Optimisation of DNA electroporation protocols for different plant-associated bacteria.

Electroporation is a vital process that facilitates the use of modern recombineering and other high-throughput techniques in a wide array of microorganisms, including non-model bacteria like plant growth-promoting bacteria (PGPB). These microorganisms play a significant role in plant health by colonizing plants and promoting growth through nutrient exchange and hormonal regulation. In this study, we introduce a sequential Design of Experiments (DOE) approach to obtain highly competent cells swiftly and reliably for electroporation. Our method focuses on optimizing the three stages of the electroporation procedure-preparing competent cells, applying the electric pulse field, and recovering transformed cells-separately. We utilized a split-plot fractional design with five factors and a covariate to optimize the first step, response surface methodology (RSM) for the second step, and Plackett-Burman design for two categorical factors and one continuous factor for the final step. Following the experimental sequence with three bacterial models, we achieved efficiencies 10 to 100 times higher, reaching orders of 105 to 106 CFU/µg of circular plasmid DNA. These results highlight the significant potential for enhancing electroporation protocols for non-model bacteria.

Data treatment methods for real-time colorimetric loop-mediated isothermal amplification reactions.

With the SARS-CoV-2 pandemic and the need for affordable and rapid mass testing, colorimetric isothermal amplification reactions such as Loop-Mediated Isothermal Amplification (LAMP) are quickly rising in importance. The technique generates data that is similar to quantitative Polymerase Chain Reaction (qPCR), but instead of an endpoint color visualization, it is possible to construct a signal over a time curve. As the number of works using time-course analysis of isothermal reactions increases, there is a need to analyze data and standardize their related treatments quantitatively. Here, we take a step forward toward this goal by evaluating different available data treatments (curve models) for amplification curves, which allows for a cycle threshold-like parameter extraction. In this study, we uncover evidence of a double sigmoid equation as the most adequate model to describe amplification data from our remote diagnostics system and discuss possibilities for similar setups. We also demonstrate the use of multimodal Gompertz regression models. Thus, this work provides advances toward standardized and unbiased data reporting of Reverse Transcription (RT) LAMP reactions, which may facilitate and quicken assay interpretation, potentially enabling the application of machine learning techniques for further optimization and classification.

Improved protocol for Bst polymerase and reverse transcriptase production and application to a point-of-care diagnostics system.

The pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has raised awareness in the scientific community about the importance of being prepared for sanitary emergencies. Many measures implemented during the COVID pandemic are now being expanded to other applications. In the field of molecular and immunological diagnostics, the need to massively test the population worldwide resulted in the application of a variety of methods to detect viral infection. Besides gold standard reverse transcription quantitative polymerase chain reaction (RT-qPCR), the use of reverse transcription loop-mediated isothermal amplification (RT-LAMP) arose as an alternative and sensitive method to amplify and detect viral genetic material. We have used openly available protocols and have improved the protein production of RT-LAMP enzymes Bst polymerase and HIV-reverse transcriptase. To optimize enzyme production, we tested different protein tags, and we shortened the protein purification protocol, resulting in reduced processing time and handling of the enzymes and, thus, preserved the protein activity with high purity. The enzymes showed significant stability at 4 °C and 25 °C, over 60 days, and were highly reliable when used as a one-step RT-LAMP reaction in a portable point-of-care device with clinical samples. The enzymes and the reaction setup can be further expanded to detect other infectious diseases agents.

Development of an optimized colorimetric RT-LAMP for SARS-CoV-2 assay with enhanced procedure controls for remote diagnostics.

The coronavirus pandemic accentuated the need for molecular diagnostic tests. A technique highly used to this end is the Polymerase Chain Reaction (PCR)-a sensitive and specific technique commonly used as the gold standard for molecular diagnostics. However, it demands highly trained personnel and high-maintenance equipment and is relatively time-consuming. An alternative is the Loop-Mediated Isothermal Amplification (LAMP) technique, which doesn't need sample purification or expensive equipment, and is similar to PCR when compared in sensitivity and specificity. In this paper, we developed an optimized colorimetric Reverse Transcriptase Loop-Mediated Isothermal Amplification (RT-LAMP) Point-of-Care test using a portable device to diagnose COVID-19. Variables such as concentration of primers, magnesium sulfate, betaine, hydrochloride guanidine, Bst, and temperature of the reactions were tested. We also created a pipetting quality control system-using a combination of dyes-to avoid false negatives due to a lack of samples added to the reaction test tube. Mineral oil was incorporated in the composition of the RT-LAMP reactions to avoid evaporation when a heating lid isn't available. The final RT-LAMP test is tenfold more sensitive when compared to the WarmStart Colorimetric Master mix from New England Biolabs with a sensitivity of 5 copies per µL.

Author Correction: The transcriptional regulator NtrC controls glucose-6-phosphate dehydrogenase expression and polyhydroxybutyrate synthesis through NADPH availability in Herbaspirillum seropedicae.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

The transcriptional regulator NtrC controls glucose-6-phosphate dehydrogenase expression and polyhydroxybutyrate synthesis through NADPH availability in Herbaspirillum seropedicae.

The NTR system is the major regulator of nitrogen metabolism in Bacteria. Despite its broad and well-known role in the assimilation, biosynthesis and recycling of nitrogenous molecules, little is known about its role in carbon metabolism. In this work, we present a new facet of the NTR system in the control of NADPH concentration and the biosynthesis of molecules dependent on reduced coenzyme in Herbaspirillum seropedicae SmR1. We demonstrated that a ntrC mutant strain accumulated high levels of polyhydroxybutyrate (PHB), reaching levels up to 2-fold higher than the parental strain. In the absence of NtrC, the activity of glucose-6-phosphate dehydrogenase (encoded by zwf) increased by 2.8-fold, consequently leading to a 2.1-fold increase in the NADPH/NADP+ ratio. A GFP fusion showed that expression of zwf is likewise controlled by NtrC. The increase in NADPH availability stimulated the production of polyhydroxybutyrate regardless the C/N ratio in the medium. The mutant ntrC was more resistant to H2O2 exposure and controlled the propagation of ROS when facing the oxidative condition, a phenotype associated with the increase in PHB content.