Wastewater and clinical surveillance of respiratory viral pathogens on a university campus.

Areas of dense population congregation are prone to experience respiratory virus outbreaks. We monitored wastewater and clinic patients for the presence of respiratory viruses on a large, public university campus. Campus sewer systems were monitored in 16 locations for the presence of viruses using next generation sequencing over 22 weeks in 2023. During this period, we detected a surge in human adenovirus (HAdV) levels in wastewater. Hence, we initiated clinical surveillance at an on-campus clinic from patients presenting with acute respiratory infection. From whole genome sequencing of 123 throat and/or nasal swabs collected, we identified an outbreak of HAdV, specifically of HAdV-E4 and HAdV-B7 genotypes overlapping in time. The temporal dynamics and proportions of HAdV genotypes found in wastewater were corroborated in clinical infections. We tracked specific single nucleotide polymorphisms (SNPs) found in clinical virus sequences and showed that they arose in wastewater signals concordant with the time of clinical presentation, linking community transmission of HAdV to the outbreak. This study demonstrates how wastewater-based epidemiology can be integrated with surveillance at ambulatory healthcare settings to monitor areas prone to respiratory virus outbreaks and provide public health guidance.

Human adenovirus outbreak at a university campus monitored by wastewater and clinical surveillance.

Areas of dense population congregation are prone to experience respiratory virus outbreaks. We monitored wastewater and clinic patients for the presence of respiratory viruses on a large, public university campus. Campus sewer systems were monitored in 16 locations for the presence of viruses using next generation sequencing over 22 weeks in 2023. During this period, we detected a surge in human adenovirus (HAdV) levels in wastewater. Hence, we initiated clinical surveillance at an on-campus clinic from patients presenting with acute respiratory infection. From whole genome sequencing of 123 throat and/or nasal swabs collected, we identified an outbreak of HAdV, specifically of HAdV-E4 and HAdV-B7 genotypes overlapping in time. The temporal dynamics and proportions of HAdV genotypes found in wastewater were corroborated in clinical infections. We tracked specific single nucleotide polymorphisms (SNPs) found in clinical virus sequences and showed that they arose in wastewater signals concordant with the time of clinical presentation, linking community transmission of HAdV to the outbreak. This study demonstrates how wastewater-based epidemiology can be integrated with surveillance at ambulatory healthcare settings to monitor areas prone to respiratory virus outbreaks and provide public health guidance.

Chemical-genetic interrogation of RNA polymerase mutants reveals structure-function relationships and physiological tradeoffs.

The multi-subunit bacterial RNA polymerase (RNAP) and its associated regulators carry out transcription and integrate myriad regulatory signals. Numerous studies have interrogated RNAP mechanism, and RNAP mutations drive Escherichia coli adaptation to many health- and industry-relevant environments, yet a paucity of systematic analyses hampers our understanding of the fitness trade-offs from altering RNAP function. Here, we conduct a chemical-genetic analysis of a library of RNAP mutants. We discover phenotypes for non-essential insertions, show that clustering mutant phenotypes increases their predictive power for drawing functional inferences, and demonstrate that some RNA polymerase mutants both decrease average cell length and prevent killing by cell-wall targeting antibiotics. Our findings demonstrate that RNAP chemical-genetic interactions provide a general platform for interrogating structure-function relationships in vivo and for identifying physiological trade-offs of mutations, including those relevant for disease and biotechnology. This strategy should have broad utility for illuminating the role of other important protein complexes.

Bacteria-to-Human Protein Networks Reveal Origins of Endogenous DNA Damage.

DNA damage provokes mutations and cancer and results from external carcinogens or endogenous cellular processes. However, the intrinsic instigators of endogenous DNA damage are poorly understood. Here, we identify proteins that promote endogenous DNA damage when overproduced: the DNA "damage-up" proteins (DDPs). We discover a large network of DDPs in Escherichia coli and deconvolute them into six function clusters, demonstrating DDP mechanisms in three: reactive oxygen increase by transmembrane transporters, chromosome loss by replisome binding, and replication stalling by transcription factors. Their 284 human homologs are over-represented among known cancer drivers, and their RNAs in tumors predict heavy mutagenesis and a poor prognosis. Half of the tested human homologs promote DNA damage and mutation when overproduced in human cells, with DNA damage-elevating mechanisms like those in E. coli. Our work identifies networks of DDPs that provoke endogenous DNA damage and may reveal DNA damage-associated functions of many human known and newly implicated cancer-promoting proteins.

Isolation and mapping of self-assembling protein domains encoded by the Saccharomyces cerevisiae genome using lambda repressor fusions.

Understanding how proteins are able to form stable complexes is of fundamental interest from the perspective of protein structure and function. Here we show that lambda repressor fusions can be used to identify and characterize homotypic interaction domains encoded by the genome of Saccharomyces cerevisiae, using a selection for polypeptides that can drive the assembly of the DNA binding domain of bacteriophage lambda repressor. Three high complexity libraries were constructed by cloning random fragments of S. cerevisiae DNA as lambda repressor fusions. Repressor fusions encoding homotypic interactions were recovered, identifying oligomerization units in 35 yeast proteins. Seventeen of these interaction domains have not been previously reported, while the other 18 represent homotypic interactions that have been characterized at varying levels of detail. The novel interactions include several predicted coiled-coils as well as domains of unknown structure. With the availability of genomic sequences it should be possible to apply this approach, which provides information about protein-protein interactions that is complementary to that obtained from yeast two-hybrid screens, on a genome-wide scale in yeast or other organisms where large-scale protein-protein interaction data is not available.