Biology subjects

Stevens, S. L. R.

Publications and source records attributed to Stevens, S. L. R..

3 recordsLinked to original sources

bioRxiv2022

Diversity, distribution, and expression of opsin genes in freshwater lakes

Microbial rhodopsins are widely distributed in aquatic environments and may significantly contribute to phototrophy and energy budgets in global oceans. However, the study of freshwater rhodopsins has been largely limited. Here, we explored the diversity, ecological distribution, and expression of opsin genes that encode the apoproteins of Type I rhodopsins in humic and clearwater lakes with contrasting physicochemical and optical characteristics. Using metagenomes and metagenome-assembled genomes, we recovered opsin genes from a wide range of taxa, mostly predicted to encode green light-absorbing proton pumps. Viral opsin and novel bacterial opsin clades were recovered. Opsin genes occurred more frequently in taxa from clearwater than from humic water, and opsins in some taxa have non-typical ion-pumping motifs that might be associated with physicochemical conditions of these two freshwater types. Analyses of the surface layer of 33 freshwater systems revealed an inverse correlation between opsin gene abundance and lake dissolved organic carbon (DOC). In humic water with high terrestrial DOC and light-absorbing humic substances, opsin gene abundance was low and dramatically declined within the first few meters, whereas the abundance remained relatively high along the bulk water column in clearwater lakes with low DOC, suggesting opsin gene distribution is influenced by lake optical properties and DOC. Gene expression analysis confirmed the significance of rhodopsin-based phototrophy in clearwater lakes and revealed different diel expressional patterns among major phyla. Overall, our analyses revealed freshwater opsin diversity, distribution and expression patterns, and suggested the significance of rhodopsin-based phototrophy in freshwater energy budgets, especially in clearwater lakes.

microbiology↗

bioRxiv2020

Expanded Phylogenetic Diversity and Metabolic Flexibility of Microbial Mercury Methylation

Methylmercury is a potent, bioaccumulating neurotoxin that is produced by specific microorganisms by methylation of inorganic mercury released from anthropogenic sources. The hgcAB genes were recently discovered to be required for microbial methylmercury production in diverse anaerobic bacteria and archaea. However, the full phylogenetic and metabolic diversity of mercury methylating microorganisms has not been fully explored due to the limited number of cultured, experimentally verified methylators and the limitations of primer-based molecular methods. Here, we describe the phylogenetic diversity and metabolic flexibility of putative mercury methylating microorganisms identified by hgcA sequence identity from publicly available isolate genomes and metagenome-assembled genomes (MAGs), as well as novel freshwater MAGs. We demonstrate that putative mercury methylators are much more phylogenetically diverse than previously known, and the distribution of hgcA is most likely due to several independent horizontal gene transfer events. Identified methylating microorganisms possess diverse metabolic capabilities spanning carbon fixation, sulfate reduction, nitrogen fixation, and metal resistance pathways. Using a metatranscriptomic survey of a thawing permafrost gradient from which we identified 111 putative mercury methylators, we demonstrate that specific methylating populations may contribute to hgcA expression at different depths. Overall, we provide a framework for illuminating the microbial basis of mercury methylation using genome-resolved metagenomics and metatranscriptomics to identify methylators based upon hgcA presence and describe their putative functions in the environment. IMPORTANCESpecific anaerobic microorganisms among the Deltaproteobacteria, Firmicutes, and Euryarchaeota have been shown to produce the bioaccumulating neurotoxin methylmercury. Accurately assessing the sources of microbial methylmercury production in the context of phylogenetic identification, metabolic guilds, and activity in the environment is crucial for understanding the constraints and effects of mercury impacted sites. Advances in next-generation sequencing technologies have enabled large-scale, cultivation-independent surveys of diverse and poorly characterized microorganisms of numerous ecosystems. We used genome-resolved metagenomics and metatranscriptomics to highlight the vast phylogenetic and metabolic diversity of putative mercury methylators, and their depth-discrete activities in the environment. This work underscores the importance of using genome-resolved metagenomics to survey specific putative methylating populations of a given mercury-impacted ecosystem.

microbiology↗

bioRxiv2018

Building a local community of practice in scientific programming for Life Scientists

For most experimental biologists, handling the avalanche of data generated is similar to learning how to drive on your own. Although that might be doable, it is preferable and safer to learn programming and good practices together and preferably from experienced scientists. One way to achieve this is to build local communities of practice in scientific programming by bringing together life scientists that perform code-intensive research to spread know-how and good practices. The community will make sure that, for a given researcher working for an academic institution, their capacity to conduct data-intensive research will not be arbitrarily reliant on the presence of well-trained bioinformaticians in their vicinity.\n\nIn this paper, we propose a three-step field guide for building a local community of practice in scientific programming for life scientists. The first step is organizing a Carpentries programming workshop designed for researchers new to computational biology. However, while such workshops provide an immediate solution for learning, more regular long-term assistance is also needed. Researchers need persisting, local support to continue learning and solving programming issues that may hamper their research progress. The solution we describe here is to implement a Mozilla Study Group where researchers can meet-up and help each other in a \"safe-learning atmosphere\". We describe two real-life examples of building local communities of practice: one in the Netherlands at the Amsterdam Science Park and one in the United States at the University of Wisconsin-Madison. In order to help future researchers to build their own community of practice in scientific programming we discuss challenges and implemented solutions.\n\nWe believe that our local communities of practice will prove useful for other life scien-tists who want to set up similar support groups for researchers involved in scientific programming and data science.\n\nAuthor summaryIn this paper, we describe why and how to build a community of practice for life scientists that start to make more use of computers and programming in their research. A community of practice is a small group of scientists that meet regularly to help each other and promote good practices in scientific computing. While most life scientists are well-trained in the laboratory to conduct experiments, good practices with (big) datasets and their analysis are often missing. This paper proposes a field-guide on how to build such a community of practice at a local academic institution. Based on two real-life examples, challenges and related recommendations are provided. We believe that the current data deluge that life scientists will increasingly face can benefit from the implementation of these small communities. Good practices spread among experimental scientists will foster open, transparent, sound scientific results beneficial to society.

scientific communication and education↗