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At least 73 records · Page 4

Sterol methyltransferases in uncultured bacteria complicate eukaryotic biomarker interpretations

Abstract Sterane molecular fossils are broadly interpreted as eukaryotic biomarkers, although diverse bacteria also produce sterols. Steranes with side-chain methylations can act as more specific biomarkers if their sterol precursors are limited to particular eukaryotes and are absent in bacteria. One such sterane, 24-isopropylcholestane, has been attributed to demosponges and potentially represents the earliest evidence for animals on Earth, but enzymes that methylate sterols to give the 24-isopropyl side-chain remain undiscovered. Here, we show that sterol methyltransferases from both sponges and yet-uncultured bacteria function in vitro and identify three methyltransferases from symbiotic bacteria each capable of sequential methylations resulting in the 24-isopropyl sterol side-chain. We demonstrate that bacteria have the genomic capacity to synthesize side-chain alkylated sterols, and that bacterial symbionts may contribute to 24-isopropyl sterol biosynthesis in demosponges. Together, our results suggest bacteria should not be dismissed as potential contributing sources of side-chain alkylated sterane biomarkers in the rock record.

59 BASIC BIOLOGICAL SCIENCES↗

Diagnosis of Alzheimer’s disease using plasma biomarkers adjusted to clinical probability

Abstract Recently approved anti-amyloid immunotherapies for Alzheimer’s disease (AD) require evidence of amyloid-β pathology from positron emission tomography (PET) or cerebrospinal fluid (CSF) before initiating treatment. Blood-based biomarkers promise to reduce the need for PET or CSF testing; however, their interpretation at the individual level and the circumstances requiring confirmatory testing are poorly understood. Individual-level interpretation of diagnostic test results requires knowledge of disease prevalence in relation to clinical presentation (clinical pretest probability). Here, in a study of 6,896 individuals evaluated from 11 cohort studies from six countries, we determined the positive and negative predictive value of five plasma biomarkers for amyloid-β pathology in cognitively impaired individuals in relation to clinical pretest probability. We observed that p-tau217 could rule in amyloid-β pathology in individuals with probable AD dementia (positive predictive value above 95%). In mild cognitive impairment, p-tau217 interpretation depended on patient age. Negative p-tau217 results could rule out amyloid-β pathology in individuals with non-AD dementia syndromes (negative predictive value between 90% and 99%). Our findings provide a framework for the individual-level interpretation of plasma biomarkers, suggesting that p-tau217 combined with clinical phenotyping can identify patients where amyloid-β pathology can be ruled in or out without the need for PET or CSF confirmatory testing.

Cell Biology↗

Exhaled breath biomarkers of influenza infection and influenza vaccination

Respiratory viral infections are considered a major public health threat, and breath metabolomics can provide new ways to detect and understand how specific viruses affect the human pulmonary system. In this pilot study, we characterized the metabolic composition of human breath for an early diagnosis and differentiation of influenza viral infection, as well as other types of upper respiratory viral infections. We first studied the non-specific effects of planned seasonal influenza vaccines on breath metabolites in healthy subjects after receiving the immunization. We then investigated changes in breath content from hospitalized patients with flu-like symptoms and confirmed upper respiratory viral infection. The exhaled breath was sampled using a custom-made breath condenser, and exhaled breath condensate (EBC) samples were analysed using liquid chromatography coupled to quadruplole-time-of-flight mass spectrometer (LC-qTOF). All metabolomic data was analysed using both targeted and untargeted approaches to detect specific known biomarkers from inflammatory and oxidative stress biomarkers, as well as new molecules associated with specific infections. We were able to find clear differences between breath samples collected before and after flu vaccine administration, together with potential biomarkers that are related to inflammatory processes and oxidative stress. Moreover, we were also able to discriminate samples from patients with flu-related symptoms that were diagnosed with confirmatory respiratory viral panels (RVPs). RVP positive and negative differences were identified, as well as differences between specific viruses defined. These results provide very promising information for the further study of the effect of influenza A and other viruses in human systems by using a simple and non-invasive specimen like breath.

60 APPLIED LIFE SCIENCES↗

Knowledge-guided learning with curated prior genetic biomarkers for robust model interpretation

Abstract Motivation Knowledge-guided learning offers effective and robust model training strategies in data-scarce settings by incorporating established domain knowledge, thereby enhancing generalization, robustness, and interpretability. By contrast, conventional deep learning approaches rely purely on data-driven learning, which can limit robust model interpretability, particularly in high-dimensional settings with limited size samples. In computational biology, knowledge-guided learning has primarily leveraged network- and structural-based knowledge, leading to biologically interpretable representations and enhanced predictive performance compared to conventional approaches. However, curated biomarkers, one of the most accessible forms of biological knowledge, remain largely unexplored within knowledge-guided paradigms. Results In this study, we propose a model-agnostic training paradigm, Biomarker-driven Explainable Prior-guided Learning (BioExPL), that can be applied to any neural networks that incorporates curated prior knowledge. BioExPL enforces neural networks to reflect curated biomarker priors in their latent representations through a novel knowledge-alignment loss. BioExPL consistently demonstrated significantly improved predictive performance and enhanced model interpretability with minimized computational overhead in simulation studies and intensive experiments on multiple cancer datasets. BioExPL not only integrates prior curated knowledge into the model but also accurately identifies unknown associated signals additionally. BioExPL is model-agnostic and domain-independent, enabling its integration into diverse neural network architectures. Availability and implementation The open-source is publicly available at: https://github.com/datax-lab/BioExPL.

Baek, Beomsu [Department of Computer Science, Univ↗

Multimodal imaging of hemorrhagic transformation biomarkers in an ischemic stroke model.

Abstract Hemorrhagic transformation of ischemic stroke has devastating consequences, with high mortality and poor functional outcomes. Animal models of ischemic stroke also demonstrate the potential for hemorrhagic transformation, which complicates biochemical characterization, treatment studies, and hinders poststroke functional outcomes in affected subjects. The incidence of hemorrhagic transformation of ischemic stroke in animal model research is not commonly reported. The postmortem brain of such cases presents a complex milieu of biomarkers due to the presence of healthy cells, regions of varying degrees of ischemia, dead and dying cells, dysregulated metabolites, and blood components (especially reactive Fe species released from lysed erythrocytes). To improve the characterization of hemorrhage biomarkers on an ischemic stroke background, we have employed a combination of histology, X-ray fluorescence imaging (XFI), and Fourier transform infrared (FTIR) spectroscopic imaging to assess 122 photothrombotic (ischemic) stroke brains. Rapid freezing preserves brain biomarkers in situ and minimizes metabolic artifacts due to postmortem ischemia. Analysis revealed that 25% of the photothrombotic models had clear signs of hemorrhagic transformation. The XFI and FTIR metabolites provided a quantitative method to differentiate key metabolic regions in these models. Across all hemorrhage cases, it was possible to consistently differentiate otherwise healthy tissue from other metabolically distinct regions, including the ischemic infarct, the ischemic penumbra, blood vessels, sites of hemorrhage, and a region surrounding the hemorrhage core that contained elevated lipid oxidation. Chemical speciation of deposited Fe demonstrates the presence of heme-Fe and accumulation of ferritin.

Pushie, M. J. (ORCID:0000000174945427)↗

Imaging biomarkers in neurodegeneration: current and future practices

There is an increasing role for biological markers (biomarkers) in the understanding and diagnosis of neurodegenerative disorders. The application of imaging biomarkers specifically for the in vivo investigation of neurodegenerative disorders has increased substantially over the past decades and continues to provide further benefits both to the diagnosis and understanding of these diseases. This review forms part of a series of articles which stem from the University College London/University of Gothenburg course “Biomarkers in neurodegenerative diseases”. In this review, we focus on neuroimaging, specifically positron emission tomography (PET) and magnetic resonance imaging (MRI), giving an overview of the current established practices clinically and in research as well as new techniques being developed. We will also discuss the use of machine learning (ML) techniques within these fields to provide additional insights to early diagnosis and multimodal analysis.

60 APPLIED LIFE SCIENCES↗

Long-Term Persistence of Three Microbial Wildfire Biomarkers in Forest Soils

Long-term monitoring of microbial communities in the rhizosphere of post-fire forests is currently one of the key knowledge gaps. Knowing the time scale of the effects is indispensable to aiding post-fire recovery in vulnerable woodlands, including holm oak forests, that are subjected to a Mediterranean climate, as is the case with forests that are found in protected areas such as the Sierra Nevada National and Natural Park in southeastern Spain. We took rhizosphere soil samples from burned and unburned holm oak trees approximately 3, 6, and 9 years after the 2005 fire that devastated almost 3500 ha in southeastern Spain. We observed that the prokaryotic communities are recovering but have not yet reached the conditions observed in the unburned forest. A common denominator between this fire and other fires is the long-term persistence of three ecosystem recovery biomarkers—specifically, higher proportions of the genera Arthrobacter, Blastococcus, and Massilia in soil microbial communities after a forest fire. These pyrophilous microbes possess remarkable resilience against adverse conditions, exhibiting traits such as xerotolerance, nitrogen mineralization, degradation of aromatic compounds, and copiotrophy in favorable conditions. Furthermore, these biomarkers thrive in alkaline environments, which persist over the long term following forest fires. The relative abundance of these biomarkers showed a decreasing trend over time, but they were still far from the values of the control condition. In conclusion, a decade does not seem to be enough for the complete recovery of the prokaryotic communities in this Mediterranean ecosystem.

54 ENVIRONMENTAL SCIENCES↗

Hopanoid Biomarker Preservation In Coniform (Phormidium) Stromatolites in Siliceous Thermal Springs, Yellowstone National Park

The microbial communities that characterize modem hydrothermal ecosystems serve as modern analogs to those thought to have dominated early environments on Earth and possibly Mars. The importance of such hydrothermal systems as targets in exploring for an early biosphere on Mars is well established. Such work provides an important basis for the analysis of Martian samples associated with such environments. The surviving molecular structure and isotopic signature of diagnostic lipid biomarkers found as chemical fossils can provide a link between modern bacterially dominated ecosystems and their ancient counterparts. We are interested in the processes involved in the deposition and/or degradation of organic material in moderately thermal, silicifying microbial mats, particularly as this relates to the potential for preservation of some biomarker components known to be more highly resistant to microbial degradation. Several excellent biomarker molecules are associated with the cyanobacteria that dominate these mats, particularly the 2-methylbacteriohopanepolyols (2-MeBHP). These compounds are ubiquitous on Earth and are not easily degraded in nature, a fact documented by their detection in ancient Earth rocks dating back as far as 2,700 Ma.

Jahnke, Linda L.↗

Use of Molecular Fossils for the Interpretation of Paleoenvironments on Early Earth: The Synthesis of Lipid Biomarkers by Methane-Oxidizing Bacteria

Over the course of Earth's history, the most important biological influence has come from the evolution of oxygenic photosynthesis and the development of an oxygen-rich biosphere. Although the availability of free oxygen had profound effects on subsequent biological and planetary evolution, clear paleobiological evidence of the timing of this transition is lacking. Recent technical advances in the microanalysis of organic matter has made it possible to detect residual molecules (biomarkers) in proterozoic (2.5 to 0.6 billion years) sedimentary rock characteristic of specific groups of microorganisms. When coupled with the carbon isotopic fractionations characteristic of biological systems and the new field of compound specific isotope analysis, biomarkers could prove to be a powerful tool for decoding ancient biochemistry from the geological record. We have been studying the carbon isotope fractionations associated with the synthesis of organic biomarker molecules in several types of methane-oxidizing bacteria that should have been key to carbon cycling in paleoenvironments after the evolution of oxygenic photosynthesis.

Jahnke, Linda L.↗

Identification of Methanotrophic Biomarker Lipids in the Symbiont-Containing Gills of Seep Mussels

Mussels collected from hydrocarbon seeps in the Gulf of Mexico grow with methane as sole carbon and energy source due to a symbiotic association with methane-oxidizing bacteria. Transmission electron micrographs of mussel gills show cells with stacked intracytoplasmic membranes similar to type I methanotrophic bacteria. Methanotrophs are known to synthesize several types of cyclic triterpenes, hopanoids and methyl sterols, as well as unique monounsaturated fatty acid, double bond positional isomers that serve as biomarkers for this group. Lipid analysis of dissected mussels demonstrated the presence of these biomarkers predominantly in the gill tissue with much smaller amounts in mantle and remaining body tissues. Gill tissue contained 1150 micrograms/g dry wt. of hopanepolyol derivatives and diplopterol while the mantle tissue contained only 17 micrograms/g. The C16 monounsaturated fatty acids (16:1) characteristic of type I methanotrophic membranes dominated the gill tissue making up 53% of the total while only 5% 16:1 was present in the mantle tissue. The methyl sterol distribution was more dispersed. The predominant sterol in all tissues was cholesterol with lesser amounts of other desmethyl and 4-methyl sterols. The gill and mantle tissues contained 3461 micrograms (17% methyl) and 2750 micrograms (5% methyl) sterol per gm dry wt., respectively. Methyl sterol accounted for 44% of the sterol esters isolated from the gill, suggesting active demethylation of the methanotrophic sterols in this tissue. The use of lipid biomarkers could provide an effective means for identifying host-symbiont relationships.

Jahnke, L. L.↗

Lipid Biomarkers for Methanogens in Hypersaline Cyanobacterial Mats for Guerrero Negro, Baja California Sur

Analyses of sediments from the vicinity of active methane seeps have uncovered a particular suite of lipid biomarker patterns that characterize methane consuming archaea and their syntrophic, sulfate reducing partners. These isoprenoid biomarkers, largely identified by their anomalously light carbon isotopic signatures, have been a topic of intense research activity and are recorded in numerous methane-rich environments from Holocene to Cenozoic. This phenomenon has implications for depleted kerogens at 2.7 Ga on early Earth (Hinrichs 2002). In contrast, the lipid biosignatures of methane producing archaea are not readily identified through distinct isotopic labels and have received comparably little attention in analyses of archaea in environmental samples. Indeed, environmental analyses generally detect only free archaeal lipids, not the intact, polar molecules found in the membrane of living organisms. As part of the Ames NAI, the 'Early Microbial Ecosystem Research Group' (EMERG) is working to understand microbial processes in the hypersaline cyanobacterial mats growing in the salt evaporation ponds of the Exportadora de Sal at Guerrero Negro, Baja California Sur, Mexico. The aim of this study was to develop methods by which we could identify the organisms responsible for methane generation in this environment. While the ester-bound fatty acids, hopanoids and wax esters provide a means to identify most of the bacterial components of these mats, the archaea which Ere evidently present through genomic assays and the fact of intense methane production (Hoehler et al. 200l), have not been identified through their corresponding lipid signatures. Archaeal core lipids present a number of analytical challenges. The core lipids of methanogens comprise C20, C40 and sometimes C25 isoprenoid chains, linked through ether bonds to glycerol. As well as archaeal (C20), sn-2- and sn-3-hydroxyarchaeol are associated particularly with methylotrophic methanogens. Recently, we have also identified a dihydroxyarchaeol in a hyperthermophilic methanogen (Summons et al. 2002). Additional structural diversity is encoded into the polar head groups that are attached to the glycerol ether cores. The C20 core lipids are readily analyzed by GC-MS as their volatile trimethylsilyl derivatives while compounds with intact polar head groups can only be detected using LC-MS approaches. Our approach was to utilize the alternative of an ether cleavage reagent (BBr3 vs. HI) and a hydride reducing agent to convert all ether lipids to hydrocarbon in order to provide a vertical profile of quantitative information that might be matched to methane fluxes. We have found that while conventional acid hydrolysis and HI treatment will destroy hydroxyarchaeols, molecular information remains intact through use of BBr3 for ether cleavage. This method revealed the presence of traces of biphytane and various ether alkyls associated with some sulfate reducing bacteria within the mat structure. An interesting, and potentially valuable, byproduct of the method utilizing HI was the identification of abundant homohopanoids after superhydride reduction. Evidently present as sulfur-bound diagenetic products these hopanoids are likely cyanobacterial biomarkers in the early stages of diagenetic preservation.

Jahnke, Linda L.↗

Hydrocarbon Biomarker Stratigraphy of C-Isotopic Excursions Marking Chemical Changes in the Ocean with Contemporanious Biotic Extinction-Radiation Events

One paper recording progress in this topic has been accepted for publication. We report a method for the rigorous identification of biomarkers (crocetane and PMI) that may be specific for methanotrophic and methanogenic archaea and, perhaps, the process of anaerobic oxidation of methane. If catastrophic methane efflux from sub-sea methane hydrate is responsible for extinction events, as has been hypothesized by many workers, then we might expect to find biomarkers for methane oxidation in sediments marking some extinction boundaries. Unfortunately, identifying crocetane and PMI with certainty is not a trivial exercise and these biomarkers appear to have been mis-identified in a recent publication by workers from Curtin University. Barber et al. (2001) identified crocetane and PMI in sediments deposited in the basal Triassic of the Perth Basin, Australia. However, Barber et al. (2001) also found crocetane and PMI in many other sediments and oils in a way that was inconsistent with our knowledge of these systems.

Summons, Roger E.↗

Carbon isotopic fractionation in lipids from methanotrophic bacteria: relevance for interpretation of the geochemical record of biomarkers

Experiments with cultured aerobic methane oxidising bacteria confirm that their biomarker lipids will be significantly depleted in 13C compared to the substrate. The methanotrophic bacteria Methylococcus capsulatus and Methylomonas methanica, grown on methane and using the RuMP cycle for carbon assimilation, show maximum 13C fractionation of approximately 30% in the resultant biomass. In M. capsulatus, the maximum fractionation is observed in the earliest part of the exponential growth stage and decreases to approximately 16% as cells approach stationary phase. This change may be associated with a shift from the particulate form to the soluble form of the methane monooxygenase enzyme. Less than maximum fractionation is observed when cells are grown with reduced methane availability. Biomass of M. capsulatus grown on methanol was depleted by 9% compared to the substrate. Additional strong 13C fractionation takes place during polyisoprenoid biosynthesis in methanotrophs. The delta 13C values of individual hopanoid and steroid biomarkers produced by these organisms were as much as l0% more negative than total biomass. In individual cultures, squalene was 13C-enriched by as much as 14% compared to the triterpane skeleton of bacteriohopaneaminopentol. Much of the isotopic dispersion in lipid metabolites could be attributed to shifts in their relative abundances, combined with an overall reduction in fractionation during the growth cycle. In cells grown on methanol, where there was no apparent effect of growth stage on overall fractionation there were still significant isotopic differences between closely related lipids including a 5.3% difference between the hopane and 3 beta-methylhopane skeletons. Hopane and sterane polyisoprenoids were also 13C-depleted compared to fatty acids. These observations have significant implications for the interpretation of specific compound isotopic signatures now being measured for hydrocarbons and other lipids present in sediments and petroleum. In particular, biomarker lipids produced by a single organism do not necessarily have the same carbon isotopic composition.

NASA Center ARC↗

Chiral Biomarkers in Meteorites

The chirality of organic molecules with the asymmetric location of group radicals was discovered in 1848 by Louis Pasteur during his investigations of the rotation of the plane of polarization of light by crystals of sodium ammonium paratartrate. It is well established that the amino acids in proteins are exclusively Levorotary (L-aminos) and the sugars in DNA and RNA are Dextrorotary (D-sugars). This phenomenon of homochirality of biological polymers is a fundamental property of all life known on Earth. Furthermore, abiotic production mechanisms typically yield recemic mixtures (i.e. equal amounts of the two enantiomers). When amino acids were first detected in carbonaceous meteorites, it was concluded that they were racemates. This conclusion was taken as evidence that they were extraterrestrial and produced by abiologically. Subsequent studies by numerous researchers have revealed that many of the amino acids in carbonaceous meteorites exhibit a significant L-excess. The observed chirality is much greater than that produced by any currently known abiotic processes (e.g. Linearly polarized light from neutron stars; Circularly polarized ultraviolet light from faint stars; optically active quartz powders; inclusion polymerization in clay minerals; Vester-Ulbricht hypothesis of parity violations, etc.). This paper compares the measured chirality detected in the amino acids of carbonaceous meteorites with the effect of these diverse abiotic processes. IT is concluded that the levels observed are inconsistent with post-arrival biological contamination or with any of the currently known abiotic production mechanisms. However, they are consistent with ancient biological processes on the meteorite parent body. This paper will consider these chiral biomarkers in view of the detection of possible microfossils found in the Orgueil and Murchison carbonaceous meteorites. Energy dispersive x-ray spectroscopy (EDS) data obtained on these morphological biomarkers will be presented to show that the elemental compositions of these morphological biomarkers are not consistent with the compositions expected for modern (i.e. post-arrival) biological contaminants.

Hoover, Richard B.↗

NSCOR for Evaluating Risk Factors and Biomarkers for Adaptation and Resilience to Spaceflight: Emotional Valence and Social Processes in ICC/ICE Environments

Space exploration class missions, such as a mission to Mars, will require optimization of human performance, adaptability, and resilience. This NASA Specialized Center of Research (NSCOR) utilizes the NIMH Research Domain Criteria (RDoC) framework to identify biological and behavioral markers of individual social adaptation and emotional resilience (as well as vulnerability) to spaceflight-relevant stressors such as living in extended isolation. The overarching goal of this NSCOR is to obtain novel information to help identify biomarkers of individuals who are resilient and/or adaptable to the stressors of isolated, confined, and controlled (ICC) and isolated, confined, and extreme (ICE) environments.A total of N=90 healthy adult astronaut surrogates are being studied in three spaceflight-analog environments: (1) n=40 healthy adults in the Isolation and Confinement Analog Research Unit (ICARUS), an ICC at the University of Pennsylvania, during 7-day missions, for a target total of 280 subject days; (2) n=32 healthy adult astronaut surrogates studied in NASA’s Human Exploration Research Analog (HERA), an ICC at Johnson Space Center during 45-day missions, for a target total of 2,112 subject days; and (3) n=18 healthy adults in the Alfred-Wegener-Institute’s Neumayer Station III, an ICE in Antarctica, during 14-month missions, for a target total of 7,560 subject days. Dr. Nindl’s Laboratory at the University of Pittsburgh is analyzing a priori selected protein biomarkers in blood, saliva, and urine. Complementary rodent models of exposure to early life stressors, confinement, and isolation are being evaluated at Dr. Hensch’s Laboratory to further validate the neurobehavioral and biological findings from the human studies.Given the inconsistency and varied definition of resilience/adaptation in the scientific literature, the NSCOR team developed a composite resilience/adaptation measure that reflects the most relevant outcomes to resilience/adaptation across psychosocial and neurobehavioral functions, as well as neurocognitive and spaceflight-relevant operational performance. To achieve this, group consensus was attained from subject matter experts to produce a rank-order of importance for each input variable. The final resilience/adaptation score included 36 variables that were collected across spaceflight analogs. As of 10/1/2021, the NSCOR project acquired data on n=27 subjects at ICARUS, n=16 at HERA, and n=18 at Neumayer. The COVID-19 pandemic delayed data acquisition at ICARUS and HERA.Among subjects studied to date, 99% of neural and neurobehavioral data (e.g., neuroimaging for structure and function, behavioral measures) as well as blood, saliva, and urine for biochemical assays have been acquired. For rodent models, Dr. Hensch’s laboratory has established biochemical and behavioral parameters reflecting confinement stress in social networks of mice for comparison to stress responses in the human spaceflight analog environments.Group social behaviors were measured with a Social Network Analysis (SNA) approach to define objective parameters associated with sociability and its plasticity by sex. This analytic approach may help identify a network of individuals who are more effective teammates or more likely to generate new social relationships. Data acquisition, biomarker assessment, and data quality control will continue through September 2022.

D F Dinges↗

Effect of salinity on the preservation of biomarkers in hypersaline microbial mat kerogens

Kerogen is the residue that remains after the minerals and organic compounds have been extracted from a rock using acid and organic solvents, respectively [1]. It is not only the largest organic carbon sink in the geological record but the best-preserved fraction due to its recalcitrance and ability to retain syngenetic source information during deposition [2]. Due to the complex, macromolecular, cross-linked polymeric structure of kerogen, it is difficult to analyse intact, often requiring breakdown into smaller subunits through thermal (pyrolysis) or chemical treatment (chemolysis) [3]. Saline and hypersaline environments host diverse microbial communities, which can trap and bind organic matrices such as cellular components (e.g., extracellular polymeric substances, cell wall, peptidoglycan, sheath material, etc.) with sediments, forming layered, laminated structures called microbial mats. Here we present depth profiles of two hypersaline cores through a microbial mat with differing total salinities. We looked at the composition of organic compounds released from kerogen during high temperature, hydrogen-assisted, pyrolysis to understand the effect of salinity on the composition and timing of their incorporation [4]. Field Site: The Exportadora del Sal S. A. (ESSA) saltern of Guerrero Negro (Baja California Sur, Mexico) lies within a typical sabhka environment adjacent to Laguna Ojo de Liebre. Note the spatial extent of the 13 major ponds of the ESSA system. The GN ponds thrive under well-monitored and stable conditions with steady state accretion and degradation of mat layers (around 0.5–1.4 cm per year). Organic mats typically attain up to 10 cm in thickness, depending on the location, which represents about 60 years of growth since these ponds were established. Sedimentation rate is rapid in these non-lithifying and non-mineralising mats, 1–1.5 cm per year. This environment is ideal for investigating in situ lipid preservation and diagenesis without the influence of constantly changing physical parameters. Methods: P4n5 and P5AB cores were collected as ~9 cm and 6.5 cm fresh cores, respectively, in June 2001 and September 2010, respectively from the ESSA saltern. The P4n5 core (9-9.1% salinity) was taken from Pond 4 near 5 and sub-divided into 10 layers. The P5AB core (11.2% salinity) was taken from Pond 5A near 5B and sub-divided into 8 layers. Lyophilised microbial mat powders were solvent-extracted using a modified Bligh-Dyer method and analysed by gas chromatography-mass spectrometry (GC-MS). Additionally, a subset of layers—layer 4 and layer 7—which represented active biomass and sediment-processed, respectively, were subjected to mild-acid methanolysis. The respective residues from conventional solvent extraction and acid methanolysis were loaded with a molybdenum sulfide catalyst and placed into a stainless-steel reactor. Samples were run on the hydropyrolysis set up (heated to 500 °C with 13-15 MPa of H2 pressure), extracted, and analysed by GC-MS. Results: Molecular profiles from the two ponds were significantly different and reflect the contributions of different photosynthetic and respiratory microbial communities to preserved organic matter. For example, the higher salinity P5AB core showed evidence of greater archaeal inputs (similarly observed in lab culture experiments [5]) as well as potential kerogen-bound carotenoids/carotenoid rearranged products or fragments. A hydrophobic emulsion formed during the acid methanolysis processing of layer 4 from both P4n5 and P5AB and layer 7 of P5AB. Hydropyrolysis of this hydrophobic residues released a greater abundance of polycyclic lipids relative to the pre-extracted control. Implications and Future Work: Catalytic hydropyrolysis of kerogen can rapidly generate abundant saturated pyrolysate products from the bound biomarker pool without altering the structures or stereochemistries of the products [6]. Chemical processing of solvent-extractable residues indicated that cellular matrices such as extracellular polymeric substances (EPS) may play a role in the sequestration of polycyclic lipid biomarkers such as steranes and hopanes. Their higher relative abundance compared to the pre-extracted control in the higher salinity layers and cores preliminarily aligns with this hypothesis, although further experiments are required to confirm this. It has been well-documented that EPS plays an important role in mineralisation, specifically carbonate formation, in microbial ecosystems. EPS can enhance calcium carbonate precipitation by providing diffusion-limited sites that create alkalinity gradients in response to microbial processes [7]. It has been experimentally demonstrated that salinity influences the total amount of EPS (both loosely- and tightly-bound) which increases with increasing salinity [8]. The higher salinity at Guerrero Negro switches the microbial population from filamentous Microcoleus to being dominated by Phormidium, Oscillatoria, and unicellular cyanobacteria. We demonstrated that lipid binding into kerogen via strong covalent linkages occurs at the very earliest stages of sedimentary diagenesis. We are currently investigating the influence of salinity on organic preservation through experimental and modelling approaches. Understanding how key biomarkers transform into preserved organic matter (i.e., from precursor biolipids to bound geolipids) in brine ecosystems will aid the search for organic biosignatures on other planetary bodies, especially Icy Moons and modern Mars.

hypersaline↗

Machine Learning Correlation of Electron Micrographs and ToF-SIMS for the Analysis of Organic Biomarkers in Mudstone

The spatial distribution of organics in geological samples can be used to determine when and how these organics were incorporated into the host rock. Mass spectrometry (MS) imaging can rapidly collect a large amount of data, but ions produced are mixed without discrimination, resulting in complex mass spectra that can be difficult to interpret. Here, we apply unsupervised and supervised machine learning (ML) to help interpret spectra from time-of-flight-secondary ion mass spectrometry (ToF-SIMS) of an organic-carbon-rich mudstone of the Middle Jurassic of England (UK). It was previously shown that the presence of sterane molecular biomarkers in this sample can be detected via ToF-SIMS (Pasterski, M. J. et al., Astrobiology 2023, 23, 936). We use unsupervised ML on scanning electron microscopy–electron dispersive spectroscopy (SEM-EDS) measurements to define compositional categories based on differences in elemental abundances. We then test the ability of four ML algorithms─k-nearest neighbors (KNN), recursive partitioning and regressive trees (RPART), eXtreme gradient boost (XGBoost), and random forest (RF)─to classify the ToF-SIM spectra using (1) the categories assigned via SEM-EDS, (2) organic and inorganic labels assigned via SEM-EDS, and (3) the presence or absence of detectable steranes in ToF-SIMS spectra. In terms of predictive accuracy and balanced accuracy, KNN was the best performing model and RPART the worst. The feature importance, or the specific features of the ToF-SIM spectra used by the models to make classifications, cannot be determined for KNN, preventing posthoc model interpretation. Nevertheless, the feature importance extracted from the other models was useful for interpreting spectra. In conclusion, we determined that some of the organic ions used to classify biomarker containing spectra may be fragment ions derived from kerogen which is abundant in this mudstone sample.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Proteomic assessment of serum biomarkers of longevity in older men

The biological bases of longevity are not well understood, and there are limited biomarkers for the prediction of long life. We used a high-throughput, discovery-based proteomics approach to identify serum peptides and proteins that were associated with the attainment of longevity in a longitudinal study of community-dwelling men age ≥65 years. Baseline serum in 1196 men were analyzed using liquid chromatography–ion mobility–mass spectrometry, and lifespan was determined during ~12 years of follow-up. Men who achieved longevity (≥90% expected survival) were compared to those who died earlier. Rigorous statistical methods that controlled for false positivity were utilized to identify 25 proteins that were associated with longevity. All these proteins were in lower abundance in long-lived men and included a variety involved in inflammation or complement activation. Lower levels of longevity-associated proteins were also associated with better health status, but as time to death shortened, levels of these proteins increased. Pathway analyses implicated a number of compounds as important upstream regulators of the proteins and implicated shared networks that underlie the observed associations with longevity. Overall, these results suggest that complex pathways, prominently including inflammation, are linked to the likelihood of attaining longevity. This work may serve to identify novel biomarkers for longevity and to understand the biology underlying lifespan.

60 APPLIED LIFE SCIENCES↗