Cognitive modeling of the Mnemonic Similarity Task as a digital biomarker for Alzheimer's Disease

AD related pathologies, such as beta-amyloid (Aβ) and phosphorylated tau (pTau), are evident decades before any noticeable decline in memory occurs. Identifying individuals during this asymptomatic phase is crucial for timely intervention. The Mnemonic Similarity Task (MST), a modified recognition memory task, is especially relevant for early AD screening, as it assesses hippocampal integrity, a region affected (both directly and indirectly) early in the progression of the disease. Further, strong inferences on the underlying cognitive mechanisms that support performance on this task can be made using Bayesian cognitive modeling. We assessed whether analyzing MST performance using a cognitive model could detect subtle changes in cognitive function and AD biomarker status prior to overt cognitive decline. We analyzed MST data from >200 individuals (young, cognitively healthy older adults, and individuals with MCI), a subset of which also had existing CSF Aβ and pTau data. Traditional performance scores and cognitive modeling using multinomial processing trees was applied to each participants MST data using Bayesian approaches. We assessed how well each could predict age group, memory ability, MCI status, Aβ/pTau status using ROC analyses. Both approaches predicted age group membership equally, but cognitive modeling approaches exceeded traditional metrics in all other comparisons. This work establishes that cognitive modeling of the MST can detect individuals with AD prior to cognitive decline, making it a potentially useful tool for both screening and monitoring older adults during the asymptomatic phase of AD.

Community ecology and functional potential of bacteria, archaea, eukarya and viruses in Guerrero Negro microbial mat

In this study, the microbial ecology, potential environmental adaptive mechanisms, and the potential evolutionary interlinking of genes between bacterial, archaeal and viral lineages in Guerrero Negro (GN) microbial mat were investigated using metagenomic sequencing across a vertical transect at millimeter scale. The community composition based on unique genes comprised bacteria (98.01%), archaea (1.81%), eukarya (0.07%) and viruses (0.11%). A gene-focused analysis of bacteria archaea, eukarya and viruses showed a vertical partition of the community. The greatest coverages of genes of bacteria and eukarya were detected in first layers, while the highest coverages of genes of archaea and viruses were found in deeper layers. Many genes potentially related to adaptation to the local environment were detected, such as UV radiation, multidrug resistance, oxidative stress, heavy metals, salinity and desiccation. Those genes were found in bacterial, archaeal and viral lineages with 6477, 44, and 1 genes, respectively. The evolutionary histories of those genes were studied using phylogenetic analysis, showing an interlinking between domains in GN mat.

Assessing hypo-arousal during reward anticipation with pupillometry in patients with major depressive disorder: replication and correlations with anhedonia

Major depressive disorder (MDD) is a devastating and heterogenous disorder for which there are no approved biomarkers in clinical practice. We recently identified anticipatory hypo-arousal indexed by pupil responses as a candidate mechanism subserving depression symptomatology. Here, we conducted a replication and extension study of these findings. We analyzed a replication sample of 40 unmedicated patients with a diagnosis of depression and 30 healthy control participants, who performed a reward anticipation task while pupil responses were measured. Using a Bayesian modelling approach taking measurement uncertainty into account, we could show that the negative correlation between pupil dilation and symptom load during reward anticipation is replicable within MDD patients, albeit with a lower effect size. Furthermore, with the combined sample of 136 participants (81 unmedicated depressed and 55 healthy control participants), we further showed that reduced pupil dilation in anticipation of reward is inversely associated with anhedonia items of the Beck Depression Inventory in particular. Moreover, using simultaneous fMRI, particularly the right anterior insula as part of the salience network was negatively correlated with depressive symptom load in general and anhedonia items specifically. The present study supports the utility of pupillometry in assessing noradrenergically mediated hypo-arousal during reward anticipation in MDD, a physiological process that appears to subserve anhedonia.

Microbial isolation and characterization from two flex lines from the urine processor assembly onboard the international space station

Urine, humidity condensate, and other sources of non-potable water are processed onboard the International Space Station (ISS) by the Water Recovery System (WRS) yielding potable water. While some means of microbial control are in place, including a phosphoric acid/hexavalent chromium urine pretreatment solution, many areas within the WRS are not available for routine microbial monitoring. Due to refurbishment needs, two flex lines from the Urine Processor Assembly (UPA) within the WRS were removed and returned to Earth. The water from within these lines, as well as flush water, was microbially evaluated. Culture and culture-independent analysis revealed the presence of Burkholderia, Paraburkholderia, and Leifsonia. Fungal culture also identified Fusarium and Lecythophora. Hybrid de novo genome analysis of the five distinct Burkholderia isolates identified them as B. contaminans, while the two Paraburkholderia isolates were identified as P. fungorum. Chromate-resistance gene clusters were identified through pangenomic analysis that differentiated these genomes from previously studied isolates recovered from the point-of-use potable water dispenser and/or current NCBI references, indicating that unique populations exist within distinct niches in the WRS. Beyond genomic analysis, fixed samples directly from the lines were imaged by environmental scanning electron microscopy, which detailed networks of fungal-bacterial biofilms. This is the first evidence of biofilm formation within flex lines from the UPA onboard the ISS. For all bacteria isolated, biofilm potential was further characterized, with the B. contaminans isolates demonstrating the most considerable biofilm formation. Moreover, the genomes of the B. contaminans revealed secondary metabolite gene clusters associated with quorum sensing, biofilm formation, antifungal compounds, and hemolysins. The potential production of these gene cluster metabolites was phenotypically evaluated through biofilm, bacterial-fungal interaction, and hemolytic assays. Collectively, these data identify the UPA flex lines as a unique ecological niche and novel area of biofilm growth within the WRS. Further investigation of these organisms and their resistance profiles will enable engineering controls directed toward biofilm prevention in future space station water systems.

Dual thermal ecotypes coexist within a nearly genetically identical population of the unicellular marine cyanobacterium Synechococcus

The extent and ecological significance of intraspecific functional diversity within marine microbial populations is still poorly understood, and it remains unclear if such strain-level microdiversity will affect fitness and persistence in a rapidly changing ocean environment. In this study, we cultured 11 sympatric strains of the ubiquitous marine picocyanobacterium Synechococcus isolated from a Narragansett Bay (RI) phytoplankton community thermal selection experiment. Thermal performance curves revealed selection at cool and warm temperatures had subdivided the initial population into thermotypes with pronounced differences in maximum growth temperatures. Curiously, the genomes of all 11 isolates were almost identical (average nucleotide identities of >99.99%, with >99% of the genome aligning) and no differences in gene content or single nucleotide variants were associated with either cool or warm temperature phenotypes. Despite a very high level of genomic similarity, sequenced epigenomes for two strains showed differences in methylation on genes associated with photosynthesis. These corresponded to measured differences in photophysiology, suggesting a potential pathway for future mechanistic research into thermal microdiversity. Our study demonstrates that present-day marine microbial populations can harbor cryptic but environmentally relevant thermotypes which may increase their resilience to future rising temperatures.

Parsing memory and nonmemory contributions to age-related declines in mnemonic discrimination performance: a hierarchical Bayesian diffusion decision modeling approach

The mnemonic discrimination task (MDT) is a widely used cognitive assessment tool. Performance in this task is believed to indicate an age-related deficit in episodic memory stemming from a decreased ability to pattern-separate among similar experiences. However, cognitive processes other than memory ability might impact task performance. In this study, we investigated whether nonmnemonic decision-making processes contribute to the age-related deficit in the MDT. We applied a hierarchical Bayesian version of the Ratcliff diffusion model to the MDT performance of 26 younger and 31 cognitively normal older adults. It allowed us to decompose decision behavior in the MDT into different underlying cognitive processes, represented by specific model parameters. Model parameters were compared between groups, and differences were evaluated using the Bayes factor. Our results suggest that the age-related decline in MDT performance indicates a predominantly mnemonic deficit rather than differences in nonmnemonic decision-making processes. In addition, this mnemonic deficit might also involve a slowing in processes related to encoding and retrieval strategies, which are relevant for successful memory as well. These findings help to better understand what cognitive processes contribute to the age-related decline in MDT performance and may help to improve the diagnostic value of this popular task.

Analyzing microbial evolution through gene and genome phylogenies

Microbiome scientists critically need modern tools to explore and analyze microbial evolution. Often this involves studying the evolution of microbial genomes as a whole. However, different genes in a single genome can be subject to different evolutionary pressures, which can result in distinct gene-level evolutionary histories. To address this challenge, we propose to treat estimated gene-level phylogenies as data objects, and present an interactive method for the analysis of a collection of gene phylogenies. We use a local linear approximation of phylogenetic tree space to visualize estimated gene trees as points in low-dimensional Euclidean space, and address important practical limitations of existing related approaches, allowing an intuitive visualization of complex data objects. We demonstrate the utility of our proposed approach through microbial data analyses, including by identifying outlying gene histories in strains of Prevotella, and by contrasting Streptococcus phylogenies estimated using different gene sets. Our method is available as an open-source R package, and assists with estimating, visualizing, and interacting with a collection of bacterial gene phylogenies.

Conserved functions of prion candidates suggest a primeval role of protein self-templating

Amyloid-based prions have simple structures, a wide phylogenetic distribution, and a plethora of functions in contemporary organisms, suggesting they may be an ancient phenomenon. However, this hypothesis has yet to be addressed with a systematic, computational, and experimental approach. Here we present a framework to help guide future experimental verification of candidate prions with conserved functions to understand their role in the early stages of evolution and potentially in the origins of life. We identified candidate prions in all high-quality proteomes available in UniProt computationally, assessed their phylogenomic distributions, and analyzed candidate-prion functional annotations. Of the 27 980 560 proteins scanned, 228 561 were identified as candidate prions (~0.82%). Among these candidates, there were 84 Gene Ontology (GO) terms conserved across the three domains of life. We found that candidate prions with a possible role in adaptation were particularly well-represented within this group. We discuss unifying features of candidate prions to elucidate the primeval roles of prions and their associated functions. Candidate prions annotated as transcription factors, DNA binding, and kinases are particularly well suited to generating diverse responses to changes in their environment and could allow for adaptation and population expansion into more diverse environments. We hypothesized that a relationship between these functions and candidate prions could be evolutionarily ancient, even if individual prion domains themselves are not evolutionarily conserved. Candidate prions annotated with these universally occurring functions potentially represent the oldest extant prions on Earth and are therefore excellent experimental targets.

Analyzing microbial evolution through gene and genome phylogenies

Microbiome scientists critically need modern tools to explore and analyze microbial evolution. Often this involves studying the evolution of microbial genomes as a whole. However, different genes in a single genome can be subject to different evolutionary pressures, which can result in distinct gene-level evolutionary histories. To address this challenge, we propose to treat estimated gene-level phylogenies as data objects, and present an interactive method for the analysis of a collection of gene phylogenies. We use a local linear approximation of phylogenetic tree space to visualize estimated gene trees as points in low-dimensional Euclidean space, and address important practical limitations of existing related approaches, allowing an intuitive visualization of complex data objects. We demonstrate the utility of our proposed approach through microbial data analyses, including by identifying outlying gene histories in strains of Prevotella, and by contrasting Streptococcus phylogenies estimated using different gene sets. Our method is available as an open-source R package, and assists with estimating, visualizing and interacting with a collection of bacterial gene phylogenies. dimension reduction, microbiome, non-Euclidean, statistical genetics, visualization.

Bayesian Modeling of the Mnemonic Similarity Task Using Multinomial Processing Trees

The Mnemonic Similarity Task (MST: Stark et al., 2019) is a modified recognition memory task designed to place strong demand on pattern separation. The sensitivity and reliability of the MST make it an extremely valuable tool in clinical settings. We develop new cognitive models, based on the multinomial processing tree framework, for two versions of the MST. The models are implemented as generative probabilistic models and applied to behavioral data using Bayesian graphical modeling methods. We demonstrate how the combination of cognitive modeling and Bayesian methods allows for flexible and powerful inferences about performance on the MST. These demonstrations include latent-mixture extensions for identifying individual differences in decision strategies, and hierarchical extensions that measure fine-grained differences in the ability to detect lures. One key finding is that the availability of a "similar" response in the MST reduces individual differences in decision strategies and allows for more direct measurement of recognition memory.

A review of applications of the Bayes factor in psychological research

The last 25 years have shown a steady increase in attention for the Bayes factor as a tool for hypothesis evaluation and model selection. The present review highlights the potential of the Bayes factor in psychological research. We discuss six types of applications: Bayesian evaluation of point null, interval, and informative hypotheses, Bayesian evidence synthesis, Bayesian variable selection and model averaging, and Bayesian evaluation of cognitive models. We elaborate what each application entails, give illustrative examples, and provide an overview of key references and software with links to other applications. The article is concluded with a discussion of the opportunities and pitfalls of Bayes factor applications and a sketch of corresponding future research lines. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Evaluating the complexity and falsifiability of psychological models

Understanding model complexity is important for developing useful psychological models. One way to think about model complexity is in terms of the predictions a model makes and the ability of empirical evidence to falsify those predictions. We argue that existing measures of falsifiability have important limitations and develop a new measure. KL-delta uses Kullback-Leibler divergence to compare the prior predictive distributions of models to the data prior that formalizes knowledge about the plausibility of different experimental outcomes. Using introductory conceptual examples and applications with existing models and experiments, we show that KL-delta challenges widely held scientific intuitions about model complexity and falsifiability. In a psychophysics application, we show that hierarchical models with more parameters are often more falsifiable than the original nonhierarchical model. This counters the intuition that adding parameters always makes a model more complex. In a decision-making application, we show that a choice model incorporating response determinism can be harder to falsify than its special case of probability matching. This counters the intuition that if one model is a special case of another, the special case must be less complex. In a memory recall application, we show that using informative data priors based on the serial position curve allows KL-delta to distinguish models that otherwise would be indistinguishable. This shows the value in model evaluation of extending the notion of possible falsifiability, in which all data are considered equally likely, to the more general notion of plausible falsifiability, in which some data are more likely than others. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Importance of mobile genetic element immunity in numerically abundant Trichodesmium clades

The colony-forming cyanobacteria Trichodesmium spp. are considered one of the most important nitrogen-fixing genera in the warm, low nutrient ocean. Despite this central biogeochemical role, many questions about their evolution, physiology, and trophic interactions remain unanswered. To address these questions, we describe Trichodesmium pangenomic potential via significantly improved genomic assemblies from two isolates and 15 new >50% complete Trichodesmium metagenome-assembled genomes from hand-picked, Trichodesmium colonies spanning the Atlantic Ocean. Phylogenomics identified ~four N2 fixing clades of Trichodesmium across the transect, with T. thiebautii dominating the colony-specific reads. Pangenomic analyses showed that all T. thiebautii MAGs are enriched in COG defense mechanisms and encode a vertically inherited Type III-B Clustered Regularly Interspaced Short Palindromic Repeats and associated protein-based immunity system (CRISPR-Cas). Surprisingly, this CRISPR-Cas system was absent in all T. erythraeum genomes, vertically inherited by T. thiebautii, and correlated with increased signatures of horizontal gene transfer. Additionally, the system was expressed in metaproteomic and transcriptomic datasets and CRISPR spacer sequences with 100% identical hits to field-assembled, putative phage genome fragments were identified. While the currently CO2-limited T. erythraeum is expected to be a 'winner' of anthropogenic climate change, their genomic dearth of known phage resistance mechanisms, compared to T. thiebautii, could put this outcome in question. Thus, the clear demarcation of T. thiebautii maintaining CRISPR-Cas systems, while T. erythraeum does not, identifies Trichodesmium as an ecologically important CRISPR-Cas model system, and highlights the need for more research on phage-Trichodesmium interactions.

A Multinomial Processing Tree Model of the 2-back Working Memory Task

The n -back task is a widely used behavioral task for measuring working memory and the ability to inhibit interfering information. We develop a novel model of the commonly used 2-back task using the cognitive psychometric framework provided by Multinomial Processing Trees. Our model involves three parameters: a memory parameter, corresponding to how well an individual encodes and updates sequence information about presented stimuli; a decision parameter corresponding to how well participants execute choices based on information stored in memory; and a base-rate parameter corresponding to bias for responding "yes" or "no". We test the parameter recovery properties of the model using existing 2-back experimental designs, and demonstrate the application of the model to two previous data sets: one from social psychology involving faces corresponding to different races (Stelter and Degner, British Journal of Psychology 109:777-798, 2018), and one from cognitive neuroscience involving more than 1000 participants from the Human Connectome Project (Van Essen et al., Neuroimage 80:62-79, 2013). We demonstrate that the model can be used to infer interpretable individual-level parameters. We develop a hierarchical extension of the model to test differences between stimulus conditions, comparing faces of different races, and comparing face to non-face stimuli. We also develop a multivariate regression extension to examine the relationship between the model parameters and individual performance on standardized cognitive measures including the List Sorting and Flanker tasks. We conclude by discussing how our model can be used to dissociate underlying cognitive processes such as encoding failures, inhibition failures, and binding failures.

Adaptive Design Optimization for a Mnemonic Similarity Task

The Mnemonic Similarity Task (MST: Stark et al., 2019) is a modified recognition memory task designed to place strong demand on pattern separation. The sensitivity and reliability of the MST make it an extremely valuable tool in clinical settings, where it has been used to identify hippocampal dysfunction associated with healthy aging, dementia, schizophrenia, depression, and other disorders. As with any test used in a clinical setting, it is especially important for the MST to be administered as efficiently as possible. We apply adaptive design optimization methods (Lesmes et al., 2015; Myung et al., 2013) to optimize the presentation of test stimuli in accordance with previous responses. This optimization is based on a signal-detection model of an individual's memory capabilities and decision-making processes. We demonstrate that the adaptive design optimization approach generally reduces the number of test stimuli needed to provide these measures.

Two co-dominant nitrogen-fixing cyanobacteria demonstrate distinct acclimation and adaptation responses to cope with ocean warming

The globally dominant N₂ -fixing cyanobacteria Trichodesmium and Crocosphaera provide vital nitrogen supplies to subtropical and tropical oceans, but little is known about how they will be affected by long-term ocean warming. We tested their thermal responses using experimental evolution methods during 2 years of selection at optimal (28°C), supra-optimal (32°C) and suboptimal (22°C) temperatures. After several hundred generations under thermal selection, changes in growth parameters, as well as N and C fixation rates, suggested that Trichodesmium did not adapt to the three selection temperature regimes during the 2-year evolution experiment, but could instead rapidly and reversibly acclimate to temperature shifts from 20°C to 34°C. In contrast, over the same timeframe apparent thermal adaptation was observed in Crocosphaera, as evidenced by irreversible phenotypic changes as well as whole-genome sequencing and variant analysis. Especially under stressful warming conditions (34°C), 32°C-selected Crocosphaera cells had an advantage in survival and nitrogen fixation over cell lines selected at 22°C and 28°C. The distinct strategies of phenotypic plasticity versus irreversible adaptation in these two sympatric diazotrophs are both viable ways to maintain fitness despite long-term temperature changes, and so could help to stabilize key ocean nitrogen cycle functions under future warming scenarios.

A Bayesian method for measuring risk propensity in the Balloon Analogue Risk Task

The Balloon Analogue Risk Task (BART) is widely-used to measure risk propensity in theoretical, clinical, and applied research. In the task, people choose either to pump a balloon to increase its value at the risk of the balloon bursting and losing all value, or to bank the current value of the balloon. Risk propensity is most commonly measured as the average number of pumps on trials for which the balloon does not burst. Burst trials are excluded because they necessarily underestimate the number of pumps people intended to make. However, their exclusion discards relevant information about people's risk propensity. A better measure of risk propensity uses the statistical method of censoring to incorporate all of the trials. We develop a new Bayesian method, based on censoring, for measuring both risk propensity and behavioral consistency in the BART. Through applications to previous data we demonstrate how the method can be extended to consider the correlation of risk propensity with external measures, and to compare differences in risk propensity between groups. We provide implementations of all of these methods in R, MATLAB, and the GUI-based statistical software JASP.

Always look on the bright side of logic? Testing explanations of intuitive sensitivity to logic in perceptual tasks

Much recent research and theorizing in the field of reasoning has been concerned with intuitive sensitivity to logical validity, such as the logic-brightness effect, in which logically valid arguments are judged to have a "brighter" typeface than invalid arguments. We propose and test a novel signal competition account of this phenomenon. Our account makes two assumptions: (a) as per the demands of the logic-brightness task, people attempt to find a perceptual signal to guide brightness judgments, but (b) when the perceptual signal is hard to discern, they instead attend to cues such as argument validity. Experiment 1 tested this account by manipulating the difficulty of the perceptual contrast. When contrast discrimination was relatively difficult, we replicated the logic-brightness effect. When the discrimination was easy, the effect was eliminated. Experiment 2 manipulated the ambiguity of the perceptual task, comparing discrimination performance when the perceptual contrast was labeled in terms of rating "brightness" or "darkness". When the less ambiguous darkness labeling was used, there was no evidence of a logic-brightness effect. In both experiments, individual sensitivity to the perceptual discrimination was negatively correlated with sensitivity to argument validity. Hierarchical latent mixture modeling revealed distinct individual strategies: responses based on perceptual cues, responses based on validity or guessing. Consistent with the signal competition account, the proportion of those responding to validity increased with perceptual discrimination difficulty or task ambiguity. The results challenge explanations of the logic-brightness effect based on parallel dual-process models of reasoning. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Why Environmental Biomarkers Work: Transcriptome-Proteome Correlations and Modeling of Multistressor Experiments in the Marine Bacterium Trichodesmium

Ocean microbial communities are important contributors to the global biogeochemical reactions that sustain life on Earth. The factors controlling these communities are being increasingly explored using metatranscriptomic and metaproteomic environmental biomarkers. Using published proteomes and transcriptomes from the abundant colony-forming cyanobacterium Trichodesmium (strain IMS101) grown under varying Fe and/or P limitation in low and high CO₂, we observed robust correlations of stress-induced proteins and RNAs (i.e., involved in transport and homeostasis) that yield useful information on the nutrient status under low and/or high CO₂. Conversely, transcriptional and translational correlations of many other central metabolism pathways exhibit broad discordance. A cellular RNA and protein production/degradation model demonstrates how biomolecules with small initial inventories, such as environmentally responsive proteins, achieve large increases in fold-change units as opposed to those with a higher basal expression and inventory such as metabolic systems. Microbial cells, due to their immersion in the environment, tend to show large adaptive responses in both RNA and protein that result in transcript-protein correlations. These observations and model results demonstrate multi-omic coherence for environmental biomarkers and provide the underlying mechanism for those observations, supporting the promise for global application in detecting responses to environmental stimuli in a changing ocean.

Preclinical Evaluation of a Fluorescent Probe Targeting Receptor CDCP1 for Identification of Ovarian Cancer

Optimal cytoreduction for ovarian cancer is often challenging because of aggressive tumor biology and advanced stage. It is a critical issue since the extent of residual disease after surgery is the key predictor of ovarian cancer patient survival. For a limited number of cancers, fluorescence-guided surgery has emerged as an effective aid for tumor delineation and effective cytoreduction. The intravenously administered fluorescent agent, most commonly indocyanine green (ICG), accumulates preferentially in tumors, which are visualized under a fluorescent light source to aid surgery. Insufficient tumor specificity has limited the broad application of these agents in surgical oncology including for ovarian cancer. In this study, we developed a novel tumor-selective fluorescent agent by chemically linking ICG to mouse monoclonal antibody 10D7 that specifically recognizes an ovarian cancer-enriched cell surface receptor, CUB-domain-containing protein 1 (CDCP1). 10D7^ICG has high affinity for purified recombinant CDCP1 and CDCP1 that is located on the surface of ovarian cancer cells in vitro and in vivo. Our results show that intravenously administered 10D7^ICG accumulates preferentially in ovarian cancer, permitting visualization of xenograft tumors in mice. The data suggest CDCP1 as a rational target for tumor-specific fluorescence-guided surgery for ovarian cancer.

The Hunt for Ancient Prions: Archaeal Prion-Like Domains Form Amyloid-Based Epigenetic Elements

Prions, proteins that can convert between structurally and functionally distinct states and serve as non-Mendelian mechanisms of inheritance, were initially discovered and only known in eukaryotes, and consequently considered to likely be a relatively late evolutionary acquisition. However, the recent discovery of prions in bacteria and viruses has intimated a potentially more ancient evolutionary origin. Here, we provide evidence that prion-forming domains exist in the domain archaea, the last domain of life left unexplored with regard to prions. We searched for archaeal candidate prion-forming protein sequences computationally, described their taxonomic distribution and phylogeny, and analyzed their associated functional annotations. Using biophysical in vitro assays, cell-based and microscopic approaches, and dye-binding analyses, we tested select candidate prion-forming domains for prionogenic characteristics. Out of the 16 tested, eight formed amyloids, and six acted as protein-based elements of information transfer driving non-Mendelian patterns of inheritance. We also identified short peptides from our archaeal prion candidates that can form amyloid fibrils independently. Lastly, candidates that tested positively in our assays had significantly higher tyrosine and phenylalanine content than candidates that tested negatively, an observation that may help future archaeal prion predictions. Taken together, our discovery of functional prion-forming domains in archaea provides evidence that multiple archaeal proteins are capable of acting as prions-thus expanding our knowledge of this epigenetic phenomenon to the third and final domain of life and bolstering the possibility that they were present at the time of the last universal common ancestor.

Model-Based Wisdom of the Crowd for Sequential Decision-Making Tasks

We study the wisdom of the crowd in three sequential decision-making tasks: the Balloon Analogue Risk Task (BART), optimal stopping problems, and bandit problems. We consider a behavior-based approach, using majority decisions to determine crowd behavior and show that this approach performs poorly in the BART and bandit tasks. The key problem is that the crowd becomes progressively more extreme as the decision sequence progresses, because the diversity of opinion that underlies the wisdom of the crowd is lost. We also consider model-based approaches to each task. This involves inferring cognitive models for each individual based on their observed behavior, and using these models to predict what each individual would do in any possible task situation. We show that this approach performs robustly well for all three tasks and has the additional advantage of being able to generalize to new problems for which there are no behavioral data. We discuss potential applications of the model-based approach to real-world sequential decision problems and discuss how our approach contributes to the understanding of collective intelligence.

Long-Term m5C Methylome Dynamics Parallel Phenotypic Adaptation in the Cyanobacterium Trichodesmium

A major challenge in modern biology is understanding how the effects of short-term biological responses influence long-term evolutionary adaptation, defined as a genetically determined increase in fitness to novel environments. This is particularly important in globally important microbes experiencing rapid global change, due to their influence on food webs, biogeochemical cycles, and climate. Epigenetic modifications like methylation have been demonstrated to influence short-term plastic responses, which ultimately impact long-term adaptive responses to environmental change. However, there remains a paucity of empirical research examining long-term methylation dynamics during environmental adaptation in nonmodel, ecologically important microbes. Here, we show the first empirical evidence in a marine prokaryote for long-term m5C methylome modifications correlated with phenotypic adaptation to CO₂, using a 7-year evolution experiment (1,000+ generations) with the biogeochemically important marine cyanobacterium Trichodesmium. We identify m5C methylated sites that rapidly changed in response to high (750 µatm) CO₂ exposure and were maintained for at least 4.5 years of CO₂ selection. After 7 years of CO₂ selection, however, m5C methylation levels that initially responded to high-CO₂ returned to ancestral, ambient CO₂ levels. Concurrently, high-CO₂ adapted growth and N₂ fixation rates remained significantly higher than those of ambient CO₂ adapted cell lines irrespective of CO₂ concentration, a trend consistent with genetic assimilation theory. These data demonstrate the maintenance of CO₂-responsive m5C methylation for 4.5 years alongside phenotypic adaptation before returning to ancestral methylation levels. These observations in a globally distributed marine prokaryote provide critical evolutionary insights into biogeochemically important traits under global change.

SARS-CoV-2 genomic diversity and the implications for qRT-PCR diagnostics and transmission

The COVID-19 pandemic has sparked an urgent need to uncover the underlying biology of this devastating disease. Though RNA viruses mutate more rapidly than DNA viruses, there are a relatively small number of single nucleotide polymorphisms (SNPs) that differentiate the main SARS-CoV-2 lineages that have spread throughout the world. In this study, we investigated 129 RNA-seq data sets and 6928 consensus genomes to contrast the intra-host and inter-host diversity of SARS-CoV-2. Our analyses yielded three major observations. First, the mutational profile of SARS-CoV-2 highlights intra-host single nucleotide variant (iSNV) and SNP similarity, albeit with differences in C > U changes. Second, iSNV and SNP patterns in SARS-CoV-2 are more similar to MERS-CoV than SARS-CoV-1. Third, a significant fraction of insertions and deletions contribute to the genetic diversity of SARS-CoV-2. Altogether, our findings provide insight into SARS-CoV-2 genomic diversity, inform the design of detection tests, and highlight the potential of iSNVs for tracking the transmission of SARS-CoV-2.

NASA GeneLab RNA-seq consensus pipeline: standardized processing of short-read RNA-seq data

With the development of transcriptomic technologies, we are able to quantify precise changes in gene expression profiles from astronauts and other organisms exposed to spaceflight. Members of NASA GeneLab and GeneLab-associated analysis working groups (AWGs) have developed a consensus pipeline for analyzing short-read RNA-sequencing data from spaceflight-associated experiments. The pipeline includes quality control, read trimming, mapping, and gene quantification steps, culminating in the detection of differentially expressed genes. This data analysis pipeline and the results of its execution using data submitted to GeneLab are now all publicly available through the GeneLab database. We present here the full details and rationale for the construction of this pipeline in order to promote transparency, reproducibility, and reusability of pipeline data; to provide a template for data processing of future spaceflight-relevant datasets; and to encourage cross-analysis of data from other databases with the data available in GeneLab.

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Analysis of omics data from different spaceflight studies presents unique challenges

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A standardized pipeline for RNA-seq analysis eliminates data processing variation

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The GeneLab RNA-seq pipeline includes QC, trimming, mapping, quantification, and DGE

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Space-relevant data processed with this pipeline are available at genelab.nasa.gov

Lettuce (Lactuca sativa) productivity influenced by microbial inocula under nitrogen-limited conditions in aquaponics

The demand for food will outpace productivity of conventional agriculture due to projected growth of the human population, concomitant with shrinkage of arable land, increasing scarcity of freshwater, and a rapidly changing climate. While aquaponics has potential to sustainably supplement food production with minimal environmental impact, there is a need to better characterize the complex interplay between the various components (fish, plant, microbiome) of these systems to optimize scale up and productivity. Here, we investigated how the commonly-implemented practice of continued microbial community transfer from pre-existing systems might promote or impede productivity of aquaponics. Specifically, we monitored plant growth phenotypes, water chemistry, and microbiome composition of rhizospheres, biofilters, and fish feces over 61-days of lettuce (Lactuca sativa var. crispa) growth in nitrogen-limited aquaponic systems inoculated with bacteria that were either commercially sourced or originating from a pre-existing aquaponic system. Lettuce above- and below-ground growth were significantly reduced across replicates treated with a pre-existing aquaponic system inoculum when compared to replicates treated with a commercial inoculum. Reduced productivity was associated with enrichment in specific bacterial genera in plant roots, including Pseudomonas, following inoculum transfer from pre-existing systems. Increased productivity was associated with enrichment of nitrogen-fixing Rahnella in roots of plants treated with the commercial inoculum. Thus, we show that inoculation from a pre-existing system, rather than from a commercial inoculum, is associated with lower yields. Further work will be necessary to test the putative mechanisms involved.

Application of Digital Cognitive Biomarkers for Alzheimer's Disease: Identifying Cognitive Process Changes and Impending Cognitive Decline

BACKGROUND

Recent Alzheimer's disease (AD) trials have faced significant challenges to enroll pre-symptomatic or early stage AD subjects with biomarker positivity, minimal or no cognitive impairment, and likelihood to decline cognitively during a short trial period. Our previous study showed that digital cognitive biomarkers (DCB), generated by a hierarchical Bayesian cognitive process (HBCP) model, were able to distinguish groups of cognitively normal individuals with impending cognitive decline from those without. We generated DCBs using only baseline Auditory Verbal Learning Test's wordlist memory (WLM) item response data from the Mayo Clinic Alzheimer's Disease Patient Registry.

OBJECTIVES

To replicate our previous findings, using baseline ADAS-Cog WLM item response data from the Alzheimer's Disease Neuroimaging Initiative, and compare DCBs to traditional approaches for scoring word-list memory tests.

DESIGN

Classified decliner subjects (n = 61) as those who developed amnestic MCI or AD dementia within 3 years of normal baseline assessment and non-decliner (n = 442) as those who did not.

MEASURES

Evaluated the relative value of DCBs compared to traditional measures, using three analytic approaches to group differences: 1) logistic regression of summary scores per ADAS-Cog WLM task; 2) Bayesian modeling of summary scores; and 3) HBCP modeling to generate DCBs from item-level responses.

RESULTS

The HBCP model produced posterior distributions of group differences, of which Bayes factor assessment identified three DCBs with notable group differences: Immediate Retrieval from Durable Storage, (BFds = 11.8, strong evidence); One-Shot Learning, (BFds = 4.5, moderate evidence); and Partial Learning (BFds = 2.9, weak evidence). In contrast, logistic regression of summary scores did not significantly discriminate between groups, and the Bayes factor assessment of modeled summary scores provided moderate evidence that the groups were equivalent (BFsd = 3.4, 3.1, 2.9, and 1.4, respectively).

CONCLUSIONS

This study demonstrated DCBs' ability to distinguish , at baseline, between impending cognitive decline and non-decline groups where individuals in both groups were classified as cognitively normal. This validated findings from our previous study, demonstrating DCBs' advantages over traditional approaches. This study warrants further refinement of the HBCP DCBs to predict impending cognitive decline in individuals and other factors associated with AD, such as physical biomarker load.

Reference-guided metagenomics reveals genome-level evidence of potential microbial transmission from the ISS environment to an astronaut's microbiome

Monitoring microbial communities aboard the International Space Station (ISS) is essential to maintaining astronaut health and the integrity of life-support systems. Using assembled genomes of ISS-derived microbial isolates as references, recruiting metagenomic reads from an astronaut's nasal microbiome revealed no recruitment to a Staphylococcus aureus isolate from samples before launch, yet systematic recruitment across the genome when sampled after 3 months aboard the ISS, with a median percent identity of 100%. This suggests that either a highly similar S. aureus population colonized the astronaut's nasal microbiome while the astronaut was aboard the ISS or that it may have been below detection before spaceflight, instead supporting a shift in community composition. This work highlights the value in generating genomic libraries of microbes from built-environments such as the ISS and demonstrates one way such data can be integrated with metagenomics to facilitate the tracking and monitoring of astronaut microbiomes and health.

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Understanding built-environment microbiomes is critical for human space exploration

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Reference-guided metagenomics is a powerful approach for monitoring microbiomes

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We show potential microbial colonization of an astronaut microbiome while aboard the ISS

DMSP synthesis genes distinguish two types of DMSP producer phenotypes

Dimethylsulfoniopropionate (DMSP) is an important organic carbon and sulfur source in the surface ocean that fuels microbial activity and significantly impacts Earth's climate. After three decades of research, the cellular role(s) of DMSP and environmental drivers of production remain enigmatic. Recent work suggests that cellular DMSP concentrations, and changes in these concentrations in response to environmental stressors, define two major groups of DMSP producers: high DMSP producers that contain ≥ 50 mM intracellular DMSP and low DMSP producers that contain < 50 mM. Here we show that two recently described DMSP synthesis genes (DSYB and TpMT2) may differentiate these two DMSP phenotypes. A survey of prokaryotic and eukaryotic isolates found a significant correlation between the presence of DSYB and TpMT2 genes and previous measurements of high and low DMSP concentrations, respectively. Phylogenetic analysis demonstrated that DSYB and TpMT2 form two distinct clades. DSYB and TpMT2 were also found to be globally abundant in in situ surface communities, and their taxonomic annotations were similar to those observed for isolates. The strong correlation of the DSYB and TpMT2 synthesis genes with high and low producer phenotypes establishes a foundation for direct quantification of DMSP producers, enabling significantly improved predictions of DMSP in situ.

Pupil Dilation during Reward Anticipation Is Correlated to Depressive Symptom Load in Patients with Major Depressive Disorder

Depression is a debilitating disorder with high prevalence and socioeconomic cost, but the brain-physiological processes that are altered during depressive states are not well understood. Here, we build on recent findings in macaques that indicate a direct causal relationship between pupil dilation and anterior cingulate cortex mediated arousal during anticipation of reward. We translated these findings to human subjects with concomitant pupillometry/fMRI in a sample of unmedicated participants diagnosed with major depression and healthy controls. We could show that the upregulation and maintenance of arousal in anticipation of reward was disrupted in patients in a symptom-load dependent manner. We could further show that the failure to maintain reward anticipatory arousal showed state-marker properties, as it tracked the load and impact of depressive symptoms independent of prior diagnosis status. Further, group differences of anticipatory arousal and continuous correlations with symptom load were not traceable only at the level of pupillometric responses, but were mirrored also at the neural level within salience network hubs. The upregulation and maintenance of arousal during reward anticipation is a novel translational and well-traceable process that could prove a promising gateway to a physiologically informed patient stratification and targeted interventions.

Metabolomics as an Emerging Tool in the Search for Astrobiologically Relevant Biomarkers

It is now routinely possible to sequence and recover microbial genomes from environmental samples. To the degree it is feasible to assign transcriptional and translational functions to these genomes, it should be possible, in principle, to largely understand the complete molecular inputs and outputs of a microbial community. However, gene-based tools alone are presently insufficient to describe the full suite of chemical reactions and small molecules that compose a living cell. Metabolomic tools have developed quickly and now enable rapid detection and identification of small molecules within biological and environmental samples. The convergence of these technologies will soon facilitate the detection of novel enzymatic activities, novel organisms, and potentially extraterrestrial life-forms on solar system bodies. This review explores the methodological problems and scientific opportunities facing researchers who hope to apply metabolomic methods in astrobiology-related fields, and how present challenges might be overcome.

Hidden genomic diversity of SARS-CoV-2: implications for qRT-PCR diagnostics and transmission

The COVID-19 pandemic has sparked an urgent need to uncover the underlying biology of this devastating disease. Though RNA viruses mutate more rapidly than DNA viruses, there are a relatively small number of single nucleotide polymorphisms (SNPs) that differentiate the main SARS-CoV-2 clades that have spread throughout the world. In this study, we investigated over 7,000 SARS-CoV-2 datasets to unveil both intrahost and interhost diversity. Our intrahost and interhost diversity analyses yielded three major observations. First, the mutational profile of SARS-CoV-2 highlights iSNV and SNP similarity, albeit with high variability in C>T changes. Second, iSNV and SNP patterns in SARS-CoV-2 are more similar to MERS-CoV than SARS-CoV-1. Third, a significant fraction of small indels fuel the genetic diversity of SARS-CoV-2. Altogether, our findings provide insight into SARS-CoV-2 genomic diversity, inform the design of detection tests, and highlight the potential of iSNVs for tracking the transmission of SARS-CoV-2.

GToTree: a user-friendly workflow for phylogenomics

Summary

Genome-level evolutionary inference (i.e. phylogenomics) is becoming an increasingly essential step in many biologists’ work. Accordingly, there are several tools available for the major steps in a phylogenomics workflow. But for the biologist whose main focus is not bioinformatics, much of the computational work required—such as accessing genomic data on large scales, integrating genomes from different file formats, performing required filtering, stitching different tools together etc.—can be prohibitive. Here I introduce GToTree, a command-line tool that can take any combination of fasta files, GenBank files and/or NCBI assembly accessions as input and outputs an alignment file, estimates of genome completeness and redundancy, and a phylogenomic tree based on a specified single-copy gene (SCG) set. Although GToTree can work with any custom hidden Markov Models (HMMs), also included are 13 newly generated SCG-set HMMs for different lineages and levels of resolution, built based on searches of ∼12 000 bacterial and archaeal high-quality genomes. GToTree aims to give more researchers the capability to make phylogenomic trees.

Availability and implementation

GToTree is open-source and freely available for download from: github.com/AstrobioMike/GToTree. It is implemented primarily in bash with helper scripts written in python.

Supplementary information

Supplementary data are available at Bioinformatics online.

Draft Genome Sequences of Bacillus glennii V44-8, Bacillus saganii V47-23a, Bacillus sp. Strain V59.32b, Bacillus sp. Strain MER_TA_151, and Paenibacillus sp. Strain MER_111, Isolated from Cleanrooms Where the Viking and Mars Exploration Rover Spacecraft Were Assembled

We report the draft genome sequences of Bacillus glennii V44-8, Bacillus saganii V47-23a, and Bacillus sp. strain V59.32b, isolated from the Viking spacecraft assembly cleanroom, and Bacillus sp. strain MER_TA_151 and Paenibacillus sp. strain MER_111, isolated from the Mars Exploration Rover (MER) assembly cleanroom.

Genomic and phenotypic characterization of Burkholderia isolates from the potable water system of the International Space Station

The opportunistic pathogens Burkholderia cepacia and Burkholderia contaminans, both genomovars of the Burkholderia cepacia complex (BCC), are frequently cultured from the potable water dispenser (PWD) of the International Space Station (ISS). Here, we sequenced the genomes and conducted phenotypic assays to characterize these Burkholderia isolates. All recovered isolates of the two species fall within monophyletic clades based on phylogenomic trees of conserved single-copy core genes. Within species, the ISS-derived isolates all demonstrate greater than 99% average nucleotide identity (with 95-99% of genomes aligning) and share around 90% of the identified gene clusters from a pangenomic analysis-suggesting that the two groups are each composed of highly similar genomic lineages and their members may have all stemmed from the same two founding populations. The differences that can be observed between the recovered isolates at the pangenomic level are primarily located within putative plasmids. Phenotypically, macrophage intracellularization and lysis occurred at generally similar rates between all ISS-derived isolates, as well as with their respective type-terrestrial strain references. All ISS-derived isolates exhibited antibiotic sensitivity similar to that of the terrestrial reference strains, and minimal differences between isolates were observed. With a few exceptions, biofilm formation rates were generally consistent across each species. And lastly, though isolation date does not necessarily provide any insight into how long a given isolate had been aboard the ISS, none of the assayed physiology correlated with either date of isolation or distances based on nucleotide variation. Overall, we find that while the populations of Burkholderia present in the ISS PWS each maintain virulence, they are likely are not more virulent than those that might be encountered on planet and remain susceptible to clinically used antibiotics.

Genomic mosaicism underlies the adaptation of marine Synechococcus ecotypes to distinct oceanic iron niches

Phytoplankton are limited by iron (Fe) in ~40% of the world's oceans including high-nutrient low-chlorophyll (HNLC) regions. While low-Fe adaptation has been well-studied in large eukaryotic diatoms, less is known for small, prokaryotic marine picocyanobacteria. This study reveals key physiological and genomic differences underlying Fe adaptation in marine picocyanobacteria. HNLC ecotype CRD1 strains have greater physiological tolerance to low Fe congruent with their expanded repertoire of Fe transporter, storage and regulatory genes compared to other ecotypes. From metagenomic analysis, genes encoding ferritin, flavodoxin, Fe transporters and siderophore uptake genes were more abundant in low-Fe waters, mirroring paradigms of low-Fe adaptation in diatoms. Distinct Fe-related gene repertories of HNLC ecotypes CRD1 and CRD2 also highlight how coexisting ecotypes have evolved independent approaches to life in low-Fe habitats. Synechococcus and Prochlorococcus HNLC ecotypes likewise exhibit independent, genome-wide reductions of predicted Fe-requiring genes. HNLC ecotype CRD1 interestingly was most similar to coastal ecotype I in Fe physiology and Fe-related gene content, suggesting populations from these different biomes experience similar Fe-selective conditions. This work supports an improved perspective that phytoplankton are shaped by more nuanced Fe niches in the oceans than previously implied from mostly binary comparisons of low- versus high-Fe habitats and populations.

Transient exposure to novel high temperatures reshapes coastal phytoplankton communities

Average sea surface temperatures are expected to rise 4° this century, and marine phytoplankton and bacterial community composition, biogeochemical rates, and trophic interactions are all expected to change in a future warmer ocean. Thermal experiments typically use constant temperatures; however, weather and hydrography cause marine temperatures to fluctuate on diel cycles and over multiple days. We incubated natural communities of phytoplankton collected from California coastal waters during spring, summer, and fall under present-day and future mean temperatures, using thermal treatments that were either constant or fluctuated on a 48 h cycle. As assayed by marker-gene sequencing, the emergent microbial communities were consistent within each season, except when culture temperatures exceeded the highest temperature recorded in a 10-year local thermal dataset. When temperature treatments exceeded the 10-year maximum the phytoplankton community shifted, becoming dominated by diatom amplicon sequence variants (ASVs) not seen at lower temperatures. When mean temperatures were above the 10-year maximum, constant and fluctuating regimes each selected for different ASVs. These findings suggest coastal microbial communities are largely adapted to the current range of temperatures they experience. They also suggest a general hypothesis whereby multiyear upper temperature limits may represent thresholds, beyond which large community restructurings may occur. Now inevitable future temperature increases that exceed these environmental thresholds, even temporarily, may fundamentally reshape marine microbial communities and therefore the biogeochemical cycles that they mediate.

Utility of Percentage Signal Recovery and Baseline Signal in DSC-MRI Optimized for Relative CBV Measurement for Differentiating Glioblastoma, Lymphoma, Metastasis, and Meningioma

BACKGROUND AND PURPOSE

The percentage signal recovery in non-leakage-corrected (no preload, high flip angle, intermediate TE) DSC-MR imaging is known to differ significantly for glioblastoma, metastasis, and primary CNS lymphoma. Because the percentage signal recovery is influenced by preload and pulse sequence parameters, we investigated whether the percentage signal recovery can still differentiate these common contrast-enhancing neoplasms using a DSC-MR imaging protocol designed for relative CBV accuracy (preload, intermediate flip angle, low TE).

MATERIALS AND METHODS

We retrospectively analyzed DSC-MR imaging of treatment-naïve, pathology-proved glioblastomas (n = 14), primary central nervous system lymphomas (n = 7), metastases (n = 20), and meningiomas (n = 13) using a protocol designed for relative CBV accuracy (a one-quarter-dose preload and single-dose bolus of gadobutrol, TR/TE = 1290/40 ms, flip angle = 60° at 1.5T). Mean percentage signal recovery, relative CBV, and normalized baseline signal intensity were compared within contrast-enhancing lesion volumes. Classification accuracy was determined by receiver operating characteristic analysis.

RESULTS

Relative CBV best differentiated meningioma from glioblastoma and from metastasis with areas under the curve of 0.84 and 0.82, respectively. The percentage signal recovery best differentiated primary central nervous system lymphoma from metastasis with an area under the curve of 0.81. Relative CBV and percentage signal recovery were similar in differentiating primary central nervous system lymphoma from glioblastoma and from meningioma. Although neither relative CBV nor percentage signal recovery differentiated glioblastoma from metastasis, mean normalized baseline signal intensity achieved 86% sensitivity and 50% specificity.

CONCLUSIONS

Similar to results for non-preload-based DSC-MR imaging, percentage signal recovery for one-quarter-dose preload-based, intermediate flip angle DSC-MR imaging differentiates most pair-wise comparisons of glioblastoma, metastasis, primary central nervous system lymphoma, and meningioma, except for glioblastoma versus metastasis. Differences in normalized post-preload baseline signal for glioblastoma and metastasis, reflecting a snapshot of dynamic contrast enhancement, may motivate the use of single-dose multiecho protocols permitting simultaneous quantification of DSC-MR imaging and dynamic contrast-enhanced MR imaging parameters.

Applications and Considerations of GToTree: A User-Friendly Workflow for Phylogenomics

Phylogenomics is the practice of attempting to infer evolutionary relationships at a genome-level. This is becoming a standard step in the characterization of newly recovered genomes and to direct/constrain further research; yet the process from start to finish of building a de novo phylogenomic tree that is specific to the organisms of interest can still be computationally intractable for many biologists. GToTree is a recently published user-friendly workflow for phylogenomics intended to give more researchers the capability to generate phylogenomic trees to help guide their work. This commentary describes two common applications where GToTree can be helpful and then discusses some things to consider when using the program.

Jellyfish Life Stages Shape Associated Microbial Communities, While a Core Microbiome Is Maintained Across All

The key to 650 million years of evolutionary success in jellyfish is adaptability: with alternating benthic and pelagic generations, sexual and asexual reproductive modes, multitudes of body forms and a cosmopolitan distribution, jellyfish are likely to have established a plenitude of microbial associations. Here we explored bacterial assemblages in the scyphozoan jellyfish Chrysaora plocamia (Lesson 1832). Life stages involved in propagation through cyst formation, i.e., the mother polyp, its dormant cysts (podocysts), and polyps recently excysted (excysts) from podocysts – were investigated. Associated bacterial assemblages were assessed using MiSeq Illumina paired-end tag sequencing of the V1V2 region of the 16S rRNA gene. A microbial core-community was identified as present through all investigated life stages, including bacteria with closest relatives known to be key drivers of carbon, nitrogen, phosphorus, and sulfur cycling. Moreover, the fact that half of C. plocamia’s core bacteria were also present in life stages of the jellyfish Aurelia aurita, suggests that this bacterial community might represent an intrinsic characteristic of scyphozoan jellyfish, contributing to their evolutionary success.