Functional decomposition of metabolism allows a system-level quantification of fluxes and protein allocation towards specific metabolic functions.

Quantifying the contribution of individual molecular components to complex cellular processes is a grand challenge in systems biology. Here we establish a general theoretical framework (Functional Decomposition of Metabolism, FDM) to quantify the contribution of every metabolic reaction to metabolic functions, e.g. the synthesis of biomass building blocks. FDM allowed for a detailed quantification of the energy and biosynthesis budget for growing Escherichia coli cells. Surprisingly, the ATP generated during the biosynthesis of building blocks from glucose almost balances the demand from protein synthesis, the largest energy expenditure known for growing cells. This leaves the bulk of the energy generated by fermentation and respiration unaccounted for, thus challenging the common notion that energy is a key growth-limiting resource. Moreover, FDM together with proteomics enables the quantification of enzymes contributing towards each metabolic function, allowing for a first-principle formulation of a coarse-grained model of global protein allocation based on the structure of the metabolic network.

Stress-induced metabolic exchanges between complementary bacterial types underly a dynamic mechanism of inter-species stress resistance.

Metabolic cross-feeding plays vital roles in promoting ecological diversity. While some microbes depend on exchanges of essential nutrients for growth, the forces driving the extensive cross-feeding needed to support the coexistence of free-living microbes are poorly understood. Here we characterize bacterial physiology under self-acidification and establish that extensive excretion of key metabolites following growth arrest provides a collaborative, inter-species mechanism of stress resistance. This collaboration occurs not only between species isolated from the same community, but also between unrelated species with complementary (glycolytic vs. gluconeogenic) modes of metabolism. Cultures of such communities progress through distinct phases of growth-dilution cycles, comprising of exponential growth, acidification-triggered growth arrest, collaborative deacidification, and growth recovery, with each phase involving different combinations of physiological states of individual species. Our findings challenge the steady-state view of ecosystems commonly portrayed in ecological models, offering an alternative dynamical view based on growth advantages of complementary species in different phases.

A sensitive and specific genetically-encoded potassium ion biosensor for in vivo applications across the tree of life.

Potassium ion (K+) plays a critical role as an essential electrolyte in all biological systems. Genetically-encoded fluorescent K+ biosensors are promising tools to further improve our understanding of K+-dependent processes under normal and pathological conditions. Here, we report the crystal structure of a previously reported genetically-encoded fluorescent K+ biosensor, GINKO1, in the K+-bound state. Using structure-guided optimization and directed evolution, we have engineered an improved K+ biosensor, designated GINKO2, with higher sensitivity and specificity. We have demonstrated the utility of GINKO2 for in vivo detection and imaging of K+ dynamics in multiple model organisms, including bacteria, plants, and mice.

Testing for SARS-CoV-2 in Symptomatic Vaccinated and Unvaccinated Health Care Workers During the Delta Variant Surge.

BACKGROUND: Infection with SARS- CoV- 2 in health care workers (HCWs) challenges employee health services. METHODS: We analyzed telephone Coronavirus Disease 2019 (COVID-19) hotline data over 8 weeks in 2021 during SARS- CoV- 2 Delta variant surge. We calculated COVID-19 case rates among persons-under-investigation (PUIs) for illness at two health care centers (HCs). RESULTS: There were 41 COVID-19 cases among the 285 PUIs (14.4%) at the study HC and 549 (16.9%) of 3244 at the comparison HC. At the study HC, 11.7% of vaccinated PUIs versus 36.6% of unvaccinated PUIs were COVID-19 positive. The COVID-19 positivity rates among vaccinated and unvaccinated PUIs at the comparison HC were 16.1% and 33.3%, respectively. DISCUSSION: In the SARS-CoV-2 Delta variant surge, COVID-19 test positivity rates among unvaccinated symptomatic HCWs are dramatically elevated. Aggressive testing of HCW PUIs is particularly critical during periods of disease upsurge.

Temporal Trends in COVID-19 Incidence in Two Healthcare Worker Cohorts.

BACKGROUND: Health care workers (HCWs) experience increased occupational risk of contracting COVID-19, with temporal trends that might inform surveillance. METHODS: We analyzed data from a Veterans Affairs hospital-based COVID-19 worker telephone hotline collected over 40 weeks (2020). We calculated the proportion of COVID-19+ cases among persons-under-investigation (PUIs) for illness compared to rates from a nearby large university-based health care institution. RESULTS: We observed 740 PUIs, 65 (8.8%) COVID-19+. Time trends were similar at the study and comparison hospitals; only for the first of 10 four-week observation periods was the ratio for observed to expected COVID-19+ significant (P < 0.001). DISCUSSION: These data suggest that employee health COVID-19+ to PUI ratios could be utilized as a barometer of community trends. Pooling experience among heath care facilities may yield insights into occupational infectious disease outbreaks.

A universal trade-off between growth and lag in fluctuating environments.

The rate of cell growth is crucial for bacterial fitness and drives the allocation of bacterial resources, affecting, for example, the expression levels of proteins dedicated to metabolism and biosynthesis1,2. It is unclear, however, what ultimately determines growth rates in different environmental conditions. Moreover, increasing evidence suggests that other objectives are also important3-7, such as the rate of physiological adaptation to changing environments8,9. A common challenge for cells is that these objectives cannot be independently optimized, and maximizing one often reduces another. Many such trade-offs have indeed been hypothesized on the basis of qualitative correlative studies8-11. Here we report a trade-off between steady-state growth rate and physiological adaptability in Escherichia coli, observed when a growing culture is abruptly shifted from a preferred carbon source such as glucose to fermentation products such as acetate. These metabolic transitions, common for enteric bacteria, are often accompanied by multi-hour lags before growth resumes. Metabolomic analysis reveals that long lags result from the depletion of key metabolites that follows the sudden reversal in the central carbon flux owing to the imposed nutrient shifts. A model of sequential flux limitation not only explains the observed trade-off between growth and adaptability, but also allows quantitative predictions regarding the universal occurrence of such tradeoffs, based on the opposing enzyme requirements of glycolysis versus gluconeogenesis. We validate these predictions experimentally for many different nutrient shifts in E. coli, as well as for other respiro-fermentative microorganisms, including Bacillus subtilis and Saccharomyces cerevisiae.