Primer pairs were evaluated on the Biomark (Fluidigm) microfluidic HT-qPCR system using DNA from single strains and from artificial mock communities. The qPCR assays worked efficiently under identical PCR conditions, and the validation showed satisfying inclusivity, exclusivity, and amplification efficiencies. Preliminary results obtained from the HT-qPCR analysis of DNA samples of model cheeses made with the addition of adjunct cultures confirmed the potential of the microfluidic HT-qPCR system to screen for selected bacterial species in the cheese microbiome. HT-qPCR data of DNA samples of two downgraded commercial cheeses showed that this approach provides valuable information that can help to identify the microbial origin of quality defects. This newly developed HT-qPCR system is a promising approach that will allow simultaneous monitoring of quality-relevant species in fermented foods with high bacterial diversity, thereby opening up new perspectives for the control and assurance of high product quality.