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ABSTRACT Aerobes require dioxygen (O2) to grow; anaerobes do not. However, nearly all microbes—aerobes, anaerobes, and facultative organisms alike—express enzymes whose substrates include O2, if only for detoxification. This presents a challenge when trying to assess which organisms are aerobic from genomic data alone. This challenge can be overcome by noting that O2 utilization has wide-ranging effects on microbes: aerobes typically have larger genomes encoding distinctive O2-utilizing enzymes, for example. These effects permit high-quality prediction of O2 utilization from annotated genome sequences, with several models displaying ≈80% accuracy on a ternary classification task for which blind guessing is only 33% accurate. Since genome annotation is compute-intensive and relies on many assumptions, we asked if annotation-free methods also perform well. We discovered that simple and efficient models based entirely on genomic sequence content—e.g., triplets of amino acids—perform as well as intensive annotation-based classifiers, enabling rapid processing of genomes. We further show that amino acid trimers are useful because they encode information about protein composition and phylogeny. To showcase the utility of rapid prediction, we estimated the prevalence of aerobes and anaerobes in diverse natural environments cataloged in the Earth Microbiome Project. Focusing on a well-studied O2 gradient in the Black Sea, we found quantitative correspondence between local chemistry (O2:sulfide concentration ratio) and the composition of microbial communities. We, therefore, suggest that statistical methods like ours might be used to estimate, or “sense,” pivotal features of the chemical environment using DNA sequencing data.IMPORTANCEWe now have access to sequence data from a wide variety of natural environments. These data document a bewildering diversity of microbes, many known only from their genomes. Physiology—an organism’s capacity to engage metabolically with its environment—may provide a more useful lens than taxonomy for understanding microbial communities. As an example of this broader principle, we developed algorithms that accurately predict microbial dioxygen utilization directly from genome sequences without annotating genes, e.g., by considering only the amino acids in protein sequences. Annotation-free algorithms enable rapid characterization of natural samples, highlighting quantitative correspondence between sequences and local O2 levels in a data set from the Black Sea. This example suggests that DNA sequencing might be repurposed as a multi-pronged chemical sensor, estimating concentrations of O2 and other key facets of complex natural settings.

ABSTRACT 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 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. IMPORTANCE When 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.

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. The concentrations of SARS-CoV-2 in wastewater samples 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, four normalization biomarkers were evaluated: crAssphage, pepper mild mottle virus, Bacteroides ribosomal RNA (rRNA), and human 18S rRNA. Of these, 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), but no normalization biomarker strengthened the correlation with clinical testing data. 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 tools that could be applied to make wastewater signal more interpretable and comparable across studies.

Many photosynthetic organisms employ a CO2 concentrating mechanism (CCM) to increase the rate of CO2 fixation 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 Escherichia coli strain engineered to depend on rubisco carboxylation for growth. Expression of 20 CCM genes enabled E. coli to grow by fixing CO2 from ambient air into biomass, with growth in ambient air depending on the components of the CCM. 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 CO2 assimilation in diverse organisms.