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From a metabolic perspective, molecular oxygen (O2) is arguably the most significant constituent of Earth’s atmosphere. Nearly every facet of microbial physiology is sensitive to the presence and concentration of O2, which is the most favorable terminal electron acceptor used by biological organisms and also a dangerously reactive oxidant. As O2 has such sweeping implications for physiology, researchers have developed diverse approaches to measure O2 concentrations in natural and laboratory settings. Recent improvements to phosphorescent O2 sensors piqued our interest due to the promise of optical measurement of spatiotemporal O2 dynamics. However, we found that our preferred bacterial model, Pseudomonas aeruginosa PA14, secretes more than one molecule that quenches such sensors, complicating O2 measurements in PA14 cultures and biofilms. Assaying supernatants from cultures of 9 bacterial species demonstrated that this phenotype is common: all supernatants quenched a soluble O2 probe substantially. Phosphorescent O2 probes are often embedded in solid support for protection, but an embedded probe called O2NS was quenched by most supernatants as well. Measurements using pure compounds indicated that quenching is due to interactions with redox-active small molecules including phenazines and flavins. Uncharged and weakly-polar molecules like pyocyanin were especially potent quenchers of O2NS. These findings underscore that optical O2 measurements made in the presence of bacteria should be carefully controlled to ensure that O2, and not bacterial secretions, is measured, and motivate the design of custom O2 probes for specific organisms to circumvent sensitivity to redox-active metabolites.ImportanceWhen they are closely-packed, as in biofilms, colonies, and soils, microbes can consume O2 faster than it diffuses. As such, O2 concentrations in natural environments can vary greatly over time and space, even on the micrometer scale. Wetting soil, for example, slows O2 diffusion higher in the soil column, which, in concert with microbial respiration, greatly diminishes [O2] at depth. Given that variation in [O2] has outsized implications for microbial physiology, there is great interest in measuring the dynamics of [O2] in microbial cultures and biofilms. We demonstrate that certain classes of bacterial metabolites frustrate optical measurement of [O2] with phosphorescent sensors, but also that some species (e.g. E. coli) do not produce problematic secretions under the conditions tested. Our work therefore offers a strategy for identifying organisms and culture conditions in which optical quantification of spatiotemporal [O2] dynamics with current sensors is feasible.

The history of Earth’s carbon cycle reflects trends in atmospheric composition convolved with the evolution of photosynthesis. Fortunately, key parts of the carbon cycle have been recorded in the carbon isotope ratios of sedimentary rocks. The dominant model used to interpret this record as a proxy for ancient atmospheric CO2is based on carbon isotope fractionations of modern photoautotrophs, and longstanding questions remain about how their evolution might have impacted the record. We tested the intersection of environment and evolution by measuring both biomass (εp) and enzymatic (εRubisco) carbon isotope fractionations of a cyanobacterial strain (Synechococcus elongatusPCC 7942) solely expressing a putative ancestral Form 1B rubisco dating to ≫1 Ga. This strain, nicknamed ANC, grows in ambient pCO2and displays larger εpvalues than WT, despite having a much smaller εRubisco(17.23 ± 0.61‰ vs. 25.18 ± 0.31‰ respectively). Measuring both enzymatic and biomass fractionation revealed a surprising result—ANC εpexceeded ANC εRubiscoin all conditions tested, contradicting prevailing models of cyanobacterial carbon isotope fractionation. However, these models were corrected by accounting for cyanobacterial physiology, notably the CO2concentrating mechanism (CCM). Our model suggested that additional fractionating processes like powered inorganic carbon uptake systems contribute to εp, and this effect is exacerbated in ANC. Understanding the evolution of rubisco and the CCM is therefore critical for interpreting the carbon isotope record. Large fluctuations in that record may reflect the evolving efficiency of carbon fixing metabolisms in addition to changes in atmospheric CO2.Significance StatementEarth scientists rely on chemical fossils like the carbon isotope record to derive ancient atmospheric CO2concentrations, but interpretation of this record is calibrated using modern organisms. We tested this assumption by measuring the carbon isotope fractionation of a reconstructed ancestral rubisco enzyme (>1 billion years old)in vivoandin vitro. Our results contradicted prevailing models of carbon flow in Cyanobacteria, but our data could be rationalized if light-driven uptake of CO2is taken into account. Our study showed that the carbon isotope record tracks both the evolution of photosynthesis physiology as well as changes in atmospheric CO2, highlighting the value of considering both evolution and physiology for comparative biological approaches to understanding Earth’s history.

Cyanobacteria rely on CO2 concentrating mechanisms (CCMs) that depend on ≈15 genes to produce two protein complexes: an inorganic carbon (Ci) transporter and a 100+ nm carboxysome compartment that encapsulates rubisco with a carbonic anhydrase (CA) enzyme. Mutations disrupting CCM components prohibit growth in today’s atmosphere (0.04% CO2), indicating that CCMs evolved to cope with declining environmental CO2. Indeed, geochemical data and models indicate that atmospheric CO2 has been generally decreasing from high concentrations over the last ≈3.5 billion years. We used a synthetic reconstitution of a bacterial CCM in E. coli to study the co-evolution of CCMs with atmospheric CO2. We constructed strains expressing putative ancestors of modern CCMs — strains lacking one or more CCM components — and evaluated their growth in a variety of CO2 concentrations. Partial forms expressing CA or Ci uptake genes grew better than controls in intermediate CO2 levels (≈1%); we observed similar phenotypes in genetic studies of two autotrophic bacteria, H. neapolitanus and C. necator. To explain how partial CCMs improve growth, we advance a model of co-limitation of autotrophic growth by CO2 and HCO3-, as both are required to produce biomass. Our model and results delineated a viable trajectory for bacterial CCM evolution where decreasing atmospheric CO2 induces an HCO3- deficiency that is alleviated by acquisition of CAs or Ci uptake genes, thereby enabling the emergence of a modern CCM. This work underscores the importance of considering physiology and environmental context when studying the evolution of biological complexity.SignificanceThe greenhouse gas content of the ancient atmosphere is estimated using models and measurements of geochemical proxies. Some inferred high ancient CO2 levels using models of biological CO2 fixation to interpret the C isotopes found in preserved organic matter. Others argued that elevated CO2 could reconcile a faint young Sun with evidence for liquid water on Earth. We took a complementary “synthetic biological” approach to understanding the composition of the ancient atmosphere by studying present-day bacteria engineered to resemble ancient autotrophs. By showing that it is simpler to rationalize the emergence of modern bacterial autotrophs if CO2 was once high, these investigations provided independent evidence for the view that CO2 concentrations were significantly elevated in the atmosphere of early Earth.

Coenzymes distribute a variety of chemical moieties throughout cellular metabolism, participating in group (e.g., phosphate, acyl) and electron transfer. For a variety of reactions requiring acceptors or donors of specific resources, there often exist degenerate sets of molecules (e.g., NAD(H) and NADP(H)) that carry out similar functions. Although the physiological roles of various coenzyme systems are well established, it is unclear what selective pressures may have driven the emergence of coenzyme redundancy. Here we use genome-wide metabolic modeling approaches to decompose the selective pressures driving enzymatic specificity for either NAD(H) or NADP(H) in the metabolic network ofEscherichia coli. We found that few enzymes are thermodynamically constrained to using a single coenzyme, and in principle, a metabolic network relying on only NAD(H) is feasible. However, structural and sequence analyses revealed widespread conservation of residues that retain selectivity for either NAD(H) or NADP(H), suggesting that additional forces may shape specificity. Using a model accounting for the cost of oxidoreductase enzyme expression, we found that coenzyme redundancy universally reduces the minimal amount of protein required to catalyze coenzyme-coupled reactions, inducing individual reactions to strongly prefer one coenzyme over another when reactions are near thermodynamic equilibrium. We propose that protein minimization generically promotes coenzyme redundancy, and that coenzymes typically thought to exist in a single pool (e.g., CoA) may exist in more than one form (e.g., dephospho-CoA).Significance statementMetabolism relies on a small class of molecules (coenzymes) that serve as universal donors and acceptors of key chemical groups and electrons. Although metabolic networks crucially depend on structurally redundant coenzymes (e.g., NAD(H) and NADP(H)) associated with different enzymes, the criteria that led to the emergence of this redundancy remain poorly understood. Our combination of modeling, and structural and sequence analysis indicates that coenzyme redundancy is not essential for metabolism, but rather an evolved strategy promoting efficient usage of enzymes when biochemical reactions are near equilibrium. Our work suggests that early metabolism may have operated with fewer coenzymes, and that adaptation for metabolic efficiency may have driven the rise of coenzyme diversity in living systems.

Wastewater surveillance for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA can be integrated with COVID-19 case data to inform timely pandemic response. However, more research is needed to apply and develop systematic methods to interpret the true SARS-CoV-2 signal from noise introduced in wastewater samples (e.g., from sewer conditions, sampling and extraction methods, etc.). In this study, raw wastewater was collected weekly from five sewersheds and one residential facility, and wastewater SARS-CoV-2 concentrations were compared to geocoded COVID-19 clinical testing data. SARS-CoV-2 was reliably detected (95% positivity) in frozen wastewater samples when reported daily new COVID-19 cases were 2.4 or more per 100,000 people. To adjust for variation in sample fecal content, crAssphage, pepper mild mottle virus, Bacteroides ribosomal RNA (rRNA), and human 18S rRNA were evaluated as normalization biomarkers, and crAssphage displayed the least spatial and temporal variability. Both unnormalized SARS-CoV-2 RNA signal and signal normalized to crAssphage had positive and significant correlation with clinical testing data (Kendall’s Tau-b (τ)=0.43 and 0.38, respectively). Locational dependencies and the date associated with testing data impacted the lead time of wastewater for clinical trends, and no lead time was observed when the sample collection date (versus the result date) was used for both wastewater and clinical testing data. This study supports that trends in wastewater surveillance data reflect trends in COVID-19 disease occurrence and presents approaches that could be applied to make wastewater signal more interpretable and comparable across studies.

Significance Knowing the absolute numbers of virions in an infection promotes better understanding of disease dynamics and response of the immune system. Here we use current knowledge on the concentrations of virions in infected individuals to estimate the total number and mass of SARS-CoV-2 virions in an infected person. Although each infected person carries an estimated 1 billion to 100 billion virions during peak infection, their total mass is no more than 0.1 mg. This curiously implies that all SARS-CoV-2 virions currently in all human hosts have a mass of between 100 g and 10 kg. Combining the known mutation rate and our estimate of the number of infectious virions, we quantify the formation rate of genetic variants., Quantitatively describing the time course of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection within an infected individual is important for understanding the current global pandemic and possible ways to combat it. Here we integrate the best current knowledge about the typical viral load of SARS-CoV-2 in bodily fluids and host tissues to estimate the total number and mass of SARS-CoV-2 virions in an infected person. We estimate that each infected person carries 109 to 1011 virions during peak infection, with a total mass in the range of 1 μg to 100 μg, which curiously implies that all SARS-CoV-2 virions currently circulating within human hosts have a collective mass of only 0.1 kg to 10 kg. We combine our estimates with the available literature on host immune response and viral mutation rates to demonstrate how antibodies markedly outnumber the spike proteins, and the genetic diversity of virions in an infected host covers all possible single nucleotide substitutions.

Many photosynthetic organisms employ a CO2concentrating mechanism (CCM) to increase the rate of CO2fixation via the Calvin cycle. CCMs catalyze ≈50% of global photosynthesis, yet it remains unclear which genes and proteins are required to produce this complex adaptation. We describe the construction of a functional CCM in a non-native host, achieved by expressing genes from an autotrophic bacterium in an engineeredE. colistrain. Expression of 20 CCM genes enabledE. colito grow by fixing CO2from ambient air into biomass, with growth depending on CCM components. Bacterial CCMs are therefore genetically compact and readily transplanted, rationalizing their presence in diverse bacteria. Reconstitution enabled genetic experiments refining our understanding of the CCM, thereby laying the groundwork for deeper study and engineering of the cell biology supporting CO2assimilation in diverse organisms.One Sentence SummaryA bacterial CO2concentrating mechanism enablesE. colito fix CO2from ambient air.

Carbon fixation via the Calvin cycle is constrained by the side activity of Rubisco with dioxygen, generating 2-phosphoglycolate. The metabolic recycling of 2-phosphoglycolate, an essential process termed photorespiration, was extensively studied in photoautotrophic organisms, including plants, algae, and cyanobacteria, but remains uncharacterized in chemolithoautotrophic bacteria. Here, we study photorespiration in the model chemolithoautotroph Cupriavidus necator (Ralstonia eutropha) by characterizing the proxy-process of glycolate metabolism, performing comparative transcriptomics of autotrophic growth under low and high CO2 concentrations, and testing autotrophic growth phenotypes of gene deletion strains at ambient CO2. We find that the canonical plant-like C2 cycle does not operate in this bacterium and instead the bacterial-like glycerate pathway is the main photorespiratory pathway. Upon disruption of the glycerate pathway, we find that an oxidative pathway, which we term the malate cycle, supports photorespiration. In this cycle, glyoxylate is condensed with acetyl-CoA to give malate, which undergoes two oxidative decarboxylation steps to regenerate acetyl-CoA. When both pathways are disrupted, autotrophic growth is abolished at ambient CO2. We present bioinformatic data suggesting that the malate cycle may support photorespiration in diverse chemolithoautotrophic bacteria. This study thus demonstrates a so-far unknown photorespiration pathway, highlighting important diversity in microbial carbon fixation metabolism.

Many bacterial autotrophs rely on CO2concentrating mechanisms (CCMs) to assimilate carbon. Although many CCM proteins have been identified, including a 200+ MDa protein organelle called the carboxysome, a systematic screen of CCM components has not been carried out. Here, we performed a genome-wide barcoded transposon screen to identify essential and CCM-related genes in the ɣ-proteobacteriumH. neapolitanus. Our screen revealed an operon critical for CCM function which encodes a domain of unknown function (PFAM:PF10070) and putative cation transporter subunit (PFAM:PF00361). These two proteins, which we name DabA and DabB for “DABs accumulate bicarbonate,” function as a heterodimeric, energy-coupled inorganic carbon pump inE. coli. Furthermore, DabA binds zinc and has a an active site homologous to a β-carbonic anhydrase. Based on these results, we propose that DABs function as vectorial CAs coupled to cation gradients and serve as inorganic carbon pumps throughout prokaryotic phyla.

Rubisco is the most abundant enzyme in the biosphere and one of the best-characterized enzymes. Based on correlations between Rubisco kinetic parameters, it is widely posited that tradeoffs embedded in the catalytic mechanism constrain its specificity and maximum catalytic rate. However, the reasoning that established this view was based on data from ≈20 organisms. We re-examine these tradeoff models using a dataset from ≈300 organisms. Most correlations are substantially attenuated, with the inverse relationship between carboxylation kcat and specificity SC/O being a key example. Only one tradeoff model survives in our dataset. In this model, increasing catalytic efficiency (kcat/KM) for carboxylation requires increased catalytic efficiency for the competing oxygenation reaction, evidenced by strong power-law correlation between catalytic efficiencies. Our results imply that Rubisco evolution is constrained primarily by the physicochemical limits of O2/CO2 discrimination, which should reframe efforts to engineer this very central enzyme.

Thermodynamics dictates the structure and function of metabolism. Redox reactions drive cellular energy and material flow. Hence, accurately quantifying the thermodynamics of redox reactions should reveal key design principles that shape cellular metabolism. However, only a limited number of redox potentials have been measured experimentally, and mostly with inconsistent, poorly-reported experimental setups. Here, we develop a quantum chemistry approach for the calculation of redox potentials of biochemical reactions. We demonstrate that our method predicts experimentally measured potentials with unparalleled accuracy. We calculate the reduction potentials of all redox pairs that can be generated from biochemically relevant compounds and highlight fundamental thermodynamic trends that define cellular redox biochemistry. We further use the calculated potentials to address the question of why NAD/NADP are used as the primary cellular electron carriers, demonstrating how their physiological redox range specifically fits the reactions of central metabolism and minimizes the concentration of reactive carbonyls. The use of quantum chemistry tools, as demonstrated in this study, can revolutionize our understanding of key biochemical phenomena by enabling fast and accurate calculation of large datasets of thermodynamic values.