Genomic evidence of functional diversity in DPANN archaea, from oxic species to anoxic vampiristic consortia

DPANN archaea account for half of the archaeal diversity of the biosphere, but with few cultivated representatives, their metabolic potential and environmental functions are poorly understood. The extreme geochemical and environmental conditions in meromictic ice-capped Lake A, in the Canadian High Arctic, provided an isolated, stratified model ecosystem to resolve the distribution and metabolism of uncultured aquatic DPANN archaea living across extreme redox and salinity gradients, from freshwater oxygenated conditions, to saline, anoxic, sulfidic waters. We recovered 28 metagenome-assembled genomes (MAGs) of DPANN archaea that provided genetic insights into their ecological function. Thiosulfate oxidation potential was detected in aerobic Woesearchaeota, whereas diverse metabolic functions were identified in anaerobic DPANN archaea, including degradation and fermentation of cellular compounds, and sulfide and polysulfide reduction. We also found evidence for “vampiristic” metabolism in several MAGs, with genes coding for pore-forming toxins, peptidoglycan degradation, and RNA scavenging. The vampiristic MAGs co-occurred with other DPANNs having complementary metabolic capacities, leading to the possibility that DPANN form interspecific consortia that recycle microbial carbon, nutrients and complex molecules through a DPANN archaeal shunt, adding hidden novel complexity to anaerobic microbial food webs

Genomic evidence for sulfur intermediates as new biogeochemical hubs in a model aquatic microbial ecosystem

Background: The sulfur cycle encompasses a series of complex aerobic and anaerobic transformations of S-containing molecules and plays a fundamental role in cellular and ecosystem-level processes, influencing biological carbon transfers and other biogeochemical cycles. Despite their importance, the microbial communities and metabolic pathways involved in these transformations remain poorly understood, especially for inorganic sulfur compounds of intermediate oxidation states (thiosulfate, tetrathionate, sulfite, polysulfides). Isolated and highly stratified, the extreme geochemical and environmental features of meromictic ice-capped Lake A, in the Canadian High Arctic, provided an ideal model ecosystem to resolve the distribution and metabolism of aquatic sulfur cycling microorganisms along redox and salinity gradients. Results: Applying complementary molecular approaches, we identified sharply contrasting microbial communities and metabolic potentials among the markedly distinct water layers of Lake A, with similarities to diverse fresh, brackish and saline water microbiomes. Sulfur cycling genes were abundant at all depths and covaried with bacterial abundance. Genes for oxidative processes occurred in samples from the oxic freshwater layers, reductive reactions in the anoxic and sulfidic bottom waters and genes for both transformations at the chemocline. Up to 154 different genomic bins with potential for sulfur transformation were recovered, revealing a panoply of taxonomically diverse microorganisms with complex metabolic pathways for biogeochemical sulfur reactions. Genes for the utilization of sulfur cycle intermediates were widespread throughout the water column, co-occurring with sulfate reduction or sulfide oxidation pathways. The genomic bin composition suggested that in addition to chemical oxidation, these intermediate sulfur compounds were likely produced by the predominant sulfur chemo- and photo-oxidisers at the chemocline and by diverse microbial degraders of organic sulfur molecules. Conclusions: The Lake A microbial ecosystem provided an ideal opportunity to identify new features of the biogeochemical sulfur cycle. Our detailed metagenomic analyses across the broad physico-chemical gradients of this permanently stratified lake extend the known diversity of microorganisms involved in sulfur transformations over a wide range of environmental conditions. The results indicate that sulfur cycle intermediates and organic sulfur molecules are major sources of electron donors and acceptors for aquatic and sedimentary microbial communities in association with the classical sulfur cycl

Multilayer spintronic neural networks with radio-frequency connections

Spintronic nano-synapses and nano-neurons perform complex cognitive computations with high accuracy thanks to their rich, reproducible and controllable magnetization dynamics. These dynamical nanodevices could transform artificial intelligence hardware, provided that they implement state-of-the art deep neural networks. However, there is today no scalable way to connect them in multilayers. Here we show that the flagship nano-components of spintronics, magnetic tunnel junctions, can be connected into multilayer neural networks where they implement both synapses and neurons thanks to their magnetization dynamics, and communicate by processing, transmitting and receiving radio frequency (RF) signals. We build a hardware spintronic neural network composed of nine magnetic tunnel junctions connected in two layers, and show that it natively classifies nonlinearly-separable RF inputs with an accuracy of 97.7%. Using physical simulations, we demonstrate that a large network of nanoscale junctions can achieve state-of the-art identification of drones from their RF transmissions, without digitization, and consuming only a few milliwatts, which is a gain of more than four orders of magnitude in power consumption compared to currently used techniques. This study lays the foundation for deep, dynamical, spintronic neural networks

Hot, rocky and warm, puffy super-Earths orbiting TOI-402 (HD 15337)

Context: The Transiting Exoplanet Survey Satellite (TESS) is revolutionising the search for planets orbiting bright and nearby stars. In sectors 3 and 4, TESS observed TOI-402 (TIC-120896927), a bright V = 9.1 K1 dwarf also known as HD 15337, and found two transiting signals with periods of 4.76 and 17.18 days and radii of 1.90 and 2.21 R⊕, respectively. This star was observed prior to the TESS detection as part of the radial-velocity (RV) search for planets using the HARPS spectrometer, and 85 precise RV measurements were obtained before the launch of TESS over a period of 14 yr. Aims: In this paper, we analyse the HARPS RV measurements in hand to confirm the planetary nature of these two signals. Methods: HD 15337 happens to present a stellar activity level similar to the Sun, with a magnetic cycle of similar amplitude and RV measurements that are affected by stellar activity. By modelling this stellar activity in the HARPS radial velocities using a linear dependence with the calcium activity index log(RHK′), we are able, with a periodogram approach, to confirm the periods and the planetary nature of TOI-402.01 and TOI-402.02. We then derive robust estimates from the HARPS RVs for the orbital parameters of these two planets by modelling stellar activity with a Gaussian process and using the marginalised posterior probability density functions obtained from our analysis of TESS photometry for the orbital period and time of transit. Results: By modelling TESS photometry and the stellar host characteristics, we find that TOI-402.01 and TOI-402.02 have periods of 4.75642 ± 0.00021 and 17.1784 ± 0.0016 days and radii of 1.70 ± 0.06 and 2.52 ± 0.11 R⊕ (precision 3.6 and 4.2%), respectively. By analysing the HARPS RV measurements, we find that those planets are both super-Earths with masses of 7.20 ± 0.81 and 8.79 ± 1.68 M⊕ (precision 11.3 and 19.1%), and small eccentricities compatible with zero at 2σ. Conclusions: Although having rather similar masses, the radii of these two planets are very different, putting them on different sides of the radius gap. By studying the temporal evolution under X-ray and UV (XUV) driven atmospheric escape of the TOI-402 planetary system, we confirm, under the given assumptions, that photo-evaporation is a plausible explanation for this radius difference. Those two planets, being in the same system and therefore being in the same irradiation environment are therefore extremely useful for comparative exoplanetology across the evaporation valley and thus bring constraints on the mechanisms responsible for the radius gap

A Microscope Automated Fluidic System to Study Bacterial Processes in Real Time

Most time lapse microscopy experiments studying bacterial processes ie growth, progression through the cell cycle and motility have been performed on thin nutrient agar pads. An important limitation of this approach is that dynamic perturbations of the experimental conditions cannot be easily performed. In eukaryotic cell biology, fluidic approaches have been largely used to study the impact of rapid environmental perturbations on live cells and in real time. However, all these approaches are not easily applicable to bacterial cells because the substrata are in all cases specific and also because microfluidics nanotechnology requires a complex lithography for the study of micrometer sized bacterial cells. In fact, in many cases agar is the experimental solid substratum on which bacteria can move or even grow. For these reasons, we designed a novel hybrid micro fluidic device that combines a thin agar pad and a custom flow chamber. By studying several examples, we show that this system allows real time analysis of a broad array of biological processes such as growth, development and motility. Thus, the flow chamber system will be an essential tool to study any process that take place on an agar surface at the single cell level

From Late Miocene to Holocene: Processes of Differentiation within the Telestes Genus (Actinopterygii: Cyprinidae)

Investigating processes and timing of differentiation of organisms is critical in the understanding of the evolutionary mechanisms involved in microevolution, speciation, and macroevolution that generated the extant biodiversity. From this perspective, the Telestes genus is of special interest: the Telestes species have a wide distribution range across Europe (from the Danubian district to Mediterranean districts) and have not been prone to translocation. Molecular data (mtDNA: 1,232 bp including the entire Cyt b gene; nuclear genome: 11 microsatellites) were gathered from 34 populations of the Telestes genus, almost encompassing the entire geographic range. Using several phylogenetic and molecular dating methods interpreted in conjunction with paleoclimatic and geomorphologic evidence, we investigated the processes and timing of differentiation of the Telestes lineages. The observed genetic structure and diversity were largely congruent between mtDNA and microsatellites. The Messinian Salinity Crisis (Late Miocene) seems to have played a major role in the speciation processes of the genus. Focusing on T. souffia, a species occurring in the Danube and Rhone drainages, we were able to point out several specific events from the Pleistocene to the Holocene that have likely driven the differentiation and the historical demography of this taxon. This study provides support for an evolutionary history of dispersal and vicariance with unprecedented resolution for any freshwater fish in this region

Drug-target identification in COVID-19 disease mechanisms using computational systems biology approaches

Introduction: The COVID-19 Disease Map project is a large-scale community effort uniting 277 scientists from 130 Institutions around the globe. We use high-quality, mechanistic content describing SARS-CoV-2-host interactions and develop interoperable bioinformatic pipelines for novel target identification and drug repurposing. Methods: Extensive community work allowed an impressive step forward in building interfaces between Systems Biology tools and platforms. Our framework can link biomolecules from omics data analysis and computational modelling to dysregulated pathways in a cell-, tissue- or patient-specific manner. Drug repurposing using text mining and AI-assisted analysis identified potential drugs, chemicals and microRNAs that could target the identified key factors. Results: Results revealed drugs already tested for anti-COVID-19 efficacy, providing a mechanistic context for their mode of action, and drugs already in clinical trials for treating other diseases, never tested against COVID-19. Discussion: The key advance is that the proposed framework is versatile and expandable, offering a significant upgrade in the arsenal for virus-host interactions and other complex pathologies.Peer Reviewe

A pair of Sub-Neptunes transiting the bright K-dwarf TOI-1064 characterised with CHEOPS

Funding: TGW, ACC, and KH acknowledge support from STFC consolidated grant numbers ST/R000824/1 and ST/V000861/1, and UKSA grant ST/R003203/1.We report the discovery and characterization of a pair of sub-Neptunes transiting the bright K-dwarf TOI-1064 (TIC 79748331), initially detected in the Transiting Exoplanet Survey Satellite (TESS) photometry. To characterize the system, we performed and retrieved the CHaracterising ExOPlanets Satellite (CHEOPS), TESS, and ground-based photometry, the High Accuracy Radial velocity Planet Searcher (HARPS) high-resolution spectroscopy, and Gemini speckle imaging. We characterize the host star and determine Teff,⋆=4734±67K⁠, R⋆=0.726±0.007R⊙⁠, and M⋆=0.748±0.032M⊙⁠. We present a novel detrending method based on point spread function shape-change modelling and demonstrate its suitability to correct flux variations in CHEOPS data. We confirm the planetary nature of both bodies and find that TOI-1064 b has an orbital period of Pb = 6.44387 ± 0.00003 d, a radius of Rb = 2.59 ± 0.04 R⊕, and a mass of Mb=13.5+1.7−1.8 M⊕, whilst TOI-1064 c has an orbital period of Pc=12.22657+0.00005−0.00004 d, a radius of Rc = 2.65 ± 0.04 R⊕, and a 3σ upper mass limit of 8.5 M⊕. From the high-precision photometry we obtain radius uncertainties of ∼1.6 per cent, allowing us to conduct internal structure and atmospheric escape modelling. TOI-1064 b is one of the densest, well-characterized sub-Neptunes, with a tenuous atmosphere that can be explained by the loss of a primordial envelope following migration through the protoplanetary disc. It is likely that TOI-1064 c has an extended atmosphere due to the tentative low density, however further radial velocities are needed to confirm this scenario and the similar radii, different masses nature of this system. The high-precision data and modelling of TOI-1064 b are important for planets in this region of mass–radius space, and it allow us to identify a trend in bulk density–stellar metallicity for massive sub-Neptunes that may hint at the formation of this population of planets.Publisher PDFPeer reviewe

Gap-filling eddy covariance methane fluxes : Comparison of machine learning model predictions and uncertainties at FLUXNET-CH4 wetlands

Time series of wetland methane fluxes measured by eddy covariance require gap-filling to estimate daily, seasonal, and annual emissions. Gap-filling methane fluxes is challenging because of high variability and complex responses to multiple drivers. To date, there is no widely established gap-filling standard for wetland methane fluxes, with regards both to the best model algorithms and predictors. This study synthesizes results of different gap-filling methods systematically applied at 17 wetland sites spanning boreal to tropical regions and including all major wetland classes and two rice paddies. Procedures are proposed for: 1) creating realistic artificial gap scenarios, 2) training and evaluating gap-filling models without overstating performance, and 3) predicting halfhourly methane fluxes and annual emissions with realistic uncertainty estimates. Performance is compared between a conventional method (marginal distribution sampling) and four machine learning algorithms. The conventional method achieved similar median performance as the machine learning models but was worse than the best machine learning models and relatively insensitive to predictor choices. Of the machine learning models, decision tree algorithms performed the best in cross-validation experiments, even with a baseline predictor set, and artificial neural networks showed comparable performance when using all predictors. Soil temperature was frequently the most important predictor whilst water table depth was important at sites with substantial water table fluctuations, highlighting the value of data on wetland soil conditions. Raw gap-filling uncertainties from the machine learning models were underestimated and we propose a method to calibrate uncertainties to observations. The python code for model development, evaluation, and uncertainty estimation is publicly available. This study outlines a modular and robust machine learning workflow and makes recommendations for, and evaluates an improved baseline of, methane gap-filling models that can be implemented in multi-site syntheses or standardized products from regional and global flux networks (e.g., FLUXNET).Peer reviewe