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Russell, J. R.

Publications and source records attributed to Russell, J. R..

4 recordsLinked to original sources

Environmental DNA Reveals Reykjavik's Human and Ecological History

Iceland was among the last large islands settled by humans, with colonization (Landnam) in the late 9th century CE (Common Era) and is often portrayed as an ecological disaster driven by the Norse settlers. Here, we revisit this narrative through environmental DNA (eDNA) and multiproxy analyses of sediment cores from Lake Tjornin in central Reykjavik, one of Icelands earliest and longest-occupied settlements. Originally a marine embayment, Tjornin became a freshwater lake around 660 CE. Our record reveals a human presence decades before the long-accepted arrival date of 877 CE, marked by the Landnam volcanic tephra. Early settlement brought livestock, barley cultivation, and other introduced taxa that enhanced nutrient cycling and unexpectedly increased local biodiversity. Contrary to the conventional view of rapid deforestation, eDNA shows that birch and willow expanded during the settlement period, likely supported by deliberate management. Pronounced ecological and land use shifts occurred after 1200 CE, but these were coeval with the Little Ice Age cooling, compounded by volcanic eruptions, storm surges, and plague, rather than anthropogenic degradation. Crop cultivation ceased, arboreal taxa retracted, and grazing pressure maintained open landscapes. Even more profound ecological changes came after c. 1750 CE with urbanization and industrialization, as wastewater discharge, heavy-metal pollution, and fossil fuel use reshaped Tjornins ecosystem. These findings challenge the prevailing model of Norse-induced environmental collapse, revealing instead a dynamic human-environment relationship shaped by both cultural practices and external stressors. By applying eDNA to a long-occupied urban catchment, we demonstrate the power of genomic methods to refine settlement chronologies, reassess ecological baselines and changes, and integrate natural and cultural histories. This approach offers a model for revisiting human-environment interactions in urban centers worldwide.

genomics↗

Vector genetics, insecticide resistance and gene drives: an agent-based modeling approach to evaluate malaria transmission and elimination

Vector control has been a key component in the fight against malaria for decades, and chemical insecticides are critical to the success of vector control programs worldwide. However, increasing resistance to insecticides threatens to undermine these efforts. Understanding the evolution and propagation of resistance is thus imperative to mitigating loss of intervention effectiveness. Additionally, accelerated research and development of new tools that can be deployed alongside existing vector control strategies is key to eradicating malaria in the near future. Methods such as gene drives that aim to genetically modify large mosquito populations in the wild to either render them refractory to malaria or impair their reproduction may prove invaluable tools. Mathematical models of gene flow in populations, which is the transfer of genetic information from one population to another through migration, can offer invaluable insight into the behavior and potential impact of gene drives as well as the spread of insecticide resistance in the wild. Here, we present the first multi-locus, agent-based model of vector genetics that accounts for mutations and a many-to-many mapping cardinality of genotypes to phenotypes to investigate gene flow, and the propagation of gene drives in Anopheline populations. This model is embedded within a large scale individual-based model of malaria transmission representative of a high burden, high transmission setting characteristic of the Sahel. Results are presented for the selection of insecticide-resistant vectors and the spread of resistance through repeated deployment of insecticide treated nets (ITNs), in addition to scenarios where gene drives act in concert with existing vector control tools such as ITNs. The roles of seasonality, spatial distribution of vector habitat and feed sites, and existing vector control in propagating alleles that confer phenotypic traits via gene drives that result in reduced transmission are explored. The ability to model a spectrum of vector species with different genotypes and phenotypes in the context of malaria transmission allows us to test deployment strategies for existing interventions that reduce the deleterious effects of resistance and allows exploration of the impact of new tools being proposed or developed. Author summaryVector control interventions are essential to the success of global malaria control and elimination efforts but increasing insecticide resistance worldwide threatens to derail these efforts. Releasing genetically modified mosquitoes that use gene drives to pass on desired genes and their associated phenotypic traits to the entire population within a few generations has been proposed to address resistance and other issues such as transmission heterogeneity that can sustain malaria transmission indefinitely. While the ethics and safety of these methods are being debated, mathematical models offer an efficient way of predicting the behavior and estimating the efficacy of these interventions if deployed to specific regions facing challenges to reaching elimination. We have developed a detailed mathematical model of vector genetics where specific genomes code for physical attributes that influence transmission and are affected by the surrounding environment. This is the first model to incorporate an individual-based multi-locus genetic model into a detailed individual-based model of malaria transmission. This model opens the door to investigate a number of subtle but important questions such as the effects of small numbers of mosquitoes in a region sustaining malaria transmission during the low transmission season, and the success of gene drives in regions where extant vector control interventions could kill off gene drive mosquitoes before establishment. Here, we investigate the reduced efficacy of current vector control measures in the presence of insecticide resistance and evaluate the likelihood of achieving local malaria elimination using gene drive mosquitoes released into a high transmission setting alongside other vector control measures.

genetics↗

Environmental DNA for the enumeration and management of Pacific salmon

Pacific salmon are a keystone resource in Alaska, generating annual revenues of well over [~]US$500 million/yr. Due to their anadromous life history, adult spawners distribute amongst thousands of streams, posing a huge management challenge. Currently, spawners are enumerated at just a few streams because of reliance on human counters and, rarely, sonar. The ability to detect organisms by shed tissue (environmental DNA, eDNA) promises a more efficient counting method. However, although eDNA correlates generally with local fish abundances, we do not know if eDNA can accurately enumerate salmon. Here we show that daily, and near-daily, flow-corrected eDNA rate closely tracks daily numbers of returning sockeye and coho spawners and outmigrating sockeye smolts. eDNA thus promises accurate and efficient enumeration, but to deliver the most robust numbers will need higher-resolution stream-flow data, at-least-daily sampling, and a focus on species with simple life histories, since shedding rate varies amongst jacks, juveniles, and adults.

ecology↗

The miR-96/RARγ signaling axis governs androgen signaling and PCa progression

Expression levels of retinoic acid receptor gamma (NR1B3/RARG, encodes RAR{gamma}), are commonly reduced in prostate cancer (PCa). Therefore we sought to establish the cellular and gene regulatory consequences of reduced RAR{gamma} expression, and determine RAR{gamma} regulatory mechanisms. RARG shRNA approaches in non-malignant (RWPE-1 and HPr1-AR) and malignant (LNCaP) prostate models revealed that reducing RAR{gamma} levels, rather than adding exogenous retinoid ligand, had the greatest impact on prostate cell viability and gene expression. ChIP-Seq defined the RAR{gamma} cistrome which was significantly enriched at active enhancers associated with AR binding sites. Reflecting a significant genomic role for RAR{gamma} to regulate androgen signaling, RAR{gamma} knockdown in HPr1-AR cells significantly regulated the magnitude of the AR transcriptome. RAR{gamma} down-regulation was explained by increased miR-96 in PCa cell and mouse models, and TCGA PCa cohorts. Biochemical approaches confirmed that miR-96 directly regulated RAR{gamma} expression and function Capture of the miR-96 targetome by biotin-miR96 identified that RAR{gamma} and a number of RAR{gamma} interacting co-factors including TACC1 were all targeted by miR-96, and expression of these genes were prominently altered, positively and negatively, in the TCGA-PRAD cohort. Differential gene expression analyses between tumors in the TCGA-PRAD cohort with lower quartile expression levels of RARG and TACC1 and upper quartile miR-96, compared to the reverse, identified a gene network including several RAR{gamma} target genes (e.g. SOX15) that significantly associated with worse disease free survival (hazard ratio 2.23, 95% CI 1.58 to 2.88, p=0.015). In summary, miR-96 targets a RAR{gamma} network to govern AR signaling, PCa progression and disease outcome.\n\nConflict of interestThe authors certify that they have NO affiliations with or involvement in any organization or entity with any financial interest (such as honoraria; educational grants; participation in speakers bureaus; membership, employment, consultancies, stock ownership, or other equity interest; and expert testimony or patent-licensing arrangements), or non-financial interest (such as personal or professional relationships, affiliations, knowledge or beliefs) in the subject matter or materials discussed in this manuscript.\n\nFUNDINGLESC acknowledges support, in part, of Roswell Park Comprehensive Cancer Center-University of Pittsburg Cancer Institute Ovarian Cancer Specialized Program of Research Excellence National Institutes of Health [P50CA159981-01A1].\n\nMDL acknowledges support of Molecular Pharmacology and Experimental Therapeutics NRSA T32 program [T32CA009072] held at Roswell Park Comprehensive Cancer Center.\n\nMJC and DJS acknowledges support in part from the Prostate program of the Department of Defense Congressionally Directed Medical Research Programs [W81XWH-14-1-0608, W81XWH-11-2-0033] and the National Cancer Institute (NCI) grant P30CA016056 involving the use of Roswell Park Comprehensive Cancer Centers Genomic Shared Resource.\n\nMJC, GL, AR, HW and PvdB acknowledges support from the European Union-United States Atlantis Program [P116J090011].\n\nMJC and LESC acknowledge support from the National Cancer Institute (NCI) grant P30CA016056 involving the use of OSUCCC The James, CCSG P30CA016058

cancer biology↗