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Uluseker, C.

Publications and source records attributed to Uluseker, C..

2 recordsLinked to original sources

Inferring antibiotic resistance selection in the environment can be confounded by correlations between resistance genes and unrelated functional traits

Antimicrobial resistance (AMR) is a silent pandemic that is coupled with other crises such as climate change in the polycrisis humanity is facing. One of the key questions is whether antibiotic resistance genes (ARGs) are selected for at the low antibiotic concentrations typical for most environments. Many studies have observed changes in the relative abundance of ARGs from one environmental compartment to the next, e.g. from wastewater treatment plant influent to effluent. Fewer studies have directly tested for selection by incubating environmental samples in mesocosms or laboratory models at different concentrations of antibiotics to infer minimal selective concentrations. We developed a mathematical model to demonstrate that these studies can be confounded by shifts in the microbial community composition that occur when a microbiome is transported from one environmental compartment to another or when incubated under different conditions. Such community shifts will confound tests of selection when there is an association between carriage of ARGs and other functional traits. As an example, we show that there is a phylum-dependent association between the number of ARGs and the number of ribosomal RNA genes, which are both higher in fast growing, copiotrophic bacteria. We then show that specific growth rate or nutrient concentration upshifts increased the proportion of copiotrophs in the community and thus the relative abundance of ARGs. This result generalizes to community shifts for other reasons if there is some association between ARGs and ecological niches. Therefore, most studies of selection for ARGs in the environment are confounded. Solutions are proposed. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=76 SRC="FIGDIR/small/681873v1_ufig1.gif" ALT="Figure 1"> View larger version (20K): org.highwire.dtl.DTLVardef@1ea4638org.highwire.dtl.DTLVardef@1a8471dorg.highwire.dtl.DTLVardef@d4d127org.highwire.dtl.DTLVardef@1ef891b_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIARG copy numbers are correlated with 16S rRNA gene copy numbers C_LIO_LIHigh rRNA gene numbers are typical for copiotrophs, which have high growth rates C_LIO_LIHence, copiotrophs tend to have higher ARG numbers C_LIO_LIChanges in environmental conditions that increase copiotrophs increase ARGs C_LIO_LIThus, ARGs can increase without selection due to shifts in community composition C_LI

microbiology↗

Field monitoring and hydraulic modelling quantify untreated wastewater as dominant source of AMR in a small river running through a big city

Quantifying sources of antimicrobial resistance (AMR) in rivers receiving various waste streams is essential for targeting mitigation strategies yet rarely performed. This study combined field monitoring with hydraulic modelling and mass balance calculations to attribute sources of AMR in the Musi River running through Hyderabad, India, a city renowned for pharmaceutical manufacturing. We quantified antibiotic resistance genes (ARGs), resistant bacteria (ARBs), and physicochemical parameters in water and sediment samples in the dry and wet season. Absolute ARG and ARB abundances spiked in the city, declining again downstream. Changes were more gradual in the wet season. Pollution levels were significantly different between upstream, city and downstream stretches and seasons. Hydraulic modelling revealed that 60-80% or 20-40% of the river water in the city derived from untreated sewage during the dry or wet seasons, respectively. This established municipal waste, not pharmaceutical sources, as the dominant driver of AMR in the Musi. Linear discriminant analysis identified dissolved oxygen and total nitrogen as reliable proxies for distinguishing AMR-polluted from less-polluted sites. The Musi, with insufficient wastewater treatment and limited dilution of point-source loadings, is typical for many urban rivers in resource-limited countries highlighting the urgent need for improved wastewater management to reduce AMR exposures.

microbiology↗