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Wastewater treatment plants consolidate high loads of fecal and environmental bacteria and residual concentrations of antibiotics and consequentially, effluents released from these facilities may contribute to antibiotic resistance in downstream ecosystems. This is especially relevant in arid and semi-arid environments, where treated wastewater (TWW) is used for irrigation. The goal of this study was to pinpoint key antibiotic resistance genes (ARGs) in wastewater effluents and to determine the impact of TWW irrigation on antibiotic resistance in terrestrial and food-associated microbiomes. The diversity and abundance of ARGs was evaluated in wastewater effluents, in TWW -irrigated soils and in crops irrigated with TWW using state of the art molecular, genomic and bioinformatic analyses. Three specific methods were applied: (A) a novel high-throughput amplicon sequencing methodology that specifically targeted ARGs associated with integron gene cassettes in effluents from 12 wastewater treatment facilities across Europe and in pristine vs. wastewater effluent-saturated soil; (B) quantitative PCR that assessed the abundance of selected ARGs along freshwater- and TWW-irrigated, water-soil-crop continuum; and (C) comparative in-silico-based analyses of human gut, wastewater and soil metagenomes to determine specific associations between wastewater and soil resistomes. Our results reveal that wastewater effluents contain a diverse array of ARGs, and that specific ARGs and class 1 integrons (mobile genetic elements that often harbor ARGs) are profuse and strongly associated with wastewater effluents. In contrast we found that other ARGs that are ubiquitous to soil regardless of TWW irrigation suggesting that these elements are common in environmental microbiomes. Collectively, the study indicates the distribution of ARGs in the environment is highly complex and is impacted by both natural and anthropogenic factors, and that while the impact of wastewater-derived ARGs in TWW-irrigated soils is limited, there is evidence that plasmid- and integron-associated ARGs are disseminated to soil microbiomes.

Nonlinear optical processes play a central role in many quantum information devices. I will describe our recent work in which we explore the use of quantum frequency conversion based on four-wave mixing to process photons with high quantum efficiency without adding noise. I will describe how we use this conversion process to create a single-photon Ramsey interferometer, temporally magnify photon wavepackets, and perform frequency multiplexing to create a quasi-deterministic photon source.

The protein degradation machinery in cells plays a critical role in the maintenance of homeostasis, preventing the accumulation of damaged or misfolded proteins and controlling the levels of regulatory proteins. The predominant degradation pathway involves the ubiquitin-dependent 26S proteasome, however recent evidence has identified an alternate ubiquitin-independent pathway involving only the 20S core particle of the proteasome. The regulatory mechanisms controlling its function are poorly understood, and only a small number of regulators have been identified. Using a combination of bioinformatics, structural and in vivo analyses, as well as native mass spectrometry techniques, new 20S proteasome regulatory proteins were identified, hinting towards an as yet undescribed regulatory network of the 20S proteasome.

The ability to computationally design efficient,
specific enzymes is a rigorous test of our understanding of the principles of catalysis and molecular recognition.
Successful designs have to date shown several limitations:
they only targeted simple reactions, involving two to three catalytic residues with low efficiencies and selectivities, and impaired stability. We developed a new algorithm using Rosetta to combine compatible backbone fragments from natural enzymes of the
same enzyme superfamily to generate novel conformations. The designs’ sequences are then optimized, guided by sequence conservation data to improve stability and expressibility. We used the algorithm to design novel TIM barrel fold enzymes belonging to the
GH10 family capable of hydrolyzing xylan, an abundant plant polysaccharide, with Kcat/Km values similar to those of natural xylanases. The designed enzyme conformations differ from one another and from any other known natural xylanase conformations and have
different substrate specificities.
The algorithm is completely automated and can be
applied to other enzymes of modular fold to efficiently and broadly explore the potential selectivities of the superfamily.