Search NASA⌕ Search

SEARCH · Search NASA

Results for “Metagenomic Analysis”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Habitat‐adapted microbial communities mediate Sphagnum peatmoss resilience to warming

Summary Sphagnum peatmosses are fundamental members of peatland ecosystems, where they contribute to the uptake and long‐term storage of atmospheric carbon. Warming threatens Sphagnum mosses and is known to alter the composition of their associated microbiome. Here, we use a microbiome transfer approach to test if microbiome thermal origin influences host plant thermotolerance. We leveraged an experimental whole‐ecosystem warming study to collect field‐grown Sphagnum , mechanically separate the associated microbiome and then transfer onto germ‐free laboratory Sphagnum for temperature experiments. Host and microbiome dynamics were assessed with growth analysis, Chl a fluorescence imaging, metagenomics, metatranscriptomics and 16S rDNA profiling. Microbiomes originating from warming field conditions imparted enhanced thermotolerance and growth recovery at elevated temperatures. Metagenome and metatranscriptome analyses revealed that warming altered microbial community structure in a manner that induced the plant heat shock response, especially the HSP70 family and jasmonic acid production. The heat shock response was induced even without warming treatment in the laboratory, suggesting that the warm‐microbiome isolated from the field provided the host plant with thermal preconditioning. Our results demonstrate that microbes, which respond rapidly to temperature alterations, can play key roles in host plant growth response to rapidly changing environments.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

High wax ester and triacylglycerol biosynthesis potential in coastal sediments of Antarctic and Subantarctic environments

The wax ester (WE) and triacylglycerol (TAG) biosynthetic potential of marine microorganisms is poorly understood at the microbial community level. The goal of this work was to uncover the prevalence and diversity of bacteria with the potential to synthesize these neutral lipids in coastal sediments of two high latitude environments, and to characterize the gene clusters related to this process. Homolog sequences of the key enzyme, the wax ester synthase/acyl-CoA:diacylglycerol acyltransferase (WS/DGAT) were retrieved from 13 metagenomes, including subtidal and intertidal sediments of a Subantarctic environment (Ushuaia Bay, Argentina), and subtidal sediments of an Antarctic environment (Potter Cove, Antarctica). The abundance of WS/DGAT homolog sequences in the sediment metagenomes was 1.23 ± 0.42 times the abundance of 12 single-copy genes encoding ribosomal proteins, higher than in seawater (0.13 ± 0.31 times in 338 metagenomes). Homolog sequences were highly diverse, and were assigned to the Pseudomonadota, Actinomycetota, Bacteroidota and Acidobacteriota phyla. The genomic context of WS/DGAT homologs included sequences related to WE and TAG biosynthesis pathways, as well as to other related pathways such as fatty-acid metabolism, suggesting carbon recycling might drive the flux to neutral lipid synthesis. These results indicate the presence of abundant and taxonomically diverse bacterial populations with the potential to synthesize lipid storage compounds in marine sediments, relating this metabolic process to bacterial survival.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

High-quality Acinetobacter genomes recovered from combat wounds via metagenomic sequencing resemble cultured isolate genomes

The ability to accurately characterize wound pathogens is critical to informing clinical decisions for wound infections with complex treatment requirements. Acinetobacter baumannii is an impactful nosocomial pathogen in combat wounds and civilian hospital-acquired infections. An informed understanding of the phylogenetics and epidemiology of A. baumannii infections in military and civilian environments could guide approaches that improve antibiotic treatment regimens for both military and civilian patients. Whole-genome data for bacterial strains can be difficult to obtain due to challenges in culturing isolates from preserved military specimens. Metagenomic sequencing and assembly create opportunities for genomic analysis of pathogens directly from clinical specimens. The ability to perform comparative analyses between metagenome-derived genomes and culture-derived genomes would support a range of comparative bacterial genomic studies. Wound tissue biopsy and effluent samples from combat injuries were subjected to metagenomic sequencing and assembly. In total, 42 microbial metagenome-assembled genomes (MAGs) were obtained directly from metagenomic sequence data, 36 of which were designated “high” quality. Thirty of these genomes corresponded to Acinetobacter, with 29 mapping specifically to A. baumannii. Other observed genera included Bordetella, Citrobacter, Escherichia, and Pseudomonas. Single-copy and multi-copy orthologs were identified across Acinetobacter MAGs and publicly available isolate genomes derived from military and civilian sources. Both MAG and military isolate genomes were annotated with antimicrobial resistance data, and MAG genomes were statistically comparable to genomes obtained from isolates. Our results highlight the potential of de novo metagenome assembly for enabling high-resolution characterization directly from clinical specimens, thereby improving diagnostic precision, guiding antimicrobial stewardship, and enhancing understanding of pathogen evolution across diverse healthcare and battlefield environments.

Acinetobacter baumannii↗
DOE OSTI2022

The IMG/M data management and analysis system v.7: content updates and new features

The Integrated Microbial Genomes & Microbiomes system at the Department of Energy (DOE) Joint Genome Institute (JGI) continues to provide support for users to perform comparative analysis of isolate and single cell genomes, metagenomes, and metatranscriptomes. In addition to datasets produced by the JGI, IMG v.7 also includes datasets imported from public sources such as NCBI Genbank, SRA, and the DOE National Microbiome Data Collaborative (NMDC), or submitted by external users. In the past couple years, we have continued our effort to help the user community by improving the annotation pipeline, upgrading the contents with new reference database versions, and adding new analysis functionalities such as advanced scaffold search, Average Nucleotide Identity (ANI) for high-quality metagenome bins, new cassette search, improved gene neighborhood display, and improvements to metatranscriptome data display and analysis. Here, we also extended the collaboration and integration efforts with other DOE-funded projects such as NMDC and DOE Biology Knowledgebase (KBase).

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

ATLAS: a Snakemake workflow for assembly, annotation, and genomic binning of metagenome sequence data

Background: Metagenomics and metatranscriptomics studies provide valuable insight into the composition and function of microbial populations from diverse environments, however the data processing pipelines that rely on mapping reads to gene catalogs or genome databases for cultured strains yield results that underrepresent the genes and functional potential of uncultured microbes. Recent improvements in sequence assembly methods have eased the reliance on genome databases, thereby allowing the recovery of genomes from uncultured microbes. However, configuring these tools, linking them with advanced binning and annotation tools, and maintaining provenance of the processing continues to be challenging for researchers. Results: Here we present ATLAS, a software package for customizable data processing from raw sequence reads to functional and taxonomic annotations using state-of-the-art tools to assemble, annotate, quantify, and bin metagenome and metatranscriptome data. Genome-centric resolution and abundance estimates are provided for each sample in a dataset. ATLAS is written in Python and the workflow implemented in Snakemake; it operates in a Linux environment, and is compatible with Python 3.5+ and Anaconda 3+ versions. The source code for ATLAS is freely available, distributed under a BSD-3 license. Conclusions: ATLAS provides a user-friendly, modular and customizable Snakemake workflow for metagenome and metatranscriptome data processing; it is easily installable with conda and maintained as open-source on GitHub at https://github.com/metagenome-atlas/atlas.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

VPF-Class: taxonomic assignment and host prediction of uncultivated viruses based on viral protein families

Abstract Motivation Two key steps in the analysis of uncultured viruses recovered from metagenomes are the taxonomic classification of the viral sequences and the identification of putative host(s). Both steps rely mainly on the assignment of viral proteins to orthologs in cultivated viruses. Viral Protein Families (VPFs) can be used for the robust identification of new viral sequences in large metagenomics datasets. Despite the importance of VPF information for viral discovery, VPFs have not yet been explored for determining viral taxonomy and host targets. Results In this work, we classified the set of VPFs from the IMG/VR database and developed VPF-Class. VPF-Class is a tool that automates the taxonomic classification and host prediction of viral contigs based on the assignment of their proteins to a set of classified VPFs. Applying VPF-Class on 731K uncultivated virus contigs from the IMG/VR database, we were able to classify 363K contigs at the genus level and predict the host of over 461K contigs. In the RefSeq database, VPF-class reported an accuracy of nearly 100% to classify dsDNA, ssDNA and retroviruses, at the genus level, considering a membership ratio and a confidence score of 0.2. The accuracy in host prediction was 86.4%, also at the genus level, considering a membership ratio of 0.3 and a confidence score of 0.5. And, in the prophages dataset, the accuracy in host prediction was 86% considering a membership ratio of 0.6 and a confidence score of 0.8. Moreover, from the Global Ocean Virome dataset, over 817K viral contigs out of 1 million were classified. Availability and implementation The implementation of VPF-Class can be downloaded from https://github.com/biocom-uib/vpf-tools. Supplementary information Supplementary data are available at Bioinformatics online.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Association of Diet and Antimicrobial Resistance in Healthy U.S. Adults

Antimicrobial resistance (AMR) represents a significant source of morbidity and mortality worldwide, with expectations that AMR-associated consequences will continue to worsen throughout the coming decades. Since resistance to antibiotics is encoded in the microbiome, interventions aimed at altering the taxonomic composition of the gut might allow us to prophylactically engineer microbiomes that harbor fewer antibiotic resistant genes (ARGs). Diet is one method of intervention, and yet little is known about the association between diet and antimicrobial resistance. To address this knowledge gap, we examined diet using the food frequency questionnaire (FFQ; habitual diet) and 24-h dietary recalls (Automated Self-Administered 24-h [ASA24 ® ] tool) coupled with an analysis of the microbiome using shotgun metagenome sequencing in 290 healthy adult participants of the United States Department of Agriculture (USDA) Nutritional Phenotyping Study. We found that aminoglycosides were the most abundant and prevalent mechanism of AMR in these healthy adults and that aminoglycoside-O-phosphotransferases (aph3-dprime) correlated negatively with total calories and soluble fiber intake. Individuals in the lowest quartile of ARGs (low-ARG) consumed significantly more fiber in their diets than medium- and high-ARG individuals, which was concomitant with increased abundances of obligate anaerobes, especially from the family Clostridiaceae, in their gut microbiota. Finally, we applied machine learning to examine 387 dietary, physiological, and lifestyle features for associations with antimicrobial resistance, finding that increased phylogenetic diversity of diet was associated with low-ARG individuals. These data suggest diet may be a potential method for reducing the burden of AMR.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

EvoNet: A phylogenomic and systems biology approach to identify genes underlying plant survival in marginal, low‐N soils

The DOE‐BER “EvoNet” project investigates the genetic and molecular basis of plant resilience in extreme environments. We do this by identifying key genes that enable “extreme survivor” species to thrive in the nitrogen-poor soils of Chile’s hyper-arid Atacama Desert. Our collections focus on 32 Atacama extremophile species, including seven grass species with potential biofuel applications. To identify genes-of-importance to survival we compared genomic and transcriptomic profiles of extremophile species that thrive in the Atacama to those of closely related “sister” species from nitrogen-rich arid and mesic regions of California. Deep RNA sequencing and de novo transcriptome assembly across these triplet species sets supported a phylogenomic framework for identifying positively selected genes associated with adaptive divergence. Our integrative analysis combined ecological and environmental data, metagenomics, evolutionary and systems biology, and metabolomics. This enabled us to create an unprecedented framework for systematically understanding how non-model plants have adapted to survive in extreme conditions. Our resulting database of positively selected ortholog groups in the extremophile plants offers promising targets for engineering crop and biofuel species with enhanced resilience to drought and extreme weather. Additionally, our newest dataset explores and exploits a complementary metabolomic approach. This new aspect provides innovative strategies to manipulate plant cell metabolism, further supporting efforts to improve agricultural productivity in the face of extreme climates. Importantly, our combined evolutionary- and metabolomic-based strategies focused on convergent patterns of adaptation, providing a genetic and metabolomic toolkit for improving crop and biofuel resilience across diverse plant species. Finally, our novel exploration of ecological and evolutionary dynamics delivered to the community a phylogenomic computational pipeline called “PhyloGeneious.” Our continued adaptations of this pipeline are publicly available to expedite evolutionary genomic research for future scientific discoveries. In total, our DOE-BER has provided genomic, metabolomic, and computational strategies to understand how extremophile plants provide evolutionary and physiological targets for improving agricultural and biofuel production.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Distinct and rich assemblages of giant viruses in Arctic and Antarctic lakes

Giant viruses (GVs) are key players in ecosystem functioning, biogeochemistry, and eukaryotic genome evolution. GV diversity and abundance in aquatic systems can exceed that of prokaryotes, but their diversity and ecology in lakes, especially polar ones, remain poorly understood. We conducted a comprehensive survey and meta-analysis of GV diversity across 20 lakes, spanning polar to temperate regions, combining our extensive lake metagenome database from the Canadian Arctic and subarctic with publicly available datasets. Leveraging a novel GV genome identification tool, we identified 3304 GV metagenome-assembled genomes, revealing lakes as untapped GV reservoirs. Phylogenomic analysis highlighted their dispersion across all Nucleocytoviricota orders. Strong GV population endemism emerged between lakes from similar regions and biomes (Antarctic and Arctic), but a polar/temperate barrier in lacustrine GV populations and differences in their gene content could be observed. Our study establishes a robust genomic reference for future investigations into lacustrine GV ecology in fast changing polar environments.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

spammR: an R package designed for analysis and integration of spatial multi-omic measurements

Spatial omics is a young and evolving field and as such shows rapid development of novel technologies and analysis methods to measure transcripts, proteins, metabolites, and post-translational modifications at high spatial resolution. These advances in technology have enabled the simultaneous generation of abundance profiles for multiple different omics types and associated microscopy imaging data, as well as their analysis in a spatial context. However, most analytical tools are designed for spatial transcriptomics platforms and are challenging to use in other contexts such as mass spectrometry-based measurements or metagenomics. To this end we present spammR (spatial analysis of multi-omics measurements in R), an R package that enables end-to-end analysis with a specific focus on mass-spectrometry derived spatial omics datasets with (1) smaller sample sizes and spatial sparsity of samples, (2) considerable missingness, and (3) no a-priori knowledge about proteins or genes of interest, relying on a fully data-driven approach.

spammR↗
DOE OSTI2022

GROWdb US River Systems - Samples

GROW Overview We developed the Genome Resolved Open Watersheds database (GROWdb), which aims to increase genomic sampling and understanding of global river microbiomes. An emphasis of GROWdb is to create a publicly available and ever-expanding microbial genome database that is focused on rivers while being interoperable with databases from other ecosystems. GROWdb is based on a network-of-networks approach to move beyond a small collection of well-studied rivers, towards a spatially distributed, global network of systematic observations. GROWdb represents the first microbial, river-focused resource parsed at various scales from genes to MAGs to community level including expression and potential based measurements that will be of interest to microbiologists, ecologists, geochemists, hydrologists, and modelers. Dataset Acknowledgement GROWdb contains data from various research campaigns, please acknowledge the following data generators, as appropriate: WHONDRS derived genomes or samples - include this statement in your acknowledgements: “This study used data from the Worldwide Hydrobiogeochemistry Observation Network for Dynamic River Systems (WHONDRS) under the River Corridor Science Focus Area (SFA) at the Pacific Northwest National Laboratory (PNNL) that was generated at the U.S. Department of Energy (DOE) Joint Genome Institute User Facility. PNNL is operated by Battelle Memorial Institute for the U.S. DOE under Contract No. DE-AC05-76RL01830. The SFA is supported by the U.S. DOE, Office of Biological and Environmental Research (BER), Environmental System Science (ESS) Program.” Total Samples loaded onto this Narrative: 178 Note: Not all GROW samples may be loaded into KBase Data Availability The data underlying GROWdb are accessible across various platforms to ensure all levels of data structure are widely available. First, all reads and MAGs are publicly hosted on National Center for Biotechnology (NCBI) under Bioproject PRJNA946291. Second, all data related data presented here including MAG annotations, extended data tables, phylogenetic tree files, antibiotic resistance gene database files, and MAG abundance tables are available in Zenodo (link). Beyond the flat database files listed above, our aim for GROWdb was to maximize data use by making the data available in searchable and interactive platforms including the National Microbiome Data Collaborative (NMDC) data portal, the Department of Energy’s Systems Biology Knowledgebase (KBase), and a GROW specific user interface released here, GROWdb Explorer. Each platform provides different ways to interact with GROWdb: NMDC GROWdb formed a pilot project for the NMDC. Specifically, individual GROWdb datasets (metagenomes, metatranscriptomes, etc) are easily accessible and searchable through the NMDC data portal, where they are systematically connected to each other and to a rich suite of sample information and standard analysis results, following Findable, Accessible, Interoperable, and Reusable (FAIR) data practices. KBase GROWdb is publicly available within KBase, including samples (this Narrative), MAGs, and corresponding genome scale metabolic models. Access within KBase allows for immediate access and reuse of data, including comparison to private data using KBase’s 500+ analysis tools. Other linked narratives in KBase: GROW Metagenome Assembled Genomes (MAGs) GROW Metabolic Models GROWdb Explorer GROWdb data is also explorable through a graphical user interface built through the Colorado State University Geospatial Centroid (https://geocentroid.shinyapps.io/GROWdatabase/), allowing users to search and graph microbial and spatial data simultaneously. In summary, this microbial genome resource represents the first publicly available genome collection from rivers and offers data that can be leveraged across microbiome studies. GROWdb is an expanding repository to incorporate and unify global river multi-omic data for the future.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Visualizing metagenomic and metatranscriptomic data: A comprehensive review

The fields of Metagenomics and Metatranscriptomics involve the examination of complete nucleotide sequences, gene identification, and analysis of potential biological functions within diverse organisms or environmental samples. Despite the vast opportunities for discovery in metagenomics, the sheer volume and complexity of sequence data often present challenges in processing analysis and visualization. This article highlights the critical role of advanced visualization tools in enabling effective exploration, querying, and analysis of these complex datasets. Emphasizing the importance of accessibility, the article categorizes various visualizers based on their intended applications and highlights their utility in empowering bioinformaticians and non-bioinformaticians to interpret and derive insights from meta-omics data effectively.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Singleton Sieving: Overcoming the Memory/Speed Trade-Off in Exascale k-mer Analysis

Traditional filter data structures, such as Bloom filters, do not offer necessary features that modern high-performance data analytics applications need in order to efficiently perform complex data analysis tasks. For example, MetaHipMer, a de novo metagenome assembler, can use filters to weed out singleton k-mers and reduce memory usage by 30%-70%. However, the filter needs the ability to associate values with k-mers in order to perform the analysis in a single communication pass. Bloom filters do not support value associations and cause the application to perform an extra communication pass, thereby increasing the run time. Therefore, MetaHipMer faces a trade off between memory and speed due to the limited capabilities of traditional filters. In this paper, we overcome the memory and speed trade off in MetaHipMer by integrating a GPU-based feature-rich filter, the Two-Choice filter (TCF), in the MetaHipMer pipeline. The TCF uses key-value association to approximately store k-mers with extensions. This allows MetaHipMer to perform k-mer analysis on the GPUs in a single communication pass. Our empirical analysis shows a 50% reduction in memory usage in k-mer analysis on each node in MetaHipMer without any effect on the overall run time or assembly quality. The memory reduction in turn results in a 43% reduction in the number of nodes required to assemble datasets and enables MetaHipMer to scale to much larger datasets.

McCoy, Hunter↗
DOE OSTI2020

Viral Annotation Pipeline in KBase

This data analysis workflow demonstrates how to process a metagenome to identify viruses using VirSorter. Then, provides taxonomic classification using vConTACT2.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

KBase Narrative - Viral Analysis End-to-End

This pipeline processes a single metagenomic dataset (downloaded from NCBI SRA) from the Global Ocean Viromes dataset, identifies the viral sequences using VirSorter, and subsequently classifies them with vConTACT2. Along the way there are several intermediary steps to convert files from one KBase object to another - and though some of these can be skipped for this particular dataset - we're explicitly doing them here as to be more easily generalized to other datasets.

Bolduc, Benjamin↗
DOE OSTI2023

Metagenomic Methods for Addressing NASA's Planetary Protection Policy Requirements on Future Missions: A Workshop Report

Molecular biology methods and technologies have advanced substantially over the past decade. These new molecular methods should be incorporated among the standard tools of planetary protection (PP) and could be validated for incorporation by 2026. To address the feasibility of applying modern molecular techniques to such an application, NASA conducted a technology workshop with private industry partners, academics, and government agency stakeholders, along with NASA staff and contractors. The technical discussions and presentations of the Multi-Mission Metagenomics Technology Development Workshop focused on modernizing and supplementing the current PP assays. The goals of the workshop were to assess the state of metagenomics and other advanced molecular techniques in the context of providing a validated framework to supplement the bacterial endospore-based NASA Standard Assay and to identify knowledge and technology gaps. In particular, workshop participants were tasked with discussing metagenomics as a stand-alone technology to provide rapid and comprehensive analysis of total nucleic acids and viable microorganisms on spacecraft surfaces, thereby allowing for the development of tailored and cost-effective microbial reduction plans for each hardware item on a spacecraft. Workshop participants recommended metagenomics approaches as the only data source that can adequately feed into quantitative microbial risk assessment models for evaluating the risk of forward (exploring extraterrestrial planet) and back (Earth harmful biological) contamination. Participants were unanimous that a metagenomics workflow, in tandem with rapid targeted quantitative (digital) PCR, represents a revolutionary advance over existing methods for the assessment of microbial bioburden on spacecraft surfaces. The workshop highlighted low biomass sampling, reagent contamination, and inconsistent bioinformatics data analysis as key areas for technology development. Finally, it was concluded that implementing metagenomics as an additional workflow for addressing concerns of NASA's robotic mission will represent a dramatic improvement in technology advancement for PP and will benefit future missions where mission success is affected by backward and forward contamination.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Catabolism and interactions of uncultured organisms shaped by eco-thermodynamics in methanogenic bioprocesses

We currently understand the carbon cycle in methanogenic environments as trophic interactions revolving around interspecies H 2 transfer between organotrophs and methanogens. However, many H 2 -generating processes are thermodynamically sensitive to H 2 accumulation and can be inhibited by high H 2 concentrations produced by other metabolisms. To uncover how anaerobes combat this H 2 conflict in situ, we employ metagenomics and metatranscriptomics to revisit a model ecosystem that has inspired many foundational discoveries in anaerobic ecology – methanogenic bioreactors. Through analysis of 15 anaerobic digesters, we recover 1343 high-quality metagenome-assembled genomes (MAGs) and corresponding gene expression profiles for diverse uncultured lineages spanning 66 phyla and reconstruct their individual metabolic capacities. We discover that diverse uncultured organotrophic populations can drive H 2 -sensitive degradation through (i) metabolic coupling with concurrent H 2 -tolerant catabolism, (ii) unprecedented shifts from H 2 generation to CO 2 -reducing formate transfer and cytochrome/pili-mediated direct interspecies electron transfer for avoiding thermodynamic conflict, and (iii) integration of low-concentration O 2 as an ancillary thermodynamics-enhancing electron sink. Archaeal populations in situ support the above processes through novel metabolisms distinct from conventional methanogenesis – high-affinity H 2 oxidation driven by methyl-reducing methanogenesis and concomitant uptake of formate, electrons, and acetate from HS metabolism by Methanothrix. In total, synthesis of omics analyses and eco-thermodynamics reveals overlooked metabolic behavior and interactions of uncultured organisms that address a central issue in methanogenic carbon cycling, thermodynamic conflict among diverse concurrent metabolic processes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Cation and Anion Channelrhodopsins: Sequence Motifs and Taxonomic Distribution

Cation and anion channelrhodopsins (CCRs and ACRs, respectively) primarily from two algal species, Chlamydomonas reinhardtii and Guillardia theta, have become widely used as optogenetic tools to control cell membrane potential with light. We mined algal and other protist polynucleotide sequencing projects and metagenomic samples to identify 75 channelrhodopsin homologs from four channelrhodopsin families, including one revealed in dinoflagellates in this study. We carried out electrophysiological analysis of 33 natural channelrhodopsin variants from different phylogenetic lineages and 10 metagenomic homologs in search of sequence determinants of ion selectivity, photocurrent desensitization, and spectral tuning in channelrhodopsins. Our results show that association of a reduced number of glutamates near the conductance path with anion selectivity depends on a wider protein context, because prasinophyte homologs with a glutamate pattern identical to that in cryptophyte ACRs are cation selective. Desensitization is also broadly context dependent, as in one branch of stramenopile ACRs and their metagenomic homologs, its extent roughly correlates with phylogenetic relationship of their sequences. Regarding spectral tuning, we identified two prasinophyte CCRs with red-shifted spectra to 585 nm. They exhibit a third residue pattern in their retinal-binding pockets distinctly different from those of the only two types of red-shifted channelrhodopsins known (i.e., the CCR Chrimson and RubyACRs). In cryptophyte ACRs we identified three specific residue positions in the retinal-binding pocket that define the wavelength of their spectral maxima. Lastly, we found that dinoflagellate rhodopsins with a TCP motif in the third transmembrane helix and a metagenomic homolog exhibit channel activity. Channelrhodopsins are widely used in neuroscience and cardiology as research tools and are considered prospective therapeutics, but their natural diversity and mechanisms remain poorly characterized. Genomic and metagenomic sequencing projects are producing an ever-increasing wealth of data, whereas biophysical characterization of the encoded proteins lags behind. In this study, we used manual and automated patch clamp recording of representative members of four channelrhodopsin families, including a family in dinoflagellates that we report in this study. Our results contribute to a better understanding of molecular determinants of ionic selectivity, photocurrent desensitization, and spectral tuning in channelrhodopsins.

59 BASIC BIOLOGICAL SCIENCES↗