Biology subjects

Feng, X.

Publications and source records attributed to Feng, X..

At least 73 records · Page 4Linked to original sources

bioRxiv2025

Phosphorylation of the α subunit inhibits proteasome assembly and regulates cell division in archaea

Archaea of the order Sulfolobales possess a eukaryotic-like cell division machinery and display a eukaryotic-like cell cycle, however, the cell division and cell cycle control mechanisms remain enigmatic. Here, we demonstrate that phosphorylation of the subunit by a eukaryotic-like protein kinase ePK2 affects 26S proteasome assembly and controls cell division in Saccharolobus islandicus. ePK2 exhibits cell cycle-dependent expression at both transcriptional and translational levels. Deletion or overexpression of ePK2 results in impaired cytokinesis, with the deletion cells being unable to generate single chromosome cells after synchronization and the overexpression cells exhibiting growth retardation and cell enlargement. Interestingly, overexpression of ePK2 leads to a coherent reduction in cellular proteasome activity and degradation of cell division proteins. We identify S200 and T213 of the proteasome subunit as specific target sites for ePK2 phosphorylation. Functional and structural analyses of site-directed mutants at S200 and T213 suggest that S200 phosphorylation disrupts the assembly of 20S into 26S proteasome whereas T213 phosphorylation interferes the de novo ring assembly. Collectively, our study uncovers an ingenious and efficient mechanism of proteasome phosphorylation-mediated cell division regulation, a prototype of the eukaryotic cell cycle regulation system, in Sulfolobales archaea.

microbiology↗

bioRxiv2025

Benchmarking Universal Machine Learning Force Fields with Hydrogen-Bonding Cooperativity

Machine learning force fields (MLFFs) offer a promising balance between quantum mechanical (QM) accuracy and molecular mechanics efficiency. While MLFFs have shown strong performance in modeling short-range interactions and reproducing potential energy surfaces, their ability to capture long-range cooperative effects remains underexplored. In this study, we assess the ability of three MLFF models -- ANI, MACE-OFF, and Orb -- to reproduce cooperative interactions arising from environmental induction and dispersion, which are essential for many biomolecular processes. Using a recently proposed framework, we quantify hydrogen bond (H-bond) cooperativity in N-methylacetamide polymers. Our results show that all MLFFs capture cooperativity to some extent, with MACE-OFF yielding the closest agreement with QM data. These findings highlight the importance of evaluating many-body effects in MLFFs and suggest that H-bond cooperativity can serve as a useful benchmark for improving their physical fidelity.

biophysics↗

bioRxiv2025

BACE1 regulates sleep-wake cycle through both enzymatic and non-enzymatic actions.

The {beta}-secretase BACE1 has become a prime target in Alzheimers disease (AD) therapy, because it drives the production of pathogenic amyloid {beta} peptides. However, clinical trials with BACE1-targeting drugs were halted due to adverse effects on cognitive performance. We propose here that cognitive impairment by BACE1 inhibitors may be a corollary of a higher function of BACE1 related to proper sleep regulation. To address non-enzymatic effects of BACE1 on ion channels likely involved in the sleep-wake cycle, we analyzed sleep patterns in both BACE1-KO mice and a newly generated transgenic line expressing a proteolysis-deficient BACE1 variant (BACE1-KI). We found that BACE1-KI and BACE1-KO mice displayed common and distinct sleep-wake disturbances. Compared to their respective wild-type littermates, both mutant lines slept less during the light phase (when they preferentially rest). Furthermore, transition rates between wake and sleep states were altered, as were sleep spindles and EEG power spectra mainly in the gamma range. Thus, a better understanding of how BACE1 interferes with sleep-modulated behaviors is needed if clinical trials with BACE1-targeted inhibitors are to resume.

animal behavior and cognition↗

bioRxiv2025

The H3K27me3 reader UAD-2 recruits a TAF-12-containing transcription condensates to initiate piRNA expression within heterochromatic clusters

Metazoans utilize the small RNA pathway to regulate gene expression and maintain genome integrity. This pathway directs histone H3 lysine 9 tri-methylation (H3K9me3) or histone H3 lysine 27 tri-methylation (H3K27me3) at target loci to induce transcriptional gene silencing. Interestingly, some small RNAs are generated from genomic loci enriched in H3K9me3 or H3K27me3. However, the transcription mechanism of small RNA precursors from these heterochromatic regions remains unclear. In C. elegans, piRNAs originate from two genomic clusters enriched with H3K27me3 marks, which recruit the H3K27me3 reader UAD-2 and the upstream sequence transcription complex (USTC). Here, we demonstrate that piRNA transcription in C. elegans relies on TAF-12, a subunit of the basal transcription factor IID (TFIID). Depletion of TAF-12 reduces the production of both piRNA precursors and mature piRNAs. TAF-12 interacts with UAD-2 and facilitates piRNA focus formation in germ cell nuclei. We further show that TAF-12 triggers piRNA transcription by recruiting the RNA polymerase II subunit RPB-5, the Mediator complex subunit MDT-8, and the general transcription factors GTF-2F2 and GTF-2H2C. Thus, piRNA transcription within heterochromatic regions depends on the collaboration between histone modification readers, piRNA-specific transcription factors, and core transcription machinery.

genetics↗

bioRxiv2025

Big Bones Mean Big Muscles: AI Quantifies 71 Individual Muscles Across the Whole Body, Revealing Widespread Links Between Muscle, Bone, and Body Size

Body sizes and shapes vary widely, even among healthy adults, resulting in diverse muscle sizes, strengths, and performance capacities. This study developed a novel AI-driven algorithm to segment and analyze individual muscles and bones from whole-body MRI. Validated via inter- and intra-observer analyses, the algorithm created 3D segmentations of 71 muscles and 13 bones across the upper limbs, trunk, and lower limbs in 48 healthy adults (24 males, 24 females) aged 18-49 years. Muscle volume, asymmetry, length, and fat fraction were quantified. While asymmetry and fat fraction varied across muscles, they did not differ significantly between sexes. Total muscle volume was the strongest predictor of individual muscle volume, followed by bone volume, which correlated with muscle size at whole-body, regional, and individual levels. Muscle-to-body size relationships (e.g., mass, height, BMI) differed between sexes, while bone-to-body size relationships did not. These findings suggest that skeletal size ("frame size") is a key determinant of muscularity. This study provides the most comprehensive in vivo dataset of human skeletal muscle to date, offering a multi-factorial explanation for variation in muscularity and benchmarks for applications ranging from athletic performance to clinical assessments in muscle disorders. SUMMARYUnderstanding how muscle size varies across the body and what influences these differences is key to advancing both health and performance. This study uses cutting-edge AI to analyze individual muscles across the whole body from MRI scans, creating the most detailed dataset of human muscle and bone relationships to date. The findings reveal how skeletal size ("frame size") and body dimensions shape muscularity, providing new insights into why people differ in muscle size and strength. These results have broad implications, from optimizing athletic training to diagnosing and treating muscle disorders. By uncovering the intricate connections between muscles, bones, and body size, this research offers a powerful framework for understanding human movement and variability.

bioengineering↗

bioRxiv2025

Spatially Aware Adjusted Rand Index for Evaluating Spatial Transcriptomics Clustering

The spatial transcriptomics (ST) clustering plays a crucial role in elucidating the tissue spatial heterogeneity. An accurate ST clustering result can greatly benefit downstream biological analyses. As various ST clustering approaches are proposed in recent years, comparing their clustering accuracy becomes important in benchmarking studies. However, the widely used metric, adjusted Rand index (ARI), totally ignores the spatial information in ST data, which prevents ARI from fully evaluating spatial ST clustering methods. We propose a spatially aware Rand index (spRI) as well as spARI that incorporate the spatial distance information. Specifically, when comparing two partitions, spRI provides a disagreement object pair with a weight relying on the distance of the two objects, whereas Rand index assigns a zero weight to it. This spatially aware feature of spRI adaptively differentiates disagreement object pairs based on their distinct distances, providing a useful evaluation metric that favors spatial coherence of clustering. The spARI is obtained by adjusting spRI for random chances such that its expectation takes zero under an appropriate null model. Statistical properties of spRI and spARI are discussed. The applications to simulation study and two ST datasets demonstrate the improved utilities of spARI compared to ARI in evaluating ST clustering methods. The R package to compute spRI and spARI is available at https://github.com/yinqiaoyan/spARI.

bioinformatics↗

bioRxiv2025

Who is who in necromass formation and stabilization in soil? Unraveling the role of fungi and bacteria as complementary players of biogeochemical functioning

Multiple global change drivers have caused a large carbon (C) debt in our soils. To remedy this debt, understanding the role of microorganisms in soil C cycling is crucial to tackle the C soil loss. Microbial carbon use efficiency (CUE) is a parameter that captures the formation of microbially-derived soil organic matter (SOM). While it is known that biotic and abiotic drivers influence CUE, it remains unclear how distinct microbial communities and abiotic conditions influence the formation of microbially-derived SOC and its persistence in soils. Here, we combined the inoculation of distinct communities (a biotic factor) grown at different moisture levels (an abiotic factor) to manipulate the formation of microbial necromass in model soil. In a follow-up experiment, we then evaluated the persistence of this previously formed microbially-derived C to decomposition. While we show that necromass formation reflects the microbial community composition, the SOC formed within the most complex community of bacteria and fungi seems to be more resistant to decomposition compared to the SOC formed within the simpler communities (bacteria and fungi simple community, bacteria only and fungi only communities). Moreover, fungal necromass proved to be more thermally-stable than bacterial necromass, if this necromass is formed under the presence of bacteria. Our findings reveal that although abiotic factors can influence microbial physiology, the biological origin of microbially-derived C and the co-occurrence of fungal and bacterial growth were the stronger drivers explaining SOM persistence in these soils, suggesting the importance of microbial succession in SOC stabilization.

ecology↗

bioRxiv2025

High-Parameter Spatial Multi-Omics through Histology-Anchored Integration

Spatial omics face challenges in achieving high-parameter, multi-omics co-profiling. Serial-section profiling of complementary panels mitigates technical trade-offs but introduces the spatial diagonal integration problem. To address this, we present SpatialEx and its extension SpatialEx+, computational frameworks leveraging histology as a universal anchor to integrate spatial molecular data across tissue sections. SpatialEx combines a pre-trained H&E foundation model with hypergraph and contrastive learning to predict single-cell omics from histology, encoding multi-neighborhood spatial dependencies and global tissue context. SpatialEx+ further introduces an omics cycle module that encourages cross-omics consistency via slice-invariant mappings, enabling seamless integration without co-measured training data. Extensive validations show superior H&E-to-omics prediction, panel diagonal integration, and omics diagonal integration across various biological scenarios. The frameworks scale to datasets exceeding one million cells, maintain robustness with non-overlapping or heterogeneous sections, and support unlimited omics layers in principle. Our work makes multi-modal spatial profiling broadly accessible.

bioinformatics↗

bioRxiv2025

The architecture, assembly, and evolution of a complex flagellar motor

Bacterial flagella drive motility in many species, likely including the last bacterial common ancestor 1,2. Knowledge of flagellar assembly and function has mainly come from studies of Escherichia coli and Salmonella enterica, which have simple flagellar motors 3-7. However, most flagellated bacteria possess complex motors with unique, species-specific adaptations whose mechanisms and evolution remain largely unexplored 8-10. Here, we deploy a multidisciplinary approach to build a near-complete model of the flagellar motor in Campylobacter jejuni, revealing its remarkable complexity in architecture and composition. We identify an E-ring around the MS-ring, a periplasmic cage with two distinctive conformations, and an intricate interaction network between the E-ring and cage. These scaffolds play critical roles in stabilizing and regulating 17 torque-generating stator complexes for optimal motility. In-depth evolutionary analyses uncover the ancient origin and prevalence of the E-ring in flagellated species of the domain Bacteria as well as a unique exaptation of type IV pili components PilMNOPQF in the ancestral motor of the phylum Campylobacterota. Collectively, our studies reveal novel mechanisms of assembly and function in complex flagellar motors and shed light on the evolution of flagella and modern bacterial species.

microbiology↗

bioRxiv2024

STAT5B leukemic mutations, altering SH2 tyrosine 665, have opposing impacts on immune gene programs

STAT5B is a vital transcription factor for lymphocytes. Here, function of two STAT5B mutations from human T cell leukemias: one substituting tyrosine 665 with phenylalanine (STAT5BY665F), the other with histidine (STAT5BY665H) was interrogated. In silico modeling predicted divergent energetic effects on homodimerization with a range of pathogenicity. In primary T cells in vitro STAT5BY665F showed gain-of-function while STAT5BY665H demonstrated loss-of-function. Introducing the mutation into the mouse genome illustrated that the gain-of-function Stat5bY665F mutation resulted in accumulation of CD8+ effector and memory and CD4+ regulatory T-cells, altering CD8+/CD4+ ratios. In contrast, STAT5BY665H knock-in mice showed diminished CD8+ effector and memory and CD4+ regulatory T cells. In contrast to wild-type STAT5, the STAT5BY665F variant displayed greater STAT5 phosphorylation, DNA binding and transcriptional activity following cytokine activation while the STAT5BY665H variant resembled a null. The work exemplifies how joining in silico and in vivo studies of single nucleotides deepens our understanding of disease-associated variants, revealing structural determinants of altered function, defining mechanistic roles, and, specifically here, identifying a gain-of function variant that does not directly induce hematopoietic malignancy.

genetics↗

bioRxiv2024

The clumped isotope signatures of multiple methanogenesis metabolisms

Methane is a potent greenhouse gas, an important energy source, and a potential biosignature on extraterrestrial planetary bodies. The relative abundances of doubly substituted ("clumped") methane isotopologues (13CH3D and 12CH2D2) offer important information on the sources and sinks of methane. However, the clumped isotope signatures of microbially produced methane from different methanogenic pathways lack a systematic investigation. In this study, we provide a dataset encompassing the relative isotopologue abundances produced by hydrogenotrophic, methylotrophic, acetoclastic, and methoxydotrophic methanogenesis. We find that a statistical "combinatorial effect" generates significant differences in 12CH2D2 compositions between hydrogenotrophic methanogenesis and other pathways. The thermodynamic drive of methanogenic reactions and phylogenetic affiliation may also influence the isotope compositions of methane. Our study provides new experimental constraints on the isotope signatures of different microbial methanogenic pathways, and evidence of the mechanisms responsible for the observed differences. TeaserA novel stable isotope tool to track and differentiate sources of biological methane.

microbiology↗

bioRxiv2024

Magnetically induced magnetosome chain (MAGiC):A biogenic magnetic-particle-imaging tracer with high performance and navigability

Magnetic particle imaging (MPI) enables real-time, sensitive and quantitative visualization of magnetic tracers spatial distribution, augmenting the capability of in vivo imaging technologies. Previous tracer studies in MPI have primarily focused on superparamagnetic nanoparticles; however, their non-ideal sigmoidal magnetization response limits the spatial resolution. Here we demonstrate the utilization of magnetically induced magnetosome chain (MAGiC) as a novel superferromagnetic MPI tracer, exhibiting a 25-fold improvement in resolution and a 91-fold enhancement in signal intensity compared to the commercial tracer VivoTrax+. The spatial resolution of MPI was pushed to an unprecedented 80 m under a 4 T/m gradient field. Additionally, MAGiC can be precisely controlled using magnetic fields, enabling it to function as a MPI trackable microrobot. We provided a theoretical model elucidating MAGiCs unique properties, and validated its imaging and actuation performance through phantom studies and in vivo experiments. As a high-performance MPI tracer and magnetic microrobot with exceptional capabilities, MAGiC holds tremendous potential for diverse applications including cell tracking, targeted drug delivery as well as therapeutic interventions.

bioengineering↗

bioRxiv2024

Time-resolved cryo-EM (TRCEM) sample preparation using a PDMS-based microfluidic chip assembly

Time-resolved cryo-EM (TRCEM) makes it possible to provide structural and kinetic information on a reaction of biomolecules before the equilibrium is reached. Several TRCEM methods have been developed in the past to obtain key insights into the mechanism of action of molecules and molecular machines on the time scale of tens to hundreds of milliseconds, which is unattainable by the normal blotting method. Here we present our TRCEM setup utilizing a polydimethylsiloxane (PDMS)-based microfluidics chip assembly, comprising three components: a PDMS-based, internally SiO2-coated micromixer, a glass-capillary microreactor, and a PDMS-based microsprayer for depositing the reaction product onto the EM grid. As we have demonstrated in recent experiments, this setup is capable of addressing problems of severe sample adsorption and ineffective mixing of fluids, and leads to highly reproducible results in applications to the study of translation. As an example, we used our TRCEM sample preparation method to investigate the molecular mechanism of ribosome recycling mediated by High frequency of lysogenization X (HflX), which demonstrated the efficacy of the TRCEM device and its capability to yield biologically significant, reproducible information. This protocol has promise to provide structural and kinetic information on pre-equilibrium intermediates in the 10-1000 ms time range in applications to many other biological systems. Key featuresO_LIDesign and fabrication of high-performance splitting-and-recombination-based micromixer and planar microsprayer. C_LIO_LIProtocol for SiO2 coating on the PDMS surface and fabrication of the microfluidic chip assembly. C_LIO_LIPreparation of time-resolved cryo-EM sample in the time range of 10 - 1000 ms. C_LIO_LIData collection on EM grid covered with droplets from the microsprayer. C_LI

biophysics↗

bioRxiv2024

TurboID-based proximity labeling identifies novel germline proteins that maintain E granule integrity and small RNA homeostasis in C. elegans

Germ granules are biomolecular condensates composed of RNA and proteins that play crucial roles in RNA metabolism and posttranscriptional gene regulation. C. elegans germ granules consist of at least seven distinct subcompartments, including P granules, Z granules, Mutator foci, SIMR foci, P-bodies, D granules and E granules. Among these condensates, the E granule, which is nonrandomly positioned within the germ granule, is required for the production of a specialized class of small interfering RNAs (siRNAs). However, the mechanisms underlying E granule formation and its functional significance remain largely unexplored. In this study, via the use of TurboID- based proximity labeling technology combined with an RNAi-based reverse genetic screen, we identified two novel components of the E granule, EGC-2/C27B7.5 and EGC-3/F59G1.8, which initiate E granule assembly. The depletion of EGC-2 or EGC- 3 disrupts the perinuclear localization of the EGO and PICS complexes, both of which are enriched in E granules and are required for E-class siRNA and piRNA biogenesis, respectively. Small RNAomic analyses revealed that both EGC-2 and EGC-3 promote the production of 5 E-class siRNA, whereas prohibiting piRNA maturation. Taken together, our results elucidate the roles of EGC-2 and EGC-3 in maintaining E granule integrity and small RNA homeostasis, and suggest that intracellular condensation may exert distinct regulatory effects on different biological processes. Additionally, the combination of proximity labeling technology and reverse genetic screening provides a robust strategy for studying the assembly of biomolecular condensates.

genetics↗

bioRxiv2024

Passage through micro-sprayer increases functional activity-implications for activity assays in time-resolved cryo-EM

This study examines the validity of an assay that is used to report on the retainment of functional competence by ribosomes as they pass a micro-sprayer. We find a reproducible increase, rather than the expected decrease in GFP production as monitored by fluorescence, which suggests heterogeneity or partial aggregation of ribosomes in solution. An even larger increase in functional activity is observed when sonication is used, pointing to mechanical agitation as the decisive factor in both scenarios. The results have a bearing on the design and interpretation of validation experiments in time-resolved cryo-EM based on microfluidic chips.

biophysics↗

bioRxiv2024

An immunomechanical checkpoint PYK2 governs monocyte-to-macrophage differentiation in pancreatic cancer

Pancreatic ductal adenocarcinoma (PDAC) is characterized by a fibrotic, stiff tumor microenvironment (TME), where tumor-associated macrophages (TAMs) drive ECM remodeling, progression, and immune evasion. The contribution of mechanical cues to monocyte differentiation into TAMs remains largely unexplored. Here we show that mechanical force is required for monocyte-to-macrophage differentiation. PYK2, as an innovative immunomechanical checkpoint, de facto governs this differentiation process. We demonstrated that PYK2 senses mechanical signals via Piezo1 and integrins, triggering F-actin polymerization and translocating to the nucleus to regulate mechanotransduction and differentiation genes (e.g., ACTR3, RELA). Targeted deletion of PYK2 impairs the differentiation and polarization of monocyte-derived macrophages, reshapes the PDAC microenvironment, and enhances the efficacy of anti-PD-1 immunotherapy. These findings underscore the critical role of mechanical cues in monocyte differentiation and suggest that targeting PYK2 is a promising strategy to modulate TAM function and improve immunotherapy outcomes in patients with PDAC. Statement of significanceThis study identifies PYK2 as an immunomechanical checkpoint that drives monocyte-to-macrophage differentiation in PDAC via Piezo1/integrin-mediated mechanical cues. Targeted deletion of PYK2 reshapes the PDAC microenvironment, and enhances the efficacy of anti-PD-1 immunotherapy, suggesting PYK2 as a promising therapeutic target to overcome immunotherapy resistance.

immunology↗

bioRxiv2024

Fate mapping of peripherally derived macrophages reveals a long-lasting engrafted population that maintains a distinct transcriptomic profile for up to 8 months after Traumatic Brain Injury

Traumatic Brain Injury (TBI) is one of the most established environmental risk factors for the development of dementia and long term neurological deficits representing a critical health problem for our society. It is well-established that TBI-induced neuroinflammation contributes to the long-lasting cognitive deficits and engages brain-resident macrophages (microglia) as well as monocytes-derived macrophages (MDMs) recruited from the periphery. While numerous studies have characterized microglia response to TBI, and the critical role of early infiltrated MDMs in the development of cognitive dysfunctions, the fate of MDMs in TBI remains unknown. Microglia and MDMs have distinct embryological origins and it is unclear if MDMs can fully transition to microglia after infiltrating the brain. This gap in knowledge is due to the fact that after brain engraftment, MDMs stop expressing their signature markers, thus making discrimination from resident microglia cells elusive. Here, for the first time, we longitudinally trace the fate of MDMs by taking advantage of two complementary yet distinct fate mapping mouse lines, CCR2-creERT2 and Ms4a3-cre, where inflammatory monocytes are permanently labeled even after in situ reprogramming. We demonstrated that early infiltrated MDMs persist in the brain for up to 8 months after TBI in adult female and male mice. Notably, MDMs retain their phagocytic activity while remaining transcriptomically distinct from microglia, and show a signature associated with aging and disease. Our data significantly advance the understanding of long-lasting MDMs and provide critical knowledge for developing more targeted therapeutic interventions for myeloid cells.

immunology↗

bioRxiv2024

Lipid hydrogen isotope compositions primarily reflect growth water in the model archaeon Sulfolobus acidocaldarius

The stable hydrogen isotope composition ({delta}2H) of lipid biomarkers can track environmental processes and remain stable over geologically relevant time scales, enabling studies of past climate, hydrology, and ecology. Most research has focused on lipids from the domain Eukarya (e.g., plant waxes, long-chain alkanes), and the potential of prokaryotic lipid biomarkers from the domain Archaea to offer unique insights into environments not captured by eukaryotic lipids remains unclear. Here, we investigate the H-isotope composition of biphytanes in Sulfolobus acidocaldarius, a model thermoacidophile and obligate heterotroph. We conducted a series of experiments that varied temperature, pH, shaking rate, electron acceptor availability, or electron donor flux. From these experiments, we quantified the lipid/water H-isotope fractionation (2{varepsilon}L/W) values for core biphytane chains derived from tetraether lipids. The 2{varepsilon}L/W values are consistently negative (-230 to - 180 {per thousand}) and are relatively invariant across all experiments despite a 20-fold change in doubling times and 2-fold change in lipid cyclization. The magnitude and relative invariance of 2{varepsilon}L/W values are consistent with studies on other heterotrophic archaea and suggests archaeal lipids may be faithful recorders of the {delta}2H composition of growth water. Our study highlights the potential of archaeal lipid {delta}2H as a hydrological proxy, offering new insights into environments where traditional proxies, such as plant-derived lipids, are not available, including extreme environments and extraterrestrial settings. ImportanceReconstructing past climates is crucial for understanding Earths environmental history and its responses to changing conditions. This study examines Sulfolobus acidocaldarius, a thermoacidophilic archaeon that thrives in extreme environments like hot springs. These microorganisms incorporate hydrogen water in the growth environment into membrane lipids, creating hydrogen isotope signatures that can reflect hydroclimate conditions. Our findings show that these hydrogen isotope ratios remain consistent even under varying temperature, pH, oxygen levels, and electron donor fluxes, indicating a stable fractionation between lipids and water. This invariance suggests that S. acidocaldarius lipids could serve as a robust proxy for reconstructing ancient water H-isotope values, especially in extreme environments where traditional proxies, such as plant waxes, are absent. This research has broader implications for planetary-scale reconstructions, including potential applications in studying past climates on other planets, such as Mars, where similar microorganisms may have existed in hydrothermal conditions.

microbiology↗