Pool Testing for COVID-19: Suitable Splitting Procedure and Pool Size for India.

OBJECTIVE: Coronavirus disease (COVID-19) has emerged as a global pandemic for public health due to the large scale outbreak, therefore there is an urgent need to detect the infected cases quickly and isolate them in order to suppress the further spread of the disease. This study tries to identify a suitable pool testing method and algorithm for COVID-19. METHODS: This study tries to derive a general equation for the number of tests required for a pooled sample to detect every infected individual in the specific pool. The gain in pool testing over the normal procedure is quantified by the percentage of tests required compared to individual testing. RESULTS: The percentage of tests required by the pool testing strategy varies according to the different splitting procedures, the size of the pooled sample, and the probability of an individual being infected in the population. If the probability of infection is 0.05, then for a pool size of 32, only 14 tests are sufficient to detect every infected individual. CONCLUSION: The number of tests required to detect infected individuals by using the pooling method is much lower than individual testing. This may help us with increasing our testing capacity for COVID-19 by testing a large number of individuals in less time with limited resources.

Human Granulocyte Macrophage Colony-Stimulating Factor Enhances Antibiotic Susceptibility of Pseudomonas aeruginosa Persister Cells.

Bacterial persister cells are highly tolerant to antibiotics and cause chronic infections. However, little is known about the interaction between host immune systems with this subpopulation of metabolically inactive cells, and direct effects of host immune factors (in the absence of immune cells) on persister cells have not been studied. Here we report that human granulocyte macrophage-colony stimulating factor (GM-CSF) can sensitize the persister cells of Pseudomonas aeruginosa PAO1 and PDO300 to multiple antibiotics including ciprofloxacin, tobramycin, tetracycline, and gentamicin. GM-CSF also sensitized the biofilm cells of P. aeruginosa PAO1 and PDO300 to tobramycin in the presence of biofilm matrix degrading enzymes. The DNA microarray and qPCR results indicated that GM-CSF induced the genes for flagellar motility and pyocin production in the persister cells, but not the normal cells of P. aeruginosa PAO1. Consistently, the supernatants from GM-CSF treated P. aeruginosa PAO1 persister cell suspensions were found cidal to the pyocin sensitive strain P. aeruginosa PAK. Collectively, these findings suggest that host immune factors and bacterial persisters may directly interact, leading to enhanced susceptibility of persister cells to antibiotics.

Signaling factor interactions with polysaccharide aggregates of bacterial biofilms.

Biofilms are surface-attached colonies of bacteria embedded in an extracellular polymeric substance (EPS). Inside the eukaryotic hosts, bacterial biofilms interact with the host cells through signaling factors (SFs). These signaling processes play important roles in the interaction between bacteria and host cells and the outcome of infections and symbiosis. However, how host immune factors diffuse through biofilms is not well understood. Here, we describe synergistic molecular dynamics and experimental approaches for studying the translocation of signaling factors through polysaccharide chain aggregates present in the extracellular matrix of bacterial biofilms. The effect of polysaccharide chain degradation on the energetics of SF-EPS interactions was examined by simulating an EPS consisting of various polysaccharide chain lengths. It is shown that the SF stabilization energy, defined as the average potential of mean force difference between the environments outside and within the matrix, increases linearly with decreasing chain length. This effect has been explained based on the changes in the polysaccharide configurations around the SF. Specifically, shorter chains are packed tightly around the SF, promoting favorable SF-EPS interactions, while longer chains are packed loosely resulting in screening of interactions with neighboring chains. We further investigated the translocation of SFs through the host cell membrane using molecular dynamics simulations. Further, simulations predict the existence of energy barriers greater than 1000 kJ mol(-1) associated with the translocation of the signaling factors necrosis factor-alpha (TNF-α) and granulocyte macrophage colony stimulating factor (GM-CSF) across the lipid bilayer. The agreement of computational and experimental findings motivates future computational studies using a more detailed description of the EPS aimed at understanding the role of the extracellular matrix on biofilm drug resistance.