Amplification Efficiency and Template Accessibility as Distinct Causes of Rain in Digital PCR: Monte Carlo Modeling and Experimental Validation.

Partitions in digital PCR (dPCR) assays do not reach the detection threshold at the same time. This heterogeneity in amplification results in intermediate endpoint fluorescence values (i.e., rain) and misclassification of partitions, which has a major impact on the accuracy of nucleic acid quantification. Rain most often results from a reduced amplification efficiency or template inaccessibility; however, exactly how these contribute to rain has not been described. We developed and experimentally validated an analytical model that mechanistically explains the relationship between amplification efficiency, template accessibility, and rain. Using Monte Carlo simulations, we show that a reduced amplification efficiency leads to broader threshold cycle (Ct) distributions that can be fitted using a log-normal probability distribution. From the fit parameters, the amplification efficiency can be calculated. Template inaccessibility, on the other hand, leads to a different rain pattern, in which a distinct exponential tail in the Ct distribution can be observed. Using our model, it is possible to determine if the amplification efficiency, template accessibility, or another source is the main contributor of rain in dPCR assays. We envision that this model will facilitate and speed up dPCR assay optimization and provide an indication for the accuracy of the assay.

Molecular detection of SARS-COV-2 in exhaled breath at the point-of-need.

The SARS-CoV-2 pandemic has highlighted the need for improved technologies to help control the spread of contagious pathogens. While rapid point-of-need testing plays a key role in strategies to rapidly identify and isolate infectious patients, current test approaches have significant shortcomings related to assay limitations and sample type. Direct quantification of viral shedding in exhaled particles may offer a better rapid testing approach, since SARS-CoV-2 is believed to spread mainly by aerosols. It assesses contagiousness directly, the sample is easy and comfortable to obtain, sampling can be standardized, and the limited sample volume lends itself to a fast and sensitive analysis. In view of these benefits, we developed and tested an approach where exhaled particles are efficiently sampled using inertial impaction in a micromachined silicon chip, followed by an RT-qPCR molecular assay to detect SARS-CoV-2 shedding. Our portable, silicon impactor allowed for the efficient capture (>85%) of respiratory particles down to 300 nm without the need for additional equipment. We demonstrate using both conventional off-chip and in-situ PCR directly on the silicon chip that sampling subjects' breath in less than a minute yields sufficient viral RNA to detect infections as early as standard sampling methods. A longitudinal study revealed clear differences in the temporal dynamics of viral load for nasopharyngeal swab, saliva, breath, and antigen tests. Overall, after an infection, the breath-based test remains positive during the first week but is the first to consistently report a negative result, putatively signalling the end of contagiousness and further emphasizing the potential of this tool to help manage the spread of airborne respiratory infections.

Transition between fermentation and respiration determines history-dependent behavior in fluctuating carbon sources.

Cells constantly adapt to environmental fluctuations. These physiological changes require time and therefore cause a lag phase during which the cells do not function optimally. Interestingly, past exposure to an environmental condition can shorten the time needed to adapt when the condition re-occurs, even in daughter cells that never directly encountered the initial condition. Here, we use the molecular toolbox of Saccharomyces cerevisiae to systematically unravel the molecular mechanism underlying such history-dependent behavior in transitions between glucose and maltose. In contrast to previous hypotheses, the behavior does not depend on persistence of proteins involved in metabolism of a specific sugar. Instead, presence of glucose induces a gradual decline in the cells' ability to activate respiration, which is needed to metabolize alternative carbon sources. These results reveal how trans-generational transitions in central carbon metabolism generate history-dependent behavior in yeast, and provide a mechanistic framework for similar phenomena in other cell types.