Technology Networks - The Canada
Clumping of Mussels Into Reefs Increases Risk of Microplastic Exposure and Consumption Three-fold - Technology Networks
Commercially important seafood species are at greater risk of microplastic contamination depending how they clump together in the marine environment, research suggests.
Commercially important seafood species are at greater risk of microplastic contamination depending how they clump together in the marine environment, new research suggests. In the first study of its kind, scientists from the University of Plymouth used a series of experiments to assess whether the reefs formed by blue mussel (Mytilus edulis) affected their exposure and consumption of tiny microplastic particles. They found that when mussels were clumped together forming reefs, as they do in nature, the reef structure slowed the sea water flowing over them, increased turbulence, and resulted in a three-fold rise in the amount of ingested plastic. Writing in Environmental Research Letters, researchers say the study suggests that the arrangement and surface roughness (complexity) of natural reef structures such as that constructed by mussel populations create conditions that make them natural sinks for plastics and other forms of human pollution. They also believe species like the blue mussel, which are important for human consumption but susceptible to microplastic pollution, may be useful indicators of the problem and its potentially harmful biological impacts. The research was led by recent graduate Marine Biology and Oceanography graduate Hyee Shynn Lim from the Universitys Marine Biology and Ecology Research Centre and School of Biological and Marine Sciences. Dr Antony Knights, Associate Professor in Marine Ecology and senior author on the study, said: Species such as the blue mussel are both commercially valuable as seafood but also environmentally important. They form natural reefs within marine and coastal settings which enhance biodiversity to such a degree that they are commonly protected under conservation actions. If they are particularly susceptible to microplastic pollution, there are many potential knock-on effects that we need to be aware of. Often we look to protect reef-forming species based on who they are. However, we are not aware of any research that has shown that the physical structure of reef itself which we have shown can help these filter-feeding organisms to be more effective feeders might also inadvertently increase their exposure to pollutants like microplastic. With no means of addressing this issue, due to our increasing awareness of the quantity of microplastic in the marine environment, this study offers the first evidence that forming a reef is a double-edged sword for individuals. For the research, mussels were placed in controlled aggregations in a water flume and exposed to different wave speeds. Quantities of microplastics added to the water, ordinarily used to characterise the physical properties of the fluid itself (including the density of plastic in and around the reef structure), allowed the team to also assess particle ingestion risk under different environmental scenarios. The study is the latest innovative project from the University examining the causes and impacts of microplastics within the marine environment. It is work which, earlier in 2020, saw the University presented with the Queens Anniversary Prize for Higher and Further Education for its pioneering research into microplastics pollution and its policy impact in the UK and globally. ReferenceLim et al: Spatial arrangement of biogenic reefs alters boundary layer characteristics to increase risk of microplastic bioaccumulation. Environmental Research Letters, DOI: 10.1088/1748-9326/ab83ae. This article has been republished from the following materials. Note: material may have been edited for length and content. For further information, please contact the cited source.
Single-cell RNA Seq Method Accurately Quantifies Cell-specific Drug Effects - Technology Networks
Researchers have developed a method to accurately assess the effect of specific drugs in isolated pancreatic tissue by using a refined single-cell RNA sequencing method.
Researchers from Stefan Kubicek's and Christoph Bocks groups, at the CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences in Vienna, have developed a method to accurately assess the effect of specific drugs in isolated pancreatic tissue by using a refined single-cell RNA sequencing method. Their study published in Genome Biology describes the technique that they have developed to overcome the problem of contaminating RNA molecules in single-cell transcriptomics, which allowed for accurate results of dynamic drug responses in pancreatic cells. These findings will support the development of targeted drug therapies for the treatment of Type 1 diabetes in the future.The pancreas is an abdominal organ that produces digestive enzymes as well as hormones that regulate blood sugar levels. This hormone-producing function is localized to the islets of Langerhans, which constitute clusters of different endocrine cell types. Among those are beta cells, which produce the hormone insulin needed to lower glucose (a type of sugar) levels in our blood, as well as alpha cells, which generate the hormone glucagon in charge of raising glucose levels in the blood. Type 1 diabetes is a chronic disease in which the bodys immune system mistakenly attacks and destroys the pancreas insulin-producing beta cells. Regenerative medicine aims to replenish beta cell mass, and thus support and ultimately substitute the current insulin replacement therapies. Alterations to islet composition, including insufficient beta cell function and beta cell dedifferention, also contribute to type II diabetes. Therefore, a deeper understanding of the identity and crosstalk of the different islet cell types leads to a better characterization of both forms of diabetes and may contribute to the development of novel therapeutic concepts. Single-cell transcriptomics is a powerful technique to characterize cellular identity. Previously, CeMM researchers from Christoph Bocks and Stefan Kubiceks groups at CeMM published the first single cell transcriptomes from primary human pancreatic islet cells. Advances in the technology have since enabled its application to the generation of global human and mouse single cell transcriptome atlases. Despite these advances, single cell approaches remain technologically challenging given that the miniscule RNA amount present is entirely used up in the experiment. Therefore, it is essential to ensure the quality and purity of the resulting single cell transcriptomes. CeMM researchers in the two contributing laboratories identified unexpectedly high hormone expression in non-endocrine cell types, both in their own dataset as well as other published single cell studies. They set out to elucidate whether this would be the result of contamination by RNA molecules, for example from dying cells, and how it could be removed to obtain a more reliable dataset. Such contamination seems present in single cell RNA-seq data from most tissues but was most visible in pancreatic islets. Islet endocrine cells are exclusively devoted to the production of single hormones, and insulin in beta cells and glucagon in alpha cells are expressed to higher levels than typical housekeeping genes. Thus, redistribution of these transcripts to other cell types was highly pronounced. Based on this observation, their goal was to develop, validate and apply a method to experimentally determine and computationally remove such contamination. In their investigation, CeMM researchers used spiked-in cells from different cell types, both mouse and human samples, that they added to their pancreatic islet samples. Importantly, the transcriptomes of these spike-in cell were fully characterized. This allowed them to control internally and accurately the level of RNA contamination in single cell RNA-seq, giving that the human transcripts detected in the mouse spike-in cells constitute contaminating RNA. In this way, they found that the samples had a contamination level of up to 20% and were able to define the contamination in each samples. They then developed a novel bioinformatics approach to computationally remove contaminating reads from single cell transcriptomes. Having now obtained a decontaminated transcriptome, from which the spurious signal has been removed, they proceeded to characterize how the cellular identity in the different cell types responded to the treatment with three different drugs. They found that a small molecule inhibitor of the transcription factor FOXO1 induces dedifferentiation of both alpha and beta cells. Furthermore, they studied artemether, which had been found to diminish the function of alpha cells and could induce insulin production in both in vivo and in vitro studies. The effects of the drug artemether were species-specific and cell-type-specific. In alpha cells, a fraction of cells increase insulin expression and gain aspects of beta cell identity, both in mouse and human samples. Importantly, researchers found that in human beta cells, there is no significant change in insulin expression, whereas in mouse islets, beta cells reduce their insulin expression and overall beta cell identity. This study is the result of a cross-disciplinary collaboration of the laboratories of Stefan Kubicek and Christoph Bock at CeMM with Patrick Collombat at the Institute of Biology Valrose (France). This is the first study to apply single cell sequencing to analyze dynamic drug response in intact isolated tissue, which benefitted from the high quantitative accuracy of the decontamination method. It provides thus not only a novel method for single-cell decontamination and highly quantitative single-cell analysis of drug responses in intact tissues, but also addresses an important current question in islet cell biology and diabetes research. These findings could open up potential therapeutic avenues to treat Type 1 diabetes in the future.ReferenceMarquina-Sanchez et al. (2020). Single-cell RNA-seq with spike-in cells enables accurate quantification of cell-specific drug effects in pancreatic islets. Genome Biology. DOI: https://doi.org/10.1186/s13059-020-02006-2 This article has been republished from the following materials. Note: material may have been edited for length and content. For further information, please contact the cited source.