Biology subjects

Arora-Williams, K.

Publications and source records attributed to Arora-Williams, K..

3 recordsLinked to original sources

bioRxiv2026

Microbial community response and recovery through an aeration-cessation time series in a eutrophic estuary

Eutrophication-driven hypoxia and harmful algal blooms are an expanding threat to water quality in estuaries. Engineered aeration is a technology used in freshwater and, to a lesser extent, estuarine systems to mitigate both hypoxia and algal blooms. However, the efficacy of engineered aeration has not been well studied within estuarine ecosystems and very little is known about the impact of aeration on microbial communities in either estuarine or freshwater environments. Here we present a time series investigation of microbial community response to aeration and cessation of aeration in a eutrophic estuary. Samples for 16S rRNA gene analysis were collected over about a month-long period during which time the aerators transitioned from being "on" to "off" to "on" again. Cessation of aeration selected for the dominance of a eukaryotic algae similar to Heterosigma akashiwo. After the resumption of aeration, H. akashiwo dominance decreased rapidly. Cessation of aeration also shifted the structure of the entire microbial community, where diversity decreased and the structure of microbial communities at the surface diverged from those from the bottom of the water column. These changes did not occur at non-aerated control sites. Distinct groups of taxa responded to the disruption in a successional pattern through time, with most taxa never returning to their pre-aeration-cessation abundance during the observational period. These findings demonstrate the complex community response to anthropogenic interventions and provide support for bloom suppression through aeration.

microbiology↗

bioRxiv2023

Major trends and environmental correlates of spatiotemporal shifts in the distribution of genes compared to a biogeochemical model simulation in the Chesapeake Bay

Microorganisms mediate critical biogeochemical transformations that affect the productivity and health of aquatic ecosystems. Metagenomic sequencing can be used to identify how the taxonomic and functional potential of microbial communities change in response to environmental variables by investigating changes in microbial genes. However, few studies directly compare gene changes to biogeochemical model predictions of corresponding processes, especially in dynamic estuarine ecosystems. We aim to understand the major drivers of spatiotemporal shifts in microbial genes and genomes within the water column of the Chesapeake and highlight the largest discrepancies of these observations with model predictions. We used a previously published shotgun metagenomic dataset from multiple months, sites, and depths within Chesapeake Bay in 2017 and a metatranscriptomic dataset from 2010-2011. We compared metagenomic observations with rates predicted with a comprehensive physical-biogeochemical model of the Bay. We found the largest changes in the relative abundance of genes involved in carbon, nitrogen, and sulfur metabolism associated with variables that change with depth and season. Several genes associated with the largest changes in gene abundance are significantly correlated to corresponding modeled processes. Yet, several discrepancies in key genes were identified, such as differences between genes mediating nitrification, higher than expected abundance and expression of denitrification genes in aerobic waters, and nitrogen fixation genes in environments with relatively high ammonia but low oxygen concentrations. This study identifies processes that align with model expectations and others that require additional investigation to determine the biogeochemical consequences of these discrepancies and their impact within an important estuarine ecosystem.

microbiology↗

bioRxiv2020

Capturing in situ Virus-Host Range and Interaction Dynamics through Gene Fusion with epicPCR

Viruses impact microbial diversity, phenotype, and gene flow through virus-host interactions that in turn alter ecology and biogeochemistry. Though metagenomics surveys are rapidly cataloging viral diversity, capturing specific virus-host interactions in situ would identify hosts for novel viruses and reveal influential ecological or environmental factors. We leveraged metagenomics and a high-throughput, cultivation-independent gene fusion technique (epicPCR) to investigate viral diversity and virus-host interactions over time in a critical estuarine environment, the Chesapeake Bay. EpicPCR captured in situ virus-host interactions for viral clades with no closely related database representatives. Abundant freshwater Actinobacteria lineages were the most common hosts for these poorly characterized viruses, and observed viral interactions with one abundant Actinobacterial population (Rhodoluna) were correlated with environmental factors. Tracking virus-host interaction dynamics also revealed ecological differences between multi-host (generalist) and single-host (specialist) viruses. Generalist viruses had significantly longer periods with observed virus-host interactions but specialist viruses were observed interacting with hosts at lower minimum abundances, suggesting more efficient interactions. Together, these observations reveal ecological differences between generalist and specialist viruses that provide insight into evolutionary trade-offs. Capturing in situ interactions with epicPCR revealed environmental and ecological factors that shape virus-host interactions, highlighting epicPCR as a scalable new tool in viral ecology.

microbiology↗